Take a look at the following articles!

OPEN ACCESS! Methodological Uncertainty: Sarstedt, M./ Adler, S.J./ Ringle, C.M./ Cho, G./ Diamantopoulos, A./ Hwang, H./ Liengaard, B.D.: Same Model, Same Data, But Different Outcomes: Evaluating the Impact of Method Choices in Structural Equation Modeling, Journal of Product Innovation Management, forthcoming.

Composite-Based Structural Equation Modeling: Rigdon, E.E.: Understanding Composite-Based Structural Equation Modeling Methods From the Perspective of Regression Component Analysis, Multivariate Behavioral Research, forthcoming.

OPEN ACCESS! PLS-SEM and missing data: Amusa, L.B./ Hossana, T. An Empirical Comparison of Some Missing Sata Treatments in PLS-SEM, PLOS ONE, Volume 19 (2024), Issue 1, e0297037.

OPEN ACCESS! Uncertainty and mediation: Sarstedt, M./ Moisescu, O.-I. Quantifying Uncertainty in PLS-SEM-based Mediation Analyses, Journal of Marketing Analytics, Volume 12 (2024), Issue 1, pp. 87-96.

OPEN ACCESS! Review of the advanced PLS-SEM book (2e): Gironda, J.T. Review of Advanced Issues in Partial Least Squares Structural Equation Modeling (Second Edition), Journal of Marketing Analytics, Volume 12 (2024), Issue 1, pp. 108-109.

NCA and IPMA in combination: Hauff, S./ Richter, N.F./ Sarstedt, M./ Ringle, C.M.: Importance and Performance in PLS-SEM and NCA: Introducing the Combined Importance-Performance Map Analysis (cIPMA), Journal of Retailing and Consumer Services, Volume 78 (2024), 103723.

On the use of PLS-SEM in research articles: Petter, S./ Hadavi, Y.: Use of Partial Least Squares Path Modeling Within and Across Business Disciplines. In Latan, H./ Hair, J.F./ Noonan, R. (Eds.), Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications (pp. 55-79). Cham: Springer International Publishing, 2023.

NCA in SmartPLS: Richter, N.F./ Hauff, S./ Ringle, C.M./ Sarstedt, M./ Kolev, A.E./ Schubring, S. (2023). How to Apply Necessary Condition Analysis in PLS-SEM. In Latan, H./ Hair, J.F./ Noonan, R. (Eds.), Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications (pp. 267-297). Cham: Springer International Publishing, 2023.

SmartPLS 4 software review article: Cheah, J.-H./ Magno, F./ Cassia, F.: Reviewing the SmartPLS 4 Software: The Latest Features and Enhancements, Journal of Marketing Analytics, Volume 12 (2024), Issue 1, pp. 97-107.

Insightful arguments for the use of PLS-SEM: Cook, D.R./ Forzani, L.: On the Role of Partial Least Squares in Path Analysis for the Social Sciences, Journal of Business Research, Volume 167 (2023), p. 114132.

PLS-SEM in logistics and supply chain management: Wang, S./ Cheah, J.-H./ Wong, C. Y./ Ramayah, T.: Progress in Partial Least Squares Structural Equation Modeling Use in Logistics and Supply Chain Management in the Last Decade: A Structured Literature Review, International Journal of Physical Distribution & Logistics Management, forthcoming.

PLS-SEM and open science: Adler, S.J./ Sharma, P.N./ Radomir, L.: Toward Open Science in PLS-SEM: Assessing the State of the Art and Future Perspectives, Journal of Business Research, Volume 169(2023), pp. 114291.

Mixed methods and PLS-SEM: Kurtaliqi, F./ Lancelot Miltgen, C./ Viglia, G./ Pantin-Sohier, G.: Using Advanced Mixed Methods Approaches: Combining PLS-SEM and Qualitative Studies, Journal of Business Research, 172(2024), pp. 114464.

Measurement invariance assessment:Liengaard, B.D.: Measurement Invariance Testing in Partial Least Squares Structural Equation Modeling, Journal of Business Research, Volume 177(2024), pp. 114581.

