Measuring and improving operational energy efficiency in short sea container shipping

RTBM-00201; No of Pages 10 Research in Transportation Business & Management xxx (2015) xxx–xxx

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Research in Transportation Business & Management

Measuring and improving operational energy efficiency in short sea container shipping Halvor Schøyen a,⁎, Svein Bråthen b a b

Buskerud and Vestfold University College, P.O. Box 235, N-3603 Kongsberg, Norway Molde University College — Specialized University in Logistics, P.O. Box 2110, NO-6402 Molde, Norway

a r t i c l e

i n f o

Article history: Received 5 March 2015 Received in revised form 29 September 2015 Accepted 6 October 2015 Available online xxxx Keywords: Energy efficiency Short sea shipping Vessel logistics Feeder operations

a b s t r a c t This study develops a detailed operational activity-based method to estimate energy efficiency for feeders vessels, both during sailing condition and whilst in port working containers. Two case studies from the North Sea provide empirical evidence on feeder operations and energy efficiency and are compared to estimates presented by International Maritime Organization. The results show that if aggregated methods for energy efficiency estimation are used, appropriate vessel sailing speed, port time/sailing time ratio and cargo capacity utilization need to be taken into account. Information sharing between ocean carriers, feeder operators, port agents and terminals is usually not adequate to allow operational speed optimization per leg. Further, port and terminal price tariffs justifying 24/7 loading/discharging seem to be necessary to stimulate shorter feeder turnaround time and allow for slow steaming and fuel savings. In addition, alignment of incentives for fuel savings among the vessel officers and other parties in the supply chain is critical. © 2015 Elsevier Ltd. All rights reserved.

1. Introduction Energy-efficient vessel operation does saves money and reduces emissions. There is a gap between what is technically and economically rational for more energy efficient vessel operations, and what is actually practised in shipping companies (Johnson, Johansson, Andersson, & Södahl, 2013). Containerships are among the largest and fastest growing maritime CO2 emitters (Corbett, Wang, & Winebrake, 2009), however the study of energy cost, CO2 emissions and their reduction within the segments of container vessels mainly focuses on the ocean-going larger vessels. Little research has been devoted to the smallest category of container vessels – feeders – which are mainly used in short sea shipping and in draught-restricted ports. This is the main concern of this paper. The objectives of this study are: (1) explain an operational activitybased method for quantifying energy efficiency for feeders, and (2) examine the interplay between supply chain actors and its impact on feeder energy efficiency. Throughout this paper, ‘feeder’ means the category of un-geared lo–lo container vessels (Stopford, 2009) in the size range 500–999 twenty feet equivalent container units (TEU), and operating in short sea shipping. Based on the theoretical outline presented in the first part of the paper, two case studies from feeder operations between selected North European ports will explore how vessel logistics influence energy efficiency. Vessel logistics is concerned with maximizing vessel utilization (Frémont, 2009). Energy efficiency for a vessel whilst sailing can ⁎ Corresponding author. E-mail addresses: [email protected] (H. Schøyen), [email protected] (S. Bråthen).

be seen as a function of (1) sailing speed, (2) cargo capacity and (3) the average cargo capacity utilization (Kristensen, 2006). This paper extends the literature on maritime logistics and energy use (e.g. Acciaro, Hoffmann, & Eide, 2013; Kontovas & Psaraftis, 2011; Lindstad, Asbjørnslett, & Pedersen, 2012) by assessing how the interplay between shipping and port actors impact feeder energy efficiency. Section 2 provides the theoretical background to the study. Section 3 describes the methodology and data collection. Section 4 explains the setting in which the two case studies are carried out and presents the two cases. Section 5 provides a discussion together with managerial implications. Section 6 contains some recommendations for further research. 2. Review of literature relevant for energy efficient feeder operations Several theoretical approaches can be used; three issues are taken into account here. Firstly, the literature relating to the role of feeders in supply chains is reviewed, with emphasis on freight market niches, costs and vessel capacity utilization. Secondly, a brief review on contractual and behavioural issues linked to incentives and disincentives for fuel saving in short sea container operations is presented. Thirdly, the literature on energy efficiency estimation methods relative to feeder shipping is reviewed. 2.1. The role of feeders in supply chains Short sea container shipping can be divided into two market niches. The first niche (a) serves pure intra-regional trade and is frequently referred to as short sea shipping, often with the use of pallet-wide

http://dx.doi.org/10.1016/j.rtbm.2015.10.004 2210-5395/© 2015 Elsevier Ltd. All rights reserved.

