Customer Perception of Single Brand and Multi Brand Retail Formats

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customer perception of single brand and multi brand retail formats: an..any customer discerns are that of “where to shop” and..differs across the store formats. for instance, distance sensitivity while buying...

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Customer Perception of Single Brand and Multi Brand Retail Formats pdf

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Customer Perception of Single Brand and Multi Brand Retail Formats  - page 1
Customer Perception of Single Brand and Multi Brand Retail Formats: An Empirical Evidence in India Rituparna Basu IIT, Kharagpur [email protected] Kalyan Sengupta IBS, Kolkata [email protected] Growing variants of retail formats makes it exceedingly important to understand their impact on a customer’s store choice behavior. While store choice can be an outcome of several factors, the perception of the store format from the customer’s perspective calls for attention. In the emerging market context customer’s perception about organized retail formats is still in a formative phase. This paper attempts to understand the developing attitude of Indian customers towards single brand and multi brand retail formats. It aims to scrutinize such format preferences across different demographic segments of urban India to serve as a foundation for future research. Keywords: Retail Formats, Store Choice, Single Brand Stores, Multi Brand Stores, Demographic Factors 1. Introduction The two most pertinent decisions that any customer discerns are that of “where to shop” and “how much to buy”. Both seem to vary more across formats than within retail formats (E. J. Fox et al, 2001). It is acceptable when Fox et al assume that travel time sensitivity of a customer is more for a pharmacy or convenience store than a departmental store. Price sensitivity at the grocers would be more than buying at an exclusive apparel boutique. A customer’s decisional sensitivity is highly dependent on the purpose of buying (P. Van Kenhove et al, 1999) and nature of product to be bought (W. Van Waterschoot et al, 2008). The idea becomes all the more intriguing if we consider a single product category and see how sensitivity of the customer differs across the store formats. For instance, distance sensitivity while buying exclusive apparel for a special social occasion is probably less than buying casuals for daily wear. Understanding the role of format in consumer’s decision making is crucial to studies on retail strategy. The format of a retailer is the overall appearance and feel of a retailer. It is different from fascia or the external appearance of the retailer ( A good format ensures footfall and is one of the key determinants of the retailer’s success. Retailers use a mix of variables in terms of assortment, price, transactional, convenience and experience to develop an effective format. Traditional grocery stores emerged in the form of supermarkets like Kroger, Albertson and Safeway are now competing with mass merchandisers like Wal-Mart, Target and Kmart and also to some extent with drug store formats like CVS, Walgreens etc especially in the packaged goods sale. For the purpose of comparing effectiveness of retail business strategies formats are undoubtedly the best way to segment retailers. (E. J. Fox et al, 2001). Taking a closer look at the Indian organized retail sector, which is still in a nascent stage reveals existence of quite a number of formats especially in some categories like apparel, grocery, footwear to name a few. Owing to relaxations in the Indian FDI regulation particularly for single brand outlets/ stores, the Indian market has attracted the best known brands to set up exclusive stores along the more traditional multi brand formats. A classification of Indian retailers into single brand stores and multi brand stores seems justified for the purpose of comparing their respective effectiveness in attracting the Indian customers. The single brand stores typically offer products of a single brand and is sized between 1000 and 5000 sq ft in area. Some of the prominent single brand stores include Nike, Adidas, Gucci, Gautier, Zara, Levis along with their counterparts of Indian origin like Biba, Fab India, Gatha, Raymonds, Wills Lifestyle to name a few. Multi brand stores traditionally offer multiple brands and include all variants of departmental stores, hypermarkets, shopping malls sized between 1000 and 20000 sq ft in area. The best known multi brand stores include Shopper’s Stop, Lifestyle, Central, Pantaloon, Big Bazaar, Westside etc. Understanding the variables that influence a customer to choose a particular format over another in the Indian context is central to our study. Store choice behavior with respect to multi brand and single brand formats in India calls for attention owing to the lack of commensurate literature from an emerging market perspective as opposed to that in more developed retail markets of the world. Store choice behavior was interpreted in terms of a utility-maximizing function with number of interdependent variables (P. R. Messinger and C. Narasimhan, 1997). Tradeoffs amongst those variables, like that between time saving shopping convenience and time are interesting to investigate. Number of categories carried by store is often an outcome of interplay between consumers’ shopping time economization and that of retail competition in presence of its operational constraints (P. R. Messinger and C. Narasimhan, 1997). Considering each product category, growth of one-stop-shops carrying larger and larger number of SKUs along with growing retailization of multinational brands result in several questions. Can both these formats exist together and be successful in this present time? Are they attracting different consumer segments altogether? When shopping for a specific product category do consumers prefer one format over another? Coexistence of retail formats or otherwise can be explicitly understood as an equilibrating market mechanism but the role of the underlying forces from a consumer’s perception dimension is important to study to aid effective retail marketing strategies. While we seek to address the above mentioned issues the objective of our present study would be an inquiry on the following two research questions: How far will a single brand store be successful in India while competing with multi brand options? How will customer attitudes patronize the success/failure of single brand stores?
