The Impact of M&As on Technology Sourcing Strategies

Transcription

1 The Impact of M&As on Technology Sourcng Strateges Elena Cefs a* a Unversty of Bergamo, Bergamo, Italy and T.C.Koopmans Research Insttute, Utrecht Unversty, Utrecht, the Netherlands September 2008 Abstract The paper nvestgates the effects of mergers and acqustons (M&As) on corporate R&D strateges usng CIS data on the Dutch manufacturng sector. The man focus of the research s whether M&As have an effects on corporate nnovaton strateges, favourng n-house R&D and nnovaton expenses versus external technologcal sourcng. The results show that M&A actvtes have a postve and sgnfcant mpact on nnovaton nvestments made by frms, n partcular on R&D ntensty and on total expenses for nnovaton. M&As affect corporate nnovaton strateges, favourng n-house R&D versus external technologcal sourcng. Frm post-merger behavour favours the consoldaton of the knowledge, competences and capabltes that has been acqured by mergng wth or by buyng another frm, confrmng that M&As are more often performed for reasons lnked to frms nnovatve performance, rather than other reasons. Followng an M&A nvolvement, frms tend to prmarly focus on fully ntegratng ther resource-bases n order to be able to produce and actually sell nnovatve products that are new for the market Keywords: technology sourcng; nnovaton; M&As; B-Tobt; Heckman two-stage JEL codes: D21, O31, O32, L22 *Emal: e.cefs@econ.uu.nl and elena.cefs@unbg.t Correspondence to: Elena Cefs, Unversty of Bergamo, Dep. of Economcs, va de Canana 2, Bergamo, Italy

2 1. Introducton At the tme of wrtng, t would seem that the 6 th merger wave n economc hstory has reached ts peak, matchng both n numbers and n value ts predecessor durng the second half of the 1990s. Whle the current wave, just lke the 4 th, s characterzed by a great number of Leveraged Buy Outs (LBOs, usually arranged by prvate equty frms), the 5 th, just lke the 1 st, 2 nd and 3 rd, would rather have to be qualfed as a normal merger wave, n the sense that by far most transactons concerned acqustons by other frms than those actve n the market for prvate equty. Whereas t has been shown that LBOs lead to negatve effects on both captal and R&D spendng (Schenk 2006), and are purely set up for fnancal reasons and/or to captalse on the target frm s earler acquston errors, normal mergers have sometmes been justfed by scrutnzng the potental benefcal effects of M&As on frms R&D and nnovaton actvtes.. Yet, most studes of the effects of M&As on nnovaton have reached rather soberng conclusons. In part ths s so because most studes have focused on large, quoted frms. However, apart from these large mergers, thousands of smaller mergers and acqustons occur. Many of these occur at natonal levels, and t s possble even lkely that the effects of such smaller M&As generate dfferent results (Cefs et al., 2007). Moreover, deteroratng or stagnatng wealth creaton after a merger does not drectly ndcate what happens n terms of technology. In fact, studes have shown that frms ratonale to engage n M&A processes has evolved over the years (De Man and Duysters, 2005), nnovaton becomng an explct reason n the last merger waves. Ths has to be consdered aganst a background of an ncreasngly open nnovaton framework (Chesbrough, 2006) and a hgher mportance gven to external markets for technology (Arora and Gambardella, 2001). Rapd technologcal change and world-wde ncreased competton have turned nnovaton nto a crtcal element not only for ensurng frms economc performance, but also ther survval n the market (Cefs and Marsl, 2006). However, these are exactly the factors that have led also to a much hgher emphass on explorng external envronments, market opportuntes and knowledge sources beyond the boundares of the frm. Corporate level managers acknowledge that the core of the nnovaton process can no longer stand only n buldng n-house R&D and relyng on nner capabltes and resources, but far more on dentfyng, connectng and leveragng external knowledge sources. 2

3 Yet, as nnovaton greatly dffers (..) n terms of characterstcs, sources, actors nvolved, boundares of the processes and the organzaton of nnovatve actvtes (Malerba, 1997), the choce of nnovaton strateges s a rather complex one. The strategc choce and the pace of nnovaton nvestment s affected by endogenous factors from wthn the frm ft between ts nnovaton strategy and prevous nvestments n dstnct dmensons of absorptve capacty- but also by exogenous factors as approprablty condtons, market structure, uncertanty, threat of compettve entres or mpact on future value of the frm (Smt and Trgeorgs, 2007). What becomes clear s that nnovatve ntatves at frm level can no longer be regarded as stand-alone decsons, but as lnks n a chan of an nterrelated nnovaton process combnng both n-house growth and procurement of knowledge and resources from external sources. Recent lterature hghlghts more and more complementartes versus the embedded substtutablty approach n nnovaton choces at frm level (Cassman and Veugelers, 2006; Catozzella and Vvarell, 2007). If formerly a negatve relatonshp was expected between n-house and external sources, now far more optmst strands support potental synergy gans dervng from the use of external sources lke M&As. Of course, hgher rsks are at stake and the process nvolves changes n frm level dynamc capabltes (Teece et al., 1997), but the pay offs n terms of nnovatve performance may also be hgher. These complementartes n terms of technology sourcng strateges avalable at frm level s also drven by the change n M&A ratonales. More and more frms, especally of small and medum sze, vew M&As as mechansms of learnng and of acqurng resources, competences and capabltes from knowledge sources beyond the boundares of the frm (Veugelers and Cassman, 1999; Cassman and Veugelers, 2007; Ahuja and Katla, 2001). Therefore, consstent wth the vew of Cassman et al. (2006) that where nnovaton s tself the man reason of the M&A actvty, the results can often be postve and sometmes extremely so, we can expect that technology-drven M&As ncrease post merger n-house R&D expendtures n order to absorb the new technology, knowledge and capabltes that have been acqured through the M&A process. The purpose of ths study s that of analyzng the way n whch M&As change the technology sourcng strateges wthn frms undergong such processes. The man focus s on whether, followng a M&A actvty and the post merger ntegraton process, frms seem more lkely to assmlate the 3

