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Şehir İçi Ulaşımda Sürdürülebilir Mikromobilite: Müşteri Tercihlerine Dayalı Bir İnceleme

Yıl 2024, , 1576 - 1589, 01.12.2024
https://doi.org/10.21597/jist.1491968

Öz

Mikromobilite araçları, günümüzde şehir içi ulaşımın önemli bir parçası haline gelmiştir. Bu araçların müşteri gözünden satın alınabilirliğini değerlendirmek, kullanıcıların tercihlerini belirlemek ve pazar dinamiklerini anlamak için önemlidir. Bu çalışmada, bisiklet (A1), e-bisiklet (A2), mopet (A3), e-skuter (A4) ve e-kaykay (A5) gibi mikromobilite araçlarının satın alınabilirliği üzerine odaklanılmıştır. Çalışma kapsamında, 16 farklı kriter belirlenmiş ve analiz için çok kriterli karar verme (ÇKKV) yöntemleri kullanılmıştır. Bu kriterler arasında ortalama hız, zorunlu ehliyet gereksinimi, sürüş imkanları, konfor seviyesi, güvenlik, park imkanı, toplu taşımaya uygunluk gibi faktörler bulunmaktadır. Analitik Hiyerarşi Süreci (AHP) yöntemi ile kriterlerin ağırlıkları belirlenmiş, en yüksek ağırlık ortalama hız, en düşük ağırlık ise bakım maliyeti olarak bulunmuştur. Çok Kriterli Optimizasyon ve Uzlaşık Çözüm (VIKOR) ve Karmaşık Oransal Değerlendirme (COPRAS) yöntemleri kullanılarak mikromobilite araçlarının performansları sıralanmıştır. Şehir içi ulaşımda e-bisiklet ve mopetin daha üstün olduğu, e-skuterlerin ise önemli bir paya sahip olduğu görülmektedir. Mikromobilite araçlarının müşteri tercihleri doğrultusunda değerlendirilmesi, şehir planlamacıları ve politika yapıcılar için önemli bilgiler sunmaktadır. Bu çalışma, mikromobilite çözümlerinin altyapı ve düzenlemelerinin geliştirilmesine rehberlik edebilir ve şehir içi ulaşımın sürdürülebilirliğini artırabilir. Elde edilen bulgular, kullanıcıların tercihlerini belirlemede ve pazarlama stratejilerini geliştirmede önemli bir kılavuz sunmaktadır. Bisiklet ve e-bisiklet gibi araçlar, kullanıcılar arasında yüksek talep görebilirken, moped ve e-skuter gibi araçlar da farklı kullanım senaryolarına uygunlukları nedeniyle dikkate değerdir.

