مکان‌یابی با سیستم اطلاعات جغرافیایی و مدل حداکثر پوشش

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استاد، دانشکده مدیریت، دانشگاه تهران.

2 دانشجوی دکتری، دانشگاه تهران.

چکیده

در عصر حاضر، بنگاه ­های اقتصادی، به‌ویژه بانک­ ها و مؤسسه­ های مالی و اعتباری، برای رقابت در دنیای کسب ­و­کار به دنبال حداکثر پوشش مشتریان، کاهش هزینه و افزایش سود و کارایی هستند. برای این منظور با استفاده از روش­ های علمی به دنبال تعیین و انتخاب بهترین مکان برای شروع فعالیت اقتصادی می ­باشند. مطالعه حاضر با هدف مکان‌یابی شعب «بانک مهر اقتصاد» در منطقه یک شهر تهران با استفاده از سیستم اطلاعات جغرافیایی و مدل حداکثر پوشش وزن­ دار انجام گرفته است. ابتدا از طریق مطالعات کتابخانه‌ای و مصاحبه با کارشناسان معیارها و زیرمعیارهای مؤثر در مکان­ یابی شعب بانک شناسایی شدند؛ سپس با تهیه دو پرسشنامه و توزیع آن­ها در میان مدیران بانک، وزن معیارها و زیرمعیارها بر اساس روش بهترین ـ بدترین به ­دست آمد. از سیستم اطلاعات جغرافیایی برای تعیین نقاط بالقوه که ورودی مدل حداکثر پوشش وزن ­دار هستند، استفاده شد؛ درنهایت مکان ­های مناسب با حل مدل حداکثر پوشش وزن ­دار در نرم‌افزار متلب مشخص شدند.

کلیدواژه‌ها


عنوان مقاله [English]

Locating using Geographical Information System and Weighted Maximal Covering Model

نویسندگان [English]

  • Ali Mohaghar 1
  • Sara Ariaee 2
1 Professor, University of Tehran.
2 Ph.D student, Tehran University.
چکیده [English]

     At the present time, firms especially banks and finance and credit institutions to compete in the business world are seeking for maximal customer covering, reducing costs and increasing profit and efficiency. For this purpose, they are looking for determining and choosing the best location to start economic activity with scientific methods. This study aimed to locate Mehr Eghtesad bank branches in the region 1 in Tehran city, using geographic information system and the weighted maximal covering model. First, through reviewing the literature and interviews with experts the criteria and sub-criteria affecting the location of bank branches were identified. After that, two questionnaires were prepared and distributed between the bank's Managers then the weights of criteria and sub-criteria were determined based on the Best-Worst Method. Geographic Information System was used to determine potential points that are inputs of the weighted maximal covering model. In the end, the weighted maximal covering model was solved in MATLAB and the best locations for opening the new branches were identified.

کلیدواژه‌ها [English]

