Logistics decision-making based on the maturity assessment of imperfect knowledge

Abstract

The main purpose of this article is to develop a method that allows for an objective quality assessment of imperfect knowledge, which is necessary for decision-making in logistics. The methodology aimed at achieving this goal is established on the system analysis of the entire process employed for obtaining, processing and using data and information as well as the knowledge generated on this basis. The result of this work is a general framework that can be used for managerial decision-making in smart systems that are part of Industry 4.0, and, in particular, Logistics 4.0. A key theoretical contribution of this framework is the concept for quantitative assessment of the maturity of imperfect knowledge acquired from Big Data. The practical implication of this concept is the possibility to use the framework for the assessment of the acceptable risk associated with a managerial decision. For this purpose, the article presents a brief example of how to use this methodology in the risk-taking decision-making process. Finally, the summary and discussion of the results are offered.