Abstract
Radio frequency identification (RFID) is one of the most promising technological innovations, with the potential to increase supply chain visibility and improve process efficiency. It allows remote identification of an object using a radio link. However, it has yet to see high rates of adoption in the manufacturing industry. Thus, effort is required to identify determinants affecting RFID adoption in the manufacturing industry. Based on the technology-organization-environment (TOE) framework of Tornatzky and Fleischer (L.G. Tornatzky, M. Fleischer, The processes of technological innovation, Lexington Books, 1990), nine variables (relative advantage, compatibility, complexity, top management support, firm size, technology competence, information intensity, competitive pressure, and trading partner pressure) are proposed to help predict RFID adoption. Data collected from 133 manufacturers in Taiwan is tested against the proposed research model using logistic regression. The results and implications included in our study contribute to an expanded understanding of the determinants that affect RFID adoption in the manufacturing industry.
| Original language | English |
|---|---|
| Pages (from-to) | 803-815 |
| Number of pages | 13 |
| Journal | Technological Forecasting and Social Change |
| Volume | 77 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - 2010 Jun 1 |
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All Science Journal Classification (ASJC) codes
- Business and International Management
- Applied Psychology
- Management of Technology and Innovation
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Understanding the determinants of RFID adoption in the manufacturing industry. / Wang, Yu Min; Wang, Yi-Shun; Yang, Yong Fu.
In: Technological Forecasting and Social Change, Vol. 77, No. 5, 01.06.2010, p. 803-815.Research output: Contribution to journal › Article
TY - JOUR
T1 - Understanding the determinants of RFID adoption in the manufacturing industry
AU - Wang, Yu Min
AU - Wang, Yi-Shun
AU - Yang, Yong Fu
PY - 2010/6/1
Y1 - 2010/6/1
N2 - Radio frequency identification (RFID) is one of the most promising technological innovations, with the potential to increase supply chain visibility and improve process efficiency. It allows remote identification of an object using a radio link. However, it has yet to see high rates of adoption in the manufacturing industry. Thus, effort is required to identify determinants affecting RFID adoption in the manufacturing industry. Based on the technology-organization-environment (TOE) framework of Tornatzky and Fleischer (L.G. Tornatzky, M. Fleischer, The processes of technological innovation, Lexington Books, 1990), nine variables (relative advantage, compatibility, complexity, top management support, firm size, technology competence, information intensity, competitive pressure, and trading partner pressure) are proposed to help predict RFID adoption. Data collected from 133 manufacturers in Taiwan is tested against the proposed research model using logistic regression. The results and implications included in our study contribute to an expanded understanding of the determinants that affect RFID adoption in the manufacturing industry.
AB - Radio frequency identification (RFID) is one of the most promising technological innovations, with the potential to increase supply chain visibility and improve process efficiency. It allows remote identification of an object using a radio link. However, it has yet to see high rates of adoption in the manufacturing industry. Thus, effort is required to identify determinants affecting RFID adoption in the manufacturing industry. Based on the technology-organization-environment (TOE) framework of Tornatzky and Fleischer (L.G. Tornatzky, M. Fleischer, The processes of technological innovation, Lexington Books, 1990), nine variables (relative advantage, compatibility, complexity, top management support, firm size, technology competence, information intensity, competitive pressure, and trading partner pressure) are proposed to help predict RFID adoption. Data collected from 133 manufacturers in Taiwan is tested against the proposed research model using logistic regression. The results and implications included in our study contribute to an expanded understanding of the determinants that affect RFID adoption in the manufacturing industry.
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UR - http://www.scopus.com/inward/citedby.url?scp=77952876516&partnerID=8YFLogxK
U2 - 10.1016/j.techfore.2010.03.006
DO - 10.1016/j.techfore.2010.03.006
M3 - Article
AN - SCOPUS:77952876516
VL - 77
SP - 803
EP - 815
JO - Technological Forecasting and Social Change
JF - Technological Forecasting and Social Change
SN - 0040-1625
IS - 5
ER -