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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.

The purpose of this study is to investigate the influence that technological, environmental and organizational factors have on the rate of Internet of Things (IoT) adoption within the logistics industry. In addition, the moderating effect that the risk factor has on the technological, environmental and organizational factors regarding the implementation of IoT in logistics.

For the purpose of testing the models and hypotheses, a survey was carried out in order to collect the responses from currently employed individuals at various companies working in the field of logistics or IoT. For the purpose of analysis, the authors made use of the partial least squares structure equation model (PLS-SEM) technique.

Findings of this study concluded that technology- and environmental-related factors significantly affect the adoption of IoT in logistics, while risk acts as a moderator for the technological-related factor only in the adoption of IoT in logistics.

The relevance of the authors' study lies in the growing importance of IoT in logistics and the need for logistics companies to understand the factors that impact the adoption of IoT in their operations. By identifying and analyzing the factors that influence IoT adoption in logistics, the authors' study provides valuable insights that can help logistics companies make informed decisions about whether and how to adopt IoT.

The research will help organizations make strategies for the successful adoption of IoT and ease the lives of all the stakeholders.

In this research, the authors attempted to find the factors that influence the adoption of IoT in logistics management. The influence of the technological, environmental, organizational and risk-related factors on the adoption of IoT in logistics management was studied. The moderating effect of risk over these factors on the adoption of IoT in logistics was also analyzed. This is original work and has never been done earlier.

There is growing empirical evidence that firm heterogeneity is technologically non-neutral. This chapter extends the Gandhi, Navarro, and Rivers (2020) proxy variable framework for structurally identifying production functions to a more general case when latent firm productivity is multi-dimensional, with both factor-neutral and (biased) factor-augmenting components. Unlike alternative methodologies, the proposed model can be identified under weaker data requirements, notably, without relying on the typically unavailable cross-sectional variation in input prices for instrumentation. When markets are perfectly competitive, point identification is achieved by leveraging the information contained in static optimality conditions, effectively adopting a system-of-equations approach. It is also shown how one can partially identify the non-neutral production technology in the traditional proxy variable framework when firms have market power.

This study explores the enablers of students “entrepreneurial intentions by identifying the factors that raise students” interest in embracing an entrepreneurial career.

Entrepreneurship education is increasingly attracting attention as a means of fostering entrepreneurial activity and creating a culture of innovation. Developing students' entrepreneurial intentions is critical to promote entrepreneurship. This research is built on a mixed method approach of partial least squares structural equation modelling and fuzzy-set qualitative comparative analysis.

The factors that influence students ‘entrepreneurial intentions are identified: business incubation programmes, non-reimbursable grants for entrepreneurial students, networking events to promote entrepreneurship, mentoring services, innovation labs for business idea validation and entrepreneurship courses. This knowledge can help develop effective entrepreneurship education programmes. The study also provides actionable insights for educational institutions and policymakers. It underscores the need for innovative educational platforms such as entrepreneurial bootcamps. It also highlights the value of advanced learning environments such as decision theatres to foster a culture of entrepreneurship and innovation.

The study contributes to the body of knowledge on entrepreneurship education. It highlights the need for a multidisciplinary approach to understand the factors that shape students’ entrepreneurial intentions.

This study aims to explore the holistic context of organisational staff retention in small, medium and large organisations. It also aims to identify the factors affecting the retention of organisations of different sizes.

The study implements an empirical test of a model created during previous research with the participation of 511 employees. The responses to the online questionnaire and the modelling were analysed using the partial least squares structural equation modelling method. The models were tested for internal consistency reliability, convergent and discriminant validity, multicollinearity and model fit.

Two models were tested by organisation size, which revealed a total of 62 significant correlations between the latent variables tested. Identical correlations were present in both models in 22 cases. After testing the hypotheses, critical variables (nature of work, normative commitment, benefits, co-workers and organisational commitment) were identified that determine employees’ organisational commitment and intention to leave, regardless of the size of the organisation.

As a result of this research, the models developed are suitable for identifying differences in organisational staffing levels, but there is as yet no empirical evidence on the use of the scales for homogeneous groups of employees.