Kaynakça

  • Abduljabbar, R.L., Liyanage, S., Dia, H., 2021. The role of micro-mobility in shaping sustainable cities: A systematic literature review. Transportation Research Part D: Transport and Environment 92, 102734. https://doi.org/10.1016/j.trd.2021.102734
  • Alemdar, K.D., Kaya, Ö., Canale, A., Çodur, M.Y., Campisi, T., 2021. Evaluation of Air Quality Index by Spatial Analysis Depending on Vehicle Traffic during the COVID-19 Outbreak in Turkey. Energies 14. https://doi.org/10.3390/en14185729
  • Alemdar, K.D., Kaya, Ö., Çodur, M.Y., 2020. A GIS and microsimulation-based MCDA approach for evaluation of pedestrian crossings. Accident Analysis and Prevention 148. https://doi.org/10.1016/j.aap.2020.105771
  • Alonso, J.A., Lamata, M.T., 2006. Consistency in the Analytic Hierarchy Process: A New Approach. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 14, 445–459. https://doi.org/10.1142/s0218488506004114
  • Altın, H., 2021. Application of the Copras Method in the Decision-Making Process. Ekonomi İşletme ve Maliye Araştırmaları Dergisi 3, 136–155. https://doi.org/10.38009/ekimad.929844
  • Bakioglu, G., Atahan, A.O., 2021. AHP integrated TOPSIS and VIKOR methods with Pythagorean fuzzy sets to prioritize risks in self-driving vehicles. Applied Soft Computing 99, 106948. https://doi.org/10.1016/j.asoc.2020.106948
  • Calan, C., Sobrino, N., Vassallo, J.M., 2024. Understanding Life-Cycle Greenhouse-Gas Emissions of Shared Electric Micro-Mobility: A Systematic Review. Sustainability (Switzerland) 16. https://doi.org/10.3390/su16135277
  • Choi, D.H., Ahn, B.S., 2009. Eliciting customer preferences for products from navigation behavior on the web: A multicriteria decision approach with implicit feedback. IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans 39, 880–889. https://doi.org/10.1109/TSMCA.2009.2018636
  • Dozza, M., Violin, A., Rasch, A., 2022. A data-driven framework for the safe integration of micro-mobility into the transport system: Comparing bicycles and e-scooters in field trials. Journal of Safety Research 81, 67–77. https://doi.org/10.1016/j.jsr.2022.01.007
  • Dündar, S., Günay, G., Karlikanovaite-Balıkçı, A., Şentürk Berktaş, E., Ulu, İ.M., 2022. Mikromobilite – Ulaşıma Mucizevi Bir Çözüm Mü, Yoksa Bir Hayal Kırıklığı Mı? İDEALKENT 13, 576–598. https://doi.org/10.31198/idealkent.1066650
  • Gangurde, S.R., Akarte, M.M., 2013. Customer preference oriented product design using AHP-modified TOPSIS approach. Benchmarking 20, 549–564. https://doi.org/10.1108/BIJ-08-2011-0058
  • Huang, F.H., 2021. User behavioral intentions toward a scooter-sharing service: an empirical study. Sustainability (Switzerland) 13. https://doi.org/10.3390/su132313153
  • Jayasingh, S., Girija, T., Arunkumar, S., 2021. Factors influencing consumers’ purchase intention towards electric two‐wheelers. Sustainability (Switzerland) 13, 1–20. https://doi.org/10.3390/su132212851
  • Kaklauskas, A., Zavadskas, E.K., Raslanas, S., 2005. Multivariant design and multiple criteria analysis of building refurbishments. Energy and Buildings 37, 361–372. https://doi.org/10.1016/j.enbuild.2004.07.005
  • Karahan, G., Garagon, E., Kurtuluş, C., 2023. Kent Ulaşımında Mikromobilite Çözümlerine Lokasyon Analitiği Yaklaşımı. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi 6, 75–86. https://doi.org/10.51513/jitsa.1079294
  • Kaya, Ö., Tortum, A., Alemdar, K.D., Çodur, M.Y., 2020. Site selection for EVCS in Istanbul by GIS and multi-criteria decision-making. Transportation Research Part D: Transport and Environment 80. https://doi.org/10.1016/j.trd.2020.102271
  • Khan, N.Z., Ansari, T.S.A., Siddiquee, A.N., Khan, Z.A., 2019. Selection of E-learning websites using a novel Proximity Indexed Value (PIV) MCDM method. Journal of Computers in Education 6, 241–256. https://doi.org/10.1007/s40692-019-00135-7
  • Kopplin, C.S., Brand, B.M., Reichenberger, Y., 2021. Consumer acceptance of shared e-scooters for urban and short-distance mobility. Transportation Research Part D: Transport and Environment 91, 102680. https://doi.org/10.1016/j.trd.2020.102680
  • Kutlu Gündoǧdu, F., Kahraman, C., Civan, H.N., 2018. A novel hesitant fuzzy EDAS method and its application to hospital selection. Journal of Intelligent and Fuzzy Systems 35, 6353–6365. https://doi.org/10.3233/JIFS-181172
