Florian Schuberth

Florian Schuberth
University of Twente | UT · Department of Design, Production and Management

PhD

About

52
Publications
104,306
Reads
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1,260
Citations
Introduction
Florian Schuberth currently works at the Department of Design, Production and Management, University of Twente. Florian does research in structural equation modeling with particular focus on composites. Moreover, I am co-developer of confirmatory composite analysis and of the R package cSEM.
Additional affiliations
November 2017 - present
University of Twente
Position
  • Professor
October 2014 - February 2016
Hochschule für angewandte Wissenschaften Würzburg-Schweinfurt
Position
  • Lecturer
Description
  • Statistics I for Bachelor Students
March 2013 - September 2013
Hochschule für angewandte Wissenschaften Würzburg-Schweinfurt
Position
  • Lecturer
Description
  • Statistics II for Bachelor Students

Publications

Publications (52)
Article
Full-text available
This article introduces confirmatory composite analysis (CCA) as a structural equation modeling technique that aims at testing composite models. It facilitates the operationalization and assessment of design concepts, so-called artifacts. CCA entails the same steps as confirmatory factor analysis: model specification, model identification, model es...
Article
Full-text available
Partial least squares path modeling (PLS-PM) is an estimator that has found widespread application for causal information systems (IS) research. Recently, the method has been subject to many improvements, such as consistent PLS (PLSc) for latent variable models, a bootstrap-based test for overall model fit, and the heterotrait-to-monotrait ratio of...
Article
Full-text available
Confirmatory composite analysis (CCA) is a subtype of structural equation modeling that assesses composite models. Composite models consist of a set of interrelated emergent variables, i.e., constructs which emerge as linear combinations of other variables. Only recently, Hair et al. (J Bus Res 109(1):101–110, 2020) proposed ‘confirmatory composite...
Article
Full-text available
Confirmatory composite analysis (CCA) was invented by Jörg Henseler and Theo K. Dijkstra in 2014 and elaborated by Schuberth et al. (2018b) as an innovative set of procedures for specifying and assessing composite models. Composite models consist of two or more interrelated constructs, all of which emerge as linear combinations of extant variables,...
Article
Structural equation modeling (SEM) is a versatile statistical method that should theoretically be able to emulate all other methods that are based on the general linear model. In practice, however, researchers using SEM encounter problems incorporating composites into their models. In this tutorial article, I present a specification for SEM that wa...
Article
Full-text available
Confirmatory composite analysis (CCA) was recently proposed as a viable approach to modeling and assessing forged concepts, i.e., theoretical concepts that emerge from their components within their environment. This study introduces CCA to the field of tourism and hospitality research and shows how CCA can be conducted using estimators known from s...
Article
Research in human development often relies on composites, that is, composed variables such as indices. Their composite nature renders these variables inaccessible to conventional factor-centric psychometric validation techniques such as confirmatory factor analysis (CFA). In the context of human development research, there is currently no appropria...
Article
Purpose In their paper titled “A Miracle of Measurement or Accidental Constructivism? How PLS Subverts the Realist Search for Truth,” Cadogan and Lee (2022) cast serious doubt on PLS’s suitability for scientific studies. The purpose of this commentary is to discuss the claims of Cadogan and Lee, correct some inaccuracies, and derive recommendations...
Article
Purpose This study aims to examine the role of an overall model fit assessment in the context of partial least squares path modeling (PLS-PM). In doing so, it will explain when it is important to assess the overall model fit and provides ways of assessing the fit of composite models. Moreover, it will resolve major concerns about model fit assessme...
Article
Full-text available
Knowledge management (KM) can facilitate collaboration and enhance innovation. To manage knowledge, organisations typically implement knowledge management systems (KMSs). It has been shown that KMS facilitates the management of explicit knowledge. However, KMSs are at times not embraced because of issues such as long file search times and informati...
Article
In 2012 and 2013, several critical publications questioned many alleged PLS properties. As a consequence, PLS benefited from a boost of developments. It is, therefore, a good time to review these developments. Evermann and Rönkkö devote their paper to this task and formulate guidelines in the form of 14 recommendations. Yet, while they identified t...
