Türkiye'de Deniz Dış Ticaretine İlişkin Boş Konteyner Hareketlerinin İncelenmesi
Analysing Empty Container Movements In Turkey In Relation To Maritime Foreign Trade
Yazar: AHMET SELÇUK BAŞARICI
Danışman: DOÇ. DR. TANZER SATIR
İstanbul Teknik Üniversitesi / Fen Bilimleri Enstitüsü / Deniz Ulaştırma Mühendisliği Ana Bilim Dalı / Deniz Ulaştırma Mühendisliği Bilim Dalı
Derece: Doktora, 2018
Konu: Denizcilik = Marine ; Ulaşım = Transportation ; İstatistik = Statistics
Dizin: Dış ticaret dengesi = Foreign trade balance ; Konteyner taşımacılığı = Container transportation ; Konteyner terminali = Container terminal ; Mevsimsellik = Seasonality

Özet:
Deniz konteyner taşımacılığının önde gelen sorunlarından birisi, taşımacılığı hızlı ve güvenli hale getiren ana unsuru konteyner ekipmanının, sektörel verimsizliğin yarattığı nedenler kaynaklı boş hareketleridir. Ticaret dengesizliği ve operasyonel zorunluluklar boş konteyner hareketlerinin doğasında mevcutken, gemi operatörlerinin ticari kararları neticesi gerçekleşen boş konteyner hareketleri ek bir maliyet oluşturmaktadır. Ticari kararlar neticesi gerçekleşen boş hareketin boyutunun nasıl ortaya konulabileceği ve bu hareketin miktarının nasıl düşürülebileceği üzerine çözüm önerileri sunmak tezin konusunu belirlemiştir. 
Tez çalışmasında öncelikle konteyner hareketleri açıklayıcı veri analizine tabi tutulmuş, ticaret dengesizliği ve ticaret dengesizliği harici boş konteyner hareketlerinin miktarları incelenmiş, terminallerdeki konteyner dengesizliklerinin boyutu ortaya konulmuştur. Türkiye çapında 2012-2016 seneleri arasında 20' konteynerlere ilişkin olarak ticaret dengesizliği, toplam dolu konteyner hareketinin % 31'ine denk gelirken, ticaret dengesizliği harici boş konteyner hareketi dolu hareketin % 20'sini denk gelmektedir. Aynı dönemde 40' konteyner trafiğine ilişkin olarak ise bu yüzdeler sırasıyla % 17 ve % 26'dır. Bu sayılar ticaret dengesizliğinin ötesinde nedenler ile gerçekleşen boş hareketlerin önemine vurgu yapmaktadır. Türkiye'de mukim pek çok terminal hem 20' hem de 40' konteyner açısından dengesizlik arz etmektedir. 20' konteyner açısından Ambarlı ve Kocaeli hinterlantları ve Antalya terminali konteyner fazlasına sahipken, Gemlik ve İzmir-Aliağa hinterlantları konteyner eksikliği çekmektedir. Mersin-İskenderun hinterlantı kendine yeter bir görüntüye sahiptir. 40' konteyner açısından ise tüm hinterlantlar ve Antalya terminali benzer konumunu korurken sadece Kocaeli hinterlantı tersi bir görüntü çizmektedir.
Ticari kararlar neticesi gerçekleşen boş hareketin boyutu ayıklama yaklaşımıyla ortaya konulmaktadır. Bir terminal ya da hinterlanta ilişkin aylık veri seti baz alınarak öncelikle ticaret dengesizliği kaynaklı boş hareketler toplam boş konteyner hareketinden özgün olarak geliştirilen bir model ile ayıklanmaktadır. Ardından oluşan yeni veri seti kargo mevsimselliği kaynaklı boş hareketlerden ayıklanır. Türkiye terminallerine yönelik olarak operasyonel zorunluluk kaynaklı boş hareketlerin önde gelen ve fark yaratan nedeni