PLS-SEM and machine learning: Richter, N.F./ Tudoran, A.A.: Elevating Theoretical Insight and Predictive Accuracy in Business Research: Combining PLS-SEM and Selected Machine Learning Algorithms, Journal of Business Research, 173(2024), pp. 114453.

PLS-SEM robustness checks: Vaithilingam, S./ Ong, C.S./ Moisescu, O.I./ Nair, M.S.: Robustness Checks in PLS-SEM: A Review of Recent Practices and Recommendations for Future Applications in Business Research, Journal of Business Research, 173(2024), pp. 114465.

OPEN ACCESS! On the use of PLS-SEM in business marketing research: Guenther, P./ Guenther, M./ Ringle, C. M./ Zaefarian, G./ Cartwright, S.: Improving PLS-SEM Use for Business Marketing Research, Industrial Marketing Management, Vol. 111 (2023), pp. 127-142.

Predictive power assessment in PLS-SEM: Sharma, P.N./ Liengaard, B.D./ Hair, J.F./ Sarstedt, M./ Ringle, C.M.: Predictive Model Assessment and Selection in Composite-based Modeling Using PLS-SEM: Extensions and Guidelines for Using CVPAT, European Journal of Marketing, Vol. 57(2023), Issue 6, pp. 1662-1677.

A permutation-based MGA approach for longitudinal data in PLS-SEM: Söllner, M./ Mishra, A.N./ Becker, J.-M./ Leimeister, J.M.: Use IT Again? Dynamic Roles of Habit, Intention and Their Interaction on Continued System Use by Individuals in Utilitarian, Volitional Contexts, European Journal of Information Systems, forthcoming.

Review of PLS-SEM studies in quality management: Magno, F./ Cassia, F./ Ringle, C.M.: A Brief Review of Partial Least Squares Structural Equation Modeling (PLS-SEM) Use in Quality Management Studies, The TQM Journal, forthcoming.

Weighted composites vs. CB-SEM: Deng, L./ Yuan, K.-H.: Which Method is More Powerful in Testing the Relationship of Theoretical Constructs? A Meta Comparison of Structural Equation Modeling and Path Analysis with Weighted Composites, Behavior Research Methods, forthcoming.

The legendary silver bullet: Sarstedt, M./ Hair, J.F./ Ringle, C.M.: "PLS-SEM: Indeed a silver bullet" – Retrospective observations and recent advances, Journal of Marketing Theory & Practice, Volume 31 (2023), Issue , pp. 261-275.

On the usefulness of PLS-SEM: Russo, D./ Stol, K.-J.: Don’t Throw the Baby Out With the Bathwater: Comments on “Recent Developments in PLS”, Communications of the Association for Information Systems, Volume 52 (2023), pp. 700-704.

Extraordinary claims: Sharma, P.N./ Liengaard, B.D./ Sarstedt, M./ Hair, J.F./ Ringle, C.M.: Extraordinary Claims Require Extraordinary Evidence: A Comment on “the Recent Developments in PLS”, Communications of the Association for Information Systems, Volume 52 (2023), pp. 739-742.

Most wanted PLS-SEM guidelines: Becker, J.-M./ Cheah, J.H./ Gholamzade, R./ Ringle, C.M./ Sarstedt, M.: PLS-SEM’s Most Wanted Guidance, International Journal of Contemporary Hospitality Management, Volume 35 (2023), Issue 1, pp. 321-346.

Predictive power of components: Cho, G./ Lee, J./ Hwang, H./ Sarstedt, M./ Ringle, C.M.: A Comparative Study of the Predictive Power of Component-based Approaches to Structural Equation Modeling, European Journal of Marketing, Volume 57 (2023), Issue 6, pp. 1641-1661.

OPEN ACCESS! On the use of PLS-SEM and HTMT update: Ringle, C.M./ Sarstedt, M./ Sinkovics, N./ Sinkovics, R.R.: A Perspective on Using Partial Least Squares Structural Equation Modelling in Data Articles, Data in Brief, Volume 48 (2023), p. 109074.

OPEN ACCESS! New corporate reputation model data: Sarstedt, M./ Ringle, C.M./ Iuklanov, D.: Antecedents and Consequences of Corporate Reputation: A Dataset, Data in Brief, Vol. 48 (2023), p. 109079.

