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Copyright by Isabella Marie Gee 2019 the Dissertation Committee for Isabella Marie Gee Certifies That This Is the Approved Version of the Following Dissertation Copyright by Isabella Marie Gee 2019 The Dissertation Committee for Isabella Marie Gee certifies that this is the approved version of the following dissertation: Deliver Me from Waste: Impacts of E-Commerce on Food Supply Chain Energy Use Committee: Michael E. Webber, Supervisor David T. Allen Joshua Apte Kasey M. Faust Katherine E. Lieberknecht Deliver Me from Waste: Impacts of E-Commerce on Food Supply Chain Energy Use by Isabella Marie Gee DISSERTATION Presented to the Faculty of the Graduate School of The University of Texas at Austin in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY The University of Texas at Austin May 2019 I want to thank my friends and family for their unending support during my research. Thank you to my friends for letting me talk about your food and ask about your trash for years. Thank you also to my family; words cannot express how grateful I am for you all. This work is dedicated to you. In particular, I dedicate this to the original Dr. Gee, my Granddad. Acknowledgments I would like to acknowledge everyone who made this work possible. I first want to thank my advisor, Dr. Webber, for your constant support and guidance. Thank you to Dr. Webber and Dr. Faust for providing much of the inspiration for this work through your classes on energy and society as well as system-of-systems analysis. Thank you to Todd Davidson, this dissertation would not be possible without your difficult questions and thoughtful critiques. I also want to thank Pete Pearson, Monica McBride, and everyone at World Wildlife Fund; working with you all helped me define the bigger picture and direction for this dissertation. Thank you to my entire committee for your feedback, suggestions, and edits. Thank you to Catherine Birney, Brittany Speetles, and Kelsey Abel for all of your contributions, and thank you to everyone in the Webber Energy Group and EWRE. This work was sponsored by the George and Cynthia Mitchell Foundation with additional support from the NSF CRISP project. v Deliver Me from Waste: Impacts of E-Commerce on Food Supply Chain Energy Use Isabella Marie Gee, Ph.D. The University of Texas at Austin, 2019 Supervisor: Michael E. Webber An increasing portion of food is purchased online through e-commerce services such as meal-kit and grocery delivery. As these services change the way food is purchased and distributed, they also impact how energy is used along the food supply chain. Impacts will differ based on type of service, location, and consumer habits. In particular, meal-kit and grocery delivery services might impact consumer food waste, packaging waste, and energy consumption for transportation related to deliveries.. This research attempts to assess the potential impact of food delivery services to energy use along the entire food supply chain, accounting for food loss and waste. An analytical model was developed to compare the energy requirements of meal-kit delivery systems to conventional grocery shopping. Meal-kit services can reduce food waste because the kits pre-portion ingredients for each recipe, thereby saving energy. However, the supply chain and packaging requirements of meal-kit delivery are different than for grocery stores, potentially offsetting any reduction of food waste. Furthermore, if meal-kit delivery replaces some trips to the grocery store, then transportation-related savings might be significant. Mass and energy balances were used to assess embedded energy in both pathways. The model was illustrated under representative operating conditions for a consumer in Austin, Texas vi using Monte Carlo simulation. Both per-meal and per-week, a meal-kit delivery service meal is more energy intensive than procuring the same meal from conventional grocery stores primarily due to single-use packaging. Consumer transportation to the grocery store was also found to be particularly energy intensive. Results also indicated that there might be a greater potential to reduce energy use when consumers live further from a grocery store. A second analytical model was developed to compare the energy requirements of grocery delivery services to grocery shopping. Two types of grocery delivery services were considered: decentralized (store-centric) and centralized (warehouse- centric). The supply chains for both store- and warehouse-centric grocery delivery services also differ from conventional grocery shopping, and might offset changes in food waste. Store-centric grocery delivery services primarily affect last-mile trans- portation by replacing a personal trip with a delivery, though they might be able to reduce energy by bundling multiple orders together in one trip. Warehouse-centric grocery delivery services might have a greater