{"$schema":"https://static.modelcontextprotocol.io/schemas/2025-12-11/server.schema.json","name":"org.agenticjournal/paper-henseler-2016-micom","description":"MICOM: tests measurement invariance of composites before comparing PLS groups.","version":"0.2.0","title":"Composite Measurement Invariance Agent","websiteUrl":"https://doi.org/10.1108/IMR-09-2014-0304","remotes":[{"type":"streamable-http","url":"https://paper-agent-micom-418969583050.europe-west1.run.app/micom/mcp"}],"_meta":{"org.agenticjournal.registry/agent":{"longDescription":"The MICOM procedure checks, in three steps, configural invariance, compositional invariance and equality of composite means and variances, so that PLS path coefficients can be compared across groups.","availability":"hosted","capabilityKinds":["score","critique"],"skills":[{"id":"micom","name":"Micom","description":"MICOM: may composites be compared, or pooled, across groups?","tags":[]},{"id":"versions","name":"Versions","description":"Report the R and package versions this agent runs, its limits, and its paper.","tags":[]}]},"org.agenticjournal.registry/official":{"status":"active","isLatest":true},"org.agenticjournal.registry/paper":{"doi":"10.1108/IMR-09-2014-0304","title":"Testing measurement invariance of composites using partial least squares","year":2016,"venue":"International Marketing Review","authors":[{"family":"Henseler","given":"Jörg"},{"family":"Ringle","given":"Christian M."},{"family":"Sarstedt","given":"Marko"}],"csl":{"DOI":"10.1108/imr-09-2014-0304","URL":"http://dx.doi.org/10.1108/IMR-09-2014-0304","ISSN":["0265-1335"],"link":[{"URL":"http://www.emeraldinsight.com/doi/full-xml/10.1108/IMR-09-2014-0304","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https://www.emerald.com/insight/content/doi/10.1108/IMR-09-2014-0304/full/xml","content-type":"application/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https://www.emerald.com/insight/content/doi/10.1108/IMR-09-2014-0304/full/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"page":"405-431","type":"journal-article","issue":"3","score":1,"title":"Testing measurement invariance of composites using partial least squares","author":[{"role":[{"role":"author","vocabulary":"crossref"}],"given":"Jörg","family":"Henseler","sequence":"first","affiliation":[]},{"role":[{"role":"author","vocabulary":"crossref"}],"given":"Christian M.","family":"Ringle","sequence":"additional","affiliation":[]},{"role":[{"role":"author","vocabulary":"crossref"}],"given":"Marko","family":"Sarstedt","sequence":"additional","affiliation":[]}],"editor":[{"role":[{"role":"editor","vocabulary":"crossref"}],"given":"Rudolf","family":"R. Sinkovics, Ruey-Jer “Bryan” Jean and Daekwan Kim","sequence":"first","affiliation":[]}],"issued":{"date-parts":[[2016,5,9]]},"member":"140","prefix":"10.1108","source":"Crossref","volume":"33","created":{"date-time":"2016-05-24T06:22:08Z","timestamp":1464070928000,"date-parts":[[2016,5,24]]},"indexed":{"version":"4.1.0","date-time":"2026-09-29T02:28:56Z","timestamp":1790648936605,"date-parts":[[2026,9,29]]},"license":[{"URL":"https://www.emerald.com/insight/site-policies","start":{"date-time":"2016-05-09T00:00:00Z","timestamp":1462752000000,"date-parts":[[2016,5,9]]},"delay-in-days":0,"content-version":"tdm"}],"subject":[],"abstract":"<jats:sec>\n                    <jats:title content-type=\"abstract-heading\">Purpose</jats:title>\n                    <jats:p>– Research on international marketing usually involves comparing different groups of respondents. When using structural equation modeling (SEM), group comparisons can be misleading unless researchers establish the invariance of their measures. While methods have been proposed to analyze measurement invariance in common factor models, research lacks an approach in respect of composite models. The purpose of this paper is to present a novel three-step procedure to analyze the measurement invariance of composite models (MICOM) when using variance-based SEM, such as partial least squares (PLS) path modeling.</jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title content-type=\"abstract-heading\">Design/methodology/approach</jats:title>\n                    <jats:p>– A simulation study allows us to assess the suitability of the MICOM procedure to analyze the measurement invariance in PLS applications.</jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title content-type=\"abstract-heading\">Findings</jats:title>\n                    <jats:p>– The MICOM procedure appropriately identifies no, partial, and full measurement invariance.</jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title content-type=\"abstract-heading\">Research limitations/implications</jats:title>\n                    <jats:p>– The statistical power of the proposed tests requires further research, and researchers using the MICOM procedure should take potential type-II errors into account.</jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title content-type=\"abstract-heading\">Originality/value</jats:title>\n                    <jats:p>– The research presents a novel procedure to assess the measurement invariance in the context of composite models. Researchers in international marketing and other disciplines need to conduct this kind of assessment before undertaking multigroup analyses. They can use MICOM procedure as a standard means to assess the measurement invariance.</jats:p>\n                  </jats:sec>","language":"en","relation":{},"resource":{"primary":{"URL":"http://www.emerald.com/imr/article/33/3/405-431/182408"}},"subtitle":[],"deposited":{"date-time":"2025-07-24T21:32:49Z","timestamp":1753392769000,"date-parts":[[2025,7,24]]},"published":{"date-parts":[[2016,5,9]]},"publisher":"Emerald","reference":[{"DOI":"10.25300/MISQ/2013/37.3.01","key":"key2020121605271756400_b1","unstructured":"Becker, J.-M. , Rai, A. , Ringle, C.M. and Völckner, F. (2013), “Discovering unobserved heterogeneity in structural equation models to avert validity threats”, MIS Quarterly , Vol. 37 No. 3, pp. 665-694.","doi-asserted-by":"crossref"},{"DOI":"10.1016/j.lrp.2014.02.005","key":"key2020121605271756400_b2","unstructured":"Bentler, P.M. and Huang, W. (2014), “On components, latent variables, PLS and simple methods: reactions to ridgon’s rethinking of PLS”, Long Range Planning , Vol. 47 No. 3, pp. 138-145.","doi-asserted-by":"crossref"},{"key":"key2020121605271756400_b3","unstructured":"Blalock, H.M. (1964), Causal Inferences in Nonexperimental Research , University of North Carolina Press, Chapel Hill, NC."},{"DOI":"10.1002/9781118619179","key":"key2020121605271756400_b4","unstructured":"Bollen, K.A. (1989), Structural Equations with Latent Variables , Wiley, New York, NY.","doi-asserted-by":"crossref"},{"DOI":"10.2307/23044047","key":"key2020121605271756400_b5","unstructured":"Bollen, K.A. (2011), “Evaluating effect, composite, and causal indicators in structural equation models”, MIS Quarterly , Vol. 35 No. 2, pp. 359-372.","doi-asserted-by":"crossref"},{"DOI":"10.1037/a0024448","key":"key2020121605271756400_b6","unstructured":"Bollen, K.A. and Bauldry, S. (2011), “Three Cs in measurement models: causal indicators, composite indicators, and covariates”, Psychological Methods , Vol. 16 No. 3, pp. 265-284.","doi-asserted-by":"crossref"},{"DOI":"10.1509/jimk.16.2.84","key":"key2020121605271756400_b7","unstructured":"Brettel, M. , Engelen, A. , Heinemann, F. and Vadhanasindhu, P. (2008), “Antecedents of market orientation: a cross-cultural comparison”, Journal of International Marketing , Vol. 16 No. 2, pp. 84-119.","doi-asserted-by":"crossref"},{"DOI":"10.1007/978-3-540-32827-8_8","key":"key2020121605271756400_b8","unstructured":"Chin, W.W. and Dibbern, J. (2010), “A permutation based procedure for multi-group PLS analysis: results of tests of differences on simulated data and a cross cultural analysis of the sourcing of information system services between Germany and the USA”, in Esposito Vinzi, V. , Chin, W.W. , Henseler, J. and Wang, H. (Eds), Handbook of Partial Least Squares: Concepts, Methods and Applications (Springer Handbooks of Computational Statistics Series, Vol. II) , Springer, Heidelberg, Dordrecht, London and New York, NY, pp. 171-193.","doi-asserted-by":"crossref"},{"DOI":"10.2307/41703491","key":"key2020121605271756400_b9","unstructured":"Chin, W.W. , Thatcher, J.B. and Wright, R.T. (2012), “Assessing common method bias: problems with the ULMC technique”, MIS Quarterly , Vol. 36 No. 3, pp. 1003-1019.","doi-asserted-by":"crossref"},{"DOI":"10.1017/CBO9780511802843","key":"key2020121605271756400_b10","unstructured":"Davison, A.C. and