New Framework Based on a Multi-Criteria Decision-Making Model of Transfer Technology in the Auto-Battery Manufacturing Industry under Uncertainty

Document Type : Original Article

Authors

1 Department of Technology Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran

2 School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

Abstract

This research builds a decision-based optimization model to evaluate and decide on the methods of technology transfer in the auto-battery industry under uncertainty. This research is conducted based on the needs of the country's battery industry and shows the impact of technology transfer on world-class manufacturing. At first, the effective indices in the assessment of a technology transfer method are singled out through reviewing the literature and the experts' judgment. The sample population in this research consists of experts from eight auto-battery manufacturing companies. Then, each of the approved indices is assessed via the best-worst method, and in continuation, the technology transfer methods are evaluated and prioritized using an MOORA method as multi-criteria decision-making under uncertainty. The gray theory is also used to deal with uncertainty. According to the results obtained from the best-worst method, the five significant indices (i.e., improving style management, business strategy, cost-effectiveness, how to communicate with the organization, and competitiveness) are considered to select the technology transfer methods in the auto-battery production industry. Finally, to implement the proposed framework in the state auto-battery manufacturing industries, a dual-purpose mathematical model is introduced for optimized world-class technology transfer methods. To solve the proposed model, the developed ε-constraint method is used. Finally, based on the results of the proposed method, the transfer method of joint investment is recognized as the most suitable technique for technology transfer in this industry.

Keywords

Main Subjects