Designing for Diagnosticity and Serendipity: An Investigation of Social Product-Search Mechanisms

References

• Adomavicius G, Tuzhilin A (2005) Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Trans. Knowledge Data Engrg. 17(6):734–749.Crossref, Google Scholar
• Adomavicius G, Bockstedt JC, Shawn PC, Zhang J (2013) Do recommender systems manipulate consumer preferences? A study of anchoring effects. Inform. Systems Res. 24(4):956–975.Link, Google Scholar
• Agarwal NK (2015) Towards a definition of serendipity in information behaviour. Inform. Res. 20(3):Paper 675.Google Scholar
• Ames M, Naaman M (2007) Why we tag: Motivations for annotation in mobile and online media. Proc. SIGCHI Conf. Human Factors Comput. Systems (ACM, New York), 971–980.Crossref, Google Scholar
• Andel PV (1994) Anatomy of the unsought finding. Serendipity: Origin, history, domains, traditions, appearances, patterns and programmability. British J. Philos. Sci. 45(2):631–648.Crossref, Google Scholar
• Ashman H, Brailsford T, Cristea AI, Sheng QZ, Stewart C, Toms EG, Wade V (2014) The ethical and social implications of personalization technologies for e-learning. Inform. Management 51(6):819–832.Crossref, Google Scholar
• Banerjee AV (1992) A simple model of herd behavior. Quart. J. Econom. 107(3):797–817.Crossref, Google Scholar
• Barclay D, Thompson R, Higgins C (1995) The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration. Tech. Stud. 2(2):285–309.Google Scholar
• Berry J, Keller E (2003) The Influentials: One American in Ten Tells the Other Nine How to Vote, Where to Eat, and What to Buy (Free Press, New York).Google Scholar
• Biel JI, Gatica-Perez D (2009) Wearing a YouTube hat: Directors, comedians, gurus, and user aggregated behavior. Proc. 17th ACM Internat. Conf. Multimedia (ACM, New York), 833–836.Crossref, Google Scholar
• Browne GJ, Pitts MG, Wetherbe JC (2007) Cognitive stopping rules for terminating information search in online task. MIS Quart. 31(1):89–104.Crossref, Google Scholar
• Burt RS (1999) The social capital of opinion leaders. Ann. Amer. Acad. Political Soc. Sci. 566(1):37–54.Crossref, Google Scholar
• Canini KR, Suh B, Pirolli P (2011) Finding credible information sources in social networks based on content and social structure. Third IEEE Internat. Conf. Soc. Comput., Boston.Crossref, Google Scholar
• Chaiken S (1987) The heuristic model of persuasion. Zanna MP, Olsen JM, Herman CP, eds. Social Influence: The Ontario Symposium, Vol. 5 (Lawrence Erlbaum, Hillsdale, NJ), 3–39.Google Scholar
• Chi EH (2009) Information seeking can be social. Computer 42(3): 42–46.Crossref, Google Scholar
• Choi B, Jiang Z, Xiao B, Kim S (2015) Embarrassing exposures in online social networks: An integrated perspective of relationship bonding and privacy invasion. Inform. Systems Res. 26(4):675–694.Link, Google Scholar
• Cohen J (1988) Statistical Power Analysis for the Behavioral Sciences (Lawrence Erlbaum, Hillsdale, NJ).Google Scholar
• David P, Song M, Hayes A, Fredin ES (2007) A cyclic model of information seeking in hyperlinked environment: The role of goals, self-efficacy, and intrinsic motivation. Internat. J. Human-Comput. Stud. 65(2):170–182.Crossref, Google Scholar
• Dew N (2009) Serendipity in entrepreneurship. Organ. Stud. 30(7): 735–753.Crossref, Google Scholar
• Evans B, Chi E (2008) Towards a model of understanding social search. Proc. 2008 ACM Comput. Supported Cooperative Work (CSCW) (ACM, New York), 485–494.Crossref, Google Scholar
• Fang X, Hu PJH, Chau M, Hu HF, Yang Z, Sheng ORL (2012) A data-driven approach to measure Web site navigability. J. Management Inform. Systems 29(2):173–212.Crossref, Google Scholar
• Foster A, Ford N (2003) Serendipity and information seeking: An empirical study. J. Documentation 59(3):321–340.Crossref, Google Scholar
• Franke N, Hippel EV, Schreier M (2006) Finding commercially attractive user innovation: A test of lead-user theory. J. Product Innovation Management 23(4):301–315.Crossref, Google Scholar