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Customer Perception of Single Brand and Multi Brand Retail Formats  - page 2
144 Eighth AIMS International Conference on Management 2. Background Literature The term retail format has been used under several contexts in the retailing literature (J. Reynolds et al, 2007). From a more general perspective it would simply mean the offer of a retailer manifested in terms of the public presentation of its offered goods and services. It can be confusing when the same retailer is portrayed under more than one format categories. For instance Wal- Mart is described as a ‘discount store operator’, ‘hypermarket’ and ‘power centre’. The same would hold true for the likes of big bazaar in the Indian retail market. According to Reynolds et al (2007) a more useable definition of retail format is that of a physical embodiment of a retail business model: “the framework that relates the firm’s activities to its business context and strategy”. Such business model would entail the retailer’s key resource and process mix aligned with their segmentation, targeting and positioning strategies. Therefore retail formats need constant nurturing and maintenance. Mintzberg’s (1994) “emergent strategy’ suggests retail formats as an evolutionary and incremental rather than a holistic creation and only continuous attention can make a format sustainable (J. Reynolds et al, 2007). Coexistence of formats within the same product category is not at all abnormal. Fundamental polarization in consumer behavior involves preference for large-scale and convenient formats alongside a growing interest in speciality formats. In fact consumer’s store learning is situational where store choice behavior is essentially an information processing behavior (W. Van Waterschoot; P. K. Sinha; P. Van Kenhove and K. de Wulf, 2008). The criteria for evaluation while choosing over formats vary with evolution of markets (P. K. Sinha and A. Banerjee, 2004) The Indian retail market which is estimated to almost double from a US $ 330 billion in 2008 to a US $ 637 billion by 2015 is undoubtedly an attractive emerging market (A. P. Tripathi, 2008). The nation of ‘dukandars’ having approximately 12 million retailers is set to see an unprecedented growth in the organized sector with higher levels of competition between and within format categories. During 2009-12 the organized retail market in India is estimated to grow at a 31% per annum rate with retail real estate growing at greater rate from existing 41 mn sq ft to a 95 mn sq ft (F. Knight, 2010) Global players like Wal-Mart, Metro coexist with domestic corporate behemoths like Reliance, Neelkamal, Aditya Birla Group or Bharti group to tap the consumption potential of the 6 million affluent with more than INR 215,000 household income along with a 75 million well off population earning between INR 45,000 and 215,000 (Marketing White Book, 2006). January 2006 announcement by Government of India permitting foreign companies to own up to 51% of single brand retail company have triggered brand retailization in a big way. Mall space grew from 28 mn sq ft in 2006 to 52 mn sq ft in 2009 (F. Knight, 2010) making room for the growing number of exclusive brand stores alongside the more traditional hypermarkets or departmental stores selling similar product categories clearly demarcate the organized retail market. Evidently marketing policies vary largely across formats (E. J. Fox et al, 2001). Literature on retail format strategies and their influence on shopping behavior are fascinatingly spread out. Pricing, promotion and product assortment which form an integral part of the retailer’s marketing policies are used as predictors of shopping behavior where the first two are firmly under the retailer’s control. Similarly the retailer’s long run store location decision directly affects the cost incurred by the shopper traveling to and from the store. Such retailer controlled variables coupled