Factor Analysis of a Decision Making Model for Outsourcing Flexible Automation System in Automotive Industry to SMEs Entrepreneurs and Executives in Thailand

Abstract

       In the current globalization era, in the automotive parts industry. Thailand has become an important hub for automotive parts manufacturing and plays an important role in global economics become to important hub for automotive parts production due to low labor and production costs. In the new era, entrepreneurs and managers are extremely important in building a business survival method in a competitive environment and implementing change. In addition, flexible automation has become an important, as it provides system efficiency,which results in sustainable growth. Outsourcing has become very popular. In general, a sustainable system should have sufficient capacity to provide services without disruption. Especially in an economic crisis. Therefore, this article aims to examine the importance of change management to enable sustainable outsourcing in automotive parts.
          The survey was conducted by using questionnaires to 260 SMEs, at least managers within SMEs manufacturer context. The results suggested significant relationship among SMEs decision to shift toward smart manufacturing by using by the outsourcing. If the changes emanating from outsourcing are managed satisfactorily, it would result in possible free of not disruptions. However, to make changes happen successfully is one of the most challenging tasks faced by the leadership and corporate management of the organizations.
          This research contributes to the knowledge regarding the relationships among SMEs decision to smart manufacturing, flexible automation and benefit of outsourcing. To achieve a high level of SMEs decision to shift toward smart manufacturing in consistent quality, profitability, productivity and growing business to sustainability. SMEs must concentrate on inspirational motivation and utilization to improved manageability, improve flexibility, and achieve to advantage technologies to shift toward smart manufacturing.
            The statistical significance has the highest value of factor loading not lower than 0.819. The significant finding illustrated that factors, mostly affect entrepreneurs’ decision-making are competitive factors in quality, price, durability and quantity or flexibility of flexible automation system. Confirmatory model of the variable in question was consistent with the empirical data considered from 2 = 275.34, df = 251, p-value = 0.13952, RMSEA = 0.018, GFI =0.936 และ AGFI = 0.911