Please cite this article as: Schøyen, H., & Bråthen, S., Measuring and improving operational energy efficiency in short sea container shipping, Research in Transportation Business & Management (2015), http://dx.doi.org/10.1016/j.rtbm.2015.10.004

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containers. The second niche, feeder service, is a continuation of the ocean liner market, using ISO containers. A feeder service connects at least two ports in order for the containers to be redistributed to or from an ocean-service in one of these ports (UNECE, 2001). In this niche, feeders represent a link in global hub-and-spoke containerized networks, hence decisions elsewhere in the maritime logistics chain (e.g. slow steaming of the large ocean-going vessels) may entail domino effects in short sea container shipping. As a result of fundamental issues within vessel design and capacity (van Dokkum, 2013), vessels have very low marginal costs related to cargo, leading to the situation that vessel operators frequently use larger vessels than required by the freight basis. Over-dimensioned vessels have the important competitive advantage in the short-to-medium term that their operators will have available capacity to service potential customers on short notice. Styhre (2010) examined operational measures to improve feeder capacity utilization in transport chains, and identified four groups of external factors (market factors, customer factors, port factors and surrounding factors) and two groups of internal factors (vessel technical factors and management factors) to influence capacity utilization and thereto energy efficiency (Kristensen, 2006). Supply networks can be roughly characterized by flexibilization and globalization (Notteboom & Rodrigue, 2008). With respect to timeliness and schedule reliability, the ocean carriers' performance varies substantially among shipping lines and routes, as documented by Saldanha, Tyworth, Swan, and Russell (2009). Hence, in hub-and spoke configurations, when an ocean carrier is subjected to delays or port reshuffling/ cancellations, the feeder service can be a flexible link in the network to get the cargo back on schedule. One example of such functioning as flexible link is short notice decisions by the feeder operator on changes in vessel and container routing and scheduling, see Section 4.1. 2.2. Incentives among supply chain actors for energy efficient feeder operations A proper way of information sharing between supply chain actors, e.g. sharing evidences on transport demand, capacity issues and customer relationships, may allow for operational improvements. Information and communication technology (ICT) and relating infrastructure is recognized as a success factor for supply chain integration, with positive implication for firms' competitiveness, also in the shipping and port industries (Cepolina & Ghiara, 2013). According to Du, Chen, Quan, Long, and Fung (2011) a potential field of information sharing and coordination between a feeder operator and terminal is to facilitate speed adjustments whilst sailing on one leg between two ports, in order to adapt to the available arrival time slot at the terminal. Such coordination may help minimize fuel consumption and port/terminal congestion. Nevertheless, Lee (2004) claimed that the alignment of the interests of all actors is a necessity for sustainable supply chains. Incentive misalignment and disincentives, possibly resulting from situations with asymmetric information and transactions costs of developing shared saving contracts, can negatively impact energy efficiency (Sorrell, O'Malley, Schleich, & Scott, 2004). Moreover, the ship-owner and actors responsible for chartering, technical management, manning and paying for fuel are frequently not the same (Panayides & Cullinane, 2002). This is one example of contractual dyadic relationships where contract typology – directly or indirectly – may affect transport energy efficiency. In short sea operations, working days on board consist of watches, usually 12 h on and 12 h off per day. However, with frequent port calls, this watch schedule is repeatedly disrupted by the many tasks to be completed when calling at the ports, e.g. vessel manoeuvring, managing cargo handling and bunkering – which often results in longer working days than 12 h. Hence, human fatigue is a general problem in shipping, and one of particular concern in short sea services (Österman & Osvalder, 2012; Wadsworth, Allen, Wellens, McNamara,

& Smith., 2006), which may contribute to bounded rationality among a vessel's shipboard management team (SMT). One example is possible limitation among SMT's individual officers in their ability to process information, which may lead to “optimizing analyses being replaced by imprecise routines and rules of thumb” (Sorrell et al., 2004, p. 78). This may in turn affect fuel consumption and alignment with the available port/terminal slots.

2.3. Energy efficiency estimation methods in container shipping The objectives for specifying an energy efficiency estimation method for feeder vessels are twofold. The first objective is to be able to track one particular vessel's performance, in time and place. The second is to be able to measure and compare energy efficiency across feeder pendulums, transport modes and supply chains. As market prices change over time, prices should not be included directly in the construction of an indicator meeting the above-stated objectives (Patterson, 1996). Transport energy efficiency can be expressed as an indicator, which here is denoted gramme of CO2 per TEU and nautical mile (nm), in line with IMO, 2009 and Psaraftis and Kontovas (2009). In our opinion there seems to be a need for approaches to evaluate energy efficiency estimation methods for container vessels which to a smaller degree are founded on assumptions and which also define sources for data collection. The purpose here is to explain an operational activity-based method for quantifying energy efficiency for feeders. The method is illustrated in a flow chart in Fig. 1 and has been applied in the case studies presented in Section 4. The method depicted in Fig. 1 includes energy efficiency measurements both for transport (legs) and for port stays. The latter is included as feeders that frequently spend a substantial amount of time in port. Emissions during port stays are here proposed to be measured in kg CO 2 /TEU move, where ‘move’ denotes one container's movement during loading or unloading between the feeder and the terminal or barge. The physical units of analysis are TEUs and vessel sailing legs. Vessel data are nominal values derived from ‘vessel particulars’. Container flow data and vessel movement data are displayed in cargo loading lists and voyage reports respectively. All these data are usually reported from the vessel to its commercial principal. The method is compiled from: Hjelle, 2010; IMO, 2009; Psaraftis & Kontovas, 2009. The Second IMO GHG Study (2009) appears, in a global context, as the most comprehensive work on energy efficiency presented in the literature so far, and is the benchmark against which the method (Fig. 1) and evidence must be judged. This will be done in Section 5.

