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AN EMPRICAL STUDY ON FACTORS INFLUENCING STORE IMAGE, SATISFACTION AND LOYALTY IN DEPARTMENT STORES 117

5 RESEARCH METHODOLOGY Simplicity is all. Simple logic, simple arguments, simple visual images. If you can’t reduce your argument to a few crisp words and phrases, there’s something wrong with your argument. There’s nothing long-winded about ‘Liberate, egalite, fraternite.’

Maurice Saatchi, M&C Saatchi

5.1 Introduction The research methodology enunciates the research process. It provides a systematic,

planned approach to the research project and ensures that all aspects of the research

project are consistent with each other. It is especially important that the research design

and implementation be consistent with the research purpose and objectives. Otherwise the

research will loose its purpose.

This chapter describes the research design and the procedures for conducting the study.

Specifically, this chapter describes the instrument development including pilot testing and

the sampling, data collection, and data analysis procedures. The data has been processed

through the eleven steps in the Marketing Research Process (Burns and Bush 2003).

5.2 The need for marketing research

During the past decades both marketing academics and practitioners have been intrigued

by the relationship between satisfaction and loyalty (Dick and Basu, 1994; Fornell et. al.,

1996; Hallowell, 1996; Kasper, 1988; LaBarbera and Mazursky, 1983; Newman and

Werbel, 1973; Oliver, 1996). Most of these studies, however, have concentrated on

products (brands) and to a somewhat lesser extent on services or channel

intermediaries. Surprisingly, research on the relationship between store, shopper, and

situational factors along with store image, satisfaction and store loyalty has remained

limited, both in actual number as well as in scope. Yet, in the present environment of

increased competition with rapid market entry of new store concepts and formats the

managerial challenge of increasing store loyalty also presents the research challenge of a

more in-depth understanding and an empirical estimation of this important type of

consumer behaviour.

There is some evidence that store loyalty may be (positively) related to store image

(Mazursky and Jacoby, 1986; Osman, 1993). However, it has remained unclear what the

exact relationship between store, shopper, and situational factors along with store

image, satisfaction and store loyalty in a retail setting is. For instance, one question


that has been left unanswered concerns the issue whether there is a direct relationship

between store image and store loyalty and whether there is an indirect relationship

via store satisfaction. This study is an attempt on acknowledging a shopper and what

contributes to his/ her loyalty for a particular store.

5.3 Definition of the problem

Defining the problem is the most important step in the research process. Why? What else

matters if we have defined the problem incorrectly?

The problem here is identified in terms of understanding the relationship between store,

shopper, and situational factors along with store image, satisfaction and store loyalty.

5.4 Establishing the Research Objectives

Research objectives, although related to and determined by the problem definition, are set

so that, when achieved, they provide the information necessary to solve the problem.

The relevance of the research is both from industry and academic viewpoints. The

objectives of this research are…

1. To compare the service and quality offered by sample stores.

2. To ascertain the factors influencing shopper’s choice and satisfaction towards a

department store.

3. To find out the relationship between store satisfaction and store loyalty.

4. To bring forth suggestions to improve store image, customer satisfaction and

loyalty.

5.5 Developing Research Hypothesis

Research hypothesis, framed on the basis of research objectives illustrated above provide

critical mass for analysis and evaluation of data and decipher concrete findings. The

hypotheses framed for the study include…

Hypo 1 Demographic factors play a significant role in shaping shopper’s buying behavior.

Hypo 2 Shopper’s perceived store image is a consequence of his or her demographics.

Hypo 3 Demographic profile of shopper plays an important role in determining the level of satisfaction shopper derives from his or her patronized department store.


5

Hypo 4 Demographic profile of shopper has an important bearing in shaping shopper’s loyalty for the department store he or she regularly visits.

Hypo 5 There is a significant difference in shoppers buying behavior patterns and the store location the shopper shops from.

Hypo 6 There is a significant difference among shoppers perception towards store image and the location of the store they shop from.

Hypo 7 There is a significant difference in level of satisfaction shoppers derive and the location of the store they shop at.

Hypo 8 There is a significant difference among shopper’s loyalty behaviour and the location of the store they shop at.

Hypo 9 There is a significant difference among shopper’s buying behaviour in respect to the store brand they usually shop at.

Hypo 10 There is a significant difference among shopper’s perceived store image and the store brand they usually visit.

Hypo 11 There is a significant difference in level of satisfaction shoppers derive and the store brand they usually visit.

Hypo 12 There is a significant difference among shopper’s loyalty behaviour and the store brand they usually visit.

Hypo 13 There is a significant difference among shoppers buying behaviour and the store format they usually visit.

Hypo 14 There is a significant difference among shoppers for their perceived store image and the store format they usually visit.

Hypo 15 There is a significant difference among shoppers in the degree of satisfaction derived and the store format they usually visit.

Hypo 16 There is a significant difference among shoppers in the level of loyalty displayed and the store format they usually visit.

Hypo 17 Location of the store and the frequency of visits of a shopper commits to a store determines his or her average money spent.

Hypo 18 Store brand and location determines the shopper’s perception towards the store factors.

Hypo 19 Among all store factors product quality and promotion have major influence on shopper’s buying behavior.

Hypo 20 Store factors have a positive effect on store satisfaction. Among all store factors, product quality, promotion, credit terms and store atmosphere have greater bearing on store satisfaction.

Hypo 21 Store factors have a positive effect on store loyalty.

Hypo 22 Satisfaction has positive effect on store loyalty.


5.6 Determining Research Design

While every research project is different yet there are enough similarities among research

projects to enable us to categorize them by the research methods and procedures used to

collect data and analyze data.

