does technological convergence imply convergence in markets

Ž .Research Policy 27 1998 445–463

Does technological convergence imply convergence in markets?Evidence from the electronics industry

Alfonso Gambardella a,), Salvatore Torrisi b

a Istituto di Studi Aziendali, Facolta di Economia, UniÕersita di Urbino, Õia Santa Chiara 1, Urbino, Italyb Libero Istituto UniÕersitario C. Cattaneo, Castellanza, and IEFE, Bocconi UniÕersity, Milan, Italy

Abstract

This paper uses data on new subsidiaries, acquisitions, collaborative agreements, and patents of the largest 32 US andEuropean electronics firms during 1984–1992 to examine the relationships between technological and business diversifica-tion. We find that during the 1980s many firms focused on fewer businesses, but we find no evidence of greatertechnological focus. We argue that this is related to the fact that, in spite of technological convergence, electronics sectorsstill command highly industry- or even product-specific downstream assets. In addition, we find that business focusimproved performance, but that better performance is also associated with greater technological diversification. We discusssome interpretation of this finding. q 1998 Elsevier Science B.V. All rights reserved.

Keywords: Electronics industry; Business diversification; Technological convergence

1. Introduction

The electronics industry is a quintessential exam-ple of technological convergence—the process bywhich different industries come to share similar tech-

Ž .nological bases Rosenberg, 1976 . Technologicalconvergence in industries like office equipment,computers, telecommunications, and consumer elec-tronics has been so profound that in the 1980s manyobservers predicted that they would soon merge intoa unique sector, and that the main players in each ofthem would compete with one other.

In fact, today, the trend towards a common elec-tronics market is far from complete. For instance,telecommunications producers have not become ma-jor competitors in PCs or consumer electronics, and

) Corresponding author.

vice versa. Moreover, as we discuss in the paper,some of these firms have made considerable attemptsto cross industry borders, and failed. This is sugges-tive of the fact that the forces that drive technologi-cal convergence may not coincide with those thatdrive convergence in industries and product markets.

This paper compares the technological diversifica-tion of the largest 32 US and European electronicsfirms with the diversification of their downstreamactivities. We measure technological diversificationby the number of company patents in five sectors—computers, telecommunications equipment, elec-tronic components, other electronics and non-elec-tronic technologies. Downstream diversification ismeasured by the number of new subsidiaries and

Ž .acquisitions internal growth operations , or joint-Žventure and other collaborative agreements external

.growth operations , in the same five sectors. While

0048-7333r98r$19.00 q 1998 Elsevier Science B.V. All rights reserved.Ž .PII: S0048-7333 98 00062-6

( )A. Gambardella, S. TorrisirResearch Policy 27 1998 445–463446

the latter may well involve some R&D, they arelikely to imply greater weight on commercialisationor production, especially if compared with patents.

Our findings can be summarised as follows. Ifone looks at their internal or external growth opera-tions during 1984–1992, our companies are of fairlydifferent types. Some of them show very diversifiedinvestments. Others are very specialised, having alltheir operations in one of the five sectors. Quite afew lay in between. By contrast, the companies inour sample are much more similar if one looks attheir technological diversification. Whether highlyspecialised, very diversified, or in between, theirpatents in the 1980s tended to spread across the fivesectors.

We also compared the diversification of the ‘stock’of 1983 subsidiaries of these companies in the fivesectors with their 1984–1992 internal and externaloperations. A good number of firms exhibit invest-ments that are more focused than their 1983 sub-sidiaries, whilst only a few display more diversifiedinvestments. Some electronic companies have thusbecome more focused, a pattern common to otherindustries as well. At the same time, patent diversifi-cation has not changed between 1984–1991 and1970–1983. Even the companies that focused down-stream have maintained a certain degree of techno-logical diversification.

Finally, we performed regression analysis to ex-amine the relationships between upstream or down-

Žstream diversification and the performance sales or.profits of our companies during 1984–1992. We

found that higher performance is associated withcompanies that focused their downstream activities,and with companies that increased their technologi-cal diversification. In other words, the best perform-ing companies were those that focused on their corebusiness, but widened their technological capabili-ties. This points to an interesting mismatch betweentechnological diversification and diversification inbusiness operations.

The most natural explanation of why companiesfocused on fewer activities is that, in spite of techno-logical convergence, the downstream assets and ca-pabilities that are needed to succeed in differentmarkets have remained distinct. This is implied bythe very nature of the process of technological con-vergence. Technological convergence is prompted by

the rise of some generic technologies, which implies,by definition, that these technologies can be appliedto a wealth of different products. But this means thatthey are applicable to industries and markets thatpreserve differences in the nature of their products,in the types of clients, and therefore, ultimately, inthe types of assets, competencies and capabilitiesthat are required for commercialisation. For instance,telecommunications equipment is still sold to few

Ž .very informed buyers carriers . PCs or consumerelectronics are vast markets of anonymous, non-spe-cialised buyers, and firms have to invest in entirelydifferent commercial services and distribution sys-tems.

In this respect, our view is close in spirit to somerecent work in the literature. Christensen and Rosen-

Ž .bloom 1995 argue that the difficulties that somefirms have faced in entering new product marketshave not stemmed from a weak commitment to

Žtechnology, but from their inability or weak incen-.tives to connect to new ‘value networks’. By the

latter, they mean the set of relationships with special-ist suppliers, customers, etc., that typically surroundsthe production and commercialisation of particularproducts or types of products. In their analysis of thedisk drive industry, some firms failed to commer-cialise even important innovations simply becausethese innovations required interactions with valuenetworks with which the firms did not have estab-lished connections. And this occurred in spite of thefact that these companies had considerable techno-logical expertise.

Ž .Similarly, Khazam and Mowery 1996 haveshown that the dominant position of Intel and Mo-

Ž .torola in CISC complex instruction-set-computingmicroprocessors have hampered their ability to make

Ža timely commitment to the new RISC reduced-in-.struction-set computing technology compared with

newcomers such as Sun and MIPS which were fastin setting up many linkages with software applica-tion developers and chip manufacturers to exploitnetwork externalities and create a ‘bandwagon ef-fect’. The bottom line is that established downstreamassets and capabilities can seriously limit down-stream diversification even by firms with strongtechnological competencies.

But why did some electronics companies remaintechnologically diversified in spite of greater focus

( )A. Gambardella, S. TorrisirResearch Policy 27 1998 445–463 447

downstream? The issue is intriguing as one expectsthat technological diversification be encouraged bythe opportunities to move into different product mar-kets wherein these technologies can be applied. Inthis paper we do not answer this question, which weleave for future research. In Section 5 below, how-ever, we speculate that the accumulation of techno-logical capabilities in different areas may also beused to extract greater rents in core product marketsby creating systemically more complex products,which incorporate many technologies. This also sug-gests that the creation of systemically complex prod-ucts may not be the deterministic outcome of charac-teristics of technology, but the result of evolutionarypatterns in industry and of deliberate choices madeby firms.

