IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/py57k.html
   My bibliography  Save this paper

A Study On Partial Least Squares Structural Equation Modeling (Pls-Sem) As Emerging Tool In Action Research

Author

Listed:
  • Hossan, Dalowar

Abstract

Structural equation modeling (SEM) depicts one of the most salient research methods across a variety of disciplines, including educational management. Recent research advocates the use of partial least squares structural equation modeling (PLS-SEM) as an attractive tool in action research. The purpose of this paper is to systematically examine how PLS-SEM has been applied in action research with the aim of investigating the effect of teacher’s leadership styles (transformational and transaction) and student’s motivational factors (intrinsic and extrinsic) on student engagement for implementation of Communicative Language Teaching (CLT) in classrooms as well as explore the mediating role of motivational factors of student between the relationship of teacher’s leadership styles and student engagement. A cross-sectional survey design was used for the study featuring a self-administrated questionnaire among the students of some selected schools in Bangladesh. The transactional leadership style of teachers influences student engagement, intrinsic, and extrinsic motivation while the transformational leadership style of teachers influences the intrinsic and extrinsic motivation of the student. Both motivational factors mediated the relationship between leadership styles and student engagement. This study contributes to the literature by providing teachers with the updated guidelines for action research by using PLS-SEM. The study also suggests the way for increasing student engagement for CLT implementation in classrooms.

Suggested Citation

  • Hossan, Dalowar, 2021. "A Study On Partial Least Squares Structural Equation Modeling (Pls-Sem) As Emerging Tool In Action Research," OSF Preprints py57k, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:py57k
    DOI: 10.31219/osf.io/py57k
    as

