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\begin{document}

             \author[1]{N.Thamarai  Selvan}

             \affil[1]{  Air India Ltd}

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\date{\small \em Received: 11 December 2015 Accepted: 4 January 2016 Published: 15 January 2016}

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\begin{abstract}
        


Purpose: The purpose of the study is to analyse the performance of Indian air transport operators using key parameters and to benchmark production, marketing and overall efficiencies that can eventually guide top management in tackling present contemporary challenges prevailing in the Indian aviation market and also to provide insights in strategic decision making process. Design/Methodology/Approach: This study applies two stage Data Envelopment Analysis (DEA) to evaluate the production and marketing and overall efficiency. Super-Efficient DEA model is used to calculate the efficiency scores and to rank the airlines. Eight Key performance indicators of production and marketing efficiencies are analysed from the year 2010 to 2014 to study the market dynamics.

\end{abstract}


\keywords{benchmarking, two stage DEA, super efficiency model, indian airlines industry.}

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\let\tabcellsep& 	 	 		 \par
Eighty five International airlines fly in the Indian sky, connecting over 40 countries. Although India's middle-income population is expected to increase from 160 Million in 2011 to 267 Million by the year 2016, the Indian air transport sector is one of the least penetrated air markets in the world with just 0.04 trips per capita per annum as compared to 0.3 in China and more than 2 in the USA. As there is good potential for growth, Indian carriers plan to increase their fleet size to reach 800 aircrafts by 2020.The Indian aviation sector is likely to see investments totaling USD 12.1 Billion during 2012-17 of which USD 9.3 Billion is expected to come from the private sector(Government of India's Make in India portal).\par
II. Indianair Transport Industry (IATI)an Overview\par
Presently eight airlines are operating in India of which, five airlines account for 97\% of the market share.\par
New startups Air cosata, Air Asia-India and Vistara are yet to make a noticeable impact in the market. Indigo, the market leader, Spice jet, and Go Air are Low Cost Carriers (LCC) and Air India (Owned by Government of India) and Jet Airways are Full Service Carriers(FSC). The market share as on August 2016 is represented in the following Figure \hyperref[fig_3]{2}. Source: Director General of Civil Aviation (DGCA), India While India's LCCs have a domestic market share of 59\%, passengers flying on full service airlines pay close to LCC fares in economy class. As a result India is virtually a 100\% low fare market. In the Indian market LCCs and FSCs both operate from the same airports with new aircraft, offering high frequencies on key markets. LCC reliability, on time performance, consistency, ground product and cabin crew service standards, are comparable with or even better than FSCs. As per center for Asia pacific aviation (CAPA) report on Indian aviation states that from the Indian passenger's perspective there is little to distinguish between an LCC and an FSC in economy class other than the fact that the latter offers a complimentary onboard meal. 
\section[{a) Strategic issues in IATI}]{a) Strategic issues in IATI}\par
Despite the phenomenal growth of the Indian aviation market and a very positive forecast for the future, Indian Air transport operators continue to struggle to stay afloat and make profits mainly due to low fares, drop in premium travels, low yields and tax burdens on fuel,. Many international airlines from other countries have started making profits after drop in oil price but in India the FSCs have been consistently making losses for last four years on the other hand, the LCCs, Indigo and Go Air are earning profits. Expected profit/ Loss for Indian airlines for FY 2015 are shown in To avoid mounting losses and to continue to grow in the field the top management of IATI requires a clear vision that can be translated into adaptable strategies and managerial decisions to turn the airlines around. A comprehensive study including vital performance indicators as major input and output parameters have not yet been carried out for IATI. It is felt that Bench marking of Airlines must be carried out using performance indicators to achieve this objective. So far, the analyses carried out in India are primarily based on one of the many key performance indicators such as revenue earned, total number of passenger carried, passenger load factor, profit generated etc.\par
It is conceived that Data Envelopment Analysis (DEA) can be used to analyse the performance of IATI using the performance indicators. This study uses a twostage DEA model to overcome shortcomings of the traditional one-stage DEA. Of the many key performance indicators used in studies reported in literature, the input and intermittent output variables for this study are selected after extensive discussions with Indian aviation experts and also with top management executives of IATI. The production, marketing and overall efficiency ranking are obtained using a super-efficient DEA model. The findings from the analysis are discussed. This article concludes with managerial implications, limitations of the study and future scope for academic research. 
\section[{III.}]{III.} 
\section[{Literature Review}]{Literature Review}\par
