Customer Satisfaction with various Airlines

Title: Customer Satisfaction with various Airlines

Author: Jasmine Koli

Introduction: Air India, Indigo, SpiceJet and Akasa Air are India’s dynamic airlines. Air India offers legacy travel with modern comforts. IndiGo’s your go-to for on time, affordable flights. SpiceJet’s quirky and budget friendly. Akasa Air’s the fresh, customer-focused newbie. Thes airlines offer diverse options for travellers, catering to different budgets and preferences. You’ll find a mix of legacy service, affordability and fresh approaches to air travel.

Objective: To understand customer satisfaction of different airlines with the help of ratings.

Literature Review:

Performance Evaluation of Indian Airline Industry: An Application of DEA

Alok Kumar Singh (2011) said that, the airlines in our country are experiencing low fares, poor load factors, drop in premium travels, decline in cargo loads and low yields due to deteriorating market conditions. To tide over the situation, companies need to have clear game plan and management strategies to effect turnaround of the airlines. This can be achieved only if companies know their performance gap with the benchmarked airline. Present work is aimed at calculating the relative performances of different Indian domestic airline industry (total 11 in India) using DEA framework. Data Envelopment Analysis is used to construct performance indices on the basis of the multiple outputs which airlines produce and the multiple inputs which they utilize. The result is used to find which variables the managers have some control over and what the relative importance of each variable is that affecting performance. Data Envelopment Analysis (DEA) provides a clear answer to the airline manager’s problem.

Drivers of operational efficiency and its impact on market performance in the Indian Airline industry

Haritha Saranga & Rajiv Nagpal (2016) said that, India is considered to be one of the toughest aviation markets in the world, due to high fuel prices, overcapacity and intense price competition. It is therefore important to identify critical drivers of performance, which enable the airlines to survive and succeed in this emerging market with huge growth potential. In the current empirical study, we investigate the linkages between various performance drivers, operational efficiencies and market performance. An extensive data collection using primary and secondary sources enabled us to gather data on all the airlines operating in India, both private and public, for the period 2005–2012, on a variety of important parameters. We carried out a two-stage empirical analysis, which involved estimation of operational efficiencies during the first stage using Data Envelopment Analysis, and determination of performance drivers during the second stage using a two-way random effects GLS regression and also a Tobit model. Our findings suggest that while some of the structural and regulatory factors have an undesirable impact on airline performance, the low cost carriers in India have managed to achieve significant operational efficiencies. In addition, we find that, while cost efficiency is driven by a variety of factors, it is the technical efficiency which brings in better market performance through pricing power in the Indian airline industry.

Data Collection: To understand customer satisfaction of different airlines with the help of ratings primary data was collected by creating a google form and respondents were asked to rate each brand on scale of 1 to 10 based on their usage experience. 40 students if ITM were surveyed and data was downloaded as excel sheet and Anova test was done on it.

Data Analysis:

Anova: Single Factor

 

SUMMARY

         
 

Groups

Count

Sum

Average

Variance

   
 

Air India

40

279

6.975

3.46

   
 

Indigo

40

296

7.4

3.84

   
 

Akasa Air

40

274

6.85

4.03

   
 

SpiceJet

40

275

6.875

3.91

   
               
               
 

ANOVA

           
 

Source of Variation

SS

df

MS

F

P-value

F crit

 

Between Groups

7.85

3

2.62

0.69

0.56

2.66

 

Within Groups

594.05

156

3.81

     
               
 

Total

601.9

159

 

 

 

 

 

Conclusion: We observe p value as p value is greater than 0.05 accept null hypothesis (H0) meaning all are same.

 

Reference:

Aczel A. D., Sounderpandian J. (2006), Sixth Edition, Complete Business Statistics, Tata McGrawHill Publishing Company Ltd., New Delhi

Agarwal S., Yadav S. S., Singh S. P (2002), Performance Evaluation of Public Sector of UP: An Application of DEA. Vision 2020: The Strategic Role of Operational Research, pp. 509–523.

Airlines performance in the new market context: a comparative productivity and efficiency analysis

Productivity analysis of European airlines, 2000–2011

 

Leave a comment