    Download full text from publisher

    File URL: https://osf.io/download/600eff3bc5784b001ed07164/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/py57k?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Claes Cassel & Peter Hackl & Anders Westlund, 1999. "Robustness of partial least-squares method for estimating latent variable quality structures," Journal of Applied Statistics, Taylor & Francis Journals, vol. 26(4), pages 435-446.
    2. Wold, Herman, 1974. "Causal flows with latent variables : Partings of the ways in the light of NIPALS modelling," European Economic Review, Elsevier, vol. 5(1), pages 67-86, June.
    3. Lee, Lorraine & Petter, Stacie & Fayard, Dutch & Robinson, Shani, 2011. "On the use of partial least squares path modeling in accounting research," International Journal of Accounting Information Systems, Elsevier, vol. 12(4), pages 305-328.
    4. Nitzl, Christian, 2016. "The use of partial least squares structural equation modelling (PLS-SEM) in management accounting research: Directions for future theory development," Journal of Accounting Literature, Elsevier, vol. 37(C), pages 19-35.
    5. Jörg Henseler & Marko Sarstedt, 2013. "Goodness-of-fit indices for partial least squares path modeling," Computational Statistics, Springer, vol. 28(2), pages 565-580, April.
    6. Jarvis, Cheryl Burke & MacKenzie, Scott B & Podsakoff, Philip M, 2003. "A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(2), pages 199-218, September.
    7. Herman Wold, 1980. "Model Construction and Evaluation When Theoretical Knowledge Is Scarce," NBER Chapters, in: Evaluation of Econometric Models, pages 47-74, National Bureau of Economic Research, Inc.
    8. Evermann, Joerg & Tate, Mary, 2016. "Assessing the predictive performance of structural equation model estimators," Journal of Business Research, Elsevier, vol. 69(10), pages 4565-4582.
    9. Marko Sarstedt & Jun-Hwa Cheah, 2019. "Partial least squares structural equation modeling using SmartPLS: a software review," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(3), pages 196-202, September.
    10. Jörg Henseler, 2010. "On the convergence of the partial least squares path modeling algorithm," Computational Statistics, Springer, vol. 25(1), pages 107-120, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Joseph F. Hair & G. Tomas M. Hult & Christian M. Ringle & Marko Sarstedt & Kai Oliver Thiele, 2017. "Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods," Journal of the Academy of Marketing Science, Springer, vol. 45(5), pages 616-632, September.
    2. Nitzl, Christian, 2016. "The use of partial least squares structural equation modelling (PLS-SEM) in management accounting research: Directions for future theory development," Journal of Accounting Literature, Elsevier, vol. 37(C), pages 19-35.
    3. Ringle, C.M. & Götz, O & Wetzels, M.G.M. & Wilson, B, 2009. "On the Use of Formative Measurement Specifications in Structural Equation Modelling: A Monte Carlo Simulation Study to Compare Covariance-Based and Partial Least Squares Model Estimation Methodologies," Research Memorandum 014, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    4. Christian Nitzl & Wynne W. Chin, 2017. "The case of partial least squares (PLS) path modeling in managerial accounting research," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 28(2), pages 137-156, May.
    5. Marko Sarstedt & Christian M Ringle & Jun-Hwa Cheah & Hiram Ting & Ovidiu I Moisescu & Lacramioara Radomir, 2020. "Structural model robustness checks in PLS-SEM," Tourism Economics, , vol. 26(4), pages 531-554, June.
    6. Ricardo E. Buitrago R. & María Inés Barbosa Camargo & Favio Cala Vitery, 2021. "Emerging Economies’ Institutional Quality and International Competitiveness: A PLS-SEM Approach," Mathematics, MDPI, vol. 9(9), pages 1-18, April.
    7. Sarstedt, Marko & Ringle, Christian M. & Smith, Donna & Reams, Russell & Hair, Joseph F., 2014. "Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers," Journal of Family Business Strategy, Elsevier, vol. 5(1), pages 105-115.
    8. Joseph F. Hair & Christian M. Ringle & Siegfried P. Gudergan & Andreas Fischer & Christian Nitzl & Con Menictas, 2019. "Partial least squares structural equation modeling-based discrete choice modeling: an illustration in modeling retailer choice," Business Research, Springer;German Academic Association for Business Research, vol. 12(1), pages 115-142, April.
    9. A. Blanco-Oliver & A. Irimia-Diéguez, 2021. "Impact of outreach on financial performance of microfinance institutions: a moderated mediation model of productivity, loan portfolio quality, and profit status," Review of Managerial Science, Springer, vol. 15(3), pages 633-668, April.
    10. Telma Mendes & Vítor Braga & Carina Silva & Alexandra Braga, 2025. "The speed of internationalization in regionally clustered family firms: a deeper understanding of innovation activities and cluster affiliation," Review of Regional Research: Jahrbuch für Regionalwissenschaft, Springer;Gesellschaft für Regionalforschung (GfR), vol. 45(1), pages 51-108, March.
    11. Jun-Hwa Cheah & Hiram Ting & T. Ramayah & Mumtaz Ali Memon & Tat-Huei Cham & Enrico Ciavolino, 2019. "A comparison of five reflective–formative estimation approaches: reconsideration and recommendations for tourism research," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(3), pages 1421-1458, May.
    12. Jörg Henseler, 2018. "Partial least squares path modeling: Quo vadis?," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(1), pages 1-8, January.
    13. Matheus Pereira Libório & Oseias da Silva Martinuci & Sandro Laudares & Renata de Mello Lyrio & Alexei Manso Correa Machado & Patrícia Bernardes & Petr Ekel, 2020. "Measuring Intra-Urban Inequality with Structural Equation Modeling: A Theory-Grounded Indicator," Sustainability, MDPI, vol. 12(20), pages 1-18, October.
    14. Christina Boedker & Kar Ming Chong, 2022. "The mediating role of accounting controls between supervisors' empowering leadership style and subordinates' creativity and goal productivity," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 62(4), pages 4587-4614, December.
    15. Minerva Martínez Avila & Juan José García-Machado & Eréndira Fierro Moreno, 2021. "A Multiple Full Mediating Effect in a PLS Hierarchical Component Model: Application to the Collaborative Public Management," Mathematics, MDPI, vol. 9(16), pages 1-19, August.
    16. Abdullah Al-Swidi & Redhwan Mohammed Saleh, 2021. "How green our future would be? An investigation of the determinants of green purchasing behavior of young citizens in a developing Country," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(9), pages 13436-13468, September.
    17. Eduardo Terán-Yépez & David Jiménez-Castillo & Manuel Sánchez-Pérez, 2023. "The role of affect in international opportunity recognition and the formation of international opportunity beliefs," Review of Managerial Science, Springer, vol. 17(3), pages 941-983, April.
    18. Mirchandani, Dinesh A. & Lederer, Albert L., 2014. "The impact of core and infrastructure business activities on information systems planning and effectiveness," International Journal of Information Management, Elsevier, vol. 34(5), pages 622-633.
    19. María de los Ángeles Pérez-Sánchez & Zhuowei Tian & Almudena Barrientos-Báez & José Gómez-Galán & Hanliang Li, 2021. "Blockchain Technology for Winning Consumer Loyalty: Social Norm Analysis Using Structural Equation Modeling," Mathematics, MDPI, vol. 9(5), pages 1-18, March.
    20. Rosanna Cataldo & Maria Gabriella Grassia & Natale Carlo Lauro & Marina Marino, 2017. "Developments in Higher-Order PLS-PM for the building of a system of Composite Indicators," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(2), pages 657-674, March.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:osfxxx:py57k. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.