OPEN ACCESS! American customer satisfaction index (ACSI) model data: Morgeson, F.V./ Hult, G.T.M./ Sharma, U./ Fornell, C.: The American Customer Satisfaction Index (ACSI): A Sample Dataset and Description, Data in Brief, Volume 48 (2023), p. 109123.

OPEN ACCESS! Extended TAM data: Richter, N.F./ Hauff, S./ Kolev, A.E./ Schubring, S.: Dataset On An Extended Technology Acceptance Model: A Combined Application of PLS-SEM and NCA, Data in Brief, Volume 48 (2023), p. 109190.

PLS-SEM and prediction solutions: Legate, A.E./ Hair, J.F./ Chretien, J.L./ Risher, J.J.: PLS-SEM: Prediction-oriented solutions for HRD researchers, Human Resource Development Quarterly, Volume 34 (2023), Issue 1, pp. 91-109.

PLS-SEM in hospitality and tourism research: Liu, Y./ Ting, H./ Ringle, C.: Appreciation to and Behavior Intention Regarding Upscale Ethnic Restaurants, Journal of Hospitality & Tourism Research, Volume 47 (2023), Issue 1, pp. 235–256.

Review of PLS-SEM applications in marketing studies: Sarstedt, M./ Hair, J.F./ Pick, M./ Liengaard, B.D./ Radomir, L./ Ringle, C.M.: Progress in Partial Least Squares Structural Equation Modeling Use in Marketing Research in the Last Decade, Psychology & Marketing, Volume 39 (2022), Issue 5, pp. 1035-1064.

PLS-SEM and NCA: Duarte, P./ Silva, S.C./ Linardi, M.A./ Novais, B.: Understanding the Implementation of Retail Self-service Check-out Technologies Using Necessary Condition Analysis, International Journal of Retail & Distribution Management, Volume 50 (2022), Issue 13, pp. 140-163.

PLS-SEM in international management research: Richter, N.F./ Hauff, S./ Ringle, C.M./ Gudergan, S.P.: The Use of Partial Least Squares Structural Equation Modeling and Complementary Methods in International Management Research, Management International Review, Volume 62 (2022), pp. 449-470.

PLS-SEM use in education research: Hair, J.F./ Alamer, A.: Partial Least Squares Structural Equation Modeling (PLS-SEM) in Second Language and Education Research: Guidelines Using an Applied Example, Research Methods in Applied Linguistics, Volume 1 (2022), Issue 3, 100027.

Nonlinear relationships: Basco, R./ Hair, J.F., Ringle, C.M./ Sarstedt, M.: Advancing Family Business Research Through Modeling Nonlinear Relationships: Comparing PLS-SEM and Multiple Regression, Journal of Family Business Strategy, Volume 13 (2022), Issue 3, 100457.

Top-journal PLS-SEM application: Rahman, S.M./ Carlson, J./ Gudergan, S./ Wetzels, M./ Grewal, D.: Perceived Omnichannel Customer Experience (OCX): Concept, measurement, and impact, Journal of Retailing, Volume 98 (2022), Issue 4, pp. 611-632. The web appendix shows how to report SmartPLS results

Search for the best model: Cho, G./ Hwang, H./ Sarstedt, M./ Ringle, C.M.: A Prediction-Oriented Specification Search Algorithm for Generalized Structured Component Analysis, Structural Equation Modeling: A Multidisciplinary Journal, Volume 29 (2022), Issue 2, pp. 229-240.

Model fit: Cho, G./ Schlägel, C./ Hwang, H./ Choi, Y./ Sarstedt, M./ Ringle, C.M.: Integrated Generalized Structured Component Analysis: On the Use of Model Fit Criteria in International Management Research, Management International Review, Volume 62 (2022), pp. 569–609.

On the importance of prediction: Sarstedt, M./ Danks, N.P.: Prediction in HRM Research: A Gap Between Rhetoric and Reality, Human Resource Management Journal, Volume 32 (2022), Issue 2, pp. 485-513.

PLS-SEM in Sports Management: Cepeda-Carrión, G./ Hair, J.F./ Ringle, C.M./ Roldán, J.L./ García-Fernández, J.: Guest Editorial: Sports Management Research Using Partial Least Squares Structural Equation Modeling (PLS-SEM), International Journal of Sports Marketing and Sponsorship, Volume 23 (2022), Issue 2, pp. 229-240.

