The impact of big-boxes on local retail : What happens when IKEA comes to town?

The development of large discount retailers, or big-boxes as they are sometimes referred to, are often subject to heated debate and their entry on a market is greeted with either great enthusiasm or dread. For instance, the world’s largest retailer Wal-Mart (Forbes 2014) has a number of anti- and pro-groups dedicated to its being and the event of a Wal-Mart entry tends to be met with protests and campaigns (Decamme 2013) but also welcomed by, for instance, consumers (Davis & DeBonis 2013). Also in Sweden, the entry of a big box is a hot topic and before IKEA’s opening i Borlänge 2013, the first in Sweden in more than five years, great expectations were mixed with worry (Västerbottens-Kuriren 2011).The presence of large scale discount retailers is not, however, a novel phenomenon but a part of a long-term change in retailing that has taken place globally over the past couple of decades (Taylor & Smalling, 2005). As noted by Dawson (2006), the trend in Europe has over the past few decades gone towards an increasing concentration of large firms along with a decrease of smaller firms.This trend is also detectable in the Swedish retail industry. Over the past decade, the retailing industry in Sweden has increased by around 190 Billion SEK, and its share of GDP has risen from 2,7% to 2,9%, while the number of employees have increased from 200 000 to 250 000 (HUI 2013). This growth, however, has not been distributed evenly but rather it has been oriented mainly towards out-of-town retail clusters. Parallel to this development, the number of large retailers has risen at the expense of market shares of smaller independent firms (Rämme et al 2010). Thereby, the presence of large scale retailers is simply part of a changing retail landscape.The effects of this development, where large scale retailing agents relocate shopping to out-of-town shopping areas, have been heavily debated. On the one hand, the big-boxes are accused of displacing independent small retail businesses in the city-centers and the residential areas, resulting in, to some extent, reduced employment opportunities and less availability for the consumers - especially the elderly (Ljungberg et al 2006). In addition, as access to shopping now tends to require some sort of a motorized vehicle, environmental aspects to the discussion have emerged. Ultimately these types of concerns have resulted in calls for regulations against this development (Olsson 2010). On the other hand, the proponents of the new shopping landscape argue that this evolution implies productivity gains, the benefits of lower prices and an increased variety of products (Maican & Orth 2012). Moreover it is argued that it leads to, for instance, better services (such as longer opening hours) and a creative destruction transformation pressure on retailers, which brings about a renewal of city-centerIIretail and services, increasing their attractivity (Bergström 2010). The belief in benefits of a big box entry can be exemplified by the attractivity of IKEA, and the fact that municipalities are prepared to commit to expenses amounting up to hundreds of millions in order to attract the entry of this big-box. Borlänge municipality, for instance, agreed to expenses of about 350 million SEK in order to secure the entry of IKEA, which opened in 2013 (Blomgren 2009).Against this backdrop, the overall effects of large discount retailers become important: Are the economic benefits enough to warrant subsidies or are there, on the contrary, some very compelling grounds for regulations against these types of establishments? In other words; how is overall retail in a region where a store like IKEA enters affected? And how are local retail firms affected?In order to answer these questions, the purpose of this thesis is to study how entry of a big-box retailer affects the entry region. The object of this study is IKEA - one of the world’s largest retailers, with 345 stores, active in over 40 countries and with profits of about 3.3 billion (IKEA 2013; IKEA 2014). By studying the effects of IKEA-entry, both on an aggregated level and on firm level, this thesis intends to find indications of how large discount retail establishments in general can be expected to affect the economic development both in a region overall, but also on the local firm level, something which is of interest to both policymakers as well as the retailing industry in general.The first paper examines the effects of IKEA on retail revenues and employment in the municipalities that IKEA chose to enter between 2000 and 2011; Gothenburg, Haparanda, Kalmar and Karlstad. By means of a matching method we first identify non-entry municipalities that have a similar probability of IKEA entry as the true entry municipalities. Then, using these non-entry municipalities as a control group, the causal effects of IKEA entry can be estimated using a treatment-control approach. We also extend the analysis to examine the spatial impact of IKEA by estimating the effects on retail in neighboring municipalities. It is found that a new IKEA store increases revenues in durable goods trade with 20% in the entry municipality and the number of employees with 17%. Only small, and in most cases statistically insignificant, negative effects were found in neighboring municipalities.It appears that there is a positive net effect on durables retail sales and employment in the entry municipality. However, the analysis is based on data on an aggregated municipality level and thereby it remains unclear if and how the effects vary within the entry municipalities. In addition, the data used in the first study includes the sales and employment of IKEA itself, which could account for the majority of the increases in employment and retail. Thereby the potential spillover effects on incumbent retailers in the entry municipalities cannot be discerned in the first study.IIITo examine effects of IKEA entry on incumbent retail firms, the second paper in this thesis analyses how IKEA entry affects the revenues and employment of local retail firms in three municipalities; Haparanda, Kalmar and Karlstad, which experienced entry by IKEA between 2000 and 2010. In this second study, we exclude Gothenburg due to the fact that big-box entry appears to have weaker effects in metropolitan areas (as indicated by Artz & Stone 2006). By excluding Gothenburg we aim to reduce the geographical heterogeneity in our study. We obtain control municipalities that are as similar as possible to the three entry municipalities using the same method as in the previous study, but including a slightly different set of variables in the selection equation. Using similar retail firms in the control municipalities as our comparison group, we estimate the impact of IKEA entry on revenues and employment for retail firms located at varying distances from the IKEA entry site.The results generated in this study imply that entry by IKEA increases revenues in incumbent retail firms by, on average, 11% in the entry municipalities. In addition, we do not find any significant impact on retail revenues in the city centers of the entry municipalities. However, we do find that retail firms within 1 km of the IKEA experience increases in revenues of about 26%, which indicates large spillover effects in the area nearby the entry site. As expected, this impact decreases as we expand the buffer zone: firms located between 0-2 km experiences a 14% increase and firms in 2-5 km experiences an increase of 10%. We do not find any significant impacts on retail employment.

