Using decision trees to identify tourism stakeholders

Purpose – The purpose of this paper is to investigate the use of decision tree analysis in the identification of stakeholders based on their participation in tourism and political activities in a community. Design/methodology/approach – A survey was sent to tourism stakeholders in two rural counties. Responses were collected and analyzed using the exhaustive chi‐square automatic interaction detection decision tree analysis. Findings – Based on the results of the decision tree analysis four tourism stakeholder groups were identified based on their participation in tourism and political activities in a community: high participants, high‐moderate participants, low‐moderate participants, and low participants. Research limitations/implications – Owing to a low response rate, an issue of non‐response bias could exist, but the information from the respondents can give insight on stakeholders in these communities. Also, the specific results of this study can only be applied to eastern North Carolina and are not generalizable to other areas. Practical implications – Results from this study demonstrate the use of decision tree analysis in identifying community stakeholders. Using decision tree analysis tourism planners can identify stakeholder groups that will participate in tourism and political activities. With this knowledge, tourism planners can identify which stakeholder groups will be the most influential and vocal in a community with regard to tourism development. Originality/value – Decision tree analysis is a tool for partitioning a data set based on the relationships between a set of independent variables and a dependent variable. The research reported here tests the application of decision tree analysis, an analytical technique that is not traditionally used to segment stakeholders in tourism.