Endüstri Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1942

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Author: search.filters.author.Ucal Sarı, İremCOAR Access Rights: search.filters.coarAccessRights.metadata only access

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  • Book Part
    Customer Segmentation Using Rfm Analysis: Real Case Application on a Fuel Company
    (Emerald Publishing Limited., 2020-12-04) Ucal Sarı, İrem; Sergi, Duygu; Ozkan, Burcu
    Customer segmentation is an important research area that helps organizations to improve their services according to customer needs. With the increased information that shows customer attitudes, it is much easier and also more necessary than before to analyze customer responses on different campaigns. Recency, frequency, and monetary (RFM) analysis allows us to segment customers according to their common features. In this chapter, customer segmentation and RFM analysis are explained first, then a real case application of RFM analysis on customer segmentation for a Fuel company is presented. At the end of the application part, possible strategies for the company are generated.
  • Book Part
    Citation - Scopus: 3
    Selection of the Best Face Recognition System for Check in and Boarding Services
    (Springer, 2021-08-27) Ucal Sarı, İrem; Sergi, Duygu; Kuchta, Dorota
    Check-in and boarding services are one of the most human oriented pre-flight services in aviation industry. The process of using face recognition systems increase with the aviation 4.0 concept, decreases need for manpower and increases the efficiency of the processes. Therefore, problems, developments and challenges of face recognition in terms of aviation 4.0 are discussed in this chapter to determine the best face recognition system for check in and boarding systems. Analytic hierarchy process and grey relational analysis are used to analyze current system providers. To handle the ambiguity in the linguistic evaluations, fuzzy Z- numbers are used. 10 face recognition system providers are evaluated according to five criteria with the proposed methodology and the results are discussed. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.