Agent-based simulation of competitive performance for supply chains based on combined contracts
Introduction
The market environment facing enterprises has become much more complicated and uncertain (Whang, 2015, Fleischhacker and Fok, 2015). In such a complex market environment, enterprises that rely on themselves alone cannot achieve competitive advantage to meet the requirements of complicated situations. Supply chain management is becoming a key competitive weapon that has the ability to increase operational efficiency, reduce costs and improve competitiveness. Thus, the form of competition for enterprises is evolving from competition among enterprises to competition among supply chains (Xiao and Yang, 2008).
To obtain advantages in competition, all supply chain members are expected to behave consistently to achieve supply chain coordination. While centralized supply chain control assures channel coordination, it may not be realistic. In decentralized control, the supply chain members optimize local decisions without consideration of the impact that their decision has on the other member's performance and on the overall performance of the supply chain. Thus, there is a need for coordination in the supply chain.
Supply chain contracts are effective instruments to conquer the conflicting objectives between supply chain members and to motivate all members to be a part of the entire supply chain (Chan and Chan, 2010). They ensure the provision of appropriate incentives so agents act in accordance with the wishes of principals, as well as cause the benefits and risks to be shared by both sides.
However, the supply chain structure is very complex and multi-level in reality. Different types of contracts may be adopted between members in different distinct interfaces for the various targets, thus forming the case for combined contracts in supply chains. We take the sale of household appliances as an example. As this type of product has short product life cycles, retailers do not wish to stock products in large quantity to avoid demand risk. However, upstream distributors can obtain considerable profits by selling large numbers of products during periods of strong sales. Distributors may therefore adopt a buy-back contract to stimulate the retailer to order more products. To gain competitive advantage on price, distributors and manufacturers usually use a revenue-sharing contract, which allow distributors to obtain products at a very low price; they will then allocate the profits through negotiation.
The various types of combined contracts caused by the reasons stated above will cause different effects on the numerous sectors of multi-echelon supply chains, including mode of operation, coordination mechanisms, optimization goals, profit allocation among the members, etc. Therefore, under the influence of a complex market environment and complex competitive relationships, different types of combined contracts will exhibit different competitive performance when multi-echelon supply chains compete together in a market.
In the practice of supply chain management, what are the effects of combined contracts on the level of profit and earnings stability of the supply chain and related members? How will members set combined contracts suitably to win competition in a complex market environment? These are highly relevant problems.
From the analysis of the existing literature, we can see that the study of combined contracts in multi-tier supply chains has not considered competition between chains generally; the study of competition between supply chains is only for a two-tier supply chain and does not consider combined contracts and the specific contract types. Thus, compared with the existing literature, this paper makes the following contributions.
First, few studies have focused on the impact that combined contracts have on supply chain competition performance. In this paper, we built a multi-agent model of four three-level supply chains that apply different types of combined contract competition in a complex market environment; we mainly observe the impact that different types of combined contracts have on the competition performance of the supply chains and relevant members using some indicators to evaluate agents’ profit size and earnings stability. The objective of this paper is to help multi-level supply chains choose the appropriate types of combined contracts in a complex and changing market environment and enhance its competitiveness correspondingly.
Second, existing studies have made a less detailed consideration of profit distribution between enterprises; however, profit distribution among enterprises is the embodiment of the vertical competition relationship in supply chains and is key for effective contract implementation. Thus, it should be regarded as the constraining condition to realize the overall performance of the supply chain in the studies. In competitive processes among supply chains, there are two types of competition. The first is vertical competition between the upstream and downstream enterprises, and the second is the industry's horizontal competition among same-level firms (Banker et al., 1998, Glock and Kim, 2015). Vertical and horizontal competition both have a direct impact on members' income, so the members adopt contracts to achieve two main objectives: one is to increase the total supply chain profits to make it closer to profits resulting from centralized control, while the other is to share risk among partners. We consider horizontal competition and vertical competition (profit distribution) in our model. Most importantly, we not only are concerned with competition between supply chains but also focus on the profit distribution among the members within a chain. We designed the profit distribution rules of chain members in detail, which makes the theoretical model more realistic and improves the rationality and effectiveness of the research results.
