Subcontracting Structure and Productivity in the Japanese Software Industry

Transcription

1 Rev Soconetwork Strat (2009) 3:51-65 Subcontractng Structure and Productvty n e Japanese Software Industry Kazunor MINETAKI 1) and Kazuyuk MOTOHASHI 2) 1) The Research Insttute for Soconetwork Strateges, Kansa Unversty Yamate-cho, Suta, Osaka , Japan 2) School of Engneerng, The Unversty of Tokyo Hongo, Bunkyo-ku, Tokyo , Japan mnetak@rcss.kansa-u.ac.jp motohash@tm.t.u-tokyo.ac.jp http// Receved: 9 March 2009 / Accepted: 28 July 2009 Sprnger 2009 Abstract. Ths paper presents an emprcal analyss of e factors determnng e productvty of e software ndustry n Japan, usng ndvdual data from e Survey of e State of e Informaton Servce Industry conducted n August 2006 by IPA (Informaton-Technology Promoton Agency, Japan). Ths paper focuses on e relatonshp between e subcontractng structure and productvty n e Japanese software ndustry. Software enterprses are classfed as prme contractors, ntermedate subcontractors, end-contractors, and ndependent enterprse. A comparson of er productvty levels reveals at ntermedate subcontractors are e least productve. However, t s observed at e ntermedate subcontractors possessng a hgh qualty of human resources measured e proporton of employees passng e Informaton Technology Engneers Examnaton (ITEE), or e ntermedate subcontractors adoptng e IT skll standard whch defnes e sklls for IT human resources clearly and systematcally, has a hgh productvty level. It can rase e productvty n software ndustry as a whole. Keywords: Software, Subcontractng structure, Productvty, Informaton Technology Engneers Examnaton (ITEE), IT skll standard. 1 Introducton In order to boost e potental grow rate of e Japanese economy, e productvty of e servce ndustry must be ncreased. In ts current state, e rate at productvty s ncreasng n Japan's servce ndustry s low consderng nternatonal trends, despte e hgh mportance of e servce ndustry. The servce ndustry accounts for a hgh share of bo GDP and of employment n comparson to e manufacturng

2 52 Rev Soconetwork Strat (2009) 3:51-65 ndustry. The trend of movng towards a servce economy s not lmted to Japan, and s also occurrng n each of e OECD countres. The share whch s 45-55% of GDP occuped by e servce market n 2001 had ncreased by 10% w respect to 1980 n e OECD countres. The servce ndustry does not only have a hgh share, t s also mportant from e perspectve of nnovaton. The servce ndustry ncludes many knowledge-based felds such as healcare, educaton and consultng. Software enterprses are an archetypcal example of knowledge-based servce enterprses w a hgh potental for productvty ncrease rough nnovaton. The demand for software s ncreasng dramatcally due to e advance of IT roughout e economy as a whole, and ere are hgh expectatons at e software ndustry, w ts ncreasng productvty supported by advances n software engneerng and an accumulaton of software development tools, wll draw up e productvty of e Japanese economy at a macroscopc level. However, when e speed of nnovaton n e software ndustry s compared w at of e IT hardware ndustry, t s laggng behnd. Hardware for computers and communcatons devces are supported by Moore's law of semconductor ntegrated crcuts, and technologcal nnovaton s advancng at a remarkable speed. For software on e oer hand, despte e fact at development envronments are mprovng rough development tools such as CASE (Computer Aded Software Engneerng) and e appearance of programmng languages, whch are closer to natural languages, productvty s strongly colored by a labor-ntensve aspect at hnges upon e abltes of software programmers. It s erefore ought at e grow n productvty s slack n comparson to e remarkable advance of producton technologes n IT hardware. The compettve standng of e software ndustry n Japan s notably low n terms of trade statstcs, and ts productvty s consdered low n comparson to at of Europe and e Unted States (Ima and Ishno [1]). It s ought at s may be caused by a low rato of package software for whch e mert of scale begns to functon and a hgh proporton of software orders whch necesstate responses to ndvdual clents (Tanaka [2], Motohash [3]). It s also ought at e fact at many of e software enterprses are medum- to small- szed enterprses w a low productvty, and e mult-tered market structure composed of large enterprses actng as prme contractors and enterprses actng as end-contractors bear an nfluence. Ths paper presents an emprcal analyss of e productvty of e software ndustry n Japan and ts market structure usng ndvdual data from e Survey of e State of e Informaton Servce Industry conducted by IPA (Informaton-Technology Promoton Agency, Japan). Productvty was compared w respect to e types of software enterprses n e mult-tered trade structure of prme contractors and subcontractors, and e causes of e low productvty of e software ndustry tself were nvestgated. The qualty of human resources s also an mportant factor n software productvty, and an analyss of ts relatonshp to productvty was also conducted. The remander of s paper s organzed as follows. Frst, Secton 2 summarzes e prevous related lteratures. In Secton 3, e data used n s research s descrbed, and enterprses are classfed by type accordng to e trade patterns n e

