Academy of Marketing Studies Journal (Print ISSN: 1095-6298; Online ISSN: 1528-2678)

Research Article: 2021 Vol: 25 Issue: 3

Customer Satisfaction and Loyalty In Retailing In the Covid19 Pandemic

Bidyut Jyoti Gogoi, Indian Institute of Management, Shillong

Abstract

Firm’s need loyal customers to sustain in tough competition and uncertainty. Customer satisfaction plays a big role in creating a pool of loyal customers. The loyal customers are needed also to voice out for the company products and services. Customer loyalty also helps in creation of positive brand image. Brand reputation helps the firm to stand out even during tough times. The Covid19 pandemic has brought in several changes in the way consumer behaves towards a brand. The brand strategies have also undergone changes to meet the consumer requirements.

Keywords

Covid19, Pandemic, Store Service, Price, Perceived Quality, Local Presence, Customer Satisfaction, Loyalty.

Introduction

India may experience a third wave of the Covid19 pandemic if measures are not taken to stop the spread of the virus (Mordani, Sneha, 2021). As per the findings of medical research, the new mutated coronavirus may be airborne (India.com, 2021). This is where even the social distancing of 2 meters will not be sufficient. Staying indoors and avoiding crowded placed will help. Already the second wave is arriving at a peak and there are several restrictions imposed including lockdown starting May 2021 in several parts of the country. Restrictions are imposed on movement of vehicles and people. Consumption of goods and services undergo changes and are dependent on their availability.

It has been seen in the pandemic that there is a relationship between the consumption patterns and undesirable environmental conditions. This is quite evident from the consumption patterns seen during the Covid19 pandemic since December 2019. Consumers are becoming more conscious in choosing their products. Brands do not matter too much but quality and safety matters. Consumers are more concerned to keep themselves and their family healthy. This is the reason why there is a change in consumption patterns which is seen during the pandemic. People cannot afford to fall sick as there are restrictions to go to the hospital unlike good times. Brands which are well known and popular are selling well as consumers do not want to try unknown brands. Even local brands are doing well due to the quality associated.

It is seen that behavioral outcomes like patronage and loyalty are a result of the attitudinal responses of the consumer (Shi et al. 2014). Attitude of a consumer develops due to cognition or learnings from the usage of products or service. Good experience during the learning stage usually helps in development of positive attitudes. Positive emotions result in customer satisfaction, delight and emotional brand attachment (Torres & Kline, 2006; Torres, et al. 2014). Satisfaction is an overall assessment of the value a customer gets from the products or services consumed. Hence, customer satisfaction is a measure of the overall experience of a customer (Jones & Suh, 2000; Johnson & Fornell, 1991).

The researcher in the paper wants to find out the influence of instore service, pricing, perceived quality and local presence on customer satisfaction and loyalty.

Literature Review

Store Service

Instore experience through the various touchpoints shape the customer experience (Lemon and Verhoef, 2016). The digital technology has given rise to a new sort of behavior generation which has to be studied well to service the customer better (Bertacchini et al., 2017; Cano et al., 2017; Dacko, 2017; Gelderman et al., 2011; Immonen et al., 2018; Pantano & Gandini, 2017; Willems et al., 2017). The pandemic has seen the transition from the offline mode to online mode. Digital technologies are helping to survive the crisis. There is a transition seen from offline to online/mobile to omnichannel mode settings (Dacko, 2017; Demirkan & Spohrer, 2014; Hilken et al., 2017; Inman & Nikolova, 2017; Papagiannidis et al., 2017; Rezaei & Valaei, 2017). Different retailers have different digital strategies. Some offer pure digital while some offer a hybrid of both digital and online (Huang & Rust, 2018). The basic idea is the same for all, to provide a seamless customer experience.

The instore frontline employees have a crucial role in enhancing shopping experience and influence purchase behavior (Lim et al., 2017). Many retailers have resorted to digital displays instore to enhance the store experience (Pantano, 2016). The instore digital displays help customers in finding, comparing, locating and buying goods which enhances their shopping experience (Van Kerrebroeck et al., 2017). Instore service has a positive influence on the satisfaction of consumers (Brown, 2001; Gogoi & Dutta, 2020; Huddleston et al., 2009). Upscale retailer’s customers desire more customer service (Huddleston et al., 2009). Hence specialty retailers need to provide more intensive store service for achieving customer satisfaction (Grewal et al., 2003) and loyalty. Based on the discussion the following hypothesis is proposed.

H1: Store Service has a positive influence on customer satisfaction.

H2: Store Service has a positive influence on loyalty.

