More Than a Bot? The Impact of Disclosing Human Involvement on Customer Interactions with Hybrid Service Agents
References
- (2022) Human vs. automated sales agents: How and why customer responses shift across sales stages. Inform. Systems Res., ePub ahead of print November 10, https://doi.org/10.1287/isre.2022.1171.Link, Google Scholar
- (2020) AI-based chatbots in customer service and their effects on user compliance. Electronic Markets 9(2):1–19.Google Scholar
- AI HLEG (2019) Ethics guidelines for trustworthy AI. Retrieved January 10, 2021, https://ec.europa.eu/futurium/en/ai-alliance-consultation/guidelines.Google Scholar
- (2021) Do customer emotions affect agent speed? An empirical study of emotional load in online customer contact centers. Manufacturing Service Oper. Management 23(4):854–875.Link, Google Scholar
- (2020) Social influence in the retail context: A contemporary review of the literature. J. Retailing 96(1):25–39.Crossref, Google Scholar
- (2010) Balancing IT with the human touch: Optimal investment in IT-based customer service. Inform. Systems Res. 21(3):423–442.Link, Google Scholar
- (2021) The next generation of research on IS use: A theoretical framework of delegation to and from agentic IS artifacts. Management Inform. Systems Quart. 45(1):315–341.Crossref, Google Scholar
- (2020) Toward awareness of human relational strategies in virtual agents. Proc. AAAI Conf. on Artificial Intelligence (AAAI Press, Palo Alto, CA), 2602–2610.Google Scholar
- (1984) Language style as audience design. Language Soc. 13(2):145–204.Crossref, Google Scholar
- (2020) Uniting the tribes: Using text for marketing insight. J. Marketing 84(1):1–25.Crossref, Google Scholar
- (2016) Impression formation and durability in mediated communication. J. Assoc. Inform. Systems 17(9):614–647.Google Scholar
- (2023) Understanding and improving consumer reactions to service bots. J. Consumer Res. Forthcoming. https://doi.org/10.1093/jcr/ucad023.Crossref, Google Scholar
- (2021) The dark side of AI-powered service interactions: Exploring the process of co-destruction from the customer perspective. Service Industry J. 41(13–14):900–925.Crossref, Google Scholar
- (2022) Exploring consumers’ response to text-based chatbots in e-commerce: The moderating role of task complexity and chatbot disclosure. Internet Res. 32(2):496–517.Crossref, Google Scholar
- (2008) Testing mediation and suppression effects of latent variables. Organ. Res. Methods 11(2):296–325.Crossref, Google Scholar
- (1971) Developing a technology of written instruction: Some determiners of the complexity of prose. Rothkopf E, Johnson P, eds. Verbal Learning Research and the Technology of Written Instruction (Teachers College Press, Columbia University, New York), 155–204.Google Scholar
- (2022) Blame the bot: Anthropomorphism and anger in customer–chatbot interactions. J. Marketing 86(1):132–148.Crossref, Google Scholar
- (1996) Consumer evaluations of new technology-based self-service options: An investigation of alternative models of service quality. Internat. J. Res. Marketing 13(1):29–51.Crossref, Google Scholar
- (2019) Frontline service technology infusion: Conceptual archetypes and future research directions. J. Service Management 30(1):156–183.Crossref, Google Scholar
- (2015) Algorithm aversion: People erroneously avoid algorithms after seeing them err. J. Experiment. Psych. General 144(1):114–126.Crossref, Google Scholar
- (2019) A taxonomy of social cues for conversational agents. Internat. J. Human Comput. Stud. 132:138–161.Crossref, Google Scholar
- (1975) Public and private self-consciousness: Assessment and theory. J. Consulting Clinical Psych. 43(4):522–527.Crossref, Google Scholar
- (2018) What makes users trust a chatbot for customer service? An exploratory interview study. Proc. 5th Internat. Conf. on Internet Sci. (Springer, Cham, Switzerland), 194–208.Google Scholar
- Forbes (2020) Artificial or human intelligence? Companies faking AI. Retrieved January 10, 2021, https://www.forbes.com/sites/cognitiveworld/2020/04/04/artificial-or-human-intelligence-companies-faking-ai.Google Scholar
- (2022) Cognitive challenges in human–artificial intelligence collaboration: Investigating the path toward productive delegation. Inform. Systems Res. 33(2):678–696.Link, Google Scholar
- (2020) Human trust in artificial intelligence: Review of empirical research. Acad. Management Ann. 14(2):627–660.Crossref, Google Scholar