3 Rev Soconetwork Strat (2009) 3: software ndustry, and descrptve statstcs are presented. In Secton 4, e framework for productvty analyss s presented and estmaton results are reported. Secton 5 concludes. 2 Prevous Lterature We summarze e prevous studes related w e quanttatve analyss n e Japanese software ndustry. There are several databases concernng about e software ndustry. The Survey of Selected Servces Industres of whch e busness categores are software and nformaton servce by METI (Mnstry of Economy, Trade, and Industry), and Survey of e State of e Informaton Servce Industry by IPA are famous. But ose databases nclude software ndustry and also nformaton servce ndustry. There are many enterprses whch have bo e software sector and e oer nformaton servce sector ncludng nternet and nformaton processng, so bo ndustres are generally researched togeer. For estmaton, most prevous studes control e dfference between e software sector and e oer nformaton servce sector. Shntan [4], Nshmura and Mnetak [5], and Mnetak and Motohash [6] conduct e emprcal studes by usng e database of 'The Survey of Selected Servces Industres'. Shntan [4] analyzes e labor productvty of e software and nformaton servce enterprses each year separately by usng CES (Constant Elastcty of Substtuton) type producton functon whch uses e number of system engneer to total employees, e number of programmer to total employees, and e number of researcher to total employees to represent e qualty of labor. Man result s at e number of system engneer to total employees has e stronger tendency to brng e postve effect on e technologcal progress compared w types of labor. Nshmura and Mnetak [5] analyzes TFP (Total Factor Productvty) of e software and nformaton servce enterprses by usng panel data from It shows at because e outsourcng of developng software s not effcently operated, e nformaton servce ndustry has run nto an exacerbated state of low productvty. And accordng to Nshmura and Mnetak [5], e number of system engneer to total employees has e postve effect on TFP. Mnetak and Motohash [6] 1 analyzes TFP of e software enterprses manly 2 by usng panel data from 2000 to Mnetak and Motohash [6] classfes software enterprses as prme contractors, ntermedate subcontractors, end-contractors, and ndependent enterprse by usng e measurement of outsourcng expense rato and 1 Ths paper uses e cross sectonal data of Survey of e State of e Informaton Servce Industry IPA. On e oer hand, Mnetak and Motohash [6] uses e panel data of Survey of Selected Servces Industres of whch e busness categores are software and nformaton servce by METI. 2 Mnetak and Motohash [6] targets e enterprses of whch software busness share of sales s hgher over 80%.

