network is an intermodal transport system, sure and efficient, whose goal is to ..... should be taken in railway transport to complete electrification of railway ...
Green Intermodal Freight Transport (GIFT) Project: Analysis and results Mario Binetti, Sara Bray, Leonardo Caggiani, Rosalia Camporeale, Leonardo Damiani, Matilda Mali and Michele Ottomanelli Dept. of Civil, Environmental and Building Engineering and Chemistry (DICATECh ) Technical University of Bari, Viale Orabona, 4 - 70125 Bari, Italy {mario.binetti, sara.bray, leonardo.caggiani, rosalia.camporeale, leonardo.damiani, matilda.mali, michele.ottomanelli}@poliba.it
Abstract. The concept of transport corridors is marked by a concentration of freight traffic between major hubs and by relatively long distances of transport. Green transport corridors will reflect an integrated transport concept where short sea shipping, rail, inland waterways and road complement each other to enable the choice of environmentally friendly transport. The main aim of Green Intermodal Freight Transport (GIFT) project is to map, analyze, and evaluate the status of the transport sector in the selected transport network and propose new policies and strategies in infrastructure, processes, assets, Information and Communication Technologies, legislation, norms and harmonization/standardization issues, in order to promote innovative green intermodal freight transport corridors. The purpose of this paper is to present the central activities of the project, and the expected/achieved results and outputs. Funding: ERDF (European Regional Development Fund) Program: SEE ID Code: SEE/C/0003/3.3/X Role of POLIBA: partner Contact person: Professor Leonardo Damiani Total Budget: € 4.040.493,70 Poliba Budget: € 223.880,00 Number of partners: 23 (from EU), 4 (from Non EU) Number of Countries involved: 7 (from EU), 3 (from Non EU) Starting date: March 1, 2012 End date: December 31, 2014 Keywords: Co-modality; European Transport Corridors; Green Intermodal Freight Transport (GIFT) project; South-Eastern Europe Program.
Page 1 of 10
1
Introduction
Road freight transport is the dominant mode of goods movement across the EU (with a share of 76.4%) as it represents a cost effective and flexible mode. According to the European Environmental Authority (EEA), the share of use of road freight transport in South East Europe (SEE) exceeds the average percentage of road transport in the EU. Its dominance in SEE countries may be attributed to the lower requirements for infrastructure, delays in border crossing, lack of standards, or more generally to the legal framework. However, road transport exhibits significant weaknesses contributing to considerable CO2 emissions, accidents, increased noise level, road congestion and wear. The contribution of road transport to the greenhouse gas (GHG) emissions chart reaches 25.1% of the global share [1], whereas according to the World Health Organization, road traffic accidents occupy the third position (23%) among the ten leading causes of mortality. It is evident that in order to relieve the pressure on the roads, transport modes have to be combined so as to reduce congestion, environmental impact, improve safety, reduce economic impact (due to fatalities and environmental harm), while at the same time meet modern demands for reliability, speed and safety. The main aim of the EU is to achieve a European transport system, which will address the current economic, social and environmental needs with a sustainable manner. Regarding transport industry, the European Union promotes various eco-friendly policies and strategies resulting from the White Paper, the Green Paper, Transport in 2050 and from the Euro vignette directive. In this framework, it is worth noting that the European Union, mainly under the Trans-European Transport Network (TEN-T) program, supports actions that promote modal shift and green transport [2]. This network is an intermodal transport system, sure and efficient, whose goal is to improve connection with the new neighboring countries as well as with other economic and political centers of the world [3]. To this end, the “Green Intermodal Freight Transport (GIFT)” project aims at enhancing green intermodality by focusing on the PEN Corridors IV, V and VII. In order to support trade oriented economic development and to promote regional/transnational sustainable and green development, GIFT project has increasingly been under pressure to improve corridors efficiency by ensuring that corridor services are provided on an internationally competitive basis. Corridors form a vital link in the overall trading chain and, consequently, corridor efficiency is an important contributor to a nation's international competitiveness. Thus, monitoring and comparing one’s corridor with other corridors in terms of overall efficiency has become an essential part of many countries’ microeconomic reform programs. This study hopes to contribute to this important task by applying an innovative approach to corridors efficiency ratings covering a selected sample of GIFT corridors based on DEA model. The paper is organized as follow. In the following section, we describe the GIFT project and its main objectives. In section 3 we explain the DEA model that we have applied to measure the efficiency of the GIFT corridors; in section 4 we have
measured the efficiency of two GIFT selected corridors (IV and V) presenting the results and the potential improvements of each corridors. Conclusions are reported in the final section.
