Feb 24, 1999 - International Energy Agency and European Conference of Ministers of. Transport, PARIS, 24th ... focused on engine performance and vehicle design. ..... Meanwhile, efforts to improve vehicle utilisation are making the optimisation of ..... Transport in Europe: In Search of a Sustainable Course' Centrum voor.
A Logistical Perspective on the Fuel Efficiency of Road Freight Transport
Professor Alan C. McKinnon, School of Management Heriot-Watt University Edinburgh, UK
Report presented to the Workshop on ‘Improving Fuel Efficiency in Road Freight: The Role of Information Technologies’ organised by the International Energy Agency and European Conference of Ministers of Transport, PARIS, 24th February 1999.
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A Logistical Perspective on the Fuel Efficiency of Road Freight Transport Professor Alan C. McKinnon, School of Management, Heriot-Watt University, Edinburgh, UK ______________________________________________________________________ 1. Introduction For many years, research on fuel efficiency in the freight transport sector was narrowly focused on engine performance and vehicle design. This engineering-based research has yielded impressive results, with average kilometres per litre for new articulated vehicles increasing by around 20% since 1980 1. More recently technical improvements in fuel performance have been supplemented by a range of management initiatives designed to ensure that vehicles are operated in a fuel-efficient manner 2. Some of these measures, such as training programmes and incentive schemes have been directed at the driver, while others have made the purchase and maintenance of vehicles more sensitive to variations in fuel consumption 3. It has been estimated that a well designed fuel management programme can improve the fuel efficiency of a road haulage operation by a further 15-20% 4. A survey of 300 firms in the UK with a total of 3600 goods vehicles found that rigid and articulated trucks operated by the top 20% of companies ran, respectively, 20% and 8% further per litre of fuel consumed than the average 5. These fuel efficiency gains, however, have been more than offset by the growth in truck traffic. Between 1985 and 1995 the total annual distance travelled by trucks in EU countries increased by around 50% 6. The total amount of energy consumed in the road freight system has, therefore, been steadily rising. With concern mounting over the environmental effects of freight movement, particularly of related CO2 emissions, many new studies have been conducted during the 1990s on the underlying growth of truck traffic and the opportunities for restraining it 7. Much of this research has adopted a broader logistical perspective on fuel consumption in the road freight sector. It has looked beyond the traditional kilometres per litre measure of fuel efficiency to three other critical ratios which affect the energy-intensity of the freight transport system. These are: 1. Road tonne-kilometres : total tonne-kilometres - Modal Split As road transport accounts for over 90% of freight-related fuel consumption in most European countries, this ratio is expressed here in terms of the split between road and alternative modes. 2. Total tonne-kilometres : output - Transport-Intensity In this context, output can be defined in different ways. Several studies have expressed it in monetary terms, such as GDP or the level of retail sales, whereas others have preferred weight-based measures. Most of the discussion in this paper relates to the weight of goods produced and distributed.
3. Vehicle kilometres : tonne kilometres - Vehicle Utilisation. 2
This is influenced by three factors: the capacity of the vehicle (in weight and volume terms), the average payload carried on loaded trips and the proportion of vehiclekms travelled empty. Studies which have explored the options for restraining the growth of road freight traffic place differing emphasis on these three key ratios (Table 1). Some focus attention on a single ratio, whereas others have a broader remit. Pastowski 8, for example, regards increases in vehicle energy efficiency, improved capacity utilisation and modal shifts as ‘necessary but not sufficient to tackle the problems that will arise from a continuation of growth in freight transport activity’. The studies also vary in the level of quantification. Some construct future freight scenarios and forecast their likely impact on energy consumption. Table 2 presents the results of future energy projections for freight transport in the Netherlands, Germany and the UK based on business-as-usual and ‘green’ scenarios. Given international differences in modal split, the composition of the vehicle fleet and the structure of production and distribution systems, it would be unwise to extrapolate these forecasts to Europe as a whole. It is worth noting, however, that there are strong similarities between the various freight rationalisation measures being considered in different European countries. 2. Logistical Decision-making Framework It is important to consider the nature of the logistical decisions that firms would have to take to reduce their overall demand for road freight. Broadly speaking, there are four levels of logistical decision-making, affecting 9: 1. Logistic structures: determined by high-level strategic decisions affecting the numbers, locations and capacity of factories, warehouses and handling facilities. 2. Pattern of trading links: determined by commercial decisions on sourcing, subcontracting and distribution. These decisions establish the freight network linking a company’s premises to those of its trading partners. 3. Scheduling of product flow: decisions on the scheduling of production and distribution operations translate trading relationships into discrete freight flows. 4. Management of transport resources: within the framework defined by decisions at the previous three levels, transport managers still have discretion over the use of transport resources. A firm’s demand for road transport is the result of a complex interaction between decisions made at these different levels. The higher order decisions at levels 1 and 2, in which logistics managers often have only a minor say, determine the number of tonnekms generated, and hence transport intensity, while those made at levels 3 and 4, over which logistics managers have greater leverage, translate this required volume of freight movement into road vehicle-kms, and hence influence vehicle utilisation. The choice of transport mode can be influenced by decisions at all four levels.
