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Article

Application of Systems-Approach in Modelling Complex City-Scale Transdisciplinary Knowledge Co-Production Process and Learning Patterns for Climate Resilience

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Faculty of Engineering, The Polytechnic Campus, University of Malawi, Blantyre 312225, Malawi
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Faculty of Applied Sciences, The Polytechnic Campus, University of Malawi, Blantyre 312225, Malawi
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Faculty of Built Environment, The Polytechnic Campus, University of Malawi, Blantyre 312225, Malawi
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Climate System Analysis Group, Environmental and Geographical Science Department, University of Cape Town, Cape Town 7701, South Africa
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ICLEI-Local Governments for Sustainability, Africa Secretariat, Cape Town 7741, South Africa
*
Author to whom correspondence should be addressed.
Received: 22 October 2020 / Revised: 2 January 2021 / Accepted: 8 January 2021 / Published: 22 January 2021
(This article belongs to the Special Issue Systems Science)
Literature shows that much research has been conducted on the co-production of climate knowledge, but it has neither established a standardized and replicable model for the co-production process nor the emergent learning patterns as collaborators transition from the disciplinary comfort-zone (disciplinary and practice biases) to the transdisciplinary third-space. This study combines algorithmic simulation modelling and case study lessons from Learning Labs under a 4-year (2016–2019) climate change management project called Future Resilience of African CiTies and Lands in the City of Blantyre in Malawi. The study fills the research gap outlined above by applying a systems-approach to replicate the research process, and a Markov process to simulate the learning patterns. Results of the study make a number of contributions to knowledge. First, there are four distinct evolutionally stages when transitioning from the disciplinary comfort-zone to the transdisciplinary third-space, namely: Shock and resistance to change; experimenting and exploring; acceptance; and integration into the third-space. These stages are marked by state probabilities of the subsequent stages relative to the initial (disciplinary comfort-zone) state. A complete transition to the third-space is marked by probabilities greater than one, which is a system amplification, and it signifies that there has been a significant increase in learning among collaborating partners during the learning process. Second, a four-step decision support tool has been developed to rank the plausibility of decisions, which is very hard to achieve in practice. The tool characterizes decision determinants (policy actors, evidence and knowledge, and context), expands the determinants, checks what supports the decision, and then rates decisions on an ordinal scale of ten in terms of how knowledge producers and users support them. Third, for a successful transdisciplinary knowledge co-production, researchers should elucidate three system-archetypes (leverage points), namely: Salient features for successful co-production, determinant of support from collaborators, and knowledge co-production challenges. It is envisioned that academics, researchers, and policy makers will find the results useful in modelling and replicating the co-production process in a methodical and systemic way while solving complex climate resilience development problems in dynamic, socio-technical systems, as well as in sustainably mainstreaming the knowledge co-produced in policies and plans. View Full-Text
Keywords: climate change; complex social-technical systems; decision-support; systems-theory; third-space-transition modelling climate change; complex social-technical systems; decision-support; systems-theory; third-space-transition modelling
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MDPI and ACS Style

Mkandawire, B.; Thole, B.; Mamiwa, D.; Mlowa, T.; McClure, A.; Kavonic, J.; Jack, C. Application of Systems-Approach in Modelling Complex City-Scale Transdisciplinary Knowledge Co-Production Process and Learning Patterns for Climate Resilience. Systems 2021, 9, 7. https://0-doi-org.brum.beds.ac.uk/10.3390/systems9010007

AMA Style

Mkandawire B, Thole B, Mamiwa D, Mlowa T, McClure A, Kavonic J, Jack C. Application of Systems-Approach in Modelling Complex City-Scale Transdisciplinary Knowledge Co-Production Process and Learning Patterns for Climate Resilience. Systems. 2021; 9(1):7. https://0-doi-org.brum.beds.ac.uk/10.3390/systems9010007

Chicago/Turabian Style

Mkandawire, Burnet, Bernard Thole, Dereck Mamiwa, Tawina Mlowa, Alice McClure, Jessica Kavonic, and Christopher Jack. 2021. "Application of Systems-Approach in Modelling Complex City-Scale Transdisciplinary Knowledge Co-Production Process and Learning Patterns for Climate Resilience" Systems 9, no. 1: 7. https://0-doi-org.brum.beds.ac.uk/10.3390/systems9010007

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