Maritime Transportation - INT
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IX Maritime Transportation In terms of port management, container circulation starts at the terminal gate. With the correct orientation at the gate, the lost time is tried to be reduced to minimum at the beginning of the circulationperiod.Inordertoaccomplishthis,variousautomationsystemsaredeveloped.Thispaper presentsacomparativeanalysisofgateentrysystemsatmajorcontainerportsinTurkey.Waittimes at gateways are used to compare different system types used at Turkish container ports and future worksaresuggested. GateEntrySystems,TurkishContainerPorts,ContainerCirculation Thecompetitivenessisstillanecessityinshippingindustryandportshaveitsshareinthatcomplex system.portswhichwanttousetheir potentialtrytobecomeahub portbyimprovingtheirservice level. A satisfactory service quality brings prestige and commercial success. Improvements are generally made in port’s location(Cuadrada et al., 2004), infrastructure (Tennet, 2004),information service(Tennet,2004),cost(Tongzon,1998),efficiency(Ugbomaetal.,2004),humanrecources(Ha, 2003) and customer services (Pedersen et al., 1998). Speed of operations and using web based informationsystemaresomefactorsintheseimprovementtools.Gateentryoperationsareconsidered astheweakestlinkinportoperations.AgateentrycirculationprocessispresentedinFigure1. Fromthepointofportmanagement,containercirculationstartsattheterminalgate.Withthecorrect orientationatthegate,thelosttimeistriedtobeminimizedatthebeginningofthecirculation.From manuel systemstotechnologicalsystems, variousgate entrymethods areused inportsalloverthe world.Inthisstudy,acomperativeanalysisofgateentrysystemsatmajorcontainerportsinTurkeyis presented. Elapsed time of a vehicle at gate entry process is measured for four ports in Turkey. ARENA simulation program is used in the analysis and some suggestions are made for further research. Inthisstudy,elapsedtimeofavehicleatgateentryprocessismeasuredforfourportsinTurkey.Two oftheseportsareoperatedbytheTurkishGovernmentandtherestisprivatized.Manualsystemand automatedsystemarecomparedfromthepointofelapsedtimeduringgateoperations.Measurements areperformedinpeakhoursbetweenavehicle’sgateentryandexittime. 553 Agateentrycirculationprocess(ArkasHolding,2008&Web1) Gathereddataisanalysedintwosteps.Firstly,dataisrunininputanalyserofARENA11.0simulation program.Figure2showstheoutputofthemanuelsystemdataandFigure3presentsthetheoutputof theautomatedsystemdata. 554 AnalysisofmanualdatainInputAnalyzer AnalysisofautomatedgatedatainInputAnalyzer The output of the first step is used for the second step which is modelling of the main scenario. Scenarioscanbemodelledasprenotifiedornotprenotified.Inthisstudy,threescenariosarerunand prenotifiedratioisacceptedas75%,85%and95%respectively.The mainmodelofthescenariois presentedinFigure4. ARENAmodelofthemainscenario 555 Thefinaloutputsofthemodelarepresentedbelow.Figure5showstheresultsofthefirstscenarioin which75%prenotifiedratioisaccepted.Accordingtotheresultstheelapsedtimeinmanualsytemis %1.99oftheelapsedtimeinautomatedgateentrysystem. Resultsofthefirstscenario Figure 6 shows the results of the second scenario in which 85% prenotified ratio is accepted. The results show that the elapsed time in automated gate entry system is 0.49 % of the elapsed time in manualsytem. Resultsofthesecondscenario Figure7showstheresultsofthethirdscenarioinwhich95%prenotifiedratioisaccepted.According totheresultstheelapsedtimeinautomatedgateentrysystemis2.01%oftheelapsedtimeinmanual sytem. Resultsofthethirdscenario As can be seen from the model outputs, vehicles enter ports which use manual system waste much moretimethanportsuseautomatedgateentrysysteminTurkey. Asasatisfactoryservicequalitybringsprestigeandcommercialsuccessportswhichwanttousetheir potentialtrytobecomeahubportbyimprovingtheirservicelevel.Speedofoperationsandusingweb 556 based information system are some important factors in port’s efficiency. Gate entry operations are consideredastheweakestlinkinportoperations. Container circulation starts at the terminal gate. From manuel systems to technological systems, various gate entry methods are used in ports. In this study, a comperative analysis of gate entry systemsatmajorcontainerportsinTurkeyispresented.Elapsedtimeofavehicleatgateentryprocess ismeasuredforfourportsinTurkey.TwooftheseportsareoperatedbytheTurkishGovernmentand therestisprivatized.Elapsedtimeduringgateoperationsareusedintheanalysis.Measurementsare performedinpeakhoursbetweenavehicle’sgateentryandexittime.Gathereddataisanalysedby ARENA 11.0 simulation program and its application. In this study, three scenarios are run and prenotifiedratioisacceptedas75%,85%and95%respectively.Theresultsofthemodelshowsthat vehicles enterportswhichuse manualsystemwaste muchmoretimethanportsuse automated gate entrysysteminTurkey. Accordingtotheresults,portsusemanualsystemmightchangetheirsystemtoautomatedgateentry systeminordertominimizevehiclewastingtimeingateoperations. For further research, the present study might be improved by modelling OCR and RFID systems regardingvehicleelapsedtimeingateoperations. ArkasHoldingA..,(2008)KapıOperasyonElKitabı,Istanbul. Cuadrado, M., Frasquet, M., Cervera A., (2004). Benchmarking port services: a custumer oriented proposal, BenchmarkingAnInternationalJournal,Vol.11,No.3,2004,pp.320330. Ha,M.S.,(2003),Acomparisionservicequalityatmajorcontainerports:implicationsforKoreanports,Journal ofTransportGeography,Vol.11,2003,pp.131137. Pedersen, E.L., Gray, R., (1998), The transport selection criteria of Norwegian exporters, International of PhysicalDistribution&LogisticsManagement,Vol.28,No.2,1998,pp.108120. Tennet,A.,(2004),Portchoicedeterminantsandportselectionprocessbasedontheperceptionsofcarriersand freightforwarders,Masterthesis,PukyongNationalUniversity,Busan,SputhKorea. Tongzon, J., (2002), Port choice determinants in a competitive environment, Proceeding of IAME 2002 Conference,Panama. Ugboma, C., Ibe, C., Ogwube, I. C., (2004), Service quality measurement in ports of a devoloping economy, ManagingServiceQuality,Vol.14,No.6,pp.487495 Web1,http://wwv.unescap.org/ttdw/common/TFS/ASIAMAR/FRETIS_TREDIT.pdf(28.05.2011) 557 Vector Autoregression Modelling for the Forecasting Freight Rates in the Dry Bulk Shipping Sector Emrah Bulut Kobe University, Japan, bltemrah@gmail.com Abstract The forecasting is significant for ship owners and companies because it has a potential to affect their profits. In the shipping market, income or profit depends on the freight rate which varies according to the type of ship and the time of the investment. Therefore, the ship owner should estimate the time of the high freight rate and determine the investment strategy accordingly. After the introduction of the Vector Autoregression (VAR) modeling, it has been widely applied to analyse and forecast time series data (Sims, 1980). In this paper, the Vector Autoregression (VAR) model is used due to it being the most appropriate model in forecasting the causality between HM and PM time charter rates. Therefore, a VARbased model is estimated to investigate the freight rate between the proposed tonnages. The monthly data between 2000 and 2009 is used for the VAR model. Keywords: Vector autoregression, Forecasting model, Handymax, Panamax. 1. Introduction A maritime economy is affected by factors that dominate the world economy and this influence indicates itself on different times for the diverse tonnages of different kind of ships. In particular, a change in freight rate on one tonnage will affect on different tonnage within a certain period in dry-bulk shipping sector. In this study, the correlation between changing of freight rate among Panamax (PM) dry-bulk carrier (75,000 deadweight tons - DWT) and Handymax dry-bulk carrier (55,000 DWT) is investigated and the direction of this interaction is revealed. As it is well known the measurable value that determines the direction of the maritime economy is freight rate. For the investor and the owner, one of the most important factors that affect profitability is the accuracy of the forecast of the freight rate. In the existing literature, there are many studies that investigate the freight rates and its forecasting possibility by using statistical methods. One of the first indications in the classical econometric analysis in maritime is Koopmans’ study which investigated the deterministic factor of freight rates in terms of a supply and demand model (Koopmans, 1939). Beenstock (1985) stated a theoretical model in which freight markets and ship markets have high correlation and 559 which is applied to analyze the dry bulk cargo market and the tanker market (Beenstock & Vergottis, 1989a, 1989b). Cullinane (1992) has proposed the Box-Jenkins method as a tool for forecasting the Baltic Freight Index (BFI). According to their studies, an assessment of the forecasts derived from the model suggests that the specification of these long-term relationships does not improve the accuracy of short or long-term forecasts. The relationship between spot freight rates and time charter (TC) rates is investigated by using Vector Error Correction Models (VECM) (Kavussanos & Alizadeh-M, 2001; Kavussanos & Nomikos, 2000; Veenstra, 1999). Merikas and Koutroubousis (2008) investigated the price ratio between the second hand (SH) vessels and newbuilding (NB) vessels for tankers by using co-integration testing method. The result of this study revealed that the SH/NB price ratio is positively related to the freight rate. The purpose of this paper is to investigate causality conditions between the Handymax-Panamax size dry bulk markets and to estimate spillovers between prices. Panamax size bulkers are particularly employed in long distance raw material routes and freight rates are affected from contribution of the economy of scale. Handymax size bulkers are usually employed for similar shipments in shorter distances and for minor industries. The particulars of charterers generally differ due to their business volume and production capacity. Among the different sizes of dry bulk carriers, Handymax and Panamax size ships are the most nearest tonnages and a possible size competition exists between these parcel sizes. Kavussanos (1996) indicates that the level of volatility declines in accordance with downsizing of the tonnage. Capesize bulkers (over 80,000 dwt, particularly over 100,000 dwt) have 62% share in whole dry bulk market while Panamax and Handymax sizes cover around 20% and 18% respectively (Wikipedia). In the sale & purchase market, the selection among the Panamax and Handymax tonnages is another critical question. After the introduction of the Vector Autoregression (VAR) model, it has been widely applied to analyse and forecast time series data (Sims, 1980). In this paper, the Vector Autoregression (VAR) model is applied because it is the most appropriate model in forecasting the causality between HM and PM time charter rates. Therefore, a VAR-based model is estimated to investigate the freight rate between the proposed tonnages. The monthly data between 2000 and 2009 is used for the VAR model. In the shipping literature, Veenstra and Franses (1997) investigate monthly ocean dry bulk freight rates for three different routes by using a vector autoregressive model under the co-integration condition. The remainder of this paper is organized as follows: Section 2 briefly describes model and method used in this paper. Next, section 3 presents empirical study, application and result. Finally, conclusion is the subject of the last section. 