DLF Ltd.

SUBMITTED TO:

Dr. TRILOCHAN TRIPATHY,

Faculty, IBS,

Hyderabad

SUBMITTED BY: (SECTION-E)

RICHA SINGH (09BSHYD0658)

S PUJA MURTHY (09BSHYD0705)

SAUMYA SAXENA (09BSHYD0748)

SHAKTI SAHAY (09BSHYD0763)

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ACKNOWLEDGEMENT

An effort is not complete and successful till the people who make it possible are given due credit

for making it possible. We take this opportunity to thank all those who have made the endeavor

of ours successful. The entire journey from the very idea of this project to reality would not have

been possible without the guidance of many experienced people. We would like to thank our

mentor Dr. Trilochan Tripathy. We thank you for being supportive. This project would not have

completed without your support.

Richa Singh

S Puja Murthy

Saumya Saxena

Shakti Sahay

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TABLE OF CONTENT

1) Real estate and DLF……………………………………………………………4

2) Key driver factors for the growth of DLF……………………..………………5

3) Analysis of demand and supply function………………………………..…….7

4) Demand forecasting of raw materials…………..………………………..…….9

5) Analysis of cost…………………………………………………………….….12

a) Cost function for variable labor and constant input cost………………….13

b) Cost function for variable cost of capital and constant labor cost.........…..13

c) Marginal cost of labor……………………………………………………..14

d) Marginal cost of capital…………………………………………………....15

e) Average of cost of labor…………………………………………..……….16

f) Average of cost of labor……………………………………………….…...17

g) Relation between total cost, average cost and marginal cost……………....18

6) Market structure in which DLF operates………………………………….……21

7) Porter’s Five Forces Model……………………………………………….…...22

8) Nash Equilibrium………………………………………………………….……24

9) Conclusion ……………………………………………………………………..25

10) References ……………………………………………………………………...26

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REAL ESTATE SECTOR AND DLF

India is the 4th largest economy in terms of purchasing power parity. With a growth rate of 9%, it

is found to be in a good shape to expand and grow further. The major factors that induced the

growth rate were the performance of Information technology, Real Estate segment, and healthy

financial conditions apart from the very conducive market initiatives taken up by the

Government of India. The real estate industry is one of the fastest growing industries in our

economy.

Growing at a scorching CAGR of 35% the realty sector is estimated to be worth US$ 90

Billion. It is anticipated to grow at a rate of 30% annually over the next decade, attracting

foreign investment worth US $ 30 Billion .This substantial growth has been the result of

increasing demand from off shoring consulting houses and call centers. Every year 78% of the

money spent on real estate goes to the GDP. About 80% of the real estate development in India

has been in the field of residential housing. The remaining 20% of the real estate includes office,

shopping malls, entertainment centers, hotels, multiplexes and hospitals. Large investments are

underway in areas of: Highway development, Air connectivity (domestic and international), up

gradation of ports with their privatization, power sector.

Real estate developers have been at the forefront of the real estate boom sweeping across the

length and breadth of India. Armed with efficient units of architects, engineers and managers,

builders like DLF have managed to change the skyline of many Indian cities.

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Key Drivers for the Growth of DLF:

Commercial:

Industry Growth: Real estate sector is growing at a rate of 35%.Credit to the housing

sector has continued to be strong and benefited from low interest rates and incentives. In

real estate sector in India, there are high returns up to 12-15% as compared to returns in

advanced countries i.e. 3-5%.Estimated growth up to 90 US$ by 2015.

Special Economic Zones: SEZs likely to be preferred for IT commercial office space

development.

Growth in retail sector, hotels and townships: Spiraling demands for hotel rooms has

brought boom in hotel industry, and the demand-supply mismatch remain over 50%

beyond 09, generating substantial business for DLF. Integrated townships, Spurt in

extremely large retail spaces results in high growth opportunities.

Retail:

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Commercial

IT/ITES,SEZ,growth of the industry.

Retail Sector,Hotels and Hospitals.

