Abstract
Online personalization presents recommendations of products and services based on customers’ past online purchases or browsing behavior. Personalization applications reduce information overload and provide value-added services. However, their adoption is hindered by customers’ concerns about information privacy. This paper reports on research undertaken to determine whether a high-quality recommendation service will encourage customers to use online personalization. We collected data through a series of online experiments to examine the impacts of privacy and quality on personalization usage and on users’ willingness to pay and to disclose information when using news and financial services. Our findings suggest that under certain circumstances, perceived personalization quality can outweigh the impact of privacy concerns. This implies that service providers can improve the perceived quality of personalization services being offered in order to offset customer privacy concerns. Nevertheless, the impact of perceived quality on personalization usage is weaker for customers who have experienced privacy invasion in the past. The results show that customers who are likely to use online personalization are also likely to pay for the service. This finding suggests that, despite privacy concerns, there is an opportunity for businesses to monetize high-quality personalization.
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References
Adomavicius G and Tuzhilin A (2005) Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17 (6), 734–749.
Andrade EB, Kaltcheva V and Weitz B (2002) Self-disclosure on the web: the impact of privacy policy, reward, and company reputation. Advances in Customer Research 29 (1), 350–353.
Ansari A and Mela CF (2003) E-customization. Journal of Marketing Research 40 (2), 131–145.
Arora N et al (2008) Putting one-to-one marketing to work: personalization, customization, and choice. Marketing Letters 19 (3/4), 305–321.
Awad FN and Krishnan MS (2006) The personalization privacy paradox: an empirical evaluation of information transparency and the willingness to be profiled online for personalization. MIS Quarterly 30 (1), 13–28.
Bailey JE and Pearson SW (1983) Development of a tool measuring and analyzing computer user satisfaction. Management Science 29 (5), 530–544.
Bardakci A and Whitelock J (2004) How ‘ready’ are customers for mass-customization? An exploratory study. European Journal of Marketing 38 (11/12), 1396–1416.
Barnes SJ and Vidgen RT (2002) An integrative approach to the assessment of e-commerce quality. Journal of Electronic Commerce Research 3 (3), 114–127.
Baron RM and Kenny DA (1986) The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology 51 (6), 1173–1182.
Belanger F, Hiller JS and Smith WJ (2002) Trustworthiness in electronic commerce: the role of privacy, security, and site attributes. Journal of Strategic Information Systems 11 (3–4), 245–270.
Benassi P (1999) TRUSTe: an online privacy seal program. Communications of the ACM 42 (2), 56–59.
Blanco CF, Sarasa RG and Sanclemente CO (2010) Effects of visual and textual information in online product presentations: looking for the best combination in website design. European Journal of Information Systems 19 (6), 668–686.
Bollen KA (1989) Structural equations with latent variables. Applied Psychological Measurement 14 (2), 213–215.
Chau PYK, Au G and Tam KY (2000) Impact of information presentation modes on online shopping: an empirical evaluation of a broadband interactive shopping service. Journal of Organizational Computing and Electronic Commerce 10 (1), 1–22.
Chellappa PK and Shivendu S (2010) Mechanism design for ‘free’ but ‘no free disposal’ services: the economics of personalization under privacy concerns. Management Science 56 (10), 1766–1780.
Chellappa RK and Sin RG (2005) Personalization versus privacy: an empirical examination of the online customer's dilemma. Information Technology and Management 6 (2–3), 181–202.
Chin WW (1998) The partial least squares approach to structural equation modeling. In Modern Methods for Business Research (Marcoulides GA, Ed), pp 295–336, Lawrence Erlbaum Associates, Mahway, NJ.
Chin WW, Marcolin BL and Newsted PR (2003) A partial least squares latent variable modeling approach for measuring interaction effects: results from a Monte Carlo simulation study and an electronic-mail emotion/adoption study. Information Systems Research 14 (2), 189–217.
Cohen J (1992) A power primer. Psychological Bulletin 112 (1), 155–159.
Coremetrics (2011) From collaboration to personalization: unlocking the potential of online marketing optimization. Special Report, Bloomberg Business Week Research Services.
