1. Prepared by: Enrique, Lihong, John, Jongkuk
Measuring Competence? Exploring Firm Effects in Pharmaceutical Research Henderson and Cockburn (1994), Strategic Management Journal, 15: 63-84
Prepared by:
Enrique, Lihong, John, Jongkuk

2. Motivation
The resource-based view of the firm suggests that inimitable firm-level heterogeneity, or the possession of unique competencies or capabilities may be an important source of enduring strategic advantage.
Despite the theoretical interest in these ideas, empirical work in the area is still at a preliminary stage.
Relatively little empirical work has attempted to combine the richness of measures of competence derived from field work with large-scale statistical studies of competition.

3. Objectives To explore the nature of firm-level effects
Firm-specific, enduring sources of heterogeneity
To explore the role of competence in pharmaceutical research
Architectural competence
Component competence

4. Prior Research
Three conditions for an organizational competence to be a source of competitive advantage:
Heterogeneously distributed within an industry
Impossible to buy or sell in the available factor markets at less than its full economic value
Difficult or costly to replicate
Unique capabilities in R&D are particularly plausible sources of competitively important competence.
There are significant and persistent differences across firms in their ability to conduct R&D.

5. Definitions
Two classes of capabilities that might act as sources of idiosyncratic firm advantage
Component competence (research program level)
The local abilities and knowledge that are fundamental to day-to-day problem solving
Includes ‘resources’ (Amit and Schoemaker 1993), and ‘knowledge and skills’ or ‘technical systems’ (Leonard-Barton 1992, Teece et al. 1992)
Architectural competence (firm level)
The ability to use these component competencies
Includes ‘integrative capabilities’ (Lawrence and Lorsch 1967), ‘organizational architecture’ (Nelson 1991), ‘dynamic capability’ (Teece et al. 1992), ‘invisible asset’ (Itami 1987), and ‘values and norms’ (Leonard-Barton 1992)

6. Hypotheses Two dimensions of component competence
Unique disciplinary expertise
Disciplinary groups embedded within particular firms develop deeply embedded knowledge or unique modes of working together that make the group particularly effective and that cannot be easily codified.
Knowledge about particular disease areas
H1: Drug discovery productivity is an increasing function of firm-specific expertise in particular disciplinary areas.
H2: Drug discovery productivity is an increasing function of component competence in particular disease areas.

7. Hypotheses Two dimensions of architectural competence
The ability to access new knowledge from outside the boundaries of the organization
The ability to integrate knowledge flexibly across disciplinary and therapeutic class boundaries within the organization
H3: Firms with the capability to encourage and maintain an extensive flow of information across the boundaries of the firm will have significantly more productive drug discovery efforts, all other things equal.
H4: Firms that encourage and maintain an extensive flow of information across the boundaries between scientific disciplines and therapeutic classes within the firm will have significantly more productive drug discovery efforts, all other things equal.

8. Specification of Model
The productivity of drug discovery
Counts of important patents that were granted in two of the three major jurisdictions: Japan, Europe, and the USA
In science-intensive industries such as pharmaceuticals, patents are closely related with economic profitability and market value
y=f (x, β)
y: patent count, x: a vector of inputs to the drug discovery process, β: a vector of parameters
Assume that patent counts are generated by a Poisson process:
E(yit) = λit = exp(xit β)
log(λit) = β log(rit) + δ zit + cit
r: the R&D variables
z: a set of control variables which include measures of competitive activity and measures of scope and scale
c: a set of variables designed to capture heterogeneous firm-level competencies.

9. Data Data sources Quantitative data Qualitative data
Public sources and the internal records of 10 major pharmaceutical firms
Quantitative data
3,210 observations ( ) indexed by firm, research program, and year
Qualitative data
In-depth field interview (110 individuals) to construct the measures of organizational structure and process

10. Measures Component competence
Firm specific expertise in particular discipline: could not be measured.
Component competence in particular disease area
KPATS: the stock of patents previously obtained in each program
Architectural capability
PROPUB: the degree to which standing in the larger scientific community was a dominant criterion for promotion of personnel
CROSS: the degree of communication within the program or across programs within the firm to solve problems
GLOBAL: the degree to which global research was managed as a seamless whole under a single director
DICTATOR: the degree to which resource allocation within research was entirely controlled by a single individual
Control variables
Size, Shape, and scope of the research portfolio
The effects of internal and external spillovers
Therapeutic class dummies: to control for differences in opportunity across classes

11. Architectural Capability
Results: Firm level
DV: patent output at the FIRM level
Indep. Variables
Model1
Model2
Model3
Model4
Firm Dummy
Not included
Included
Architectural Capability
Control variables R2
0.490
0.859
0.655
0.863
Model 2: Introducing firm-level dummy variables in the regression substantially increases the R2 (0.4900.859)
Organizational effects (architectural capability)
Systematic differences across firms in their propensity to patent, accounting practices, and labor market conditions
Model 3: Architectural Capability explains a substantial amount of the variance in patenting at the firms level (R2: 0.4900.655)
Support H3 & H4
Models 2, 3, and 4 show that Firm Dummy and Architectural Capability are not orthogonal, and so the measures of Architectural Capability are the firm effects captured by the Firm Dummy.

12. Results: Program level
DV: patent output at the research program level
Indep. Variables
Model1
Model2
Model3
Model4
Model5
Firm Dummy
Not included
Included
Component Competence
(Program level)
Architectural Capability (Firm level)
Therapeutic class Dummies
Control variables R2
0.383
0.503
0.655
0.446
0.693
Model1: Therapeutic class effects and spillovers are strongly significant in the regressions (R2=0.383).
Model2: Firm dummies significantly increase R2 but they are much less important than at the firm level (R2: 0.3830.503).
Model3 supports H2: component competence has a very significant impact on research productivity (R2: 0.3830.655).
Model4: Architectural capability only marginally improve the overall fit of the equation in the presence of other controls for firm heterogeneity.
Model 5: Preferred model

13. Discussion and Conclusions
Differences in local capabilities may play an important role in shaping enduring differences between firms.
There are long-lived sources of heterogeneity in research productivity across programs.
Econometric Identification Problems
PROPUB and DICATOR research performance
PROPUB and DICATOR may be measures of results as much as they are measures of causes.

14. Discussion and Conclusions
The small changes in the way in which research is managed inside the firm appear to have major implications for its productivity.
The research efforts of firms which score the highest on the use of publication records as an important criterion in promotion are 38% more productive than those at bottom end of the scale.
Firm that allocate resources through a process of consensus appear to be as much as 55% more productive than those which use a ‘dictator’.
It is puzzling that there are such large and persistent differences across firms in these dimensions.
Explanations
The measured capabilities are fundamentally inimitable.
The failure to adopt efficient techniques for managing research reflects agency problems.
The measures reflect the quality of the scientists recruited by the sample companies, rather than any fundamental difference in the quality of the information flow within the organization.

15. Discussion and Conclusions
Firm-specific knowledge is an important source of strategic advantage.
The capability to integrate knowledge both across the boundaries of the firm and across disciplines and product areas within the firm is an important source of strategic advantage.