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669419-1 EFFICIENCY of AIRLINES in INDIA ABSTRACT This Paper Measures the Technical Efficiency of Various Airlines Operating In

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  • Natarajan and Jain
  • Efficiency of Airlines in India

EFFICIENCY OF AIRLINES IN INDIA

Ramachandran Natarajan, College of Business, Tennessee Technological University,
Cookeville TN, 38505, U.S.A. E-Mail: [email protected], Tel: 931-372-3001

and
Ravi Kumar Jain, Icfai Business School, IFHE University, Hyderabad-501203 (AP) India.
E-Mail: [email protected], Mobile: 91+94405-71846

ABSTRACT

This paper measures the technical efficiency of various airlines operating in India over a ten-year period, 2001-2010. For this, the Input Efficiency Profiling model of DEA along with the standard Data Envelopment Analysis (DEA) is used to gain additional insights. The study period is divided into two sub-periods, 2001-2005 and 2006-2010, to assess if there is any impact on the efficiency of airlines due to the significant entry of private operators. The study includes all airlines, private and publicly owned, both budget and full service, operating in the country offering scheduled services on domestic and international routes. While several studies on efficiency of airlines have been conducted globally, a research gap exists as to similar studies concerning airlines in India. This paper addresses that gap and thus contributes to the literature.

Key Words: Airlines in India, DEA analysis, Input efficiency profiling, Productivity analysis, Technical efficiency.

Introduction

The civil aviation industry in India has come a long way since the Air Corporation Act was repealed in the year 1994 allowing private players to operate in scheduled services category. Several private players showed interest and were granted the status of scheduled carriers in the year 1995. However, many of those private airlines soon shut down. Only Jet Airways and Sahara Airlines survived and continued to offer scheduled services, (Table 1). Till the year 2001- 2003, the Indian civil aviation sector was characterized by the domination of government owned national carriers like Indian Airlines (domestic) and Air India (international), excessive regulations (e.g., control of aviation fuel) and taxation. All this resulted in high cost of operating airline services which acted not only as an entry barrier for the private players but also made air travel an expensive affair giving it an image of elitist mode of travel.

However, the scenario has changed rapidly over the last decade and the sector has witnessed a significant growth not only in terms of the entry of new private players but also in terms of increase in passenger traffic (16% CAGR between 2001-2011 with a more rapid growth at an average of 19% in the latter half of the decade from 2006-2010, Chart 1). All this can be attributed to the introduction of structural reforms, entry of new private airlines especially with different cost structures e.g., low cost - no frills, airport modernizations, and improvement in

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  • Natarajan and Jain
  • Efficiency of Airlines in India

service standards (ICRA Research Report; March 2012). Also, as the Indian economy began to grow faster, international passenger traffic into and out of India also began to grow, (Chart 1).

In the year 2003, India’s first low-cost carrier (LCC), Air Deccan, entered the market. This was a landmark event for this industry, which triggered an entry of several other private players. The year 2005 was also a watershed year for the Indian civil aviation sector as several private low cost and full services carriers (such as Kingfisher, Indigo, SpiceJet, GoAir, and Paramount) commenced their operations (Table 1). This led to the rapid increase in capacity as measured by Available Seat Kilometers (ASK). Some of the new entrants - Air Deccan, Spice Jet, GoAir and IndiGo - were pursuing a different strategy and competed as low cost carriers (LCC).

TABLE 1: Industry Evolution
Year

1953 1953 1986 1994 1995 1997 2001 2003 2005 2007

Major Milestones

Nine Airlines existed including Indian Airlines & Air India Nationalization of all private airlines through Air Corporations Act; Private players permitted to operate as air taxi operators Air Corporation Act repealed; Private players allowed to operate scheduled services Jet, Sahara, Modiluft, Damania, East West granted scheduled carrier status 4 out of 6 operators shut down; Jet & Sahara continue Aviation Turbine Fuel (ATF) prices decontrolled Air Deccan starts operations as India’s first LCC Kingfisher, SpiceJet, IndiGo, GoAir, Paramount start operations Industry consolidates; Jet acquired Sahara; Kingfisher acquired Air Deccan; Air India and Indian airlines combined to form NACIL
2010 2011 2012
SpiceJet starts international operations IndiGo starts international operations, Kingfisher exits LCC segment Government allows direct ATF imports, FDI proposal for allowing foreign carriers to pick up to 49% stake under consideration

