Competing Destinations Model Research Articles

Retail location modeling of supermarket chains in Taipei city

This study collected the annual revenue data of the top three supermarket chains in Taiwan (PX Mart, Simple Mart, and Wellcome), shopping frequency in supermarkets, and the average expenditure of the general public in order to construct models for simulating supermarket revenue by calibrating model parameters to the actual data. This study employed the competing destinations model (CDM) to designate supermarket shoppers' shopping areas and simulate supermarket sales. The CDM calculated the probability of consumers selecting each supermarket, simulated the total revenues of supermarkets and the average daily revenue of a single store using the expenditure equation, and added spatial competition and agglomeration effect parameters to the model to observe variations in revenue with changing parameter values. The study results revealed profitable expansion opportunities and highly competitive locations not advised for new outlets. Beitou district had the lowest population density in Taipei City yet a high-sales cluster, making it an area suitable for new PX Mart stores. Shilin and Xinyi districts could also be considered suitable areas for new stores because they had insignificant distributions of stores, high-sales clusters, and competition was not yet severe. The study extends the use of analytical revenue and spatial models to empirically study the agglomeration forces between supermarket chains, analyzes the influence of distance variation on supermarket revenues, and determines the most suitable locations for the future inauguration of supermarket stores in Taipei City.

International student mobility: onset for a future career or an experiential opportunity?

ABSTRACT International student mobility (ISM) has emerged as an important field of study that various nations and organizations have been attaching great importance to. This paper studies the drivers of international student mobility, using a competing destinations model for the international student flows among 35 OECD countries in the period 2004–2018, by integrating the motivations for ISM. We find that OECD students are motivated by both career orientation and personal and cultural experience when decide to move abroad for study. Nonetheless, remarkable differences emerge when considering country subgroups (origin countries, wealthier, English-speaking top destination (namely US, the UK, Canada, and Australia), and European countries, students search for personal and cultural experience, valuing the lifestyle of the destination country. Students seeking for education quality are instead polarised in the rest of the OECD countries.

Universities’ attractiveness to students: The Darwinism effect

AbstractDue to significant government cuts to Higher Education funding in Southern European systems, their already underfunded universities were forced to increasingly compete for students as sources of additional revenue. Concurrently, families and students that continued to afford participation in Higher Education became more selective when choosing a university, realising the riskier investment that Higher Education participation had become. Through a competing destinations model and relying on all Italian private and public universities, this study finds that the competition forces characterising universities’ attractiveness over the last decade have changed since the financial crisis of 2008. In a context of lower demand for Higher Education, the competition for students grew and universities in close proximity were better prepared to face the new challenges, leading to the growth of Higher Education clusters.

University spatial competition for students: the Italian case

ABSTRACTUniversity spatial competition for students: the Italian case. Regional Studies. The ability to attract students has become crucial for the sustainability of universities, especially in Southern Europe, where the decrease of governmental funding has been dramatic following the financial crisis. By using a competing destinations model on the student flows to 75 Italian universities in the period 2003–12, and modelling university competition with respect to different market segmentations, the paper provides evidence that Italian universities operated under competition forces in the last decade. Results hold when controlling for universities’ educational offer, trying different definitions of university attractiveness, excluding private academic institutions and limiting the analysis to non-selective courses.

Enhanced Destination Choice Models Incorporating Agglomeration Related to Trip Chaining While Controlling for Spatial Competition

It is common knowledge that travelers often choose clusters or groups of nearby destinations that can be visited conveniently in a single tour. This propensity is becoming increasingly important in the context of rising fuel costs. However, gravity models, as well as most destination choice models, ignore these agglomeration effects and treat each trip or destination choice as independent. Some models have captured economies of agglomeration related to trip chaining through the use of accessibility variables. Accessibility variables, however, generally do not identify trip chaining effects uniquely, but measure differential spatial competition that arises because nearby destinations are generally better substitutes than distant ones. Because spatial competition effects generally dominate trip chaining agglomeration effects, models with a single accessibility variable have been called competing destinations models following Fotheringham. This paper presents an advance on Fotheringham's approach by introducing two distinct accessibility variables to represent agglomeration and spatial competition among destinations separately rather than their net effect. These new agglomerating and competing destination choice models were applied in Knoxville, Tennessee. The new models, which outperformed both gravity and competing destinations models, began to present a new alternative to activity-based models by allowing the incorporation of some of the most important trip chaining effects in trip-based travel demand models. For example, a sensitivity test showed that a new factory employing 1,000 workers would attract 125 new nonwork trips to the surrounding area on an average day as a result of stops on the way to and from work.