Hinkley, D.V. (1997), Bootstrap Methods and Their Application , Cambridge University Press, Cambridge.","doi-asserted-by":"crossref"},{"DOI":"10.1108/17465660610667775","key":"key2020121605271756400_b11","unstructured":"Diamantopoulos, A. (2006), “The error term in formative measurement models: interpretation and modeling implications”, Journal of Modelling in Management , Vol. 1 No. 1, pp. 7-17.","doi-asserted-by":"crossref"},{"DOI":"10.1057/jibs.2009.37","key":"key2020121605271756400_b12","unstructured":"Diamantopoulos, A. and Papadopoulos, N. (2010), “Assessing the cross-national invariance of formative measures: guidelines for international business researchers”, Journal of International Business Studies , Vol. 41 No. 2, pp. 360-370.","doi-asserted-by":"crossref"},{"DOI":"10.1509/jmkr.38.2.269.18845","key":"key2020121605271756400_b14","unstructured":"Diamantopoulos, A. and Winklhofer, H.M. (2001), “Index construction with formative indicators: an alternative to scale development”, Journal of Marketing Research , Vol. 38 No. 2, pp. 269-277.","doi-asserted-by":"crossref"},{"DOI":"10.1016/j.jbusres.2008.01.009","key":"key2020121605271756400_b13","unstructured":"Diamantopoulos, A. , Riefler, P. and Roth, K.P. (2008), “Advancing formative measurement models”, Journal of Business Research , Vol. 61 No. 12, pp. 1203-1218.","doi-asserted-by":"crossref"},{"DOI":"10.1016/j.lrp.2014.02.004","key":"key2020121605271756400_b15","unstructured":"Dijkstra, T.K. (2014), “PLS’ Janus face – response to Professor Rigdon’s ‘rethinking partial least squares modeling: in praise of simple methods’”, Long Range Planning , Vol. 47 No. 3, pp. 146-153.","doi-asserted-by":"crossref"},{"DOI":"10.1007/s11135-010-9359-z","key":"key2020121605271756400_b16","unstructured":"Dijkstra, T.K. and Henseler, J. (2011), “Linear indices in nonlinear structural equation models: best fitting proper indices and other composites”, Quality & Quantity , Vol. 45 No. 6, pp. 1505-1518.","doi-asserted-by":"crossref"},{"DOI":"10.1016/j.csda.2014.07.008","key":"key2020121605271756400_b17","unstructured":"Dijkstra, T.K. and Henseler, J. (2015a), “Consistent and asymptotically normal PLS estimators for linear structural equations”, Computational Statistics & Data Analysis , Vol. 81 No. 1, pp. 10-23.","doi-asserted-by":"crossref"},{"DOI":"10.25300/MISQ/2015/39.2.02","key":"key2020121605271756400_b18","unstructured":"Dijkstra, T.K. and Henseler, J. (2015b), “Consistent partial least squares path modeling”, MIS Quarterly , Vol. 39 No. 2, pp. 297-316.","doi-asserted-by":"crossref"},{"DOI":"10.1201/9781420011814","key":"key2020121605271756400_b19","unstructured":"Edgington, E. and Onghena, P. (2007), Randomization Tests , Chapman & Hall, Boca Raton, FL.","doi-asserted-by":"crossref"},{"DOI":"10.2139/ssrn.2394044","key":"key2020121605271756400_b20","unstructured":"Esposito Vinzi, V. , Ringle, C.M. , Squillacciotti, S. and Trinchera, L. (2007), “Capturing and treating unobserved heterogeneity by response based segmentation in PLS path modeling: a comparison of alternative methods by computational experiments”, Working Paper No. 07019, ESSEC Research Center, Cergy-Pontoise.","doi-asserted-by":"crossref"},{"DOI":"10.1002/asmb.728","key":"key2020121605271756400_b21","unstructured":"Esposito Vinzi, V. , Trinchera, L. , Squillacciotti, S. and Tenenhaus, M. (2008), “REBUS-PLS: a response-based procedure for detecting unit segments in PLS path modelling”, Applied Stochastic Models in Business and Industry , Vol. 24 No. 5, pp. 439-458.","doi-asserted-by":"crossref"},{"DOI":"10.1177/002224378201900406","key":"key2020121605271756400_b22","unstructured":"Fornell, C.G. and Bookstein, F.L. (1982), “Two structural equation models: LISREL and PLS applied to consumer exit-voice theory”, Journal of Marketing Research , Vol. 19 No. 4, pp. 440-452.","doi-asserted-by":"crossref"},{"DOI":"10.1198/000313006X152649","key":"key2020121605271756400_b23","unstructured":"Gelman, A. and Stern, H. (2006), “The difference between ‘significant’ and ‘not significant’ is not itself statistically significant”, The American Statistician , Vol. 60 No. 4, pp. 328-331.","doi-asserted-by":"crossref"},{"DOI":"10.2307/41703490","key":"key2020121605271756400_b24","unstructured":"Goodhue, D.L. , Lewis, W. and Thompson, R. (2012), “Does PLS have advantages