The paper is organised as follows. Section 2presents a brief survey of the literature on firms’diversification, and provides some evidence of thedifficulties of electronics companies in moving intoother downstream sectors during the 1980s. Section3 describes our data. Section 4 presents our empiricalresults about the relationships between patent diver-sification and the diversification of internal and ex-ternal growth operations. Section 5 presents our re-gressions about the relationships between firm per-formance and upstream or downstream diversifica-tion. Section 6 concludes. Appendices A and Breports our classifications of patents and SIC codes.

2. Diversification, firm competencies andeconomies of scope

2.1. Recent literature on diÕersification

In recent years the economic and managerial liter-ature has paid increasing attention to diversification.This has stemmed, in part, from the observation thatsince the 1980s many companies have focused ontheir core businesses, or they have reduced theirdiversification vis-a-vis the 1960s and 1970sŽHoskisson and Johnson, 1992; Linchtenberg, 1992;

.Markides, 1995 .The literature has highlighted several factors that

affect diversification. One group of studies haspointed to factors external to the firms. For instance,during the 1960s and the 1970s antitrust policy in the

US discouraged mergers of firms in the same indus-try, while less stringent antitrust regulation in the1980s favored, along with other factors, a wave ofintra-industry diversifications via mergers and re-

Ž .structuring Schleifer and Vishny, 1991 . In addition,the increased efficiency of capital market has re-duced the advantage of large diversified firms vis-a-vis the market as a means of efficiently allocating

Žfinancial resources to different businesses Markides,.1995 . Finally, during the 1960s the market for

corporate control encouraged diversification by re-acting positively to these operations. By contrast, inthe 1980s financial markets discouraged diversifica-tion, especially unrelated diversification, while en-couraging diversification in related businessesŽ .Schleifer and Vishny, 1991 .

A second stream of the literature has focused onfirm-specific, technological and organisational deter-minants of diversification produced by economies ofscope, cognitive boundaries, and organisational iner-

Žtia Rumelt, 1974, 1995; Panzar and Willig, 1981;Teece, 1988; Montgomery and Wernerfelt, 1988;

.Pavitt, 1991; Teece et al., 1994 . These studies pointto the importance of firm-specific excess resources

Žor quasi-public inputs e.g., technology and manage-.rial skills whose markets are imperfect because of

transaction costs, externalities, and systemic com-plexity of process and product technology. The na-ture of these resources and the imperfections of theirmarkets can give rise to increasing returns to growthand diversification.

But if the quasi-public inputs are employed in anever increasing number of different businesses, theadvantages of diversification may eventually de-

Ž .crease Montgomery and Wernerfelt, 1988 . Relat-edly, managers are often over-optimistic about theirability to manage a diversified business portfolio,and on many occasions they apply the same ‘domi-nant logic’ to strategically distinct activities whichwould require somewhat different approaches. 1 Inaddition, there can be agency costs. Managers mayvalue diversification more highly than shareholders,and hence more highly than what is required for

1 Ž .Prahalad and Bettis 1986 have defined ‘dominant logic’ as‘‘the way in which managers conceptualize the business and make

Ž .critical resource allocation decisions.’’ p. 490 .


Žmaximising the value of the firm Jensen and Meck-.ling, 1976 . Finally, the costs of diversification may

increase with the spread of business for reasons likethe relative scarcity of managerial capabilities, theincreasing costs of processing information resultingfrom an increasing number of managerial layers, andthe increasing difficulty to devise efficient incentiveschemes as the scope of corporate activities widensŽsee Penrose, 1959; Williamson, 1967; Rotemberg

.and Saloner, 1994 . As a matter of fact, during the1980s diversified firms that showed poor perfor-mance reduced their diversification, and this im-

Žproved their results Hoskisson and Johnson, 1992;. 2Markides, 1995 .

This paper contributes to this second stream of theliterature by highlighting the distinction betweentechnological diversification and diversification inbusiness capabilities. The issue is important becausethere may be differences between economies of scopein technological assets and commercialisation or otherdownstream operations. Granstrand and SjolanderŽ . Ž .1990 and Patel and Pavitt 1993, 1994 , for in-stance, showed that large corporations make use anddevelop in-house capabilities in many technologies,including generic ones like mechanical engineering,chemicals, and information technology. But this doesnot elicit a corresponding degree of product diversi-fication. Particularly, Patel and Pavitt examined theUS patents of large firms. They found that theirtechnological bases, measured by patent classes, weremuch wider than their product mix. For instance,they note that large chemical and electrical firmsaccumulate more competencies in non-metallic min-erals technologies than the large firms in non-metallicminerals technologies themselves. As Patel and Pavittsuggest, this depends on systemic complexity ofprocess and product technology. As a matter of fact,these firms diversify their technology not becausethey want to enter into non-metallic mineral markets,but because research in non-metallic minerals is

2 The empirical evidence shows a bimodal distribution of re-structuring firms in the 1980s: related-diversified firms reducedtheir diversification to exploit economies of scope while unre-

Ž .lated-diversified conglomerate firms increased diversification toŽtake advantage of financial economies see Hoskisson and John-

.son, 1992 .

important for their core business—catalysis in thechemical industry, and the search for very purematerials in electronics. 3

Our analysis focuses on a group of related-di-versified firms that in the 1980s tried to diversify intechnologically connected areas. 4 But in spite of thetechnological convergence prompted by informationtechnology, these industries remained different interms of market structure and other characteristicsŽentry barriers and number of competitors, marketing

.and sales channels, etc. . The managers of somelarge firms like AT&T and IBM were probablyover-optimistic about their ability to share their tech-nological resources among apparently similar andconverging product markets, and probably tried toapply their ‘dominant logic’ to the new areas. Theyunder-evaluated the difficulties associated with thecreation of downstream assets, including the knowl-edge of customers, industry-specific trade practices,and economies of scale. In light of the many prob-lems encountered, some firms changed their strategy.They re-focused on their core business or attacked

Žnew related markets with low entry barriers e.g.,.software and on-line services , and this improved

performance. Our story is then one in which firmsare allowed to make mistakes, which they can cor-rect by learning from experience. Moreover, in theirsearch for efficiency firms have to overcome organi-sational inertia and other rigidities arising from theirexisting competencies and beliefs.

2.2. Limits to downstream diÕersification in largeelectronics firms

After AT&T’s divestiture in 1984, and the risingtechnological convergence between telecommunica-tion, computers and consumer electronics, there was

3 We thank one the referees for suggesting us this example.4 Ž .Rumelt 1974 has developed a categorical measure of diver-

Žsification which relies on the specialisation ratio, SR share of the.largest business and a relatedness ratio, RR. The latter is based

on the similarity between businesses in terms of technology,customer base and commercialisation assets. Following Rumelt’s

Ž .methodology, Markides 1995 has suggested four main diversifi-Ž . Žcation categories—Single Business SR)0.95 , Dominant 0.70

. Ž . Ž-0.95 , Related RS-0.70 and RR)0.70 and Unrelated SR.-0.70 and RR-0.70 .


a widespread belief that large firms like AT&T itselfor IBM would rapidly diversify to become globalelectronics vendors. Companies thought that theycould take advantage of the diversified technologicalcapital that they had accumulated in previous years.The reasons why they diversified their technologicalactivities in the first place are not completely clear.Most probably, system complexity and technologicalconvergence led to technological diversification irre-spective of business diversification. At any rate, inthe mid-1980s the business press and business execu-tives underestimated the limits to diversifying inrelated sectors. For instance, this led computer firms