2. Methodology 560 2.1. Vector autoregression (VAR) The vector autoregression (VAR) model is proposed to analyse the multivariate time series (Sims, 1980). The VAR is a systems regression model that can be considered a kind of hybrid between the univariate time series models; therefore, the VAR model depends on more than one variable. The VAR model is widely used to forecast the economic and financial dynamic behaviour of time series. It often provides superior forecasts to those from univariate time series models and elaborate theory-based simultaneous equations models. For the simple case, the mathematical form of a bivariate VAR, where there are only two variables, PM and HM, is as follows; k k PM t j PM t j j HM t j u1t (1) j 1 j 1 k k HM t ' j PM t j j HM t j u2t (2) j 1 j 1 where uit is a white noise disturbance term with E(uit) = 0 and PM is Panamax and HM is Handymax. The general VAR model has many parameters that may be difficult to interpret due to complex interactions and feedback between the variables in the model. As a result, the dynamic properties of a VAR are often summarized using various types of structural analysis. The three main types of structural analysis summaries are (1) Granger causality tests; (2) impulse response functions; and (3) forecast error variance decompositions. 2.2. Unit root test In statistics, it is important that the unit root test is applied to observe whether a time series data is stationary or non-stationary because the traditional statistical analysis assumes that the time series at hand are stationary. There are two different methods widely used for unit root test, Augmented Dickey-Fuller test (ADF) (Dickey & Fuller, 1979) and Phillips-Perron test (Phillips & Perron, 1988) and ADF test is applied in this study. For the ADF test, the null hypothesis assumes a time series is non-stationary with a unit root. In this study, time series for PM and HM are non-stationary at 1%, 5% and 10% level; therefore, the first order differences are required to obtain stationarity. The calculation of first order differences is as follows: Δ Y(t) = Y(t)− Y(t-1) (3) 2.3. Granger causality test Granger-causality test determines whether lagged values of one variable helps to predict another variable. For the VAR analysis, the Granger-causality test reports the correlation between time series and whether 561 there is a causality between them coefficient on the lagged are statistically different from zero in the equation. The test involves estimating the following pair of regressions: n n PM t i HM t i j PM t j u1t (4) i 1 j 1 n n HM t i HM t i j PM t j u2t (5) i 1 j 1 where u1t and u2t are white noise disturbance assumed that the disturbances u1t and u2t are uncorrelated and PMt and HMt are two different variables. Causality tests seek to answer simple questions of the type, ‘Do changes in PM cause changes in HM? The argument follows that if PM causes HM, lags of PM should be significant in the equation for HM. On the other hand, if HM causes PM, lags of HM should be significant in the equation for PM. For the first case, it would be said that PM ‘Granger-causes’ HM or HM ‘Granger-causes’ PM for the second case. If both sets of lags were significant, it would be said that there was ‘bi-directional causality’ or ‘bidirectional feedback’. In this paper, all statistics equations are computed by using Eviews software. 3. Application and results Table 1 shows descriptive statistics for a HM ship and a PM ship. The freight rate is the measurement of profitability for the owners. According to descriptive statistics, mean of freight rate of PM ships is higher than HM ships; however, it is not known whether the difference of mean of freight rate between PM ships and HM ships compensates the difference of initial cost between PM ships and HM ships because the initial cost of PM is higher than HM. Table 1. Descriptive statistics for a HM ship and a PM ship. Mean Median Std. Dev. Skewness Kurtosis HM 21331.65 17612.50 14920.76 1.537153 4.720162 PM 25740.64 20656.25 18876.96 1.450644 4.398514 Fig. 1 shows the correlation between HM ships and PM ships. They have high correlation, 0.9863, which indicates that the HM and PM are co-trended but the course of causality is also important for the forecasting. 562 Fig. 1. Time series data set for HM ships and PM ships. All variables in the VAR are required to be stationary in order to apply the significance tests on the lags of variables. Therefore, the ADF test for all variables is used to explore whether unit root exists in time series data sets. The time series for each data of PM and HM is found non-stationary (existing a unit root); hence, first difference of data sets is computed to obtain the stationary data (Table 2). Table 2. ADF test for Handymax and Panamax after first order difference calculation. Null hypothesis is based on existence of a unit root. d(HM)* Augmented Dickey-Fuller test statistic Test critical values: d (PM)* Augmented Dickey-Fuller test statistic Test critical values: * d( ): The first differences of series -5.627605 1% level 5% level 10% level -5.973516 1% level 5% level 10% level t-Statistic 0.0000 -4.030729 -3.445030 -3.147382 t-Statistic 0.0000 -4.030729 -3.445030 -3.147382 Prob. Prob. The first step for the VAR model should be to determine the appropriate lag length and the same variables is required for the VAR to be unrestricted. In order to determine the appropriate lag lengths for a VAR, the multivariate generalization of Akaike’s information criterion (AIC) is applied (Akaike, 1974). Because Burnham and Anderson (2002) argue that AIC has theoretical advantages and Yang (2005) exposes that AIC is asymptotically optimal in selecting the model with the least mean squared error. The result of Lag length criteria for the VAR shows that the fourth length is appropriate for the lag (Table 3). The forecasting plays a significant role for the owners and it affects companies’ profit. If the causality from HM ships to PM ships is ignored and the data set of PM or HM is just considered in the VAR model, the result of the forecasting can be inaccurate. For instance, according to the causality between HM and 563 PM, not only using the time series data of PM but also the time series data of HM can be used for the forecasting of freight of PM ships in VAR model. Table 3. The selection of lag length. Sample: 2000M01 2010M12 Lag LogL LR FPE 0 -2175.815 NA 2.70e+13 1 -2114.729 119.0914 1.03e+13 2 -2106.048 16.63394 9.56e+12 3 -2103.861 4.115336 9.85e+12 4 -2097.573 11.62516 9.48e+12* 5 -2096.674 1.632603 1.00e+13 6 -2093.864 5.006312 1.02e+13 7 -2089.879 6.965535 1.02e+13 8 -2084.251 9.647200* 9.95e+12 * indicates lag order selected by the criterion LR: sequential modified LR test statistic (each test at 5% level) FPE: Final prediction error AIC: Akaike information criterion SC: Schwarz information criterion HQ: Hannan-Quinn information criterion AIC 36.60193 35.64251 35.56383 35.59431 35.55585* 35.60796 35.62796 35.62821 35.60086 SC 36.64864 35.78264* 35.79737 35.92127 35.97623 36.12175 36.23516 36.32883 36.39489 HQ 36.62090 35.69941 35.65866* 35.72708 35.72655 35.81660 35.87453 35.91271 35.92329 Table 4. The pairwise Granger causality tests Sample: 2000M01 2010M12 Lags: 4 Null Hypothesis: dPM does not Granger Cause dHM dHM does not Granger Cause dPM Obs 127 F-Statistic 13.1506 5.08133 Prob. 0.0000 0.0008 * Significant at 0.05 confidence level For the VAR estimate model for PM ships, coefficient of first, second and fourth (except third) lags are statistically significant for the forecasting equation of freight rate. The just coefficient of fourth lag of HM and the coefficient of first, second and fourth lags of PM are statistically significant impact for the VAR estimation model of HM ships (Table 5). In addition, in the VAR model, the sum of residuals should be always zero for being uncorrelated with the predicted results. Table 5. The VAR estimation models for Panamax and Handymax. For Panamax Variables C dPM(-1) dPM(-2) dPM(-3) dPM(-4) dHM(-1) dPM 8.360d (PM )1 3.819d (PM )2 3.309d (PM )4 2.100d (HM )1 2.709d (HM )2 3.195d (HM )4 Estimated -0.448 Standard Coefficient 9.856 1.266 -0.722 0.244 -0.588 0.213 564 t-statistics Error 222.304 0.151 0.189 0.194 0.177 -2.100* 0.044 8.360* -3.819* 1.258 -3.309* dHM(-2) dHM(-3) dHM(-4) R-squared Adj. R-squared 0.608 -0.232 0.667 For Handymax dHM 1.992d (HM )4 6.654d (PM )1 3.186d (PM )2 1.920d (PM )4 0.224 0.228 0.208 0.654 0.630 C 23.508 dHM(-1) 0.005 dHM(-2) 0.269 dHM(-3) -0.237 dHM(-4) 0.303 dPM(-1) 0.735 dPM(-2) -0.439 dPM(-3) 0.214 dPM(-4) -0.249 R-squared 0.649 Adj. R-squared 0.625 * Significant at %5 confidence level ** Significant at %10 confidence level 2.709* -1.017 3.195* AIC SBIC 0.155 0.163 0.166 0.152 162.201 0.110 0.138 0.141 0.129 AIC SBIC 18.556 18.757 0.032 1.164 -1.422** 1.992* 0.144 6.654* -3.186* 1.510** -1.920* 17.925 18.127 According to the table 5, Panamax freight rates are figured to be affected by itself and Handymax rates. However, Handymax freight rates are particularly leaded by Panamax rates. Both high t-statistics and coefficient indicate that the direction of lead-lag effect is strongly presented in Panamax →Handymax (PMHM) direction. A possible reason of the PM-HM direction is the relative domination of the Panamax size in the market and substitution of Handymax fleet. Charterers tend to hire Panamax size as much as possible and alternatively choose Handymax tonnage. In the freight markets, multiple chartering for a single voyage is common and several holds of the hull is hired to different shippers. Similar group of shippers may prefer larger size (Panamax) in case of proper parcel size and smaller size (Handymax) in case of limited parcel size. Intentions are switching based on the charterers’ parcel size and also available cargo in the loading port. While contracts of Handymax and Panamax fleet have close relationship, Capesize and Handysize fleet have distinction because of their specific parcel size and charterer characteristics. 