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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 for researchers using structural equation models.

This paper uses scenario analysis to show which estimators are appropriate for reflective measurement models and composite models, and formulates the statistical model that underlies PLS Mode A. It also contrasts two different perspectives: PLS as an estimator for structural equation models vs. PLS-SEM as an overarching framework with a sui generis logic.

There are different variants of PLS, which include PLS, consistent PLS, PLSe1, PLSe2, proposed ordinal PLS and robust PLS, each of which serves a particular purpose. All of these are appropriate for scientific inquiry if applied properly. It is not PLS that subverts the realist search for truth, but some proponents of a framework called “PLS-SEM.” These proponents redefine the term “reflective measurement,” argue against the assessment of model fit and suggest that researchers could obtain “confirmation” for their model.

Researchers should be more conscious, open and respectful regarding different research paradigms.

Researchers should select a statistical model that adequately represents their theory, not necessarily a common factor model, and formulate their model explicitly. Particularly for instrumentalists, pragmatists and constructivists, the composite model appears promising. Researchers should be concerned about their estimator’s properties, not about whether it is called “PLS.” Further, researchers should critically evaluate their model, not seek confirmation or blindly believe in its value.

This paper critically appraises Cadogan and Lee (2022) and reminds researchers who wish to use structural equation modeling, particularly PLS, for their statistical analysis, of some important scientific principles.

Partial least squares structural equation modeling (PLS-SEM) has become an established social sciences multivariate analysis technique. Since quality management researchers also increasingly using PLS-SEM, this growing interest calls for guidance.

Based on established guidelines for applying PLS-SEM and evaluating the results, this research reviews 107 articles applying the method and published in eight leading quality management journals.

The use of PLS-SEM in quality management often only draws on limited information and analysis results. The discipline would benefit from the method's more comprehensive use by following established guidelines. Specifically, the use of predictive model assessment and more advanced PLS-SEM analyses harbors the potential to provide more detailed findings and conclusions when applying the method.

This research provides first insights into PLS-SEM's use in quality management. Future research should identify the key areas and the core quality management models that best support the method's capabilities and researchers' goals.

The results of this analysis guide researchers who use the PLS-SEM method for their quality management studies.

This is the first article to systematically review the use of PLS-SEM in the quality management discipline.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

Structural equation modeling (SEM) has been widely used to examine complex research models in international business and marketing research. While the covariance-based SEM (CB-SEM) approach is dominant, the authors argue that the field’s dynamic nature and the sometimes early stage of theory development more often require a partial least squares SEM (PLS-SEM) approach. The purpose of this paper is to critically review the application of SEM techniques in the field.

The authors searched six journals with an international business (and marketing) focus (Management International Review, Journal of International Business Studies, Journal of International Management, International Marketing Review, Journal of World Business, International Business Review) from 1990 to 2013. The authors reviewed all articles that apply SEM, analyzed their research objectives and methodology choices, and assessed whether the PLS-SEM papers followed the best practices outlined in the past.

Of the articles, 379 utilized CB-SEM and 45 PLS-SEM. The reasons for using PLS-SEM referred largely to sampling and data measurement issues and did not sufficiently build on the procedure’s benefits that stem from its design for predictive and exploratory purposes. Thus, the procedure’s key benefits, which might be fruitful for the theorizing process, are not being fully exploited. Furthermore, authors need to better follow best practices to truly advance theory building.

The authors examined a subset of journals in the field and did not include general management journals that publish international business and marketing-related studies. Fur-thermore, the authors found only limited use of PLS-SEM in the journals the authors considered relevant to the study.

The study contributes to the literature by providing researchers seeking to adopt SEM as an analytical method with practical guidelines for making better choices concerning an appropriate SEM approach. Furthermore, based on a systematic review of current practices in the international business and marketing literature, the authors identify critical challenges in the selection and use of SEM procedures and offer concrete recommendations for better practice.

This paper aims to investigate the interplay of memorable tourism experiences (MTE) dimensions in driving behavioral intentions of heritage tourists through the mediating role of satisfaction.

Empirical data were collected from tourists in the heritage city of Kashan, Iran. Partial least squares-structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) were applied to analyze the data.

The results of PLS-SEM showed that three dimensions of MTE as follows: local culture, involvement and knowledge, significantly directly or indirectly influence tourists’ behavioral intention toward a destination. However, the results of fsQCA identified greater heterogeneity among the respondents by highlighting the positive effects of hedonism and novelty on satisfaction and revisit and word-of-mouth intentions.

