Fitting Covariance Models for Theory Generation

Covariance-based structural equation modeling (CB-SEM) is an increasingly popular technique for analyzing quantitative data in Information Systems research. As such, it is traditionally viewed as a method to test theory, rather than build it. However, many of the theoretical models tested with this technique in IS research show significant differences between the model and the data. This paper shows that as part of the pursuit of model fit, researchers using CB-SEM can provide deeper insights into a phenomenon, allowing us to build theories based on quantitative data.

[1]  Leslie A. Hayduk.  Structural equation modeling with LISREL: essentials and advances , 1987 .

[2]  J. M. Cortina,et al.  What Is Coefficient Alpha? An Examination of Theory and Applications , 1993 .

[3]  Wynne W. Chin,et al.  A Fast Form Approach to Measuring Technology Acceptance and Other Constructs , 2008, MIS Q..

[4]  Mario Bunge,et al.  The Myth of Simplicity: Problems of Scientific Philosophy. , 1964 .

[5]  Frederick J. Riggins,et al.  Consumer Adoption of Net-Enabled Infomediaries: Theoretical Explanations and an Empirical Test , 2006, J. Assoc. Inf. Syst..

[6]  Prashant Palvia,et al.  Research Methodologies in MIS: An Update , 2004, Commun. Assoc. Inf. Syst..

[7]  John Fox,et al.  TEACHER'S CORNER: Structural Equation Modeling With the sem Package in R , 2006 .

[8]  Randolph C. Grace,et al.  On the Failure of Operationism , 2001 .

[9]  L A Hayduk.  Should Model Modifications be Oriented Toward Improving Data Fit or Encouraging Creative and Analytical Thinking? , 1990, Multivariate behavioral research.

[10]  Andrew B. Whinston,et al.  Discovery and Representation of Causal Relationships in MIS Research: A Methodological Framework , 1997, MIS Q..

[11]  D. Campbell,et al.  Nonreactive Measures in the Social Sciences , 1981 .

[12]  R. MacCallum,et al.  Power analysis and determination of sample size for covariance structure modeling. , 1996 .

[13]  P. Medawar.  Induction and intuition in scientific thought , 1969 .

[14]  B. Muthén,et al.  How to Use a Monte Carlo Study to Decide on Sample Size and Determine Power , 2002 .

[15]  Kevin G. Corley,et al.  Building Better Theory by Bridging the Quantitative-Qualitative Divide , 2006 .

[16]  Eric Verbeek,et al.  The Weird World, and Equally Weird Measurement Models: Reactive Indicators and the Validity Revolution , 2007 .

[17]  Peter H. Gray,et al.  Pursuing Failure , 2010 .

[18]  T. Little,et al.  On selecting indicators for multivariate measurement and modeling with latent variables: When "good" indicators are bad and "bad" indicators are good. , 1999 .

[19]  A. Satorra,et al.  Corrections to test statistics and standard errors in covariance structure analysis. , 1994 .

[20]  K. Weick,et al.  The Social Psychology of Organizing, 2d ed. , 1980 .

[21]  D DavisFred.  Perceived usefulness, perceived ease of use, and user acceptance of information technology , 1989 .

[22]  Uljana Feest,et al.  Operationism in psychology: what the debate is about, what the debate should be about. , 2005, Journal of the history of the behavioral sciences.

[23]  M. Tiku.  Noncentral Chi-Square Distribution , 2006 .

[24]  K. Bollen,et al.  The Noncentral Chi-square Distribution in Misspecified Structural Equation Models: Finite Sample Results from a Monte Carlo Simulation , 2002, Multivariate behavioral research.

[25]  Samuel B. Bacharach,et al.  Organizational Theories: Some Criteria for Evaluation , 1989 .

[26]  W. Thorngate.  Possible Limits on a Science of Social Behavior , 1976 .

[27]  K. Weick.  Theory Construction as Disciplined Imagination , 1989 .

[28]  R Scheines,et al.  The TETRAD Project: Constraint Based Aids to Causal Model Specification. , 1998, Multivariate behavioral research.

[29]  Joerg Evermann,et al.  Multiple-Group Analysis Using the sem Package in the R System , 2010 .

[30]  Leslie A. Hayduk,et al.  LISREL Issues, Debates and Strategies , 1996 .

[31]  Mike W-L Cheung,et al.  Meta-analytic structural equation modeling: a two-stage approach. , 2005, Psychological methods.

[32]  Kathleen M. Eisenhardt,et al.  Theory Building From Cases: Opportunities And Challenges , 2007 .

