Store choice and store loyalty: an investigation on shopper's behaviour towards organized versus unorganized retail stores.
Retailing is one of the pillars of the economy in India and accounts for 10 percent of GDP (Chatterjee, 2009). This sector has become one of India's fastest growing sectors with a 5 percent compounded annual growth rate. India's huge middle class base and its untapped retail industry are key attractions for global retail giants planning to enter newer markets. Driven by changing lifestyles, strong income growth and favorable demographic patterns, Indian retail is expected to grow 25 percent annually and could be worth US$ 175-200 billion by 2016.
Roots of modern trade can be traced back to the 60s with the formation of cooperative stores; this was the time when Indians experienced their first self service format. Till 1980s, India knew only kirana stores. Things started to change slowly after that, with companies like Bombay Dyeing, Raymond's, S Kumar's and Grasim opening their company owned outlets. Later on, Titan, maker of premium watches, successfully created an organized retailing concept in India by establishing a series of elegant showrooms. Early 90s witnessed the family managed stores modernizing their operation and gaining scale over a period of time. Late 90s and the beginning of the new century (year 2000) saw some of the key players scale up operations, introduce multiple formats and roll out larger stores.
The organized retail industry in India had not evolved till the early 1990s. Until then, it was a seller's market, with a limited number of brands, and little choice available to customers. Lack of trained manpower, tax laws and government regulations all discouraged the growth of organized retailing in India during that period. Lack of consumer awareness and restrictions over entry of foreign players into the sector also contributed to the delay in the growth of organized retailing. Foundation for organized retail in India was laid by Kishore Biyani of Pantaloon Retails India Limited (PRIL). Following Pantaloon's successful venture a host of Indian business giants such as Reliance, Bharti, Birla and others are now entering into retail sector.
There is no doubt about the potential of retailing in India but it is still at a very early stage. Most retail firms arc companies from other industries that arc now entering the retail sector on account of its amazing potential. There are only a handful of companies with a retail background. One such company is Nilgiri's from Bangalore that started as a dairy and incorporated other areas in its business with great success (Mukherjee and Patel, 2005). Their achievement has led to the arrival of numerous other players, most with the backing of large groups, but usually not with a retail background. Most new entrants to the India retail scene are either from real estate groups who see their access to knowledge of land, location and construction as prime factors for entering the market or from non-retailing sectors (like textiles, communication, pharma industry) which is evident by the fact that out of top 15 retailers in India 12 are from non-retailing background (Akhter and Iftekhar, 2012). Further, it appears that the retailing scenario in India is driven more by euphoria which is evidenced by the fact that new expansions are adaptations from the western formats resulting in moderate to lukewarm success, resulting in the need to evaluate the true drivers of shopping behaviour in the Indian context (Sinha, Banerjee and Uniyal, 2002).
It is also important to note that there is limited information and literature available in the public domain regarding Indian shopping behaviour, especially in the context of the changing retailing environment (Sinha, Banerjee and Uniyal, 2002, Mittal and Mittal, 2008).
This back ground makes it very relevant to make a study about Store choice and its relation with other important concepts like store patronage and loyalty. Thus, the primary objective of this research is to find out if the store patronage helps in determining the selection of store as well as the purchasing outcome and to find out if the concept of loyalty exists in today's scenario or is it a myth.
REVIEW OF LITERATURES
Store choice has emerged as new area of study. The decision of store choice is of utmost importance for a shopper. The present formats prevalent in India have been a successful saga in developed economics but in India they have gained a moderate or lukewarm response. Indian customer does not perceive these new formats as a value addition and want to continue with traditional Kirana store.. Therefore, it is important for a store owner to understand this behavior for developing marketing strategies to attract and retain its customers. Hence, Store choice has become a subject of great relevance and area of wide research in the developing economies like India. Studies by Fotheringham (1988), and Meyer and Eagle ((1982), suggest that location influences store choice. This was further established by another study carried out in Chinese market itself by Mai and Hui Zhao (2004), that location (Closeness to home) is a major driver for store choice. Store promotion has been a widely studied area in the literature, notably by Gupta, (1984). Over the years a number of researchers have focused on examining different elements of price as a determinant of store choice (Yavas, 2003).
