Academic Scientific JournalsDraft to Implement a Logistics Information System for Corporate Management Using Multi-Criteria Decision Making Methods
DOI:
https://doi.org/10.26881/etil.2019.82.04Keywords:
corporate management, logistics information system, multi-criteria decision making, Scoring method, Saaty quantitative pairwise comparison methodAbstract
This manuscript is focused on describing and analyzing certain logistics processes and activities in a chosen light manufacture, warehouse and distribution enterprise, and subsequently a proposal for implementing a suitable logistics information system for corporate management providing interconnection among all the logistics activities of such an enterprise. The first two chapters outline the basic concepts related to the issue of logistics processes, electronic information systems as well as a brief description of the analyzed enterprise. The following chapters consist of the most important parts of this research study. An advanced logistics information system is specified and thereafter implemented on the basis of a predefined set of criteria and by implementing certain opted methods included into the Operations Research, particularly the multi-criteria decision making problems. Specifically, the Scoring Method is utilized, and subsequently the results obtained are compared using the Saaty quantitative pairwise comparison method.
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Bazhenov, A. A., Mizikovsky, I. E., Garina, E. P., Kuznetsov, V. P., Gavrilov, A. I. (2019), Normal Flow of Resources as a Basis for Improving the Quality of Final Financial Information. In: Popkova, E. (Ed.), The Future of the Global Financial System: Downfall or Harmony, Springer, Cham, pp. 309–315, https://doi.org/10.1007/978-3-030-00102-5_32.
Chovancova, M., Klapita, V. (2017), Modeling the Supply Process Using the Application of Selected Methods of Operational Analysis. Open Engineering, 7(1), pp. 50–54, https://doi.org/10.1515/eng-2017-0009.
Eschenfelder, K. R., Shankar, K., Williams, R. D., Salo, D., Zhang, M., Langham, A. (2019), A Nine Dimensional Framework for Digital Cultural Heritage Organizational Sustainability. A Content Analysis of the LIS Literature (2000–2015). Online Information Review,43(2), pp. 182–196, https://doi.org/10.1108/OIR-11-2017-0318.
Golini, R., Guerlain, C., Lagorio, A., Pinto, R. (2018), An Assessment Framework to Support Collective Decision Making on Urban Freight Transport. Transport, 33(4), pp. 890–901, https://doi.org/10.3846/transport.2018.6591.
Grischuk, O. A., Gunicheva, E. L. (2017), Management of Logistics System at Modern Enterprise of Machine-Building. Quid-investigacion Ciencia y Tecnologia, 1, pp. 1380–1388.
Hruška, R., Průša, P., Babič, D. (2014), The Use of AHP Method for Selection of Supplier. Transport, 29(2), pp. 195–203.
Hu, Z. H., Sheng, Z. H. (2014), A Decision Support System for Public Logistics Information Service Management and Optimization. Decision Support Systems, 59, pp. 219–229, https://doi.org/10.1016/j.dss.2013.12.001.
Hwang, C. L., Yoon, K. (1981), Multiple Attribute Decision Making: Methods and Applications, Springer-Verlag, Berlin.
Jurkovič, M., Sosedová, J. (2013), Simulation Process of Optimal Transport Department Regarding to Transport Vehicles Based on AHP Method – Applied to Slovakia. Asian Journal of Engineering and Technology, 1(4), pp. 124–128.
Krásenský, D. (2010), Supporting Logistic Processes: How to Choose a Suitable Information System. Logi – Scientific Journal on Transport and Logistics, 1, pp. 61–70.
Kubasakova, I., Kubanova, J., Poliakova, B. (2015), Modelling of Opened System in the Road Freight Transport and Its Impact on the System Characteristics, 19th International Scientific Conference on Transport Means, Kaunas, Lithuania, 22–23 October 2015, pp. 405–409.
Lin, S. S. C. (2019), Analytic Hierarchy Process by Least Square Method Revisit. Mathematical Problems in Engineering, 2797515, https://doi.org/10.1155/2019/2797515.
Liu, G. S., Lin, K. P. (2019). A Decision Support System of Green Inventory-Routing Problem. Industrial Management & Data Systems, 119(1), pp. 89–110, https://doi.org/10.1108/IMDS-11-2017-0533.
