Marko Sarstedt

Ludwig-Maximilians-University of Munich | LMU · Faculty of Business Administration - Munich School of Management

Partial least squares structural equation modeling (PLS-SEM) has become a popular method for estimating (complex) path models with latent variables and their relationships. Building on an introduction of the fundamentals of measure- ment and structural theory, this chapter explains how to specify and estimate path models using PLS-SEM. Complementin...

Discussions concerning different structural equation modeling methods draw on an increasing array of concepts and related terminology. As a consequence, misconceptions about the meaning of terms such as reflective measurement and common factor models as well as formative measurement and composite models have emerged. By distinguishing conceptual va...

Composite-based structural equation modeling (SEM), and especially partial least squares path modeling (PLS), has gained increasing dissemination in marketing. To fully exploit the potential of these methods, researchers must know about their relative performance and the settings that favor each method’s use. While numerous simulation studies have...

Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. For variance-based structural equa-tion modeling, such as partial least squares, the Fornell-Larcker criterion and the examination of cross-loadings are the dominant approaches for evaluating discriminant validity. By...

Structural equation modeling (SEM) has become a quasi-standard in marketing and management research when it comes to analyzing the cause-effect relations between latent constructs. For most researchers, SEM is equivalent to carrying out covariance-based SEM (CB-SEM). While marketing researchers have a basic understanding of CB-SEM, most of them are...

Purpose The purpose of this paper is to present integrated generalized structured component analysis (IGSCA) as a versatile approach for estimating models that contain both components and factors as statistical proxies for the constructs. The paper sets out to discuss the how-tos of using IGSCA by explaining how to specify, estimate, and evaluate d...

Corporate reputation is crucial for maintaining and enhancing a company's competitiveness in the marketplace. To actively manage this important intangible asset, which significantly contributes to a company's value, managers need to understand the relationship between reputation and its antecedents and consequences. The dataset presented in this ar...

Multiple scales measuring a customer’s, or consumer’s, engagement (CE) with a brand or specific brand elements (e.g., advertising/social media content) have been proposed in the literature, offering researchers different options to gauge CE. However, the myriad proposed operationalizations can yield confusion among scholars regarding how to best ca...

Picking one “winner” model for researching a certain phenomenon while discarding the rest implies a confidence that may misrepresent the evidence. Multimodel inference allows researchers to more accurately represent their uncertainty about which model is “best.” But multimodel inference, with Akaike weights—weights reflecting the relative probabili...

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 backgr...

Cette troisième édition de Modèles d’équations structurelles Partial Least Squares (PLS-SEM) (1re édition française) guide les lecteurs dans l'apprentissage et la maîtrise des techniques de cette approche. Les auteurs s'appuient sur leurs années de recherche et d'enseignement pour communiquer les principes fondamentaux de la méthode PLS-SEM dans un...

Structural equation modeling (SEM) has remained two mutually exclusive domains, factor-based vs. component-based, depending on whether a construct is modeled by either a factor or a compo-nent (i.e., weighted composite of indicators). Research in international management (IM) and inter-national business (IB), however, needs to accommodate a more ge...

Purpose Partial least squares structural equation modeling (PLS-SEM) has attracted much attention from both methodological and applied researchers in various disciplines – also in hospitality management research. As PLS-SEM is relatively new compared to other multivariate analysis techniques, there are still numerous open questions and uncertaintie...

In 2021, the third edition of our introductory book A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) was published (Hair, Hult, Ringle, & Sarstedt, 2022). The book covers the latest developments in the ield, including recent advances in model evaluation (e.g., inference testing in discriminant validity assessment, predictive...

Researchers often stress the predictive goals of their partial least squares structural equation modeling (PLS-SEM) analyses. However, the method has long lacked a statistical test to compare different models in terms of their predictive accuracy and to establish whether a proposed model offers a significantly better out-of-sample predictive accura...

Structural equation modeling (SEM) has emerged into two domains, factor-based and component-based, dependent on whether constructs are statistically represented as common factors or components. The two SEM domains are conceptually distinct, each assuming their own population models with either of the statistical construct proxies, and statistical S...

