Exploring customer adoption of autonomous shopping systems

Telematics and Informatics - Tập 73 - Trang 101861 - 2022
Shavneet Sharma1, Gurmeet Singh1, Loveleen Gaur2, Anam Afaq2
1School of Business and Management, The University of The South Pacific, Fiji
2Amity International Business School, Amity University, Noida, India

Tài liệu tham khảo

Aguirre, 2015, Unraveling the spersonalisation paradox: The effect of information collection and trust-building strategies on online advertisement effectiveness, J. Retail., 91, 34, 10.1016/j.jretai.2014.09.005 Alalwan, 2020, Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse, Int. J. Inf. Manage., 50, 28, 10.1016/j.ijinfomgt.2019.04.008 Alalwan, 2017, Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust, Int. J. Inf. Manage., 37, 99, 10.1016/j.ijinfomgt.2017.01.002 Al-Khalaf, 2020, Increasing customer trust towards mobile commerce in a multicultural society: A case of Qatar, J. Internet Commerce, 19, 32, 10.1080/15332861.2019.1695179 Baabdullah, 2019, Consumer adoption of self-service technologies in the context of the Jordanian banking industry: Examining the moderating role of channel types, Inf. Syst. Manage., 36, 286, 10.1080/10580530.2019.1651107 Baganzi, 2017, Examining trust and risk in mobile money acceptance in Uganda, Sustainability, 9, 2233, 10.3390/su9122233 Bagozzi, 2012, Specification, evaluation, and interpretation of structural equation models, J. Acad. Mark. Sci., 40, 8, 10.1007/s11747-011-0278-x Cameron, 2021, The effect of social-cognitive recovery strategies on likability, capability and trust in social robots, Comput. Hum. Behav., 114, 10.1016/j.chb.2020.106561 Cha, 2020, Customers’ intention to use robot-serviced restaurants in Korea: relationship of coolness and MCI factors, Int. J. Contemp. Hospitality Manage., 32, 2947, 10.1108/IJCHM-01-2020-0046 Chang, 2017, User trust in social networking services: A comparison of Facebook and LinkedIn, Comput. Hum. Behav., 69, 207, 10.1016/j.chb.2016.12.013 Chen, 2011, An investigation of email processing from a risky decision making perspective, Decis. Support Syst., 52, 73, 10.1016/j.dss.2011.05.005 Cheng, 2021, The good, the bad, and the ugly: impact of analytics and artificial intelligence-enabled personal information collection on privacy and participation in ridesharing, Eur. J. Inf. Syst., 1–25 De Bellis, 2020, Autonomous Shopping Systems: Identifying and Overcoming Barriers to Consumer Adoption, J. Retail., 96, 74, 10.1016/j.jretai.2019.12.004 Dirsehan, 2020, Examination of trust and sustainability concerns in autonomous vehicle adoption, Technol. Soc., 63, 10.1016/j.techsoc.2020.101361 Du, 2021, Why travelers trust and accept self-driving cars: an empirical study, Travel Behav. Society, 22, 1, 10.1016/j.tbs.2020.06.012 Dwivedi, Y.K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., 2021. Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management 57, 101994. doi:10.1016/j.ijinfomgt.2019.08.002. Fernandes, 2021, Understanding consumers’ acceptance of automated technologies in service encounters: Drivers of digital voice assistants adoption, J. Bus. Res., 122, 180, 10.1016/j.jbusres.2020.08.058 Ferrario, 2019, In AI we trust incrementally: a multi-layer model of trust to sanalyse human-artificial intelligence interactions, Philos. Technol., 1–17 Glikson, 2020, Human trust in Artificial Intelligence: Review of empirical research, Acad. Manage. Ann., 14, 10.5465/annals.2018.0057 Grewal, 2020, The future of in-store technology, J. Acad. Mark. Sci., 48, 96, 10.1007/s11747-019-00697-z Grewal, 2020, Understanding retail experiences and customer journey management, J. Retail., 96, 3, 10.1016/j.jretai.2020.02.002 Gursoy, D., Chi, O.H., Lu, L., Nunkoo, R., 2019. Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management 49, 157-169. doi:10.1016/j.ijinfomgt.2019.03.008. Hair, 2010 Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E., Tatham, R.L., 2006. Multivariate data analysis 6th Edition. Pearson Prentice Hall. New Jersey. Humans: Critique and reformulation. Journal of Abnormal Psychology 87, 49-74. Hanafizadeh, 2014, Mobile-banking adoption by Iranian bank clients, Telematics Inform., 31, 62, 10.1016/j.tele.2012.11.001 Hengstler, 2016, Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices, Technol. Forecast. Soc. Chang., 105, 105, 10.1016/j.techfore.2015.12.014 Hu, 2021, Can AI artifacts influence human cognition? The effects of