Environmental Uncertainty & Porter.ppt

8/10/2019 Environmental Uncertainty & Porter.ppt

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ENVIRONMENTAL UNCERTAINTYLiterature Review and Strategic Classification


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Managerial Decision-Making

Bounded rationality

Information required vs. information available

Cost of obtaining missing information

Temporal window for making the decision

Limitations of human cognition

Environmental uncertainty

Dimensions of the environment

Vectors and rates of change


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Definition

An inability to assign probabilities as to the likelihood of

future events (Duncan, 1972; Pennings & Tripathi, 1978;

Pfeffer & Salancik, 1978)

A lack of information about cause-effect relationships

(Duncan, 1972; Lorsch & Lawrence, 1965)

An inability to predict accurately what the outcomes of a

decision might be (Downey, Hellriegel, & Slocum Jr, 1975;

Hickson, Hinings, Lee, Schneck, & Pennings, 1971;

Schmidt & Cumming, 1976)

(Milliken, 1987)


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Management Field


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Sample Population

141 journal articles

Divided into three timeframes

19661980 (early development)

19811995 (refinement of measures)

1996present (construct frozen)

Article count by fields of management

General = 69

Strategy = 47

Operations = 14

Information = 7

Entrepreneurship = 4


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Two Types

Objective (OEU)

Economic in origin (Simon, 1957)

Supply uncertainty

Demand uncertainty

Cost uncertainty

Perceptual (PEU)

Market, scientific, and plant sectors of the environment along with

certainty of information, rate of change of the environment, and

time range of task as the vectors impacting bounded rationality

(Lorsch and Lawrence, 1965)


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Construct Research


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Construct Research


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PEUOEU Test

Tosi, Aldag, and Storey (1973) investigated Lorsch and

Lawrences perceived measures and scales, and checked

their results against objective measures of the

environment.

They found little correlation between perceived and

objective data

The debate continued for seven years


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PEU-OEU Resolution

Bourgeois (1985) recognized that each type of measure

had a place in management studies.

Objective measures of environmental uncertainty were well suited

for the initial stage of strategic planning that is domain identification

and selection. Perceptual measures of environmental uncertainty were a better

indicator when studying managerial decision making involved with

domain navigation as the firm attempted to fit the environment.


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PEU-OEU Measures and Scales Integration

Miller and Friesen (1982) recognized three dimensions

Environmental dynamism

Environmental heterogeneity

Environmental hostility

Dess and Beard (1984) recognized three dimensions

Dynamism

Munificence

Complexity


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Miller & Friesen (1982)


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OEU Measures and Scales

Keats and Hitt (1988) refined the Dess and Beard

measures with regression equations:

Growth and volatility in industry sales

Growth and volatility in industry operating income

Three-part calculation of industry concentration

Grossacks(1965) dynamic measure

Four-firm concentration ratio

HerfindahlHirschman Index (Hirschman, 1964)


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EU Research

EnvironmentalUncertainty

Objective Perceived

EconomyIndustry sales

Industry growthConcentrationCosts of inputs

Technology (R&D cost& patents)

Capital markets

EconomyCustomers

CompetitorsSuppliers

Technology (pace)Capital markets

Regulators

Unions

Range ofunpredictability

DynamismMunificence

Complexity


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Strategic Classification

Following Bourgeois (1985), use OEU as means of

identifying and selection strategic domains.


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Porters Five Forces

Threat ofNew

Entrants

CustomerPower

SupplierPower

Threat ofSubstitutes

Threat ofCompetitive

Rivalry


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Porters Five Forces as OEU

Bargaining power of suppliers

Impact of inputs on cost or differentiation

Importance of volume to the supplier

Differentiation of inputs

Competition between producers

Size and concentration of suppliers relative to industry

Switching costs

Asymmetry of suppliers information

Suppliers ability to forward integrate


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Impact of inputs on cost or differentiation

Calculate the suppliers contribution to margin, take the natural logarithm of

that figure and regress over at least five years against an index such as

the S&P 500. The antilog of the regression coefficient will represent

munificence (growth) while the antilog of the standard error indicates the

dynamism (volatility).

Yi

^

= b0+ b1Xi+ i

eb1 = munificence measure

e

= dynamism measure

where Y = ln(supplier's contribution to margin)

and X = index/year measure


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Importance of volume to the supplier

Determined using the measures of supplier industry concentration: Grossacks(1965) dynamic measure of industry concentration, the four-firm concentrationratio, and the HerfindahlHirschman Index (Hirschman, 1964).

Grossack is a regression of current-year market shares of all firms in a given industryupon their shares 5 years ago. The reciprocal of the regression coefficient indicatesthe decrease or increase of monopoly power in the industry and is used as onemeasure of complexity.

