2016Indian Journal of Science and TechnologyOpen access

Development of Regional Industrial Trip Generation Model

Vinodkumar R. Patel, H. R. Varia, Gargi Rajpara

Open full text 0 citations

Abstract

Background/Objectives: The aim of this research work is to determine the factors affecting trip generation for the selected groups of industries within the region and to develop trip generation model. Methods/Statistical Analysis: To develop trip generation model considering all the affecting parameters for the future trips estimation, the industries are classified based on the plot area and numbers of employee. The model has been developed using several regression analyses by means of Statistical Package for the Social Sciences (SPSS), which establishes relationship between number of trips each activity produce or attract by the employees and their socioeconomic attributes. Findings: A general model for trip generation has been developed. The model result gave an effective value of R2 equal to 0.99, indicating that the explanatory variables such as area of industries, income of employee, travel distance, travel time and travel cost included in the model explain 99% of the dependent variable. Travel cost and travel time are the main factors affecting trip generation. Applications/Improvements: A more detailed research work is necessary to use this model for planning purpose. Reliable forecasting of future trips using this model can be done. Keywords: Kadi, Regression, Trip Generation, Trip Production, Trip Attraction, SPSS

About this research paper

What this paper is about

Background/Objectives: The aim of this research work is to determine the factors affecting trip generation for the selected groups of industries within the region and to develop trip generation model. Methods/Statistical Analysis: To develop trip generation model considering all the affecting parameters for the future trips estimation, the industries are classified based on the plot area and numbers of employee. The model has been developed using several regression analyses by means of Statistical Package for the Social Sciences (SPSS), which establishes relationship between number of trips each activity produce or attract by the employees and their socioeconomic attributes. Findings: A general model for trip generation has been developed. The model result gave an effective value of R2 equal to 0.99, indicating that the explanatory variables such as area of industries, income of employee, travel distance, travel time and travel cost included in the model explain 99% of the dependent variable. Travel cost and travel time are the main factors affecting trip generation. Applications/Improvements: A more detailed research work is necessary to use this model for planning purpose. Reliable forecasting of future trips using this model can be done. Keywords: Kadi, Regression, Trip Generation, Trip Production, Trip Attraction, SPSS

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Background/Objectives: The aim of this research work is to determine the factors affecting trip generation for the selected groups of industries within the region and to develop trip generation model. Methods/Statistical Analysis: To develop trip generation model considering all the affecting parameters for the future trips estimation, the industries are classified based on the plot area and numbers of employee. The model has been developed using several regression analyses by means of Statistical Package for the Social Sciences (SPSS), which establishes relationship between number of trips each activity produce or attract by the employees and their socioeconomic attributes. Findings: A general model for trip generation has been developed. The model result gave an effective value of R2 equal to 0.99, indicating that the explanatory variables such as area of industries, income of employee, travel distance, travel time and travel cost included in the model explain 99% of the dependent variable. Travel cost and travel time are the main factors affecting trip generation. Applications/Improvements: A more detailed research work is necessary to use this model for planning purpose. Reliable forecasting of future trips using this model can be done. Keywords: Kadi, Regression, Trip Generation, Trip Production, Trip Attraction, SPSS

Key concepts: Trip generation, TRIPS architecture, Variables, Computer science, Regression analysis, Transport engineering, Variable (mathematics), Work (physics)

Related papers

Back to paper searchBrowse research topicsOriginal source
Development of Regional Industrial Trip Generation Model — Research Paper | ScholarLens