Birds of a feather flock together: matched personality effects of product recommendation chatbots and users

PurposeAI-driven product recommendation chatbots have markedly reduced operating costs and increased sales for marketers. However, previous literature has paid little attention to the effects of the personality of e-commerce chatbots. This study aimed to examine the ways that the interplay between the chatbot's and the user's personality can increase favorable product attitudes and future intentions to use the chatbot. Based on prior literature, we specifically focused on the degree of extroversion of both chatbot and user.Design/methodology/approachA total of 291 individuals participated in this study. Two different versions of chatbot were created for this study (i.e. extroversion: high vs. low). Participants self-reported their degree of extroversion. The PROCESS macro Model 1 and Model 7 with the Johnson–Neyman technique were employed to test the hypotheses.FindingsThe results showed that the high extroversion chatbot elicited greater user satisfactions and perceptions of chatbot friendliness among users with a high level of extroversion. On the contrary, the low extroversion chatbot resulted in greater user satisfactions and perceived chatbot friendliness among users with a low level of extroversion. This study further found that user satisfactions and perceived chatbot friendliness mediated the effects of the chatbot on greater intentions to use the chatbot and more favorable product attitudes.Originality/valueBy showing the effects of matching the personality of the chatbot and user, this study revealed that similarity-attraction effects also apply to human–chatbot interaction in e-commerce. Future studies would benefit by investigating the similarity-attraction effects in different characteristics, such as appearance, opinion and preference. This study also provides useful information for e-commerce marketers and chatbot UX/UI designers.

[1]  Weng Marc Lim,et al.  From direct marketing to interactive marketing: a retrospective review of the Journal of Research in Interactive Marketing , 2022, Journal of Research in Interactive Marketing.

[2]  Jamye K. Foster,et al.  Brand avatars: impact of social interaction on consumer–brand relationships , 2021, Journal of Research in Interactive Marketing.

[3]  Hyunjin Kang,et al.  Bots vs. humans: how schema congruity, contingency-based interactivity, and sympathy influence consumer perceptions and patronage intentions , 2021, International Journal of Advertising.

[4]  C. Chuan,et al.  How chatbots' social presence communication enhances consumer engagement: the mediating role of parasocial interaction and dialogue , 2021, Journal of Research in Interactive Marketing.

[5]  C. Wang.  New frontiers and future directions in interactive marketing: Inaugural Editorial , 2021, Journal of Research in Interactive Marketing.

[6]  Sara H. Hsieh,et al.  Hey Alexa: examining the effect of perceived socialness in usage intentions of AI assistant-enabled smart speaker , 2021, Journal of Research in Interactive Marketing.

[7]  Rajat Roy,et al.  Enhancing chatbot effectiveness: The role of anthropomorphic conversational styles and time orientation , 2021 .

[8]  R. Petty,et al.  A Review and Conceptual Framework for Understanding Personalized Matching Effects in Persuasion , 2020, Journal of Consumer Psychology.

[9]  Yang Cheng,et al.  How Do AI-driven Chatbots Impact User Experience? Examining Gratifications, Perceived Privacy Risk, Satisfaction, Loyalty, and Continued Use , 2020, Journal of Broadcasting & Electronic Media.

[10]  Ayşe Barış.  A NEW BUSINESS MARKETING TOOL: CHATBOT , 2020 .

[11]  Eunju Ko,et al.  Chatbot e-service and customer satisfaction regarding luxury brands , 2020 .

[12]  Itai Himelboim,et al.  Introducing a Model of Automated Brand-Generated Content in an Era of Computational Advertising , 2020, Journal of Advertising.

[13]  Jiang Yun,et al.  I, Chatbot: Modeling the determinants of users' satisfaction and continuance intention of AI-powered service agents , 2020, Telematics Informatics.

[14]  M. G. Perrucci,et al.  Sense or sensibility? The neuro-functional basis of the structural matching effect in persuasion , 2020, Cognitive, Affective, & Behavioral Neuroscience.

[15]  Peter A. M. Ruijten.  The similarity-attraction paradigm in persuasive technology: effects of system and user personality on evaluations and persuasiveness of an interactive system , 2020, Behav. Inf. Technol..

[16]  Naoyuki Kubota,et al.  Self-Adapting Chatbot Personalities for Better Peer Support , 2019, 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC).

