Project 2 - Supply and Demand Gap Analysis

Abstract

The supply and demand of a cab service plays a crucial role in determining the price and availability of the service. When demand for the service is high, there may be a shortage of cabs available, leading to higher prices. On the other hand, when demand is low, there may be an excess of cabs available, resulting in lower prices. Factors that can influence the supply and demand of a cab service include the availability of other transportation options, the price of gasoline, the strength of the local economy, and the overall population density of the area. By understanding these factors, cab companies can better predict and respond to changes in demand and adjust their pricing accordingly.

Main

The main factors that influence the supply and demand of a cab service include:

• The number of cabs available: The supply of cabs is determined by the number of cabs available and the willingness of cab drivers to work.
• The number of people looking to use the service: The demand for cabs is determined by the number of people looking to use the service and their willingness to pay for it.
• The availability of other transportation options: If there are other transportation options available, such as public transportation or ride-sharing services, this can affect the demand for cabs.
• The price of gasoline: The cost of operating a cab, including the price of gasoline, can impact the supply of cabs and the prices charged for the service.
• The strength of the local economy: A strong economy may lead to an increase in demand for cabs, while a weak economy may result in lower demand.
• The overall population density of the area: In areas with higher population densities, there may be a higher demand for cabs due to a larger number of people needing transportation.
• By understanding these factors, cab companies can better predict and respond to changes in demand and adjust their pricing accordingly.

From the cab service dataset we get values like driver Id, request ID, Request Time, Drop Time, Status, Region

The demand is nothing but the sum of people needed the cab service at this point, the supply is how many service can be provided at that point

From the above picture we can see that the Demand is very high on both the regions but the service that the cab company provided to the people is very low

We also take the node over six thousands of demand arise over the period of time on that company only able to fulfil about half of the demand

From the picture we can see that nearly half of the demand can’t be fulfilled due to the lack of cabs

Demand is taken by combination of all status of the customer,

The supply value is taken from the status of completed

Status

The status column is given the value like Trip Completed or cancelled by the customer or due to unavailability of cabs the company not able to process the demand

From the above diagram we see that the Demand and the status of the demand

We get this value of cumulative of the individual status over the region

From this we get the cumulative of each status by region

By this picture we can learn that the how many of the customer requirement have met and how many of them are rejected and how many of them cancelled service due to many various reason

By this we learn that the cancellation due to cab not available is higher in airport than city by twice

Cancellation of the cabs are higher in city on enormously higher rate consider to the airport region

By this we learn that we need to increase the cab service on the airport region

From the trip requested time value we can able to subdivide the time into 4 category by separating by six hours on the day cycle

The time period of the subdivided time are morning, noon, Evening, Night

Draw a bar graph of status on different time period on the basic separation of region

From this we learn that the availability of cab on the airport region is very low on Evening time period and we need to supply more cabs to the airport at the evening time and the demand of cabs are comparatively very less in the city region

The cancellation of the cabs by the customer is high on morning on the city it may due many reasons, on that cabs are not near also comes under recurring reason for cancellation of cabs on city so increase the cabs service on city at morning

By comparing the demand on cab service for continuous days we can see that the demand on cab service varies with time period regularly

Like the demand of cabs are high on airport at evening and low on remaining times

The demand of cabs are high on city at Morning and low or intermediate at different time period over the course of action

From above picture we learn that that on airport many of the demand can’t fulfilled due to lack of cabs. The company needs to increase the cab service on the evening and reroute the cabs to the city at the time of 6AM to 12 AM

By this we can able to increase the productivity of the cab company and also maintain the price of the cab service. If the cabs are increased highly then the price will go down

Limitation

In this dataset main limitation is we don’t have the details about the reason for cancellation of cabs by the customer, so that we only able to work on assumption if we include the reason for cancellation we can able to improve on the aspect of the customer expectation.

Conclusion

In conclusion, the supply and demand of a cab service plays a significant role in determining the price and availability of the service. When demand for the service is high, there may be a shortage of cabs available, leading to higher prices. On the other hand, when demand is low, there may be an excess of cabs available, resulting in lower prices. Factors that can influence the supply and demand of a cab service include the availability of other transportation options, the price of gasoline, the strength of the local economy, and the overall population density of the area. By understanding these factors, cab companies can better predict and respond to changes in demand and adjust their pricing accordingly.