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Understanding Physicians’ Online-Offline Behavior Dynamics: An Empirical Study

Author

Listed:
  • Liuan Wang

    (School of Economics and Management, Beihang University, Beijing 100191, China;)

  • Lu (Lucy) Yan

    (Department of Operations and Decision Technologies, Kelley School of Business, Indiana University, Bloomington, Indiana 47405;)

  • Tongxin Zhou

    (Department of Information Systems and Operations Management, Michael G. Foster School of Business, University of Washington, Seattle, Washington 98195;)

  • Xitong Guo

    (School of Management, Harbin Institute of Technology, Harbin 150080, China;)

  • Gregory R. Heim

    (Department of Information & Operations Management, Mays Business School, Texas A&M University, College Station, Texas 77843)

Abstract

Physicians’ participation in online healthcare platforms serves to integrate online healthcare resources with the offline medical system. This integration brings opportunities for reshaping healthcare delivery systems. In the field of telemedicine, there has been an extensive discussion about physician participation, but little is known about how physicians actually participate in online healthcare platforms and offline medical systems. Understanding physicians’ participation dynamics between online and offline channels is of great importance to academic researchers, practitioners, and policy makers. Such an understanding can reveal insights into how healthcare is actually delivered to patients through both channels, how to contribute to quantifying the social impacts of online healthcare services (Health 2.0), and how to improve healthcare delivery systems. Thus, in this study, we investigate physicians’ online-offline behavior dynamics using data from both online and offline channels to conduct our analysis. As physicians’ online and offline activities are highly endogenous, we deploy a time-series technique and develop a structural vector autoregression model to examine the behavior dynamics. We find that physicians’ online activities can lead to a higher service quantity in offline channels, whereas offline activities may reduce physicians’ online services because of resource constraints. Our results also show that the more offline patients physicians serve, the more articles the physicians will likely share online. These findings are robust to various econometric specifications and estimation methods. Our research advocates for the benefits Health 2.0 produces and provides evidence of the value of online healthcare communities and the policies that support them.

