This study aims to explore the relationship between dialect diversity and collaborative innovation, drawing on the absorptive capacity view. It examines how communication barriers caused by dialect differences hinder firms’ ability to absorb external knowledge and investigates the moderating roles of digital transformation and employee education level in mitigating these effects.
The study leverages a dataset of 3,228 listed firms from 200 cities in China, covering the period from 2008 to 2020. A dialect diversity index is constructed using linguistic data from the Dictionary of Chinese Dialects and the Atlas of Chinese Dialects. Hypotheses are tested using multivariate regression models with robust controls for industry, province and year-fixed effects, supplemented by robustness checks.
Dialect diversity negatively impacts collaborative innovation due to communication and understanding barriers that hinder knowledge absorption. However, firms with higher levels of digital transformation and a greater proportion of highly educated employees experience mitigated negative effects of dialect diversity.
Managers should recognize the detrimental effects of dialect diversity on collaborative innovation and address language-related barriers proactively. Investments in digital technologies and employee training programs can facilitate smoother communication and knowledge sharing to maximize collaborative efficiency in linguistically diverse settings.
This study develops a contingent ACAP view of innovation by introducing dialect diversity as a significant factor influencing collaborative innovation. It provides a nuanced understanding of the contingent effects of digital transformation and employee education on overcoming dialect-related barriers, offering valuable insights for managing linguistic diversity in complex innovation environments.
