Information Technology Externalities: Vertical and Horizontal Spillovers in Taiwan Industries

Transcription

1 Informaton Technology Externaltes: Vertcal and Horzontal Spllovers n Tawan Industres Dana H.A. Tsa Graduate Insttute of Economcs Natonal Sun Yat-Sen Unversty Kaohsung, Tawan Phone: Emal: danahtsa@gmal.com Chu-Fan Kao Graduate Insttute of Economcs Natonal Sun Yat-Sen Unversty Kaohsung, Tawan Phone: Abstract Ths artcle examnes the adopton of nformaton communcaton technology (ICT) and ts dffuson and network effects. The ICT dffuson s llustrated by vertcal and horzontal spllover effects of ICT usage n the hgh-technology ndustres. The analyss focuses on the mpact of ICT adopton on vertcal and horzontal ntegraton and how does t change the cost of nternal coordnaton, external coordnaton, and producton. Prevous lteratures suggested that the use of ICT s found to be assocated wth substantal decreases n vertcal ntegraton and weak ncreases n dversfcaton. Ths study examnes the emprcal relatonshp between ICT and frm structure and evaluates whether ths structure s consstent wth pror arguments about ICT and coordnaton when explctly consderng ICT network effects. We overvew and dentfy the dynamc perspectves of the ICT network effects. The ICT mpacts, ts network effects, and ts assocated adjustments on ndustry and enterprse are examned and estmated for Tawan hgh-technology ndustres. Keywords: Informaton communcaton technology (ICT); ICT adopton; ICT dffuson; Tawan hgh-technology ndustres 1. Introducton Wth the prolferaton of nformaton and communcatons technologes (ICTs) over the past several decades, ICT dffuson and networks effects have become ncreasngly mportant. ICT dffuson s regarded as supply sde technology dffuson. Network effects, and demand-sde economes of scale more generally, s defned as the ICT network value ncreases n the number of network sze and the number of ts users t serves. 1

2 Informaton and communcatons technologes (ICTs) can also be regarded from two perspectves. Frst, they have played a facltatng role n the process of economc globalzaton. It has acted as a dstance-reducng agent reducng transacton and communcatons costs and ncreasng the effcency of such transactons. The ncreasng enforceablty of cross-border agreements, the convergence n technologcal trajectores across countres, and ncreased cross-border competton have fundamentally affected the way n whch frms are organzed, and have changed the way frms organze ther nnovatve actvty. Second, they have economc sgnfcance as a technology per se. Therefore the use of nformaton technologes has a substantal mpact on the desgn of organzatons. Informaton communcaton technology can affect frm boundares by changng the costs of coordnatng economc actvty wthn and between frms (nternal and external coordnaton). The analyss focuses on the mpact of ICT adopton on vertcal and horzontal ntegraton and how does t change the cost of nternal coordnaton, external coordnaton, and producton. Prevous lteratures suggested that the use of ICT s found to be assocated wth substantal decreases n vertcal ntegraton and weak ncreases n dversfcaton. Ths study examnes the emprcal relatonshp between ICT and frm structure and evaluates whether ths structure s consstent wth pror arguments about ICT and coordnaton when explctly consderng ICT network effects. We stress the role of the "networks of nnovators" (communcaton and nformaton technology) play on R&D and technologcal nnovaton for hgh-technology ndustres. ICTs play an mportant role n facltatng knowledge spllovers and promotng nnovaton. Many lteratures study knowledge spllovers through the proxes of R&D stock and patent counts (Smth, 1999; Chung, 00; Hollanders and Weel, 00; and Tsa, 005). Recently, the focus of knowledge dffuson has been geared toward ICTs and the resultng network effects (Cowan and Jonard, 004; Chen, Lu, and Huang, 004). Kagam and Tsuj (001) fnd rapd advances n ICT n the late-ndustralzng natons by catchng-up more advanced natons through network effects of ICT dffuson. Accordng to Malerba (199), learnng s lnked to dfferent sources of nternal or external knowledge to the frm. Internal learnng s generated drectly from frm actvtes such as R&D. External sources nclude nter-frm knowledge spllovers from supplers or users wthn ndustry. Stolpe (00) proposed three channels of spllover: rent spllovers transmtted through trade n goods, pure knowledge spllovers transmtted through non-market channels, and nnovaton transmtted

