Determinants and consequences of trust in AI-based customer service chatbots

References

• Adam, M., Wessel, M., & Benlian, A. (2021). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31(2), 427–445. https://doi.org/10.1007/s12525-020-00414-7
   Web of Science ®Google Scholar
• Ahonen, E. (2020). The effects of transactionality on trust in customer service chatbots. [Master’s thesis, Aalto University]. Aalto University eTheses Repository. https://aaltodoc.aalto.fi/handle/123456789/47150
   Google Scholar
• Alt, M., Vizeli, I., & Săplăcan, Z. (2021). Banking with a chatbot - a study on technology acceptance. Studia Universitatis Babes-Bolyai Oeconomica, 66(1), 13–35. https://doi.org/10.2478/subboec-2021-0002
   Google Scholar
• Bansal, G., Zahedi, F. M., & Gefen, D. (2016). Do context and personality matter? Trust and privacy concerns in disclosing private information online. Information & Management, 53(1), 1–21. https://doi.org/10.1016/j.im.2015.08.001
   Web of Science ®Google Scholar
• Bedué, P. (2020). Lecture notes in business information processing. Lecture Notes in Business Information Processing, 389(LNBIP), 291–306. https://doi.org/10.1007/978-3-030-53337-3_22
   Google Scholar
• Belanche, D., Casaló, L. V., & Flavián, C. (2021a). Frontline robots in tourism and hospitality: Service enhancement or cost reduction? Electronic Markets, 31(3), 477–492. https://doi.org/10.1007/s12525-020-00432-5
   Web of Science ®Google Scholar
• Belanche, D., Casaló, L. V., Flavián, C., & Schepers, J. (2020a). Robots or frontline employees? Exploring customers’ attributions of responsibility and stability after service failure or success. Journal of Service Management, 31(2), 267–289. https://doi.org/10.1108/JOSM-05-2019-0156
   Web of Science ®Google Scholar
• Belanche, D., Casaló, L. V., Flavián, C., & Schepers, J. (2020b). Service robot implementation: A theoretical framework and research agenda. The Service Industries Journal, 40(3-4), 203–225. https://doi.org/10.1080/02642069.2019.1672666
   Web of Science ®Google Scholar
• Belanche, D., Casaló, L. V., Schepers, J., & Flavián, C. (2021b). Examining the effects of robots’ physical appearance, warmth, and competence in frontline services: The humanness-value-loyalty model. Psychology & Marketing, 38(12), 2357–2376. https://doi.org/10.1002/mar.21532
   Web of Science ®Google Scholar
• Berge, S. H. (2018). Rise of the chatbots: Trust in artificial intelligence during extreme weather events. [Master’s Thesis, University of Oslo]. University of Oslo e-Theses Repository. https://www.duo.uio.no/handle/10852/63372
   Google Scholar
• Biocca, F., Harms, C., & Burgoon, J. K. (2003). Toward a more robust theory and measure of social presence: Review and suggested criteria. Presence: Teleoperators and Virtual Environments, 12(5), 456–480. https://doi.org/10.1162/105474603322761270
   Web of Science ®Google Scholar
• Brachten, F., Kissmer, T., & Stieglitz, S. (2021). The acceptance of chatbots in an enterprise context – A survey study. International Journal of Information Management, 60, 102375. https://doi.org/10.1016/j.ijinfomgt.2021.102375
   Web of Science ®Google Scholar
• Cao, X., Yu, L., Liu, Z., Gong, M., & Adeel, L. (2018). Understanding mobile payment users’ continuance intention: A trust transfer perspective. Internet Research, 28(2), 456–476. https://doi.org/10.1108/IntR-11-2016-0359
   Web of Science ®Google Scholar