4. Conclusion In this study, the appropriate VAR estimation model is investigated for the PM ship and HM ship. For this purpose, Granger causality test is applied to reveal the direction of causality between PM and HM and it is seen that there is bidirectional causality for them. Therefore, the bivariate VAR model is applied for the forecasting of the shipping freight rate. The lag length plays significant role for the accuracy of VAR estimation model and the fourth lag length is appropriate according to the AIC. According to the VAR estimation model, the constant is not statistically significant and three variables of PM and HM for VAR estimation model for PM are statistically 565 significant. The variables of PM have amazingly more significant than the variable of HM that one coefficient is just statistically significant. The lead-lag relationship indicated that the market of 40k-80k DWT has strong cross links while broadly leaded by the rates of Panamax tonnage. References Akaike, H. (1974). A new look at the statistical model identification. Automatic Control, IEEE Transactions on, 19, 716-723. Beenstock, M. (1985). A theory of ship prices. Maritime Policy & Management, 12, 215-225. Beenstock, M., & Vergottis, A. (1989a). An econometric model of the world market for dry cargo freight and shipping. Applied Economics, 21, 339 - 356. Beenstock, M., & Vergottis, A. (1989b). An Econometric Model of the World Tanker Market. Journal of Transport Economics and Policy, 23, 263-280. Burnham, K. P., & Anderson, D. R. (2002). Model selection and multimodel inference: a practical informationtheoretic approach: Springer. Cullinane, K. (1992). A short-term adaptive forecasting model for BIFFEX speculation: a Box—Jenkins approach. Maritime Policy & Management: The flagship journal of international shipping and port research, 19, 91 - 114. Dickey, D. A., & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series With a Unit Root. Journal of the American Statistical Association, 74, 427-431. Kavussanos, M. G. (1996). Comparisons of Volatility in the Dry-Cargo Ship Sector: Spot versus Time Charters, and Smaller versus Larger Vessels. Journal of Transport Economics and Policy, 30, 67-82. Kavussanos, M. G., & Alizadeh-M, A. H. (2001). Seasonality patterns in dry bulk shipping spot and time charter freight rates. Transportation Research Part E: Logistics and Transportation Review, 37, 443-467. Kavussanos, M. G., & Nomikos, N. K. (2000). Constant vs. time-varying hedge ratios and hedging efficiency in the BIFFEX market. Transportation Research Part E: Logistics and Transportation Review, 36, 229-248. Koopmans, T. C. (1939). Tanker freight rates and tankship building: an analysis of cyclical fluctuations: Bohn. Merikas, A. G., Merika, A. A., & Koutroubousis, G. (2008). Modelling the investment decision of the entrepreneur in the tanker sector: choosing between a second-hand vessel and a newly built one. Maritime Policy & Management: The flagship journal of international shipping and port research, 35, 433 - 447. Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75, 335-346. Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48, 1-48. Veenstra, A. W. (1999). Quantitative Analysis of Shipping Markets. T99/3, TRAIL Thesis Series. Delft University Press: The Netherlands. Veenstra, A. W., & Franses, P. H. (1997). A co-integration approach to forecasting freight rates in the dry bulk shipping sector. Transportation Research Part A: Policy and Practice, 31, 447-458. Yang, Y. (2005). Can the strengths of AIC and BIC be shared? A conflict between model indentification and regression estimation. Biometrika, 92, 937-950. Wikipedia: http://en.wikipedia.org/wiki/Bulk_carrier#cite_note-18 566 Department of Maritime Transportation and Management Engineering,Đstanbul University, Avcılar, Đstanbul, Turkey, gelmas@istanbul.edu.tr 567 568 569 570 571 572 573 574 Planning Phase Engineering Phase Pre-planning Detailed Planning Kick-off Meeting Manning Requirements Fact Finding Validation by Simulation Layout Planning Financial Analysis Commissioning Phase Capacity Analysis Criteria Aggregation & System Recommendation Equipment Requirements System Decision 575 576 577 578 579 580 581 582 AIS Implementation to Turkish Aids to Navigation System (An electronic support to safety of navigation in Turkish waters) Bilal Emiroğlu Abstract Keywords: 1. Introduction 583 2. General view to AIS and usage of its technology 3. Shore Applications of AIS and General AIS AtoN Concept 584 4. AtoN Service and AIS Developing Process in Turkey 585 5. Turkish AIS AtoN System (SOTAS Project) 586 Fig. 1. 587 Fig. 2. 6. SOTAS System Components and Functions Fig. 3. 588 589 Fig. 4. Fig. 5. 7. Benefits of AIS Aids to Navigation Application in Turkey 590 Fig. 6. 8. Unique Applications of SOTAS Project and Planned Enhancements for Second Phase 591 9. Conclusions 592 References 593 Investigation of Turkish Container Ports Abdi Kükner, İlke Özgen Köleli Istanbul Technical University, Turkey, kukner@itu.edu.tr, koleli@itu.edu.tr Abstract Turkey has an important place in the World’s container transportation in Mediterranean, Middle East, Aegean and Black Sea Regions and this severity is increasing day by day. In this study traffic of TEU 20 and TEU 40 containers in Izmir, Haydarpaşa and Mersin Ports are examined with respect to the last 10 years’ data to analyze the fluctuations of the export and import. Hinterland connections of each port are studied; connected world ports and markets accessed through the land are analyzed according to transported product types. Conditions of three main container ports in Turkey are analyzed by SWOT method. In this analysis, graphics and detailed advantages and disadvantages according to bureaucratic decisions of each port, existing private projects, projects that have incentive from government, restructurings, handling and optimization capacities are considered. As a result, solutions have been suggested for existing deficiencies. Furthermore, it must be denoted that there is no hub port in Turkey which might enhance great opportunities and economic developments. How to create a hub port in Turkey is also defined in the study. Keywords: İzmir Alsancak Port, Mersin Port, Haydarpaşa Port, Sea Transport, Container Transport, Container Ports 1. Introduction Sea transport is the most important means of transport among other sectors contributing to national economies and its significance has been growing rapidly. Thanks to its advantages container transportation has an ever-growing dynamism and thus new large hub ports with massive hinterlands have been constructed in the world. These ports are supposed to have not only strategic and geopolitical locations but also appropriate infrastructure and high operational systems. Significantly; land, sea and air connections of the ports have to be deployed and well managed. 595 2. Ports in Turkey Surrounded with three seas and having long cost line, Turkey geopolitically operates as a gate opening to Asia, Europe, Central Asia and Middle East. Thus, developing highly equipped ports with not narrow but large hinterlands is very important in Turkey. ¼ of the world’s container transportation traffic proceeds through Mediterranean. Therefore, planning a new project to benefit from the advantages of Izmir and Mersin Ports and attracting the traffic to our Mediterranean ports will be a significant step for Turkish economy. Shortening the lay days, having large container storage areas, and in case of insufficient storage areas modernizing storage handling machines can make significant contributions to the efficiency of ports and increase the financial turnover. 2.1. İzmir and Alsancak Port Izmir is the third largest city and one of the leading trade centers of Turkey as well as the urban center of a large industrial and agricultural region and it is located on a geopolitically important region. Only container handling port of Aegean Region Izmir Alsancak Port is located at the head of the Gulf of Izmir on the Aegean Sea and has natural protection and operational advantages thanks to its location. Izmir Alsancak Port meets not only the Aegean Region’s demands but also Marmara and inter Anatolia are included in its large hinterland. Fig. 1. A view from İzmir Port 596 2.1.1. Container Docks on Port and Container Transportation The container terminal of Izmir Port has seven berths with alongside depth of 13 meters. The port also has ample storage facilities. The container terminal covers 152,000 m² and has holding capacity for approximately 7,000 TEU’s. Container ships have to stay in long queues in Izmir Port because of long lay days and lengthy operations. Under these circumstances losses in dispatch earnings, late fees may occur. These problems leaf exporter and importer ship owners to look for alternatives and shifting regional potential to other alternative means of trade threatens the regional economy. The main reason of the retardations in the port is the operational deficiency. Equipments frequently go out of order, delays may occur because of repairs, insufficient equipments prolong the days of discharging. Disorganized use of area and planning mistakes hinder effective use. Besides, entrances of heavily loaded ships are not detected and thus service ranges are limited. The studies about Izmir Port mostly focus on the optimization of storage areas and increasing water depth. As already pointed out, increasing the capacity of storage areas enhances storage so that port can be used extensively and efficiently. One of the most important problems is the length of waiting periods in the port or off-shore and these periods should be shortened. By increasing the depth of seashore, the port can be made available for fully loaded ships. Despite the fact that the port has a crucial geographic location, the port is badly affected by these problems. Considering all these angles SWOT analyses demonstrate in Table 1: Table 1: SWOT analyses for İzmir Port Strenghts: Weaknesses Appropriate sea entrance Rapid growing trade volume Employees are qualified enough to use modern equipments Near to the industry zones Naturally protected Chance of expansion Appropriate geographic and logistic location Deficiency of handling equipments and long lay days in offshore waters Weaknesses of labor force Strict regulations and tariffs Lay