Modeling Choice Interdependence in a Social Network

Published Online:https://doi.org/10.1287/mksc.2013.0811

References

  • Algesheimer R, Borle S, Dholakia UM, Singh SS (2010) The impact of customer community participation on customer behaviors: An empirical investigation. Marketing Sci. 29(4):756–769.LinkGoogle Scholar
  • Allenby GM, Rossi PE (1999) Marketing models of consumer heterogeneity. J. Econom. 89(1–2):57–78.CrossrefGoogle Scholar
  • Ansari A, Koenigsberg A, Stahl F (2011) Modeling multiple relationships in social networks. J. Marketing Res. 48(4):713–728.CrossrefGoogle Scholar
  • Aral S, Walker D (2011) Creating social contagion through viral product design: A randomized trial of peer influence in networks. Management Sci. 57(9):1623–1639.LinkGoogle Scholar
  • Aral S, Walker D (2012) Identifying influential and susceptible members of social networks. Science 337(6092):337–341.CrossrefGoogle Scholar
  • Aral S, Muchnik L, Sundararajan A (2009) Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks. Proc. Natl. Acad. Sci. USA 106(51):21544–21549.CrossrefGoogle Scholar
  • Aribarg A, Arora N, Bodur HO (2002) Understanding the role of preference revision and concession in group decisions. J. Marketing Res. 39(3):336–349.CrossrefGoogle Scholar
  • Aribarg A, Arora N, Kang MY (2010) Predicting joint choice using individual data. Marketing Sci. 29(1):139–157.LinkGoogle Scholar
  • Arora N, Allenby GM (1999) Measuring the influence of individual preference structure in group decision making. J. Marketing Res. 36(4):476–478.CrossrefGoogle Scholar
  • Bakshy E, Eckles D, Yan R, Rosenn I (2012) Social influence in social advertising: Evidence from field experiments. Proc. 13th ACM Conf. Electronic Commerce (ACM, New York), 146–161.CrossrefGoogle Scholar
  • Bass F (1969) A new product growth model for consumer durables. Management Sci. 15(5):215–227.LinkGoogle Scholar
  • Batra R, Homer PM, Kahle LR (2001) Values, susceptibility to normative influence, and attribute importance weights: A nomological analysis. J. Consumer Psych. 11(2):115–128.CrossrefGoogle Scholar
  • Bearden WO, Etzel MJ (1982) Reference group influence on product and brand purchase decisions. J. Consumer Res. 9(2):183–194.CrossrefGoogle Scholar
  • Bearden WO, Rose RL (1990) Attention to social comparison information: An individual difference factor affecting consumer conformity. J. Consumer Res. 16(4):461–471.CrossrefGoogle Scholar
  • Bearden WO, Netemeyer RG, Teel JE (1989) Measurement of consumer susceptibility to interpersonal influence. J. Consumer Res. 15(4):473–481.CrossrefGoogle Scholar
  • Belk RW (1988) Possession and the extended self. J. Consumer Res. 15(2):139–168.CrossrefGoogle Scholar
  • Bell DR, Song S (2007) Neighborhood effects and trail on the Internet: Evidence from online grocery retailing. Quant. Marketing Econom. 5(4):361–400.CrossrefGoogle Scholar
  • Besag J (1974) Spatial interaction and the statistical analysis of lattice systems. J. Roy. Statist. Soc. Ser. B 36(2):192–236.Google Scholar
  • Besag J (1975) Statistical analysis of non-lattice data. J. Roy. Statist. Soc. Ser. D 24(3):179–195.Google Scholar
  • Bourne FS (1957) Group influence in marketing and public relations. Likert R, Hayes SP, eds. Some Applications of Behavioral Research (UNESCO, Basel, Switzerland), 207–255.Google Scholar
  • Bramoullé Y, Djebbari H, Fortin B (2009) Identification of peer effects through social network. J. Econometrics 150(1):41–55.CrossrefGoogle Scholar
  • Brock WA, Durlauf SN (2001) Discrete choice with social interactions. Rev. Econom. Stud. 68:235–260.CrossrefGoogle Scholar
  • Burnkrant RE, Cousineau A (1975) Informational and normative social influence in buyer behavior. J. Marketing Res. 2(3):206–215.Google Scholar
  • Centola D (2010) The spread of behavior in an online social network experiment. Science 329(5996):1194–1197.CrossrefGoogle Scholar
