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2023 | Buch

Introduction to the Partial Least Squares Path Modeling: Basic Concepts and Recent Methodological Enhancements Kapitel lesen Erstes Kapitel lesen

Partial Least Squares Path Modeling

Basic Concepts, Methodological Issues and Applications

herausgegeben von: Hengky Latan, Joseph F. Hair, Jr., Richard Noonan

Verlag: Springer International Publishing

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

Now in its second edition, this edited book presents recent progress and techniques in partial least squares path modeling (PLS-PM), and provides a comprehensive overview of the current state-of-the-art in PLS-PM research. Like the previous edition, the book is divided into three parts: the first part emphasizes the basic concepts and extensions of the PLS-PM method; the second part discusses the methodological issues that have been the focus of recent developments, and the last part deals with real-world applications of the PLS-PM method in various disciplines.

This new edition broadens the scope of the first edition and consists of entirely new original contributions, again written by expert authors in the field, on a wide range of topics, including: how to perform quantile composite path modeling with R; the rationale and justification for using PLS-PM in top-tier journals; psychometric properties of three weighting schemes and why PLS-PM is a better fit to mode B; a comprehensive review of PLS software; how to perform out-of-sample predictions with ordinal consistent partial least squares; multicollinearity issues in PLS-PM using ridge regression; theorizing and testing specific indirect effects in PLS and considering their effect size; how to run hierarchical models and available approaches; and how to apply necessary condition analysis (NCA) in PLS-PM.

This book will appeal to researchers interested in the latest advances in PLS-PM as well as masters and Ph.D. students in a variety of disciplines who use PLS-PM methods. With clear guidelines on selecting and using PLS-PM, especially those related to composite models, readers will be brought up to date on recent debates in the field.

