EconPapers    
Economics at your fingertips  
 

Green Technology Investment with Data-Driven Marketing and Government Subsidy in a Platform Supply Chain

Ke Li, Gengxin Dai, Yanfei Xia, Zongyu Mu, Guitao Zhang and Yangyan Shi
Additional contact information
Ke Li: Department of Management Science and Engineering, School of Business, Qingdao University, Qingdao 266071, China
Gengxin Dai: Department of Management Science and Engineering, School of Business, Qingdao University, Qingdao 266071, China
Yanfei Xia: Department of Management Science and Engineering, School of Business, Qingdao University, Qingdao 266071, China
Zongyu Mu: Department of Management Science and Engineering, School of Business, Qingdao University, Qingdao 266071, China
Guitao Zhang: Department of Management Science and Engineering, School of Business, Qingdao University, Qingdao 266071, China
Yangyan Shi: Macquarie Business School, Macquarie University, Sydney 2109, Australia

Sustainability, 2022, vol. 14, issue 7, 1-22

Abstract: Expanding green consumption market and precise data promotion advantages make the platform economy have a significant effect on influencing manufacturers to carry out green R&D and production activities, and government subsidies have a positive incentive effect. In this context, for the studies about platform supply chain management with manufacturer’s green production and the platform’s marketing activities simultaneously are rare, we consider that a manufacturer invests in green technologies to produce products and sell them through a smart platform supply chain by an agency selling or reselling strategy, in which the platform provides data-driven marketing technology to promote green products. Four game models are constructed to study the operational efficiency of the platform supply chain considering selling strategy difference and government subsidy. The results show that: (1) The manufacturer’s green technology and the platform’s data-driven marketing levels, as well as all member’s profits are all influenced by the potential market demand of green products, the sensitivities of consumers to green product attributes, and data analysis technology. (2) The service commission rate charged by the platform plays a main role on the manufacturer’s selling strategy choice, when the service commission rate is low, the manufacturer chooses an agency selling strategy and can obtain more profit, but now the green technology level is not necessarily better than that in the reselling system. With the service commission rate increases, a manufacturer that chooses the reselling strategy can obtain more profit, and the green technology level is better than in the agency selling system. (3) Government subsidy can effectively encourage the manufacturer to improve the green technology level, and now the platform will improve the data-driven marketing level. There is a threshold range of the service commission rate charged by the platform in which the government can guide the manufacturer and the platform to reach an equilibrium selling strategy by regulating the subsidy level.

Keywords: supply chain management; online platform; green technology; data-driven marketing; government subsidy (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/7/3992/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/7/3992/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:7:p:3992-:d:781533

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jsusta:v:14:y:2022:i:7:p:3992-:d:781533