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The purpose of this study is to examine role stress over the course of an alliance between supply chains. This study examines ambiguity as antecedent to multiple organisational outcomes.

This study subsequently uses a time series design that uses a close replication of the authors’ initial study. The design affords the opportunity to examine the dynamics associated with the evolution of the alliance.

This study recognises that the relationships developed by collaborating firms are enacted by downstream entrepreneurs in the supply chain, yet this observation is rarely incorporated into interfirm research. The authors illustrate that the alliances have a significant downstream influence on operations at the retail level.

This longitudinal research has the potential to reduce common method variance and enhance causal inference. The second limitation concerns the simultaneous collection of the predictor and criterion variables. The third limitation is the use of single informants as the primary vehicle for the analysis of the theoretical model when prior research indicates that multiple informants offer enhanced reliability and validity.

The findings contribute to the management theory of business entrepreneurship and strategic alliances and research on supply chains.

This study underscores the need to examine alliances via time series. Research that attempts to generalise from data collected at a single point in time is unlikely to be able to capture the dynamics associated with the development of a joint venture and offers limited opportunity to make inferences about the causal order of relationships. The model based on longitudinal data reveals that the stage of an alliance influences the level of vertical control and ambiguity and the effect of control on role ambiguity.

This study aims to evaluate the usage of partial least squares structural equation modeling (PLS-SEM) in journals related to logistics and supply chain management (LSCM).

Based on a structured literature review approach, the authors reviewed 401 articles in the field of LSCM applying PLS-SEM published in 15 major journals between 2014 and 2022. The analysis focused on reasons for using PLS-SEM, measurement model and structural model evaluation criteria, advanced analysis techniques and reporting practices.

LSCM researchers sometimes did not clarify the reasons for using PLS-SEM, such as sample size, complex models and non-normal distributions. Additionally, most articles exhibit limited use of measurement models and structural model evaluation techniques, leading to inappropriate use of assessment criteria. Furthermore, progress in the practical implementation of advanced analysis techniques is slow, and there is a need for improved transparency in reporting analysis algorithms.

This study contributes to the field of LSCM by providing clear criteria and steps for using PLS-SEM, enriching the understanding and advancement of research methodologies in this field.

The purpose of this paper is to integrate the findings of articles appearing in European Journal of Marketing’s special section on covariance-based versus composite-based structural equations modeling (SEM).

This is an editorial which uses literature review to draw conclusions regarding areas of agreement, areas for further research, and changing the discussion around composite-based SEM methods.

There are now four new areas of agreement regarding composite-based SEM. Researchers should adopt a toolbox approach to their methods and know the strengths and weaknesses of the research tools in their toolbox. Partial least squares (PLS) SEM and covariance-based SEM are not substitutes, and it is inappropriate to use the language of confirmatory factor analysis (CFA) in reporting measurement estimates from PLS SEM. Measurement matters and researchers need to devote effort to using reliable and valid multi-item measures in their investigations.

This postscript article outlines recommendations for authors, reviewers and editors regarding the analysis of data and reporting of results using structural equations models.

The paper aims to assess the impact of a government digital platform, WoredaNet on the dynamic capabilities (DCs) of government organizations, that provides government services to citizens in Ethiopia.

The study adopted a quantitative strategy using 10 local government administrative regions in Ethiopia (Woredas), which digitally innovate using the government digital platform. This study sampled 970 employees from government organizations to better understand the usage of digital government in low-income countries to enhance service delivery through DCs. The study adopted a conceptual formative model using the covariance-based structural equation modeling (SEM) technique. The model integrated seven latent variables, namely, WoredaNet usage, adaptive capability, absorptive capability, innovative capability, opportunity-sensing ability, opportunity-seizing ability and opportunity-reconfiguring ability. The relationships between the latent variables were then created, and 15 hypotheses were designed.

The research showed that government organizations’ ability to adapt, absorb and innovate is enhanced by using WoredaNet. The study revealed how government organizations could enhance their opportunity seizing and opportunity reconfiguring capabilities by leveraging their adaptive, absorptive and innovative capabilities. On the other hand, the findings of the study indicated that there is no significant relationship between WoredaNet usage and the microfoundations of government organizations. This could be because of the varied nature of government organizations. And hence, could be addressed by considering the same formative model on narrower segment of government organizations.

The paper contributes to digital government literature in revealing how DCs of government organizations in resource-constrained low-income countries could be assessed effectively using formative models.

Expanded awareness and application of recent PLS-SEM reporting practices were again called for by Hair (2022) in his PLS 2022 Keynote Address. This paper aims to analyze and extend the application of PLS-SEM in Industrial Management and Data Systems (IMDS) to focus on trends emerging in the more recent 2016–2022 period.

A review of PLS-SEM applications in information systems studies published in IMDS and MISQ for the period 2012–2022 identifies and comments on a total of 135 articles. Selected emerging advanced analytical PLS-SEM applications are also highlighted to expand awareness of their value in more rigorously evaluating model results.

There is a continually increasing maturity of the information systems field in applying PLS-SEM, particularly for IMDS authors. Model complexity and improved prediction assessment as well as other advanced analytical options are increasingly identified as reasons for applying PLS-SEM.

