This article presents results from a randomized controlled eco-driving experiment with differential treatment between two groups of truck drivers in Norway. Using data from in-vehicle devices, we investigate whether eco-driving interventions (a course, active monthly follow-ups, and non-monetary incentives) reduce fuel consumption by inducing more efficient driving behavior for drivers in a treatment group, compared to a control group. Hereby, we consider persistence of effects over time and the relative importance of eco-driving factors, while controlling for fixed vehicles, routes, drivers, and weather. We find significant fuel consumption reductions, persisting over a longer period of time than in most previous studies (where effects fade or disappear), that weather conditions are important, and evidence of an ‘eco-driving learning curve’. This might result from monthly follow-ups and driver rewards. Further, we find spill-over effects through significant fuel savings for drivers in the control group (undergoing no interventions). These are likely the result of them becoming aware that ‘something eco-driving related’ is going on. Our analysis suggests that improvements on engine and gear management contribute most to fuel savings. We estimate the potential for fuel savings to lie between 5.2 and 7.5% (lower bound, control group) and 9% (upper bound, treatment group). This implies a potential for significant cost savings and emission reductions, which might to some extent be scalable and transferable to other settings. As such, eco-driving may play one part in reducing emissions from road freight, for which much-needed emission reductions are challenging to achieve, especially in the shorter run.
Bø, Eirill (2020)
Transparency Issues Within a Transport Buyer and Provider Relationship
Dwivedi, Ashish & Alshamrani, Mohammed Saad (red.). Leadership Strategies for Global Supply Chain Management in Emerging Markets
Transport is an important function in the supply chain. This chapter focuses on how to buy a transport service, how to form a transport contract, and how a transparent relationship will influence the risk and the relationship between transport provider and buyer. By developing a decision support tool (DST-model) and calculating the cost and the time parameters, the right price and the cost drivers will appear. The cases described in this chapter are a large Norwegian wholesaler for food, distribution to the retailer, and two Norwegian municipalities collecting household waste. In these cases, the buyer and the provider are acting blind in setting the transport price. This means that there is a huge risk for either a bankruptcy by the transport provider or an overpriced transport for the buyer.
Bø, Eirill & Baxter, John (2020)
Transparency as a Driver for Logistical Efficiency in WEEE Collection and Transport
Inefficiency in complex reverse-logistical operations, such as the collection and transport of various wastes, can often be traced to two related factors. Adversarial and arms-length relationships between service providers and customers are commonplace, alongside surprisingly limited understanding of the cost base. This study investigated transparency and shared understanding as drivers for higher efficiency and lower costs. Observation and intervention in contractual negotiations was combined with analyses of cost and sensitivity, and a post-contractual transparency exercise with bidders where findings were shared with all parties. The work yielded both immediate efficiency gains and a longer-term infrastructure for cost evaluation and negotiation. Ongoing work is extending the approach into yet more complex and broader areas of municipal waste management.
Bø, Eirill & Baxter, John (2017)
The effects of geographical, operational and service parameters on WEEE transport networks
International Journal of Logistics Research and Applications, 20(4), s. 342- 358. Doi: 10.1080/13675567.2016.1255718