Political rotations and cross-province firm acquisitions in China

Abstract

The underdeveloped institutional framework and trade barriers between China's provinces make cross-province acquisitions challenging. We explore how Chinese firms can mitigate this problem. Drawing on social network theory we propose that cross-province rotation of political leaders-a key element of the promotion system of political cadres in China-is a mechanism enabling growth through cross-province acquisitions. We conceptualize rotated leaders as brokers between two geographically dispersed networks. We contribute to the literature on the characteristics of Chinese social networks, the effect of political connections on firm strategy, and the impact of political rotations on firm growth in China's provinces.

Promotion Pressures of Local Leaders and Real Estate Investments: China and Leader Heterogeneity

“…For another, experienced officials are expected to be sufficiently capable to deal with complexity. Evidence shows that cross-province occupational experiences have a significantly positive effect on local growth (Muratova et al 2018). In fact, governors and provincial party secretaries with occupational experience in other provinces outperform their counterparts assigned from the government in terms of local economy and their individual political position (Wu and Cao 2021;Li et al 2022).…”

Implementation Efficiency of Corporate Social Responsibility in the Construction Industry: A China Study

“…Marketization is characterized by five indicators including (1) the relationship of intervention between the government and market; (2) the development of the non-state economy; (3) the development of the product market; (4) the development of the factor market; and (5) the development of the legal-system environment [ 81 ]. The data of indicators were obtained from the database developed by the National Economic Research Institute, which is widely applied for measuring the maturity of marketization in Chinese provinces [ 83 ]. However, the latest full version of this database only contains data from 2008–2014 [ 81 ], which does not match the period of 2012–2016 in this research.…”