Ž .to think that PBX private branch exchange wasgoing to be the core product of office automation,and they had to develop competencies in this areaŽ .Datamation, 15 September 1986, p. 36 . The idea ofconvergence in electronics was so popular that stan-dard textbooks in computer economics argued that‘‘Major companies such as IBM, AT&T, and ITT,already strong in one segment of the computer andcommunication industry, are clearly well placed toexpand into those sectors where new market arise,

Ž .and this they do’’ p. 268 of Gotlieb, 1985 .Technological competencies however are not suf-

ficient to enter into different market because othercomplementary assets are required, such as produc-tion facilities, marketing capabilities, sales and ser-vice networks. As obvious as it may seem, thisstatement was not appreciated either by ‘textbooks’like the one cited above, or by the companies them-selves, which, as we shall see below, attemptedwithout success to enter into these markets. Thepoint is the one noted very clearly by ChandlerŽ .1990 —‘‘the cost advantages of joint distribution orscope were reduced when products required spe-cialised facilities and skills in their marketing and

Ž .their distribution’’ p. 30 . According to Chandler inthe end of the last century, sales, installation, post-sales services and customer credit arrangements be-came more and more product-specific. The highfixed costs associated with these investments re-duced the comparative advantages of full-line whole-salers and mass retailers, and spurred the verticalintegration of large manufacturing firms.

Thus, even companies like AT&T or IBM failedto enter into computers and telecommunications, re-spectively, in spite of major attempts to do so. These

are firms endowed with large and diversified techno-logical and financial resources. If crossing industryborders proved to be difficult for them, it was un-likely to be easier for others, even though these twofirms may have suffered of organisational inertia anda lack of incentives to create the capabilities requiredby the new market as compared with newcomersŽ .Christensen and Rosenbloom, 1995 .

After its divestiture, AT&T’s top managementwas convinced that a telephone network was like abig computer, and therefore the company could eas-

Žily enter the computer market cf. Business Week, 20.January 1992, p. 36 . Diversification was pursued

through acquisitions and agreements. AT&T firstentered into a strategic alliance with Olivetti in 1984.This ended up a few years later after AT&T’scomputer division registered negative resultsŽ .Datamation, 15 June 1989, p. 84 . In 1987 AT&Tsigned an agreement with Sun Microsystems, spe-cialised in workstations. In 1991 it acquired NCR,specialised in computers, software, and informationtechnology services, and sold its 19% stake in Sun

Ž .Microsystems Financial Times, 4 June 1991, p. 17 .AT&T’s strong technological basis was comple-mented by NCR’s base of customers in the financialand retail sector. But AT&T underestimated thedifferences between computers and computer ser-vices, on the one hand, and telecommunicationsservices, on the other. For instance, it appointed asNCR’s CEO Jerre Stead, a former president of AT&T’s Global Business Communications Systems unit,with experience in PBX, wireless communicationsequipment, voice recognition and message systemsŽ .Electronic Business, May 1993, p. 35 .

AT & T had numerous sources of potentialeconomies of scope. Assets like sales services andsoftware consulting, which were employed, for ex-ample, in the PBX division, could be employed bythe computer division. However, the differences be-tween the types of customers and the specificity ofthe products reduced the importance of theseeconomies. AT&T’s capabilities in digital networktechnology had potential spillovers onto computernetwork services for the financial sector, which wasthe domain of NCR’s competencies. But the poorperformance of AT&T’s computer and InformationSystem divisions testifies the problems in combininggeneral telecommunications services with computer-


based network services and equipment. Althoughmany reasons probably explain these poor perfor-mances, the lack of economies of scope typicallyimplies that in order to succeed in new marketscompanies have to invest in assets that are specific tothem. NCR’s share of the world information technol-

Žogy industry was small only 2% in 1990—Datama-.tion, 15 June 1991, p. 12 . The market size of the

company was then not large enough to justify highfixed investments in distribution and other operationsthat were largely idiosyncratic to this business. 5

In 1995 AT&T divided its activities into threeseparate companies: AT&T Services which includes

Ž .its core business long distance network servicesand mobile telephone, AT&T Network Equipmentand AT&T Global Information Systems. AT&T’stop management has recently recognises that ‘‘syn-ergy is dead, and the concept of converging commu-nications and computer markets, which drove the

ŽNCR deal, is an illusion’’ Business Week, 2 Octo-.ber 1995, p. 28 . Probably, if NCR had remained

independent its performance would not have dif-fered. However, the separation from AT&T’s corebusiness may reduce misallocation of resources andimprove managerial efficiency of computer activi-ties.

IBM had tried for many years to enter thetelecommunications market. It first attempted to de-

Žvelop its own PBX products IBM’s PBX 170 and.3750 . In 1983 it started the acquisition of Rolm, a

PBX producer, after Mitel, another PBX manufac-turer, had failed to develop a new switch for IBM.Soon after the acquisition IBM realised that conver-gence between computer and communications tech-

Žnologies was difficult to achieve Electronic Busi-.ness, 15 June 1988, p. 63 . In 1988 it sold Rolm to

Siemens, which was interpreted as a retreat from theŽtelecommunications equipment business The Wall

.Street Journal, 14 December 1988, p. 3 . In 1985 itŽ .acquired Satellite Business Systems SBS from MCI,

one of AT&T’s main competitors. In 1986 MCIrepurchased SBS, and in 1991 IBM sold back toMCI a minority share in MCI itself. By contrast, in

5 For a discussion of different kinds of convergence in newinformation technology markets, see Greenstein and KhannaŽ .1995 .

the 1990s IBM, like most large computer firms, hasfocused on new markets such as data and voiceservices, mobile communication and multimediaŽ .Business Week, 30 October 1995, pp. 40–48 . Thehigh growth rates of these markets, and the absenceof established producers, suggest that companies likeIBM may gain markets of sufficient size to justify

Ž .large fixed investments in downstream assets thatare specific to these operations, unlike PBX whichwas a mature market with small growth rates andstiff price competition.

3. Sample and data

Our sample is composed of all the US and Euro-pean firms in computers, telecommunications, semi-conductors, and other electronic products listed in

Ž .Fortune 500 1990 classification . AT&T, which isnot listed in Fortune 500, was also included. Thirteencompanies are Europeans and 19 are from the USŽ .including one Canadian . Four companies have theircore business in telecommunications, 13 in comput-ers, three in semiconductors, and 12 in other elec-tronics.

We collected data on the number of new sub-sidiaries, acquisitions, joint-ventures, and other col-laborative agreements of these firms during 1984–

Ž1992. These data are drawn from the ARGO Agree-.ments, Restructuring and Growth Operations

database which uses information from the annualissues of Predicasts F & S Index, InternationalŽ1984–1992, Predicasts F&S Index, United StatesŽ . 61984–1992 . Predicasts reports information aboutevents concerning individual companies which ap-peared on a large set of specialised trade journals,along with a brief description of the event. Theestablishment of a new subsidiary or division, or acollaborative agreement are normally reported bysuch journals. We found a good number of suchevents for our firms, and more generally all firms inour sample appear to be well-documented.

