African Journal of
Business Management

  • Abbreviation: Afr. J. Bus. Manage.
  • Language: English
  • ISSN: 1993-8233
  • DOI: 10.5897/AJBM
  • Start Year: 2007
  • Published Articles: 4164

Full Length Research Paper

Developing a model for evaluating and prioritizing of new product development strategies under fuzzy environment

Ali Badizadeh1* and Sohrab Khanmohammadi2
1Department of Industrial Management, Faculty of Management and Economics, Science and Research Branch, Islamic Azad University, Tehran, Islamic Republic of Iran. 2Control Engineering Department, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.  
Email: [email protected]

  •  Accepted: 16 May 2011
  •  Published: 30 September 2011


In the varying and uncertain environmental desires of customers, companies can not produce their current products forever. They apply different strategies to keep themselves competitive and effective in this altering environment. In this regard one of the key strategies is development of new products. New product development is one of the risky activities and is vital for survival and success of organizations. This paper introduces a model for evaluating and prioritizing new products development strategies. First, effective criteria and alternatives are identified. Then, the fuzzy multi criteria decision making method is applied to weight different measures and alternatives. In this paper, different new methods are introduced for calculation of fuzzy utilities and weights of criteria and prioritizing alternatives. For validation of the proposed model, it is applied for evaluation and prioritizing development strategies of new products in an automobile parts manufacturer. Compared to hierarchical process, the results of the proposed model were different. Also, identification and classification of effective factors for success of a new product development strategy is application of the proposed model. 


Key words: New product development, strategy, multi criteria decision making, fuzzy logic.