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Measuring the Performance of Taxi Aggregator Service Supply Chain


Affiliations
1 Presidency College, India
2 Alliance University, India
 

The taxi aggregator services (also called as ride sourcing services) have become popular in the last few years in India. The companies managing these services call themselves as technology companies. This excludes them from the purview of transport regulations that a typical transport operator has to adhere to. One of the major reasons for the success of Ola and Uber, the two ride sourcing services in India, is their ability to digitally match supply and demand by successful deployment of technology. Technology has enabled the right information to be available to the right persons at the right time. The business model of taxi aggregators has intelligently woven solutions to address the gaps in the present call taxi system - namely driver behavior, lack of focus on performance, uncertainty of demand, difficulty in matching capacity with demand, increase in prices etc. With technology comprising of software algorithms enabling accurate matching of demand and supply, the wait time is reduced for the customer and for the drivers, the idle time is reduced. The other benefit for the consumer is that travel using ride sourcing services is at an affordable cost due to the volume of the operations. This has created a win-win-win situation for all - the taxi aggregator gets his commission, the driver gets assurance of demand and the consumer has to wait less and pay reasonable charges for availing the taxi services. The pricing structure is also very dynamic. This paper attempts to study the technique by which performance of these aggregator services can be measured. The paper has identified the criteria and measures of performance that can help ta xi aggregator services to improve customer satisfaction and quality of service. The paper has also suggested possible ways in which these services can use an innovation strategy to drive the business agenda.

Keywords

Innovation, Technology, Ola, Ride Sourcing, Services, Service Supply Chain, Spokes Model, Taxi Aggregator, Transportation Network Companies, Uber.
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  • Measuring the Performance of Taxi Aggregator Service Supply Chain

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Authors

G. Venkatesh
Presidency College, India
George Easaw
Alliance University, India

Abstract


The taxi aggregator services (also called as ride sourcing services) have become popular in the last few years in India. The companies managing these services call themselves as technology companies. This excludes them from the purview of transport regulations that a typical transport operator has to adhere to. One of the major reasons for the success of Ola and Uber, the two ride sourcing services in India, is their ability to digitally match supply and demand by successful deployment of technology. Technology has enabled the right information to be available to the right persons at the right time. The business model of taxi aggregators has intelligently woven solutions to address the gaps in the present call taxi system - namely driver behavior, lack of focus on performance, uncertainty of demand, difficulty in matching capacity with demand, increase in prices etc. With technology comprising of software algorithms enabling accurate matching of demand and supply, the wait time is reduced for the customer and for the drivers, the idle time is reduced. The other benefit for the consumer is that travel using ride sourcing services is at an affordable cost due to the volume of the operations. This has created a win-win-win situation for all - the taxi aggregator gets his commission, the driver gets assurance of demand and the consumer has to wait less and pay reasonable charges for availing the taxi services. The pricing structure is also very dynamic. This paper attempts to study the technique by which performance of these aggregator services can be measured. The paper has identified the criteria and measures of performance that can help ta xi aggregator services to improve customer satisfaction and quality of service. The paper has also suggested possible ways in which these services can use an innovation strategy to drive the business agenda.

Keywords


Innovation, Technology, Ola, Ride Sourcing, Services, Service Supply Chain, Spokes Model, Taxi Aggregator, Transportation Network Companies, Uber.

References