3 through organzatonal and collaboratve afflatons. The study apples the dynamc spllover model to buld up the ICT ndcators and to examne the vertcal and horzontal spllovers n Tawan hgh-technology ndustres. The ICT ndcators are bult up by Hedonc Prce Index approach n order to adjust for the qualty dmenson. The ICT network effects are descrbed by how ICT dffuse to upstream and downstream ndustres. And ICT dffuson wll be llustrated by vertcal and horzontal spllover effects of ICT usage n the hgh-technology ndustres. Network effects are defned as ndustral clusterng effects, whch are assumed to operate through knowledge spllovers that may result from actvty levels of supplers, customers, and other frms n an ndustry. In ths study, we focus on how ICT uses contrbute to the knowledge spllovers (vertcal and horzontal spllovers from upstream and downstream ndustres) and the effects of ICT on coordnaton costs. The emprcal work s conducted by usng data from the Tawanese government s ndustral census of technologcal actvtes at the plant level. Snce prevous emprcal studes on ICT suggest that frm-specfc characterstcs have very mportant nfluences, the best way to tackle these problems s to use panel data. Tawan hgh-tech ndustres were chosen snce t has been characterzed by ncreasng nnovaton and nvestment n ICTs, especally the rapd nnovaton n electroncs, computers, materals, and processes whch had marked as the source of the substantal growth. Ths paper nvestgates the relatonshp between knowledge captal dffuson (ncludng R&D, AICT, EICT) and productvty. The rest of paper s organzed as follows: Secton presents theoretcal model and emprcal model. Secton 3 descrbes data sources and the emprcal results. The concluson s presented n secton 4.. The Vertcal and Horzontal Spllovers n the Tawan Hgh-Technology Industres In ths secton, we descrbe the vertcal and horzontal spllovers n Tawan hgh-technology ndustres. The ICT network effects are descrbed by how ICT dffuse to upstream and downstream ndustres. And ICT dffuson wll be llustrated by vertcal and horzontal spllover effects of ICT usage n the hgh-technology ndustres. Network effects are defned as ndustral clusterng effects, whch are assumed to 3

4 operate through knowledge spllovers that may result from actvty levels of supplers, customers, and other frms n an ndustry. In ths study, we focus on how ICT uses contrbute to the knowledge spllovers (vertcal and horzontal spllovers from upstream and downstream ndustres) and the effects of ICT on coordnaton costs. The hgh-technology sector n Tawan s growng rapdly n ts clusterng and ncludes a large contngent of hgh-tech multnatonals and blue-chp local frms. The hgh-technology cluster boasts hgh rates of ndgenous entrepreneurshp, and at the scence park, the technology ndustry conssts of thousands of specalzed and fercely compettve small and medum-szed enterprses as well as a handful of larger producers. Local nsttutons and socal networks support ntense communcatons, nformal collaboraton, and collectve learnng across frm boundares. It s strkng that ndependent accounts of the performance of producers n ths regon stress ther flexblty, speed, and nnovatve capacty relatve to ther leadng compettors. The hgh-technology cluster s based on research and development, warehousng and dstrbuton functons, and manufacturng. Its success s bult on a central locaton, hgh vsblty, a postve hgh-tech mage, good qualty of lfe, a vsonary town councl, good nvestment returns, low operatng costs and a lack of local competton. Its weaknesses are that t has not been bult on a sold foundaton of hgh-technology nfrastructure and lacks hgh-technology dynamsm, renderng ts locatonal advantage somewhat fragle. The Tawan hgh-technology cluster s characterzed by a more fragmented ndustral structure organzed around networks of ncreasngly-specalzed producers. The ndependent enterprses produce all of the components that were once nternalzed wthn a sngle large corporaton. In the semconductor ndustry, for example, ndependent producers specalze n chp desgn, fabrcaton, packagng, testng, as well as dfferent segments of the manufacturng materals equpment sector. A new generaton of frms has n turn emerged n the late 1990s, whch specalzes n provdng ntellectual property n the form of desgn modules rather than the entre chp desgn. Whle hgh-technology entrepreneurs nnovate n ncreasngly- specalzed nche markets, ntense communcatons n turn nsure the speedy, often unantcpated, recombnaton of these specalzed components nto changng end-products. Unlke Japan and Korea, whch are domnated by large enterprses, the majorty of Tawan s enterprses are relatvely small and medum szed. They cannot afford long-term, enormous R&D expendtures for hgh technology. Thus, only the government can fund poneer research, technology transfer and dffuson, 4

