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Liman Sıkışıklığı Faktörleri ve Çözümüne Yönelik Stratejilerin Analizi

Year 2024, In Press Articles, 1 - 15

İlke Sezin Ayaz Umur Bucak

https://doi.org/10.52998/trjmms.1401523

Abstract

Limancılık endüstrisinde hızla artan rekabet koşulları neticesinde liman performansı kavramı oldukça büyük bir önem kazanmıştır. Son yıllarda sıklıkla deneyimlenen ve liman performansını derinden etkileyen liman tıkanıklığı kavramı da liman rekabeti açısından ele alınması gereken bir sorun olarak ön plana çıkmaktadır. Bu noktadan hareketle çalışmada ilk olarak Türkiye’nin çeşitli bölgelerinde faaliyet gösteren limanların yöneticileri ile yarı yapılandırılmış görüşmeler gerçekleştirilerek liman tıkanıklığının sebepleri ve en sık yaşandığı dönemler, liman tıkanıklığına karşı alınabilecek önlemler ve geliştirilebilecek stratejiler araştırılmıştır. Daha sonra ise Bulanık AHP-TOPSIS hibrit yöntemi kullanılarak liman tıkanıklığı faktörleri ve önleyici stratejiler önceliklendirilmiştir. Gerçekleştirilen yarı yapılandırılmış görüşme sonuçları analiz edildiğinde kapasite yetersizliğinin; Bulanık AHP-TOPSIS sonuçları incelendiğinde ise beklenmedik ticaret yoğunluğunun liman tıkanıklığının altında yatan en önemli sebepler olduğu sonucuna ulaşılmıştır. Ayrıca, hem yarı yapılandırılmış görüşme hem de Bulanık AHP-TOPSIS sonuçlarına göre liman tıkanıklığını önlemek adına en etkili önlemler olarak paydaşlarla işbirliği ve kalifiye insan kaynağına yatırım yapılmasının uygun olacağı sonucuna varılmıştır. Keşifsel bir niteliğe sahip olan bu çalışma sonucunda belirlenen ve önceliklendirilen liman tıkanıklığına karşı önlemler ve stratejiler ile limancılık endüstrisine fayda sağlanacağı düşünülmektedir.

Keywords

Liman Tıkanıklığı Liman Kapasitesi Paydaşlarla İşbirliği Yarı Yapılandırılmış Görüşme Bulanık AHP-TOPSIS

Ethical Statement

Yazarlar, bu çalışmanın insan veya hayvan deneylerinin etik komite prosedürlerine uygun olarak gerçekleştirildiğini beyan ederler. E-94094268-108.99-510091 sayı numaralı etik kurul onayı Kocaeli Üniversitesi Sosyal ve Beşeri Bilimler Etik Kurulu’ndan alınmıştır.