for small sample size or non-normal data?”, MIS Quarterly , Vol. 36 No. 3, pp. 891-1001.","doi-asserted-by":"crossref"},{"DOI":"10.1016/j.jbusres.2008.01.012","key":"key2020121605271756400_b25","unstructured":"Gudergan, S.P. , Ringle, C.M. , Wende, S. and Will, A. (2008), “Confirmatory tetrad analysis in PLS path modeling”, Journal of Business Research , Vol. 61 No. 12, pp. 1238-1249.","doi-asserted-by":"crossref"},{"DOI":"10.1007/BF03396655","key":"key2020121605271756400_b26","unstructured":"Hahn, C. , Johnson, M.D. , Herrmann, A. and Huber, F. (2002), “Capturing customer heterogeneity using a finite mixture PLS approach”, Schmalenbach Business Review , Vol. 54 No. 3, pp. 243-269.","doi-asserted-by":"crossref"},{"key":"key2020121605271756400_b27","unstructured":"Hair, J.F. , Black, W.C. , Babin, B.J. and Anderson, R.E. (2010), Multivariate Data Analysis , Prentice Hall, Englewood Cliffs, NJ."},{"key":"key2020121605271756400_b28","unstructured":"Hair, J.F. , Hult, G.T.M. , Ringle, C.M. and Sarstedt, M. (2017), A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) , 2nd ed., Sage, Thousand Oaks, CA."},{"DOI":"10.1016/j.lrp.2012.09.008","key":"key2020121605271756400_b29","unstructured":"Hair, J.F. , Sarstedt, M. , Pieper, T.M. and Ringle, C.M. (2012a), “The use of partial least squares structural equation modeling in strategic management research: a review of past practices and recommendations for future applications”, Long Range Planning , Vol. 45 Nos 5-6, pp. 320-340.","doi-asserted-by":"crossref"},{"DOI":"10.1007/s11747-011-0261-6","key":"key2020121605271756400_b30","unstructured":"Hair, J.F. , Sarstedt, M. , Ringle, C.M. and Mena, J.A. (2012b), “An assessment of the use of partial least squares structural equation modeling in marketing research”, Journal of the Academy of Marketing Science , Vol. 40 No. 3, pp. 414-433.","doi-asserted-by":"crossref"},{"DOI":"10.1007/s00180-009-0164-x","key":"key2020121605271756400_b31","unstructured":"Henseler, J. (2010), “On the convergence of the partial least squares path modeling algorithm”, Computational Statistics , Vol. 25 No. 1, pp. 107-120.","doi-asserted-by":"crossref"},{"DOI":"10.1007/s11747-011-0298-6","key":"key2020121605271756400_b32","unstructured":"Henseler, J. (2012), “Why generalized structured component analysis is not universally preferable to structural equation modeling”, Journal of the Academy of Marketing Science , Vol. 40 No. 3, pp. 402-413.","doi-asserted-by":"crossref"},{"DOI":"10.1080/10705510903439003","key":"key2020121605271756400_b33","unstructured":"Henseler, J. and Chin, W.W. (2010), “A comparison of approaches for the analysis of interaction effects between latent variables using partial least squares path modeling”, Structural Equation Modeling , Vol. 17 No. 1, pp. 82-109.","doi-asserted-by":"crossref"},{"DOI":"10.1007/978-3-540-32827-8_31","key":"key2020121605271756400_b35","unstructured":"Henseler, J. and Fassott, G. (2010), “Testing moderating effects in PLS path models: an illustration of available procedures”, in Esposito Vinzi, V. , Chin, W.W. , Henseler, J. and Wang, H. (Eds), Handbook of Partial Least Squares: Concepts, Methods and Applications (Springer Handbooks of Computational Statistics Series, Vol. II) , Springer, Heidelberg, Dordrecht, London and New York, NY, pp. 713-735.","doi-asserted-by":"crossref"},{"DOI":"10.1007/s00180-012-0317-1","key":"key2020121605271756400_b39","unstructured":"Henseler, J. and Sarstedt, M. (2013), “Goodness-of-fit indices for partial least squares path modeling”, Computational Statistics , Vol. 28 No. 2, pp. 565-580.","doi-asserted-by":"crossref"},{"key":"key2020121605271756400_b36","unstructured":"Henseler, J. , Ringle, C.M. and Sarstedt, M. (2012), “Using partial least squares path modeling in international advertising research: basic concepts and recent issues”, in Okazaki, S. (Ed.), Handbook of Research in International Advertising , Edward Elgar Publishing, Cheltenham, pp. 252-276."