Date of Graduation

5-2024

Document Type

Thesis

Degree Name

Bachelor of Science in Data Science

Degree Level

Undergraduate

Department

Data Science

Advisor/Mentor

Schubert, Karl

Committee Member/Reader

Wolf, Jared

Committee Member/Second Reader

Petris, Giovanni

Abstract

This project focuses on JB Hunt Transport Inc's intermodal business unit (JBI) by focusing on the challenges associated with Published Pricing and Contractual Pricing. The primary issue revolves around the variance between the awarded freight volumes in Requests for Pricing (RFPs) and the actual volumes realized when the freight is shipped. This discrepancy poses challenges for effective sales planning, revenue goals, and optimal freight network management within JBI. Reporting tools, such as PowerBI, are currently used by JBI to provide insights into award compliance on a weekly basis. However, our goal with this project was to provide a deeper understanding by examining a variety of subsets of customers, lanes, and industries in the data to identify patterns of primary award compliance. Any specific subsets with predictive power are used as inputs for the OASIS optimization engine, used to maximize network profitability.

The analysis includes categorizing national accounts and lanes into industries and assessing the consistency of award compliance seen across different combinations. The study also investigates the seasonality of primary award compliance, focusing on specific industries and customer accounts. This allows us to examine the correlation between primary award volumes and compliance, utilizing subsets based on multiples of key numerical values. This analysis was designed to uncover predictability in the data, which was used to create preliminary predictive models for subsets of the data that exhibit consistent award compliance. Any finds

My individual contributions to this project mainly include comprehensive boxplot analyses, offering nuanced insights for the group into the distribution and variability of award compliance across different customer and lane subsets. I also ran Granger causality tests to explore potential causal relationships between various factors and award compliance, providing a deeper understanding of the interaction effects between factors and across industries. Overall, my individual contributions in the statistical analysis ­­—boxplot analysis and Granger causality testing— contributed to the broader objectives of this capstone project, such as enhancing the group’s understanding of factors influencing award compliance which led to informed decision-making and recommendations for JB Hunt Transport Inc's intermodal business unit.

Keywords

statistical analysis, intermodal transportation, transportation logistics, predictive models

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Available for download on Tuesday, April 29, 2025

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