Modeling fuel saving investments and fleet management in the trucking industry: The impact of shipment performance on GHG emissions

Fuel price elasticities for single-unit truck operations in the United States

“…For instance, West et al (2011), in estimating the determinants of demand for HDV freight in the US, estimated the elasticity of HDV freight activity with respect to fuel price as À0.05; however, West et al used ton-miles as the measure of freight activity, and there are important limitations with respect to US ton-mile data, so we are hesitant to place a high level of confidence in this estimate. 3 In another study, Guerrero (2014) used freight price elasticities of demand (percent change in demand for , 1980-2012. 3 The Bureau of Transportation Statistics (BTS) reports ton-mile data for ''freight trucks'' in Table 1-50 of the National Transportation Statistics.…”

“…Beuthe et al (2001) was reviewed in Winebrake et al (2012) which notes that the Beuthe et al estimates were based on simulation analyses of the Belgian transportation network and there are numerous caveats to their estimates that they themselves are very open about. Therefore, the ''rebound effect'' that emerges from Guerrero (2014) is actually based on an approximation and simplification of estimates of elasticities from Graham and Glaister (2004), which is further based on studies that are either old (1970s or 1980s), measure different types of elasticities, are based on regions other than the US, and consist of simulation results as opposed to econometric analyses. Problems with using these types of elasticities were discussed in Winebrake et al (2012).…”

Carbon management in the logistics and transportation sector: an overview and new research directions

“…They used a simulation study to demonstrate the reduction in carbon emissions. Guerrero (2014) investigated fleet management in the trucking industry and found that speeding up shipments can significantly reduce carbon emissions. Pan, Ballot, and Fontane (2013) used a case study of two French retailers to explore the environmental impact of pooling supply chains at a strategic level and to compute the potential of carbon emissions reduction.…”

A two-stage heuristic approach for fleet management optimization under time-varying demand

“…This class of problems aim to find the optimal replacement schedules (or more generally, the purchase and retirement schedules if the number of assets is not fixed) of assets (in our case, the vehicles) that minimize the total cost over a given planning horizon. The assets considered in these problems are interdependent due to budget constraints (Karabakal et al, 1994;Lee and Madanat, 2015;Lee et al, 2016;Zhang et al, 2017), economies of scale (Jones et al, 1991;Büyüktahtakın et al, 2014), demand constraints (Wu et al, 2003;Wu et al, 2005;Guerrero et al, 2013;Guerrero, 2014;Seif et al, 2019;Shields et al, 2019), or combinations of the above (Büyüktahtakın and Hartman, 2016;Des-Bordes and Büyüktahtakın, 2017).…”