Data Envelopment Analysis (DEA) is a linear programming based technique that converts multiple output and input measures into a single comprehensive measure of performance. This is performed by the construction of an empirical-based production or resource conversion frontier, and by the identification of peer groups. DEA has also been widely applied in evaluating airline performance. \hyperref[b16]{Schefczyk et al. (1993)} used the DEA technique to analyze and compare operational performance of 15 international airlines using non-financial data such as available ton kilometer, revenue passenger kilometer etc. The study demonstrated that DEA can be a very effective tool to assess the technical efficiency of international airlines compared to financial analysis. Sickles et al.  {\ref (1995)} examined the performance of the eight largest European and the eight largest American airlines for a ten year period between 1976-1986 using two methods -parametric analysis using statistical estimation and non-parametric analysis (DEA) using linear programming. The authors observed discrepancy in the productive efficiency of European airlines even under the conditions of deregulations and liberalization of the airline industry. \hyperref[b14]{Michaelides et al. (2009)} have employed both Stochastic Frontier Analysis (SFA) and DEA using a panel data set of 24 world's largest network airlines to estimate technical efficiency in International Air Transport for the period 1991-2000. The authors observed that the airlines achieved constant returns to scale with technical efficiencies ranging from 51\% to 97\%. They also observed that ownership (private or public) did not affect the technical efficiency of the airlines and the results from both SFA and DEA did not vary significantly. Airlines. This study determined whether the inclusion of low-cost airlines in a dataset of international and domestic airlines has an impact on the efficiency scores of 'prestigious' and purportedly 'efficient' airlines. The findings reveal that the majority of budget airlines are efficient relative to their more prestigious counterparts. Moreover, most airlines identified as inefficient are so largely because of improper utilization of non-flight assets. Domenico \hyperref[b7]{Campisi et al. (2010)} analyzed the relationship between low cost carriers (LCC) passenger traffic, secondary airports utilization and regional economic development in Italy. LCCs have been the fastest growing sector of the aviation industry. The routes served by these carriers were undersized in comparison with principal routes. The findings indicated that increased service at Italian secondary airports could affect economic development in the surrounding regions, including increased tourism and the potential for cluster development.  {\ref Wen} Two portfolios, one consisting of efficient airlines, and the other consisting inefficient airlines, were compared. The efficient portfolio was found to outperform the inefficient portfolio by an annual margin of 23\% using raw returns.\par
It can be seen that no bench marking tools including DEA have included Indian Airlines in their study and a literature survey shows that there are, hitherto, no articles reporting analysis of IATI. The input/output variables used in earlier DEA analyses of the airline industry and their key findings are given in Table2. Airlines are grouped in to efficient and inefficient airlines The efficient portfolio outperforms the inefficient portfolio by an annual margin of 23\% using raw returns From the literature available, it can be inferred that DEA serves as an effective bench marking tool and multiple important parameters used as input and output variables can be extended to the Indian context as well. As most of the earlier studies have been carried out using older data sets, the findings probably may not be appropriate for present managerial decisions. This paper aims at analyzing the IATI using DEA model with vital parameters as variables. Five year data from FY 2009-2014 are collected for analysis so that the findings would not only give directions to guide in managerial decisions but also helps for future strategic planning.\par
IV.  
\section[{The Efficiency Analysis}]{The Efficiency Analysis} 
\section[{a) Two-stage model}]{a) Two-stage model}\par
Evaluating the organizations performance is a complex process that cannot take just one criterion or one dimension. Traditional DEA neglects the intermediate measure or linking activities \hyperref[b10]{(Fare and Whittaker, 1995;}\hyperref[b6]{Chen and Zhu, 2004;}\hyperref[b18]{Tone and Tsutsui, 2009)}. In this study two stage DEA model is applied. The overall efficiency score is calculated by combining production and marketing process. In the first stage, the production efficiency is calculated using three inputs namely fleet, employees and operating expenses, which produce two outputs which are taken available ton kilometers, and available seat kilometers. These two intermittent variables are taken as input variables for marketing efficiency calculations. The final out variablesparameters considered are revenue passenger kilometer, Total operating revenue and total cargo carried. The input, output, intermittent variables used in two stage DEA Model are shown in Figure \hyperref[fig_3]{2}.    Further ranking of the efficient set of DMUs is possible by computing efficiency scores in excess of unity. Consider unit B in figure \hyperref[fig_8]{4}. If it were excluded from the frontier, a new frontier would be created comprising only units A and C. The super-efficient score for unit B is obtainable by calculating its distance to the new frontier whereby this 'extra' or 'additional' efficiency denotes the increment that is permissible in its inputs before it would become inefficient. The consequence of this modification is to allow the scores for efficient units to exceed unity. For instance, a score of 1.25 for unit B would imply that it could increase its inputs by 25 percent and still remain efficient. This super-efficient model \hyperref[b0]{(Andersen and Petersen, 1993}) is applied in this analysis using the approach described in Zhu (2004). 
\section[{V.}]{V.} 
\section[{Table 5: Correlation coefficients matrix}]{Table 5: Correlation coefficients matrix}\par