• Castillo, D., Canhoto, A. I., & Said, E. (2021). The dark side of AI-powered service interactions: Exploring the process of co-destruction from the customer perspective. The Service Industries Journal, 41(13-14), 900–925. https://doi.org/10.1080/02642069.2020.1787993
   Web of Science ®Google Scholar
• Chen, S. C., Yen, D. C., & Hwang, M. I. (2012). Factors influencing the continuance intention to the usage of Web 2.0: An empirical study. Computers in Human Behavior, 28(3), 933–941. https://doi.org/10.1016/j.chb.2011.12.014
   Web of Science ®Google Scholar
• Cheng, X., Zhang, X., Cohen, J., & Mou, J. (2022). Human vs. AI: Understanding the impact of anthropomorphism on consumer response to chatbots from the perspective of trust and relationship norms. Information Processing & Management, 59(3), 102940. https://doi.org/10.1016/j.ipm.2022.102940
   Web of Science ®Google Scholar
• Cheung, C. M., & Lee, M. K. (2001). Trust in internet shopping. Journal of Global Information Management, 9(3), 23–35. https://doi.org/10.4018/jgim.2001070103
   Google Scholar
• Chocarro, R., Cortiñas, M., & Marcos-Matás, G. (2021). Teachers’ attitudes towards chatbots in education: A technology acceptance model approach considering the effect of social language, bot proactiveness, and users’ characteristics. Educational Studies, 1–19. https://doi.org/10.1080/03055698.2020.1850426
   Web of Science ®Google Scholar
• Clark, L., Doyle, P., Garaialde, D., Gilmartin, E., Schlögl, S., Edlund, J., Aylett, M., Cabral, J., Munteanu, C., Edwards, J., & R Cowan, B. (2019). The state of speech in HCI: Trends, themes and challenges. Interacting with Computers, 31(4), 349–371. https://doi.org/10.1093/iwc/iwz016
   Web of Science ®Google Scholar
• Colquitt, J. A., Scott, B. A., & LePine, J. A. (2007). Trust, trustworthiness, and trust propensity: A meta-analytic test of their unique relationships with risk taking and job performance. Journal of Applied Psychology, 92(4), 909–927. https://doi.org/10.1037/0021-9010.92.4.909
   PubMed Web of Science ®Google Scholar
• Computer Generated Solutions. (2019). CGS survey reveals consumers prefer a hybrid AI/human approach to customer service. Is there chatbot fatigue? Available at https://www.cgsinc.com/en/resources/2019-CGS-Customer-Service-Chatbots-Channels-Survey
   Google Scholar
• Corritore, C., Kracher, B., & Wiedenbeck, S. (2003). On-line trust: Concepts, evolving themes, a model. International Journal of Human-Computer Studies, 58(6), 737–758. https://doi.org/10.1016/S1071-5819(03)00041-7
   Web of Science ®Google Scholar
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
   Web of Science ®Google Scholar
• Dimitriadis, S., & Kyrezis, N. (2010). Linking trust to use intention for technology-enabled bank channels: The role of trusting intentions. Psychology & Marketing, 27(8), 799–820. https://doi.org/10.1002/mar.20358
   Web of Science ®Google Scholar
• Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80. https://doi.org/10.1287/isre.1060.0080
   Web of Science ®Google Scholar
• Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21(3), 719–734. https://doi.org/10.1007/s10796-017-9774-y
   Web of Science ®Google Scholar
• Ebadi, S., & Amini, A. (2022). Examining the roles of social presence and human-likeness on Iranian EFL learners’ motivation using artificial intelligence technology: A case of CSIEC chatbot. Interactive Learning Environments, 1–19. https://doi.org/10.1080/10494820.2022.2096638
   Web of Science ®Google Scholar
• Elliott, M. N., & Haviland, A. (2007). Use of a web-based convenience sample to supplement a probability sample. Survey Methodology, 33(2), 211–215.