Culnan MJ and Bies JR (2003) Consumer privacy: balancing economic and justice considerations. Journal of Social Issues 59 (2), 323–342.
Davis FD (1989) Perceived usefulness, perceived ease of use, and customer acceptance of information technology. MIS Quarterly 13 (3), 319–340.
Delone WH and McLean ER (1992) Information systems success: the quest for the dependent variable. Information Systems Research 3 (1), 60–95.
Dinev T and Hart P (2006) An extended privacy calculus model for e-commerce transactions. Information Systems Research 17 (1), 61–80.
Field A and Hole GJ (2003) How to Design and Report Experiments. Sage Publications, University of Sussex, UK.
Fornell C and Larcker DF (1981) Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research 18 (1), 39–50.
Gefen D, Benbasat I and Pavlou P (2008) A research agenda for trust in online environments. Journal of Management Information Systems 24 (4), 275–286.
Gefen D, Straub DW and Boudreau MC (2000) Structural equation modeling and regression: guidelines for research practice. Communications of the Association for Information Systems 4 (7), 1–77.
Henseler J and Fassott G (2010) Testing moderating effects in PLS path models: an illustration of available procedures. In Handbook of Partial Least Squares (Esposito Vinzi V, Ed), pp 713–735, Springer-Verlag, Berlin Heidelberg.
Ho SY, Bodoff D and Tam KY (2011) Timing of adaptive web personalization and its effects on online consumer behavior. Information Systems Research 22 (3), 660–679.
Ishitani L, Almeida V and Meira JW (2003) Masks: bringing anonymity and personalization together. IEEE Security and Privacy 1 (3), 18–23.
Jahng JJ, Jain H and Ramamurthy K (2002) Personality traits and effectiveness of presentation of product information in e-business systems. European Journal of Information Systems 11 (3), 181–195.
Jarvenpaa SL, Tractinsky N and Vitale M (2000) Customer trust in an internet store. Information Technology and Management 1 (1/2), 45–71.
Junglas IA, Johnson NA and Spitzmuller C (2008) Personality traits and concern for privacy: an empirical study in the context of location-based services. European Journal of Information Systems 17 (4), 387–402.
Kim SS and Son JY (2009) Out of dedication or constraint? A dual model of post-adoption phenomena and its empirical test in the context of online services. MIS Quarterly 33 (1), 49–70.
Knowledge@Wharton (2006) Nowhere to run, nowhere to hide: the online privacy issue. [WWW document] http://knowledge.wharton.upenn.edu/article.cfm?articleid=1437 (accessed 1 September 2011).
Kobsa A (2007) Privacy-enhanced personalization. Communications of the ACM 50 (8), 24–33.
Komiak SYX and Benbasat I (2006) The effects of personalization and familiarity on trust and adoption of recommendation agents. MIS Quarterly 30 (4), 941–960.
Kumar N and Benbasat I (2006) The influence of recommendations and consumer reviews on evaluations of websites. Information Systems Research 17 (4), 425–439.
Liang TP, Lai HJ and Ku YC (2006) Personalized content recommendation and customer satisfaction: theoretical synthesis and empirical findings. Journal of Management Information Systems 23 (3), 45–70.
Liang TP, Yang YF, Chen DN and Ku YC (2008) A semantic-expansion approach to personalized knowledge recommendation. Decision Support Systems 45 (3), 401–412.
Liu FK and Lee HJ (2010) Use of social network information to enhance collaborative filtering performance. Expert Systems with Applications 37 (7), 4772–4778.
Lohr S (2009) Netflix awards $1 million prize and starts a new contest. New York Times 21 September. [WWW document] http://bits.blogs.nytimes.com/2009/09/21/netflix-awards-1-million-prize-and-starts-a-new-contest/ (accessed 1 September 2011).
Madu CN and Madu AA (2002) Dimensions of e-quality. International Journal of Quality and Reliability Management 19 (3), 246–258.
Malhotra NK, Kim SS and Agarwal J (2004) Internet customers’ information privacy concerns (IUIPC): the construct, the scale, and a causal model. Information Systems Research 15 (4), 336–355.