5 nfrastructure buld-up, and provde nvestment ncentves. Government nvolvement s very mportant n Tawan: start up fnancng, ITC, deprecaton allowance, specal tax treatments, etc. Tawan s government has employed a strategy to support non-proft R&D nsttutes to develop technology and then dssemnate the results to ndustry. The msson of the government-supported R&D nsttutes s to ad ndustral growth va technologcal development. (Chang, Hsu and Tsa, 1999; Lu, 1993) In facng these technologcal bottleneck challenges, Tawan s government blueprnts ts country as the Green Slcon Island and promotes Tawan hgh-technology ndustres as a well-known, hgh-tech pvot n the world. Tawan seeks to be a hgh value-added manufacturng center coupled wth an outwardly buldng up of sx support systems: the nnovaton R&D framework, venture captal nvestment system, supply chan management network, hgh-technology collectve captal mechansm, nternatonal fnancal value-added servce system, and warehousng transshpment nucleus. At the same tme, the goal s to buld up more hgh technology clusters lke Hsnchu Scence-based Industral Park wth government nvestment ncentves and coordnaton support. The core hgh-technology ndustral cluster s our target ndustres whch nclude the semconductor ndustry as the upstream ndustry and computer and perpheral equpment ndustry, communcaton equpment ndustry, and consumpton electrc parts ndustry as downstream ndustres. From <Graph 1>, we show how Tawan hgh-technology ndustres rely on the nter-dependences of the upstream and downstream ndustres. In addton to the purely spatal dmenson of ndustral clusterng, thck market lnkages mght arse from proxmty to supplyng or demandng sectors, both n the own- and upstream and downstream ndustres, whch s smlar n sprt to the agglomeraton effects n Bartlesman, Caballero and Lyons (1994) and Morrson and Sgel (1999). The actvty measures may be expressed n terms of nput or output levels of the drect supplyng/demandng sectors, or weghted averages of a varety of sectors. Accordng to the Input-Output Tables 1999 from the Drectorate General of Budget Accountng and Statstcs Executve Yuan, we buld up the upstream-downstream ndustres correlaton for Tawan hgh-technology ndustres n <Graph 1>. In the graph, every crcle represents an ndustry sector; and the number n the crcle s the rato of self-usage to total producton for the ndustry. For Semconductor ndustry, for producng one unt of product needs 0.33 nputs from ts own ndustry. The drecton of the arrows ndcates the requred nput ratos from one 5

6 ndustry to the other. For Tawan hgh-technology ndustres, the core hgh-technology ndustral clusters (as shown n the shaded area n Graph 1) that tags semconductors ndustry as the upstream ndustry and the downstream ndustres nclude computer and perpheral equpment ndustry, communcaton equpment ndustry, and consumpton electrc parts ndustry. The other related upstream ndustres for the core hgh-technology ndustral clusters nclude: Non-metallc Mneral Products Manufacturng; Machnery; Fabrcated Metal Products Manufacturng; Iron; Electrcal Machnery and Other Electrc Power Supply; Other Metal; Chemcal Materal; and Plastc Products Industres. And the related downstream ndustres for the core hgh-technology ndustral cluster are: Electrc Power; Servces of Industry and Busness; Merchandse tradng; Transportaton, Storage and Communcaton; Other Manufacturng Products; and Fnance and Insurance Servces Industres. 6