mevsimselliktir. Öncelikle kargo mevsimselliğinin varlığı incelenmiş, mevsimsellik tespit edilen veri setleri zaman serisi analizi yöntemlerinden X-13 ARIMA-SEATS ile ayrıştırılmıştır. Ayrıştırma neticesi dolu konteyner hareketine ilişkin mevsimsel miktarlar tespit edilmiştir. Analiz edilen 112 veri setinin 33 adedinde kargo mevsimselliği mevcuttur. Mevsimselliğin terminal ya da hinterlant bazlı kabulü bağlamında 17 terminalde/hinterlantta mevsimsellik olduğu anlaşılmıştır. Özgün bir yorumlama doğrultusunda mevsimsel hareket, boş konteyner hareketlerinden ayıklanmıştır. Elde edilen nihai veri seti, terminal/hinterlant bazlı olarak gemi operatörlerinin bireysel ya da sektörel ticari kararları neticesi gerçekleşen boş konteyner hareket miktarını yansıtmaktadır. Bu hareketler piyasa etkisi kaynaklı olarak tanımlanmıştır. Tez çalışmasında piyasa etkisi kaynaklı hareketlerin nedenleri gemi operatörü bazlı konteyner dengesizliği ve gemi operatörleri arası rota bazlı rekabet olarak düşünülmüştür. Gemi operatörlerinin hinterlant ve ithalat-ihracat bazlı pazar paylarını barındıran ikinci bir veri seti üzerinden, hem her bir gemi operatörünün konteyner dengesizlik analizi yapılmış hem de gemi operatörleri arası rekabet seviyeleri özgün olarak oluşturulan entropi yöntemi temelli bir indeks vasıtasıyla ölçülmüştür. 
Türkiye çapında dört hinterlant tespit edilmiştir. Bir hinterlanttaki gemi operatörü bazlı konteyner dengesizliğinin toplamı ile piyasa etkisi kaynaklı boş konteyner hareketi arasındaki ilişki regresyon analizi ile incelenmiştir. 2012-2016 senelerine ve 20'- 40' konteyner ekipmanlarına ilişkin 32 adet gözlem değeri analize dahil edilmiştir. Piyasa etkisi kaynaklı boş hareketin % 33'ünün gemi operatörü bazlı konteyner dengesizliğinden kaynaklandığı sonucuna varılmıştır. İzmir-Aliağa hinterlantının 20' konteyner gözlem değerleri diğer gözlem değerleriyle uyumlu değildir. Uyumsuz gözlem değerleri göz ardı edildiğinde piyasa etkisi kaynaklı boş hareketin % 71'i gemi operatörü bazlı konteyner dengesizliği ile açıklanabilmektedir. Rekabet seviyesinin boş konteyner hareketine etkisi ise rekabet indeksi ve piyasa etkisi kaynaklı boş hareketi temsil eden konteyner dengesizlik oranı üzerinden aynı dönem verisi vasıtasıyla incelenmiştir. Yüksek konteyner hareketine sahip olan bir hinterlant ile düşük harekete sahip bir hinterlantın piyasa etkisi kaynaklı boş hareket miktarları üzerinden karşılaştırılması yanıltıcı olacağından boş hareket miktarının direkt alınması yerine oran kullanılması tercih edilmiştir. Bu iki değişkenin regresyon analizi, rekabet seviyesinin zayıfta olsa boş konteyner hareketini etkileyebileceğini göstermektedir. Gemi operatörleri arası yüksek rekabet, piyasa etkisi kaynaklı boş hareketin yaklaşık % 10'luk kısmını açıklamaktadır. 
Türkiye bağlamında ulaştığımız çıkarım, gemi operatörü bazlı konteyner dengesizliğinin birincil derecede piyasa etkisi kaynaklı boş hareketi tetiklediği, gemi operatörleri arası pazar payı bazlı rekabetin ise buna ikincil derecede katkı verdiğidir.