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3. Modal Split Several of the studies identify modal shift as the most promising method of reducing energy consumption in the freight sector 10. When expressed in terms of kilo-joules per tonne-km, the specific primary energy consumption of road freight transport is 4.3 times higher than rail and 6.8 times greater than waterborne transport 11. Even when compared with the heaviest articulated vehicles, rail has double the fuel efficiency of road 12. A major transfer of freight to these alternative modes could, therefore, substantially reduce the overall energy-intensity of the freight transport system. This would effectively reverse the modal shift to road, which according to Schipper et al. 13 increased the total amount of energy consumed by freight transport in eight European countries by an average of 15% between 1972 and 1992. In France and West Germany it increased it by 27%. Other studies are more pessimistic about the potential contribution of a modal shift to energy conservation in the freight sector, for several reasons: 1. In those countries where the modal split is heavily skewed towards road, total energy consumption would be relatively insensitive to even quite large proportional increases in rail or water-based transport. Whitelegg 14, for instance, assesses the effect, in the UK, of a large modal shift from road to rail and water (50-90% of all motorway truck traffic transferred to rail) on future road freight volumes and concludes that, while such a shift would be feasible and environmentally desirable, it would not on its own adequately address the problem of road freight traffic growth. In the UK, where the rail network handles only 7% of total tonne-kms, doubling the amount of freight carried by rail would offset only around 4 years growth of freight movement (in tonne-kms) on the road network 15. It would also yield a smaller energy saving than more marginal improvements in the utilisation of road freight capacity, such as a 10% increase in average payload weight or a reduction in the proportion of lorry kilometres run empty from 29% to 25% (Figure 1). 2. As the accessibility of the alternative modal networks is relatively low, road feeder movements are often required at one or both ends of the trunk haul and the routing of the flows made more circuitous. The integration of rail and water-based trunk hauls into intermodal services therefore reduces their relative energy advantage. Indeed, a comparative study of the energy requirements of road and intermodal transport concluded that they were broadly similar 16. 3. In capturing traffic from road, particularly manufactured products of relatively low density and high time-sensitivity, the utilisation of railfreight capacity would be likely to decline, with consequent reductions in average fuel efficiency 17. 4. Doubts have been expressed about the ability of the operators of rail and waterbased services to improve their competitiveness and thus secure a larger share of the freight market. Even if the most optimistic projections of a freight modal shift were to materialise, road would remain by the far the dominant mode across the EU. The vast majority of road freight journeys are short and between premises that are not rail-connected. It is important, therefore, to investigate the opportunities for rationalising the road freight 4
system. This would involve reducing transport intensity and / or improving vehicle utilisation. 4. Transport Intensity The transport intensity of a supply chain is determined both by the number of links and their average length (Figure 2). The number of links can be crudely measured by dividing the tonnes-lifted statistic by the actual weight of goods produced or consumed (i.e. at either end of the supply chain). This index, known as the handling factor, effectively measures the number of separate freight journeys that a consignment makes in moving from raw material source to final point of sale. As limited data are available on the weight of products produced and consumed, handling factor calculations are inevitably highly approximate. An attempt was made in the EU Redefine project to analyse the trend in handling factors in five European countries (France, Germany, the Netherlands, Sweden and the UK) 18. This suggested that over the period 1980-1995 handling factors had fluctuated and shown no consistent trend. Some industrial trends are likely to have been increasing the number of links in the supply chain. In some manufacturing sectors, for instance, a process of vertical disintegration has been occurring, with non-core activities increasingly subcontracted to outside agencies. Extra tiers have also been added to some supply chains in an effort to rationalise inbound logistics and to permit local customisation of products. In the retail sector, on the other hand, distribution channels have become more streamlined with products passing through fewer stockholding points en route to shop. The counteracting effects of these processes on the structure of the supply chain may partly explain the absence of any clear trend in handling factor values. In contrast, the average length of links in the supply chain, known as the average length of haul, has been rising steadily, in most countries, for over past forty years. Within Europe it has been increasing at an average rate of 1.5-2.0% per annum 19. Increasing haul lengths have been the main cause of road freight growth. Over the past thirty years, they have been responsible for approximately two-thirds of the increase in road tonne-kms within Europe. This increase in average length of haul has been attributed to several developments, mainly the expansion of market areas, the wider sourcing of supplies, the centralisation of production and warehousing and the development of hub-satellite systems, principally by parcel carriers. Empirical evidence, in the form of surveys and case studies, has accumulated to confirm the existence of these trends 20. 4. 1 Reducing transport intensity At a macro-economic level, transport intensity can be defined as the ratio of road freight tonne-kms to the level of economic activity measured by GDP. This ratio has been relatively stable for several decades, suggesting that it may be difficult to ‘decouple’ these two variables. This decoupling process would entail reducing the number and/or length of links in the supply chain by means of what Bleijenberg calls ‘spatio-economic changes’ 21. The number of links in the chain could be cut by increasing the degree of vertical integration in manufacturing, expanding the range of activities carried out on a single site. In some sectors, this would involve reversing the process of ‘vertical disintegration’ and discouraging the customisation of products at a separate location. Distribution channels might be further streamlined to reduce the number of 5
intermediate storage and handling points. In countries such as the UK, however, this streamlining process is well advanced leaving little opportunity for further rationalisation. Moreover, eliminating from the supply chain nodes at which loads are consolidated could be counterproductive as it might reduce vehicle load factors. In theory it would be possible to reduce the average length of haul or at least moderate its rate of increase by reconfiguring production and distribution systems, sourcing products from local suppliers and finding shorter routes between collection and delivery points. (i) Reconfiguring production and distribution systems: These systems, which are shaped by decisions at level 1 in the logistics management hierarchy, are relatively fixed in the short- to medium-term. It would be very difficult to reverse the geographical concentration of production, given the magnitude of the scale economies that firms have achieved. The logistical cost trade-offs that firms make between transport, inventory and warehousing costs are also very robust. This was confirmed by a computer simulation exercise which modelled the effect of increasing road transport costs on the distribution of products of differing value density 22. This analysis established the transport cost levels at which firms would have an economic incentive to decentralise their stockholding/distribution operations. It found that even in the case of products with a relatively low value density, transport costs would have to rise by over 100% to make it