   Web of Science ®Google Scholar
• Eren, B. A. (2021). Determinants of customer satisfaction in chatbot use: Evidence from a banking application in Turkey. International Journal of Bank Marketing, 39(2), 294–311. https://doi.org/10.1108/IJBM-02-2020-0056
   Web of Science ®Google Scholar
• Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474. https://doi.org/10.1016/S1071-5819(03)00111-3
   Web of Science ®Google Scholar
• Flavián, C., & Casaló, L. V. (2021). Artificial intelligence in services: Current trends, benefits and challenges. The Service Industries Journal, 41(13–14), 853–859. https://doi.org/10.1080/02642069.2021.1989177
   Web of Science ®Google Scholar
• Flavián, C., Pérez-Rueda, A., Belanche, D., & Casaló, L. V. (2022). Intention to use analytical artificial intelligence (AI) in services – the effect of technology readiness and awareness. Journal of Service Management, 33(2), 293–320. https://doi.org/10.1108/JOSM-10-2020-0378
   Web of Science ®Google Scholar
• Gan, C., & Li, H. (2018). Understanding the effects of gratifications on the continuance intention to use WeChat in China: A perspective on uses and gratifications. Computers in Human Behavior, 78, 306–315. https://doi.org/10.1016/j.chb.2017.10.003
   Web of Science ®Google Scholar
• Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 51–90. https://doi.org/10.2307/30036519
   Web of Science ®Google Scholar
• Gefen, D., & Straub, D. (2003). Managing user trust in B2C e-services. E-Service Journal, 2(2), 7–24. https://doi.org/10.2979/esj.2003.2.2.7
   Google Scholar
• Gnewuch, U., Morana, S., Adam, M. T. P., & Maedche, A. (2022). Opposing effects of response time in human–chatbot interaction. Business & Information Systems Engineering, 1–19. https://doi.org/10.1007/S12599-022-00755-X
   Web of Science ®Google Scholar
• Go, E., & Sundar, S. S. (2019). Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions. Computers in Human Behavior, 97(1), 304–316. https://doi.org/10.1016/j.chb.2019.01.020
   Web of Science ®Google Scholar
• Grand View Research. (2021). Chatbot Market Size Worth $2,485.7 Million By 2028. Available at https://www.grandviewresearch.com/press-release/global-chatbot-market.
   Google Scholar
• Griffith, E., & Simonite, T.. (2018). Facebook’s virtual assistant M is dead. So are Chatbots. Wired Business, 8. https://www.wired.com/story/facebooks-virtual-assistant-m-is-dead-so-are-chatbots/
   Google Scholar
• Gulati, S., Sousa, S., & Lamas, D. (2019). Design, development and evaluation of a human-computer trust scale. Behaviour & Information Technology, 38(10), 1004–1015. https://doi.org/10.1080/0144929X.2019.1656779
   Web of Science ®Google Scholar
• Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
   Web of Science ®Google Scholar
• Hasan, R., Shams, R., & Rahman, M. (2021). Consumer trust and perceived risk for voice-controlled artificial intelligence: The case of siri. Journal of Business Research, 131, 591–597. https://doi.org/10.1016/j.jbusres.2020.12.012
   Web of Science ®Google Scholar
• Hollebeek, L., & Rather, R. A. (2019). Service innovativeness and tourism customer outcomes. International Journal of Contemporary Hospitality Management, 31(11), 4227–4246. https://doi.org/10.1108/IJCHM-03-2018-0256
   Web of Science ®Google Scholar
• Hsu, C. L., & Lin, J. C. C. (2021). Factors affecting customers’ intention to voice shopping over smart speaker從智慧音箱品質、互補性與隱私風險探討影響智慧音箱使用者語音購物因素. The Service Industries Journal, 1–21. https://doi.org/10.1080/02642069.2021.2008913
   Web of Science ®Google Scholar
• Huang, B., & Philp, M. (2021). When AI-based services fail: Examining the effect of the self-AI connection on willingness to share negative word-of-mouth after service failures. The Service Industries Journal, 41(13-14), 877–899. https://doi.org/10.1080/02642069.2020.1748014
   Web of Science ®Google Scholar
• Huang, Y.-S., & Kao, W.-K. (2021). Chatbot service usage during a pandemic: Fear and social distancing. The Service Industries Journal, 41(13-14), 964–984. https://doi.org/10.1080/02642069.2021.1957845
   Web of Science ®Google Scholar
• Hyun, Y., Hlee, S., Park, J., & Chang, Y. (2022). Discovering meaningful engagement through interaction between customers and service robots. The Service Industries Journal, 42(13–14), 973–1000. https://doi.org/10.1080/02642069.2022.2088738
