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In this paper, in relation to a two-level GSC consisting of manufacturers and suppliers, differential equations involving the greenness of intermediate and final products as state variables are constructed considering the effect of digital capability on green innovation. Subsequently, designs for three incentive mechanisms\u2014the greenness reward, the R&amp;D effort reward, and the digital construction reward\u2014are presented, and their long-term dynamic effects on the economic, environmental, and social benefits are compared and analyzed. Finally, the impacts of consumer green preference and the contribution of digital capability to the advancement of green innovation are explored. The findings show that all these incentives can boost economic, environmental, and social benefits while motivating the supplier. To achieve the best incentive effect, the reward coefficient should fall within a specific range. The digital construction reward mechanism is the most favourable in the initial stage, while the R&amp;D effort reward mechanism is the most appropriate in the long term. The promotion effects of digital capability on green innovation and consumer green preference have the potential to enhance economic, environmental, and social performance.<\/jats:p>","DOI":"10.3390\/jtaer19020065","type":"journal-article","created":{"date-parts":[[2024,6,3]],"date-time":"2024-06-03T12:29:47Z","timestamp":1717417787000},"page":"1267-1302","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Dynamic Incentive Mechanisms for Collaborative Innovation of Green Supply Chain Considering Digital Capability and Consumer Green Preference"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7594-1062","authenticated-orcid":false,"given":"Wen","family":"Cheng","sequence":"first","affiliation":[{"name":"School of Economics and Management, Chang\u2019an University, Xi\u2019an 710064, China"},{"name":"Transportation Management College, Zhejiang Institute of Communications, Hangzhou 311112, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7594-4263","authenticated-orcid":false,"given":"Qunqi","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Chang\u2019an University, Xi\u2019an 710064, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3164-2332","authenticated-orcid":false,"given":"Qian","family":"Li","sequence":"additional","affiliation":[{"name":"School of Economics and Management, Chang\u2019an University, Xi\u2019an 710064, China"}]},{"given":"Fei","family":"Ye","sequence":"additional","affiliation":[{"name":"Transportation Management College, Zhejiang Institute of Communications, Hangzhou 311112, China"}]},{"given":"Lingling","family":"Tan","sequence":"additional","affiliation":[{"name":"School of Modern Post, Xi\u2019an University of Posts and Telecommunications, Xi\u2019an 710061, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"8515","DOI":"10.1007\/s00500-021-05779-1","article-title":"Pricing Rules of Green Supply Chain Considering Big Data Information Inputs and Cost-Sharing Model","volume":"25","author":"Liu","year":"2021","journal-title":"Soft Comput."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"108073","DOI":"10.1016\/j.cie.2022.108073","article-title":"Optimal Production and Subsidy Rate Considering Dynamic Consumer Green Perception under Different Government Subsidy Orientations","volume":"168","author":"Chen","year":"2022","journal-title":"Comput. 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