4 acqured knowledge and resources and develop n-house R&D or just contnue to buy the results of R&D n the market. More specfcally, the questons addressed n the paper are as follows: ) Do M&As have an mpact on R&D ntensty and on the total cost of nnovaton? ) Whch, f any, are the effects of M&As on corporate R&D strateges? Do M&As favour n-house R&D or external R&D? ) Whch, f any, are the effects of M&As on the choce frms make between dfferent ways of procurng external technology? The emprcal part of the analyss wll use Communty Innovaton Survey data for the Netherlands,.e. data from CIS2, CIS2.5, CIS3, and CIS3.5. By lnkng these data to data from the Busness Regster database as compled by the Central Bureau of Statstcs/Statstcs Netherlands (CBS), I was able to ntegrate, at the frm level, comprehensve data on nnovaton and M&As. The results show that M&A actvtes have a postve and sgnfcant mpact on nnovaton nvestments made by frms, n partcular on total R&D ntensty and on total expenses for nnovaton. M&As seem to foster nternal R&D, whle they do not have any effect on R&D outsourcng. Wth regard to the corporate choce between dfferent external technology sourcng, M&As seem to postvely affect the acquston of new machnery but they do not affect the expenses for external knowledge as the purchase of rghts to use patents, lcenses or other types of knowledge from thrd partes. These fndngs suggest that frm post-merger behavour favours the consoldaton of the knowledge, competences and capabltes that has been acqured by mergng wth or by buyng another frm, confrmng that M&As are more often performed for reasons lnked to frms nnovatve performance, rather than other reasons. Wth regard to R&D and nnovaton cost effcency n terms of new products for the frm, the results ndcate postve effects of M&A nvolvement on frms capacty of dervng dynamc effcences. Followng an M&A nvolvement, frms tend to prmarly focus on fully ntegratng ther resource-bases n order to be able to produce and actually sell nnovatve products that are new for the market. The paper s structured as follows. Secton 2 dscusses the lnks n the lterature between M&As and nnovaton and/or R&D sourcng. Secton 3, 4 and 5 presents respectvely a descrpton of the data, llustrates both dependent and ndependent varables, and ntroduces the methodology used n the research. Results are presented n Secton 6 whle conclusons are drawn n Secton 7. 4

5 2. Theoretcal background 2.1. The mpact of M&A on R&D efforts Assumng ratonal economc behavour n M&As, frms would be expected to undertake mergers or acqustons wth the goal of ether rasng productvty (lowerng costs) and/or creatng synerges. Alternatvely, M&As are done n order to buld up or strengthen monopoly power. All are to be seen aganst a background of compettveness. In ths context, M&As can have or not effects on frms nnovaton dependng on the nature of the M&As and on nnovatve characterstcs of frms nvolved. De Man and Duysters (2005) cluster recent studes on the effects of M&As on corporate R&D and nnovaton performance nto two man groups: those that have studed the condtons for M&As to have a postve effect on nnovaton performance and those that have consdered the mpact of M&As on proxes of R&D actvtes. In terms of condtons facltatng a postve effect of M&As on corporate nnovaton performance, complementartes n resources (relatedness) (Cassman et al., 2005), smlar culture and management styles (organzatonal ft) (Chakrabart et al., 1994; Hagedoorn and Duysters, 2002), post-merger ntegraton, and assmlaton processes (Ahuja and Katla, 2001; Epsten, 2004; Cloodt et al., 2006) are more lkely to lead to nnovatve gans followng a M&A process. In terms of M&A mpact on R&D efforts and nnovaton actvtes, two economc mechansms should be consdered: economes of scale and economes of scope (Cefs et al., 2007; Henderson and Cockburn, 1996).). Both economes of scale and economes of scope allow frms to gan compettve advantages, or keep abreast wth the competton. Companes should be keen to ncrease research expendtures as they can proft of economes of scale and to expand the number of R&D projects to proft of economes of scope. In order to mnmze costs, companes have also ncentves to rase productvty n terms of R&D (ncreasng the ncdence of nnovaton output per nvested euro), or to decrease R&D expenses for any gven nnovaton output. Wth the excepton of Ikeda and Do (1983), emprcal studes have manly reported negatve effects of M&As on frms R&D efforts (de Man and Duysters, 2005; Htt et al, 1991; Capron, 1999). The present study ams to assess the effects of M&As on nnovaton nputs consderng as a proxy for frm nnovaton nputs two major ndcators: R&D ntensty and, n broader terms, the costs of nnovaton (scaled by frm-sze) that nclude ntramural and extramural R&D expenses, ndustral 5

6 desgn costs, and nvestments n acqustons of external knowledge lke lcences, copy-rghts, trademarks or software, costs for market research for nnovatve products, for tranng personnel for nnovaton actvtes, etc.. The choce of nnovaton proxes s justfed by the hypotheses, later tested, that M&As could possbly lead to hgher technology awareness, mplyng stepped-up R&D efforts, thus ncreasng R&D ntensty and total nnovaton costs frst, and ncreased performance later. Ths hypothess s manly fuelled by the fact that M&As are more and more employed as mechansms of learnng and of acqurng resources, competences and capabltes from knowledge sources beyond the boundares of the frm (Veugelers and Cassman, 1999; Cassman and Veugelers, 2002; Ahuja and Katla, 2001). 2.2 Effects of M&As on R&D make or buy strateges If stepped-up R&D efforts can be derved from M&A processes, t s of equal mportance to nvestgate also the extent to whch M&As affect the decomposton of R&D expendtures wthn the frms. Decomposng the structure of R&D expenses allows to analyse whether frms change the proporton of nternal versus external technology sourcng followng a M&A process. Several papers (Cassman and Veugelers, 2006; Catozzella and Vvarell, 2007) suggest that there exst complementartes between n-house R&D and external technology sourcng. Furthermore they state that t s partcularly these complementartes that allow frms to attan a hgher nnovatve performance. Focusng solely on one technology sourcng strategy - ether constantly accumulatng nhouse R&D but not explorng the opportuntes avalable on the market, or to the contrary contnuously buyng technology on the market, but not assmlatng the new knowledge wll lead to lower nnovatve performances (Cassman and Veugelers, 2006). Ths vew of complementartes and supportve nnovatve actvtes (Catozzella and Vvarell, 2007) suggests a two way relatonshp between external and nternal technology sourcng: ) frms are able to use and assmlate external sourcng only after havng reached certan level of nternal R&D and havng developed the absorptve capacty (Cohen and Levnthal, 1989); ) symmetrcally, 6

