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FAKTOR PEMILIHAN MODA PENGUNJUNG CAR-FREE DAY KOTA BANDUNG
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This paper aims to reveal the dimension underlying variables that affect the trip makers; mode choice to reach Car-Free Day location, taking Bandung as a case study. Twelve variables are gathered from several works of literature, namely trip cost, parking cost, trip duration, trip distance, number of people on the trip, the highest number of lanes in the trip, the age of the trip maker(s), number of vehicle ownership, whether those are motorized or non-motorized, and the number of household member. Correlations between variables are more than possible to find in that amount. Therefore, a principal component analysis is used to group the variables into factors, representing the structure or dimension laid down beneath them. This method shows that five groups of variables, or factors, are generated. The result then is compared to number of literatures that priorly have been reviewed. These factors finally are refined by grouping them into only 3 factors: “trip characteristics”, which consist of trip duration, the highest number of lanes in the trip, and trip distance. The second factor, namely trip-maker characteristics, which is built upon trip maker’s age(s), number of people on the trip, and vehicle ownership of the trip maker(s). The last, but not least, factor is labeled “household structure”, with its variables being the number of adults and kids in the trip maker’s household. Each factor also contains the variables’ factor loadings.
Institut Teknologi Sumatra
Title: FAKTOR PEMILIHAN MODA PENGUNJUNG CAR-FREE DAY KOTA BANDUNG
Description:
This paper aims to reveal the dimension underlying variables that affect the trip makers; mode choice to reach Car-Free Day location, taking Bandung as a case study.
Twelve variables are gathered from several works of literature, namely trip cost, parking cost, trip duration, trip distance, number of people on the trip, the highest number of lanes in the trip, the age of the trip maker(s), number of vehicle ownership, whether those are motorized or non-motorized, and the number of household member.
Correlations between variables are more than possible to find in that amount.
Therefore, a principal component analysis is used to group the variables into factors, representing the structure or dimension laid down beneath them.
This method shows that five groups of variables, or factors, are generated.
The result then is compared to number of literatures that priorly have been reviewed.
These factors finally are refined by grouping them into only 3 factors: “trip characteristics”, which consist of trip duration, the highest number of lanes in the trip, and trip distance.
The second factor, namely trip-maker characteristics, which is built upon trip maker’s age(s), number of people on the trip, and vehicle ownership of the trip maker(s).
The last, but not least, factor is labeled “household structure”, with its variables being the number of adults and kids in the trip maker’s household.
Each factor also contains the variables’ factor loadings.
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