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The purpose of this paper is to determine best practices of aid agencies for outsourcing logistics to commercial logistics service providers (LSPs) in disaster relief. Moreover, it evaluates the application of the Delphi method for research in humanitarian logistics.

The paper is based on a two-round Delphi study with 31 experts from aid agencies and a complementary full-day focus group with 12 experts from aid agencies and LSPs.

The study revealed 12 best practices for outsourcing logistics in disaster relief and a compilation of more than 100 activities for putting these practices into action. Experts consider a proper balance between efficiency and compliance, a detailed contract and a detailed service request most important. Additionally, the Delphi method was found to be a promising technique for research on humanitarian logistics.

By critically examining the Delphi method, this study establishes the basis for a wider application of the technique in the field of humanitarian logistics. Furthermore, it can help to prioritize future research as the ranking of practices reflects the priorities of practitioners.

The paper provides guidance to practitioners at aid agencies in charge of outsourcing logistics.

This research is one of the first in the field of humanitarian logistics to apply the Delphi method. Moreover, it addresses the lack of literature dealing with approaches for building successful cross-sectoral partnerships.

The purpose of this paper is to explore the perceptions of supply chain managers regarding the elements that make up cyber supply chain risk management (CSCRM) and the related level of alignment, to understand how organizations can deploy a CSCRM strategy that goes beyond the technical, internal functioning of single companies and moves beyond the dyad, to create a better alignment that can ultimately lead to improved cyber supply chain resilience.

An exploratory survey in the fast-moving consumer goods (FMCG) industry involving over 100 organizations in Italy was conducted. Results were analysed through one-way analysis of variance, to appraise the differences in the perceptions of the various actors of the FMCG supply chain (Manufacturers, Logistics Service Providers, Retailers).

While a certain degree of alignment of the perceptions across the FMCG supply chain exists, the study found that Logistics Service Providers can play a crucial role as orchestrators of the CSCRM process towards a more “supply chain-oriented” response to cyber threats and risk events. The research also highlights the necessity to see people as key elements for improving cyber resilience in the supply chain.

Through a vertical analysis of a supply chain, the study extends the existing theory on CSCRM, which contains isolated case studies. It also contributes to extending the current theory with the proposal of the paradigm of Logistics Service Providers as orchestrators of the CSCRM process. The study combines different classifications of CSCRM initiatives and embraces theories external to the supply chain literature.

Through the empirical analysis, this study helps practitioners in streamlining the design of cyber security strategies and actions that span across the supply chain for better alignment. This could mean more coordination of efforts and more targeted/accurate investments in CSCRM initiatives. The study invites practitioners to ponder the perceived relevance of the human factor as a source of risk and the perceived importance of countermeasures aimed at mitigating risk events stemming from that source.

By focusing on an entire supply chain, this is one of the first studies on CSCRM that goes beyond the dyad. Its originality also lies in its use of the investigations of perceptions along the supply chain as pillars for the alignment of CSCRM strategies and mitigation initiatives. This original perspective allows for discovering the role of Logistics Service Providers in driving the alignment of the efforts towards better outcomes of the CSCRM process.

The purpose of this study is to elaborate on how analytics capability develops within the PSM function. This study is an in-depth exploration of how analytics capability develops within the purchasing and supply management (PSM) function.

A multiple case study was conducted of the PSM function of six case firms, in which primary data were collected through semi-structured interviews with PSM analytics stakeholders. The data were analyzed based on an analytics capability framework derived from the literature. Cases were chosen based on them having advanced PSM practices and ongoing analytics projects in the PSM area.

The findings shed light on how the firms develop their analytics capability in the PSM functional area. While we identify several commonalities in this respect, the authors also observe differences in how firms organize for analytics, bringing analytics and PSM decision-makers together. Building on the knowledge-based view of the firm, The authors offer a theoretical explanation of our observations, highlighting the user-driven side of analytics development, which has largely been unrecognized by prior literature. The authors also offer an explanation of the observed dual role that analytics takes in cross-functional initiatives.

The exploratory nature of our study limits the generalizability of our results. Further, our limited number of cases and interviewees indicate that there is still much to explore in the phenomenon of developing analytics capability.

