970 resultados para Location-Allocation Models


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Low corporate taxes can help attract new firms. This is the main mechanism underpinning the standard 'race-to-the-bottom'view of tax competition. A recent theoretical literature has qualified this view by formalizing the argument that agglomeration forces can reduce firms' sensitivity to tax differentials across locations. We test this proposition using data on firm startups across Swiss municipalities. We find that, on average, high corporate income taxes do deter new firms, but that this relationship is significantly weaker in the most spatially concentrated sectors. Location choices of firms in sectors with an agglomeration intensity at the twentieth percentile of the sample distribution are estimated to be twice as responsive to a given difference in local corporate tax burdens as firms in sectors with an agglomeration intensity at the eightieth percentile. Hence, our analysis confirms the theoretical prediction: agglomeration economies can neutralize the impact of tax differentials on firms' location choices.

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The optimal location of services is one of the most important factors that affects service quality in terms of consumer access. On theother hand, services in general need to have a minimum catchment area so as to be efficient. In this paper a model is presented that locates the maximum number of services that can coexist in a given region without having losses, taking into account that they need a minimum catchment area to exist. The objective is to minimize average distance to the population. The formulation presented belongs to the class of discrete P--median--like models. A tabu heuristic method is presented to solve the problem. Finally, the model is applied to the location of pharmacies in a rural region of Spain.

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The Maximum Capture problem (MAXCAP) is a decision model that addresses the issue of location in a competitive environment. This paper presents a new approach to determine which store s attributes (other than distance) should be included in the newMarket Capture Models and how they ought to be reflected using the Multiplicative Competitive Interaction model. The methodology involves the design and development of a survey; and the application of factor analysis and ordinary least squares. Themethodology has been applied to the supermarket sector in two different scenarios: Milton Keynes (Great Britain) and Barcelona (Spain).

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We offer a formulation that locates hubs on a network in a competitiveenvironment; that is, customer capture is sought, which happenswhenever the location of a new hub results in a reduction of thecurrent cost (time, distance) needed by the traffic that goes from thespecified origin to the specified destination.The formulation presented here reduces the number of variables andconstraints as compared to existing covering models. This model issuited for both air passenger and cargo transportation.In this model, each origin-destination flow can go through either oneor two hubs, and each demand point can be assigned to more than a hub,depending on the different destinations of its traffic. Links(``spokes'' have no capacity limit. Computational experience is provided.

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Previous covering models for emergency service consider all the calls to be of the sameimportance and impose the same waiting time constraints independently of the service's priority.This type of constraint is clearly inappropriate in many contexts. For example, in urban medicalemergency services, calls that involve danger to human life deserve higher priority over calls formore routine incidents. A realistic model in such a context should allow prioritizing the calls forservice.In this paper a covering model which considers different priority levels is formulated andsolved. The model heritages its formulation from previous research on Maximum CoverageModels and incorporates results from Queuing Theory, in particular Priority Queuing. Theadditional complexity incorporated in the model justifies the use of a heuristic procedure.

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The goal of this paper is to present an optimal resource allocation model for the regional allocation of public service inputs. Theproposed solution leads to maximise the relative public service availability in regions located below the best availability frontier, subject to exogenous budget restrictions and equality ofaccess for equal need criteria (equity-based notion of regional needs). The construction of non-parametric deficit indicators is proposed for public service availability by a novel application of Data Envelopment Analysis (DEA) models, whose results offer advantages for the evaluation and improvement of decentralised public resource allocation systems. The method introduced in this paper has relevance as a resource allocation guide for the majority of services centrally funded by the public sector in a given country, such as health care, basic and higher education, citizen safety, justice, transportation, environmental protection, leisure, culture, housing and city planning, etc.

