Modal split in offshore supply network under the objective of emissions minimization

We study modal split under the objective of emissions minimization in the transportation of cargo from centralized vendors in the oil and gas industry to decentralized supply bases on the Norwegian coast. The supply network includes direct road transport and a sea route along the coast. To gain insight into modal split decisions between road and sea transport from the shipper’s perspective multi-period mixed integer optimization models are formulated. Particularly the models give possibilities to examine how weekly demand patterns at supply bases, cargo commitments to sea transport, storage possibilities at supply bases, and shipper’s responsibility for a certain share of vessel capacity may effect the emissions and the modal split. Experiments on real data from an oil and gas company operating offshore show that the size of the share of vessel capacity and the possibility for storage at supply bases are the major determinants for a larger shift to environmentally friendly sea transport. The models can be used as means for making decisions regarding how a shipper can commit to sea transport to achieve less emissions.     

Reducing emissions through speed optimization in supply vessel operations

This paper examines how optimizing sailing speeds can reduce supply vessels emissions in the upstream supply chain to offshore installations. We introduce several speed optimization strategies to be used in construction of periodic vessel schedules. The strategies consider vessel waiting times before the start of service at installations and at supply base. Tests carried out on real instances from Statoil’s activities on the Norwegian continental shelf indicate that a 25% emissions and fuel cost reductions can be achieved without fleet size increase.     

Factors influencing the purchasing decisions of low emission cars: A study of Slovenia

This paper presents a study of customer preferences and opinions about alternative fuel vehicles. Nowadays the studies of green technologies, especially in the area of green transport, are interesting for policy makers, vehicle producers, customers and energy suppliers. Many stakeholders from public and private sector are investing a lot of effort to identify consumer behaviour for future improvements in development of their green products and strategies. This study is a modification of previously conducted research on customer behaviour on the same topic in Scotland. The survey includes almost 700 participants to identify the most important parameters of consumer behaviour related to purchase of alternative fuel vehicle. Therefore the questionnaire includes different factors, combining financial and technical aspects, environmental performance and vehicle design. Results have revealed that the most relevant factor for purchasing low emission vehicle is total vehicle price, and that the segment of potential alternative fuel vehicles buyers is much larger than we initially anticipated. Such vehicles are, surprisingly, also more attractive for the older population, according to our results.     

Short Sea Shipping’s Green Label at Risk

Abstract

Shifting cargo from land‐based modes to maritime transport has been a prioritized policy in many policy papers to make transport more environmental friendly. Traditional calculations of emissions per transport capacity unit have supported this. However, maritime transport may stand to loose its good environmental reputation in comparison to road transport due to (1) the sluggish processes in maritime environmental policies and the low ambition level of current regulations, (2) the much higher focus on improving the environmental efficiency of the road haulage industry, (3) the much longer economic life of vessels compared to trucks, and (4) focus on faster vessels that increase the average fuel consumption of the sea transport alternative. Through a realistic case study, the energy efficiency and emissions of alternative multimodal transport chains is presented to illustrate these points.     

A multiobjective chance constrained programming model for supplier selection under uncertainty

Risk management is an inherent part of supplier selection. While companies are enjoying the benefits of outsourcing, risks brought by this practice should be taken into account in the process of decision making. This paper presents a multiobjective stochastic sequential supplier allocation model to help in supplier selection under uncertainty. Demand for products, capacities at suppliers as well as transportation and other variable costs are the main sources of uncertainty and are modeled using probability distributions. Disruptions are exogenous events and the model provides proactive mitigation strategies against disruptions by assigning backup suppliers who can be used in case of a default at a primary supplier. When there is no disruption, the model’s solution is an optimal supplier order assignment, considering operational risks.     