3. Methodology 3.1. Case study design A case study method is used in this paper (Yin, 2009). To obtain a closer look on the operational activity-based method and on the interactions between supply chain actors' impacts on energy efficiency as presented in Section 2, data from two separate vessel operating companies were collected. The data from the first company apply to a pendulum which is mainly a feeder service and relates to case 1. The data from the second case apply to a pure intra-regional service and relates to case 2. The reason for examining two cases pertaining to separate vesseloperating companies is to study how fundamental market differences between feeder services and intra-regional trade may affect energy efficiency. Because of the utilization of a two-case cross-sectional study where the quantifiable data were too limited to be subjected to statistical tests, a generalization of results should be made to theory and not to populations (Yin, 2009).

Please cite this article as: Schøyen, H., & Bråthen, S., Measuring and improving operational energy efficiency in short sea container shipping, Research in Transportation Business & Management (2015), http://dx.doi.org/10.1016/j.rtbm.2015.10.004

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Fig. 1. Operational activity-based method for calculation of energy efficiency.

3.2. Data collection

3.3. Background to the intra-regional case

Data has been collected from the following actors along the supply chain: ship operators, ship officers, port agent and some port managers. Sources of evidence have been companies' and ports' web pages, internal company documents, personal communication (face to face, phone, e-mail) with managers at various levels ashore and on board vessels, on-board observations with field notes and interviews. The interviews comprise for case 1 one focus interview with the director for business development, a business development manager and an analyst for business development in a north European feeder operating company, conducted and transcribed by the authors and reviewed and approved by the informants. For case 2 three semi-structured interviews were conducted by the authors on board ‘Case 2’; the Captain, Chief Officer and Chief Engineer, respectively, including the two former answering written questionnaires (Appendix B). For cases 1 and 2, both qualitative and quantifiable data were collected. Multiple sources of evidence and activities have provided a process of triangulation, thus enhancing the validity and authenticity of this case study (Ellram, 1996). Case study tactics for ensuring case study reliability include the use of a research protocol comprising review of the literature, explanations of the applied research method and the interview guides (see Appendix A & B), all stored in a case study database.

Fig. 2 shows the feeder vessel ‘Case 2’. The photo is taken in Oslo Fjord in Norway, when the vessel was underway from Drammen to Moss. The data necessary to calculate energy efficiency were collected on board by the authors on that particular voyage. Some observations linked to energy efficiency can be drawn from the photograph in Fig. 1: containers are stowed both on deck (visible in the photo) and in cargo holds (invisible). A situation of many containers on deck indicates that the ship is nearly fully loaded in respect of slot utilization. However, on the hull, the belt of red-coloured antifouling paint visible above the waterline and the bulbous bow is semi-submersed, which indicates that the ship is floating high on the water and thus is light loaded, in respect of deadweight. Therefore, many of the containers on board at the time when this photo was taken are probably light or empty. Vessel's flotation, e.g. with the bulbous bow semi-submersed, as in the photo, may for some vessel design increase the vessel's overall hydrodynamic resistance and thus increase fuel consumption, compared to a heavy loaded condition where the bulbous bow is fully submerged and with less aerodynamic resistance. Consequently, it is not granted that a fully loaded vessel consumes more fuel compared to a less loaded vessel (Schneekluth & Bertram, 1998).

Fig. 2. The feeder vessel in Case 2. Photo: Author.

Please cite this article as: Schøyen, H., & Bråthen, S., Measuring and improving operational energy efficiency in short sea container shipping, Research in Transportation Business & Management (2015), http://dx.doi.org/10.1016/j.rtbm.2015.10.004

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Combined, the observations and issues mentioned above illustrate complexity and some of the internal and external factors that affect energy efficiency in feeder operations. The observation session on board the vessel “Case 2”, evolved into a combination of unstructured informal interviews and observations, the outcome included a permission to access to loading lists. A key feature of theory-building case research is the freedom to make adjustments during the data collection process (Eisenhardt, 1989). 4. The two cases The case in Section 4.1 applies to a pendulum which is mainly a feeder service. The case in Section 4.2 applies to a pure intra-regional service. Fig. 3 shows sailing routes and ports called in cases 1 and 2. Although the vessels in cases 1 and 2 are of different vintages, built in 2006 and 1992 respectively, they share similar function and technology, i.e. both are equipped with four-stroke propulsion engines fuelled on variants of heavy fuel oil (HFO). The voyages took place in August 2009 (case 1) and September 2010 (case 2). As of March 2015 these two vessels are still operating. The average age of scrapped containerships in 2009 was 27 years, which has resulted in a present situation of slow fleet turnover (UNCTAD, 2010). This implies that behavioural change, e.g. demand management, can be the main cause for possible energy efficiency improvements in the short to medium term. One aspect of demand management linked to feeder services is the generation of useful information, which may allow for increased precision in demand forecasts (Ascencio, González-Ramírez, Bearzotti, Smith, & Camacho-Vallejo, 2014) to support tactical and operational decisionmaking relating to vessel cargo capacity utilization. 4.1. Case 1 — Feeder service The operator of the vessel ‘Case 1’ is one of the larger feeder operators in the North and Baltic Sea. The operator is a commercial manager, not a vessel owner, technical manager or responsible for the manning. Table 1 shows the vessel particulars for ‘Case 1’ and its published schedule. Table 1 shows that the container capacity is 700 TEU slots, a portion of the container units then has to be empty, due to vessel stability restrictions. The main engine of the vessel consumes 32 tonnes/day of heavy fuel oil (HFO) at a design service speed of 17.5 knots. The published schedule (see Table 1) is adjusted weekly, and flexibility in

