Regional cooperation stands as a key strategy to address intense economic competition and formidable local governance challenges. Successful regional collaborations are typically founded on the basis of institutional similarity, which also serves as the starting point for a multitude of related theoretical studies. Consequently, the regional cooperation within the context of institutional conflicts has been overlooked. This paper aims to explore the process of regional cooperation against the backdrop of conflicts, using the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as a case study and analyzing it from the perspective of the sociology of knowledge. The article posits that conflicts can stimulate interactions among various actors, foster the generation of local knowledge, and propel specific cooperative practices. Moreover, local and central governments, grounded in local knowledge and universal managerial insights, continuously authenticate and propagate local innovations, establishing guiding policies and, consequently, producing rational knowledge. The accumulation of such knowledge has not only strengthened civilian cooperation but also facilitated broader collaborative efforts. The study reveals that despite the GBA’s remarkable achievements in cooperation, challenges persist: on the one hand, there are issues with the government’s process of rational knowledge production and the quality of knowledge itself; on the other hand, excessive governmental dominance may suppress the production and application of local knowledge. Therefore, refining the knowledge production mechanism is especially critical. The findings of this paper uncover the mechanisms of regional cooperation amidst institutional conflicts and deepen our understanding of regional collaboration and cross-border governance.

This research aims to explore the impact of government policies to promote mass tourism in Bali. Qualitative method with the support of a phenomenological approach and in-depth interviews and FGD. The Butler tourism area life cycle model theory is used to evaluate the impact of tourism on land use and cultural conflict with six stages of destination development, namely exploration, involvement, development, consolidation, stagnation, and decline or rejuvenation. The findings reveal that Bali has experienced all stages of Butler’s model. From 1960–1970, Bali was in the exploration phase, offering tourists authentic experiences. At the beginning of 1970–2000, Bali had entered five phases marked by rapid tourism growth. Now, Bali reached a consolidation phase with a focus on managing tourism quality. Now, Bali is entering a phase of stagnation, facing challenges such as overcrowding and environmental degradation. Bali is at the crossroads between phases of decline and rejuvenation, with efforts to overcome environmental problems and diversify tourism products. This study concludes that mass tourism has significant positive and negative impacts on tourist destinations. Although it can improve the local economy and preserve culture, it can also cause environmental damage and cultural conflict. The Bali government’s policy strategy for the future is to overcome cultural conflicts including tourist education, sustainable tourism development, empowerment of local communities, enforcement of regulations, and intercultural dialogue. The implementation of this policy strategy can be carried out effectively to manage cultural conflicts towards a sustainable Bali tourism future.

The focus of this research is the task of assistance from the government in improving agriculture in the region and analyzing the obstacles that occur. However, there has been a decrease in the number of assistance tasks given by the central government to the local government of Rokan Hulu, Riau Province, Indonesia in 2022. This study aims to evaluate and find out the obstacles to the implementation of assistance tasks in Rokan Hulu Regency in 2022. This study uses a qualitative method with an exploratory type and is analyzed using Nvivo 12 Plus software. The results of this study show that the Rokan Hulu regional government only gets one implementation of assistance tasks, namely from the Ministry of Agriculture through the Director General of Infrastructure and the Director General of Food Crops whose performance achievements have been maximized. The findings in this study are that in its implementation there are obstacles, one of which is the relatively short period of implementation of assistance tasks, making it difficult to implement assistance tasks by regional apparatus organizations as recipients of assistance tasks. The conclusion in this study is that the implementation of assistance tasks there is one assistance task received from the Ministry of Finance whose implementation in the region is carried out by the Food Crops and Horticulture Service. This research contributes to the government of Rokan Hulu, Indonesia, namely as a basis for policymaking, especially in the use of the budget for assistance tasks.

Cities play a key role in achieving the climate-neutral supply of heating and cooling. This paper compares the policy frameworks as well as practical implementation of smart heating and cooling in six cities: Munich, Dresden and Bad Nauheim in Germany; and Jinan, Chengdu and Haiyan in China, to explore strategies to enhance policy support, financial mechanisms, and consumer engagement, ultimately aiming to facilitate the transition to climate-neutral heating and cooling systems. The study is divided into three parts: (i) an examination of smart heating and cooling policy frameworks in Germany and China over the past few years; (ii) an analysis of heating and cooling strategies in the six case study cities within the context of smart energy systems; and (iii) an exploration of the practical solutions adopted by these cities as part of their smart energy transition initiatives. The findings reveal differences between the two countries in the strategies and regulations adopted by municipal governments as well as variations within each country. The policy frameworks and priorities set by city governments can greatly influence the development and implementation of smart heating and cooling systems. The study found that all six cities are actively engaged in pioneering innovative heating and cooling projects which utilise diverse energy sources such as geothermal, biomass, solar, waste heat and nuclear energy. Even the smaller cities were seen to be making considerable progress in the adoption of smart solutions.

Accurate prediction of US Treasury bond yields is crucial for investment strategies and economic policymaking. This paper explores the application of advanced machine learning techniques, specifically Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) models, in forecasting these yields. By integrating key economic indicators and policy changes, our approach seeks to enhance the precision of yield predictions. Our study demonstrates the superiority of LSTM models over traditional RNNs in capturing the temporal dependencies and complexities inherent in financial data. The inclusion of macroeconomic and policy variables significantly improves the models’ predictive accuracy. This research underscores a pioneering movement for the legacy banking industry to adopt artificial intelligence (AI) in financial market prediction. In addition to considering the conventional economic indicator that drives the fluctuation of the bond market, this paper also optimizes the LSTM to handle situations when rate hike expectations have already been priced-in by market sentiment.

The purpose of this study is to predict the frequency of mortality from urban traffic injuries for the most vulnerable road users before, during and after the confinement caused by COVID-19 in Santiago de Cali, Colombia. Descriptive statistical methods were applied to the frequency of traffic crash frequency to identify vulnerable road users. Spatial georeferencing was carried out to analyze the distribution of road crashes in the three moments, before, during, and after confinement, subsequently, the behavior of the most vulnerable road users at those three moments was predicted within the framework of the probabilistic random walk. The statistical results showed that the most vulnerable road user was the cyclist, followed by motorcyclist, motorcycle passenger, and pedestrian. Spatial georeferencing between the years 2019 and 2020 showed a change in the behavior of the crash density, while in 2021 a trend like the distribution of 2019 was observed. The predictions of the daily crash frequencies of these road users in the three moments were very close to the reported crash frequency. The predictions were strengthened by considering a descriptive analysis of a range of values that may indicate the possibility of underreporting in cases registered in the city’s official agency. These results provide new elements for policy makers to develop and implement preventive measures, allocate emergency resources, analyze the establishment of policies, plans and strategies aimed at the prevention and control of crashes due to traffic injuries in the face of extraordinary situations such as the COVID-19 pandemic or other similar events.