Our findings can help firms gain a better understanding of how they could develop their analytics capability and what issues they need to consider when seeking leveraging data through analytics for PSM decisions.

This paper is, to the best knowledge of the authors, the first empirical study of analytics capability in PSM.

The practice of consanguinity has been culturally preferred in most Arab countries, including Morocco. This behavior leads to an increase in genetic abnormalities, such as hypertension and diabetes. This paper examines the prevalence and determinants of first-cousin marriages and their impact on diabetes among offspring.

Data on 882 couples were collected through face-to-face interview via a pre-established questionnaire based on the variables selected within the objectives of this study. The authors used the multiple logistic regression modeling procedure in this study.

The results of the study indicate that the prevalence of first-cousin marriages were 15% among students’ parents. From the multiple logistic regression modeling, the authors found a significant effect of paternal and maternal grandparents’ first-cousins marriage on that of parents (aOR = 3.27 and aOR = 3.36, respectively). However, an 11-fold higher risk of first relative marriages among parents once the paternal and maternal grandparents were first-cousins and the father was illiterate (aOR = 11.01). Moreover, the authors reported a diabetes risk of more than 14 times when the effects of first-cousin maternal grandparents and parents and the hypertension among mother or her sibling were combined (aOR = 14.48) or when the effects of first-cousins maternal grandparents, first-cousin parents and mother’s age at marriage between 21 and 29 years were combined (aOR = 14.56).

First-cousin marriage depends on the father’s illiteracy and the consanguinity of grandparents’ factors. The cumulative effect of first-cousin marriage among grandparents, parents and a family history of hypertension among mother or her sibling increase the risk of diabetes among these mothers.

This study advocates the importance of taking an evolutionary perspective in the strategic configuration of closed-loop supply chains (CLSC) in the transition to a circular economy. Building on the supply chain management and industrial dynamics research domains, an evolutionary analytical framework was developed and applied in the empirical context of the ongoing industrial transition to e-mobility.

This study is designed as an in-depth exploratory case study to capture the multi-layer dynamic complexities and their interplay in CSLC development. The empirical investigation was based on two-year interactions between the authors and various departments in a leading European heavy vehicle manufacturer. The proposed evolutionary analytical framework was used for investigating the dynamics of four CLSC configurations through ten possible trajectories.

The findings demonstrate that the evolution of each CLSC configuration comes with multiple challenges and requirements and point out the necessity for the co-development of technologies, product design and production, and infrastructure through long-term relationships among key supply chain actors. However, this evolutionary journey is associated with multiple dilemmas caused by uncertainties in the market and technology developments. All these factors were properly captured and critically analyzed, along with their interactions, thanks to the constructs included in the proposed evolutionary analytical framework.

The proposed evolutionary framework is applicable for examination of SC transformation in the context of market and technology development, and is particularly relevant for transitioning from linear SC to CLSC. The framework offers a single actor perspective, as it does not directly tackle dynamics and effects of actions taken by SC actors.

The developed framework can support SC managers in identifying, framing, and comparing alternative strategies for CLSC configuration in the transition process.

This study proposes the framework for understanding and guiding the evolutionary process of CLSC development. Its uniqueness lies in the integration of concepts from innovation and evolutionary theories coming from industrial dynamics and SCM literature streams.

Understanding the supply network of construction materials used to construct shelters in refugee camps, or during the reconstruction of communities, is important as it can reveal the intricate links between different stakeholders and the volumes and speeds of material flows to the end-user. Using social network analysis (SNA) enables another dimension to be analysed – the role of commonalities. This is likely to be particularly important when attempting to replace vernacular materials with higher-performing alternatives or when encouraging the use of non-vernacular methods. This paper aims to analyse the supply networks of four different disaster-relief situations.

Data were collected from interviews with 272 displaced (or formally displaced) families in Afghanistan, Bangladesh, Nepal and Turkey, often in difficult conditions.

The results show that the form of the supply networks was highly influenced by the nature/cause of the initial displacement, the geographical location, the local availability of materials and the degree of support/advice given by aid agencies and or governments. In addition, it was found that SNA could be used to indicate which strategies might work in a particular context and which might not, thereby potentially speeding up the delivery of novel solutions.