First-principle data-driven models for assessment of motor disorders in Parkinson’s disease

Parkinson’s disease (PD) is an increasing neurological disorder in an aging society. The motor and non-motor symptoms of PD advance with the disease progression and occur in varying frequency and duration. In order to affirm the full extent of a patient’s condition, repeated assessments are necessary to adjust medical prescription. In clinical studies, symptoms are assessed using the unified Parkinson’s disease rating scale (UPDRS). On one hand, the subjective rating using UPDRS relies on clinical expertise. On the other hand, it requires the physical presence of patients in clinics which implies high logistical costs. Another limitation of clinical assessment is that the observation in hospital may not accurately represent a patient’s situation at home. For such reasons, the practical frequency of tracking PD symptoms may under-represent the true time scale of PD fluctuations and may result in an overall inaccurate assessment. Current technologies for at-home PD treatment are based on data-driven approaches for which the interpretation and reproduction of results are problematic.  The overall objective of this thesis is to develop and evaluate unobtrusive computer methods for enabling remote monitoring of patients with PD. It investigates first-principle data-driven model based novel signal and image processing techniques for extraction of clinically useful information from audio recordings of speech (in texts read aloud) and video recordings of gait and finger-tapping motor examinations. The aim is to map between PD symptoms severities estimated using novel computer methods and the clinical ratings based on UPDRS part-III (motor examination). A web-based test battery system consisting of self-assessment of symptoms and motor function tests was previously constructed for a touch screen mobile device. A comprehensive speech framework has been developed for this device to analyze text-dependent running speech by: (1) extracting novel signal features that are able to represent PD deficits in each individual component of the speech system, (2) mapping between clinical ratings and feature estimates of speech symptom severity, and (3) classifying between UPDRS part-III severity levels using speech features and statistical machine learning tools. A novel speech processing method called cepstral separation difference showed stronger ability to classify between speech symptom severities as compared to existing features of PD speech. In the case of finger tapping, the recorded videos of rapid finger tapping examination were processed using a novel computer-vision (CV) algorithm that extracts symptom information from video-based tapping signals using motion analysis of the index-finger which incorporates a face detection module for signal calibration. This algorithm was able to discriminate between UPDRS part III severity levels of finger tapping with high classification rates. Further analysis was performed on novel CV based gait features constructed using a standard human model to discriminate between a healthy gait and a Parkinsonian gait. The findings of this study suggest that the symptom severity levels in PD can be discriminated with high accuracies by involving a combination of first-principle (features) and data-driven (classification) approaches. The processing of audio and video recordings on one hand allows remote monitoring of speech, gait and finger-tapping examinations by the clinical staff. On the other hand, the first-principles approach eases the understanding of symptom estimates for clinicians. We have demonstrated that the selected features of speech, gait and finger tapping were able to discriminate between symptom severity levels, as well as, between healthy controls and PD patients with high classification rates. The findings support suitability of these methods to be used as decision support tools in the context of PD assessment.