Pricing

Price is an indicator of product quality (Chen et al., 2015; Stiglitz, 1987). Pricing package has a significant effect on customer satisfaction (Campo & Yagüe, 2008). The positive image created by quality might counterbalanced by the negative pricing effect (Chen et al., 2015). Fairness is a judgement of the means of achievement to reach an outcome (Bolton et al., 2003). The fairness of judgement of price is based on certain norm or standard (Estalami, et al., 2007). Price is considered an important antecedent of customer satisfaction as consumer thinks basically of price paid post purchase (Anderson & Sullivan, 1993; Anderson et al., 1994; Cronin et al., 2000; Fornell, 1992; Zeithaml, 1988).

The extent of influence of price over satisfaction is dependent on the service quality, product quality, price, situation and personal factors (Zeithaml & Bitner, 1996). Price sensitivity increases with heightened unfair practices adopted by firms (Xia et al., 2004) which also affects the satisfaction level (Oliver & Swan, 1989) and lower purchase intentions (Campbell, 1999a, 1999b). The pandemic has taught several lessons to business. Consumers are becoming more price sensitive and at the same time cautious about the product quality. Value added services like home delivery and customized orders matter a lot. It is seen that price has a positive influence on consumer perception and thereby influences the purchase decision (Gogoi, 2020). It is also seen that mediumly processed products/services attains the maximum customer satisfaction (Campo & Yagüe, 2009). Perceived price has a significant influence on the service quality (Bojanic, 1996; Parasuraman et al, 1991) and hence also influences customer satisfaction and loyalty. Based on the discussion the following hypothesis is proposed.

H3: Price has a positive influence on customer satisfaction.

H4: Price has a positive influence on loyalty.

Perceived Quality

Quality is generally taken as the overall judgement of the consumer on the product or service (Steenkamp,1990; Zeithaml, 1988). There exists relationship between quality and customer satisfaction (Reimann, et al., 2008). Perceived quality is the differentiation the product or service creates to mark its superiority (Zeithaml, 1988). Perceived quality influences the affective behavior of the consumer (Anselmsson et al., 2007). Perceived quality is the overall assessment of the product performance rather than perceptions on any product attribute (Holbrook & Corfman, 1985). Employee services influence the consumer perceive quality which helps in getting satisfied consumers (Pan & Zinkhan, 2006). Perceived quality depends on the way the employees are oriented towards service delivery and has a large influence on the customer satisfaction (Baker et al., 2002; Jang & Namkung, 2009). Perceived product quality induces customer satisfaction (Gomez et al., 2004; Huddleston et al.,2009; Zhao and Huddleston, 2012). If the perceived quality of the store is high there is customer satisfaction (Zhao and Huddleston, 2012) which leads to loyalty. The Covid19 pandemic has changed the consumer behavior and their expectations. Consumers now aspire for more perceived quality to endorse a product. For a customer now, their personal health and their family health is the first priority. They will not compromise with quality for any product they purchase. Based on the discussion the following hypothesis is proposed.

H5: Perceived quality has a positive influence on customer satisfaction

H6: Perceived quality has a positive influence on loyalty

Local Presence

Research shows that physical proximity attracts consumers and increases impulse buying (Peck, & Childers, 2006).

The lockdowns during the covid19 pandemic posed a lot of problems in getting the regular products for consumption. During the lockdowns the local brands played a big role in supporting the local people. It is also seen that local retailers’ sense of social responsibility towards their local community is very high (Razalan, et al., 2017). Because of the local presence they were easily available for consumption while most of the brands were out of reach due to movement restriction and logistics issues. The support from local brands during tough times led to popularity of local brands during the pandemic and consumers too voiced for the local brands. Moreover, with consumers starting to use products available locally they could also see the genuine quality of the products which can be compared with the other branded products. Thus, the crisis has led consumers to voice out for the local brands which could cater to their requirements. Based on the discussion the following hypothesis is proposed.

H7: local presence of brands has a positive influence on customer satisfaction.

H8: local presence of brands has a positive influence on loyalty.

