CUSTOMER LOYALTY

Aarhus School of Business, Denmark Faculty of Business Performance Management

Joanna Waligóra Student ID 254 581 Robert Waligóra Student ID 254 582

MEASURING CUSTOMER SATISFACTION AND

LOYALTY IN THE AUTOMOTIVE INDUSTRY

A CASE OF PREMIUM BRAND OF PASSENGER CARS

Master Thesis Advisor: Jacob Kjær Eskildsen

Department of Marketing and Statistics

Aarhus, 2007

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CONTENTS

EXECUTIVE SUMMARY ..................................................................................................5 INTRODUCTION – A NEED FOR THE STUDY..............................................................7 MAIN OBJECTIVES OF THE PAPER..............................................................................8 1. THE IMPORTANCE OF CUSTOMER SATISFACTION FOR BUSINESS PERFORMANCE ................................................................................................................9

1.1. Customer satisfaction in customer orientation model .................................................10 1.2. Customer satisfaction in The EFQM Excellence Model .............................................13 1.3. The evidence of positive impact of satisfaction on business results ............................15

1.3.1. Satisfaction influence on ROI, stock prices and shareholder value.......................16 1.3.2. Customer retention impact on business results.....................................................17 1.3.3. Dissatisfaction influence on business performance ..............................................18

2. THE THEORY OF CUSTOMER SATISFACTION....................................................22 2.1. The definition of customer satisfaction.......................................................................22 2.2. Antecedents of customer satisfaction .........................................................................22 2.3. Consequences of customer satisfaction. .....................................................................25

3. CUSTOMER SATISFACTION MEASUREMENT SYSTEMS ..................................29 3.1. Antecedents of satisfaction measurement system implementation – customer’s personal values research .................................................................................................................29 3.2. Rationale for development and use of industry or nation universal customer satisfaction measurement indexes........................................................................................................32 3.3. National Customer Satisfaction Indexes .....................................................................33

3.3.1. Swedish Customer Satisfaction Barometer ..........................................................33 3.3.2. American Customer Satisfaction Index ...............................................................36 3.3.3. European Customer Satisfaction Index................................................................39 3.3.4. Automotive industry specific customer satisfaction indexes ................................43

4. COMPANY X CUSTOMER’S PROFILE ....................................................................47 4.1. Company X customers – demographics .....................................................................47 4.2. Company X customers – benefits driving the car purchase.........................................53 4.3. Company X customers – attitudes to vehicle ..............................................................58 4.4. Summary of Company X customer’s profile ..............................................................59

5. STRUCTURAL EQUATION MODELING AND PARTIAL LEAST SQUARES .....61 5.1. Structural Equation Modeling – covariance-based approach.......................................61 5.2. Partial Least Squares..................................................................................................62

5.2.1. Specification of the model...................................................................................62 5.2.2. Estimation...........................................................................................................64 5.2.3. Validation of model ............................................................................................67

6. MEASURING CUSTOMER SATISFACTION AT COMPANY X IN POLAND ......71 6.1. Customer Satisfaction Index at Company X – Sales Service Quality..........................72 6.2. Customer Satisfaction Index at Company X – After - Sales Service Quality...............74 6.3. Brand Satisfaction Model at Company X in Poland – history, underpinnings and structure ...........................................................................................................................75

6.3.1. Questionnaire development .................................................................................79 6.3.2. Computer software for Partial Least Squares models...........................................84 6.3.3. Working out the structure of the model ...............................................................85 6.3.4. Discussion on BSM structure ..............................................................................89 6.3.5. Quality criteria evaluation ...................................................................................92

7. RESULTS OF BRAND SATISFACTION MODEL FOR COMPANY X ...................95 7.1. Sample description.....................................................................................................95

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7.2. Estimation results for Brand Satisfaction Model – Total Brand ................................101 7.3. Estimation results – Total brand - detailed analysis of performance..........................108 7.4. Estimation results for Brand Satisfaction Model – 3 segments of customers.............115

7.4.1. General estimation results for 3 customer segments...........................................115 7.4.2. Total effects analysis – 3 customer segments .....................................................119 7.4.3. Satisfaction vs. importance analysis - 3 clients segments - inner model .............123 7.4.4. Satisfaction vs. importance analysis - 3 customer segments –outer model..........127 7.4.5. Summary of analysis for 3 customer segments...................................................135

CONCLUSIONS AND RECOMMENDATIONS ...........................................................137 REFERENCES .................................................................................................................139 APPENDICES ..................................................................................................................142

Appendix 1. ....................................................................................................................142 Appendix 2. ....................................................................................................................143 Appendix 3. ....................................................................................................................149 Appendix 4. ....................................................................................................................163 Appendix 5. ....................................................................................................................182 Appendix 6. ....................................................................................................................203

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EXECUTIVE SUMMARY

The new method of customer satisfaction and loyalty measurement has been developed for

Company X in Poland. The method is called Brand Satisfaction Model.

The Company X is operating on the automotive market representing premium brand of

passenger vehicles in Poland.

The model has been created based on customer satisfaction and loyalty theories and so far

implemented and practically adopted models. The Brand Satisfaction Model is mainly built

on the ACSI, ECSI and JD Power CSI studies with particular use of satisfaction theories

presented in the paper.

The BSM structure is adjusted to industry specific requirements which have been verified by

customer focus groups and statistical validity tests.

Therefore unique, industry specific method for measuring satisfaction of passenger

vehicles clients has been developed and is presented below:

Practical research on a group of 346 customers of Company X in Poland has been

conducted. After analysis of satisfaction scores and importance levels for all the areas

included in the study four areas that need to be definitely improved have been revealed: After

Sales service quality, Value for money, Costs of ownership and Brand Image.

The results of the study have been made well-known across the entire organization. The

reparation program has been developed and implemented and as a result of it the next After

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Sales service satisfaction study presented the increase in overall score by 2 percentage points.

Further actions concentrating on improvement of the other three mentioned areas have been

implemented but their results were not known yet when the paper was written.

Therefore the knowledge gained with Brand Satisfaction Model helped Company X prioritize

its actions and concentrate on those areas that need to be taken care of in a first place.

Furthermore the study analyzed three customer groups separately: Compact, Mid-size and

Full-size and Large vehicles owners in order to discover differences in their definition of

satisfaction and loyalty. Compact vehicles users are much more price and costs sensitive.

They also pay stronger attention to the image of a brand and post-purchase service they

receive. Mid-size vehicles users are definitely closer in terms of their profile to the third group

of customers however they are more vehicle comfort and quality oriented while at the same

time do not expect so high value for money as other clients. The full-size and large vehicles

owners are definitely the least price and costs sensitive. Vehicle quality, comfort and

functionality and sales service quality are the most important elements strongly affecting the

level of their loyalty.

The knowledge gained from the analysis of three customer segments helped the sales and

marketing as well as PR departments adjust its operations and strategy to specific

requirements of different customer groups in order to improve their overall satisfaction and

loyalty to a brand.

Developed model proved to be very explanatory with regard to the type of knowledge

received after application of the structure to the dataset gathered during interviews with

Company X customers. The BSM is also an effective tool that not only helps to understand

customers better but also answers the question: how to improve customers’ satisfaction and

loyalty.

The Polish Automotive Market Research Institute presented interest in the model with the aim

to make the Brand Satisfaction Model the uniform platform for measuring and comparing

customer satisfaction and loyalty across whole polish automotive sector. Successful

implementation of Brand Satisfaction Model by all brands of passenger vehicles operating in

Poland would definitely supply automotive companies in Poland with knowledge

comparisons of brands performance on the Polish market.

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INTRODUCTION – A NEED FOR THE STUDY

There is a need for the comprehensive study at Company X in Poland which would cover all

aspects of customer satisfaction and loyalty. The need was recognized by the marketing and

sales department and the board of directors due to the fact that so far the knowledge about

Company X clients was limited to their demographic and social profile and customer’s

evaluation of sales and after-sales service quality. All other areas such as vehicle quality,

design, comfort and functionality, cost of ownership, value for money etc. have been so far

neglected and not measured. Therefore the Brand Satisfaction Model has been created in

order to close the gap in knowledge about Company X clients.

Customer Satisfaction can be measured and monitored on many levels of advancement. First

of all, customer orientation concept, means-end chain theory, expectations disconfirmation

and performance models, Hirschman’s exit theory are important theories which define clients’

satisfaction and loyalty concepts and their influence on company business results. Than, the

EFQM Excellence Model takes the satisfaction studies to the next level and measures

customer satisfaction importance and influence on company’s profitability and success.

Finally, there are those customer satisfaction measurement nation-wide studies such as SCSB,

ECSI and ACSI, which define the satisfaction concept empirically and help understand the

relationships between antecedents of satisfaction and its consequences such as loyalty and

retention. Additionally, there are industry specific types of researches such as JD Power

automotive CSI that measure clients’ satisfaction with different aspects of product usage

which are usually applicable to only one industry.

Taking into consideration all the above mentioned satisfaction theories, the Brand Satisfaction

Model has been built up based on the above mentioned theories and researches as a complete

and comprehensive measurement method of clients’ satisfaction and loyalty for Company X

in Poland. Although its structure is similar to ECSI, the BSM includes some of the JD Power

CSI study elements. Such combination of the theories and the two researches offers a valuable

tool that combines most of theoretical and empirical knowledge so far possessed by academic

and professional environment.

The Brand Satisfaction Model may be useful sales and marketing tool not only for Company

X but also for other automotive companies operating on Polish market. If the study was

applied to other firms, than a great portion of knowledge could be added to the whole

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automotive sector in Poland by allowing for cross industry comparisons. Provided that the

BSM is well grounded in terms of its statistical properties as well as satisfaction theories,

there is high probability that the same structure could be applied to other automotive brands.

So far there has been no other unified measurement model of customer satisfaction and

loyalty created and used in the polish automotive sector. There are different researches

covering some aspects of company’s performance but the unified and complete approach

allowing for comparison between different brands is not available. Therefore the study that is

comprehensive and at the same time industry specific – such as Brand Satisfaction Model -

would be a huge contribution to the Polish automotive sector.

MAIN OBJECTIVES OF THE PAPER

The main objective of the study is:

- Creation of complete satisfaction measurement model for Company X selling

premium passenger vehicles in Poland and assessment of Company X customers’

satisfaction and loyalty based on the new methodology. Up till now the Company X

has been only using its own Customer Satisfaction Index study as the measure for sales

company performance. However such approach leads to severe limitations of the study

results, as the Customer Satisfaction Index concentrates only on measurement of

satisfaction with sales and after-sales service quality. Therefore more comprehensive

approach covering all aspects of customer experience with product, brand and dealerships

is needed.

In order to support the main goal some sub objectives shall be fulfilled:

- Creation of theoretical satisfaction measurement model and statistical validation of the

model. The model shall be based on customer satisfaction theories and measurement

models described in this paper.

- Application of the theoretical model into the practical research - measurement of

Company X customers’ satisfaction and loyalty using the new methodology.

- Analysis of the research results and comparison of the differences between Company X

customer segments. The Company X clientele shall be segmented into three groups based

on existing Customer Profile study: Compact vehicles, Mid-size vehicles, Full-size and

Large vehicles owners.

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1. THE IMPORTANCE OF CUSTOMER SATISFACTION FOR BUSINESS

PERFORMANCE

Satisfaction understood as emotional state shall be held by people, who are willing to develop

successfully personal relations, but has also been of utmost importance in business and

professional situations. The latter will be of our interest in the further course of this work.

In general, satisfied customers, satisfied employees and satisfied shareholders all have one

common characteristic – they are positive and enthusiastic about the company they are

dealing with. Talking in more detail, they shall behave in a way desired and understood by a

firm, when it comes to making decision about further cooperation with the company.

Specifically, they will be making repeat purchases, delivering best quality of work and

investing additional funds in the company stocks. Such behavior of satisfied customers,

employees and shareholders will contribute to business growth. Therefore satisfaction,

understood in such a wide context, shall definitely be on the top of board of directors’ list as it

has strong positive impact on business results.

Although satisfaction is applicable to organization’s customers, employees and shareholders,

within the course of this work customer satisfaction will be discussed. Specifically, customer

as the ultimate judge of products or service quality and his or her satisfaction with the

delivered products or services will be taken into account.

Customer satisfaction is crucial for business performance, as it is the driver of customer

loyalty and consecutive retention. This statement, although intuitively true, could be argued

with.

On one side, it could be said, that there is no need to dedicate time and funds to make the

customer’s satisfied, but it is less expensive and sufficient to deliver high quality offerings,

which will certainly be purchased by some clients. Furthermore, one could argue that even

though customers are not loyal and will not stay with the company, new clients can be easily

found.

On the other side it can be argued, that even though customers will buy the product, they will

not repurchase unless the offering meets customers’ needs. Moreover, it may turn out, that

despite product’s quality is high it does not fill client’s expectations, as it misses some of

required benefits. Finally, one could say that it is much more expensive to acquire new

customers than retain current ones, as the costs associated with the customer recruitment are

higher than those connected with customer retention.

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The above arguments connected with customer satisfaction concept have been widely

measured and discussed in the literature. As a result there is lots of evidence supporting the

initial statement: customer satisfaction is crucial for business performance, as it is the driver

of customer loyalty and consecutive retention the importance of customer satisfaction for

business results.

Within the course of this chapter, we will focus on only few supportive theories.

First of all, the importance of customer satisfaction for business performance has been

justified within the customer orientation concept. Secondly, the actual importance of customer

satisfaction for business performance versus importance of other factors has been quantified

within the EFQM Excellence Model. Finally, also the impact of increased satisfaction on

business results was researched and quantified within the literature.

1.1. Customer satisfaction in customer orientation model

Customer satisfaction concept has been placed at the heart of customer orientation model.

Based on this model, there are two kinds of companies;

on the one side, there are product oriented companies, who are trying to sell the

products which they produce regardless of the level, to which those products satisfy

their customers’ needs. To simplify it, product oriented companies are searching for

customers, whose needs can be matched with the products, that the company is

offering. Very often those companies end up in the business stagnation phase, as they

are not be able to follow the natural development of customer needs – they continue to

offer what they think is desired by the consumers instead of delivering what is actually

desired.

on the opposite side, there are customer oriented companies, who are focused on

meeting customer’s needs and satisfying him or her, as they know that satisfaction is a

prerequisite to retention, which in turn has positive impact on the long-term health of

their business.

Customer orientation is an ongoing process, during which organizations pursue three goals:

1. attain customer information,

2. disseminate and use that information when making decisions

3. implement change (Johnson, Herrmann, Huber, Gustafsson, 1997).

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First goal - “attain customer information” - means that a firm must collect information

about its customers. This is done through various research techniques in order to find out,

what are the needs and values of customers and how they are served by current products and

services. The information attained shall also point out future customer’s needs and the

direction into which they will be developing.

Secondly, a customer oriented company needs to ensure, that the “disseminate and use the

information” goal is met. Therefore it is necessary to make sure that the information

collected is shared between all departments involved in production and delivery of products

or services to customers. For that to be possible, tight cooperation between market research

and other departments is necessary. Moreover, organization’s leadership must understand the

necessity of and support the facts-based decision process.

Finally, there is no use of information, which is collected and stored in databases. To fulfill

the third goal – “implement the change” - it is necessary to translate the conclusions and

recommendations from the research into actions, which will enable the company to deliver

improved products and services.

To summarize, a customer oriented company has one primary goal – to satisfy its customers,

which is realized by getting to know customer needs and values, sharing this knowledge

throughout the company and translating it into improved products and services, which are

able to satisfy the customer to largest possible extent.

Satisfying the customers is a never ending process. As the customer grows up, gets older and

ages, his or her needs and values change. Moreover, as the economies develop, mature and

decline, the wants of human beings also change. As a result, companies are forced to follow

or even be ahead of customer’s needs in order ensure business growth. Customer orientation

process never comes to an end – it is a sequence of repetitive stages. The theory of customer

orientation distinguishes four major phases, which a customer oriented company has to go

through all over again to ensure growth in customer orientation (Johnson, Herrmann, Huber,

Gustafsson, 1997):

1. Customer strategy and focus

2. Customer satisfaction measurement

3. Analysis and priority setting

4. Implementation.

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Figure 1.1. The four phases of customer orientation

Source: Johnson, Herrmann, Huber, Gustafsson, 1997

In the first phase of the process, companies should answer the question, how important is the

customer for their business performance and to what extent is the customer orientation their

business priority. In other words, it shall be clearly stated, to what extent company shall and

can adjust their strategy to consumers needs. Furthermore, phase 1 is the right time to specify,

which customer segments shall be in the center of organizations attention – e.g. referring to

automotive industry, shall the company focus on premium or mass cars’ users, shall the

company target young and dynamic or adult and affluent customers?

During phase two of customer orientation process, organization shall develop a measurement

system, which will enable to evaluate the level of customers’ satisfaction of particular target

groups with currently delivered products or services. In more detail, the measurement system

shall answer the question, which needs, values and benefits are key for consumers within

customer segments. Specifically, the research shall evaluate, to what extent current products

and services’ attributes deliver the desired benefits and therefore fill customers’ needs.

As the second phase provides the company with the assessment of benefits’ importance and

the extent to which current offerings fill those benefits, during third phase organization shall

analyze the information gathered and set priorities for further actions. In other words,

organization shall spot for product benefits, which are very important for target customers,

however not delivered by current products or services. Such benefits shall be the key priority

for company and a main focus in order to make the customers more satisfied and therefore

more prone to repeat purchases.

Phase I: Customer

Strategy and Focus

Phase II: Customer

Satisfaction Measuremen

t

Phase III: Analysis and

Priority Setting

Phase IV: Implementation

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Fourth phase of the customer orientation process requires that all the priorities set in phase

three are translated into specific actions and process, which will be conducted. Those actions

shall result in making the customer more satisfied through delivery of improved product or

service.

This customer orientation process shall never end and shall be repeated – after fourth phase,

phase one shall start, which shall verify, if the improved product really satisfied customer to

larger extent.

To summarize the customer orientation model, it is entirely focused on customer satisfaction.

Based on this model, only customer oriented company, which tries to deliver offerings

tailored to customer’ needs may expect returns from their actions. Returns equal higher

satisfaction levels being observed, which in turn shall increase the probability of repeat

purchases and as a result, increasing returns for the organization. Customer orientation model

undoubtedly has the customer focus and customer orientation in its hearth and stresses the

importance of customer satisfaction for the business performance.

Although customer orientation model has stressed the importance of customer satisfaction for

business performance, it has not quantified the importance. This leads us to the next theory,

which has taken the discussion to next level and quantified the importance of customer

satisfaction to business performance – The EFQM Excellence Model.

1.2. Customer satisfaction in The EFQM Excellence Model

The authors of The EFQM Excellence Model have not only acknowledged the importance of

customer satisfaction for organizations, but also measured the importance for the business

performance.

The EFQM Excellence Model was introduced in 1992 and is a practical tool, which in mid-

term helps organizations to evaluate and improve their performance, and in long term enables

them to strive for excellence.

The organizations are evaluated based on nine criteria, which are included in The EFQM

Model. Five of them are “enablers” – they cover, what an organization does, and remaining

four are “results”, which include what an organization achieves. There is relation between

two groups – the “results” are driven by “enablers”. The structure of the model is presented in

the below figure.

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Figure 1.2. The EFQM Excellence Model

Source: www.efqm.org

The EFQM Excellence Model, similarly as customer orientation model, puts customer and his

satisfaction in the heart of the theory. Specifically, it discusses the concept of customer

satisfaction within three of its nine criteria:

1. firstly, it is stressed within “Leadership” criterion, that company leaders need to

meet, understand and respond to needs and expectations of stakeholders, which also

include customers as one of most important groups.

2. secondly, also “Processes” criterion concentrates on satisfaction. Processes in the

organization shall be designed in such manner that they support organizations’ policy

and strategy, fully satisfy and generate value for its customers and other stakeholders

(The EFQM Excellence Model 1999 manual).

3. lastly, “Customer results” criterion is completely dedicated to customers’

satisfaction. Measures within this criterion are supposed to assess customer’s

perception of overall organization’s image, his or her satisfaction with

www.efqm.org

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products/services, sales and after sales support and evaluate customer loyalty to the

organization.

The focus on customer and his or her satisfaction in three out of nine criteria in The EFQM

Excellence Model is the evidence supporting the importance of customer satisfaction for the

business performance.

The authors of the model have established importance weights for each criterion in the model.

It is necessary to stress, that “Customer results”, called also customer satisfaction criterion,

is the weightiest criterion in the model and accounts for twenty percent of the total scoring

system when companies assess and measure their own excellence (Gronholdt, Kristensen,

Martensen, 2002). To put it differently, customer satisfaction has not only the largest impact

on evaluation of organization excellence, but most importantly understanding the customers

and measuring their satisfaction is important step in quality improvement, which than results

in higher satisfaction levels, improved business results and business excellence.

To summarize, based on the EFQM Excellence Model, customer satisfaction is the most

important factor driving the organization towards excellent performance and increasing

financial results. Having in mind that customer satisfaction is important for business

performance, that it is the most important factor in driving business towards excellence, it is

important to quantify the influence of increased satisfaction on the company performance.

1.3. The evidence of positive impact of satisfaction on business results

In literature, there have been lots of empirical studies conducted on satisfaction influence on

company’s performance, as well as effect on the influence of customer dissatisfaction on the

firm’s results. The satisfaction or dissatisfaction influence on organization’s performance may

be discussed in three aspects:

1. positive impact of growing satisfaction on return on investments (ROI), prices of

stocks and shareholder value

2. positive impact of satisfaction on customer retention and as a result lower costs or

higher returns resulting from long term relationship with the customers

3. negative impact of customer dissatisfaction on business performance and business

results

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There is strong evidence within those three aspects for positive correlation between growing

customer satisfaction and business results.

1.3.1. Satisfaction influence on ROI, stock prices and shareholder value

The empirical studies were conducted based on customer satisfaction measurement models

and using the data acquired during models testing and implementation in order to evaluate if

there is positive correlation between increased satisfaction and ROI, stock prices and

shareholder value.

Starting with Swedish Customer Satisfaction Barometer index (which will be described in

detail in further course of this paper), it was analyzed, what is the effect of increased

satisfaction on ROI. The results of the study conducted by Anderson, Fornell and Lehmann

(1994) are the first, large sample evidence, that customer satisfaction is related with company

performance. The study revealed that as the satisfaction changes by one percent, ROI changes

by 0.4 percent.

Further studies conducted on SCSB by Anderson, Fornell and Rust (1997) proved that

average elasticity of ROI is higher for goods – 0.265 than for services – 0.14. This implies

that it is much more difficult for service companies to satisfy their clients than it is for

production companies. Such difference may be related to the fact, that it is much easier for a

consumer to distinguish between and objectively evaluate the quality of the product rather

than the service.

Referring further to the Swedish example, Ittner and Larcker have taken the analysis to the

next level, and examined the correlation between satisfaction and stock prices. The results of

their study prove that a one percent change in the satisfaction index translate into about seven

percent change in shareholder value (Gronholdt, Kristensen, Martensen, 2002).

The same authors carried the analysis based on American Customer Satisfaction Index

(ACSI). The study results were in line with the Swedish results and they confirmed that there

is relation between satisfaction levels and stock prices; companies with highest customer

satisfaction indexes earn return on stock price of 1-2 percent per month above the average

return on the market (Gronholdt, Kristensen, Martensen, 2002).

To summarize, there is solid evidence in the form of results of various empirical studies, that

customer satisfaction is correlated with financial results in following manner:

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1. increasing customer satisfaction positively influences return on investments (ROI)

2. the higher the customer satisfaction, the higher earnings on stocks for shareholders

3. increasing satisfaction drives positive change in shareholder value

1.3.2. Customer retention impact on business results

Satisfaction is a prerequisite for customer loyalty and retention. In other words, if customers

are satisfied with the product, it is probable, that they will be loyal to the company and that

the loyalty will be translated into repeated purchases. Repeated purchases are in turn

prerequisite to increasing financial results for the company, what implies that customer

retention is profitable to the organization. Going further, the benefits from retaining the

customers are larger than from acquiring new one and the costs associated with current

customer are lower and declining as compared to new customer.

This thesis has been supported by Reichheld (Johnson, Herrmann, Huber, Gustafsson, 1997),

who has been discussing effects of customer retention on business performance and he

defined areas – both cost and revenue, which are strongly impacted by customer retention:

1. Acquisition costs; all costs related with attracting customer to the company, such as

incentive program, creation of customer accounts, customer training. As these costs

appear in the early stage of relationship with the customer, customer retention allows

for avoiding them.

2. Start-up costs; costs, they are related to the beginning of cooperation with the

customer, egg. set up of customer bank account. With time, the account is maintained

and some costs are associated with that, but one time set up costs do not happen again.

3. Base revenues; the revenue, which a company accounts for regularly during each

following period, e.g. base revenue from monthly payment for mobile phones. When

customer is retained, the base revenue is guaranteed cash flow for a firm.

4. Volume effects; the surplus revenue, which company earns as the relation with a

customer is developing. Customers, if satisfied, tend to increase their spending with a

company by either buying larger quantities of a product.

5. Spin-off effects; with time, customers have a tendency to purchase complementary

products or services, e.g. satisfied car owner shall buy second car for his family

members or will acquire a car gadgets from the company, e.g. watch from Company X

collection

6. General efficiency effects; operation costs are expected to decrease with time, as the

company gets to know its customers better and therefore is capable of delivering the

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products or services in the required manner. On the other hand, customers get to know

the structure of the company and the requirements from the company side, which

enable for delivery of higher quality offerings. In other words, cooperation between

both sides becomes smoother.

7. Referral effects; satisfied customer shall talk to two persons about his or her positive

purchase experience, however dissatisfied customer will talk to and discourage ten

persons from potential cooperation with the organization. Nowadays, this factor is

becoming of extreme importance – as the traditional marketing tools have become

well known and understood by customers, customer referrals and so called word of

mouth has a great power.

8. Price- sensitivity effects; loyal customers are less price sensitive than new customers.

If the relationship with the company is satisfactory for the customer, he is willing to

pay more for the same products. Moreover, if the customer is acquired in his early

stage of life, as he grows older and becomes more affluent, he is also willing to trade

for premium products within the same supplier.

If customer is satisfied, he is probable to continue the relationship with the company. If that is

the case, the above described effects shall happen – they will either lead to lower costs or

higher returns. In the end, as the relationship with customer is continued, profit per customer

shall grow over time.

1.3.3. Dissatisfaction influence on business performance

We have already explained the importance of customer satisfaction for business performance

and proved that there is measurable, positive impact of increased customer satisfaction on

business results. This implies that companies, which enjoy increasing satisfaction of its

customers, at the same time note increasing business results. However, there are those

companies, who observe declining satisfaction. The question is therefore what are the results

of customer satisfaction decline?

Based on Hirschman’s theory (Johnson, 1996), dissatisfied customers may react in two ways

– they may either voice or exit.

Customer exit is the worse consequence of customer evaluation of product offering. In such

situation, the organization looses customers, what results in declining sales and revenues for

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the company. Moreover, such customer, called “dissatisfied switcher”, will most probably

express his or her dissatisfaction through word of mouth to other potential customers. In other

words, dissatisfaction has not only direct effect on organization business measured as lost

potential sales, but may also have indirect effect on the business in the form of negative word

of mouth. Therefore it is of extreme importance for the company to handle in the right manner

second possible reaction of dissatisfied customer –customer voice.

If a customer is dissatisfied, before he or she exits, he or she may also complain to the

company. Depending on how his or her complaint is handled – whether in satisfactory or non-

satisfactory manner, he or she will either exit or retain with a company. Therefore it is

extremely crucial for the company to establish effective complaint management system which

will ensure, that two actions happen: a) listening to complaints and b) reaction to the

complaints.

The establishment of complaint system is important due to three reasons:

1. effective complaint handling system may prevent from customer exit and therefore

business loss

2. it may prevent from negative word of mouth from dissatisfied switchers

3. dissatisfied customers, who are potential “dissatisfied switchers” and whose

complaints are handled in satisfactory manner, may become even more satisfied and

loyal clients – so called “satisfied repeaters”. As a result, they shall not only

repurchase from the company, but shall also convert the negative word of mouth into

the positive one.

Apart from dissatisfaction consequences described by Hirschman – exit or voice, it may also

happen that a dissatisfied customer will not voice and will not exit. In such case the

dissatisfied customer will not voice a complaint, as he or she believes that there will be no

benefit from such action – no positive response from the company. At the same time, he or

she will retain with the company, as there is no other available or no better product or service

provider. Such consumers are called dissatisfied repeaters. They are most often acting in the

low competition or even monopoly markets – e.g. state-owned services, where a choice is

limited or none, therefore despite dissatisfaction, consumers need to repeat the purchase.

However, if the economic environment changes, competition increases and more interesting

offerings appear, dissatisfied repeaters are likely to switch to those new options. Therefore

those customers shall also be in the loop and actions shall be taken to increase their

satisfaction levels so as to prevent them from switching to other companies.

20

The below table presents four types of customers, out of which two were described above –

dissatisfied switchers and dissatisfied repeaters.

Figure 1.3. Four customer types

Repeat Switch

High Satisfied Repeaters

Satisfied Switchers

Low Dissatisfied Repeaters

Dissatisfied Switchers

Repurchase Behaviour

Customer Satisfaction

Source: Johnson 1996

The empirical studies on satisfaction and dissatisfaction influence on business performance in

general confirm and support the conclusions, that;

satisfaction is of crucial importance for business performance

satisfaction has positive impact on business results

retention, as a result of satisfaction, has positive influence on lower costs and higher

returns

dissatisfaction may lead to customer base decline and therefore generate lower return

In more detail, the discussed studies justify organizations’ choice of customer orientation

strategy. Starting from positive influence of customer retention on lower costs and higher,

increasing profits and ending with higher return on investment for companies, who are able to

raise customer satisfaction levels – these are all undeniable evidences, that investment in

customer satisfaction and retention shall be the key area of focus for managers. In particular

in maturing economies, where market dynamics presents a one-digit quote or even zero

number, where markets are saturated with competing, comparable products or services, it is

important to adopt defensive strategy. Defensive marketing concentrates on customer

retention by either increasing customer satisfaction or building switching barriers and is

opposite to offensive marketing, which focuses on increasing market size and building market

21

share. Majority of companies adopt balanced mix of both strategies - acquiring new customers

and retaining the current ones. However, in maturing economies, the skewness is towards

defensive strategies, as it becomes more and more difficult and costly to acquire new clients.

Therefore, increasing customer satisfaction has become a key focus area for managers in

today’s organizations.

In the course of this chapter we have proven the undeniable importance of customer

satisfaction for increasing business excellence and described the studies, which measure the

impact of customer satisfaction on ROI and on stock prices. We came to the conclusion that

as increasing customer satisfaction has positive effects on business growth, it shall be the top

priority for the management. However, we have also discussed that in order to satisfy the

customers better, it is necessary to diagnose current level of satisfaction by establishment and

implementation of customer satisfaction measurement model. Thank to such model, the

weaknesses of current offerings can be spotted and eliminated to deliver products capable of

satisfying the customer to larger extent. However, to build the satisfaction measurement

system, it is necessary to understand the concept of satisfaction, its drivers and consequences.

Therefore next chapter will focus on theoretical framework of satisfaction, its antecedents and

consequences.

22

2. THE THEORY OF CUSTOMER SATISFACTION

2.1. The definition of customer satisfaction

In the literature, there has been discussion about two major concepts of satisfaction;

transaction-specific satisfaction and cumulative satisfaction (Gustafsson, Herrmann, Huber,

Johnson, 1997).

The first one is described as customer evaluation of single experience with a product or

service – therefore how happy the customer is with the offering at given point of time, during

concrete transaction. Transaction-specific concept refers to satisfaction as the evaluation of

single experience.

Opposite to transaction specific satisfaction is the concept of cumulative satisfaction, which

understands satisfaction as customer’s up to date experience with a product or service. In such

comprehension, satisfaction is the sum of evaluations of all purchase and consumption

experiences with a product during whole relationship.

During the course of this paper, cumulative satisfaction concept will be used, as it is more

appropriate for automotive industry. In this durables business, purchases are infrequent and

satisfaction is understood as a long term experience. The owners of the cars, if asked about

satisfaction with the particular brand, refer to cumulative satisfaction – they talk about

purchase experience, vehicle use experience, ending with after-sales service experience.

2.2. Antecedents of customer satisfaction

Satisfaction has its antecedents or drivers – factors, which influence the satisfaction levels.

In general, there are two major drivers of customer satisfaction – product’s performance,

which includes both product’s quality and product’s value (relation of price and quality). In

more detail, satisfaction drivers were initially defined in two models in the literature –

disconfirmation model, which is often associated with transaction-specific satisfaction and

performance model used in studies of cumulative satisfaction.

Specifically, the theory of the models and the differences between them are described below:

a) Disconfirmation model

Referring to disconfirmation model, the difference between perceived product’s

performance and expected performance is a driver of satisfaction.

23

Disconfirmation model assumes that satisfaction increases if performance exceeds

expectations – in such case we talk about positive disconfirmation. In the opposite case,

when product or service performs below expectations, there is negative disconfirmation

effect, which leads to decline in satisfaction.

The figure below graphically presents the reasoning of disconfirmation model. It assumes

that expectations may have both positive and negative influence on satisfaction. If

performance increases over constant expectations, there is positive disconfirmation, which

positively influences satisfaction. However, if expectations grow above constant

performance, there is negative disconfirmation of expectations and satisfaction decreases.

Such transaction specific gaps are than aggregated into an overall customer satisfaction

(Johnson, M.D., 1996).

Figure 2.1 The Disconfirmation Model

Source: Johnson, M.D., 1996

b) Performance model

Within the performance model, expectations of product or service performance are

similar to product’s image, which is based on either personal experiences with the

product or information and opinions heard and learned from other users. As opposite

to disconfirmation model, expectations have only positive influence on satisfaction.

Moreover, expectations shall have positive impact on perceived performance, what

means that expectations are able to predict current level of performance. In addition, if

expectations are strong, than they shall positively influence the perceived performance

– therefore in such case the evaluation of performance may be far from real

performance level.

