Marko Sarstedt
Biographic Data
| ID | 1654071 |
|---|---|
| NAME | Marko Sarstedt |
| GIVEN NAMES | Marko |
| FAMILY NAME | Sarstedt |
| SIGNATURE | SARSTEDT M |
| AFFILIATIONS | Otto-von-Guericke-Universität Magdeburg |
| ORCID | 0000-0002-5424-4268 |
| VERIFIED | Yes |
| TOTAL WORKS | 59 |
| TOTAL CITATIONS | 94 |
| AUTHOR COUNT | 58 |
| EDITOR COUNT | 1 |
| FIRST PUBLICATION YEAR | 2011 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 4 |
Effects of Psychological Distance on Mental Abstraction: A Registered Report of Four Tests of Construal-Level Theory
Construal-level theory (CLT) proposes that psychological distance influences the level of abstraction at which something is mentally construed: Things perceived as less probable (likelihood) or further away from the here (spatial distance), now (temporal distance), or self (social distance) are thought about more abstractly. In this international multilab study, we tested four basic hypotheses derived from core assumptions of CLT and explore pote…
Consistent Partial Least Squares Structural Equation Modeling Using SmartPLS
This Teacher’s Corner article provides a comprehensive illustration of consistent partial least squares structural equation modeling (PLSc-SEM), a variant of the original PLS-SEM method, which corrects construct correlations for attenuation. The method thereby allows estimating common factor models within a composite-based SEM framework. Our descriptions draw on SmartPLS 4, the most frequently used software for conducting PLS-SEM analyses, illust…
Conceptual structure and thematic evolution in partial least squares structural equation modeling research
Structural equation modeling (SEM) using partial least squares (PLS) has received considerable attention in recent years. We address the increasing fragmentation of PLS-SEM-related research across multiple fields of scientific inquiry by presenting a bibliometric analysis’s results of n = 9,150 documents from the Web of Science database. We identify the main themes by using bibliometric content analysis to explore the PLS-SEM knowledge structure’…
Regularized Structural Equation Modeling with Both Factors and Components
The use of synthetic data in tourism
Large language models can support stimuli evaluation. • Synthetic data suits early research such as pretests; avoid it for main studies. • Prompt-tuning and fine-tuning improve large language model's responses
“Pls-Sem: Indeed a silver bullet” – retrospective observations and recent advances
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 today’s background knowledge of the method. Taking a reviewer’s perspective in our comments, we clar…
A perspective on using partial least squares structural equation modelling in data articles
This perspective article on using partial least squares structural equation modelling (PLS-SEM) is intended as a guide for authors who wish to publish datasets that can be analysed with this method as stand-alone data articles. Stand-alone data articles are different from supporting data articles in that they are not linked to a full research article published in another journal. Nevertheless, authors of stand-alone data articles will be required…
PLS-SEM’s most wanted guidance
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 uncertainties in its application. This study aims to address this important issue by offering guidance regarding…
Progress in partial least squares structural equation modeling use in marketing research in the last decade
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, raising the question of whether the method's users are following the most recent best practice guidelines. Extending prior research in the field, this paper presents the results of a new analysis of PLS‐SEM use in marketing research, foc…
A Prediction-Oriented Specification Search Algorithm for Generalized Structured Component Analysis
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 unambiguously specify the relationships between variables in the model. In such situations, a specification search strategy allows for exploring potential relations…
Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook
Prediction: Coveted, Yet Forsaken? Introducing a Cross‐Validated Predictive Ability Test in Partial Least Squares Path Modeling
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 theories that offer both explanation and prediction. A limitation of PLS, however, is the lack of a s…
Evaluation of Reflective Measurement Models
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 consistency reliability (Cronbach’s alpha, reliability coefficient rho A , and composite reliability rho C…
Executing and interpreting applications of PLS-SEM: Updates for family business researchers
An Introduction to Structural Equation Modeling
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 represents a causal–predictive approach to SEM that emphasizes prediction in estimating models, whose…
Digital Socialligators? Social Media-Induced Perceived Support During the Transition to the Covid-19 Lockdown
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, and use of social media, facilitated the perceived social support during the transition to the COVID-1…
Partial least squares structural equation modeling in HRM research
Partial least squares structural equation modeling (PLS-SEM) has become a key multivariate analysis technique that human resource management (HRM) researchers frequently use. While most disciplines undertake regular critical reflections on the use of important methods to ensure rigorous research and publication practices, the use of PLS-SEM in HRM has not been analyzed so far. To address this gap in HRM literature, this paper presents a critical …
Beyond a tandem analysis of SEM and PROCESS: Use of PLS-SEM for mediation analyses!
