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THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS
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THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS

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  • 我們建議搜索和知識轉移跨部門多樣化的公司可以培養創新。在期間 1985–96 期間使用來自 1,644 公司的 211,636 專利的樣本,我們發現使用內部間的知識帶來的積極影響後續技術發展的一項發明的影響。此外,使用內部間的知識的一項發明影響的積極作用比使用分區的界限內或從外部企業邊界從知識的效果。我們的實證研究結果在多元化公司產生重大影響的知識管理。
  • 移動周圍不同的企業不有很多共同想法,通用電氣(General Electric)這樣做是因為它有。如果沒有,那麼它只是一個控股公司。。。。通用電氣公司自有的醫療系統業務,與相對較小的修改,導致了一種由哪一家飛機引擎可以發送連續信息有關刀片的速度,發動機熱機和其他相關數據關於其在飛行性能以及在任何可能的安全形勢之前的方法。這一創新,進而催化的一個重要的新的發展方面的自我監控系統,裝有心臟起搏器的使用。我還可以舉出一些其他的例子,做共享的銷售方法,採購技術,提高了存儲程序和數據的安全性等。
  • 簡介新知識開發對於創新方法論結果討論
  • 資料和樣本專利引用措施 : 度量法分析
  • 這項研究的主要資料來自於國家經濟研究署(美國)專利引用包括(統一證券辨認委員會(美國)所認證,範圍則是包含於 1969–1999 年間的專利資訊。 該資料所列出包含公司和業務單位,每個專利申請、 及技術類的每個專利所屬,以及與每個專利相關的被引用專利。另外補充的資料來源為Micropatent公司 (湯姆森收購-2004)。它是線上的專利和商標資訊商業來源。該服務提供了可全文搜索的專利資料庫,該專利資料庫包括從法國、 德國、 日本、 英國、美國、歐洲專利局(EPO)和世界智慧財產權組織(WIPO)。
  • 這份研究包括在不同行業中的公司的運作,在專利類別或技術領域兩者之間發展專利等級並控制其差異的引用行為是有必要的.單一事業公司可能在其定位或工作小組兩者間進行知識轉移,但我們假設認為這種現象是使用知識範圍內企業結構的公認司的界線。因此我們用十年的資料來建立控制變數,只納入 1985–96 間的專利。還有,用所需的計量經濟模型來觀察各個公司至少兩組以上的發明,及一個以上非零值的因變數.因此, 這測試樣本我們假設有 211,636 個專利.
  • 本研究從 NBER & MicroPatent(Thomson Reuters)取得了 1985 至 1996 年間在 1,644 間公司的 211,636 個專利
  • 專利引用美國專利和商標辦公室負責監督進程的給予產權到發明家的發明,是“有用的”和“新奇的"。根據法律規定,專利申請人和他們的律師必須包括在應用程式中所有"事先藝術",他們都意識到: 他們正在尋求對專利和其索賠以前有關該項發明的專利。專利審查員的法官這些引文的充分性。"原則上,由專利 Y 專利 X 的引文指示專利 Y 借鑒以前現有專利 X 中所體現的知識"。
  • 因變數自變數控制變數
  • 線性迴歸Apples are sold for $2.00 a pound.If people had unlimited resources when purchasing apples, then the total cost of apples purchased would be dependent upon the number of pounds of apples purchased. 蘋果賣為 2.00 美元為一英磅。如果人們有無限的資源,可以購買的蘋果,然後購買蘋果的總費用將取決於每英鎊購買蘋果的數量。
  • 因變量的影響,測量的程度,一個企業的專利,隨後其他公司的專利引用。被視為更具相關性,創新性,重要的不是那些被忽略的專利被引用的專利,其他公司在未來的發展。大廳和Trajtenberg(2000)提供的這些“向前參考文獻的證據的審查。”弗萊明和索倫森寫一個專利的數量向前參考文獻相關性高,其技術的重要性,作為測量專家意見,社會價值,和行業獎項“。此外,高被引專利專利權人以外,經常提到的導致更多的經濟利益。要測量的影響,我們計算了後續的專利,不包括自引,在此期間1985年至1996年的焦點專利被引用的總次數。
  • 若要創建主要的獨立變數,我們審查了焦專利引文模式,以確定是否由同一司舉行過的被引的專利、 在同一個組織或另一個組織中的另一個司。每個變數的內部分區自我引文數的計數,除分區自我的引文或額外組織引文。
  • 如上所述,理論的本地搜索意味著除了直接流到另一個發明家從知識的專利引文的頻率模式。例如,某一維的本地搜索是時間。當發明家結合先進的知識元件,而不是較舊的技術時,他們的發明有更大的影響。因此,我們包括所有引文所作的每個專利,平均引文年齡的平均年齡的措施。我們還計算結合較早和較新的知識元件中的潛在效益作用控制的引文年齡差異。一些引專利權被授予前擁有權或技術域上的資料都在資料庫中,可用,但而不是排除這些引文,我們計他們為其他引文。
