Impact of public research on industrial innovation

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1 211 Internatonal Conference on Economcs and Fnance Research IPEDR vol.4 (211) (211) IACSIT Press, Sngapore Impact of publc research on ndustral nnovaton An emprcal analyss focused on pharmaceutcal ndustry and bo-ventures Abstract Ths paper emprcally analyzes how frms create nnovatve products based on research outcomes of unverstes and publc nsttutes ( publc research ) usng questonnare data for nventors. In partcular, we target nventors belongng to the pharmaceutcal ndustry, whch s regarded as a scence-based ndustry. Partcpants were asked how many products they had not been able to produce wthout the support of publc research resources. The response rate was 48% out of 332 nventors. Results ndcate that although they each value publc research, dfferences exst between nventors belongng to large pharmaceutcal frms and nventors belongng to bo-ventures regardng product evaluaton based on publc research outcomes. Ths paper shows how nventors value the ntroducton of external scentfc knowledge, specfcally knowledge from unverstes and publc research nsttutes; such knowledge s very useful for ndustral applcaton. Keywords-basc scence; publc research; nnovaton; pharmaceutcal ndustry; bo-venture I. INTRODUCTION Even wth the ceaseless ntroducton of recent advanced technology, basc scence contnues to contrbute to ndustral technology. However, uncertanty and hgh costs surround basc scence. Thus, only unverstes and publc research nsttutes are able to conduct basc scentfc research. Prvate frms ntroduce external research outcomes because t s dffcult for them to mplement research and develop nventons ndependently amongst trends of severe global competton, vast dversty of product technologes, and short-term product cycles. Ths stuaton s otherwse known as open nnovaton [1][2]. We beleve that unverstes and publc research nsttutes play mportant roles for scence-based ndustres, ncludng the pharmaceutcal ndustry, as provders of basc scentfc knowledge. However, t s burdensome to decpher to what extent unversty and prvate nsttute-based research outcomes contrbute to the ndustry. Scentfc knowledge produced by basc scence leads to technologcal products through varous paths. It s dffcult for us to trace them ndvdually. On the other hand, evdence s requred wth regard to knowledge management and polcy plannng at present. We can not avod ths task even f t s dffcult for us to solve t wth conventonal method. Therefore, we must consder methods to explan how ndustres absorb and use knowledge based on basc Hrom Sato Koch Sumkura Natonal Graduate Insttute for Polcy Studes GRIPS Tokyo, Japan hrom_sato@grps.ac.jp sumkura@grps.ac.jp scence and research conducted by unverstes and publc research nsttutes ( publc research ). When quanttatvely analyzng such ssues, we use ether objectve data (ex. patent data, fnancal data) or subjectve data (ex. questonnare data). Some prevous studes of ths ssue analyzed coauthorshp relatons on papers and how the relatonshps between academc researchers and pharmaceutcal researchers affect pharmaceutcal frms performance [3][4][5]. Other study focused on the number of partner frms that jontly apply patents [6]. The study ntroduced the concept of ndexng the amount of scentfc knowledge that frms assmlate from unverstes and publc research nsttutes. Ths ndex was used to verfy whether absorpton of such knowledge nfluences corporate performance. Nonetheless, such an ndex of objectve data s not suffcent to fully comprehend the effects of basc scence on the ndustry because t can not capture several alternatve avalable nformaton routes to publc research outcomes (ex. conferences, symposums, personal exchanges wth academa). In some cases, subjectve data, such as questonnares, are effectve. In one such survey, Mansfeld asked Unted States frms how many products they could not develop wthout the outcomes of basc scence [7][8]. The results reflected that basc scence partcularly contrbutes to advancements n the pharmaceutcal ndustry. We asked the