   Web of Science ®Google Scholar
• Jang, M., Jung, Y., & Kim, S. (2021). Investigating managers’ understanding of chatbots in the Korean financial industry. Computers in Human Behavior, 120, 106747. https://doi.org/10.1016/j.chb.2021.106747
   Web of Science ®Google Scholar
• Jiang, C., Rashid, R. M., & Wang, J. (2019). Investigating the role of social presence dimensions and information support on consumers’ trust and shopping intentions. Journal of Retailing and Consumer Services, 51, 263–270. https://doi.org/10.1016/j.jretconser.2019.06.007
   Web of Science ®Google Scholar
• Jiménez-Barreto, J., Rubio, N., & Molinillo, S. (2021). “Find a flight for me, Oscar!” motivational customer experiences with chatbots. International Journal of Contemporary Hospitality Management, 33(11), 3860–3882. https://doi.org/10.1108/IJCHM-10-2020-1244
   Web of Science ®Google Scholar
• Jin, E., & Eastin, M. S. (2022). Birds of a feather flock together: Matched personality effects of product recommendation chatbots and users. Journal of Research in Interactive Marketing. https://doi.org/10.1108/JRIM-03-2022-0089
   Web of Science ®Google Scholar
• Kaplan, A. D., Kessler, T. T., Brill, J. C., & Hancock, P. A. (2021). Trust in artificial intelligence: Meta-analytic findings. Human Factors: The Journal of the Human Factors and Ergonomics Society, 00(0), 001872082110139. https://doi.org/10.1177/00187208211013988
   Web of Science ®Google Scholar
• Kasilingam, D. L. (2020). Understanding the attitude and intention to use smartphone chatbots for shopping. Technology in Society, 62, 101280. https://doi.org/10.1016/j.techsoc.2020.101280
   Web of Science ®Google Scholar
• Koo, C., Wati, Y., & Chung, N. (2013). Vicious and virtuous circles of offshoring attitudes and relational behaviours. A configurational study of German IT developers. Information Systems Journal, 23(1), 65–88. https://doi.org/10.1111/j.1365-2575.2012.00399.x
   Web of Science ®Google Scholar
• Krogue, K. (2017, September 11). artificial intelligence is here to stay, but consumer trust is a must for AI in business. Forbes website. https://www.Forbes.com/Sites/Kenkrogue/2017/09/11/Artificial-Intelligence-Is-Here-to-Stay-but-Consumer-Trust-Is-a-Must-for-Ai-in-Business.
   Google Scholar
• Lankton, N. K., Harrison Mcknight, D., & Tripp, J. (2015). Technology, humanness, and trust: Rethinking trust in technology. Journal of the Association for Information Systems, 16(10), 880. https://doi.org/10.17705/1jais.00411
   Web of Science ®Google Scholar
• Le, N. T., Rao Hill, S., & Troshani, I. (2022). Perceived control and perceived risk in self-service technology recovery. Journal of Computer Information Systems, 62(1), 164–173. https://doi.org/10.1080/08874417.2020.1756533
   Web of Science ®Google Scholar
• Lee, J. G., & Lee, K. M. (2022). Polite speech strategies and their impact on drivers’ trust in autonomous vehicles. Computers in Human Behavior, 127, 107015. https://doi.org/10.1016/j.chb.2021.107015
   Web of Science ®Google Scholar
• Lee, M. K., & Turban, E. (2001). A trust model for consumer internet shopping. International Journal of Electronic Commerce, 6(1), 75–91. https://doi.org/10.1080/10864415.2001.11044227
   Web of Science ®Google Scholar
• Loureiro, S. M. C., Japutra, A., Molinillo, S., & Godinho Bilro, R. (2021). Stand by me: Analyzing the tourist-intelligent voice assistant relationship quality. International Journal of Contemporary Hospitality Management, 33(11), 3840–3859. https://doi.org/10.1108/IJCHM-09-2020-1032
   Web of Science ®Google Scholar
• Lv, L., Huang, M., & Huang, R. (2022). Anthropomorphize service robots: The role of human nature traits. The Service Industries Journal, 1–25. https://doi.org/10.1080/02642069.2022.2048821
   Web of Science ®Google Scholar
• Ma, C., & Ye, J. (2022). Linking artificial intelligence to service sabotage. The Service Industries Journal, 42(13–14), 1054–1074. https://doi.org/10.1080/02642069.2022.2092615
   Web of Science ®Google Scholar
• MacKenzie, S. B., & Podsakoff, P. M. (2012). Common method bias in marketing: Causes, mechanisms, and procedural remedies. Journal of Retailing, 88(4), 542–555. https://doi.org/10.1016/J.JRETAI.2012.08.001
   Web of Science ®Google Scholar
