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

• Autorzy: Bukowski Lech

Identyfikatory

DOI

10.2478/emj-2019-0034

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

Industry 4.0; logistics 4.0; big data; imperfect knowledge; knowledge maturity

PL

Przemysł 4.0; Logistyka 4.0; big data; wiedza niedoskonała; wiedza dojrzała

• Wydawca: Oficyna Wydawnicza Politechniki Białostockiej
• Czasopismo: Engineering Management in Production and Services
• Rocznik: 2019
• Tom: Vol. 11, no. 4
• Strony: 65--79
• Opis fizyczny: Bibliogr. 40 poz., rys., tab.

Twórcy

autor

Bukowski Lech

• WSB University in Dąbrowa Górnicza, Poland

Bibliografia

• Ackoff, R.L. (1989). From Data to Wisdom. Journal of Applies Systems Analysis, 16, 3-9.
• Adamczewski, P. (2016). E-logistyka ery now economy. Przedsiębiorczość i zarządzanie, XVII(12/1), 9-2.
• Albjoren, J.S., & Haldorson, A. (2002). Logistics knowledge creation: reflections on content, context and processes. International Journal of Physical Distribution and Logistics Management, 1, 22-40.
• Al Shalabi, L., Shaaban, Z., & Kasasbeh, B. (2006). Data Mining: A Preprocessing Engine. Journal of Computer Science, 2(9), 735-739.
• Aven, T. (2015). Risk analysis. John Wiley and Sons.
• Bergmann, G. (1957). Philosophy of science. Madison, United States: University of Wisconsin Press.
• Blaik, P. (2010). Logistyka. Koncepcja zintegrowanego zarządzania [Logistics. The concept of integrated management]. Warszawa, Poland: Polskie Wydawnictwo Ekonomiczne.
• Blaik, P., & Matwiejczuk, R. (2008). Logistyczny łańcuch tworzenia wartości [Logistic value creation chain]. Opole, Poland: Wydawnictwo Uniwersytetu Opolskiego.
• Blanchard, B.S. (2015). Logistics Engineering and Management. Pearson Education.
• Bukowski, L. (2016). Zapewnienie ciągłości dostaw w zmiennym i niepewnym otoczeniu [Ensuring continuity of supply in variable and uncertain services]. Dąbrowa Gornicza, Poland: Wydawnictwo Naukowe WSB w Dąbrowie Gorniczej.
• Bukowski, L. (2016a). System of Systems Dependability - Theoretical Models and Applications Examples. Reliability Engineering & System Safety, 151, 76-92.
• Bukowski, L. (2019). Reliable, Secure and Resilient Logistics Networks. Delivering products in a risky environment. Switzerland: Springer Nature.
• Corrigan, D. (2013). Integrating and governing big data. IBM Corporation Software Group.
• Coyle, J., Bogostardi, E., & Langley, C. Jr. (2010). Zarządzanie logistyczne [Logistics management]. Warszawa, Poland: Polskie Wydawnictwo Ekonomiczne S.A.
• Gudehus, T., & Kotzab, H. (2009). Comprehensive Logistics. Berlin, Heidelberg, Germany: Springer.
• Harisson, A., & van Hoek, R. (2010). Zarządzanie logistyką [Logistics management]. Warszawa, Poland: Polskie Wydawnictwo Ekonomiczne S.A.
• ISO, (2009). Risk Management – Principles and Guidelines. ISO 31000:2009.
• Junemann, R. (1989). Materialfluss und Logistik. Springer.
• Kagermann, H., Wahlster, W. & Helbig, J. (2013). Recommendation for implementing Industry 4.0. National Academy of Science and Engineering.
• Kirsch, W., Bamberger, I., Gabele, E., & Klein, H.K. (1973), Betriebswitschafliche Logistik – Systeme, Entscheidungen, Methoden. Wiesbaden, Germany: Gabler.
• Klimko, G. (2001). Knowledge management and maturity models: building common understanding. Proceedings of the Second European Conference on Knowledge Management. Bled, Slovenia.
• Klir, G.J. (1991). Facets of systems science. New York, United States: Plenum.
• Krawczyk, S. (2011). Logistyka. Teoria i praktyka [Logistics. Theory and practice]. Warszawa, Poland: Difin.
• Kulikowski, J.L. (2014). Data Quality Assessment: Problems and Methods. International Journal of Organizational and Collective Intelligence (IJOCI), 4(1), 24-36.
• Lasch, R. (2014). Strategisches und operatives Logistikmanagement: Prozesse. Wiesbaden, Germany: Springer Gabler.
• Magruk, A. (2017). Concept of uncertainty in relation to the foresight research. Engineering Management in Production and Services, 9(1), 46-55.
• Mangan, J. et al. (2004). Combining quantitative and qualitative methodologies in logistics research. International Journal of Physical Distribution and Logistics Management, 7, 565-578.
• Michlowicz, E. (2002). Podstawy logistyki przemysłowej [Basics of industrial logistics].Krakow, Poland: Uczelniane Wydawnictwa Naukowo-Dydaktyczne Akademii Gorniczo-Hutniczej im. Stanisława Staszica.
• Morgenstern, O. (1955). Note on the Formulation of the Theory of Logistics. Neval Research Logistics Quartely, 5, 129-136.
• Pfohl, H.Ch. (1998). Systemy logistyczne. Podstawy organizacji i zarządzania [Logistics systems. Basics of organisation and management]. Poznań, Poland: Instytut Logistyki i Magazynowania.
• Schonsleben, P. (1998). Integrales Logistikmanagement. Planung und Steuerung von umfassenden Geschaftsprozessen, Berlin Heidelberg, Germany: Springer-Verlag.
• Schumacher, A., Erol, S., & Sihn, W. (2016). A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises, Procedia CIRP, 52, 161-166.
• Skyttner, L. (2008). General systems theory. Problems, perspectives, practice. Word Scientific.
• Ślusarczyk, B., Haseeb, M., & Hussain, H. I. (2019). Fourth industrial revolution: a way forward to attain better performance in the textile industry. Engineering Management in Production and Services, 7(4), 54-64.
• Stock, J.R., & Lambert, D.M. (2001). Strategic Logistics Management. Mc Grow-Hill Higher Education.
• Strandhagen, J.O. et al. (2017). Logistics 4.0 and emerging sustainable business models. Advances in Manufacturing, 5, 359-369.
• Tadejko, P. (2015). Application of Internet of Things in Logistics – current challenges. Engineering Management in Production and Services, 7(4), 54-64.
• Weerdmeester, R., Pocaterra, C., & Hefke, M. (2003). VISION: Next generation knowledge management: Knowledge management maturity model. Information Societies Technology Programme.
• Wieland, A., Handfield, R.B., & Durach, C.F. (2016). Mapping the landscape of future research themes in supply chain management. Journal of Business Logistics, 37(3), 205-212.
• Witkowski, J. (2010). Zarządzanie łańcuchem dostaw: koncepcje, procedury, doświadczenia [Supply chain management: concepts, procedures, experiences]. Warszawa, Poland: PWE.