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The purpose of this study is to examine supply network designs that large service organisations use in the residential-FM sector to respond to the organising requirements of their operating environments.

The study is theoretically grounded in the well-established literature on the organisational design and structural contingency theory. Utilising a framework of generic organising problems proposed by Miles and Snow (1978) and a multiple-case study design, the study elaborates how large service organisations organise and manage their supply networks in the Finnish residential-FM sector.

The study identifies four supply network designs that organisations use for responding to the organising problems inherent in the property and resident services domains in the residential-FM sector. These include regional production organisation, horizontal decentralisation, environment stabilisation and demand – supply pooling, reflecting the type of the service-market domain and the organisation’s service strategy.

The study contributes to the facilities management literature by expanding the field of inquiry from the commercial real estate sector into the emerging field of professional residential facility services. In particular, the study adds to the discussion on supply strategies and design, offering a service provider perspective to the organisation of service supply in housing.

Supply chain risk management can effectively reduce the loss of retailers. In this regard, retailers need to consider the competition risks of competitors in addition to the disruption risks. This paper designs a resilient retail supply chain network for perishable foods under the dynamic competition to maximize retailer's profits.

A two-stage mixed-integer non-linear model is presented for designing the supply chain network. In the first stage, an equilibrium model that considers the characteristics of perishable foods is developed. In the second stage, a mixed integer non-linear programming model is presented to deal with the strategic decisions. Finally, an efficient memetic algorithm is designed to deal with large-scale problems.

The optimal the selection of suppliers, distribution centers and the order allocation are found among the supply chain entities. Considering the perishability of agri-food products, the equilibrium retail price and selling quantity are determined. Through a numerical example, the optimal inventory period under different maximum shelf life and the impact of three resilient strategies on retailer's profit, selling price and selling quantity are analyzed.

As for future research, the research can be extended in a number of directions. First, this paper studies the retail supply chain network design problem under competition among retailers. It can be an interesting direction to consider retailers competing with suppliers. Second, the authors can try to linearize the non-linear model and solve the large-scale integer programming problem by exact algorithm. Finally, the freshness of perishable foods gradually declines linearly to zero as the maximum shelf life approaches, and it would be a meaningful attempt to consider the freshness of perishable foods declines exponentially.

This paper innovatively designs the resilient supply chain network for perishable foods under dynamic competition. The retailer's dynamic competition and resilient strategies are considered simultaneously when designing supply chain network for perishable foods. In addition, this paper gives insights into how to obtain the optimal inventory period and compare the retailer's resilient strategies.

As globalisation makes supply networks more complex, the risk of material disruptions increases. Many factors have been considered as affecting the reliability of supply networks. However, no empirical research has been carried out to assess and evaluate the impact of each of these factors on the reliability of supply networks. This paper aims to address this issue.

A gap in the literature was identified around the evaluation of the impact of supply network design characteristics on reliability. This gap is addressed by performing a full factorial experimental design considering all the factors described in the literature, and then analysing (by using analysis of variance and linear regression models), thousands of theoretical and extreme structures of supply networks, thus allowing the analysis of the influence of each factor on the overall network resilience.

Results show that network density, node criticality and complexity are significant factors in reducing the reliability of supply networks. In particular, node complexity (i.e. the total number of nodes in the network) was found to have the strongest negative effect on network reliability, while the strongest positive factor was sources criticality (i.e. the level of redundancy of suppliers).

The identification of these factors and their relative impacts on network reliability can serve as a guide for the design of more reliable networks, and to know which are the most important to consider when designed distribution networks.

The paper identifies, from the literature, key factors affecting supply network reliability and evaluates their relative impact. Given the number of factors identified, an extensive Monte Carlo simulation is used for the first time, by considering simple and very complex networks, to allow the testing of the role of each factor in supply network reliability.

