An Analysis of the Relationship between Product Diversification, … · 2005. 7. 22. · diversification, or they concentrate on input diversification, e. g. technological diversification,

Discussion Paper on International Management and Innovation Michael Stephan1

An Analysis of the Relationship between Product Diversification, Geographical Diversification and Technological Diversification

Discussion-Paper 02-02 Stuttgart, December 2002 ISSN 1433-531X

1 Dipl.-oec. Michael Stephan, Center for International Management and Innovation. Contact: Department of

International Management (510K), University of Hohenheim, D-70593 Stuttgart, Tel: ++49-711-459-3761, Fax: ++49-711-459-3446, E-mail: [email protected]

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Abstract

Building upon a firm-level empirical investigation we conduct a phenomenological analysis of

corporate diversification patterns. We take up a more holistic, multilevel approach towards

corporate diversification: In our investigation we capture diversification at the output level, at

the input level, and at the geographical market level and analyze the relationships between

the individual dimensions. The analysis is based on a study of trends in corporate diversifi-

cation over a fifteen years period ranging from 1983 to 1997. Our sample comprises 46 mul-

tinational corporations headquartered all over the triad countries. Based on our three-dimen-

sional view of diversification, we set up three propositions on the relationships between the

individual diversification strategies. We then test the correlations between these diversifica-

tion strategies and derive different phenotypes of corporate diversification. Each phenotype

is characterized by a distinctive corporate diversification pattern. From a dynamic perspective

these phenotypes translate into paths of evolution of corporate diversification patterns. It can

be shown, that there are several homogenous groups of sample companies with similar

corporate diversification patterns and similar paths of evolution.

Keywords:

Product Diversification

Technological Diversification

Geographical Diversification

Growth Strategies

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Introduction

The world’s largest multinational corporations are actively engaged in a multitude of busi-

nesses and usually manage a broad spectrum of technological resources. In contrary to in-

ternational diversification and product diversification, the latter phenomenon - technological

diversification - has attracted comparatively little attention in management research (Breschi,

Lissoni, and Malerba, 1998). A few empirical studies have come to the conclusion that tech-

nological diversification had been on the rise in the 1970s and 80s (Fai, 1999; Granstrand

and Oskarsson, 1994; Kodama, 1995; Oskarsson, 1993). This increase has been observed

at corporate level across all industries and across all triad countries. Various empirical inves-

tigations in international management research have revealed that most of the multinational

corporations have further increased the geographical range of their business activities during

that period of time. However, and most interestingly, at the same time numerous studies

have revealed that product diversification has been declining during the same period of time

(e.g. Markides, 1996). Common to most of these studies is that they take up a partial view on

corporate diversification. Product diversification, technological diversification and geographic

diversification have usually been analyzed separately as distinctive phenomena or alternative

routes to growth. Studies either focus on output diversification, i. e. product or business

diversification, or they concentrate on input diversification, e. g. technological diversification,

or they analyze international diversification, i. e. geographical diversification. Only a few

studies in the international and strategic management disciplines have tried to take up at

least a two-dimensional view of corporate diversification. Beyond these two-dimensional

approaches there exists no detailed multilevel-analysis of the corporate diversification phe-

nomenon.

This paper tries to overcome this deficiency and takes up a more holistic, multilevel ap-

proach. In our empirical investigation we will capture both diversification at the output level,

at the input level and at the geographical level. Building upon a corporate-level empirical in-

vestigation we conduct a phenomenological analysis of corporate diversification patterns.

The analysis is based on a study of trends in corporate diversification over a fifteen years

period ranging from 1983 to 1997. Our sample comprises 46 multinational corporations

headquartered all over the triad countries. Based on our three-dimensional view of diversifi-

cation, we set up three propositions on the relationships between the individual diversification

strategies. We then test the correlations between these diversification strategies and derive

different phenotypes of corporate diversification. Each phenotype is characterized by a

distinctive corporate diversification pattern. From a dynamic perspective these phenotypes

translate into paths of evolution of corporate diversification patterns. It can be shown, that

there are several homogenous groups of sample companies with similar corporate diversifi-

4

cation patterns and similar paths of evolution. Furthermore, most of the diversification

patterns change only gradually over time.

