과제정보
이 논문(작품)은 한신대학교 학술연구비 지원에 의하여 연구(창작)되었음.
참고문헌
- 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. https://doi.org/10.1145/3341107
- 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. https://doi.org/10.1016/j.jretconser.2010.09.003
- Bashir, N., Papamichail, K. N. and Malik, K. (2017). Use of Social Media Applications for Supporting New Product Development Processes in Multinational Corporations, Technological Forecasting and Social Change, 120, 176-183. https://doi.org/10.1016/j.techfore.2017.02.028
- Burgess, J. and Green, J. (2013). YouTube: Online Video and Participatory Culture, Medford, John Wiley & Sons.
- Chae, B. K. (2015). Insights From Hashtag# Supply Chain and Twitter Analytics: Considering Twitter and Twitter Data for Supply Chain Practice and Research, International Journal of Production Economics, 165, 247-259. https://doi.org/10.1016/j.ijpe.2014.12.037
- Chang, Y. I. and Jung, Y. S. (2019). A Study on YouTube Product Review Channel Subscribers' Product Attitude Formation Process, The e-Business Studies, 20(2), 77-97. https://doi.org/10.20462/TeBS.2019.4.20.2.77
- 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, 1-18. https://doi.org/10.1016/j.tele.2019.101326
- Cheng, J, J., Liu, Y., Shen, B. and Yuan, W. G. (2013). An Epidemic Model of Rumo Diffusion in Online Social Networks, The European P hysical Journal B, 86(29), 1-7. https://doi.org/10.1140/epjb/e2012-30483-5
- Choi, J, Y., Han, C. H. and Kim, B. S. (2020). The Influence of YouTube Creator's Attraction and Communication on Relationship Building and Supporting Intention: Relationship Marketing Strategy Approach, The e-Business Studies, 21(1), 131-151 https://doi.org/10.20462/TeBS.2020.02.21.1.131
- Choi, J. W. (2019). The Effect of YouTube Travel Contents Features on Flow and Satisfaction, Journal of Tourism Management Research, 23(2), 193-211. https://doi.org/10.18604/tmro.2019.23.2.10
- Dong, W. Y., Park, S. W. and Lee, D. H. (2021). Demand Chain Operational Solutions in the Manufacturing Industry: A New Retail Perspective, Korean Production and Operations Management Society, 32(4), 335-355. https://doi.org/10.32956/kopoms.2021.32.4.335
- 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, 1-10. https://doi.org/10.1016/j.ijdrr.2020.101498
- Ferrara, E. and Yang, Z. (2015). Quantifying the Effect of Sentiment on Information Diffusion in Social Media, Computer Science, 1(51), 1-15. https://doi.org/10.7717/peerj-cs.26
- Go, S. R. (2022). The Effect of Characteristics of Information Sources and Content on the Purchase Intention of YouTube Viewers: Differences on the Level of Self-Control of Viewers, Korean Journal of Business Administration, 35(1), 53-70. https://doi.org/10.18032/kaaba.2022.35.1.53
- Goh, K. Y., Heng, C. S. and Lin, Z. (2013). Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User-and Marketer-generated Content, Information Systems Research, 24(1), 88-107. https://doi.org/10.1287/isre.1120.0469
- 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. https://doi.org/10.1016/j.ijinfomgt.2019.01.009
- Han, M. C. (2019). Social Media Commerce: Next Frontier in Online Shopping Focused on Chinese Consumers, Global Business & Finance Review, 24(1), 80-93. https://doi.org/10.17549/gbfr.2019.24.1.80
- Han, S. J. (2020). The Effect of Characteristics of YouTube Tourism Contents on Use Satisfaction, Continuous Use Intention and Information Sharing Intention, Journal of Corporation and Innovation, 43(3), 155-175.
- Haryanto, B. and Budiman, S. (2016). The Green Brand Marketing Strategies that Utilize Word of Mouth: Survey on Green Electronic Products in Indonesia, Global Business & Finance Review, 21(2), 20-33. https://doi.org/10.17549/gbfr.2016.21.2.20
- Jeong, E. B. (2022). A Study on Negative Word-of-mouth Virality of Social Media Using Big Data Analysis: From the Supply Chain Risk's Perspective, Journal of the Korea Industrial Information Systems Research, 27(2), 163-176.