  • Liu, L., Miller, H.J., 2022. Measuring the impacts of dockless micro-mobility services on public transit accessibility. Computers, Environment and Urban Systems 98, 101885. https://doi.org/10.1016/j.compenvurbsys.2022.101885
  • Mulliner, E., Smallbone, K., Maliene, V., 2013. An assessment of sustainable housing affordability using a multiple criteria decision making method. Omega (United Kingdom) 41, 270–279. https://doi.org/10.1016/j.omega.2012.05.002
  • Önder, H., Akdemir, F., 2022. Sürdürülebilir Ulaşım Altyapısının Pandemi Döneminde Yeniden Kurgulanması: Mikromobilite Trendleri ve Türkiye. İDEALKENT 13, 748–770. https://doi.org/10.31198/idealkent.1039996
  • Opricovic, S., Tzeng, G.H., 2004. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research 156, 445–455. https://doi.org/10.1016/S0377-2217(03)00020-1
  • Osei, I., Addo, A., Kemausuor, F., 2023. Optimal evaluation of crop residues for gasification in Ghana using integrated multi-criterial decision making techniques. Heliyon 9, e20553. https://doi.org/10.1016/j.heliyon.2023.e20553
  • Özdemir, P., 2023. University students’ perspectives on micromobility: An evaluation based on e-scooters. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi 6, 223–237. https://doi.org/10.51513/jitsa.1257000
  • Özden, A., Betül, S., Kun, K., Bölümü, M., Fakültesi, T., Uygulamalı, S., Üniversitesi, B., 2024. Türkiye’ de Bisiklet ve E-Skuter Altyapısının Kentsel Ulaşım Bakımından Değerlendirilmesi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 30. https://doi.org/10.5505/pajes.2024.09633
  • Qi, J., Hu, J., Peng, Y.H., 2020. New design concept evaluation method involving customer preferences based on rough distance to redefined ideal solution. Computers and Industrial Engineering 147, 106677. https://doi.org/10.1016/j.cie.2020.106677
  • Rajagopal, R., Del Castillo, E., 2007. A Bayesian approach for multiple criteria decision making with applications in Design for Six Sigma. Journal of the Operational Research Society 58, 779–790. https://doi.org/10.1057/palgrave.jors.2602184
  • Saaty, T.L., 1980. The Analytic Hierarchy Process, in: Encyclopedia of Biostatistics. McGraw-Hill, New York.
  • Sadati, İ., 2023. Integrating a Connected Micromobility Infrastructure to the Existing Public Transport. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi 6, 184–193. https://doi.org/10.51513/jitsa.1148025
  • Sennaroglu, B., Varlik Celebi, G., 2018. A military airport location selection by AHP integrated PROMETHEE and VIKOR methods. Transportation Research Part D: Transport and Environment 59, 160–173. https://doi.org/10.1016/j.trd.2017.12.022
  • Stanujkic, D., Karabasevic, D., Zavadskas, E.K., 2015. A framework for the selection of a packaging design based on the SWARA method. Engineering Economics 26, 181–187. https://doi.org/10.5755/j01.ee.26.2.8820
  • Susewind, R., 2021. Dreaming in the shadow of history: micro-mobilities and belonging in Lucknow. Contemporary South Asia 29, 500–513. https://doi.org/10.1080/09584935.2021.1995329
  • Tiwari, A., n.d. Micro-mobility: the next wave of urban transportation in India [WWW Document]. URL https://yourstory.com/journal/micro-mobility-edc6x8f1y1 (accessed 2.5.24).
  • Tu, J.C., Jia, X.H., Yang, T.J., 2022. Discussion on the Purchase Factors and the User Demands of Electric Scooters from the Perspective of Consumers’ Life Style—A Case Study on Gogoro. Processes 10. https://doi.org/10.3390/pr10020395
  • Wang, Z.L., You, J.X., Liu, H.C., Wu, S.M., 2017. Failure Mode and Effect Analysis using Soft Set Theory and COPRAS Method. International Journal of Computational Intelligence Systems 10, 1002–1015. https://doi.org/10.2991/ijcis.2017.10.1.67
  • Xu, S., Nupur, R., Kannan, D., Sharma, R., Sharma, P., Kumar, S., Jha, P.C., Bai, C., 2023. An integrated fuzzy MCDM approach for manufacturing process improvement in MSMEs. Annals of Operations Research 322, 1037–1073. https://doi.org/10.1007/s10479-022-05093-5
  • Yang, H., Ma, Q., Wang, Z., Cai, Q., Xie, K., Yang, D., 2020. Safety of micro-mobility: Analysis of E-Scooter crashes by mining news reports. Accident Analysis and Prevention 143, 105608. https://doi.org/10.1016/j.aap.2020.105608