Mediation and conditional process analyses have become popular approaches for examining the mechanisms by which effects operate and the factors that influence them. To estimate mediation models, researchers often augment their structural equation modeling (SEM) analyses with additional regression analyses using the PROCESS macro. This duality is surprising considering that research has long acknowledged the limitations of regression analyses when…
Cutoff criteria for overall model fit indexes in generalized structured component analysis
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) and the standardized root mean square residual (SRMR). While these indexes have a solid standing in fa…
When predictors of outcomes are necessary: Guidelines for the combined use of PLS-SEM and NCA
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 of combining PLS-SEM and NCA as complementary views of causality and data analysis. Design/methodology…
Quantify uncertainty in behavioral research
How to Specify, Estimate, and Validate Higher-Order Constructs in PLS-SEM
Higher-order constructs, which facilitate modeling a construct on a more abstract higher-level dimension and its more concrete lower-order subdimensions, have become an increasingly visible trend in applications of partial least squares structural equation modeling (PLS-SEM). Unfortunately, researchers frequently confuse the specification, estimation, and validation of higher-order constructs, for example, when it comes to assessing their reliabi…
Factors versus Composites: Guidelines for Choosing the Right Structural Equation Modeling Method
Structural equation modeling (SEM) is a widely applied and useful tool for project management scholars. In this Thoughtlet article, we critically reflect on the measurement philosophy underlying the two streams of SEM and their adequacy for estimating relationships among concepts commonly encountered in the field (e.g., team performance). We also discuss considerations to ponder when making the choice between the two types of SEM as well as betwe…
When to use and how to report the results of PLS-SEM
Purpose The purpose of this paper is to provide a comprehensive, yet concise, overview of the considerations and metrics required for partial least squares structural equation modeling (PLS-SEM) analysis and result reporting. Preliminary considerations are summarized first, including reasons for choosing PLS-SEM, recommended sample size in selected contexts, distributional assumptions, use of secondary data, statistical power and the need for goo…
Structural model robustness checks in PLS-SEM
Partial least squares structural equation modeling (PLS-SEM) has become a standard tool for analyzing complex inter-relationships between observed and latent variables in tourism and numerous other fields of scientific inquiry. Along with the recent surge in the method’s use, research has contributed several complementary methods for assessing the robustness of PLS-SEM results. Although these improvements are documented in extant literature, rese…
Heuristics versus statistics in discriminant validity testing: A comparison of four procedures
Purpose The purpose of this paper is to review and extend recent simulation studies on discriminant validity measures, contrasting the use of cutoff values (i.e. heuristics) with inferential tests. Design/methodology/approach Based on a simulation study, which considers different construct correlations, sample sizes, numbers of indicators and loading patterns, the authors assess each criterion’s sensitivity to type I and type II errors. Findings …
Methodological research on partial least squares structural equation modeling (PLS-SEM): An analysis based on social network approaches
Purpose The purpose of this paper is to explore the knowledge infrastructure of methodological research on partial least squares structural equation modeling (PLS-SEM) from a network point of view. The analysis involves the structures of authors, institutions, countries and co-citation networks, and discloses trending developments in the field. Design/methodology/approach Based on bibliometric data downloaded from the Web of Science, the authors …
Internet research using partial least squares structural equation modeling (PLS-SEM)
The use of synthetic data in tourism
Large language models can support stimuli evaluation. • Synthetic data suits early research such as pretests; avoid it for main studies. • Prompt-tuning and fine-tuning improve large language model's responses
In Pursuit of Understanding What Drives Fan Satisfaction