Table 1 Vessel particulars “Case 1” and published schedule. Flag/Nationality

Cyprus

Container capacity (TEU slots) Reefer container capacity (plugs) Year built Gross tonnage Deadweight (mt) Max draught (m) Length over all (m) Breadth over all (m) Design service speed (knots) Consumption/day (mt/24 h) Fuel for propulsion Main engine RPM/kW Bowthruster (kW) Auxiliary engines Auxiliary engines fuel Shaft generator (kW) Ballast water capacity (mt)

700 120 2006 7545 8300 7.4 129.2 20.6 17.5 32 HFO 500/7200 600 3 × 450 kW, 1 × 120 kW MDO 1000 3300

Weekly sailing schedule Port

Day

Bremerhaven Hamburg Halmstad/Aarhus Moss/Fredrikstad/Larvik/Oslo Bremerhaven

Sunday Monday/Tuesday Wednesday Thursday/Friday Sunday

routing between ports and between terminals within one port area are keys. Four terminals were called in Hamburg (Altenwerder, Burchardkai, Eurogate & Tollerort) and two terminals were called in Bremerhaven (North Sea Terminal & Eurogate). Altogether 23 different ocean container liner companies were identified as customers in the vessel cargo loading lists. Ocean carriers' performance on schedule reliability and timeliness varies, as reported in Section 2 (Saldanha et al., 2009). Sometimes the feeder operator learns as late as 3 h in advance the ocean vessel's ETA and the number of containers to handle. Therefore, when calling a hub port, short notice decisions have to be made regarding which terminals to call in that port area and in which sequence; routing and scheduling of hauling operations have to be flexible. Table 2 contains capacity utilizations and energy efficiency per leg. Table 2 is derived according to the method depicted in Fig. 1, Section 2. Vessel capacity utilization rates were between 63% and 91%

Fig. 3. Map over vessel sailing routes in cases 1 and 2.

Please cite this article as: Schøyen, H., & Bråthen, S., Measuring and improving operational energy efficiency in short sea container shipping, Research in Transportation Business & Management (2015), http://dx.doi.org/10.1016/j.rtbm.2015.10.004

14 11 13 14 10 13 13 5414 4787 2615 2832 3414 4653 3953 Ave: 0.3 0.6 0.2 0.2 0.3 0.8 2.3 6.9 7 16.4 13.5 2.3 2.6 22.8 64.6 1.4 382 119 424 237 201 244 205 40 343 36 364 340 Sum fuel consumption at sea: Sum fuel consumption in port: Hamburg Aarhus Moss Fredrikstad Larvik Bremerhaven Bremerhaven Hamburg Aarhus Moss Fredrikstad Larvik

45458 100488 49044 8200 12348 123760

mt mt nm TEU Port of departure (left) and arrival (right)

TEU nm

Fuel consumption GO Fuel consumption HFO Transport work Distance Containers carried on-board Leg

Table 2 Case 1. Capacity utilization and energy efficiency per leg.

15.3 kg CO2/TEU move Energy efficiency performance in port, average:

91% 82% 63% 70% 72% 78% 76% 7579 6791 5214 5829 5998 6514 6321 368 347 335 326 322 309 334 1747 1607 2214 2621 2212 1502 1984

