Activity Substitutability and Degree of Specialization Among Deer and Elk Hunters in Multiple States

Abstract

This article examines relationships between hunter specialization and activity substitutability. Data were obtained from a mail survey of 6,983 deer hunters in eight states and 2,584 elk hunters in three states. Activity substitutability was measured by asking what activity would provide the same satisfaction as deer or elk hunting. Between 41% and 59% of deer hunters and 38% to 46% of elk hunters reported substitutes such as fishing and other big game hunting. Cluster analyses of hunter skill, centrality, equipment, and experience revealed four specialization groups (casual, intermediate, focused, and veteran). Casual hunters were most likely to report a substitute followed by intermediates, focused, and veterans. This inverse relationship between concepts was consistent across states and species hunted. Veteran hunters were most likely to report other big game hunting as a substitute, whereas casual hunters in many states were most likely to consider fishing as a substitute.

Keywords:

• hunting
• recreation specialization
• substitutability
• wildlife

Acknowledgments

This article is based on a project of the Human Dimensions Committee of the Western Association of Fish and Wildlife Agencies. Committee members and agency representatives are thanked for their support. Earlier versions were presented at the National Recreation and Park Association Leisure Research Symposium in Seattle, Washington in October 2006, and the Northeastern Recreation Research Symposium in Bolton Landing, New York in April 2011. Two anonymous reviewers and the editors are thanked for their comments.

Notes

Mail questionnaires were pretested with other deer/elk hunters in each state (n = 659). Details are provided in Needham, Vaske, and Manfredo (2004).

Weights calculated using: Weight = Population%/Sample%, where (Population% = number of hunters in stratum/number of hunters in state) and (Sample% = number of respondents in stratum/number of respondents in state). To represent all Arizona deer hunters combined, for example, the weight for Arizona resident deer hunters was 2.05 (32,502 deer hunters in stratum/33,581 deer hunters in state) / (396 respondents in stratum/840 respondents in state) and for nonresident deer hunters it was 0.06 (1,079 deer hunters in stratum/33,581 deer hunters in state) / (444 respondents in stratum/840 respondents in state).

Ancillary analyses tested single factor models (all 11 variables forced to load on one factor). These models did not withstand criteria for reasonable fitting models (NFI*, NNFI*, IFI*, CFI* ≤ .79; RMSEA* ≥.14), suggesting that traditional single item or summative approaches for measuring specialization may be inappropriate.

FIGURE 1 Second-order CFAs of four-dimensional measurement model of hunter specialization. First path loadings/coefficients represent range from lowest to highest among all 11 strata (e.g., .83–.88). Second path loadings/coefficients represent average across all strata (e.g., [.86]). All loadings/coefficients are standardized and statistically significant at p < .001 across all strata. Model estimation based on Satorra-Bentler robust estimation for multivariate non-normality. Model fit indices: S-B χ²(42) = 198.30 to 347.32 (average = 251.30), all p < .001, NFI* = .91 to .94 (average = .92), NNFI* = .90 to .93 (average = .91), IFI* = .91 to .95 (average = .94), CFI* = .92 to .95 (average = .94), RMSEA* = .07 to .09 (average = .08). See Table 4 for variables corresponding to codes (e.g., V₁).