When recommending a product backfires: The effects of justication and source on user responses to online personalized recommendations

Auteurs

  • Laurie Balbo Montpellier Business School
  • Florence Jeannot INSEEC Business School Laboratoire CERAG - Université de Grenoble Alpes
  • Agnés Helme-Guizon IAE, Université Grenoble Alpes CERAG, CNRS

Mots-clés :

Online personalized recommendation, Justification, Social distance, Construal level, Intrusiveness.

Résumé

Providing users with personalized product or service recommendations has undergone considerable development with the advent of Web 2.0. Recommendations allow websites to convey tailored information to users, but they also contribute to reduce the users’ efforts at searching online. Despite corporate enthusiasm for online personalized recommendations, some previous investigations have demonstrated that this practice requires precautions in order to avoid potential counterproductive effects. This research aims at better understanding the boundaries conditions under which the justification for product recommendations displayed on a website are needed. It compares the effects of justification when a recommendation is issued by the previously navigated website or by a partner website. According to the Construal Level Theory, the navigated website is a proximal source while the partner website is a distal source of recommendation. Through a full-factorial experimental design with 328 participants, this study assesses the interaction between justification (justified vs not-justified) and source (proximal vs distal) of a recommendation. Results reveal that on the one hand a recommendation delivered by a proximal source is more persuasive if the recommendation is justified than if it is not-justified. On the other hand, for a distal source, superior effects are achieved if no justification is provided. Perceived intrusiveness is the underlying mechanism of these effects.

Biographie de l'auteur

Laurie Balbo, Montpellier Business School

Assistant Professor in marketing

Références

Aguirre E , Mahr D , Grewal D , de Ruyter K , Wetzels M (2015), “Unraveling the Personalization Paradox: The Effect of Information Collection and Trust-Building Strategies on Online Advertisement Effectiveness”, Journal of Retailing, vol 91, n°1, p 34-49

Ansari A , Mela C F (2003), “E-Customization”, Journal of Marketing Research, vol 40, n°2, p 131-145

Aron A , Aron E N , Smollan D (1992), “Inclusion of Other in the Self-Scale and the Structure of Interpersonal Closeness”, Journal of Personality and Social Psychology, vol 63, n°4, p 596-612

Awad N F , Krishan M S (2006), “The Personalization Privacy Paradox: an Empirical Evaluation of Information Transparency and the Willingness to be Pro led Online for Personalization”, MIS Quarterly, vol 30, n°1, p 13-26

Ball A , Sawyer A G (2013), “Issues Involving the Use of signi cant Sameness in Testing Replications and Generating Knowledge”, Journal of Business Research, vol 66, n°9, p 1389-1392

Baskin E , Wakslak C J , Trope Y , Novemsky N (2014), “Why Feasibility Matters More to Gift Receivers than Givers: A Construal-Level Approach to Gift Giving”, Journal of Consumer Research, vol 41, n°1, p 169-182

Brehm J W (1966), A Theory of Psychological Reactance, Academic Press, New York, 1966

Breugelmans E , Köhler C F , Dellaert B G C and de Ruyter K (2012), “Promoting Interactive Decision Aids on Retail Websites: A Message Framing Perspective with New Versus Traditional Focal Actions”, Journal of Retailing, vol 88, n°2, p 226-235

Chaudoir S R , Fisher J D (2010), “Disclosure is a Critical Aspect of the Experience of People Who Live with Concealable Stigmatized Identities”, Psychological Bulletin, vol 136, n°2, p 236-256

Choi J, Lee H J , Kim Y C (2011), “The In uence of Social Presence on Customer Intention to Reuse Online Recommender Systems: The Roles of Personalization and Product Type”, International Journal of Electronic Commerce, vol 16, n°1, p 129-154

Dabholkar P A , Sheng X (2012), Consumer participation in using online recommendation agents: Effects on satisfaction, trust, and purchase intentions”, The Service Industries Journal, vol 32, n°9, p 1433-1449

Doorn J , Hoekstra J C (2013), “Customization of Online Advertising: The Role of Intrusiveness”, Marketing Letters, vol 21, n°2, p 1-13

Edwards S M , Li H , Lee J H (2002), “Forced Exposure and Psychological Reactance: Antecedents and Consequences of the Perceived Intrusiveness of Pop-Up Ads”, Journal of Advertising, vol 31, n°3, p 83-95

Ein-Gar D , Levontin L (2013), “Giving from a Distance: Putting the Charitable Organization at the Center of the Donation Appeal”, Journal of Consumer Psychology, vol 23, n°2, p 197-211

Fan H , Poole M S (2006), “What Is Personalization? Perspectives on the Design and Implementation of Personalization in Information Systems”, Journal of Organizational Computing and Electronic Commerce, vol 16, n° 3&4, p 179–202

Fishbein, M , Ajzen, I (1975), Belief, attitude, intention and behavior: An introduction to theory and research Reading, MA: Addison-Wesley

