Academic involvement in technology activity: do modes of involvement make a difference? The Flemish case. Julie Callaert, Mariette Du Plessis, Bart Van.

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Presentation transcript:

Academic involvement in technology activity: do modes of involvement make a difference? The Flemish case. Julie Callaert, Mariette Du Plessis, Bart Van Looy Research Division INCENTIM – Faculty of Business and Economics ECOOM KU Leuven

Background -Increased reliance on indicators for mapping and monitoring science-technology interactions in innovation systems -Indicators based on “university-owned” patents (i.e. patents with universities acting as assignees) do not reveal the full picture of university involvement in technology development -Need for identifying patents that are “university- invented” (and not university-owned) -…to grasp a more complete picture of academic patenting -…to allow for the assessment of differences between university- owned and university-invented patents

Background -Sharp increase in academic patenting has raised suspicions / fears about decreasing quality of university patents  relevance of analyzing patent-value of academic patents -Research objective: to study whether modes of involvement in academic patenting matter for patent value -Assessment of differences between university-owned and university-invented patents in terms of : -‘Originality’ (or: relatedness to a more diverse knowledge base): extent to which the nature of the research underlying the patent is based on prior art in a broad range of fields -‘Generality’: extent to which the outcome of the research serves as prior art for a broad range of technology fields -‘Impact’: assessed by forward patent citations

Data & Methodology Data cover Flemish universities: KU Leuven (KUL), Universiteit Gent (UG), Universiteit Antwerpen (UA), Universiteit Hasselt (UH) and Vrije Universiteit Brussel (VUB) Identification of university-owned patents: –EPO and USPTO granted patents –with at least 1 Flemish university as applicant (< ECOOM sector allocation and name harmonization) –application years (allowing for time window forward citations)

Data & Methodology Identification of university-invented patents: –We consider all inventor names on EPO and USPTO granted patents with application years between –Personnel data files of the Flemish universities for the years –Matching between personnel surnames and inventor surnames First visual scan to eliminate certain mismatches For the withheld potential matches: search contact details of university researcher Contact researcher to confirm inventorship Only confirmed matches are retained in the database

Data & Methodology

Additional information extracted for all withheld university-owned and university-invented (source) patents (Source: PATSTAT version Autumn 2011): -Technology domains of source patent (IPC 1 digit) -Applicants and inventors of source patents -Backward cited and forward citing patents with respective IPC3digit codes -Number of cited non-patent references

Data & Methodology Unit of analysis = patent Dependent Variables: Indicators related to patent ‘value’: Impact (number of forward patent citations) as basic quality indicator Forward citation window: 9 years Originality:extent to which the nature of the research underlying the patent is based on prior art in a broad range of fields calculated as 1- the Herfindahl index of technological classes (3 digit IPC) of all backward cited patents Generality: extent to which the outcome of the research serves as prior art for a broad range of technology fields. calculated as 1- the Herfindahl index of technological classes (3 digit IPC) of all forward citing patents Independent variable: University-owned <> University-invented Control variables: Application year, Technological field (IPC1 digit level), Technological breadth (number of IPC3 digit codes), Patent system (EPO / USPTO) Number of backward patent citations Number of non-patent references

Descriptives IPC (1 digit) University- invented University- owned Total A. HUMAN NECESSITIES136 (74%)47 (26%)183 (100%) B. PERFORMING OPERATIONS; TRANSPORTING59 (88%)8 (12%)67 (100%) C. CHEMISTRY; METALLURGY196 (76%)63 (24%)259 (100%) D. TEXTILES; PAPER2 (40%)3 (60%)5 (100%) E. FIXED CONSTRUCTIONS2 (67%)1 (33%)3 (100%) F. MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING 2 (100%)0 (0%)2 (100%) G. PHYSICS66 (58%)48 (42%)114 (100%) H. ELECTRICITY38 (44%)49 (56%)87 (100%) TOTAL501 (70%)219 (30%)720 (100%) University- invented University- owned Total EPO grants59 (63%)35 (37%)94 (100%) USPTO grants260 (69%)117 (31%)377 (100%) Total319 (68%)152 (32%)471 (100%)

Descriptives Sector-breakdown of university-invented patents: Sector breakdown of university-owned patents: -19% is co-owned with a non-profit or governmental institute - 8% is co-owned with a company - 6% is co-owned with an individual SECTOR% university-invented patents COMPANY92% INDIVIDUAL5% GOV NON-PROFIT3%