The results of the correlation coefficient matrix show a significantly positive relationship between inputs and outputs. The data set satisfies the assumption of isotonicity wherein, increasing the value of any input while keeping other factors constant should not decrease any output but should instead lead to an increase in the value of at least one output.\par
The production efficiency scores obtained using super efficient DEA with input and output variables taken for study are shown in Figure \hyperref[fig_9]{5}. The minimum values represent the Go air (LCC) and the maximum values are for Air India (FSC). 
\section[{Fleet}]{Fleet}\par
Correlation coefficients for inputs and outputs for the overall efficiency for the year 2009-10 are presented in Table  {\ref 5}.  LCC are seen to be very efficient, occupying the first position whereas FSCs are least efficient for all the five years. Indigo (LCC) occupied the fourth position in FY 2010-11 had improved their performance in the following years. The finding is in line with higher aircraft utilization, more numbers of departures made by LCC (DGCA-Airlines performance data) than FSCs .This could be due to the reason that LCC's maintain similar type of aero planes, the maintenance of aircrafts, availability, and mandatory checks are optimized.\par
The marketing efficiency scores derived are reflected in Figure \hyperref[fig_10]{6}.  Both production and marketing efficiencies have positive impacts on overall efficiency whereas the increase in the production performance has a higher impact on the overall performance of the Indian airlines. Marketing efficiency has comparatively lower effect.\par
VI. 
\section[{Conclusion}]{Conclusion}\par
This study has been performed using the latest data available and therefore, the results give valuable insights to airlines strategic decision makers to increase efficiency. Eight vital key performance indicators are taken as variables for analysis to produce reliable results. The practical implications from the study are ? Airlines in India must emulate the LCC model to be highly efficient. ? Available resources may be allotted to increase technical efficiency, which in turn produces more seats and capacity for sale. ? Marketing efficiency has less impact than production efficiency on overall efficiency of the Airlines. Indian Airline companies may try to adopt new innovative marketing strategies other than pricing to improve overall efficiency. ? FSCs must focus on improving their technical efficiency so that overall efficiency can be increased.\par
The results derived correlate well with the performance of the Indian air transport market in last five years. LCCs s are in a position to stay afloat but FSCs have been making heavy losses, which have gone as far as forcing Air India to go in for bailout package with Indian government and causing Jet Airways to sell their shares to foreign carrier Ethihad Airways. It is also observed that the no Indian airlines operator has hitherto implemented notable marketing initiatives that could change the market dynamics other than offering attractive fares.\par
The limitation of this study is that IATI is analysed, taking only the domestic market of Indian airlines, which account for 68\% of passenger carried (for the FY2015). The performance of Indian Airlines has not been compared with foreign carries or other Asia pacific carriers. Future studies may be carried out by including international data and comparing with foreign carrier's data.\par
This study may lead to more analyses in the Indian aviation sector using proven tools, which will be helpful for all stake holders in the industry. Future studies could group Indian carriers into LCC, FSC and Government owned, to get better insights. Improvements in marketing efficiency may be attempted by carrying out gap analysis, important and performance analyses (Fang-Yuan et.al.) on Indian airlines sector. This work may also open up further academic research and analyses aimed at guiding the industry to optimize resources.\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}Introduction}\end{figure}
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\caption{\label{fig_1}Figure 1 :}\end{figure}
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\noindent\textbf{}\includegraphics[]{image-5.png}
\caption{\label{fig_4}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-6.png}
\caption{\label{fig_5}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2}\includegraphics[]{image-7.png}
\caption{\label{fig_6}Figure 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-8.png}
\caption{\label{fig_7}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4}\includegraphics[]{image-9.png}
\caption{\label{fig_8}Figure 4 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{5}\includegraphics[]{image-10.png}
\caption{\label{fig_9}Figure 5 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{6}\includegraphics[]{image-11.png}
\caption{\label{fig_10}Figure 6 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.09784172661870504\textwidth}P{0.3669064748201439\textwidth}P{0.2384892086330935\textwidth}P{0.02446043165467626\textwidth}P{0.02446043165467626\textwidth}P{0.02446043165467626\textwidth}P{0.04892086330935252\textwidth}P{0.02446043165467626\textwidth}}
\tabcellsep \tabcellsep \multicolumn{4}{l}{MARKKET SHARE}\\
NEW PLAYER\tabcellsep VISTARA AIR ASIA OTHERS\tabcellsep 2\% 2\% 2\%\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep INDIGO\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep 39\%\\
LCC\tabcellsep SPICE JET\tabcellsep 12\%\tabcellsep \tabcellsep \tabcellsep \\
\tabcellsep GO AIR\tabcellsep 8\%\tabcellsep \tabcellsep \tabcellsep \\
FCC\tabcellsep JET AIR INDIA\tabcellsep \multicolumn{2}{l}{15\%}\tabcellsep 20\%\tabcellsep \\
\tabcellsep 0\%\tabcellsep 10\%\tabcellsep \multicolumn{2}{l}{20\%}\tabcellsep 30\%\tabcellsep 40\%\tabcellsep 50\%\end{longtable} \par
 
