Customer intention towards self-service checkout at Watson

Nurulizwa Abdul Rashid; Ameer Farhan Mohd Arzaman; Muhamad Amirul Razali; Anisah Jospat; Noor Aisyah Abdul Aziz; Indriana Damaianti

doi:10.31893/multiscience.2024129

Keywords:

self-checkout technology adoption

Covid-19 pandemic

UTAUT2

Abstract

This research focuses on customers intentions to use the self-checkout technology at Watson during the Covid-19 endemic using UTAUT2 model. The main objective is to identify the factors that affect the behavioral intention to use the self-checkout technology from a consumer perspective. This study investigated the influencing factors of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, and habit towards customers' intention to use the self-checkout systems. The data for this study were collected using a questionnaire shared among 200 respondents who are Watson customers were selected by stratified random sampling technique through online. The data were analyzed using IBM- SPSS version 26 to test the hypotheses. The findings indicate that customers intention is significantly and positively influenced by performance expectancy, effort expectancy, facilitating condition, hedonic motivation and habit behaviour. A number of implications for theory and practice are derived based on the findings.
References
1. Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99-110.
2. Alfany, Z., Saufi, A., & Mulyono, L. E. H. (2019). The impact of social influence, self-efficacy, perceived enjoyment, and individual mobility on attitude toward use and intention to use mobile payment of OVO. Global Journal of Management and Business Research, 19(7), 1-8.
3. Alpert, H. K. (2008). The self-service ‘buy-and-pay’market: kiosk, vending and foodservice trends in the US. Accessed on June 6, 2023.
4. Arzaman, A. F. M., Salleh, H. S., Mat, N. H. N., & Talaat, W. I. A. W. (2021). Potentials of associated traditional knowledge on marine resources for economic and general well-being among coastal communities in Terengganu, Malaysia. International Journal of Advanced and Applied Sciences, 8(12), 93-101
5. Azizi, S. M., Roozbahani, N., & Khatony, A. (2020). Factors affecting the acceptance of blended learning in medical education: application of UTAUT2 model. BMC medical education, 20, 1-9.
6. Bitner, M. J., Ostrom, A. L., & Meuter, M. L. (2002). Implementing successful self-service technologies. Academy of management perspectives, 16(4), 96-108.
7. Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS quarterly, 399-426.
8. Cabrera-Sánchez, J. P., Villarejo-Ramos, Á. F., Liébana-Cabanillas, F., & Shaikh, A. A. (2021). Identifying relevant segments of AI applications adopters–Expanding the UTAUT2’s variables. Telematics and Informatics, 58, 101529.
9. Cebeci, U., Ertug, A., & Turkcan, H. (2020). Exploring the determinants of intention to use self-checkout systems in super market chain and its application. Management Science Letters, 10(5), 1027-1036.
10. Chan, F. K., Thong, J. Y., Venkatesh, V., Brown, S. A., Hu, P. J., & Tam, K. Y. (2010). Modeling citizen satisfaction with mandatory adoption of an e-government technology. Journal of the association for information systems, 11(10), 519-549.
11. Chang, A. (2012). UTAUT and UTAUT 2: A review and agenda for future research. The Winners, 13(2), 10-114.
12. Chang, C. M., Liu, L. W., Huang, H. C., & Hsieh, H. H. (2019). Factors influencing online hotel booking: Extending UTAUT2 with age, gender, and experience as moderators. Information, 10(9), 281.
13. Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in psychology, 10, 1652.
14. Chatterjee, S., & Kar, A. K. (2020). Why do small and medium enterprises use social media marketing and what is the impact: Empirical insights from India. International Journal of Information Management, 53, 102103.
15. Chayomchai, A., Phonsiri, W., Junjit, A., Boongapim, R., & Suwannapusit, U. (2020). Factors affecting acceptance and use of online technology in Thai people during COVID-19 quarantine time. Management Science Letters, 10(13), 3009-3016.
16. Cheng, Y., Sharma, S., Sharma, P., & Kulathunga, K. M. M. C. B. (2020). Role of personalization in continuous use intention of Mobile news apps in India: Extending the UTAUT2 model. Information, 11(1), 33.
17. Damaianti, I., Farradia, Y., Shafi, S., Arzaman, A. F. M., & Salleh, H. S. (2023). Sustainable Practices in West Java Hotels: Perspectives from the Hotel Association, Hotel Management, and Visitors. International Journal of Sustainable Development & Planning, 18(11), 3575-3584
18. Erjavec, J., & Manfreda, A. (2022). Online shopping adoption during COVID-19 and social isolation: Extending the UTAUT model with herd behavior. Journal of Retailing and Consumer Services, 65, 102867.
19. Fakhoury, R., & Aubert, B. (2017). The impact of initial learning experience on digital services usage diffusion: A field study of e-services in Lebanon. International Journal of Information Management, 37(4), 284-296.
20. Jalil N. A., & Koay, K. Y. (2021). Consumers’ intention to use self-checkout technology in a retail context: a comparison of alternative competing models. International Journal of Business Information Systems, 1-17
21. Jambulingam, M. (2013). Behavioural intention to adopt mobile technology among tertiary students. World Applied Sciences Journal, 22(9), 1262-1271
22. Jeong, E. Y. (2019). A study on the intention to reuse mobile airline application: An application of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) model. Journal of Tourism Management Research, 23(2), 719–735
