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The credit of agricultural product quality and safety reflects the ability of the main actors involved in the supply chain to provide reliable agricultural products to consumers. To fundamentally solve the problem of agricultural product quality and safety, it is worth studying how to make the credit awareness and integrity self-discipline of the supply chain agriculture-related subjects strengthened and the role and value of credit supervision given full play. Starting from the application of blockchain in the agricultural product supply chain, this paper aims to investigate the main factors affecting the credit regulation of agricultural product quality.

Using the DEMATEL-ISM (decision-making trial and evaluation laboratory–interpretative structural modeling) method, we analyze the credit influencing factors of agricultural quality and safety empowered by blockchain technology, find the causal relationship between the crucial influencing factors and deeply explore the hierarchical transmission relationship between the influencing factors. Then, the path analysis in structural equation modeling is utilized to verify and measure the significance and effect value of the transmission relationship among the crucial influencing factors of credit regulation.

The results show that the quality and safety credit regulation of agricultural products is influenced by a combination of direct and deep influencing factors. Long-term stable cooperative relationship, Quality and safety credit evaluation, Supply chain risk control ability, Quality and safety testing, Constraints of the smart contract are the main influence path of blockchain embedded in agricultural product supply chain quality and safety credit supervision.

Credit supervision is an important means to improve the ability and level of social governance and standardize the market order. From the perspective of blockchain embedded in the agricultural supply chain, the regulatory body is transformed from the product body to the supply chain body. Take the credit supervision of supply chain subjects as the basis of agricultural product quality supervision. With the help of blockchain technology to improve the effectiveness of agricultural product quality and safety credit supervision, credit supervision is used to constrain and incentivize the behavior of agricultural subjects.

Data sharing is increasingly being recognized as an essential component of scholarly research and publishing. Sharing data improves results and propels research and discovery forward. Given the importance of data sharing, the purpose of the study is to unveil the present scenario of research data repositories (RDR) and sheds light on strategies and tactics followed by different countries for efficient organization and optimal use of scientific literature.

The data for the study is collected from registry of RDR (re3data registry) (re3data.org), which covers RDR from different academic disciplines and provides filtration options “Search” and “Browse” to access the repositories. Using these filtration options, the researchers collected metadata of repositories i.e. country wise contribution, content-type data, repository language interface, software usage, metadata standards and data access type. Furthermore, the data was exported to Google Sheets for analysis and visualization.

The re3data registry holds a rich and diverse collection of data repositories from the majority of countries all over the world. It is revealed that English is the dominant language, and the most widely used software for the creation of data repositories are “DataVerse”, followed by “Dspace” and “MySQL”. The most frequently used metadata standards are “Dublin Core” and “Datacite metadata schema”. The majority of repositories are open, with more than half of the repositories being “disciplinary” in nature, and the most significant data sources include “scientific and statistical data” followed by “standard office documents”.

The main limitation of the study is that the findings are based on the data collected through a single registry of repositories, and only a few characteristic features were investigated.

The study will benefit all countries with a small number of data repositories or no repositories at all, with tools and techniques used by the top repositories to ensure long-term storage and accessibility to research data. In addition to this, the study provides a global overview of RDR and its characteristic features.

Barriers to adequate healthcare in rural areas remain a grand challenge for local healthcare systems. In addition to patients' travel burdens, lack of health insurance, and lower health literacy, rural healthcare systems also experience significant resource shortages, as well as issues with recruitment and retention of healthcare providers, particularly specialists. These factors combined result in complex change management-focused challenges for rural healthcare systems. Change management initiatives are often resource intensive, and in rural health organizations already strapped for resources, it may be particularly risky to embark on change initiatives. One way to address these change management concerns is by leveraging socio-technical simulation models to estimate techno-economic feasibility (e.g., is it technologically feasible, and is it economical?) as well as socio-utility feasibility (e.g., how will the changes be utilized?). We present a framework for how healthcare systems can integrate modeling and simulation techniques from systems engineering into a change management process. Modeling and simulation are particularly useful for investigating the amount of uncertainty about potential outcomes, guiding decision-making that considers different scenarios, and validating theories to determine if they accurately reflect real-life processes. The results of these simulations can be integrated into critical change management recommendations related to developing readiness for change and addressing resistance to change. As part of our integration, we present a case study showcasing how simulation modeling has been used to determine feasibility and potential resistance to change considerations for implementing a mobile radiation oncology unit. Recommendations and implications are discussed.

