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Partial Least Squares Structural Equation Modeling

Recent Advances in Banking and Finance

  • Book
  • © 2018

Overview

Editors:
  1. Necmi K. Avkiran

    1. School of Business, University of Queensland, St Lucia, Australia

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    You can also search for this editor in PubMed   Google Scholar

  2. Christian M. Ringle

    1. Institute of HRM, Hamburg University of Technology, Hamburg, Germany

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • First book to present research on PLS-SEM in Banking and Finance
  • Editors are prominent names in the field
  • Assumes no strong mathematical or statistical background in the reader

Part of the book series: International Series in Operations Research & Management Science (ISOR, volume 267)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-x
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  2. Rise of the Partial Least Squares Structural Equation Modeling: An Application in Banking

    • Necmi K. Avkiran
    Pages 1-29

  3. Bank Soundness: A PLS-SEM Approach

    • Charmele Ayadurai, Rasol Eskandari
    Pages 31-52

  4. The Customer Loyalty Cascade and Its Impact on Profitability in Financial Services

    • Anne-Kathrin Hegner-Kakar, Nicole F. Richter, Christian M. Ringle
    Pages 53-75

  5. Corporate Reputation: The Importance of Service Quality and Relationship Investment

    • Lăcrămioara Radomir, Alan Wilson
    Pages 77-123

  6. The Compliance Index Model: Mitigating Compliance Risks by Applying PLS-SEM to Measure the Perceived Effectiveness of Compliance Programs

    • Sebastian Rick, Ralf Jasny
    Pages 125-170

  7. Why Should PLS-SEM Be Used Rather Than Regression? Evidence from the Capital Structure Perspective

    • Nur Ainna Ramli, Hengky Latan, Gilbert V. Nartea
    Pages 171-209

  8. Management Accounting and Partial Least Squares-Structural Equation Modelling (PLS-SEM): Some Illustrative Examples

    • Christian Nitzl
    Pages 211-229

  9. Back Matter

    Pages 231-239
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Keywords

About this book

This book pulls together robust practices in Partial Least Squares Structural Equation Modeling (PLS-SEM) from other disciplines and shows how they can be used in the area of Banking and Finance. In terms of empirical analysis techniques, Banking and Finance is a conservative discipline. As such, this book will raise awareness of the potential of PLS-SEM for application in various contexts. PLS-SEM is a non-parametric approach designed to maximize explained variance in latent constructs. Latent constructs are directly unobservable phenomena such as customer service quality and managerial competence. Explained variance refers to the extent we can predict, say, customer service quality, by examining other theoretically related latent constructs such as conduct of staff and communication skills.

Examples of latent constructs at the microeconomic level include customer service quality, managerial effectiveness, perception of market leadership, etc.; macroeconomic-level latent constructs would be found in contagion of systemic risk from one financial sector to another, herd behavior among fund managers, risk tolerance in financial markets, etc. Behavioral Finance is bound to provide a wealth of opportunities for applying PLS-SEM. The book is designed to expose robust processes in application of PLS-SEM, including use of various software packages and codes, including R.

PLS-SEM is already a popular tool in marketing and management information systems used to explain latent constructs. Until now, PLS-SEM has not enjoyed a wide acceptance in Banking and Finance. Based on recent research developments, this book represents the first collection of PLS-SEM applications in Banking and Finance. This book will serve as a reference book for those researchers keen on adopting PLS-SEM to explain latent constructs in Banking and Finance.

Editors and Affiliations

  • School of Business, University of Queensland, St Lucia, Australia

    Necmi K. Avkiran

  • Institute of HRM, Hamburg University of Technology, Hamburg, Germany

    Christian M. Ringle

About the editors

Necmi Kemal Avkiran is currently an Associate Professor in banking and financial studies. The main focus of his research has been bank performance measurement. Necmi is currently studying the efficiency of bank networks and transmission of systemic risk. He specializes in the applications of the productivity measurement technique data envelopment analysis and structural equation modelling in the service sector. He holds an award for excellence from the MCB University Press for a research paper on bank customer service quality, and his publication on bank networks has been identified by Thomson Reuters Essential Science Indicators as a featured Fast-Breaking Paper in the field of Economics & Business, August 2010.

In May 2006 he published the third edition of the research book entitled Productivity Analysis in the Service Sector with Data Envelopment Analysis. The journals in which he has published include the Journal of Banking and Finance, OMEGA, Pacific-BasinFinance Journal, Accounting & Finance, Journal of Business Research, Annals of Operations Research, Scientometrics, Personnel Review, and International Journal of Human Resource Management, as well as on-campus publications.

He is a member of the Australian Society for Operations Research (ASOR), and FINSIA.

Christian M. Ringle is a Chaired Professor of Management at the Hamburg University of Technology (TUHH) and a Conjoint Professor at the Faculty of Business Law at the University of Newcastle. His research addresses the management of organizations, strategic and human resource management, marketing, and quantitative methods for business and market research. His research in these fields has been published in well-known journals such as Annals of Tourism Research, International Journal of Research in Marketing, Information Systems Research, Journal of Business Research, Journal of Service Research, Journal of the Academy of Marketing Science, Long Range Planning, MIS Quarterly, and Tourism Management. He is a cofounder of SmartPLS, a statistical software tool with a graphical user interface for partial least squares structural equation modeling (PLS-SEM).

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