Collaboration among industry, universities, and research is crucial for building an innovative nation. Although industry-university-research collaborative innovation (IURCI) and time-space convergence can drive innovation, increase productivity, and spur economic development, their effects on the regional economy have not been thoroughly examined in existing literature. Therefore, this study investigates the impact of industry-university-research collaborative innovation (IURCI) and time-space convergence on economic development in China. Specifically, we focus on local-level cities in the Chengdu-Chongqing Economic Circle (CCEC) and construct an evaluation index system and time-space convergence model to measure the effects of IURCI and time-space convergence on economic development from 2007 to 2021. Our findings indicate that the efficacy of IURCI on economic development in China follows an inverted U-shaped curve, meaning that the marginal impact of IURC may decrease as more creative funds are deployed. Furthermore, the positive marginal effect of inventive talent input may decrease when it surpasses a certain value in an open innovation environment. The spatiotemporal convergence of collaborative innovation and development levels of IURCI in the CCEC shows significant differences. Regionally, the development level of IURCI in different regions exhibits significant differences in state and speed of convergence. In the southern Sichuan urban agglomeration, the collaborative innovation level of industry, education, and research follows an evolutionary process from convergence to divergence and then to convergence. Policymakers should pay close attention to the spatial effect of high-level development of regional IURCI and promote regions with higher development to drive regions with relatively weak development levels.
The use of healthcare data analytics is anticipated to play a significant role in future public health policy formulation. Therefore, this study examines how big data analytics (BDA) may be methodically incorporated into various phases of the health policy cycle for fact-based and precise health policy decision-making. So, this study explores the potential of BDA for accurate and rapid policy-making processes in the healthcare industry. A systematic review of literature spanning 22 years (from January 2001 to January 2023) has been conducted using the PRISMA approach to develop a conceptual framework. The study introduces the emerging topic of BDA in healthcare policy, goes over the advantages, presents a framework, advances instances from the literature, reveals difficulties and provides recommendations. This study argues that BDA has the ability to transform the conventional policy-making process into data-driven process, which helps to make accurate health policy decision. In addition, this study contends that BDA is applicable to the different stages of health policy cycle, namely policy identification, agenda setting as well as policy formulation, implementation and evaluation. Currently, descriptive, predictive and prescriptive analytics are used for public health policy decisions on data obtained from several common health-related big data sources like electronic health reports, public health records, patient and clinical data, and government and social networking sites. To effectively utilize all of the data, it is necessary to overcome the computational, algorithmic and technological obstacles that define today's extremely heterogeneous data landscape, as well as a variety of legal, normative, governance and policy limitations. Big data can only fulfill its full potential if data are made available and shared. This enables public health institutions and policymakers to evaluate the impact and risk of policy changes at the population level.
In Bangladesh, many people are being displaced in riverine island (char) areas every year due to climate change and its associated natural catastrophes. This study intends to investigate the impact of climate change on internally displaced char people's lives and livelihoods along with local adaptation strategies and hindrances to the coping mechanism. Data have been collected from 280 internally displaced households in two sub-districts. A mixed-method approach has been considered combined with qualitative and quantitative methods. The results disclose that frequent flooding, riverbank erosion, and crop loss are the leading causes for relocation, and social relations are impeded in the new place of residence. Increasing summer and winter temperatures, recurrent flooding, severity of riverbank erosion, and expanding disease outbreaks are also important indicators of climate change identified by displaced people, which are consistent with observed data. This study also reveals that almost all households come across severe livelihood issues like food shortage, unemployment and income loss, and housing and sanitation problems due to the changing climate associated with disasters in the former and present places. In response to this, the displaced people acclimatize applying numerous adaptation strategies in order to boost the livelihood resilience against climate change. However, fragile housing, financial conditions, and lack of own land are still the highest impediments to the sustainability of adaptation. Therefore, along with the government, several organizations should implement a dynamic resettlement project through appropriate scrutiny to eradicate the livelihood complications of internally displaced people.