This study enriches the empirical evidence on MTE by constructing a composite picture of the memorability of tourists’ experiences within a heritage tourism context. This study is one of the first to investigate the effects of dimensions of MTE on behavioral intentions using both symmetric (PLS-SEM) and asymmetric approaches to identify the more significant dimensions of MTE, as well as sufficient combinations of dimensions to predict behavioral intentions.

本文旨在研究难忘旅游体验 (MTE) 各维度通过满意度这个中介变量来驱动遗产旅游游客行为意图的机制

实证数据是从伊朗遗产城市卡尚的游客那里收集的。本研究采用偏最小二乘结构方程模型（PLS-SEM）和模糊集定性比较分析（fsQCA）对数据进行分析

偏最小二乘结构方程模型的研究结果表明，难忘旅游体验（MTE）的三个维度：当地文化、参与度和熟悉程度，显著地直接或间接地影响游客对目的地的行为意向。然而，模糊集定性比较分析的研究结果表明受访者间存在更大的异质性，其结果凸显了享乐主义和新鲜感对满意度、重游意向和口碑(WOM)意向的正效应

本研究通过构建遗产旅游背景下游客体验难忘性的相互影响机制，丰富了关于难忘旅游体验（MTE）的实证研究证据。本研究是第一个同时使用对称方法（PLS-SEM）和非对称方法（fsQCA）来探究MTE各维度对行为意向的影响的研究之一，通过这种方式可以识别出MTE各维度中更为重要的维度以及维度组合，以此来预测行为意向

Este artículo investiga la influencia de las dimensiones de las experiencias turísticas memorables (ETM) en el fomento de las intenciones de comportamiento de los turistas del patrimonio a través del papel mediador de la satisfacción.

Se recogieron datos empíricos de turistas en la ciudad patrimonial de Kashan, Irán. Para analizar los datos se aplicaron las técnicas partial least squares – structural equation modeling (PLS-SEM) y fuzzy-set qualitative comparative analysis (fsQCA).

Los resultados que proporcionó el análisis PLS-SEM mostraron que tres dimensiones de las ETM: cultura local, implicación y conocimiento, influyen significativamente, de forma directa o indirecta, en la intención de comportamiento de los turistas hacia un destino. Sin embargo, los resultados del enfoque fsQCA identificaron una mayor heterogeneidad entre los encuestados al destacar los efectos positivos del hedonismo y la novedad sobre la satisfacción y las intenciones tanto de volver a visitar el destino como de realizar una comunicación de boca a boca (WOM).

Este estudio enriquece la evidencia empírica sobre las ETM al construir una imagen combinada del carácter memorable de las experiencias de los turistas dentro de un contexto de turismo patrimonial. Este estudio es uno de los primeros en investigar los efectos de las dimensiones las ETM en las intenciones de comportamiento utilizando enfoques simétricos (PLS-SEM) y asimétricos para identificar las dimensiones más significativas las ETM, así como para determinar las combinaciones necesarias de dimensiones para predecir las intenciones de comportamiento.

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 assessment that have been raised in the literature on PLS-PM.

This paper explains when and how to assess the fit of PLS path models. Furthermore, it discusses the concerns raised in the PLS-PM literature about the overall model fit assessment and provides concise guidelines on assessing the overall fit of composite models.

This study explains that the model fit assessment is as important for composite models as it is for common factor models. To assess the overall fit of composite models, researchers can use a statistical test and several fit indices known through structural equation modeling (SEM) with latent variables.

Researchers who use PLS-PM to assess composite models that aim to understand the mechanism of an underlying population and draw statistical inferences should take the concept of the overall model fit seriously.

To facilitate the overall fit assessment of composite models, this study presents a two-step procedure adopted from the literature on SEM with latent variables.

This paper clarifies that the necessity to assess model fit is not a question of which estimator will be used (PLS-PM, maximum likelihood, etc). but of the purpose of statistical modeling. Whereas, the model fit assessment is paramount in explanatory modeling, it is not imperative in predictive modeling.

The purpose of this paper is to develop a structural relationship model to study the relationship between causes and effects of poor communication and information exchange in construction projects using Smart-PLS.

