Reaserch Final

8/2/2019 Reaserch Final

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A RESEARCHA RESEARCH

PROJECTPROJECTONON

FINDING FACTORS

AFFECTING THE BRAND PREFERENCE:

A CASE STUDY ON AIRTEL BANGLADESH LIMITED.

Submitted to:

Professor A. K. FAZLUL H. SHAH

Department of Marketing

University of Dhaka

Submitted By:

Mohammad Mohaiminul Islam

Class Roll: 29

ID. NO: 40916018(16th

Bagch)EMBA program

Letter of Transmittal


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3rd May 2011

To

Professor A. K. FAZLUL H. SHAH

Department of Marketing

University of Dhaka

Subject: Report Submission

Dear Sir,

I am a student of EMBA (16h Batch), Department of Marketing, University of Dhaka. With

humble respect I would like to convey you knowledge that I have prepared my report. Thisreport writing assignment is a partial requirement of the course Advanced Marketing

Research in the EMBA program of Dhaka University. I have tried my best to prepare the

report in consistence with the optimal standard under your valuable direction.

I would be very grateful if you kindly accept this report. I tried heart and soul to make this

report as a complete one. It would be pleasure for us if this report can serve its purpose.

Sincerely,

Mohammad Mohaiminul Islam

ID# 4091601816h Batch, EMBA.

AcknowledgementAcknowledgement


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At the very beginning, I would like to express my deepest gratitude to the Almighty

ALLAH for giving me the strength and the ability to finish the task within the scheduled

time.

It should be mentioned that I am grateful to our course teacher professor A. K. FAZLUL H.

SHAH, Department of Marketing, University of Dhaka for their part on preparing thisreport. At last I wish to our entire course mates.

My sincere thanks goes to, all of my friends who gave the opportunity me to give time in

preparation of the report.

At last my sincere apology goes to the readers for my conceptual and printing mistakes, if

there is any.

Table of Contents

Letter of Transmittal

Acknowledgement


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Executive Summery

Problem Definition

Objective

Methodology

Approach to the Problem

Research Design

Data Analysis

Result

Conclusion

Recommendations

Exhibit

1.Executive Summery

A brand is a collection of images and ideas representing an economic producer; more

specifically, it refers to the concrete symbols such as a name, logo, slogan, and design

scheme. Brand recognition and other reactions are created by the accumulation of


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experiences with the specific product or service, both directly relating to its use, and

through the influence of advertising, design, and media commentary. A brand is a symbolic

embodiment of all the information connected to a company, product or service. A brand

serves to create associations and expectations among products made by a producer.

The brand, and "branding" and brand equity have become increasingly important

components of culture and the economy. Customers often say that they prefer a brand that

is reliable, available, affordability etc. The set of factors that finally determines customers

preference about a particular brand and which works as the key factor that makes them

choose a certain brand over others is the ongoing concern for both the market leader and

the followers. Based on this, the original problem statement has been constructed on a

specific product that is airtel sim.

Problem statement:

Research will be done to investigate whether the factors Corporate Image, Brand

Loyalty, Competitive Advantage, Value added services of the Product, Network quality,

Past Usage Experiences, Network Availability, Price, Advertising have significant

influence on brand preference forairtel , over its competitors like Grameen Phone, Aktel,

Banglalink, Citycell and Teletalk.

Therefore, the problem statement of this research is

FINDING FACTORS AFFECTING THE BRAND PREFERENCE: A CASESTUDY ON airtel Bangladesh Limited.

2. Problem identification

The problem was identified as the preference of the subscribers towards airtel is

decreasing day by day due to some factors though its revenue is still on rise, which are

identified as independent variables from the initial study.

Dependent Variable:

Brand Preference of airtel is decreasing day by day

Independent Variables:

1. Corporate image of Bharti Airtel will be a key factor on preferring Airtel SIM.

2. Brand loyalty towards airtel is very strong


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3. Competitive Advantage of airtel over other brands is unquestionable.

