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The present study aims to specify, estimate, and validate the composite formative model of consumer eSports engagement (CeSE) through utilizing the composite confirmatory analysis (CCA) methodological approach.

To validate the composite model of CeSE, we collected the data using the Mturk online tool from eSports gamers located in European countries. The partial least squares based structural equation modelling (PLS-SEM) approach was employed using SmartPLS to conduct CCA analyses.

Using CCA, the authors first evaluated the reflective constructs (three first-order dimensions comprising cognitive, affective, and activation) and found reliable and valid reflective constructs. The authors then proceeded to assess the composite formative model of CeSE at higher-order level and resulted that CeSE is a valid composite model. Besides, the nomological network of CeSE with technology acceptance variables (e.g. behavioral intention and usage behavioral were estimated and found significant results).

This study contributes to consumer engagement literature in many directions. First, this study applies consumer engagement scale in the eSports context (i.e. eSports game brands). Second, this study notably specifies, estimates, and validates CeSE as composite model comprising cognitive, affective, and activation factors as first-order reflective constructs and CeSE as second/higher-order formative construct. Third, this study applies CCA guidelines to establish the CeSE as a composite formative measurement model and make significant methodology contribution. Fourth, this study extends the TAM model via studying CeSE as an important determinant of behavioral intention to play eSports games, which in turn impacts on eSports gaming/usage behavior.

The purpose of this paper is to critically review and synthesize the scale development practices in hospitality and tourism and propose updated guidelines applicable for both reflective and composite scales.

Using a critical review of a sample of scale development papers published in six top-tier tourism and hospitality journals, the current guidelines' weaknesses and strengths and their applications are identified. Updated procedures are proposed to overcome these weaknesses.

This review showed several issues in applying existing guidelines, including incomplete and unclear data collection processes, inconsistent data analysis processes including validity/reliability assessment and lack of criteria to identify and assess composite scales. As such, this paper proposes updated guidelines by incorporating the confirmatory composite analysis to assess composite scales.

This paper offers unique theoretical and methodological contributions to scale development literature, by identifying the shortcomings of current practices of scale development and propose guidelines for both reflective and composite scales. The current scale development procedures cannot be applied for composite scales, and so the results of composite scale development using the current procedures are questionable. The updated guidelines by the current study improve new scales' accuracy, reliability and validity.

Drawing upon the relational exchange theory, the longitudinal relationship between various stages of project management customer satisfaction, value for money and repurchase intent are examined.

Using a survey questionnaire, data were gathered over four consecutive quarters (N = 2,537). The statistical methods included exploratory factor analysis, confirmatory composite analysis (CCA) and partial least squares structural equation modeling (PLS-SEM).

Project management was perceived as a three-dimensional construct (proposal, installation, commissioning/start-up). There was a significant longitudinal relationship between project stages and satisfaction in the complete data set. The results varied on the quarterly basis. The relationship customer satisfaction/repurchase intent was significant in the whole data set and during all quarters. This was the case for the relationships between value for money and customer satisfaction and between value for money and repurchase intent. The effect sizes were small between project management stages and customer satisfaction, small to medium for the value for money construct and large for the customer satisfaction construct.

An important implication is the significant relationship between the stages of project management and satisfaction. However, the effect sizes were small, however. The importance of the effect size in comparison to the significance of the relationships is highlighted especially when the sample size is large. The paper also confirms the linear relationship between satisfaction and repurchase intent. The nature of the relationship between customer satisfaction and loyalty is based on a moderate exchange relationship in the relational exchange continuum. The study contributes to the relational exchange theory in the context of project management.

This study examines the vital factors that influence digital marketing adoption among small travel agencies (brick-and-mortar) and the impact of digital marketing adoption on organizational performance modeled as a formative-formative HOC.

This empirical study builds on diffusion of innovation (DOI) theory and technology-organization-environment (TOE) framework to identify the factors of digital marketing adoption by small travel agencies. Data were collected from 226 small travel agents in India using purposive and snowball sampling. Partial least square-structural equation modelling (PLS-SEM) is used to analyze the reflectively and formatively measured constructs.

The findings reveal significant constructs of digital marketing adoption by small travel agencies. The study also establishes the positive impact of digital marketing adoption on organizational performance. Trust partially mediates the impact of technological factors (relative advantage, security concerns) and organizational factor (knowledge) on digital marketing adoption.

The study provides methodological contribution to the literature by applying confirmatory composite analysis (CCA) approach in PLS-SEM. The study contributes to the literature by integrating DOI theory and TOE framework. The study enriches the literature on trust as it recognizes the crucial role of trust as a mediating construct.

The study provides useful implications to marketing practitioners of small travel agencies. The study shows strong predictive capacity and can be generalized throughout diverse samples.

The study adds value to the literature as it explores the digital marketing adoption among the under researched small travel agencies by integrating DOI-TOE theory. The study uniquely proposes and validates organizational performance as a formative-formative higher-order construct.