},{"DOI":"10.1007/s11747-014-0403-8","key":"key2020121605271756400_b37","unstructured":"Henseler, J. , Ringle, C.M. and Sarstedt, M. (2015), “A new criterion for assessing discriminant validity in variance-based structural equation modeling”, Journal of the Academy of Marketing Science , Vol. 43 No. 1, pp. 115-135.","doi-asserted-by":"crossref"},{"DOI":"10.1108/S1474-7979(2009)0000020014","key":"key2020121605271756400_b38","unstructured":"Henseler, J. , Ringle, C.M. and Sinkovics, R.R. (2009), “The use of partial least squares path modeling in international marketing”, in Sinkovics, R.R. and Ghauri, P.N. (Eds), Advances in International Marketing , Emerald, Bingley, pp. 277-320.","doi-asserted-by":"crossref"},{"DOI":"10.1177/1094428114526928","key":"key2020121605271756400_b34","unstructured":"Henseler, J. , Dijkstra, T.K. , Sarstedt, M. , Ringle, C.M. , Diamantopoulos, A. , Straub, D.W. , Ketchen, D.J. , Hair, J.F. , Hult, G.T.M. and Calantone, R.J. (2014), “Common beliefs and reality about partial least squares: comments on Rönkkö & Evermann (2013)”, Organizational Research Methods , Vol. 17 No. 2, pp. 182-209.","doi-asserted-by":"crossref"},{"DOI":"10.1080/03610739208253916","key":"key2020121605271756400_b40","unstructured":"Horn, J.L. and McArdle, J.J. (1992), “A practical and theoretical guide to measurement invariance in aging research”, Experimental Aging Research , Vol. 18 No. 3, pp. 117-144.","doi-asserted-by":"crossref"},{"DOI":"10.2307/25148830","key":"key2020121605271756400_b41","unstructured":"Hsieh, J.J.P.-A. , Rai, A. and Keil, M. (2008), “Understanding digital inequality: comparing continued use behavioral models of the socio-economically advantaged and disadvantaged”, MIS Quarterly , Vol. 32 No. 1, pp. 97-126.","doi-asserted-by":"crossref"},{"DOI":"10.1057/palgrave.jibs.8400396","key":"key2020121605271756400_b42","unstructured":"Hult, G.T.M. , Ketchen, D.J. , Griffith, D.A. , Finnegan, C.A. , Gonzalez-Padron, T. , Harmancioglu, N. , Huang, Y. , Talay, M.B. and Cavusgil, S.T. (2008), “Data equivalence in cross-cultural international business research: assessment and guidelines”, Journal of International Business Studies , Vol. 39 No. 6, pp. 1027-1044.","doi-asserted-by":"crossref"},{"DOI":"10.1007/BF02295841","key":"key2020121605271756400_b43","unstructured":"Hwang, H. and Takane, Y. (2004), “Generalized structured component analysis”, Psychometrika , Vol. 69 No. 1, pp. 81-99.","doi-asserted-by":"crossref"},{"DOI":"10.1086/376806","key":"key2020121605271756400_b44","unstructured":"Jarvis, C.B. , MacKenzie, S.B. and Podsakoff, P.M. (2003), “A critical review of construct indicators and measurement model misspecification in marketing and consumer research”, Journal of Consumer Research , Vol. 30 No. 2, pp. 199-218.","doi-asserted-by":"crossref"},{"DOI":"10.1287/mksc.16.1.39","key":"key2020121605271756400_b45","unstructured":"Jedidi, K. , Jagpal, H.S. and DeSarbo, W.S. (1997), “Finite-mixture structural equation models for response-based segmentation and unobserved heterogeneity”, Marketing Science , Vol. 16 No. 1, pp. 39-59.","doi-asserted-by":"crossref"},{"DOI":"10.1177/0022022104272905","key":"key2020121605271756400_b46","unstructured":"Johnson, T. , Kulesa, P. , Cho, Y.I. and Shavitt, S. (2005), “The relation between culture and response styles: evidence from 19 countries”, Journal of Cross-Cultural Psychology , Vol. 36 No. 2, pp. 264-277.","doi-asserted-by":"crossref"},{"DOI":"10.1086/518532","key":"key2020121605271756400_b47","unstructured":"Jong, M.G.D. , Steenkamp, J.-B.E.M. and Fox, J.-P. (2007), “Relaxing measurement invariance in cross-national consumer research using a hierarchical IRT model”, Journal of Consumer Research , Vol. 34 No. 2, pp. 260-278.","doi-asserted-by":"crossref"},{"DOI":"10.2307/2285946","key":"key2020121605271756400_b48","unstructured":"Jöreskog, K.G. and Goldberger, A.S. (1975), “Estimation of a model with multiple indicators and multiple causes of a single latent variable”, Journal of the American Statistical Association , Vol. 70 No. 351, pp. 631-639.","doi-asserted-by":"crossref"},{"DOI":"10.1007/978-3-642-52512-4","key":"key2020121605271756400_b50","unstructured":"Lohmöller, J.