7 nvestment n external sources of knowledge and technologes stmulates n-house nnovatve research (Veugelers, 1997; Lokshn et al., 2008). Ths study focuses on the second part of ths two-way relatonshp. Assumng that complementartes exst among nnovaton actvtes, we would expect two dfferent effects of M&As on the proporton of resources devoted to nternal versus external technology sourcng. The mpact wll vary accordng to the dfferent nature of the M&As. If M&As are performed merely for ganng market domnance (wthout any technologcal reason nvolved) then M&As would not be expected to have any a pror effects on ether nternal or external technology sourcng. On the other hand, M&As, especally among small and medum frms, are often technology drven, that s performed n order to acqure new knowledge, technology, and capabltes that are not avalable to the acqurng frm due to the lack of nternal competences. In ths case, we should expect that M&As have an effect on the composton of the technologcal sources beng the M&A act regarded as a buy act n ts own rght, snce t has been motvated by the desre to acqure new knowledge and technology. Two dfferent vews have been formulated n the lterature also wth respect to the possble changes n the allocaton of frms n-house R&D expendtures, followng a M&A process. The frst one sees nternal R&D and technology drven M&As as frm level nnovatve strateges that substtute each other; thus a negatve relatonshp between the two s hypotheszed (Basant and Fkkert, 1996; Bagues, 2004). The second sezes the potental synergy gans dervng from the M&A process and therefore predcts a possble postve effect on future n-house R&D development (Blonngen and Taylor, 1997; Lokshn et al., 2008; Belderbos et al., 2006). However, Rcart and Adegbesan (2007) suggest that ths to some extent depends on the (rather vaguely defned) ft between a frm s nnovaton strategy and ts prevous nvestments n dstnct dmensons of absorptve capacty. It also would seem to depend on the wealth bult up by the acqurng frm n the past. In lne wth the fndngs of Cassman and Veugelers (2006) ths study adopts the complementartes approach n studyng frms Make or Buy nvestment decsons. Hence, gven the complementartes of nnovaton actvtes, we should expect frms that have prevously used M&As as sources of external procurement to later ncrease n-house R&D efforts n order to fully explot the new technology, knowledge and capabltes acqured from explorng the markets for technology (Arora and Gambardella, 1994; Rosenberg, 1990). Ths swtch n strateges s expected to derve from a hgher 7

8 technology awareness: the externally acqured knowledge and technologes wll be ntegrated and assmlated, enhancng frms capabltes to develop R&D and nnovatve actvtes nternally. 3. The data The data used n ths paper stem from two dfferent sources. I merged frm level nformaton on nnovaton behavour and technologcal change from the Dutch Communty Innovaton Survey (CIS) wth frm specfc demographc characterstcs taken from the Busness Regster (ABR), both elaborated and made avalable by Central Bureau of Statstcs Netherlands (CBS). The CIS database gathers nformaton on the extent and characterstcs of frms nnovaton actvty, technologcal performance and organzatonal change. In the Netherlands, the CIS s conducted on a two-year bass. Each wave covers the three year perod pror to the survey. Up to ths moment, fve CIS waves have been made avalable at CBS, coverng the perod and allowng analyses of nnovaton dynamcs at frm level. We allow for a post-acquston ntegraton perod from 3 up to 5 years followng frms M&A nvolvement, n analysng the effects of M&A on frms R&D and nnovaton expenses structure. The need to account for a post-acquston ntegraton perod lmted the tme frame of the analyss to , coverng the frst four CIS waves (CIS 2, CIS 2.5, CIS 3 and CIS 3.5) and excludng CIS 4 because the prevous wave, namely CIS 3.5, does not contan any varable related to M&A actvty performed by the frm. The target populaton of the CIS covers prvate sector frms, drawn as a stratfed sample 1 from those present n the Busness Regster wth at least 10 employees. Two CIS waves, namely CIS2.5 and CIS3, fnanced by the Mnstry of Economc Affars, also nclude frms wth 1-10 employees. In order to have comparable sample we exclude n those two waves frms wth less than 10 employees. The second data source, ABR, supples frm demographc nformaton, age, sze, the ndustral sector and the nature of the frm s nvolvement n an M&A process. A schematc overvew of the constructon desgn of our panel s gven n Fgure 1. ABR ncludes frm ndustral sector (at 5 dgt level), sze (expressed by the number of employees), as well as the date of entry and ext n/from the 8

