Faculty of Business

Permanent URI for this communityhttps://hdl.handle.net/10679/4

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Analysis of customer switching behavior in omni-channel retailing
(Institute of Industrial and Systems Engineers, IISE, 2020) Cesaret, Bahriye; Bayram, A.; Business Administration; CESARET, Bahriye
Omni-channel retailing is a recent approach that allows customers to purchase products from anywhere and return them anywhere and allows retailers to fulfill orders from anywhere. This flexibility improves the customer experience by integrating all channels, allows retailers to achieve more availability and drives the sales and traffic of the retailers. In this study, we consider two omni-channel implementations: (i) ship-from-store, and (ii) home delivery, by considering customer switching behavior across the sales channels. Store customers can be fulfilled in store or they can ask for home delivery. Online orders, on the other hand, can be shipped either from the fulfillment center or from any other store location that maximizes the overall profit of the retailer. We further consider that both store and online customers can switch across channels. We build a dynamic programming framework to investigate optimal fulfillment decisions for both online and store orders. We incorporate the uncertainty both in demand and in the cost of shipment to individual customers. We present our results through optimal fulfillment strategies and numerical experiments.
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Carrier selection for Less-Than-Truckload (LTL) shipments
(Elsevier, 2021) Konur, D.; Yıldırım, G.; Cesaret, Bahriye; Business Administration; CESARET, Bahriye
This chapter reviews the basics of carrier selection for less-than-truckload (LTL) shipments. First, the impacts of LTL carrier selection on various strategic, tactical, and operational supply chain planning decisions are discussed. Then, the key principles of LTL carriers and the key carrier attributes LTL shippers account for in their selection of LTL carriers are summarized. A numerical study using a continuous review inventory control model under stochastic demand is presented in order to demonstrate the effects of four key LTL carrier attributes (transit time, transit time variability, and freight minimums and maximums) on a shipper's cost and service level.
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Curb space management in urban mobility system
(Springer Nature, 2019) Yu, M.; Bayram, A.; Cesaret, Bahriye; Business Administration; Fathi, M.; Khakifirooz, M.; Pardalos, P. M.; CESARET, Bahriye
Curb space management and traffic flow are two important elements of the transportation system that interact with each other and affect the overall system performance. Moreover, the growth of new mobility operators and goods delivery in urban result in a growing demand for pickup/drop off access to the curb sides. The curb space is now also a spot for pickup/drop off passengers and loading/unloading goods. Thus, the traditional use of curb space for parking only is challenged and it becomes important to manage the curb space effectively and determine the optimal capacity decisions for different uses. Our study investigates the allocation of curb space for various uses so that the overall transportation system performance can be enhanced. We simulate the transportation system and analyze the interactions between traffic flow and curb space usage. We propose optimal capacity allocation decisions that ensure a smooth traffic flow. We derive optimal curb space allocation policies that vary according to the customer demand during the day.
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On member‐driven, efficient and fair timeshare exchanges
(Wiley, 2019-01) Cesaret, Bahriye; Dawande, M.; Rajapakshe, T.; Business Administration; CESARET, Bahriye
Vacation Timeshare is a form of ownership or "right to use" of a resort property for a specific time period (typically a week) each year. Timeshare exchange refers to the non-monetary trading of timeshare weeks among owners, so that they can interchange their vacation homes to experience new destinations. The need for member participation during the exchange process has been well-recognized for a variety of practical reasons, including the reluctance of members to accept an authoritarian solution that does not provide any information about the exchange process and their desire to experience some control over the process. Another important need is to ensure that, given the members' preferences, an exchange solution offers collectively the best-possible improvement over their currently-owned weeks, while being "fair" to all participants. We suggest two objectives to capture the efficiency and fairness of an exchange solution. For the resulting bi-criteria problem, we show that a solution that is simultaneously near-optimal on both objectives may not exist. Our main contribution is an efficient algorithm in which (i) each member uses her private preference list to communicate with other members, and the members, through such communications, collectively achieve an individually rational allocation, and (ii) for any desired approximation bounds alpha and beta on, respectively, efficiency and fairness, the following property holds: if an (alpha, beta)-approximate solution exists, then the solution provided by the algorithm satisfies this approximation guarantee; otherwise, the solution is an alpha-approximation on the efficiency measure and, among all such allocations, has the best fairness measure.