The first method of this research is to identify the causes and effects factors of poor communication in construction projects from the extant of literature. The data used to develop the model was collected using a questionnaire survey, which targeted construction practitioners in the Malaysian construction industry. A five-point Likert type scale was used to rate the significance of the factors. The factors were classified under their relevant construct/group using exploratory factor analysis. A hypothetical model was developed and then transformed into Smart-PLS in which the hypothetical model suggested that each group of the cause factors has a direct impact on the effect groups. The hypothesis was tested using t-values and p-values. The model was assessed for its inner and outer components and achieved the threshold criterion. Further, the model was verified by engaging 14 construction experts to verify its applicability in the construction project setting.

The study developed a structural equation model to clarify the relationships between causes and effects of poor communication in construction projects. The model explained the degree of relationships among causes and effects of poor communication in construction projects.

The published academic and non-academic literature introduced many studies on the issue of communication including the definitions, importance, barriers to effective communication and means of poor communication. However, these studies ended up only on the general issue of communication lacking an in-depth investigation of the causes and effects of poor communication in the construction industry. The study implemented advanced structural modeling to study the causes and effects. The questionnaire, the data and concluding results fill the identified research gap of this study. The addressed issue is also of interest because communication is considered one of the main knowledge areas in construction management.

This study aims to examine the role of the dimensions of entrepreneurial orientation (EO) under turbulent market conditions and reveal the role of an entrepreneur's perception of a crisis in shaping the impact of EO on firm performance.

This study uses partial least squares structural equation modeling (PLS-SEM), multiple linear regression (MLR) and fuzzy-set qualitative comparative analysis (fsQCA). The study sample was comprised of 117 one- and two-star hotels that were operating in Poland.

The results showed that proactiveness and risk-taking significantly affected firm performance. Furthermore, the results revealed that an entrepreneur's perception of a crisis moderated the impact of risk-taking and proactiveness on firm performance. In particular, the findings suggested that, in firms where the crisis strongly influenced their operations, performance was affected by proactiveness, while in those firms where the crisis influenced their operations to a low or moderate degree, performance was affected by risk-taking. Furthermore, fsQCA unveiled the role of innovativeness, which (along with risk-taking) is a sufficient condition that leads to firm performance.

Two characteristics make this study original: first, it investigates EO under turbulent market conditions, and second, it analyzes the role of an entrepreneur's perception of crisis consequences for business operations. The study contributes to the literature on entrepreneurship and crisis management with findings on the different roles of EO dimensions under crisis conditions and an observation about the moderating role of an entrepreneur's perception of the impact of a crisis on operational management and how this perception differentiates the impact of risk-taking and proactiveness on firm performance.

The purpose of this paper is to investigate the relationship between corporate entrepreneurship (CE), organizational culture (OC) and business performance (BP). Additionally, the study has attempted to address the moderating influence of OC on CE–BP relationship.

Data were collected from middle managers of Big Five banks of Pakistan. A two-step approach to structural equation modeling was used. Using confirmatory factor analysis, the measurement model fit was determined. The significance of the theoretical relationship was assessed using structural model.

The results have supported the hypothesized direct and moderated relationship.

The present study extends the body of knowledge in testing the resource-based view of the firm theory and contingency theory through providing empirical evidence on the hypothesized relationships. Additionally, the study has contributed in the existing theory through evaluating the moderating of OC by using interaction effect in partial least squares structural equation modeling (PLS-SEM).

The need for context-specific adoption models led to the development of the firm technology adoption model (F-TAM) model. Among small to medium-scale enterprises (SMEs); however, firm-level factors were rather insignificant in engendering SME level adoption of technological innovation. This study aims to examine the effect of firm size and other moderating and mediating factors on the relationships between personal, firm, societal and technological factors proposed in the stakeholder-oriented F-TAM among SMEs.

A research instrument was developed, reviewed by experts, and pilot tested with a sample of 25 respondents. Data were purposively collected from four hundred (400) SMEs and analyzed with partial least squares structural equation modeling (PLS-SEM).

The study discovered that employees, societal and technological factors moderate the relationship between firm factors of adoption and firm adoption. Without these moderating effects, firm factors of adoption would have been insignificant at the SMEs’ level of organizational technology adoption. The study further discovered that firm size, as well as risk propensity, also affect the relationships proposed in the model.

Data was collected on voluntary adoption from the most cosmopolitan area of a developing country. It, therefore, needs further contextual validation across the country and different countries.

The engagement of innovations in firms must be planned with employees and society as major stakeholders.

The significance of this finding is the study’s emphasis on an eco-system approach for examining the phenomenon of innovation adoption. To the best of the authors’ knowledge, this study is the first to examine the effect of firm characteristics on is proposed eco-system of stakeholders.