Identifying Dimensions and Components for Improving Technology Transfer Capabilities in Automotive Safety Systems and Ranking Them Using the Analytic Network Process
الموضوعات : International Journal of Finance, Accounting and Economics Studies
AMIR REZA NAKHAEI
1
,
Soleyman Iranzadeh
2
,
mehrdad hoseinishakib
3
1 - 1- PhD Student, Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran.
2 - 2- Department of Industrial Management, Tabriz Branch, Islamic Azad University, Tabriz, Iran
3 - 3- Department of Industrial Management, Karaj Branch, Islamic Azad University, Karaj, Iran.
الکلمات المفتاحية: Technology, Technology Transfer, Automotive Safety Systems, Analytic Network Process,
ملخص المقالة :
Purpose: The present research aims to identify the components for improving technology transfer capabilities in automotive safety systems and to rank them accordingly.
Design/methodology/approach: A mixed method of structural equation modeling and the Analytic Network Process (ANP) has been employed to achieve this. The technology transfer capabilities were derived from a literature review, previous research, and interviews with experts from these companies. The identification and categorization of the 37 indicators into four dimensions were based on the meticulous design of the research questionnaire. To assess the validity of the theoretical model, factor analysis was conducted using structural equation modeling and PLS software, resulting in the removal of five indicators at this stage.
Findings: The confirmed dimensions and indicators significantly impact the success of the technology transfer process. Furthermore, the ranking of the capabilities influencing the success of the technology transfer process was conducted using the Analytic Network Process and Super Decisions software, revealing that the capability for localization and technology deployment ranked as the highest priority, followed by technology negotiation and acquisition, development and commercialization, and technology identification and selection in subsequent ranks.
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