\caption{\label{tab_0}Table 1 .}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.5594936708860759\textwidth}P{0.29050632911392404\textwidth}}
Airline\tabcellsep Net Profit/(Loss ) In \$ -Million\\
Indigo\tabcellsep 150-175\\
Go Air\tabcellsep 14-15\\
Spice Jet\tabcellsep (-107)\\
Jet Airways\tabcellsep (-343)\\
Air India\tabcellsep (-900to -920)\\
New Airlines: Air Asia India, Air\tabcellsep \\
CoastaandVistara\tabcellsep (-50to -60)\\
\multicolumn{2}{l}{Source: Center for Aviation -India (CAPA) Market study-2015}\end{longtable} \par
 
\caption{\label{tab_1}Table 1 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{} \par 
\begin{longtable}{P{0.004207920792079208\textwidth}P{0.8457920792079208\textwidth}}
\tabcellsep -Min Lu et al.\\
\tabcellsep (2011)analyzed the effects of corporate governance on\\
\tabcellsep airline performance (Production and marketing\\
\tabcellsep efficiency). The study applied two-stage Data\\
\tabcellsep Envelopment Analysis (DEA) truncated regression to\\
\tabcellsep find out if the characteristics of corporate governance\\
\tabcellsep affect airline performance. The results demonstrate that\\
\tabcellsep corporate governance influences firm performance\\
\tabcellsep significantly. Seong-Jong Joo and Karen L. Fowler\\
\tabcellsep (2012) studied comparative efficiency and determinants\\
\tabcellsep of efficiency for major world airlines found that revenues\\
235\tabcellsep and expenses were significant in explaining the\\
\tabcellsep efficiency score of airlines.\end{longtable} \par
 
