Search results

This paper aims to determine the impact of perceived virtuality on team dynamics and outcomes by adopting the Input-Mediators-Outcome (IMO) framework. Further, it also investigates the mediating role of team processes and emergent states.

The authors collected survey data from 315 individuals working in virtual teams (VTs) in the information technology sector in India using both offline and online questionnaires. They performed the analysis using Partial Least Squares Structural Equation Modelling (PLS-SEM).

The authors investigated two sets of hypotheses – both direct and indirect (or mediation interactions). Results show that psychological empowerment and conflict management are significant in managing VTs. Also, perceived virtuality impacts team outcomes, i.e. perceived team performance, team satisfaction and subjective well-being.

The interplay between the behavioural team process (conflict management) and the emergent state (psychological empowerment) was examined. The study also helps broaden our understanding of the various psychological variables associated with teamwork in the context of VTs.

Findings from this study will aid in assessing the consequences of virtual teamwork at both individual and organisational levels, such as guiding the design and sustainability of VT arrangements, achieving higher productivity in VTs, and designing effective and interactive solutions in the virtual space.

The study examined the interplay between behavioural team processes (such as conflict management) and emergent states (such as psychological empowerment). The study also theorises and empirically tests the relationships between perceived virtuality and team outcomes (i.e. both affective and effectiveness). It may serve as a guide to understanding team dynamics in VTs better.

This exploratory study attempts to enhance the current understanding of the research and practice of VTs within a developing economy.

This paper aims to investigate the effect of supplier relationship management (SRM) on the business performance of small-scale grapes processing firms in Dodoma, Tanzania. The paper also examines the moderating role of logistics capabilities in the relationship between SRM and business performance.

This research uses a cross-sectional survey design. A structured questionnaire was used to collect data from 202 small-scale grape processing firms. The data were analysed through descriptive and structural equation modelling.

The findings revealed that buyer-supplier relationships, supplier development and supplier selection were positively and significantly related to business performance. Furthermore, knowledge transfer had no relationship with business performance. On the other hand, the findings showed that logistics capabilities significantly moderated the relationship between SRM and business performance.

The study was cross-sectional, conducted only in Tanzania, and focussed entirely on small-scale firms processing grapes as raw materials. Thus, generalising the study findings to other countries with different conditions should be done cautiously. Also, this study used subjective measures, and other studies could use objective measures.

The study helps firm managers understand the importance of supplier relationship management on business performance. The findings also can be used by policymakers to create targeted policies and initiatives that support the firm’s growth and sustainability.

To the best of the researchers’ knowledge, this is the first attempt to find empirical support for the moderating role of logistics capability in supplier relationship management and the business performance of small-scale grapes processing firms in the Tanzanian context.

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.

Subjective career success has been widely researched by academics and researchers as it provides job and career satisfaction that can lead to the perceived life satisfaction of employees, as well as their engagement in organizations. This study demonstrates that subjective career success depends not merely on career adaptability but also on the connections people build throughout their professional lives.

The study was conducted in the socioeconomic context of Latvia with a sample size of 390 respondents. Interpersonal behavioral factors from the perception of career success measure and the influence of the Career Adapt-Abilities Scale (CAAS) on subjective career success (two statements from Gaile et al., 2020) were used. The constructed research model was tested using the SPSS 28 and WarpPLS 8.0 software tools. The primary data analysis method used was partial least squares structural equation modeling (PLS-SEM). Then 12 moderators and their effects on the main relationships of the model were reviewed.

The study confirms that relationships at work have the most significant effect on subjective career success, followed by control behaviors and curiosity behaviors. Moreover, a list of significant and insightful moderation effects was found, most significantly the relationship between connections and subjective career success.

Until now, the CAAS was not integrated with the behaviors and attitudes that depict the social relationships of individuals at work. This study aims to narrow this gap by exploring whether (and, if so, how) career adaptability and interpersonal relationships in the workplace (i.e. professional connections) contribute to subjective career success.

學者和研究人員一直對主觀的事業成功課題進行廣泛的討論和研究, 這類研究會給予僱員工作和事業的滿足感, 繼而使他們感到生活圓滿, 並促進他們對組織的參與。本研究展示了主觀的事業成功不但取決於生涯調適力, 同時也取決於僱員在整個職業生涯裡人際聯繫的建立。

研究人員在拉脫維亞的社會經濟背景下進行這個研究; 樣本為390名回應者。研究人員使用了衡量事業成功概念內的人際行為因素, 以及職業適應能力量表對主觀事業成功的影響 (來自 (Gaile 等, 2020) 的兩個聲明) 。研究人員採用 SPSS 28和 WarpPLS 8.0兩個軟件工具, 來測試他們構建的研究模型。主要分析數據的方法為基於偏最小平方法的結構方程模型, 研究人員仔細審核12個調節因素和它們對模型的主要關聯的影響。

研究確認了工作方面的關係對主觀的事業成功影響最為顯著, 其次則為控制行為和好奇行為; 而且, 研究人員發現了一系列重要的、富有洞察力的調節效果; 更具意義的是, 他們發現了建立聯繫與主觀事業成功之間的關係。

職業適應能力量表至今仍未融合於可描繪在工作上各個個體的社會關係的行為和態度。本研究探索了職業適應能力和在工作場所的人際關係, 如何能促進主觀的事業成功; 就此而言, 本研究縮窄了有關的研究缺口。

This study examined the psychometric properties of intention to drop out and study satisfaction measures for first-year South African students. The factorial validity, item bias, measurement invariance and reliability were tested.

