A significant portion of small and medium-sized enterprises (SMEs) are usually allocated to the construction sector, which plays a vital role in many economies. SMEs currently face serious concerns regarding the pursuit of sustainability. Limited financial resources (FRs) frequently prevent SMEs from implementing sustainable practices. Therefore, these enterprises should mitigate expenses to invest in environmentally friendly initiatives. Enhancing resources and developing ways to accelerate Turkish SMEs’ shift toward sustainability is vital. Moreover, adopting artificial intelligence (AI) and green innovation strategies (GISs) can boost sustainable competitive advantage (SCA) and lead them to success. This study utilized the natural resource-based view theory (NRBV), developed to compensate for the RBV’s shortcomings by incorporating the natural environment into the RBV’s framework. This study uses structural equation modeling (SEM) to examine the causal effect between the study variables based on the responses received from 228 executives within SMEs in Turkey’s construction sector. The findings of this study reveal that FRs significantly impact the SCA among SMEs, while GIS serves as a mediator in the relationship. Additionally, the moderating impact of AI adoption promotes sustainability development in this industry. This study is significant because it contributes to the body of knowledge regarding the relationship between the study’s constructs that align with Sustainable Development Goal 9 (Industry, Innovation, and Infrastructure), presented by the United Nations in 2015. This goal promotes robust infrastructure, encourages sustainable and inclusive industrialization, and stimulates innovation in the SME construction industry. Although these variables have been studied individually in previous studies, this study integrates them into a thorough framework that emphasizes the function of GIS as a mediator in the relationship between FRs and SCA, and the interaction effect of AI adoption. This study offers useful information to managers, stakeholders, politicians, and SME leaders, enabling them to make well-informed decisions about sustainable practices.

Technological development in artificial intelligence (AI) has significantly transformed the learning context, and university-level students are now required to possess AI literacy. Effective research, however, has not been conducted to study factors influencing AI literacy. Grounded in engagement theory, self-efficacy theory, and transactional distance theory, this research investigates how anxiety, self-efficacy, and AI literacy are associated among Northern Cyprus University students. A cross-sectional survey was conducted, gathering data from 222 participating students from different universities in the region. Findings indicate that for university students in Northern Cyprus, student engagement significantly influences AI literacy. Also, the relationship between student engagement and AI literacy is mediated by anxiety reduction, which denotes that higher engagement decreases anxiety, enhancing AI literacy. Moreover, it is found that self-efficacy mediates the relationship between student engagement and AI literacy, which indicates that higher levels of engagement result in higher levels of self-efficacy, resulting in higher levels of AI literacy outcomes. Smart PLS 4 structural equation modeling (SEM) was used in data analysis and gaining meaningful insight into these relationships. The study contributes to Sustainable Development Goals (SDGs) 3 and 4 through the facilitation of mental well-being and inclusive quality education via improved AI competencies, proposing evidence-based perceptions into how engagement, anxiety reduction, and self-efficacy boost well-being and education. The findings of the study will enable educators, policymakers, and curriculum developers to design curricula and educational strategies that reduce anxiety, strengthen the self-efficacy of learners, and thereby strengthen their AI literacy level.

This study investigates the influence of technostress (Tech) on the well-being (WB) of employees in manufacturing sectors employing Industry 4.0 in Turkey, examining the effect of work exhaustion (WE) as a mediator in the association between technostress and well-being. How digital leadership (Dg) moderates these relationships is analyzed and discussed accordingly. This article also presents strategies for digital leaders to mitigate employees’ technostress in the digital transformation era and discusses their positive role. Using the Job Demands–Resources (JD-R) framework and Conservation of Resources (COR) theory, data were gathered from 329 workers employed at three manufacturing firms located in Istanbul. Structural equation modeling (SEM) was employed to test this study’s hypothesis. The results indicate that increased technostress notably reduces employee well-being, primarily because it heightens work exhaustion. Moreover, robust digital leadership effectively lessens these negative impacts, underscoring its value in managing technological stress. This research explains the importance of the Sustainable Development Goal (SDG 3) for better health and well-being practices in workplaces. It suggests practical implications for organizations, including developing digital leadership skills, routinely assessing technostress, and applying targeted actions to sustain employee health during digital shifts.