This study represents the first attempt in theorising and empirically investigating supply networks using SNA in a post-disaster reconstruction context. It is suggested that future studies might map the up-stream supply chain to include manufacturers and higher-order, out of country, suppliers. This would provide a complete picture of the origins of all materials and components in the supply network.

This is original research, and it aims to produce new knowledge.

The purpose of this paper is to explore the relationship between leadership and business model innovation (BMI) in an entrepreneurial firm. From the literature, it was found that the role of a leader in BMI was unexplored. A research framework was created which was the replication of the model created showing the relationship between leadership and innovation.

The qualitative single in-depth case study was used to understand the effects of leadership in BMI. The case of an entrepreneurial firm in the graphic and animation education sector from India was chosen to test the research framework. The leader of Xplora Design Skools was observed closely, and he was interviewed multiple times.

From the analysis, it was clear that, in this organization, the leader was a trigger for BMI through creating and influencing creativity and innovation in the organization. This case also shows that he was making tangible contribution to the work being done and motivating his employees. These initiatives show his influence on the process or execution of BMI.

This is the first study explores the role of a leader in BMI in an entrepreneurial firm in emerging economy contexts like India.

Unforeseen events can disrupt the operational process and negatively impact emergency resources optimization and its supply chain. A limited number of studies have addressed risk management issues in the context of emergency supply chains, and this existing research lacks inbuilt and practical techniques that can significantly affect the reliability of risk management outcomes. Therefore, this paper aims to identify and practically analyze the specific risk factors that can most likely disrupt the normal functioning of the emergency supply chain in disaster relief operations.

This paper has used a three-step process to investigate and evaluate risk factors associated with the emergency supply chain. First, the study conducts a comprehensive literature review to identify the risk factors. Second, the research develops a questionnaire survey to validate and classify the identified risk factors. At the end of this step, the study develops a hierarchical structure. Finally, the research investigates the weighted priority of the validated risk factors using the fuzzy-analytical hierarchy process (FAHP) methodology. Experts were required to provide subjective judgments.

This paper identified and validated 28 specific risk factors prevalent in emergency supply chains. Based on their contextual meanings, the research classified these risk factors into two main categories: internal and external risk factors; four subcategories: demand, supply, infrastructural and environmental risk factors; and 11 risk types: forecast, inventory, procurement, supplier, quality, transportation, warehousing, systems, disruption, social and political risk factors. The most significant risk factors include war and terrorism, the absence of legislative rules that can influence and support disaster relief operations, the impact of cascading disasters, limited quality of relief supplies and sanctions and constraints that can hinder stakeholder collaboration. Therefore, emergency supply chain managers should adopt appropriate strategies to mitigate these risk factors.

This study will contribute to the general knowledge of risk management in emergency supply chains. The identified risk factors and structural hierarchy taxonomic diagram will provide a comprehensive risk database for emergency supply chains.

The research findings will provide comprehensive and systemic support for respective practitioners and policymakers to obtain a firm understanding of the different risk categories and specific risk factors that can impede the effective functioning of the emergency supply chain during immediate disaster relief operations. Therefore, this will inform the need for the improvement of practices in critical aspects of the emergency supply chain through the selection of logistics and supply chain strategies that can ensure the robustness and resilience of the system.

This research uses empirical data to identify, categorize and validate risk factors in emergency supply chains. This study contributes to the theory of supply chain risk management. The study also adopts the fuzzy-AHP technique to evaluate and prioritize these risk factors to inform practitioners and policymakers of the most significant risk factors. Furthermore, this study serves as the first phase of managing risk in emergency supply chains since it motivates future studies to empirically identify, evaluate and select effective strategies that can eliminate or minimize the effects of these risk factors.

The purpose of this paper is to understand the nomological network of associations between collective mindfulness and big data analytics in fostering resilient humanitarian relief supply chains.

The authors conceptualize a research model grounded in literature and test the hypotheses using survey data collected from informants at humanitarian aid organizations in Africa and Europe.

The findings demonstrate that organizational mindfulness is key to enabling resilient humanitarian relief supply chains, as opposed to just big data analytics.

This is the first study to examine organizational mindfulness and big data analytics in the context of humanitarian relief supply chains.