Research Design is the framework or plan for a study (research) used as a guide in

collecting and analyzing data. It is also a blueprint to follow in completing a study. The

purposes of making a proper research design are:

a. To ensure that the study is relevant to the research problem

b. To ensure that the study uses relevant and economical procedures

c. To learn more about research methods

There is never a single, correct, optimal or standard method for carrying out research

(Molde university College website).

Our basic research design process is Descriptive. Further the study is cross sectional in

nature so as to describe the statistical association between two or more variables.

5.7 Identifying Information Types and Sources

Basically, two types of information are available to a marketing researcher: secondary data

and primary data.

The most major type of information utilized by us is primary data. This is done thru one on

one interview at the place of discussion i.e., the department store, both stand-alone or at

malls.

The literature review is a secondary data type. The sources have been books, periodicals,

websites, printed literature about the industry etc.

5.8 Determining Methods of Accessing Data

How is this accomplished? It depends largely upon the type of data needed. Compared to

the primary data, accessing secondary data is relatively easy, especially in today’s age of

the internet.


The survey research methods have been employed for accessing the primary data. This

has been taken care of thru designing of the Questionnaire and self-administered: face to

face interviews.

The secondary data is taken from newspapers, books, periodicals, internet search, printed

literature on retail sector, and business reports etc.

5.9 Design Data Collection Form

The design of the data collection that is used to ask and record information gathered in

marketing research projects is critical to the success of the project.

5.9.1 Instrument Development

A structured questionnaire was developed to collect data on the variables in this study. The

questionnaire includes over 100 items that are related to the characteristics of store

factors, shoppers’ buying behaviour, customer satisfaction and store loyalty in Likert Scale

and demographic characteristics in nominal, interval and ratio scale.

The items are refined and paraphrased in both wording and contextual application as

appropriate to suite research purposes. To obtain a comprehensive and industry specific

measure of the shoppers’ buying behaviour, store satisfaction and loyalty construct, the

research based on retail sector was undertaken.

The respective scales are used for pilot so as to get feedback on all parameters i.e.,

shopping habit, buyer behaviour, store image, store satisfaction and store loyalty. The pilot

was administered to 50 respondents. The one on one interviews brought out some of the

shortcomings clearly. The same are listed below…

The questions were more westernized and less pertinent in the Indian market.

Some Indian features in terms of what Indian shoppers look forward to, were

although missing.

Buyer behaviour and store image questions were very direct while the questions

from satisfaction and loyalty were subtle and gentle and could not get the desired

inputs.


It was difficult to cater to so many cross-sections.

Table 5.1. Questions for Department Store Customers

Component Previous Studies Items of Questions

Quality Kunkel & Berry, Lindquist

Excellence of quality relative to other stores Excellence of quality relative to price

Price Kunkel & Berry, Nevin & Houstan

Low price relative to other stores Reasonable price relative to product Overall lowness of product prices

Assortment Kunkel & Berry, Berman & Evans

Availability of new (fashionable) products Variety of brands Variety of product design and colours Variety of kinds of products

Promotion Kunkel & Berry, Lindquist, Berman & Evans

Frequency of sales Scope of sale product Providence of new product information Invitation of cultural events and special

sales Sending cards for birthday and anniversary Frequency of gift events

Advertisement Kunkel & Berry, Lindquist, Hansen & Deutscher

Information providence of advertisement Usefulness of shopping plan advertisement Appeal of advertisement

Convenience of Shopping

Hansen & Deutscher Easy movement within the store Easy search of wanted goods Possibility of blanket purchase

Convenience of Location

Lindquist, Easy entrance and exit to parking lot Connection to public transport (bus and

metro)

Store Facilities Easy use of physical facilities of the store (escalator, elevator, kids play area)

Well assorted rest area (seating, toilets)

Salesperson Service Kunkel & Berry, Lindquist, Hansen & Deutscher, Brown & Churchill

Kindness of salesperson Assistance of sales person on product and

related information Affirmative action and solution to complaints

by salesperson

Credit Service Kunkel & Berry, Lindquist, Hansen & Deutscher

Variety of credit cards accepted Easy return and exchange of goods

Store Brand Hansen & Deutscher High class image High brand name

Store Atmosphere Kunkel & Berry, Lindquist, Hansen & Deutscher

Happiness of shopping experience Luxurious atmosphere of lighting, colour,

and facilities

Store Loyalty Samli, Zeithaml, Berry, Parasuramam

Favourable wording Repetitive purchase Intention of repurchase


The respondents’ suggestions were better tuned to split the buyer behaviour and

store image questions.

The comments and observation from pilot led to…

A single questionnaire with questions split under various sections.

Addition of many questions on satisfaction and loyalty parameters.

Deletion of some questions which were either not very persistent to Indian public or

they were aware of.

The Likert scale with the legend was placed at conspicuous place to aid the

respondents.

The duly tested and finalized questionnaire is displayed in Appendix. All the questionnaire

questions are close ended except for the demographic profiling questions. The details of

questionnaire with variable definition and measurement is illustrated in table 5.2.

