{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T11:25:08Z","timestamp":1774351508903,"version":"3.50.1"},"reference-count":118,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T00:00:00Z","timestamp":1769558400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Fundacao para a Ciencia e a Tecnologia","doi-asserted-by":"publisher","award":["UID\/PRR\/04152\/2025"],"award-info":[{"award-number":["UID\/PRR\/04152\/2025"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001871","name":"Fundacao para a Ciencia e a Tecnologia","doi-asserted-by":"publisher","award":["UID\/04152\/2025"],"award-info":[{"award-number":["UID\/04152\/2025"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005855","name":"Universidade Nova de Lisboa","doi-asserted-by":"publisher","award":["2025-01-01\/ 2026-06-30"],"award-info":[{"award-number":["2025-01-01\/ 2026-06-30"]}],"id":[{"id":"10.13039\/501100005855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005855","name":"Universidade Nova de Lisboa","doi-asserted-by":"publisher","award":["2025-01-01\/2028-12-31"],"award-info":[{"award-number":["2025-01-01\/2028-12-31"]}],"id":[{"id":"10.13039\/501100005855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000921","name":"European Cooperation in Science and Technology","doi-asserted-by":"publisher","award":["CA22137"],"award-info":[{"award-number":["CA22137"]}],"id":[{"id":"10.13039\/501100000921","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computational Statistics & Data Analysis"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.csda.2026.108348","type":"journal-article","created":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T17:25:07Z","timestamp":1769707507000},"page":"108348","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Automated specification search for composite-based structural equation modeling: A genetic approach"],"prefix":"10.1016","volume":"219","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9679-0956","authenticated-orcid":false,"given":"Laura","family":"Trinchera","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7623-8419","authenticated-orcid":false,"given":"Gloria","family":"Pietropolli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8793-1451","authenticated-orcid":false,"given":"Mauro","family":"Castelli","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2110-9086","authenticated-orcid":false,"given":"Florian","family":"Schuberth","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0001","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/0304-4076(81)90071-3","article-title":"Likelihood of a model and information criteria","volume":"16","author":"Akaike","year":"1981","journal-title":"J. Econom."},{"key":"10.1016\/j.csda.2026.108348_bib0002","series-title":"Selected Papers of Hirotugu Akaike. Springer Series in Statistics (Perspectives in Statistics)","first-page":"199","article-title":"Information theory and an extension of the maximum likelihood principle","author":"Akaike","year":"1998"},{"issue":"10","key":"10.1016\/j.csda.2026.108348_bib0003","doi-asserted-by":"crossref","first-page":"3142","DOI":"10.1016\/j.cnsns.2009.11.003","article-title":"A novel bee swarm optimization algorithm for numerical function optimization","volume":"15","author":"Akbari","year":"2010","journal-title":"Commun. Nonlinear Sci. Numer. Simul."},{"issue":"3","key":"10.1016\/j.csda.2026.108348_bib0004","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1016\/j.compstruct.2008.05.004","article-title":"Design optimization of composite laminated structures using genetic algorithms and finite element analysis","volume":"88","author":"Almeida","year":"2009","journal-title":"Compos. Struct."},{"key":"10.1016\/j.csda.2026.108348_bib0005","series-title":"Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence","first-page":"57","article-title":"Selective pressure in evolutionary algorithms: a characterization of selection mechanisms","author":"Back","year":"1994"},{"key":"10.1016\/j.csda.2026.108348_bib0006","series-title":"Evolutionary Algorithms in Theory and Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms","author":"Back","year":"1996"},{"issue":"6","key":"10.1016\/j.csda.2026.108348_bib0007","doi-asserted-by":"crossref","first-page":"1173","DOI":"10.1037\/0022-3514.51.6.1173","article-title":"The moderator\u2013mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations","volume":"51","author":"Baron","year":"1986","journal-title":"J. Pers. Soc. Psychol."},{"issue":"57","key":"10.1016\/j.csda.2026.108348_bib0008","article-title":"How to perform and report an impactful analysis using partial least squares: guidelines for confirmatory and explanatory IS research","volume":"2","author":"Benitez","year":"2020","journal-title":"Inf. Manag."