Intent to purchase a plug-in electric vehicle: A survey of early impressions in large US cites

This paper examines consumer stated intent to purchase plug-in electric vehicles and assesses the factors that increase or decrease interest. We surveyed adult drivers in large US cities in early fall 2011, before vehicle manufacturers and dealers began marketing campaigns. The survey responses thus document early impressions of this transport technology. We find that, given current battery technology and public perceptions, overall stated intent to purchase or lease electric vehicles is low. Interest in plug-in hybrid technology is somewhat greater than interest in all-electric technology. Consumers who express early interest in adopting electric vehicles are typically highly educated, previous owners of conventional hybrids, environmentally sensitive, and concerned about dependence on foreign oil. Enhanced fuel economy, the primary tangible advantage of plug-in technology, is recognized as favorable by respondents but fails to exert a strong influence on purchasing intentions. Interest in plug-in electric vehicles is shaped primarily by consumers’ perceptions of electric vehicle disadvantages.     

CO2 emissions in relation to street-network configuration and city size

The street-network efficiency of tens of British cities in relation to transport fuel consumption and CO₂ emissions are analyzed. The results show a strong linear positive correlation between length entropy and average street length, and a negative correlation between entropy and street density. Also, the results suggest that in a large city the street network is used more efficiently than in a small city, as indicated by the sublinear relations between city size (population) and the number of streets, total length of streets, and the area covered by the street network. The sublinear relation means that these parameters grow more slowly than the city size. By contrast, because a larger fraction of the street network is used at close to full capacity during considerable part of the time in a large city than a small one, the fuel consumption and the CO₂ emissions show a linear relation with city size and superlinear relation with total street length. The superlinear relation means that the CO₂ emissions increase faster than the total street length, a measure of the network size. Thus, large cities may be less energy efficient and environmentally friendly than small cities. In every city the street network needs to interconnect all the buildings, which requires a certain minimum size. In a small city, however, the network is used to a low capacity most of the time so that its relations to fuel consumption and the CO₂ emissions are more favorable than those in a large city.     

Non-discriminatory train dispatching in a rail transport market with multiple competing and collaborative train operating companies

Train dispatching is vital for the punctuality of train services, which is critical for a train operating company (TOC) to maintain its competitiveness. Due to the introduction of competition in the railway transport market, the issue of discrimination is attracting more and more attention. This paper focuses on delivering non-discriminatory train dispatching solutions while multiple TOCs are competing in a rail transport market, and investigating impacting factors of the inequity of train dispatching solutions. A mixed integer linear programming (MILP) model is first proposed, in which the inequity of competitors (i.e., trains and TOCs) is formalized by a set of constraints. In order to provide a more flexible framework, a model is further reformulated where the inequity of competitors is formalized as the maximum individual deviation of competitors’ delay cost from average delay cost in the objective function. Complex infrastructure capacity constraints are considered and modelled through a big M-based approach. The proposed models are solved by a standard MILP solver. A set of comprehensive experiments is conducted on a real-world dataset adapted from the Dutch railway network to test the efficiency, effectiveness, and applicability of the proposed models, as well as determine the trade-off between train delays and delay equity.     

A two-sided market platform analysis for the electric vehicle adoption: Firm strategies and policy design

This study explores how to facilitate the electric vehicle (EV) diffusion from a two-sided market platform competition. We develop a stylized model depicting the platform competition between electric and gasoline vehicles by combining indirect network effects of consumer and energy supplier sides as well as vehicle manufacturers’ profits. The findings of this study provide several meaningful strategic and policy implications for EV manufacturers and policymakers who wish to enhance EV diffusion. First, EV sales are significantly influenced by indirect network effects from the energy supplier side to the consumer side, and vice versa. This implies that EV manufacturers who wish to boost EV diffusion should implement a strategy providing energy suppliers with incentives to willingly join the EV platform. Second, the dynamic nature of the effects of energy costs on platform competition might render counter-intuitive evidence that the drop in oil prices does not always negatively influence EV sales. This requires EV manufacturers to prepare a contingent strategy adjusting to such unexpected conditions. Third, governments should consider the energy supplier side as well as the consumer side in designing EV diffusion policies. When governments have a very challenging EV diffusion target, a balanced policy, which treats both gasoline and electric vehicle technologies fairly, may be more effective than a consumer subsidy policy.     

