Non-professional investors often rely on information obtained from social media to make investment decisions. Extant literature has not examined the most effective strategy for the target company to counter the rumors so that investors will be more willing to continue investing in the target firm. Drawing on source credibility theory and the moral intensity model, I propose that the most effective strategy would vary given different agents who are selected to counter the rumor. After conducting a 2 x 3 (counter-rumor source x counter-rumor strategy) experiment with 272 non-professional investors recruited from Amazon Mechanical Turk, my study shows that when an internal agent (e.g., the CEO) acts as a counter-rumor source, shareholders are more willing to invest in the company when the internal agent utilizes a denial strategy rather than a reassociation or a questioning strategy. In contrast, when an external agent (e.g., a famous food blogger) serves as the counter-rumor source, the external agent can also use a questioning strategy in addition to a denial strategy to motivate shareholders to be more willing to invest in the company; however, the external agent still needs to avoid from engaging a reassociation strategy. Moderated serial-mediation analysis shows that the persuasiveness of the counter-rumor information and investors' perceived rumor intensity serially mediate the effect of counter-rumor source on investors' willingness to invest, and this effect is conditioned on the different strategy used to counter the rumor. Overall, the main effect of counter-rumor source suggests that external agents are perceived as more persuasive, which leads investors to perceive less rumor intensity, making them more willing to invest in the target company. The results of my paper can thus inform companies' social media policy.
Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc1986945 |
Date | 08 1900 |
Creators | Li, Ziyin |
Contributors | Curtis, Mary, Kipp, Peter, Wright, Rex |
Publisher | University of North Texas |
Source Sets | University of North Texas |
Language | English |
Detected Language | English |
Type | Thesis or Dissertation |
Format | Text |
Rights | Public, Li, Ziyin, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved. |
Page generated in 0.0168 seconds