Policy Suggestions Research Articles

Exploration of the model of deepen industry–education integration in the digital economy era

PurposeWhile the industry–education integration has achieved significant results, it also faces many prominent problems. The current problems include some projects prioritizing research and development over education, insufficient breadth and depth of cooperation and a lack of quality monitoring and evaluation mechanisms. Breaking through these problems to deepen industry–education integration is an important issue that urgently needs to be studied.Design/methodology/approachTaking the second batch of 10,283 industry–education integration projects of the Ministry of Education in 2019 as a case study, the problems existing in the Chinese industry–education integration projects are analyzed. We should make full use of the advantages and resources in the era of digital economy to seek the right path to deepen the integration of industry–education.FindingsThe study finds that governments can leverage the advantages and opportunities of the digital economy to deepen the reform of industry–education integration.Originality/valueThe policy suggestion is to deepen the mechanism of multi-party linkage and collaborative education, actively build an industry–education integration service platform and promote the two-way docking of industry education supply and demand.

Temporal Evolution Pathway and Forecasting of Non‐Fossil Energy Consumption and Carbon Emission Under China's Carbon Peak Target: A Markov Switching AR and RNN Approach

ABSTRACTTo fulfil the commitments of the Paris Agreement, China will strive to achieve carbon peak (CP) by 2030. It is necessary to identify the evolution characteristics of China's carbon emissions and provide a scientific path prediction for the formulation of reasonable emission reduction policies and measures. This study summarises and predicts the pathway of China's carbon peak (CP) using carbon emission intensity (CEI) and the percentage of non‐fossil energy consumption (NEC) as indicators, and combining MSIH(3)‐AR(2) model and recurrent neural network. The results show that: (1) China's CEI experiences a ‘low decline regime’ (LDR), a ‘medium decline regime’ (MDR) and a ‘high decline regime’ (HDR), while the share of NEC goes through a ‘low fluctuation regime’ (LFR), a ‘medium growth regime’ (MGR) and a ‘high growth regime’ (HGR). (2) For CEI, the switching probability from MDR to the HDR is 74.88%, illustrating a substantial improvement. For NEC, the switching probability from MGR to HGR is 28.92%, but the probability of returning to MGR is 61.76%, indicating an adjustment. (3) By 2030, CEI will reach 0.9896 tons/100 million CNY, decreased by 66.35% compared with 2005. While the percentage of NEC will rise to 26.61%. Based on these, policy suggestions such as strengthening the top‐level design, upgrading energy mix and accelerating green technological changes are proposed to break the bottlenecks of reaching CP and further zero carbon goal. This study is expected to provide theoretical support and empirical evidence for the achievement CP in China, and to provide empirical references for promoting the ‘dual carbon’ process in other countries.

Research on the Development of Hainan Rural Tourism and Cultural Handicrafts Under the Background of Rural Revitalization

Under the background of rural revitalization strategy, Hainan has become a hot spot of rural tourism development by virtue of its unique natural scenery and rich ethnic cultural resources. This paper aims to explore the development path and strategy of rural tourism cultural handicrafts in Hainan, analyze the development status of rural tourism in Hainan, put forward specific development strategies and policy suggestions, in order to provide theoretical support and practical guidance for the upgrading and development of rural tourism industry in Hainan.

The disappearance of ‘poverty’ in Dutch House of Representatives debates on the sexual exploitation of children in travel and tourism (SECTT)

Policymaking is storytelling; through stories, the policymaker learns of the problem, and based on these stories, the policymaker formulates a solution. In our earlier study of discussions about sexual exploitation of children in the context of travel and tourism (SECTT) in the Dutch House of Representatives, we suggest that the central story in these discussions revolves around ‘crime’ and law enforcement. Despite evidence on the links between poverty and SECTT, few policy suggestions target this risk factor. In our current study, we piece together the story told about the role of poverty in SECTT in Dutch House of Representatives debates, letters and documents from 1995 to 2020 using Faircloughian CDA enhanced with an analysis of transitivity. Our findings indicate that initially, poverty was indeed discussed as a key cause of SECTT. SECTT was understood as a fundamentally commercial practice through which children and their families aim to escape that poverty. Over time, however, the agency attributed to these families diminishes and focus shifts to (the actions of) abusers and exploiters. This development appears to be connected to shifting political orientations of consecutive Dutch government coalitions.