A scientific performance evaluation model is necessary to establish a performance evaluation index system for compulsory education in ethnic areas and to conduct objective and impartial evaluations. After conducting theoretical analysis and reviewing literature, it was determined that existing educational input performance evaluation models are general and fail to reflect the unique characteristics of compulsory education development in ethnic areas of China. Therefore, this study intends to improve their self-adaptability and degree of fit. Based on the features of China's ethnic areas and the current situation of compulsory education development, a trinity evaluation model of compulsory education input performance in ethnic regions was constructed using the classical performance evaluation theoretical framework. This model includes the "implementation topic - target concept - performance dimension." The government is the main organization responsible for organizing and implementing the entire performance evaluation, with publicness and responsiveness as the value idea of evaluation. The "4E″ of enough, equity, efficiency, and effectiveness are the evaluation objectives, and input, allocation, output, and effect are the dimensions of the building of the performance evaluation index system. The "4E″ evaluation objectives are integrated into the performance evaluation dimensions and index system. The reconstructed theoretical model of performance evaluation combines universality and specificity, highlights the dual attributes of "tool-value," realizes the organic combination of internal and external performance evaluation, illustrates the overall performance evaluation process and ensures objective, fair, and accurate performance evaluation results. It provides useful guidelines for further optimizing compulsory education investment policies and promoting high-quality and well-balanced compulsory education in China's ethnic areas.
This study analyses environmental sustainability indicators (ESIs) and explores their governance challenges in developing countries (Bangladesh and Thailand) and advances possible remedies in light of the practices of a developed country (Japan). A comparative analysis of countries' performance based on the ESIs could help identify useful practices from countries with high ESI to improve the poor ESI countries. While it is broadly understood that renewable energy and effective governance support environmental sustainability, our findings extend this knowledge by detailing how these factors interact specifically within the contexts of developed and developing nations. The analysis delineates the complex relationship between GDP growth, fossil fuel reliance, and sustainability efforts, offering a detailed examination of the variance in ESI performance across these countries. Beyond established notions, this study empirically validates the relationships between environmental sustainability (ES) and its influencing factors, providing a country-specific analysis that emphasizes the differential impact of renewable energy adoption, governance quality, and economic policies on environmental sustainability in Japan, Bangladesh, and Thailand. The results also revealed that Bangladesh's performance in terms of majority ESIs ranges from bad to worse, while Japan exhibits good performance in all its ESI indicators except for emissions. Thailand's ESI performance indicates its vulnerability to climate disasters and slow growth of renewable energy. The ESI measures of Thailand have shown its susceptibility to climate-related calamities and a slowdown in the rate of renewable energy implementation. A noticeable discrepancy in the execution of regulatory frameworks was noted between developing countries, such as Bangladesh, and industrialized ones, such as Japan. The outstanding results of Japan's ESI may be credited to the successful practices of its citizens and their strong devotion to the rule of law.
Food insecurity is one of the rising problems in Bangladesh, and it is severely prevalent among informal migrant workers. In this case, the COVID-19 pandemic has multiplied the food insecurity of informal migrant workers. This study explores and synthesizes the COVID-19 induced food insecurity impact among informal migrants and recommends policy actions to tackle the COVID-19 led food crisis in Bangladesh. A qualitative research approach, including in-depth interviews, four FGDs, and participant observation, has been applied to data collection from different parts of Dhaka city. A thematic approach to interpretive phenomenological analysis is followed in this study. The results show that COVID-19 induced lockdown significantly affects informal migrants' household food security. Most participants report severe complications due to food insecurity like consuming less food, price hiking, no fish or meat, potato, and vegetable. Food insecurity leads to migrant's chronic food shortage, starvation, malnutrition of mother and children, and unhealthy food. As a result, the way of life of informal migrants has been directed to more fragility and vulnerability during the pandemic; even they are not affordable to maintain a minimal level of family affairs and necessity. The findings of this study would be essential guidelines for the governmental and non-governmental organizations and development practitioners to address the food insecurity situations.