days Low handling performance compared to the world standards Inefficient administration Pollution in the Gulf No chance of extension or widening Opportunities: Threats: Most significant geographic location of the region Price policies of competitive ports Chance of modernization with R&D initiatives No chances of expansion Appropriate water structure and depth Other privatized ports making sizeable New container storage area project on the port investments Water channel detection project for large DWT ships Strategies: Gaining the previously lost ships back by shortening lay days Using port area effectively by optimizing storages and necessarily creating external area to attract new ships Implementing technological devices to the port in order to modernize and provide succesful logistic management Increasing depth by using water detection 597 2.2. Mersin and Mersin Port Since 1860 port side constructions have been important in Mersin and in 1886 after the opening of Adana-Mersin railway, the number of visitor ships has increased. The Port of Mersin lies on the north end of the Mersin Bay off the Mediterranean Sea. It is the main port serving eastern Mediterranean agriculture and industry. This port has easy access to the nation’s rail and highway networks. Port also has modern infrastructure, ample-cargo handling equipment and vast areas of storage. Mersin’s Port container terminal covers 251.400 m² and the container yard has capacity for 10.000 TEU’s. Construction of Mersin Port started on 3rd May 1954 under modern and safe circumstances by Netherlands Royal Port Construction Company. The port started its operations in 1962 with its all supplied facilities and was privatized for Akfen Holding and PSA International in 12.05.2007.. Fig. 2. A view from Mersin Port 2.2.1. Container Transportation Mersin Port, one of the important ports of East Mediterranean, is not only the trade gate to Central Anatolia, Mediterranean and Southeast Anatolia but is also a transit center for Middle East. In the port which has 28 docks, approximately 30 ships can be loaded and unloaded simultaneously. Port has services for passengers, bulk cargos, containers, living animals, grain transportation and petroleum ships. Privatized in May 2007 port’s capacity has grown by % 30 and since it was taken over, a number of infrastructure applications have been conducted to keep up with the world standards. In the frame of this infrastructure applications after the completion of cementation and asphalting operations for container storage, arrangement of inner port traffic and acceleration of operations, port became ready to serve. 598 “New Railway Project” which has been planned to improve the operational efficiency of Turkish State Railways and MIP is still on progress. With these arrangements loading and unloading operations of wagons can be done in only one area and trains will not need to maneuver. Thanks to the advantages of the project train entrances and exists will be under superhighway and Adana-Mersin motorway will not be blocked with train passing. Mersin Free Zone renders services directly to Mersin Port and thus developments in the region will result in the improvements for the port’s economic and international vision. Mersin is also the place from which transportation toward to other industrial cities such as Kayseri, Gaziantep, Konya, and Maraş flows. Considering all these angles SWOT analyses demonstrate that: Table 2: SWOT analyses for Mersin Port Strenghts: Geographic and strategic location of the port Handling availability everyday Existing motorway connections Near to airways Near to industrial cities Located in a region with international trade network Being equal to international standards Weaknesses: Underdeveloped railway connections Insufficient computer network Unqualified employees Dune formation because of wind and currents and need for detection in the port Insufficient bilingual personnel to communicate with foreign ships Opportunities: Threats: Insufficient industrial movements in hinterland Low turnover of Mersin Port in case of international crises Effects of the port to hinterland, developments in industry Obscurity of Turkey and international Port’s place in international trade environment Port’s hinterland is not large enough Strategies: Extension of container area and developing terminal stations Sustainability of trade and keeping track of technology Increasing diversity and container handling in case of any imminent economic crises Building up modernization and administrative structure to compete with other Mediterranean ports Use of bar-coding for efficient container storage Effective realization of present projects especially railway projects 2.3. Haydarpaşa and Haydarpaşa Port Construction of Istanbul’s biggest trade port started in 1873 after Haydarpasa-Izmit railway route was put into service. The port of Haydarpaşa is located in Anatolia side of Istanbul, on the shares of Marmara Sea. The Port has a container land terminal outside of the port, in Göztepe district for stacking. Total container 599 handling capacity of the five container terminals is 1,200 vessels a year. The space for container terminal is approximately 100,000 m² with a handling capacity of 6,000 TEU’s. It covers an area of 55,000 m² with a holding capacity of 52,800 TEUs. Fig. 3. A view from Haydarpaşa Port 2.3.1. Container Transportation Haydarpaşa Port has a strategic location but has many deficiencies in terms of modernization. Particularly because of insufficient storage areas, loading and unloading operations cannot be managed efficiently and this results in long lay days as it is the case in Izmir Port and also there is loss of time and shipping charge. Considering all these dimensions of Haydarpaşa SWOT analyses demonstrate that: Table 3: SWOT analyses for Haydarpaşa Port Strengths: Close to industrial zones Freight easiness because of its location in city center Easy accessibility to satellites because of its location Motorway, airway and railway connections Opportunities: Effects of the port on hinterland Port’s place in foreign trade Narrow hinterland Weaknesses: Environmental pollution Long lay days Inappropriate neighborhood for expansion Insufficiency of computer systems and qualified employees Insufficient number of docks compared to ship capacities Threats: Other new port projects and planning because of the port’s insufficiency Strategies: Extension of container areas or replacing the storage areas outside the terminal as satellite areas Keeping up with technology and successful administration Modernization of equipments 600 3. Conclusion Considering three ports altogether, it is obvious that Izmir made more handling in each and every year however after 2006 due to privatization Mersin Port kept up with Izmir Port in two segments. Haydarpaşa Port had and increasing trend but after 2007 it was in decline in two segments. Mersin Port is the greatest power of the region in container transportation and this will make Mersin a “logistic center” leading all southern and neighbor cities arises from Mersin Port. Transit loads coming to Mersin by seaway have been transported to Middle Eastern countries and Middle Asian Turkish Republics by railway. Mersin Port will constitute the most. Mersin Port will develop on its own and influence regional economy because it has a significant location in Mediterranean and is turning into a hub port. After infrastructure and necessary administrative planning applications it will be making considerable contributions to Turkey’s economy. After privatization some projects which are on the parallel of economic developments, have been implemented to provide convenience for exporters and importers. First project offered to Turkish State Railways and supported by EU aims to connect Mersin-Samsun railway bridge with Mediterranean and Black Sea Regions. There are also projects to shift Iranian and Iraqi transit loads to Mersin. Projects, aiming to develop sea transport between Mersin and Egypt, rollon roll-off transport from Mersin to Europe and cruise tourism in Mersin, are also present. Izmir Port has no chance of extension and it is in the inner- city. Therefore port is planned to be moved in Çandarlı region. After this arrangement, possibility of an increase in container capacity will be observed. Technological improvements, modernization, advanced computer networks, modern handling equipments and implementation of automation systems will be a crucial step and affect regional employment. Future of Haydarpaşa Port is obscure because its operations are dependent on political decisions. It is estimated that the port will be changed for a tourism center called Galataport and the container port can be moved to Tekirdağ or Ambarlı. If the reformation of the port is confirmed, extension of terminal area, modernization of handling and logistics equipments will be of great importance. A successful operational administration can guarantee fast and flawless services, saving of time and money. References Deniz Ticaret Odası 2007 Deniz Sektörü Raporu, İstanbul 2008 Yüksel Y. & Çevik E. & Akyarlı A. & Yalçıner C. & Güler I., (2002) Dünya Limna Örnekleri ile Türkiye Limancılık Politikası Üzerine bir Çalışma, 4. Kıyı Mühendisliği Ulusal Sempozyumu, Antalya 601 Aydınoğlu N. & Yetkin Ü. & Güler I. & Akarsu Ö. & Çelebi N., (16-20 Ekim 2007) Liman Yapıları ve Demiryolu Köprüleri Deprem Yönetmeliğinde Performansa Göre Tasarım Yaklaşımı, 6. Ulusal Deprem Mühendisliği Konferansı, İstanbul Oral Z., (2004) İzmir Alsancak Limanının Darboğazları, 6. Kıyı Mühendisliği Ulusal Sempozyumu Oral Z. & Karataş Ç., (2004) Aktarma Limanlarının Seçim Kriterleri, 6. Kıyı Mühendisliği Ulusal Sempozyumu Ceylan H. & Baykan N. & Haldenbilen S. & Ceylan H., (2004) İzmir Limanına Yapılacak Ek Konteyner Terminalinin Depolama ve Elleçleme Kapasitesinin Araştırılması, 6. Kıyı Mühendisliği Ulusal Sempozyumu Baykan N. & Baykan O., Limanlarda Konteyner Sahalarının Planlanmasında Yeni Bir Yaklaşım, 6. Ulusal Kıyı Mühendisliği Sempozyumu Gürhan G., (2000) İzmir Limanı Konteyner Terminali Optimum Kapasite Analizi, 3. Ulusal Kıyı Mühendisliği Sempozyumu, Çanakkale Özmen İ. & Özen S., (2000) Limanlardaki Konteyner Depolama Sahalarının Optimum Boyutlandırılmasına Yönelik Bir Yöntem, 3. Ulusal Kıyı Mühendisliği Sempozyumu, Çanakkale Elçin E., (Şubat 1998) Konteyner Taşımacılığında Navlun Hesap Modeli, Yüksek Lisans Tezi Sukas N., (Haziran 1998) Konteyner Gemilerinde Yatırım Analizi, Yüksek Lisans Tezi Yılmazer D., (2005) Türkiye’de Planlanacak Bir Analiman Üzerine Çalışma ve Ege Bölgesi Örneği, Doktara Tezi “İzmir Limanının Yük Trafiği Yolları