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A Hybrid Framework for Improving Sustainable Urban Mobility: Integrating Multi-Criteria Decision-Making and Maximal Covering Location Problem for Bike-Sharing System Site Selection

Yıl 2025, Cilt: 41 Sayı: 1, 346 - 369, 30.04.2025

Öz

Sustainable urban mobility is crucial for reducing environmental impacts and enhancing transportation efficiency. The effectiveness of Bike-Sharing Systems (BSS) largely depends on the optimal placement of stations. In this study, a data-driven framework integrating Multi-Criteria Decision-Making (MCDM) and spatial optimization techniques was developed for BSS station site selection. The Integrated Determination of Objective Criteria Weights (IDOCRIW) method was employed to determine criterion weights, while the Combined Compromise Solution (CoCoSo) method was used for evaluating alternatives. The analysis considered factors such as proximity to bicycle lanes and tram stations, population density, and traffic accident rates. To enhance result robustness, TOPSIS, ARAS, and COPRAS methods were applied, and the results were aggregated using the Borda Count method. Additionally, the Maximum Coverage Problem was utilized to optimize population coverage, with the selected three optimal station locations covering 18% of the urban population, demonstrating the effectiveness of the proposed approach. Scenario analyses assessed the impact of service distance thresholds on system performance, providing insights into planning flexibility. The findings highlight that integrating MCDM techniques with spatial modeling enhances the efficiency and sustainability of BSS implementations.

Destekleyen Kurum

YÖK 100/2000

Kaynakça

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Sürdürülebilir Kentsel Hareketliliğin İyileştirilmesi için Hibrit Bir Çerçeve: Paylaşımlı Bisiklet Sistemi İstasyon Yer Seçiminde Çok Kriterli Karar Verme ve Maksimum Kapsama Probleminin Entegrasyonu

Yıl 2025, Cilt: 41 Sayı: 1, 346 - 369, 30.04.2025

Öz

Sürdürülebilir kentsel hareketlilik çevresel etkilerin azaltılması ve ulaşım verimliliğinin artırılması açısından kritik öneme sahiptir. Paylaşımlı Bisiklet Sistemleri (BSS), istasyonların optimal konumlandırılmasına bağlı olarak etkinlik göstermektedir. Bu çalışmada, BSS istasyonlarının yer seçimi için Çok Kriterli Karar Verme (ÇKKV) ve mekânsal optimizasyon teknikleri entegre edilerek veri odaklı bir çerçeve geliştirilmiştir. Kriter ağırlıklarının belirlenmesinde IDOCRIW yöntemi ile alternatiflerin değerlendirilmesinde CoCoSo yöntemini bir arada kullanılmıştır. Bisiklet yollarına, tramvay duraklarına yakınlık, nüfus yoğunluğu ve trafik kaza oranları gibi faktörler dikkate alınarak analiz gerçekleştirilmiştir. Sonuçların sağlamlığını artırmak amacıyla TOPSIS, ARAS ve COPRAS yöntemleri uygulanmış ve Borda Sayım yöntemiyle sonuçlar birleştirilmiştir. Ek olarak Maksimum Kapsama Problemi kullanılarak nüfus kapsama oranı optimize edilmiştir. Seçilen üç optimal istasyon konumu, kent nüfusunun %18’ini kapsayarak yöntemin etkinliğini ortaya koymuştur. Senaryo analizleri, hizmet mesafesi eşik değerlerinin sistem performansı üzerindeki etkisini değerlendirerek planlama esnekliği konusunda içgörüler sunmaktadır. Bulgular, ÇKKV teknikleri ile mekânsal modellemenin entegrasyonunun BSS'nin verimliliğini ve sürdürülebilirliğini artırdığını göstermektedir.