Sustainable Micro-Mobility in Urban Transportation: An Analysis Based on Customer Preferences

Yıl 2024, , 1576 - 1589, 01.12.2024
https://doi.org/10.21597/jist.1491968

Öz

Micro mobility vehicles have become an essential part of urban transportation today. Evaluating the purchase feasibility of these vehicles from the customer's perspective is crucial to understand user preferences and market dynamics. This study focuses on the purchase feasibility of micro mobility vehicles such as bicycles (A1), e-bikes (A2), mopeds (A3), e-scooters (A4), and e-skateboards (A5). Within the scope of the study, 16 different criteria were determined, and multi-criteria decision-making (MCDM) methods were used for analysis. These criteria include average speed, mandatory license requirement, driving possibilities, comfort level, safety, parking convenience, and public transport compatibility. The Analytical Hierarchy Process (AHP) method was used to determine the weights of the criteria, with the highest weight found for average speed and the lowest for maintenance cost. The performance of micro mobility vehicles was ranked using the VIšeKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Complex Proportional Assessment (COPRAS) methods. It is observed that e-bikes and mopeds stand out in urban transportation, while e-scooters also hold a significant position. Evaluating micro mobility vehicles according to customer preferences provides essential information for urban planners and policymakers. This study can guide the development of infrastructure and regulations for micro mobility solutions and enhance the sustainability of urban transportation. The findings offer valuable insights into determining user preferences and developing marketing strategies. Vehicles such as bicycles and e-bikes may see high demand among users, while mopeds and e-scooters are also noteworthy due to their suitability for various usage scenarios.