HerfindahlHirschman measures the smallness among the number of firm and the

variation among the sizes of firms


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Supplier industry concentration

GrossacksMeasure

Herfindahl-Hirschman Index

b=1+ wii

yi xi

xi

wi=xi

2

xi2

i

b=r y

x

y

x

=

yi2

xi2

C(HI) =HI

y

HIx=

yi2+

1

ny

xi2+

1

nx

HIx= Xi2

i

+1

n

where X is the market share of the iith

firm expressedas a ratio and nis the number of firms in the industry


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Differentiation of inputs

Differentiation is linked to above-average profits

Regress the natural log of the operating profit margin for the supplier

industry against an index variable of years

Antilog of the regression coefficient represents supplier OPM growth Antilog of the standard error represents supplier OPM volatility

Yi= b0+ b1Xi+ i

where Y = ln(supplier OPM)

and X = index/years

eb1 = supplier OPM munificence

e = supplier OPM dynamism


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Competition between producers

Determined by regressing unit prices against an index variable of

years.

Regression coefficient represents price growth (complexity)

Standard error represents price volatility

Yi= b0+ b1Xi+ i

where Y = unit prices

and X = index/years

b1= unit price complexity

= unit price dynamism


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Size and concentration of suppliers relative to industry

Calculate Grossacksconcentration index for producer and supplier

industries and regress this ratio against an index variable of years.

Regression coefficient represents producer/supplier complexity

Standard error of regression indicates producer/supplier volatility

b=1+ wii

yi xi

xi

wi=xi

2

xi2i

Y= b0+ b1Xi+ i

bp

bs= Y=producer/supplier concentration ratio

X = index variable of years


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Switching costs Static measure using ranked scale

1 = low impact

2 = moderate impact

3 = high impact

Determined using NPV of switching costs Measure of complexity


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Asymmetry of suppliers information

Static measure using ranked scale

1 = Supplier provides financial data, producer does not

2 = Both producer and supplier share financial data

3 = Neither producer nor supplier share financial data 4 = Producer provides financial data, supplier does not


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Suppliers ability to forward integrate Determined by computing the number and strength of related

acquisitions by suppliers and regressed over an index variable ofyears.

Using logistic regression over an index variable of years, determine the

probability of supplier-sourced related acquisition Multiply this number by the natural log of the value of the acquisitions

ln p

1 p

= b0+ b1Xi

eln

p

1

p

= odds ratio

Probability =OR

1+OR


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Suppliers ability to forward integrate

Determined by multiplying the number and value of related

acquisitions by suppliers in each year of the period; take the natural

log of these figures and regress over an index variable of years.

Antilog of regression coefficient represents complexity Antilog of standard error indicates volatility

Y= b0+ b1Xi+

i

where Y = ln(number ivalue of acquisitions)

X = index variable of years


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OEU Summary


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Bargaining power of customers

Cost of product relative to total customer purchases

Differentiation of outputs (product differentiation)

Importance of volume to customers

Competition between customers Customer profitability

Size and concentration of customers relative to industry

Customers switching costs

Asymmetry of customers information Customers ability to backward integrate


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Threat of New Entrants

Economies of scale

Absolute cost advantages

Capital requirements

Product differentiationAccess to distribution channels

Government and legal barriers

Retaliation by established producers

Market share shifts


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Economies of scale

Perform industry concentration computation for producer industry:

Grossacksmeasure

Four-firm concentration ratio

Herfindahl-Hirschman index Higher concentration indices represent greater economies of scale

as a complexity measure


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Absolute cost advantages Dependent upon unique contingencies

However, proxy measure could be implemented as:

Tobins q

Measure of value of technological assets; brand equity; intangible value

Number of patents awarded to the industry and regressed over an indexvariable of years

f2Rqirmi

Y

qK+Mp

qK+M

p( ) =M

p


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Capital requirements Specific capital requirements are contingent by entrant.

Better understanding may come from access to and cost of capital

Take the natural logarithm of the total liquidity of the credit market andregressing against an index variable of years provides the foundationfrom which the antilog of the regression coefficient is used as ameasure for capital market growth. Further, the antilog of the standarderror of the regression coefficient represents the measure of creditmarket volatility.

Additional measure could be added in the form of a regression equationcomputing the coefficient and standard error of capital rates over anindex variable of years.


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Product differentiation

Take the natural logarithm of the total operating profit margin of the

producer industry cataloged by four-digit NAICS code and regress

against an index variable of years; the antilog of the regression

coefficient is used as a measure for operating profit margin growth.Further, the antilog of the standard error of the regression coefficient

represents the measure of operating profit margin volatility.


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Access to distribution channels

A suitable proxy is the four or eight-firm concentration ratio; higher

levels of industry concentration will inhibit access to distribution.

Capturing several years of data could then be regressed and

examined as complexity and dynamism measures.