2
About GIFT Project
In 2007, the EU introduced a new concept of transport networks, the corridors. According to EC 2007, “transport corridors are marked by a concentration of freight traffic between major hubs and by relatively long distances… Industry will be encouraged along these corridors to rely on co-modality and on advanced technology in order to accommodate rising traffic volumes, while promoting environmental sustainability and energy efficiency… Green corridors could be used to experiment with environmentally-friendly, innovative transport units, and with advanced Intelligent Transport Systems (ITS) applications” [4]. The number of projects that in one way or the other relate to the concept of green corridors is huge. The reason is, to a large extent, that the concept of green corridor cover environmental and economic perspectives-areas which most “modern” projects have been focusing their efforts for many years (before “inventing” the green corridor concept) [5]. Among these projects involved in supporting the development of a sustainable transport network, worth of mention the GIFT. The main aim GIFT project is to map, analyze and evaluate the status of the transport sector in the South East Europe Regions and to propose new policies and strategies in infrastructure, processes, assets, ICT (Information and Communication Technology), legislation, norms, harmonization/standardization issues, and also to develop tools and methodologies for monitoring CO2 emissions, in order to promote innovative green intermodal freight transport corridors. GIFT project will drill down in three Pan-European Transport Corridors, namely IV, V and VII that cover almost the entire SEE region (Fig. 1). ▪ GIFT Corridor IV: Rusovce/Rajka - Bratislava - Győr - Budapest - Arad Bucharest - Constanţa/Craiova - Sofia - Thessaloniki (SK, H, RO, BG, GR); ▪ GIFT Corridor V: Venice - Triest/Koper - Ljubljana - Maribor - Budapest Uzhhorod; Branch A - Bratislava - Žilina - Košice - Uzhhorod; Branch B - Rijeka Zagreb - Budapest; Branch C - Ploče - Sarajevo - Osijek - Budapest (I, SLO, H, SK, CRO); ▪ GIFT Corridor VII: Danube river (SK, H, RO, BG).
Page 3 of 10
Fig. 1. GIFT Project: Pan-European Transport Corridors (IV, V, VII)
2.1
Main objectives of the project
In order to fulfill the initial aim, GIFT consortium will: 1. map and assess the current status in terms of transport strategy, operations and policies of the three selected corridors; 2. support discussion platforms (public consultations) for communication and coordination between regional authorities and private service providers and their collective associations in order to assess current status of the GIFT transport corridors and suggest methods, techniques and tools to transform them into more efficient and environmental friendly; 3. synthesize concrete and pragmatic proposals for the improvement of the current transport network and for relevant policies to promote green transport in the selected corridors; 4. improve interoperability and intermodality of freight transport on land, IWW (Inland Waterway), and sea; 5. prefer a shift towards the least polluting and most efficient modes of transport; 6. develop an ICT tool for CO2 footprint monitoring that will support the minimization of environmental impact; 7. develop transnational agreements, common measures and Memoranda of Understanding (MoUs) on multimodal connections especially among agglomerations.
2.2
Transnational approach
The transnational character of the project represents one of its most important aspects. A joint approach is necessity since the transportation of goods is a core matter of transnational cooperation. More so in order to address current challenges in the region regarding seamless accessibility, improvement of organization, processes, promotion of services for enhanced quality, and for less polluting integrated transport systems. Moreover, the importance of standards and procedures and the absence of a harmonized legal framework for intermodal transportation among the SEE countries, create the necessity for transnational cooperation for marked improvements in efficiency, and enhancement in the share of alternative transport modes. Apart from the nature of the project, the transnational character is guaranteed by the solid and balanced participation of the partners throughout the entire project planning, research, implementation, and capitalization.
