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Fritz, Franz (2023) An evaluation of managers’ behaviour towards high-tech machinery relocations to China. PhD thesis, University of Gloucestershire. doi:10.46289/RR22A7K2
Full text not available from this repository.Abstract
Setting up a new supply chain is a systematically and technically complex process. The theories and existing models used in this process have been developed for common industries or consumer goods, but to the best knowledge of the researcher, a theory or model has not yet to be established for high-tech machinery for capital equipment in the semiconductor, display and solar industry. These key sectors are part of the “China 2025” programme to enhance manufacturing capability development, research and development commitment, and human capital investment. Although there are a few isolated but significant studies on relocation, outsourcing and offshoring, there is comparatively little empirical research on how relocation practitioners perceive attitudes and how competencies influence their intention for management systems and tools after the organisation has already prepared for outsourcing. This study, which uses a human behaviour perspective to fill this knowledge gap, examines how managers perceive the value of and choice in methods and tools, how those interpretations (expressed in their beliefs) in turn influence their behaviour, and which type of relocation operations they prefer and choose in their future intention for offshoring. This study constructs a theoretical model to explain the fundamental linkages between beliefs and usage in relocation management by supply chain/operations practitioners, because many supply chain management-focused studies lack significant theoretical underpinnings. To achieve the intended outcome for a model derived from the technology acceptance theories, the theory of planned behaviour (TPB) was adapted. A quantitative study design was used to empirically validate the conceptual model, which was theoretically grounded. To determine whether the identified measuring items adequately represented the main theoretical model constructs, a pilot study was conducted. The main study's findings were analysed using multinomial logit regression and structural equation modelling. This model is based on the direct impact of the most important predictor (manager's attitude) by controlling for social pressures and skills. This refers to unstructured influences from peers and management of supply chain / production practitioners. This study's main theoretical contribution is that it integrates supply chain and production practitioners into the relocation efforts adapted to the TPB model. Second, this research advances knowledge by developing a model for the high technology business that is more theoretically sound than the "make or buy" models that have previously been used. By applying an inner and outer model, this research was able to evaluate both aspects simultaneously, the factors that determine intentions, as well as the factors that influence the behaviour of interest in the next three to five years. The model offers an insight into the beliefs of supply chain and production relocation management practitioners, and management support, as well as an understanding of how the classification of core competences plays a crucial role in the managers intention for the selected the relocation operation mode. As a result, the study's practical contribution to business managers enables them to suggest targeted interventions and better develop strategies to realign unfavourable beliefs and resistance to relocation and open the door to sustained, long-term efforts that organisations must make to achieve successful relocation.
| Item Type: | Thesis (PhD) | |||||||||
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| Uncontrolled Keywords: | Supply chain relocation management; High-tech machinery; Theory of Planned Behaviour (TPB) | |||||||||
| Subjects: | H Social Sciences > HF Commerce > HF5001 Business > HF5419 Wholesale | |||||||||
| Divisions: | Schools and Research Institutes > School of Business, Computing and Social Sciences | |||||||||
| Research Priority Areas: | Applied Business & Technology | |||||||||
| Depositing User: | Susan Turner | |||||||||
| Date Deposited: | 04 Jan 2024 10:43 | |||||||||
| Last Modified: | 04 Jan 2024 10:56 | |||||||||
| URI: | https://eprints.glos.ac.uk/id/eprint/13531 |
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