Towards sustainable collaborative networks for smart cities co-governance |
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| Institution: | 1. RIADI Laboratory, National School of Computer Sciences, University of Manouba, Manouba, Tunisia;2. Østfold University College, Faculty of Computer Sciences, Norway;1. University of Nevada, Las Vegas, Las Vegas, NV, 89154, United States;2. Towson University, Towson, MD, 21252, United States;3. Western Carolina University, Cullowhee, NC, 28723, United States;4. University of Virginia, Charlottesville, VA, 22903, United States;1. Management Information Systems Group, Indian Institute of Management Calcutta, Kolkata, India;2. Research School of Management, Australian National University, Canberra, Australia;3. Marketing Group, Indian Institute of Management Calcutta, Kolkata, India;1. Indian Institute of Technology, Kanpur, India;2. University of Wisconsin, Milwaukee, Wisconsin, USA;3. University of South Florida, Tampa, Florida, USA;1. Department of Systems and Technology, Harbert College of Business, Auburn University, Auburn, AL, 36849, USA;2. School of Accountancy & MIS, DePaul University, Chicago, IL, 60604, USA;3. Department of Marketing, Eli Broad College of Business, Michigan State University, East Lansing, MI, 48824, USA;1. University of North Carolina at Greensboro, Information Systems & Supply Chain Management Dept. 516 Stirling St., Greensboro, NC, 27412, USA;2. University of New South Wales, School of Information Systems Technology and Management, Sydney, Australia;1. College of Business Administration, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates;2. Faculty of Commerce, Helwan University, Cairo, Egypt;3. College of Computing and Informatics, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates |
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| Abstract: | This paper addresses the concept of collaborative governance in the context of smart cities, with a focus on supporting and recommending performing organizational structures for sustainable collaborative networks (SCN). It highlights that governing a smart city is about promoting an effective environment of collaboration in the government and implying adaptive policy-making to construct new, internal and external human collaborations. Considering the smart governance as a collaborative network of government agencies and external stakeholders including citizens and a socio-technical system, we conduct in this paper an ethnographic mixed method by combining a qualitative method that studies actors’ collaboration and engagement in co-governance with a quantitative method that is based on graph theory to provide numerical analyses of organizational structures. While the qualitative method aims to discover organizational “smart factors” that affect the performance of SCN structures or configurations, the quantitative method aims to find “smart indicators” and metrics to evaluate these organizational factors. The result of this mixed method is an analytical recommender framework of the relevant SCN organizational structures in terms of robustness, flexibility and efficiency. |
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| Keywords: | Sustainable collaborative network Organizational structures Collaborative governance Smart City Recommendation |
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