The rapid development of information technology has promoted the digital transformation of the service supply chain. Members can collect, store, and transform the value of data to gain profits. Due to the different roles during the service delivery, service integrators (SIs) and service providers (SPs) transform the data value from different sources, which leads to the demand and supply-driven data, respectively. As the leader of service supply chain, the SI may show altruistic behavior and share the data value with SPs. This study constructs a service supply chain consisting of two SPs and one SI and establishes five analytical models. Several important conclusions are obtained. First, the demand-driven data value leads to a decrease in the SI's optimal pricing and the SP's optimal value-added service level, leading to the “paradox of demand-driven data value”. Second, supply-driven data value leads to the increase in SI and SPs’ optimal decisions, and SI can get higher expected utility at no cost, achieving the "free-riding effect". Finally, there is a "transmission effect" among the altruistic behavior, demand-driven and supply-driven data value. When the parameters meet certain condition, customers can obtain an "optimal purchasing area" and obtain higher-level value-added service at a lower price.

信息技术的飞速发展促进了服务供应链的数字化转型。成员可以收集，存储和转换数据的价值以获取利润。由于服务交付过程中角色的不同，服务集成商（SI）和服务提供商（SP）会从不同来源转换数据值，从而分别导致需求和供应驱动的数据。作为服务供应链的领导者，SI可能表现出利他行为并与SP共享数据值。这项研究构建了一个由两个SP和一个SI组成的服务供应链，并建立了五个分析模型。得到了几个重要的结论。首先，需求驱动的数据价值导致SI的最佳定价和SP的最佳增值服务水平下降，导致“需求驱动的数据价值悖论”。其次，供应驱动的数据价值导致SI和SP的最佳决策增加，并且SI可以免费获得更高的预期效用，从而实现“搭便车效应”。最后，在利他行为，需求驱动和供应驱动的数据值之间存在“传递效应”。当参数满足特定条件时，客户可以获得“最佳购买区域”，并以较低的价格获得更高级别的增值服务。需求驱动和供应驱动的数据价值。当参数满足特定条件时，客户可以获得“最佳购买区域”，并以较低的价格获得更高级别的增值服务。需求驱动和供应驱动的数据价值。当参数满足特定条件时，客户可以获得“最佳购买区域”，并以较低的价格获得更高级别的增值服务。