tıkıyor”, http://www.destinationizmir.com/haber_detay.asp?haberID=1086 “İzmir Limanı 1.275 Milyar Dolar”, http://arsiv.ntvmsnbc.com/news/406960.asp “İzmir imanı Adeta Sinek Avlıyor”, http://www.denizhaber.com.tr/limanlar/17387/izmir-limani-adeta-sinekavliyor.html Mersin Limanı İstatistikleri, http://www.mdto.org.tr/istatistik.asp?islem=akat&id=31 Mersin Limanı İşlenmeyi Bekleyen bir Pırlanta, AKIB Aktüel, http://www.virahaber.com/haber/mersin-limanipirlanta-5027.htm Global Krizden Mersin Limanı Karlı Çıkıyor, http://www.mersintercuman.com/detay.asp?p=h1049 Mersin Limanı Hakkında Genel Bilgi, http://www.mdto.org.tr/icerik.asp?id=164 Mersin Limanına Bağlı Dünya Limanları, http://www.mdto.org.tr/icerik.asp?id=175 “Mersin Limanına 6 Yeni Proje”, http://www.lojiport.com/news_detail.php?id=12196 MIP, Mersin International Port, http://www.mersinport.com.tr/ “Mersin Limanı Sorunları ve Gelişimi”, http://www.denizhaber.com/index.php?sayfa=yazar&id=3&yazi_id=100216 602 Oil Tanker Shipping in Turkey Gülsüm Aydin, Sibel Bayar Çağlak, Güler Alkan Abstract KeyWords: 1. Introduction 2. General Terms of Tanker 603 are designed to move petrochemicals from refineries to points near consuming markets. Products are carried by tankers, including: hydrocarbon products such as oil, liquefied petroleum gas (LPG), and liquefied natural gas (LNG) chemicals, such as ammonia, chlorine, and styrene monomer fresh water wine molasses. Before this, technology had simply not supported the idea of carrying bulk liquids. The market was also not geared towards transporting or selling cargo in bulk, therefore most ships carried a wide range of different products in different holds and traded outside fixed routes. (http://en.wikipedia.org/wiki/Oil_tanker). In figure 1 a typical “oil tanker side view” is seen. Fig. 1. Oil tanker side view (Web 2) 2.1. Categorization of Tankers by Type of Cargo Categorization of tankers in terms of carrying cargoes can be divided into 5 groups, as follows (Web 1): Oil Tanker; is a tanker carrying petroleum oils and petroleum products. They are called as a crude oils and petroleum products. They are called as a crude oil tanker, product tanker, crude oil/ product tanker according to their purpose respectively. Product Tanker; is an oil tanker carrying petroleum products and mainly divided into two kinds, clean tanker product which carries light petroleum products and dirty product tanker which carries heavy petroleum products. Chemical Tanker; is a tanker carrying chemicals and usually divided in two kinds, parcel chemical tanker capable of carrying many kinds of chemical cargoes including petroleum products and exclusive chemical tanker carrying very limited kinds of chemical cargoes. In the definition of by Chemical in Bulk (IBC) Code and Annex II of MARPOL 73/78, chemical tanker is defined as a tanker used for carriage of dangerous chemicals and/ or noxious liquid substances in bulk. Liquefied Gas Tanker; is a tanker carrying liquefied gases in pressurized and/ or refrigerated conditions. They are such as LPG carriers and LNG carriers. 604 Combination Carrier; cargo ship which carries ore or solid cargo and crude oil alternatively. They are such as ore/oil carriers or ore/ bulk/ oil carriers. 2.2. Types of Petroleum Tankers The size of any particular tanker depends on many factors. Use, cargo type, amount and demand, passage length and port restrictions at both loading port and the discharge port are among the most important of these. In 1954 Shell Oil developed the average freight rate assessment (AFRA) system which classifies tankers of different sizes. To make it an independent instrument, Shell consulted the London Tanker Brokers‟ Panel (LTBP). At first, they divided the groups as General Purpose for tankers under 25,000 tons deadweight (DWT); Medium Range for ships between 25,000 and 45,000 DWT and Large Range for the then-enormous ships that were larger than 45,000 DWT. The ships became larger during the 1970s, which prompted rescaling (Evangelista, 2002). The system was developed for tax reasons as the tax authorities wanted evidence that the internal billing records were correct. Before the New York Mercantile Exchange started trading crude oil futures in 1983, it was difficult to determine the exact price of oil, which could change with every contract. Shell and BP, the first companies to use the system, abandoned the AFRA system in 1983, later followed by the US oil companies. However, the system is still used today. Besides that, there is the flexible market scale, which takes typical routes and lots of 500,000 barrels (Evangelista, 2002, Shipping Shorthand). Merchant oil tankers carry a wide range of hydrocarbon liquids ranging from crude oil to refined petroleum products (Hayler, et al., 2003). Their size is measured in deadweight metric tons (DWT). Crude carriers are among the largest, ranging from 55,000 DWT Panamax-sized vessels to ultra-large crude carriers (ULCCs) of over 440,000 DWT (Hayler, et al., 2003). In table 1 it can be seen oil Tanker size categories according to both AFRA and Flexible market scale. Table1. Oil Tanker Size Categories (Web 2) AFRA Scale Flexible Market Scale Class Size in DWT Class Size in DWT General Purpose tanker 10,000-24,999 Product Tanker 10,000-60,000 Medium Range Tanker 25,000-44,999 Panamax 60,000-80,000 LR1 (Large Range 1) 45,000-79,999 Aframax 80,000-120,000 LR2 (Large Range 2) 80,000-159,999 Suezmax 120,000-200,000 VLCC ( Very Large Crude Carrier) 160,000-319,999 VLCC 200,000-320,000 ULCC (Ultra Large Crude Carrier) 320,000-549,999 Ultra Large Crude Carrier 320,000-550,000 While no standardized system for the classification of oil tankers exists; the fleet is typically divided into four major categories based on carrying capacity. These categories are Ultra Large Crude Carrier) ULCCs and Very Large Crude Carrier (VLCCs), Suezmax, Aframax, and Panamax and Handysize 605 tankers. To benefit from economies of scale charterers typically charter the largest possible vessel that can be accommodated in a particular voyages arrival and discharge ports. ULCCs and VLCCs are the largest vessels in the world tanker fleet. „Supertanker‟ is an informal term used to describe the largest tankers. They carry cargoes of 200,000 DWT or greater and typically transport oil in long-haul trades mainly from the Arabian Gulf to Western Europe and the United States via the Cape of Good Hope and Asia. The large carrying capacity of ULCCs and VLCCs make them attractive to traders, however, this large size limits their access into some of the world‟s ports. Suezmax are offering the relative economies of scale that can be achieved with VLCCs; however, their slightly smaller size offers increased versatility and access to a majority of the world‟s ports. Suezmax tankers primarily operate in the Atlantic Basin delivering cargoes from West Africa, the North Sea, and the former Former Soviet Union (FSU). Aframax vessels are mid-size tankers and typically engage in medium to short haul oil trades in nearly all operating regions and can carry cargos of 80,000 to 120,000 DWT. Widely considered to be the work horses of the fleet, their size makes them ideally suited to operate in areas of lower crude production or where draft and size restrictions prevent the use of larger vessels. Panamax and Handysize tankers are primarily used for both the transportation of crude oil and petroleum products and trade in short haul. Handysize tankers primarily carry finished petroleum products as their smaller size makes them less economic for the transport of crude (Web 1). In 2010, oil tankers made up 38.39% of the world's fleet in terms of deadweight tonnage. In January 2010, there were 102,194 commercial ships in service, with a combined tonnage of 1,276,137 thousand DWT. Oil tankers accounted for 450 million DWT and dry bulk carriers for 457 million DWT (35.8 per cent), representing annual increases of 7.6 and 9.1 per cent respectively (Maritime Review Report, 2010). 2.3 Cargo Operations Tanker loading and unloading operations are very important in terms of economic and safety aspects. Loading an oil tanker consists primarily of pumping cargo into the ship's tanks. As oil enters the tank, the vapors inside the tank must be somehow expelled. Depending on local regulations, the vapors can be expelled into the atmosphere or discharged back to the pumping station by way of a vapor recovery line. It is also common for the ship to move water ballast during the loading of cargo to maintain proper trim. Loading starts slowly at a low pressure to ensure that equipment is working correctly and that connections are secure. Then a steady pressure is achieved and held until the "topping-off" phase when the tanks are nearly full. Topping off is a very dangerous time in handling oil, and the procedure is handled particularly carefully. Tank-gauging equipment is used to tell the person in charge how much space is left in the tank, and all tankers have at least two independent methods for tank-gauging. As the tanker becomes full, crew members open and close valves to direct the flow of product and 606 maintain close communication with the pumping facility to decrease and finally stop the flow of liquid (Hayler, et al.,2003). Unloading process of moving oil off of a tanker is similar to loading, but has some key differences (Turpin, et al,1980). The first step in the operation is following the same pre transfer procedures as used in loading. When the transfer begins, it is the ship's cargo pumps that are used to move the product ashore. As in loading, the transfer starts at low pressure to ensure that equipment is working correctly and that connections are secure. Then a steady pressure is achieved and held during the operation. While pumping, tank levels are carefully watched and key locations, such as the connection at the cargo manifold and the ship's pump room are constantly monitored. Under the direction of the person in charge, crew members open and close valves to direct the flow of product and maintain close communication with the receiving facility to decrease and finally stop the flow of liquid (Hayler, et al., 2003). After unloading process finished, tanks must be cleaned from time to time and need to made gas free for every loading and unloading operation for safety. 