Aligning Demographics for Segmentations

MALL MOTIVATIONS IN INDIA

ALIGNING DEMOGRAPHICS FOR SEGMENTATIONS

Ritu Srivastava,

Assistant Professor, School of Management,

Gautam Buddha University, Greater Noida, U.P.,

Abstract

Purpose: Mall Management is a new discipline in India where Consumer Motivations and Market Segmentation are concerns of the Marketing strategy that Mall Managers must understand essentially to craft success. This study addresses these concerns with the objectives of identifying the primary reasons/ motivations for Indian customers to visit malls and analysing the influence of demographic variables of Age, Education, Income and Gender on the identified customer motivations to visit malls that could affect mall patronage and segmentation.

Research Design and Methodology: The study is a cross sectional survey executed in the National Capital region (NCR) of New Delhi, India. The data was collected from more than 600 respondents through a “Mall Intercept Survey” from 27 malls. Factor Analysis was used to identify the Shopping Motivations. Multivariate Analysis of Variance was done to analyse whether the Select Demographic variables create a variation in the Shopping Motivations.

Findings: People in India visit malls in India for Diversion/Browsing, Economic Reasons, Shopping Environment, Refreshments and Snacking, Services and Social Experience. Of the select demographic factors only Age shows a significant effect on shopping motivations in malls in India, individually. However interactions in various combinations are relevant for different shopping motivations. Within each demographic variable different level behave differently with respect to each shopping motivational factor. This finding is important for mall planners and retailers when planning their market segmentation strategy.

Value: The paper will help mall managers/retailers in India design their marketing strategies better with respect to shopper motivations and demographic influences.

Keywords:-India, Retailing, Malls, Shoppers, Demographic Variables, Market Segmentation

[1] 1. INTRODUCTION The study would throw light on;

Malls in India mirror the present stage of  The principle reasons for which people Indian consumerism and Organized Retail life cycle. visit malls in India; The Indian retail industry is in its’ growth phase with the gradual phasing of the Foreign Direct  What is the direction of the trend, hedonic Investment (FDI) restrictions, since 1996 to 2012. or utilitarian? While the industry itself is as old as business in India, it has basically existed in unorganized form.  The effect of select Demographic factors Even today organized retail accounts for only 7% of on Retail Market Segmentation strategy India’s approximately $435 billion market that is 4. SHOPPING MALLS expected to grow at 20% by 2020 (A.T. Kearney, 2011). The regulatory changes coupled with the The study builds on the significant distinction in lifestyle changes have changed the business models shopping benefits that is utilitarian versus hedonic wherein the customers have become more values. Utilitarian values involve satisfying basic demanding and competition intense. physiological needs and assuring the security of satisfying purchase performance whereas hedonic To garner success firms must have very clear values involve fun, gratification and pleasure. understanding of fundamental and critical strategic Utilitarianism involves an attempt to reduce needs business decisions such as; arising from states of deprivation, whereas  Who is our customer? hedonism involves pleasure seeking instead of pain avoidance. Hedonism is a prominent feature of the  Why does he come to us? consumer culture and results in an endless and ultimately unfulfilling quest for novelty, primarily  How are we going to serve them, i.e., why through consumption (Campbell, 1987; Tse, Belk should he come to us? and Zhou, 1989; Dholakia, 1999; Solomon, 2002; Arnold and Reynolds, 2003; Rintamäki et.al, 2006). 2. RESEARCH OBJECTIVES An insight of these two values is given below.

To answer the third question a retailer has to 4.1 Utilitarian Benefits answer the first two. This study germinates at this point with a focus on the Mall Customers Consumers may be attracted to a particular addressing following objectives; shopping centre because of the existence of special store that appeals to them (Nevin and Houston,  What are the primary reasons / 1980; Bleomer and Ruyter, 1998; Koo, 2003). To motivations for Indian customers to visit illustrate; anchor stores, consisting of a mix of mass malls? merchandise anchors and department store anchors, help draw customers to a shopping centre.  Do demographic variables of Age, Non anchors also sometimes have a high customer Education, Income and Gender create a drawing power (Andersen, 1985; Ibrahim and variation in the customer motivations to Galven, 2007). The smaller specialty stores typically visit malls? found in the malls include bookshops, music stores, gift shops, apparel and shoe stores etc. to satisfy 3. RESEARCH OUTCOME the consumer desire for comparison shopping. Competitors generally locate their stores in close