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Aim  The imperfect detection of species may lead to erroneous conclusions about species-environment relationships. Accuracy in species detection usually requires temporal replication at sampling sites, a time-consuming and costly monitoring scheme. Here, we applied a lower-cost alternative based on a double-sampling approach to incorporate the reliability of species detection into regression-based species distribution modelling.Location  Doñana National Park (south-western Spain).Methods  Using species-specific monthly detection probabilities, we estimated the detection reliability as the probability of having detected the species given the species-specific survey time. Such reliability estimates were used to account explicitly for data uncertainty by weighting each absence. We illustrated how this novel framework can be used to evaluate four competing hypotheses as to what constitutes primary environmental control of amphibian distribution: breeding habitat, aestivating habitat, spatial distribution of surrounding habitats and/or major ecosystems zonation. The study was conducted on six pond-breeding amphibian species during a 4-year period.Results  Non-detections should not be considered equivalent to real absences, as their reliability varied considerably. The occurrence of Hyla meridionalis and Triturus pygmaeus was related to a particular major ecosystem of the study area, where suitable habitat for these species seemed to be widely available. Characteristics of the breeding habitat (area and hydroperiod) were of high importance for the occurrence of Pelobates cultripes and Pleurodeles waltl. Terrestrial characteristics were the most important predictors of the occurrence of Discoglossus galganoi and Lissotriton boscai, along with spatial distribution of breeding habitats for the last species.Main conclusions  We did not find a single best supported hypothesis valid for all species, which stresses the importance of multiscale and multifactor approaches. More importantly, this study shows that estimating the reliability of non-detection records, an exercise that had been previously seen as a naïve goal in species distribution modelling, is feasible and could be promoted in future studies, at least in comparable systems.

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Durant el segle XIX, l'economia espanyola va transitar per les primeres etapes de la industrialització. Aquest procés es va donar en paral·lel a la integració del mercat domèstic de béns i factors, en un moment en què les reformes liberals i la construcció de la xarxa ferroviària, entre d'altres, van generar una important caiguda en els costos detransport. Al mateix temps que es donava aquesta progressiva integració del mercat domèstic espanyol, es van produir canvis significatius en la pauta de localització industrial. D'una banda, hi hagué un augment considerable de la concentració espacial de la indústria des de mitjans de segle XIX i fins a la Guerra Civil, i d¿altra, un increment de l'especialització regional. Ara bé, quines van ser les forces que van generar aquests canvis? Des d¿un punt de vista teòric, el model de Heckscher-Ohlin suggereix que la distribució a l'espai de l¿activitat econòmica ve determinada per l'avantatge comparativa dels territoris en funció de la dotació relativa de factors. Al seu torn, els models de Nova Geografia Econòmica (NEG) mostren l'existència d'una relació en forma de campana entre el procés d'integració econòmica i el grau de concentració geogràfica de l'activitat industrial. Aquest article examina empíricament els determinants de la localització industrial a Espanya entre 1856 i 1929, mitjançant l'estimació d¿un model que combina els elements de tipus Heckscher-Ohlin i els factors apuntats des de la NEG, amb l'objectiu de contrastar la força relativa dels arguments vinculats a aquestes dues interpretacions a l'hora de modular la localització de la indústria a Espanya. L'anàlisi dels resultats obtinguts mostra que tant la dotació de factors com els mecanismes de tipus NEG van ser elements determinants que expliquen la distribució geogràfica de la indústria des del segle XIX, tot i que la seva força relativa va anar variant amb el temps.

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Durant el segle XIX, l'economia espanyola va transitar per les primeres etapes de la industrialització. Aquest procés es va donar en paral·lel a la integració del mercat domèstic de béns i factors, en un moment en què les reformes liberals i la construcció de la xarxa ferroviària, entre d'altres, van generar una important caiguda en els costos detransport. Al mateix temps que es donava aquesta progressiva integració del mercat domèstic espanyol, es van produir canvis significatius en la pauta de localització industrial. D'una banda, hi hagué un augment considerable de la concentració espacial de la indústria des de mitjans de segle XIX i fins a la Guerra Civil, i d¿altra, un increment de l'especialització regional. Ara bé, quines van ser les forces que van generar aquests canvis? Des d¿un punt de vista teòric, el model de Heckscher-Ohlin suggereix que la distribució a l'espai de l¿activitat econòmica ve determinada per l'avantatge comparativa dels territoris en funció de la dotació relativa de factors. Al seu torn, els models de Nova Geografia Econòmica (NEG) mostren l'existència d'una relació en forma de campana entre el procés d'integració econòmica i el grau de concentració geogràfica de l'activitat industrial. Aquest article examina empíricament els determinants de la localització industrial a Espanya entre 1856 i 1929, mitjançant l'estimació d¿un model que combina els elements de tipus Heckscher-Ohlin i els factors apuntats des de la NEG, amb l'objectiu de contrastar la força relativa dels arguments vinculats a aquestes dues interpretacions a l'hora de modular la localització de la indústria a Espanya. L'anàlisi dels resultats obtinguts mostra que tant la dotació de factors com els mecanismes de tipus NEG van ser elements determinants que expliquen la distribució geogràfica de la indústria des del segle XIX, tot i que la seva força relativa va anar variant amb el temps.

