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NTIS 바로가기한국산업정보학회논문지 = Journal of the Korea Industrial Information Systems Research, v.27 no.2, 2022년, pp.163 - 176
정의범 (한신대학교 글로벌협력대학 경영학과)
As the business ecosystem has become more uncertain, the sources of supply chain risk have also been becoming more diverse. In particular, due to the development of informational technology in recent years, firms need to consider the emerging supply chain risk sources as well as traditional supply c...
Aswani, R., Kar, A. K. and Ilavarasan, P. V. (2020). Experience: Managing Misinformation in Social Media-Insights for Policymakers from Twitter Analytics. Journal of Data and Information Quality, 12(1), 1-18.
Balaji, M. S., Khong, K. W. and Chong A. Y. L. (2016). Determinants of Negative Word-of-Mouth Communication using Social Networking Sites. Information & Management, 53(4), 528-540.
Bambauer-Sachse, S. and Mangold, S. (2011). Brand Equity Dilution through Negative Online Word-of-Mouth Communication, Journal of Retailing and Consumer Services, 18(1), 38-45.
Brown, J. J. and Reingen, P. H. (1987). Social ties and word of mouth referral behavior. Journal of Consumer Research, 14(3), 350-362.
Chen, S., Mao, J., Li, G., Ma, C. and Cao, Y. (2020). Uncovering Sentiment and Retweet Patterns of Disaster-Related Tweets from a Spatiotemporal Perspective - A Case Study of Hurricane Harvey. Telematics and Informatics, 47, 101326.
Cheng, J.-J., Liu, Y., Shen, B. and Yuan, W.-G. (2013). An Epidemic Model of Rumor Diffusion in Online Social Networks. The European Physical Journal B, 86(29), 1-7.
Christopher, M. and Lee, H. (2004). Mitigating Supply Chain Risk Through Improved Confidence, International Journal of Physical Distribution and Logistics Management, 34(5), 388-396.
Chu, Z., Gianvecchio, S., Wang, H. and Jajodia, S. (2010). Who is Tweeting on Twitter: Human, Bot, or Cyborg? Proceedings of the Twenty Sixth Annual Computer Security Applications Conference, ACSAC 2010, 21-30.
Coleman, J. S. (2018). Socail Capital in the Creation of Human Capital. American Journal of Sociology, 94, 65-120.
Fan, C., Jiang, Y., Yang, Y., Zhang, C. and Mostafavi, A. (2020). Crowd or Hubs: Information Diffusion Patterns in Online Social Networks in Disasters. International Journal of Disaster Risk Reduction, 46, 101498.
Ferrara, E. and Yang, Z. (2015). Quantifying the Effect of Sentiment on Information Diffusion in Social Media, PeerJ Computer Science, 1(51), 1-15.
Fu, X. J., Goh, R. S., Tong, J. C., Ponnambalam, L., Yin, X. F., Wang, Z. X., … and Lu, S. F. (2013). Social Media for Supply Chain Risk Management. IEEE International Conference on Industrial Engineering and Engineering Management, 206-210.
Grover, P., Kar, A. K. and Ilavarasan, P. V. (2019). Impact of Corporate Social Responsibility on Reputation-Insights from Tweets on Sustainable Development Goals by CEOs. International Journal of Information Management, 48, 39-52.
Han, Y., Lappas, T. and Sabnis, G. (2020). The Importance of Interactions between Content Characteristics and Creator Characteristics for Studying Virality in Social Media. Information Systems Research, 31(2), 576-588.
Hoang, T.-A. and Lim, E.-P. (2012). Virality and Susceptibility in Information Diffusions. Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media, 146-153.
Hoang, T. B. N. and Mothe, J. (2018). Predicting Information Diffusion on Twitter-Analysis of Predictive Features. Journal of Computational Science, 28, 257-264.
Kim, J., Bae, J. and Hastak, M. (2018). Emergency Information Diffusion on Online Social Media during Storm Cindy in U.S. International Journal of Information Management, 40, 153-165.
Kim, H. and Choi, D. (2021). A study of supply network characteristics of the Korean automobile industry by parts function: Through social network analysis. Journal of the Korean Production and Operations Management Society, 33(4), 317-334.
King, K. and Wang, B. (2021). Diffusion of Real versus Misinformation during a Crisis Event: A Big Data-driven Approach. International J ounral of Information Management, 22(July), 102390.
