Academic journal article Journal of Leisure Research

Recreation Demand and the Influence of Site Preference Variables

Academic journal article Journal of Leisure Research

Recreation Demand and the Influence of Site Preference Variables

Article excerpt

Introduction

Recent advances in recreation modeling are motivated by the need to examine how changes in site quality affect outdoor participation (Bockstael, Hanemann, & Kling, 1987). In contrast, leisure researchers with their conceptions of how participants make choices about activities and site trips require insight into participant choice behaviors when specifying site demand (Ditton, Loomis, & Choi, 1992; Williams, 1984).

Our research is motivated by the fact that published discrete-count models of recreation demand fail to adequately identify and integrate individual preferences, like the importance of site characteristics, that shape trip choices. Using recent theoretical advances in the specification of discretecount models, we speculate that the inclusion of data regarding the perceived importance of site attributes to participants should improve a choice model's predictive power (Adamowicz, 1994). Clark and Downing (1984), for example, believe that explanatory variables like the importance of site attributes to a participant might influence the marginal choice of a recreation site in a particular geographical area.

We begin with a recent review of recreation demand theory, which leads us to specify a discrete-count model for lake boating trips. We then report on the benefits gained from specifying a nested logit model to explain lake choices. We end with a discussion on the implications of the discrete-count method in estimating outdoor recreation demand.

Related Research

Recent articles advance competing theories of recreation demand that allow analysts to link independent discrete site choices to the aggregate demand for seasonal trip-counts (Hausman, Leonard, & McFadden, 1995; Feather, Hellerstein, & Tomasi, 1995; and Parsons & Kealy, 1995). The main purpose of the advances is to explain users' recreation behaviors when faced with environmental threats to site quality. The demand theories, although different in their hypotheses about individual decision processes, support discrete-count empirical applications. Specifically, each theory differs with respect to a trip-price index that links the allocations of trips among substitute sites (discrete choices) to the seasonal aggregate demand for the seasonal counts of trips. It must be emphasized that the estimation of a discretecount demand model cannot be completed in a single statistical process. Rather, discrete choice and the trip-count models are two different types of travel cost models described in previous JLR literature reviews (e.g., Fletcher, Adamowicz, & Tomasi, 1990). Trip-counts refer to the quantity of seasonal trips by individuals, with the analysis of trip-counts following a count-data or Poisson distribution.

Feather et al. (1995) follow a household production function where recreation opportunities are produced and consumed by a household, constrained by such scarce resources as the amounts of leisure time, money, and effort. Unknown to the analyst, and therefore to be estimated, are the proportions of scarce resources that are necessary to produce a recreation trip and a participant's expectation of site quality. Feather and colleagues suggest multiplying a participant's probability of visiting regional recreation sites by the travel costs and the measures of site quality to compute an expected cost, expected time, and expected quality per trip. Substituting the computed values into a participant's budget and time constraints results in a single, expected full-income constraint. Maximizing the recreation utility function for site trips, subject to the expected full-income constraint, yields the ordinary recreation demand function for seasonal trips.

Hausman et al. (1995) propose a budgeting model to support their trip demand theory. They view the participant first as budgeting a number of seasonal trips and second as allocating trips across substitute sites. The solution to the household budgeting problem is a Gorman generalized polar form that includes the prices faced by participants in travelling to and from recreation sites. …

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