mt mt mt

Fuel Ballast

55% 61% 29% 29% 49% 52% 46% mt/TEU mt

506 534 878 970 741 600 705

g CO2/TEU nm

By dead-weight Pay-load per container, ave.-rage Pay-load incl tare

Sum dwt

Vessel capacity utilization Deadweights

By occupied TEU slots

Energy efficiency performance at sea

H. Schøyen, S. Bråthen / Research in Transportation Business & Management xxx (2015) xxx–xxx

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based on deadweight, and 29% and 61% based on slots. A substantial amount of ballast water was carried on every leg. Having ballast water on board means to ensure vessel trim and stability, reduce propeller racing and control vessel motions. Empty containers are included in Table 2; 19% of the TEUs loaded and 26% of the discharged TEUs were empties. Table 2 reports that during the voyage the vessel burned 64.6 mt of HFO and 2.3 tonnes of MDO whilst sailing, and 1.4 mt and 6.9 mt respectively whilst in ports. The energy efficiency was in the range of 506 to 970 g CO2/TEU nm, on average 705 g CO2/TEU nm. In ports an average of 15.3 kg CO2 was emitted from the vessel per TEU moved, i.e. loaded/discharged. Fig. 4 reports that ‘Case 1’ stayed 53% of the time in port and 11% of the carbon dioxide emissions took place in port. Table 2 and Fig. 5 show that the Bremerhaven–Hamburg leg was the most energy-efficient, even though the speed on that leg was relatively high, the no. of TEUs on board modest (55% slot capacity utilization), and the deadweight capacity utilization as high as 91%. The average speed on the Hamburg–Aarhus leg was only 11.0 knots despite the ‘full speed’ order by the operator, a fact that can be explained by the passing of the Kiel Canal on that leg. During that canal transit the average speed was 6.4 knots. Despite the variable speed on this leg, the energy efficiency was relatively high, giving 534 g CO2/TEU nm. The two shorter legs, Moss–Fredrikstad and Fredrikstad–Larvik, were relatively energy-inefficient, even though the speed also was low, due to low capacity utilization. One further finding was that the operator sometimes orders their vessels to speed up or to lay idle during night time on Norwegian terminals, to do cargo handling on the terminal day shift, which is very much cheaper than the night shift. Such behaviour will not improve transport energy-efficiency. 4.1.1. Conclusion, case 1 It appears that in feeder services, flexibility in routing and scheduling between ports and between terminals within a port area is imperative. The relationships between capacity utilization, speed order, actual speed and energy efficiency are hard to identify. The amount of CO2 emitted in port per TEU moved is a significant amount. Information distortion between ocean carriers, feeder operators, feeder SMT, port agents and terminals does take place. Slack in the published feeder schedule may be spent idle whilst berthed and not by slowing down at sea. 4.2. Case 2 — Intra-regional service The company operating the vessel ‘Case 2’ provides a short sea and logistics services in the North and Baltic Sea and is a relatively new entrant in feeder shipping. As in Case 1, this company acts as a commercial manager and other actors are responsible for ownership, manning and technical management. Table 3 shows the vessel data for ‘Case 2’. The published schedule is fixed, as it remained unchanged for several months both before and after the particular voyage presented in this case. As stated by the captain, they were ‘always ahead of schedule’. When approaching Rotterdam, information about the berthing window is received usually only half an hour before the pilot is picked up at the port entrance, meaning that potential surplus time cannot be spread out over much of that sailing leg, i.e. seeking for optimum speed per leg is difficult. Berthing information is given by the operator's port agent. The captain commented: ‘More quality info from the agent would afford us better speed decisions on legs’. Table 4 shows capacity utilizations and energy efficiency per leg. One container terminal was called per port. Capacity utilization rates were between 56% and 84% based on deadweight, and 46% and 69% based on slots. The average mass of ballast water carried was 1418 mt, which equals 53% of the average payload carried. ‘Case 2’ stayed 40% of the time in port and 6% of carbon dioxide emissions took place in port. Fig. 6 shows per leg energy efficiency.

Please cite this article as: Schøyen, H., & Bråthen, S., Measuring and improving operational energy efficiency in short sea container shipping, Research in Transportation Business & Management (2015), http://dx.doi.org/10.1016/j.rtbm.2015.10.004

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Fig. 4. Case 1. Decomposition of time, distance and CO2 emissions for the voyage.

The vessel's officers make all voyage planning and speed decisions themselves, as the operator seldom gives speed orders other than the standing order for ‘Eco speed’. According to the Chief Engineer, ‘Eco speed’ equals to 54% engine load and 14 knots speed. The discrepancy between the ‘Eco speed’ and the actual speeds displayed in Fig. 6 cannot be explained. The vessel, ordered by either the operator or the captain, stayed idle for several hours whilst berthed in Larvik; a lapse which could possibly have been spent at sea, slow steaming and saving fuel. The reason for this behaviour leading to inactivity could probably be, like in Case 1, related to operators' choice based on terminal tariffs on loading/discharging. In combination there could be other explanations, one rooted in the fact that the manning on ‘Case 2’ comprised only of three deck officers, including the captain. This means that the captain himself had to keep regular watch on the bridge, day and night, in addition to added administrative work when calling ports. The crew was happy to get one peaceful night's sleep undisturbed by cargo operations when the ship was lying idle. 4.2.1. Conclusion, case 2 In an intra-regional service it appears that vessel routing and scheduling is more fixed than in a feeder service. Slack in the schedule may be spent idle whilst berthed and not by slowing down at sea. The SMT is aware of fuel costs importance, but their focus on other duties and rest leads to a situation where working on fuel savings is given a low priority. 5. Main findings and managerial implications 5.1. Consideration on method to estimate energy efficiency Table 5 illustrates that short sea container shipping operations may be significantly more energy-inefficient than reported in the Second IMO GHG Study (2009). This finding is supported by the fact that the vessel speeds observed in the cases were much lower than the assumed values for capacity utilization, time in port versus at sea, and vessel speed in the Second IMO GHG Study (2009). Table 5 illustrates that on

average, in both Cases 1 and 2, the vessel capacity utilizations were much higher in respect of deadweight than in respect of slots, due to ballast water on laden legs. Hence, if a feeder is fully loaded according to number of slots, it has to be assumed that a portion of the containers is empty. The use of slots as the only vessel capacity measure seems to be of restricted validity for feeders, due to ballast water on laden legs. Implications are that the use of assumed vessel sailing speed as well as the use of assumed port time seem to be of restricted validity for feeders. Therefore, appropriate vessel sailing speed, port time/sailing time ratio and vessel cargo capacity utilization need to be taken into account. 5.2. Inter-firm information sharing and incentive alignment The findings in the two cases indicate that information sharing between ocean carriers, feeder operators, port agents and terminals is not adequate in supporting better logistics planning, e.g. in the form of improved voyage planning on board for more economical sailing speeds on legs. Various mind sets among maritime logistics actors could be a barrier to better planning and energy efficient operations. Moreover,