with demographic characteristics of the shoppers are analyzed for the purpose of explaining shoppers choosing one format over another (E. J. Fox et al, 2001). Fox et al’s research analysis reveals variability in shopping expenditure is explained largely by retail format. Between grocery stores, an intrinsic preference for patronizing one chain is a strong negative predictor of preference for the others. Behaviors like ‘trip chaining’ (C. J. Thill and I. Thomas, 1987) as a practice results in shoppers requiring less time than measured travel time for a particular store visit as they club such shopping trips with other required travel, and thus shop more than expected at the distant stores. Intrinsic preferences like retailer’s general positioning, operational policies, and overall excellence in execution including variety (breadth) of product categories affect shopping behavior. The growth and evolution of one-stop shopping with basic modeling approach consider 4 distributional elements of retailing that influence consumer’s choice of a retailer. The 4 functional elements are (1) assortment (2) price (3) transactional conveniences relating to shopping time and logistics, and (4) utility/ disutility from shopping experience (P. R. Messinger and C. Narasimhan, 1997). The first 3 factors exist with tradeoffs among them. Empirically the growth is due to increased consumer valuation of time because of greater female labour force participation, higher disposable incomes. Also improved logistics and storage/ refrigeration make it possible. Therefore for countries where there are lot of operational predicaments there would be a greater barrier to ensure efficiency with such one-stop shop destinations affecting consumer’s utility. Store assortment is given endogenously in such studies. Economies of scale are probably not the guiding force behind the growth of such one-stop shops. Determining aspects of shopping time include the wage rate and demographic correlation with search time (J. A. Carlson and R. J. Gieseke, 1983) time available for shopping and perceived pressures during in store behaviors (E. S. Iyer, 1989) and price comparison shopping (J. Kolodinski, 1990). Multipurpose shopping applies more to shopping centre and not supermarkets. Location considerations are believed to be far less applicable to sparsely populated regions with few stores but in India where consumers are within easy driving distance of more than one retail format option such study will be more applicable and worthwhile. In the grocery category empirically observed patterns of consumer shopping trips can be categorized under two heads (1) regular and (2) quick. Regular is more to do with single store visit with most grocery needs. Quick involves purchasing few items at frequent time intervals (B. E. Kahn and C. S. David, 1989). To sum up consumer decision making style is defined “as a mental orientation characterizing a consumer’s approach to making choices” between alternative products. It has cognitive and affective characteristics (for example quality consciousness and fashion consciousness) (G. B. Sproles, E. L. Kendall, 1986). Sproles and Kendall used the consumer characteristics approach to measure decision making styles as opposed to psychographic/ lifestyle approach or the consumer typology approach. For instance brand conscious consumers show positive attitude towards specialty and department stores where brand names and higher prices are prevalent. Price and ‘value for money’ consciousness is more likely associated with comparisons shoppers with the attributes of switchers. Habitual, brand loyal shoppers have favorite stores and brands. Consumers may have different styles for different product characteristics which are ultimately reflected in their attitude towards format choice. Thus consumer profiles in terms of their demographics can be readily reckoned as a big influence on their criteria for evaluating formats (P. Van Kenhove et al, 1999).
