scholarly journals Strategic and Tactical Design of Competing Decentralized Supply Chain Networks with Risk-Averse Participants for Markets with Uncertain Demand

2011 ◽  
Vol 2011 ◽  
pp. 1-27 ◽  
Author(s):  
Ashkan Hafezalkotob ◽  
Ahmad Makui ◽  
Seyed Jafar Sadjadi

An integrated equilibrium model for tactical decisions in network design is developed. We consider a decentralized supply chain network operating in markets under uncertain demands when there is a rival decentralized chain. The primary assumption is that two chains provide partial substitutable products to the markets, and markets' demands are affected by tactical decisions such as price, service level, and advertising expenditure. Each chain consists of one risk-averse manufacturer and a set of risk-averse retailers. The strategic decisions are frequently taking precedence over tactical ones. Therefore, we first find equilibrium of tactical decisions for each possible scenario of supply chain network. Afterwards, we find optimal distribution network of the new supply chain by the scenario evaluation method. Numerical example, including sensitivity analysis will illustrate how the conservative behaviors of chains' members affect expected demand, profit, and utility of each distribution scenario.

2018 ◽  
Vol 2018 ◽  
pp. 1-18
Author(s):  
Tirazheh Zare-Garizy ◽  
Gilbert Fridgen ◽  
Lars Wederhake

Globalization and outsourcing are two main factors which are leading to higher complexity of supply chain networks. Due to the strategic importance of having a sustainable network, it is necessary to have an enhanced supply chain network risk management. In a supply chain network many firms depend directly or indirectly on a specific supplier. In this regard, unknown risks of network’s structure can endanger the whole supply chain network’s robustness. In spite of the importance of risk identification of supply chain network, firms are not willing to exchange the structural information of their network. Firms are concerned about risking their strategic positioning or established connections in the network. The paper proposes to combine secure multiparty computation cryptography methods with risk identification algorithms from social network analysis to address this challenge. The combination enables structural risk identification of supply chain networks without endangering firms’ competitive advantage.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Chongfeng Lan ◽  
Jianfeng Zhu

New product presale is a strategic behavior of manufacturers to transfer inventory risks to consumers. The research purpose of this paper is to examine the presale discount, inventory, and service level decisions in an e-commerce supply chain, where the first period is the presale period and the second is the selling period for the new product. First, consumers were divided into two types—those who are risk averse and those who are not. Then, considering different presale discounts applied for new products, three presale strategy models were discussed: no-presale strategy, presale strategy with a moderate discount, and complete presale strategy, and the optimal decisions of e-commerce supply chain members were obtained under different valuations of the new product by consumers. Finally, the effects of the correlation coefficient between the numbers of the two types of consumers, the loss aversion degree of consumers, and the marginal profit in the sales period on the optimal discounted price and the maximum expected profit were analyzed. The conclusions of this article show that the presale strategy is not always optimal but depends on the parameters of the market and the type of consumers. For example, when the correlation coefficient between the two types of consumers is high, it is more profitable for the suppliers if they choose the presale strategy with a moderate discount, while e-commerce platforms tend to adopt the no-presale strategy. The optimal discounted price in the complete presale case is not necessarily lower than that in the moderately discounted presale case. If the marginal profit is high in the normal sales period or consumers are less averse to losses, suppliers are more likely to adopt the complete presale strategy. The research conclusions provide some theoretical reference for companies in the development of new product presale strategies in the e-commerce supply chain.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amir Rahimzadeh Dehaghani ◽  
Muhammad Nawaz ◽  
Rohullah Sultanie ◽  
Tawiah Kwatekwei Quartey-Papafio

PurposeThis research studies a location-allocation problem considering the m/m/m/k queue model in the blood supply chain network. This supply chain includes three levels of suppliers or donors, main blood centers (laboratories for separation, storage and distribution centers) and demand centers (hospitals and private clinics). Moreover, the proposed model is a multi-objective model including minimizing the total cost of the blood supply chain (the cost of unmet demand and inventory spoilage, the cost of transport between collection centers and the main centers of blood), minimizing the waiting time of donors in blood donating mobile centers, and minimizing the establishment of mobile centers in potential places.Design/methodology/approachSince the problem is multi-objective and NP-Hard, the heuristic algorithm NSGA-II is proposed for Pareto solutions and then the estimation of the parameters of the algorithm is described using the design of experiments. According to the review of the previous research, there are a few pieces of research in the blood supply chain in the field of design queue models and there were few works that tried to use these concepts for designing the blood supply chain networks. Also, in former research, the uncertainty in the number of donors, and also the importance of blood donors has not been considered.FindingsA novel mathematical model guided by the theory of linear programming has been proposed that can help health-care administrators in optimizing the blood supply chain networks.Originality/valueBy building upon solid literature and theory, the current study proposes a novel model for improving the supply chain of blood.


2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Yixin Zhou ◽  
Zhen Guo

With the advent of the era of big data (BD), people’’s living standards and lifestyle have been greatly changed, and people’s requirements for the service level of the service industry are becoming higher and higher. The personalized needs of customers and private customization have become the hot issues of current research. The service industry is the core enterprise of the service industry. Optimizing the service industry supply network and reasonably allocating the tasks are the focus of the research at home and abroad. Under the background of BD, this paper takes the optimization of service industry supply network as the research object and studies the task allocation optimization of service industry supply network based on the analysis of customers’ personalized demand and user behavior. This paper optimizes the supply chain network of service industry based on genetic algorithm (GA), designs genetic operator, effectively avoids the premature of the algorithm, and improves the operation efficiency of the algorithm. The experimental results show that when m = 8 and n = 40, the average running time of the improved GA is 54.1 s. The network optimization running time of the algorithm used in this paper is very fast, and the stability is also higher.


2019 ◽  
Vol 15 (2) ◽  
pp. 54-68 ◽  
Author(s):  
Jian Tan ◽  
Guoqiang Jiang ◽  
Zuogong Wang

In the supply chain network, information sharing between enterprises can produce synergistic effect and improve the benefits. In this article, evolutionary game theory is used to analyse the evolution process of the information sharing behaviour between supply chain network enterprises with different penalties and information sharing risk costs. Analysis and agent-based simulation results show that when the amount of information between enterprises in supply chain networks is very large, it is difficult to form a sharing of cooperation; increase penalties, control cost sharing risk can increase the probability of supply chain information sharing network and shorten the time for information sharing.


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