Journal of the Korean Data and Information Science Society

The Korean Data and Information Science Society (한국데이터정보과학회)
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Face/non-face channel fit comparison of life insurance company and non-life insurance company using social network analysis

소셜네트워크 분석을 활용한 생보사와 손보사의 대면/비대면 채널의 적합성 비교

  • Chun, Heuiju (Department of Statistics & Information, Dongduk Women's University) ;
  • Leem, Byunghak (Division of Business Administration, Busan University of Foreign Studies)
  • 전희주 (동덕여자대학교 정보통계학과) ;
  • 임병학 (부산외국어대학교 경영학부)
  • Received : 2014.07.14
  • Accepted : 2014.08.26
  • Published : 2014.11.30
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Abstract

In this study, 1) we compare face channel and non-face channel of life insurance company and non-life insurance company with insurance employs' suitability opinion about channel type, channel property, channel evaluation items requiring when selling insurance products, 2) we construct two social networks for life insurance companies and non-life insurance companies and find/compare two networks' properties, and then want to suggest any direction about sale channel strategy. As the result of comparing social networks of life insurance company and non-life insurance company created by insurance selling channel fit evaluation, employs of life insurance companies have more common opinion than those of non-life insurance companies and so can have more same directional channel strategy. However, property insurance companies need to manage their own channel strategy based on their own circumstance.

본 연구의 목적은 1) 보험전문가인 보험회사에 근무하는 임직원들이 가지고 있는 채널의 유형, 채널평가 항목, 보험 상품과 보험판매 시 요구되는 채널특성들간의 적합성에 대한 의견을 가지고 생명보험업계와 손해보험업계 각각 2-mode 소셜네트워크 데이터를 구성하고 2) 생명보험업계와 손해보험업계 2-mode 소셜 네트워크 데이터를 1-mode 소셜 네트워크 데이터로 변환하여 생명보험업계와 손해보험업계 두 소셜 네트워크의 구조와 네트워크 특성 변수들을 찾아 비교 분석하고, 소셜 네트워크 기반 측면에서의 생명보험사와 손해보험사의 판매채널 전략의 방향을 제시하고자 한다. 보험 판매채널의 평가에 의한 소셜 네트워크를 비교한 결과, 생명보험업계 소셜 네트워크가 손해보험업계 소셜 네트워크보다 더욱 강한 연결을 보였다. 즉 생명보험업계의 소셜 네트워크의 중심성 변수들이 손해보험업계의 것 들 보다 모두 높게 나타나 생명보험회사들은 채널전략 운영 측면에서 한 방향으로 움직이기가 수월함을 보이는 반면, 손해보험사들은 회사의 규모나 처한 환경에 따라 판매채널 전략이 다를 수 있어 각사의 개별적인 보험 판매 채널전략을 운영해야 함을 의미한다.

Keywords

References

  1. Ahn, C. (2010). Recent trend and implication of home shopping insurance sales. KiRi Weekly, Korea.
  2. Ahn, C. and Jung, S. (2010). The channel strategies based on the analysis of the characteristics of distribution channel. The Journal of Risk Management, 21, 67-95. https://doi.org/10.21480/tjrm.21.2.201012.003
  3. Bisker, J. H., Dietrich, B. L., Ehrlich, K., Helander, M. E., Lin, C. and Williams, P. (2008). Health insurance fraud detection using social network analytics, Patent Application Publication, USA.
  4. Bloch, F., Genicot, G. and Ray, D. (2005). Informal insurance in social networks. Available from http://www.econ.nyu.edu/user/debraj/Papers/BlochGenicotRay.pdf.
  5. Bonacich, P. (1972). Factoring and weighting approaches to status scores and clique identification. The Journal of Mathematical Sociology, 2, 113-120. https://doi.org/10.1080/0022250X.1972.9989806
  6. Bonacich, P. (1987). Power and centrality: A family of measures. American Journal of Sociology, 92, 1170-82. https://doi.org/10.1086/228631
  7. Choi, S., Kang C., Choi, H. and Kang, B. (2011). Social network analysis for a soccer game. Journal of the Korean Data & Information Science Society, 22, 1053-1063.
  8. Cho, J. S. (2012). Inflow and outflow analysis of double majors using social network analysis. Journal of the Korean Data & Information Science Society, 23, 693-701. https://doi.org/10.7465/jkdi.2012.23.4.693
  9. Chun, H. (2011). Analysis and application to customers' social roles using voice network of A telecom, company. The Korean Journal of Appled Statistics, 24, 1237-1248. https://doi.org/10.5351/KJAS.2011.24.6.1237
  10. Chun, H. and Oh, P. S. (2011). A study on determinant effect of non-face channel growth using proportional logit model. The Journal of Risk Management, 22, 77-99. https://doi.org/10.21480/tjrm.22.2.201112.003
  11. Coleman, J. (1988). Social capital in the creation of human capital. The American Journal of Sociology, 94, S95-S120. https://doi.org/10.1086/228943
  12. Cross, R. and Cummings, J. (2004). Tie and network correlates of individual performance in knowledgeintensive work. Academy of Management Journal, 47, 928-937. https://doi.org/10.2307/20159632
  13. DiMaggio, P. and Powell, W. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48, 147-160. https://doi.org/10.2307/2095101
  14. Freeman, L. C. (1979). Centrality in social networks: Conceptual clarification. Social Networks, 1, 215-239.
  15. Granovetter, M. (2005). The impact of social structure on economic outcomes. Journal of Economic Perspectives, 19, 33-50.
  16. Jung, S., Ouh, C. and Kim, H. (2010). The performance of direct marketing in the life insurance industry. Korean Insurance Journal, 85, 79-108.
  17. Jung, S. and Song, Y. (2008). The effects of bancassurance and the business strategies of life insurance companies. Journal of Insurance and Finance, 19, 33-54.
  18. Kim, J. H. (2007). Impact of bancassurance on cost efficiency and productivity change in the Korean life insurance industry. Journal of Insurance and Finance, 18, 3-40.
  19. Kim, J. D. and Son, M. J. (2008). Change in the efficiency of the Korean life insures with the introduction of bancassurance. Korean Insurance Journal , 79, 61-92.
  20. Kim, Y. H. (2007). Social network analysis, Parkyoungsa, Seoul.
  21. Knoke, D. and Yang, S. (2008). Social network analysis, 2nd Ed., SAGE, London.
  22. Lee, G. H. (2005), New product marketing, Kyungmoonsa, Seoul.
  23. LIMRA (2005). LIMRA's market trends: Trends in U.S. insurance book, LIMRA International, New York.
  24. Oh, K. (2009). The effectiveness of Korean life insurance marketing channels focusing on customer characteristics and product types. Korean Insurance Journal, 84, 1-34.
  25. Son, D. W. (2007). Social network analysis, Parkyoungsa, Seoul.
  26. Uzzi, B. (1997). Social structure and competition in interirm networks: The paradox of embeddedness. Administrative Science Quarterly, 42, 35-67. https://doi.org/10.2307/2393808
  27. Watts, D. J. and Strogatz, S. H. (1998). Collectively dynamics of small-world networks. Nature, 393, 440-442. https://doi.org/10.1038/30918

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