Investigating the Mental Models of Managers of Research and Technology Funds, In Accordance With the Concepts of Behavioral Economics, For the Development of the Innovation Ecosystem in Manufacturing

The purpose of this article is to recognize and understand the views and mental models of managers of research and technology funds in line with the new concepts of behavioral economics. Research and technology funds are considered as one of the facilitating arms in the economic system, which have a significant contribution to the sustainable development of the country. The main idea is to recognize the viewpoints and subjectivities of these managers as scientific human resources, who influence the advancement of technology and research of the country, in line with the concepts of behavioral economics. The present study includes 13 senior managers of research and technology funds in 2022, which were obtained by purposive sampling and through in-depth interviews to the propositions resulting from Q methodology. The results show 17 verified propositions and three mental models of managers of research and technology funds related to behavioral economics concepts. The results indicate the existence of cognitive and behavioral bias of representativeness, competence, and confirmation in the first mental model, anchoring and adjustment bias, as well as overconfidence bias in the second mental model. In the third mental model obtained from managers, there are bias of eventuality and data dilution. Finally, by providing nudges (suggestions), an attempt has been made to reduce these biases and to see more efficient management decisions.

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Publication Details

Journal
international journal of advanced design and manufacturing technology
Published
2025-01-09
DOI
https://doi.org/10.71644/admt.2025.1195963
Primary Topic
Q Methodology Applications
Type
article
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article

Investigating the Mental Models of Managers of Research and Technology Funds, In Accordance With the Concepts of Behavioral Economics, For the Development of the Innovation Ecosystem in Manufacturing

Mohammad Yazdaanian, Mahla Sadat Hosseini
international journal of advanced design and manufacturing technology
Q Methodology Applications
article

Investigating the Mental Models of Managers of Research and Technology Funds, In Accordance With the Concepts of Behavioral Economics, For the Development of the Innovation Ecosystem in Manufacturing

Mohammad Yazdaanian, Mahla Sadat Hosseini
article en

Abstract

The purpose of this article is to recognize and understand the views and mental models of managers of research and technology funds in line with the new concepts of behavioral economics. Research and technology funds are considered as one of the facilitating arms in the economic system, which have a significant contribution to the sustainable development of the country. The main idea is to recognize the viewpoints and subjectivities of these managers as scientific human resources, who influence the advancement of technology and research of the country, in line with the concepts of behavioral economics. The present study includes 13 senior managers of research and technology funds in 2022, which were obtained by purposive sampling and through in-depth interviews to the propositions resulting from Q methodology. The results show 17 verified propositions and three mental models of managers of research and technology funds related to behavioral economics concepts. The results indicate the existence of cognitive and behavioral bias of representativeness, competence, and confirmation in the first mental model, anchoring and adjustment bias, as well as overconfidence bias in the second mental model. In the third mental model obtained from managers, there are bias of eventuality and data dilution. Finally, by providing nudges (suggestions), an attempt has been made to reduce these biases and to see more efficient management decisions.

international journal of advanced design and manufacturing technology
University of Tehran (IR)
Industry, innovation and infrastructure
Openalex Percentile: Top 30%
Q Methodology Applications
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