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ÖZEN, Ulaş

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Ulaş

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ÖZEN
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Now showing 1 - 5 of 5
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    Setting the right incentives for global planning and operations
    (Elsevier, 2016-09-01) Norde, H.; Özen, Ulaş; Slikker, M.; Management Information Systems; ÖZEN, Ulaş
    We study incentive issues seen in a firm performing global planning and manufacturing, and local demand management. The stochastic demands in local markets are best observed by the regional business units, and the firm relies on the business units' forecasts for planning of global manufacturing operations. We propose a class of performance evaluation schemes that induce the business units to reveal their private demand information truthfully by turning the business units' demand revelation game into a potential game with truth telling being a potential maximizer, an appealing refinement of Nash equilibrium. Moreover, these cooperative performance evaluation schemes satisfy several essential fairness notions. After analyzing the characteristics of several performance evaluation schemes in this class, we extend our analysis to include the impact of effort on demand.
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    Economic models of sponsored content in wireless networks with uncertain demand
    (Wiley, 2014-09-09) Andrews, M.; Özen, Ulaş; Reiman, M. I.; Wang, Q.; Management Information Systems; ÖZEN, Ulaş
    This chapter evaluates an approach whereby the service provider can tap into an alternative source of revenue, originating from sales of advertisements or products and channelled by the content provider in the form of sponsorship of viewing. It presents a simple economic model in which service provider congestion costs, end user (EU) bandwidth costs, and the price that the content provider must pay for sponsoring content are all determined on a per-byte basis. A key feature of the model is that the content has uncertain demand. The chapter focuses on the relationship between the service provider and a single content provider. It also presents a numerical example to demonstrate how the optimization might work in practice. The chapter indicates how the results can be adapted for the case of EU quotas. In most current wireless data plans, the EUs pay a certain fee for a fixed quota of data.
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    Tactical inventory planning at alcatel-lucent’s repair and exchange services
    (Informs, 2015-05-01) Doğru, M. K.; Özen, Ulaş; Management Information Systems; ÖZEN, Ulaş
    Alcatel-Lucent, a major telecommunications equipment manufacturer, provides equipment, solutions, and services to customers worldwide. Post-sales support services are a growing business segment for the company, and require significant investment in spare parts. The inventory investment constitutes a considerable portion of the total cost of providing post-sales support services for new customer contracts; it is also an important element in estimating new contract offerings and evaluating and redesigning business processes that affect inventories. Because of Alcatel-Lucent's two-echelon supply chain structure, inventory sizing for post-sales support services is a complicated task that spreadsheet applications cannot handle adequately. Thus, the company's repair and exchange services (RES) group needed a fast, user-friendly, and generic software solution with advanced analytic capabilities to support its business tendering and evaluation processes. To meet this requirement, we developed the tactical inventory planning tool, which uses stochastic modeling and optimization algorithms, for this purpose. Although the tool's primary function is to support the RES business tendering process, it has also been useful in other business analysis because of its generic nature.
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    Conference paperPublicationMetadata only
    Economic models of sponsored content in wireless networks with uncertain demand
    (IEEE, 2013) Andrews, M.; Özen, Ulaş; Reiman, M. I.; Wang, Q.; Management Information Systems; ÖZEN, Ulaş
    The interaction of a content provider with end users on an infrastructure platform built and maintained by a service provider can be viewed as a two-sided market. Content sponsoring, i.e., charging the content provider instead of viewers for resources consumed in viewing the content, can benefit all parties involved. Without being charged directly or having it counted against their monthly data quotas, end users will view more content, allowing the content provider to generate more advertising revenue, extracted by the service provider to subsidize its investment and operation of the network infrastructure. However, realizing such gains requires a proper contractual relationship between the service provider and content provider. We consider the determination of this contract through a Stackelberg game. The service provider sets a pricing schedule for sponsoring and the content provider responds by deciding how much content to sponsor. We analyze the best strategies for the content provider and service provider in the event that the underlying demand for the content is uncertain. Two separate settings are defined. In the first, end users can be charged for non-sponsored views on a per-byte basis. In the second we extend the model to the more common case in which end users purchase data quotas on a periodic basis. Our main conclusion is that a coordinating contract can be designed that maximizes total system profit. Moreover, the additional profit due to sponsoring can be split between the content provider and service provider in an arbitrary manner.
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    Heuristic methods for the capacitated stochastic lot-sizing problem under the static-dynamic uncertainty strategy
    (Elsevier, 2019-09) Randa, A. C.; Doğru, M. K.; Iyigun, C.; Özen, Ulaş; Management Information Systems; ÖZEN, Ulaş
    We consider a lot-sizing problem in a single-item single-stage production system facing non-stationary stochastic demand in a finite planning horizon. Motivated by common practice, the set-up times need to be determined and frozen once and for all at the beginning of the horizon while decisions on the exact lot sizes can be deferred until the setup epochs. This operating scheme is referred to as the static-dynamic uncertainty strategy in the literature. It has been shown that a modified base stock policy is optimal for a capacitated system with minimum lot size restrictions under the static-dynamic uncertainty strategy. However, the optimal policy parameters require an exhaustive search, for which the computational time grows exponentially in the number of periods in the planning horizon. In order to alleviate the computational burden for real-life size problems, we developed and tested seven different heuristics for computational efficiency and solution quality. Our extensive numerical experiments showed that average optimality gaps less than 0.1% and maximum optimality gaps below 4% can be attained in reasonable running times by using a combination of these heuristics.