The paper is organized according to the following plan. The first section gives an overview of

the relevant strands of literature that incorporate more holistic, two-level perspectives on

corporate diversification and address the relationship between different diversification di-

mensions. In the following we set up the resourced-based framework on the relationship

between product diversification, technological and international diversification strategies. The

resource-based framework incorporates three theoretical propositions about the relationships

between each of the dimensions. The next section introduces our empirical data and

discusses the methodology that we have employed in capturing corporate diversification. In

addition we present the recent trends in product diversification, technological diversification,

and geographical diversification of the sample companies. We then present the results of the

correlation analysis and test our propositions. Building upon the empirical results we derive

different phenotypes of corporate diversification patterns. We conclude the paper with an

illustration of the individual paths in the evolution of the corporate diversification patterns.

Multilevel Perspectives on Corporate Diversification: Synopsis of the Literature

Today, the literature on corporate diversification not only covers a wide range of research is-

sues, but also represents a great variety of perspectives and disciplinary paradigms. Since

the middle of the 70s, literature on product diversification and its effect on corporate per-

formance has been a mainstay of strategic management research. The international man-

agement discipline has dealt exhaustively with the phenomenon of geographical diversifica-

tion. And lastly, technological diversification has been a primary focus for quite a number of

researchers in the technology management domain. However, most researchers have dealt

with the individual corporate diversification dimensions in an isolated way. Only a few studies

take on a more holistic, two-level perspective on corporate diversification and address the

relationship between two diversification dimensions. In the following we give a short overview

on the studies that incorporate a two-dimensional perspective.

Literature on the Relationship between Product and International Diversification

Within the plethora of strategic management literature on product diversification one can find

two types of studies that consider international diversification as a further variable. The first

category represents the majority of these studies and contains work that investigates the

combined effects of product and international diversification on firm performance. These

studies do not look directly at the relationship between product diversification and interna-

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tional diversification since the primary focus is on performance. E.g., Geringer et al. (1989)

conduct an explanatory analysis of potential links between MNCs’ performance and the di-

versification strategy and degree of internationalization which characterized their operations.

They tested their hypotheses using data on 200 of the largest MNCs in the U.S. and Europe.

The study’s results showed that in fact the degree of internationalization has an important

role in understanding performance differences among diversified MNCs. Based on a sample

of 62 MNCs Kim et al. (1989) analyzed the impact of global diversification strategy on corpo-

rate profit performance by integrating the product and the international market dimensions of

diversification. They found that integrated international and product diversification strategies

had a positive influence on firm profits growth. Sambharya (1995) examined the individual

and joint effects of product and international diversification on firm performance. In a study of

53 U.S.-based MNCs the author made the observation that both international and product

diversification strategies are not profitable by themselves. However, he found that the inter-

action effects of product and international diversification lead to a substantial increase in firm

performance. Hitt et al. (1997) tested the effects of international diversification on innovation

and performance in product-diversified firms. They suggest that product diversification posi-

tively moderates the international diversification and performance relationship. Kim et al.

(1993) analyzed the influence of global diversification and product diversification on the risk-

return trade-off, i.e., firms with high returns can have low risk (Bowman paradox). In a sam-

ple of 152 large U.S. multinationals the authors found that diversified firms can indeed

achieve a favorable risk-return performance with global market diversification.

