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Technological Resources and the Direction of Corporate Diversification: Toward an Integration of the Resource- based View and Transaction Cost Economics.

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Presentation on theme: "Technological Resources and the Direction of Corporate Diversification: Toward an Integration of the Resource- based View and Transaction Cost Economics."— Presentation transcript:

1 Technological Resources and the Direction of Corporate Diversification: Toward an Integration of the Resource- based View and Transaction Cost Economics Silverman, B. S. 1999. Management Science, 45(8): 1109-1124. Rotman School of Management PhD, UC Berkeley MA, UC Berkeley SM, MIT AB, Harvard Presented by Jae Kyun Yoo

2  A study of how a firm’s resource base affects the choice of industries into which the firm diversifies.  Empirically, operationalizes technological resources at a more fine-grained level than has been done in prior resource-based research.  Theoretically, examines and tests the assumption that rent- generating resources are necessarily too asset specific to allow contracting (link between RBV and TCE). OVERVIEW

3  RBV describes the firm as a “collection of sticky and imperfectly imitable resources or capabilities that enable it to successfully compete against other firms” (see Penrose, 1959).  These same characteristics prevent firms from “transplanting” resources into new contexts.  It is assumed that more “related” diversification supports more extensive exploitation of resources.  Studies use SIC system to measure degree of industry relatedness.  R&D intensity, advertising intensity, and other such investments serve as proxies for underlying resources and that firms will diversify into industries with relative intensities. RBV AND DIVERSIFICATION

4  However, current studies depend on strong assumptions regarding the ordering and applicability of the SIC system as well as the fungibility of R&D and advertising intensity.  Popular studies on diversification using RBV characterize resources at the industry level, and leave open the effects of firms’ repositories of expertise or technology.  Identification of individual firms’ resources allows for greater insights into the role of resources in diversification. RBV AND DIVERSIFICATION

5  Hypothesis 1: Ceteris paribus, a firm is more likely to diversify into a business the more applicable its existing technological resources are to that business (in absolute terms).  Hypothesis 2: Ceteris paribus, a firm is more likely to diversify into a business the more applicable its existing technological resources are to that business, relative to other opportunities facing the firm.  Hypothesis 3. Ceteris paribus, a firm is more likely to diversify in to a business the more likely that contracting out its technological resources in that business is subject to high contractual hazards.  A: A firm is more likely to diversify into a business as the feasibility of licensing its technological resources in that business decreases.  B: A firm is more likely to diversify into a business as the need for secrecy to appropriate returns to its technological resources in that business increases.  C: A firm is more likely to diversify into a business as the degree of tacit knowledge associated with its technological resources in that business increase. HYPOTHESES

6  The empirical test of the hypotheses entailed estimating the entry of existing firms into new SICs during the three-year window 1982-1985 as a function of firm, industry, and resource characteristics in 1981.  Each firm’s resource base was determined through the use of patent data.  Issues arise where firm knowledge is not patented due to ineligibility or firm choice.  It should also be noted that differences in the comprehensiveness of patenting may exist across firms, industries, and time. METHODOLOGY

7  Dependent Variable  Div ij = 1 where firm (i) enters industry (j) during allotted time  Independent variables  AbsTech ij = absolute level of firm (i) patent portfolio applicable to industry (j)  RelTech ij = applicability of firm (i) patent portfolio to industry (j) relative to other industries  Royalty j = the feasibility of licensing innovations in industry (j)  Secrecy j = the importance of secrecy to appropriating returns to innovation in industry (j)  Learning j = the importance of learning curve advantages to appropriating returns to innovation in industry (j) VARIABLES

8

9 MODEL SPECIFICATION

10 CORRELATION TABLE

11 RESULTS Hypothesis 1 supported. Hypothesis 2 supported. Hypothesis 3a, 3c supported.

12  This paper has many firsts:  Measures effects of firm heterogeneous technological resources via patent data on diversification.  Examines empirically the hypothesis that firms prioritize their diversification options according to the relative applicability of their resources.  Examines empirically the role of transaction costs on diversification in an RBV context. CONTRIBUTIONS

13  The results of this study suggest that a firm’s technological resource base significantly influences its diversification decisions (as seen through a patent portfolio lens).  Firms elect to enter markets where it can exploit its existing technological resources and in which its existing technological resource base is strongest.  Firms’ diversification decisions are influenced by the severity of hazards surrounding contractual alternatives  The source of innovation in an industry indicates the direction of likely diversifying entry into that industry. (Pavitt et al., 1989)  This study integrates TCE with RBV and suggests that “while conflicts between the two theories exist, the strong complementarities between them should not be ignored”. CONTRIBUTIONS


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