Mgrl Implication Binary Logistic

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Prepared by Saurabh Bhattacharya@ IBS, Hyderabad for MR Sec (E) ON 05.09.2012 Page 1

Data Methodology, Analysis and Managerial Implication for

Dell Direct

Logistic Regression

(Case 1.1; page 772-776 of MR course Book)

Managerial Problem- To determine whether differences in the perception about Dell PC

exist between the recent purchasers of Dell PC who are very satisfied versus those who are

dissatisfied

Objective of the Study

1) Identifying the important variables that impact group membership (very satisfied vsdissatisfied) of the recent purchasers of Dell PC.

2) Establishing a classification system for determining group membership.Data and Methodology

A survey method was used by Burke, an independent marketing research firm to collect the data

required for the study. 372 recent purchasers of Dell PCs and notebooks participated in the study.

Apart from demographic and other basic information, the questionnaire consisted of 13 items

measuring the customers perception of performance of Dell computers on various aspects like

make ordering, quality of peripherals, ease of assembling the computer, speed, quick delivery

etc. The 13 items were rated by the customers on a 9 point likert scale ranging from dont agree

at all (1) to agree completely (9). Respondents were also asked a question on over all satisfactionwith dell computer system on a four point scale- very satisfied (1) to very dissatisfied (4). Burke

then recoded the overall satisfaction item into two categories very satisfied (coded as 1) and

dissatisfied (coded as 0). Since the objective of the study is identify the important variables that

help to discriminate between two groups very satisfied and dissatisfied, either a discriminant or a

logistic regression analysis could be used. Both the approaches deal with categorical dependent

variables. The advantage of logistic regression over discriminant analysis is that it could be used

when none of the assumptions of regression are met. In this manner logistic is a more robust

technique than discriminant analysis. Thus Burke decided to use logistic regression over the data

collected. In the given study SPSS Ver 17.0 was used and the output obtained is given below-


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Analysis

The total number of respondents is 372 and there are no missing cases. The dependent variable

overall satisfaction is a categorical variable with dissatisfied being coded as 0 and very

satisfied being coded as 1. Thus a positive (negative) coefficient for an independent variable

indicates that increasing (decreasing) values of that independent variable indicates an increasing

(decreasing) likelihood of very satisfied classification.

Logistic regression in SPSS is conducted using two steps. In step 0 only the constant term is

present while in step 1 all the significant independent variables are considered along with theconstant term. The step 0 classification table indicates that when no independent variable is

considered then at least 55.9% of the respondents (belonging to the satisfied group) will be

correctly classified. This indicates that if no logistic regression is applied, by chance a correct

classification of 55.9% will be achieved. Thus classification due to logistic regression should be

atleast as good as 55.9%. In the next step i.e., step 1 all the significant independent variables are

considered.

As regards to the predictive accuracy of the model (step 1), the Nagelkerkes R square points out

to the fact that the model with independent variables accounts for 34.2 % of the variance of how

respondents were categorized as very satisfied or dissatisfied. The goodness of fit of the logisticmodel is further reflected by the Hosmer and Lemeshow test. Since the chi square value of 7.112

with eight degrees of freedom is more than .05, the test is insignificant indicating that the model

has a good fit.

In step 1 all the independent variables which are significant at .05 level are considered. In the

present study quick delivery, competitive price, speed and high quality peripherals all have


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Walds statistics which are significant at .05 level. Further the direction of the relationship of

quick delivery, competitive price, speed and high quality peripherals with overall satisfaction is

positive as indicated by the positive beta values (B) of .216, .491, .158, .380 respectively and

Exp (B) of all the variables being greater than 1. The magnitude of the relationship is as follows-

Quick Delivery --------------(1.241-1)*100% = 24.1%

Competitive Price-----------(1.634-1)*100% =63.4%

Speed -------------------------(1.171-1)*100 = 17.1%

High Quality Peripherals ---(1.463-1)*100% =46.3%

Thus a one unit change in quick delivery, competitive price, speed and high quality peripherals

implies the likelihood that a person will be categorized as very satisfied increases by 24.1%,

63.4%, 17.1% and 46.3% respectively. Thus the most important variable for classification is

competitive price, followed by high quality peripherals, quick delivery and speed. The logisticregression has also led to an increase in the number of appropriately classified as compared to

the step 0 classification from 55.9 % to 71.8%. The hit ratio of 71.8% using logistic regression

is further better than the proportional chance criterion Cpro (Cpro = p^2 +(1-p)^2) = (55.9)^2

+(44.1)^2) = 51%, where p is the proportion of people in the sample who are satisfied) and

thereby indicating that the model is externally valid and generalizable.

Managerial Implications

The study conducted by Burke (a marketing research consultancy) on the behalf of Dell points

out to the fact that four variables namely- quick delivery, competitive price, speed and highquality peripherals are the most important factors for Dell. The classification of the consumers as

very satisfied increases as these factors increase. Also among the four variables competitive price

is the most important variable and thus Dell if it needs to thrive in the PC and notebook market

should remain price competitive. It can also be argued that these four variables are the ones

which are creating the difference between a satisfied and dissatisfied purchaser. Any future

marketing communication of Dell should highlight on these four aspects of Dell computers.

Mgrl Implication Binary Logistic

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