Browsing by Author "Erkip, Nesim Kohen"

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Open Access
Can accessing much data reshape the theory? Inventory theory under the challenge of data-driven systems
(Elsevier, 2022-08-24) Erkip, Nesim Kohen
In this review, we discuss the data-driven systems and their effects on the implementation of the inventory theory. After overviewing the theory briefly, we group the data-driven approaches to simplify exposition. We consider the use of available data to estimate the parameters of more complex models, and propose developing the theory in that direction, as well. As a pedagogical example, an extension of the standard EOQ model with heterogenous customers is presented. The review proposes a research agenda for inventory problems and concludes with discussing challenges for the future.
Open Access
Designing intervention scheme for vaccine market: A bilevel programming approach
(Springer, 2020-06) Demirci, E. Z.; Erkip, Nesim Kohen
Public-interest goods benefit consumers and also generate external benefits boosting societal welfare. Despite this characteristic of these goods, their level of consumption or production are generally well below the socially desirable levels without intervention. Motivated by influenza vaccine market, this paper examines the intervention design problem for a public-interest good facing yield uncertainty in production as well as inefficiencies in distribution and allocation. The proposed mechanism considers two intervention tools with the aim of resolving the inefficiencies in the system and allowing the actors to take socially desirable decisions. The first tool is to intervene so that demand level for the good is increased; we call it demand increasing strategy. The second tool aims to support the production, allocation, and distribution by investing in research and development and better planning and enhances the availability; we call this as availability increasing strategy. The intervention design problem is based on stylized demand and availability models that take into account investments made to improve them. The model suggested is experimented by a numerical study to analyze the impact of applying proposed joint mechanism in US influenza vaccine market. The results show that proposed strategy is very effectual in terms of vaccination percentages achieved and budget savings realized beyond the current practices, and the improvement in vaccination percentages is even greater when uncertainty in the system is higher. Besides, the results suggest that as long as the parameter calibration and decision problems are solved consistently, availability can be approximated by its average value when necessary.
Open Access
End-of-life inventory management problem: results and insights
(Elsevier, 2021-09-30) Ozyoruk, E.; Erkip, Nesim Kohen; Ararat, Çağın
We consider a manufacturer who manages the end-of-life phase and takes one of the three actions at each period: (1) place an order, (2) use existing inventory, (3) stop holding inventory and use an outside/alternative source. Two examples of this source are discounts for a new generation product and delegating operations. Demand is described by a non-homogeneous Poisson process, and the decision to stop holding inventory is described by a stopping time. After formulating this problem as an optimal stopping problem with additional decisions and presenting its dynamic programming algorithm, we use martingale theory to facilitate the calculation of the value function. Moreover, we show analytical results to understand the additional difficulties of the problem solved, as well as structural results on optimal stopping times. Furthermore, we devise an expandable taxonomy and categorize the models in the literature. Analytical insights from the models as well as an extensive numerical analysis show the value of our approach. The results indicate that the loss can be high in case the manufacturer does not exploit flexibility in placing orders or use an outside source. Several managerial insights are obtained through numerical analysis as well as structural results to facilitate decision-making during the end-of-life horizon. © 2021 Elsevier B.V.
Open Access
Word of mouth on action: analysis of optimal shipment policy when customers are resentful
(Elsevier Ltd, 2023-03-04) Çavdar, Bahar; Erkip, Nesim Kohen
Word-of-Mouth (WoM) communication via online reviews plays a vital role in customers’ purchasing decisions. As such, retailers must consider the impact of WoM to manage customer perceptions and future demand. This paper considers an online shopping system with premium and regular customers. Building on the behavioral and operations management literature, we model customer preferences based on the perceived service quality indicated by WoM and integrate this into the retailer's operational problem to determine a shipment policy regarding the timing of consolidated shipments and the treatment of regular demand. First, we study the e-tailer's problem when they have no knowledge of WoM and only react to the changes in demand. We analyze the long-term behavior of customer demand and show that potential market size and customer sensitivity are the key parameters determining this behavior. Then, we build a model to integrate the knowledge of WoM into operational decision-making and partially characterize the optimal solution. We show that (i) underpromise-and-overdeliver can be a hurtful strategy since it creates a false sense of fast delivery for the regular service, (ii) relaxations in operational constraints may hurt profitability due to the associated difficulties of managing perceptions, and (iii) seeking a stationary policy can lead to suboptimal solutions; therefore, cyclic policies should also be considered when appropriate. © 2023