The merits of accelerated depreciation for promoting investment in clean transport technologies: A simulation study in the Australian rail freight industry

This article ascertains the viability of promoting accelerated depreciation for newly acquired locomotives and other rolling stock as a means of encouraging technological investment in more efficient and environmentally friendly assets. The study uses a tax-adjusted asset replacement model to evaluate the merits of accelerated depreciation, and then compares the outcomes with alternative incentive schemes. It also examines what would occur if various schemes were used simultaneously.     

Traffic Noise in Europe: A Comparison of Calculation Methods,Noise Indices and Noise Standards for Road and Railroad Traffic in Europe

The demand for inland freight transport in Europe is mainly met by road transport, leading to unsustainable impacts such as air pollution, greenhouse gas emissions and congestion. Since rail transport has lower externalities than road transport, a modal shift from road to rail is an accepted policy goal for achieving a more sustainable and competitive transport system. However, intermodal road–rail transport is mainly competitive for long-distance transport, and as a consequence, the potential for modal shift is limited. The cost efficiency of road–rail intermodal transport is particularly sensitive to pre- and post-haulage (PPH) costs, since this activity typically has a larger cost compared with its share of the total distance in the transport chain. For intermodal transportation over shorter distances, for example, below 300 km and where there are substantial PPH activities at both ends of the chain, the competitiveness of the intermodal transport system compared with that of direct road is low. Improving the efficiency of PPH activities is, therefore, of utmost importance for the competitiveness of the intermodal transport system. This paper looks into the issue of improving the cost efficiency of an intermodal transport chain by implementing an innovative and flexible legal framework regarding the PPH activities in the chain. By extending the legal framework with exemptions for longer vehicles in PPH, the cost efficiency could be greatly improved. The purpose of such a framework is to allow and enable, for PPH exclusively, the use of 2?×?40 foot or even two semi-trailers using only one vehicle in the context of the Swedish regulatory framework. This paper develops a strategic calculation model for assessing and investigating the consequences of such a framework and investigates the framework's potential in terms of cost efficiency. The model in combination with a sensitivity analysis of input variables gives a comprehensive understanding of the effects of PPH under different circumstances. From the results, it is evident that there are substantial positive effects associated with a PPH framework of longer vehicles. Results indicate that a typical shipper may experience cost reductions of about 5–10% of the total costs of the intermodal transport chain. In summary, a more innovative and flexible legal framework regarding vehicle length in the PPH links can contribute to a greater modal shift, improved cost efficiency and more environmentally friendly transportation systems.     

Transport-related CO2 effects of online and brick-and-mortar shopping: A comparison and sensitivity analysis of clothing retailing

This paper compares transport-related CO₂ emissions of online and brick-and-mortar shopping based on supply, delivery, order and travel data related to one multi-channel clothing retailer. A sensitivity analysis sheds more light on how situational factors, such as the customers’ travel distances, returns, the use of public transport modes and information behavior via different channels influence the outcome of this comparison. The results show that online retailing causes lower CO₂ emissions under many conditions. Nevertheless, the brick-and-mortar channel is more environmentally friendly when travel distances are small. The radius for which brick-and-mortar shopping has an advantage increases when returns, shifts in the use of public transport and information behavior are also considered.     

A framework to evaluate policy options for supporting electric vehicles in urban freight transport

Electric vehicles (EVs) are considered as a feasible alternative to traditional vehicles. Few studies have addressed the impacts of policies supporting EVs in urban freight transport. To cast light on this topic, we established a framework combining an optimization model with economic analysis to determine the optimal behavior of an individual delivery service provider company and social impacts (e.g., externalities and welfare) in response to policies designed to support EVs, such as purchase subsidy, limited access (zone fee) to congestion/low-emission zones with exemptions for EVs, and vehicle taxes with exemptions for EVs. Numerical experiments showed that the zone fee can increase the company’s total logistics costs but improve the social welfare. It greatly reduced the external cost inside the congestion/low-emission zone with a high population, dense pollution, and heavy traffic. The vehicle taxes and subsidy were found to have the same influence on the company and society, although they have different effects with low tax/subsidy rates because their different effects on vehicle routing plans. Finally, we performed a sensitivity analysis. Local factors at the company and city levels (e.g., types of vehicle and transport network) are also important to designing efficient policies for urban logistics that support EVs.     