Lizbetin, J. (2018), Decision-Making Processes in Introducing RFID Technology in Manufac-turing Company. Nase More, 65(4), pp. 289–292, https://doi.org/10.17818/NM/2018/4SI.23.
Ližbetinová, L., Štarchoň, P., Lorincová, S., Weberová, D., Průša, P. (2019), Application of Cluster Analysis in Marketing Communications in Small and Medium-Sized Enterprises: An Empirical Study in the Slovak Republic. Sustainability, 11(8), https://doi.org/10.3390/su11082302.
Lorenc, A., Michnej, M., Szkoda, M. (2016), Information System Aiding the Logistics Processes of Loading and Securing in Railway Transport. International Journal of Shipping and Transport Logistics, 8(5), pp. 568–589, https://doi.org/10.1504/IJSTL.2016.10000182.
Mahmoudsalehi, M., Feizi, K., Taqhavifard, M. T., Vanani, I. R. (2019), Is Information Technology Valuable for Automotive Production Industries? An Empirical Insight from Iranian Automotive Industries. International Journal of Value Chain Management, 10(2), pp. 107–122, https://doi.org/10.1504/IJVCM.2019.099098.
Maznah, M. K., Haslinda, I., Bataineh, M. S. B. (2011), Multi-Criteria Decision Making Methods for Determining Computer Preference Index. Journal of ICT, 10, pp. 137–148.
Mirkouei, A., Haapala, K. R., Sessions, J., Murthy, G. S. (2017), A Mixed Biomass-Based Energy Supply Chain for Enhancing Economic and Environmental Sustainability Benefits: A Multi-Criteria Decision Making Framework. Applied Energy, 206, pp. 1088–1101, https://doi.org/10.1016/j.apenergy.2017.09.001.
Nadoushani, Z. S. M., Akbarnezhad, A., Jornet, J. F., Xiao, J. Z. (2017), Multi-Criteria Selection of Facade Systems Based on Sustainability Criteria. Building and Environment, 121, pp. 67–78, https://doi.org/10.1016/j.buildenv.2017.05.016.
Odero, K., Ochara, N. M., Quenum, J. (2017), Towards Big Data-Driven Logistics Value Chains for Effective Decision Making and Performance Measurement, 11th European Conference onInformation Systems Management (ECISM), 14–15 September 2017, Genoa, Italy, pp. 233–241.
Podvezko, V. (2009), Application of AHP Technique. Journal of Business Economics and Man-agement, 10(2), pp. 181–189, https://doi.org/10.3846/1611-1699.2009.10.181-189.
Rasouli, M. R. (2019), Intelligent Process-Aware Information Systems to Support Agility in Disaster Relief Operations: A Survey of Emerging Approaches. International Journal of Production Research, 57(6), pp. 1857–1872, https://doi.org/10.1080/00207543.2018.1509392.
Rezaei, J., Roekel van, W. S., Tavasszy, L. (2018), Measuring the Relative Importance of the Logistics Performance Index Indicators Using Best Worst Method. Transport Policy, 68, pp. 158–169, https://doi.org/10.1016/j.tranpol.2018.05.007.
Saaty, T. L. (2013), The Modern Science of Multicriteria Decision Making and Its Practical Applications: The AHP/ANP Approach. Operations Research, 61(5), pp. 1101–1118, https://doi.org/10.1287/opre.2013.1197.
Singh, R. K., Gunasekaran, A., Kumar, P. (2018), Third Party Logistics (3PL) Selection for Cold Chain Management: A Fuzzy AHP and Fuzzy TOPSIS Approach. Annals of Operations Research, 267, pp. 531–553, https://doi.org/10.1007/s10479-017-2591-3.
Sýkorová, M., Čverhová, D. (2011), ISO 20000 – the Possibility of Increase Effectiveness of Processes Through Information Technology. Logi – Scientific Journal on Transport and Logistics, 2, pp. 99–106.
Triantaphyllou, E., Mann, S. H. (1995), Using the Analytic Hierarchy Process for Decision Making in Engineering Applications: Some Challenges. International Journal of Industrial Engineering: Applications and Practice, 2(1), pp. 35–44.
