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Nokels, L., Fahmy, T. and Crochemore, S. (2010) Interpretation of the Preferences of Automotive Customers Applied to Air Conditioning Supports by Combining GPA and PLS Regression. In: Vinzi, V.E., Chin, W.W., Henseler, J. and Wang, H., Eds., Handbook of Partial Least Squares: Concepts, Methods and Applications, Springer, Berlin, 775.
https://doi.org/10.1007/978-3-540-32827-8_34

has been cited by the following article:

• TITLE: Public Transit Performance Evaluation Using Data Envelopment Analysis and Possibilities of Enhancement

  AUTHORS: Sunil Sujakhu, Wenquan Li

  KEYWORDS: Public Transit System, Data Envelopment Analysis, Performance Evalua-tion, Partial Least Squares Regression

  JOURNAL NAME: Journal of Transportation Technologies, Vol.10 No.2, February 28, 2020

  ABSTRACT: This study evaluates the operational performance of all routes of Sajha Bus Yatayat operating inside Kathmandu valley using Data Envelopment Analysis (DEA) in terms of efficiency and effectiveness score. This approach allows us to access the relative performance of transit system in absence of historical data and research to compare with. To explore the possibility of enhancing the performance, scenarios were created for relatively underperforming routes and long route problem by changing the most important input variable and output variables accordingly with regression model where it was relevant. Partial Least Squares (PLS) regression was used to determine the most influential input variables to the output variables. DEA was conducted to access the performance of all routes under these scenarios. Underperforming routes except the longest route under the first set of scenarios, emerge to be better performing efficiently without considerable negative deviation in effectiveness. The result of second set of scenarios for long route problem suggests that the longest route’s performance can be enhanced significantly upon proper route alignment. Scenarios development and evaluation can help lead transit companies to explore the strategies to facilitate operational performance enhancement.