Predicasts reports the SIC code to which the eventcan be attributed. This, along with its description,

6 ARGO database was compiled at the University of Urbinoand the University of Castellanza with the collaboration of IEFE,Bocconi University.


enabled us to classify each operation into five sectors—computers, telecommunications equipment, elec-tronic components, other electronic products, othernon-electronic products. Appendix A reports detailsof this classification. In most cases, the descriptionof the event enabled us to distinguish whether theoperation was concerned primarily with productionand commercialisation, or research. Practically allnew subsidiaries and acquisitions regarded activitiesrelated to the former. We eliminated all joint-ven-tures and other agreements concerned predominatelywith research. Thus, our external operations alsomeasure investments in downstream operations.

Event counts do not account for the importance ofthe events themselves. Thus, apart from the numberof operations, we counted the number of citations indifferent trade journals wherein the event was re-ported. Presumably, an event cited in many journalsis more important than one cited only on very specialones. The number of citations also depends on the

Ž .‘importance’ size of the firm. But the set of trademagazines from which Predicasts collects its infor-mation is large. Moreover, we are considering arange of firms that is of sufficiently large size to bemonitored systematically by the specialised press.For the same reasons, we do not think that the bias infavour of Anglo-Saxon firms vis-a-vis German orother European firms is substantial. 7

We also want to note that the use of citations toweigh the importance of business operations is anovel approach, which, to our knowledge, has neverbeen used in the literature. In fact, as we shall see inSection 4, our results do not really change when weuse citations rather than simple number counts. De-pending on the way one wants to see this, it eithersays that number counts already contain enoughinformation, or that citations are not that informative.At any rate, we think that it is worth pursuing thisapproach further, especially because the value of

7 Predicasts’ original sources also include important non-En-glish magazines and journals such as the German FrankfurtenAllgemein, the French Echo de la Bourse and the Italian Il Sole 24Ore. In the case of joint-ventures or other agreements citationsmay increase because of the importance of the partner. But this isprecisely what we want to measure. We want to distinguishwhether such an agreement is with another major firm or it is aminor one, with an unknown small company.

operations like mergers, acquisitions or agreementsare rarely available on a systematic basis, and cita-tions may be correlated with the money values in-volved.

We obtained the annual number of patents grantedto these companies in the US during 1970–1991 bytechnological classes from SPRU. We aggregated theSPRU classes into our five sectors above. Details ofour aggregation are given in Appendix A. From

Žanother Predicasts publication Predicasts Company.Thesaurus, 1983 , we obtained data on the existing

subsidiaries of our companies in 1983. This publica-tion reported the SIC codes of the subsidiaries, whichwe used to classify them in our five sectors. We used

Žthe 1983 subsidiaries to measure the stock of down-.stream activities of our companies in the five sec-

tors prior to 1984–1992.

4. Technological diversification vs. diversificationin downstream operations: empirical results

We first compared the technological diversifica-tion of our companies with the diversification oftheir internal growth operations during 1984–1992.We measured technological diversification by theHerfindhal index of their total number of 1984–1991patents in the five sectors. We defined internal growthoperations to be the number of new subsidiaries andacquisitions. Acquisitions were included because theyare a measure of internalisation of assets. We mea-sured downstream diversification by the Herfindhalindex of the total number of these operations during1984–1992 in each of the five sectors. 8

Figs. 1 and 2 show the distributions of the indicesfor patents and internal growth investments. The twodistributions have different shapes. While the patentindex distribution is skewed towards the left, the

8 As well known, the Herfindhal index is the sum over allclasses of the square of the shares of the variable. We have fiveclasses corresponding to the five sectors. The Herfindhal then

Ž . Žvaries between 0.20 max diversification, equal shares to 1 max.specialization, share of the highest sector equal to 1 . We per-

formed this and all other analyses presented in this paper by usingŽother measures of diversification as well—entropy sum of the

.logs of one over the variable in each class , and the specialisationŽ .ratio share of the highest sector . These produce very similar

results.


Ž .Fig. 1. Herfindhal index 1984–1991 patents .

Ž .Fig. 2. Herfindhal index 1984–1992 new subsidiaries acquisitions .

distribution of the index of downstream operations ismore uniform. Thus, for instance, the vast majorityof our companies have patent indices that belong to

Ž .the first class between 0.20–0.36 , and no firm hasa patent index greater than 0.56. 9 This says thatmost of the companies in our sample have a highdegree of technological diversification. By contrast,the more uniform distribution of the index for inter-nal operations suggests that the extent of down-stream diversification is more heterogeneous. Somecompanies have diversified operations, while othersshow more specialised investments. The average

Ž .patent index is 0.31 standard deviation 0.08 ,whereas the mean of the distribution for internal

Ž .operations is 0.55 standard deviation 0.25 . The

9 We also analysed the distribution of patent applications fromthe European Patent Office provided by CESPRI, Bocconi Univer-sity, Milan. The results are similar to those obtained using the USpatents of our firms.

correlation coefficient between the indices for patentsand internal operations is positive, 0.31, with stan-dard deviation equal to 0.14. Companies that aremore specialised downstream also show more spe-cialised technological operations. 10

We have also computed the distribution of theHerfindhal indices for the 1984–1992 internal opera-tions weighed by citations. We do not present thisdistribution as it is similar to the non-weighed one. Itshows that there are companies with diversified in-vestments, while others have more concentrated op-erations. The mean of the weighed distribution isslightly higher than the simple count of operations—

10 Clearly, the incentives for technological diversification aregreater if the breadth of downstream operations is greater. Forinstance, Nokia, originally a manufacturer of pulp and paper

Žproducts, has diversified into electronics since the 1960s business.and consumer electronics, mobile telephone technologies . Its

patent share in electronics technologies has then increased from27% in 1970–1983 to 51% in 1987–1991.


Ž .Fig. 3. Herfindhal index 1970–1983 patents .

Ž .Fig. 4. Herfindhal index 1983 subsidiaries .

Ž .0.61 standard deviation 0.24 . This denotes a higherdegree of specialisation, which probably arises be-cause operations in the core business of the firms area little more ‘important’, in the sense that they aremore highly publicised by the business press.

Figs. 3 and 4 compare the distribution of theHerfindhal indices of the 1970–1983 patents, and ofthe ‘stock’ of existing subsidiaries of our companiesin 1983. These are measures of their upstream anddownstream diversification in earlier periods. Thedistribution of the 1970–1983 patent indices is verysimilar to the one of the 1984–1991 patents. Techno-logical diversification has been a stable feature of thelargest electronics firms for a long period of time. 11

11 We also broke up the 1970–1983 patents into 1970–1976 and1977–1983. The distributions of the corresponding Herfindhal aresimilar. In addition, the mean of the distribution of the 1970–1983patents is very close to the one of the 1984–1991 patents—0.32Ž .standard deviation 0.09 .

