A Study on Customer Attitude towards Online Cab Services with Special Reference to Madurai City

The taxi space in India is heating up and has been seeing phenomenal growth in the past 6-7 years. An organized rental cab was introduced in the Indian market in 2004 with Meru cab service. It soon became popular among customers in metropolitan cities, but the actual revolution came in 2010 when app-based services started its operation. Soon the market became competitive, and consumers became more demanding. Now companies are using various strategies to bring more customers as well as to retain their old customers. The study of customer attitude is important for every cab service provider to get the maximum market share in the business. Customer attitude is a post dissonance of consumption activity influenced by various factors. To study the customer attitude towards online cab services, a sample of 150 respondents was selected in Madurai city. The purpose of the present study is to know the various factors influencing the customers while selecting a cab service. The study also focuses on the problems faced in online cab services, and also the future needs of the customers are also found. The study also reveals the most preferred online cabs by the customers.


Introduction
In a developing country like India, the standard of living rises due to the development of all operations, which leads to an increase in the needs of the public. Most of the people highly depend on Public Transport Services as they are not able to afford personal vehicles for traveling. One of the most important sources of Public Transport Service is the Taxi. Most the Indian citizens use Taxi every day not only to commute their workplace but also for shopping, going for a picnic with family, and the list continues. With smartphones and the internet, commuters can call, message, use WhatsApp or e-hail For-Hire Vehicle (FHV) like a taxi. Now the ecosystem is evolving with several apps using real-time information to provide consumers more choice regarding payment and comfort. The number of organized cab service providers is increasing in recent years. There is stringent competition among various operators like Ola, Uber, Meru cab, etc. Customer attitude is the post dissonance of the satisfaction process. A positive attitude is influenced by various factors like Safety, Comfort, Technology Trends, Ease of Availability, Tariff, and Different Payment Options. The study of customer attitude is an urge for every cab service provider to survive in the long run. The present study aims to know the various factors like innovativeness, mode of payment, and coupon redemption of online cab service, influencing the customers in selecting the cab services in Madurai city. The online cab service provider satisfies the needs of the customer can succeed in their business.

Review of Related Literature
Ruchi Shukla, Ashish Chandra & Himanshi Jain (2017) compared the two cab aggregators Ola and Uber using SWOT analysis. They analyzed the pricing strategies, investments, and special offers of Ola and Uber and concluded that India's market size and increasing purchasing power are attractive to the cab aggregation industry. Khupse (2017) surveyed 150 app-based taxi users with a structured questionnaire. They suggested that these service providers must focus on a cashless system, wificonnectivity, negotiations, and bargaining while improving their services. Hanif and Sagar (2016) have explained the demand for Call-a-Cab service offered by Meru Cab. The online cab services prove security through global positioning system (GPS) and women taxi drivers for women passengers, especially during night times. Dr .P. Kishore Kumar and Dr. N. Ramesh Kumar (2016) studied the factors influencing the consumers while selecting cab services.
The dependent variable is" coupon redemption behavior," and the independent variables are" innovativeness and price consciousness" The study revealed that consumers are comfortable redeem coupons through mobile apps while booking cab services. Sarvepalli and Prakash (2016) proposed a model RIDE where R stands for 'Research' meaning thereby that the company needs to do research continuously to meet the customer is looking forward." I" stands for 'innovative.' Here feasibility of research solution is checked. Next comes 'D' refers to Deploy. Lastly, 'E' denotes 'execute,' implying the company should perform this process quickly to have a competitive edge over its competitors. They recommended that drivers be provided with proper training, and the ride-sharing concept must be advertised more. Venkatesh and Easaw (2015) found that technology plays a very significant role in cab-aggregator service. They studied Ola and Uber, tapping the Indian market using smart phone technology and converted the loopholes in traditional transportation into business opportunities. Shivangi Dhawan and Prinyanka Yadav (2018) have found that the Taxi market is very modern. It provides several benefits to the customers regarding convenience, comfort, estimated traveling time, real-time information, economy, and safety. E-hailing cabs have become an essential element of metropolitan cities, and they provide more customer value than traditional taxi services. Utsav Pandya, Rungta, Rishi, and Geetha (2017) studied the impact of the private taxi market and modern along with features like GPS, more comfort, and safety. These variables have been considered considering the usual factors that customers might think of hiring a taxi.
Objectives of the Study 1. To understand the socio-economic profile of the respondents. 2. To know the various factors which are influencing the customers while selecting a cab service online. 3. To identify the problems faced by the customers of cab services. 4. To measure the level of satisfaction of the customers towards online cab services.

