Network structure and observational learning: Evidence from a location-based social network

Journal of Management Information Systems

Volumn 30, Issue 2, 2013, Pages 185-212

  Shi, Zhan ^a   Whinston, Andrew B ^b  

^a ARIZONA STATE UNIVERSITY   (United States)

^b UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

Experience goods; Location based social network; Matrix factorization; Observational learning; Social effect; Social networks

Indexed keywords

ECONOMIC AND SOCIAL EFFECTS; PRODUCT DESIGN;

EMPIRICAL ANALYSIS; EXPERIENCE GOODS; INTERPERSONAL RELATIONSHIP; LOCATION-BASED SOCIAL NETWORKS; MATRIX FACTORIZATIONS; NETWORK STRUCTURES; OBSERVATIONAL LEARNING; PROMOTIONAL CAMPAIGN;

SOCIAL NETWORKING (ONLINE);

EID: 84898485428     PISSN: 07421222     EISSN: None     Source Type: Journal    
DOI: 10.2753/MIS0742-1222300207     Document Type: Conference Paper

References (43)

1. Adomavicius, G., and Tuzhilin, A. Towards 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 (2005), 734-749.
2. Aral, S., and Walker, D. Creating social contagion through viral product design: A randomized trial of peer influence in networks. Management Science, 57, 9 (2011), 1623-1639.
3. Aral, S.; Muchnik, L.; and Sundararajan, A. Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks. Proceedings of the National Academy of Sciences, 106, 51 (December 22, 2009), 21544-21549.
4. Banerjee, A. A simple model of herd behavior. Quarterly Journal of Economics, 107, 3 (1992), 797-817.
5. Benlian, A.; Titah, R.; and Hess, T. Differential effects of provider recommendations and consumer reviews in e-commerce transactions: An experiment study. Journal of Management Information Systems, 29, 1 (Summer 2012), 237-272.
6. Bikhchandani, S.; Hirshleifer, D.; and Welch, I. A theory of fads, fashion, custom and cultural change as information cascades. Journal of Political Economy, 100, 5 (1992), 992-1026.
7. Bikhchandani, S.; Hirshleifer, D.; and Welch, I. Learning from the behavior of others: Conformity, fads, and informational cascades. Journal of Economic Perspectives, 12, 3 (Summer 1998), 151-170.
8. Bramoull, Y.; Djebbari, H.; and Fortin, B. Identification of peer effects through social networks. Journal of Econometrics, 150, 1 (2009), 41-55.
9. Brin, S., and Page, L. The anatomy of a large-scale hypertextual Web search engine. In Proceedings of the 7th International World Wide Web Conference. New York: ACM Press, 1998, pp. 107-117.
10. Burt, R. Social contagion and innovation: Cohesion versus structural equivalence. American Journal of Sociology, 92, 6 (1987), 1287-1335.
11. Burt, R. Brokerage and Closure. New York: Oxford University Press, 2005.
12. Chamberlain, G. Analysis of covariance with qualitative data. Review of Economic Studies, 47, 1 (1980), 225-238.
13. Duan, W.; Gu, B.; and Whinston, A. Informational cascades and software adoption on the internet: An empirical investigation. MIS Quarterly, 33, 1 (2009), 23-48.
14. Freeman, L. A set of measures of centrality based on betweenness. Sociometry, 40, 1 (1977), 35-41.
15. Garg, R.; Smith, M.; and Telang, T. Measuring information diffusion in an online community. Journal of Management Information Systems, 28, 2 (Fall 2011), 11-37.
16. Granovetter, M. The strength of weak ties. American Journal of Sociology, 78, 6 (1973), 1360-1380.
17. Granovetter, M. Threshold models of collective behavior. American Journal of Sociology, 83, 6 (1978), 1420-1443.
18. Grewal, R.; Lilien, G.; and Mallapragada, G. Location, location, location: How network embeddedness affects project success in open source systems. Management Science, 52, 7 (2006), 1043-1056.
19. Hendricks, K.; Sorensen, A.; and Wiseman, T. Observational learning and demand for search goods. American Economic Journal: Microeconomics, 4, 1 (2012), 1-31.
