Cleaning house before hosting new guests: A political path dependence model of political connection adaptation in the aftermath of anticorruption shocks

Han Jiang, Nan Jia, Tao Bai and Garry D. Bruton

Strategic Management Journal, 2021, vol. 42, issue 10, 1793-1821

Abstract: Research Summary We develop a political path dependence model that integrates the network embeddedness perspective and the literature on corporate political strategy to understand how firms adapt their political connections when anticorruption efforts lead to the turnover of government officials. We posit that although firms that have close associations with ousted corrupt officials can benefit from both removing existing political connections (“cleaning house”) and developing new connections with their successors (“hosting new guests”), political path dependence enables firms to do the former but constrains them from doing the latter. These effects are magnified when firms are highly dependent on the government, and when the ousted corrupt officials have great political power. Evidence from anticorruption campaigns in China between 2012 and 2018 lends support for our theoretical predictions. Managerial Summary It is common for firms to strive to stay connected with government officials. Of interest is, when political power shifts, can firms “update” their connections by severing ties with politicians who fall out of power and building new ones? Our political path dependent model demonstrates that it may not be a symmetric process. After the downfall and replacements of public officials due to corruption indictments, firms that are more closely associated with ousted, corrupt officials will indeed be more motivated and able to remove existing connections. However, the successors of ousted officials will more likely distance themselves from these firms, thereby undermining the firms' abilities to build new connections with them. Empirical evidence from anticorruption campaigns in China between 2012 and 2018 supports our predictions.

Date: 2021
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