same type of questons n a large survey for Japanese frms [9]. More specfcally, we asked frms how many products they could not produce wthout the research outcomes conducted by unverstes and publc research nsttutes. There are eght alternatve responses to these questons: all (f the alternatve s 1% accurate), very large (more than 3% but less than 1%), large (more than 1% but less than 3%), moderately large (more than 3% but less than 1%), moderately small (more than 1% but less than 3%), small (more than.3% but less than 1%), very small (not zero but less than.3%), and nothng (%). Through ths survey, we examned how basc scence leads to product nnovaton. As a result of our survey, Fg.1 ndcates that a few pharmaceutcal frms (23) answered moderately large whereas a majorty of pharmaceutcal frms (5) answered nothng. In addton, the dstrbuton of responses showed a dsproportonate weght on low evaluaton. 11

2 We should note that 5% of respondents are n a zone of management [9]. We can expect dfferences between managers, who manage companes, and nventors, who actually conduct research and develop products, regardng the evaluaton of how publc research contrbutes to commercalzaton. Managers mght not be able to comprehend the process of basc scence to practcal applcaton of technology, even though they can evaluate commercalzaton n the fnal stage. On the other hand, nventors who practce research and apply patents as a result of research and development could understand how basc scence contrbutes to product nnovaton and fully apprecate the connecton between basc scence and technology % Nothng (%) Very Small (~.3%) Small (.3~1%) Moderately Small (1~3%) Moderately Large (3~1%) Large (1~3%) Very Large (3~1%) Not Pharma Pharma All (1%) Pharmaceutcal frms; N = 23, Other frms; N = 5 Source: The author drew data based on [1] Fgure 1. Evaluaton for product nnovaton based on the publc research by managers: Comparson between non-pharmaceutcal frms and pharmaceutcal frms Therefore, we emprcally analyzed the extent to whch the pharmaceutcal ndustry has used outcomes of publc research for ther commercalzaton based on the questonnare data for nventors who apply mportant patents. In partcular, we analyzed on dfferences among nventors who evaluate the outcomes of publc research and ts effect on the ndustry. We also focused on dfferences between managers and nventors. We analyzed whether there are dfferences n the evaluaton of publc research between nventors belongng to large pharmaceutcal frms and nvestors belongng to bo-ventures. We concretely examned dfferences and smlartes between both groups of partcpants based on nformaton of dstrbuton by kernel estmaton. In addton, we analyzed what factors affect nvestors n ther evaluaton of publc research wth the ordered probt model. II. DATA Focusng on pharmaceutcal frms n Japan, we chose the top 1 frms on sales n 28 (excludng foregn frms) based on IMS pharmaceutcal market statstcs [11] and 23 frms lsted n September 29 as bo-ventures. Focusng on the patent document appled after 25, we tred to extract the each frm s nventors whom have appled patents wth hgh degree of mportance. However, nventors dd not necessarly belong to the sad frms. The reason that we put subjects down to mportant patents s that the random samplng ncluded low-value patents. To avod mxture of low-value patents wth mportant patents, we focused on mportant patents only. We used the BzCruncher of Patent Result Co., Ltd ndex to exact mportant patents. Ths ndex gves each patent a patent score, whch s an aggregated score for each factor (acton of the applcant or other people) to be postvely correlated to the degree of mportance of the patent. These factors mply patent applcaton cted by offcers on another patent examnaton, patent applcaton cted n another patent document, patent applcaton on nvaldaton tral, patent applcaton on early examnaton request, and patent applcaton regstered n the Unted States. Next, we relatvely compared each patent wth other patents submtted for approval around the same tme to modfy the tendency of evaluatng older patents as