Convergence or Divergence: A Computational Text Analysis of Stakeholder Concerns on Manufacturing Upgrading in China

Abstract

Stakeholder participation is essential to the reasonable design and smooth implementation of industrial policies. Discourse analysis can be employed as a valuable methodology to decode stakeholder (dis)agreements. Following stakeholder theory, we examine four stakeholder groups, namely the government, enterprises, media, and academia, to analyze the public focus of industrial upgrading in China. We adopt a computational text analysis approach (keyword frequency calculation, word collocation analysis, and theme identification) to understand the divergent and convergent stakeholders’ concerns toward manufacturing upgrading in China from 2015 to 2020, which is widely considered as a manufacturing upgrading policy formulation stage. Our results show that stakeholders mainly focus on innovation capability and digital transformation for China's manufacturing upgrading. There, industrial planning is the major issue for government and academia. Contradistinctively, enterprises’ main concern is servitization. Enterprise internationalization is more frequently mentioned than manufacturing upgrading in the media industry. Policymakers should engage in various tactics to make the policies endorsed by other stakeholders. Most importantly, the government should fully integrate the views of entrepreneurs in the policy initiation stage. We provide practical implications for the Chinese government to implement better the Made in China 2025 plan.