Browse > Article
http://dx.doi.org/10.14400/JDPM.2014.12.1.37

A Study on the Effects of Operating Systems Platform Characteristics on the Network Effect and Intention to Use Operating Systems  

Jeong, Tae-Seok (Dept. of Business Administration, Sahmyook University)
Lee, Sang-Hyun (Dept. of Business Administration, Sahmyook University)
Yim, Myung-Seong (Dept. of Business Administration, Sahmyook University)
Publication Information
Journal of Digital Convergence / v.12, no.1, 2014 , pp. 37-50 More about this Journal
Abstract
The purpose of this research is to look upon the smartphone market from the perspective of business ecosystems and to extract the critical success factors of OS platforms. Furthermore, this research aims to verify the effect of those factors on increasing utility resulting from the rising number of users as well as on intention of use. In order to do this, OS compatibility and OS upgradability were presented as the major characteristics of OS platforms and a logical causal relationship between network effect and intention to use which shows the increase of utility according to the number of users was established which was then followed by an empirical analysis. The results of the research showed that OS compatibility and OS upgradability both had positive effects on network effect and intention to use. By presenting the characteristics of OS platforms, a subject which has lacked pervious empirical studies, and establishing a logical causal relationship for the role platform characteristics play in the formation of business ecosystem in the smartphone market, it is expected that the findings of this research will contribute greatly not only academically but also in practical applications.
Keywords
Business ecosystem; Operating System Platform; OS Compatibility; OS Upgradability; Network Effect; Intention of Use;
Citations & Related Records
연도 인용수 순위
  • Reference
1 A. B. Costello and J. W. Osborne, Best practices in exploratory factor analysis: four recommendations for getting the most from your analysis. practical assessment, Research & Evaluation, Vol. 10, No. 7, pp. 1-9, 2005.
2 A. Pontiggia and F. Virili, Network effects in technology acceptance: laboratory experimental evidence, International Journal of Information Management, Vol. 30, pp. 68-77, 2010.   DOI   ScienceOn
3 C. C. Seepersad, F. Mistree, and J. K, Allen, A Quantitative approach for designing multiple product platforms for an evolving portfolio of products, Proceedings of the DECT'02: ASME 2002 Design Engineering Technical Conference, Montreal, Canada, Sep.29-Oct.2, pp. 579-592, 2002.
4 C. Fornell and D. F. Larcker, Structural equation models with unobservable variables and measurement error: algebra and statistics, Journal of Marketing Research, Vol. 18, No. 3, pp. 328-388, 1981.
5 C. M. Ringle, S. Wende, and A. Will, SmartPLS 2.0(beta), Hamburg, Germany, 2005.
6 D. Gefen and D. Straub, A practical guide to factorial validity using PLS-graph: tutorial and annotated example, Communications of the Association for Information Systems, Vol. 16, pp. 91-109, 2005.
7 D. W. Barclay, C. Higgins, and R. Thompson, The partial least squares approach to causal modeling: personal computer adoption and use as illustration, Technology Studies, Vol. 2, No. 2, pp. 285-309, 1995.
8 F. D. Davis, Perceived usefulness, perceived ease of use and user acceptance of information technology, MIS Quarterly, Vol. 13, pp. 319-340, 1989.   DOI   ScienceOn
9 G. A. Marcoulides, W. W. Chin, and C. Saunders, A critical look at partial least squares modeling, MIS Quarterly, Vol. 33, No. 1, pp. 171-175, 2009.   DOI
10 H. E. A. Tinsley and D. J. Tinsley, Uses of factor analysis in counseling psychology research, Journal of Counseling Psychology, Vol. 34, No. 4, pp. 414-424, 1987.   DOI
11 H. Nair, P. Chintagunta, and J. P. Dube, Empirical analysis of indirect network effects in the market for personal digital assistants, Quantitative Marketing and Economics, Vol. 2, No. 1, pp. 23-58, 2004.   DOI   ScienceOn
12 J. C. Nunnally and I. H. Bernstein, Psychometric Theory, 3rd eds. McGraw-Hill Inc., New York, 1994.
13 J. F. Hair, W. C. Black, B. J. Babin, R. E. Anderson, and R. L. Tatham, Multivariate Data Analysis, 6th eds. Pearson Education Inc., Upper Saddle River, NJ, 2006.
14 J. F. Hair, C. M. Ringle, and M. Sarstedt, Partial least squares structural equation modeling: rigorous applications, better results and higher acceptance, Long Range Planning, Vol. 46, pp. 1-12, 2013.   DOI   ScienceOn
15 J. F. Moore, Business ecosystems and the view from the firm, Antitrust Bulletin, Vol. 51, No. 1, pp. 31-75, 2006.   DOI
16 J. Farrell and G. Saloner, Installed base and compatibility: predation, product preannouncements and innovation, American Economic Review, Vol. 76, No. 5, pp. 940-955, 1986.
17 J. J. Sosik, S. S. Kahai, and M. J. Piovoso, Silver bullet or voodoo statistics? a primer for using the partial least squares data analytic technique in group and organization research, Group and Organization Management, Vol. 34, No. 1, pp. 5-36, 2009.   DOI
18 J. Henseler, C. M. Ringle, and R. R. Sinkovics, The use of partial least squares path modeling in international marketing, Advances in International Marketing, Vol. 20, pp. 277-319, 2009.
