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E-ISSN : 2233-5382
Exploration of Research Trends in The Journal of Distribution Science Using Keyword Analysis
Abstract
Purpose - The purpose of this study is to find out research directions for distribution and fusion and complex field to many domestic and foreign researchers carrying out related academic research by confirming research trends in the Journal of Distribution Science (JDS). Research Design, Data, and Methodology - To do this, I used keywords from a total of 904 papers published in the JDS excluding 19 papers that were not presented with keywords among 923. The analysis utilized word clouding, topic modeling, and weighted frequency analysis using the R program. Results - As a result of word clouding analysis, customer satisfaction was the most utilized keyword. Topic modeling results were divided into ten topics such as distribution channels, communication, supply chain, brand, business, customer, comparative study, performance, KODISA journal, and trade. It is confirmed that only the service quality part is increased in the weighted frequency analysis result of applying to the year group. Conclusion - The results of this study confirm that the JDS has developed into various convergence and integration researches from the past studies limited to the field of distribution. However, JDS's identity is based on distribution. Therefore, it is also necessary to establish identity continuously through special editions of fields related to distribution.
- keywords
- Research Trend, Distribution Journal, Keywords Analysis, Word Clouding, Topic Modeling
Reference
Blei, D. M., Andrew, Y. N., & Jordan, M. I. (2003). Latent dirichlet allocation. The Journal of Machine Learning Research, 3(Jan), 993-1022.
Blei, D., & Lafferty, J. (2007). A correlated topic model of science. Annals of Applied Statistics, 1(1), 17-35.
Choi, Y. J., & Kim, W. K. (2018). Strategies for continuous transactions with customers for B2B software retailers: Case study. Journal of Distribution Science, 16(12), 81-93.
Griffiths, T. L., & Steyvers, M. (2004). Finding scientific topics. Proceedings of the national academy of sciences of the United States of America, 101, 5228-5235.
Grun, B., & Hornik, K. (2011). Topic models: An R package for fitting topic models. Journal of Statistical Software, 40(13), 1-30.
Hahn, Y. N., Kim, D. H., & Youn, M. K. (2017). A brief analysis of Amazon and aistribution strategy. Journal of Distribution Science, 16(4), 17-20.
Hwang, H. J., Lee, J. H., Lee, J. W., Kim, Y. E., Yang, H. C., Youn, M. K., & Kim, D. H., (2015). Strengthening publication ethics for KODISA journals:Learning from the cases of plagiarism. Journal of Distribution Science, 13(4), 5-8.
Hwang, H. J., Lee, J. W., Youn, M. K., Kim, D. H., Lee, J. H., Shin, D. J., Kim, B. G., Kim, T. J., Lee, Y. K., & Kim, W. K. (2017). Future development strategies for KODISA journals: Overview of 2016 and strategic plans for the future. Journal of Distribution Science, 15(5), 75-83.
Hwang, H. J., Shin, D. J., Lee, J. W., Kim, D. H., Lee, J. H., Kim, B. G., Kim, T. J., Lee, Y. K., Suh, E. K., Kang, M. S., Seo. W. J., Kim, J. J., Zhang, F., Su, S., & Youn, M. K. (2018). Future development strategies for KODISA journals: Overview of 2017 and strategic plans for the future. Journal of Distribution Science, 16(5), 83-90.
Hwang, S. I., & Hwang, D. R. (2018). A study on the research trends in arts management in Korea using topic modeling and semantic network analysis. Korean Association of Arts Management, 47, 5-29.
Kang, A. T. (2016). A study on regional characteristics on the stress sentiment and topics extracted from tweet data. (Doctorial dissertation, Ewha University). Retrieved May 23, 2019 from http://dcollection.ewha.ac.kr/
Kang, C. W., Kim, K. K., & Choi, S. B. (2018). A topic analysis of abstracts in journal of Korean data analysis society. Journal of the Korean Data Analysis Society, 20(6), 2907-2915.
Kim, K. W., Jeong, J. J., Kwan, H. Y., Lee, Y. J., & Kim, C. K. (2011). Analysis of research in the Korean journal of counseling and psychotherapy (2000~2009). Korean Journal of Counseling And Psychotherapy, 23(3), 521-542.
Kim, S. H., & Yoo, B. K. (2018). The effect of brand equity of CVS PB products on repurchase intention. Journal of Distribution Science, 16(12), 23-31.
Kim, Y. H., & Bae, M. U. (2005). The effect of perceived justice on customer satisfaction and repurchase intention in the discount stores service recovery. Journal of Distribution Science, 3(1), 23-42.
Kim, Y. H., & Kim, Y. S. (2019). Trend analysis of healthcare research in Korea using topic modeling. Korean Society for Wellness (KSW), 14(1), 253-262.
Kim, Y. M., Kim, Y. E., & Youn, M. K. (2010). Analysis of research trends in journal of distribution science. Journal of Distribution Science, 8(4), 5-15.
KCI (2019). Statistics of Journals and institutions. (Korea Citation Index). Retrieved May 23, 2019 from https://www.kci.go.kr/kciportal/po/statistics/poStatisticsMain.kci
Koo, Y. D. (2005). The effect of the perception on the physical environment in discount stores on customer satisfaction and intention. Journal of Distribution Science, 3(2), 29-56.
Park, Y. K., Park, Y. B., & Lee, D. H. (2006). The influence of store choice criteria on store value and patronage intentions. Journal of Distribution Science, 4(1), 79-102.
Ryu, J. H. (2018). Analysis of research trends in Korean academic journals on health sciences using topic modeling. (Doctorial dissertation, Kosin University). Retrieved May 26, 2019 from http://www.riss.kr/search/detail/
Won, J. Y., & Kim, D. G. (2014). Deduction of social risk issues using text mining. Crisisonomy, 10(7), 33-52.
Youn, M. K., Lee, J. H., Kim, Y. E., Yang, H. C., Hwang, H. J., Kim, D. H., & Lee, J. W. (2015). KODISA journals and strategies. Journal of Distribution Science, 13(3), 5-9.
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