Digital Dashboards for Smart City Governance: A Case Project to Develop an Urban Safety Indicator Model

Marco, Alberto De; Mangano, Giulio; Zenezini, Giovanni

doi:10.4236/jcc.2015.35018

Cited by 14 publications

(10 citation statements)

References 23 publications

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“…The city development index (CDI), developed to readjust the human development index, is one of the best-known indicators [80], which was issued by United Nations Development Programme (UNDP) Human Development Report Office. Dameri investigated many studies and summarized seven city indicators [1]: urban audit (UA), European common indicators (ECI), global city indicators facility (GCIF), quality of life (QoL) reporting system, cities data book (CDB), global urban indicators, and global sustainable urban development (GSUD).…”

Section: Urban Indicators Used For City Performancementioning

confidence: 99%

Geospatial Dashboards for Monitoring Smart City Performance

Jing

et al. 2019

Sustainability

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Geospatial dashboards have attracted increasing attention from both user communities and academic researchers since the late 1990s. Dashboards can gather, visualize, analyze and advise on urban performance to support sustainable development of smart cities. We conducted a critical review of the research and development of geospatial dashboards, including the integration of maps, spatial data analytics, and geographic visualization for decision support and real-time monitoring of smart city performance. The research about this kind of system has mainly focused on indicators, information models including statistical models and geospatial models, and other related issues. This paper presents an overview of dashboard history and key technologies and applications in smart cities, and summarizes major research progress and representative developments by analyzing their key technical issues. Based on the review, we discuss the visualization model and validity of models for decision support and real-time monitoring that need to be further researched, and recommend some future research directions.

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Section: Urban Indicators Used For City Performancementioning

confidence: 99%

Geospatial Dashboards for Monitoring Smart City Performance

Jing

et al. 2019

Sustainability

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“…as well as articles discussing issues mostly focused on city growth (like "urban growth assessment") or modeling and benchmarking in general. Screening examined citations that leave space for further exploration resulted in 48 publications as shown in Table 1 Anthopoulos (2015); Anthopoulos and Fitsilis (2013); Bakici et al (2013); Baron (2012); Batty et al (2012); Bellini et al (2014); Calvillo et al (2016); Caragliu et al (2011); da Cruz and Marques (2014); De Marco et al (2015); Desouza and Flanery (2013); Duarte et al (2014); Edvinsson (2016); Fan et al (2016);Fei. (2012); Giffinger et al (2007); Glebova et al (2014); Hancke et al (2013); Kii et al (2014); Kourtit et al (2014); Hollands (2008); ISO (2014); ITU (2014); Lazaroiu and Roscia (2012); Liu et al (2014); Lee et al (2013); Lee et al (2014); Leydesdorff and Deakin (2011); Lombardi et al (2012); Malek (2010); Marsal-Llacuna et al (2015); Mori and Christodoulou (2012); Naphade et al (2011); Neirotti et al (2014); Pires et al (2014); Shapiro (2006); Shwayri (2013); Singhal et al (2013);…”

Section: Research Approachmentioning

confidence: 99%

“…Their study identified the most relevant variables with the highest loading factors, in regard to advanced business and socio-cultural attractiveness (ADBA), presence of a broad (public and private) labour force and public facilities (PBLFPF) and presence and use of sophisticated e-services (PUSS) of smart cities. De Marco et al (2015) propose several safety measurement indicators, which provide decision makers with a significant tool to develop corresponding policies. Their study developed a three-level index named global safety indicator, which is analyzed in road safety and personal safety (second level).…”

Section: Smart City Benchmarkingmentioning

confidence: 99%

A Unified Smart City Model (USCM) for Smart City Conceptualization and Benchmarking

Ανθόπουλος

Janssen

Weerakkody

2018

E-Planning and Collaboration

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Smart cities have attracted an extensive and emerging interest from both science and industry with an increasing number of international examples emerging from all over the world. However, despite the significant role that smart cities can play to deal with recent urban challenges, the concept has been being criticized for not being able to realize its potential and for being a vendor hype. This paper reviews different conceptualization, benchmarks and evaluations of the smart city concept. Eight different classes of smart city conceptualization models have been discovered, which structure the unified conceptualization model and concern smart city facilities (i.e., energy, water, IoT etc.), services (i.e., health, education etc.), governance, planning and management, architecture, data and people. Benchmarking though is still ambiguous and different perspectives are followed by the researchers that measure -and recently monitor- various factors, which somehow exceed typical technological or urban characteristics. This can be attributed to the broadness of the smart city concept. This paper sheds light to parameters that can be measured and controlled in an attempt to improve smart city potential and leaves space for corresponding future research. More specifically, smart city progress, local capacity, vulnerabilities for resilience and policy impact are only some of the variants that scholars pay attention to measure and control.

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“…Apart from health, electronic or visual dashboards are also used in a company to report supply chain operations in order to improve company performance (Busi & Strandhagen, 2004). E-dashboard in government supports the existence of an integrated instrument used for evaluation that can improve government performance (Marco, Mangano, and Zenezini 2015).…”

Section: Introductionmentioning

confidence: 99%

Development of prototype electronic dashboard service performance of LPKA class I Palembang

Hadiwijaya¹,

Febrianty²,

Azdy³

2021

SinkrOn

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LPKA Palembang provides services to the community in the form of coaching in the fields of education, skills training, community guidance, and alleviation, services for Andikpas visits and complaints, remission submission services, assimilation, and other submissions especially to support alleviation programs such as the Conditional Leave (CB) program, Leaving Towards Free (CMB), and Parole (PB). To provide the best convenience and quality in providing services, a system is needed that can not only be used to submit and process service data online, but also can integrate service data so that it can be more easily accessed anytime and anywhere. The system created is an electronic dashboard or e-dashboard that can present data visually so that it is easily understood by readers. This study aims to build a prototype that can provide an overview of the e-dashboard system to be built. From the prototype evaluation, user feedback can be obtained which can be used to build an actual e-dashboard system so that it can reduce deviations from the system being built. The stages in this research are planning, designing, building, and evaluating the prototype. The results of this study are the development of e-Dashboard prototype that had been tested by 80% of LPKA Class I Palembang employees. The developed prototype has features that almost meet user needs because the system development is based on a quick analysis of the needs of future e-Dashboard users.

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Digital Dashboards for Smart City Governance: A Case Project to Develop an Urban Safety Indicator Model

Cited by 14 publications

References 23 publications

Geospatial Dashboards for Monitoring Smart City Performance

Geospatial Dashboards for Monitoring Smart City Performance

A Unified Smart City Model (USCM) for Smart City Conceptualization and Benchmarking

Development of prototype electronic dashboard service performance of LPKA class I Palembang

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