References

  • Akkaynak Çelik, Y., Başarıcı, A.S. (2021). Konteyner terminallerinde performans değerlendirmesi ve kriterleri. Mersin Üniversitesi Denizcilik ve Lojistik Araştırmaları Dergisi 3(2): 136-159.
  • Ayaz, İ.S., Bucak, U., Mollaoğlu, M., Esmer, S. (2022). Resilience strategies of ports against covid-19 in terms of chaos theory. Marine Policy 146: 105323.
  • Bai, X, Jia, H., Xu, M. (2022). Port congestion and the economics of LPG seaborne transportation. Maritime Policy & Management 49(7): 913-929.
  • Balcı, G., Çetin, I.B., Esmer, S. (2018). An evaluation of competition and selection criteria between dry bulk terminals in Izmir. Journal of Transport Geography 69: 294-304.
  • Baştuğ, S., Haralambides, H., Esmer, S., Eminoğlu, E. (2022). Port competitiveness: Do container terminal operators and liner shipping companies see eye to eye?. Marine Policy 135: 104866.
  • Bayraktutan, Y., Özbilgin, M. (2013). Limanların uluslararası ticarete etkisi ve Kocaeli limanlarının ülke ekonomisindeki yeri. Kocaeli Üniversitesi Sosyal Bilimler Dergisi (26): 11-41.
  • Bolat, P., Kayişoğlu, G., Gunes, E., Kizilay, F., Ozsogut, S. (2020). Weighting key factors for port congestion by AHP method. Journal of ETA Maritime Science 8(4): 252-273.
  • Buckley, J.J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems 17(3): 233-247.
  • Çelik, E., Akyuz, E. (2018). An interval type-2 fuzzy AHP and TOPSIS methods for decision-making problems in maritime transportation engineering: the case of ship loader. Ocean Engineering 155: 371-381.
  • Demirel, H., Balın, A., Çelik, E., Alarçin, F. (2018). A fuzzy AHP and ELECTRE method for selecting stabilizing device in ship industry. Brodogradnja: Teorija i praksa brodogradnje i pomorske tehnike 69(3): 61-77.
  • Doğusel, V. (2021). Kocaeli limanları talep tahmini. Journal of Maritime Transport and Logistics 2(2): 82-90.
  • Ertuğrul, I., Karakaşoğlu, N. (2008). Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection. The International Journal of Advanced Manufacturing Technology 39: 783–795.
  • García-Morales, R.M., Baquerizo, A., Losada, M.A. (2015). Port management and multiple-criteria decision making under uncertainty. Ocean Engineering 104: 31-39.
  • Gidado, U. (2015). Consequences of port congestion on logistics and supply chain in African ports. Developing Country Studies 5(6): 160-167.
  • Gui, D., Wang, H., Yu, M. (2022). Risk assessment of port congestion risk during the COVID-19 pandemic. Journal of Marine Science and Engineering 10(2): 150.
  • Hatch, J.A. (2002). Doing Qualitative Research in Education Settings. New York, Suny Press.
  • Hwang, C.L., Yoon, K. (1981). Multiple Attributes Decision Making Methods and Applications. Berlin, Springer.
  • Iris, Ç., Christensen, J., Pacino, D., Ropke, S. (2018). Flexible ship loading problem with transfer vehicle assignment and scheduling. Transportation Research Part B: Methodological 111: 113-134.
  • Jiang, C., Wan, Y., Zhang, A. (2017). Internalization of port congestion: strategic effect behind shipping line delays and implications for terminal charges and investment. Maritime Policy & Management 44(1): 112-130.
  • Ke, G.Y, Li, K.W., Hipel, K.W. (2012). An integrated multiple criteria preference ranking approach to the Canadian west coast port congestion conflict. Expert Systems with Applications 39(10): 9181-9190.
  • Li, K.X., Lin, K.C., Jin, M., Yuen, K.F., Yang, Z., Xiao, Y. (2020). Impact of the belt and road initiative on commercial maritime power. Transportation Research Part A: Policy and Practice 135: 160-167.
  • Lirn, T.C., Thanopoulou, H.A., Beynon, M.J., Beresford, A.K.C. (2004). An application of AHP on transhipment port selection: A global perspective. Maritime Economics & Logistics 6: 70-91.
  • McCracken, G. (1988). The Long Interview. London, Sage Publications.
  • Merriam, S.B. (1988). Case Study Research in Education – A Qualitative Approach. San Francisco, Jossey-Bass Publishers.
  • Merriam, S.B., Grenier, R. (2019). Qualitative Research in Practice: Examples for Discussion and Analysis. San Francisco, CA, Jossey-Bass Publishers.
  • Mollaoğlu, M., Bucak, U., Demirel, H. (2019). A quantitative analysis of the factors that may cause occupational accidents at ports. Journal of ETA Maritime Science 7(4): 294-303.
  • Morgan, D.L. (1996). Focus Groups as Qualitative Research. New York, Sage Publications.
  • Nazemzadeh, M., Vanelslander, T. (2015). The container transport system: Selection criteria and business attractiveness for North-European ports. Maritime Economics & Logistics 17(2): 221-245.
  • Nishimura, E. (2020). Yard and berth planning efficiency with estimated handling time. Maritime Business Review 5(1): 5-29.
  • Notteboom, T.E. (2006). The time factor in liner shipping services. Maritime Economics & Logistics 8: 19-39.
  • Parung, G.A., Hidayanto, A.N., Sandhyaduhita, P.I., Ulo, K.L.M., Phusavat, K. (2018). Barriers and strategies of open government data adoption using fuzzy AHP-TOPSIS: A case of Indonesia. Transforming Government: People, Process and Policy 12(3/4): 210-243.
  • Paul, J.A., Maloni, M.J. (2010). Modeling the effects of port disasters. Maritime Economics & Logistics 12: 127-146.
  • Pekkaya, M., Bucak, U. (2018). Çok kriterli karar verme yöntemleriyle bölgesel liman kuruluş yeri seçimi: Bati Karadeniz’de bir uygulama. Uluslararası İktisadi ve İdari İncelemeler Dergisi 18.EYİ Özel Sayı: 253-268.
  • Saban, M., Güğerçin, G. (2009). Deniz taşımacılığı işletmelerinde maliyetleri etkileyen faktörler ve sefer maliyetleri. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi 1(1): 1-16.
  • Somsuk, N., Laosirihongthong, T. (2014). A fuzzy AHP to prioritize enabling factors for strategic management of university business incubators: Resource-based view. Technological Forecasting and Social Change 85: 198-210.
  • Takebayashi, M., Hanaoka, S. (2021). Efficient inter-port cooperation considering port congestion and port charge. Maritime Transport Research 2: 100011.
  • Talley, W.K., Ng, M. (2016). Port multi-service congestion. Transportation Research Part E: Logistics and Transportation Review 94: 66-70.
  • Tseng, P.H., Cullinane, K. (2018). Key criteria influencing the choice of Arctic shipping: a fuzzy analytic hierarchy process model. Maritime Policy & Management 45(4): 422-438.
  • Uluslararası Taşımacılık ve Lojistik Hizmet Üretenleri Derneği, Lojistik Sektörü Raporu UTİKAD (2021). Erişim Tarihi: 15.03.2023, https://www.utikad.org.tr/images/HizmetRapor/utikadl ojistiksektoruraporu2021-1654.pdf adresinden alınmıştır.
  • Wang, J.W., Cheng, C.H., Huang, K.C. (2009). Fuzzy hierarchical TOPSIS for supplier selection. Applied Soft Computing 9(1): 377-386.
  • Wang, T, Tian, X., Wang, Y. (2020). Container slot allocation and dynamic pricing of time-Sensitive cargoes considering port congestion and uncertain demand. Transportation Research Part E: Logistics and Transportation Review 144: 102149.
  • Yeo, G.T, Roe, M., Soak, S.M. (2007). Evaluation of the marine traffic congestion of north harbor in busan port. Journal of Waterway, Port, Coastal, and Ocean Engineering 133(2): 87-93.
  • Yıldırım, A., Şimşek, H. (2003). Sosyal Bilimlerde Nitel Araştırma Yöntemleri. Ankara, Seçkin Yayınları.
  • Zhen, L. (2016). Modeling of yard congestion and optimization of yard template in container ports. Transportation Research Part B: Methodological 90: 83-104.

