Estimation issues with PLS and CBSEM: Where the bias lies!
Tài liệu tham khảo
Albers, 2010, PLS and success factor studies in marketing, 409
Antonakis, 2010, On making causal claims: A review and recommendations, The Leadership Quarterly, 21, 1086, 10.1016/j.leaqua.2010.10.010
Astrachan, 2014, A comparative study of CB-SEM and PLS-SEM for theory development in family firm research, Journal of Family Business Strategy, 5, 116, 10.1016/j.jfbs.2013.12.002
Atinc, 2012, Control variable use and reporting in macro and micro-management research, Organizational Research Methods, 15, 57, 10.1177/1094428110397773
Bandalos, 2009, Four common misconceptions in exploratory factor analysis, 61
Barroso, 2012, Multi-dimensional analysis of perceived switching costs, Industrial Marketing Management, 41, 531, 10.1016/j.indmarman.2011.06.020
Barroso, 2010, Applying maximum likelihood and PLS on different sample sizes: Studies on SERVQUAL model and employee behavior model, 427
Baxter, 2009, Reflective and formative metrics of relationship value: A commentary essay, Journal of Business Research, 62, 1370, 10.1016/j.jbusres.2008.12.004
Bearden, 2011
Becker, 2013
Becker, 2013, Discovering unobserved heterogeneity in structural equation models to avert validity threats, MIS Quarterly, 37, 665, 10.25300/MISQ/2013/37.3.01
Bentler, 2014, On components, latent variables, PLS and simple methods: Reactions to Rigdon's rethinking of PLS, Long Range Planning, 47, 138, 10.1016/j.lrp.2014.02.005
Bollen, 1989
Bollen, 2002, Latent variables in psychology and the social sciences, Annual Review of Psychology, 53, 605, 10.1146/annurev.psych.53.100901.135239
Bollen, 2011, Evaluating effect, composite, and causal indicators in structural equation models, MIS Quarterly, 35, 359, 10.2307/23044047
Bollen, 2011, Three Cs in measurement models: Causal indicators, composite indicators, and covariates, Psychological Methods, 16, 265, 10.1037/a0024448
Bollen, 2009, Causal indicator models: Identification, estimation, and testing, Structural Equation Modeling, 16, 498, 10.1080/10705510903008253
Bollen, 2016, In defense of causal-formative indicators: A minority report, Psychological Methods
Bollen, 1991, Conventional wisdom on measurement: A structural equation perspective, Psychological Bulletin, 110, 305, 10.1037/0033-2909.110.2.305
Boomsma, 2001, The robustness of LISREL modeling revisited, 139
Borsboom, 2003, The theoretical status of latent variables, Psychological Review, 110, 203, 10.1037/0033-295X.110.2.203
Bruner, 2001
Chang, 2016, Comparing reflective and formative measures: New insights from relevant simulations, Journal of Business Research, 69, 3177, 10.1016/j.jbusres.2015.12.006
Chin, 1998, Commentary: Issues and opinion on structural equation modeling, MIS Quarterly, 22, xii
Chin, 2010, How to write up and report PLS analyses, 655
Churchill, 1979, A paradigm for developing better measures of marketing constructs, Journal of Marketing Research, 16, 64, 10.2307/3150876
Cliff, 1983, Some cautions concerning the application of causal modeling methods, Multivariate Behavioral Research, 18, 115, 10.1207/s15327906mbr1801_7
Coltman, 2008, Formative versus reflective measurement models: Two applications of formative measurement, Journal of Business Research, 61, 1250, 10.1016/j.jbusres.2008.01.013
2007
Diamantopoulos, 1994, Modelling with LISREL: A guide for the uninitiated, Journal of Marketing Management, 10, 105, 10.1080/0267257X.1994.9964263
Diamantopoulos, 2005, The C-OAR-SE procedure for scale development in marketing: A comment, International Journal of Research in Marketing, 22, 1, 10.1016/j.ijresmar.2003.08.002
Diamantopoulos, 2006, The error term in formative measurement models: Interpretation and modeling implications, Journal of Modelling in Management, 1, 7, 10.1108/17465660610667775
Diamantopoulos, 2011, Incorporating formative measures into covariance-based structural equation models, MIS Quarterly, 35, 335, 10.2307/23044046
Diamantopoulos, 2011, Using formative measures in international marketing models: A cautionary tale using consumer animosity as an example, Advances in International Marketing, 10, 11, 10.1108/S1474-7979(2011)0000022004
Diamantopoulos, 2001, Index construction with formative indicators: An alternative to scale development, Journal of Marketing Research, 38, 269, 10.1509/jmkr.38.2.269.18845
Diamantopoulos, 2008, Advancing formative measurement models, Journal of Business Research, 61, 1203, 10.1016/j.jbusres.2008.01.009
Dijkstra, 2011, Linear indices in nonlinear structural equation models: Best fitting proper indices and other composites, Quality & Quantity, 45, 1505, 10.1007/s11135-010-9359-z