7 <Graph 1> The Upstream-Downstream Industres Correlaton wth Tawan Hgh-technology Industres 7

8 3. Model and Methodology ln Y LKNO Assume the frm s producton process s descrbed by followng producton functon: Y = F( K, L, KNO) (1) where Y s output, K, L, KNO, are physcal captal, labor and knowledge captal. The Translog producton functon s gven by = α + α ln K 0 ln L K ln KNO + α ln L L + 1/ β + α KK KNO (ln K ln KNO ) + 1/ β LL KL ln K (ln L ) ln L + 1/ β KKNO KNOKNO The knowledge producton functon s constructed as follows. ln K ln KNO (ln KNO ) () KNO = F( RD, AICT, EICT) (3) where R&D, AICT, EICT, are research and development stock, automaton captal stock ndex, and electronc system ndex respectvely. Equaton () can be rewrtten as: lny + η S 0 LS1 S1 S EICTS + 1/ β = α + α ln K KAICT ln S RDAICT ln K ln RD ln AICT ln L ln S ln S ln AICT 1 1 ln S ln K ln EICT ln S EICTEICT KL ln L + γ ln RD + φ ln AICT + ω ln EICT + ρ ln L RDS1 KS + 1/ β ln RD ln S ln K (lneict) + 1/ β LAICT ln K ln L ln AICT RDEICT KRD KK ln RD ln EICT ln S 1 (lns S1 S1 ln RD AICTS1 LS ) + 1/ β 1 ln K ln AICT ln S ln L ln S ln L ln RD S S 1 (lns RDS (lnk ) + 1/ β (lnl ) + 1/ β KEICT LL LRD AICTEICT ) S1 ln EICT ln S EICTS1 1 ln AICT ln EICT ln RD ln S RDRD LEICT ln L ln EICT KS1 ln EICT ln S ln K 1 AICTS (lnrd ) + 1/ β ln S 1 ln AICT ln S AICTAICT (ln AICT) where S 1 present the ntra-ndustry spllover of R&D, AICT, EICT, S present the nter-ndustry spllover of R&D, AICT, EICT ndvdually. 1 (4) Based on Tsa and Ln (005), the total factor productvty (TFP) growth equaton s modfed to ncorporate R&D, AICT, EICT effects and the resultng spllover effects through ntermedate goods and other frm s R&D, AICT, EICT nvestments. 1 The ntra-ndustry spllovers same ndustry. The nter-ndustry spllover ndustres. S 1, = θ 1 j, t j S, = θ j, t j S 1,* are proxed by accumulated R&D, AICT, EICT from other frms n the The sgn denotes the knowledge stock of R&D, AICT, EICT, respectvely. producton coeffcents. S,* are proxed by accumulated R&D, AICT, EICT from other The sgn θ s ndcate weghts of 8

9 TFP RD = γ + ρ TFP RD (5) S1RD S RD AICT S1AICT S AICT EICT S1EICT S1RD + η S RD + φ + ρ S1AICT + η S AICT + ω + ρ S1EICT + η S EICT S1RD S RD AICT S1AICT S AICT EICT S1EICT S EICT S EICT The degree of the extent of vertcal and horzontal ntegraton s then measured by the vertcal ntegraton (VIC) and dversfcaton (DIV) measures. Montgomery (1994) ndcates the hgher a frm s market power, the hgher ts degree of dversfcaton. Follow Htt (1999), we defne the dversfcaton ndex (DIV) by the share of frm employment n the ndustry. DIV = N N = 1 j= 1 α α ω (6) j j where, j =1,, N, N s the number of 4-dgt ndustres a frm partcpates n α s the share of ndustry n the frms total employment ω j s a weghtng functon: 0 f the ndustres share the same 3-dgt SICs 1 f the ndustres have dfferent 3-dgt SICs but the same -dgt SIC f the ndustres have dfferent -dgt SICs The vertcal ntegraton ndex (VIC) represents the correlaton strength of nput and output between ndustres. VIC, constructed by Maddgan (1981), s hgher when the nput and output matrx data n the IO table s hgher. For example, the VIC values are qute hgh n the car manufacturng ndustry and the steel ndustry. The VIC s bult up from the nput and output matrx data. The VIC for frm k s defned 1 VIC k = 1 (7) = N T T ( C ) ( C )( D ) ( D ) = 1 where N s the number of ndustres n whch frm k operates; C ndcates the column of frm k s nput matrx; D ndcates row of frm k s output matrx; ICT affects frm structure by changng the degree of the vertcal ntegraton and dversfcaton, and thus s examned by the followng equatons. V = 0 ε (8) V V V V V λ + λaict AICT + λeict EICT + λsaict SAICT + λseict SEICT + V Data are from Statstcs Bureau of DGBAS. 9