Road network and GPS tracking with data processing and quality assessment

GPS technology has been embedded into portable, low-cost electronic devices nowadays to track the movements of mobile objects. This implication has greatly impacted the transportation field by creating a novel and rich source of traffic data on the road network. Although the promise offered by GPS devices to overcome problems like underreporting, respondent fatigue, inaccuracies and other human errors in data collection is significant; the technology is still relatively new that it raises many issues for potential users. These issues tend to revolve around the following areas: reliability, data processing and the related application. This thesis aims to study the GPS tracking form the methodological, technical and practical aspects. It first evaluates the reliability of GPS based traffic data based on data from an experiment containing three different traffic modes (car, bike and bus) traveling along the road network. It then outline the general procedure for processing GPS tracking data and discuss related issues that are uncovered by using real-world GPS tracking data of 316 cars. Thirdly, it investigates the influence of road network density in finding optimal location for enhancing travel efficiency and decreasing travel cost. The results show that the geographical positioning is reliable. Velocity is slightly underestimated, whereas altitude measurements are unreliable.Post processing techniques with auxiliary information is found necessary and important when solving the inaccuracy of GPS data. The densities of the road network influence the finding of optimal locations. The influence will stabilize at a certain level and do not deteriorate when the node density is higher.

Using Spatiotemporal Methods to Fill Gaps In Energy Usage Interval Data

Researchers analyzing spatiotemporal or panel data, which varies both in location and over time, often find that their data has holes or gaps. This thesis explores alternative methods for filling those gaps and also suggests a set of techniques for evaluating those gap-filling methods to determine which works best.

RWater – A Cyber Enabled Tool For Hydrologic Modeling And Analysis

Existing distributed hydrologic models are complex and computationally demanding for using as a rapid-forecasting policy-decision tool, or even as a class-room educational tool. In addition, platform dependence, specific input/output data structures and non-dynamic data-interaction with pluggable software components inside the existing proprietary frameworks make these models restrictive only to the specialized user groups. RWater is a web-based hydrologic analysis and modeling framework that utilizes the commonly used R software within the HUBzero cyber infrastructure of Purdue University. RWater is designed as an integrated framework for distributed hydrologic simulation, along with subsequent parameter optimization and visualization schemes. RWater provides platform independent web-based interface, flexible data integration capacity, grid-based simulations, and user-extensibility. RWater uses RStudio to simulate hydrologic processes on raster based data obtained through conventional GIS pre-processing. The program integrates Shuffled Complex Evolution (SCE) algorithm for parameter optimization. Moreover, RWater enables users to produce different descriptive statistics and visualization of the outputs at different temporal resolutions. The applicability of RWater will be demonstrated by application on two watersheds in Indiana for multiple rainfall events.

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise based upon data from a well known survey is also presented. Overall, theoretical and empirical results show promise for the feasible bias-corrected average forecast.

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular it delivers a zero-limiting mean-squared error if the number of forecasts and the number of post-sample time periods is sufficiently large. We also develop a zero-mean test for the average bias. Monte-Carlo simulations are conducted to evaluate the performance of this new technique in finite samples. An empirical exercise, based upon data from well known surveys is also presented. Overall, these results show promise for the bias-corrected average forecast.