• Maedche, A., Morana, S., Schacht, S., Werth, D., & Krumeich, J. (2016). Advanced user assistance systems. Business & Information Systems Engineering, 58(5), 367–370. https://doi.org/10.1007/s12599-016-0444-2
   Web of Science ®Google Scholar
• Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. The Academy of Management Review, 20(3), 709–734. https://doi.org/10.2307/258792
   Web of Science ®Google Scholar
• Mcknight, D. H., Carter, M., Thatcher, J. B., & Clay, P. F. (2011). Trust in a specific technology. ACM Transactions on Management Information Systems, 2(2), 1. https://doi.org/10.1145/1985347.1985353
   Google Scholar
• Mcknight, H. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research, 13(3), 334–359. https://doi.org/10.1287/isre.13.3.334.81
   Web of Science ®Google Scholar
• McLean, G., Osei-Frimpong, K., Wilson, A., & Pitardi, V. (2020). How live chat assistants drive travel consumers’ attitudes, trust and purchase intentions. International Journal of Contemporary Hospitality Management, 32(5), 1795–1812. https://doi.org/10.1108/IJCHM-07-2019-0605
   Web of Science ®Google Scholar
• Melián-González, S., Gutiérrez-Taño, D., & Bulchand-Gidumal, J. (2021). Predicting the intentions to use chatbots for travel and tourism. Current Issues in Tourism, 24(2), 192–210. https://doi.org/10.1080/13683500.2019.1706457
   Web of Science ®Google Scholar
• Mostafa, R. B., & Kasamani, T. (2022). Antecedents and consequences of chatbot initial trust. European Journal of Marketing, 56(6), 1748–1771. https://doi.org/10.1108/EJM-02-2020-0084
   Web of Science ®Google Scholar
• Moussawi, S., Koufaris, M., & Benbunan-Fich, R. (2021). How perceptions of intelligence and anthropomorphism affect adoption of personal intelligent agents. Electronic Markets, 31(1), 343–361. https://doi.org/10.1007/s12525-020-00411-w
   Web of Science ®Google Scholar
• Muir, B. M., & Moray, N. (1996). Trust in automation. Part II. Experimental studies of trust and human intervention in a process control simulation. Ergonomics, 39(3), 429–460. https://doi.org/10.1080/00140139608964474
   PubMed Web of Science ®Google Scholar
• Namahoot, K. S., & Laohavichien, T. (2018). Assessing the intentions to use internet banking. International Journal of Bank Marketing, 36(2), 256–276. https://doi.org/10.1108/IJBM-11-2016-0159
   Web of Science ®Google Scholar
• Nass, C., & Moon, Y. (2000). Machines and mindlessness: Social responses to computers. Journal of Social Issues, 56(1), 81–103. https://doi.org/10.1111/0022-4537.00153
   Web of Science ®Google Scholar
• Nass, C., Moon, Y., Fogg, B. J., Reeves, B., & Dryer, D. C. (1995). Can computer personalities be human personalities? International Journal of Human-Computer Studies, 43(2), 223–239. https://doi.org/10.1006/ijhc.1995.1042
   Web of Science ®Google Scholar
• Nitzl, C., Roldan, J. L., & Cepeda, G. (2016). Mediation analysis in partial least squares path modeling. Industrial Management & Data Systems, 116(9), 1849–1864. https://doi.org/10.1108/IMDS-07-2015-0302
   Web of Science ®Google Scholar
• Noor, N., Rao Hill, S., & Troshani, I. (2022). Artificial intelligence service agents: Role of parasocial relationship. Journal of Computer Information Systems, 1–15. https://doi.org/10.1080/08874417.2021.1962213
   Web of Science ®Google Scholar
• Nordheim, C. B., Følstad, A., & Bjørkli, C. A. (2019). An initial model of trust in chatbots for customer service—findings from a questionnaire study. Interacting with Computers, 31(3), 317–335. https://doi.org/10.1093/iwc/iwz022
   Web of Science ®Google Scholar
• Pal, D., Funilkul, S., & Papasratorn, B. (2019). Antecedents of trust and the continuance intention in IoT-based smart products: The case of consumer wearables. IEEE Access, 7, 184160–184171. https://doi.org/10.1109/ACCESS.2019.2960467
   Web of Science ®Google Scholar
• Parrey, S. H., Hakim, I. A., & Rather, R. A. (2019). Mediating role of government initiatives and media influence between perceived risks and destination image: A study of conflict zone. International Journal of Tourism Cities, 5(1), 90–106. https://doi.org/10.1108/IJTC-02-2018-0019
   Web of Science ®Google Scholar
• Patel, S. (2022, July, 19). Top 12 Chatbots Trends and Statistics to Follow in 2022. Revechat. https://www.revechat.com/blog/chatbots-trends-stats/.
