MANAGERIAL ECONOMICS
PROJECT: ONLINE TRAVEL INDUSTRY
GROUP MEMBERS:
Nikita Goenka (PGP30324)
Padmaja Agnihotri (PGP30316)
Sandeep Kumar (ABM11034)
Ravali Malka (PGP30317)
Vishwas Nandan (PGP 30353)
Saurav Kumar (PGP30340)
Rohan Kokane (PGP30336)
BACKGROUND
India is a country with vast demography and a wide spectrum of opportunities. Better job avenues have gifted the youth with greater discretionary power. Rising use of internet & plastic money has made the field of e-commerce an exponentially growing field in recent times.
Why E-Travel as a subject of research?
E-travel in India has a lion’s share in the Indian E-commerce contributing to a whopping 82% to the entire market share in the year 2013 (Graph 1). Also, E-travel exhibited a marvelous annual growth of 53% in 2013 over 2012. This is further complemented by the fact that the Indian tourism industry is the 2nd fastest growing in the world. The present paper aims at unravelling various facets of this booming industry and studying its position in the private sector, especially e-commerce industry.
Other merits:
Online travel demands least capital & infrastructure costs
Quick delivery of services enhances consumer satisfaction
EVOLUTION
Based on the single idea of easing travelling in India, online travel services started around a decade ago. Booming of IT sector in India was one of the major factors stimulating online travel. Online travelling segment constitutes around 70% – 80% ($25 billion) of all e-commerce activities and has been a major driver of the industry. Key schemes and policies implemented by e-commerce industry can be considered as major factor for success of the segment. Exhaustive assistance, user friendly websites, customer grievance redress are the major attractions prevailing in the segment. Makemytrip, Yatra.com, Redbus are some websites which have seen rocketed growth as presented in Graph 2 and Graph 3.
PRICE ELASTICITY OF DEMAND
Price Elasticity is defined as percentage change in demand due to one percent change in price. Online travel industry faces more level of price sensitivity than traditional channels, majorly because of ease of access to-
PRODUCT INFORMATION
PRICE INFORMATION
CHANNEL SELECTION
FORWARD LINKAGES:
Nowadays Travel industry is not restricted to its conventional travel business only. It has extended to forward linkages like bus tickets, travel insurance firm & hotels. Share of each linkage has been presented in Graph 4
Regulations Introduced by the government and its impact:
The regulatory norms laid down by the government of India are aimed at promoting growth of the market which have effect on the online travel industry. With the customers slowly moving from traditional ways of booking to online, these norms have greatly influenced the growth of online travel industry.
A few regulatory norms laid are as follows:
COST STRUCTURE:
The cost structure of online travel can be analysed in two ways:
Traditional costing analysis through study of the P&L statement
ABC (activity based costing ) by analyzing the cost driver for each specific segment
The following sections explains both the above stated viewpoints:
Traditional costing analysis:
The income statements of various big players of the online travel industry are available for study. One such player is Makemytrip.com, a leading firm in online travel.
Graph 5 summarizes the various expenses of Makemytrip for 4 consecutive years in descending order.
Activities of online travel:
The various activities of online travel have been are categorized as:
and
The activities are studied considering their respective drivers in terms of the resources allotted and other factors such as time and space devoted etc.
PRODUCTION STRUCTURE
Online travel industry offers services to its customers as a product. There are various types of services which online travel industry offers:-
Core services
Air, Rail and hotel advance bookings and ticketing
Discount fares program
Event management service
Value added services
Tracking of journey
24 hours emergency service
Ticket approval using email system
Insurance
Graph 6: Traffic generated from mobile devices.
Graph 7: Reach of travel portals (India and Global)
Graph 8: Profit Margin by segments
PRODUCTION FUNCTION
A production function gives relationship between inputs (capital, labour and other factors) and outputs (goods and services). Online travel agency have high initial and fixed cost which it makes as less labour intensive sector.
U= U (P, Y)
Y= F (K, L)
Where U = utility function of cost (P) and trips (Y)
F = Production function of capital (K) (travel agencies)
In short run, if labour is increased, the performance and maintenance of the online portal will be improvised. So this in-turn might increase number of trips for some time period then falls as online travel agency is more technology based and improving labour doesn’t increase much of output.