[17]  Kun Xu,et al.  A Systematic Review of the Personality of Robot: Mapping Its Conceptualization, Operationalization, Contextualization and Effects , 2019, Int. J. Hum. Comput. Interact..

[18]  Karolien Poels,et al.  Chatbot advertising effectiveness: When does the message get through? , 2019, Comput. Hum. Behav..

[19]  Marco Aurélio Gerosa,et al.  How Should My Chatbot Interact? A Survey on Social Characteristics in Human–Chatbot Interaction Design , 2019, Int. J. Hum. Comput. Interact..

[20]  David Baxter,et al.  Chatbots and Gender Stereotyping , 2019, Interact. Comput..

[21]  Xialing Lin,et al.  Evaluations of an artificial intelligence instructor's voice: Social Identity Theory in human-robot interactions , 2019, Comput. Hum. Behav..

[22]  Bingjie Liu,et al.  Should Machines Express Sympathy and Empathy? Experiments with a Health Advice Chatbot , 2018, Cyberpsychology Behav. Soc. Netw..

[23]  Zeynep Cemalcilar,et al.  Role of personality traits in first impressions: An investigation of actual and perceived personality similarity effects on interpersonal attraction across communication modalities, , 2018, Journal of Research in Personality.

[24]  Alessandro Vinciarelli,et al.  Do We Really Like Robots that Match our Personality? The Case of Big-Five Traits, Godspeed Scores and Robotic Gestures , 2018, 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN).

[25]  Adam J. Hampton,et al.  You’re like me and I like you: Mediators of the similarity–liking link assessed before and after a getting-acquainted social interaction , 2018, Journal of Social and Personal Relationships.

[26]  Lionel Robert,et al.  Personality in the Human Robot Interaction Literature: A Review and Brief Critique , 2018, AMCIS.

[27]  Seunga Venus Jin,et al.  "Narcissism 2.0! Would narcissists follow fellow narcissists on Instagram?" the mediating effects of narcissists personality similarity and envy, and the moderating effects of popularity , 2018, Comput. Hum. Behav..

[28]  Dong Liu,et al.  The Big Five personality traits, Big Two metatraits and social media: A meta-analysis , 2017 .

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

[30]  Dan Nathan-Roberts,et al.  Personality Measurement and Design in Human-Robot Interaction: A Systematic and Critical Review , 2017 .

[31]  Junho Choi,et al.  Enhancing user experience with conversational agent for movie recommendation: Effects of self-disclosure and reciprocity , 2017, Int. J. Hum. Comput. Stud..

[32]  D. Wegener,et al.  Attitude similarity and attraction: Validation, positive affect, and trust as sequential mediators , 2017 .

[33]  H. A. Schwartz,et al.  Birds of a Feather Do Flock Together , 2017, Psychological science.

[34]  S. Gaur,et al.  Does buyer–seller similarity affect buyer satisfaction with the seller firm? , 2012 .

[35]  Brian Scassellati,et al.  The similarity-attraction effect in human-robot interaction , 2010, 2010 IEEE 9th International Conference on Development and Learning.

[36]  W. Ickes,et al.  Big Five predictors of behavior and perceptions in initial dyadic interactions: personality similarity helps extraverts and introverts, but hurts "disagreeables". , 2009, Journal of personality and social psychology.

[37]  Jaap J. A. Denissen,et al.  In the eye of the beholder: perceived, actual, and peer-rated similarity in personality, communication, and friendship intensity during the acquaintanceship process. , 2009, Journal of personality and social psychology.

[38]  Marilyn A. Walker,et al.  Using Linguistic Cues for the Automatic Recognition of Personality in Conversation and Text , 2007, J. Artif. Intell. Res..

[39]  D. Barelds,et al.  Love at first sight or friends first? Ties among partner personality trait similarity, relationship onset, relationship quality, and love , 2007 .

[40]  Zsolt Ugray,et al.  Looking at human-computer interface design: Effects of ethnicity in computer agents , 2007, Interact. Comput..

[41]  K. M. Lee,et al.  Can robots manifest personality? : An empirical test of personality recognition, social responses, and social presence in human-robot interaction , 2006 .

[42]  Caren B. Goldberg.  Relational Demography and Similarity-Attraction in Interview Assessments and Subsequent Offer Decisions , 2005 .

[43]  Hock-Hai Teo,et al.  An empirical study of the effects of interactivity on web user attitude , 2003, Int. J. Hum. Comput. Stud..