4. Voice quality of airtel is very satisfactory.

5. First test experience of airtel is unique

6. Users of airtel are satisfied.

7. Past Usage Experiences of airtel is enough for repurchasing.

8. Availability of Airtel SIM is in more than 95% of the entire market

9. Price of airtel is highly affordable

10. Advertising activities of airtel has always increased its demand in the market

11. Packaging of airtel is appraised by one & all

3.Approach to the problem

Due to unavailability of sufficient secondary data, very little was known about the

problem. So, the researcher conducted a qualitative investigation among some

judgmentally selected customers. They identified a number of factors including Corporate

Image, Brand Loyalty, Competitive Advantage, Value added services of the Product,

Network quality, Past Usage Experiences, Network Availability, Price, Advertising. It was

found from the exploratory study that the product, that provide the maximum value and

preference, gains the highest brand value from the customer. The preference occurs when

the offer provided by the seller wins the trade-off between cost & benefit. It is finally seenthat higher the preference creates higher brand value, and ultimately creates the higher

preference towards that brand.

Research Methodology

Research Design

This present study will investigate the influence of 11 independent variables on

brand preference towards airtel.

Data collection


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In this unique study, secondary sources of data are not sufficiently available. As a

result, the researcher requires primary data to investigate the research problem. To collect

data from the primary sources, the researcher will use questionnaire method. Survey will be

done among the DU students available at TSC.

Survey Instrument

Questionnaire: A structured questionnaire will be used to collect data from the respondent.

Sample size:The sample size of the research will be 30.

4. Methodology for Data Analysis

There are various types of data analysis which could be used for this study purpose. Forexample- ANOVA, Multiple Regression Analysis, Discriminant Analysis. As the study

included a relationship among some variables, multiple regression analysis was chosen.ANOVA was also necessary. Also the significance of the variables and their importance

was also needed to be analyzed. Considering the circumstances, we also carried out a

discriminant analysis. Details theoretical backgrounds and descriptions of these techniquesare given in the following subsections.

4.1 Multiple Regression Analysis

Regression analysis is used to describe the relationship among two variables. When there

are more than two variables, multiple regression analysis is applicable. In this study, thereare 10 independent variables acting upon the dependent variable. So use of multiple

regression analysis was justified.

Multiple regression analysis results in an equation, in which, the dependent variablebecomes a result from the summation of all the independent variables. The coefficient of

each of the independent variables results in the significance of it. That is, higher the

coefficient, higher the contribution of that independent variable. A positive sign in front ofthe independent variable means the contribution is positive. That is, an increase in the

contribution results in an increase in the dependent variable. Oppositely, a negative sign

means the contribution is negative and an increase in the contribution of that independent

variable would result in a decrease in the dependent variable.An example of such equation can be given below-

Y= 0+ 1X1+ 2X2+ 3X3+ 4X4+ 5X5+..+ nXnThe Y denotes the dependent variable and the X are the independent variables.

Multiple Regression analysis was also used to test the hypotheses. As the null hypothesis

was assumed that, there is no contribution of each of the factors over the dependentvariable, there was a measure required to identify the contribution of the factors. For this


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purpose the R2 value was used. The R2 value indicates the overall contribution or influence

of the independent variables on the dependent variable. If the value is zero, then it indicates

no summed contribution of the independent variables in building the build image. A valueabove zero indicates some contribution. So, clearly it indicates that a zero R2 value results

in an acceptance of the null hypothesis.

In a brief, the hypotheses test according to multiple regression analysis can be stated as

H0: R2 =0

H1: R2 0

4.2 Discriminant Analysis

Discriminant analysis is a marketing study analysis used when the dependent variable is

categorical and the independent variables are metric scaled in nature. Discriminant analysis

is a strong analytical tool for measuring the effects of some independent variables on a

dependent variable. On the basis of the influences of the independent variables, thedependent variable is grouped into some categories. The discriminant analysis shows the

significance of each of the independent variables in creating such categories, also theirrelative importance and their ability to distinguish among the categories.