2.4. Tanker Operators The main clients of tanker companies include oil companies, oil traders, large oil consumers, petroleum product producers, and government agencies. The tanker industry has undergone a dynamic evolution sinces its inception over a century ago. However, many of the industry‟s fundamentals remain unchanged. The pricing of crude oil transportation services is determined in a highly competitive tanker charter market. The major hubs of shipping are located in New York, London, Oslo, Singapore, and Tokyo. According to “Tanker Operator 2009 Report” top 30 owners of large oil tanker fleets are Teekay Corporation, Frontline, Mitsui O.S.K.Lines (MOL) Tankship Management, Overseas Shipholding Group, Euronav, Tanker Pacific Management, Kristen Navigation, Nippon Yusen Kaisha, MISC Berhad, Tsakos Group, Vela International Marine, NITC, Hyundai Merchant Marine, BW Shipping, Dynacom Tankers Management, Maersk Tankers, BP Shipping, Sovcomflot, Novorossiysk Shipping Company, National Shipping Company of Saudi Arabia, Shipping Corporation of India, Thenamaris, TORM, Chevron Shipping, COSCO Group, Kuwait Oil Tanker Co., Titan Ocean, China Shipping Development Tanker, SK Shipping and Minerva Marine (Tanker Operator Review Report, 2009). In shortly, some selected tanker operators DWT are summarized from their internet sites. Frontline Limited controlled 81 vessels, with 20 million DWT, including 23 Suezmax, 51 VLCC and 6 OreBulk-Oil vessels (Web 3). “Teekay Corporation” controlled 135 vessels and another 11 new building on order and in all size sectors of the crude and product market, they are 34 Aframax, the slightly larger 27 Suezmax and 1 VLCCs (Web 4). “Tanker Pacific” is a leading provider of Marine Transportation for the energy markets. They manage a fleet of 39 vessels spread across all vessel classes i.e. VLCCs, Aframaxes and MR‟s with an excess of 4.6 million deadweight tonnes capacity 607 (Web 4). “Overseas Shipholding Group” operates 12 million DWT includes vessel as follows; 44 Handymax, 16 VLCCs, 15 Panamax,11 Aframax 2 Suezmax, 2 FSO and 17 other vessels (Web 5). Although, Frontline is operating less tankers than Teekay in number, the VLCC total pushes Frontline into first place in terms of deadweight tonnage under its control. 3. World Oil Production and Consumption In 2010, as shown in figure 2, world oil production grew by 1.8 million barrel daily (b/d) (3,9 million tonnes ) and surpassed the level reached in 2008. Growth was the largest since 2004 and was divided Fig. 2. World oil production by region (BP Statistic Data, 2011) evenly between OPEC and non-OPEC. The largest increases in OPEC were in Nigeria (340,000 b/d) and Qatar (220,000 b/d). Non-OPEC output increased by 0.9 million b/d, the highest since 2002, and was led by China (+271 Kb/d) - which recorded its largest increase ever-, the US (+242 Kb/d), and Russia (+236 Kb/d) (BP Statistics Review, 2011). Global oil supply in June increased by 1.2 million b/d from May, to average 88.3 million b/d, with OPEC crude rising by 0.8 million b/d to 30 million b/d as Saudi Arabia boosted supply. Non-OPEC supply is now seen averaging a lower 53.1 million b/d in 2011, on prolonged production outages, before rising to 54 million b/d in 2012. The „call on OPEC crude and stock change‟ now rises by 1.3 million b/d in 3Quarter 2011 to 31.3 million b/d. It averages 30.7 million b/d for 2012, +0.1 million b/d versus 2011(Web 6). 608 Fig. 3. World oil consumption by region (BP Statistic Data, 2011) As shown in figure 3 World oil consumption grew by 87,4 million b/d (4028,1 million tonnes) or 3.1%. Non-OECD demand rose by 2.2 Mb/d – the highest annual growth on record in volumetric terms just slightly outpacing the growth seen in 2004. Growth remained robust in China and the Middle East with Chinese consumption growing by 9,057 million b/d or 10.4%. OECD oil consumption rose by 4,64 million b/d, -making 2010 the first year of annual OECD growth since 2005. Despite the increase, consumption in 2010 was still 5 million b/d below the peak in 2005. The tanker market is in 2010 was characterized by a strong first half and a weak second half. This pattern was most pronounced for the VLCCs, which achieved an average of $ 51,000 in the first half of the year and $19,000 in the second half of year. A sudden decline in floating storage during the summer resulted in a sharp drop in freight rates. Oil consumption increased by 3 percent and seaborne oil trade in terms of ton-miles showed the strongest growth since the late 1980s.The fleet growth of 5 percent was somewhat higher than expected due to fewer removals of single –hull tankers than anticipated. Despite the brisk rise in tonnage demand, the utilization rate for the total tanker fleet recovered only marginally from 85 to 86 percent, significantly below the 90 percent level that we define as full capacity utilization (Platou Report, 2011).Oil prices increased from $89.9 per barrel (pbroughly 50 tonnes a year) in January 2008 to $133 per barrel in July, before falling by more than 70.0 percent to $ 39,7 in December 2008. By mid-2009, growth in oil prices has gained speed, with levels reaching $71.4 per barrel in August and $ 73.0 per barrel in December. During the first quarter of 2010, oil prices picked up further speed, increasing to $82 per barrel in April. The strong rise in oil prices since 2009 reflects anticipation of a revival in demand, and positive sentiment about the global 609 economy (Maritime Review Report, 2010). OPEC production restraint helped to push prices higher late in the year, with prices reaching a peak near $94 at year-end (BP Statistics Review Report, 2011). 4. Oil Tanker Industry in Turkey The biggest tankers (oil tanker, product tankers and chemical tankers) fleets with open registry flags (1000 grt and above), in national and foreign flag vessels Greece is on the 1st row, Japan is on the 2nd and China is on the 3rd row, whereas Turkey is on the 23st row. The biggest oil tankers fleets with open registry flags (1000 grt and above), in national and foreign flag vessels Greece is on the 1st row, Japan is on the 2nd and China is on the 3rd row, whereas Turkey is on the 23st row. Our shipyards have a good reputation in building of small and medium tonnage chemical tankers (DTO, 2010). 2010, Turkey is in the 4th place among the countries which takes tanker orders (Chamber of Commerce (DTO) Sector Report, 2010). By the effect of the new regulations, especially about the tankers, ship breaking in Turkey increased % 76 in quantity, %96 in LDT when compared with the previous years. 3.8 % of the oil tanker segment which is totally 1.146.473 DWT are registered in National Ship Registry, 96.2 % are registered in International Ship Registry. The average age of oil tanker is 16 which consist of 14.8 % of the general fleet (DTO, 2010). Turkish oil tankers by tonnage and age groups 1000 GRT and over has 34 ships which total 120.322 DWT,17 ships of 907.068 DWT are 0-9 age range, 2 ships of 5.49 DWT are 10-19 age range, 8 ships of 184.212 DWT are 2029 age range, 7 ships of 23.545DWT are 30 age and over (DTO, 2010). The tanker industry has been dominated by large corporations and state owned entities. In Turkey,tthe vast majority of shipping is conducted by small independent ship-owners. One of the biggest Tanker operator, Geden Lines operates a fleet of 26 vessels which includes 7 Suezmax Crude Oil Tankers, 8 Aframax Crude Oil Tankers, 1 LR1 Crude/Product Tanker, and 10 Chemical Product Tankers (Web 7). Yasa Tanker & Transportation operates 11 vessels which includes 4 MR Product, 4 Aframax Tanker and 3 Suezmax tanker, total deatweight is 1124.000 DWT. There are two new building Suezmax ships which will be finished in June 2012 (Web 8). By the January The pick-up in oil prices, the offshore disaster in the Gulf of Mexico, a shifting focus from downstream to upstream and elaborate discussions on shale reserves have been the global headlines in 2010 (Web 9). Energy consumption in Turkey is low when compared with Western European countries. However, the large, young and increasingly urban population together with expected industrial development potential in Turkey represents a significant growth potential (Turkish Energy Industry Report,2010). The oil consumption in Turkey has reached a level of 624.000 b/d (28,7 million tonnes) in 2010. 90 percent of Turkey‟s crude oil is imported, mainly from Saudi Arabia, Iran, Iraq and Russia. 70 percent of domestically produced oil is provided by the state-run Turkish Petroleum Corporation (TPAO), with the remainder produced mainly by Royal Dutch/Shell. As of December 2009 Turkey‟s producible oil reserves correspond to 299 million barrel TPAO (Turkish Petroleum Corporation, 2009) - 2009 Oil and Natural Gas Sector Report Oil production is far lower than the estimated consumption of 610 c.663,000 barrel per day (b/d) in 2009. It is estimated that in 2009, c.31 percent of the total primary energy consumption in Turkey was constituted from oil, showing a slight decrease compared to 2008. Turkey is divided into 18 onshore oil exploration zones. Over the 77-year period since the first drill, however, only three zones in south-eastern Anatolia (Zone 10, 11, 12) and one in Thrace (Zone 1) have received sustained investment interest. Although the total investment in oil and gas exploration grew seven-fold between 2002 and 2009, reaching US$716 million, only 20% of onshore reserves have been explored so far (Web 9). Fig. 4. Turkish oil consumption, imports and products (BMI,2009), On the other hand, an estimated 50,000 vessels pass through the Turkish straits annually, 20% of which are crude oil and petroleum product tankers. Even in the best of weather, the Bosphorus Strait is quite difficult to navigate, as evidenced by the more than 180 recorded collisions, resulting in 47 deaths, between 1982 and 2008. Pipelines have already become imperative to mitigate the risk to human and marine life, given the growing oil production in Russia and the Caspian region. In this regard, the Baku-Tbilisi- Ceyhan (BTC) pipeline constitutes an important example, one to be followed by the Samsun-Ceyhan pipeline, for the total transportation of more than 150 million tonnes of crude oil and petroleum products per annum, bypassing straits (Web 9). 