hgher. We also compared each patent wth other patents n dentcal technologcal felds (IPC) to correct dfferences of patent frequency and dfferences n the dffcultes of patent applcatons. Each factor s weghted on the bass of statstcs of the margn mantenance rato because mportant patents tend to be kept for a long tme. The patent score s computed as a devaton value. Followng ths ndex, we can obtan an nventor s patent score by aggregatng the patent score of each patent applcaton n whch the nventor s a contrbutor. Ths study chose the top nventors n the patent score out of each subjectve frm s patent applcaton appled after 25. We extracted nventors out of each large pharmaceutcal frm. As a result, the number of object nventors was 148, but then we excluded 2 resdng abroad. We also extracted bo-venture nventors n the same way. However, some bo-ventures have less than nventors after 25. In ths case we extracted as many nventors as possble. As a result, the number of object bo-venture nventors was 184. The total number of nventors/partcpants was 332. We sent questonnare sheets to these 332 nventors. However, some questonnare sheets were returned because of address unknown (6 sheets n large frms and 23 sheets n bo-ventures). The tentatve nvestgaton perod was from December 1 to 18, 29. However, we also collected questonnare sheets after the deadlne by proddng. The fnal sample was 16 (ncludng non-responders) out of 332 object respondents. The response rate was 48%. The sample sze comprsng large frms was 74 and the sample sze comprsng bo-ventures was

3 TABLE I shows the defntons and descrptve statstcs of basc attrbutes of nventors n our data. As seen n the table1, the sample numbers of the opposng groups large frm nventors and bo-venture nventors s nearly dentcal. The mean of nventors research years s about In educaton background, most hold a master s degree (M.A.), 42.9%. % Product Sales 1 TABLE I. DEFINITIONS AND DESCRIPTIVE STATISTICS FOR BASIC ATTRIBUTES Varable Defnton Obs Mean S.D. Mn Max Bg frm 1 f a nventor belongs to bg pharmacuetcal frm, f she belongs to bo-venture. Research year The number of year whch the researcher have researched at current afflaton. Ph.D. 1 f a nventor's educatonal record s doctoral degree, otherwse M.A. 1 f a nventor's educatonal record s master's degree., otherwse B.A. 1 f a nventor's educatonal record s bachelor's degree, otherwse Junor college 1 f a nventor's educatonal record s Junor college, otherwse Tertary college 1 f a nventor's educatonal record s Tertary college, otherwse Career college 1 f a nventor's educatonal record s Carrer college, otherwse Hgh/Junor hgh 1 f a nventor's educatonal record s Hgh/ Junor hgh, otherwse We asked the partcpants how many of ther commodtes they could not produce wthout publc research outcomes lke [7][8]. In other words, ths mples How does the outcome of publc research contrbute to product nnovaton? We also asked what percentage of ther sales reles on publc research outcomes. Ths mples to ask the market value of product nnovaton. The alternatves are same to Fg.1. Fg. 2 shows those results. The shaded area shows the dstrbuton of evaluaton of commercalzaton based on publc research outcomes. The dstrbuton has two peaks: the largest response s very large and the next s moderately large. We found that nventors evaluate product nnovaton based on the outcomes of publc research more than managers responses n [9]. The dotted area descrbes the dstrbuton of evaluaton for contrbuton on sales based on the outcomes of publc research. The peak of dstrbutons s some small. Therefore, we fnd that nventors value contrbuton on sales by the outcomes of publc research less than commercalzaton. 