Table 5.2. Variable Definitions and Measurements

Variable Name Details of Measure

Shopping Habit

Shopping habit of respondents is determined by establishing their… - frequency of visit to a store

(where 1=Ebony, 2=Globus, 3=Lifestyle, 4=Pantaloons and 5=Shoppers’ Stop)

- goods purchased (1=Apparels, 2=Accessories, 3=Home decor, and 4= Gifts)

- average spending per visit (1=Less than Rs.2,000, 2=Rs.2,001 to Rs.5,000, 3=Rs.5,001 to Rs.10,000, 4=More than Rs.10,000)

Buyer Behaviour

To understand shopper’s buying behaviour respondents were asked… - their liking or disliking for shopping - purchases being made as impulse or necessity - seeking variety in assortment in a store - looking for trendy and fashionable assortment - whether shopper being shopping freak or not

In all 25 statements are generated to seek respondents’ buying behaviour. Statements are rated on 1 to 5 scale (where 1=Strongly Disagree, 2=Disagree, 3=Neither Agree nor Disagree, 4=Agree, and 5=Strongly Agree)


Store Image

To capture shopper’s perceived image for the store they patronize, respondents are asked to rate…

- merchandise quality, price and assortment of the store

- promotion and advertisement initiatives of the store - convenience of shopping at store - convenience of location at the store - store facilities - store service (salesperson and credit) - store atmosphere - store brand

35 statements are asked on a sale of 1 to 5 (where 1=Strongly Disagree, 2=Disagree, 3=Neither Agree nor Disagree, 4=Agree, and 5=Strongly Agree)

Store Satisfaction

To capture shopper’s satisfaction with the shopping experience the respondents are asked to rate…

- price of the goods - convenience of approach

- availability of goods - service quality - add on service(s) provided - transparency in billing - service efficacy of sales person - promotional offers and discounts - store layout and ambience - overall satisfaction with the store

Ten statements are asked on a sale of 1 to 5 (where 1=Highly Dissatisfied, 2=Dissatisfied, 3=Neither Satisfied nor Dissatisfied, 4=Satisfied, and 5=Highly Satisfied)

Store Loyalty

Loyalty is determined by asking respondents… - do they feel proud to be customer of this

department store - is the store you patronize keen on customer

feedback - would you eagerly recommend this store to your

friends and colleagues - would you continue to shop at this store even if

you get a better option to shop at - in lieu of any inefficiency at store, you would not

hesitate to recommend any appropriate action.

Statements are rated on a sale of 1 to 5 (where 1=Strongly Disagree, 2=Disagree, 3=Neither Agree nor Disagree, 4=Agree, and 5=Strongly Agree)


5.9.2 Sampling Plan

Under this heading details, details about the population, sampling frame, sampling unit,

sampling procedure, sample size and contact method have been provided.

5.9.2.1 Population

All the shoppers visiting department stores (Ebony, Globus, Lifestyle, Pantaloons and

Shopper Stop) either in ‘stand alone’ stores or ‘malls’ from the population of the study.

These above mentioned stores are limited to National Capital Region- NCR (Delhi,

Ghaziabad, Gurgoan, Faridabad, and Noida). The universe or the population is thus the

shoppers visiting above stated department stores in National Capital Region.

5.9.2.2 Sampling Frame

The population for this study as stated above is from NCR. This includes the national

capital Delhi, besides the satellite township of Ghaziabad, Gurgoan, Faridabad and Noida.

India happens to be one of the most happening places for retail (ranked third in AT

Kearney Global Retail Development Index (GRDI) Survey, 2010 after China and Kuwait).

And within India NCR has emerged as fastest growing retail destination. Being

cosmopolitan and resembling more of India, NCR has emerged as leading attraction for

organized retailers. Moreover, it amalgamates metro and sub-urban areas, ensuring more

vividness among shoppers and markets. Also, there is large influx of department stores in

Demographic Variables

The respondents are asked… - age (1=18-24 years, 2=25-34 years, 3=35-44 years, 4=45-54 years, 5=55-64 years and 6=65 and over)

- gender (1=male, 2=female)

- family size (number of members in the family) - education (1=high school, 2=senior school, 3=graduate, 4=post graduate, and 5=professional)

- vocation (1=white collar, 2=self employed, 3=sales/skilled, 4=housewife, and 5=others) - income (per annum) (1=up to Rs.3,00,000, 2=Rs.3,00,001 to Rs.6,00,000, 3=Rs.6,00,001 to Rs.10,00,000, 4=More than Rs.10,00,000)


NCR with multiple outlets. So as to make it a representative sample the following

department stores are considered for narrowing down…

a. Ebony

b. Globus

c. Lifestyle

d. Pantaloons

e. Shoppers’ Stop

The sampling frame for the study was done after due diligence, table 5.3 illustrates the

sample frame for the study.

5.9.2.3 Sample Unit

Who is to be surveyed or who can constitute the sampling unit, is very critical and needs to

be answered rightly since the proper prediction about population can be made only when

Table 5.3 Sample Frame Store Brand Location Format Address

EBONY

Delhi

Stand Alone

South Extn. II, ND-49

Faridabad Mall Crown Plaza, Sector 15 A, Faridabad.

GLOBUS

Delhi

Stand Alone

South Extension II, ND-49

Ghaziabad Mall Pacific Mall, Kaushambi, Ghaziabad

Noida Mall Unitech Mall, Sector 38 A, Noida

LIFESTYLE

Delhi

Stand Alone

MGF City Square, Rajouri Garden, ND-27

Gurgoan Mall DLF City Center, Gurgoan-02

Noida Mall Unitech Mall, Sector 38 A, Noida

PANTALOONS

Delhi

Mall

Saket Mall, DC, Saket Delhi-25

Ghaziabad Stand Alone Plot #9, Indirapuram, Ghaziabad

Noida Stand Alone Great Indian Place, Sector 38A, Noida

SHOPPERS

STOP

Delhi

Stand Alone

Ansal Plaza, Andrew Ganj, ND-49.

Gurgoan Mall The Metropolitan Mall, Gurgoan-02


the sampling units are the true representative of the population. Sampling unit for this

study is the department store shopper of the above mentioned stores.