4 54 Rev Soconetwork Strat (2009) 3:51-65 ntra-ndustry sales rato. The partcularty of Mnetak and Motohash [6] s to nvestgate e relatonshp between TFP and patent or R&D nvestment n each classfed software enterprses. Also Mnetak and Motohash [6] nvestgates e relatonshp between TFP and e labor qualty measured by e type of labor whch are e number of system engneer to total employee and e number of programmer to total employee. As e emprcal study results, Mnetak and Motohash [6] concludes at for e prme contractors, e nnovatve actvty of patent and R&D nvestment s e most mportant, and for e ndependent enterprse, e qualty of labor s e most mportant to determne TFP. Hromatsu, et al. [7] develops er orgnal database 3 from 1994 to Hromatsu, et al. [7] clarfes e source of compettve edge of nformaton servces enterprse by emprcal analyses of at ose management resources effect on value added from e vewpont of sale economy by usng translog type cost functon and SEM (Structural Equaton Modelng). Hromatsu, et al. [7] concludes at busness model, human resources whch have rch talents and technology measured by e proporton of employees qualfed w e advanced IT certfcaton and e rato of researcher to total employees, and outsourcng are closely related to scale economes, and e most mportant management resource. Ths paper nvestgates e relatonshp between e subcontractng structure and productvty as same as Mnetak and Motohash [6] because we nk e subcontractng structure s e partcularty n e Japanese software ndustry. We use e rato of outsourcng cost to total cost when classfyng software enterprses, and erefore our study s related to Nshmura and Mnetak [5] and Hromatsu, et al. [7]. Also we share e vew at e labor qualtes have e effect on e productvty, w Shntan [4], Nshmura and Mnetak [5], and Hromatsu, et al. [7]. 3 Overvew of e Data and Classfcaton of Software Enterprses In s secton, we overvew our data set and we classfes e software enterprses. The purpose of usng Survey of e State of e Informaton Servce Industry s at we can study emprcally e relatonshp between e IT skll whch employees hold and e productvty n e Japanese software ndustry. 4 In order to grasp e state of trade n software enterprses, Survey of e State of e Informaton Servce Industry s conducted every year. The research descrbed n s paper used e enterprse data from e '28 Survey' conducted n August Ths survey targets e nformaton servce ndustry ncludng custom software, prepackaged software, nternet related feld, nformaton processng and oer nformaton servces. The tems n s survey ncludes are fnancal accounts and 3 Hromatsu,et al. [7] ntegrates e fnancal database of each enterprse and nformaton servce enterprse regster. 4 Because e data of usng n s paper s e cross sectonal data, we can not strctly treat e causal relatonshp and so we nvestgate e correlaton n s paper.

5 Rev Soconetwork Strat (2009) 3: revenue statement, state of loans, employment, The Informaton Technology Engneers Examnaton and e IT skll standards. For e enterprse targeted by e survey, 861 busnesses provded vald responses (581 software busnesses, and 280 busnesses provdng IT servces), and e rato of vald respondents was 21.5%. We classfy e enterprses nto four enterprse groups accordng to two ndcators of e outsourcng cost rato (e proporton of total cost occuped by outsourcng cost), and e ntra-ndustry sales rato (e proporton of sales whch contrbute to e sales wn e nformaton servce ndustry as a whole). 5 Enterprses were dentfed as havng above or below average outsourcng cost ratos and ntra-ndustry sales ratos, and classfed nto e four groups shown n Table 1. Enterprses w a hgh outsourcng cost rato and a low ntra-ndustry sales rato were consdered to be large enterprse prme contractors. Large enterprse prme contractors are located at e top of e pyramdal structure of ndustral organzatons, because ey tend to have a hgh proporton of sales outsde e software ndustry, whle emselves largely outsourcng to subcontractors. Enterprses w a hgh outsourcng cost rato and a hgh ntra-ndustry sales rato are consdered to be ntermedate subcontractors. It was ought at ey tend to receve orders from prme contractors whle emselves subcontractng. Enterprses w a low outsourcng cost rato and a hgh ntra-ndustry sales rato are consdered to be end-contractors, because er low outsourcng cost rato ndcates at ey do not place orders w enterprses benea em, whle er hgh ntra-ndustry sales rato ndcates at er sales are largely for ntermedate subcontractors. Table 1. Classfcaton of enterprses n software ndustry Above average outsourcng cost rato Below average outsourcng cost rato Above average ntra-ndustry sales rato ntermedate subcontractors end-contractors Below average ntra-ndustry sales rato prme contractors ndependent enterprses 5 Our classfcaton of e enterprses was verfed by e 29 Survey of e State of e Informaton Servce Industry conducted n 2007 by IPA.

