FIVE FORCE MODEL IN THEORY AND PRACTICE: ANALYSIS …

Volume:01, Number:04, August-2011 82 www.theinternationaljournal.org

FIVE FORCE MODEL IN THEORY AND PRACTICE: ANALYSIS

FROM AN EMERGING ECONOMY

Baragur Venkateshiah Krishnamurthy

Professor,

Strategy and International Business

RAMAIAH INSTITUTE OF MANAGEMENT STUDIES

ABSTRACT

For thirty years, the five-force model of Michael Porter has been used as a standard tool to

analyze and determine industry attractiveness. In a recent interview to mark thirty years of

the theoretical framework, Porter reaffirmed his faith in the model, quoting examples from

the airline and steel industries. The model along with the others that Porter has developed,

such as the value chain, strategic groups and national competitive advantage, continue to

influence strategic thinking in profound ways. And yet, one cannot help observing that

perhaps the time has come to re-examine these models in the light of empirical evidence.

This paper attempts to argue that the usefulness of the five-force model is limited in emerging

economies as compared to mature markets. A longitudinal study of the IT Enabled Services

Industry in India demonstrates that with low entry barriers, a high degree of competition

(industry rivalry), bargaining power of buyers (Fortune 100 companies), bargaining power of

suppliers (large manufacturers of hardware who force technological up gradation at regular

intervals), and the absence of clear differentiators (or close substitutes being offered), the

industry should have been very unattractive according to the five-force model. On a practical

level though, the paper shows that the major players in the industry have all been able to turn

in stellar performances year after year. With this apparent dichotomy between theory and

practice, the paper questions the usefulness of depending on one model for all situations.

Volume:01, Number:04, August-2011 Page 183 www.theinternationaljournal.org

INTRODUCTION:

The five-force model of competition was first introduced by Porter in 1980 in his book on

Competitive Strategy. For 30 years since the concept was first outlined, the model has been

considered an important tool in understanding industry structures and analyzing industry

attractiveness. In a recent video interview, Porter has emphasized his faith in the model and

has provided examples from the airline and steel industries to argue that the model is

universal. The model is an integral part of books on management in general and on strategy

in particular. Thus, the five-force model can be seen as a torch-bearer of robust theory.

The question however arises as to whether the model is equally applicable in all situations.

Should managers use this as the ultimate tool in formulating strategy? To understand the

practical implications, the author has studied a number of industries from an emerging

economy, India. For many years, India has shown a robust growth of 9% per year and even in

the midst of a global recession, has managed a decent growth of about 6%. Against this

scenario, an attempt has been made to test the efficacy of the five-force model on a variety of

industries. This is a work-in-progress and the results from one industry are presented in this

paper. The initial results seem to indicate that managers need to exercise caution while using

the model. Particularly in the context of emerging economies, the results obtained so far seem

to suggest that a re-thinking of the model may be necessary. This interesting but paradoxical

intersection of strategy theory and strategy practice is the focus of this paper. Obviously, a lot

more needs to be done in terms of gathering data not only from the Indian context but also

from other economies notably China, Korea, Brazil, Russia, and the ASEAN countries before

more forceful conclusions can be drawn. The author’s hope is that the findings would

stimulate objective discussion on the scope of interpreting theoretical frameworks in practical

situations.

THE MODEL IN BRIEF:

The five forces identified by Porter are:

Threat of new entrants

Industry rivalry (consolidated vs. fragmented industries)

Bargaining power of buyers

Bargaining power of suppliers

Threat of substitutes

Some experts have sought to introduce a sixth force – complementors – while others have

argued in favor of including the government. Since the focus of this paper is the five-force

model, the embellishments suggested have not been considered.

