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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.

As the Chinese economy has grown rapidly and as its container throughputs has demonstrated a stark increase in recent decades, companies worldwide have developed stronger financial connections with supply chain entities in China, a huge “Production Factory” in the world. This global economic trend arouses significant attention to distinct preference of individual entities in supply chain. The primary goal of the study is to establish statistical understanding on factors of logistics service preferences of each supply chain of each supply chain entity in China, especially Shandong Province. Ultimately, the study aims i) to establish the solid framework for proper evaluation of logistics services in supply chains, ii) to enhance the preferences of logistics services as a differentiating feature on behalf of entities. The study utilizes a holistic approach in analyzing logistics service attributes which affect overall logistics entities in an effort to overcome the limitations of previous studies which failed to provide integrating viewpoint of supply chain entities. In this study, AHP (Analytic Hierarchy Process) method is used as an analysis tool which allows an in-depth examination of the differences between factors and evaluations of customers regarding the logistics service attributes. The results clearly show distinctive service preferences for each four supply chain entities in Shandong Province of China such as 3PLs (forwarder, carrier, and warehouse), Customs (airport, seaport, and bonded area), Market channels (wholesaler, retailer, and e-retailer), and Manufacturers regarding the logistics service attributes.

This study introduces three variables related to brands that have the potential to enhance university students' advocacy intentions. The research explores how university brand identification, the perceived prestige of the university brand and the social benefits associated with the university brand impact students' advocacy intentions. Additionally, the study examines the moderating role of gender in these relationships.

Cross-sectional surveys of 326 undergraduate students enrolled in a Spanish university, and structural equation modeling was used to test and validate the conceptual model.

The findings from the structural equation modeling indicate that university brand identification, perceived university brand prestige and university brand social benefits significantly influence students' advocacy intentions. Furthermore, the multigroup analysis reveals a gender difference in the factors influencing advocacy intentions. Female students demonstrate significance in all three antecedents, whereas male students only show significance in university brand identification and perceived university brand prestige.

The current study's findings provide several insights for higher education institutions in developing enduring and committed relationships with their students.

This study offers relevant insights into the body of research on university branding, explaining the students' advocacy intentions through the variables of university brand identification, perceived university brand prestige and university brand social benefits. Also, this study is a novelty in introducing empirical evidence for the importance of the moderating role of students' gender.

This study aims to examine and understand the impact of reverse logistics adoption on firms' digitalization and collaboration activities. Specifically, leveraging the knowledge-based view, this study examines how adopting sustainable logistic practices (reverse logistics) prepares firms to embrace digitalization and encourages them to collaborate with other organizations.

The study used longitudinal survey data from two waves (2017 and 2019) from the Mannheim Centre for European Economic Research. The authors used the negative binomial regression analyses to test the impact of reverse logistics adoption on the digitalization and inter-organizational collaboration dependent count variables.

The study's findings highlight the usefulness of reverse logistics in enabling digitalization and inter-organizational collaboration. The results show that the firms investing in sustainable supply chains will be better positioned to nurture digitalization and inter-organizational collaboration.

For resource-bound managers, this study provides an important insight into prioritizing activities by highlighting how reverse logistics can facilitate digitalization and collaboration. The study demonstrates that the knowledge generated by reverse logistics adoption can be an essential pillar and enabler toward achieving firms' digitalization and collaboration goals.

The study is among the first to examine the effect of reverse logistics adoption on firm activities that are not strictly associated with the circular economy (digitalization and collaboration). Utilizing the knowledge-based view, this study reports on the additional benefits of reverse logistics implementation previously not discussed in the literature.

Twenty-first century online retailing has reshaped the retail landscape. Grocery shopping is emerging as the next fastest growing category in online retailing in the UK, having implications for the channels we use to purchase goods. Using Sainsbury’s data, the authors create a bespoke set of grocery click&collect catchments. The resultant catchments allow an investigation of performance within the emerging channel of grocery click&collect. The paper aims to discuss these issues.

The spatial interaction method of “Huff gravity modeling” is applied in a semi-automated approach, used to calculate grocery click&collect catchments for 95 Sainsbury’s stores in England. The catchments allow investigation of the spatial variation and particularly rural-urban differences. Store and catchment characteristics are extracted and explored using ordinary least squares regression applied to investigate “demand per day” (a confidentiality transformed revenue value) as a function of competition, performance and geodemographic factors.

The findings show that rural stores exhibit a larger catchment extent for grocery click&collect when compared with urban stores. Linear regression finds store characteristics as having the greatest impact on demand per day, adhering to wider retail competition literature. Conclusions display a need for further investigation (e.g. quantifying loyalty).

New insights are contributed at a national level for grocery click&collect, as well as e-commerce, multichannel shopping and retail geography. Areas for further investigation are identified, particularly quantitatively capturing brand loyalty. The research has commercial impact as the catchments are being applied by Sainsbury’s to decide the next 100 stores and plan for the next five years of their grocery click&collect offering.

The transition to omnichannel retail is the recognized future of retail, which uses digital technologies (e.g. augmented reality shopping assistants) to enhance the customer shopping experience. However, retailers struggle with the implementation of such technologies in brick-and-mortar stores. Against this background, the present study investigates the impact of a smartphone-based augmented reality shopping assistant application, which uses personalized recommendations and explainable artificial intelligence features on customer shopping experiences.

The authors follow a design science research approach to develop a shopping assistant application artifact, evaluated by means of an online experiment (n = 252), providing both qualitative and quantitative data.

Results indicate a positive impact of the augmented reality shopping assistant application on customers' perception of brick-and-mortar shopping experiences. Based on the empirical insights this study also identifies possible improvements of the artifact.

This study's assessment is limited to an online evaluation approach. Therefore, future studies should test actual usage of the technology in brick-and-mortar stores. Contrary to the suggestions of established theories (i.e. technology acceptance model, uses and gratification theory), this study shows that an increase of shopping experience does not always convert into an increase in the intention to purchase or to visit a brick-and-mortar store. Additionally, this study provides novel design principles and ideas for crafting augmented reality shopping assistant applications that can be used by future researchers to create advanced versions of such applications.

This paper demonstrates that a shopping assistant artifact provides a good opportunity to enhance users' shopping experience on their path-to-purchase, as it can support customers by providing rich information (e.g. explainable recommendations) for decision-making along the customer shopping journey.

This paper shows that smartphone-based augmented reality shopping assistant applications have the potential to increase the competitive power of brick-and-mortar retailers.

This study aims to propose a service robot option to address shortages of human frontline employees (FLEs) in long-term care (LTC) service settings. With a field study, the authors investigate the effect of psychological comfort with robot reminders of LTC residents and human FLEs on acceptance and attentive engagement, ultimately resulting in effort and willingness to interact with the service robot. The outcomes provide valuable insights into human-robot interaction in the LTC sector.

The 45 residents and 49 human FLEs who participated in the field study completed a survey measuring various perceptual variables after deploying a service robot.

Both the residents’ sample and the FLE sample demonstrate that psychological comfort with robot reminders increases robot acceptance. This increased acceptance evokes greater attentive engagement, ultimately leading to a higher willingness to exert effort to interact with the service robots.

This study highlights service robots with well-received reminder functions and the ability to prompt efforts by both residents and employees during their implementation at LTC services. The findings suggest further research avenues for designing service robots that can be effectively integrated.

This study leverages a service robot in a field study involving LTC residents and human FLEs rather than hypothetical scenarios, which is rather limited in current studies. The findings are both timely and relevant, considering the gradual implementation of service robots into LTC services.