The application of Business Intelligence systems in logistics. review of selected practical examples

• Autorzy: Grabińska Aleksandra , Ziora Leszek

Identyfikatory

DOI

10.2478/czoto-2019-0130

• Konferencja: 7th International Conference System Safety: Human - Technical Facility - Environment, CzOTO 2018 (7 ; 12-14.12.2018 ; Zakopane, Poland)
• Języki publikacji: EN

Abstrakty

EN

The goal of the paper is to present the application of Business Intelligence systems belonging to the area of business analytics in the domain of logistics and particularly indicate its role and meaning in supporting logistics decision making processes. Its content embraces the characteristic of BI systems, its functionality, construction and benefits resulting from its implementation. The paper also presents review of research and case studies connected to the BI usage in such areas of logistics as optimization of supply chain, managerial dashboard design and improvement of business processes.

Słowa kluczowe

EN

Business Intelligence systems; business analytics; decision making support; logistics processes

PL

analityka biznesowa; podejmowanie decyzji; proces decyzyjny; optymalizacja łańcucha dostaw; kokpit menedżerski; proces biznesowy; systemy Business Intelligence

• Wydawca: De Gruyter
• Czasopismo: System Safety : Human - Technical Facility - Environment
• Rocznik: 2019
• Tom: Vol. 1, nr 1
• Strony: 1028--1035
• Opis fizyczny: Bibliogr. 28 poz.. rys.

