Recent years have shown an increasing interest in local factors shaping the happiness or attachment of citizens in regard to their daily living environment, sometimes also coined city love or neighborhood love. This new strand of literature—often framed in the context of the “geography of happiness” or the “economics of happiness”—means an extension of quantitative socio-psychological or socio-economic research on determinants of people’s affection for their living environment, including local quality-of-life, sense of community, place-based social capital, attachment to “urban ambiance,” and so on. The present paper conceptualizes the nature and composition of urban characteristics of place attachment and appreciation (city love) in terms of two constituent factors, viz. city soul (indicators on the perceived intangible attractiveness of the city and its neighborhoods) and city body (indicators reflecting the tangible attractiveness features of the city). This analytical approach will empirically be tested for four Swedish cities. Resident surveys were conducted among a total of 2,573 respondents; the multidimensional relationships between outcome variables and background factors were tested through a Partial Least Squares Structural Equation Model (PLS-SEM), which revealed significant effects of Aesthetics, Amenities, Accessibility, Safety and Health, and City Image on place attachment and appreciation (“city love”). A more detailed city level analysis revealed salient place-specific differences. In general, Aesthetics seemed to be the most universal driver for city love, while City Image was the most important factor to contribute to city soul.

The contemporary 'digital age' prompts the need for a re-assessment of urban planning principles and practices. Against the background of current data-rich urban planning, this study seeks to address the question whether an appropriate methodological underpinning can be provided for smart city governance based on a data-driven planning perspective. It posits that the current digital technology age has a drastic impact on city strategies and calls for a multi-faceted perspective on future urban development, termed here the 'XXQ-principle' (which seeks to attain the highest possible level of quality for urban life). Heterogeneity in urban objectives and data embodied in the XXQ-principle can be systematically addressed by a process of data decomposition (based on a 'cascade principle'), so that first, higher-level urban policy domains are equipped with the necessary ('big') data provisions, followed by lower-ranking urban governance levels. The conceptual decomposition principle can then be translated into a comprehensive hierarchical model architecture for urban intelligence based on the 'flying disc' model, including key performance indicators (KPIs). This new model maps out the socio-economic arena of a complex urban system according to the above cascade system. The design of this urban system architecture and the complex mutual connections between its subsystems is based on the 'blowing-up' principle that originates from a methodological deconstruction-reconstruction paradigm in the social sciences. The paper advocates the systematic application of this principle to enhance the performance of smart cities, called the XXQ performance value. This study is not empirical, although it is inspired by a wealth of previous empirical research. It aims to advance conceptual and methodological thinking on principles of smart urban planning.

Sustainable urban development calls for a balanced package of conditions that induce a high quality of life (including safety and security) in cities. We argue that modern cities have to develop knowledge- based strategies for smart, safe and sound (3-S) city development, supported by urban performance assessment (UPA) as a framework for sustainable urban planning. The present study builds on these strategic notions and articulates the message that smart urban policy should look into input resources in relation to output performance. Particular attention will be paid to the constituents and the role of multiple safety indicators in urban performance analysis. Next, an appropriate method from the industrial management literature, namely, super-efficient data envelopment analysis (SE-DEA) will be utilized in order to undertake a comparative performance assessment of safety conditions in 57 world cities, followed by a similar analysis for 14 large European cities. Both world-wide and Europe-wide, there appear to be significant differences in safety performance of cities, which means that there is much scope for strategic and effective safety policy in many cities.

Cities - and, in general, urban agglomerations - have in recent years become foci of social science research and policy interest. Prominent attention has been given to agglomeration advantages, mobility patterns, urban decay, inequity problems, residents' quality of life, safety and crime, labour and housing markets, public amenities, and urban planning issues. Less attention however, has been paid to the basic question: what makes the city a 'real' and attractive city? This question prompts essentially a research challenge on the 'raison d'etre' of cities, in particular on the residential satisfaction and quality-of-life motives of urban inhabitants. The present paper aims to pinpoint attractiveness characteristics of cities based on perceptions of urban quality by residents and their affinity with city life. This paper offers a micro-based (individual) assessment of motives and appreciations of citizens, in terms of their love for the city. A typological distinction will be made between the 'soul' of the city (its spirit, history, cultural identity, ambiance, social capital, etc.) and the 'body' of the city (its built environment, infrastructure, public amenities, supply of housing, green areas, etc.). The empirical analysis - applied to the four largest cities in Sweden (Stockholm, Gothenburg, Malmoe and Umea) - will be undertaken in two steps: (i) an exploratory statistical analysis of the findings from an extensive micro-based survey questionnaire among inhabitants in these four urban agglomerations; (ii) an explanatory evaluation of the individual appreciation scores using a regression approach. Our results show that the 'City Love Index' is a useful construct that can be decomposed into 'soul' and 'body' aspects of the city. Our multivariate regression analysis demonstrates clearly that both factors matter. More detailed results suggest that it is the perceptions regarding the city's 'walkability' and 'vibrancy', both part of the 'soul' of the city, that have a significant influence on the City Love Index -for all cities studied.