Performance minus

expectations Customer

satisfaction +

24

Figure 2.2. The Performance Model


Despite the expectations importance in the performance model, it is the performance,

which is main driver of customer satisfaction. Based on the model, performance has

positive effect on satisfaction level. The graph below represents the performance

model (Johnson, M.D., 1996).

Comparing disconfirmation and performance models, it is necessary to say, that the second

one has been evaluated as more appropriate model for predicting customer satisfaction. In

general, empirical studies of satisfaction confirm that expectations have rather positive than

negative influence on satisfaction. Moreover, disconfirmation model is adjusted to studies of

transaction specific satisfaction, while majority of empirical studies understand satisfaction as

cumulative, not transaction specific. As an effect of the above arguments, performance model

is evaluated as superior to disconfirmation model in the studies of customer satisfaction. Such

conclusion will be also valid in the practical part of this work, as the satisfaction measurement

model will be assessing up to date experience and therefore satisfaction with the automobiles,

rather than single transaction satisfaction.

Performance Customer

satisfaction

Expectations

+

+

+

25

2.3. Consequences of customer satisfaction.

Satisfaction has not only its drivers – performance and expectations, but also its results –

loyalty and retention. Those two consequences are correlated with each other, but are at the

same time distinct results of customer satisfaction.

Loyalty is only expressed psychological predisposition toward purchasing and/or using a

particular product/service once again, however it does not guarantee a success to an

organization measured as customer retention. In other words, loyalty is a high perceived or

expressed likelihood of repurchase or willingness to pay a higher price, but does not mean,

that customer will repurchase from an organization (Johnson, M.D., 1996). It is the retention,

which is ultimate consequence of satisfaction and which is the actual act of repurchase.

There are various reasons, due to which loyal customer – or the one, who expresses the

loyalty attitude, in the end switches to competition. The Customer Experience Model

(presented in the figure below) explains why loyalty does not necessarily end up with

retention.

Figure 2.3. The Customer Experience Model


Customer

perceptions, judgements and

choice

Customer’s internal knowledge database

Consumption,

customer satisfaction and

loyalty

External market infomation

26

The model separates the consumption experience and resulting satisfaction and loyalty from

the repurchase decisions and explains, what happens, when potentially satisfied consumer

does not repeat the purchase with the same company. Based on the model, there are three

aspects of product or service consumption and the consecutive satisfaction and loyalty.

First of all, customer relation with the company starts with the decision about the product or

service purchase and the consumption. As a result of consumption experience, customer

forms the evaluation, perception and expectation towards the product and at the same time, he

or she becomes more or less satisfied with the product.

Secondly, during the consumption process, consumer stores in mind all the information

learned regarding experience with the product. He or she uses those experiences and

information when making decision about the future repurchase. Supposing that he or she is

satisfied with the product, this makes him or her more predisposed towards repeated purchase.

Finally, the consumer comes to the decision about repurchase of the product. He or she will

most probably make the decision based on the knowledge and experience gained so far.

However, as the world is changing, customer is exposed to new information during the

consumption – repurchase process. He or she receives information about new offerings, is

exposed to word-of-mouth information. As a result, even though customer is satisfied with the

current product and expresses to be loyal, external markets conditions may influence his

decisions and he or she may switch. Such customers are called satisfied switchers – they may

switch e.g. from Audi to BMW, because BMW will offer better priced offer – therefore

customer will perceive BMW as higher value car, or BMW will offer technological

advancements, that Audi is not able to deliver. On the other side, the above described scenario

may not happen. Even though a customer is exposed to external information and knows other

options, he may stick with the current brand and repurchase. But such case will most often

happen by habitual, daily purchases. In case of durables – and such is the automotive industry,

companies need to make sure, that they have the absolute competitive advantage and that no

other brand is capable of attracting current customers.

Both satisfaction drivers and results are linked in a theoretical framework, which helps to

understand the relations between drivers and effects of satisfaction. The framework is

presented in the below figure.

27

Figure 2.4. A framework for linking quality, satisfaction and retention

Source: Johnson, Herrmann, Huber, Gustafsson, 1997

At the beginning of the whole process is the actual production of product or service and

placing an offer to the consumer. Providing that the product matches consumers needs, the

consumption process starts. During that process, consumers evaluate the product with regard

to its performance – understood as evaluation of quality, value (equal to quality versus price

paid and price paid versus quality) and confront the performance versus expectations. Such

evaluation lays ground for perception of satisfaction – the extent to which product or service

met customers needs. The level of satisfaction or dissatisfaction strongly affects and predicts

customer loyalty and as a result customer retention, however it guarantees nothing, as even

satisfied customers may switch to competition. Therefore in order to retain customers,

companies need to continuously improve current offering, present revolutionary and

innovative products and constantly deliver higher customer value. In other words, satisfying a

customer is a constant process, which means that new and better ways need to be found to

customer needs.

To summarize, customer satisfaction is important concept for business performance and has

measurable impact on business results. It is due to the fact that satisfaction influences loyalty

and consecutive retention. In other words, dissatisfied consumers may substantially negatively

impact business results. Therefore, it is of extreme importance to measure the current

satisfaction levels to be able to spot problems, eliminate them and deliver improved products

and services to customers in order to lift current satisfaction levels.

Internal product and

service production

and maintenance

process

Perceived value,

quality, and expectations

Customer satisfaction

Customer

loyalty and complaint behavior

C O N T E X T

Customer retention

28

Having discussed the theory of satisfaction, its importance and impact on business

performance, we will now discuss satisfaction measurement systems developed so far within

the literature.

29

3. CUSTOMER SATISFACTION MEASUREMENT SYSTEMS

3.1. Antecedents of satisfaction measurement system implementation – customer’s

personal values research

Referring to customer orientation strategy, an organization, which recognizes the need to

make its customers more satisfied, shall first develop the customer satisfaction measurement

system in order to evaluate current level of satisfaction and be able to translate findings of the

study into the specific improvement plans. Therefore, for each organization, which is

customer focused, settlement and implementation of customer satisfaction measurement

system is a must and a major step towards customer satisfaction growth. However, customer

satisfaction measurement systems are just part of overall customer research.

Before any satisfaction measurement system is implemented, an organization shall get to

know its customers better. This includes knowledge of demographic characteristics, such as

age, gender, income, but most of all the set of customer’s personal values.

The theory, which justifies the importance of the knowledge of customer’s values is the

means-end theory. The theory explains how the choice of concrete product enables the

consumer to satisfy his or her personal values. In other words, how the “means” – products

lead to desired end states – called “ends”.

Referring to the theory, customers consider products as bundles of attributes (Johnson,

Herrmann, Huber, Gustafsson, 1997). During the decision - making process, they do not

analyze the attributes of the offering separately, but they analyze all product attributes

together as a set, and based on their perceived utility, customers make decision about the

offering purchase. As a result, these are those attributes, which enable the customer to fill his

or her wants. What drives customer perception of attributes utility and ability to satisfy his or

her wants are the personal values in life, which the customer is trying to satisfy and which

guide his or her decision-making process. The central hypothesis of the means-end theory is

that customers consider bundles of products attributes to be the instrument (means) for

fulfilling desirable goals or values (ends) (Johnson, Herrmann, Huber, Gustafsson, 1997).

The means-end theory argues, that customers make their decisions about the product purchase

based on the knowledge gained during up to date consumption process, which is structured

into so called means-end chains. These chains link product’s attributes, utility components

30

and set of personal values into a process, which explains, what drives customer decision about

the purchase and how the process is being conducted.

Figure 3.1. The means-end model

Figure 3.1. Johnson, Herrmann, Huber, Gustafsson, 1997

Attributes, which are products characteristics, can be divided into:

Concrete attributes – which include physical, chemical or technical properties of the

product

Abstract attributes – which are as opposite to concrete attributes, non-measurable

ones, they are one’s subjective perceptions about the products, e.g. aggressive line of

the vehicle

Based on concrete or abstract attributes of the product, consumer evaluates its utility. There

are two types of utility assessment, which are connected with two kinds of attributes:

functional utility is the assessment of the concrete attributes – therefore of physical

characteristics of the product.

socio-psychological utility is connected with abstract attributes – usefulness and

results of non-measurable attributes, e.g. thank to aggressive line of the vehicle

customer will feel much younger, when driving the car.

Finally, the set of values is understood as series of individual standards, which remain

constant over period of time and serve to formulate goals in life and put them into practice in

everyday behaviour (Johnson, Herrmann, Huber, Gustafsson, 1997). In other words, personal

attributes utility components set of values

concrete abstract functional socio-psychological instrumental terminal

31

values are the ultimate drivers of consumers’ behaviour and decisions. The values are split

into two distinct types:

instrumental goals consist of moral (tolerance, responsibility, honesty) and

achievement-oriented values (logical, intellectual and imaginative)

terminal values include desirable goals in life, which can be divided into personal

values (inner harmony, maturity in love) and social values (global peace, national

security).

Based on the means-end theory, consumers will choose products with attributes, which will

produce desirable consequences – therefore will offer desirable utility components and will

respond to customer’s personal values. For example, if social acceptability value is core to

customer, than he or she will choose a car with high brand image, e.g. BMW, as driving the

BMW will confirm his or her membership in a high class of society and will impress family,

friends and colleagues and as a result will lead to feeling of social acceptability. Such

customer will under any circumstance choose e.g. a Fiat brand, as this is brand has value or

mass image and will not impress the others and therefore will not lead to social acceptability

feeling or state.

In general, consumers hold different personal values in their lives and based on those values,

they make choices between offerings. Knowledge of customers’ values helps the organization

to tailor its offerings to those needs and by that respond to them better than competitors. As

the end result, such action will ensure that organizations’ product, not the competitors’ is

chosen and that customers’ satisfaction is brought to higher levels.

In more detail, all customers of a particular company have diverse values and needs. As a

result of such heterogeneity between customers, only differentiated offerings are able to

satisfy customer’s diverse needs.

Specifically, based on the knowledge of customers’ personal values and needs, a firm’s

clientele shall be divided into groups, which will be homogenous inside and heterogeneous

between the groups. Only such segmentation will enable to:

deliver products tailored to needs of each customer segment

lead to higher satisfaction of firm’s clientele.

32

Therefore before satisfaction measurement system is implemented, creative and flexible

research methods shall be used to discover the hidden needs and values of customers. Most

often qualitative methods used for this part of research are focus groups, face to face

interviews, surveys, laddering methods etc.

After knowledge of customer personal values is gained, satisfaction measurement system

shall be implemented, as it is the most informative tool to measure the extent, to which

product attributes are able to respond to customer needs.

3.2. Rationale for development and use of industry or nation universal customer

satisfaction measurement indexes

Thank to knowledge of customer’s needs, company is able to evaluate, how well its current

offerings serve customer needs. Such evaluation shall be done with use of customer

satisfaction measurement system.

Satisfaction measurement system is a crucial part of customer research helpful in diagnosing

customers’ satisfaction levels. Such findings are good guidance about areas of products

performance, which shall be improved in order to lift the satisfaction to the next level. Many

companies have been measuring satisfaction levels on continuous basis. It has been done in

more or less advanced manner and most probably many tools – mainly qualitative - were

developed to measure customer satisfaction. However regardless of the advancement of

methodology used by single companies, satisfaction measurement systems developed for a

single organization have major limitations.

First of all, measurement systems of that kind can not verify whether satisfaction index equal

to 80 is a “high” or “low” result, as there is no benchmark. As companies build satisfaction

measurement systems based on different methodologies and measurement indexes, which are

tailored to only this organization’s competitive environment, results are not comparable

between the organizations. It means that satisfaction index of 70 scored by company A’s may

be in reality higher result than index of 80 reached by company B provided that both

companies use different satisfaction measurement systems.

Secondly, such indexes deliver results, which are not comparable within the industry. It

implies that it is not possible to say, whether index of 80 is “good” or “bad” result on industry

level, as there is no average for industry available. Therefore, it can not be assessed if

companies in industry A satisfy their customers better than companies in industry B.

33

Finally, without unified, industry or even nation wide index, satisfaction levels can not be

compared across companies from other industries, sectors or other countries.

To summarize, without usage of industry universal index, an organization can only monitor

progress and dynamics of its customer’s satisfaction over time. Such firm is even not able to

say, whether the score is on high or low level. What is more, there is no benchmark to

competition, not to mention industry or other economies.

In order to respond to such limitation and enable comparisons, nation and industry wide

measurement models were developed in various countries and continents. The ones that are

perceived as pioneering ones and which laid ground for further development of satisfaction

models were:

1. Swedish Customer Satisfaction Barometer – SCSB

2. American Customer Satisfaction Index – ACSI

3. European Customer Satisfaction Index – ECSI

3.3. National Customer Satisfaction Indexes

3.3.1. Swedish Customer Satisfaction Barometer

First national customer satisfaction index was developed in Sweden in 1989. It was designed

in such a manner, that it enabled for estimating satisfaction index on the level of company and

total industry. As a result, it enabled to make comparisons of satisfaction measurement results

between companies, but also industries.

Since SCSB establishment, data was collected annually. Every year customers of about 100

companies from 30 leading industries were contacted for the interview, what resulted in ca.

25 000 respondents answering to the survey questionnaire every year. Respondents were

contacted via telephone and during ca. eight minute survey they were answering to the

questions using 10 point scale (Fornell, 1992). The customers evaluated their satisfaction with

organizations offerings on the brand level. However, if a company was selling multiple

brands, only the largest brand was chosen to represent the company.

34

After data collection results of the survey were analyzed using partial least squares

methodology, which details will be described in further chapters of this paper.

The structure of the original SCSB model is presented in the below figure.

Figure 3.2. The SCSB (Swedish Customer Satisfaction Index)

Source: Fornell, 1992

In each satisfaction measurement model, which will be discussed within the course of this

work, satisfaction is central variable and has its antecedents and consequences. What is more,

usually all or majority of variables in the model are latent variables – variables, which can not

be observed separately. Each of the latent variables is described by set of observable

variables.

Within the SCSB model, satisfaction is a function of only two antecedents – expectations and

perceived performance. This part of the model is based on the performance model described

in the chapter 2.2 of this paper.

Expectations are defined as what customers expect regarding the product performance – how

well, they believe, the product or service will perform. In the SCSB model, expectations play

an important role as determinants of satisfaction. According to the model, they shall

positively influence the perceived performance, as customers learn from experience and based

on the knowledge form expectations towards a product performance. Moreover, as

Perceived Performance

(Value)

Customer Expectations


(SCSB)

Customer Complaints

Customer Loyalty

35

expectations forecast firm’s ability to provide future performance, it is argued that

expectations shall have positive impact on satisfaction (Andreassen, Cha, Gustafsson,

Johnson, Lervik, 2001). The SCSB model lays heavy importance on confirmation /

disconfirmation of expectations, as driver of satisfaction. Expectations are not only included

as a separate construct, which influences perceived performance and satisfaction, but

discrepancy of expectations is also part of definition of satisfaction construct. In the SCBS

index expectations are the observable variable, operationalised by just one question.

Second driver of customer satisfaction in the SCSB model - perceived performance (value) -

is defined as relation of product price to product quality. This variable is described by two

measures:

quality given price

price given quality.

In other words, authors of the SCSB model believe, that customers evaluate product’s

performance by comparing the quality of the offering versus price paid and price paid versus

quality of the offering. Perceived performance is expected to positively influence customer

satisfaction – when it increases, so does the satisfaction.

Satisfaction variable in the SCSB index described by three measures:

1) general satisfaction,

2) confirmation of expectations,

3) the distance from the customer’s hypothetical ideal product or service (Fornell,

1992).

Such defined satisfaction is expected to have two immediate consequences – customer

complaint and customer loyalty.

Customer complaints are measured by two variables – complaint to personnel and complaints

to management. Similarly, customer loyalty is also operationalized by two variables: (1)

tolerance to price increase – how much more the customer is ready to pay provided that he or

she is likely to repurchase, (2) declared repurchase intention.

Such consequences of satisfaction are derived from previously discussed Hirschman’s exit –

voice theory. Based on it, if a customer is dissatisfied, he or she may either stop the

relationship with a company (exit) or complain (voice). Within the SCSB model, there is

36

relation between customer complaint and customer loyalty. The authors of the model suggest

that, if the company develops proper complaint handling system, the complaining customers

may turn into loyal ones. However, if the company does not handle complaints, customer exit

is likely.

The SCBS model, as the first national satisfaction measurement system, delivered few key

findings, which were later often discussed in the literature.

Firstly, the SCSB index turned out to be higher for industries, where:

1. offerings were differentiated and customer demand was also such, therefore match

between supply and demand was possible. An example is an automobiles industry,

where heterogeneous demand was satisfied by differentiated offerings and this

industry in 1991 scored 78 on satisfaction index.

2. needs and supply were homogenous – basic foods (milk, sugar) scored also highest

results in 1991 – 78 as in case of automobile.

Secondly, lowest satisfaction levels were visible for industries, where heterogeneous demand

could not be matched by supply, which was not differentiated. Good example of such industry

is television broadcasting, which received one of the lowest scores of SCSB index – 48.

Finally, it was apparent, that services received lower scores on satisfaction index than

products (Fornell, 1992).

The Swedish Customer Satisfaction Index, as the first truly national satisfaction measurement

system, laid ground for development of the indexes in other countries, as well as other

continents.

3.3.2. American Customer Satisfaction Index

Second national satisfaction measurement index was developed in United States in 1994 and

was named The American Customer Satisfaction Index.

The methodology of the ACSI was based on the SCSB, however due to size of American

economy, was applied to larger number of companies, industries and sectors.

The largest companies from industries representative to major industry groups, which were

chosen from seven major economic sectors were included in the design of the sample used in

ACSI research. As a result, in 1994 ACSI research covered more than two hundred companies

from over forty industries in the seven major consumer sectors of the economy (Anderson,

37

Bryant, Cha, Fornell, Johnson, 1996). Within each company approximately 250 interviews

with company customers were conducted.

Respondents were supposed to answer brand or model level questions using 10 point scale.

As in case of SCSB, partial least squares methodology was applied to the analysis of the

results from the survey.

The structure of the ACSI model was based on the SCSB, however there were few differences

regarding model structure, but also measurement properties of the model.

Figure 3.3. The American Customer Satisfaction Index (ACSI) Model

Source: Anderson, Bryant, Cha, Fornell, Johnson, 1996

The major improvements in the ACSI versus SCSB models are as follows:

1. Expectations variable is explained by three observable variables - as opposite to

SCSB, where it was measured by only one construct.

2. Perceived performance (value) construct used in SCSB model was replaced with

two separate constructs – perceived quality and perceived value. The first one

measures the influence of the quality and the second one the influence of the price on

Perceived quality

Customer expectations


(ACSI)

Customer Complaints

Customer Loyalty

Perceived value

+

+

+

+

+

+

-

38

customer satisfaction. Such modification enables to evaluate, whether satisfaction in

certain companies or industries is more driven by price or by quality of the offering.

Perceived value variable was described by two questions – quality relative to price and

price relative to quality. Perceived quality variable is measured by three questions,

which enable to confront the product or service actual performance versus

expectations held by customer before the purchase.

3. Customer loyalty is described by one extra variable as compared to SCSB index –

the additional variable is supposed the give answer to the questions, of how much the

price would need to be discounted to encourage the customers to repurchase, provided

that they are unlikely to repurchase.

Findings from ACSI index contributed greatly to explanation of satisfaction concept and its

consecutive driver - loyalty.

In general, in line with findings from SCSB index, the ACSI Model confirmed, that

satisfaction is greatest in goods, lower in services and definitely lowest in public

administration. However, satisfaction scores for goods and services were higher in ACSI than

in SCSB. Referring to literature, satisfaction levels are expected to be higher when

competition, differentiation, involvement, or experience is high or when switching cost,

difficulty of standardization or ease of evaluating quality is low (Anderson, Bryant, Cha,

Fornell, Johnson, 1996). Authors of ACSI model used those findings to conclude, that

satisfaction is higher in U.S. compared to Sweden due to higher differentiation and

competitiveness in U.S. To comment further on that conclusion, it shall be also taken into

consideration, that cultural and psychological conditions may to large extent explain those

differences. As Americans are much more optimistic than Europeans on average and Swedes

in particular, this shall in general predispose Americans to choose higher scores on the scale,

when responding to survey questionnaire.

Furthermore, the ACSI model delivered important findings, which explain the complex theory

of satisfaction and loyalty. Specifically, there were three major conclusions from the ACSI

Model (Anderson, Bryant, Cha, Fornell, Johnson, 1996):

1. Customization of an offering (how well does the offering fit the personal needs?)

is more important than reliability of the offering (how often has the things gone

wrong?). Naturally, customization is more important for services than manufactured

goods, however it still implies that tailoring the product or service to customer’s needs

shall have larger impact on perceived quality and satisfaction than standardizing the

39

offerings in order to ensure greater reliability.

2. Expectations have stronger influence on perceived quality and perceived value

for industries, where there is relatively low variance in consumption and

production – and where customers make routine purchases. Once the variance in

offerings is large and so is variance in consumption, than expectations shall have

weaker impact on perceived quality and price. As a result, expectations impact turned

out to be lowest in manufacturing durables, finance/insurance and services. The same

conclusions were valid with regards to expectations influence on satisfaction – lowest

impact was observed in manufacturing durables and finance/insurance. Simplifying,

the latest quality experiences with an automobile or insurance play more central role

to satisfaction than expectations held before purchase. If a customer is more engaged

in the decision process and the purchase, product performance will influence to larger

extent his or her satisfaction than the expectations held before the purchase and before

the experience with the offering.

3. Based on ACSI Model, quality has larger impact on customer satisfaction than

value. As long as value concept plays important role in customer attraction and during

decision-making process, quality is more important in satisfying the customer and

therefore predisposing him to be loyal and retain with a company. There were industry

differences visible; price-driven satisfaction was highest for non-durables, while

lowest for durables, services, retail and government agencies. Implication from this

finding is such, that in maturing economies, where industries are saturated, where

supply is heterogeneous where acquiring the customer is extremely difficult and in

practice very often equals taking over competitor’s customer base, quality is crucial

and is much stronger predictor of customer loyalty and therefore probable repeated

purchase than price.

The ACSI Index was widely commented after its creation and it was also tested and applied in

many empirical studies. It also laid ground for development of European based index called

the European Customer Satisfaction Index (ECSI).

3.3.3. European Customer Satisfaction Index

The goal of ECSI development was to supply European companies and countries with similar

diagnostic tool as American counterparts have been using since 1994. Moreover, development

40

of similar index enabled the comparisons between countries within Europe, but also between

Europe and North America.

The ECSI model was developed and tested for the first time in 1999, while second round of

research was carried out in 2000 with minor changes implemented to the original model.

Twelve European countries participated in the 1999 project. In terms of industries covered by

ECSI model, telecommunication was included in the research in all markets, while retail

banking and supermarkets in almost all participating countries (Juhl, Kristensen, Ostergaard,

2002). It was also possible to include sectors of special interest in single markets, as it was in

case of Denmark.

For majority of companies in each country, about 250 of their customers responded to the

telephone survey. As a result, almost 55 000 interviews were held in 1999. The ten point scale

was used in the survey however results were afterwards adjusted to ACSI 1-100 points scale

to enable comparisons between ACSI and ECSI index.

Figure 3.4. The European Customer Satisfaction Index (ECSI) Model

Source: Juhl, Kristensen, Ostergaard, 2002

Image

Expectations

Perceived quality of

„hard ware”

Perceived value

Customer satisfaction

Customer loyalty

Perceived quality of

„human ware”

41

As discussed previously, ECSI methodology was based on ACSI model. As in case of SCSB

and ACSI models, partial least squares methodology is used for estimation of the model.

Furthermore, as in case of ACSI, all variables are latent ones operationalized by few

measurement variables – specifically by two to six variables (indicators), which are translated

into specific questions asked during the survey.

With regard to ECSI model structure, ACSI was an exemplar for ECSI construction, however

the latter one is different due to three constructs:

1. within ECSI model, image variable was included, which is expected to influence

perceived value, satisfaction and customer loyalty variables

2. perceived quality was divided into separate variables;

a product quality – so called “hard ware quality” – which describes performance

of the product/service attributes

a service quality – so called “human ware quality” – the quality of service

delivered to the customer (Juhl, Kristensen, Ostergaard, 2002)

3. Customer complaint variable was excluded from the ECSI model as compared to

ACSI index.

There are also differences compared to ACSI model with regard to variables measuring

loyalty construct, which is the ultimate variable explained by the model. Within ECSI model,

loyalty is measured by following questions:

(1) the product repurchase likelihood,

(2) the probability of buying another product from the same company,

(3) intention to switch to competitor – price tolerance

(4) intention to recommend the offering to other consumers (Gronholdt, Kristensen,

Martensen, 2000).

The difference in loyalty variable compared to ACSI lies in second and fourth question.

Within ACSI first question was the same as in ECSI, however the other two questions in

ACSI regarded price tolerance, while in ECSI only third question is dedicated to price

tolerance. The remaining ones in ECSI examine the probability of purchase extension to other

offerings within the same company, probability of positive word of mouth and probability of

product repurchase.

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Among results of ECSI pilot study from 1999 several key conclusions were drawn, from

which there is one applicable to Polish economy and business environment in which

Company X is operating. The analysis of results for Denmark revealed that the link between

satisfaction and loyalty is stronger in competitive industries. In other words, the positive

effect of customer satisfaction on loyalty increases with the degree of competition in the

market (Gronholdt, Kristensen, Martensen, 2000). This conclusion is extremely crucial for

Company X, which operates in highly competitive automotive industry. Based on this finding,

it is important, that Company X tries to increase customer satisfaction as such increases shall

be strongly reflected in growing customer loyalty. In general, increasing loyalty has

measurable, positive effects for business performance. Specifically, there are few key results

of increasing customer loyalty for company results:

1. Increasing revenues due to customer retention and repeated purchases

2. Costs decline, as there is no need to acquire new customers, because the current

ones stay with the company, so the costs connected with new customers

acquisition decrease

3. Employee retention increases as a result of job pride and job satisfaction. As the

relationship with customers and familiarity of their needs is sustained customers

are served better and therefore their satisfaction and retention increases. Increase

productivity results from increasing employee tenure (Hopton, Markey, Reichheld,

2000)

As the increased loyalty has such strong influence on business performance, and satisfaction

influence on loyalty is stronger in competitive industries, therefore it is of utmost importance

for Company X in Poland to make customer satisfaction its priority goal.

The Customer Satisfaction Indexes described so far in this chapter – SCSB, ACSI and ECSI

are the most important indexes developed so far and used for measuring customer satisfaction

and customer loyalty. They are universal methodologies and can be applied to various

industries, sectors and on various markets. As a result they allow for comparisons of results

and benchmarking between companies, industries and results.

However, specific industries often tailor satisfaction measurement studies to the specifics of

the concrete industry or even company.

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3.3.4. Automotive industry specific customer satisfaction indexes

Within automotive industry, which lies at the heart of this paper, J.D. Power and Associates is

the most important and most referred to marketing information organization, which measures

the customer satisfaction in the automotive industry.

J.D. Power is an independent and unbiased source of customer satisfaction, product quality

and buyer behaviour researches. As it is global company, it measures customer satisfaction

with brands in many countries what enables companies to compare results on local and

regional level.

J.D. Power provides following syndicated reports, which deliver information for automotive

industry and which are widely used within automotive companies:

1. Initial Quality Study (IQS)

2. Sales Satisfaction Index (SSI)

3. Customer Satisfaction Index (CSI)

4. Automotive Performance, Execution and Layout (APEAL)

5. Vehicle Dependability Index (VDI)

Initial Quality Study

Initial Quality Study (IQS) is a research, which is supposed to evaluate the automotive quality

after three months of usage. During the study respondents are asked to asses the quality of the

car with regard to:

design – problems with design include car components or features, which may be

working right, however they may be perceived as difficult to use or understand

defects / malfunctions – this kind of problems include complete breakdown of any

component or car feature.

In the course of the study 217 car attributes are evaluated with regards to its functionality and

reliability. As a result, the study reports number of defects and malfunctions per 100 cars at

the level of whole brand, but also at the model level.

IQS study is conducted annually and has been is use for the past twenty years – since 1987. It

serves as benchmark for evaluating new vehicles quality.

44

In the latest, 2007 release of the study, 97 000 purchasers and lessees of new car models

launched in 2007 were surveyed ninety days after the purchase. Within this study, Company

X scored enormous improvement as a total brand with regard to quality of the vehicles. In the

ranking of the brands with lowest rate of faults, it advanced by more than 10 positions.

Moreover, such substantial increase was driven by all models and such results have been

described by Neal Oddes, director of product research and analysis at J.D. Power and

Associates as Company X commitment to quality (http://www.jdpower.com ). Company X as

a whole brand received the highest quality ratings with regard to: body and interior quality –

mechanical, overall quality – mechanical and power train quality – design.

Sales Satisfaction Index

Another important J.D Power study, widely used within automotive industry, is Sales

Satisfaction Index (SSI). It has also been in use for the past twenty years.

As opposite to IQS, which measures automotive quality itself – therefore referring to ECSI it

measures “human ware quality”, SSI evaluates the customer satisfaction with dealers and

vehicles, therefore so called “hard ware quality” as defined in ECSI. In more detail, it covers

the area of sales moment – therefore this is an evaluation of customers’ first experience with

the company. Specifically, it evaluates customer satisfaction in five dimensions: dealership

facility, salesperson, paperwork/finance process, delivery process and vehicle price

(http://www.jdpower.com). This implies that SSI results in evaluation of “human ware

quality” to larger extent than “hard ware quality”. The 2007 results of SSI study are not

available however in 2006 Company X was positioned in top ten in ranking of automotive

brands, whose customers are most satisfied with the car purchase process. Company X scored

much above the average for the industry, which in 2006 amounted to 847 points

(http://www.jdpower.com ).

APPEAL

Automotive Performance, Execution and Layout Study (APEAL) is the latest study offered by

J.D. Power, as it is in use only since 1996. This is also the only study, which measures the

emotional side of car ownership – it examines what customers feel about their cars. The study

was designed to complement the IQS study, which concentrates on the quality, while

APPEAL on the owners delight with car design, content, layout and performance.

http://www.jdpower.com



45

The respondent in the study are car owners, who have been using their car for only 90 days.

During the research, respondents are supposed to evaluate their cars on more than 100

attributes, which cover eight categories of vehicle performance and design:

engine/transmission; ride, handling and braking; comfort/convenience; seats;

cockpit/instrument panel; heating, ventilation and cooling; sound system; and styling/exterior.

The 2007 survey was based on responses from more than 91 000 car purchases and lessees of

new 2007 model-year cars and trucks, who purchased their vehicles ninety days earlier.

The results of the APEAL study were extremely satisfactory to Company X brand. The brand

received highest scores in four out of five measured areas. Such result can be translated into

high profitability of the brand, as based on the results from the 2007 study results,

manufacturers and dealers of models with higher APEAL scores can offer lower incentives to

new-buyers (http://www.jdpower.com).

Vehicle Dependability Index

One more study offered by J.D. Power and Associates is the Vehicle Dependability Index

(VDI). The study is designed to evaluate the long-term experience with a vehicle, as it

measures the quality after three years of car ownership. The study covers such areas as

durability of specific items, frequency of warranty work, ratings of the work performed and

the amount spent on non-routine repairs during the past year (Johnson, Herrmann, Huber,

Gustafsson, 1997). Therefore the index is a solid insight for the consumers of the model’s

reliability and dependability within the warranty period.

Customer Satisfaction Index

Finally, J.D. Power could not lack customer satisfaction index in its portfolio - it is called

Customer Satisfaction Index (CSI). As all indexes described in previous chapters, the J.D.

Power CSI index is supposed to measure the level of customer satisfaction with the car usage

during the first three years of the automotive use.

The CSI index is composed of variables, while each of them is measured by few questions.

Based on results released for German market in 2005, the four variables explaining customer

satisfaction are:

quality and reliability of vehicle - covers problems with vehicle,

vehicle appeal – means satisfaction with the vehicle’s performance, design,


46

function and styling

service satisfaction – is understood as customer satisfaction with dealership and

service

ownership costs – cover costs of car use, insurance and repairs

J.D. Power vehicle quality and satisfaction measurement studies are used widely among

automotive industry organizations. They enable to evaluate satisfaction levels and benchmark

them against competitors. Moreover, J.D. Power methodologies, as external ones, are

objective in measuring and evaluating satisfaction levels. Therefore they are good indicator of

direction, into which automotive firm is heading in terms of vehicle quality, performance,

brand image and sales services, which are prerequisites for customer satisfaction, which in

turn impacts organizations financial results.

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4. COMPANY X CUSTOMER’S PROFILE

Nowadays, majority of companies are conducting mainly qualitative research which measures

customer’s values, needs and beliefs. Such qualitative methods are also used to measure

consumer demographics.

Company X in Poland conducts an annual research with the external agency, which supplies

the company with following information:

1. consumer demographics and interests

2. benefits driving the car purchase

3. reasons for vehicle purchase and attitudes towards the car

The research is conducted on yearly basis since 2002 by the same research agency, what

allows for results comparisons and trends observations. The study, which results will be cited

in the next chapters, was conducted in autumn 2006. The research uses mail questionnaires as

a data collection methodology. In last year wave there were 326 respondents, who returned

the filled questionnaire. Within this chapter, we will present analysis of the results of 2006

wave, which will describe the demographic profile, but also personal needs and values of

Company X car owners.

4.1. Company X customers – demographics

In general, the analysis of demographics from the 2006 survey allows for customer

segmentation into groups, which are homogenous inside, while they differ between the

groups:

Compact cars – users of smallest cars and at the same time the most affordable

among all Company X models belong to this group,

Mid size cars – cars within this segment are larger and more comfortable than

compact cars, and at the same time more expensive as well as more luxurious.

Full size and large cars – these are definitely the most expensive cars, largest ones

and most prestigious and luxurious ones.

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Each of the segments can be described by seven dimensions: gender, age, size of household,

occupation, income of the owner, previous experience with Company X cars, interests and

hobby.

Starting with gender, among Company X car owners, 75% of clients is male. Across the

segments, there is correlation visible between gender and car size – the larger the car, the

larger percentage of men owners versus women. Therefore, largest percentage of women

owners is in the compact cars segment, where 32% of the car owners are women versus 25%

for the total brand. Contrary, in full size cars segment, 89% of car owners are men. Such

results are very natural – the smaller the car, the more appealing to women. As a result

compact cars are most often in the possession of women, while only few of them (11% of

total population of full size cars owners) own models from full size segment.