The Factors of Port Congestion and the Analysis of Strategies Towards Solution

Year 2024, In Press Articles, 1 - 15

İlke Sezin Ayaz Umur Bucak

https://doi.org/10.52998/trjmms.1401523

Abstract

As a result of the rapidly increasing competitive conditions in the port industry, the concept of port performance has gained great importance. The concept of port congestion, which has been experienced frequently in recent years and deeply affects port performance, also comes to the fore as a problem that needs to be addressed in terms of port competition. Starting from this point in the study, firstly, semi-structured interviews were conducted with the managers of the ports operating in various regions of Türkiye, and the reasons for port congestion and the most frequent periods, the measures that can be taken against port congestion, and the strategies that can be developed were investigated. Then, port congestion factors and preventive strategies were prioritized using Fuzzy AHP-TOPSIS hybrid method. When the results of the semi-structured interviews were analyzed, it was determined that there was a lack of capacity; when the fuzzy AHP-TOPSIS results were examined, it was concluded that unexpected trade density was the most important underlying reason for port congestion. Moreover, according to both the semi-structured interview and Fuzzy AHP-TOPSIS results, it was concluded that cooperation with stakeholders and investment in qualified human resources would be the most effective measures to prevent port congestion. It is thought that the determined and prioritized measures and strategies against port congestion as a result of this exploratory study will benefit the port industry.