• Fu WT (2008) The microstructures of social tagging: A rational model. Proc. 2008 ACM Comput. Supported Cooperative Work (ACM, New York), 229–238.Crossref, Google Scholar
• Giraldeau L-A, Caraco T (2000) Social Foraging Theory (Princeton University Press, Princeton, NJ).Crossref, Google Scholar
• Gladwell M (2002) The Tipping Point: How Little Things Can Make a Big Difference (Little, Brown and Company, Boston).Google Scholar
• Goes P, Lin M, Yeung CA (2014) “Popularity effect” in user-generated content. Inform. Systems Res. 25(2):222–238.Link, Google Scholar
• Goldenberg J, Oestreicher-Singer G, Reichman S (2012) The quest for content: How user-generated links can facilitate online exploration. J. Marketing Res. 49(4):452–468.Crossref, Google Scholar
• Golder SA, Huberman BA (2006) Usage patterns of collaborative tagging systems. J. Inform. Sci. 32(2):198–208.Crossref, Google Scholar
• Golin M (1957) Serendipity—Big word in medical progress. J. Amer. Medical Assoc. 165(16):2084–2087.Crossref, Google Scholar
• Graebner ME (2004) Momentum and serendipity: How acquired leaders create value in the integration of technology firms. Strategic Management J. 25(8–9):751–777.Crossref, Google Scholar
• Gray PH, Parise S, Iyer B (2011) Innovative impacts of using social bookmarking systems. MIS Quart. 35(3):629–643.Crossref, Google Scholar
• Gupta M, Li R, Yin Z, Han J (2011) An overview of social tagging and applications. Aggarwal C, ed. Social Network Data Analytics (Springer, New York), 447–497.Crossref, Google Scholar
• Haubl G, Trift V (2000) Consumer decision making in online shopping environments: The effects of interactive decision aids. Marketing Sci. 19(1):4–21.Link, Google Scholar
• Hayes AF (2013) Introduction to Mediation, Moderation and Conditional Process Analysis (Guilford Press, New York).Google Scholar
• Herlocker JL, Konstan JA, Terveen LG, Riedl JT (2004) Evaluating collaborative filtering recommender systems. ACM Trans. Inform. Systems 22(1):5–53.Crossref, Google Scholar
• Ho SY, Bodoff D (2014) The effects of Web personalization on user attitude and behavior: An integration of the elaboration likelihood model and consumer search theory. MIS Quart. 38(2): 497–520.Crossref, Google Scholar
• Iyengar R, Van den Bulte C, Valente TW (2011) Opinion leadership and social contagion in new product diffusion. Marketing Sci. 30(2):195–212.Link, Google Scholar
• Jiang Z, Benbasat I (2004) Virtual product experience: Effects of visual and functional control on perceived diagnosticity in electronic shopping. J. Management Inform. Systems 21(3):111–147.Crossref, Google Scholar
• Johnson EJ, Moe WW, Fader PS, Bellman S, Lohse GL (2004) On the depth and dynamics of online search behavior. Management Sci. 50(3):299–308.Link, Google Scholar
• Kamis A, Koufaris M, Stern T (2008) Using an attribute-based DSS for user-customized products online: An experimental investigation. MIS Quart. 32(1):159–177.Crossref, Google Scholar
• Katz MA, Byrne MD (2003) Effects of scent and breadth on use of site-specific search on e-commerce websites. ACM Trans. Comput.-Human Interaction 10(3):198–220.Crossref, Google Scholar
• Kempf DS, Smith RE (1998) Consumer processing of product trial and the influence of prior advertising: A structural modeling approach. J. Marketing Res. 35(3):325–338.Crossref, Google Scholar
• Kim J (2009) Describing and predicting information-seeking behavior on the Web. J. Amer. Soc. Inform. Sci. Tech. 60(4):679–693.Crossref, Google Scholar
• Klein DE (2008) The loss of serendipity in psychopharmacology. J. Amer. Medical Assoc. 299(9):1063–1065.Crossref, Google Scholar
• Kratzer J, Lettl C (2009) The distinctive role of lead users and opinion leaders in the social networks of schoolchildren. J. Consumer Res. 36(4):646–659.Crossref, Google Scholar
• Krug S (2006) Don’t Make Me Think: A Common Sense Approach to the Web Usability, 2nd ed. (New Riders Publishing, Thousand Oaks, CA).Google Scholar
