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Appears in Collections:Management, Work and Organisation Journal Articles
Peer Review Status: Refereed
Title: Systems Evaluation of University-Industry Collaboration Efficiency in Iran: Current Situation and Proposed Policy Framework
Author(s): Edgar, Gerry
Kharazmi, Omid Ali
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Keywords: University
Systems thinking
Issue Date: 29-Jan-2022
Date Deposited: 9-Mar-2022
Citation: Edgar G & Kharazmi OA (2022) Systems Evaluation of University-Industry Collaboration Efficiency in Iran: Current Situation and Proposed Policy Framework. Journal of the Knowledge Economy.
Abstract: The research objective is to develop system models of the university-industry collaboration (UIC) element of a national innovation system and to evaluate its potential as a framework to inform economic policies. A UIC system model for Iran was developed and applied to explore key policy concerns, current performance, and barriers to development. A mixed-method approach was used. Firstly, a survey was used to scope system elements from the input of 94 expert stakeholders and to establish related issues. An insight of the difference between university and industry actors’ views regarding problems of UIC effectiveness was also formed. Secondly, 25 semi-structured interviews with stakeholders were used for building the conceptual model of the UIC system. Quantitative data were analyzed with Mann–Whitney U test, and for analyzing interviews, theme analysis was applied. Analysis of the causal relationships in the UIC model indicated there are a range of barriers that maintain a predominant negative behaviour pattern that limits UIC performance. This negative equilibrium is manifest as significant lack of trust at all interfaces in the system. The systems model is a complex interaction of reinforcing loops that emphasizes the scale of challenge policy-makers face in creating effective UIC outcomes. A set of policy choices informs an improvement agenda for UIC activities in Iran. This method is a framework to address the current lack of effective approaches to aid understanding of the complexity of behavioural forces that can help politicians to form coherent policies that address often hidden systematic biases.
DOI Link: 10.1007/s13132-021-00873-z
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Notes: Output Status: Forthcoming/Available Online
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