Customer Perception of Single Brand and Multi Brand Retail Formats  - page 3
Basu, Sengupta 145 3. Methodology and Scope of the Present Study An exploratory study based on items relating to attitudinal preference of customers (for apparel) with respect to determinants of store format choice. Variables indicating preferences towards single and multi brand stores while considering parameters like variety, quality of products, service ambience, fashion and designs, sales staff behaviors etc. The items measured were on a scale of 1 to 7, with ratings of “very strongly disagree” and “strongly agree” as end points. 20 such items were framed and a pilot study was carried out using 24 shoppers. By careful examination of the pilot survey data ultimately 7 items were selected for the study. Unimportant ones were discarded. The rest were eliminated because of problems related to ambiguity, clarity, significance and communality. Finally, the questionnaire was administered in 4 Indian metros namely, Kolkata, Delhi, Bangalore and Mumbai. It was felt that presences of developed organized retail in these cities are relatively high and consequently administration of survey was restricted to these four metro cities only. A convenient sample of adult respondents covering varied socio economic classes and cultural groups were considered. Respondents were asked to respond to each item to the best of their ability. 150 respondents were tried out. All the questionnaires were scrutinized and those with incomplete or unlikely responses were deleted, resulting in a sample size of 126. 4. Findings and Analysis Profile of the sample, thus collected, is shown in table 1. Table 1 Profile of Sampled Respondents Item Gender Marital Status Male Female Unmarried Married 18-25 years 26-30 years Age Category 31-35 years 36-45 years Above 45 years Less than 5000 5000-10000 Average Monthly Income (INR) 10000-20000 20000-40000 40000-50000 Above 50000 Personal Computer Possessions Air Conditioner 4 Wheeler Percentage 42.9 57.1 45.2 54.8 24.6 26.2 18.3 23.0 7.9 24.0 6.4 18.4 13.6 7.2 30.4 57.6 42.4 58.4 With an objective to figure out the differences in the choice criteria of shoppers with respect to the single brand stores and multi brand stores, we identified 7 items which directly reflected some positive feeling or attitude towards one of the two store formats. Out of the chosen 7 statements, 2 reflected a positive feeling towards multi brand stores while the rest 5 indicated the same towards single brand stores. An exploratory factor analysis using principle components method with varimax rotation of factors revealed two well defined factors for the given format. The KMO Barlett’s test score (.702) indicated a reliable model which is described in table 2. The model extracted nearly 58% variance in the data, where the first factor (single-brand trait) contributed 37.4% and the second (multi-brand trait) contributed 20.2% of the variation. The output of the extraction reflects that the first 2 components account 57.69% of the total variance. Thus two components were extracted demarcating the interrelationships among the variables for single brand stores and multi brand stores respectively. Table 2 The Factor Model Component 1 2 Initial Eigen Values 2.621 1.417 37.440 20.248 37.440 Extraction Sums of Squared Loadings % of Variance 37.440 Cumulative % 37.440 2.621 Rotation Sums of Squared Loadings Total 2.619 1.419 % of Variance 37.412 20.275 Cumulative % 37.412 57.688 Total % of Variance Cumulative % Total 57.688 1.417 20.248 57.688 Extraction Method Principal Component Analysis The reliability of the factors has been measured using Cronbach’s Alpha scores, which happen to be 0.77 and 0.58 respectively. These are no doubt satisfactory. The canonical correlation coefficients of the factor components are illustrated in table 3. It is apparent from the table that the factor 1 comprises of the following five items.
