Design of an intelligent supplier relationship management system for new product development

2004 ◽  
Vol 17 (8) ◽  
pp. 692-715 ◽  
Author(s):  
Kl Choy ◽  
Wb Lee ◽  
Henry Lau ◽  
Dawei Lu ◽  
Victor Lo
Keyword(s):  
Product Development ◽  
New Product Development ◽  
Management System ◽  
Relationship Management ◽  
New Product ◽  
Supplier Relationship Management ◽  
Supplier Relationship

AN EMPIRICAL STUDY OF KNOWLEDGE TRANSFER IN WORKING RELATIONSHIPS WITH SUPPLIERS IN NEW PRODUCT DEVELOPMENT

2012 ◽  
Vol 16 (02) ◽  
pp. 1250013 ◽  
Author(s):  
YUSHAN ZHAO ◽  
MARILYN LAVIN
Keyword(s):  
Knowledge Transfer ◽  
Product Development ◽  
New Product Development ◽  
Explicit Knowledge ◽  
New Product ◽  
Working Relationships ◽  
Relationship History ◽  
The Impact ◽  
Npd Performance ◽  
Supplier Relationship

This study examines the factors (trust, communication, supplier relationship specific adaptations, supplier flexibility, and relationship history) that influence knowledge transfer from the supplier to the customer firm in new product development, and the impact of knowledge transfer on product development performance. It also suggests that knowledge tacitness moderates these relationships. Based on a sample of 186 US firms, this study finds that trust, communication, supplier relationship specific adaptations, and supplier flexibility influence knowledge transfer. Knowledge transfer, in turn, has an effect on new product development performance. Mixed findings have also been reported in this paper with respect to the moderating effects of knowledge tacitness. Trust, supplier flexibility, and relationship history are more important for tacit knowledge transfer than for explicit knowledge. Knowledge tacitness does not moderate the relationship between knowledge transfer and NPD performance. However, the results show that both tacit and explicit knowledge transfer significantly affects NPD performance.

HEKM: A High-End Equipment Knowledge Management System for Supporting Knowledge-Driven Decision-Making in New Product Development

2018 ◽  
Author(s):  
Chao Zhang ◽  
Guanghui Zhou ◽  
Quandong Bai ◽  
Qi Lu ◽  
Fengtian Chang
Keyword(s):  
Decision Making ◽  
Knowledge Management ◽  
Product Development ◽  
New Product Development ◽  
Management System ◽  
New Product ◽  
Decision Makers ◽  
Knowledge Management System ◽  
Personalized Pagerank ◽  
Knowledge Resources

Pre-existing knowledge buried in high-end equipment manufacturing enterprises could be effectively reused to help decision-makers develop good judgements to make decisions about the problems in new product development, which in turn speeds up and improves the quality of product innovation. Nevertheless, a knowledge-based decision support system in high-end equipment domain is still not fully accomplished due to the complication of knowledge content, fragmentation of knowledge theme, heterogeneousness of knowledge format, and decentralization of knowledge storage. To address these issues, this paper develops a high-end equipment knowledge management system (HEKM) for supporting knowledge-driven decision-making in new product development. HEKM provides three steps for knowledge management and reuse. Firstly, knowledge resources are captured and structured through a standard knowledge description template. Then, OWL ontologies are employed to explicitly and unambiguously describe the concepts of the captured knowledge and also the relationships that hold between those concepts. Finally, the Personalized PageRank algorithm together with ontology reasoning approach is used to perform knowledge navigation, where decision-makers could acquire the most relevant knowledge for a given problem through knowledge query or customized active push. The feasibility and effectiveness of HEKM are demonstrated through three industrial application examples.

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