5.9.2.4 Sample Size

Sample Size is one of the most important parameters in the sample, being the true

representative of Population or the Universe under study. It is paradoxical to state here

that the size of the population is not that important as the variability between the

respondents. Assuming the highest variability of 50% and designing for a ± 5% Sample

error at 95 percent level of confidence the number of respondents required is 384 (Burns

and Bush 2003, pp. 392). We have taken a sample size of 500 all of which were

administered personally. The questionnaires were got filled by the shoppers at particular

department stores. The list of department store and location with numbers of respondents

is detailed in table 5.4.

5.9.2.5 Sampling Procedure

The target population for the study consisted of department stores shoppers at the five

listed department stores NCR (Delhi, Ghaziabad, Gurgoan, Faridabad, and Noida). The

survey was based on the random visit at random times to the department stores for

interaction with randomly chosen shoppers without any bias or judgment. The study was

also undertaken at the respective department stores at different times to further minimize

the bias.

Table 5.4. Data Collection Framework and Actual Store Brand Location Format Sample Size Total

Planned Actual

EBONY Delhi Stand Alone 50 51 101

Faridabad Mall 50 50

GLOBUS

Delhi Stand Alone 50 51 103 Ghaziabad Mall 25 26

Noida Mall 25 26

LIFESTYLE

Delhi Stand Alone 50 51 102 Gurgoan Mall 25 25

Noida Mall 25 26

PANTALOONS

Delhi Mall 50 51 103 Ghaziabad Stand Alone 25 26

Noida Stand Alone 25 26

SHOPPERS STOP

Delhi Stand Alone 50 51 102

Gurgoan Mall 50 51

Delhi Satellite towns Malls Stand Alone TOTAL

255 256 255 256 511


5.9.2.6 Contact method

At the pilot stage as also during the actual survey stage, the questionnaires were filled by

interviewing them personally.

The final realized sample included a total of 511 usable questionnaires, representing 100

percent success rate primarily.

The questionnaire was pre-tested using a convenience sample of approximately 50

respondents. Final data was collected over a period of three months. The study included a

variety of respondents, like genders, different age groups, education, occupation and

income levels to minimize any bias.

We have used Stratified Random Sampling in the said department stores by taking

randomly equal (nearly) number of respondents so as to study any relationships between

the two. About 250 shoppers each have been interviewed at ‘stand alone’ store and ‘malls’.

Similarly, nearly 100 respondents have been interviewed at each retail outlet with 50 each

from ‘stand alone’ store and ‘mall’ of that store (see table 5.4).

5.10 Collection of Data

Data collection is extremely important because, regardless of the data analysis methods

used, data analysis can not ‘fix’ the bad data (Clancy and Shulman 1994).

The data was collected on the Questionnaires personally to minimize the non-sampling

errors. The questionnaires were not got filled up from the non interested or ‘much in a

hurry’ respondents.

5.11 Analyzing Data

Once data are collected, data analysis is used to give the raw data meaning. Data analysis

involves entering data into computer files, inspecting the data for errors, and running

tabulations and various statistical tests. The first step is the data cleaning.

5.11.1 Reliability and Validity of the Instrument

Measures of variables should have reliability and validity (Cronbach, 1971; Nunally, 1978)

so as to draw valid inferences from the research. Reliability deals with how consistently


identical measures produce identical results (Rosenthal & Rosnow, 1984), and it has the

two dimensions of repeatability and internal consistency (Zigmund, 1995).

Internal consistency refers to the ability of a scale item to correlate with other items in the

scale that are intended to measure the same construct. Items measuring the same

construct are expected to be positively correlated with each other. A common measure of

the internal consistency of a measurement instrument is Cronbach’s alpha. If the reliability

is not acceptably high, the scale can be revised by altering or deleting items that have

scores lower than a pre-determined cut-off point. If a scale used to measure a construct

has an alpha value greater than 0.70, the scale is considered reliable in measuring the

construct (Hair, Anderson, Tatham, and Black, 1998; Nunnally, 1978; Leedy, 1997).

According to Schuessler (1971), a scale is considered to have good reliability if it has an

alpha value greater than 0.60. Hair, Anderson, Tatham, and Black (1998) suggest that

reliability estimates between 0.6 and 0.7 represent the lower limit of acceptability for

reliability estimates.

In this research, the multi-item scales measuring expectations and perceptions of the

shoppers were checked for reliability by determining Cronbach’s alpha and an alpha value

of 0.60 or greater was considered acceptable. The validity of a measurement instrument

refers to how well it captures what it is designed to measure (Rosenthal & Rosnow, 1984).

Several different types of validity are of concern: content validity, the degree of

correspondence between the items selected to constitute a summated scale and its

conceptual definition; criterion validity, the degree of correspondence between a measure

and a criterion variable, usually measured by their correlation; and construct validity, the

ability of a measure to confirm a network of related hypotheses generated from a theory

based on constructs.

Cronbach’s alpha coefficient ranges from 0.0 to 1.0 and reflects the strength of the

relationship between items within a scale. If the Cronbach’s alpha coefficient is close to 1.0

then it implies that the item is measuring similar dimensions of a construct.

The table 5.5 below demonstrates each of the Alpha values for the 75 variables to be

much above 0.60. The 75 variables are: 25 variables for shoppers’ buying behaviour, 35


variables for store image, 10 variables for store satisfaction and 5 variables for store

loyalty. To be specific, in the case of the shoppers’ buying behaviour instrument the alpha

value is in excess of 0.90. The alpha value for each of the 35 variables for the store image

instrument is above 0.92. The alpha value for each of the 10 variables for the store

satisfaction is above 0.79. And the alpha value for each of the five variables for the store

loyalty is above 0.89.

Table 5.5. Cronbach’s Alpha Coefficients Construct Number of Items Cronbach’s Alpha

Shoppers’ Buying Behaviour 25 0.902

Store Image 35 0.923

Store Satisfaction 10 0.796

Store Loyalty 05 0.894

This establishes the reliability and validity of the instrument without any doubt and hence

no fine tuning or changes in the instruments are required.

