The growing complexity and uncertainty of sustainable supply chain environments demand advanced digital capabilities that sustain competitiveness through effective decision-making. This study investigates how Generative AI (GenAI)-enabled digital dexterity strengthens decision-making performance and, in turn, contributes to organizational future performance. Integrating dynamic capabilities theory with institutional theory, we develop and test a model in which decision-making quality and decision-making efficiency represent distinct dimensions of decision-making performance, while ethical identity and regulatory governance effectiveness shape the strength of relationships. Survey data were collected from 296 Chinese firms across multiple industries and analysed using partial least squares structural equation modeling. The results show that GenAI-enabled digital dexterity significantly enhances both decision-making quality and decision-making efficiency, and that both dimensions are positively associated with organizational future performance. Ethical identity further amplifies the positive effects of GenAI-enabled digital dexterity on decision-making outcomes, highlighting the importance of normative commitments for responsible and credible use of GenAI. Regulatory governance effectiveness exhibits asymmetric boundary effects, dampening the performance value of decision-making quality while strengthening the contribution of decision-making efficiency to future performance. This study advances research on digital transformation and sustainable operations by clarifying the distinctive role of GenAI-enabled digital dexterity, identifying decision-making performance as a central mechanism, and explaining how institutional governance conditions shape value realization. It also offers practical guidance on how firms can build and govern GenAI-enabled capabilities to support future-oriented performance in sustainability-focused supply chains. • Shows how GenAI-enabled digital dexterity improves decision-making in supply chains. • Identifies ethical identity as a normative amplifier of GenAI decision benefits. • Reveals regulatory governance as a boundary condition shaping GenAI decision outcomes. • Conceptualises and validates GenAI-enabled digital dexterity as an organizational capability. • Offers managers guidance on extracting value from GenAI in complex environments.

Digital orientation and the hybrid tipping point: Balancing in-person and remote work

Digital transformation is widely viewed as a driver of organizational performance, yet limited evidence explains how its specific dimensions translate into performance outcomes in developing-country contexts. This study examines the effects of digital applications, process automation, digital infrastructure, human resources, and the institutional environment on organizational performance, with a particular focus on the mediating role of administrative creativity. Data were collected from supervisory and managerial employees in seven commercial banks in Sana'a, Yemen, and analyzed using Partial Least Squares Structural Equation Modeling. The findings reveal that digital applications and human resources have significant direct effects on organizational performance, whereas process automation, digital infrastructure, and the institutional environment do not. However, digital applications, digital infrastructure, human resources, and the institutional environment significantly enhance administrative creativity, which in turn exerts a strong positive effect on organizational performance. Mediation analysis shows that administrative creativity selectively mediates the effects of digital infrastructure, human resources, and the institutional environment on performance. These results demonstrate that digital transformation in banking organizations yields performance benefits primarily when digital initiatives are converted into outcomes through creative administrative behavior. By identifying administrative creativity as a key human-centered conversion mechanism, this study advances digital transformation theory and provides evidence from a developing-economy banking context on how digital investments generate sustainable organizational performance.

Laying the ground for product environmental footprint category rules of hydrogen devices through product categorisation

Purpose: Despite the two recent trends in the business world—environmental sustainability and technological advancement, there is a paucity of research that melds the two latest developments. Thus, this study empirically tests the association between GHRM practices and sustainable employee performance with the underlying intervening role of chatbot usability. Considering the contextual nature of technology acceptance, the paper also examines how technostress moderates the association among chatbot usability and sustainable employee performance. Design/methodology/approach: Employees in Pakistan's manufacturing and service sectors were surveyed using a survey questionnaire. The proposed framework was tested using Partial Least Squares Structural Equation Modelling on a sample of 453 respondents chosen purposively from businesses pursuing green agenda. Findings: The statistical analysis confirmed the positive effect of GHRM practices on sustainable employee performance. Furthermore, chatbot usability was confirmed to have a mediating effect on the relationship. Importantly, technostress also moderates the link of chatbot usability and sustainable employee performance such that the relationship is weakened in the presence of chatbot usability. Originality/value: The results of this research make significant theoretical advances and provide a more thorough knowledge of employee outcomes, specifically in the context of workplace technology. It also confirms that the influence of GHRM extends beyond green outcomes. Consequently, the current research fosters the advancement of GHRM research while also realizing an interdisciplinary debate in the fields of HRM and Artificial intelligence technology. Furthermore, the current study’s findings have significant practical ramifications for businesses and decision makers attempting to adopt GHRM practices and technology in the workplace.

