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This study aims to help understand individual donors’ preferences over different designs of humanitarian–business partnerships in managing humanitarian operations and to help understand if donors’ preferences align with their actual donation behavior.

Choice-based conjoint analysis was used to understand donation preferences for partnership designs, and a donation experiment was performed using real money to understand the alignment of donors’ preferences with actual donation behavior.

The results show that partnering with the business sector can be a valuable asset for humanitarian organizations in attracting individual donors if these partnerships are managed well in terms of partnership strategy, partnership history and partnership report and disclosure. In particular, the study finds that the donation of services and products from businesses corporations to humanitarian organizations are preferable to individual donors, rather than cash. Furthermore, donors’ preferences are not necessarily aligned with actual donation behavior.

The results highlight the importance of presenting objective data on projects to individual donors. The results also show that donors value the provision of services and products by business corporations to humanitarian operations.

Partnerships between humanitarian organizations and business corporations are important for the success of humanitarian operations. However, little is known about which partnership designs are most preferable to individual donors and have the biggest chance of being supported financially.

The purpose of this study is to develop a methodology which amalgamates quantitative and qualitative approaches to determine the best placement of mobile logistics hubs (MLH) to be established in different parts of Nepal as a part of real-life project, “Augmentation of National and Local-Level Emergency Logistics Preparedness in Nepal” (2017–2020), implemented by the World Food Programme in cooperation with the Government of Nepal.

The study develops a methodology using a combination of a modified version of the maximal covering location problem (MCLP) and focus group discussion. The MCLP model is used to determine the optimal number and spatial location of MLHs, and focus group discussion is used to identify the five first-priority strategic MLH locations using expert knowledge.

The authors identify the five first-priority locations for establishing MLHs using an amalgamation of quantitative approach (mathematical model) and qualitative approach (focus group discussion). By amalgamating mathematical model with expert knowledge, findings acceptable to a wide range of stakeholders are obtained. The focus group discussion helps to pinpoint the location of MLHs to city-level granularity which is otherwise impossible with data available on hand.

Although multiple experts’ judgements were obtained via focus group discussion, subjectivity and possible bias is inevitable. Overall, the quantitative results of the study are purely based on the data available during the study period; therefore, having updated data could possibly improve the quality of the results.

This study is the first of its kind that uses an amalgamation of mathematical model and expert knowledge to determine the strategic locations of MLHs and has been successful to an extent that the selected locations have been vetted by the government of Nepal for establishing MLHs and are undergoing implementation in real life. This study also considers multiple disaster scenarios and employs the concepts of human development, disaster risk and transportation accessibility to reflect Nepal's socioeconomic, geo-climatic and topographical features.

The purpose of this paper is to apply social theory to the creation of a mass-media communications intervention designed to encourage earthquake-resistant construction in Nepal.

A three-step process was employed in this study: first, a narrative literature review was completed regarding the motivation of protective action. Second, key informant elicitation interviews with 15 community members at five public schools who supported making their buildings earthquake-resistant informed the script for a documentary film. Finally, the film was reviewed with stakeholders, plus 16 community members associated with a school in need of seismic work. Sociograms were used to determine relative closeness of the study participants to the film role models.

Motivating factors identified in the literature synthesis were included in the film, which focussed on effective actions taken by role models, and avoided the use of fear-based appeals. Key informant interviews yielded role-modeling details for the film script, including triggers and obstacles faced by the community members, and outcomes of their actions. Sociogram outcomes guided film editing and increased relative screen time for those community members with whom the study participants felt greater closeness. A pretest-posttest cluster randomized trial (details reported elsewhere) showed greater gains in knowledge, perceived outcome effectiveness, and intended behaviors among intervention film viewers than control participants.

This three-step process yielded the information required by a practitioner to develop a theory-based, culturally appropriate mass-media intervention designed to motivate reduction of disaster risk.

Spam emails classification using data mining and machine learning approaches has enticed the researchers' attention duo to its obvious positive impact in protecting internet users. Several features can be used for creating data mining and machine learning based spam classification models. Yet, spammers know that the longer they will use the same set of features for tricking email users the more probably the anti-spam parties might develop tools for combating this kind of annoying email messages. Spammers, so, adapt by continuously reforming the group of features utilized for composing spam emails. For that reason, even though traditional classification methods possess sound classification results, they were ineffective for lifelong classification of spam emails duo to the fact that they might be prone to the so-called “Concept Drift”. In the current study, an enhanced model is proposed for ensuring lifelong spam classification model. For the evaluation purposes, the overall performance of the suggested model is contrasted against various other stream mining classification techniques. The results proved the success of the suggested model as a lifelong spam emails classification method.

