Decision optimization in service supply chain: the impact of demand and supply-driven data value and altruistic behavior

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.