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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6
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Publication Open Access An investigation of time-inconsistency(Informs, 2009) Öncüler, Ayşe; Department of Business Administration; Department of Business Administration; Sayman, Serdar; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 112222Preference between two future outcomes may change over time-a phenomenon labeled as time inconsistency. The term "time inconsistency" is usually used to refer to cases in which a larger-later outcome is preferred over a smaller-sooner one when both are delayed by some time, but then with the passage of time a preference switches to the smaller-sooner outcome. The current paper presents four empirical studies showing that time inconsistency in the other direction is also possible: A person may prefer the smaller-sooner outcome when both options are in the future, but decide to wait for the larger-later one when the smaller option becomes immediately available. We. find that such "reverse time inconsistency" is more likely to be observed when the delays to and between the two outcomes are short (up to a week). We propose that reverse time inconsistency may be associated with a reversed-S shape discount function, and provide evidence that such a discount function captures part of the variation in intertemporal preferences.Publication Open Access Capacity planning for effective cohorting of hemodialysis patients during the coronavirus pandemic: a case study(Elsevier, 2023) Bozkır, C.D.C.; Özmemiş, C.; Kurbanzade, A.K.; Balçık, B.; Tuğlular, S.; Department of Business Administration; Güneş, Evrim Didem; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 51391Planning treatments of different types of patients have become challenging in hemodialysis clinics during the COVID-19 pandemic due to increased demands and uncertainties. In this study, we address capacity planning decisions of a hemodialysis clinic, located within a major public hospital in Istanbul, which serves both infected and uninfected patients during the COVID-19 pandemic with limited resources (i.e., dialysis machines). The clinic currently applies a 3-unit cohorting strategy to treat different types of patients (i.e., uninfected, infected, suspected) in separate units and at different times to mitigate the risk of infection spread risk. Accordingly, at the beginning of each week, the clinic needs to allocate the available dialysis machines to each unit that serves different patient cohorts. However, given the uncertainties in the number of different types of patients that will need dialysis each day, it is a challenge to determine which capacity configuration would minimize the overlapping treatment sessions of different cohorts over a week. We represent the uncertainties in the number of patients by a set of scenarios and present a stochastic programming approach to support capacity allocation decisions of the clinic. We present a case study based on the real-world patient data obtained from the hemodialysis clinic to illustrate the effectiveness of the proposed model. We also compare the performance of different cohorting strategies with three and two patient cohorts.Publication Open Access Modeling and analysis of an auction-based logistics market(Elsevier, 2008) Ağralı, Semra; Department of Business Administration; Department of Industrial Engineering; Tan, Barış; Karaesmen, Fikri; Faculty Member; Faculty Member; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Engineering; 28600; 3579We consider a logistics spot market where the transportation orders from a number of firms are matched with two types of carriers through a reverse auction. In the spot market, local carriers compete with in-transit carriers that have lower costs. In order to analyze the effects of implementing a logistics spot market on these three parties: firms, local carriers, and in-transit carriers and also the effects of various system parameters, we develop a two-stage stochastic model. We first model the auction in a static setting and determine the expected auction price based on the number of carriers engaging in the auction and their cost distributions. We then develop a continuous-time Markov chain model to evaluate the performance of the system in a dynamic setting with random arrivals and possible abandonment of orders and carriers. By combining these two models, we evaluate the performance measures such as the expected auction price, price paid to the carriers, distribution of orders between local and in-transit carriers, and expected number of carriers and orders waiting at the logistics center in the long run. We present analytical and computational results related to the performance of the system and discuss operation of such a logistics spot market in Turkey.Publication Open Access A method for estimating stock-out-based substitution rates by using point-of-sale data(Taylor _ Francis, 2009) Öztürk, Ömer Cem; Department of Business Administration; Tan, Barış; Karabatı, Selçuk; Faculty Member; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600; 38819Empirical studies in retailing suggest that stock-out rates are quite high in many product categories. Stock-outs result in demand spillover, or substitution, among items within a product category. Product assortment and inventory management decisions can be improved when the substitution rates are known. In this paper, a method is presented to estimate product substitution rates by using only Point-Of-Sale (POS) data. The approach clusters POS intervals into states where each state corresponds to a specific substitution scenario. Then available POS data for each state is consolidated and the substitution rates are estimated using the consolidated information. An extensive computational analysis of the proposed substitution rate estimation method is provided. The computational analysis and comparisons with an estimation method from the literature show that the proposed estimation method performs satisfactorily with limited information.Publication Open Access Front-office multitasking between service encounters and back-office tasks(Elsevier, 2020) Legros, Benjamin; Jouini, Oualid; Koole, Ger; Department of Business Administration; Karaesmen, Zeynep Akşin; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 4534We model the work of a front-line service worker as a queueing system. The server interacts with customers in a multi-stage process with random durations. Some stages require an interaction between server and customer, while other stages are performed by the customer as a self-service task or with the help of another resource. Random arrivals by customers at the beginning and during an encounter create random lengths of idle time in the work of the server (breaks and interludes respectively). The server considers treatment of an infinite amount of back-office tasks, or tasks that do not require interaction with the customer, during these idle times. We consider an optimal control problem for the server's work. The main question we explore is whether to use the interludes in service encounters for treating back-office, when the latter incur switching times. Under certain operating environments, working on back-office during interludes is shown to be valuable. Switching times play a critical role in the optimal control of the server's work, at times leading the server to prefer remaining idle during breaks and interludes, instead of working on back-office, and at others to continue back-office