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The purpose of this paper is to understand how big data and predictive analytics (BDPA), as an organizational capability, can improve both visibility and coordination in humanitarian supply chains.

The authors conceptualize a research model grounded in contingent resource-based view where the authors propose that BDPA capabilities affect visibility and coordination under the moderating effect of swift trust. Using ordinary least squares regression, the authors test the hypotheses using survey data collected from informants at 205 international non-government organizations.

The results indicate that BDPA has a significant influence on visibility and coordination. Further, the results suggest that swift trust does not have an amplifying effect on the relationships between BDPA and visibility and coordination. However, the mediation test suggests that swift trust acts as a mediating construct. Hence, the authors argue that swift trust is not the condition for improving coordination among the actors in humanitarian supply chains.

The major limitation of the study is that the authors have used cross-sectional survey data to test the research hypotheses. Following Guide and Ketokivi (2015), the authors present arguments on how to address the limitations of cross-sectional data or use of longitudinal data that can address common method bias or endogeneity-related problems.

Managers can use this framework to understand: first, how organizational resources can be used to create BDPA, and second, how BDPA can help build swift trust and be used to improve visibility and coordination in the humanitarian supply chain.

This is the first research that has empirically tested the anecdotal and conceptual evidence. The findings make notable contributions to existing humanitarian supply chain literature and may be useful to managers who are contemplating the use of BDPA to improve disaster-relief-related activities.

The purpose of this paper is to identify the issues and challenges in humanitarian logistics and to develop a framework for effectively managing the humanitarian logistics in disaster relief supply chain operations in India.

This paper presents a framework to manage humanitarian logistics effectively in disaster management through qualitative analysis. First, the author examines the challenges facing the humanitarian logistics and supply chain through the reviews of the literature on various disasters. Then, the author presented a framework based on the best practices and initiatives taken worldwide in the preparedness and response stage of the humanitarian supply chain to manage and reduce the aftermath of any disaster in context to India.

A framework has been developed to manage humanitarian logistics in the disaster relief operation, which would improve the humanitarian supply chain in India and help to effectively manage natural disasters in the preparedness and response stage at the state and district levels.

The paper mainly emphasises on the preparedness and response stage of disaster supply chain management in Indian context.

None of the disaster incidents can be stopped from taking place, but the impact can be minimised by proper preparedness and effective response during the operations of humanitarian logistics. With this hope, the framework has been developed, which if implemented would help to plan and manage any disaster incident in an effective manner, which ultimately would save millions of lives and cost in terms of infrastructure, property, assets etc.

As natural disaster incidents are occurring frequently in Indian states, there is an urgent need for a framework to manage the logistics operations effectively and efficiently during any disaster relief operations. Limited literature is found on developing and presenting a framework focusing on the preparedness and response phase of disaster supply chain management in context to India. Hence, this paper is believed to be the first to fulfil this gap with main emphasis on the preparedness and response stage of disaster supply chain management in Indian scenario.

The study aims to have adults discuss experiences, practices needs and feelings related to health management, diet and food security.

A total of 22 immigrants were recruited from the Open School of Immigrants in Piraeus, Attica, Greece, to participate in focus group discussions. The discussions were audio recorded and thematically analyzed. Three major themes were developed: pathways to health care, nutrition management and experiences related to food shortages.

Most of the participants identified internet as the most commonly used way to obtain health advice; they also stated that unexpected ill-health is usually accompanied by feelings of fear, anxiety and loneliness. Immigrants, who had visited a public hospital in Greece, identified the language barrier as the most challenging issue, followed by the long waiting lists. Fear and anxiety of hospital visits was an important factor in their decision to vaccinate against COVID-19. Lack of time, high cost of healthy food and lack of knowledge were the most common obstacles to a healthy diet. One in two immigrants reported that they have faced food insecurity issues in the past. Stress, psychological distress and irritation were reported, due to food shortages, especially during the first few years of arriving in Greece. The exclusion of some foods, reduced portion sizes and buying cheaper foods were among the coping strategies to address food shortages.

The study offers an insight into immigrant’s experiences, practices and feelings about managing health issues and could be useful for health-care practitioners, researchers and policymakers.