Customer Satisfaction

The role of satisfaction has been extensive researched in retailing, e-commerce and mobile commerce (Demirci Orel and Kara, 2014; Vesel and Zabkar, 2009). The strength of relationship between satisfaction and loyalty varies across different nations (Aksoy et al., 2013). Satisfaction is a cognitive behavior and a result of post purchase evaluation (Bearden & Teel, 1983; Churchill G & Suprenant, 1982; Oliver,1979, 1980; Oliver & DeSarbo, 1988). Customer satisfaction is also viewed as a judgement based on cumulative accumulation on perceived services and not just transaction specific phenomenon (Anderson, E.W, et al., 1994; Bayus, 1992; Wilton & Nicosia,1986). Satisfaction is judgement of the feeling post the evaluation of the services (Oliver, 1979). Satisfaction is the influence of confirmation which arise out of expectations and perceived performance (Bhattacherjee, 2001; Swan and Oliver, 1989). Satisfaction helps in understanding loyalty (Anaza and Zhao, 2013; Calder et al., 2013; Shankar et al.,2003). Customer satisfaction is cumulative satisfaction from products/services and leads to loyalty (J. C. Anderson & Narus,1990; Ganesan, 1994). Customer satisfaction is an antecedent of loyalty (Bitner,1990; Bloemer, 2002; Chen and Quester, 2006). Customer satisfaction has a positive influence on loyalty (Gogoi, B. J, 2021). Customer Satisfaction is found to be linked to loyalty of service organizations (Bowen and Chen, 2015; Lee, 2013). Based on the discussion the following hypothesis is proposed.

H9: Customer Satisfaction has a positive influence on Loyalty.

Based on the literature review a conceptual model is developed as depicted in Figure 1.

Figure 1 The Conceptual Model

Methodology

A primary survey was carried out to collect data from customers. The research was carried out using a structured questionnaire. Out of a total of 500 questionnaires distributed there were only 209 completely filled questionnaires. The sample size of the survey is 209. The respondents were general shoppers. 65.5% of the respondents were male and 34.4% of the respondents were female. The respondents are in the age group 21 years to 30 years. The data was analyzed using SmartPLS 3 (Ringle, et al. 2015).

Measurement Scale

The questionnaire consisted of a total of 23 statements. The scale for service quality is adapted from (Burt & Carralero-Encinas, 2000; Semeijn et al., 2004). The scale for pricing is adapted from (Campbell, 1999a, 1999b; Huber et al., 2001; Kimes, 1994); The scale for perceived quality is adapted from (Grunert, 1997; Pappuet et al. 2005); The scale for local presence is adapted from (Juan & Joele 2011; Klein, 2003; Verhagen, et al. 2014). The scale for customer satisfaction is adapted from (Bloemer and Ruyter, 1998). The scale for loyalty is adapted from (Bigne, et al. 2001; Cronin et al. 2000; Reynolds & Beatty’s, 1999).

One of the statements, SAT3, from the construct customer satisfaction was removed for making the model more stable in Table 1

Table 1 Model Fit Summary
  Saturated Model Estimated Model
SRMR 0.169 0.204
d_ULS 7.237 10.499
d_G 4.143 4.570
Chi-Square 3041.394 3232.208
NFI 0.423 0.387

Results and Discussion

SRMR: A value less than 0.10 or of 0.08 (Hu & Bentler, 1999) is considered a good fit (Henseler et al., 2015). Here the SRMR value is 0.169 in Figure 2.

Figure 2 SEM Path Analysis

NFI: The NFI results in values between 0 and 1. The closer the NFI to 1, the better the fit (Lohmöller, 1989). The NFI value is 0.423 which is moderate.

Rms Theta: The measure should be close to zero to indicate good model fit (Henseler et al., 2015; Lohmöller, 1989). The rms Theta value is 0.263 in Table 2.

Table 2 R Square
  R Square R Square Adjusted
LTY 0.315 0.312
SAT 0.730 0.725

The r square value of satisfaction is 0.730 which shows 73% of the variance being explained by the independent variables and r square value of Loyalty is 0.315 which shows 31.5% of the variance is explained by the independent variables in Table 3.

Table 3 Construct Reliability
  Cronbach’s Alpha rho_A Composite Reliability Average Variance Extracted (AVE)
Store Service 0.748 0.730 0.829 0.496
Pricing 0.955 0.957 0.971 0.918
Perceived Quality 0.585 0.601 0.797 0.584
Local Presence 0.738 1.059 0.788 0.559
Satisfaction 0.668 0.782 0.834 0.649
Loyalty 0.630 0.656 0.773 0.415

Chronbach’s alpha value of 0.5 and above is good. Rho A of 0.7 and above is good. Composite reliability of 0.7 and above is good. AVE of 0.5 and above is good. Overall it is seen that the constructs used are reliable in Table 4.

Table 4 Discriminant Validity, Fornell-Larcker Criterion
  Local Presence Loyalty Perceived Quality Pricing Satisfaction Store Service
Local Presence 0.748          
Loyalty 0.457 0.644        
Perceived Quality 0.330 0.628 0.764      
Pricing 0.294 0.711 0.417 0.958    
Satisfaction 0.826 0.561 0.350 0.376 0.806  
Store Service 0.488 0.640 0.536 0.388 0.325 0.705

The diagonals are the square root of the AVE. Off-diagonals are the correlations of the latent constructs. The diagonals indicate the highest of any column or row. This complies with the discriminant validity requirements in Table 5.