economically beneficial to move to a more decentralised structure. It is likely too that this modelling exercise will have under-estimated the transport cost threshold as it failed to incorporate all the benefits that firms claim to derive from centralisation and took no account of restructuring costs. As road transport costs represent only around 1.6% of sales revenue for the average European company 23 and as fuel accounts for only 20-30% of these costs, much strategic decision-making is relatively insensitive to variations in fuel prices. This may partly explain why Schipper et al.24 could find ‘no correlation between change in trucking fuel price and change in trucking modal intensity between 1973 and 1992’. This casts doubt on the recommendation by the Royal Commission on Environmental Pollution 25 that a large fuel price increase be used to dampen freight traffic growth, predicting that this will ‘modify manufacturing and distribution patterns over a number of years by shortening the average length of trips’. The report does not elaborate on the nature of this restructuring process or the level to which fuel prices might ultimately have to be raised to achieve the RCEP’s goal or halving the growth in freight tonne-kms in the UK from 20% to 10% per decade. The use of IT in inventory management can help to ease the pressure on firms to centralise inventory, which often has the effect of increasing lengths of haul. As Christopher 26 explains, ‘Whilst the logic of centralisation is sound, it is becoming increasingly recognised that there may be even greater gains to be had by not physically centralising the inventory but rather locating it strategically near the customer or point of production by managing and controlling it centrally. This is the idea of ‘virtual’ or ‘electronic’ inventory. The idea is that by the use of information, the organisation can achieve the same stock rotation that it would achieve through centralisation while retaining greater flexibility by localising it.’ (ii) Pattern of sourcing: This pattern, which is shaped by decisions at level 2 in the management hierarchy, is becoming more transport-intensive through time, as products are sourced and marketed over wider areas. The geographical expansion of trade areas appears so fundamental to the process of economic development, that it is difficult to 6
see how it can be contained. In many industries, factor cost differentials are very wide relative to road transport costs, making it economic to move products long distances for intermediate processing that may only add marginally to the product’s value. For most product groups, only a very steep increase in transport costs and/or transit times would be likely to offset these production cost differentials and promote a return to more localised sourcing, as advocated by Holzafpel, Strutyniski, Whitelegg and Pastowski 27. Holzafpel favours the development of ‘regional supply structures’ within which firms would source as much as possible from local suppliers. Using data, collected by Boge on the ‘transport logistics’ of a pot of strawberry yogurt 28, he calculates that if, in the production and distribution of this product, the nearest suppliers had been used, total lorry-kms could have been reduced by 67%. Strutyniski has shown how rationalisation of the supply networks of large car assembly plants, with greater ‘vertical integration’ at the regional level, could reduce freight transport requirements by 70%. He concedes, however, that large increases in transport costs (at least 5-fold) would be needed to induce this process of rationalisation. Whitelegg also argues that to achieve long term ‘transport stabilisation’ it will be necessary to rationalise the road freight system. Drawing empirical support mainly from the German studies, he assumes that ‘50% of the vehicle kilometres can be eliminated by removing geographical illogicalities in the distribution chain and by substituting ‘near’ for ‘far’ in sourcing decisions.’ His ‘strong sustainability’ scenario for freight transport would reduce fuel consumption in the UK by around 60% by 2025. (iii) Vehicle Routing: The efficiency with which vehicles are routed around collection and delivery points influences the tonne-kilometre figure. It has been estimated that the use of computerised vehicle routing and scheduling packages can, on average, reduce the distance travelled by around 5-10%, though instances of 20% distance savings are quoted in the literature 29. Minimising the distance travelled, however, need not minimise fuel consumption, as the shortest route may involve traversing hilly terrain, urban areas or congested sections of the road network. While, in theory, it would be possible for users of routing software to calibrate routes along which their vehicles regularly travel in terms of fuel consumption, no examples have been found of firms actually doing this in practice. The real costs of CVRS have been falling while its functionality has been expanding. New versions of the software can accommodate the return loading of vehicles and interface more effectively with other distribution packages. The development of in-cab mobile data communications now allows firms to re-route vehicles dynamically while they are on the road network in response to changing commercial opportunities and traffic conditions 30. Meanwhile, efforts to improve vehicle utilisation are making the optimisation of vehicle routing much more complex. Increasing numbers of firms, for example, are abandoning fixed service areas around their depots allowing vehicles based at one depot to intrude into what was previously the territory of another. This introduces greater flexibility into the delivery operation and makes for more effective use of vehicle capacity across the entire distribution system. In some sectors, ‘primary distribution’ (from factory to distribution centre (DC)) is being integrated with secondary distribution (from DC to shop) to create ‘network systems. The problem of optimising vehicle movements within these systems is an order of magnitude more complex than the traditional routing problem for a single depot. This may require the 7
application of artificial intelligence in the form of genetic algorithms which can ‘evolve’ to produce better solutions than those attainable by more conventional operational research techniques. Indeed, the use of genetic algorithms has the potential to transform the management of road freight operations, significantly increasing levels of vehicle utilisation and reducing transport costs 31. 5. Vehicle Utilisation Vehicle utilisation is determined by three factors the maximum carrying capacity of the vehicles (in terms of weight and volume), the average weight and size of consignments and the proportion of truck kilometres run empty (Figure 2). The utilisation of vehicle fleets can be measured in different ways, each giving a different impression of transport efficiency. 5.1 Measures of Utilisation Tonne-kilometre utilisation: One index which portrays road freight management in a very favourable light is tonnekms per vehicle per annum 32. On the basis of this measure, the average amount of ‘work’ done by lorries in the UK, for example, increased by 72% between 1986 and 1996 33. This was mainly achieved in two ways: a) Running of vehicles over longer periods, often double- or treble-shifting them during the 24 hour cycle. This increase in the intensity with vehicles are used can have both a positive and negative effect on energy consumption. On the positive side, it wears the trucks out more quickly and accelerates the introduction of new, more fuel efficient and cleaner vehicles. On the negative side, by reducing the real cost of road freight transport, it can promote the processes of centralisation and wider sourcing which generate additional freight movement. b) Increasing average payload weight. Official statistics for several European countries indicate that average payload weight has been increasing 34. This, coupled in some countries with a slight reduction in empty running, has caused vehicle-kilometres to grow at a slower rate than tonne-kilometres. In the UK 35, for example, vehicle-kms increased by 22% between 1986 and 1996, by comparison with a 39% growth in tonne-kms (for vehicles with gross weights over 3.5 tonnes). Baum 36 observed a similar trend in Germany and argued that it could be reinforced to achieve a 20% improvement in truck utilisation between 1991 and 2011. Average payload weights have increased despite the widespread application of the just-in-time (JIT) principle. Bleijenberg37 argues that its ‘more stringent requirements have led to an decrease in the average load factor and an increase in the frequency of hauls. As a consequence, a greater number of vehicle-kms are needed for the same transport volume in tonne-kms.’ While this may have happened in particular sectors, there is no evidence of JIT causing a net reduction in average payload weight across the truck fleet as a whole in countries such as UK, the Netherlands and Sweden (Figure 3). Many of the firms supplying or receiving products on a JIT basis have taken measures which, directly or indirectly, have 8
