Delighting customers: Evaluating service quality and customer satisfaction of self-checkout users in sports retail
-
DOIhttp://dx.doi.org/10.21511/im.20(3).2024.08
-
Article InfoVolume 20 2024, Issue #3, pp. 97-109
- 391 Views
-
189 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
Digitalization has transformed dynamics across all fields, and technology has completely changed the customer experience. One prominently utilized technology in offline retail is self-checkout services. The present study intends to investigate the attributes that influence people to use self-checkout services and assess their impact on service quality and customer satisfaction. Drawn from Dabholkar’s attribute-based model, the study employs a positivist approach to test the conceptual framework. After the preliminary survey of 330 respondents, it identified ninety-nine consumers who had used the self-service check-out facility. The data collected were analyzed using a multi-variate technique – Partial Least Squares Structural Equation Modeling (PLS-SEM) – owing to the small sample size requirement. All independent variables taken for the study positively affect the service quality. Customer perception of control, ease of use, reliability, enjoyment, speed, adventure, and openness positively affect service quality. It was noted that ease of use, with a variance value of 2.451, and openness to experience, with a variance value of 2.437, show the importance of determining independent variables with service quality. The study findings reported that service quality is primarily influenced by ease of use, enjoyment, and openness to experience. It underlines that some retail customers will likely feel frustrated rather than enjoy the self-service technology, perceiving it as less reliable. The study suggests incorporating openness to experience and adventure shopping in retail outlets that can enhance consumer satisfaction and loyalty. Adopting an immersive and interactive shopping experience will ultimately improve the perception of service quality and customer happiness.
- Keywords
-
JEL Classification (Paper profile tab)M31, L81, O33
-
References45
-
Tables8
-
Figures2
-
- Figure 1. Conceptual model
- Figure 2. Structural model Assessment-Output derived from Smart PLS-4 software
-
- Table 1. Respondents’ profile
- Table 2. Assessment of measurement model
- Table 3. Heterotrait-Monotrait (HTMT)
- Table 4. Collinearity statistics
- Table 5. R2 and Q2 values
- Table 6. Model fit
- Table 7. Path analysis
- Table A1. Operationalization of the constructs
-
- Alexander, B., & Kent, A. (2021). Tracking technology diffusion in-store: a fashion retail perspective. International Journal of Retail & Distribution Management, 49(10), 1369-1390.
- Arnold, M., Fraser, B., & Arcodia, C. (2024). The Role of Self-Service Technologies in the New Normal of Hospitality Service Encounters. In Tourist Behaviour and the New Normal, Volume I: Implications for Tourism Resilience (pp. 201-226). Cham: Springer Nature Switzerland.
- Arnold, M. J., & Reynolds, K. E. (2003). Hedonic shopping motivations. Journal of Retailing, 79(2), 77-95.
- Basu, R., Paul, J., & Singh, K. (2022). Visual merchandising and store atmospherics: An integrated review and future research directions. Journal of Business Research, 151, 397-408.
- Bateson, J. E. B. (1987). Perceived control as a crucial dimension of the service experience: An experimental study. In Schwartz, T. A., & Iacobucci, D. (Eds.), Handbook of Services Marketing and Management. SAGE Publications, Inc.
- Bonfanti, A., Vigolo, V., Yfantidou, G., & Gutuleac, R. (2023). Customer experience management strategies in upscale restaurants: Lessons from the Covid-19 pandemic. International Journal of Hospitality Management, 109.
- Bulmer, S., Elms, J., & Moore, S. (2018). Exploring the adoption of self-service checkouts and the associated social obligations of shopping practices. Journal of Retailing and Consumer Services, 42, 107-116.
- Chen, C. Y. (2018). How customer participation influences service failure attribution: The moderating effect of self-efficacy. Journal of Service Theory and Practice, 28(3).
- Collier, J. E., & Kimes, S. E. (2013). Only if it is convenient: Understanding how convenience influences self-service technology evaluation. Journal of Service Research, 16(1), 39-51.
- Cui, Y., van Esch, P., & Jain, S. P. (2022). Just walk out: the effect of AI-enabled checkouts. European Journal of Marketing, 56(6), 1650-1683.
- Dabholkar, P. A. (1996). Consumer evaluations of new technology-based self-service options: An investigation of alternative service quality models. International Journal of Research in Marketing, 13(1), 29-51.
- Dabholkar, P. A., & Bagozzi, R. P. (2002). An Attitudinal Model of Technology-Based Self-Service: Moderating Effects of Consumer Traits and Situational Factors. Journal of the Academy of Marketing Science, 30(3), 184-201.
- Dabholkar, P. A., Thorpe, D. I., & Rentz, J. O. (1996). A measure of service quality for retail stores: scale development and validation. Journal of the Academy of Marketing Science, 24(1), 3-16.
- Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340.
- Dean, D. H. (2008). Shopper age and the use of self-service technologies. Managing Service Quality: An International Journal, 18(3), 225-238.
- Duarte, P., Silva, S. C., Linardi, M. A., & Novais, B. (2022). Understanding the implementation of retail self-service check-out technologies using necessary condition analysis. International Journal of Retail & Distribution Management, 50(13), 140-163.
- Elms, J., De Kervenoael, R., & Hallsworth, A. (2016). Internet or store? An ethnographic study of consumers’ Internet and store-based grocery shopping practices. Journal of Retailing and Consumer Services, 32, 234-243.
- Fernandes, T., & Pedroso, R. (2017). The effect of self-checkout quality on customer satisfaction and repatronage in a retail context. Service Business, 11, 69-92.
