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postgraduate thesis: Monitor digitalization : evidence from a large manufacturing firm in China
| Title | Monitor digitalization : evidence from a large manufacturing firm in China |
|---|---|
| Authors | |
| Issue Date | 2025 |
| Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
| Citation | Li, J. [李軍]. (2025). Monitor digitalization : evidence from a large manufacturing firm in China. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. |
| Abstract | This paper investigates the organizational barriers that hinder the adoption of new managerial
practices, focusing on interest misalignment within firms. Using TGOOD Chuankai Electric Co.,
Ltd., a Chinese manufacturing firm, as a case study, the research explores the effects of
implementing a digital managerial system, the Smart Factory, on group productivity, worker wages,
and personnel transfers. The staggered rollout of the Smart Factory system across different product
families between 2020 and 2023 provides a unique opportunity to examine the impact of modern
management practices on traditional production methods. Through a staggered difference-indifferences
(Diff-in-Diff) identification strategy, the study evaluates the influence of the system on
total wages, performance wages, working hours, subjective evaluations, and skill levels at both
individual and team levels.
The findings demonstrate that the Smart Factory system enhances worker productivity and
improves managerial coordination by providing more precise monitoring tools. However, the
effects of the system are more pronounced in teams that have not yet established assembly lines,
indicating the importance of context in the effectiveness of new systems. Additionally, the study
includes a survey to assess workers’ attitudes toward the Smart Factory, revealing that job
satisfaction, egalitarian beliefs, and perceived productivity benefits significantly influence their
willingness to adopt the system.
Overall, this study contributes to the literature on organizational change by identifying key
factors—such as interest misalignment—that impede the adoption of modern managerial systems
in developing countries. The research offers practical insights for firms seeking to integrate digital
management tools and highlights the importance of aligning managerial practices with workers'
perceptions to ensure successful adoption.
|
| Degree | Doctor of Business Administration |
| Subject | Industrial management - China Organizational change - China Technological innovations - Management - China |
| Dept/Program | Business Administration |
| Persistent Identifier | http://hdl.handle.net/10722/366223 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Li, Jun | - |
| dc.contributor.author | 李軍 | - |
| dc.date.accessioned | 2025-11-18T05:36:06Z | - |
| dc.date.available | 2025-11-18T05:36:06Z | - |
| dc.date.issued | 2025 | - |
| dc.identifier.citation | Li, J. [李軍]. (2025). Monitor digitalization : evidence from a large manufacturing firm in China. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. | - |
| dc.identifier.uri | http://hdl.handle.net/10722/366223 | - |
| dc.description.abstract | This paper investigates the organizational barriers that hinder the adoption of new managerial practices, focusing on interest misalignment within firms. Using TGOOD Chuankai Electric Co., Ltd., a Chinese manufacturing firm, as a case study, the research explores the effects of implementing a digital managerial system, the Smart Factory, on group productivity, worker wages, and personnel transfers. The staggered rollout of the Smart Factory system across different product families between 2020 and 2023 provides a unique opportunity to examine the impact of modern management practices on traditional production methods. Through a staggered difference-indifferences (Diff-in-Diff) identification strategy, the study evaluates the influence of the system on total wages, performance wages, working hours, subjective evaluations, and skill levels at both individual and team levels. The findings demonstrate that the Smart Factory system enhances worker productivity and improves managerial coordination by providing more precise monitoring tools. However, the effects of the system are more pronounced in teams that have not yet established assembly lines, indicating the importance of context in the effectiveness of new systems. Additionally, the study includes a survey to assess workers’ attitudes toward the Smart Factory, revealing that job satisfaction, egalitarian beliefs, and perceived productivity benefits significantly influence their willingness to adopt the system. Overall, this study contributes to the literature on organizational change by identifying key factors—such as interest misalignment—that impede the adoption of modern managerial systems in developing countries. The research offers practical insights for firms seeking to integrate digital management tools and highlights the importance of aligning managerial practices with workers' perceptions to ensure successful adoption. | - |
| dc.language | eng | - |
| dc.publisher | The University of Hong Kong (Pokfulam, Hong Kong) | - |
| dc.relation.ispartof | HKU Theses Online (HKUTO) | - |
| dc.rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works. | - |
| dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
| dc.subject.lcsh | Industrial management - China | - |
| dc.subject.lcsh | Organizational change - China | - |
| dc.subject.lcsh | Technological innovations - Management - China | - |
| dc.title | Monitor digitalization : evidence from a large manufacturing firm in China | - |
| dc.type | PG_Thesis | - |
| dc.description.thesisname | Doctor of Business Administration | - |
| dc.description.thesislevel | Doctoral | - |
| dc.description.thesisdiscipline | Business Administration | - |
| dc.description.nature | published_or_final_version | - |
| dc.date.hkucongregation | 2025 | - |
| dc.identifier.mmsid | 991045115415003414 | - |
