five force model in theory and practice: analysis …
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Volume:01, Number:04, August-2011 Page 182 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.
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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
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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
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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
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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,
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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.
The effect of the independent variables (entry barriers, supplier bargaining power, buyer
bargaining power, and substitution/industry competitiveness) on industry attractiveness was
next analyzed using multiple linear regression.
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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:
The effect of the independent variables (entry barriers, supplier bargaining power, buyer
bargaining power, and substitution/industry competitiveness) on industry attractiveness was
analyzed in terms of differences/quarterly changes.
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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
** Correlation is significant at the 0.01 level (1-tailed).
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.
The effect of the independent variables (entry barriers, supplier bargaining power, buyer
bargaining power, and substitution/industry competitiveness) on industry attractiveness was
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) .999 .999 10.88028
a Predictors: (Constant), change no. of cos. , change IT SW sales, change av. mkt.
capitalization, change IT HW sales
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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
The results of the regression analysis indicated that industry attractiveness was strongly
influenced jointly by the independent variables (entry barriers, supplier bargaining power,
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
of Porter’s five force model.
ANALYSIS 3:
The effect of the independent variables (entry barriers, supplier bargaining power, buyer
bargaining power, and substitution/industry competitiveness) on industry attractiveness was
analyzed in terms of percentage growth/change.
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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 0.01 level (1-tailed).
* 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
of Porter’s five force model.
The effect of the independent variables (entry barriers, supplier bargaining power, buyer
bargaining power, and substitution/industry competitiveness) on industry attractiveness was
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 .00034
a Predictors: (Constant), % change no. of cos. , % change IT HW sales, % change av. mkt.
capitalization, % change IT SW sales
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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
The results of the regression analysis indicated that industry attractiveness was strongly
influenced jointly by the independent variables (entry barriers, supplier bargaining power,
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
of Porter’s five force model.
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
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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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