Sense and sensibility in personalized e‐commerce: How emotions rebalance the purchase intentions of persuaded customers

This research develops and tests a theoretical model of customer persuasion in personalized online shopping, building on information processing theory, and addressing cognitive and affective stages of the persuasion process. Data from 582 experienced online customers were used to validate the proposed model through structural equation modeling and multigroup analysis. Results show that quality of personalization, message quality, and benefits of the personalized recommendations are important in the persuasion process. Positive emotions increase the effect of persuasion on purchase intentions, contrary to negative emotions. The study extends online personalization theory, offers an in-depth analysis of the persuasion process in online shopping, and provides valuable recommendations for personalized online marketing.

[1]  Michail N. Giannakos,et al.  The interplay of online shopping motivations and experiential factors on personalized e-commerce: A complexity theory approach , 2017, Telematics Informatics.

[2]  Euripidis Loukis,et al.  Editorial of special issue 'Digital Technologies in the Mediterranean Region' , 2017, Telematics Informatics.

[3]  C. Flavián,et al.  The Role of Anticipated Emotions in Purchase Intentions , 2016 .

[4]  Panos E. Kourouthanassis,et al.  Explaining online shopping behavior with fsQCA: The role of cognitive and affective perceptions , 2016 .

[5]  Dawn Iacobucci,et al.  Toward a More Nuanced Understanding of the Statistical Properties of a Median Split , 2015 .

[6]  Boris E. R. de Ruyter,et al.  Personalizing persuasive technologies: Explicit and implicit personalization using persuasion profiles , 2015, Int. J. Hum. Comput. Stud..

[7]  Hsi-Peng Lu,et al.  Persuasive messages, popularity cohesion, and message diffusion in social media marketing , 2015 .

[8]  Gunnar Mau,et al.  Brand Communication Success in Online Consumption Communities: An Experimental Analysis of the Effects of Communication Style and Brand Pictorial Representation , 2015 .

[9]  Tina Kiefer,et al.  Approach or Avoid? Exploring Overall Justice and the Differential Effects of Positive and Negative Emotions , 2014 .

[10]  Naveen Donthu,et al.  The fluent online shopping experience , 2014 .

[11]  P. Aurier,et al.  Using Affect–Expectations Theory to Explain the Direction of the Impacts of Experiential Emotions on Satisfaction , 2014 .

[12]  Yi-Ching Hsieh,et al.  Customer Response to Web Site Atmospherics: Task-relevant Cues, Situational Involvement and PAD , 2014 .

[13]  En-Chung Chang,et al.  Now or later: Delay's effects on post-consumption emotions and consumer loyalty , 2014 .

[14]  Donghyun Kim,et al.  Predicting personal information system adoption using an integrated diffusion model , 2014, Inf. Manag..

[15]  Shuk Ying Ho,et al.  The Effects of Web Personalization on User Attitude and Behavior: An Integration of the Elaboration Likelihood Model and Consumer Search Theory , 2014, MIS Q..

[16]  Nwamaka A. Anaza.  Personality Antecedents of Customer Citizenship Behaviors in Online Shopping Situations , 2014 .

[17]  Michail N. Giannakos,et al.  Shiny happy people buying: the role of emotions on personalized e-shopping , 2014, Electronic Markets.

[18]  Adam D. I. Kramer,et al.  Detecting Emotional Contagion in Massive Social Networks , 2014, PloS one.

[19]  S. Putrevu.  Effects of Mood and Elaboration on Processing and Evaluation of Goal-Framed Appeals , 2014 .

[20]  Dong Hoo Kim,et al.  Gucci versus Old Navy: Interplay of Brand Personality and Regulatory Focus in Advertising Persuasion , 2013 .

[21]  Youjae Yi,et al.  Customer value co-creation behavior: scale development and validation , 2013 .

[22]  Izak Benbasat,et al.  Integrating Service Quality with System and Information Quality: An Empirical Test in the E-Service Context , 2013, MIS Q..

[23]  Viswanath Venkatesh,et al.  Leveraging Digital Technologies: How Information Quality Leads to Localized Capabilities and Customer Service Performance , 2013, MIS Q..

[24]  Debora Viana Thompson,et al.  Consumer-Generated Ads: Does Awareness of Advertising Co-Creation Help or Hurt Persuasion? , 2013 .

[25]  Nancy J. King,et al.  The effect of behavioral tracking practices on consumers' shopping evaluations and repurchase intention toward trusted online retailers , 2013, Comput. Hum. Behav..

