- E-ISSN2233-5382
- KCI
E-ISSN : 2233-5382
Strategies for the Development of Watermelon Industry Using Unstructured Big Data Analysis
SON, Chansoo
SHIM, Joonyong
LEE, Hyerim
LEE, Hye-Jin
CHO, Yongbeen
Abstract
Purpose: Our purpose in this study was to examine the strategies for the development of watermelon industry using unstructured big data analysis. That is, this study was to look the change of issues and consumer's perception about watermelon using big data and social network analysis and to investigate ways to strengthen the competitiveness of watermelon industry based on that. Methodology: For this purpose, the data was collected from Naver (blog, news) and Daum (blog, news) by TEXTOM 4.5 and the analysis period was set from 2015 to 2016 and from 2017-2018 and from 2019-2020 in order to understand change of issues and consumer's perception about watermelon or watermelon industry. For the data analysis, TEXTOM 4.5 was used to conduct key word frequency analysis, word cloud analysis and extraction of metrics data. UCINET 6.0 and NetDraw function of UCINET 6.0 were utilized to find the connection structure of words and to visualize the network relations, and to make a cluster of words. Results: The keywords related to the watermelon extracted such as 'the stalk end of a watermelon', 'E-mart', 'Haman', 'Gochang', and 'Lotte Mart' (news: 015-2016), 'apple watermelon', 'Haman', 'E-mart', 'Gochang', and' Mudeungsan watermelon' (news: 2017-2018), 'E-mart', 'apple watermelon', 'household', 'chobok', and 'donation' (news: 2019-2020), 'watermelon salad', 'taste', 'the heat', 'baby', and 'effect' (blog: 2015-2016), 'taste', 'watermelon juice', 'method', 'watermelon salad', and 'baby' (blog: 2017-2018), 'taste', 'effect', 'watermelon juice', 'method', and 'apple watermelon' (blog: 2019-2020) and the results from frequency and TF-IDF analysis presented. And in CONCOR analysis, appeared as four types, respectively. Conclusions: Based on the results, the authors discussed the strategies and policies for boosting the watermelon industry and limitations of this study and future research directions. The results of this study will help prioritize strategies and policies for boosting the consumption of the watermelon and contribute to improving the competitiveness of watermelon industry in Korea. Also, it is expected that this study will be used as a very important basis for agricultural big data studies to be conducted in the future and this study will offer watermelon producers and policy-makers practical points helpful in crafting tailor-made marketing strategies.
- keywords
- Watermelon, Big data, Unstructured data, Strategy
Reference
Ali, Q., Salman, A., Yaacob, H., Zaini, Z., & Abdullah, R. (2020). Does Big Data Analytics Enhance Sustainability and Financial Performance? The Case of ASEAN Banks. Journal of Asian Finance, Economics and Business, 7(7), 1-13. https://doi.org/10.13106/jafeb.2020.vol7.no7.001
An, H. & Park, M. (2018). A Study on the Evaluation of Fashion Design Based on Big Data Text Analysis: Focus on Semantic Network Analysis of Design Elements and Emotional Terms. Journal of the Korean Society of Clothing and Textiles, 42(3), 428-437. https://doi.org/10.5850/jksct.2018.42.3.428
Chae, K., Kim, B. Y., & Min, S. H. (2017). A Study on the Upland Crops Awareness Using SNS Big Data. Korea Rural Economic Institute.
Cho, Y., Oh, E., Cho, W.-S., Nasridinov, A., Yoo, K.-H., & Rah, H. (2019). Relations Between Paprika Consumption and Unstructured Big Data, and Paprika Consumption Prediction. International Journal of Contents, 15(4), 113-119. https://doi.org/10.5392/IJOC.2019.15.4.113
Choi, C., Kim, C., & Kim, C. (2019). Towards Sustainable Environmental Policy and Management in the Fourth Industrial Revolution: Evidence from Big Data Analytics. Journal of Asian Finance, Economics and Business, 6(3), 185-192. https://doi.org/10.13106/JAFEB.2019.VOL6.NO3.185
George, G., Hass, M. R., & Pentland, A. (2014). Big Data and Management. Academy of Management Journal, 57(2), 321-326. https://doi.org/10.5465/amj.2014.4002
Hong, C., & We, J. (2019). A Study on the Tourism Destination Regeneration and the Change of Destination Image: Focusing on Text Mining. Journal of Tourism Management Research, 23(2), 631-648. http://dx.doi.org/10.18604/tmro.2019.23.2.30
Hwang, U.-S., & Min, J.-K. (2017). The Analysis of Consumption Trend of Tourists to Resorts by Big Data Application. Journal of Hotel & Resort, 16(2), 5-26.
Jang, B.-Y., & Wang, Y.-D. (2019). A Study on the Perception of Golf Course Service and Golf Course Satisfaction by Analyzing Big Data. Korean Journal of Sports Science, 28(2), 561-573. https://doi.org/10.35159/kjss.2019.04.28.2.561
Kim, D., & Cha, K. (2019). Formulating Strategies from Consumer Opinion Analysis on AI Kids Phone using Text Mining. The Journal of Society for e-Business Studies, 24(2), 71-89.