Among this stream of literature, price is depicted as pure monetary cost (Fox et al., 2004) and as an element of broader concepts such as store image (Finn and Louviere, 1996) and consumer value (Sweeney and Soutar, 2001). The role of store atmospherics, ambience and store environment has been studied by Kotler (1973), Baker, Grewal and Levy (1992) and an important relationship is being found with store choice. Retail salespeople often serve as a critical nexus between retailers and their customers. Understanding consumer perceptions is an important precursor to understanding consumer behavior during retail sales encounters (Mallalieu, L., 2006) and this signifies the importance of salesperson. Waiting for service in a retail store is an experience that can lead to consumer dissatisfaction which in turn can result in negative effects on store patronage behavior (Hui, Dube and Chebat, 1997). Further, Khadilkar (2012), identified various categorized services under various parameters like-promptness in service, multiple counters, long working hours, handling customer complaints, error free sales transactions, parking facility, home delivery facility. It has also been found to be dependent on the timing of shopping trips, with consumers visiting smaller local store for short "fill-in" trips Walters and Jamil (2003), Frisbie (1980), Kollat and Willet (1967) and larger store for "major" shopping trips. Self-congruity theory suggests that favorable brand attitudes are partially a function of the image congruence phenomenon, a mental comparison that consumers make in regards to the similarity or dissimilarity of a brand's image and their own self-image (Sutherland et al., 2004).Shoppers consistently say that retail assortments affect their store choice decisions, ranking it third in importance behind convenient locations and low prices as a choice criterion (Arnold, Roth and Tigert, 1981, Arnold, Oum and Tigert, 1983).
However, recent studies have failed to find a positive relationship between assortment size and category sales in grocery stores (Broniarczyk, Hoyer and McAlister, 1998). It refers to the various types of people that shop at the store. People who have positive association with the clientele tend to be more loyal (Engel et al., 1995).The reason imparted to it that customer aspires to be recognized as a part of other shoppers visiting outlet. Corporate image can be described as the overall impression made on the public psyche about a firm (Barich and Kotler, 1991). Corporate image may be considered as, "a function of the accumulation of purchasing/consumption experience over time" (Andreassen and Lindestad, 1998). Therefore, corporate image essentially results from an evaluation process (Aydin and Ozer, 2005). Previous studies have found that the effects of corporate image on customer loyalty can be both direct (Nguyen and Leblanc, 2001) and indirect (Ball et al., 2006).
Berry (1969), in particular stresses the importance of studying retail loyalty primarily due to the fact that customers are finding it increasingly difficult to distinguish between the retail store and retailers brand that are offered. At the heart of customers retail loyalty is the relationships that can be established between consumers and retail establishments (Hartman and Spiro, 2005; Fullerton, 2005) similar to the importance of the creation of strong relationships between consumers and brands in order for the formation of customers brand loyalty to take place researchers suggested that such relationships must exist between consumers and retail establishments in order for customer retail loyalty to emerge (Reynolds and Arnold, 2000; Wong and Sohal 2003). Such relationships can affect the attitude of consumers, resulting in a stronger relative preference to shop at one retail store over another. Customer brand loyalty research has shown that loyalty that is embedded in consumers attitude can be a much stronger predictor of current and future loyalty behaviors towards a preferred brand (Oliver, 1999).
The degree to which a consumer shops at a particular store is relative to competitive outlets. The store patronage involves the consumer's choice for a particular retail store. Store patronage is identified in Bitner's (1992) model as approach-avoidance behaviour. She proposes that perceptions of the environment or environmental dimensions lead to certain beliefs or emotions about the environment, which then determine whether a consumer will approach (i.e. patronize) or avoid a particular setting. Thus, Patronage of a store is derived out of both i.e.; attributes of the store and buying intentions
In this section the relevant hyposes for this study is discussed in details. There are four hypotheses that have been tested to meet the objectives of the study. They are as follows:
[H.sub.1]: Store patronage does not determine store choice.
Area related studies with focus on patronage have found convenience as the primary reason for customer's patronage (Huff, 1964) where as product related studies have emphasized the uniqueness of assortment as a way of influencing patronage. It was also found that in customer priorities assortment and variety comes after convenience and price (Arnold et al, 1983).