As Company X cars are premium ones, they are sold at correspondingly high prices and

therefore younger consumers in majority can not afford them. This is reflected in the age

structure of Company X owners – 78% of respondents are in the age of 29 to 58 years.

Another conclusion applicable in the analysis of age structure of respondents is that the

smaller the car and therefore more affordable, the youngest and the oldest consumers are

driving it. Within the owners of compact cars, there is largest percentage of youngest (below

29 years old) and oldest respondents (above 59 years old) as compared to other segments –

7% and 16% respectively. Such observation is related not only to the fact that disposable

income of youngest and oldest consumers is relatively lower than of mid age consumers, but

also to the fact, that compact cars are proper size cars at youngest and oldest stage of life, as

respondents at this stage of life usually don’t have the children yet or already don’t have

children dependent on them.

The Company X car owners most often have four members in the family (over 50% of

respondents). However, within compact cars segment, 2-persons families are statistically

more often. This finding is in line with the analysis of age structure – the youngest and oldest

customers are most often driving compact cars, as they are of comfortable size for their two-

person household.

The largest group among Company X customers are managers - entrepreneurs (private

companies’ owners), managers, directors and business owners – 45% of respondents. Second

49

largest group is intellectuals (doctors, lawyers, scientists) – 22% of respondents belonged to

this group. There were significant differences visible among segments; among compact cars

owners, intellectuals were much more visible than in mid size and full size car owners. On the

other hand, managers are largest group among owners of full size cars as compared to other

segments. Such relation has its background in the income – as the managers are on average

most affluent group, they are most likely to purchase full size car as opposite to less affluent

intellectuals.

The size of the car is reflected in its price, therefore the larger the car, the higher the price and

as a result higher income of the owners. Such relation was observed in the analysis of income

among Company X car owners. Respondents, who are driving compact cars, have on average

lower income than mid size car owners and much lower than full size car drivers.

Company X customers are split in half in terms of previous experience with the brand – 51%

of respondents confirmed, that they have had a Company X car before the current one. On

average more often men and persons working on managerial positions are within this group.

Among customers, who had Company X car before, 30% had one car before, while remaining

70% had more than one Company X car before the current one.

There were significant differences visible between customer segments with regard to previous

experience with the brand. For compact cars owners, statistically more often current car is a

first Company X car – this is valid for 62% of compact car respondents, who claim that

compact car is their first one. This is opposite to full size cars owners, where for only 22% of

respondents this is first Company X vehicle. Moreover, among full size cars owners, 77% of

them have had more than two cars of this brand previously. Among those compact car

owners, who had Company X before, only 51% had more than one such car before the current

one.

With regards to interests and hobbies, in general Company X customers are most interested

with movies (56% of respondents), house and garden (56%), winter sports (40%), travelling

(36%) and music (35%). It is important to note, that during the past four years (2002 – 2006),

increasing interest with tennis was noted, while fewer respondents claimed, that they are

interested in cooking. This observation is in line with the changes within culture and style of

living in Poland and with increasing purchasing power of Polish consumers.

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With regards to differences between models owned and interests, the higher the car model, the

more expensive the hobby. Compact car users statistically more often claimed that they are

interested in cooking, house and garden, while they claimed lower interest in winter sports

and golf. On the opposite side, full size car owners responded, that they are most interested in

travelling, tennis, water sports and golf.

Such differences are related to financial and social status – travelling or water sports

definitely require more investments that interest in cooking, house or garden. On the other

hand, sports such as tennis or golf are regarded as sports for people from upper classes of

society, those with higher income and such hobbies are regarded as prestigious ones.

Therefore full size car owners will more often declare interest in golf or tennis, than in

cooking, house and garden.

Summing up the analysis of demographic characteristics of Company X car owners, the main

conclusions from analysis are:

Company X cars are more appealing to men, as every 3 out of 4 respondents is

men. Female respondents are most often driving the smallest models of Company X –

compact cars. This implies that if Company X wants to target women, it shall

concentrate on offering smaller cars, while the larger cars shall be offered rather to

male customers.

As Company X cars are premium ones, therefore they are affordable at maturity

stage of life, when disposable income is relatively larger – 78% of respondents are

in the age of 29 to 58 years. Therefore marketing efforts such as communication,

marketing campaigns shall be focused on places, media channels, which are most

often used by respondents in such age. However, if there is desire to attract younger

customers, than smaller models shall be offered to them, as these are the ones that this

target group can afford.

As Company X cars are premium cars, customers most often purchase compact

car as their first car of this brand – 62% of compact cars owners declare, that

this is their first vehicle of Company X, while only 22% of full size cars owners

confirm this statement. This implies that to gain new customers, compact cars will

be the best incentive. Furthermore, to overcome high price barrier, promotional tools

shall be used with the offer of smallest cars, as they shall be most effective in case of

new customers. On the contrary, clients who decide to purchase larger models as their

first Company X car are affluent enough and as a result price incentives will rather not

51

be effective tool to attract their attention.

Company X shall target mainly managers and intellectuals with its offerings –

67% of respondents belong to those two occupation groups. It shall be noted

however, that offerings which will meet intellectuals’ needs are those placed in the

compact car segment, as they are the affordable ones for this group. Contrary,

managers shall rather be targeted with mid-size and full size cars, as these are the ones

affordable by this group, but also the ones, which are more prestigious to drive.

As owners of Company X cars are mainly in their mature life stage, most often

four persons live in their household – two adults and two children. This implies,

that Company X shall offer solutions friendly to families – comfortable sizes of

trunks, foldable back seats to fit more luggage if necessary.

With regard to income of respondents, compact car owners are on average less

affluent than respondents, who drive mid size and full size cars. Therefore

offerings for compact cars customers shall deliver more value for money, as these

customers will be more price sensitive than owners of mid size of full size models.

The analysis of Company X customers’ demographics showed also, that there is justification

for segmentation of respondents into three groups – compact cars, mid size cars and full size

cars, as respondents within these groups are homogenous. The differences between

respondents within each group and the average for total Company X are as below:

The average Company X client is male (75% of respondents) in the middle age –

from 28 to 58 years old. Every second respondent lives in a four persons households

(50% of customers). Almost half of Company X clients are managers, while almost

20% of them represent intellectuals’ group. Company X customers most often agree

that their hobbies are movies, house and garden, winter sports, travelling and music.

Compact cars owners – in general, this group differs a lot from mid and full size

car owners. Compact car drivers are mainly youngest or oldest customers (below 29

years old or above 59 years old). Majority of this group belongs to intellectuals,

pensioners and students. Within this group, two person households are much more

often present than in other groups. Compact car drivers have also the lowest income

compared to other groups – as they are either youngest or oldest persons, therefore

least affluent. Statistically, women more often drive and own compact cars than other

52

models. Respondents within this group have only started their adventure with

Company X brand – within compact cars owners there is largest percentage of

customers who declare, that this is their first Company X car. In terms of interest and

hobbies, respondents within this group declared more often than customers within

other groups that their hobbies are those least demanding in terms of financial input –

cooking, house and garden.

The profile of mid size car owners is most similar to average demographic profile

of Company X customer. 80% of customers within this group are men. They are in

their maturity stage of life, being between 39 to 58 years old (64% of respondents).

Their households are of traditional size – three of four persons. Almost half of the

customers in the mid size car segment are managers (45%) followed by intellectuals.

Their income is on the level of average income observed for Company X customers.

For 50% of customers within this group current Company X car is not the first one –

they have had a car of such brand previously. In terms of interests, customers within

this group statistically more often claim interest in pop music, tennis and soccer.

The owners of full size models differ a lot compared to compact car drivers, but

there are similarities to mid size cars owners. The owners of full size Company X

cars are in almost 90% men. As in case of mid size car owners, they are most often in

the age of 39 to 58 years old – within this group there is lowest percentage of youngest

(below 29 years old) and oldest (above 59 years old) respondents. They are well

settled in life – in majority they work as managers and their income is the highest

among Company X customers. Customers within this group have larger families –

most often four persons within the household. Furthermore, as they are the wealthiest

group, they have largest experience with the Company X cars – 78% of customers

from this group have had Company X car before. Customers within this group

statistically more often declare, that they have either expensive or prestigious hobbies

and interests – they are more often than other customers interested in travelling,

tennis, water sports and golf.

The differences between three core groups of Company X customers deliver important

knowledge to the management, which enables to target each customer segment with such

offer, that it is adjusted to each customer profile and by doing so maximize the probability of

satisfying the customer. The analysis of factors, which drive the decision of car purchase,

53

shall deliver more detail knowledge of customer needs and values, which shall further

enhance the knowledge of differences between customer segments.

4.2. Company X customers – benefits driving the car purchase

During the annual customer research, not only customer profile is measured, but also

Company X customers are questioned to point out three most important benefits, as well as

factors, which are crucial in their car purchase decision making process.

Respondents are asked to choose three most important benefits from the list of fourteen,

which are the most important for them when deciding about the car purchase. The benefits

and factors used in the survey are:

1. Safety of the vehicle

2. Comfort of the vehicle and delight from driving

3. The technological advancement of the car

4. The brand image

5. The unique design of the car

6. Previous experience with the brand

7. High expected return if car is sold after few years

8. Functionality and economy of the car

9. Prestige due to car ownership

10. Recommendation from a friend regarding the car

11. Promotion or advertising influence

12. The environment friendliness of the car

13. After sales services

14. Other reasons

The results of 2006 survey revealed, that in general there are four benefits, which where

chosen most often as the crucial ones for Company X customers:

safety of the car – 59% of respondents pointed this factor as one of most

important, when purchasing the car

comfort of the vehicle and delight from driving – 56% of those asked pointed

this benefit as very important

54

technological advancement of the vehicle – 28% of respondents believe, that this

benefit is crucial factor, when purchasing the car

brand image – this benefit was chosen by 27% of Company X customers

On the other hand, the least important factors for Company X customers, which are able to

influence the decision about car purchase, were:

after sales service – only 1% of respondents believes, that this is important factor,

which is taken into account while making decision about car purchase

the environment friendliness of the car – was also chosen by only 1% of

customers

promotion or advertising – this factor was taken into account by only 2% of

Company X car owners, when making the decision about the brand they want to

drive

These results have crucial implications and are important advices for Company X managers.

First of all, based on the survey, safety of the car, comfort and delight from driving are the

key benefits that Company X cars shall deliver to their owners. These are also the key car

features, which if performed on high level, are able to attract future consumers and retain

current clientele. Furthermore, these features shall be claimed in any promotional materials

and advertising, as their importance is so high to Company X clients.

Secondly, if Company X has any issues with quality, which leads to lower safety, less comfort

or lack of technological advancements, than it can expect declining number of customers

attracted or the customer exit to happen, as the most important benefits will not be delivered

to the customers.

Finally, as promotion and advertising factors are least important for Company X customers,

those tools shall not communicate promotional activities – attractive pricing or discounts. The

advertising shall rather be used for image building, as image is one of the most important

factors for Company X clientele. Therefore, instead of communication of promotional

incentives in media, advertising shall communicate brand benefits and in this manner enhance

the brand image further as the factor taken into account by 27% of respondents during car

purchase decision making process.

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The 2006 study revealed the differences between various models owners – other benefits were

pointed out as the most important by different model owners. As a result, three customer

segments divided based on demographic characteristics may be described by other benefits,

which are on average more important for them during decision-making process.

Compact car owners pointed out more often than other models owners to safety of the

vehicle, brand image and functionality and economy of the car as benefits important to

them during the car purchase decision process.

The larger sensitivity to those factors is related to demographic profile of compact cars

customer segment:

1. Functionality and economy of the car; as discussed before, compact car owners are

the group with smallest disposable income. Therefore functionality and economy of

the car is on average more important to them than to any other customer segment, as

their funds are more limited than funds of other Company X customers.

2. Safety; Company X cars score five stars in the Euro NCAP safety ranking and are

perceived as safest cars. Safety benefit does differentiate Company X from other

brands and has been pointed out by 59% of Company X customers as very important.

However, safety benefit was chosen more often by compact car owners, than mid size

and full size car drivers. Such difference is also related to demographics. Compact car

owners are the youngest and the oldest customers of Company X and very often

compact car is their first Company X car. While comparing the options on the market,

they are searching for safe vehicles and if a car is described as very safe, this feature

may be decisive for them to choose this particular brand. Therefore Company X cars

are more appealing to them than any other brand, as they are perceived as the safest.

For mid size or full size cars owners’ safety is more of a granted benefit, as they most

often have been driving Company X before. Furthermore, as they are more wealthy

customers and they are driving more expensive cars than compact ones, they are

searching for other benefits than just safety, which is important, but basic one for

them. For the same reason safety is more important for compact car users – as they

have the smallest income, they can afford smallest Company X cars and those

delivering basic benefits, such as safety. On the other hand, those basic benefits are

the ones that compact cars owners are searching for – safety, but also reliability and

economy of the vehicle.

3. Image; this benefit is more important to compact size owners than other segments for

56

several reasons. First of all, compact car customers are the youngest and the oldest

groups and very often they did not have previous experience with Company X.

Therefore, image benefit acts as strong differentiating feature, which makes Company

X car more attractive than other brands. Than, as this may be the customer first

Company X car, the desire to drive a high image, admired brand car is larger than for

customers, who are driving Company X for longer time. For such clients, the desire to

drive high image brand has been fulfilled before and therefore is not perceived as

important now. Contrary, for compact cars owners, image benefit may be very

important, as this may be their first premium brand car.

To summarize, customers within compact cars segment perceive safety, functionality and

economy of the vehicle, as well as image of the brand as more important factors than mid size

and full size cars segments. The skewness towards such benefits is partly related to

demographics of the compact car owners; 1) lower income of compact car owners, therefore

more focus on basic benefits such as safety, reliability and economy, 2) as the compact cars

owners are the youngest or oldest customers, it is very often their first Company X car. As a

result safety and image of the car, which strongly differentiates Company X from other

brands, push this group towards purchase of Company X, 3) as this may be their first

Company X car, the desire to drive high image car may be stronger than for mid and full size

car owners, for which this is next Company X model and they are used to such high image

cars.

Based on the benefits, which are on average more important for compact car owners, this

customer segment can be described as functional segment.

Mid size cars owners on average pointed more often to comfort and pleasure of driving than

other customer segments. At the same time, functionality and economy of the vehicle was

chosen very seldom by this customer segment. Such discrepancies are also related to

demographic characteristics of this customer segment.

Customers within this group have higher income than compact car users and are better settled

in life. They are also more often managers, therefore handling high positions within the

company, which are associated with higher standard of life. As a result, mid size car owners

can choose vehicles, which offer comfort, delight of drive and some portion of image to the

users. Those customers take functionality of the vehicle for granted and do not put so much

57

attention into economy of the vehicle, as they can afford higher expenses. They are searching

for pleasure, comfort and delight when driving. As a result, mid size car segment can be

called pleasure segment, as customers within this group value the delight higher than the

functionality.

The benefits which were on average more often chosen as the most important ones by full size

cars owners were pleasure and comfort of driving, previous experience with the brand and

prestige of car ownership.

The full size car owners are most affluent customers of Company X. Therefore pleasure and

excitement of driving is very important for them and this is why they choose the largest, most

expensive and most luxurious models. Furthermore, prestige is important for this group, as

these customers are mainly managers, well settled and affluent, therefore they need to be

surrounded by prestigious products - with cars between them. Lastly, the current model is not

their first Company X car. Those customers have experience with other Company X cars and

as a result it influences their decisions about the car purchase.

The full size car owners may be called as prestige segment due to benefits, which were

pointed by them on average more often than by other customers.

The analysis of key benefits, which are most important for Company X customers during the

decision about car purchase, revealed that Company X customers can not only be segmented

due to demographic characteristics, but also based on key benefits which they are searching

for.

Company X clientele can be segmented into three distinct groups:

1. compact car owners – so called functional segment. Customers within this group

are more often than other customers searching for cars, which are safe, functional and

economical and have high image.

2. mid size car owners – so called pleasure segment. Such customers focus more often

on pleasure and comfort of driving than customers within remaining segments.

3. full size and large car owners – so called prestige segment. Clients within this

segment are those most experienced with Company X and those searching for pleasure

of car driving and prestige of car ownership

The knowledge of key benefits, which are important for particular customer segments,

enables the company to target each customer group with different car attributes which will

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respond to different benefits. Such knowledge is of inestimable value in creating offerings

tailored to customer needs, what in turn drives higher satisfaction and loyalty.

4.3. Company X customers – attitudes to vehicle

During the survey, not only demographic characteristics of consumers and benefits driving

car purchase were examined, but also general attitude to vehicle. Respondents were asked to

agree or disagree with twelve statements describing their attitude to cars. The statements were

ranging from “My car shall express my personality” to “I take care of my car myself”. The

respondents were supposed to evaluate whether they agree with the statement (4) or disagree

(1) or they have no opinion.

In general, the statements, with which customers agreed to largest extent, corresponded with

most important benefits taken into account during the car purchase process.

Respondents to largest extent agreed with following statements:

“The vehicle shall guarantee maximum safety” – 97% of respondents agreed

completely with this statement. This is in line with safety benefit, which was pointed

out by largest percentage of respondents as important benefit taken into account

during purchase decisions.

“I would like to have a feeling, that all latest technical advancements were used in

the car” – 94% of those questioned agreed with this statement. This is in line with the

technological advancements benefit, which was chosen 28% of Company X customers

are key while making car purchase decision.

“I like the vehicles with unique design” and “The car gives me feeling of freedom

and independence” – 92% of respondents agreed with both statements completely.

This statement corresponds with two benefits; comfort and pleasure of driving, which

was chosen by 56% of respondents as important for them and unique design, which is

perceived as important factor during car purchase process by 27% of Company X

customers.

There were some differences between customers’ demographics and their attitude to vehicle.

In general, women are searching for cars, who give them sense of freedom and independence,

which have unique design and which express their personality.

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When it comes to age groups, youngest consumers (up to 39 years old) enjoy dynamic driving

more than any other group. On the opposite side are customers above 49 years old, who more

often treat their car as locomotion only.

With regards to differences between various customer segments, they were no strong

differences. The only exception is the full size segment (prestige segment). Customers within

this segment believe that the car shall reflect their social status and that it shall attract others

attention. This is in line with the list of key benefits which are important for this customer

group. As discussed before, customers from this segment are on average more often taking

into account the prestige of the car ownership when they are making their purchase decisions.

As customers within this group are most affluent ones and are most often on high managerial

positions, naturally they will be searching for cars, which are prestigious because they believe

that the car shall reflect their social status.

4.4. Summary of Company X customer’s profile

To summarize the customer profile research study results from 2006, the analysis revealed,

that Company X customers can be divided into three major groups. Customers within those

groups are alike taking into account their demographic profile, their needs and attitudes

towards vehicle. Moreover, those groups are similar in terms of car models that they choose.

Contrary, the groups differ significantly between them.

The characteristics of average Company X customer and specifics of the three customer

segments are:

1. Company X customers in majority are men (75% of respondents) in the middle age –

from 28 to 58 years old. 50% of respondent lives in a four persons households. In

terms of occupations, almost half of Company X clients are managers, while almost

20% of them represent intellectuals’ group. Company X customers are most often

interested in movies, house and garden, winter sports, travelling and music. The most

often cited benefits or factors, which are important for Company X customers during

car purchase are safety of the car, comfort of the vehicle and delight from driving and

technological advancement of the vehicle and brand image.

2. Compact cars owners – functional segment. Among this segment, there is larger

percentage of youngest and oldest customers (below 29 years old or above 59 years

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old) than in remaining segments. Women are also driving compact cars than other

models. Majority of this group belongs to intellectuals, pensioners and students and

live in two person households more than customers from remaining segments.

Compact car drivers have the lowest income compared to other groups and within this

segment there is largest percentage of customers who declare, that this is their first

Company X car. In terms of interest and hobbies, respondents within this group

declared more often than customers within other groups that their hobbies are those

least demanding in terms of financial input – cooking, house and garden. Customers

within this group are more often than other customers searching for cars, which are

safe, functional and economical and have high image.

3. Mid size cars owners – pleasure segment. 80% of customers within this group are

men in the age between 39 to 58 years old (64% of respondents). They have

households with three or four persons. Almost half of the customers in the mid size car

segment are managers (45%) followed by intellectuals. Their income is on the level of

average income observed for Company X customers. 50% of customers within this

group have had a Company X car previously. In terms of interests, customers within

this group statistically more often claim interest in pop music, tennis and soccer. Mid

size car owners focus more often on pleasure and comfort of driving than customers

within remaining segments.

4. Full size and large cars owners – prestige segment. Customers within this segment

are almost only men (90%), in the age of 39 to 58 years old – within this group there is

lowest percentage of youngest (below 29 years old) and oldest (above 59 years old)

respondents. Full size car owners are in majority managers and their income is the

highest among Company X customers. They also have larger families than average

Company X customer – four persons within the household. Car owners within this

group have largest experience with the Company X cars – 78% of them have had

Company X car before. Customers within this group statistically more often than other

segments declare, that they are interested in travelling, tennis, water sports and golf.

They are also those most experienced owners of Company X and are searching for

pleasure of car driving and prestige of car ownership. Furthermore, they more often

than other customers believe that the car shall reflect their social status and that it shall

attract others attention.

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5. STRUCTURAL EQUATION MODELING AND PARTIAL LEAST SQUARES

Partial Least Squares approach is one of the data analysis techniques that is applied to

similar problems as Structural Equation Modeling. PLS has been mainly developed by

Herman Wold (Wold, 1985), Jan-Bernd Lohmöller (1984, 1989) and by Wynne W. Chin

(1998, 1999, 2001). Some researchers claim that PLS is not one of the SEM methods due

to different estimation procedures and objectives of the methods as well as different

strengths and weaknesses of both techniques. On the other hand beside many differences

both methods can be grouped under one set of techniques used to analyze similar

problems with conceptually continuous latent constructs.

5.1. Structural Equation Modeling – covariance-based approach

Many researchers identify SEM mainly with covariance-based approaches represented by

such computer software programs as for example LISREL. This kind of approach is an

evaluation of sample covariance or correlation matrix consistence with a theoretical model

specified by the researcher. Therefore it concentrates on maximizing fit between sample

correlations matrix and parameter estimates meaning that the estimating procedure

changes the estimates to improve the fit function until no improvement is possible. The

covariance-based techniques optimize parameters by maximizing fit but not variance

explained. Therefore estimated models can have very good fit to sample data set which is

crucial to interpretation however with low explanatory power. One of important

limitations of this methodology is the assumption that the observations are independent

and all indicators follow normal distribution which in most customer satisfaction studies is

not fulfilled due to strong negative skewness of satisfaction scores. Furthermore SEM

does not allow to predict value of latent variables specified in the structure of the model.

This property is of high importance especially in customer satisfaction researches where

calculation of latent scores is essential to further interpretation of the subject.

To sum up covariance-based approaches are very demanding if it comes to distribution of

the sample data set plus they concentrate on explaining covariation of all used indicators

to prove the theory lying behind the research while not allowing for calculation of latent

variable scores. Therefore if created structure of the model is proper in terms of explaining

covariation structure of all manifest variables the SEM techniques produce optimal

parameters. However there is certain amount of risk involved in the covariance-based

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technique as under conditions of small sample size or data set violating assumptions about

distribution incorrect solutions can result. Furthermore latent variable values are never

calculated at the same time eliminating the possibility to predict observed variables.

5.2. Partial Least Squares

On the other hand researchers can use PLS technique which is definitely less demanding

in terms of assumptions about data distribution, measurement scales and size of sample.

Parameter estimates are obtained by minimizing the variance of dependent variables

therefore producing the best fit of collected sample data set to defined model structure

proved by theory or research assumptions. PLS is aimed at obtaining determinate values

of all unobservable constructs that are approximated by their respective set of manifest

variables thus avoiding factor indeterminacy. Weighting scheme for each latent variable

depends on the kind of relationship assumed between the construct and its indicators. It

can be either reflective or formative while other SEM techniques allow only for reflective

mode – the modes will be explained further in this chapter. Therefore having all the above

mentioned arguments in hand the researchers can view PLS technique more suitable in

cases where properties of sample data do not meet assumptions of multivariate normal

distribution, where sample size is relatively small, where there is a certain amount of

uncertainty between theory and data creating need for theory confirmation or where

project requires calculation of scores for unobservable factors defined in the structure of

the model for predictive purposes.

5.2.1. Specification of the model

Before explaining PLS estimation technique some background on possible model

structures as well as names of constructs used in this technique is needed. Let’s consider

Figure 5.1. Circles named A and B represent latent (not observable) constructs.

Rectangles named ax, ay and bx, by represent manifest variables (observable indicators)

that form latent constructs A and B respectively. Arrow scheme represents inner relations

of the model (relationships between latent variables) and outer relations (relationships

between latent constructs and their respective indicators). Figure 5.1 represents one inner

relation of A influencing B and two sets of outer relations – reflective mode of connection

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between A and its respective manifest variables ax, ay and formative mode of connection

between B and its respective indicators bx, by.

In the reflective mode indicators measure the same unobservable phenomenon in a way

that if the level of the latent construct changes than all observable variables should also

change in the same direction. The strength of change is dependent on how strong is the

Figure 5.1. Structure of latent blocks model with formative and reflective modes

relationship between the indicator and the latent construct. The strength in the reflective

mode is represented by loading (the amount of variance in the indicator that the respective

latent phenomenon accounts for). Loadings of manifest variables on their latent construct

represent the correlation between them.

The question whether researcher should use reflective mode depends on several

considerations:

- theory behind the measurement model – if researcher conceptualizes latent construct

as a phenomenon influencing responses to the indicators scores the reflective mode

should be used

- objective of the study – reflective specification should be used if the objective of the

study is to explain and predict the observed variables (maximize variance of

indicators)

B

xa ya xb yb

A

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- empirical conditions – reflective mode assures stable estimates in situations where

either sample size is small or there is suspicion about multicollinearity among

indicators.

The weights in the reflective specification are calculated in order to create LV that

explains as much variance as possible in all its observed indicators.

In the formative mode indicators do not represent the same unobserved factor and they

are also not correlated to each other. The latter condition arises from the fact that in case

of significant correlation of formative indicators the problem of multicollinearity may

cause unstable estimates of multivariate regression of latent construct on its manifest

variables. Therefore formative variables provide some kind of conditions under which the

LV is being created. The aim of formative mode is to maximize the variance explained at

the LV level. Therefore all indicators are weighted with the aim to maximize correlations

in the inner structure of the model.

The decision as to whether researcher should use the formative specification depends on

the same 3 considerations as in reflective mode: knowledge on investigated theory,

purpose of the research and empirical conditions. If the sample size is large enough, the

indicators are not related to each other (no multicollinearity) and are conceptualized as the

ones that form the latent construct meaning that the change in the level of latent

phenomenon does not necessarily means changes in the same direction for all its

indicators the formative mode should be used. Furthermore if the aim of the researcher is

to maximize the variance explained in the latent abstracts level not the outer part of the

model and there is a substantive theory confirming formative relationships the choice of

formative specification is well-grounded.

5.2.2. Estimation

PLS estimation procedure consists of 3 stages. In the first stage each block of indicators

is assigned some weights to obtain latent variable estimates by performing iterations of

simple and/or multiple regressions (outside approximation). Then the proxies for each

latent construct are created based on its relations to other LVs (inside approximation).

With the proxy estimates the regressions specified by the structure of the model are

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performed in order to calculate new weights. For formative indicators the multivariate

regression with their latent construct is performed opposed to individual regressions for

reflective mode. The regressions’ estimates form a base for new weights to start another

outside approximation. The whole procedure stops when next iteration does not produce

better estimates according to applied stopping rule meaning that the percentage change in

all estimated weights is for example less than 0,001.

Therefore PLS iteratively performs estimation of latent variable scores in two ways. One

mode is an outside approximation which calculates LVs by weighting their respective

indicators. When researcher is operating on a set of observed measures representing

unobservable construct without additional information it is advised to start approximation

of LV by summation of its indicators. Next part of PLS estimation procedure is an inside

approximation that concentrates on calculating LV scores by combining LVs most closely

related to the LV in question. The inner weights can be calculated according to three

schemes: the centroid scheme, the path weighting scheme and the factor weighting

scheme. Assume that Ai and Aj are the estimated standardized latent variables

representing real latent constructs Ei and Ej in the outside approximation and wij are the

inner weights. The centroid scheme assumes that wij have the same signs as the correlation

coefficient between Ai and Aj. The factor weighting scheme calculates inner weights wij as

correlation coefficients between Ai and Aj. In the path weighting scheme the latent

constructs are divided into predecessors of Ej meaning latent variables explaining Ej and

successors of Ej , latent variables explained by Ej . For a predecessor Ei the inner weight

wij is the regression coefficient of Ai from the regression of Aj on all Ai’s influencing

predecessors of Ej. For a successor Ei the inner weight wij is equal to the correlation

coefficient of Ai and Aj.

To sum up the estimation procedure PLS operates and uses the information at both levels

to estimate the next possible score of LV while maximizing variance explained of all

dependent variables. PLS minimizes residual variance for a set of estimated parameters

given fixed estimates or proxies for other parameters being estimated. Therefore it is

partial in this sense that only part of the model is estimated in each iteration.

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Sample size requirements

One important advantage of PLS modeling is small to medium sample size required for

estimation. Taking a close look at all three stages of estimation procedure the

requirements for sample size appears to be obvious and clear. PLS consists of simple and

multiple regressions depending on the specification of latent constructs (formative vs.

reflective) and inner relations of the model. As it has been mentioned before PLS is a

partial procedure meaning that only part of the model is estimated at one time. Therefore

the requirement of sample size for overall model comes down to the requirement for the

sample size of the largest multiple regression. Therefore assuming that model consists of

formative and reflective indicators the researchers has to find the biggest of the two

possibilities:

a) the latent phenomenon with the largest number of formative indicators

b) the dependent latent construct with the largest number of independent other latent

variables influencing it.

Assuming well known rule for regression sample size requirements of ten cases for

predicted variable the researcher has to make sure that ten times a) or b) cases are

gathered (choosing greater value). If the model consists of only reflective indicators the

sample size requirement is then limited to condition b).

Standardization of manifest variables

Lohmöller designed METRIC parameter for standardization of variables. It has 4 variants

depending on 3 conditions put on the data:

Condition 1: Comparability of the manifest variables’ scales. For example Satisfaction

scores measured on the same scale 1-10 are comparable however height and weight are

not comparable.

Condition 2: Interpretability of the means of the manifest variables.

Condition 3: The variances of the manifest variables reflect their importance.

If variable scales are not comparable, meaning that condition 1 does not hold (METRIC 1)

than standardization of variables is necessary (mean=0 with variance = 1). Standardization

is also obligatory if scales are comparable but the other conditions do not hold (METRIC

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2). In this case after standardization for the estimation phase the manifest variables are

then rescaled to the original means and variances. If conditions number 1 and 2 hold but

not condition 3 (METRIC 3) than the variables have to be standardized to unit variance

but are not centered to the same mean equal to 0 for the estimation phase. After that the

variables are rescaled to their original variances. In the last case of METRIC all

conditions hold (METRIC 4). In this case the original values of variables are used in the

whole process of estimation.

5.2.3. Validation of model

In order to evaluate model estimated by PLS method researchers have to apply an

approach which is consistent with assumptions of PLS estimation such as no distributional

demands and prediction oriented specification. Therefore traditional parametric statistical

tests are not appropriate for PLS model validation. Traditional R-square, the Stone Geisser

test (Stone, 1974, Geiser, 1975) , average variance extracted measure (AVE) assesses

predictiveness while bootstrapping and jackknifing validate the stability of estimates.

R-square

The R-square can be used as a first indicator of predictive power of specified model. Its

interpretation is the same as in traditional regression. The indicator measures how much

variance of dependent variable is explained by its predictors. It is possible to calculate R

square for latent variables due to their determinacy during PLS estimation.

Stone Geisser Q2

The technique is a combination of function fitting and cross-validation. It assumes that

prediction of observed measures used in the estimation is of more importance than the

artificial constructs’ parameters estimation. The cornerstone of the methodology is the

blindfolding procedure that estimates parameters without part of the data for a particular

set of manifest variables and then uses estimated parameters for estimating the omitted

block. Such iteration is repeated until every data point has been withdrew and estimated.

Let’s consider a data set and assume that N and K are omission numbers for cases and

indicators respectively, and D is an omission distance. Wold (1982) suggests that D

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should be an integer between K and N. Blindfolding procedure takes out NxK data points

starting with first point and omitting every other D data point moving across all columns

and rows until the end of matrix. All missing values are then replaced using pairwise

deletion, mean replacement or procedure of imputation. The sum of squares for

prediction error E is calculated and the withdrawn data points are predicted. The sum of

squares errors based on the mean for prediction O is also calculated. The whole process is

being repeated by returning omitted data points to the matrix and moving to the next data

point - case 1 and indicator 2 – as a beginning of new round of withdrawal. During this

iterative procedure D sets of Es and Os are calculated. The Stone-Geisser measure is

defined as follows:

Q2 = 1 – (ΣDED) / (ΣDOD) (1)

Therefore Q2 represents a measure of how ell the specified model is able to reproduce the

observable variables. If Q2 > 0 than the model is predictive and opposite when Q2 < 0.

Jackknifing

Jackknifing is a procedure that allows researchers to evaluate stability of particular

statistic by measuring variability of data set used for calculations instead of using

parametric assumptions. The technique provides estimates as well as confidence intervals

for the estimates. Contrary to the blindfolding procedure it uses the algorithm of deleting

n cases while estimating parameters in each iteration. Finally it examines variation of all

obtained estimates. Detailed description of Jackknife procedure is for example described

in Chin W.W. (1998).

Bootstrapping

Bootstrapping is the more advanced methodology. It is also the nonparametric approach

that measures the stability of parameter estimates. Jackknifing is usually treated as an

approximation to bootstrapping which is in most cases more efficient. Bootstrapping is

aimed at obtaining N estimates for every parameter by creating N sample sets. By

sampling with replacement from the original data set the N samples are created. The

higher the number of resamples the more reasonable standard error estimates can be

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usually obtained. The default number of bootstrap runs is usually 100, (Tenehaus et. al.