KREI (2018). The Consumer Behavior Survey for Food 2018. Korea Rural Economic Institute.
KREI (2020). Agricultural Outlook: 2020. Korea Rural Economic Institute.
Lim, J., Kim, J, Ko, A., & Lee, S. (2019). A Study on Development Factors of Boeun Jujube Industry: Focusing on Boeun-gun Policy and Big Data Analysis. The Korean Journal of Local Government Studies, 23(3), 1-28.
Lee, J.-H., Lim, S.-J., & Kim, S.-Y. (2018). Professional Volleyball Keyword Analysis Using Social Networks. Korean Journal of Sports Science, 27(2), 595-613. https://doi.org/10.35159/kjss.2018.06.27.2.595
Lee, J. W. (2020). Big Data Strategies for Government, Society and Policy-Making. Journal of Asian Finance, Economics and Business, 7(7), 475-487. https://doi.org/10.13106/jafeb.2020.vol7.no7.475
Lee, J.-Y., & Jung, H. J. (2020). Exploring Consumers’Perceptions of Bags using the SNS Big Data. Journal of Brand Design Association of Korea, 18(1), 56-70. https://doi.org/10.18852/bdak.2020.18.1.55
Lee, S.-Y., & Lee, H.-S. (2020). A Study on the Smart Tourism Awareness through Bigdata Analysis. Journal of Industrial Distribution & Business, 11(5), 45-52. https://doi.org/10.13106/jidb.2020.vol11.no5.45
Lee, Y.-S. (2017). A Basic Study for Utilizing Big Data in Early Childhood Education. Journal of early childhood education, 37(4), 585-610. https://doi.org/10.18023/kjece.2017.37.4.024
MAFRA (Ministry of Agriculture, Food and Rural Affairs) (2019). The Status of Greenhouse and Vegetable Production in 2018. Sejong-si, Korea.
Marr, B. (2016). Big Data in Practice. Wiley.
Min, J.-H., & Bae, J.-H. (2015). The Impact of Big Data Investment on Firm Value. Journal of Distribution Science, 13(9), 5-11. https://doi.org/10.15722/JDS.13.9.201509.5
Park, S.-H., & Lee, H.-C. (2017). Traditional Market Change of Perception Analysis through Society Network Analysis of Text. SH Urban Research & Insight, 7(2), 109-125. https://doi.org/10.26700/shuri.2017.08.7.2.109
Park, T.-S., Moon, J.-H., Cho, M.-C, Yang, E.-Y., & Kim, S. (2015). The King of Summer Fruit & Vegetables, Watermelon. Rural Development Administration Interrobang, 153.
Park, Y.-E., & Javed, Y. (2020). Insights Discovery through Hidden Sentiment in Big Data: Evidence from Saudi Arabia’s Financial Sector. Journal of Asian Finance, Economics and Business, 7(6), 457-464. https://doi.org/10.13106/jafeb.2020.vol7.no6.457
Pramana, S., Paramartha, D. Y., Adhinugroho, Y., & Nurmalasari, M. (2020). Air Pollution Changes of Jakarta, Banten, and West Java, Indonesia During the First Month of COVID-19Pandemic. Journal of Business, Economics and Environmental Studies, 10(4), 15-19. https://doi.org/10.13106/jbees.2020.vol10.no4.15
Rah, H., Oh, E., Yoo, D.-I., Cho, W.-S., Nasridinov, A., Park, S. Cho, Y., & Yoo, K.-H. (2018). Prediction of Onion Purchase Using Structured and Unstructured Big Data. Journal of the Korea Contents Association, 18(11), 30-37. https://doi.org/10.5392/jkca.2018.18.11.030
Rho, H. Y., Kim, S. Y., & Kim, T. (2019). Does the Internet Search Index Precede the Purchase of Agro-food Products? Journal of Rural Development, 42(2), 1-34. https://doi.org/10.36464/jrd.2019.42.2.001
Seok, H. D., Choi, J., Byun, S. Y., & Min, S. H. (2019). Analysis on Consumer’s Preference for Non-Timber Forest Product (Shiitake, Chest nut, Persimmon): Social Big-data Analysis. Journal of Korean Society of Forest Science, 108(1), 97-108. http://dx.doi.org/10.14578/jkfs.2019.108.1.97
Sunil, S. (2013). Big Data Governance. MC Press.
Wi, T. (2017). A Study on the Change and Characteristics of Consumer Trends about Watermelon. Farm & Market (June).
Yoo, H.-Y., Kim, S.-C., Jang, K., & Yang, D.-S. (2020). Strategies for Strengthening of Taekwondo Competitiveness Using Big Data Analysis: Mainly on Education and Institutions. Taekwondo Journal of Kukkiwon, 11(1), 101-122. http://dx.doi.org/10.24881/tjk.2020.11.1.101
- Downloaded
- Viewed
- 0KCI Citations
- 0WOS Citations