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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.

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.

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.

Bipolar and depression disorders are some of the most common mental health disorders affecting millions of people in low-and middle-income countries, including those in Africa. These disorders are therefore major contributors to the burden of diseases and disability. While an enhancement in income is seen as a major approach towards reducing the burden of these disorders, empirical evidence to support this view in the African context is lacking. This study therefore aims to examine the effect of per capita income growth on bipolar and depression disorders across African countries.

The study uses data from secondary sources comprising 42 African countries over the period, 2002–2019, to achieve its objective. The prevalence of bipolar and major depressive disorders (depression) are used as the dependent variables, while per capita income growth is used as the main independent variable. The system Generalised Method of Moments regression is used as the estimation technique.

In the baseline, the authors find per capita income growth to be associated with a reduction in the prevalence of bipolar (coefficient: −0.001, p < 0.01) and depression (coefficient: −0.001, p < 0.1) in the short-term. Similarly, in the long-term, per capita income growth is found to have negative association with the prevalence of bipolar (coefficient: −0.059, p < 0.01) and depression (coefficient: −0.035, p < 0.1). The results are similar after robustness checks.

This study attempts at providing the first empirical evidence of the effect of per capita income growth on bipolar and depression disorders across several African countries.

Over recent years, the multi-stakeholder role in sustainable ecotourism within Asia has emerged as a crucial narrative for sustainable ecotourism management across countries on the continent. This trend is perhaps due to the fact that ecotourism is one of the most rapidly growing sectors within the tourism industry. However, to date, no reviews have provided a comprehensive analysis related to the role of multi-stakeholders in the achievement of ecotourism sustainability, particularly in the Asian context. This study aims to fill this knowledge gap by examining the current knowledge regarding multi-stakeholder involvement in sustainable ecotourism within Asia.

A systematic review procedure was followed. 320 articles were finalized, from which 34 related pieces of research were selected from the Scopus and Web of Science databases.

Three themes emerged from this paper. Recommendations were highlighted to enhance sustainable ecotourism. The study concluded that a more enabling research environment should be provided to improve discourse and encourage policy interventions.

No previous studies have explored the multi-stakeholder's role in achieving Asian sustainable ecotourism, indicating a critical gap to be fulfilled. This paper uniquely contributes to the field by providing a comprehensive review of the roles and challenges of multiple stakeholders in sustainable ecotourism across Asia and proposing innovative policy solutions tailored to the region's unique socio-economic and cultural context. Moreover, it puts forward potential solutions to bolster sustainable ecotourism within Asia, benefiting both stakeholders and the destination.