The Sources Of Competitive Advantage

The Sources Of Competitive Advantage

Strategic Management/ Business Policy Power Point Set #3: Industry Analysis 1 Efficient Markets The efficient market hypothesis, which Professor Eugene Fama of the University of Chicago has supported (e.g., in financial markets), is one in which prices reflect information instantaneously and one in which extraordinary profit opportunities are thus rapidly dissipated by the action of profit-seeking individuals in the market. How well does the efficient market hypothesis for capital markets apply to product markets? If the efficient market hypothesis applied fully to product markets then we should see over time equalization in riskadjusted rates of return across industries. What do the data support? 2 D iffe re n c e s in P ro fita b ility A c ro s s In d u s trie s A v e ra g e R e tu rn o n E q u ity in U S In d u s trie s , 1 9 8 2 -1 9 9 3

16.5% 90 13.8% 11.7% 100 80 F irs t Q u a rtile A v e ra g e 2 2 .2 % F o u rth Q u a rtile A v e ra g e 9 .3 % 70 60

Num ber 50 of In d u s tr ie s 40 A v e r a g e = 1 4 .7 % M e d ia n = 1 3 .8 % 30 20 10 0 32% 30% 28% 26%

24% 22% 20% 18% 16% 14% 12% 10% 8% 6% 4%

2% R e tu r n o n E q u ity (P e r c e n t) N o te : S o u rc e : R e tu r n o n E q u ity = N e t In c o m e / Y e a r E n d S h a re h o ld e r s E q u it y ; A n a ly s is b a s e d o n s a m p le o f 5 9 3 in d u s tr ie s S ilv e rm a n 2 0 0 0 2 0 0 5 M a ra L e d e rm a n , R o tm a n S c h o o l o f M a n a g e m e n t 3 Some Industries Are More Profitable Than Others Differences in Profitability Across Selected Industries Pharmaceuticals Semiconductors ROE & ROA - Selected Industries, 1989 Dental equipment

30% 25% Drug stores Race track operations 20% Engineering services ROE 15% ROA Cable television service 10% Scheduled air transport 5% -5

0 5 10 15 20 25 Operating income / assets, 1988-95 (%) 0% Tires / Rubber Source: Pankaj Ghemawat and Jan W.Pharmaceuticals Rivkin, Creating Competitive Advantage 2005 Mara Lederman, Rotman School of Management Home Appliances 4

Within Industries, Some Competitors Perform Better than Others. Differences in Profitability W ithin Selected Industries S e m ic o n d u c to r In d u s tr y - Pharmaceutical Industry 1989 InteROE l 60%Te xa s 50% Ins trum e nts M o to ro la AMD 40% A na lo g D e vic e s 30% N a tio na l S e m ic o nd uc to r

20% -5 0 5 10 15 20 25 O p e rating inc o m e / as s e ts , 1 9 8 8 -9 5 (% ) 10% 0% Amgen

AMP Eli Lilly Merck S ource: P ankaj Ghem aw at and Jan W . R ivkin, C reating C om petitive Adva ntage 2005 Mara Lederm an, R otm an Schoo l of Ma nagem ent Mylan Pfizer 5 The U.S. Auto Industrys Profit Pool Exhibit 5.7 The U.S. Auto Industrys Profit Pool Source: Adapted by permission of Harvard Business Review. Exhibit from A Fresh Look at Strategy by O. Gadiesh and J. L. Gilbert, Harvard Business Review 76, no. 3 (1998), pp. 139-48. Copyright 1998 by the Harvard Business School

Publishing Corporation, all rights Copyright 2005 by TheMcGraw-Hill Companie s, Inc.reserved. All rights reserved. 6 5-22 Does Does Industry Industry Matter? Matter? Schmalensee (1985) Rumelt (1991) McGahan & Porter 1997)

Hawawini et al (2003) Percentage of variance in firms return on assets explained by: Industry Firm-specific Unexplained effects effects variance 19.6% 0.6% 80.4% 4.0% 44.2% 44.8% 18.7%

31.7% 48.4% 8.1% 35.8% 52.0% 7 Decomposition of Variance in Profitability Year 2% Industry 18% Corporate parent 4%

Transient 46% Business segment 30% Source: Anita M. McGahan and Michael E. Porter, How Much Does Industry Matter Really? Strategic Management Journal, 1997 2005 Mara Lederman, Rotman School of Management 8 Three Factors Determining Company Performance Industry Context e.g., during the last two decades, companies in the airlines industry have been less profitable than those in the pharmaceutical industry National Context e.g., worlds most successful consumer electronics firms are in Japan