OPEN ACCESS! Endogeneity and Gaussian copula: Becker, J.-M./ Proksch, D./ Ringle, C.M.:. Revisiting Gaussian Copulas to Handle Endogenous Regressors, Journal of the Academy of Marketing Science, Volume 50 (2022), pp. 46-66.

Uncovering unobserved heterogeneity: Sarstedt, M./ Radomir, L./ Moisescu, O.I./ Ringle, C.M.: Latent Class Analysis in PLS-SEM: A Review and Recommendations for Future Applications, Journal of Business Research, Volume 138 (2022), pp. 398-407.

The power of PLS-SEM: Petter, S./ Hadavi, Y.: With Great Power Comes Great Responsibility: The Use of Partial Least Squares in Information Systems Research, ACM SIGMIS Database: the DATABASE for Advances in Information Systems, Volume 52 (2021), pp. 10-23.

Mediation and prediction: Danks, N.: The Piggy in the Middle: The Role of Mediators in PLS-SEM-based Prediction, ACM SIGMIS Database: the DATABASE for Advances in Information Systems, Volume 52 (2021), pp. 24-42.

Conditional mediation analysis: Cheah, J.H./ Nitzl, C./ Roldán, J.L./ Cepeda Carrión, G./ Gudergan, S.P.: A Primer on the Conditional Mediation Analysis in PLS-SEM, ACM SIGMIS Database: the DATABASE for Advances in Information Systems, Volume 52 (2021), pp. 43-100.

Reflections on PLS-SEM: Hair, J.F.: Reflections on SEM: An Introspective, Idiosyncratic Journey to Composite-based Structural Equation Modeling, ACM SIGMIS Database: the DATABASE for Advances in Information Systems, Volume 52 (2021), pp. 101-113.

New PLS-SEM handbook article: Sarstedt, M./ Ringle, C.M./ Hair, J.F.: Partial Least Squares Structural Equation Modeling. In Homburg, C./ Klarmann, M./ Vomberg, A. (Eds.), Handbook of Market Research. Cham: Springer, 2021.

PLS-SEM comparison: Yuan, K.-H./ Deng, L.: Equivalence of Partial-Least-Squares SEM and the Methods of Factor-Score Regression, Structural Equation Modeling: A Multidisciplinary Journal, Volume 28 (2021), Issue 4, pp. 557-571.

Update on PLS-SEM: 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, Volume 12 (2021), Issue 3, 100392.

PLS-SEM and fsQCA: 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, Vol. 33 (2021), Issue 5, pp. 1571-1592.

PLS-SEM "how to" in entrepreneurship: Manley, S.C./ Hair, J.F./ Williams, R.I./ McDowell, W.C.: Essential New PLS-SEM Analysis Methods for Your Entrepreneurship Analytical Toolbox, International Entrepreneurship and Management Journal, Volume 17 (2021), pp. 1805-1825.

Weighted PLS-SEM (WPLS): Cheah, J.-H./ Roldán, J. L./ Ciavolino, E./ Ting, H./ Ramayah, T.: Sampling Weight Adjustments in Partial Least Squares Structural Equation Modeling: Guidelines and Illustrations, Total Quality Management & Business Excellence, Volume 32 (2021), Issue 13-14, pp. 1594-1613.

Predictive model selection test: Liengaard, B./ 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 53 (2021), Issue 2, pp. 362-392.

Predictive model selection: Sharma, P.N./ Shmueli, G./ Sarstedt, M./ Danks, N./ Ray, S.: Prediction-oriented Model Selection in Partial Least Squares Path Modeling, Decision Sciences, Voume 52 (2021), Issue 3, pp. 567-607.

PLS-SEM software review: Memon, M.A./ Ramayah, T./ Cheah, J.-H./ Ting, H./ Chuah, F./ Cham, T.H.: PLS-SEM Statistical Program: A Review, Journal of Applied Structural Equation Modeling, Volume 5 (2021), Issue 1, pp. i-xiii.