Inhaltsverzeichnis

Frontmatter

Basic Concepts and Extensions

Frontmatter
Chapter 1. Introduction to the Partial Least Squares Path Modeling: Basic Concepts and Recent Methodological Enhancements
Abstract
This chapter aims to provide a brief overview of the three primary structural equation modeling approaches, which include partial least squares-path modeling (PLS-PM), covariance-based structural equation modeling (CB-SEM), and generalized structure component analysis (GSCA). We also provide guidelines regarding the appropriate situation to apply each of the three SEM methods. In addition, we describe recent methodological developments in SEM, particularly the method of PLS-PM, as well as applications of selected essential features of PLS-PM. We identify these topics as essential emerging tools for PLS-PM scholars since increasingly their understanding and application will be required in research utilizing PLS-PM. In the end, we summarize our observations and conclusions regarding the evolving state of PLS-PM.
Hengky Latan, Joseph F. Hair Jr., Richard Noonan, Misty Sabol
Chapter 2. Quantile Composite-Based Path Modeling with R: A Hands-on Guide
Abstract
The aim of the chapter is to provide step-by-step instructions to implement, estimate, and interpret a Quantile Composite-based Path Model, exploiting the qcpm package (https://​rdrr.​io/​cran/​qcpm/​), freely available for the R software. The chapter encompasses both methodological aspects of this recent quantile approach to Partial Least Squares Path Modeling, and real data applications, so as to offer a comprehensive guide to the readers interested in the use of the method on their own data. All steps of a quantitative analysis, i.e., data loading, pre-processing, coefficient estimation and model validation are described showing the options and functionalities of the package along with the corresponding methodology.
Cristina Davino, Pasquale Dolce, Giuseppe Lamberti, Domenico Vistocco
Chapter 3. Use of Partial Least Squares Path Modeling Within and Across Business Disciplines
Abstract
The acceptance and application of PLS-PM vary dramatically across business disciplines. Some business disciplines, such as marketing and information systems, have used PLS-PM for decades. Other disciplines, such as accounting, have been slower at incorporating path models and PLS-PM in their research studies. The differences in adoption of PLS-PM across business disciplines can be confusing for authors interested in applying, using, and reporting the PLS-PM results in published research within their own discipline or across business disciplines. To address this concern, this chapter reviews the use and application of PLS-PM in Financial Times (FT50) journals. Our results identify the prevalence of PLS-PM use within and across business disciplines. This chapter reviews the rationales provided by authors for their use of PLS-PM within and across business disciplines, discusses questionable and appropriate rationales for PLS-PM, and offers guidance for authors intending to publish articles using PLS-PM.
Stacie Petter, Yasamin Hadavi
Chapter 4. Statistical and Psychometric Properties of Three Weighting Schemes of the PLS-SEM Methodology
Abstract
Structural equation modeling (SEM) is a widely used technique for studies involving latent constructs. While covariance-based SEM (CB-SEM) permits estimating the regression relationship among latent constructs, the parameters governing this relationship do not apply to that among the scored values of the constructs, which are needed for prediction, classification and/or diagnosis of individuals/participants. In contrast, the partial-least-squares approach to SEM (PLS-SEM) first obtains weighted composites for each case and then estimates the structural relationship among the composites. Consequently, PLS-SEM is a preferred method in predicting and/or classifying individuals. Nevertheless, properties of PLS-SEM still depend on how the composites are formulated. Herman Wold proposed to use mode A to compute the scores for constructs with reflective indicators. However, Yuan and Deng recently showed that composites under mode B enjoy better psychometric properties. The authors thus proposed a structured transformation from mode A to mode B, denoted as mode \(\mathrm{B_A}\). This chapter further studies properties of the three modes of PLS-SEM. Analytical and numerical results show that (1) Mode A does not possess any solid statistical or psychometric properties, (2) Mode B possesses good theoretical properties but is over sensitive to sampling errors, and (3) Mode \(\mathrm{B_A}\) possesses good theoretical properties as well as numerical stability. The performances of the three modes are also illustrated with two real data examples.
Ke-Hai Yuan, Zhiyong Zhang
Chapter 5. Software Packages for Partial Least Squares Structural Equation Modeling: An Updated Review
Abstract
As a result of its ability to deal with situations that are difficult to address using other SEM methods, the partial least squares (PLS) approach to structural equation modeling (SEM) has attracted a lot of attention in recent years from applied researchers and practitioners in various fields. One reason for this growth in interest is represented by the many theoretical contributions emerging from the PLS-SEM research community, which have allowed us to deepen our knowledge of the method and extend its capabilities into new contexts. However, these contributions would have remained confined to academic journals if not for a parallel and similar development in the software packages available to implement these methodological innovations. Indeed, it is a well-known fact in the history of PLS-SEM that the lack of advanced and user-friendly software has been the main reason for the delay in the diffusion of this method in the applied sciences. Fortunately, we find ourselves nowadays in the opposite situation, as many high-quality packages for performing all varieties of PLS-SEM analyses have become available. In this chapter we present an updated review of the most popular commercial and open-source software packages for PLS-SEM. In particular, we discuss and compare ADANCO, SmartPLS, WarpPLS, XLSTAT-PLSPM, the plssem package for Stata, and the cSEM and SEMinR packages for R. Using a publicly available data set, we briefly illustrate the main features of each of these software packages and examine their corresponding strengths and weaknesses.
Sergio Venturini, Mehmet Mehmetoglu, Hengky Latan