10 D = 0 ε (9) D D D D D λ + λaict AICT + λeicteict + λsaictsaict + λseictseict + where V ndcates the vertcal ntegraton ndex D represents the dversfcaton ndex AICT s Automaton captal stock ndex EICT s Electronc system ndex SAICT denotes the AICT spllover SEICT denotes the EICT spllover D 4. The Emprcal Implementaton All nferences n ths paper are based on data drawn from the Tawan Industral Census of Technologcal Actvtes at the Mcro Level and the Tawan Automaton and Electronc Survey, both survey publshed by Mnstry of Economc Affars (MOEA) of the Government of the Republc of Chna. The emprcal work s conducted for plant level data of the three-dgt Tawan hgh-technology ndustres 3, The three-dgt hgh-technology ndustres nclude 9 SIC ndustres: Electrcal machnery (SIC311); Electrcal applance and household applances (SIC31); Lghtng equpment manufacturng (SIC313); Data storage perpheral equpments (SIC314); Audo and vdeo equpments (SIC315); Communcaton equpment and apparatus (SIC316); Electronc components and accessores (SIC317); Batteres (SIC318); and Other electrc and electronc machnery and equpment (SIC319). Three ndustres, SIC314, SIC316, and SIC318, are dropped because there are few samples The contrbuton of R&D, AICT, EICT on TFP growth The emprcal mplementaton s conducted by GMM (generalzed method of moments) estmaton, we found R&D stock, AICT, and EICT are postve and statstcally sgnfcant contrbuted to TFP growth (shown n Table 9). The coeffcent of R&D stock elastcty on TFP growth s 0.475, compared to the smlar results n Chung and Tsu (1999) and Yang and Chen (00). The contrbuton of the automaton ICT (AICT) on TFP growth s also postve sgnfcant at the 5% statstcal level wth the coeffcent of AICT elastcty The contrbuton s hgher compared to Chen, Huang and Lu (00) that they found the elastcty 3 The defnton of hgh-tech ndustry n ths paper s based on Tsa and Chen (00) and Young (00) to defne three-dgt electronc ndustres as hgh-technology ndustry. 4 The data sources and varable specfcaton are the same specfcaton and detaled n Tsa and Chang (006). 10

11 of IT captal s for Tawan manufacturng ndustry. The electronc ICT (EICT) ndcator also shows hgher contrbuton on TFP growth (wth the coeffcent of EICT 0.573) than the results n Chen, Huang and Lu (00). The emprcal results provde evdence that Tawan hgh-technology ndustres nvest more electronc ICTs than n the whole manufacturng ndustres, and thus have better productvty performance. Table 1 Total Factor Productvty (base year: 1998 = 100) SIC ndustry Year 1999 Year 000 Year 001 Industry clssfcaton Sample Mean Std Dev Mean Std Dev Mean Std Dev Electrcal machnery Electrcal applance and household applances Lghtng equpment manufacturng Audo and vdeo equpments Electronc components and accessores Other electrc and electronc machnery and equpment Table The Impacts of R&D, AICT, EICT on TFP Growth Varable Coeffcent Standard Error P-value RD 0.475* AICT 0.446* EICT 0.573* Note: 1. * represent sgnfcant at the 5% level.. N=333 R-squared = The contrbuton of R&D, AICT, EICT spllovers on TFP growth The nter-ndustry knowledge spllovers are prmarly from the accumulated knowledge 11