5 Nothng (%) Very Small (~.3%) Small (.3~1%) Moderately Small (1 ~3%) Moderately Large (3~1%) Large (1~3%) Very Large (3~1%) All (1%) Fgure 2. Evaluaton for product nnovaton and the market value based on the publc research by nventors. III. LARGE PHARMACEUTICAL FIRMS VS BIO-VENTURE Frst, we examne how responses vary between nventors belongng to large frms and nventors belongng to bo-ventures. We expect that nventors belongng to bo-ventures evaluate publc research contrbutons for commercalzaton hgher than large frm nventors because some bo-ventures are spun off from publc research whle large frms can conduct research and develop products ndependently. However, ths s not necessarly clear based on the data. In addton, there are dfferences n belefs between frms and ndvdual nventors. Therefore, we explan whether bo-venture nventors evaluate publc research contrbutons for ndustral applcatons hgher than large frms by usng the kernel estmaton of nformaton. Kernel estmaton s usually used for metrc varables; however, we appled kernel estmaton as an approxmate treatment because the questonnare has eght ordered alternatve varables. Fg. 3 descrbes the dstrbuton of evaluaton of commercalzaton based on the outcomes of publc research. The thck lne ndcates evaluatons of nventors belongng to large frms whle the thn lne ndcates evaluaton of bo-ventures. The response results (alternatves 1~8) are lsted n the order of evaluaton from left to rght. 13

4 Densty product Venture Bg frm Densty sales N=148 Fgure 3. Dstrbuton of evaluaton for commercalzaton based on the outcomes of publc research : Large frms nventors VS bo-venture s nventors We found a dfference n the dstrbuton of nventors belongng to large frms and bo-ventures. The dstrbuton of nventors belongng to large frms s a lttle skew to the rght but near normal dstrbuton. On the other hand, the dstrbuton of nventors belongng to bo-ventures s skew to the rght more than nventors belongng to large frms. Therefore, we confrm that nventors belongng to bo-ventures hghly evaluate the outcomes of publc research for commercalzaton more than nventors of large frms. Fg. 4 descrbes the dstrbuton of evaluaton for sales based on the outcomes of publc research. In ths case, we also fnd that the dstrbuton of nventors belongng to large frms s dfferent from that of bo-ventures. The dstrbuton of nventors belongng to large frms s near normal dstrbuton whereas the dstrbuton of nventors belongng to bo-ventures s skew to the rght. Ths fndng s smlar to Fg. 3. In fact, bo-venture nventors evaluate publc research outcomes hgher than large pharmaceutcal frm nventors do, whether t s evaluaton of commercalzaton or for sales. However, both dspersons of dstrbuton are large and the peak dstrbuton s more skew to the left than n Fg. 3. Ths result mples that nventors evaluate publc research contrbutons for commercalzaton more than for sales. However, ths result does not explan on what factors the evaluaton for commercalzaton or sales are based. The outcomes of publc research depend on several factors, but we only focused on whether the nvestors were afflated wth large frms or bo-ventures. We admt that evaluatons of publc research depend on background factors other than afflaton; for example, research experence and educaton background and so on. Therefore, we control these factors wth the ordered logt model to analyze how the background of nventors affects evaluaton. N=146 Fgure 4. Dstrbuton of evaluaton for sales based on the outcomes of publc research : Large frms nventors VS bo-venture s nventors Ⅳ. WHICH INVENTORS HIGHLY EVALUATE PUBLIC RESEARCH CONTRIBUTIONS TO INDUSTRY? We accept eght order alternatves for commercalzaton and sales as dependent varables to analyze how nventors evaluate publc research contrbutons for commercalzaton and sales. We also use the ordered logt model to analyze how publc research outcomes help frms performance. We propose eght ordered answers to the queston of contrbuton to commercalzaton and to sales as ordered varables n usng the ordered logt model. The model s y X a e y j f 2 e ~ N(, s ) y, j 1,..., J,, j 1 j Venture Bg frm y s an unobservable latent varable, whle J y s an observable varable. j corresponds to 8 f a respondent sad all, 7 f very large, 6 f large, 5 f moderately large, 4 f moderately small, 3 f small, 2 f very small, and 1 f nothng. a s a parameter. X s a dummy varable descrbng the background of nventors. Table Ⅰ shows the detals. We suppose that the error term e exhbts a logstc dstrbuton. We also use the same model for the contrbuton to sales by such research outcomes. TABLE Ⅱ shows estmaton results. Results for commercalzaton and sales are smlar. (1) 14