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Aim Conservation strategies are in need of predictions that capture spatial community composition and structure. Currently, the methods used to generate these predictions generally focus on deterministic processes and omit important stochastic processes and other unexplained variation in model outputs. Here we test a novel approach of community models that accounts for this variation and determine how well it reproduces observed properties of alpine butterfly communities. Location The western Swiss Alps. Methods We propose a new approach to process probabilistic predictions derived from stacked species distribution models (S-SDMs) in order to predict and assess the uncertainty in the predictions of community properties. We test the utility of our novel approach against a traditional threshold-based approach. We used mountain butterfly communities spanning a large elevation gradient as a case study and evaluated the ability of our approach to model species richness and phylogenetic diversity of communities. Results S-SDMs reproduced the observed decrease in phylogenetic diversity and species richness with elevation, syndromes of environmental filtering. The prediction accuracy of community properties vary along environmental gradient: variability in predictions of species richness was higher at low elevation, while it was lower for phylogenetic diversity. Our approach allowed mapping the variability in species richness and phylogenetic diversity projections. Main conclusion Using our probabilistic approach to process species distribution models outputs to reconstruct communities furnishes an improved picture of the range of possible assemblage realisations under similar environmental conditions given stochastic processes and help inform manager of the uncertainty in the modelling results

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Aim: Climatic niche modelling of species and community distributions implicitly assumes strong and constant climatic determinism across geographic space. This assumption had however never been tested so far. We tested it by assessing how stacked-species distribution models (S-SDMs) perform for predicting plant species assemblages along elevation. Location: Western Swiss Alps. Methods: Using robust presence-absence data, we first assessed the ability of topo-climatic S-SDMs to predict plant assemblages in a study area encompassing a 2800 m wide elevation gradient. We then assessed the relationships among several evaluation metrics and trait-based tests of community assembly rules. Results: The standard errors of individual SDMs decreased significantly towards higher elevations. Overall, the S-SDM overpredicted far more than they underpredicted richness and could not reproduce the humpback curve along elevation. Overprediction was greater at low and mid-range elevations in absolute values but greater at high elevations when standardised by the actual richness. Looking at species composition, the evaluation metrics accounting for both the presence and absence of species (overall prediction success and kappa) or focusing on correctly predicted absences (specificity) increased with increasing elevation, while the metrics focusing on correctly predicted presences (Jaccard index and sensitivity) decreased. The best overall evaluation - as driven by specificity - occurred at high elevation where species assemblages were shown to be under significant environmental filtering of small plants. In contrast, the decreased overall accuracy in the lowlands was associated with functional patterns representing any type of assembly rule (environmental filtering, limiting similarity or null assembly). Main Conclusions: Our study reveals interesting patterns of change in S-SDM errors with changes in assembly rules along elevation. Yet, significant levels of assemblage prediction errors occurred throughout the gradient, calling for further improvement of SDMs, e.g., by adding key environmental filters that act at fine scales and developing approaches to account for variations in the influence of predictors along environmental gradients.

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An important evaporitic sedimentation occurred during the Paleogene (Eocene to lower Oligocene) in the Barberà sector of the southeastern margin of the Tertiary Ebro Basin. This sedimentation took place in shallow lacustrine environments and was controlled by a number of factors: 1) the tectonic structuration of the margin; 2) the high calcium sulphate content in the meteoric waters coming from the marginal reliefs; 3) the semiarid climate; and 4) the development of large alluvial fans along the basin margin, which also conditioned the location of the saline lakes. The evaporites are currently composed of secondary gypsum in surface and anhydrite at depth. There are, however, vestiges of the local presence of sodium sulphates. The evaporite units, with individual thicknesses ranging between 50 and 100 m, are intercalated within various lithostratigraphic formations and exhibit a paleogeographical pattern. The units located closer to the basin margin are characterized by a massive gypsum lithofacies (originally, bioturbated gypsum) bearing chert, and also by meganodular gypsum locally (originally, meganodules of anhydrite) in association with red lutites and clastic intercalations (gypsarenites, sandstones and conglomerates). Chert, which is only linked to the thickest gypsum layers, seems to be an early diagenetic, lacustrine product. Cyclicity in these proximal units indicates the progressive development of lowsalinity, lacustrine bodies on red mud flats. At the top of some cycles, exposure episodes commonly resulted in dissolution, erosion, and the formation of edaphic features. In contrast, the units located in a more distal position with regard to the basin margin are formed by an alternation of banded-nodular gypsum and laminated gypsum layers in association with grey lutites and few clastic intercalations. These distal units formed in saline lakes with a higher ionic concentration. Exposure episodes in these lakes resulted in the formation of synsedimentary anhydrite and sabkha cycles. In some of these units, however, outer rims characterized by a lithofacies association similar to that of the proximal units occur (nodular gypsum, massive gypsum and chert nodules).