Company Capabilities and Strategies E.g., Wal-mart and Southwest Airlines 9 Industry Analysis Supports The Identification of Threats and Opportunities Strengths, Weaknesses, Opportunities, and Threats - SWOT Analysis Industry Analysis Strengths & Weaknesses Internal Factors Drivers

Opportunities & Threats External Factors Strategy Values Of Management Objective s Values Of Stakeholders 10 S tru c tu re -C o n d u c t-P e rfo rm a n c e In d u s try S tru c tu re N u m b e r o f b u y e rs a n d s e lle r s

D e g re e o f p ro d u ct d i ff e r e n t i a t i o n B a r r ie r s t o e n t r y C o s t s tru c tu re s V e r t ic a l in t e g r a t io n A llia n c e s F ir m C o n d u c t P r ic in g A d v e r t is in g R & D I n v e s t m e n t in p la n t a n d e q u ip m e n t P e rfo rm a n c e

E c o n p r o fi t s A c c o u n t in g p r o fi t s ( r a t i o s ) N P V /D C F M V A /E V A T o b in s Q 11 TheStructure-ConductPerform anceParadigm The Causal View Market Structure Conduct Performance TheFeedback Critique

Noone-waycausal link. Conduct canaffect m arket structure. Market perform ancecanaffect conduct as well as m arket structure. ClarkeModifications of BayeChapter 7 4 12 Structure-Conduct-Performance Market Structure: Number of buyers and sellers (e.g., CR4) Barriers to entry Substitutes Cost Structures

Regulation 13 Structure-Conduct-Performance Industry concentration is measured by the four-firm sales concentration ration (CR4). Problem: CR4 = .6 (.15, .15, .15, .15) or CR4 = .6 (.57. .01, .01, .01) Which is more likely to exhibit monopoly power? Alternative Measure: HHI index 7 firms (15, 15, 15, 15, 15, 15, 10) = 1450 44 firms (57, 1, 1, 1 ) = 3292 (3249 + 43) Correlation between CR4 and HHI in 1982 was 0.954 14 Structure-Conduct-Performance Defining the relevant market: Even more important than choosing the proper index of concentration is ensuring that the market for which concentration is being measured is properly defined.

In the United States, the basic system is called the Standard Industrial Classification (SIC). Onto it, the Census Bureau has grafted an even more intricately subdivided system organized around a series of seven digit numbers, each successive digit reflecting a finer degree of classification. 15 Structure-Conduct-Performance In 1982, the manufacturing sector was divided into 450 such four-digit industries. SIC Code 3632 3511 2082 3011 2834 3237 CR4

household refrigerators turbines .84 beer .77 tires .66 pharmaceuticals .26 ready-mix concrete .06 # of firms .94 HHI 39 71 67 108 584 4161

2745 2602 2089 1591 1306 18 16 Porters Five Forces Model of Industry Competition Threat of new entrants Bargaining power of suppliers Bargaining power of buyers Threat of

Substitute products and services Adapted from Exhibit 2.2 Porters Five Forces Model of Industry Competition Copyright 2005 by TheMcGraw-Hill Companies, Inc. All rights reserved. 17 2-17 Barriers To Entry The free entry and free exit assumption that works reasonably well for describing financial markets seems to be a premise that strays so far from our world of experience that the assumption impedes our understanding of real-world product competition. Thus, empirical evidence suggests that(risk-adjusted) ROE does NOT equalize in the long run. 18 A Taxonomy of Barriers to Entry

(1) Economies of Scale Product-specific economies of scale Lower setup costs as a percentage of total costs More specialized machinery and tooling (e.g., Honda) Plant-specific economies of scale Engineers 2/3 rule: Since the area of a sphere or cylinder varies as two-thirds power of volume, the cost of constructing process industry plants can be expected to rise as two thirds power of their output capacity. (This rule applies to petroleum refining, cement making, iron ore reduction and steel conversion). Also economies of massed reserves 19 Economies Economies of of Scale: Scale: The The Long-Run Long-Run Cost Cost Curve

Curve for for aa Plant Plant Sources of scale economies: - technical input/output relationships - indivisibilities - specialization Cost per unit of output Minimum Efficient Plant Size Units of output per period 20 M i n i m u m E ffi c i e n t S c a l e

