Drawing on conservation of resources theory, this study examines how flexible human resource management affects employee deviant innovation. Survey data were collected from 282 employees working in information technology, machinery manufacturing, and biopharmaceutical firms in Shanghai, Hefei, and Zhejiang Province. Both dimensions of flexible human resource management, coordination flexibility and resource flexibility, were positively related to employee deviant innovation. Psychological resilience mediated both relationships. The supervisor-subordinate relationship moderated the link between psychological resilience and deviant innovation: the stronger the relationship, the weaker the positive effect of resilience on deviant innovation. These findings clarify how flexible human resource management shapes deviant innovation, identify the psychological mechanism through which it operates, and specify the relational condition under which that mechanism is strongest.

The survey assessed the strategies that could effectively improve the application of the participative leadership model in CSR infrastructure delivery in the Niger Delta with a quantitative research design approach. Through multi-stage sampling, a total of 125 participants comprising CSR officers, project managers, site supervisors and community liaison representatives, invited from the core Niger Delta states, Akwa Ibom and Bayelsa, responded to structured, cross-sectional questionnaires as a survey instrument. Data were descriptively analysed using frequency and percentage, while inferential statistics used the Kruskal-Wallis H test. The survey findings indicate 'Relevant training on adoption and implementation of a participative approach', 'Establishment of an organised community project office and non-permanent advisory committees', and 'Allocation of resources for participative engagement and commitment' as key strategies to enhancing the effective application of a participative approach to CSR infrastructure delivery. These strategic variables for fulfilling corporate responsibility are also a panacea for the effective application of the participative model. The study concludes that entrenching these variables would curb the current fragmented application of the model. Additionally, it would strengthen participative engagement and move CSR delivery from mere passive consultation to active partnership for sustainable regional progress and stability, fostering mutual trust and improving corporate-community relationships.

There are many studies made to explain the relationship between the organizational factors. Burden of them, tried to mathematically model this relationship using traditional methods like PLS (Partial Least Squares), SEM (Structural Equation Modeling), RA (Regression Analysis) or Co-relation analysis. Besides, the limited explanatory variables were recently applied in such studies. Additionally, there are very rare quantitative investigations discovering the structural cause and effect interconnections among the huge number of organizational factors. This research has been designed to first distinguish the cause and effect group among the 20 organizational factors and second to weight these factors as well. DEMATEL and SWARA methodologies are the main multi criteria tools used in the present study. Results show the top 4 factors of EBLPOC(Employees' Basic Level of Perception Regarding Organizational Complexities), OCB(Organizational Citizenship Behavior), BC(Business Climate) and EJP(Employee Job Performance) hold relatively the utmost weights (closely 0.826 together). EBLPOC, EJP and BC are the cause factors. OCB is recognized as the effect factor. Furthermore, it is worthy to mention that the factor of EBLPOC (as a qualitative variable which were usually missed or ignored in previous studies), is totally ranked at first position. Finally, present study is inherently readdressing the organization's leaders, chief executives, intermediate managers and policy makers to focus on some classical foremost factors like OCB, BC and EJP (the old wounds) again.

The study aims to analyze trends in the number of leading Angolan insurance companies for benchmarking purposes in the sector between 2020 and 2023, using the DEA-VRS window model. The analysis was conducted by calculating the efficiency scores of each insurer in two-year-wide moving windows, followed by a comparison of efficiency distributions over time and the identification of the insurers that served as benchmarks in each window for benchmarking purposes. The analysis was conducted by calculating the efficiency scores of each insurer in two-year movable windows, followed by a comparison of efficiency distributions over time and the identification of the insurers that served as benchmarks in each window for benchmarking purposes. The results reveal a trend of increasing average efficiency scores and a concomitant reduction in the number of insurers identified as benchmarks, a pattern that was consistently evident across the three analysis windows. In practical terms, the findings also indicate that the universe of benchmarks is becoming more concentrated, which requires attention to the periodic updating of the analysis windows and the selection of variables to ensure that benchmarking continues to reflect efficient practices within the analyzed sample. The article stands out for exploring a little-studied market, using robust primary data, offering practical value by identifying benchmark insurers, and revealing an unexpected inverse relationship between average efficiency and the number of benchmarks DMUs.

Despite 72 percent of organizations adopting artificial intelligence, nearly half of implementations fail due to employee resistance, a paradox that challenges technology acceptance models. Prior research has examined either cognitive acceptance or motivational responses in isolation, leaving the interplay between these pathways and their ethical contingencies unresolved. This research addresses this critical gap through a sequential explanatory mixed-method design combining a quantitative survey of 1,785 employees in AI-adopting organizations with in-depth qualitative interviews with 19 participants, analysed using SmartPLS 4 for structural equation modelling and NVivo 14 for thematic analysis. The findings reveal three key insights. First, psychological empowerment mediates the relationship between technology characteristics and job satisfaction more strongly than technology acceptance, a counterintuitive finding that challenges the technology acceptance model's 30-year dominance. Second, job satisfaction emerges as the strongest predictor of organizational performance. Third, ethical leadership moderates both pathways, such that high ethical leadership amplifies empowerment effects by 34 percent. This research advances a novel Ethical Dual-Pathway Technology Acceptance Model (EDP-TAM), offering actionable guidance for organizations to implement AI that simultaneously optimises performance and safeguards employee well-being.