• Larson K, Czerwinski M (1998) Web page design: Implications of memory, structure and scent for information retrieval. Proc. SIGCHI Conf. Human Factors Comput. Systems (ACM, New York), 25–32.Crossref, Google Scholar
• Lawrance J, Bellamy R, Burnett M (2007) Scents in programs: Does information foraging theory apply to program maintenance? Proc. IEEE Sympos. Visual Languages Human-Centric Comput., Coeur d’Alène, Idaho, 15–22.Crossref, Google Scholar
• Lawrance J, Burnett M, Bellamy R, Bogart C, Swart C (2010) Reactive information foraging for evolving goals. Proc. SIGCHI Conf. Human Factors Comput. Systems (ACM, New York), 25–34.Crossref, Google Scholar
• Lee L, Ariely D (2006) Shopping goals, goal concreteness and conditional promotions. J. Consumer Res. 33(1):60–70.Crossref, Google Scholar
• Malhotra NK, Kim SS, Patil A (2006) Common method variance in IS research: A comparison of alternative approaches and a reanalysis of past research. Management Sci. 52(12):1865–1883.Link, Google Scholar
• McAfee AP (2006) Enterprise 2.0: The dawn of emergent collaboration. Sloan Management Rev. 47(3):21–28.Google Scholar
• McCay-Peet L, Toms EG (2011) Exploring the precipitating conditions of serendipity. Proc. 2nd Annual Graphics, Animation New Media NCE Conf., Vancouver, BC, Canada.Google Scholar
• McKenzie PJ (2003) A model of information practices in accounts of everyday-life information seeking. J. Documentation 59(1):19–40.Crossref, Google Scholar
• Metzger MJ, Flanagin AJ (2013) Credibility and trust of information in online environments: The use of cognitive heuristics. J. Pragmatics 59:210–220.Crossref, Google Scholar
• Millen DR, Feinberg J, Kerr B (2006) Dogear: Social bookmarking in the enterprise. Proc. SIGCHI Conf. Human Factors Comput. Systems (ACM, New York), 111–120.Crossref, Google Scholar
• Moody G, Galletta DF (2015) Lost in cyberspace: The impact of information scent and time constraints on stress, performance, and attitudes. J. Management Inform. Systems 32(1):192–224.Crossref, Google Scholar
• Nahapiet J, Ghoshal S (1998) Social capital, intellectual capital, and the organizational advantage. Acad. Management Rev. 23(2): 242–266.Crossref, Google Scholar
• Nelson PJ (1970) Information and consumer behavior. J. Political Econom. 78(2):311–329.Crossref, Google Scholar
• Nielsen J (2003) Information foraging: Why Google makes people leave your site faster. Nielsen Norman Group (June 30), https://www.nngroup.com/articles/information-scent/.Google Scholar
• Oku K, Hattori F (2012) User evaluation of fusion-based approach for serendipity-oriented recommender system. Proc. Workshop Recommendation Utility Evaluation: Beyond RMSE (RUE 2012), Dublin, Ireland, 39–44.Google Scholar
• Olston C, Chi EH (2003) ScentTrails: Integrating browsing and searching on the Web. ACM Trans. Comput.-Human Interaction 10(3):177–197.Crossref, Google Scholar
• Otter M, Johnson H (2000) Lost in hyperspace: Metrics and mental models. Interacting Comput. 13(1):1–40.Crossref, Google Scholar
• Pak R, Price MM, Thatcher J (2009) Age-sensitive design of online health information: Comparative usability study. J. Medical Internet Res. 11(4):e45.Crossref, Google Scholar
• Pavlou PA, Fygenson M (2006) Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quart. 30(1):115–143.Crossref, Google Scholar
• Pavlou PA, Liang H, Xue Y (2007) Understanding and mitigating uncertainty in online exchange relationships: A principal-agent perspective. MIS Quart. 31(1):105–136.Crossref, Google Scholar
• Payne JW, Bettman JR, Johnson EJ (1992) Behavioral decision research: A constructive processing perspective. Annual Rev. Psych. 43(1):87–131.Crossref, Google Scholar
• Pereira RE (2001) Influence of query-based decision aids on consumer decision making in electronic commerce. Inform. Resources Management J. 14(1):31–48.Crossref, Google Scholar
• Pirolli P (2007) Information Foraging: A Theory of Adaptive Interaction with Information (Oxford University Press, New York).Crossref, Google Scholar
