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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.

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.

Sports marketing and sponsorship research is located at the intersection of behavioral and design research, which means that it analyzes the current world and shapes a future world. This dual focus poses challenges for formulating and testing theories of sports marketing.

This article develops criteria for categorizing theoretical concepts as either behavioral or formed as different ways of expressing ideas of sports marketing research. It emphasizes the need for clear concept categorization for proper operationalization and applies these criteria to selected theoretical concepts of sports marketing and sponsorship research.

The study defines three criteria to categorize theoretical concepts, namely (1) the guiding idea of research, (2) the role of observed variables, and (3) the relationship among observed variables. Applying these criteria to concepts of sports marketing research manifests the relevance of categorizing theoretical concepts as either behavioral or formed to operationalize concepts correctly.

This study is the first in sports marketing to clearly categorize theoretical concepts as either behavioral or formed, and to formulate guidelines on how to differentiate behavioral concepts from formed concepts.

The ongoing business dynamics show two aspects for generating innovation: first, high-impact innovations are developed jointly by several actors, such as universities, enterprises, and governments. Second, startups are better suited to develop innovation during crises or periods of low growth as experienced at the moment. Based on these aspects and drawing on the constructs of the triple helix, this study analyzes the influence between the characteristics of the actors on the quality of the startup ecosystem from a global view.

The study examines the cross-section data of 35 countries between 2017 and 2018 and applies the partial least squares structural equation modeling (PLS-SEM) for assessing the relationships between the triple helix on the quality of the startup ecosystem on a country-level.

The findings suggest that each actor of the triple helix individually does not positively affect the quality of the startup ecosystem. Yet, when analyzing the actors jointly by creating a second-order latent variable (i.e. triple helix), the study found out that in this way, the triple helix construct has a positive effect on the quality of the startup ecosystem.

Although a large body of prior literature indicates the importance of generating interrelationships among the different entities involved in ecosystems, few studies provide empirical evidence from a global perspective of the need for these entities to act in an overlapping manner. The present study supports previous research and reinforces the importance of the triple helix for a more innovative environment.

After assessing papers on efficiency, most of the studies available are focused on the analysis of efficiency measures, without providing a deep discussion of the factors that determine efficiency. This study aims to evaluate the efficiency of Brazilian electricity distribution companies based on a structural model that enables the identification of a network of relationships among representative variables that contribute to efficiency.

Structural equation modeling was applied in a sample of 62 electricity distribution companies operating in Brazil, forming a balanced panel from 2010 to 2014. Then, the authors verified the model compliance according to the empirical evidence of the entities analyzed. This verification included a survey of the variables, which was supported by theoretical references related to the phenomenon studied. The data collected were statistically treated, and benchmarking models and multivariate techniques were used. Once the adjustments were made, the re-specified model was estimated using the maximum likelihood method.

The empirical model reached good adjustment rates. The analysis concluded that the constructs information system, structural system, management system and sociocultural system affect efficiency.

This study adds to several other papers, and this is one of its main contributions. Relationships among the constructs have been systematized according to literature in the form of a structural model, which will enable future researchers to have a reference frame of relevant studies and a research foundation in this area of knowledge. A third contribution is the model tested in a sample of Brazilian electricity distribution companies, whose results can be compared to other utility sectors (e.g. telecommunications) or to other countries' electrical sectors, thus providing an empirical basis for the proposed hypotheses. Finally, this study also offers a contribution to the Brazilian Electrical Energy Agency (Aneel, in Portuguese), a regulatory agency, providing mechanisms to guide tariff adjustments, seeking a balance between costs and the need for investments allied to tariff affordability.

This article intends to investigate on the undeclared work (UW) by involving several features, which can be evaluated throughout a set of appropriate variables. The REBUS-PLS (Response Based procedure for detecting Unit Segments–Partial Least Squares) has been proposed in order to support policy decisions targeted to this heterogeneous scenario. The authors refer to Italy, due to the disparity of its territorial districts, but the conclusions can be extended to different European countries.

A total of 2,877,000 firms has been involved for empirical analysis. The manifest variables have been obtained by fixing both NACE codes and the NUTS2 level.

The analysis confirms that the model is suitable to evaluate the effects of the indicators connected to ‘Labour force’, ‘Tax system’, ‘Non-Profit Organizations’, and ‘Migrants’. Special prominence has been dedicated to the labour inspections' features.

If the management designs the policy actions by using the model proposed, a critical evaluation of the implications is needed, by focusing different perspectives and several weaknesses.

Assuming that the Italian regions are relatively homogeneous, results reveal no significant correlations to the UW, except for the taxes. In contrast, the involvement of the heterogeneity shows that the UW significantly depends on the changes of Labour force, Tax system and NPOs dimensions, in 11 out of 18 Italian regions. No clear evidence emerges from Migrants feature, which seems to have a negatively impact on the UW.

To the authors' knowledge, compared to the previous research papers, the analysis of the UW via REBUS-PLS and the mentioned manifest variables, has never been undertaken so far.

