The research was designed to identify and analyze the need for School MIS at secondary and higher secondary school levels in Punjab. Three separate questionnaires were developed for school principals, teachers and parents. The population of the study was the principals, teachers and parent members of the school councils of public schools. Punjab has 36 districts and the study was delimited to 12 districts selected randomly. A 10% sample from each of twelve districts was taken. Findings of the study indicated that there is no type of school-based MIS available in public schools and there is a dire need of school-based MIS to easily record and retrieve information. It was concluded that school efficiency cannot be improved significantly without introducing school-based MIS in public schools of Punjab
Strong governance is vital for developing environmental policies to promote renewable energy consumption and discourage nonrenewable energy sources. The present research explores the effect of economic growth and different governance indicators on renewable and nonrenewable energy consumption in Pakistan, India, Bangladesh, and Sri Lanka using data from 1996 to 2019. For this purpose, the study uses different econometric techniques to find the long-term effects of the rule of law, regulatory quality, corruption control, government effectiveness, political stability, voice and accountability, and economic growth on oil, natural gas, coal, hydroelectricity, and renewable energy consumption. The results show that economic growth has a positive impact on all investigated renewable and nonrenewable energy sources. Additionally, regulatory quality measures also increase all types of renewable and nonrenewable energy consumption. Except for natural gas, the impact of the rule of law is negative, and government effectiveness positively affects all energy sources. Control of corruption has a positive effect on natural gas consumption. Political stability has a negative effect on nonrenewable energy sources and a positive impact on renewable energy sources. The magnitudes of the effects of economic growth and most governance indicators are found to be larger on nonrenewable sources than renewable sources. The testing of the energy consumption and governance nexus is scant in global literature and is missing in South Asian literature. Hence, the study results contribute to how South Asian economies can be more sustainable in energy use by enhancing governance indicators in the economies. Particularly, the results imply that these countries should focus on improving the rule of law, corruption control, governance, regulatory quality, political stability, and economic growth to help maintain a sustainable balance of renewable and nonrenewable energy sources. Moreover, this issue needs further attention in developing countries, as governance indicators would play an effective role in promoting sustainable energy.
The purpose of the study was to determine the impact of nepotism on employment status of fresh graduates in public sector institution along with other relevant factors. Current study is the first study in which the impact of nepotism was estimated by adding different factors responsible for nepotism by using primary data. Primary data were collected from 400 respondents through survey research. Logit model was applied to check the probability for a graduate. The results showed significant impact of nepotism on probability job of a graduate in public sector institutions. Political affiliation has a strong positive and significant impact on hiring process to make a candidate successful in getting job in public sector institutions. The nature of home institution also has an impact on probability of getting a job in public sector institutions. The candidates graduated from the public sector university have more probability to get a job. The graduates from private sector institutions are unable to be selected in public sector institutions as compared to graduates from public sector institutions. Financially strong families can easily influence on the hiring process for obtaining a job in public sector. The positive and significant impact of land on probability of getting a job has proven the presence of the element of nepotism in hiring process.
Big data analytics and artificial intelligence are revolutionizing the global healthcare industry. As the world accumulates unfathomable volumes of data and health technology grows more and more critical to the advancement of medicine, policymakers and regulators are faced with tough challenges around data security and data privacy. This paper reviews existing regulatory frameworks for artificial intelligence-based medical devices and health data privacy in Bangladesh. The study is legal research employing a comparative approach where data is collected from primary and secondary legal materials and filtered based on policies relating to medical data privacy and medical device regulation of Bangladesh. Such policies are then compared with benchmark policies of the European Union and the USA to test the adequacy of the present regulatory framework of Bangladesh and identify the gaps in the current regulation. The study highlights the gaps in policy and regulation in Bangladesh that are hampering the widespread adoption of big data analytics and artificial intelligence in the industry. Despite the vast benefits that big data would bring to Bangladesh's healthcare industry, it lacks the proper data governance and legal framework necessary to gain consumer trust and move forward. Policymakers and regulators must work collaboratively with clinicians, patients and industry to adopt a new regulatory framework that harnesses the potential of big data but ensures adequate privacy and security of personal data. The article opens valuable insight to regulators, academicians, researchers and legal practitioners regarding the present regulatory loopholes in Bangladesh involving exploiting the promise of big data in the medical field. The study concludes with the recommendation for future research into the area of privacy as it relates to artificial intelligence-based medical devices should consult the patients' perspective by employing quantitative analysis research methodology.
This research develops a dual-cycle ELV recycling and remanufacturing system to better understand and improve the efficiency of the ELV recycling and remanufacturing businesses. For the flawless operation of this system, the researchers employed evolutionary game theory to establish a game model between original vehicle manufacturers (OVMs) and third-party recyclers with the government involved. This research presents evolutionary stable strategies (ESS) that could promote an ELV recycling and remanufacturing system. Results show that OVMs' expected profit difference between choosing and not choosing authorization is crucial in their ESS. The licensing fee plays a part of OVMs' expected profit difference. Based on the results, optimal ESS could be achieved when the OVMs' expected profit difference between choosing authorization and not choosing authorization and the third-party recyclers' profit when paying the licensing fee are both positive. Then, the two groups' involvement in dual-cycle ELV recycling and the remanufacturing system can be ensured. This research implicates the government to devise appropriate reward and punishment strategy to encourage OVMs and third-party recyclers to collaborate for efficient recycling and remanufacturing systems. Particularly, the government is suggested to impose strict restrictions on OVMs to carry ELV recycling and provide support to promote recycling quantity standards. Hence, the ELV recycling and remanufacturing system would be strengthened, thus improving waste management which is crucial for both environmental and resource efficiency.