Partial least squares structural equation modeling (PLS-SEM) is an essential element of marketing researchers’ methodological toolbox. During the last decade, the PLS-SEM field has undergone massive developments, and raising the question of whether the method’s users are following the most recent best practice guidelines. This paper extends Hair et...

Continuous exposure to marketing communication has led to its commoditization. Addressing this concern, marketing practitioners increasingly rely on social media-based influencer marketing as a counterstrategy to effectively position products and brands in the market. Social media-based influencer marketing has also attracted considerable attention...

Generalized structured component analysis (GSCA) is used for specifying and testing the relationships between observed variables and components. GSCA can perform model selection by comparing theoretically established models. In practice, however, theories may not always completely and unambigu-ously specify the relationships between variables in th...

In 2011, the Journal of Marketing Theory & Practice published “PLS-SEM: Indeed a silver bullet,” which became a cornerstone contribution in marketing. Critical reflection of research work is a fundamental building block of science, including one’s own writing. In this spirit, we offer a review of our own 2011 paper, assuming we were reviewers with...

Generalized structured component analysis (GSCA) and partial least squares path modeling (PLSPM) are two key component-based approaches to structural equation modeling that facilitate the analysis of theoretically established models in terms of both explanation and prediction. This study is the first to offer a comparative evaluation of GSCA and PL...

Full analysis

Evermann and Rönkkö (2021) review recent developments in partial least squares (PLS) with the aim of providing guidance to researchers. Indeed, the explosion of methodological advances in PLS in the last decade necessitates such overview articles. In so far as the goal is to provide an objective assessment of the technique, such articles are most w...

With the increasing prominence of partial least squares structural equation modeling (PLS-SEM) in business research, the use of latent class analyses for identifying and treating unobserved heterogeneity has also gained momentum. Researchers have introduced various latent class approaches in a PLS-SEM context, of which finite mixture PLS (FIMIX-PLS...

Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method’s flexibility in terms of data requirements and meas...

Ambient scents often have fascinating effects on consumer behavior. The perceived scent temperature can, for example, affect purchase behavior (Biswas and Szocs 2019). Consumer researchers have recently started explaining these effects by exploring the causal chains triggering consumers’ responses to ambient scents.In this study, we extend prior re...

The sudden COVID-19-induced transition from a physical university life to a virtual one was a painful one for many students. Social distancing measures mean more than a simple change from face-to-face to online education. This study investigates how different social aspects, such as the students’ psychological sense of community, social capital, an...

Structural equation modeling (SEM) has become a quasi-standard tool for analyzing complex interrelationships between observed variables and theoretical constructs.

Formative Messmodelle basieren auf einem völlig anderen „Weltbild“ als reflektive Messmodelle, da sie unterstellen, dass ein Konstrukt aus seinen Indikatoren geformt wird, während reflektive Messmodelle davon ausgehen, dass die Messvariablen das betrachtete Konstrukt reflektieren und damit Folgen bzw. Konsequenzen der Wirksamkeit des Konstruktes in...

Im fünften Schritt des in Abschn. 4.1 dargestellten allgemeinen Ablaufprozesses der Strukturgleichungsmodellierung (Kausalanalyse) erfolgt die Schätzung der Modellparameter sowie in folgenden Schritten die Evaluation und Interpretation der gewonnenen Schätzergebnisse. Die Kap. 8, 9, 10, und 11 fokussieren dabei den sog. kovarianzanalytischen Ansatz...

Nach einem Überblick zu den Methoden der Strukturgleichungsanalyse werden in Abschn. 3.2 die Grundlagen der Pfadanalyse sowie der Kausalanalyse dargestellt und anhand von einfachen Beispielen erläutert. In Abschn. 3.3 werden sodann die Charakteristika und Ablaufschritte von Strukturgleichungsmodellen mit latenten Variablen allgemein dargestellt und...

Die Anfänge der Strukturgleichungsmodellierung mit latenten Variablen wurden vor allem durch den kovarianzanalytische Ansatz (LISREL; AMOS) dominiert. Mittlerweile hat aber auch PLS als ein komponentenbasierter Schätzansatz für Strukturgleichungsmodelle eine nicht minder hohe Bedeutung erlangt. Neben dem PLS-Ansatz hat die Methodenforschung mittler...