Discriminant analysis results in some tables. These tables include the within meancorrelation tables, ANOVA table, test of significance tables,

Structured metric tables, standardized canonical discriminant coefficient tables etc. There

are some values based on which the analysis is done. Among these values, most importantones are- Wilks lambda, F ratio, standardized canonical discriminant function coefficient

etc. Wilks Lambda gives the categorization capability of the variables while F ratio givesthe significance of the variables and standardized canonical discriminant functioncoefficient gives the relative importance of each of the factors.

To convert the metric data into categorical data, the raw data was modified. The responsecategories from 1 to3 were assumed to be low response categories and were assigned the

number one in the SPSS variable view. Response categories 4to 6 were assigned number

two and response categories from 7 to 9 were assigned number three in the SPSS variableview.

5. Results

The data collected from the fieldwork were input in the SPSS. Before input, the variables

were declared in the variable view window. After then, in the data window, the data were

input. After inputting, analysis was made by clicking onto the analyze tab. For regressionanalysis, the linear regression was used and for discriminant analysis,

analyze>classify>discriminant tab was used. After then, two output windows were found.

Contents of these windows are analyzed and are given as results at the following sections.


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Oneway

ANOVA

BRAND_PREFERENCE

32.783 5 6.557 5.213 .002

30.183 24 1.258

62.967 29

Between Groups

Within Groups

Total

Sum ofSquares df

MeanSquare F Sig.

As we know, P (FCal )< 0.05.So, H0 is rejected.

1 2 3 .

5.1 Regression Analysis

5.1.1 Hypotheses Test

The hypotheses assumed for the hypotheses test were

H0: R2 =0

H1: R2 0

From the regression analysis, the following table was found

Model Summary

.798 a .637 .446 1.097

Model

1

R R SquareAdjusted R

Square

Std. Errorof the

Estimate

Predictors: (Constant), PACKAGING, PURCHASE_DECISION, AVAILABILITY, QUALITY,CORPORATE_IMAGE, PRICE, BRAND_NAME, AD_EFFECTIVENESS, TEST, SATISFACTION

a.

From it, it can be seen that, the value of R2 =.446 which is more than zero. R2 =0 means

there is no correlation among the variables. But as this value is .446 which is greater than

zero, this conclusion can be drawn that there is a significant amount of correlation amongthe variables. So, according to the one tailed test, the null hypothesis can be rejected which

means an automatic acceptance of the alternative hypothesis. That is, the decision can be

drawn that there are some relationships existing among the variables.

5.1.2 Relationship Analysis

The summary of the multiple regression analysis, from which the relationship is analyzed,

can be given in the following table.


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Coefficients a

.892 2.026 .440 .665

.349 .169 .387 2.064 .053

.007 .117 .011 .063 .950

-.498 .388 -.287 -1.284 .215

.113 .152 .147 .743 .466

-.124 .141 -.152 -.876 .392

.027 .350 .022 .077 .940

.797 .353 .671 2.256 .036

-.022 .258 -.019 -.087 .931

.415 .254 .394 1.634 .119

-.202 .176 -.289 -1.146 .266

(Constant)

CORPORATE_IMAGE

PURCHASE_DECISION

BRAND_NAME

PRICE

QUALITY

TEST

SATISFACTION

AVAILABILITY

AD_EFFECTIVENESS

PACKAGING

Model

1

B Std. Error

UnstandardizedCoefficients

Beta

Standardized

Coefficients

t Sig.

Dependent Variable: BRAND_PREFERENCEa.