Source: ICRA Research

CHART 1: Passenger Traffic Growth

Source: CAPA 2010, Preparing for Long Term Growth of Indian Aviation, New Delhi, India

The entry of the LCCs has significantly expanded the civil aviation market by making air travel both affordable and accessible to the middle class. Low fares offered by LCCs have made air travel very attractive, prompting travelers to switch to air travel from road and rail travel. In the

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early days of Air Deccan 40% of its passengers were first-time flyers. SpiceJet, for instance, targeted passengers who were traveling by air-conditioned classes in Indian Railways. LCCs ushered in a new era of competition among airlines. For instance, LCCs competitive pricing set off a price war with the incumbent Full Service Carriers (FSCs) such as Indian Airlines, Jet Airways, and Air Sahara. This compelled the FSCs to discount their fares by as much as 60%- 70% in some routes to match the prices of LCCs. While the aggressive pricing strategy of LCCs has created both depth and width of demand which has percolated to non-metro towns and TierII cities, this has hurt not only the profitability of LCCs but also the revenues, margins, and market shares of FSCs. For instance, Jet Airways, which controlled about 50% of the domestic market in 2003, saw its share (including that of its acquisition Jet Lite) drop to about one-third by 2007.

According to Kapil Kaul of Centre for Asia Pacific Aviation, “….but the aggressive expansion of the LCC segment comes at a cost to the whole sector. India’s airlines are expected to post a combined loss of approximately USD$500 million in the current financial year ending 31-Mar07,” (Kaul, 2007).

Aggressive expansion of capacity and inability to control costs were other factors which contributed to the mounting losses. These conditions can lead only to two types of outcomes for the airlines—either some of them go bust in a market shake-out or they merge/get acquired by other airlines or business groups. Whereas in the 1990s, many private carriers went bust, this time around the industry has witnessed a wave of consolidation. Year 2007 became a landmark year in the industry when major consolidation took place, (Table 1).

In 2008, there was a steep fall in the domestic air travel due to the slowdown in the Indian economy, the H1N1 flu scare, and the terrorist attack in Mumbai in November 2008 (Chart 1). There was excess capacity all around and the airlines responded by developing plans to layoff employees and by offering deeply discounted fares to stimulate demand. Rival airlines Jet Airways and Kingfisher formed a strategic alliance for code sharing and cutting costs. The trend was to shift more capacity to LCC operations. The Indian economy slowed in 2008-09 but there was no recession and as the economy picked up in the second half of 2009, the demand for air travel made a comeback (Chart 1). Interestingly, the “pure” LCCs like SpiceJet and IndiGo made profits while carriers like Kingfisher, Jet Airways and NACIL, which had merged in 2007 and operated both FSC and LCC services, experienced huge losses. The anticipated cost reduction due to synergies from the mergers could not be realized. In 2012, the slowing economy affected demand and the domestic market was down by 4.9% compared to 2011. The airlines were also adjusting their capacities downwards to more realistic levels, (IATA, 2013).

Despite these setbacks and massive losses, the long term prospects for the industry appear to be quite good. The reason why foreign airlines such as Air Asia (Asia’s largest low cost airline wants to take 49% stake in a joint venture with the Tata Group) and Abu Dhabi-based Etihad (which took a stake in Jet Airways) still find the Indian market attractive is the huge potential for growth in air travel (Kazmin, 2013). India accounts for only about 2% of global air traffic. Only about 4% of India’s population of over 1.1 billion people had ever been on a flight. Low cost and budget airlines are better positioned to dominate this market which is highly price sensitive.

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  • Efficiency of Airlines in India

The above backdrop raises the research question whether the developments described have brought about any significant change in productive efficiency of the airlines. Addressing this objective, this study investigates the productivity (technical efficiency) of various airlines operating in India over a period of ten year period starting from 2001 till 2010. Further, the study period is divided into two sub-periods, from 2001-2005 and 2006-2010, to assess if there is any impact on the productivity of airlines due to the significant entry of private operators. The study includes all airlines, both budget and full-service, operating in the country offering scheduled services on domestic and international routes. While there are several airline studies conducted globally, none to our knowledge have attempted to study the Indian airlines industry. The present study, by addressing this gap, contributes to the existing body of literature.

