MEASURING THE ROLE OF TECHNOLOGY-PUSH AND DEMAND-PULL IN THE DYNAMIC DEVELOPMENT OF THE SEMICONDUCTOR INDUSTRY: THE CASE OF THE GLOBAL DRAM MARKET

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1 Journal of Appled Economcs. Vol XII, No. 1 (May 2009), MEASURING THE ROLE OF TECHNOLOGY-PUSH AND DEMAND-PULL IN THE DYNAMIC DEVELOPMENT OF THE SEMICONDUCTOR INDUSTRY: THE CASE OF THE GLOBAL DRAM MARKET Wonjoon Km* Korea Advanced Insttute of Scence and Technology Jeong-Dong Lee Seoul Natonal Unversty Submtted June 2005; accepted July 2008 Ths paper reexamnes and resolves the long dspute over the source of technologcal nnovaton by suggestng an ntegrated technology-push and demand-pull model. We derve an equlbrum model wthn the framework of dfferentated product analyss and explan the dynamc nteracton between these two sources of nnovaton. Based on the emprcal analyss of the global DRAM market, we show that the relatve mportance of technology-push and demandpull n technologcal nnovaton s descrbed by an L-type curve whch descrbes the phenomenon where technology-push s greater than demand-pull n the early stages and then decreases as demand-pull becomes greater. Our fndng suggests that the role of supply and demand s dfferent n nducng technologcal change and ther relatve mportance changes wth product development over the technologcal lfe cycle; the margnal prces of products are an mportant factor n determnng the prncpal forces of technologcal nnovaton between these two sources. JEL classfcaton codes: O32, O31 Key words: sources of technologcal nnovaton, technology-push, demand-pull, Nash equlbrum of technologcal nnovaton, DRAM * Wonjoon Km (correspondng author): Korea Advanced Insttute of Scence and Technology, Guseong-dong, Yusoeng-gu, Daejeon , Korea; emal: wonjoon.km@kast.ac.kr. Jeong-Dong Lee: Technology Management, Economcs and Polcy Program, Seoul Natonal Unversty, Seoul , Korea; leejd@snu.ac.kr. Ths work was supported by a Korea Research Foundaton Grant (H00003).

2 84 Journal of Appled Economcs I. Introducton In ths study, we reexamne and resolve the long dspute over the source of technologcal nnovaton by theoretcally and emprcally verfyng the dynamc changes n the nteracton between two sources of nnovaton, technology-push and demand-pull, n the development of the global semconductor ndustry. The sources of techncal change and ts role n economc growth has been a central ssue among economsts snce Schumpeter frst publshed hs key wrtng on nventon and nnovaton (Schumpeter 1934, Scherer 1982, Ruttan 2001). However, even though more than half century has passed, several controversal ssues reman. The frst and most controversal ssue s the role of demand n nducng technologcal nnovaton. Snce Grllches (1957) and Schmookler (1962, 1966) demonstrated the mportance of the role of demand n stmulatng nventve actvty, arguments about the relatve prorty of demand- and supply-sde n nducng technologcal nnovaton have ntensfed. After much research (Lucas 1967, Ben- Zon and Ruttan 1978, Ruttan 1997, 2001), economsts have mostly settled on the vew that both demand and supply factors play an mportant role n nnovaton and the lfe cycles of technology (Mowery and Rosenberg 1979, Walsh 1984, Scherer 1982). However, there has been no attempt to emprcally mplement an ntegrated factor and demand nduced nnovaton model (Ruttan 2001). Therefore, mportant questons reman unanswered. If both sources play an mportant role n nducng technologcal nnovaton, how dfferent s ther role? Does ther relatve mportance change over the lfe cycle of technology? Does t dffer dependng on the technology under consderaton? The second unsettled argument s about the role of nnovaton sources n the late stage of technology lfe. Economsts generally accept that, even when the ntal path (technologcal lock-n ) of technologcal development s generated by technology-push n the early stage of technology lfe where ncreasng returns to scale are mportant, factor market forces often act to modfy the path of techncal change (Arthur et al. 1987, Ruttan 2001). However, there has been lttle dscusson of how frms or ndustres escape from lock-n and how the nnovaton sources change as techncal progress slows down or scale economes erode. What happens when the scale economes resultng from an earler change n technology have been exhausted and the ndustry enters a constant or decreasng returns stage? The thrd remanng queston concerns the lack of emprcal analyss of technologcal nnovaton and ts sources from the perspectve of evolutonary economcs (Arrow 1995). Although there s ongong debate about the Schumpeter

3 Measurng the Role of Technology-Push and Demand-Pull 85 Mark I and II dscussons, both nduced nnovaton and evolutonary theory suggest that, as scale economes are exhausted, the pressure of growth n demand wll force research efforts to be drected to removng the technologcal constrants on growth or nelastc factor supples. 1 However, economsts have made only lmted efforts to test the evolutonary theory aganst hstorcal experence (Ruttan 2001). Does the actual development of ndustres verfy evolutonary economsts pont of vew on technologcal nnovaton? In response to these questons, ths paper recommends an ntegrated factor and demand nduced nnovaton model whch analyzes the dynamc balancng act between the nnovaton sources, technology-push and demand-pull, over the technology lfe cycle and emprcally supports one of the evolutonary theores of technologcal nnovaton by applyng t to the global DRAM (Dynamc Random Access Memory) market n the semconductor ndustry. The paper proceeds as follows. In Secton II, we ntroduce a smple model of competton among dfferentated olgopolsts based on Anderson, de Palma, and Thsse (1992) to model technologcal nnovaton. A key assumpton of our model s that a product s qualty mproves over tme (Adner and Zemsky 2003). The supplysde qualty mprovement can be generally thought of n terms of the ncreasng memory densty of DRAM, the ncreasng sze of flat panel dsplays or the ncreasng speed of broadband network connectons. On the demand-sde, we focus on the dynamcs of consumers wllngness-to-pay for the qualty of products, whch decreases wth the mprovement of products qualty over the technology lfe cycle. By consderng these dynamc changes of the demand envronment, we suggest a new perspectve on the nteracton between technologcal nnovaton and demand. In Secton III, we descrbe the DRAM market. In Secton IV, we emprcally apply the model to the global DRAM market and suggest polcy mplcatons. Secton V concludes. II. The model We employ two mportant elements from the tradtonal models of product dfferentaton (Anderson et al. 1992). The frst element s the noton of heterogenety of consumers and of technologcal nnovaton of products. The extent of technologcal 1 Schumpeter Mark I suggests that nnovatons are carred out by ndvdual entrepreneurs who create new frms by means of borrowed money. In contrast, the Mark II dscusson suggests that nnovatons are permanently performed by many large corporatons n ther monopolstc competton.

