The relatve value of nternal and external nformaton sources to nnovaton Anthony Arundel and Catalna Bordoy MERIT, Unversty of Maastrcht Abstract Ths workng paper nvestgates the factors that nfluence frms to adopt an nward lookng approach to nnovaton, n whch they rely on knowledge sources wthn the frm, versus an external lookng approach n whch they rely on sources outsde the frm. The analyss s based on responses from up to 527 surveyed frms on the mportance of nternal and external knowledge sources to the development of ts most economcally mportant nnovaton. The factors nclude appropraton condtons, technology characterstcs, the frm s nternal nnovatve capabltes, and frm boundary characterstcs such as whether or not t s part of a larger frm and ts sze. After employment weghtng, 48.4% of frms fnd nternal knowledge sources of greatest mportance, 17.1% prefer external sources, and 34.5% found them of equal mportance. Three dfferent regresson models explored the effect of several factors on the relatve mportance of these three categores of knowledge sources. Frms actve n the hgh technology telecom equpment sector are more lkely than the reference category of the food sector to fnd nternal sources of greater value than external sources. Frm sze and R&D ntensty have no effect on preferences, whle ndependent frms are less lkely to prefer nternal knowledge sources. The analyses for the Netherlands show that the cost of the frm s most mportant nnovaton reduces the probablty of fndng nternal sources of greater value than external sources. Ths fndng shows that frms are compelled to seek out external sources for ther more expensve nnovatons. Introducton Innovaton theory over the past decade has emphassed the growng mportance of networks, research cooperaton, and the need for frms to access external nformaton sources n order to successfully nnovate 1. Innovaton surveys, such as the frst and second Communty Innovaton Surveys n Europe have provded emprcal evdence n support of the mportant role of external knowledge sources to the nnovatve actvtes of frms. These surveys consstently show that frms attach a hgh mportance to nformaton obtaned from ther customers and supplers, from attendng trade fars and conferences, and from readng journals 2. Other nformaton sources, such as patent databases or publc research nsttutons (PRIs), are of consderably less value to most frms, although they are ntensvely used by 1 A theoretcal framework for accessng external knowledge s provded by Davd and Foray (1994), Roelandt and Hertog (1996), Antonell (1999) and Georghou (1998). 2 See the collected research reports for the frst CIS n Arundel and Garrelfs (1997), Baldwn and Da Pont (1996) on Canada, Francos and Favre (1998) for the second CIS for France, Levn et al (1987) for the Unted States C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 1
specfc sub-groups, as shown by the close lnks between pharmaceutcal and botechnology frms and unverstes (Refs). There s no denyng that external nformaton sources must play a vtal role n nnovaton. Nevertheless, emprcal research on the role of external nformaton sources n nnovaton tends to gnore nternal nnovaton actvtes. The result s that there could be an unrealstc focus on the value of external sources that s partly due to current nnovaton theory and the structure of nnovaton questonnares, whch gve consderably more space to nvestgatng external than nternal nformaton sources 3. A better understandng of the relatve mportance of nternal versus external sources, and the role of the latter n nnovatve success, would help place knowledge sources n perspectve. Several factors could nfluence the relatve mportance of nternal versus external knowledge sources: concern over leakng strategc nformaton to compettors, the nternal capabltes of the frm, technologcal factors, frm characterstcs such as ts sze or boundares, and the cost of developng the nnovaton. Strategc concerns over the release of nformaton to compettors could nfluence the wllngness of the frm to use dfferent types of external nformaton sources. Some external sources, such as publcatons, patent databases, and reverse engneerng can be accessed or used wthout revealng any nformaton about the frm s nnovaton strateges to compettors. Other external sources, such as attendng fars or conferences, are possbly low rsk, whle many of the sources of greatest nterest today supplers and customers (user-producer relatonshps), and PRIs requre sharng nformaton and thereby ncrease the rsk of leakng nformaton to compettors. Patents could play a role n reducng rsk by conferrng clear ownershp rghts and by reducng the probablty of nfrngement. The frm s nternal capabltes should play an mportant role n the value attrbuted to external nformaton sources. Frms wth only lmted n-house capabltes should be more lkely to rely on external sources. However, ths effect wll be medated both by the type of technology and by the frm s absorptve capacty. Internal expertse could suffce for the development of well-understood technologes, whle complex technologes or technologes at the technologcal fronter such as botechnology could requre frms to actvely seek knowledge from external sources. However, the frm wll also need a hgh level of nternal capabltes to be able to explot ths knowledge. In ths case, t s not clear f the frm wll fnd ts nternal or external knowledge sources of greater mportance. Alternatvely, t could fnd them of equal mportance. The value of external 3 For nstance, the second CIS questonnare asks about 10 external nformaton sources and only 2 sources wthn the frm or ts group. An excepton s a seres of nnovaton surveys by Statstcs Canada on botechnology and on the use of Advanced Manufacturng Technologes, whch ask an equal number of questons about nternal and external knowledge sources. The former ncludes producton engneerng departments, the head offce, related plants, sales and marketng staff, etc. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 2