20. Hill, S.; Provost, F.; and Volinsky, C. Network-based marketing: Identifying likely adopters via consumer networks. Statistical Science, 21, 2 (2006), 256-276.
21. Katona, Z.; Zubscek, P.; and Sarvary, M. Network effects and personal influences: The diffusion of an online social network. Journal of Marketing Research, 48, 3 (2011), 425-443.
22. Kauffman, R.J., and Li, X. Payoff externalities, informational cascades and managerial incentives: A theoretical framework for IT adoption herding. Working Paper WP 03-18, Management Information Systems Research Center, University of Minnesota, 2003.
23. Koren, Y.; Bell, R.; and Volinsky, C. Matrix factorization techniques for recommendation systems. IEEE Computer, 42, 8 (2009), 30-37.
24. Lee, D., and Seung, H. Learning the parts of objects by non-negative matrix factorization. Nature, 401 (October 21, 1999), 788-791.
25. Lee, D., and Seung, H. Algorithms for non-negative matrix factorization. In T.K. Leen, T.G. Dietterich, and V. Tresp (eds.), Advances in Neural Information Processing Systems, vol. 13. Cambridge: MIT Press, 2001, pp. 556-562.
26. Liben-Nowell, D., and Kleinberg, J. The link-prediction problem for social networks. Journal of the American Society for Information Science and Technology, 58, 7 (2007), 1019-1031.
27. Ma, H.; Yang, H.; Lyu, M.; and King, I. SoRec: Social recommendation using probabilistic matrix factorization. In J. Shanahan, S. Amer-Yahia, I. Manolescu, Y. Zhang, D. Evans, A. Kolcz, K. Choi, and A. Chowdhury (eds.), Proceedings of the 17th ACM Conference on Information and Knowledge Management. New York: ACM Press, 2008, pp. 931-940.
28. Manski, C. Identification of endogenous social effects: The reflection problem. Review of Economic Studies, 60, 3 (1993), 531-542.
29. Mundlak, Y. On the pooling of time series and cross section data. Econometrica, 46, 1 (1978), 69-85.
30. Nair, H.; Manchanda, P.; and Bhatia, T. Asymmetric social interactions in physician prescription behavior: The role of opinion leaders. Journal of Marketing Research, 47, 5 (2010), 883-895.
31. Nelson, P. Information and consumer behavior. Journal of Political Economy, 78, 2 (March-April 1970), 311-329.
32. Newman, M. The structure and function of complex networks. SIAM Review, 45, 2 (2003), 167-256.
33. Pathak, B.; Garfinkel, R.; Gopal, R.; Venkatesan, R.; and Yin, F. Empirical analysis of the impact of recommender systems on sales. Journal of Management Information Systems, 27, 2 (Fall 2010), 159-188.
34. Sasidharan, S.; Santhanam, R.; Brass, D.; and Sambamurthy, V. The effects of social network structure on enterprise systems success: A longitudinal multilevel analysis. Information Systems Research, 23, 3 (2011), 658-678.
35. Smith, L., and Sorensen, P. Pathological outcomes of observational learning. Econometrica, 68, 2 (2000), 371-398.
36. Van den Bulte, C., and Lilien, G. Medical innovation revisited: Social contagion versus marketing effect. American Journal of Sociology, 106, 5 (2001), 1409-1435.
37. Wasserman, S., and Faust, K. Social Network Analysis: Methods and Applications. New York: Cambridge University Press, 1994.
38. Watts, D. A simple model of global cascades on random networks. Proceedings of the National Academy of Sciences, 99, 9 (30, 2002), 5766-5771.
39. Watts, D., and Strogatz, S. Collective dynamics of "small- world" networks. Nature, 393 (June 4, 1998), 440-442.
40. Wooldridge, J. Econometric Analysis of Cross Section and Panel Data. Cambridge: MIT Press, 2001.
41. Zhang, J. The sound of silence: Observational learning in the U.S. kidney market. Marketing Science, 29, 2 (March-April 2010), 315-335.
42. Zhang, M., and Wang, C. Network positions and contributions to online public goods: The case of Chinese Wikipedia. Journal of Management Information Systems, 29, 2 (Fall 2012), 11-40.
43. Zhang, S.; Wang, R.; and Zhang, X. Uncovering fuzzy community structure in complex networks. Physical Review E, 76, 4 (2007), 046103.