Dijkstra, 2015, Consistent partial least squares path modeling, MIS Quarterly, 39, 297, 10.25300/MISQ/2015/39.2.02
Edwards, 2000, On the nature and direction of relationships between constructs and measures, Psychological Methods, 5, 155, 10.1037/1082-989X.5.2.155
Ehrenberg, 1962, Some questions about factor analysis, Journal of the Royal Statistical Society Series D (The Statistician), 12, 191
Fornell, 1982, Two structural equation models: LISREL and PLS applied to consumer exit-voice theory, Journal of Marketing Research, 19, 440, 10.2307/3151718
Fox
Gelhard, 2016, The role of organizational capabilities in achieving superior sustainability performance, Journal of Business Research, 10.1016/j.jbusres.2016.03.053
Gilliam, 2013, A proposed procedure for construct definition in marketing, European Journal of Marketing, 47, 5, 10.1108/03090561311285439
Goodhue, 2012, Does PLS have advantages for small sample size or non-normal data?, MIS Quarterly, 36, 981, 10.2307/41703490
Grace, 2008, Representing general theoretical concepts in structural equation models: The role of composite variables, Environmental and Ecological Statistics, 15, 191, 10.1007/s10651-007-0047-7
Guide, 2015, Notes from the editors: Redefining some methodological criteria for the journal, Journal of Operations Management, 37, v, 10.1016/S0272-6963(15)00056-X
Hair, 2011, PLS-SEM: Indeed a silver bullet, Journal of Marketing Theory and Practice, 19, 139, 10.2753/MTP1069-6679190202
Hair, 2012, An assessment of the use of partial least squares structural equation modeling in marketing research, Journal of the Academy of Marketing Science, 40, 414, 10.1007/s11747-011-0261-6
Hair, 2017
Henseler, 2014, Common beliefs and reality about partial least squares: Comments on Rönkkö & Evermann (2013), Organizational Research Methods, 17, 182, 10.1177/1094428114526928
Henseler, 2016, Using PLS path modeling in new technology research: Updated guidelines, Industrial Management & Data Systems, 116, 1, 10.1108/IMDS-09-2015-0382
Henseler, 2016, Testing measurement invariance of composites using partial least squares, International Marketing Review, 33, 405, 10.1108/IMR-09-2014-0304
Howell, 2013, Formative measurement: A critical perspective, The DATA BASE for Advances in Information Systems, 44, 44, 10.1145/2544415.2544418
Hu, 1998, Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification, Psychological Methods, 3, 424, 10.1037/1082-989X.3.4.424
Hui, 1982, Consistency and consistency at large of partial least squares estimates, 119
Hwang, 2010, A comparative study on parameter recovery of three approaches to structural equation modeling, Journal of Marketing Research, 47, 699, 10.1509/jmkr.47.4.699
Jarvis, 2003, A critical review of construct indicators and measurement model misspecification in marketing and consumer research, Journal of Consumer Research, 30, 199, 10.1086/376806
Jones, 2000, Switching barriers and repurchase intentions in services, Journal of Retailing, 76, 259, 10.1016/S0022-4359(00)00024-5
Jöreskog, 1978, Structural analysis of covariance and correlation matrices, Psychometrika, 43, 443, 10.1007/BF02293808
Jöreskog, 1975, Estimation of a model with multiple indicators and multiple causes of a single latent variable, Journal of the American Statistical Association, 70, 631, 10.2307/2285946
Jöreskog, 1982, The ML and PLS techniques for modeling with latent variables: Historical and comparative aspects, 263
Kaufmann, 2015, A Structured Review of Partial Least Squares in Supply Chain Management Research, Journal of Purchasing and Supply Management, 10.1016/j.pursup.2015.04.005
Law, 1999, Multidimensional constructs in structural equation analysis: An illustration using the job perception and job satisfaction constructs, Journal of Management, 25, 143, 10.1016/S0149-2063(99)80007-5
Law, 1998, Toward a taxonomy of multidimensional constructs, The Academy of Management Review, 23, 741, 10.5465/amr.1998.1255636
Lee, 2013, Problems with formative and higher-order reflective variables, Journal of Business Research, 66, 242, 10.1016/j.jbusres.2012.08.004
Lohmöller, 1989
MacCallum, 1993, The use of causal indicators in covariance structure models: Some practical issues, Psychological Bulletin, 114, 533, 10.1037/0033-2909.114.3.533
MacCallum, 2007, Factor analysis models as approximations: Some history and some implications, 153
MacKenzie, 2003, The dangers of poor construct conceptualization, Journal of the Academy of Marketing Science, 31, 323, 10.1177/0092070303031003011
MacKenzie, 2011, Construct measurement and validation procedures in MIS and behavioral research: Integrating new and existing techniques, MIS Quarterly, 35, 293, 10.2307/23044045