Die in Kap. 14 behandelte Multi-Group-Analysis (MGA) ermöglicht die simultane Schätzung eines Kausalmodells über mehrere (Befragungs-)Gruppen hinweg. Entspricht das betrachtete Kausalmodell einem konfirmatorischen Faktorenmodell, so wird von Mehrgruppen-Faktorenanalyse (MGFA) gesprochen, während die Betrachtung eines vollständigen Kausalmodells als...

Bei der praktischen Durchführung von Kausalanalysen treten häufig Problemfelder auf, die im Wesentlichen auf den Prozess der Datengenerierung zurückzuführen sind und im Ergebnis vor allem zu verzerrten Schätzergebnissen führen. In diesem Kapitel werden deshalb Ansätze aufgezeigt, mit deren Hilfe diese Problemfelder zum einen analysiert und zum ande...

Bei den meisten hypothetischen Konstrukten wird unterstellt, dass diese anhand von beobachtbaren Indikatoren über reflektive Messmodelle (Kap. 6) oder formative Messmodelle (Kap. 12) erfasst werden können. Solche Konstrukte werden auch als Konstrukte erster Ordnung bezeichnet. Demgegenüber existieren aber auch vielfältige Beispiele für Konstrukte z...

Bei praktischen Anwendungen stellt sich häufig die Frage, welche Maßnahmen ergriffen werden können, um eine Modellverbesserung etwa durch bisher nicht berücksichtigte Wirkbeziehungen vorzunehmen. Unter Rückgriff auf die vorliegenden Daten werden in Kap. 11 Hinweise zur Modifikation der Modellstruktur und der im Fallbeispiel aufgestellten Hypothesen...

In Kapitel 7 wird die Güteprüfung bei reflektiven Messmodellen allgemein sowie anhand des Fallbeispiels erläutert. Die Güteprüfung reflektiver Messmodelle wird dabei auf die Reliabilitäts- und die Validitätsprüfung fokussiert. Im Rahmen der Reliabilitätsprüfung werden sowohl Gütekriterien der ersten Generation (Cronbachs Alpha, Inter-Item-Korrelati...

Nach der Konzeptualisierung sind die hypothetischen Konstrukte einer empirischen Messung zugänglich zu machen. Zu diesem Zweck müssen Messmodelle für die latenten Variablen entwickelt werden, durch die die betrachteten endogenen und exogenen latenten Variablen messbar gemacht werden können. Die Betrachtungen in Kap. 6 (Operationalisierung) konzentr...

In Kap. 15 werden zur Verdeutlichung welchen Sachverhalts? Sachverhaltes – aufbauend auf dem allgemeinen Vergleich zwischen dem kovarianzanalytischen Ansatz (LISREL) und dem varianzanalytischen Ansatz (PLS) in Abschn. 3.3.4 – die zentralen Unterschiede des PLS-Ansatzes im allgemeinen Prozess der Strukturgleichungsmodellierung herausgearbeitet. Ansc...

Kap. 4 bildet den Einstieg in Teil II des Buches (Kausalanalyse) und erläutert nochmals kurz die acht Schritte des allgemeinen Ablaufprozesses der Strukturgleichungsmodellierung. Anschließend wird in Abschn. 4.2 das Fallbeispiel aufgezeigt, an Hand dessen die Ablaufschritte erläutert werden. In diesem Fallbeispiel geht ein Hotelbesitzer der Frage n...

Kap. 9 stellt Ansätze zur Evaluation des Gesamtmodells für die mit AMOS für das Fallbeispiel gewonnenen Ergebnisse vor. Dabei erfolgt zunächst die Evaluation des Gesamtmodells mittels inferenzstatistischer (z. B. Likelihood-Ratio-Test; Root-Mean-Square-Error of Approximation-RMSEA; Chi-Quadrat-Test) und deskriptiver Gütekriterien (z. B. Root-Mean-S...

In der Wissenschaft besitzen die Bildung und empirische Prüfung von Modellen einen zentralen Stellenwert zur Erklärung und Prognose der unterschiedlichsten Sachverhalte in der Wirklichkeit. Voraussetzung dabei ist, dass klare und in einer Theorie oder in der Sachlogik begründete Vorstellungen über die Zusammenhänge eines betrachteten Sachverhalts v...

