Abstract: Organised retail in the past one decade is growing at a faster rate in India. Albeit the burgeoning size, the organised retailers are finding it difficult to be in black. One of the marketing strategies is to focus on retaining the existing customers as they are five times more profitable than new ones. In this study the author examine the factors that influence the customers switching behavior in organized retail. The study was done based on certain factors which are recognized to be the main dimensions which are congruent with the switching cost. The researcher used structured questionnaire as instrument and collected data from the customers of organized retail stores in India. The collected data were analyzed with the help of statistical tool, namely, Multiple Regression through SPSS. The Regression tests have revealed that the demographic variables: Patronage period, Purchase size, Profession will have significant impact on switching behavior dimensions. The study concludes with suggestions on increasing switching cost to the customers of retail stores in order to retain loyalty in the long run.
INTRODUCTION
Services marketers know that having customers, not merely acquiring customers, is crucial for service firms (Berry, 1980). Research show that customer can be acquired by improving service quality (Bitner, 1990), relationship quality (Crosby et al., 1990) and overall satisfaction (Cronin and Taylor, 1992). But, what of losing a customer? What actions of service firms or their employees, cause customers to switch from one service provider to another? The answers to these questions are important as to both executives of service firms and service marketing scholars. Service firm executives are concerned about the negative effects of customer switching on market share and profitability (Rust and Zahorik, 1993). In the simplest sense, switching delinks a service firm from the customer’s future revenue stream. Executives need research-based knowledge if they are to avoid the revenue-reducing and cost-incurring impacts of customer switching (Keaveney, 1995).
Most companies strive for customer loyalty in a retail setting and considerable efforts are put in to maintain a loyal customer base. As the competition in most sectors grows tighter, both the importance and the challenge in, keeping customers loyal increased. Statement of the problem, It has been widely argued that lasting customer relationships are beneficial for the company (Reichheld and Sasser, 1990; Rust and Oliver, 1994; Berry, 1995) and several claims as to how organizations benefit from having loyal customers have been made.
Research have shown that decreasing the retention rate by only a few percentages can have a major impact on the levels of profitability of a company (Reichheld and Sasser, 1990).
Retail sector was chosen as the context for the empirical study, as retail sector is an interesting sector for studying disloyalty. It is a context where retail market has gone through several important changes during the last decade which have created challenges for maintaining customer loyalty. In such a situation, a study of customer disloyalty should also have managerial relevance.
The general purpose of this study is to identify, describe and analyze factors that have an impact on customer switching behavior. The study aims to identify factors that influence customers becoming disloyal. The empirical study was carried out in Coimbatore, India, in select organized retail stores, a service context where long-term relationships have been the norm. Increasing competition has challenged traditionally stable relationships, making retail sector an interesting context for studying customer disloyalty.
Exploratory research was conducted among service customers to investigate the following questions: What are the determinants of customers' decisions to switch stores? What critical events, combinations of events or series of events cause customers to leave familiar service providers and seek new ones? What roles do service encounters and technical service quality play relative to other functions of the service firm? Such questions were posed in order to help managers and researchers understand service switching from the customer’s perspective.
Literature survey: Keaveney (1995) through her empirical study found eight reasons for switching behavior in 25 different services the various categories found are pricing, inconvenience, core service failure, service encounter failure, response to service failure, competition, ethical problems and involuntary switching.
Gremler and Brown (1996) defined service loyalty as follows; “service loyalty is the degree to which a customer exhibits repeat purchase behavior from a service provider, possesses a positive attitudinal disposition toward the provider and considers using only this provider when a need for this service arises”
Alford and Sherell (1996) in their study examined that it is cheaper to retain existing customers than attracting new customers; it appears that managers need to re-emphasize how customers “feel” about their experiences of service delivery.