The distribution of the Herfindhal indices for theŽ .1983 subsidiaries is more skewed towards the left

than the one for the 1984–1992 investments. Thus,while the extent of technological diversification hasnot changed, in the 1980s a good number of compa-nies in our sample reduced the breadth of theirdownstream operations. 12

The importance of re-focusing in the electronicsindustry is confirmed by Table 1. Table 1 ranks our

12 The mean of the indices for the 1983 subsidiaries is 0.51Ž .standard deviation 0.23. . The correlation between the Herfindhalof the 1970–1983 patents and the 1983 subsidiaries is still posi-

Ž .tive, 0.24, although its standard deviation 0.22 is higher. Weshould also mention here that one caveat in interpreting our resultsis that the SIC codes of the new subsidiaries and acquisitions arethose of their principal activity. But a certain subsidiary mayperform activities related to other sectors as well. Patents insteadare a more ‘divisible’ measure, and they track more precisely thenuances of diversification in research. As a result, we may beunderestimating the diversification of the downstream operations.

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1998445

–463

454Table 1Ž .Patterns of diversification of the largest US and European electronics firms internal growth operations ranked by Herfindhal of new subsidiaries and acquisitions

New 1983 Herfindhal Herfindhal Herfindhal Herfindhal Herfindhala bS&A Sub. new 1983 1984–1991 1970–1983 new S&A

b cS&A Sub. patents patents weighed

Siemens dd dd 0.23 0.35 0.25 0.27 0.37Ž .STC ICL dd dd 0.26 0.23 0.23 0.26 0.34

Motorola dd dd 0.27 0.30 0.22 0.22 0.27Nokia dd dd 0.28 0.27 0.39 0.57 0.27Racal dd dd 0.29 0.26 0.29 0.28 0.28Thomson dd dd 0.30 0.22 0.26 0.27 0.38CGE dd dd 0.31 0.28 0.34 0.36 0.59

Ž .GEC dd q d 0.33 0.42 0.34 0.33 0.38Ž .Philips d y dd 0.37 0.29 0.33 0.30 0.45Ž .NCR d q s 0.38 0.75 0.25 0.28 0.46

ThornEmi d d 0.40 0.45 0.31 0.44 0.29Ž .AT&T d q ss 0.41 0.93 0.23 0.23 0.53

H-P d d 0.42 0.48 0.30 0.28 0.69Ž .Raytheon d y dd 0.42 0.28 0.25 0.28 0.36Ž .Honeywell d y dd 0.48 0.33 0.27 0.26 0.55

Intel d d 0.51 0.51 0.31 0.37 0.66Ž .Olivetti m y d 0.54 0.43 0.37 0.34 0.74Ž .Ericsson m y d 0.57 0.43 0.31 0.29 0.79Ž .Digital m q s 0.58 0.82 0.28 0.33 0.48

Texas m m 0.65 0.62 0.24 0.21 0.66Ž .Wang m q s 0.66 0.78 0.31 0.26 0.67

AMP m m 0.68 0.56 0.48 0.39 0.74Ž .TRW s y dd 0.69 0.32 0.46 0.46 0.75Ž .Unisys s y dd 0.71 0.34 0.24 0.46 0.85Ž .Apple s y d 0.80 0.44 0.37 0.28 0.95Ž .IBM s y m 0.82 0.62 0.25 0.24 0.86Ž .CDC ss y s 0.85 0.70 0.38 0.27 0.90

Compaq ss ss 0.91 1.00 0.28 na 0.65Ž .Bull ss y m 0.92 0.61 0.35 0.31 0.98Ž .Northern T ss y d 1.00 0.45 0.28 0.27 1.00Ž .Zenith ss y m 1.00 0.68 0.56 0.50 1.00

Nixdorf ss ss 1.00 1.00 0.23 0.23 1.00Average 0.55 0.49 0.31 0.32 0.61SD 0.24 0.21 0.08 0.09 0.24

a1984–1992 new subsidiaries and acquisitions.bStock of 1983 subsidiaries.c1984–1992 new subsidiaries and acquisitions weighed by number of citations.

Ž . Ž . Ž . Ž .dds very diversified first class of the corresponding distribution ; dsdiversified second class ; msmedium third class ; ssspecialised fourth class ; sss very specialised.


Ž .Fig. 5. Herfindhal index 1984–1992 joint ventures and other collaborative agreements in the five sectors .

firms according to the degree of diversification oftheir 1984–1992 investments in new subsidiaries and

Ž .acquisitions counts . It also reports the four sets ofHerfindhal indices used to compute the distributionsin Figs. 1–4, and the Herfindhal for the 1984–1992internal growth operations weighed by citations. Weclassified the investments of our firms in five cate-

Ž . Ž .gories: very diversified dd ; diversified d ; mediumŽ . Ž . Ž .m ; specialised s ; very specialised ss . Very di-versified means that the Herfindhal of the invest-ments of these firms falls in the first class of the

Ž .distribution 0.20–0.36 ; the other categories accountfor each of the successive Herfindhal classes. Wealso classified the Herfindhal of the 1983 sub-sidiaries in the same five categories. One can thencompare the diversification of the ‘flow’ of 1984–1992 investments with the ‘stock’ of 1983 sub-sidiaries of our firms. 13

Quite a few firms have 1984–1992 investmentsthat are more focused than their 1983 subsidiaries.Thirteen firms had 1984–1992 investments belong-ing to a category that denotes ‘less diversification’than the class of their 1983 subsidiaries. For in-stance, the 1983 subsidiaries of Honeywell orRaytheon fell into the ‘dd’ category, while their1984–1992 investments are in the ‘d’ category. Sim-ilarly, Apple moved from ‘d’ to ‘s’ or NorthernTelecom moved from ‘d’ to ‘ss’. By contrast, only

13 The majority of sample firms are diversified electronics firms.Only four firms had a share of their 1983 subsidiaries outsideelectronics larger than 30%—Nokia, Raytheon, TRW and Unisys.In the period 1984–1992 these firms, except TRW, reduced theirdiversification outside electronics.

five firms had 1984–1992 investments more diversi-Žfied than their 1983 subsidiaries GEC, NCR, AT&T,

.Digital, and Wang .Finally, we compared the technological diversifi-

cation of the companies in our sample with theirexternal growth operations. We defined the latter tobe joint-ventures plus other collaborative agree-ments. As suggested earlier, we eliminated all joint-ventures or agreements that were predominately re-lated to research. As a result, this is mostly a mea-sure of external growth in downstream assets.

Predictions about the diversification of externalgrowth investments are not unambiguous. For onereason, if internal and external operations are com-plementary strategies, they will move in the samedirection. 14 Thus, if during the 1980s most compa-nies focused their internal operations, they focusedtheir joint-ventures and collaborative agreements aswell. External operations, however, are also a more‘reversible’ form of investment if compared to ac-quisitions or new subsidiaries. This is because, bycooperating with other companies, the capital that a

Žgiven company sinks in the investment vis-a-vis. Žfully internal operations is smaller other things

.being equal . Moreover, the vast literature that origi-Ž .nated with the article of Teece 1986 suggests that

collaborations enable companies to match their com-petencies and assets with the complementary re-

14 Ž . Ž .Arora and Gambardella 1990 and Malerba and Torrisi 1992discuss the complementarity between internal competencies andexternal links, respectively, in the pharmaceutical and softwareindustries.


sources of their partners. Collaborations then repre-sent a viable alternative to internal investments formoving into unfamiliar markets.