As mentioned earlier in the data analysis section, these coefficients indicate therelationships among the variables. From this table, the following equation can be createdPR= 0.892 + 0.387 C + 0.011 P - 0.287 B + 0.147 Pr - 0.152 Q + 0.022 T + 0.671 S

- 0.019 A + 0.394 AD - 0.289 PA

Where,

PR= Preference of Airtel Sim

C = Corporate ImageP = Purchase Decision

B = Brand Name

Pr= Price

Q = Quality

T = TestS = Satisfaction

A = AvailabilityAD = Ad. Effectiveness

PA = Packaging

All the coefficients of the independent variables are not positive. It means, there is a

positive relationship between the dependent variable and few of the independent variable

and there is a negative relationship between the dependent variable and rest of the

independent variable. It means, an increase in some of the independent variable wouldresult in an increase in the dependent variable. In contrast a decrease in some other

independent variables would result in a decrease in the dependent variable. The followingsection shows how much contribution each of the independent variable has over thepreference of Airtel Sim.

Corporate Image has only 38.7 % positive contribution on the preference of AirtelSim

Purchase Decision has 1.1 % positive contribution

Brand Name has a negative contribution, 28.7 %


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Price has a positive contribution of 14.7 %

Quality has a negative contribution of 15.2 %

Test experience has a positive contribution of 2.2 %

Satisfaction has positive contribution of 67.1 %

Availability has negative contribution of 1.9 %

Ad. Effectiveness has 39.4 % positive contribution Packaging has a negative contribution of 28.9 %

Based on this regression analysis, the ratings can be done for the independent variables-

Effects of independent variables on preference of Airtel Sim and their corresponding

importance (Multiple Regression Analysis)

Name of the Variables Effect on the

preference of Airtel

Sim

Rank

SatisfactionCorporate Image

Ad. EffectivenessPrice

Test experience

Purchase Decision

AvailabilityVoice Quality

Brand Name

Packaging

High

Low

12

34

5

6

78

9

10

5.2 Discriminant Analysis

We have selected the Wilks Lambda coefficient, F ratio and standardized canonicalDiscriminant Function Coefficients for analysis of discrimination among the groups. There

are other measures based on which the analysis can be done. But due to the simplicity of

the project, we have adopted these techniques. The main part of the analysis can be givenin a tabular form-


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Tests of Equality of Group M eans

.998 .048 1 28 .827

.969 .892 1 28 .353

.960 1.159 1 28 .291

.985 .434 1 28 .515

.965 1.016 1 28 .322

.987 .365 1 28 .551

.809 6.613 1 28 .016

.911 2.723 1 28 .110

.901 3.089 1 28 .090

.987 .360 1 28 .553

CORPORATE_IMAGE

PURCHASE_DECISION

BRAND_NAME

PRICE

QUALITY

TEST

SATISFACTION

AVAILABILITY

AD_EFFECTIVENESS

PACKAGING

Wilks'

Lambda F df1 df2 Sig.

5.2.1 Analysis made on Wilks' Lambda

Wilks Lambda coefficient shows how much discrimination one independent variable can

make among the three categories imagined for the preference of bansaicars. The highervalues indicate lower discrimination ability and a lower value indicates higher

discrimination ability. The variable which causes the most discrimination among the

categories is indeed the most important one to look for.

The value of Wilks' Lambda is least for satisfaction. As we know, the lower the value, the

higher the ability to discriminate. So, satisfaction has the highest discriminating poweramong all the independent variables.

Corporate image, packaging, test and price have high Wilks' Lambda value. In fact these

values are the highest among all the independent variables. So it can be assumed thatcorporate image, packaging, test and price have a low discriminating capability.

Other independent variables have moderate values of Wilks' Lambda. So these independent

variables can be described as medium discriminating variables.

5.2.2 Analysis made on Standardized Canonical Discriminant Function Coefficients

Standardized Canonical Discriminant Function Coefficients shows the relative importance

of each of the independent variable in discriminating the categories of preference of Airtel

Sim. The lower value of an independent variable shows a lower importance while a highervalue shows the higher importance. From the table, it can be seen that, the value of lead

time has the highest Standardized Canonical Discriminant Function Coefficients. It means

this independent variable is the most important one, or the great influencer to discriminate


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among the three categories of preference. The following table shows the relative

importance of each of the independent variables.

