The study explores the hormonal influences on entrepreneurial opportunity persuasion decisions (OPD). It also analyzes how behavioural psychology influences the entrepreneurial opportunity recognition-refinement process (OPRR). The machine learning and structural equation modelling analyses of the data from 271 Indian entrepreneurs support the hypotheses of a direct effect of the physiological biomarker—Testosterone-Cortisol Ratio (TCR) and behavioural marker—communities of inquiry (COI) on OPD. Further, partial mediation indicated an indirect positive effect of COI on OPD, with OPRR moderating this relationship. Shedding new light on the enigmatic entrepreneurial opportunity behaviour from a biological and behavioural perspective improves the causal inference of external and socially-influenced COI and internally-triggered TCR. Finally, theoretical and methodological contributions are discussed along with implications that can guide future research on entrepreneurial opportunity behaviours.

NGOs provide support services in developing countries when governments are unable to improve the growth indicators. There exists a requirement for sustainable NGOs that can help fill the gap between the needs of the people and the scarce resources available in developing countries. This study aimed to identify essential factors that are internally controllable by the NGO and to reflect on the impact of the internally controllable factors on the NGO’s sustainability. The study used established theories to investigate internal and external factors influencing NGOs and to identify the factors of significance. This qualitative research was designed with a systematic review followed by content analysis. It was undertaken in a developing country with a sample size of thirty-four using Purposive sampling. Analysis suggests that three variables including Financial Performance, Organizational Practices, and Community Interest have a statistically significant effect on sustainability. The study infers that considering the business environment, NGOs must focus on internal controllable factors. It also reiterates that NGOs should ensure a steady flow of funds, have robust management and should enjoy the support of the community to remain sustainable.

This study explores the potential of artificial intelligence (AI) in assisting novice entrepreneurs in evaluating the effectiveness of ex-ante measures of business model design and their impact on ex-post measures of performance. The study adopts a decision science approach to argue that entrepreneurs create business models by making choices based on what is valuable and possible rather than what is available. The Startup Evaluation Calculus with Research Evidence (SECURE I) framework has shown that the careful design of ex-ante measures can positively impact ex-post standards of firm performance. The study proposes a SECURE II framework integrating AI tools to improve the frameworks' predictive ability. By unlocking insights and patterns hidden in large volumes of data, AI can assist entrepreneurs in making informed decisions and becoming more responsive and agile to market needs. By unlocking patterns hidden in voluminous data, AI can assist entrepreneurs to predict Entrepreneurial Capability for making informed decisions and becoming more responsive and agile to market needs. The study's contributions include integrating Symbolic AI and Neural AI to aid entrepreneurial decision-making, enhancing the cognitive capacity of decision-making, and using an evaluation tool that incorporates automation and persuasiveness. The research relies on quantitative data and uses an experimental method to examine the effects of AI on entrepreneurial decision-making.

Introduction: Choosing a specialty after graduation plays an important role in the life of a student. However, little is known about students' preferences about selection of specialties in physical therapy students in developing countries. This study aimed to find out specialties' preferences and factors that influence students' choices of selection any specialty in physical therapy students studying in final year. Material & Methods: This cross-sectional study was conducted on students of physical therapy institutes located in Peshawar, Khyber Pakhtunkhwa. The study was carried out from November 2018 to April 2019. Data was collected from final year students only. All students who were eligible, were included for this survey and a total of 185 students participated in this survey. Written informed consent was obtained from all participants and questionnaires were distributed amongst them. The data collection tool used for this study was a semi-structured questionnaire. SPSS version 22 was used for data analysis. The measure of frequencies was obtained for variables and chi-square test was applied to measure the association between variables. Results: A total of 185 students, 101 (54.6%) female and 84 (45.4%) male with a mean age of 23.44 ± 1.54 years participated in this study. Among all the participants, 145 (78.3%) intended to specialize in the future. The most preferred specialty amongst these participants was Musculoskeletal Physical Therapy (n=80,43.2%). The least chosen specialty was Geriatrics Physical Therapy (n=2, 1.1%). Among male participants no one selected Gynecological Physical Therapy as specialty. Prestige within the profession was considered the most important factor for specialty preference (n=118, 81.4%). Conclusion: Musculoskeletal Physical Therapy remained preferred choice of specialty amongst students of final year studying Doctor of Physical Therapy in Peshawar, Khyber Pakhtunkhwa. The most important reported factor effecting specialty preferences amongst physical therapy students is prestige within the profession.