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- W857580933 abstract "The fundamental motivation for this research is to understand the recent trends of goods movements within the changing environment of economy, goods movement behaviors, and logistics and supply chain management (SCM), and analyze their impacts on truck trips. The research develops a model of truck trip generation (TTG) at the disaggregate level that incorporates various decisions made by individual businesses. The main assumption of the study is that TTG is an outcome of a series of strategic and operational decisions of businesses. The research team conducted the survey on the national retail chains. For this paper, the data sets obtained from two furniture chains were used. Since the dependent variable, the number of truck deliveries per week, turned out to be binary, the models were built using binary logit model. The selected models using the first data set were tested for the validation with the second data set. Although the results were not conclusive, the study suggests a potential of the approach, and its transferability. In addition, the study found that the location characteristics and types of stores to have good explanatory powers for predicting delivery trips. With a well-defined data for store type and location, it may be possible to build a genearlizable TTG model for similar retail sectors." @default.
- W857580933 created "2016-06-24" @default.
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- W857580933 date "2006-01-01" @default.
- W857580933 modified "2023-09-23" @default.
- W857580933 title "Development of Disaggregate-Level Truck Trip Generation Model: Case Study of Furniture Chain Stores" @default.
- W857580933 hasPublicationYear "2006" @default.
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