The results show that employees’ normative commitment and organisational commitment are critical factors for retention. Of the satisfaction factors examined, the nature of work, benefits and co-workers have a significant impact on retention in organisations, so organisational retention measures should focus on improving satisfaction regarding these factors.

The readers of the journal would appreciate the work, which highlights the significance of employee psychology and retention for organisational success.

The study is based on primary data and, to the best of the authors’ knowledge, is one of the few studies that take a holistic approach to organisational staff retention in the context of the moderating effect of organisational size. This study contributes to a comprehensive understanding of the phenomenon of employee retention and in contrast to previous research, examines the combined effect of several factors.

This study aims to understand the learner behaviour of millennials for Massive Open Online Courses (MOOCs) in the post-adoption stage by extending the theory of Unified Theory of Acceptance and User Technology 2 (UTAUT2) with expectancy confirmation model (ECM) along with personal innovativeness as the exogenous, satisfaction as a mediating and continued intention as an endogenous construct.

This study applied a cross-sectional research design by using a survey method to collect primary data with a structured questionnaire. Convenience sampling was used to collect data from millennial MOOC users, and partial least square structural equation modelling method was applied for data analysis.

The results indicate that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation influence satisfaction. Similarly, performance expectancy, hedonic motivation, personal innovativeness and satisfaction influence the continued intention for MOOCs.

In terms of limitations, the study applied a cross-sectional research design that could lead to data collection bias. Similarly, the study used convenience sampling as the authors did not have access to the participant list of users from MOOC platforms.

The research highlights various insights to all the stakeholders on improving MOOC satisfaction and enhance the continued intention for millennial learners.

The findings of this research bridge this gap by examining the post-adoption usage behaviour of MOOCs by extending the baseline model of UTAUT2 with personal innovativeness and integrating it with ECM.

Based on the stimuli-organism-response model and relationship marketing theory, the effect of different dimensions of Servicescape (Ambience, Cleanliness, Functionality, Spatial Layout, Employee Service Quality) on Customer Satisfaction and Behavioral Intention in hospitals during the COVID-19 pandemic are considered.

The study takes a quantitative approach, applying structural equation model using partial least square structural equation modeling to test the hypotheses. A total of 360 responses were collected using questionnaires distributed to different individuals who visited private hospitals in the past two months in India.

Contradicting previous research, this study found that among servicescape dimensions, employee service quality had the maximum influence on customer satisfaction and cleanliness does not have any significant impact on customer satisfaction as hypothesized. Mediation results show that customer satisfaction has a partial mediation effect for all servicescape dimensions except ambience, as both direct and indirect effects are significant. Importance-performance map analysis was performed on the responses collected, and it was found that employee service quality is the most important dimension affecting servicescape, followed by functionality and spatial layout. Thus, health-care institutions should focus on these factors to keep their customers satisfied.

Past studies have focused on the roles of servicescape and customer satisfaction separately. The authors have extended the literature by examining the combined effects of both servicescape and customer satisfaction. The findings from the study, therefore, help in developing a deeper understanding of the literature on the behavior intention relationship in the context of health care, as well as in service marketing.

This paper aims to determine the effect of a set of factors (attitude toward entrepreneurship, perceived behavioral control or entrepreneurial self-efficacy, previous experience, internal locus of control and entrepreneurial alertness) on the entrepreneurial intentions of Chilean secondary vocational school students.

An online survey was sent to all secondary-level students from four Chilean vocational schools (3,052 students). A total of 1,644 valid questionnaires were received. The data were analyzed using partial least squares structural equation modeling (PLS-SEM).

The results show that attitude toward entrepreneurship and perceived behavioral control positively and significantly impact the students’ entrepreneurial intentions, but not the previous experience.

Since this research was carried out in a specific reality, the results may lack generalizability. Also, the proposed model requires further development through the incorporation of other factors. It is then suggested to replicate this study in other countries as well as to incorporate new variables and test new relationships.

Entrepreneurship education programs at the secondary level should emphasize changing/stimulating adolescents’ attitudes toward entrepreneurship as well as improving their confidence in their entrepreneurial abilities.