Fig. 5 reports the distribution of the Herfindhalindices of the number of 1984–1992 joint-venturesand other collaborative agreements in our five sec-tors. 15 This distribution is not substantially differentfrom that of the 1984–1992 internal investmentsŽ .Fig. 2 . This suggests that collaborative agreementshave contributed to make electronics companies morefocused. At the same time, Fig. 5 indicates that onlytwo companies have very specialised investments inexternal operations. Thus, unlike internal operations,most companies in our sample undertook joint-ven-tures and collaborations in more than one of our fivesectors. With 32 observations, it is difficult to main-tain that observed differences in our distributions arestatistically significant. Our data however are sugges-tive of the fact that collaborations may be moreresponsive than internal investments to opportunitiesfor diversification. 16

5. Diversification and performance: empirical re-sults

The discussion in Section 4 leads to a very naturalquestion—so what? After all, whether companiesfocus or diversify is relatively uninteresting unlessone can link these patterns to economic performance.In this section, we perform some regressions wherebywe attempt to correlate company performance withtheir upstream or downstream diversification.

Our sample is composed of our 32 electronicsfirms during 1984–1992. We used three measures of

15 Using citations to weigh our external operations does notchange the distribution in a significant way.

16 Olivetti for instance has diversified into mobile telecommuni-cations services by creating Omnitel, and after setting up a jointventure with France Telecom, Atlantic Bell and other telecommu-nications services providers. Similarly, in 1984 Wang Laborato-

Ž .ries computers stipulated an agreement with Mitel for jointdevelopment of data communications equipment, and initiated astrategy of diversification in telecommunications through agree-

Žments and minority participation for instance in US Satellite.Systems and Telenova .

Ž .performance: 1 the log of the sales of our compa-Ž . Ž .nies in each year—log S ; 2 their after-tax neti t

Ž .income—PROFITS ; 3 the ratio between sales andi t

employees—SLSEMP . 17 We regressed each ofi tŽ .these measures on variables accounting for: a the

extent to which the companies focused their down-Ž .stream operations during 1984–1992; b the extent

to which they focused their technological capabilitiesŽ .in the same period; c control variables.

To measure downstream focus define HSi to bethe Herfindhal index of the 1984–1992 new sub-sidiaries and acquisitions, and HS83 the Herfindhali

of the existing subsidiaries in 1983. DOWNFOCUSi

is the difference between HS and HS83 . It mea-i i

sures the extent to which our companies changed thefocus of their investments in 1984–1992 comparedto the earlier period. A positive value of this variabledenotes greater focus in 1984–1992; a negative valuedenotes an increase in diversification, and the largerthe difference the greater the extent of change in onedirection or the other. Similarly, HPAT is thei

Herfindhal of the 1984–1992 patents of our compa-nies, and HPAT83 is the Herfindhal of the 1970–i

1983 patents. TECHFOCUS , the difference betweeni

HPAT and HPAT83 , measures the change in tech-i i

nological focus during 1984–1992.Our control variables are the following.Ž .i The log of the number of employees of our

Ž .companies in 1983—log EMP83 . This controls fori

the size of the firm.Ž .ii Time dummies to account for time-specific

factors.Ž .iii A dummy variable for the US companies,

DUS , and dummies for companies whose core busi-i

ness is in telecommunications, DTEL , computers,i

DCOMPUT , electronic components, DCOMPON .i i

The US dummy accounts for differences in institu-tional conditions and other factors between US andEuropean firms. The core business dummies controlfor differences in the growth of markets and othercharacteristics of the main activity of our firms. Theregressions also include a dummy for AT&T,

17 Sales figures, profits and employees were obtained fromFortune 500 classification annual issues. We use subscript i todenote firms and t to denote time.


DATT . This accounts for the peculiar position ofi

this company, which had invested for many years ina wealth of different technologies, and only since1984 was allowed to operate in markets other thantelecommunications.

Ž .iv Finally, the regressions include HPAT83 andi

HS83 . Although these two variables are already parti

of DOWNFOCUS and TECHFOCUS, by introduc-ing them independently we are not forcing the coef-ficients of HS and HS83 and of HPAT and HPAT83to be the same. Moreover, HPAT83 and HS83 con-trol for differences in the technological and commer-cial diversification of our companies before the sam-ple period.

Thus, using a linear specification, our regressionsare of the following form

PERFORM sCONSTqa PTIME DUMMIESi t 1

qa PDOWNFOCUS qa PTECHFOCUS2 i 3 i

qa PHS83 qa PHPAT834 i 5 i

qa P log EMP83 qa PDATTŽ . i6 7 i

qa PDTELECOM qa PDCOMPUT8 i 9 i

qa PDCOMPON qe10 i i t

where PERFORM is one of our three measures ofperformance, the a’s are the parameters to be esti-mated, and e is the error term. Note that all ouri t

regressors vary only across firms. Variations overtime are captured by the time dummies. We esti-mated our equations by OLSQ using heteroskedastic

Ž .consistent standard errors Eicker–White .Table 2 presents our results. The log of sales or

the ratio between sales and employees yield similarŽ .qualitative results. The estimated coefficients of thePROFITS equation have larger standard errors, andthe R2 of this equation is smaller than in the othertwo equations. This is natural as accounting profitsare a noisy measure of performance, and they areinfluenced by accounting procedures and other prac-tices which are often uncorrelated with ‘true’ perfor-mance. Moreover, there could be differences in theway net income is computed among firms of differ-ent countries.

While the estimated coefficient of DOWNFOCUSŽis positive and statistically significant apart from the

.PROFITS equation , the estimated coefficient of

Table 2Diversification and performance—OLSQ regressions

Measures of Performance

Ž .log sales Profits SalesrEmployees

CONST 1.484 y4.337 0.472Ž . Ž . Ž .0.633 2.218 0.085

DOWNFOCUS 0.583 0.921 0.085Ž . Ž . Ž .0.152 0.620 0.015

TECHFOCUS y4.365 y3.623 y0.247Ž . Ž . Ž .0.579 1.380 0.048

HS83 y0.391 0.160 y0.085Ž . Ž . Ž .0.207 0.288 0.026

HPAT83 y1.547 y0.670 y0.146Ž . Ž . Ž .0.390 0.676 0.039

Ž .log EMP83 0.661 0.400 y0.031Ž . Ž . Ž .0.048 0.174 0.006

DATT 0.859 1.104 0.150Ž . Ž . Ž .0.201 0.422 0.025

DUS 0.162 0.396 0.028Ž . Ž . Ž .0.061 0.131 0.006

DTEL 0.120 0.375 y0.017Ž . Ž . Ž .0.094 0.186 0.010

DCOMPUT 0.310 0.368 0.034Ž . Ž . Ž .0.101 0.311 0.009

DCOMPON y0.072 0.167 y0.021Ž . Ž . Ž .0.090 0.191 0.009

No. of observations 278 278 2782R 0.768 0.225 0.618

Ž .Heteroskedastic consistent errors in parenthesis Eicker–White .All regressions include time dummies.Thirty-two firms, 1984–1992—278 observations because of miss-ing values.