9 regster. The mergng process leads to an unbalanced panel of 4604 frm-level observatons, from 1994 to 2002, whch correspond to 2913 manufacturng frms. 4. The varables Frms use more and more M&As as mportant channels of ganng access to technology and of fosterng nnovatve actvtes. However, assessng M&A processes n terms of frms ex-post capabltes to manage nnovaton (frms dynamc effcences) stll remans a controversal ssue. One mportant aspect s the way n whch M&As affect the composton of R&D and all the costs related to nnovaton. Ths study consders M&As mpact on frms technology sourcng strateges, dstngushng between: ) the decomposton of R&D expendture n n-house R&D, external R&D and R&D personnel; ) the decomposton of nnovaton costs n external knowledge (acqurng patents and lcenses), acquston of new machnery and software, market research and R&D personnel related expenses; and ) capablty of these nvestments n generatng new products and processes (R&D and nnovaton effcences). 4.1 The selecton model We can reasonably assume that frms decde to nvest n nnovatve actvtes only f the foreseeable pay offs from dong so are mportant and the rsks assocated to them are below certan threshold. We can only observe frms behavour (.e. the level of R&D expenses or, more n general, the nnovaton nvestments) only for frms that have decded to nvest n nnovatve actvtes more than a certan threshold. Gven ths nature of frms behavour concernng R&D and nnovaton expenses, I had to account for a selectvty bas n the sample. 2 I ntroduce a selecton model that explan the decson of the frm to nvest n nnovatve actvtes dependng on frm-specfc varables lke: fnancal constrants, marketng constrants, organzatonal, regulatory and strategc constrants that have been perceved by the companes as mpedng n any way ther nnovatve actvtes. These are endogenous and exogenous factors meant to dentfy and capture plausble reasons affectng frms poston of enterng/not enterng nnovatve actvtes as well as ther nnovatve performance. The frst proxy used - fnancal constrants - measures the lack of approprate fnancal resources for engagng 9

10 n nnovatve actvtes. It s a dummy varable, takng the value 1 f the company gves a postve answer to the queston: has your company been faced wth fnancal constrants due to whch nnovaton projects have not started? The rest of our proxes have a smlar structure (1/0 dummes). The marketng constrants proxy captures whether frms have been reluctant to engage n nnovatve actvtes due to uncertan market future development of new products. The dummy on nternal organzatonal constrants questons whether the cause of lack of nnovaton actvty has been due to nflexble organzatonal structures exstent wthn company. The strategc proxy offers as plausble cause of not engagng n nnovatve actvtes the uncertanty of outputs and future profts dervng from nnovaton especally due to the lack of manageral, organsatonal and technologcal capabltes nsde the frm. Fnally, the regulatory constrant varable comprses exogenous legslatve ssues (personnel, tax or envronment related) that mght affect nnovatve performance at frm level. As explanatory varables of frm s probablty to nvest on nnovaton, I have also ncluded some frm s characterstcs lke frm sze, frm age, and technologcal regmes (Pavtt categores). In fact, these characterstcs have been proven n the lterature to be relevant n shapng the nnovatve behavour of the frms (see among others: Pavtt, 1984; Dos, 1988; Bresch et al, 2002; Marsl and Verspagen, 2002; Cefs, 2003) 4.2. The technology sources model Dependent Varables Frm-level nnovaton actvtes requre a broad spectrum of nvestments, rangng from expenses devoted to nternal or external R&D to nvestment n new machnery, n acqurng patents and lcences, n tranng R&D personnel or n launchng new products n the market. These dfferent types of engagement can be embedded under two man groups: a) R&D related expenses and b) nnovaton nvestments. The CIS-ABR panel allowed us to analyze these dfferent types of technology sourcng ndcators and ther decomposton. We also analyse the extent to whch frms are able to derve dynamc effcences from the nnovaton process, by constructng R&D and nnovaton effcency proxes. 10

11 The Decomposton of R&D Expendtures The dstncton between nternal and external R&D expenses s of utmost mportance n a postacquston technology sourcng study. Cassman and Veugelers (2006) emphasze the complementartes between nternal and external R&D, ndcatng that frms need to combne both types n order to attan the hghest nnovatve performance. However, Cohen and Levnthal (1989) sustan that frms need frst to conduct nternal R&D n order to be able to successfully ntegrate technology and knowledge bases produced outsde the frm. Frms need to nternally develop the absorptve capacty before beng able to source knowledge and technologes externally. Beng a study of frms technology sourcng strateges and how they are affected by M&A nvolvement, t s nterestng to acknowledge the changes nduced by the M&A process n the structure of R&D expenses. In terms of R&D expenses (as well as when consderng the total costs related to nnovaton) M&As could ether nfluence frms nto ) makng use of the recently acqured knowledge bases and technologcal capactes and captalze on the company s nternal technologcal assets, as nhouse R&D performers; ) mantanng a hgh level of external R&D spendng, by preferrng to acqure knowledge base and technologcal know-how from thrd partes or subcontractors rather than producng t nternally; ) combnng nternal and external R&D, as a fully ntegrated entty takng advantage at the maxmum by both n-house technologcal nvestments and frms absorptve capacty of external R&D. In order to test these hypotheses, we use as proxes of R&D engagement frm total R&D expenses, the dvson between nternal and external R&D spendng, as well as the total hours worked by R&D personnel. Total R&D expenses nclude all creatve, systematc research performed wth the purpose of realsng nnovatons. It conssts of nvestments and research related expenses ncurred durng R&D projects, as well as of costs wth hrng R&D personnel. The dvson between external/nternal R&D refers to whether these actvtes are performed wthn the frm, or by employng subcontractors or thrd partes (ncludng specalsts temporary employed to work on a specfc nnovaton). These proxes are consdered n relatve terms, as R&D ntenstes, calculated as ratos of R&D expendtures on total number of employees. The total hours of R&D personnel ncludes hours worked by all employees nvolved n R&D actvtes, such as researchers, techncans, assstants and other staff workng on R&D projects. 11