Twórcy

autor

Grabińska Aleksandra

• Czestochowa University of Technology, Poland

autor

Ziora Leszek

• Czestochowa University of Technology, Poland

Bibliografia

• [1] Baars, H., Kemper, H.G., Lasi, H., Siegel, M. 2008. Combining RFID Technology and Business Intelligence for Supply Chain Optimization – Scenarios for Retail Logistics. In: Proceedings of the 41st Hawaii International Conference on System Sciences – 2008.
• [2] Brzozowska, A., Sałek, A., Sałek, R., Ziora, L. 2016. The Possibilities of Big Data Solutions Application in Logistics. In: XXX. microCAD International Multidisciplinary Scientific Conference University of Miskolc, Miskolc, Hungary 2016.
• [3] Cerasis: The Most Impactful Supply Chain & Logistics Trends in 2017. https://cerasis. com/wp-content/uploads/2017/02/The-Most-Impactful-Supply-Chain_Logistics-Tre nds-in-2017-eBook.pdf.
• [4] Clavier, P. 2016. Understanding Business Intelligence Understanding: Through Goods- and Service-Dominant Logic Lenses. The Electronic Journal of Knowledge Management, 14, 2, 103-115, (available online at www.ejkm.com).
• [5] Dowse, S. Why Supply Chains Need Business Intelligence: http://www.predictive analyticsworld.com/patimes/why-supply-chains-need-business-intelligence/2600. (Retrieved 12.09.2018).
• [6] Dziembek, D., Ziora, L. 2014. Business intelligence systems in the SaaS model as a tool supporting knowledge acquisition in the virtual organization. Online Journal of Applied Knowledge Management, 2, 2, 82-96.
• [7] Globonix Case Study: CF Industries – Supply Chain BI, http://globonix.com/home/case-study-cf-industries-supply-chain/, (Retrieved 15.11.2018).
• [8] Hajdul, M. 2014. Virtual co-opetition in transport - T-Scale platform case study. Procedia - Social and BehavioralSciences. 111, 761 – 769.
• [9] Hanus, P., Zowada, K. 2015. Narzędzia IT w logistycznych procesach decyzyjnych małych i średnich przedsiębiorstw. In: Witkowski, J., Skowrońska, A. Prace Naukowe UE Wrocław, 382, Ed. UE Wrocław, 290-304.
• [10]. Kerdprasop, N., Kongchai, P., Kerdprasop, K. .2013. Constraint Mining in Business Intelligence: A Case Study of Customer Churn Prediction. International Journal of Multimedia and Ubiquitous Engineering, 8, 3.
• [11] Nwaubani, J. Business Intelligence and Logistics. In: Proceedings of the 1st Olympus International Conference on Supply Chains, Katerini, Greece, www.teicm.gr.
• [12] Olariu I., (2014) Decision making strategies regarding logistics organization, Studies and Scientific Researches. Economics Edition, No 19, 2014, (available online at http://sceco.ub.ro).
• [13] Olexova C. (2014), Business intelligence adoption: a case study in the retail chain. WSEAS Transactions on Business and Economics. Volume 11, 2014, E-ISSN: 2224-2899.
• [14] Olszak, C., Ziemba, E. 2006. Business Intelligence Systems in the Holistic Infrastructure Development Supporting Decision-Making in Organisations. Interdisciplinary Journal of Information, Knowledge, and Management, 1, (available online at http://ijikm.org/Volume1/IJIKMv1p047-058Olszak19.pdf).
• [15] Olszak, C., Ziemba, E. 2012. Critical Success Factors for Implementing Business Intelligence Systems in Small and Medium Enterprises on the Example of Upper Silesia, Poland. Interdisciplinary Journal of Information, Knowledge, and Management, 7, (available online at http://www.ijikm.org/Volume7/IJIKMv7p129-150Olszak634.pdf).
• [16] Partridge, A.R. Business Intelligence in the Supply Chain. http://www.inboundlogistics. com/cms/article/business-intelligence-in-the-supply-chain/ (Retrieved 11.10.2017).
• [17] Peto, M., The Decision Making Systems Model for Logistics. http://www.pefka.men delu.cz/predmety/simul/PEFnet13/prispevky/Peto.pdf (Retrieved 11.10.2017).
• [18] Presthus, W., Canales, C. 2015. Business Intelligence Dashboard Design. A case study of a large Logistics company. (available online at http://ojs.bibsys.no/index.php/ Nokobit/article/view/261/225).
• [19] Radivojević, G.M., Šormaz, G.R., Lazić, B.S. 2013. BI applications in Logistics. In: 1st Logistics International Conference Belgrade, Serbia, 28 - 30 November.
• [20] Sahay, B.S, Ranjan, J. 2008.Real time business intelligence in supply chain analytics. Information Management & Computer Security, 16 1, 28-48.
• [21] Senthil, S, Srirangacharyulub, B., Ramesh, A. 2012. A decision making methodology for the selection of reverse logistics operating channels. In: International Conference on Modeling, Optimization and Computing. Procedia Engineering, 38, 418 – 428.
• [22] Srinivasa, R.P., Saurabh, S. Business Intelligence and Logistics, White paper. (available online at www.wipro.co.in).
• [23] Tan P.S., Leeb S. S. G., Goh A.E.S, 2012. Multi-criteria decision techniques for context-aware B2B collaboration in supply chains. Decision Support Systems. 52, 779–789, (available online at www.elsevier.com/locate/dss).
• [24] Transportation Busines Intelligence: http://cerasis.com/transportation-technology/trans portation-business-intelligence/, (Retrieved 15.11.2017).
• [25] Williams, S., Williams, N. 2007. The Profit Impact of Business Intelligence. Morgan Kaufman, Elsevier, New York.
• [26] VatovecKrmac, E. 2011. Intelligent Value Chain Networks: Business Intelligence and Other ICT Tools and Technologies in Supply/Demand Chains decisions, (available online at www.intechopen.com), DOI: 10.5772/18850.
• [27] Ziora, L. 2016. The Applicability of Business Intelligence Systems in the Support of Managerial Decisions in the International Enterprises. International Journal of Economics and Statistics, 4, 131-135.
• [28] Zowada, K. 2013. Decyzje logistyczne w sektorze MSP – wyniki badań. Logistyka, 5, 229-231.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).