TECHFOCUS is negative and significant. This saysthat the companies that focused their downstreamoperations during 1984–1992 had better perfor-mance. At the same time, better performance isassociated with companies that increased their tech-nological diversification. As many studies havenoted, quite a few companies reduced diversificationin the 1980s, and this improved their performance.But our results also suggest that if companies nar-rowed their upstream technological capabilities, theirperformance suffered. The magnitude of these effectsis not trivial. For instance, the estimated parameterof DOWNFOCUS in the log-sales equation is 0.58.From Table 1, the mean of the Herfindhal of newsubsidiaries, HS, is 0.55, and its standard deviation is0.24. Compare two companies that are identical inany respect, and with the same Herfindhal of 1983


subsidiaries, HS83. If the HS of one of the twocompanies is one standard deviation higher, the sales

Žof that company are about 14% higher i.e., 0.58.times 0.24 . Similarly, from Table 1 the standard

deviation of the Herfindhal for the 1984–1992patents, HPAT, is 0.08, and the estimated coefficientof TECHFOCUS on log-sales is y4.37. If twocompanies are identical, but now the HPAT of oneof them is one standard deviation higher, the sales of

Ž .that company are 35% smaller y4.37 times 0.08 .The effects of technological diversification can thenbe substantial.

At the same time, the estimated coefficients ofŽHS83 and of HPAT83 are negative apart from HS83

.in the PROFITS equation . This says that if during1984–1992 two companies focused their upstreamand downstream operations to the same extent, then,all else held constant, if one company was morediversified in the past, whether upstream or down-stream, it showed higher performance. The positiveeffect of technological diversification simply con-firms the earlier result. Technologically diversifiedcompanies perform better, and this was true in1984–1992 as well as in earlier periods. But thedifference in the effects of downstream diversifica-tion during 1984–1992 and in the earlier period isworth noting. One interpretation is the following.During the 1980s, many companies were over-di-versified, and this explains why greater downstreamfocus improved performance. Yet, in the long-runŽ .related diversification remains a profitable strategy.Thus, companies that have been diversified for along time show better results. This is the Chandlerianview of the firm: Greater benefits accrue to compa-nies that have benefitted for a long time fromeconomies of scale and scope.

Put differently, this says that the opportunitiesassociated with diversification do not arise in a shortperiod of time, and indeed they take longer to mate-rialise than the opportunities associated with techno-logical diversification. This is related to our discus-sion about the difficulties of moving into manyunfamiliar markets because of the specialised assetsand capabilities that are required in each of them.Thus, the companies that were already diversifiedbefore the 1980s obtained greater benefits from tech-nological diversification because they already hadthese complementary assets and capabilities, and they

benefitted more effectively from the economies ofscope generated by technological convergence.

A related interpretation of the opportunities asso-ciated with technological diversification is that notonly may different technologies be used to enter intodifferent markets, but also to improve the existingproducts of the companies. This would explain whycompanies may benefit from technological diversifi-cation in spite of the fact that they do not augmenttheir downstream diversification in the short run.

Ž .Granstrand and Oskarsson 1994 provide interestingevidence of this phenomenon. They first classifiedthe technologies and the engineering competenciesthat were necessary to develop certain types of elec-tronics products in well defined classes. They thenshowed that the technology of cellular phonesevolved from the use of technologies in five classesand one engineering competence to 14 technologiesand four engineering competencies. Similarly,telecommunications cables used five technologiesand three engineering competencies during the early1980s vs. 10 and later four in the decade. Mostnotably, they document similar patterns in productsthat are not commonly thought to be very high-tech.For instance, the refrigerators of the late 1970s usedtechnologies in five classes and two engineeringcompetencies. The latest technology of refrigeratorsin the 1980s used technologies in seven classes, andfive engineering competencies—e.g., today’s refrig-erator employ technologies like voltage transforma-tion technologies, digital processing, digital sensors,or digital switching.

6. Conclusions

ŽThis paper used data on the internal new sub-. Žsidiaries and acquisitions and external collaborative

.agreements growth operations of the largest 32 USand European firms in the electronics industry. Wefound that during the 1980s many of this companieshave focused on fewer industries, while preserving ahigh degree of technological diversification. More-over, consistently with previous work in the litera-ture, we found that greater focus in business opera-tions improved performance. However, we also foundthat performance is positively correlated with techno-logical diversification.


We suggest that the idiosyncratic nature of thedownstream assets that are required in the differentelectronics markets have played an important role inpreventing extensive diversification, in spite of tech-nological convergence amongst many electronicssectors. But the reason why these companies re-mained technologically diversified, and why techno-logical diversification improves performance remainsan open one. We speculated that the inability offirms to move across downstream sectors may haveencouraged them to embody different technologies inthe product markets wherein they were already oper-ating. This would explain, for instance, the observedincreased in technological complexity of many elec-tronics products.

Acknowledgements

This work is part of the activities conducted atIEFE, Bocconi University, Milan, within the EC

ŽHuman Capital and Mobility Program Contract.N.ERBCHRXCT920002 . We thank SPRU, Univer-

sity of Sussex, Brighton, and CESPRI, Bocconi Uni-versity, Milan, for supplying us with the data on USpatents and European patents, respectively. Earlierversions of this paper were presented at four semi-nars at Stanford University, University of BritishColumbia, Vancouver, University of Reading andPolitecnico of Milan. We wish to acknowledge thecomments of participants at these seminars. We alsoacknowledge financial support from the Italian Na-

Žtional Research Council CNR-Committees 10 and. Ž11 and MURST Ministry of University and Scien-

.tific and Technological Research . Iolanda Schiavoneand Stefania Trenti provided valid research assis-tance. Finally, two anonymous referees have pro-vided helpful comments and suggestions to a previ-ous version of the paper.

Appendix A. Concordance between technologicaland industry classification

This work utilises data on patents granted by theUS Department of Commerce, Patent and Trademark

.Office , and classified according to the 1990 USŽ .Patent Classification USPC . We obtained these data

Ž .from the Science Policy Research Unit SPRU ,

University of Sussex. SPRU organised US patents in99 technological classes, including 13 classes whichrepresent the bulk of electrical and electronic tech-

Ž .nologies: telecommunications SPRU class 73 , radioŽ . Ž .communications 74 , other communications 75 ,

Ž .computing and office equipment 85 and 87 , semi-Ž .conductors 82 , television, faxes and other image

Ž .processing technologies 77 , sound technologiesŽ . Ž . Ž .78 , electrical devices 79 , electric motors 80 ,

Ž .illumination 81 , electricrelectronic instrumentsŽ . Ž .83 and other instruments 84 .

We grouped these 13 classes into five macroclasses: telecommunications equipment, computersand office equipment, semiconductors, other elec-tronics technologies and non electronics technolo-gies.