  • 近的重要性遠遠超出特定被引專利也有科學的進步,要考慮的"熱點"地區。如果發明人不熟悉微電子中的最新發現,他們可能不能設計一個玩具、 一個裝置或甚至將擁有所有功能客戶想要的服裝的一個專案。我們的每個專利的技術域分配依靠主美國專利類,它屬於,但最多的專利分配多個二級類,以説明將來的專利搜索。對最近看到率高的積極申請專利的技術類的引用影響影響。我們計算特定子類列出 (更多最近使用計數更重貼現隨著時間的推移使用) 的次數要創建的元件熟悉到這種效果的控制措施。
  • 它也是可能發明家或專利審查員熟悉技術的每個域中的某些關鍵專利,並通過尋找其他引用這些關鍵專利的專利進行他們的搜索。或發明家可能嘗試援引來自其他域的知名專利的信號其索賠的廣度。我們控制援引重要前體通過的時間包括變數影響轉發引文以前引張的引文從所有受讓人,調整減去的年均過去十年的可能性。除了任何特定的專利或任何類別的最近和頻繁使用,更多的輔助類指專利是更有可能把其他發明家的搜索中,因此更有可能引。因此,菲林明道與 Sorenson (2004 年) 發現被合併為一項專利技術的數目和轉發次數之間的關係。我們複製他們的主要類的數目、 的子類,數目和虛擬變數,以指示當專利列出僅向這些效果控制單個子類的措施。
  • 最後,模型還包括四套虛擬變數。第一、 年為 96,與作為引用者,1985年 1986– 控制的未觀測因素隨時間而異,但對於整個公司 (例如,經濟週期) 是相對不變的的傻瓜書。此外,年三十年來控制為較新的專利,以接收較少比老年人專利引文的趨勢。第二,行業傻瓜書控制的特定于行業的影響。公司均以兩位數的 SIC 程式碼業,他們進行大部分工序的分類。我們從 COMPUSTAT 獲得這些資料。行業與只有一間公司或小於 1%的樣本中的專利的假變數被省略,援助收斂。第三,技術是假捕獲專利技術域的行為差異。例如,大廳中南工業大學 (2001 年) 顯示引文在某些領域比其他人來得更快。獲得的能力,包括技術管制是我們定義在專利一級,該示例的一個主要原因,而不將聚合到公司一級。第四,受讓人固定在固定效應模型中的影響和控制的可能超過申請專利公司內部分歧顯著差異的因素的隨機效應模型中的隨機效果受讓人。
  • 我們的考試分析單位是發明。為了評估搜索行為和發明的影響之間的關係,我們使用面板資料 (即截面、 時間序列資料)。每個依賴變數是一個非負的事件計數。展出的從屬變數 over-dispersion 差異大大超過了平均值和負二項式回歸從而更常見的泊松模型相比是首選。然而,與負二項式模型假設是事件計數是獨立的而不是這裡的情形。為彌補非獨立性,我們進行了我們使用固定效果的分析和隨機效應的負二項式模型通過 STATA 中的 XTNBREG 過程。因為隨機效應模型產生了幾乎完全相同的估計,我們只報告從固定效應模型的估計。
  • 以前的研究相比,穩固性檢查限制和未來研究
  • 專利引文和知識流部門和地域界限分部和收購衝擊與企業績效
  • Transcript

    • 1. THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS DOUGLAS J. MILLER University of Illinois at Urbana-Champaign MICHAEL J. FERN University of Victoria LAURA B. CARDINAL Tulane University
    • 2. Abstract • • • • We propose that searching for and transferring knowledge across divisions in a diversified firm can cultivate innovation. Using a sample of 211,636 patents from 1,644 companies during the period 1985–96, we find that the use of interdivisional knowledge positively affects the impact of an invention on subsequent technological developments. Furthermore, the positive effect of the use of interdivisional knowledge on the impact of an invention is stronger than the effect of using knowledge from within divisional boundaries or from outside firm boundaries. Our empirical findings have significant implications for the management of knowledge in diversified firms.