Considerable details are available on each of the forces and their possible impact on an

industry. It would be redundant to reproduce all the myriad dimensions. Merely as

illustrations, the bargaining power of suppliers is supposed to be high when the industry is

dominated by a few large suppliers, the customers are small and fragmented, there are no

substitutes for the product being supplied, switching costs are high, and suppliers have the

capability to integrate forwards. The bargaining power of buyers is a mirror image of the

bargaining power of suppliers. The threat of new entrants is a function of entry barriers.

Porter has cited the example of the airline industry as being extremely unattractive and the


aerospace industry as attractive precisely due to the low and high entry barriers of these

industries. Initial investments, scale economies, brand loyalty, scarcity of critical resources

and the extent of access to raw materials and distribution channels have all been identified

under the threat of new entrants and entry barriers. The threat of substitutes is high when

alternatives are available with similar functions but a lower price, or better functions at the

same price. When technology drives markets, the threat of substitutes is perennial and

imminent. Industry rivalry is generally plotted on a continuum from consolidated (a few,

large companies) to fragmented (a large number of small companies). Consolidated industries

are considered to be relatively immune from cyclical fluctuations while fragmented industries

are portrayed typically as going through boom-and-bust cycles.

USES OF THE MODEL:

Commentators are agreed that the model has uses for strategic planners in one or more of

three aspects of the planning process:

Statistical Analysis – decisions relating to entry into or exit from an industry or even

market segment; comparison with competitors; impact analysis of decisions by

organization or by competitors.

Dynamic Analysis – Combined with an environmental analysis, the model can be used to

forecast the potential future attractiveness of an industry; alternate scenarios can be built

and their outcomes can be extrapolated.

Analysis of Options – With the knowledge available from the first two types of analyses,

organizations can determine which of the options to follow to derive competitive

advantage.

The five-force model is steeped in microeconomics. It considers factors like supply and

demand, complementary products and substitutes, relationship between volumes and costs,

and market structures such as monopoly, oligopoly or perfect competition.

Suggestions have also been made to mitigate the effect of the forces. Buyer or Supplier

bargaining power can be reduced through partnering, elimination of intermediaries and

increased dependency. New entrants can be blocked through scale and scope economies,

brand loyalty and tie up with other players of the value system. Rivalry can be reduced by

avoiding price competition, looking for new ways to differentiate, and by having a constant

dialogue with competitors. The threat of substitutes can be reduced by increasing switching

costs, buying out potential substitutes and by accentuating differences (real or perceived).

CRITICISMS:

Major criticisms of the model include the following:

From an economic standpoint, the model assumes a classic perfect market, something that

may not exist in the real world

The model is most useful for analyzing simple market structures. A comprehensive

analysis of all the forces in complex industries with interrelationships is very difficult if

not impossible for managers

The model assumes static market structures. In today’s dynamic structures with rapid

technological change, with consequent irrelevance of one or more of the forces, the model

may not provide sufficient insights for preventive action


The model assumes competition as a driving force with organizations trying to derive an

advantage at the expense of others. This is hardly the case today with coopetition often

holding the key, strategic alliances becoming ever more popular, and virtual networks

being a reality.

Specifically, Porter’s model represents the classical view. The Resource Based View

identifies a firm’s internal competencies as being critical to success. Rumelt (1991) has

shown that industry factors can explain only 9 – 16% of variations in profit. Teece (1997)

has further extended the argument to emphasize the dynamic nature of industries and the

futility of applying static industry structures.

Porter (1996) has defended the model and argued that good positioning still matters. In

contrast, Hax (2002) has shown with the Delta Model that there is more to strategy than

positioning.

Whittington (2001) has pointed out how Porter (1980) “blithely relegates his assumption

of profit objectives to a footnote, and concentrates his industry analysis on five sets of

economic forces amongst which government and labor are almost completely lost.”

THE INDIAN SCENARIO:

The Indian economy was subject to extensive and elaborate regulation till 1991. Forced by a

near-default situation, the then government introduced some bold initiatives that have since

been popularized as the LPG model – Liberalization, Privatization, and Globalization.