5. Conclusion In addition to Turkey has an advantage of operating as an energy hub between Europe and the Middle East, , survival in the Turkish downstream oil market is becoming more of a volume play, especially for the mid and small size players. Considering the regulatory requirements pushing for a strong financial structure to meet rules such as minimum sales volume or national marker responsibilities, coupled with financial liabilities in imports, it is realistic to expect more consolidation in this segment as well as vertical integration attempts in the horizon. The shipping industry is heavily regulated due to its global nature and the inherent risks of transporting large cargoes across the world‟s oceans. In recent years, safety and quality standards of 611 the seaborne transportation of crude oil and petroleum products have been raised significantly with the passage of stricter international regulations. The result has been increasing standards of safety and professionalism, environmental responsibility, and increasing consolidation by large, public companies. References Business Monitor International -BMI (2009) Power Industry View Turkey Report, July 2009. BP Statistical Review of World Energy Report 2011. Deniz Ticaret Odası (Chamber of Commerce) Sector Report 2010. Evangelista, Joe, Ed. (Winter 2002). "Scaling the Tanker Market" (PDF). Surveyor (American Bureau of Shipping) (4): 5–11. Archived from the original on 2007-09-30. Retrieved 2008-02-27) Evangelista, Joe, Ed. (Winter 2002). "Shipping Shorthand" (PDF). Surveyor (American Bureau of Shipping) (4): 5–11. Archived from the original on 2007-09-30. Retrieved 2008-02-27). Hayler, William B.; Keever, John M. (2003). American Merchant Seaman's Manual. Cornell Maritime Pr. ISBN 0-87033-549-9.p 9,10,14). The Platou Report (2011). Tanker Operator Review Report, (2009). Tanker Operator‟s Top 30 Owners and Operators,TANKER Operator Annual Review Report, 2009. Tanker Operator Review Report, (2008). Tanker Review Shipping, TANKER Operator Annual Review Report, March 2008. TPAO (Turkish Petroleum (Corporation,2009) 2009 Oil and Natural Gas Sector Report Oil Turpin, Edward A.; McEwen, William A. (1980). Merchant Marine Officers' Handbook (4th ed.). Centreville, MD: Cornell Maritime Press. ISBN 0-87038-056-X. United Nations Conference on Trade and Development, Review of Maritime Transport (2010) ISBN 978-92-1112810-9. Web 1, http://www.worldtraderef.com/WTR_site/vessel_classification.asp Web 2, http://en.wikipedia.org/wiki/Oil_tanker Web 3, http:// www. frontline.bm/fleetlist/index.php. Web 4, http://www.tanker.com.sg/about.html. Web 5, http://www.osg.com/index.cfm?pageid=20 Web 6, http://www.omrpublic.iea.org Web 7, http:www.gedenlines.com/en/line/gedenLines.asp. Web 8, http://www.yasahold.com.tr/en/Fleet_list_new_tanker.html. Web 9, http://www.pwc.com/gx/en/oil-gas-energy/issues-trends/turkish-petroleum-market-developments.jhtml. 612 A Case Study: Investigation of the Most Cost-Effective Transportation Mode Between Istanbul and Denizli Eda Turan *, Fahri Çelik, Melike Dilek** * Dept. of Naval Arch. and Marine Eng., Yildiz Technical University, Turkey, edaturan@yildiz.edu.tr ** Naval Architect and Marine Engineer, Turkey, melikedilek88@gmail.com Abstract The amount of cargoes and transportation ratios increase subject to human requirements. Alternative transportation modes are also being developed in this parallel. General transportation modes are highway, railway, seaway and airway transportations. Due to high costs, airway is not mostly preferred for cargo transportation. Especially in Turkey, although seaway and railway transportations are cheaper than highway, cargo transportation is mainly done by highway. In this study, the most cost-effective transportation mode is investigated for cargo transportation from among highway, railway and intermodal (seaway+highway) modes by considering a line between Istanbul and Denizli. Levelised Cost Analysis Method is applied during the cost analysis of 3,000 tonnes of cargoes transportation in the case study. Total transportation cost by highway transportation mode is calculated as 132,750 USD. It is also calculated that total transportation cost by railway is 29% less and by intermodal transportation (seaway+highway) is 38% less than highway transportation mode. Keywords: Transportation, Levelised Cost Analysis Method, Mode Choice 1. Introduction An expectation from a transportation system is causing minimum cost to the country while providing the best service. This expression emphasises that transportation systems should not be evaluated only with the profit of carrier criteria in a narrow sense and they are also supposed to be considered with social cost criteria including the costs of wastage of energy and dependence of foreign countries, traffic accidents, environmental pollutions, noise pollutions etc effects to the country. In this context, efficiency and suitability of a transportation system depend on selecting and using of proper modes of transport such as highway, railway, seaway, airway, water way, pipe line etc (Evren, 1997). There are many companies which conduct freight shipment as part of logistics services in Turkey. After analyzing the transportation modes used by these companies for freight movements, it is obviously seen that highway transportation’s superiority is distinct. 613 According to the Review of Maritime Transport 2010, 95% of freight shipment is carried out by highway transportation mode and railway has 5% share of the total amount in Turkey. In recent years, freight shipment by seaway and airway don’t have enough level to place among other modes of transportation. These distributions indicate that railway and seaway transportations, which are cheaper and more effective than the other modes, aren’t been utilized sufficiently and also it reveals lack of technical infrastructure in this area. Considering Turkey’s three sides are surrounded by the sea, proportion of seaway transportation is situated in a worried level. Meanwhile, primarily European countries and other countries make a great effort to use inland waterways more efficient. Mentioning about inland waterways transport is very hard for Turkey. The researches show that whether the propensity of developing in past 25 years continues, increase in passenger traffic in Turkey is expected about 3.3 times more than nowadays which means 540 billion passenger-km, the increase in freight traffic is expected about 2.5 times more which means 300 billion ton-km in 2020. Therefore supplying of goods by highway transportation will become harder gradually. Nowadays transportation system in Turkey is seen as dependent to highway transportation. Consequently, approximately 6000 people have been losing their life in traffic accidents; thousands of people have become permanently disabled, being badly injured and financial damages approaching trillions occur (Önder,2007) Thus, in the next years, benefitting from seaway transportation efficiently is an essential necessity. Otherwise, facing harder troubles is inevitable due to the highway transportation’s uncontrollable increase. None of the countries use only one mode of transportation systems in the World. Almost all countries benefit from seaway transportation and pipe lines at liquid transporting along with railway, highway and airway transportation subject to their geographical position. The crucial point is to choose an appropriate transportation system by considering the social situation, financial possibility, existing energy sources with features of its area, technological structures of the country and benefit from each of them properly (Web 1). The added value in logistic sector due to the combination between transportation systems in recent years supports progress of new transportation systems. The intermodal transportation that fulfils different distribution needs and transport all types of cargoes, is an important result of this progress. The system contains tandem connecting shipping which carrier is responsible from whole of the transportation or some part of the transportation by using two or more transportation modes and also maintains the movement of cargo in more than one transportation mode with a standardized transport unit is enabled (Ergin, 2008). 614 In this study, modes of transportation in Turkey and the World are explained in a comparative way, then feasibility of intermodal transportation system in Turkey is evaluated with a case study between Istanbul and Denizli line. The purpose of the study is to provide creation of cost items according to the structures, sizes and the needs of the companies through analysing approaches and methods in order to select the most economical transportation system so as to minimize transportation costs and contribute to prefer a proper transportation system (Dilek, 2011). 2. The Position of Cargo Transportation in Turkey and the World. Modal split of inland freight transportation as world basis is indicated in Table 1. It is seen that the cargo transportation is mainly done by highway transportation in Turkey. Inland water way transportation is seen as well developed in the Netherlands with 33% ratios. The cargoes mostly transported in Turkey are given in Table 2. The costs per ton-miles and ton-km are given in Table 3 and the unit costs based on vessel types are given in Table 4. Table 1: Modal split of inland freight transport: the share of rail, road and inland waterway in total inland transport (as a percentage of total ton-kilometres) (Review of Maritime Transport, 2010) 2002 2007 Rail Road Inland water way Total Rail Road Inland water way Total EU-27 18 75 6 100 18 77 6 100 Austria 29 66 5 100 35 61 4 100 Belgium 11 78 12 100 13 71 16 100 Bulgaria 33 63 4 100 25 70 5 100 Croatia 23 76 1 100 25 74 1 100 Cyprus 100 Czech Republic 27 73 Denmark 8 Estonia 100 0 100 100 100 25 75 92 100 8 92 100 70 30 100 57 43 100 Filand 23 77 0 100 26 74 0 100 France 19 78 3 100 15 81 3 100 Germany 19 66 15 100 22 66 12 100 100 3 97 100 21 74 Greece Hungry 28 Iceland 66 6 100 100 100 Ireland 3 97 Italy 10 90 Latvia 71 29 0 615 0 100 100 5 100 100 100 1 99 100 100 12 88 100 58 42 0 100 100 (Table 1: cont.) Liechtenstein 100 Lithuania 48 Luxembourg 6 Malta 52 0 91 4 100 Netherlands 3 63 Norway 15 85 Poland 37 62 Portugal 7 93 Romania 34 57 Slovakia 41 59 Slovenia 30 Spain 6 Sweden 34 United Kingdom Sources: 100 42 100 4 100 33 59 0 93 3 100 100 100 100 100 6 61 100 15 85 100 26 74 100 5 95 8 100 19 71 10 100 0 100 26 72 3 100 70 100 21 79 100 94 100 4 96 100 66 100 36 64 100 100 54 45 100 5 95 100 13 87 1 Switzerland Turkey 100 5 95 10 90 0 33 100 100 0 100 100 1 100 100 0 100 UNCTAD secretariat calculations, based on Eurostat the Directorate-General for energy and Transport, (European Commission), the intermodal Transport Forum, and national statistical estimates. Table 2: The most loaded cargoes transported by Coastal Transportation in Turkey (Web 2) SOLID CARGOES QUANTITY (tonnes) LIQUID CARGOES QUANTITY (tonnes) Bulk Cement 1,581,630 Diesel Fuel 3,175,334 Flux 471,100 Fuel Oil 1,634,158 Construction Iron 375,598 Jet Fuel 1,167,843 Marble 375,076 Gasolin 674,180 Steel Roll 319,180 Crude Oil 352,465 Ingot 297,631 Naphta 302,000 Sand 277,900 Heating Oil 189,350 Fertilizer 246,991 Engine Oil 96,062 Loam 239,407 C4, ACN, PX ETHYL 89,740 