竞争环境下考虑供应链透明度的大数据投资决策

针对供应链中的大数据投资决策与激励问题,考虑两个制造商通过大数据投资预测需求,并通过集团采购获取产品部件,进而展开产品数量竞争.从纵向与横向刻画供应链透明度,构建分散决策下的大数据投资决策模型,分析供应链透明度、竞争强度和大数据技术水平等因素对均衡结果的影响,并与集中决策进行绩效对比.研究发现:纵向与横向透明对大数据投资均有负效应,因而'会降低其可行性和投资水平;当竞争足够激烈时,纵向透明的负效应小于横向透明,且能抑制横向透明的负效应,从而产生正的溢出效应;竞争导致大数据投资过度,横向透明导致大数据投资不足,而纵向透明却可能在竞争强度与大数据技术水平均较低或较高时实现大数据投资最优.

Big data investment decisions in a supply chain under the impact of transparency and competition

To investigate the decision and incentive issues arising from big data investment in supply chains, this paper studies a supply chain where two manufacturers source components through a group purchasing organization (GPO). The manufacturers compete in quantity and can invest in big data to achieve accurate demand forecasts, which can be shared horizontally with their competitors or vertically with the GPO. By presenting a measurement of supply chain transparency in vertical and horizontal dimensions, a game model is established to address the decision problems of big data investment. Then, impacts of supply chain transparency, competition intensity, and technological level of big data on the equilibrium results are analyzed, and the investment performance is compared with the centralized decision scenario. The results indicate that both vertical and horizontal transparency has a negative effect on big data investment, such that the feasibility and the level of the investment will be reduced by supply chain transparency. When the competition intensity is sufficiently high (low), the negative effect of vertical transparency can not only be smaller (greater) than that of horizontal transparency but also reduce (enlarge) the negative effect of horizontal transparency, thus spillover effects exist between the two dimensions of transparency. Moreover, competition induces overinvestment in big data, while horizontal transparency induces underinvestment. Vertical transparency can induce either overinvestment or underinvestment in big data, but it can also realize the optimal investment when both the competition intensity and big-data technological level are sufficiently high or low. Finally, numerical examples show that the manufacturers may sink into prisoner's dilemma in big-data investment when only vertical transparency exists.