},{"key":"10.1016\/j.csda.2026.108348_bib0009","series-title":"EQS Structural Equations Program Manual","volume":"6","author":"Bentler","year":"1995"},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0010","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1037\/0033-2909.106.2.315","article-title":"Choice of structural model via parsimony: a rationale based on precision","volume":"106","author":"Bentler","year":"1989","journal-title":"Psychol. Bull."},{"issue":"4","key":"10.1016\/j.csda.2026.108348_bib0011","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1348\/014466600164633","article-title":"Self-categorization, affective commitment and group self-esteem as distinct aspects of social identity in the organization","volume":"39","author":"Bergami","year":"2000","journal-title":"Br. J. Social Psychol."},{"key":"10.1016\/j.csda.2026.108348_bib0012","series-title":"Proceedings of PLS\u201907 - The 5th International Symposium on PLS and Related Methods","first-page":"57","article-title":"Exploring causal path directionality for a marketing model: using Cohen\u2019s path method","author":"Callaghan","year":"2007"},{"issue":"5","key":"10.1016\/j.csda.2026.108348_bib0013","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1016\/j.orl.2014.06.002","article-title":"Genetic algorithm with variable neighborhood search for the optimal allocation of goods in shop shelves","volume":"42","author":"Castelli","year":"2014","journal-title":"Oper. Res. Lett."},{"issue":"12","key":"10.1016\/j.csda.2026.108348_bib0014","doi-asserted-by":"crossref","first-page":"2161","DOI":"10.1108\/IMDS-10-2019-0529","article-title":"Demystifying the role of causal-predictive modeling using partial least squares structural equation modeling in information systems research","volume":"120","author":"Chin","year":"2020","journal-title":"Indus. Manag. Data Syst."},{"key":"10.1016\/j.csda.2026.108348_bib0015","series-title":"Modern Methods for Business Research","first-page":"295","article-title":"The partial least squares approach for structural equation modeling","author":"Chin","year":"1998"},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0016","doi-asserted-by":"crossref","first-page":"220","DOI":"10.1111\/bmsp.12255","article-title":"A comparative evaluation of factor- and component-based structural equation modeling approaches under (in)correct construct representations","volume":"75","author":"Cho","year":"2022","journal-title":"Br. J. Math. Stat. Psychol."},{"issue":"4","key":"10.1016\/j.csda.2026.108348_bib0017","doi-asserted-by":"crossref","first-page":"611","DOI":"10.1080\/10705511.2022.2057315","article-title":"A prediction-oriented specification search algorithm for generalized structured component analysis","volume":"29","author":"Cho","year":"2022","journal-title":"Struc. Eq. Model. Multidiscip. J."},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0018","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1037\/0033-2909.112.1.155","article-title":"A power primer","volume":"112","author":"Cohen","year":"1992","journal-title":"Psychol. Bull."},{"key":"10.1016\/j.csda.2026.108348_bib0019","article-title":"On the role of partial least squares in path analysis for the social sciences","volume":"167","author":"Cook","year":"2023","journal-title":"J. Bus. Res."},{"key":"10.1016\/j.csda.2026.108348_bib0020","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.jbusres.2020.03.019","article-title":"Model selection uncertainty and multimodel inference in partial least squares structural equation modeling (PLS-SEM)","volume":"113","author":"Danks","year":"2020","journal-title":"J. Bus. Res."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0021","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1509\/jmkr.38.2.269.18845","article-title":"Index construction with formative indicators: an alternative to scale development","volume":"38","author":"Diamantopoulos","year":"2001","journal-title":"J. Market. Res."},{"key":"10.1016\/j.csda.2026.108348_bib0022","series-title":"Latent Variables in Linear Stochastic Models: Reflections on \u201cMaximum Likelihood\u201d and \u201cPartial Least Squares\u201d Methods","volume":"1","author":"Dijkstra","year":"1985"},{"key":"10.1016\/j.csda.2026.108348_bib0023","series-title":"Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications","first-page":"55","article-title":"A perfect match between a model and a mode","author":"Dijkstra","year":"2017"},{"key":"10.1016\/j.csda.2026.108348_bib0024","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.csda.2014.07.008","article-title":"Consistent and asymptotically normal PLS estimators for linear structural equations","volume":"81","author":"Dijkstra","year":"2015","journal-title":"Comput. Stat. Data Anal."