Big data empowering low-carbon smart tourism study on low-carbon tourism O2O supply chain considering consumer behaviors and corporate altruistic preferences. (March 2021)

• Record Type: Journal Article
• Authors: Ma, Deqing; Hu, Jinsong; Yao, Fanjun
• Is Part Of: Computers & industrial engineering. Volume 153(2021)
• Publication Date: 2021-03
• Subjects: Big-data marketing -- Differential game -- Reference effect -- Low-carbon -- Tourism supply chain; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2020.107061
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A low-carbon tourism online-to-offline supply chain empowered by big data is investigated. The impacts of big-data empowerment and enterprise altruistic behavior are discussed. The ideal operating status of the low-carbon smart O2O tourism supply chain empowered by big data are given. Abstract: This paper investigates a low-carbon tourism online-to-offline(O2O) supply chain consisting of a tourist spot(TS) that is responsible for providing low-carbon service and an online tourism agency(OTA) that is in charge of providing big-data marketing effort. Under the context of low-carbon smart tourism empowered by big data, the impacts of big-data empowerment, consumer reference effect, channel preference, and enterprise altruistic behavior on the optimal decision making and performance of enterprises are discussed. Then, the optimal decision and performance of the firms in three decision modes (centralized, decentralized, and altruistic) are obtained with the help of differential game theory and Bellman's continuous dynamic planning theory. Our findings as follows are acquired through comparative analysis and sensitivity analysis of essential parameters. First, big-data marketing technology can personalize more low-carbon travel plans for tourists and enhance tourists' awareness of environmental protection. Besides, the low-carbon smart tourism supply chain empowered by big data could also have greater market potential. Thus, this marketing technology can subvert the traditional tourism business model and provide a more low-carbon, sustainable, and smart development path for the future of the tourism supply chain. Moreover, TS can continuously improve the level of low-carbon service because of the inspiration of consumers' reference low-carbon service effect, contributing to forming a virtuous cycle and stimulating the low-carbon, efficient, and sustainable development of the tourism supply chain. Furthermore, the cooperation among tourism supply chain members can be deepened by the altruistic preference between TS and OTA, resulting in not only enhancing the low-carbon goodwill and environmental benefits but also bringing a better experience for tourists. The findings indicate that the altruistic preference can simultaneously promote the sustainable development of low-carbon tourism supply chain and achieve supply chain coordination. At the end of the article, we also give the ideal operating status of the low-carbon smart O2O tourism supply chain empowered by big data.