Growing Knowledge and Technology Intensive sector

Growing FDI

Growth in organized retail

Rising consumerism

Entry of international retailers

Concept of specialized malls gaining popularity

Tourism:

Increase in International tourist arrivals

Growth in domestic tourism

Low cost airlines and improvement of airports

Medical tourism

Tremendous potential for budget hotels

Growing Knowledge and technology driven sector: Demand for higher level

education, professional trainings, better infrastructural facilities have given a boost to

DLF’s business. The robust growth in IT sector has pumped up the growth in real estate

sector, approx 60% of new construction is for IT sector resulting in major projects for

DLF.

Growing FDI: FDI regulations are liberalized, and 100% FDI is allowed under

automatic route in townships, housing, built up infrastructure and construction

development projects. Venture capitalists are also allowed investing in India, giving a

boost to its operations. The Reserve Bank of India announced a special stimulus package,

to allow banks to provide special treatment to real estate sector. It has decided to extend

exceptional concessional treatment from June 30th, 2009.

o Area for integrated townships increased.

Minimum capital investment decreased.

Full repatriation of original investment after 3 years.

Residential:

Urbanization: According to the United Nations Population Fund (UNFPA) By 2030

more than 40.7% of Indian population would be urbanized. Presently, more than 28.7

per cent of India’s area is urban as against the global average of 48.7 per cent. India’s

‘Mega-Cities’ of Mumbai and Delhi would be the world’s 2nd and 3rd largest cities by

2015, which is a big time demand driver for DLF.

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Growth in per capita income: India’s per capita income is expected to be US$ 693 this

year and is further expected to grow by 8-13 per cent in the next five years, particularly

due to growth in the services sector, which thereby results in increase in demand for the

residential sector.

Rising first time buyers and increasing household: With an increase in per capita

income, the number of first time buyers also increases resulting in up thrust in the

demand.

Analysis of Demand and supply function for DLF

Demand side analysis: There are various other factors which affect the demand. Based on these

factors we can derive the demand function for DLF.

D=F (I, P, Cb, Cr, T, Ps)

D=demand for DLF; I= Income of consumers; P=price of housing; Cb= cost of borrowing;

Cr= availability of credit; T= Consumer preferences; Ps= price of substitute and complement.

Rising income levels of a growing middle class along with increase in nuclear families, low

interest rates, modern attitudes to home ownership (average age of a new home owner in 2006

was 32yrs compared with 45yrs a decade ago) and a change of attitude among the young

working population from that of ‘save and buy’ to ‘buy and repay’ have all combined to boost

housing demand.

Growth in commercial office space requirement is led by the joining outsourcing and

information technology industry and organized retail. Rising middle class and its consumer

demand is driving the retail boom- around 11malls is under development by DLF.

SUPPLY SIDE ANALYSIS: The factors determining supply of real estate can be stated in the

form of a supply function.

S= F (P, A, B, Cr, L)

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S= supply of real estate property; P= Price of the property; A= Availability of land; B= efficient

builders; Cr= easy accessibility of credit; L= Skilled labor

The residential sector which accounts for 75-80% of the turnover has been on a high growth

path. According to the ministry of housing and urban poverty alleviation there is a shortage of

24.7 million houses in the country. So far, the situation in both the office and residential market

has been that whatever is billed gets sold or rented. In future, as supply increases, DLF has to be

more careful about factors like location and target those segments for which they are developing

the products. In this supply rich environment, accurate demand estimates will become very

important.

DEMAND PULL

FACTORS

IMPACT SUPPLY PUSH

FACTORS

IMPACT

Robust and

sustained growth

Upsurge in

industrial activities

Favorable

demographic

parameters

Rise in

consumerism

Rapid urbanization

Increasing

occupier base

Rise in demand

for industrial

space

Demand for new

avenues

Creation

demand for new

housing

Policy and

regulatory

reforms

Positive outlook

of global

investors

Infrastructure

support and

development by

government

Entry of domestic

and foreign players

Improved quality of

real estate assets

Large scale

development

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Demand forecasting of raw material

A method to estimate future value on the basis of past information is called demand forecasting.

