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

Published Online:https://doi.org/10.1287/isre.2014.0528

References

  • Bagozzi R, Yi Y (2012) Specification, evaluation, and interpretation of structural equation models. J. Acad. Marketing Sci. 40(1):8–34.CrossrefGoogle Scholar
  • Bala H, Venkatesh V (2013) Changes in employees' job characteristics during an enterprise system implementation: A latent growth modeling perspective. MIS Quart. 37(4):1113–1140.CrossrefGoogle Scholar
  • Bapna R, Jank W, Shmueli G (2008) Price formation and its dynamics in online auctions. Decision Support Systems 44(3):641–656.CrossrefGoogle Scholar
  • Bardhan I, Cath O, Zheng Z, Kirksey K (2014) A predictive model for readmission of patients with congestive heart failure. Inform. Systems Res. Forthcoming.Google Scholar
  • Baron R, Kenny D (1986) The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J. Personality Soc. Psych. 51(6):1173–1182.CrossrefGoogle Scholar
  • Bauer DJ (2003) Estimating multilevel linear models as structural equation models. J. Educational Behav. Statist. 28(2):134–167.CrossrefGoogle Scholar
  • Bhattacherjee A, Premkumar G (2004) Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quart. 28(2):351–370.CrossrefGoogle Scholar
  • Boh W, Slaughter S, Spinosa S (2007) Learning from experience in software development: A multilevel analysis. Management Sci. 53(8):1315–1331.LinkGoogle Scholar
  • Bollen K, Curran P (2006) Latent Curve Models: A Structural Equation Perspective (Wiley & Sons, Hoboken, NJ).Google Scholar
  • Boudreau M, Gefen D, Straub DW (2001) Validation in information systems research: A state-of-the-art assessment. MIS Quart. 25(1):1–16.CrossrefGoogle Scholar
  • Box GEP, Pierce DA (1970) Distribution of residual autocorrelations in autoregressive integrated moving average time series models. J. Amer. Statist. Assoc. 65(332):1509–1526.CrossrefGoogle Scholar
  • Chatterjee P (2001) Online reviews: Do consumers use them? Gilly MC, Meyers-Levy J, eds. Advances in Consumer Research, Vol. 28 (Association for Consumer Research, Valdosta, GA), 129–133.Google Scholar
  • Cogley T, Sargent TJ (2005) Drifts and volatilities: Monetary policies and outcomes in the post WWII, US. Rev. Econom. Dynam. 8(2):262–302.CrossrefGoogle Scholar
  • Cooley TF, Prescott EC (1976) Estimation in the presence of stochastic parameter variation. Econometrica 44(1):167–184.CrossrefGoogle Scholar
  • Curran P, Willoughby T (2003) Implications of latent trajectory models for the study of developmental psychopathology. Developmental Psychopathology 15(3):581–612.CrossrefGoogle Scholar
  • Curran P, Bauer D, Willoughby T (2004) Testing main effects and interactions in latent curve analysis. Psych. Methods 9(2):220–237.CrossrefGoogle Scholar
  • Daft RL, Lengel RH (1986) Organizational information requirements, media richness and structural design. Management Sci. 32(5): 554–571.LinkGoogle Scholar
  • Dewan S, Ramaprasad J (2014) Social media, traditional media and music sales: A panel VAR approach. Inform. Systems Res. 38(1):102–122.Google Scholar
  • Diggle P, Heagerty P, Liang K, Zeger S (2013) Analysis of Longitudinal Data (Oxford University Press, Oxford, UK).Google Scholar
  • Duan W, Gu B, Whinston A (2008) Do online reviews matter?—An empirical investigation of panel data. Decision Support Systems 45(3):1007–1016.CrossrefGoogle Scholar
  • Duan W, Gu B, Whinston A (2009) Informational cascades and software adoption on the Internet: An empirical investigation. MIS Quart. 33(1):23–48.CrossrefGoogle Scholar
  • Duncan TE, Duncan SC, Strycker LA (2006) An Introduction to Latent Variable Growth Curve Modeling (Lawrence Erlbaum Associates, Mahwah, NJ).Google Scholar
  • Fichman R, Kemerer C (1999) The illusory diffusion of innovation: An examination of assimilation gaps. Inform. Systems Res. 10(3):255–275.LinkGoogle Scholar
