In the fast moving life, people have less time for each work/task. This study focuses on knowing the factors that contribute to the buyer’s willingness to wait and shop during the opening hours in the morning. A grocery store needs to focus well on the improvement of the retail service quality of grocery that helps to sustain and retain customers. Rarely, it so happens that the buyer needs to wait during the opening hours, as there is some delay in setting-up.
This study aims at predicting the factors that comforts the buyer to wait to shop during the delay in the setup using Binary Logistic Regression. The important factor that contributes to the prediction is identified along with the target group. Few suggestions are given in the conclusion to build customer relationship and empathy for sustenance.
Key words: Service Quality, Grocery, Retail Store, Sustenance
Measuring service quality is difficult because of its unique characteristics: Intangibility, heterogeneity, inseparability and Perishability (Bateson, 1995).
Service quality is linked to the concepts of perceptions and expectations (Parasuraman et al., 1985, 1988.
Based on this perspective, Parasuraman et al. developed a scale for measuring service quality, which is mostly popular known as SERVQUAL. SERVQUAL represents five service quality dimensions known as tangibility, reliability, responsiveness, assurance, and empathy.
The researcher had customized the items of the five dimensions to suit grocery retailing. After calculating the SERVQUAL score, the researcher aims at predicting the factor that makes shopper to wait during the store opening hours along with few predictor variables as follows, spending on grocery, frequency of grocery shopping, age, occupation.
The prediction helps to improve the service quality.
It is universal fact that customer satisfaction is the base for repeated purchase. For example, when buyers perceive as a good product or service, each one of the buyer will voluntarily share their experience with few people in their circle. A fact, that more than half of Indian’s business is the outcome “word-of-mouth” communication. Improvement in customer retention even by small percentage can increase profits by atleast 25% (Griffin, 1995). The University of Michigan in a research concluded that for every percentage increase in customer satisfaction, there is an average increase of 2.37% of return on investment (Keiningham & Vavra, 2001). Hence, sustainability plays a major role. In general, the buyers largely praise the businesses that service them the way they expected to be serviced; they will even be ready to offer more price for that service.
The message is obvious finally that the customer’s willingness to wait during store opening hours is an indication that the customers are satisfied and customers not willing to wait may not be loyal to the store at present and chances are there that they might also change. Customer satisfaction is like a “Golden egg” that should be monitored and managed just like any physical asset. This is applicable for both service-oriented and product-oriented organizations (Sureshchander, Rajendran, & Kamalanabhan, 2001).
Strategies that are more effective are required to increase the Food & Vegetable buying in grocery stores. Grass roots action involving specific strategies that enhance a sense of economy buying for low-income communities are key considerations to sustainability (Glanz & Yaroch, 2004). A conceptual framework on service quality to examine the impact of customer participation in service delivery infers that for certain service that are familiar to consumers or the ones that require a low level of expertise is suggested to increased customer participation , thus it enhance service quality and sustainability (Dabholkar, Thorpe, & Rentz, 1995).
In the past two decades, academics (Gr?nroos, 1984; Parasuraman, Zeithaml and Berry, 1985; Cronin and Taylor, 1992; Teas, 1993) have identified the core attributes of service quality, and devised a methodology to measure and stressed that to compete or sustain any organisation needs to understand the customers’ expectations and perceptions of service quality as these factors influences the customers’ choice of store based on their comfort level.
Due to the growth in the number of retail stores and the quality of service, the buyers prefer a better store that is assessable to them. Sometimes the main gate into the store is opened but the buyer has to wait as pre preparation is delayed. Some buyers move to another store. Hence, the researcher would like to predict the loyal customers who are willing to wait to shop during the store opening hours along with the factors that motivate a buyer to wait. This study aims at Predicting the contribution of the factors that makes the Buyer to Wait to Shop Grocery when the shop is yet to be opened. 355 respondents said that they would not wait for the shop to be opened and 187 respondents said that they would wait when the shop is yet to be opened. This research predicts from both the category of respondents.
The study is confined to five major cities in Tamilnadu, India (Chennai, Salem, Trichy, Madurai, and Tirunelveli).
The objective of this study is to assess the influence of the selected factors on customer’s Willingness to wait when the shop is yet to be open. In accordance with this objective, the research encompasses the below objectives:
a. To predict the contribution of the factors that motivates the Buyer to Wait to Shop Grocery when the shop is yet to be open using Binary Logistic Regression.
b. To predict the conversion from those who said they would wait and those who said they will not wait to shop grocery.
Research study is descriptive in nature. Descriptive method is a method that describes the study systematically, methodologically, rationally and ethically utilizing opinion, behavior and its relevance to the phenomenon being studied (Ayyamperumal, 2015)
A structured questionnaire was constructed taking into account SERVQUAL dimensions such as Tangibility, Reliability, Responsiveness, Assurance, Empathy and the reliability and validity was tested. Since the population is not known the sampling Method employed is Convenience sampling. The questionnaire was collected from the 542 people who have shopping experience.
Binary Logistic Regression – willingness to wait to shop grocery as dependent variable and the covariates/predictors are spending on grocery, frequency of grocery shopping, age, occupation.
Among 187 respondents, those who said they would wait to shop, only 51 respondents might wait and 136 respondents are predicted not to wait. The correctness of the predicted percentage is in the coumn 4, is 27.3%.
Based on the four predictors using binary logistic regression predicted that 98 respondents out of 542 have the intention to wait to shop grocery during the opening hours in the morning.
a. In predicting the factors that contribute to the prediction of the intention to wait, found that occupation is the only factor that contributes to the decision on the intention to wait is correct in reality too. People of different occupation have different urgency and this has helped to identify the factor that contributes.
b. Among 355 respondents those who had said they will not wait, 47 respondents might have the intention to wait in future. Among 187 respondents, those who said they would wait to shop, only 51 respondents might wait in future. Based on the analysis using four predictors, predicted that 98 respondents have the intention to wait. Hence, it is clear that the predicted conversion from the analysis, among those who said yes and no.
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