Lee, D. and Lee, D. H. (2021). Theoretical Review of the Relationship among Perceived Uncertainty, Transaction Characteristics, Supplier Capability, and Supply Chain Performance, Journal of the Korea Industrial I nformation Systems Research, 26(4), 47-58.
Lee, S., Lee, H. and Whang, I. (2017). The effects of consumers emotional response toward negative information of service corporation on anti-corporate sentiments and negative WOM intention, Journal of Korea Service Management Society, 18(2), 249-270.
Lee, S. and Kim, S. (2019). The Boomerang Effect of Influencer Marketing : How the Interaction Between Influencer Type and Social Distance Affects Negative Word of Mouth Intentions, Korean Jouranl of Business Administration, 32(11), 2005-2028.
Leonard-Barton, D. (1985), Experts as negative opinion leaders in the diffusion of a technological innovation, Journal of Consumer Research, 11(4), pp.914-926.
Li, L., Tian, J., Zhang, Q. and Zhou, J. (2021). Influence of Content and Creator Characteristics on Sharing Disaster-Related Information on Social Media. Information & Management, 58(5), 103489.
Lin, Y. and Zhou. L. (2011). The Impacts of Product Design Changes on Supply Chain Risk: A Case Study, International Journal of Physical Distribution and Logistics Management, 41(2), 162-186.
Liu, H., Ke, W., Wei, K. K. and Hau, Z. (2013). The Impact of IT Capabilities on Firm Performance: The Mediating Roles of Absorptive Capacity and Supply Chain Agility, Decision Support Systems, 54(3), 1452-1462.
Oh, O., Kwon, K. H. and Rao, H. R. (2010). An Exploration of Social Media Inextreme Events: Rumor Theory and Twitter during the Haiti Earthquake 2010, Proceedings of the thirty frst international conference on information systems, 1-13.
Rao, S. and Goldsby, T. J. (2009). Supply Chain Risks: A Review and Typology, The International Journal of Logistics Management, 20(1), 97-123.
Shin, J., Jian, L., Driscoll, K. and Bar, F. (2018). The Diffusion of Misinformation on Social Media: Temporal Pattern, Message, and Source. Computers in Human Behavior, 83(6), 278-287.
Son, J., Lee, J., Larsen, K. R. and Woo, J. (2020). Understanding the Uncertainty of Disaster Tweets and Its Effect on Retweeting: The Perspectives of Uncertainty Reduction Theory and Information Entropy. Journal of the Association for Information Science and Technology, 71(10), 1145-1161.
Stieglitz, S. and Dang-Xuan, L. (2013). Emotions and Information Diffusion in Social Media-Sentiment of Microblogs and Sharing Behavior. Journal of Management Information Systems, 29(4), 217-248.
Suh, B., Hong, L., Pirolli, P. and Chi, E. H. (2010). Want to be Retweeted? Largescale Analytics on Factors Impacting Retweet in Twitter Network. Proceedings of the IEEE Second International Conference on Social Computing, 177-184.
Tang, C. S. (2006). Perspectives in Supply Chain Risk Management, International Journal of Production Economics, 103(2), 451-488.
Tang, O. and Musa, S. N. (2011). Identifying Risk Issues and Research Advancements in Supply Chain Risk Management, International Journal of Production Economics, 133(1), 25-34.
Verhagen, T., Nauta, A. and Feldberg, F. (2013). Negative Online Word-of-Mouth: Behavioral Indicator or Emotional Release? Computers in Human Behavior, 29(4), 1430-1440.
Vosoughi, S., Roy, D. and Aral, S. (2018). The Spread of True and False News Online. Science, 359(6380), 1146-1151.
Wu, T., Blackhurst, J. and Chidambaram, V. (2006). A Model for Inbound Supply Risk Analysis, Computers in Industry, 57(4), 350-365.
Zhu, Q., Krikke, H. and Caniels, M. C. J. (2017). Integrated Supply Chain Risk Management: A Systematic Review, The International Journal of Logistics Management, 28(4), 1123-1141. https://doi.org/10.1108/IJLM-09-2016-0206.
동아일보 (2020), 마스크 포장 전 '얼굴 부비부비'…웰킵스 "해당 라인 전량 폐기", 김진하 기자. https://www.donga.com/news/Society/article/all/20200305/100021888/2 (Accessed on March. 5th, 2020)
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