Table 5 Path Coefficients
  Original Sample (O) Sample Mean (M) Standard Deviation (STDEV) T Statistics (|O/STDEV|) P Values Results
Store Service -> Satisfaction -0.212 -0.214 0.092 2.313 0.021 Accept H1
Store Service -> Loyalty -0.119 -0.119 0.048 2.495 0.013 Accept H2
Pricing -> Satisfaction 0.162 0.155 0.048 3.395 0.001 Accept H3
Pricing -> Loyalty 0.091 .089 0.032 2.807 0.005 Accept H4
Perceived Quality -> Satisfaction 0.118 0.121 0.059 2.004 0.045 Accept H5
Perceived Quality -> Loyalty 0.066 0.069 0.034 1.936 0.053 Reject H6
Local Presence -> Satisfaction 0.843 0.855 0.060 13.959 0.000 Accept H7
Local Presence -> Loyalty 0.473 0.482 0.041 11.464 0.000 Accept H8
Satisfaction -> Loyalty 0.561 0.567 0.062 9.029 0.000 Accept H9

From the path analysis of the model in Table 5, it is seen that store service has a positive influence on customer satisfaction and loyalty. A customer goes to a retail store where he feels comfortable to shop. A good store service adds to his/her satisfaction and makes him a loyal customer.

Pricing has a positive influence on customer satisfaction and loyalty. Price comparisons are common wherever a customer goes shopping. A reasonable price for good quality is desirable to the customer. This makes the customer happy and satisfied. It is seen during the pandemic that consumers are becoming more price sensitive due to reduced income generation and uncertainty. Yet, pricing reasonably and making the products available in time will help the retailer.

Perceived quality has a positive influence on customer satisfaction. A customer always compares the product or service after the consumption to check the quality. If the customer experiences a superior quality it gives him satisfaction. But it is also seen that perceived quality do not directly influence loyalty. This is the case which we see during the pandemic. Due to unavailability of the desired product, the customer has no other option but to select a substitute product. This is where the consumer may not consider the superior product quality but the availability of a substitute. The retailer can help the customer to switch to a local product which matches the quality requirement.

Local presence has a positive influence on customer satisfaction and loyalty. The pandemic has seen the growth of the local products. The local retailers and producers have kept their shop open even during the pandemic to serve the local population. The sincerity of the local producers to meet the requirement of the local population during troubled times is helping popularize the brand. Consumers have understood the significance of a local brand during the pandemic.

Customer satisfaction has a positive influence on loyalty. It goes without saying that a satisfied customer will come back to the outlet again for shopping. The customer will also recommend others to buy from the outlet. This is the reason why retailers have to take more care on thinking about consumer requirements than focusing only on profitability in Table 6.

Table 6 Indirect Effects
  Original Sample (O) Sample Mean (M) Standard Deviation (STDEV) T Statistics (|O/STDEV|) P Values
Local Presence -> Loyalty .473 .482 .041 11.464 .000
Local Presence -> Satisfaction          
Perceived Quality -> Loyalty .066 .069 .034 1.936 .053
Perceived Quality -> Satisfaction          
Pricing -> Loyalty .091 .089 .032 2.807 .005
Pricing -> Satisfaction          
Satisfaction -> Loyalty          
Store Service -> Loyalty -.119 -.119 .048 2.495 .013
Store Service -> Satisfaction          

The three indirect effects: Store Service -> Loyalty, Pricing -> Loyalty, Local Presence -> Loyalty are significant and has full mediation. Perceived Quality -> Loyalty is not significant and has a partial mediation.

Conclusion

Store service, pricing, perceived quality and local presence have a positive influence on customer satisfaction. Customer satisfaction is dependent on how the retailer services his customers well. The experience the customer gets while availing the retailer’s services creates a memorable feeling for the customer. This helps in creating loyal customers. The pandemic has made it difficult for retailers to serve their customers better. Generic strategies don’t seem to work. A well-designed retail strategy to suit the consumer during the pandemic will help in keeping their customers together.

Limitations

The sample size is low, a bigger sample size would help in getting a better model fit. The responses were not any location specific. A sample size of other age groups would have provided a wider understanding.

Business Implications

Customer loyalty is crucial for sustaining any business. Understanding the existing business environment and consumer behavior will help design better marketing strategies. The world is going through a period of uncertainty. Understanding the consumer requirements and helping the consumer in the tough times will help a brand to stand out in the long run. Compliance of the business houses with the Government norms for the safety of the citizens will help in building consumer confidence.

