Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
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Analyzing Customer Feedback Differences between VOCs and External Channels

VOC와 외부채널간의 고객 피드백 차이 분석

  • 안상현 (한국생산성본부) ;
  • 백동현 (한양대학교 경상대학 경영학부)
  • Received : 2018.07.02
  • Accepted : 2018.09.06
  • Published : 2018.09.30
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Abstract

VOCs have been used as the most definitive resource to reflect customer feedback when developing products and services. However, due to the development of the Internet and the emergence of SNS, VOC is no longer the only channel that represents customer opinions. There are also a number of studies showing that many customers express complaints through channels other than VOCs. In this paper, we analyze the difference between the official VOC data and the data collected through the external channel, and suggest ways to reflect the various opinions of customers. To do this, this study uses keyword analysis that can identify differences according to frequency through social network, modular analysis to distinguish topics according to centrality and similarity, and emotional analysis to confirm word polarity (positive and negative). The results of this study show that the opinions of the customers were different depending on channels such as VOCs and external channels. Therefore, the collected data through VOC as well as external channels should be used in order to reflect the opinions of customers. In particular, this paper confirms that the results of one channel may vary depending on the channel characteristics even for the same channel. This confirms that collecting voc only on certain channels may differ from what real customers require. Therefore, data collected through VOCs as well as external channels must be used to reflect various customer feedback.

