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Measuring Competence? Exploring Firm Effects in Pharmaceutical Research Henderson and Cockburn (1994), Strategic Management Journal, 15: 63 -84 Prepared by: Enrique, Lihong, John, Jongkuk 1
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 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. 2
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 3
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. 4
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 dayto-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) 5
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 H 1: Drug discovery productivity is an increasing function of firm-specific expertise in particular disciplinary areas. H 2: Drug discovery productivity is an increasing function of component competence in particular disease areas. 6
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 H 3: 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. H 4: 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 7 other things equal.
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 8 competencies.
Data sources Public sources and the internal records of 10 major pharmaceutical firms Quantitative data 3, 210 observations (1975 -88) indexed by firm, research program, and year Qualitative data In-depth field interview (110 individuals) to construct the measures of organizational structure and process 9
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 10 across classes
Results: Firm level DV: patent output at the FIRM level Indep. Variables Model 1 Model 2 Model 3 Model 4 Firm Dummy Not included Included Architectural Capability Not included Included Control variables Included R 2 0. 490 0. 859 0. 655 0. 863 Model 2: Introducing firm-level dummy variables in the regression substantially increases the R 2 (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 (R 2: 0. 490 0. 655) Support H 3 & H 4 Models 2, 3, and 4 show that Firm Dummy and Architectural Capability are not orthogonal, and so the measures of Architectural Capability are the 11 firm effects captured by the Firm Dummy.
Results: Program level DV: patent output at the research program level Indep. Variables Model 1 Model 2 Model 3 Model 4 Model 5 Firm Dummy Not included Included Component Competence (Program level) Not included Included Architectural Capability (Firm level) Not included Included Therapeutic class Dummies Control variables Included Included R 2 0. 383 0. 503 0. 655 0. 446 0. 693 Model 1: Therapeutic class effects and spillovers are strongly significant in the regressions (R 2=0. 383). Model 2: Firm dummies significantly increase R 2 but they are much less important than at the firm level (R 2: 0. 383 0. 503). Model 3 supports H 2: component competence has a very significant impact on research productivity (R 2: 0. 383 0. 655). Model 4: Architectural capability only marginally improve the overall fit of the equation in the presence of other controls for firm heterogeneity. 12 Model 5: Preferred model
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. 13
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. 14
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. 15