Higher-order models: Crocetta, C./ Antonucci, L./ Cataldo, R./ Galasso, R./ Grassia, M.G./ Lauro, C.N./ Marino, M.: Higher-order PLS-PM Approach for Different Types of Constructs, Social Indicators Research, Volume 154 (2021), Issue 2, pp. 725-754.

PLS-SEM and fsQCA: 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, Volume 33 (2021), Issue 5, pp. 1571-1592.

PLS-SEM in software engineering: Russo, D./ & Stol, K.-J.: PLS-SEM for Software Engineering Research: An introduction and Survey, ACM Computing Surveys, Volume 54 (2021), Issue 4, pp. 1-38.

Mediation analysis: Rasoolimanesh, S.M./ Wang, M./ Roldán, J.L./ Kunasekaran, P.: Are We in Right Path for Mediation Analysis? Reviewing the Literature and Proposing Robust Guidelines, Journal of Hospitality and Tourism Management, Volume 48 (2021), pp. 395-405.

PLS-SEM and binary data: Van der Schyff, K./ Flowerday, S./ Lowry, P.: [Information Privacy Behavior in the Use of Facebook Apps: A Personality-based Vulnerability Assessment] (https://www.sciencedirect.com/science/article/pii/S2405844020315577), Heliyon, Volume 6 (2020), Issue 8, pp. 1-13.

Mediation and no need for PROCESS: 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.

PLS-SEM and NCA: 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.

PLS-SEM in Higher Education: 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, Volume 80 (2020), pp. 1121–1152.

PLS-SEM and future time perspectives: 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, Volume 35 (2020), Issue 1, pp. 65-77.

PLS-SEM in Operations Management: Bayonne, E./ Marin-Garcia, J.A./ Alfalla-Luque, R.: Partial least squares (PLS) in Operations Management Research: Insights From a Systematic Literature Review, Journal of Industrial Engineering and Management, Volume 13 (2020), Issue 3.

Prediction metrics: Hair, J.F.: Next-generation Prediction Metrics for Composite-based PLS-SEM, Industrial Management & Data Systems, Volume 121 (2020), Issue 1, pp. 5-11.

SmartPLS multigroup analysis: Cheah, J./ Ramayah, T./ Memon, M.A./ Chuah, F./ Ting, H.: Multigroup Analysis using SmartPLS: Step-by-Step Guidelines for Business Research, Asian Journal of Business Research, Volume 10 (2020), Issue 3, pp. 1-19.

Causal-predictive PLS-SEM: Chin, W./ Cheah, J.-H./ Liu, Y./ Ting, H./ Lim, X.-J./ & Cham Tat, H.: Demystifying the Role of Causal-predictive Modeling Using Partial Least Squares Structural Equation Modeling in Information Systems Research, Industrial Management & Data Systems, Volume 120 (2020), Issue 12, pp. 2161-2209.

Necessary condition analysis (NCA) and PLS-SEM: 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.

PLS-SEM results assessment: 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.

Model fit: 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.

PLS-SEM and GSCA: 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.

IPMA application in hospitality management: 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.

More common factor issues: Rhemtulla, M./ van Bork, R./ Borsboom, D.: Worse Than Measurement Error: Consequences of Inappropriate Latent Variable Measurement Models, Psychological Methods, Volume 25 (2020), Issue 1, pp. 30-45.

Different views on CCA: Crittenden, V., Sarstedt, M., Astrachan, C., Hair, J., and Lourenco C. E.: Guest Editorial: Measurement and Scaling Methodologies, Journal of Product & Brand Management, Volume 29 (2020), Issue 4, pp. 409-414.

CCA: 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. Also take a look here: https://www.unibw.de/ciss-en/methodpaper-nitzl-et-al

PLS-SEM and GSCA: 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.

PLS-SEM in HRM: 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.

PLS-SEM and binary data: 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), Issue April, pp. 115-140.

Common factor issue: Rigdon, E.E., Becker, J.-M./ Sarstedt, M.: Factor Indeterminacy as Metrological Uncertainty: Implications for Advancing Psychological Measurement, Multivariate Behavioral Research, Volume 54 (2019), Issue 3, pp. 429-443.

PLS-SEM software review: Sarstedt, M./ Cheah, J.-H.: Partial Least Squares Structural Equation Modeling Using SmartPLS: A Software Review, Journal of Marketing Analytics, Volume 7 (2019), Issue 3, pp 196–202.