With consistent findings that service quality and satisfaction are different constructs and that service quality leads to customer satisfaction, the research interest moved to study the linkages between customer satisfactions, service quality and customer loyalty/retention. While, the direct relationship between customer satisfaction and loyalty has been shown to complex and asymmetric (Bloemer and Kasper, 1995; Mittal and Lassar, 1998; Oliver, 1999) and some research has shown that switching behavior and repurchase intentions are not consistent with satisfaction levels (Stauss and Nehaus, 1997), a number of studies suggest that there is a significant positive relationship between customer satisfaction and customer loyalty/retention.
Ennew and Binks (1996) argued in favor of core marketing concept i.e; studied the center of the marketing concept is the idea of improving organizational performance by attracting and retaining satisfied customers. Much of the teaching and research in marketing has tended to focus on the former- acquiring new customers by developing products to satisfy specific needs has been one of the main concerns of the academics and practitioners. However, the relative costs of customer acquisition and customer retention have resulted in a growing interest in issues surrounding the building and maintenance of long-term customer relationships as a key to improved profitability. This notion of relationship marketing thought to be of particular relevance in industrial and service markets, although many consumer goods suppliers are becoming increasingly interested in the concept of customer relationships and customer retentions.
Levesque and McDougall (1996) conducted a study to investigate customer dissatisfaction diminishes organizations customer base, forces the firms to rely on a more volatile customer mix and erodes the firm’s reputation. This is particularly true in service industries, where customer dissatisfaction is a significant problem (Singh,2009). Customer responses to dissatisfaction occur along a continuum of severity and although some defections are caused by dissatisfaction (Keaveney, 1995), consumers may simply remain inactive and take no action all when dissatisfied.
Rowley and Dawes (2000), breaking away from the tradition of analyzing the loyalty, have researched on the disloyalty and the characteristics of non-loyals. They had initially resituated the loyalty the loyalty-ladder proposed by Dick and Basu and adopted analytical approach to gain more insight on loyalty behaviors. It was claimed that analyzing the other side of loyalty, termed as ‘dis-loyalty’ would certainly contribute to widening the base of the loyalty customers. Through an empirical approach they have proposed four types of disloyal: disturbed, disenchanted, disengaged and disruptive. They also suggested these four categories that can be mapped on to a grid with attitudinal and behavioral dimensions.
Mattila (2004) investigated on the negative impact of service failures in customer loyalty with a special focus on moderating effect of affective commitment on post-failure loyalty intentions. The results of empirical study established that emotionally bonded customers might feel ‘betrayed’ when a service failure occurs, thus resulting in sharp decrease in post recovery attitudes. Conversely, this negative effect was limited to poor service recovery among customers with low affective commitment. The results also suggested that affective commitment might reduce the spill-over effects of service failures to future loyalty behaviors.
This survey on parsimonious research studies in retail context from the extant literature has yielded propitiation that customer switching behavior is significantly influenced by a set of factors, viz., store attributes, service failure, family factors, reference groups and word-of-mouth, competitor attractiveness, involuntary switching, service encounter failure, ethical standards, loyalty incentives, pricing factors, convenience factors. And with this conceptual framework, the research proceeded further to empirically test and confirms the proposed model (Fig. 1).
| Fig. 1: | The conceptual fram work of propsed model |
The framework thus obtained succinctly outlines the components of switching cost to customers of retail stores in Indian retail sector context.
RESEARCH METHOD
The present study is an exploratory research conducted in the city of Coimbatore, Tamil Nadu, India. It specifically focuses on customer switching behavior in organized retail stores. The research was conducted with the sample size of 120. The respondents were interviewed at different organized retail stores at varied timings and on different weekdays with the help of a structured questionnaire. A multivariate statistics tool namely, multiple regression analysis was deployed. The data was analyzed with the help of statistical package available in the form of software i.e., SPSS 13. 120 respondents were collected for the study from three types of retail stores-Hyper Market, Super Market and Departmental Stores in Coimbatore.
RESULTS AND DISCUSSION
MULLTIPLE REGRESSION RESULTS
Multiple regression analyses were performed to find the impact of select demographic variables on various customer switching behavior, dimensions and results with interpretations are given below.