   Google Scholar
• Pillai, R., & Sivathanu, B. (2020). Adoption of AI-based chatbots for hospitality and tourism. International Journal of Contemporary Hospitality Management, 32(10), 3199–3226. https://doi.org/10.1108/IJCHM-04-2020-0259
   Web of Science ®Google Scholar
• Pitardi, V., & Marriott, H. R. (2021). Alexa, she’s not human but … Unveiling the drivers of consumers’ trust in voice-based artificial intelligence. Psychology & Marketing, 38(4), 626–642. https://doi.org/10.1002/mar.21457
   Web of Science ®Google Scholar
• Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879. https://doi.org/10.1037/0021-9010.88.5.879
   PubMed Web of Science ®Google Scholar
• Prakash, A. V., & Das, S. (2021). Medical practitioner’s adoption of intelligent clinical diagnostic decision support systems: A mixed-methods study. Information & Management, 58(7), 103524. https://doi.org/10.1016/j.im.2021.103524
   Web of Science ®Google Scholar
• Qin, F., Li, K., & Yan, J. (2020). Understanding user trust in artificial intelligence-based educational systems: Evidence from China. British Journal of Educational Technology, 51(5), 1693–1710. https://doi.org/10.1111/bjet.12994
   Web of Science ®Google Scholar
• Qiu, L., & Benbasat, I. (2009). Evaluating anthropomorphic product recommendation agents: A social relationship perspective to designing information systems. Journal of Management Information Systems, 25(4), 145–182. https://doi.org/10.2753/MIS0742-1222250405
   Web of Science ®Google Scholar
• Rafaeli, S. (1988). From new media to communication. Sage Annual Review of Communication Research: Advancing Communication Science, 16(1), 110–134.
   Google Scholar
• Rasoolimanesh, S. M., Seyfi, S., Rather, R. A., & Hall, C. M. (2022). Investigating the mediating role of visitor satisfaction in the relationship between memorable tourism experiences and behavioral intentions in heritage tourism context. Tourism Review, 77(2), 687–709. https://doi.org/10.1108/TR-02-2021-0086
   Web of Science ®Google Scholar
• Rather, R. A. (2018). Investigating the impact of customer brand identification on hospitality brand loyalty: A social identity perspective. Journal of Hospitality Marketing & Management, 27(5), 487–513. https://doi.org/10.1080/19368623.2018.1404539
   Web of Science ®Google Scholar
• Rather, R. A. (2019). Consequences of consumer engagement in service marketing: An empirical exploration. Journal of Global Marketing, 32(2), 116–135. https://doi.org/10.1080/08911762.2018.1454995
   Google Scholar
• Rather, R. A. (2021). Demystifying the effects of perceived risk and fear on customer engagement, co-creation and revisit intention during COVID-19: A protection motivation theory approach. Journal of Destination Marketing & Management, 20(6), 1–11. https://doi.org/10.1016/j.jdmm.2021.100564
   Web of Science ®Google Scholar
• Rather, R. A., & Hollebeek, L. D. (2019). Exploring and validating social identification and social exchange-based drivers of hospitality customer loyalty. International Journal of Contemporary Hospitality Management, 31(3), 1432–1451. https://doi.org/10.1108/IJCHM-10-2017-0627
   Web of Science ®Google Scholar
• Rather, R. A., & Hollebeek, L. D. (2021). Customers’ service-related engagement, experience, and behavioral intent: Moderating role of age. Journal of Retailing and Consumer Services, 60, 102453. https://doi.org/10.1016/j.jretconser.2021.102453
   Web of Science ®Google Scholar
• Rather, R. A., Hollebeek, L. D., & Islam, J. U. (2019). Tourism-based customer engagement: The construct, antecedents, and consequences. The Service Industries Journal, 39(7-8), 519–540. https://doi.org/10.1080/02642069.2019.1570154
   Web of Science ®Google Scholar
• Rather, R. A., Hollebeek, L. D., & Rasoolimanesh, S. M. (2022). First-time versus repeat tourism customer engagement, experience, and value cocreation: An empirical investigation. Journal of Travel Research, 61(3), 549–564. https://doi.org/10.1177/0047287521997572
   Web of Science ®Google Scholar
• Raza, A., Rather, R. A., Iqbal, M. K., & Bhutta, U. S. (2020). An assessment of corporate social responsibility on customer company identification and loyalty in banking industry: A PLS-SEM analysis. Management Research Review, 43(11), 1337–1370. https://doi.org/10.1108/MRR-08-2019-0341
   Web of Science ®Google Scholar
• Sahi, G. K., Sekhon, H. S., & Quareshi, T. K. (2016). Role of trusting beliefs in predicting purchase intentions. International Journal of Retail & Distribution Management, 44(8), 860–880. https://doi.org/10.1108/IJRDM-10-2015-0157
   Web of Science ®Google Scholar
• Sharma, A. (2018, November 23). 7 Ways To Increase Trust For Your Chatbot - Chatbots Life. Chatbots Life. https://chatbotslife.com/7-ways-to-increase-trust-for-your-chatbot-19f7be70ead8.
