Search results

This study aims to review the results of relevant studies to shed light on social trust-building in different contexts and the factors that affect it in disaster risk management.

This systematic review was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses model. The study keywords were searched for in PubMed, Scopus and Web of Science databases on August 2021. The inclusion criteria were English-written articles published in social trust and disaster relief efforts. Exclusion criteria were lack of access to the full text and article types such as nonoriginal articles.

Out of 1,359 articles found, 17 articles were included in the final analysis using four general categories: six articles on the role of local government in trust-building (local governments), five articles on the role of social media in trust-building (social media), four articles on the role of social capital in trust-building (social capital) and two articles on the importance of community participation in trust-building (community participation).

Understanding the role of social trust and the factors which influence it will help the development of community-based disaster risk management. Therefore, disaster management organizations and other relief agencies should take the findings of this study into account, as they can help guide policymaking and the adoption of strategies to improve public trust and participation in comprehensive disaster risk management. Further studies recommended understanding people’s experiences and perceptions of social trust, relief and disaster preparedness.

This research sought to show that consumers with strong green attitudes modify their consumption criteria, getting them to consider green products as more aligned with their preferences. Utilizing the theory of reasoned action (TRA) and self-regulation theory, this study investigated how consumers’ green attitudes influence their intentions to buy eco-friendly products, both directly and through the mediating role of consumer-green product congruence. Furthermore, to find more specific insights for businesses, drawing on attitude-behavior-context (ABC) theory, this study compared the results between males and females.

To evaluate the proposed conceptual model, this study surveyed 272 consumers and analyzed the data using partial least squares structural equation modeling (PLS-SEM) with the help of Smart-PLS 4.0 software.

The results indicated that consumers with green attitudes have higher intentions to buy green products, both directly and through the mediating role of consumer-green product congruence. While, in contrast to women, no significant direct relationship between men’s green attitude and their green purchase intentions was observed, we found a stronger mediating role for green-product congruence among males than females.

The findings suggest that fostering consumers’ green attitudes not only enhances consumers’ perceived alignment with green products but also significantly increases their intentions to purchase eco-friendly products. Furthermore, a comparison between males and females shows that men only decide to purchase green products when they see an alignment between their preferences and those products. Green attitudes are not sufficient for men to purchase green products. This is among a few studies addressing the above issues from the perspective of TRA, self-regulation theory and ABC theory.

The purpose of this study was to address waste management in the food supply chain (FSC) through the integration of inspection processes in production and distribution centers under uncertain conditions, aiming to enhance sustainability across environmental, economic and social dimensions. The study introduces a sustainable forward and reverse FSC network using a closed-loop supply chain network approach to prevent the transfer of spoiled products, ultimately providing competitive advantages to stakeholders.

A robust multi-objective mathematical programming model is proposed, incorporating inspection processes to manage perishable products effectively. The model is solved using the Augmented Epsilon Constraint technique implemented in GAMS software, providing Pareto-optimal solutions tailored to decision-makers’ preferences. Furthermore, the methodology is applied in a real-world case study and solved with the Benders Decomposition algorithm to validate its practicality and effectiveness.

The proposed methodology effectively minimizes waste and enhances sustainability in the FSC by optimizing decision-making processes under uncertainty. The illustrative examples and real case study demonstrate the efficiency of the model and solution approach, highlighting the significant role of inspection in improving all three dimensions of sustainability.

The study offers valuable insights into and tools for food industry managers to make informed strategic and tactical decisions. By addressing waste management through advanced supply chain modeling, the research helps organizations reduce costs, improve sustainability and gain a competitive edge in the market.

This research is novel in its focus on integrating inspection into the FSC network and addressing uncertainty through robust mathematical modeling. It contributes to the existing literature by demonstrating the impact of inspection on sustainability in FSCs and providing practical solutions for real-world implementation.

The purpose of the study is to analyse the occurrence and distribution of different tree species in Gilgit-Baltistan, Pakistan, as a baseline for further inventories, and estimate the biomass per species and plot. Furthermore, it aims to measure forest biodiversity using established formulae for tree species diversity index, richness, evenness and accumulative curve.

Field data were collected, including stratification of forest sample plots. Statistical analysis of the data was carried out, and locally appropriate allometric equations were applied for biomass estimation.

Representative circular 556 forest sample plots of 1,000 m² contained 13,135 trees belonging to nine tree species with a total aboveground biomass of 12,887 tonnes. Sixty-eight per cent of the trees were found between 2,600 and 3,400 masl; approximately 63 per cent had a diameter at breast height equal to 30 cm, and 45 per cent were less than 12 m in height. The Shannon diversity index was 1.82, and Simpson’s index of diversity was 0.813.

Rough terrain, long distances, harsh weather conditions and location of forest in steep narrow valleys presented challenges for the field crews, and meant that fieldwork took longer than planned.

Estimating biomass in Gilgit-Baltistan’s forests using locally developed allometric equations will provide transparency in estimates of forest reference levels, National Forest Monitoring System in Pakistan and devising Reducing Emissions from Deforestation and Forest Degradation national strategies and for effective implementation.

This paper presents the first detailed forest inventory carried out for the dry temperate and semi-arid cold region of Gilgit-Baltistan, Pakistan.