Understanding the decision rules for 3D printing adoption

ABSTRACT

While 3D printing is a radically different manufacturing method based on advanced technologies, it has not been adopted to-date with as much alacrity as was originally expected. A variety of hidden rules may influence the broad adoption of this novel technology. The purpose of this study is to explore the decision rules for 3D printing adoption from an organisational perspective. Hybrid approaches are proposed to integrate the technology-organisation-environment (TOE) framework and the rough set theory (RST) in order to generate the decision rule and the determinants for 3D printing adoption. An empirical study on manufacturing enterprises in Taiwan is subsequently carried out, with the results revealing a considerable amount of meaningful information that may therefore be useful in the context of management.

KEYWORDS:

• 3D printing
• additive manufacturing
• decision rules
• technology-organisation-environment (TOE) framework
• rough set theory

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Cheng-An Tsai is an Associate Professor of innovation and entrepreneurship in the Department of Business Administration at School of Management at Shih Chien University, Taipei, Taiwan. .His main research themes include entrepreneurship, business model innovation, technology adoption and new business development, and sharing economy. His research has been published in journals such as International Journal of Entrepreneurial Behaviour & Research, Journal of Technology Management, Industry and Management Forum, Journal of Management Research, Management Review. He is also closely involved with business practice through company-funded research projects and in speaker and advisory roles.

Ching-Chiang Yeh is currently a professor in the Department of Business Administration, National Taipei University of Business, Taiwan. He received his Ph.D. degree in Institute of Business and Management, and MBA from National Chiao Tung University, Taiwan. His research focuses on decision science, data mining, and management of technology. Moreover, he has published in leading journals such as the Technological Forecasting and Social Change, Technology Analysis & Strategic Management, Information Science, International Journal of Mobile Communication, Journal of Engineering and Technology Management, Expert Systems with Applications, International Journal of Electronic Business Management, Knowledge-Based Systems, International Journal of Innovative Computing, Information and Control, Cybernetics & Systems: An International Journal, Journal of Testing and Evaluation, and others.

Additional information

Funding

The authors would like to thank the Ministry of Science and Technology of the Republic of China, Taiwan, for financially supporting this research under Contract No. MOST 104-2221-E-141-005, MOST 105-2221-E-141-003 and MOST 106-2410-H-158-017.