12 The Decomposton of Innovaton Costs As R&D s only a part of the nnovaton process, the second dstncton that needs to be emphaszed concerns nnovaton nvestments. By nvestments n nnovaton, we consder all expenses made by a frm n order to develop technologcally new, or substantally mproved, products, processes or servces. Arrow (1962) stresses the dstncton between R&D and nnovaton engagement, n what he labels as an economc dlemma of R&D fnancng. Frms experence gaps n fnancng ther R&D actvtes especally due to the sunk cost nature of R&D expenses. Ths s to a large extent also confrmed by the study of Hall (1999), whch emphaszes that ths gap s explaned by a reluctance to allocate money n research or knowledge and a far hgher prevalence of fnancng physcal assets (lke acquston of machnery, for example). The varable Innovaton Expenses ncludes frm expenses for the acquston of nnovatve machnery, computer hardware and software specfcally purchased for realsng nnovatons, acqustons of patents and lcenses, as well as market researches and tranng costs of the R&D personnel. I decompose t consderng dstnctly three proxes of nnovaton engagement: a) purchase of rghts to use patents, lcenses or other types of knowledge from thrd partes, labelled as external knowledge expenses ; b) acquston of hardware/software and new machnery; c) costs due to market research actvtes drectly amed at the market ntroducton of new products or servces, as well as the tranng costs of the R&D personnel, labelled as market and personnel related nnovaton expenses. These proxes are also consdered n relatve terms, as nnovaton ntenstes, calculated as ratos of nnovaton expendtures on total number of employees. R&D and Innovaton Effcences Analysng the mpact of M&A processes frms capacty of stmulatng dynamc effcences completes our technologcal sourcng post-m&a analyss wth detals on frm nnovatve achevements. Dynamc effcences are the effcences amed at generatng hgher levels of nnovatons. They are estmated as the rato between frms nnovatve output and frms nnovatve nputs (done n the prevous CIS wave). We consder frms nnovatve output only n terms of frms total sales due to new or sgnfcantly mproved products, but we account for two levels of novelty, namely, products that are 12

13 new or technologcally mproved for the frm and those that are new or mproved for the market. We choose as proxes of nnovatve nputs total R&D expenses and total costs for nnovaton. Thus, I construct 4 effcency varables: 1) R&D effcency n terms of new products for the market, as rato between total sales due to new products for the market at tme t and total R&D expenses at tme t-1, where t represents a specfc CIS wave and t-1 the prevous wave, thus allowng a lag of 2 years; 2) nnovaton cost effcency n terms of new products for the market, as rato between total sales due to new products for the market at tme t and total cost of nnovaton at t-1; 3) R&D effcency n terms of new products for the frm, as rato between total sales due to new products for the frm at tme t and total R&D expenses at tme t-1; 4) nnovaton cost effcency n terms of new products for the frm, as rato between total sales due to new products for the frm at tme t and total cost of nnovaton at tme t Independent Varables The M&A proxy The man nterest of our study s that of analyzng the extent to whch the occurrence of a M&A event nfluences frm technology sourcng strateges. M&As mpact on frm nnovaton-related sourcng strateges cannot be easly predcted, as t often depends on several technology and market related dmensons surroundng the two mergng companes. Prevous lterature (Cassman et al., 2005; Cassman and Colombo, 2006) reports both postve and negatve effects of M&A on nnovaton. The negatve effects refer to decreases n R&D outputs and productvty followng a M&A, wth mergng companes rarely beng able to approprate the benefts of scale and scope economes n R&D. However, evdence shows also postve effects of M&As on frms R&D and nnovatve capactes: puttng together ther knowledge bases, resources and technologes frms are able to develop new knowledge, competences and capabltes allowng them to become successful nnovators. 13

14 Moreover, undertakng a case-study approach, Cassman and Colombo (2006) fnd evdence that an effcent management of the post-m&a ntegraton process can lead to mproved nnovatve performance despte a short-term weakenng of R&D efforts and fnancng. Ths s also confrmed by Haspeslagh and Jemson (1991) and Jansen (2002) who stress the mportance of a very well-planned post merger ntegraton perod that should allow an effcent transfer of strategc capabltes from the target to the acqurer frm. We have chosen as M&A proxy an ndcator denotng whether or not the company has engaged n the acquston of other frms n the prevous three year-perod. We have used the lagged value of ths ndcator, n order to allow for a suffcently long post-merger ntegraton perod. Accordngly, we allow for a tme span of 3-5 years followng frms M&A nvolvement, analysng the effects of M&As takng place n the prevous CIS wave on frm nnovaton and R&D expenses, as well as on the effectveness of R&D and nnovaton nput usage, as reported n the current CIS wave. Accountng for technologcal regmes and frm demographc characterstcs In order to capture technology-specfc condtons, we choose to ntroduce n our model proxes classfyng the frms accordng to Pavtt s taxonomy (1984). Accordngly, we construct 4 dummy varables, classfyng our sample n: scence-based frms, specalzed supplers, scale ntensve and suppler domnated frms. The last category (suppler domnated) acts as reference category for our estmates. The Pavtt s dummes are meant to capture and control for technologcal opportunty condtons (easer to nnovate n certan felds than n others; possbly ndustry targeted nnovaton polces), approprablty condtons and organsatonal characterstcs gven by the technology (Maresse and Mohnen, 2002). Teece (1986) stresses the mportance of technologcal regmes n selectng for nternal versus external nnovatve strateges. Another mportant aspect that needs to be accounted for n analyzng frm knowledge and technology sourcng strateges concerns frm sze and age. Gopalakrshnan and Berly (2006) found evdence that both age and sze nfluence the relatonshp between frm knowledge sourcng strateges and ther nnovatve behavour. Large frms are more lkely to beneft both from n-house R&D and from external technology sourcng, due to ther hgher absorptve capacty (Cockburn and Henderson, 1998). Addtonally, small frms may prove more nnovatve effcent, due to ther lower level of bureaucracy and ncreased adaptablty (Acs and Audretsch, 1987). Concernng age, younger frms 14

