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http://dx.doi.org/10.13106/jafeb.2020.vol7.no10.461

Decision-Making on Incoterms 2020 of Automotive Parts Manufacturers in Thailand  

SURARAKSA, Juthathip (Faculty of Logistics, Burapha University)
AMCHANG, Chompoonut (Faculty of Logistics, Burapha University)
SAWATWONG, Nutcharin (International Trade and Logistics Management Program, Faculty of Logistics, Burapha University)
Publication Information
The Journal of Asian Finance, Economics and Business / v.7, no.10, 2020 , pp. 461-470 More about this Journal
Abstract
The objective of this research is to examine the factors affecting the decision-making of International Commercial Terms (Incoterms) of automotive parts manufacturers in Thailand. This mixed method study applied qualitative and quantitative research methods and utilized the analytical hierarchy process (AHP) to prioritize the significance of the factors. By an in-depth literature review and expert interview, four main criteria were identified. These criteria include Operating costs, Cooperation and bargaining power, Knowledge and understanding and Operation duration then main criteria divided into fifteen sub-criteria. The common Incoterms, Ex Works (EXW), Free On Board (FOB), Free Carrier (FCA), and Cost, Insurance and Freight (CIF), were determined as alternatives to the incoterms through a preliminary survey. The results revealed that the operating costs were the most important factor for the company. Moreover, it was discovered that this was consistent with the priority of the secondary factors, which included the annual budget for the transportation expenses and product value at one time. The respondents' perspective suggested that FCA was the most appropriate Incoterms for international trade for a company. The findings of this research suggest a hierarchy model for organizations to prioritize the significant factors in order to make a decision on the most appropriate Incoterms.
Keywords
Incoterms; Decision Making; Analytical Hierarchy Process; Automotive; International Trade;
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Times Cited By KSCI : 6  (Citation Analysis)
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