23. Kamaghe, J. S., Luhanga, E. T., & Michael, K. (2020). The challenges of adopting M-learning assistive technologies for visually impaired learners in higher learning institution in Tanzania. International Journal of Emerging Technologies in Learning, 15(1). 140-151
24. Katzan, J. R. H. (2011). Essentials of service design. Journal of Service Science, 4(2), 43–60
25. Kayali, M., & Alaaraj, S. (2020). Adoption of cloud based E-learning in developing countries: a combination a of DOI, TAM and UTAUT. International Journal of Contemporary Management and Information Technology, 1(1), 1-7
26. Korukcu, O., Ozkaya, M., Faruk, O., & Boran, M. (2021). The effect of the COVID‐19 pandemic on community mental health: A psychometric and prevalence study in Turkey. Health Social Care in the Community, 29(5), 204-e213
27. Lee, H. J., & Lyu, J. (2019). Exploring factors which motivate older consumers’ self-service technologies (SSTs) adoption. The International Review of Retail, Distribution and Consumer Research, 29(2), 218-239
28. Lee, J. M., Sim, M. Y., Kang, M. S., Kang, H. G., Jang, J. N., & Kim, D. Y. (2019b). Effects of perceived risk and consumer characteristics on the continuous use intention of technology-based self service. Journal of Consumer Studies, 30(1), 69–92
29. Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS quarterly. 705-737.
30. Marikyan, D., Papagiannidis, S., & Alamanos, E. (2021). Smart home sweet smart home: An examination of smart home acceptance. International Journal of E-Business Research, 17(2), 1-23
31. Mohd Arzaman, A. F., Salleh, H. S., Nik Mat, N. H., & Asma Wan Talaat, W. I. (2022). Traditional Knowledge of Marine Resources and Their Relations to the Coastal Community’s Economic Well-Being in Peninsular Malaysia. International Journal of Sustainable Development & Planning, 17(6), 1973-1982
32. Neslin, S. A., & Shankar, V. (2009). Key issues in multichannel customer management: current knowledge and future directions. Journal of interactive marketing, 23(1), 70-81
33. Nguyen, N. M., & Borusiak, B. (2021). Using utaut2 model to examine the determinants of omnichannel technology acceptance by consumers. LogForum. 17(2), 231-41.
34. 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
35. Katzan, Jr, H. (2011). Essentials of service design. Journal of Service Science, 4(2), 43-60.
36. Park, J. S., Ha, S., & Jeong, S. W. (2021). Consumer acceptance of self-service technologies in fashion retail stores. Journal of Fashion Marketing and Management: An International Journal, 25(2), 371-388.
37. Qi, C. (2019). Is checkout-free store a flash in the pan? Factors influencing Hong Kong people’s adoption intention of checkout-free stores. Australasian Conference on Information Systems, 108-114
38. Salleh, H. S., Mat, N. H. N., Mohamed, W. N., Arzaman, A. F. M., Samsuddin, N. S., & Ahnual, N. K. (2022). Moderating Effect of Experience on the Intention-Behavioral Relationship Towards Sustainable Food Consumption. ABAC Journal, 42(1), 142-159.
39. Sattari, A., Abdekhoda, M., & Zarea Gavgani, V. (2017). Determinant factors affecting the web–based training acceptance by health students, applying UTAUT model. Internation Journal of Emerg Technology Learning, 12(10), 112-126
40. Schomakers, E. M., Lidynia, C., Vervier, L. S., Calero, V. A., & Ziefle, M. (2022). Applying an extended UTAUT2 model to explain user acceptance of lifestyle and therapy mobile health apps: survey study. JMIR mHealth and uHealth, 10(1), e27095
41. Sekaran, U, & Bougie, R. (2013). Research Methods for Business: A Skill Building Approach (6th ed.). Wiley.
42. Siah, J. W., Fam, S. F., Prastyo, D. D., Yanto, H., & Fam, K. S. (2018). Service quality of self-checkout technology in Malaysian hypermarket: A case study in Johor. Journal of Telecommunication, Electronic and Computer Engineering, 10(2), 109-112
43. Tan, G. W. H., Ooi, K. B., Sim, J. J., & Phusavat, K. (2012). Determinants of mobile learning adoption: An empirical analysis. Journal of Computer Information Systems, 52(3), 82-91.
44. Taber, K. S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in science education, 48, 1273-1296.
45. Tao, K. C., Hsu, C. Y., Yang, J. J., Ke, M. F., & Chiang, C. H. (2023). Exploring Use Behavior of Self-Service Ordering at Restaurants with Application Unified Theory of Acceptance and Use of Technology Model. Engineering Proceedings, 38(1), 26.
46. Turner, T., & Shockley, J. (2014). Creating shopper value: Co-creation roles, in-store self-service technology use, and value differentiation. Journal of Promotion Management, 20(3), 311-327.
47. Venkatesh, V. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology 1. MIS Quarterly, 36(1), 157-178
48. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425-478
49. Wang, X., Wong, Y. D., & Yuen, K. F. (2021). Does COVID-19 promote self-service usage among modern shoppers? An exploration of pandemic-driven behavioural changes in self-collection users. International Journal of Environmental Research and Public Health, 18(16), 8574.
50. Wang, X., Wong, Y. D., & Yuen, K. F. (2021b). Rise of ‘lonely’consumers in the post-COVID-19 era: A synthesised review on psychological, commercial and social implications. International journal of environmental research and public health, 18(2), 404.
51. Wijaya, I., Rai, A., & Hariguna, T. (2019). The impact of customer experience on customer behavior intention use in social media commerce, an extended expectation confirmation model: An empirical study. Management Science Letters, 9(12), 2009-2020
52. Wu, W., Zhang, B., Li, S., & Liu, H. (2022). Exploring Factors of the Willingness to Accept AI-Assisted Learning Environments: An Empirical Investigation Based on the UTAUT Model and Perceived Risk Theory. Frontiers in Psychology, 13, 870777.