Convenience factor: It is obvious from the Table 1, that profession of the customers has a strong impact in explaining the convenience dimension ‘I will switch if parking area is not available’ (Standardized Beta Coefficient = 0.82 and T value is 5.66; significant at 0.05 levels). The model F-statistic of 42.47 is also significant at 0.05 levels. The adjusted R2 value of 0.52 is also reasonable and explains approximately 52% of variance in the convenience dimension total score. Profession of the customers has some impact on the indicator “I will switch if it is not located in the proper location’ (Standard Beta Coefficient = 0.47 and T-value is 3.88; significant at 0.05 levels). The model F-statistic of 38.37 is also significant at 0.05 levels.
Profession of the customers has a strong impact in explaining the convenience dimension ‘I will switch if home delivery is not available’ (Standardized Beta Coefficient = 0.73 and T value is 6.41; significant at 0.05 levels). The adjusted R2 value of 0.56 is also reasonable and explains approximately 56% of variance in the convenience dimension total score. Profession of the customers has a strong impact in explaining the convenience dimension ‘I will switch if store is overcrowd’ (Standardized Beta Coefficient = 0.72 and T value is 7.01; significant at 0.05 levels). The adjusted R2 value of 0.64 is also reasonable and explains approximately 64% of variance in the convenience dimension total score.
Profession of the customers has a strong impact in explaining the convenience dimension ‘I will switch if store timings are inconvenient’ (Standardized Beta Coefficient = 0.63 and T value is 4.68; significant at 0.05 levels). The adjusted R2 value of 0.37 is also reasonable and explains approximately 37% of variance in the convenience dimension total score. Profession of the customers has a strong impact in explaining the convenience dimension ‘I will switch if there are long waiting lines’ (Standardized Beta Coefficient = 0.39 and T value is 3.47; significant at 0.05 levels). The adjusted R2 value of 0.57 is also reasonable and explains approximately 57% of variance in the convenience dimension total score.
Purchase size of the customers has an impact in explaining the convenience dimension “I will switch if home delivery is not available’ (Standardized Beta Coefficient = 0.67 and T value is 5.24; significant at 0.05 levels).
| Table 1: | Results of multiple regression analysis to find the impact of demographic varibles on various customer swithing behavions in dimensions |
Patronage period of the customers has an impact in explaining the convenience dimension “I will switch if long waiting lines are there’. (Standardized Beta Coefficient = 0.31 and T value is 2.89; significant at 0.05 levels). In fact, it can be inferred from the results that, the lesser the education, the more the favorable impact on the switching behavior indicators (Standard Beta Coefficients = 093 and -0.54).
Loyalty incentives: It is apparent from the Table 1, that profession of the customers has a strong impact in explaining the loyalty incentives dimension ‘I will switch if no reward points / bonus points’ (Standardized Beta Coefficient = 0.50 and T value is 3.36; significant at 0.05 levels). The model F-statistic of 11.87 is also significant at 0.05 levels. The adjusted R2 value of 0.23 is also reasonable and explains approximately 23% of variance in the loyalty incentives dimension total score.
Profession of the customers has some impact on the indicator “I will switch if no discount offers are there’ (Standard Beta Coefficient = 0.69 and T-value is 6.09; significant at 0.05 levels). The model F-statistic of 50.64 is also significant at 0.05 levels. The adjusted R2 value of 0.55 is also reasonable and explains approximately 55% of variance in the Loyalty Incentives dimension total score.
Average purchase size of the customers has a reasonable impact in explaining the Loyalty Incentives dimension ‘I will switch if reward points/bonus points’ (Standardized Beta Coefficient = -0.08 and T value is -0.76; significant at 0.05 levels). The adjusted R2 value of 0.21 is also reasonable and explains approximately 21% of variance in the loyalty incentives dimension total score. Patronage period of the customers has a reasonably good impact in explaining the loyalty incentives dimension ‘I will switch if store has no loyalty cards’ (Standardized Beta Coefficient = 0.39 and T value is 3.37; significant at 0.05 levels). The model F-statistic of 37.57 is also significant at 0.05 levels. The adjusted R2 value of 0.49 is also reasonable and explains approximately 49% of variance in the loyalty incentives dimension total score.