Table 3 Vessel particulars “Case 2” and published schedule. Flag/Nationality

Antigua and Barbuda

Container capacity (TEU slots) Reefer container capacity (plugs) Year built Gross tonnage Deadweight (mt) Max draught Length over all (m) Breadth over all (m) Design service speed (knots) Consumption/day (mt/24 h) Fuel for propulsion Main engine RPM/kW Bowthruster (kW) Auxiliary engines Auxiliary engines fuel Shaft generator (kVA) Ballast water capacity (mt), at least

510 50 1992 5025 6545 6.87 116.79 18.1 15.8 20.83 HFO 450/4 441 350 2 × 250 kVA, 1 × 40 kVA MGO1 1000 2245

Weekly sailing schedule Port

Rotterdam Drammen Moss Larvik Esbjerg Immingham Fig. 5. Case 1. Per leg energy efficiency, speed order instruction and actual speed.

ETA

ETD

Day

Time

Day

Time

Friday Monday Monday Tuesday Wednesday Thursday

PM AM PM AM AM PM

Saturday Monday Monday Tuesday Wednesday Thursday

AM AM PM AM PM PM

1 MGO and MGO are both destillates of crude oil and they have identical fuel mass to CO2 conversion factor.

Please cite this article as: Schøyen, H., & Bråthen, S., Measuring and improving operational energy efficiency in short sea container shipping, Research in Transportation Business & Management (2015), http://dx.doi.org/10.1016/j.rtbm.2015.10.004

47% 50% 46% 48% 61% 69% 54%

541 565 913 496 464 453 572 9.1 kg CO2/TEU move

g CO2/TEU nm

By occupied TEU slots By dead-weight

81% 84% 56% 58% 76% 66% 70% 12 1836 113 5276 11 2245 111 5507 9 1001 108 3683 9 977 97 3777 10 1380 81 4995 8 1072 71 4339 10 1418 97 4596 Energy efficiency performance in port, average: 2931 2754 2178 2306 3137 2799 2684 Ave:

mt mt

mt mt/TEU mt

Fuel Ballast

Sum dwt Pay-load per container, ave.-rage

Deadweights

0.6 0.2 0.4 0.5 0.4 0.6 2.6 3.8 22 1.1 2.4 9.4 14.7 9.7 59.3 0 131634 7160 9547 62874 102697 71569 239 551 256 28 233 41 246 256 313 328 354 202 Sum fuel consumption at sea: Sum fuel consumption in port: Drammen Moss Larvik Esbjerg Immingham Rotterdam Rotterdam Drammen Moss Larvik Esbjerg Immingham

mt TEU·nm TEU Port of departure (left) and arrival (right)

nm

mt

Fuel consumption GO Transport work Containers carried on-board

Distance

Fuel consumption HFO

the results in the two cases suggest that feeder vessels frequently stay idle when berthed in a port. It can be extracted from the results of the two cases that port and terminal contracts and price tariffs justifying 24/7 loading/discharging seem to be necessary to stimulate shorter vessel turnaround time, and may allow for lower vessel sailing speed and fuel savings. It is widely accepted in the supply chain literature that an exchange of information and business knowledge improves logistics service quality. 5.3. Intra-firm information sharing and incentive alignment It seems that the staff on-board does not have the real time information nor the incentives to plan for operational fuel savings leading to more energy-efficient freight. This implies that ship managers may need to take more into account incentive alignment for ship and shore-based staff in order to make better decisions on managing their shipping business more agile and energy-efficient. 5.4. Investing in new technology

Leg

Table 4 Case 2. Capacity utilization and energy efficiency per leg.

7

Fig. 6. Case 2. Per leg energy efficiency, speed order instruction and actual speed.