Discriminating capability of independent variables over the categories of preference

and their corresponding importance (Standardized Canonical Discriminant Function

Coefficients Analysis)

Name of the Variables Effect on the

preference of Airtel

Sim

Rank

SatisfactionCorporate Image

Ad. Effectiveness

PriceTest

Purchase Decision

AvailabilityQuality

Brand Name

Packaging

High

Low

12

3

45

6

78

9

10

5.2.3 Significance test for the independent variables (Analysis made on F ratio)

F ratios indicate the significance of the independent variables effect in discrimination. The

degree of freedom according to the test of equality table is 1 and 28. Between these two

values, the F ratio is 5.213 (approx). The independent variable having a lower F ratio thanthis value means its effect is insignificant.

From the table of group means, it can be seen that, only corporate image has the lowest Fvalue(.048), and then Packaging(.360) .

All the other variables have a high significance as their F ratio value is much higher than

the theoretical value.


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6. Recommendation and Conclusion

After analyzing the results on both regression analysis and discriminant analysis

perspective, the following recommendations can be made

a. Preference ofAirtel Sim heavily depend on satisfaction. It proves that, customerspreferAirtel Sim because it ensures the highest satisfaction to the customer. As

Airtel Sim has offered this quality, it contributed highest amount in preference. So

the company should keep on serving such satisfaction in the future. This can be theprinciple quality for this company.

b. Corporate image also had a high amount of contribution in the preference. Thecorporate image of Airtel Sim is very high. This means that corporate image of the

telecom is very important to the customers.

c. Advertisement effectiveness brings the preference to Airtel Sim. So, it is

recommended that Airtel Sim must ensure the quality of the advertisement.

d. Packaging is negatively related to the preference development. But this can beovercome by providing better packaging quality, design.

e. The areas where Airtel Sim can improve customer preferences are availability,quality, test. Improvement in these areas can bring positive preference to the Airtel

Sim as presently these are negatively contributing to the preferences.


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7. Limitations of Study

Errors

Doing a study of such proportions may have resulted in errors to take place. Muchpotential error is systematic, the error that results from bias, while the remainder is

random. This study takes into account these cases of errors. Major sources of error

have been identified as follows:

Situation as an Error: This perhaps has been one of the principle sources of errors.

Such errors usually result from any condition that may have placed a strain on thesurvey. Customers who shop online are reluctant to take part in such studies

and pay no heed to such surveys the respondent could not freely answer the

questions. The physical and mental status of the respondent also at times resulted inerror as respondents varied in enthusiasm and participation depending on their mood.

Respondent as an Error: This kind of error results due to both non-response as well

as inaccurate perception with regard to a specific concept or construct of aquestionnaire. In this study, at times the respondents were reluctant to provide

extreme positive or negative views and preferred to reside in the neutral area.


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Exhibit A -QUESTIONNAIRE:

Following questions are some items that ask your opinions about airtel

SIM. Please fill up (

) one number per statement using the scale.