• Pirolli P (2009) An elementary social information foraging model. Proc. SIGCHI Human Factors Comput. Systems Conf. (ACM, New York), 605–614.Crossref, Google Scholar
• Pirolli P, Card SK (1999) Information foraging. Psych. Rev. 106(4): 643–675.Crossref, Google Scholar
• Pirolli P, Card SK (2005) The sensemaking process and leverage points for analyst technology as identified through cognitive task analysis. Proc. Internat. Conf. Intelligence Anal., McLean, VA.Google Scholar
• Preacher KJ, Hayes AF (2004) SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behav. Res. Methods, Instruments, Comput. 36(4):717–731.Crossref, Google Scholar
• Rivoal I, Salazar NB (2013) Contemporary ethnographic practice and the value of serendipity. Soc. Anthropology 21(2):178–185.Crossref, Google Scholar
• Roberts RM (1989) Serendipity: Accidental Discoveries in Science (Wiley, New York).Google Scholar
• Shami NS, Muller M, Millen D (2011) Browse and discover: Social file sharing in the enterprise. Proc. ACM 2011 Conf. Comput. Supported Cooperative Work (ACM, New York), 295–304.Crossref, Google Scholar
• Simon HA (1955) A behavioral model of rational choice. Quart. J. Econom. 69(1):99–118.Crossref, Google Scholar
• Sin SCJ, Kim KS (2013) International students’ everyday life information seeking: The informational value of social networking sites. Library Inform. Sci. Res. 35(2):107–116.Crossref, Google Scholar
• Speier C, Morris MG (2003) The influence of query interface design on decision-making performance. MIS Quart. 27(3):397–423.Crossref, Google Scholar
• Spool JM, Perfetti C, Brittan D (2004) Designing for the Scent of Information (User Interface Engineering, Middleton, MA).Google Scholar
• Sun T, Zhang M, Mei Q (2013) Unexpected relevance: An empirical study of serendipity in retweets. Proc. 7th Internat. Conf. Web Soc. Media, Boston.Google Scholar
• Swearingen K, Sinha R (2001) Beyond algorithms: An HCI perspective on recommender systems. Proc. ACM SIGIR 2001 Workshop Recommender Systems, New Orleans.Google Scholar
• Trier M, Molka-Danielsen J (2013) Sympathy or strategy: Social capital drivers for collaborative contributions to the IS community. Eur. J. Inform. Systems 22(3):317–335.Crossref, Google Scholar
• Trusov M, Bodapati AV, Bucklin RE (2010) Determining influential users in Internet social networks. J. Marketing Res. 47(4):643–658.Crossref, Google Scholar
• Wixom BH, Todd P (2005) A theoretical integration of user satisfaction and technology acceptance. Inform. Systems Res. 16(1):85–102.Link, Google Scholar
• Xiao B, Benbasat I (2007) E-commerce product recommendation agents: Use, characteristics, and impact. MIS Quart. 31(1): 137–209.Crossref, Google Scholar
• Yi C, Jiang Z, Benbasat I (2015) Enticing and engaging consumers via online product presentations: The effects of restricted interaction design. J. Management Inform. Systems 31(4):213–242.Crossref, Google Scholar
• Yi C, Jiang Z, Zhou M (2014) The effects of social popularity and deal scarcity at different stages of online shopping. Proc. Internat. Conf. Inform. Systems (ICIS), Auckland, New Zealand.Google Scholar
• Zeng X, Wei L (2013) Social ties and user content generation: Evidence from Flickr. Inform. Systems Res. 24(1):71–87.Link, Google Scholar
• Zhang J, Liu Y, Chen Y (2015) Social learning in networks of friends versus strangers. Marketing Sci. 37(4):573–589.Link, Google Scholar
• Zhang YC, Seaghdha D, Quercia D, Jambor T (2012) Auralist: Introducing serendipity into music recommendation. Proc. 5th ACM Internat. Conf. Web Search Data Mining (ACM, New York),13–22.Crossref, Google Scholar
• Zhu L, Benbasat I, Jiang Z (2010) Let’s shop online together: An empirical investigation of collaborative online shopping support. Inform. Systems Res. 21(4):872–891.Link, Google Scholar
• Ziegler CN, McNee SM, Konstan JA, Lausen G (2005) Improving recommendation lists through topic diversification. Proc. 14th Internat. Conf. World Wide Web (ACM, New York), 22–32.Crossref, Google Scholar