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مقالات بسیار مهم reference نرم افزار SMART PLS

مقالات بسیار مهم reference نرم افزار SMART PLS

تاکنون در کلاس های مدل سازی معادلات ساختاری کواریانس محور و واریانس محور آکادمی تحلیل آماری ایران(مدرسه پژوهش کمی و کیفی ایران) از بیش از 70 کتاب و مقاله به عناون منابع بروز دنیا استفاده شده است. مطالبی که پیرامون متغیر های SINGLE ITEM می شود یا مطالبی که از مفاهیم مرتبه بالاتر، تقسیم بندی مشتریان یا تحلیل ناهمگنی، تحلیل میانجی و تعدیلگر و …. در کلاس ها عناون می شود همگی از دل کتاب ها و مقالات روز دنیا استخراج می شود. در این مطلب و مقاله مهم مقالات بسیار مهم این حوزه را با اطلاعات کتاب شناسی و نیز سایتی که می توانید به آن دسترسی پیدا کنید را بعد از برگزاری 311 دوره اسمارت پس ال اس برای عزیزان قرار دادیم. فراموش نکنید در کلاس ها دیدید که که کار با نرم افزار و ران کردن مدل ها حتی یک درصد هم ارزش علمی نداشت و 99 درصد ارزش این دوره ها به مطالبی که است که متاسفانه در بسته های آموزشی یا ویدئو ها و کلاس های دیگر مشاهده نمی شود و افتخار می کنیم که این دوره ها از دل ارزشمند ترین مراجع علمی دنیا و با زبانی ساده و دسته بندی جدید علمی به عزیزان ارائه می شود و عزیزانی که از کلاس فارغ التحصیل می شوند حتی از تحلیل گران آماری خارج از کشور برتر هستند.اکنون این مقالات بسیار مهم reference نرم افزار SMART PLS برای شما قابل مشاهده و دریافت و استفاده است. عمده این مقالات مربوط به 3 سال اخیر است.

 

SmartPLS multigroup analysis: Chean, 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

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, forthcoming.

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, forthcoming.

Prediction Metrics: Hair, J.F.: Next-generation Prediction Metrics for Composite-based PLS-SEM, Industrial Management & Data Systems, forthcoming.

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, forthcoming.

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, forthcoming.

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, forthcoming.

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 (2020), forthcoming.

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.

Fit criteria: 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.

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, 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 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.

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, Issue 2, “Haters Gonna Hate”: PLS and Information Systems Research, May 2018.

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 (2018).

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.

Handbook article on PLS-SEM: Sarstedt, M./ Ringle, C.M./ Hair, J.F. (2017): Partial Least Squares Structural Equation Modeling. In Homburg, C., Klarmann, M., and Vomberg, A. (Eds.), Handbook of Market Research. Heidelberg: Springer, 1-40.

Mediation: 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.

 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.

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.

 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.

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