- Grand View Research. (2022).Self-checkout systems market size, share & trends analysis report by component (systems, services), by type (cash, cashless based), by application, by region, and segment forecasts, 2023-2030 Report ID (2022) GVR-4-68038-411-6.
- Grewal, D., Benoit, S., Noble, S. M., Guha, A., Ahlbom, C. P., & Nordfält, J. (2023). Leveraging In-Store Technology and AI: Increasing Customer and Employee Efficiency and Enhancing their Experiences. Journal of Retailing, 99(4), 487-504.
- Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed, a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139-152.
- Halvorsrud, R., Kvale, K., & Følstad, A. (2016). Improving service quality through customer journey analysis. Journal of Service Theory and Practice, 26(6), 840-867.
- Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135.
- Hong, E., & Ahn, J. (2023). The role of autonomy, competence, and relatedness in motivation to use self-service technology (SST) among customers with difficulties in SST. Journal of Hospitality and Tourism Technology, 14(4), 630-642.
- Isharyani, M. E., Sopha, B. M., Wibisono, M. A., & Tjahjono, B. (2024). Retail technology adaptation in traditional retailers: A technology-to-performance chain perspective. Journal of Open Innovation: Technology, Market, and Complexity, 10(1).
- Jeon, H. M., Sung, H. J., & Kim, H. Y. (2020). Customer’s acceptance intention of self-service technology of restaurant industry: Expanding UTAUT with perceived risk and innovativeness. Service Business, 14, 533-551.
- Lee, H. J., Cho H. J., Xu W., & Fairhurst A. (2010). The Influence of Consumer Traits and Demographics on Intention to Use Retail Self-Service Checkouts. Marketing Intelligence & Planning, 28(1), 46-58.
- Lee, H.-J. (2017). Personality determinants of need for interaction with a retail employee and its impact on self-service technology (SST) usage intention. Journal of Research in Interactive Marketing, 11(3), 214-231.
- Leng, H. K., & Wee, K. N. L. (2017). An examination of users and non-users of self-checkout counters. The International Review of Retail, Distribution and Consumer Research, 27(1), 94-108.
- Liang, Y., Lee, S. H., & Workman, J. E. (2022). How do consumers perceive mobile self-checkout in fashion retail stores? International journal of retail & distribution management, 50(6), 677-691.
- Makgosa, R., & Sangodoyin, O. (2018). Retail market segmentation: the use of consumer decision-making styles, overall satisfaction, and demographics. The International Review of Retail, Distribution and Consumer Research, 28(1), 64-91.
- Mamakou, X. J., Zaharias, P., & Milesi, M. (2024). Measuring customer satisfaction in electronic commerce: The impact of e-service quality and user experience. International Journal of Quality & Reliability Management, 41(3), 915-943.
- Moslehpour, M., Pham, V. K., Wong, W. K., & Bilgiçli, I. (2018). E-purchase intention of Taiwanese consumers: sustainable mediation of perceived usefulness and perceived ease of use. Sustainability, 10(1), 234-251.
- Nusrat, F., & Huang, Y. (2024). Feeling rewarded and entitled to be served: Understanding the influence of self-versus regular checkout on customer loyalty. Journal of Business Research, 170.
- Penttinen, E., & Rinta-Kahila, T. (2021). Four Flavours of Customers: A dual-system perspective on self-service technology use. Australasian Journal of Information Systems, 25, 1-27.
- Rinta-Kahila, T., Penttinen, E., Kumar, A., & Janakiraman, R. (2021). Customer reactions to self-checkout discontinuance. Journal of Retailing and Consumer Services, 61.
- Roy, R., & Ramakrishnan, S. (2024). Embracing the Future of Retail with Virtual Try-On Technology. In Data-Driven Intelligent Business Sustainability (pp. 344-359). IGI Global.
- Sari, Y. K., & Gani, A. N. (2024). The Effect of In-store Logistics, Store Image, Sales Promotion, and Service Quality on Customer Satisfaction. Research of Business and Management, 2(1), 15-28.
- Sivadas, E., & Baker-Prewitt, J. L. (2000). An examination of the relationship between service quality, customer satisfaction, and store loyalty. International Journal of Retail & Distribution Management, 28(2), 73-82.
- Thomas-Francois, K., & Somogyi, S. (2023). Self-Checkout Behaviours at supermarkets: Does the technological acceptance model (TAM) predict smart grocery shopping adoption? The International Review of Retail, Distribution and Consumer Research, 33(1), 44-66.
- Triantafillidou, A., Siomkos, G., & Papafilippaki, E. (2017).The effects of retail store characteristics on in-store leisure shopping experience. International Journal of Retail and Distribution Management, 45(10), 1034-1060.
- Wong, A., & Sohal, A. (2002). Customers’ perspectives on service quality and relationship quality in retail encounters. Managing Service Quality: An International Journal, 12(6), 424-433.
- Yesitadewi, A. Z., Alqahtani, N., Tsiotsou, R. H., Rehman, U., & Ting, D. H. (2023). ESports as Playful Consumption Experiences: Examining the Antecedents and Consequences of Game Engagement. Telematics and Informatics, 77.
- Yesitadewi, V. I., & Widodo, T. (2024). The Influence of Service Quality, Perceived Value, and Trust on Customer Loyalty via Customer Satisfaction in Deliveree Indonesia. Quality-Access to Success, 25(198), 418-424.
- Yoshida, M., & James, J. D. (2010). Customer satisfaction with game and service experiences: antecedents and consequences. Journal of Sport Management, 24(3), 338-361.