scholarly journals Gambling Outlets Location in Urban Areas: A Case Study of Madrid

2021 ◽  
Author(s):  
Levi Pérez ◽  
Ana Rodríguez ◽  
Andrey Shmarev
Keyword(s):  
Urban Areas ◽  
Local Governments ◽  
Spatial Econometric ◽  
Spatial Error ◽  
Spatial Dependencies ◽  
Key Factor ◽  
Sar Model ◽  
Spatial Autoregressive ◽  
The City

AbstractCities are certainly a key factor in the location of gambling facilities. This paper aims to map the location of gambling outlets in urban areas and to examine potential links between neighborhoods socioeconomic and demographic characteristics and gambling supply, taking into account spatial dependencies of neighboring areas. This correlation is of interest because neighborhood characteristics may attract sellers, and because the presence of gambling sellers may cause changes in neighborhood demographics. Using detailed official data from the city of Madrid for the year 2017, three spatial econometric approaches are considered: spatial autoregressive (SAR) model, spatial error model (SEM) and spatial lag of X (explicative variables) model (SLX). Empirical analysis finds a strong correlation between neighborhoods characteristics and co-location of gambling outlets, highlighting a specific geographic patterning of distribution within more disadvantaged urban areas. This may have interesting implications for gambling stakeholders and for local governments when it comes to the introduction and/or increase of gambling availability.

Social urbanism: public policy and place brand

2019 ◽  
Vol 12 (3) ◽  
pp. 326-337 ◽  
Author(s):  
Caroline Doyle
Keyword(s):  
Public Policy ◽  
Social Problem ◽  
Local Governments ◽  
Structured Interviews ◽  
Content Type ◽  
Study Approach ◽  
Local Stakeholders ◽  
Place Brand ◽  
The City

PurposeThis paper aims to focus on how a public policy designed to address a social problem ultimately became the place brand.Design/methodology/approachThis paper uses a qualitative case study approach focusing on the city of Medellín, Colombia. It draws from fieldwork conducted in Medellín over 2014 and 2015, including semi-structured interviews with an array of local stakeholders.FindingsThe paper concludes that local governments should be aware that the policymaking process can become part of their branding. It also shows the importance of the continual involvement of stakeholders in the place brand process to ensure it is a sustainable brand.Originality/valueThere are limited studies which focus on how a public policy designed to address a social problem ultimately becomes the place brand. This paper shows how a public policy, social urbanism, became the branding of Medellín.

SPATIAL AUTOREGRESSIVE (SAR) MODEL WITH ENSEMBLE LEARNING-MULTIPLICATIVE NOISE WITH LOGNORMAL DISTRIBUTION (CASE ON POVERTY DATA IN EAST JAVA)

2021 ◽  
Vol 14 (1) ◽  
pp. 89-97
Author(s):  
Dewi Retno Sari Saputro ◽  
Sulistyaningsih Sulistyaningsih ◽  
Purnami Widyaningsih
Keyword(s):  
Regression Model ◽  
Ensemble Learning ◽  
Spatial Data ◽  
Lognormal Distribution ◽  
Multiplicative Noise ◽  
Spatial Regression ◽  
Spatial Error ◽  
Spatial Regression Model ◽  
Sar Model ◽  
Spatial Autoregressive

The regression model that can be used to model spatial data is Spatial Autoregressive (SAR) model. The level of accuracy of the estimated parameters of the SAR model can be improved, especially to provide better results and can reduce the error rate by resampling method. Resampling is done by adding noise (noise) to the data using Ensemble Learning (EL) with multiplicative noise. The research objective is to estimate the parameters of the SAR model using EL with multiplicative noise. In this research was also applied a spatial regression model of the ensemble non-hybrid multiplicative noise which has a lognormal distribution of cases on poverty data in East Java in 2016. The results showed that the estimated value of the non-hybrid spatial ensemble spatial regression model with multiplicative noise with a lognormal distribution was obtained from the average parameter estimation of 10 Spatial Error Model (SEM) resulting from resampling. The multiplicative noise used is generated from lognormal distributions with an average of one and a standard deviation of 0.433. The Root Mean Squared Error (RMSE) value generated by the non-hybrid spatial ensemble regression model with multiplicative noise with a lognormal distribution is 22.99.

scholarly journals Building Smarter Cities through Social Entrepreneurship

2017 ◽  
pp. 327-362 ◽  
Author(s):  
Susana Bernardino ◽  
J. Freitas Santos
Keyword(s):  
Urban Areas ◽  
Smart Cities ◽  
Qualitative Approach ◽  
Non Profit ◽  
Social Interventions ◽  
Social Ventures ◽  
Different Characteristics ◽  
The City ◽  
Disadvantaged People

The objective of the present study is to examine the extent to which social ventures are able to increase the “smartness” of cities. To achieve this goal, we adopt a qualitative approach using a case study method to obtain valuable insights about different characteristics and strategies of Cais (a non-profit association dedicated to helping disadvantaged people in urban areas). Through our analysis of Cais's activities, we assess whether its social interventions match the dimensions proposed by Giffinger et al. (2007) to rank smart cities' performance; specifically, it has smart: economy, people, governance, mobility, environment, and living. The research shows that the action pursued comprises elements from all the above-mentioned dimensions. Further, the analysis reveals that Cais reinforces the smartness of the city in which it acts (in terms of attributes such as living, economy, people, and environment).

