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Evaluation of Users Approbation Indicators of Delhi Metro
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Evaluation of Users Approbation Indicators of Delhi Metro (2022)Evaluation of Users Approbation Indicator…RFRSF: Employee Turnover Prediction Based on Random Forests and Survival Analysis (2020)RFRSF: Employee Turnover Pred…Study on Effect of Chennai Metro Rail Limited Routing System and its Future Growth (2018)Study on Effect of Chennai Me…Mode Choice Analysis Using Random Forrest Decision Trees (2016)Mode Choice Analysis Using Ra…Binary Logistic Model for Estimation of Mode Shift into Delhi Metro (2016)Binary Logistic Model for Est…Access–egress and other travel characteristics of metro users in Delhi and its satellite cities (2015)Access–egress and other trave…MRTS System in Delhi: Increase in Mode Choice and its Mobility and Equity Implications (2008)MRTS System in Delhi: Increas…Multimodal public transport: an analysis of travel time elements and the interconnectivity ratio (2004)Multimodal public transport: …Work Travel Mode Choice Modeling with Data Mining: Decision Trees and Neural Networks (2003)Work Travel Mode Choice Model…Two Approaches to Service Quality Dimensions (1991)Two Approaches to Service Qua…A Conceptual Model of Service Quality and Its Implications for Future Research (1985)A Conceptual Model of Service…A Service Quality Model and its Marketing Implications (1984)A Service Quality Model and i…Public Transportation Access (1998)The access journey to the railway station and its role in passengers’ satisfaction with rail travel (2007)Access to railway stations and its potential in increasing rail use (2008)Role of user's socio-economic and travel characteristics in mode choice between city bus and informal transit services: Lessons from household surveys in Visakhapatnam, India (2018)Investigating the association between population density and travel patterns in Indian cities—An analysis of 2011 census data (2020)The first-and-last-mile of public transportation: A study of access and egress travel characteristics of Dhaka’s suburban commuters 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Behavior to Understand Commuter’s Perception towards Mass Rapid Transit in Dhaka City, Bangladesh (2023)Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)Forecasting with artificial neural networks: (1998)Trip distribution modeling with Twitter data (2019)Deep neural networks for choice analysis: Architecture design with alternative-specific utility functions (2020)Non-Linear Associations Between the Urban Built Environment and Commuting Modal Split: A Random Forest Approach and SHAP Evaluation (2023)Labor Pains: Change in Organizational Models and Employee Turnover in Young, High‐Tech Firms (2001)A decade of research on machine learning techniques for predicting employee turnover: A systematic literature review (2023)Transformative AI in human resource management: enhancing workforce planning with topic modeling (2024)A Deep Learning Model Based on Bidirectional Temporal Convolutional Network (Bi-TCN) for Predicting Employee Attrition (2025)
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References

  • 1985A Conceptual Model of Service Quality and Its Implications for Future Research21,635 cited
  • 1984A Service Quality Model and its Marketing Implications6,560 cited
  • 1991Two Approaches to Service Quality Dimensions709 cited
  • 2020RFRSF: Employee Turnover Prediction Based on Random Forests and Survival Analysis282 cited
  • 2004Multimodal public transport: an analysis of travel time elements and the interconnectivity ratio247 cited
  • 2003Work Travel Mode Choice Modeling with Data Mining: Decision Trees and Neural Networks211 cited
  • 2016Mode Choice Analysis Using Random Forrest Decision Trees104 cited
  • 2015Access–egress and other travel characteristics of metro users in Delhi and its satellite cities103 cited
  • 2016Binary Logistic Model for Estimation of Mode Shift into Delhi Metro32 cited
  • 2008MRTS System in Delhi: Increase in Mode Choice and its Mobility and Equity Implications8 cited
  • 2018Study on Effect of Chennai Metro Rail Limited Routing System and its Future Growth4 cited

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