Kitap Bölümü Koleksiyonu
https://hdl.handle.net/20.500.12511/4482
Book Chapter Collection2024-03-29T14:32:26ZApplications of data mining algorithms for customer recommendations in retail marketing
https://hdl.handle.net/20.500.12511/10037
Applications of data mining algorithms for customer recommendations in retail marketing
Delice, Elif; Polatlı, Lütviye Özge; Düzdar Argun, İrem; Tozan, Hakan
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.
2022-01-01T00:00:00ZDetermining the priority of university technology transfer office activities for each group of the stakeholder using SWARA method
https://hdl.handle.net/20.500.12511/9577
Determining the priority of university technology transfer office activities for each group of the stakeholder using SWARA method
Karadayı, Melis Almula; Ekinci, Yeliz
This chapter is an attempt to summarize the University Technology Transfer Office (UTTO) activities firstly. The main objective is to determine the priority of these activities for each group of the stakeholder; namely, students, academicians, and industry. UTTOs promote the conversion of knowledge created at university to marketable goods; which makes them crucial for the countries. Moreover, UTTOs serve to the economic development of countries by bringing companies and researchers together and motivating them for technology transfer. In this study, we firstly examine the UTTOs to understand the dynamics of these offices. Then, we list the critical activities of the UTTOs and conduct three surveys specific to each group of the stakeholder where the participants evaluate the relative importance of the activities determined. Importance/priority of UTTO activities is determined using Stepwise Weight Assessment Ratio Analysis (SWARA) method, for each group of the stakeholder. Finally, the results are presented, which will shed light on the decisions in managing and organizing UTTO activities.
2022-01-01T00:00:00ZEnhanced performance assessment of airlines with integrated balanced scorecard, network-based superefficiency DEA and PCA methods
https://hdl.handle.net/20.500.12511/6737
Enhanced performance assessment of airlines with integrated balanced scorecard, network-based superefficiency DEA and PCA methods
Aydın, Umut; Almula Karadayı, Melis; Ülengin, Füsun; Ülengin, Kemal Burç
In the last decade, due to the aggressively increasing competition in the airline industry, strategic decisions to improve airline performance have become crucial. However, evaluating airline efficiency is an extremely complex, multidimensional problem and requires the application of Multiple Criteria Decision-Making (MCDM) methods. This study evaluates the performance of 45 airline companies via combining the balanced scorecard (BSC) approach and the network-based superefficient data envelopment analysis (DEA). The proposed methodology incorporates finance, customers, internal processes, learning, and growth dimensions of BSC into the analysis in order to conduct a comprehensive assessment of airline companies from financial and nonfinancial perspectives of performance. Moreover, the eigenvector centrality concept is used to determine the airlines that should act as a role model (peer) for efficiency in each dimension of BSC. Rankings of airline companies in each dimension are also presented using the eigenvector centrality values. Additionally, in order to improve the discriminatory power of DEA, initially the principal component analysis (PCA) is conducted and based on the representation of the 14 variables by seven factors revealed from PCA, a compact model that integrates the four dimensions of the evaluation is obtained. Those factors are named according to their characteristics as Flight Capacity, Profitability, Profitability per Employee, Customer Satisfaction, Operational Profitability, Liquidity, and Operational Performance. Those key performance indicators are used in order to make overall performance evaluation and reveal the overall rankings. Finally, the significance of the ranking differences between the ranking based on each of the four dimensions and the overall ranking is tested by spearman rank correlation.
2021-01-01T00:00:00ZAn MCDM-based health technology assessment (HTA) study for evaluating kidney stone treatment alternatives
https://hdl.handle.net/20.500.12511/6735
An MCDM-based health technology assessment (HTA) study for evaluating kidney stone treatment alternatives
Erol, Eren; Yılmaz, Beyza Özlem; Almula Karadayı, Melis; Tozan, Hakan
The prevalence of kidney stone disease has increased during the last decade due to various reasons such as changes in dietary and water consumption. To overcome this issue, new treatment approaches are being developed. Today, Extracorporeal Shock Wave Lithotripsy (ESWL) and Laser Lithotripsy (LL) are the most popular approaches for the fragmentation of kidney stones. However, the advantages and limitations of these treatment methods are still being questioned by healthcare professionals. A systematic and efficient approach is thus required to help healthcare providers for selecting the best treatment approach. Multi-Criteria Decision-Making (MCDM) techniques are a reliable and powerful approach to respond to the need for such comparative analysis. Hence, the aim of this study is to propose an HTA-based hierarchical evaluation structure for kidney stone treatment methods utilizing the Hierarchical Fuzzy TOPSIS method and conduct a case study on LL and ESWL. The structure consists of 5 main criteria and 24 sub-criteria. The study group for linguistic evaluations consists of medical doctors (nephrologists and urologists) and researchers. Closeness coefficient values are obtained as 0.577 and 0.372 for LL and ESWL, respectively. It is concluded that LL should be selected as the ideal alternative under the proposed hierarchical evaluation structure. The study is expected to bring insights to further studies as well as healthcare providers who are working in the field.
2021-01-01T00:00:00Z