Fisher R J , Ma Y (2014), “The Price of Being Beautiful: Negative Effects of Attractiveness on Empathy for Children in Need”, Journal of Consumer Research, vol 41, n°2, p 436-450

Fitzsimons G J , Lehmann D R (2004), “Reactance to Recommendations: When Unsolicited Advice Yields Contrary Responses”, Marketing Science, vol 23, n°1, p 82-94

Goodman J K , Malkoc S A (2012), “Choosing Here and Now versus There and Later: The Moderating Role of Psychological Distance on Assortment Size Preferences”, Journal of Consumer Research, vol 39, n°4, p 751-768

Ha L (1996), “Observations: Advertising Clutter in Consumer Magazines: Dimensions and Effects”, Journal of Advertising Research, vol 36, n°4, p 76-84

Han Y J , Nunes J C , Drèze X (2010), Signaling Status with Luxury Goods: The Role of Brand Prominence, Journal of Marketing, vol 74, n°4, p 15-30

Häubl G , Murray K B (2003), “Preference Construction and Persistence in Digital Marketplaces: The Role of Electronic Recommendation Agents”, Journal of Consumer Psychology, vol 13, n°1, p 75–91

Hostler R E , Yoon V Y , Guo Z , Guimaraes T , Forgionne G (2011), Assessing the Impact of Recommender Agents on On-Line Consumer Unplanned Purchase Behavior, Information & Management, vol 48, n°8, p 336–343

Iacobucci D , Arabie P , Bodapati A (2000), “Recommendation Agents on the Internet”, Journal of Interactive Marketing, vol 14, n°3, p 2-11

Kankanhalli A , Ye H J , Teo H H (2015), “Comparing Potential and Actual Innovators: An Empirical Study of Mobile Data Services Innovation”, MIS Quarterly, vol 39, n°3, p 667-682

Kim J -Y , Kaufmann K , Stegemann M (2014), “The Impact of Buyer–Seller Relationships and Reference Prices on the Effectiveness of the Pay What You Want Pricing Mechanism”, Marketing Letters, vol 25, n°4, p 409-423

Köhler C F , Breugelmans E , Dellaert B G C (2011), “Consumer Acceptance of Recommendations by Interactive Decision Aids: The Joint Role of Temporal Distance and Concrete versus Abstract Communications”, Journal of Management Information Systems, vol 2, n°4, p 231-260

Lee K T , Noh M J , Koo D M (2013), “Lonely People are No Longer Lonely on Social Networking Sites: The Mediating Role of Self-Disclosure and Social Support”, Cyberpsychology, Behavior and Social Networking, vol 16, n°6, p 413-418

Leavitt N (2006), “Recommendation Technology: Will it Boost e-commerce?”, IEEE Computer Society, vol 39, n° 5, p 13-16

Li H , Edwards, S M , Lee, J -H (2002), “Measuring the Intrusiveness of Advertisements: Scale Development and Validation”, Journal of Advertising, vol 31, n°2, p 37-47

Liberman N , Trope Y (1998), “The Role of Feasibility and Desirability Considerations in Near and Distant Future Decisions: A Test of Temporal Construal Theory”, Journal of Personality and Social Psychology, vol 75, n°1, p 5-18

Liviatan I , Trope Y , Liberman N (2008), “Interpersonal Similarity as a Social Distance Dimension: Implications for Perception of Others’ Actions”, Journal of Experimental Social Psychology, vol 44, n°5, p 1266-1269

Liu W , Gal D (2011), “Bringing Us Together or Driving Us Apart: The Effect of Soliciting Consumer Input on Consumers’ Propensity to Transact with an Organization”, Journal of Consumer Research, vol 38, n°2, p 242-259

Ma Z , Yang Z , Mourali M (2014), “Consumer Adoption of New Product: Independent versus interdependent self-perspectives”, Journal of Marketing, vol 78, n°2, p 101-117

McCoy S , Everard A , Galletta D F , Moody G D (2016), “Here We Go Again! The Impact of Website Ad Repetition on Recall, Intrusiveness, Attitudes, and Site Revisit Intentions”, Information & Management, in press

Montgomery A L , Smith M D (2009), “Prospects for Personalization on the Internet”, Journal of Interactive Marketing, vol 23, n°2, p 130-137

Morimoto M , Chang S (2006), “Consumer’s Attitudes Toward Unsolicited Commercial e-mail and Postal Direct Mail Marketing Methods: Intrusiveness, Perceived Loss of Control, and Irritation”, Journal of Interactive Advertising, vol 7, n°1, p 8-20

Ochi P , Rao S , Takayama L , Nass C (2010), “Predictors of User Perceptions of Web Recommender Systems: How the basis for generating experience and search product recommendations affects user responses”, International Journal of Human-Computer Studies, vol 68, n°8, p 472-482

Preacher K J , Hayes A F (2004), “SPSS and SAS procedures for Estimating Indirect Effects in Simple Mediation Models”, Behavior Research Methods, Instruments, & Computers, vol 36, n°4, p 717-731

