Predicting determinant factors and development strategy for tourist villages

IF 1.4 Q3 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
N. Ariyani, A. Fauzi, Farhat Umar
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引用次数: 3

Abstract

Tourist village program is one development priority program for rural development. Despite numerous opportunities to develop tourist villages such as the availability of natural resources and high demand for tourist villages recently, some challenges are still faced to develop tourist villages, especially in a developing country such as Indonesia. Governance problems, infrastructure, and effective partnership are among other factors that remain challenging in developing tourist villages. This study attempts to identify factors that determine the state of tourist villages in Indonesia and determine the appropriate strategies for better tourist village development. Using the case of tourist villages in Kedung Ombo, Central Java, a water based attractive tourist village, this study uses both machine learning and multicriteria approaches by means of Promethee in order to address the objective of the study. This study shows that government support, application of information technology, infrastructure, local participation, partnership, and attractive variations, are among the determinant factors that affect tourist village development. The study also reveals that the appropriate strategies for tourist village development include, improving infrastructure, institutional strengthening, and capacity building. This study could be used to assist local national as well as sub-national governments to effectively manage tourist villages in Indonesia.
旅游村的决定因素预测与发展策略
旅游村计划是农村发展的重点项目之一。尽管有许多发展旅游村的机会,如自然资源的可用性和最近对旅游村的高需求,但发展旅游村仍然面临一些挑战,特别是在印度尼西亚这样的发展中国家。治理问题、基础设施和有效的伙伴关系是发展旅游村仍然具有挑战性的其他因素之一。本研究试图找出决定印尼旅游村状态的因素,并确定更好的旅游村发展的适当策略。本研究以中爪哇Kedung Ombo的旅游村为例,该旅游村是一个基于水的有吸引力的旅游村,本研究通过Promethee方法使用机器学习和多标准方法来解决研究的目标。研究表明,政府支持、信息技术应用、基础设施、地方参与、伙伴关系和吸引力变化是影响旅游村发展的决定因素。研究还表明,旅游村发展的适当策略包括改善基础设施、加强制度建设和能力建设。本研究可用于协助印尼地方国家及地方政府有效管理旅游村。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Decision Science Letters
Decision Science Letters Decision Sciences-Decision Sciences (all)
CiteScore
3.40
自引率
5.30%
发文量
49
审稿时长
20 weeks
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