12 captal of R&D, AICT, EICT n other upstream and downstream ndustres The spllovers from external sources can be generated ether through the purchase of goods and servces or by adoptng the scentfc knowledge from other sectors. The ntra-ndustry spllovers are prmarly from the accumulated knowledge n other plants wthn the ndustry. The relatonshp of spllover effects of R&D, AICT, EICT on TFP growth are derved from equaton (7). Table 3 presents the nter-ndustry and ntra-ndustry R&D, AICT, EICT spllover effects on TFP n the three-dgt Tawan electronc ndustres. We found nter-ndustry spllovers of R&D, AICT and EICT all show postve and statstcally sgnfcant effects on TFP for both SME and large plants 5. It mples technologcal knowledge of one ndustry does not exclude the usage by other ndustres due to the publc goods characterstcs of knowledge. The emprcal evdence can be found also n Chung and Tsu (1999) and Chen, Huang and Lu (004) for Tawan manufacturng ndustres. The mpact of ntra-ndustry knowledge spllovers reflects qute ambguous results. In SME plants, ntra-ndustry spllover effect of EICT captal s negatvely contrbuted to TFP growth, though knowledge spllovers from R&D show postve mpacts on TFP growth. In large plants, except negatve ntra-ndustry spllover effects of R&D, knowledge spllover effects from EICT show postve mpacts on TFP growth. The ntra-ndustry AICT spllover effects are not sgnfcant n both SME plants and large plants. One explanaton for the dfferent spllover effect can be attrbuted to the dfferent ndustry structures. The total spllovers effects wll depend on the mutual nfluence from varous sources of knowledge captals and the assocated spllover effects. Accordng to Grllches (1979), the exstence of negatve spllover effects mght reflect that there s hghly substtutable between hgh technology ndustry or the knowledge captals wthn the ndustry and the products. When an ndustry devoted to nvestment n knowledge captals, knowledge captals of other ndustres may be replaced that led to the declne producton of knowledge captals n other ndustres. We also observe the nter-ndustry R&D spllovers acts as substtutes for the own R&D captal n SME plants, and complements for the own R&D captal n large plants. The postve R&D contrbuton to TFP growth n large plants s qute sgnfcant that they have more motvaton n devotng to R&D than n SME plants. And the free rder property explans why own R&D n SME s negatve contrbuton to TFP. Accordng to Bernsten (1988), the 5 We also dvded the dataset nto two sub-groups, small-medum (SME) plants (wth the employment equal or less than 50) and large plants (wth the employment larger than 50). 1

13 nter-ndustry spllovers lower the unt producton costs and t also create ncentves for frms to free rde on the efforts of other ndustres by reducng ts own R&D nvestment. In summary, the nter-ndustry R&D, AICT and EICT spllovers have greater contrbutons to TFP growth than ntra-ndustry R&D, AICT and EICT spllovers. And the mpacts are more sgnfcant n Tawan hgh-technology SME plants than n large plants. Ths s due to the fact that most Tawanese hgh-technology plants are of small-medum szes. Also accordng to Remeo (1975), the smaller frms may have knowledge dffuson faster because of the relatvely qucker decson-makng process wthn the frm. 4.3 Vertcal ntegraton and dversfcaton measures of AICT and EICT The dversfcaton ndex and vertcal ntegraton ndex are derved from equaton (5) and (6). Table 5 shows the relatonshp between dversfcaton ndex and AICT, AICT spllovers, EICT, EICT spllovers. AICT and EICT all have postve and statstcally sgnfcant effects related to dversfcaton. In other words, ncreasng usage of AICT and EICT wll ncrease the degree of dversfcaton. Ths s consstent wth the trend estmated by Gollop and Monahan (1991) that the dversfcaton amont establshments for US manufacturng ndustres has ncreased form 0.39 to over the perod. We also observe that AICT spllovers have negatve and statstcally sgnfcant mpacts related to dversfcaton. It could be because the AICT spllovers may reduce the market power, and hence resultng decreases n dversfcaton. Table 15 shows the relatonshp between vertcal ntegraton and AICT, AICT spllovers, EICT, EICT spllovers, whch are derved from equaton (3..1). There are negatve effects of AICT, AICT spllovers, EICT, and EICT spllovers contrbutng to vertcal ntegraton. That means ncreased usage of EICT and through spllover effect wll decrease n the degree n vertcal ntegraton of frms. We emprcally proved that hghly usage of IT s assocated wth substantal decreases n the degree of vertcal ntegraton and also lower the degree of dversfcaton, proposed frst by Htt (1999). 13

