Ali, F., Rasoolmanesh, S. M., Sarstedt, M., Ringle, C. M., Ryu, K.: An Assessment of the Use of Partial Least Squares Structural Equation Modeling (PLS-SEM) in Hospitality Research. The International Journal of Contemporary Hospitality Management, Volume 30 (2018), Issue 1, pp. 514-538. https://www.emeraldinsight.com/doi/full/10.1108/IJCHM-10-2016-0568

 

Ahrholdt, D. C., Gudergan, S. P., Ringle, C. M.: Enhancing Service Loyalty: The Roles of Delight, Satisfaction, and Service Quality. Journal of Travel Research, Volume 56 (2017), Issue 4, pp. 436-450. http://journals.sagepub.com/doi/10.1177/0047287516649058

 

Avkiran, N. K., Ringle, C. M., Low, R. K. Y.: Monitoring Transmission of Systemic Risk: Application of Partial Least Squares Structural Equation Modeling in Financial Stress Testing. Journal of Risk, Volume 20 (2018), Issue (5), pp. 83-115. http://doi.org/10.21314/JOR.2018.386

 

Becker, J.-M., Ismail, I. R.: Accounting for Sampling Weights in PLS Path Modeling: Simulations and Empirical Examples, European Managament Journal, Volume 34 (2016), Issue (6), pp. 606-617. https://doi.org/10.1016/j.emj.2016.06.009

 

Becker, J.-M., Ringle, C. M., Sarstedt, M.: Estimating Moderating Effects in PLS-SEM and PLSc-SEM: Interaction Term Generation*Data Treatment. Journal of Applied Structural Equation Modeling, Volume 2 (2018), Issue 2, pp. 1-21. http://jasemjournal.com/journal-of-applied-structural-equation-modeling-volume-2-issue-2-june-2018/jasem_22_becker-et-al-2018/

 

Chaouali, W., Souiden, N., Ringle, C. M.: Elderly Customers' Reactions to Service Failures: The Role of Future Time Perspctive, Wisdom and Emotional Intelligence. Journal of Services Marketing, forthcoming. https://doi.org/10.1108/JSM-08-2019-0318

 

Cheah, J.-H., Sarstedt, M., Ringle, C. M., Ramayah, T., Ting, H:  Convergent Validity Assessment of Formatively Measured Constructs in PLS-SEM: On Using Single-item versus Multi-item Measures in Redundancy Analyses. International Journal of Contemporary Hospitality Management, Volume 30 (2018), Issue 11, pp. 3192-3210. https://www.emeraldinsight.com/doi/abs/10.1108/IJCHM-10-2017-0649

 

Chin, W., Cheah, J.-H., Liu, Y., Ting, H., Lim, X.-J., Cham, T. H.: Demystifying the Role of Causal-Predictive Modeling Using Partial Least Squares Structural Modeling in Information Systems Research. Industrial Managament & Data Systems, forthcoming. https://doi.org/10.1108/IMDS-10-2019-0529

 

Cho, G., Hwang, H., Sarstedt, M., Ringle, C. M.: Cutoff Criteria for Overall Model Fit Indexes in Generalized Structured Component Analysis. Journal of Marketing Analytics, Volume 8 (2020) Issue 4, pp. 189-202. https://doi.org/10.1057/s41270-020-00089-1

 

Franke, G. R., Sarstedt, M.: Heuristics Versus Statistics in Discriminant Validity Testing: A Comparison of Four Procedures, Internet Research, Volume 29 (2019), Issue 3, pp. 430-447. https://doi.org/10.1108/IntR-12-2017-0515

 

Ghasemy, M., Teeroovengadum, V., Becker, J.-M., & Ringle, C. M.: This Fast Car Can Move Faster: A Review of PLS-SEM Application in Higher Education Research, Higher Education, forthcoming. https://doi.org/10.1007/s10734-020-00534-1

 

Gudergan, S., Ringle, C. M., Wende, S., Will, A.: Confirmatory Tetrad Analysis in PLS Path Modeling. Journal of Business Research (JBR), Volume 61 (2008), Issue 12, pp. 1238-1249. http://linkinghub.elsevier.com/retrieve/pii/S0148296308000143

 

Hair, J. F., Binz Astrachan, C., Moisescu, O. I., Radomir, L., Sarstedt, M., Vaithilingam, S., Ringle, C. M.: Executing and Interpreting Applications of PLS-SEM: Updates for Family Business Researchers, Journal of Family Business Strategy, forthcoming. https://doi.org/10.1016/j.jfbs.2020.100392

 

