Evidence map›Paper›PMID 37297367›Full record

ArticleFoods (Basel, Switzerland)2023

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

Jianping Qian, Jiali Li, Bojian Geng, Cunkun Chen, Jianjin Wu, Haiyan Li

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Jianping QianKey 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.ORCID 0000-0002-2134-6903
Jiali LiKey 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.
Bojian GengYangtze River Delta Intelligent Agriculture Research Institute of Chinese Academy of Agricultural Sciences, Suzhou 215331, China.
Cunkun ChenInstitute of Agricultural Products Preservation and Processing Technology (National Engineering Technology Research Center for Preservation of Agriculture Product), Tianjin Academy of Agricultural Sciences/Key Laboratory of Postharvest Physiology and Storage of Agricultural Products, Ministry of Agriculture and Rural Affairs, Tianjin 300384, China.
Jianjin WuTianjin Agricultural Development Service Center, Tianjin 300061, China.
Haiyan LiTianjin Agricultural Development Service Center, Tianjin 300061, China.

Funding

Central Public-interest Scientific Institution Basal Research Fund CAAS-ZDRW202107The National Natural Science Foundation of China 31971808
6 · The paper itself

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.

Indexed as

empirical analysisinfluence factorsrough settraceability granularityvegetable companies

Identifiers

PMID37297367
PMCPMC10252484

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.