M in im m in im It re v ca n o u m u m e a ls p e ra e ffi c i e n t s c a l e ( M E S ) i s t h e p o i n t o f a v e ra g e c o s t. t h e l o w e s t o u t p u t a t w h i c h t h e fi r m t e a t t h e lo w e s t c o s t . AA TT CC ( ( QQ ) ) AA TT CC ( ( QQ ) ) M E S N ile H a tc h 1 9 9 6 , 2 0 0 0 QQ

M E S AA TT CC ( ( QQ ) ) QQ M E S QQ 21 A Taxonomy of Barriers to Entry Economies of Scale Multi-product economies of scale (economies of scope) Example: Cost (Iron, Steel) < Cost (Iron) + Cost (Steel) Key idea: Shareable input (In this case, thermal economies in the production of iron and steel) Modern examples: Aircraft, Automobiles, Consumer electronics, Household Appliances; Personal Computers, Software, Power Tools

Multi-plant economies of scale Economies of multi-plant production, investment, and physical distribution. 22 Examples of Economies of Scope Aircraft: Common wing, nose, and tail components allow several models to be leveraged using different numbers of fuselage modules to create aircraft of different lengths and passenger freight capacities by Boeing and Airbus Industries. Automobiles: The Taurus platform is leveraged to provide the basis for Taurus and Mercury Sable sedans and wagons and the Ford Windstar. 23 Examples of Economies of Scope Consumer Electronics: Over 160

variations of the Sony Walkman were leveraged by mixing and matching modular components in a few basic system designs. (Legos) Personal Computers: Personal computers typically consist largely of modular components like hard drives, flat screen displays, and memory chips, coupled with some distinctive components like a microprocessor chip and enclosure. 24 Examples of Economies of Scope Software Software designers are creating modules of routines which can be combined to create customized applications programs. (The term modularity gained wide currency by software designers in the 1960s.) 25

A Taxonomy of Barriers To Entry (2) Experience Curve Advantages Marvin Lieberman, a management professor at UCLA, found that in the chemical industry, on average, each doubling of plant scale over time was accomplished by an 11% reduction in unit costs. Thus, there is an 89% learning curve. (Note: The mere presence of an experience curve does not insure an entry barrier. Another critical prerequisite is that the experience be kept proprietary, and not be made available to competitors and potential entrants.) 26 Hours per unit, TN 120 100 80 60 40 20

0 TN = (100)(N log.90/log2) 90% curve 80% curve 0 100 200 Cumulative units, N 300 400 27 Aircraft Assembly (1925-57): 80%

Calculator (1975-78): 74% 1995 Corel Corp. Heart Transplants (1985-88): 79% 1995 Corel Corp. 28 5-7 Production and Efficiency: Learning Effects Economies of Scale and Learning Effects Unit Costs . A

Economies of Scale . . B C Learning Effects Average Costs Average Costs Output 29 Copyright 1998 by Houghton Mifflin Company. All rights reserved. A Taxonomy of Barriers To Entry Limits of Learning Curve Advantages:

Copying and reverse engineering of products; Hiring a competitors employees; Purchasing the know-how from consultants; Obtaining the know-how from customers; and Experience advantages are often nullified by innovations. 30 A Taxonomy of Barriers To Entry (3) Intended Excess Capacity Building extra capacity for the intended purpose of deterring entrants from entering the industry. (Note: potential free-rider problems) Excess capacity deters entry by increasing the credibility of price cutting as an entry response by incumbents. Innocent excess capacity: Demand is cyclical; Demand falls short of expectations; Demand is expected to grow. 31 A Taxonomy of Barriers To Entry

(4) Reputation A history of incumbent firms reacting aggressively to entrants may play a role in current market interactions. (5) Product Differentiation Brand identification and customer loyalty to incumbent products may be a barrier to potential entrants (e.g. Coca-Cola). Product differentiation appears to be an important entry barrier in the market for over-the counter drugs and in the brewing industry 32 A Taxonomy of Barriers To Entry (6) Capital Requirements (7) High Switching Costs of Buyers E.g., changing may require employee retraining

(e.g., IV solutions, and computer software). 33 A Taxonomy of Barriers To Entry (8) Access to Distribution Channels The manufacturer of a new food product, for example, must persuade the retailer to give it space on the fiercely competitive supermarket shelf via promises of promotion, and intense selling efforts to retailers. (9) Favorable Access to Raw Materials and to Markets Alcoa --> bauxite Exclusive dealing arrangements Favorable geographic locations 34 A Taxonomy of Barriers To Entry (10) Proprietary Technology Product know how Low cost product design