The purpose of this paper is to assist a manufacturing firm in designing the closed-loop supply chain network under risks that are affecting its supply quality and logistics operations. The modeling approach adopted aims at the embedding supply chain risks in a closed-loop supply chain (CLSC) network design process and suggests optimal supply chain configuration and risk mitigation strategies.

The method proposes a closed-loop supply chain network and identifies the network parameter and variables required for closing the loop. Mixed-integer-linear-programming-based mathematical modeling approach is used to formulate the research problem. The solutions and test results are obtained from CPLEX solver.

The outcomes of the proposed model were demonstrated through a case study conducted in an Indian hospital furniture manufacturing firm. The modern supply chain is mapped to make it closed loop, and potential risks in its supply chain are identified. The supply chain network of the firm is redesigned through embedding risk in the modeling process. It was found that companies can be in great profit if they follow closed-loop practices and simultaneously keep a check on risks as well. The cost of making the supply chain risk averse was found to be insignificant.

Although the study was conducted in a practical case situation, the obtained results are not indiscriminate to the other circumstances. However, the approach followed and proposed methodology can be applied to many industries once a firm decides to redesign its supply chain for closing its loop or model under risks.

By using the identified CLSC parameters and applying the proposed network design methodology, a firm can design/redesign their supply chain network to counter the risk and accordingly come up with planned mitigation strategies to achieve a certain degree of robustness.

Supply chains need to balance competing objectives; in addition to efficiency, supply chains need to be resilient to adversarial and environmental interference and robust to uncertainties in long-term demand. Significant research has been conducted designing efficient supply chains and recent research has focused on resilient supply chain design. However, the integration of resilient and robust supply chain design is less well studied. The purpose of the paper is to include resilience and robustness into supply chain design.

The paper develops a method to include resilience and robustness into supply chain design. Using the region of West Africa, which is plagued with persisting logistical issues, the authors develop a regional risk assessment framework and then apply categorical risk to the countries of West Africa using publicly available data. A scenario reduction technique is used to focus on the highest risk scenarios for the model to be tractable. Next, the authors develop a mathematical model leveraging this framework to design a resilient supply network that minimizes cost while ensuring the network functions following a disruption. Finally, the authors examine the network's robustness to demand uncertainty via several plausible emergency scenarios.

The authors provide optimal sets of transshipment hubs with varying counts from 5 through 15 hubs. The authors determine there is no feasible solution that uses only five transshipment hubs. The authors' findings reinforce those seven transshipment hubs – the solution currently employed in West Africa – is the cheapest architecture to achieve resilience and robustness. Additionally, for each set of feasibility transshipment hubs, the authors provide connections between hubs and demand spokes.

While, at the time of this research, three other manuscripts incorporated both resilience and robustness of the authors' research unique solved the problem as a network flow instead of as a set covering problem. Additionally, the authors establish a novel risk framework to guide the required amount of redundancy, and finally the out research proposes a scenario reduction heuristic to allow tractable exploration of 512 possible demand scenarios.

The purpose of this study is to systematically review the existing literature on the blood supply chain (BSC) from a network design perspective and highlight the research gaps in this area. Moreover, it also aims to pinpoint new research opportunities based on the recent innovative technologies for the BSC network design.

The study gives a comprehensive systematic review of the BSC network design studies until October 2021. This review was carried out in accordance with preferred reporting items for systematic reviews and meta-analyses (PRISMA). In the literature review, a total of 87 studies were analyzed under six main categories as model structure, application model, solution approach, problem type, the parties of the supply chain and innovative technologies.

The results of the study present the researchers’ tendencies and preferences when designing their BSC network models.

The study presents a guide for researchers and practitioners on BSC from the point of view of network design and encourages adopting innovative technologies in their BSC network designs.

The study provides a comprehensive systematic review of related studies from the BSC network design perspective and explores research gaps in the collection and distribution processes. Furthermore, it addresses innovative research opportunities by using innovative technologies in the area of BSC network design.

