Industrial heritage is a legacy from the past that we live with today and pass on to future generations. The economic value of this heritage can be defined as the amount of welfare that it generates for society, and this value should not be ignored. However, current research based on economic analysis has mostly focused on qualitative statements instead of quantitative assessment. This study proposes an innovative methodology combining qualitative (field research) and quantitative (willingness to pay and contingent valuation) methods to assess the economic value of industrial heritage. The industrial heritage of Tangshan, China, was chosen as a case study, and the research found that museums and cultural creative parks are effective ways to conserve industrial heritage. The entrance fee can be used to represent the economic value of the heritage site. There was a positive correlation between the influence of economic value and the entrance fees residents would prefer to pay. The results indicate the locals would prefer lower entrance fees for the transformed heritage museums (The average current cost: $2.23). Locals were most concerned about the entrance fees for the Kailuan Coal Mine and Qixin Cement Plant Museums, which have both been renewed as urban landmarks for city tourism. Renewal methods have been applied to six industrial heritage sites in Tangshan; these sites have their own conservation and renewal practices based on city-level development or industrial attributes. Thus, when residents recognize the economic value of a heritage site, they are willing to pay a higher entrance fee. This research demonstrates the economic value of industrial heritage using a mixed methods approach and provides a basis for assessing the value of cultural heritage for urban tourism analysis.

This study introduces an innovative approach to assessing seismic risks and urban vulnerabilities in Nador, a coastal city in northeastern Morocco at the convergence of the African and Eurasian tectonic plates. By integrating advanced spatial datasets, including Landsat 8–9 OLI imagery, Digital Elevation Models (DEM), and seismic intensity metrics, the research develops a robust urban vulnerability index model. This model incorporates urban land cover dynamics, topography, and seismic activity to identify high-risk zones. The application of Landsat 8–9 OLI data enables precise monitoring of urban expansion and environmental changes, while DEM analysis reveals critical topographical factors, such as slope instability, contributing to landslide susceptibility. Seismic intensity metrics further enhance the model by quantifying earthquake risk based on historical event frequency and magnitude. The calculation based on higher density in urban areas, allowing for a more accurate representation of seismic vulnerability in densely populated areas. The modeling of seismic intensity reveals that the most susceptible impact area is located in the southern part of Nador, where approximately 50% of the urban surface covering 1780.5 hectares is at significant risk of earthquake disaster due to vulnerable geological formations, such as unconsolidated sediments. While the findings provide valuable insights into urban vulnerabilities, some uncertainties remain, particularly due to the reliance on historical seismic data and the resolution of spatial datasets, which may limit the precision of risk estimations in less densely populated areas. Additionally, future urban expansion and environmental changes could alter vulnerability patterns, underscoring the need for continuous monitoring and model refinement. Nonetheless, this research offers actionable recommendations for local policymakers to enhance urban planning, enforce earthquake-resistant building codes, and establish early warning systems. The methodology also contributes to the global discourse on urban resilience in seismically active regions, offering a transferable framework for assessing vulnerability in other coastal cities with similar tectonic risks.

A method for studying the resilience of energy and socio-ecological systems is considered; it integrates approaches developed at the International Institute of Applied Systems Analysis and the Melentyev Institute of Energy Systems (MESI) of the Siberian Branch of the Russian Academy of Sciences. The article discusses in detail the methods of using intelligent information technologies, in particular semantic technologies and knowledge engineering (cognitive probabilistic modeling), which the authors propose to use in assessing the risks of natural and man-made threats to the resilience of the energy sector and social and ecological systems. More attention is paid to the study and adaptation of the integral indicator of quality of life, which makes it possible to combine these interdisciplinary studies.

Hazards are the primary cause of occupational accidents, as well as occupational safety and health issues. Therefore, identifying potential hazards is critical to reducing the consequences of accidents. Risk assessment is a widely employed hazard analysis method that mitigates and monitors potential hazards in our everyday lives and occupational environments. Risk assessment and hazard analysis are observing, collecting data, and generating a written report. During this process, safety engineers manually and periodically control, identify, and assess potential hazards and risks. Utilizing a mobile application as a tool might significantly decrease the time and paperwork involved in this process. This paper explains the sequential processes involved in developing a mobile application designed for hazard analysis for safety engineers. This study comprehensively discusses creating and integrating mobile application features for hazard analysis, adhering to the Unified Modeling Language (UML) approach. The mobile application was developed by implementing a 10-step approach. Safety engineers from the region were interviewed to extract the knowledge and opinions of experts regarding the application’s effectiveness, requirements, and features. These interview results are used during the requirement gathering phase of the mobile application design and development. Data collection was facilitated by utilizing voice notes, photos, and videos, enabling users to engage in a more convenient alternative to manual note-taking with this mobile application. The mobile application will automatically generate a report once the safety engineer completes the risk assessment.

The Middle East and North Africa (MENA) region faces unique challenges and opportunities in integrating sustainability into sovereign credit assessments. This research study examines environmental, social, and governance (ESG) factors embedded in the lending policies of jurisdictional institutions in MENA. By analyzing existing literature and case studies, we identify key drivers and barriers to ESG integration in sovereign lending. Our findings suggest a growing recognition of sustainability’s importance in financial stability and credit, driven by global climate guarantees and local socio-economic development. However, challenges such as data availability, regulatory frameworks, and market acceptance persist. This paper provides an overview of current practices, highlights best practices, and offers recommendations to enhance ESG integration in sovereign debt reviews in the MENA region. The study concludes that a robust ESG framework is necessary to accurately reflect the long-term risks and opportunities associated with sovereign debt, ultimately contributing to sustainable economic growth regionally.