Here, it is interesting to note that factors which are influencing store patronage (i.e. larger percentage of total shopping trips to similar stores happen at a particular store) are also the drivers for store choice and store patronage involves the consumer's choice for a particular retail store i.e. larger percentage of total shopping trips to similar stores happen at a particular store (Shim and Kotsiopoulos, 1992).Thus, a need was felt to assess if store patronage determines store choice which has resulted in [H.sub.1].
[H.sub.2]: Store patronage docs not determine percentage of expense through particular store.
At the same time store patronage is also determined by the amount the customer spend as a percentage of total expenditure at a particular store which has given the reason to assess if it is applicable in context to Uttarakhand leading to the development of [H.sub.2].
[H.sub.3]: Percentage of expense incurred through store is not dependent on the type of store one visits.
In the backdrop of [H.sub.1] and [H.sub.2], a new assumption that percentage of expense incurred through store is dependent on the type of store one visits is being verified through [H.sub.3] i.e.-Percentage of expense incurred through store is not dependent on the type of store one visits.
[H.sub.4] : There is no relationship between store choice made by the shopper and store loyalty.
Customers retail loyalty is the relationship that can be established between consumers and retail establishments (Hartman and Spiro, 2005; Fullerton, 2005(.Previous studies have suggested that such relationships must exist between consumers and retail establishments for customer retail loyalty to emerge (Reynolds and Arnold, 2000; Wong and Sohal 2003). These relationships can affect the attitude of consumers, resulting in a stronger relative preference to shop at one retail store over another (Oliver, 1999) which is being tested through [H.sub.4].
This section describes the instrument design, sampling method and data collection method used in this study. In order to develop a reliable and valid scale, to attain the objectives of the study, validity and reliability tests have also been conducted.
Questionnaire Design and Measurement
A self administered questionnaire was designed to collect data on the following constructs. Fifty seven measures were developed to collect information on above mentioned eleven drivers. Eleven additional measurements were also included to measure LOYALTY(07), and PATRONAGE(04).These drivers and questionnaire items for these drivers were developed from inferences obtained through the review of literature and exploratory interviews. Each of these items was evaluated on a five-point Likert scale ranging from 1-Strongly disagrees to 5-Strongly agree (i.e.-Strongly disagree, disagree, Can't Say, Agree, Strongly agree). Few of the items have been illustrated as below for better understanding.
1) One item used to measure PRODUCT using above mentioned scale which was included in the final questionnaire is as below : My store has a wide variety of product range
2) To capture SALESPERSON one item using similar scale included in the final questionnaire is as below: My store has responsive salesperson
3) To capture CONGENIALITY one item using similar scale included in the final questionnaire is as below: My store attracts quality of clientele
4) To capture LOYALTY one item using similar scale included in the final questionnaire is as below: I will frequently shop at this store in future.
5) To capture PATRONAGE one item using similar scale included in the final questionnaire is: I will participate in any community event organized by the store.
Sampling and Data Collection
Primary data has been collected in the month of July, August, and September of the year 2011. Mall intercept method is used to collect the data. The instrument used for the collection of the data is questionnaire which has been got filled by intercepting the customer at the exit doors of the retail stores or at the counter in case of Kirana stores. The systematic random sampling method (i.e. every tenth shopper coming out from the outlet) is used to select the respondents.
A total of 352 shoppers including males, females of all age groups from cities like Dehradun, Kashipur, Haldwani, and Rudrapur participated in the survey. A total of 102 respondents did not provide complete information making them unusable; this resulted in samples size of 250 yielding a response rate of 71.4 percent. For sample size calculation the researcher wants no more than 5 percent error and is satisfied with 95 percent of confidence level. Assuming all other things constant, then in cities selected for sample selection considering where 70 percent of the population is aware about organized retailing and 30 percent is not aware of it a sample size of 352 is needed for the result. This sample size has been finalized based upon the standard sampling table for problems involving sample proportions (Lin, 1976)
Researcher has used statistical tools (like-Chi-Square test) and procedures to analyze the collected data. To develop an authentic instrument, reliability and validity analysis have also been carried out.