In Kap. 1 wird zunächst der Prozess der Theorieprüfung anhand des Hempel-Oppenheim-Schemas in seiner Grundform erläutert. Die Abbildung von Ursache-Wirkungsbeziehungen im Sinne einer formalen Gleichungsstruktur erfolgt durch die Unterscheidung zwischen abhängigen (endogenen) und unabhängigen (exogenen) Variablen, wobei die unabhängigen Variablen al...

Die Strukturgleichungsmodellierung mit latenten, also nicht direkt beobachtbaren, Variablen (Konstrukten) erfordert im Ausgangspunkt die Existenz eines zu prüfenden Hypothesensystems, welches die unterstellten Wirkbeziehungen zwischen den Konstrukten abbildet. Während das sachlogisch abgeleitete Hypothesensystem des Fallbeispiels bereits in Kap. 4...

In Kap. 10 erfolgt die Interpretation der gewonnenen Parameterschätzungen vor dem Hintergrund der mit dem formulierten Kausalmodell definierten Hypothesen. Dabei ist neben der Bedeutsamkeit und statistischen Signifikanz einzelner Wirkbeziehungen insbesondere auch die Plausibilität der Ergebnisse zu berücksichtigen. Es wird für das Fallbeispiel aus...

Computational statistics is now an increasingly popular method of analysis for researchers that combines a vast array of algorithms, statistical methods, and the power of functional coding. The R programming language, in particular, has benefitted from this development alongside of traditional graphical user interface (GUI) software. Today, it has...

Mediation occurs when a third variable, referred to as a mediator construct, intervenes between two other directly related constructs. More precisely, a change in the exogenous construct results in a change of the mediator construct, which in turn changes the endogenous construct. The mediator analysis evaluates the factors related to the cause–eff...

Structural equation modeling is a multivariate data analysis method for analyzing complex relationships among constructs and indicators. To estimate structural equation models, researchers generally draw on two methods: covariance-based SEM (CB-SEM) and partial least squares SEM (PLS-SEM). Whereas CB-SEM is primarily used to confirm theories, PLS r...

When moderation is present, the strength and even the direction of a relationship between two constructs depend on a third construct (i.e., the moderator). In other words, the strength of the relationship between two constructs changes as the levels of the moderator construct change. As an example, the relationship between customer satisfaction and...

The goal of reflective measurement model assessment is to ensure the reliability and validity of the construct measures and therefore provides support for the suitability of their inclusion in the path model. This chapter introduces the key criteria that are relevant in reflective measurement model assessment: indicator reliability, internal consis...

Structural model assessment in PLS-SEM focuses on evaluating the significance and relevance of path coefficients, followed by the model’s explanatory and predictive power. In this chapter, we discuss the key metrics relevant to structural model assessment in PLS-SEM. We also discuss model comparisons and introduce key criteria for assessing and sel...

SEMinR is a software package developed for the R statistical environment (R Core Team, 2021). The package includes a user-friendly syntax for creating and estimating structural equation models using estimators such as partial least squares. In this chapter, we introduce the syntax to create, estimate, and report structural equation models using SEM...

PLS-SEM is the preferred approach when formatively specified constructs are included in the PLS path model. In this chapter, we discuss the key steps for evaluating formative measurement models. These include the assessment of (1) convergent validity, (2) indicator collinearity, and (3) statistical significance and relevance of the indicator weight...

Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method’s flexibility in terms of data requirements and meas...

While nonlinear relationships play an important role in explaining distinct family business behaviors and outcomes, researchers rarely consider them in their theoretical and statistical models. To address this concern, this article introduces partial least squares structural equation modeling (PLS-SEM) as a suitable means for estimating nonlinear e...

The use of partial least squares structural equation modeling (PLS-SEM) has been gaining momentum in family business research. Since the publication of a PLS-SEM guidelines article in the Journal of Family Business Strategy’s special issue on “Innovative and Established Research Methods in Family Business” in 2014, methodological research has devel...

Construal level theory (CLT) offers a valuable framework to explain the mechanisms that trigger evaluations, predictions, and behaviors by linking the degree of mental abstraction (the construal level) to psychological distance. CLT-related research has produced numerous publications in a variety of domains, impeding an ongoing overview of the rese...