A panel data approach to economic forecasting: the bias-corrected average forecast

In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise, based upon data from a well known survey is also presented. Overall, these results show promise for the feasible bias-corrected average forecast.

Emprego formal na região nordeste brasileira: seus efeitos na inclusão social

This work aims to study the problem of the formal job in the Brazilian Northeast region and its effect in the social inclusion, taking for base the analysis of variables defined in the Atlas of Social Exclusion, which is based on the 2000 Brazilian Census, choosing the county as unit of analysis. As methodological options, an exploratory data analysis was performed, followed by multivariate statistical techniques, such as weighted multiple regression analysis, cluster analysis and exploratory analysis of spatial data. The results pointed out to low rates of formal job for the active age population as well as low indexes of social inclusion in the Northeast region of Brazil. A strong association of the formal job with the indicators of social inclusion under investigation, was evidenced (schooling, inequality, poverty, youth and income form government transfers), as well as a strong association of the formal job with the new index of social inclusion (IIS), modified from the IES. At the Federative Units, in which better levels of formal job had been found, good indexes of social inclusion are also observed. Highlights for the state of the Rio Grande do Norte, with the best conditions of life, and for the states of the Maranhão and Piauí, with the worst conditions. The situation of the Northeast region, facing the indicators under study, is very precarious, claiming for the necessity of emphasizing programs and governmental actions, specially directed to the raise of formal job levels of the region, reflecting, thus, in improvements on the income inequality, as well as in the social inclusion of the population of Northeastern natives.

Caracterização geomorfológica e modelagem de dados espaciais na plataforma continental rasa do RN nos limites da folha Touros

This work focuses the geomorphological characterization and spatial data modeling in the shallow continental shelf within the Folha Touros limits (SB-25-CV-II), based on bathymetric data analysis and remote sensing products interpretation. The Rio Grande do Norte state is located in northeastern Brazil and the work area is located at the transition region between the eastern and northern portions of their coast. The bathymetric surveys were conduced between march and may 2009, using a 10 meters long vessel and 0.70 meters draught, equipped with global positioning system and echo sounder (dual beam, 200KHz , 14°). The fieldwork resulted in 44 bathymetric profiles espaced 1.5 km and 30 km average length. The bathymetric data amount were 111,200 points and were navigated 1395.7 km within na area about 1,850 km2. The bathymetric data were corrected for the tide level, vessel draught and were subsequently entered into a geographic information system for further processing. Analysis of remote sensing products was carried out using Landsat 7/ETM + band 1, from november 1999. The image was used for visualization and mapping submerged features. The results showed the presence of geomorphological features within the study area. Were observed, from the analysis of local bathymetry and satellite image, seven types of geomorphological features. The channels, with two longitudinals channels (e. g. San Roque and Cioba channels) and other perpendicular to the coast (e. g. Touros, Pititinga and Barretas). Coastal reef formations (Maracajaú, Rio do Fogo and Cioba). Longitudinal waves, described in the literature as longitudinal dunes. The occurrence of a transverse dune field. Another feature observed was the oceanic reefs, an rock alignment parallel to the coast. Were identified four riscas , from north to south: risca do Liso, Gameleira, Zumbi, Pititinga (the latter being described for the first time). Finally, an oceanic terrace was observed in the deepest area of study. Image interpretation corroborated with the in situ results, enabling visualization and description for all features in the region. The results were analysed in an integrating method (using the diferent methodologies applied in this work) and it was essential to describe all features in the area. This method allowed us to evaluate which methods generated better results to describe certain features. From these results was possible to prove the existence of submerged features in the eastern shallow continental shelf of Rio Grande do Norte. In this way, the conclusions was (1) this study contributed to the provision of new information about the area in question, particularly with regard to data collection in situ depths, (2) the method of data collection and interpretation proves to be effective because, through this, it was possible to visualize and interpret the features present in the study area and (3) the interpretation and discussion of results in an integrated method, using different methodologies, can provide better results