The paper is organized as follows. In section I, the existing literature is reviewed. The research methodology is discussed in Section II. Section III presents the sample and the data set. Results are presented and discussed in section IV. Conclusions follow in section V.

Literature Review

The existing literature in this area has covered major airlines in Asia, Europe and the USA across different cost structures (full service carriers, budget airlines and low cost carriers); size (large and small), and service type (domestic and international). Some of the important studies are cited below.

Schefczyk (1993), used the DEA technique, apparently for the first time, to analyze and compare operational performance of 15 international airline using non financial data such as Available Ton kilometer, revenue passenger kilometer etc. The study demonstrated that DEA can be a very useful tool to assess the technical efficiency of international airlines which otherwise was difficult to do using financial data because: (1) most airlines lease a substantial fraction of their fleet; and (2) different accounting and taxation rules in various countries result in different impacts of leased assets on profit and balance-sheet information of airlines.

Good, Roller, and Sickles (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 – one a parametric using statistical estimation and another non-parametric (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. The study suggested that if European airlines were as productively efficient as their American counterparts then they could save approximately $4 billion per year (in 1986 dollars).

Fethi, Jackson and Jones (2001) studied efficiency across a panel of 17 European airlines in the 1990s during the early phase of liberalization using stochastic DEA constructs (which develops production frontiers that incorporate both inefficiency and stochastic error). They use the Land, Lovell and Thore (1993) model incorporating information on the covariance structure of inputs and outputs. Stochastic DEA was chosen to achieve a closer envelopment of the mean performance of the companies in the sample and reduce, if not eliminate, the effect of extreme outliers. This model computes the relative efficiencies after allowing for stochastic error. They concluded that the airlines that were efficient in 1995 resembled those that were efficient in 1993

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  • Efficiency of Airlines in India

but not those in 1991. Interestingly, they also found that larger size airline companies were efficient thus implying that size of an airline does contribute to their degree of efficiency.

Scheraga (2004), investigated the structural drivers of operational efficiency as well as the financial position of airlines in a industry ridden by financial crises post-September 11, 2001. The study analyzed 38 airlines from North America, Europe, Asia and the Middle East and across different cost structures (low cost and budget airlines included for the first time in such a study) to investigate whether relative operational efficiency implied superior financial performance. The author used DEA technique to derive efficiency scores for individual airlines followed by Tobit analysis to investigate the underlying structural drivers of efficiency. The study concluded that the traditional framework developed in the literature still provided reasonable explanatory power for realized relative operational efficiency. The author also observed that relative operational efficiency did not inherently imply superior financial performance and airlines that had chosen relatively efficient operational strategies found themselves vulnerable in terms of financial performance and thus suffered the consequences in the post-September 11 environment.

Zhu (2011), measured performance efficiency of 21 airlines in the US during 2007-2008 using the centralized efficiency model, a two-stage process used to optimize performance simultaneously, instead of a standard DEA technique thus generating efficiency decomposition for the two individual stages. For instance, in stage one, resources (fuel, salaries, and other factors) are used to maintain the fleet size and load factor, and in stage two, the revenue generating capacity is assessed given the fleet size and load factors. The study considers airlines with different cost structures unlike most of the earlier studies that analyzed only major full service airlines.

Lee and Worthington (2010) is one of the very few studies in that included airlines across different cost structures (full services, low cost and budget airlines) and service types (international and domestic services). The study investigates whether the inclusion of low-cost airlines in the data set of international and domestic airlines has any impact on the efficiency scores of those otherwise ‘efficient’ full service airlines. The authors analyzed 53 airlines in the year 2006 using the non-parametric technique of DEA to investigate their technical efficiency. The study reveals that the majority of budget airlines are efficient relative to the more prestigious full service airlines. Moreover, most airlines identified as inefficient are so largely because of the overutilization of non-flight assets.

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) does not affect the technical efficiency of the airlines. Further, it is interesting to note that results from both SFA and DEA did not vary significantly.

Tofallis (1997), used a modified version of DEA called input efficiency profiling method to assess the technical efficiency of 14 major full service airlines across all five continents using the same data set used by Schefczyk (1993). The study demonstrated that input efficiency profiling

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  • Efficiency of Airlines in India

gives better results when compared to standard DEA in measuring technical efficiency of the airlines.