The reliability analysis for each of the above constructs namely, shopper’s buying

behaviour, store image, store satisfaction and store loyalty is detailed in tables 5.6, 5.7, 5.8

and 5.9 respectively in following pages.


Table 5.6. Reliability Analysis for Shoppers’ Buying Behaviour Construct R E L I A B I L I T Y A N A L Y S I S - S C A L E (C R O N B A C H’ S A L P H A)

Statistics for Scale

Mean Variance SD No. of Variables

93.69 157.32 12.54 25 Item Mean

Mean Minimum Maximum Range Max/Min

3.75 3.55 4.23 0.68 1.19 Item Variances


0.85 0.24 1.08 0.84 4.49

Item-total Statistics

Scale Mean

if Item Deleted

Scale Variance if

Item Deleted

Corrected Item-Total Correlation

Squared Multiple

Correlation

Cronbach's Alpha if Item

Deleted

‘prefer shopping’ 89.98 147.59 0.796 0.730 0.896

‘impulse purchasing‘ 90.09 142.85 0.777 0.875 0.893

‘visit to seek ideas’ 90.03 143.74 0.749 0.825 0.894

‘seek variety at stores’ 90.02 142.71 0.754 0.825 0.893

‘shop to replace old wear’ 89.98 142.98 0.776 0.846 0.893

‘frequent shopper’ 89.54 147.28 0.518 0.323 0.898

‘visit to see new’ 89.93 145.19 0.487 0.506 0.898

‘fuel price as hindrance’ 90.02 147.37 0.379 0.223 0.901

‘active lifestyle’ 89.90 140.46 0.829 0.912 0.891

‘shop at many stores’ 90.05 141.94 0.588 0.737 0.896

‘stays with trends’ 90.11 145.98 0.408 0.234 0.900

‘prefer traditional styles’ 90.01 145.75 0.419 0.266 0.900

‘less fashion considerate’ 90.11 147.30 0.365 0.179 0.901

‘buy known brands’ 90.07 147.91 0.336 0.172 0.902

‘buy private labels too’ 90.14 147.44 0.364 0.209 0.901

‘reference to others’ 90.06 144.90 0.470 0.634 0.899

‘buy acceptable trends’ 90.12 148.12 0.328 0.159 0.902

‘feel good when buying’ 90.08 146.36 0.396 0.251 0.900

‘fashion pacesetter’ 90.12 146.86 0.400 0.245 0.900

‘excessive spending’ 90.10 147.55 0.377 0.572 0.901

‘buying reflects oneself’ 90.07 145.09 0.471 0.406 0.899

‘planned shopping trips’ 89.58 147.24 0.418 0.362 0.900

‘dress better than others’ 89.51 148.37 0.401 0.280 0.900

‘plan wardrobe’ 89.46 144.71 0.525 0.438 0.897

‘apparel persona match’ 89.54 144.00 0.577 0.437 0.896

Reliability Coefficients 25 items

Alfa=0.902 Standardized item Alfa=0.913


Table 5.7. Reliability Analysis for Store Image Construct R E L I A B I L I T Y A N A L Y S I S - S C A L E (C R O N B A C H’ S A L P H A)



1.31 305.87 17.49 35 Item Mean


3.75 3.51 4.23 0.71 1.20 Item Variances


0.91 .471 1.216 0.75 2.58


Scale Mean

if Item Deleted

Scale Variance if

Item Deleted


Squared Multiple

Correlation


Deleted

‘quality assortment’ 127.15 290.91 0.565 0.460 0.920

‘assortment– other stores’ 127.43 293.77 0.376 0.283 0.922

‘excellent service’ 127.02 289.27 0.472 0.406 0.921

‘reasonable pricing’ 127.09 288.57 0.535 0.409 0.920

‘cheaper private labels’ 127.47 291.66 0.402 0.230 0.922

‘pricing matches quality’ 127.47 290.96 0.435 0.313 0.921

‘high prices’ 127.57 292.72 0.349 0.409 0.922

‘latest fashion trends’ 127.59 289.41 0.449 0.468 0.921

‘wider range than others’ 127.58 288.79 0.504 0.441 0.920

‘varied design & colours’ 127.49 291.98 0.387 0.265 0.922

‘wide range’ 127.42 284.22 0.803 0.885 0.918

‘regular sales & discounts’ 127.67 290.89 0.430 0.292 0.921

‘inform new arrivals’ 127.56 293.25 0.354 0.405 0.922

‘events’ 127.61 291.92 0.367 0.281 0.922

‘anniversary cards’ 127.72 289.48 0.405 0.457 0.922

‘informative adds’ 127.70 290.20 0.431 0.314 0.921

‘adds guide shopping’ 127.59 288.86 0.478 0.428 0.921

‘convenience in shopping’ 127.64 287.83 0.518 0.323 0.920

‘free movement’ 127.56 290.19 0.450 0.278 0.921

‘goods display’ 127.61 290.29 0.437 0.309 0.921

‘one roof shopping’ 127.66 290.06 0.456 0.319 0.921

‘parking enter & exit’ 127.55 288.66 0.511 0.416 0.920

‘public transport’ 127.49 288.27 0.512 0.335 0.920

‘proximity to home/office’ 127.54 286.06 0.567 0.531 0.920

‘comfortable facilities’ 127.47 285.49 0.628 0.469 0.919

‘well assorted rest area’ 127.01 292.11 0.567 0.437 0.920

‘courteous sales staff’ 127.53 286.95 0.586 0.463 0.919

‘well informed sales staff’ 127.39 286.71 0.545 0.416 0.920

‘affirmative sales staff ’ 127.36 288.84 0.519 0.366 0.920

‘easy payment mode’ 127.48 287.24 0.510 0.417 0.920

‘exchange & return’ 127.60 289.57 0.475 0.341 0.921

‘happiness’ 127.46 290.33 0.463 0.341 0.921

‘luxurious atmosphere’ 127.44 288.26 0.513 0.395 0.920

‘high class image’ 127.56 287.68 0.512 0.366 0.920

‘high brand name’ 127.36 284.20 0.623 0.500 0.919




Table 5.8 Reliability Analysis for Store Satisfaction Construct R E L I A B I L I T Y A N A L Y S I S - S C A L E (C R O N B A C H’ S A L P H A)