Kaynakça

  • Knudsen C, Moreno E, Arimah B, Otieno R, Ogunsanya O, Arku G and Leck H 2020. World cities report 2020: The value of sustainable Urbanization. United Nations, United Nation Human Settlements Programme.
  • Bank W. Cities and Climate Change: An Urgent Agenda. 2010. Available Online: Openknowledge. Worldbank. Org. Bai X, Shi P and Liu Y 2014. Society: Realizing China's Urban Dream. Nature, 509(7499), 158-160. https://doi.org/10.1038/509423a
  • Abubakar I R and Dano U L 2020. Sustainable Urban Planning Strategies for Mitigating Climate Change in Saudi Arabia. Environment, Development and Sustainability, 22(6), 5129-5152. https://doi.org/10.1007/s10668-019-00417-1
  • Bauman A, Crane M, Drayton B A and Titze S 2017. The Unrealised Potential of Bike Share Schemes to Influence Population Physical Activity Levels–A Narrative Review. Preventive Medicine, 103, S7-S14. https://doi.org/10.1016/j.ypmed.2017.02.015
  • Tiwari A and Sharma P 2024. Preference-based grey theory model and its application in waste disposal selection: a case study. Sādhanā, 49(1), 64. https://doi.org/10.1007/s12046-023-02413-8
  • Fontaine P, Minner S and Schiffer M 2023. Smart And Sustainable City Logistics: Design, Consolidation and Regulation. European Journal of Operational Research, 307(3), 1071-1084. https://doi.org/10.1016/j.ejor.2022.09.022
  • Demaio P 2009. Bike-Sharing: History, Impacts, Models of Provision and Future. Journal Of Public Transportation, 12(4), 41-56. https://doi.org/10.5038/2375-0901.12.4.3
  • CSB. 2024. Environmental indicators. Retrieved https://www.csb.gov.tr/ (Access date, 07.02.2024).
  • Caulfield B, O'Mahony M, Brazil W and Weldon P 2017. Examining Usage Patterns of a Bike-Sharing Scheme in A Medium Sized City. Transportation Research Part A: Policy and Practice, 100, 152-161 https://doi.org/10.1016/j.tra.2017.04.023
  • Zhao P, Yuan D and Zhang Y 2022. The Public Bicycle as A Feeder Mode for Metro Commuters in The Megacity Beijing: Travel Behavior, Route Environment, and Socioeconomic Factors. Journal of Urban Planning and Development, 148(1), 04021064. https://doi.org/10.1080/01441647.2023.2222911
  • Rowangould G M and Tayarani M 2016. Effect of Bicycle Facilities on Travel Mode Choice Decisions. Journal of Urban Planning and Development, 142(4), 04016019. https://doi.org/10.1061/(ASCE)UP.1943-5444.00003414
  • Wang Y, Liu Y, Ji S, Hou L, Han S S and Yang L 2018. Bicycle Lane Condition and Distance: Case Study of Public Bicycle System in Xi’an, China. Journal of Urban Planning and Development, 144(2), 05018001. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000436
  • Glass C, Appiah-Opoku S, Weber J, Jones Jr S L, Chan A and Oppong J 2020. Role of bikeshare programs in transit-oriented development: case of Birmingham, Alabama. Journal of Urban Planning and Development, 146(2), 05020002. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000567
  • Chevalier A, Charlemagne M and Xu L 2019. Bicycle Acceptance on Campus: Influence of The Built Environment and Shared Bikes. Transportation Research Part D: Transport and Environment, 76, 211-235. https://doi.org/10.1016/j.trd.2019.09.011
  • Zhao P, Yuan D and Zhang Y 2022. The Public Bicycle as A Feeder Mode for Metro Commuters in The Megacity Beijing: Travel Behavior, Route Environment, and Socioeconomic Factors. Journal of Urban Planning and Development, 148(1), 04021064. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000785
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  • Kabak M, Erbaş M, Cetinkaya C and Özceylan E 2018. A GIS-Based MCDM Approach for The Evaluation of Bike-Share Stations. Journal Of Cleaner Production, 201, 49-60. https://doi.org/10.1016/j.jclepro.2018.08.033
  • Mete S, Cil Z A and Özceylan E 2018. Location And Coverage Analysis of Bike-Sharing Stations in University Campus. Business Systems Research: International Journal of The Society for Advancing Innovation and Research in Economy, 9(2), 80-95. https://doi.org/10.2478/bsrj-2018-0021