6 56 Rev Soconetwork Strat (2009) 3:51-65 Table 2. Descrptve statstcs Total prme ntermedate ndependent end-contractors contractors subcontractors enterprses Value Added Physcal fxed assets Software assets Number of employees Labor productvty Outsourcng cost rato Intra-ndustry sales rato Custom Software sales rato Software product sales rato Software sales rato Employees passng e Informaton Technology Engneers Examnaton rato Rato of enterprses adoptng e IT skll standard Number of enterprses whch have Partnershps w computer maker Number of enterprses whch have Partnershps w computer user Number of enterprses (Note) Value Added, Physcal fxed assets, and Software assets are shown at 100 mllon yen respectvely. Labor productvty s shown at yen per man hour. Last, enterprses w bo a low outsourcng cost rato and a low ntra-ndustry sales rato are consdered to be ndependent enterprses w no dependence on enterprses n e same ndustry. Table 2 summarzes e characterstcs of each of e groups n s classfcaton of software enterprses, showng er value added, physcal fxed assets, software assets, number of employees, labor productvty 6, outsourcng cost rato (e proporton of total cost occuped by outsourcng cost), ntra-ndustry sales rato (e proporton of total sales whch contrbute to e sales of e IT servce ndustry), custom software sales rato (custom software sales to total sales), software product sales rato (software product sales to total sales), and employees passng e Informaton Technology Engneers Examnaton (ITEE) to total employee. Insofar as can be seen from descrptve basc statstcs, one result s at e labor productvty of e prme contractor group s e hghest. The value added, physcal fxed assets and number of employees are also overwhelmngly hgh for s group of enterprses. Next, n e ndependent enterprses e labor productvty s relatvely hgh. The custom software sales rato s e hghest for e ntermedate subcontractor group. The pyramdal structure of ndustral organzatons s a phenomenon often 6 Ths s obtaned by dvdng e value added by e labor nput (number of employees multpled workng tme).

7 Rev Soconetwork Strat (2009) 3: observed w custom software. In partcular, e rato of custom software sales s e hghest for e enterprses n e ntermedate subcontractor group. Subcontractng downstream s a characterstc of software development n Japan, partcularly for custom software. The proxy for e labor qualty s e rato of employees passng ITEE whch s a natonal examnaton under METI. The rato of employees passng e ITEE to total employees s comparatvely hgher for e enterprses n e prme contractor group and n e ntermedate subcontractor group. Also proxy for e labor qualty s e rato of enterprses adoptng e IT skll standard. It defnes e sklls for IT human resources clearly and systematcally. Ths rato s e hghest for e enterprses n e prme contractor group. 4 Framework for Productvty Analyss and Analytcal Results 4.1 Analytcal framework To obtan e robust estmaton result, we use bo e Cobb-Douglas producton functon and TFP, as e framework for analyzng e productvty of software enterprses. In e case of e Cobb-Douglas producton functon, e dependant varable s e labor productvty whch s e amount of value added per man hour. Explanatory varables are, frst, e captal labor rato (e amount of captal stock per man hour). We have two types of e captal labor rato for physcal fxed assets and for software assets. Secondly, e labor qualty s explanatory varable. We use e rato of employees passng ITEE to total employees for e proxy for e labor qualty. Thrdly, we use e dummy varables for busness partnershp w computer maker and w computer user. Fourly, we use e rato of software sales to control e dfference between e software sector and e oer nformaton servce sector. The specfc formulaton s as follows. Y K K 2, 1, ln ln ln + labor _ qualty L = α + L L β λ + θ dummy _ for _ partnershp + δ rato _ software + cons. + ε. (1) In equaton (1), e varables are defned as follows: Y =Value added of e enterprse, K 1, = Captal stock (physcal fxed assets) of e enterprse, K 2, =Captal stock (software assets) of e enterprse, L =Labor nput (number of employees multpled workng) of e Labor _ qualty =Varable representng human captal, enterprse,

8 58 Rev Soconetwork Strat (2009) 3:51-65 dummy _ for _ partnershp = Dummy varables for partnershps w computer maker or computer user 7, rato _ software =Rato of software sales to total sales, ε = error term. The assumpton of Cobb-Douglas producton functon at e margnal substtuton of nputs s 1 s strct, and so we try to use TFP where e contrbutons of nputs of captal stocks and labor are controlled. TFP ln TFP Y = ln Y 1 X j j j ln. (2) = K, K, L 2 X 1 2 j j ( s + s ) In equaton (2), e varables are defned as follows: TFP =TFP level of e enterprse, TFP = TFP level of e average enterprse, Y =Value added of e enterprse, Y = Value added of e average enterprse, s = Cost share of e j nput of e enterprse, j s = Cost share of e nput of e average enterprse, j j X = The j nput of e enterprse, j X = The j j nput of e average enterprse. We defne TFP level by usng equaton (2), and estmate TFP level as follow as equaton (3). ( TFP ) = λ labor _ qualty + θ dummy for _ ln _ partnershp + δ rato _ software + cons. + μ. (3) The notatons of varables are e same as equatons (1), (2), and μ s e error term. The estmaton meod s bascally OLS, but we perform e Breusch-Pagan test for heteroskedastcty. In e case at Breusch-Pagan test shows e heteroskedastcty, we use e Huber-Whte-sandwch estmator of varance. 7 Dummy for partnershps w computer maker s 1 f e software company belong to e computer maker, oerwse 0. Dummy for partnershps w computer user s 1 f e software company belong to e computer user, oerwse 0.

