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Modeling hunters preferences using discrete choice experiments

Muhammad I Khan, University of Nebraska - Lincoln


Careful utilization of natural resources to meet human demands is the pivotal concern of the evolving discipline of “human dimensions of natural resources”. In the USA, government agencies such as the Nebraska Game and Parks Commission (NGPC) regularly offer state-wide programs to manage wildlife, such as controlling the abundance of deer species through licensed hunting. Hunting is an outdoor activity for all kinds of citizens, and generates revenue to support management of game species. Agencies often conduct surveys to better understand stakeholders’ perceptions for planning better management strategies. An online survey included a discrete choice experiment (DCE) was planned to elicit hunters’ preferences who hunt in Nebraska on publicly accessible land for hunting. The current research describes the design and analysis of the DCE portion of the survey. Discrete choice experiments (DCEs) are based on random utility theory. In DCEs, distinct choice sets, each with at least two alternatives, were constructed. Every alternative is based on some combination of attributes, where each attribute is measured and/or observed with different levels. A group of choice sets is offered to every respondent to choose the alternative which he/she likes the most. This multivariable approach better describes tradeoffs between attributes than uni-dimensional approaches such as nominal and/or Likert-scale questions. Two approaches for designing discrete choice experiments, Yong Method (2-Level design) and Street-and-Burgess Method (3-Level design), were compared. Further, three commonly used analysis approaches for analyzing the discrete choice data are briefly reviewed. These are Multinomial Logit Models (MNL), Mixed Logit Models (MXL), and Latent Class Models (LCM). DCEs generated from the 2 and 3 level designs were analyzed with each of MNL, MXL and LCM. Design and analysis methods of DCEs suggest that careful consideration of both is necessary to effectively address the research objectives.

Subject Area

Wildlife Management|Statistics|Natural Resource Management

Recommended Citation

Khan, Muhammad I, "Modeling hunters preferences using discrete choice experiments" (2016). ETD collection for University of Nebraska-Lincoln. AAI3745411.