sources could also vary between product and process nnovatons. The development of process technology could requre close cooperaton wth equpment supplers. In addton to the nnovatve capabltes of the frm, other frm characterstcs could nfluence the value of nternal versus external knowledge sources. Frms that are part of a larger group wll be able to access knowledge from other dvsons wthout leakng nformaton to compettors. Mult-unt frms can also span a range of techncal expertses, whch means that one unt can acqure essental knowledge outsde ts range of expertse wthout gong beyond the frm boundares. Smlarly, the range of avalable expertse n-house could ncrease wth frm sze. Another factor that could nfluence boundary condtons s the recept of government subsdes for nnovaton. In Europe, many nnovaton subsdes, such as the EU Framework Programme, requre frms to collaborate wth other frms or wth PRIs. The last factor s the cost of developng the nnovaton. Innovaton costs should ncrease wth techncal complexty and when the development work s not routne. In both cases, the frm wll need to conduct a search for possble solutons that could lead to areas outsde of the frm s n-house expertse. The frm wll ether need to buld up nternal capabltes n these areas, partly by brngng n new expertse from external sources, or by collaboratng wth external partners that already have the necessary expertse. In both cases, the relatve value of external versus nternal knowledge sources should ncrease. Ths paper uses the results of the KNOW survey to frst explore the effects of these factors on the relatve mportance of nternal versus external knowledge sources. The analyss s lmted to a set of questons on the frm s most economcally mportant nnovaton, followng a smlar technque used by Baldwn and Da Pont (1996). Methodology The KNOW survey was conducted n the Sprng of 2000 n seven EU countres: the UK, Denmark, the Netherlands, France, Germany, Italy, and Greece. The choce of countres to nclude n the survey depended on the orgn of the partcpants n the KNOW project, funded by the Framework Programme of the European Commsson. Although the survey does not cover all EU countres due to fundng lmtatons, the four largest EU economes were ncluded plus two of the smaller, developed economes and one of the less developed economes. The survey was lmted to fve sectors: food and beverages (NACE 15), chemcals excludng pharmaceutcal (NACE 24 mnus NACE 24.2), telecom equpment (NACE 32), telecom servces (NACE 64.2), and computer servces (NACE 72). These specfc sectors were chosen to provde a range of low, medum and hgh technology manufacturng and to nclude two nnovatve servce sectors. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 3
In each country, a random sample of frms from two sze classes (10 249 employees and 250 999 employees) wthn each of the fve sectors was drawn from a natonal busness regstry. A standard survey protocol based on a telephone CATI technque wth up to three call-backs was used n all countres wth the excepton of the UK, where a postal survey was used. Table 1 gves the number of frms surveyed, the number of responses, the response rates, and the number of useable responses. The latter s less than the number of responses because the analyses exclude non-nnovatve frms, frms that dd not ft the samplng crtera for sze and sector, and frms that dd not answer the questons on ther most economcally mportant nnovaton 4. The response rates by country vary from 9.6% n the UK to 76.5% n Denmark, wth an average of 25.3% f the UK s ncluded and 33.2% f the UK s excluded. Table 1. Survey results by country Frms Surveyed Responses Response rate Useable responses UK 1003 96 9.6% 44 Denmark 170 130 76.5% 78 Netherlands 331 151 45.6% 114 France 613 76 12.4% 65 Germany 470 101 21.5% 51 Italy 278 92 33.1% 75 Greece 260 110 42.3% 100 Total 3017 764 25.3% 527 Total excludng UK 2014 668 33.2% Some of the frms dd not complete all survey questons. Where possble, the value of mssng varables for nterval varables were estmated usng regresson technques based on the frm s sector, country, and sze. These estmated values are ncluded n the results gven below. The KNOW survey asked a seres of questons on the frm s most economcally mportant nnovaton that was ntroduced n the prevous three years. The key queston s: Overall, how mportant to the successful completon of ths nnovaton were nternal knowledge sources compared to external sources?. Three optons were provded: Internal most mportant, external most mportant, and both of equal mportance. External sources are defned to nclude sources wthn other dvsons or unts of the same frm, whle nternal sources must be located at the same physcal ste. Ths should ncrease the role of external sources compared to a defnton based only on sources outsde the frm. Informaton was also obtaned on other characterstcs of the frm and ts nnovaton strateges that could nfluence the relatve mportance of nternal versus external knowledge sources. These nclude the type of nnovaton (product/servce, process, combned product and 4 For sze, a maxmum cut-off of 1,250 employees was used to allow for natural employment growth between the C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 4