Organizations within the fashion industry have been encouraged to adopt more sustainable marketing strategies to address growing sustainability concerns. Nevertheless, the unpredictability of environmental volatility makes it difficult to adopt green practices. Since the fashion industry is the most environmentally damaging sector, applying sustainable practices may develop competitiveness in the dynamic nature of the environment. The study utilizes resource-based view (RBV) theory to investigate how competitiveness might be enhanced in this setting through sustainable strategies. Using a purposive and convenience sampling method, 400 questionnaires were distributed to managers of Iranian textile companies and company personnel knowledgeable about green initiatives and AI. After screening the data, 230 questionnaires were considered appropriate for analysis. A quantitative analysis was carried out to analyze the data. Using PLS-SEM for analysis, the findings indicate that green marketing (GM) significantly impacts green marketing strategies (GMS), with competitive strategy (CS) serving as a mediator. Furthermore, green marketing significantly impacts the competitive strategy, and competitive business strategies affect the company’s green initiatives. Additionally, environmental turbulence (ET) is found to negatively moderate the relationship between green marketing and competitive strategies, indicating that ET (market turbulence, technological turbulence, as well as competition intensity) can diminish the effectiveness of sustainability initiatives. Managers and marketers in the fashion industry interested in enhancing their competitive edge through environmentally friendly marketing and sustainable tactics will find this study informative and insightful.

This study explores the impact of sustainable leadership (SL) on environmental performance (EP), focusing on the mediating role of employee well-being (EW) and the moderating role of eco-anxiety in green companies in Turkey. The framework is founded on the Job Demands-Resources (JD-R) paradigm and is enhanced by Sustainable Leadership Theory, Bottom-Up Spillover Theory, and Terror Management Theory. Data were collected from 289 employees at five environmentally sustainable enterprises in Turkey, using a standardized questionnaire to evaluate characteristics through validated multi-item scales. Structural equation modeling (SEM) with SmartPLS4 was employed to assess reliability, validity, and the suggested correlations. The study’s findings demonstrate that SL has a substantial and favorable impact on EP, both directly and indirectly, through the enhancement of staff well-being. Furthermore, research indicates that eco-anxiety mitigates the association between SL and well-being, suggesting that increased eco-anxiety diminishes the beneficial effects of leadership. These findings underline the significance of robust, SL and proactive management of eco-anxiety to enhance employee well-being and optimize corporate environmental results. The outcomes indicate that firms should allocate resources to leadership development initiatives and staff support frameworks to alleviate climate-related anxiety and enhance resilience. The study advances Sustainable Development Goal 3 (Good Health and Well-being) by demonstrating how psychological health and leadership synergize to enhance environmental performance. It also offers practical implications for sustainable workplace practices.

Education in entrepreneurship offers university students the opportunity to develop sound problem-solving and critical-thinking dexterity, which are crucial for navigating contemporary higher education. This research explores the opportunities and challenges of education in entrepreneurship within universities based in Lebanon, focusing on the role of fostering entrepreneurial alertness/awareness. This paper further examines how emerging technologies—specifically Generative Artificial Intelligence (Gen-AI)—impact these relationships. In spite of the increasing relevance of entrepreneurship, the results reveal constant limitations in students’ innovation and creativity, together with a lack of mentorship and training prospects for teachers. The study underlines the importance of integrating innovative systems, digital technological means, and sustainable education values to support SDG 4 (Quality Education) and reinforce learning quality environments. To empirically explore the relationships between the variables, the research uses a quantitative research design, using SmartPLS4 to investigate the structural paths between entrepreneurship education, student innovative behavior, entrepreneurial alertness, and the use of Gen-AI. Our data was collected from 197 participants through a validated survey scheme, together with insights received from instructors and students. The results indicate that instructors consider entrepreneurship education positively and recognize the potential of Gen-AI to improve teaching quality, encourage entrepreneurial alertness, and strengthen quality learning practices. Students also highlighted their requirement to acquire new skills and access new opportunities to enhance their decision-making abilities. Generally, the results/findings suggest that entrepreneurship education—emboldened by entrepreneurial alertness and moderated by Gen-AI—plays a vital role in improving students’ innovative behaviors and progressing SDG 4 through high-quality, inclusive, and transformative higher education.