Marcoulides, 2013, You write, but others read: Common methodological misunderstandings in PLS and related methods, Vol. 56, 31
Marcoulides, 2006, PLS: A silver bullet?, MIS Quarterly, 30, III, 10.2307/25148727
Marcoulides, 2012, When imprecise statistical statements become problematic: A response to Goodhue, Lewis, and Thompson, MIS Quarterly, 36, 717, 10.2307/41703477
Mattson, 1997, How to generate non-normal data for simulation of structural equation models, Multivariate Behavioral Research, 32, 355, 10.1207/s15327906mbr3204_3
McDonald, 1996, Path analysis with composite variables, Multivariate Behavioral Research, 31, 239, 10.1207/s15327906mbr3102_5
Michell, 2013, Constructs, inferences and mental measurement, New Ideas in Psychology, 31, 13, 10.1016/j.newideapsych.2011.02.004
Monecke, 2012, semPLS: Structural equation modeling using partial least squares, Journal of Statistical Software, 48, 1, 10.18637/jss.v048.i03
Nunnally, 1994
Pedhazur, 1991
Peng, 2012, Using partial least squares in operations management research: A practical guideline and summary of past research, Journal of Operations Management, 30, 467, 10.1016/j.jom.2012.06.002
R Core Team, 2014
Reinartz, 2002, Generating non-normal data for simulation of structural equation models using Mattson's method, Multivariate Behavioral Research, 37, 227, 10.1207/S15327906MBR3702_03
Reinartz, 2009, An empirical comparison of the efficacy of covariance-based and variance-based SEM, International Journal of Research in Marketing, 26, 332, 10.1016/j.ijresmar.2009.08.001
Rigdon, 1998, Structural equation modeling, 251
Rigdon, 2012, Rethinking partial least squares path modeling: In praise of simple methods, Long Range Planning, 45, 341, 10.1016/j.lrp.2012.09.010
Rigdon, 2013, Partial least squares path modeling, Vol. 1, 81
Rigdon, 2014, Rethinking partial least squares path modeling: Breaking chains and forging ahead, Long Range Planning, 47, 161, 10.1016/j.lrp.2014.02.003
Rigdon, 2016, Choosing PLS path modeling as analytical method in European management research: A realist perspective, European Management Journal, 10.1016/j.emj.2016.05.006
Rigdon, 2011, Overcoming measurement dogma: A response to Rossiter, European Journal of Marketing, 45, 1589, 10.1108/03090561111167306
Rigdon, 2014, Conflating antecedents and formative indicators: A comment on Aguirre-Urreta and Marakas, 25, 780
Ringle, 2012, A critical look at the use of PLS-SEM in MIS quarterly, MIS Quarterly, 36, iii, 10.2307/41410402
Rönkkö
Rönkkö, 2013, A critical examination of common beliefs about partial least squares path modeling, Organizational Research Methods, 16, 425, 10.1177/1094428112474693
Rönkkö, 2015, On the adoption of partial least squares in psychological research: Caveat emptor, Personality and Individual Differences, 87, 76, 10.1016/j.paid.2015.07.019
Rönkkö, 2016, Partial least squares path modeling: Time for some serious second thoughts, Journal of Operations Management, 10.1016/j.jom.2016.05.002
Rossiter, 2011, Marketing measurement revolution: The C-OAR-SE method and why it must replace psychometrics, European Journal of Marketing, 45, 1561, 10.1108/03090561111167298
Salzberger, 2016, Measurement in the social sciences: Where C-OAR-SE delivers and where it does not, European Journal of Marketing, 10.1108/EJM-10-2016-0547
Sarstedt, 2013, Measuring reputation in global markets — A comparison of reputation measures' convergent and criterion validities, Journal of World Business, 48, 329, 10.1016/j.jwb.2012.07.017
Sarstedt, 2014, PLS-SEM: Looking back and moving forward, Long Range Planning, 47, 132, 10.1016/j.lrp.2014.02.008
Sarstedt, 2014, On the emancipation of PLS-SEM: A commentary on Rigdon (2012), Long Range Planning, 47, 154, 10.1016/j.lrp.2014.02.007
Schlittgen
Schneeweiß, 1991, Models with latent variables: LISREL versus PLS, Statistica Neerlandica, 45, 145, 10.1111/j.1467-9574.1991.tb01300.x
Schönemann, 1972, Some new results on factor indeterminacy, Psychometrika, 37, 61, 10.1007/BF02291413
Spearman, 1927
Temme, 2014, Specifying formatively-measured constructs in endogenous positions in structural equation models: Caveats and guidelines for researchers, International Journal of Research in Marketing, 31, 309, 10.1016/j.ijresmar.2014.03.002
Tenenhaus, 2011, Regularized generalized canonical correlation analysis, Psychometrika, 76, 257, 10.1007/s11336-011-9206-8
Tenenhaus, 2005, PLS path modeling, Computational Statistics & Data Analysis, 48, 159, 10.1016/j.csda.2004.03.005
Thurstone, 1947
Wickens, 1972, A note on the use of proxy variables, Econometrica, 40, 759, 10.2307/1912971
Wold, 1982, Soft modeling: The basic design and some extensions, 1