Generally demand forecasting is done for either estimating the future sales or estimating future

requirement of inventory or raw material.

Here demand forecasting for raw material for the “quarter 30-Jun-09” has been done on the basis

of last four quarters. First, a relation has been established by using regression tool, where the

coefficient of intercept and the coefficient of sales (which is the independent variable) were

found.

Data:

Quarter Ended Net Sales/Income from Operations

31-Mar-09 5553 -9276

Consumption of Raw Materials

Based upon above data, the coefficient of determination, the coefficient of intercept and the

coefficient of sales is given below:

Quarter Ended

From the above figures demand of raw materials for the quarter 30-Jun-09 has been calculated

by the formula:

Forecasted raw materials= -3749.134+ 0.3310* 41797

[Where: 41797= sales of quarter 30-Jun-09]

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Net Sales Forecasted Value Actual Value30-Jun-09 41797 10086.6590470936 12756

It can be seen that the forecasted value is very near to the actual value. It can therefore be

concluded that consumption of raw material is dependent upon the sales and can therefore be

forecasted for proper utilization.

PRICE ELASTICITY OF DEMAND

Price elasticity of demand is a measure of how much the quantity demanded of a good responds

to a change in the price of that good. It is defined as the percentage change in quantity demanded

divided by the percentage change in price.

Assumption:

As the demand figure is not available so the sales figure can be used.

As the individual cost of raw materials is not available therefore total cost of production

is used.

Data:

Sl. No. Year total cost sales (Cr.) projected1 Mar '00 105.01 184.39 -52.9554622 Mar '01 161.68 179.98 81.40009913 Mar '02 293.59 280.03 394.1377384 Mar '03 254.19 244.96 300.7266025 Mar '04 435.5 495.8 730.5837886 Mar '05 342.04 412.23 509.0049867 Mar '06 644.28 953.46 1225.567988 Mar '07 434.5 1,101.66 728.212946

Here it can be seen that projected sales has been calculated using total cost and actual sales to

establish price elasticity of demand by using regression tool.

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Sl. No. Year total cost1 Mar '00 105.012 Mar '01 161.683 Mar '02 293.594 Mar '03 254.195 Mar '04 435.5

It can be seen that the coefficient of determination is very high.

Mar '00 Mar '01 Mar '02 Mar '03 Mar '04 Mar '05 Mar '06 Mar '07 Mar '08-500

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

5500

6000

projected

sales (Cr.)

Also from the figure it can be concluded that demand varies with change in price that is demand

is relatively price inelastic.

Demand is relatively inelastic because of the following reasons:

Large number of close substitutes (like Indiabulls Real, GMR infra,

Parsavnath, and other local construction companies).

Real estate comes under both necessity and luxury.

Time period is very long and therefore demand becomes elastic.

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ANALYSIS OF COST

Cost curve shows the relationship between the quantity of output produced and the total cost of

production. The total cost curve gets steeper as the quantity of output increases because of

diminishing marginal product.

Assumption:

We have not considered the Depreciation, financial services, net fixed assets, interest

paid and employee compensation costs, as they do not directly affect the cost of

production.

Since we are considering the short run cost process, we have shown the AC, MC and

TC analysis keeping one of the variables fixed at a time.

The sales value of the unit product is constant through out the period.

All the employees are considered to contribute to the cost of the product.

The input cost is constant and is considered to be the same through out the period.

Data:

Sl. No. Year employee cost (Cr.) Total input cost (Cr.) sales (Cr.)1 Mar '00 10.33 94.68 184.392 Mar '01 15.46 146.22 179.983 Mar '02 14.19 279.40 280.034 Mar '03 15.49 238.70 244.965 Mar '04 21.4 414.10 495.86 Mar '05 33.32 308.72 412.237 Mar '06 16.76 627.52 953.46

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Cost function for variable labor and constant input cost (K constant):

Mar '00 Mar '01 Mar '02 Mar '03 Mar '04 Mar '05 Mar '06 Mar '07 0

200

400

600

800

1000

1200

Sales (Rs. Cr)

employee cost (Cr.)

