Assessing Operational Efficiency of Banks via Quantitative Analysis of ATM Location Selection Criteria
Subject Areas : Business ManagementHamid Shahbandarzadeh 1 , mohammadhossein kabgani 2
1 - Associate Prof..Faculty of Business and Economics, Persian Gulf University, Bushehr, Iran
2 - Ph.D. Student, Faculty of Business and Economics, Persian Gulf University, Bushehr, Iran
Keywords: Location, Facilities, ATM Machines, Mathematical Modeling Prioritize,
Abstract :
Customers require various service facilities including department stores, ATMs, and gas stations the use of which has become a daily routine. Some researchers believe that location choice of such facilities should be based on maximum population coverage within the network. The current research set out to identify potential factors that may bear an impact on location selection of ATM machines through exploring the existing literature on banking and interviewing experts in the field. Moreover, it aimed to prioritize the most important factors among those already specified through mathematical modeling. The findings emerging from the literature and expert review indicated 15 factors influencing ATM location decisions that were further subcategorized into four major factor sets of economic, competitive, coverage, and investment - legal. The results of mathematical modeling weighing revealed the priority of factors with Coverage, weighing 0.43, as the first and most important one followed in significance by economic factors, weighing 0.23, competitive factors, weighing 0.19, and investment - law factors, weighing 0.13. The results of this study also indicated that each of the four factors sets could impact decision-makers differently; therefore, bank managers are suggested to vary their decisions with respect to each of the factors to achieve optimal effectiveness.
Aksoy, S., & Ozbuk, M. Y. (2017), . Multiple criteria decision making in hotel location: Does it relate to postpurchase consumer evaluations? Tourism Management Perspectives, 22, 73-81.
Boloori Arabani, A., & Zanjirani Farahani, R. (2012). Facility location dynamics: An overview of classifications and applications. Computers & Industrial Engineering, 62(1), 408–420 .
Brickley, J. A., Linck, J., & Smith, C. (2012). Vertical integration to avoid contractin gwith potential competitors:Evidence from bankers’banks. Journal of Financial Economics, 105(1), 113-130.
Brimberg, J.; and Drezner, Z. (2013), A new heuristic for solving the p-median problem in the plane. Computers & Operations Research, 40(1), 427-437.
Chauhan, A., & Singh, A.(2016), A hybrid multi-criteria decision making method approach for selecting a sustainable location of healthcare waste disposal facility. Journal of Cleaner Production, 139, 1001-1010.
Dinler, D., Kemal Tural, M., & Iyigun, C. (2015). Heuristics for a continuous multi-facility location problem with demand regions. Computers & Operations Research, 62, 237- 256.
Donze, J., & Dubec, I. (2006). The role of interchange fees in ATM networks. International Journal of Industrial Organization, 24(1), 29– 43 .
Izdebski, M., & Jacyna-Gołda, I. (2017), The Multi-criteria Decision Support in Choosing the Efficient Location of Warehouses in the Logistic Network. Procedia Engineering, 187, 635-640.
KalliorasA, TsangaratosP, PizpikisTh, VasileiouE, IliaI, & PliakasF. (2017),. Multi-criteria Decision Support System (DSS) for optimal locations of Soil Aquifer Treatment (SAT) facilities. Science of the Total Environment, 603-604, 472-486.
Kyu Suhr, J., Eum, S., Gi Jung, H., Li, G., Kim, G., & Kim, J. (2012). Recognizability assessment of facial images for automated teller machine applications. Pattern Recognition, 45(5), 1899–1914 .
Mahmood, T., & Mujtaba Shaikh, G. (2012). Adaptive Automated Teller Machines. Expert Systems with Applications, 40(4), 1152- 1169.
OLfat, L., Goli, A., & Foukardi, R. (2010). ATM Locator Using Analytical Hierarchy Process (AHP) Case Study: Agricultural Bank Branches in Tehran 10th District Municipality. Geography and Development, 8(18), 93-108. [In pershian].
Arena, M., & Dewally, M. (2012). Firm location and corporate debt. Journal of Banking & Finance, 36(4), 1079–1092 .
Pelegrn, B., Fernandez, P., Dolores Garcıa Perez, M., & Cano Hernandez, S. l. (2012), On the location of new facilities for chain expansion under delivered pricing. Omega, 40(2,)149–158 .