Chiang Rai being an earthquake-prone city, it is essential to raise awareness about earthquake safety and readiness, especially amongst the elderly population who spend most of their time at home. The purpose of this paper is to evaluate the earthquake preparedness of elders in relation to knowledge, attitude and practice.

This was an analytic cross-sectional study. Research data were collected from 480 elders of 60 years old and above. The research instruments were questionnaires about knowledge, attitude and self-assessment of practices in earthquake situations. Data were analyzed by number, percentage and a χ² test.

Of participants interviewed, 39.4 percent were aged between 60 and 66 years old. Overall, 94.0 percent of them had already experienced an earthquake, with 79.4 percent having experienced it in 2014. Participants had a good level of knowledge and attitude toward earthquake safety. Their practices toward earthquake readiness, however, were insufficient due to the lower practice scores (<12), especially found in the high seismic zone. The score level of knowledge, attitude and self-assessment of practice in earthquake situations showed that there is a difference in statistical significance (p<0.05).

This study focuses attention on the need to increase levels of preparedness. Safety instructions and earthquake drills should be promoted and supported in order to prepare elders for an earthquake in the study area. Research findings identified in this study will help to address the specific needs of the elderly when implementing an earthquake disaster risk reduction plan.

This study aims to evaluate the perception of the local experts and end users on the drivers, barriers and strategies to the use of alternative building technologies (ABTs), with a focus on sandbag building technologies (SBTs) in the provision of sustainable housing in South Africa towards improving the public's understanding of SBTs.

This research adopted a qualitative approach that used focus group meetings as the primary data collection method for this study. This study's focus group participants comprised ABT experts and end users of ABT houses in South Africa who were selected using a convenient sampling technique. The data were recorded, transcribed verbatim and analysed using NVivo 11 software.

This study found that the perceived drivers to using ABTs such as SBT comprise sustainability, affordability, job creation potentials, fire-resistant and earthquake resistance. This study revealed strategies for the SBTs, including awareness, building sandbag prototypes across cities and training.

This study's findings have practical implications for the practice and praxis of ABT implementation and uptake in South Africa. This study provides a framework for broadening the worldwide understanding of use and uptake of SBTs to provide sustainable and affordable housing.

This study adds significantly to the limited body of knowledge on ABTs, focusing on sandbag houses. Consequently, the findings provide policymakers with information on the expert and end-user perspectives on the barriers and strategies to using ABTs.

This study aims to explore the challenges and complexities of interaction in international stakeholder networks within the context of projects focused on the implementation of sustainable development goals (SDGs). In particular, it examines the challenges faced by stakeholders in a network from a developed country during interaction in the context of a developing country.

Using a qualitative approach, this study analyses interview data collected from the key managers of an international consulting company in charge of a water supply and sanitation project in Nepal. The primary data is triangulated with secondary data, such as project reports and related academic articles.

This study illustrates how interaction in international stakeholder networks affects and is interrelated with SDGs, as well as how aiming to achieve one specific goal can stimulate the implementation of other sustainable goals. Further, this research shows how project managers from a developed country had to adapt to the specifics of the developing country context and how their sustainability project influenced the well-being of local communities by improving environmental and social sustainability.

The research suggests that challenges in stakeholder interaction may arise because of differences in process management methods used by the international stakeholders involved in the project and country-context specifics, such as corruption, imperfect national regulations, cultural specifics, effects of climate change, etc.

The paper contributes to the literature on international multi-stakeholder interaction between actors from developed and developing countries. Furthermore, it adds to the literature on stakeholder networking by highlighting the importance of engaging in a dialogue with local communities during the conceptualisation stages of both sustainability and SDG implementation because of diverging worldviews and practices.

Disasters and armed conflict often co-occur, but does that imply that disasters trigger or fuel conflict? In the small but growing body of literature attempting to answer this question, divergent findings indicate the complex and contextual nature of a potential answer to this question. The purpose of this study is to contribute a robust cross-country analysis of the co-occurrence of disaster and conflict, with a particular focus on the potential role played by disaster.

Grounded in a theoretical model of disaster–conflict co-occurrence, this study merges data from 163 countries between 1990 and 2017 on armed conflict, disasters and relevant control variables (low human development, weak democratic institutions, natural resource dependence and large population size/density).

The main results of this study show that, despite a sharp increase in the co-occurrence of disasters and armed conflict over time, disasters do not appear to have a direct statistically significant relation with the occurrence of armed conflict. This result contributes to the understanding of disasters and conflicts as indirectly related via co-creation mechanisms and other factors.

This study is a novel contribution, as it provides a fresh analysis with updated data and includes different control variables that allow for a significant contribution to the field.

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.