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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.

Globalization and population explosion have worsened postharvest losses (PHL) in developing countries. This study looks to identify numerous controllable variables to reduce these losses and make the fresh produce supply chain more efficient.

The study employs the interpretive structural modelling (ISM) technique to develop a hierarchical model to comprehend the intricate relationships between the variables influencing PHL. These variables are further classified based on the relative levels of importance in terms of their driving and dependence powers.

The findings of this research provide variables for enterprises operating in fresh food supply chains to understand the specific risks that that supply chain faces and how these risks interact within the system. The fuzzy MICMAC analysis also classifies and highlights critical risk factors in the supply chain to aid implementation of PHL mitigation measures. The study highlights the importance of devising policies, legislation and efforts to regulate and curtail PHL across the global food supply chain.

The efficiency of the food supply chain contributes not only to economic sustainability but also to broader goals such as food security, better utilisation of global resources and sustainability in the supply chain.

It also highlights the significance of well-informed government policies, laws and regulations in successfully controlling and reducing PHL.

This study compares factors contributing to PHL in the fresh produce supply chain and emphasises the stakeholders’ critical role in alleviating these losses. It also highlights the significance of well-informed government policies, laws and regulations in successfully controlling and reducing PHL.

The purpose of this paper is to integrate branding and higher education literature to conceptualize, develop, and empirically examine a model of university social augmenters’ brand equity.

Drawing on an empirical survey of 401 undergraduate students enrolled in private universities in Egypt, this study model was tested using structural equation modeling.

The findings reveal that university social augmenters’ reputation, coach-to-student interactions, and student-to-student interactions influence students’ satisfaction with social augmenters. The results also suggest that students satisfied with university social augmenters are more likely to exhibit outcomes of brand equity – namely, brand identification, willingness to recommend, and willingness to incur an additional premium cost.

The results offer managerial implications for university administrators in their quest to enrich students’ university experiences and build strong sub-brands within the university setting. University social augmenters are found to have strong brand equity manifestations and may hold the potential to differentiate university brands in an industry dominated by experience and credence.

This research contributes to the extant literature by filling two gaps in university branding literature. First, previous research has never unified separate streams of literature related to augmented services and brand equity. Second, limited conceptual and empirical research on university branding in general and university social augmentation in particular has been conducted in emerging markets, which has resulted in conceptual ambiguity for the key factors constructing students’ university social experiences.