The Structure of Withdrawals from ATMs Depending on Their Location Type
DOI:
https://doi.org/10.18778/0208-6018.348.08Keywords:
location of ATMs, structure of withdrawals, replenishment managementAbstract
One of the main goals of ATMs’ management is a thorough analysis of the structure of withdrawals for individual ATM and groups of ATMs installed in similar places. This type of research constitutes a necessary background for decision making about the installation or de‑installation of ATMs in each location type. The most important factors from the point of view of the profitability of the ATM is the number of withdrawals and the value of a single withdrawal. A number of withdrawals from ATM determine the revenue of ATM owners due to interchange fees and advertisements displayed in ATMs at the time of withdrawal. A large number of withdrawals generate large revenues. The value of a single withdrawal has an impact on costs. The larger withdrawals generate larger costs including preparation and delivery of cash for an ATM and “freezing” of funds in the ATM. The main goal of this research was to identify locations of the ATMs generating largest revenues i.e. locations with a large number of withdrawals and small value of single withdrawal. In addition, we tested hypotheses concerning differences in a number of withdrawals and values of single withdrawals from ATMs installed in different types of locations. In this paper, we used a time series of numbers and values of withdrawals from ATMs supplied by one of the largest ATMs networks in Poland. The data set concerns ATM’s located in Małopolskie and Podkarpackie provinces in Poland. In the research concerning the structure of withdrawals, we have used basic descriptive statistics and selected statistical tests. The study concluded with the selection of locations where with high probability installation of ATM would generate profits. The results of the analysis may be of interest to owners of networks with respect of the choice of location type.
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References
Amromin E., Chakravorti S. (2007), Debit card and cash usage: a cross‑country analysis, Technical report, Federal Reserve Bank of Chicago, Chicago.
Google Scholar
DOI: https://doi.org/10.2139/ssrn.981236
Boeschoten W. C. (1998), Cash management, payment patterns and the demand for money, „De Economist”, t. 146, nr 1, s. 117–142.
Google Scholar
Brentnall A. R., Crowder M. J., Hand D. J. (2008), A statistical model for the temporal pattern of individual automated teller machine withdrawals, „Applied Statistics”, t. 57, nr 1,, s. 43–59.
Google Scholar
Brentnall A. R., Crowder M. J., Hand D. J. (2010), Predicting the amount individuals withdraw at cash machines using a random effects multinomial model, „Statistical Modelling”, t. 10, nr 2, s. 197–214.
Google Scholar
Carlsen M., Storgaard P. E. (2010), Dankort payments as a timely indicator of retail sales in Denmark, Danmarks Nationalbank Working Papers, nr 66.
Google Scholar
Cleveland W. S., Devlin S. J. (1980), Calendar Effects in Monthly Time Series: Detection by Spectrum Analysis and Graphical Methods, „Journal of the American Statistical Association”, t. 371, nr 75, s. 487–496.
Google Scholar
Esteves P. S. (2009), Are ATM/POS Data Relevant When Now casting Private Consumption?, Banco de Portugal Working Paper, nr 25.
Google Scholar
Górka J. (2011), Rozwój sieci bankomatów w Polsce a opłaty interchange i surcharge, „Gospodarka Narodowa”, nr 7–8, s. 89–112.
Google Scholar
Górka J. (2013), Efektywność instrumentów płatniczych w Polsce, Wydawnictwo Naukowe Wydziału Zarządzania Uniwersytetu Warszawskiego, Warszawa.
Google Scholar
Górka J., Chodnicka P. (2012), Prognoza rozwoju sieci bankomatów w Polsce, [w:] J. Sokołowski, M. Sosnowski, A. Żabiński (red.), Polityka ekonomiczna, „Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu”, nr 246, s. 96–105.
Google Scholar
Gurgul G., Suder M. (2012), Efekt kalendarza wypłat z bankomatów sieci Euronet, „Zeszyty Naukowe Wyższej Szkoły Ekonomii i Informatyki w Krakowie”, nr 8, s. 25–42.
Google Scholar
Gurgul H., Suder M. (2013a), Modeling of Withdrawals from Selected ATMs of the „Euronet” Network, „Managerial Economics”, t. 13, s. 65–82.
Google Scholar
DOI: https://doi.org/10.7494/manage.2013.13.65
Gurgul H., Suder M. (2013b), The properties of ATMs development stages – an empirical analysis, „Statistics in Transition”, t. 3, s. 443–466.
Google Scholar
Gurgul H., Suder M. (2013c), Rozkład prawdopodobieństwa dziennych wypłat z bankomatów, „Wiadomości Statystyczne”, t. 58, nr 4, s. 1–22.
Google Scholar
Gurgul H., Suder M. (2015), Prognozowanie wypłat z bankomatów, „Wiadomości Statystyczne”, t. 60, nr 8, s. 25–48.
Google Scholar
Gurgul H., Suder M. (2018), Impact of ATM location on its profitability in Malopolskie and Podkarpackie provinces, „Managerial Economics”, t. 19, s. 49–73.
Google Scholar
Holden K., El‑Bannany M. (2004), Investment in information technology systems and other determinants of bank profitability in the UK, „Applied Financial Economics”, t. 14, s. 361–365.
Google Scholar
Kondo K. (2010), Do ATMs influence bank profitability in Japan?, „Applied Economics Letters”, t. 17, nr 3, s. 297–303.
Google Scholar
Kruskal W. H., Wallis A. (1952), Use of ranks in one‑criterion variance analysis, „Journal of the American Statistical Association”, t. 47, nr 260,, s. 583–621.
Google Scholar
Kufel T. (2010), Ekonometryczna analiza cykliczności procesów gospodarczych o wysokiej częstotliwości obserwowania, Wydawnictwo Naukowe Uniwersytetu Mikołaja Kopernika, Toruń.
Google Scholar
Mester L. (2009), Changes in the use of electronic means of payment: 1995–2007, „Business Review”, nr Q3, s. 29–37.
Google Scholar
Polasik M., Maciejewski K. (2017), Skutki obniżenia opłaty interchange na polskim rynku kart płatniczych, „Annales Universitatis Mariae Curie‑Skłodowska”, t. 6, nr 51,, s. 331–341.
Google Scholar
Snellman H., Viren M. (2009), ATM networks and cash usage, „Applied Financial Economics”, t. 19, nr 10,, s. 841–851.
Google Scholar
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