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0025","doi-asserted-by":"crossref","first-page":"297","DOI":"10.25300\/MISQ\/2015\/39.2.02","article-title":"Consistent partial least squares path modeling","volume":"39","author":"Dijkstra","year":"2015","journal-title":"MIS Quart."},{"issue":"4","key":"10.1016\/j.csda.2026.108348_bib0026","doi-asserted-by":"crossref","first-page":"585","DOI":"10.1007\/s11336-013-9370-0","article-title":"Consistent partial least squares for nonlinear structural equation models","volume":"79","author":"Dijkstra","year":"2014","journal-title":"Psychometrika"},{"key":"10.1016\/j.csda.2026.108348_bib0027","first-page":"663","article-title":"Recent developments in PLS","volume":"52","author":"Evermann","year":"2023","journal-title":"Commun. Assoc. Inf. Syst."},{"key":"10.1016\/j.csda.2026.108348_bib0028","series-title":"Genetic Programming","first-page":"3","article-title":"A self-adaptive approach to exploit topological properties of different GAs\u2019 crossover operators","author":"Ferreira","year":"2023"},{"issue":"4","key":"10.1016\/j.csda.2026.108348_bib0029","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1177\/002224299606000403","article-title":"The american customer satisfaction index: nature, purpose, and findings","volume":"60","author":"Fornell","year":"1996","journal-title":"J. Mark."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0030","doi-asserted-by":"crossref","first-page":"iii","DOI":"10.2307\/23044042","article-title":"An update and extension to SEM guidelines for administrative and social science research","volume":"35","author":"Gefen","year":"2011","journal-title":"MIS Quart."},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0031","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1093\/biomet\/61.1.101","article-title":"A predictive approach to the random effect model","volume":"61","author":"Geisser","year":"1974","journal-title":"Biometrika"},{"key":"10.1016\/j.csda.2026.108348_bib0032","series-title":"Springer Handbook of Engineering Statistics","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1007\/978-1-4471-7503-2_33","article-title":"Genetic algorithms and their applications","author":"Gen","year":"2023"},{"key":"10.1016\/j.csda.2026.108348_bib0033","series-title":"Tabu Search","author":"Glover","year":"1998"},{"issue":"4","key":"10.1016\/j.csda.2026.108348_bib0034","first-page":"964","article-title":"A simple genetic algorithm for multiple sequence alignment","volume":"6","author":"Gondro","year":"2007","journal-title":"Gen. Mol. Res."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0035","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1007\/s10651-007-0047-7","article-title":"Representing general theoretical concepts in structural equation models: the role of composite variables","volume":"15","author":"Grace","year":"2008","journal-title":"Environ. Ecol. Stat."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0036","doi-asserted-by":"crossref","first-page":"139","DOI":"10.2753\/MTP1069-6679190202","article-title":"PLS-SEM: indeed a silver bullet","volume":"19","author":"Hair","year":"2011","journal-title":"J. Market. Theory Prac."},{"issue":"6","key":"10.1016\/j.csda.2026.108348_bib0037","doi-asserted-by":"crossref","first-page":"1923","DOI":"10.1007\/s00521-020-05035-x","article-title":"An efficient optimization approach for designing machine learning models based on genetic algorithm","volume":"33","author":"Hamdia","year":"2021","journal-title":"Neural Comput. Appl."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0038","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1111\/j.2517-6161.1979.tb01072.x","article-title":"The determination of the order of an autoregression","volume":"41","author":"Hannan","year":"1979","journal-title":"J. R. Stat. Soc. Ser. B (Methodol.)"},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0039","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11135-018-0689-6","article-title":"Partial least squares path modeling: Quo vadis?","volume":"52","author":"Henseler","year":"2018","journal-title":"Qual. Quant."},{"key":"10.1016\/j.csda.2026.108348_bib0040","series-title":"Composite-Based Structural Equation Modeling: Analyzing Latent and Emergent Variables","author":"Henseler","year":"2021"},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0041","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1177\/1094428114526928","article-title":"Common beliefs and reality about PLS: comments on R\u00f6nkk\u00f6 and Evermann (2013)","volume":"17","author":"Henseler","year":"2014","journal-title":"Organ. Res. Methods"},{"issue":"3","key":"10.1016\/j.csda.2026.108348_bib0042","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1108\/IMR-09-2014-0304","article-title":"Testing measurement invariance of composites using partial least squares","volume":"33","author":"Henseler","year":"2016","journal-title":"Int. Market. Rev."