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to cite

Rashid, N. A., Arzaman, A. F. M., Razali, M. A., Jospat, A., Aziz, N. A. A., & Damaianti, I. (2024). Customer intention towards self-service checkout at Watson. Multidisciplinary Science Journal, 6(7), 2024129. https://doi.org/10.31893/multiscience.2024129

[1] Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99-110.

[2] Alfany, Z., Saufi, A., & Mulyono, L. E. H. (2019). The impact of social influence, self-efficacy, perceived enjoyment, and individual mobility on attitude toward use and intention to use mobile payment of OVO. Global Journal of Management and Business Research, 19(7), 1-8.

[3] Alpert, H. K. (2008). The self-service ‘buy-and-pay’market: kiosk, vending and foodservice trends in the US. Accessed on June 6, 2023.

[4] Arzaman, A. F. M., Salleh, H. S., Mat, N. H. N., & Talaat, W. I. A. W. (2021). Potentials of associated traditional knowledge on marine resources for economic and general well-being among coastal communities in Terengganu, Malaysia. International Journal of Advanced and Applied Sciences, 8(12), 93-101

[5] Azizi, S. M., Roozbahani, N., & Khatony, A. (2020). Factors affecting the acceptance of blended learning in medical education: application of UTAUT2 model. BMC medical education, 20, 1-9.

[6] Bitner, M. J., Ostrom, A. L., & Meuter, M. L. (2002). Implementing successful self-service technologies. Academy of management perspectives, 16(4), 96-108.

[7] Brown, S. A., & Venkatesh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS quarterly, 399-426.

[8] Cabrera-Sánchez, J. P., Villarejo-Ramos, Á. F., Liébana-Cabanillas, F., & Shaikh, A. A. (2021). Identifying relevant segments of AI applications adopters–Expanding the UTAUT2’s variables. Telematics and Informatics, 58, 101529.

[9] Cebeci, U., Ertug, A., & Turkcan, H. (2020). Exploring the determinants of intention to use self-checkout systems in super market chain and its application. Management Science Letters, 10(5), 1027-1036.

