Search results

This paper aims to examine the integration of lateral transshipment and road vulnerability into the humanitarian relief chain in light of affected area priority to address equitable distribution and assess the impact of various parameters on the total average inflated distance traveled per relief item.

After identifying comprehensive critical criteria and subcriteria, a hybrid multi-criteria decision-making framework was applied to obtain the demand points’ weight and ranking in a real-life earthquake scenario. Direct shipment and lateral transshipment models were then presented and compared. The developed mathematical models are formulated as mixed-integer programming models, considering facility location, inventory prepositioning, road vulnerability and quantity of lateral transshipment.

The study found that the use of prioritization criteria and subcriteria, in conjunction with lateral transshipment and road vulnerability, resulted in a more equitable distribution of relief items by reducing the total average inflated distance traveled per relief item.

To the best of the authors’ knowledge, this study is one of the first research on equity in humanitarian response through prioritization of demand points. It also bridges the gap between two areas that are typically treated separately: multi-criteria decision-making and humanitarian logistics.

This is the first scholarly work in Shiraz focused on the equitable distribution system by prioritization of demand points and assigning relief items to them after the occurrence of a medium-scale earthquake scenario considering lateral transshipment in the upper echelon.

The paper clarifies how to prioritize demand points to promote equity in humanitarian logistics when the authors have faced multiple factors (i.e. location of relief distribution centers, inventory level, distance, lateral transshipment and road vulnerability) simultaneously.

Throughout human history, the occurrence of disasters has been inevitable, leading to significant human, financial and emotional consequences. Therefore, it is crucial to establish a well-designed plan to efficiently manage such situations when disaster strikes. The purpose of this study is to develop a comprehensive program that encompasses multiple aspects of postdisaster relief.

A multiobjective model has been developed for postdisaster relief, with the aim of minimizing social dissatisfaction, economic costs and environmental damage. The model has been solved using exact methods for different scenarios. The objective is to achieve the most optimal outcomes in the context of postdisaster relief operations.

A real case study of an earthquake in Haiti has been conducted. The acquired results and subsequent management analysis have effectively assessed the logic of the model. As a result, the model’s performance has been validated and deemed reliable based on the findings and insights obtained.

Ultimately, the model provides the optimal quantities of each product to be shipped and determines the appropriate mode of transportation. Additionally, the application of the epsilon constraint method results in a set of Pareto optimal solutions. Through a comprehensive examination of the presented solutions, valuable insights and analyses can be obtained, contributing to a better understanding of the model’s effectiveness.

This chapter demonstrates that social business models do not meaningfully prioritize or impose accountability to “social good” over other purposes in ways that (a) best protect against owners changing their minds or entry of new owners with different priorities and (b) enable reliable accountability over time and across circumstances. This chapter further suggests a model – a “social primacy company” – that actually prioritizes “social good” and meaningful accountability to it. This chapter thus clarifies circumstances under which existing models might be most useful and are not particularly useful, especially as investors, entrepreneurs, employees, regulators, and others pursue shared, common understandings about purposes, priorities, and accountability.

Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.

This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.

Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.

This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

Public higher education institutions (HEIs) infrastructure funding is challenging in many developing countries. Encouraging private investment in HEIs infrastructure via a developed expanded corporate social responsibility (ECSR) may improve physical facilities. ECSR is a form of infrastructure tax relief providing physical facilities for HEIs. Academic literature is scarce concerning how ECSR can improve Nigeria’s public HEIs infrastructure and achieve education infrastructure related to Sustainable Development Goal 4 (SDG 4). Therefore, this study aims to proffer measures to improve public HEIs infrastructure and achieve sustainable development connected to Goal 4 focussing on infrastructure via a developed framework.

This is an expansion of an ongoing study, and data were collated via virtual interviews across the six geo-political zones in Nigeria. The analysed data were presented in a thematic pattern.

A total of 18 measures (sub-variables) emerged and were re-grouped into six variables. This includes institutionalising ECSR, HEIs infrastructure via ECSR awareness, HEIs infrastructure incentives, national and state action plans on HEIs infrastructure, a legal framework for HEIs infrastructure and key stakeholders’ participation. Also, the study used the generated six main variables to develop the improved public HEIs infrastructure via ECSR in developing countries, using Nigeria as a case study. This can enhance achieving infrastructure associated with SDG 4 (quality education) and targets.

This study intends to develop the philosophy (ECSR) with an implementable framework to encourage the private sector further to expand their CSR in the infrastructure development to the educational sector, especially in developing countries higher institutions, using Nigeria as a case study.

Food banks play an increasingly important role in society by mitigating hunger and helping needy people; however, research aimed at improving food bank operations is limited.

This systematic review used Web of Science and Scopus as search engines, which are extensive databases in Operations Research and Management Science. Ninety-five articles regarding food bank operations were deeply analyzed to contribute to this literature review.

