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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/6
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Publication Open Access Modelling and analysis of the impact of correlated inter-event data on production control using Markovian arrival processes(Springer, 2019) Department of Business Administration; Department of Industrial Engineering; N/A; Tan, Barış; Dizbin, Nima Manafzadeh; Faculty Member; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Engineering; Graduate School of Business; 28600; N/AEmpirical studies show that the inter-event times of a production system are correlated. However, most of the analytical studies for the analysis and control of production systems ignore correlation. In this study, we show that real-time data collected from a manufacturing system can be used to build a Markovian arrival processes (MAP) model that captures correlation in inter-event times. The obtained MAP model can then be used to control production in an effective way. We first present a comprehensive review on MAP modeling and MAP fitting methods applicable to manufacturing systems. Then we present results on the effectiveness of these fitting methods and discuss how the collected inter-event data can be used to represent the flow dynamics of a production system accurately. In order to study the impact of capturing the flow dynamics accurately on the performance of a production control system, we analyze a manufacturing system that is controlled by using a base-stock policy. We study the impact of correlation in inter-event times on the optimal base-stock level of the system numerically by employing the structural properties of the MAP. We show that ignoring correlated arrival or service process can lead to overestimation of the optimal base-stock level for negatively correlated processes, and underestimation for the positively correlated processes. We conclude that MAPs can be used to develop data-driven models and control manufacturing systems more effectively by using shop-floor inter-event data.Publication Open Access An integrated analysis of capacity allocation and patient scheduling in presence of seasonal walk-ins(Springer, 2018) Çayırlı, Tuğba; Dursun, Pınar; Department of Business Administration; Güneş, Evrim Didem; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 51391This study analyzes two decision levels in appointment system design in the context of clinics that face seasonal demand for scheduled and walk-in patients. The macro-level problem addresses access rules dealing with capacity allocation decisions in terms of how many slots to reserve for walk-ins and scheduled patients given fixed daily capacity for the clinic session. The micro-level problem addresses scheduling rules determining the specific time slots for scheduled arrivals. A fully-integrated simulation model is developed where daily demand actualized at the macro level becomes an input to the micro model that simulates the in-clinic dynamics, such as the arrivals of walk-ins and scheduled patients, as well as stochastic service times. The proposed integrated approach is shown to improve decision-making by considering patient lead times (i.e., indirect wait), direct wait times, and clinic overtime as relevant measures of performance. The traditional methods for evaluating appointment system performance are extended to incorporate multiple trade-offs. This allows combining both direct wait and indirect wait that are generally addressed separately due to time scale differences (minutes vs. days). The results confirm the benefits of addressing both decision levels in appointment system design simultaneously. We investigate how environmental factors affect the performance and the choice of appointment systems. The most critical environmental factors emerge as the demand load, seasonality level, and percentage of walk-ins, listed in the decreasing order of importance.Publication Open Access Modeling and analysis of vessel casualties resulting from tanker traffic through narrow waterways(Wiley, 1999) Otay, Emre N.; Department of Business Administration; Tan, Barış; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600In this paper, we present a physics-based stochastic model to investigate vessel casualties resulting from tanker traffic through a narrow waterway. A state-space model is developed to represent the waterway and the location of vessels at a given time. We first determine the distribution of surface current at a given location of the waterway depending on channel geometry, bottom topography, boundary conditions, and the distribution of wind. Then we determine the distribution of the angular drift for a given vessel travelling at a given location of a waterway. Finally, we incorporate the drift probabilities and random arrival of vessels into a Markov chain model. By analyzing the time-dependent and the steady-state probabilities of the Markov chain, we obtain risk measures such as the probability of casualty at a given location and also the expected number of casualties for a given number of vessels arriving per unit time. Analysis of the Markovian model also yields an