  • Centola D (2011) An experimental study of homophily in the adoption of health behavior. Science 334(6060):1269–1272.CrossrefGoogle Scholar
  • Chen Y, Wang Q, Xie J (2011) Online social interactions: A natural experiment on word of mouth versus observational learning. J. Marketing Res. 48(2):238–254.CrossrefGoogle Scholar
  • Chevalier JA, Mayzlin D (2006) The effect of word of mouth on sales: Online book reviews. J. Marketing Res. 43(3):345–354.CrossrefGoogle Scholar
  • Childers TL, Rao AR (1992) The influence of familial and peer-based reference groups on consumer decisions. J. Consumer Res. 19(2):198–211.CrossrefGoogle Scholar
  • Cohen JB, Golden E (1972) Informational social influence and product evaluation. J. Appl. Psych. 56(1):54–59.CrossrefGoogle Scholar
  • Czepiel JA (1974) Word-of-mouth processes in the diffusion of a major technological innovation. J. Marketing Res. 11(2):172–180.CrossrefGoogle Scholar
  • De Bruyn A, Lilien GL (2008) A multi-stage model of word-of-mouth influence through viral marketing. Internat. J. Res. Marketing 25(3):151–163.CrossrefGoogle Scholar
  • DeBono KG, Harnish RJ (1988) Source expertise, source attractiveness, and the processing of persuasive information: A functional approach. J. Personality Soc. Psych. 55(4):541–546.CrossrefGoogle Scholar
  • Deutsch M, Gerard HB (1955) A study of normative and informational social influences upon individual judgment. J. Abnormal Soc. Psych. 51(3):626–636.Google Scholar
  • Ding M (2007) An incentive-aligned mechanism for conjoint analysis. J. Marketing Res. 44(May):214–223.CrossrefGoogle Scholar
  • Godes D, Mayzlin D (2004) Using online conversations to study word-of-mouth communication. Marketing Sci. 23(4):545–560.LinkGoogle Scholar
  • Godes D, Mayzlin D, Chen Y, Das S, Dellarocas C, Pfeiffer B, Libai B, Sen S, Shi M, Verlegh P (2005) The firm's management of social interactions. Marketing Lett. 16(3–4):415–428.CrossrefGoogle Scholar
  • Granovetter M (1973) The strength of weak ties. Amer. J. Sociol. 78(6):1360–1380.CrossrefGoogle Scholar
  • Granovetter M (1978) Threshold models of collective behavior. Amer. J. Sociol. 83(6):1420–1443.CrossrefGoogle Scholar
  • Haaijer R, Wedel M (2003) Conjoint choice experiments: General characteristics and alternative model specifications. Gustafsson A, Herrmann A, Huber F, eds. Conjoint Measurement Methods and Applications, 3rd ed. (Springer, New York), 371–412.CrossrefGoogle Scholar
  • Hartmann WR, Nair H, Manchanda P, Bothner M, Dodds P, Godes D, Hosanagar K, Tucker C (2008) Modeling social interactions: Identification, empirical methods and policy implication. Marketing Lett. 19(3):287–304.CrossrefGoogle Scholar
  • Hartmann WR (2010) Demand estimation with social interactions and the implications for targeted marketing. Marketing Sci. 29(4):585–601.LinkGoogle Scholar
  • Hill S, Provost F, Volinsky C (2006) Network-based marketing: Identifying likely adopters via consumer networks. Statist. Sci. 21(2):256–276.CrossrefGoogle Scholar
  • Hoff PD, Raftery AE, Handcock MS (2002) Latent space approaches to social network analysis. J. Amer. Statist. Assoc. 97(460):1090–1098.CrossrefGoogle Scholar
  • Hunter DR (2007) Curved exponential family models for social networks. Soc. Networks 29(2):216–230.CrossrefGoogle Scholar
  • Iacobucci D, Hopkins N (1992) Modeling dyadic interactions and networks in marketing. J. Marketing Res. 29(1):5–17.CrossrefGoogle Scholar
  • Jacoby J, Hoyer WD (1981) What is opinion leaders didn't know more? A question of nomological validity. Monroe KB, ed. Advance in Consumer Research, Vol. 8 (Association for Consumer Research, Ann Arbor, MI), 299–303.Google Scholar
  • Katz E, Lazarsfeld PF (1955) Personal Influence: The Part Played by People in the Flow of Mass Communications (Free Press, New York).Google Scholar
  • Keeney RL, Raiffa H (1993) Decision with Multiple Objectives (Cambridge University Press, New York).CrossrefGoogle Scholar