\caption{\label{tab_2}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2} \par 
\begin{longtable}{P{0.08752021563342317\textwidth}P{0.0022911051212938004\textwidth}P{0.0022911051212938004\textwidth}P{0.12280323450134771\textwidth}P{0.014663072776280324\textwidth}P{0.012830188679245283\textwidth}P{0.10584905660377358\textwidth}P{0.10172506738544473\textwidth}P{0.3555795148247978\textwidth}P{0.04444743935309973\textwidth}}
\multicolumn{3}{l}{Year and name}\tabcellsep \multicolumn{2}{l}{Inputs}\tabcellsep \multicolumn{2}{l}{Parameters}\tabcellsep Outputs\tabcellsep Findings\\
\multicolumn{4}{l}{Schefczyk M (1993) Available}\tabcellsep \tabcellsep Ton-\tabcellsep \multicolumn{2}{l}{Passenger Revenue,}\tabcellsep DEA can be very useful tool to assess the technical\\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{Kilometres (ATK),}\tabcellsep Non\tabcellsep passenger\tabcellsep efficiency of international airlines which otherwise was\\
\tabcellsep \tabcellsep \tabcellsep operating\tabcellsep \multicolumn{2}{l}{costs,}\tabcellsep \multicolumn{2}{l}{revenue(NPR)}\tabcellsep difficult to do using financial data\\
\tabcellsep \tabcellsep \tabcellsep and\tabcellsep \multicolumn{2}{l}{non-flight}\tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{assets (NFA)}\tabcellsep \tabcellsep \\
\multicolumn{3}{l}{MICHAELIDES(200}\tabcellsep \multicolumn{3}{l}{employee, fuel and}\tabcellsep total\tabcellsep annual\tabcellsep Airlines achieved constant returns to scale with\\
9)\tabcellsep \tabcellsep \tabcellsep oil, fleet\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{passenger-}\tabcellsep technical efficiencies ranging from 51\% to 97\%.\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{kilometers}\tabcellsep ownership (private or public) does not affect the\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep technical efficiency of the airlines\\
\multicolumn{3}{l}{A. George Assafet}\tabcellsep \multicolumn{3}{l}{labour expenses,}\tabcellsep Tone\tabcellsep kilometers,\tabcellsep The technical efficiency of UK airlines has\\
\multicolumn{2}{l}{al (2009).}\tabcellsep \tabcellsep \multicolumn{3}{l}{aircraft fuel and oil}\tabcellsep \multicolumn{2}{l}{available and total}\tabcellsep continuously declined since 2004\\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{expenses, aircraft}\tabcellsep \multicolumn{2}{l}{operational revenues}\tabcellsep Airline size and load factor positively affect the\\
\tabcellsep \tabcellsep \tabcellsep value\tabcellsep \tabcellsep \tabcellsep \tabcellsep efficiency.\\
\multicolumn{4}{l}{Boon L. Lee (2010) available}\tabcellsep \tabcellsep ton-\tabcellsep \multicolumn{2}{l}{revenue passenger-}\tabcellsep Majority of budget airlines are efficient compare to\\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{kilometers (ATK),}\tabcellsep \multicolumn{2}{l}{kilometers (RPK) and}\tabcellsep their more prestigious counterparts.\\
\tabcellsep \tabcellsep \tabcellsep operating\tabcellsep \multicolumn{2}{l}{costs,}\tabcellsep \multicolumn{2}{l}{non-passenger}\tabcellsep Most airlines identified as inefficient are mainly\\
\tabcellsep \tabcellsep \tabcellsep and\tabcellsep \multicolumn{2}{l}{non-flight}\tabcellsep \multicolumn{2}{l}{revenue}\tabcellsep because of the overutilization of non-flight assets.\\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{assets (NFA)}\tabcellsep \tabcellsep \\
\multicolumn{3}{l}{Domenico Campisi}\tabcellsep \multicolumn{3}{l}{Accessibility and}\tabcellsep \multicolumn{2}{l}{Passenger}\tabcellsep traffic\tabcellsep LCCs have been the fastest growing sector of the\\
\multicolumn{2}{l}{et al. (2010)}\tabcellsep \tabcellsep \multicolumn{2}{l}{traffic growth.}\tabcellsep \tabcellsep \multicolumn{2}{l}{growth}\tabcellsep aviation industry.\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep Increased service level at Italian secondary airports\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep could positively affect economic development in the\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep surrounding regions.\\
\multicolumn{3}{l}{Wen-Min Lu et al}\tabcellsep FTE-Full\tabcellsep \tabcellsep time\tabcellsep RPK,\tabcellsep NPR-\tabcellsep Non\tabcellsep Two-stage Data Envelopment Analysis (DEA) is used\\
(2011).\tabcellsep \tabcellsep \tabcellsep \multicolumn{3}{l}{employees, Fuel,}\tabcellsep \multicolumn{2}{l}{passenger revenue}\tabcellsep corporate governance influences firm performance\\
\tabcellsep \tabcellsep \tabcellsep Seats,\tabcellsep \tabcellsep Flight\tabcellsep \tabcellsep significantly.\\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Maintenance}\tabcellsep \tabcellsep \\
\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{expenditure}\tabcellsep \tabcellsep \\
\multicolumn{2}{l}{Seong-Jong}\tabcellsep Joo\tabcellsep Expenses\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Revenues,}\tabcellsep Efficiency of the airlines in Europe is the lowest\\
and\tabcellsep Karen\tabcellsep L.\tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{passengers, RPK,}\tabcellsep comparing with Asia and North America.\\
\multicolumn{2}{l}{Fowler (2012)}\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{Seat factor}\end{longtable} \par
 