Higher-order models: 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.

How to use PLSpredict?! 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.

PLS-SEM results reporting: 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.

PLS-SEM research networks: 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.

Some rethinking of the PLS-SEM rethinking: Hair, J.F. / Sarstedt, M. / Ringle, C.M.: Rethinking Some of the Rethinking of Partial Least Squares, European Journal of Marketing, Volume 53, Issue 4, pp. 566-584.

More on predictive model selection: Sharma, P.N./ Shmueli, G./ Sarstedt, M./ Thiele, K.O.: PLS-based Model Selection: The Role of Alternative Explanations in MIS Research, Journal of the Association for Information Systems, Volume 20 (2019), Issue 4, pp. 346-397.

PLS-SEM in marketing: Ahrholdt, D.C./ Gudergan, S./ Ringle, C.M.: Enhancing Loyalty: When Improving Consumer Satisfaction and Delight Matters, Journal of Business Research, Volume 94 (2019), Issue 1, pp. 18-27.

PLS-SEM in environmental management: 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), pp. 203-212.

Formative and reflective measurment: Cheah, J.-H./ Ting, H., Ramayah, T./ Memon, M.A./ Cham, T.-H., Ciavolino, E.: A Comparison of Five Reflective–formative Estimation Approaches: Reconsideration and Recommendations for Tourism Research, Quality & Quantity, Volume 53 (2019), pp. 1421-1458.

Moderation analysis: Memon, M.A./ Cheah, J.-H./ Ramayah, T./ Ting, H./ Chuah, F./ Cham, T.H. Moderation Analysis: Issues and Guidelines, Journal of Applied Structural Equation Modeling, Volume 3 (2019), Issue 1, pp. i-ix.

Something for PLS-SEM haters: Petter, S.: "Haters Gonna Hate": PLS and Information Systems Research, ACM SIGMIS Database: the DATABASE for Advances in Information Systems, Volume 49 (2018), Issue 2, "Haters Gonna Hate": PLS and Information Systems Research, pp. 10-13.

OPEN ACCESS! Data from experiments and PLS-SEM: 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. 115–142.

Convergent valdity: 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.

Patient satisfaction: Rosenbusch, J./ Ismail, I.R./ Ringle, C.M.: The Agony of Choice for Medical Tourists: A Patient Satisfaction Index Model, Journal of Hospitality and Tourism Technology, Volume 9 (2018), Issue 3, pp. 267-279.

Endogeneity in PLS-SEM: 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.

Moderation: Becker, J.-M./ Ringle, C.M./ Sarstedt, M.: Estimating Moderating Effects in PLS-SEM and PLSc-SEM: Interaction Term Generation x Data Treatment, Journal of Applied Structural Equation Modeling, Volume 2 (2018), Issue 2, pp. 1-21.

PLS-SEM in hospitality research: 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.

PLS-SEM in finance: Avkiran, N.K./ Ringle, C.M. (2018): Partial Least Squares Structural Equation Modeling: Recent Advances in Banking and Finance. Berlin: Springer.

Mediation analysis: Memon, M.A./ Cheah, J.-H./ Ramayah, T./ Ting, H./ Chuah, F.: Mediation Analysis: Issues and Recommendations, Journal of Applied Structural Equation Modeling, Volume 2 (2018), Issue 1, pp. i-ix.

Mediation analysis: Cepeda Carrión, G./ Nitzl, C./ Roldán, J.L. (2017): Mediation Analyses in Partial Least Squares Structural Equation Modeling: Guidelines and Empirical Examples. In H. Latan & R. Noonan (Eds.), Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications. Cham: Springer, pp. 173-195.

Segmentation: Sarstedt, M./ Ringle, C.M./ Hair, J.F. (2017): Treating Unobserved Heterogeneity in PLS-SEM: A Multi-method Approach. In H. Latan & R. Noonan (Eds.), Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications. Cham: Springer, pp. 197-217.

OPEN ACCESS! CB-SEM and PLS-SEM: Rigdon/ E. E./ Sarstedt, M./ Ringle, C. M. (2017). On Comparing Results from CB-SEM and PLS-SEM. Five Perspectives and Five Recommendations. Marketing ZFP, 39(3), 4-16.

