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Students pursuing different professional courses at the higher education level during 2021–2022 saw the first-time occurrence of a pandemic in the form of coronavirus disease 2019 (COVID-19), and their mental health was affected. Many works are available in the literature to assess mental health severity. However, it is necessary to identify the affected students early for effective treatment.

Predictive analytics, a part of machine learning (ML), helps with early identification based on mental health severity levels to aid clinical psychologists. As a case study, engineering and medical course students were comparatively analysed in this work as they have rich course content and a stricter evaluation process than other streams. The methodology includes an online survey that obtains demographic details, academic qualifications, family details, etc. and anxiety and depression questions using the Hospital Anxiety and Depression Scale (HADS). The responses acquired through social media networks are analysed using ML algorithms – support vector machines (SVMs) (robust handling of health information) and J48 decision tree (DT) (interpretability/comprehensibility). Also, random forest is used to identify the predictors for anxiety and depression.

The results show that the support vector classifier produces outperforming results with classification accuracy of 100%, 1.0 precision and 1.0 recall, followed by the J48 DT classifier with 96%. It was found that medical students are affected by anxiety and depression marginally more when compared with engineering students.

The entire work is dependent on the social media-displayed online questionnaire, and the participants were not met in person. This indicates that the response rate could not be evaluated appropriately. Due to the medical restrictions imposed by COVID-19, which remain in effect in 2022, this is the only method found to collect primary data from college students. Additionally, students self-selected themselves to participate in this survey, which raises the possibility of selection bias.

The responses acquired through social media networks are analysed using ML algorithms. This will be a big support for understanding the mental issues of the students due to COVID-19 and can taking appropriate actions to rectify them. This will improve the quality of the learning process in higher education in Oman.

Furthermore, this study aims to provide recommendations for mental health screening as a regular practice in educational institutions to identify undetected students.

Comparing the mental health issues of two professional course students is the novelty of this work. This is needed because both studies require practical learning, long hours of work, etc.

This study addresses the COVID-19 infection and its relationship with the city’s constructive intensity, commuting time to work and labor market dynamics during the lockdown period.

Microdata from formal workers in Recife was used to adjust a probability model for disease contraction.

The authors' results indicate that greater distance to employment increases the probability of infection. The same applies to constructive intensity, suggesting that residences in denser areas, such as apartments in buildings, condominiums and informal settlements, elevate the chances of contracting the disease. It is also observed that formal workers with completed higher education have lower infection risks, while healthcare professionals on the frontlines of combating the disease face higher risks than others. The lockdown effectively reduced contagion by limiting people’s mobility during the specified period.

The research shows important causal relationships, making it possible to think about public policies for the health of individuals both when commuting to work and in living conditions, aiming to control contagion by COVID-19.

The lockdown effectively reduced contagion by limiting people’s mobility during the specified period.

It is also observed that formal workers with completed higher education have lower infection risks, while healthcare professionals on the frontlines of combating the disease face higher risks than others.

The authors identified positive and significant relationships between these urban characteristics and increased contagion, controlling for neighborhood, individual characteristics, comorbidities, occupations and economic activities.

Although microfinancing is considered a key tool for fostering women's entrepreneurship development, there is growing concern regarding the impact of loan repayment strategies on the mental health of women entrepreneurs. This study seeks to unravel the implications of microfinance loans on the mental well-being of women entrepreneurs.

A carefully structured questionnaire was distributed to a purposive sample of one hundred women entrepreneurs in Lagos State using a mixed-method research approach. Also, interviews were conducted using an interview guide, which directly mirrored the questionnaire administered to five focus groups within Lagos State.

The study found that loan repayment and recovery strategies positively and significantly impact women entrepreneurs' mental well-being, with psychological distress serving as a measure for measuring mental well-being. Additionally, other factors such as the number of dependants and household headship trigger psychological distress, while age in business was associated with a reduction in psychological distress.

This study contributes to the existing literature by delving into the psychological implications of loan repayment strategies on the mental health of female entrepreneurs in Lagos State, Nigeria. Furthermore, it employs a triangulation research approach to validate questionnaire responses through focus group discussions.

The vulnerability of the tourism industry to an array of risks, encompassing family-related, small- and medium-sized enterprise-specific, strategic, tourism-specific and external factors, highlights the landscape within which small and medium family enterprises (SMFEs) operate. Although SMFEs are an important stakeholder in the dynamic tourism sector, they are not one homogenous group of firms, but have different strategic orientations. This study aims to investigate the interplay between strategic orientation and risk perception to better understand SMFEs risk perception as it is impacting their decision-making processes, resilience and long-term survival. The authors investigate how different strategic orientations contribute to different perspectives on risk among owner-managers.

Based on a qualitative data corpus of 119 face-to-face interviews, the authors apply various coding rounds to better understand the relationship between strategic orientations and the perceptions of risks. Firstly, the authors analysed the owner–manager interviews and identified three groups of different strategic orientations: proactive and sustainability-oriented SMFE, destination-affirmative and resilience-oriented SMFE and passive SMFE. Secondly, the authors coded the interviews for different risks identified. The authors identified that the three groups show differences in the risk perceptions.

