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http://dx.doi.org/10.9723/jksiis.2021.26.5.007

Spread of Negative Word-of-mouth of Manufacturing Companies Via Twitter: From the Supply Chain Risk's Perspective  

Jeong, EuiBeom (한신대학교 경영학과)
Yoo, Hanna (연세대학교 빈곤문제국제개발연구원)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.26, no.5, 2021 , pp. 79-94 More about this Journal
Abstract
Despite the importance of the supply chain risk due to the negative word-of-mouth (NWOM) in social media, related research is insufficient. Thus, this study analyzes how the NWOM of the product is distributed through social media and the characteristics of the distributor based on social exchange theory. For this purpose, we collected information on car recalls from four companies using Twitter from the National Highway Traffic Safety Administration (NHTSA). Based on the Seed Tweet, a Re-Tweet (RT) network was constructed to examine the distribution and spread of NWOM, and regression analysis was performed to test the hypothesis. As a result, it was confirmed that NWOM is a small world network structure that spreads around hub users connected to many users. Moreover, it was found that the more interactive and reciprocal relations the first distributor has, the greater the speed and scale of distribution of NWOM.
Keywords
Negative word-of-mouth; supply chain risk; social exchange theory; social media;
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1 Komorita, S. S. and Parks, C. D. (1999). Reciprocity and Cooperation in Social Dilemmas: Review and Future Directions. In Budescu, D. V., Erev, I. and Zwick, R. (Eds.), Games and Human Behavior: Essays in Honor of Amnon Rapoport, Psychology Press.
2 Krebs, D. (1975). Empathy and Altruism, Journal of Personality and Social Psychology, 32(6), 1134-1146. https://doi.org/10.1037/0022-3514.32.6.1134   DOI
3 Kwak, H., Lee, C., Park, H. and Moon, S. (2010). What is Twitter, A Social Network or A News Media?, In Proceedings of the 19th International Conference on World Wide Web, 591-600.
4 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   DOI
5 Lee, D, H. and Seo, Y. W. (2016). A Study on The Optimal Portfolio for Inventory Distribution of a Warehouse-Retailer under Supply Chain Disruptions, Journal of the Korean Production and Operations Management Society, 27(4), 407-425.
6 Oyewo, O. O. (2007). Rumour: An Alternative Means Of Communication In A Developing Nation: The Nigerian Example. International Journal of African & African American Studies, 6(1), 1-15.
7 Pal, A. and Counts, S. (2011). Identifying Topical Authorities in Microblogs, In Proceedings of the Fourth ACM International Conference on Web Search and Data Mining, 45-54.
8 Palmatier, R. W., Jarvis, C. B., Bechkoff, J. R. and Kardes, F. R. (2009). The Role of Customer Gratitude in Relationship Marketing, Journal of Marketing, 73(5), 1-18. https://doi.org/10.1509/jmkg.73.5.1   DOI
9 Park, N. and Jeong, J. (2011). Who Retweet and Why? : Retweeting Motivation Factors and Socio-demographic Variables' Influence on Retweeting, Journal of Media Economics & Culture, 9(3), 95-132.
10 Rao, S. and Goldsby, T. J. (2009). Supply Chain Risks: A Review and Typology, The International Journal of Logistics Management, 20(1), 97-123. https://doi.org/10.1108/09574090910954864.   DOI
11 Ratkiewicz, J., Conover, M., Meiss, M., Goncalves, B. and Flammini, F. (2011). Detection and Tracking Political Abuse, In Social Media. Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media. 297-304.
12 Cha, M., Haddadi, H., Benevenuto, F. and Gummadi, K. (2010). Measuring User Influence in Twitter: The Million Follower Fallacy, Proceedings of the International AAAI Conference on Web and Social Media, 4(1), 10-17.
13 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   DOI
14 Bolici, F., Acciarini, C., Marchegiani, L. and Pirolo, L. (2020). Innovation Diffusion in Tourism: How Information about Blockchain is Exchanged and Characterized on Twitter, The TQM Journal, 1754-2731. https://doi.org/10.1108/TQM-01-2020-0016   DOI
15 Centola, D. (2010). The Spread of Behavior in an Online Social Network Experiment, Science, 329(5996), 1194-1197. https://doi.org/10.1126/science.1185231   DOI
16 Stephen, A. T. and Toubia, O. (2010). Deriving Value from Social Commerce Networks, Journal of Marketing Research, 47(2), 215-228. https://doi.org/10.1509/jmkr.47.2.215   DOI
17 Tajvidi, R. and Karami, A. (2017). The Effect of Social Media on Firm Performance, Computers in Human Behavior, 115, 105174. https://doi.org/10.1016/j.chb.2017.09.026   DOI
18 Seo, J. (2012). A Study on the Effect of Word of Mouth(WOM) Acceptance and Diffusion for Network Characteristics of Online Information in Food Service Industry, Journal of Tourism Management Research, 16(4), 163-183.
