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A decision support system for evaluation of the knowledge sharing crossing boundaries in agri-food value chains

Biljana Mileva Boshkoska, Shaofeng Liu, Guoqing Zhao, Alejandro Fernandez, Susana Gamboa, Mariana del Pino, Pascale Zarate, Jorge Hernandez, Huilan Chen

Computers in Industry, Volume: 110, Pages: 64 - 80

Swansea University Author: Guoqing Zhao

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DOI (Published version): 10.1016/j.compind.2019.04.012

Abstract

An agri-food value chain (VC) represents a set of activities aimed at delivering highly valuable products to the market. Due to the diversity of actors in the agri-food VCs´ accumulated knowledge is typically situated within the boundaries of each entity of the VC. Hence, the question is how to impr...

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Published in: Computers in Industry
ISSN: 0166-3615
Published: Elsevier BV 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa62350
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first_indexed 2023-01-17T12:53:38Z
last_indexed 2023-02-18T04:13:56Z
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spelling 2023-02-17T13:37:47.3705852 v2 62350 2023-01-17 A decision support system for evaluation of the knowledge sharing crossing boundaries in agri-food value chains 2ff29aa347835abe2af6d98fa89064b4 Guoqing Zhao Guoqing Zhao true false 2023-01-17 BBU An agri-food value chain (VC) represents a set of activities aimed at delivering highly valuable products to the market. Due to the diversity of actors in the agri-food VCs´ accumulated knowledge is typically situated within the boundaries of each entity of the VC. Hence, the question is how to improve knowledge sharing in agri-food VC, or more specifically how can knowledge flow and mobilize among different actors in the VC. To answer this question, we present a decision support system (DSS) for evaluation of knowledge sharing crossing boundaries in agri-food VC. The proposed DSS is developed through two phases: (i) identification of the most common knowledge boundaries by using machine learning and ontology technologies; (ii) transformation of the obtained ontology into a DSS for the evaluation of existing knowledge boundaries. In particular, the developed DSS helps in identifying, evaluating and providing directions for improvement of the knowledge sharing crossing boundaries in agri-food VC. We apply the DSS to evaluate three real VCs: a tomato VC in Argentina, a Chinese leaf VC in China and a brassica VC in the UK. The comparative analysis across the three varied case studies and their evaluation with the proposed DSS lead to more insights into knowledge-based decisions that a particular VC needs to address to improve its knowledge flow, in particular, to obtain insights in the transparency and interoperability of data and knowledge crossing boundaries in agri-food VCs. Journal Article Computers in Industry 110 64 80 Elsevier BV 0166-3615 1 9 2019 2019-09-01 10.1016/j.compind.2019.04.012 COLLEGE NANME Business COLLEGE CODE BBU Swansea University 2023-02-17T13:37:47.3705852 2023-01-17T12:50:44.4628069 Faculty of Humanities and Social Sciences School of Management - Business Management Biljana Mileva Boshkoska 1 Shaofeng Liu 2 Guoqing Zhao 3 Alejandro Fernandez 4 Susana Gamboa 5 Mariana del Pino 6 Pascale Zarate 7 Jorge Hernandez 8 Huilan Chen 9
title A decision support system for evaluation of the knowledge sharing crossing boundaries in agri-food value chains
spellingShingle A decision support system for evaluation of the knowledge sharing crossing boundaries in agri-food value chains
Guoqing Zhao
title_short A decision support system for evaluation of the knowledge sharing crossing boundaries in agri-food value chains
title_full A decision support system for evaluation of the knowledge sharing crossing boundaries in agri-food value chains
title_fullStr A decision support system for evaluation of the knowledge sharing crossing boundaries in agri-food value chains
title_full_unstemmed A decision support system for evaluation of the knowledge sharing crossing boundaries in agri-food value chains
title_sort A decision support system for evaluation of the knowledge sharing crossing boundaries in agri-food value chains
author_id_str_mv 2ff29aa347835abe2af6d98fa89064b4
author_id_fullname_str_mv 2ff29aa347835abe2af6d98fa89064b4_***_Guoqing Zhao
author Guoqing Zhao
author2 Biljana Mileva Boshkoska
Shaofeng Liu
Guoqing Zhao
Alejandro Fernandez
Susana Gamboa
Mariana del Pino
Pascale Zarate
Jorge Hernandez
Huilan Chen
format Journal article
container_title Computers in Industry
container_volume 110
container_start_page 64
publishDate 2019
institution Swansea University
issn 0166-3615
doi_str_mv 10.1016/j.compind.2019.04.012
publisher Elsevier BV
college_str Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Business Management{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Business Management
document_store_str 0
active_str 0
description An agri-food value chain (VC) represents a set of activities aimed at delivering highly valuable products to the market. Due to the diversity of actors in the agri-food VCs´ accumulated knowledge is typically situated within the boundaries of each entity of the VC. Hence, the question is how to improve knowledge sharing in agri-food VC, or more specifically how can knowledge flow and mobilize among different actors in the VC. To answer this question, we present a decision support system (DSS) for evaluation of knowledge sharing crossing boundaries in agri-food VC. The proposed DSS is developed through two phases: (i) identification of the most common knowledge boundaries by using machine learning and ontology technologies; (ii) transformation of the obtained ontology into a DSS for the evaluation of existing knowledge boundaries. In particular, the developed DSS helps in identifying, evaluating and providing directions for improvement of the knowledge sharing crossing boundaries in agri-food VC. We apply the DSS to evaluate three real VCs: a tomato VC in Argentina, a Chinese leaf VC in China and a brassica VC in the UK. The comparative analysis across the three varied case studies and their evaluation with the proposed DSS lead to more insights into knowledge-based decisions that a particular VC needs to address to improve its knowledge flow, in particular, to obtain insights in the transparency and interoperability of data and knowledge crossing boundaries in agri-food VCs.
published_date 2019-09-01T04:21:54Z
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score 11.013148

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