Risk response decisions (RRDs) are vital for project risk mitigation. Although past research has focused on RRDs for independent single projects, it has scarcely explored how to make RRDs for single projects in project portfolios (SPPPs). Consequently, this study aims to bridge the gap in extant literature by developing an integrated approach to select risk response strategies (RRSs) for SPPPs considering objective adjustments and project interdependencies (PIs).

An integrated quality function deployment (QFD) method was used throughout this study. More so, a balanced score card (BSC) and stratified-Z-numbers-full consistency method (SZFUCOM) was applied to identify SPPP success criteria (SP3SC) to determine their weights. In addition, a spherical fuzzy set-design structure matrix (SFDSM) was used to quantify the correlation between the risks and the relationship between the risks and the predecessor projects. Consequently, the relationships between the risks and SP3SC and RRSs were described by the spherical fuzzy set (SFS) and Z-numbers, respectively. Besides, the results are weaved into QFD to transform SP3SC into risks and then into RRSs, while a linear optimization model is used to obtain the optimal RRSs. Lastly, a construction project portfolio (PP) was used to test the veracity of the results to prove their validity.

The approach to RRDs for single projects is observed to be different from that of SPPPs. In addition, this study finds that project portfolio objective adjustments (PPOAs) and PIs have significant impacts on RRDs given that they influence the risk priorities of independent single projects and SPPPs. Moreover, the application of an integrated QFD effectively synthesized the results from the findings of this study, as well as enabled companies to determine robust RRSs. Finally, the consistency results of the SZFUCOM were better than those of the triangular fuzzy number-full consistency method.

The study innovatively explores the method of RRDs for SPPP, which has been ignored by past research. SP3SC highly compatible with PP success is determined. Z-numbers are first used to evaluate the effect of RRSs to enhance the robustness of RRDs. The study proposes a method of RRDs comprehensively considering PPOAs and PIs, which provides robust methodological guidance for SPPP managers to control risks.

The purpose of this paper is to introduce a novel approach to studying disaster management operations: the emergence of coordination-clusters in long-term rehabilitation projects and innovation dynamics in coordination-clusters.

The problem addressed is examining the coordination dynamics in long-term rehabilitation operations. A mixed methods research approach was adopted where a combination of qualitative and quantitative techniques was used for data collection and analysis to study the phenomenon of the coordination evolution in long-term rehabilitation projects.

The results indicate resilience in the behavior of involved actors from different organizations as they re-organize into coordination-clusters and collectively work to overcome the unfolding challenges of long-term rehabilitation projects in areas affected by major disaster.

The results provide some answers to the question of how to map and analyze the phenomenon of coordination-clusters and their consequent coordination dynamics, and thereby steps to redesign the approach to execute long-term rehabilitation projects in places affected by major disasters.

The combination of Actor-network theory and critical incident technique with social network analysis and community detection provides an integrated network-based view of coordination dynamics in long-term recovery operations. Such perspective would broaden the empirical basis for the planning and management of complex disaster management operations.

The results of the research offer a new approach to study coordination dynamics in disaster management operations. The proposed method provides a tool to examine the evolution of processes involved with the recovery phase of a disaster management cycle.

A fleet of mobile robots has been effectively used in various application domains such as industrial plant inspection. This paper proposes a solution to the combined problem of task allocation and motion planning problem for a fleet of mobile robots which are requested to operate in an intelligent industry. More specifically, the robots are requested to serve a set of inspection points within given service time windows. In comparison with the conventional time windows, our problem considers fuzzy time windows to express the decision maker’s satisfaction for visiting an inspection point.

The paper develops a unified approach to the combined problem of task allocation and motion planning for a fleet of mobile robots with three objectives: (a) minimizing the total travel cost considering all robots and tasks, (b) balancing fairly the workloads among robots and (c) maximizing the satisfaction grade of the decision maker for receiving the services. The optimization problem is solved by using a novel combination of a Genetic Algorithm with pareto solutions and fuzzy set theory.

The computational results illustrate the efficiency and effectiveness of the proposed approach. The experimental analysis leverages the potential for using fuzzy time windows to reflect real situations and respond to demanding situations.

This paper provides trade-off solutions to a realistic combinatorial multi-objective optimization problem considering concurrently the motion and path planning problem for a fleet of mobile robots with fuzzy time windows.