Abstract:
One of the major reasons of maritime container transportation is the fact of empty container movements occurring due to sectoral inefficiency. Beyond trade imbalance, empty movements are subject to operational drivers and other reasons arising from voluntary commercial decisions of ship operators, called the market effect. Container transportation inherently consists of both trade imbalance and operational drivers. However commercial decisions create extra costs i.e. operational cost and environmental disaster arising from empty container circulation. Submitting how to reveal the amount of empty movements originating from commercial decisions and submitting solution proposals how to decrease this determine the topic of this dissertation. 
First of all, this dissertation analyses empty container movements relevant to foreign trade of Turkey in terms of trade imbalance and other than trade imbalance. The amount of additional empty container movements (AECM) refers to the magnitude of empty movements other than trade imbalance. The amount of AECM has been calculated on terminal basis by means of a genuine model. Theoretically and generally in practice, any inbound container that is full or empty is expected to depart the same terminal as an outbound container that is full or empty, including deliveries to inland depots apart from exceptional cases. This fact in Turkish terminals shapes our model, which is called the closed-circuit model (CCM). A generic formula is proposed in this study to analyse the available statistical data on a terminal basis. The AECM calculation in this study covers only datasets of inbound and outbound traffics of Turkey but not the cargo operations under transit and cabotage regulations. The scope of a CCM has been extended to an area including several terminals rendering service for a common hinterland, where applicable. This study reveals that practically AECM is mainly reduced by two methods. These are container transfers between terminals and container interchange between ship operators. Accordingly, the magnitude of container imbalance on terminal basis has been revealed in the analysis. After deducting both from the original AECM called hereafter "true AECM - AECM_T"), the novel concept can be described as "visible AECM (AECM_V)". Namely, true AECM indicates the AECM if no equipment transfers or interchange was implemented. Each equipment interchange between ship operators reduces two units of containers for AECM (one for inbound and one for outbound traffic). Within this scope, the sum of visible AECM, equipment transfers between terminals/hinterlands (ECM_RC), and two-fold equipment interchange (N_IC  ) comprises the true AECM. 

AECM_T= AECM_V+ECM_RC+2N_IC

All versions of AECM are on terminal/hinterland basis. Since we do not have data about the amount of equipment interchange, we could not calculate true AECM. Nevertheless, we can calculate the sum of AECM_V  and EMC_RC. It is called here in this study as "initial AECM (AECM_I)".

AECM_I= AECM_V+ ECM_RC

The calculation steps of visible AECM have been detailed herebelow. In case the number of full inbound throughput is more than the number of full outbound throughput in a terminal, the difference between the numbers of full inbound and full outbound reflects the excess number of empty containers to depart (step 1). After extracting this from the number of actual empty outbound containers, we compute the number of departed containers except structural trade imbalance (step 2). Then, we add the number of empty inbound units to reach the total AECM (step 3). The AECM calculated herein is visible AECM because we can calculate it through a dataset including equipment transfers and interchanges already conducted. In case the number of full outbound throughput is more than the number of full inbound throughput, the difference between the numbers of full outbound and full inbound throughput reflects the short-coming of empty containers to arrive. After extracting this amount from the number of actual empty inbound containers, we compute the number of arrived containers except for structural trade imbalance. Then, we add the number of empty outbound units to reach the total number of AECM. 

Our model, the CCM, states the following:

 AECM_V= {  E_o-(F_i-F_o )+ E_i,        if F_i  ≥ F_o  or,
 AECM_V= {  E_i-(F_o-F_i )+ E_o,        if F_o  ≥ F_i 

Subject to     F_i+E_i=F_o+E_o

Where
Full Inbound Container Movement               :  F_i                                                                                                                    Full Outbound Container Movement              :  F_o                                                                                                                    Empty Inbound Container Movement              :  E_i                                                                                                                            Empty Outbound Container Movement             :  E_o                                                                                                                              Additional Empty Container Movement (Visible) : AECM_V   