Customer Perception of Single Brand and Multi Brand Retail Formats  - page 4
146 Eighth AIMS International Conference on Management quality of products sold from single brand stores are better compared to multi brand stores single brand stores would always have clothes that fit me perfectly single brand stores are the best to get the latest designs single brand stores have better display of the clothing range than multi brand ones; and in single brand stores the staff is more attentive Factor 1 has the common underlying dimension of shopping behavior in the form of single brand positivity (SBP) orientation. Such shopping attitude can be expected when a customer knows what to buy or at least which brand/ label to buy. To some extent he would already have a budget in mind with a clearer purpose of buying. Target shoppers are probably sensitive to the extent of merchandise mix and time taken to find the right merchandise. Single brand stores with assortment within the product category are more suited for such target shopping behavior. Table 3 Rotated Component Matrix a Component 1 Cronbach’s Alpha I get more variety in a multi-brand shop Quality of products sold from single brand outlets are better (compared to multi-brand outlets) Single brand outlets would always have clothes that fit me perfectly Single brand outlets are the best to get the latest designs Multi- brand outlets are better places for spending time with family/ friends (compared to single brand outlets) Single brand shops have better display of the clothing range than multi-brand ones In single brand outlets the staff is more attentive (compared to multi-brand outlets) Extraction Method Principal Component Analysis Rotation Method Varimax with Kaiser Normalization Rotation converged in 3 iterations .704 .708 .626 .799 .762 .837 .767 2 .577 .839 Factor 2 comprises of the following 2 items: I get more variety in a multi brand shop; and multi brand stores are better places for spending time with family/ friends compared to single brand stores Factor 2 reflects a multi brand positivity (MBP) orientation. The multi brand shoppers have a more casual approach to shopping. Actual buying results more out of an impulse than compulsion. They are more likely to be sensitive to shopping conditions as they seek a satisfying shopping experience. Time sensitivity is less owing to the leisurely attitude. Departmental stores, hypermarkets or shopping malls with their entertainment oriented in store features coupled with amenities like in store refreshment areas, play areas for children are best suited for shopping as a leisure activity. Our analysis starts with each individual respondent being mapped with their scores pertaining to each of two factor components. Multivariate analysis of variance with target shopping(single brand store) and leisure shopping (multi brand store) components as the two dependent variables is used to explore their relationship with six categorical independent variables namely; gender, marital status, age categories, occupation categories, monthly personal income and monthly family income respectively. Table 4 Gender and Factor Scores Respondent Gender Female Male Mean Mean SBP Factor Score -.123 .092 MBP Factor Score -.286 .215 The first treatment with gender reveals a difference in shopping attitudes amongst male and female respondents. While men tend to be more prone to shopping than women, they also happen to prefer the multi brand shopping experience (mean score 0.215) to single brand shopping at the single brand stores (mean score 0.0924). Women show a highly adverse attitude towards multi brand store (mean score -0.286). Such behavior can be explained in terms of the basic Indian patriarchal society, where women are seen as homemakers with more of specific shopping needs. With more and more working women balancing their work life as well as their responsibilities as a homemaker, they are left with little or no time to engage in leisure driven shopping. Rather men have the privilege and means to indulge in more leisure driven shopping not only for their own recreation but also as a provider to the family. A T-test on multi brand positivity scores for male and female showed a significant difference at a P value of .004. Table 5 Marital Status and Factor Scores Marital Status Unmarried Married Mean Mean SBP Factor Score .042 .045 MBP Factor Score -.302 .260
Customer Perception of Single Brand and Multi Brand Retail Formats  - page 5
Basu, Sengupta 147 Analysis with marital status showed married people having a greater affinity towards shopping than unmarried. This is probably due to the fact that married people have a higher need for social factors, so spending time with family at the shopping malls, and need to shop for pleasure as well as sustenance is equally important for them. The choice of a multi brand store for leisure shopping (mean score 0.2600) over target shopping (mean score 0.045) becomes obvious with such needs to fulfill. For singles shopping for pleasure or shopping as an activity to pass time is more likely to be of lesser importance. Shopping is viewed as an activity with a purpose which makes them need or target shopping oriented (mean score of -0.0421 over a negative 0.302 for leisure shopping) without being totally attached to a particular store format. A T-test on multi brand positivity