Laboratory Testing of Spurious Spatial Structure in Trip Distribution Models

In this paper we examine the risk of reporting spurious relationships in trip distribution models. We show how to make synthetic data sets that (by construction) are neutral with respect to clustering effects. We study a particular case with two non-interacting groups of jobs/workers. A competing destinations model is applied to 100 randomly drawn data sets of this type. Quite disturbingly, the loglikelihood ratio test reported a significant clustering effect in all of these data sets. This shows that statistical tests based on likelihood values may not be the right tool to examine the effect of such model extensions.

MODELING MULTIPLE SOURCES OF HETEROGENEITY IN MODE CHOICE MODEL

This paper is to compare the difference of heterogeneous effect caused by multiple sources, including unobserved heterogeneity in alternatives, taste variation, and heterogeneous choice sets. We construct several heterogeneous discrete choice models to conduct with various heterogeneities. A stated preference data of intercity travel choice is used as empirical case. The empirical results show that the mixed logit model conducting with taste variation has better explanatory power in single heterogeneity and heterogeneous competing destinations model integrating multiple heterogeneities has the best explanatory power. If we ignore heterogeneity in constructing discrete choice models, the estimation of value of time will be biased. Sensitivity analysis presents that expensive alternatives, like air mode, should adopt cut-price strategy to increase choice share and inexpensive alternatives, like bus and train mode, should improve the level of service in travel time to increase choice share.

Sectoral Shifts and Occupational Migration in the United States

This research is grounded in notions of differential economic restructuring across employment sectors and geographic space, as well as migration selectivity by occupation. A series of unconstrained competing-destinations models were employed to analyze the response by workers in thirteen occupational categories to sectoral employment change, average wages, and distance. As was hypothesized, workers in occupations that require high levels of education and skills are more responsive, in terms of migration, to economic opportunities in alternative labor-market areas. However, the results do not support the hypothesis that highly educated and skilled workers migrate longer distances. Further investigation suggests that opportunities for highly educated and skilled workers may be clustering in relatively few areas that are in relatively close proximity.

An empirical test of the competing destinations model

It has long been believed that properties of spatial structure have a strong effect on trip distribution, which thus leads to a bias in the estimated distance decay parameters of spatial interaction models. This paper is an attempt to identify to what extent the spatial structure effect affects the trip distribution and determine whether the incorporation of a term to account for the relative location of destinations into the conventional gravity models, results in a model that can more correctly represent the actual trip distribution. The main focus is on the comparison of the origin–specific estimates of the distance decay parameter, calibrated from the traditional production-constrained model and the production-constrained competing destinations model. The results show that the competing destinations model is superior to the conventional model in both reproducing the interaction flows and giving behavioral explanation to the distance decay parameters, but the essential aim of the competing destinations model to remove the map pattern from the distance decay parameters of the conventional model has not been identified.

Modelling spatial choice: a review and synthesis in a migration context

This paper reviews various approaches to the modelling of spatial choice. Spatial choice modelling is viewed as a distinct area of research, within the larger field of discrete choice modelling, with a sound methodological basis and computationally tractable modelling framework. This review draws upon empirical application of spatial choice models to interregional migration and identifies the main research issues, summarizes the progress of research thus far, and suggests some paths for future research. It is argued that some of the widely used models suffer from problems derived from their development in aspatial choice contexts. Acknowledging the increased complexity and, possibly, the different choice process that spatial choice situations present over their aspatial counterparts leads to the development of the socalled competing destinations model and its variants. Evidence from empirical tests of these spatial choice models suggests that analysts engaged in interregional migration modelling risk model misspecification if they ignore the peculiarities of spatial choice.

A Competing Destinations Approach to Modeling Commuting Flows: A Theoretical Interpretation and An Empirical Application of the Model

We introduce a modified version of the competing destinations model as a framework to estimate how discontinuities in the road network affect commuting flows. An economic interpretation of the model is presented in terms of random utility theory and hierarchical destination choice. Based on data from western Norway, we estimate a set of parameters which are assigned to different aspects of spatial structure in a region where the road network is disconnected owing to numerous topographical barriers. The model is applied to predict how commuting flows in the region are influenced by transportation innovations where ferry connections are subtituted by tunnels and bridges.