In addition, this paper considers a more complex dynamic market environment. In reality, the market demand for an enterprise is affected by many uncertain factors, such as consumer preferences, product returns, emergence of new products, competitors’ marketing strategies, weather and so on. Consumer preferences have become more diverse, and the requirements for the functions and services of merchandise are also accounting for more diverse tastes. Predicting market demand well and accurately is becoming increasingly difficult for enterprises. Some enterprises allow consumers to return products to stimulate sales growth, but if consumers feel that items do not fit their needs or match their tastes, they may return products, which increases demand uncertainty. For example, in the United States, the return rate from consumers to manufacturers or retailers is in the range of 6–15% (Xiao et al., 2010). As the pace of product replacement accelerates or the life cycle of product shortens, the emergence of new products will change the market size. We may lose our market share because of a variety of surprise marketing strategies adopted by competitors. Even the vagaries of weather also impact market demand. The U.S. National Research Council has estimated that 46% of U.S. gross domestic product is affected by weather (Chen and Yano, 2010). Moreover, numerous unobservable factors also affect demand and make our market more complex and uncertain.
In summary, considering some scenarios, which include changing consumer preferences and demand uncertainty, we construct an agent-based simulation model to primarily observe the impact of different types of combined contracts on the competition performance of supply chains and relevant members using profits and profit stability indicators in the scenarios above, thus revealing influence mechanisms that more systematically show the effect of combined contracts on chain-chain competition and corporate profit performance.
As supply chain systems involve many heterogeneous agents who have autonomous decision-making capacity, these agents can adjust their behavior according to the external market environment change or others' strategy adjustments. Therefore, interactions between agents and the environment or among agents always show non-linear, dynamic and close relationships (Ashmos et al., 2002). For the reasons above, we will use multi-agent modelling to build our model and adopt the corresponding object-oriented programming techniques to generate the agents participating in supply chain systems. The participating agents who interact with each other may “emerge” various behaviors and phenomena out of system from the bottom up. We will then build a simulation model that can be controlled and repeated to simulate supply chain members’ interactions and the general phenomenon. This study will consider not only profit distribution among members within a chain at the micro level, but will also take into account competition performance between the supply chains from the macro level. Lastly, we will determine the active management implications through comparative analysis of the experimental results.
The remainder of this paper is structured as follows. Section 2 presents a brief review of the literature on supply chain contracts, supply chain competition and agent-based simulation in supply chains. Section 3 describes our simulation model and experiment design in detail. Section 4 presents the results of the simulation studies. Section 5 summarizes the insights gained from this study.
Section snippets
Supply chain contracts
A contract can be defined as an agreement between two parties. A supply chain contract is the set of many clauses that offer suitable information and incentive mechanism to guarantee that all the firms in the supply chain achieve coordination and optimize channel performance (Cachon, 2003). Supply chain contracts formally govern transactions between the supply chain actors and later utilize incentives (risk and rewards) to make the supply chain members’ decisions consistent with one another.
Notations of parameters in experiments
Notations and meanings of agents’ parameters in model are shown in Table 1.
Experimental model
The experimental model considers four types of competing supply chains. Each supply chain is a three-level system with a manufacturer, distributor and retailer; their upstream-downstream relations remain unchanged during the operation process. There are three situations for using contracts between enterprises: not using contracts, using buyback contracts, or using revenue-sharing contracts. The combination form of
Competitive performance without considering changes in market parameters
In this experiment, we assumed that the total market demand () is a random variable meeting the normal distribution without considering the changes of market parameters over time, such as consumer price preference, service preference and demand uncertainty, to investigate the impact of different types of combined contracts on the coordinative effect and competitive performance of a supply chain and its members. The experimental results of product retail price and service levels in
Conclusions
When members in distributed supply chains face demand uncertainty, coordination contracts are critical tools in achieving a “balanced” solution among enterprises. However, supply chains using different types of combined contracts will lead to different performance results under different uncertain conditions. This paper presents a model of four supply chains competing together in a demand uncertainty market through agent-based simulation. The structure of each chain has three levels, including
Acknowledgements
We appreciate the comments from anonymous reviewer that have greatly improved presentation of the paper. This work was supported by the National Natural Science Foundation of China (Nos. 71501084, 71671078, 71301062, 71373103, 71471076, 71401082, 71471077, 71671088); Youth Backbone Teacher Training Project of Jiangsu University.
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