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Multiple stages of procurement for a product in a supply chain (SC) altogether form a “multi-Tier” supply network. The purpose of this paper is to develop and verify a systematic solution approach to ascertain the realistic cost advantage of a coordinated centralized sourcing strategy as compared to an isolated decentralized sourcing strategy for a multi-tier supply network under demand uncertainty.

The proposed systematic solution approach consists of seven steps to compare and contrast the cost advantage of a centralized coordinated sourcing strategy over a decentralized stage-wise sourcing strategy for a multi-tier supply network. A real-life automotive industry case analysis of two distinct products provides sufficient empirical evidence on the expected cost advantage of centralized coordinated sourcing strategy under demand uncertainty.

The case analysis affirms the practicability of the proposed seven-step solution approach to determine the realistic cost advantage of coordinated sourcing.

The scope of this research is restricted to a single product and two-tier supply network analysis. This research work also considers a restrictive assumption of negligible coordination cost.

The suitability of the proposed solution approach is verified using real-life case examples. This research provides theoretical insights and factual evidence to SC practitioners, so as to adopt a centralized sourcing strategy in a varied manufacturing environment.

There is no evidence of a systematic step-by-step solution approach to determine the cost advantage of a coordinated sourcing strategy over an isolated decentralized sourcing strategy for a multi-tier supply network under demand uncertainty.

This paper attempts to address three key objectives. The primary aim is to enhance sourcing strategy for a centralized and coordinated multitier multiple suppliers networks with uncertain demand and supplier failure risks. The second objective is to enumerate all possible practical supplier(s) failure scenarios and quantify expected loss of demand cost. Finally, the work illustrates statistical experimentation to identify “influential” variables that can significantly impact the expected supply network and loss costs.

A seven-step solution framework is proposed to derive an optimal sourcing strategy for the specific network configuration with varied supplier failure scenarios. Five distinct models are formulated to address all possible scenarios of supplier failure events. Mixed-integer nonlinear programming technique is used to derive expected supply network cost and loss cost. The solution framework is verified using a real-life case.

A cross-case analysis indicates that an increase in suppliers' failure risk (SFR) probabilities or customer demand rate increases the expected loss of demand costs for a multitier supply network. Besides, an increase in unit component prices increases the expected supply network cost.

A two-tier automotive supply network for a single product is considered for all case studies.

The enhanced strategy can facilitate practitioners enumerate different supply network failure scenarios and implement the best solution.

There is no evidence of earlier research to derive optimal sourcing strategy for a centralized, coordinated multitier multiple supplier's network, considering demand uncertainties and SFR.

The purpose of the present research is to explore the current situation and future expectations on whether to self‐manage or outsource logistics operations in centralized healthcare networks, and to analyse and quantify the relationships between logistics outsourcing, costs and performance.

The paper is based on a thorough study of a local Italian healthcare network, which evaluated the economic sustainability of logistics outsourcing. The data were collected using interviews, documentation and observations in hospital pharmacies and wards, and by referring to public information available on the internet. A system dynamic simulation followed by a sensitivity analysis was used to investigate the impact of changing key variables as well as the advice of logistics providers.

The sensitivity analysis demonstrates that logistics outsourcing is often the most economical choice.

Performance‐oriented concepts applied to healthcare have many pros in terms of sustainable delivery of quality healthcare at affordable costs.

While there are numerous studies on logistics outsourcing in many industries, when it comes to the healthcare sector literature is scarce, probably due to the great changes this sector has faced in recent times: thus, the paper's quantitative findings should be seen as a first attempt to assist the “make‐or‐buy” decision process toward sustainable development of the healthcare sector.

The purpose of this paper is to examine the impacts of supply chain management (SCM) benefits on the interactive performance between supply chain members.

The contingency theory and socio‐technical theory were applied in the construction of the research model. Four constructs were adopted for the development of the research model: contingency factors, interaction process, interactive performance, and SCM system benefits.

To respond to the challenges in global markets, an increasing number of enterprises strive for better profits by working closely with suppliers. As the interaction increases, the buyer‐seller relationship changes accordingly.

Empirical studies require further analysis and suggestions were also made for further explication.

The interaction between the manufacturing and marketing departments is a determinant for the firm's competitive advantages.