minimised the negative effect of JIT on vehicle utilisation. These include the insertion of an additional consolidation point into the supply chain, the ‘milkround’ collection of orders, the single-sourcing of supplies and the use of parcel networks. Nissan, for example, employs the logistics firm Ryder in the UK to collect components from suppliers and consolidate them at a ‘cross-dock’ for ‘line-haul’ delivery to its assembly plant. It has been estimated that if these suppliers delivered directly to the plant, the inbound vehicle-kilometres would be around 80% higher. Furthermore, as larger, more fuel efficient vehicles can be used for supplier collection and line-haul operations than would be possible with JIT delivery direct from supplier, fuel savings are proportionally greater than this reduction in vehiclekms. Altogether around 870,000 litres of fuel are saved annually, valued at £427,000 38. Workgroep 2000 and Baum 39, nevertheless, ague that to improve vehicle utilisation it will be necessary to relax JIT requirements. The former study concludes that ‘the transport customer will, therefore, have to look for other solutions in order to maintain the competitiveness of production flexibility’. Load Factor If one measures utilisation by the ratio of actual tonne-kms handled to the capacity in the road freight system to carry tonne-kms, a different picture emerges. According to UK government statistics, the vehicle load factor (ie. the ‘ratio of the actual goods moved to the maximum tonne-kms achievable if the vehicles, whenever loaded, were loaded to their maximum carrying capacity’) remained fairly stable at around 63% between 1986 and 1996 40. This too, however, is only a partial measure of vehicle utilisation. As it is an exclusively weight-based measure it takes no account of the use of vehicle space or deck-area or the proportion of vehicle-kms run empty. Space-utilisation: Many low-density products fill the available vehicle space (or ‘cube out’) long before the maximum permitted weight is reached. In sectors characterised by low-density products, weight-based lading factors tend to under-estimate the true level of utilisation. Where there are tight limits on the stacking height of the product, loading is usually constrained much more by the available deck-area than by the cubic capacity. This deck area can be covered with pallets stacked to a height of 1.5 metres, leaving a further 2 metres of wasted space above them. A.T. Kearney has calculated that ‘there are 15% extra grocery trucks on European roads as a result of failure to optimise available height’ 41. Very little research has been done on the space utilisation of vehicles and few attempts made to collect volumetric data on road freight flows. In a study conducted in the Netherlands and Sweden, Samuelson and Tilanus 42 asked a panel of industry experts to estimate the average utilisation of lorries with reference, inter alia, to a series in spacerelated indices (Figure 4). This revealed that cube utilisation was typically very low at around 28%. On average, however, just over 80% of deck-area would be occupied and 70% of the available pallet positions filled. It was therefore mainly in the vertical 9
dimension that space was being wasted, with average load heights reaching only 47% of the maximum. Empty running: Between 1980 and 1996, the proportion of truck-kms run empty in the UK declined from approximately 33% to 29% (Figure 5). Had the empty running proportion remained at its 1980 level, trucks (with a gross weight of over 3.5 tonnes) would have run an additional 1.2 billion kilometres on Britain’s roads and consumed roughly 400 million more litres of fuel. An analysis of the possible reasons for this trend identified five contributory factors: the lengthening of truck journeys, an increase in the number of drops per trip, the expansion of load-matching services, a growth in the reverse flow of packaging material / handling equipment and greater efforts by shippers to obtain return loads 43. In a recent survey, forty-two freight transport specialists predicted that, on average, empty running in the UK will decline from 28% of vehicle activity in 1996 to 25% by 2000 and 24% by 2005 44. It is generally acknowledged, however, there will remain a substantial proportion of ‘structural’ empty running which will be very difficult to eliminate. 5.2 Improving Vehicle Utilisation This section reviews a broad range of measures that companies can adopt to improve the utilisation of vehicle capacity and thereby fuel-efficiency expressed on a litres per tonne-kilometre basis. 5.2.1 Increasing the Level of Return-Loading. The British supermarket chain Tesco has demonstrated how backloading initiatives can improve energy efficiency. It has implemented both ‘supplier collection’ and ‘onward delivery’ schemes. In the case of supplier collection, a returning shop delivery vehicle collects goods from a supplier’s premises and carries them to the retailer’s DC. Onward delivery occurs where a supplier’s vehicle offloads goods at the DC and backloads with supplies destined for one of the retailer’s shops. This is delivered on the way back to the factory, usually with minimal deviation from the direct route. These schemes have required modest conversions to both the retailer’s and suppliers’ vehicles. The cost of these conversions has been greatly exceeded by the resulting transport cost savings. Tesco has estimated that over a five year period, its supplier collection scheme increased the annual volume of goods carried per trailer by 26.5% and the average annual distance travelled per vehicle by 19.9%. Over this period, there was a total saving in vehicle-kms of around 4.8 million, cutting fuel expenditure by £750,000 and CO2 emissions by 23,000 tonnes 45. Advances in IT and telecommunications are creating major new opportunities for backloading 46: •
Electronic load matching: Agencies providing electronic clearing house services for return loads are increasing their share of the freight market, though from a very low base
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Electronic client validation: One of the deterrents to backloading with third-party traffic has been uncertainty about the client’s financial position. On-line credit references linked to computerised load matching help to overcome this constraint.
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Electronic monitoring of vehicle activity: In-cab recording devices, supplementing conventional tachographs, provide operators with a detailed break-down of vehicle performance and activity. This facilitates analysis of vehicle utilisation across the fleet and can help identify backloading opportunities.
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Vehicle tracking / in-cab mobile data communication: As outlined above, this allows vehicle schedules and routes to be replanned in real-time while the vehicle is on the road. Operators are then able to exploit backloading and load consolidation opportunities that arise at short notice. Communication with the vehicle and information on its positioning gives clients greater confidence in ‘return load’ services. It also helps the operator to co-ordinate more effectively outbound and return movement.
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Creation of a virtual market for road haulage services: The logical extension of these developments will be an real-time electronic trading network for road haulage capacity. Electronic brokerages are likely to emerge in the general road haulage market within which vehicle capacity will be traded over differing time-scales. This is an example of what Clarke calls ‘virtual logistics’ 47.