Puerto, J., Ramos, A., & Rodrıguez-Chıa, A. (2011). Single-allocation ordered median hub location problems. Computers &Operations Research 38(2)559–570 .
Rodríguez, D., Levine, J., Weinstein Agrawal, A., & Song, J. (2011). Can information promote transportation-friendly location decisions?A simulation experiment. Journal of Transport Geography, 19(2), 304–312 .
Seetharam , S., & Guanghua, k. (2010). Firm location choice in cities: Evidence from China, India, and Brazil. China Economic Review, 21(1) 113–122.
Tavana, M., J. Santos Arteaga, F., Mohammadi, S., & Alimohammadi, M. (2017), A fuzzy multi-criteria spatial decision support system for solar farm location planning. Energy Strategy Reviews, 18, 93-105.
Torfi, F., Zanjirani Farahani, R., & Mahdavi, I. (2016). Fuzzy MCDM for weight of object’s phrase in location routing problem. Applied Mathematical Modelling, 40(1), 526-541.
Tóth, B., Fernández, J., Pelegrín, B., & Plastria, F. (2009), Sequential versus simultaneous approach in the location and design of two new facilities using planar Huff-like models. Computers & Operations Research 36(5), 1393 – 1405 .
Tsolas, I. E. (2011). Bank branch-level DEA to assess overall efficiency. EuroMed Journal of Business, 6(3), 359-377 .
Villacreses, G., Gaona, G., Martinez-Gomez, D, & Juan Jion, D. (2017), Wind farms suitability location using geographical information system (GIS), based on multi-criteria decision making (MCDM) methods: The case of continental Ecuador. Renewable Energy, 109, 275-286.
Willmer Escobar, J. L. (2013), A two-phase hybrid heuristic algorithm for the capacitated location-routing problem. Computers & Operations Research, 40(1), 70-79.
Yen, W. C.-K. (2012), The connected p-center problem on block graphs with forbidden vertices. . Theoretical Computer Science, 426-427, 13-24.
Zanjirani Farahani, R., SteadieSeifi, M., & Asgari, N. (2010). Multiple criteria facility location problems: A survey. Applied Mathematical Modelling 34(7), 1689–1709 .
Zangirchi, seyyd mahmoud (2012). Fuzzy Analytical Hierarchy Process. Tehran: Sanei Shahmirzadi Publications, 1, 1-284. [In persian].
ŻAK, j., & WĘGLIŃSKIb, S. (2014). The selection of the logistics center location based on MCDM/A methodology. Transportation Research Procedia 3, 555 – 564.
Zhu, H., Eden, L., R. Miller, S., E. Thomas, D., & Fields, P. (2012). Host-country location decisions of early movers and latecomers:The role of local density and experiential learning. International Business Review, 21(2), 145–155 .
_||_Aksoy, S., & Ozbuk, M. Y. (2017), . Multiple criteria decision making in hotel location: Does it relate to postpurchase consumer evaluations? Tourism Management Perspectives, 22, 73-81.
Boloori Arabani, A., & Zanjirani Farahani, R. (2012). Facility location dynamics: An overview of classifications and applications. Computers & Industrial Engineering, 62(1), 408–420 .
Brickley, J. A., Linck, J., & Smith, C. (2012). Vertical integration to avoid contractin gwith potential competitors:Evidence from bankers’banks. Journal of Financial Economics, 105(1), 113-130.
Brimberg, J.; and Drezner, Z. (2013), A new heuristic for solving the p-median problem in the plane. Computers & Operations Research, 40(1), 427-437.
Chauhan, A., & Singh, A.(2016), A hybrid multi-criteria decision making method approach for selecting a sustainable location of healthcare waste disposal facility. Journal of Cleaner Production, 139, 1001-1010.
Dinler, D., Kemal Tural, M., & Iyigun, C. (2015). Heuristics for a continuous multi-facility location problem with demand regions. Computers & Operations Research, 62, 237- 256.
Donze, J., & Dubec, I. (2006). The role of interchange fees in ATM networks. International Journal of Industrial Organization, 24(1), 29– 43 .