In contrast to the work that primarily focuses on the performance effects of combined diver-

sification, the second category of research directly addresses the relationship between pro-

duct and international diversification. This limited number of studies come to a somehow

puzzling conclusion as they indicate a negative relationship between international diversifi-

cation and product diversification. E.g., Madura and Rose (1987) reported that reverse pro-

duct diversification occurred in favor of international diversification. In a study of 262 British

manufacturing firms Grant et al. (1988) reported that multinational diversity was strongly

negatively associated with product diversity. Lastly, Sambharya (1995) analyzed the rela-

tionship between product and international diversification. In his study of the combined effect

of international diversification and product diversification strategies on firm performance he

observed an inverse relationship between both diversification dimensions. Sambharya (1995)

argues that product diversification and international diversification strategies require different

types of skills and are risky, since in both strategies firms spread themselves out in terms of

product proliferation or market proliferation. According to him it is unlikely that firms would

take both risks simultaneously. Thus, MNCs that are diversified internationally are likely to be

less diversified in terms of products. Though, finally it has to be noted that, apart from the

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work of Madura and Rose (1987), none of the studies specifies the nature of the causality

between product and international diversification.

To sum it up, the strategic management literature on the combined effects of product and

international diversification on firm performance comes to the (comparatively unambiguous)

conclusion that international diversification positively moderates the relationship between

product diversification and performance. The authors from that field argue for this moderation

effect from the resource-based perspective. An integration of product and international

diversification helps firms exploit interdependencies across their businesses to achieve po-

tential scope economies. Thus, from the resource-based view of the firm, the structures and

capabilities developed to implement product diversification strategies should also help im-

plement international diversification, and vice versa. In contrast to these findings stand the

empirical observations of the authors that more directly address the relationship between

international and product diversification. These studies indicate a negative relationship be-

tween international diversification and product diversification. In opposition to the arguments

above it is argued that both diversification strategies require different types of skills and are

too risky.

Literature on the Relationship between Technological and International Diversification

The number of studies that address the relationship between technological diversification

and international diversification has been growing considerably during recent years. Most of

the contemporary research suggests that these strategies have become essentially com-

plementary to each other. As opposed to the work on the relationship between product and

international diversification the overwhelming number of studies on the relationship between

technological and international diversification also incorporate assumptions concerning the

causality between both diversification strategies. Theoretical arguments supporting the posi-

tive relationship between both diversification strategies have been advanced that suggest

two different positions: either technological diversification precedes internationalization or

internationalization precedes technological diversification. In a study of large technology-

based firms in Europe, Japan and US, Granstrand (1996) argues that in recent years a posi-

tive causation has run from technological diversification to internationalization. He hypothe-

sizes that an increase in technological activities leads to higher R&D expenditures, which can

be recovered through the internationalization of activity, serving a wider range of markets.

Especially in high-technology industries, firms operating only in domestic markets may find it

difficult and time consuming to recoup initial R&D investments. From this point of view,

international diversification of markets and activities has been found to be the main response

to a broadening of the firm’s technology base.

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On the other hand, quite a number of theoretical and empirical models conversely argue, that

international diversification precedes technological diversification. This work has been

devised of the process by which MNCs access locationally dispersed technological assets

through their international operations. The models suggest that the geographical diversifica-

tion of markets and activities has a positive influence on the firms’ innovative activities and

heavily promotes the diversification of technological activities. Mitchell et al. (1996) conduct a

study about the direction of causality between international diversification and investment in

intangible assets in the case of 239 public American manufacturing companies. The authors

find that firms increase their R&D expenditures after expanding their multinational structure,

but not vice versa. Of course, the recorded increase in R&D expenditures may be attributable

to activities that Kuemmerle (1996) terms home-base exploiting R&D activities. Home-base

exploiting R&D activities support the local adaptation of the firm’s products and do not

necessarily imply an increase in the span of technological activities and resources. Home-

base exploiting R&D activities facilitate the local exploitation of the MNCs core capabilities.