Validity and Reliability Analysis
To establish content validity, construct validity and face validity store managers (10), shopkeepers (15), senior faculty members (5) of researcher's institute were asked to compare and evaluate the items included in the questionnaire with the objectives of the research. For examples jargons like VFM, PL etc have been removed from the instrument. Scales for this study were considered to have good reliability with a Cronbach's alpha value of 0.738.
Table 1 reveals the findings of cross tabulation on the variables store patronage category and type of store listed. In order to test the hypothesis Hi (store patronage does not determine store choice). The researchers have applied chi-square test to test the hypothesis (Table 2). They have categorized store patronage in three categories on the basis of their scores calculated as below:
Category I (less patronizers)--4-9 Category II (moderate patronizers)--10-15 Category III (most patronizers)--16-21
Four statements used to measure store patronage were taken and 1 point to least important ----5 point to most important was awarded. Thus minimum score achieved was 4(i.e. -4*l) and maximum score achieved was 20(i.e. -4*5). Further, three intervals were developed between 4 and 21. Table 1 shows the numbers of customers visiting to different type of stores (i.e. -organized and unorganized) category wise.
Chi-square test of independence that is used to investigate the distribution of categorical variables has been applied using SPSS 16 software. Before that, researcher has ensured that all assumptions of chi-square test are met. Chi-Square measures test the hypothesis whether the row and column variables in a cross tabulation are independent or not. Above table contains the output of the Chi-Square test. Significance value (0.495) of Pearson Chi-square test which is typically greater than 0.05 indicate that values are not significant. Researcher has further calculated the value of chi-square that comes to be as following-
[[chi square].sub.Cal] = 1.408
For level [alpha] = 0.05, df = 2 the cut off point for the test statistic
[[chi square].sub.tab] = 5.99
Since [[chi square].sub.cal] < [[chi square].sub.tab]
It is further evident from the above that null hypothesis can easily be accepted at 5 percent level of significance and concluded that different categories of store patronage and type of store format are independent of each other. Therefore it is easy to conclude that store patronage does not determine type of store one visits.
[H.sub.2]: Store patronage does not determine percentage of expense through a particular store.
To test the above hypothesis, researchers have decided to apply chi-square test (Table 4). For that, they have categorized store patronage in three categories on the basis of their scores calculated as below-
Category I (less patronizers)--4-9 Category II (moderate patronizers)--10-15 Category III (most patronizers)--16-21
Four statements used to measure store patronage were taken and 1 point to least important ----5 point to most important was awarded. Thus minimum score achieved was 4(i.e.-4*l) and maximum score achieved was 20(i.e.-4*5).Further, three intervals were developed between 4 and 21. Table 3 shows percentage of the expense incurred by the customers from a particular type of store, category wise. Table 4 reveals the Chi-Square test results for store patronage category and percentage of expense through store.
Chi-square test of independence that is used to investigate the distribution of categorical variables has been applied using SPSS 16 software. Before that, researcher has ensured that all assumptions of chi-square test are met. Chi-square statistics tests the hypothesis whether the row and column variables in a cross tabulation are independent or not. Table 4 reveals the output of the Chi-Square test. Significance value (0.309) of Pearson Chi-square test which is typically greater than 0.05 indicate that there is no relationship between the two variables. Researcher has further applied further calculated the value of chi-square that comes to be as following-
[[chi square].sub.Cal] = 9.414
For level [alpha] = 0.05, df=2 the cut off point for the test statistic
[[chi square].sub.tab = 15.5
Since, [chi square] cal < [chi square] tab
It is evident from the above that null hypothesis can easily be accepted at 5 percent level of significance and concluded that different categories of store patronage and percentage of expenses incurred format are independent of each other. Therefore, it is easy to conclude that store patronage docs not determine percentage of expense through that store.
[H.sub.3]: Percentage of expense incurred through store is not dependent on the type of store one visits
Table 5 reveals the results of cross tabulation for the type of stores visited and percent of expense through store. Chi-square test (Table 6) of independence that is used to investigate the distribution of categorical variables has been applied using SPSS 16 software. Before that, researcher has ensured that all assumptions of chi-square test are met. Chi-square statistics test the hypothesis whether the row and column variables in a cross tabulation are independent or not. Table 6 contains the output of the Chi-Square test.
