New Product Development And Innovation Through Joint Knowledge Creation And Transfer In A Dyadic Supply Chain Relationship

Author : Qile He
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (757 download)

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Download or read book Knowledge Transfer Within Supply Chain Partnerships written by Qile He and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Rapid technological change fuelled by convergence of discreet technologies, increased market instability, and better-informed and demanding customers have combined to significantly alter the traditional business models. As a result, the generation of knowledge and its management are among key management concerns. Over the last decade, the increasing attention by practitioners has been matched by an increasing interests and focus by academics on issues surrounding knowledge creation and knowledge deployment in organizations. Nevertheless, 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' effort to gain sustainable competitive advantage. Schools of organizational learning and inter-organizational relationship argue that interfirm relationship is an important conduit to valuable know-how and capabilities, which are difficult to generate efficiently within the firm. Among various types of partnerships - for example, franchise, R & D partnership, joint venture, and licensing agreement - supply chain partnership is a specific type of relationship. As a conduit of interfirm knowledge transfer, it has attracted increasing attention from practitioners and academics. Despite numerous efforts in examining knowledge transfer in supply chains, previous researchers appear to provide limited clarifications on characteristics of supply chain partnership. Thus particular characteristics of knowledge transfer in supply chain partnership are less clarified. As a result, influential factors unique to the process of supply chain knowledge transfer and the patterns of influence also require examination. Drawing upon theories of the resource-based view and the knowledge-based view of the firm, this research sought to explore the nature of interfirm knowledge transfer between supply chain partners and relationship factors that affect the effectiveness of knowledge transfer between supply chain partners. It also sought to develop models capable of explaining the nature and process of knowledge transfer in supply chain partnership. Based on extensive literature review, it is concluded that supply chain partnership has unique characteristics, such as vertical functional cooperative interface, loosely defined contractual agreement, more indirect performance target, and potential network-based partnership extension. These characteristics make supply chain knowledge transfer different from that of other interfirm partnerships. First, it is concluded that knowledge transfer in supply chain partnership typically occurs because of the vertical complementarities between partners. Secondly, knowledge transfer in supply chain partnership is non-targeted and less guaranteed. Thirdly; there are more concerns of network-based knowledge spillover from supply chain partners during knowledge transfer process. Fourthly, interfirm knowledge transfer is better to be understood as a multiple-stage process. Thorough examination of literature and use of theory enabled the researcher to develop a theoretical model, which focused on various relationship factors, including trust, commitment, interdependence, shared meaning, restrained use of power, and availability of alternatives. The model also explains the influence of knowledge transfer process to the supply chain performance and market performance of firms. A large-scale questionnaire survey through snowball sampling was executed in the supply chain network of a large Chinese steel producer. Given that knowledge transfer theories were developed more in the western countries, the survey in China also enabled the researcher to explore how knowledge transfer theories could be applied into different geographical area. A systematic process of data validation and model testing was followed to ensure the quality of Statistical tests. Moreover, the measurement model was examined before structural equation modelling was carried out to ensure reliability and validity of input data. Results of hypotheses testing provided varied support to the original model. Although not all relationship factors showed consistent support to the process of knowledge transfer, commitment, interdependence between partners and restraint in use of power appeared to be more significant facilitators. Consistently, knowledge transfer is more likely to occur in supply chain partnership where partners have irreplaceable role in their daily cooperation. At the other end of the model, it was shown that knowledge acquisition itself might not benefit firm performance directly. Knowledge internalization is playing a more important role in improving supply chain performance and market performance of partner firms, while knowledge utilization is more likely to benefit supply chain operations of firms. To reach a more comprehensive view as to the nature of knowledge transfer in the target supply chain network, the entire sample were divided according to various characteristics of supply chain partnership, including duration of partnership, contract status, upstream or downstream of the supply chain. Thus, multiple structural equation models were constructed with sub-samples. The result of model testing demonstrated the varied nature of knowledge transfer in supply chain partnerships with different characteristics. The research findings generally supported the positive role of interfirm knowledge transfer in the context of supply chain to firm performance. Even if knowledge acquisition may not lead to immediate benefits, such activities may result in more intensive absorption of external knowledge and further usage. In the longer term, firms are more likely to gain from knowledge interactions with key supply chain partners. However, little external knowledge could be used directly so that to generate immediate market improvement. Therefore, it was argued that one major barrier to effective knowledge transfer could be the lack of patience and support from the management. This calls upon the commitment from managers to allow more continuous knowledge transfer programs to take place and changes in attitude throughout the organization to put more persistent effort in disseminating and deploying new knowledge. Gaining from interfirm knowledge transfer also depends upon effective management of the partnership. Mutual contributions from both sides of partnership should be examined carefully to determine the potential of knowledge exchange. Explicit agenda of knowledge transfer could be developed between supply chain partners to legitimize the knowledge transfer practices. Moreover, the stronger parties in a supply chain partnership need to be careful in using excessive power. On the other hand, they should play a more constructive role in initiating or facilitating joint learning activities. This research widens the existing literature in a number of ways. Theoretically, it highlights the unique characteristics of the supply chain partnership from that of other interfirm partnerships. It extracts the relationship factors that have more significant influence on the knowledge transfer processes. It also examines the multiple-stage process of interfirm knowledge transfer, which is previously regarded as a "black box". In consideration 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 the gap of previous studies and examines the interfirm knowledge transfer in the context of a large supply chain network. Methodologically, snowball sampling has proved to be an effective approach to collect 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. Some of them are common to survey based studies. For instance, this research may suffer from common method bias, since respondents were asked to rate not only the scales of partnership characteristics but also the scales of knowledge transfer and firm performance in one questionnaire. Moreover, key informant bias may be an issue as 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 relationship was more preferred. Because this research was carried out in the supply chain network of one large firm, the findings could be contextual. This, however, remains an issue to be addressed by the future researchers.