An Analysis of Inter-Municipal Migration Flows in Japan Using GIS and Spatial Interaction Modeling

The purpose of this paper is to carefully examine the spatial pattern of human migration during the second half of the 1980s, by using geographical information system (GIS) and spatial interaction models (SIMs). It should be noted that this paper is based on the full data set of the inter-municipal migration extracted from the 1990 population census of Japan. This paper firstly uses GIS to provide the features of the Japanese migration system based on municipality units. As a result, the two major migration patterns in the late 1980s are observed; influx of population to the Keihin metropolitan area from non-metropolitan areas, and to prefectural capital cities from other cities of the same prefecture. Next, Fotheringham's competing destinations models are also applied to the inter-municipal migration flows. It is found that the spatial distribution of accessibility parameter estimates has a significantly contrastive pattern: the estimates of the origins in the non-metropolitan areas are positive and show the agglomeration effect in migration process, while the ones in the metropolitan areas are negative and show the competing effect. These results suggest that accessibility parameter estimates reflect not only the spatial configuration of origins and destinations, but also the preference of migrants for the large metropolitan areas reflecting the Japanese core-periphery structure and the business cycle in the boom period of the late 1980s.

Intermetropolitan Migration and Hierarchical Destination Choice: A Disaggregate Analysis from the US Public Use Microdata Samples

In this paper the authors describe the application of spatial choice models to microlevel intermetropolitan migration destination choice data from the US Public Use Microdata Samples (PUMS) for the period 1985–90. The metropolitan and the microlevel data facilitate an analysis incorporating well-defined geographic units and their respective attributes, as well as an analysis disaggregated by the personal factors of migrants. The PUMS files provide one of the richest sources of national-level migration micro data in terms of geographic resolution, the number of individual or household characteristics recorded, sample size, and availability. The focus of the modelling exercise is to examine the performance of competing-destinations migration models which are based on the assumption that migrants process spatial information hierarchically. To date the only empirical testing of such models has been undertaken with aggregate spatial flow data, so the PUMS data provide a unique opportunity to examine the behaviour of the competing destinations framework in more detail. The authors provide information on the determinants of intermetropolitan migration within the USA and on the validity of the theoretical foundations of the competing-destinations framework. Traditional spatial choice models are shown to be severely misspecified and the distance-decay parameter estimates from such models to be potentially biased in such a manner that they exhibit the well-known ‘spatial structure’ effect. This effect does not appear when the parameters are estimated from competing-destinations models.

Competing destinations and intervening opportunities interaction models of inter-city telecommunication flows

This research makes use of a large sample (600,000) of individual telephone calls between local exchanges (cities, villages) within a U.S. region. Callers and callees are identified by their 4-digit SIC (Standard Industrial Classification) code. The intersectoral and interlocational flows (number of messages and conversation minutes) are aggregated into major economic sectors (Agriculture, Manufacturing, Retail Trade ...., and Households), and are analyzed by estimating, in a simultaneous equation framework, spatial interaction models that account for (1) the role of the spatial structure, which reflects the competition and agglomeration effects that take place among the flow destinations, and (2) the role of the reverse flows, which reflect the process of information creation necessary to complete intersectoral economic transactions. A particular focus is set on Fotheringham's competing destinations model and Stoufer's intervening opportunities model, while accounting for the effects of place hierarchy. A theoretical framework is presented, to guide the interpretation of the empirical results and their policy implications regarding the impacts of telecommunications deregulation, transportation and telecommunications interactions, and the role of information technologies in fostering the development of rural and peripheral areas.

Competing destinations and intervening opportunities interaction models of inter‐city telecommunication flows

Abstract. This research makes use of a large sample of individual telephone calls between local exchanges (cities, towns, villages) within a U.S. region. The interlocational flows, measured in conversation seconds, are analyzed by estimating, in a simultaneous equation framework, spatial interaction models that account for (1) the role of the spatial structure, which reflects the competition and agglomeration effects that take place among the flow destinations, and (2) the role of the reverse flows, which reflect the process of information creation necessary to complete economic and social transactions. A particular focus is set on Fotheringham's competing destinations model and Stouffer's intervening opportunities model. The implications of the results are discussed and areas for further research are outlined.