15 seem more lkely to develop and mantan connectons to sources from outsde the frm and more easly approprate the benefts related to external sourcng than old frms. However, both relatonshps are more lkely to show a non-lnear trend. To account for the non-lnearty, we ntroduce squared terms of both age and sze proxes n our models. We measure frm sze usng the natural logarthm of the number of employees as reported n the ABR fles. Age s calculated usng also the ABR dataset, as dfference n months between the date of the CIS wave (December of the last year of the wave) and frm s date of entry n the Busness Regster (always expressed n logarthmc terms). 5. Methodology The focus on structural dfferences n frm R&D and nnovaton expenses and cost-effcences mpled estmatng separate regresson models for each R&D and nnovaton proxy descrbed n the above Secton. The panel structure of our dataset allowed modellng the change observed n these proxes over tme ( ) and under partcular crcumstances (followng an M&A event). Condtonng on a multtude of nfluencng factors, frms make decsons as to whether nvest money n fnancng R&D actvtes or n developng nnovatve products, processes and technologes. The nature of frm s R&D and nnovaton nvestment behavour rases a few methodologcal concerns. The man ssue s that of selectvty, analogous to estmatng a labour supply functon, where ncome data s only avalable for those actve n the labour market (Love &Roper, 2002; Grffth et al., 2006)). Lkewse, we can only observe R&D expendtures and nnovaton costs for those frms that spend more than a certan threshold on fnancng such actvtes (Crepon et al,. 1998; Benavente, 2006). Gonzalez and Pazo (2003) show that frms perform R&D and nnovaton actvtes only when ther optmal level of R&D expendture surpasses a certan threshold level, at whch the frms would be ndfferent between performng R&D or not. That s, f: * * ** π ( p,x ) > π ( p,0 ),where: * p = the optmal prce; * x =the optmal R&D expendtures; 15

16 ** p = the prce the frm wll set f t decdes not to nvest n R&D. Thus, the amount of money nvested n nnovaton and R&D may be zero for many companes, but ths should be regarded as ther decson not to get nvolved n such actvtes, ether because they consder t too rsky, too dffcult gven ther nternal organzatonal structure and nternal competences and capabltes at that moment, or smply they don t dspose of enough funds for enterng nnovaton actvtes. To account for ths, I estmate a two-stage Heckman model. The framework of a sample selecton model allows specfyng: (1) a probt model for the decson of frms to nvest or not n nnovaton actvtes, whch allows estmatng the sample selecton term 3 λ and (2) a model for how much funds has a frm actually allocated to R&D and nnovaton, ether nternally or externally, corrected for selectvty bas. The selecton model can be wrtten as: z = w' α + e * z = 0 f z * 0 z = 1 f z * > 0, where z = frm s choce to nvest n nnovaton actvtes, constructed on the bass of frms total cost of nnovaton. The second model conssts of an OLS regresson model estmatng the expected value of y condtonal on z=1 and other explanatory varables denoted by X. The specfcaton of the OLS model s of the form: y = X ' β + u * y = f z = 1 * y, y not observed f z =0. where y * = the amount allocated by frms to nternal/external R&D and nnovaton actvtes ( ether taken as global costs, or as dsaggregated elements). The Heckman 2-stage estmator requres excluson restrctons (Heckman,1979): varables that are lkely to affect the probablty of nvestng n nnovaton, but are unrelated (orthogonal) to the 16

17 actual amount spent nternally or externally by frms for nnovaton-related actvtes. Therefore, the selecton functon ncludes a set of explanatory varables z, whch nclude some X factors, but must also nclude addtonal factors that do not appear n X. In our selecton model, the dependent varable s a dummy, ndcatng whether a frm has nvested n nnovaton or not. Ths proxy has been calculated accountng for frm total cost of nnovaton. If a frm cost of nnovaton has been above zero, the frm s consdered as nvestng n nnovaton actvtes, wthout dfferentatng whether the nvestment contrbuted to nnovatve development nternally or externally. If frm total cost of nnovaton has been zero, or the frms have skpped ths queston n the CIS questonnare (due to a non-nnovatve status, acknowledged n the openng queston of the CIS), they have been placed n the non-nvestors category. As ndependent varables, we have used sze, age, technologcal classes, as well as a number of proxes denotng whether durng the process of consderng nnovaton actvtes, a frm has experenced problems of fnancal rsks, market ncerttude, strategc/nternal organzatonal problems or regulaton ssues that have mpeded or affected n any way the nnovatve process and ultmately ther decson to nvest/not nvest n nnovaton. Thus, the selecton model s estmated by: P( nvest ) = probt( β fn _ rsk + β mkt _ rsk + β nt_ org + β regulatons + t 1 t 2 t 3 t 4 t + β strategc _ rsk + β age + β age + β sze + β sze t 6 t 7 t 8 t 9 t + β scen based + β specal sup + β scale nt + µ ) 10 t 11 t 12 t The second stage of the Heckman model, the OLS regresson, wll capture the effects of frm s prevous M&A nvolvement on frm R&D and nnovaton expendtures, controllng for frm s demographc and technologcal specfctes, as well as for any selectvty bas. The followng model has been estmated usng a pooled OLS estmator: ln( tech _ source ) = α + β ( M & A ) + β age + + β sze + β scen based + t 1 t 1 2 t 3 t 4 + β specal sup + β scale nt + β λ + ε where s the Mlls rato that captures the sample selecton bas estmated n the frst stage wth the Probt model. As a senstvty analyss to evaluate whether the results are robust to changes of the model or are model-drven, Random Effect (RE) models have been estmated on the baselne specfcaton used for Heckman two-stage models. Furthermore, RE allow to explot the panel structure of the data 4 and tme 17