-B. (1989), Latent Variable Path Modeling with Partial Least Squares , Physica, Heidelberg.","doi-asserted-by":"crossref"},{"DOI":"10.1016/j.ijresmar.2011.03.006","key":"key2020121605271756400_b51","unstructured":"Lu, I.R.R. , Kwan, E. , Thomas, D.R. and Cedzynski, M. (2011), “Two new methods for estimating structural equation models: an illustration and a comparison with two established methods”, International Journal of Research in Marketing , Vol. 28 No. 3, pp. 258-268.","doi-asserted-by":"crossref"},{"DOI":"10.1207/s15327906mbr3102_5","key":"key2020121605271756400_b52","unstructured":"McDonald, R.P. (1996), “Path analysis with composite variables”, Multivariate Behavioral Research , Vol. 31 No. 2, pp. 239-270.","doi-asserted-by":"crossref"},{"DOI":"10.1177/1094428104268027","key":"key2020121605271756400_b53","unstructured":"Meade, A.W. and Lautenschlager, G.J. (2004), “A comparison of item response theory and confirmatory factor analytic methodologies for establishing measurement equivalence/invariance”, Organizational Research Methods , Vol. 7 No. 4, pp. 361-388.","doi-asserted-by":"crossref"},{"DOI":"10.1007/BF02294825","key":"key2020121605271756400_b54","unstructured":"Meredith, W. (1993), “Measurement invariance, factor analysis and factorial invariance”, Psychometrika , Vol. 58 No. 4, pp. 525-543.","doi-asserted-by":"crossref"},{"DOI":"10.4324/9780203821961","key":"key2020121605271756400_b55","unstructured":"Millsap, R.E. (2011), Statistical Approaches to Measurement Invariance , Routledge, New York, NY.","doi-asserted-by":"crossref"},{"DOI":"10.18637/jss.v048.i03","key":"key2020121605271756400_b56","unstructured":"Monecke, A. and Leisch, F. (2012), “semPLS: structural equation modeling using partial least squares”, Journal of Statistical Software , Vol. 48 No. 3, pp. 1-32.","doi-asserted-by":"crossref"},{"DOI":"10.1016/j.lrp.2012.09.003","key":"key2020121605271756400_b57","unstructured":"Money, K.G. , Hillenbrand, C. , Henseler, J. and Da Camara, N. (2012), “Exploring unanticipated consequences of strategy amongst stakeholder segments: the case of a european revenue service”, Long Range Planning , Vol. 45 Nos 5-6, pp. 395-423.","doi-asserted-by":"crossref"},{"DOI":"10.1057/palgrave.jibs.8490264","key":"key2020121605271756400_b58","unstructured":"Morris, T. and Pavett, C.M. (1992), “Management style and productivity in two cultures”, Journal of International Business Studies , Vol. 23 No. 1, pp. 169-179.","doi-asserted-by":"crossref"},{"DOI":"10.1108/02651330710827960","key":"key2020121605271756400_b59","unstructured":"Okazaki, S. , Mueller, B. , Okazaki, S. and Mueller, B. (2007), “Cross-cultural advertising research: where we have been and where we need to go”, International Marketing Review , Vol. 24 No. 5, pp. 499-518.","doi-asserted-by":"crossref"},{"key":"key2020121605271756400_b60","unstructured":"R Core Team (2014), R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna."},{"DOI":"10.1037/0021-9010.87.3.517","key":"key2020121605271756400_b61","unstructured":"Raju, N.S. , Laffitte, L.J. and Byrne, B.M. (2002), “Measurement equivalence: a comparison of methods based on confirmatory factor analysis and item response theory”, Journal of Applied Psychology , Vol. 87 No. 3, pp. 517-529.","doi-asserted-by":"crossref"},{"DOI":"10.1007/s11747-014-0391-8","key":"key2020121605271756400_b62","unstructured":"Raykov, T. and Calantone, R. (2014), “The utility of item response modeling in marketing research”, Journal of the Academy of Marketing Science , Vol. 42 No. 4, pp. 337-360.","doi-asserted-by":"crossref"},{"DOI":"10.1016/j.ijresmar.2009.08.001","key":"key2020121605271756400_b63","unstructured":"Reinartz, W.J. , Haenlein, M. and Henseler, J. (2009), “An empirical comparison of the efficacy of covariance-based and variance-based SEM”, International Journal of Research in Marketing , Vol. 26 No. 4, pp. 332-344.","doi-asserted-by":"crossref"},{"DOI":"10.1016/j.lrp.2012.09.010","key":"key2020121605271756400_b64","unstructured":"Rigdon, E.E. (2012), “Rethinking partial least squares path modeling: in praise of simple methods”, Long Range Planning , Vol. 45 Nos 5-6, pp. 341-358.","doi-asserted-by":"crossref"},{"DOI":"10.1016/j.lrp.2014.02.003","key":"key2020121605271756400_b65","unstructured":"Rigdon, E.E. (2014), “Rethinking partial least squares path modeling: breaking chains and forging ahead”, Long Range Planning , Vol. 47 No. 3, pp. 161-167.","doi-asserted-by":"crossref"},{"DOI":"10.1108/S1474-7979(2011)0000022011","key":"key2020121605271756400_b66","unstructured":"Rigdon, E.E. , Ringle, C.M. , Sarstedt, M. and Gudergan, S.P. (2011), “Assessing heterogeneity in customer satisfaction studies: across industry similarities and within industry differences”, Advances in International Marketing , Vol. 22, pp. 