To control for this exploitative kind of technological activities, several studies directly address

the causal relationship between a firm’s internationalization of technological activities and the

degree of technological diversification. Cantwell (1995) has suggested a positive causal re-

lationship running from international networks of technological development to corporate

technological diversification. His idea is that MNCs with internationally integrated research

facilities are able to access locationally dispersed technological assets in the relevant host

countries. Hence, geographical diversification of MNCs becomes an exogenous source of

technological diversification. In a study of 24 Swedish MNCs, Zander (1997) argues likewise

that the geographical dispersion of innovative activities may come to facilitate the techno-

logical development of the firm, since the MNC can tap into alternative streams of innovation

in different centers, and integrate technologies from different national sources on an interna-

tional scale. More generally, Birkinshaw and Hood (2001) point out that growth-triggering in-

novation often emerges in foreign subsidiaries – from employees closest to innovative cus-

tomers and least attached to the procedures and politesse of the headquarters.

While most of the studies on the relationship between international and technological diver-

sification have relied on prior assumptions on the variables’ exogenity and thus provide little

evidence about the real determinants of the interrelationship between technological diversifi-

cation and geographical diversification, Cantwell and Piscitello (1997) analyzed the causal

relationship between both dimensions. In their empirical study comprising a sample of 40

U.S. and European MNCs in the 1980s, the authors come to the conclusion that the causality

between geographical and technological diversification runs in both directions. Increases in

technological competence, together with the greater dispersion across fields of technological

8

activities and across geographical sites, are likelier to be combined, and to mutually reinforce

one another. Cantwell and Piscitello (1997) argue from a network perspective and point out

that in the MNC network each affiliate specializes in accordance with the specific

characteristics of local production conditions, technological capabilities and user require-

ments. In this event international diversification of (technological) activities and technological

diversification (competence creation) become interconnected and thus mutually positively

related parts of a common process. Supplementary to these results, Cantwell and Piscitello

(1999a) found that there is a trade-off between geographical complexity and technological

complexity in managing international networks. Firms which have developed internationally

integrated networks for technological development have tended to concentrate either on a

wider geographical dispersion of competence creation, or alternatively instead on a wider

sectoral dispersion of interrelated competencies across technical fields but in a more con-

fined set of geographical locations.

Most of the research work cited above has focused on the relationship between technological

diversification and international diversification from a quite recent perspective as they

analyzed the situation in the 80s and early 1990s. In contrast, Piscitello and Cantwell (1999)

take on a historical perspective on corporate diversification and explore the evolution of the

relationship in 166 large European and U.S. industrial firms from 1901 to 1995. They found

that only since the 1980s geographical diversification and technological diversification (com-

petence creation) have become interconnected and mutually positively related parts of a

common corporate development process. Prior to the 1980s they could not identify a positive

relationship between both strategies. According to them, in the inter-war and early post-war

periods, there was no particular linkage running from corporate technological diversification

to the internationalization of the firm’s capability. Thus, in the earlier stages of development

of large firms it is reasonable to depict technological diversification and internationalization of

markets as two alternative strategies for corporate growth. While large firms were commonly

diversifying their technological competence in the normal course of growth, their internation-

alization was aimed at the wider exploitation of the basic technological competencies and re-

sources they had already established at home rather than at extending their competencies

and resources into new fields abroad.

Literature on the Relationship between Technological and Product Diversification

Only a few theoretical and empirical studies have focused on the relationship between tech-

nological diversification and product diversification. Most authors implicitly assume that tech-

nological diversification and product diversification should be intrinsically linked (Stephan,

9

2001). Pioneering insights into the phenomenon of technological diversification in multi-busi-

ness corporations beyond such basic assumptions have been contributed by Kodama

(1986), Pavitt et al. (1989) and Granstrand and Sjölander (1990). They have shown that to-

day the world’s largest multinational corporations are not only actively engaged in a multitude

of businesses but also manage a broad spectrum of technological resources. Subsequently,

a few empirical studies have come to the conclusion that technological diversification in

multi-business corporations had been on the rise in the 1970s and 80s (Fai, 1999;

Granstrand and Oskarsson, 1994; Kodama, 1995; Oskarsson, 1993, Sjölander and Oskars-

son, 1995). This increase has been observed at corporate level across all industries and triad

countries.