In short run some inputs cannot be varied for a certain period of time. This period varies from

one firm to the other. As seen from the graph that as the no of employees in a firm increases the

output or the sales of the firm also increases. Due to huge difference in scale it is not clearly

visible.

Cost function for variable cost of capital and constant labor cost (Labor constant)

Mar '00 Mar '01 Mar '02 Mar '03 Mar '04 Mar '05 Mar '06 Mar '07 0

200

400

600

800

1000

1200

Sales (Rs. Cr)

Total Input Cost (Rs. Cr)

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As seen from the graph that as the cost of capital employed in a firm increases the output or the

sales of the firm also increases.

Marginal Cost of Labor (MC of labor):

3) Marginal Cost of Labor (MC of labor)

Sl. No. Year employee cost (Cr.) Sales (Rs. Cr) Change in LaborMar '00 10.33 184.39 0 0

2 Mar '01 15.46 179.98 5.13 -4.41 -0.859653 Mar '02 14.19 280.03 -1.27 100.05 -78.77954 Mar '03 15.49 244.96 1.3 -35.07 -26.97695 Mar '04 21.4 495.8 5.91 250.84 42.44332

Change in Sales (Rs.

Cr)

Marginal Cost of

employee(Rs. Cr)

Mar '00

Mar '01

Mar '02

Mar '03

Mar '04

Mar '05

Mar '06

Mar '07

0

200

400

600

800

1000

1200

Sales (Rs. Cr)Total Input Cost (Rs. Cr)

In the table above, marginal cost of employee has been calculated.

Mar '00 Mar '01 Mar '02 Mar '03 Mar '04 Mar '05 Mar '06 Mar '07 Mar '08

-100

-80

-60

-40

-20

0

20

40

60

80

100

Marginal Cost of employee(Rs. Cr)

Marginal Cost of employee(Rs. Cr)

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Marginal cost is specified as the change in total cost divided by the change in the quantity of

output produced.

Graph is drawn based upon the calculation above. It can bee seen that there is an upward trend in

the graph. However the upward trend is not smooth. This could be because of the nature of

business where there is no need of too many employees and the labor working at the construction

site are employed on daily wage basis.

Marginal Cost of capital (MC of capital):

4) Marginal Cost of capital (MC of capital)

Sl. No. Year Sales (Rs. Cr) Change in CostMar '00 94.68 184.39 0 0

2 Mar '01 146.22 179.98 51.54 -4.41 -0.085563 Mar '02 279.40 280.03 133.18 100.05 0.7512394 Mar '03 238.70 244.96 -40.7 -35.07 0.8616715 Mar '04 414.10 495.8 175.4 250.84 1.430103

Total Input Cost (Rs. Cr)

Change in Sales (Rs.

Cr)MC of Capital

The table above gives marginal cost of capital employed figure.

Mar '00 Mar '01 Mar '02 Mar '03 Mar '04 Mar '05 Mar '06 Mar '07 Mar '08

-1

-0.5

0

0.5

1

1.5

2

2.5

Chart Title

MC of Capital

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The U-shape of the marginal cost curve is a direct reflection of first increasing marginal returns,

as marginal cost falls to a minimum, then decreasing marginal returns and the onset of the law of

diminishing marginal returns as marginal cost rises.

As it can be seen that there is steady rise in the marginal cost curve. However during the period

2006-07 due to a sudden surge in the demand of real estate the cost of production decreased

drastically because of economies of scale. Again from the end of 2007 there is a sharp increase in

marginal cost. This was because of recession and inflation, in turn due to which raw materials

became expensive thus increasing the cost of capital.

Average Cost of Labor (AC of labor):

5 Mar '04 414.10 495.8 175.46 Mar '05 308.72 412.23 -105.387 Mar '06 627.52 953.46 318.88 Mar '07 389.68 1,101.66 -237.849 Mar '08 2,315.07 5,496.96 1925.39

5) Avarage Cost of Labor (AC of labor)

The table gives the average cost of employed.