artificial autonomy in intelligent personal assistants, Int. J. Inf. Manage., 56, 10.1016/j.ijinfomgt.2020.102250 Inman, 2017, Shopper-facing retail technology: A retailer adoption decision framework incorporating shopper attitudes and privacy concerns, J. Retail., 93, 7, 10.1016/j.jretai.2016.12.006 Kankanamge, 2021, Public perceptions on artificial intelligence driven disaster management: Evidence from Sydney, Melbourne and Brisbane, Telematics Inf., 65 Kapser, 2020, Acceptance of autonomous delivery vehicles for last-mile delivery in Germany-Extending UTAUT2 with risk perceptions, Transp. Res. Part C: Emerg. Technol., 111, 210, 10.1016/j.trc.2019.12.016 Kaye, 2020, A priori acceptance of highly automated cars in Australia, France, and Sweden: A theoretically-informed investigation guided by the TPB and UTAUT, Accid. Anal. Prev., 137, 10.1016/j.aap.2020.105441 Lau, 2020, Investigating nonusers’ behavioural intention towards solar photovoltaic technology in Malaysia: The role of knowledge transmission and price value, Energy Policy, 144, 10.1016/j.enpol.2020.111651 Lee, 2004, Trust in automation: Designing for appropriate reliance, Hum. Factors, 46, 50, 10.1518/hfes.46.1.50.30392 Lee, 2013, Effects of trust and perceived risk on user acceptance of a new technology service, Social Behav. Personality: Int. J., 41, 587, 10.2224/sbp.2013.41.4.587 Lejealle, 2021, Decoding the educational travel decision: destinations, institutions and social influence, Curr. Issues Tourism, 1–14 Li, 2008, Why do we trust new technology? A study of initial trust formation with sorganisational information systems, J. Strateg. Inf. Syst., 17, 39, 10.1016/j.jsis.2008.01.001 Liew, 2021, Social cues and implications for designing expert and competent artificial agents: A systematic review, Telematics Inform., 65, 10.1016/j.tele.2021.101721 Lim, 2018, Dialectic antidotes to critics of the technology acceptance model: Conceptual, methodological, and replication treatments for behavioural modelling in technology-mediated environments, Aust. J. Inf. Syst., 22 Lin, 2020, Antecedents of customers’ acceptance of artificially intelligent robotic device use in hospitality services, J. Hospitality Mark. Manage., 29, 530, 10.1080/19368623.2020.1685053 Loureiro, 2018, Fashion brands on retail websites: Customer performance expectancy and e-word-of-mouth, J. Retailing Consumer Serv., 41, 131, 10.1016/j.jretconser.2017.12.005 Lu, 2019, Developing and validating a service robot integration willingness scale, Int. J. Hospitality Manage., 80, 36, 10.1016/j.ijhm.2019.01.005 McLean, 2020, How live chat assistants drive travel consumers’ attitudes, trust and purchase intentions, Int. J. Contemp. Hospitality Manage., 32, 1795, 10.1108/IJCHM-07-2019-0605 Merhi, 2019, A cross-cultural study of the intention to use mobile banking between Lebanese and British consumers: Extending UTAUT2 with security, privacy and trust, Technol. Soc., 59, 10.1016/j.techsoc.2019.101151 Meske, 2020, Explainable Artificial Intelligence: Objectives, Stakeholders, and Future Research Opportunities, Inf. Syst. Manage., 1–11 Miltgen, 2015, Exploring information privacy regulation, risks, trust, and behavior, Inf. Manage., 52, 741, 10.1016/j.im.2015.06.006 Naeem, 2021, Do social media platforms develop consumer panic buying during the fear of Covid-19 pandemic, J. Retailing Consumer Serv., 58 Okazaki, 2020, Understanding the Strategic Consequences of Customer Privacy Concerns: A Meta-Analytic Review, J. Retail., 96, 458, 10.1016/j.jretai.2020.05.007 Ozturk, 2017, Understanding mobile hotel booking loyalty: an integration of privacy calculus theory and trust-risk framework, Inf. Syst. Front., 19, 753, 10.1007/s10796-017-9736-4 Park, 2020, Multifaceted trust in tourism service robots, Ann. Tourism Res., 81, 10.1016/j.annals.2020.102888 Pillai, 2020, Shopping intention at AI-powered automated retail stores (AIPARS), J. Retailing Consumer Serv., 57 Podsakoff, 2003, Common method biases in behavioral research: a critical review of the literature and recommended remedies, J. Appl. Psychol., 88, 879, 10.1037/0021-9010.88.5.879 Prokofieva, 2019, Blockchain in healthcare, Aust. J. Inf. Syst., 23 Shankar, 2020, How Technology is Changing Retail, J. Retail., 97, 13, 10.1016/j.jretai.2020.10.006 Shareef, 2017, Content design of advertisement for consumer exposure: Mobile marketing through short messaging service, Int. J. Inf. Manage., 37, 257, 