4 86 Journal of Appled Economcs nnovaton dffers across products, and consumers dffer n ther wllngness to pay for the products. Secondly, we consder a dscrete choce stuaton where a consumer buys a unt of a technologcally nnovatve durable product. A. Demand-sde The qualty percepton of a consumer (q ) can be descrbed as q s the = x η, x performance level of the product s man attrbute representng the level of technologcal nnovaton of the frm producng the product, and η (wth 0 < η 1) s the degree of decreasng margnal utlty from technology nnovaton (.e., the extent of technology saturaton n the market where saturaton s represented by smaller values of η). 2 If x > 1, q s margnally decreasng wth x descrbng the stuaton where the addtve technologcal nnovaton of product s not valued as much as t would have been n earler perods. In order to smplfy matters, the analyss s restrcted to x > 1 as n Adner and Zemsky (2002). The maxmum wllngness-topay of consumers for product can be expressed as w = α q = α x η where α s the margnal wllngness-to-pay for the unt mprovement of a product s qualty. Each ndvdual s supposed to have a determnstc utlty functon U defned on C n, where C n s a fnte choce set of dfferentated products. U s modeled by the random varable Ũ = V +ε. (1) Here, V s a consumer s condtonal ndrect utlty from purchasng product, whle ε takes nto account dosyncratc taste dfferences. Products = 1,,n are the varatons of a dfferentated product sold at prces p 1,,p n. We assume that a consumer s condtonal ndrect utlty s gven by the followng addtve form: V = w p = α x η p, = 1,,n. (2) Then, a multnomal logt demand functon represents the probablstc demand for the product wth q = ( q q a vector of qualtes, and p= ( p 1 n ), 1 p n ), a vector of prces. The demand for product, D, s as follows: 2 Technology saturaton means that further technologcal mprovement of a product could not gve as much utlty ncrease as the prevous nnovaton dd, ceters parbus. In other words, consumers become ndfferent to nnovaton, snce they feel that ther technologcal needs have been already satsfed. See Km, Lee and Km (2005) for a more detaled explanaton.

5 Measurng the Role of Technology-Push and Demand-Pull 87 D ( p; q) = M s ( p; q) = M exp( α q p) n =,,n exp( α q p ), 1, (3) where M denotes total demand and the rest of the varables s as before. B. Supply-sde Let us assume that each frm produces only one product and that t s the sole producer of that product, so the ndex = 1 through n denotes a specfc frm producng a specfc product. Frm s producton costs comprse sunk costs K that are constant and equal for all frms, and the technology-dependent margnal cost c(q ). The n frms are players of a non-cooperatve game (when the model nvolves the outsde alternatve n + 1, there s no player assocated wth t). Suppose also that frms set prces and set the levels of performance of those product attrbutes, whch represent the frm s technologcal nnovaton. The frms supply consumers wth the quanttes demanded at the prces set. In other words, frm s strategy s settng prces and choosng the level of ts products attrbutes. Frm s (expected) proft can then be defned as follows: ( pq ; ) [ p cq ( )] D( pq ; ) K π = (4) where D s the demand for product n equaton (3). Now suppose that the margnal cost s constant wth respect to quantty but s ncreasng and strctly convex representng the technologcal nnovaton of a frm, so that we can defne the margnal cost of technologcal nnovaton as cq ( where δ > 1, whch results n 3 ) cx ( ) = x δ δ 1, c ( x We also defne ) = δ x > 0. a frm s nnovaton capablty, λ = 1/ δ,, where the capablty of a frm s nnovaton, specfcally the process nnovaton, ncreases wth the ncrease of λ resultng n a lower cost to produce a product wth the same level of performance. 4 We now turn to a subgame perfect Nash equlbrum, followng Anderson et al. (1992). Here, frms frst choose the level of qualty attrbutes whch s the performance 3 We assume that α < lm x c ( x), whch explans that the consumer valuaton of qualty s smaller than the margnal cost of the hghest possble qualty. 4 We follow Utterback and Abernathy (1975) and Porter (1983) here n defnng process nnovaton as an nnovaton that reduces producton costs, resultng n the decrease of a product s prce. By contrast, product nnovaton means an nnovaton that mproves product performance.