The data unveil that the three groups of SMFEs have several differences in how they perceive risks. Proactive and sustainability-oriented SMFEs prioritize business risks, demonstrating a penchant for innovation and sustainability. Destination-affirmative and resilience-oriented SMFEs perceive a broader range of risks, tying their investments to destination development, emphasizing family and health risks and navigating competitive pressures. Passive SMFEs, primarily concerned with external risks, exhibit limited awareness of internal and strategic risks, resist change and often defer decision-making to successors. The findings underscore how different strategic orientations influence risk perceptions and decision-making processes within SMFEs in the tourism industry.

The authors contribute to existing knowledge include offering a comprehensive status quo of perceived risks for different strategic orientations, a notably underexplored area. In addition, the differences with respect to risk perception shown in the paper suggest that simplified models ignoring risk perception may be insufficient for policy recommendations and for understanding the dynamics of the tourism sector. For future research, the authors propose to focus on exploring the possible directions in which strategic orientation and risk perception influence one another, which might be a limitation of this study due to its qualitative nature.

Varying strategic orientations and risk perceptions highlight the diversity within the stakeholder group of SMFE. Recognizing differences allows for more targeted interventions that address the unique concerns and opportunities of each group and can thus improve the firm’s resilience (Memili et al., 2023) and therefore leading to sustainability destinations development. The authors suggest practical support for destination management organizations and regional policymakers, aimed especially at enhancing the risk management of passive SMFEs. Proactive SMFE could be encouraged to perceive more family risks.

Viewing tourism destinations as a complex stakeholder network, unveiling distinct risk landscapes for various strategic orientations of one stakeholder has the potential to benefit the overall destination development. The proactive and sustainability-oriented SMFEs are highly pertinent as they might lead destinations to further development and create competitive advantage through innovative business models. Passive SMFEs might hinder the further development of the destination, e.g. through missing innovation efforts or succession.

Although different studies explore business risks (Forgacs and Dimanche, 2016), risks from climate change (Demiroglu et al., 2019), natural disasters (Zhang et al., 2023) or shocks such as COVID-19 (Teeroovengadum et al., 2021), this study shows that it does not imply that SMFE as active stakeholder perceive such risk. Rather, different strategic orientations are in relation to perceiving risks differently. The authors therefore open up an interesting new field for further studies, as risk perception influences the decision-making of tourism actors, and therefore resilience.

Digital supply chains require nascent technologies like blockchain and Internet of Things (IoT). There is a need to develop a roadmap for the implementation of these technologies, as they require a huge amount of resources and infrastructure. The purpose of this paper is to analyze the challenges of implementing blockchain-IoT integrated architecture in the green supply chain and develop strategies for the same.

After a thorough literature survey of Scopus-indexed journals and books, 37 barriers were identified, which were then brought down to 15 barriers after confirming with industry and academic experts using the Delphi method. Using the total interpretive structural modeling (TISM) method and cross-impact matrix multiplication applied to classification (MICMAC) analysis, the barriers were modeled, and finally, strategies were formulated using a concept map to handle the barriers in the blockchain-IoT integrated architecture for a green supply chain.

This paper presents the research on barriers that can be considered for incorporating blockchain and IoT in the green supply chain. It was found from the TISM model that environmental concerns are Level-1 barriers and need to be addressed by developing appropriate technology and allocating funds for the same. An integrated ecosystem with blockchain and IoT is developed.

The focus of this study was on the challenges of blockchain and IoT; hence, it is required to extend the research and find challenges for different industries and also analyze the criteria using other multi-criteria decision-making (MCDM) methods. Further research is required for the integration of blockchain-IoT with supply chain functions.

The transformation of a traditional supply chain into a green supply chain is possible with the integration of technologies. This research work and the strategies developed are useful to managers and practitioners working on technology implementation. Planning resources and addressing key barriers is possible with the concept maps and architecture developed.

Green supply chain management (SCM) is gaining importance in industry as well as the academic sector due to government Policies and norms worldwide for reducing emissions and encouraging environment-friendly production systems. Incorporating blockchain and IoT in a green supply chain will further digitize and increase transparency in supply chains.

We have done a categorization of all barriers based on the expert survey by academicians and industry experts from industries in India. The concept map helps in identifying possible solutions for the challenges and initiatives to be taken for the smooth integration of technologies in the green supply chain.

This study introduces three variables related to brands that have the potential to enhance university students' advocacy intentions. The research explores how university brand identification, the perceived prestige of the university brand and the social benefits associated with the university brand impact students' advocacy intentions. Additionally, the study examines the moderating role of gender in these relationships.

Cross-sectional surveys of 326 undergraduate students enrolled in a Spanish university, and structural equation modeling was used to test and validate the conceptual model.

The findings from the structural equation modeling indicate that university brand identification, perceived university brand prestige and university brand social benefits significantly influence students' advocacy intentions. Furthermore, the multigroup analysis reveals a gender difference in the factors influencing advocacy intentions. Female students demonstrate significance in all three antecedents, whereas male students only show significance in university brand identification and perceived university brand prestige.