[2] proximity in these shopping centres. Mall Jarboe and McDaniel, 1987; Bloch et al., 1989; attractiveness also increases with agglomeration of Lombart, 2004; Lombart and Labbe´-Pinlon, 2007). diverse retailers (Kimball, 1991; Brown, 1992; Browsers may make unplanned purchases because Balaz, 1995; Yavas, 2001; Nicholls et al 2002, Ismail, of in-store promotions and exposure to new 2007). To reduce the time and cost of shopping, products. They also gather information in advance consumers may sometimes by pass closer stores to of future purchasing (Bloch and Richins, 1983; visit agglomeration stores which are farther away in Bloch, Ridgway and Sherell, 1989). The browsers order to shop for different types of goods on the are also effective word of mouth advertisers, peer same trip (Ghosh, 1986). This phenomenon of influencers and trend setters especially for socially multipurpose shopping can offer “one stop for all visible products (Jarboe and Mc Daniel, 1987; needs”, to more cost and time efficient functional Nsairi, 2012). shoppers. 5. RESEARCHING THE MALL SHOPPER IN 4.2 Hedonic Benefits INDIA

Since an increasing number of consumers use While malls have been an interest of research convenience as a primary basis for making purchase for more than forty years, country specific research decisions, retailers generally tend to focus on related to Mall Management in India is only about a consumer purchase patterns and to ignore the decade old. The Indian researchers have been emotional benefits that can be provided during working on consumer visit to malls with respect to shopping activities (Babin et al, 1994). Shopping shopping style orientations (Sinha, 2003), shopper may be done for emotional and experiential boredom which encourages out-shopping (Roy and reasons (Babin et al, 1994; Tauber 1972, Westbrook Masih, 2007; Singh and Bose, 2008), sustainability and Black 1985; Jones, 1999; Arnold and Reynolds, of shopping malls in India (Srivastava, 2008), in 2003; Lotz et al., 2010). The mall offers experiences context of Gen Y (Hemalatha, Jagannathan and that are consumable and mall managers do build Ravichandran, 2009), shopper attributes and retail on this trend by organizing special events format (Prasad and Aryasri, 2010), and consumer (Christman, 1988). decision making styles (Reji Kumar, Sudharani and Harisunder 2010).Whereas there is an emergence Traditionally malls have offered patrons the of research in this field, it is still a new area and advantage of climate comfort and freedom from research done is in isolation. the noise and traffic that characterize other shopping venues. Some shoppers may be 6. RESEARCH DESIGN AND METHODOLOGY interested in “seeing new items and learning about new trends”; others may go shopping in their The study has been designed as a cross leisure time (Tauber, 1972; Hirschman and sectional descriptive study executed in the National HollBrook, 1982; Dholakia, 1999, Arnold and Capital region (NCR) of New Delhi, India. India has Reynolds, 2003; Howard, 2007). Malls have become approximately 200 malls (Singh, Bose, Sahay, 2010) places that provide opportunities for social of which almost one third are in the NCR. Delhi NCR experience outside home (Richardson, 1993). Many and Mumbai pioneered mall development and people enjoy the pleasant, park like atmosphere contribute nearly 79 per cent of available mall (Balazs, 1994). The regional shopping mall offers space (Taneja, 2007).The NCR region was divided maximum opportunity for browsing and browsers into nine zones, East, North, West, South Delhi, are often considered to be essential to the success Gurgaon, Faridabad, Noida, Greater Noida and of such an institution (Bloch and Richins, 1983; Ghaziabad. The data was collected from more than

[3] 600 respondents through a “Mall Intercept Survey”, highly correlated among themselves but have by trained MBA student enumerators who were relatively smaller correlations with motivational specializing in Retail Management. Altogether reasons in a different group. In consequence, it is twenty seven malls, three from each zone, across conceivable that each group of motivational nine zones of NCR of New Delhi were randomly reasons represents a single unobserved random selected for the survey. The survey instrument was variable named as factor, which is responsible for a questionnaire that was prepared in consultation the observed correlation among the motivational from industry and academic literature in the reasons. Mathematically factor model of p domain. motivational reasons and m common factors is represented in matrix notation as; 7. FACTOR ANALYSIS [1] The data is collected in the form of score on seven point Likert type scale through individual The factor loading lij are estimated by the interview using a questionnaire from more than popular estimation procedure, principal component

