Masoud Latifian - Department of Technology Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran
Mohammad Ali Keramati - Department of Technology Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran
Reza Tavakkoli-Moghaddam - School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

Reviewing the efficiency of Research and Development (R&D) by giving an equal amount of importance to different R&D actions can make the measuring process too simple, which may cause an inaccurate interpretation of the R&D function and lead to an imprecise interpretation of R&D models. R&D comprises the creative work undertaken on a systematic basis to increase the stock of knowledge, including knowledge of man, culture, and society, and the use of this stock of knowledge to devise new applications. This research provides a two-phase approach to designing an R&D model in the auto battery manufacturing industry based on customer satisfaction. Due to the important role of R&D in customer satisfaction, no study has been conducted in this field and industry. In the first phase, the effective models for R&D management and the indices influencing customer satisfaction in R&D models are identified. In the second phase, the significance coefficients related to the customer satisfaction indices are obtained by using the fuzzy SWARA (Stepwise Weight Assessment Ratio Analysis) as a multi-criteria decision-making method. Furthermore, each model’s importance and final priority are calculated by the fuzzy COPRAS (Complex Proportional Assessment) method. Finally, to apply the proposed framework in the battery manufacturing industry, a bi-objective R&D model is presented. The coefficients obtained by the fuzzy COPRAS method are utilized as the input for the proposed model. Therefore, policy-makers and managers can perform their activities based on this method. The obtained results showed that the proposed framework is effective in the case under study.

research and development, Bi-objective mathematical model, Fuzzy multi-criteria decision making, Battery industry, Uncertainty