Power, concession and agreement in freight distribution chains: subject to distance-based user charges

A time-period choice model for road freight transport in Flanders based on stated preference data

“…The latter is the value of travel time changes, which is additive with respect to the value of travel time changes that is implied by the transport costs function of the carrier. Our finding that transport costs and time of delivery are the main variables explaining the choices of the receivers is consistent with the outcomes of Hensher and Puckett (2008). CT: containers (22%); NCT: non-containers (78%);…”

“…The duration of the stop also comes from a Monte Carlo process. Hensher and Puckett (2008) carried out a stated preference experiment in Sydney, Australia, in an interactive setting where both carriers and their clients were interviewed to make inferences about decision-making in the supply chains. They found that for receivers of goods the key variables were the price to be paid and the time of delivery of the goods.…”

Accounting for Preference and Scale Heterogeneity in Establishing Whether it Matters Who is Interviewed to Reveal Household Automobile Purchase Preferences

“…The findings suggest however that preference heterogeneity is significant for the four attributes in the model that has all samples of individual choice responses (model M1), but the influence diminishes as we move to focusing only on the primary decision maker in a two-person group setting, continuing to diminish as we focus on only the secondary decision maker. The influence of specific attributes, given a random parameter treatment, is mixed in the group choice model; for example, none of the standard deviation parameters are statistically significant, 10 We had planned to include a model estimated along the lines of Arora and Allenby (1999), Beharry et al (2009) andPuckett (2008), complete with power weights, to establish the role of each player in respect of influencing each attribute, but we were unable to identify any significant differences when combining individual and group decisions. What the current data suggests is that there are definitely differences between individuals and groups, but that where a group is involved there appears to be no differences between the preferences of each of the primary and secondary decision maker.…”

“…We also have data on the extent to which particular alternatives are acceptable and the degree to which they are certain they would choose that alternative if it were available in the market (a hypothetical bias linked source of information). The data also provides an empirical opportunity to assess the bargaining power of each household member in the joint choice setting, using methods developed by Dosman and Adamowicz (2006), Hensher and Puckett (2008) and Beharry et al (2009), as well as the interactive agency choice experiment model of feedback and revision of group preferences (see Brewer andHensher 2000 and) The data set is complex and comprehensive and was collected using advanced computer-based survey technologies in which capturing the interplay between members of households was a major challenge. The discussions between paired household members were recorded, giving us a massive amount of qualitative data to use in gaining a better understanding of the processes used in arriving at a preferred alternative.…”

Knowledge Analysis on Logistics Cost Trade-Offs: a Study With Portuguese Food Sector’ Professionals

“…Blecic et al (2007) emphasize in their studies the importance of the trade-offs between the level of service and the costs of maintenance of inventories, one of the main activities of logistics. De Jong et al (2016) also draw attention to the trade-offs between time and transport costs, which according to Hensher and Puckett (2008) are the main variables explaining the choices of the receivers, especially when it comes to products with short-term transport.Amaral and Guerreiro (2014) emphasize, in turn, the trade-offs present between inventory maintenance and transport activities, and the costs related to the two activities are the most relevant in proportion to the total logistics costs. Jackson et al (1994) explain that as the stock is reduced, transportation costs increase because smaller 157 IJIEM quantities are sent more frequently.…”