600 hundred selected respondents. The collected method. In order to summarize the information data from the questionnaires were filter out for contained in the original p variables, m number of missing values, duplication and other anomalies, factors is extracted. finally 532 data points were used for the analysis. Based on the value of the Kaiser-Meyer-Olkin Initially Shopping motivations of mall shoppers Measure of Sampling Adequacy (KMO = 0.836) and were evaluated through p = 31 original variables high chi-square value of the Bartlett’s test of such as “I visit malls to get best deals”, or “I visit Sphericity (Chi-sq = 3507 with degree of freedom = malls just to enjoy crowds” etc. but examining the 531), which shows the degree of common variance value of communality, the part of the total variance among the variables is quite high, Factor analysis explained by the common factors, greater than 0.5 technique is undertaken to explain the covariance (Table 2) only p=22 variables were iteratively relationships among the motivational reasons for retained in the analysis. In the absence of any prior Mall Shoppers (Table 1). information, the number of factors (m) is estimated through evaluation of following facts. Table 1: KMO and Barlett’s Test of Sphericity Table 2: Variables Retained in the Analysis based Kaiser-Meyer-Olkin Measure of 0.836 on Extracted Communalities Sampling Adequacy Bartlett's Test of Sphericity Chi- Square (approximate) 3507 Degree of freedom 231 Level of significance 0.000 This in turn, describes the covariance relationship in terms of few underlying, but unobservable random quantities called Factors. However, the factor analysis is guided by the following argument that motivational reasons can be grouped by their correlations. That is, all motivational reasons within a particular group are

[4] VARIABLES UNDER should be six. Thus, six factors of motivational reasons are extracted, which explains 60.34 per OBSERVATION INITIAL EXTRACTION cent of the total variability, were named as MEALS 1.000 0.589 Diversion/Browsing, Economic Reasons, Shopping FRIENDS 1.000 0.535 Environment, Refreshments and Snacking, Services AVOID BOREDOM 1.000 0.672 and Social Experience (Table 3). To enhance the FUN 1.000 0.651 interpretation, these extracted factors were FIND GOOD PRICES 1.000 0.681 orthogonally rotated by varimax procedure with BUY 1.000 0.560 Kaiser Normalization. COMPARISON SHOP 1.000 0.613 HASSLE FREE PARKING 1.000 0.661 6 CLEAN AND POSH ENV 1.000 0.528 GYM/SPA 1.000 0.535 5 CHANGE 1.000 0.585 OTHER SERVICES 1.000 0.635 4 s e

HAIR AND BEAUTY 1.000 0.536 u l a V OUT OF HOUSE 1.000 0.576 3 n

MULTIPLE SHOPPING 1.000 0.532 e g i BETTER STORE E 2 1.000 0.590 PERSONNEL CONVENIENCE SHOPPING 1.000 0.682 1 SNACK 1.000 0.562 MEAL AT FOOD COURT 1.000 0.657 0 1 4 7 10 13 16 19 22 SPEND TIME WITH 1.000 0.642 Number of Motivational Reasons of Mall Shoppers FAMILY CHILD ENJOY 1.000 0.741 BEST DEALS 1.000 0.513

Table 3: Factor Influencing Motivational Reasons of Mall Shoppers The Scree plot, which is nothing but a plot between number of eigen values and factor of motivational Facto Factor Loadin Variables reasons in order of extraction, has distinct break r Interpretatio g Included in point between the steep slope of factors and a n the Factors gradual trailing off associated with rest of the (% Variance factors. This gradual trailing off points indicated the Explained) possible number of factors and it is observed to be F1 Diversion/ Avoid 0.794 six in this analysis (Figure 1). At the same time the Browsing Boredom eigen values of these factors are greater than one (13.16% ) 0.755 Fun whereas other factors has less than one, which 0.722 Out Of again indicate the extracted number of factors House

