6 resultados para Recreation areas.

em Dalarna University College Electronic Archive


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This paper is concerned with the use of the choice experiment method for modeling the demand for snowmobiling . The Choice Experiment includes five attributes, standard, composition, length, price day card and experience along trail. The paper estimates the snowmobile owners’ preferences and the most preferred attributes, including their will-ingness to pay for a daytrip on groomed snowmobile trail. The data consists of the an-swers from 479 registered snowmobile owners, who answered two hypothetical choice questions each. Estimating using the multinominal logit model, it is found that snow-mobilers on average are willing to pay 22.5 SEK for one day of snowmobiling on a trail with quality described as skidded every 14th day. Furthermore, it is found that the WTP increases with the quality of trail grooming. The result of this paper can be used as a yardstick for snowmobile clubs wanting to develop their trail net worth, organizations and companies developing snowmobiling as a recreational activities and marketers in-terested in marketing snowmobiling as recreational activities.

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Mountainous areas with a high dependency on its tourism industry are often relatively small and remote. But some of these areas have faced a population increase due to large in-migration;Wanaka in New Zealand’s Southern Alps is one example. This paper is studying the migration motivations of a few individuals that have moved to Wanaka and how they started to feel like part of their new community. The meaning of the place is important for these newcomers. The results of the study indicate that there is a strong link between the community and the lifestyle that in-migrants are seeking. It also highlights the importance for in-migrants to be a part of the social community. Social Clubs, sport clubs and voluntary work are ways of becoming a part of a social network.

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Location Models are usedfor planning the location of multiple service centers in order to serve a geographicallydistributed population. A cornerstone of such models is the measure of distancebetween the service center and a set of demand points, viz, the location of thepopulation (customers, pupils, patients and so on). Theoretical as well asempirical evidence support the current practice of using the Euclidian distancein metropolitan areas. In this paper, we argue and provide empirical evidencethat such a measure is misleading once the Location Models are applied to ruralareas with heterogeneous transport networks. This paper stems from the problemof finding an optimal allocation of a pre-specified number of hospitals in alarge Swedish region with a low population density. We conclude that the Euclidianand the network distances based on a homogenous network (equal travel costs inthe whole network) give approximately the same optimums. However networkdistances calculated from a heterogeneous network (different travel costs indifferent parts of the network) give widely different optimums when the numberof hospitals increases.  In terms ofaccessibility we find that the recent closure of hospitals and the in-optimallocation of the remaining ones has increased the average travel distance by 75%for the population. Finally, aggregation the population misplaces the hospitalsby on average 10 km.

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The p-median model is used to locate P facilities to serve a geographically distributed population. Conventionally, it is assumed that the population patronize the nearest facility and that the distance between the resident and the facility may be measured by the Euclidean distance. Carling, Han, and Håkansson (2012) compared two network distances with the Euclidean in a rural region witha sparse, heterogeneous network and a non-symmetric distribution of thepopulation. For a coarse network and P small, they found, in contrast to the literature, the Euclidean distance to be problematic. In this paper we extend their work by use of a refined network and study systematically the case when P is of varying size (2-100 facilities). We find that the network distance give as gooda solution as the travel-time network. The Euclidean distance gives solutions some 2-7 per cent worse than the network distances, and the solutions deteriorate with increasing P. Our conclusions extend to intra-urban location problems.

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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. Distance measure can vary if the accuracy of the road network varies. The rst 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 nd 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 dierent algorithms for large p-median problem. The investigation is conducted by the means of a case study in a rural region with an 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 optimized for. It is also shown that the simulated annealing algorithm not just is much faster than the classic heuristic used here, but also in most cases gives better location solutions.