Collaborative Innovation with Dynamic Incentive Contracts in a Supply Chain

Abstract

The collection and sharing of consumers’ knowledge by retailers can help manufacturers improve the innovation level of products, thereby improving the performance of supply chain. However, due to the cost of collecting consumers’ knowledge, the wholesale price contract can no longer coordinate supply chain members effectively. It is necessary to study the problem how the retailers are encouraged to make more efforts for the cooperative innovation with manufacturers. This paper introduces two dynamic incentive contracts for improving collaborative innovation level in a two-player supply chain, and the impacts of these contracts on supply chain’s performance are investigated, by using a Stackelberg differential game model. The manufacturer, as a Stackelberg leader, determines the R&D investment while the retailer is responsible for the retail price and the efforts in collection of the consumer’s information (or preference) to the products. The model incorporates a wholesale price contract and two incentive contracts to better understand how the manufacturer can facilitate the retailer’s efforts in the collection of consumer’s information and increase the profits of the members of supply chain. Our results suggest that the optimal profit of the supply chain, the retailer’s efforts in the collection of consumer’s knowledge, the retail price, and the innovation level under the reward incentive contract are higher than their counterparts in other contracts. In particular, the retailer’s optimal effort under the reward incentive contract is even higher than the one in the centralized decision scenario. However, if the manufacturer commits an effort target to the retailer, it shows that the retailer’s optimal effort is independent of the target. The manufacturer’s optimal R&D investments are constants in the three contracts under the dynamic setting. Furthermore, numerical simulations show that the effort target has little impact on profits of the supply chain although it affects the decision making of supply chain members to some extent, whereas the retailer’s marginal reward offered by the manufacturer influences the innovation level of product and the supply chain’s profit significantly.

Dynamic Incentive Mechanisms for Collaborative Innovation of Green Supply Chain Considering Digital Capability and Consumer Green Preference

“…For businesses to implement digital construction, investments are required. Assuming that the digital capability levels of the manufacturer and supplier are 𝑑 and 𝑑 , respectively, referring to the research of Hao et al [27] and Kumar Jena and Singhal [13], the cost to the manufacturer and supplier to carry out digital construction is set as a quadratic function of the digital capability level, i.e., 𝐶 𝐼 𝑑 and 𝐶 𝐼 𝑑 , where 𝐼 and 𝐼 are the cost coefficients of digital construction for the manufacturer and supplier, respectively. Similarly, with reference to the studies by Zhou et al [53] and Meng et al [6], the manufacturer and supplier adopt a classical quadratic convex form for green innovation…”

“…For businesses to implement digital construction, investments are required. Assuming that the digital capability levels of the manufacturer and supplier are d m and d s , respectively, referring to the research of Hao et al [27] and Kumar Jena and Singhal [13] , where E m and E s are the green innovation R&D effort levels of the manufacturer and supplier, and I g and I s are the cost coefficients of green innovation R&D of the manufacturer and supplier, respectively.…”

“…The equipment and facilities employed in green production will keep wearing out and green technologies will eventually become outdated over time. Therefore, there is a natural attenuation impact on product greenness [5], which is commonly cited in the literature on green innovation and environmental decision making (such as Zhu et al [5], Chang et al [55], and Hao et al [27]).…”

“…The optimal decision making and incentive contracts of the GSC are analyzed dynamically rather than statically. Green innovation, pollutant emissions, and energy efficiency are all dynamic phenomena [5,26,27]. The product's greenness and the pertinent decisions made in the subsequent stage will be influenced by the innovation efforts within GSC participators in the preceding stage.…”