3
Formulation of the proposed methodology
In this section we investigate the DEA model that we have applied for the study of corridors efficiency. This technique offers a significant alternative to classical econometric approaches to extracting efficiency information from sample observations, such as the use of stochastic frontier production functions. DEA is a linear programming (LP) based deterministic and non-parametric method for measuring the relative efficiency of DMUs (Decision Making Units) with multiple inputs and outputs. The DEA models most widely used in practice is the CCR. The CCR model assumes constant returns to scale (CRS). DEA models can be distinguished according to whether they are input-oriented or output-oriented (i.e. either minimizing inputs for a given level of output, or maximizing output for a given level of input). Charnes, Cooper and Rhodes [6] extended Farrell’s [7] work in the measurement of technical efficiency and first introduced the term data envelopment analysis, known as the CCR model. Here we give the formulation of the model. More formally, assume that there are n DMUs to be evaluated. Each DMU consumes varying amounts of m different inputs to produce s different outputs. Specifically, DMUj consumes amounts 𝑋𝑗 = �𝑥𝑖𝑗 � of inputs (i = 1; . . . ;m) and produces amounts 𝑌𝑗 = [𝑦𝑟𝑖 ] of outputs (r = 1; . . . ; s). The 𝑠 × 𝑛 matrix of output measures is denoted by 𝑌, and the 𝑚 × 𝑛 matrix of input measures is denoted by 𝑋. Also, assume that 𝑥𝑖𝑗 > 0 and𝑦𝑟𝑖 > 0. Consider the problem of evaluating the relative efficiency for any one of the n DMUs, which will be identified as DMU0. Relative efficiency for DMU0 is calculated by forming the ratio of a weighted sum of outputs to a weighted sum of inputs, subject to the constraint that no DMU can have a relative efficiency score greater than unity. Symbolically:
Page 5 of 10
Input-oriented CCR model
Subject to
ur , vi ≥ 0
𝑚𝑎𝑥u,v
∑r ur yr0 ∑i vi xi0
(1)
∑r ur yrj ≤1 ∑i vi xij
for j = 1, 2, … , n; r = 1, 2, … , s; and i = 1, 2, … , n
where ur and vi are weights assigned to output r and input i, respectively. This fractional programming problem can be easily transformed into the following equivalent linear programming problem: Subject to
𝑚𝑎𝑥𝑢,𝑣 ∑r ur yr0
(2)
∑i vi xi0 = 1
∑r ur yrj − ∑i vi xij ≤ 0 ur , v i ≥ 0
In the Input-oriented CCR model, efficiency scores range between 0 and 1.0. If a DMU has efficiency score smaller than 1 then it is inefficient. In the next section we can see the application of DEA-CCR input oriented model to evaluate the efficiency of two selected GIFT corridors (IV,V) considering five inputs (relative unit cost, transport time, delay risk, CO2 and SO2 emissions) and one output (frequency of regular service). With the application of this model we obtain the efficiency measure of the two corridors. Furthermore we can observe how the emissions of inefficient corridors can be reduced in order to improve the efficiency and the transformation to Green Corridors.
4
DEA for GIFT corridors efficiency evaluation
The information obtained from GIFT Project was analysed and gathered in order to make a selection process of KPIs and corridors for doing the efficiency analysis with DEA. Specifically, during this project, a set of Key Performance Indicators (KPIs) have been developed. The KPIs were calculated based on the data provided by all GIFT project partners during the Mapping of Current status. Once analyzed all KPIs for each
corridor, we have selected two specific corridors (corridor IV and V), which contain the more complete and comprehensive KPIs data for the evaluation of their relative efficiency with the application of DEA methodology. This selection process involves both the actual availability of data on certain KPIs both the specific modes of transport for each corridor. The selected KPIs have been used as inputs and outputs in the DEA-CCR input oriented model for corridor IV and V. Specifically, eighteen KPI-s divided in 4 categories (Service Efficiency, Service Quality, Infrastructure and Transport Business Players) have been elaborated during GIFT project. For the purpose of efficiency measure based on DEA only the KPIs related to transport operations were used, and they have been estimated for each specific mode of transport (road, rail) for each corridor (IV, V), as we can see below: • Relative unit cost (cost of goods transported per ton-km) • Transport time (average transport time from node to node) • Delay risk (amount of serious disruptions like cancellations, strikes, etc.) • Frequency of regular service (number of service per week) • CO2 emissions (total grams per ton-km that are emitted by transport activity • SO2 emissions (total grams per ton-km that are emitted by transport activity). The selected KPIs have been divided in five inputs and one output. The output measure used is one: frequency of regular service. The inputs measures used are five: relative unit cost, transport time, delay risk, CO2 and SO2 emissions.The data are listed in Table 1 for each mode of transport. Table 1. Values of the selected KPIs, divided in five inputs and one output per road/rail mode on Corridor IV and V GIFT Cor.s
Md
Rel. unit cost
Trans. time
Del. Risk
CO2
SO2
Freq. of reg. serv.