process), the ownershp status of the frm (dvson, natonal subsdary, or ndependent), whether or not the nnovaton had been patented, the recept of government subsdes to develop the nnovaton, the number of employees, sector of actvty, the frm s R&D status, and the dvson of R&D expendtures by locaton (n-house, other dvsons or subsdares of the same frm, ndependent organsatons). In addton, the Dutch survey obtaned ordnal data on the development cost of the most mportant nnovaton. The descrptve results gven below (wth the excepton of frm counts) are weghted by the number of employees n each frm. As an example, a frm wth 200 employees wll contrbute twce as much to a weghted average on whether or not the nnovaton had been patented as a frm wth 100 employees. The assumpton s that the economc value of the nnovaton wll be greater for larger frms. Descrptve Results 375 frms n the sample (71.2%) have less than 249 employees, whle 152 (28.8%) frms are md-szed, wth between 250 and 1,250 employees. The md-sze frms account for 78.3% of total employment among the sample. Almost all the respondent frms, 96%, perform R&D: 71% on a contnuous bass and 25% on an occasonal bass. Several characterstcs of the frms most economcally mportant nnovaton are gven n Table 2, plus nformaton on the use of nformaton sources n ts development. Product or servce nnovatons predomnate, wth only 17.7% of small and 22.0% of md-sze frms ntroducng a process nnovaton alone. For the product nnovatons only, the product nnovaton accounted for 16.1% of the total sales of all small frms and 15.2% of the total sales of the md-sze frms, ndcatng hardly any dfference by frm sze. The most mportant nnovaton has been patented for almost twce as many md-sze as small frms. These dfferences are not entrely due to sectoral effects, snce the most mportant nnovaton s sgnfcantly less lkely to be patented by small frms n the chemcal and telecom equpment sectors compared to md-sze frms n these two sectors. However, the rates are not sgnfcantly dfferent (although favourng md-sze frms) n food and beverages, telecom servces, and computer servces. Almost equal percentages of small and md-sze frms receved government subsdes to develop the nnovaton. Slghtly more md-sze frms brought n new scentsts or engneers to work on the nnovaton. Over 70% of frms noted that external nformaton sources (excludng other unts of the same frm) contrbuted to both the orgnal dea behnd the nnovaton and to ts completon. The external sources lsted n the questonnare nclude compettors, supplers, customers, PRIs, and consultants. The use of many of these external sources wll depend on tme that the data n the busness regstres were collected and the survey date. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 5
drect person-to-person contact and therefore rase the possblty of leakng nformaton, n contrast to the use of sources such as readng the lterature or accessng patent databases. Table 2. Characterstcs of the most economcally mportant nnovaton Type of nnovaton Small (< 250 emps) Md-sze (250 1,250) Product/servce 50.0% 44.9% Combned product & process 32.4% 33.1% Process 17.7% 22.0% 100.0% 100.0% Sales share from product, servce, product/process nnovatons 1 16.1% 15.2% Receved a development subsdy 15.5% 16.1% Patented (by frm or another organsaton) 19.6% 38.2% New scentsts/engneers brought n to develop nnovaton 2 49.4% 55.4% External sources contrbuted to orgnal dea 3 79.5% 76.7% External sources contrbuted to completon 3 70.8% 80.1% Notes: Unless otherwse specfed, employment weghted wthn each sze class. 1: No employment weghtng, calculated across all sales from frms wthn each sze class. 2: Excludes staff from other unts of the same frm, but ncludes new staff from supplers, customers, PRIs, and consultants.. 3: Excludes sources from other unts of the same frm, but ncludes compettors, supplers, customers, PRIs, and consultants. Relatve mportance of nternal versus external knowledge sources Table 3 provdes descrptve results for the effect of four factors on the percentage of frms that found nternal, external, or both equally to be ther most mportant knowledge source for developng ths nnovaton. The four factors are appropraton condtons, the type of technology, the frm s research capabltes, and the frm s boundares. Appropraton The two varables for appropraton condtons are whether or not the nnovaton was patented and f secrecy was the most mportant appropraton method used by the frm. The results for secrecy dffer very lttle from the average, but patentng slghtly ncreases the value of external knowledge sources, wth an ncrease n both external and the equal categores. Ths effect could be due to patentng solvng ownershp dsputes and allowng frms to protect ther nnovatons when nformaton s shared wth external partners. Technology There are two varables for dfferences n the type of technology: whether t s a process nnovaton alone or contans a product component (ths ncludes combned product/process nnovatons) and the frm s sector of actvty. We would expect external sources to be the most wdely used n hgh technology sectors such as telecom equpment, whle nternal sources could suffce for low technology sectors such as food and beverages, although C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 6
external sources could be used n the latter for process nnovatons. The results for the telecom sector conflct wth expectatons, wth almost 74% of telecom equpment frms fndng nternal knowledge sources to be of greatest value, whch s sgnfcantly more than the average of 48.4%, whle the results for the food and beverage sector are close to the average. A very low percentage of telecom equpment frms, 7.4%, fnd external sources to be the most valuable. Table 3. Factors nfluencng the most mportant knowledge source N Internal External Equal All frms 517 48.4% 17.1% 34.5% 100% By appropraton Innovaton patented 128 41.9% 21.1% 37.1% 100% Not patented 376 52.6% 14.6% 32.9% 100% Frm reles most on secrecy 149 47.5% 13.9% 38.6% 100% By technology measures Food and beverages 123 50.5% 20.4% 29.1% 100% Chemcals 125 45.0% 19.5% 35.5% 100% Telecom equpment 92 73.7% 7.4% 18.9% 100% Telecom servces 45 50.0% 17.2% 32.8% 100% Computer servces 132 34.3% 16.3% 49.4% 100% Product nnovaton 427 48.5% 14.8% 36.7% 100% Process nnovaton 82 47.6% 26.4% 26.0% 100% By frm capabltes Contnuous R&D performer 357 47.5% 16.3% 36.2% 100% Occasonal and never 147 51.0% 19.7% 29.7% 100% R&D personnel share < 5% 203 49.7% 17.4% 32.9% 100% 5% - 20% 165 38.2% 20.7% 41.1% 100% > 20% 147 64.9% 6.2% 28.9% 100% Brng n new scentsts/engneers 1 Yes 256 35.6% 19.7% 44.7% 100% No 258 64.0% 14.0% 22.0% 100% By frm boundares Independent 286 38.5% 17.1% 44.4% 100% Part of a group 226 58.1% 17.1% 24.8% 100% < 250 employees 367 57.4% 14.0% 28.6% 100% 250 + employees 150 46.0% 17.9% 36.2% 100% Receved subsdy Yes 95 40.3% 21.4% 38.3% 100% No 422 49.9% 16.3% 33.9% 100% Notes: Percentages are employment weghted. The total number of frms s less than the total n Table 1 (527) due to mssng values. 1: Excludes scentsts brought n from other unts of the same frm. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 7