40.61 24.94 5.00 10 Item Mean


4.06 3.94 4.48 0.54 1.14 Item Variances


0.71 0.64 0.77 0.13 1.20


Scale Mean if Item Deleted

Scale Variance if Item Deleted


Squared Multiple

Correlation


Deleted

‘price’ 36.13 19.95 0.585 0.362 0.765

‘convenience’ 36.67 21.82 0.316 0.138 0.796

‘availability’ 36.66 21.05 0.442 0.249 0.781

‘service quality’ 36.67 20.59 0.451 0.244 0.781

‘add on services’ 36.63 20.58 0.461 0.265 0.779

‘billing’ 36.57 20.99 0.399 0.190 0.787

‘sales staff’ 36.58 20.55 0.483 0.294 0.777

‘offers & discounts’ 36.62 20.48 0.485 0.276 0.776

‘store lay out’ 36.58 20.62 0.486 0.264 0.776

‘overall satisfaction’ 36.35 20.01 0.583 0.400 0.765



Table 5.9 Reliability Analysis for Store Loyalty Construct

R E L I A B I L I T Y A N A L Y S I S - S C A L E (C R O N B A C H’ S A L P H A) Statistics for Scale


19.98 7.02 2.65 5 Item Mean


4.00 3.15 4.62 1.47 1.47 Item Variances


0.40 .302 0.57 0.27 1.89


Scale Mean

if Item Deleted

Scale Variance if

Item Deleted


Squared Multiple

Correlation


Deleted

‘proud to be customer’ 15.36 4.79 0.760 0.599 0.868

‘customer feedback’ 16.83 4.32 0.762 0.648 0.867

‘recommend’ 16.03 5.06 0.670 0.492 0.887

‘ever patronize’ 15.97 4.99 0.682 0.470 0.884

‘ask action on any lapse’ 15.73 3.88 0.864 0.763 0.843




5.11.2 Demographic Profile of the Sample

Table 5.10 depicts the demographic characteristics of the overall sample for the

department stores comprising of 511 respondents in total.

Table 5.10. Demographic Characteristics of overall sample

Frequency Percent

Age

18-24 years 152 29.7

25-34 years 152 29.7

35-44 years 104 20.4

45-54 years 103 20.2

Total 511 100.0

Gender

Female 205 40.1

Male 306 59.9

Total 511 100.0

Marital Status

Single 281 55.1

Married 229 44.9

Total 510 100.0

Number of Family Members

1.00 004 00.8

2.00 020 03.9

3.00 113 22.1

4.00 204 39.9

5.00 126 24.7

6.00 044 08.6

Total 511 100.0

Education

Senior School 024 04.7

Graduate 293 57.3

Post Graduate 108 21.1

Professional 086 16.8

Total 511 100.0

Occupation

White Collar 143 27.9

Self Employed 164 32.1

Sales/ Skilled 149 29.2

Housewife 029 05.7

Other 026 05.1

Total 511 100.0

Annual Income

Up to Rs. 3,00,000 180 35.2

Rs. 3,00,001 to Rs. 6,00,000 178 34.8

Rs. 6,00,001 to Rs. 10,00,000 074 14.5

Rs. 10,00,001 and Above 079 15.5

Total 511 100.0


Figure 5.1- Age (in years) of Respondents

The sample has dominance of youth with about 60 percent of them in age group of less

than 35 years. Rest 40 percent of respondents are in the age group of 35 to 54 years.

Figure 5.2- Gender of Respondents

Males dominate the sample with a little less than 60 percent of them included in the

survey. Of the 511 respondents participating in the study 305 are males and rest 206, a

little above 40 percent are females.


Figure 5.3- Marital Status of Respondents

Married respondents are reported to be less (about 45 percent) to one who are single

(about 55 percent). Since the sample representation is more for younger population in the

age group of 18-34 years, single status is predominant.

Figure 5.4- Number of Family Members of Respondents

About two-third of respondents surveyed for this study has a family size of four or less

members. Respondents who participated in study usually have family size of four members

(about 40 percent) or five members (about 25 percent).


Figure 5.5- Education Level of Respondents

Most of the respondents are graduates (about 58 percent) or post graduates (about 21

percent). About 17 percent of respondents included in the study are having professional

qualifications and only a little less than five percent among them are school pass outs.

Figure 5.6- Occupation of Respondents

Respondents are largely self employed (nearly 32 percent) or either are sales/ skilled

professional (about 30 percent) or have white collar jobs (about 28 percent). About six

percent of respondents include house wives and nearly five percent rest has other jobs.


Figure 5.7- Annual Household Income of Respondents

House hold income of respondents varies in the range of less than Rs.3,00,000 per annum

and Rs.3,00,001 to Rs.6,00,000 (about 35 percent each) and Rs. 6,00,001 to Rs.

10,00,000 and Rs. 10,00,001 & Above (about 15 percent each).