169-194.","doi-asserted-by":"crossref"},{"DOI":"10.1007/978-1-4419-1280-0_2","key":"key2020121605271756400_b67","unstructured":"Ringle, C.M. , Sarstedt, M. and Mooi, E.A. (2010), “Response-based segmentation using finite mixture partial least squares: theoretical foundations and an application to American customer satisfaction index data”, Annals of Information Systems , Vol. 8, pp. 19-49.","doi-asserted-by":"crossref"},{"DOI":"10.1007/s00291-013-0320-0","key":"key2020121605271756400_b68","unstructured":"Ringle, C.M. , Sarstedt, M. and Schlittgen, R. (2014), “Genetic algorithm segmentation in partial least squares structural equation modeling”, OR Spectrum , Vol. 36 No. 1, pp. 251-276.","doi-asserted-by":"crossref"},{"DOI":"10.2307/41410402","key":"key2020121605271756400_b70","unstructured":"Ringle, C.M. , Sarstedt, M. and Straub, D.W. (2012), “A critical look at the use of PLS-SEM in MIS quarterly”, MIS Quarterly , Vol. 36 No. 1, pp. iii-xiv.","doi-asserted-by":"crossref"},{"DOI":"10.2753/MTP1069-6679190407","key":"key2020121605271756400_b71","unstructured":"Ringle, C.M. , Sarstedt, M. and Zimmermann, L. (2011), “Customer satisfaction with commercial airlines: the role of perceived safety and purpose of travel”, Journal of Marketing Theory and Practice , Vol. 19 No. 4, pp. 459-472.","doi-asserted-by":"crossref"},{"key":"key2020121605271756400_b72","unstructured":"Ringle, C.M. , Wende, S. and Becker, J.-M. (2015), SmartPLS 3, SmartPLS GmbH, Bönningstedt."},{"DOI":"10.1016/j.jbusres.2012.02.031","key":"key2020121605271756400_b69","unstructured":"Ringle, C.M. , Sarstedt, M. , Schlittgen, R. and Taylor, C.R. (2013), “PLS path modeling and evolutionary segmentation”, Journal of Business Research , Vol. 66 No. 9, pp. 1318-1324.","doi-asserted-by":"crossref"},{"DOI":"10.1108/02651330610678976","key":"key2020121605271756400_b73","unstructured":"Salzberger, T. and Sinkovics, R.R. (2006), “Reconsidering the problem of data equivalence in international marketing research: contrasting approaches based on CFA and the Rasch model for measurement”, International Marketing Review , Vol. 23 No. 4, pp. 390-417.","doi-asserted-by":"crossref"},{"DOI":"10.1108/17465660810890126","key":"key2020121605271756400_b74","unstructured":"Sarstedt, M. (2008), “A review of recent approaches for capturing heterogeneity in partial least squares path modelling”, Journal of Modelling in Management , Vol. 3 No. 2, pp. 140-161.","doi-asserted-by":"crossref"},{"DOI":"10.1007/978-3-642-53965-7","key":"key2020121605271756400_b77","unstructured":"Sarstedt, M. and Mooi, E.A. (2014), A Concise Guide to Market Research: The Process, Data, and Methods Using IBM SPSS Statistics , Springer, Heidelberg, Dordrecht, London and New York, NY.","doi-asserted-by":"crossref"},{"DOI":"10.1080/02664760903030213","key":"key2020121605271756400_b78","unstructured":"Sarstedt, M. and Ringle, C.M. (2010), “Treating unobserved heterogeneity in PLS path modelling: a comparison of FIMIX-PLS with different data analysis strategies”, Journal of Applied Statistics , Vol. 37 No. 8, pp. 1299-1318.","doi-asserted-by":"crossref"},{"DOI":"10.1108/S1474-7979(2011)0000022012","key":"key2020121605271756400_b76","unstructured":"Sarstedt, M. , Henseler, J. and Ringle, C.M. (2011a), “Multi-group analysis in partial least squares (PLS) path modeling: alternative methods and empirical results”, in Sarstedt, M. , Schwaiger, M. and Taylor, C.R. (Eds), Advances in International Marketing , Vol. 22, Emerald, Bingley, pp. 195-218.","doi-asserted-by":"crossref"},{"DOI":"10.1007/BF03396886","key":"key2020121605271756400_b75","unstructured":"Sarstedt, M. , Becker, J.-M. , Ringle, C.M. and Schwaiger, M. (2011b), “Uncovering and treating unobserved heterogeneity with FIMIX-PLS: which model selection criterion provides an appropriate number of segments?”, Schmalenbach Business Review , Vol. 63 No. 1, pp. 34-62.","doi-asserted-by":"crossref"},{"DOI":"10.1016/j.lrp.2014.02.007","key":"key2020121605271756400_b79","unstructured":"Sarstedt, M. , Ringle, C.M. , Henseler, J. and Hair, J.F. (2014), “On the emancipation of PLS-SEM: a commentary on Rigdon (2012)”, Long Range Planning , Vol. 47 No. 3, pp. 154-160.","doi-asserted-by":"crossref"},{"DOI":"10.1016/j.jfbs.2014.01.002","key":"key2020121605271756400_b80","unstructured":"Sarstedt, M. , Ringle, C.M. , Smith, D. , Reams, R. and