Since 2019, Togo has resolutely engaged in the decentralization process marked by communalization and elections of municipal councilors. Financial autonomy constitutes an essential lever for the free administration of municipalities, allowing them to ensure decision-making and the implementation of development projects. However, despite a legal and regulatory framework defining taxation specific to local authorities, Togolese municipalities are often perceived as needing more financial resources. This study aims to map the financing mechanisms for decentralization in Togo and analyze their contribution to municipal budgets. By adopting a quantitative approach combining documentary analysis and interviews with 188 experts and practitioners of local finance from various Togolese structures, four main financing mechanisms were identified: local, national, Community, and international. Among these mechanisms, own resources (in particular from the sale of products and services, fiscal and non-fiscal taxes) and state transfers via the Support Fund for Local Authorities emerge as the primary sources of financing for municipalities. However, the study reveals that several instruments of local mechanisms, although institutionally defined, still need to be updated in many municipalities, thus limiting their effectiveness in resource mobilization. These results highlight the importance of optimizing the management of local mechanisms to strengthen municipalities’ financial autonomy and support territories’ sustainable development.

The purpose of Vehicular Ad Hoc Network (VANET) is to provide users with better information services through effective communication. For this purpose, IEEE 802.11p proposes a protocol standard based on enhanced distributed channel access (EDCA) contention. In this standard, the backoff algorithm randomly adopts a lower bound of the contention window (CW) that is always fixed at zero. The problem that arises is that in severe network congestion, the backoff process will choose a smaller value to start backoff, thereby increasing conflicts and congestion. The objective of this paper is to solve this unbalanced backoff interval problem in saturation vehicles and this paper proposes a method that is a deep neural network Q-learning-based channel access algorithm (DQL-CSCA), which adjusts backoff with a deep neural network Q-learning algorithm according to vehicle density. Network simulation is conducted using NS3, the proposed algorithm is compared with the CSCA algorithm. The find is that DQL-CSCA can better reduce EDCA collisions.

Corporate social responsibility (CSR) is an important concept of modern economic theory. In the last few decades, it has become an increasingly popular marketing tool used by companies. Consumers too want to see more CSR activities, especially those focused on environmental protection. The petroleum industry produces both toxic and non-toxic waste at almost all stages of production. While petroleum companies satisfy market demand, they also want to meet consumers’ moral and ethical demands. In this light, CSR has become vital for the development of industry. This paper looks at CSR in the petroleum industry, and its effect on customer satisfaction and subsequently toward the customer repurchase intention in Malaysia. The starting point of this paper is the Stakeholder Theory. It then examines CSR endeavors within the oil and gas sector and its link to customer repurchase intentions. It also looks at the established hypotheses between the activities of CSR (Economic Responsibility, Legal Responsibility, Ethical Responsibility, Philanthropic Responsibility), customer satisfaction and repurchase intention. This paper aims to learn about the customer’s sense of fulfilment with the CSR activities, and what could be the reaction base on the customer’s expectation.

Introduction: With the adoption of the rural rehabilitation strategy in recent years, China’s rural tourist industry has entered a golden age of growth. Due to the lack of management and decision-support systems, many rural tourist attractions in China experience a “tourist overload” problem during minor holidays or Golden Week, an extended vacation of seven or more consecutive days in mainland China formed by transferring holidays during a specific holiday period. This poses a severe challenge to tourist attractions and relevant management departments. Objective: This study aims to summarize the elements influencing passenger flow by examining the features of rural tourist attractions outside China’s largest cities. Additionally, the study will investigate the variations in the flow of tourists. Method: Grey Model (1,1) is a first-order, single-variable differential equation model used for forecasting trends in data with exponential growth or decline, particularly when dealing with small and incomplete datasets. Four prediction algorithms—the conventional GM(1,1) model, residual time series GM(1,1) model, single-element input BP neural network model, and multi-element input BP network model—were used to anticipate and assess the passenger flow of scenic sites. Result: The multi-input BP neural network model and residual time series GM(1,1) model have significantly higher prediction accuracy than the conventional GM(1,1) model and unit-input BP neural network model. A multi-input BP neural network model and the residual time series GM(1,1) model were used in tandem to develop a short-term passenger flow warning model for rural tourism in China’s outskirts. Conclusion: This model can guide tourists to staggered trips and alleviate the problem of uneven allocation of tourism resources.

Shared education has the potential to foster pluralistic values and improve relations between individuals from diverse ethno-linguistic backgrounds. This study aims to contribute to the understanding of how shared learning experiences can promote pluralism and social equality by examining the pedagogical factors that influence their success. This study focuses on a shared English learning model implemented with 8th-grade Arab and Jewish students in homogenous Israeli cities. This qualitative study, involving observations, interviews, focus groups, and transcript analysis, engaged 42 students, two teachers, and two administrators. The findings suggest that shared education has positive social implications. It facilitated interaction between Arab and Jewish students and challenged negative stereotypes. Notably, the Jewish students’ limited Arabic language proficiency led to complex interactions, stimulating critical thinking about linguistic inequality and increasing motivation to learn Arabic. While shared education improved intergroup relations, it also encountered logistical challenges that necessitated institutional support to optimize its effectiveness.