Hair, J. F., Howard, M. C., Nitzl, C.: Assessing Measurement Model Quality in PLS-SEM Using Confirmatory Composite Analysis, Journal of Business Research, Volume 109 (2020), pp. 101-110. https://doi.org/10.1016/j.jbusres.2019.11.069

 

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M.: A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 2nd ed. Sage, Thousand Oaks (2017). https://uk.sagepub.com/en-gb/eur/a-primer-on-partial-least-squares-structural-equation-modeling-pls-sem/book244583

 

Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Thiele, K. O.: Mirror, Mirror on the Wall: A Comparative Evaluation of Composite-based Structural Equation Modeling Methods. Journal of the Academy of Marketing Science, Volume 45 (2017), Issue 5, pp. 616-632. https://link.springer.com/article/10.1007/s11747-017-0517-x

 

Hair, J. F., Ringle, C. M., Gudergan, S. P., Fischer, A., Nitzl, C., Menictas, C.: Partial Least Squares Structural Equation Modeling-based Discrete Choice Modeling: An Illustration in Modeling Retailer Choice. Business Research, Volume 12 (2019), pp. 115-140. http://doi.org/10.1007/s40685-018-0072-4

 

Hair, J. F., Ringle, C. M., Sarstedt, M.: PLS-SEM: Indeed a Silver Bullet. Journal of Marketing Theory and Practice (JMTP), Volume 19 (2011), Issue 2, pp. 139-152. https://www.tandfonline.com/doi/abs/10.2753/MTP1069-6679190202

 

Hair, J. F., Ringle, C. M., Sarstedt, M.: Partial Least Squares: The Better Approach to Structural Equation Modeling? Long Range Planning, Volume 45 (2012), Issue 5-6, pp. 312-319. http://www.sciencedirect.com/science/article/pii/S0024630112000593

 

Hair, J. F., Ringle, C. M., Sarstedt, M.: Partial Least Squares Structural Equation Modeling: Rigorous Applications, Better Results and Higher Acceptance. Long Range Planning, Volume 46 (2013), Issue 1-2, pp. 1-12. http://www.sciencedirect.com/science/article/pii/S0024630113000022

 

Hair, J. F., Risher, J. J., Sarstedt, M., Ringle, C. M.: When to Use and how to Report the Results of PLS-SEM, European Business Review, Volume 31 (2019), Issue 1, pp. 2-24. https://doi.org/10.1108/EBR-11-2018-0203

 

Hair, J. F., Sarstedt, M., Pieper, T., Ringle, C. M.: 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 (LRP), Volume 45 (2012), Issue 5-6, pp. 320-340. http://www.sciencedirect.com/science/article/pii/S0024630112000568

 

Hair, J. F., Sarstedt, M., Ringle, C. M.: Rethinking Some of the Rethinking of Partial Least Squares, European Journal of Marketing, Volume 53 (2019), Issue 4, pp. 566-584. https://doi.org/10.1108/EJM-10-2018-0665

 

Hair, J. F., Sarstedt, M., Ringle, C. M., Mena, J. A.: An Assessment of the Use of Partial Least Squares Structural Equation Modeling in Marketing Research. Journal of the Academy of Marketing Science (JAMS), Volume 40 (2012), Issue 3, pp. 414-433. http://www.springerlink.com/content/t502155t60nv8005/

 

Henseler, J.: Why Generalized Structured Component Analysis Is Not Universally Preferable to Structural Equation Modeling. Journal of the Academy of Marketing Science, Volume 40 (2012), Issue 3, pp. 402-413. http://www.springerlink.com/content/m538w5208r940658/

 

Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., Ketchen, D. J. J., Hair, J. F., Hult, G. T. M., and Calantone, R. J.: Common Beliefs and Reality about Partial Least Squares: Comments on Rönkkö & Evermann (2013). Organizational Research Methods, Volume 17 (2014), Issue 2, pp. 182-209. http://orm.sagepub.com/content/17/2/182.full.pdf+html

 

Henseler, J., Ringle, C. M., Sarstedt, M.: A New Criterion for Assessing Discriminant Validity in Variance-based Structural Equation Modeling. Journal of the Academy of Marketing Science, Volume 43 (2015), Issue 1, pp. 115-135. http://link.springer.com/article/10.1007/s11747-014-0403-8

 

Henseler, J., Ringle, C. M., Sarstedt, M.: Using Partial Least Squares Path Modeling in International Advertising Research: Basic Concepts and Recent Issues. Okazaki (Ed.), Handbook of Research in International Advertising, Cheltenham: Edward Elgar Publishing, pp. 252-276. http://www.elgaronline.com/abstract/9781848448582.00023.xml

 