Return loading will, nevertheless, continue to be subject to other constraints, such as: International and inter-regional imbalances in trade flows: These imbalances, which are reflected both in the volume and composition of freight traffic, impose a structural limit on backloading. This often forces carriers to ‘triangulate’, i.e. routing vehicles around several countries or regions in order to achieve more balanced loading. Management structure: It is likely that many return-loading opportunities are missed because of a lack of co-ordination both between purchasing and transport managers and between firms at different levels in the supply chain. Incompatibility of vehicles and products: The incompatibility of upstream and downstream flows can severely limit the scope for backhaulage, particularly for firms in process industries. Some firms, however, now use ‘dual-purpose’ trailers to increase the potential for backloading 48. Delays at collection and delivery points: Backloading is often inhibited by the unreliability of delivery schedules. Where scheduling is tight, there is little time to wait for a return load or to deviate from the return route to collect one. 5.2.2 Adoption of More Transport-efficient Order Cycles. The nature of the order-fulfilment process can have a significant impact on the energy efficiency of the transport operation. There are two ways in which this process can be modified to allow firms to increase the degree of load consolidation and hence reduce traffic levels and energy consumption: Adoption of the Nominated Day Delivery System: Firms operating this system achieve much higher levels of transport efficiency by encouraging customers to adhere to a ordering and delivery timetable. Customers are informed that a vehicle will be visiting 11
their area on a ‘nominated’ day and that to receive a delivery on that day, they must submit their order a certain period in advance. The advertised order lead time is thus conditional on the customer complying with the order schedule. By concentrating deliveries in particular areas on particular days, suppliers can achieve higher levels of load consolidation, drop density and vehicle utilisation. This practice is often resisted by sales and marketing staff, however, who fear that the resulting loss of customer service might jeopardise sales. Abandoning the Monthly Payment Cycle: Many companies invoice their customers at the end of each month, giving them an incentive to order at the start of the month and thereby obtain a longer period of interest-free credit. This can induce wide monthly fluctuations in freight traffic levels, making it difficult for firms to manage their vehicle capacity efficiently. By abandoning the monthly payment cycle and moving to a system of ‘rolling credit’, which computerised financial accounting systems now facilitate, firms can increase the average level of vehicle loading and reduce traffic levels. One British manufacturer has estimated that this measure could allow it to reduce truck-kms by 10%. 5.2.3 Relaxing the Requirement for Dedicated Delivery. During the 1980s and early 1990s, there was a sharp increase in the proportion of thirdparty haulage services provided on a dedicated basis for individual clients. Dedication denies contractors the opportunity to perform their traditional ‘groupage’ role and, as a result, carries a vehicle utilisation penalty. There is, nevertheless, increasing evidence of major users of dedicated services granting contractors the freedom to carry other firms’ traffic in their vehicles, with the additional revenue split between contractor and client. There has also been a growth of shared user (or ‘network’) services in recent years 49. Several company-sponsored studies in the UK of the potential benefits of shared-user services in the automotive, consumer electrical and clothing sectors, in each case replacing four or five separate dedicated services, have indicated that this can reduce transport costs and vehicle-kms by around 20%. 5.2.4
Use of Vehicles with Greater Carrying Capacity
A significant proportion of loads are weight- or volume-constrained. Increasing maximum lorry weights and dimensions permits greater load consolidation and a reduction in vehicle kilometres. The UK government 50 estimated that raising the maximum lorry weight limit from 38 tonnes to 44 tonnes would cut total lorry kms on British roads by approximately 6%. Truck dimensions are clearly constrained by the geometry of road layouts, bridge heights, reception facilities at industrial and retail premises as well as public opinion. The use of drawbar-trailer combinations and double-deck trailers, however, can allow firms to increase cubic capacity utilisation within these various constraints. There has been a steep increase in the number of companies operating double-deck trailers in recent years, particularly in the UK. This can be attributed to a number of factors, including improvements in double-deck design and performance, a decline in the average density and ‘stackability’ of loads and real increases in vehicle operating costs 51. A survey of firms operating double-deck trailers found that on average this had enabled them to reduce vehicle-kms by 24% 52.
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One must exercise caution, however, in advocating increases in truck carrying capacity as a means of reducing energy consumption in the freight sector. There is a danger that the resulting savings in road transport costs per unit will encourage a transfer of freight traffic from other, more energy-efficient modes and / or facilitate the development of more transport-intensive production and distribution systems. Vehicles can also be redesigned in other ways to permit greater load consolidation. The compartmentalisation of lorries has enabled grocery retailers and their contractors to combine the movement of products at different temperatures on a single journey. This form of ‘composite distribution’ has, for example, enabled the UK retailer Safeway to reduce the average number of vehicle trips required to deliver 1000 cases from five in 1985 to one in 1995 53. There is scope for greater use of multi-compartment / multifunctional vehicles to increase the degree of load consolidation. The consolidation of loads in larger and heavier vehicles also has a more direct on fuel efficiency as the number of tonne-kms moved per litre increases with the gross vehicle weight 54 (Table 3). 5.2.5
Use of More Space-Efficient Handling Systems and Packaging.
The efficiency with which the cubic capacity of a vehicle is used partly depends on the nature of the packaging and handling equipment. Companies must reconcile the desire to maximise vehicle fill with the need to protect products from damage in transit and to minimise handling costs. The following examples, however, illustrate the effects that handling / packaging changes can have on the transport operation. • Choice of loading method: A large mail order company managed to improve vehicle cube utilisation and cut vehicle-kms by 6% by loading parcels loose rather than in bags. • Nature of the handling system: By using wooden pallets rather than roll cages a grocery retailer can load 15-20% more cases onto a conventional trailer. • Stacking height: One fast moving consumer goods manufacturer has calculated that by increasing pallet height from 1.7 to 2.1 metres it could reduce its road freight demand by 1.6 million truck-km per annum. As the pallet slots in most warehouses offer only 1.7-1.8 metre clearance, however, such a change would require reconfiguration of racking systems. • Shape and dimensions of product packaging: By marginally redesigning its packaging, a printer manufacture was able to save around 60,000 vehicle-kms per annum. 6. Supply Chain Initiatives The previous section quoted numerous examples of individual firms rationalising their road freight operations. The efficiency of a firm’s transport operation is, however, severely constrained by the requirements of suppliers, distributors and customers above and below it in the supply chain. With the development of supply chain management and efficient consumer response (ECR), firms at different levels in the supply chain have been trying to co-ordinate their logistical activities, primarily with the goal of minimising inventory 55. The aim is now to exploit this closer supply chain cooperation to achieve better utilisation of transport capacity and thereby reduce the energy-intensity of distribution operations. 13