6 88 Journal of Appled Economcs level of the product s man attrbute and then choose prces. Gven qualtes q _ * * selected n the frst stage, the correspondng prce subgame s solved by p1 ( q) pn( q), such that * * * π ( p, p ; q) π ( p, p ; q) for all q and = 1,, n. (5) Denote the proft functons evaluated at the second-stage equlbrum * * p ( q) as π ( q) π ( p ( q); q). The equlbrum of the qualty game s then gven by q * * 1 q n satsfyng * * * π ( q, q ) π ( q, q ) for all q and = 1,, n. (6) A subgame perfect Nash equlbrum s defned by q * and by p * ( q) for all qualty confguratons _ q. The correspondng equlbrum path s q * and p * ( q). In what follows we restrct the analyss to the case of a symmetrc equlbrum n whch all frms choose the same qualty. C. The Nash equlbrum of technologcal nnovaton (NETI) If we consder the second stage of the game where frm has chosen qualty q whle all other frms have selected q, then there s a unque prce equlbrum for the game that gves us the followng relatonshp: 5 * * 1 Φ ( p p ) = ( cq ( ) cq ( )) +, n 2 + Φ n 1 * * where Φ exp α ( q q) ( p p ), p * = c( q ) + { } 1, * 1 { exp( α q p )}/ Δ (7) p * j = c( q) + 1, j = 1,, n and j, * 1 { exp( α q p )}/ Δ 5 See chapter 6 of Anderson et al. (1992) for the proof of the exstence and unqueness of the prce equlbrum.

7 Measurng the Role of Technology-Push and Demand-Pull 89 n = j j Δ exp( * ) + exp( * * α q p j 1 α q p ) = exp( α q p ) * + ( n 1) exp( α q p ). Therefore, the payoff functon for the frst-stage game from the evaluaton of frm s proft at the equlbrum can be derved by nsertng equatons (3) and (7) nto equaton (4) as follows: M π = K. ( n 1) Φ (8) The frst-order condton wth respect to x s π M Φ = = M Φ η α η x 1 * * + p p x ( n 1) x ( n 1) ( ) x = 0, (9) snce q q = x η < = x η 1, 0 η 1and η. x x Based on equaton (7), the second term n equaton (9) becomes * * 1 1 ( p p ) = c ( q) n 2 + Φ ( ) + 2 n 1 Φ = c ( q ), 1 x (10) Φ where = 0 for any soluton of the frst-order condton based on equaton (9). x Thus, equaton (9) becomes π x M Φ η 1 = α η x c ( q) = 0. ( n 1) (11) Equaton (11) has a unque soluton x * snce c s ncreasng, such that * c ( q ) x = α η 1 η 1. (12) Then, as we assumed cx ( ) = x δ, where δ > 1 and λ = 1/δ, equaton (12) becomes: x * = α λ η λ λη 1. (13)

8 90 Journal of Appled Economcs D. The role of technology-push and demand-pull n technologcal nnovaton To derve the role of technology-push n technologcal nnovaton, we smplfy the model wth the assumpton of a duopolstc market structure. Two frms produce two types of products, each wth dfferent levels of the man qualty attrbute. Therefore, the margnal costs of the two frms dffer dependng on the qualty level of each product s man attrbute. We have the same margnal prces for both products (.e. = 1 = 2 ) under the assumpton that product features are standardzed across brands and vertcally dfferentated as n the case of the DRAM market. In addton, the decreasng margnal utlty s the same for both products (.e.,η = η 1 = η 2 ) under the assumpton of homogeneous consumers n a specfc perod of tme. By defnton, the entrant s (frm 2) product s superor to the ncumbent s (frm 1) wth respect to the performance level of ts man attrbute, x * 2 > x *. 1 Then, we can defne the payoff functon of the entrant for the frst-stage game as π = M 2 Φ K, { } (14) η η * * where Φ= exp α ( x The entrant has ncentves to nnovate 2 x1 ) ( p2 p1). f π 2 0, whch gves η η TP x x τ + ϖ, 2 1 (15) * * 1 K where τ = ( p2 p1) and ϖ = ln. We defne the ncentve to nnovate, α α M η η the entrant s ncentve to ntroduce the product wth better qualty ( x ) 2 x1 0 nto the market, as technology-push (TP). In addton, we defne τ as the mnmum dfference n process nnovaton for technology-push (MI), whch represents the crtcal pont up to whch consumers prefer the exstng product. We also defne ϖ as the crtcal level of demand for technologcal nnovaton (CD), whch represents the mnmum level of demand needed for the entrant s technologcal nnovaton to enter the market. In order to derve demand-pull, we defne consumer s margnal beneft from frm s perspectve as 6 6 Ths s the margnal beneft of demand-sde from the perspectve of a frm, whch s dfferent from consumer surplus (or utlty). Under ths defnton, we do not consder the prce coeffcent whch

9 Measurng the Role of Technology-Push and Demand-Pull 91 η dp = α x p * *. (16) When the entrant expects ths margnal beneft of an entrant s product (product 2) to be greater than that of ncumbent s (product 1),.e. dp 2 > dp 1, the entrant expects hgher sales of ts product (product 2) than the ncumbent s (product 1) and has ncentves to nnovate and ntroduce product 2. Therefore, we defne demand-pull (DP) as follows: DP DP ' η η = = x (17) 2 x1 ξ > 0, α η η * * 1 where DP ' dp2 dp1 = α( x2 x1 ) ( p2 p1), α > 0, and ξ = ( p * 2 p * 1) > 0. α Here ξ s the mnmum dfference n equlbrum prces for demand pull (MP), whch represents the crtcal dfference n prce up to whch consumers prefer the exstng product when the technologcal nnovaton of products s gven. The relatonshp between the MI (τ) of technology-push and MP (ξ) of demandpull s easly derved as follows: τ = ξ (18) Ths enables us to derve the followng propostons about the relatonshp between technology-push and demand-pull. Proposton 1. Technology-push s always greater than demand-pull when consumers are relatvely ndfferent to the prce change of the product, that s, when < 1, under the assumpton that the ncumbent has a postve prce advantage. However, when consumers are relatvely senstve to the prce change of the product, > 1, the man dervatve of the technologcal nnovaton s determned n a more complex manner (refer to Appendx for the proof). Proposton 2. Demand-pull s always greater than technology-push when consumers are relatvely senstve to the prce change of the product, > 1, under the assumpton that there s no crtcal level of demand for technologcal nnovaton (CD), ϖ = 0. Otherwse technology-push s always greater than demand-pull (refer to Appendx for the proof). comes from the consumer utlty s perspectve. Here we assume that entrant s product has not been ntroduced nto the market and the entrant frm consders the absolute prce t wll charge n ts estmaton of product s beneft of demand-sde before t ntroduce ts product.

