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Modelling Performance and the Resource BasedView

Anup NandialathHEC Paris

September 7, 2011

Anup Nandialath Modelling Performance and the Resource Based View


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Strategy as a Discipline

What do we seek to study in Strategy?

Why do some firms perform better than the other???

Multiple Theoretical lens1 Resource Based View

2 Knowledge Based View

3 Real Options

4 Transaction Cost Economics



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Strategy as a Discipline

What do we seek to study in Strategy?

Why do some firms perform better than the other???

Multiple Theoretical lens1 Resource Based View

2 Knowledge Based View

3 Real Options

4 Transaction Cost Economics



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Resource Based View

Firms performance and the Resource Based View

Performance= f(R1,R2, ...,Rn)

1 R1,R2, ...,Rn represents different resources and capabilities

2 R&D, patents, brands, organizational routines, knowledgeassets and relationship management among others

3 RBV is a dominant theory in strategic management to explainsuperior performance (Wernerfelt, 1984; Barney, 1991;Conner, 1991; Peteraf 1993 among others)

4 Empirical evidence has been rather inconclusive (Newbert,2007; Arend 2006)



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Approaches to empirical evaluation

Resource Heterogeneity approach

1 Grounded in the VRIO framework

2 Resources are identified, measured and regressed onperformance metrics to draw inference

3 eg. Shamsie and Miller (1996); Henderson and Cockburn

(1995)

Organization also matters approach

1 VRIO is not sufficient but resources need to be well organized

2 Resources are identified, measured and interacted withorganizational contexts and then regressed on performancemetrics to draw inference

3 eg. Wiklund and Shepard (2003)



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RBV Empirics

Typical RBV study is modeled as followsYi = Xi + Zi+ i

1 Yi represents a measure of firm performance such as

ROA,ROE or other profitability measures2 Xi represents resource and capability profiles

3 Zi represents relevant control variables such as firm size,competitive considerations etc.

4 , represent the relevant sensitivities and

represents theerror term

5 OLS regression and positive is deemed as support for RBV



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Critical Assumptions

1 Value, Rarity and Inimitability of resources are assumed to bepresent (Consistency with theory!!!)

2 The functional form chosen is correct (Violation of

monotonicity?)



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monotonicity?)3 Managers and Researchers (us) observe the same level of

information (Endogeneity)



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4 Though RBV is a firm specific theory, empirics assume that itis sufficient to show the positive effect of resources on

performance (Heterogeneity)



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4 Though RBV is a firm specific theory, empirics assume that itis sufficient to show the positive effect of resources on

performance (Heterogeneity)



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Motivation for a new stream of research

Unresolved Problems!

1 Measurement : The value, rarity and inimitability are ex-anteunobservable (Godfrey and Hill, 1995)

2

Endogeneity: Resources are costly to acquire and maintainand hence need to be accounted for (Arend, 2006)

3 Endogeneity: Is there a process by which firms pick the rightresources or is it blind luck (Barney, 1986)?

4 Heterogeneity: Firms need resources and also the ability toallocate them optimally (Mahoney and Pandian, 1993)



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Issues in Measurement

Measurement

1 What is a resource/capability? How do we measure them?

2 Several approaches have been proposed with surveys tendingto be favored (e.g. Newbert, 2008)

3 However the properties of a resource are Latent and hencepotentially unobserved

4 Taking averages or sums of any linear combinations of theresponses from a survey involves critical assumptions (which

are likely to fail)5 Is measurement a problem ?? Do we have a solution??



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Non Linear Measurement Models1 Is Measurement a problem??

Classical econometrics tells us that measurement error on theright hand side of an equation biases results (Greene, 2003)Higher order moment estimators can be used to correct for

such measurement error (Erickson and Whited, 2000)2 Non linear measurement models?

Borrow methodology from psychometrics primarily Factoranalysis and Item response theoryMeasuring intention to leave and stress levels in the call center

industry (Nandialath, Das and Mohan, 2011)Prospective work in measuring resources and capabilities withRafael Goldszmidt



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Non Linear Measurement Models1 Is Measurement a problem??

Classical econometrics tells us that measurement error on theright hand side of an equation biases results (Greene, 2003)Higher order moment estimators can be used to correct for

such measurement error (Erickson and Whited, 2000)2 Non linear measurement models?

