This research intends to find out the compliance acts based on the manufacturing industry of Bangladesh and lead to the development of the integrated theory of compliance model. There are several compliance regulations, that are separately dealt with in any manufacturing organization. These compliance regulations are handled at various ends of the organization making the process quite scattered, time-consuming, and tedious. To fix this problem, the integration of organizational compliance regulations is brought under one platform. Researchers have applied the qualitative approach with multiple case studies methodology scrutinizing the in-depth interviews and transcripts. Furthermore, the NVIVO tool has been used to analyze, where the necessary themes of the Organizational Compliance Regulations are found. Therefore, we have proposed a conceptual framework to inaugurate a standalone combined framework, which is an innovative and novel measure.

This article explores the development and legislative process of concession agreements within the framework of Public-Private Partnerships (PPPs) in the EU, tracing their origins to the United Kingdom in the early 1990s. Driven by national policies, the Ministry of Finance in China has promoted PPPs in infrastructure and public services. This study focuses on the basic principles, legal nature, and general rules of EU concession agreements, aiming to provide legal strategies for Chinese franchising agreement legislation by drawing on the EU’s legislative experiences.

Soundscape tourism has become one type of tourism, and its trend is emerging in most areas with hilly, forested, and natural landscapes, such as Bantul Indonesia, becoming a mainstay for region development and its community. This article explores four human manufactured soundscape tourism destinations in Bantul, Indonesia, examining the interrelationships between each tourism stakeholder and pinpointed development from a socio-economic perspective. We adopt a cross-case study approach, drawing main sources from government statistics, regulations, social media narratives, and online news. Using the NVivo 12 Plus software, we coded and annotated the research source. Our research revealed that in four case studies, tourism soundscapes emerged as the primary tourist attractions, with other attractions only marginally contributed. Presenting music or acoustic stages enabled tourism industry to reap benefits, particularly for local community and regional income. However, it is important to emphasize sustainability issues, thus, the continuous increased in music soundscape in nature has led to the formation of collaborations among tourism actors, with local communities “Pokdarwis” posed as the principal driving force behind destination development. This study demonstrates that human-manufactured soundscapes have the potential to increase visitor numbers and outperform natural soundscapes in natural destinations.

The potential of entrepreneurship to reduce poverty is closely tied to critical factors such as access to finance, training and education, networks and social capital, and supportive regulatory environments. Understanding and addressing these underlying issues through the lens of the Social Capital theory can help foster an entrepreneurial spirit in cities and mitigate poverty through business and community development. This paper explores the insights and standpoints of key stakeholders about poverty in Saint John and its impact on entrepreneurship. The study uses a quantitative method and analyzes data from surveys with stakeholders. The results show that social isolation, system inflexibility, individual issues, housing, and financial support programs are significant poverty challenges in Saint John, and these issues have implications for entrepreneurship. By integrating Social Capital Theory into policy initiatives, policymakers can enhance community resilience and empower vulnerable individuals. This application of social capital principles provides a holistic framework for designing effective poverty-reduction measures, offering transformative insights applicable not only to Saint John but also to diverse small cities. The study contributes a nuanced understanding of poverty’s impact on entrepreneurship, advocating for inclusive strategies that resonate with the social fabric of communities.

This study investigates the potential predictors of resource creation behaviours in the Shanxi merchant courtyard scenic areas based on resource dependence theory. The research was conducted in China using questionnaire survey, and data analysis employed structural equation modelling, including mediation and moderation effects. The model was tested using a sample of 376 individual managers from scenic areas. The results show that external resource integration, internal resource integration, and shared value significantly affect resource creation in scenic areas. The findings indicate that shared value plays a significant mediating role in the relationship between resource integration and resource creation, while environmental dynamism significantly moderates this relationship. This study clearly demonstrates the relationship among resource integration, shared value, and value creation in scenic areas. This research contributes to the tourism management literature by identifying gaps and offering a comprehensive perspective to understand resource creation behaviours in the tourism industry.

Vehicle detection stands out as a rapidly developing technology today and is further strengthened by deep learning algorithms. This technology is critical in traffic management, automated driving systems, security, urban planning, environmental impacts, transportation, and emergency response applications. Vehicle detection, which is used in many application areas such as monitoring traffic flow, assessing density, increasing security, and vehicle detection in automatic driving systems, makes an effective contribution to a wide range of areas, from urban planning to security measures. Moreover, the integration of this technology represents an important step for the development of smart cities and sustainable urban life. Deep learning models, especially algorithms such as You Only Look Once version 5 (YOLOv5) and You Only Look Once version 8 (YOLOv8), show effective vehicle detection results with satellite image data. According to the comparisons, the precision and recall values of the YOLOv5 model are 1.63% and 2.49% higher, respectively, than the YOLOv8 model. The reason for this difference is that the YOLOv8 model makes more sensitive vehicle detection than the YOLOv5. In the comparison based on the F1 score, the F1 score of YOLOv5 was measured as 0.958, while the F1 score of YOLOv8 was measured as 0.938. Ignoring sensitivity amounts, the increase in F1 score of YOLOv8 compared to YOLOv5 was found to be 0.06%.