Article
Full-text available
Heterogeneity is a pertinent issue in Information Systems (IS) research because human behavior often differs across groups. In the partial least squares path modeling (PLS-PM) context, several approaches have been proposed to investigate potential group differences. Despite the availability of numerous approaches, literature that compares their eff...
Article
Full-text available
Studying and modeling theoretical concepts is a cornerstone activity in information systems (IS) research. Researchers have been familiar with one type of theoretical concept, namely behavioral concepts, which are assumed to exist in nature and measured by a set of observable variables. In this paper, we present a second type of theoretical concept...
Presentation
Full-text available
Structural equation modeling (SEM) is a versatile statistical method that can deal in principle with latent variables and composites. In practice, however, researchers using SEM encounter problems incorporating composites into their models. To overcome this problem, I present a specification for SEM that was recently sketched by Henseler (2020) to...
Article
Full-text available
Confirmatory composite analysis (CCA) is a structural equation modeling (SEM) technique that specifies and assesses composite models. In a composite model, the construct emerges as a linear combination of observed variables. CCA was invented by Jörg Henseler and Theo K. Dijkstra in 2014, was subsequently fully elaborated by Schuberth et al. (2018),...
Article
Full-text available
Purpose One popular method to assess discriminant validity in structural equation modeling is the heterotrait-monotrait ratio of correlations (HTMT). However, the HTMT assumes tau-equivalent measurement models, which are unlikely to hold for most empirical studies. To relax this assumption, the authors modify the original HTMT and introduce a new c...
Article
Full-text available
The dual theory of passion indicates harmonious passion leads to obsessive passion. This study contemplates that brand engagement (harmonious passion) leads to compulsive behavior (obsessive passion) in two ways: compulsive social media use and compulsive buying. Echoing prior passion research, we posit that three personality traits associated with...
Conference Paper
Existing literature showed that motivating consumers to defend a brand during a brand crisis can be an effective approach to deal with brand crises. However, antecedents of consumers’ motivation to defend a brand and the feasibility of co-creation during a brand crisis are not well explored. The study explores the antecedents which influence consum...
Article
The study’s purpose is threefold: (i) to propose partial least squares path modeling (PLS-PM) as a way to estimate models containing composites of composites and to compare the performance of the PLS-PM approaches in this context, (ii) to provide and evaluate two testing procedures to assess the overall model fit of such models, and (iii) to introd...
Article
Full-text available
Outliers can seriously distort the results of statistical analyses and thus threaten the validity of structural equation models. As a remedy, this article introduces a robust variant of Partial Least Squares Path Modeling (PLS) and consistent Partial Least Squares (PLSc) called robust PLS and robust PLSc, respectively, which are robust against dist...
Article
Full-text available
Purpose – People seem to function according to different models, which implies that in business and social sciences, heterogeneity is a rule rather than an exception. Researchers can investigate such heterogeneity through multigroup analysis (MGA). In the context of partial least squares path modeling (PLS-PM), MGA is currently applied to perform m...
Article
Full-text available
Purpose – The paper enhances consistent partial least squares (PLSc) to yield consistent parameter estimates for population models whose indicator blocks contain a subset of correlated measurement errors. Design/methodology/approach – Correction for attenuation as originally applied by PLSc is modified to include a priori assumptions on the struct...
Code
Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modelling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PL...
Presentation
Full-text available
I present a non-iterative method-of-moments estimator for non-linear latent variable (LV) models, i.e., models including quadratic terms, interaction terms, etc. of LVs. Under the assumption of joint normality of all exogenous variables, the corrected moments of linear combinations of the observed indicators (proxies) can be used to obtain consiste...
Article
Full-text available
This paper examine the concept of tourist engagement modeled as a second-order composite in the context of a heritage destination in Malaysia. In doing so, this study investigates the direct and indirect effects of tourist engagement through satisfaction on destination loyalty. Data was collected from tourists visiting Kinabalu National Park, Sabah...