Fai and Cantwell (1999) as well as Fai (1999) have analyzed the development of the rela-

tionship between technological diversification on the one hand, and corporate growth and

product diversification on the other hand from the beginning of the last century up to the

1980s. They have shown that technological diversification was historically associated with

increases in firm size and product diversification, whereas in the 1980s it appeared that di-

versification into new technologies may or may not lead to diversification into new product

areas. Obviously there is a certain degree of decoupling of technological diversification from

product diversification and corporate growth in the 1980s. These results are in line with em-

pirical observations made by other authors who revealed that technological diversification

has been on the rise in the 1980s while during the same period (unrelated) product diversifi-

cation has been declining in many MNCs. These MNCs have refocused their business lines

and simultaneously expand the span of their technological activities (Markides, 1996; Gran-

strand and Oskarsson, 1994; Gambarella and Torrisi, 1998).

Some authors have analyzed the causality between technological diversification and product

diversification. According to Granstrand and Sjölander (1990) technological diversification

was a major determinant of corporate growth in Swedish MNCs in the 1980s. In a another

empirical study from the 1980s Chatterjee and Wernerfelt (1991) were able to explain prod-

uct diversification in the 1981-1985 period with the technology profiles of their sample com-

panies prior to 1981. There seems to be a time lag between product diversification and tech-

nological diversification steps: Companies that plan to diversify their range of businesses first

have to tap into the new technological resources that are necessary to develop new

products. Thus, technological diversification is largely determined by product diversification.

However, technological diversification steps precede product diversification (Stephan, 2002).

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The synopsis of the literature adopting a two-level perspective on corporate diversification

has revealed inconsistencies in the core results of the studies. Inconsistencies in the results

do not only appear within the individual strands of literature on the bilateral relationships but,

and even worse, also across the three two-level perspectives on corporate diversification.

These inconsistencies remain, even if we exclude the issue of causalities between the diver-

sification strategies. In the following we draw on the resource-based view of the firm and try

to resolve some of these inconsistencies.

A Resource-based Framework on the Relationship Between Product Diversi-fication, Technological and International Diversification Strategies

We start our resource-based framework with propositions about the relationship between

technological diversification and product diversification since the technology management

literature offers only little inconsistencies with regard to the core results. Although some au-

thors have observed a certain degree of decoupling between technological diversification

and product diversification in the 1980s we still propose a strong positive relationship be-

tween both diversification dimensions. We further consider a natural time lag between input

and output diversification steps. Firms from high-technology sectors that intend to diversify

their lines of businesses into more or less related areas may of course draw on their existing

resource-base to realize economies of scope, but, in addition, will have to accumulate new,

complementary technological resources that are necessary for developing new products.

Proposition 1a Product diversification and technological diversification are tightly coupled strategies to corporate growth into new fields in dynamic, technology intensive industries: Compa-nies that plan to diversify their range of businesses must tap into new technological re-sources that are necessary to develop the new products. Proposition 1b Technological diversification precedes product diversification: Companies that plan to diversify their range of businesses first have to tap into the new technological re-sources.

More or less consistent results are also presented by the contemporary research on the re-

lationship between international and technological diversification. Most of the studies in this

domain suggest that these diversification strategies have become essentially complementary

to each other. The extent to which a firm has diversified its portfolio of technological compe-

tencies and resources influences (as well as being influenced by) the extent to which those

capabilities are internationalized. Increases in technological competence, together with the

greater dispersion across fields of technological activities and across geographical sites, are

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likelier now to be combined, and to mutually reinforce one another. International diversified

firms may be better able to broaden their technological capabilities by tapping the various

technological resources available globally. At the same time, international diversification may

generate the resources necessary to sustain large-scale R&D operations that are necessary

for innovating simultaneously in multiple technological fields. The costs associated with

technological diversification can be recovered through the internationalization of activity,

serving a wider range of markets. We therefore propose a positive relationship between both

diversification dimensions.