This study synthesizes what is known about time-to-impact in quality improvement (QI) and transformation initiatives and, drawing on a large body of High Performance Organization (HPO) transformation cases, identifies which factors delay or accelerate impact and which organizational practices shorten benefit lead-times. It combines a structured synthesis of academic studies addressing impact, time-to-impact, timing evidence, and associated factors/practices with a case-survey of 54 documented HPO transformation cases that were systematically coded using a common framework. Factors and practices are prioritized based on their recurrence across cases, after which the resulting empirical patterns are mapped back to literature-based categories to assess convergence and divergence. Across the HPO cases, the most recurrent sources of delay are weak change communication and dialogue, weak follow-up and accountability, inconsistent leadership attention, and limited transparency in performance measurement and reporting. The most recurrent accelerators are strong communication and knowledge sharing, a tight review cadence with closed feedback loops, transparent measurement and reporting, and cross-unit collaboration. The most frequently reported time-to-impact reduction practices include institutionalizing a recurring communication-and-review cadence, increasing measurement transparency, clarifying leadership roles and accountabilities, and creating structured dialogue channels supported by internal coaches or champions. Overall, the findings overlap substantially with the literature, but differ in emphasis, and the study positions time-to-impact as a distinct dimension of improvement effectiveness while offering an evidence-informed, prioritized set of practical levers grounded in both research and cross-case practice.

This study investigates how effectively European Union Member States transform circular economy (CE) practices into social well-being, addressing a critical but underexplored dimension of circular transition research. While existing CE assessments primarily emphasize material flows, recycling performance, and resource productivity, far less is known about how circularity contributes to consumer-relevant and inclusive social outcomes. Using an output-oriented Data Envelopment Analysis (DEA) framework under variable returns to scale, the study evaluates the social efficiency of CE across 27 EU countries, drawing on indicators of circular material use, material intensity, international recycling flows, self-perceived health, social inclusion, and real income. The results reveal substantial heterogeneity in social efficiency, showing that higher levels of circular activity do not automatically translate into stronger well-being outcomes for consumers. Countries such as Denmark, Finland, Estonia, Ireland, Luxembourg, and Spain achieve full efficiency, indicating effective alignment between circularity practices, welfare structures, and socially inclusive outcomes. Conversely, several countries operate under decreasing returns to scale, suggesting that CE initiatives may dilute social effects and generate uneven distributional outcomes when implemented beyond their optimal capacity. Overall, the findings highlight the importance of policy coherence, institutional capability, and consumer-oriented governance in ensuring that circular economy strategies deliver inclusive and socially sustainable benefits.

This paper explores the association between supplier management orientation (SMO), information integration (II), organizational culture (OC) and supplier delivery performance (SDP). A systematic questionnaire survey was employed to gather cross-sectional data from 403 manufacturing firms in Uganda's Greater Kampala Metropolitan Area were analyzed using SmartPLS 4. The study shows a full mediating role of OC in the relationship between SMO, II and SDP. A positively significant relationship was established between II and OC, and between OC and SDP. Also, the relationship between SMO and OC was positively significant. Whereas the effect of SMO, II, OC on SDP is significant, related literature remains limited. This signifies a deficiency in the current literature that necessitates additional research to investigate other external factors that substantially impact SDP. Managers need to nurture cultural qualities, like teamwork, openness, and responsiveness, that enhance employees to effectively interpret information and act in a coordinated manner. This study extends the Resource-Based View Theory to the SDP domain, by drawing insights on the mediating role of OC in the relationship between SMO and SDP.

Sugarcane must be harvested at the time of maturity, known as the Period of Industrial Utilization (PIU). The PIU analysis is expensive and is performed in a laboratory by measuring an index defined as Total Recoverable Sugar (TRS). The fact is that harvesting is the most expensive stage in sugarcane production and decision-making in this segment depends on TRS level estimates. However, forecasting models aimed at replacing laboratory analyses do not meet the reality regarding the estimation of the TRS index. There is a great demand for tools capable of estimating the index and/or the factors that affect TRS. In this context, this article presents a case study whose objective is to apply statistical models to estimate the TRS index in the sugarcane production of a mill in the interior of São Paulo, Brazil. Variance Analysis (ANOVA) with one classification and Multiple Linear Regression (MLR) models are applied by using Minitab®. These models are based on covariates related to the TRS index to estimate the productivity of 48,151 plots from the 2016/2017 to the 2022/2023 harvests. It is shown that the adjusted models identify the most important covariates (5% significance level) that affect productivity and the TRS index. The accuracy is satisfactory for all covariates of the adjusted MLR model and for the coefficients that measure the proportion of data variability for productivity (76%) and the TRS index (55%). This article brings important contributions to the sugar and ethanol industries worldwide and in Brazil.

This study investigates the dynamics of relative technical efficiency across Angolan universities from 2017 to 2022, aiming to establish operational benchmarks and support strategic decision-making in higher education. Data were collected from eighteen officially recognized public and private institutions using annual statistical reports published by MESCTI. The methodology relies on non-parametric intertemporal models, specifically DEA-VRS and Window DEA, which capture performance variations across consecutive time windows. Results include efficiency scores per institution and time frame, input and output slacks required to achieve technical efficiency, and identification of reference peers for benchmarking purposes. Findings reveal a consistently declining trend in average efficiency over the period, with UCC being the most frequently referenced unit. Critical variables such as enrollment and course offerings underscore the need for diversification and alignment with labor market demands. Estimated slacks offer actionable insights for policy and cost optimization. As a methodological extension, the study proposes investigating the relationship between variable-level inefficiencies (SBM) and global efficiency scores (CRS) to better understand interwindow performance trajectories.