AI-based chatbots in customer service and their effects on user compliance

Communicating with customers through live chat interfaces has become an increasingly popular means to provide real-time customer service in many e-commerce settings. Today, human chat service agents are frequently replaced by conversational software agents or chatbots, which are systems designed to communicate with human users by means of natural language often based on artificial intelligence (AI). Though cost- and time-saving opportunities triggered a widespread implementation of AI-based chatbots, they still frequently fail to meet customer expectations, potentially resulting in users being less inclined to comply with requests made by the chatbot. Drawing on social response and commitment-consistency theory, we empirically examine through a randomized online experiment how verbal anthropomorphic design cues and the foot-in-the-door technique affect user request compliance. Our results demonstrate that both anthropomorphism as well as the need to stay consistent significantly increase the likelihood that users comply with a chatbot’s request for service feedback. Moreover, the results show that social presence mediates the effect of anthropomorphic design cues on user compliance.

[1]  Reza Etemad-Sajadi,et al.  The impact of online real-time interactivity on patronage intention: The use of avatars , 2016, Comput. Hum. Behav..

[2]  C. Nass,et al.  How “Real” Are Computer Personalities? , 1996 .

[3]  Mark A. Fuller,et al.  Designing Interfaces with Social Presence: Using Vividness and Extraversion to Create Social Recommendation Agents , 2009, J. Assoc. Inf. Syst..

[4]  John Short,et al.  The social psychology of telecommunications , 1976 .

[5]  Yong Lu,et al.  Mood and social presence on consumer purchase behaviour in C2C E-commerce in Chinese culture , 2012, Electron. Mark..

[6]  Kun Xu,et al.  Persuasive computing: Feeling peer pressure from multiple computer agents , 2017, Comput. Hum. Behav..

[7]  Joseph Weizenbaum,et al.  ELIZA—a computer program for the study of natural language communication between man and machine , 1966, CACM.

[8]  Timothy W. Bickmore,et al.  Establishing and maintaining long-term human-computer relationships , 2005, TCHI.

[9]  J. Freedman,et al.  Compliance without pressure: the foot-in-the-door technique. , 1966, Journal of personality and social psychology.

[10]  C. Nass,et al.  Are People Polite to Computers? Responses to Computer-Based Interviewing Systems1 , 1999 .

[11]  M. Cunningham,et al.  To comply or not comply: testing the self-perception explanation of the "foot-in-the-door" phenomenon. , 1975, Journal of personality and social psychology.

[12]  Sheizaf Rafaeli,et al.  Social Presence: Influence on Bidders in Internet Auctions , 2005, Electron. Mark..

[13]  A. Herrmann,et al.  Direct and indirect effects of self-image congruence on brand loyalty , 2006 .

[14]  Ritu Agarwal,et al.  A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology , 1998, Inf. Syst. Res..

[15]  Jennifer Chu-Carroll,et al.  Building Watson: An Overview of the DeepQA Project , 2010, AI Mag..

[16]  Hugh J. Watson,et al.  Preparing for the Cognitive Generation of Decision Support , 2017, MIS Q. Executive.

[17]  David Gefen,et al.  Managing User Trust in B2C e-Services , 2003 .

[18]  Jay F. Nunamaker,et al.  Predicting Users' Perceived Trust in Embodied Conversational Agents Using Vocal Dynamics , 2012, 2012 45th Hawaii International Conference on System Sciences.

[19]  Eleonora Bilotta,et al.  Shopping with a robotic companion , 2017, Comput. Hum. Behav..

[20]  O. Gadiesh,et al.  Transforming corner-office strategy into frontline action. , 2001, Harvard business review.

[21]  Jay F. Nunamaker,et al.  Design Principles for Special Purpose, Embodied, Conversational Intelligence with Environmental Sensors (SPECIES) Agents , 2011 .

[22]  Arne De Keyser,et al.  “Service Encounter 2.0”: an investigation into the roles of technology, employees and customers , 2017 .

[23]  Nancy Viola Wünderlich,et al.  The Value of Self-Service: Long-Term Effects of Technology-Based Self-Service Usage on Customer Retention , 2015, MIS Q..

[24]  Jerry M. Burger,et al.  The Effect of Fleeting Attraction on Compliance to Requests , 2001 .

[25]  Carrie M. Heilman,et al.  Determinants of Product-Use Compliance Behavior , 2004 .

[26]  Judee K. Burgoon,et al.  Toward an Objective Linguistic-Based Measure of Perceived Embodied Conversational Agent Power and Likeability , 2014, Int. J. Hum. Comput. Interact..