14 Table 3 The Spllover Effect of R&D, AICT, EICT on TFP Varable Coeffcent Standard Error P-value ID=1 (Labor < = 50) RD -0.07* Intra-ndustry Inter-ndustry 1.694* AICT Intra-ndustry Inter-ndustry 1.676* ECIT 6.589* Intra-ndustry * Inter-ndustry 0.55* ID= (Labor > 50) RD 5.885* Intra-ndustry -5.41* Inter-ndustry 4.351* AICT Intra-ndustry Inter-ndustry * ECIT Intra-ndustry Inter-ndustry 1.583* Note: 1. * represents sgnfcant at the 5% level.. N=333 (ncludes 19 SME plants and 114 large plants) 3. R-squared =

15 Table 4 DIV (the dversfcaton measures ndex) SIC ndustry Year1999 Year000 Year Table 5 VIC (the vertcal ndustry connecton ndex) SIC ndustry Year1999 Year000 Year Table 6 Dversfcaton and AICT, SAICT, EICT, SEICT Varable Coeffcent Standard Error P-value λ 7.469* AICT 0.4* SAICT * EICT 0.05* SEICT Note: * represent sgnfcant at the 5% level. R-squared =

16 Table 7 Vertcal Integraton and AICT, SAICT, EICT, SEICT Varable Coeffcent Standard Error P-value λ 6.015* AICT SAICT -.677* EICT * 0.514E SEICT -.31* Note: * represent sgnfcant at the 5% level. R-squared = Concluson In ths paper, we overvew and dentfy the dynamc perspectves of the ICT network effects. The dynamc perspectves of the ICT ndcators nclude the noton of an nformaton economy characterzed by the growth pattern of contemporary economes. The dynamc perspectves of ICT and ts network effects are examned and how ICT stocks and assocated spllovers contrbute to TFP are estmated for Tawan hgh-technology ndustres. The major fndngs are as follow: Frst, TFP grows faster n Audo and Vdeo Equpments Industry (SIC 315) than others hgh technology ndustres. Second, R&D, AICT, EICT have postve and statstcally sgnfcant contrbuton to TFP growth. Thrdly, for SME plants, we found nter-ndustry spllovers n R&D, AICT, EICT have postve and statstcally sgnfcant effects on TFP growth, however, there exst negatve ntra-ndustry EICT spllovers effects. Fourthly, for large plants the nter-ndustry spllover effects of R&D, AICT, EICT are postve, however, the ntra-ndustry spllover effects of R&D are negatve on TFP growth. Ffthly, the nter-ndustry R&D, AICT, EICT spllovers have greater contrbuton to TFP growth than the ntra-ndustry R&D, AICT, EICT spllovers. Sxthly, we observe the nter-ndustry R&D spllovers are substtutes for the own R&D captal n SME plants, and complements for the own R&D captal n large plants. Seventhly, the AICT and EICT have postve and statstcally sgnfcant mpacts on the degree of dversfcaton. And there are negatve effects of AICT spllovers and EICT spllovers on the degree of vertcal ntegraton ACKNOWLEDGMENT The research was supported by Tawan Natonal Scence Councl H and 16

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