Henseler, J., Ringle, C. M., Sinkovics, R. R.: The Use of Partial Least Squares Path Modeling in International Marketing. Sinkovics, R. R., Ghauri, P. N. (eds.), Advances in International Marketing (AIM), Vol. 20, Bingley 2009, pp. 277-320. http://www.emeraldinsight.com/books.htm?chapterid=1775963&show=abstract

 

Henseler, J., Sarstedt, M.: Goodness-of-Fit Indices for Partial Least Squares Path Modeling. Computational Statistics, Volume 28 (2013), Issue 2, pp. 565-580. http://link.springer.com/article/10.1007/s00180-012-0317-1

 

Hult, G. T. M., Hair, J. F., Proksch, D., Sarstedt, M., Pinkwart, A., Ringle, C. M: Addressing Endogeneity in International Marketing Applications of Partial Least Squares Structural Equation Modeling. Journal of International Marketing, Volume 26 (2018), Issue 3, pp. 1-21. http://doi.org/10.1509/jim.17.0151

 

Hwang, H., Sarstedt, M., Cheah, J. H., & Ringle, C. M.: A Concept Analysis of Methodological Research on Composite-Based Structural Equation Modeling: Bridging PLSPM and GSCA, Behaviormetrika, Volume 47 (2020), pp. 219-241. https://doi.org/10.1007/s41237-019-00085-5

 

Kawalla, C., Höck, M., Ullmann, M., Ringle, C. M.: An Empirical Examination of the Thickness Profile Formation of Twin-Roll-Cast Magnesium Strips. Archives of Civil and Mechanical Engineering, Volume 18 (2018), Issue 1, pp. 227-234. https://www.sciencedirect.com/science/article/pii/S1644966517300791?via%3Dihub

 

Khan, G.F., Sarstedt, M., Shiau, W.L., Hair, J.F., Ringle, C.M., Fritze, M.P.: Methodological Research on Partial Least Squares Structural Equation Modeling (PLS-SEM): An Analysis Based on Social Network Approaches. Internet Research, Volume 29 (2019), Issue 3, pp. 407-429. https://doi.org/10.1108/IntR-12-2017-0509

 

Kotilainen, K., Saari, U. A., Mäkinen, S. J., Ringle, C. M.: Exploring the Microfoundations of End-user Interests toward Co-creating Renewable Energy Technology Innovations, Journal of Cleaner Production, Volume 229 (2019), 203-212. https://doi.org/10.1016/j.jclepro.2019.04.296

 

Latan, H., Ringle, C.M., Jabbour, C.J.C.: Whistleblowing Intentions Among Public Accountants in Indonesia: Testing for the Moderation Effects. Journal of Business Ethics, Volume 152 (2018), Issue 2, pp. 573-588. https://link.springer.com/article/10.1007/s10551-016-3318-0

 

Liengaard, B. D., Sharma, P. N., Hult, G. T. M., Jensen, M. B., Sarstedt, M., Hair, J. F., Ringle, C. M. : Prediction: Coveted, Yet Forsaken? Introducing a Cross-Validated Predictive Ability Test in Partial Least Squares Path Modeling, Decision Sciences, Volume 52 (2021), Issue 2, pp. 362-392. https://doi.org/10.1111/deci.12445

 

Liu, Y., Ting, H., Ringle, C. M.: Appreciation to and Behavior Intention Regarding Upscale Ethnic Restaurants, Journal of Hospitality & Tourism Research, forthcoming. https://doi.org/10.1177/10963480211011544
 

Nunkoo, R., Teeroovengadum, V., Ringle, C. M., Sunnassee, V.: Service Quality and Customer Satisfaction: The Moderating Effects of Hotel Star Rating, International Journal of Hospitality Management, Volume 91 (2020), Issue 102414. https://doi.org/10.1016/j.ijhm.2019.102414

 

Rasoolimanesh, S. M., Ringle, C. M., Jaafar, M., Ramayah, T.: Urban vs. Rural Destinations: Residents’ Perceptions, Community Participation and Support for Tourism Development. Tourism Management, Volume 60 (2017), pp. 147-158. https://www.sciencedirect.com/science/article/pii/S0261517716302357?via%3Dihub

 

Rasoolimanesh, S. M., Ringle, C. M., Sarstedt, M., Olya, H.: The Combined Use of Symmetric and Asymmetric Approaches: Partial Least Squares-Structural Equation Modeling and Fuzzy-Set Qualitative Comparative Analysis, International Journal of Contemporary Hospitality Management, forthcoming. doi: https://doi.org/10.1108/IJCHM-10-2020-1164

 