[27]  R. Cialdini Influence: Science and Practice , 1984 .

[28]  Richard H. Smith,et al.  The Effect of a Favor on Public and Private Compliance: How Internalized is the Norm of Reciprocity? , 1999 .

[29]  Alexander Benlian,et al.  Nudging users into digital service solutions , 2019, Electronic Markets.

[30]  D. Bem Self-Perception Theory , 1972 .

[31]  E. S. Knowles,et al.  Approach-Avoidance Model of Persuasion: Alpha and Omega Strategies for Change , 2004 .

[32]  Matthias Söllner,et al.  AI-Based Digital Assistants , 2019, Business & Information Systems Engineering.

[33]  Alexander Benlian,et al.  The impact of sold-out early birds on option selection in reward-based crowdfunding , 2019, Decis. Support Syst..

[34]  S. Chaiken Heuristic versus systematic information processing and the use of source versus message cues in persuasion. , 1980 .

[35]  Chris Janiszewski,et al.  The Influence of Avatars on Online Consumer Shopping Behavior , 2006 .

[36]  Alexander Benlian,et al.  Anthropomorphic Information Systems , 2019, Business & Information Systems Engineering.

[37]  Mary Jo Bitner,et al.  Choosing among Alternative Service Delivery Modes: An Investigation of Customer Trial of Self-Service Technologies , 2005 .

[38]  C. Fornell,et al.  Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics , 1981 .

[39]  Jerry M. Burger,et al.  Increasing compliance by improving the deal: The that's-not-all technique. , 1986 .

[40]  N. Wilkinson,et al.  An Introduction to Behavioral Economics , 2007 .

[41]  Wolfgang Maass,et al.  Editorial: Software Agents , 2010 .

[42]  A. Gustafsson,et al.  The Effects of Customer Satisfaction, Relationship Commitment Dimensions, and Triggers on Customer Retention , 2005 .

[43]  J. Cacioppo,et al.  On seeing human: a three-factor theory of anthropomorphism. , 2007, Psychological review.

[44]  Soojin Jun,et al.  The Use of Voice Input to Induce Human Communication with Banking Chatbots , 2018, HRI.

[45]  A Disrupt-Then-Reframe Technique of Social Influence , 1999 .

[46]  C. Nass,et al.  Are Machines Gender Neutral? Gender‐Stereotypic Responses to Computers With Voices , 1997 .

[47]  Izak Benbasat,et al.  Evaluating Anthropomorphic Product Recommendation Agents: A Social Relationship Perspective to Designing Information Systems , 2009, J. Manag. Inf. Syst..

[48]  Mark P. Zanna,et al.  Narrative Persuasion and Overcoming Resistance. , 2004 .

[49]  Christof Weinhardt,et al.  Designing a robo-advisor for risk-averse, low-budget consumers , 2017, Electronic Markets.

[50]  Izak Benbasat,et al.  A study of demographic embodiments of product recommendation agents in electronic commerce , 2010, Int. J. Hum. Comput. Stud..

[51]  Alexander Benlian,et al.  How pull vs. push information delivery and social proof affect information disclosure in location based services , 2018, Electronic Markets.

[52]  Clifford Nass,et al.  Computers are social actors , 1994, CHI '94.

[53]  Alexander Maedche,et al.  A Taxonomy of Social Cues for Conversational Agents , 2019, Int. J. Hum. Comput. Stud..

[54]  Jonathan E. Butner,et al.  Compliance with a Request in Two Cultures: The Differential Influence of Social Proof and Commitment/Consistency on Collectivists and Individualists , 1999 .

[55]  Abigail Sellen,et al.  "Like Having a Really Bad PA": The Gulf between User Expectation and Experience of Conversational Agents , 2016, CHI.

[56]  Nicole C. Krämer,et al.  "It doesn't matter what you are!" Explaining social effects of agents and avatars , 2010, Comput. Hum. Behav..

[57]  Alexander Benlian,et al.  Mr. and Mrs. Conversational Agent - Gender Stereotyping in Judge-Advisor Systems and the Role of Egocentric Bias , 2019, ICIS.

[58]  B. J. Fogg,et al.  Can computer personalities be human personalities? , 1995, Int. J. Hum. Comput. Stud..

[59]  David F. Larcker,et al.  Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics: , 1981 .

[60]  B. J. Fogg,et al.  Silicon sycophants: the effects of computers that flatter , 1997, Int. J. Hum. Comput. Stud..

[61]  R. Cialdini,et al.  Social influence: Social norms, conformity and compliance. , 1998 .