Punj G N , Moore R (2007), “Smart versus Knowledgeable Online Recommendation Agents”, Journal of Interactive Marketing, vol 21, n° 4, p 46-60

Simonson I (2005), “Determinants of Customers’ Responses to Customized Offers: Conceptual Framework and Research Propositions”, Journal of Marketing, vol 69, n°1, p 32-45

Sipior J C , Ward B T (1995), “The Ethical and Legal Quandary of email Privacy”, Proceedings of the Association for Computing Machinery, vol 38, n°12, p 48-54

Spassova G , Lee A Y (2013), “Looking Into the Future: A Match between Self-View and Temporal Distance”, Journal of Consumer Research, vol 40, n°1, p 159-171

Sutanto J , Palme E , Tan C -H , Phang C W (2013), “Addressing the personalization–privacy paradox: An empirical assessment from a eld experiment on smartphone users”, MIS Quarterly, vol 37, n°4, p 1141-1164

Swaminathan V (2003), “The Impact of Recommendation Agents on Consumer Evaluation and Choice: The Moderating Role of Category Risk, Product Complexity, and Consumer Knowledge”, Journal of Consumer Psychology, vol 13, n°1/2, p 93-101

Tam K Y , Ho S Y (2006 ), “Understanding the Impact of Web Personalization on User Information Processing and Decision Outcomes”, MIS Quarterly, vol 30, n°4, p 865-890

Trope Y , Liberman N (2010), “Construal-Level Theory of Psychological Distance”, Psychological Review, vol 117, n°2, p 440-463

Tucker C (2012), “The Economics of Advertising and Privacy”, International Journal of Industrial Organization, vol 30, n°3, p 326-329

Tucker C E (2014), “Social Network, Personalized Advertising, and Privacy Control”, Journal of Marketing Research, vol 51, n°5, p 546-562

Vallacher R R , Wegner D M (1987), “What do People Think they’re Doing? Action Identi cation and Human Behavior”, Psychological Review, vol 94, n°1, p 3-15

Venugopal K , Das S , Nagaraju M (2013), “Business Made Easy by Af liate Marketing”, Journal of Business Management and Social Sciences Research, vol 2, n°6, p 50-56

Wang W , Benbasat I (2016), “Empirical Assessment of Alternative Designs for Enhancing Different Types of Trusting Beliefs in Online Recommendation Agents”, Journal of Ma-

nagement Information Systems, vol 33, n°3, p 744-775

Wang W , Benbasat I (2009), “Interactive Decision Aids for Consumer Decision Making in e-Commerce: The In uence of Perceived Strategy Restrictiveness”, MIS Quarterly, vol 33, n°2, p 293-320

Wang W , Benbasat I (2007), “Recommendation Agents for Electronic Commerce: Effects of Explanation Facilities on Trusting Beliefs”, Journal of Management Information Systems, vol 23, n°4, p 217-246

Wang W , Qiu L , Kim D , Benbasat I (2016), “Effects of Rational and Social Appeals of Online Recommendation Agents on Cognitionand Affect-based Trust”, Decision Support Systems, vol 86, n°3, p 48-60

White T B , Zahay D L , Thorbjornsen H and Shavitt S (2008), “Getting Too Personal: Reactance to Highly Personalized Email Solicitations”, Marketing Letters, vol 19, n°1, p 39-50

White K , MacDonnell R , Dahl D W (2011), “It’s The Mindset That Matters: The Role of Construal Level and Message Framing in In uencing Consumer Ef cacy and Conservation Behaviors over the Long-Term”, Journal of Marketing Research, vol 48, n°3, p 472-485

Wright S , Manolis C , Brown D , Guo X , Dinsmore J , Chiu C Y P , Kardes F R (2011), “Construal-Level Mind-Sets and the Perceived Validity of Marketing Claims”, Marketing Letters, vol 23, n°1, p 253-261

Ying L , Korneliussen T , Grønhaug K (2010), “The Effect of Ad Value, Ad Placement and Ad Execution on the Perceived Intrusiveness of Web Advertisements”, International Journal of Advertising, vol 28, n°4, p 623–638

Zhang J , Wedel M (2009), “The Effectiveness of Customized Promotions in Online and Of ine Stores,” Journal of Marketing Research, vol 46, n°2, p 190–206

Zhao M , Xie J (2011), “Effects of Social and Temporal Distance on Consumers’ Responses to Peer Recommendations”, Journal of Marketing Research, vol 48, n°3, p 486-496

Publiée

2017-02-17

Comment citer

Balbo, L., Jeannot, F., & Helme-Guizon, A. (2017). When recommending a product backfires: The effects of justication and source on user responses to online personalized recommendations. Systèmes d’Information Et Management (French Journal of Management Information Systems), 22(2). Consulté à l’adresse https://revuesim.org/index.php/sim/article/view/781

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