The education sector has been severely affected by the global pandemic of COVID-19, and the need for improvement in its aftermath became a challenge for scholars and practitioners alike. The current research focuses on the role of Green Human Resource Management (GHRM) initiatives as an independent variable that is innovation-centric, and improved innovation performance of education sector employees as the dependent variable. GHRM in the current context is described as focusing on environmental aspects within the processes and functions of work in a comprehensive manner that incorporates both resource/waste management and areas of development, as well as green behavior among members. Moreover, the mediating effect of green innovation on the aforementioned relationship and enhancing the role of environmental leadership are examined through a quantitative approach using purposive and convenience sampling techniques. Data from several universities across Northern Cyprus have been gathered with regard to the design, aims, and context of this study. With a total of 187 teachers and administrators from three different universities and using PLS-SEM for analysis, the results show that human resource departments in universities can play a major role in determining the extent of innovation performance within the organization. Green innovation as a mediator can improve the workplace environment, which can be significantly enhanced through an adequate leadership that supports such initiatives (i.e., environmental leadership). The current results can be beneficial for scholars (organizational psychology, innovation, and sustainable HRM), as well as decision-makers in the universities in Northern Cyprus as a small island.

At the heart of supply chain innovation lies the challenge of complexity, a pivotal force shaping the pathways to resilience and sustainable success in today’s business environment. Drawing from the resource-based view, dynamic capabilities, and contingency theories, this study examines the impact of green innovation strategies on supply chain resilience through the mediation role of green logistics management practices and the moderation effects of dynamic and structural supply chain complexity. Leveraging a quantitative approach, this study surveyed 404 managers from manufacturing firms in Turkey using a combination of physical and electronic questionnaires. Our analysis robustly supports the interconnected roles of green innovation strategy and logistics management practices in bolstering supply chain resilience. A green innovation strategy significantly enhances green logistics management practices and supply chain resilience. Further, green logistics practices contribute positively to supply chain resilience, acting as a crucial mediator in translating green innovation strategies into heightened supply chain resilience. Additionally, the effectiveness of green innovation strategies in improving green logistics management practices is amplified in less structurally complex supply chains. In contrast, the impact of green logistics practices on supply chain resilience becomes more pronounced in environments with lower dynamic complexity, highlighting the nuanced influence of supply chain complexity on sustainability efforts. The study’s findings contribute a novel perspective to the sustainability discourse, emphasizing complexity’s nuanced role as a determinant of supply chain resilience.

Academics and practitioners have shown growing interests in big data analytics and artificial intelligence (BDA-AI) in recent years. Despite this, research on the application of BDA-AI for green supply chain collaboration (GSCC) and its influence on environmental performance (EP) is still limited. The current research addresses this gap and extends organizational information processing theory by incorporating BDA-AI and exploring top management commitment (TMC) as a moderator. The current study developed a moderated mediation model based on 402 samples of data from Turkish manufacturing firms. The result revealed that the application of BDA-AI has a positive impact on GSCC and EP. The results also indicated that GSCC has a positive impact on EP. Our findings revealed that GSCC mediated the association between BDA-AI and EP. The results also revealed that TMC moderated the positive relationship between BDA-AI and GSCC, such that the strength of the positive relationship is further intensified at higher levels of TMC. The results also show that TMC moderated the positive relationship between BDA-AI and EP, such that the strength of the positive relationship is dampened at lower levels of TMC; significant findings have not been outlined in the extant literature. The current research will assist supply chain and logistics managers and top management in deploying BDA-AI technology to support GSCC and improve EP.

Modern workplaces increasingly use algorithmic management practices (AMPs), which shape task assignment, monitoring, and evaluation. Despite the potential benefits these practices offer, like increased efficiency and objectivity, their impact on workforce well-being (WFW) has raised concerns. Drawing on self-determination theory (SDT) and conservation of resources theory (COR), this study examines the relationship between algorithmic management practices and workforce well-being, incorporating job burnout (JBO) and perceived threat (PT) as parallel mediators and person–job fit (PJF) as a moderator. The research employed a cross-sectional survey design targeting 2450 KOSGEB-registered manufacturing SMEs in Istanbul, Turkey. A sample of 666 respondents participated, and the data were analyzed using Smart PLS 4, employing structural equation modeling to test the proposed model. The results indicated that algorithmic management practices significantly increased job burnout and perceived threat, both of which negatively impacted workforce well-being. However, the direct effect of algorithmic management practices on workforce well-being was non-significant. Person–job fit moderated the relationships between algorithmic management practices and both job burnout and perceived threat, further influencing workforce well-being. The findings underscore the critical need for organizations to balance algorithmic efficiency with human-centric practices. Prioritizing person–job fit and fostering transparency in algorithmic processes can mitigate negative impacts, enhance employee well-being, and drive sustainable organizational success in the digital age.

Strategic entrepreneurship behaviors enhance business performance and sustainability in Turkish SMEs by fostering innovation and leveraging competitive intensity for sustained growth. Employing strategic leadership theory, this study examines the effect of strategic entrepreneurial behaviors on business performance through the mediation role of business model innovation (BMI) and the moderation effect of competitive intensity. A quantitative approach was used, and data from 313 managers and business owners in Turkish small and medium enterprises (SMEs) were collected using a structured questionnaire. The results have shown that strategic entrepreneurial behavior significantly and positively impacts business performance and business model innovation. Business model innovation, in turn, positively affects business performance. Competitive intensity moderates the relationship between strategic entrepreneurial behavior and business model innovation, strengthening it under higher competitive pressure levels. However, competitive intensity does not moderate the direct link between strategic entrepreneurial behavior and business performance. At higher levels of competitive intensity, the conditional indirect effect of strategic entrepreneurial behavior on business performance through business model innovation becomes more prominent. The findings of this study offer actionable insights for enhancing SME performance through strategic entrepreneurship, innovative business models, and competitive strategy adaptation.

The pursuit of sustainable development has become a global priority, with the United Nations Sustainable Development Goals (UN SDGs) serving as a comprehensive framework for addressing various social, economic, and environmental challenges. Employing the stimulus–organization–response (SOR) model, this study examines the impact of customer’s perceptions of the firm’s compliance with the SDGs on customers’ perceptions and loyalty through the mediation roles of image, trust, and reputation in the customer’s evaluation of the firm in the banking sector in Turkey. To achieve these objectives, a quantitative research approach was used, and 455 valid responses were collected from retail banking customers through an online survey. Data from the study were statistically analyzed using partial least-squares–structural equation modeling (PLS-SEM). The findings reveal significant positive relationships between SDG implementation and customers’ perceptions of banking institutions’ image, trust, and reputation. Furthermore, favorable image, trust, and favorable reputation are found to positively influence customer loyalty in the banking sector. The mediation analyses confirm that each of the mediating variables partially mediates the relationships between SDG implementation and customer loyalty, underscoring the significance of these intermediate variables in shaping customers’ loyalty behaviors. This research contributes to both theoretical and practical domains by providing insights into the role of SDG implementation in enhancing customer perceptions and loyalty in the banking sector. Managerial implications are discussed, and recommendations are provided for banking institutions seeking to leverage the SDGs to strengthen customer relationships and achieve sustainable growth.