1. Tacit Knowledge and the Dynamics of Inventor Activity Per Botolf Maurseth (BI, Oslo) Roger Svensson (IFN, Stockholm)

2. Tacit knowledge Inventors know more than what is included in patent application Tacit (experience) vs. codified knowledge (patent application) Pure tacit knowledge vs. spillovers (unintended) Tacit knowledge → cooperation and face-to-face interaction necessary during commercialization Costly to transfer tacit knowledge

3. Purpose Empirically test when tacit knowledge is important for successful commercialization of patents Seldom tested empirically Patent data is appropriate, since patents are related to both codified (application) and tacit knowledge (experience) Unique patent dataset makes test possible: Inventor activity Commercialization mode Profitability of commercialization

4. Model based on Arora et al. (2001) Two-step contract to use patent between inventor (IN) and external firm (F) Transfer of tacit knowledge is beneficial for F and costly for IN. Transfer of tacit knowledge is also risky for IN since IN cannot take the transferred knowledge back once it is transferred and it makes it possible for F to circumvent the patented knowledge. Model shows that: Inventor activity often necessary for success when external firm commercializes the patent. A two stage contract can give IN first best incentives to transfer knowledge. First best transfer depends on the strength of IPR and whether the contract can be renegotiated.

5. Patent database Based on a questionnaire Swedish patents owned by small firms and individuals 867 observations (patents) 80 % response rate Database includes information about inventor activity during commercialization commercialization mode (existing/new firm, sold, licensed) success of commercialization in profit terms Possible to test when inventor activity is important!

6. Commercialization of patents Kind of firm where invention was created Number of patentsPercent commerci- alized Commercialization Total YesNo Medium-sized firms 77 3911666 % Small firms137 6420168 % Micro companies105 3714274 % Inventors20720140851 % Total52634186761 %

7. Performance of commercialization Kind of firm where invention was created Success Total ProfitBreak- even LossMiss. Value Medium-sized firms 55 18 3 1 77 Small firms 97 24 15 1137 Micro companies 60 17 27 1105 Inventors 69 47 87 4207 Total281106132 7526 Considerably worse performance for patents owned by individuals

8. Inventor activity across com. mode Commercialization mode (phase 1) Inventor activity TotalPercent active YesNo Sold 910 1947 % Licensed 3115 4667 % Existing firm, employed1203815876 % Existing firm, owner228 423298 % New firm, owner 70 1 7199 % Total4586852687 % Commercialization mode (phase 2) Sold 82937 22 % Licensed 6 3 9 67 % New firm, owner 4 0 4100 % Total183248 36 %

9. Econometric methodology Dependent variable: Success of commercialization Profit = 2 Break-even = 1 Loss = 0 Ordered probit model with sample selection Two-step procedure: First step: Probit model Second step: Ordered probit model Selection variable = Commercialization (Yes / No)

10. Explanatory variables Dummy for inventor activity Active in phases 1 or 2 = ACTIVE1 and ACTIVE2 Dummies for commercialization modes Sold or licensed in phases 1 or 2 = EXT1 and EXT2 Commercialization mode may change! New firm in phase 1 = NEW1 Interaction dummies between activity and modes Control variables Dummies for size of inventing firm Some characteristics of inventors (ethnics, gender) Technology class dummies

11. Table 6. Phase 1 Dependent variable = SuccessStatistical model = Ordered Probit model Explanatory variables A1A2B1B2C1C2 ACTIVE1+ *** EXT1+ *** −− NEW1+ − ** EXT1*ACT1+ ** + ***+ ** NEW1*ACT1 + + *** Industry classes Yes ρ 0.99 *** 0.96 ***0.99 *** Note: n=858. Standard errors are in parentheses. ***, ** and * indicate significance at the 1%-, 5%- and 10%-level, respectively. Parameter estimates of industry class dummies are not reported, but are available from the author on request..

12. Table 7. Phases 1 and 2 Dependent variable = SuccessStatistical model = Ordered Probit model Explanatory variables D1D2E1E2F1F2 EXT1−−−− EXT2+ *** + **+ * EXT3−− NEW1− ** − ** EXT1*ACT1+ ** + ***+ ** EXT2*ACT1−− EXT2*ACT2++++ EXT3*ACT1+ ** EXT3*ACT2 − − Note: n=858. Standard errors are in parentheses. ***, ** and * indicate significance at the 1%-, 5%- and 10%-level, respectively. Parameter estimates of industry class dummies are not reported, but are available from the author on request..

13. Conclusions Patents are related to both codified and tacit knowledge Unique patent dataset with info on inventor activity, commercialization mode and profitability Inventor activity → Higher profit Especially when patent is licensed or sold to an external firm But also when patent is commercialized in a start-up firm Inventor activity is only important in the first commercialization phase