\caption{\label{tab_3}Table 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3} \par 
\begin{longtable}{P{0.1791843220338983\textwidth}P{0.0036016949152542373\textwidth}P{0.008103813559322035\textwidth}P{0.09994703389830509\textwidth}P{0.5591631355932203\textwidth}}
\multicolumn{2}{l}{Variables}\tabcellsep \tabcellsep Unit /Measurement\tabcellsep Definition\\
Input\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{2}{l}{Aircrafts (Fleet)}\tabcellsep \tabcellsep Numbers\tabcellsep Total number of aero planes operated by the airlines\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep including leased flights.\\
Employees\tabcellsep \tabcellsep \tabcellsep Numbers\tabcellsep Total number of full time employees\\
\multicolumn{3}{l}{Operating cost (TOC)}\tabcellsep Million in INR (Indian\tabcellsep Total cost spent for operations of the all aircrafts\\
\tabcellsep \tabcellsep \tabcellsep rupee)\tabcellsep \\
Intermediate\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
Available\tabcellsep tone\tabcellsep kilometer\tabcellsep Million\tabcellsep The number of tonnes of capacity available for the\\
(ATK):\tabcellsep \tabcellsep \tabcellsep \tabcellsep carriage of revenue load (passenger and cargo)\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep multiplied by the distance flown.\\
\multicolumn{3}{l}{Available seat KM's(ASK):}\tabcellsep Million\tabcellsep Available seat kilometres (ASK). The number of seats\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep available for sale to passenger multiplied by the distance\\
\tabcellsep \tabcellsep \tabcellsep \tabcellsep flown\\
Output\tabcellsep \tabcellsep \tabcellsep \tabcellsep \\
\multicolumn{3}{l}{Revenue Passenger KM's}\tabcellsep Million\tabcellsep The number of revenue passengers carried multiplied by\\
(RPK):\tabcellsep \tabcellsep \tabcellsep \tabcellsep the distance\\
\multicolumn{3}{l}{Total Operating Revenue}\tabcellsep Million in INR(Indian\tabcellsep Revenues received from total airline operations including\\
(TOR)\tabcellsep \tabcellsep \tabcellsep Rupee)\tabcellsep scheduled and non-scheduled service\\
\multicolumn{3}{l}{Total Cargo Carried (TCC)}\tabcellsep Tons\tabcellsep The freight plus mail carried by an aircraft.\end{longtable} \par
 
\caption{\label{tab_4}Table 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{6} \par 
\begin{longtable}{P{0.12142857142857141\textwidth}P{0.10755102040816325\textwidth}P{0.1457142857142857\textwidth}P{0.15612244897959185\textwidth}P{0.1526530612244898\textwidth}P{0.16653061224489796\textwidth}}
\tabcellsep 1\tabcellsep 2\tabcellsep 3\tabcellsep 4\tabcellsep 5\\
2009-10\tabcellsep Go air\tabcellsep Spice jet\tabcellsep Jet Airways\tabcellsep Indigo\tabcellsep Air India\\
2010-11\tabcellsep Go air\tabcellsep Jet Airways\tabcellsep Spice jet\tabcellsep Indigo\tabcellsep Air India\\
2011-12\tabcellsep Indigo\tabcellsep Go air\tabcellsep Spice jet\tabcellsep Jet Airways\tabcellsep Air India\\
2012-13\tabcellsep GO air\tabcellsep Indigo\tabcellsep Spice jet\tabcellsep Jet Airways\tabcellsep Air India\\
2013-14\tabcellsep GO air\tabcellsep Air India\tabcellsep Indigo\tabcellsep Spice jet\tabcellsep Jet Airways\end{longtable} \par
 