Proposition 2 Technological diversification and international diversification are complementary ways of competence and resource building: Diversifying the technology base and expanding the geographical scope of the operations are prerequisites for corporate growth and development.

The strategic management literature on the relationship between product diversification and

international diversification has produced rather inconsistent results. The strand of literature

that deals with the combined effects of product and international diversification on firm per-

formance comes to the conclusion that international diversification positively moderates the

relationship between product diversification and performance. In contrast, studies that di-

rectly address the relationship between international and product diversification indicate a

negative relationship between international diversification and product diversification. The

results of these latter studies are somehow puzzling since they suggest that, despite a good

chance to achieve positive performance effects, firms will not risk to pursue combined prod-

uct and international diversification strategies. Furthermore, from a holistic, three-dimen-

sional perspective on corporate diversification, the proposition of a negative relationship

between product diversification and international diversification produces model inconsisten-

cies. Since we propose positive relationships on the other two bilateral diversification levels,

a negative relationship on the third level would not fit into the complete model. We thus rely

on the indications offered by the literature on the combined effects of product and interna-

tional diversification on firm performance and propose, from a resource-based view, a posi-

tive relationship between product and international diversification. An integration of product

and international diversification strategies helps firms exploit interdependencies across their

businesses to achieve potential scope economies.

Proposition 3: Product and international diversification are complementary ways to corporate growth and development. Resources and competencies developed to implement product di-versification strategies should also help implement international diversification, and vice versa.

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In the following we will test our propositions with a simple correlation analysis between the

individual diversification levels. Before we start our analysis, we shortly introduce our sample

data and the methodology used.

Methodology – Sample Selection and Data Collection

To analyze corporate diversification patterns of firms we selected 46 multinational corpora-

tions from the international R&D Scoreboard ranking of the top 300 companies by R&D ex-

penditures (random selection).2 The sample companies are headquartered in the U.S. (15),

Europe (12) and Japan (11). For each company we assembled an extensive data set cover-

ing statements about financial measures (revenues, R&D expenditures), technological re-

sources (technology portfolio), product diversification (product portfolio) and international di-

versification (geographical market portfolio) for a time period of 15 years (1983-1997) on an

annual basis. Data on product diversification and international diversification were assembled

from the annual reports and other primary company sources. Product diversification is

captured by the dispersion of the firms’ product sales across 4-digit-ISIC codes. Corre-

spondingly, international diversification is captured by the dispersion of the firms’ sales

across major regional (geographical) markets.3 In contrast to product diversification and

international diversification, a direct measure of technological resources or technological

activities of firms is not available. The approach to grasp technological diversification is to

view technology as consisting of a number of distinct ‘technological areas’ (for a similar ap-

proach see e. g. Jaffe, 1989). A multi-technology corporation will typically engage in R&D in

a number of such areas. From this perspective, technological activities can be measured by

two fundamental proxies: patents and R&D expenditures. While R&D expenditures are an

input measure, patent filings are an indicator of the firm’s innovative output (Gavetti, 1994).

The paper uses patent data to characterize the technological position of firms and to meas-

ure technological diversification.

The method of measuring technological diversification in our investigation is based on the

notion that patents are a more valid indicator to assess technological resources and activities

of firms. According to Gavetti (1994) and Pavitt (1988) we can synthesize the major advan-

tages of the use of patents as follows:

2 The R&D scoreboard is published annually by the UK Department of Trade and Industry (DTI).

13

Patent data are effective and valid measures of the technological activities of companies;

Patent data also capture technological activities that are not rooted in the formal R&D or-

ganization;

Patents offer detailed information on the relevant technological area, which is of particular

relevance in order to assess the spectrum of technological activities of companies.

