Decision-making of the Multi-channel Low-carbon Tourism Supply Chain under a Competitive Environment with Fairness Concern

In the context of the Internet-driven low-carbon economy, it is crucial to investigate the effects of multi-channel competition and fairness-concerned behaviors among supply chain participants on the decision-making dynamics within low-carbon tourism supply chains. This paper constructs a multi-channel low-carbon tourism supply chain model, which includes a tourist spot (TS) offering low-carbon services and two online travel agencies (OTAs) providing big data low-carbon marketing. Subsequently, differential game theory is utilized to explore the optimal strategy of primarily supply chain participants across three different models (centralized, decentralized, and fairness-concerned). The analysis further examines how the intensity of competition in big data low-carbon marketing, tourists’ preference for online channels, and the fairness-focused behaviors of supply chain participants affect their decision-making and profits. The findings indicate that: 1) In the decentralized and fairness-concerned models, an increase in the degree of competition in big data low-carbon marketing encourages OTAs to intensify their big data low-carbon marketing efforts. Conversely, in the centralized model, increased competition will prompt OTAs to enhance their efforts only if their marginal profit exceeds that of their competitors. 2) Across the three distinct decision-making models, an increase in tourists’ preference for online channels leads to a rise in low-carbon service inputs, low-carbon service levels, big data low-carbon marketing efforts, low-carbon goodwill, profits for the TS, profits for the OTAs, and overall system profits. 3) Fairness-concerned behavior will lower the decision-making level of the supply chain and exert a detrimental influence on the supply chain system.