Multi-criteria approach for the selection of alternative options for environmentally sustainable transport system in Delhi

The present study examines the impact of including various qualitative criteria for the selection of alternative transportation options in Delhi. Three alternative transport options viz. 4-stroke 2-wheelers, CNG cars and CNG buses are prioritized based on six different criteria––energy saving potential (energy), emission reduction potential (environment), cost of operation (cost), availability of technology (technology), adaptability of the option (adaptability) and barriers to implementation (barrier). Based on quantitative criteria ‘energy’, ‘environment’ and ‘cost’, CNG car showed more potential in contributing to environmentally sustainable transport system in Delhi followed by 4-stroke 2-wheelers and CNG buses. Qualitative criteria viz. ‘technology’, ‘adaptability’ and ‘barriers’ in prioritization process resulted in higher priority for 4-stroke 2-wheelers followed by CNG bus and CNG car. Integrated quantitative and qualitative criteria gave a contrasting result as compared to that of the conventional quantitative approach and qualitative approach with highest priority for CNG bus followed by 4-stroke 2-wheelers and CNG car. This could explain the reasons for failure of many potential alternative urban transport options.     

Consumer car preferences and information search channels

In this paper, we measure the relations between stated and revealed car preferences and the use of information sources in the car-purchasing process, based on a survey of households in the Netherlands. The analysis showed that attitudinal and behavioral constructs are found for ‘environmental’, ‘performance’, and ‘convenience’ preferences, but that there is a ‘gap’ between attitude and behavior. The results show that people with a positive environmental attitude who also show environmentally friendly behavior have more involvement with cars than people who do not translate their environmental attitude into the corresponding behavior. This leads to the idea that not only environmental knowledge but also involvement with cars is a prerequisite for buying an environmentally friendly car.     

Does driving behavior matter? An analysis of fuel consumption data from heavy-duty trucks

In a case study of a Norwegian heavy-duty truck transport company, we analyzed data generated by the online fleet management system Dynafleet. The objective was to find out what influenced fuel consumption. We used a set of driving indicators as explanatory variables: load weight, trailer type, route, brake horsepower, average speed, automatic gearshift use, cruise-control use, use of more than 90% of maximum torque, a dummy variable for seasonal variation, use of running idle, use of driving in highest gear, brake applications, number of stops and rolling without engine load. We found, via multivariate regression analysis and corresponding mean elasticity analysis, that with driving on narrow mountainous roads, variables associated with infrastructure and vehicle properties have a larger influence than driver-influenced variables do. However, we found that even under these challenging infrastructure conditions, driving behavior matters. Our findings and analysis could help transport companies decide how to use fleet management data to reduce fuel consumption by choosing the right vehicle for each transportation task and identifying environmentally and economically benign ways of driving.     

A cost and CO2 comparison of using trains and higher capacity trucks when UK FMCG companies collaborate

Companies working in a collaboration are able to achieve higher vehicle capacity utilisation and reduced empty running, resulting in lower costs and improved sustainability through reduced emissions and congestion. Collaboration produces higher volumes of goods to be moved than individual companies which means that further efficiencies may be possible by relaxing the freight mode constraints and considering rail and higher capacity vehicles. This paper explains how real world data has been used in a model to quantify the economic and environmental benefits in the FMCG sector delivered through collaboration utilising road and rail freight modes. Data for one month was provided by 10 FMCG companies and included freight transport flows between depots and customers, inter depot movements, and supplier collections. Detailed road and rail costs and operating characteristics were obtained and, with the transport flows, applied to a network design model which was used to validate the company data sets. A strategy examining the potential use of alternative higher capacity vehicles and rail for the flows between nine regional consolidation centres showed cost and CO₂ savings. Just under half the inter-regional flows benefited from double deck trailers, longer heavier vehicles for 30% of the flows and rail with different wagon configurations for the rest. In summary there was a 23% reduction in cost with 58% fewer road kilometres and a 46% reduction in CO₂ emissions. The ability to backhaul the same mode of transport between most of the regional centres was one of the strengths of this strategy.     