This is one of the few studies that provide empirical evidence about the determinants of entrepreneurial intentions in adolescents, particularly in Latin America, and with a large sample.

El propósito de este estudio es determinar el efecto de un conjunto de factores (actitud hacia el emprendimiento, control conductual percibido o autoeficacia emprendedora, experiencia previa, locus de control interno y alerta emprendedora) sobre las intenciones emprendedoras de estudiantes secundarios técnico-profesionales chilenos.

Una encuesta online fue enviada a todos los estudiantes de nivel secundario de cuatro escuelas técnico-profesionales chilenas (3,052 estudiantes). Se recibieron un total de 1,644 cuestionarios válidos. Los datos obtenidos fueron analizados a través de una técnica de modelización de ecuaciones estructurales (PLS-SEM).

Los resultados muestran que la actitud y el control conductual percibido impactan positiva y significativamente sobre las intenciones emprendedoras de los estudiantes, no así la experiencia previa.

Dado que esta investigación se llevó a cabo en una realidad específica, se debe ser cauteloso a la hora de generalizar sus resultados. Asimismo, el modelo propuesto requiere un mayor desarrollo a través de la incorporación de otras variables. Se sugiere entonces replicar este estudio en otros países, así como incorporar nuevas variables y someter a prueba nuevas relaciones.

Los programas de educación emprendedora en el nivel secundario debiesen poner énfasis en cambiar/estimular las actitudes hacia el emprendimiento de los adolescentes, así como en mejorar su confianza en sus propias habilidades emprendedoras.

Este es uno de los pocos estudios que aporta evidencia empírica acerca de los determinantes de las intenciones de emprender en adolescentes, particularmente en América Latina y con una muestra amplia.

Smart manufacturing (SM) lies at the core of Industry 4.0. Uniform adoption of SM across business partners is crucial to exploit its value creation potential. However, firms' willingness to invest in SM is limited by insufficient or inconclusive evidence on its performance-related benefits. To close this gap, this paper develops and tests a model linking SM adoption to firms' financial performance. Improvements along the four dimensions of operational performance (i.e. cost quality, delivery and flexibility) mediate this relation.

This study follows an empirical research approach. In particular, survey data from 234 automotive component suppliers are analyzed via covariance-based structural equation modeling to explore the link between SM adoption and operational performance. Survey data are then matched with secondary data from balance sheets of 81 firms to investigate the impact of SM on financial performance via partial least square structural equation modeling.

Findings highlight that adoption of SM results in improvements in cost, quality, delivery performance, thus suggesting that SM is a mean to overcome performance trade-offs. Improvements in operational performance enabled by SM do not give rise to superior financial performance, thus implying that SM might support firms in maintaining the competitive position in the market, but could be insufficient to generate higher margin.

Results have implications for SM research and for manufacturing executives engaged in the adoption of SM, as they provide a detailed analysis of the impact of SM on operational performance and clarify the effect that SM adoption has on financial performance.

This study aims to investigate religiosity and entrepreneurial motivation roles in the goal-specific, involving Muslim students’ entrepreneurial intention and self-efficacy. Besides, it examines the robustness model based on group context.

Partial least square structural equation modelling is employed to examine 502 data collected from Muslim students in Indonesia through an online survey. Meanwhile, partial least square multigroup analysis tests the robustness model.

Religiosity plays a powerful role in increasing goal-specificity. Meanwhile, entrepreneurial motivation and self-efficacy perform as full mediations in the pathway mechanism of religiosity's effect on entrepreneurial intention.

The current study is conducted based on the previous recommendations and contradictions. Therefore, it clarifies and develops a study on the role of religiosity and entrepreneurial motivation in the goal-specific motivation of Muslim students.

To increase the goal-specificity of entrepreneurship activities, policymakers in the ministry of education and universities must implement and revitalize Muslim students' understanding of the relationship between religiosity and entrepreneurship.

This study defines the role of religiosity in goal-specific, especially Muslim students’ entrepreneurial intentions, by gender, faculty/department and age. Furthermore, it completes the opportunity for research agendas on the relationship between religiosity, entrepreneurial motivation, self-efficacy and entrepreneurial intention.