Johan Håkansson

Does Euclidean distance work well when the p-median model is applied in rural areas?

The p-median model is used to locate P centers to serve a geographically distributed population. A cornerstone of such a model is the measure of distance between a service center and demand points, i.e. the location of the population (customers, pupils, patients, and so on). Evidence supports the current practice of using Euclidean distance. However, we find that the location of multiple hospitals in a rural region of Sweden with a non-symmetrically distributed population is quite sensitive to distance measure, and somewhat sensitive to spatial aggregation of demand points.

Optimal retail location and CO2 emissions

In this article, the p-median model is used to find the location of retail stores that minimizes CO2 emissions from consumer travel. The optimal location is then compared with the existing retail location, and the excess CO2 emissions compared with the optimal solution is calculated. The results show that by using the environmentally optimal location, CO2 emissions from consumer travel could be reduced by approximately 22%.

Firm migration in the Swedish wholesale trade sector

This article analyzes the determinants of firm migration in the Swedish wholesale trade sector using a unique dataset covering over 10,000 Swedish wholesale trade firms during the years 2000–2004. The results indicate that there are negative correlations between profits, firm age, and firm size and the probability of firm migration. There is a positive correlation between firm growth in the previous year and firm migration, indicating that growth opportunities that cannot be realized at the present location are an important motivation for migration.

How Does Different Algorithm Work When Applied on the Different Road Networks When Optimal Location of Facilities Is Searched for in Rural Areas

The p-median problem is often used to locate P service facilities in a geographically distributed population. Important for the performance of such a model is the distance measure. The first aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the road network is alternated. It is hard to find an exact optimal solution for p-median problems. Therefore, in this study two heuristic solutions are applied, simulating annealing and a classic heuristic. The secondary aim is to compare the optimal location solutions using different algorithms for large p-median problem. The investigation is conducted by the means of a case study in a rural region with a. asymmetrically distributed population, Dalecarlia. The study shows that the use of more accurate road networks gives better solutions for optimal location, regardless what algorithm that is used and regardless how many service facilities that is opt for. It is also shown that the Simulating annealing algorithm not just is much faster than the classic heuristic used here, but also in most cases gives better solutions.

Predicting entry of Swedish wholesale firms into local markets

Applying microeconomic theory, we develop a forecasting model for firm entry into local markets and test this model using data from the Swedish wholesale industry. The empirical analysis is based on directly estimating the profit function of wholesale firms. Profits are assumed to depend on firm- and location-specific factors, and the profit equation is estimated using panel data econometric techniques. Using the residuals from the profit equation estimations, we identify local markets in Sweden where firm profits are abnormally high, given the level of all independent variables included in the profit function. From microeconomic theory, we then know that these local markets should have higher net entry than other markets, all else being equal, and we investigate this in a second step, also using a panel data econometric model. The results of estimating the net-entry equation indicate that 19 of 30 estimated models have more net entry in high-return municipalities, but the estimated parameter is only statistically significant at conventional levels in one of our estimated models, and then with an unexpected negative sign.

Smart Parking Tools Suitability for Open Parking Lots: A Review.

Parking a vehicle in traffic dense environments is a common issue in many parts of the world which oftenleads to congestion and environmental pollution. Lack of guidance information to vacant parki ...

The spatial extent of agglomeration economies across the wage earnings distribution: HÅKANSSON and ISACSSON

We investigate the spatial extent of agglomeration economies across the wage earnings distribution using economic mass (total employment) in four distance bands around each individual’s establishment in a quantile regression framework. We control for observable and unobservable individual and establishment characteristics. Remaining endogeneity in the model is assessed with a set of instrumental variables. Results indicate a positive effect of economic mass on wage earnings up to 25 km away from the establishment. The spatial extent of agglomeration economies is similar across the wage earnings distribution. However, increases in economic mass shift the wage earnings distribution in a nonsymmetric way.

Multiobjective Optimization for Multimode Transportation Problems

We propose modelling for a facilities localization problem in the context of multimode transportation. The applicative goal is to locate service facilities such as schools or hospitals while optimizing the different transportation modes to these facilities. We formalize the School Problem and solve it first exactly using an adapted -constraint multiobjective method. Because of the size of the instances considered, we have also explored the use of heuristic methods based on evolutionary multiobjective frameworks, namely, NSGA2 and a modified version of PAES. Those methods are mixed with an original local search technique to provide better results. Numerical comparisons of solutions sets quality are made using the hypervolume metric. Based on the results for test-cases that can be solved exactly, efficient implementation for PAES and NSGA2 allows execution times comparison for large instances. Results show good performances for the heuristic approaches as compared to the exact algorithm for small test-cases. Approximate methods present a scalable behavior on largest problem instances. A master/slave parallelization scheme also helps to reduce execution times significantly for the modified PAES approach.

Town centre cooperation : Changing perception of property owners

Purpose – The purpose of this paper is to investigate if, and how, different stakeholders perceive property owners (PO) have changed their activities in a town centre after increased competition, a ...

Residential planning, driver mobility and CO2 emission: a microscopic look at Borlänge in Sweden

ABSTRACT In a city there are hotspots that attract citizens, and most of the transportation arises when citizens move between their residence and primary destinations (i.e. hotspots). However, an ex ante evaluation of energy-efficient mobility and urban residential planning has seldom been conducted. Therefore, this paper proposes an ex ante evaluation method to quantify the impacts, in terms of CO2 emissions induced by intra-urban car mobility, of residential plans for various urban areas. The method is illustrated in a case study of a Swedish midsize city, which is presently preoccupied with urban planning of new residential areas in response to substantial population growth due to immigration. In general, CO2 emissions increase from the continued urban core area (CUCA), to the sub-polycentric area (SPA), to the edge urbanization area (EUA), where CO2 emission of EUA is twice that of the CUCA. The average travel distances also increase in the same pattern, though the relative increase is more than four times. Apartment buildings could be more effective in meeting residential needs and mitigating CO2 emissions than dispersed single-family houses.