Analysis of green productivity in manufacturing based on different air pollution levels

China’s manufacturing industry needs to change from a high-emission model to one that is more environmentally friendly to reduce air pollution and achieve sustainable growth. Therefore, it is important to decrease manufacturing waste gas emissions by improving green productivity. This paper expands on the theories of green economic growth and sustainable development to present a framework for analysis of manufacturing green productivity at various levels of air pollution. It applies the Metafrontier Malmquist Luenberger index and SBM model to data from 30 Chinese manufacturing sectors from 2012 to 2022 to identify the obstacles to developing green productivity in the manufacturing sectors. The results show that: (1) From 2012 to 2022, the overall waste gas emission efficiency and GTFP of China’s manufacturing industry showed an increasing trend. (2) The manufacturing industry with light air pollution had the fastest growth in GTFP, followed by manufacturing with heavy air pollution, and manufacturing with moderate air pollution had the lowest. (3) The primary driver of GTFP growth is technological progress, while technical inefficiency has severely hindered GTFP growth. (4) There is a “Matthew effect” in the green productivity of China’s manufacturing industry. High waste gas emission efficiency often accompanies high levels of GTFP, and vice versa. Finally, this paper proposes policy suggestions to improve the green productivity of the manufacturing industry and reduce air pollution.

Bridging the Gap: Analyzing Healthcare Access and Inequalityin Ghana

Ghana’s National Health Insurance Scheme (NHIS) has made tremendous progress towards the aimof obtaining universal healthcare coverage. By boosting access to key healthcare services, the NHIS hasplayed a vital role in improving healthcare outcomes across the country. However, despite these advancements, major discrepancies in healthcare access exist, especially among low-income households and rural communities. These inconsistencies show fundamental injustices in the distribution of healthcare services and raise doubts about the NHIS’s potential to effectively serve themost vulnerable parts of society. This research tries to explore the difficulties of healthcare access in Ghana by delving into NHIS membership data. Through an analysis of this data, the study shows patterns of inequality related to both economic status and geographic location. By concentrating on how different economic quintiles connect with the NHIS, the research highlights important hurdles to enrollment and continuing access to healthcare. Additionally, the spatial research indicates considerable inequalities, illustrating how rural residents often experience more severe obstacles in getting healthcare compared to their urbancounterparts. Furthermore, the quality of healthcare services given under the NHIS is severely assessed. Issues such as inconsistent service delivery, poor resource allocation, and different levels of patient satisfaction emerge as important concerns that must be addressed to increase the overall success of the plan. Beyond Ghana’s boundaries, the research encompasses a comparative review of health insurancemodels from Rwanda, South Africa, Mexico, and Kenya—each country presenting a unique approach to healthcare funding and insurance coverage. Rwanda’s community-based health insurance, South Africa’s progressive changes, Mexico’s focus on service quality, and Kenya’s required enrollment offer useful lessons for resolving the inadequacies in Ghana’s NHIS. By drawing on these different models, the study intends to highlight best practices and lessons that could drive policy suggestions customizedto Ghana’s specific social, political, and economic setting. The study offers three critical policy reforms that might strengthen the NHIS and improve healthcare access across the country. Enhancing community participation is regarded as a critical way to enhance NHIS enrollment, particularly among underrepresented populations. Moreover, improving the subsidy mechanisms to better support low-income households is advocated as a manner of eliminating financial obstacles to healthcare. The study also advocates for specific measures to addressthe regional imbalances in healthcare infrastructure, noting the need for increased access in rural areas. Ultimately, these steps are not only meant to eliminate the gaps in coverage but also to secure the long-term sustainability of the NHIS, positioning it to continue offering fair healthcare to all Ghanaians. By tackling these problems and implementing targeted changes, Ghana can make considerable steps toward obtaining true universal healthcare coverage. The NHIS has the potential to become amore inclusive and resilient healthcare system, capable of fulfilling the requirements of the entire population.