2005) however, the t-values obtained with a bootstrap of 500 runs tend to be quite similar

each time the bootstrap is performed. Only rarely does the significance-level of an

estimate change in between different bootstrap runs with 500 iterations. The literature also

suggests choosing the bootstrap sample size equal to the number of cases in the dataset,

because the standard error estimates are dependent upon the number of observations in

each replication. Significance is determined against an ordinary t-statistic table, using the

number of bootstrap runs as the degrees of freedom (df=500). For a typical one-sided test,

the following t-values correspond to a given level of significance (df=500):

3.107 ~ p<0.001

2.334 ~ p<0.010

1.648 ~ p<0.050

1.283 ~ p<0.100

Generally the methodology is more time consuming than the jackknife procedure under

the assumption that the number of resamples for bootstrapping is greater.

Composite Reliability

Composite reliability is a measure of internal consistency applicable only to reflective

indicators which has been developed by Werts, Linn and Jöreskog (1974). It is similar in

interpretation to Cronbach’s alpha which is usually lower estimate of composite reliability

under the assumptions of parameter accuracy. The property is due to the fact that the

composite reliability does not assume all indicators to be equally weighted.

AVE –Average Variance Extracted

Fornell and Larcker (1981) developed another measure applicable only to reflective

specification called AVE. It represents the amount of variance that the latent construct in

question captures from its manifest, observable variables. It is advised that AVE is greater

than 50% meaning that the particular latent construct captures more than 50% of variance

of its indicators. It is also suggested that AVE of each LV should be greater than the

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square of correlations between LVs confirming that more variance is shared between

chosen LV and its respective manifest variables than with another latent phenomenon.

Cross-Loadings

Another measure for validating latent constructs and the structure of the model specified

by researcher is the test of cross-loadings. It is obtained by calculating correlation

coefficients between every set of indicators and every latent construct used in the model.

Each block of indicators is expected to load higher on its respective latent component. If

the condition is not met than the researcher should reconsider the structure of relationships

between the set of manifest variables and latent components.

Summary

To sum-up PLS avoids serious problems with data distribution and sample size

requirements which are crucial in covariance-based approaches. Furthermore its

determinate nature allowing for calculation of unobservable components gives PLS the

predictive sense and power and avoids parameter identification problems that may occur

for covariance-based approaches. Finally PLS does not limit specification of models only

to reflective mode allowing for formative specification where weights of indicators are

estimated in order to maximize prediction of particular LV. All the arguments and

advantages presented above prove PLS as the most suitable method for estimating

Customer Satisfaction models such as Brand Satisfaction Model designed for Company X

in Poland.

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6. MEASURING CUSTOMER SATISFACTION AT COMPANY X IN POLAND

Until the Brand Satisfaction Model based on PLS methodology has been introduced at

Company X in Poland as a complete measurement of customer satisfaction and loyalty

there have been two unified approaches to exploring satisfaction of its customers. First

one, Sales Service Quality CSI concentrates on measuring satisfaction with the sales

service quality while the second one – After Sales Service CSI - measures satisfaction

with after-sales service. These are two separate researches deeply investigating all aspects

connected with the two areas which are the main responsibility of sales companies in

different countries. While for example product quality is the sole responsibility of

headquarter, the sales and after-sales service constitute the core business of the company

locally. Therefore based on the Company X Global Board of Directors’ decision, the two

above mentioned studies have been approved as the main measures of sales companies

performance in particular markets. The methodology has been unified on every market

meaning that research questionnaire is the same in all countries. Thus each sales company

in every market is using sales service quality CSI and after-sales service quality CSI

researches. Both measures has become extremely important for the whole company and

became part of upper-level management bonus system in order to make sure that all

respective employees are devoted to achieve the best possible score in both areas.

Based on all the information written above it seems there has been no place for additional

research investigating customers satisfaction beyond sales and after-sales service.

Especially bearing in mind the fact that the CSI has been introduced as a global,

obligatory project. However the authors realized that although both existing measurement

methods are necessary and important for the organization, they do not allow for creating a

local and complete picture of Company X customers’ feelings about the brand with regard

to all the areas of their experience with the vehicle. Therefore the authors decided to

propose the Brand Satisfaction Model methodology to the Board of Directors in Poland as

the unique, complete measurement method for receiving comprehensive picture of

Company X customers’ needs, wants and satisfaction. The comprehensive picture means

not only investigating satisfaction in other areas of customer experience with vehicle such

as: product quality, image, ownership costs etc. but also measuring importance of

particular areas in generating satisfaction and loyalty. By introducing the new research

the company could gain knowledge of the strength of particular areas influence on

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satisfaction and loyalty and thus would be able to make better sales, marketing and PR

decisions.

To better understand the advantages of BSM over CSI researches used currently at

Company X, it is necessary to familiarize with assumptions and structure of both

methodologies.

6.1. Customer Satisfaction Index at Company X – Sales Service Quality

The main objective of the research is to deliver better knowledge about customers’

satisfaction with the process of purchase of the vehicle. Core aspects under investigation

are: purchase situation process, quality of sales personnel, timing of vehicle delivery,

vehicle reception by the customer and general satisfaction with the service provided by

the dealer. Over 2 000 questionnaires are being sent to the customers twice a year by mail.

The effective rate is around 20-30%. The study covers only those customers who bought

the vehicle not earlier than 3 months before the research is actually conducted and at the

same time not later than 4 years of vehicle usage. Structure consists of scaled, non-scaled

as well as sociodemographic questions. Description of purchasing process, choice factors,

willingness of next purchase and recommendation are the non-scaled parameters.

Sociodemographic part is standard as in every other study. The most important part of the

research is of course the one that measures satisfaction of customers with different

elements constituting every-day business for sales companies in different countries. In

case of CSI it is the section with scaled questions. It consists of inquires about:

- Satisfaction with overall dealer service

o Satisfaction with visit to the dealer

o Credibility of the dealer

o Honesty and reliability of the dealer

o Time spend during vehicle purchase

o Ability to agree on vehicle pick-up based on customer needs and schedule

- Showroom atmosphere

o Overall satisfaction with the showroom (design and atmosphere)

o Completeness of customers’ care (coffee, tea, resting sofas etc.)

o Availability of sales materials

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- Telephone contact

o Possibility of receiving trading information through the telephone

- Sales representative

o Easiness in dealing with purchase situations

o Honesty

o Clarity of information given to the customer

o Customers’ time respectfulness

o Knowledge about product offer

o Helpfulness in choosing the right vehicle

o Service provided between contract conclusion and vehicle delivery

o Frequency of salesman contact

o Behaviour of sales representative

o Explanation of vehicle or leasing price

o Credibility of salesman promises during purchase of the vehicle

o Helpfulness of salesman in dealing with formalities.

- Test drives

o Availability of test drives

- Timing of delivery and basic instruction

o Satisfaction with timing of delivery

o Explanation of warranty conditions

o Explanation of after-sales service conditions

o Information given on principles of vehicle usage

- Overall condition of the vehicle during receipt

o Cleanliness of interior

o Cleanliness of exterior

- After purchase contact

o Thankfulness expression after purchase

o Contact of salesman after purchase and receipt of the vehicle

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- Complaints handling

o Overall dealing with complaints

- Loyalty

o Willingness to recommend the dealer

o Willingness to purchase a vehicle at the same dealer

o Evaluation of the dealer comparing to other brands’ dealers

6.2. Customer Satisfaction Index at Company X – After - Sales Service Quality

The main purpose of the CSI-after-sales research is to measure performance of each after-

sales service point in Poland. It concentrates on such areas as customers’ first contact with

the reception and services advisor, quality of facility operation and infrastructure,

competence of service advisor, transparency of service provided, timing, general vehicle

reception process and overall quality of service provided. Over 2 000 questionnaires are

being sent to the customers twice a year by mail. The effective rate is around 15-25%. The

questionnaires are sent only to those customers who bought the vehicle not earlier than 3

months before the research and at the same time have not used the vehicle longer than 4

years. Below is the description of the areas under investigation:

- Booking in process

o Schedule service within reasonable time

o Effort to help you maintain normal schedule

o Amount of time spent waiting to speak to someone

- Facilities

o Convenience of opening days and hours

o Convenience of location

o Ease of parking

o Provision of comfortable waiting area

o Overall cleanliness of waiting area

o Amenities available

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- Service advisor

o Provision of advice with regard to service needs

o Courtesy and respectfulness of service staff against customers

o Honesty of service staff

o Display of knowledge and expertise

o Attentiveness to your inquiries

o Extent to which they clarified your needs

o Degree to which they understood problems with your car

o Extent to which they kept their promises

- Vehicles reception process

o Promptness in having car ready when promised

o Explanation of work performed on your car

o Explaining charges for work performed

o Process of paying for the service

o Cleanliness and appearance of car

o Amount of time for payment and collection of the vehicle

- Quality of after-sales service

o Amount of time spent waiting for service

o Ability to diagnose problems

o Quality of work performed

o Thoroughness in fulfilling your requests

o Availability of parts required

o Extent to which they stand behind service

6.3. Brand Satisfaction Model at Company X in Poland – history, underpinnings and

structure

The need for more complete approach to measuring customer satisfaction and loyalty

arisen together with the need of product management, marketing and PR departments of

Company X in Poland for better knowledge about clients behavior and their way of

thinking and making purchasing decisions. So far the two existing CSI studies offered a

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limited amount of knowledge, which covered two areas: sales service quality and after-

sales service quality. Until the Brand Satisfaction Model has been introduced there has

been no official representative information on how Polish customers perceive Company X

in terms of product quality, image, design, expectations, costs of ownership, comfort and

functionality, value/price ratio etc. There was also no measurement of customers’ loyalty

against dealers, against brand or their willingness for recommendation.

But defining the areas of clients’ feelings about a particular brand is not that complex and

is in fact easy to possess. The sales and marketing staff of each automotive company is

definitely well experienced to define all the areas which should be investigated and those

defined constructs can then be verified by focus groups or individual interviews with

customers giving them a chance to add those important elements that are not covered in

the research. After such process, researcher can be sure that his study covers all the

important elements creating overall picture of customers’ brand perception.

However there is also one more and very important aspect of knowledge about your

customers. The sole satisfaction scores for all significant areas creating overall satisfaction

and loyalty of the end-users have limited power for practical application in real business

life unless the importance of all the elements is calculated. Computation of each element’s

weight is crucial for creating complete picture of customers’ perception and the way they

evaluate the brand performance. If the whole process ensures that (1) satisfaction areas

definition is properly conducted internally in the company, (2) then the structure is

verified and supplemented by the sample of customers and (3) the importance scores for

all attributes are calculated, then it is guaranteed, that the whole approach is complete and

offers number of advantages which help better understand the clients.

One important aspect is the computation of importance weights. The question arises

whether the weights should be calculated by asking customers straight questions about the

importance of particular attributes or they should be computed statistically. Many

researches proved that the latter one is a better approach as it is resistant to one important

disadvantage of the first approach. Usually in case of having customers declare the

importance of the areas of their satisfaction the distribution of answers is for most areas

strongly negatively skewed meaning that all the elements are equally and very important.

Such methodology in most cases creates a picture of equal importance of the elements by

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limiting the distinction of the ones that are really important and that create the most

significant part of customers’ satisfaction and loyalty from those which are not important

and can be almost eliminated from the research. By statistical computation the importance

weights are more reliable and less biased by human factor. Moreover, statistical

computation allows for segmenting the results in satisfaction – importance matrix, as the

weight are spread wider as opposed to importance weights declared by respondents. The

satisfaction – importance matrix is presented in Figure 6.1.

Figure 6.1. Segmentation of satisfaction with attributes according to their importance.

The figure divides all attributes into four groups. Taking into account the importance

declaration, all the elements would be almost equally important and as a result all of them

would lie close to the middle of Importance axis. Thus the distinction of the real drivers of

customers’ satisfaction would not be possible. On the other hand statistical computation of

real importance scores of all areas included in the customer satisfaction study by using for

example PLS approach offers the researcher practical ability to discover elements that

need improvement and those where company can save some money. The most important

Attribute’s importance

Satis

fact

ion

Importance

Hig

h

High Low

Low

Needs improvement

Potential for savings

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field in the matrix presented in Figure 6.1. is the one with low satisfaction and high

importance attributes. This quarter of the matrix is the starting point of every analysis as

improvement of the areas which lie in this field has the biggest influence on overall

satisfaction score improvement. The field, where company can save some money, is the

one containing high satisfaction and low importance attributes meaning that customers

evaluation of these areas is too high relative to their importance. In general, for business

to be most effective, all measured variables should lie close to the diagonal - with some

tolerance which is calculated by confidence intervals.

This kind of satisfaction/importance analysis can be conducted for both overall

satisfaction and customers’ loyalty. Thus first figure would present all attributes

satisfaction scores and their influence (importance) on the overall satisfaction score while

the second one would present the influence of these elements on customers’ loyalty. The

two steps analysis is crucial for practical interpretation of the results. Although overall

customers satisfaction plays an important role in every company strategy it may be useless

if it does not create loyal customers. Loyal customers are the source of company’s higher

incomes and form the strong and stable base for sales performance. Therefore company

with quite satisfied but not loyal customers is definitely exposed for higher risk of loosing

business and has to constantly seek for other customers, explore new segments by for

example introducing new products which is extremely costly and may be successful only

in a short term as the number of market opportunities is usually limited.

One important aspect here is the definition of areas of responsibility for a company.

Global companies operate with a structure led by headquarter and represented by sales

companies or agents in different countries. In case of automotive sector the headquarter is

usually responsible for inventing, designing and producing a certain product with very

limited influence of sales companies on this process. Therefore such areas as product

quality, comfort and functionality of vehicle are not dependent on sales companies’

performance locally in different countries. On the other hand, it is sales company that

creates particular level of sales and after-sales service quality for customers in particular

country. In this case, the headquarter has very limited influence on what level of service is

provided beside producing some guidelines and pushing for their implementation.

Therefore some areas lie mainly in the responsibility of the headquarter while sales

companies are responsible for the other areas. Thus when conducting importance vs.

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satisfaction analysis the researcher needs to remember about the aim of the study whether

its objective is to analyze and improve total business or local performance of a brand.

To sum up Brand Satisfaction Model has been designed in order to create a complete

measurement method that would not only explore all the areas of customers satisfaction

but would also measure their influence on customers’ satisfaction and loyalty. This kind

of approach allows for confirmation and verification of different theories on customer

satisfaction in the automotive market by understanding customers perception of Company

X brand locally in Poland. It also forms a solid base for making practical

recommendations useful for making tactical, operational and strategic decisions in sales,

marketing and PR departments. Thus BSM is an universal tool that offers significant

amount of knowledge with limited amount of effort. It would have more advantages when

applied to most of the automotive producers selling new vehicles in Poland. This would

allow for comparisons between satisfaction and loyalty scores between different

companies as well as for comparisons of different brands’ customer profiles.

6.3.1. Questionnaire development

In order to create a proper questionnaire exploring all areas of customers satisfaction with

a brand, a 3 steps approach was applied.

First a project group has been set at Company X in Poland. The group consisted of sales

representatives from the dealer network and headquarter employees responsible for sales

planning, product management, marketing, PR, customer relationship management

including Customer Service employees that have frequent telephone contact with clients.

The aim and preliminary structure of the research was presented in front of the project

group. All the members were asked to give their input into definition of all the areas of

clients satisfaction with a brand in order to build a complete measurement tool covering

all aspects of the research. All in all, 3 meetings were held and finally the first official

structure of the questionnaire was developed.

In the second phase the research agency was contacted in order to give its input into

development of the tool. The agency was presented the assumptions of the study as well

as the questionnaire created during first phase of the research. It combined all its

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experience in conducting customer satisfaction studies, analyzed the research objectives

and suggested some changes in the questionnaire. Therefore the second version of the

questionnaire arisen.

In the third phase 10 individual interviews with Company X customers were carried out in

order to verify the completeness of the questionnaire as well as to make it comprehensible

and understandable. In this phase clients were firstly asked to state their definition of

satisfaction with an automotive brand and then all the areas from the second version of the

questionnaire were verified with respect to their clarity and completeness.

Ultimately the third and final version of the research tool has been developed. It consists

of questions defined by not only people working in sales and marketing, PR and CRM

departments at Company X in Poland but also sales representatives who have day-to-day

contact with clients. What is most important, it has been verified by customers with

respect to its completeness and clarity. Below is the description of all the elements

included in the final version of the questionnaire. It consists of 3 parts. First is the

definition of the respondent, second is the main part of the questionnaire that consists of

questions defining Brand Satisfaction Model (measured on a scale from 1 to 10 where 1 is

the absolutely negative score and 10 is definitely positive score) and the third part is the

demographic one.

I. Definition of the respondent

1. Gender of a respondent

2. Definition of the concrete model that the respondent is driving (8 models that cover

95% of the total sales volume have been specified)

3. Definition of the type of the engine (petrol/diesel)

4. The date of the vehicle reception after purchase

5. Specification of the dealer where the vehicle was purchased

II. Main part of the questionnaire

1. Expectations at the purchase of the vehicle

a. Overall expectation of quality

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b. Expectation of how well the product fits the requirements

c. Expectation of reliability/How often things could go wrong

2. Overall Satisfaction

a. Overall satisfaction with usage of the vehicle

b. Overall satisfaction with the vehicle compared to an ideal vehicle

c. Overall satisfaction with the vehicle compared to expectations at the purchase.

3. Image

a. Overall satisfaction with image of a brand

b. Assurance of safety when driving

c. Stable position of a brand on the market

d. Technological leadership of a brand

e. Brand involvement in customers’ satisfaction improvement

f. Brand involvement in social actions

g. Brand involvement in promotional events (trades, advertising campaigns,

sponsoring etc.)

h. Brand involvement in environmental protection

i. Brand involvement in making drivers’ lives easier

4. Sales service quality

a. Overall satisfaction with sales service quality

b. Professionalism of the sales representative

c. Kindness and good manners of the sales representative

d. Sales rep willingness to inform customer

e. Contact renewal after customers visit in the dealership

f. Ease of contact with the sales rep

g. Atmosphere in the showroom

h. Wide product offer

i. Availability of additional services (financing, test drives etc.)

j. Promptitude of service realization

k. Abidance of timing of the service

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5. Quality of the vehicle

a. Overall satisfaction with the quality of the vehicle

b. Reliability of the vehicle

c. Quality of exterior painting

d. Quality of interior materials and finishing

e. Quality of the upholstery

f. Driving quality (driving and steering systems)

g. Suspension quality

h. Breaking quality

6. Design of the vehicle

a. Overall satisfaction with the design of the vehicle

b. Exterior design

c. Interior design

d. Modernity of design

e. Uniqueness of design

7. Comfort and functionality of the vehicle

a. Overall satisfaction with comfort and functionality

b. Seats comfort

c. Visibility from driver’s seat

d. Functionality of steering elements

e. Interior space

f. Possibilities of interior space management (folding, removing seats etc.)

g. Boot capacity

h. Communication systems (radio, navigation etc.)

i. Air-conditioning/ventilating systems

8. Costs of ownership

a. Overall satisfaction with costs of ownership

b. Fuel usage

c. Insurance costs

d. After-sales service costs

e. Repairing costs

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f. Spare parts exchange costs

9. After-sales service quality

a. Overall satisfaction with after-sales service quality

b. Professionalism of the after-sales representative

c. Sales rep willingness to inform customer

d. Atmosphere in the after-sales showroom

e. Availability of substitute vehicle

f. Availability of spare parts

g. Promptitude of service realization

h. Abidance of timing of the service

10. Value for money

a. Evaluation of the quality with respect to the price of the vehicle

b. Evaluation of the price with respect to the quality of the vehicle

11. Loyalty

a. Willingness to recommend the brand

b. Willingness to recommend the dealer where the vehicle was purchased

c. Willingness to purchase a vehicle of the same brand

If the answer is negative than the customer is asked to tick out the reasons:

i. Bad quality of the vehicle

ii. Bad quality of service received at the dealership

iii. Design of the vehicle

iv. Reliability of the vehicle

v. Comfort

vi. Too high price of the vehicle

vii. Attractiveness of other brands

viii. Too high ownership costs

ix. The vehicle does not meet the expectations

x. Other brands offer same quality vehicles with lower price

xi. Other reasons

d. Willingness to purchase a vehicle at the same dealership

If the answer is negative than the customer is asked to tick out the reasons:

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i. Poor quality of service

ii. Inconvenient location

iii. To high prices of after-sales service

iv. Incompetent staff

v. Poor quality of repairing

vi. Negative experience with vehicle delivery

vii. Timing/Promptitude of service

viii. Poor atmosphere at the dealership

ix. Poor availability of additional services such as for example substitute

vehicle, financing etc.

x. Other reasons

III. Demographic questions

1. Age of the respondent

2. Education of the respondent

3. Number of family members living with the respondent

4. Profession/Occupation of the respondent

5. Number of habitants in the city of respondent

6. Voyevodship/Province/County of the respondent

7. Earnings of the respondent

6.3.2. Computer software for Partial Least Squares models

The authors of this paper have conducted significant research on all the computer

programs that could handle Partial Least Squares calculations and produce necessary

output. Unfortunately not many programs support this methodology. Furthermore some

programs supporting PLS calculations are not user friendly not allowing for graphical

definition and representation of the model. However there are two programs with

graphical interfaces helping researchers easily build the structure of relationships for

particular study. These are: PLS Graph and Smart PLS. Ultimately the authors have

chosen the latter one as the most complete, professional and at the same time easiest and

most user friendly tool for performing PLS on BSM. The Smart PLS software has been

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created by a group of developers sited at the University of Hamburg (Germany) and is so

far available as a freeware for all academic users.

6.3.3. Working out the structure of the model

The objective of the research was to build an industry specific model of customer

satisfaction and loyalty which would completely cover all aspects of brand performance

perception. The ACSI and ECSI models are the cornerstones of the structure for Brand

Satisfaction Model. However the two models have been developed in order to serve as a

universal tool for measuring satisfaction of different industries’ clients. Therefore a

certain portion of generality have been applied in both American and European

methodology.

The Brand Satisfaction Model was designed as an automotive industry specific

measurement method with strong attention to details. Thus the BSM had to cover more

areas of customer satisfaction as well as some of the areas had to be divided into more

detailed ones. The ACSI model consists of Perceived Quality, Perceived Value, Customer

Expectations, Customer Satisfaction Index, Customer Complaints and Customer Loyalty

scores. The ECSI model adds Image factor and divides Perceived Quality into “software”

and “hardware” areas. According to all the research done during preparation of BSM

structure and based on Company X employees experience as well as customers’ definition

of satisfaction concept, the structure of the study had to be modified versus ACSI and

ECSI models. If we take the ECSI methodology as a starting point than in order to create

BSM structure the authors added 3 factors: Comfort and Functionality, Vehicle Design

and Costs of Ownership. These 3 elements have been defined during first phase of study

preparation as important elements of customer satisfaction and are rather specific for

automotive industry. Furthermore Perceived quality of “software” and “hardware” has

been divided into Product Quality, Sales Service Quality and After-Sales Service Quality.

This distinction is justified by the fact that these 3 elements are clearly recognized by

customers of passenger cars because in vast amount of cases there are 3 separate units

responsible for each of the areas: Producer, After-Sales Service department of the

dealership and Sales Service department of the dealer point. Furthermore The Customer

complaints area has been replaced/covered by the After-Sales Service Quality factor. All

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these changes modified the ECSI model to make it more automotive industry specific as

well as to make it more useful for management of Company X in Poland.

Ultimately the structure of relationships between all latent variables had to be also altered

and adjusted to the defined structure of Brand Satisfaction Model. This has not been an

easy task due to higher number of variables included into specification. First attempt of

the authors was to make the structure of relationships as much similar to ECSI as possible.

Figure 6.2 presents the first structure of Brand Satisfaction Model with similar

relationships as in ECSI methodology.

Figure 6.2. First version of Brand Satisfaction Model based on ECSI

methodology.

The latent variables not included in ECSI such as: Comfort and Functionality, Costs of

Ownership and Vehicle Design have been connected to Value for Money and Customer

Satisfaction Index variables, what was done based on theoretical knowledge and

assumptions.

However after validation of the model it appeared that the structure had to be significantly

altered. Although Cross Loadings and AVE test confirmed proper specification of latent

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variables, the Bootstrapping algorithm (with 346 cases, 500 samples, construct level

changes and mean replacement algorithm) which results are presented in Figure 6.3,

confirmed that most of relationships are not significant therefore the arrows between such

variables should be deleted from the model.

Figure 6.3. Results of Bootstrapping algorithm for first version of Brand Satisfaction

Model

After this failure the authors decided to apply different algorithm for defining structure

relationships for industry specific model called Brand Satisfaction Model.

The authors decided to firstly investigate the correlation matrix for all latent variables

received from performing PLS on the first version of Brand Satisfaction Model (The

matrix is attached in Appendix 1.).

Furthermore an expert advisory had to be applied in order to build a model that could be

justified by satisfaction theories and practical knowledge. Therefore some arrows were

specified in order to confirm some theoretical assumptions of researchers although the

correlation score did not necessarily justify the relationship. While creating new structure

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of models that have not been confirmed before by any kind of studies the researchers have

to bear in mind that the model has to be proven not only by statistical tests but also by the

theory lying behind the study. Therefore after many trials, the authors worked out the final

structure of Brand Satisfaction Model which can be justified by model validation

techniques and complies with the satisfaction theories as well as practical experience. The

complete model is presented below in Figure 6.4. The detailed results of PLS algorithm

application are attached in Appendix 3.

Figure 6.4. Final structure of Brand Satisfaction Model for Company X in Poland

Figure 6.5 presents results of application of Bootstrapping algorithm to the final

specification of BSM. Detailed Bootstrapping algorithm results are attached in Appendix

2. It confirms all relationships in a very significant manner. According to t-values

received all path coefficients are significant (df = 500) with a confidence level of at least

99%. Thus this structure can represent a complete picture of how customers of Company

X in Poland evaluate its brand performance. As the bootstrapping algorithm proves all the

relationship in a very strong manner it would be worth verifying if the model could be

also applied to other automotive brands in Poland but this topic would be touched upon in

further course of this paper.

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Figure 6.5. Results of Bootstrapping algorithm for final version of Brand Satisfaction

Model

6.3.4. Discussion on BSM structure

To justify the structure and all the relationships of the Brand Satisfaction Model not only

statistical tests or measures such as bootstrapping, AVE, Cronbach’s alpha or Cross

Loadings have to prove the model. Beside statistical confirmation the theoretical and

practical knowledge also has to stand behind the structure. Therefore the aim of this part

of the chapter will be to explain what has already been confirmed by statistics.

Some clarification regarding applied modes for latent constructs is needed. Firstly all the

latent constructs are created in a reflective way due to the fact that they reflect particular

feelings of customers regarding some aspect of their satisfaction i.e. Vehicle quality etc.

Secondly the manifest variables in all cases do not completely define and form the latent

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construct to which they are related. Furthermore all latent constructs include one manifest

variable that evaluates general satisfaction of customers with a specific latent construct

thus forcing somehow the reflective mode. Finally all sets of manifest variables that form

each specific construct are usually correlated to each other thus making it impossible for

applying formative specification.

Let’s move on to analysis of structure of inner relationships.

Let’s take a closer look at Comfort and Functionality variable. It is the only latent

construct related to the Vehicle Quality meaning that satisfaction of customers with

comfort and functionality of driving the vehicle influences their opinion about vehicle

quality. It can be reasonably explained because when the vehicle offers good comfort and

is functional it creates better opinion about the product itself. When the customer has

positively evaluated the vehicle in terms of comfort he/she also has a positive attitude for

evaluating quality of a vehicle. The strength of the relationship should be quite strong as

both latent constructs reflect practical elements of product evaluation.

Moving on to Costs of ownership, this latent construct is related only to after-sales service

quality variable as it partly reflects costs of service, spare-parts and repairs. However it

does not prove any direct influence on value for money concept. It only has an indirect

influence on the construct through the quality of after-sales service. This can be justified

by the fact that the Costs of ownership construct does not include any evaluation of price

of the vehicle or its quality which are the cornerstones of the Value for money factor.

When analyzing Vehicle design concept the only proven relationship binds it to Image

variable. This relationship can easily be proven as the exterior and interior outlook,

modernity and innovativeness of a design create the image of the brand. If the design is

modern and the exterior as well as interior catch the eye of customer, the evaluation of

brand image performance should be higher than in the opposite case.

Vehicle quality construct shows positive influence on Value for money, Overall

Satisfaction and Image. The first two relationships have already been proven by for

example ECSI methodology. The positive connection with Image concept confirms the

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theory that reliable, good quality vehicles such as i.e. Toyota have better perceived image

than the ones from the lower part of the quality ranking.

Image variable influences Value for Money and Expectations factors. The first

relationship is also proven by i.e. ECSI model. The connection to expectations can be

explained by the fact that the evaluation of brand Image has a positive influence on what

customers will expect from the vehicle and the brand itself. If a brand is perceived as

being environmental friendly, reliable, safe, involved in customers satisfaction

improvement as well as strongly involved in communication campaigns than the

customers will expect such attitudes when they decide to buy the vehicle of a particular

brand.

The expectations on the other hand are connected only to Sales service quality.

Unfortunately no relationship between Expectations and Value for money, Vehicle

Quality, Overall Satisfaction or Loyalty has been statistically proven. The only path

approved by bootstrapping with stable parameter estimate is the path to Sales service

quality. The reason for this kind of result is first of all the fact that in ACSI, ECSI and

other customer satisfaction models usually the customer expectations have rather low

influence on overall satisfaction and loyalty of customers. It seems that in the automotive

industry in Poland in case of a premium brand like Company X the expectations have no

direct influence on the 3 most important elements of the BSM: Value for Money, Overall

Satisfaction and Loyalty. However they have a positive influence on Satisfaction with

sales service quality. Such outcome can be explained in a way that when customers have

some specific expectations about the brand and they consider buying the vehicle of this

brand they first go to the showroom meaning that the first thing they evaluate is the sales

service quality. Those customers in such process verify their expectations about the brand

by direct contact with a dealer (representing brand) and the product itself (showroom and

test drives). After buying a vehicle the expectations have no influence on customers’

evaluation of Perceived Value of the vehicle or their overall satisfaction with the car as

customers begin to care more about real attributes of the product and soft elements of the

service they receive than about the expectations they had before the purchase of the

vehicle. The expectations have an indirect influence on loyalty through the sales service

quality variable.

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Sales service quality opposite to perceived quality of “software” in ECSI model does not

show any positive influence on Value for money or Overall satisfaction of clients. SSQ is

only connected to Loyalty construct. This relationship can be justified as follows.

Customers have direct contact with sales service quality usually when they aim to buy a

vehicle. While actually using a vehicle they have no contact to sales representatives

meaning that it should not influence their evaluation of their satisfaction with vehicle

usage. Next contact with sales service is most often when a customer decides whether to

buy a vehicle of the same brand at the same dealer or not. If the service received will be

positively evaluated than it may also positively influence their decision whether to buy the

vehicle of the same brand again. Therefore the above presented reasoning confirms the

sole path connecting SSQ and Loyalty.

After-sales service quality as the third part of Perceived quality construct in ACSI is

related to Value for money factor which is the same as in ECSI and to Loyalty which can

be explained similar to relationship between SSQ and Loyalty. If a client is well treated

during each and every visit at the workshop than he/she will be more loyal against the

dealer as well as the brand itself.

The Value for money concept is related only to Overall Customer Satisfaction variable

which is related only to Loyalty construct. This structure of relationships is no different to

ACSI or ECSI and needs no explanation.

6.3.5. Quality criteria evaluation

As discussed earlier the bootstrapping algorithm proved the structure of inner relations

between all latent constructs used in the model. The three tables included in Appendix 2:

Outer Model T-statistics, Path coefficients T-statistics, Total Effects T-statistics present

the results of bootstrapping algorithm application to Brand Satisfaction Model. The results

generally confirm inner and outer relations used in the structure applying the rule of t-

statistic greater than 2. The are some inner relations (path coefficients and total effects)

with t-statistic values between 1 and 2 meaning that the parameter estimate are not quite

stable however the relations are proved by underlying theory of customer satisfaction

therefore the authors decided to maintain the original structure of BSM. The problem of

low t-statistic values exists mainly in bootstrapping algorithm of total effects and applies

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mainly to indirect relations with usually low parameter estimates. Thus such relationships

are rather harmless to the whole structure of the model as they have low influence on the

interpretation of the results but on the other hand explain all the theoretical correlations of

particular latent constructs.

In order to evaluate the appropriateness of specification some other quality criteria

described in PLS theory part of the thesis have to be analyzed. All the information on

quality criteria is included in Appendix 3.

The overview of quality criteria presents values for AVE, communality, composite

reliability, Cronbachs Alpha and R square.

In general AVE and communality values should be greater than 0,5 as well as greater than

the square of correlations between all Latent Variables used in the model (Tenenhaus et al.

2005). Such condition is met with two exceptions of Comfort and Functionality and Image

variables where the AVE values are equal to 0,48 and 0,49 respectively. This kind of

deviation can be easily omitted as the value is very close to the minimum.

In case of composite reliability and Cronbachs Alpha both statistics should be higher than

0,7 (Tenenhaus et al. 2005). All the values for latent constructs used in the Brand

Satisfaction Model are greater than 0,84 further confirming the reliability of the outer

structure.

Analyzing the R-square values the only important variables in terms of predictive power

of the model are Overall Satisfaction, Loyalty and Value for money. Other variables for

which R-square was calculated serve as the connectors of indirect relations for other latent

constructs and are not main elements in terms of predictive properties of the model.

Therefore considering the three main variables in question all R-square values are high

enough in order to give significant predictive power for the model. In general the

minimum value is 0,5 (Rossiter 2002) therefore the Loyalty 0,6 value, the Overall

Satisfaction 0,72 value and Value for money 0,69 value offer strong base for further

analysis.

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The analysis of cross-loadings confirms the validity of the latent constructs and their

respective indicators meaning that the appropriate indicators build up the latent constructs.