Nudging towards sustainability: A systematic review of digital strategies for achieving ESG goals in corporate real estate

Nanoscale organization, thermal properties, and encapsulation performance of star-shaped poly(l-Lactide): Effect of glycerol- and diglycerol-based core geometry

• Culturally Adaptive Framework: Proposes a "Culturally Adaptive AI" framework to harmonize algorithmic efficiency with social norms in high-power-distance cultures. • Sustainability Mediation: Demonstrates that AI adoption positively mediates the relationship between Green HRM (GHRM) practices and organizational sustainability performance. • The "Kreng Jai" Paradox: Identifies unique cultural moderators, specifically Kreng Jai (deferential consideration) and "face-saving," that necessitate a "human-in-the-loop" approach to AI. • TOE Predictors: Reveals that Technological Readiness and Organizational Support are the primary drivers of AI integration for sustainable futures. • Institutional Theory Contrast: Uncovers a paradox where Environmental Pressure shows a significantly weaker effect on AI adoption than predicted by Western-centric models. • Mixed-Methods Rigor: Utilizes a sequential explanatory design combining PLS-SEM analysis of 420 professionals with in-depth qualitative insights from 25 experts. The integration of Artificial Intelligence (AI) into sustainable operations frequently encounters algorithmic friction due to localized socio-cultural constraints, which Western-centric models often fail to address. This study proposes a novel constraint-aware algorithmic architecture for "Culturally Adaptive AI" that utilizes a structured Human-in-the-Loop (HITL) approach. The proposed system architecture consists of four distinct layers: a Data Integration Layer, an AI Decision Engine Layer, a Cultural Adaptation Middleware, and a User Interface Layer. To empirically validate the system's efficacy in driving sustainable performance, a sequential explanatory mixed-methods design was employed, combining a quantitative evaluation of 420 professionals with qualitative insights from 25 expert interviews. Structural equation modeling (PLS-SEM) confirms that technological readiness and organizational support significantly drive system adoption, effectively mediating the optimization of sustainable operations. Furthermore, qualitative findings reveal that specific cultural variables, such as "Kreng Jai" (deferential consideration) and high power distance, necessitate parameterizing the Cultural Adaptation Middleware to temper the speed of autonomous deployment. By harmonizing algorithmic efficiency with social norms, this engineering framework provides a robust, scalable blueprint for implementing HITL AI systems in emerging economies to achieve Sustainable Development Goals (SDGs).

Are mature firms more sustainable? An analysis of industry 4.0 maturity

The COVID-19 pandemic accelerated the adoption of work-from-home (WFH) practices, raising important questions about their long-term implications for organisational performance. This issue is particularly salient for multinational enterprises (MNEs) and international small and medium-sized enterprises (SMEs), where digitalisation has significantly reshaped work arrangements. This study evaluates the advantages and disadvantages of WFH and their differential impacts on MNEs and international SMEs. A comparative analysis was conducted using expert pairwise judgements, assessed through linguistic terms with weakened hedges (LTWHs) within the Best–Worst Method (BWM) framework. The LTWHs approach enables experts to articulate nuanced and flexible preferences, extending traditional linguistic scales by softening the strength of evaluations. This makes it particularly suited for capturing subjective assessments of WFH impacts under conditions of uncertainty. The findings indicate substantial variation in WFH adoption, with private sector organisations demonstrating approximately 50 % greater willingness to adopt WFH compared to public authorities. The analysis further highlights the distinct advantages and disadvantages that shape the performance outcomes of MNEs and international SMEs. By introducing a novel hesitant fuzzy linguistic preference approach, this study develops a comprehensive framework for assessing the organisational consequences of WFH. The results offer valuable insights for managers and policymakers seeking to strike a balance between flexibility, productivity, and resilience in the design of post-pandemic work strategies. • Paper investigates the implications of work-from-home using digitalisation. • This is done on the performance of multinational enterprises and international SMEs. • Findings reveal a difference between the public and private sectors in their adoption of WFH. • Study highlights pros and cons of WFH, demonstrating their varying impacts.

Regional variations in molecular testing and treatment of patients with metastatic NSCLC in the Netherlands.