Discovering temporal-spatial features of jobs-housing relationship from a regional perspective: A nationwide study

The recent developments in regionalization have redefined the concept of jobs-housing relationship, calling for reexaminations from the regional perspective. This paper studies the temporal and spatial features of jobs-housing relationship and their relations with regional mobility and regional structure in 2258 Quxians (urban districts or rural counties) across China based on 49 months of cellular signaling data. Results show that jobs-housing relationship differ between city types and have seasonal cycles and yearly trends reflecting the rhythm and development of human activity. The temporal variations in jobs-housing relationship are affected by regional mobility, and larger intercity travel volume leads to lower balance level. The spatial variations in jobs-housing relationship are influenced by the form of regional structure, as measured using the Zipf scaling exponent. More polarized regions are less balanced with exceptions in underdeveloped regions. There is an underlying inflection point in jobs-housing relationship that is similar to its long-term average value and reflects regional market equilibrium. This paper contributes to existing literature by providing a big-data driven nationwide jobs-housing study fully aware of the theoretical and practical needs of a regionalizing world. Findings advances our understanding of macroscopic jobs-housing relationship, and offers policy suggestions for governments across the globe.

Resource curse, energy consumption, and moderating role of digital governance: Insights from South Asian countries

This study investigates the relationships between the resource curse, energy consumption, and the moderating role of digital governance within the context of South Asian countries. By employing a robust analytical framework, the study delves into how digital governance can potentially mitigate the adverse effects of the resource curse while influencing energy consumption patterns. It employs Method of Moment Quantile Regression (MMQR) on south asian countries panel from 2003 to 2022. The findings report detrimental impact of natural resources rent on economic growth, confirming resource curse hypothesis in low and high growth countries. Digital governance has a positive and significant impact at middle and higher quantiles. The joint influence of natural resources rent, and digital governance is associated with lower economic growth. It imply that digital governance doest not decreases the negative effect of natural resources rent on economic growth. Energy consumption contributes to higher economic growth from lower to higher quantiles. The interaction of digital governance and energy consumption has significant and positive impact on higher quantiles, suggesting that digital governance enhances energy consumption efficiency. These findings suggest valuable policy suggestions.

Overview of Governance and Rampant Corruption in Land Administration in Bangladesh

This study focuses on the governance and corruption in the land management system of Bangladesh and the effect of these factors on the tenure security of land and the country’s economic growth. This study used a quantitative research design. The research outcomes show that corruption is systematic in all levels of land management, thus eroding the security of tenure, and worsening social inequalities. The new governance reforms have also been implemented to curb corruption; however, these changes’ impact has been rather poor. In light of the findings of the study, there is a well-established need for systematic reform to improve the situation in Bangladesh through digitization of land records, better transparency, and higher accountability in the land administration sector. The investigation presented in this research adds to the discussion of governance and development and offers practical policy suggestions that relate to fighting corruption and enhancing the efficient utilization of Bangladeshi land.

Spatial connection strength and endogenous and exogenous interactive driving factors of carbon efficiency in China's metropolitan areas with higher energy consumption

Investigating the spatial effects and driving factors of carbon efficiency is meaningful for the sustainable development of metropolitan areas. However, research on the spatial connection strength and endogenous and exogenous interactive driving factors for metropolitan areas' carbon efficiency are limited. This research studies the carbon efficiency in China's metropolitan areas within year 2003–2019. The spatial connection strength using the gravity model with the “dual” driving factors and the geographical detector are analyzed. The results show that: 1) Shanghai metropolitan area performs well and promotes the development of neighboring cities, but Shenyang and Taiyuan metropolitan areas have negative effects on the neighboring cities; 2) The interaction between land resource consumption and pollution index, energy consumption and economic development level is the main endogenous driving factor with the determinant force values of 0.712, 0.674 and 0.634. Energy consumption is a secondary endogenous factor. Capital input, labor input and pollution play weaker roles. 3) Openness degree and education development level and their interaction are the main exogenous driving factors of carbon efficiency in China's metropolitan areas with the determinant force value of 0.673. Based on the results of interactive driving factors of China's metropolitan areas, this paper gives policy suggestions accordingly.