Among the above cited studies and several others (not cited in detail here) such as: Banker and Johnston, (1994); Charnes, Galleous and Li, (1996); Gillen and Lall, (1997); Alam, Semenick and Sickles (1998); Adler and Golany, (2001); and Coli, Nissi and A. Rapposelli, (2011), none have included airlines operating in an important market like India. While such omission is perhaps justifiable for academic studies till 2003 as the Indian aviation sector was very limited with only a few players operating and primarily dominated by government owned airlines, the more recent studies also seem to have ignored the Indian aviation sector. The present study adds value to the body of literature in this area by analyzing all the airlines operating in domestic and international services in full services, budget and low cost segments.

Research Methodology

While there are many ways to define and measure the productive efficiency of an organizational/industrial unit, also called Decision Making Unit (DMU), there are two widely employed techniques namely Data Envelopment Analysis (DEA) and Stochastic Frontier Analysis (SFA), (Farrell, 1957). These methods provide a measure of the technical efficiency of a DMU in terms of radial distance from the best unit on the production frontier represented by the production function of the efficient units. Lesser the distance greater is the efficiency.

DEA is a non-parametric method as it does not impose an explicit functional form for the production frontier unlike an econometric method like SFA. DEA method assumes that all deviations from the efficient frontier are due to inefficiencies, whereas the SFA technique assumes that deviations from the efficient frontier can be a random error or due to realization of inefficiency or a random shock. In short, DEA measures efficiency relative to a deterministic frontier using linear programming techniques to envelop observed input/output vectors as tightly as possible rather than explicitly stating the form of the frontier based on the defined relationship between inputs and outputs.

As seen in the literature on measurement of airline efficiency, DEA method is widely employed for assessing the productive efficiencies of airlines across the world. This study uses the standard model of DEA i.e., Charnes, Cooper, Rhodes (CCR) formulation, (Charnes et al., 1978), which considers all the inputs together, and the input efficiency profiling model of DEA (Tofallis,1997), where the effect of each input is considered separately. Both the standard model and the input efficiency profiling model assume constant returns to scale. The standard DEA model of CCR with constant returns to scale (CRS) has linear weighted combination of all the inputs in the denominator of the objective function. This implies that all the inputs are perfectly substitutable with the weights as the marginal rates of substitution.

The study uses the following two inputs and two outputs, consistent with the ones used in the earlier academic studies, (Schefczyk, 1993; Scheraga, 2004; Lee and Worthington, 2010) but exclude the third input, ‘non-flight assets’ (NFA), in airlines operations. Lee and Worthington (2010) in their recent study has observed that excluding NFA from input set does not seem to have any significant affect on the overall efficiency of the airlines.

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Input 1: X1 = Total Available Ton Kilometer (ATKM) (reflects airline fleet capacity in tonnage) Input 2: X2 = Operating Cost (OC) (all operating cost excluding aircraft rentals, depreciation and amortization and other capital expenditure) Output 1: Y1 = Revenue Passenger Kilometer Performed (RPKM) (Kilometers performed of revenue paying passenger traffic) Output 2: Y2 = Non-Passenger Revenue (NPR) (revenue from non-passenger traffic such as carrying cargo)

The rationale for using the input efficiency profiling model is as follows. The input profiling model is more discriminating than the conventional DEA model when the inputs are not substitutes. This applies in the case of airlines where the two inputs i.e., available ton kilometers (a capacity measure) and operating costs (which include fuel and labor costs) are not substitutes. Before Toffalis (1997), Kopp (1981) and Kumbhakar (1988), in their productivity studies -which do not use DEA - have considered effects of each input separately. As Kumbhakar (1988) puts it “knowing the magnitude of (overall) technical efficiency is not enough. It is important to know which inputs are causing the inefficiency and to what extent”. Input profiling helps in isolating the inefficiencies with respect to each input. This information is useful for managers to set priorities and input-specific targets for improvements.

Input efficiency profiling model of DEA is particularly relevant to the situation in the airline industry in India for the following reasons.

1) The airlines in India want to expand their fleet by significant margins (see Table 2 for aircraft on order), (Arushi and Drews, 2011). For instance, IndiGo’s aircraft orders in 2011 is more than six times its fleet size! This raises questions about utilization of the ATKM input.