An organization’s long-term success is primarily tied to employee performance, creating a mutually beneficial relationship. High-performance employees drive organizational excellence, whereas effective organizations foster employee growth and development. Strategic compensation and benefit management enable employee performance by fostering trust, well-being, and engagement. This productivity gain translates to a sustainable competitive advantage, as high-performance and engaged human resources consistently deliver superior outcomes and innovations. Therefore, this study proposes an innovative Big Data Analytics (BDA)-enabled Organizational Performance Optimization (OPO) framework for compensation and benefit management. Integrating two technological models–Big Data Enabled Decision Support Architecture (BD-DSA) for secure beneficiary verification, and Contextual Recurrent-Value Learning Unit Gated Recurring Unit (CR-VLU-GRU) for accurate pay-grade classification–this framework addresses critical gaps in Human Resource (HR) decision-making. To balance operational efficiency and employee trust, this study incorporates data privacy-preserving techniques and efficient structuring into the model. The findings of the study show significant improvements in the proposed model when compared with the existing models, with – 50 % faster data retrieval for employee queries, 70 % reduction in employee digital signature creation and verification time, and 99 % accuracy and fairness in compensation allocation based on pay-grade classifications. The study highlights how data-driven compensation and benefit management strategies directly contribute to employee performance, reducing employee turnover, and eventually boosting the productivity and performance of the organization. Limitations and future direction discussions indicate that the integration of corporate social responsibility dimensions and cross-sectoral validations would strengthen the proposed framework to broaden generalizability.

In the rapidly digitalizing economy, information technology has become vital for businesses to build competitive advantage and survive in increasingly competitive environments. Export businesses must coordinate their planning and operations to meet customer needs effectively. This research examined the impact of perceived organizational support (POS) on organizational performance (OPerf) through the mediating roles of organizational learning capability (OLC) and technology capability (TC) in export enterprises. Using quantitative methodology, data were collected via questionnaires from 385 food manufacturing exporters in the Bangkok Metropolitan Region. Statistical analysis included descriptive statistics (frequency, percentage, mean, standard deviation) and Partial Least Squares-Structural Equation Modeling (PLS-SEM) for hypothesis testing. PLS-SEM was used to analyze complex relationships involving latent variables and estimate cause-effect models with mediators. The findings revealed that POS had positive and significant direct effects on OPerf (p < .001), with OLC and TC serving as significant mediators. Both OLC and TC also showed positive and significant effects on OPerf (p < .001). Theoretically, the research extends Social Exchange Theory by demonstrating that perceived organizational support enhances learning and technology capabilities that drive organizational performance. Practically, it suggests fostering a supportive organizational climate helps sustain competitiveness through learning and technology adoption.

Effective leadership for learning, innovation and sustainable organizational performance

ABSTRACT The study investigates the influence of information systems audit processes (ISAP) on organizational performance (OP) in Jordanian Universities. The mediating mechanism in the findings is accounting information systems (AIS), and a moderating factor is massive data analytics capability (BDAC) regarding data integrity and cybersecurity assurance. A quantitative method was used and structured questionnaires were used to assume data from 478 respondents. The data were analyzed through PLS-SEM and hypotheses testing was accomplished to test the hypothesis. The results suggest that ISAP has a positive effect on organizational performance, both straight and indirectly via AIS. AIS is crucial in the transformation of audit processes into expert information quality and decision-making results. Moreover, BDAC enhances the ties between ISAP and AIS, and between AIS and organizational performance. The results here object to the need for the convergence of audit processes, accounting systems and analytics in progressing performance in the emerging markets.

Employee well-being has become a critical concern for organizations across the globe due to rising job demands, technological advancement, competitive work environments, and changing employment structures. High levels of workplace stress adversely affect employee health, productivity, engagement, and overall organizational performance. In recent years, Artificial Intelligence (AI) has emerged as a transformative tool for managing workplace stress by enabling real-time monitoring, predictive analysis, and personalized interventions. This review paper synthesizes existing research on employee well-being and AI-based stress management systems. It explores conceptual foundations, emerging trends, practical applications, benefits, and ethical challenges associated with AI adoption. By reviewing scholarly literature, the paper identifies key findings and offers recommendations for responsible and effective implementation of AI-driven stress management practices in organizations. Keywords: Employee Well-being, Workplace Stress, Artificial Intelligence, Stress Management Systems, Organizational Performance