Auditing road safety achievement using MEREC–ARAS–QBKM model: an empirical study for APEC member economies

Progress monitoring and action recalibrations are advocated as promising methods for improving road safety, which significantly relates to economic stability and social development. To achieve this, an auditing framework that can evaluate road safety and aid in policymaking is urgently required. To this end, this study developed a systemic decision model that integrates the method based on the removal effects of criteria (MEREC), additive ratio assessment (ARAS), and quantile-based k-means clustering (QBKM), termed MEREC–ARAS–QBKM, with the aim of auditing road safety achievements and providing corresponding policy suggestions with substantial reliability. In particular, the performance of the traditional k-means clustering model was improved by implanting quantiles to determine the initial clustering, which overcomes the uncertainty of k-means clustering owing to the variety of initial cluster centers. Multiple comparisons of empirical results based on a case study of the Asia-Pacific Economic Cooperation (APEC) member economies verified the robustness of the proposed model, demonstrating its applicability, practicability, and reliability in handling real-world multi-criteria decision-making problems in the field of road safety. The empirical findings show that road safety developments among the APEC countries are of class differentiation, suggesting an urgent regional benchmarking. Overall, the proposed methodology empowers decision-makers and policymakers in APEC to swiftly formulate effective action plans, countermeasures, and investment schemes, ultimately contributing to the enhancement of road safety performance and socio-economic benefit across APEC members.

Smart city governance: assessing modes of active citizen engagement

ABSTRACT This paper discusses how to govern smart cities that nurture and promote citizen engagement. By reviewing the emergent literature on the topic and rooting in a pluralistic – a descriptive and normative orientation, we identify three novel governance models: embedded, blended and networked. Our review indicates that the depth of citizen engagement varies between models based on the roles played by closely aligned resourceful actors. A collaborative environment driven by, for and with citizens seeks to build smart cities embedded in local realities. Drawing on examples from smart cities across the globe, we offer policy suggestions for building futuristic citizen-engaged smart cities.

The Integration of Machine Learning in Central Banks: Implications and Innovations

The effectiveness of using artificial intelligence (AI) techniques to lessen the negative effects of economic cycles is examined in this study article. Economic cycles, which are defined by variations in the level of economic activity, present important difficulties for decision-makers in government, business, and society at large. This research investigates many approaches to reducing economic cycles, such as forecasting, policy creation, and adaptive decision-making, by utilizing AI, namely machine learning algorithms. The first section of the paper reviews the body of research on economic cycles and how artificial intelligence might be used to address them. After that, it explores certain AI methods including neural networks, time series analysis, and natural language processing, explaining how they might be used for risk management and economic forecasting. Additionally, the study investigates AI-driven policy interventions, examining how machine learning algorithms might be used to optimize monetary and fiscal policies in order to sustain growth and prevent economic downturns. The study also addresses the difficulties and constraints that come with using AI technologies in economic management, such as problems with algorithmic biases, data quality, and legal considerations. It highlights how crucial interdisciplinary cooperation and openness are to creating AI-driven solutions that are reliable, moral, and socially conscious. This research paper offers insights into the possible advantages and disadvantages of employing AI tools for damping economic cycles through empirical analysis and case studies. In order to fully realize AI's promise in fostering resilience and stability in the economy, it ends by presenting future research areas and policy suggestions. Keywords: artificial intelligence, trend, economic cycles, resilience

Identification and prediction of the degree of multidimensional returning to poverty risk for the household in China through the novel hybrid model: Based on the survey data of China Family Panel Studies (CFPS)