MODELING SPATIAL STRUCTURES THROUGH EQUILIBRIUM STATES FOR TRANSITION MATRICES*

ABSTRACT. In this paper we present a model for spatial interaction within a network of towns. This interaction is modeled through equilibrium states for certain Markov chains where, in particular, explicit formulas for these states are given. Our model exploits and intertwines ideas from gravity models, the competing destinations model and the intervening opportunities model. The central idea in the paper is to capture the effect of spatial structure in a framework where interaction is determined by the global network configuration.

Destination Interdependence and the Competing-Destinations Model

There are two types of destination interdependence; one arises because of people's preferences towards destination activities, and the other because of the locational arrangement of space. Destination interdependence affects spatial behaviour. In a previous paper it was shown that the conventional gravity model can handle neither aspect of destination interdependence. In this paper it is shown that the competing-destinations model, as a reformulated gravity prototype, is at best able to describe only locational structure effects.

Spatial Flows and Competing Central Places: Towards a General Theory of Hierarchical Interaction

This paper presents a variation of Fotheringham's competing destinations model using categorized information on spatial flows in a central place system. A competing central place model is developed using spatially defined choice sets for origin — destination pairs by threshold distance and central place order. The competing central place generalization is empirically tested by undertaking a comparative analysis of 1980 domestic airline passenger traffic amongst selected cities in the continental United States. A host of modeling strategies are contrasted and the effects of mass, separation, and competitive forces noted in the presence or absence of hierarchical data. The production-constrained competing central place specification is shown to exhibit not only greater explanatory power than Fotheringham's competing destinations model, but also significant reductions in potential multicollinear relations between regressors. The model is later extended to incorporate an intervening opportunities filter. Competitive flow patterns between paired origins and destinations are then delimited by geographic range, compatibility, and the impeding effects of substitute and/or intervening flows within a hierarchical network.

Note—Consumer Store Choice and Choice Set Definition

Consumer store choice results from a process whereby information on various alternatives is evaluated by the consumer prior to the selection of one of these alternatives. In the application of store choice models it is often assumed that the information-processing strategy underlying store choice is a simultaneous one in which all possible alternatives are evaluated by an individual. A competing assumption, increasingly recognized in aspatial choice, is that individuals initially evaluate clusters of alternatives and then only evaluate alternatives within a chosen cluster. The nested logit model is a well-known formulation for capturing this type of choice process. This paper adds to the above understanding of consumer spatial choice in the following ways: (i) It describes an alternative to the nested logit model, known as a competing destinations model, which can be used to model hierarchical spatial choice processes. While this model has been described previously in the geography and planning literature, this paper contains a novel derivation of it from within the random utility maximization framework. (ii) A general choice formulation is derived from which the logit, nested logit, and competing destinations models can be obtained. This allows the behavioral assumptions embedded in each model to be seen clearly and it allows a comparison of the nested logit and competing destinations formulations. The latter is shown to be preferable in most spatial choice situations. In particular, the latter can be used when restricted choice sets are fuzzy. (iii) The errors that arise when spatial choice results from a hierarchical process and when a simultaneous choice structure is assumed are demonstrated and are related to the presence of consumer competition/agglomeration effects between stores which are thought to be important in store choice.

Hierarchical interaction: The modeling of a competing central place system

This paper presents a comparative analysis of alternative specifications of the competing destinations model. The competing central place extension is shown to be a model that is sensitive to the spatial and structural intricacies of hierarchical interaction. It is stressed that choice of estimation procedure is as important as model specification, where significance of extracted parameter estimates are subject to spatial autocorrelative transformations. An interactional simulation exercise is performed to expose conceptual and methodological differences in parameter estimates using ordinary least squares (OLS), estimated generalized least squares (EGLS), seemingly unrelated group regression (SUR), and a spatially adjusted version of the seemingly unrelated regression system (SASUR). The combination of a competing central place or weighted destinations model and SASUR is shown to exhibit some interesting results in the estimation of a simulated flow pattern. The competing central place variation of the competing destinations model is proposed as a generalization which recognizes the hierarchical components of flow patterns.