  • Kelman HC (1958) Compliance, identification, and internalization: Three processes of attitude change. J. Conflict Resolution 2(1):51–60.CrossrefGoogle Scholar
  • Kelman HC (1961) Process of opinion change. Public Opinion Quart. 25:57–78.CrossrefGoogle Scholar
  • Koskinen JH, Snijders TAB (2007) Bayesian inference for dynamic social network data. J. Statist. Plan. Inference 137(12):3930–3938.CrossrefGoogle Scholar
  • Kuhfeld WF, Tobias RD, Garratt M (1994) Efficient experimental design with marketing research applications. J. Marketing Res. 31(4):545–557.CrossrefGoogle Scholar
  • Leider S, Mobius MM, Rosenblat T, Do Q-A (2009) Directed altruism and enforced reciprocity in social networks. Quart. J. Econom. 124(4):1815–1851.CrossrefGoogle Scholar
  • Manchanda P, Packard G, Pattbhiramaiah A (2013) Social dollars: The economic impact of customer participation in a firm-sponsored online community. Working paper, University of Michigan, Ann Arbor.Google Scholar
  • Manski CF (1993) Identification of endogenous social effects: The reflection problem. Rev. Econom. Stud. 60(3):531–542.CrossrefGoogle Scholar
  • Manski CF (2000) Economic analysis of social interactions. J. Econom. Perspect. 14(3):115–136.CrossrefGoogle Scholar
  • McGuire WJ (1969) The nature of attitudes and attitude change. Lindzey G, Aronson E, eds. The Handbook of Social Psychology, 2nd ed., Vol. 3 (Addison-Wesley Publishing, Reading, MA), 136–314.Google Scholar
  • Midgley DF (1976) A simple mathematical theory of innovation behavior. J. Consumer Res. 3(1):31–41.CrossrefGoogle Scholar
  • Miller CM, McIntyre SH, Mantrala MK (1993) Toward formalizing fashion theory. J. Marketing Res. 30(2):142–157.CrossrefGoogle Scholar
  • Miller DT, Prentice DA (1996) The construction of social norms and standards. Higgins ET, Kruglanski AW, eds. Social Psychology: Handbook of Basic Principles (Guilford Press, New York), 799–829.Google Scholar
  • Moffitt R (2001) Policy interventions, low-level equilibria, and social interactions. Durlauf S, Young P, eds. Social Dynamics (Brookings Institution Press, Washington, DC), 45–82.Google Scholar
  • Moon S, Russell GJ (2008) Predicting product purchase from inferred customer similarity: An autologistic model approach. Management Sci. 54(1):71–82.LinkGoogle Scholar
  • Murray I, Ghahramani Z, MacKay DJC (2006) MCMC for doubly-intractable distributions. 22nd Conf. Uncertainty in Artificial Intelligence (UAI 2006), July 13–16, Cambridge, MA.Google Scholar
  • Myers JH, Robertson TS (1972) Dimensions of opinion leadership. J. Marketing Res. 9(1):41–46.CrossrefGoogle Scholar
  • Nair H, Manchanda P, Bhatia T (2010) Asymmetric social interactions in physician prescription behavior: The role of opinion leaders. J. Marketing Res. 47(5):883–895.CrossrefGoogle Scholar
  • Nam S, Manchanda P, Chintagunta PK (2010) The effect of signal quality and contiguous word of mouth on customer acquisition for a video-on-demand service. Marketing Sci. 29(4):690–700.LinkGoogle Scholar
  • Narayan V, Rao VR, Saunders C (2011) How peer influence affects attribute preferences: A Bayesian updating mechanism. Marketing Sci. 30(2):368–384.LinkGoogle Scholar
  • Niraj R, Padmanabhan V, Seetharaman PB (2008) Cross-category model of households' incidence and quantity decisions. Marketing Sci. 27(2):225–235.LinkGoogle Scholar
  • Park CW, Lessig VP (1977) Students and housewives: Differences in susceptibility to reference group influence. J. Consumer Res. 4(2):102–110.CrossrefGoogle Scholar
  • Reingen PH, Kernan JB (1986) Analysis of referral networks in marketing: Methods and illustration. J. Marketing Res. 23(4):370–378.CrossrefGoogle Scholar
  • Reingen PH, Foster BL, Brown JJ, Seidman SB (1984) Brand congruence in interpersonal relations: A social network analysis. J. Consumer Res. 11(3):771–783.CrossrefGoogle Scholar
  • Robertson TM, Zielinski J, Ward S (1984) Consumer Behavior (Scott, Foresman and Company, Glenview, IL).Google Scholar
