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Logistics Modeling and Forecasting with Regression

Logistics Modeling and Forecasting with Regression

Ariadni Papana Dagiasis
Copyright: © 2013 |Pages: 15
ISBN13: 9781466620087|ISBN10: 1466620080|EISBN13: 9781466620094
DOI: 10.4018/978-1-4666-2008-7.ch013
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MLA

Dagiasis, Ariadni Papana. "Logistics Modeling and Forecasting with Regression." Outsourcing Management for Supply Chain Operations and Logistics Service, edited by Dimitris Folinas, IGI Global, 2013, pp. 223-237. https://doi.org/10.4018/978-1-4666-2008-7.ch013

APA

Dagiasis, A. P. (2013). Logistics Modeling and Forecasting with Regression. In D. Folinas (Ed.), Outsourcing Management for Supply Chain Operations and Logistics Service (pp. 223-237). IGI Global. https://doi.org/10.4018/978-1-4666-2008-7.ch013

Chicago

Dagiasis, Ariadni Papana. "Logistics Modeling and Forecasting with Regression." In Outsourcing Management for Supply Chain Operations and Logistics Service, edited by Dimitris Folinas, 223-237. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2008-7.ch013

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Abstract

In this chapter, the method of multiple regression is introduced for describing the functional relationship among several variables, as well as for predicting the values of a variable from the values of a group of variables. The tools for model fitting, model validation, and prediction are presented, while emphasis is given on understanding the types of data that can be analyzed via regression. More specifically, the method of least squares is discussed. Regression analysis is proposed due to its simplicity and wide applicability. Modeling outsourcing or demand forecasting can both be achieved by regression analysis, providing useful information for logistics service providers or 3PL companies. Hauling freight data collected from a logistics company based in Ohio were utilized to demonstrate the applicability of regression analysis and its usefulness for logistics service providers, 3PL companies, and transportation companies. Finally, limitations, solutions, and alternative strategies are discussed.

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