The lowest relance on nternal sources occurs n the computer servces sector, where only 34.3% fnd nternal sources to be more mportant than the alternatves, whle almost half of computer servce frms fnd both nternal and external sources of equal value. The latter could be due to the frequency of customsaton n ths sector, n whch software s developed to meet the customer s requrements. In support of ths possblty, sgnfcantly more computer servce frms than all other frms combned state that customers contrbuted to both the dea (62% versus 49%) and to the completon (61% versus 40%) of ther most mportant nnovaton 5. There s very lttle dfference between product and process nnovators n the preference for nternal knowledge sources, but a hgher percentage of process nnovators prefer external sources (26.4% versus 14.8%), probably reflectng the role of equpment supplers, whle more product nnovators fnd both sources of equal value (36.7% versus 26.0%). Innovatve capabltes There s lttle dfference by the R&D status of the frm, except that a hgher percentage of contnuous R&D performers than occasonal/non R&D performers fnd nternal and external knowledge sources of equal mportance (36.2% versus 29.7%). There are greater dfferences by R&D ntensty (measured here as the percentage of all employees actve n R&D). 65% of frms wth a hgh R&D ntensty cte nternal sources, compared to 38% of frms wth md and 50% of frms wth low R&D ntenstes. The most nterestng dfference for these three groups s n the dstrbuton of the results for the two categores wth an external component (external and equal). Frms wth a hgh R&D ntensty favour equal over external by a factor of 4.7 tmes, whle frms n the other two classes favour equal by a factor of around 2 tmes. Frms can mprove ther nternal capabltes by brngng n or hrng new scentsts or engneers to work on ths nnovaton from ether ther supplers or customers, PRIs, or consultants. The queston specfcally refers to both hrng and brngng n, snce frms can obtan external expertse on a temporary bass wthout gong through a formal hrng process. A sgnfcantly hgher percentage of frms that dd not brng n new scentsts and engneers fnd ther nternal sources to be of greatest mportance (64% versus 35.6%) whle frms that brng n new expertse are more lkely to fnd both nternal and external sources of equal mportance. The hgh prevalence of the equal group suggests that the frm must have nhouse capabltes n order to beneft from brngng n new scentsts and engneers. Frm boundares 58% of frms that are part of a group cte nternal sources, compared to 38.5% of frms that are ndependent. A hgher percentage of small (57.4%) than md-sze (46.0%) frms prefer nternal sources, although ths could partly be due to sector dfferences n the sze of the frms. 5 Employment weghted results (rescaled). For unweghted results, the dfference s also statstcally sgnfcant for deas but not for contrbutng to the completon of the nnovaton. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 8
As expected, frms that receve subsdes are less lkely to cte nternal sources (40.3% versus 49.9%), wth an ncrease n both the external and equal optons. Brngng-n new staff Brngng n new scentsts and engneers on ether a temporary or permanent bass s one of the most mportant methods that frms can use to develop ther own nternal capabltes. For ths reason, ths actvty deserves a closer look at the specfc sources of new staff. The questonnare asks f these staff were obtaned from supplers, customers, PRIs, or consultants. We would expect sourcng from supplers to be temporary and more prevalent for the ntroducton of process technology, whle sourcng from PRIs could be more frequent among hgh technology sectors. Both expectatons are met. The source of new staff vares by sector, as shown n Table 4, and by the type of the frm s most economcally mportant nnovaton. Food and beverage frms are less lkely than other frms to brng n any addtonal staff. Ths s partcularly pronounced for customers, PRIs, and consultants, whle they are smlar to the average for supplers. The low overall rate n ths sector of brngng n new staff could be due to low techncal complexty and lttle need for addtonal expertse, wth the excepton of brngng n scentsts from supplers to nstall new process equpment. New staff from supplers are used by 38% of food frms when ther most mportant nnovaton contans a process component and by only 22% of food frms when the nnovaton s a product or servce. Telecom equpment frms have the lowest rate of brngng n staff from supplers, but an above average rate of drawng staff from PRIs. The two servce sectors have the hghest overall rates of brngng n new staff, although telecom servce frms rely more on supplers, probably for equpment nstallaton, snce staff are obtaned from supplers by 31% of the process nnovators compared to 9% of the product/servce nnovators. In contrast, computer servce frms rely more on customers. Table 4. Percent of frms brngng n new scentsts or engneers from four sources to work on ther most economcally mportant nnovaton Supplers Customers PRIs Consultants Any of these Food and beverages 31.6% 3.3% 11.0% 10.6% 45.3% Chemcals 30.5% 14.5% 18.7% 16.9% 52.4% Telecom equpment 22.2% 19.2% 25.1% 16.9% 53.2% Telecom servces 55.0% 10.7% 29.8% 21.8% 61.0% Computer servces 34.9% 25.0% 27.7% 36.5% 65.6% Total 31.7% 14.4% 20.1% 20.1% 54.1% Notes: Percentages are employment weghted. Excludes scentsts brought n from other unts of the same frm. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 9
