Application of adversarial risk analysis model in pricing strategies with remanufacturing

Abstract

Purpose: This paper mainly focuses on the application of adversarial risk analysis (ARA) in the pricing strategy with remanufacturing. We hope to obtain more realistic results than classical model. In fact, the classical Stackelberg model believes that since OEMs are the monopoly position, they know the pricing strategy of remanufacturers in the second period. However, the development of remanufacturing industry shakes OEMs’ monopoly position and makes remanufacturers become stronger and stronger, so, in fact, OEMs don’t know the pricing strategy of remanufacturers in the second period. Hence, the classical Stackelberg model isn’t suited for reality. In this paper, we suppose that the OEMs don’t know the pricing strategy of remanufacturers and recovery cost and only know their own information. Based on these assumptions, we predict the pricing strategy of remanufacturers from OEMs’ point. Furthermore, we build OEMs’ own pricing strategy based on the predicted the remanufacturers’ pricing strategy, which is called OEMs’ 1-order ARA model. Similarly, we look ourselves as remanufacturers and forecast OEMs’ pricing strategy. Based on the forecasted OEMs’ pricing strategy, we create the remanufacturers’ own pricing strategy. Simulated results make us find ARA model gets more profit than classical Stackelberg model. Design/methodology/approach: In order to gain more actual research, we apply adversarial risk analysis to the pricing strategy with remanufacturing. As OEMs, they don’t the recovery cost and the pricing strategy of remanufacturers, so they have to analyze and predict the pricing strategy of remanufacturers and based on this predicted the pricing strategy of remanufacturers build their own pricing strategy. The pricing strategy of OEMs is called 1-order ARA model of OEMs. To similar, remanufacturers build their own pricing strategy based on predicting the pricing strategy of OEMs. In the other words, remanufacturers build their own 1-order ARA model. Moreover, we use Monte Carlo simulation to numerically analyze and compare the 1- order ARA models with the classical Stackelberg models. Findings: We research the OEM’s 1-order ARA model with the uncertainty rate of recovery. That is, as OEMs, they don’t know the recovery cost of remanufacturers and only know their own unit product cost c. So, they suppose the recovery cost is τc(0 < τ < 1) and τ satisfied on an uniform distribution on [0, 1]. Based on this assumption, OEMs forecast the pricing strategy of remanufacturers. Furthermore，their own the pricing strategy which is called OEM’s 1- order ARA model. Similarly, as remanufacturers, they don’t know the unit cost c and only know the recover cost τc. Hence, they suppose C is random variable and satisfied on an uniform distribution on [0, 1]. With this assumption, remanufacturers forecast the pricing strategies of OEMs. Moreover, remanufacturers create their own the pricing strategies based on the forecasted OEMs’ pricing strategies. Besides, by Monte Carlo simulation, we can come to the conclusion that pricing strategies based on 1-order ARA model have advantage over than the classical model regardless of OEMs and remanufacturers. Research limitations/implications: We discuss OEMs and remanufacturers’ 1-order ARA models are more practical than classical Stackelberg pricing strategies. In particular, on the one hand, the rate of recovery changes because of development of remanufacturing industry, improvement of new machines, disassemble-ability or other un-predicted reasons. As for OEMs, it is impossible to accurately know the rate of recovery. So, OEMs don’t know the exactly pricing strategies of remanufacturers. Hence, the OEM’s 1-oreder ARA model is more practical than the classical Stackelberg model and has advantage over the classical pricing strategies in profit. On the other hand, the unit production cost is not fixed but rather changed. Production technology and process improvement causes this cost to change. Similar to OEM, as for remanufacturers, they have no way to know exactly the unit production cost. Consequently, remanufacturers have more disadvantages if they use the classical pricing strategy than they use remanufacturers’ 1-order ARA model. In our simulating analysis, we can come to the coincident conclusions. In general, the research on application of ARA implies that we can get more actual results with this kind of modern risk analysis method and ARA can be extensively in pricing strategies of supply chain. Moreover, the thought and method of building ARA model can be widely applied to other strategies in all kinds of economic field, such as investing strategy, the problems about auction, bidding strategies, and so on. Originality/value: Our research makes the pricing strategies of OEMs and remanufacturers be more actual than classical Stackelberg model and help OEMs and remanufacturers to get more profit. Furthermore, we improve the application of ARA in remanufacturing industry. Meanwhile, inspired by this analysis, we can also create different ARA models for different parameters. Furthermore, some results and analysis methods can be applied to other pricing strategies of supply chain and other economic field.