McKinney V and Yoon K (2002) The measurement of web-customer satisfaction: an expectation and disconfirmation approach. Information Systems Research 13 (3), 296–315.
McKnight DH, Choudhury V and Kacmar C (2002) The impact of initial customer trust on intentions to transact with a web site: a trust building model. Journal of Strategic Information Systems 11 (3–4), 297–323.
Miyazaki AD and Krishnamurthy S (2002) Internet seals of approval: effects on online privacy policies and customer perceptions. Journal of Customer Affairs 36 (1), 28–49.
Moores T (2005) Do customers understand the role of privacy seals in e-commerce? Communications of the ACM 48 (3), 86–91.
Moorman C, Zaltman G and Deshpande R (1992) Relationships between providers and users of market research: the dynamics of trust within and between organizations. Journal of Marketing Research 29 (3), 314–328.
Murthi BPS and Sarkar S (2003) The role of the management sciences in research on personalization. Management Science 49 (10), 1344–1362.
Nanou T, Lekakos G and Fouskas K (2010) The effects of recommendations’ presentation on persuasion and satisfaction in a movie recommender system. Multimedia Systems 16 (4/5), 219–230.
Palmisano C, Tuzhilin A and Gorgoglione M (2008) Using context to improve predictive modeling of customers in personalization applications. IEEE Transactions on Knowledge and Data Engineering 20 (11), 1535–1549.
Ribbink D, van Riel ACR, Liljander V and Streukens S (2004) Comfort your online customer: quality, trust and loyalty on the internet. Managing Service Quality 14 (6), 446–456.
Senecal S and Nantel J (2004) The influence of online product recommendations on customers’ online choices. Journal of Retailing 80 (2), 159–169.
Sheng H, Nah F and Siau K (2008) An experimental study on U-commerce adoption: the impact of personalization and privacy concerns. Journal of Associations for Information Systems 9 (6), 344–376.
Sirdeshmukh D, Singh J and Sabol B (2002) Consumer trust, value, and loyalty in relational exchanges. Journal of Marketing 66 (1), 15–37.
Siwicki B (2011) Online sales of full-priced items jump in April. Internet Retailer, 12 May. [WWW document] http://www.internetretailer.com/2011/05/12/online-sales-full-priced-items-jump-april-mybuys-finds (accessed 1 September 2011).
Tam KY and Ho SY (2005) Web personalization as a persuasion strategy: an elaboration likelihood model perspective. Information Systems Research 16 (3), 271–291.
Tam KY and Ho SY (2006) Understanding the impact of web personalization on user information processing and decision outcomes. MIS Quarterly 30 (4), 865–890.
Tsai JY, Egelman S, Cranor L and Acquisti A (2011) The effect of online privacy information on purchasing behavior: an experimental study. Information Systems Research 22 (2), 254–268.
Verma R, Iqbal Z and Plaschka G (2004) Understanding customer choices in e-financial services. California Management Review 46 (4), 43–67.
Vesanen J (2007) What is personalization? A conceptual framework. European Journal of Marketing 41 (5/6), 409–418.
Vesanen J and Raulas M (2006) Building bridges for personalization: a process model for marketing. Journal of Interactive Marketing 20 (1), 5–20.
Westin AF (1967) Privacy and Freedom. Athenaeum, New York.
Wind J and Rangaswamy A (2001) Customerization: the next revolution in mass customization. Journal of Interactive Marketing 15 (1), 13–32.
Xu H, Luo X, Carroll JM and Rosson MB (2011) The personalization privacy paradox: an exploratory study of decision making process for location-aware marketing. Decision Support Systems 51 (1), 42–52.
Yang YH (2010) Web user behavioral profiling for user identification. Decision Support Systems 49 (3), 261–271.
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Li, T., Unger, T. Willing to pay for quality personalization? Trade-off between quality and privacy. Eur J Inf Syst 21, 621–642 (2012). https://doi.org/10.1057/ejis.2012.13
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DOI: https://doi.org/10.1057/ejis.2012.13