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0043","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1007\/s00180-012-0317-1","article-title":"Goodness-of-fit indices for partial least squares path modeling","volume":"28","author":"Henseler","year":"2013","journal-title":"Comput. Stat."},{"key":"10.1016\/j.csda.2026.108348_bib0044","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.jbusres.2020.07.026","article-title":"Using confirmatory composite analysis to assess emergent variables in business research","volume":"120","author":"Henseler","year":"2020","journal-title":"J. Bus. Res."},{"key":"10.1016\/j.csda.2026.108348_bib0045","series-title":"Composite-based Structural Equation Modeling: Analyzing Latent and Emergent Variables","first-page":"25","article-title":"Auxiliary theories","author":"Henseler","year":"2021"},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0046","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1038\/scientificamerican0792-66","article-title":"Genetic algorithms","volume":"267","author":"Holland","year":"1992","journal-title":"Sci. Am."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0047","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1007\/s11336-017-9572-y","article-title":"Asymptotics of AIC, BIC, and RMSEA for model selection in structural equation modeling","volume":"82","author":"Huang","year":"2017","journal-title":"Psychometrika"},{"key":"10.1016\/j.csda.2026.108348_bib0048","series-title":"Systems under Indirect Observation: Causality, Structure, Prediction Part II","first-page":"119","article-title":"Consistency and consistency at large of partial least squares estimates","author":"Hui","year":"1982"},{"issue":"3","key":"10.1016\/j.csda.2026.108348_bib0049","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1037\/met0000336","article-title":"An approach to structural equation modeling with both factors and components: integrated generalized structured component analysis","volume":"26","author":"Hwang","year":"2021","journal-title":"Psychol. Methods"},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0050","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1007\/BF02295841","article-title":"Generalized structured component analysis","volume":"69","author":"Hwang","year":"2004","journal-title":"Psychometrika"},{"issue":"5","key":"10.1016\/j.csda.2026.108348_bib0051","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1080\/10705511.2021.2020119","article-title":"Model specification searches in structural equation modeling with a hybrid ant colony optimization algorithm","volume":"29","author":"Jing","year":"2022","journal-title":"Struc. Eq. Model. Multidiscip. J."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0052","first-page":"i","article-title":"A general method for estimating a linear structural equation system","volume":"1970","author":"J\u00f6reskog","year":"1970","journal-title":"ETS Res. Bull. Ser."},{"key":"10.1016\/j.csda.2026.108348_bib0053","series-title":"Lisrel 8: structural equation modeling with the SIMPLIS command language","author":"J\u00f6reskog","year":"1993"},{"key":"10.1016\/j.csda.2026.108348_bib0054","series-title":"Proceedings of the Genetic and Evolutionary Computation Conference","first-page":"914","article-title":"Large language model-based test case generation for GP agents","author":"Jorgensen","year":"2024"},{"key":"10.1016\/j.csda.2026.108348_bib0055","doi-asserted-by":"crossref","DOI":"10.3389\/fpsyg.2018.00174","article-title":"Consistent partial least squares path modeling via regularization","volume":"9","author":"Jung","year":"2018","journal-title":"Front. Psychol."},{"issue":"3","key":"10.1016\/j.csda.2026.108348_bib0056","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1108\/IntR-12-2017-0509","article-title":"Methodological research on partial least squares structural equation modeling (PLS-SEM): an analysis based on social network approaches","volume":"29","author":"Khan","year":"2019","journal-title":"Internet Res."