Browsing by Author "Sicakyuz, Cigdem"

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Citation - WoS: 3
Citation - Scopus: 9
Data Mining Applications in Risk Research: a Systematic Literature Review
(Sage Publications inc, 2025) Sicakyuz, Cigdem; Edalatpanah, Seyyed Ahmad; Pamucar, Dragan
Despite the rising literature on data mining (DM) approaches, there is a lack of a complete literature review and categorization system within risk research. This paper presents the first recognized academic literature review on the application of data mining tools in risk research provides an up-to-date SCOPUS literature database. Based on bibliometric analysis, 5422 papers related torisk were identified from a total of 77,410 studies on data mining and thoroughly analyzed. Each of the selected 5422 papers was classified into four risk categories: global risk, public health risk, molecular and biomedical risk, and pharmaceutical risk. Each primary risk category was further subdivided to highlight the specific research focuses within each domain. Global risks encompass business, environmental, and social risks. Scholars have predominantly focused on the banking, market, and construction sectors within business risk, while environmental risk includes catastrophe-related risks. Social risks encompass areas such as education, traffic safety, and transportation concerns. Clinical data is usually employed in public health risk research, while various radiomic databases are utilized in genetic and molecular biology research. In pharmaceutical research, DM is primarily used to detect adverse drug effects. According to the findings of this review, the fields of computer science and medicine received the most significant research attention. The review also discusses limitations and provides a roadmap to guide future research, aiming to enhance knowledge development related to the application of data mining techniques in risk-related studies.
Supply Chain Network Design Focused on Financial Measures and Performance Metrics: a Systematic Literature Review
(Springer, 2025) Abbasi, Sina; Sicakyuz, Cigdem
Through an extensive literature review, this study determines which metrics and measures are relevant for supply chain (SC) performance. We reviewed several universal papers published between 2012 and 2023. A selection of review papers was made according to the methods, contribution, and scope for measuring SC performance metrics and measures. By reviewing the literature, this survey prepares benchmarks and approaches for determining SC performance from a financial viewpoint. As core financial measures of SC performance, we investigation looked at inventory turnover ratios, logistics costs, and cash flows expressed as return on investment (ROI), return on equity (ROE), return on asset (ROA), profit margins, assets/liabilities, and working capital. Additionally, the study determined that key non-financial measures of SC performance are customer satisfaction, delivery performance, quality services, improved relationships, and competitive advantages. According to the study, the appropriate approaches for assessing SC performance are financial and non-financial measures. Using the same approach, measures, and metrics at all SC nodes is essential to determine SC performance appropriately. Moreover, research is needed to identify the benefits and issues preventing SC measurements and performance across different industries.