The general rule is that the indicators should load higher on its respective latent construct

and that the values of cross loadings for particular latent construct should be higher than

0,7. This conditions are met in most cases with some minor exceptions when cross-

loadings values are between 0,55 and 0,7. However this is a small scale problem which

can be definitely omitted especially when the number of variables is so high and the

number of cross-loadings parameters is equal to 528. Therefore in general the values of

cross-loadings prove the outer structure of the model.

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7. RESULTS OF BRAND SATISFACTION MODEL FOR COMPANY X

7.1. Sample description

Before any analysis, the detailed check of gathered data was applied. The database was

checked for possible outliers as well as with regard to its consistency and possible logical

mistakes. After data import to the software programs, the consistency of data with the

original base was also investigated in order to assure the highest possible data validity and

quality.

Sample for the Brand Satisfaction Model study has been carefully selected in order to

reflect the structure of Company X customers in Poland. The whole database of all the

clients as well as the sales volume segmentation have been analyzed. Based on the

analysis the sample of all the customers that purchased a vehicle one to four years before

the research was extracted. The number of customers of particular vehicle models

reflected the structure of sales volume as well as regionalization of sales with respect to

dealerships shares in sales. The factors that have also been taken into account while

creating sample database are gender, age group, education, occupation and earnings. From

the total number of over 10 000 customers the database including 2 030 clients that meet

the assumptions of the research was created. Firstly the mailing with the information

about possible individual interview was sent out to all 2 030 customers. Finally the

requested number of 346 responses was gathered which gives a reasonable response rate

of 17%. The responses were collected through the individual interviews with the clients -

the method that assures customers about importance of the research by rising its prestige.

It also offers lower possibility of collecting not proper responses through eye to eye

contact what gives confidence that the appropriate person is responding to the

questionnaire.

Below are the figures describing the sample data set in detail presenting the main

characteristics of the respondent group. The figures prove and are in line with the profile

of Company X consumers.

Respondents are mainly male according to profile of Company X customers.

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Figure 7.1. Gender of respondents

77%

23%

0%

10%

20%

30%40%

50%60%

70%

80%

Man Woman

The model range has been split into three categories: Compact, Mid-Size, Full-size and

Large. Under compact category there are customers of two models: Compact vehicle and

Compact MPV. Mid-size category is also represented by two vehicles which fall into a

Mid-size sedans and Mid-size Specialty Coupes segments of passenger vehicles

segmentation. Full-size and Large category is built up of 4 models: Full-size sedan, Large-

size sedan, Full-size Off-road and Luxury Specialty Coupes.

Figure 7.2. Model range

29% 29%

41%

0%5%

10%15%20%25%30%35%40%45%

Compact Mid-size Large

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Figure 7.3. Engine type

48% 52%

0%

20%

40%

60%

80%

100%

diesel petrol

The shares of fuel types also are in line with actual state of vehicles sold to customers

although the trend is strongly changing to diesel engines. Furthermore, the split would be

different for different models as for example all sport-type vehicles as coupes or roadsters

are sold mainly with petrol engines while at the same time all off-road vehicles are

equipped mainly with diesel engines. Compact and limousine type vehicles sedan as well

as estate wagons so far have a split of 60% diesel to 40% petrol engines with a moderate

trend towards diesel.

The figure presenting age of Company X customers in Poland confirms the fact that the

majority of clients falls into 40 to 60 years old category. The group of 30 to 39 years old

customers is already significant category with high potential for growth due to

development of Polish economy which forces the growth of earnings especially for young

people.

Analyzing education of the customers there are two groups that cover over 90% of the

total number. The biggest category consists of clients with higher/university type

education. The other significant group is the one with only secondary education (38%).

The group consists mainly of company owners that started their businesses and at the

same time decided not to continue education. We have to bear in mind that those people

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attended schools 15-30 years ago when the number of schools offering higher education

was significantly lower. This proportion changes at a high pace towards higher education

category.

Figure 7.4. Age groups

3%

19%

33%35%

10%

0%

5%

10%

15%

20%

25%

30%

35%

40%

18 to 29 30 to 39 40 to 49 50 to 60 over 60

Figure 7.5. Education

1%5%

38%

4%

53%

0%

10%

20%

30%

40%

50%

60%

preliminary secondarytechnical

secondarygeneral

bachelors masters

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Occupation of Company X customers in Poland is dominated by two categories: owners

of the companies and upper-level managers what is in line with clients’ profile. There are

also 3 interesting categories with equal 5% share in the total sample: Pensioners, Highly

qualified specialists and people with free occupation such as for example Artists and

Farmers. While the first and the latter groups have rather stable share in the total number

of customers the group consisting of highly qualified specialists is the one with extremely

high potential for growth which is also connected with economy development and Poland

accession to EU which in long term will significantly increase salaries.

Figure 7.6. Occupation/Position

2% 5% 2% 0% 0% 1% 2%5%

14%

64%

5%

0%

10%

20%

30%

40%

50%

60%

70%

Une

mpl

oyed

Pens

ione

r

Publ

ic c

lerk

Bue

rau

cler

k

Not

qua

lifie

d ph

ysic

al w

orke

r

Qua

lifie

d ph

ysic

al w

orke

r

Qua

lifie

d te

chni

cal w

orke

r

Hig

hly

qual

ified

spe

cial

ist

Man

ager

pos

ition

Ow

ner o

f the

com

pany

Free

occu

patio

n/A

rtist

/Agr

icul

ture

The total income of households doesn’t need any comment as this is clear that biggest

group of Company X customers is of course the one that has the highest earnings and the

trend will maintain as it is now.

Figures 7.8 and 7.9 present the regional split of customers divided into the size of cities

and name of voyevodship. Naturally the strongest demand for vehicles from Premium

segment is visible in biggest cities. Analysts predict that in a long term there will be

negative migration to the largest agglomerations which means that more and more

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wealthy people will move to smaller cities. Thus a higher share of customers living in

cities with 50 to 200 thousands inhabitants shall be observed in future.

Figure 7.7. Total household income (in PLN)

4%7% 4%

7%

78%

0%

10%

20%

30%

40%

50%

60%

70%

80%

below 4000 4000 - 6000 6000 - 8000 8000 - 10 000 over 10 000

Figure 7.8. Size of the city (in thousands of inhabitants)

9% 8% 10%

23%

49%

0%5%

10%15%20%25%30%35%40%45%50%

village city up to 10city 10 to 50 city 50 to200

city over 200

101

There are 5 strongest sales regions in Poland when it comes to analysis of customers

divided into voyevodships. The biggest voyevodship regarding sales of new vehicles is

Mazowieckie with its capital – Warsaw. The second biggest region is Slaskie (Katowice)

and Dolnoslaskie (Wroclaw) on the south of Poland which, when summed together, have

the same share as Mazowieckie (23%). Moving to northern part of Poland there are three

significant regions with high demand potential: Wielkopolskie (Poznan),

Zachodnipomorskie (Szczecin) and Pomorskie (Gdansk) with 8%, 8% and 6% share

respectively.

Figure 7.9. Region/Voyevodships

8%

3% 2%5%

6%

3%

23%

1%4% 3%

6%

15%

2% 1%

8% 8%

0%

5%

10%

15%

20%

25%

Dol

nosl

aski

e

Kuj

awsk

ie

Lube

lski

e

Lubu

skie

Lodz

kie

Mal

opol

skie

Maz

owie

ckie

Opo

lski

e

Podk

arpa

ckie

Podl

aski

e

Pom

orsk

ie

Slas

kie

Swie

tokr

zysk

ie

War

min

skie

Wie

lkop

olsk

ie

Zach

odni

opom

orsk

ie

7.2. Estimation results for Brand Satisfaction Model – Total Brand

The parameter estimates for inner model as well as R square values for all dependent

variables are presented in Figure 7.10. To actually analyze the strength of impact of

particular constructs on Satisfaction and Loyalty measures the total effects were calculated

and are presented in Figure 7.11.

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Figure 7.10. Results of PLS algorithm application on final version of BSM.

Looking at differences of importance of particular latent constructs regarding satisfaction

and loyalty it is obvious that satisfaction does not always mean loyalty. Even if the

customer is satisfied he/she does not have to purchase or recommend a vehicle of the

same brand until certain conditions are met. There are 2 elements Vehicle Quality and

Comfort and Functionality that generate 75% of customers satisfaction while at the same

time creating only 31% of customers loyalty. This example shows how different are both

concepts and that company sole orientation on satisfying its customers is not enough to be

successful. In order to make customers loyal an automotive company has to take care of

many areas that altogether have strong influence on loyalty. Beside Vehicle Quality and

Comfort and Functionality it is Overall Satisfaction, Sales Service Quality and After Sales

Service quality that all together generate 79% of customers loyalty. The moderate

influence on Loyalty (6% each) have cost/price variables: Costs of ownership and Value

for money. Expectations, Image of a brand as well as Vehicle Design present rather low

influence on both customers satisfaction and loyalty. The comparison of importance

scores for each latent construct with regard to its influence on satisfaction and loyalty

clears out the direction into which the strategy of Company X in Poland should be

heading. To have satisfied and loyal customers, the headquarter of Company X has to

produce good quality products that offer proper driving comfort and are functional, while

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at the same time the sales company in Poland needs to take care mainly of the quality of

sales service and after sales service. The sales company can not forget and disregard price

positioning of the vehicles with respect to the value they represent in comparison to

competition. The level of costs of vehicle ownership is also quite important and needs to

be monitored and eventually adjusted to those offered by competitors. This general

implications for the total brand might be different if applied to the 3 model groups -

Compact vehicles, Mid-size sedans and coupes and Full-size and Large premium

vehicles. The possible differences will be investigated in further analysis.

Figure 7.11. Comparison of relative Total Effects on Overall Satisfaction and Loyalty.

In order to discover the areas where improvement is absolutely necessary, the importance

versus satisfaction analysis has to be conducted. Table 1. presents the latent variable

scores received from Brand Satisfaction model estimation by PLS procedure.

In general for the total brand the score of 78% in overall satisfaction and 83% in loyalty

was received. It is difficult to set the minimum value for both indices as there is no direct

comparison to previous studies. However comparing BSM to CSI scores and in order to

force some improvement of satisfaction and loyalty the authors decided that the minimum

3%

32%

18%

1% 0% 3% 0% 0%

16%

1%

43%

13% 13%

6% 5% 3%

14%

21%

6%1%

0%5%

10%15%20%25%30%35%40%45%50%

After-s

ales q

uality

Comfor

t

Costs o

f owne

rship

Expect

ation

sIm

age

Overall

Satisfa

ction

Sales S

ervice

Qual

ity

Value f

or mon

ey

Vehicle

Desi

gn

Vehicle

Qual

ity

Overall satisfaction Loyalty

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score for all investigated areas is 85%. Therefore all variables that rank below 85% should

be deeply investigated for improvement plan.

Table 1. Latent constructs’ scores (rescaled to 0-100).

Latent Variable ScoreExpectations 93%

Vehicle Design 91%Sales Service Quality 89%

Comfort 87%Vehicle quality 86%

Loyalty 83%Image 82%

Overall satisfaction 78%After-sales quality 75%Value for money 75%

Costs of ownership 68%

The highest two scores were noted for the two area, which have very low influence on

customers’ satisfaction and loyalty: expectations at the time of purchase and design of the

vehicle, which scored 93% and 91% respectively. Two highest scores are followed by 3

very important areas for company’s overall performance which are: Sales Service Quality

(89%), Comfort and Functionality (87%) and Vehicle Quality (86%). These 3 constructs

have the strongest influence on customer satisfaction and as they received scores above

86%, there is no negative signal for improvement within those 3 areas. Below the

minimum score there are 4 quite important areas: Image 82%, After-Sales service quality

75%, Value for Money 75%, Costs of ownership 68%. The company definitely needs to

concentrate on these areas in order to improve the overall satisfaction and loyalty of

customers.

In order to discover what needs to be done to improve evaluation of Company X, the

analysis needs to be divided into two approaches. One would be headquarters’ while the

other one would be local sales companies’ responsibilities. Such distinction is necessary

as headquarter and sales companies are responsible for a bit different areas included in the

study. The headquarter is designing and inventing vehicles meaning that it is solely

responsible for the vehicle quality, design and the comfort and functionality they provide.

At the same time sales companies have very limited influence on the product

characteristics - what vehicles are being produced and what quality they provide. On the

105

other hand it is sales company in every country that is responsible for sales and after-sales

service quality, costs of ownership. Furthermore, local sales companies in a large part

create image of a brand, as well as they offer certain value for money to the consumer by

applying certain pricing strategy. As the BSM is conducted on sales company level, the

authors decided to split the analysis into:

1. presentation of all results for satisfaction and importance on one Figure 7.12 as an

overall picture of Company X performance and importance of particular areas

2. the presentation of only those areas that are under strict or indirect supervision of

sales companies as an analysis of local performance – Figure 7.13.

Figure 7.12. Satisfaction scores vs. satisfaction importance analysis – overall

60%

65%

70%

75%

80%

85%

90%

95%

0% 10% 20% 30% 40% 50%

Satisfaction Importance

Satis

fact

ion

Scor

e

Vehicle quality

Comfort/Functionality

Value for money

Image

After-Sales Quality

Vehicle design

Costs of ownership

Referring to the figure 7.12, the red line draws the minimum value score for all the areas.

Therefore all the areas below this line should be pushed up in order to improve the overall

satisfaction score. Looking at the figure it is obvious that among all constructs below the

red line the highest influence on satisfaction is given by Value for money (16%) variable

and than by After-Sales quality (3%) and Image (3%).

Moving on to local sales company performance the spectrum of areas in question is

smaller. There are 5 areas, on which performance sales company has some kind of

influence. Among them only Sales Service quality is above the red line with unfortunately

106

no influence on customers overall satisfaction. Therefore there are 4 remaining areas

which need improvement: Value for money, After Sales service quality, Image and Costs

of ownership. They all have different priorities: 69%, 13%, 12% and 6% respectively.

However as the responsibility of local sales company, they should all be taken care of.

Figure 7.13. Satisfaction scores vs. satisfaction importance analysis – sales company

60%

65%

70%

75%

80%

85%

90%

95%

0% 10% 20% 30% 40% 50% 60% 70% 80%Satisfaction Importance

Satis

fact

ion

Scor

e

Value for money

Image

After-Sales Quality

Costs of ownership

Sales service quality

In order to discover detailed areas for improvement the importance versus satisfaction

analysis have to be performed for each construct on a manifest variables level. Before this

detailed approach is implemented, Loyalty concept and the areas that have the highest

influence on Loyalty shall be explored. Here the two steps approach have also been

applied – overall and sales company specific.

As can be seen in Figure 7.14 there are repeating areas such as After-Sales Service

Quality, Costs of Ownership, Value for Money and Image that lower the overall loyalty of

Company X clients and therefore need improvement. Furthermore the Overall Satisfaction

score is also not satisfying enough and has to be improved. If the above mentioned factors

are improved, the overall satisfaction score will increase as well, as there are links

between the satisfaction and the mentioned areas.

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Figure 7.14. Satisfaction scores vs. loyalty importance analysis - overall

60%

65%

70%

75%

80%

85%

90%

95%

0% 5% 10% 15% 20% 25%Loyalty Importance

Satis

fact

ion

Scor

e

Value for money

Image

After-Sales Quality

Costs of ownership


Comfort and functionality

Overall Satisfaction

Vehicle qualityVehicle design

Expectations

Figure 7.15. Satisfaction scores vs. loyalty importance analysis – sales company

60%

65%

70%

75%

80%

85%

90%

95%

0% 5% 10% 15% 20% 25% 30% 35% 40%Loyalty Importance

Satis

fact

ion

Scor

e

Value for money

Image

After-Sales Quality

Costs of ownership


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Moving on to Figure 7.15, local sales company performance on factors that have influence

on Company X customers’ loyalty can be analyzed. Again it is After Sales service

Quality, Value for Money, Costs of Ownership and Image Variables that negatively

influence the level of clients’ loyalty. The only positive sign here is the performance of

sales service at dealerships. It definitely pushes the loyalty score above average.

After the general analysis of different areas performance and their influence on overall

satisfaction and loyalty of Company X customers in Poland, detailed satisfaction vs.

importance analysis of areas that need improvement shall be conducted. However there is

a strong argument to stop here and make the summary of general analysis.

The Brand Satisfaction Model has been designed as a tool for measuring and improving

Company X customers’ satisfaction and loyalty in order to create better image of the

brand, increase brand sales and its general position on Polish automotive market.

Therefore BSM includes areas that are under strict supervision of company’s headquarter,

on which sales companies have very poor influence such as vehicle quality, comfort and

functionality of the vehicle as well as its design. BSM includes also areas which are either

sole responsibility of sales companies or which performance can be improved by local

sales companies. Within those areas there is Sales service quality, After-Sales service

quality, Value for Money of the vehicle in terms of its pricing strategy, Costs of vehicle

ownership and Image of a Brand. Although all the areas have very different weight in

terms of generating higher overall satisfaction or loyalty of Company X customers, they

should all be taken care of if their score is not satisfactory enough (below 85%). The

priorities should be definitely accepted and respected but unless it doesn’t require too

much effort from the sales company, all the negatively scoring areas should be analyzed,

monitored and improved. Such methodology is not fully consistent with satisfaction vs.

importance analysis however due to responsibility split between headquarter and sales

company, it is much easier and effective to take care of more areas than the satisfaction

vs. importance analysis would suggest.

7.3. Estimation results – Total brand - detailed analysis of performance

Having in hand all the areas that need a reparation program, which were discovered in the

general analysis of latent constructs performance and importance, the detailed analysis of

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those areas can be implemented. The performance of headquarter in terms of providing

good quality products which offer good design, are comfortable and functional in use is

generally well enough. This means that these areas do not need any reparation program

but definitely have to be monitored in order to assure at least the same level of customers

satisfaction with those areas.

What definitely has to be implemented is the program for Company X Polish customers in

terms of their satisfaction with work of sales company as well as dealerships representing

the brand in Poland. Four areas have been recognized as those that need improvement and

the vast amount of responsibility for customers satisfaction with these areas lies in hands

of sales company employees as well as the dealer network. The analysis of performance

of manifest variables that create After Sales Service Quality, Value for Money, Costs of

Ownership and Image will be now presented.

The loyalty of customers creates higher value for the company than satisfaction, therefore

the analysis will be conducted according to the strength of areas influence on customers’

loyalty (After Sales service quality 30%, Value for Money 15%, Costs of ownership 15%,

Image 7% – relative local influence).

Taking into consideration the after sales service quality, Company X customers evaluated

all factors creating the overall perception of after sales service below 79% - as presented

in the Figure 7.16. This creates a significant room for improvement in this area meaning

that satisfaction with all elements creating perception of service during customers visits in

the workshop is not satisfactory and significantly decreases customers satisfaction and

loyalty. All manifest variables generating after sales service latent construct have an

importance level of between 9 and 14%. The least significant element according to the

research is the availability of substitute car when customer’s vehicle is being serviced. At

the same time it has very negative evaluation. The recommendation is that Company X

does not have to necessarily take care of this part of post purchase service as its influence

on overall satisfaction with after sales service is at the bottom of the list.

Than in the middle of importance scale we have availability of spare parts with a bit

higher evaluation than in case of substitute car. The logistics issue in terms of proper stock

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management in the logistics center as well as faster delivery of required spare parts should

be monitored but not considered as one of the most important factors.

The most important elements of service that should definitely be improved as they have

the highest influence on customers satisfaction and loyalty and at the same time do not

meet customers requirements and expectations are: willingness to properly inform

customer about required service, professionalism of after-sales representative,

promptitude and timing abidance of service, overall service quality and after-sales service

reception atmosphere. It seems that soft skills training for after sales representatives

having direct contact with customers is needed. The reps should be trained in order to

know what kind of attitude they shall represent in front of the customer meaning that they

should serve as a credible source of information. When having contact with customer the

rep should concentrate on providing as much information as necessary to make sure that

the client knows what needs to be done with his vehicle, how long it will last and how

much it shall cost.

Furthermore the after sales representatives should be trained with respect to their

professional knowledge about technical issues in order to behave professionally when

serving a customer.

The next important factor strongly affecting customers satisfaction and loyalty is the

promptitude of service in terms of quickness of service. This negative evaluation can be

connected to shorts of staff in particular after sales service workshops which cause longer

waiting lines or to the availability of spare parts which has been negatively evaluated by

customers. The whole service logistics process needs to be investigated and parts of the

process which extend the service time have to be either eliminated or accelerated.

Timing abidance is also a significant element in terms of its influence on satisfaction with

after sales service. This can be partly connected to the promptitude of service but in a

large part it is the pressure of customers who during the time when vehicle is in the

service, do not want to wait too long time and force the after sales rep to declare the

earlier vehicle pick up time. In some cases shorts of service staff can also cause the

negative evaluation of this area. To summarize, improvement of promptitude of service

factor requires that employee count is evaluated and discussed with the staff, but also soft

111

skills training could also be valuable in order to train after sales reps to be assertive and to

communicate rather longer than shorter service deadlines.

The atmosphere in the workshop reception room needs improvement too as it is one of the

most important elements of customers service. The client has to feel as someone special

and needs to be treated well. Furthermore if customers like the atmosphere of the

workshop reception it improves their evaluation of the image of the brand meaning that

they feel as someone unique while using the vehicle of the brand.

The overall service quality was evaluated negatively meaning that the quality of service

provided needs to be improved as customers are definitely not satisfied with what is being

done with their vehicles and how well they are served.

Figure 7.16. Satisfaction scores vs. loyalty importance – after sales service quality

6869

70

7172

7374

75

7677

7879

9% 10% 11% 12% 13% 14%

Loyalty importance

Satis

fact

ion

scor

e

Availability of substitute car

Availability of spare parts

Timing abidance

Atmosphere

Professionalism of repWillingness to inform

Promptitude of service

Overall service quality

The value for money construct (figure 7.17) is built out of two elements: price and quality

received. As vehicle quality is a separated from value for money latent construct in the

analysis therefore value for money factor can be simplified to the pricing strategy of

Company X in Poland with respect to the quality of vehicle and service provided. The

area was evaluated close to 75% which is definitely too low score and it needs to be

improved. It is difficult to judge whether the prices of vehicles should be drastically

decreased. However the pricing list modification is required in order to make the price

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positioning against main competitors more acceptable for Company X customers.

Probably customers do not see such a big difference between Company X and other

brands in terms of vehicle quality, sales and after sales service, comfort and functionality

of the vehicles etc. but they see the difference in price positioning. Improvement of this

element could definitely increase customers satisfaction and loyalty against the brand.

However the sales company has to be careful at the same time as price is also the

antecedent of value of the vehicle provided that it offers proper quality and comfort of

usage. Therefore too low pricing can deteriorate value of a brand in eyes of its clients.

Figure 7.17. Satisfaction scores vs. loyalty importance – Value for money

71

72

72

73

73

74

74

75

75

76

49,0% 50,0% 51,0%

Loyalty Importance

Satis

fact

ion

Scor

e

Vehicle quality with respect to its price

Price of the vehicle with respect to its quality

Analyzing evaluation of costs of ownership (figure 7.18) it seems that the lowest score is

given in the areas of after-sales service responsibility and costs of vehicle insurance.

Insurance is the least important factor among the others however the difference in the

importance levels is not that big to definitely ignore this element. Insurance can serve as

first of all attractive sales incentive for customers as well as advertising keyword to attract

customers to the showrooms.

113

Coming back to satisfaction with costs of after sales service it seems like Company X in

Poland has quite a problem with general perception of workshop service. It is not only

expensive but at the same time not satisfactory enough. Again the pricing strategy needs

to be revised in order to make brands of Company X more competitive and maybe some

promotional events decreasing costs of Company X vehicle usage such as free service for

winter and summer holidays could also be introduced.

Figure 7.18. Satisfaction scores vs. loyalty importance – Costs of ownership

60

62

64

66

68

70

72

74

76

78

80

13% 14% 15% 16% 17% 18% 19%

Loyalty Importance

Satis

fact

ion

Scor

e

Costs of insurance

Costs of fuel Overall costs of vehicle usage

Costs of regular service

Costs of repairs

Costs of spare parts

Costs of fuel are not that important comparing to the costs of after sales service however

some inexpensive improvement in this area could also be implemented. Fuel card with a

limit of e.g. 3% of a price of the vehicle given with each car sold may be a good mean for

improving customers satisfaction with costs of ownership. Next idea is to offer a fully

tanked vehicle after each visit to a workshop which costs exceeds e.g. 100 PLN.

Image of a brand (figure 7.19) is also in large portion a responsibility of sales company

locally in particular country. In this case Company X in Poland should definitely increase

its involvement in customers’ satisfaction improvement by e.g. allowing customers to

114

express their opinion about the quality that they receive. The researches such as Brand

Satisfaction Model give the possibility for each customer to speak up and evaluate the

brand in terms of soft service and vehicle quality and comfort that they receive. It gives

the strong feeling to the customers that the brand takes care about them and wants to listen

to their opinions in order to improve its performance and at the same time its clients

satisfaction.

Figure 7.19. Satisfaction scores vs. loyalty importance – Image

68

73

78

83

88

93

8,5% 9,5% 10,5% 11,5% 12,5% 13,5%

Loyalty Importance

Satis

fact

ion

Scor

e

Involvement in social actions

Promotional Visibility (motorshows, sponsoring, advertising)

Environmental care Overall image

Safety assurance

Technological leadership

Stable market position of a brand

Brand involvement in improvement

of customers satisfaction

Making drivers' lives easier

Technological leadership is on the edge of 85% bottom line. Such position can be a result

of the fact that either the competition is quite close to Company X in terms of

technological advancements or Company X customers are not aware of its brand

advantage over competitors. The best solution here is surely better communication of all

most important advantages of Company X vehicles in terms of modern technology used in

them.

The area called “making drivers’ lives easier” also has to be improved and it may be

definitely connected with the above mentioned factor which is technological advantage

over its main competitors.

115

Factors that increase customers evaluation of a brand with regard to its image are: safety

assurance and its stable market position. This areas improve overall score meaning that

Company X vehicles are definitely safe in the eyes of clients, the position of a brand is

very stable on the market and is not deteriorating.

The elements that are of lower importance are environmental care, company’s

involvement in social actions and promotional visibility of a brand in terms of its presence

on motor shows, in advertising campaigns and sponsoring. As the difference in

importance levels is not that significant these above mentioned areas could also be

improved in order to increase the score of overall image perception especially having in

mind that they are some basic factors of company’s presence on particular market.

7.4. Estimation results for Brand Satisfaction Model – 3 segments of customers

The analysis presented in previous chapter is applied to total brand, meaning Company X

customers in general. However there are different groups of customers with different

profiles depending on what vehicle they buy. Different customers have various

demographic characteristics and needs which impact their requirements towards vehicles

they drive. Therefore the authors decided to perform 3 separate analysis based on

different customer groups: Compact vehicles owners, Mid-size vehicles owners and Full-

Size and Large vehicles owners. The aim of the study is to discover main differences

between customer groups which have different requirements for the vehicle they drive as

well as different demographic characteristics and the amount of income they want to

spend on vehicle.

7.4.1. General estimation results for 3 customer segments

The parameter estimates for inner model as well as R square values for all dependent

variables are presented in Figure 7.20, 7.21 and 7.22 for three model groups respectively.

We can see quite different parameter estimates for three vehicles groups. In order to

analyze differences between the customer segments we should firstly take a look at the

comparison of satisfaction scores presented in Table 1.

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Table 1. Latent constructs’ scores for 3 model groups (rescaled to 0-100).

Variable Compact Mid-sizeFull-size and

LargeExpectations 92% 92% 95%

Vehicle Design 89% 90% 92%

Sales quality 88% 89% 88%

Comfort 86% 86% 88%

Vehicle quality 85% 88% 85%

Loyalty 83% 86% 81%

Image 82% 83% 82%

Overall satisfaction 77% 81% 77%

After-sales quality 75% 78% 74%

Value for money 74% 77% 73%

Costs of ownership 67% 67% 70%

Generally, with minor exceptions, the overall evaluation of particular latent areas is

similar concerning the hierarchy of scores meaning that the highest scores for all customer

groups are given to expectations and vehicle design and than to sales service quality,

comfort and functionality, vehicle quality followed by loyalty, image, overall satisfaction,

after sales service quality, value for money and costs of ownership.

Figure 7.20. Results of PLS algorithm application on BSM – Compact vehicles.

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Figure 7.21. Results of PLS algorithm application on BSM – Mid-size vehicles.

Figure 7.22. Results of PLS algorithm application on BSM – Full-size and Large

vehicles.

118

However looking at the Table 1 in more detail, significant differences between evaluation

of particular latent constructs are discovered. First of all some trends are visible if we

compare scores of one variable for all model groups. Rising expectations moving towards

Full-size and Large vehicles customer group are observed what is understandable having

in mind the fact that these clients are wealthiest segment and spend more money on their

vehicles at the same time expecting more from quality and service they will receive.

Secondly, the evaluation of vehicle design is also rising moving from Compact to Large

vehicles group. This also does not require very deep investigation as simply the vehicle

design of more expensive, more luxurious vehicles catches the eyes of most customers.

Finally, similar relationship can be found for all model groups regarding comfort and

functionality of the cars. Larger vehicles are usually more comfortable, better equipped

and because they are usually more expensive they use modern technology what increases

their functionality. In case of costs of ownership the wealthier the customer segment, the

higher the satisfaction with costs of vehicle usage what is natural and does not require any

comment.

Two variables have almost constant satisfaction scores for all groups of customers. Image

scores between 82 and 83 while sales service quality is evaluated at the level of 88 to 89%

which positions this area at the top of the list. Regarding the sales service quality it can be

argued as natural state however in real life its sometimes difficult to train the sales staff in

order to maintain the same and high level of service provided for all customer groups. In

case of Company X this is really a success that the sales staff does not prioritize the

customers who are wealthier and able to spend more money which in the end reach

pockets of sales representatives. The more expensive the vehicle the more money goes to

the person that sold it to the customer. Naturally sales staff would like to earn more

money thus providing better service for those customers who are wiling to buy more

expensive vehicle. Therefore it is a big value of Company X dealer network responsible

for sales service quality which offers high and at the same time similar level of service no

matter how wealthy the customer is.

Analyzing other variables we can also see a strong trend although it does not depend on

the size and price of the vehicle. For vehicle quality, after-sales service quality, value for

money and overall satisfaction as well as loyalty, one group stands out of the crowd. It is a

group of mid-size vehicles customers that on average in all the above mentioned areas

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scores better than other model groups. This means that these vehicles offer higher quality

in terms of dependability, driving quality etc. therefore creating higher value for money

for mid-size vehicles owners. Surprising is the fact that the after sales service quality

received by this group of customers is also higher than for compact cars and large vehicles

owners. Maybe the number of visits to the workshop was lower for the group which could

go in line with higher vehicle quality evaluation meaning that mid-size vehicles customers

were not able to receive so much not satisfactory service from after-sales service

department. Because the score on vehicle quality, value for money and after sales service

quality is higher than in other groups the overall satisfaction as well as loyalty of mid-size

vehicles owners scores also above other model groups.

7.4.2. Total effects analysis – 3 customer segments

Let’s compare the strength of influence of all latent constructs on satisfaction and loyalty

between all customer groups included in the study.

Figure 7.23 presents the influence of every latent variable on overall satisfaction scores

divided into customer segments. It can be observed that in terms of overall satisfaction

generation the customers are quite unanimous. There are 3 exceptions from the rule. First

of all image of a brand is much more important for compact vehicles users than for mid-

size or full-size cars owners, what is in line with customer profile research results. It

seems that customers that buy the least expensive vehicle in Company X portfolio very

much appreciate the image that the brand acquired during its presence on the market. On

the other hand brand image is of little importance for premium customers who buy

expensive vehicles. For these customers the other factors count when it comes to creation

of their overall satisfaction. They are satisfied not due to brand image, but because the

vehicle offers high quality and comfort that also generates higher perceived value.

If value for money factor is analyzed, it can be observed that it is of highest importance

for compact vehicles users and the lowest important for mid-size cars users. Generally

customers who buy compact vehicles of Company X brand expect decent value for money

that they have to pay. This is understandable as, referring to the results of customer profile

study, clients with lowest income are more price sensitive and they require more for what

they pay. On the other hand, value for money factor is of lowest importance for

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satisfaction of owners of mid-size cars, while it is more important for full size and large

cars owners. Mid-size vehicles clients break out of the pattern probably because their

evaluation of vehicle quality is better than in case of other clients. That is why the value

for money factor is not as important for mid size cars owners as for other customer

segments, because they perceive quality as more important driver of their satisfaction than

other customer segments do.

Figure 7.23. Influence of latent constructs on overall satisfaction – comparison between

different customers’ groups

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Moving to vehicle quality, comfort and functionality it seems that customers that pay

more for their vehicles require higher dependability and quality as well as comfort of the

car they drive. The importance of this latent constructs is almost equal for mid-size, full-

size and large vehicles clients (46-49% - vehicle quality, 35% comfort and functionality)

while compact cars users pay less attention to both factors (36% and 30% respectively).

This may be easily explained by the fact that wealthier customers expect higher values in

their products what means that they have to be of good quality and offer decent

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functionality as well as comfort of driving. On the other hand compact vehicles users pay

more attention to the value for money that is offered by their products as well as image of

the brand. Due to premium character of a brand the “compact” customers pay more for the

Company X vehicles comparing to direct competition thus expecting higher perceived

value and proper image of the brand they represent. .

Let’s now move on to analysis of different satisfaction areas influence on customers

loyalty. Taking a closer look at Figure 7.24 it seems that loyalty construct is definitely

much more complicated than satisfaction and requires deeper insight.

Among all factors, only vehicle design and overall satisfaction are the areas which have

similar importance level for all customer groups.

Analyzing the importance of after sales service quality we discover that the more

customers pay for their vehicles the less they require from after sales service in order to

become loyal to the brand and dealer. For ”mid-size”, “full-size” and “large” clients there

are 2 other factors that they pay special attention too – vehicle quality and comfort and

functionality. Costs of vehicle ownership and usage are of course more important for

“compact” customers than for “mid-size” clients and the least important for those clients

who pay the most for their cars. This can be easily explained by different income levels

for the 3 analyzed clients’ groups, what was also observed in customer profile research.