Richter, N. F., Schubring, S., Hauff, S., Ringle, C. M., Sarstedt, M.: When Predictors of Outcomes Are Necessary: Guidelines for the Combined Use of PLS-SEM and NCA, Industrial Management & Data Systems, Volume 120 (2020), Issue 12, pp. 2243-2267. https://doi.org/10.1108/IMDS-11-2019-0638

 

Rigdon, E. E., Becker, J.-M., Rai, A., Ringle, C. M., Diamantopoulos, A., Karahanna, E., Straub, D., Dijkstra, T. K.: Conflating Antecedents and Formative Indicators: A Comment on Aguirre-Urreta and Marakas. Information Systems Research, Volume 25 (2014), Issue 4, pp. 780-784. http://dx.doi.org/10.1287/isre.2014.0543

 

Rigdon, E. E., Becker, J.-M., Sarstedt, M.: Factor Indeterminacy as Metrologiacl Uncertainty: Implications for Advancing Psychological Measurement, Multivariate Behavioral Research, Volume 54 (2019), Issue 3, pp. 429-443. https://doi.org/10.1080/00273171.2018.1535420

 

Rigdon, E. E., Becker, J.-M., Sarstedt, M.: Parceling Cannot Reduce Factor Indeterminacy in Factor Analysis: A Research Note, Psychometrika, Volume 84 (2019), Issue (3), pp. 773-780. https://doi.org/10.1007/s11336-019-09677-2

 

Rigdon, E. E., Ringle, C. M., Sarstedt, M., Gudergan, S.P.: Assessing Heterogeneity in Customer Satisfaction Studies: Across Industry Similarities and Within Industry Differences. Advances in International Marketing (AIM), Vol. 22, Bingley 2011, pp. 169-194. https://www.emeraldinsight.com/doi/abs/10.1108/S1474-7979%282011%290000022011

 

Rigdon, E. E., Ringle, C. M., Sarstedt, M.: Structural Modeling of Heterogeneous Data with Partial Least Squares. Malhotra, N.K. (ed.), Review of Marketing Research, Volume 7 (2010), Armonk, pp. 255-296.
http://www.emeraldinsight.com/books.htm?chapterid=1896306&show=abstract

 

Rigdon, E. E., Sarstedt, M., Becker, J.-M.: Quantify Uncertainty in Behavioral Research, Nature Human Behavior, Volume 4 (2020), pp. 329-331. https://doi.org/10.1038/s41562-019-0806-0

 

Rigdon, E. E., Sarstedt, M., Ringle, C. M.: On Comparing Results from CB-SEM and PLS-SEM: Five Perspectives and Five Recommendations. Marketing ZfP - Journal of Research and Management, Volume 39 (2017), Issue 3, pp. 4-16. https://elibrary.vahlen.de/10.15358/0344-1369-2017-3-4.pdf

 

Ringle, C. M., Sarstedt, M., Mitchell, R., Gudergan, S. P.: Partial Least Squares Structural Equation Modeling in HRM Research. The International Journal of Human Resource Management, Volume 31 (2020), Issue 12, pp. 1617-1643. http://doi.org/10.1080/09585192.2017.1416655

 

Ringle, C. M., Sarstedt, M., Mooi, E. A.: Response-based Segmentation Using FIMIX-PLS: Theoretical Foundations and an Application to American customer Satisfaction Index Data. Stahlbock, R., Crone, S. F., Lessmann, S. (eds.): Annals of Information Systems (AoIS), Volume 8, Berlin-Heidelberg: Springer, 2010, pp. 19-49. http://www.springerlink.com/content/j4543621w61w375m/

 

Ringle, C. M., Sarstedt, M., Straub, D. W.: A Critical Look at the Use of PLS-SEM in MIS Quarterly. MIS Quarterly, Volume 36 (2012), Issue 1, pp. iii-xiv. http://misq.org/skin/frontend/default/misq/pdf/V36I1/EdCommentsV36N1.pdf

 

Rosenbusch, J., Ismail, I. R., Ringle, C. M.: The Agony of Choice for Medical Tourists: A Patient Satisfaction Index Mode. Journal of Hospitality and Tourism Technology, Volume 9 (2018), Issue 3, pp. 267-279. https://www.emeraldinsight.com/doi/full/10.1108/JHTT-10-2017-0107

 

Saari, U. A., Damberg, S., Frömbling, L., Ringle, C. M.: Sustainable Consumption Behavior of Europeans: The Influence of Environmental Knowledge and Risk Perception on Environmental Concern and Behavioral Intention, Ecological Economics, Volume 189 (2021), pp. 1-14. https://doi.org/10.1016/j.ecolecon.2021.107155

 

Sarstedt, M., Becker, J.-M., Ringle, C. M., Schwaiger, M.: Uncovering and treating unobserved heterogeneity with FIMIX-PLS: Which model selection criterion provides an appropriate number of segments? Schmalenbach Business Review (sbr), Volume 63 (2011), Issue 1, pp. 34-62. http://www.fachverlag.de/sbr/pdfarchive/einzelne_pdf/sbr_2011_jan_034-06...