Supply chain network design is an important strategic decision that firms make considering both the short‐ and long‐term consequences of the network's performance. The typical design approach implicitly assumes that, once designed, the facilities and the links will always operate as planned. In reality, however, facilities and the links connecting them, fail from time to time due to poor weather, natural or man‐made disasters, or a combination of any other factors. This work aims to propose a design framework that addresses the facility and link failures explicitly by accounting for their impact on a network's performance measures of efficiency and robustness.

The study incorporated a robustness metric for evaluating the resiliency of supply chains in the case of a network disruption. This robustness metric is based on expected losses incurred due to network failures. It defines efficiency and robustness in terms of operational cost and expected disruption cost (EDC), respectively. The EDC is defined in terms of loss of opportunity cost incurred due to not meeting demand on time after a disruption has occurred. The study used a scenario planning approach and formulated a mixed integer linear program model with the objective of maximizing both efficiency and robustness. It also evaluates the trade‐offs between efficiency and robustness.

The resulting supply chain is much more reliable in the long term since we have shown that a significant amount of robustness can be built into the system without compromising a lot on efficiency.

This work demonstrates a methodology which incorporates such disaster scenarios into the design of a supply chain network. This leads to a more reliable supply chain which would lead to higher profitability and lower disruption rates.

This chapter proposes a multiobjective model to design a Closed Loop Supply Chain (CLSC) network. The first objective is to minimize the total cost of the network, while the second objective is to minimize the carbon emission resulting from production, transportation, and disposal processes using carbon cap and carbon tax regularity policies. In the third objective, we maximize the service level of retailers by using maximum covering location as a measure of service level. To model the proposed problem, a physical programming approach is developed. This work contributes to the literature in designing an optimum CLSC network considering the service level objective and product substitution.

This study aims to design a proper supply chain network for the vaccine industry in Iran, which considers several features such as uncertainties in demands and cost, perishability of vaccines, wastages in storage, limited capacity and different priorities for demands.

This study presents a mixed-integer linear programming (MILP) model and using a robust counterpart approach for coping with uncertainties of model.

The presented robust model in comparison with the deterministic model has a better performance and is more reliable for network design of vaccine supply chain.

This study considers uncertainty in the network design of vaccine supply chain for the first time in the vaccine context It presents an MILP model where strategic decisions for each echelon and tactical decisions among different echelons of supply chain are determined. Further, it models the difference between high- and low-priority demands for vaccine.

A sustainable selection method for facility location of the water treatment is formulated by best–worst method. In addition, the model addresses the selection of appropriate technologies in the treatment plant, management of water leakage in the whole transmission network by using modernization and selection of different transmission technologies. Finally, the interaction between water and energy in this network seems to be paying particular attention.

Rapid population growth and urban development, and the constraints of water supply have become one of the crucial challenges around the world in the 21st century. Hence, the use of refined urban wastewater is increasing in many countries as an alternative source of water. In this regard, the rehabilitation of urban wastewater recycling and reuse has been proposed as one of the most suitable solutions for urban water management. Hence, in this paper, a mathematical model is formulated to design the simultaneous marketing of the urban water distribution network and wastewater treatment (including).

It seeks to ensure that energy is supplied through chemical methods to ensure that the system's energy dependence is on the national electricity grid. And in order to validate the model, a case study has been studied. By analyzing the results, it can be concluded that the upgrading of sewage treatment plants to replace underground water and water from nearby dams in household, agricultural and industrial applications will have positive environmental and economic impacts. One of the notable environmental impacts is the decline in groundwater and water scarcity in the coming years.

The summary of contributions is presented follow as: design and planning of water and urban wastewater integrated network; sustainable selection of facility location for the water treatment; capability selecting different treatment technologies in simultaneous design water and urban sewage supply chain; managing water leak in the network; proposed a water–energy nexus model in simultaneous design water and urban sewage supply chain; studying the feasibility of construction of power plants from biogas, the resulting of anaerobic digestion in treatment centers.