Research Methodology
A sample of 150 respondents from Madurai city who use online apps for availing cab services was selected random, ly, and information was collected with a structured questionnaire and through Google Forms. The primary data were collected during January 2019. The statistical tools like Simple percentage, Garrett Ranking, Chi-square test, ANOVA are used, and the interpretations are made thereon.  It is inferred from the table 3 that the factors for choosing cabs are the price. It is ranked first, and the mean score is 60.8; the second rank is convenient, and the mean score is 52.9; the third rank is Quality of services, and the mean score is 51.7. The fourth rank is safety and security, and the mean score is 48.9. The fifth rank is easy to book, and the mean score is 43.2, and sixth rank is at time pick-up and drop, and the mean score is 43.2.

Source: Primary data
It is inferred from the table 4 that 131 of the respondents prefer cash payments,9 of the respondents prefer paying through credit/debit card,6 of the respondents prefer UPI link to pay online cabs, and one prefers paying through internet banking; the majority of the respondents prefer for cash payments. It is inferred from the table 5 that the problems in online cab service are Unable to contact drivers, So it is ranked as first, and the mean score is 60.74; feeling unsecured during night rides is ranked as second, and its mean score is 55.1; drivers unnecessarily engaging in conversation with passengers is ranked as third and its mean score is 51.1, Unavailable of cabs at sometimes is ranked as fourth, and its mean score is 50.54, Cab drivers are not reliable is ranked as fifth, and its mean score is 48.6, Poor conditions of the cabs is ranked as sixth, and its mean score is 47.28 and Do not trust online transactions is ranked as seventh, and its mean score is 40.07

Difference among Age Group with Respect to Overall Services of Online Cabs
Null Hypothesis: There is no significant difference among age group concerning the overall services of online cabs Since P-value is greater than 0.01, the null hypothesis is accepted at a 1% level about the overall services of Ola, Fast track, Red taxi, and others (Meru cabs, Friends track). Hence there is no significant difference among Age Group in years of customers about the overall services of Ola, Fast track, Red taxi, and others (Meru cabs, Friends track).
Since P-value is less than 0.05, the null hypothesis is rejected at a 5% level about the overall services of Uber. Hence there is a significant difference among the age group in years of customers about the overall services of Uber.

Association between Gender and Level of Satisfaction
Null Hypothesis: There is no association between gender and level of satisfaction towards online cab services. Since P-value is less than 0.01, the null hypothesis is rejected at a 1% level of significance. Hence concluded that there is an association between Gender and Level of satisfaction towards online cab services. Based on row percentage, 26.1% of male have a low level of satisfaction, and 36.2% of a male has a high level of satisfaction. In contrast, for female customers, 23.4% belong to a low level of satisfaction, and 16.1% belong to a high level of satisfaction. Hence a majority of male customers have a high level of satisfaction, and the majority of female customers have a low level of satisfaction because of unable to contact drivers on time, feeling unsecured during night rides, unnecessary conversations of the drivers, etc.

Conclusion
Online cab services are having a bright future in India and especially in metropolitan cities where parking and long distance are big challenges. This study reveals the various factors which are influencing the customers while selecting online cabs. This study also finds the level of satisfaction provided by various online cab services. The modern customers are innovative, and at the same time, they are price sensitive; therefore, more discounts help in customer retention. In the present scenario, our finance minister Mrs. Nirmala Sivaraman has reported that due to more emergence of online cab services, people are not buying their car so, the automobile industry has been declined. This report shows the likeliness towards online cab services by all level income group people. Thus it contributes to our country's GDP and thereby leading to its growth and development.