The Factors Affecting Place Branding based on Data Mining Approach (Case Study: Instagram Social Media)

Document Type : Research Paper

Authors

1 , Assistant Prof, Department of Management, Faculty of Management and Economic, Shahid Bahonar University of Kerman, Kerman, Iran.

2 MSc. Student, Department of Business Management, Faculty of Management and Economic, Shahid Bahonar University of Kerman, Kerman, Iran.

3 Associate Prof., Department of Computer Engieering, Faculty of Computer Engieering, Shahid Bahonar University of Kerman, Kerman, Iran.

Abstract

Objective
The introduction of facilities, capabilities, attractions, and various tourism conveniences of the country is regarded as a crucial measure in the development of tourism industry in Iran. It is also recommended to persuade, encourage, and convince domestic and foreign audiences to visit these attractions. Hence, the use of the Internet, as a primary source of tourist destination information, is growing increasingly. Investigating the factors affecting place branding in social networks (tourism) can have a significant impact on the exchange of information and experiences about traveling to different regions and tourists' intention to choose Iran as a tourism destination. This will help formulate appropriate strategies to create a promising mental image for the tourists. As a result, it can lead to a greater number of tourists to Iran, job creation, and destination development. This research aims to answer the following question: What factors affect the branding of places in the social network Instagram?
 
Methodology
The present quantitative study is exploratory in nature because it intends to find the factors affecting place branding in the Instagram. In this study, the Instagram pages of three domestic tourism destinations and four foreign tourism destinations were examined. Then, 912 Instagram posts were examined on these target pages during in a one-year span. Data analysis and data mining were performed using IBM SPSS Modeler software using the two methods of linear support vector machine and neural network.
 
Findings
Several effective factors were considered as inputs, such as post type, post content, caption type, caption language, the number of tags, number of hashtags, hashtag language, and the date of the post. Besides, the following factors were considered as outputs: the number of likes and comments (indicating the level of brand awareness, which means the main factor in the development of the place brand). It was found that the higher number of likes and comments is associated with the greater place brand awareness and more prevalence of the city's tourism brand.
 
Conclusion
The subject of the research, which has a comparative approach in the study of international, Middle East, and domestic levels; and the aim of the research was to compare the famous international tourism Instagram pages (London and Paris), in the Middle East (Dubai and Turkey)and also the domestic pages. It was concluded that the posts that were shared in September, July, March, and May have received more likes and greater brand awareness on domestic Instagram pages (Isfahan, Kerman, Tehran). Moreover, sharing posts in December, January, and July will trigger more comments on Instagram. In addition, it can be said that using appropriate captions for the places and events, emotional captions, and question-form captions have only led to receiving more likes and brand awareness. Furthermore, sharing different images of cultural attractions, urban attractions, entertainments, as well as restaurants and coffee shops cause more likes and comments and may increase brand awareness. In addition, sharing posts on Sundays, Mondays, and Wednesdays will cause more likes and increase brand awareness. Finally, sharing a post as a photo leads to more comments and thus increases brand awareness.

Keywords

References

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Journal of Business Management
Volume 13, Issue 2
2021
Pages 473-501

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