(€/tonkm)
(h/100k m)
(min/1 00km)
(g/tonkm)
(g/tonkm)
(numb.serv./w.)
Cor. IV
Rd
0,04
1,49
20,28
72,76
0,09
14,00
Cor. V
Rd
0,05
1,40
10,48
68,64
0,09
2,25
Cor. IV
Rl
0,03
1,51
25,82
19,66
0,06
9,00
Cor. V
Rl
0,03
1,83
50,31
17,65
0,09
104,73
Source: SEE-GIFT Project
Page 7 of 10
After applying CCR input oriented model, the results of efficiency analysis on the two selected corridors are shown in Tables 2 for mode of transport. DEA Excel Solver, the widely used DEA software, is used for the analysis. As shown in Table 3, for road mode, Corridor IV is efficient (100%) while Corridor V is inefficient (31%). For what concern rail mode Corridor IV is inefficient (17%) while Ccorridor V is efficient (100%). Table 2. Relative efficiency measures using DEA (CCR input oriented) per road/ rail mode for Corridor IV and V DEA CCR input-oriented
Mode Efficiency (%)
Corridor IV Corridor V
Road Road
100% 31%
Corridor IV Corridor V
Rail Rail
17% 100%
As shown in Tables 3 the corridors that are inefficient (Corridors V for road mode and Corridors IV for rail mode) can increase their efficiency score decreasing properly their input variables. In fact, the application of DEA-CCR input oriented model allows to determine, for a given value of output, the optimal reduction of inputs in order to reach the corridors the efficiency of 100%. Specifically, in the first row of Tables 3 are reported the original values of the inputs, in the second row are reported the values of the inputs properly reduced by the application of DEA to increase the efficiency score of Corridors IV and V. Table 3. Potential improvement of Corridor IV and V through the reduction of inputs by DEA CCR input-oriented Gift Cor.s
Mode
Cor. V
Road
Cor.IV
Rail
Relative unit cost
Transport time
Delay risk
CO2
SO2
0,05
1,40
10,48
68,64
0,09
0,01
0,44
3,26
21,35
0,03
0,03
1,51
25,82
19,66
0,06
0,01
0,25
4,32
3,29
0,01
Obviously, corridor IV in road mode and corridor V in rail mode will not change in anyway their inputs values because, according to DEA efficiency analysis, they are already operating in their optimal condition. We conclude by highlighting that the reduction of the input variables for inefficient corridors will also lead to an increase in performance in terms of green transport objectives achieved through sustainable transport based on cleaner fuels which will
reduce emissions of pollutants, tax incentives, good infrastructure and organisation etc.