Suggested Citation

  • Liuan Wang & Lu (Lucy) Yan & Tongxin Zhou & Xitong Guo & Gregory R. Heim, 2020. "Understanding Physicians’ Online-Offline Behavior Dynamics: An Empirical Study," Information Systems Research, INFORMS, vol. 31(2), pages 537-555, June.
    • Handle: RePEc:inm:orisre:v:31:y:2020:i:2:p:537-555
    DOI: 10.1287/isre.2019.0901
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    as
    1. Blanchard, Olivier Jean & Quah, Danny, 1989. "The Dynamic Effects of Aggregate Demand and Supply Disturbances," American Economic Review, American Economic Association, vol. 79(4), pages 655-673, September.
    2. Raghuram Iyengar & Christophe Van den Bulte & Thomas W. Valente, 2011. "Opinion Leadership and Social Contagion in New Product Diffusion," Marketing Science, INFORMS, vol. 30(2), pages 195-212, 03-04.
    3. Josh Lerner & Jean Tirole, 2002. "Some Simple Economics of Open Source," Journal of Industrial Economics, Wiley Blackwell, vol. 50(2), pages 197-234, June.
    4. Jordi Gali, 1999. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," American Economic Review, American Economic Association, vol. 89(1), pages 249-271, March.
    5. Ikujiro Nonaka, 1994. "A Dynamic Theory of Organizational Knowledge Creation," Organization Science, INFORMS, vol. 5(1), pages 14-37, February.
    6. Nigar Hashimzade & Michael A. Thornton (ed.), 2013. "Handbook of Research Methods and Applications in Empirical Macroeconomics," Books, Edward Elgar Publishing, number 14327.
    7. Gottschalk, Jan, 2001. "An Introduction into the SVAR Methodology: Identification, Interpretation and Limitations of SVAR models," Kiel Working Papers 1072, Kiel Institute for the World Economy (IfW Kiel).
    8. Lu (Lucy) Yan & Xiangbin Yan & Yong Tan & Sherry X. Sun, 2019. "Shared Minds: How Patients Use Collaborative Information Sharing via Social Media Platforms," Production and Operations Management, Production and Operations Management Society, vol. 28(1), pages 9-26, January.
    9. Ritu Agarwal & Guodong (Gordon) Gao & Catherine DesRoches & Ashish K. Jha, 2010. "Research Commentary ---The Digital Transformation of Healthcare: Current Status and the Road Ahead," Information Systems Research, INFORMS, vol. 21(4), pages 796-809, December.
    10. Gediminas Adomavicius & Jesse Bockstedt & Alok Gupta, 2012. "Modeling Supply-Side Dynamics of IT Components, Products, and Infrastructure: An Empirical Analysis Using Vector Autoregression," Information Systems Research, INFORMS, vol. 23(2), pages 397-417, June.
    11. Jie Mein Goh & Guodong (Gordon) Gao & Ritu Agarwal, 2011. "Evolving Work Routines: Adaptive Routinization of Information Technology in Healthcare," Information Systems Research, INFORMS, vol. 22(3), pages 565-585, September.
    12. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    13. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    14. Thies, Ferdinand & Wessel, Michael & Benlian, Alexander, 2016. "Effects of Social Interaction Dynamics on Platforms," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 84688, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    15. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    16. Elina H. Hwang & Param Vir Singh & Linda Argote, 2015. "Knowledge Sharing in Online Communities: Learning to Cross Geographic and Hierarchical Boundaries," Organization Science, INFORMS, vol. 26(6), pages 1593-1611, December.
    17. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    18. Sims, Christopher A. & Zha, Tao, 2006. "Does Monetary Policy Generate Recessions?," Macroeconomic Dynamics, Cambridge University Press, vol. 10(2), pages 231-272, April.
    19. Yan Huang & Param Vir Singh & Anindya Ghose, 2015. "A Structural Model of Employee Behavioral Dynamics in Enterprise Social Media," Management Science, INFORMS, vol. 61(12), pages 2825-2844, December.
    20. Olivier Blanchard & Roberto Perotti, 2002. "An Empirical Characterization of the Dynamic Effects of Changes in Government Spending and Taxes on Output," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(4), pages 1329-1368.
    21. Robert G. Fichman & Rajiv Kohli & Ranjani Krishnan, 2011. "Editorial Overview ---The Role of Information Systems in Healthcare: Current Research and Future Trends," Information Systems Research, INFORMS, vol. 22(3), pages 419-428, September.
    22. Thies, Ferdinand & Wessel, Michael & Benlian, Alexander, 2016. "Effects of Social Interaction Dynamics on Platforms," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 82420, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    23. Yingda Lu & Kinshuk Jerath & Param Vir Singh, 2013. "The Emergence of Opinion Leaders in a Networked Online Community: A Dyadic Model with Time Dynamics and a Heuristic for Fast Estimation," Management Science, INFORMS, vol. 59(8), pages 1783-1799, August.
    24. Xueming Luo & Jie Zhang & Wenjing Duan, 2013. "Social Media and Firm Equity Value," Information Systems Research, INFORMS, vol. 24(1), pages 146-163, March.
    25. Sonali K. Shah, 2006. "Motivation, Governance, and the Viability of Hybrid Forms in Open Source Software Development," Management Science, INFORMS, vol. 52(7), pages 1000-1014, July.
    26. Dellarocas, Chrysanthos, 2003. "The Digitization of Word-of-mouth: Promise and Challenges of Online Feedback Mechanisms," Working papers 4296-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    27. Jannis Kallinikos & Niccolò Tempini, 2014. "Patient Data as Medical Facts: Social Media Practices as a Foundation for Medical Knowledge Creation," Information Systems Research, INFORMS, vol. 25(4), pages 817-833, December.
    28. James H. Stock & Mark W. Watson, 2001. "Vector Autoregressions," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 101-115, Fall.
    29. Brian S. Butler, 2001. "Membership Size, Communication Activity, and Sustainability: A Resource-Based Model of Online Social Structures," Information Systems Research, INFORMS, vol. 12(4), pages 346-362, December.
    30. Xueming Luo, 2009. "Quantifying the Long-Term Impact of Negative Word of Mouth on Cash Flows and Stock Prices," Marketing Science, INFORMS, vol. 28(1), pages 148-165, 01-02.
    31. Shaila M. Miranda & Carol S. Saunders, 2003. "The Social Construction of Meaning: An Alternative Perspective on Information Sharing," Information Systems Research, INFORMS, vol. 14(1), pages 87-106, March.
    32. Jeffrey A. Roberts & Il-Horn Hann & Sandra A. Slaughter, 2006. "Understanding the Motivations, Participation, and Performance of Open Source Software Developers: A Longitudinal Study of the Apache Projects," Management Science, INFORMS, vol. 52(7), pages 984-999, July.
    33. Peter Kennedy, 2003. "A Guide to Econometrics, 5th Edition," MIT Press Books, The MIT Press, edition 5, volume 1, number 026261183x, December.
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