@article{Shin:208220,
      recid = {208220},
      author = {Shin, Hyeon-Shic and Kawamura, Kazuya},
      title = {Framework for a Disaggregate Truck Trip Generation Model  Based on a Survey of Retail Businesses},
      address = {2005-03},
      number = {1426-2016-118435},
      pages = {21},
      year = {2005},
      abstract = {While considerable strides have been made in forecasting  truck travel demand in the past
several years, there remain  several critical gaps that need to be addressed. The new  trends
in goods movements like the growth of e-commerce and  distribution systems will likely
affect the patterns of  truck trip generation. Through an extensive literature  review, it was
found that past truck trip generation  analyses used only aggregate variables or proxies  of
economic activities such as land use types, number of  employees, and the gross floor
space. Such analyses only  indicate the relative importance of trip generators at a  general
level and ignore the influence of business  management and operations decisions such as
sales, types of  goods, various physical constraints of stores, and  socioeconomic
characteristics surrounding communities.  Preliminary interviews with the experts from  a
manufacturing plant, a trucking company, and two  logistics and supply chain solution
providers were  conducted. Based on the interviews and literature review, a  conceptual
framework of truck trip generation analysis has  been developed. This paper argues that
the truck trip  generation should be estimated at the individual facility  level because the
number and type of freight truck trips  are the outcome of a series of decisions about
products,  sales, locations, delivery times, and frequencies, where  the strategic and tactical
decisions are made in order to  maximize the facility’s efficiency and profit by
minimizing  costs. As an issue paper, this paper reports the experience  from an ongoing
effort of modeling truck trip generation.  First, the paper describes the current trends of
truck  dominance in freight shipments and its relevance to the  current research. Second, a
brief discussion of the  definition of truck trip generation is followed by the  summary of
the literature regarding TTG models used in past  studies. Then the paper provides the
new framework of truck  trip generation analysis that is based on the findings from  the
literature review, studies on business behavior and  preliminary interviews. Before
concluding, the most  difficult task for this study, data requirement and  collection
strategies are discussed. The paper ends with  the discussions on expected outcomes,
implications, and  contributions of the study.},
      url = {http://ageconsearch.umn.edu/record/208220},
      doi = {https://doi.org/10.22004/ag.econ.208220},
}