Izdebski, M., & Jacyna-Gołda, I. (2017), The Multi-criteria Decision Support in Choosing the Efficient Location of Warehouses in the Logistic Network. Procedia Engineering, 187, 635-640.
KalliorasA, TsangaratosP, PizpikisTh, VasileiouE, IliaI, & PliakasF. (2017),. Multi-criteria Decision Support System (DSS) for optimal locations of Soil Aquifer Treatment (SAT) facilities. Science of the Total Environment, 603-604, 472-486.
Kyu Suhr, J., Eum, S., Gi Jung, H., Li, G., Kim, G., & Kim, J. (2012). Recognizability assessment of facial images for automated teller machine applications. Pattern Recognition, 45(5), 1899–1914 .
Mahmood, T., & Mujtaba Shaikh, G. (2012). Adaptive Automated Teller Machines. Expert Systems with Applications, 40(4), 1152- 1169.
OLfat, L., Goli, A., & Foukardi, R. (2010). ATM Locator Using Analytical Hierarchy Process (AHP) Case Study: Agricultural Bank Branches in Tehran 10th District Municipality. Geography and Development, 8(18), 93-108. [In pershian].
Arena, M., & Dewally, M. (2012). Firm location and corporate debt. Journal of Banking & Finance, 36(4), 1079–1092 .
Pelegrn, B., Fernandez, P., Dolores Garcıa Perez, M., & Cano Hernandez, S. l. (2012), On the location of new facilities for chain expansion under delivered pricing. Omega, 40(2,)149–158 .
Puerto, J., Ramos, A., & Rodrıguez-Chıa, A. (2011). Single-allocation ordered median hub location problems. Computers &Operations Research 38(2)559–570 .
Rodríguez, D., Levine, J., Weinstein Agrawal, A., & Song, J. (2011). Can information promote transportation-friendly location decisions?A simulation experiment. Journal of Transport Geography, 19(2), 304–312 .
Seetharam , S., & Guanghua, k. (2010). Firm location choice in cities: Evidence from China, India, and Brazil. China Economic Review, 21(1) 113–122.
Tavana, M., J. Santos Arteaga, F., Mohammadi, S., & Alimohammadi, M. (2017), A fuzzy multi-criteria spatial decision support system for solar farm location planning. Energy Strategy Reviews, 18, 93-105.
Torfi, F., Zanjirani Farahani, R., & Mahdavi, I. (2016). Fuzzy MCDM for weight of object’s phrase in location routing problem. Applied Mathematical Modelling, 40(1), 526-541.
Tóth, B., Fernández, J., Pelegrín, B., & Plastria, F. (2009), Sequential versus simultaneous approach in the location and design of two new facilities using planar Huff-like models. Computers & Operations Research 36(5), 1393 – 1405 .
Tsolas, I. E. (2011). Bank branch-level DEA to assess overall efficiency. EuroMed Journal of Business, 6(3), 359-377 .
Villacreses, G., Gaona, G., Martinez-Gomez, D, & Juan Jion, D. (2017), Wind farms suitability location using geographical information system (GIS), based on multi-criteria decision making (MCDM) methods: The case of continental Ecuador. Renewable Energy, 109, 275-286.
Willmer Escobar, J. L. (2013), A two-phase hybrid heuristic algorithm for the capacitated location-routing problem. Computers & Operations Research, 40(1), 70-79.
Yen, W. C.-K. (2012), The connected p-center problem on block graphs with forbidden vertices. . Theoretical Computer Science, 426-427, 13-24.
Zanjirani Farahani, R., SteadieSeifi, M., & Asgari, N. (2010). Multiple criteria facility location problems: A survey. Applied Mathematical Modelling 34(7), 1689–1709 .
Zangirchi, seyyd mahmoud (2012). Fuzzy Analytical Hierarchy Process. Tehran: Sanei Shahmirzadi Publications, 1, 1-284. [In persian].
ŻAK, j., & WĘGLIŃSKIb, S. (2014). The selection of the logistics center location based on MCDM/A methodology. Transportation Research Procedia 3, 555 – 564.
Zhu, H., Eden, L., R. Miller, S., E. Thomas, D., & Fields, P. (2012). Host-country location decisions of early movers and latecomers:The role of local density and experiential learning. International Business Review, 21(2), 145–155 .