PLS-SEM performance: 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, 616-632.

Prediction: Shmueli, G./ Ray, S./ Velasquez Estrada, J.M./ Chatla, S.B. The Elephant in the Room: Evaluating the Predictive Performance of PLS Models, Journal of Business Research, Volume 69 (2016), Issue 10, pp. 4552–4564.

PLS-SEM: Richter, N.F./ Cepeda Carrión, G./ Roldán, J.L./ Ringle C.M.: European Management Research Using Partial Least Squares Structural Equation Modeling (PLS-SEM): Editorial, European Management Journal, Volume 34 (2016), Issue 6, pp. 589-97.

OPEN ACCESS! CB-SEM and PLS-SEM: 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 of Business Research, 69 (2016), Issue 10, pp. 3998-4010.

Mediation: Nitzl, C./ Roldán, J.L./ Cepeda Carrión, G.: Mediation Analysis in Partial Least Squares Path Modeling: Helping Researchers Discuss More Sophisticated Models, Industrial Management & Data Systems, Volume 119 (2016), Issue 9, pp. 1849-1864.

Importance-performance map (IPMA): Ringle, C.M./ Sarstedt, M.: Gain More Insight from Your PLS-SEM Results: The Importance-Performance Map Analysis, Industrial Management & Data Systems, Volume 119 (2016), Issue 9, 1865-1886.

Measurement invariance: Henseler, J./ Ringle, C.M./ Sarstedt, M.: Testing Measurement Invariance of Composites Using Partial Least Squares, International Marketing Review, Volume 33 (2016), Issue 3, pp. 405-431.

Weigthed PLS: Becker, J.-M./ Ismail, I. R. Accounting for Sampling Weights in PLS Path Modeling: Simulations and Empirical Examples, European Management Journal, Volume 34 (2016), Issue 6, pp. 606-617.

FIMIX-PLS segmentation: Hair, J.F./ Sarstedt, M./ Matthews, L./ Ringle, C.M.: Identifying and Treating Unobserved Heterogeneity with FIMIX-PLS: Part I - Method, European Business Review, Volume 28 (2016), Issue 1, pp. 63-76.

FIMIX-PLS tutorial: Matthews, L./ Sarstedt, M./ Hair, J.F./ Ringle, C.M.: Identifying and Treating Unobserved Heterogeneity with FIMIX-PLS: Part II – A Case Study, European Business Review, Volume 28 (2016), Issue 2, pp. 208-224.

Dynamic PLS: Schubring, S./ Lorscheid, I./ Meyer, M./ Ringle, C.M.: The PLS Agent: Predictive Modeling with PLS-SEM and Agent-based Simulation, Journal of Business Research, Volume 69 (2016), Issue 10, pp. 4604–4612.

Weighted regression segmentation: Schlittgen, R./ Ringle, C.M./ Sarstedt, M./ Becker, J.-M.: Segmentation of PLS Path Models by Iterative Reweighted Regressions, Journal of Business Research, Volume 69 (2016), Issue 10, pp. 4583–4592.

OPEN ACCESS! HTMT: Henseler, J./ Sarstedt, M./ Ringle, C.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.

Uncovering heterogeneity and prediction-oriented segmentation: Becker, J.-M./ Rai, A./ Ringle, C.M./ Völckner, F. Discovering Unobserved Heterogeneity in Structural Equation Models to Avert Validity Threats, MIS Quarterly, Volume 37 (2013), Issue 3, pp. 665-694.

The future of PLS-SEM! Sarstedt, M./ Ringle, C.M./ Henseler, J./ Hair, J.F. On the Emancipation of PLS-SEM: A Commentary on Rigdon (2012), Long Range Planning, 47 (2014), Issue 3, pp. 154-160.

Creating myths when chasing myths! Rigdon, E.E./ Becker, J.-M./ Rai, A./ Ringle, C.M./ Diamantopoulos, A./ Karahanna, E./ Straub, D.W./ 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.

The silver bullet! Hair, J.F./ Ringle, C.M./ Sarstedt, M. PLS-SEM: Indeed a Silver Bullet, Journal of Marketing Theory and Practice, 19 (2011), Issue 2, pp. 139-152.