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The present study investigates the impact of digital entrepreneurial education and training and its impact on the digital entrepreneurial intention (EI) through the mediating character of entrepreneurial competence.

A total of 391 survey responses were collected from employees using convenient and snowball sampling methods.

Digital entrepreneurial education and training showed a positive influence on entrepreneurial competence and EI, with entrepreneurial competence mediating the relationship between digital entrepreneurial education and training practices and EI.

This study is intended to assist the development of digital entrepreneurs. The implications of this study are also useful for governments, entrepreneurs, venture capitalists, angel investors and various international development institutions.

The novelty of this study relates to exploring the relationship between digital entrepreneurial education and training, entrepreneurial competence and digital EI.

This paper examines the decline of the largest working parliamentary democracy in India overtime, but accelerating since 2014 as the Bharatiya Janata Party (BJP), under the leadership of Prime Minister Narendra Modi at the Center (as the federal government is commonly known).

It is eclectic. Original constitution, along with commentaries, are studied. News outlets, government pronouncements, journal articles, and other media outlets — electronic and print — are also sourced.

The findings show how three important features in democracy — elections and their outcomes, control of information, and suppression of dissent are widely used to undermine constitutional democracy.

Democracy can be undermined without altering the Constitution itself. It also explains the irony of Modi’s popularity, given the undemocratic practices. As he may continue in office for some time to come, commanding a log-rolling majority, the need of the hour is a united, constructive and effective opposition to ensure a healthy working democracy.

Due to unceasing declination in environment, sustainable agro-food supply chains have become a topic of concern to business, government organizations and customers. The purpose of this study is to examine a problem associated with sustainable network design in context of Indian agro-food grain supply chain.

A mixed integer nonlinear programming (MINLP) model is suggested to apprehend the major complications related with two-echelon food grain supply chain along with sustainability aspects (carbon emissions). Genetic algorithm (GA) and quantum-based genetic algorithm (Q-GA), two meta-heuristic algorithms and LINGO 18 (traditional approach) are employed to establish the vehicle allocation and selection of orders set.

The model minimizes the total transportation cost and carbon emission tax in gathering food grains from farmers to the hubs and later to the selected demand points (warehouses). The simulated data are adopted to test and validate the suggested model. The computational experiments concede that the performance of LINGO is superior than meta-heuristic algorithms (GA and Q-GA) in terms of solution obtained, but there is trade-off with respect to computational time.

In literature, inadequate study has been perceived on defining environmental sustainable issues connected with agro-food supply chain from farmer to final distribution centers. A MINLP model has been formulated as practical scenario for central part of India that captures all the major complexities to make the system more efficient. This study is regulated to agro-food Indian industries.

The suggested network design problem is an innovative approach to design distribution systems from farmers to the hubs and later to the selected warehouses. This study considerably assists the organizations to design their distribution network more efficiently.

This study aims to develop a comprehensive conceptual framework that serves as a foundation for identifying most critical delay risk drivers for Building Information Modelling (BIM)-based construction projects.

A systematic review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to identify key delay risk drivers in BIM-based construction projects that have significant impact on the performance of delay risk predictive modelling techniques.

The results show that contractor related driver and external related driver are the most important delay driver categories to be considered when developing delay risk predictive models for BIM-based construction projects.

This study contributes to the body of knowledge by filling the gap in lack of a conceptual framework for selecting key delay risk drivers for BIM-based construction projects, which has hampered scientific progress toward development of extremely effective delay risk predictive models for BIM-based construction projects. Furthermore, this study's analyses further confirmed a positive effect of BIM on construction project delay.

This research aims to explore the significance of cooperative efforts in promoting financial participation to enhance the socio-economic empowerment of the rural Muslims.

The primary study with a structured questionnaire has been conducted taking a sample of 398 rural Muslim respondents from various rural regions of south India through proportionate stratified sampling techniques. Regression analysis, paired sample t-test and structural equation modelling (SEM) through statistical package for social sciences (SPSS) 26 & SPSS analysis of moment structures (AMOS) 23 software have been implemented to test the relationship.

The research outcome demonstrated a remarkable difference in the rural Muslim’s socio-economic conditions before and after availing the loans from cooperatives. Consequently, an extension of cooperative efforts widens the scope of financial participation which again has positively enhanced rural Muslim’s socio-economic empowerment.