in the presence of waiting customers. The optimal policy for use of the interludes is one with multiple thresholds depending on both the customers queueing for service, and the ones who are in-service. We illustrate that in settings with multiple interludes in an encounter, if at all, the back-office work should be concentrated on fewer, longer and later interludes.Publication Open Access Design of balanced energy savings performance contracts(Taylor _ Francis, 2020) Department of Business Administration; Department of Industrial Engineering; Tan, Barış; Faculty Member; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Engineering; 28600Energy savings performance contracts between the energy users and the energy service companies (ESCO) are used to finance energy efficiency investments by using the future energy savings that will result from these investments. We present an analytical model to characterise the energy savings performance contracts and discuss how the risks of estimating the energy savings affect the energy user and the service provider. This characterisation allows determination of the contract parameters for a balanced contract with the information about the energy savings that are expected from the planned energy-efficiency investments. Since it is difficult to get the statistical information about the energy savings before investing in an energy-efficiency project, we develop a distribution-free contract that sets the guaranteed energy savings level based on the mean and the standard deviation of the energy savings and the profit-sharing ratio between the ESCO and the energy user. We show that a simple distribution-free balanced contract performs satisfactorily when the distribution of the energy savings is not known and its mean and the standard deviation are estimated with error. Our analytical results show that the energy savings contracts with the right parameters can mitigate the risks related to realisation of the anticipated energy savings.Publication Open Access On the benefits of assortment-based cooperation among independent producers(Wiley, 2008) Department of Business Administration; Tan, Barış; Akçay, Yalçın; Faculty Member; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600; 51400Motivated by the challenges small- to medium-size companies face in export-oriented industries, we consider a competitive market for a set of substitutable products. Depending on the assortment of the firms and the substitution behavior of the customer, either a product is sold to the customer or the sale is lost. We consider the cooperation of independent producers that offer a combined set of products to their customers. Producers use discounted price contracts to manage the exchange of products among themselves. We propose an analytical model that enables us to determine the characteristics of firms and their products that would facilitate a beneficial cooperation. We conclude that a cooperation between symmetric single-product firms is always beneficial, whereas threshold-type criteria should be satisfied so that assortment-based cooperation is beneficial for asymmetric firms. We also show that commonality in product assortments of cooperating firms has adverse effects on the benefit from cooperation. For the most general problem setting, we propose a method to determine the set of firms that should cooperate and set the parameters of the contract among the members of cooperation in such a way that each member of the cooperation is better off. We use a numerical study to draw insights on the conditions for which our cooperation scheme is beneficial in the most general problem setting.Publication Open Access Formulation and a two-phase matheuristic for the roaming salesman problem: application to election logistics(Elsevier, 2020) Shahmanzari, Masoud; Salhi, Said; Department of Business Administration; Aksen, Deniz; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 40308In this paper we investigate a novel logistical problem. The goal is to determine daily tours for a traveling salesperson who collects rewards from activities in cities during a fixed campaign period. We refer to this problem as the Roaming Salesman Problem (RSP) motivated by real-world applications including election logistics, touristic trip planning and marketing campaigns. RSP can be characterized as a combination of the traditional Periodic TSP and the Prize-Collecting TSP with static arc costs and time-dependent node rewards. Commercial solvers are capable of solving small-size instances of the RSP to near optimality in a reasonable time. To tackle large-size instances we propose a two-phase matheuristic where the first phase deals with city selection while the second phase focuses on route generation. The latter capitalizes on an integer program to construct an optimal route among selected cities on a given day. The proposed matheuristic decomposes the RSP into as many subproblems as the number of campaign days. Computational results show that our approach provides near-optimal solutions in significantly shorter times compared to commercial solvers.Publication Open Access Production control with backlog-dependent demand(Taylor _ Francis, 2009) Gershwin, Stanley B.; Veatch, Michael H.; Department of Business Administration; Tan, Barış; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600A manufacturing firm that builds a product to stock to meet a random demand is studied. Production time is deterministic, so that if there is a backlog, customers are quoted a lead time that is proportional to the backlog. In order to represent the customers' response to waiting, a defection functionthe fraction of customers who choose not to order as a function of the quoted lead timeis introduced. Unlike models with backorder costs, the defection function is related to customer behavior. Using a continuous flow control model with linear holding cost and Markov modulated demand, it is shown that the optimal production policy has a hedging point form. The performance of the system under this policy is evaluated, allowing the optimal hedging point to be found.Publication Open Access Agricultural planning of annual plants under demand, maturation, harvest, and yield risk(Elsevier, 2012) Department of Industrial Engineering; Tan, Barış; Faculty Member; Department of Industrial Engineering; College of Engineering; College of Administrative Sciences and Economics; N/A; 28600In this study we present a planning methodology for a firm whose objective is to match the random supply of annual premium fruits and vegetables from a number of contracted farms and the random demand from the retailers during the planning period. The supply uncertainty is due to the uncertainty of the maturation time, harvest time, and yield. The demand uncertainty is the uncertainty of weekly demand from the retailers. We provide a planning methodology to determine the farm areas and the seeding times for annual plants that survive for only one growing season in such a way that the expected total profit is maximized. Both the single period and the multi period cases are analyzed depending on the type of the plant. The performance of the solution methodology is evaluated by using numerical experiments. These experiments show that the proposed methodology matches random supply and random demand in a very effective way and improves the expected profit substantially compared to the planning approaches where the uncertainties are not taken into consideration. (c) 2012 Elsevier B.V. All rights reserved.
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