Information‐sharing strategies for geographical indication agricultural products governance in the context of digital technology
Yajun Liu & Guangyuan He
What the paper says
The development of Geographical Indication Agricultural Products (GIAP) plays a critical role in promoting rural revitalization. However, due to information asymmetry among stakeholders, producers often tend to pursue opportunistic gains by “free‐riding,” such as producing low‐quality agricultural products, which severely damages the reputation of GIAP. By improving information provision, digital technologies offer a means to eliminate this information asymmetry, facilitate stakeholders' sharing of GIAP production and quality information, and ultimately make GIAP governance possible. Based on this, the paper first discusses the digital information sharing mechanisms of GIAP under different collaboration models. Next, we develop a differential game model based on information sharing. Finally, we compare the differences in information sharing efforts and benefits among various stakeholders. Results show that (i) under the context of digital technology, GIAP's information‐sharing behaviors can be categorized into three modes: decentralized, subsidy, and centralized; (ii) as the cooperation model progresses, the information‐sharing efforts of the government, industry associations, and enterprises increase to varying degrees within a specific range of coefficients; (iii) in the enhancement pathways for information sharing among the three parties, there exists a Pareto improvement path that yields benefits; and (iv) the “consortium” model under centralized decision‐making can achieve dual maximization of information sharing efforts and benefits for all parties involved through the Pareto improvement path.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.