Pricing factors: Patronage period of the customers has an impact in explaining the Pricing dimension “I will switch if no reduction in MRP’ (Standardized Beta Coefficient = 0.33 and T value is 1.02; significant at 0.05 levels). The model F-statistic of 36.45 is also significant at 0.05 levels. The adjusted R2 value of 0.47 is also reasonable and explains approximately 47% of variance in the pricing dimension total score.
Ethical standards: It is obvious from the Table 1, that patronage period of the customers has a strong impact in explaining the Ethical standard dimension ‘I will switch if the store tries to cheat’ (Standardized Beta Coefficient = 0.69 and T value is 9.02; significant at 0.05 levels). The model F-statistic of 136.08 is also significant at 0.05 levels. And “I will switch if the store tries to sell low quality products for high price’ (Standard Beta Coefficient = 0.44 and T-value is 3.45; significant at 0.05 levels). The adjusted R2 value of 0.77 is also reasonable and explains approximately 77% of variance in the Ethical standard dimension total score.
Profession of the customers has some impact on the indicator “I will switch if the store tries to sell low quality products for high price’ (Standard Beta Coefficient = 0.33 and T-value is 2.46; significant at 0.05 levels). The model F-statistic of 24.88 is also significant at 0.05 levels. The adjusted R2 value of 0.39 is also reasonable and explains approximately 39% of variance in the Ethical standard dimension total score.
Servie encounter failure: It is very clear from the Table 1, that profession of the customers has a strong impact in explaining the Service encounter failure dimension ‘I will switch if poor counter service is there’ (Standardized Beta Coefficient = 0.61 and T value is 6.0; significant at 0.05 levels). The model F-statistic of 73.29 is also significant at 0.05 levels. The adjusted R2 value of 0.64 is also reasonable and explains approximately 64% of variance in the Service encounter failure dimension total score.
Service failure perception: It can be inferred from the Table 1, that profession of the customers has a reasonably good impact in explaining the Service failure dimension ‘I will switch if less variety of products are not available in the store’ (Standardized Beta Coefficient = 0.53 and T value is 4.51; significant at 0.05 levels). The model F-statistic of 95.46 is also significant at 0.05 levels. The adjusted R2 value of 0.70 is also reasonable and explains approximately 70% of variance in the Service failure dimension total score.
Average purchase size of the customers has a reasonable impact in explaining the Service failure dimension ‘I will switch if low quality products are sold’ (Standardized Beta Coefficient =-0.44 and T value is 3.48; significant at 0.05 levels). The model F-statistic of 25.0 is also significant at 0.05 levels. The adjusted R2 value of 0.37 is also reasonable and explains approximately 37% of variance in the Service failure dimension total score.
Patronage period of the customers has a reasonably good impact in explaining the Service failure dimension ‘I will switch if store has no stock’ (Standardized Beta Coefficient = 0.69 and T value is 0.62; significant at 0.05 levels). The adjusted R2 value of 0.71 is also reasonable and explains approximately 71% of variance in the Service failure dimension total score.
Store attributes: It is notable from the Table 1, that profession of the customers has a reasonably good impact in explaining the Store attribute dimension ‘I will switch if the store has no amenities’ (Standardized Beta Coefficient = 0.50 and T value is 4.18; significant at 0.05 levels). The model F-statistic of 42.38 is also significant at 0.05 levels.
The adjusted R2 value of 0.51 is also reasonable and explains approximately 51% of variance in the Store attribute dimension total score. Average purchase size of the customers has a strong impact in explaining the store attribute dimension ‘I will switch if the store has no product assortment’ (Standardized Beta Coefficient = 0.70 and T value is 7.20; significant at 0.05 levels). The adjusted R2 value of 0.64 is also reasonable and explains approximately 64% of variance in the store attribute dimension total score.