Destination attractiveness research has become an important research domain in leisure and tourism economics. But the mobility behaviour of visitors in relation to local public transport access in tourist places is not yet well understood. The present paper seeks to fill this research gap by studying the attractiveness profile of 25 major tourist destination places in the world by means of a 'big data' analysis of the drivers of visitors' mobility behaviour and the use of public transport in these tourist places. We introduce the principle of 'the path of least resistance' to explain and model the spatial behaviour of visitors in these 25 global destination cities. We combine a spatial hedonic price model with geoscience techniques to better understand the place-based drivers of mobility patterns of tourists. In our empirical analysis, we use an extensive and rich database combining millions of Airbnb listings originating from the Airbnb platform, and complemented with TripAdvisor platform data and OpenStreetMap data. We first estimate the effect of the quality of the Airbnb listings, the surrounding tourist amenities, and the distance to specific urban amenities on the listed Airbnb prices. In a second step of the multilevel modelling procedure, we estimate the differential impact of accessibility to public transport on the quoted Airbnb prices of the tourist accommodations. The findings confirm the validity of our conceptual framework on 'the path of least resistance' for the spatial behaviour of tourists in destination places.

We use a theoretical political-economy model with three cities and analyze three questions. First, should police in these cities have access to contentious crime fighting technologies such as facial recognition software? We describe a condition involving benefit, cost, and spatial spillover terms which tells us when the police ought to be provided with this technology. Second, if police are to be offered this technology then what are the properties of a policy regime that provides this technology in a decentralized way? We identify a condition that depends only on benefit and cost terms which tells us when this technology is to be made available in the cities in a decentralized way. Finally, what are the properties of a policy regime that provides the technology in a centralized way with equal cost sharing by the cities? We obtain two conditions involving benefit and spatial spillover terms that describe scenarios in which (i) the technology is provided with majority voting in a city even though it is inefficient to do so and (ii) it is efficient to provide the technology in a city but majority voting will lead to this technology not being provided.

The aim of the paper is to elaborate the popular concept of spatial clusters in a broader regional development context. Are regional clusters natural and emergent? Do we understand how and why? Does the concept necessarily imply nearness? How much? How little? Is there a role for policy makers? This contribution offers an up-to-date critical perspective. 

Urban agglomerations - irrespective of their size or location - may act not only as engines of economic growth, but also as vehicles of environmental and climate sustainability that may stimulate both socioeconomic achievements and environmentally-benign outcomes. Clearly, the efficiency of these outcomes may differ for different types of urban agglomeration in the world. This paper aims to present and test an advanced methodology for assessing economic and sustainability-oriented performance strategies for global cities, by developing and applying a super-efficient Data Envelopment Analysis (DEA) model. We compare 40 global cities - included in the Global Power City Index (GPCI) database - in a benchmark study in order to trace the highest-performing urban regions from both an economic and environmental-climatological efficiency perspective, by applying relevant quantitative GPCI indicators to these 40 cities. Our ultimate goal is to test what is termed the 'delinking' hypothesis, from the viewpoint of both economic prosperity and urban size externalities. This approach will be applied empirically by examining the GPCI data set comprised of various multidimensional and empirically verified indicators on economic performance and climatological-environmental conditions for the 40 global cities concerned. We regard both the size of these agglomerations and their economic welfare position as critical parameters for assessing their economic and environmental efficiency performance. In the framework of our original DEA approach, these urban areas are categorised according to 2x2 dimensions, viz. in terms of both agglomeration size (big or medium-sized) and the economic development level of the area (highly developed or developing/emerging). Our contribution serves to assess - by means of regression techniques - the highest performing agglomerations among the urban sustainability champions on the basis of the two above-mentioned assessment criteria. This approach provides the opportunity to test the so-called Kuznets sustainability curve under two different conditions, viz. agglomeration size and economic development. The study presents and interprets the empirical findings for these four classes of global cities. (C) 2019 Elsevier B.V. All rights reserved.

This paper maps out the structure and relative dynamics of cities of various size classes in India. It aims to address their hierarchical distribution, by employing the rank-size rule, Gibrat's law, and a primacy index. The implications of urban concentrations for GDP, banking system, FDI, civic amenities, and various urban externalities (such as pollution and spatial exclusion) are also examined. It shows that India's urban system, though it follows the rank-size rule, is huge and top-heavy. It follows also Gibrat's law of proportionate growth. Although India's cities collectively account for less than one third of the total population, they command more than three fourths of the country's GDP. Megacities have become congested, clogged, polluted, and also show significant social polarization. There is a gridlock situation for the cities, inhibiting their potential for becoming effective economic and social change sites. The top-heavy character of India's urban system also adversely impacts the balanced regional development of the country.