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RESEARCH PAPER
Methodology of building relationships with customers in the area of transport services
 
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1
Department of Economics, University of Žilina
 
2
Department of Road and Urban Transport, University of Žilina
 
3
Transportation Economics Department, Petersburg State Transport University
 
 
Submission date: 2021-09-10
 
 
Final revision date: 2021-09-26
 
 
Acceptance date: 2021-09-30
 
 
Publication date: 2021-09-30
 
 
Corresponding author
Ekaterina Salamakhina   

Department of Road and Urban Transport, University of Žilina
 
 
The Archives of Automotive Engineering – Archiwum Motoryzacji 2021;93(3):59-65
 
KEYWORDS
TOPICS
ABSTRACT
The current focusing of market on customer comfort wdemands that service providers orienconstantly modernize their structures and methods of operation. Due to the progressive digitization of various areas of business activity it is necessary to know and regularly implement up-to-date technological aids available to maintain competitiveness and build long-term relationships with the client. Delivering products to the point of consumption is an extremely important element in the supply chain and transport companies play the role of both intermediaries and service providers. This article is a framework proposal of a methodological solution for entities dealing with transport services in terms of building long-term relationships with the client with the help of modern technologies and methodologies. The findings show strategies and systems with which transport companies can strive to build a competitive offer in the logistics chain. A process portal was proposed as the target solution as an internet base of the transport offer using big data as a means to optimize the service. The study was devoted to analysing multi-criteria decision-making methods with a view to using solutions in the process of developing methodologies for building customer relations in the field of transport services.
 
REFERENCES (17)
1.
Bagasworo W.: Increased Customer Loyalty with the Use of Customer Relation Management Through Customer Satisfaction: Assa Rent (Car Rental) Case Study, Jakarta, Indonesia. Actual Problems of Economics. 2017, 2(188), 74–83.
 
2.
Becker A., Hippe A., Mclean E.L.: Cost and Materials Required to Retrofit US Seaports in Response to Sea Level Rise: A Thought Exercise for Climate Response. Journal of Marine Science and Engineering, Kingston. 2017, 5(3), 44, DOI: 10.3390/jmse5030044.
 
3.
Bojanowska A.: Evolution of the Concept of SCM in the Direction of Building a Relationship with the Customer. Systemy Logistyczne Wojsk. Warsaw .2014, 40, 29–37.
 
4.
Dhiaf M.M., Haj Khalifa A.: Do Information and Communication Technologies Affect the Performance of a Supply Chain? Pieces of Evidence from the Tunisian Food Sector. Yugoslav Journal of Operations Research. 2019, 4(29), 539–552, DOI: 10.2298/YJOR190415020H.
 
5.
Dyer J.S., Maut - Multiattribute Utility Theory. Multiple Criteria Decision Analysis: State of the Art Surveys. 2005, 78, 265–292, DOI: 10.1007/0-387-23081-5_7.
 
6.
Gasparik J., Zitricky V., Abramovic B., David A.: Role of CRM in Supply Chains Using the Process Portal. Business Logistics in Modern Management. 2017, 17, 385–404.
 
7.
Chopra S., Meindl P.: Supply Chain Management: Startegy, Planning and Operation, New Jersey 2004, ISBN-10: 0273765221, ISBN-13: 9780273765226.
 
8.
Jahanshahloo G.R., Lotfi F.H., Izadikhah M.: An Algorithmic Method to Extend TOPSIS for Decision-making Problems with Interval Data. Applied Mathematics and Computation. 2006, 175(2), 1375–1384, DOI: 10.1016/j.amc.2005.08.048.
 
9.
Kacprzak D.: Objective Weights Based on Ordered Fuzzy Numbers for Fuzzy Multiple Criteria Decision Making Methods. Entropy. 2017, 19(7), 373, DOI:10.3390/e19070373.
 
10.
Kubina M., Lendel V.: Successful Application of Social CRM in The Company. Procedia Economics and Finance. 2015, 23(2015), 1190–1194, DOI: 10.1016/S2212-5671(15)00487-6.
 
11.
Lendel V., Varmus M.: Proposal of Innovative Approaches of Relationship Marketing in Business. Business: Theory and Practice. 2015, 16(1), 63–74, DOI: 10.3846/btp.2015.434.
 
12.
Lotfi F.H., Fallahnejad R., Imprecise Shannon’s Entropy and Multi Attribute Decision Making. Entropy. 2010, 12(1), 53–62, DOI: 10.3390/e12010053.
 
13.
Roszkowska E., Kacprzak D.: The Fuzzy SAW and Fuzzy TOPSIS Procedures Based on Ordered Fuzzy Numbers. Information Sciences. 2016, 369, 564–584, DOI: 10.1016/j.ins.2016.07.044.
 
14.
Roy B.: Multicriteria Decision Support. Scientific and Technical Publishing House, Warsaw. 1990.
 
15.
Roy B.: Paradigms and challenges. Multiple Criteria Decision Analysis: State of the Art Surveys. 2005, 78, 3–24, DOI: 10.1007/0-387-23081-5_1.
 
16.
Trzaskalik T., Multiple: Criteria Decision Making (MCDM). Publishing House of the University of Economics in Katowice, 2006.
 
17.
Waściński T.: Logistics processes in supply chain management. Zeszyty Naukowe Uniwersytetu Przyrodniczo-humanistycznego w Siedlcach. 2014, 103, 25–38.
 
 
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