In long run, an improvement in the state of technology shifts the production function up, leading to an increase in output per worker for a given level of capital per worker. The higher the technology, higher Y for a given K and L. An improvement in the state of technology shifts the production function up, leading to an increase in output per worker for a given level of capital per worker
COST FUNCTION
Cost function is effect of level of production on the cost which the firm is incurring. Since in online travel industry we don’t have any such physical product, we can relate the level of production with the sales generated by company.
Cost analysis for Thomas Cook has been done in Table 1 and Graph 9.
TABLE – 1: Thomas Cook- Average and Marginal cost of the service delivered
Year
Sales
(INR in mn)
Total Cost
(INR in mn)
AC
MC
2010
3455
3086
0.8932
2011
4017
3094
0.7703
0.01
2012
4386
3300
0.7524
0.557
2013
13031
10269
0.7881
0.80
Source: www.securities.com/emis/ Industry- Online travel
Graph 9: Cost analysis for Thomas Cook (All money figures are in INR million)
Inferences:
The data given in Table 1 shows the average and marginal cost of the service delivered. From graph 9 we can see that the average cost reaches a minimum value of 0.45 at a sales value of INR 8700mn approximately. As the scale of operations of Thomas Cook went up beyond this point the average cost also increased. Clearly it is evident that the company isn’t operating at its minimum cost point. Due to sudden increase in scale of operations, the company might not have optimized its value chain.
REGRESSION ANALYSIS
IRCTC E-ticket booking:
IRCTC started its e-ticket booking facility from 2005 August. By that time there was already i-ticket booking in IRCTC where tickets will be delivered through courier to the house after booking through internet. Once IRCTC launched E-ticket booking, the sales through I-ticketing started declining and this new facility increasing sales of IRCTC. Number of people using internet in 2012 is 11.4% of total population as compared to 4.5% of total population in 2005. This rapid growth in internet users resulted in increment of number of tickets booked through IRCTC.
Graph 10: Regression Analysis for IRCTC E-ticket booking
Inferences:
In 2005, internet Company Sify had announced its tie up with Indian Railway Catering and Tourism Corporation (IRCTC) to make online railway ticketing service available at over 3,400 iWay cybercafés across 154 cities, on cash payments.
In 2008, With 8 lacs tickets sold every day on its website, IRCTC had announced its expansion policy to give services and sell airline tickets.
With overall increase in train travel quality and increase in train travelling, e-tickets are in demand.
PROFIT OR LOSS ANALYSIS:
MAKE MY TRIP
www.moneycontrol.com
Year
Revenue
Total Cost
Profit
2011
$124,721.00
$119,891.00
$4,830.00
2012
$196,599.00
$189,951.00
$7,048.00
2013
$228,822.00
$256,411.00
($27,589.00)
2014
$255,375.00
$276,281.00
($20,906.00)
Graph 11
Inferences:
Based on the above analysis MakeMyTrip has achieved its break-even point somewhere in between 2012 and 2013.
After that point it has been experiencing losses.
PROFIT OR LOSS ANALYSIS
THOMAS COOK
www.moneycontrol.com
Year
Revenue(In Cr.)
Total Cost(In Cr.)
Profit(In Cr.)
2009
242.00
184.00
58.00
2010
282.00
193.00
89.00
2011
340.00
232.00
108.00
2012
386.00
270.00
116.00
2013
383.00
267.00
116.00
Graph 12
Inferences:
From above graph, Thomas cook has passed its break-even point and has been experiencing profits for last 5 years.
APPENDIX
Graph 1: E commerce Market share
Graph 2: Growth trend in the online travel market Graph 3: Percentage of online users
Graph 4: E commerce market share (including the forward linkages)
Graph 5: Summary of expenses of Makemytrip for 4 consecutive years in descending order:
Source : http://www.nasdaq.com/symbol/mmyt/financials?query=income-statement
Graph 6: Traffic generated from mobile devices Graph 7: Reach of travel portals
Segment
% age
Air Travel
7
Train Travel
5
Bus Travel
12
Car Rentals
15
Hotels tours and Packages
20
Graph 8: Profit Margin by segments – 2013
Source: E & Y
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