Kaynakça

  • Abduljabbar, R.L., Liyanage, S., Dia, H., 2021. The role of micro-mobility in shaping sustainable cities: A systematic literature review. Transportation Research Part D: Transport and Environment 92, 102734. https://doi.org/10.1016/j.trd.2021.102734
  • Alemdar, K.D., Kaya, Ö., Canale, A., Çodur, M.Y., Campisi, T., 2021. Evaluation of Air Quality Index by Spatial Analysis Depending on Vehicle Traffic during the COVID-19 Outbreak in Turkey. Energies 14. https://doi.org/10.3390/en14185729
  • Alemdar, K.D., Kaya, Ö., Çodur, M.Y., 2020. A GIS and microsimulation-based MCDA approach for evaluation of pedestrian crossings. Accident Analysis and Prevention 148. https://doi.org/10.1016/j.aap.2020.105771
  • Alonso, J.A., Lamata, M.T., 2006. Consistency in the Analytic Hierarchy Process: A New Approach. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 14, 445–459. https://doi.org/10.1142/s0218488506004114
  • Altın, H., 2021. Application of the Copras Method in the Decision-Making Process. Ekonomi İşletme ve Maliye Araştırmaları Dergisi 3, 136–155. https://doi.org/10.38009/ekimad.929844
  • Bakioglu, G., Atahan, A.O., 2021. AHP integrated TOPSIS and VIKOR methods with Pythagorean fuzzy sets to prioritize risks in self-driving vehicles. Applied Soft Computing 99, 106948. https://doi.org/10.1016/j.asoc.2020.106948
  • Calan, C., Sobrino, N., Vassallo, J.M., 2024. Understanding Life-Cycle Greenhouse-Gas Emissions of Shared Electric Micro-Mobility: A Systematic Review. Sustainability (Switzerland) 16. https://doi.org/10.3390/su16135277
  • Choi, D.H., Ahn, B.S., 2009. Eliciting customer preferences for products from navigation behavior on the web: A multicriteria decision approach with implicit feedback. IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans 39, 880–889. https://doi.org/10.1109/TSMCA.2009.2018636
  • Dozza, M., Violin, A., Rasch, A., 2022. A data-driven framework for the safe integration of micro-mobility into the transport system: Comparing bicycles and e-scooters in field trials. Journal of Safety Research 81, 67–77. https://doi.org/10.1016/j.jsr.2022.01.007
  • Dündar, S., Günay, G., Karlikanovaite-Balıkçı, A., Şentürk Berktaş, E., Ulu, İ.M., 2022. Mikromobilite – Ulaşıma Mucizevi Bir Çözüm Mü, Yoksa Bir Hayal Kırıklığı Mı? İDEALKENT 13, 576–598. https://doi.org/10.31198/idealkent.1066650
  • Gangurde, S.R., Akarte, M.M., 2013. Customer preference oriented product design using AHP-modified TOPSIS approach. Benchmarking 20, 549–564. https://doi.org/10.1108/BIJ-08-2011-0058
  • Huang, F.H., 2021. User behavioral intentions toward a scooter-sharing service: an empirical study. Sustainability (Switzerland) 13. https://doi.org/10.3390/su132313153
  • Jayasingh, S., Girija, T., Arunkumar, S., 2021. Factors influencing consumers’ purchase intention towards electric two‐wheelers. Sustainability (Switzerland) 13, 1–20. https://doi.org/10.3390/su132212851
  • Kaklauskas, A., Zavadskas, E.K., Raslanas, S., 2005. Multivariant design and multiple criteria analysis of building refurbishments. Energy and Buildings 37, 361–372. https://doi.org/10.1016/j.enbuild.2004.07.005
  • Karahan, G., Garagon, E., Kurtuluş, C., 2023. Kent Ulaşımında Mikromobilite Çözümlerine Lokasyon Analitiği Yaklaşımı. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi 6, 75–86. https://doi.org/10.51513/jitsa.1079294
  • Kaya, Ö., Tortum, A., Alemdar, K.D., Çodur, M.Y., 2020. Site selection for EVCS in Istanbul by GIS and multi-criteria decision-making. Transportation Research Part D: Transport and Environment 80. https://doi.org/10.1016/j.trd.2020.102271
  • Khan, N.Z., Ansari, T.S.A., Siddiquee, A.N., Khan, Z.A., 2019. Selection of E-learning websites using a novel Proximity Indexed Value (PIV) MCDM method. Journal of Computers in Education 6, 241–256. https://doi.org/10.1007/s40692-019-00135-7
  • Kopplin, C.S., Brand, B.M., Reichenberger, Y., 2021. Consumer acceptance of shared e-scooters for urban and short-distance mobility. Transportation Research Part D: Transport and Environment 91, 102680. https://doi.org/10.1016/j.trd.2020.102680
  • Kutlu Gündoǧdu, F., Kahraman, C., Civan, H.N., 2018. A novel hesitant fuzzy EDAS method and its application to hospital selection. Journal of Intelligent and Fuzzy Systems 35, 6353–6365. https://doi.org/10.3233/JIFS-181172
