Henderson, R. & Cockburn, I. (1994). Measuring Com-petence? Exploring Firm Effects in Pharmaceutical Re-search. Strategic Management Journal, 15: 63-84.

Seung Hoon Lee

Empirical work on Resource Based View so far…

Firm effects account for diversification strategy (Hitt & Ireland, 1985; Montgomery & Wernerfelt, 1988) and performance (Cool & Schendel, 1988; Rumelt, 1991).

But… Few studies considered particular competences(had to rely on aggregate level measures of compe-tence)

And more importantly, a puzzle remained from their own recent research (using the same data set). - A more direct motivation of the study

Overview

Henderson, R. & Cockburn, I. (1994). Scale, Scope and Spillovers: The Determinants of Research Productivity in Drug Discovery. NBER Working Paper. (Later published in Rand J Econ, 1996)

Originally about firm size (economy of scope) and efficiency in management of research.

But also found, 1) Variance in research productivity explained by firm fixed effects after controlling for firm size, scope, program size, etc.2) Despite the fact that differences in the structure of the research portfolio (e.g., industry) had significant effects on research productivity, variations in portfolio structure across firms were persistent (e.g., firm specific competence).

Guided by the resource-based view lens, the authors at-tempt to explain these finings.

Why (Pharmaceutical) Research?

Successful research efforts take many years to build and often rely on idiosyncratic search routines that may be dif-ficult to transfer across organizations (Nelson, 1991).More Generally, Knowledge as exemplar of valuable, rare, imperfectly imitable, non-substitutable resource.

In particular,

Absorptive Capacity (Cohen & Levinthal, 1990) Combinative Capability (Kogut & Zander, 1992)

Dynamic Capability (Teece, Pisano & Shuen, 1997)...

Architectural Competence (Henderson & Cockburn, 1994)A Proliferation of Concepts?

Architectural Competence

Component Competence - Abilities or knowledge specific to particular local

activities within the firm (e.g., expertise in partic-ular disciplinary areas)

- Fundamental to day-to-day problem solving

Architectural Competence - Ability to use component competence - Integrate them effectively and to develop fresh

component competences as they are required

Hypotheses

Component CompetenceHypothesis1: Drug discovery productivity is an increasing function of firm specific expertise in particular disciplinary areas (e.g., molecular biology, physiology, biochemistry, etc.)Hypothesis2: in particular disease areas (e.g., diabetics, anxiety)

Architectural CompetenceHypothesis3: Firms with the ability to encourage and maintain an extensive flow of information across the boundaries of the firm will have significantly more productive drug discovery ef-forts, all other things equal.Hypothesis4: Firms that encourage and maintain an extensive flow of information across the boundaries between scientific disciplines and therapeutic classes within the firm will have sig-nificantly more productive drug discovery efforts, all other things equal.

Sample and Data, Measures of Variables

Population: Firms in pharmaceutical industry

Sample: 10 major European and American firms- Data collection at research project level- 3210 observations (research project * year)- Data source: archival for drug discovery productivity; internal

for R&D input; qualitative for Architectural Com-petence

Variables- Productivity: Counts of “Important” patent grants. (Impor-

tant, if granted in at least two out of America, EU, Japan)

- Size (R&D input): Annual expenditures on exploratory re-search and clinical development by research program

- Other controls: shape, scope of research portfolio, internal and external spillovers, therapeutic class dummies

Measures of Variables

Variables- Component Competence 1) firm specific expertise in particular disciplinary areas:

not measured, not tested 2) firm specific expertise in particular disease areas: the

stock of patents obtained in each program (stock calcu-lated by assuming 20% depreciation rate for knowl-edge)

- Architectural Competence: 3) Information flow between the boundaries of firms: the

degree to which reputation in wider community is the dominant criterion for promotion of scientific personnel

4) Information flow within firms (between scientific disci-plines and therapeutic classes): the degree of ex-change of rich information; the degree of regional inte-gration; the degree of centralized resource allocation (inverse)

Model Specification

Poisson Process1) Poisson Distribution (mean=variance for d.v.) if violated, estimators consistent but standard errors underes-timated2) Negative Binominal (gamma distribution for residual term) if violated, estimators inconsistent3) Nonlinear least-square estimates4) quasi-generalized pseudo-maximum likelihood (or weighted 3))

For robustness check

Assumption check: ANOVAMost of the variance for Architectural Competence variables are accounted by between firms rather than within firms

Results

Results