Doctoral Dissertations
Date of Award
5-2023
Degree Type
Dissertation
Degree Name
Doctor of Philosophy
Major
Business Administration
Major Professor
Theodore P. Stank, Lance W. Saunders
Committee Members
Stephanie Eckerd, Jason Merrick, Tom Goldsby
Abstract
This thesis investigates supply chain planning and how firms can utilize it for improved performance. There are three distinct essays. The first examines a firm’s actions in the months following the COVID-19 pandemic, providing the first empirical evidence of the efficacy of resilience techniques. The demand during this period increased significantly, requiring changes to the firm’s operating plans. We built a simulation which allowed for investigation into how each action taken by the firm allowed for a return to normal business operations. We found that planning actions, specifically shortening the forecast length and integrating demand information more frequently, rather than physical changes such as reducing the number of products offered and adding an extra work day, permitted the firm to respond quickly to the demand changes and meet customer expectations. The second essay examines how firms in the customization market can use supplier lead time performance to improve customer lead time performance. Using data from a large Make-To-Order company, we first segment components based on planned lead time and lead time deviation. We then use a simulation to investigate how different buffering and bridging actions on each segmentation of components impacts customer lead time. We find that each group of components provide threats and opportunities to the firm, giving guidance on how firms can manage their suppliers to reduce customer lead time. The final essay investigates planner biases after an increase in volatility in their supply chains. Increases in demand volatility can occur in such instances as disruptions, items going viral on social media, or increased offerings of similar products. Using knowledge activation theory as the lens, we explored what information is ‘activated’ and used in ordering decisions when demand volatility increases. Specifically, we use a multi-period newsvendor experiment to investigate if the original volatility of a supply chain or experience with a prior increase in volatility impacts ordering decisions. 193 planners from seven different companies took the experiment, revealing that planners from originally high volatile supply chains and who have experience with an increase in volatility perform better than those from low volatility supply chains with no experience.
Recommended Citation
Dohmen, Anne Elizabeth, "Leveraging Supply Chain Planning for Improved Supply Chain Performance. " PhD diss., University of Tennessee, 2023.
https://trace.tennessee.edu/utk_graddiss/8147