References

  1. Aksoy, L., Buoye, A., Aksoy, P., Larivière, B., & Keiningham, T.L. (2013). A cross-national investigation of the satisfaction and loyalty linkage for mobile telecommunications services across eight countries. Journal of Interactive Marketing, 27(1), 74-82.
  2. Anaza, N.A., & Zhao, J. (2013). Encounter-based antecedents of e-customer citizenship behaviors. Journal of Services Marketing.
  3. Anderson, E.W., & Sullivan, M.W. (1993). The antecedents and consequences of customer satisfaction for firms. Marketing Science, 12, 125 – 143.
  4. Anderson, E.W., Fornell, C., & Lehmann, D.R. (1994). Customer satisfaction, market share, and profitability: Findings from Sweden. Journal of Marketing, 58, 53-66.
  5. Anderson, J.C., & Narus, J.A. (1990). A model of distributor firm and manufacturer firm working partnerships. Journal of Marketing, 54, 42 – 58.
  6. Anderson, R.E., & Srinivasan, S.S. (2003). E‐satisfaction and e‐loyalty: A contingency framework. Psychology & Marketing, 20(2), 123-138.
  7. Anselmsson, J., Johansson, U., & Persson, N. (2007). Understanding price premium for grocery products: a conceptual model of customer‐based brand equity. Journal of Product & Brand Management, Vol. 16 No. 6, pp. 401-414.
  8. Baker, J., Parasuraman, A., Grewal, D. & Voss, G.B. (2002). The influence of multiple store environment cues on perceived merchandise value and patronage intentions. Journal of Marketing, Vol. 66 No. 2, pp. 120-141.
  9. Bayus, B.L. (1992). Brand loyalty and marketing strategy: An application to home appliances. Marketing Science, 11, 21 – 38.
  10. Bearden, W.O., & Teel, J.E. (1983). Selected determinants of consumer satisfaction and complaint reports. Journal of Marketing Research, 20, 21-28.
  11. Bertacchini, F., Bilotta, E. & Pantano, P. (2017). Shopping with a robotic companion. Computers in Human Behavior, Vol. 77, pp. 382-395.
  12. Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 351-370.
  13. Bloemer, J. (2002). Store satisfaction and store loyalty explained by customer and store-related factors. Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behaviour, Vol. 15 No. 1, pp. 68-80.
  14. Bojanic, D.C. (1996). Consumer perceptions of price, value and satisfaction in the hotel industry: An exploratory study. Journal of Hospitality & Leisure Marketing, 4(1), 5-22.
  15. Bolton, L.E., Warlop, L. & Alba, J.W. (2003). Consumer perceptions of price (un)fairness. Journal of Consumer Research, Vol. 29, pp. 474-91.
  16. Bowen, J.T., Chen McCain, S.L. (2015). Transitioning loyalty programs: a commentary on the relationship between customer loyalty and customer satisfaction. International Journal of Contemporary Hospitality Management, 27 (3), 415–430.
  17. Brown, J.D. (2001). Segmentation correlates for small grocery chain preference. Journal of Food Products Marketing, Vol. 6 No. 4, pp. 53-62.
  18. Calvo Porral, C., & Levy Mangin, J.P. (2016). Specialty food retailing. British Food Journal.
  19. Campbell, M.C.  (1999a). Why   did   you   do   that? The important role of inferred motive in perceptions of price fairness. Journal of Product & Brand Management, Vol. 8 No. 2, pp. 145-52.
  20. Campbell, M.C. (1999b). Perceptions of price unfairness: antecedents   and   consequences. Journal of Marketing, Vol. 36, May, pp. 187-99.
  21. Campo, S., Yagüe, M.J. (2008). Effects of price on the tourist satisfaction. Tourism Economics 14(3), 657–661.
  22. Cano, M.B., Perry, P., Ashman, R. & Waite, K. (2017). The influence of image interactivity upon user engagement when using mobile touch screens. Computers in Human Behavior, Vol. 77, pp. 406-412.
  23. Chen, C.M., Yang, H.W., Li, E.Y., & Liu, C.C. (2015). How does hotel pricing influence guest satisfaction by the moderating influence of room occupancy? International Journal of Hospitality Management, 49, 136-138.
  24. Chen, S.C. & Quester, P.G. (2006). Modeling store loyalty: perceived value in market orientation practice. Journal of Service Marketing, Vol. 20 No. 3, pp. 188-198.
  25. Churchill, G., & Suprenant, C. (1982). An investigation into the determinants of customer satisfaction. Journal of Marketing Research, 19, 491 – 504.
  26. Cronin, J. Jr, Brady, M.K. & Hult, G.T.M. (2000). Assessing the effects of quality, value, and   customer satisfaction on consumer behavioral intentions in service environments. Journal of Retailing, Vol. 76 No.2, pp. 193-218.
  27. Dacko, S.G. (2017). Enabling smart retail settings via mobile augmented reality shopping apps. Technological Forecasting and Social Change, Vol. 124, pp. 243-256.
  28. De Matos, C.A., & Rossi, C.A.V. (2008). Word-of-mouth communications in marketing: a meta-analytic review of the antecedents and moderators. Journal of the Academy of marketing science, 36(4), 578-596.
  29. Demirkan, H. & Spohrer, J. (2014). Developing a framework to improve virtual shopping in digital malls with intelligent self-service systems. Journal of Retailing and Consumer Services, Vol. 21 No. 5, pp. 860-868.
  30. Estalami, H., Maxwell, S., Martín‐Consuegra, D., Molina, A., & Esteban, Á. (2007). An integrated model of price, satisfaction and loyalty: an empirical analysis in the service sector. Journal of Product & Brand Management.
  31. Fornell, C. (1992).  A national customer satisfaction barometer: Swedish experience. Journal of Marketing, Vol. 56, January, pp. 6-21.
