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Silverman – 1999, MS

Technological Resources and the Direction of Corporate Diversification: Toward an Integration of the Resource-Based View and Transaction Cost Economics. Silverman – 1999, MS. Overview. A study of how a firm’s resource base affects the choice of industries into which the firm diversifies

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Silverman – 1999, MS

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  1. Technological Resources and the Direction of Corporate Diversification: Toward an Integration of the Resource-Based View and Transaction Cost Economics Silverman – 1999, MS

  2. Overview • A study of how a firm’s resource base affects the choice of industries into which the firm diversifies • Silverman (1999)integrates principles of both the Resource-based View (RBV) and Transaction Cost Economics (TCE) to develop a theory of firm diversification • Looks beyond methodologies used at the time to develop new sources of insight into firm behavior

  3. RBV and Diversification • 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 • It is also assumed that R&D intensity, advertising intensity, etc. serve as proxies for underlying resources and that firms will diversify into industries with relative intensities

  4. RBV and Diversification • 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

  5. Hypotheses • 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

  6. Methodology • 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

  7. Variables • Dependent Variable • Divij= 1 where firm (i) enters industry (j) during allotted time • Independent variables • AbsTechij = absolute level of firm (i) patent portfolio applicable to industry (j) • RelTechij = applicability of firm (i) patent portfolio to industry (j) relative to other industries • Royaltyj = the feasibility of licensing innovations in industry (j) • Secrecyj = the importance of secrecy to appropriating returns to innovation in industry (j) • Learningj = the importance of learning curve advantages to appropriating returns to innovation in industry (j)

  8. Variables

  9. The MODEL SPECIFICATION

  10. Correlation Table

  11. Results • Hypothesis 1 was corroborated(AbsTech = significant & positive) • Hypothesis 2 was corroborated(RelTech = significant &positive) • Hypothesis 3a was corroborated(Royalty = significant &negative) • Hypothesis 3b was not supported(Secrecy = not statistically significant) • Hypothesis 3c was corroborated(Learning = significant & positive)

  12. Contributions • 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 • 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”

  13. Contributions • The measure developed by this study links a firm’s position to product markets where its technological strength is likely to offer commercial advantage • 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 to the strongest extent • 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

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