A zonal inference model based on observed smart-card transactions for Santiago de Chile

The collection of origin–destination data for a city is an important but often costly task. This way, there is a need to develop more efficient and inexpensive methods of collecting information about citizens’ travel patterns. In this line, this paper presents a generic methodology that allows to infer the origin and destination zones for an observed trip between two public transport stops (i.e., bus stops or metro stations) using socio-economic, land use, and network information. The proposed zonal inference model follows a disaggregated Logit approach including size variables. The model enables the estimation of a zonal origin–destination matrix for a city, if trip information passively collected by a smart-card payment system is available (in form of a stop-to-stop matrix). The methodology is applied to the Santiago de Chile’s morning peak period, with the purpose of serving as input for a public transport planning computational tool. To estimate the model, information was gathered from different sources and processed into a unified framework; data included a survey conducted at public transport stops, land use information, and a stop-to-stop trip matrix. Additionally, a zonal system with 1176 zones was constructed for the city, including the definition of its access links and associated distances. Our results shows that, ceteris paribus, zones with high numbers of housing units have higher probabilities of being the origin of a morning peak trip. Likewise, health facilities, educational, residential, commercial, and offices centres have significant attraction powers during this period. In this sense, our model manages to capture the expected effects of land use on trip generation and attraction. This study has numerous policy implications, as the information obtained can be used to predict the impacts of changes in the public transport network (such as extending routes, relocating their stops, designing new routes or changing the fare structure). Further research is needed to improve the zonal inference formulation and origin–destination matrix estimation, mainly by including better cost measures, and dealing with survey and data limitations.     

Innovative alternatives take action – Investigating determinants of alternative fuel vehicle adoption

Alternative fuel vehicles (AFVs) as environmentally friendly alternatives to conventional internal combustion engines have gained increasing attention in general public. While empirical studies have begun to explore product-specific factors that drive consumer adoption of AFVs, an integrative framework of a comprehensive set of AFV adoption factors and its theoretical foundation as well as empirical validation is still missing. By drawing on theory of innovation adoption and theory of reasoned action we show that consumers’ perceptions of AFV attributes lead to a general attitude formation towards AFV. In conjunction with consumers’ subjective and personal norm, this in turn determines AFV adoption behavior. Concerning AFV attributes, compatibility, design, and relative advantage of AFVs exhibit the strongest influence on consumers’ attitude formation toward AFV. We derive implications for future research and policy makers. The latter include suggestions on how to develop and communicate AFV in order to stimulate AFV adoption.     

Combining Intermodal Transport With Electric Vehicles: Towards More Sustainable Solutions

Abstract

This paper analyses the feasibility of incorporating electric or hybrid vehicles in intermodal transport for the transportation of containers in the pre- and post haulage (PPH) operation. In Europe, the intermodal transport market is being strongly supported, as it is seen as one of the keystones of a sustainable mobility system policy. The introduction of environmentally friendly electric/hybrid vehicles for the pre- and post haulage operation would mean a further enhancement leading to a more complete ecological intermodal transport chain. PPH operations are usually no longer than 30 km, and, hence, could possibly be handled by electric or hybrid vehicles.

Hybrid electric vehicles (HEV) combine electric and other drive systems, such as internal combustion engines, gas turbines and fuel cells. Hybrid electric vehicles merge the zero pollution and high efficiency benefits of electric traction with the high fuel energy density benefits of an energy source or thermal engine. The use of electrically driven vehicles for goods distribution has already been successfully proven in international demonstration projects, such as ELCIDIS. Transport of intermodal units (such as ISO containers), however, requires electric/hybrid heavy-duty goods vehicles, which are not readily available on the market, but for which the technology exists.

Different possibilities are assessed as to their technical, financial, organizational and environmental feasibility and suitability. This analysis is based on a typical mission for pre-and post haulage operations, such as type of trips, distance, frequency, urban/suburban, etc.