This study considers a project scheduling model to assess the project risks and the impacts on project sustainability when subcontractors collaborate under uncertainty. Moreover, some allocation methods are applied for fair allocating utility of the project and supper-additivity, stability and satisfaction level of each coalition. Finally, sustainability concept is considered in risk assessment in all coalitions.

The proposed mathematical programming model evaluates project risks when the subcontractors cooperate with each other by sharing their limited resources. Then, some cooperative game theory methods are applied for fair allocation of net present value, of the cooperation and finally sustainability aspects (economic, social and environmental) are investigated in risk assessment for each possible coalition.

The results of the proposed model indicate that the subcontractors can increase their profit by 10 per cent ($14,028,450 thousand) and save the equilibrium between sustainability aspects especially in grand coalition. It means that subcontractors do not have incentive to leave the coalition and the supper-additive property is feasible. Furthermore, risk assessment shows that project risks have less impact on subcontractor profits when they cooperate with each other.

Sustainability aspects may be investigated in project management in previous studies, but the authors study sustainability indicators when subcontractors form a coalition and share their resources in response to the risks of availability to resources and delay in completing the project under uncertainty.

This research is about embedding service-based supply chain management (SCM) concepts in the education sector. Due to Canada's competitive education sector, the authors focus on Canadian universities.

The authors develop a framework for evaluating and forecasting university performance using data envelopment analysis (DEA) and artificial neural networks (ANNs) to assist education policymakers. The application of the proposed framework is illustrated based on information from 16 Canadian universities and by investigating their teaching and research performance.

The major findings are (1) applying the service SCM concept to develop a performance evaluation and prediction framework, (2) demonstrating the application of DEA-ANN for computing and predicting the efficiency of service SCM in Canadian universities, and (3) generating insights to enable universities to improve their research and teaching performances considering critical inputs and outputs.

This paper presents a new framework for universities' performance assessment and performance prediction. DEA and ANN are integrated to aid decision-makers in evaluating the performances of universities.

The findings suggest that higher education policymakers should monitor attrition rates at graduate and undergraduate levels and provide financial support to facilitate research and concentrate on Ph.D. programs. Additionally, the sensitivity analysis indicates that selecting inputs and outputs is critical in determining university rankings.

This research proposes a new integrated DEA and ANN framework to assess and forecast future teaching and research efficiencies applying the service supply chain concept. The findings offer policymakers insights such as paying close attention to the attrition rates of undergraduate and postgraduate programs. In addition, prioritizing internal research support and concentrating on Ph.D. programs is recommended.

This paper sets out to discuss practical inventory control systems. Orthodox theory revolves around the purchaser and balances ordering costs against charges for carrying goods in stock. However, for any company holding thousands of different items the directives for constructing the best system(s) are confusing and the logic seems inconsistent. The research objective is to clarify this hitherto unsatisfactory situation and to provide robust guidelines for managing such inventories.

A small number of published examples are described in sufficient detail to reveal what these firms actually do. Each case is dissected to uncover management's motives, since the original reports were not embellished with useful analytical comments. The aim is to reconstruct the overall design process.

The myopic standpoint of established models neglects the impact of various ordering policies at the supplier's end, where the promotion of cost‐effective and responsive warehouse and transport operations is paramount. As a rule, both areas benefit from stable resources planning, based on cyclic orders and delivery schedules along fixed vehicle routes.

An alternative “top down” approach is proposed. The main thrust is the efficient deployment of a designated transport fleet. Also, some salient points are made concerning the relative merits of P‐ and Q‐type stock replenishment modes.

The paper provides a new perspective on stock control that brings theory into line with modern supply chain management concepts.

Examines the literature to identify the essential components of kaizen or continuous improvement programmes. Relying on published sources on the North American experience with continuous improvement, also tries to identify organizational structures and practices likely to lead to successful implementation of such programmes. Distinguishes between kaizen and more radical, “strategic leap” improvement approaches, and describes the North American record of success with continuous improvement programmes. An emergent theme is that success with continuous improvement requires a wide array of systems, processes, and orientations to be congruent within the organization. Argues that the study of when, how, and why kaizen succeeds is by no means complete, and proposes a set of open research questions whose investigation is likely to be useful to both scholars and practitioners. Finally, discusses some of the ways in which the existing literature can be immediately useful for practice in organizations.