[10] Chan, F. K., Thong, J. Y., Venkatesh, V., Brown, S. A., Hu, P. J., & Tam, K. Y. (2010). Modeling citizen satisfaction with mandatory adoption of an e-government technology. Journal of the association for information systems, 11(10), 519-549.

[11] Chang, A. (2012). UTAUT and UTAUT 2: A review and agenda for future research. The Winners, 13(2), 10-114.

[12] Chang, C. M., Liu, L. W., Huang, H. C., & Hsieh, H. H. (2019). Factors influencing online hotel booking: Extending UTAUT2 with age, gender, and experience as moderators. Information, 10(9), 281.

[13] Chao, C. M. (2019). Factors determining the behavioral intention to use mobile learning: An application and extension of the UTAUT model. Frontiers in psychology, 10, 1652.

[14] Chatterjee, S., & Kar, A. K. (2020). Why do small and medium enterprises use social media marketing and what is the impact: Empirical insights from India. International Journal of Information Management, 53, 102103.

[15] Chayomchai, A., Phonsiri, W., Junjit, A., Boongapim, R., & Suwannapusit, U. (2020). Factors affecting acceptance and use of online technology in Thai people during COVID-19 quarantine time. Management Science Letters, 10(13), 3009-3016.

[16] Cheng, Y., Sharma, S., Sharma, P., & Kulathunga, K. M. M. C. B. (2020). Role of personalization in continuous use intention of Mobile news apps in India: Extending the UTAUT2 model. Information, 11(1), 33.

[17] Damaianti, I., Farradia, Y., Shafi, S., Arzaman, A. F. M., & Salleh, H. S. (2023). Sustainable Practices in West Java Hotels: Perspectives from the Hotel Association, Hotel Management, and Visitors. International Journal of Sustainable Development & Planning, 18(11), 3575-3584

[18] Erjavec, J., & Manfreda, A. (2022). Online shopping adoption during COVID-19 and social isolation: Extending the UTAUT model with herd behavior. Journal of Retailing and Consumer Services, 65, 102867.

[19] Fakhoury, R., & Aubert, B. (2017). The impact of initial learning experience on digital services usage diffusion: A field study of e-services in Lebanon. International Journal of Information Management, 37(4), 284-296.

[20] Jalil N. A., & Koay, K. Y. (2021). Consumers’ intention to use self-checkout technology in a retail context: a comparison of alternative competing models. International Journal of Business Information Systems, 1-17

[21] Jambulingam, M. (2013). Behavioural intention to adopt mobile technology among tertiary students. World Applied Sciences Journal, 22(9), 1262-1271

[22] Jeong, E. Y. (2019). A study on the intention to reuse mobile airline application: An application of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) model. Journal of Tourism Management Research, 23(2), 719–735

[23] Kamaghe, J. S., Luhanga, E. T., & Michael, K. (2020). The challenges of adopting M-learning assistive technologies for visually impaired learners in higher learning institution in Tanzania. International Journal of Emerging Technologies in Learning, 15(1). 140-151

[24] Katzan, J. R. H. (2011). Essentials of service design. Journal of Service Science, 4(2), 43–60

[25] Kayali, M., & Alaaraj, S. (2020). Adoption of cloud based E-learning in developing countries: a combination a of DOI, TAM and UTAUT. International Journal of Contemporary Management and Information Technology, 1(1), 1-7

[26] Korukcu, O., Ozkaya, M., Faruk, O., & Boran, M. (2021). The effect of the COVID‐19 pandemic on community mental health: A psychometric and prevalence study in Turkey. Health Social Care in the Community, 29(5), 204-e213

[27] Lee, H. J., & Lyu, J. (2019). Exploring factors which motivate older consumers’ self-service technologies (SSTs) adoption. The International Review of Retail, Distribution and Consumer Research, 29(2), 218-239

[28] Lee, J. M., Sim, M. Y., Kang, M. S., Kang, H. G., Jang, J. N., & Kim, D. Y. (2019b). Effects of perceived risk and consumer characteristics on the continuous use intention of technology-based self service. Journal of Consumer Studies, 30(1), 69–92

[29] Limayem, M., Hirt, S. G., & Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS quarterly. 705-737.