Findings demonstrate the continued use and acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is the preferred SEM method in many research settings, but particularly when the research objective is prediction to the population, mediation and mediated moderation, formative constructs are specified, constructs must be modeled as higher-order and for competing model comparisons.

This update on PLS-SEM applications and recent methodological developments will help authors to better understand and apply the method, as well as publish their work. Researchers are encouraged to engage in more complete analyses and include enhanced reporting procedures.

Applications of PLS-SEM for prediction, theory testing and confirmation are increasing. Information systems scholars should continue to exercise sound practice by reporting reasons for using PLS-SEM and recognizing its wider applicability for both exploratory and confirmatory research.

Generalized structured component analysis (GSCA) and partial least squares path modeling (PLSPM) are two key component-based approaches to structural equation modeling that facilitate the analysis of theoretically established models in terms of both explanation and prediction. This study aims to offer a comparative evaluation of GSCA and PLSPM in a predictive modeling framework.

A simulation study compares the predictive performance of GSCA and PLSPM under various simulation conditions and different prediction types of correctly specified and misspecified models.

The results suggest that GSCA with reflective composite indicators (GSCA_R) is the most versatile approach. For observed prediction, which uses the component scores to generate prediction for the indicators, GSCA_R performs slightly better than PLSPM with mode A. For operative prediction, which considers all parameter estimates to generate predictions, both methods perform equally well. GSCA with formative composite indicators and PLSPM with mode B generally lag behind the other methods.

Future research may further assess the methods’ prediction precision, considering more experimental factors with a wider range of levels, including more extreme ones.

When prediction is the primary study aim, researchers should generally revert to GSCA_R, considering its performance for observed and operative prediction together.

This research is the first to compare the relative efficacy of GSCA and PLSPM in terms of predictive power.

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.

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.

Horses play an important role in the agricultural industry around the world. The equestrian sector offers new markets and sustainable business opportunities. This paper, based on a structural equation modelling approach, seeks to explore the interests of Romanian entrepreneurs in developing a sustainable business in the equestrian sector by investing in the use of horse manure. This manure is an important renewable resource in the circular economy, including in the production of bioenergy and bio-fertilizers. The present research investigates whether there is an interest in developing such a business in Romania, built around three pillars: the environment, society and the economy.

PLS-SEM is an appropriate method for this research, where prediction of interest for sustainable entrepreneurship plays a central role. In total, 153 responses have been collected and validated based on a questionnaire and the invitations to complete were sent to people who are already entrepreneurs or have intention to become entrepreneurs in the near future.

The structural model shows that society's interest has the strongest effect on developing a sustainable business model through horse manure. Surprisingly, the study does not reflect an expected correlation between the interest in the environment and the development of a sustainable business model through horse manure resulting in bioenergy.

This study contributes to arousing the interest in research and even the development of a business by presenting the sustainability factors in the horse industry and adopting technological innovations, services, products and business models. The study was conducted in Romania, where, currently, the manure produced by horses is underexploited, and the equestrian sector requires new business models, innovations and sustainable development.

This study examines the quality of work-life (QoWL) as a formative construct and validates the scale in an Indian context. Taking a cue from the two-factor (Herzberg) theory, the study developed and validated a formative assessment model of QoWL in the current scenario.

Cross-sectional data and a self-administered questionnaire were used to analyze the QoWL scale based on a sample of 841 respondents from IT/ITES, BFSI, CPG and manufacturing sectors. Indicators/items of QoWL were considered a first-order reflective construct, and factors of QoWL were considered second-order formative construct in the study. Embedded two-stage approach was used to assess the antecedent construct in the model in which QoWL was measured with seven formative indicators in stage one, and all the constructs of the QoWL are measured with a single item (Global_QWL, i.e. the essence of all constructs) in stage two.

The study found QoWL as a formative construct with seven significant dimensions; namely, hygiene factors included fairness in compensation (FC), job security (JS), interpersonal relationship (IR), health and wellbeing (HWB), where motivational factors had rewards and career growth (RG), work-life balance (WLB) and learning and development (LD). The study also indicated the strong association of a single item (global_QWL) with all constructs of QoWL. The study findings conceptualize a QoWL as a formative construct within the mentioned sector and can be generalized and extended to other sectors of the economy as well.

Future researchers can take guidance to deal with the formative construct in the development and validation of scale in various topics in the field of HRM. Future researchers can extend the study across cities and different sectors.

In this VUCA world, employees have to be constantly on their toes to ensure their organization remains relevant. In this context, the least organization can do for their employees is to offer a conducive environment and favorable QoWL. This study aims to assist the key decision-makers in applying the QoWL index as a formative construct and aiding them in improving the quality of their decisions.

Researcher believes that applying the QoWL index as a formative construct can aid decision-makers in improving the quality of their decisions by equipping them with relevant inputs and knowledge. Government can focus on the employees' welfare and introduce the current motivational and hygiene factors in the area of quality of life of the Indians.

Formative assessment measurement of QoWL model was validated with the two-factor theory to understand the work environment of India in the private sector across different sectors. The unique finding of the study was a single item (global_QWL) to conclude the QoWL index as a formative construct by redundancy analysis.