Identifying Destination Image of Rural Areas: The Case of Brookings, South Dakota

IF 0.6 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE International Journal of Biometrics Pub Date : 2020-06-04 DOI:10.5539/ijbm.v15n7p1
Chinomso Diejomaoh, Xu Li, Hungling Liu
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引用次数: 0

Abstract

A clear understanding of destination image is crucial for developing effective marketing and positioning strategies. The purpose of the study is to examine the images of Brookings perceived by actual tourists. An online questionnaire was developed and sent to email subscribers of the largest local event center. A total of 344 valid responses were received. Overall tourists had positive perceptions of Brookings as a tourism destination. The study identified six Brookings’ image dimensions, including Outdoor Activities and Natural Scenery, Atmosphere, Tourism Infrastructure, Value for Money and Convenience, Historic Attractions, and College Town Style. The social and cultural environment is the most favored element in Brookings. As a college town, Brookings was differentiated from other rural tourism destinations. It is suggested that the city and the university work in partnership to increase visitation both to the campus and the community. To enhance Brookings’ image, destination marketers should focus on the low-rated image items and incorporate them in destination marketing materials.
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确定农村地区的目的地形象:以南达科他州布鲁金斯为例
对目的地形象的清晰理解对于制定有效的营销和定位策略至关重要。这项研究的目的是检验实际游客对布鲁金斯的印象。开发了一份在线问卷,并将其发送给当地最大的活动中心的电子邮件订阅者。我们共收到344份有效回复。总体而言,游客对布鲁金斯作为旅游目的地的看法是积极的。该研究确定了布鲁金斯学会的六个形象维度,包括户外活动和自然景观、氛围、旅游基础设施、物有所值和便利、历史景点和大学城风格。社会文化环境是布鲁金斯最受青睐的因素。作为一个大学城,布鲁金斯区别于其他乡村旅游目的地。建议城市和大学合作,增加校园和社区的访问量。为了提升布鲁金斯的形象,目的地营销人员应该关注低评级的形象项目,并将其纳入目的地营销材料。
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来源期刊
International Journal of Biometrics
International Journal of Biometrics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
1.50
自引率
0.00%
发文量
46
期刊介绍: Biometrics and human biometric characteristics form the basis of research in biological measuring techniques for the purpose of people identification and recognition. IJBM addresses the fundamental areas in computer science that deal with biological measurements. It covers both the theoretical and practical aspects of human identification and verification.
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