[62]  C. Nass,et al.  Machines and Mindlessness , 2000 .

[63]  W. R. Ford,et al.  Real conversations with artificial intelligence: A comparison between human-human online conversations and human-chatbot conversations , 2015, Comput. Hum. Behav..

[64]  Clifford Nass,et al.  The media equation - how people treat computers, television, and new media like real people and places , 1996 .

[65]  Claudia Wagner,et al.  Anthropomorphic inferences from emotional nonverbal cues: A case study , 2010, 19th International Symposium in Robot and Human Interactive Communication.

[66]  Scott B. MacKenzie,et al.  Common method biases in behavioral research: a critical review of the literature and recommended remedies. , 2003, The Journal of applied psychology.

[67]  J. Zaichkowsky Measuring the Involvement Construct , 1985 .

[68]  J. Svennevig Getting acquainted in conversation , 1999 .

[69]  Patric R. Spence,et al.  Robots in the classroom: Differences in students' perceptions of credibility and learning between "teacher as robot" and "robot as teacher" , 2016, Comput. Hum. Behav..

[70]  Oliver Hinz,et al.  Investment Decisions with Robo-Advisors: the Role of anthropomorphism and Personalized Anchors in Recommendations , 2019, ECIS.

[71]  M. Deutsch,et al.  A study of normative and informational social influences upon individual judgement. , 1955, Journal of abnormal psychology.

[72]  T. M. Holtgraves,et al.  Perceiving artificial social agents , 2007, Comput. Hum. Behav..

[73]  Eun Go,et al.  Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions , 2019, Comput. Hum. Behav..

[74]  Rajiv Vaidyanathan,et al.  The Wretched Refuse of a Teeming Shore? A Critical Examination of the Quality of Undergraduate Marketing Students , 2007 .

[75]  Tibert Verhagen,et al.  Virtual Customer Service Agents: Using Social Presence and Personalization to Shape Online Service Encounters , 2014, J. Comput. Mediat. Commun..

[76]  B. Weiner,et al.  Spontaneous" causal thinking. , 1985 .

[77]  Alan R. Dennis,et al.  Crossing the Uncanny Valley? Understanding Affinity, Trustworthiness, and Preference for More Realistic Virtual Humans in Immersive Environments , 2019, HICSS.

[78]  Joel Mero,et al.  The effects of two-way communication and chat service usage on consumer attitudes in the e-commerce retailing sector , 2018, Electronic Markets.

[79]  H. Simon,et al.  Invariants of human behavior. , 1990, Annual review of psychology.

[80]  Brett Browning,et al.  Believable Robot Characters , 2011, AI Mag..

[81]  J. Burger The Foot-in-the-Door Compliance Procedure: A Multiple-Process Analysis and Review , 1999, Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc.

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

[83]  Alexander Maedche,et al.  Towards Designing Cooperative and Social Conversational Agents for Customer Service , 2017, ICIS.

[84]  Joseph Weizenbaum,et al.  and Machine , 1977 .

[85]  Justine Cassell,et al.  Negotiated Collusion: Modeling Social Language and its Relationship Effects in Intelligent Agents , 2003, User Modeling and User-Adapted Interaction.

[86]  Theo Araujo,et al.  Living up to the chatbot hype: The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions , 2018, Comput. Hum. Behav..

[87]  Verena Dorner,et al.  Robo-Advisory , 2018, Bus. Inf. Syst. Eng..

[88]  M. Mori THE UNCANNY VALLEY , 2020, The Monster Theory Reader.

[89]  Alexander Benlian,et al.  Mitigating the intrusive effects of smart home assistants by using anthropomorphic design features: A multimethod investigation , 2019, Inf. Syst. J..

[90]  Naphtali Rishe,et al.  I Can Help You Change! An Empathic Virtual Agent Delivers Behavior Change Health Interventions , 2013, TMIS.

[91]  Yongjun Sung,et al.  The roles of spokes-avatars' personalities in brand communication in 3D virtual environments , 2009 .

[92]  Seung-A Annie Jin,et al.  The Roles of Modality Richness and Involvement in Shopping Behavior in 3D Virtual Stores , 2009 .

[93]  R. Cialdini,et al.  Reciprocal Concessions Procedure for Inducing Compliance: The Door-in-the-Face Technique , 1975 .

[94]  Chris Janiszewski,et al.  The Influence of Avatars on Online Consumer Shopping Behavior , 2006 .

[95]  Noah J. Goldstein,et al.  Social influence: compliance and conformity. , 2004, Annual review of psychology.