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.