Relativism in the approach to managing supply chain maturity

Anna Baranicka , Alicja Jajko-Siwek , Mariusz Szuster , Maciej Szymczak , Grażyna Wieteska

Abstract

Over the past 30 years, a number of models supporting assessment processes and development of supply chains have emerged. Such models make it possible to analyse the existing state of processes in the supply chain and represent a source of guidance for streamlining these processes. Clear assignment of a certain level of maturity to a given supply chain can be a real challenge, when only part of the criteria for classification is fulfilled. The main scientific purpose of the paper is to propose an advanced statistical non-classical method as an approach to interpreting data from research projects on the supply chain maturity. The method of classification trees has been used and presented in this paper as a tool to achieve reasonable and valuable findings. The procedure of non-classical statistical analysis of the supply chain maturity level in conjunction with an array of variables is intended to standardize the inference on the maturity of supply chains.
Author Anna Baranicka - Wroclaw University of Economics
Anna Baranicka,,
-
, Alicja Jajko-Siwek (WIiGE / KE)
Alicja Jajko-Siwek,,
- Department of Econometrics
, Mariusz Szuster (WGM / KLM)
Mariusz Szuster,,
- Department of International Logistics
, Maciej Szymczak (WGM / KLM)
Maciej Szymczak,,
- Department of International Logistics
, Grażyna Wieteska - Uniwersytet Łódzki (UŁ)
Grażyna Wieteska,,
-
Journal seriesProcedia Engineering, ISSN 1877-7058, (0 pkt)
Issue year2017
No182
Pages50-57
Publication size in sheets0.5
Conference7th International Conference on Engineering, Project and Production Management EPPM2016, 21-09-2016 - 23-09-2016, Białystok, Polska
Keywords in Englishsupply chain management, supply chain maturity, supply chain maturity assessment, classification trees in supply chain maturity assessment
DOIDOI:10.1016/j.proeng.2017.03.113
URL https://www.sciencedirect.com/science/article/pii/S1877705817312493
Languageen angielski
Score (nominal)15
Score sourceconferenceIndex
ScoreMinisterial score = 15.0, 28-02-2020, ArticleFromConference
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