However, the author is well aware that patents are far from being a perfect proxy. The con-

struct validity of the indicator is weakened by the fact that patents do not grasp technological

activities that are not characterized by technical novelty (originality). The contents validity of

patent data is impaired by the fact that the propensity to patent differs amongst technical

fields, reflecting differences in the relative importance of patenting as a protection against

imitation. In the absence of a more appropriate alternative, we believe that the granting of a

patent reflects the judgment that the applicant has the competence to improve technology in

a given field significantly.

To minimize the home country bias in comparing the technological activities of the sample

companies headquartered across the U.S., Japan and Europe, we analyze the patent filings

at the European Patent Office (see also Schmoch, 1999). The primary field of technological

activity of each patent can be derived from the International Patent Classification system

(IPC). To assess the diversity of the patent portfolios of the sample companies we have

adopted a technology-oriented classification system which has been elaborated jointly by the

German Fraunhofer Institute of Systems and Innovation Research (ISI), the French Patent

Office (INIPI) and the Observatoire des Science and des Techniques (OST). The so called

“OST/INPI/ISI”-technology classification is based on the IPC and distinguishes between 30

different fields of technology and five higher-level technology areas (see figure 1). For each

patent filing we collected information about the IPC class which was assigned by the patent

examiners at the European Patent Office and then reassigned it to the corresponding

OST/INPI/ISI-classification.

3 As alternative measures of international diversification one may use the global dispersion of firms’ assets

and international employment data. However, these indicators generally suffer from the lack of availability of firm-level data. For a detailed discussion of the scope and limits of indicators to measure the degree of internationalisation see Stephan and Pfaffmann (2001).

14

Figure 1. OST/INPI/ISI-technology Classification Defined by IPC symbol

Electrical machinery and apparatus, electrical energy

Audio-visual technology

Telecommunications

Information technology

Semiconductors

Electricalengineering

Optics

Analysis, measurement, control technology

Medical technology

Nuclear engineering

Instruments

Organic fine chemistry

Macromolecular chemistry, polymers

Pharmaceuticals, cosmetics

Biotechnology

Agriculture, food chemistry

Chemistry, Pharmaceuticals

Chemical and petrol industry, basic materials chemistry

Chemical engineering

Surface technology, coating

Materials, metallurgy

Materials processing, textiles, paper

Process engineering

Handling, printing

Agricultural and food processing, machinery and apparatus

Environmental technology

Machine tools

Engines, pumps, turbines

Thermal processes and apparatus

Mechanical elements

Transport

Space technology, weaponsConsumer goods and equipment

Civil engineering, building, mining

Mechanical engineering

I. II. III. IV. V.



Telecommunications


Semiconductors



Telecommunications


Semiconductors

Electricalengineering

Optics


Medical technology

Nuclear engineering

Instruments

Optics


Medical technology

Nuclear engineering

Instruments

Organic fine chemistry

Macromolecular chemistry, polymers

Pharmaceuticals, cosmetics

Biotechnology

Agriculture, food chemistry

Chemistry, Pharmaceuticals

Chemical and petrol industry, basic materials chemistry





Process engineering

Handling, printing







Process engineering

Handling, printing



Machine tools



Mechanical elements

Transport




Machine tools



Mechanical elements

Transport




I. II. III. IV. V.

For each sample company we compiled the technology portfolios for the three five-years pe-

riods 1983-1987, 1988-1992 and 1993-1997. The aggregated observation of five-years peri-

ods served to eliminate cyclical fluctuations in the individual firms’ patent filings. Although the

EPO database covers information about patent filings dating back to 1978, our analysis

starts in 1983. In fact, the sample of patents from 1978-1982 could be biased by the fact that

only large European firms are likely to have used the European Patent Office since its very

beginning. Figure 2 illustrates the profiles of the technology portfolios of the sample compa-

nies for the period 1993-1997 according to their ‘core’ technology fields. By employing a non-

hierarchical cluster analysis we were able to identify eight homogenous groups of companies

with similar technology profiles (“Telecom”, “Computer/Electronics”, “System Technology”,

“Automotive”, “Engines/Pumps/Turbines”, “Materials”, “Chemicals”, “Pharmaceuticals”). Each

cluster is characterized by a specific set of core technologies that the member companies

have focused on. Besides the eight clusters with homogenous technology profiles we have a

residual of companies that do not fit into any of these groups. The nonconforming companies

are grouped into the “hybrid” cluster.