- Jeong, E. B., and Kim, D. S. (2023). Supply Network Risk Analysis from Social and Bayesian Network Perspectives, Korean Production and Operations Management Society, 34(1), 1-17. https://doi.org/10.32956/kopoms.2023.34.1.1
- Jeong, E. B. and Yoo, H. N. (2021). Spread of Negative Word-of-mouth of Manufacturing Companies Via Twitter: From the Supply Chain Risk's Perspective. Journal of the Korea Industrial Information Systems Research, 26(5), 79-94.
- 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. https://doi.org/10.1016/j.ijinfomgt.2018.02.003
- Kim, M. R. and Jeon, J. E. (2019). The Effects of Video-sharing Platform Activities on Brand Equity : Focusing on YouTube Channel, Journal of Distribution and Management Research, 22(2), 25-33.
- Korea Petroleum Association (2018). Global Electric Vehicle Distribution Trends .https://www.petroleum.or.kr/information/report.
- Krause, S., Mattner, L., James, R., Guttridge, T., Corcoran, M. J., Gruber, S., H. and Krause, J. (2009). Social Network Analysis and Valid Markov Chain Monte Carlo Tests of Null Models, Behavioral Ecology and Sociobiology, 63(7), 1089-1096. https://doi.org/10.1007/s00265-009-0746-1
- Kwak, K., Y. (2017). Social Network Analysis, Seoul, Cheongram.
- Lam, H. K., Yeung, A. C. and Cheng, T. E. (2016). The Impact of Firms' Social Media Initiatives on Operational Efficiency and Innovativeness, Journal of Operations Management, 47, 28-43. https://doi.org/10.1016/j.jom.2016.06.001
- Lee, D. H. and Jeong, E, B. (2023). Analysis of Trends of Critical Issues and Topics in the Service Sector: Comparing YouTube Videos and Research Publications, Journal of the Korea Industrial Information Systems Research, 28(4), 59-76.
- Lee, H. J. and Kim, Y, H. (2022). A Study on the Advertising Effect According to the Level of Awareness on Influencers and the Type of Advertisement: Focusing on Youtube, The e-Business Studies, 23(6), 115-129. https://doi.org/10.20462/tebs.2022.11.23.6.115
- Lee, M. T., Yi, J. Y. and Shim, S. W. (2020), An Exploratory Study on the Effect of YouTube Beauty Influencer Attributes on Contents Attitude, Product Attitude, Word of Mouth Intention, and Purchase Intention, The Korean Journal of Advertising, 31(5), 117-142. https://doi.org/10.14377/KJA.2020.7.15.117
- 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 Journal of Business Administration, 32(11), 2005-2028. https://doi.org/10.18032/kaaba.2019.32.11.2005
- 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), 1-18.
- Lusher, D., Koskinen, J., and Robins, G. (2013). Exponential Random Graph Models for Social Networks: Theory, Methods, and Applications, Cambridge, Cambridge University Press.
- Majumdar, A. and Bose, I. (2019). Do Tweets Create Value? A Multi-Period Analysis of Twitter Use and Content of Tweets for Manufacturing Firms, International Journal of Production Economics, 216(October), 1-11. https://doi.org/10.1016/j.ijpe.2019.04.008
- Marketing Chart (2017). The Fortune 500 increasingly embraces YouTube & Instagram. Available at https://www.marketingcharts.com/digital/social-media-81061.
- OECD (2008). Productivity Growth in Services. OECD Facebook
- Oh, K. T., Jeong, E. B. and Yoo, H. N. (2023). Effects of Working Capital Management on Small and Medium-sized Enterprises' Profitability from the Continuity of Supply Chain Relationships, Global Business & Finance Review, 28(5), 51-66.
- 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 First International Conference on Information Systems, 1-13.