TABLE 2
Market share, fleet size, aircrafts on order of scheduled domestic airlines in 2011
Airline

Kingfisher IndiGo
Jet Airways Indian Airlines
SpiceJet

  • Market Share (%
  • Fleet

66 39 96
119
26 19 10
375

Orders

130 241
29
19
18.70
18
15.80 13.80
8.1
30 66
8
10
JetLite GoAir Total
6.6

  • 100
  • 514

2) Fuel costs make up around between 40% and 50% of total operating expenses of airline industry in India, (Arushi and Drews, 2011). In comparison, this cost factor accounted for 33% on average for the global airline industry in 2008 and 2012 and 26% in 2009 and 2010, respectively, according to the International Air Transport Association (IATA, 2012).

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    MEMBERS REFERENCE SERVICE LARRDIS LOK SABHA SECRETARIAT NEW DELHI REFERENCE NOTE For the use of Members of Parliament NOT FOR PUBLICATION No.11/RN/Ref/March/2018 REGIONAL CONNECTIVITY SCHEME – UDAN Prepared by, Shri Naushad Alam, Additional Director (23034299) and Smt. Shalima Sharma, RO of Lok Sabha Secretariat under the supervision of Smt. Kalpana Sharma, Joint Secretary and Smt. Anita Khanna, Director. The Reference Note is for personal use of the Members in the discharge of their Parliamentary duties, and is not for publication. This Service is not to be quoted as the source of information as it is based on the sources indicated at the end/in the context. REGIONAL CONNECTIVITY SCHEME – UDAN Introduction The Ministry of Civil Aviation launched the 'Regional Connectivity Scheme (RCS) UDAN---- Ude Desh Ka Aam Naagrik' on 21 October 2016 with the twin objectives of1: i. Promoting Balanced Regional Growth; and ii. Making Flying Affordable For Masses The scheme is a major step towards making flying a reality for the small town common man. With the launch of UDAN, the Aviation Sector is set to get a big boost and tap huge market of middle class flyers living in Tier-2 and Tier-3 cities2. Highlights of the Scheme3 Pay only Rs. 2500 per seat for One Hour of flight by an aeroplane or a journey covered in 30 minutes by the helicopter. In a Century of Civil Aviation, only 76 airports connected by scheduled commercial flights but now in 16 months of UDAN, 56 unreserved airports and 30 unreserved helipads awarded for connectivity.
  • The Shut Down of Jet Airways

    The Shut Down of Jet Airways

    Global Journal of Economics and Finance; Vol. 3 No. 3; October 2019 ISSN 2578-8809 (Print), ISSN 2578-8795 (Online) Published by Research Institute for Progression of Knowledge The Shut Down of Jet Airways Ashmita Tikku LIM College New York, USA Herbert Sherman, Ph.D. Professor of Management Department of Business Administration School of Business, Public Admin., and Info Sciences LIU-Brooklyn, H-700 1 University Plaza, Brooklyn, NY 11201, USA Abstract The challenges of running a profitable, sustainable business are many, especially in the airline industry where profit margins are historically low. This case will examine the failure of Jet Airways, India’s second largest aviation company, to address allegations of financial misconduct and equipment failure that resulted in 30 passengers in one flight therein experiencing nose and ear bleeding. The question is, how did management address the sudden business downfall that resulted from these negative incidents? More specifically, what were the recovery plans that were developed to combat the adverse effects of these incidents on the company’s reputation, relationship with customers? More specifically, what was the impact of the firm’s decision to ask employees to leave without prior notice given its economic downturn. This failure will be analyzed through the lens of three organizational change models: Kotter’s 8-Step Change Model, the Organizational Life Cycle Model and Kurt Lewin’s Change Management Model. This analysis will include the question, how could the leaders and management team have acted as a support system for the consumers and the employees in the company. Behind the Scenes: About Jet Airways and its Origin Jet Airways (India) Private Limited was a highly reputed private airline in India with an average fleet age of 4.45 years.
  • Dubai to Delhi Air India Flight Schedule