scores for married and unmarried showed a significant difference at a P value of .002. Table 6 Age Category and Factor Scores Age Category 18-25 26-30 31-35 36-45 Above 45 Mean Mean Mean Mean Mean SBP Factor Score -.063 -.088 -.196 .209 .330 MBP Factor Score -.464 -.079 .283 .300 .177 The age-wise analysis revealed pretty distinct choice patterns. The distinctions becoming more prominent with older people. The above 45 years age category showed a heavily skewed preference for the single brand store (mean score 0.330) to the multi brand option (mean score 0.177), the maximum relative to the other age groups. The target oriented shopping behavior is probably due to the convenience factor and need driven approach. Brand loyalty especially amongst older men in India is pretty apparent. Single brand store like Raymond is one such example. The age categories of 18-25 years and 26-30 years are more or less similar with their behavioral patterns. Both the age groups show no clear preference for either format. This is due to the fact that for such age categories shopping is hardly an important activity. While target shopping needs are limited, the leisure shopping needs are also replaced by alternatives like socializing at coffee shops or colleges or movie halls, focusing on career oriented activities or personal hobbies. The 31-35 years age category is a leisure shopping prone group (mean score 0.283 over a negative 0.196). This is explainable in terms of their specific needs to spend time with family, where shopping malls and multi-brand stores fit as the best possible options. The 35 -45 years age group is mostly a situation driven shopper with a need for target shopping (mean score 0.209) and a considerable need for leisure shopping (mean score 0.300). An ANOVA reveals that there are significant differences in attitude towards multiple brands shopping for different age groups in the data with a significance value of 0.01. Table 7 Occupation and Factor Scores Occupation Student Salaried Professional Self employed Housewife Others Mean Mean Mean Mean Mean SBP Factor Score -.171 .099 -.123 -.685 1.121 MBP Factor Score -.559 .147 .179 -.032 .418 Occupation wise both students and housewives have limited shopping preferences. While students are least prone to seen leisure shopping (mean score negative 0.559 for multi brand against negative 0.171 for single brand stores) owing to the number of leisure alternatives available to them. This could also be due to a higher level of brand loyalty amongst youngsters which leads them to the store of the brand of their choice. Both salaried professional and self employed people prefer a leisure shopping experience at multi brand outlets (mean score of 0.1466515 and 0.1786682). This occupation categories are very well supported by our age category data specific to 31 to 45 years, where there is likely to be a great deal of overlapping respondents. An ANOVA reveals that there are significant differences in attitude towards multiple brands shopping for different occupational groups in the data with a significance value of 0.02. Table 8 Average Monthly Income and Factor Scores Average Monthly Income Less than 5000 INR 5000-10000 INR 10000-20000 INR 20000-40000 INR 40000-50000 INR Above 50000 INR Mean Mean Mean Mean Mean Mean SBP Factor Score -.114 .023 -.143 .242 -.256 .123 MBP Factor Score -.383 -.555 -.036 .413 .264 .194 The treatment of average monthly family income bore no significant patterns compared to average monthly personal income. The data shows that the persons shopping preferences and choices are mostly guided by his perception of himself. Though each respondent being part of a family happens to spend from his family income pool, yet his preferences come from his own money
Customer Perception of Single Brand and Multi Brand Retail Formats  - page 6
148 Eighth AIMS International Conference on Management power. For instance a person in a very highly paid job and senior position will need to shop in tune with his esteem needs, inspite of being the only provider in his family. His need to look good and fit for his position like his counterpart coming from a more affluent background will have to be met at least to an extent. The above Rs.50,000 personal income per month category are the ones who are situation driven shoppers having needs for target shopping (mean score 0.123) and a little higher leisure shopping need (mean score 0.194) that is almost similar to the Rs60,000 plus average family income per month category. The less than Rs5,000 personal income groups are the ones most averse to shopping owing to their lower levels of disposable income. The Rs.5,000 to 10,000 category are necessarily target shoppers (mean score 0.0227367) as opposed to any leisure seeking shopping (mean score negative 0.5552369). Rs.10,000 to 20,000 category are no better off with hardly any affinity towards shopping. They are simply in their social need satisfying state with an aspiration to reach the next level. The Rs.20,000-40,000 and Rs.40,000- 50,000 have strong affinity towards leisure shopping (mean scores 0.413 and 0.264 respectively) compared to target shopping. This is definitely due to higher levels of disposable income and higher needs to socialize with family and friends. The Rs,20,000 to 40,000 family income categories is also behaviorally same as their counterparts. An ANOVA reveals that there are significant differences in attitude towards multiple brands shopping for different income groups in the data with a significance value of 0.03. 