Scholarly record
INFORMATION SHARING WITH UPSTREAM PARTNERS OF SUPPLY CHAINS
Abstract
Companies with financial stability and relatively good market share usually invest in software for supply chain management. IT can be used to transmit real-time market information for real demand on the supply chain. The analysis of the current development of the IT sector and the good practices for SCM software application, determine the need to formulate some novelties regarding information sharing with upstream partners. The aim of this article is to give some methods for information sharing in supply chains with upstream partners. The main used method for analysis is content analysis of expert opinions of practitioners in logistics and supply chain management. This paper proposes some novelties in information sharing with upstream partners. The design of specialized reports is given. The format and sample contents of the data sent to upstream partners is also given. A sample XML file is created. A hierarchical model of logistics information for ordered quantities is created. The results of this paper may be useful for other researchers, practitioners and software companies who plan to extend the functionality of their ERP systems in the direction of integration with upstream partners in supply chains.
Publication Impact Profile
Publication details
References15
Sulova, S. Integration of structured and unstructured data in the analysis of e-commerce customers. International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM, Bulgaria, vol. 18, issue 2.1, 2018 pp 499-506.
Sergeev, A.P., Buevich, A.G., Baglaeva, E.M., Shichkin, A.V. Combining spatial autocorrelation with machine learning increases prediction accuracy of soil heavy metals. Catena, Netherlands, vol. 174, issue March 2019, pp 425-435, 2019.
Sulova, S. Association rule mining for improvement of IT project management. TEM Journal, Serbia, vol. 7, issue 4, pp 717-722, 2018.
Subbotina, I.E., Buevich, A.G., Shichkin, A.V., Sergeev, A.P., Tarasov, D.A., Tyagunov, A.G., Sergeeva, M.V., Baglaeva, E.M. Multilayer perceptron, generalized regression neural network, and hybrid model in predicting the spatial distribution of impurity in the topsoil of urbanized area. AIP Conference Proceedings, USA, 1982, 020004, DOI: 10.1063/1.5045410, 2018.
Sulova, S. Creating groups for marketing purposes from website usage data. Vestnik Udmurtskogo Universiteta: Matematika, Mekhanika, Komp'yuternye Nauki, Russia, vol. 27, issue 3, pp 470-478, 2018.
Tarasov, D.A., Buevich, A.G., Sergeev, A.P., Shichkin, A.V. High variation topsoil pollution forecasting in the Russian Subarctic: Using artificial neural networks combined with residual kriging. Applied Geochemistry 88, USA, pp 188-197, 2018.
Sulova, S.D, Todoranova, L., Penchev, B., Nacheva, R. Using text mining to classify research papers, International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM, Bulgaria, vol. 17, issue 21, 2017, pp 647-654.
Jablonska, M.R., Polkowski, Z. Why do young people hate on the internet? Advances in Intelligent Systems and Computing, issue 646, pp 163-174, 2018.
Ileanu, B.V., Ausloos, M., Herteliu, C., Cristescu, M.P. Intriguing behavior when testing the impact of quotation marks usage in Google search results. Quality and Quantity, Italy, pp 1-13, 2018.
Savulescu, C., Polkowski, Z. An approach for systems identification using artificial intelligence. Proceedings of the 9th International Conference on Electronics, Computers and Artificial Intelligence, ECAI 2017, Romania, 2017, pp 1-4.
Bunescu, L., Cristescu, M. Analysis Of the procedure for Balancing the local budgets in Romania. Romanian Journal of Economic Forecasting, vol. 14, issue 1, pp 193-211, 2011.
Dimitrova, V. Gross margin and buyer power in Bulgarian food retailing, Ikonomicheski Izsledvania, Bulgaria, 2017.
Souroujon, D., Zapryanova, T. On the iterates of Jackson type operator GS,N in Hilbert space. Quaestiones Mathematicae, UK, pp 1-8, 2018.
Shukur, G., Doszyń, M., Dmytrów, K. Comparison of the effectiveness of forecasts obtained by means of selected probability functions with respect to forecast error distributions. Communications in Statistics: Simulation and Computation, Canada, vol. 46, issue 5, pp 3667-3679, 2017.
Todorova, M., Stoyanov, B., Szczypiorski, K., Kordov, K. SHAH: Hash function based on irregularly decimated chaotic map. International Journal of Electronics and Telecommunications, Poland, vol. 64, issue 4, pp 457-465, 2018.
Citing literature
Number of times cited according to Crossref: 2
View or Download full articleAccess options
SWS access login
Login as SWS Scientific CommitteeLogin as SWS Scientific PartnerLogin as SWS AuthorAuthors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.
For librarian assistance: [email protected]
Purchase Instant Access
- Article can be downloaded after successful payment.
- Article may be used according to SWS library access terms.
- Article cannot be redistributed.