[33]  D. Markland.  The golden rule is that there are no golden rules: A commentary on Paul Barrett’s recommendations for reporting model fit in structural equation modelling , 2007 .

[34]  Zvi Drezner,et al.  Model Specification Searches Using Ant Colony Optimization Algorithms , 2003 .

[35]  L. Hayduk,et al.  Testing! testing! one, two, three - Testing the theory in structural equation models! , 2007 .

[36]  D. Kaplan.  Evaluating and Modifying Covariance Structure Models: A Review and Recommendation. , 1990, Multivariate behavioral research.

[37]  Gary James Jason,et al.  The Logic of Scientific Discovery , 1988 .

[38]  A. Panter,et al.  Writing about structural equation models. , 1995 .

[39]  Liping Liu,et al.  Technology acceptance model: A replicated test using TETRAD , 2009, Int. J. Intell. Syst..

[40]  K. Bollen,et al.  A Comment on Model Evaluation and Modification. , 1990, Multivariate behavioral research.

[41]  Albert H. Segars,et al.  Re-examining perceived ease of use and usefulness , 1993 .

[42]  Cameron N. McIntosh,et al.  Rethinking fit assessment in structural equation modelling: A commentary and elaboration on Barrett (2007) , 2007 .

[43]  R. Hoyle.  Structural equation modeling: concepts, issues, and applications , 1997 .

[44]  H. Blalock.  Conceptualization and Measurement in the Social Sciences , 1982 .

[45]  Zvi Drezner,et al.  Model specification searches in structural equation modeling using tabu search , 1998 .

[46]  K. Weick.  The social psychology of organizing , 1969 .

[47]  Robert C. MacCallum,et al.  SPECIFICATION SEARCHES IN COVARIANCE STRUCTURE MODELING , 1986 .

[48]  K. Yuan,et al.  5. Three Likelihood-Based Methods for Mean and Covariance Structure Analysis with Nonnormal Missing Data , 2000 .

[49]  S. S. Wilks.  The Large-Sample Distribution of the Likelihood Ratio for Testing Composite Hypotheses , 1938 .

[50]  Kalle Lyytinen,et al.  Data matters in IS theory building , 2009, J. Assoc. Inf. Syst..

[51]  M. Bunge,et al.  Intuition and Science. , 1963 .

[52]  K. Ting.  The TETRAD Approach to Model Respecification. , 1998, Multivariate behavioral research.

[53]  Jijie Wang,et al.  A TETRAD-based Approach for Theory Development in Information Systems Research , 2007, Commun. Assoc. Inf. Syst..

[54]  James H. Steiger,et al.  Understanding the limitations of global fit assessment in structural equation modeling , 2007 .

[55]  T. Raykov.  Estimation of Composite Reliability for Congeneric Measures , 1997 .

[56]  R. Goffin.  Assessing the adequacy of structural equation models: Golden rules and editorial policies , 2007 .

[57]  K. Eisenhardt.  Building theories from case study research , 1989, STUDI ORGANIZZATIVI.

[58]  Peter A. Todd,et al.  Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication , 1992, MIS Q..

[59]  Detmar W. Straub,et al.  Structural Equation Modeling and Regression: Guidelines for Research Practice , 2000, Commun. Assoc. Inf. Syst..

[60]  P. Barrett.  Structural equation modelling : Adjudging model fit , 2007 .

[61]  Cathy Urquhart,et al.  Putting the ‘theory’ back into grounded theory: guidelines for grounded theory studies in information systems , 2009, Inf. Syst. J..

[62]  J. S. Long,et al.  Testing Structural Equation Models , 1993 .

[63]  Rudy Hirschheim,et al.  A paradigmatic and methodological examination of information systems research from 1991 to 2001 , 2004, Inf. Syst. J..

[64]  J. H. Steiger.  Structural Model Evaluation and Modification: An Interval Estimation Approach. , 1990, Multivariate behavioral research.

[65]  A. Strauss,et al.  The discovery of grounded theory: strategies for qualitative research aldine de gruyter , 1968 .

[66]  K. Gergen,et al.  Social psychology in transition , 1976 .

[67]  Adam LeBrocq.  Style Guide for the Journal of the Association for Information Systems , 2022 .

[68]  J. Miles,et al.  A time and a place for incremental fit indices , 2007 .

[69]  Shirley Gregor,et al.  The Nature of Theory in Information Systems , 2006, MIS Q..

[70]  Eugene J. Webb.  Nonreactive measures in the social sciences , 1981 .