Open AccessModel of Truck Travel Timeliness Based on Driver Environment Psychology and Technical Factor: A Warp.PLS-SEM Approach
Author(s) -
Dewi Yuniar,
Ludfi Djakfar,
Achmad Wicaksono,
Achmad Efendi
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1783/1/012100
Subject(s) - truck , structural equation modeling , work (physics) , transport engineering , quality (philosophy) , data collection , applied psychology , psychology , business , engineering , computer science , mathematics , mechanical engineering , philosophy , statistics , epistemology , machine learning , aerospace engineering
The importance of knowing the factors that influence coal transportation travel time based on driver behavior through work motivation. This research to assess the effect of presents inferential statistical data that determined the impact of environmental psychology and technical factors such as operational operational, social, health conditions, road quality, truck conditions, and weather on the travel timeliness with intervening work motivation. The data collected from 116 coal drivers using coal haul private roads in South Kalimantan, Indonesia. The research method uses qualitative and quantitative with structured drivers demographic and behavior questionnaires distributed to drivers. Structural equation modeling (SEM) using the Warp. PLS version 6 package to display the primary data results. Result-based research analysis on the hypothesis shows the more significant the road quality of coal haul drivers will increase work motivation and travel timeliness via work motivation. The higher the work motivation of coal haul drivers will increase travel timeliness performance. Based on the research equation that increasing operational working conditions, social conditions, road quality, truck conditions, weather conditions, and work motivation tend to increase travel timeliness. However, for health conditions negatively affect travel timeliness through work motivation, so the better health conditions will reduce travel timeliness.