Borrow methodology from psychometrics primarily Factoranalysis and Item response theoryMeasuring intention to leave and stress levels in the call center

industry (Nandialath, Das and Mohan, 2011)Prospective work in measuring resources and capabilities withRafael Goldszmidt



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Endogeneity!!

Causes of Endogeneity

1 Omitted correlated variablesRefers to variables that should have been included in theregression but for whatever reason are notProblem is critical for strategy researchthe RBV as a theory stresses that firms are heterogeneous

across multiple dimensions and hence controlling for alldeterminants of performance in a large sample study becomesextremely difficultE.g Barney (1986) suggests that managerial skill is critical torecord superior performance but skill is often unobserved andhence never part of a regressionThe unobserved factors are pushed into the error term of theregressionInference can be problematic especially if the unobservedfactor is correlated with the independent variable (e.g. skilland resources)



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Endogeneity!!


1 Simultaneity

Occurs when the dependent and independent variables tend tobe jointly determined

Refers to the classic problem!! Did superior resources lead tosuperior performance or vice versa?

2 Measurement Error

Measurement error in the dependent variableIf performance is measured with error then it is a problem only

if it is correlated with the independent variable (resources)


E d i !!


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Endogeneity!!


1 Simultaneity



2 Measurement Error


if it is correlated with the independent variable (resources)Measurement error in the independent variable


E d i !!


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Endogeneity!!


1 Simultaneity



2 Measurement Error


if it is correlated with the independent variable (resources)Measurement error in the independent variable


E d i !!


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Endogeneity!!

Solutions to the Endogeneity problem1 Instrumental Variables

Standard treatment is to find an instrument which is correlatedwith the endogeneous variable but not with the error term(Hamilton and Nickerson, 2003)

Makes assumptions on the form of endogeneity (more later onthis) and hence might be troublesome for strategy researchWhat is a good instrument and how do we identify one?Weak instruments problem

2 Treatment Effect Models

Self selection correction (Heckman, 1979; Shaver, 1998)Matching models (Rosenbaum and Rubin, 1982)Natural experiments


E d it !!


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Endogeneity!!

Solutions to the Endogeneity problem1 Instrumental Variables

Standard treatment is to find an instrument which is correlatedwith the endogeneous variable but not with the error term(Hamilton and Nickerson, 2003)

Makes assumptions on the form of endogeneity (more later onthis) and hence might be troublesome for strategy researchWhat is a good instrument and how do we identify one?Weak instruments problem

2 Treatment Effect Models

Self selection correction (Heckman, 1979; Shaver, 1998)Matching models (Rosenbaum and Rubin, 1982)Natural experiments


E d it !!


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Endogeneity!!

Intercept vs. Slope Endogeneity

Performance= + Resources

1 Econometrically unobserved factors affect performancethrough the intercept

2 This is one form of endogeneity but not the only one!!

3 Problem has been identified in the literature (Bjorkman andMoffit 1987, Verbeek and Nijman, 1992; Heckman, 1997)

4 Superior performance could be on account of unobservedcorrelated variables which are captured through () -

Intercept Endogeneity5 Superior performance could also be on account of private

information that the manager possesses about the propertiesof the resource captured by () - Slope Endogeneity


Endogeneity!!


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Endogeneity!!



1 Prior research has primarily focused on solving the interceptendogeneity problem

2 Traditional cures for endogeneity such as InstrumentalVariables and Treatment effect models solve interceptendogeneity


Endogeneity!!


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Endogeneity!!



1 However, theoretically slope endogeneity is more appealing to

strategy problems2 E.g. Makadok (2001) talks about superior resource picking as

the path to generate superior advantages.