Collaboration between companies across the supply chain has traditionally been inhibited by the adversarial nature of the trading relationships, a mutual fear that the benefits of any joint initiative would not be fairly distributed and uncertainty about each company’s current level of transport efficiency. A supply chain initiative in the UK has attempted to overcome these problems. It was based in the frozen-food sector, where refrigeration increases transport-related energy consumption by roughly 20%. This was an industry-led initiative organised by the Cold Storage and Distribution Federation with financial support from the UK government as part of its Energy Efficiency Best Practice Programme 56. 6.1 Benchmarking the Energy-Efficiency of Road Freight Transport Operations The refrigerated transport operations of eleven firms were closely monitored over a 48 hour period to measure vehicle utilisation and fuel efficiency against a standard set of key performance indicators (KPIs). The survey covered a total of 1300 trailers which travelled half a million kilometres on 3000 trips during the two day period. The results were aggregated to provide average measures of utilisation and efficiency and enabled the participating companies to benchmark their operations. Energy-intensity was measured in terms of the amount of fuel consumed in moving one pallet-load of frozen food one kilometre 57. Figure 6 shows how this index varied across the eleven companies participating in the audit. It ranged from 45.4 to 16.7 millilitres per palletkilometre, and averaged 32.1. The differentials were much wider for retailer-controlled operations (R1-7) than for manufacturer-controlled operations (M1-4). Much of the disparity was due to differences in the size and weight of trailers and the nature of the distribution operation. Insufficient data were collected during the audit to control for this variability. It is likely, however, that even if allowance were made for these differences, there would remain a significant variation in energy efficiency. If all the companies currently recording energy-intensity indices below the mean were able to achieve this average performance, 1.3 million litres of fuel could be saved on an annual basis. The detailed results were also presented at workshops attended both by the participating firms and other companies involved in the distribution of frozen food. This stimulated wide discussion and created a forum within which firms could exchange ideas and explore opportunities for collaboration. According to the trade association which organised these feedback sessions, approximately 15 inter-company initiatives have so far emerged from the discussions involving mainly backloading, delivery rescheduling and the consolidation of deliveries to retailers’ distribution centres. 6.2 Scheduling of Freight Movement across the Supply Chain. Another important finding to emerge from this research was that the refrigerated vehicles spent only around 25% of their time running on the road and that much of this transit time occurred during periods of heavy traffic flow on the road network. This will have reduced average speeds and exposed vehicles to congestion-related delays. Much of the idle time was between 2000 and 0400 hours. This is confirmed by road traffic surveys which indicate that in the UK only around 17% of truck-kms are run between 2000 and 0600 58. By rescheduling trips to off-peak periods when traffic is 14
relatively free-flowing, firms could reduce the energy-intensity of their distribution operations both directly through running vehicles at more fuel-efficient speeds and indirectly by enhancing the reliability of the delivery operations, making it easier to plan backloads and more complex multi-leg journeys. The magnitude of the direct savings is indicated by the experience of a dairy company in London which managed to improve the fuel efficiency of its delivery operations by 13% by switching from daytime to night deliveries 59. Increasing traffic congestion will give companies across the supply chain an greater incentive to reschedule vehicle movements to avoid peak periods. The timing of deliveries is currently constrained by the scheduling of production, warehousing and retailing operations and by working practices within the industry. Relaxing these constraints will require close co-operation by firms at different levels in the supply chain. The potential benefits in fuel efficiency could be very significant as it has been estimated that, in the case of a 40 tonne articulated lorry, making ‘two stops per kilometre leads to an increase of fuel consumption by roughly a factor of 3’ 60. 7. Conclusion Technical and managerial improvements in the fuel efficiency of road freight transport have not been able to keep pace with the rapid growth of freight traffic. As a result, total energy consumption in the road freight sector has been steadily rising. This paper has examined the opportunities for slowing, and possibly reversing, the growth of truck traffic by reducing three critical ratios: road’s share of total freight movement (the modal split), transport intensity and vehicle utilisation. The rationalisation of road freight transport has been the subject of numerous studies during the 1990s. These have varied in the relative emphasis placed on the three key ratios and on the measures that would be required to effect the desired changes in these indices. They suggest, however, that a concerted action to promote alternative modes, encourage more localised sourcing and raise vehicle load factors could yield substantial savings in vehicle-kms and fuel. The most promising measures are likely to be those targeted on vehicle utilisation, as they offer the potential of cutting costs as well as reducing environmental impact. Despite an increase in average payload weight, vehicle load factors have been relative stable and, in some countries, slightly declined. The paper has outlined many ways in which companies can improve vehicle fill and shown how 10-20% reductions in vehicle-kms can accrue from individual measures. Many of these measures involve the use of more advanced IT systems, particularly in support of vehicle routing and scheduling operations and return loading. Efforts to economise on road freight transport are often inhibited, however, in two respects: •
by decisions made at a higher strategic level within the corporate hierarchy where the objectives of marketing and production are typically given priority and can increase the overall transport-intensity of the business. Future increases in transport costs, tightening environmental controls and worsening traffic congestion will help to redress the balance and force a reassessment of logistical options.
15
•
by the activities of a firm’s customers, distributors and suppliers with which its transport operation must interface. Major reductions in the energy-intensity of logistical operations will require close co-operation by firms at different levels in the supply chain. Recent experience suggests that there is growing enthusiasm, particularly among the larger companies, for wider transport-optimisation initiatives.
16
References: 1. International Road Union (1997) ‘Driving Towards Sustainable Development’ Geneva. 2. Freight Transport Association (1992) ‘Fuel Management Guide’ Tunbridge Wells. 3. Department of the Environment (1995) ‘Energy Savings through Improved Driver Training’ Case Study 311, Energy Efficiency Best Practice Programme, ETSU, Harwell; McKinnon, A., Stirling,I and Kirkhope,J. (1993) ‘Improving the Fuel Efficiency of Road Haulage.’ International Journal of Physical Distribution and Logistics Management, vol.23, no.9 4. Holman, C. (1996) ‘The Greening of Freight Transport in Europe’ European Federation of Transport and Environment (T&E) , Report 96/12, Brussels. 5. Department of the Environment (1996) ‘Fuel Consumption in Freight Haulage Fleets’ Guide 59, Energy Efficiency Best Practice Programme, 1996. 6. Department of the Environment, Transport and the Regions (1998) ‘Transport Statistics Great Britain, 1998 Edition’ The Stationery Office, London. 7. Baum,H. (1994) ‘Desynchronization of Economic Growth and Transport Development in Europe.’ University of Cologne; Bleijenberg, A. (1996) ‘Freight Transport in Europe: In Search of a Sustainable Course’ Centrum voor Energiebesparing en schone technologie (CE), Delft: CE, TLN and KNV ‘Taking the Helm: On the Road to Cleaner Transport’ Report of the Transport Industry, Environment and Economics Project, Delft, 1996; DIW, ifeu, IVA/HACON (1994) ‘Reduction of Air Pollution and Noise from Long Distance Freight Transport by the Year 2010’ Research project no. 104 04 962, Federal Environment Agency (Umweltbundesamt), Berlin; Hey,C. et al. (1992) ‘Dead End Road’ Eures / Greenpeace, Freiburg; Holman, C. (1996), op.cit.; Holzapfel,H. (1995) ‘Potential Focus of Regional Economic Co-operation to Reduce Goods Transport’ World Transport Problems and Practice, vol.1 no.2; International Road Union (1997) op.cit.; McKinnon, A.C. (1996) ‘Freight Distribution and Logistics: Fuel Use and Potential Savings.’ ETSU, Harwell; Pastowski, A. (1997) ‘Decoupling Economic Development and Freight for Reducing its Negative Impacts’ Wupperthal paper no. 78, Wupperthal Institute for Climate, Environment and Energy, 1997; Plowden,S. and Buchan,K. ‘A New Framework for Freight Transport’ Civic Trust, London, 1995; Royal Commission on Environmental Pollution (RCEP) (1994) ‘Transport and the Environment’ HMSO London; Schipper, L., Scholl, L. and Price, L. (1997) ‘Energy Use and Carbon Emissions from Freight in 10 Industrialised Countries: An Analysis of Trends From 1973 to 1992.’ Transportation Research Part D, 2, 1.; Strutyniski,P. (1994) ‘Reduction of Freight Transport Through Lean Production.’ World Transport Problems and Practice, vol.1 no.1; TNO Institute of Spatial Organisation (1992) ‘EC Policy Measures Aiming at Reducing CO2 Emissions in the Transport Sector.’ Report for the European Commission (DGXI), Delft; UK Roundtable on Sustainable Development (1997) ‘Making Connections’ London; Werkgroep 2000 (1993) ‘A New Course in Freight Transport’ Amersfoort, Netherlands; Whitelegg,J. (1995) ‘Freight Transport, Logistics and Sustainable Development.’ World Wide Fund for Nature, London. 8. Pastowski (1998) op.cit. 17
9. McKinnon, A.C. and Woodburn, A. "Logistical Restructuring and Freight Traffic Growth: An Empirical Assessment" Transportation, 23, 2, 1996 10. Baum, (1994) (1994), op.cit.
