There is a growing interest among industry and policymakers for the application of cargo cycles in commercial transport. Although the potential of this type of vehicle has been shown in the pertinent literature, the factors affecting the purchase decision of cargo cycles by commercial users are yet to be explored. Hence, this research aims at identifying the relevant factors, using data from Europe's largest cargo cycle testing project "Ich entlaste Städte". Two different binary logit models are estimated, one for the intention to purchase cargo cycles (stated at the end of a 3-month vehicle trial), and another for the actual purchase decision made (queried three months or later, after the trial). A comparison of both the models shows that the actual purchase decision is significantly influenced by hard facts like the deteriorating conditions (e.g., vehicle access restrictions) for conventional vehicles, while the purchase intention is not. Factors that influence the actual purchase decision include catchment area of cargo cycle trips, daily usage during the trial phase, trial phase season, type of cargo cycle tested, mode substituted by cargo cycles during the trial phase and business sector. Further, three other factors, which are latent variables constructed through exploratory factor analysis, are found to have significant influence: perception of operational and non-operational benefits, and importance of deterioration of conditions for conventional vehicles. Insights from the research include the effectiveness of the trial schemes, substitution potential for car trips, favorable business sectors and requirement of campaigns to promote soft benefits.     «

There is a growing interest among industry and policymakers for the application of cargo cycles in commercial transport. Although the potential of this type of vehicle has been shown in the pertinent literature, the factors affecting the purchase decision of cargo cycles by commercial users are yet to be explored. Hence, this research aims at identifying the relevant factors, using data from Europe's largest cargo cycle testing project "Ich entlaste Städte". Two different binary logit models are...     »