impact on energy use because they set up their own separate supply chain with primary fulfillment centers and delivery vehicles. Mass and energy balances were used to assess embedded energy per-week in both pathways. The model was illustrated under two consumer case studies using Monte Carlo simulation. In both cases, the warehouse-centric grocery delivery ser- vice was the least energy intensive. The store-centric grocery delivery service showed slight energy savings. Results suggest that consumer transportation and retail en- ergy use are the two major contributing factors to relative energy intensity between scenarios. Results also indicated that grocery delivery services might be able to save more energy for consumers that live further away from a grocery store. For all food purchase pathways analyzed, consumer last-mile transportation vii (the last leg of the supply chain before food reaches a consumer) was found to be par- ticularly energy intensive. Additionally, results suggested that food delivery services might be able to save more energy for rural consumers. To build off of these findings, a hybrid agent-based and discrete-event simulation modelling framework was devel- oped to capture the last-mile transportation energy use of food delivery services for rural consumers. The framework operates in a geographic information system (GIS) space and tracks per-trip energy use of a delivery van and delivery car operating in a sample neighborhood in west Austin, TX. A sensitivity analysis was performed to gauge the impact of vehicle speed and number of orders fulfilled on per-trip energy use. In general, the delivery van trip was always more energy intensive than the delivery car over the range of values studied. However, results indicated that there is a theoretical threshold based on consumer demand and density that dictates when van- or car-based delivery is energetically preferable. Taken together, this body of work provides methods for evaluating the farm- to-fork energy impacts of food delivery services, with particular attention to last-mile transportation. viii Table of Contents Acknowledgments v Abstract vi List of Tables xii List of Figures xiii Chapter 1. Introduction 1 1.1 Motivation . .1 1.2 Scope and organization of dissertation . .4 Chapter 2. Literature Review and Background Information 6 2.1 Meal-kit Delivery Services . .6 2.1.1 Meal-Kit History . .8 2.1.2 Purchasing Power of Millennial Urbanites . .9 2.1.3 Packaging, Produce, and Sustainability . 10 2.1.4 Environmental Impacts of Meal-Kits . 12 2.2 Grocery Delivery Services . 15 2.2.1 Online Grocery History . 17 2.2.2 Warehouses and Automation . 17 2.2.3 Fresh Food . 20 2.2.4 Environmental Impact of Online Grocery . 21 2.3 The Food Supply Chain and System of Systems Modeling . 30 2.3.1 Discrete Event Simulation . 30 2.3.2 Agent Based Modeling . 31 2.3.3 Hybrid Modeling Techniques . 31 Chapter 3. Comparison of Embedded Energy for Meal-kit Delivery Services and Traditional Grocery Shopping 34 3.1 Introduction . 34 3.2 Methods . 35 3.2.1 Total Meal Energy . 36 ix 3.2.2 Energy for Agriculture . 37 3.2.3 Energy for Retail . 38 3.2.4 Energy for Storage . 43 3.2.5 Energy for Transportation . 45 3.2.6 Energy for Packaging . 51 3.2.7 Model Inputs . 51 3.2.8 Sensitivity Analysis . 53 3.2.9 Model Illustration . 54 3.2.10 Geographic Illustration . 55 3.3 Results and Discussion . 55 3.3.1 Sensitivity Analysis . 55 3.3.2 Model Illustration . 62 3.3.3 Geographic Illustration . 69 Chapter 4. Comparison of Embedded Energy for Grocery Delivery Services and Traditional Grocery Shopping 79 4.1 Introduction . 79 4.2 Methods . 80 4.2.1 Total Per-Week Energy . 82 4.2.2 Energy for Agriculture . 84 4.2.3 Energy for Transportation . 85 4.2.4 Energy for Retail . 89 4.2.5 Energy for Storage . 93 4.2.6 Energy for Packaging . 95 4.2.7 Model Inputs . 96 4.2.8 Case Studies . 98 4.2.9 Model Implementation . 100 4.2.10 Geographic Illustration . 100 4.3 Results and Discussion . 101 4.3.1 Case Studies . 101 4.3.2 Warehouse-Centric Grocery Delivery . 107 4.3.3 Store-Centric Grocery Delivery . 113 4.3.4 Geographic Illustration . 121 x Chapter 5. Methods for Determining Energy Use of Last-Mile Trans- portation for Food Delivery Services in Rural Communi- ties 127 5.1 Introduction . 127 5.1.1 Last-Mile Transportation Energy Use . 128 5.1.2 Rural Food Delivery . 130 5.1.3 Hybrid Modeling Approach . 131 5.2 Methodology and Development . 133 5.2.1 Model Implementation . 138 5.2.2 Validation and Verification . 145 5.2.3 Assumptions and Limitations . 146 5.3 Results and Discussion . 149 5.4 Summary . 153 Chapter 6. Conclusions 155 6.1 Meal-Kit Delivery Conclusions . 155 6.2 Grocery Delivery Conclusions . 157 6.3 Last-Mile Food Delivery Conclusions . 160 6.3.1 Final Conclusions . 162 Bibliography 163 xi List of Tables 2.1 Studies comparing energy for traditional retail and e-commerce .
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