\caption{\label{tab_6}Table 6 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{9} \par 
\begin{longtable}{P{0.32499999999999996\textwidth}P{0.3625\textwidth}P{0.0625\textwidth}P{0.09999999999999999\textwidth}}
\tabcellsep \multicolumn{2}{l}{Production Marketing}\tabcellsep overall\\
Production\tabcellsep 1\tabcellsep \tabcellsep \\
Marketing\tabcellsep 0.16\tabcellsep 1\tabcellsep \\
overall\tabcellsep 0.46\tabcellsep 0.24\tabcellsep 1\end{longtable} \par
 
\caption{\label{tab_7}Table 9 :}\end{figure}
 			\footnote{© 2016 Global Journals Inc. (US)} 			\footnote{© 2016 Global Journals Inc. (US) 1} 			\footnote{Benchmarking for Indian Airlines Industry in Contemporary Market Scenario} 		 		\backmatter  			 
\subsection[{Data Analysis and Findings}]{Data Analysis and Findings}\par
After selecting the parameters to get the best results from the study, the required data on TKA, ASK, RPK and TCC are collected for five years from DGCA yearly aircraft statistics published. Further, annual reports and balance sheets of these airlines are also referred to collect data on the number of employees, fleet, TOC\& TOR. The analysis is carried out on five Indian airline companies operating in the domestic sector in the years 2009-10 to 2013-14 which account for 97\% Indian domestic market. The airline companies include Air India, Jet airways, -FSC, Spice jet, Go air and Indigo-LCC. Each airline company is treated as one DMU in DEA analysis. Descriptive statistics for the airline sample taken for the year 2009 -10 is shown in Table  {\ref 4}.  There is no consistent occupier for the first and last ranking either from LCC or from FSC. It is also observed that IATI competes only on the price front by offering attractive fares. This could be due to the fact that Indian passengers are sensitive to price, which causes IATI to adopt predatory pricing strategy (center for monitoring Indian economy Pvt. Ltd-passenger forecast May 2015)\par
The overall efficiency scores obtained by the combination of all input and intermittent variables are shown in table  {\ref 10}.  LCC are seen to be highly efficient and the Government-owned Airline Air India is least efficient consistently for five years. Spice jet -LCC is also found to be less efficient in the past three years, which is in line with losses observed by the airlines company. Similarly Go air has become profitable only in the past two years. Further analysis is carried out to find out the impact of production and marketing efficiency on overall efficiency. The correlation score is reproduced in the correlation matrix in table 9. 			 			  				\begin{bibitemlist}{1}
\bibitem[ European Journal of Transport and Infrastructure Research]{b15}\label{b15} 	 		\textit{},  	 	 		\textit{European Journal of Transport and Infrastructure Research}  		9  (4)  p. .  	 
\bibitem[Andersen and Petersen ()]{b0}\label{b0} 	 		‘A Procedure for Ranking Efficient Units in Data Envelopment Analysis’.  		 			P Andersen 		,  		 			Petersen 		.  	 	 		\textit{Management Science}  		1993. 39  (10)  p. .  	 
\bibitem[Good et al. ()]{b12}\label{b12} 	 		‘Airline Efficiency Differences between Europe and the United-States -Implications for the Pace of Ec Integration and Domestic Regulation’.  		 			D H Good 		,  		 			L H Roller 		,  		 			Sickles 		.  	 	 		\textit{EJOR. EJOR}  		1995. 8 p. .  	 
\bibitem[Airport authority of India (AAI) ()]{b2}\label{b2} 	 		 \url{www.aai.aero.com}  		\textit{Airport authority of India (AAI)},  				2015.  	 
\bibitem[Fare and Whittaker ()]{b10}\label{b10} 	 		‘An intermediate input model of dairy production using complex survey data’.  		 			R Fare 		,  		 			G Whittaker 		.  	 	 		\textit{Journal of Agricultural Economics}  		1995. 46  (2)  p. .  	 