 

Sarstedt, M., Hair, J. F., Cheah, J.-H., Becker, J.-M., & Ringle, C. M.: How to Specify, Estimate, and Validate Higher-Order Constructs in PLS-SEM, Australasian Marketing Journal, Volume 27 (2019), Issue 3, pp. 197-211. doi.org/10.1016/j.ausmj.2019.05.003

 

Sarstedt, M., Hair, J. F., Nitzl, C., Ringle, C. M., Howard, M. C.: Beyond a Tandem Analysis of SEM and PROCESS: Use of PLS-SEM for Mediation Analyses!, International Journal of Market Research, Volume 62 (2020), Issue (3), pp. 288-299. https://doi.org/10.1177/1470785320915686

 

Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O., Gudergan, S. P.: Estimation Issues with PLS and CBSEM: Where the Bias Lies! Journal fo Business Research, Volume 69 (2016), Issue 10, pp. 3998-4010. http://www.sciencedirect.com/science/article/pii/S0148296316304404

 

Sarstedt, M., Henseler, J., Ringle, C. M.: Multigroup Analysis in Partial Least Squares (PLS) Path Modeling: Alternative Methods and Empirical Results. Advances in International Marketing (AIM), Vol. 22, Bingley 2011, pp. 195-218. http://www.emeraldinsight.com/books.htm?chapterid=1947659

 

Sarstedt, M., Ringle, C. M.: Treating Unobserved Heterogeneity in PLS Path Modelling: A Comparison of FIMIX-PLS With Different Data Analysis Strategies. Journal of Applied Statistics (JAS), Volume 37 (2010), Issue 8, pp. 1299-1318. https://www.tandfonline.com/doi/abs/10.1080/02664760903030213

 

Sarstedt, M., Ringle, C.M.,  Cheah, J.H., Ting, H., Moisescu, O.I., Radomir, L.: Structural Model Robustness Checks in PLS-SEM. Tourism Economics, Volume 26 (2020), Issue 4, pp. 531-554. https://doi.org/10.1177/1354816618823921

 

Sarstedt, M., Ringle, C.M.,  Hair, J.F.: Partial Least Squares Structural Equation Modeling. Homburg, C., Klarmann, M., and Vomberg, A. (eds.), Handbook of Market Research. Heidelberg: Springer, 2018, pp. 1-40. https://link.springer.com/referenceworkentry/10.1007/978-3-319-05542-8_15-1

 

Sarstedt, M., Ringle, C. M., Hair, J. F.: PLS-SEM: Looking Back and Moving Forward. Long Range Planning, Volume 47 (2014), Issue 3, pp. 132-137. http://www.sciencedirect.com/science/article/pii/S002463011400020X

 

Schirmer, N., Ringle, C. M., Gudergan, S. P., Feistel, M. S. G.: The Link between Customer Satisfaction and Loyalty: The Moderating Role of Customer Characteristics. Journal of Strategic Marketing, Volume 26 (2018), Issue 4, pp. 298-317. http://dx.doi.org/10.1080/0965254X.2016.1240214

 

Schlittgen, R., Sarstedt, M., Ringle, C. M.: Data Generation for Composite-Based Structural Equation Modeling Methods, Advances in Data Analysis and Classification, forthcoming. https://doi.org/10.1007/s11634-020-00396-6

 

Sharma, P. N., Sarstedt, M., Shmueli, G., Kim, K. H., Thiele, K. O.: PLS-Based Model Selection: The Role of Alternative Explanations in Information Systems Research, Journal of the Association for Information Systems, Volume 20 (2019), Issue (4). https://aisel.aisnet.org/jais/vol20/iss4/4

 

Sharma, P. N, Shmueli, G., Sarstedt, M., Danks, N., Ray, S.: Prediction-oriented Model Selection in Partial Least Squares Path Modeling, Decision Science, forthcoming. https://doi.org/10.1111/deci.12329

 

Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J.-H., Ting, H., Vaithilingam, S., Ringle, C. M.: Predictive Model Assessment in PLS-SEM: Guidelines for Using PLSpredict, European Journal of Marketing, Volume 53 (2019), Issue 11, pp. 2322-2347. https://doi.org/10.1108/EJM-02-2019-0189