Yazar "Argun, I.D." seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • Küçük Resim Yok
    Öğe
    Applications of data mining algorithms for customer recommendations in retail marketing
    (Nova Science Publishers, Inc., 2022) Delice, E.; Polatli, L.Ö.; Argun, I.D.; Tozan, H.
    In recent years, researchers have highlighted how large volumes of data can be transformed into information to determine customer behaviors, and data mining applications have become a major trend. It has become critical for organizations to use a tool for understanding the relationships between data to protect their marketplace by increasing customer loyalty. Thanks to data mining applications, data can be processed and transformed into information, and in this way, target audiences can be determined while developing marketing strategies. This chapter aims to increase the market share with products specific to the customer portfolio, introduce strategic marketing tools for retaining old customers, introduce effective methods for acquiring new customers, and increase the retail sales chart, based on purchasing habits of customers. The data set was collected under pandemic conditions during the COVID-19 process and analyzed to support retail businesses in their online shopping orientation. By examining the local customer base, it was assumed that the customer group would display similar behaviors in online or teleordering methods, customer identification and order estimation were made to follow an effective sales policy. Segmentation was performed with data mining applications, and the grouped data were separated according to their similarities. The data set consisting of demographic characteristics and various product information of the enterprise's customers were analyzed with Decision Tree and Random Forest, which are data mining methods, the best performing algorithm in the data set was selected by comparing the performance of the methods. As a result of the findings, appropriate suggestions were given to the business to determine the purchasing tendencies of the customers and to increase the level of effectiveness in sales-marketing strategies. In this way, materials were presented to assist the enterprise in developing strategies to increase the number of sales by taking faster and more accurate action by avoiding the time and expense that would be lost by the trial-error method. © 2022 Nova Science Publishers, Inc. All rights reserved.
  • Küçük Resim Yok
    Öğe
    Fuzzy Logic Approach in Failure Mode and Effects Analysis: Glass Industry Application
    (Springer Science and Business Media Deutschland GmbH, 2023) Argun, I.D.; Ozdemir, T.
    The competitive environment in market circumstances, invites wide notice from glass factory managers about quality complications. There is a direct connection between quality and production efficiency. Increasing quality increases efficiency in production, reduces costs and increases market share. The company, which has to compete with many companies in glass production, aims to increase its competitive advantage with the quality and production efficiency. The desired feature in glass production is durability and a world-class production quality. Defects occurring in the glass in the production of flat glass in the Düzce Glass Factory lead to loss of production. For this reason, the company carries out the necessary studies in order to achieve quality in production and to ensure that the established quality management system is in operation. In the study, Pareto analysis and Failure Mode and Effects Analysis (FMEA) technique are examined in the quality improvement process. In this study, Pareto analysis of the glass produced and sold according to the customer complaint form is applied, FMEA is handled and the processes is examined. The aim of this study is to be encountered the defects in the glass production process are analyzed according to the FMEA technique. As a result of the analysis, it has been shown that the technique provides success in improving the quality functions of the company. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.