Please use this identifier to cite or link to this item: https://hdl.handle.net/11499/58110
Title: Big data analytics software selection with multi-criteria decision-making methods for digital transformation
Authors: Öztaş, Tayfun
Abstract: In the process of transitioning to digital businesses, managers are faced with numerous decision-making challenges across various domains. This complexity poses a significant hurdle for traditional businesses seeking to embrace digital transformation. To address this challenge, the Preference Selection Index (PSI) and Additive Ratio Assessment (ARAS) methods are utilized for selecting Big Data Analytics (BDA) software, employing multi-criteria decision-making (MCDM) approaches. With a scenario involving 8 alternatives and 7 criteria, the PSI method is employed to establish the weights of the criteria. Subsequently, the ARAS method is utilized to rank the alternatives. The analysis identifies \"Ease of Use\" as the criterion with the highest importance weight (0.1464), while \"Data Workflow\" emerges as the least significant criterion (0.1378). Based on the highest utility degree (0.9548), the fifth alternative was identified as the most suitable big data analytics software for this scenario. Furthermore, the proposed method's applicability is validated through comparative analysis with five different MCDM methods, reinforcing the reliability of the obtained results.
URI: https://doi.org/10.30794/pausbed.1398830
https://search.trdizin.gov.tr/tr/yayin/detay/1264595
https://hdl.handle.net/11499/58110
ISSN: 1308-2922
Appears in Collections:İktisadi ve İdari Bilimler Fakültesi Koleksiyonu
TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collection

Files in This Item:
File SizeFormat 
document - 2024-10-31T111501.747.pdf2.19 MBAdobe PDFView/Open
Show full item record



CORE Recommender

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.