1. I prefer airtel among all other branded sim in the market.

Extremely

Disagree

Strongly

Disagree

Disagree

Some

what

Disagree

Neither

agree

nordisagree

Some

what

Agree

Agree Strongly

Agree

Extremely

Agree

1 2 3 4 5 6 7 8 9

2. Corporate image of airtel will be a key factor on preferring airtel SIM

Extremely

Disagree

Strongly

Disagree

Disagree

Some

what

Disagree

Neither

agree

nordisagree

Some

what

Agree

Agree Strongly

Agree

Extremely

Agree

1 2 3 4 5 6 7 8 9

3. I never purchase any other brand than airtel.

Extremely

Disagree

Strongly

Disagree

Disagree

Some

what

Disagree

Neither

agree

nordisagree

Some

what

Agree

Agree Strongly

Agree

Extremely

Agree

1 2 3 4 5 6 7 8 9

4. I feel Airtel is a better brand than other brands.

ExtremelyDisagree

StronglyDisagree

Disagree

Some

whatDisagree

Neither

agreenor

disagree

Some

whatAgree

Agree StronglyAgree

ExtremelyAgree

1 2 3 4 5 6 7 8 9

5. Price of airtel SIM is reasonable to me.

Extremely

Disagree

Strongly

Disagree

Disagree

Some

what

Disagree

Neither

agree

nordisagree

Some

what

Agree

Agree Strongly

Agree

Extremely

Agree

1 2 3 4 5 6 7 8 9

6. airtel SIM assure a better voice quality.

ExtremelyDisagree

StronglyDisagree

Disagree

Some

whatDisagree

Neither

agreenor

disagree

Some

whatAgree

Agree StronglyAgree

ExtremelyAgree

1 2 3 4 5 6 7 8 9

7. My first test experience of airtel SIM is unique.


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Extremely

Disagree

Strongly

Disagree

Disagree

Some

what

Disagree

Neither

agree

nor

disagree

Some

what

Agree

Agree Strongly

Agree

Extremely

Agree

1 2 3 4 5 6 7 8 9

8. The users of airtel SIM are satisfied.

Extremely

Disagree

Strongly

Disagree

Disagree

Some

what

Disagree

Neither

agree

nor

disagree

Some

what

Agree

Agree Strongly

Agree

Extremely

Agree

1 2 3 4 5 6 7 8 9

9. airtel SIM are available in all the major localities

ExtremelyDisagree

StronglyDisagree

Disagree

Some

whatDisagree

Neither

agreenor

disagree

Some

whatAgree

Agree StronglyAgree

ExtremelyAgree

1 2 3 4 5 6 7 8 9

10. airtel SIM have effective advertisement campaigns.

Extremely

Disagree

Strongly

Disagree

Disagree

Some

what

Disagree

Neither

agree

nor

disagree

Some

what

Agree

Agree Strongly

Agree

Extremely

Agree

1 2 3 4 5 6 7 8 9

11. airtel SIM have an attractive packaging.

Extremely

Disagree

Strongly

Disagree

Disagree

Some

what

Disagree

Neither

agree

nordisagree

Some

what

Agree

Agree Strongly

Agree

Extremely

Agree

1 2 3 4 5 6 7 8 9


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Exhibit B- Regression AnalysisOneway

ANOVA

BRAND_PREFERENCE

32.783 5 6.557 5.213 .002

30.183 24 1.258

62.967 29

Between Groups

Within Groups

Total

Sum ofSquares df

MeanSquare F Sig.

Regression

Variables Entered/Removedb

PACKAGING,PURCHASE

_DECISION,

AVAILABILITY,QUALITY,CORPORATE_IMAGE,PRICE,BRAND_NAME, AD_

EFFECTIVENESS,TEST,SATISFACTION

a

. Enter

Model1

Variables

Entered

Variables

Removed Method

All requested variables entered.a.

Dependent Variable: BRAND_PREFERENCEb.


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Model Summary

.798 a .637 .446 1.097

Model

1

R R SquareAdjusted R

Square

Std. Errorof the

Estimate

Predictors: (Constant), PACKAGING, PURCHASE_DECISION, AVAILABILITY, QUALITY,CORPORATE_IMAGE, PRICE, BRAND_NAME, AD_EFFECTIVENESS, TEST, SATISFACTION

a.

ANOVA b

40.114 10 4.011 3.335 .012a

22.853 19 1.203

62.967 29

Regression

Residual

Total

Model

1

Sum ofSquares df

MeanSquare F Sig.

Predictors: (Constant), PACKAGING, PURCHASE_DECISION,AVAILABILITY, QUALITY, CORPORATE_IMAGE, PRICE, BRAND_NAME,AD_EFFECTIVENESS, TEST, SATISFACTION

a.