Patronage period of the customers has a reasonably good impact in explaining the Service failure dimension ‘I will switch if store has no ambience’ (Standardized Beta Coefficient = 0.43 and T value is 2.17; significant at 0.05 levels). The adjusted R2 value of 0.35 is also reasonable and explains approximately 35% of variance in the Store attribute dimension total score.
Competitor attractiveness: From Table 1, it can be observed that profession of the customers has a reasonably good impact in explaining the Competitor attractiveness dimension ‘I will switch if a new store opens in my area’ (Standardized Beta Coefficient = 0.61 and T value is 4.55; significant at 0.05 levels). The model F-statistic of 73.29 is also significant at 0.05 levels. The adjusted R2 value of 0.36 is also reasonable and explains approximately 36% of variance in the Competitor attractiveness total score. Average purchase size of the customers has a directional impact in explaining the Competitor attractiveness dimension ‘I will switch if new store opens in my area’. The higher the purchase size the lesser the switching intention if a new store opens.
Patronage period of the customers has a reasonably good impact in explaining the Competitor attractiveness dimension ‘I will switch if store has no better service’ (Standardized Beta Coefficient = 0.43 and T value is 2.17; significant at 0.05 levels). The model F-statistic of 21.70 is also significant at 0.05 levels. The adjusted R2 value of 0.35 is also reasonable and explains approximately 35% of variance in the Competitor attractiveness dimension total score.
Involuntary switching: It is obvious from the Table 1, that patronage period of the customers has a strong impact in explaining the involuntary switching dimension ‘I will switch if a store is closed or moved’ (Standardized Beta Coefficient = 0.69 and T value is 9.02; significant at 0.05 levels). The model F-statistic of 136.08 is also significant at 0.05 levels.
The adjusted R2 value of 0.77 is also reasonable and explains approximately 77% of variance in the involuntary switching total score. Patronage period of the customers has a reasonably good impact in explaining the Competitor attractiveness dimension ‘I will switch if I am moved or transferred from that area’ (Standardized Beta Coefficient = 0.69 and T value is 7.90; significant at 0.05 levels). The model F-statistic of 95.46 is also significant at 0.05 levels. The adjusted R2 value of 0.70 is also reasonable and explains approximately 70% of variance in the involuntary switching dimension total score.
Family factors: It is obvious from the Table 1, that profession of the customers has a reasonably good impact in explaining the Family Factors dimension ‘I will switch if children suggests to change’ (Standardized Beta Coefficient = 0.61 and T value is 4.38; significant at 0.05 levels). The model F-statistic of 20.07 is also significant at 0.05 levels. The adjusted R2 value of 0.32 is also reasonable and explains approximately 32% of variance in the Family Factors total score.
Average purchase size of the customers has a directional impact in explaining the Family factors dimension ‘I will switch if children suggests changing’. The higher the purchase size the, lesser the switching intention when children suggests.
Patronage period of the customers has a reasonably good impact in explaining the Competitor attractiveness dimension ‘I will switch if spouse suggests to change’ (Standardized Beta Coefficient = 0.53 and T value is 5.40; significant at 0.05 levels). The model F-statistic of 65.85 is also significant at 0.05 levels. The adjusted R2 value of 0.62 is also reasonable and explains approximately 62% of variance in the Family factors dimension total score.
Reference groups and word of mouth: From Table 1, it is inferred that profession of the customers has a reasonably good impact in explaining the Reference groups and Word of mouth dimension ‘I will switch if friends suggests to change’ (Standardized Beta Coefficient = 0.61 and T value is 6.01; significant at 0.05 levels). The model F-statistic of 73.29 is also significant at 0.05 levels. The adjusted R2 value of 0.32 is also reasonable and explains approximately 32% of variance in the Family Factors total score. Average purchase size of the customers has a directional impact in explaining the Reference groups and Word of mouth dimension ‘I will switch if colleague suggests changing’. The higher the purchase size the, lesser the switching intention when colleague suggests.
