Identifying the Factors of Technological Capability Assessment – Case study Pressing parts Manufacturing Department of Iran Khodro1

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تعداد صفحات :۱۸

چکیده مقاله:

Considering the increasing role of technology in competition development along with economic growth, technological capability assessment in developed countries has come under the spotlight. Comprehensive knowledge of firm- level technological capability and its proper employment is one of the most significant factors in efficient application of technology to acquire the competition advantages. Technological needs assessment is an appropriate tool by which the required capabilities for technological priorities implementation are identified. Automotive industry as a technology—based industry is among the significant and strategic industries in today s world. The present study is aimed at prioritizing technological capabilities assessment indicators in order to assess technological capabilities and strategic planning in pressing parts manufacturing department of Iran khodro. Thus, concerning the importance of technological capability assessment and the issue of strategic planning and their close relation, this research identifies andprioritizes the appropriate indicators of technological capability assessment in automotive industry and pressing parts manufacturing department. The outcome of this prioritization is of great help to formulation of future policies in this department. In this study,subsequent to the review of literature, 36 indicators proper for the research were identified. After designing the questionnaire based on the aforementioned indicators, and verifying its validity by the experts, 123questionnaires were collected. Then the questionnaire reliability was confirmed using Cronbach’s alfa and the correlation of the data for factor analysis was ensured employing KMO and Bartlett’s test. Following these procedures,exploratory factor analysis was carried out and the 23 indicators under study were classified into 6 factors and prioritized according to their factor loadings.