This study will help various policymakers, academicians and communities to take necessary action for the upliftment of a particular community. The research further adds on to the existing research on the need and importance of cooperative efforts as an alternative finance for marginalised community in developing and emerging countries.

The result of this study is only confined to south India, posing a limitation for the study. Apart from the geographical restriction, the study solemnly covers the rural Muslim community extracting other sections of the society. Hence, for more generalisable pictures of the current results, further research is recommended from other stakeholders’ perspectives.

This paper aims to find the best tools to influence the improvement of sustainability in food supply chains (FSCs) by conducting a systematic review of articles. The reader will learn how the different industry 4.0 tools (I4.0T) benefit the FSC and the limitations of each tool.

A review of 436 articles published during the period 2019 to 2022 referenced in the Scopus and Web of Science databases was performed. The review was limited to articles published in English and directly related to Industry 4.0, circular economy and sustainability in the food supply chain.

The results show different contributions of I4.0, with some being more influential than others in improving sustainability in FSCs; for example, Internet of Things and Blockchain have been shown to contribute more toward transparency, traceability, process optimization and waste reduction.

The paper's contribution consisted of ranking according to their importance and the I4.0T that affect sustainability in FSCs by classifying the aspects of each tool and the sustainability factors through a categorization by the Analysis Hierarchy Process.

The study explores the perspectives of college students on the pedagogical shift as well as frequent transitions between online and offline learning modes during the COVID-19 pandemic in Kerala, the most literate state in India.

A descriptive cross-sectional study was conducted among 1,366 college students in Kerala during December 2021. A pre-tested questionnaire was sent using Google Forms to students of arts and science colleges. The authors analyzed quantitative data using descriptive statistics and qualitative data using thematic content analysis.

The reported advantages of online learning were increased technical skill, flexibility in study time, effectiveness in bridging the gap of the missed academic period and provision of attending more educational webinars. Students expressed concerns of increased workload, difficulty in concentration due to family circumstances, academic incompetency, uncleared doubts and addiction to mobile phones and social media during the online classes. The main advantages reported for switching to an offline learning mode were enhanced social interaction, effective learning, better concentration and reduced stress. The reported challenges of offline classes were fear of getting the disease, concern of maintaining social distancing and difficulty in wearing masks during the classes. The shift in offline to online learning and vice versa was perceived as a difficult process for the students as it took a considerable time for them to adjust to the switching process of learning.

Students' concerns regarding transition between different learning modes provide important information to educators to better understand and support the needs of students during the pandemic situations.

Even with the Saudi Arabian Government's discretionary measures to mitigate the spread of the coronavirus disease 2019 (COVID-19), the economic sectors were not spared from the damage. Thus, the paper aims to use a computable general equilibrium (CGE) model to evaluate the impact of COVID-19 on the Kingdom of Saudi Arabia's (KSA) economy, with a special focus on small and medium enterprises (SMEs) and production. These influence the level of poverty.

The paper adopted the social accounting matrix (SAM) for Saudi Arabia built in 2021 by Imtithal Althumairi from Saudi Arabia's 2017 SAM. The model represents a snapshot of the economy and different flows that exist within the tasks and institutions. Two simulations (mild and severe) were conducted because of the focus on the distributional outcomes.

Decrease in job creation and economic growth were significant evidence from the study's findings. Findings show that more families hit below the poverty line because the negative impacts of the pandemic have shifted the income allocation curve. Findings show that the weakest of the poor are mitigated by government social grants during the pandemic.

The paper is restricted to the relevant literature relating to the impact of COVID-19 on Saudi Arabia's economy and evaluated using the SAM model. Moreover, the COVID-19 is still an ongoing scenario; thus, the model should be updated as data utilised for the operationalisation are made available.

The information from the suggested model can be suitable to measure the degree of the harm, and thus, the likely extent of the desirable policy feedback. Also, the model can be updated, as data are made available and formulated policies based on the updated data implemented by the policymakers.

Apart from the recovery planning of SMEs during the pandemic, the paper intends to stir up Saudi Arabia's policymakers through the macro-micro model to recovery planning and resilience of the economy with emphasis on mitigating unemployment.