  • Locating
  • Bank Branches
  • Best-Worst Method (BWM)
  • Geographical Information System (GIS)
  • Weighted Maximal Covering Model (WMCM)
1. Guneri, A. F., Cengiz, M. & Seker, S. (2009). A fuzzy ANP approach to shipyard location selection. Expert Systems with Applications, 36(4): 7992-7999.
2. Berjisian, A. & Abedin Darkoosh, S. (2012). Site selection of private banks branches in Tehran's twenty two areas (A case study of Parsian Bank). Economics Research, 12(45): 55-74. (in Persian)
3. Cebi, F. & Zeren, Z. (2008). A decision support model for location selection: Bank branch case. In Management of Engineering & Technology, 2008. PICMET 2008. Portland International Conference on: 1069-1074. IEEE.
4. Fen Li, C. (2007). Problems in Bank Branch Inefficiency: Management Scale and Location. C. F. Li / Asian Journal of Management and Humanity Sciences: 523-538.
5. Farahani, R. Z., SteadieSeifi, M. & Asgari, N. (2010). Multiple criteria facility location problems: A survey. Applied Mathematical Modelling, 34(7): 1689-1709.
6. Gigović, L., Pamučar, D., Božanić, D. & Ljubojević, S. (2017). Application of the GIS-DANP-MABAC multi-criteria model for selecting the location of wind farms: A case study of Vojvodina, Serbia. Renewable Energy, 103: 501-521.
7. Bilginol, K., Denli, H. H. & Şeker, D. Z. (2015). Ordinary Least Squares Regression Method Approach for Site Selection of Automated Teller Machines (ATMs). Procedia Environmental Sciences, 26: 66-69.
8. Awaghade, S., Dandekar, P. & Ranade, P. (2014). Site Selection and Closest Facility Analysis for Automated Teller Machine (ATM) Centers: Case Study for AUNDH (PUNE), INDIA. International Journal of Advancement in Remote Sensing, GIS and Geography, 2(1): 19-29.
9. Tabar, M. M., Bushehrian, O. & Moghadam, R. A. (2013). Locating ATMs in Urban Areas. International Journal on Computer Science and Engineering, 5(8): 753.
10. Suárez-Vega, R., Santos-Peñate, D. R. & Dorta-González, P. (2012). Location models and GIS tools for retail site location. Applied Geography, 35(1): 12-22.
11. Daskin, M. S. (2011). Network and discrete location: models, algorithms, and applications. John Wiley & Sons.
12. Murray, A. T., Tong, D. & Kim, K. (2010). Enhancing classic coverage location models. International Regional Science Review, 33(2): 115-133.
13. Church, R. L. & Murray, A. T. (2009). Business site selection, location analysis, and GIS. Hoboken, NJ: John Wiley & Sons.
14. Murray, A. T., O’Kelly, M. E. & Church, R. L. (2008). Regional service coverage modeling. Computers & Operations Research, 35(2): 339-355.
15. Spaulding, B. D. & Cromley, R. G. (2007). Integrating the maximum capture problem into a GIS framework. Journal of Geographical Systems, 9(3): 267-288.
16. Monteiro, M. S. R. & Fontes, D. B. (2006). Locating and sizing bank-branches by opening, closing or maintaining facilities. In Operations Research Proceedings 2005, Springer Berlin Heidelberg: 303-308.
17. Monteiro, M. S. R. (2004). Bank-branch location and sizing under economies of scale (Doctoral dissertation, Universidade do Porto).
18. Berman, O., Drezner, Z. & Wesolowsky, G. O. (2003). Locating service facilities whose reliability is distance dependent. Computers & Operations Research, 30(11): 1683-1695.
19. Church, R. L. (2002). Geographical information systems and location science. Computers & Operations Research, 29(6): 541-562.
20. Degl’Innocenti, M., Matousek, R., Sevic, Z., & Tzeremes, N. G. (2017). Bank efficiency and financial centres: Does geographical location matter? Journal of International Financial Markets, Institutions and Money, 46: 188-198.
21. Farzad, F., Maddah, M., & Zarkar, A. (2017). A pattern to identify and assess the location of representatives and branches of industrial services. Journal of Industrial Management Perspective, 9: 117-134. (in Persian)
22. Hirtle, B. (2007). The impact of network size on bank branch performance. Journal of Banking & Finance, 31(12): 3782-3805.
23. Okeahalam, C. (2008). Client profiles and access to retail bank services in South Africa. Applied Financial Economics, 18(14): 1131-1146.
24. Okeahalam, C. C. (2005). Cost structures and new technology: a case study of a bank in South Africa. International Journal of Financial Services Management, 1(1): 41-65.
25. Tabar, M. M., Bushehrian, O., & Moghadam, R. A. (2013). Locating ATMs in Urban Areas. International Journal on Computer Science and Engineering, 5(8): 753.
26. Wang, Y. W., & Wang, C. R. (2010). Locating passenger vehicle refueling stations. Transportation Research Part E: Logistics and Transportation Review, 46(5): 791-801.
27. Xia, L., Yin, W., Dong, J., Wu, T., Xie, M., & Zhao, Y. (2010). A hybrid nested partitions algorithm for banking facility location problems. Automation Science and Engineering, IEEE Transactions on, 7(3): 654-658.
28. Alexandris, G., & Giannikos, I. (2010). A new model for maximal coverage exploiting GIS capabilities. European Journal of Operational Research, 202(2): 328-338.
29. Aldajani, M. A., & Alfares, H. K. (2009). Location of banking automatic teller machines based on convolution. Computers & Industrial Engineering, 57(4): 1194-1201.