18 dummes have been added as regressors. A tme dummy for each CIS waves has been added, namely d1998, d2000 and d2002 ndcatng the last year of each CIS wave and d2000 has been chosen has the year of reference, therefore dropped from the regressors. RE estmators have been appled at the emprcal models specfed n Table 5, 6, and 9 and the Tables showng the results are n the Appendx. The second part of the analyss concerns frms opton to act as ether n-house or external R&D/nnovaton nvestors. Assumng that frms decson to nvest n ether nternally or externally drven nnovaton s made smultaneously wth the choce of the actual nvested amount, we estmate bvarate tobt regresson models of : (1) nternal R&D expendtures vs. external R&D expendtures; (2) nternal cost of nnovaton (n partcular the cost for acqurng nnovatve equpment) vs. external cost of nnovaton (namely the expenses for acqurng patents and lcenses). 6. Results 6.1 The Unvarate Analyss Unvarate analyses are conducted both on the ndvdual CIS waves consdered and on the complete CIS-ABR panel. Tables 1 and 3 present descrptve statstcs dstngushng across CIS waves, whle Tables 2 and 4 focus on the mean dfferences between the two groups of frms of nterest: those prevously nvolved n M&A actvtes and those not engaged n these knd of actvtes. Table 1 gves a general overvew of our sample, splttng the frms nto M&A actve and M&A nonactve frms. The average mean values of frm demographc characterstcs (age and sze) are calculated across the complete panel. Values of frm sze proxes (frm number of employees and frm total sales) as well as frm age (expressed n number of months) are presented for both M&A actve and non-actve frms, n order to reflect ther potental mportance n nvestgatng post-m&a technology sourcng strateges at frm-level. The mean values of frm sze (regardless f we use as proxy the total sales or the number of employees) are clearly larger for frms prevously actve n M&A actvtes. Ths s the reason why n the multvarate analyss I control for sze and age not only by nsertng these proxes n the model, but also by consderng all dependent varables n relatve terms, namely scaled by frm sze Insert Table 1 around here Tables 2 and 3 present the descrptve statstcs on the dependent proxes we have used to model the decomposton of frm total R&D expenses and total cost for nnovaton. The dstncton s gven by the 18

19 fact that Table 2 dsplays frm-level technology sourcng statstcs across CIS waves, whle Table 3 gves an averaged mage of these proxes across our complete CIS-ABR panel, makng the dstncton between M&A actve and non-actve frms. Table 2 shows that the mean of the varables of nterest s qute stable across CIS waves. The only proxes showng a dfferent trend are frm total cost for nnovaton and the expendtures devoted to the acquston of machnery. Actually, the former ncludes the latter, ths suggestng that the cause of the sudden decrease found n the total costs made for nnovaton at frm level are explaned by the decrease of cost for acqustons of machnery, whch can be consdered our most pro-cycle varables. Indeed, we see that the expenses made for acquston of machnery exhbt the lowest level n the last CIS wave consdered (CIS 3.5) n our analyss,, coverng the tme perod Durng these three years, the Dutch economy experenced a recesson, whch reached ts mnmum exactly n the year 2002 (CPB s Economc Outlook, Report 2003/1) Insert Table 2 around here Table 3 presents the descrptve statstcs of the same R&D and nnovaton technology sourcng proxes as before, averaged along our CIS-ABR panel. It presents the mean of frm R&D expenses and total nnovaton cost, as well as ther decomposton proxes, dstngushng between M&A and non M&A actve frms. Generally, M&A actve frms show hgher means than non-actve counterparts and the dfference s sgnfcant. Ths suggests that M&A frms nvest and spend more n R&D and nnovaton related actvtes than M&A non actve frms. More n detal, the dfference between the two groups s sgnfcant for the total R&D expenses proxy and for the n-house R&D proxy, whle not sgnfcant for the external R&D proxy (the R&D actvtes performed by thrd partes). It seems that there s not any dfference between M&A and non-m&a frms when they have to decde to outsource R&D actvtes. The dfference between means s not sgnfcant for the proxes denotng the total expenses devoted by frms to the acquston of machnery and frm market and personnel nnovaton related expenses ( ncludng marketng actvtes drectly amed at the market ntroducton of new products or servces, as well as the tranng costs of the R&D personnel). It s worth notng that the hgher mean values, n terms of R&D ntenstes or nnovaton expenses scaled by sze, regstered by frms nvolved n M&As as shown n Table 3, s not the result of an accountng artefact due to the fact that frms have been merged or acqured. In fact, the statstcs are calculated consderng frms that have been M&A actve from 3 to 5 years before the year of the 19

20 statstcs, thus allowng a post-merger ntegraton perod that should elmnate or at least consderably reduce the accountng dstorton Insert Table 3 around here The panel-level descrptve statstcs allow dscernng whether most of the varaton n our sample can be found between frms or across frms over tme. The results suggest that most of the total varaton observed s accounted by the between frms varaton, ths beng one of the arguments justfyng the choce of our model estmaton technque n the multvarate analyss The Multvarate Analyss As a frst step, we look at the effects of M&As on total R&D expenses and on ther decomposton between R&D performed by frm nternal personnel and thrd partes (see Tables 5 and 7). The results of the selecton equaton are presented n Table 4. Strategy constrants, namely uncertanty of outputs and future profts dervng from nnovaton especally due to the lack of manageral, organsatonal and technologcal capabltes nsde the frm, s the only proxy that shows a sgnfcant effect on frm nvestment decson, controllng for the other factors. It seems that what really matters for a frm to decde to nvest n nnovatve actvtes s to be sure that nsde ts structure there are all the manageral, organzatonal and technologcal resources that she needs to carry out nnovatve actvtes. The other constrants do not play such an mportant role Insert Table 4 around here Consderng the decomposton of R&D expenses, M&As seem to postvely affect the total R&D expenses scaled by the number of employees. In partcular, the expenses for R&D actvtes performed by frms own personnel ncrease after frms have engaged n M&As. Ths result should not be derved merely from the post-m&a ntegraton process or the accountng destorson that can rase after a M&A, snce I allowed from 3 up to 5 year lag (from the moment n whch the M&A has taken place to the tme I whch the data on R&D and nnovaton expenses have been collected) n order for the ntegraton process to take place and the accountng dstorton to be elmnated or sgnfcantly reduced. Ths ncreased engagement n nternal R&D actvtes s confrmed by the ncrease of the total hours of frm s nternal R&D personnel. In fact, frms that have experenced a M&A do not seem to 20