  • George JM, Jones GR (2000) The role of time in theory and theory building. J. Management 26(4):657–684.Google Scholar
  • Geweke J (2007) Bayesian model comparison and validation. Amer. Econom. Rev. 97(2):60–64.CrossrefGoogle Scholar
  • Goldstein H (1995) Multilevel Statistical Models (John Wiley & Sons, New York).Google Scholar
  • Gottfried AE, Marcoulides GA, Gottfried AW, Oliver PH (2009) A latent curve model of parental motivational practices and developmental decline in math and science academic intrinsic motivation. J. Educational Psych. 101(3):729–739.CrossrefGoogle Scholar
  • Guo W (2004) Functional data analysis in longitudinal settings using smoothing splines. Statist. Methods Medical Res. 13(1):49–62.CrossrefGoogle Scholar
  • Hall P, Muller H, Wang J (2006) Properties of principal component methods for functional and longitudinal data analysis. Ann. Statist. 34(3):1493–1517.CrossrefGoogle Scholar
  • Heinen T (1996) Latent Class and Discrete Latent Trait Models (Sage Publications, New York).Google Scholar
  • Hsiao C, Pesaran M (2008) Random coefficient model. Matyas L, Sevestre P, eds. The Econometrics of Panel Data (Springer-Verlag, Berlin Heidelberg), 185–213.CrossrefGoogle Scholar
  • Hu L, Bentler PM (1999) Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling 6(1):1–55.CrossrefGoogle Scholar
  • Jabr W, Zheng Z (2014) Know yourself and know your enemy: An analysis of firm recommendations and consumer reviews in a competitive environment. MIS Quart. 38(3):635–654.CrossrefGoogle Scholar
  • Jackman S (2009) Bayesian Analysis for the Social Sciences (John Wiley, New York).CrossrefGoogle Scholar
  • Jank W, Shmueli G (2006) Functional data analysis in electronic commerce research. Statist. Sci. 21(2):155–166.CrossrefGoogle Scholar
  • Kim D, Ferrin D, Rao H (2009) Trust and satisfaction, the two wheels for successful e-commerce transactions: A longitudinal exploration. Inform. Systems Res. 20(2):237–257.LinkGoogle Scholar
  • Kline R (2011) Principles and Practice of Structural Equation Modeling, 3rd ed. (Guilford Press, New York).Google Scholar
  • Lecinski J (2011) ZMOT Handbook—Ways to Win Shoppers at the Zero Moment of Truth. Accessed July 28, 2014, http://www.zeromomentoftruth.com/assets/files/ZMOT_Handbook.pdf.Google Scholar
  • Levinthal D, March J (1993) The myopia of learning. Strategic Management J. 14(S2):95–112.CrossrefGoogle Scholar
  • Lewicki RJ, Tomlinson EC, Gillespie N (2006) Models of interpersonal trust development: Theoretical approaches, empirical evidence, and future directions. J. Management 32(6):991–1022.CrossrefGoogle Scholar
  • Liu Y (2006) Word of mouth for movies: Its dynamics and impact on box office revenue. J. Marketing 70(3):74–89.CrossrefGoogle Scholar
  • MacKenzie S, Podsakoff P, Podsakoff N (2011) Construct measurement and validation procedures in MIS and behavioral research: Integrating new and existing techniques. MIS Quart. 35(2):293–334.CrossrefGoogle Scholar
  • Marcoulides GA, Hershberger SL (1997) Multivariate Statistical Methods: A First Course (Lawrence Erlbaum Associates, Mahwah, NJ).Google Scholar
  • Massey A, Montoya-Weiss M (2006) Unraveling the temporal fabric of knowledge conversion: A model of media selection and use. MIS Quart. 30(1):99–114.CrossrefGoogle Scholar
  • Mitchell T, James L (2001) Building better theory: Time and the specification of when things happen. Acad. Management Rev. 26(4):530–547.CrossrefGoogle Scholar
  • Mithas S, Ramasubbu N, Krishnan MS, Fornell C (2006) Designing websites for customer loyalty across business domains: A multilevel analysis. J. Management Inform. Systems 23(3):97–127.CrossrefGoogle Scholar
  • Oh W, Lucas HC Jr (2006) Information technology and pricing decisions: Price adjustments in online computer markets. MIS Quart. 30(3):755–775.CrossrefGoogle Scholar