Foreign investment was permitted in several sectors. Many industries were taken out of the

purview of licensing. Private players were allowed into areas that were till then the monopoly

of the government. Incentives were provided for Indian industry to be competitive globally.

In particular, import duties were reduced and export incentives were enhanced. Bank credit

was made available in a relatively easier manner. Policies were simplified. Greenfield areas

like IT were given a special thrust with infrastructure being provided at subsidized prices and

tax holidays.

The results have been significant. Between 1947 when the country became independent and

1990, the average annual growth rate was a measly 2.3%. After liberalization, it started

moving up to 5 – 6%. For almost a decade, 1999 – 2008, the growth has been impressive –

between 7 and 9%.

In particular, the new economy comprising of sectors like IT, BT and Telecom have shown

remarkable growth and resilience. The IT Enabled Services industry has become a

benchmark to measure success. BT has made rapid strides with many ground-breaking

innovations. India today has nearly 350 million mobile subscribers – something that could not

have been imagined even a decade back. The acronym BRIC has become synonymous with

emerging economies.

THE IT ENABLED SERVICES INDUSTRY:

The industry presents a fascinating picture of imagination and innovation. INFOSYS,

established in 1982 with a capital of less than $1000/- is today an icon in the IT industry. It

has crossed $4 billion in revenues and has created a number of Rupee millionaires and

billionaires, and a few dollar billionaires as well. Similar is the case with the two other

leading companies, TCS and WIPRO. TCS was a consulting company that entered IT looking

at the opportunity and is today the #1 IT Company in India. The vision of TCS is to be a $10


billion company by 2010. WIPRO started off making vegetable oils and forayed into IT

mainly to exploit the opportunity.

INDIAN ITES AND THE FIVE-FORCE MODEL:

When the model is applied to the IT Enabled Services industry in India, the following points

emerge:

The industry has low entry barriers. When INFOSYS could be started with less than

$1000/- this factor becomes evident. With a surplus of talented engineers and scientists

(the most critical resource), anyone can enter the industry with a few computers, a rented

office space and an internet connection. This is precisely what has happened. Thousands

of companies have come up in the last two decades. WIPRO alone has spawned more

than 200 entrepreneurs. According to the model, the industry could be termed

fragmented. Price competition is high.

The bargaining power of buyers is very high. The buyers or clients of the industry are

large companies in the developed world. The clients of TCS, INFOSYS and WIPRO are

the FORTUNE 100 Companies. Many of these companies have IT departmental budgets

that are more than the revenues of the supplying companies. Thus, the CTO of the client

company may be more powerful than the CEO of the service-providing company. The

clients can play one service provider against another, drive down prices, introduce stiff

penalty clauses, insist on quick delivery and render maintenance into a low-cost or no-

cost proposition.

The bargaining power of suppliers is also very high. The suppliers are the hardware giants

like IBM, HP, DELL, CISCO and others. With rapid changes in technology, suppliers can

force the buying companies to adapt to new technologies. Sometimes, this can happen

every year. The buying companies have no choice. If they do not adapt, they will be

wiped out. They have to listen to the suppliers of hardware.

Industry rivalry is high. With players of all hues and sizes, price competition is rampant.

As an example, when medical transcription first came to India, the price was $15 per

module (of about 45 minutes). Today, the price is 75 cents per module. Companies are

forced to look at new ways of reducing costs or be cast into oblivion.

Since all players provide what in essence are similar services, they are inherent substitutes

for each other. Every large and some medium sized organizations too claim to provide

end-to-end solutions. The major players have a presence in all horizontals and verticals.

Differentiation is practically non-existent. In that sense, this force can also be considered

to be very high.

Thus, with low entry barriers, high bargaining power of buyers and suppliers, intense

rivalry, and the services on offer being close substitutes, the industry would be termed

extremely unattractive from the viewpoint of the five-force model. Organizations should

be fighting for survival, profits should be low or absent, and many organizations should

be extinct every day. That is what the model would suggest. What is the reality?

