The most effective technological learning mechanisms for innovation: evidence from Iran's steel industry

Mohammad Reza Attarpour and Abolfazl Nasri

International Journal of Technological Learning, Innovation and Development, 2023, vol. 15, issue 1, 90-113

Abstract: The complex nature of the industrial environment has made innovation the most important factor in maintaining or enhancing corporate performance. Considering the importance of a comprehensive look at the innovation concept, researchers proposed and developed the term 'innovation ambidexterity' which refers to the competitiveness of existing products and seeking new markets and products. According to the literature, one of the key processes to achieve this type of innovation and overcome its challenges, especially in latecomer companies, is to enhance technological capabilities through learning mechanisms. In addition to prioritising technological learning mechanisms, this research tries to propose appropriate policy programs in the Iranian steel industry. For this purpose, focus group and artificial neural network methods were used. The results indicated that learning by doing is the most effective mechanism for enhancing innovation in steel companies. Learning by copying, designing for exploitative innovation, learning by research, and interactions for exploratory innovation are placed in the next ranks. In the final stage, 20 policy tools have been identified. Finally, seven programs have been chosen as the most efficient tools in this context.

Keywords: technological learning; innovative ambidexterity; explorative innovation; exploitative innovation; policy programs; steel industry; Iran. (search for similar items in EconPapers)
Date: 2023
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