5.11.3 Pearson Correlation Coefficient Matrices

Some degree of multicollinearity [The situation in which two or more predictors (or subsets

of predictors) are strongly (but not perfectly) correlated to one other, making it difficult to

interpret the strength of the effect of each predictor (or predictor subset). For example, it

would be hard to detect a gene if its effect is 'absorbed' (or masked) by combinations of

genetic background action/interaction parameters in the model)] is desirable in factor

analysis since the objective is to identify interrelated sets of variables. Moderate to

moderate-high intercorrelations without multicollinearity are not mathematically required,

but applying factor analysis to a correlation matrix with only low intercorrelations will

require for solution nearly as many principal components as there are original variables,

thereby defeating the data reduction purposes of factor analysis. On the other hand, too

high intercorrelations may indicate a multicollinearity problem and colinear terms should be

combined or otherwise eliminated prior to factor analysis. KMO statistics may be used to

address multicollinearity in a factor analysis.

(http://www2.chass.ncsu.edu/garson/pa765/factor.htm)


Measured by the Kaiser-Meyer-Olkin (KMO) statistics, sampling adequacy predicts if data

are likely to factor well, based on correlation and partial correlation. KMO can be used in

the present times to assess which variables to drop from the model because they are too

multicollinear.

There is a KMO statistic for each individual variable, and their sum is the KMO overall

statistic. KMO varies from 0 to 1.0 and KMO overall should be 0.60 or higher to proceed

with factor analysis. If it is not, drop the indicator variables with the lowest individual KMO

statistic values, until KMO overall rises above 0.60.

(http://www2.chass.ncsu.edu/garson/pa765/factor.htm#kmo)

If visual inspection of correlation matrix reveals substantial number of correlations greater

than 0.30, then factor analysis is appropriate (Hair, Anderson, Tatham, and Black, 1998).

http://www2.chass.ncsu.edu/garson/pa765/factor.htm#kmo


Table 5.11. Pearson Correlation Matrix for Shoppers’ Buying Behaviour

SB01 SB02 SB03 SB04 SB05 SB06 SB07 SB08 SB09 SB10 SB11 SB12 SB13

SB01 1

SB02 .550** 1

SB03 .637** .615** 1

SB04 .510** .653** .579** 1

SB05 .536** .755** .623** .794** 1

SB06 .380** .448** .442** .361** .403** 1

SB07 .319** .342** .630** .327** .341** .299** 1

SB08 .335** .314** .310** .276** .338** .339** .197** 1

SB09 .550** .734** .756** .868** .875** .440** .435** .329** 1

SB10 .349** .691** .674** .563** .631** .326** .344** .239** .658** 1

SB11 .281** .289** .295** .309** .313** .198** .268** .257** .331** .230** 1

SB12 .348** .326** .319** .285** .257** .267** .258** .119** .319** .163** .157** 1

SB13 .284** .276** .305** .276** .261** .160** .257** .119** .291** .203** .087 .181** 1

SB14 .256** .270** .219** .289** .279** .205** .088* .141** .278** .167** .099* .124** .166**

SB15 .354** .235** .301** .298** .248** .174** .217** .182** .304** .185** .127** .223** .131**

SB16 .293** .638** .310** .549** .615** .265** .183** .206** .548** .302** .161** .203** .187**

SB17 .231** .266** .298** .215** .236** .231** .250** .137** .269** .242** .172** .226** .155**

SB18 .323** .327** .319** .336** .280** .221** .242** .169** .317** .240** .214** .247** .198**

SB19 .298** .299** .332** .335** .353** .218** .242** .124** .366** .263** .255** .223** .237**

SB20 .213** .579** .254** .227** .280** .231** .250** .147** .292** .226** .170** .254** .151**

SB21 .369** .293** .327** .557** .364** .210** .205** .151** .459** .235** .203** .245** .244**

SB22 .321** .292** .254** .256** .269** .266** .190** .214** .267** .150** .133** .181** .170**

SB23 .321** .263** .289** .313** .341** .260** .195** .170** .324** .237** .197** .216** .120**

SB24 .373** .383** .374** .363** .357** .274** .165** .224** .392** .284** .250** .254** .166**

SB25 .401** .402** .415** .387** .391** .285** .291** .184** .436** .332** .281** .269** .259**

Continued …

SB14 SB15 SB16 SB17 SB18 SB19 SB20 SB21 SB22 SB23 SB24 SB25

SB14 1

SB15 .170** 1

SB16 .169** .084 1

SB17 .136** .133** .128** 1

SB18 .257** .161** .178** .164** 1

SB19 .153** .177** .187** .121** .068 1

SB20 .199** .148** .167** .150** .149** .157** 1

SB21 .200** .304** .230** .161** .257** .138** .093* 1

SB22 .164** .158** .174** .125** .159** .167** .135** .181** 1

SB23 .128** .158** .183** .106* .105* .191** .075 .174** .286** 1

SB24 .200** .210** .244** .135** .161** .253** .196** .250** .476** .378** 1

SB25 .229** .274** .252** .180** .222** .281** .180** .294** .458** .410** .484** 1

N= 511 ** Significant at 0.01 confidence level.

* Significant at 0.05 confidence level.