[44]  James Kalbach.  Persuasive technology: using computers to change what we think and do , 2002, UBIQ.

[45]  D. Schmitt.  Personality, attachment and sexuality related to dating relationship outcomes: contrasting three perspectives on personal attribute interaction. , 2002, The British journal of social psychology.

[46]  Murray R. Barrick,et al.  An investigation of personality similarity effects (relational and perceived) on peer and supervisor ratings and the role of familiarity and liking , 2001 .

[47]  Anol Bhattacherjee,et al.  Understanding Information Systems Continuance: An Expectation-Confirmation Model , 2001, MIS Q..

[48]  C. Nass,et al.  Does computer-synthesized speech manifest personality? Experimental tests of recognition, similarity-attraction, and consistency-attraction. , 2001, Journal of experimental psychology. Applied.

[49]  Clifford Nass,et al.  Consistency of personality in interactive characters: verbal cues, non-verbal cues, and user characteristics , 2000, Int. J. Hum. Comput. Stud..

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

[51]  Clifford Nass,et al.  Perceptual user interfaces: perceptual bandwidth , 2000, CACM.

[52]  J. Pennebaker,et al.  Linguistic styles: language use as an individual difference. , 1999, Journal of personality and social psychology.

[53]  Peter B. Seddon.  A Respecification and Extension of the DeLone and McLean Model of IS Success , 1997, Inf. Syst. Res..

[54]  B. J. Fogg,et al.  Can computers be teammates? , 1996, Int. J. Hum. Comput. Stud..

[55]  R. Petty,et al.  Measuring the Affective and Cognitive Properties of Attitudes: Conceptual and Methodological Issues , 1994 .

[56]  R. Batra,et al.  Measuring the hedonic and utilitarian sources of consumer attitudes , 1991 .

[57]  W. Crano,et al.  Inferred evaluation and the relation between attitude similarity and interpersonal attraction. , 1988 .

[58]  Mark P. Zanna,et al.  Attitude and activity preference similarity: Differential bases of interpersonal attraction for low and high self-monitors. , 1987 .

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

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

[61]  J. J. Seta,et al.  Effects of contrast and generalization on the attitude similarity–attraction relationship. , 1979 .

[62]  David T. Wilson,et al.  An Experimental Analysis of a Salesman's Expert and Referent Bases of Social Power in the Buyer-Seller Dyad , 1976 .

[63]  C. Berger,et al.  SOME EXPLORATIONS IN INITIAL INTERACTION AND BEYOND: TOWARD A DEVELOPMENTAL THEORY OF INTERPERSONAL COMMUNICATION , 1975 .

[64]  J. Geer.  A test of the classical conditioning model of emotion: the use of nonpainful aversive stimuli as unconditioned stimuli in a conditioning procedure. , 1968, Journal of personality and social psychology.

[65]  F. Evans,et al.  Selling as a Dyadic Relationship – A New Approach , 1963 .

[66]  C. Izard,et al.  Personality similarity and friendship. , 1960, Journal of abnormal and social psychology.

[67]  Robert F. Winch,et al.  Mate-Selection: A Study of Complementary Needs , 1959 .

[68]  Ischen,et al.  UvA-DARE (Digital to Assist You Today”: The Role of Entity, Interactivity and Experiential Perceptions in Chatbot Persuasion , 2021 .

[69]  Amon Rapp,et al.  The human side of human-chatbot interaction: A systematic literature review of ten years of research on text-based chatbots , 2021, Int. J. Hum. Comput. Stud..

[70]  A. Czarna,et al.  Personality and Friendships , 2019, Encyclopedia of Personality and Individual Differences.

[71]  Brandon Brown,et al.  I just text to say I love you: Partner similarity in texting and relationship satisfaction , 2018, Comput. Hum. Behav..

[72]  L. R. Goldberg.  THE DEVELOPMENT OF MARKERS FOR THE BIG-FIVE FACTOR STRUCTURE , 1992 .

[73]  J. Touhey.  Comparison of two dimensions of attitude similarity on heterosexual attraction. , 1972 .

[74]  R. Hogan.  An Extension of the Similarity-Attraction Hypothesis to the Study of Vocational Behavior. , 1972 .

[75]  G. Clore,et al.  A reinforcement model of evaluative responses. , 1970 .

[76]  D. Byrne,et al.  Similarity and awareness of similarity of personality characteristics as determinants of attraction. , 1969 .