  • Chen H, Cheng T and Zhang Y 2019. Locating Stations in Bike-Sharing Service: A Special Maximal Covering Location Problem. http://newcastle.gisruk.org/proceedings/
  • Gehrke S R and Welch T F 2019. A Bikeshare Station Area Typology to Forecast the Station-Level Ridership of System Expansion. Journal Of Transport and Land Use, 12(1), 221-235 https://www.jstor.org/stable/26911265
  • Hu Y, Zhang Y, Lamb D, Zhang M and Jia P 2019. Examining And Optimizing the Bicycle Bike-Sharing System–A Pilot Study in Colorado, US. Applied Energy, 247, 1-12. https://doi.org/10.1016/j.apenergy.2019.04.007
  • Jahanshahi D, Minaei M, Kharazmi O A and Minaei F 2019. Evaluation And Relocating Bicycle Sharing Stations in Mashhad City Using Multi-Criteria Analysis. International Journal of Transportation Engineering, 6(3), 265-283.
  • Shu S, Bian Y, Rong J and Xu D 2019. Determining the exact location of a public bicycle station—The optimal distance between the building entrance/exit and the station. PloS one, 14(2), e0212478. https://doi.org/10.1371/journal.pone.0212478
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  • Lee T Y, Jeong M H, Jeon S B and Cho J M 2020. Location Optimization of Bicycle-Sharing Stations Using Multiple-Criteria Decision Making. Sensors And Materials, 32(12), 4463-4470. https://doi.org/10.18494/SAM.2020.3125
  • Salih-Elamin R and Al-Deek H 2021. A New Method for Determining Optimal Locations of Bike Stations to Maximize Coverage in A Bike Share System Network. Canadian Journal of Civil Engineering, 48(5), 540-553. https://doi.org/10.1139/cjce-2020-014
  • Alkılınç E, Cenani Ş and Çağdaş G 2021. Bisiklet Paylaşım Istasyonlarının Belirlenmesi: CBS Tabanlı Çok Kriterli Karar Verme Yaklaşımı. Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 23(2), 471-489 https://doi.org/10.25092/baunfbed.893434
  • Guler D and Yomralioglu T 2021. Location Evaluation of Bicycle Sharing System Stations and Cycling Infrastructures with Best Worst Method Using GIS. The Professional Geographer, 73(3), 535-552. https://doi.org/10.1080/00330124.2021.1883446
  • Öztaşçi D D, Ünalan G and Ersoy U 2021. Cost-Benefits Analysis of Establishing a Bike-Sharing System Between Başkent University and Koru Metro. Journal of Public Finance Studies, (66), 107-137. https://doi.org/10.26650/mcd2021-989630
  • Bahadori M S, Gonçalves A B and Moura F 2022. A GIS-MCDM Method For Ranking Potential Station Locations in The Expansion of Bike-Sharing Systems. Axioms, 11(6), 263. https://doi.org/10.3390/axioms11060263
  • Mix R, Hurtubia R and Raveau S 2022. Optimal location of bike-sharing stations: A built environment and accessibility approach. Transportation research part A: policy and practice, 160, 126-142 https://doi.org/10.1016/j.tra.2022.03.022
  • Qian X, Jaller M and Circella G 2022. Equitable Distribution of Bikeshare Stations: An Optimization Approach. Journal of Transport Geography, 98, 103174. https://doi.org/10.1016/j.jtrangeo.2021.103174
  • Chai L, Zeng C, Zhao L and Hu J 2023. Location Selection of Shared Bicycle Distribution Points Based on User Demand. IEEE Access, 11, 22629-22636. https://doi.org/10.1109/ACCESS.2023.3248304.
  • Zhou J, Guo Y, Sun J, Yu E and Wang R 2022. Review Of Bike-Sharing System Studies Using Bibliometrics Method. Journal Of Traffic and Transportation Engineering (English Edition), 9(4), 608-630 https://doi.org/10.1016/j.jtte.2021.08.003
  • Eslami V, Ashofteh P S, Golfam P and Loáiciga H A 2021. Multi-Criteria Decision-Making Approach for Environmental Impact Assessment to Reduce the Adverse Effects of Dams. Water Resources Management, 35(12), 4085-4110. https://doi.org/10.1007/s11269-021-02932-1