Significance value (0.002) of Pearson Chi-square test which are typically lesser than 0.05 indicate that there is relationship between the two variables. Researcher has further calculated the value of chi-square that comes to be as following-
[[chi square].sub.Cal] = 16.986
For level [alpha] = 0.05, df = 2 the cut off point for the test statistic
[[chi square].sub.tab] = 9.49
Since [[chi square].sub.tab] < [[chi square].sub.cal]
It is evident from the above that null hypothesis can easily be rejected at 5 percent level of significance and concluded that 'type of store visited' and 'percentage of expenses incurred are dependent of each other. Therefore, it is easy to conclude that these factors are dependent on each other.
[H.sub.4]: There is no relationship between store choice made by the shopper and store loyalty.
Table 7 and 8 reveals the findings of Chi-square test and dicrestional measure respectively. The test statistics of .036 and .010 indicate that researcher has reduced error rate by 3.6 percent and 1 percent respectively over what one could expect by error chance. Chi-square test of independence that is used to investigate the distribution of categorical variables has been applied using SPSS16 software. Before that, researcher has ensured that all assumptions of chi-square test are met. To test the above hypothesis, researcher decided to apply chi-square test.
Chi-square statistics test the hypothesis whether the row and column variables in a cross tabulation are independent or not. Above table contains the output of the Chi-Square test. Significance value (0.851) of Pearson Chi-square test which is greater than 0.05 indicates that there is no relationship between the two variables i.e. type of Store visited and loyalty.
Hence, based upon discussion made above, the null hypothesis can easily be accepted at 5 percent level of significance and concluded that since the value is insignificant, there is no significant relationship between the two variables i.e.-type of Store visited and loyalty.
Table 1 reveals that store patronage does not determine store choice as the percentage of shoppers belonging to cither of the patronizing category for both type of formats (organized and unorganized) are almost same. This is further supported by the results obtained after testing the hypothesis [H.sub.1], which also indicates that store patronage docs not determine store choice.
Based upon the information provided in Table 3 related to [H.sub.2], it is evident that majority of the respondents' i.e. 153 out of 250 come under category-2, (i.e., moderate patronizers). On further analyzing catcgory-2 it was found that, 92 respondents make only up to 40 percent of their expenditure through a particular store. Twenty-four respondents make 61-100 percent of their expenditure through a particular store.
Thirty-seven respondents make decent 41-60 percent of their expenditure to a particular store respectively which further confirms that average consumer visit more than one store while making the purchase. Even out of 85 respondents who belong to catcgory-3(i.e., most patronizers) major number of respondents 41 make only up to 40 percent of their purchase from a particular retail outlet and only 14 respondents make expenses up to 61-100 percent. All this shows that shopper of Uttarakhand is not loyal and docs not patronizes any particular store format. This is in line with the findings of the research carried out in McKinsey, 2008 which says that while Indian shoppers clearly enjoy shopping but they are much less loyal to a single retailer. Over 60 percent of Indian shoppers covered in the survey said that they buy at more than one retailer in comparison to 10 percent of Brazilian and 24 percent of Chinese shoppers.
In addition to it the result of testing of [H.sub.2], indicates that store patronage does not determine amount of expenditure incurred by the shopper. This is because decision of an average shopper visiting a particular store format depends upon what type of benefit (i.e., emotional or functional benefit or both) he expects during that visit. Consequently, the percentage of expense incurred varies w.r.t. type of one visit.
From Table 5, it is evident that 66 percent respondents visit organized retail (new format) and 34 percent visit unorganized retail (old format) for making the purchase. It means that average Indian (Uttarakhand) consumer's preference is changing with regards to store choice. Average consumer is more inclined in visiting to stores with new format. But only 10 percent respondents visiting new format make 61-100 percent of their purchase where as 26 percent respondents who visit old format make 61-100 percent of their purchase from that store. This shows that shopper visiting old format is more patronizing in nature in comparison to the shopper of new format. It is explained on the basis that Indians hold a lot of value for the 'old' who may be culturally driven where one is asked to respect old rather than look for new. Though this is changing fast especially among younger generation but it will take time.