Article
Full-text available
Purpose As technology in tourism and hospitality (TTH) develops technical artifacts according to visitors’ demands, it must deal with both behavioral and design constructs in the context of structural equation modeling (SEM). While behavioral constructs are typically modeled as common factors, the study at hand introduces the composite into TTH to...
Presentation
Auxiliary theories are indispensable to operationalize abstract concepts in structural equation modeling (SEM). While for behavioral concepts, such as traits or attitudes, auxiliary theories already exist, the current literature lacks of auxiliary theories for design concepts. Obviously, this is particularly disadvantageous for disciplines that inv...
Article
Full-text available
Refined olive oil (ROO) and extra virgin olive oil (EVOO) categories are different products with respect to their objective quality. Nevertheless, this quality gap is not reflected in the purchase behaviour of consumers in Spain, which is the main producer country worldwide. On the basis of economic theory, the price gap could be a part of the expl...
Code
The purpose of this paper is to provide a practical tool for assessing the statistical difference between two parameter estimates in SEM using PLS. This guideline is intended to be used to test a parameter difference based on the parameter estimates and the bootstrap distribution. The input required for the proposed methodological procedure directl...
Article
Full-text available
Structural equation modeling using partial least squares (PLS-SEM) has become a main-stream modeling approach in various disciplines. Nevertheless, prior literature still lacks a practical guidance on how to properly test for differences between parameter estimates. Whereas existing techniques such as parametric and non-parametric approaches in PLS...
Article
Full-text available
This article introduces a new consistent variance-based estimator called ordinal consistent partial least squares (OrdPLSc). OrdPLSc completes the family of variance-based estimators consisting of PLS, PLSc, and OrdPLS and permits to estimate structural equation models of composites and common factors if some or all indicators are measured on an or...
Thesis
Full-text available
This dissertation deals with composite-based methods for structural equation models with latent variables and their enhancement. It comprises five chapters. Besides a brief introduction in the first chapter, the remaining chapters consisting of four essays cover the results of my PhD studies. Two of the essays have already been published in an inte...
Chapter
In this chapter, we present a new variance-based estimator called ordinal consistent partial least squares (OrdPLSc). It is a promising combination of consistent partial least squares (PLSc) and ordinal partial least squares (OrdPLS), respectively, which is capable to deal in structural equation models with common factors, composites, and ordinal c...
Research
Full-text available
I replicate the results from the Monte Carlo simulation presented in the Chapter ’A perfect match between a model and mode’ (Dijkstra, forthcoming) using Summers’ model containing composites instead of common factors. Furthermore, I compare the results of the generalized canonical correlation analysis (GCCA) using MAXVAR to those obtained from part...
Article
In this paper we provide an extensive comparison between commonly used linear econometric methods in the audit fee literature and explicitly address their underlying assumptions. As opposed to common practice in similar papers we explicitly consider violations of the strict exogeneity assumption in terms of unobserved firm-specific effects and argu...

Questions

Questions (6)

Projects

Projects (3)
Project
Estimate, assess, test, and study linear, nonlinear, hierarchical and multigroup structural equation models using composite-based approaches and procedures, including estimation techniques such as partial least squares path modeling (PLS-PM) and its derivatives (PLSc, ordPLSc, robustPLSc), generalized structured component analysis (GSCA), generalized structured component analysis with uniqueness terms (GSCAm), generalized canonical correlation analysis (GCCA), principal component analysis (PCA), factor score regression (FSR) using sum score, regression or bartlett scores (including bias correction using Croon’s approach), as well as several tests and typical postestimation procedures (e.g., verify admissibility of the estimates, assess the model fit, test the model fit etc.).
Project
Theo K. Dijkstra gave a talk at the European Methodology Congress, 2014, on "Very simple estimators for a class of polynomial factor models" where promising results were presented for the method developed. We want to turn this into a more general tool, with software available in R.