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The roles of news in management

Han, T. (2021) The roles of news in management. PhD thesis, University of Reading

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To link to this item DOI: 10.48683/1926.00099632

Abstract/Summary

News, arguably a key information intermediary, is increasingly attracting the attention of management researchers. The developing literature suggests that news fulfils two key functions in relation to management practice. First, as an information synthesiser it alleviates information asymmetry between firms and their stakeholders. Second, news acts as a decision-making influencer. By shaping managerial cognition news exerts an important influence on firms’ behaviours and actions. Despite the current research endeavours, gaps remain in three important areas. First, little is known regarding how corporate actions affect the media coverage (i.e., media reputation) of the focal firms. Second, the literature overlooks the importance of co-coverage networks in identifying competitive relationships. Third, the literature focuses heavily on exploring news as an explanation of actions taken by individual firms, neglecting its role in explaining cluster behaviours, for example, merger waves. To address these research gaps, I develop three empirical studies fulfilling the overall aim of this thesis – that is, enhancing our nascent understanding of the role of news in the management field. I opted for the so-called three paper format because I study three unresolved problems using news as the common spine. In the first study I theorise and test the mechanism through which mergers and acquisitions (M&As) affect the media reputation of acquiring firms. I argue that when making reputational judgements, the stakeholders of acquiring firms assess not only the outcomes of M&As, but also firms’ underlying intention of making those deals. The reputation of acquirers will be enhanced if the outcomes or intentions of the deals satisfy their stakeholders’ expectations. I use announcement returns to proxy the outcome-based channel and deal characteristics to proxy the intention-based channel. The results largely support the hypotheses, suggesting that M&As affect the acquirer’s media reputation through both outcome- and intention-based channels. In doing so, this study develops the reputation antecedent research, moreover, provides a more balanced assessment for M&A success by investigating the “soft” (i.e. reputational) consequences of M&As. In the second study, I propose a novel approach based on the news co-coverage networks to identify competitors and strategic groups. Strategic groups are often delineated by either attribute similarities or cognitive maps. The former is criticised for producing methodological artefacts, while the latter has cognitive limitations. The co-coveragebased approach can address these deficiencies. The proposed methodology is applied to a sample collected from the US high-tech sector between 2001 and 2017. Testing the robustness of the group solutions, in several key strategic dimensions, I document strong intra-group similarities and inter-group differences. I also find that firms in the same groups tend to be cited as competitors rather than cooperators in news articles, suggesting the proposed approach is effective in capturing rivals. In the third study, I examine the link between the industry-specific optimism and the formation of merger waves as well as the impact of firm-specific optimism on mergers’ value destruction. M&As are among the most frequently exercised strategic decisions, often occurring in waves. The extant literature draws on either neo-classical or behavioural theory to explain the formation of merger waves. The neo-classical theory fails to fully explain post-merger waves value destruction, a void filled by the behavioural theory drawing primarily on the overvaluation concept and principally neglecting the function of sentiment, as a critical component, in the formation of merger waves and the subsequent value destruction. Through large-scale textual analysis of news releases, this study provides direct evidence that industry-specific optimism plays a pivotal role in the formation of merger waves. Further, I demonstrate that firm-specific optimism, as a proxy of managerial overconfidence, is fostered by industry-specific optimism and leads to significant value destruction. This study sheds new light on why merger waves occur and why merger waves result in inadvertent outcomes. Taken together the three papers advance knowledge by answering three research questions: (a) Can corporate actions change the tone of media coverage of the focal firms – and if so, how? (b) How can the structural properties of interorganisational networks be used to identify strategic groups? (c) Can industry-level news optimism explain merger wave formation and the value destruction? In so doing, my research enhance our understanding of the interplay of news with managerial cognition and decision-making. The thesis also identifies new avenues of research. These are discussed at the conclusion of each paper. The key areas for future research are: (a) investigating the causes and consequences of corporate actions with the media reputation indexes, (b) refining the network-based approach and extending its application to firms in different industries or countries, and (c) investigating the interplay between CEO overconfidence and TMT overconfidence and its implications on managerial decisions. The thesis is structured as follows. Chapter 1 provides an overall introduction of the thesis. Chapter 2 presents the first paper discussing the reputational consequences of M&As. Chapter 3 presents the second paper deploying the news co-coverage-based network in identifying strategic groups. And Chapter 4 presents the third paper examining the role of news in explaining the formation of merger waves and the subsequent value destruction.

Item Type:Thesis (PhD)
Thesis Supervisor:Ghobadian, A.
Thesis/Report Department:Henley Business School
Identification Number/DOI:https://doi.org/10.48683/1926.00099632
Divisions:Henley Business School > Leadership, Organisations and Behaviour
ID Code:99632
Date on Title Page:December 2020

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