  • Liu, L., Miller, H.J., 2022. Measuring the impacts of dockless micro-mobility services on public transit accessibility. Computers, Environment and Urban Systems 98, 101885. https://doi.org/10.1016/j.compenvurbsys.2022.101885
  • Mulliner, E., Smallbone, K., Maliene, V., 2013. An assessment of sustainable housing affordability using a multiple criteria decision making method. Omega (United Kingdom) 41, 270–279. https://doi.org/10.1016/j.omega.2012.05.002
  • Önder, H., Akdemir, F., 2022. Sürdürülebilir Ulaşım Altyapısının Pandemi Döneminde Yeniden Kurgulanması: Mikromobilite Trendleri ve Türkiye. İDEALKENT 13, 748–770. https://doi.org/10.31198/idealkent.1039996
  • Opricovic, S., Tzeng, G.H., 2004. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research 156, 445–455. https://doi.org/10.1016/S0377-2217(03)00020-1
  • Osei, I., Addo, A., Kemausuor, F., 2023. Optimal evaluation of crop residues for gasification in Ghana using integrated multi-criterial decision making techniques. Heliyon 9, e20553. https://doi.org/10.1016/j.heliyon.2023.e20553
  • Özdemir, P., 2023. University students’ perspectives on micromobility: An evaluation based on e-scooters. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi 6, 223–237. https://doi.org/10.51513/jitsa.1257000
  • Özden, A., Betül, S., Kun, K., Bölümü, M., Fakültesi, T., Uygulamalı, S., Üniversitesi, B., 2024. Türkiye’ de Bisiklet ve E-Skuter Altyapısının Kentsel Ulaşım Bakımından Değerlendirilmesi. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 30. https://doi.org/10.5505/pajes.2024.09633
  • Qi, J., Hu, J., Peng, Y.H., 2020. New design concept evaluation method involving customer preferences based on rough distance to redefined ideal solution. Computers and Industrial Engineering 147, 106677. https://doi.org/10.1016/j.cie.2020.106677
  • Rajagopal, R., Del Castillo, E., 2007. A Bayesian approach for multiple criteria decision making with applications in Design for Six Sigma. Journal of the Operational Research Society 58, 779–790. https://doi.org/10.1057/palgrave.jors.2602184
  • Saaty, T.L., 1980. The Analytic Hierarchy Process, in: Encyclopedia of Biostatistics. McGraw-Hill, New York.
  • Sadati, İ., 2023. Integrating a Connected Micromobility Infrastructure to the Existing Public Transport. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi 6, 184–193. https://doi.org/10.51513/jitsa.1148025
  • Sennaroglu, B., Varlik Celebi, G., 2018. A military airport location selection by AHP integrated PROMETHEE and VIKOR methods. Transportation Research Part D: Transport and Environment 59, 160–173. https://doi.org/10.1016/j.trd.2017.12.022
  • Stanujkic, D., Karabasevic, D., Zavadskas, E.K., 2015. A framework for the selection of a packaging design based on the SWARA method. Engineering Economics 26, 181–187. https://doi.org/10.5755/j01.ee.26.2.8820
  • Susewind, R., 2021. Dreaming in the shadow of history: micro-mobilities and belonging in Lucknow. Contemporary South Asia 29, 500–513. https://doi.org/10.1080/09584935.2021.1995329
  • Tiwari, A., n.d. Micro-mobility: the next wave of urban transportation in India [WWW Document]. URL https://yourstory.com/journal/micro-mobility-edc6x8f1y1 (accessed 2.5.24).
  • Tu, J.C., Jia, X.H., Yang, T.J., 2022. Discussion on the Purchase Factors and the User Demands of Electric Scooters from the Perspective of Consumers’ Life Style—A Case Study on Gogoro. Processes 10. https://doi.org/10.3390/pr10020395
  • Wang, Z.L., You, J.X., Liu, H.C., Wu, S.M., 2017. Failure Mode and Effect Analysis using Soft Set Theory and COPRAS Method. International Journal of Computational Intelligence Systems 10, 1002–1015. https://doi.org/10.2991/ijcis.2017.10.1.67
  • Xu, S., Nupur, R., Kannan, D., Sharma, R., Sharma, P., Kumar, S., Jha, P.C., Bai, C., 2023. An integrated fuzzy MCDM approach for manufacturing process improvement in MSMEs. Annals of Operations Research 322, 1037–1073. https://doi.org/10.1007/s10479-022-05093-5
  • Yang, H., Ma, Q., Wang, Z., Cai, Q., Xie, K., Yang, D., 2020. Safety of micro-mobility: Analysis of E-Scooter crashes by mining news reports. Accident Analysis and Prevention 143, 105608. https://doi.org/10.1016/j.aap.2020.105608
Toplam 38 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Ulaşım ve Trafik, Ulaştırma Mühendisliği
Bölüm İnşaat Mühendisliği / Civil Engineering
Yazarlar