Coal 215,121 Gasoil 64,307 Pyrites 121,824 Paraxylen 44,200 Mosaic 120,630 Phosphoric Acid 36,750 Soil 120,584 MEG 28,400 Copper Ore 88,770 LPG 24,810 Iron Ore 81,900 Asphalt 16,950 Quarz 80,516 Bilge (Slop) 14,156 Ceramic Tile 75,748 Sülfuric Acid 11,000 616 (Table 2: cont.) SOLID CARGOES QUANTITY (tonnes) Pyrites Ash 43,205 Water QUANTITY (tonnes) 3,490 Wheat 43,047 Oil Alloyed Elements 2500 Oxide Layer 42,400 Petrol Products 950 Others 448,060 Others 700 Total 5,666,320 Total 7,929,345 LIQUID CARGOES Table 3: The costs per ton-miles and ton-km (Akten, 1994) Transportation Cost Transportation System ton-km Ton-miles Scheduled Flight(yük,yolcu,posta) 25.2 36.8 Cargo Flight 10 15 Highway (cargo) 8 12 Railway (cargo) 0.75-5 0.1-7 Seaway (cargo) 0.1-2 0.1-3 Table 4: The unit costs based on vessel types (Akten, 1994) Vessel Type Unit Cost (ton-mile) Truck (with 10 tonnes cargoes) 1.000 Train (with 500 tonnes cargoes) 0.030 Cargo Ship (100.000 DWT) 0.006 Howercraft 7.800 Flight 4.400 The ratios of different transportation systems subject to travel distance in the World is given in Table 5. However, this figure is not valid for Turkey. Seaway transportation, which is the cheapest way of transportation, is seen as last choice for coastal transportation in Turkey. The mostly used mode is highway transportation which has the highest unit costs. This situation is a big risk for the oil dependent countries. In the foreign trade transportation in Turkey, the commonly used mode is seaway transportation. Secondly, highway transportation is selected by the companies. The distribution of mode choice is shown in Table 6. 617 Table 5: The ratios of different transportation systems subject to travel distance (Akten,1994) DISTANCE SEAWAY HIGHWAY RAILWAY (km) 1-50 0.8 97.1 2.1 51-100 7.9 73.9 18.2 101-200 16.9 43.4 39.7 201-400 33.8 16.6 49.5 401-600 42.2 12.2 45.6 601+ 59.9 3.1 37.0 Table 6: The distribution of foreign trade transportation in Turkey subject to transportation modes (Web 3) YEAR 2000 SEAWAY RAILWAY HIGHWAY AIRWAY OTHERS 88.6 0.5 8.6 0.2 2.1 2001 87.0 0.6 10.6 0.2 1.6 2002 87.3 0.7 9.7 0.2 2.1 2003 87.6 0.8 10.5 0.1 1.0 2004 87.4 1.2 10.3 0.1 1.0 2005 86.0 1.2 11.9 0.2 0.7 2006 87.4 1.1 10.4 0.1 1.0 2007 87.4 1.1 10.0 0.6 0.9 2008 86.5 1.1 10.7 0.7 1.0 2009 85.0 0.8 12.6 0.8 0.8 3. A Case Study for Transportation of Goods between Istanbul and Denizli In this study, 3000 tonnes of textile cargoes’ transportation cost analysis between İstanbul and Denizli cities were evaluated with three different transportation modes. Firstly, cargo was transported from origin location Istanbul to destination location Denizli directly by highway, secondly in the same O-D pair directly by railway and in third alternative, the cargo was transported from Istanbul to Izmir by seaway and then from Izmir to Denizli by highway. Fig. 1 shows the transportation alternatives between İstanbul and Denizli. Red line shows the sea transportation from Istanbul to Izmir, and aqua coloured line shows the highway transportation from Izmir to Denizli. Purple line shows directly highway transportation between Istanbul and Denizli. Technical and cost datas were collected for these lines and unit cargo cost was calculated for each line and the most appropriate transportation mode between Istanbul and Denizli cities is designated. Levelised Cost Analysis Method, which was developed by Sahin et. al. (2009) was used in order to calculate the unit cargo cost. 618 a) Highway Transportation: The goods are directly transported from Istanbul to Denizli by trucks. Standard type trucks with 20 tonnes cargo capacity are considered in this study. Therefore 150 trucks (100% loaded) are required for 3,000 tonnes cargoes transportation. b) Railway Transportation: The goods are directly transported from Istanbul to Denizli by freight trains. Standard type 700 tonnes capacity freight trains are considered in this study. Therefore 4 units 100% loaded and one unit 28,57% loaded freight trains are required for 3,000 tonnes cargoes transportation. c) Intermodal Transportation: The goods are directly transported from Istanbul to İzmir by sea vessels and from İzmir to Denizli by trucks. One unit 100% loaded cargo vessel with 3000 tonnes capacity for sea transportation and then 150 trucks with 20 tonnes capacity for highway transportation are required. Fig.1: Transportation Alternatives Between Istanbul and Denizli (Web 4) The technical and economical particulars for these transportation modes are given in Table 7. 619 Table 7: Technical and Economical Particulars for Highway, Railway and Intermodal Transportation between İstanbul and Denizli Particulars Unit Investment cost $ Average economic life year Insurance percentage $ (%Ic) Service speed of the km/h vessel Cargo capacity tonnes Annual maintenance hours repair time Daily idle time hours/day Fuel consumption per liters/ km (main and aux.) km Lubricant liters/ consumption per km km (main and aux.) Fuel price $/liters Lubricant price $/liters Annual operation and $/Year maintenance costs Interest Rate Discount Rate Escalation rate for future operational and maintenance costs Escalation rate for future fuel cost Escalation rate for future insurance cost Escalation rate for future external cost Route length km Waiting time between hour sequential trips Specific cost of $/cargo-km accident Specific cost of $/cargo-km pollution Specific cost of noise $/cargo-km INTERMODAL INTERMODAL - Seaway – Highway (Istanbul – (Izmir - Denizli) Izmir) HIGHWAY (Istanbul – Denizli) RAILWAY (Istanbul – Denizli) 65,000 25 6,440,000 20 30,000,000 25 65,000 25 0.02706 0.00776 0.01702 0.00595 70 35 37,04 70 20 700 3000 20 720 1200 67,2 300 15 3.041 0 15 0.35 7 43.2 0.35 0,0015 0,05 0,27 0,0015 2.3 3.87 1.127 5.00 0.6 2.00 2.3 3.87 9,032 710,000 1,460,000 9,032 0.08 0.1 0.08 0.1 0.08 0.1 0.08 0.1 0.03 0.03 0.03 0.03 0.05 0.05 0.05 0.05 0.03 0.03 0.03 0.03 0.03 0.03 0.03 0.03 649 726 592,64 225 0.00 30.00 0.00 0.00 1.24E-04 1.24E-04 1.24E-04 1.24E-04 2.48E-03 2.48E-03 2.48E-03 2.48E-03 0.00E+00 0.00E+00 0.00E+00 0.00E+00 Unit cargo cost (UT) for three alternative transportation modes, that was calculated by levelised cost analysis method, are given in Table 8. 620 Table 8: Unit cargo costs (UT) subject to fullness ratios (Kd) of the vessels Kd 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 HIGHWAY RAILWAY UT ($/cargo) 442.53 221.27 147.51 110.63 88.51 73.76 63.22 55.32 49.17 44.25 UT ($/cargo) 269.34 134.67 89.78 67.34 53.87 44.89 38.48 33.67 29.93 26.93 INTERMODAL INTERMODAL - Seaway - Highway UT ($/cargo) UT ($/cargo) 123.57 151.09 61.79 75.55 41.19 50.36 30.89 37.77 24.71 30.22 20.60 25.18 17.65 21.58 15.45 18.89 13.73 16.79 12.36 15.11 Total costs, obtained for 3,000 tonnes cargo transportation from İstanbul to Denizli, are as follows: 150 units of fully loaded (fullness ratio=Kd=1) trucks are required for highway transportation between İstanbul and Denizli. Unit cargo price is 44.25 USD/cargo. Total transportation cost for 3,000 tonnes cargo is calculated as 132,750 USD with highway transportation mode. 4 units of fully loaded (Kd=1) freight trains and one unit of 28% loaded freight train are required for railway transportation between İstanbul and Denizli. Unit cargo price for 100% loaded train is 26.93 USD and 28,57% loaded train is 94.27 USD. Total transportation cost for 3,000 tonnes cargo is calculated as 94,258 USD with railway transportation mode. One unit of fully loaded (Kd=1) cargo vessel for sea transportation and 150 units of fully loaded (Kd=1) trucks for highway transportation are required for intermodal transportation between İstanbul and Denizli. Unit cargo price for 100% loaded cargo vessel is 12.36 USD between Istanbul-Izmir and 100% loaded truck between Izmir-Denizli is 15.11 USD. Total transportation cost for 3,000 tonnes cargo is calculated as 82,410 USD with intermodal transportation mode. The comparison of total costs calculated above is shown in Fig. 2. Fig. 2: Comparison of total costs for 3,000 tonnes of cargoes with highway, railway and intermodal transportation modes between Istanbul and Denizli. 621 4. Conclusions In this study the most cost effective transportation mode is investigated for cargo transportation from Istanbul to Denizli by using Levelised Cost Analysis Method. Total transportation costs for 3,000 tonnes of cargo are calculated for three types of transportation modes as highway, railway and intermodal (seaway+highway) transportation. Intermodal transportation is designated as the most cost-effective alternative. Highway transportation is the most expensive transportation alternative in this line. Total transportation cost by highway transportation mode is calculated as 132,750 USD. It is also calculated that total transportation cost by railway is 29% less and by intermodal transportation (seaway+highway) is 38% less than highway transportation mode. It is clearly seen that highway transportation ratio, which is 95% in Turkey should be reduced. Alternative transportation modes such as railway and especially seaway transportation which has the lowest costs should be adopted in the place of highway transportation. This mode choice should be considered not only for costs but also for the accidents due to the increase in the highway traffic, environmental effects of highway transportation and sustainability. 5. References Akten, N., (1994), Utilization from the Sea in the Transportation of Istanbul, Istanbul Chamber of Commerce Publications, Istanbul. Dilek M., (2011), Cost Analysing Of Highway, Railway, Combined (Seaway+Highway) Container Shipping Systems On Istanbul – Denizli Line, İstanbul. Ergin, H., Çekerol, G.S., (2008), Intermodal Freight Transportation And A Case Study For The Distribution Of Fast Comsumption Goods in Turkey, Dumlupınar University, Social Sciences Journal 22. Evren, G. ve Öğüt, S., (1997). Railways inTurkey as part of Transportation Policy, Istanbul Technical University, Civil Engineering Faculty, Department of Transportation. Önder B.,(2007), The Examination of Transportation Sectors within the logistic Phenomenon in Turkey, Istanbul. 1,9-13. Review of Maritime Transport, (2010), United Nations Conference on Trade and Development, United Nations Publications, pp. 112. Sahin, B., Yilmaz, H., Ust, Y., Guneri, AF., Gulsun B., (2009), An approach for analysing transportation costs and a case study - European Journal of Operational Research 193, 1–11 Web 1., http://www.karid.org.tr/tr/article.asp?ID=23 Web 2., http://www.denizticaretodasi.org/DetoPortal/Default.aspx?tabid=71 Web 3., http://www.tuik.gov.tr/VeriBilgi.do?tb_id=12&ust_id=4 Web 4., http://maps.google.com/ 622