EMPIRICAL ANALYSIS OF THE PORTER FIVE-FORCE MODEL FOR THE

INDIAN IT/ITES INDUSTRY:

In order to analyze Porter’s five-force model empirically, quarterly data for the years 2006 -

2009 for the following variables was collected from the Capitaline database:

1. Net profit was used to measure industry attractiveness,

2. Average market capitalization was used to measure entry barriers,


3. IT hardware industry sales was used to measure supplier bargaining power,

4. IT software industry sales was used to measure buyer bargaining power, and

5. The number of listed IT companies was used to measure substitution/industry

competitiveness

ANALYSIS 1:

The effect of the independent variables (entry barriers, supplier bargaining power, buyer

bargaining power, and substitution/industry competitiveness) on industry attractiveness was

analyzed in absolute terms.

Correlations

net

profit

av. mkt.

capitalization

IT HW

sales

IT SW

sales

no. of

cos.

net profit Pearson

Correlation 1 .732(**) .904(**) .999(**)

-

.928(**)

Sig. (1-tailed) .001 .000 .000 .000

N 14 14 14 14 14

av. mkt.

capitalization

Pearson

Correlation .732(**) 1 .709(**) .707(**) -.538(*)

Sig. (1-tailed) .001 .002 .002 .024

N 14 14 14 14 14

IT HW sales Pearson

Correlation .904(**) .709(**) 1 .890(**)

-

.701(**)

Sig. (1-tailed) .000 .002 .000 .003

N 14 14 14 14 14

IT SW sales Pearson

Correlation .999(**) .707(**) .890(**) 1

-

.942(**)

Sig. (1-tailed) .000 .002 .000 .000

N 14 14 14 14 14

no. of cos. Pearson

Correlation

-

.928(**) -.538(*) -.701(**)

-

.942(**) 1

Sig. (1-tailed) .000 .024 .003 .000

N 14 14 14 14 14

** Correlation is significant at the 0.01 level (1-tailed).

* Correlation is significant at the 0.05 level (1-tailed).

The correlation between net profit (industry attractiveness) and the independent variables of

average market capitalization (entry barriers), IT hardware sales (supplier bargaining power),

IT software sales (buyer bargaining power), and number of listed IT companies

(substitution/industry competitiveness) was found to be statistically significant. Further,

industry attractiveness was positively correlated with entry barriers, supplier bargaining

power, and buyer bargaining power, and negatively correlated with substitution/industry

competitiveness. The positive correlation of net profit (industry attractiveness) with the

variables (except for with substitution/industry competitiveness) seems to contradict the

predictions of Porter’s five force model.



next analyzed using multiple linear regression.


Regression

Model Summary

Model R R

Square

Adjusted

R Square

Std. Error

of the

Estimate

1 1.000(a) 1.000 1.000 12.03914

a Predictors: (Constant), no. of cos. , av. mkt. capitalization, IT HW sales, IT SW sales

ANOVA (b)

Model Sum of Squares df Mean Square F Sig.

Regression 247835006.314 4 61958751.578 427476.330 .000(a)

1 Residual 1304.467 9 144.941

Total 247836310.781 13

a Predictors: (Constant), no. of cos. , av. mkt. capitalization, IT HW sales, IT SW sales

b Dependent Variable: net profit

Coefficients (a)

Model

Unstandardized

Coefficients

Standardized

Coefficients

t

Sig.

B

Std.

Error Beta

(Constant) -1308.032 269.292 -4.857 .001

1

av. mkt.

capitalization 20.646 .950 .037 21.742 .000

IT HW sales .118 .020 .030 5.909 .000

IT SW sales .728 .009 .979 76.846 .000

no. of cos. 1.831 .414 .035 4.422 .002

a Dependent Variable: net profit

The results of the regression analysis indicated that industry attractiveness was strongly

influenced jointly by the independent variables (entry barriers, supplier bargaining power,

buyer bargaining power, and substitution/industry competitiveness). Further, the partial

regression coefficients of all the independent variables were positive, again contradicting the

predictions of Porter’s five force model.