  32. Ganesan, S. (1994). Determinants of long-term orientation in buyer seller relationships. Journal of Marketing, 58, 1-19.
  33. Gelderman, C.J., Paul, W.T., & Van Diemen, R. (2011). Choosing self-service technologies or interpersonal services-The impact of situational factors and technology-related attitudes. Journal of Retailing and Consumer Services, 18(5), 414-421.
  34. Goel, S., Hawi, S., Goel, G., Thakur, V. K., Agrawal, A., Hoskins, C., ... & Barber, A. H. (2020). Resilient and agile engineering solutions to address societal challenges such as coronavirus pandemic. Materials Today Chemistry, 17, 100300.
  35. Gogoi, B. J, & Dutta, H.K. (2020). Increasing Store Loyalty and Patronage: What Matters? International Journal of Management, 11(4).
  36. Gogoi, B.J. (2020). Changing Consumer Preferences: Factors Influencing Choice of Fast Food Outlet. Academy of Marketing Studies Journal, 24(1), 1-17.
  37. Gogoi, B.J. (2021). Influence of Service Quality and Trust in spreading positive WOM and increasing Loyalty of a Tourist Location. Academy of Marketing Studies Journal, 25(2), 1-14.
  38. Gomez, M.I., McLaughlin, E.W. & Wittink, D.R. (2004). Customer satisfaction and retail sales performance: an empirical investigation. Journal of Retailing, Vol. 80 No. 4, pp. 265-278.
  39. Grewal, D., Baker, J., Lévy, M. & Voss, G.B. (2003). The effects of wait expectations and store atmosphere evaluations on patronage intentions in service-intensive retail stores. Journal of Retailing, Vol. 79 No. 4, pp. 259-268.
  40. Hilken, T., de Ruyter, K., Chylinski, M., Mahr, D. & Keeling, D.I. (2017). Augmenting the eye of the beholder: exploring the strategic potential of augmented reality to enhance online service experiences. Journal of the Academy of Marketing Science, Vol. 45 No. 6, pp. 884-905
  41. Holbrook, M.B. & Corfman, K.P. (1985). Quality and value in the consumption experience: phaedrus rides again”, in Jacoby, J. & Olson, J. (Eds), Perceived Quality, Lexington Books, Lexington, MA, pp. 31-57.
  42. Homburg, C., & Giering, A. (2001). Personal characteristics as moderators of the relationship between customer satisfaction and loyalty-an empirical analysis. Psychology & Marketing, 18(1), 43-66.
  43. Huang, M.H. & Rust, R.T. (2018). Artificial intelligence in service. Journal of Service Research, Vol. 21 No. 2, pp. 155-172.
  44. Huber, F., Herrmann, A. & Wricke, M. (2001). Customer satisfaction as an antecedent of price acceptance: results of an empirical study. Journal of Product & Brand Management, Vol. 10 No. 3, pp. 160-9.
  45. Huddleston, P., Whipple, J., Mattick, R.N. & Lee, S.J. (2009). Customer satisfaction in food retailing: comparing specialty and conventional grocery stores. International Journal of Retail & Distribution Management, Vol. 37 No. 1, pp. 63-80.
  46. Immonen, I., Sintonen, S. & Koivuniemi, J. (2018). The value of human interaction in service channels. Computers in Human Behavior, Vol. 78, pp. 316-325
  47. India.com (2021):https://www.india.com/health/new-covid-19-variant-has-airborne-transmission-social-distancing-not-enough-to-cut-the-risk-indoors-4636626/
  48. Inman, J.J. & Nikolova, H. (2017). Shopper-facing retail technology: a retailer adoption decision framework incorporating shopper attitudes and privacy concerns. Journal of Retailing, Vol. 93 No. 1, pp. 7-28.
  49. Jang, S. & Namkung, Y. (2009). Perceived quality, emotions and behavioural intentions: application of an extended Mehrabian-Russell model to restaurants. Journal of Business Research, Vol. 62 No. 2, pp. 451-460.
  50. Juan, M.C., & Joele, D. (2011). A comparative study of the sense of presence and anxiety in an invisible marker versus a marker augmented reality system for the treatment of phobia towards small animals. International Journal of Human-Computer Studies, 69(6), 440-453.
  51. Kim, T.T., Kim, W.G., & Kim, H.B. (2009). The effects of perceived justice on recovery satisfaction, trust, word-of-mouth, and revisit intention in upscale hotels. Tourism management, 30(1), 51-62.
  52. Kimes, S.E. (1994). Perceived fairness of yield management. The Cornell Hotel and Restaurant Administration Quarterly, Vol. 35, February, pp. 22-9.
  53. Klein, L.R. (2003). Creating virtual product experiences: The role of telepresence. Journal of interactive Marketing, 17(1), 41-55.
  54. Lee, H.S. (2013). Major moderators influencing the relationships of service quality, customer satisfaction and customer loyalty. Asian Social Sciience, 9 (2), 1.
  55. Lemon, K.N. & Verhoef, P.C. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing, Vol. 80, pp. 69-96
  56. Lim, E.A.C., Lee, Y.H. & Foo, M.-D. (2017). Frontline employees’ nonverbal cues in service encounters: a double-edged sword. Journal of the Academy of Marketing Science, Vol. 45, pp. 657-675.
  57. Mordani Sneha (2001), India may see 3rd Covid wave, no point of night curfews, weekend lockdowns, India Today: https://www.indiatoday.in/coronavirus-outbreak/story/india-may-see-3rd-covid-wave-no-point-of-night-curfews-weekend-lockdowns-aiims-randeep-guleria-1798689-2021-05-04
  58. Oliver, R.L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17, 460 – 469.
  59. Oliver, R.L. (1997). Satisfaction-A behavioral perspective on the consumer. New York: McGraw-Hill.