Prevalência e localização espacial dos casos de tracoma detectados em escolares de Botucatu, São Paulo - Brasil

OBJETIVO: Avaliar a prevalência de tracoma em escolares de Botucatu/SP-Brasil e a distribuição espacial dos casos. MÉTODOS: Foi realizado um estudo transversal, em crianças de 7-14 anos, que frequentavam as escolas do ensino fundamental de Botucatu/SP, em novembro/2005. O tamanho da amostra foi estimado em 2.092 crianças, considerando-se a prevalência histórica de 11,2%, aceitando-se erro de estimação de 10% e nível de confiança de 95%. A amostra foi probabilística, ponderada e acrescida de 20%, devido à possível ocorrência de perdas. Examinaram-se 2.692 crianças. O diagnóstico foi clínico, baseado na normatização da Organização Mundial da Saúde (OMS). Para avaliação dos dados espaciais, utilizou-se o programa CartaLinx (v1.2), sendo os setores de demanda escolar digitalizados de acordo com as divisões do planejamento da Secretaria de Educação. Os dados foram analisados estatisticamente, sendo a análise da estrutura espacial dos eventos calculadas usando o programa Geoda. RESULTADOS: A prevalência de tracoma nos escolares de Botucatu foi de 2,9%, tendo sido detectados casos de tracoma folicular. A análise exploratória espacial não permitiu rejeitar a hipótese nula de aleatoriedade (I= -0,45, p>0,05), não havendo setores de demanda significativos. A análise feita para os polígonos de Thiessen também mostrou que o padrão global foi aleatório (I= -0,07; p=0,49). Entretanto, os indicadores locais apontaram um agrupamento do tipo baixo-baixo para um polígono ao norte da área urbana. CONCLUSÃO: A prevalência de tracoma em escolares de Botucatu foi de 2,9%. A análise da distribuição espacial não revelou áreas de maior aglomeração de casos. Embora o padrão global da doença não reproduza as condições socioeconômicas da população, a prevalência mais baixa do tracoma foi encontrada em setores de menor vulnerabilidade social.

Evaluation of neighborhood impacts caused by companies of the high-tech industrial cluster of São Carlos, SP, Brazil

The purpose of this study was to develop a methodology for evaluating neighborhood impacts using a Geographic Information System (GIS) and to apply the procedures to the companies of the High-Technology Industrial Cluster of São Carlos. To this end, an evaluation was made of the neighborhood impacts on the physical environment, urban components, quality of life, and urban infrastructure using impact matrices, and the impacts were assigned scores according to type, order, magnitude and duration. Fifty one companies were examined based on data provided by the companies themselves and on field surveys. The impacts are represented spatially in proportional symbols maps, based on the spatial distribution of the companies in the urban area of the city of São Carlos and the areas of influence of each company. The application of the proposed methodology served to validate it and indicated that the neighborhood impacts caused by the companies of this study are related to each company's type of activity, its size, and its occupation of the area. © 2008 Journal of Urban and Environmental Engineering (JUEE). All rights reserved.

Spatial clustering applied to health area

The significant volume of work accidents in the cities causes an expressive loss to society. The development of Spatial Data Mining technologies presents a new perspective for the extraction of knowledge from the correlation between conventional and spatial attributes. One of the most important techniques of the Spatial Data Mining is the Spatial Clustering, which clusters similar spatial objects to find a distribution of patterns, taking into account the geographical position of the objects. Applying this technique to the health area, will provide information that can contribute towards the planning of more adequate strategies for the prevention of work accidents. The original contribution of this work is to present an application of tools developed for Spatial Clustering which supply a set of graphic resources that have helped to discover knowledge and support for management in the work accidents area. © 2011 IEEE.

Suporte à elaboração de plano diretor com ênfase na aplicação de instrumento urbanístico do estatuto da cidade. Estudo de caso: Bastos-SP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Extração semi-automática do eixo de rodovia em imagens de média e alta resolução usando programação dinâmica

Pós-graduação em Ciências Cartográficas - FCT