[5] The items included in the second motivational 0.707 Change factor are; “to find good price” (0.803), “to 0.619 Friends comparison shop” (0.729), “buying” (0.683), and for Find Good “for best deal” (0.633). This is a utilitarian function 0.803 Prices for which the customer visits the mall and focus on Economic Comparison 0.729 price related reasons. F2 Reasons Shop 0.683 Buy (12.377% ) 7.3 Shopping Environment 0.633 Best Deal Better Store Service atmosphere and physical evidence are 0.697 Personnel an established part of the marketing strategy. Clean And 0.665 Consumers wish to shop in a pleasant atmosphere. Shopping Posh Convenienc This means that instead of following more F3 Environment 0.631 es Shopping traditional consumption related motives as was the (10.521% ) Hassel Free 0.607 cases in India, consumers now visit malls also Parking Multiple because it presents an attractive décor and 0.563 Shopping pleasant atmosphere. The results in Table 3 Refreshment 0.751 Meals highlight these trends. Indian Consumers go to s and Meal At malls for “Better store personnel” (0.697), “Clean F4 0.678 Snacking Food Court and Posh Environment” (0.665), “Conveniences (8.876% ) 0.648 Snacks Shopping” (0.631), “Hassel Free Parking” (0.607), Other “Multiple Shopping” (0.563). These have been 0.782 Services captured in this motivational factor. This is a Services F5 Gym/ Spa hedonic motive. (8.441% ) 0.683 Hair And 7.4 Refreshments and Snacking 0.628 Beauty Social Let My Child 0.821 An excellent restaurant or food court provides F6 Experience Enjoy unique dining opportunity for which a consumer (6.967% ) 0.668 Spend Time With Family may visit a mall. Food consumption has become a major reason to visit such places. Items included in 7.1 Diversion/ Browsing this factor were; “To Have a Meal at the The first factor accounted for 13.16% variance. Restaurant” (0.751), “To Have a Meal at the Food The items located in this factor with their factor Court” (0.678), and “When I want to Snack” (0.648). loadings are; “Avoid Boredom” (0.794), “Fun” 7.5 Services (0.755), “Out of House” (0.722), “Change" (0.707), and “Freak out with Friends” (0.619). Indian The Indian customer has started availing and Consumers visit malls just because they may be expecting services such as; “ATM/Banking” (0.782), getting bored or want to break free from a routine “Gym / Spa” (0.683) and “Hair and Beauty” (0.628), rather than for purchasing motivations. This is a in the malls. As consumers perceive their time form of hedonic motivation. increasingly limited and valuable they not only do multiple shopping for products but also look for 7.2 Economic Reasons services that are conveniently available in Malls. This is a utilitarian function that has been captured in the factor on Services where customer looks for

[6] accomplishing assorted tasks to save time and demographic profiling based on variables such as achieve efficiency. These services work as gender, age, education, population growth rate, life incentives for customers. expectancy, literacy, education, language spoken, household size, marital status, income, occupation 7.6 Social Experience is typically done. These factors affect retail shopping and retailer’s actions (Bermans and Evans, Social experience is considered as a hedonic 2010). Four established demographic factors that motivation. (Richardson, 1993) has mentioned that influence market segmentation strategies; Gender, malls may have become important locations for Education, Age and Monthly Household Income are providing opportunities for social experience being considered in this study (Crask and Reynolds, outside home such as meeting friends and watching 1978; Sampson and Tigert, 1992; Arnold, 1994; Fox people. Indian customer with the lifestyle changes et.al., 2004, Carpenter and Moore, 2006). takes his family and children out to malls for socializing and spending time with them; “Let My Table 4 Demographic Composition of the Sample Child Enjoy” (0.821) and “Spend Time with Family” Data (0.668). Demograp Demograph To summarize the shopping motivational N % N % factors of Economic Reasons, Refreshments and hic factors ic factors th Snacking and Services reflect motivations of A E > 12 18-25 42. shoppers that are utilitarian in nature. In contrast g 227 d standar 36 6.8 the motivational factors of Diversion/Browsing, years 9 Shopping Environment and Social Experience e u d reflect hedonic considerations. Together these six 25-30 25. Gradua 20 37. 135 c factors account for 60.34% variance where hedonic years 6 tion 0 8 a factors contribute to almost equal variance as Post utilitarian factors. This is a major cultural shift for a 30-35 18. t 19 37. country like India, which focused more on 99 Gradua years 8 i 6 1 utilitarian functions. It carries bearings for service tion marketers o Profess 8. A NOTE ON DEMOGRAPHIC VARIABLES > 35 12. n ional 18. 67 96 Demographic characteristics of the sample years 7 Qualific 3 survey data including gender, age, education and ation income are represented in Table 4. A good understanding of its customers is the key to the M < G success of a retail strategy. This involves 10. 33 63. understanding of the target customer’s needs and o 10,00 54 e Male 2 5 5 desires, shopping attitudes and behaviour, his n 0 n lifestyles and demographics. The task of profiling 10,00 120 22. Female 19 36. the target customer begins with consumer t d 0- 7 3 5 demographics. Demographics are objective, h e quantifiable, easily identifiable and measurable 24,99 population data. To begin the identification l r 9