  60. Oliver, R.L., & DeSarbo, W. S. (198). Response determinants in satisfaction judgements. Journal of Consumer Research, 14, 495-507.
  61. Orel, F.D., & Kara, A. (2014). Supermarket self-checkout service quality, customer satisfaction, and loyalty: Empirical evidence from an emerging market. Journal of Retailing and Consumer services, 21(2), 118-129.
  62. Pan, Y. & Zinkhan, G.M. (2006). Determinants of retail patronage: a meta-analytical perspective. Journal of Retailing, Vol. 82 No. 3, pp. 229-243.
  63. Pantano, E. (2016). Engaging consumer through storefront: evidences from integrating interactive technologies. Journal of Retailing and Consumer Services, Vol. 28, pp. 149-154.
  64. Pantano, E. & Gandini, A. (2017). Exploring the forms of sociality mediated by innovative technologies in retail settings. Computers in Human Behavior, Vol. 77, pp. 367-373.
  65. Papagiannidis, S., Pantano, E., See-To, E., Dennis, C. & Bourlakis, M. (2017). To immerse or not? Experimenting with two virtual retail environments. Information Technology & People, Vol. 34 No. 1, pp. 163-188.
  66. Parasuraman, A., Berry, L.L., Zeithaml, V. A., (1991). Understanding customer expectation of service. Sloan Management Review, 32(3),39–48.
  67. Peck, J., & Childers, T.L. (2006). If I touch it I have to have it: Individual and environmental influences on impulse purchasing. Journal of business research, 59(6), 765-769.
  68. Razalan, D. M., Bickle, M. C., Park, J., & Brosdahl, D. (2017). Local retailers’ perspectives on social responsibility. International Journal of Retail & Distribution Management.
  69. Reimann, Martin, Ulrich F. Lunemann, and Richard B. Chase (2008). Uncertainty Avoidance as a Moderator of the Relationship between Perceived Service Quality and Customer Satisfaction. Journal of Service Research,11(1), 63–73.
  70. Reynolds, K.E. & Beatty, S. (1999). Customer benefits and company consequences of customer-salesperson relationships in retailing. Journal of Retailing, Vol. 75 No. 1, pp. 11-32.
  71. Rezaei, S. & Valaei, N. (2017). Branding in a multichannel retail environment: online stores vs appstores and the effect of product type. Information Technology & People, Vol. 30 No. 4, pp. 853-886.
  72. Shankar, V., Smith, A.K., & Rangaswamy, A. (2003). Customer satisfaction and loyalty in online and offline environments. International Journal of Research in Marketing, 20(2), 153-175.
  73. Steenkamp, J.B. (1990). Conceptual model of the quality perception process. Journal of Business Research, Vol. 21 No. 4, pp. 309-333
  74. Stiglitz, J.E. (1987). The causes and consequences of the dependence of quality on price. Journal of Economic Literature, 25(1), 1-48.
  75. Swan, J.E., & Oliver, R.L. (1989). Postpurchase communications by consumers. Journal of retailing, 65(4), 516.
  76. Thakur, R. (2019). The moderating role of customer engagement experiences in customer satisfaction-loyalty relationship. European Journal of Marketing.
  77. Toufaily, E., Ricard, L., & Perrien, J. (2013). Customer loyalty to a commercial website: Descriptive meta-analysis of the empirical literature and proposal of an integrative model. Journal of Business Research, 66(9), 1436-1447.
  78. Van Kerrebroeck, H., Brengman, M. & Willems, K. (2017). Escaping the crowd: an experimental study on the impact of a virtual reality experience in a shopping mall. Computers in Human Behavior, Vol. 77, pp. 437-450.
  79. Vannucci, V., & Pantano, E. (2019). Digital or human touchpoints? Insights from consumer-facing in-store services. Information Technology & People.
  80. Verhagen, T., Vonkeman, C., Feldberg, F., & Verhagen, P. (2014). Present it like it is here: Creating local presence to improve online product experiences. Computers in Human Behavior, 39, 270-280.
  81. Vesel, P., & Zabkar, V. (2009). Managing customer loyalty through the mediating role of satisfaction in the DIY retail loyalty program. Journal of Retailing and Consumer Services, 16(5), 396-406.
  82. Vonkeman, C., Verhagen, T., & Van Dolen, W. (2017). Role of local presence in online impulse buying. Information & Management, 54(8), 1038-1048.
  83. Willems, K., Smolders, A., Brengman, M., Luyten, K. and Schoning, J. (2017). The path-to-purchase is paved with digital opportunities: an inventory of shopper-oriented retail technologies. Technological Forecasting and Social Change, Vol. 124, pp. 228-242.
  84. Wilton, P. C., & Nicosia Franco, M. (1986). Emerging paradigms for the studyof consumer satisfaction. European Research, 14, 4 –11.
  85. Xia, L., Monroe, K.B.  & Cox, J.L.  (2004). The price is unfair! A conceptual framework of price   fairness perceptions. Journal of Marketing, Vol. 68, October, pp. 1-15.
  86. Zeithaml, V.A.  & Bitner, M.J.  (1996), Service Marketing, McGraw-Hill, New York, NY.
  87. Zeithaml, V.A. (1988). Consumer perceptions price, quality, and value: a means-end model and synthesis of evidence. Journal of Marketing, Vol. 52, July, pp. 2-22.
  88. Zeithaml., V.A. (1988). Consumer perception of price, quality and value: a means-end model and synthesis of evidence. Journal of Marketing, Vol. 52 No. 3, pp. 2-22.
  89. Zhao, J. & Huddleston, P. (2012). Antecedents of specialty food store loyalty. The International Review of Retail, Distribution & Consumer Research, Vol. 22 No. 2, pp. 171-187.