Correlations GENERALITYORIGINALITYIMPACT NBR BW PAT CITNBR IPC3APPYNBR NPR GENERALITYPearson Correlation1,386 **,036,043,221 **,004,082 * Sig. (2-tailed),000,386,303,000,917,049 N ORIGINALITYPearson Correlation,386 ** 1-,116 **,194 **,365 ** -,041,164 ** Sig. (2-tailed),000,004,000,313,000 N IMPACTPearson Correlation,036-,116 ** 1,135 ** -,214 **,153 **,004 Sig. (2-tailed),386,004,000,921 N NBR BW PAT CITPearson Correlation,043,194 **,135 ** 1-,080 *,179 **,699 ** Sig. (2-tailed),303,000,032,000 N NBR IPC3Pearson Correlation,221 **,365 ** -,214 ** -,080 * 1-,048,022 Sig. (2-tailed),000,032,201,559 N APPYPearson Correlation,004-,041,153 **,179 ** -,0481,043 Sig. (2-tailed),917,313,000,201,252 N NBR NPRPearson Correlation,082 *,164 **,004,699 **,022,0431 Sig. (2-tailed),049,000,921,000,559,252 N **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

Results: Originality (ANCOVA) Dependent Variable:ORIGINALITY Source Type III Sum of SquaresdfMean SquareFSig. Corrected Model 5,390 a 13,41511,539,000 Intercept,0871 2,408,121 Univ-owned / Univ-invented,0101,270,604 Patent System,0401 1,125,289 Tech domain IPC1,5567,0792,212,032 Appl year,0811 2,258,133 Tech breadth (# IPC3) 3, ,219,000 NBR BW PAT CIT, ,666,000 NBR NPR,0201,554,457 Error21,236591,036 Total213, Corrected Total26, a. R Squared =,202 (Adjusted R Squared =,185) No difference between university-owned and university-invented patents Technologically broader patents are more original Positive relation between number of patents cited and originality Significant technology domain effects

Results: Generality (ANCOVA) Dependent Variable:GENERALITY Source Type III Sum of SquaresdfMean SquareF Sig. Corrected Model3,366 a 13,2595,971,000 Intercept,1551 3,570,059 Univ-owned / Univ-invented,0301,687,407 Patent System1, ,884,000 Tech domain IPC1,3216,0531,234,287 Appl year,1481 3,406,065 Tech breadth (# IPC3) 1, ,000,000 NBR BW PAT CIT,0121,265,607 NBR NPR,0371,845,358 NBR FW PAT CIT,1271 2,919,088 Error24,626568,043 Total197, Corrected Total27, a. R Squared =,120 (Adjusted R Squared =,100) No difference between university-owned and university- invented patents Higher generality for US patents Higher generality for technologically broader patents Slightly higher generality for older patents Slight positive relation between generality and number of forward patent citations

Results: Impact (Neg Binomial regr) University owned patents have higher impact Higher impact for US patents Positive relation between backward patent citations and impact Lower impact for technologically broader patents Lower impact for patents with more NPRs Significant technolgical domain differences Strong interaction between patent system and university-owned versus -invented Tests of Model Effects Source Type III Wald Chi- SquaredfSig. (Intercept),0391,844 Univ-owned / Univ-invented21,4861,000 Tech domain IPC144,2774,000 Patent System50,3901,000 NBR NPR8,6581,003 Tech breadth (# IPC3)26,4831,000 NBR BW PAT CIT13,1451,000 Appl year,0601,806 Univ-owned / Univ-invented * Patent System 19,3931,000 Dependent Variable: Impact

Results: Impact (Neg Binomial regr) Tests of Model Effects a Source Type III Wald Chi-SquaredfSig. (Intercept)2,0591,151 Univ-owned / Univ- invented,0421,838 Tech domain IPC149,4534,000 NBR NPR4,5021,034 Tech breadth (# IPC3) 15,9451,000 NBR BW PAT CIT7,0581,008 Appl year2,2231,136 Dependent Variable: Impact a. PAT_AUTH = US Tests of Model Effects a Source Type III Wald Chi-SquaredfSig. (Intercept)3,9111,048 Univ-owned / Univ- invented 8,0461,005 Tech domain IPC12,2884,683 NBR NPR2,7461,098 Tech breadth (# IPC3) 11,0111,001 NBR BW PAT CIT29,2001,000 Appl year3,8711,049 Dependent Variable: Impact a. PAT_AUTH = EP Higher impact of university-owned patents is significant for EPO patents, not for USPTO patents

Conclusions Are academic patents more ‘valuable’ if firms are involved? Our findings do not support this: No significant difference between university-owned and university-invented patents in terms of “originality” (or rather: diversity in the related knowledge base). No significant difference between university-owned and university-invented patents in terms of generality. The impact of university-owned patents is not lower than the impact of university-invented patents. On the contrary even: for EPO patents, university- owned patents receive significantly more citations than university-invented patents. The volume of university-owned patents has known a large increase over the last decades. Some suspect a decreasing quality. Our findings do not support this (~ no significant decrease of originality / generality / impact of academic patents over time).