In China, absolute poverty has been effectively eliminated, but this does not signify the complete eradication of poverty. Instead, poverty persists in the forms of relative and secondary poverty. More concerningly, regions or households lifted out of poverty continue to face numerous risks of returning to poverty. In this context, measuring poverty solely based on monetary metrics is no longer adequate. Furthermore, the primary focus of grassroots governance has shifted from merely assessing poverty to accurately predicting the multifaceted risks associated with falling back into poverty. A multidimensional poverty indicator system is constructed to measure and predict the risk of multidimensional returning to poverty in China. Then, the Alkire–Forster counting method is applied to measure the risk of multidimensional poverty return and demonstrate the contribution of various indicators to multidimensional poverty return using tracking survey data from the China Family Panel Studies (CFPS). The results show that the multidimensional poverty return in China is mainly caused by the factors in two or three dimensions, where the social development capability dimension has the highest contribution to the multidimensional poverty return index with 43.12%, followed by the health and education dimensions. Moreover, according to the finding that the identification of multidimensional poverty varies with the values of the poverty cut-off, a novel and practicable method is proposed to classify the risk into three levels, noted as the high, medium and low levels. Consequently, a hybrid model is constructed to predict the risk of multidimensional poverty return by integrating the Archimedes optimization algorithm (AOA), variational mode decomposition (VMD) and Bi-directional long short-term memory (BiLSTM) neural networks. Finally, the performance of the constructed model is validated with an accuracy up to 99.81%. The constructed model's efforts outperform the traditional BiLSTM and several prevalent machine learning algorithms through extensive comparative experiments. These results illustrate that the proposed model can accurately and stably predict the potential risk of poverty return for multidimensional poverty groups and regions. In conclusion, drawing from the analysis of factors contributing to the risk of relapsing into poverty in this study, policy suggestions have been formulated focusing on education, social capacity enhancement, and healthcare system advancement. In summary, this paper provides new insights into the factors contributing to multidimensional poverty recurrence and the methods for assessing its risk levels, while also introducing a more precise approach to predicting these levels.

Changing of the coordination of socioeconomic development and the environment as sustainable development progresses

The relationship between socioeconomic development and the environment is intimately linked with the level of regional sustainable development. Clarifying the evolution pattern of this relationship during the sustainable development progress is crucial for achieving all of the Sustainable Development Goals (SDGs), but less research has focused on this problem. Here, we have utilized statistical and remote sensing data from 290 municipal units in China to analyze the evolution of the coupling coordination degree (CCD) between socioeconomic development and the environment along a progression of sustainable development measured by the SDG Index. The results show that the hotspot areas of CCD are concentrated in coastal regions, gradually decreasing as they move inland. Additionally, as sustainable development progresses, both socioeconomic and environment levels exhibit a nonlinear rise. The coupling coordination between the two demonstrates a pattern of initial increasing, then decreasing, and finally increasing again, which may be related to changes in industrial structure. Our study delves deeply into the patterns of evolution in the relationship between socioeconomic and environments, exploring the challenges and opportunities faced by regions at different stages of sustainable development. The findings can deepen our understanding of sustainable development and provide policy suggestions and theoretical support for achieving SDGs.

청원경찰의 직무스트레스가 이직의도에 미치는 영향: LMX를 중심으로

This study attempted to determine how job stress generated by the cheongwon police's job affects the intention to turnover. The cheongwon police are highly stressed about their duties due to the response of malicious complaints such as verbal abuse and intimidation of public officials, verbal abuse and assault on civil petitioners, and shift work. This job stress of cheongwon police officers can lead to job change. It was found that job stress affects turnover intention not only in them but also in various occupations. However, this study sought to empirically verify the moderating effect of LMX on job stress and turnover intention. LMX explains the effectiveness of leadership through the interaction of the relationship between superiors and subordinates. It is explained that when the quality of LMX is high, turnover intention toward the organization decreases due to identification with the organization and commitment to the organization. To achieve the purpose of this study, a survey was conducted targeting police officers working in the northern Gyeonggi region and Incheon. As a result of the analysis, it was confirmed that their job stress had an effect on their turnover intention. And the moderating effect of LMX on job stress and turnover intention, which is the main purpose of this study, was confirmed to have a partial effect. In other words, emotional bond and dedication were confirmed to have an effect on turnover intention in cheongwon police officers' job stress, and it was confirmed that desire to contribute and respect for professionalism were not statistically significant in their job stress and turnover intention. Based on these analysis results, policy suggestions were made regarding the their LMX.