Patents (and other government restrictions) (11) Exit barriers (of incumbents) can be entry barriers (to potential entrants) 35 A Taxonomy of Barriers To Entry High exit costs: High exogenous and endogenous sunk costs (not just high fixed costs!) High asset specificity Highly illiquid assets Low salvage value if exit occurs High switching costs Low mobility of assets Credible commitments Irreversible investment e.g., Alaskan pipeline built in 1977 at a cost of $10 billion 36 Bargaining Power of Buyers

Buyers compete within the industry by forcing down prices, bargaining for higher quality or more services, and playing competitors against each other. A buyer group is powerful when: The buyer group is concentrated (potential collusion); The buyer group purchases large volumes relative to seller sales (e.g., HMO power buying drugs); The product is standard and undifferentiated; Few switching costs on the part of the buyer; High switching costs on the part of the seller; and Buyers pose a credible threat of backward integration 37 Threat From Substitutes Substitute products increase the industrys overall elasticity of demand and limit the potential returns of the industry by placing a ceiling on the prices that firms in the industry can profitably charge. Companies in the coffee industry compete indirectly in the tea and soft-drink industries (all three industries serve consumer needs for drinks).

38 Bargaining Power of Suppliers Suppliers can be broadly defined as the supplier of any input: Labor, Management, Technology, Physical Materials The bargaining power of suppliers is high when: It is dominated by a few companies and is more concentrated than the industry it sells to; It does not contend with substitute products; The suppliers product is an important input to the buyers business; and Suppliers products are differentiated (high switching costs for the buyer). 39 Degree Of Rivalry Increases When: Industry Concentration is lower; Industry Growth is slower; Product Differentiation is lower; Over-capacity is higher; and

Exit Barriers are higher Price competition is highly unstable. Price cuts are quickly and easily matched by rivals, and once matched, they lower revenues for all firms (unless price elasticity of demand is high enough). 40 Degree Of Rivalry Advertising battles, on the other hand, may well expand or enhance the level of product differentiation in the industry for the benefit for all firms. In other words, advertising is not necessarily a zero-sum game. 41 The Uses of Industry Analysis Static Analysis How Do We Explain Current Rivalry and Profitability? Dynamic Analysis Where Is The Industry In The Future?

Headed 42 Industries Evolve Over Time As The Relationships Between The Five Forces Change demand Dynamic 5-Forces Analysis time 43 F ix o p e Fiv

ive eF Fo orc rce es so orrS S ix?In ?Intro trod du uc cin ing gC C om m ple lem

m en nts ts The suppliers of complements create value for the industry and canexercise bargaining power SUPPLIERS Bargaining power of suppliers INDUSTRY COMPETITORS POTENTIAL Threat of ENTRANTS newentrants COMPLEMENTS Threat of

Rivalry among existing firms SUBSTITUTES substitutes Bargaining power of buyers BUYERS 44 A Sixth Force - The Presence of Complementors Complementors Industry participants whose businesses enhance the value of yours The opposite of Substitutes The emergence of Networks of organizations Examples Computer manufacturers and software makers

Consumer electronics and entertainment companies The Central Issue How to get complementors to make strategic investments, which mutually benefit both companies? 45 A Sixth Force -The Presence of Complementors The biggest benefit of considering complementors is that they add a cooperative dimension to Porters (1980) competitive forces model. Thinking [about] complements is a different way of thinking about business. Its about finding ways to make the pie bigger rather than fighting with competitors over a fixed pie. To benefit from this insight, think about how to expand the pie by developing new complements or making existing complements more affordable. Brandenburger & Nalebuff Co-opetition 46 Empirical Testing of Structure-Conduct (Strategy)- Performance

ROE(j) = 14.7 + .050 CR4(j) + .119 [CAP/S](j) + (2.08) (1.98) 1.30 [A/S](j) +1.40 [R&D/S](j) +0.26 [GROW](j) (7.20) (2.95) (2.90) t-statistics in parentheses R-squared = .43 CR4 = 4-firm concentration ROE = return on equity R&D/S = R&D/Sales A/S = advertising/sales CAP/S = capital expenditures/Sales GROW = demand growth 47 Empirical Testing of Structure-Conduct (Strategy)- Performance Model Specification In practice, researchers estimate a statistical

model of the following form where data are aggregated to the industry level: Industry Profit Rates = f (Concentration, Barriers to Entry, Demand ) 48 Empirical Testing of Structure-Conduct (Strategy)- Performance Model Specification Multiple regression analysis seeks to evaluate the degrees to which deviations of the dependent variable (and in this course our focus has been on profit rates as the dependent variable) from its mean are explained by or associated with variations in each of a set of independent or explanatory variables (e.g., concentration, barriers to entry, demand, etc.) 49 Empirical Testing of Structure-Conduct (Strategy)- Performance