[7] y Multivariate Analysis of Variance (MANOVA) was conducted. Dependent variables consisted of six

24,99 identified shopping motivational factors as H mentioned in the preceding section; Diversion / 9- 29. Browsing, Shopping Environment, Economic o 158 49,99 9 Reasons, Refreshments and Snacking, Services and u Social Experience. Categorical independent 9 variables included Age with four levels (18-25 years, s 50,00 25-30 years, 30-35 years and 35-50 years), th e 0- 18. Education with four levels ( Below class 12 , 96 Graduation, Post Graduation and Professional h 1,00,0 2 Qualification.), Monthly Household Income with o 00 five levels ( less than INR 10000, 10000-24999, 25000-49999, 50000-100000 and more than l 100000.) and Gender (Male and Female). The Wilks d Lambda test results are displayed in Table no. 5.

Table 5 Results Of Multivariate Analysis Of I Variance for Select Demographic Factors on Shopping Motivations, Wilks Lambda (At 95% n Confidence Interval) c Effect Signif o > Hypoth Error icanc m 18. 1,00,0 100 Value F esis df df e e 9 Gende 468.00 00 .990 .750 6.000 .610 r 0 ( Month I ly N House 1.00 1.6340 .950 24.000 .459 R hold 3 00 ) Incom e Educat 1.27 1.3240 .953 18.000 .197 ion 2 00 9. EFFECTS OF DEMOGRAPHIC FACTORS ON Age 4.31 1.3240 SHOPPER MOTIVATIONS .851 18.000 .000 6 00 To examine whether the demographic factors of age, education, income and gender have an Results from MANOVA revealed insignificant effect on different shopping motivations effect on the shopping motivational factors for

[8] malls because of education, monthly household income and gender. Only Age had a significant effect on them (p=0.000). In addition a two way interaction of gender and age on motivational factors was significant (p =0 .024) whereas all the other interactions were insignificant. These results led to further probing of the situation as household income and education along with gender do display significant differences in the consumer behaviour in markets, where malls are an application area.

To explore the results of MANOVA, the Tests of Between Subjects Effects were analyzed. The tests show effect of each demographic variable on six individual shopping motivational factors. The results are reported in Table no. 6 and summarized in following sections.

Table 6 Tests of between Subject Effects of Select Demographic Factors and Shopping Motivations at 95% Confidence Interval