Keywords

Port Congestion Port Capacity Cooperation with Stakeholders Semi Structured Interview Fuzzy AHP-TOPSIS

References

  • Akkaynak Çelik, Y., Başarıcı, A.S. (2021). Konteyner terminallerinde performans değerlendirmesi ve kriterleri. Mersin Üniversitesi Denizcilik ve Lojistik Araştırmaları Dergisi 3(2): 136-159.
  • Ayaz, İ.S., Bucak, U., Mollaoğlu, M., Esmer, S. (2022). Resilience strategies of ports against covid-19 in terms of chaos theory. Marine Policy 146: 105323.
  • Bai, X, Jia, H., Xu, M. (2022). Port congestion and the economics of LPG seaborne transportation. Maritime Policy & Management 49(7): 913-929.
  • Balcı, G., Çetin, I.B., Esmer, S. (2018). An evaluation of competition and selection criteria between dry bulk terminals in Izmir. Journal of Transport Geography 69: 294-304.
  • Baştuğ, S., Haralambides, H., Esmer, S., Eminoğlu, E. (2022). Port competitiveness: Do container terminal operators and liner shipping companies see eye to eye?. Marine Policy 135: 104866.
  • Bayraktutan, Y., Özbilgin, M. (2013). Limanların uluslararası ticarete etkisi ve Kocaeli limanlarının ülke ekonomisindeki yeri. Kocaeli Üniversitesi Sosyal Bilimler Dergisi (26): 11-41.
  • Bolat, P., Kayişoğlu, G., Gunes, E., Kizilay, F., Ozsogut, S. (2020). Weighting key factors for port congestion by AHP method. Journal of ETA Maritime Science 8(4): 252-273.
  • Buckley, J.J. (1985). Fuzzy hierarchical analysis. Fuzzy Sets and Systems 17(3): 233-247.
  • Çelik, E., Akyuz, E. (2018). An interval type-2 fuzzy AHP and TOPSIS methods for decision-making problems in maritime transportation engineering: the case of ship loader. Ocean Engineering 155: 371-381.
  • Demirel, H., Balın, A., Çelik, E., Alarçin, F. (2018). A fuzzy AHP and ELECTRE method for selecting stabilizing device in ship industry. Brodogradnja: Teorija i praksa brodogradnje i pomorske tehnike 69(3): 61-77.
  • Doğusel, V. (2021). Kocaeli limanları talep tahmini. Journal of Maritime Transport and Logistics 2(2): 82-90.
  • Ertuğrul, I., Karakaşoğlu, N. (2008). Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection. The International Journal of Advanced Manufacturing Technology 39: 783–795.
  • García-Morales, R.M., Baquerizo, A., Losada, M.A. (2015). Port management and multiple-criteria decision making under uncertainty. Ocean Engineering 104: 31-39.
  • Gidado, U. (2015). Consequences of port congestion on logistics and supply chain in African ports. Developing Country Studies 5(6): 160-167.
  • Gui, D., Wang, H., Yu, M. (2022). Risk assessment of port congestion risk during the COVID-19 pandemic. Journal of Marine Science and Engineering 10(2): 150.
  • Hatch, J.A. (2002). Doing Qualitative Research in Education Settings. New York, Suny Press.
  • Hwang, C.L., Yoon, K. (1981). Multiple Attributes Decision Making Methods and Applications. Berlin, Springer.
  • Iris, Ç., Christensen, J., Pacino, D., Ropke, S. (2018). Flexible ship loading problem with transfer vehicle assignment and scheduling. Transportation Research Part B: Methodological 111: 113-134.
  • Jiang, C., Wan, Y., Zhang, A. (2017). Internalization of port congestion: strategic effect behind shipping line delays and implications for terminal charges and investment. Maritime Policy & Management 44(1): 112-130.
  • Ke, G.Y, Li, K.W., Hipel, K.W. (2012). An integrated multiple criteria preference ranking approach to the Canadian west coast port congestion conflict. Expert Systems with Applications 39(10): 9181-9190.
  • Li, K.X., Lin, K.C., Jin, M., Yuen, K.F., Yang, Z., Xiao, Y. (2020). Impact of the belt and road initiative on commercial maritime power. Transportation Research Part A: Policy and Practice 135: 160-167.
  • Lirn, T.C., Thanopoulou, H.A., Beynon, M.J., Beresford, A.K.C. (2004). An application of AHP on transhipment port selection: A global perspective. Maritime Economics & Logistics 6: 70-91.
  • McCracken, G. (1988). The Long Interview. London, Sage Publications.
  • Merriam, S.B. (1988). Case Study Research in Education – A Qualitative Approach. San Francisco, Jossey-Bass Publishers.