19 Ren, F., Tan, Y. and Wan, F. (2017). Social Media Engagement and Performance of E-Tailers: An Empirical Study. Available at SSRN. http://dx.doi.org/10.2139/ssrn.3642048   DOI
20 Schaupp, L. C. and Belanger, F. (2014). The Value of Social Media for Small Businesses, Journal of Information Systems, 28(1), 187-207. https://doi.org/10.2308/isys-50674   DOI
21 Perugini, M., Gallucci, M., Presaghi, F. and Ercolani, A. P. (2003). The Personal Norm of Reciprocity, European Journal of Personality, 17(4), 251-283. https://doi.org/10.1002/per.474   DOI
22 Wang, G., Gunasekaran, A., Ngai, E. W. and Papadopoulos, T. (2016). Big Data Analytics in Logistics and Supply Chain Management: Certain Investigations for Research and Applications, International Journal of Production Economics, 176, 98-110. https://doi.org/10.1016/j.ijpe.2016.03.014   DOI
23 Tang, C. S. (2006). Perspectives in Supply Chain Risk Management, International Journal of Production Economics, 103(2), 451-488. https://doi.org/10.1016/j.ijpe.2005.12.006.   DOI
24 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. https://doi.org/10.1016/j.ijpe.2010.06.013   DOI
25 Thibaut, J. W. and Kelley, H. H. (1959). The Social Psychology of Groups, New York: John Wiley and Sons, Inc.
26 Wasko, M. M. and Faraj, S. (2005). Why Should I Share? Examining Social Capital and Knowledge Contribution in Electronic Networks of Practice, MIS Quarterly, 29(1), 35-57. https://doi.org/10.2307/25148667   DOI
27 Shi, J., Hu, P., Lai, K. K. and Chen, G. (2018). Determinants of Users' Information Dissemination Behavior on Social Networking Sites: An Elaboration Likelihood Model Perspective, Internet Research, 28(2), 393-418. https://doi.org/10.1108/IntR-01-2017-0038   DOI
28 Wu, C. W. (2016). The Performance Impact of Social Media in The Chain Store Industry, Journal of Business Research, 69(11), 5310-5316. https://doi.org/10.1016/j.jbusres.2016.04.130   DOI
29 Gadek, G., Pauchet, A., Malandain, N., Vercouter, L., Khelif, K., Brunessaux, S. and Grilheres, B. (2018). Topological and Topical Characterisation of Twitter User Communities, Data Technologies and Applications, 52(4), 482-501. https://doi.org/10.1108/DTA-01-2018-0006   DOI
30 Chae, B. K. (2015). Insights from Hashtag# Supplychain 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   DOI
31 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. https://doi.org/10.1108/09600030410545436   DOI
32 Regan, D. T. (1971). Effects of A Favor and Liking on Compliance, Journal of Experimental Social Psychology, 7(6), 627-639. https://doi.org/10.1016/0022-1031(71)90025-4   DOI
33 Wiertz, C. and De Ruyter, K. (2007). Beyond The Call of Duty: Why Customers Contribute to Firm-hosted Commercial Online Communities, Organization Studies, 28(3), 347-376. https://doi.org/10.1177/0170840607076003   DOI
34 Cialdini, R. B., Green, B. L. and Rusch, A. J. (1992). When Tactical Pronouncements of Change Become Real Change: The Case of Reciprocal Persuasion, Journal of Personality and Social Psychology, 63(1), 30. https://doi.org/10.1037/0022-3514.63.1.30   DOI
35 Fehr, E. and Gachter, S. (2000). Fairness and Retaliation: The Economics of Reciprocity, Journal of Economic Perspectives, 14(3), 159-181. https://doi.org/10.1257/jep.14.3.159   DOI
36 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.
