DOI QR코드

DOI QR Code

Specificity and Commitment: UX approach to Netflix

  • 투고 : 2017.08.17
  • 심사 : 2017.09.01
  • 발행 : 2017.12.31

초록

The strategy that using data collection from Netflix uses for its services is different from traditional human interaction and the communication, and it is represented by the systematic algorithm that rooted from intelligent information system based on the human interaction and communication. These characteristics allowed the study to reflect the influence of 'Asset specificity' which affects the continuous consumption of the media services of Netflix users through economic psychological analysis based on transactional cost economics. The result from the survey on actual Netflix users, three types of specificity (Space specificity, time specificity, relational specificity) reduced perceived searching cost whereas perceived instrumentality has increased, eventually reinforces the commitment to the service. This implies that the service characteristics of Netflix, trying to communicate with the individuals based on intelligent information system are distinct from the existing platform services and it gives the significance of work very effective for user's continuous consumption of the media services.

키워드

참고문헌

  1. M. A. Cano, "The War on Drugs: An Audience Study of the Netflix Original Series Narcos," Undergraduate Student Research Awards, 24, 2015.
  2. G. Adomavicius and Y. Kwon, "Maximizing aggregate recommendation diversity: A graph-theoretic approach," In Proc. of the 1st International Workshop on Novelty and Diversity in Recommender Systems, pp. 3-10, 2011(October).
  3. V. K. Adhikari, Y. Guo, F. Hao, M. Varvello, V. Hilt, M. Steiner, and Z. L. Zhang, "Unreeling Netflix: Understanding and improving multi-cdn movie delivery," In INFOCOM 2012 Proceedings IEEE, pp. 1620-1628, 2012.
  4. C. A. Gomez-Uribe and N. Hunt, "The Netflix recommender system: Algorithms, business value, and innovation," ACM Transactions on Management Information Systems (TMIS), Vol. 6, no. 4, 2016. http://dx.doi.org/10.1145/2843948
  5. O. E. Williamson, Transaction cost economics, Handbook of industrial organization, pp. 135-182, 1989.
  6. M. Olssen and M. A. Peters, "Neoliberalism, higher education and the knowledge economy: From the free market to knowledge capitalism," Journal of Education Policy, Vol. 20, no. 3, pp. 313-345, 2005.. http://dx.doi.org/10.1080/02680930500108718
  7. P. Dourish, "HCI and environmental sustainability: the politics of design and the design of politics," In Proceedings of the 8th ACM Conference on Designing Interactive Systems, pp. 1-10, Aug. 2010. http://dx.doi.org/10.1145/1858171.1858173
  8. J. M. Sheth and W. W. Talarzyk, "Perceived instrumentality and value importance as determinants of attitudes," Journal of Marketing Research, Vol. 9, no. 1, pp. 6-9, Feb. 1972. http://dx.doi.org/10.2307/3149597
  9. H. A. Shelanski and P. G. Klein, "Empirical research in transaction cost economics: a review and assessment," Journal of Law, Economics, & Organization, Vol. 11, no. 2, pp. 335-361, Oct. 1995.
  10. E. Brynjolfsson and M. Van Alstyne, "Information Worker Productivity: Evidence from Worker Output, Compensation and Email Traffic Data," 2004.
  11. P.L. Joskow, "The role of transaction cost economics in antitrust and public utility regulatory policies," Journal of Law, Economics, & Organization, 7, pp. 53-83, 1991. https://doi.org/10.1093/jleo/7.special_issue.53
  12. B.S. Silverman, "Technological resources and the direction of corporate diversification: Toward an integration of the resource-based view and transaction cost economics," Management Science, vol. 45, no. 8, pp. 1109-1124, 1999. http://dx.doi.org/10.1287/mnsc.45.8.1109
  13. A. Zeng, S. Gualdi, M. Medo, and Y. C. Zhang, "Trend prediction in temporal bipartite networks: the case of Movielens, Netflix, and Digg," Advances in Complex Systems, Vol. 16, no. 4, 2013. http://dx.doi.org/10.1142/S0219525913500240