With economic considerations exerting an ever-increasing influence on soccer club activities, fan satisfaction has become an essential focus for these organizations. Despite the obvious relevance of this topic, the literature has paid little attention to the measurement of fan satisfaction. Based on a thorough literature review and an empirical study of soccer fans, this paper outlines the development of a formative measurement index for fan sati…
Quantify uncertainty in behavioral research
Guidelines for treating unobserved heterogeneity in tourism research: A comment on Marques and Reis (2015)
Measurement and Research Methods in International Marketing
A"Publishing cross-national research is often a difficult endeavour as ensuring equivalence of method and measures can be challenging. Even though the importance of sound data and valid measures has long been an acknowledged, it is often problematic to follow required quality standards in concrete research situations. Against this background, this volume addresses issues pertaining to measurement and research methodology in an international marke…
Multigroup Analysis in Partial Least Squares (PLS) Path Modeling: Alternative Methods and Empirical Results
Purpose – Partial least squares (PLS) path modeling has become a pivotal empirical research method in international marketing. Owing to group comparisons' important role in research on international marketing, we provide researchers with recommendations on how to conduct multigroup analyses in PLS path modeling.Methodology/approach – We review available multigroup analysis methods in PLS path modeling and introduce a novel confidence set approach…
PLS-Sem: Indeed a Silver Bullet
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 only barely familiar with the other useful approach to SEM-partial least squares SEM (PLS-SEM). The…
Editor’s Comments
Partial Least Squares: The Better Approach to Structural Equation Modeling?
Guidelines for choosing between multi-item and single-item scales for construct measurement: A predictive validity perspective
Establishing predictive validity of measures is a major concern in marketing research. This paper investigates the conditions favoring the use of single items versus multi-item scales in terms of predictive validity. A series of complementary studies reveals that the predictive validity of single items varies considerably across different (concrete) constructs and stimuli objects. In an attempt to explain the observed instability, a comprehensive…
An assessment of the use of partial least squares structural equation modeling in marketing research
Goodness-of-fit indices for partial least squares path modeling
This paper discusses a recent development in partial least squares (PLS) path modeling, namely goodness-of-fit indices. In order to illustrate the behavior of the goodness-of-fit index (GoF) and the relative goodness-of-fit index (GoF rel ), we estimate PLS path models with simulated data, and contrast their values with fit indices commonly used in covariance-based structural equation modeling. The simulation shows that the GoF and the GoF rel ar…
On the Emancipation of PLS-SEM: A Commentary on Rigdon (2012)
Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers
Common Beliefs and Reality About PLS: Comments on Rönkkö and Evermann (2013)
This article addresses Rönkkö and Evermann’s criticisms of the partial least squares (PLS) approach to structural equation modeling. We contend that the alleged shortcomings of PLS are not due to problems with the technique, but instead to three problems with Rönkkö and Evermann’s study: (a) the adherence to the common factor model, (b) a very limited simulation designs, and (c) overstretched generalizations of their findings. Whereas Rönkkö and …
Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research
Purpose – The authors aim to present partial least squares (PLS) as an evolving approach to structural equation modeling (SEM), highlight its advantages and limitations and provide an overview of recent research on the method across various fields. Design/methodology/approach – In this review article, the authors merge literatures from the marketing, management, and management information systems fields to present the state-of-the art of PLS-SEM …
In Pursuit of Understanding What Drives Fan Satisfaction
With economic considerations exerting an ever-increasing influence on soccer club activities, fan satisfaction has become an essential focus for these organizations. Despite the obvious relevance of this topic, the literature has paid little attention to the measurement of fan satisfaction. Based on a thorough literature review and an empirical study of soccer fans, this paper outlines the development of a formative measurement index for fan sati…