30. Cebi, F., & Zeren, Z. (2008, July). A decision support model for location selection: Bank branch case. In Management of Engineering & Technology, 2008. PICMET 2008. Portland International Conference on: 1069-1074. IEEE.
31. Boufounou, P. V. (1995). Evaluating bank branch location and performance: A case study. European Journal of Operational Research, 87(2): 389-402.
32. Azimi Hosseini, M., Nazarifar, M., & Momeni, R. (2014) .Application of GIS in locating. Tehran: Mehregan Ghalam. (in Persian)
33. Zhao, L. (2002). The integration of Geographical information systems and multicriteria decision making models for the analysis of branch bank closures. University of New South Wales.
34. Miliotis, P., Dimopoulou, M., & Giannikos, I. (2002). A hierarchical location model for locating bank branches in a competitive environment. International transactions in operational research, 9(5): 549-565.
35. Morrison, P. S., & O’Brien, R. (2001). Bank branch closures in New Zealand: the application of a spatial interaction model. Applied Geography, 21(4): 301-330.
36. MacDonald, E. H. (2001). GIS in banking: Evaluation of Canadian bank mergers. Canadian Journal of Regional Science, 24(3): 419.
37. Duggal, N. (2007). Retail Location Analysis: A Case Study of Burger King & McDonald’s in Portage & Summit Counties. Ohio, the degree of Masters of Arts.
38. Turk, T. (2009). Creating a Sustainable Disaster Information System and its Application on the North Anatolian Fault Zone (NAFZ). PhD. Degree Thesis, Yildiz Technical University, Istanbul.
39. Burrough, P. A., McDonnell, R., McDonnell, R. A., & Lloyd, C. D. (2015). Principles of geographical information systems. Oxford University Press.
40. Amiri, M., Khatami Firuzabadi, M., & Mobin, M. (2012). Allocation of road relief stations along Tehran-Qom Highway using Hypercube Queuing Model. Journal of Industrial Management Perspective, 7: 45-70. (in Persian).
41. Church, R., & Velle, C. R. (1974). The maximal covering location problem. Papers in regional science, 32(1): 101-118.
42. Baray, J., & Cliquet, G. (2013). Optimizing locations through a maximum covering/p-median hierarchical model: Maternity hospitals in France. Journal of Business Research, 66(1): 127-132.
43. Berman, O., Drezner, Z., & Krass, D. (2010). Generalized coverage: New developments in covering location models. Computers & Operations Research, 37(10): 1675-1687.
44. Schmid, V., & Doerner, K. F. (2010). Ambulance location and relocation problems with time-dependent travel times. European journal of operational research, 207(3): 1293-1303.
45. Geroliminis, N., Karlaftis, M. G., & Skabardonis, A. (2009). A spatial queuing model for the emergency vehicle districting and location problem. Transportation Research Part B: Methodological, 43(7): 798-811.
46. Wagner, M. R., Bhadury, J., & Peng, S. (2009). Risk management in uncapacitated facility location models with random demands. Computers & Operations Research, 36(4): 1002-1011.
47. Beraldi, P., & Bruni, M. E. (2009). A probabilistic model applied to emergency service vehicle location. European Journal of Operational Research, 196(1): 323-331.
48. Wacker, J. G. (1998). A definition of theory: research guidelines for different theory-building research methods in operations management. Journal of operations management, 16(4): 361-385.
49. Goli, A., Alfat, L., & Fokardei, R. (2010). Locating ATMs using Analytical Hierarchy Process (AHP) Case Study: Keshavarzai Bank Branches, 10th District of Tehran Municipality. Geography and development Iranian journal, 8(18): 93-108. (in Persian).
50. Ashournejad, Q., FarajiSabokbar, H., AlaviPanah, K., & Nami, M. (2012). Locating new branches of banks, financial and credit institutions using fuzzy network analysis process. Research and urban planning, 2(7): 1-20. (in Persian)
51. Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53: 49-57.
52. Guo, S., & Zhao, H. (2017). Fuzzy best-worst multi-criteria decision-making method and its applications. Knowledge-Based Systems, 121: 23-31.
53. Mou, Q., Xu, Z., & Liao, H. (2016). An intuitionistic fuzzy multiplicative best-worst method for multi-criteria group decision making. Information Sciences, 374: 224-239.
54. Finch, B.J. (2003). Operation prices (Value and Profitability), McGrave- Hill, New York.
55. Safarian, M. (2001). Designing genetic algorithm to solve maximal covering problem. (Master dissertation), Tarbiat Modares University. (in Persian).
56. Church, R. L., & ReVelle, C. S. (1976). Theoretical and Computational Links between the p Median, Location Set covering, and the Maximal Covering Location Problem. Geographical Analysis, 8(4): 406-415.
57. Farahani, R. Z., Asgari, N., Heidari, N., Hosseininia, M., & Goh, M. (2012). Covering problems in facility location: A review. Computers & Industrial Engineering, 62(1): 368-407.
58. Soleymani Damaneh, R., Momeni, M., Mostafayi, A., & Rostami, M. (2017). Developing a Dynamic Network Data Envelopment Analysis Model to assess bank performance. Journal of Industrial Management Perspective, 25: 67-89. (in Persian)
59. Okeahalam, C. (2009). Bank branch location: A count analysis. Spatial economic analysis, 4(3): 275-300.