Interviews with six case firms in the information/electronic industry show that external and internal factors affect the interaction between supply chain members and result performance improvement.

The purpose of this paper is to investigate the level of concern and practice of sustainability development and also policy failure in the fast food supply chain.

A questionnaire using Likert scoring recorded variations in current practice and attitudes toward sustainable business. A two-stage cluster analysis was conducted to analyze the multi-attribute ordinal data obtained from the questionnaire.

Significant differences were found among clusters of fast food businesses in terms of their sustainability concern and practice, which is of interest to policy makers, consumers and supply chain partners. Medium-sized fast food dealers emerge with high environmental and social concern, but poor practice; larger retailers and fast food chains appear to have both fair social and environmental awareness and practice; and there is a cluster of small takeaway-specific outlets that have particularly low levels of knowledge of sustainability or sustainable practices. Policy failure is prevalent amongst these businesses and without regulation this represents a possible threat to the sector.

Reliance on stated rather than revealed preferences of the study may limit the implications of this analysis but it is a major step forward in understanding what has in the past been a very difficult sector to investigate due to data paucity.

Fast food is a sector with a lack of transparency which has attracted little academic attention to date, due to the difficulties of empirical analysis rather than lack of interest in a key food consumption sector. The message for the sector is to monitor its act, across all business types or face regulatory and policy intervention.

The research conducts a three-dimensional sustainability analysis of fast food supply chains to investigate the differences and trade-offs between different sustainability dimensions.

The study identifies nine important research areas and critically maps the structural relationships among supply chain resilience (SCRES) dimensions, namely, vulnerabilities, capabilities, strategies and performance metrics. The analysis also revealed various influential authors, journals, institutions and trending articles, across SCRES literature.

This study performs a bibliometric analysis of 771 articles published over the 32 years from 1988 to 2020, and network analysis in combination with content analysis of 90 most cited articles published in research fronts of SCRES.

The results demonstrate the underlying research areas within the SCRES, which are clustered into nine research themes: (1) conceptual development of SCRES, (2) recent developments of designing resilient supply chain (SC) networks, (3) focus on identifying drivers of SC vulnerability and risks, (4) impact of risks on network resilience, (5) risk assessment to avoid breakdowns/disruptions, (6) measuring resilience approaches/drivers to improve SC performance, (7) building resilient capabilities by integrating other SC dimensions, (8) quantification of SC network and (9) emphasis on developing robustness in SC networks.

This research offers implications for classifying the works in literature based on bibliometric information and network analysis techniques. This can help researchers and practitioners to understand the prominent areas in SCRES and provide guidelines for future research in this area.

This study provides an overview of the evolution of SCRES over time in the domain of supply chain management and also outlines a future research agenda claimed by the trending articles to encourage further investigations in the field of SCRES.

The main objective of this study is to consider how to benefit efficiently from the significant potential of humanitarian operations by individuals. For this purpose, this study aims to assess failure factors in humanitarian supply chain operations after the Kermanshah earthquake considering the role of all parties, focusing on individuals who did not wish to work with formal organisations on the whole. In the aftermath of the Kermanshah earthquake, which occurred on 12 November 2017, improvised groups of Iranian civilians from all over the country played an important role in humanitarian supply chain operations as individuals. Although most of these groups sincerely intended to help the affected society, victims could not benefit properly from these significant potential humanitarian actions. On the contrary, these potential actions caused some issues during humanitarian operations, such as blocking roads, inappropriate last-mile distribution, wasting resources and so on.

This research study considers mixed methods, including an on-site survey, semi-structured interviewing and a questionnaire designed for statistical analyses. The analysis included 140 responses to the questionnaire, semi-structured interviews with 32 affected families, interviews with 5 emergency managers from the Housing Foundation of the Islamic Republic of Iran and on-site survey reports.

This study presents a framework for humanitarian supply chain management to deal with future disasters in the same area or areas with similar characteristics to the case study. In general, the results of this study demonstrate that the nature of humanitarian supply chain operations makes it impossible to consider that these operations are free of challenges. However, several influential factors, such as training humanitarian actors and integrated management, might considerably increase the efficiency of humanitarian operations by individuals.

