 Determinants of the adoption of modern technology in the handloom industry in AssamAlin Borah Bortamuly and Kishor Goswami Technological Forecasting and Social Change, 2015, vol. 90, issue PB, 400-409 Abstract: This paper identifies and analyzes the determinants of technology adoption in the handloom industry in Assam. Binary logistic regression model is used to analyze the primary data in which the dependent factor (technology adoption) is dichotomous. Results show that education and annual income of the industry owners play a crucial role in the adoption of modern technology. In the case of small owners, gender has positive and significant influence, whereas age, education, and distance to the nearest market have significant but negative influences on the adoption of modern technology. In the case of contractual workers, age has a negative but significant influence on the adoption, whereas annual income, access to government credit, and access to training have positive and significant influences on the adoption of modern technology. As access to training and credit increases the likelihood of the adoption of modern technology for the contractual workers, adequate facilities for such determinants should be made available to the grass root workers. Keywords: Technology adoption; Handloom; Logistic regression; Traditional and modern technologies (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:90:y:2015:i:pb:p:400-409 DOI: 10.1016/j.techfore.2014.04.018 Access Statistics for this article Technological Forecasting and Social Change is currently edited by Fred Phillips More articles in Technological Forecasting and Social Change from Elsevier |
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