The Role of Trusting Beliefs in Voice Assistants during Voice Shopping

Artificial intelligence-based voice assistants (VAs) such as Amazon Alexa deliver personalized product recommendations in order to match consumers’ needs. The use of voice assistants for shopping purposes incorporates elements of risk affecting when and how they are considered trusted relationship partners. In this uncertain environment, it is unclear ‘when’ voice assistants are capable of gaining trust and ‘how’ the development of such a trusted relationship affects decisions. This research explores the effect of trusting beliefs towards voice assistants on decision satisfaction through the indirect effect of consideration set size (n. of options), in the context of voice shopping. Findings of an individual-session online experiment (N = 180) show a positive direct effect of trust on customer’s satisfaction and a mediating role of set size, confirming consumers’ bias towards default choices. This study highlights the consequences of trust in AI-enabled voice assistants for decision-making during utilitarian purchases.

[1]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[2]  Daniel G. Goldstein,et al.  Nudge Your Customers Toward Better Choices , 2008 .

[3]  J. H. Davis,et al.  An Integrative Model Of Organizational Trust , 1995 .

[4]  Eric J. Johnson,et al.  Framing, probability distortions, and insurance decisions , 1993 .

[5]  Izak Benbasat,et al.  Recommendation Agents for Electronic Commerce: Effects of Explanation Facilities on Trusting Beliefs , 2007, J. Manag. Inf. Syst..

[6]  Arun Rai,et al.  Explainable AI: from black box to glass box , 2019, Journal of the Academy of Marketing Science.

[7]  Sophie Ahrens,et al.  Recommender Systems , 2012 .

[8]  Izak Benbasat,et al.  E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact , 2007, MIS Q..

[9]  Irwin P. Levin,et al.  Need for Cognition and Choice Framing Effects , 1996 .

[10]  K. Diehl,et al.  Great Expectations?! Assortment Size, Expectations, and Satisfaction , 2008 .

[11]  A. Herrmann,et al.  Choice Goal Attainment and Decision and Consumption Satisfaction , 2007 .

[12]  Izak Benbasat,et al.  Understanding Customer Trust in Agent-Mediated Electronic Commerce, Web-Mediated Electronic Commerce, and Traditional Commerce , 2004, Inf. Technol. Manag..

[13]  R. Thaler,et al.  Choice Architecture , 2010 .

[14]  Aradhna Krishna,et al.  The Skeptical Shopper: A Metacognitive Account for the Effects of Default Options on Choice , 2004 .

[15]  G. Fitzsimons.  Consumer Response to Stockouts , 2000 .

[16]  Valerie J. Trifts,et al.  Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids , 2000 .

[17]  John G. Lynch,et al.  Smart Agents: When Lower Search Costs for Quality Information Increase Price Sensitivity , 2003 .

[18]  Norman L. Chervany,et al.  What Trust Means in E-Commerce Customer Relationships: An Interdisciplinary Conceptual Typology , 2001, Int. J. Electron. Commer..

[19]  R. Olshavsky,et al.  Consumer Decision Making—Fact or Fiction? , 1979 .

[20]  A. Hayes.  Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach , 2013 .

[21]  R. Oliver.  A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions , 1980 .

[22]  S. Hunt,et al.  The Commitment-Trust Theory of Relationship Marketing , 1994 .

[23]  G. Zaltman,et al.  Factors affecting trust in market research relationships. , 1993 .

[24]  Charles J. Kacmar,et al.  Developing and Validating Trust Measures for e-Commerce: An Integrative Typology , 2002, Inf. Syst. Res..

[25]  Richard H. Thaler,et al.  Design Choices in Privatized Social-Security Systems: Learning from the Swedish Experience , 2004 .

[26]  Jim Sterne,et al.  Artificial Intelligence for Marketing: Practical Applications , 2017 .

[27]  Dhruv Grewal,et al.  How artificial intelligence will change the future of marketing , 2019, Journal of the Academy of Marketing Science.

[28]  Joseph W. Newman,et al.  SATISFACTION/DISSATISFACTION IN THE PURCHASE DECISION PROCESS , 1978 .

[29]  Chris Arney.  Nudge: Improving Decisions about Health, Wealth, and Happiness , 2015 .

[30]  Nick Feamster,et al.  Alexa, Who Am I Speaking To?: Understanding Users’ Ability to Identify Third-Party Apps on Amazon Alexa , 2019, ACM Trans. Internet Techn..

[31]  Catalina L. Toma,et al.  There Are Plenty of Fish in the Sea: The Effects of Choice Overload and Reversibility on Online Daters’ Satisfaction With Selected Partners , 2017 .

[32]  René Algesheimer,et al.  The Evolution of Marketing in the Context of Voice Commerce: A Managerial Perspective , 2020, HCI.

[33]  Asbjørn Følstad,et al.  An Initial Model of Trust in Chatbots for Customer Service - Findings from a Questionnaire Study , 2019, Interact. Comput..

[34]  D. Hoffman,et al.  Relationship journeys in the internet of things: a new framework for understanding interactions between consumers and smart objects , 2018, Journal of the Academy of Marketing Science.

[35]  Detmar W. Straub,et al.  Trust and TAM in Online Shopping: An Integrated Model , 2003, MIS Q..

[36]  Gerhard Friedrich,et al.  Recommender Systems - An Introduction , 2010 .

[37]  Bernd H. Schmitt,et al.  Consumer decisions with artificially intelligent voice assistants , 2020, Marketing Letters.

[38]  Gerald Häubl,et al.  Preference Construction and Persistence in Digital Marketplaces: The Role of Electronic Recommendation Agents , 2001 .

[39]  R. Dhar.  Consumer Preference for a No-Choice Option , 1997 .

[40]  Izak Benbasat,et al.  The Effects of Personalizaion and Familiarity on Trust and Adoption of Recommendation Agents , 2006, MIS Q..

[41]  E. De Bellis,et al.  Autonomous Shopping Systems: Identifying and Overcoming Barriers to Consumer Adoption , 2020, Journal of Retailing.

[42]  Kurt P. Munz,et al.  Not-so Easy Listening: Roots and Repercussions of Auditory Choice Difficulty in Voice Commerce , 2019, SSRN Electronic Journal.

[43]  Antti Oulasvirta,et al.  When more is less: the paradox of choice in search engine use , 2009, SIGIR.

[44]  Efraim Turban,et al.  Effect of personalization on the perceived usefulness of online customer services: a dual-core theory , 2009, ICEC.

[45]  Rita Walczuch,et al.  Psychological antecedents of institution-based consumer trust in e-retailing , 2004, Inf. Manag..

[46]  Andy Field,et al.  Discovering statistics using SPSS: and sex and drugs and rock 'n' roll, 3rd Edition , 2009 .

[47]  Peter Wright.  Consumer Choice Strategies: Simplifying Vs. Optimizing , 1975 .

[48]  W. Goldstein,et al.  Consumer Choice and Autonomy in the Age of Artificial Intelligence and Big Data , 2017, Customer Needs and Solutions.

[49]  William Samuelson,et al.  Status quo bias in decision making , 1988 .

[50]  Eric J. Johnson,et al.  Behavioral decision research: A constructive processing perspective. , 1992 .