analytical result that shows that the expected number of casualties is proportional to square of the tanker arrival rate. We present our methodology on an experimental model of a hypothetical narrow waterway.Publication Open Access Dynamics of price premiums in loyalty programs(Emerald, 2014) Hoch, Stephen J.; Department of Business Administration; Department of Business Administration; Sayman, Serdar; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 112222Purpose - A loyalty program might influence buyer behavior in several ways. Prior research offers evidence that buyers might increase the frequency of purchases and volume per occasion in a loyalty program; however, the effect on buyers' price tolerance has not been studied before. The aim of this paper is to examine buyers' willingness to pay a price premium for a firm offering a loyalty program reward.Design/methodology/approach - An analytical model of dynamic consumer choice is developed, where one of the two selling firms offers a reward for a certain number of purchases. The maximum price premium that a normatively rational buyer should be willing to pay at each level of accumulated purchases is obtained. A price tolerance in controlled settings is obtained and these are compared with normative solutions. Findings - Analytically, it is shown that the maximum price premium increases as purchases are accumulated; and the exact solutions can be found, given the price distributions and program design parameters. In the empirical studies it is found that individuals' maximum premiums are less than the normative levels. On the other hand, as buyers accumulate purchases from the reward offering firm, and get closer to the reward, maximum premiums paid increase - particularly when the reward is immediate. Originality/value - This paper contributes to the loyalty programs literature by examining the price premium, or switching barrier, aspect of buyer response. Furthermore, the paper not only models and solves the normative strategy, but also obtains actual price tolerance in laboratory settings.Publication Open Access Analysis of a group purchasing organization under demand and price uncertainty(Springer, 2018) Department of Business Administration; Department of Industrial Engineering; Tan, Barış; Karabağ, Oktay; Faculty Member; Resercher; Department of Business Administration; Department of Industrial Engineering; College of Administrative Sciences and Economics; College of Engineering; 28600; N/ABased on an industrial case study, we present a stochastic model of a supply chain consisting of a set of buyers and suppliers and a group purchasing organization (GPO). The GPO combines orders from buyers in a two-period model. Demand and price in the second period are random. An advance selling opportunity is available to all suppliers and buyers in the first-period market. Buyers decide how much to buy through the GPO in the first period and how much to procure from the market at a lower or higher price in the second period. Suppliers determine the amount of capacity to sell through the GPO in the first period and to hold in reserve in order to meet demand in the second period. The GPO conducts a uniform-price reverse auction to select suppliers and decides on the price that will be offered to buyers to maximize its profit. By determining the optimal decisions of buyers, suppliers, and the GPO, we answer the following questions: Do suppliers and buyers benefit from working with a GPO? How do the uncertainty in demand, the share of GPO orders in the advance sales market, and the uncertainty in price influence the players' decisions and profits? What are the characteristics of an environment that would encourage suppliers and buyers to work with a GPO? We show that a GPO helps buyers and suppliers to mitigate demand and price risks effectively while collecting a premium by serving as an intermediary between them.Publication Open Access Cyclical dynamics of industrial production and employment: Markov chain-based estimates and tests(Elsevier, 2012) Gencer, Gözde; Department of Business Administration; Tan, Barış; Altuğ, Sumru; Faculty Member; Faculty Member; Department of Business Administration; College of Administrative Sciences and Economics; 28600; N/AThe purpose of this paper is to understand differences in cyclical phenomena across a broad range of developed and emerging countries based on the behavior of two key economic times series—industrial production and employment. The paper characterizes the series in question as a recurring Markov chain. Univariate processes are estimated for each series individually, and a composite indicator is constructed by using information on both series. Based on tests of equality of the estimated Markov chains across countries as well as the expected times to switch between different states, we find evidence that (i) the developed and emerging economies are “de-coupled” from each other in terms of their cyclical dynamics, and (ii) the behavior of industrial production and employment growth are “de-coupled” for the emerging economies. Our results suggest new directions for the analysis of emerging economy cyclical fluctuations.