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Highway maintenance engineers and administrators are often confronted with a number of problems related to highway maintenance work programs. One of these problems is concerned with determining the optimum number and locations of highway maintenance garages in a given area. Serious decline in highway revenues and a high inflation rate have made it necessary to examine existing maintenance practices and to allocate reduced financial resources more effectively and efficiently. Searching for and providing of reasonable solutions to these problems is the focus of this research project. The methodology used is to identify and modify for use (if necessary) those models which have already been developed. Models which could give optimum number and locations of highway maintenance garages were found to be too theoretical and/or practically infeasible. Consequently, research focus was shifted from these models to other models that could compare alternatives and select the best among these alternatives. Three such models -- the Alabama model, California model, and Louisiana model, were identified and studied.

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Aim To evaluate the effects of using distinct alternative sets of climatic predictor variables on the performance, spatial predictions and future projections of species distribution models (SDMs) for rare plants in an arid environment. . Location Atacama and Peruvian Deserts, South America (18º30'S - 31º30'S, 0 - 3 000 m) Methods We modelled the present and future potential distributions of 13 species of Heliotropium sect. Cochranea, a plant group with a centre of diversity in the Atacama Desert. We developed and applied a sequential procedure, starting from climate monthly variables, to derive six alternative sets of climatic predictor variables. We used them to fit models with eight modelling techniques within an ensemble forecasting framework, and derived climate change projections for each of them. We evaluated the effects of using these alternative sets of predictor variables on performance, spatial predictions and projections of SDMs using Generalised Linear Mixed Models (GLMM). Results The use of distinct sets of climatic predictor variables did not have a significant effect on overall metrics of model performance, but had significant effects on present and future spatial predictions. Main conclusion Using different sets of climatic predictors can yield the same model fits but different spatial predictions of current and future species distributions. This represents a new form of uncertainty in model-based estimates of extinction risk that may need to be better acknowledged and quantified in future SDM studies.

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Aim To assess the geographical transferability of niche-based species distribution models fitted with two modelling techniques. Location Two distinct geographical study areas in Switzerland and Austria, in the subalpine and alpine belts. Methods Generalized linear and generalized additive models (GLM and GAM) with a binomial probability distribution and a logit link were fitted for 54 plant species, based on topoclimatic predictor variables. These models were then evaluated quantitatively and used for spatially explicit predictions within (internal evaluation and prediction) and between (external evaluation and prediction) the two regions. Comparisons of evaluations and spatial predictions between regions and models were conducted in order to test if species and methods meet the criteria of full transferability. By full transferability, we mean that: (1) the internal evaluation of models fitted in region A and B must be similar; (2) a model fitted in region A must at least retain a comparable external evaluation when projected into region B, and vice-versa; and (3) internal and external spatial predictions have to match within both regions. Results The measures of model fit are, on average, 24% higher for GAMs than for GLMs in both regions. However, the differences between internal and external evaluations (AUC coefficient) are also higher for GAMs than for GLMs (a difference of 30% for models fitted in Switzerland and 54% for models fitted in Austria). Transferability, as measured with the AUC evaluation, fails for 68% of the species in Switzerland and 55% in Austria for GLMs (respectively for 67% and 53% of the species for GAMs). For both GAMs and GLMs, the agreement between internal and external predictions is rather weak on average (Kulczynski's coefficient in the range 0.3-0.4), but varies widely among individual species. The dominant pattern is an asymmetrical transferability between the two study regions (a mean decrease of 20% for the AUC coefficient when the models are transferred from Switzerland and 13% when they are transferred from Austria). Main conclusions The large inter-specific variability observed among the 54 study species underlines the need to consider more than a few species to test properly the transferability of species distribution models. The pronounced asymmetry in transferability between the two study regions may be due to peculiarities of these regions, such as differences in the ranges of environmental predictors or the varied impact of land-use history, or to species-specific reasons like differential phenotypic plasticity, existence of ecotypes or varied dependence on biotic interactions that are not properly incorporated into niche-based models. The lower variation between internal and external evaluation of GLMs compared to GAMs further suggests that overfitting may reduce transferability. Overall, a limited geographical transferability calls for caution when projecting niche-based models for assessing the fate of species in future environments.