Pay-load incl tare

Vessel capacity utilization

Energy efficiency performance at sea

H. Schøyen, S. Bråthen / Research in Transportation Business & Management xxx (2015) xxx–xxx

It would be a waste of resources if feeder owners and charterer were unable to make energy-efficient use of its existing vessels due to behavioural barriers or market constraints as pointed out in this paper, ascribing instead inferior energy use in operations solely to technological deficiencies, and erroneously continued only with a technological investment programme. Some actors in the shipping industry have expressed the possibility that retrofitting of fuel saving devices like shaft generator (see Tables 1 & 3) frequency converters (Solla, Coache, & Sarasquete, 2012) might lead to fuel savings as high as those realized by state-of-the-art “Eco-ships” (Boonzaier, 2013). Therefore both operational and technological measures may lead to a situation with more energy-efficient feeder services provided by existing vessels. 5.5. Port and terminal performance linked to transport energy efficiency The findings on inadequate information sharing between actors and the fact that feeders in liner operations frequently stay idle in port should be of relevance for investigators on port performance linked to energy management. Port performance literature seem to have focussed on physical resources for physical flows (e.g. berth lengths), while seldom measured and included in their research information system capabilities and time costs relating to physical flows. 6. Limitations and recommendations for further research The findings presented in this paper are valid within what can be considered as realistic operating environments with respect to distance, time, sailing speed and achieved capacity utilization. It should hold true at least for feeders deployed in similar trades and conditions as

Please cite this article as: Schøyen, H., & Bråthen, S., Measuring and improving operational energy efficiency in short sea container shipping, Research in Transportation Business & Management (2015), http://dx.doi.org/10.1016/j.rtbm.2015.10.004

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Table 5 Comparing evidence from the two cases and the Second IMO GHG Study (2009).

Unit of analysis Year Vessel capacity (slots, in TEU) Average vessel capacity utilization Average container weight (mt) Speed (knots) Time at sea Time in port Average energy efficiency performance for port stays (kg CO2/TEU move) Average energy efficiency performance sailing (g CO2/TEU·nm)

Case 1

Case 2

Second IMO GHG Study

One roundtrip 2009 700 76% by dwt 46% by slots 13 11.0 – 15.3 47% 53% 15,3 705

One roundtrip 2010 510 70% by dwt 54% by slots 10 11.4 – 14.7 60% 40% 9,1 572

Feeder world-wide fleet, 1120 vessels 2007 0–999 n/a 70% by slots 7 17.0 70% 30% n/a 471⁎

⁎ Based on 1 km = 0.534 nm.

presented in the cases and is highly dependent on the prevailing market situations (Halldórsson & Aastrup, 2003). Compared to other areas in the Baltic and North Sea, the peculiar port structure in the Oslo Fjord, with many small and adjacent ports, does influence shipping operations in that area. Thin linkages may be characterized by low capacity utilization and energy inefficiency. Future research may extend this study to other feeder markets.

• Can you describe what factors impact energy efficiency in your operations?

Acknowledgements

• See Interview protocol in (Styhre, 2010)1, Study III.

The authors acknowledges the participation of the interviewed managers and ship officers. The authors are sincerely thankful to comments from three anonymous referees, as well as Alice Tonzig for her proofreading of the English language. Any errors are our responsibility. Appendix A. Questions to the feeder vessel operator This section presents relevant topics that were covered in a semistructured interview with managers in a feeder operator company; these topics were then developed as a guide for in-depth interviews with ship operators. The objective of the interview was to develop an understanding about feeder operations in The North Sea and the Baltic Sea, and particularly to achieve an insight into the conditions and mechanisms which influence operational energy efficiency. The data collected in the interview were part of the research related to case 1. Before the interview took place, a quantifiable data set on vessel movements and cargo carried for one specific feeder vessel chartered by the same operator was received from the operator, and analysed with respect to operational energy efficiency — as part of this research project. The preliminary results from this analysis were presented in writing to the managers before the interview took place, as well as in the course of the interview. The interview guide below is developed on the basis of the semistructured interview and further literature reviews, and can be used to interview managers in ship operating companies about operational energy efficiency. A Awareness and knowledge about operational energy efficiency

• Can you describe how energy efficiency is defined in your company? • Can you describe how energy efficiency is measured in your company? • Can you describe how energy efficiency is informed (e.g. CO 2 calculator) in your company? • Can you describe how energy efficiency is dealt with/specified by your customers?

B Cargo capacity utilization of feeders, including issues of customer demand, vessel scheduling and routing, port and sea interface.

C The chartering of feeder vessels and energy efficiency

• Does energy efficiency affect your company's strategy when chartering vessels? • Can you describe what types of contracts which are used when chartering feeders? • Can you describe how fuel consumption and energy efficiency is dealt with in the charter contracts? • How is SMT training and competences in respect of ‘Eco-driving’ and fuel savings included in chartering negotiations? • Would SMT training affect the competence level of the personnel on board in respect of ‘Eco-driving’ and fuel savings? • Can you describe how fuel consumption and possibly energy efficiency is monitored during the contract duration?

D The operation of feeder vessels: Speed orders, fuel consumption and time in ports

• Who in your organization (ashore and on board) decides a vessel's speed during a voyage and during a leg? • Which company-internal matters influence operational speed decisions? • Which external conditions influence operational speed decisions? • How often is the speed changed during a leg? • How is the ‘berthing window’ determined for each port? • What is the relationship between ‘berthing window’ and vessel speed and speed changes during a leg? • How is updated information on ‘berthing windows’ communicated to the vessel? • Is there something called an ‘optimal speed’ in your operations? If so, how is it determined? 1 Styhre, L. 2010. Capacity utilization in short sea shipping. PhD-thesis, Department of Technology Management and Economics, Chalmers University of Technology, Sweden.