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Government and legal barriers

The uncertainty of government and legal barriers might be captured

as the number of regulatory actions taken at the national, provincial,

and local levels against the industry and ranked by severity:

3 = strategic impact 2 = operational impact

1 = paperwork impact

Means could be calculated by year for an index variable of years.

The Friedman Two-Way ANOVA by Ranks could be applied to

ensure a significant differentiation between ranked categories. Capturing this data by year would allow a regression equation

where the regression coefficient is a measure of complexity while

the standard error is volatility.


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Retaliation by established producers

Dependent upon the market entry strategy employed by new

entrants (Kotler and Keller, 2009):

Frontal attack

Flanking attack Encirclement

Guerilla warfare


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Market share shifts

Use Grossacksexpanded measure of the producer industry to

discover if new entrants are affecting industry concentration.

b=r y

x

y

x

=

yi2

xi2

C(HI) =HIy

HIx=

yi2+

1

ny

xi2+

1

nx


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OEU Summary


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Threat of Competitive Rivalry

Cost conditions (fixed and storage)

Unique to producers dependent on their strategy

Cost-based

Differentiation

Niche Contingencies include

Organizational structure

Supply chain

Intellectual and human capital


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Concentration of producers

Grossacksdynamic measure of industry concentration, the four-firm

concentration ratio, and the HerfindahlHirschman Index.

However, we caution researchers about the use of producer

concentration as the sole measure of complexity because of thecompetitive stratification generated as a result of niche strategies.


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Diversity of competitors

Regress the number of producers against the number of strategic

business units over an index variable of years.

Regression coefficient represents producer diversity complexity

Standard error indicates diversity volatility

Yi= b0+ b1Xi+

where Y = number of producersXi= number of SBUs


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Product differentiation Take the natural logarithm of the total operating profit margin of the

producer industry cataloged by four-digit NAICS code and regressagainst an index variable of years

The antilog of the regression coefficient is used as a measure for

operating profit margin growth. The antilog of the standard error of the regression coefficient

represents the measure of operating profit margin volatility.


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Excess capacity

Regress the natural logarithm of the industry capital investment

against the natural logarithm of the industry sales to uncover

capacity breakpoints and estimate excess capacity.


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Exit barriers

Detect growth in the number of producers as determined by the

measures for industry concentration ratio and map against

moderate to high sales growth; this indicates lower exit barriers

because a market exists to dispose of structural elements.

Detect a decline or stasis in the number of producers as determined

by the measures for industry concentration ratio and map against

slow sales; lack of growth indicates higher exit barriers because a

market does not exist to dispose of structural elements.

These measures represent complexity components


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OEU Summary


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Threat of Substitutes

Switching costs

Buyer inclination to substitute

Price-performance trade-off of substitutes


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The Dess and Beard OEU Classification Framework


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The Porter

Four Forces

as OEU

Dynamism Munif icence Compl exit y

Suppl ier Mar g inCon t r ibut ion,

Suppl ierConcentr at ion,

Oper ating Mar gin,Uni t Pr ice,

Pr oducer Revenue/Cust omer Cost Rat io,

Cust omer

Concentr at ion,Cust omer OPM,Capital Liquidit y Size,

Capital Rates,Dist r ibu t ion

Channel s,# of Pr oducer s,

Suppl ier Mar g inCon t r ibu t ion ,

Oper ating Mar gin,Uni t Pr ice,

Cust omer OPM,Capit al Liquidit y

Size,Capit al Rat es,

Dis t r ibut ionChannel s,# of Pr oducer s,Excess Capacit y

Cal cu l at ion,

Obj ect ive Envir onmental Uncer t ainty

Pr oducer/Suppl ierRevenue Rati o,

Suppl ierConcentr at ion,

Pr oducer Switch ingCosts (r anked),

Inf or mati on Asymmet r y(P/S r anked),

Suppl ier Rel at edAcqu isi t ion Pr obabi l i t y

& Power ,Pr oducer Revenue/

Cust omer Cost Rati o,Cust omer Pur chase/Pr oducer Revenue

Rat io,Cust omer

Concentr at ion,Cust omer Swit ching

Costs (r anked),Inf or mati on Asymmet r y

(P/C r anked),Cust omer Rel ated

Acqu isi t ion Pr obabi l i t y& Power ,Four -f i r m

Concent r at ion Rat io ,Pr oducer Tobin's q

Gover nment Act ions(r anked),Pr oducer

Concentr at ion,Pr oducer Rel at ed

Acquisi t ion s,Exi t Bar r ie rCal cu l at ion


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Limitations

Access to financial and regulatory information

Public vs. Private

U.S. vs. ROW

Lack of empirical evidence as of yet


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Future Research

Instrument development process(Chen and Paulraj, 2004)

Environmental Uncertainty & Porter.ppt

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