},{"issue":"4598","key":"10.1016\/j.csda.2026.108348_bib0057","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1126\/science.220.4598.671","article-title":"Optimization by simulated annealing","volume":"220","author":"Kirkpatrick","year":"1983","journal-title":"Science"},{"issue":"3","key":"10.1016\/j.csda.2026.108348_bib0058","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1145\/3551783.3551787","article-title":"Multigroup analysis in information systems research using PLS-PM: a systematic investigation of approaches","volume":"53","author":"Klesel","year":"2022","journal-title":"Data Base Adv. Inf. Syst."},{"key":"10.1016\/j.csda.2026.108348_bib0059","series-title":"Principles and Practice of Structural Equation Modeling","author":"Kline","year":"2023"},{"issue":"3","key":"10.1016\/j.csda.2026.108348_bib0060","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1080\/00273170802285743","article-title":"Item selection for the development of short forms of scales using an ant colony optimization algorithm","volume":"43","author":"Leite","year":"2008","journal-title":"Multivariate Behav. Res."},{"key":"10.1016\/j.csda.2026.108348_bib0061","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2022.101223","article-title":"Inferring p systems from their computing steps: an evolutionary approach","volume":"76","author":"Leporati","year":"2023","journal-title":"Swarm Evol. Comput."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0062","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1111\/deci.12445","article-title":"Prediction: coveted, yet forsaken? introducing a cross-validated predictive ability test in partial least squares path modeling","volume":"52","author":"Liengaard","year":"2021","journal-title":"Decis. Sci."},{"key":"10.1016\/j.csda.2026.108348_bib0063","series-title":"Latent Variable Path Modeling with Partial Least Squares","author":"Lohm\u00f6ller","year":"1989"},{"key":"10.1016\/j.csda.2026.108348_bib0064","series-title":"Covariance Structure Models: An Introduction to LISREL","author":"Long","year":"1983"},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0065","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1037\/0033-2909.100.1.107","article-title":"Specification searches in covariance structure modeling","volume":"100","author":"MacCallum","year":"1986","journal-title":"Psychol. Bull."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0066","first-page":"1","article-title":"Using simulated annealing for model selection in multiple regression analysis","volume":"25","author":"Marcoulides","year":"1999","journal-title":"Multiple Linear Regres. Viewpoints"},{"key":"10.1016\/j.csda.2026.108348_bib0067","series-title":"New Developments and Techniques in Structural Equation Modeling","first-page":"267","article-title":"Specification searches in structural equation modeling with a genetic algorithm","author":"Marcoulides","year":"2001"},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0068","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1207\/S15328007SEM1001_8","article-title":"Model specification searches using ant colony optimization algorithms","volume":"10","author":"Marcoulides","year":"2003","journal-title":"Struc. Eq. Model. Multidiscip. J."},{"issue":"4","key":"10.1016\/j.csda.2026.108348_bib0069","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1080\/10705519809540112","article-title":"Model specification searches in structural equation modeling using tabu search","volume":"5","author":"Marcoulides","year":"1998","journal-title":"Struc. Eq. Model. Multidiscip. J."},{"issue":"3","key":"10.1016\/j.csda.2026.108348_bib0070","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1108\/JHTT-09-2017-0106","article-title":"PLS Path modeling - a confirmatory approach to study tourism technology and tourist behavior","volume":"9","author":"M\u00fcller","year":"2018","journal-title":"J. Hospit. Tourism Technol."},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0071","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1006\/jmps.1999.1283","article-title":"The importance of complexity in model selection","volume":"44","author":"Myung","year":"2000","journal-title":"J. Math. Psychol."},{"issue":"3","key":"10.1016\/j.csda.2026.108348_bib0072","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1007\/s41965-023-00125-w","article-title":"A grammatical evolution approach to the automatic inference of p systems","volume":"5","author":"Nadizar","year":"2023","journal-title":"J. Membrane Comput."