Hair, J.F. (2014), “Partial least squares structural equation modeling (PLS-SEM): a useful tool for family business researchers”, Journal of Family Business Strategy , Vol. 5 No. 1, pp. 105-115.","doi-asserted-by":"crossref"},{"DOI":"10.1007/BF03396685","key":"key2020121605271756400_b81","unstructured":"Schwaiger, M. (2004), “Components and parameters of corporate reputation: an empirical study”, Schmalenbach Business Review , Vol. 56 No. 1, pp. 46-71.","doi-asserted-by":"crossref"},{"DOI":"10.1108/02651330610646304","key":"key2020121605271756400_b82","unstructured":"Singh, N. , Fassott, G. , Chao, M.C.H. and Hoffmann, J.A. (2006), “Understanding international website usage”, International Marketing Review , Vol. 23 No. 1, pp. 83-97.","doi-asserted-by":"crossref"},{"DOI":"10.1007/978-3-540-32827-8_10","key":"key2020121605271756400_b83","unstructured":"Squillacciotti, S. (2010), “Prediction-oriented classification in PLS path modeling”, in Esposito Vinzi, V. , Chin, W.W. , Henseler, J. and Wang, H. (Eds), Handbook of Partial Least Squares: Concepts, Methods and Applications (Springer Handbooks of Computational Statistics Series, Vol. II) , Springer, Heidelberg, Dordrecht, London and New York, NY, pp. 219-233.","doi-asserted-by":"crossref"},{"DOI":"10.1086/209528","key":"key2020121605271756400_b84","unstructured":"Steenkamp, J.-B.E.M. and Baumgartner, H. (1998), “Assessing measurement invariance in cross-national consumer research”, Journal of Consumer Research , Vol. 25 No. 1, pp. 78-107.","doi-asserted-by":"crossref"},{"DOI":"10.1016/S0167-8116(02)00076-9","key":"key2020121605271756400_b85","unstructured":"Steenkamp, J.-B.E.M. and Hofstede, F.T. (2002), “International market segmentation: issues and outlook”, International Journal of Research in Marketing , Vol. 19 No. 3, pp. 185-213.","doi-asserted-by":"crossref"},{"DOI":"10.1007/s11135-007-9143-x","key":"key2020121605271756400_b86","unstructured":"Steinmetz, H. , Schmidt, P. , Tina-Booh, A. , Wieczorek, S. and Schwartz, S.H. (2009), “Testing measurement invariance using multigroup CFA: differences between educational groups in human values measurement”, Quality and Quantity , Vol. 42 No. 4, pp. 599-616.","doi-asserted-by":"crossref"},{"DOI":"10.1177/109442810031002","key":"key2020121605271756400_b87","unstructured":"Vandenberg, R.J. and Lance, C.E. (2000), “A review and synthesis of the measurement invariance literature: suggestions, practices, and recommendations for organizational research”, Organizational Research Methods , Vol. 3 No. 1, pp. 4-70.","doi-asserted-by":"crossref"},{"DOI":"10.1007/978-1-4615-4651-1","key":"key2020121605271756400_b88","unstructured":"Wedel, M. and Kamakura, W.A. (2000), Market Segmentation: Conceptual and Methodological Foundations , Kluwer, Boston, MA.","doi-asserted-by":"crossref"},{"key":"key2020121605271756400_b89","unstructured":"Wold, H.O.A. (1982), “Soft modeling: the basic design and some extensions”, in Jöreskog, K.G. and Wold, H.O.A. (Eds), Systems under Indirect Observations: Part II , North-Holland, Amsterdam, pp. 1-54."}],"short-title":[],"journal-issue":{"issue":"3","published-print":{"date-parts":[[2016,5,9]]}},"alternative-id":["10.1108/IMR-09-2014-0304"],"content-domain":{"domain":[],"crossmark-restriction":false},"original-title":[],"container-title":"International Marketing Review","published-print":{"date-parts":[[2016,5,9]]},"reference-count":88,"references-count":88,"is-referenced-by-count":2791},"relation":"is_derived_from"},"org.agenticjournal.registry/classification":{"contributionType":"methodological","contributionSubtype":"new_method","secondaryContributionTypes":[],"dataBasis":"synthetic","documentType":"full_article","reviewStage":"peer_reviewed","disciplines":["marketing","structural equation modelling"]},"org.agenticjournal.registry/verification":{"doi_resolved":{"result":"pass","checkedAt":null},"endpoint_verified":{"result":"pass","checkedAt":"2026-09-29T13:23:51+00:00"}},"org.agenticjournal.registry/runtime":{"mcpRevisions":["2026-07-28"]},"org.agenticjournal.registry/links":{"self":"https://api.ajournal.xyz/works/10-1108-imr-09-2014-0304","agentCard":"https://api.ajournal.xyz/works/10-1108-imr-09-2014-0304/agent-card.json","jsonLd":"https://api.ajournal.xyz/works/10-1108-imr-09-2014-0304/paper.jsonld"}}}