  • Robins G, Pattison P, Kalish Y, Lusher D (2007) An introduction to exponential random graph (p*) models for social network. Soc. Networks 29(2):173–191.CrossrefGoogle Scholar
  • Rogers EM, Cartano DG (1962) Methods of measuring opinion leadership. Public Opinion Quart. 26(3):435–441.CrossrefGoogle Scholar
  • Ross SM (1996) Stochastic Processes (John Wiley & Sons, New York).Google Scholar
  • Rubin DB (1974) Estimating causal effects of treatments in randomized and nonrandomized studies. J. Ed. Psych. 66(5):688–701.CrossrefGoogle Scholar
  • Russell G, Peterson A (2000) Analysis of cross category dependence in market basket selection. J. Retailing 76(3):367–392.CrossrefGoogle Scholar
  • Schelling T (1971) Dynamic models of segregation. J. Math. Soc. 1(2):143–186.CrossrefGoogle Scholar
  • Shalizi CR, Thomas AC (2011) Homophily and contagion are generically confounded in observational social network studies. Soc. Methods Res. 40(2):211–239.CrossrefGoogle Scholar
  • Snijders TAB, Steglich C, Schweinberger M (2007) Modeling the coevolution of networks and behavior. van Montfort K, Oud H, Satorra A, eds. Longitudinal Models in the Behavioral and Related Sciences (Lawrence Erlbaum Associates, Mahwah, NJ), 41–71.Google Scholar
  • Steglich C, Tom EG, Snijders AB, Pearson M (2010) Dynamic networks and behavior: Separating selection from influence. Soc. Methodol. 40(1):329–393.CrossrefGoogle Scholar
  • Stephen AT, Toubia O (2010) Deriving value from social commerce networks. J. Marketing Res. 47(2):215–228.CrossrefGoogle Scholar
  • Song I, Chintagunta P (2006) Measuring cross-category price effects with aggregate store data. Management Sci. 52(10):1594–1609.LinkGoogle Scholar
  • Toubia O, Stephen AT, Freud A (2011) Viral marketing: A large-scale field experiment. Econom., Management, Financial Markets 6(3):43–65.Google Scholar
  • Trusov M, Bodapati AV, Bucklin RE (2010) Determining influential users in Internet social networks. J. Marketing Res. 47(4):643–658.CrossrefGoogle Scholar
  • Tucker C (2008) Identifying formal and informal influence in technology adoption with network externalities. Management Sci. 54(12):2024–2038.LinkGoogle Scholar
  • Van den Bulte C, Joshi YV (2007) New product diffusion with influentials and imitators. Marketing Sci. 26(3):400–421.LinkGoogle Scholar
  • Van den Bulte C, Stremersch S (2004) Social contagion and income heterogeneity in new product diffusion: A meta-analytic test. Marketing Sci. 23(4):530–544.LinkGoogle Scholar
  • Van den Bulte C, Wuyts S (2007) Social Network and Marketing. Marketing Science Institute Relevant Knowledge Series (Marketing Science Institute, Cambridge, MA).Google Scholar
  • Wang J, Atchadé YF (2014) Approximate Bayesian computation for exponential random graph models for large social networks. Commun. Statist. Simulat. 43(2). Forthcoming.CrossrefGoogle Scholar
  • Wasserman S, Faust K (1994) Social Network Analysis: Methods and Applications (Cambridge University Press, New York).CrossrefGoogle Scholar
  • Wasserman S, Pattison P (1996) Logit models and logistic regressions for social networks: An introduction to Markov random graph and p*. Psychometrika 61(3):401–425.CrossrefGoogle Scholar
  • Watts DJ, Dodds PS (2007) Influentials, networks, and public opinion formation. J. Consumer Res. 34(4):441–458.CrossrefGoogle Scholar
  • Yang S, Allenby GM (2003) Modeling interdependent consumer preferences. J. Marketing Res. 40(3):282–294.CrossrefGoogle Scholar
  • Yang S, Zhao Y, Erdem T, Zhao Y (2010) Modeling the intra-household behavioral interaction. J. Marketing Res. 47(3):470–484.CrossrefGoogle Scholar
  • Zhang J (2010) The sound of silence: Observational learning in the U.S. kidney market. Marketing Sci. 29(2):315–335.LinkGoogle Scholar
  • Zhu F, Zhang X (2010) Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics. J. Marketing. 74(2):133–148.CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.