},{"key":"10.1016\/j.csda.2026.108348_bib0073","series-title":"Systems under Indirect Observation: Causality, Structure, Prediction Part II","first-page":"75","article-title":"PLS Path modeling with indirectly observed variables: a comparison of alternative estimates for the latent variable","author":"Noonan","year":"1982"},{"key":"10.1016\/j.csda.2026.108348_bib0074","series-title":"European Conference on Genetic Programming (Part of EvoStar)","first-page":"19","article-title":"Combining geometric semantic gp with gradient-descent optimization","author":"Pietropolli","year":"2022"},{"key":"10.1016\/j.csda.2026.108348_bib0075","doi-asserted-by":"crossref","unstructured":"Rademaker, M. E., Schuberth, F., 2020. cSEM: Composite-Based Structural Equation Modeling. Package version: 0.6.1.9000. https:\/\/floschuberth.github.io\/cSEM\/.","DOI":"10.32614\/CRAN.package.cSEM"},{"issue":"3","key":"10.1016\/j.csda.2026.108348_bib0076","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1108\/IntR-12-2017-0525","article-title":"Measurement error correlation within blocks of indicators in consistent partial least squares","volume":"29","author":"Rademaker","year":"2019","journal-title":"Internet Res."},{"issue":"4","key":"10.1016\/j.csda.2026.108348_bib0077","doi-asserted-by":"crossref","first-page":"627","DOI":"10.1109\/TEVC.2015.2505317","article-title":"An enhanced genetic algorithm for Ab initio protein structure prediction","volume":"20","author":"Rashid","year":"2015","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0078","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1207\/S15327906Mb340204","article-title":"On structural equation model equivalence","volume":"34","author":"Raykov","year":"1999","journal-title":"Multivariate Behav. Res."},{"issue":"4","key":"10.1016\/j.csda.2026.108348_bib0079","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1016\/j.ijresmar.2009.08.001","article-title":"An empirical comparison of the efficacy of covariance-based and variance-based SEM","volume":"26","author":"Reinartz","year":"2009","journal-title":"Int. J. Res. Market."},{"issue":"3","key":"10.1016\/j.csda.2026.108348_bib0080","doi-asserted-by":"crossref","first-page":"4","DOI":"10.15358\/0344-1369-2017-3-4","article-title":"On comparing results from CB-SEM and PLS-SEM: five perspectives and five recommendations","volume":"39","author":"Rigdon","year":"2017","journal-title":"Marketing ZFP"},{"issue":"12","key":"10.1016\/j.csda.2026.108348_bib0081","doi-asserted-by":"crossref","first-page":"1617","DOI":"10.1080\/09585192.2017.1416655","article-title":"Partial least squares structural equation modeling in HRM research","volume":"31","author":"Ringle","year":"2020","journal-title":"Int. J. Human Resour. Manag."},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0082","doi-asserted-by":"crossref","first-page":"iii","DOI":"10.2307\/41410402","article-title":"A critical look at the use of PLS-SEM in MIS quarterly","volume":"36","author":"Ringle","year":"2012","journal-title":"MIS Quart."},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0083","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1109\/TEVC.2018.2844116","article-title":"Multiobjective metaheuristic to design RNA sequences","volume":"23","author":"Rubio-Largo","year":"2018","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"38","key":"10.1016\/j.csda.2026.108348_bib0084","first-page":"1","article-title":"Evolving neural networks with genetic algorithms to study the string landscape","volume":"2017","author":"Ruehle","year":"2017","journal-title":"J. High Energy Phys."},{"key":"10.1016\/j.csda.2026.108348_bib0085","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.1002\/mar.21640","article-title":"Progress in partial least squares structural equation modeling use in marketing research in the last decade","volume":"39","author":"Sarstedt","year":"2022","journal-title":"Psychol. Market."},{"issue":"5","key":"10.1016\/j.csda.2026.108348_bib0086","doi-asserted-by":"crossref","first-page":"1035","DOI":"10.1002\/mar.21640","article-title":"Progress in partial least squares structural equation modeling use in marketing research in the last decade","volume":"39","author":"Sarstedt","year":"2022","journal-title":"Psychol. Market."},{"issue":"6","key":"10.1016\/j.csda.2026.108348_bib0087","doi-asserted-by":"crossref","first-page":"1789","DOI":"10.1108\/IMDS-07-2022-0418","article-title":"Conducting monte carlo simulations with PLS-PM and other variance-based estimators for structural equation models: a tutorial using the R package cSEM","volume":"123","author":"Schamberger","year":"2023","journal-title":"Indus. Manag. Data Syst."},{"key":"10.1016\/j.csda.2026.108348_bib0088","series-title":"Partial Least Squares Path Modeling -","first-page":"155","article-title":"Revisiting and extending PLS for ordinal measurement and prediction","author":"Schamberger","year":"2023"},{"key":"10.1016\/j.csda.2026.108348_bib0089","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1007\/s41237-019-00088-2","article-title":"Robust partial least squares path modeling","volume":"47","author":"Schamberger","year":"2020","journal-title":"Behaviormetrika"},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0090","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1177\/00131644231160552","article-title":"Model specification searches in structural equation modeling using bee swarm optimization","volume":"84","author":"Schroeders","year":"2024","journal-title":"Educ. Psychol. Meas."