scholarly journals Improving Collaborative Decision Making in New Product Development Projects Using Clustering Algorithms

2015 ◽  
Vol 62 (4) ◽  
pp. 475-483 ◽  
Author(s):  
Hadi Jaber ◽  
Franck Marle ◽  
Marija Jankovic
2016 ◽  
Vol 24 (3) ◽  
pp. 240-250 ◽  
Author(s):  
Chiu-Chi Wei ◽  
Agus Andria ◽  
Houn-Wen Xiao ◽  
Chiou-Shuei Wei ◽  
Ting-Chang Lai

2015 ◽  
Vol 7 (1) ◽  
pp. 29-36 ◽  
Author(s):  
Mishelle Doorasamy

Abstract The aim of this article is to provide reader with a comprehensive insight on the theories, empirical findings and models of Product Portfolio Management (PPM) during new product development. This article will allow for an in-depth theoretical approach on PPM and demonstrate to managers the importance of adopting PPM as business strategy during decision making. The objective of this paper is to present a literature review of models, theories, approaches and findings on the relationship between Product Portfolio Management and new product development. Relevant statistical trends, historical developments, published opinion of major writers in this field will be presented to provide concrete evidence of the problem being discussed.


2017 ◽  
Vol 21 (5) ◽  
pp. 1035-1052 ◽  
Author(s):  
David T. Rosell ◽  
Nicolette Lakemond ◽  
Lisa Melander

Purpose The purpose of this paper is to explore and characterize knowledge integration approaches for integrating external knowledge of suppliers into new product development projects. Design/methodology/approach This paper is based on a multiple, in-depth case study of six product development projects at three knowledge-intensive manufacturing firms. Findings Firms make purposeful choices to devise knowledge integration approaches when working in collaborative buyer – supplier projects. The knowledge characteristics of the supplier input guide the choice of either coupling knowledge sharing and combining across firms or decoupling knowledge sharing (across firms) and knowledge combining (within firms). Research limitations/implications This study relies on a limited number of case studies and considers only one supplier relationship in each project. Further studies could examine the challenge of knowledge integration in buyer – supplier relationships in different contexts, i.e. in relation to innovation complexity and uncertainty. Practical implications Managers need to make choices when designing knowledge integration approaches in collaborative product development projects. The use of coupled and decoupled approaches can help balance requirements in terms of joint problem-solving across firms, the efficiency of knowledge integration and the risks of knowledge leakage. Originality/value The conceptualization of knowledge integration as knowledge sharing and knowledge combining extends existing perspectives on knowledge integration as either a transfer of knowledge or as revealing the presence of pertinent knowledge without entirely transmitting it. The findings point to the complexity of knowledge integration as a process influenced by knowledge characteristics, perspectives on knowledge, openness of firm boundaries and elements of knowledge sharing and combining.


2020 ◽  
Vol 3 (1) ◽  
pp. 17-35
Author(s):  
Brian J. Galli

In today's fiercely competitive environment, most companies face the pressure of shorter product life cycles. Therefore, if companies want to maintain a competitive advantage in the market, they need to keep innovating and developing new products. If not, then they will face difficulties in developing and expanding markets and may go out of business. New product development is the key content of enterprise research and development, and it is also one of the strategic cores for enterprise survival and development. The success of new product development plays a decisive role both in the development of the company and in maintaining a competitive advantage in the industry. Since the beginning of the 21st century, with the continuous innovation and development of Internet technology, the era of big data has arrived. In the era of big data, enterprises' decision-making for new product development no longer solely relies on the experience of decision-makers; it is based on the results of big data analysis for more accurate and effective decisions. In this thesis, the case analysis is mainly carried out with Company A as an example. Also, it mainly introduces the decision made by Company A in the actual operation of new product development, which is based on the results of big data analysis from decision-making to decision-making innovation. The choice of decision-making is described in detail. Through the introduction of the case, the impact of big data on the decision-making process for new product development was explored. In the era of big data, it provides a new theoretical approach to new product development decision-making.


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