Methodological Issues

Frontmatter
Chapter 6. Revisiting and Extending PLS for Ordinal Measurement and Prediction
Abstract
Traditionally, partial least squares (PLS) and consistent partial least squares (PLSc) assume the indicators to be continuous. To relax this restrictive assumption, ordinal partial least squares (OrdPLS) and ordinal consistent partial least squares have been developed. They are extensions of PLS and PLSc, respectively, that are able to take into account the nature of ordinal variables—both belonging to exogenous and endogenous constructs. In the PLS context, assessing the out-of-sample predictive power of models has increasingly gained interest. In contrast to PLS and PLSc, performing out-of-sample predictions is not a straightforward process for OrdPLS and OrdPLSc because the two assume that ordinal indicators are the outcome of categorized unobserved continuous variables, i.e., they rely on polychoric and polyserial correlations. In this chapter, we present OrdPLSpredict and OrdPLScpredict to perform out-of-sample predictions with models estimated by OrdPLS and OrdPLSc. A Monte Carlo simulation demonstrates the performance of our proposed approach. Finally, we provide concise guidelines using the open source R package cSEM to enable researchers to apply OrdPLSpredict and OrdPLScpredict using an empirical example.
Tamara Schamberger, Gabriele Cantaluppi, Florian Schuberth
Chapter 7. Multicollinearity: An Overview and Introduction of Ridge PLS-SEM Estimation
Abstract
Multicollinearity, or the existence of excessive correlations among (combinations of) predictor variables, is a commonly encountered phenomenon that affects (PLS-SEM) parameter estimates. This chapter provides an extensive overview of multicollinearity, its consequences, detection, and possible solutions. Critical to this overview is the explicit distinction among three types of multicollinearity: canonical structural multicollinearity, numerical multicollinearity, and common-factor multicollinearity. In addition, ridge PLS-SEM—an approach that combines the principles of ridge regression and PLS-SEM modeling—is introduced as an effective approach to mitigate the effects of canonical structural multicollinearity on estimation results.
Sandra Streukens, Sara Leroi-Werelds
Chapter 8. Demystifying Prediction in Mediation Research and the Use of Specific Indirect Effects and Indirect Effect Sizes
Abstract
The maturing state of partial least squares structural equation modeling (PLS-SEM) research has seen exceptional knowledge advances over the past decade. However, advances in practice among lay researchers have advanced at a slower pace. We conclude that this gap between PLS-SEM research and practice may be attributed to the sophisticated and arcane approach to detailing new methodological advances. Moreover, prediction has been a peripheral topic in PLS-SEM mediation literature to date. This chapter sits at the intersection of these two gaps. We first seek to advance understanding of the intertwining roles of prediction and mediation. We then provide practical demonstrations of two particularly occluded topics in mediation research: specific indirect effects and indirect effect sizes.
James Gaskin, Samuel Ogbeibu, Paul Benjamin Lowry
Chapter 9. Alternative Approaches to Higher Order PLS Path Modeling: A Discussion on Methodological Issues and Applications
Abstract
In the context of Partial Least Squares-Path Modeling (PLS-PM), higher-order constructs have enjoyed increasing popularity in the last few years in relation to the investigation of models with a high level of abstraction, particularly in cases where the building of a system of indicators depends on different levels of information. Higher-order constructs in PLS-PM are considered as explicit representations of multidimensional constructs which are related to other constructs at a higher level of abstraction, thereby mediating completely the influence received from, or exercised on, their underlying dimensions. This chapter investigates the status and evolution of research studies on higher-order constructs in PLS-PM and focuses attention on the potentiality of their recent methodological developments, specifically on how they can help researchers in the estimation of complex and multidimensional phenomena. Different approaches will be discussed and compared using a case study within a social context.
Rosanna Cataldo, Maria Gabriella Grassia, Carlo Natale Lauro
Chapter 10. How to Apply Necessary Condition Analysis in PLS-SEM
Abstract
This chapter illustrates the application of necessary condition analysis (NCA) in the context of partial least squares structural equation modeling (PLS-SEM). We demonstrate the joint use of the two methods using the standard software application SmartPLS 4, which incorporates PLS-SEM and the core NCA computation capabilities, and we offer background information on the key steps and interpretations associated with the combined application. We introduce the fundamentals of necessity logic and NCA, outlining key differences to PLS-SEM and its underlying logic. Using a recently published guideline and an illustrative example of the combined application of the two methods, the chapter provides guidance on generating results and interpreting must-have and should-have factors in the PLS-SEM context, enabling researchers to identify necessary conditions that may underlie their significant but also nonsignificant structural model relationships. The consideration of both must-have and should-have factors through the joint use of PLS-SEM and NCA is a unique way of assessing causality that may advance research in multiple fields. Our approach contributes to the further diffusion of the two logics in research applications. Our guidelines and systematic application of the two methods will assist researchers in exploiting these analyses’ valuable potentials in their own studies.
Nicole Franziska Richter, Sven Hauff, Christian M. Ringle, Marko Sarstedt, Aleksandar E. Kolev, Sandra Schubring