[9] Type

III Age showed a significant effect on Diversion / Sum Mea Browsing (p=.000), Economic Reasons (p=0.028) and Social Experience (p=0.000). Age was Depende of n insignificant for Shopping Environment, Meals and nt Squar Squa Signific Snacks consumption and Services. Gender and Monthly Household Income was insignificant for all. Source Variable es df re F ance Education was significant for Diversion / Browsing EDUCATI Diversion (p=0.034). These were the individual results of 2.37 2.90 ON / 7.130 3 .034 demographic variables on shopping motivations. 7 9 However, interaction of two variables on shopping Browisng motivations reflected a different pattern:- AGE Diversion 5.14 6.29  Gender + Age were significant for / 15.437 3 .000 6 9 Refreshment and Snacking (p=0.020); Browisng Economic 2.89 3.05  Monthly Household Income + Age were 8.680 3 .028 significant for Economic Reasons Reasons 3 4 (p=0.044); Social 8.50 10.0 Experienc 25.501 3 .000  Gender + Education were significant for 0 07 Economic Reasons (p = 0.021) and e GENDER Refreshm  Monthly Household Income + Education 3.16 3.31 were significant for Diversion / Browsing *AGE ents and 9.492 3 .020 4 5 (p=0.018) Snacking MONTHL Economic Reasons is a utilitarian function Economic whereas Diversion/Browsing is a hedonic one. Of YHOUSE the six motivational factors for mall visits these two Reasons HOLDINC 1.71 1.80 accounts for 25% of variance (Table 3) 12-13% 20.552 12 .044 respectively. They are both thus important for mall 3 8 OME * managers/ store operators. Of these the hedonic AGE one is even more important than the utilitarian GENDER Economic one, since it marginally contributes more. Variables that affect the motivational factors are in different * Reasons 3.10 3.28 combinations for both of them; 9.321 3 .021 EDUCATI 7 0  For Diversion / Browsing the effective ON combination is Monthly Household Income MONTHL Diversion + Gender + Education whereas,

YHOUSE /  For Economic Reasons the effective HOLDINC Browisng 1.68 2.06 combination would be Monthly Household 20.229 12 .018 Income + Age +Gender + Education. OME * 6 3

[10] At this point it is required that the effect of different layers of select individual demographic factors may also be explored where results are significant, which has been done through pair wise comparisons in the following section.

10. PAIRWISE COMPARISONS

10.1 Age

On examination of pair wise comparisons of four age levels for each motivational factor it was observed each age group category behaved differently with respect to others. Age group 18-25 years (‘young adults’) displayed a significant variance to age group 25-30 years (“growing adults1”, p=0.012) and 30-35 years (“growing adults 2”,p=0.000) for Diversion / Browsing; Age group 25-30 years showed a difference to age group 35-50 years (p=0.008). Age group 35-50 years (“mature adults”) showed a significant difference to all other age group levels for Diversion / Browsing.

It is therefore clear that Age is creating significant difference and different age levels are behaving differently for this motivational factor and accordingly customer behaviour and customer characteristics across age levels must be studied by a retailer.

Table 7 Results of Pairwise Comparisons for Age across Demographic Variables And Shopping Motivations At 95% Confidence Interval

[11] 95% For Economic Reasons age group 18-25 years Confidenc behave differently in terms of their shopping e Interval behaviour to that of 30-35 years (p =0.040)and 35- 50 years (p=0.015); Age group 25-30 years behaves for differently than age group 35-50 years (p=0.08). Difference This means that “young adults” behave differently Mean Std Low Upp than “growing adults 2” and “mature adults”, whereas similar to “growing adults 1”. “Growing Depende Differ . er er adults 1” behave differently than “growing adults nt (I) (J) ence Err Signific Bou Bou 2”.

Variable AGE AGE (I-J) or ance nd nd For Socialising Experience- Age group 18-25 Diversion 18- 25- . years showed a significant difference from age /Browsing 25 30 .410 16 .012 .090 .731 groups 25-30 years (p=0.028), 30-35 years (p=0.000) and 35-50 years (p=0.000); age group 25- 3 30 years shows a significant difference with age 35- . group 18-25 years, 35-50 years (p=.011) and 35-50 1.64 50 1.100 27 .000 .553 years (p=0.005); age group 30-35 years shows a 6 significant difference to age group 18-25 years and 8 30-35 years but insignificant difference with age 25- 35- . group 35-50 years. 1.26 30 50 .689 29 .019 .116 3 2 30- 35- . 10.2 Education 1.84 35 50 1.059 39 .008 .276 Education showed significant variance only for 2 the motivational factor Diversion / Browsing in Test 8 of Between Subject Effects. Within the four levels Economic 18- 30- . - -.03 of education for Diversion / Browsing there was a Reasons 25 35 -.718 34 .040 1.40 significant difference (p= 0.004) in the behaviour of 1 graduates and post graduates. Thus while class 12th 9 4 or below category and professional categories did 35- . - -.14 not display any significant difference these two 50 -.729 30 .015 1.31 categories showed difference and it may be viewed 0 that people with education level of graduation and 0 8 below behave differently from people with Socializin 18- 25- . -.04 education at post graduate level or above. This is g 25 30 -.367 16 .028 -.694 important for retailers. 0 Experienc 6 Table 8 Results of Pairwise Comparisons for 30- . - Education across Demographic Variables And e - -.61 35 33 .000 1.91 Shopping Motivations At 95% Confidence Interval 1.268 8 1 8 35- . -