21 nvest more than those not nvolved n M&As n R&D performed by thrd partes. Thus, M&As seem to foster nnovaton through the drect channel of R&D resources nvested nsde the frm Insert Table 5 around here When we take n consderaton a more comprehensve proxy than R&D expenses, the varable that tres to measure all costs that a frm faces to fnance the nnovaton process (total nnovaton expenses), the prevous results are confrmed. Tables 6 presents the coeffcent estmates of the regressons run on total nnovaton expenses (from these expenses the R&D expenses have been subtracted) and on some of ts components dvded n expenses for developng nnovatons nternally or externally. The expenses made by the frm to enhance nnovatve actvtes wthn the frm nclude expenses for the acquston of nnovatve machnery, computer hardware and software specfcally purchased for realsng nnovatons, market researches for launchng new products, tranng courses for nternal personnel n order to use nnovatve machnery or to apply a new producton process, The expenses to fnance the develop of nnovatons carred out by thrd partes, external to the nclude expenses for acqurng external knowledge lke patent lcences, copy-rghts, etc., market research for launchng new products conducted by thrd partes M&As performed 3-5 years before have a postve sgnfcant effect on frm total expenses for nnovaton (excludng R&D expenses). The estmates show that M&As have a sgnfcant role n ncreasng the expenses made to enhance nnovaton wth the frm, consttuted by expendtures for the acquston of new types of machnery or software, marketng actvtes, and tranng costs of the R&D personnel. Consstently wth the R&D results, Table 5 shows that M&As do not sgnfcantly affect the expenses for outsourcng nnovaton actvtes and n external knowledge. M&As seem not to enhance the purchase of rghts to use patents, lcenses or other types of knowledge from thrd partes. It could be argued that M&As themselves are means to acqure external knowledge, and therefore, frm post-merger behavour favours the consoldaton of the knowledge that has been acqured by mergng wth or by buyng another frm. As a consequence, we should wtness an ncrease n expenses that enhance the consoldaton of the knowledge and, more n general, of the competences and capabltes that a frm has acqured through the M&A process. Ths nterpretaton would support the argument that M&As are more often performed for reasons lnked to frms nnovatve performance, rather than other reasons Insert Table 6 around here

22 The same results are confrmed when assumng that frms decson to nvest n ether nternally or externally drven nnovaton s made smultaneously wth the choce of the actual nvested amount. The estmates of the Bvarate Tobt models are presented n Tables 7 and 8. In partcular Table 7 show the results of the regresson when consderng the smultaneous choce between nternal R&D expendtures and external R&D expenses. The results re-confrm the prevous fndngs that followng an M&A process frms seem to nvest more n n-house R&D expendtures than n outsourcng to thrd partes the R&D actvtes. The results shown n Table 8 goes n the same drecton: M&As seem to favour the frm nvestment n nternal cost of nnovaton (n partcular the cost for acqurng nnovatve machnery) rather than keepng explorng market opportuntes (nvestng n acquston of patents and lcenses) Insert Tables 7-8 around here Table 9 completes the nvestgaton of M&As effects on corporate strateges for R&D nvestment by consderng the effcency sde: frms capacty of transformng R&D and nnovaton nvestments nto valuable nnovatve output, namely n new products for the frms and new products for the market. By tacklng ths, we assess not only the changes n frms technology sourcng strateges, but also the extent to whch these changes have proven to be benefcal n terms of dynamc effcences. For R&D and nnovaton cost effcency n terms of new products for the frm, the estmates ndcate a negatve effect of a M&A nvolvement on frms capacty of dervng dynamc effcences. On the contrary, for the second group of effcency proxes, namely for R&D and nnovaton cost effcency n terms of new or sgnfcantly mproved products for the market, the estmates ndcate a postve effect of M&A nvolvement. Ths seems to suggest that besdes contrbutng to an ncrease n frms n-house R&D potental and absorptve capacty of external R&D, M&As also stmulate frms n dervng valuable gans n terms of frm-level nnovatveness. In fact, the results seem to pont at the fact that frms nvolved n M&As processes are more effcent n terms of beng able to ntroduce new products and servces nto the market. New not only for the frms but for the entre market. These results seem to emphasze that M&As play an mportant role n ncreasng the radcal nnovatveness of the frms, and support the argument accordng to whch followng an M&A process frms put together ther knowledge bases, competences and technologes, enhancng ther ablty to produce new products for the market, that s 22

23 not merely mtatng products already present n the market (products new for the frm but not for the market, frst and thrd column of the Table) Insert Table 9 around here Fnally, n the Appendx are reported the results of the senstvty analyss. In order to check whether the results obtan are robust to some change n the model, I estmated all the models n Table 5, 6, and 9 usng a Random Effect estmator and explotng the panel structure of the data (ncludng year dummes). The results concernng the man varable of nterest, M&As (t-1), dd not change qualtatvely: the sgn and the sgnfcance of the coeffcents consstently reman the same and the magntude does not change sgnfcantly. In consderng the effects of M&As on R&D expenses and nnovaton expenses (Table 5a and 6a), the proxes for technologcal regmes, Pavtt s categores, become always postve and sgnfcant at 1%, whle n the Heckman models they were often non sgnfcant. On the contrary, n the effcency models (Table 9a), Pavtt s proxes become all not sgnfcant. The tme dummes are n general very sgnfcant n all models suggestng that the tme dmenson of the panel s actually mportant. 7. Concluson The results that have been reported n ths paper suggest that M&A actvtes have a postve and sgnfcant mpact on nnovaton nvestments made by frms. In partcular, M&As seem to foster nnovaton through the drect channel of R&D resources nvested nsde the frm. In fact, frms that have experenced a M&A do not seem to nvest more than before n R&D performed by thrd partes, whle they do nvest more n nternal R&D actvtes preformed by ther own personnel. Smlarly, M&As performed 3-5 years before have a postve sgnfcant effect on frms total cost for nnovaton. The estmates show that M&As have a sgnfcant role n ncreasng the expenses due to the acquston of new types of machnery or software, the marketng actvtes, and the tranng costs of the R&D personnel. M&As do not sgnfcantly affect the expenses n external knowledge lke the purchase of rghts to use patents, lcenses or other types of knowledge from thrd partes. It could be argued that M&As themselves are means to acqure external knowledge, and therefore, frm post-merger behavour favours the consoldaton of the knowledge that has been acqured by 23