Qian Jianping, Li Jiali, Geng Bojian, Chen Cunkun, Wu Jianjin, Li Haiyan
Key Laboratory of Agricultural Remote Sensing (AGRIRS), Ministry of Agriculture and Rural Affairs/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China.
Yangtze River Delta Intelligent Agriculture Research Institute of Chinese Academy of Agricultural Sciences, Suzhou 215331, China.
Foods. 2023 May 24;12(11):2124. doi: 10.3390/foods12112124.
The effectiveness evaluation of the traceability system (TS) is a tool for enterprises to achieve the required traceability level. It plays an important role not only for planning system implementation before development but also for analyzing system performance once the system is in use. In the present work, we evaluate traceability granularity using a comprehensive and quantifiable model and try to find its influencing factors via an empirical analysis with 80 vegetable companies in Tianjin, China. We collect granularity indicators mostly through the TS platform to ensure the objectivity of the data and use the TS granularity model to evaluate the granularity score. The results show that there is an obvious imbalance in the distribution of companies as a function of score. The number of companies (21) scoring in the range (50,60) exceeded the number in the other score ranges. Furthermore, the influencing factors on traceability granularity were analyzed using a rough set method based on nine factors pre-selected using a published method. The results show that the factor "number of TS operation staff" is deleted because it is unimportant. The remaining factors rank according to importance as follows: Expected revenue > Supply chain (SC) integration degree > Cognition of TS > Certification system > Company sales > Informationization management level > System maintenance investment > Manager education level. Based on these results, the corresponding implications are given with the goal of (i) establishing the market mechanism of high price with high quality, (ii) increasing government investment for constructing the TS, and (iii) enhancing the organization of SC companies.
可追溯系统(TS)的有效性评估是企业实现所需可追溯水平的一种工具。它不仅在系统开发前的规划实施中起着重要作用,而且在系统投入使用后分析系统性能方面也发挥着重要作用。在本研究中,我们使用一个全面且可量化的模型来评估可追溯粒度,并通过对中国天津80家蔬菜公司的实证分析来试图找出其影响因素。我们主要通过TS平台收集粒度指标以确保数据的客观性,并使用TS粒度模型来评估粒度得分。结果表明,公司分布随得分呈现明显的不均衡。得分在(50,60)区间的公司数量(21家)超过了其他得分区间的公司数量。此外,基于一种已发表方法预先选定的九个因素,我们使用粗糙集方法分析了可追溯粒度的影响因素。结果表明,因素“TS操作人员数量”因不重要而被剔除。其余因素按重要性排序如下:预期收益>供应链(SC)整合程度>对TS的认知>认证体系>公司销售额>信息化管理水平>系统维护投入>经理教育水平。基于这些结果,给出了相应的启示,目标是:(i)建立优质高价的市场机制;(ii)增加政府对TS建设的投入;(iii)加强SC公司的组织建设。