[26]  Amélie Marian,et al.  Improving the quality of predictions using textual information in online user reviews , 2013, Inf. Syst..

[27]  K. Scherer,et al.  The GRID meets the wheel: assessing emotional feeling via self-report , 2013 .

[28]  Scott B. MacKenzie,et al.  Common Method Bias in Marketing: Causes, Mechanisms, and Procedural Remedies , 2012 .

[29]  Eva A van Reijmersdal,et al.  Interactivity in Brand Web Sites: Cognitive, Affective, and Behavioral Responses Explained by Consumers’ Online Flow Experience , 2012 .

[30]  Dean Eckles,et al.  Heterogeneity in the Effects of Online Persuasion , 2012 .

[31]  Donghee Yoo,et al.  A hybrid online-product recommendation system: Combining implicit rating-based collaborative filtering and sequential pattern analysis , 2012, Electron. Commer. Res. Appl..

[32]  G. Bodenhausen,et al.  Personalized Persuasion , 2012, Psychological science.

[33]  Ying-Feng Kuo,et al.  Satisfaction and post-purchase intentions with service recovery of online shopping websites: Perspectives on perceived justice and emotions , 2012, Int. J. Inf. Manag..

[34]  Kishore Pillai,et al.  Differential effects of value consciousness and coupon proneness on consumers’ persuasion knowledge of pricing tactics , 2012 .

[35]  Reduce Content or Raise Price? The Impact of Persuasion Knowledge and Unit Price Increase Tactics on Retailer and Product Brand Attitudes , 2011 .

[36]  Tibert Verhagen,et al.  The influence of online store beliefs on consumer online impulse buying: A model and empirical application , 2011, Inf. Manag..

[37]  Kaan Varnali,et al.  Personality Traits and Consumer Behavior in the Mobile Context: A Critical Review and Research Agenda , 2011, Int. J. E Serv. Mob. Appl..

[38]  Narongsak Thongpapanl,et al.  Enhancing Online Performance through Website Content and Personalization , 2011, J. Comput. Inf. Syst..

[39]  Gianfranco Walsh,et al.  Emotions, store-environmental cues, store-choice criteria, and marketing outcomes. , 2011 .

[40]  Mary Beth Rosson,et al.  The personalization privacy paradox: An exploratory study of decision making process for location-aware marketing , 2011, Decis. Support Syst..

[41]  M. Minor,et al.  Aesthetics and the online shopping environment: Understanding consumer responses , 2011 .

[42]  Rebeca San José,et al.  Does involvement matter in online shopping satisfaction and trust , 2011 .

[43]  Vladas Griskevicius,et al.  The Many Shades of Rose-Colored Glasses: An Evolutionary Approach to the Influence of Different Positive Emotions , 2010 .

[44]  Hong-Youl Ha,et al.  Alternative explanations of online repurchasing behavioral intentions: A comparison study of Korean and UK young customers , 2010 .

[45]  Dong-Mo Koo,et al.  The interactional effects of atmospherics and perceptual curiosity on emotions and online shopping intention , 2010, Comput. Hum. Behav..

[46]  Samantha L. Neufeld,et al.  Influence of Different Positive Emotions on Persuasion Processing: a Functional Evolutionary Approach the Traditional Approach: Affect Valence and Cognition Recent Advances: Discrete Emotions and Cognition a New Approach: Functional Definitions of Discrete Positive Emotions Research Overview Study 1 , 2022 .

[47]  Denise J. Luethge,et al.  Toward an integrated framework for online consumer behavior and decision making process: A review , 2010 .

[48]  Brian Sternthal,et al.  Value from Regulatory Construal Fit: The Persuasive Impact of Fit between Consumer Goals and Message Concreteness , 2010 .

[49]  Ritu Agarwal,et al.  Adoption of Electronic Health Records in the Presence of Privacy Concerns: The Elaboration Likelihood Model and Individual Persuasion , 2009, MIS Q..

[50]  Chad R. Mortensen,et al.  Fear and Loving in Las Vegas: Evolution, Emotion, and Persuasion , 2009, JMR, Journal of marketing research.

[51]  Ming-Chi Lee,et al.  Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit , 2009, Electron. Commer. Res. Appl..

[52]  Harri Oinas-Kukkonen,et al.  Persuasive Systems Design: Key Issues, Process Model, and System Features , 2009, Commun. Assoc. Inf. Syst..