    • 3. • As to moving ideas around diverse businesses that don’t have a lot in common, General Electric does this because it has to. If it doesn’t, then it is just a holding company. . . . • A breakthrough in GE’s Medical Systems business, with relatively little modification, led to a method by which an aircraft engine can transmit continuous information about blade speed, engine heat and other relevant data about its in-flight performance well in advance of any possible safety situation. • • This innovation, in turn, catalyzed an important new development with respect to a self-monitoring system for use with heart pacemakers. I could cite any number of other examples having to do with sharing methods of selling, sourcing techniques, procedures for improved storage and security of data and so on. Steve Kerr, vice president of Corporate Leadership Development and chief learning officer, General Electric Corporation, 1997
    • 4. THE USE OF KNOWLEDGE FOR TECHNOLOGICAL INNOVATION WITHIN DIVERSIFIED FIRMS INTRODUCTION SOURCING KNOWLEDGE FOR INNOVATION METHODOLOGY RESULTS DISCUSSION
    • 5. 2) SOURCING KNOWLEDGE FOR INNOVATION The Use of Local and Distant Knowledge Knowledge Exploration across Organizational Boundaries Hypotheses
    • 6. 2.2) Knowledge Exploration across Organizational Boundaries Organizational boundaries Intrafirm technological diversity Firm divisionalization
    • 7. 2.3) Hypotheses Intradivisional knowledge Extraorganizational knowledge Interdivisional knowledge Interdivisional versus other knowledge
    • 8. 3) METHODOLOGY Data and Sample Patent Citations Measures Analysis
    • 9. 3.1) Data and Sample • The main data for this research were obtained from the National Bureau of Economic Research(NBER) Patent Citations Data include Committee on Uniform Security Identification Procedure(CUSIP) identifiers, which contains a breadth of information concerning every patent granted in the period 1969–99. • The data file lists the corporation and business unit that applied for each patent, the technological class to which each patent belongs, and the cited patents associated with each patent. • We supplemented these data with additional information on the relevant patents using a database from the Micropatent Corporation(Thomson takeover-2004).
    • 10. 3.1) Data and Sample • The study includes firms that operate in different industries, it is necessary to move to the patent level to control for differences in citation behavior between patent classes or technological domains. • Single-business firms may transfer knowledge between locations or work teams, but the phenomenon considered in our hypotheses is use of knowledge over the boundaries of recognized divisions within a corporate structure. • Because we used ten years of data to create control variables, only patents from 1985–96 were included. • Also, the econometric model required the observation of at least two patents for each firm, with at least one having a nonzero value for the dependent variable. Thus, the sample for tests of hypotheses was 211,636 patents.
    • 11. 3.1) Data and Sample Using a sample of 211,636 Patents from 1,644 Companies during the period 1985–96
    • 12. 3.2) Patent Citations • The U.S. Patent and Trademark Office oversees the process of granting property rights to inventors for inventions that are “useful” and “novel.” • By law, patent applicants and their lawyers must include in applications all “prior art” of which they are aware: previous patents relating to the invention they are seeking to patent and its claims. • A patent examiner judges the adequacy of these citations. “In principle, a citation of Patent X by Patent Y indicates that Patent Y builds upon previously existing knowledge embodied in Patent X”.