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Mar '00 Mar '01 Mar '02 Mar '03 Mar '04 Mar '05 Mar '06 Mar '07 Mar '080

10

20

30

40

50

60

Chart Title employee cost (Cr.)

In general, average cost is simply the cost per unit of output. It is the total cost divided by the

total quantity produced. It can be seen that till 2005 average cost was steady but it suddenly

started showing irregular trend. However nothing much can be inferred from the graph as there is

no particular relation fitting.

Average Cost of Capital (AC of capital):

6) Avarage Cost of Capital (AC of capital)

Sl. No. Year Sales (Rs. Cr) AC of Capital1 Mar '00 94.68 184.39 1.94750739332 Mar '01 146.22 179.98 1.2308849679

Total Input Cost (Rs. Cr)

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Mar '00 Mar '01 Mar '02 Mar '03 Mar '04 Mar '05 Mar '06 Mar '07 Mar '080

0.5

1

1.5

2

2.5

3

AC of Capital

AC of Capital

The curve shows a normal average cost of capital graph as it is a “u” shaped. In the initial years

it is decreasing but in the later years it has started increasing.

Relation between Total Cost, Average Cost and Marginal Cost for constant cost of labor:

9 Mar '08 2,315.07 5,496.96 2.3744249634

7) Relation between Total Cost, Avarage Cost and Marginal Cost for constant Labor (TC, AC and MC for consant Labor)

Sl. No. Year1 Mar '00 1.8439 1.94750739332 Mar '01 1.7998 -0.085564610011641 1.2308849679

Total Cost (Rs. 100 Cr)

Marginal Cost of capital (Rs. Cr)

Average Cost of Capital

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Mar '00 Mar '01 Mar '02 Mar '03 Mar '04 Mar '05 Mar '06 Mar '07

-2

0

2

4

6

8

10

12

Average Cost of Capital

Marginal Cost of capital (Rs. Cr)

Total Cost (Rs. 100 Cr)

A curve that graphically represents the relation between the total costs incurred by a firm in the

short-run production of a good or service and the quantity produced. The total cost curve is a

cornerstone upon which the analysis of short-run production is built. It combines all opportunity

cost of production into a single curve, which can then be used with the total revenue curve to

determine profit. The marginal cost curve, the focal point for the analysis of short-run

production, is derived directly from the total cost curve. The shape of the curve reflects

increasing marginal returns at small quantities of output and decreasing marginal returns at larger

quantity. .

It can be seen from the graph that when marginal cost exceeds average cost, average cost must be

rising. When marginal cost is less than average cost, average cost must be falling. Also the

position of the marginal cost relative to average total cost tells us whether average total cost is

rising or falling. The short-run marginal cost curve will at first decline and then will go up at

some point, and will intersect the average total cost and average variable cost curves at their

minimum points. This however is not clearly visible from the figure as there are other factors

also involved in changing the curve.

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Relation between Total Cost, Average Cost and Marginal Cost for constant cost of capital

4) Marginal Cost of capital (MC of capital)

Sl. No. Year Sales (Rs. Cr) Change in CostMar '00 94.68 184.39 0

2 Mar '01 146.22 179.98 51.543 Mar '02 279.40 280.03 133.184 Mar '03 238.70 244.96 -40.75 Mar '04 414.10 495.8 175.4

Total Input Cost (Rs. Cr)

Mar '00 Mar '01 Mar '02 Mar '03 Mar '04 Mar '05 Mar '06 Mar '07 Mar '08

-100

-80

-60

-40

-20

0

20

40

60

80

100Marginal Cost of employee(Rs. Cr)Average Cost of employeeTotal Cost (Rs. 100 Cr)

The short-run marginal cost curve will at first decline and then will go up at some point, and will

intersect the average total cost and average variable cost curves at their minimum points.