Dependent Variable: BRAND_PREFERENCEb.

Coefficients a

.892 2.026 .440 .665

.349 .169 .387 2.064 .053

.007 .117 .011 .063 .950-.498 .388 -.287 -1.284 .215

.113 .152 .147 .743 .466

-.124 .141 -.152 -.876 .392

.027 .350 .022 .077 .940

.797 .353 .671 2.256 .036

-.022 .258 -.019 -.087 .931

.415 .254 .394 1.634 .119

-.202 .176 -.289 -1.146 .266

(Constant)

CORPORATE_IMAGE

PURCHASE_DECISIONBRAND_NAME

PRICE

QUALITY

TEST

SATISFACTION

AVAILABILITY

AD_EFFECTIVENESS

PACKAGING

Model1

B Std. Error

UnstandardizedCoefficients

Beta

Standardized

Coefficients

t Sig.

Dependent Variable: BRAND_PREFERENCEa.

Discriminant


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Analysis Case Processing Summary

30 100.0

0 .0

0 .0

0 .0

0 .0

30 100.0

Unweighted Cases

Valid

Missing orout-of-range group

codesAt least one missingdiscriminating variable

Both missing orout-of-range groupcodes and at leastone missingdiscriminating variable

Total

Excluded

Total

N Percent


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Group Statistics

6.47 1.922 15 15.000

4.73 2.086 15 15.0006.80 .941 15 15.000

5.20 1.656 15 15.000

5.27 1.580 15 15.000

6.40 1.454 15 15.000

6.13 1.302 15 15.000

7.13 1.457 15 15.000

6.67 1.718 15 15.000

6.13 1.885 15 15.000

6.33 1.345 15 15.000

5.47 2.167 15 15.000

7.13 .743 15 15.000

4.73 2.187 15 15.000

5.93 2.017 15 15.000

6.67 .900 15 15.000

7.20 .941 15 15.000

7.87 .915 15 15.000

7.53 .834 15 15.000

5.67 2.350 15 15.000

6.40 1.632 30 30.000

5.10 2.123 30 30.000

6.97 .850 30 30.000

4.97 1.921 30 30.000

5.60 1.812 30 30.000

6.53 1.196 30 30.000

6.67 1.241 30 30.000

7.50 1.253 30 30.000

7.10 1.398 30 30.000

5.90 2.107 30 30.000

CORPORATE_IMAGE

PURCHASE_DECISIONBRAND_NAME

PRICE

QUALITY

TEST

SATISFACTION

AVAILABILITY

AD_EFFECTIVENESS

PACKAGING

CORPORATE_IMAGE

PURCHASE_DECISION

BRAND_NAME

PRICE

QUALITY

TEST

SATISFACTION

AVAILABILITY

AD_EFFECTIVENESS

PACKAGING

CORPORATE_IMAGE

PURCHASE_DECISION

BRAND_NAME

PRICE

QUALITY

TEST

SATISFACTION

AVAILABILITY

AD_EFFECTIVENESS

PACKAGING

Gp1.00

2.00

Total

MeanStd.

Deviation Unweighted Weighted

Valid N (listwise)

Tests of Equality of Group Means

.998 .048 1 28 .827

.969 .892 1 28 .353

.960 1.159 1 28 .291

.985 .434 1 28 .515

.965 1.016 1 28 .322

.987 .365 1 28 .551

.809 6.613 1 28 .016

.911 2.723 1 28 .110

.901 3.089 1 28 .090

.987 .360 1 28 .553

CORPORATE_IMAGE

PURCHASE_DECISION

BRAND_NAMEPRICE

QUALITY

TEST

SATISFACTION

AVAILABILITY

AD_EFFECTIVENESS

PACKAGING

Wilks'Lambda F df1 df2 Sig.