9 Rev Soconetwork Strat (2009) 3: Estmaton results The estmaton results are shown n Tables 3-6. Tables 3 and 4 are e results of usng e rato of employees passng ITEE where we estmate equaton (1) of Cobb- Douglas producton functon n Table 3, and we estmate equaton (3) of TFP n Table 4. Also Tables 5 and 6 are e results of usng e IT skll standard where we estmate equaton (1) of Cobb-Douglas producton functon n Table 5, and we estmate equaton (3) of TFP n Table 6. There are fve cases of results n each table. Frst s e total case. Second s e case of prme contractors. Thrd s e case of ntermedate subcontractors. Four s e case of end-contractors. Ff s e case of ndependent enterprses. We manly focus on e sgnfcance of labor qualty measured by e rato of employees passng e Informaton Technology Engneers Examnaton (ITEE) n Tables 3 and 4. The labor qualty s not sgnfcant statstcally n e total case. Wn e classfcaton of enterprses, e only case of ntermedate subcontractors can show e postve correlaton between e labor qualty and productvty whch s statstcally sgnfcant at 1% level n e case of usng Cobb-Douglas producton functon shown n Table 3, and also s statstcally sgnfcant at 5% level n e case of usng TFP shown n Table 4. Next, we use e rato of enterprses adoptng e IT skll standard whch s anoer proxy for labor qualty. The estmaton results are shown n Tables 5 and 6. The labor qualty has e postve correlaton w e productvty n e case of ntermedate subcontractors. Table 5 shows e results of Cobb-Douglas producton functon whch s 5% level sgnfcant, and Table 6 shows e results of TFP whch s 10% level sgnfcant. Oer cases except for ntermedate subcontractors are not sgnfcant statstcally. Our estmaton results are concluded at e labor qualty whch s measured by bo e rato of employees passng ITEE and e rato of enterprses adoptng e IT skll standard, can have e correlaton w e productvty n ntermedate subcontractors of e software ndustry.

10 60 Rev Soconetwork Strat (2009) 3:51-65 Table 3. Estmaton results (case of usng e rato of employees passng ITEE) Cobb-Douglas producton functon Total Prme contractors coeffcent S.E. coeffcent S.E. captal labor rato(physcal fxed assets) *** captal labor rato(software assets) *** *** qualty of labor dummy for partnershps w computer maker *** dummy for partnershps w computer user *** software sales rato * constant *** *** number of observatons Breusch-Pagan Test ch2 Prob >ch Intermedate subcontractors End-contractors coeffcent S.E. coeffcent S.E. captal labor rato(physcal fxed assets) ** captal labor rato(software assets) *** ** qualty of labor *** dummy for partnershps w computer maker *** dummy for partnershps w computer user ** software sales rato * constant *** *** number of observatons Breusch-Pagan Test ch2 Prob >ch Independent enterprses coeffcent S.E. captal labor rato(physcal fxed assets) *** captal labor rato(software assets) *** qualty of labor dummy for partnershps w computer maker dummy for partnershps w computer user *** software sales rato constant *** number of observatons Breusch-Pagan Test ch2 Prob >ch (Note) ***, **, and * mean 1%, 5%, and 10% statstcally sgnfcant each oer