Through a systematic literature review, this paper identifies the challenges faced by food banks from an operations management perspective and positions the scientific contributions proposed to address these challenges.

This study makes three main contributions to the current literature. First, this study provides new researchers with an overview of the key features of food bank operations. Second, this study identifies and classifies the proposed optimization models to support food bank managers with decision-making. Finally, this study discusses the challenges of food bank operations and proposes promising future research avenues.

This study evaluates the impact of government social protection interventions on households’ welfare in South Africa.

The study uses survey data comprising 393 observations and the multinomial logistic regression technique to analyse the effect of government interventions on households’ welfare. For robustness purposes, a negative binomial regression model is also estimated whose results corroborate the main results from the multinomial regression model.

The study’s findings show that government economic interventions through social protection significantly reduce the likelihood of a decrease in household income or consumption. COVID-19 grant/social relief of distress grant, unemployment insurance, tax relief and job protection and creation are all significant in sustaining household income and consumption.

The findings have policy implications for social development. Specifically, the findings support the use of government social protection as a safety net for low-income groups in South Africa.

The study presents preliminary evidence on the effectiveness of several measures used to ameliorate the COVID-19-induced recession within the South African context.

The purpose of the paper is to analyze the new Bankruptcy Law in Saudi Arabia (KSA Bankruptcy Law) under both a comparative lens and a policy-oriented one, while highlighting some of the most essential operational steps and procedures in a bankruptcy proceeding under the law.

The approach adopted analyzes the specific mechanics and procedures of a bankruptcy law under the general policies and goals of bankruptcy. Additionally, where appropriate, a brief comparison to the US Bankruptcy code and its provisions is presented to provide an alternative approach on how similar issues are handled under a reputable and proven bankruptcy system.

Overall, the KSA Bankruptcy Law is a major accomplishment and advancement to the Kingdom’s insolvency regime. The law consolidated and codified the laws governing bankruptcy under the Kingdom’s prior regime, and followed the structure of a modern bankruptcy regime. In doing so, several of the law’s policies and objectives have been fulfilled by providing an effective, predictable and reliable bankruptcy system.

Given the relatively recent adoption of the KSA Bankruptcy Law, the paper provides a comprehensive assessment of the law’s operation and its effectiveness in achieving its policy goals as a modern bankruptcy law.

This study aims to deepen the understanding of the challenges and implications entailed by deploying mobile clinics in conflict zones to reach populations affected by violence and cut off from health-care services.

This research combines an integrated literature review and an instrumental case study. The literature review comprises two targeted reviews to provide insights: one on conflict zones and one on mobile clinics. The case study describes the process and challenges faced throughout a mobile clinic deployment during and after the Iraq War. The data was gathered using mixed methods over a two-year period (2017–2018).

Armed conflicts directly impact the populations’ health and access to health care. Mobile clinic deployments are often used and recommended to provide health-care access to vulnerable populations cut off from health-care services. However, there is a dearth of peer-reviewed literature documenting decision support tools for mobile clinic deployments.

This study highlights the gaps in the literature and provides direction for future research to support the development of valuable insights and decision support tools for practitioners.

Increasing trends of climatic risk pose challenges to the food security and livelihoods of smallholders in vulnerable regions, where farmers often face loss of the entire crop, pushing farmers (mostly men) out of agriculture in destitution, creating a situation of agricultural making agriculture highly feminization and compelling male farmers to out-migrate. Climate-smart agricultural practices (CSAPs) are promoted to cope with climatic risks. This study aims to assess how knowledge related to CSAPs, male out-migration, education and income contribute to the determinants of male out-migration and CSAPs adoption and how they respond to household food security.

Sex-disaggregated primary data were collected from adopter and non-adopter farm families. STATA 13.1 was used to perform principle component analysis to construct knowledge, yield and income indices.

Yield and income index of adopters was higher for men than women. The probability of out-migration reduced by 21% with adoption of CSAPs. An increase in female literacy by 1 unit reduces log of odds to migrate by 0.37. With every unit increase in knowledge index, increase in log-odds of CSAPs adoption was 1.57. Male:female knowledge gap was less among adopters. Non-adopters tended to reduce food consumption when faced with climatic risks significantly, and the probability of migration increased by 50% with a one-unit fall in the nutrition level, thus compelling women to work more in agriculture. Gender-equitable enhancement of CSAP knowledge is, therefore, key to safeguarding sustainable farming systems and improving livelihoods.

The enhancement of gender equitable knowledge on CSAPs is key to safeguard sustainable farming systems and improved livelihoods.

This study is based on the robust data sets of 100 each of male and female from 100 households (n = 200) using well-designed and validated survey instrument. From 10 randomly selected climate-smart villages in Samastipur and Vaishali districts of Bihar, India, together with focus group discussions, the primary data were collected by interviewing both men and women from the same household.