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Title: Knowledge transfer within supply chain partnerships : an empirical study of a Chinese steel producer
Author: He, Qile
ISNI:       0000 0004 2690 530X
Awarding Body: Middlesex University
Current Institution: Middlesex University
Date of Award: 2009
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Over the last decade, increasing attention by practitioners has been matched by an increasing interest and focus by academics on issues surrounding knowledge creation and knowledge deployment in organizations. There is also increasing recognition that knowledge generated solely within the firm is likely to have a limited impact on performance improvement. Knowledge from external sources is an important contributor to firms' efforts to gain sustainable competitive advantage. Schools of organizational learning and inter-organizational relationship argue that interfirm relationship is an important conduit for valuable know-how and capabilities, which are difficult to generate efficiently within the firm. Among various types of partnership - for example, franchise, R&D partnership, joint venture, and licensing agreement - supply chain partnership as a conduit of interfirm knowledge transfer has attracted increasing attention from practitioners and academics. Despite numerous attempts to examine knowledge transfer in supply chains, previous researchers appear to provide limited clarification on particular characteristics of knowledge transfer in supply chain partnerships. As a result, influential factors unique to the process of supply chain knowledge transfer and the patterns of influence also require examination. The current study sought to explore the nature of interfirm knowledge transfer between supply chain partners and of relationship factors that influence the effectiveness of that knowledge transfer. It also sought to develop a model capable of explaining the process of knowledge transfer in supply chain partnerships and the influence of knowledge transfer processes on partner firms' supply chain performance and market performance. A large-scale questionnaire survey was executed using snowball sampling in the supply chain network of a large Chinese steel producer. The measurement model was examined before structural equation modelling was carried out to ensure reliability and validity of input data. Moreover, multiple structural equation models were constructed with sub-samples according to partnership characteristics of duration, contract status, and location in the supply chain. Results of model testing provided varied evidence to support the original model and generally demonstrated the positive role of interfirm knowledge transfer in the context of supply network to firms' performance. Although not all relationship factors showed consistent support for the process of knowledge transfer, commitment, interdependence, and restraint in use of power appeared to be more significant facilitators. This research widens the existing literature in a number of ways. Theoretically, it highlights the unique characteristics of the supply chain partnership compared with those of other interfirm partnerships. It extracts the relationship factors that have a more significant influence on the knowledge transfer processes. It also examines the multi-stage process of interfirm knowledge transfer, which has previously been regarded as a “black box”. Given that existing literature was largely developed in the Western countries, this research extends the knowledge transfer theories to a Chinese industrial context. Empirically, this research fills gaps in previous studies and examines interfirm knowledge transfer in the context of a large supply chain network. Methodologically, snowball sampling has proved to be an effective approach to collecting data from a network of firms. The systematic approach of construct development, validation, cross-validation and model testing could also serve as a guideline for future empirical researchers in the area. There are several limitations in this research. This research may suffer from common method bias. Moreover, key informant bias may be an issue as a single respondent from each organization was asked to return the questionnaire. Although snowball sampling is an effective data collection method, it may end up including more favourable or mature partnerships in the sample. However, given that this research sought to study partnerships rather than arms-length relationships, closer relationships were preferred. Because this research was carried out in the supply network of one large firm, the findings could be contextual. This, however, remains an issue to be addressed by future researchers.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available