Moving to expectations it seems obvious that higher segments clients demand more from

the vehicle and the brand what was confirmed by the Brand Satisfaction Model study. The

importance of Image against Loyalty goes in line with Image importance against Overall

Satisfaction and can be explained in the same manner.

There is a big gap between strength of influence of sales service quality on customers

loyalty between customers of compact vehicles and the rest. “Mid-size”, “full-size” and

“large” customers demand much more from sales service quality and position this factor

as the second important for their loyalty towards a brand. At the same time compact cars

users diminish the importance of this factor placing it behind vehicle quality, comfort and

functionality, after-sales service quality and value for money. This discrepancy gives the

marketers quite important message that the “mid-size” and “full-size and large” customers

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need to receive extraordinary sales service in order to make them loyal to the Company X

brand.

Figure 7.24. Influence of latent constructs on loyalty – comparison between different

customers’ groups

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Finishing the loyalty importance analysis it is discovered that value for money is

definitely of highest importance for “compact” clients but at the same time it is the least

important for “mid-size” customers. Clients of higher segments place the importance of

this element somewhere in between the scores for two other groups. Again the lowest

importance of this area for mid-size vehicle users can be explained by the highest quality

level of vehicles they drive comparing to the rest of model groups.

To sum up we discovered definitely different profiles of the three analyzed groups of

clients. They differ not so much in terms of their definition of overall satisfaction however

differences with regard to loyalty generation are significant in many aspects of customers

satisfaction. We can in some part merge the mid-size, full-size and large vehicles’ clients

but the “compact” customers differ a lot from the others. While “compact” clients are

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more price sensitive and pay a lot of attention to value for money of their vehicle as well

as to the after-sales service quality they receive in the workshop, the remaining two

customer segments require more from vehicle quality and especially from sales service

quality. These findings are in line with customer profile research which revealed, than

compact car customers are more price sensitive and more often than other customer

segments search for vehicles, which are functional and economical.

7.4.3. Satisfaction vs. importance analysis - 3 clients segments - inner model

Let’s analyze differences between the 3 model groups on a satisfaction vs. importance

analysis figures. As discussed earlier we discovered 4 areas that definitely need

improvement with regard to total brand. It will be good to know whether the same rule

applies to all customers or there are some differences in approach to increase satisfaction

and loyalty of customers. There might be either one strategy which could be applied to all

customers segments or more strategies may arise in order to better serve needs of

customers who, depending on the segment, may have different requirements against the

brand performance. This part of analysis will help understand the differences between

customers of Company X in Poland not only through comparison of the scores of

satisfaction for specified areas but also by discovering different priorities lists for all the

elements included in the study.

The graphical representation of satisfaction versus importance analysis will not include

the division of matrix into important and not important areas due to the fact that not all of

the areas are under direct supervision of neither the headquarter nor sales company.

Therefore further analysis will have to be adjusted to either sales company or headquarter

perspective. The authors concentrate on performance of sales company thus such analysis

should include only those factors that are directly controlled by Company X in Poland.

Figures 7.25 to 7.30 present satisfaction scores for all latent variables versus their

influence on either satisfaction or loyalty and are divided into 3 customers segments:

Compact , Mid-size and Full-size and large vehicles owners. The analysis will allow for

distinguishing important areas creating satisfaction and loyalty of customers in 3

segments.

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Figure 7.25. Satisfaction scores vs. satisfaction importance analysis – Compact vehicles

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Figure 7.26. Satisfaction scores vs. loyalty importance analysis – Compact vehicles

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Figure 7.27. Satisfaction scores vs. satisfaction importance analysis – Mid-size vehicles

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Figure 7.28. Satisfaction scores vs. loyalty importance analysis – Mid-size vehicles

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Figure 7.29. Satisfaction scores vs. satisfaction importance analysis – Full-size and large

vehicles

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Figure 7.30. Satisfaction scores vs. loyalty importance analysis – Full-size and large

vehicles

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Division of the analysis into different customer segments does not significantly change the

overall picture. Again the most important is loyalty but the loyalty is in a large part

created by overall satisfaction. Fortunately outcome from satisfaction importance and

loyalty importance analysis is the same. There are definitely four areas that score much

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below the minimum level of 85%. After sales service quality, value for money, costs of

ownership and image need to be taken care of in order to improve overall satisfaction and

loyalty of Company X customers in Poland. The strength of influence on satisfaction and

loyalty generation is not that significant compared to e.g. vehicle quality or comfort and

functionality however as discussed earlier this is the scope of responsibility for sales

company in Poland.

The other factors beside sales service quality (where score is high enough and positively

influences satisfaction and loyalty) are beside the direct responsibility of sales company

representing brand in Poland. Furthermore the score on those factors lies above the red

line of 85% thus the improvement of brand performance in this respect is definitely more

difficult to achieve.

The segmentation of customers does not produce different results in terms of which areas

score the lowest and have quite strong influence on satisfaction and loyalty creation. The

only difference is prioritization of the four areas. For all groups of customers analyzed in

the study between the four analyzed areas for improvement action the most important is

the quality of after-sales service. Value for money is the second important element with

exception of mid-size vehicles customers that place this element at the end of the list.

Very close to value for money factor with regard to its strength of influence lies the costs

of ownership variable. The least important element is the image of a brand.

7.4.4. Satisfaction vs. importance analysis - 3 customer segments –outer model

In order to roll out some action plan the detailed analysis needs to be performed

analogically to the one carried out for the total brand.

Analyzing after sales service quality, for all customer groups professionalism of sales

representatives, willingness to properly inform customers, overall service quality,

promptitude of service and timing abidance are the most important elements generating

the largest part of overall after-sales service satisfaction. For mid-size vehicles customers

the atmosphere of showroom is placed at the 6th position of importance list while for the

two other model groups it is one of the most important elements. Availability of spare

parts is in the middle range of strength of influence for all customers. At the bottom of

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the list for after sales service quality is the availability of substitute vehicle. It is the least

important area and at the same time it scores the lowest for mid-size and full-size vehicles

clients which is understandable as the more customers spend on their vehicle the more

service they require if their car visits the workshop.

If it comes to evaluation of customers satisfaction with particular elements of after-sales

service it occurs that all of them score much below the minimum level of 85% which

means that they all need to be taken care of however with different prioritization list for

different model ranges. The most satisfied customers with after-sales service are the ones

who drive the mid-size vehicles. However the score is not satisfactory enough to resign

from reparation program. Therefore the action plan needs to be invented in order to

improve customers’ satisfaction with service offered by after-sales department at the

dealerships with accordance to the presented priorities list. It seems that a small

“revolution” is needed in order fix all the problems as there is no positive sign of service

which is satisfactory for the clients.

Figure 7.31. Satisfaction score vs. loyalty importance – After sales service– Compact

vehicles

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Figure 7.32. Satisfaction score vs. loyalty importance – After sales service – Mid-size

vehicles

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Figure 7.33. Satisfaction score vs. loyalty importance – After sales service – Full-size and

large vehicles

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Moving on to value for money evaluation there are two elements that create it. It is

generally perceived product quality with regard to its price. As the perception of product

quality itself and its comfort and functionality is good enough the only element that needs

improvement is the level of price. Generally customers perceive Company X vehicles as

being too expensive with regard to the overall quality they offer. Therefore some re-

pricing program might be useful in order to improve the perceived value of cars. This

element might be also dangerous as too much intervention into pricing policy may

diminish the value of particular brand vehicles. Price is also the factor that creates value of

the car thus it needs to be carefully tailored to each model against competition. The value

for money score is the lowest for full-size and large vehicles owners than for compact cars

and the highest for mid-size range. Therefore it seems that pricing policy has to be

definitely adjusted for the least and the most expensive vehicles and only slightly for the

middle sized cars.

Figure 7.34. Satisfaction score vs. loyalty importance – Value for money– Compact, Mid-

size, Full-size and large vehicles

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Vehicle quality with respect to its price - Full-size and large

Price of the vehicle with respect to its quality - Full-size and large

Vehicle quality with respect to its price - Compact

Price of the vehicle with respect to its quality - Compact

Vehicle quality with respect to its price - Mid-size

Price of the vehicle with respect to its quality - Mid-size

Moving to detailed analysis of costs of ownership, it is apparent that comparing to results

for the total brand there are not many differences. For all model groups the highest

importance and at the same time the lowest scores are given for costs of regular service,

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costs of spare parts and repairs. After sales service pricing list needs to be adjusted in

order to improve customers perception of this area and at the end their loyalty.

Figure 7.35. Satisfaction score vs. loyalty importance – Costs of ownership – Compact

vehicles

60,0%62,0%64,0%66,0%68,0%70,0%72,0%74,0%76,0%78,0%

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Costs of repairs


Figure 7.36. Satisfaction score vs. loyalty importance – Costs of ownership – Mid-size

vehicles

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Costs of insurance

Costs of fuel Overall costs of vehicle usage


Costs of repairs


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Furthermore costs of fuel are the least important for clients of full-size and large vehicles

which is understandable. The strength of their importance rises while moving towards less

expensive segments of cars. Costs of insurance are the least important for compact and

mid-size vehicles customers and move one position up in the list for full-size and large

vehicles owners.

To sum up general evaluation of costs of ownership it seems that first thing that should be

improved is the pricing policy of after sales service department. This result proves

negative evaluation of this area in total. Next elements that could improve customers

satisfaction and loyalty lie in the area of responsibility of sales department. Costs of fuel

or insurance may be decreased by incentive campaigns where i.e. fuel card with particular

limit or free insurance could be given to customers at the purchase of the vehicle.

Figure 7.37. Satisfaction score vs. loyalty importance – Costs of ownership – Full-size

and large vehicles

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Costs of insurance

Costs of fuel

Overall costs of vehicle usage

Costs of regular serviceCosts of repairs


In terms of image, the company involvement in improvement of customers satisfaction

definitely needs to be increased. Such researches as brand satisfaction model give clients

the possibility to speak up and express their opinion about the brand and the offered

products. This area is not evaluated as satisfactory enough and for all model groups lies at

the top of the importance list. Customers evaluation of sales company involvement in

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actions that make the driver’s lives easier scores also below 85% and is one of the most

important elements creating brand image. As the area is not precise it needs to be

investigated in more details by maybe a small, one time conversation with the group of

customers.

Stable market position and safety and technological leadership are also important

elements for all model groups however their score lies above minimum level of 85% thus

they need no improvement.

Figure 7.38. Satisfaction score vs. loyalty importance – Image – Compact vehicles

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Environmental care Overall image

Safety assurance






Safety assurance gives very interesting field for analysis. The score for each model range

is one of the highest and also does not need any reparation action. However for compact

vehicles owners it is one of the most important factors, while for mid-size vehicles clients

is the least important one and for full-size and large vehicles customers is placed in the

middle of importance scale. These findings are in-line with customer profile research,

which pointed out that safety is much more important factor for compact cars owners,

than for remaining customer segments. Environmental care is not that much important for

“compact” clients while it moves to the middle importance for the two other model

groups. As it scores below 85% in each case it requires some action to be taken. One of

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the actions suggested would be more news about ecological properties of Company X

vehicles given to press and media in order to improve brand image in this respect.

Figure 7.39. Satisfaction score vs. loyalty importance – Image – Mid-size vehicles

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Figure 7.40. Satisfaction score vs. loyalty importance – Image – Full-size and large

vehicles

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Involvement in social actions is evaluated as the worst element of brand image however

its importance is the lowest for all models. The company may think about some action

plan in this area provided that all other elements that have higher priority are taken care

of.

Generally promotional visibility of a brand is of middle importance for lower segments

customers and is the least important for full-size and large vehicles owners. As its score is

below 85% in each case the company may introduce some program that will improve

brand visibility in media, press and outdoor visuals especially in the two lowest segments.

To sum up the analysis of image it seems that beside safety assurance, customers

evaluation of brand stability and technological leadership, the company needs to take care

of all the other elements that create brand image. The priority list is a bit different for

different model ranges however it can be merged in order to save resources and achieve a

goal of image improvement.

7.4.5. Summary of analysis for 3 customer segments

The three analyzed groups of customers present a bit different approach to purchasing and

using a vehicle. While their satisfaction is generated in quite similar manner, the loyalty

generation is much more complicated. The owners of compact vehicles place more

importance in Value for Money and Costs of Ownership meaning that they are simply

more price/costs sensitive. Such result is definitely understandable as limited amount of

resources forces the more cost saving approach while deciding on vehicle purchase.

Furthermore After-sales service is the most important element for compact cars users. The

other two groups of customers place less importance in this area.

Mid-size, Full-size and Large vehicles owners are more similar to each other compared to

the compact cars customers. Instead of placing more importance to after-sales service

quality, costs of ownership and Value for money, their loyalty is in a larger part generated

by better sales service quality, vehicle quality as well as comfort and functionality.

In order to implement some action plan the detailed analysis of the four areas that need

improvement presented above in the chapter should be deeply investigated. Some detailed

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areas score better or lower for different customer groups. Furthermore the importance of

the areas is different for the three analyzed customer segments. All in all, the action plan

for the total brand has to be adjusted according to differences in results achieved in the

analysis. The acquired intelligence about levels of importance should be made well-

known across the whole company in order to prioritize or disregard taken operations.

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CONCLUSIONS AND RECOMMENDATIONS

After detailed analysis of Brand Satisfaction Model results the following conclusions and

recommendations arisen:

- The structure of BSM evolving mainly from ECSI and JD Power methodology for

automotive industry is comprehensive, statistically well grounded and offers a great

portion of knowledge for Company X in Poland. It covers all important aspects of

customer satisfaction as total experience with a brand. The BSM not only covers

evaluation of company’s performance in different areas but, what is most important,

distinguishes the importance of specified areas to overall satisfaction and loyalty

generation.

- The BSM model discovered that there are significant differences in how satisfaction and

loyalty of customers are created. Satisfaction concept in the automotive industry is less

complicated and is based mainly on vehicle quality, comfort and functionality which

generate over 75% of customers satisfaction. On the other hand client’s loyalty is much

more complex. Importance of vehicle quality, comfort and functionality decreases while

at the same time the importance of sales and after sales service quality as well as costs of

ownership drastically increases. Therefore there are not 2 but 5 factors that should be

taken into account when implementing loyalty improvement programs.

- There are different perceptions of satisfaction and loyalty concepts between the 3

specified segments of customers. Compact vehicles users are much more price and costs

sensitive. They also pay stronger attention to the image of a brand and post-purchase

service they receive. Mid-size vehicles users are definitely closer in terms of their profile

to the third group of customers however they are more vehicle comfort and quality

oriented while at the same time do not expect so high value for money as other clients.

The full-size and large vehicles owners are definitely the least price and costs sensitive.

Vehicle quality, comfort and functionality and sales service quality are the most important

elements strongly affecting the level of their loyalty.

- Company X should definitely conduct the Brand Satisfaction Model study at least on a

yearly basis. The knowledge should be regularly spread across the entire organization and

management should make sure that all employees understand their customers according to

BSM findings. Marketing, sales and PR actions should always take into consideration the

recommendations of BSM in order to create more satisfied and loyal customers. The

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operations should be adjusted according to different customer profiles analyzed in the

study as clients from different segments have different priorities lists. Therefore all

measures such as incentive actions, communication, improvement of customer service

processes should be targeted at specific wants and needs of particular segment.

- After the Brand Satisfaction Model was conducted, analyzed and the acquired knowledge

was spread out across the whole company, the reparation program for after-sales service

quality has started. First improvements are already visible in higher scores (+2 pp) for CSI

in after-sales service quality. According to BSM findings the prioritization of actions has

been set which helped to concentrate on those areas that have the strongest influence on

quality of after-sales service. This is a short term success which hopefully will turn into

long term trend.

- The next valuable step would be to propose the BSM as a unified tool for measuring

satisfaction and loyalty of customers in the whole automotive sector in Poland. The model

could be proposed to the Board of Directors of Polish Official Association of Automotive

Importers in order to create a comprehensive platform for comparison of different brands

performance in a field of customer satisfaction. Such platform would be not only valuable

for automotive companies present on Polish markets but also for customers which would

benefit from higher level of service provided. This step could ignite the positive

improvement of competitiveness between automotive producers operating in Poland.

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REFERENCES

ANDERSON, E.W., FORNELL, C., LEHMANN, D.R. (1994): “Customer satisfaction,

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142

APPENDICES

Appendix 1.

Latent Variables Correlation matrix (First Version of BSM)

After-sales qualit

y

Comfort

Costs of

ownership

Expectations

Image Loyal

ty


Sales qualit

y

Value for

money

Vehicle

Design

Vehicle

quality

After-sales

quality

1,000000

Comfort 0,462303

1,000000

Costs of ownersh

ip

0,472885

0,540268

1,000000

Expectations

0,195676

0,419443

0,233657

1,000000

Image 0,467905

0,723528

0,496245

0,367943

1,000000

Loyalty 0,577201

0,544896

0,443039

0,199537

0,607374

1,000000

Overall satisfact

ion

0,473978

0,594959

0,480412

0,270644

0,684018

0,665158

1,000000

Sales quality

0,436633

0,541961

0,375076

0,320457

0,481802

0,551462

0,348733

1,000000

Value for

money

0,561808

0,643671

0,531382

0,298537

0,687365

0,655578

0,773088

0,405219

1,000000

Vehicle Design

0,271908

0,668756

0,389303

0,397870

0,567409

0,400030

0,412773

0,462821

0,431422

1,000000

Vehicle quality

0,507657

0,744820

0,518336

0,287704

0,735878

0,671108

0,841218

0,422455

0,807373

0,568071

1,000000

143

Appendix 2. Results of Bootstrapping algorithm application on the final structure of the Brand Satisfaction Model (sample size 346, number of iterations 500) Outer Model T-Statistic

After-sales

quality

Comfort

Costs of

ownership

Expectation

s

Image

Loyalty

Overall

satisfaction

Sales qualit

y

Value for

money

Vehicle Design

Vehicle quality

comfort

23,347965

comfort%a

30,133715

comfort%b

19,462846

comfort%c

16,789108

comfort%d

9,561638

comfort%e

16,056396

comfort%f

13,349930

comfort%g

10,380644

comfort%h

8,818462

costs 18,045577

costs%a

12,355443

costs%b

13,254982

costs%c

43,047303

costs%d

41,803177

costs 40,78

144

%e 8004

design 58,4998

48

design%a

41,3434

76

design%b

40,3026

58

design%c

58,7475

64

design%d

47,2310

27

image 17,033243

image%a

14,581061

image%b

17,074691

image%c

27,029983

image%d

24,127112

image%e

9,084976

image%f

9,776476

image%g

11,197843

image%h

20,873509

loyalty1

35,316365

loyalty2

32,050081

loyalty3

28,204140

loyalty4

15,118128

oczek%d

23,318976

oczek%f

23,676596

oczek%g

33,347890

sales 30,009971

sales 26,46

145

%a 1719

sales%b

29,926009

sales%c

26,380701

sales%d

33,180027

sales%e

34,553519

sales%f

16,711855

sales%g

15,773017

sales%h

16,193364

sales%i

15,716443

sales%j

12,893444

sat1 126,703100

sat1a 124,851939

sat1b 148,710726

service 69,8193

07

service%a

69,832265

service%b

87,335571

service%c

36,940796

service%d

14,434900

service%e

25,797621

service%f

58,003685

service%g

35,655748

value1 472,423

591

value2 489,753

636

vehqua 47,9541

146

l 61

vehqual%a

31,6665

12

vehqual%b

11,9413

13

vehqual%c

10,9076

35

vehqual%d

14,5858

02

vehqual%e

19,9560

50

vehqual%f

20,4257

33

vehqual%g

12,2437

94

Path Coefficients (Mean, STDEV, T-Values)

Original

Sample (O) Sample

Mean (M)

Standard Deviation (STDEV)

Standard Error

(STERR)

T Statistics (|O/STERR|)

After-sales quality -> Loyalty

0,238271 0,239061 0,072230 0,072230 3,298767

After-sales quality -> Value for money

0,187820 0,187318 0,044108 0,044108 4,258204

Comfort -> Vehicle quality

0,747348 0,747459 0,033822 0,033822 22,096331

Costs of ownership -> After-sales quality

0,483602 0,485781 0,044575 0,044575 10,849238

Expectations -> Sales quality

0,325988 0,332319 0,055971 0,055971 5,824281

Image -> Expectations

0,369774 0,374751 0,059031 0,059031 6,264093

Image -> Value for money

0,167117 0,171554 0,054613 0,054613 3,059988

Overall satisfaction -> Loyalty

0,447200 0,444217 0,076290 0,076290 5,861885

Sales quality -> Loyalty

0,294576 0,299933 0,067905 0,067905 4,338093

Value for money -> Overall satisfaction

0,297836 0,298635 0,069204 0,069204 4,303737

Vehicle Design -> Image

0,224727 0,222102 0,061789 0,061789 3,637015

Vehicle quality -> Image

0,603007 0,602738 0,051742 0,051742 11,654194

147

Vehicle quality -> Overall satisfaction

0,591712 0,589664 0,062870 0,062870 9,411712

Vehicle quality -> Value for money

0,585819 0,579589 0,060972 0,060972 9,607931

Total Effects (Mean, STDEV, T-Values)

Original

Sample (O) Sample

Mean (M)

Standard Deviation (STDEV)

Standard Error

(STERR)

T Statistics (|O/STERR|)

After-sales quality -> Loyalty

0,263287 0,263663 0,068598 0,068598 3,838100

After-sales quality -> Overall

satisfaction 0,055940 0,055355 0,016876 0,016876 3,314835

After-sales quality -> Value for money

0,187820 0,187318 0,044108 0,044108 4,258204

Comfort -> Expectations

0,166641 0,168877 0,031725 0,031725 5,252745

Comfort -> Image 0,450656 0,450739 0,045892 0,045892 9,819875

Comfort -> Loyalty 0,282105 0,281160 0,050080 0,050080 5,633063

Comfort -> Overall satisfaction

0,595041 0,593675 0,032774 0,032774 18,155782

Comfort -> Sales quality

0,054323 0,056662 0,016462 0,016462 3,299916

Comfort -> Value for money

0,513122 0,510928 0,037349 0,037349 13,738612

Comfort -> Vehicle quality

0,747348 0,747459 0,033822 0,033822 22,096331

Costs of ownership -> After-sales quality

0,483602 0,485781 0,044575 0,044575 10,849238

Costs of ownership -> Loyalty

0,127326 0,128075 0,035859 0,035859 3,550800

Costs of ownership -> Overall

satisfaction 0,027052 0,026942 0,008732 0,008732 3,098027

Costs of ownership -> Value for money

0,090830 0,091187 0,023729 0,023729 3,827742

Expectations -> Loyalty

0,096028 0,099249 0,026947 0,026947 3,563543

Expectations -> Sales quality

0,325988 0,332319 0,055971 0,055971 5,824281

Image -> Expectations

0,369774 0,374751 0,059031 0,059031 6,264093

Image -> Loyalty 0,057767 0,060417 0,015713 0,015713 3,676356

148

Image -> Overall satisfaction

0,049773 0,051291 0,020562 0,020562 2,420635

Image -> Sales quality

0,120542 0,125779 0,033990 0,033990 3,546394

Image -> Value for money

0,167117 0,171554 0,054613 0,054613 3,059988

Overall satisfaction -> Loyalty

0,447200 0,444217 0,076290 0,076290 5,861885

Sales quality -> Loyalty

0,294576 0,299933 0,067905 0,067905 4,338093

Value for money -> Loyalty

0,133192 0,133208 0,040312 0,040312 3,304033

Value for money -> Overall satisfaction

0,297836 0,298635 0,069204 0,069204 4,303737

Vehicle Design -> Expectations

0,083098 0,082224 0,023415 0,023415 3,548991

Vehicle Design -> Image

0,224727 0,222102 0,061789 0,061789 3,637015

Vehicle Design -> Loyalty

0,012982 0,013184 0,004496 0,004496 2,887577

Vehicle Design -> Overall satisfaction

0,011185 0,011109 0,004972 0,004972 2,249745

Vehicle Design -> Sales quality

0,027089 0,027531 0,009785 0,009785 2,768330

Vehicle Design -> Value for money

0,037556 0,037089 0,013870 0,013870 2,707606

Vehicle quality -> Expectations

0,222977 0,225960 0,041241 0,041241 5,406681

Vehicle quality -> Image

0,603007 0,602738 0,051742 0,051742 11,654194

Vehicle quality -> Loyalty

0,377475 0,376180 0,064792 0,064792 5,825977

Vehicle quality -> Overall satisfaction

0,796203 0,794373 0,028609 0,028609 27,830996

Vehicle quality -> Sales quality

0,072688 0,075799 0,021703 0,021703 3,349242

Vehicle quality -> Value for money

0,686592 0,683642 0,040862 0,040862 16,802540

149

Appendix 3. Results of PLS algorithm application on the final structure of the Brand Satisfaction Model – Total Brand (Path Weighting Scheme, Mean replacement algorithm for missing values, Mean 0 and Var 1 data metric, Abort Criterion 1.0E-5, Initial Weights 1.0)