Development cost for the most economcally mportant nnovaton The Dutch verson of the KNOW questonnare ncluded a categorcal queston on the development costs for the nnovaton. Four categores were provded: less than 0.05 mllon Euros, 0.05 to 0.5 mllon Euros, 0.5 to 5 mllon Euros, and over 5 mllon Euros 6. Data on development costs are avalable for 105 frms, but only 14 frms spent less than 0.05 mllon and 12 spent more than 5 mllon. For ths reason, the categores are combned nto two groups: less than 0.5 mllon Euros and over 0.5 mllon Euros. As shown n Table 5, the percentage of frms that fnd nternal knowledge sources to be more mportant than external sources declnes wth the development costs from 43.1% of frms that spent less than 0.5 mllon Euros to develop the nnovaton, to 32.7% of frms that spent over 5 mllon Euros. The dfference s pcked up by the equal group, whch ncreases from 32.0% of frms that spent less than 0.5 mllon Euros to 41.8% of frms that spent over 5 mllon. Table 5. Dstrbuton of the most mportant source of knowledge by the development cost of the most economcally mportant nnovaton Cost (Euros) N Internal External Equal < 0.5 mllon 63 43.1% 25.5% 32.0% 100% > 0.5 mllon 42 32.7% 25.9% 41.8% 100% Total 105 37.1% 25.7% 37.1% 100% Notes: Employment weghted. Lmted to Dutch frms. Weghtng by INWEIGHT produces a smlar pattern for nternal sources, but the declne by cost s pcked up by both the equal and external groups. The development cost also has a strong mpact on whether or not the frms brngs n new scentsts and engneers. For development costs below 0.5 mllon Euros, 23.5% of frms brng n new staff, compared to 58.2% of frms that spent more than ths amount 7. Regresson Results The regressons explore the factors that nfluence the probablty that a frm fnds nternal sources, external sources, or both equally to be the most mportant knowledge source for the development of the nnovaton 8. The regresson results frequently do not confrm the descrptve results gven above. However, ths s partly because the descrptve results are employment weghted, whle the regresson results are ether unweghted or weghted by the nverse of the response rates n each sector by sze samplng cell. The regresson results are provded for all countres combned, separately for each sector, and separately for each country. 6 The Euro costs are approxmate and use an exchange rate of 1 NLG = 0.5 Euros, whereas the real exchange rate s 1 NLG = 0.455 Euros. 7 Ths s a robust dfference that holds n an unweghted, employment weghted, or INWEIGHT weghted analyss. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 10
Model specfcaton A basc problem for nvestgatng the effect of multple factors on the frm s choce of ts most mportant knowledge source s the model specfcaton. Three model specfcatons are possble for a dependent varable wth three optons: an ordered logt, a multnomal logt, or a bnary logt. Each model, descrbed below, was appled to the KNOW data n order to determne whch one most accurately ft the data. A smlar vector of ndependent varables s used n all three models. Ordered logt The ordered logt s the model of choce f the relatonshp between the relatve mportance of nternal and external knowledge sources follows an ntrnsc ordnal relatonshp, wth the equal category fallng between a preference for nternal and external knowledge sources. Ths would occur f a preference for nternal sources was determned, for example, by two factors, and f frms wth ntermedate values for both tended to prefer the equal opton. The ordered logt model assumes that the dependent varable y s generated by a contnuous * latent varable y whose values are unobserved. The model assumes that there are a set of * ordered values (μ 1, μ 2,.. μ n-1 ) and a varable y such that: (1) y = 1 y = k y = n f f f y * µ µ < µ k 1 n 1 1 < y < y * * < µ k for 1 < k < n The unobserved varable y * s modelled as a lnear functon of the ( N, k) vector of exogenous varables X: * (2) y = β X + ε, 1,... N, = where ε functon: has a dstrbuton functon f derved from the logstc cumulatve dstrbuton (3) 1 F( x) = 1+ exp( x). Gven the characterstcs X of ndvdual, the probablty that y s found n category k s: 8 We also explored the effect of dfferent knowledge sources on the economc value of product-based nnovatons to the frm, usng the percentage of the frm s sales from the nnovaton. Only the coeffcents for the frm s sector were sgnfcant. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 11
(4) Prob Y = 1/ X ) = F( µ βx ) ( 1 Prob Y k / X ) = F( µ βx ) F( µ βx ) ( = k k 1 Prob Y n / X ) = 1 F( µ βx ) ( = n 1 wth n number of categores. Multnomal logt The descrptve results suggest that the preferences are much more complex than the assumptons of the ordered logt, wth each of the three optons provdng dscrete choces. The evdence for a more complex relatonshp s due to the pattern of preferences for the external and for the equal categores, both of whch nvolve usng external knowledge sources. The results suggest that the preference for the equal opton over the external opton depends on n-house capabltes. As noted above, frms wth a hgh R&D ntensty strongly prefer the equal opton, whle frms from the hgh technology telecom equpment sector have a greater preference for the equal opton than frms from the low technology food and beverages sector. Frms that brng n new scentsts and engneers also prefer the equal opton (even over nternal sources), suggestng that they must have the necessary nhouse capabltes to frutfully use new expertse. If the optons are dscrete choces, the correct model s a multnomal logt, where the probablty that ndvdual makes choce j (j=1, m) s gven by: where m s the number of possble choces. ' exp( β j X ) Prob ( y = j) =, m ' exp( β X ) Bnary logt The thrd possblty s that there s lttle dfference between the two choces that nclude an external component: external and equal (or alternatvely there s lttle dfference between the two optons that contan an nternal component). In ths case, the correct model s a bnary logt, n whch the choce of nternal knowledge sources are compared to the two choces wth an external component. The bnary logt assumes that there s an unobservable * varable y such that k = 1 k y = 1 y = 0 f f y * > 0 otherwse, * and y s defned by * ' y = β + ε, X C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 12