A cross-sectional design was used. For the study on intention to drop out, 1,820 first-year students participated, whilst 780 first-year students participated in the study on satisfaction with studies. Confirmatory factor analysis (CFA), differential item functioning (DIF), measurement invariance and internal consistency were used to test the scales.

A one-factor structure was confirmed for both scales. For the intention to drop out scale, Items 3 and 4 were identified with statistically significant item bias; however, these differences had no practical impact. Except for scalar invariance for language, sufficient measurement invariance was established. No problematic items were identified for the study satisfaction scale.

In essence, this study provides evidence of two short measures that are culturally sensitive that could be used as short and valid measures across contextual boundaries as practically valuable tools to measure intention to drop out and study satisfaction in diverse and multicultural contexts.

This study contributes to limited research on bias and invariance analyses for scales that can be used in interventions to identify students at risk of leaving the university and utilising psychometric analyses to ensure the applicability of these two scales in diverse and multicultural settings.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

The article aims to present the results of adapting the team boosting behaviors (TBB) scale to Polish cultural conditions and validating it.

The research methodology consisted of three steps. In the first step, I translated the TBB scale into Polish using a rigorous back-translation method. Next, to assess content validity, nine domain experts reviewed the initial version of the instrument for clarity and relevance. Finally, I applied the scale to a sample of 532 team members and underwent thorough psychometric testing to assess construct validity. I employed structural equation modeling (SEM) with the partial least squares (PLS) factor-based algorithm technique for confirmatory factor analysis to assess the scale’s reliability and validity.

After development, the Polish version of the TBB scale kept its three sub-scale structures. However, the validation process led to a slight reduction in the number of test items compared to the original scale.

The findings imply that the Polish version of the scale is a valid and reliable tool for assessing TBB. However, I recommend additional studies to confirm this instrument’s structure.

The results confirmed the reliability and relevance of the tool for measuring TBBs in Polish cultural conditions. The tool provides the basis for implementing further research with the TBB construct in Poland and internationally.

The European Union (EU) Medical Device Regulations (MDR) 2017/745 entered into force on May 2021 with changes related to strengthening the clinical evaluation requirements, particularly for high-risk devices. This study aims to investigate the impact of these strengthened requirements on medical device manufacturers by investigating the challenges they encounter while generating an MDR-compliant clinical evaluation report.

A systematic literature review was carried out using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses method of peer-reviewed literature and various government jurisdictional reports and legislation.

The findings from the study understanding what constitutes sufficient clinical evidence poses the biggest challenge to the generation of an MDR-compliant clinical evaluation report. Resulting from the challenges they are facing, manufacturers of certain CE-marked medical devices are planning to remove (and have removed) devices from the EU market upon expiration of their certificate, and in the case of new and innovative devices, some manufacturers are planning to launch in other markets ahead of the EU. These challenges will lead to a potential shortage of certain medical devices in the EU and a delay in access to new devices, thereby negatively impacting patients’ quality of life.

This study provides a unique insight into the challenges currently experienced by medical device manufacturers as they transition to the MDR clinical evaluation requirements and the subsequent impact on the continued availability of medical devices in the EU. A limitation is the lack of literature analysing the regulations and their effects.

This study has both theoretical contributions in that, to the best of the authors’ knowledge, it is the first detailed and systematic review of the new MDR Regulations and has implications for practice as manufacturers and policymakers can leverage it alike to understand the challenges of the new MDR.

Drawing on the conservation of resources (COR) theory, this study aims to assess the moderating effect of the psychological contract (PC) type (relational, transactional and balanced) on the relationship between psychological contract breach (PCB) and organizational citizenship behaviours (OCBs).

The authors administered a survey to a sample of 159 nurses working in a large public hospital. To analyse the survey data, the authors used partial least squares with SmartPLS v.3.3, a variance-based structural equation modelling technique that combines principal component analysis, path analysis and regression analysis.

This study shows that nurses counteract the loss of resources following a PCB by investing more in stronger interpersonal relationships with co-workers and patients as a way to recuperate from resource loss and gain social resources. In addition, the moderating effect of the PC type reinforces the relationship between a PCB and OCB in a way that relational and balanced PC types support OCB-I positively but negatively OCB-O. Furthermore, the transactional PC does not reinforce negatively the link between PCB and OCB-I, and the negative interacting effect on the PCB and OCB-O link is only partially supported.

The study findings are grounded on a cross-sectional research design and a convenience sampling strategy.

The results highlight the relevance of human resources management practices centred on employee involvement and participatory supervision styles for ensuring OCB display at the workplace.

The results add new evidence to COR theory by highlighting the importance of social resources as a mitigator in the relationship between nurses’ PCB and OCB towards co-workers and patients (OCB-I). Hence, the OCB-I display will vary in function of the target and the moderating effect of PC type (relational, balanced or transactional).

This paper intends to verify the extent to which Clean Development Mechanism (CDM) projects intend to contribute to sustainable development (SD) in Brazil, one of the top three leading countries in terms of the number of CDM projects. The authors assess the impact of CDMs not only in environmental aspects, but also social and economic ones.

The authors define a set of qualitative sustainability indicators and scrutinize documents regarding a sample of almost half of all the projects registered in Brazil between 2004 and 2020 (219 projects).

The findings of this study contradict many previous studies finding very limited evidence of SD in CDMs in many different countries: most projects in Brazil intend to contribute to some extent with SD, with 91% and 75% claiming to improve social and economic aspects, respectively.

The authors derive lessons from Brazil that can be used in other researches.

The authors derive lessons from Brazil and propose paths for public policy toward encouraging sustainable development.

The empirical data set relies on data collected directly from each of the projects in Brazil (roughly half of all of them) between 2004 and 2020. This is not only up to date, but pushes further the analytical scope of previous works.