Climate change is a problem that concerns all of us. Despite the information produced by organizations such as the Expert Team on Climate Change Detection and Indices and the United Nations, only a few cities have been planned taking into account the climate changes indices. This paper aims to study climatic variations, how climate conditions might change in the future and how these changes will affect the activities and living conditions in cities, specifically focusing on Mexico city.

In this approach, two distinct machine learning regression models, k-Nearest Neighbors and Support Vector Regression, were used to predict variations in climate change indices within select urban areas of Mexico city. The calculated indices are based on maximum, minimum and average temperature data collected from the National Water Commission in Mexico and the Scientific Research Center of Ensenada. The methodology involves pre-processing temperature data to create a training data set for regression algorithms. It then computes predictions for each temperature parameter and ultimately assesses the performance of these algorithms based on precision metrics scores.

This paper combines a geospatial perspective with computational tools and machine learning algorithms. Among the two regression algorithms used, it was observed that k-Nearest Neighbors produced superior results, achieving an R² score of 0.99, in contrast to Support Vector Regression, which yielded an R² score of 0.74.

The full potential of machine learning algorithms has not been fully harnessed for predicting climate indices. This paper also identifies the strengths and weaknesses of each algorithm and how the generated estimations can then be considered in the decision-making process.

The purpose of this paper is to understand the financial opaqueness established through offshore businesses and financial secrecy through the requirements of information exchanges, and their deadly combination for facilitating money-laundering activities and tax evasion. It also puts into light some key recommendations for a country like Nepal that has been struggling to put adequate efforts into understanding financial opacity and secrecy.

This paper navigates through global issues on layering through opaque corporate structures, and mechanisms required for information exchange so as to figure out solutions and challenges to address them by developing countries like Nepal, with specific actions pertaining to Nepal.

Understanding financial opacity and secrecy is a prerequisite to tackling financial crimes. While focusing on global solutions and inherent challenges regarding such issues, concerted efforts are required to capacitate a country on contextual matters.

This work is an original work with an analysis of a global issue in an interconnected world with solutions catered to the local contexts of Nepal.

Drug use in prisons remains a public health concern because it is often the place of drug initiation. The purpose of this study was to analyze the drug use in prison in Burkina Faso.

We conducted cross-sectional study in the prison of Ouagadougou. The adult prisoners (male and female) incarcerated for more than one month at the largest prison of Burkina Faso were included in the study. Participants were selected using a systematic random sampling. Data were collected from October 28 to November 26, 2018. The face-to-face interviews were conducted in the prison grounds. Logistic multivariate regression was used to identify factors associated with in prison drug use. All analysis was done using Stata.

A total of 379 prisoners were included in this study. Approximately one-third inmates (32.71%; n = 124) experienced illicit drug in lifetime. Nearly one-third (28.76%; n = 109) of the prisoners were drug users before incarceration and 11.87% (n = 45) used drug inside the prison, of which 33.33% (n = 15) initiated drug use in the prison. Cannabis was the first drug used by the prisoners (71.11%) followed by tramadol (62.22%), diazepam (13.33%) and cocaine (2.22%). Four prisoners (3.63%) had reported Heroin use before incarceration. Cannabis was mainly smoked. Tramadol, diazepam and amphetamines were swallowed or mixed with food. Cocaine is smoked and snorted. Case of injection of cocaine and heroin was reported before incarceration. Main factors independently associated with drug use in prison is drug use before prison and young age of inmates. Indeed, inmates who had reported drug use before prison had 4.01 time {adjusted odd ratio (AOR: 4.01 [95% CI: 1.91–8.41])} higher odds to use drug in prison.

To conduct the interviews in the prison grounds could be a limitation due to social desirability bias. Indeed, the prisoners may understate drug use in prison for the fear of likely additional sentence. Availability of biological tests for drug markers might help addressed this bias. Nevertheless, the findings of this study should help to plan effective drug use prevention and care programs for prisoners.

The actions must include the implementation of a medical and psychological care in continuum of healthcare system in Burkina Faso. This system should include screening at entry and adequate health and psychological care in prison for drug users for an effective control of drugs use in prison.