5. Managerial Implications The present study has been able to successfully draw the picture of customer perception towards retail formats namely single and multi brand stores. The two distinct positivity traits for multiple and single brand stores have been distinctly demarcated by the survey data. Attitude towards multi brand stores have been sharply contrasted by demographic characteristics, which may ultimately create various market segments. On the other hand it seems from the study, that Indian customers have yet to form a concrete idea and perception towards single brand stores, as these are relatively new and low in number. However, it may be justified a scope for both single brand and multi brand formats may coexist successfully in urban India. The consumer profiles for these two segments are distinct and noteworthy suggesting the probability of a rewarding coexistence of both the formats with proper positioning strategies. The managerial implications of our research can be summed up as follows: Format choices are driven by customer’s target/ leisure seeking shopping attitude. Multi brand stores must engage in offering the best possible leisure shopping experience as against single brand stores concentrating on offering the best possible assortment and service for serious and focused customers. Exclusive brand stores like Biba, Fab India, speciality saree shops etc are here to exist attracting the fashion conscious, novelty seeking urban Indian female population. Single brand stores for men should target above 45 age groups pertaining to upper middle class segments. Multi brand stores would remain as an entertainment destination for middle class Indian families seeking value added services on top of an all encompassing shopping experience. Multi brand stores would be mass driven while single brand options would be highly class oriented. 6. Conclusion In our study there was an effort to investigate customer perception towards retail formats in the Indian environment of emerging market. The study revealed that although organized retail is a relatively new concept in the country yet a clear cut perception has been establishes into the minds of the shoppers in urban India. This has also been consistently reflected in the behaviors of such shoppers. A picture of various segments based on broad demographic classification has been establishes successfully by way of our present study. However, there may be other important determinants for format choice like situation, task, purpose etc. for which a detailed model needs to be established. We have already elaborated a series of research which have been conducted by a number of authors in establishing a proper choice of the format. Yet, none of these models have been fruitful to predict the shopper’s choice in an emerging environment like India. Several other issues may be addressed in future investigations of retail format choice behavior. It is important to note that any such research is unlikely to be homogeneous for all categories of product. Similar research carried out in grocery, electronics may suggest different behavioral patterns. Such variation is also expected when a different population is taken up for the study. Also it may be noted that the present study is limited to a pretesting objective with a rather small sample size which may restrict the scope for generalization to some extent. Nevertheless our paper provides a relevant foundation for further application and testing of customer attitudes towards format choice. 7. Reference 1. 2. 3. 4. 5. 6. 7. 8. 9. (n.d.). Retrieved July 20, 2010, from B. E. Kahn and C. S. David. (1989). Shopping Trip Behavior: An Empirical Investigation. Marketing Letters , 1, 55-69. C. J. Thill and I. Thomas. (1987). Toward Conceptualizing Trip Chaining Behavior: A Review. Geographical Analysis , 1, 1-17. E. J. Fox, A.L. Montgomery, L. M. Lodish. (2001, January). 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Customer Perception of Single Brand and Multi Brand Retail Formats  - page 7
Basu, Sengupta 149 10. Kolodinsk, J. (1990). Time As Direct Source Of Utility: The Case Of Price Information Search For Groceries. Journal Of Consumer Affairs , 24 (Summer), 89-109. 11. Marketing White Book. (2006). Business world , pp. 114-15. 12. P. K. Sinha and A. Banerjee. (2004). Store Choice In An Evolving Market. Internationa Journal Of Retail And Distribution Management , 32 (10), 444-82. 13. P. R. Messinger and C. Narasimhan. (1997). A Model Of Retail Formats Based On Consumers' Economizing On Shopping Time. Marketing Science , 16 (1), 1-23. 14. P. Van Kenhove; W. Van Waterschoot and K. De Wulf. (1999). The Inpact Of Task Definition On Store-Attribute Saliences And Store Choice. Journal Of Retailing , 75 (1), 125-37. 15. Tripathi, A. P. (2008). Emerging Trends In Modern Retail Formats And Customer Shopping Behavior In Indian Scenario: A Meta Analysis And Review. 16. W. Van Waterschoot; P. K. Sinha; P. Van Kenhove and K. de Wulf. (2008). Consumer Learning And Its Impact On Store Format Selection. Journal Of Retailing And Consumer Services , 15, 194-210.
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