Table 3 reports the concordance between ourclassification, SPRU classification and the three digitUSPC. The table also shows the concordance be-tween patent classes and the SIC industrial classesthat we used to classify subsidiaries and firm growthoperations. Data on granted patents are more reliablethan patent applications, although there is an averagelag between application and grant of about 18 monthsthat may produce an underestimation of emergingtechnologies.

As illustrated by Table 3, some USPC classeswere classified in two or more SPRU classes. This is

Ždue to the fact that different sub-classes four digit.and more of the same three digit USPC class were

assigned to different SPRU classes. For instance, USŽ377 class was separated in subclass 377.105 field

.effect transistor , assigned to SPRU class 82, sub-Žclass 377.001 applications: counting means or cir-

.cuits , assigned to class 83, and subclass 377.027ŽSystems: circuitry with more than a counter or a

.shift register, etc. , assigned to class 85.The concordance and classification criteria show

some minor problems which however should notaffect significantly our results. For instance, USPC

Žclass 360 dynamic magnetic information storage or. Žretrieval is classified in SPRU class 77 television,

.fax and other image processing rather than SPRUŽ .classes 82 or 85 semiconductors and computers .

ŽSimilarly, USPC class 357 active solid-state de-.vices, including transistors and solid state diodes is

not included in any of the 13 electronics SPRUclasses.


Table 3Concordance between technological and industry classes

USPC classes Class description of technology SPRU classes

( )1 Telecommunications178 Telegraphy 73179 Telephony 73333 Wave transmission lines and networks 73367 Communications, electrical: acoustic wave system and devices 73370 Multiplex communications 73375 Pulse or digital communications 73379 Telephonic communications 73455 Telecommunications 73342 Communications, directive radio wave systems and devices 74343 Communications, radio wave 74174 Electricity, conductors and insulators 75200 Electricity, circuit makers and breakers 75335 Electricity, magnetically operated switches, magnets and electromagnets 75337 Electricity, electrothermally or thermally actuated switches 75340 Communications, electrical 75363 Electric power conversion systems 75

( )2 Computers and office equipmentŽ .235 Registers part only 85

341 Coded data generation or conversion 85364 Electrical computers and data processing systems 85365 Static information storage and retrieval 85371 Error detectionrcorrection and fault detectionrrecovery 85

Ž395 Information processing system organisation artificial intelligence, digital 85.processing

400 Typewriting machines 87

( )3 Semiconductors307 Electrical transmission or interconnection system 82

Ž .257 Active solid-state devices e.g., transistors and solid-state diodes 82377 Electrical pulse counters, pulse dividers or shift registers: circuits and systems 82437 Semiconductor device manufacturing: process 82

( )4 Other electronics345 Selective visual display systems 77

Ž348 Television generating, processing, transmitting and displaying a sequence 77.of imaging

358 Pictorial communication, television 77360 Dynamic magnetic information storage and retrieval 77382 Image analysis 77430 Radiation imagery chemistry-process, composition or product 7784 Music 78181 Acoustics 78369 Dynamic information storage or retrieval 78381 Electrical audio signal processing and systems, and devices 78328 Miscellaneous electron space discharge device systems 79329 Demodulators 79330 Amplifiers 79331 Oscillators 79332 Modulators 79334 Tuners 79336 Inductor devices 79338 Electrical resistors 79


Ž .Table 3 continued

USPC classes Class description of technology SPRU classes

( )4 Other electronicsŽ .339 Electrical connectors electrically conducing joints between conductors and electr. 79

361 Electricity, electrical systems and devices 79392 Electric resistance heating devices 79439 Electrical connectors 79290 Prime-mover dynamo plants 80310 Electrical generator or motor structure 80318 Electricity, motive power systems 80322 Electricity, single generator systems 80323 Electricity, power supply, or regulatory systems 80388 Electricity, motor control systems 80313 Electric lamps and discharge devices 81314 Electric lamps and discharge devices, consumable electrodes 81315 Electric lamps and discharge devices, systems 81362 Illumination 81445 Electric lamp or space discharge component or device manufactured 81324 Electricity, measuring and testing 83346 Recorders 83368 Horology: time measuring systems and devices 83377 Electrical pulse counters, pulse dividers or shift 83378 X-ray or g-ray systems or devices 83380 Cryptography 8333 Geometrical instruments 8473 Measuring and testing 84116 Signals and indicators 84177 Weighing scales 84352 Optics, motion pictures 84353 Optics, image projectors 84356 Optics, measuring and testing 84

Ž .359 Optics: systems including communication and elements 84374 Thermal measuring and testing 84

( ) ( )5 Non-electricalrelectronic technologies all remaining technologiesŽ .Industries SIC classes

Ž .1 Telecommunications equipment and servicesŽ3661 to 3669 telephone and telegraph apparatus, radio and television broadcasting and communication equipment,

.communication equipment NECŽ4800, excluding 4830 and 4843 telephone communications, telegraph communications and satellite communications,

.excluding satellite TV communicationsŽ .2 Computers and office equipment, and computer software and services

Ž .3571 to 3579 computers and office equipmentŽ .7371 to 7379 computer programming, data processing and other computer related services

Ž .3 SemiconductorsŽ .3670 integrated and hybrid circuits, transistors, diodes etc.

Ž .4 Other electronicsŽ .3500 machinery ex electric, including industrial robots

Ž .3600, excluding 3660 and 3670 electrical and electronic equipment, excluding telecommunications equipment and electronic componentsŽ .3810 to 3870 instruments and related products engineering and scientific instruments

Ž .5 Other industriesAll industries not included in classes 1 to 4

Sources: US Department of Commerce, Patent and Trademark Office, various years, Classification office, US patent classificationdefinitions, Washington, DC; Executive Office of the President, Office of Management and Budget, 1987, Standard Industrial ClassificationManual, 1987, Springfield, Virginia.


Appendix B. List of firms in sample by nationalityand 1983 core business

TLC s Telecommunications equipment androrservicesCMPsComputers and office equipment, includ-ing computer software and servicesSEMsSemiconductorsOELsOther electronicsNONELsNon electronic sectors

Ž .American Telephone and Telegraph US–TLCŽ .Amp US–SEM

Ž .Apple Computers US–CMPŽ .Bull France–CMPŽ .CGE France–TLC

Ž .Compaq Computers US–CMPŽ .Control Data US–CMP

Ž .Digital Equipment US–CMPŽ .GEC UK–OEL

Ž .Hewlett-Packard US–OELŽ .Honeywell US–CMP

Ž .IBM US–CMPŽ .Intel US–SEM

Ž .LM Ericsson Sweden–TLCŽ .Motorola US–CMP

Ž .NCR US–CMPŽ .Nixdorf Computers Germany–CMP

Ž .Nokia Finland–NONELŽ .Northern Telecom Canada–TLC

Ž .Olivetti Italy–CMPŽ .Philips Netherlands–OEL

Ž .Racal Electronics UK–TLCŽ .Raytheon US–NONELŽ .Siemens Germany–OEL

Ž .STC UK–CMPŽ .Texas Instruments US–SEM

Ž .Thomson France–OELŽ .Thorn Emi UK–OEL

Ž .TRW US–NONELŽ .Unisys US–NONEL

Ž .Wang Laboratories US–CMPŽ .Zenith Electronics US–OEL

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