scholarly journals A bi-objective integer programming model for locating garbage accumulation points: a case study

2019 ◽  
pp. 70-81
Author(s):  
Diego Gabriel Rossit ◽  
Sergio Nesmachnow ◽  
Jamal Toutouh
Keyword(s):  
Integer Programming ◽  
Local Governments ◽  
Programming Model ◽  
Mathematical Formulation ◽  
Msw Management ◽  
Accumulation Points ◽  
Starting Point ◽  
Support Tools ◽  
The City

Enhancing efficiency in Municipal Solid Waste (MSW) management is crucial for local governments, which are generally in charge of collection, since this activity explains a large proportion of their budgetary expenses. The incorporation of decision support tools can contribute to improve the MSW system, specially by reducing the required investment of funds. This article proposes a mathematical formulation, based on integer programming, to determine the location of garbage accumulation points while minimizing the expenses of the system, i.e., the installment cost of bins and the required number of visits the collection vehicle which is related with the routing cost of the collection. The model was tested in some scenarios of an important Argentinian city that stills has a door-to-door system, including instances with unsorted waste, which is the current situation of the city, and also instances with source classified waste. Although the scenarios with classified waste evidenced to be more challenging for the proposed resolution approach, a set of solutions was provided in all scenarios. These solutions can be used as a starting point for migrating from the current door-to-door system to a community bins system.

scholarly journals Modelling Housing Rents Using Spatial Autoregressive Geographically Weighted Regression: A Case Study in Cracow, Poland

2020 ◽  
Vol 9 (6) ◽  
pp. 346
Author(s):  
Mateusz Tomal
Keyword(s):  
Geographically Weighted Regression ◽  
Rental Housing ◽  
Ordinary Least Squares ◽  
Weighted Regression ◽  
Spatial Econometric ◽  
Econometric Methods ◽  
Depth Analysis ◽  
Sar Model ◽  
Internet Platform ◽  
Spatial Autoregressive

The proportion of tenants will undoubtedly rise in Poland, where at present, the ownership housing model is very dominant. As a result, the rental housing market in Poland is currently under-researched in comparison with owner-occupancy. In order to narrow this research gap, this study attempts to identify the determinants affecting rental prices in Cracow. The latter were obtained from the internet platform otodom.pl using the web scraping technique. To identify rent determinants, ordinary least squares (OLS) regression and spatial econometric methods were used. In particular, traditional spatial autoregressive model (SAR) and spatial autoregressive geographically weighted regression (GWR-SAR) were employed, which made it possible to take into account the spatial heterogeneity of the parameters of determinants and the spatially changing spatial autocorrelation of housing rents. In-depth analysis of rent determinants using the GWR-SAR model exposed the complexity of the rental market in Cracow. Estimates of the above model revealed that many local markets can be identified in Cracow, with different factors shaping housing rents. However, one can identify some determinants that are ubiquitous for almost the entire city. This concerns mainly the variables describing the area of the flat and the age of the building. Moreover, the Monte Carlo test indicated that the spatial autoregressive parameter also changes significantly over space.

scholarly journals Effects of Repeated Sand Replenishment Projects on Runs of a Beach-Spawning Fish, the California Grunion

2020 ◽  
Vol 8 (3) ◽  
pp. 178 ◽  
Author(s):  
Karen L. M. Martin ◽  
Loni C. Adams
Keyword(s):  
Urban Areas ◽  
Sandy Beaches ◽  
Sandy Sediment ◽  
Spawning Habitat ◽  
California Department ◽  
Beneficial Effects ◽  
Late Night ◽  
Method Of Placement ◽  
The City

Beach habitats are diminishing globally, particularly in urban areas, as sea-level rise, erosion, and shoreline hardening, along with reduced sediment inputs, combine to squeeze the coast. In California, USA an endemic marine fish, the California grunion, spawns on sandy beaches during late-night spring tides. Its unique recreational fishery is managed by the California Department of Fish and Wildlife. The City of Oceanside, CA contracts for annual harbor dredging and, after testing, places the sandy sediment on its public beach. The effects on local beach wildlife from this annual sand replenishment are not known. We examined the effect of this repeated activity as a case study over three years on the spawning runs of the California grunion. Some spawning runs occurred in all three years, but the fish avoided areas with high scarps in the intertidal zone that developed following sand placement activity. Grunion spawning runs have declined in the habitat range as a whole over the past two decades, and those in Oceanside have declined to an even greater extent. Increasing sandy beach habitat can be beneficial to wildlife, but the method of placement, timing of the project, and fate of the beach afterward can modulate or prevent beneficial effects. Frequent repetition of sand placement may accumulate impacts without allowing sufficient time for the ecosystem to recover. Rather than improving the habitat, these repeated projects in Oceanside may degrade the spawning habitat for the grunion. Alternative discharge methods and locations, slope and elevation designs, sediment volumes, and greater care in beach fill practices should be implemented to reduce future impacts.