10 92 Journal of Appled Economcs Propostons 1 and 2 show that consumer prce senstvty s an mportant factor for the determnaton of the dervatve of technologcal nnovaton. Ths result not only gves us a new perspectve on the development of technologcal nnovaton, t also suggests the answer to the long dspute over the sources of technologcal nnovaton. That s, t descrbes how the two dfferent sources of technology nnovaton, technology-push and demand-pull, are nterrelated and develop through the market sgnal of prce senstvty. Based on the above propostons, we further assume decreasng margnal utlty n a market over the technology lfe cycle. Then, Proposton 3 allows us to dentfy the dynamc change of the relatve role between technology-push and demand-pull. Proposton 3. The role of technology-push n technologcal nnovaton s greater than that of demand-pull n the early-stage of the technology lfe cycle, f we assume that the margnal prce () of technologcal nnovaton ncreases wth the evoluton of technology lfe cycle. However, n the later-stage of technology lfe cycle, the role of technology-push rapdly decreases and the role of demand-pull becomes greater than that of technology-push (refer to Appendx for the proof). Based on equaton (18), proposton 2, and 3, we can have the followng L-type curve, shown n Fgure 1. Fgure 1 descrbes the dynamc relatonshps between TP and DP, when we defne the dfference between TP and DP as Γ, so η η η η 1 Ã= TP DP= ( x2 x1 τ) ( x2 x1 ξ) = τ ( ), where > 0 and τ > 0. 7 (19) Fgure 1 descrbes the dynamc change of the relatve mportance of the two sources of technologcal nnovaton, technology-push and demand-pull, dependng on changes n margnal prce. Here the ncrease of corresponds to the tme elapsed over the technology lfe cycle under the assumpton of the Nash equlbrum of technologcal nnovaton (NETI). At the same tme consumers prce senstvty ncreases also. In Fgure 1, when the margnal prce s low ( < 1), the relatve role of technologypush s far greater than that of demand-pull. However, t exponentally decreases wth the ncrease of margnal prce. In other words, the ncentve to push the nnovaton from the supply sde dramatcally decreases as consumers become more senstve to the prce of products. Therefore, the consumer s prce senstvty serves as an mportant sgnal for frms when they map out ther product nnovaton strategy. 7 When > 0, we have τ > 0 based on equatons (17) and (18).

11 Measurng the Role of Technology-Push and Demand-Pull 93 Fgure 1. The Γ curve, representng the dynamc changes n the relatve mportance of technologypush and demand-pull over the technologcal lfe cycle (L-type) On the other hand, when the margnal prce s greater than 1 ( > 1), the role of demand-pull s greater than that of technology-push n the development of technologcal nnovaton. Ths makes sense when consumers are more concerned about the prce rather than the qualty of products. In these stuatons, there are few ncentves for the frm to nnovate. Ths leads frms to focus on a strategy of cuttng prces. However, the ncentve to nnovate derved from demand-pull n ths stage s smaller than the amount of technology-push when the margnal prce s hgh or when t s almost constant. From the perspectve of economc hstory, Schumpeter s (1934) vew that technology-push plays a major role n technologcal nnovaton has long been domnant. The early stage of the technology lfe cycle wth less than 1 (n Fgure 1) clearly supports ths vew of the role of technology-push. On the other hand, the ncreasng role of demand-pull n the later stage of the technology lfe cycle wth greater than 1 (n Fgure 1) supports the vew of Schmookler (1966) and Scherer (1967), and Barzel (1968). They challenged Schumpeter s vew on technologcal nnovaton, nsstng that the greater the demand for a set of products, the more proftable nnovatons to these products were lkely to be. They also argued that we should expect more nnovatons amed at satsfyng consumers demands for those products. Therefore, the ncreasng role of demand-pull n the later stage of the technology lfe cycle n Fgure 1 clearly supports ther arguments on the other sde. Therefore, Proposton 3 and Fgure 1 help to dsentangle the long dspute over the

12 94 Journal of Appled Economcs role and process of nnovaton n economcs by llustratng the two sdes of nnovatons and descrbe how those two major dervatves of technologcal nnovaton develop over the technology lfe cycle nteractvely. Consequently, these results gve us new strategc and publc polcy perspectves. From a frms manageral pont of vew, dynamc nnovaton strateges should depend on a products technology lfe cycle. A frm can allocate ther resources on R&D for new product ntroducton and for product nnovaton n the early stages of the technology lfe cycle. On the other hand, n the later stages, they can focus on process nnovaton n order to reduce the producton cost of ther product and hence ts prce. The result of propostons based on the Nash equlbrum of technologcal nnovaton (NETI) suggests that frms wll have optmal proft levels f they use ther resources followng the dynamc change of the dervatves of technologcal nnovaton. From the perspectve of publc polcy, the government can modulate ndustry regulatons and supports, dependng on an ndustry s stage n ts technology lfe cycle. For example, n the case of the botechnology ndustry that s currently n the early stages of technology development, government can use regulatons and subsdzatons to encourage frms to emphasze R&D, new technology development, and subsequently commercalzaton. Ths wll lead to greater returns from the dynamc perspectve of technology development. Therefore, the results encourage us to have a dynamc perspectve regardng publc polcy for technology nnovaton n publc sectors as well. The results also strongly support drect nvestment n R&D, reducton or exempton of taxes related to R&D actvtes n the early state of the technology lfe cycle. In addton, promoton of the nteracton between product development and markets, such as the nsttutonal support of market formaton for specfc products, wll enable publc polcy to be more effectve when we consder the role of demand n the later stage of technology lfe cycle. III. The DRAM market Memory chps are the largest sngle segment n the semconductor market and DRAMs are the hghest volume commodty semconductors wth more than 11% of the total semconductor market. 8 Dynamc random access memory (DRAM) s the most common knd of random access memory (RAM) for personal computers and workstatons. Random access ndcates that the PC processor can access any 8 Status Report on Semconductor Industry, Integrated Crcut Engneerng Corporaton (2000).