- Park, C. S. and Kang., Ah. R. (2020). Exploring Endogeneous Processes in Automobile Supply Network: An Exponential Random Graph Model Analysis, Korean Management Review, 49(1), 129-153. https://doi.org/10.17287/kmr.2020.49.1.129
- Park, E. K. (2021). Relationships among Characteristics of Tourism Contents on YouTube, User Satisfaction and Travel Intention: Additional test of Differences among the Variables by User Characteristics, Journal of Tourism Management Research, 25(2), 183-207. https://doi.org/10.18604/tmro.2021.25.2.10
- Park, H. H. (2019). Using ERGM (Exponential Random Graph Model) in Exploring Network Effects: A Case Study of Policy Networks, Modern Society and Public Administration, 29(1), 35-61. https://doi.org/10.26847/mspa.2019.29.1.35
- Park, S. J., Yon, S. L. and Park, H. W. (2015). Comparing Twitter and YouTube Networks in Information Diffusion: The Case of the 'Occupy Wall Street' Movement, Technological Forecasting and Social Change, 95, 208-217. https://doi.org/10.1016/j.techfore.2015.02.003
- Pew Research Center (2023). https://www.pewresearch.org/short-reads/2023/04/24/teens-and-social-media-key-findings-from-pew-research-center-surveys/.
- Prell, C. (2012). Social Network Analysis: History, Theory, and Methodology, California, SAGE Publications Inc.
- Robins, G. (2007). Advances in Exponential Random Praph (p*) Models, Social Networks, 29(2), 169-172. https://doi.org/10.1016/j.socnet.2006.08.004
- Robins, G., Pattison, P., Kalish, Y. and Lusher, D. (2007a). An Introduction to Exponential Random Graph (p*) Models for Social Networks, Social Networks, 29(2), 173-191. https://doi.org/10.1016/j.socnet.2006.08.002
- Robins, G., Snijders, T. A. B. Wang, P., Handcock, M. and Pattison, P. (2007b). Recent Developments in Exponential Random Graph (p*) Models for Social Networks, Social Networks, 29(2), 192-215. https://doi.org/10.1016/j.socnet.2006.08.003
- 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. https://doi.org/10.1016/j.chb.2018.02.008
- Snijders, T. A. (2017). Stochastic Actor-oriented Models for Network Dynamics, Annual Review of Statistics and Its Application, 4, 343-363. https://doi.org/10.1146/annurev-statistics-060116-054035
- 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. https://doi.org/10.1002/asi.24329
- 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. https://doi.org/10.2753/MIS0742-1222290408
- Tajvidi, R. and Karami, A. (2017). The Effect of Social Media on Firm Performance, Computers in Human Behavior, 115, 1-10. https://doi.org/10.1016/j.chb.2017.09.026
- Thomas, K. J. and Akdere, M. (2013). Social Media as Collaborative Media in Workplace Learning, Human Resource Development Review, 12(3), 329-344. https://doi.org/10.1177/1534484312472331
- 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. https://doi.org/10.1016/j.chb.2013.01.043
- Wang, G., Gunasekaran, A., Ngai, E. W. and Papadopoulos, T. (2016). Big Data Analytics in Logistics and Supply Chain Management: Certain Investigations for Research an Applications, International Journal of Production Economics, 176, 98-110 https://doi.org/10.1016/j.ijpe.2016.03.014
- Watts, D. J. and Strogatz, S. H. (1998). Collective Dynamics of 'Small-world' Networks, Nature, 393, 440-44. https://doi.org/10.1038/30918
- Wi, J., N. and Kim, Y., J. (2018). A Study on the Vendor Evaluation of the Automotive Industry Using Social Network Analysis, Korean Journal of Logistics, 26(2), 41-53. https://doi.org/10.15735/KLS.2018.26.2.003
- Wu, T., Blackhurst, J. and Chidambaram, V. (2006). A Model for Inbound Supply Risk Analysis, Computers in Industry, 57(4), 350-365. https://doi.org/10.1016/j.compind.2005.11.001
- Yoo, J. M. (2012). A Study on the Promotional Activities Employing SNS (Social Network Service), CJU Journal of Business and Economics, 35(2), 101-123.
- YTN (2018), http://www.sedaily.com/NewsView/1RZJJ60AYG.
- Yu, E. A. and Choi, J. E. (2020). Effect of Influencer Characteristics and Consumer Persuasion Knowledge on Consumer WOM Intention, The Korean Journal of Advertising and Public Relations, 22(4), 36-61. https://doi.org/10.16914/kjapr.2020.22.4.36