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​Top management team social interaction and conservative reporting decision: A language style matching approach
Date:2022-03-03

Author: Zhang, T., Liu, F., Baojun Gao, & Yen, D.


Abstract: The study uses a novel psychological text-mining approach, language style matching (LSM), to examine the effect of the social interaction of top management team (TMT) members on conservative accounting reporting practices. We posit that similar language styles help to form consensus and social integration, leading to better cooperation in group decision-making. Using 10,531 firm-year observations, we show that there is a positive association between TMT LSM and accounting conservatism, suggesting that TMT members who share similar linguistic styles respond quickly to corporate news on firm value. This implies that TMTs with better language style alignment facilitate social interactions among members to form a consensus view, enhancing decision making on how a firm should react to various corporate events that affect its value. Additional analyses indicate that the impact of LSM on conservative accounting reporting behavior is more pronounced when firms face a more competitive business environment, severe information asymmetry, and higher financial distress. By examining TMT characteristics from the dynamic psycholinguistic perspective, we shed light on the understanding of how executives' cognitive values collectively affect a firm's conservative reporting decisions.

Keywords:Language style matching;Social interaction; Upper echelons theory; Accounting conservatism


This article was officially published in Decision Support Systems in March 2020, which is a B+ award-winning journal in English. Gao Baojun is the co-corresponding author of this article.

Link: https://doi.org/10.1016/j.dss.2020.113469


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