Big Data and Analytics as Strategies to Generate Public Value in Smart Cities: Proposing an Integrative Framework

Author(s):  
Felippe Cronemberger ◽  
J. Ramon Gil-Garcia
2015 ◽  
Vol 20 (3) ◽  
pp. 237-248 ◽  
Author(s):  
Elcio M. Tachizawa ◽  
María J. Alvarez-Gil ◽  
María J. Montes-Sancho

Purpose – The purpose of this paper is to analyze the impact of smart city initiatives and big data on supply chain management (SCM). More specifically, the connections between smart cities, big data and supply network characteristics (supply network structure and governance mechanisms) are investigated. Design/methodology/approach – An integrative framework is proposed, grounded on a literature review on smart cities, big data and supply networks. Then, the relationships between these constructs are analyzed, using the proposed integrative framework. Findings – Smart cities have different implications to network structure (complexity, density and centralization) and governance mechanisms (formal vs informal). Moreover, this work highlights and discusses the future research directions relating to smart cities and SCM. Research limitations/implications – The relationships between smart cities, big data and supply networks cannot be described simply by using a linear, cause-and-effect framework. Accordingly, an integrative framework that can be used in future empirical studies to analyze smart cities and big data implications on SCM has been proposed. Practical implications – Smart cities and big data alone have limited capacity of improving SCM processes, but combined they can support improvement initiatives. Nevertheless, smart cities and big data can also suppose some novel obstacles to effective SCM. Originality/value – Several studies have analyzed information technology innovation adoption in supply chains, but, to the best of our knowledge, no study has focused on smart cities.


Author(s):  
Andrew Omambia

The concept of smart city is a burgeoning strategy that is fast becoming popular as a strategy that will be able to mitigate the problems emanating from the uncontrolled population growth and urbanization. Academicians have turned their attention to the smart city concept, but an in-depth understanding of the concept is still required. There is a dearth of information on the concept and hence the phenomenon is not well understood. This study, therefore, aims to fill the gap in literature regarding smart cities and propose a framework for grasping the concept further. Based on exploratory studies on the concept of smart cities, this chapter focusses on nine key factors that will form the framework for smart cities and the smart cities initiatives. These nine critical factors include the management, organization governance, technology, people, policy, economy, natural environment, built environment, and the implications of big data on smart cities. These factors provide the basis for the development of an integrative framework that can be employed to examine the manner in which governments around the world, including Kenya, are envisioning smart city initiatives. The framework provides the agendas and directions for smart approaches that can be implemented in cities and a road map for the attainment of smart cities.


MedienJournal ◽  
2017 ◽  
Vol 41 (3) ◽  
pp. 15-28 ◽  
Author(s):  
Paul Clemens Murschetz

Der vorliegende Beitrag untersucht Potenziale und Risiken von Big Data für das Leitmedium Fernsehen. Er nimmt dabei eine betont kritisch-normative Perspektive aus Sicht der Medienökonomie ein und analysiert diese anhand des Beispiels Konvergenzfernsehen. Eine der vielen Dimensionen von Big Data ist nämlich die Analyse des Nutzungsverhaltens einer Vielzahl von Konsumenten. Big Data-Dienste verwenden die Analyseergebnisse nicht nur dazu, individuelle Filmempfehlungen zu geben, sondern entscheiden vielmehr darüber, welche Inhalte überhaupt in das Portfolio eines Anbieters aufgenommen bzw. produziert werden. Auch wenn diese Dienste zu einer Optimierung von TV-Vermarktung führen, ist bis heute umstritten, inwiefern Big Data auch Mehrwert für Nutzer generiert. Auf der Sollseite stehen Überwachung, die Frageder Individualisierung und Rationalisierung des Konsums und generell die Kommodifizierung des Mediums.


2015 ◽  
Author(s):  
Fahimeh Tabatabaei ◽  
Tahir Wani ◽  
Nastran Hajiheidari
Keyword(s):  
Big Data ◽  

2021 ◽  
Vol 24 ◽  
pp. 100192
Author(s):  
Mariagrazia Fugini ◽  
Jacopo Finocchi ◽  
Paolo Locatelli

2020 ◽  
Vol 12 (14) ◽  
pp. 5595 ◽  
Author(s):  
Ana Lavalle ◽  
Miguel A. Teruel ◽  
Alejandro Maté ◽  
Juan Trujillo

Fostering sustainability is paramount for Smart Cities development. Lately, Smart Cities are benefiting from the rising of Big Data coming from IoT devices, leading to improvements on monitoring and prevention. However, monitoring and prevention processes require visualization techniques as a key component. Indeed, in order to prevent possible hazards (such as fires, leaks, etc.) and optimize their resources, Smart Cities require adequate visualizations that provide insights to decision makers. Nevertheless, visualization of Big Data has always been a challenging issue, especially when such data are originated in real-time. This problem becomes even bigger in Smart City environments since we have to deal with many different groups of users and multiple heterogeneous data sources. Without a proper visualization methodology, complex dashboards including data from different nature are difficult to understand. In order to tackle this issue, we propose a methodology based on visualization techniques for Big Data, aimed at improving the evidence-gathering process by assisting users in the decision making in the context of Smart Cities. Moreover, in order to assess the impact of our proposal, a case study based on service calls for a fire department is presented. In this sense, our findings will be applied to data coming from citizen calls. Thus, the results of this work will contribute to the optimization of resources, namely fire extinguishing battalions, helping to improve their effectiveness and, as a result, the sustainability of a Smart City, operating better with less resources. Finally, in order to evaluate the impact of our proposal, we have performed an experiment, with non-expert users in data visualization.


Sign in / Sign up

Export Citation Format

Share Document