Digitalisation of supply chain management system for customer quality service improvement

• Autorzy: Shevtshenko Eduard , Maas Rene , Murumaa Lea , Karaulova Tatjanja , Raji Ibrahim Oluwole , Popell Janek

Identyfikatory

DOI

10.36897/jme/147803

• Języki publikacji: EN

Abstrakty

EN

The main idea of the current research is to apply customer satisfaction level Key Performance Indicators (KPIs) for supply chain reliability improvement. The Supply Chain Operations Reference (SCOR) model-based KPI metrics increase the quality of product/service by monitoring, visualising, and digitalising directly involved processes. In the long run, the solution will ultimately help reduce/eliminate the number of customer reclamations in the supply chain. An industry-oriented performance measurement model based on SCOR can be easily adapted for different sectors. The approach proposed in the current research is based on identifying key factors of supply chain performance of the SCOR model connected with the predictive and diagnostic capability of Bayesian Believe Networks. The difference in performance can be reached via applying the best practices to processes, affecting the performance on a larger scale.

Słowa kluczowe

EN

digitalisation; performance; reliability; customer service quality

• Wydawca: Wydawnictwo Wrocławskiej Rady FSNT NOT
• Czasopismo: Journal of Machine Engineering
• Rocznik: 2022
• Tom: Vol. 22, No. 3
• Strony: 78--90
• Opis fizyczny: Bibliogr. 39 poz., rys., tab.

Twórcy

autor

Shevtshenko Eduard

• Faculty of Science and Technology, Institute of Computer Science, University of Tartu, Estonia
• Institute of Logistics, TTK UAS, Estonia

• https://orcid.org/0000-0002-1389-3245

autor

Maas Rene

• Institute of Logistics, TTK UAS, Estonia
• Faculty of Science and Technology, Institute of Computer Science, University of Tartu, Estonia

autor

Murumaa Lea

• Institute of Engineering and Circular Economy, TTK UAS, Estonia
• Department of Mechanical and Industrial Engineering, TalTech, Estonia

autor

Karaulova Tatjanja

• Department of Mechanical and Industrial Engineering, TalTech, Estonia

autor

Raji Ibrahim Oluwole

• Management Leadership & Organisations, Middlesex University, United Kingdom

autor

Popell Janek

• Institute of Logistics, TTK UAS, Estonia

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).