[53]  Kun Chang Lee,et al.  Online shopping recommendation mechanism and its influence on consumer decisions and behaviors: A causal map approach , 2008, Expert Syst. Appl..

[54]  Borka Jerman Blažič,et al.  Factors and Sustainable Strategies Fostering the Adoption of Broadband Communications in an Enlarged European Union , 2008 .

[55]  Richard E Petty,et al.  Affective and cognitive meta-bases of attitudes: Unique effects on information interest and persuasion. , 2008, Journal of personality and social psychology.

[56]  Deborah Roedder John,et al.  Consumer response to brand extensions: Construal level as a moderator of the importance of perceived fit , 2008 .

[57]  G. Maio,et al.  Should Persuasion Be Affective or Cognitive? The Moderating Effects of Need for Affect and Need for Cognition , 2008, Personality & social psychology bulletin.

[58]  Shu-Hui Chen,et al.  The role of personality traits and perceived values in persuasion: An elaboration likelihood model perspective on online shopping , 2008 .

[59]  Abigail A. Scholer,et al.  Regulatory Fit and Persuasion: Basic Principles and Remaining Questions , 2008 .

[60]  S. Noar,et al.  Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions. , 2007, Psychological bulletin.

[61]  R. O’Brien,et al.  A Caution Regarding Rules of Thumb for Variance Inflation Factors , 2007 .

[62]  Shuk Ying Ho,et al.  Understanding the Impact of Web Personalization on User Information Processing and Decision Outcomes , 2006, MIS Q..

[63]  Anol Bhattacherjee,et al.  Influence Processes for Information Technology Acceptance: An Elaboration Likelihood Model , 2006, MIS Q..

[64]  J. Peck,et al.  It Just Feels Good: Customers’ Affective Response to Touch and Its Influence on Persuasion: , 2006 .

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

[66]  J. Brockner,et al.  Value from hedonic experience and engagement. , 2006, Psychological review.

[67]  S. Shyam Sundar,et al.  The Psychological Appeal of Personalized Content in Web Portals: Does Customization Affect Attitudes and Behavior? , 2006 .

[68]  Debora Viana Thompson,et al.  The Effects of Information Processing Mode on Consumers' Responses to Comparative Advertising , 2006 .

[69]  David M. Shannon,et al.  Development of a scale to measure the perceived benefits and risks of online shopping , 2006 .

[70]  Shuk Ying Ho,et al.  Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective , 2005, Inf. Syst. Res..

[71]  E. Higgins,et al.  Value From Regulatory Fit , 2005 .

[72]  William J. Doll,et al.  A multi-group analysis of structural invariance: an illustration using the technology acceptance model , 2005, Inf. Manag..

[73]  Yu-Chen Chen,et al.  Extrinsic versus intrinsic motivations for consumers to shop on-line , 2005, Inf. Manag..

[74]  Jon P. Howell,et al.  The impact of societal cultural values and individual social beliefs on the perceived effectiveness of managerial influence strategies: a meso approach , 2004 .

[75]  E. Higgins,et al.  Regulatory fit and persuasion: transfer from "Feeling Right.". , 2004, Journal of personality and social psychology.

[76]  Angela Y. Lee,et al.  Bringing the frame into focus: the influence of regulatory fit on processing fluency and persuasion. , 2004, Journal of personality and social psychology.

[77]  David P Mackinnon,et al.  Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods , 2004, Multivariate behavioral research.

[78]  Duane T. Wegener,et al.  Discrete emotions and persuasion: the role of emotion-induced expectancies. , 2004, Journal of personality and social psychology.

[79]  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.

[80]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[81]  Carol Stoak Saunders,et al.  The Social Construction of Meaning: An Alternative Perspective on Information Sharing , 2003, Inf. Syst. Res..

[82]  Lei-da Chen,et al.  Enticing online consumers: an extended technology acceptance perspective , 2002, Inf. Manag..

[83]  E. Higgins.  Making a good decision: value from fit. , 2000, The American psychologist.

[84]  Joan Meyers-Levy,et al.  Consumers' processing of persuasive advertisements: An integrative framework of persuasion theories , 1999 .

[85]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[86]  Franziska Marquart,et al.  Communication and persuasion : central and peripheral routes to attitude change , 1988 .

[87]  P. Biernacki,et al.  Snowball Sampling: Problems and Techniques of Chain Referral Sampling , 1981 .

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

[89]  W. M. Guire.  7 – Personality and Attitude Change: An Information-Processing Theory , 1968 .