13 Measurng the Role of Technology-Push and Demand-Pull 95 part of the memory drectly n any order. DRAM s dynamc n that t needs to have ts storage cells refreshed or gven a new electronc charge every few mllseconds. DRAM has shown clear dscrete nnovatons n ts product characterstcs, especally n memory densty, makng t a typcal mult-generaton product. The standardzed features of DRAM, whch allows for almost perfect substtuton among successve generatons and brands, enhance competton and cause product nnovaton to occur n dscrete steps, whle maxmzng the number of generatons n order to skm the hgh margns assocated wth early ntroducton. Snce the ntroducton of ntegrated crcuts (IC) n 1959, more than 10 generatons have been brought onto the market, each havng four tmes hgher memory densty compared to the prevous generaton up untl the recent 256M generaton. The source of the recent rapd nnovaton n DRAM products can be found n the demand, supply and technologcal sdes of the market. On the demand sde, DRAM has manly been used n PCs, workstatons, manframes and other computer related equpment, such as hard dsk drves, prnters and scanners. However, DRAM has been expandng ts scope of applcatons to nclude the moble handsets and other telecommuncaton equpment, such as notebooks, PDA s (Personal Dgtal Assstants), GPS (Global Postonng Systems) as well as dgtal consumer applcatons, such as dgtal vdeo recorders and gamng consoles. Therefore, we understand that the ncreasng total demand and the ncreasng number of DRAM varetes accelerate the nnovaton of DRAM, as the general communcaton technology accelerates ts transformaton from analog to dgtal and from wred to wreless. On the supply sde, the ntense competton among the DRAM manufacturers spurred the rapd ntroducton of new DRAM generatons resultng n substantal restructurng of the ndustry, whch caused the market to evolve from a state of almost perfect competton to an olgopolstc one. The market leaders have made a desperate attempt to survve the severe competton by ntroducng successve generatons earler than the other compettors and have enjoyed a sgnfcant cost advantage over the smaller companes by reachng the economes of scale earler than others. On the technologcal sde, snce DRAM supports the storage of nformaton of the CPU (Central Processng Unt), a complementary technologcal nnovaton n both CPU and DRAM has come about wth developments n one trggerng complementary developments n the other. As the system software becomes more complex to meet the demand of consumers for ever more advanced programs, the CPU has grown faster and more powerful. Recently, to match the advancement of

14 96 Journal of Appled Economcs CPU, DRAM has been developed also nto three dfferent types of SDRAM (Synchronous), DDR (Double Data Rate) SDRAM, and RDRAM (Rambus DRAM). Wth these fast and dynamc developments of demand, supply, and technology, the DRAM market seems to be one of the most motvatng and approprate markets to examne the relatonshp between technology push and demand pull. IV. The emprcal analyss for the global DRAM market In ths secton, we verfy the dynamcs of technology-push and demand-pull by applyng the suggested model to the global DRAM market. In order to verfy the dynamcs, we estmate equaton (19), the nterrelatonshp between technologypush and demand-pull. Therefore, we frst estmate τ of equaton (15). However, snce τ s a functon of α and, we frst estmate the demand functon of equaton (3). In order to estmate equaton (3), we assume the multnomal logt demand model and follow the estmaton approach suggested by Km et al. (2005). A. Data set The dataset we use s provded by Vctor and Ausubel (2002) and conssts of 25 yearly observatons of worldwde DRAM shpments and ther prce per megabt, for 7 successve generatons from 1974 to 1998: 4K (t 1 =1974), 16K (t 2 =1976), 64K (t 3 =1978), 256K (t 4 =1982), 1M (t 5 =1985), 4M (t 6 =1987), 16M (t 7 =1991). Table 1 shows the summary statstcs for DRAM generatons. The means of global DRAM shpment constantly ncrease from to mllon unts as DRAM generatons evolve from 4K to 16M. 9 In the case of prce, the annual prces per bt drastcally decrease from to 3.01 dollar per megabt (Mbt) as DRAM generatons evolve, whch reflects technologcal nnovaton, learnng-by-dong, and ncreasng compettveness of DRAM market. Fgure 2 below represents the cumulatve unt shpment of DRAM generatons. Each generaton clearly shows an S-type dffuson curve of ts technology lfe cycle. As we can expect from the summary statstcs, the market saturaton ponts for each generaton has drastcally ncreased as generatons evolved over tme. In other words, demand for DRAM has radcally ncreased wth the evoluton of DRAM 9 For 64M DRAM, the mean of shpment, mllons unts, s smaller than 16M DRAM, because 64M DRAM were ntroduced n 1994 wth only 5 years of product lfe n the market compared to 8 years of 16M DRAM. Average product lfe of DRAMs s 12.3 years for 4K to 1M DRAMs.