\bibitem[Charnes et al. ()]{b5}\label{b5} 	 		 			A Charnes 		,  		 			W W Cooper 		,  		 			A Y Lewin 		,  		 			L M Seiford 		.  		\textit{Data Envelopment Analysis: Theory, Methodology and Applications},  				 (Boston, MA)  		1994. Kluwer Academic Publishers.  	 
\bibitem[Director General of Civil Aviation, (DGCA) Government of India, www.dgca.nic]{b8}\label{b8} 	 		\textit{Director General of Civil Aviation, (DGCA) Government of India, www.dgca.nic},  		p. .  	 
\bibitem[Fang-Yuan Chen and Chang ()]{b9}\label{b9} 	 		‘Examining airline service quality from a process perspective’.  		 			Yu-Hern Fang-Yuan Chen 		,  		 			Chang 		.  	 	 		\textit{Journal of Air Transport Management}  		2005. 11 p. .  	 
\bibitem[Yawe ()]{b4}\label{b4} 	 		‘Hospital Performance Evaluation in Uganda: A Super-Efficiency Data Envelope Analysis Model’.  		 			Bruno Yawe 		.  	 	 		\textit{Zambia Social Science Journal}  		2010. 1  (1) .  	 
\bibitem[Michaelides et al. ()]{b14}\label{b14} 	 		\textit{International Air Transportation Carriers: Evidence from SFA and DEA Technical Efficiency Results},  		 			P G Michaelides 		,  		 			A Belegri-Roboli 		,  		 			M Karlaftis 		,  		 			Marinos 		.  		2009. 1991-2000.  	 
\bibitem[Make in India, Government of India International Air Transport Association (IATA), www.iata.com ()]{b13}\label{b13} 	 		‘Make in India, Government of India’.  		 \url{www.makeinindia.com}  	 	 		\textit{International Air Transport Association (IATA), www.iata.com},  				2015. 2015. 17.  	 
\bibitem[Rai ()]{b1}\label{b1} 	 		‘Measurement of efficiency in the airline industry using data envelopment analysis’.  		 			Atul Rai 		.  	 	 		\textit{Investment Management and Financial Innovations}  		2013. 2013. 10  (1) .  	 
\bibitem[Chen and Zhu ()]{b6}\label{b6} 	 		‘Measuring information technology's indirect impact on firm performance’.  		 			Y Chen 		,  		 			J Zhu 		.  	 	 		\textit{Information Technology and Management Journal}  		2004. 5  (1-2)  p. .  	 
\bibitem[Tone and Tsutsui ()]{b18}\label{b18} 	 		‘Network DEA: a slacksbased measure approach’.  		 			K Tone 		,  		 			M Tsutsui 		.  	 	 		\textit{European Journal of Operational Research}  		2009. 197  (1)  p. .  	 
\bibitem[Schefczyk ()]{b16}\label{b16} 	 		‘Operational Performance of Airlines: An Extension of Traditional Measurement Paradigms’.  		 			M Schefczyk 		.  	 	 		\textit{Strategic Management Journal}  		1993. 1 p. .  	 
\bibitem[Seiford and Thrall ()]{b17}\label{b17} 	 		‘Recent developments in DEA: the mathematical programming approach to frontier analysis’.  		 			L M Seiford 		,  		 			R M Thrall 		.  	 	 		\textit{Journal of Econometrics}  		1990. 46  (2)  p. .  	 
\bibitem[Lu et al. ()]{b19}\label{b19} 	 		‘The effects of corporate governance on airline performance: Production and marketing efficiency perspectives’.  		 			Wen-Min Lu 		,  		 			Wei-Kang Wang 		,  		 			Shiu-Wan 		,  		 			En-Tzu Hung 		,  		 			Lu 		.  	 	 		\textit{Transportation Research}  		2012. Elsevier. 48 p. .  	 	 (Part E) 
\bibitem[Campisi et al. ()]{b7}\label{b7} 	 		‘The Effects of Low Cost Airlines Growth in Italy’.  		 			Domenico Campisi 		,  		 			Roberta Costa 		,  		 			Paolo Mancuso 		.  	 	 		\textit{Modern Economy}  		2010. 1 p. .  	 
\bibitem[Josiassen ()]{b11}\label{b11} 	 		‘The operational performance of UK airlines’.  		 			GeorgeAssaf 		,  		 			.A 		,  		 			Alexander Josiassen 		.  	 	 		\textit{Journal of Economic Studies}  		2009. 2002-2007. 2011. 38  (1)  p. .  	 
\bibitem[Boon et al. ()]{b3}\label{b3} 	 		‘The Relative Efficiency of International, Domestic, and Budget Airlines: Nonparametric Evidence’.  		 			L Boon 		,  		 			Andrew C Lee 		,  		 			Worthington 		.  		 classifications: D24.  	 	 		\textit{Journal of Economic Literature}  		2010. p. L93.  	 
\end{bibitemlist}
 			 		 	 
\end{document}