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P o o l e d W i th i n - G r o u p s M a tr i c e s

1 .0 0 0 .2 3 8 .2 4 7 .2 7 7 .2 4 3 .4 9 6 .4 5 6 .2 6 1 .2 5 0 .6 1

.2 3 8 1 .0 0 0 .3 4 2 .1 1 8 .2 8 3 .3 8 8 .4 4 5 .0 7 5 .1 6 1 .2 9.2 4 7 .3 4 2 1 .0 0 0 .2 4 2 .4 8 7 .5 8 8 .7 4 2 .4 7 3 .6 2 2 .4 1

.2 7 7 .1 1 8 .2 4 2 1 .0 0 0 .3 6 5 .5 5 5 .4 2 8 .1 8 3 .2 3 4 .5 8

.2 4 3 .2 8 3 .4 8 7 .3 6 5 1 .0 0 0 .4 7 4 .5 3 2 .2 9 7 .3 9 2 .4 4

.4 9 6 .3 8 8 .5 8 8 .5 5 5 .4 7 4 1 .0 0 0 .8 1 1 .5 7 1 .6 2 7 .7 1

.4 5 6 .4 4 5 .7 4 2 .4 2 8 .5 3 2 .8 1 1 1 .0 0 0 .5 9 8 .5 8 4 .6 3

.2 6 1 .0 7 5 .4 7 3 .1 8 3 .2 9 7 .5 7 1 .5 9 8 1 .0 0 0 .6 6 8 .4 8

.2 5 0 .1 6 1 .6 2 2 .2 3 4 .3 9 2 .6 2 7 .5 8 4 .6 6 8 1 .0 0 0 .5 8

.6 1 4 .2 9 1 .4 1 7 .5 8 1 .4 4 6 .7 1 5 .6 3 1 .4 8 3 .5 8 8 1 .0

C O R P O R A T E _ IM A G E

P U R C H A S E _ D E C IS IO NB R A N D _ N A M E

P R IC E

Q U A L IT Y

T E S T

S A T IS F A C T IO N

A V A I L A B IL IT Y

A D _ E F F E C T IV E N E S S

P A C K A G IN G

C o r r e la ti o n

C O R P O R AT E _ IM A G E

P U R C H A S E _D E C IS IO N

B R A N D _N A M E P R IC E Q U A L IT Y T E S T

S A T IS F AC T IO N

A V A IL A BIL IT Y

A D _E F F E C T IV E N E S SP A C K A

Analysis 1

Summary of Canonical Discriminant Functions

Eigenvalues

.932 a 100.0 100.0 .695

Function1

Eigenvalue%of

VarianceCumulative

%CanonicalCorrelation

First 1 canonical discriminant functions were used in theanalysis.

a.

Wilks' Lambda

.518 15.149 10 .127

Test of Function(s)

1

Wilks'

Lambda Chi-square df Sig.

Standardized Canonical

Discriminant Function Coefficients

.058

.085

-.827

.037

.082

-.770

1.731

-.049

.817

-.889

CORPORATE_IMAGE

PURCHASE_DECISION

BRAND_NAME

PRICEQUALITY

TEST

SATISFACTION

AVAILABILITY

AD_EFFECTIVENESS

PACKAGING

1

Function


23/23

23

Structure Matrix

.503

.344.323

.211

.197

.185

-.129

.118

-.117

-.043

SATISFACTION

AD_EFFECTIVENESSAVAILABILITY

BRAND_NAME

QUALITY

PURCHASE_DECISION

PRICE

TEST

PACKAGING

CORPORATE_IMAGE

1

Function

Pooled within-groups correlations betweendiscriminating variables and standardized

canonical discriminant functionsVariables ordered by absolute size ofcorrelation within function.

Functions at Group Centroids

-.933

.933

Gp1.00

2.00

1

Function

Unstandardized canonical discriminantfunctions evaluated at group means

Reaserch Final

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Transcript of Reaserch Final