where ε has a dstrbuton functon f derved from the logstc cumulatve dstrbuton functon 1 F( x) =. 1+ exp( x) Then, gven the characterstcs X of ndvdual, we have that ' ' exp( β X ) Prob ( y = 1) = 1 F( β X ) =. ' 1+ exp( β X ) Independent varables The regressons nclude varables from each of the four factors covered n Table 3: appropraton condtons, technology characterstcs, frm capabltes, and frm boundares. The regressons also nclude several addtonal varables that are not lsted n Table 3. These varables provde more detaled nformaton on the types of external sources that contrbuted ether to the orgnal dea behnd the nnovaton or to ts completon. The questonnare obtaned nformaton on fve external sources: compettors, supplers (SUPL), customers (CUST), PRIs (UNIV), and consultants. Each source can provde an dea (IDEA) for the nnovaton or provde nformaton that s used to complete the nnovaton (COMPL). In total, there are eght dummy varables, ncludng OTHER for compettors and consultants, wth no use of external source as the reference category. We expect sources that contrbute to the completon of the nnovaton to have a greater effect on reducng the mportance of nternal knowledge sources than those that contrbute to the orgnal dea. The reason for ths s that deas can often be theoretcal or quckly obtaned, whle the necessary work to turn an dea nto an nnovaton can be extensve and tme consumng 9. In the separate regressons by country and by sector, the total number of ndependent varables needs to be reduced to avod saturatng the model. In these regressons, COMPLETE s a dummy varable that equals 1 when any of these fve external sources contrbuted to the completon of the nnovaton (0 otherwse), whle IDEA equals 1 when any of them contrbuted to the orgnal dea (0 otherwse). Alternatvely, COMPET, SUPPLIER, CUSTS and PRI equal 1 when each source s used ether for the orgnal dea or for help completng the nnovaton (0 otherwse). Two varables capture the effect of brngng n new staff. BRINGPRI equals 1 f the frm brought n new staff from PRIs whle BRINGIN equals 1 f the frm brought n new staff from ether supplers, customers, PRIs, or consultants. Fnally, two varables are ncluded to capture the possblty that frms could be sourcng most of ther external knowledge from sources that do not requre sharng or revealng nformaton. JOURNALS equals 1 f the frm regularly reads scentfc or busness journals as a source of deas for nnovaton(0 otherwse), whle REVERSE = 1 f the frm regularly analyses ts compettors products for deas(0 otherwse). 9 Add references on the relatve amount that frms spend on research versus development. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 13
These two varables refer to all of the frm s nnovatve actvtes, nstead of just to the development of ts most economcally mportant nnovaton. The model for the Netherlands also ncludes a varable for the cost of the nnovaton (HIGHCOST) whch equals 1 when the nnovaton cost s over 0.5 mllon Euros and zero otherwse. Results Multnomal logt results for all countres combned are gven n Table 6 whle the ordered logt and bnary logt results are gven n Table 7. All of these regressons nclude dummy varables for country (Netherlands s the reference category), although the coeffcents for the country dummes are not provded. The country dummes are ncluded to adjust for natonal dfferences n the responses that are not captured by the other varables. Only bnary logt results are gven for each sector (Table 8) and for each country (Table 9). As shown n Table 6, the multnomal results wth nternal as the reference category show that frms that fnd external and nternal knowledge sources to be of equal mportance and frms that prefer external sources dffer sgnfcantly from the reference category. However, when equal s the reference category, there are nne statstcally sgnfcant coeffcents for the nternal group, but only one for frms that prefer external knowledge sources. These results ndcate that there s lttle dfference between the external and equal groups of frms. In contrast, both the equal and the external groups dffer from the nternal group. Ths suggests that the multnomal logt s not the best model specfcaton. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 14
Table 6. Multnomal regresson results Internal as reference category Equal as reference category Varables Equal External Internal External Constant -2.57*** -1.13 2.57*** 1.44 In-house product share -0.015*** -0.02*** 0.015*** -0.005 Appropraton condtons FIRMPAT -0.08-0.59 0.08-0.511 OTHPAT 0.36 0.84* -0.36 0.48 Technology characterstcs PRODUCT 0.023-0.26-0.023-0.29 Chemcals 0.317 0.22-0.317-0.09 Telecom equpment -0.68* -0.54 0.68* 0.14 Telecom servces 0.06 0.6-0.06 0.54 Computer servces 0.45-0.26-0.45-0.7 Internal capabltes Share R&D employees 0.004 0.003-0.004-0.0009 Frm boundares SMALL -0.38-0.38 0.38-0.0013 SUBSIDY 0.79** 0.45-0.79** -0.34 INDEPENDENT 0.75** 0.51-0.75** -0.25 External knowledge sources JOURNALS 0.34-0.26-0.34-0.6 REVERSE -0.052-0.28 0.052-0.22 IDEASUPL 1.046** 1.45** -1.046** 0.4 IDEACUST 0.58 0.62-0.58 0.04 IDEAUNIV 0.23-0.42-0.23-0.65 IDEAOTHER 0.61 1.03* -0.61 0.42 COMPLSUP 1.69*** 1.63** -1.69*** -0.06 COMPLCUST 1.89*** 1.77*** -1.89*** -0.13 COMPLUNIV 0.6 2.4** -0.6 1.8* COMPLOTHER 1.43** 0.98-1.43** -0.46 BRINGPRI 0.23-0.25-0.23-0.48 Number of cases 483 Pseudo R 2.33 Model χ 2 P <.000 * p<0.1, ** p<0.05, *** p<0.001 Note: Only two reference categores are gven because the thrd (external) s redundant. In ths case, the coeffcents for nternal compared to the reference category external are dentcal to the external compared to the reference category nternal. Smlarly, the coeffcents for equal n reference to external are dentcal to external n reference to equal. There are only mnor dfferences n the results gven n Table 7 for the ordered and bnary logt models, although the latter has a slghtly hgher pseudo R 2 value of.315 versus.283. Conversely, the lack of dfferences n the results between the two models suggests that the smpler, bnary logt provdes an adequate explanaton of the relatonshp between the ndependent varables and the dependent varables. Ths suggests that the man dfference C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 15