5 TABLE II. ESTIMATION BY ORDERED LOGIT MODEL Product Sales Varable Coef. S.E. Z-value Coef. S.E. Z-value Bg frm Research year Ph.D M.A B.A Junor college Tertary college Career college cut cut cut cut cut cut cut Observaton Psued R Psued log lkelhood Both wald test were rejected. Baselne of educaton record s Hgh/Junor hgh. We confrm that large frm nventors tend to gve low evaluatons for the outcomes of publc research on both commercalzaton and sales because the large frm dummy varable s sgnfcantly negatve. Ths s consstent wth results of the kernel estmaton n secton Ⅲ. In addton, we found that nventors wth extended research hstory tend to gve low evaluatons for publc research contrbutons for commercalzaton and sales because research years are sgnfcantly negatve on both commercalzaton and sales. On the other hand, nventors wth a Ph.D. tend to gve hgh evaluaton for the outcomes of publc research because the Ph.D. varable s sgnfcantly postve on both commercalzaton and sales. Ths suggests that those wth a Ph.D. understand the contents of advanced technology and tend to apprecate the labors of publc research. Although junor college graduates also show a sgnfcant postve, t does not have sgnfcant bearng, because only two partcpants were junor college graduates. Ⅴ. CONCLUSION Usng kernel estmaton, we found that nventors of bo-ventures gve hgher evaluatons for the outcomes of publc research than nventors assocated wth large frms. Ths suggests that publc research contrbutes more to commercalzaton than sales. However, estmaton by the ordered logt model suggests that there are not dfferences between evaluaton for commercalzaton based on basc scence and contrbutons of ntroducng basc scence for sales. Moreover, factors other than assocaton, for example, research experence and educaton background, affects evaluaton. Ths paper s a prelmnary report and some fact fndng stll remans. In the future, we wll add new analyss and consder more deeply how frms should mplement basc scence knowledge from unverstes and publc research nsttutes. ACKNOWLEDGEMENT Ths study was a part of jont research wth RIKEN. However, the opnons expressed n ths paper do not represent those of RIKEN. REFERENCES [1] H.W. Chesbrough, Open Innovaton: The new mperatve for creatng and proftng from technology. Harvard Busness School press, Boston Mass, 23. [2] H.W. Chesbrough, Open Busness Models: How to thrve n the new nnovaton landscape. Harvard Busness School Press, Boston Mass, 26. [3] I. Cockburn and R Henderson (1998). Publc-prvate nteracton and the productvty of pharmaceutcal research, NBER Workng Paper Seres, workng paper 618. [4] L.G. Zucker, and M.R. Darby, Capturng technologcal opportunty va Japan s star scentsts: Evdence from Japanese frm s botech patents and products, Journal of Technology Transfer, vol. 26, Nos. 1 2, 21, pp [5] L.G. Zucker, M.R. Darby, and J.S. Armstrong (21). Commercalzng knowledge: Unversty scence, knowledge capture, and frm performance n botechnology, NBER Workng Paper Seres, workng paper [6] H. Sato and K. Sumkura, An Emprcal Analyss on Absorptve Capacty Based on Lnkage wth Academa, Internatonal Journal of Innovaton Management, vol. 14, No.3, 21, [7] E. Mansfeld, Academc research and ndustral nnovaton Research Polcy, vol. 2, 1998, pp [8] E. Mansfeld, Academc research and ndustral nnovaton: An update of emprcal fndngs, Research Polcy, vol. 26, 1998, pp [9] H. Sato, and K. Sumkura, How are fruts of research n unverstes and publc research nsttutes used?: Bref overvew from GRIPS frm survey. GRIPS Dscusson Paper Seres 1-, (accessble, Nov. 18, 211) [1] K. Sumkura and H. Sato, How scentfc knowledge assmlated from academa nfluences corporate performance Based on three emprcal analyses, Proceedngs of Intellectual Property Assocaton of Japan 21, Intellectual Property Assocaton of Japan, Japan, 21 (n Japanese). [11] IMS pharmaceutcal market statstcs, (accessble, 17/11/21)