A distinct feature of China's involvement in the economic development of African countries in recent years has been the Chinese government's financing and participation in infrastructure construction projects through its state-owned firms. However, there remains limited academic research on labour relations' issues concerning Chinese firms in Africa. This article fills part of the research gap by examining key aspects of labour relations of Chinese construction firms operating in Africa. The article mobilises the notion of space in analysing the role of the state and its agencies in shaping the transnational labour market of construction workers and workplace industrial relations. Drawing on data from 52 interviews with managers, professionals and government officials, this study highlights the interdependence and interconnectedness of the Chinese lead construction firms, subcontractor firms and employment agencies on the one hand, and legislative and representational gaps for the Chinese dispatched workers on the other.
This paper investigates the time lags effects of innovation input on output in the national innovation systems (NIS). Firstly, we analyze the intrinsic properties of China’s NIS based on the conceptual framework and the causal loop diagram. Secondly, we construct a time lags distribution calculation model and employ the main innovation input indicators to measure the specific characteristics of time lags effects of innovation input on output for China in the period 2000–2012. The results indicate that there are considerable time lags in the four major feedback loops, and the distribution of time lags is various according to the characteristics of innovation input and influencing factors in the internal transformation. The trends of time lags from R&D personnel and industry-academia-research collaboration show steady growth, and the trends of time lags from R&D expenditure and government’s macro-control take inverted U-shaped pattern. Finally, we combine the estimation results of lags distribution calculation model with the analysis results of the causal loop diagram (including positive loops and negative loops) to provide some innovation policy suggestions. This study provides important implications for our understanding of the long-term complex lags effects of innovation input on output as well as for policy-makers designing and implementing the innovation strategies.
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