Abstract:
Clean technolog concept has been widely used since the late eighties in influencing the behavior of firms concerning production activities in a more environmentally friencly direction. As a consequence, many clean technology projects have rapidly diffused and widely been carried out in various countries due to the findings that clean technology is a potential mechanism for creating competitive advantage. Therefore, this technology has been integrated into the strategic plans of various leading firms around the world including the ones in Thailand. Thai govement, with the support from both Thai and foreign organizations that promote the practice of clean technology, campaigned for the adoption of clean technology among firms in Thailand at large in order to preserve the natural environmental and crate advantage for competing with the foreign firms in Thailand at large in order to preserve the natural environmental and crate advantage for competing with the foreign rivals who use the environmental issues as the trade barriers. However, the diffusion rate of clean technology adoption in Thailand remains frustratingly slow and originate the questions of what are the factors that promote the multiplication of clean technology adoption in Thailand at the satisfactory rate. This research aims to studythe effects of institutional factors, organizational factors, and management factors on the adoption of clean technology by manufacturing firms in Thailand. The conceptual framework of the study is developed from the institutional theory,k the resource-based theory, and the diffusion of innovation theory. The sample of this study includes firms in the electrical/electronics industry and food processing industry, which are the major Thai industries with the highest and the second highest export values respectively. Data collection of this study compriese of plant manager interivews, pilot study, and mail survey. There were 190 usable questionnaires. Response rate was 13 percent. Data analyses include descriptive statistics, factor analysis, analysis of variance, bivariate correlation, and stepwise multiple regression analysis.