The purpose of this paper is to determine the drivers of the formation of e-loyalty in a tourist destination, providing a model composed of variables that are under the control of the firm along with others that are not fully controllable by professionals.

The study was carried out with a sample of 497 subjects, university students and online consumers, and with the use of structural equations (partial least squares).

Results show that young people give a high valuation to all the variables used in the research. These results contribute to the literature on e-loyalty in tourism destinations and improve tourism loyalty in this population segment.

The main limitation of this research has been related to the number of variables and measurement indicators that, according to the literature review, influence e-loyalty. Finally, a balanced and statistically significant model has been developed that has practical utility and analyzes online purchase of tourism products from a process perspective that includes variables that are internal and external to the firm.

The study suggests that young people have a favourable attitude and predisposition towards e-commerce, which, in turn, favours firms’ efforts to promote consumption and loyalty within the framework of the model’s variables.

This research paper has important value by analysing the initiating variables to determine how e-loyalty can be managed in tourist destinations, in addition to analysing an important segment for future tourism development.

The purpose this paper is to review some of the statistical methods used in the field of social sciences.

A review of some of the statistical methodologies used in areas like survey methodology, official statistics, sociology, psychology, political science, criminology, public policy, marketing research, demography, education and economics.

Several areas are presented such as parametric modeling, nonparametric modeling and multivariate methods. Focus is also given to time series modeling, analysis of categorical data and sampling issues and other useful techniques for the analysis of data in the social sciences. Indicative references are given for all the above methods along with some insights for the application of these techniques.

This paper reviews some statistical methods that are used in social sciences and the authors draw the attention of researchers on less popular methods. The purpose is not to give technical details and also not to refer to all the existing techniques or to all the possible areas of statistics. The focus is mainly on the applied aspect of the techniques and the authors give insights about techniques that can be used to answer problems in the abovementioned areas of research.

The purpose of this study is to analyze the influence of social capital on human capital; the effect of social capital on transaction costs; the influence of social capital, human capital and transaction costs on empowerment; the indirect effect of social capital on empowerment through human capital; and the indirect effect of social capital on empowerment through transaction costs in Bangli Regency.

The population in this research is all wood carving business in Bangli Regency, in all districts some 366 business units. The number of respondents surveyed were 191 business units in all sub-districts. The sampling technique used is stratified random sampling, with strata of business area. Inferential analysis is preceded by using factor analysis techniques to obtain factor scores on each latent variable, followed by path analysis to answer the research objectives.

Based on the analysis, the following conclusions are drawn: social capital has a positive and significant impact on human resources; positive social capital and significant positive to transaction costs; social capital and human resources have a positive and significant effect while transaction costs and no significant positive effect on empowerment; human resources partially mediate the influence of social capital on empowerment; and transaction costs do not act as a variable, mediating the influence of social capital on empowering small woodcraft industry in Bangli Regency.

This study is one of the few to investigate the role of social capital, human capital and transaction cost on empowerment of small industries, especially wood carving in Bangli District. This small woodcraft industry is famous for its uniqueness that characterizes Balinese carving ornaments. But lately, the productivity of handicrafts wood carving, especially in Bangli District, fluctuates tend to decline. Social capital, in addition to human capital and technology, also plays an important role in the production process. Social capital equals other physical capital and can increase productivity and economic efficiency. Higher social capital owned by individuals or groups can reduce transaction costs; thus economic activity can run efficiently. Social capital is the information, trust and norms of reciprocity inherent in social networks.

During the pandemic, two types of fear were identified that occur significantly in all groups or profiles of people. The aim of this paper is to determine which of the two types of fears exist in certain psychological groups, and which of the fears strongly influence the decision to travel.

The VALS 2 method and standardized questionnaire were used for the segmentation of the tourist market or for the determination of the psychographic profiles of the consumers, and three additional questions were joined to it as they were vital for the research of the type of fear and its impact on the decision for traveling. When the reliability of the questionnaire and the validity of the sample were determined, the data were further processed using a computer program package IMB AMOS SPSS 21.00, and then, based on the theoretical suppositions and hypotheses, the SEM structural model was created.

The paper indicates the existence of established types of fears in humans, when it comes to pandemics and similar crisis situations. People are most afraid of infection during travel, and lack of funds and job loss during the critical period of the pandemic. The research conducted confirms that all groups of people, who are determined by the psychological technique VALS 2, react with a certain dose of fear and make decisions under the pressure of fears.

The research had limitations in terms of contact with people and conducting live surveys. The measures during the pandemic, which were carried out by the state, included social distance and limited movement of people.

The work can contribute to the community, along with similar research. The results of the research will be available, and it will be possible to see the behavior of people during crisis situations, and the impact of fears on making decisions, both travel decisions and decisions related to other areas of life.

The paper provides research results on a large sample of respondents, and can serve as a basis for further research in the field of tourism, psychology and similar fields. It is crucial to consider the type of fears, and the strength of the impact of these fears on the decision to travel, during crisis situations.