Abstract

The effect of crowding is a major concern in outdoor recreation, particularly in wild or back-country areas. But the process by which different numbers of people are experienced and evaluated is complex. How many can enter an area before it becomes crowded, reducing the quality of individual experience? Because resource managers regulate the number of people using certain areas and may turn away potential users, the question has applied as well as theoretical significance. The crowding model commonly used to answer this question comes from an economic tradition. It is essentially a production function relating density and satisfaction in an attempt to maximize aggregate satisfaction (Clawson and Knetsch 1966, pp. 164-75; Fisher and Krutilla 1972; Cicchetti and Smith 1973, 1976; Alldredge 1973). Crowding has also been studied with an implied rather than explicit economic model (LaPage 1963; Lucas 1966; Held, Brickler, and Wilcox 1969; Willard 1971; Boster 1972; Godfrey and Peckfelder 1972; Stankey 1972; McConnell 1977). Besides appealing to many researchers, this model is often the intuitive basis for decisions made by managers. In its simplest form, the economic model contends that there comes a degree of intensity of use . . . where . . . satisfactions from the area or activity decline (Clawson and Knetsch 1966, p. 167). The reasoning (outlined by Alldredge 1973) is that the first visitor to enter a given area experiences uncontaminated solitude. When a second user is added, the enjoyment of each user is reduced, because solitude is no longer absolute. As long as the gain from admitting additional numbers exceeds the loss due to congestion costs, aggregate net benefits will increase. Beyond a point the congestion costs exceed the gains experienced by the additional recreationists and total net benefits diminish .... Optimal capacity is the point at which the total benefit is a maximum and the incremental or marginal benefit is zero (Fisher and Krutilla 1972, p. 425). McConnell's empirical study (1977) of Rhode Island beaches comes closest to this two-variable approach. Density was measured by counting people per acre on a given beach, and satisfaction was measured as individual willingness to pay. Combining the data for six beaches and controlling the effects of air temperature, income, and number of previous visits, McConnell found a significant negative effect due to density. The simple two-variable approach has

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