Further based upon the findings of [H.sub.3], that percentage of expenditure through the store is dependent on the type of store one visits it can be inferred that it means that he visits both types of formats for making his purchases as he has diverse set of needs which he feels would not be satiated by one type of store format only. Thus, the selection of store formats depends upon mapping of requirement of an individual to be fulfilled and source from where it gets fulfilled. It is natural the percentage expenses incurred will vary according to the requirement. Thus, percentage of expenses incurred will vary according to the type of store one visits.
As per the result derived for [H.sub.4], significance value (0.851) of Pearson Chi-square test which is greater than 0.05 indicates that there is no relationship between the two variables i.e. type of Store you visit and loyalty. This may be accorded to the reason that as the concept of organized retailing is not very old for the shopper of Uttarakhand therefore it is bit difficult for him to shift entirely towards this new format leaving old formats from where his association has been quiet long but at the same time his inclination is tilting towards new formats because of the rising aspirations of an average shopper thus he goes to both type of store and not to only one type of format.
It is in line with the findings that Indians hold a lot of value for the 'old' who may be culturally driven where one is asked to respect old rather than look for new. Though this is changing fast especially among younger generation but it will take time, thus he visits both type of stores. As far as the finding that shopper is not loyal to a particular store is concerned ,it is in accordance with the findings of the research carried out in McKinsey (2008) which says that while Indian shoppers clearly enjoy shopping but they are less loyal to a single retailer. Over 60 percent of Indian shoppers covered in the survey said that they buy at more than one retailer in comparison to 10 percent of Brazilian and 24 percent of Chinese shoppers.
Shopper making frequent visit to a particular format (store choice) is said to be patronizing that particular store format but as it is evident from findings that the vice-versa is not true. It means that store choice leads to store patronage but the store patronage does not lead to store choice.
The average shopper of Uttarakhand is not loyal to a particular store format and does not patronize to a single store. It is also concluded that amount of expense incurred by a shopper leads to consider that shopper as patron/non-patron of that store depending upon the amount of expenditure he incurs .But the vice-versa is not true. It means that store patronage does not lead to store choice.
The average shopper while making purchase used to seek functional benefit only (as he up to now had the option of making purchases only from kirana outlets) but with the advent of organized retailing, he has started seeking emotional benefits as well.
Respondents visiting to old format are more patronizing in nature in comparison to shopper visiting new format which leads to the conclusion that although shopper is developing its inclination towards organized retail but his long association with conventional stores is still strong .This can be taken as challenge by retailers of new format and opportunity for the retailers of old formats. The shopper of Uttarakhand uses both type of formats for making his purchase and is not loyal to only one type of format only. This is a matter of concern for both types of retailers as in order to sustain the business loyal customers are a must.
LIMITATIONS OF THE STUDY
The study was conducted only in Uttarakhand due to time and cost limitation. As a result, findings are representative of regional population. The sampling technique used in the study was the Systematic Random sampling technique.
Respondents chosen for the sample were intercepted at the exit doors and on few occasions, filled up the questionnaire under pressure of time as they were in hurry. In short, not all customers responded as per planning thus rendering some sampling error. Comparatively a small sample size has reduced the power of statistical analysis. Furthermore, a large scale field survey could have been more useful in developing larger dataset that could be applicable to larger population. Inclusion of more stores in the study could have been produced more reliable findings.
FUTURE SCOPE OF THE STUDY
The implications of the above research are critical as they suggest the changing preferences of the average Indian shopper with regards to the facilities offered by the retailers. This section makes suggestion about areas where the similar research may be conducted in future:
* The scope of research was limited to five urban cities (i.e.Dehradun, Rudrapur, Haldwani, Kashipur, Haridwar) of Uttarakhand. However, this research can be conducted in other urban as well as rural parts of state /country.
* The sample size in this research study has been 352(valid sample-250). A significantly larger sample size may be more representative of population.
* The study has divided retail formats as unorganized and organized. However, a similar study may be conducted for various types of formats falling under organized sector.