    • 13. 3.3) Measures Dependent variable Independent variables Control variables
    • 14. Dependent and Independent variables http://www.narragansett.k12.ri.us/resources/necap%20sup port/gle_support/Math/resources_functions/dep_indep.htm
    • 15. 3.3.1) Dependent variable • The dependent variable, impact, gauged the degree to which a firm’s patents are subsequently cited by patents of other firms. • Patents that are cited in future developments by other firms are deemed more relevant, innovative, and important than those patents that are disregarded. • Hall and Trajtenberg (2000) provided a review of the evidence on these “forward citations.” Fleming and Sorenson wrote that a patent’s number of forward citations “correlates highly with its technological importance, as measured by expert opinions, social value, and industry awards.” • Furthermore, highly cited patents lead to more economic profits than patents that are less frequently cited. • To measure impact, we counted the total number of times a focal patent was cited by subsequent patents, excluding self-citations, over the period 1985–96.
    • 16. 3.3.2) Independent variables • To create the main independent variables, we examined a focal patent’s citation pattern to determine whether the cited patents were held by the same division, another division in the same organization, or another organization. • Each variable was a count of the number of intra-divisional selfcitations, interdivisional self-citations, or extra-organizational citations.
    • 17. 3.3.3) Control variables • As noted above, the theory of local search implies patterns in the frequency of patent citations besides the direct flow of knowledge from one inventor to another. • For example, one dimension of local search is time. • When inventors combine state-of-the-art knowledge components rather than older technology, their inventions have greater impact. • Thus, we included a measure of the mean age of all citations made by each patent, average citation age. • We also computed the variance in citation age to control for the potentially beneficial effects of combining older and newer knowledge components. • Some cited patents were granted before data on ownership or technology domain were available in the database, but rather than exclude these citations, we counted them as other citations.
    • 18. 3.3.3) Control variables • Our assignment of each patent to a technological domain relied on the primary U.S. patent class to which it belonged, but most patents are assigned multiple secondary classes to aid future patent searches. • Counted the number of times a particular subclass was listed (discounting over time so more recent use counted more heavily) to create a measure of component familiarity to control for this effect. • Controlled for the possibility that citing important precursors affects forward citations by including a variable for the times previously cited a count over the last ten years of citations from all assignees, adjusted by subtracting the annual mean. • Replicated their measures of the number of major classes, the number of subclasses, and a dummy variable to indicate when a patent listed only a single subclass to control for these effects.
    • 19. • • • • • 3.3.3) Control variables Adopted Fleming and Sorenson’s (2004) measure of coupling to indicate “the degree to which an invention’s components have been previously combined . . . [because] combining some pieces which interact sensitively with each other proves more difficult than connecting relatively independent chunks of knowledge”. Our focus on multi-business firms in the broad economy suggests additional controls. Added the logarithm of firm assets (in millions of dollars) to control for the possibility that market power, economies of scale in R&D, or similar factors play a role in how patents are cited. Included a measure of technological diversity, an entropy index using the patent class of all patents filed by a firm in the five years prior to the observed patent. Thus, we included the number of assign assignees in a firm, measured as the number of subsidiaries that applied for patents in the year of a focal patent application.
    • 20. 3.3) Measures • Finally, the models also included four sets of dummy variables. • • • • First, year dummies for 1986– 96, with 1985 as the referent, controlled for unobserved factors that vary over time but are relatively invariant across firms (e.g., economic cycles). In addition, the year dummies controlled for the tendency for newer patents to receive fewer citations than older patents. Second, industry dummies controlled for industry-specific effects. Firms were classified according to the two-digit SIC code industry in which they conducted most of their operations. We obtained these data from COMPUSTAT. Dummy variables for industries with only one firm or with less than 1 percent of the patents in the sample were omitted to aid convergence. Third, technology dummies captured differences in patenting behavior according to technology domain. For example, Hall et al. (2001) showed that citations come more quickly in some domains than others. Gaining the ability to include technology controls was a major reason we defined the sample at the patent level, rather than aggregating to the firm level. Fourth, assignee fixed effects in the fixed-effects model and an assignee random effect in the random-effects model controlled for factors that might vary substantially over patenting divisions within firms.
