Bilateral (Hong Kong): Innovative management practices and firm performance: A Quasi-natural experiment within a private manufacturing firm in China

DOI

The project will study "high performance work systems" and company performance in the plants of a large Chinese food/noodle manufacturing firm. The principal investigators are Stan Siebert and Xiangdong Wei (Lingnan University, Hong Kong), with John Heywood of Wisconsin-Milwaukee as co-investigator. The aim is to find the root of China's world-beating productivity, and in particular to assess how the company has adapted to China's relatively high levels of labour regulation. (as measured, for example, by the World Bank's current Ease of Doing Business Report). The company is experimenting with various innovative labour practices such as team-working and incentive pay schemes, and the results will be tracked. A further aspect of the research is assessing the consequences of these practices for workers, by conducting periodic job satisfaction surveys. The project addresses central concerns of personnel economics and strategic human resource researchers. The evidence on the high performance paradigm tends to be distorted by omission of the management ability factor which our quasi-experimental approach avoids. In fact, our results may well not support the paradigm, or support a "contingency" view whereby high performance practices improve outcomes when applied to some worker groups (eg full-timers), but not when applied to others.

survey questionnaire of employees, employee payroll records

Identifier
DOI https://doi.org/10.5255/UKDA-SN-850809
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=31402122c64ae6ad00a96b9bec6b66e7211d959b0341727428f994987707bf26
Provenance
Creator Siebert, S, University of Birmingham
Publisher UK Data Service
Publication Year 2013
Funding Reference Economic and Social Research Council
Rights Stan Siebert, University of Birmingham; The Data Collection is available for download to users registered with the UK Data Service.
OpenAccess true
Representation
Resource Type Numeric
Discipline Social Sciences
Spatial Coverage Hong Kong