Plowden and Buchan (1995), RCEP (1994) ,Workgroep 2000
11. RCEP (1994), op. cit. 12. McKinnon (1996) op.cit. 13. Schipper et al. (1997) op.cit. 14. Whitelegg (1995) op.cit. 15. Department of the Environment, Transport and the Regions (1998) op.cit. 16. Batelle Institute (1982) ‘Comparative Study of the Energy Requirements of Road Transport and Various Combined Transportation Techniques.’ Geneva. 17. National Economic Research Associates (1997) ‘The Potential for Rail Freight’ Office of the Rail Regulator, London; TNO-INRO (1998) ‘Eufranet Survey Report: Inventorisation of Customer Needs of Freight Rail in Europe’ Delft. 18. Netherlands Economic Institute, Heriot-Watt University, TFK and Service Economiques et Statistique (1997) ‘Analysis of Collected Data and Selection of Goods Flows’ Deliverables 1 and 2, REDEFINE project, European Commission, Brussels. 19. ECMT (1998) ‘Trends in the Transport Sector, 1970 - 1996’ OECD, Paris. 20. e.g. Cooper, J., Peters, M. and Bence, V. (1995) ‘Supply Chain Dynamics: A Study of Six Industry Sectors’ Cranfield School of Management Working Paper 1/95, Cranfield University; McKinnon, A.C. (1998) ‘Logistical Restructuring, Road Freight Traffic Growth and the Environment’ in D.Banister (ed.),‘Transport Policy and the Environment’ Spon, London. 21. Bleijenberg (1996) op.cit. 22. McKinnon (1998) op.cit. 23. Touche Ross (1995) ‘European Logistics Comparative Costs 1995’ Institute of Logistics / European Logistics Association, Corby. 24. Schipper et al. (1997) op.cit. 25. RCEP (1994) op.cit. 26. Christopher, M.C. (1998) ‘Logistics and Supply Chain Management’ Financial Times Management, London. 27. Holzapel (1995), Strutyniski (1994), Whitelegg (1995) and Pastowski (1997) op.cit. 18
28. Boge,S. (1994) ‘The Well Travelled Yogurt Pot: Lessons for New Freight Transport Policies and Regional Production.’ World Transport Problems and Practice, vol.1 no.1. 29. Eibl,P.G. ‘Computerised Vehicle Routeing and Scheduling in Road Transport.’ Avebury, 1996; Eibl,P.G., Mackenzie,R. and Kidner,D.B. (1994) ‘Vehicle Routeing and Scheduling in the Brewing Industry: A Case Study.’ International Journal of Physical Distribution and Logistics Management, 24, 6; Ball,F. and Bliss,D.H. (1993) ‘Energy Conservation in Road Transport Operations.’ Proceedings of the Chartered Institute of Transport, 2, 1, 1993. 30. Dodgson,J. et al. ‘Motors or Modems’ Report for the RAC by NERA, London. 31. Berry, L.M. et al. (1998) ‘Genetic Algorithms in the Design of Complex Distribution Systems’ International Journal of Physical Distribution and Logistics Management, 28, 5. 32. Freight Transport Association (1995) ‘Vehicle Utilisation: Making the Most of Every Journey.’ Freight Matters 3/ 95, Tunbridge Wells. 33. Department of the Environment, Transport and the Regions (1998) op.cit. 34. Netherlands Economic Institute et al. (1998) op.cit. 35. Department of the Environment, Transport and the Regions (1998) ‘Transport of Goods by Road in Great Britain 1997’ London. 36. Baum (1994) op.cit. 37. Bleijenberg (1996) op.cit. 38. Department of the Environment, Transport and the Regions (1999) ‘Efficient JIT Supply Chain Management: Nissan Motor Manufacturing (UK) Ltd.’ Good Practice Case Study 374, Energy Efficiency Best Practice Programme, ETSU, Harwell. 39. Workgroep 2000 (1993) op.cit., Baum (1994) op.cit. 40. Department of the Environment, Transport and the Regions (1998) ‘Transport of Goods by Road in Great Britain 1997’. 41. A.T. Kearney ‘The Efficiency Unit Loads Report’ ECR Europe, Brussels, 1997. 42. Samuelsson, A. and Tilanus, B. ‘A Framework Efficiency Model for Goods Transportation, with an Application to Regional Less-than-Truckload Distribution.’ Transport Logistics, 1, 2, 1997. 43. McKinnon,A.C. (1995) ‘The Empty Running and Return Loading of Road Goods Vehicles’ Transport Logistics, 1, 1, 1996. 44. Browne, M. and Allen, J. ‘Forecasting the Future of Freight Transport and Distribution in Britain’ Lloyds Bowmaker Group / University of Westminster, London, 1997. 19
45. Department of the Environment (1997) ‘Energy Savings from Integrated Logistical Management: Tesco plc’ Good Practice Case Study 364, Energy Efficiency Best Practice Programme, ETSU, Harwell. 46. Dodsgon et al. (1997) op.cit. 47. Clarke, M.P. (1998) ‘Virtual Logistics: An Introduction and Overview of the Concepts’ International Journal of Physical Distribution and Logistics Management, 28, 7. 48. Holman (1996) op.cit. 49. Pellew, M. (1998) ‘Pan European Logistics: Strategies for Success in Supply Chain Management’ Financial Times Management Report, London. 50. Department of Transport (1996) ‘Lorry Weights: A Consultative Document’ London 51. McKinnon, A.C. and J. Campbell (1997) 'Opportunities for Consolidating VolumeConstrained Loads in Double-deck and High-cube Vehicles.' Christian Salvesen Logistics Research Paper no. 1, School of Management, Heriot-Watt University, 1997. 