11 Rev Soconetwork Strat (2009) 3: Table 4. Estmaton results (case of usng e rato of employees passng ITEE) TFP Total Prme contractors coeffcent Robust S.E. coeffcent Robust S.E. qualty of labor dummy for partnershps w computer maker *** *** dummy for partnershps w computer user *** *** software sales rato *** ** constant *** *** number of observatons Breusch-Pagan Test ch2 Prob >ch Intermedate subcontractors End-contractors coeffcent Robust S.E. coeffcent Robust S.E. qualty of labor ** dummy for partnershps w computer maker *** dummy for partnershps w computer user ** software sales rato * constant ** number of observatons Breusch-Pagan Test ch2 Prob >ch Independent enterprses coeffcent Robust S.E. qualty of labor dummy for partnershps w computer maker dummy for partnershps w computer user software sales rato constant *** number of observatons Breusch-Pagan Test ch2 Prob >ch (Note) ***, **, and * mean 1%, 5%, and 10% statstcally sgnfcant each oer.

12 62 Rev Soconetwork Strat (2009) 3:51-65 Table 5. Estmaton results (case of usng IT skll standard) Cobb-Douglas producton functon Total Prme contractors coeffcent Robust S.E. coeffcent Robust S.E. captal labor rato(physcal fxed assets) *** captal labor rato(software assets) *** *** qualty of labor dummy for partnershps w computer maker *** dummy for partnershps w computer user *** software sales rato * constant *** *** number of observatons Breusch-Pagan Test ch2 Prob >ch Intermedate subcontractors End-contractors coeffcent Robust S.E. coeffcent Robust S.E. captal labor rato(physcal fxed assets) ** captal labor rato(software assets) *** *** qualty of labor ** dummy for partnershps w computer maker *** dummy for partnershps w computer user *** software sales rato * constant *** *** number of observatons Breusch-Pagan Test ch2 Prob >ch Independent enterprses coeffcent Robust S.E. captal labor rato(physcal fxed assets) *** captal labor rato(software assets) *** qualty of labor ** dummy for partnershps w computer maker dummy for partnershps w computer user *** software sales rato constant *** number of observatons Breusch-Pagan Test ch2 Prob >ch (Note) ***, **, and * mean 1%, 5%, and 10% statstcally sgnfcant each oer.

13 Rev Soconetwork Strat (2009) 3: Table 6. Estmaton results (case of usng IT skll standard) TFP Total Prme contractors coeffcent Robust S.E. coeffcent Robust S.E. qualty of labor dummy for partnershps w computer maker *** *** dummy for partnershps w computer user *** *** software sales rato *** ** constant *** ** number of observatons Breusch-Pagan Test ch2 Prob >ch Intermedate subcontractors End-contractors coeffcent Robust S.E. coeffcent Robust S.E. qualty of labor * dummy for partnershps w computer maker *** dummy for partnershps w computer user *** software sales rato * constant ** number of observatons Breusch-Pagan Test ch2 Prob >ch Independent enterprses coeffcent Robust S.E. qualty of labor dummy for partnershps w computer maker dummy for partnershps w computer user software sales rato constant *** number of observatons Breusch-Pagan Test ch2 Prob >ch (Note) ***, **, and * mean 1%, 5%, and 10% statstcally sgnfcant each oer. 5 Conclusons Ths paper presented an emprcal analyss of e factors determnng productvty n e software ndustry n Japan, usng ndvdual data from e 28 Survey of e State of e Informaton Servce Industry conducted n August Software enterprses were classfed as prme contractors, ntermedate subcontractors, endcontractors, and ndependent enterprses. There are herarchcal structure among prme contractors, ntermedate subcontractors and end-contractors, outsourcng e software development from upstream to downstream. Ths herarchcal structure of e software ndustry s consdered partcularly promnent for custom software whch s popular n Japan compared w e U.S., European countres, and Inda. One of