15 Measurng the Role of Technology-Push and Demand-Pull 97 Table 1. Summary statstcs for DRAM generatons ( ) DRAM generaton Global DRAM shpment by IC densty Annual DRAM prce-per-bt (bt) (mllon unts) ($ per Mbt) Mean Max Mn Mean Max Mn 4K K K K M M M M Note: K stands for klobte, M for megabte. generatons. Ths notable expanson of demand for DRAM can be attrbuted to the IT revoluton n the late 80 s and 90 s. Durng ths perod, the demand for computers and perpheral equpments, moble handsets, telecommuncaton related equpments, and dgtal consumer applcatons notably expanded. Correspondng to ths epochal expanson of IT products, demand for DRAM had the hghest rate of ncrease over the past decades, because DRAM s one of the key components for most of those IT products. Fgure 2. Cumulatve DRAM unt shpments by DRAM generatons ( )

16 98 Journal of Appled Economcs Fgure 3 shows the cumulatve market share of each DRAM generaton. As generatons evolve, the maxmum market share of each generaton decreased sgnfcantly, 8 % on average. 10 The decrease of maxmum market share results from the ncreased product lfe and sgnfcant prce reducton of later generatons stemmng from accelerated technologcal nnovaton. The DRAMs are products wth a hgh rate of nnovaton n ther technologcal attrbutes, especally n ther memory denstes (Mbt). Therefore, the development of ther technologcal nnovaton can be clearly classfed by the generatons defned by ther memory denstes. Of course, the DRAMS have other technologcal attrbutes, such as frequency (MHz). However, the development of frequency (MHz) wth each generaton of DRAMS shows a smlar trajectory to that of the memory densty. Fgure 3. DRAM market share by generatons ( ) B. Estmaton A choce stuaton s defned as the one n whch a consumer s faced wth a choce among a set of alternatves whch s fnte, mutually exclusve and ncludes all possble alternatves (Tran 2002). A consumer chooses one alternatve, whch 10 The case of 4M DRAM has been excluded n the calculaton, snce the DRAM market between 1990 and 1993 experenced an overall depresson when 1M DRAM was the major memory chp. The maxmum market share of 4M DRAM ncreased 4% compared to 1M DRAM after the DRAM market recovered from the depresson.

17 Measurng the Role of Technology-Push and Demand-Pull 99 maxmzes hs/her utlty under a lmted budget. In the case of mult-generatonal products, consumers should decde whch generaton to purchase n each perod. We denote a choce set for all DRAM generatons at tme t wth J alternatves as Ct = {, 12,, Jt}, a memory densty vector of a DRAM generaton as MD(t) j observed by consumer, the prce as p(t) j, and the tme varable represented by the age of the product as a jt = t t j + 1, where t s the tme ndex and t j s the ntroducton tme of the j th generaton. Then, the utlty of consumer when he/she chooses generaton j from the set C t can be defned as follows, ut () j = U ( MDt (), j pt (), j ajt ) = V ( MDjt, pjt, ajt ) + εjt. (20) Here, the utlty functon u(t) j can be parttoned nto two parts. The frst, V (MD jt,p jt,a jt ), depends on the memory densty, prces, and generaton, whch can be captured by the data. The second part s the random error term whch represents all the other factors of utlty that cannot be captured as data represented by ε jt. Actng on the assumpton of addtve separablty n the utlty functon, we can specfy V of product j at tme t, V( MD, p, a ) = α MD + p + γ a. jt jt jt j jt j jt j jt (21) Consequently, the market share of generaton j at tme t can be represented drectly by the average probablty of a consumer choosng ths partcular generaton based on the product characterstcs. 11 Under the assumpton that the random varable a jt s ndependently, dentcally dstrbuted wth extreme value dstrbuton, 12 we can have market share functon as follows, exp( V( MDjt, pjt, ajt)) Sj() t = Pj() t = k Ct exp( V( MD, p, a )), for all n, k Jt kt kt kt (22) 11 In estmatng dscrete choce models of consumer demand on market-level data, aggregate estmates can be obtaned from the above choce probablty stuaton by sample enumeraton. Here, the choce probabltes of each consumer n a sample are summed, or averaged, over a set of consumers. See Km et al. (2005) for a more detaled explanaton. 12 We approach the demand analyss wth a smple logt model as a prmtve case. However, applyng varous dscrete choce models, such as probt and nested logt, results n a more realstc estmaton of demand.

18 100 Journal of Appled Economcs by employng the nverson routne suggested by Berry (1994) 13, equaton (22) becomes 14 ln( f ( t)) ln( f ( t)) = α MD p a, j j jt + j jt + γ j jt 0 where f j (t) s the market share of product j at tme t n equaton (22) and f 0 (t) s the market share of outsde goods. 15 Followng Km et al. (2003), we use OLS to estmate equaton (23) for each generaton ndependently wthn the framework of a tme-seres data analyss. Ths not only has the advantages of Seemngly Unrelated Regressons (SUR), but also avods the problem of prce endogenety, snce the product characterstcs of one generaton generally do not change over tme untl that partcular generaton dsappears from the market. Table 2 reports the estmaton results for seven generatons usng OLS. We performed an F-test for our panel data n order to test whether our model allows the coeffcents to vary across generatons wth the null hypothess of H 0 : α1 = = α, 1 = = and γ = = γ We reject the hypothess of parameter homogenety over generatons, snce the F-statstc s (for 1% level of sgnfcance, the crtcal value s about 2.10). Therefore, our model can have dfferent coeffcents across generatons, allowng separate estmatons of equaton (23) for each generaton. All the coeffcents of prces ( j ) turn out to be statstcally sgnfcant wth 1% sgnfcance except 16M (5% sgnfcance) and have negatve values as we would reasonably expect: unt sales decrease wth the ncrease of prce. In the case of age (γ j ) coeffcents, we also have negatve values wth 1% sgnfcance for 4K, 16K, and 64K descrbng the stuaton where the unt sales decrease as the generaton become older correspondng to the ntroducton of new generatons. Regardng the coeffcents of Memory Densty (α j ), only 4K has a sgnfcant and postve coeffcent. Based on these estmaton results, we analyze the development of the demand envronment wth respect to technologcal nnovaton. Fgure 4 summarzes the dynamc changes of demand correspondng to the evoluton of DRAM generatons. (23) 13 Berry (1994) suggested the method of nvertng market share functon to overcome the nonlnear nstrumental varables (IV) problem n estmatng dscrete choce models wth unobserved product characterstcs, allowng for tradtonal (lnear) IV methods. 14 See Km et al. (2005) for more detals. 15 We assume the exstence of an outsde good, j = 0, as suggested by Berry (1994). The outsde good s a good whch the consumer can purchase nstead of one of the J nsde goods n hs choce set, but whose prce s not set n response to the prces of the nsde goods. See Berry (1994) for more detals.