  • Zavadskas E K and Podvezko V 2016. Integrated determination of objective criteria weights in MCDM. International Journal of Information Technology & Decision Making, 15(02), 267-283. https://doi.org/10.1142/S0219622016500036
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  • Ali T, Aghaloo K, Chiu Y R and Ahmad M 2022. Lessons Learned from the COVID-19 Pandemic in Planning the Future Energy Systems Of Developing Countries Using An Integrated MCDM Approach In The Off-Grid Areas Of Bangladesh. Renewable Energy, 189, 25-38. https://doi.org/10.1016/j.renene.2022.02.099
  • Aktaş N and Demirel N 2021. A Hybrid Framework for Evaluating Corporate Sustainability Using Multi-Criteria Decision Making. Environment, Development and Sustainability, 23(10), 15591-15618 https://doi.org/10.1007/s10668-021-01311-5
  • Hwang C L and Yoon K 1981. Multiple Attribute Decision Making: Methods and Applications Springer-Verlag. New York, NY, USA. https://doi.org/10.1007/978-3-642-48318-9_3
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  • Ustinovichius L, Zavadskas E K and Podvezko V 2007. Application Of a Quantitative Multiple Criteria Decision Making (MCDM-1) Approach to The Analysis of Investments in Construction. Control And Cybernetics, 36(1), 251-268.
  • Yazdani M, Zarate P, Kazimieras Zavadskas E and Turskis Z 2019. A Combined Compromise Solution (Cocoso) Method for Multi-Criteria Decision-Making Problems. Management Decision, 57(9), 2501-2519. https://doi.org/10.1108/MD-05-2017-0458
  • Ecer F and Pamucar D 2020. Sustainable Supplier Selection: A Novel Integrated Fuzzy Best Worst Method (F-BWM) And Fuzzy Cocoso with Bonferroni (Cocoso’b) Multi-Criteria Model. Journal of Cleaner Production, 266, 121981. https://doi.org/10.1016/j.jclepro.2020.121981
  • Hashemkhani Zolfani S, Yazdani M, Ebadi Torkayesh A and Derakhti A 2020. Application Of a Gray-Based Decision Support Framework for Location Selection of a Temporary Hospital During COVID-19 Pandemic. Symmetry, 12(6), 886. https://doi.org/10.3390/sym12060886
  • Leigh C, Peterson J and Chandra S 2009. Campus Bicycle-Parking Facility Site Selection: Exemplifying Provision of An Interactive Facility Map. In Proceedings of The Surveying & Spatial Sciences Institute Biennial International Conference, Adelaide (Pp. 389-398).
  • Wuerzer T, Mason S and Youngerman R 2012. Boise Bike Share Location Analysis. Community And Regional Planning
  • Croci E and Rossi D 2014. Optimizing The Position of Bike Sharing Stations. The Milan Case.
  • Ekundayo O E 2023. Optimizing Bike-Sharing in Glasgow Using a Multi-Criteria Analysis Approach.
  • Eren E and Uz V E 2020. A Review on Bike-Sharing: The Factors Affecting Bike-Sharing Demand. Sustainable Cities and Society, 54, 101882. https://doi.org/10.1016/j.scs.2019.101882
  • Hagwall R 2023. Mapping Stockholm's Bike-share Future: A GIS-based Analysis of Bicycle-sharing Stations in Stockholm.
  • Kayseri Municipality. 2023. Kayseri Population Density In 2022. Retrieved From Https://Cbs.Kayseri.Bel.Tr/ (Access Date: 20.11.2023)
  • Zavadskas E K and Turskis Z 2010. A new additive ratio assessment (ARAS) method in multicriteria decision‐making. Technological and economic development of economy, 16(2), 159-172. https://doi.org/10.3846/tede.2010.10
  • Zavadskas E K, Kaklauskas A and Šarka V 1994. The new method of multicriteria complex proportional assessment of projects. https://etalpykla.vilniustech.lt/handle/123456789/111916
  • Borda, J. D. (1781). M'emoire sur les' elections au scrutin. Histoire de l'Acad'emie Royale des Sciences.
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  • Ozdemir, S. (2024). Unveiling environmental resilience: A data-driven multi-criteria decision-making approach. Environmental Impact Assessment Review, 108, 107607. https://doi.org/10.1016/j.eiar.2024.107607
Toplam 84 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mekansal Veri ve Bilgi İşleme
Bölüm Makaleler
Yazarlar