  • Pavlou P, Gefen D (2004) Building effective online marketplaces with institution-based trust. Inform. Systems Res. 15(1):37–59.LinkGoogle Scholar
  • Pavlou PA, El Sawy OA (2010) The “third hand”: IT-enabled competitive advantage in turbulence through improvisational capabilities. Inform. Systems Res. 21(3):443–471.LinkGoogle Scholar
  • Pearl J (2009) Causality: Models, Reasoning and Inference, 2nd ed. (Cambridge University Press, New York).CrossrefGoogle Scholar
  • Pearl J (2012) The causal foundations of structural equations modeling. Hoyle RH, ed. Handbook of Structural Equation Modeling (Guilford Press, New York).CrossrefGoogle Scholar
  • Pitariu A, Ployhart R (2010) Explaining change: Theorizing and testing dynamic mediated longitudinal relationships. J. Management 36(2):405–429.Google Scholar
  • Preacher K, Wichman A, Maccallum R, Briggs N (2008) Latent Growth Curve Modeling (Sage Publications, Thousand Oaks, CA).CrossrefGoogle Scholar
  • Qureshi I, Fang Y (2011) Socialization in open source software projects: A growth mixture modeling approach. Organ. Res. Methods 14(1):208–239.CrossrefGoogle Scholar
  • Rai A, Pavlou PA, Im G, Du S (2012) Inter-firm IT capability profiles and communications for co-creating relational value: Evidence from the logistics industry. MIS Quart. 36(1):233–262.CrossrefGoogle Scholar
  • Ramsey J, Silverman W (2005) Functional Data Analysis, 2nd ed. (Springer, New York).CrossrefGoogle Scholar
  • Raykov T, Marcoulides GA (2008) An Introduction to Applied Multivariate Analysis (Lawrence Erlbaum Associates, Mahwah, NJ).Google Scholar
  • Serva M, Kher H, Larenceau J (2011) Using latent growth modeling to understand longitudinal effects in MIS theory: A primer. Comm. AIS 28(1):213–232.Google Scholar
  • Silva R, Scheines R, Glymour C, Spirtes P (2006) Learning the structure of linear latent variables. J. Machine Learn. Res. 7(2):191–246.Google Scholar
  • Spirtes P, Glymour C, Scheines R (2000) Causation, Prediction and Search, 2nd ed. (Springer-Verlag, New York).Google Scholar
  • Spliid H (1983) A fast estimation for the vector autoregressive moving average models with exogenous variables. J. Amer. Statist. Assoc. 78(384):843–849.CrossrefGoogle Scholar
  • Straub DW (1989) Validating instruments in MIS research. MIS Quart. 13(2):147–169.CrossrefGoogle Scholar
  • Trusov M, Bucklin R, Pauwels K (2009) Effects of word-of-mouth versus traditional marketing: Findings from an Internet social networking site. J. Marketing 73(3):90–102.CrossrefGoogle Scholar
  • Venkatesh V, Davis FD (2000) A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Sci. 46(2):186–204.LinkGoogle Scholar
  • Wang P (2010) Chasing the hottest IT: Effects of information technology fashion on organizations. MIS Quart. 34(1):63–85.CrossrefGoogle Scholar
  • Wang S, Jank W, Shmueli G, Smith P (2008) Modeling price dynamics in eBay auctions using differential equations. J. Amer. Statist. Assoc. 103(483):1100–1118.CrossrefGoogle Scholar
  • Whiteman S, Mroczek D (2007) A brief introduction to growth curve models. Irish J. Psych. 28(1):77–85.CrossrefGoogle Scholar
  • Wooldridge JM (2010) Econometrics Analysis of Cross Section and Panel Data, 2nd ed. (MIT Press, Cambridge, MA).Google Scholar
  • Xue L, Ray G, Gu B (2011) Environmental uncertainty and IT infrastructure governance: A curvilinear relationship. Inform. Systems Res. 22(2):389–399.LinkGoogle Scholar
  • Yao F, Muller H, Wang J (2005) Functional linear regression analysis for longitudinal data. Ann. Statist. 33(6):2873–2903.CrossrefGoogle Scholar
  • Zheng Z, Pavlou P (2010) Toward a causal interpretation from observational data: A new bayesian networks method for structural models with latent variables. Inform. Systems Res. 21(2):365–391.LinkGoogle Scholar
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