Ömer Kaya 0000-0003-1037-5546

Yayımlanma Tarihi 1 Aralık 2024
Gönderilme Tarihi 29 Mayıs 2024
Kabul Tarihi 16 Eylül 2024
Yayımlandığı Sayı Yıl 2024

Kaynak Göster

APA Kaya, Ö. (2024). Şehir İçi Ulaşımda Sürdürülebilir Mikromobilite: Müşteri Tercihlerine Dayalı Bir İnceleme. Journal of the Institute of Science and Technology, 14(4), 1576-1589. https://doi.org/10.21597/jist.1491968
AMA Kaya Ö. Şehir İçi Ulaşımda Sürdürülebilir Mikromobilite: Müşteri Tercihlerine Dayalı Bir İnceleme. Iğdır Üniv. Fen Bil Enst. Der. Aralık 2024;14(4):1576-1589. doi:10.21597/jist.1491968
Chicago Kaya, Ömer. “Şehir İçi Ulaşımda Sürdürülebilir Mikromobilite: Müşteri Tercihlerine Dayalı Bir İnceleme”. Journal of the Institute of Science and Technology 14, sy. 4 (Aralık 2024): 1576-89. https://doi.org/10.21597/jist.1491968.
EndNote Kaya Ö (01 Aralık 2024) Şehir İçi Ulaşımda Sürdürülebilir Mikromobilite: Müşteri Tercihlerine Dayalı Bir İnceleme. Journal of the Institute of Science and Technology 14 4 1576–1589.
IEEE Ö. Kaya, “Şehir İçi Ulaşımda Sürdürülebilir Mikromobilite: Müşteri Tercihlerine Dayalı Bir İnceleme”, Iğdır Üniv. Fen Bil Enst. Der., c. 14, sy. 4, ss. 1576–1589, 2024, doi: 10.21597/jist.1491968.
ISNAD Kaya, Ömer. “Şehir İçi Ulaşımda Sürdürülebilir Mikromobilite: Müşteri Tercihlerine Dayalı Bir İnceleme”. Journal of the Institute of Science and Technology 14/4 (Aralık 2024), 1576-1589. https://doi.org/10.21597/jist.1491968.
JAMA Kaya Ö. Şehir İçi Ulaşımda Sürdürülebilir Mikromobilite: Müşteri Tercihlerine Dayalı Bir İnceleme. Iğdır Üniv. Fen Bil Enst. Der. 2024;14:1576–1589.
MLA Kaya, Ömer. “Şehir İçi Ulaşımda Sürdürülebilir Mikromobilite: Müşteri Tercihlerine Dayalı Bir İnceleme”. Journal of the Institute of Science and Technology, c. 14, sy. 4, 2024, ss. 1576-89, doi:10.21597/jist.1491968.
Vancouver Kaya Ö. Şehir İçi Ulaşımda Sürdürülebilir Mikromobilite: Müşteri Tercihlerine Dayalı Bir İnceleme. Iğdır Üniv. Fen Bil Enst. Der. 2024;14(4):1576-89.