Model Specification The nature of this association is captured by regression coefficients relating the profit rates in the industry of each independent variable, allowing us to determine the effect, for example, of a 10% increase in seller concentration on profit rates, holding all other explanatory variables constant (i.e., ceteris paribus) 50 Empirical Testing of Structure-Conduct (Strategy)- Performance Model Specification S tru c tu re -C o n d u c t-P e rfo rm a n c e In d u s try S tru c tu re Predicted Sign Reason N u m b e r o f b u y e rs a n d s e lle r s D e g re e o f p ro d u ct

d i ff e r e n t i a t i o n B a r r ie r s t o e n t r y C o s t s tru c tu re s V e r t ic a l in t e g r a t io n A llia n c e s CR4 + Higher concentration enables higher prices CAP/S+ Capital-cost barrier to entry A/S + Advertising intensity as a product differentiation barrier to entry R&D/S + Technological know-how GROW + Demand growth leads to likely price wars

F ir m C o n d u c t P r ic in g A d v e r t is in g R & D I n v e s t m e n t in p la n t a n d e q u ip m e n t P e rfo rm a n c e E c o n p r o fi t s A c c o u n t in g p r o fi t s ( r a t i o s ) N P V /D C F M V A /E V A T o b in s Q

less 51 Empirical Testing of Structure-Conduct (Strategy)- Performance Model Specification Note that the multiple regression results are consistent with (but do not prove!) the structure-conduct-performance model. As you probably are aware from your statistics classes, there are many potential problems that can interfere with the reliable estimation of regression models, leading to incorrect inference about the statistical significance and economic importance of explanatory variables. 52 Empirical Testing of Structure-Conduct (Strategy)- Performance Three Potential Problems: (1)

Mis-specification problems; (2) Measurement problems; and (3) Identification problems 53 Empirical Testing of Structure-Conduct (Strategy)- Performance (1) Mis-specification Problems: Important Variables Omitted. In our regression, the impact of substitute products, and the power of buyers and suppliers have not been included in the model specification. Irrelevant Variables Included. If you believe fervently in perfect capital markets then you may question the idea of capital cost entry barriers and therefore you

would question the inclusion of the independent variable [CAP/S] in the model. 54 Empirical Testing of Structure-Conduct (Strategy)- Performance (1) Mis-specification Problems: Model assumes a linear relationship. Since the regression assumes a linear relationship, this may turn out to be a poor approximation if some of the explanatory variables (e.g., ADV/S) influence the dependent variable (i.e., ROE) in a non-linear way. Independent variable may not be truly independent. For example, not only can increased concentration affect profit rates but profit rates may affect industry concentration. Multicollinearity. If independent variables such as S) and {R&D/S) are highly correlated, then the t-statistics come into question. (ADV/ validity of the 55

Empirical Testing of Structure-Conduct (Strategy)- Performance (2) Measurement Problems: For example, CR4 may not be the best measure of industry concentration, where the HHI is a better measure. Perhaps some performance measure other than ROE would also be better for testing the theory. Note: If the evidence is not consistent with the theory it is not necessarily the case that we abandon the theory. One of the many possibilities is that we do not have good measures of the theoretical concepts. 56 Empirical Testing of Structure-Conduct (Strategy)- Perform ance (3) Identification Problems: - These problems are related to the idea that correlation does not imply causality. For example, you might maintain that high advertising/ sales is a barrier to entry (product differentiation) strategy that causes high profit rates. The regression is

consistent with Porters (1980) theory. 57 Empirical Testing of Structure-Conduct (Strategy)- Performance (3) Identification Problems However, you might argue instead that high profit rates allow more discretionary spending in marketing and thus, high profit rates cause high advertising/sales. The empirical evidence is also consistent with this theory. Thus, we have an identification problem. The data are consistent with multiple theories and we must find more refined tests and better econometric methods in order to advance our scientific knowledge in strategic management. 58

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