The rapid development of Artificial Intelligence (AI) and Digital Information Systems has significantly influenced organizational management practices in various sectors. This research aims to analyze the role of Artificial Intelligence and Digital Information Systems in enhancing organizational management performance through improvements in operational efficiency, decision-making accuracy, employee productivity, communication effectiveness, and system reliability. The study employed a quantitative descriptive method involving organizational employees, managers, and information system administrators as research subjects. Data were collected through questionnaires, observations, and documentation analysis, then analyzed using descriptive statistical techniques. The findings indicate that the implementation of AI-supported Digital Information Systems improved operational efficiency by 23%, decision-making accuracy by 21%, employee productivity by 22%, communication effectiveness by 22%, and system reliability by 20%. The results demonstrate that AI technologies contribute significantly to automating operational processes, reducing human error, accelerating information processing, and supporting data-driven managerial decisions. In addition, integrated digital systems improved organizational coordination, transparency, and information accessibility. Despite several implementation challenges, such as infrastructure limitations and employee adaptation, organizations that successfully adopted AI technologies experienced measurable improvements in management performance and operational effectiveness. Therefore, Artificial Intelligence and Digital Information Systems can be considered effective technological solutions for supporting organizational competitiveness and sustainability in the digital era.

Employee welfare measures are among the most critical instruments organizations use to cultivate a motivated, productive, and loyal workforce. This study examines the relationship between employee welfare measures and job satisfaction at Dong Woo Surface Tech (India) Pvt. Ltd., a medium-sized industrial manufacturing firm based in Thiruvallur District, Tamil Nadu. The study adopts a descriptive research design and collects data from 50 respondents using a structured questionnaire. Statistical tools such as percentage analysis, chi-square test, and weighted average method are employed to analyze the data. The findings indicate that welfare measures including safe working environments, canteen facilities, transport, medical benefits, insurance, and rest breaks significantly influence employee satisfaction. The study concludes that well-designed welfare programs are strategic investments that yield measurable improvements in satisfaction, morale, retention, and organizational performance.

The global organizational landscape in 2025 is defined by rapid technological disruption, generational workforce transitions, and what scholars describe as 'permanent volatility.' In this context, traditional transactional leadership—built on a straightforward exchange of rewards for effort—has proven structurally insufficient to foster the innovation and adaptability demanded by Industry 4.0. This empirical study investigates the interplay between transformational leadership, training and development (T&D), and employee job performance within a technology-driven corporate environment, with specific reference to Creating Advanced Financial Solutions Pvt. Ltd. (CAFS), Chennai. Using a structured questionnaire adapted from the Multifactor Leadership Questionnaire (MLQ-45) and the Organizational Performance Scale, primary data were collected from 385 respondents across the Chennai–Tambaram industrial corridor. With 76.9% of respondents belonging to the Gen Z cohort (aged 18–25), the workforce sample reflects a digitally native professional population with distinct leadership expectations. Statistical analyses—including Pearson Correlation (r = 0.849, p < 0.001), One-Way ANOVA (F = 15.483, p < 0.001), Chi-Square (2 = 81.542, p < 0.001), and SEM-PLS mediation testing—collectively confirm that training motivation acts as a full mediator between leadership support and innovative work behavior (IWB). A structural 'digital insecurity gap,' affecting 27.8% of the workforce, was identified as a key performance barrier that targeted T&D programs can systematically bridge. The study concludes that organizations aspiring to sustained competitive advantage must invest simultaneously in transformational leadership development and deep-tech upskilling initiatives, operationalizing what this research terms the Leadership–Training–Performance (LTP) Triad. Keywords: Transformational Leadership, Employee Job Performance, Training and Development, Digital Insecurity Gap, Gen Z Workforce, Training Motivation, SEM-PLS Mediation, Industry 4.0, Organizational Citizenship Behavior, Innovative Work Behavior, CAFS Chennai

ABSTRACT The increasing complexity of public health organizations’ environments make strategic planning more important for these organizations. Therefore , understanding how strategic planning influences performance is essential. This study examines the relationship between strategic planning and performance, with strategy implementation, stakeholder participation, and accountability as mediating variables in the context of Turkish public hospitals. The findings indicate that strategic planning has a positive and significant effect on both financial and non-financial performance through the mediating variables of stakeholder participation and accountability. The results show that strategic planning has no significant influence on financial performance, either directly or indirectly through strategy implementation.