Quality Criteria

Overview

AVE Composite Reliability

R Square

Cronbachs Alpha

Communality Redundancy

After-sales quality

0,743979 0,958390 0,233871 0,949202 0,743979 0,172559

Comfort 0,482429 0,892422 0,864926 0,482429

Costs of ownership

0,610747 0,902457 0,870282 0,610747

Expectations 0,690098 0,869728 0,136733 0,776171 0,690098 0,094039

Image 0,495642 0,897251 0,570014 0,872570 0,495642 0,102415

Loyalty 0,677321 0,893289 0,595556 0,840668 0,677320 0,148198


0,921945 0,972553 0,721920 0,957658 0,921945 0,342770

Sales quality 0,596738 0,941729 0,106268 0,931259 0,596738 0,064057

Value for money

0,975887 0,987796 0,690302 0,975291 0,975887 0,171579

Vehicle Design 0,808352 0,954709 0,940627 0,808352

Vehicle quality 0,544042 0,904136 0,558528 0,878112 0,544042 0,306066

Cross Loadings

After-

sales

quality

Comfort

Costs of

ownership

Expectation

s

Image

Loyalty

Overall

satisfactio

n

Sales qualit

y

Value for

money

Vehicle Design

Vehicle quality

comfort 0,415183

0,770665

0,404223

0,328513

0,657844

0,598381

0,626970

0,377897

0,642243

0,522135

0,728104

comfort%a

0,354047

0,793244

0,430350

0,322557

0,622905

0,434095

0,518745

0,415753

0,566367

0,521415

0,631213

comfort%b

0,332936

0,714081

0,333370

0,376840

0,507730

0,306953

0,356747

0,473658

0,428011

0,492300

0,496822

comfort%c

0,27680

0,734312

0,295233

0,345748

0,476674

0,347658

0,374541

0,467008

0,400978

0,567581

0,507877

150

9

comfort%d

0,300580

0,627962

0,279222

0,257976

0,314571

0,277699

0,330457

0,351621

0,353677

0,455456

0,454317

comfort%e

0,311307

0,725196

0,414829

0,245186

0,499085

0,330134

0,350544

0,311385

0,406373

0,439208

0,475461

comfort%f

0,251195

0,687559

0,398984

0,227010

0,454725

0,327627

0,343565

0,303355

0,360940

0,438660

0,460855

comfort%g

0,279274

0,582573

0,357147

0,228855

0,431754

0,288484

0,322177

0,325045

0,330619

0,314690

0,371115

comfort%h

0,329279

0,580688

0,295748

0,251586

0,451390

0,335876

0,333032

0,343880

0,376734

0,394746

0,411571

costs 0,340566

0,524954

0,737651

0,207349

0,478685

0,374383

0,437970

0,345899

0,462975

0,416896

0,492386

costs%a

0,264699

0,452463

0,656791

0,231846

0,411347

0,318954

0,393485

0,335405

0,394696

0,391963

0,433479

costs%b

0,275724

0,376959

0,636457

0,176097

0,343324

0,248807

0,279896

0,240078

0,392383

0,232566

0,340275

costs%c

0,491574

0,456671

0,867725

0,188785

0,428528

0,397181

0,424120

0,284023

0,474482

0,304713

0,450861

costs%d

0,433000

0,348362

0,877533

0,160271

0,324645

0,370097

0,377997

0,271003

0,392683

0,227527

0,373318

costs%e

0,394622

0,314541

0,872290

0,131860

0,282688

0,331793

0,290175

0,242410

0,336733

0,206015

0,288161

design 0,229239

0,600900

0,331491

0,363685

0,528830

0,343476

0,406151

0,455968

0,410713

0,919560

0,546477

design%a

0,198722

0,571377

0,292561

0,405965

0,457387

0,296767

0,299219

0,411820

0,346832

0,899103

0,456093

design%b

0,291491

0,613764

0,306746

0,340915

0,517063

0,390298

0,414257

0,443990

0,424585

0,881753

0,569434

design%c

0,234516

0,620817

0,335826

0,371381

0,535218

0,379453

0,354769

0,399881

0,390044

0,921550

0,519393

design%d

0,262882

0,601991

0,369807

0,335811

0,523198

0,371789

0,362871

0,363611

0,353926

0,872376

0,486892

151

image 0,397550

0,487995

0,386380

0,218654

0,701045

0,562129

0,780180

0,291337

0,633681

0,293073

0,683729

image%a

0,283872

0,592018

0,326940

0,301642

0,704244

0,393883

0,441665

0,328708

0,487133

0,482871

0,557372

image%b

0,353776

0,556210

0,305367

0,303942

0,731372

0,424540

0,491362

0,333849

0,515819

0,441912

0,556405

image%c

0,337251

0,600184

0,338403

0,302684

0,798033

0,418049

0,474734

0,349939

0,525782

0,499644

0,557637

image%d

0,428350

0,567990

0,392895

0,298147

0,801905

0,540814

0,523949

0,347597

0,545508

0,457748

0,591331

image%e

0,213286

0,353444

0,288737

0,162197

0,571081

0,310326

0,300137

0,287903

0,301389

0,284767

0,313185

image%f

0,264687

0,363756

0,323750

0,226507

0,589476

0,251352

0,256501

0,335371

0,296640

0,314730

0,273876

image%g

0,279573

0,448949

0,272204

0,230241

0,641581

0,264844

0,355340

0,350556

0,348369

0,365722

0,363895

image%h

0,333433

0,518644

0,358198

0,269058

0,757166

0,488783

0,484440

0,426619

0,524712

0,442051

0,553281

loyalty1 0,483405

0,542229

0,422210

0,165258

0,654117

0,858884

0,730237

0,350103

0,708825

0,419505

0,717310

loyalty2 0,491248

0,393705

0,360559

0,150659

0,388519

0,849768

0,409149

0,601351

0,447147

0,284613

0,443346

loyalty3 0,462433

0,489677

0,399238

0,162518

0,597794

0,832810

0,668537

0,302142

0,643657

0,353262

0,640383

loyalty4 0,468023

0,323256

0,241284

0,160352

0,284187

0,745602

0,320568

0,599213

0,299679

0,233010

0,339920

oczek%d

0,208939

0,387432

0,169969

0,819162

0,317313

0,223781

0,281840

0,273308

0,278932

0,344653

0,275686

oczek%f

0,124990

0,292288

0,175901

0,812377

0,288441

0,112014

0,170220

0,214761

0,245670

0,248257

0,207826

oczek%g

0,138563

0,353935

0,213511

0,859832

0,314003

0,142032

0,203527

0,314813

0,209067

0,397306

0,229824

sales 0,36 0,45 0,252 0,246 0,397 0,528 0,316 0,822 0,3822 0,3493 0,350412

152

5264

5753 875 057 370 009 121 780 28 66

sales%a

0,327842

0,423849

0,298947

0,287025

0,336650

0,419545

0,248279

0,811570

0,295502

0,362691

0,291633

sales%b

0,328393

0,381770

0,208227

0,296067

0,315855

0,357203

0,225193

0,821681

0,288470

0,351713

0,277101

sales%c

0,305046

0,399836

0,286708

0,263665

0,321495

0,392029

0,252964

0,815307

0,290497

0,385053

0,292211

sales%d

0,270273

0,389058

0,294132

0,261081

0,319880

0,411527

0,206702

0,816170

0,236789

0,450888

0,277261

sales%e

0,276229

0,406462

0,271066

0,308866

0,329426

0,383189

0,199607

0,829765

0,265471

0,379245

0,281593

sales%f 0,308260

0,403858

0,212616

0,270649

0,346995

0,417746

0,205749

0,808609

0,273074

0,377013

0,296421

sales%g

0,404361

0,472152

0,332306

0,249525

0,450652

0,427141

0,283768

0,695434

0,352868

0,344120

0,397562

sales%h

0,377200

0,394668

0,312984

0,201336

0,420483

0,450126

0,303961

0,694660

0,314624

0,308830

0,325406

sales%i 0,365871

0,454564

0,324306

0,197376

0,421795

0,395518

0,316973

0,702338

0,356275

0,349571

0,400534

sales%j 0,330599

0,379938

0,238499

0,180078

0,376948

0,460754

0,339650

0,648593

0,323825

0,257665

0,371654

sat1 0,417867

0,556977

0,430503

0,227884

0,654572

0,635319

0,958058

0,337111

0,736771

0,397883

0,801064

sat1a 0,491572

0,570757

0,468881

0,264398

0,639015

0,634799

0,955991

0,315372

0,737137

0,401569

0,777754

sat1b 0,457392

0,571887

0,445007

0,271523

0,654514

0,634422

0,966457

0,334284

0,752872

0,383440

0,814336

service 0,910850

0,397577

0,432903

0,159438

0,418893

0,534221

0,448605

0,361303

0,542832

0,226392

0,459934

service%a

0,911145

0,376071

0,430566

0,126537

0,421646

0,540981

0,429138

0,376452

0,534953

0,197169

0,449369

service%b

0,93124

0,399419

0,415085

0,163067

0,425608

0,551151

0,446226

0,371266

0,529704

0,235909

0,457422

153

0

service%c

0,884382

0,359159

0,362684

0,226747

0,373055

0,499078

0,336338

0,391197

0,427578

0,208134

0,362109

service%d

0,664849

0,338446

0,371706

0,140057

0,347030

0,413316

0,276660

0,337838

0,339494

0,217735

0,309927

service%e

0,796449

0,441042

0,433435

0,180463

0,423007

0,448083

0,447569

0,372279

0,492849

0,311935

0,485847

service%f

0,904052

0,467676

0,495106

0,161749

0,432259

0,494987

0,452318

0,394942

0,519078

0,264389

0,498021

service%g

0,865445

0,394507

0,384298

0,166703

0,363543

0,489400

0,405165

0,380300

0,454930

0,216542

0,439719

value1 0,563265

0,640399

0,515694

0,284279

0,675551

0,650288

0,757064

0,400800

0,987803

0,426308

0,793564

value2 0,547027

0,622089

0,506996

0,294617

0,675118

0,637679

0,770308

0,389200

0,987937

0,422385

0,793294

vehqual 0,462767

0,592375

0,409694

0,212044

0,677228

0,644525

0,899455

0,351119

0,759266

0,401898

0,863618

vehqual%a

0,502939

0,515642

0,459355

0,201739

0,581245

0,589465

0,813009

0,255949

0,703783

0,325862

0,812594

vehqual%b

0,261506

0,451192

0,314975

0,106089

0,445967

0,287377

0,401476

0,218691

0,430503

0,360262

0,600098

vehqual%c

0,354099

0,549219

0,327104

0,225812

0,470070

0,393356

0,466195

0,378855

0,481796

0,452400

0,659822

vehqual%d

0,384045

0,606278

0,351052

0,239984

0,525130

0,409600

0,486742

0,306893

0,503818

0,512430

0,710773

vehqual%e

0,323608

0,542878

0,314562

0,191736

0,536490

0,497961

0,622123

0,289875

0,612721

0,418084

0,769276

vehqual%f

0,372208

0,605111

0,371688

0,247211

0,519143

0,537681

0,588587

0,359426

0,643092

0,449720

0,767180

vehqual%g

0,273064

0,568867

0,382380

0,274130

0,533741

0,464865

0,473031

0,329764

0,521626

0,536410

0,682027

154

Total Effects

After-

sales quali

ty

Comfort

Costs of

ownership

Expectatio

ns Image

Loyalty

Overall

satisfactio

n

Sales qualit

y

Value for

money

Vehicle Design

Vehicle quality

After-sales

quality

0,263287

0,055940

0,18782

0

Comfort 0,166641

0,450656

0,282105

0,595041

0,054323

0,513122

0,74734

8

Costs of ownersh

ip

0,483602

0,1273

26 0,027052

0,09083

0

Expectations

0,0960

28

0,325988

Image 0,369774

0,0577

67 0,049773

0,120542

0,167117

Loyalty

Overall satisfact

ion

0,447200

Sales quality

0,2945

76

Value for money

0,1331

92 0,297836

Vehicle Design

0,083098

0,224727

0,012982

0,011185

0,027089

0,037556

Vehicle quality

0,222977

0,603007

0,377475

0,796203

0,072688

0,686592

Calculation Results

Outer Loadings

After-

sales quali

ty

Comfort

Costs of

ownership

Expectation

s

Image

Loyalty

Overall

satisfaction

Sales qualit

y

Value for

money

Vehicle Design

Vehicle quality

comfort 0,77066

5

comfort%a

0,79324

4

comfort%b

0,71408

1

comfort%c

0,73431

2

155

comfort%d

0,62796

2

comfort%e

0,72519

6

comfort%f

0,68755

9

comfort%g

0,58257

3

comfort%h

0,58068

8

costs 0,737651

costs%a

0,656791

costs%b

0,636457

costs%c

0,867725

costs%d

0,877533

costs%e

0,872290

design 0,91956

0

design%a

0,89910

3

design%b

0,88175

3

design%c

0,92155

0

design%d

0,87237

6

image 0,701045

image%a

0,704244

image%b

0,731372

image%c

0,798033

image%d

0,801905

image%e

0,571081

image%f

0,589476

156

image%g

0,641581

image%h

0,757166

loyalty1 0,858884

loyalty2 0,849768

loyalty3 0,832810

loyalty4 0,745602

oczek%d

0,819162

oczek%f

0,812377

oczek%g

0,859832

sales 0,822780

sales%a

0,811570

sales%b

0,821681

sales%c

0,815307

sales%d

0,816170

sales%e

0,829765

sales%f

0,808609

sales%g

0,695434

sales%h

0,694660

sales%i 0,702338

sales%j

0,648593

sat1 0,958058

sat1a 0,955991

sat1b 0,966457

157

service 0,910850

service%a

0,911145

service%b

0,931240

service%c

0,884382

service%d

0,664849

service%e

0,796449

service%f

0,904052

service%g

0,865445

value1 0,987803

value2 0,987937

vehqual 0,86361

8

vehqual%a

0,81259

4

vehqual%b

0,60009

8

vehqual%c

0,65982

2

vehqual%d

0,71077

3

vehqual%e

0,76927

6

vehqual%f

0,76718

0

vehqual%g

0,68202

7

158

Outer Weights

After-

sales quali

ty

Comfort

Costs of

ownership

Expectations

Image

Loyalty

Overall satisfac

tion

Sales qualit

y

Value for

money

Vehicle

Design

Vehicle

quality

comfort 0,2281

24

comfort%a

0,1977

67

comfort%b

0,1556

61

comfort%c

0,1591

24

comfort%d

0,1423

43

comfort%e

0,1489

68

comfort%f

0,1443

92

comfort%g

0,1162

75

comfort%h

0,1289

50

costs 0,1944

64

costs%a

0,1511

44

costs%b

0,1574

39

costs%c

0,2806

90

costs%d

0,2472

44

costs%e

0,2253

30

design 0,229616

design%a

0,198596

design%b

0,224507

design%c

0,232390

design 0,227

159

%d 170

image 0,192667

image%a

0,172659

image%b

0,174731

image%c

0,178627

image%d

0,183037

image%e

0,100752

image%f

0,101445

image%g

0,121345

image%h

0,173047

loyalty1 0,338436

loyalty2 0,296380

loyalty3 0,309419

loyalty4 0,267946

oczek%d

0,412285

oczek%f

0,352844

oczek%g

0,436863

sales 0,139212

sales%a

0,121809

sales%b

0,110031

sales%c

0,113265

sales%d

0,116978

sales%e

0,116967

sales% 0,119

160

f 434

sales%g

0,118792

sales%h

0,117647

sales%i 0,105878

sales%j 0,117243

sat1 0,34735

2

sat1a 0,34297

6

sat1b 0,35111

2

service 0,156899

service%a

0,156584

service%b

0,155714

service%c

0,134208

service%d

0,116158

service%e

0,142107

service%f

0,155768

service%g

0,138065

value1 0,504755

value2 0,507524

vehqual 0,217690

vehqual%a

0,194552

vehqual%b

0,127356

vehqual%c

0,144981

vehqual%d

0,156144

vehqual 0,171

161

%e 400

vehqual%f

0,174276

vehqual%g

0,154366

Path coefficients

After-sales qualit

y

Comfort

Costs of

ownership

Expectations

Image Loyal

ty

Overall satisfac

tion

Sales qualit

y

Value for

money

Vehicle

Design

Vehicle

quality

After-sales

quality

0,238271

0,187820

Comfort 0,747348

Costs of ownersh

ip

0,483602

Expectations

0,325988

Image 0,36977

4

0,167117

Loyalty

Overall satisfact

ion

0,447200

Sales quality

0,294576

Value for

money

0,297836

Vehicle Design

0,2247

27

Vehicle quality

0,6030

07

0,591712

0,585819

162

Index values

Index Values for Latent Variables

LV Index Values

After-sales quality 7,761776

Comfort 8,816234

Costs of ownership 7,148388

Expectations 9,386072

Image 8,388493

Loyalty 8,490361

Overall satisfaction 8,025636

Sales quality 8,973071

Value for money 7,715634

Vehicle Design 9,150832

Vehicle quality 8,710951

163

Appendix 4. Results of PLS algorithm application on the final structure of the Brand Satisfaction Model – Compact Vehicles (Path Weighting Scheme, Mean replacement algorithm for missing values, Mean 0 and Var 1 data metric, Abort Criterion 1.0E-5, Initial Weights 1.0)

Quality Criteria Overview

AVE Composite Reliability R Square Cronbachs Alpha

After-sales quality 0,772868 0,964042 0,321751 0,955294

Comfort 0,615318 0,933864 0,918409

Costs of ownership 0,594624 0,896510 0,860870

Expectations 0,669758 0,858374 0,112756 0,752665

Image 0,530648 0,909568 0,710467 0,888146

Loyalty 0,710878 0,907125 0,526028 0,866536

Overall satisfaction 0,914288 0,969696 0,679328 0,953114

Sales quality 0,603427 0,943242 0,219643 0,933588

Value for money 0,975473 0,987584 0,655323 0,974863

Vehicle Design 0,838080 0,962769 0,951549

Vehicle quality 0,610209 0,925904 0,661250 0,908580


After-sales quality 0,772868 0,246238

Comfort 0,615318


Expectations 0,669758 0,076245

Image 0,530648 0,106508

Loyalty 0,710877 0,177967

Overall satisfaction 0,914288 0,420520

Sales quality 0,603427 0,127688

Value for money 0,975473 0,169007


Vehicle quality 0,610209 0,408075

Cross Loadings After-sales quality Comfort Costs of ownership Expectations

comfort 0,368551 0,908322 0,499223 0,311158

comfort%a 0,327109 0,893459 0,499673 0,257111

comfort%b 0,361751 0,803184 0,460079 0,372541

164

comfort%c 0,302326 0,840362 0,394585 0,317704

comfort%d 0,361084 0,763051 0,354829 0,227643

comfort%e 0,199894 0,749876 0,390077 0,111858

comfort%f 0,186670 0,736981 0,451857 0,160103

comfort%g 0,363920 0,780359 0,514510 0,320726

comfort%h 0,489744 0,516300 0,317839 0,296705

costs 0,323558 0,604837 0,676427 0,161764

costs%a 0,405242 0,577586 0,702207 0,242610

costs%b 0,314904 0,393787 0,633019 0,161419

costs%c 0,578369 0,534594 0,866037 0,216390

costs%d 0,497287 0,255268 0,856442 0,156119

costs%e 0,425561 0,264512 0,856077 0,145133

design 0,287264 0,664686 0,428636 0,250960

design%a 0,300855 0,669477 0,434323 0,337540

design%b 0,411170 0,729221 0,456849 0,335446

design%c 0,305569 0,703783 0,440488 0,314366

design%d 0,285438 0,599688 0,410695 0,229690

image 0,398424 0,526238 0,205550 0,283699

image%a 0,359292 0,743258 0,435439 0,250016

image%b 0,460009 0,537668 0,341913 0,258252

image%c 0,280902 0,666360 0,312323 0,248947

image%d 0,414474 0,582726 0,439095 0,234541

image%e 0,219540 0,380064 0,393251 0,178537

image%f 0,388467 0,459375 0,465197 0,253475

image%g 0,223394 0,425230 0,294965 0,147012

image%h 0,358957 0,540787 0,333553 0,310490

loyalty1 0,458454 0,479358 0,345089 0,128059

loyalty2 0,506714 0,301610 0,311258 0,233225

loyalty3 0,536437 0,508535 0,389942 0,238747

loyalty4 0,519625 0,249811 0,284650 0,237279

oczek%d 0,275680 0,299216 0,202976 0,750044

oczek%f 0,127218 0,287645 0,121946 0,827469

oczek%g 0,257396 0,252971 0,243957 0,872927

sales 0,404769 0,442999 0,237130 0,350181

sales%a 0,381844 0,436183 0,346435 0,352979

sales%b 0,293988 0,366277 0,270342 0,351298

sales%c 0,188020 0,345695 0,203641 0,293284

sales%d 0,301803 0,314968 0,261372 0,329294

165

sales%e 0,299072 0,380650 0,269954 0,425858

sales%f 0,374332 0,489102 0,354409 0,375734

sales%g 0,444635 0,504594 0,404195 0,473086

sales%h 0,417590 0,383684 0,399467 0,375602

sales%i 0,398822 0,492094 0,310554 0,298625

sales%j 0,336892 0,336203 0,233454 0,306225

sat1 0,504947 0,564225 0,374221 0,292436

sat1a 0,535152 0,555470 0,471571 0,271302

sat1b 0,538631 0,603846 0,417269 0,262348

service 0,924823 0,369664 0,545683 0,237857

service%a 0,939795 0,322607 0,544257 0,171778

service%b 0,955505 0,380540 0,537828 0,240033

service%c 0,942639 0,345214 0,522347 0,272474

service%d 0,614823 0,323734 0,437543 0,276801

service%e 0,804694 0,411014 0,400930 0,209357

service%f 0,931314 0,435218 0,576036 0,203998

service%g 0,866021 0,315132 0,391975 0,290829

value1 0,526192 0,693837 0,444741 0,393231

value2 0,556832 0,662393 0,439332 0,412993

vehqual 0,491381 0,605398 0,433815 0,244930

vehqual%a 0,516622 0,528989 0,436933 0,261298

vehqual%b 0,290631 0,593782 0,451570 0,220136

vehqual%c 0,420471 0,661912 0,439413 0,203009

vehqual%d 0,364674 0,755923 0,457825 0,264613

vehqual%e 0,263166 0,630274 0,336632 0,184753

vehqual%f 0,417013 0,685958 0,330493 0,323697

vehqual%g 0,341722 0,654619 0,376165 0,339362

Image Loyalty Overall satisfaction Sales quality

comfort 0,754672 0,549088 0,647363 0,438249

comfort%a 0,730202 0,493370 0,622558 0,406887

comfort%b 0,583248 0,328100 0,450903 0,467230

comfort%c 0,594069 0,392949 0,478213 0,561639

comfort%d 0,455845 0,391088 0,409851 0,487933

comfort%e 0,507905 0,290753 0,349771 0,378407

comfort%f 0,549891 0,249086 0,358570 0,245879

comfort%g 0,575915 0,286322 0,401313 0,444689

comfort%h 0,469960 0,290676 0,436499 0,337467

166

costs 0,480153 0,320673 0,490458 0,308860

costs%a 0,561985 0,384154 0,576437 0,390137

costs%b 0,279476 0,085663 0,217221 0,267759

costs%c 0,495916 0,451528 0,395165 0,373683

costs%d 0,233201 0,297785 0,234874 0,278985

costs%e 0,197189 0,233616 0,164818 0,211063

design 0,636785 0,331077 0,458280 0,471075

design%a 0,631628 0,342133 0,428524 0,403599

design%b 0,695114 0,516884 0,560308 0,480789

design%c 0,644403 0,373852 0,415969 0,372850

design%d 0,555452 0,388670 0,377373 0,332598

image 0,775949 0,568405 0,828879 0,296067

image%a 0,775879 0,485195 0,559352 0,387512

image%b 0,799332 0,460316 0,718094 0,269166

image%c 0,777067 0,275709 0,548401 0,182650

image%d 0,804154 0,503103 0,629020 0,201691

image%e 0,611620 0,337185 0,434025 0,229895

image%f 0,636556 0,228182 0,418841 0,272683

image%g 0,604099 0,120880 0,390861 0,238497

image%h 0,733552 0,467777 0,591210 0,450810

loyalty1 0,639892 0,880996 0,753689 0,249019

loyalty2 0,233753 0,825759 0,304632 0,529759

loyalty3 0,643355 0,920330 0,744416 0,348400

loyalty4 0,183991 0,733808 0,247049 0,518657

oczek%d 0,321902 0,270106 0,326801 0,276801

oczek%f 0,250976 0,151076 0,197608 0,384053

oczek%g 0,262132 0,182082 0,200995 0,469960

sales 0,347974 0,427017 0,304894 0,753118

sales%a 0,312176 0,326912 0,255750 0,796759

sales%b 0,186679 0,239523 0,213803 0,803543

sales%c 0,088585 0,156231 0,123442 0,761355

sales%d 0,174630 0,336700 0,152535 0,781378

sales%e 0,206593 0,203987 0,167502 0,848090

sales%f 0,279980 0,381372 0,260731 0,899755

sales%g 0,392661 0,442698 0,381117 0,772912

sales%h 0,391562 0,340626 0,370779 0,643172

sales%i 0,445318 0,364946 0,440641 0,760951

sales%j 0,349042 0,504882 0,430442 0,693442

167

sat1 0,797655 0,615742 0,954712 0,383589

sat1a 0,745893 0,613281 0,949013 0,336583

sat1b 0,754752 0,650965 0,964760 0,370669

service 0,486682 0,547504 0,579499 0,404216

service%a 0,402038 0,523575 0,462961 0,415584

service%b 0,453194 0,562715 0,484813 0,438358

service%c 0,382281 0,560829 0,463280 0,416586

service%d 0,308607 0,455986 0,295031 0,341641

service%e 0,493007 0,540754 0,553773 0,417783

service%f 0,486378 0,498535 0,532701 0,403423

service%g 0,350801 0,448881 0,456908 0,423829

value1 0,742745 0,549651 0,737279 0,503510

value2 0,735974 0,525044 0,778980 0,476037

vehqual 0,794575 0,607016 0,880075 0,361486

vehqual%a 0,694599 0,580618 0,795334 0,370588

vehqual%b 0,647227 0,409009 0,591498 0,328690

vehqual%c 0,552084 0,422845 0,402185 0,417867

vehqual%d 0,656758 0,462371 0,489199 0,388314

vehqual%e 0,616650 0,401348 0,602246 0,319883

vehqual%f 0,557686 0,502996 0,444612 0,488590

vehqual%g 0,657414 0,438577 0,572402 0,463896

Value for money Vehicle Design Vehicle quality

comfort 0,712730 0,687441 0,794166

comfort%a 0,698607 0,645204 0,805647

comfort%b 0,601338 0,588098 0,637560

comfort%c 0,558592 0,666439 0,666711

comfort%d 0,528462 0,573384 0,592607

comfort%e 0,380165 0,554615 0,553722

comfort%f 0,402825 0,503301 0,538826

comfort%g 0,464557 0,565825 0,587421

comfort%h 0,374374 0,366866 0,465039

costs 0,454806 0,495524 0,582239

costs%a 0,504564 0,548883 0,647319

costs%b 0,330916 0,303975 0,304578

costs%c 0,415018 0,453915 0,503085

costs%d 0,234755 0,231700 0,254675

costs%e 0,187220 0,214586 0,181882

168

design 0,571507 0,900610 0,681746

design%a 0,578582 0,941631 0,649038

design%b 0,638644 0,904622 0,778274

design%c 0,519481 0,947728 0,672265

design%d 0,418929 0,880969 0,598435

image 0,700385 0,471843 0,726129

image%a 0,582580 0,717619 0,694918

image%b 0,627994 0,522354 0,717465

image%c 0,522483 0,545757 0,595983

image%d 0,548802 0,501566 0,638817

image%e 0,389807 0,374189 0,423211

image%f 0,452090 0,383334 0,485405

image%g 0,395712 0,417817 0,432659

image%h 0,586856 0,558723 0,646043

loyalty1 0,612411 0,462091 0,691900

loyalty2 0,306701 0,258431 0,348208

loyalty3 0,605995 0,453942 0,648796

loyalty4 0,185048 0,198109 0,280320

oczek%d 0,350518 0,244451 0,258087

oczek%f 0,337788 0,271976 0,283668

oczek%g 0,322329 0,276661 0,263122

sales 0,502144 0,364339 0,384655

sales%a 0,428005 0,424800 0,360741

sales%b 0,371157 0,342401 0,294043

sales%c 0,284391 0,265476 0,214434

sales%d 0,200163 0,349407 0,292422

sales%e 0,271003 0,404204 0,318533

sales%f 0,353524 0,413347 0,389772

sales%g 0,476481 0,379817 0,454920

sales%h 0,398824 0,257749 0,412825

sales%i 0,477194 0,356862 0,539603

sales%j 0,362766 0,271507 0,463181

sat1 0,764842 0,507511 0,780181

sat1a 0,718662 0,443496 0,713547

sat1b 0,718588 0,463178 0,747491

service 0,559483 0,291251 0,471896

service%a 0,478728 0,244507 0,396507

service%b 0,490427 0,291477 0,433071

169

service%c 0,454239 0,235901 0,399983

service%d 0,348076 0,288809 0,322507

service%e 0,538369 0,483845 0,565999

service%f 0,494196 0,357989 0,496701

service%g 0,467562 0,270357 0,418240

value1 0,987265 0,603624 0,755166

value2 0,988056 0,583587 0,763376

vehqual 0,731346 0,522453 0,829399

vehqual%a 0,683846 0,413127 0,774443

vehqual%b 0,556052 0,508740 0,755625

vehqual%c 0,503735 0,646114 0,730919

vehqual%d 0,536518 0,685336 0,806023

vehqual%e 0,574611 0,643254 0,816924

vehqual%f 0,585655 0,631184 0,726910

vehqual%g 0,590505 0,640185 0,802099

Total Effects After-sales quality Comfort Costs of ownership Expectations

After-sales quality

Comfort 0,194786


Expectations

Image 0,335792

Loyalty


Sales quality

Value for money





Comfort 0,580080 0,277585 0,591317 0,091289

Costs of ownership 0,173636 0,044302


Image 0,081926 0,126879 0,157373

Loyalty


170


Value for money 0,181322 0,408035

Vehicle Design 0,164722 0,013495 0,020900 0,025923

Vehicle quality 0,713354 0,341360 0,727172 0,112262



Comfort 0,516269 0,813173


Expectations

Image 0,310951

Loyalty


Sales quality

Value for money



Outer Loadings

After-sales quality Comfort Costs of ownership Expectations

comfort 0,908322

comfort%a 0,893459

comfort%b 0,803184

comfort%c 0,840362

comfort%d 0,763051

comfort%e 0,749876

comfort%f 0,736981

comfort%g 0,780359

comfort%h 0,516300

costs 0,676427

costs%a 0,702207

costs%b 0,633019

costs%c 0,866037

costs%d 0,856442

costs%e 0,856077

design

design%a

171

design%b

design%c

design%d

image

image%a

image%b

image%c

image%d

image%e

image%f

image%g

image%h

loyalty1

loyalty2

loyalty3

loyalty4

oczek%d 0,750044

oczek%f 0,827469

oczek%g 0,872927

sales

sales%a

sales%b

sales%c

sales%d

sales%e

sales%f

sales%g

sales%h

sales%i

sales%j

sat1

sat1a

sat1b

service 0,924823

service%a 0,939795

service%b 0,955505

service%c 0,942639

service%d 0,614823

172

service%e 0,804694

service%f 0,931314

service%g 0,866021

value1

value2

vehqual

vehqual%a

vehqual%b

vehqual%c

vehqual%d

vehqual%e

vehqual%f

vehqual%g


comfort

comfort%a

comfort%b

comfort%c

comfort%d

comfort%e

comfort%f

comfort%g

comfort%h

costs

costs%a

costs%b

costs%c

costs%d

costs%e

design

design%a

design%b

design%c

design%d

image 0,775949

image%a 0,775879

image%b 0,799332

173

image%c 0,777067

image%d 0,804154

image%e 0,611620

image%f 0,636556

image%g 0,604099

image%h 0,733552

loyalty1 0,880996

loyalty2 0,825759

loyalty3 0,920330

loyalty4 0,733808

oczek%d

oczek%f

oczek%g

sales 0,753118

sales%a 0,796759

sales%b 0,803543

sales%c 0,761355

sales%d 0,781378

sales%e 0,848090

sales%f 0,899755

sales%g 0,772912

sales%h 0,643172

sales%i 0,760951

sales%j 0,693442

sat1 0,954712

sat1a 0,949013

sat1b 0,964760

service

service%a

service%b

service%c

service%d

service%e

service%f

service%g

value1

value2

vehqual

174

vehqual%a

vehqual%b

vehqual%c

vehqual%d

vehqual%e

vehqual%f

vehqual%g


comfort

comfort%a

comfort%b

comfort%c

comfort%d

comfort%e

comfort%f

comfort%g

comfort%h

costs

costs%a

costs%b

costs%c

costs%d

costs%e

design 0,900610

design%a 0,941631

design%b 0,904622

design%c 0,947728

design%d 0,880969

image

image%a

image%b

image%c

image%d

image%e

image%f

image%g

image%h

175

loyalty1

loyalty2

loyalty3

loyalty4

oczek%d

oczek%f

oczek%g

sales

sales%a

sales%b

sales%c

sales%d

sales%e

sales%f

sales%g

sales%h

sales%i

sales%j

sat1

sat1a

sat1b

service

service%a

service%b

service%c

service%d

service%e

service%f

service%g

value1 0,987265

value2 0,988056

vehqual 0,829399

vehqual%a 0,774443

vehqual%b 0,755625

vehqual%c 0,730919

vehqual%d 0,806023

vehqual%e 0,816924

vehqual%f 0,726910

176

vehqual%g 0,802099

Outer Weights

After-sales quality Comfort Costs of ownership Expectations

comfort 0,177406

comfort%a 0,179971

comfort%b 0,142422

comfort%c 0,148934

comfort%d 0,132380

comfort%e 0,123694

comfort%f 0,120367

comfort%g 0,131222

comfort%h 0,103884

costs 0,162277

costs%a 0,203244

costs%b 0,157936

costs%c 0,290074

costs%d 0,249408

costs%e 0,213435

design

design%a

design%b

design%c

design%d

image

image%a

image%b

image%c

image%d

image%e

image%f

image%g

image%h

loyalty1

loyalty2

loyalty3

loyalty4

oczek%d 0,357005

177

oczek%f 0,396709

oczek%g 0,462771

sales

sales%a

sales%b

sales%c

sales%d

sales%e

sales%f

sales%g

sales%h

sales%i

sales%j

sat1

sat1a

sat1b

service 0,157215

service%a 0,147306

service%b 0,151640

service%c 0,146665

service%d 0,118517

service%e 0,140880

service%f 0,149264

service%g 0,124452

value1

value2

vehqual

vehqual%a

vehqual%b

vehqual%c

vehqual%d

vehqual%e

vehqual%f

vehqual%g


comfort

comfort%a

178

comfort%b

comfort%c

comfort%d

comfort%e

comfort%f

comfort%g

comfort%h

costs

costs%a

costs%b

costs%c

costs%d

costs%e

design

design%a

design%b

design%c

design%d

image 0,185528

image%a 0,173121

image%b 0,176278

image%c 0,151102

image%d 0,156924

image%e 0,109200

image%f 0,127162

image%g 0,110384

image%h 0,167391

loyalty1 0,339297

loyalty2 0,243649

loyalty3 0,361820

loyalty4 0,227432

oczek%d

oczek%f

oczek%g

sales 0,131173

sales%a 0,114939

sales%b 0,100061

sales%c 0,076234

179

sales%d 0,112523

sales%e 0,106877

sales%f 0,127922

sales%g 0,154808

sales%h 0,121097

sales%i 0,111994

sales%j 0,136657

sat1 0,355462

sat1a 0,338477

sat1b 0,351815

service

service%a

service%b

service%c

service%d

service%e

service%f

service%g

value1

value2

vehqual

vehqual%a

vehqual%b

vehqual%c

vehqual%d

vehqual%e

vehqual%f

vehqual%g


comfort

comfort%a

comfort%b

comfort%c

comfort%d

comfort%e

comfort%f

comfort%g

180

comfort%h

costs

costs%a

costs%b

costs%c

costs%d

costs%e

design 0,219799

design%a 0,218019

design%b 0,239932

design%c 0,222428

design%d 0,191725

image

image%a

image%b

image%c

image%d

image%e

image%f

image%g

image%h

loyalty1

loyalty2

loyalty3

loyalty4

oczek%d

oczek%f

oczek%g

sales

sales%a

sales%b

sales%c

sales%d

sales%e

sales%f

sales%g

sales%h

sales%i

181

sales%j

sat1

sat1a

sat1b

service

service%a

service%b

service%c

service%d

service%e

service%f

service%g

value1 0,498178

value2 0,514309

vehqual 0,193525

vehqual%a 0,173547

vehqual%b 0,153884

vehqual%c 0,136810

vehqual%d 0,157488

vehqual%e 0,156039

vehqual%f 0,146490

vehqual%g 0,159477

Index Values Results Index Values for Latent Variables

LV Index Values


Comfort 8,739694



Image 8,389854

Loyalty 8,469529






182

Appendix 5. Results of PLS algorithm application on the final structure of the Brand Satisfaction Model – Mid-size vehicles (Path Weighting Scheme, Mean replacement algorithm for missing values, Mean 0 and Var 1 data metric, Abort Criterion 1.0E-5, Initial Weights 1.0)