Nimet Elmacıoğlu 0000-0003-0008-5182

Yayımlanma Tarihi 30 Nisan 2025
Gönderilme Tarihi 18 Mart 2025
Kabul Tarihi 19 Nisan 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 41 Sayı: 1

Kaynak Göster

APA Elmacıoğlu, N. (2025). A Hybrid Framework for Improving Sustainable Urban Mobility: Integrating Multi-Criteria Decision-Making and Maximal Covering Location Problem for Bike-Sharing System Site Selection. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, 41(1), 346-369.
AMA Elmacıoğlu N. A Hybrid Framework for Improving Sustainable Urban Mobility: Integrating Multi-Criteria Decision-Making and Maximal Covering Location Problem for Bike-Sharing System Site Selection. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi. Nisan 2025;41(1):346-369.
Chicago Elmacıoğlu, Nimet. “A Hybrid Framework for Improving Sustainable Urban Mobility: Integrating Multi-Criteria Decision-Making and Maximal Covering Location Problem for Bike-Sharing System Site Selection”. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi 41, sy. 1 (Nisan 2025): 346-69.
EndNote Elmacıoğlu N (01 Nisan 2025) A Hybrid Framework for Improving Sustainable Urban Mobility: Integrating Multi-Criteria Decision-Making and Maximal Covering Location Problem for Bike-Sharing System Site Selection. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi 41 1 346–369.
IEEE N. Elmacıoğlu, “A Hybrid Framework for Improving Sustainable Urban Mobility: Integrating Multi-Criteria Decision-Making and Maximal Covering Location Problem for Bike-Sharing System Site Selection”, Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, c. 41, sy. 1, ss. 346–369, 2025.
ISNAD Elmacıoğlu, Nimet. “A Hybrid Framework for Improving Sustainable Urban Mobility: Integrating Multi-Criteria Decision-Making and Maximal Covering Location Problem for Bike-Sharing System Site Selection”. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi 41/1 (Nisan 2025), 346-369.
JAMA Elmacıoğlu N. A Hybrid Framework for Improving Sustainable Urban Mobility: Integrating Multi-Criteria Decision-Making and Maximal Covering Location Problem for Bike-Sharing System Site Selection. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi. 2025;41:346–369.
MLA Elmacıoğlu, Nimet. “A Hybrid Framework for Improving Sustainable Urban Mobility: Integrating Multi-Criteria Decision-Making and Maximal Covering Location Problem for Bike-Sharing System Site Selection”. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, c. 41, sy. 1, 2025, ss. 346-69.
Vancouver Elmacıoğlu N. A Hybrid Framework for Improving Sustainable Urban Mobility: Integrating Multi-Criteria Decision-Making and Maximal Covering Location Problem for Bike-Sharing System Site Selection. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi. 2025;41(1):346-69.

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