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Systems 2019, 7(1), 15;

Developing a Systematic Diagnostic Model for Integrated Agricultural Supply and Processing Systems

Department of Bioresources Engineering, University of KwaZulu-Natal, Private Bag X01 Scottsville, Pietermaritzburg 3209, South Africa
Graduate School of Business and Leadership, University of KwaZulu-Natal, Private Bag X54001, Durban 3600, South Africa
Department of Consumer and Food Science, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa
Author to whom correspondence should be addressed.
Received: 31 December 2018 / Revised: 25 February 2019 / Accepted: 7 March 2019 / Published: 12 March 2019
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Despite all the innovative research in agriculture, technology adoption in integrated agricultural supply and processing systems (IASPS) remains a challenge. This is attributed to the complex nature of IASPS and the continued lack of a holistic view towards most of the interventions into the systems. To make sense of issues that affect IASPS, it is important to recognise that most issues within these systems do not exist in isolation, but are imbedded within complex interrelationships. This research developed and demonstrated a systematic diagnostic model that could be used to locate high leverage intervention points within IASPS and to make predictions about the systems behaviour. A meta-analysis was conducted to test the evidence of the interlinkages between IASPS domains and to compare the strength of these relationships. The model revealed that the collaboration, structure and information sharing domains had a higher direct leverage over the other IASPS domains as these were associated with a larger number of interlinkages. Additionally, collaboration and structure provided dynamic leverage as these domains were part of feedback loops. In terms of the potency, collaboration was highly correlated to culture compared to the other domains, viz., information sharing, coercive power and transaction costs. View Full-Text
Keywords: adoption; interlinkages; meta-analysis; supply systems; systems thinking adoption; interlinkages; meta-analysis; supply systems; systems thinking

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Shongwe, M.I.; Bezuidenhout, C.N.; Sibomana, M.S.; Workneh, T.S.; Bodhanya, S.; Dlamini, V.V. Developing a Systematic Diagnostic Model for Integrated Agricultural Supply and Processing Systems. Systems 2019, 7, 15.

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