scholarly journals Environmental Urbanization Assessment Using GIS and Multicriteria Decision Analysis: A Case Study for Denizli (Turkey) Municipal Area

2018 ◽  
Vol 2018 ◽  
pp. 1-7
Author(s):  
Erdal Akyol ◽  
Mutlu Alkan ◽  
Ali Kaya ◽  
Suat Tasdelen ◽  
Ali Aydin
Keyword(s):  
Decision Analysis ◽  
Environmental Quality ◽  
Urban Areas ◽  
Spatial Information ◽  
Life Quality ◽  
Multicriteria Decision Analysis ◽  
Multicriteria Decision ◽  
The City

In recent years, life quality of the urban areas is a growing interest of civil engineering. Environmental quality is essential to display the position of sustainable development and asserts the corresponding countermeasures to the protection of environment. Urban environmental quality involves multidisciplinary parameters and difficulties to be analyzed. The problem is not only complex but also involves many uncertainties, and decision-making on these issues is a challenging problem which contains many parameters and alternatives inherently. Multicriteria decision analysis (MCDA) is a very prepotent technique to solve that sort of problems, and it guides the users confidence by synthesizing that information. Environmental concerns frequently contain spatial information. Spatial multicriteria decision analysis (SMCDA) that includes Geographic Information System (GIS) is efficient to tackle that type of problems. This study has employed some geographic and urbanization parameters to assess the environmental urbanization quality used by those methods. The study area has been described in five categories: very favorable, favorable, moderate, unfavorable, and very unfavorable. The results are momentous to see the current situation, and they could help to mitigate the related concerns. The study proves that the SMCDA descriptions match the environmental quality perception in the city.

scholarly journals How Does China’s New Consumption Era Reshape Residents’ Shopping Behaviors from the Perspective of Community in Hohhot, China

2021 ◽  
Vol 13 (14) ◽  
pp. 7599
Author(s):  
Fangqu Niu ◽  
Fang Wang
Keyword(s):  
Urban Areas ◽  
Structural Equation ◽  
Field Survey ◽  
Penetration Rate ◽  
Equation Model ◽  
New Era ◽  
Different Types ◽  
Variable Influence ◽  
The City

In the new consumption era, the popularization and application of information technology has continuously enriched residents’ consumption channels, gradually reshaping their consumption concepts and shopping behaviors. In this paper, Hohhot is taken as a case study, using open-source big data and field survey data to theorize the characteristics and mechanism of residents’ shopping behaviors in different segments of consumers based on geography. First, communities were divided into five types according to their location and properties: main communities in urban areas (MCs), historical communities in urban areas (HCs), high-grade communities in the outskirts of the city (HGCs), mid-grade communities in urban peripheries (MGCs), and urban villages (UVs). On this basis, a structural equation model is used to explore the characteristics of residents’ shopping behaviors and their influencing mechanisms in the new consumption era. The results showed that: (1) The online shopping penetration rate of residents in UVs and HCs is lowest, and that of residents in HGC is highest. (2) The types of products purchased in online and offline shopping by different types of community show certain differences. (3) From the perspective of influencing mechanisms, residents’ characteristics directly affect their shopping behaviors and, indirectly (through the choice of community where they live and their consumption attitudes), their differences in shopping behaviors. Different properties of communities cannot directly affect residents’ shopping behaviors, but they can affect them indirectly by influencing consumption attitudes and then affect such behaviors. Typical consumption attitudes of the new era, such as shopping for luxuries and emerging consumption, have the most significant and direct influence on shopping behaviors, as well as an intermediate and variable influence.

scholarly journals Model Regresi Spasial dan Aplikasinya pada Kasus Tingkat Kemiskinan Kabupaten Soppeng

2018 ◽  
Vol 4 (2) ◽  
pp. 102
Author(s):  
Anggi Ananda Putri ◽  
Wahidah Sanusi ◽  
Sukarna Sukarna
Keyword(s):  
Social Issues ◽  
Well Being ◽  
Error Model ◽  
Poor Household ◽  
Spatial Dependency ◽  
Spatial Error Model ◽  
Spatial Error ◽  
Sar Model ◽  
Spatial Autoregressive ◽  
Independent Variable

Poverty is one of the major problem that frequently faced by human. Begin from poverty, consequently emerged several social issues, such as homeless, beggar, defendant, and prostitution. On this research were conducted modeling poverty degree in Soppeng with using number of poor household as the dependent variable. Modeling were done by using area approach which is a Spatial Autoregressive (SAR) model and Spatial Error Model (SEM). As for the independent variable used on this research is the number of health services, school facility, population density, social well being disable, and the distance on village and centre of Soppeng.  Regarding to the analysis of Spatial Autoregressive (SAR) and Spatial Error Model (SEM) shows that there is a spatial dependency lag and error on number of poor household variable. As for the independent variable which have the significancy account for 5% on Spatial Autoregressive (SAR) and Spatial Error Model (SEM) are every variables with a number R2= 90,9% on SAR and R2= 90,1% on SEM.

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