19 Measurng the Role of Technology-Push and Demand-Pull 101 Table 2. Estmates for seven generatons of DRAM by multnomal logt functon Generatons Estmates Adj_R 2 Memory densty MD jt Unt prce p jt Age a jt (α j ) ( j ) (γ j ) 4K ( ) *** (0.000) *** (0.047) *** 16K (0.000) *** (0.129) *** 64K (0.000) *** (0.082) *** 256K (0.002) *** M (0.015) *** M (0.291) *** (0.014) *** M (0.059) *** (0.062) ** (0.145) *** Notes: K stands for klobte, M for megabte. Standard errors are n parentheses. *** denotes 1% sgnfcance, ** 5% sgnfcance, and * 10% sgnfcance. Fgure 4. Saturaton of technology n the global DRAM market

20 102 Journal of Appled Economcs As the generatons evolve from 4K to 16M, the coeffcent of memory densty (α j ) decreases n contrast to the ncrease of the absolute values of the unt prce coeffcent ( j ), although not all of α j are sgnfcant. Therefore, the effects of technologcal factors on consumers choces become smaller, whereas prce senstvty ncreases wth each successve generaton. In other words, Fgure 4 shows that consumer markets become saturated by technologcal nnovaton over the technology lfe cycle. Consumers become ndfferent to the addtve ncrease of memory densty n choosng DRAM, snce they feel that ther technologcal needs for memory densty have already been satsfed. Thus, consumers choose whatever generaton has the lowest prce per bt for the requred DRAM confguraton, whle whatever generaton provdes the hghest margn for the DRAM manufacturer s produced n the extreme case (Km et al. 2005). Therefore, we fnd that the evoluton of a market nto a condton of technology saturaton whch supports the mportant role of the demand-sde n the development of technologcal nnovaton. From the estmated results of the demand functon n equaton (23), we also derve the relatonshp between technology-push and demand-pull suggested by equaton (19) n Proposton Fgure 5 shows the derved results for the DRAM generatons (16K, 64K, 256K, 1M, 4M, and 16M). The y-axs s the dfference between TP and DP,.e. Γ. Surprsngly, all the patterns of Γ clearly exhbt the L- type curve, as n Fgure 1, suggested by Proposton 3. The curves n Fgure 5 show the dstnctve feature of the DRAM market n whch technology-push s the major dervatve of technologcal nnovaton n ther early perods of ther technology lfe as we would expect. As for the 256K DRAM, the role of technology-push does not look dstnctve ts early perods. Ths could be explaned by the rapd growth of demand for 256K DRAMs n the perod of 1982 to 1985 compared to other perods. Ths results n an unexpectedly large role of demand-pull n the technologcal nnovaton of DRAM. In Fgure 5, the absolute scale of the Γ curves n the early perods of the technology lfe ncreases wth each DRAM generaton, whch explans the ncreasng role of technology-push n the technologcal nnovaton of the DRAM market. One reason for ths phenomenon could be the ncreasng competton n the DRAM market over tme. Ths ntense competton led to substantal restructurng of the ndustry untl recently from a state of almost perfect competton to an olgopolstc one. Untl 16 In dervng ths relatonshp, we assume a duopolstc market structure n whch only two successve generatons compete wth each other n the market.

21 Measurng the Role of Technology-Push and Demand-Pull 103 Fgure 5. The Γ curve n the global DRAM market 1997, there were more than 10 supplers, each wth less than 20% of the market share. However, after the enormous consoldatons that started n 1998, the top four companes, Mcron, Samsung, Hynx and Infneon, ncreased ther overall market

22 104 Journal of Appled Economcs share to 71.6% by The market leaders have made a desperate attempt to survve the severe competton by expandng ther market share n order to explot the cost advantage from economes of scale. Snce, for these companes, the expanson of market share comes manly from ntroducng new product generatons before ther compettors, technologcal nnovaton whch orgnated from the nternal dervatves, technology-pull, has been accelerated. Consequently, we fnd that the role of technology-push and demand-pull change dynamcally wth the evoluton of tme, and also wth DRAM generatons. The role of technology-push n technologcal nnovaton s greater n the early perods of the technology lfe than the role of demand-pull n ther later perods. Demandpull s relatvely low degree of mportance n the later perods provdes an opportunty for dstnctve nnovaton drven by technology-push from the supply sde. Ths results n the ntroducton of successve generatons of the DRAM market. The L-type curve representng the sources of technologcal nnovaton gves some mportant strategc nsght for semconductor manufacturng frms. When ther products are n the later perods n an L-type curve, the nnovaton of products, especally process nnovaton whch consequently decreases the prce of the products, needs to be responsve to market demand. Ths can be captured through market sgnals, such as margnal prce and margnal return of technologcal nnovaton, because the major dervatve of ther nnovaton comes from demand-pull n ths stage. By contrast, when ther products are n the early perods of ther technology lfe cycle, the nnovaton strategy should focus on product nnovaton whch enables frms to ntroduce new features of products or new products, snce the source of nnovaton s technology-push. V. Conclusons In ths paper, technology-push and demand-pull, the two prncpal drvng forces of technologcal nnovaton, are modeled. The equlbrum s determned by the nteracton between technologcal nnovaton and the dynamc evoluton of the demand envronment. The model shows that the two drvng forces of technologcal nnovaton are hghly nterrelated. Each one s a necessary condton for the nnovaton process as a whole. By adoptng the multnomal logt (MNL) wthn the framework of olgopolstc competton n descrbng demand for dfferentated products, the unque subgame 17 Source: Cahners In-Stat Group, DRAM Market Forecast Detaled Update, 2000.