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Order fulfillment policies for ship-from-store implementation in omni-channel retailing
(Elsevier, 2021-11-01) Bayram, A.; Cesaret, Bahriye; Business Administration; CESARET, Bahriye
One of the recent trends in omni-channel retailing is ship-from-store which allows a retailer to fulfill online orders by using inventory from a nearby store. The benefits of this fulfillment model include faster delivery, lower shipment costs, higher in-stock probability, increased sales and customer satisfaction, etc. Despite its many benefits, this fulfillment model introduces many new operational challenges to the retailer, including the need to identify from which location to fulfill an online order when it arrives. In this study, we consider a retailer having both online and store operations, with each channel carrying its own inventory. Store orders are fulfilled from store inventories, whereas an online order can be shipped either from an online fulfillment center or from any other store that maximizes the retailer's overall profit. Our study investigates dynamic fulfillment decisions: from which location to fulfill an online order when it arrives. We incorporate the uncertainty both in demand and in the cost of shipment to individual customers to characterize the optimal cross-channel fulfillment policy. Due to the optimal policy being computationally intractable for large-sized problems, we construct an intuitive heuristic policy to guide the retailers in their fulfillment decisions. We find that the proposed heuristic method is effective and obtains solutions within a reasonable amount of time for the cross-channel fulfillment problem.
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Selecting a winning team: Management of surgical team composition in robotic surgery
(Elsevier, 2023-01) Bayram, A.; Solak, S.; Harmanli, O.; Cesaret, Bahriye; Business Administration; CESARET, Bahriye
Surgical robots can offer higher precision, flexibility, and control during surgeries compared to conventional approaches. Robotic surgeries lead to a decrease in surgical error rates, lengths of hospital stays, and patient recovery times. The effectiveness of robotic surgeries depends on many factors, including the individual performance of team members. Although the experience of every team member makes a difference, the performance in the operating room depends as well on the cohesion among surgical team members. In this study, we address a team composition problem in robotic surgery in which we evaluate the efficiency of an operating room by assessing individual and dependent performances of surgical team members. We build a two-stage stochastic programming model, where the team members’ performance values are stochastic, to decide on team compositions. We propose two easy-to-implement algorithms based on implementations of data analyses and a stochastic programming model to identify surgical team compositions where the resulting computational difficulties are addressed through the Lagrangian decomposition procedure. We also describe computational results based on actual historical data, which indicate that the operating room time and surgical team performances can be improved if the proposed policies are implemented. With the model developed, surgical team composition decisions can be made more systematically and effectively. We also highlight the importance of considering individual and dependent performances of all surgical team members on operating room time and overall team performance.
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Ship-from-store operations in omni-channel retailing
(Institute of Industrial Engineers, 2017) Bayram, A.; Cesaret, Bahriye; Business Administration; Coperich, K.; Nembhard, H.; Cudney, E.; CESARET, Bahriye
One of the recent trends in omni-channel retailing is ship-from-store which allows a retailer to fulfill online orders from a brick-and-mortar store. The benefits of this relatively new fulfillment model includes faster delivery, lower transportation costs, higher in-stock probability, increased sales and customer service, etc. Despite the many benefits, the model introduces many new operational challenges to the retailer. Retailer needs to identify which stores should be integrated as active fulfillment centers, and from which location to satisfy an online order when it arrives. Best Buy, Macy's and Walmart successfully integrate ship-from-store to their fulfillment strategies. We consider a retailer having both online and store operations and each channel carrying its own inventory. Store orders are fulfilled from store inventories, but for an online order the retailer can ship either from the online distribution center or from any other store location that maximizes the overall profit. Our study investigates dynamic fulfillment decisions: from which location to fulfill an online order when it arrives. We incorporate the uncertainty both in demand and in the cost of shipment to individual customers. We develop a stochastic dynamic framework and present some results on optimal fulfillment strategies.

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