A Pattern of Collaborative Networking for Enhancing Sustainability of Smart Cities

Abstract

This paper represents a research response to the current vision on transformations regarding the capacity building of smart cities focused towards sustainability, by addressing the knowledge based urban development and collaborative tools that support the development, dissemination, and use of knowledge. The purpose of this paper is to develop a collaborative pattern of knowledge networking, focusing on sustainability goals within a smart city concept, using the logic of the Complex Adaptive System (CAS). The study was carried out in an innovation cluster in Romania; the Social Network Analysis (SNA) was used as a tool to perform the study. The results of this analysis, due to the suggested networking, have led to delimitation of the roles that Groups of Competences play to enhance the sustainability of smart cities in areas where the use of knowledge has the greatest impact. Results show that the success of the smart solutions’ implementation depends on how the social and competence structures of the network are shaped and whether it permanently adapts to fit the sustainability objectives in the considered areas.

Exploring the raison d’etre behind metric selection in network analysis: a systematic review

“…Beyond the established centrality which dominate local analysis, there are 8 additional centrality metrics that cumulatively account for < 1% (7 papers). These are as follows: Cascading Centrality and Random Centrality (Der Sarkissian et al 2020), Directed Alternative Centrality and Directed Alternative Power (Zheng et al 2020), Egobetweenness Centrality (Hossain and Kuti 2010), Percolation Centrality (Dong et al 2020), Power Centrality (Radulescu et al 2020), and Status Centrality (Ongkowijoyo and Doloi 2017; Tang and Lai 2019). All but three of these centrality measures (Directed Alternative Centrality, Directed Alternative Power and Power Centrality) were applied in the context of disaster management using either spatial networks or SNA, whereas the other three were applied in urban systems in the context of smart cities (SNA) or examining spatial interaction, migration and inter-city flows (spatial network).…”

Systems thinking to operationalize knowledge‐to‐action in fish and wildlife agencies

“…Overcoming the limitations of agent boundaries involves nurturing bottom-up emergent processes that lead to collaboration despite real or perceived barriers (Kettl, 2006;Westley et al, 2013). Among the many concepts discussed in the organizational literature, it is a knowledge network that holds the greatest promise for overcoming boundaries and other selfreinforcing mechanisms that limit the innovation needed to improve the coordination among research, management, and policy in F&W agencies (Castells, 1996;Radulescu et al, 2020). Rules should be minimized so that nimbleness, flexibility, interoperability, and response are maximized.…”

Smart City Results and Sustainability: Current Progress and Emergent Opportunities for Future Research

“…While technology and data plays a crucial role in smart city development [8,9], smart city initiatives also encompass other essential components, such as government, society, and the physical environment, all influence smart city development and its success [1,10,11]. It has also been noted that the design and implementation of smart city initiatives are interdisciplinary and require collaboration among multiple actors across the public, private, and nonprofit sectors and with citizens [12]. Accordingly, the identification of key actors and their roles is paramount whenever studying smart cities [5].…”

“…As a result, both academics and practitioners are now working to better understand how a city can be both smart and sustainable, that is, how information and communication technologies (ICTs) can contribute to the sustainable development of a city [17]. Consistently, a growing body of research has now attempted to better understand how smart city initiatives can either undermine or boost sustainability [12,[18][19][20].…”