This research aims to investigate the influence of the implementation of technical cycles on both captured value and shared value in the circular economy context. Moreover, it analyses the moderating effect of competitive criteria on the relationship between technical cycles and captured value. Finally, it examines the relationship between the captured value and the shared value.

This research follows survey-based research with data gathered from 50 countries and 16 sectors, whose final sample represented 233 organisations. In order to validate the structural and measurement model, the authors applied the partial least squares structural equation modelling technique in the strict rigour of the confirmatory algorithm.

The validated research model demonstrates the value flow through technical cycles. Moreover, it shows the crucial role of the competitive criteria in the value stream through direct, moderate and indirect effects by influencing the relationship between technical cycles and captured and shared values. Finally, the study fills the gap for quantitative studies in the circular economy field.

From a practical perspective, this study contributes to structuring circular business models more robustly, by understanding the influence of competitive criteria (cost, quality, flexibility and delivery) on the conversion of operation strategy in the implementation of the technical cycles in the circular economy context. It contributes to decision-makers, in deciding on which competitive criteria to invest more, which brings more consistent results for technical cycle implementation. It also confirms the importance of partnerships, demonstrating how value cascades from the company through the value network.

As far as is known to date, this is the first study investigating the influence of competitive criteria in the circular economy context. Furthermore, it sheds light on the direct and indirect effects of the technical cycles on value captured by organisations and flow shared value with other players.

This study aims to develop and validate a scale for measuring accounting service quality (ASQ), which is named ACCOUNTQUAL.

The authors initially investigated the service quality literature in the context of accounting. To develop the scale, the authors carried out three studies. First, the authors conducted 20 in-depth interviews to generate the ASQ items. Then, they undertook a survey with 174 accounting services clients to group these items into factors through exploratory factor analysis (EFA). Finally, the authors carried out another survey with 330 clients to purify and validate the scale through a confirmatory composite analysis (CCA) and structural equation modeling (SEM).

The authors were able to validate the ACCOUNTQUAL scale, which is composed of the following dimensions: efficiency, trust, technological innovation and accountant knowledge, the latter being composed of three aspects: consultative view, technical capacitation and knowledge about clients.

The authors concluded that ASQ is a multidimensional construct that covers the assessment of technical, tooling, relationship and qualification aspects of the accounting service. To the best of the authors’ knowledge, this is the first study that developed and validated a scale for measuring ASQ. If accounting service providers meets the elements presented in the scale, they will potentially deliver a high-quality service.

Unlike traditional products and services, customer motivation to purchase green products/services may be due to non-marketing factors, such as their personal values about health. In this study, the authors aim to propose and validate an integrative model using both advertising attitude factors and health beliefs to explain purchase intention and word of mouth in the context of green marketing. The authors focus specifically on collectivist consumers as values and social norms that tend to be more salient in driving their decisions.

The model was tested empirically using a survey study with 308 Chinese consumers in Hong Kong. The data were analyzed using confirmatory composite analysis (CCA) and partial least squares structural equation modeling.

All health beliefs were significant predictors of green advertising attitude. Green satisfaction fully mediates the relationship between green advertising attitude and positive word of mouth for products and services with green advertising for collectivist Chinese consumers. Meanwhile, green satisfaction partially mediates the relationship between green advertising attitude and purchase intention. In addition, green brand equity partially mediates the green advertising attitude–purchase intention/positive word of mouth link.

The significant impacts of health belief factors on green advertising attitude present important implications to advertising managers in terms of the use of information appeal in promoting green products/services. Green brand equity should also be developed in order to optimize green advertising effectiveness, especially in the context of collectivist customers.

This research is one of the first few studies investigating the mediating role of green satisfaction and green brand equity for collectivist consumer behaviors based on the health belief model (HBM).

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 consistent measure for congeneric measurement models: the HTMT2.

The HTMT2 is designed in analogy to the HTMT but relies on the geometric mean instead of the arithmetic mean. A Monte Carlo simulation compares the performance of the HTMT and the HTMT2. In the simulation, several design factors are varied such as loading patterns, sample sizes and inter-construct correlations in order to compare the estimation bias of the two criteria.

The HTMT2 provides less biased estimations of the correlations among the latent variables compared to the HTMT, in particular if indicators loading patterns are heterogeneous. Consequently, the HTMT2 should be preferred over the HTMT to assess discriminant validity in case of congeneric measurement models.

However, the HTMT2 can only be determined if all correlations between involved observable variables are positive.

This paper introduces the HTMT2 as an improved version of the traditional HTMT. Compared to other approaches assessing discriminant validity, the HTMT2 provides two advantages: (1) the ease of its computation, since HTMT2 is only based on the indicator correlations, and (2) the relaxed assumption of tau-equivalence. The authors highly recommend the HTMT2 criterion over the traditional HTMT for assessing discriminant validity in empirical studies.

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.