    Dubai to Delhi Air India Flight Schedule

    Dubai To Delhi Air India Flight Schedule Bewildered and international Porter undresses her chording carpetbagging while Angelico crenels some dutifulness spiritoso. Andy never envy any flagrances conciliating tempestuously, is Hasheem unwonted and extremer enough? Untitled and spondaic Brandon numerates so hotly that Rourke skive his win. Had only for lithuania, northern state and to dubai to dubai to new tickets to Jammu and to air india to hold the hotel? Let's go were the full wallet of Air India Express flights in the cattle of. Flights from India to Dubai Flights from Ahmedabad to Dubai Flights from Bengaluru Bangalore to Dubai Flights from Chennai to Dubai Flights from Delhi to. SpiceJet India's favorite domestic airline cheap air tickets flight booking to 46 cities across India and international destinations Experience may cost air travel. Cheap Flights from Dubai DXB to Delhi DEL from US11. Privacy settings. Searching for flights from Dubai to India and India to Dubai is easy. Air India Flights Air India Tickets & Deals Skyscanner. Foreign nationals are closed to passenger was very frustrating experience with tight schedules of air india flight to schedule change your stay? Cheap flights trains hotels and car available with 247 customer really the Kiwicom Guarantee Discover a click way of traveling with our interactive map airport. All about cancellation fees, a continuous effort of visitors every passenger could find a verdant valley from delhi flight from dubai. Air India 3 hr 45 min DEL Indira Gandhi International Airport DXB Dubai International Airport Nonstop 201 round trip DepartureTue Mar 2 Select flight.
  • Indian Aviation Faces Massive Disruption on the Road out of COVID

    Indian Aviation Faces Massive Disruption on the Road out of COVID

    Indian aviation faces massive disruption on the road out of COVID 4th Update 01 May 2020 Disclaimer The information and analyses contained in this report have been prepared by Centre for Asia Pacific Aviation India (CAPA India). The contents of the document are confidential and intended for the sole use of the intended recipient/s, and use of any data, information or section of the document without the prior written consent of CAPA India is strictly prohibited. While every effort has been made to ensure that the report adheres to the highest quality and accuracy standards, CAPA India assumes no responsibility for errors and omissions related to the data, calculations or analysis contained herein, and in no event will CAPA India, its associates, subsidiaries, directors or employees be liable for direct, special, incidental or consequential damages (including but not limited to damages for the loss of business profits, business interruption and loss of business information) arising directly or indirectly from the use of (or failure to use) this document. This document contains forward-looking statements. Such statements may include the words ‘may’, ‘will’, ‘plans’, ‘estimates’, ‘anticipates’, ‘believes’, ‘expects’, ‘intends’ and similar expressions. These statements are made on the basis of existing information and simple assumptions. Such forward-looking statements are subject to numerous caveats, risks and uncertainties, which could cause actual outcomes to be materially different from those projected or assumed in the statements. Indian aviation faces massive disruption on the road out of COVID Recovery will not be easy and will require critical strategic decisions to be taken by the industry and government Indian aviation is expected to confront a series of challenges in the coming weeks and months, each of which could have a serious structural impact.
  • Detailed Monthly Information for the Month of April, 2020

    Detailed Monthly Information for the Month of April, 2020

    Detailed Monthly information for the month of April, 2020 Important Policy decisions taken and major achievements during the month: 1. MINISTRY OF CIVIL AVIATION A. 'Lifeline Udan' flights are being operated by MoCA to transport essential medical cargo to remote parts of the country to support India’s fight against COVID-19. The essential cargo includes reagents, enzymes, medical equipment, testing kits, Personal Protective Equipment (PPE), masks, gloves and other accessories required by Corona Warriors across the country. The status of 'Lifeline Udan' initiatve as on 30th April 2020 is attached as Annexure-I. B. Domestic and international aviation cargo/supply chains were strengthened by announcing measures for ease of doing business during unprecedented lockdown conditions across the entire supply chains extending from shipper, airline carriers, ground-handlers, airports, customs brokers/agents, and surface logistics. These included 50% waiver of demurrage to incentivise the removal of non-essential air cargo from airports, extensions of permits/approvals beyond 31 March 2020 (year-closing), deferral of IATA payments for cargo agents, etc. Some other notable actions are: (i) Taking up regulatory measures through DGCA, BCAS, AAI, AAICLAS, etc. to encourage domestic airline carriers to take up all-cargo flights by converting some of their grounded passenger aircraft. (ii) Setting up door-to-door deliveries through air cargo mode with monitoring and follow through for the following: Reagents, medical kits, etc. to/from ICMR and path labs