10.1016/j.ijinfomgt.2017.02.003 Shareef, 2021, A new health care system enabled by machine intelligence: Elderly people’s trust or losing self control, Technol. Forecast. Soc. Chang., 162, 10.1016/j.techfore.2020.120334 Sharma, 2020, Does Consumers’ Intention to Purchase Travel Online Differ Across Generations?, Aust. J. Inf. Syst., 24 Sharma, 2020, Exploring consumer behavior to purchase travel online in Fiji and Solomon Islands? An extension of the UTAUT framework, Int. J. Culture, Tourism Hospitality Res., 15, 227, 10.1108/IJCTHR-03-2020-0064 Sharma, 2021, Competitors' envy, gamers' pride: An exploration of gamers' divergent behavior, Psychol. Mark., 38, 965, 10.1002/mar.21469 Sharma, 2021, Modeling the Multi-dimensional Facets of Perceived Risk in Purchasing Travel Online: A Generational Analysis, J. Qual. Assurance Hospitality Tourism, 1–29 Sharma, 2020, Use of social networking sites by SMEs to engage with their customers: a developing country perspective, J. Internet Commerce, 19, 62, 10.1080/15332861.2019.1695180 Sharma, 2022, Virtual Fitness: Investigating Team Commitment and Post-Pandemic Virtual Workout Perceptions, Telematics Inform., 71, 1, 10.1016/j.tele.2022.101840 Sharma, 2021, Exploring gamers' crowdsourcing engagement in Pokémon Go communities, TQM J., 10.1108/TQM-05-2021-0131 Sharma, 2022, Why Do Retail Customers Adopt Artificial Intelligence (AI) Based Autonomous Decision-Making Systems?, IEEE Trans. Eng. Manage., 1–16 Sharma, 2022, From virtual to actual destinations: do interactions with others, emotional solidarity, and destination image in online games influence willingness to travel?, Curr. Issues Tourism, 1–19 Siau, 2018, Building trust in artificial intelligence, machine learning, and robotics, Cutter Bus. Technol. J., 31, 47 Singh, 2021, Exploring panic buying behavior during the COVID-19 pandemic: a developing country perspective, Int. J. Emerg. Markets, 10.1108/IJOEM-03-2021-0308 Singh, S., 2020. An integrated model combining ECM and UTAUT to explain users’ post- adoption behaviour towards mobile payment systems. Australasian Journal of Information Systems 24. doi:10.3127/ajis.v24i0.2695. Song, 2021, The face of trust: The effect of robot face ratio on consumer preference, Comput. Hum. Behav., 116, 10.1016/j.chb.2020.106620 Straub, 2004, Validation guidelines for IS positivist research, Commun. Assoc. Inf. Syst., 13, 24 Sun, 2020, Newspaper coverage of artificial intelligence: A perspective of emerging technologies, Telematics Inform., 53, 10.1016/j.tele.2020.101433 Tabachnick, 2007 Tan, 2012, Impact of privacy concern in social networking web sites, Internet Res., 22, 211, 10.1108/10662241211214575 Venkatesh, 2010, Expectation disconfirmation and technology adoption: polynomial modeling and response surface analysis, MIS Q., 34, 281, 10.2307/20721428 Venkatesh, 2003, User acceptance of information technology: Toward a unified view, MIS Q., 27, 425, 10.2307/30036540 Venkatesh, 2012, Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology, MIS Q., 36, 157, 10.2307/41410412 Wahlstrom, 2020, Privacy by design, Aust. J. Inf. Syst., 24 Wang, 2019, Does privacy assurance on social commerce sites matter to millennials?, Int. J. Inf. Manage., 44, 164, 10.1016/j.ijinfomgt.2018.10.016 Widjaja, 2019, Understanding ”””users’ willingness to put their personal information on the personal cloud-based storage applications: An empirical study, Comput. Hum. Behav., 91, 167, 10.1016/j.chb.2018.09.034 Wong, 2020, Unearthing the determinants of Blockchain adoption in supply chain management, Int. J. Prod. Res., 58, 2100, 10.1080/00207543.2020.1730463 Xu, 2019, An empirical study of patients’ privacy concerns for health informatics as a service, Technol. Forecast. Soc. Chang., 143, 297, 10.1016/j.techfore.2019.01.018 Zarifis, 2020, Evaluating if trust and personal information privacy concerns are barriers to using health insurance that explicitly sutilises AI, J. Internet Commerce, 20, 1 Zhao, 2020, What factors determining customer continuingly using food delivery apps during 2019 novel coronavirus pandemic period?, Int. J. Hospitality Manage., 91, 10.1016/j.ijhm.2020.102683 Zheng, 2012, Empirical study and model of ”””” ’User’s acceptance for mobile commerce in China, Int. J. Comput. Sci. Issues (IJCSI), 9, 278 Zhou, 2020, Understanding consumers’ behavior to adopt self-service parcel services for last-mile delivery, J. Retailing Consumer Serv., 52