14 64 Rev Soconetwork Strat (2009) 3:51-65 e reasons why e share of custom software s hgher n Japan an oer countres s at IT vendor 8 has had e domnant power n s strong herarchcal structure. Comparng productvty revealed at productvty was lowest for ntermedate subcontractors. They play as Intermedary to connect prme contractors and endcontractors. The technology level s e hghest n prme contractors whch ntroduces new technology. On e oer hand, e tact knowledge 9 of software development tends to be accumulated n e actual development process whch s manly charged n end-contractors. The estmaton results show at e empowerment of labor qualty can have e correlaton w e productvty n ntermedate subcontractors. ITEE qualfes e ablty of system engneer and programmer. IT skll standard defnes e sklls for IT human resources clearly and systematcally. The knowledge of software development s not formalzed n ntermedate subcontractors compared w prme contractors. So to utlze ITEE or IT skll standard s one of effectve meod n ntermedate subcontractors. The share of ntermedate subcontractors to total enterprses s above 25%. To rase e productvty n ntermedate subcontractors can lead to brng hgher productvty n e Japanese software ndustry as a whole. Our estmaton results of s paper can develop e concluson shown n Mnetak and Motohash [6], from organzaton skll towards ndvdual employee's skll. Also our s paper can provde e way how to change e subcontractng structure n e Japanese software ndustry, on e oer hand Nshmura and Mnetak [5] only shows e neffcency structure n s ndustry. In future, e stream where software s consdered as a servce wll spread and change e ndustral organzaton n e Japanese software ndustry. Accordng to Cusumano [9], e most sgnfcant change n software ndustry s e declne of tradtonal product sales or lcense fees and e shft n product company revenues to servces. Subcontractor enterprses whch have abundant human resources and can adjust to e new stream n e software ndustry wll have e chance to become ndependent and grow Major IT vendors are Htach, Fujtsu, and NEC whch have produced bo man frame computer and custom software n Japan. 9 Brooks [8] shows at an ncrease n e number of programmers or system engneers can actually have a negatve mpact on productvty for software frms, partcularly n cases where communcaton among programmers or system engneers plays a vtal role. Ths mples at e exchange of tact knowledge among employees s very dffcult, and erefore t decreases e productvty consequently. 10 Cusumano [9] shows at n e case of Sebel, er product sales fell dramatcally before t was acqured by Oracle and, Even Oracle experenced e crsscross (servce and mantenance revenues crossng over to exceed product revenues) as long ago as For Oracle or Sebel, eer er product sales were droppng or product prces were fallng. (Cusumano [9]) On e oer hand, Cusumano [9] ntroduces e company of Salesforce.com for e example of e provder of SaaS (Software as a Servce).

15 Rev Soconetwork Strat (2009) 3: Acknowledgements We would lke to ank IPA (Informaton-Technology Promoton Agency, Japan) at permts us to use ndvdual data from e '28 Survey of e State of e Informaton Servce Industry' conducted n August Also we would lke to ank to RIETI (Research Insttute of Economy, Trade and Industry) to provde us w e opportunty conduct s research. Ths work s supported n part by Japan Socety for e Promoton of Scence: Grant-n-Ad for Scentfc Research (B) ( ). References 1. Ima, K., Ishno, F.: Software busness n Japan. Busness Revew. 41(1), 1-18, 1991 (n Japanese) 2. Tanaka, T.: Software ndustry. Goto, A., Odagr, H.: IT Scence-based Industres. NTT publshng Co. Ltd., , 2003 (n Japanese) 3. Motohash, K.: The IT revoluton's mplcatons for e Japanese economy. Takeuch, H., Shbata, T.: Japan: Movng Toward a More Advanced Knowledge Economy. World Bank Insttute, , Shntan, M.: Quanttatve analyss of e structural change n e Japanese nformaton servce ndustry by usng mcro data. Japan Socety for e Promoton of Scence: Grant-n- Ad for Scentfc Research, 1-31, 2002 (n Japanese) 5. Nshmura, G., Mnetak, K.: Informaton Communcaton Technology and e Japanese Economy. Yuhkaku, 2004 (n Japanese) 6. Mnetak, K., Motohash, K.: Subcontractng structure n e software ndustry - emprcal study of nnovaton and productvty. RIETI Dscusson Paper Seres. 09-J-002, 1-26, 2009 (n Japanese) 7. Hromatsu, T., Tsubone, N., Kurta, M., Kobayash, M.: An emprcal study on effects of management resources gvng to value added rough scale economes n nformaton servces ndustry. Journal of e Japan Socety for Management Informaton. 17(1), 25-49, 2008 (n Japanese) 8. Brooks, F. P. Jr.: The Mycal Man-Mon: Essays on Software Engneerng Annversary edton. Addson-Wesley Publshng Company Inc., Cusumano, M.: The changng software busness: from products to servces and oer new busness models. The MIT Center for Dgtal Busness Paper. 236, 1-24, 2008