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Machine Learning in Estimating Vehicular Efficiency With Special Focus on Customer Acquisition and Retention
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Author(s): R. C. Thivyarathi (RMK College of Engineering and Technology, India), Parul Sharda (Medi Caps University, India), B. Ranjitha (Mohan Babu University, India), Utpal Saikia (Silapathar College, India), M. Clement Joe Anand (Mount Carmel College, Bengaluru, India)and Charles Robert Kenneth (Loyola College, India)
Copyright: 2025
Pages: 20
Source title:
Networking, Transport, and Quality of Service in Vehicular Networks
Source Author(s)/Editor(s): Truong Khang Nguyen (Van Lang University, Vietnam)and Devasis Pradhan (Acharya Institute of Technology, India)
DOI: 10.4018/979-8-3693-6422-2.ch007
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Abstract
The estimation of vehicular efficiency is highly significant in enhancing the sustainability of transportation and optimizing the allocation of resources. Machine learning algorithms are extensively applied in the domain of vehicular networks with a special focus on enriching vehicular potency. In this research work, a machine learning-based estimation model is developed for customer relationship management. The association between vehicular efficiency and customer acquisition cum retention is studied exclusively in this chapter. This work is indeed an intersection of machine learning algorithms, vehicular efficiency calculation, and customer relationship management. The interventions of the customer-oriented strategies with vehicular efficiency are explored in this study by determining the influence of customer-oriented metrics over vehicular efficiency. The results and the insights acquired from this work will certainly facilitate the policymakers and decision-makers in comprehending a comprehensive model integrating customer-centered metrics.
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