5
Conclusions
Many transportation companies have started to adopt new methods to reduce freight costs (mainly through co-modality) and become more environmental friendly. The strengthening of intermodality through green transport corridors may be an effective approach to environmentally friendly and safer freight transport. Furthermore, the modernization of administrative processes coupled with suitable initiatives could lead to substantial increase of the share and efficiency of alternative modes. GIFT aspires to contribute significantly in defining efficient green transport corridors through the SEE region. As a matter of fact, too often the current transport networks cut out the South-East Europe corridors and refuse to acknowledge the importance of southern ports. This EU attitude constricts national infrastructure policies. Just as an example, Bari-Naples high capacity is seen only in terms of local transport, and not as an element of intermodal traffic to the West-East, where the ports of Barcelona, Naples-Salerno and Bari-Brindisi could play an important role as intermodal hubs. Policy makers, industry players and institutions, will have the opportunity to exchange views and support the collaboration between key transport players (i.e. shippers, carriers, forwarders). The latter will be also supported by the creation of Local Discussion & Consultation Platforms and the formulation of an innovative Green Intermodal Freight Transport Cluster. Furthermore, various tools (e.g. web site, publication material, etc) for the dissemination and communication activities of the project have been developed. In particular, this article is an attempt to provide a satisfactory answer to the problem of making efficiency comparisons across corridors of South East Europe by applying the DEA analysis to a sample of GIFT corridors (IV, V) for which relevant data are available. DEA has recently been successfully applied to a number of different economic efficiency measurement situations. This study has shown the suitability of DEA for GIFT corridor efficiency evaluation and produced useful findings for certain corridors. The results clearly show lowest performance level of GIFT corridor V compared gift corridor IV (road mode) while, for rail mode, GIFT corridor IV is inefficient compared to corridor V. Through DEA-CCR input oriented analysis we can reduce the inputs values of inefficient corridors to increase efficiency score and, contemporary, to improve their operational status and their transformation to Green Corridors. Promotion of intermodality, purchase of new trucks, and use of high quality fuels, along with better road conditions (especially on corridor V), may contribute to reduction of CO2 pollution emitted by road transport. Far more extensive measures should be taken in railway transport to complete electrification of railway corridor and
Page 9 of 10
replace old diesel traction units as well as to solve insufficient railway capacities entailing bad transport optimisation and resulting in higher CO2 emissions (especially on corridor IV). However, we can consider the road and railway results very reliable. Acknowledgements. This study was supported by the South-East Europe (SEE) Transnational Cooperation Project GIFT – Green Intermodal Freight Transport – Project No. SEE/C/0003/3.3/X (http://www.gift-project.eu)
References [1] Lammgård, C.: Intermodal train services: A business challenge and a measure for decarbonisation for logistics service providers. In: Research in Transportation Business and Management, vol.5, pp. 48-56 (2012) [2 ] Bray S, Arampantzi C, Binetti M, Caggiani L, Minis I, Ottomanelli M, Zeimpekis V: DEA for reen intermodal freight transport efficiency evaluation: the case of South East Europe corridor. In: Proc. of the 8th International Scientific Conference - Ports and waterways POWA2013. Zagreb, Croatia (2013) [3] Tangari, L., Ottomanelli, M., Sassanelli, D.: Multicriteria Fuzzy Methodology for Feasibility Study of Transport Projects. Case Study of Southeastern Trans-European Transport Axes. In: Transportation Research Record: Journal of the Transportation Research Board, No. 2048, Transportation Research Board of the National Academies, pp. 26–34. Washington, D.C. (2008) [4] European Commission. Freight Transport Logistics Action Plan. Communication from the Commission, COM(2008) 607. Brussels (2007) [5] Engström, R.: The swedish green corridor initiative – history, current situation and thoughts about the future. In: Proc. of the 8th SoNorA University Think Tank Conference. Szczecin, Poland (2011) [6] Charnes, A., Cooper, W.W., & Rhodes, E.: Measuring the Efficiency of Decision Making Unit. In: European Journal of Operational Research, vol. 2, No. 6, pp.429-444 (1978) [7] Farrell, M.J. : The measurement of productive efficiency. In: Journal of the Royal Statistical Society (Series A), vol. 120, No. 3, pp.253-281 (1957)
[8] Bray, S., Caggiani, L., Dell'orco, M., Ottomanelli, M.: Measuring Transport Systems Efficiency under Uncertainty by Fuzzy Sets Theory based Data Envelopment Analysis. In: Procedia - Social and Behavioral Sciences, 111, 770-779 (2014) [9] Camporeale,R., Chiarazzo,V., Caggiani,L.,Binetti,M., Ottomanelli,M.: GIFT Project. Actions, infrastructures and ICT measures for the improvement of the current South East Europe green intermodal freight transport network. In: CEUR Workshop Proceedings (2014)