How collinearity affects mixture regression results
A new criterion for assessing discriminant validity in variance-based structural equation modeling
Discriminant validity assessment has become a generally accepted prerequisite for analyzing relationships between latent variables. For variance-based structural equation 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 means of a simulation study, we show that these approaches do not reliably detect the lack of discrim…
Guidelines for treating unobserved heterogeneity in tourism research: A comment on Marques and Reis (2015)
Testing measurement invariance of composites using partial least squares
Purpose – Research on international marketing usually involves comparing different groups of respondents. When using structural equation modeling (SEM), group comparisons can be misleading unless researchers establish the invariance of their measures. While methods have been proposed to analyze measurement invariance in common factor models, research lacks an approach in respect of composite models. The purpose of this paper is to present a novel…
Identifying and treating unobserved heterogeneity with Fimix-PLS: Part I – method
Purpose – The purpose of this paper is to provide an overview of unobserved heterogeneity in the context of partial least squares structural equation modeling (PLS-SEM), its prevalence and challenges for social science researchers. Part II – in the next issue ( European Business Review , Vol. 28 No. 2) – presents a case study, which illustrates how to identify and treat unobserved heterogeneity in PLS-SEM using the finite mixture PLS (FIMIX-PLS) …
Estimation issues with PLS and CBSEM: Where the bias lies!
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 variables and their measurement model operationalization from the estimation perspective, we disentang…
Gain more insight from your PLS-SEM results: The importance-performance map analysis
Purpose The purpose of this paper is to introduce the importance-performance map analysis (IPMA) and explain how to use it in the context of partial least squares structural equation modeling (PLS-SEM). A case study, drawing on the IPMA module implemented in the SmartPLS 3 software, illustrates the results generation and interpretation. Design/methodology/approach The explications first address the principles of the IPMA and introduce a systemati…
Partial Least Squares Strukturgleichungsmodellierung: Eine anwendungsorientierte Einführung
Die Partial Least Squares Strukturgleichungsmodellierung (PLS-SEM) hat sich in der wirtschafts- und sozialwissenschaftlichen Forschung als geeignetes Verfahren zur Schätzung von Kausalmodellen behauptet. Dank der Anwenderfreundlichkeit des Verfahrens und der vorhandenen Software ist es inzwischen auch in der Praxis etabliert.
On Comparing Results from CB-SEM and PLS-SEM: Five Perspectives and Five Recommendations
Descriptive statistics and the application of multivariate data analysis techniques such as regression analysis and factor analysis belong to the core set of statistical instruments, and their use has generated findings that have significantly shaped the way we see the world today. The increasing reliance on and acceptance of statistical analysis, as well as the advent of powerful computer systems that allow for handling large amounts of data, pa…
Mirror, mirror on the wall: A comparative evaluation of composite-based structural equation modeling methods
Partial Least Squares Structural Equation Modeling
PLS-SEM or CB-SEM: Updated guidelines on which method to use
Numerous statistical methods are available for social researchers. Therefore, knowing the appropriate technique can be a challenge. For example, when considering structural equation modelling (SEM), selecting between covariance-based (CB-SEM) and variance-based partial least squares (PLS-SEM) can be challenging. This paper applies the same theoretical measurement and structural models and dataset to conduct a direct comparison. The findings revea…
Computer Science (41 works) · Mathematics (41 works) · Structural equation modeling (36 works) · Partial least squares regression (31 works) · Statistics (30 works) · Customer Service Quality and Loyalty (29 works) · Econometrics (26 works) · Psychology (22 works) · Machine learning (19 works) · Technology Adoption and User Behaviour (18 works)