PLS Quality Criteria Overview



Comfort 0,477433 0,889969 0,859571


Expectations 0,721923 0,886158 0,315686 0,808046

Image 0,435126 0,871934 0,434305 0,838482

Loyalty 0,597603 0,855461 0,629035 0,780341


Sales quality 0,539511 0,927087 0,116399 0,912917

Value for money 0,963072 0,981189 0,639334 0,961658

Vehicle Design 0,748316 0,936884 0,915850

Vehicle quality 0,433883 0,856771 0,497074 0,807901



Comfort 0,477433



Image 0,435126 0,097289

Loyalty 0,597602 0,109489


Sales quality 0,539511 0,062490

Value for money 0,963072 0,204720



183


comfort 0,308752 0,783414 0,412866 0,429905

comfort%a 0,392647 0,673697 0,492601 0,305820

comfort%b 0,325933 0,576920 0,253288 0,376092

comfort%c 0,324076 0,634751 0,258848 0,373511

comfort%d 0,368962 0,751996 0,428558 0,319650

comfort%e 0,365378 0,821899 0,544734 0,305516

comfort%f 0,217808 0,745449 0,403458 0,226113

comfort%g 0,201183 0,565853 0,306022 0,252304

comfort%h 0,135515 0,613711 0,254531 0,201124

costs 0,327053 0,508553 0,774391 0,226708

costs%a 0,288790 0,471841 0,660889 0,264715

costs%b 0,139414 0,340539 0,556635 0,140856

costs%c 0,429941 0,464214 0,827629 0,200236

costs%d 0,404361 0,443280 0,911505 0,195620

costs%e 0,421943 0,385126 0,877803 0,144413

design 0,258299 0,523393 0,363193 0,411304

design%a 0,126542 0,523524 0,289120 0,383848

design%b 0,323992 0,522699 0,407946 0,284960

design%c 0,235131 0,563868 0,267012 0,408389

design%d 0,265372 0,572632 0,348402 0,330201

image 0,394457 0,436110 0,370251 0,295115

image%a 0,045427 0,400365 0,290620 0,352588

image%b 0,182039 0,498763 0,359325 0,442809

image%c 0,197907 0,520551 0,322750 0,489439

image%d 0,457271 0,503274 0,375328 0,506104

image%e 0,118870 0,259327 0,161160 0,232050

image%f 0,128174 0,313669 0,189707 0,317089

image%g 0,212006 0,373238 0,247957 0,297562

image%h 0,143441 0,360514 0,406030 0,290159

loyalty1 0,449200 0,603369 0,480556 0,221409

loyalty2 0,476286 0,419578 0,295457 0,200192

loyalty3 0,318066 0,399337 0,475625 0,103996

loyalty4 0,364914 0,328934 0,209691 0,114329

oczek%d 0,136680 0,462026 0,196352 0,874321

oczek%f 0,069130 0,268173 0,224955 0,825496

oczek%g 0,031583 0,399661 0,206882 0,848461

184

sales 0,290037 0,456063 0,276385 0,238430

sales%a 0,206820 0,436130 0,329059 0,298692

sales%b 0,158164 0,325877 0,115696 0,267963

sales%c 0,288450 0,479698 0,407889 0,315613

sales%d 0,218621 0,554479 0,372548 0,333404

sales%e 0,162124 0,443950 0,286325 0,305336

sales%f 0,140842 0,287470 0,156298 0,204494

sales%g 0,275020 0,530494 0,280986 0,262864

sales%h 0,363254 0,401764 0,260901 0,140518

sales%i 0,310068 0,466105 0,345423 0,158220

sales%j 0,148726 0,390157 0,213028 0,179351

sat1 0,429349 0,502421 0,446556 0,201576

sat1a 0,415239 0,613185 0,475102 0,294473

sat1b 0,329843 0,546482 0,436096 0,378687

service 0,934754 0,388721 0,393166 0,091033

service%a 0,901923 0,366785 0,449997 0,099025

service%b 0,938874 0,386548 0,403345 0,089459

service%c 0,769283 0,278074 0,204724 0,114576

service%d 0,610486 0,300189 0,356267 0,021815

service%e 0,751032 0,388057 0,428134 0,071878

service%f 0,894927 0,425357 0,406080 0,095758

service%g 0,865595 0,336381 0,383524 0,026495

value1 0,555860 0,604494 0,565361 0,333318

value2 0,534136 0,570017 0,583718 0,346989

vehqual 0,411798 0,537057 0,361586 0,224805

vehqual%a 0,448304 0,461375 0,481538 0,191582

vehqual%b 0,144237 0,265801 0,206763 0,029286

vehqual%c 0,241615 0,333578 0,111133 0,245830

vehqual%d 0,379203 0,438931 0,361180 0,197741

vehqual%e 0,164634 0,586594 0,318908 0,324709

vehqual%f 0,326688 0,467251 0,527871 0,254507

vehqual%g 0,326000 0,566660 0,637906 0,308630


comfort 0,499146 0,450938 0,493559 0,408250

comfort%a 0,469256 0,383535 0,425850 0,416263

comfort%b 0,442506 0,305192 0,317228 0,444659

comfort%c 0,334085 0,275475 0,424768 0,357509

185

comfort%d 0,426097 0,524615 0,420760 0,488123

comfort%e 0,553928 0,447311 0,382615 0,385671

comfort%f 0,426195 0,479140 0,466926 0,439320

comfort%g 0,411985 0,354294 0,376957 0,338288

comfort%h 0,418178 0,367472 0,340569 0,426516

costs 0,465327 0,457412 0,447024 0,375072

costs%a 0,396150 0,476783 0,445455 0,332420

costs%b 0,251541 0,273421 0,299824 0,164197

costs%c 0,436205 0,372556 0,372110 0,325408

costs%d 0,354102 0,396203 0,397737 0,315469

costs%e 0,332908 0,358656 0,335459 0,284766

design 0,501816 0,369159 0,488219 0,472939

design%a 0,362796 0,348715 0,283510 0,463244

design%b 0,455043 0,405743 0,530696 0,422975

design%c 0,482972 0,437275 0,336702 0,505521

design%d 0,514930 0,405844 0,455662 0,386809

image 0,612705 0,580233 0,738605 0,311307

image%a 0,558133 0,243627 0,224097 0,343926

image%b 0,699180 0,454425 0,431886 0,456570

image%c 0,764794 0,344335 0,378394 0,456332

image%d 0,806129 0,450317 0,396707 0,513104

image%e 0,509472 0,125331 0,137816 0,067978

image%f 0,654318 0,169139 0,211457 0,320316

image%g 0,655640 0,272753 0,342951 0,413105

image%h 0,622939 0,251595 0,217031 0,294143

loyalty1 0,603379 0,830309 0,757562 0,487273

loyalty2 0,334404 0,770412 0,268209 0,601662

loyalty3 0,424506 0,785952 0,671154 0,370646

loyalty4 0,200314 0,699817 0,218398 0,486825

oczek%d 0,460332 0,186505 0,258695 0,350156

oczek%f 0,477104 0,173191 0,302937 0,159021

oczek%g 0,495491 0,181525 0,238027 0,339963

sales 0,471630 0,554155 0,370551 0,818970

sales%a 0,401170 0,537192 0,307661 0,782944

sales%b 0,355684 0,321913 0,223589 0,780680

sales%c 0,470640 0,598582 0,435024 0,821675

sales%d 0,504127 0,472071 0,283816 0,816178

sales%e 0,426730 0,429376 0,207567 0,792365

186

sales%f 0,229444 0,379938 0,119058 0,672968

sales%g 0,491701 0,355670 0,297747 0,638617

sales%h 0,405922 0,507686 0,376317 0,606046

sales%i 0,445724 0,428493 0,316544 0,701865

sales%j 0,274575 0,271176 0,258624 0,593031

sat1 0,506581 0,627164 0,936009 0,378612

sat1a 0,542748 0,619161 0,944008 0,373638

sat1b 0,557773 0,625754 0,937158 0,389331

service 0,337991 0,501633 0,390205 0,288323

service%a 0,340608 0,460621 0,401281 0,278644

service%b 0,362982 0,525353 0,408137 0,315646

service%c 0,237963 0,408676 0,163748 0,278043

service%d 0,296633 0,346311 0,213807 0,236343

service%e 0,250121 0,356742 0,389503 0,220560

service%f 0,290049 0,470631 0,424604 0,277936

service%g 0,199636 0,389397 0,330235 0,266995

value1 0,637283 0,644650 0,635171 0,370359

value2 0,629540 0,658703 0,674506 0,403114

vehqual 0,524711 0,563923 0,792004 0,432705

vehqual%a 0,443824 0,543471 0,668893 0,160704

vehqual%b 0,245626 0,220350 0,335432 0,094903

vehqual%c 0,369118 0,330209 0,448417 0,356268

vehqual%d 0,379023 0,414369 0,534652 0,275173

vehqual%e 0,347887 0,377637 0,408615 0,349617

vehqual%f 0,339184 0,425700 0,467986 0,289904

vehqual%g 0,518538 0,556644 0,532064 0,355763


comfort 0,475532 0,472732 0,560491

comfort%a 0,519348 0,382030 0,518859

comfort%b 0,336533 0,371001 0,400768

comfort%c 0,286365 0,431626 0,458778

comfort%d 0,444658 0,615776 0,553677

comfort%e 0,519851 0,485424 0,537796

comfort%f 0,411389 0,447878 0,508234

comfort%g 0,299135 0,255572 0,384356

comfort%h 0,373593 0,369247 0,417634

costs 0,449348 0,422911 0,499244

187

costs%a 0,457795 0,221919 0,458798

costs%b 0,414334 0,086670 0,298991

costs%c 0,536476 0,379086 0,512281

costs%d 0,488924 0,341875 0,506274

costs%e 0,429455 0,267497 0,457530

design 0,356722 0,908290 0,548997

design%a 0,260709 0,813503 0,385783

design%b 0,369991 0,889411 0,597482

design%c 0,291826 0,867795 0,424100

design%d 0,334324 0,843018 0,471438

image 0,668747 0,339963 0,693426

image%a 0,311555 0,318575 0,417938

image%b 0,519289 0,316762 0,480622

image%c 0,449668 0,493586 0,409509

image%d 0,484416 0,519980 0,432793

image%e 0,221357 0,201947 0,166161

image%f 0,242265 0,327241 0,188118

image%g 0,292835 0,321140 0,278872

image%h 0,369763 0,258330 0,286404

loyalty1 0,735828 0,521314 0,731981

loyalty2 0,352228 0,276390 0,327543

loyalty3 0,572570 0,359737 0,631823

loyalty4 0,283854 0,171784 0,279171

oczek%d 0,313367 0,356669 0,312039

oczek%f 0,375863 0,166838 0,297116

oczek%g 0,210968 0,512143 0,270074

sales 0,367428 0,305614 0,393529

sales%a 0,267069 0,350798 0,336866

sales%b 0,166184 0,324944 0,225457

sales%c 0,343287 0,549620 0,473235

sales%d 0,304071 0,647422 0,382309

sales%e 0,283773 0,355637 0,256205

sales%f 0,161354 0,262864 0,185119

sales%g 0,274446 0,311356 0,377426

sales%h 0,364066 0,351201 0,334936

sales%i 0,361275 0,356044 0,331316

sales%j 0,238279 0,258994 0,219035

sat1 0,605676 0,449900 0,769066

188

sat1a 0,652056 0,479701 0,761919

sat1b 0,622555 0,454056 0,775451

service 0,560380 0,248188 0,458067

service%a 0,564136 0,239262 0,467364

service%b 0,539122 0,262069 0,454964

service%c 0,356811 0,106547 0,238792

service%d 0,303684 0,201607 0,264684

service%e 0,437300 0,307401 0,389073

service%f 0,521502 0,262279 0,484615

service%g 0,360624 0,267513 0,406240

value1 0,981114 0,349506 0,720335

value2 0,981610 0,387951 0,709617

vehqual 0,568566 0,415946 0,784338

vehqual%a 0,591599 0,327433 0,759266

vehqual%b 0,299595 0,203319 0,471343

vehqual%c 0,371766 0,310619 0,541233

vehqual%d 0,491295 0,546857 0,708736

vehqual%e 0,378512 0,362391 0,596198

vehqual%f 0,503552 0,258179 0,629480

vehqual%g 0,552686 0,501805 0,714346


After-sales quality

Comfort 0,179940


Expectations

Image 0,561859

Loyalty


Sales quality

Value for money





189

Comfort 0,320258 0,256940 0,559518 0,061391



Image 0,091344 0,044817 0,191691

Loyalty



Value for money 0,063140 0,151180

Vehicle Design 0,285429 0,026072 0,012792 0,054714

Vehicle quality 0,454244 0,364436 0,793604 0,087075



Comfort 0,396431 0,705034


Expectations

Image 0,296450

Loyalty


Sales quality

Value for money



Outer Loadings After-sales quality Comfort Costs of ownership Expectations

comfort 0,783414

comfort%a 0,673697

comfort%b 0,576920

comfort%c 0,634751

comfort%d 0,751996

comfort%e 0,821899

comfort%f 0,745449

comfort%g 0,565853

comfort%h 0,613711

costs 0,774391

costs%a 0,660889

costs%b 0,556635

190

costs%c 0,827629

costs%d 0,911505

costs%e 0,877803

design

design%a

design%b

design%c

design%d

image

image%a

image%b

image%c

image%d

image%e

image%f

image%g

image%h

loyalty1

loyalty2

loyalty3

loyalty4

oczek%d 0,874321

oczek%f 0,825496

oczek%g 0,848461

sales

sales%a

sales%b

sales%c

sales%d

sales%e

sales%f

sales%g

sales%h

sales%i

sales%j

sat1

sat1a

sat1b

191

service 0,934754

service%a 0,901923

service%b 0,938874

service%c 0,769283

service%d 0,610486

service%e 0,751032

service%f 0,894927

service%g 0,865595

value1

value2

vehqual

vehqual%a

vehqual%b

vehqual%c

vehqual%d

vehqual%e

vehqual%f

vehqual%g


comfort

comfort%a

comfort%b

comfort%c

comfort%d

comfort%e

comfort%f

comfort%g

comfort%h

costs

costs%a

costs%b

costs%c

costs%d

costs%e

design

design%a

design%b

192

design%c

design%d

image 0,612705

image%a 0,558133

image%b 0,699180

image%c 0,764794

image%d 0,806129

image%e 0,509472

image%f 0,654318

image%g 0,655640

image%h 0,622939

loyalty1 0,830309

loyalty2 0,770412

loyalty3 0,785952

loyalty4 0,699817

oczek%d

oczek%f

oczek%g

sales 0,818970

sales%a 0,782944

sales%b 0,780680

sales%c 0,821675

sales%d 0,816178

sales%e 0,792365

sales%f 0,672968

sales%g 0,638617

sales%h 0,606046

sales%i 0,701865

sales%j 0,593031

sat1 0,936009

sat1a 0,944008

sat1b 0,937158

service

service%a

service%b

service%c

service%d

service%e

193

service%f

service%g

value1

value2

vehqual

vehqual%a

vehqual%b

vehqual%c

vehqual%d

vehqual%e

vehqual%f

vehqual%g


comfort

comfort%a

comfort%b

comfort%c

comfort%d

comfort%e

comfort%f

comfort%g

comfort%h

costs

costs%a

costs%b

costs%c

costs%d

costs%e

design 0,908290

design%a 0,813503

design%b 0,889411

design%c 0,867795

design%d 0,843018

image

image%a

image%b

image%c

194

image%d

image%e

image%f

image%g

image%h

loyalty1

loyalty2

loyalty3

loyalty4

oczek%d

oczek%f

oczek%g

sales

sales%a

sales%b

sales%c

sales%d

sales%e

sales%f

sales%g

sales%h

sales%i

sales%j

sat1

sat1a

sat1b

service

service%a

service%b

service%c

service%d

service%e

service%f

service%g

value1 0,981114

value2 0,981610

vehqual 0,784338

vehqual%a 0,759266

195

vehqual%b 0,471343

vehqual%c 0,541233

vehqual%d 0,708736

vehqual%e 0,596198

vehqual%f 0,629480

vehqual%g 0,714346

Path Coefficients After-sales quality Comfort Costs of ownership Expectations

After-sales quality

Comfort


Expectations

Image 0,561859

Loyalty


Sales quality

Value for money

Vehicle Design

Vehicle quality



Comfort

Costs of ownership


Image

Loyalty








196

Comfort 0,705034

Costs of ownership

Expectations

Image 0,296450

Loyalty


Sales quality

Value for money

Vehicle Design


Outer Weights After-sales quality Comfort Costs of ownership Expectations

comfort 0,185464

comfort%a 0,171688

comfort%b 0,132612

comfort%c 0,151808

comfort%d 0,183209

comfort%e 0,177954

comfort%f 0,168172

comfort%g 0,127182

comfort%h 0,138193

costs 0,202320

costs%a 0,178649

costs%b 0,086243

costs%c 0,265967

costs%d 0,250143

costs%e 0,261020

design

design%a

design%b

design%c

design%d

image

image%a

image%b

image%c

image%d

197

image%e

image%f

image%g

image%h

loyalty1

loyalty2

loyalty3

loyalty4

oczek%d 0,406008

oczek%f 0,346104

oczek%g 0,423485

sales

sales%a

sales%b

sales%c

sales%d

sales%e

sales%f

sales%g

sales%h

sales%i

sales%j

sat1

sat1a

sat1b

service 0,170441

service%a 0,171948

service%b 0,171614

service%c 0,114346

service%d 0,115953

service%e 0,141448

service%f 0,163219

service%g 0,131030

value1

value2

vehqual

vehqual%a

vehqual%b

198

vehqual%c

vehqual%d

vehqual%e

vehqual%f

vehqual%g


comfort

comfort%a

comfort%b

comfort%c

comfort%d

comfort%e

comfort%f

comfort%g

comfort%h

costs

costs%a

costs%b

costs%c

costs%d

costs%e

design

design%a

design%b

design%c

design%d

image 0,231491

image%a 0,155932

image%b 0,204714

image%c 0,204584

image%d 0,216027

image%e 0,093189

image%f 0,117729

image%g 0,131753

image%h 0,138858

loyalty1 0,406386

loyalty2 0,301708

199

loyalty3 0,332320

loyalty4 0,241415

oczek%d

oczek%f

oczek%g

sales 0,145619

sales%a 0,149058

sales%b 0,099722

sales%c 0,164081

sales%d 0,139278

sales%e 0,126925

sales%f 0,104634

sales%g 0,106300

sales%h 0,124301

sales%i 0,109543

sales%j 0,078584

sat1 0,354658

sat1a 0,353523

sat1b 0,356725

service

service%a

service%b

service%c

service%d

service%e

service%f

service%g

value1

value2

vehqual

vehqual%a

vehqual%b

vehqual%c

vehqual%d

vehqual%e

vehqual%f

vehqual%g

200


comfort

comfort%a

comfort%b

comfort%c

comfort%d

comfort%e

comfort%f

comfort%g

comfort%h

costs

costs%a

costs%b

costs%c

costs%d

costs%e

design 0,249801

design%a 0,180597

design%b 0,226517

design%c 0,240420

design%d 0,256329

image

image%a

image%b

image%c

image%d

image%e

image%f

image%g

image%h

loyalty1

loyalty2

loyalty3

loyalty4

oczek%d

oczek%f

oczek%g

sales

201

sales%a

sales%b

sales%c

sales%d

sales%e

sales%f

sales%g

sales%h

sales%i

sales%j

sat1

sat1a

sat1b

service

service%a

service%b

service%c

service%d

service%e

service%f

service%g

value1 0,506136

value2 0,512854

vehqual 0,245772

vehqual%a 0,219700

vehqual%b 0,115829

vehqual%c 0,153286

vehqual%d 0,186449

vehqual%e 0,172461

vehqual%f 0,179454

vehqual%g 0,216891

202


LV Index Values


Comfort 8,736349



Image 8,467164

Loyalty 8,736364






203

Appendix 6. Results of PLS algorithm application on the final structure of the Brand Satisfaction Model – Full-size and large vehicles (Path Weighting Scheme, Mean replacement algorithm for missing values, Mean 0 and Var 1 data metric, Abort Criterion 1.0E-5, Initial Weights 1.0)

PLS Quality Criteria Overview



Comfort 0,417075 0,862975 0,825457


Expectations 0,688444 0,868744 0,101650 0,772819

Image 0,515331 0,903972 0,540174 0,881729

Loyalty 0,683263 0,895821 0,668624 0,844064


Sales quality 0,631180 0,948994 0,069712 0,939794

Value for money 0,980902 0,990359 0,752208 0,980530

Vehicle Design 0,821036 0,958165 0,945447

Vehicle quality 0,556229 0,906952 0,575419 0,880875



Comfort 0,417075



Image 0,515331 0,094646

Loyalty 0,683262 0,132700


Sales quality 0,631180 0,044446

Value for money 0,980902 0,159029



204


comfort 0,486584 0,701444 0,358895 0,302654

comfort%a 0,379716 0,785724 0,348787 0,353190

comfort%b 0,338939 0,714064 0,297551 0,358419

comfort%c 0,236001 0,682580 0,256100 0,385769

comfort%d 0,247213 0,451548 0,142889 0,218285

comfort%e 0,382478 0,659463 0,353861 0,333402

comfort%f 0,366883 0,606493 0,355257 0,245082

comfort%g 0,284473 0,527113 0,322851 0,206239

comfort%h 0,274856 0,619692 0,307845 0,255494

costs 0,386846 0,456552 0,776274 0,233476

costs%a 0,165649 0,309901 0,637468 0,145489

costs%b 0,332093 0,386249 0,678024 0,197377

costs%c 0,469630 0,416694 0,893648 0,193685

costs%d 0,413690 0,377911 0,869240 0,125562

costs%e 0,367094 0,313662 0,876489 0,114905

design 0,172556 0,587421 0,245510 0,438682

design%a 0,145712 0,491685 0,188848 0,531135

design%b 0,174418 0,556224 0,115859 0,410043

design%c 0,180344 0,578444 0,303586 0,389941

design%d 0,261063 0,625606 0,359490 0,428830

image 0,399395 0,535569 0,508721 0,175029

image%a 0,336038 0,550161 0,286933 0,320668

image%b 0,351798 0,621586 0,252952 0,203443

image%c 0,440366 0,603556 0,382295 0,235845

image%d 0,418318 0,641452 0,401432 0,291397

image%e 0,254347 0,425490 0,328220 0,135004

image%f 0,270540 0,356726 0,349798 0,143900

image%g 0,376664 0,533043 0,279515 0,289664

image%h 0,403120 0,599637 0,366024 0,229804

loyalty1 0,512689 0,612642 0,467497 0,195850

loyalty2 0,484392 0,495551 0,440663 0,086442

loyalty3 0,476453 0,562117 0,384430 0,174686

loyalty4 0,464469 0,405859 0,247259 0,150493

oczek%d 0,217163 0,411070 0,122880 0,790053

oczek%f 0,235346 0,323431 0,195756 0,826712

oczek%g 0,153565 0,410431 0,206856 0,870456

205

sales 0,370460 0,481707 0,265872 0,196862

sales%a 0,368645 0,430058 0,259101 0,233853

sales%b 0,429625 0,436230 0,227805 0,316616

sales%c 0,389417 0,429925 0,281320 0,242127

sales%d 0,283848 0,359523 0,277888 0,158366

sales%e 0,331734 0,418245 0,265890 0,229892

sales%f 0,358292 0,418498 0,159242 0,277565

sales%g 0,425825 0,444385 0,321235 0,136097

sales%h 0,362657 0,443438 0,309245 0,186311

sales%i 0,369058 0,451953 0,334545 0,197408

sales%j 0,403004 0,427782 0,268307 0,112262

sat1 0,356390 0,610812 0,468097 0,221811

sat1a 0,496962 0,581794 0,476182 0,255537

sat1b 0,446464 0,601986 0,487976 0,259751

service 0,891576 0,431957 0,402760 0,176200

service%a 0,894955 0,446260 0,378132 0,148404

service%b 0,912642 0,428400 0,362681 0,182187

service%c 0,900188 0,422797 0,352342 0,294909

service%d 0,784663 0,404870 0,370116 0,180126

service%e 0,812486 0,517402 0,475678 0,265185

service%f 0,885154 0,534140 0,510663 0,217410

service%g 0,867337 0,517744 0,410374 0,235519

value1 0,587218 0,660415 0,555849 0,220129

value2 0,543788 0,656576 0,530888 0,219318

vehqual 0,456868 0,667845 0,444476 0,245849

vehqual%a 0,511586 0,587148 0,484406 0,219857

vehqual%b 0,293151 0,425623 0,280357 0,067521

vehqual%c 0,365287 0,577256 0,374623 0,218713

vehqual%d 0,406049 0,577041 0,279144 0,257162

vehqual%e 0,402442 0,538878 0,339559 0,202613

vehqual%f 0,364311 0,626742 0,344546 0,217115

vehqual%g 0,210936 0,521364 0,276647 0,220795


comfort 0,662560 0,695889 0,655821 0,337419

comfort%a 0,665404 0,483882 0,543719 0,445745

comfort%b 0,508045 0,353709 0,346294 0,531378

comfort%c 0,470020 0,374716 0,291116 0,472384

206

comfort%d 0,198086 0,135793 0,276695 0,200980

comfort%e 0,471679 0,326035 0,362254 0,225314

comfort%f 0,425086 0,387703 0,319339 0,305911

comfort%g 0,383435 0,270345 0,281171 0,274535

comfort%h 0,462597 0,355790 0,260550 0,329058

costs 0,494821 0,430027 0,436368 0,383500

costs%a 0,329866 0,257025 0,285571 0,331358

costs%b 0,458229 0,355972 0,319883 0,264686

costs%c 0,378019 0,374106 0,461891 0,213744

costs%d 0,374292 0,401561 0,450663 0,251026

costs%e 0,315602 0,381746 0,347942 0,242843

design 0,469513 0,392449 0,357143 0,458396

design%a 0,349744 0,276832 0,220791 0,408554

design%b 0,435562 0,347048 0,272388 0,473404

design%c 0,495616 0,396902 0,344947 0,372807

design%d 0,526840 0,395221 0,338722 0,391876

image 0,703457 0,561065 0,774887 0,292171

image%a 0,707365 0,409327 0,459711 0,287959

image%b 0,713735 0,426688 0,367014 0,348544

image%c 0,824082 0,566679 0,469841 0,428460

image%d 0,800597 0,590742 0,503559 0,389015

image%e 0,583350 0,383945 0,296413 0,426618

image%f 0,553195 0,369520 0,218649 0,404790

image%g 0,696339 0,434967 0,362858 0,439194

image%h 0,825874 0,622906 0,529532 0,480704

loyalty1 0,693729 0,858880 0,708885 0,365961

loyalty2 0,525380 0,885788 0,514963 0,649274

loyalty3 0,648846 0,788246 0,631226 0,254410

loyalty4 0,417124 0,767739 0,405118 0,726514

oczek%d 0,254600 0,236988 0,285617 0,241158

oczek%f 0,264277 0,092023 0,116269 0,188079

oczek%g 0,274213 0,120435 0,221913 0,225251

sales 0,416742 0,610626 0,306903 0,876228

sales%a 0,341776 0,456658 0,227086 0,849399

sales%b 0,410572 0,463508 0,231161 0,855927

sales%c 0,414405 0,455673 0,249660 0,850556

sales%d 0,341424 0,458515 0,209312 0,845315

sales%e 0,387441 0,508878 0,228113 0,842762

207

sales%f 0,482676 0,473198 0,217528 0,823817

sales%g 0,483542 0,439269 0,219931 0,669414

sales%h 0,461684 0,503751 0,251426 0,776448

sales%i 0,408678 0,417268 0,256908 0,664272

sales%j 0,448981 0,521209 0,317422 0,633991

sat1 0,627899 0,667030 0,966102 0,308483

sat1a 0,615213 0,671882 0,964621 0,290163

sat1b 0,629980 0,642692 0,976425 0,309832

service 0,412514 0,540259 0,382202 0,378064

service%a 0,477303 0,572075 0,410383 0,402454

service%b 0,446144 0,554400 0,436812 0,365524

service%c 0,449371 0,487477 0,333232 0,443502

service%d 0,425084 0,480436 0,328529 0,418970

service%e 0,443966 0,423765 0,400220 0,408544

service%f 0,459418 0,489041 0,412027 0,445882

service%g 0,441900 0,520552 0,394840 0,403760

value1 0,659258 0,718975 0,806262 0,358275

value2 0,661473 0,704921 0,800878 0,335814

vehqual 0,661258 0,695790 0,938753 0,332606

vehqual%a 0,564415 0,614300 0,869479 0,239796

vehqual%b 0,359425 0,243625 0,299708 0,204830

vehqual%c 0,476505 0,424111 0,552200 0,373482

vehqual%d 0,509388 0,385121 0,477798 0,275832

vehqual%e 0,561994 0,591955 0,681101 0,269071

vehqual%f 0,569625 0,596753 0,711340 0,317015

vehqual%g 0,465631 0,456070 0,400253 0,246163


comfort 0,664926 0,444845 0,741440

comfort%a 0,551400 0,519356 0,624199

comfort%b 0,394224 0,482644 0,482133

comfort%c 0,359097 0,564153 0,424692

comfort%d 0,233716 0,260167 0,365169

comfort%e 0,390681 0,315698 0,431073

comfort%f 0,357687 0,333296 0,430835

comfort%g 0,295682 0,245100 0,289719

comfort%h 0,395963 0,433617 0,364341

costs 0,513348 0,330894 0,466261

208

costs%a 0,328155 0,342579 0,312130

costs%b 0,439696 0,263282 0,399437

costs%c 0,480751 0,162574 0,403281

costs%d 0,443364 0,167005 0,408087

costs%e 0,387377 0,169018 0,297152

design 0,340317 0,951949 0,465140

design%a 0,215935 0,901079 0,333651

design%b 0,316908 0,849767 0,411623

design%c 0,368710 0,933445 0,463358

design%d 0,345271 0,890844 0,436989

image 0,585685 0,184422 0,673724

image%a 0,510536 0,336713 0,512497

image%b 0,446873 0,428563 0,473477

image%c 0,562427 0,483582 0,585734

image%d 0,562297 0,451074 0,607668

image%e 0,292138 0,289659 0,314508

image%f 0,263021 0,296337 0,218211

image%g 0,361392 0,345050 0,374045

image%h 0,555650 0,466454 0,593347

loyalty1 0,749828 0,376810 0,730284

loyalty2 0,561475 0,346122 0,538444

loyalty3 0,690450 0,302772 0,640725

loyalty4 0,384183 0,310550 0,395111

oczek%d 0,231454 0,439052 0,301536

oczek%f 0,145876 0,337763 0,162649

oczek%g 0,171937 0,411157 0,227419

sales 0,313214 0,370407 0,315818

sales%a 0,234957 0,316560 0,241437

sales%b 0,281869 0,379559 0,278850

sales%c 0,273477 0,398764 0,277198

sales%d 0,231830 0,407975 0,236709

sales%e 0,266370 0,376516 0,288328

sales%f 0,283630 0,435985 0,292145

sales%g 0,302195 0,364573 0,361965

sales%h 0,247126 0,367063 0,284307

sales%i 0,287436 0,370262 0,355627

sales%j 0,333372 0,255317 0,372273

sat1 0,766175 0,322736 0,827692

209

sat1a 0,778694 0,353568 0,827803

sat1b 0,813528 0,327862 0,867137

service 0,523042 0,156771 0,439373

service%a 0,555610 0,142634 0,470256

service%b 0,553706 0,168962 0,474773

service%c 0,447946 0,254798 0,387653

service%d 0,388077 0,217009 0,358713

service%e 0,480422 0,173475 0,462421

service%f 0,528232 0,196900 0,498958

service%g 0,471426 0,170463 0,458337

value1 0,990470 0,360181 0,841739

value2 0,990339 0,347947 0,844406

vehqual 0,832742 0,355462 0,907941

vehqual%a 0,750984 0,304548 0,858737

vehqual%b 0,403120 0,298963 0,531512

vehqual%c 0,554009 0,330215 0,691101

vehqual%d 0,499262 0,324846 0,664484

vehqual%e 0,696997 0,344251 0,788866

vehqual%f 0,732261 0,429057 0,837131

vehqual%g 0,471919 0,494689 0,602734


After-sales quality

Comfort 0,144802


Expectations

Image 0,318826

Loyalty


Sales quality

Value for money





Comfort 0,454172 0,318870 0,639516 0,038232

210



Image 0,041322 0,021322 0,084180

Loyalty



Value for money 0,125661 0,263727

Vehicle Design 0,228841 0,009456 0,004879 0,019264

Vehicle quality 0,598727 0,420360 0,843061 0,050401



Comfort 0,574451 0,758564


Expectations

Image 0,080849

Loyalty


Sales quality

Value for money



Outer Loadings After-sales quality Comfort Costs of ownership Expectations

comfort 0,701444

comfort%a 0,785724

comfort%b 0,714064

comfort%c 0,682580

comfort%d 0,451548

comfort%e 0,659463

comfort%f 0,606493

comfort%g 0,527113

comfort%h 0,619692

costs 0,776274

costs%a 0,637468

costs%b 0,678024

costs%c 0,893648

211

costs%d 0,869240

costs%e 0,876489

design

design%a

design%b

design%c

design%d

image

image%a

image%b

image%c

image%d

image%e

image%f

image%g

image%h

loyalty1

loyalty2

loyalty3

loyalty4

oczek%d 0,790053

oczek%f 0,826712

oczek%g 0,870456

sales

sales%a

sales%b

sales%c

sales%d

sales%e

sales%f

sales%g

sales%h

sales%i

sales%j

sat1

sat1a

sat1b

service 0,891576

212

service%a 0,894955

service%b 0,912642

service%c 0,900188

service%d 0,784663

service%e 0,812486

service%f 0,885154

service%g 0,867337

value1

value2

vehqual

vehqual%a

vehqual%b

vehqual%c

vehqual%d

vehqual%e

vehqual%f

vehqual%g


comfort

comfort%a

comfort%b

comfort%c

comfort%d

comfort%e

comfort%f

comfort%g

comfort%h

costs

costs%a

costs%b

costs%c

costs%d

costs%e

design

design%a

design%b

design%c

213

design%d

image 0,703457

image%a 0,707365

image%b 0,713735

image%c 0,824082

image%d 0,800597

image%e 0,583350

image%f 0,553195

image%g 0,696339

image%h 0,825874

loyalty1 0,858880

loyalty2 0,885788

loyalty3 0,788246

loyalty4 0,767739

oczek%d

oczek%f

oczek%g

sales 0,876228

sales%a 0,849399

sales%b 0,855927

sales%c 0,850556

sales%d 0,845315

sales%e 0,842762

sales%f 0,823817

sales%g 0,669414

sales%h 0,776448

sales%i 0,664272

sales%j 0,633991

sat1 0,966102

sat1a 0,964621

sat1b 0,976425

service

service%a

service%b

service%c

service%d

service%e

service%f

214

service%g

value1

value2

vehqual

vehqual%a

vehqual%b

vehqual%c

vehqual%d

vehqual%e

vehqual%f

vehqual%g


comfort

comfort%a

comfort%b

comfort%c

comfort%d

comfort%e

comfort%f

comfort%g

comfort%h

costs

costs%a

costs%b

costs%c

costs%d

costs%e

design 0,951949

design%a 0,901079

design%b 0,849767

design%c 0,933445

design%d 0,890844

image

image%a

image%b

image%c

image%d

215

image%e

image%f

image%g

image%h

loyalty1

loyalty2

loyalty3

loyalty4

oczek%d

oczek%f

oczek%g

sales

sales%a

sales%b

sales%c

sales%d

sales%e

sales%f

sales%g

sales%h

sales%i

sales%j

sat1

sat1a

sat1b

service

service%a

service%b

service%c

service%d

service%e

service%f

service%g

value1 0,990470

value2 0,990339

vehqual 0,907941

vehqual%a 0,858737

vehqual%b 0,531512

216

vehqual%c 0,691101

vehqual%d 0,664484

vehqual%e 0,788866

vehqual%f 0,837131

vehqual%g 0,602734

Path Coefficients After-sales quality Comfort Costs of ownership Expectations

After-sales quality

Comfort


Expectations

Image 0,318826

Loyalty


Sales quality

Value for money

Vehicle Design

Vehicle quality



Comfort

Costs of ownership


Image

Loyalty








Comfort 0,758564

Costs of ownership

217

Expectations

Image 0,080849

Loyalty


Sales quality

Value for money

Vehicle Design


Outer Weights After-sales quality Comfort Costs of ownership Expectations

comfort 0,271227

comfort%a 0,228339

comfort%b 0,176370

comfort%c 0,155357

comfort%d 0,133583

comfort%e 0,157692

comfort%f 0,157604

comfort%g 0,105982

comfort%h 0,133280

costs 0,223340

costs%a 0,095635

costs%b 0,191729

costs%c 0,271134

costs%d 0,238838

costs%e 0,211937

design

design%a

design%b

design%c

design%d

image

image%a

image%b

image%c

image%d

image%e

image%f

218

image%g

image%h

loyalty1

loyalty2

loyalty3

loyalty4

oczek%d 0,410311

oczek%f 0,379351

oczek%g 0,416126

sales

sales%a

sales%b

sales%c

sales%d

sales%e

sales%f

sales%g

sales%h

sales%i

sales%j

sat1

sat1a

sat1b

service 0,149729

service%a 0,154507

service%b 0,151026

service%c 0,131583

service%d 0,126007

service%e 0,138867

service%f 0,154127

service%g 0,142760

value1

value2

vehqual

vehqual%a

vehqual%b

vehqual%c

vehqual%d

219

vehqual%e

vehqual%f

vehqual%g


comfort

comfort%a

comfort%b

comfort%c

comfort%d

comfort%e

comfort%f

comfort%g

comfort%h

costs

costs%a

costs%b

costs%c

costs%d

costs%e

design

design%a

design%b

design%c

design%d

image 0,180053

image%a 0,166860

image%b 0,150272

image%c 0,184022

image%d 0,188729

image%e 0,099408

image%f 0,084730

image%g 0,128439

image%h 0,182850

loyalty1 0,315840

loyalty2 0,319585

loyalty3 0,268910

loyalty4 0,304374

220

oczek%d

oczek%f

oczek%g

sales 0,139083

sales%a 0,111480

sales%b 0,119984

sales%c 0,111997

sales%d 0,105346

sales%e 0,121582

sales%f 0,118556

sales%g 0,099577

sales%h 0,116801

sales%i 0,100462

sales%j 0,113910

sat1 0,341292

sat1a 0,343210

sat1b 0,347400

service

service%a

service%b

service%c

service%d

service%e

service%f

service%g

value1

value2

vehqual

vehqual%a

vehqual%b

vehqual%c

vehqual%d

vehqual%e

vehqual%f

vehqual%g

221


comfort

comfort%a

comfort%b

comfort%c

comfort%d

comfort%e

comfort%f

comfort%g

comfort%h

costs

costs%a

costs%b

costs%c

costs%d

costs%e

design 0,227457

design%a 0,169434

design%b 0,211009

design%c 0,240102

design%d 0,255229

image

image%a

image%b

image%c

image%d

image%e

image%f

image%g

image%h

loyalty1

loyalty2

loyalty3

loyalty4

oczek%d

oczek%f

oczek%g

sales

222

sales%a

sales%b

sales%c

sales%d

sales%e

sales%f

sales%g

sales%h

sales%i

sales%j

sat1

sat1a

sat1b

service

service%a

service%b

service%c

service%d

service%e

service%f

service%g

value1 0,506563

value2 0,503125

vehqual 0,220447

vehqual%a 0,197553

vehqual%b 0,104167

vehqual%c 0,152303

vehqual%d 0,144527

vehqual%e 0,175684

vehqual%f 0,187009

vehqual%g 0,130075

223


LV Index Values


Comfort 8,952333



Image 8,345158

Loyalty 8,331630






CUSTOMER LOYALTY

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