- (2022) Opposing effects of response time in human–chatbot interaction. Bus. Inform. Systems Engrg. 64(6):773–791.Crossref, Google Scholar
- (2019) Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions. Comput. Human Behav. 97:304–316.Crossref, Google Scholar
- (2001) Development and validation of the situational self-awareness scale. Conscious Cognition 10(3):366–378.Crossref, Google Scholar
- (2021) Mental models and expectation violations in conversational AI interactions. Decision Support Systems 144:113515.Crossref, Google Scholar
- (2022) Bots with feelings: Should AI agents express positive emotion in customer service? Inform. Systems Res., ePub ahead of print December 2, https://doi.org/10.1287/isre.2022.1179.Link, Google Scholar
- (2015) Real conversations with artificial intelligence: A comparison between human-human online conversations and human-chatbot conversations. Comput. Human Behav. 49:245–250.Crossref, Google Scholar
- (2022) Chatbots and service failure: When does it lead to customer aggression. J. Retailing Consumer Services 68:103044.Crossref, Google Scholar
- (1994) Identification and estimation of local average treatment effects. Econometrica 62(2):467–475.Crossref, Google Scholar
- (2021) Editorial for the special section on humans, algorithms, and augmented intelligence: The future of work, organizations, and society. Inform. Systems Res. 32(3):675–687.Link, Google Scholar
- (2021) Augmenting medical diagnosis decisions? An investigation into physicians’ decision-making process with artificial intelligence. Inform. Systems Res. 32(3):713–735.Link, Google Scholar
- (2016) Inferring capabilities of intelligent agents from their external traits. ACM Trans. Interactive Intelligence Systems 6(4):1–25.Crossref, Google Scholar
- (2012) Does the web reduce customer service cost? Empirical evidence from a call center. Inform. Systems Res. 23(3):721–737.Link, Google Scholar
- (1990) Impression management: A literature review and two-component model. Psych. Bull. 107(1):34–47.Crossref, Google Scholar
- (2019) Frontiers: Machines vs. humans: The impact of artificial intelligence chatbot disclosure on customer purchases. Marketing Sci. 38(6):913–1084.Google Scholar
- (2021) Algorithmic management of work on online labor platforms: When matching meets control. Management Inform. Systems Quart. 45(4):1999–2022.Crossref, Google Scholar
- (2017) The media inequality: Comparing the initial human-human and human-AI social interactions. Comput. Human Behav. 72:432–440.Crossref, Google Scholar
- (2022) Trust me, I’m a bot: Repercussions of chatbot disclosure in different service frontline settings. J. Service Management 33(2):221–245.Crossref, Google Scholar
- (2015) Linguistic inquiry and word count. Accessed August 21, 2020, www.LIWC.net.Google Scholar
- (2019) Editor’s comments: Next-generation digital platforms: Toward human–AI hybrids. Management Inform. Systems Quart. 43(1):iii–ix.Google Scholar
- (2020) Frontline encounters of the AI kind: An evolved service encounter framework. J. Bus. Res. 116:366–376.Crossref, Google Scholar
- (2012) lavaan: An R package for structural equation modeling. J. Statist. Software 48(2):1–36.Crossref, Google Scholar
- (2021) Estimating the impact of “humanizing” customer service chatbots. Inform. Systems Res. 32(3):736–751.Link, Google Scholar
- (2021) Deciding whether and how to deploy chatbots. MIS Q. Executive 20(1):1–15.Crossref, Google Scholar
- (2003) Media inequality in conversation: How people behave differently when interacting with computers and people. Proc. CHI Conf. on Human Factors in Comput. Systems (Association for Computing Machinery, New York), 281–288.Google Scholar
- State of California (2018) Senate Bill No. 1001. Chapter 89. Retrieved January 10, 2021, https://leginfo.legislature.ca.gov/faces/billTextClient.xhtml?bill_id=201720180SB1001.Google Scholar
- (2014) The influences of online service technologies and task complexity on efficiency and personalization. Inform. Systems Res. 25(2):420–436.Link, Google Scholar
- (2019) Audience design in multiparty conversation. Cognition Sci. 43(8):1–28.Google Scholar
- (1993) Children’s linguistic choices: Audience design and societal norms. Language Soc. 22(2):257–274.Crossref, Google Scholar
- (2010) Reconsidering Baron and Kenny: Myths and truths about mediation analysis. J. Consumer Res. 37(2):197–206.Crossref, Google Scholar