Please cite this article as: Schøyen, H., & Bråthen, S., Measuring and improving operational energy efficiency in short sea container shipping, Research in Transportation Business & Management (2015), http://dx.doi.org/10.1016/j.rtbm.2015.10.004

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• How slow can a vessel sail technically, with respect to main engine and propulsion system operational conditions? • How can the operator influence turnaround time for one specific vessel in one specific port? Please give examples. • How do you determine the turnaround time for each port stay? • Do any of your vessels stay idle in port? If so, what are the possible reasons for staying idle? • Do you have a determined policy on how the auxiliary engines are operated in port? • Is any measure used to reduce the use of auxiliary engines in port, such as for example shore side electricity?

E Other issues Can you describe how energy efficient operations may affect safety and security in your business?

Appendix B. Questionnaire to the shipboard management team This questionnaire was used to collect evidence from officers on board a feeder vessel and was sometimes combined with informal talks on board. This evidence was part of the research related to case 2. Container port performance and transport energy efficiency from the shipboard management teams' perspective. Introduction: Present the research project and which phenomenon is being investigated. Activity: Observations and talks to officers onboard a container feeder calling at several Norwegian ports on its North Sea roundtrip.

Which ports are visited on the roundtrip? Are there ports where your vessel calls at more than one terminal, if so which ports and terminals? Is any of the ports in the roundtrip ‘greener’ than the others, for example by applying environmentally-differentiated harbour fees? Or by offering/requiring other measures?

The following statements describe various factors that contribute to make any container port/terminal efficient. To what degree do you think the following statements give accurate descriptions of the experiences your shipping line has with this port/terminal? Please use the 1–5 ranking, from strongly disagree to strongly agree for your answer. Please answer by setting a ring around one of the values. All information collected through this questionnaire will be strictly confidential.

Strongly Disagree Average Agree Strongly disagree agree 1. There is seldom congestion or unexpected waiting time before berthing or before starting loading/discharging in this port/terminal

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(continued) Strongly Disagree Average Agree Strongly disagree agree 2. This terminal has made a high level of investments in equipments, tools, service, etc. in providing facilities which are used specially by our shipping company 3. Our shipping line has made investments in equipment, tools, services, etc. at this terminal to make service quick and convenient for us 4. We are satisfied with container loading/discharging rate per hour at this terminal 5. The total stay of the vessel at berth is not very long 6. This terminal has the ability to handle large volumes of cargo 7. Personal contacts and relationships to terminal staff is key for good operations at this terminal 8. There is good early communication between port/terminal and our ship to allow for ‘Just-in-time’ operations when calling at this port 9. Our shipping line is discharging/loading only at daytime shifts (07–15 h) at this terminal 10. This port/terminal can be operated 24/7 for discharging/loading 11. Our shipping line has a balance in no. of loaded and discharged TEUs for this port 12. There are few empty containers loaded/discharged from our vessel at this terminal 13. We seldom experience off-hire (for example mechanical failures) on the ship-to-shore gantry/mobile cranes in this port 14. We seldom experience unexpected waiting time in access channels for this port. For example irregularities in pilotage, towage services, delays at sea locks, tidal windows, ice on the water, or other delays. 15. We frequently experience unexpected waiting times due by chance in this port. Weather circumstances, on route problems or unexpected waiting time at a bunkering site or port. 16. There is sufficient slack in our roundtrip sailing schedule, thus most delays we experience in this port do not cause delays elsewhere on the roundtrip

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Please cite this article as: Schøyen, H., & Bråthen, S., Measuring and improving operational energy efficiency in short sea container shipping, Research in Transportation Business & Management (2015), http://dx.doi.org/10.1016/j.rtbm.2015.10.004

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Vessel fuel consumption • What is the fuel type for ME and AE? • Do you use the same fuel type on the whole round-trip for each of the engines? • Is the fuel consumption of the vessel monitored quantitatively? How frequently? • How often do you receive speed order from the operator, and in which form is a speed order given? (E.g. ‘Full speed’, ‘Optimum speed’, ‘Eco speed’) • How and to which extent is it possible to ‘slow steam’ with this vessel? • How do vessel speed variations affect power consumption for this specific vessel? For example, to which extent is the daily fuel consumption reduced with an average speed reduction of 1 knots, 2 knots, 3 knots etc. Please give your opinion and experience of measures for more vessel fuel-efficient operations for this particular operation. Strongly Disagree Average Agree Strongly disagree agree Improved voyage planning. Optimum route. Software tools Shorter turnaround time in ports Reduced maximum speed of the vessel Limited number of port calls Better weather routing Good early communication with the next port in order to give notice of berth availability, thus enabling speed optimization Good early communication with the operator enabling speed optimization Optimum trim Optimum ballast More efficient autopilot to optimize the use of rudder Better hull and propeller maintenance (cleaning) More efficient waste heat recovery system

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Please cite this article as: Schøyen, H., & Bråthen, S., Measuring and improving operational energy efficiency in short sea container shipping, Research in Transportation Business & Management (2015), http://dx.doi.org/10.1016/j.rtbm.2015.10.004