Hyperconnected fulfillment and inventory allocation and deployment models
Kim, Na Yeon
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Consumption patterns have been changed dramatically over the past decades, notably by the growth of e-commerce. With the prevalence of e-commerce and home delivery, customer expectations for a faster, punctual, and cheap delivery are increasing. In fact, many customers are expecting for same-day or x-hour deliveries now and offering fast delivery becomes more and more critical for e-retailers to survive in a fierce market competition. However, many companies are simply lacking financial, physical, and/or operational resources to increase their responsiveness. Focusing on solving the challenges in the perspective of fulfillment and inventory, we aim to find a breakthrough from a recently emerging logistics innovation movement induced by the introduction of the Physical Internet (PI). PI can potentially enable responsive yet affordable fulfillment for companies of any size through open asset utilization and multi-player operations. The key of PI innovation is transforming asset-driven logistics operations to service-driven logistics operations. This thesis provides an academic foundation for hyperconnected fulfillment to effectively satisfy the growing customer expectations on responsive deliveries. We first present a comprehensive design and evaluation of a hyperconnected fulfillment system. Then, we focus on providing inventory operations models, inventory allocation and deployment respectively, which maximally utilize the key features of hyperconnected fulfillment system: connectivity, flexibility, and decentralization. In Chapter 2, a hyperconnected fulfillment and delivery system is designed in the context of the last-mile operations in urban areas. A comprehensive system and decision architecture of the hyperconnected system is modeled. We carefully design the scenarios to show a gradual transformation from dedicated to hyperconnected system in each thread of delivery and fulfillment so as to reveal the marginal impact of each step of transformation. We conduct a scenario analysis using a simulation platform built upon the system and decision architecture where autonomous agents are optimizing their decisions and interact with the environment. The experimental results clearly demonstrate the potential benefit of hyperconnected urban fulfillment and delivery system by concurrently improving often opposing performance criteria: economic efficiency, service capability and sustainability. Chapter 3 tackles an optimal inventory allocation problem among multiple sales outlets. Specifically, we analyze a case where a dropshipper allocates availability to multiple e-retailers via availability promising e-contracts (APCs). Under the APC, the e-retailers do not observe actual availability and this information asymmetry leads them to pose a promised availability threshold (PAT). PAT is a threshold on remaining promised availability set by an e-retailer for a product of a dropshipper, below which the e-retailer unlists the product and thus does not accept any more orders from customers, until the promised availability is climbed above the threshold by the dropshipper. The dropshipper's APC problem with PAT is modeled as 2-stage stochastic program with two stochastic parameters: demand and PAT. We design and evaluate three contract policies differentiated by the allowance level for overpromising: guaranteed fulfillment, controlled fillrate, and penalty-driven fillrate policies. We also present a modeling approach to convert the endogenous demands, per-retailer-distribution of which is affected by the APCs, to exogenous demands with linear substitution constraints. The numerical results show the penalty-driven fillrate policy is the dominating strategy for dropshippers especially under a lean availability. Chapter 4 tackles an inventory deployment problem under the context of open asset utilization and responsive fulfillment. When it comes to very responsive deliveries, such as X-hour deliveries, the physical availability of inventories near the delivery locations becomes necessary, which requires a broad and dense fulfillment network. The open asset utilization and service-driven fulfillment operations of the PI can enable affordable access to such decentralized fulfillment network comprised of the open fulfillment centers. We evaluate the benefit of such decentralized fulfillment network for a responsive fulfillment and develop an appropriate inventory deployment model, which possesses a partially pooled demand and inventory structure induced by responsiveness requirements, as a variant of Newsvendor. We derive a pragmatic heuristic inventory solution, W-solution, and present an efficient binary search based solution heuristic, W-heuristic. Then, via numerical experiments over both theoretical and empirical demand distributions, we demonstrate the advantage of decentralized network and w-solution over centralized network and allocation-based inventory model, pre-allocation model, respectively. We also report rather counter-intuitive observations that the w-solution which accounts for pooling leads to more inventory than pre-allocation model which does not account for pooling under low sales margin.
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