ANALYSIS 2:



analyzed in terms of differences/quarterly changes.


Correlations

change

net

profit

change av.

mkt.

capitalization

change

IT HW

sales

change

IT SW

sales

change

no. of

cos.

change net profit Pearson

Correlation 1 .319 .922(**) .964(**) .402

Sig. (1-tailed) .144 .000 .000 .087

N 13 13 13 13 13

change av. mkt.

capitalization

Pearson

Correlation .319 1 -.019 .081 .348

Sig. (1-tailed) .144 .476 .397 .122

N 13 13 13 13 13

change IT HW

sales

Pearson

Correlation .922(**) -.019 1 .944(**) .449

Sig. (1-tailed) .000 .476 .000 .062

N 13 13 13 13 13

change IT SW

sales

Pearson

Correlation .964(**) .081 .944(**) 1 .237

Sig. (1-tailed) .000 .397 .000 .218

N 13 13 13 13 13

change no. of

cos.

Pearson

Correlation .402 .348 .449 .237 1

Sig. (1-tailed) .087 .122 .062 .218

N 13 13 13 13 13


The correlation between change in net profit (industry attractiveness) and the independent

variables of change in IT hardware sales (supplier bargaining power) and change in IT

software sales (buyer bargaining power) were found to be statistically significant and were

highly positive, while the correlation between change in net profit and change in average

market capitalization and change in the number of listed IT companies was positive, but not

statistically significant. Again, the positive correlations seemed to contradict the predictions

of Porter’s five force model.




Regression

Model Summary

Model R R

Square

Adjusted

R Square

Std. Error

of the

Estimate

1 1.000(a) .999 .999 10.88028

a Predictors: (Constant), change no. of cos. , change IT SW sales, change av. mkt.

capitalization, change IT HW sales


ANOVA (b)

Model Sum of Squares df Mean Square F Sig.

Regression 1752562.549 4 438140.637 3701.125 .000(a)

1

Residual 947.043 8 118.380

Total 1753509.592 12

a Predictors: (Constant), change no. of cos. , change IT SW sales, change av. mkt.

capitalization, change IT HW sales

b Dependent Variable: change net profit

Coefficients (a)

Model

Unstandardized

Coefficients

Standardized

Coefficients t

Sig.

B

Std.

Error Beta

(Constant) 116.183 44.373 2.618 .031

change av. mkt.

capitalization 21.715 1.169 .262 18.576 .000

1 change IT HW sales .247 .048 .288 5.148 .001

change IT SW sales .605 .046 .665 13.241 .000

change no. of cos. .636 .506 .024 1.257 .244

a Dependent Variable: change net profit



and buyer bargaining power), but the influence of substitution/industry competitiveness on

industry attractiveness was not statistically significant. Further, the partial regression

coefficients of all the independent variables were positive, again contradicting the predictions


ANALYSIS 3:



analyzed in terms of percentage growth/change.


Correlations

%

change

net

profit

% change av.

mkt.

capitalization

%

change

IT HW

sales

%

change

IT SW

sales

%

change

no. of

cos.

% change net

profit

Pearson

Correlation 1 .350 .957(**) .994(**) .572(*)

Sig. (1-tailed) .120 .000 .000 .021

N 13 13 13 13 13

% change av. mkt.

capitalization

Pearson

Correlation

.350 1 .085 .248 .462

Sig. (1-tailed) .120 .392 .207 .056

N 13 13 13 13 13

% change IT HW

sales

Pearson

Correlation .957(**) .085 1 .981(**) .438

Sig. (1-tailed) .000 .392 .000 .067

N 13 13 13 13 13

% change IT SW

sales

Pearson

Correlation .994(**) .248 .981(**) 1 .535(*)

Sig. (1-tailed) .000 .207 .000 .030

N 13 13 13 13 13

% change no. of

cos.

