Clustering Neural Network Analysis of Recreational Fisheries Management Strategies
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Asian Institute of Research, Journal Publication, Journal Academics, Education Journal, Asian Institute
Asian Institute of Research, Journal Publication, Journal Academics, Education Journal, Asian Institute

Economics and Business

Quarterly Reviews

ISSN 2775-9237 (Online)

asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, managemet journal
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doi
open access

Published: 19 November 2019

Clustering Neural Network Analysis of Recreational Fisheries Management Strategies

Yeong Nain Chi

University of Maryland Eastern Shore, USA

asian institute research, jeb, journal of economics and business, economics journal, accunting journal, business journal, management journal

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doi

10.31014/aior.1992.02.04.164

Pages: 1238-1257

Keywords: Saltwater, Recreational Anglers, Preferences, Recreational Fisheries Management Strategies, Factor Analysis, Cluster Analysis, Discriminant Analysis, Multilayer Perceptron, Neural Network

Abstract

This study utilized data extracted from the 2013 National Saltwater Angler Survey to understand saltwater recreational anglers’ preferences toward recreational fisheries management strategies, to identify groups exhibiting common patterns of responses, and to examine the association between socio-demographic characteristics and the groups identified. Saltwater recreational anglers’ preferences toward recreational fisheries management strategies were examined through factor analysis which identified four reliable factors. Cluster analysis was employed to identify three prominent recreational angler groups. Statistical tests were employed to investigate the association between socio-demographic characteristics, including age, gender, income level, educational level, region of the respondent, and the identified recreational angler groups. The multilayer perceptron neural network model was utilized as a predictive model in deciding recreational anglers’ preferences toward recreational fishing management strategies. From an architectural perspective, it showed a 15-7-3 neural network construction. The results also revealed that fisheries habitat development and bag limit consideration were the greatest effect on how the recreational anglers’ preferences in terms of recreational fisheries management strategies. Results of this study may provide insight regarding the preferences toward recreational fisheries management strategies from saltwater recreational anglers as an indicator of potential participation and behavior of saltwater recreational fisheries management.

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