[12] 95% Me 95% Confidence an Confidence Interval for (I) (J) Dif Interval for Mea Difference MONTH MONT fer Differencea Depen n Lowe Uppe Depe LYHOUS HLYHO enc Std Lowe dent (I) (J) Differ r r ndent E- USEHO e . r Variabl EDUC EDUCATI ence Std. Boun Boun Varia HOLDIN LDINCO (I- Err Boun Upper e ATION ON (I-J) Error Sig d d ble COME ME J) or Sig d Bound Diversi GRAD POSTGRA . Econo LESSTHA 25000- . . . on / UATIO DUATION -.359 .123 00 -.601 -.116 mic N10000 49999 76 36 03 .056 1.479 Browsi N 4 Reaso 7 2 5 ng 50000- . . . ns 100000 97 38 01 .212 1.731 10.3 Monthly Household Income 1 7 2 Pair wise comparison for five income levels MORET . . . revealed significant differences only for factor Economic Reasons between Monthly Household HAN10 67 37 07 -.064 1.409 Income of less than INR 10000 and 25000- 49999 0000 2 5 4 (p= 0.035) and 50000-Rs. 100000 (p = 0.012). Rest there also there is no significant difference. Gender displayed no significant variance at all for any of the motivational factors.

The results of MANOVA reveal that individually Table 9 Results of Pairwise Comparisons for only Age causes significant variance in Shopping Monthly Household Income across Demographic Motivations. However, even Age is significant only Variables and Shopping Motivations At 95% for three shopping motivations, whereas Education Confidence Interval is significant for one shopping motivation. The other variables of Gender and Monthly Household income do not create any significant variance at all on the shopping motivations individually but in various interactions and combinations that are different for utilitarian and hedonic motivations. Further pair wise comparisons reveal that different layers within each demographic variable behave differently with respect to each other in context of various shopping motivations. The summary and implications of these results are presented in the following section on Conclusion.

[13] shopping motivation and choose its placement in a mall, whereas the mall planners will have to keep a 11. CONCLUSION balanced tenancy and select store operators accordingly. These points emerge from the study; c) Pair wise comparisons reveal how different levels a) The primary reason for which people visit malls of individual select demographic factors behave in India are Diversion/Browsing, Economic Reasons, with respect to each shopping motivational factor. Shopping Environment, Refreshments and This helps in choosing a focus for the target market. Snacking, Services and Social Experience. This is a reflection of a shift in the trend where people not The above findings raise concerns that may have only visit for utilitarian functions but also go for very deep implications for retail strategy pleasure. a) Demographics are typically the first step for b) Of the select demographic factors that form the identification of market segments. If they are clear most fundamental bases for market segmentation enough they may form market segments that are strategy only Age shows a significant effect on measurable, actionable, sustainable and accessible shopping motivations in malls in India, individually. but with all these characteristics also their nuances need to be understood. However interactions in various combinations as highlighted in the Tests of Between Subject effects b) Focus and Differentiation are still not evident in are relevant for different shopping motivations. the Indian Malls. Since Organized Retail is just picking up, Indian industry may just be witnessing This is a critical finding for store operators and mall the growth while experimenting with business planners as store operators will have to match their models, whereas now it must act to achieve focus product assortments and its nature to the kind of and differentiate since different layers within the same parameter behave 12. IMPLICATIONS FOR FUTURE RESEARCH: differently in malls.  This research study establishes a need for c) Since Age individually shows influence over working on marketing segmentation variables Hedonic Shopping Motivations like Diversion / for Indian retail industry. Browsing and Social Experience, Mall planners may work on the probabilities to mall becoming social  The role of demographics; individual variables destinations. The marketing strategies will have to and combinations of variables for crafting more be craft accordingly, so that purchases are induced. customer centric strategies may be explored.

 Research needs to be done on exploring the possibilities of Indian malls being the new age social destination.

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