3 In an empirical test of the RBV this means that managers

should have some private information about which in turnleads to super performance


Treating Slope Endogeneity


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Treating Slope Endogeneity

1 Joint work with Prof. Rodolphe Durand (HEC Paris) and

Prof. Jeffrey Dotson (Vanderbilt University)2 We offer a comprehensive solution to testing the Resource

Based View (RBV)

3 We show that using a simple model of resource picking,

traditional regression models will not estimate the requiredtreatment effect4 We then construct a simple input-output system (Lieberman

and Dhawan, 2005) and estimate structural parameters whileallowing for

Resource Heterogeneity (allow firms to pick resources)Organizational abilities (allow firms to be allocativelyinefficient)Provide an empirical operationalization of how manager skillsdiffer


A simple model of resource picking


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A simple model of resource picking

argmaxr

Bi(r) (r)

where

B(r) = Benefits from the resource = Cost of acquiring/developing the resource

Full information

Applying first order condition and setting = 0 we getoptimal level of resources when B

i(r) = 0

Model suggests that B

i(r) = B

j(r) = for i = j implying noheterogeneity in resource stocks between firms

However, we observe variation in resources and thereforesomething must be wrong!


Why is this a bigger problem!


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Why is this a bigger problem!

If all firms are making optimal choices with respect to theirresources a simple comparison of outcomes represented byE(Bi|R= r) E(Bi|R= 0) is misleading

Intuitively, this suggests that firms that benefit more frommore resources will be worth more

Thus if the firm follow such optimizing behavior, then the truetreatment effect should technically be zero!

This brings into question the validity of those studies which

find positive coefficients on performance-resource regressions


Simulated Example


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Simulated Example


Alternative explanation!


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Alternative explanation!

However an alternative explanation could be identification

through heterogeneity in Our analysis till this point assumes that = 0. However, wenow relax this assumption

Structural interpretation of

captures the cost associated with the resource

We can reframe the problem such that refers to the level ofmanagerial skill in resource picking

Thus managers will superior skills (lower ) will be better at picking

and allocating resources as compared to others.Consistent with the traditional view in strategic factor markettheory (Barney, 1986)

But introduces slope endogeneity in the regression model!!!!


Structural Models of Simultaneous Supply and Demand


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Structural Models of Simultaneous Supply and Demand

We follow the Otter et al. (2008) and Dotson and Allenby (2009)approach to developing a structural model of simultaneous supplyand demand. We begin by consider the following (general) revenuegeneration process:

yit = 0i

K

k=1

xkikit

eit

Where:

yit is revenue realized by unit i in time t{xkit} denotes inputs into the production function



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Optimal Input Selection


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Optimal Input Selection

Optimal inputs, X, can be computed according to the following:

ln (xit) =

ln (x1it)

...ln (xKit)

=

(1i 1) Ki

.... . .

...1i (Ki 1)

1

ln (1 + 1) ln (0i) ln (1i) + ln (p1it)...

ln (K + 1) ln (0i) ln (Ki) + ln (pKit)

We translate this deterministic model of resource selection into astatistical model by introducing error into the system, thusallowing observed allocations to depart from theoretical optimality.


A Simple Example


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p p

We demonstrate the value of our proposed approach in simulation.To simplify exposition (and enhance clarity) we employ thefollowing simplifications of the general model:

1 1 Firm (with many observations)2 1 endogenous resource, R

3 1 exogenous control variable, C

4 Known input prices, = 1


A (Simple) Structural Model of Resource Selection


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( p )

Managers pick the level of resources R utilized in order tomaximize profitability (subject to a resource constraint M):

maxR

0R1C2 R

s.t R M

where:

R denotes the resource of interestC represents an exogenous control variabley = 0R

1C2 is a revenue production function


Simulation Results


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By fixing parameter values and simulating data according to ourmodel, we are able to contrast the proposed methods ability torecover parameter values relative to standard approaches:

Parameter True Value OLS 2SLS Structural Model

0 1.00 1.17 (0.02) 1.16 (0.03) 0.98 (0.04)1 0.15 -0.16 (0.03) -0.14 (0.04) 0.17 (0.07)2 0.55 0.72 (0.03) 0.64 (0.03) 0.52 (0.04) 0.25 0.28 (0.11)2y 0.25 0.24 (0.02)2x1 0.25 0.24 (0.04)

yx1 0.10 0.09 (0.01)


Conclusions


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This work showcases the use of structural modeling instrategy research

The full version of the paper has several extensions e.g: Panel

data, Strategic interactions between firms


Conclusions


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data, Strategic interactions between firmsModel is very general and can accomodate multiple functionalforms


Conclusions


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Model ouput can be used to analyze a wide variety oftheoretical propositions


Conclusions


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Model ouput can be used to analyze a wide variety oftheoretical propositions


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