The average variable cost curve will go down (but will not be as steep as the marginal cost), and

then go up. This will not go up as fast as marginal cost curve. The average fixed cost curve will

decline as additional units are produced, and continue to decline. The average total cost curve

initially will decline as fixed costs are spread over a larger number of units, but will go up as

marginal costs increase due to the law of diminishing returns.

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Market structure in which DLF operates

Real estate in India follows an oligopoly type market structure with the following characteristics-

Real estate sector is quite fragmented with most players having presence limited to select cities

or regional geographies & relatively few players having national presence. Larger regional

developers increasing their footprints across the country include Ansals, DLF, Raheja group,

Parsavnath developers, Unitech, Vatika group.

Homogeneous but differentiated products

The real estate companies’ main offering is buildings to the customers. The basic product

is same for all the major players in India. The differentiating factor is the package

offered by these players like the location, add on facilities, premium apartments etc. So

we can say the offering given by the players is homogenous but differentiated.

DLF’s ship-shaped Gateway Towers in Gurgaon, a 12-storey complex, has become a

landmark of sorts for its unique architectural design. DLF Nestle House has been

designed aesthetically together with functional efficiency. Product differentiation is very

important as a developer has to cater to all classes of the society. These projects are very

different from other projects in all aspects - architecture, quality and developmental

mix - and are targeted towards the niche segment.”

High entry barriers

According to the JLLM report, there is low availability of land banks due to which

about use bank loans for purchasing land parcels, capital raised through private

placements, foreign investments & funds are being used largely for land purchases. Also

initial capital outlay for new entrants is very high and not many firms can afford it.

Long gestation periods

The market adjustment process is subject to time delays due to the length of time it

takes to finance, design & construct new buildings and also due to the relatively slow rate

of change of demand. Because of these lags there is a great potential for disequilibrium in

the short run. Adjustments mechanisms tend to be slow, relative to more fluid markets.

Both investment and consumption good

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Real estate can be purchased with the expectation of attaining a return (an investment

good), or with the intention of using it (consumption good) or both. These functions can

be separated (with participants concentrating on one or the other function) or can be

combined (in the case of the person who lives in a house that they own). This dual

nature of the good means that it is uncommon for people to over invest in real estate,

that is, to invest more money in an asset than it is worth on the open market.

Few dominant firms

Oligopolists are often large firms, each producing a significant portion of total market

output like DLF has 24.38% of the total real estate market, and other players like

unitech & ansals also hold a major share in the market. Also very few firms have a

national presence in India like Ansals, Unitech, parsvnath developers and K. Raheja.

Porter’s five forces model

Porter’s competitive framework represents the relationship between profitability and efficiency

faced by the firms while operating in an oligopolistic kind of market. It includes three forces

from ‘horizontal competition’: threat of substitute products, threat of established rivals and the

threat of new entrants and two forces from ‘vertical’ competition: the bargaining power of

suppliers, the bargaining power of consumers.

Porters Competitive Framework

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Profitability Of Firms

threat from substitute

threat of entrybargaining power of

buyersbargaining power of suppliers

threat from existing rivals

Threat of new entrants: Profitable markets that yield high returns will draw firms. This

results in many new entrants, which will effectively decrease profitability. But in real

estate sector entry barriers are high because the working capital requirements are

high. Moreover, the existing firms have the advantage over others due to learning curve

advantages. This can be seen in the case of DLF which started in 1946 and developed

DLF city in 1985 and in 2008 they opened up the first luxury mall. The gestation period

is very long so investors will not be induced to invest.

Threat of established rivals: 25% of the market share is held by the DLF in the real

estate sector. This shows that the competition is high in this sector with DLF, Unitech,

and Ansals being the major players. This may prove to be a threat to upcoming players,

as the established players are deep rooted in the industry. Though this threat shall not be

faced by DLF as it holds the major market share.

The bargaining power of suppliers: It is low. Due to the increase in the number of

contractors or service providers, margins have been stagnant despite strong growth in

volumes. The number of suppliers is large so if one will increase the cost than there

will be a shift from one contractor to another.

