Araştırma Makalesi

BIG DATA ANALYTICS SOFTWARE SELECTION WITH MULTI-CRITERIA DECISION-MAKING METHODS FOR DIGITAL TRANSFORMATION

Sayı: 63 22 Temmuz 2024
PDF İndir
EN TR

BIG DATA ANALYTICS SOFTWARE SELECTION WITH MULTI-CRITERIA DECISION-MAKING METHODS FOR DIGITAL TRANSFORMATION

Öz

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.

Anahtar Kelimeler

Kaynakça

  1. Abbasianjahromi, H., Rajaie, H., & Shakeri, E. (2013). “A Framework for Subcontractor Selection in the Construction Industry”, Journal of Civil Engineering and Management, 19/2, 158–168. https://doi.org/10.3846/13923730.2012.743922
  2. Aksoy, S., & Yetkin Ozbuk, M. (2017). “Multiple Criteria Decision Making in Hotel Location: Does It Relate to Postpurchase Consumer Evaluations?”, Tourism Management Perspectives, 22, 73–81. https://doi.org/10.1016/j.tmp.2017.02.001
  3. Albawab, M., Ghenai, C., Bettayeb, M., & Janajreh, I. (2020). “Sustainability Performance Index for Ranking Energy Storage Technologies using Multi-Criteria Decision-Making Model and Hybrid Computational Method”, Journal of Energy Storage, 32, 101820. https://doi.org/10.1016/j.est.2020.101820
  4. Alkan, N., & Kahraman, C. (2024). “CODAS Extension Using Novel Decomposed Pythagorean Fuzzy Sets: Strategy Selection for IOT Based Sustainable Supply Chain System”, Expert Systems with Applications, 237, 121534. https://doi.org/10.1016/J.ESWA.2023.121534
  5. Almomani, M. A., Aladeemy, M., Abdelhadi, A., & Mumani, A. (2013). “A Proposed Approach for Setup Time Reduction Through Integrating Conventional SMED Method With Multiple Criteria Decision-Making Techniques”, Computers & Industrial Engineering, 66/2, 461–469. https://doi.org/10.1016/j.cie.2013.07.011
  6. Ampaw, E. M., Chai, J., Jiang, Y., Darko, A. P., & Ofori, K. S. (2024). “Rethinking Small-Scale Gold Mining in Ghana: A Holy Grail for Environmental Stewardship and Sustainability”, Journal of Cleaner Production, 437, 140683. https://doi.org/10.1016/j.jclepro.2024.140683
  7. Asemi, A., Asemi, A., Ko, A., & Alibeigi, A. (2022). “An Integrated Model for Evaluation of Big Data Challenges and Analytical Methods in Recommender Systems”, Journal of Big Data, 9/1, 13. https://doi.org/10.1186/s40537-022-00560-z
  8. Attri, R., & Grover, S. (2015). “Application of Preference Selection Index Method for Decision Making Over the Design Stage of Production System Life Cycle”, Journal of King Saud University - Engineering Sciences, 27/2, 207–216. https://doi.org/10.1016/j.jksues.2013.06.003

Ayrıntılar

Birincil Dil

İngilizce

Konular

İş Analitiği, İşletme

Bölüm

Araştırma Makalesi

Erken Görünüm Tarihi

22 Temmuz 2024

Yayımlanma Tarihi

22 Temmuz 2024

Gönderilme Tarihi

1 Aralık 2023

Kabul Tarihi

24 Haziran 2024

Yayımlandığı Sayı

Yıl 2024 Sayı: 63

Kaynak Göster

APA
Öztaş, T. (2024). BIG DATA ANALYTICS SOFTWARE SELECTION WITH MULTI-CRITERIA DECISION-MAKING METHODS FOR DIGITAL TRANSFORMATION. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 63, 297-317. https://doi.org/10.30794/pausbed.1398830
AMA
1.Öztaş T. BIG DATA ANALYTICS SOFTWARE SELECTION WITH MULTI-CRITERIA DECISION-MAKING METHODS FOR DIGITAL TRANSFORMATION. PAUSBED. 2024;(63):297-317. doi:10.30794/pausbed.1398830
Chicago
Öztaş, Tayfun. 2024. “BIG DATA ANALYTICS SOFTWARE SELECTION WITH MULTI-CRITERIA DECISION-MAKING METHODS FOR DIGITAL TRANSFORMATION”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, sy 63: 297-317. https://doi.org/10.30794/pausbed.1398830.
EndNote
Öztaş T (01 Temmuz 2024) BIG DATA ANALYTICS SOFTWARE SELECTION WITH MULTI-CRITERIA DECISION-MAKING METHODS FOR DIGITAL TRANSFORMATION. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 63 297–317.
IEEE
[1]T. Öztaş, “BIG DATA ANALYTICS SOFTWARE SELECTION WITH MULTI-CRITERIA DECISION-MAKING METHODS FOR DIGITAL TRANSFORMATION”, PAUSBED, sy 63, ss. 297–317, Tem. 2024, doi: 10.30794/pausbed.1398830.
ISNAD
Öztaş, Tayfun. “BIG DATA ANALYTICS SOFTWARE SELECTION WITH MULTI-CRITERIA DECISION-MAKING METHODS FOR DIGITAL TRANSFORMATION”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 63 (01 Temmuz 2024): 297-317. https://doi.org/10.30794/pausbed.1398830.
JAMA
1.Öztaş T. BIG DATA ANALYTICS SOFTWARE SELECTION WITH MULTI-CRITERIA DECISION-MAKING METHODS FOR DIGITAL TRANSFORMATION. PAUSBED. 2024;:297–317.
MLA
Öztaş, Tayfun. “BIG DATA ANALYTICS SOFTWARE SELECTION WITH MULTI-CRITERIA DECISION-MAKING METHODS FOR DIGITAL TRANSFORMATION”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, sy 63, Temmuz 2024, ss. 297-1, doi:10.30794/pausbed.1398830.
Vancouver
1.Tayfun Öztaş. BIG DATA ANALYTICS SOFTWARE SELECTION WITH MULTI-CRITERIA DECISION-MAKING METHODS FOR DIGITAL TRANSFORMATION. PAUSBED. 01 Temmuz 2024;(63):297-31. doi:10.30794/pausbed.1398830

Cited By


download?token=eyJhdXRoX3JvbGVzIjpbXSwiZW5kcG9pbnQiOiJqb3VybmFsIiwib3JpZ2luYWxuYW1lIjoiYnkucG5nIiwicGF0aCI6ImEyZjUvYWI0ZS8zZjQ0LzZhNDM3MWIyYzBiZDE0LjAyNjIzMzMyLnBuZyIsImV4cCI6MTc4MjgwODUxNSwibm9uY2UiOiIyNmYzZWIxZTEyZTBjNjdjZTI1OWI0ODdjYzFmYmUxNSJ9.2VF5ZYgyC7BIkKy9Ta-JdpGfwAHc5fhFuhz086x-jcQ Bu dergide yer alan çalışmalar Creative Commons Atıf 4.0 Uluslararası Lisansı ile lisanslanmıştır.