The current study's findings provide several insights for higher education institutions in developing enduring and committed relationships with their students.

This study offers relevant insights into the body of research on university branding, explaining the students' advocacy intentions through the variables of university brand identification, perceived university brand prestige and university brand social benefits. Also, this study is a novelty in introducing empirical evidence for the importance of the moderating role of students' gender.

The paper aims to investigate the relationship between institutions and economic growth in developing countries, considering the role of financial inclusion, education spending and military spending.

The study employs dynamic panel analysis, specifically two-step system generalized method of moments (GMM), on a sample of 61 developing countries over the period 2009–2020.

The results confirm that weak institutional quality, weak financial inclusion and increased military spending are barriers to economic growth, conversely, increased spending on education and gross capital formation contribute to economic growth in developing countries. Regarding the specific institutional factor, we find that corruption, ineffective government, voice and accountability and weak rule of law contribute negatively to growth.

The study calls for strengthening institutions so that the financial system supports economic growth and suggests increasing spending on education to improve access to and the quality of human capital, which is an important determinant of economic growth.

The study contributes to scarce literature by empirically analyzing the relationship between institutions and economic growth by considering the role of financial inclusion, public spending on education and military spending, factors that have been ignored in previous studies. In addition, the study identifies the institutional dimension that contributes to reduced economic growth in developing countries.

Sex and age estimation is important, particularly when information about the deceased is unavailable. There are limited radiological studies investigating side, sex and age differences in normal ankle morphometric parameters. The authors’ goal was to evaluate different ankle joint morphometric measurements and document variations among Egyptians.

A prospective study was conducted throughout 23 months on 203 (100 males and 103 females) adult Egyptians, aged between 20-69 years old, who were referred for a plain x-ray of bilateral normal ankle joints.

Ankle parameters showed no statistical difference between both sides, except for tarsal width (TaW) which was significantly higher on right than left side (26.92 ± 2.66 vs 26.18 ± 2.65 mm). Males showed significantly higher morphometric values except for anteroposterior gap (APG) and talus height (TaH) which were significantly higher in females (2.29 ± 0.80 vs 1.80 ± 0.61 mm and 13.01 ± 1.68 vs 11.87 ± 1.91 mm, respectively). There was significant increase in tibial arc length, APG, distance of level of MTiTh from anterior limit of mortise, distance of level of MTiTh from vertex of mortise, sagittal distance between tibial and talar vertices and sagittal radius of trochlea tali arc in old age group compared to young one. A significant decrease in tibial width, malleolar width, TaW and TaH was noted in old age group compared to young one.

Ankle joints of both sides are mostly symmetrical; however, there are significant differences in most morphometric values due to sex and age factors. These findings may be essential during side, sex and age determination.

The purpose of this study is to examine how informational faultlines on a board affect the management of knowledge owned by directors and the consequences on organizational performance. In this study, informational faultlines are defined as hypothetical lines that divide a group into relatively homogeneous subgroups based on the alignment of several informational attributes among board members.

The study uses unique hand-collected panel data covering 7,247 board members at 106 publicly traded firms to provide strong support for the hypothesized U-shaped relationship. The authors use a fixed effects approach and a system generalized method of moments approach to test the hypothesis.

The study finds that the relationship between informational faultlines on a board and organizational performance is U shaped, with the least optimal organizational performance experienced when boards have moderate informational faultlines. More specifically, informational faultlines within boards are negatively related to organizational performance across the weak-to-moderate range of informational faultlines and positively related to organizational performance across the moderate-to-strong range.

By explaining the mechanisms through which informational faultlines are related to organizational performance, the authors contribute to the literature in a number of ways. By conceptualizing how the management of knowledge plays an important role in the particular setting of corporate boards, the authors add not only to literature on knowledge management but also to the faultline and corporate governance literature.

This study offers a rationale for prior mixed findings by providing an alternative theoretical basis to explain the effect of informational faultlines within boards on organizational performance. To advance the field, the authors build on the concept of knowledge demonstrability to illuminate how informational faultlines affect the management of knowledge within boards, which will translate to organizational performance.

The present study reviews the literature on the history and evolution of investment strategies in the stock market for the period from 1900 to 2022. Conflicts and relationships arising from such diverse seminal studies have been identified to address the research gaps.

The studies for this review were identified and screened from electronic databases to compile a comprehensive list of 200 relevant studies for inclusion in this review and summarized for the cognizance of researchers.

The study finds a coherence to complex theoretical documentation of more than a century of evolution on investment strategy in stock markets, capturing the characteristics of time with a chronological study of events.

There were complications in locating unpublished studies leading to biases like publication bias, the reluctance of editors to publish studies, which do not reveal statistically significant differences, and English language bias.

Practitioners can refine investment strategies by incorporating behavioral finance insights and recognizing the influence of psychological biases. Strategies span value, growth, contrarian, or momentum indicators. Mitigating overconfidence bias supports effective risk management. Social media sentiment analysis facilitates real-time decision-making. Adapting to evolving market liquidity curbs volatility risks. Identifying biases guides investor education initiatives.

This paper is an original attempt to pictorially depict the seminal works in stock market investment strategies of more than a hundred years.