23 Measurng the Role of Technology-Push and Demand-Pull 105 perfect Nash equlbrum of technologcal nnovaton (NETI) s derved under demand- and supply-sde constrants consderng the prces and the product attrbutes whch represent frms technologcal nnovatons. Our key nsght s that the margnal prces of products are the major factor n determnng the prncpal forces of technologcal nnovaton between technology-push and demand-pull. The emprcal results from the global DRAM market show the L-shaped curves descrbng technology-push s greater than demand-pull n the early perods of a technology s lfe and decreases wth the evoluton of the lfe cycle. All the DRAM generatons n our emprcal analyss shows that technology-push s greater than demand-pull n the early stage and decreases over the course of tme. In addton, the ntensty of technology-push n the early stage becomes magnfed wth the ntroducton of new generatons and the ncrease of competton. These fndngs are mportant n several aspects. Frst, the results gve possble answers for the long dspute over the source of techncal changes and ts role n economc growth. Economsts have long argued about the role of demand and supply n nducng technologcal nnovaton. Our fndngs suggest that the role of supply and demand s dfferent n nducng technologcal change and ther relatve mportance changes over technologcal lfe cycle wth an L-shape curve. Secondly, we provde, to our knowledge, the frst ntegrated model regardng the role of supply and demand n nducng technologcal nnovaton. There have been many attempts to examne the role of supply and demand n nducng technologcal nnovaton snce Schumpeter frst publshed hs central wrtng on nventon and nnovaton. However, those attempts have been lmted to the onesded role of supply or demand, wthout any ntegrated model and correspondng emprcal examnaton. In ths paper, we also emprcally verfy the nteractve relatonshp between the two roles of nnovaton sources. Thrdly, these fndngs gve us mportant polcy mplcatons regardng R&D nvestment. R&D nvestment n basc technology s dstngushed by hgh rsk so that governments have been major sources of supply-push nvestment. However, governments need to pay attenton to demand-pull polces. These polces can nclude support for the commercalzaton of specfc technologes and the related product markets, as well as nvestment n the early stages of technology development. In the case of publc goods markets, such as energy technology, envronmental technology, and telecommuncaton networks markets, frms generally face dffcultes n successful commercalzaton of technology resultng n market falure. Therefore, governments need to ntervene n these markets for socal welfare reasons. However, demand-pull polcy has been a mnor ssue n government polcy makng because

24 106 Journal of Appled Economcs ts role and mpact on technology nnovaton has not been fully understood. Our fndngs llumnate the mportant role of demand pull, so governments need to have dynamc polces for ndustres and frms dependng on the stage of the technology lfe cycle. On the other hand, there are lmtatons n our model. Our model s developed under the assumpton of olgopolstc competton n whch Schumpeter s Mark II s domnant. Therefore, the model has some lmtatons n the case of Mark I condtons where small frms preval. In future research, the assumptons of our model wll be relaxed encompassng varous market condtons. For example, we can extend our model to monopolstc and compettve markets. We can also explore a model n whch margnal cost depends on nnovaton, or fxed costs depend on R&D. We also need to apply the model to other durable goods markets, such as computer and related equpments, telecommuncaton applcatons, and automobles n whch consumers are more drect decson makers n purchasng behavor. In these markets, demand pull seems to play a more mportant role than n the DRAM market. We expect that we wll fnd market dependent development patterns of the relatve mportance between supply and demand n nducng technologcal nnovaton from these applcatons. Appendx A. Proof of Proposton 1 Let A be defned as Α x η x η. 2 1 Then, from the equaton (15) and (17), and usng τ the equaton (18), TP Α τ + ϖ and DP Α. The followng relatonshp between TP and DP holds: τ TP = DP + + = DP + + τ ϖ τ 1 ( ) ϖ. 1 Therefore, TP DP = τ ( ) + ϖ, where > 0 and ϖ > 0. When < 1, equaton * * * * (19) s always postve, snce τ = ( p2 p1) > 0, where p2 p1 > 0. α

25 Measurng the Role of Technology-Push and Demand-Pull 107 However, when > 1, the man dervatve of technologcal nnovaton s determned as follows; (a) DP becomes the major dervatve of technologcal nnovaton, when 1 τ ( ) > ϖ. (A1) (b) Otherwse, TP becomes the major dervatve of technologcal nnovaton. B. Proof of Proposton 2 Let A be defned as Α x η x η. Then, under the assumpton that there s no crtcal 2 1 level of demand for technologcal nnovaton (CD), ϖ = 0, equaton (15) and (17) τ become as follows: TP Α τ and DP Α ξ = A where τ = ξ. (equaton 18) The followng relatonshp between TP and DP holds: τ TP = DP + = DP + τ τ 1 ( ). 1 Therefore, TP DP = τ ( ), where > 0. Therefore, f > 1, then DP s always greater than TP. Otherwse, the stuaton s reversed. C. Proof of Proposton 3 If we defne the dfference between technology-push and demand-pull as 1 Γ TP DP = τ ( ), where > 0, we have an nverse relatonshp between Γ and. The frst-order Γ condton confrms the negatve relatonshp, where > 0 and τ > 0. = τ 12,

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