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References

  1. Allen, J., James, A.D., and Gamlen, P., Formal versus informal knowledge network in R&D : a case study using social network analysis, R&D Management, 2007, Vol. 37, No. 3, pp. 179-196. https://doi.org/10.1111/j.1467-9310.2007.00468.x
  2. Baek, B.S., Research of VOC operating system and the problems of the police service, Korean Association of Police Science, 2013, Vol. 15, No. 5, pp. 115-146.
  3. Blondel, V.D., Guillaume, J.L., Lambiotte, R., and Lefebvre, E., Fast unfolding of communities in large network, Journal of Statistical Mechanics : Theory and Experiment, 2008, pp. 1-12.
  4. Chang, J.Y., An Opinion Document Clustering Technique for Product Characterization, Society for E-Business Studies, 2014, Vol. 19, No. 2, pp. 95-108.
  5. Cho et al., Sentiment Analysis Using News Comments for Public Opinion Mining, Korean Institute of Intelligent Systems Conference, 2013, Vol. 23, No. 1, pp. 149-150.
  6. Cho, Y.H. and Bang, J.H., Social Network Analysis for New Product Recommendation, Journal of Intelligent Information Systems, 2009, Vol. 15, No. 4, pp. 183-199.
  7. Choi, C.H., A Study on the Informal Networks in Organizations : An Application of Social Network Analysis, Seoul Association For Public Administration, 2006, Vol. 17, No. 1, pp. 1-23.
  8. Choi, C.I. and Kang, B.Y., Social Network Analysis on the Climate Change Researches and its Implications, The Korean Regional Development Association, 2012, Vol. 24, No. 5, pp. 1-20.
  9. Freeman, L.C., Centrality in social networks conceptual clarification, Social Networks, 1979, Vol. 1, No. 3, pp. 215-239. https://doi.org/10.1016/0378-8733(78)90021-7
  10. Griffin, A. and Hauser, J.R., The Voice of Customer, Marketing Science, 1993, Vol. 12, No. 1, pp. 1-24. https://doi.org/10.1287/mksc.12.1.1
  11. Han, S.H., A Study on Keyword Extraction From a Single Document Using Term Clustering, Journal of the Korean Society for Library and Information Science, 2010, Vol. 44, No. 3, pp. 155-173. https://doi.org/10.4275/KSLIS.2010.44.3.155
  12. Hui, Z. and Trevor, H., Regulariuzation and variable selection via elastic net, Journal of the Royal Statistical Society : Series B, 2005, Vol. 67, No. 2, pp. 301-320. https://doi.org/10.1111/j.1467-9868.2005.00503.x
  13. Hyeon et al., Customers who take advantage of multidimensional clustering analysis of the topic, Korea Intelligent Information Systems Society conference, 2014, pp. 183-185.
  14. Jang, G.S., A Integrated VOC Management Schema in Large-Scale Manufacturing Companies : A Case Study on Implementation for Construction Equipment Division in 'H' Heavy Industry, Journal of the Korea Society of Computer and Information, 2009, Vol. 14, No. 8, pp. 127-136.
  15. Ju, J.M. and Hwang, S.G., Establish of VOC analysis system for efficient CRM, The Korean Society for Quality Management, 2003, Vol. 32, No. 1, pp. 75-91.
  16. Kang, B.I., Song, M., and Jho, W.S., A Study on Opinion of Newspaper Texts based on Topic Modeling, Journal of the Korean Society for Library and Information Science, 2013, Vol. 47, No. 4, pp. 315-334. https://doi.org/10.4275/KSLIS.2013.47.4.315
  17. Kim et al., A Social Network Analysis on Stakeholders of Watershed Management in Saemanguem Area, The Korean Association For Environmental Sociology, 2013, Vol. 17, No. 2, pp. 227-274.
  18. Kim et al., A Technique of the Approval Rating Analysis for Political Party Using Opinion Mining, Journal of Korean Institute of Information Technology, 2014, Vol. 12, No. 10, pp. 133-141.
  19. Kim, J.E., Kim, N.G., and Cho, Y.H., User-Perspective Issue Clustering Using Multi-Layered Two-Mode Network Analysis, Journal of Intelligent Information Systems, Vol. 20, No. 2, pp. 93-107.
  20. Kim, J.H. and Kwon, O.B., Business Intelligence from Voice of Customer, Korean Academic Society of Business Administration Conference, 2015, pp. 1-9.
  21. Kim, J.Y., An efficient acquisition method of VOC in new product development, Korea Business Education Association, 2012, Vol. 23, No. 1, pp. 54-76.
  22. Kim, S.H. and Jang, R.S., The Study on the Research Trend of Social Network Analysis and its Applicability to Information Science, Journal of the Korean Society for Information Management, 2010, Vol. 27, No. 4, pp. 71-87. https://doi.org/10.3743/KOSIM.2010.27.4.071
  23. Kim, Y.G., Lee, W.H., and Kwon, H.C., Clustering of Web Document Exploiting with the Co-link in Hypertext, Journal of Korean Library and Information Science Society, 2003, Vol. 34, No. 2, pp. 233-253.
  24. Kim, Y.H., In, K.H., and Kim, E.M., The Blog Polarity Classification Technique using Opinion Mining, Korean Intelligent Information Systems Society Conference, 2012, pp. 225-228.
  25. Kim, Y.S. and Jeong, S.R., Intelligent VOC Analyzing System Using Opinion Mining, Journal of Intelligent Information Systems, 2013, Vol. 19, No. 3, pp. 113-125. https://doi.org/10.13088/jiis.2013.19.3.113
  26. Kwon, B.C. and Cho, N.W., A Study on the Relationship between Social Network of Code share and Performances in Airline Industries, Journal of the Korean society for Quality Management, Vol. 39, No, 2, pp. 271-280.
  27. Lee et al., Developing Corporate Valuation System with Opinion Mining Based on Big Data, Proceedings of the 25th Annual Conference on Human and Cognitive Language Technology, 2013, Vol. 25, pp. 126-128.
  28. Lee, D.R., A Social Network Analysis on Basic Old-age Pension Policymaking Process, Korean Association For Policy Science, 2012, Vol. 16, No. 3, pp. 109-135.
  29. Lee, H.J., Analysis of marketing research knowledge structure using social network analysis, Korean Academic Society of Business Administration, 2014, Vol. 43, No. 3, pp. 965-992.
  30. Lee, K.M., Text Characteristic Recognition Using by Clustering, Korea Information Processing Society, 2001, Vol. 8, No. 1, pp. 837-840.
  31. Lee, M.H., Kim, J.H., and Jang, J.Y., Intermediate support organizations analyzed using Social Network Analysis, Seoul Association For Public Administration, 2011, Vol. 22, No. 1, pp. 141-178.
  32. Lee, S.H., Hwang, H.K., and Kim, J.Y., A Study on Utilization of Customers(VOC) for Improvement in Information Services, Journal of Korean Library and Information Science Society, 2015, Vol. 46, No. 1, pp. 25-42. https://doi.org/10.16981/kliss.46.1.201503.25
  33. Lee, S.Y. and Kim, Y.E., A Study on the establishment of VOC system in compliance with the shift in customer trend, Journal of Distribution Science, 2009, Vol. 7, No. 2, pp. 89-119. https://doi.org/10.15722/jds.7.2.200906.89
  34. Lee, S.Y., In, K.H., and Kim, U.M., Analyzing University Bulletin Board Data by using Opinion Mining, Korea Information Science Society Conference, 2012, Vol. 39, No. 2, pp. 104-106.
  35. Lee, W.K., Community centrality of power analysis through network analysis, The Korean Association For Public Administration Conference, 1997, pp. 377-394.
  36. Moody, J., The structure if a social science collaboration network : Disciplinary cohesion from 1963 to 1999, American sociological review, 2004, Vol. 69, No. 2, pp. 213-238. https://doi.org/10.1177/000312240406900204
  37. Moon, H.N. and Kim, J.W., Internet news research individual stock returns prediction models utilizing : the use of opinion mining techniques, Korea Intelligent Information Systems Society Conference, 2014, pp. 387-393.
  38. Park et al., Two-Level Clustering for Sub-Topic Labelling of Social Media Data, Journal of KISS : Software and Applications, 2014, Vol. 41, No. 3, pp. 225-232.
  39. Park, C.Y., Simple principal component analysis using Lasso, Journal of the Korean Data and Information Science Society, 2013, Vol. 24, No. 3, pp. 533-541. https://doi.org/10.7465/jkdi.2013.24.3.533
  40. Park, W.J. and Yu, K.Y., Spatial Clustering Analysis based on Text Mining of Location-Based Social Media Data, Journal of the Korean Society for Geo-Spatial Information System, 2015, Vol. 23, No. 2, pp. 89-96.
  41. Seung, H.W. and Park, M.Y., A Clustering Technique Using Association Rules for The Library and Information Science Terminology, Journal of the Korean Society for Library and Information Science, 2003, Vol. 37, No. 2, pp. 89-105. https://doi.org/10.4275/KSLIS.2003.37.2.089
  42. Singh, J., A Typology Consumer Dissatisfaction Response Styles, Journal of Retailing, 1990, Vol. 66, No. 1, pp. 57-99.
  43. Song et al., An Integrated Data Mining Model for Customer Relationship Management, Korea Information Science Society, 2006, Vol. 33, No. 2, pp. 154-159.
  44. Woo, J.Y., Choi, M.S., and Park, S.C., Systematic research on the causes of changes occurring Voice of Customer, Korean Institute of Industrial Engineers Fall Conference Proceeding, 2004, pp. 33-37.
  45. Yun, S.J., Kim, S.H., and Shin, K.S., Development of the Accident Prediction Model for Enlisted Men through an Integrated Approach to Datamining and Textmining, Journal of Intelligent Information Systems, 2015, Vol. 21, No. 3, pp. 1-17.