本项目从供应链的全局和运营视角出发，以改善食品安全和降低掺假风险为目的，研究开发了相应的数据分析技术并提出了基于风险的监管资源配置策略。本项目以水产品为研究对象，在国家食品药品监督管理总局（现并入国家市场监督管理总局）公布的260万批次食品安全检测数据集中提取了89970批次水产品检测数据，构建了全国范围的结构化水产品检测面板数据集；结合水产品供应链结构开发创新的数据分析技术，识别中国水产品的掺假风险来源。基于开发的创新分析技术和独有的数据集，项目的研究获得了多种管理洞察。特别地，研究显示现有监管资源在水产品供应链中的分配与其中的风险分布存在不匹配的现象。研究发现水产品供应链的高风险环节(批发和农贸市场)的监管资源地投入相对不足，而相对安全的零售和超市却获得了较多的监管投入。本项目研究开发的供应链分析技术对有效开展食品安全监管有重要意义。

This paper illustrates how supply chain (SC) analytics could provide strategic and operational insights to evaluate the risk-based allocation of regulatory resources in food SCs, for management of food safety and adulteration risks. This paper leverages data on 89,970 tests of aquatic products extracted from a self-constructed data set of 2.6 million food safety tests conducted by the China Food and Drug Administration (CFDA) orga[1]nizations. The integrated and structured data set is used to conduct innovative analysis that identifies the sources of adulteration risks in China’s food SCs and contrasts them with the current test resource allocations of the CFDA. The analysis highlights multiple strategic insights. Particularly, it suggests potential gaps in the current CFDA testing allocation by SC location, which is heavily focused on retail and supermarkets. Instead, the analysis indicates that high-risk parts of the SC, such as wholesale and wet markets, are under[1]sampled. Additionally, the paper highlights the impact that SC analytics could have on policy-level operational decision making to regulate food SCs and manage food safety. The hope is that the paper will stimulate the interest of academics with expertise in these areas to conduct more work in this important application domain.

团队照片

团队成员实地调研