  • Merriam, S.B., Grenier, R. (2019). Qualitative Research in Practice: Examples for Discussion and Analysis. San Francisco, CA, Jossey-Bass Publishers.
  • Mollaoğlu, M., Bucak, U., Demirel, H. (2019). A quantitative analysis of the factors that may cause occupational accidents at ports. Journal of ETA Maritime Science 7(4): 294-303.
  • Morgan, D.L. (1996). Focus Groups as Qualitative Research. New York, Sage Publications.
  • Nazemzadeh, M., Vanelslander, T. (2015). The container transport system: Selection criteria and business attractiveness for North-European ports. Maritime Economics & Logistics 17(2): 221-245.
  • Nishimura, E. (2020). Yard and berth planning efficiency with estimated handling time. Maritime Business Review 5(1): 5-29.
  • Notteboom, T.E. (2006). The time factor in liner shipping services. Maritime Economics & Logistics 8: 19-39.
  • Parung, G.A., Hidayanto, A.N., Sandhyaduhita, P.I., Ulo, K.L.M., Phusavat, K. (2018). Barriers and strategies of open government data adoption using fuzzy AHP-TOPSIS: A case of Indonesia. Transforming Government: People, Process and Policy 12(3/4): 210-243.
  • Paul, J.A., Maloni, M.J. (2010). Modeling the effects of port disasters. Maritime Economics & Logistics 12: 127-146.
  • Pekkaya, M., Bucak, U. (2018). Çok kriterli karar verme yöntemleriyle bölgesel liman kuruluş yeri seçimi: Bati Karadeniz’de bir uygulama. Uluslararası İktisadi ve İdari İncelemeler Dergisi 18.EYİ Özel Sayı: 253-268.
  • Saban, M., Güğerçin, G. (2009). Deniz taşımacılığı işletmelerinde maliyetleri etkileyen faktörler ve sefer maliyetleri. Dokuz Eylül Üniversitesi Denizcilik Fakültesi Dergisi 1(1): 1-16.
  • Somsuk, N., Laosirihongthong, T. (2014). A fuzzy AHP to prioritize enabling factors for strategic management of university business incubators: Resource-based view. Technological Forecasting and Social Change 85: 198-210.
  • Takebayashi, M., Hanaoka, S. (2021). Efficient inter-port cooperation considering port congestion and port charge. Maritime Transport Research 2: 100011.
  • Talley, W.K., Ng, M. (2016). Port multi-service congestion. Transportation Research Part E: Logistics and Transportation Review 94: 66-70.
  • Tseng, P.H., Cullinane, K. (2018). Key criteria influencing the choice of Arctic shipping: a fuzzy analytic hierarchy process model. Maritime Policy & Management 45(4): 422-438.
  • Uluslararası Taşımacılık ve Lojistik Hizmet Üretenleri Derneği, Lojistik Sektörü Raporu UTİKAD (2021). Erişim Tarihi: 15.03.2023, https://www.utikad.org.tr/images/HizmetRapor/utikadl ojistiksektoruraporu2021-1654.pdf adresinden alınmıştır.
  • Wang, J.W., Cheng, C.H., Huang, K.C. (2009). Fuzzy hierarchical TOPSIS for supplier selection. Applied Soft Computing 9(1): 377-386.
  • Wang, T, Tian, X., Wang, Y. (2020). Container slot allocation and dynamic pricing of time-Sensitive cargoes considering port congestion and uncertain demand. Transportation Research Part E: Logistics and Transportation Review 144: 102149.
  • Yeo, G.T, Roe, M., Soak, S.M. (2007). Evaluation of the marine traffic congestion of north harbor in busan port. Journal of Waterway, Port, Coastal, and Ocean Engineering 133(2): 87-93.
  • Yıldırım, A., Şimşek, H. (2003). Sosyal Bilimlerde Nitel Araştırma Yöntemleri. Ankara, Seçkin Yayınları.
  • Zhen, L. (2016). Modeling of yard congestion and optimization of yard template in container ports. Transportation Research Part B: Methodological 90: 83-104.
There are 44 citations in total.

Details

Primary Language Turkish
Subjects Maritime Business Administration
Journal Section Research Article
Authors

İlke Sezin Ayaz 0000-0002-7053-3940

Umur Bucak 0000-0001-5112-8133

Early Pub Date April 15, 2024
Publication Date
Submission Date December 7, 2023
Acceptance Date March 18, 2024
Published in Issue Year 2024 In Press Articles

Cite

APA Ayaz, İ. S., & Bucak, U. (2024). Liman Sıkışıklığı Faktörleri ve Çözümüne Yönelik Stratejilerin Analizi. Turkish Journal of Maritime and Marine Sciences1-15. https://doi.org/10.52998/trjmms.1401523

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