This study highlights the influential factors of inappropriate humanitarian operations by individuals, derived from an analysis of the Kermanshah case and literature review. The authors suggest a framework to benefit from the significant potential of individuals with wide-ranging experiences and proficiency, for future cases similar to the case study.

This study aims to analyze the competition of two financial chains (FCs) when the government intervenes in the financial market to prohibit the excessively high-interest rate by minimizing the arbitrages caused by speculative transactions. Each FC comprises an investor and one intermediary, attempts to finance the capital-constrained firms in financing needs.

Using a Stackelberg game theoretic framework and formulating two- and three-level optimization problems for six possible scenarios, the authors establish an integrative framework to evaluate the scenarios through the lens of the two main decision-making structures of the FCs (i.e. centralized and decentralized) and three policies of the government (i.e. speculation minimizing, revenue gaining and utility maximizing).

Solving the problem results in optimal values for tariffs, which guarantee a stable competitive market. Consequently, policymaking by the government influences the decision variables, which is shown in a numerical study. The authors find that the government can orchestrate the FCs in the competitive market by imposing tariffs and prohibiting high-interest rates via regulating the speculation impacts, which guarantees a stable market and facilitates the financing of capital-constrained firms.

This paper aids the financial markets and governments to control the interest rate by minimizing the speculation level.

This paper investigates the impact of government intervention policies – as a leading player – on the competition of FCs – as followers – in providing financial services and making profits. The government imposes tariffs on the interest rate to stabilize the market by limiting speculative transactions. The paper presents the mathematical models of the optimization problems through the game-theoretic framework and comparison of the scenarios through a numerical experiment.

This paper aims to study a dynamic post-disaster emergency planning (PDEP) problem in an integrated network through the investigation of the selection of shelters, medical centers and distribution centers (DCs), and the allocation of evacuees and injured people. The resource and people assignment in multiple periods are considered.

A mathematical formulation is provided for the PDEP problem. The authors decompose the model into two sub-models as follows: the primary model is an integer programming model and the subproblem is a nonlinear programming model with continuous variables. The simulated annealing is used to solve the primary problem, and particle swarm optimization (PSO) mixed with beetle antennae search (BAS) is used to solve the subproblem.

The paper finds that BAS can increase the stability of PSO and keep the advantages of PSO’s rapid convergence. By implementing these algorithms on emergency planning after the Wenchuan earthquake that happened in China in 2008, this paper finds that the priority of different levels of injured people is influenced by several factors. Even within the same disaster, the priority of different levels of injured can be inconsistent because of the differences in resource levels.

The authors integrate the shelters, medical centers and DCs as a system, and simultaneously, consider evacuees and injured people and different resource assignments. The authors divide the injured people into three levels and use survival rate function to simulate the survival conditions of different people. The authors provide an improved PSO algorithm to solve the problem.

Despite a growing body of research on the problem of increasing disaster preparedness by pre-positioning relief supplies at strategic locations, there is a lack of a benchmark set of problem instances that hinders thorough hypotheses testing, sensitivity analysis, model validation or solution procedure evaluation. The purpose of this paper is to address this issue by constructing a public library of diverse pre-positioning problem instances.

By carefully manipulating some of the instance parameters, the authors generated 30 case studies that were inspired by four instances collected from the literature that focus on disasters of different type and scale that occurred in different parts of the world. In addition, the authors developed a tool to algorithmically generate arbitrarily many diverse random instances of any size.

For many purposes, the problem library can eliminate or reduce the time-consuming process of data collection, conversion, digitization, calibration and validation, while simultaneously increasing the statistical significance of research results and allowing comparison with different works in the literature.

The case studies are inspired by only four disasters, and some of the instance parameters are defined in a reasonable, albeit arbitrary way. The instances are also limited by the underlying problem assumptions.

The instances provide a more comprehensive and balanced experimental setting (compared to a single case study) that can be used to study the pre-positioning and related problems, or derive managerial implications that can directly benefit the practitioners.

The instances can be used to derive practical guidelines that humanitarian workers can use on the ground to better plan their pre-positioning strategies and therefore minimize human suffering.

The case studies and the random instance generator are made publicly available to foster further research on the problem of pre-positioning relief supplies and humanitarian logistics in general.