   Google Scholar
• Sheehan, B. T. (2018). Customer service chatbots: Anthropomorphism, adoption and word of mouth (Doctoral dissertationQueensland University of Technology). Queensland University of Technology eThesis Repository. https://eprints.qut.edu.au/121188/1/Benjamin_Sheehan_Thesis.pdf.
   Google Scholar
• Song, M., Xing, X., Duan, Y., Cohen, J., & Mou, J. (2022). Will artificial intelligence replace human customer service? The impact of communication quality and privacy risks on adoption intention. Journal of Retailing and Consumer Services, 66, 102900. https://doi.org/10.1016/j.jretconser.2021.102900
   Web of Science ®Google Scholar
• Song, S. W., & Shin, M. (2022). Uncanny valley effects on chatbot trust, purchase intention, and adoption intention in the context of E-commerce: The moderating role of avatar familiarity. International Journal of Human–Computer Interaction, 1–16. https://doi.org/10.1080/10447318.2022.2121038
   Web of Science ®Google Scholar
• Sundar, S. S., Bellur, S., Oh, J., Jia, H., Kim, H.-S., & Sundar, S. S. (2016). Theoretical importance of contingency in human-computer interaction. Communication Research, 43(5), 595–625. https://doi.org/10.1177/0093650214534962
   Web of Science ®Google Scholar
• Sundar, S. S., Go, E., Kim, H.-S., & Zhang, B. (2015). Communicating art, virtually! psychological effects of technological affordances in a virtual museum. International Journal of Human-Computer Interaction, 31(6), 385–401. https://doi.org/10.1080/10447318.2015.1033912
   Web of Science ®Google Scholar
• Tan, S. M., & Liew, T. W. (2022). Multi-chatbot or single-chatbot? The effects of M-commerce chatbot interface on source credibility, social presence, trust, and purchase intention. Human Behavior and Emerging Technologies, 2022, 1–14. https://doi.org/10.1155/2022/2501538
   Google Scholar
• Toader, D. C., Boca, G., Toader, R., Măcelaru, M., Toader, C., Ighian, D., & Rădulescu, A. T. (2020). The effect of social presence and chatbot errors on trust. Sustainability, 12(1), 256. https://doi.org/10.3390/SU12010256
   Web of Science ®Google Scholar
• Troshani, I., Rao Hill, S., Sherman, C., & Arthur, D. (2021). Do We trust in AI? Role of anthropomorphism and intelligence. Journal of Computer Information Systems, 61(5), 481–491. https://doi.org/10.1080/08874417.2020.1788473
   Web of Science ®Google Scholar
• Tussyadiah, I. P., Zach, F. J., & Wang, J. (2020). Do travelers trust intelligent service robots? Annals of Tourism Research, 81, 102886. https://doi.org/10.1016/j.annals.2020.102886
   Web of Science ®Google Scholar
• van Pinxteren, M. M. E., Wetzels, R. W. H., Rüger, J., Pluymaekers, M., & Wetzels, M. (2019). Trust in humanoid robots: Implications for services marketing. Journal of Services Marketing, 33(4), 507–518. https://doi.org/10.1108/JSM-01-2018-0045
   Web of Science ®Google Scholar
• Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 157–178. https://doi.org/10.2307/41410412
   Web of Science ®Google Scholar
• Venkatesh, V., Thong, J. Y. L., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328. https://doi.org/10.17705/1jais.00428
   Web of Science ®Google Scholar
• Ventre, I., & Kolbe, D. (2020). The impact of perceived usefulness of online reviews, trust and perceived risk on online purchase intention in emerging markets: A Mexican perspective. Journal of International Consumer Marketing, 32(4), 287–299. https://doi.org/10.1080/08961530.2020.1712293
   Web of Science ®Google Scholar
• Vitezić, V., & Perić, M. (2021). Artificial intelligence acceptance in services: Connecting with generation Z. The Service Industries Journal, 41(13–14), 926–946. https://doi.org/10.1080/02642069.2021.1974406