Purchase size of the customers has a reasonably good impact in explaining the Reference groups and Word of mouth dimension ‘I will switch if friends suggests to change’ (Standardized Beta Coefficient = 0.53 and T value is 5.40; significant at 0.05 levels). The model F-statistic of 73.29 is also significant at 0.05 levels. The adjusted R2 value of 0.64 is also reasonable and explains approximately 64% of variance in the Reference groups and Word of mouth dimension total score.
Patronage period of the customers has a strong impact in explaining the Competitor attractiveness dimension ‘I will switch if colleague suggests to change’ (Standardized Beta Coefficient = 0.78 and T value is 7.78; significant at 0.05 levels). The model F-statistic of 64.86 is also significant at 0.05 levels. The adjusted R2 value of 0.61 is also reasonable and explains approximately 61% of variance in the Reference groups and word of mouth dimension total score.
Suggestions, Key Implications, Limitations and Directions for Future Research:
| • | Customer relationship management (CRM) initiatives should be incorporated with specific focus on loyalty management by identifying different levels of customers’ interests based on their demographic factors as the results of the study clearly brought out the impact of profession, average purchase size and period of patronage on various dimensions of customer switching behavior |
| • | Pricing should be designed to attract all type of customers and competitor pricing policies and the quality of the products should also be maintained in order to not to lose the both customers who are quality conscious and pricing conscious |
| • | The inconvenience of customers should be minimized because many people tend to switch if inconvenience factors such as parking, location, home delivery, overcrowd, store timings and long waiting lines |
| • | As the purchasing power of the customers is increasing they will be ready to spend more if they are given incentives who shop regularly and by that purchase size, frequency and there by defection of customers can be minimized |
| • | Service encounter failures should be reduced and if any should be corrected immediately because now the customer has got many options (organized retail stores) to shop. Hence, the employees should be caring toward the customers and should be polite, good looking, knowledgeable and fast in service because customers are ready to switch if slow counter service is there or less counters is there, hence the counters must be increased to decrease the long waiting lines in the time of first ten days of every month |
| • | Retail stores main purpose is to provide the service if it fails then customers will defect for sure. Hence, the factors like no stock, low quality or spoiled products and less variety of products should be taken care to keep the customer loyal |
| • | Many of the customers come to store for family shopping and family plays a major role in switching behavior. Hence, care should be taken in attracting children and making them happy with the aid of ambience of the store. Women and children products should be kept in a separate easy assortment. So as to facilitate the ubiquitous ‘market basket’ |
| • | The organized retail stores should be more competitive and should change their offering according to the competitor’s service, advertisements, promotional offers, corporate image or reputation |
| • | As the customer’s education levels are increasing customers are becoming aware of the consumer protection acts and rules, so stores should be very careful in not committing ethical mistakes |
| • | The organized retail stores change the store attributes regularly because many customers like the newness, innovation and creativity so layout, assortment, ambience and amenities should be maintained properly and attractively because many customers are willing to change the store if proper store attributes are not there |
| • | The retail stores should be more careful about word of mouth and reference groups, as a satisfied customer tells two other people about store but a dissatisfied customer informs 6-8 people |
CONCLUSION
The key notation of success in the highly competitive current retail industry is not just winning customers but in keeping them. Customers will try a store based on their perception, if that result in satisfaction, perceived value of the store will increase and there by prompting repeat visit for future shopping. If any of the factors, viz., inconvenience, pricing, loyalty incentives, ethical standards, service encounter failures, service failures, store attributes, competitor attractiveness, involuntary switching, family factors and reference groups and word of mouth, fail ,that could cast a spell of influence, consequently the customer may switch the store. The influences of the said factors were tested through empirical approach in this study and this view is exactly endorsed by the results of this study.
The study on customer switching cost was carefully analyzed and interpreted with the help of statistical tool multiple regression analysis applied on the primary data from customers of organized retail stores in Coimbatore, India.
Further research in this context can be taken up incorporating employees’ role in switching behavior and the results perhaps then be extended to other related service industries. Such efforts would certainly corroborate the maiden attempt made in this study to decipher the disloyalty content i.e., switching behavior dimensions which could vitally impact the performance of the rapidly booming retail sector in Indian context.