* In future, study can be made on determining the role of various demographic factors on Store Choice.
* Role of family size, combined income of family, in store selection can also be the area of study.
Received 18 August, 2012 Accepted 24 December, 2012
Chief Editor: Mohammad Safa
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(a) Pankaj Madan, (b) Deependra Sharma *
(a) Faculty of Management Studies, Gurukul Kangri Vishwavidyalaya, India
(b) Institute of Management Studies, Uttarakhand Technical University, India
* email@example.com [mail]
Table 1: Cross tabulation (store patronage category and type of store listed) Store Patronage Type of Store visited Total category Organized Stores Unorganized Stores 4-9 Count 9 3 12 (Less patronizer) Expected 7.9 4.1 12 Count 10-15 Count 103 50 153 (Moderate patronizer) Expected 100.4 52.6 153 Count 16-21 Count 52 33 85 (Most patronizer) Expected 55.8 29.2 85 Count Count 164 86 250 Total Expected 164 86 250 Count Table 2: Chi-Square test (store patronage category and type of store visited) Item Value Df Asymp. Sig. (2-sidcd) Pearson Chi-Square 1.408(a) 2 .495 Likelihood Ratio 1.421 2 .491 Linear-by-Linear 1.393 1 .238 Association N of Valid Cases 250 Note: 1 cells (16.7 percent) have expected count less than 5. The minimum expected count is 4.13. Table 3: Cross tabulation (store patronage category and percentage expense through store) Store Patronage Category Percentage of expense through store Total 0-20 21-40 41-60 61-80 81-100 Category-1 Count 5 2 5 0 0 12 (Less Expected 2.8 3.9 3.5 1.3 0.5 12 patronizer) Count Category-2 Count 39 53 37 17 7 153 (Moderate Expected 36.1 49.6 44.1 16.5 6.7 153 patronizer) Count Catcgory-3 Count 15 26 30 10 4 85 (Most Expected 20.1 27.5 24.5 9.2 3.7 85 patronizer) Count Count 59 81 72 27 11 250 Total Expected 59 81 72 27 11 250 Count Table 4: Chi-Square test (store patronage category and percentage of expense through store) Item Value Df Asymp. Sig. (2-sided) Pearson Chi-Square 9.414(a) 8 .309 Likelihood Ratio 11.135 8 .194 Linear-by-Linear 3.498 1 .061 Association N of Valid Cases 250 Note: 6 cells (40.0 percent) have expected count less than 5, The minimum expected count is 0.53 Table 5: Cross tabulation (type of stores visited and percent of expense through store) Item Percentage of expense through store 0-20 21-40 41-60 61-80 Type Organized Count 47 57 44 10 of Store Expected 38.7 53.1 47.2 17.7 Store Count visited Unorganized Count 12 24 28 17 Stores Expected 20.3 27.9 24.8 9.3 Count Count 59 81 72 27 Total Expected 59 81 72.0 27 Count Item Total 81-100 Type Organized 6 164 of Store 7.2 164 Store visited Unorganized 5 86 Stores 3.8 86 11 250 Total 11 250 Table 6: Chi-Square test (type of store visited and percent of expense through store visited) Item Value Df Asymp. Sig. (2-sided) Pearson Chi-Square 16.986(a) 4 .002 Likelihood Ratio 16.802 4 .002 Linear-by-Linear Association 13.868 1 .000 N of Valid Cases 250 Note: 1 cells (10.0 percent) have expected count less than 5. The minimum expected count is 3.78. Table 7: Chi-Square test (store choice and store loyalty) Item Value Df Asymp. Sig. (2-sided) Pearson Chi-Square .322(a) 2 .851 Likelihood Ratio .319 2 .852 Lincar-by-Lincar association .023 1 .879 N of Valid Cases 250 Note: Cells (16.7 percent) have expected count less than 5. The minimum expected count is 3.44 Table 8: Directional measures (store choice and store loyalty) Item Value Nominal by Interval Eta Type of Store visited .036 loyalty category .010
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|Title Annotation:||Research Paper|
|Author:||Madan, Pankaj; Sharma, Deependra|
|Publication:||International Journal of Business and Management Science|
|Date:||Dec 1, 2012|
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