    • 21. 3.4) Analysis • • • • • • For our examination, the unit of analysis was the invention. To assess the relationship between search behavior and an invention’s impact, we used panel data (i.e., cross-section, time series data). Each dependent variable was a nonnegative event count. The dependent variables exhibited over-dispersion the variance significantly exceeded the mean and thus negative binomial regression was preferred over the more common Poisson model. However, the assumption with a negative binomial model is that event counts are independent, which was not the case here. To compensate for non-independence, we conducted our analysis using fixed-effects and random-effects negative binomial models via the XTNBREG procedure in STATA. We only report estimates from the fixed-effects models because the randomeffects models yielded almost identical estimates.
    • 22. 4) RESULTS
    • 23. Table1 a Statistics and Correlation Matrix
    • 24. 5) DISCUSSION Comparison to Prior Research Robustness Check Limitations and Future Research
    • 25. 5.1) Comparison to Prior Research • We began this paper by discussing the potential problems associated with local and distant exploration. • Focus on a given expertise underpins the development of core capabilities, yet failure to explore beyond existing techniques leads to a decayed competitive stance. • We have presented the sourcing of distant knowledge from disparate divisions in a diversified firm as an alternative.
    • 26. 5.1) Comparison to Prior Research • The value of interdivisional knowledge sharing is even greater than what is revealed in these empirical results. • Our findings confirmed that the use of interdivisional knowledge is effective in innovation activities. • Thus, there are times when local knowledge is more valuable than distant knowledge; the problem with local search is that inventors often use local knowledge too frequently.
    • 27. using our independent variables, including the interdivisional citations use Rosenkopf and Nerkar’s (2001) independent variables separate the backward citations according to both divisional and technological boundaries
    • 28. 5.2) Robustness Check • To gain a finer-grained measure of the knowledge being used from prior patents, we distinguished the first backward citation by an assignee to any particular patent and then reran the analysis as discussed above. • We conjectured that the first use of a specific patent likely represents a greater degree of knowledge use than do subsequent citations of that same patent. • We find that first-use citations have a more strongly positive effect on impact whether they refer to intra-divisional, interdivisional, or extraorganizational patents.
    • 29. 5.3)Limitations and Future Research Patent citations and knowledge flows Divisional and geographic boundaries Divisions and acquisitions Impact and firm performance
    • 30. Patent citations and knowledge flows • Patenting is a coarse measure of the knowledge firms possess and maintain, and citations are not an exhaustive measure of knowledge flows. • Citation can mean something other than the use of knowledge from a prior patent. • According to past research, examiners seem to add citations that come from various sources—the same division, other divisions in the same firm, and other firms—in the same proportion as inventors cite from each source. • Therefore, the examiner citations should be adding similar noise to each type.
    • 31. Divisional and geographic boundaries • This study examined only two dimensions of distance in knowledge: • • Technological domains Organizational boundaries. • Our exploratory research showed a high correlation between divisional boundaries within the diversified firms and the locations of the inventors by state in our sample: • Divisions that file patents separately from their parent organization tend to be geographically distant from other divisions in the same firm. • However, as scholars attempt to incorporate multiple dimensions of knowledge distance into a single study, divisional boundaries need to be considered to have a full view of the effects of a firm using its existing knowledge.
    • 32. Divisions and acquisitions • This study should be interpreted as a close complement to research on acquisitions as a means to facilitate knowledge transfer. • An acquiring firm gains control of its target firm’s employees and routines and thus its tacit knowledge, but at the risk of alienating employees or overpaying for the target firm. • Also, our finding that most interdivisional citations were within single domains is consistent with the literature’s emphasis on horizontal acquisitions. • Distant search across “unrelated” divisions might be rare, but also less imitable, and thus a possible source of sustainable competitive advantage.
    • 33. Impact and firm performance • Finally, we have not linked our dependent variable to product-market or firm financial performance. • Despite 30 years of research, there is still extensive debate concerning the relationship between corporate diversification and performance. • If synergy is based upon shared R&D knowledge, then small coordinating units may achieve this with only minimal interference in divisional authority”. • Further research linking the use of different types of knowledge to firm financial performance could estimate the benefits of such hybrid diversification strategies.
    • 34. Q&A

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