Pearson

Correlation .572(*) .462 .438 .535(*) 1

Sig. (1-tailed) .021 .056 .067 .030

N 13 13 13 13 13


* Correlation is significant at the 0.05 level (1-tailed).

The correlation between percentage change in net profit (industry attractiveness) and the

independent variables of percentage change in IT hardware sales (supplier bargaining power),

percentage change in IT software sales (buyer bargaining power), and percentage change in

number of listed companies (substitution/industry competitiveness) were found to be

statistically significant and were highly positive, while the correlation between percentage

change in net profit and change in average market capitalization was positive, but not

statistically significant. Again, the positive correlations seemed to contradict the predictions





Regression

Model Summary

Model R R

Square

Adjusted

R Square

Std. Error

of the

Estimate

1 1.000(a) 1.000 1.000 .00034

a Predictors: (Constant), % change no. of cos. , % change IT HW sales, % change av. mkt.

capitalization, % change IT SW sales


ANOVA (b)

Model Sum of

Squares df

Mean

Square F Sig.

Regression .019 4 .005 40896.520 .000(a)

1

Residual .000 8 .000

Total .019 12

a Predictors: (Constant), % change no. of cos. , % change IT HW sales, % change av. mkt.

capitalization, % change IT SW sales

b Dependent Variable: % change net profit

Coefficients (a)

Model

Unstandardized

Coefficients

Standardized

Coefficients t

Sig.

B

Std.

Error Beta

(Constant) -.012 .002 -6.800 .000

% change av. mkt.

capitalization .023 .001 .109 23.138 .000

1 % change IT HW

sales .001 .004 .004 .161 .876

% change IT SW

sales 1.173 .032 .960 36.248 .000

% change no. of cos. .003 .002 .005 1.451 .185

a Dependent Variable: % change net profit



and substitution/industry competitiveness), but the influence of supplier bargaining power on

industry attractiveness was not statistically significant. Further, the partial regression

coefficients of all the independent variables were positive, again contradicting the predictions


CONCLUSION:

From the above analyses it can be concluded that the independent variables (entry barriers,

supplier bargaining power, buyer bargaining power, and substitution/industry

competitiveness) have a positive impact on industry attractiveness in emerging economies.

Since what appears at first sight to be a very unattractive industry has turned in stellar

performance year after year, perhaps there is more to profitability and competitiveness than

the industry structure suggested by the five-force model. A preliminary analysis of the fast

food industry in India suggests that industry structure does not explain more than 18 – 20% of

the profitability while a firm’s internal dynamics – leadership, organizational culture, and

competencies developed diligently account for 45 – 55% of the profitability with the

remaining being determined by environmental factors like government regulation. A third

analysis with the consumer electronics industry which has seen many global players entering

the Indian market in the last decade has shown that industry structure could explain only 12 –

14% of the profitability while internal dynamic capabilities were responsible for 63 – 68% of


profitability. Given this compelling empirical evidence, perhaps the time has come to re-visit

the model to make it useful to managers.

LIMITATIONS AND SCOPE FOR FURTHER STUDY:

The analyses above have only considered specific variables to represent each of the

dimensions (entry barriers, supplier bargaining power, buyer bargaining power, and

substitution/industry competitiveness). In fact, there are further components of each of these

dimensions which were not considered in the analyses. Thus, the results are only partially

indicative of the impact of the independent variables (entry barriers, supplier bargaining

power, buyer bargaining power, and substitution/industry competitiveness) on industry

attractiveness. Further, we are currently working on a model to quantify the overall impact of

all the forces impacting an industry and this should give us a better perspective than the

present study. We are also studying data available from other emerging economies to find

points of convergence or otherwise with our findings.

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