Araştırma Makalesi

EVALUATION OF SUPPLY CHAIN ANALYTICS WITH AN INTEGRATED FUZZY MCDM APPROACH

1 Ekim 2019
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EVALUATION OF SUPPLY CHAIN ANALYTICS WITH AN INTEGRATED FUZZY MCDM APPROACH

Öz

Recently, the popularity of big data and business analytics has increased with advanced technological developments. Supply chain analytics (SCA) notion was born with the implementation of these technologies in supply chains that become more global, more complex, more extended, and more connected each day. SCA aims to find meaningful patterns in supply chain processes with the application of statistics, mathematics, machine-learning techniques, and predictive modeling. In this context, companies try to find ways to create business value for their supply chains by leveraging SCA. However, the selection of the most appropriate SCA tool is a complicated process that contains many influencing factors. For instance, the graphical and intuitive features, the data extraction method and real-time operability can be the influencing factors for such a selection. Therefore, in this study, it is aimed to provide an integrated technique for prioritizing SCA success factors and for evaluating SCA tools. For addressing these problems, fuzzy logic and multi-criteria decision making (MCDM) techniques are used. An integrated fuzzy simple additive weighting (SAW) - a technique for order preference by similarity to ideal solution (TOPSIS) approach is applied. The weights of the success factors are calculated by using fuzzy SAW technique, and the SCA tools are evaluated by using fuzzy TOPSIS technique. The success factors and the SCA tool alternatives are determined by reviewing the literature and industry reports, and by collecting experts' opinions. An application is given to illustrate the potential of the proposed approach. At the end of the study, the suggestions for future studies are presented.

Anahtar Kelimeler

Kaynakça

  1. Arunachalam, D., Kumar, N., & Kawalek, J. P. (2018). Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges, and implications for practice. Transportation Research Part E: Logistics and Transportation Review, 114, 416-436.
  2. Arya, V., Sharma, P., Singh, A., & De Silva, P. T. M. (2017). An exploratory study on supply chain analytics applied to spare parts supply chain. Benchmarking: An International Journal, 24(6), 1571-1580.
  3. Barbosa, M. W., Ladeira, M. B., & de la Calle Vicente, A. (2017). An analysis of international coauthorship networks in the supply chain analytics research area. Scientometrics, 111(3), 1703-1731.
  4. Barbosa, M. W., Ladeira, M. B., & de la Calle Vicente, A. (2017). An analysis of international coauthorship networks in the supply chain analytics research area. Scientometrics, 111(3), 1703-1731.
  5. Barnaghi, P., Sheth, A., & Henson, C. (2013). From data to actionable knowledge: big data challenges in the web of things. IEEE Intelligent Systems, (6), 6-11.
  6. Biswas, S., & Sen, J. (2017). A proposed architecture for big data driven supply chain analytics. arXiv preprint arXiv:1705.04958.
  7. Büyüközkan, G., & Çifçi, G. (2012). A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Expert Systems with Applications, 39(3), 3000-3011.
  8. Chae, B., Olson, D., & Sheu, C. (2014). The impact of supply chain analytics on operational performance: a resource-based view. International Journal of Production Research, 52(16), 4695-4710.

Ayrıntılar

Birincil Dil

İngilizce

Konular

-

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

1 Ekim 2019

Gönderilme Tarihi

22 Ağustos 2019

Kabul Tarihi

26 Eylül 2019

Yayımlandığı Sayı

Yıl 2019

Kaynak Göster

APA
Büyüközkan, G., Güler, M., Mukul, E., & Göçer, F. (2019). EVALUATION OF SUPPLY CHAIN ANALYTICS WITH AN INTEGRATED FUZZY MCDM APPROACH. Beykoz Akademi Dergisi, 136-147. https://doi.org/10.14514/byk.m.26515393.2019.sp/136-147
AMA
1.Büyüközkan G, Güler M, Mukul E, Göçer F. EVALUATION OF SUPPLY CHAIN ANALYTICS WITH AN INTEGRATED FUZZY MCDM APPROACH. Beykoz Akademi Dergisi. Published online 01 Ekim 2019:136-147. doi:10.14514/byk.m.26515393.2019.sp/136-147
Chicago
Büyüközkan, Gülçin, Merve Güler, Esin Mukul, ve Fethullah Göçer. 2019. “EVALUATION OF SUPPLY CHAIN ANALYTICS WITH AN INTEGRATED FUZZY MCDM APPROACH”. Beykoz Akademi Dergisi, Ekim 1, 136-47. https://doi.org/10.14514/byk.m.26515393.2019.sp/136-147.
EndNote
Büyüközkan G, Güler M, Mukul E, Göçer F (01 Ekim 2019) EVALUATION OF SUPPLY CHAIN ANALYTICS WITH AN INTEGRATED FUZZY MCDM APPROACH. Beykoz Akademi Dergisi 136–147.
IEEE
[1]G. Büyüközkan, M. Güler, E. Mukul, ve F. Göçer, “EVALUATION OF SUPPLY CHAIN ANALYTICS WITH AN INTEGRATED FUZZY MCDM APPROACH”, Beykoz Akademi Dergisi, ss. 136–147, Eki. 2019, doi: 10.14514/byk.m.26515393.2019.sp/136-147.
ISNAD
Büyüközkan, Gülçin - Güler, Merve - Mukul, Esin - Göçer, Fethullah. “EVALUATION OF SUPPLY CHAIN ANALYTICS WITH AN INTEGRATED FUZZY MCDM APPROACH”. Beykoz Akademi Dergisi. 01 Ekim 2019. 136-147. https://doi.org/10.14514/byk.m.26515393.2019.sp/136-147.
JAMA
1.Büyüközkan G, Güler M, Mukul E, Göçer F. EVALUATION OF SUPPLY CHAIN ANALYTICS WITH AN INTEGRATED FUZZY MCDM APPROACH. Beykoz Akademi Dergisi. 2019;:136–147.
MLA
Büyüközkan, Gülçin, vd. “EVALUATION OF SUPPLY CHAIN ANALYTICS WITH AN INTEGRATED FUZZY MCDM APPROACH”. Beykoz Akademi Dergisi, Ekim 2019, ss. 136-47, doi:10.14514/byk.m.26515393.2019.sp/136-147.
Vancouver
1.Gülçin Büyüközkan, Merve Güler, Esin Mukul, Fethullah Göçer. EVALUATION OF SUPPLY CHAIN ANALYTICS WITH AN INTEGRATED FUZZY MCDM APPROACH. Beykoz Akademi Dergisi. 01 Ekim 2019;136-47. doi:10.14514/byk.m.26515393.2019.sp/136-147

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