},{"issue":"4","key":"10.1016\/j.csda.2026.108348_bib0091","doi-asserted-by":"crossref","first-page":"843","DOI":"10.1037\/met0000432","article-title":"The Henseler-Ogasawara specification of composites in structural equation modeling: a tutorial","volume":"28","author":"Schuberth","year":"2023","journal-title":"Psychol. Methods"},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0092","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1007\/s11135-016-0401-7","article-title":"Partial least squares path modeling using ordinal categorical indicators","volume":"52","author":"Schuberth","year":"2018","journal-title":"Qual. Quant."},{"issue":"6","key":"10.1016\/j.csda.2026.108348_bib0093","doi-asserted-by":"crossref","first-page":"1678","DOI":"10.1108\/EJM-08-2020-0586","article-title":"Assessing the overall fit of composite models estimated by partial least squares path modeling","volume":"57","author":"Schuberth","year":"2023","journal-title":"Eur. J. Mark."},{"key":"10.1016\/j.csda.2026.108348_bib0094","doi-asserted-by":"crossref","first-page":"4205","DOI":"10.3758\/s13428-023-02256-5","article-title":"More powerful parameter tests? no, rather biased parameter estimates. some reflections on path analysis with weighted composites","volume":"56","author":"Schuberth","year":"2024","journal-title":"Behav. Res. Methods"},{"key":"10.1016\/j.csda.2026.108348_bib0095","first-page":"711","article-title":"Partial least squares is an estimator for structural equation models: a comment on Evermann and R\u00f6nkk\u00f6 (2021)","volume":"52","author":"Schuberth","year":"2023","journal-title":"Commun. Assoc. Inf. Syst."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0096","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1214\/aos\/1176344136","article-title":"Estimating the dimension of a model","volume":"6","author":"Schwarz","year":"1978","journal-title":"Ann. Stat."},{"key":"10.1016\/j.csda.2026.108348_bib0097","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v053.i04","article-title":"Ga: a package for genetic algorithms in r","volume":"53","author":"Scrucca","year":"2013","journal-title":"J. Stat. Softw."},{"issue":"4","key":"10.1016\/j.csda.2026.108348_bib0098","first-page":"346","article-title":"PLS-based model selection: the role of alternative explanations in information systems research","volume":"20","author":"Sharma","year":"2019","journal-title":"J. Assoc. Inf. Syst."},{"issue":"3","key":"10.1016\/j.csda.2026.108348_bib0099","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1111\/deci.12329","article-title":"Prediction-oriented model selection in partial least squares path modeling","volume":"52","author":"Sharma","year":"2021","journal-title":"Decis. Sci."},{"issue":"3","key":"10.1016\/j.csda.2026.108348_bib0100","doi-asserted-by":"crossref","first-page":"553","DOI":"10.2307\/23042796","article-title":"Predictive analytics in information systems research","volume":"35","author":"Shmueli","year":"2011","journal-title":"MIS Quart."},{"issue":"10","key":"10.1016\/j.csda.2026.108348_bib0101","doi-asserted-by":"crossref","first-page":"4552","DOI":"10.1016\/j.jbusres.2016.03.049","article-title":"The elephant in the room: predictive performance of PLS models","volume":"69","author":"Shmueli","year":"2016","journal-title":"J. Bus. Res."},{"key":"10.1016\/j.csda.2026.108348_bib0102","series-title":"2015 International Conference on Futuristic Trends on Computational Analysis and Knowledge Management (ABLAZE)","first-page":"515","article-title":"Comparative review of selection techniques in genetic algorithm","author":"Shukla","year":"2015"},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0103","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1111\/j.2517-6161.1974.tb00994.x","article-title":"Cross-validatory choice and assessment of statistical predictions","volume":"36","author":"Stone","year":"1974","journal-title":"J. R. Stat. Soc. Ser. B Stat. Methodol."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0104","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1137\/0201010","article-title":"Depth-first search and linear graph algorithms","volume":"1","author":"Tarjan","year":"1972","journal-title":"SIAM J. Comput."},{"key":"10.1016\/j.csda.2026.108348_bib0105","unstructured":"R. C. Team, 2023. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna, Austria. https:\/\/www.R-project.org\/."},{"key":"10.1016\/j.csda.2026.108348_bib0106","series-title":"Proceedings of the XLII SIS Scientific Meeting","first-page":"739","article-title":"A global goodness-of-fit index for PLS structural equation modelling","volume":"1","author":"Tenenhaus","year":"2004"},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0107","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.csda.2004.03.005","article-title":"PLS Path modeling","volume":"48","author":"Tenenhaus","year":"2005","journal-title":"Comput. Stat. Data Anal."},{"key":"10.1016\/j.csda.2026.108348_bib0108","series-title":"Proceedings of the Genetic and Evolutionary Computation Conference Companion","first-page":"2119","article-title":"Genetic programming for the reconstruction of delay differential equations in economics","author":"Tonelli","year":"2024"},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0109","article-title":"Crossover operators in genetic algorithms: a review","volume":"6","author":"Umbarkar","year":"2015","journal-title":"ICTACT J. Soft Comput."},{"issue":"2","key":"10.1016\/j.csda.2026.108348_bib0110","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1111\/j.1540-5915.2008.00192.x","article-title":"Technology acceptance model 3 and a research agenda on interventions","volume":"39","author":"Venkatesh","year":"2008","journal-title":"Decis. Sci."},{"issue":"3","key":"10.1016\/j.csda.2026.108348_bib0111","doi-asserted-by":"crossref","first-page":"425","DOI":"10.2307\/30036540","article-title":"User acceptance of information technology: toward a unified view","volume":"27","author":"Venkatesh","year":"2003","journal-title":"MIS Quart."},{"issue":"1","key":"10.1016\/j.csda.2026.108348_bib0112","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1006\/jmps.1999.1278","article-title":"Bayesian model selection and model averaging","volume":"44","author":"Wasserman","year":"2000","journal-title":"J. Math. Psychol."},{"key":"10.1016\/j.csda.2026.108348_bib0113","series-title":"Quantitative Sociology","first-page":"307","article-title":"Path models with latent variables: the NIPALS approach","author":"Wold","year":"1975"},{"key":"10.1016\/j.csda.2026.108348_bib0114","series-title":"Systems under Indirect Observation: Causality, Structure, Prediction Part II","first-page":"1","article-title":"Soft modeling: the basic design and some extensions","author":"Wold","year":"1982"},{"key":"10.1016\/j.csda.2026.108348_bib0115","series-title":"Encyclopaedia of Statistical Sciences","first-page":"581","article-title":"Partial least squares","volume":"6","author":"Wold","year":"1985"},{"issue":"4","key":"10.1016\/j.csda.2026.108348_bib0116","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1002\/sam.11608","article-title":"Specifying composites in structural equation modeling: a refinement of the henseler\u2013ogasawara specification","volume":"16","author":"Yu","year":"2023","journal-title":"Stat. Anal. Data Min. ASA Data Sci. J."},{"issue":"SI","key":"10.1016\/j.csda.2026.108348_bib0117","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1145\/3505639.3505647","article-title":"Counterpoint: representing forged concepts as emergent variables using composite-based structural equation modeling","volume":"52","author":"Yu","year":"2021","journal-title":"ACM SIGMIS Database DATABASE Adv. Inf. Syst."},{"issue":"4","key":"10.1016\/j.csda.2026.108348_bib0118","doi-asserted-by":"crossref","first-page":"1064","DOI":"10.1111\/sjos.12084","article-title":"Selection of latent variables for multiple mixed-outcome models","volume":"41","author":"Zhou","year":"2014","journal-title":"Scand. J. Stat."}],"container-title":["Computational Statistics & Data Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0167947326000174?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0167947326000174?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T09:29:43Z","timestamp":1774344583000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0167947326000174"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":118,"alternative-id":["S0167947326000174"],"URL":"https:\/\/doi.org\/10.1016\/j.csda.2026.108348","relation":{},"ISSN":["0167-9473"],"issn-type":[{"value":"0167-9473","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Automated specification search for composite-based structural equation modeling: A genetic approach","name":"articletitle","label":"Article Title"},{"value":"Computational Statistics & Data Analysis","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.csda.2026.108348","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"108348"}}