*** This is an updated version of the 2017 chapter in the same edited volume *** Partial least squares structural equation modeling (PLS-SEM) has become a popular method for estimating path models with latent variables and their relationships. A common goal of PLS-SEM analyses is to identify key success factors and sources of competitive advantage...

Este libro ha sido concebido como una ampliación del Manual de Partial Least Squares Structural Equation Modeling (PLS-SEM) (segunda edición) (2019). El manual está diseñado como un guía práctica de fácil manejo para abordar los siguientes contenidos avanzados de PLS-SEM: • Modelos de componentes jerárquicos o de orden superior • Modelización, esti...

There are broadly two dimensions on which researchers can evaluate their statistical models: explanatory power and predictive power. Using data on job satisfaction in aging workforces, we empirically highlight the importance of clearly distinguishing between these two dimensions by showing that a model with a certain degree of explanatory power can...

Purpose – This research proposes guidelines for the joint use of partial least squares structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to combine symmetric and asymmetric perspectives in model evaluation, in the hospitality and tourism field. Design/methodology/approach – Our study discusses PLS-SEM as...

Evaluations of convergent and discriminant validity are generally conducted by analyzing constructs in isolation or by comparing pairs of latent variables. These approaches ignore the broader nomological network that is intrinsic to a measure’s construct validity, and fail to test the implications of either perfect correlations (convergence) or imp...

Marketing has started exploring ambient scents’ diverse effects and the psychological mechanisms through which they affect consumer behaviour. Recent research focuses on ambient scents’ perceived temperature’s impact on consumer behaviour. In this research, we first replicate prior research by showing that consumers exposed to a warm (vs. cool) amb...

Management researchers often develop theories and policies that are forward-looking. The prospective outlook of predictive modeling, where a model predicts unseen or new data, can complement the retrospective nature of causal-explanatory modeling that dominates the field. Partial least squares (PLS) path modeling is an excellent tool for building t...

Strukturgleichungsmodelle stellen das Standardinstrument zur empirischen Prüfung von hypothetisierten Beziehungen zwischen theoretischen Konstrukten (latenten Variablen) dar. Das Buch zeichnet den gesamten Prozess der Strukturgleichungsmodellierung von der Konzeptualisierung theoretischer Konstrukte über die Spezifikation von Messmodellen, die Reli...

Most project management research focuses almost exclusively on explanatory analyses. Evaluation of the explanatory power of statistical models is generally based on F-type statistics and the R2 metric, followed by an assessment of the model parameters (e.g., beta coefficients) in terms of their significance, size and direction. However, these measu...

Continuous exposure to marketing communication has led to its commoditization. Addressing this concern, marketing practitioners increasingly rely on social media-based influencer marketing as a counterstrategy to effectively position products and brands in the market. Social media-based influencer marketing has also attracted considerable attention...

Generalized structured component analysis (GSCA) is a technically well-established approach to component-based structural equation modeling that allows for specifying and examining the relationships between observed variables and components thereof. GSCA provides overall fit indexes for model evaluation, including the goodness-of-fit index (GFI) an...

Every year, food manufacturers spend billions of dollars on sensory acceptance tests in new food product development processes. These tests are either carried out in sensory labs or in natural consumption environments (field tests). Both types have merits, but also limitations. Research has started investigating whether tests in immersive consumpti...

Questo manuale, versione italiana del bestseller A Primer on Partial Least Squares Structural Equation Modeling, presenta con un linguaggio accessibile e con un approccio orientato alla pratica il metodo noto come Partial Least Squares Structural Equation Modeling (PLS-SEM), o modelli di equazioni strutturali basati sui minimi quadrati parziali. Qu...

The emergence of digital data and the methods used to analyze them are revolutionizing marketing research. The vast quantity of data offers marketing researchers countless opportunities to better predict and potentially explain consumer behavior. Yet, as we will argue in this paper, marketing researchers should not prematurely abandon cognitive and...

Purpose: This research introduces the combined use of partial least squares–structural equation modeling (PLS-SEM) and necessary condition analysis (NCA) that enables researchers to explore and validate hypotheses following a sufficiency logic, as well as hypotheses drawing on a necessity logic. The authors’ objective is to encourage the practice o...