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.
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.
**
2024
NCA, PLS-SEM, 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.
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, Volume 36 (2024), Issue 5, pp. 1242-1251.
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.
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, Volume 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 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.
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, Volume 33 (2024), Issue 1, pp. 80-96.
2023
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.: 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.
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.
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, Volume 76 (2023), Issue 3, pp. 646-678.
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.
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.
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.
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.
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.
2022
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.
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.
2021
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.
2020
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.
2019
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 (2019), 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.
2018
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.
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.: 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.
2017
Mediation analysis: Cepeda Carrión, G./ Nitzl, C./ Roldán, J.L.: 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 (pp. 173-195). Cham: Springer, 2017.
Segmentation: Sarstedt, M./ Ringle, C.M./ Hair, J.F.: 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 (pp. 197-217), Cham: Springer, 2017.
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, pp. 616-632.
2016
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.
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.
2015
2014
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.
2013
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.
2011
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.