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Latent Growth Modeling for Information Systems: Theoretical Extensions and Practical Applications

Author

Listed:
  • Zhiqiang (Eric) Zheng

    (Jindal School of Management, University of Texas at Dallas, Dallas, Texas 75080)

  • Paul A. Pavlou

    (Fox School of Business, Temple University, Philadelphia, Pennsylvania 19122)

  • Bin Gu

    (W. P. Carey School of Business, Arizona State University, Tempe, Arizona 85287)

Abstract

This paper presents and extends Latent Growth Modeling (LGM) as a complementary method for analyzing longitudinal data, modeling the process of change over time, testing time-centric hypotheses, and building longitudinal theories. We first describe the basic tenets of LGM and offer guidelines for applying LGM to Information Systems (IS) research, specifically how to pose research questions that focus on change over time and how to implement LGM models to test time-centric hypotheses. Second and more important, we theoretically extend LGM by proposing a model validation criterion, namely “ d - separation ,” to evaluate why and when LGM works and test its fundamental properties and assumptions. Our d -separation criterion does not rely on any distributional assumptions of the data; it is grounded in the fundamental assumption of the theory of conditional independence. Third, we conduct extensive simulations to examine a multitude of factors that affect LGM performance. Finally, as a practical application, we apply LGM to model the relationship between word-of-mouth communication (online product reviews) and book sales over time with longitudinal 26-week data from Amazon. The paper concludes by discussing the implications of LGM for helping IS researchers develop and test longitudinal theories.

Suggested Citation

  • Zhiqiang (Eric) Zheng & Paul A. Pavlou & Bin Gu, 2014. "Latent Growth Modeling for Information Systems: Theoretical Extensions and Practical Applications," Information Systems Research, INFORMS, vol. 25(3), pages 547-568, September.
    • Handle: RePEc:inm:orisre:v:25:y:2014:i:3:p:547-568
    DOI: 10.1287/isre.2014.0528
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    1. Wai Fong Boh & Sandra A. Slaughter & J. Alberto Espinosa, 2007. "Learning from Experience in Software Development: A Multilevel Analysis," Management Science, INFORMS, vol. 53(8), pages 1315-1331, August.
    2. Daniel J. Bauer, 2003. "Estimating Multilevel Linear Models as Structural Equation Models," Journal of Educational and Behavioral Statistics, , vol. 28(2), pages 135-167, June.
    3. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    4. Robert G. Fichman & Chris F. Kemerer, 1999. "The Illusory Diffusion of Innovation: An Examination of Assimilation Gaps," Information Systems Research, INFORMS, vol. 10(3), pages 255-275, September.
    5. Timothy Cogley & Thomas J. Sargent, 2005. "Drift and Volatilities: Monetary Policies and Outcomes in the Post WWII U.S," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 8(2), pages 262-302, April.
    6. Daniel A. Levinthal & James G. March, 1993. "The myopia of learning," Strategic Management Journal, Wiley Blackwell, vol. 14(S2), pages 95-112, December.
    7. Wang, Shanshan & Jank, Wolfgang & Shmueli, Galit & Smith, Paul, 2008. "Modeling Price Dynamics in eBay Auctions Using Differential Equations," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 1100-1118.
    8. Richard L. Daft & Robert H. Lengel, 1986. "Organizational Information Requirements, Media Richness and Structural Design," Management Science, INFORMS, vol. 32(5), pages 554-571, May.
    9. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1, July-Dece.
    10. Patrick Sevestre & Laszlo Matyas, 2008. "The Econometrics of Panel Data," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00279977, HAL.
    11. Cooley, Thomas F & Prescott, Edward C, 1976. "Estimation in the Presence of Stochastic Parameter Variation," Econometrica, Econometric Society, vol. 44(1), pages 167-184, January.
    12. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    13. John Geweke, 2007. "Bayesian Model Comparison and Validation," American Economic Review, American Economic Association, vol. 97(2), pages 60-64, May.
    14. Paul A. Pavlou & David Gefen, 2004. "Building Effective Online Marketplaces with Institution-Based Trust," Information Systems Research, INFORMS, vol. 15(1), pages 37-59, March.
    15. Ling Xue & Gautam Ray & Bin Gu, 2011. "Environmental Uncertainty and IT Infrastructure Governance: A Curvilinear Relationship," Information Systems Research, INFORMS, vol. 22(2), pages 389-399, June.
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    Cited by:

    1. Jeremy S. Wolter & Dora Bock & Jeremy Mackey & Pei Xu & Jeffery S. Smith, 2019. "Employee satisfaction trajectories and their effect on customer satisfaction and repatronage intentions," Journal of the Academy of Marketing Science, Springer, vol. 47(5), pages 815-836, September.
    2. Mingwen Yang & Zhiqiang (Eric) Zheng & Vijay Mookerjee, 2021. "The Race for Online Reputation: Implications for Platforms, Firms, and Consumers," Information Systems Research, INFORMS, vol. 32(4), pages 1262-1280, December.
    3. Dmytro Babik & Rahul Singh & Xia Zhao & Eric W. Ford, 2017. "What you think and what I think: Studying intersubjectivity in knowledge artifacts evaluation," Information Systems Frontiers, Springer, vol. 19(1), pages 31-56, February.

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