52. McKinnon,A.C. and Campbell,J.B. (1998) ‘The Double Decking of Road Goods Vehicles: An Assessment of the Opportunities and Constraints’ Paper presented to the World Conference on Transport Research, Antwerp. 53. Freight Transport Association ‘JIT: Time sensitive distribution’ Freight Matters 1/95, Tunbridge Wells, 1995. 54. McKinnon (1996), op.cit. ; Cooke, P.N.C. (1981) ‘Energy Saving in Distribution’ Gower Press, Aldershot. 55. Christopher, M.C. (1998) op.cit. 56. Energy Efficiency Best Practice Programme (1998) ‘Improving Distribution Efficiency through Supply Chain Co-operation’ General Information Leaflet 47, ETSU, Harwell. 57. McKinnon, A.C. and Campbell, J.B. (1998) ‘Key Performance Indicators in the Temperature-Control Supply Chain: Summary Report’ School of Management, Heriot-Watt University, Edinburgh. 58. Department of the Environment, Transport and the Regions (1998) ‘Focus on Roads’ The Stationery Office, London. 59. Cooper, J. and Tweddle, G. (1994) ‘Distribution Round the Clock’ in Cooper, J. (ed.) ‘Logistics and Distribution Planning: Strategies for Management’ Kogan Page, London. 60. International Road Union (1997) op.cit. 20
21
Table 1: Studies Examining the Rationalisation of the Freight Transport System: (* denotes consideration of key index) ---------- KEY INDICES ------------Author Organisation Tanja et al. TNO / EC Hey et al. EURES / Greenpeace Peeters Workgroep 2000 Baum University of Cologne DIW / Ifeu / IVU/Hacon
Study Area
Date
Modal split
Transport intensity
Vehicle utilisation
Europe
1992
*
*
*
Europe
1992
*
*
*
Netherlands
1993
*
*
Germany
1994
*
*
Germany
1994
*
*
Royal Commission on Environmental Pollution Strutyniski
UK
1994
*
Germany
1994
Whitelegg WWF
UK
1995
*
*
*
Plowden & Buchan Civic Trust Holzapfel
UK
1995
*
*
*
Germany
1995
Netherland
1996
UK
1996
*
*
*
Europe
1996
*
*
*
Europe
1996
*
*
*
UK
1997
*
CE / TLN /KNV McKinnon ETSU Bliejenberg CE Holman T&E UK Round Table on Sustainable Development Pastowski Wupperthal Institut Schipper et al.
Germany
1997
International
1997
International Road Union
Europe
1997
For bibliographical details see reference 7.
22
*
*
*
* *
* *
*
*
* *
Table 2: Effects of Freight Rationalisation Measures on Energy Consumption
Country Study
The Netherlands Workgroep 2000
Germany* DIW / ifeu / IVU / HACON
**
UK
Royal Commission on Environmental Pollution
*
Time Period
Main measures
• increased fuel efficiency 1990-2015 • consolidation of loads • reduced empty running • large modal shift to rail • improved fuel efficiency • large modal 1988- 2010 shift to rail • higher vehicle utilisation • shorter distances travelled • halving of the rate of tonnekm growth to 1995- 2020 10% per decade
Change in energy consumption business as usual
with rationalisation
+47%
-46%
+55%
+28%
+56%
-4.4%
• large modal shift to rail and water
relates to long distance transport
**
Energy calculations based on RCEP modal split targets and estimates of specific energy consumption by mode. Freight traffic forecasts based on Department of the Environment, Transport and the Regions ‘National Road Traffic Forecasts (Great Britain) 1997’. London, 1997.
23
Table 3: Relationship between Gross Vehicle Weight and Fuel Efficiency on Tonne-km per Litre Basis. Vehicle type and gross weight Rigid goods vehicle 3.5 -7.5 tonnes 7.5-17 tonnes 17-25 tonnes > 25 tonnes
Average tonne-kms per litre 4.2 9.5 12.7 18.5
Articulated goods vehicle < 33 tonnes > 33 tonnes
16.4 27.6
Source: McKinnon (1996) ref. 7
Figure 1: Comparison of Energy Saving Scenarios Reduction in Fuel Consumption (million litres / annum)
0
100
200
300
400
500
Double railfreight traffic Reduce empty running to 25% 10% increase in load factor
Based on data from the 1995 data for the UK from ref. 6 and McKinnon (1996) ref. 7
24
Figure 2: Key Road Freight Parameters Affecting Transport Intensity and Vehicle Utilisation
Weight of goods transported by road
Handling factor
Road tonnes-lifted
Average length of haul Road tonne-kilometres
Maximum vehicle carrying capacity
Average payload weight / size
Road vehicle-kilometres
% of empty running
Aggregate
25
Ratio
Figure 3: Change in Average Payload Weight in the UK, the Netherlands and Sweden: 1980-1995
% Change since 1980
40 35
1985
30
1990
25
1995
20 15 10 5 UK
Netherlands
Sweden
Source: REDEFINE project. ref. 18
% Utilisation
Figure 4: Estimates of the Average Utilisation of Road Goods Vehicle Capacity: Based on a Survey of Expert Opinion in Sweden and the Netherlands.
90 80 70 60 50 40 30 20 10 0
Cubic capacity
Floor space
Load height
Source: Samuelson and Tilanus (1997) ref. 42.
26
Pallet fill
% of total vehicle km s
Figure 5: Proportion of Truck Kilometres Run Empty on UK Roads: 1973 - 1996
35 33 31 29 27 25 73
75
77
79
81
83
85
87
89
91
93
95
YEAR
Source: UK Continuing Survey of Road Goods Transport.
Figure 6: Fuel Required to Move One Pallet-load of Frozen Food One Kilometre. (M = manufacturer-controlled operation R = retailer-controlled operation) 60
50
millilitre
40
30
20
10
0 M1
M2
M3
M4
M5
R1
Source: McKinnon and Campbell (1998) ref. 57.
27
R2
R3
R4
R5
R6
R7