산재노동자의 심리회복 과정에 관한 현상학적 연구

The purpose of this study is to provide a contextual examination of the process of psychological recovery of injured workers after industrial accidents and to understand the nature of common experiences in the recovery process. This study uses Colaizzi's method of phenomenological research. A total of 4 times, 4 themes, and 11 categories were identified through the analysis of interviews with eight workers with recognized compensation claims for physical, psychological workplace. The 4 themes and times of the study were:‘ A Life of Running Ahead (Before an Industrial Accident),’‘Feeling Like I've been Struck by Lightning (Immediately After an Industrial Accident),’‘A Desperate Effort to Recover (During a Medical Care Duration),’ and ‘Rewriting a Second Life (After a Termination of Care Duration). Based on these findings, practical and policy suggestions were presented for the psychological recovery of injured workers, welfare improvement, and social insurance improvement as a social protection network.

교정시설의 지역사회 수용태도의 영향 요인

The overcrowding and aging of correctional facilities must be seriously addressed in order to protect the human rights of prisoners and the safety of the public, and it is currently necessary to relocate existing facilities or build new ones every year in order for Korean correctional facilities to fulfil their role. However, new construction and relocation has not been carried out in a timely manner due to ongoing local opposition to the siting of correctional facilities. This study was conducted to investigate the attitudes of residents in neighborhoods without correctional facilities and to identify factors that influence their acceptance of correctional facilities. Specifically, based on the results of the literature review, the following variables were identified as factors that directly or indirectly influence residents' attitudes: local image damage, trust in government, need for facilities, and fear of crime. The relative magnitude of their influence was compared, and policy implications related to the siting of correctional facilities were suggested. The study found that residents' perceptions of a correctional facility being located in a neighborhood are negatively related to the perceived damage to the neighbourhood's image, and that higher perceptions of fear of crime are positively related to the perception of siting of a correctional facility. However, the more residents perceive the need for correctional facilities, the more negatively they perceive the community location of correctional facilities, which can be interpreted as a confirmation of the NIMBY phenomenon suggested by previous studies. And policy suggestions and limitations are presented.

BRIDGING DIGITAL AND GOOD GOVERNANCE: A REVIEW OF E-GOVERNANCE FRAMEWORKS AND CHALLENGES

This review article, explores the intricate relationship between e-governance and good governance through a comprehensive analysis of theoretical and empirical perspectives. The study begins with an introduction to the significance of e-governance in enhancing public service delivery and citizen engagement. It proceeds to examine key theories relevant to e-governance. The empirical section is organized into three parts: the relationship between e-governance and digital governance, the interplay between e-governance and good governance, and the challenges faced in implementing e-governance initiatives. The findings highlight that while e-governance holds significant promise for improving governance outcomes, various obstacles, such as inadequate infrastructure and digital literacy, hinder its effectiveness. Policy suggestions derived from the reviews emphasize the need for targeted investments in ICT infrastructure, community-centric applications, and inter-agency collaboration to promote successful e-governance implementation. The article concludes by offering final remarks that underscore the importance of a holistic approach in bridging digital governance and good governance, ultimately enhancing public value and societal well-being.

Effectively Utilizing Infrastructure to Achieve Economic and Societal Growth in Developing Countries

Developing countries can benefit economically and socially from the construction of infrastructure. However, poor policy decisions regarding investment in public goods and services often impede infrastructure’s effectiveness in achieving such benefits. This paper seeks to provide a coherent framework for developing countries to consider when planning and implementing infrastructure projects. Gathering insights and policy suggestions from various relevant studies, it proposes three factors necessary for developing countries to consider. These three factors emphasize individual quality of life and long-term development instead of simple short-term economic growth described by basic economic indicators. They also account for the social and environmental concerns or implications of infrastructure construction, often overlooked in many policy agendas. The first factor is the efficiency of expenditure and accessibility of infrastructure, achieved through the consideration of diminishing returns to scale for capital investment and an emphasis on the delivery, not just the provision, of public services; the second is resilience and sustainability in the context of local environmental attributes and regional independence during the decision-making process; the third is the maximization of indirect benefits, most notably the increases in human capital and productivity caused by infrastructure construction.