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ItemTowards Smarter Cities: Linking Human Mobility and Energy Use Fluctuations across Building Types( 2017-01-04)Urban areas consume up to 80 percent of the world's total energy production and are growing in size and complexity. At present, urban building energy consumption is largely considered solely in terms of individual building types, neglecting the effects of residents’ location-based activities that influence patterns in energy supply and demand. Here, we examine the spatial fluctuations of these effects. A spatial regression analysis of 3,613,360 positional records containing human mobility and energy consumption data across 983 areas in Greater London and 801 areas in the City of Chicago in residential and commercial buildings over the course of one month revealed spatial dependencies for both residential and commercial buildings’ energy consumption on human mobility. This dependency represents a strong connection with residential buildings’ energy consumption, with a spatial spillover effect. Future energy efficiency strategies should thus reflect the spatial dependencies, creating new ways for residential buildings to play a major role in energy related strategies.
ItemInformational Urbanism. A Conceptual Framework of Smart Cities( 2017-01-04)Contemporary and future cities are often labeled as “smart cities,” “digital cities” or “ubiquitous cities,” “knowledge cities,” and “creative cities.” Informational urbanism includes all aspects of information and (tacit as well as explicit) knowledge with regard to urban regions. “Informational city” (or “smart city” in a broader sense) is an umbrella term uniting the divergent trends of information-related city research. Informational urbanism is an interdisciplinary endeavor incorporating on the one side computer science and information science as well as on the other side urban studies, city planning, architecture, city economics, and city sociology. In this article, we present both, a conceptual framework for research on smart cities as well as results from our empirical studies on smart cities all over the world. The framework consists of seven building blocks, namely information and knowledge related infrastructures, economy, politics (e-governance) and administration (e-government), spaces (spaces of flows and spaces of places), location factors, the people’s information behavior, and problem areas. \ \
ItemBig Data and Evidence-Driven Decision-Making: Analyzing the Practices of Large and Mid-Sized U.S. Cities( 2017-01-04)With the growing ease of collecting, transmitting, storing, processing, and analyzing massive amounts of data, Big Data has caught the attention of local officials in recent years. Based on a multi-layered institutional theories and an extensive analysis of the 30 largest cities and 35 selected mid-sized cities in the U.S, this study examines how U.S. cities are using mobile phone apps, sensors, data analytics, and open data portals to pursue Big Data opportunities, and what institutional factors influence their choices. The results show three distinct clusters of data practices among the selected 65 cities. Socio-demographics, cultural institutions, professional networks, and an internal data-driven culture as indicated by the use of performance budgeting are significantly associated with more extensive Big Data initiatives. The paper concludes by discussing the implications for Big Data practices and the theoretical development of e-government research.