19 J. H. Kahn, Factor analysis in counseling psychology research, training, and practice: principles, advances, and applications, Counseling Psychologist, Vol. 34, No. 5, pp. 684-718, 2006.   DOI   ScienceOn
20 J. H. Pae and J. S. Hyun, Technology advancement strategy on patronage decision: the role of switching costs in high-technology markets, The International Journal of Management Science, Vol. 34, No. 1, pp. 19-27, 2006.
21 K. Xing and M. Belusko, Design for upgradability algorithm: configuring durable products for competitive reutilization, Journal of Mechanical Design, Vol. 130, No. 11, pp. 111102_1-111102_14, 2008.
22 M. A. Schilling, Winning the standards race: building installed base and the availability of complementary goods, European Management Journal, Vol. 17, No. 3, pp. 265-274, 1999.   DOI   ScienceOn
23 M. Cusumano, Cloud computing and SaaS as new computing platforms, Communications of the ACM, Vol. 53, No. 4, pp. 27-29, 2010.
24 M. Iansiti and R. Levien, Strategy as ecology, Harvard Business Review, March, pp. 1-10, 2004.
25 M. Kahan and M. Klausner, Standardization and innovation in corporate contracting, Virginia Law Review, Vol. 83, No. 4, pp. 713-770, 1997.   DOI   ScienceOn
26 M. L. Tushman and L. Rosenkopf, On the organizational determinants of technological change: toward a sociology of technological evolution, Research in Organizational Behavior, Vol 14, pp. 311-347. 1992.
27 M. Kenny, and B. Pon, Structuring the smartphone industry: is the mobile internet OS platform the key?, Journal of Industry Competition, and Trade, Vol. 11, No. 3, pp. 239-261, 2011.   DOI
28 M, Kotabe, A, Sahay, and PS, Aulakh, Emerging role of technology licensing in the development of global product strategy: conceptual framework and research propositions, Journal of Marketing, Vol. 60, pp. 73-88, 1996.   DOI   ScienceOn
29 M. L. Katz and C. Shapiro, Network externalities, competition, and compatibility, American Economic Review, Vol. 75, No. 3, pp. 424-440, 1985.
30 M. Peltoniemi, Preliminary theoretical framework for the study of business ecosystems, E:CO, Vol. 8 No. 1, pp. 10-19, 2006.
31 M. Tenenhaus, V. E. Vinzi, Y. M. Chaterlin, and C. Lauro, PLS path modeling, Computational Statistics & Data Analysis, Vol. 48, No. 1, pp. 159-205, 2005.   DOI   ScienceOn
32 M. Wetzels, G. Odekerken-Schroder, and C. van Oppen, Using PLS path modeling for assessing hierarchical construct models: guidelines and empirical illustration, MIS Quarterly, Vol. 33, No. 1, pp. 177-195, 2009.   DOI
33 N. Economides, Desirability of compatibility in the absence of network externalities, American Economic Review, Vol. 78, No. 1, pp. 108-121, 1989.
34 P. I. Jeffers, W. A. Muhanna, and B. R. Nault, Information technology and process performance: an empirical investigation of the interaction between IT and non-IT resources, Decision Sciences, Vol. 39, No. 4, pp. 703-734, 2008.   DOI   ScienceOn
35 R. M. Henderson and K. B. Clark, Architectural innovation: the reconfiguration of existing product technologies and the failure of established firms, Administrative Science Quarterly, Vol. 35, No. 1, pp. 9-30, 1990.   DOI   ScienceOn
36 P. M. Podsakoff, S. B. MacKenzie, J. Y. Lee, and N. P. Podsakoff, Common method biases in behavioral research: a critical review of the literature and recommended remedies, Journal of Applied Psychology, Vol. 88, No. 5, pp. 879-903, 2003.   DOI   ScienceOn
37 R. Garud and K. Kumaraswamy, Technological and organizational designs for realizing economies of subsitution, Strategic Management Journal, Vol. 16, pp. 93-109, 1995.   DOI   ScienceOn
38 R. K. Henson and J. K. Roberts, Use of exploratory factor analysis in published research: common errors and some comment on improved practice, Education and Psychological Measurement, Vol. 66, No. 3, pp. 393-416, 2006.   DOI
39 S. Kondoh, Y. Umeda, and H. Yoshikawa, Devleopment of upgradability cellular machines for environmentally conscious products, Manufacturing Technology, Vol. 47, No. 1, pp. 381-384, 1998.
40 T. Eisenmann, Managing proprietary and shared platforms. California Management Review, Vol. 50, No. 4, pp. 31-53, 2008.
41 W. W. Chin, Issues and opinion on structural equation modeling, MIS Quarterly, Vol. 22, No. 1, pp. vii-xvi, 1998.
42 W. W. Chin and P. R. Newsted, Structural equation modeling analysis with small samples using partial least squares. In:R. H. Hoyle (Ed.), Statistical Strategies for Small Sample Research, Thousand Oaks, CA:Sage, pp. 307-342, 1999.