Most of these drug users in prison have a low level of education and are unemployed. Education activities and training on occupational activities to prepare drug users for a successful social reintegration less dependent on drugs is essential. This study can be a basis to explore more possibilities and find out what is available to help those with substance use disorder, manage these cases in prison and prevent relapse on release.

To the best of the authors’ knowledge, this study is the first study on drug use in prison in Burkina Faso. It indicates that the repressive strategy against drug use seems ineffective because former users continue their consumption inside and also new users are initiated to use drugs in prison.

The reason for concern is the rapid decline in loans to small enterprises which is critical to their performance, compared to large businesses following the periods of banking reformations in Nigeria. Thus, the purpose of this paper is to investigate the influence of risk perception on bank lending behaviour to small enterprises. It also investigates the impact of government intervention, consolidation and recapitalization on the relationship between risk perception and bank lending behaviour to small enterprise.

This study empirically analysed (ordinary least square) secondary data obtained from the Central Bank of Nigeria Statistical Bulletins, Annual Statement of Accounts covering the period 1992–2020.

The results show that the absence of government interventions and the presence of banking reformations have statistically negative significant effect on bank lending to small enterprises. The findings challenge the argument that generally assumes risk aversion of banks towards small enterprise lending because of small enterprise’s inability to prove their credit worthiness and consequently constraining access to finance to the sector. Instead, the results and analysis from this study found theoretical support for the variation of bank behaviour in lending to small enterprises depending on the status of wealth of the financial system.

A key lesson from this study for government concerned about promoting performance of the small enterprise sector is that regulating and enforcing lending requirements on access to debt financing of the sector is necessary if constraints in access debt finance is to be eliminated. Second, while strategies such as bank consolidation, recapitalization may help strengthen and make financially robust the banking system; it places the banks in a gain position where losses looms to them than gain.

This study challenges the argument that generally assumes risk aversion of banks towards small enterprise lending as a result of inability to prove their credit worthiness and consequently constraining access to finance to the sector. Instead, the results and analysis from this study reveal a variation in lending to small enterprises and suggests that the position of the bank in relation to a reference point influences how risk is perceived by the bank and thus impacts on their risk decision-making behaviour.

The purpose of this study is shed light on the underlying forces behind entrepreneurship within a regional innovation system (RIS) in a remote rural region. The authors examine the following questions: Which are the main underlying forces behind the entrepreneurial process in a rural RIS characterized by traditionally low-tech, small-scale businesses? How can the development of a low-tech regional innovation system be conceptualized?

The design of the study is based on entrepreneurship theory. Data analysis followed practices used in phenomenography, a research approach used to analyse and identify commonalities and variations in populations' perceptions of a certain phenomenon. Data are composed using semi-structured interviews and a database composed of company information of all firms in the population.

A proactive mobilization of regional stakeholders and resources can be an important driving force behind the entrepreneurial process and generation of a rural RIS. Innovation can be generated within low-tech industries turning the rural context into an asset. An RIS in a remote rural context can be initiated and orchestrated by regional authorities, but knowledge brokering and orchestration can also be managed by networks of small-scale businesses brought together by mutual benefit and common interests.

Regional innovation systems theory is most often used to study high-tech industries. But by combining regional innovation systems with rural entrepreneurship and entrepreneurship context theory is a fruitful avenue to understand the role of rural entrepreneurship in regional development, even in remote and peripheral regions. Innovation does not need to entail high-tech international environments; it can appear as the result of efforts in low-tech industries in rural and remote environments. The authors’ findings need to be scrutinized; therefore, the authors call for more research on regional innovation systems in rural environments.

It is possible for regional authorities to orchestrate a development process through the actions of a strong regional agent but also by supporting the creation of networks of small businesses that are built on trust and common interests.

This study contributes to the literature with a new perspective to the study of entrepreneurship and of regional innovation systems. Entrepreneurship research with focus on rural contexts most often highlight limits to entrepreneurship and see entrepreneurship as “just running a business”. A perspective that starts from innovation and innovative behaviour, despite the rural context and embedded resources, helps to generate new knowledge that can enrich the understanding of entrepreneurship and also be the foundation for more precise business development policies in rural settings.