37 Lee, W. H. (2015). Dynamic Interaction of Performance Information and Word-of-Mouth in Film Industry, Korean Management Science Review, 32(2), 125-143.   DOI
38 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. https://doi.org/10.1108/09600031111118549   DOI
39 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 Information Systems Research, 26(4), 47-58.   DOI
40 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   DOI
41 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. https://doi.org/10.1016/j.dss.2012.12.016   DOI
42 Watts, D. J. and Strogatz, S. H. (1998). Collective Dynamics of 'Small-world' Networks, Nature, 393, 440-442.   DOI
43 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.   DOI
44 Zhou, J., Liu, Z. and Li, B. (2007). Influence of Network Structure on Rumor Propagation, Physics Letters A, 368(6), 458-463. https://doi.org/10.1016/j.physleta.2007.01.094   DOI
45 Pyun, J. and Jeong, E. B. (2018). A Study on Recent Research Trend in New Product Development Using Keyword Network Analysis, Journal of the Korea Industrial Information Systems Research, 23(5), 119-134.   DOI
46 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.   DOI
47 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)
48 Honings, H., Knapp, D., Nguyen, B. C., Richter, D., Williams, K., Dorsch, I. and Fietkiewicz, K. J. (2021). Health Information Diffusion on Twitter: The Content and Design of WHO Tweets Matter, Health Information and Libraries Journal, 1-14. https://doi.org/10.1111/hir.12361   DOI
49 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.
50 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   DOI
51 Lee, W., Cha, M. and Yang, H. (2011). Network Properties of Social Media Influentials: Focusing on the Korean Twitter Community, Journal of Communication Research, 48(2), 44-79. https://doi.org/10.22174/jcr.2011.48.2.44   DOI
52 Lee, H. (2015). Brand Rumor Transmission in Twitter : Moderating Roles of Informational Quality, Journal of Practical Research in Advertising and Public Relations, 8(3), 125-143.   DOI
53 Goldenberg, J., Han, S., Lehmann, D. R. and Hong, J. W. (2009). The Role of Hubs in The Adoption Process, Journal of Marketing, 73(2), 1-13. https://doi.org/10.1509/jmkg.73.2.1   DOI
54 Jeong, E. B. and Yoo, H. (2021). The Effect of Monitoring on Performance According to the Degree of Supplier's Importance under Supply Chain Risk, Korean Journal of Logistics, 29(4), 35-47.   DOI
55 Kumar, A., Bezawada, R., Rishika, R., Janakiraman, R. and Kannan, P. K. (2016). From Social to Sale: The Effects of Firm-generated Content in Social Media on Customer Behavior, Journal of Marketing, 80(1), 7-25. https://doi.org/10.1509/jm.14.0249   DOI
56 Ma, E. and Kim, M. (2005). An Empirical Study on Knowledge Sharing among Individuals in Public Institutions : A Social Exchange Theory Approach, Information Systems Review, 7(1), 195-217.
57 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, 1-11. https://doi.org/10.1016/j.ijpe.2019.04.008   DOI
58 Lee, D. (2019). The Effect of Supplier Dependence on Relationship Performance: Focusing on Supply Chain Relationships and Communication Practices. Journal of the Korea Industrial Information Systems Research, 24(4), 37-52.   DOI
59 Miller, N. J. and Kean, R. C. (1997). Reciprocal Exchange in Rural Communities: Consumers' Inducements to Inshop, Psychology and Marketing, 14(7), 637-661. https://doi.org/10.1002/(SICI)1520-6793(199710)14:7<637::AID-MAR1>3.0.CO;2-H   DOI
60 MS, M. (2020). Positive Word of Mouth for Supply Chain Management Create a Psychological Effect Which Increases the Intention to Purchase among Indonesian Electronic Industry. International Journal of Supply Chain Management, 9(3), 674-687.
61 ISM (2014). CPSM® Study Guide, 2nd Edition.
62 Arora, A., Bansal, S., Kandpal, C., Aswani, R. and Dwivedi, Y. (2019). Measuring Social Media Influencer Index-insights from Facebook, Twitter and Instagram, Journal of Retailing and Consumer Services, 49, 86-101. https://doi.org/10.1016/j.jretconser.2019.03.012   DOI
63 Barabasi, A. L., and Albert, R. (1999). Emergence of Scaling in Random Networks, Science, 286(5439), 509-512. https://doi.org/10.1126/science.286.5439.509   DOI
64 Barabasi, A. L., and Bonabeau, E. (2003). Scale-free Networks, Scientific American, 288(5), 60-69.   DOI
65 Gupta, M., Sharma, T. G. and Thomas, V. C. (2021). Network's Reciprocity: A Key Determinant of Information Diffusion Over Twitter, Behaviour and Information Technology, 1-18. https://doi.org/10.1080/0144929X.2021.1927187   DOI
66 Hong, J. H. and Yun, H. J. (2014). The Diffusion of Rumor Via Twitter : The Diffusion Trend and The User Interactivity in The Korea-U.S. FTA Case, Korean Journal of Communication & Information, 66, 59-86.
67 Huang, X., Zhu, S. and Wang, J. (2021). Optimal Emission Reduction and Pricing in the Tourism Supply Chain Considering Different Market Structures and Word-of-Mouth Effect. Sustainability, 13(7), 3893. https://doi.org/10.3390/su13073893   DOI