How infomediaries on Twitter influence business outcomes of a bank

Abstract

PurposeThe purpose of this paper is to empirically explore under which conditions Tweets of infomediaries (i.e. ordinary users having few or no followers on Twitter) might nevertheless promote a negative sentiment toward a corporation to the point of having a negative impact on the corporation's outcomes.Design/methodology/approachThe empirical study is based on a unique database that combines a sample of one year of Twitter conversations about an Italian bank and its daily business performances (i.e. number of closures and openings). The relationship between these two is analyzed using autoregressive time series models (VAR).FindingsFindings indicate that a tweet affects a bank’s outcomes only when embedded in a larger conversation about the bank, rather than simply repetitively shared. These findings contribute to two debates within bank marketing literature. First is the debate about the role of infomediaries in banks' outcomes, as it urges to reconsider the way banks' online reputation is conceptualized and measured. Second is the debate on opportunities and threats of social media for the banking industry, as it indicates that negative sentiment expressed by the general public influences not only stock markets but also directly banks' outcomes.Originality/valueThis study allows managers and corporations to understand what to do when conversations of unknown individuals become threatening for the company. To influence such situations, the company should identify not only the actors that are influencers but also the communications that have been popular in the past for their brand or the brand of their competitors and monitor the conversational volume and broadness.

From Micro-Level to Macro-Level Legitimacy: Exploring How Judgments in Social Media Create Thematic Broadness at Meso-Level

“…However, their expressed judgments give birth to plural and unaggregated conversations (Schultz, Castelló, & Morsing, 2013). Recent research has shown that judgments posted by individuals on social media can nevertheless become central in bridging conversations, as they give the impression that these are part of a larger conversation, thereby potentially impacting business outcomes (Illia, et al, 2021). As we will argue next, it is the bridging of such propriety judgments at the meso-level which eventually enables propriety judgments to influence validity judgments expressed by news media.…”

“…Indeed, social media have become a vehicle, where propriety judgments become increasingly expressed by diverse actors (Etter et al, 2018(Etter et al, , 2019Wang, Reger, & Pfarrer, 2021). More importantly, through the expression of individual judgments, other individuals may be encouraged to similarly express theirs, accumulating to generate substantive contestation of organizations (Albu & Etter, 2016;Illia et al, 2021). This becomes particularly important when individuals harbor beliefs that their personal judgment deviates from an assumed majority opinion, which inhibits them from expressing their propriety judgments (Bitektine & Haack, 2015;Clemente & Roulet, 2015).…”

“…In this chapter, we address this question, arguing that the profound digital transformation of the media landscape over the last decade (Etter et al, 2019) has provided the configuration through which individual propriety judgments are publicly expressed and might move from the micro-level to the macro-level. We argue that social media have allowed propriety judgments to be revealed at the meso-level as multiple stand-alone conversations and related judgments become inter-connected (Albu & Etter, 2015;Etter et al, 2019;Illia et al, 2021). In other words, social media users engage in co-creation (Bauer & Gegenhuber, 2015), thereby establishing arenas of meaning-making that create the basis for (de-)legitimation of firms (Lounsbury & Glynn, 2019;Seidel et al, 2020).…”

“…We focus on data related to the post-scandal phase, when thematic broadness may be most relevant for news media, given that, once the scandal pick is over, journalists look for stories that attract a wide audience (Coombs, 2015;Henderson, 2009). We measure thematic broadness through a semantic network analysis (De Nooy, Mrvar, & Batagelj, 2005;Evans & Aceves, 2016;Illia, Bantimadouris, & Meggiorin, 2016;Illia et al, 2021) and use machine-learning-based text analysis (Etter, Colleoni, Illia, Meggiorin, & D' Eugenio, 2018;Liu, 2012) to measure legitimacy judgments in both social media and traditional news media. The presented findings extend our understanding of the construction and modification of organizational legitimacy in a multi-level process as suggested by institutional theory (Bitektine & Haack, 2015;Haack et al, 2020;Suddaby et al, 2017).…”

Does Sharing Economy Have a Moral Capital? Comparing Semantic Networks in Social Media and News Media

“…After this procedure, the sample contained 149,366 tweets. Then we selected those tweets that were crucial to create volume of conversations, and specifically those tweets that were central in the networked conversations in terms of bridging and retweeting power on a weekly basis (Illia, Colleoni, & Meggiorin, 2021). After this, we ended up with a total of 3513 tweets that were core for the emergence of network of conversations in the 13 weeks from January to April 2017.…”