The proposed methodology determines the true AECM, utilising a CCM, determining the effect of trade imbalance, and considering the effects arising from equipment transfer and interchange. However in this study AECM refers to initial AECM. Trade imbalance is the difference between full container inbound and outbound traffic of similar types of equipment. We can only distinguish 20-foot and 40-foot equipment types regardless of whether they are standard or special. The traffic between 2012 and 2016 for 20-foot equipment in Turkey where the trade imbalance ratio (trade imbalance/full in and out containers) is 0.31, the initial AECM ratio (initial AECM/full in and out containers) is 0.20. The traffic between 2012 and 2016 for 40-foot equipment the trade imbalance ratio is 0.17, the initial AECM ratio is 0.26. The results indicate that trade imbalance is not the sole reason for empty container movements in Turkish terminals. Several terminals in Turkey exhibit container imbalances both for 20-foot and 40-foot equipments. For 20-foot equipment, Ambarli and Kocaeli hinterlands and Antalya terminal have excess equipment, while Gemlik and İzmir-Aliaga hinterlands suffer from lack of equipment. Mersin-Iskenderun hinterland seems self-sufficient. For 40-foot equipment, all hinterlands and Antalya terminal keep the same outlook except Kocaeli hinterland which has a reverse situation.
The main approachment in the dissertation is the method of sorting each element out from total number of empty container movement. The first element to sort out is trade imbalance. Initial AECM reflects the remainder of sorting out process. The second element is operational drivers. The prominent driver in Turkey is cargo seasonality. Other operational drivers i.e. abundant container owners, container condition, uncertainties in demand/handling/shipment and blind spots in supply chain have been ignored because appropriate data have not been acquired. However effects of these parameters are limited for the case of Turkey. In terms of cargo seasonality, existence of seasonality in a dataset is investigated by combined seasonality test which comprises of parametric and non-parametric test procedures. If seasonality exists seasonality effect in a dataset of full container traffic is decomposed on monthly basis by means of X-13 ARIMA-SEATS which is one of major decomposition methods. In conclusion, in a number of 33 datasets in total 112 in hand, seasonality effect has been detected.  A genuine algorithm to determine whether seasonality exists on terminal or hinterland basis has revealed that a number of 17 terminals/hinterlands consists of cargo seasonality and a genuine interpretation has helped to sort the seasonality effect out from initial AECM. The final dataset on terminal basis in hand reflects empty container movements arising from commercial decisions of ship operators on individual or sectoral basis, i.e. market effect. Since the datasets of seasonality adjusted initial AECM represent market effect it can be described as AECM originating from market effect. The root causes of market effect are described as container imbalance based on ship operator and competition in a route among ship operators. We have two separate datasets to analyse. The first one includes inbound and outbound throughputs between 2006 and 2016 relevant to 18 terminals located in Turkey. The other one comprises full container throughputs on ship operator basis. Since they both are to be exploited one has to test that the same population is measured by two separate measurers. It was performed by Wilcoxon signed rank test. According to the test result it cannot be rejected that data pairs of each year are from the same population. Accordingly, both root causes have been analysed through regression analysis. In the analysis of container imbalance the dependent variable is AECM originating from market effect and the independent variable is total container imbalance based on ship operator. In the analysis of competition the dependent variable is a ratio connected with AECM originating from market effect and the independent variable is the element of competition index that was generated by utilising entropy method. Since it would be misleading to compare hinterlands of which one owns high amount of throughput while other one owns low, utilising the concept of ratio is preferable instead of utilising magnitude of AECM. The elements of the ratio are AECM and the amount of initial empty container movement which means that the amount of container transfer between terminals should be added on sea-going empty movement of foreign trade. Both regression analyses lean on both datasets for each variable. The study is limited to four hinterlands across Turkey. They are Istanbul-Kocaeli, Gemlik, Izmir-Aliaga and Mersin. For both regression analyses 32 observation units belonging to 20' and 40' types of container traffics between 2012 and 2016 were included. The results indicate that 33 percent of AECM originating from market effect arises from container imbalance based on ship operator. Furthermore it runs into 71 percent if the incompatible observation units of Izmir-Aliaga hinterland for 20' containers are removed from the dataset. On the other hand, the level of competition among ship operators feebly leads to AECM originating from market effect in Turkey. 10 percent of AECM originating from market effect can be explained by the effect of competition. 

As a result, regarding container throughput in Turkey, one might come up with the inference that primarily container imbalance based on ship operator and secondarily competition level among ship operators trigger empty container movements originated from market effect.