The entrepreneurial stress construct’s nomological validity is not well established as past studies have not delineated between entrepreneurial and employee stress. This study investigated several entrepreneurship-specific stressors positing their causal effect on perceived entrepreneurial stress (PES). It examined four directional hypotheses testing the causal, reverse, reciprocal relationships and moderation effects between stressors and PES. Further, it looked at the moderating impact of psychological capital. More than 300 entrepreneurs in emerging markets, namely India, Pakistan, and the United Arab Emirates, participated in this longitudinal study (Time 1 n = 325, Time 2 n = 310). The study adopted a cross-lagged competing model research design and analyzed the data using structural equation modeling (SEM). The results show that entrepreneurship-specific personal, social, and occupational stressors cause PES. Further, the results also support the reverse causal effect of PES on stressors and a reciprocal relationship. The study advances resource-based theory to an entrepreneurial background, highlighting the role of intangible resource gaps in perceived entrepreneurial stress. The study concludes that entrepreneurship-specific intangible resources are useful to entrepreneurs at personal, social, and occupational levels. An actual or perceived loss of these resources may lead to perceived entrepreneurial stress. Furthermore, PES can interfere with the entrepreneurial capacity for innovation over time. Psychological capital can be an effective coping response as a moderator of perceived entrepreneurial stress’ adverse effects. This is one of the first studies that examines PES in an emerging market context, specific to entrepreneurial employment.

Belt and Road Initiative (BRI), one of the largest logistics and transportation infrastructures to date, has focused on much work in the economics and political sciences. However, little research has been done on how BRI can affect supply chain management on the whole. Since BRI is a large-scale logistics infrastructure-building project, it is clear that it will have several implications for supply chains. This study aimed to fill this gap in supply chain management literature within the context of the BRI. In particular, this paper aimed to unveil the potential challenges and threats that BRI may bring to supply chain management. Using 20 semistructured interviews with supply chain managers located on the BRI lane in South Asian countries (Pakistan, India, Bangladesh, etc.), this study posed six distinct implications of BRI for logistics and supply chain management. This article concludes by articulating its contributions to theory and practice and, finally, limitations and future research directions.

Objective- The research looks forward to extracting strategies for accelerated recovery during the ongoing Covid-19 pandemic. Design - Research design considers quantitative methodology and evaluates significant factors from 170 countries to deploy supervised and unsupervised Machine Learning techniques to generate non-trivial predictions. Findings - Findings presented by the research reflect on data-driven observation applicable at the macro level and provide healthcare-oriented insights for governing authorities. Policy Implications - Research provides interpretability of Machine Learning models regarding several aspects of the pandemic that can be leveraged for optimizing treatment protocols. Originality - Research makes use of curated near-time data to identify significant correlations keeping emerging economies at the center stage. Considering the current state of clinical trial research reflects on parallel non-clinical strategies to co-exist with the Coronavirus.

This qualitative study investigates the perceptions of learners regarding the potential role of generative AI language models in supporting autonomy, competence, and relatedness, the three key dimensions of self-determination theory (SDT).The research employs a thematic analysis of learning artifacts created by 25 learners engaging with AI models in various educational settings to gain insights into how these technologies may support certain aspects of personalized learning experiences, task scaffolding, and sense of community under specific conditions. The findings suggest that, from the perspective of this limited sample, generative AI language models have the potential to foster learner autonomy by enabling adaptive content, encouraging exploration, and supporting some self-regulated learning strategies. The results also indicate possible avenues through which these models may bolster aspects of perceived competence and relatedness for some learners. This study contributes to the emerging body of exploratory research on the prospective roles of AI in education.

Creativity and innovation are integral to progress, yet neurocognitive mechanisms underlying creative thought remain unclear. This EEG study examined gender differences in brain activation during verbal and figural creative thinking tasks in 20 adults (10M, 10F). Participants completed verbal (Ask-and-Guess, Just Suppose) and figural (Unusual Uses) divergent thinking tasks from the Abbreviated Torrance Test while EEG was recorded. Analyses examined default mode, executive control, and salience network activity across frequency bands. Results revealed subtle gender differences in network activations and interactions during creative ideation. Females exhibited greater frontoparietal coupling, indicating enhanced cognitive flexibility. Males displayed higher default mode synchronization, suggesting greater persistence within an imaginative space. Findings provide initial neural evidence for specialized neurocognitive profiles between genders, with female advantages in flexible divergent thinking and male strengths in focused conceptual exploration. Request access from your librarian to read this chapter's full text.