scholarly journals The Effect of Service Attributes’ Hierarchy on Passengers’ Segmentation. A Light Rail Transit Service Case Study

2016 ◽  
Vol 18 ◽  
pp. 234-241
Author(s):  
Francisco Diez-Mesa ◽  
Rocío de Oña ◽  
Juan de Oña
Keyword(s):  
Light Rail ◽  
Rail Transit ◽  
Light Rail Transit ◽  
Transit Service

scholarly journals Impacts of New Light Rail Transit Service on Riders' Residential Relocation Decisions

2017 ◽  
Vol 20 (2) ◽  
pp. 152-165
Author(s):  
You-Lian Chu ◽  
◽  
Yi Deng ◽  
Rongfang Liu ◽  
◽  
...  
Keyword(s):  
Light Rail ◽  
Rail Transit ◽  
Light Rail Transit ◽  
Residential Relocation ◽  
Transit Service

scholarly journals The effect of service attributes’ hierarchy on passengers’ segmentation. A light rail transit service case study

2016 ◽  
Author(s):  
Francisco Javier Diez de los Rios Mesa ◽  
Rocío De Oña López ◽  
Juan De Oña López
Keyword(s):  
Service Quality ◽  
Clustering Algorithm ◽  
Latent Class ◽  
Light Rail ◽  
Rail Transit ◽  
Light Rail Transit ◽  
Quality Factors ◽  
Analytical Technique ◽  
Transit Service ◽  
Satisfaction Rates

Market segmentation can help transit operators to identify groups of passengers that share particular characteristics and specific needs and requirements about the service. Traditionally, socioeconomic variables have been used to perform a simple segmentation, although satisfaction rates about service attributes were not similar among individuals belonging to a group. Cluster analysis emerges as a novel analytical technique for extracting passengers’ profiles. This paper investigates passengers’ profiles at the metropolitan Light Rail Transit service of Seville (Spain). Latent Class Clustering algorithm is applied and satisfaction rates about different service quality attributes are considered for the segmentation. Particularly, two different cluster analyses are accomplished: first level, with only socioeconomic attributes; and second level, with eight service quality factors and socioeconomic attributes. The service quality factors are obtained through a principal component analysis, at which, the large number of attributes describing the service is reduced into constructs underlying them. Equivalent satisfaction rates are calculated for these service factors. Then, homogeneous groups of passengers are obtained. Additionally, the main differences among cluster are identified.DOI: http://dx.doi.org/10.4995/CIT2016.2016.3844

scholarly journals Effects of Traffic Loads and Track Parameters on Rail Wear: A Case Study for Yenikapi–Ataturk Airport Light Rail Transit Line

2020 ◽  
Vol 6 (4) ◽  
pp. 244-264
Author(s):  
Hazal Yılmaz Sönmez ◽  
Zübeyde Öztürk
Keyword(s):  
Traffic Load ◽  
Light Rail ◽  
Rail Transit ◽  
Light Rail Transit ◽  
Independent Variables ◽  
Rail Wear ◽  
Traffic Loads ◽  
Dependent Variables ◽  
Train Speed

AbstractThe aim of this study is to investigate the effects of traffic loads and track parameters, including track curvature, superelevation, and train speed, on vertical and lateral rail wear. The Yenikapi–Ataturk Airport Light Rail Transit (LRT) line in Istanbul was selected as a case study, and rail wear measurements were carried out accordingly. Passenger counts were performed in all wagons of the train on different days and time intervals to calculate the number of passengers carried in track sections between stations regarding traffic loads on the LRT line. Values of traffic load, track curvature, superelevation, and speed were determined for each kilometer where measurements of rail wear were conducted. A multiple linear regression analysis (MLRA) method was used to identify effective parameters on rail wear. Independent variables in MLRA for both vertical and lateral wear include traffic load, track curvature, superelevation, and train speed. The dependent variables in MLRA for vertical and lateral wear are the amount of vertical and lateral wear, respectively. The correlation matrix of the dependent and independent variables was analyzed before performing MLRA. Multicollinearity tests and cross-validation analyses were conducted. According to the results of MLRA for vertical and lateral wear, the obtained coefficients of determination indicate that a high proportion of variance in the dependent variables can be explained by the independent variables. Traffic load has a statistically significant effect on the amount of vertical and lateral rail wear. However, track curvature, superelevation, and train speed do not have a statistically significant effect on the amount of vertical or lateral rail wear.

scholarly journals Pengendalian Waktu Produksi Balok Girder Dengan Menggunakan Metode CPM dan LoB

2018 ◽  
Vol 13 (2) ◽  
Author(s):  
Christofer Christofer ◽  
Anisah Anisah ◽  
Adhi Purnomo
Keyword(s):  
Waiting Time ◽  
Primary Data ◽  
Light Rail ◽  
Rail Transit ◽  
Light Rail Transit ◽  
Beam Production ◽  
Fourth Cycle ◽  
Time Cycle ◽  
Line Of Balance

This research is purpose to control time in Girder beam production using CPM (Criticial Paht Method) and LoB (Line of Balance) to get maximum productions amount with  time adaptability precisely. This research is using count method and management of secondary and primary data that illustrated to graphic and diagram. Case study at project of building the overpass LRT (Light Rail Transit), to productions girder beam at PT. Adhi Karya Factory Precast Sentul. The result of this research shows that productions capability girder beam increase as much 21 unit girder beam per mount with speed track 59,4268 unit per hour, balance delay 42,3678 %, line efficiency 42,267 with time cycle that using is 68,5 hour in first cycle, 69 hours in second cycle, 69 hours in third cycle, 69 hours in fourth cycle and having waiting time that happen to every trun of cycle is one hour. So that the result of research can declare is happen productions acceleration with using CPM (Criticial Paht Method) and LoB (Line of Balance) is 10 hour per mount.

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