[30] Marikyan, D., Papagiannidis, S., & Alamanos, E. (2021). Smart home sweet smart home: An examination of smart home acceptance. International Journal of E-Business Research, 17(2), 1-23

[31] Mohd Arzaman, A. F., Salleh, H. S., Nik Mat, N. H., & Asma Wan Talaat, W. I. (2022). Traditional Knowledge of Marine Resources and Their Relations to the Coastal Community’s Economic Well-Being in Peninsular Malaysia. International Journal of Sustainable Development & Planning, 17(6), 1973-1982

[32] Neslin, S. A., & Shankar, V. (2009). Key issues in multichannel customer management: current knowledge and future directions. Journal of interactive marketing, 23(1), 70-81

[33] Nguyen, N. M., & Borusiak, B. (2021). Using utaut2 model to examine the determinants of omnichannel technology acceptance by consumers. LogForum. 17(2), 231-41.

[34] 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

[35] Katzan, Jr, H. (2011). Essentials of service design. Journal of Service Science, 4(2), 43-60.

[36] Park, J. S., Ha, S., & Jeong, S. W. (2021). Consumer acceptance of self-service technologies in fashion retail stores. Journal of Fashion Marketing and Management: An International Journal, 25(2), 371-388.

[37] Qi, C. (2019). Is checkout-free store a flash in the pan? Factors influencing Hong Kong people’s adoption intention of checkout-free stores. Australasian Conference on Information Systems, 108-114

[38] Salleh, H. S., Mat, N. H. N., Mohamed, W. N., Arzaman, A. F. M., Samsuddin, N. S., & Ahnual, N. K. (2022). Moderating Effect of Experience on the Intention-Behavioral Relationship Towards Sustainable Food Consumption. ABAC Journal, 42(1), 142-159.

[39] Sattari, A., Abdekhoda, M., & Zarea Gavgani, V. (2017). Determinant factors affecting the web–based training acceptance by health students, applying UTAUT model. Internation Journal of Emerg Technology Learning, 12(10), 112-126

[40] Schomakers, E. M., Lidynia, C., Vervier, L. S., Calero, V. A., & Ziefle, M. (2022). Applying an extended UTAUT2 model to explain user acceptance of lifestyle and therapy mobile health apps: survey study. JMIR mHealth and uHealth, 10(1), e27095

[41] Sekaran, U, & Bougie, R. (2013). Research Methods for Business: A Skill Building Approach (6th ed.). Wiley.

[42] Siah, J. W., Fam, S. F., Prastyo, D. D., Yanto, H., & Fam, K. S. (2018). Service quality of self-checkout technology in Malaysian hypermarket: A case study in Johor. Journal of Telecommunication, Electronic and Computer Engineering, 10(2), 109-112

[43] Tan, G. W. H., Ooi, K. B., Sim, J. J., & Phusavat, K. (2012). Determinants of mobile learning adoption: An empirical analysis. Journal of Computer Information Systems, 52(3), 82-91.

[44] Taber, K. S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in science education, 48, 1273-1296.

[45] Tao, K. C., Hsu, C. Y., Yang, J. J., Ke, M. F., & Chiang, C. H. (2023). Exploring Use Behavior of Self-Service Ordering at Restaurants with Application Unified Theory of Acceptance and Use of Technology Model. Engineering Proceedings, 38(1), 26.

[46] Turner, T., & Shockley, J. (2014). Creating shopper value: Co-creation roles, in-store self-service technology use, and value differentiation. Journal of Promotion Management, 20(3), 311-327.

[47] Venkatesh, V. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology 1. MIS Quarterly, 36(1), 157-178

[48] Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425-478

[49] Wang, X., Wong, Y. D., & Yuen, K. F. (2021). Does COVID-19 promote self-service usage among modern shoppers? An exploration of pandemic-driven behavioural changes in self-collection users. International Journal of Environmental Research and Public Health, 18(16), 8574.

[50] Wang, X., Wong, Y. D., & Yuen, K. F. (2021b). Rise of ‘lonely’consumers in the post-COVID-19 era: A synthesised review on psychological, commercial and social implications. International journal of environmental research and public health, 18(2), 404.

[51] Wijaya, I., Rai, A., & Hariguna, T. (2019). The impact of customer experience on customer behavior intention use in social media commerce, an extended expectation confirmation model: An empirical study. Management Science Letters, 9(12), 2009-2020

[52] Wu, W., Zhang, B., Li, S., & Liu, H. (2022). Exploring Factors of the Willingness to Accept AI-Assisted Learning Environments: An Empirical Investigation Based on the UTAUT Model and Perceived Risk Theory. Frontiers in Psychology, 13, 870777.

Abstract

References

How to cite