between the three groups of frms s between those that stress nternal knowledge sources and those that stress external knowledge sources. The ntermedate group of equal s ndstngushable from the external group. Table 7. Ordered Logt and Bnary Logt results Varables Ordered Logt Bnary logt (reference to external/equal) Constant -1.439** -2.93*** 1.22** % products developed n house 0.012*** 0.02*** Appropraton condtons FIRMPAT 0.18 0.145 OTHPAT -0.37* -0.522 Technology characterstcs PRODUCT -0.08 0.15 Chemcals -0.27-0.22 Telecom equpment 0.45* 0.7* Telecom servces -0.17-0.23 Computer servces -0.11-0.23 Internal capabltes Share R&D employees -0.0031-0.005 Frm boundares SMALL 0.26 0.36 SUBSIDY -0.42** -0.66** INDEPENDENT -0.49** -0.66** External knowledge sources JOURNALS -0.025-0.17 REVERSE 0.14 0.13 IDEASUPL -0.8** -1.12** IDEACUST -0.46* -0.54 IDEAUNIV -0.07-0.04 IDEAOTHER -0.58** -0.68* COMPLSUP -1.28*** -1.63*** COMPLCUST -1.38*** -1.78*** COMPLUNIV -1.07** -1.11* COMPLOTHER -1.1*** -1.23** BRINGPRI -0.033-0.09 Number of cases 483 484 Pseudo R-square 0.283 0.315 Model ch-square p 0.000 0.000 % correctly classfed 49.3 71.7 C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 16
Whether or not the nnovaton was patented has no effect on the preference for nternal knowledge sources. By technology characterstcs, the dummy varable for an nnovaton wth a PRODUCT component s not sgnfcant. The only sgnfcant dfference by sector s for telecom equpment frms, for whch the coeffcent s postve. Ths confrms the descrptve results n Table 3. The frm s R&D employment ntensty also has no effect, but the percentage of products developed n-house sgnfcantly ncreases the probablty that the frm wll prefer nternal knowledge sources. The frm boundary varables have a greater effect on the preference for nternal sources, wth the excepton of frm sze (also not sgnfcant when entered as the log of the number of employees). Frms that receved a subsdy to develop the nnovaton are sgnfcantly less lkely to prefer nternal knowledge sources, as are ndependent frms. The latter s a pecular result, snce external knowledge sources nclude other dvsons or unts of the same frm. Therefore, we expected frms that are part of a group to be less lkely to cte nternal sources, whereas the opposte occurs 10. As expected, external sources that are used to complete the nnovaton have a greater mpact on reducng the preference for nternal sources than external sources that contrbuted to the orgnal dea. Table 8 provdes bnary logt results for three sectors wth an acceptable model ft, food, chemcals and computer servces. Separate results are provded by sector n case the assumpton n the full data model of lnearty n the sector dummy varables s untenable. Appropraton and technology characterstcs have no effect n any of the sector models. Low and medum technology food frms are more lkely to prefer nternal sources, but R&D ntensty has no effect n the other two sectors. The sgnfcant and negatve result for the low technology food sector partly corroborates other results ndcatng that a mnmal level of nhouse expertse s requred to use external knowledge sources. Brngng n new scentsts and engneers (BRINGIN) has no effect n any of the three sectors. The recept of subsdes sgnfcantly reduces the preference for nternal sources n both the food and chemcal sectors, but has no effect n computer servces, probably because very few of the latter receved a subsdy. Independent food frms were less lkely to prefer nternal sources, but ths varable, whle negatve, s not sgnfcant n the other two sectors. COMPLETE s negatve and sgnfcant across all three sectors, hghlghtng the shft to external sources when they are brought n to help frms complete the nnovaton. IDEA s also negatve, but not sgnfcant n the food sector. The use of supplers decreases the preference for nternal knowledge sources n the food sector. The postve effect of PRIs as a knowledge source s lmted to computer servce frms, out of the three sector analyses. 10 Ths result s robust and also occurs n separate regressons for manufacturng and servce frms. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 17
Table 8. Bnary logt results for three sectors for nternal knowledge sources Food Chemcals Computer servces Constant 2.88*.75 1.57 % product nnovatons developed n-house.01.03***.02* Appropraton condtons Innovaton patented.87 -.46 -.26 Technology characterstcs PRODUCT -.49.43.10 Internal capabltes 1 Low R&D employee share (< 5%) 2.25*.60 -.86 Medum R&D employee share (5% 20%) 2.42*.40 -.28 Frm boundares SMALL.10.63.44 SUBSIDY -1.64** -1.62**.32 INDEPENDENT -2.06*** -.88 -.47 External knowledge sources COMPLETE -1.87** -2.37*** -2.24*** IDEA -1.57** -.43-1.65* COMPET -.30.66 1.88* SUPPLIER -1.33** -.35 1.19* CUSTS.34.25.32 PRI -.81 1.61 2.25* BRINGIN.22 -.39 -.04 Number of cases 119 116 126 Pseudo R 2.49.41.44 Model ch-square p.000.004.000 % correctly classfed 81.5 77.6 76.2 Notes: All analyses nclude country dummes, wth the Netherlands as the reference category. * =.05 < p <.10, ** =.01 < p <.05, *** = p <.01. 1: Reference category s over 20% of employees actve n R&D Table 9 provdes results for three countres wth an acceptable model ft; Germany, the Netherlands, and France, although the model for France s of borderlne acceptablty. Only a lmted number of varables are ncluded for Germany, due to a low number of cases. All regressons are weghted by the nverse of the response rate 11. The results for the Netherlands nclude the dummy varable HIGHCOST that equals 1 when total development costs for the nnovaton exceeded 0.5 mllon Euros and 0 otherwse. 11 We dd not attempt a model for the UK, due to a small number of cases. The models for Italy and Greece had acceptable model ch-square values, but the results for Greece dd not meet the Hosmer and Lemeshow test. Furthermore, both Greece and Italy had coeffcents wth unmagnably large coeffcents, suggestve of a lack of varaton n the varables or collnearty problems. The model for Denmark dd not meet basc requrements, possbly because of poor weghtng values. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 18