Table 5.12. Pearson Correlation Matrix for Store Image

SI01 SI02 SI03 SI04 SI05 SI06 SI07 SI08 SI09 SI10 SI11 SI12 SI13

SI01 1

SI02 .238** 1

SI03 .297** .284** 1

SI04 .248** .261** .515** 1

SI05 .262** .260** .184** .278** 1

SI06 .177** .151** .189** .316** .193** 1

SI07 .197** .134** .210** .260** .199** .153** 1

SI08 .275** .227** .269** .306** .235** .162** .096* 1

SI09 .297** .157** .205** .297** .213** .199** .151** .262** 1

SI10 .210** .194** .362** .278** .161** .214** .153** .185** .235** 1

SI11 .391** .255** .385** .446** .319** .339** .472** .529** .533** .278** 1

SI12 .204** .176** .193** .240** .240** .268** .217** .145** .185** .225** .373** 1

SI13 .091* .076 .170** .271** .160** .265** .229** .170** .122** .120** .489** .197** 1

SI14 .245** .027 .175** .218** .112* .123** .185** .128** .280** .028 .379** .175** .161**

SI15 .292** .185** .238** .234** .193** .228** .230** .150** .298** .085 .521** .149** .177**

SI16 .309** .151** .215** .259** .156** .177** .216** .279** .250** .154** .397** .170** .116**

SI17 .289** .189** .331** .304** .232** .204** .171** .248** .254** .233** .535** .290** .149**

SI18 .313** .229** .266** .301** .211** .236** .203** .228** .284** .278** .420** .302** .190**

SI19 .294** .206** .185** .234** .193** .230** .275** .182** .169** .211** .383** .262** .149**

SI20 .176** .185** .263** .306** .240** .207** .163** .300** .265** .284** .431** .272** .157**

SI21 .374** .181** .237** .290** .218** .280** .292** .246** .276** .108* .369** .141** .203**

SI22 .307** .205** .242** .258** .254** .244** .256** .256** .301** .236** .571** .277** .269**

SI23 .353** .196** .216** .248** .245** .231** .241** .201** .357** .205** .474** .262** .202**

SI24 .347** .192** .235** .331** .200** .277** .232** .327** .311** .248** .608** .368** .233**

SI25 .422** .282** .292** .301** .310** .301** .258** .292** .386** .295** .524** .278** .286**

SI26 .468** .219** .272** .275** .283** .244** .211** .310** .253** .201** .400** .190** .160**

SI27 .446** .313** .295** .324** .277** .277** .196** .217** .358** .234** .403** .266** .168**

SI28 .376** .330** .234** .318** .223** .247** .200** .196** .294** .233** .402** .149** .164**

SI29 .366** .232** .351** .306** .241** .209** .220** .217** .255** .286** .385** .268** .150**

SI30 .412** .176** .232** .254** .205** .256** .116** .232** .238** .244** .335** .281** .132**

SI31 .297** .135** .219** .237** .164** .294** .109* .237** .292** .206** .340** .214** .202**

SI32 .258** .279** .285** .252** .233** .177** .190** .107* .219** .244** .306** .169** .148**

SI33 .324** .260** .299** .274** .262** .223** .163** .200** .313** .226** .416** .239** .202**

SI34 .388** .265** .167** .228** .159** .248** .171** .270** .216** .197** .366** .237** .206**

SI35 .385** .294** .287** .357** .292** .162** .223** .294** .337** .272** .482** .269** .212**


The correlation coefficients in the above tables are all in the significant zone at more than

95% confidence level and hence ready for Factor analysis and such further studies. We

also observe here that most of the correlations are above 0.300, the Factor Analysis is in

order. We continue the detailed analysis of data through the next chapter.

Continued…

SI14 SI15 SI16 SI17 SI18 SI19 SI20 SI21 SI22 SI23 SI24 SI25 SI26

SI14 1

SI15 .267** 1

SI16 .182** .256** 1

SI17 .224** .197** .220** 1

SI18 .177** .261** .295** .294** 1

SI19 .191** .212** .213** .280** .288** 1

SI20 .201** .204** .158** .322** .186** .221** 1

SI21 .270** .257** .217** .175** .282** .279** .122** 1

SI22 .202** .240** .229** .265** .296** .265** .248** .246** 1

SI23 .260** .298** .291** .318** .313** .328** .221** .223** .292** 1

SI24 .282** .209** .248** .327** .330** .248** .292** .297** .327** .362** 1

SI25 .194** .321** .297** .304** .338** .335** .318** .318** .410** .377** .472** 1

SI26 .175** .255** .296** .274** .278** .230** .209** .295** .268** .303** .310** .296** 1

SI27 .275** .245** .254** .302** .299** .256** .250** .294** .307** .369** .331** .385** .332**

SI28 .198** .257** .384** .272** .342** .265** .258** .221** .282** .280** .317** .361** .414**

SI29 .186** .143** .222** .277** .270** .319** .307** .236** .249** .311** .331** .251** .378**

SI30 .142** .154** .168** .251** .232** .226** .244** .274** .261** .290** .296** .320** .402**

SI31 .216** .160** .252** .227** .269** .151** .285** .171** .228** .229** .268** .251** .363**

SI32 .156** .235** .241** .253** .341** .227** .175** .234** .210** .210** .229** .260** .390**

SI33 .315** .259** .108* .246** .232** .198** .322** .213** .359** .362** .366** .364** .313**

SI34 .166** .223** .265** .185** .331** .274** .139** .294** .273** .268** .296** .317** .411**

SI35 .230** .320** .225** .289** .343** .300** .311** .251** .335** .298** .370** .383** .463**

Continued…

SI27 SI28 SI29 SI30 SI31 SI32 SI33 SI34 SI35

N= 511 ** Significant at 0.01 confidence level. * Significant at 0.05 confidence level.

SI27 1

SI28 .391** 1

SI29 .382** .289** 1

SI30 .493** .334** .250** 1

SI31 .331** .381** .349** .298** 1

SI32 .275** .337** .352** .227** .299** 1

SI33 .453** .333** .296** .391** .244** .218** 1

SI34 .322** .397** .298** .347** .309** .305** .224** 1

SI35 .445** .435** .374** .377** .393** .387** .401** .375** 1


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http://www2.chass.ncsu.edu/garson/pa765/factor.htm

http://www2.chass.ncsu.edu/garson/pa765/factor.htm#kmo


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