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Using Big Data Analytics to Forecast Trade Volumes in Global Supply Chain Management

Using Big Data Analytics to Forecast Trade Volumes in Global Supply Chain Management

Murat Ozemre, Ozgur Kabadurmus
Copyright: © 2019 |Pages: 30
ISBN13: 9781522581574|ISBN10: 152258157X|EISBN13: 9781522581581
DOI: 10.4018/978-1-5225-8157-4.ch004
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MLA

Ozemre, Murat, and Ozgur Kabadurmus. "Using Big Data Analytics to Forecast Trade Volumes in Global Supply Chain Management." Managing Operations Throughout Global Supply Chains, edited by Jean C. Essila, IGI Global, 2019, pp. 70-99. https://doi.org/10.4018/978-1-5225-8157-4.ch004

APA

Ozemre, M. & Kabadurmus, O. (2019). Using Big Data Analytics to Forecast Trade Volumes in Global Supply Chain Management. In J. Essila (Ed.), Managing Operations Throughout Global Supply Chains (pp. 70-99). IGI Global. https://doi.org/10.4018/978-1-5225-8157-4.ch004

Chicago

Ozemre, Murat, and Ozgur Kabadurmus. "Using Big Data Analytics to Forecast Trade Volumes in Global Supply Chain Management." In Managing Operations Throughout Global Supply Chains, edited by Jean C. Essila, 70-99. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-8157-4.ch004

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Abstract

As the supply chains become more global, the operations (such as procurement, production, warehousing, sales, and forecasting) must be managed with consideration of the global factors. International trade is one of these factors affecting the global supply chain operations. Estimating the future trade volumes of certain products for specific markets can help companies to adjust their own global supply chain operations and strategies. However, in today's competitive and complex global supply chain environments, making accurate forecasts has become significantly difficult. In this chapter, the authors present a novel big data analytics methodology to accurately forecast international trade volumes between countries for specific products. The methodology uses various open data sources and employs random forest and artificial neural networks. To demonstrate the effectiveness of their proposed methodology, the authors present a case study of forecasting the export volume of refrigerators and freezers from Turkey to United Kingdom. The results showed that the proposed methodology provides effective forecasts.

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