  14. R. A. M. Gonzalez, "The Nostalgia Economy: Netflix and New Audiences in the Digital Age," Doctoral Dissertation, The London School of Economics and Political Science, 2017. http://dx.doi.org/10.1145/2843948
  15. C. A. Gomez-Uribe and N. Hunt, "The Netflix recommender system: Algorithms, business value, and innovation," ACM Transactions on Management Information Systems, Vol. 6, no. 4, pp. 13:2-13:19, 2016. http://dx.doi.org/10.1145/2843948
  16. A. Amatriain, "Big & personal: data and models behind netflix recommendations," In Proceedings of the 2nd international workshop on big data, streams and heterogeneous source mining: Algorithms, systems, programming models and applications X, pp. 1-6, Aug. 2013. http://dx.doi.org/10.1145/2501221.2501222
  17. M. Jenner, "Is this TVIV? On Netflix, TVIII and binge-watching," New Media and Society, Vol. 18, no. 2, pp. 257-273, 2016. http://dx.doi.org/10.1177/1461444814541523
  18. D. C. North, "A transaction cost theory of politics," Journal of Theoretical Politics, Vol. 2, no. 4, 1990, pp. 355-367. https://doi.org/10.1177/0951692890002004001
  19. R. N. Langlois, "Transaction-cost Economics in real time," Industrial and Corporate Change, Vol. 1, no. 1, 1992, pp. 99-127. https://doi.org/10.1093/icc/1.1.99
  20. R. Kochhar, R. "Explaining firm capital structure: The role of agency theory vs. transaction cost economics," Strategic Management Journal, Vol. 17, no. 9, 1996, pp. 713-728. https://doi.org/10.1002/(SICI)1097-0266(199611)17:9<713::AID-SMJ844>3.0.CO;2-9
  21. M. Mazzanti, S. Montresor, and P. Pini, "Outsourcing and transaction costs in "real" time and space: evidence for a province of Emilia-Romagna(Italy)," The ICFAI Journal of Industrial Economics, Vol. 4, no. 3, 2007, pp. 7-22.
  22. N. Srinivasan and B. T. Ratchford, "An empirical test of a model of external search for automobiles," Journal of Consumer research, Vol. 18, no. 22, 1991, pp. 233-242. http://dx.doi.org/10.1086/209255
  23. B. Berman, "Should your firm adopt a mass customization strategy?," Business Horizons, Vol. 45, no. 4, pp. 51-60, 2002. https://doi.org/10.1016/S0007-6813(02)00227-6
  24. Y. Ge, Q. Liu, H. Xiong, A. Tuzhilin, and J. Chen, "Cost-aware travel tour recommendation," In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 983-991, Aug. 2011. http://dx.doi.org/10.1145/2020408.2020568
  25. T. H. Chiles and J. F. McMackin, "Integrating variable risk preferences, trust, and transaction cost economics," Academy of Management Review, Vol. 21, no. 1, 1996, pp. 73-99. http://dx.doi.org/10.5465/AMR.1996.9602161566
  26. M. J. Arnold and K. E. Reynolds, "Hedonic shopping motivations," Journal of Retailing, Vol. 79, no. 2, pp. 77-95, 2003. https://doi.org/10.1016/S0022-4359(03)00007-1
  27. R. P. Bagozzi and Y. Yi, "On the evaluation of structural equation models," Journal of the Academy of Marketing Science, Vol. 16, no. 1, pp. 74-94, 1998. https://doi.org/10.1177/009207038801600107
  28. W. W. Chin, A. Gopal, and W. D. Salisbury, "Advancing the theory of adaptive structuration: The development of a scale to measure faithfulness of appropriation," Information Systems Research, Vol. 8, no. 4, pp. 342-367, 1997. https://doi.org/10.1287/isre.8.4.342
  29. C. Fornell and D. F. Larcker, "Evaluating structural equation models with unobservable variables and measurement error," Journal of Marketing Research, pp. 39-50, 1981. https://doi.org/10.2307/3151312
  30. D. Constant, S. Kiesler, and L. Sproull, "What's mine is ours, or is it? A study of attitudes about information sharing," Information Systems Research, Vol. 5, no. 4, pp. 400-421, 1994. https://doi.org/10.1287/isre.5.4.400
  31. D. Gefen, D. W. Straub, and M. C. Boudreau, "Structural equation modeling and regression: Guidelines for research practice," In Communications of the Association for Information Systems. 2000. http://dx.doi.org/10.1080/13683500.2011.641947