Purpose: Building upon the theory of planned behaviour and the entrepreneurial event model, the purpose of this paper is to test the effects of the following covariates in predicting entrepreneurial intention among tourism students in Bangladesh, namely, attitude, subjective norm, perceived behavioural control (PBC), perceived desirability and perceived feasibility. Design/methodology/approach: A total of 137 private university students participated in the study by means of questionnaire. The hypotheses were tested using partial least squares (PLS) analysis. Findings: Findings indicate that attitude and subjective norm significantly influence perceived desirability. It was also found that subjective norm and PBC positively influence perceived feasibility. Interestingly also, both perceived desirability and perceived feasibility predict entrepreneurial intention. Originality/value: The study proves the robustness of the integration of the two intent models in explaining entrepreneurial intention in a developing country. The new PLS predict algorithm has been used to generate and evaluate predictions from the path model estimations.

Integrating artificial intelligence (AI) into sustainable urban development presents an innovative pathway for addressing global environmental and socio-economic challenges. This study examines how AI technologies—such as machine learning, the Internet of Things (IoT), and big data analytics—can advance the three zeros method, a sustainability framework proposed by Nobel laureate Muhammad Yunus, which focuses on zero carbon emissions, zero poverty, and zero waste. By analyzing panel data across 50 countries and incorporating case studies, the research highlights AI’s role in promoting carbon neutrality, economic inclusivity, and waste reduction. The findings reveal that AI-driven R&D innovation exerts the most decisive influence on sustainability, followed by AI-powered infrastructure, while market advantage plays a comparatively more minor role. Additionally, the study uncovers regional disparities in AI’s impact, with the most significant benefits observed in countries at upper-middle levels of sustainable development. Moreover, urbanization serves as a threshold factor, altering AI’s effects on sustainability. When urbanization is below a critical level, AI-driven innovation and infrastructure support sustainability, whereas the AI market advantage inhibits it. However, infrastructure may hinder sustainable development beyond this threshold while AI market mechanisms become more influential. These insights underscore the need for policymakers to tailor AI-driven sustainability strategies based on urbanization dynamics and regional development levels.

Within the intricate interplay of socio-economic, natural and anthropogenic factors, haze pollution stands as a stark emblem of environmental degradation, particularly in the South Asian Association for Regional Cooperation (SAARC) region. Despite significant efforts to mitigate greenhouse gas emissions, several SAARC nations consistently rank among the world’s most polluted. Addressing this critical research gap, this study employs robust econometric methodologies to elucidate the dynamics of haze pollution across SAARC countries from 1998 to 2020. These methodologies include the Pooled Mean Group (PMG) and Augmented Mean Group (AMG) estimator, Panel two-stage least squares (TSLS), Feasible Generalized Least Squares (FGLS) and Dumitrescu–Hurlin (D–H) causality test. The analysis reveals a statistically significant cointegrating relationship between PM2.5 and economic indicators, with economic development and consumption expenditure exhibiting positive associations and rainfall demonstrating a mitigating effect. Furthermore, a bidirectional causality is established between temperature and economic growth, both influencing PM2.5 concentrations. These findings emphasize the crucial role of evidence-based policy strategies in curbing air pollution. Based on these insights, recommendations focus on prioritizing green economic paradigms, intensifying forest conservation efforts, fostering the adoption of eco-friendly energy technologies in manufacturing and proactively implementing climate-sensitive policies. By embracing these recommendations, SAARC nations can formulate comprehensive and sustainable approaches to combat air pollution, paving the way for a healthier atmospheric environment for their citizens.