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This study aims to develop a robust predictive model for anticipating financial distress within Pakistani companies, providing a crucial tool for proactive economic turbulence management.

To achieve this objective, the study examines a comprehensive data set comprising nonfinancial firms listed on the Pakistan Stock Exchange from 2005 to 2022. It investigates 23 financial ratios categorized under profitability, liquidity, leverage, asset efficiency, size and growth.

The study reveals that financial ratio indices are more effective in forecasting financial distress compared to individual ratios. These indices achieve impressive accuracy rates, ranging from a robust 93.90% in the first year leading up to bankruptcy to a commendable 73.71% in the fifth year. Furthermore, the research identifies profitability, liquidity, leverage, asset efficiency, size and growth as pivotal indicators for financial distress prediction.

This research underscores the utility and practicality of financial ratio indices, offering a comprehensive perspective on risk assessment and management. In conclusion, this pioneering study provides valuable insights into financial distress prediction, highlighting the enhanced information capture made possible by financial ratio indices. It equips stakeholders in the Pakistan Stock Exchange with an effective means to proactively address financial risks.

Research on women-owned businesses is more extensive in developed countries than in developing countries. This prompted the authors to investigate the factors that affect women entrepreneurs' motives to start a business and the challenges they faced in running their businesses in India.

Data for the analysis were collected from 620 respondents using a structured questionnaire and in-depth interviews with 20 women entrepreneurs. The data were then analyzed using descriptive and factor analysis in the statistical software “SPSS” (Statistical Package for the Social Sciences).

The findings showed that the primary motivation for women to launch their own business was to achieve self-employment. Other motivations include increasing income and allowing women to follow their passion. Factor analysis indicates that women entrepreneurs are more motivated by push than pull factors. The research also shows that women encounter challenges in their entrepreneurial journey, such as access to financing, issues with gender equality and social and cultural obligations.

The study on women entrepreneurs in the Indian context is limited. This study responds to a need of better understanding of women motivations and challenges. By studying these constructs, the study shows that start-up motives and challenges faced by female entrepreneurs are unique to different contexts.

This study examines how the importance of external investment environment factors affects stock market perception, and how stock market perception affects stock investments after stock market crash witnessed by individual investors in one of the emerging stock markets.

A cross-sectional survey was administrated among 223 individual investors who experienced stock market crash in 2010–2011 in Bangladesh, and the proposed model was tested by the partial least squares-structural equation modeling PLS-SEM model.

Findings show that the importance of Bangladesh's stock market performance, government policy, economic issues and neighboring country's stock market performance have effects on investors' stock market perception. This perception, in turn, decreases monthly stock trading and short-term investment horizon. The findings further show the mediating effect of stock market perception.

Investors need to carefully consider the external investment environment when they form their stock market perception, as this perception drives stock investments. Analogously, regulators should ensure releasing timely and updated statistics on external investment factors.

Addressing those investors who encountered stock market crash, a set of external investment environment issues, stock market perception and stock investments are new in the literature.

In recent years, deep learning and extended reality (XR) technologies have gained popularity in the built environment, especially in construction engineering and management. A significant amount of research efforts has been thus dedicated to the automation of construction-related activities and visualization of the construction process. The purpose of this study is to investigate potential research opportunities in the integration of deep learning and XR technologies in construction engineering and management.

This study presents a literature review of 164 research articles published in Scopus from 2006 to 2021, based on strict data acquisition criteria. A mixed review method, consisting of a scientometric analysis and systematic review, is conducted in this study to identify research gaps and propose future research directions.

The proposed research directions can be categorized into four areas, including realism of training simulations; integration of visual and audio-based classification; automated hazard detection in head-mounted displays (HMDs); and context awareness in HMDs.

This study contributes to the body of knowledge by identifying the necessity of integrating deep learning and XR technologies in facilitating the construction engineering and management process.

Academic institutions play a crucial role in social and economic development. They share responsibilities to equip students with knowledge and skills. This study aims to examine and investigate the impact of knowledge sharing enablers (KSE) on knowledge sharing behavior (KSB). The paper measured KSE through perceived instructor support of knowledge sharing instructor support (IS), perceived information and communication technology (ICT) support of knowledge sharing and perceived ability to share knowledge (ASK).

A survey questionnaire was used as an instrument for data collection. A sample of 597 students from Al Ain University in UAE participated in the study. The collected data were treated and analyzed through MS Excel and International Business Machines Statistical Package for the Social Sciences (SPSS) version 25. The theory of reasoned action (TRA) was used in formulating a conceptual framework. Several statistical techniques, including partial least square structural equation modeling, were used to test and verify hypotheses.

Findings of the study supported TRA theory by suggesting a positive and significant impact of KSE (IS, ICT and ASK) on KSB. The findings supported the stated three hypotheses and confirmed that at least 45% of the variation in students’ KSB is explained by a variation in one of the three KSE indicators. The paper provided important theoretical and practical implications for researchers and managers of academic institutions.

Academic institutions need to advance their strategies to create more collaborative environments for boosting knowledge sharing among students. Such practice will contribute in improving the students’ overall capabilities, skills and success of academic institutions.