Table 9. Bnary logt results by country for nternal sources as the most mportant knowledge source Germany France Holland Constant -1.33.59.72 Percent product nnovatons developed n-house.051*.05**.026** Appropraton condtons Innovaton patented 2.02.47 Technology characterstcs Chemcal sector 2.90.10.11 Telecom equpment.083 2.21 2.47** Telecom servces 1.53-3.11** Computer servces 2.51** 3.81** -.48 PRODUCT -1.41-2.09** Internal capabltes 1 Low R&D employee share (< 5%).84 1.57 Medum R&D employee share (5% 20%) 1.77.32 Frm boundares SMALL 3.78* 1.87* SUBSIDY 2.38-6.97-2.81*** INDEPENDENT 1.72-3.36** -1.38* External knowledge sources COMPLETE -3.88-4.99 IDEA -1.54-4.19 COMPET 1.69-1.58 SUPPLIER.74-1.93** CUSTS.89-1.52** PRI 4.16 1.03 BRINGIN 1.46.78 HIGHCOST -1.25** Number of cases 49 63 104 Pseudo R 2.62.52.54 Model ch-square p.001.04.000 % correctly classfed 87.6 86.2 81.1 1: Reference category s over 20% of employees actve n R&D The most robust results (sgnfcant and n the same drecton for at least two countres) are as follows. The percent of product nnovatons developed n house ncreases the preference for nternal knowledge sources. In both Germany and France, computer servce frms are more lkely than the reference category of the food sector to prefer nternal sources. Smaller frms n France and Holland are also more lkely to prefer nternal sources, whle ndependent frms are less lkely to prefer nternal sources. HIGHCOST s negatve and sgnfcant n the model for Holland, ndcatng that frms are more lkely to seek out external knowledge sources for ther more expensve nnovatons. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 19
Conclusons The results n Table 3 show that almost half of total employment (48.4%) among the sampled frms s wthn frms that gave greater mportance to nternal rather than external knowledge sources n the development of ther most economcally mportant nnovaton. Only 17.1% of total employment s wthn frms that stressed external sources, whle the remanng 34.5% s wthn frms that gave equal mportance to nternal and external sources. However, the results of the three regresson models suggest that the man dfference among frms s between those that prefer nternal sources versus frms that ether prefer external sources or whch fnd external sources of equal value to nternal sources. Other robust results are as follows. Frst, appropraton condtons, as measured by whether or not the nnovaton was patented, do not nfluence preferences, possbly because appropraton ssues, and concern over nformaton leakage, play only a mnor role n the decson to obtan nformaton from external sources. Second, frms that receved nnovaton subsdes were less lkely to prefer nternal sources. Ths probably llustrates the effect of the strngs attached to subsdes rather than strategc choces. Thrd, ndependent frms are less lkely to prefer nternal sources. Ths appears plausble snce these frms have fewer nternal sources, on average, to draw upon compared to frms that are part of a larger group. However, the questonnare defnes other dvsons wthn a frm as part of the external sources, whch muddes the nterpretaton. Fourth, the type of external source that s used nfluences the relatve mportance of nternal sources. Frms that use supplers are the least lkely to fnd nternal sources more mportant than the other two optons. Ths could be most frequent for frms wth low nnovatve capabltes, a queston whch needs to be explored further. Furthermore, the purpose of the knowledge obtaned from external sources nfluences the results. Frms that use external sources to help complete the nnovaton are less lkely to prefer nternal sources than frms that obtaned the orgnal dea from an external source. Fnally, the results for the Netherlands show that frms are less lkely to rely on nternal sources for more costly nnovatons. In general, the results provde strong support for the role of external knowledge sources n the nnovatve actvtes of frms. Although approxmately half the frms stress nternal sources, the remanng half attach a sgnfcant value to external knowledge sources. The regresson results show that dfferences n preferences by sector or nternal nnovatve capabltes are mnor, wth the excepton of frms n the telecom sector. References Antonell C. Industral organsaton and the producton of knowledge. Cambrdge Journal of Economcs 23:243-260, 1999. Arundel A, Garrelfs R. (Eds) Innovaton Measurement and Polces, European Commsson, EIMS publcaton 50, 1997. Baldwn, JR. Da Pont M. Innovaton n Canadan Manufacturng Enterprses, Statstcs Canada Catalogue no. 88-513-XPB, Industry Canada, 1996. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 20
Davd PA, Foray D. Natonal profles n the systems of scence and technology learnng: a framework for nterpretng avalable quanttatve measures. Report for Dvson of Scence Technology and Industry, OECD, 1994. Francos J-P, Favre F. Technologcal nnovaton s progressng n ndustry. SESSI: Le 4 Pages des Statstques Industrelles, SESSI, Pars, 1998. Jaffe, A.B., Trajtenberg, M. Flows of knowledge from unverstes and federal laboratores: Modelng the flow of patent ctatons over tme and across nsttutonal and geographc boundares. Proceedngs of the Natonal Academy of Scences 93:12671-12677, 1996. Levn RC et al, Appropratng the returns from ndustral research and development. Brookngs Papers on Economc Actvty 3:242-279, 1987. Roelandt TJA, den Hertog P. Assessng the knowledge dstrbuton power of natonal nnovaton systems. OECD Conference on new S&T ndcators for the knowledge-based economy, Pars, June 1996. C:\WINDOWS\Επιφάνεια εργασίας\rename-oanna\int-extmerit_fnal.doc 21