The bargaining power of buyers: It is low. The country still lacks adequate

infrastructure facilities and citizens have to pay for using public utilities. It is very

difficult to predict the direction and magnitude of price movement on real estate.

One can only assume that forces of demand and supply would always apply and price

movement would follow accordingly.

Threat of substitute product: There are no substitutes to the basic product so there is

not any threat of substitute products.

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Nash Equilibrium

This is a situation where each player chooses an optimal strategy, given the strategy chosen by

other players in the market. DLF also operates under the same kind of equilibrium. The ultimate

value of commercial real estate emanates from its rental flow, which reflects the in price the

market is willing to pay for the use of space. The developers formulate their

construction/exercise strategies in a world in which the demand for space is stochastic, and

where the construction strategies of their competitors impact the payoff from their own

strategies. Thus, the inputs of the equilibrium are the degree of competition in the market, the

impact of competitive development, and the stochastic process driving the demand for space.

The outputs of the equilibrium are the processes for construction starts, short-term rents,

building values and land values.

Say for e.g.: For office space the demand might be driven by job growth. For industrial space

demand might be driven by changes in industrial production. For hotel space demand might be

driven by changes in disposable income.

At any point in time, each firm can develop new rentable units at a cost of K per unit of space.

New development represents an increase in space. Thus, the path of output is continuous, and if

all firms increase capacity simultaneously, the optimal development decision must be part of an

endogenous, Nash equilibrium. Each firm chooses its supply process strategy so as to maximize

its value, conditional on the assumed supply processes of its competitors.

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CONCLUSION

Reality sector has seen an increase in competition with the emergence of some of the big players

like DLF, Unitech, GMR, and Ansals. This has brought a sort of price war among them with no

individual player in position of dictating the terms. Even DLF, the market leader has not been

able to set a competitive price to beat its competitors. The Oligopolistic nature of market has

prevented DLF to gain considerable competitive edge. The recent economic downturn saw profit

of all the real estate companies go down.

Real estate price bubble that was assumed to burst in the recessionary cycle did not burst. The

sky high prices of real estate that should have come down did not come down. However a

consolidation phase was seen in the last few quarters. But share prices and profit margins of few

of the big giants eroded considerably. Net profit of DLF declined 85.68% to Rs 100.40 crore in

the quarter ended June 2009 as against Rs 700.99 crore during the previous quarter ended June

2008. Sales declined 67.31% to Rs 417.97 crore in the quarter ended June 2009 as against Rs

1278.61 crore during the previous quarter ended June 2008. DLF had to restructure about

Rs2000 crore of short- and long-term loans out of its Rs16358 crore debt by selling a stake worth

Rs2,200 crore. Even Unitech had to raise Rs1620 crore through a qualified institutional

placement and still the firm currently has Rs7800 crore of debt. Ansal’s (API) revenues also fell

21% during Q3FYE09. It also reported a consolidated loss of Rs. 156m for Q309 as against

profit of Rs. 522m in Q308.

Their condition however is fast improving on the back of improving economy. DLF has even

started looking for new investments; the recent land acquisition of 350 acres in Gurgaon is one

such investment. The economic recovery is likely to reinvigorate the interest of foreign investors in

India's real estate market with an enhanced capital inflow in the real estate sector in the medium-to-long-

term. We can thus expect to see competition in real estate sector heating up with a renewed price war.

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REFERENCES

1. www.dlf.in

2. en.wikipedia.org/wiki/environmental scanning

3. www.allbusiness.com/glossaries/macroenvironment/4954903-1.html

4. www.valuenotes.com

5. www.moneycontrol.com

6. www.rediffmoneywiz.com

7. Prowess database

8. http://www.investopedia.com/

9. http://www.indianrealtynews.com/

10. http://headlinesindia.com/

11. http://www.brint.com/

12. http://www.allbusiness.com/

13. http://www.emkayresearch.com/

14. http://www.dlfindia.com/

15. http://www.livemint.com/2009/06/24005439/DLF-Unitech-show-path-to-beat.html

16. http://in.reuters.com/article/domesticNews/idINNWNA728420090224

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