   Web of Science ®Google Scholar
• Wirtz, B. W., Weyerer, J. C., & Geyer, C. (2019a). Artificial intelligence and the public sector—applications and challenges. International Journal of Public Administration, 42(7), 596–615. https://doi.org/10.1080/01900692.2018.1498103
   Web of Science ®Google Scholar
• Wirtz, B. W., Weyerer, J. C., & Rösch, M. (2019b). Open government and citizen participation: An empirical analysis of citizen expectancy towards open government data. International Review of Administrative Sciences, 85(3), 566–586. https://doi.org/10.1177/0020852317719996
   Web of Science ®Google Scholar
• Wirtz, J., Kunz, W., & Paluch, S. (2022). How smart should a service robot be? Journal of Service Research, 25(5), 565. https://doi.org/10.1177/10946705221107704
   Web of Science ®Google Scholar
• Xie, W., Fowler-Dawson, A., & Tvauri, A. (2019). Revealing the relationship between rational fatalism and the online privacy paradox. Behaviour & Information Technology, 38(7), 742–759. https://doi.org/10.1080/0144929X.2018.1552717
   Web of Science ®Google Scholar
• Xin, H., Techatassanasoontorn, A. A., & Tan, F. B. (2015). Antecedents of consumer trust in mobile payment adoption. Journal of Computer Information Systems, 55(4), 1–10. http://doi.org/10.1080/08874417.2015.11645781
   Web of Science ®Google Scholar
• Xu, K., Chen, X., & Huang, L. (2022). Deep mind in social responses to technologies: A new approach to explaining the computers are social actors phenomena. Computers in Human Behavior, 134, 107321. https://doi.org/10.1016/j.chb.2022.107321
   Web of Science ®Google Scholar
• Yen, C., & Chiang, M. C. (2021). Trust me, if you can: A study on the factors that influence consumers’ purchase intention triggered by chatbots based on brain image evidence and self-reported assessments. Behaviour & Information Technology, 40(11), 1177–1194. https://doi.org/10.1080/0144929X.2020.1743362
   Web of Science ®Google Scholar
• Youn, S., & Jin, S. V. (2021). “In A.I. We trust?” The effects of parasocial interaction and technopian versus luddite ideological views on chatbot-based customer relationship management in the emerging “feeling economy”. Computers in Human Behavior, 119(6), 1–13. https://doi.org/10.1016/j.chb.2021.106721
   Web of Science ®Google Scholar
• Yuan, S., Liu, Y., Yao, R., & Liu, J. (2016). An investigation of users’ continuance intention towards mobile banking in China. Information Development, 32(1), 20–34. https://doi.org/10.1177/0266666914522140
   Web of Science ®Google Scholar
• Zarouali, B., van den Broeck, E., Walrave, M., & Poels, K. (2018). Predicting consumer responses to a chatbot on Facebook. Cyberpsychology, Behavior, and Social Networking, 21(8), 491–497. https://doi.org/10.1089/cyber.2017.0518
   PubMed Web of Science ®Google Scholar
• Zhang, J. J., Følstad, A., & Bjørkli, C. A. (2023). Organizational factors affecting successful implementation of chatbots for customer service. Journal of Internet Commerce, 1–35. https://doi.org/10.1080/15332861.2021.1966723
   Web of Science ®Google Scholar
• Zhou, T. (2011). The impact of privacy concern on user adoption of location-based services. Industrial Management & Data Systems, 111(2), 212–226. https://doi.org/10.1108/02635571111115146
   Web of Science ®Google Scholar
• Zierau, N., Engel, C., Söllner, M., & Leimeister, J. M. (2021). Trust in smart personal assistants: A systematic literature review and development of a research agenda. SSRN Electronic Journal, 1–16. https://doi.org/10.2139/ssrn.3920577
   Google Scholar