Appendix

Variable Codes Statements
Store Service Store Service (STSER)
STSER1 Store staffing levels affect the level of satisfaction
STSER2 Store service policies and practices affect the satisfaction
STSER3 Store transaction speed and waiting time at the check-outs affect the satisfaction
STSER4 Managing Covid19 guidelines for safety is mandatory for all stores
Pricing Pricing (PRICE)
PRIC1 I believe the retailer should charge a fair price for the products
PRIC2 Fair pricing policy of the store is important to me
PRIC3 The store products should be reasonably priced
Perceived Quality Perceived Quality (PERQL)
PERQL1 The products in the store should be good in texture and appearance
PERQL2 The product should be of good quality and appealing
PERQL3 Product freshness and newness matters a lot
PERQL4 Products available in the store should be safe and hygienic
Local Presence Local Presence (LOCPR)
LOCPR1 I prefer to go for local brands
LOCPR2 I feel comfortable to shop in stores having local brands
LOCPR3 I think local brands should be given more preference
Customer Satisfaction Customer Satisfaction (SAT)
SAT1 Generally, I am very happy with this store
SAT2 I am extremely pleased with the quality of service provided by this store
SAT3 This store meets my expectations
SAT4 I am extremely pleased with the quality of service provided by the self-checkout system
Loyalty Loyalty (LTY)
LTY1 I would shop in this store again
LTY2 I would recommend this store to any of my friends
LTY3 If I need to shop again, I would come to this store
LTY4 I would speak positively about this store to others
LTY5 This store is my preferred choice
Get the App