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Finding Traceability Granularity Influencing Factors Using Rough Set Method: An Empirical Analysis of Vegetable Companies in Tianjin City, China

Authors :
Jianping Qian
Jiali Li
Bojian Geng
Cunkun Chen
Jianjin Wu
Haiyan Li
Source :
Foods, Vol 12, Iss 11, p 2124 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

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.

Details

Language :
English
ISSN :
23048158
Volume :
12
Issue :
11
Database :
Directory of Open Access Journals
Journal :
Foods
Publication Type :
Academic Journal
Accession number :
edsdoj.4ccabe812fdb45f5b5cca60a9581fe7b
Document Type :
article
Full Text :
https://doi.org/10.3390/foods12112124