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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 aim of this study is to examine the behavioral intention (BI) to adopt the Coinbase Wallet by Spanish users.

A survey was administered to individuals residing in Spain between March and April 2021. There were 301 questionnaires analyzed. This research applies a new predictive model based on technology acceptance model (TAM) 2, the unified theory of acceptance and use of technology (UTAUT) model, the theory of perceived risk and the commitment trust theory. A mixed partial least squares structural equation modeling (PLS-SEM)/fuzzy-set qualitative comparative analysis (fsQCA) methodology was employed for the modeling and data analysis.

The results showed that all the variables proposed have a direct and positive influence on the intention to use a Coinbase Wallet. The findings present clear directions for traders, investors and academics focused on improving their understanding of the characteristics of these markets.

First, this study addresses important concerns relating to the adoption of crypto-wallets during the global pandemic. Second, this research contributes to the existing literature by adding electronic word of mouth (e-WOM), trust, web quality and perceived risk as new drivers of the intention to use the Coinbase Wallet, providing unique and innovative insights. Finally, the study offers a solid methodological contribution by integrating linear (PLS) and nonlinear (fsQCA) techniques, showing that both methodologies provide a better understanding of the problem and a more detailed awareness of the patterns of antecedent factors.

In response to growing concerns over the negative consequences of Internet addiction on adolescents’ mental health, coupled with conflicting results in this literature stream, this meta-analysis sought to (1) examine the association between Internet addiction and depressive symptoms in adolescents, (2) examine the moderating role of Internet freedom across countries, and (3) examine the mediating role of excessive daytime sleepiness.

In total, 52 studies were analyzed using robust variance estimation and meta-analytic structural equation modeling.

There was a significant and moderate association between Internet addiction and depressive symptoms. Furthermore, Internet freedom did not explain heterogeneity in this literature stream before and after controlling for study quality and the percentage of female participants. In support of the displacement hypothesis, this study found that Internet addiction contributes to depressive symptoms through excessive daytime sleepiness (proportion mediated = 17.48%). As the evidence suggests, excessive daytime sleepiness displaces a host of activities beneficial for maintaining mental health. The results were subjected to a battery of robustness checks and the conclusions remain unchanged.

The results underscore the negative consequences of Internet addiction in adolescents. Addressing this issue would involve interventions that promote sleep hygiene and greater offline engagement with peers to alleviate depressive symptoms.

This study utilizes robust meta-analytic techniques to provide the most comprehensive examination of the association between Internet addiction and depressive symptoms in adolescents. The implications intersect with the shared interests of social scientists, health practitioners, and policy makers.

The purpose of this paper is to investigate how different manufacturing technologies are bundled together and how these bundles influence operations performance and, indirectly, business performance. With the emergence of Industry 4.0 (I4.0) technologies, manufacturing companies can use a wide variety of advanced manufacturing technologies (AMT) to build an efficient and effective production system. Nevertheless, the literature offers little guidance on how these technologies, including novel I4.0 technologies, should be combined in practice and how these combinations might have a different impact on performance.

Using a survey study of 165 manufacturing plants from 11 different countries, we use factor analysis to empirically derive three distinct manufacturing technology bundles and structural equation modeling to quantify their relationship with operations and business performance.

Our findings support an evolutionary rather than a revolutionary perspective. I4.0 technologies build on traditional manufacturing technologies and do not constitute a separate direction that would point towards a fundamental digital transformation of companies within our sample. Performance effects are rather weak: out of the three technology bundles identified, only “automation and robotization” have a positive influence on cost efficiency, while “base technologies” and “data-enabled technologies” do not offer a competitive advantage, neither in terms of cost nor in terms of differentiation. Furthermore, while the business performance impact is positive, it is quite weak, suggesting that financial returns on technology investments might require longer time periods.

Relying on a complementarity approach, our research offers a novel perspective on technology implementation in the I4.0 era by investigating novel and traditional manufacturing technologies together.

This paper aims to propose and test a corporate entrepreneurship strategy (CES) model in small- and medium-sized enterprises (SMEs) with international activity located in Andalusia (Spain) – a peripheral region with high levels of inequality in the European Union (EU).

A quantitative analysis has been carried out with data from 101 SMEs to contrast and analyze the proposed CES model. The sample data were obtained through questionnaire-guided interviews with chief executive officers. Data processing has been done using partial least squares-path modeling, a variance-based technique for structural equation modeling.

The results of this study show the positive effect of environmental conditions on the development of CES actions in Andalusian SMEs (Spain) and the positive influence of CES on the results of SMEs’ international activity. In turn, environmental conditions do not directly affect the international activity.

Although previous works address the relationship between corporate entrepreneurship (CE) and international enterprise activity, to the best of the authors’ knowledge, this work is original in testing a CES model (including CE and the entrepreneurial strategic vision) in SMEs in a region that has one of the lowest levels of development in the EU. The results have important implications for SMEs and policymakers and could be extrapolated to other emerging economies.

The primary objective of this investigation was to explore how employees’ utilization of social media for work-related purposes impacts their service innovation behavior, both directly and through the intermediary mechanisms of knowledge management and employees’ risk-taking.

In developing its conceptual framework, this study has drawn upon the stimulus-organism-response (SOR) theory. To test its hypotheses, this study has surveyed 241 financial analysts from ten Iranian financial companies and has employed variance-based structural equation modeling (specifically, PLS-SEM) with the assistance of “WarpPLS 8.0 software.”