Applications

Frontmatter
Chapter 11. New Insights for Public Diplomacy Using PLS-SEM to Analyze the Polyphony of Voices: Value Drivers of the Country Image in Western European and BRICS Countries
Abstract
For the successful public diplomacy of a nation-state, it is essential to thoroughly analyze the country image in strategically relevant countries and develop coherent communication strategies that take into consideration the polyphony of voices raised by different countries when fostering a good country image abroad. In our study, we apply the five-dimensional country image measurement scale to data collected in cooperation with the Federal Department of Foreign Affairs in Switzerland (Presence Switzerland). Specifically, we analyze the similarities and differences among the (drivers of) country image in neighboring and close countries (France, Germany, Italy, and the United Kingdom) and those with a significant geographical distance from Switzerland (Brazil, Russia, China, and South Africa). We also conduct a cluster analysis, resulting in a Western European cluster and a BR(I)CS cluster. Based on the news values theory and stereotypes, we empirically test and confirm our hypothesis that countries differ in their image of other countries regarding geographical, cultural, and political proximity to the target country. Finally, we discuss potential benefits for public diplomacy when applying PLS-SEM and developing coherent communication strategies.
Diana Ingenhoff, Dominique Richner, Marko Sarstedt
Chapter 12. To Survive or not to Survive: Findings from PLS-SEM on the Relationship Between Organizational Resources and Startups’ Survival
Abstract
This study explores the phenomenon of startup survival in an incipient entrepreneurship ecosystem. For this purpose, multiple and simultaneous relationships between organizational resources, incubation, and startup survival are validated empirically. The analysis used PLS-SEM on a sample of 119 startups operating in different markets in Peru. The results show that survival is explained directly by a combination of entrepreneurial and organizational capital but indirectly by a chain of causal links. In this way, social capital determines human capital, and human capital also determines entrepreneurial capital. Thus, this study contributes to the literature in management and entrepreneurship with one alternative way to measure a phenomenon of greater complexity to demonstrate the survival of Peruvian startups.
Jubalt Alvarez-Salazar, Jean Pierre Seclen-Luna
Chapter 13. Influence of Earnings Quality Dimensions on the Perception of Earnings Quality: An Empirical Application of Composite PLS Using Archival Data
Abstract
Despite the fact that empirical research on earnings quality (EQ) has used a wide range of earnings properties that are expected to be related to EQ, research on how these properties affect investors’ perception of earnings quality is scarce, as most of the papers on EQ focus on a single EQ dimension. Moreover, extant research presents some limitations, as most studies rely on first-generation statistical methods (mainly OLS), without empirically testing the validity of the indicators used for capturing the underlying EQ dimension. This paper aims to explore how the different EQ properties described by previous literature map onto stockholders’ perceptions of EQ. Using partial least squares path modeling (PLS-PM), our results show that some of the properties more widely studied by accounting research (such as accruals quality) have little influence on stockholders’ perceptions of earnings quality, whereas other, less studied properties (such as persistence and smoothing) exhibit a stronger relationship with stockholders’ perceptions of EQ. Our results also show that the most usual indicators previously used in empirical research to represent accounting conservatism do not converge in a single construct, possibly indicating that those indicators may represent different underlying concepts.
Manuel Cano-Rodríguez, Ana Licerán-Gutiérrez
Chapter 14. Importance-Performance Map Analysis of Capital Structure Using PLS-SEM: Evidence from Non-financial Sector
Abstract
This study aims to identify the most important determinant that affects the capital structure decision of non-financial firms listed on the Pakistan Stock exchange (PSX) with balanced panel data of firm, industry, and macroeconomic-specific observations for the period of 14 years (2006–2019) and variance-based regression technique of partial least square structural equation modelling (PLS-SEM). Subsequently ‘Importance-Performance Map Analysis’ (IPMA) was performed to determine the most important determinant of capital structure decisions for Pakistan’s non-financial firms. The study illustrates the ceteris paribus interpretation that asset structure is the most important determinant of long-term debt selection in the capital structure decision for non-financial firms as such that leverage performance is increased by the amount of total effect of asset structure and cited tangibility as the most important indicator of asset structure in modelling the trend of capital structure which needs managerial attention to achieve optimal capital structure. The chapter provides prospects to financial managers and policy-makers for implementing better capital structure strategies to improve firm performance considering the importance of individual factors for the enrichment of investments and boost the economy.
Umme Habiba Rehman, Ambreen Rehman, Zeeshan Ahmed, Muhammad Maaz Sajid, Fasih Ur Rehman
Backmatter
Metadaten
Titel
Partial Least Squares Path Modeling
herausgegeben von
Hengky Latan
Joseph F. Hair, Jr.
Richard Noonan
Copyright-Jahr
2023
Electronic ISBN
978-3-031-37772-3
Print ISBN
978-3-031-37771-6
DOI
https://doi.org/10.1007/978-3-031-37772-3

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