The findings revealed that employees’ work-related use of social media positively influences their service innovation behavior using knowledge management, encompassing knowledge sharing and acquisition capability as well as employee risk-taking. However, this influence is not directly significant.

To the best of our knowledge, this study marks the first instance in which the effect of work-related use of social media on employee service innovation behavior directly and through the mediating roles of knowledge management and risk-taking has been investigated through the lens of the SOR paradigm, especially in the financial sector.

The objective of this paper is to examine the profound repercussions of workplace bullying (WB), emotional exhaustion (EE), and psychological distress (PD) on poor job performance (PJP) within the intricacies of Thailand’s healthcare sector. It also seeks to elucidate the moderating influence of COVID-19 burnout (CBO) on these variables.

This paper utilized a quantitative research approach. A total of 230 responses were collected from healthcare workers using convenience sampling during a significant surge of the coronavirus in March 2022. To assess the reliability and correlations between constructs, a dual-stage structural equation modeling (SEM) technique was applied.

During the global health crisis caused by COVID-19, WB and PD were found to positively predict PJP, except for EE. The presence of WB elevated EE and PD among Thai hospital staff. PD and EE partially mediated the relationship between WB and PJP. The positive moderating role of CBO among hospital employees significantly buffered the relationship between WB and EE.

The originality of this study lies in the examination of the poor mental health of Thai healthcare workers during the COVID-19 pandemic. Healthcare reforms are required to protect the mental health of Thai healthcare staff to prevent poor job performance following unprecedented circumstances.

User acceptance is a necessary precondition to implementing self-driving buses as a solution to public transport challenges. Focusing on potential users in a real-life setting, this paper aims to analyze the factors that affect their willingness to use public autonomous shuttles (PASs) as well as their word-of-mouth (WOM) intentions.

Grounded on Unified Theory of Acceptance and Use of Technology (UTAUT2), the study was carried out on a sample of 318 potential users in a real-life setting. The hypothesized relationships were tested using partial least squares structural equation modeling (PLS-SEM).

The study reveals that performance expectancy, facilitating conditions, hedonic motivation and trust are significant predictors of PAS usage intention, which is, in turn, related to WOM communication. Additionally, the factors that impact the intention to use a PAS are found to exert an indirect effect on WOM, mediated by usage intention.

This study includes practical insights for transport decision-makers on PAS service design, marketing campaigns and WOM monitoring.

While extant research focuses on passengers who have tried autonomous shuttles in experimental settings, this article adopts the perspective of potential users who have no previous experience with these vehicles and identifies the link between usage intention and WOM communication in a real-life traffic environment.

若要引入自動駕駛巴士來解決公共交通的問題和挑戰,一個必不可少的先決條件是得到用戶的認可。本研究透過重點分析活在真實生活環境中的潛在用戶,來探討影響他們使用公共自動交通工具的意願和口碑動機的各個因素。

本研究以延伸整合型科技接受模式為基礎,對一個涵蓋處身於真實生活環境中318名潛在用戶的樣本進行分析和探討。研究人員以偏最小平方法的結構方程模型 (PLS-SEM), 去測試各個被假設的關聯。

研究結果顯示,績效期望、有利條件、享樂動機和信任均明顯能夠預測人們使用公共自動交通工具的意願,而人們使用公共自動交通工具的意願又反過來與口碑溝通有所相關。另外,研究人員發現,影響人們使用公共自動交通工具意願的各個因素,對口碑會產生間接的影響,而使用意願是會起著調節作用的。

現存的學術研究均聚焦分析那些曾於實驗設置下坐過自動交通工具的人士,而本研究卻採用從未坐過自動交通工具人士的角度來進行分析與探討,並且找出了於實際的交通環境裡、使用意願與口碑溝通之間的關聯。

本研究提供的啟示,對有關公共自動交通工具服務設計、市場營銷活動和口碑監督工作的運輸決策者來說頗具實務意義。

Considering the significant increase in researchers’ interest in human resource management (HRM) in the public sector domain, this study aims to focus on producing a scale of HRM practices customized for the context of public organizations.

Experts and semantic analysis were performed for the scale development (qualitative stage), and exploratory and confirmatory factor analysis through structural equation modeling was conducted for the scale validation (quantitative stage).

The public HRM practices scale (public HRMPS) is composed of 19 items, distributed along four factors/dimensions, named training, development and education; relationship; work conditions; and competency and performance appraisal. The scale showed evidence of internal and construct validity (convergent, divergent, criterion-related and discriminant), as well as reliability and content validity.

The public HRMPS can be applied in relational studies to test structural models of prediction, mediation and moderation to evaluate relationships with organizational behavior variables, such as leader-members exchange, engagement at work, life quality at work and well-being at work, among others.

The public HRMPS may also serve as a useful diagnostic tool for the decision-making process made by public managers so they can promote a strategic, evidence-based HRM. Furthermore, the transforming role of strategic HRM can be operationalized by adopting practices gathered in the public HRMPS, advancing toward new HRM strategies to promote healthier and more productive work environments.

Healthier and more productive environments translate into real impacts for society, the first beneficiary of public services with more quality, efficiency and accountability.

The public HRMPS is the first attempt to produce an operationally valid and reliable measure to evaluate strategic HRM practices, responding to calls in the literature concerning the need for an integrated, comprehensive and customized HRM practices scale for the public service context.