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Figure 2. Technology Clusters in the Sample (1993-1997 Period)

Engineering/System Techn.

Telecom.

Computer,Electronics

Data processing,Audio-visual technologyTelecommunication Electronics

Optics,Cybernetics

Motor,Turbine

Technology

Transport

Machine Tools

ThermalProcesses,

Equipm.

MaterialsProductionTechnology

OrganicChemistry

Polymers

Pharma-ceut.

BasicChemistry

Biotech-nology

NokiaEricssonMotorolaAlcatel

PhillipsSony

MatsushitaMitsubishi

Toshiba

IBMHP

NEC Sharp

ABBSiemens

Hitachi

Kyocera

Automotive

FordGeneral Motors

ToyotaDaimler Benz

Bosch

Materials

ThyssenAlcoa

KruppSaint Gobain

Transport Techn.

PharmaGlaxo Kao

LillyPfizer

Novo NordiskRoche

Merck USA

Chemistry

BayerNovartis

Akzo NobelDow Chemical

BASFDuPontToray

Merck DGeneral Electric

Allied SignalUTC

Medical Technology

Sulzer

Johnson&Johnson

Engineering/System Techn.

Telecom.

Computer,Electronics

Data processing,Audio-visual technologyTelecommunication Electronics

Optics,Cybernetics

Motor,Turbine

Technology

Transport

Machine Tools

ThermalProcesses,

Equipm.

MaterialsProductionTechnology

OrganicChemistry

Polymers

Pharma-ceut.

BasicChemistry

Biotech-nology

NokiaEricssonMotorolaAlcatel

PhillipsSony

MatsushitaMitsubishi

Toshiba

IBMHP

NEC Sharp

ABBSiemens

Hitachi

Kyocera

Automotive

FordGeneral Motors

ToyotaDaimler Benz

Bosch

Materials

ThyssenAlcoa

KruppSaint Gobain

Transport Techn.

PharmaGlaxo Kao

LillyPfizer

Novo NordiskRoche

Merck USA

Chemistry

BayerNovartis

Akzo NobelDow Chemical

BASFDuPontToray

Merck DGeneral Electric

Allied SignalUTC

Medical Technology

Sulzer

Johnson&Johnson

Analogue to the technology portfolio we compiled the geographical market portfolios and

product portfolios for each company. To compile the geographical market portfolios we col-

lected the firms’ revenues in the major global regions. In our study, the major global regions

correspond to relatively heterogonous geographical market areas based on their economic

and political conditions. We differentiate between 6 geographical market areas. These are:

North America, Latin America, Europe, Africa/Middle East, Asia/Pacific and the individual

home country of each sample corporation. To compile the product portfolios we collected the

firms’ revenues in different ISIC classes (International Standard Industrial Classification) on a

4-digit level. Figure 3 illustrates the profiles of the product portfolios of the sample companies

for the period 1993-1997 according to their top-selling businesses. Again, by employing a

non-hierarchical cluster analysis we were able to identify homogenous clusters of compa-

nies. On the whole, we have identified ten industry clusters with more or less homogenous

product profiles: “Chemicals”, “Pharmaceuticals”; “Materials”; “Metal Products”; “Automotive”;

“Engines/Machinery”; “Diversified Electrical Engineering”, “Telecommunications”; “Consumer

Electronics”, and “IT/Computer”. Surprisingly, the product clusters only partially correspond

to the technology clusters. While some of the clusters find rough correspondents in the other

dimension, with moderate differences in terms of composition, others do not have similar

counterparts. Obviously there is a certain degree of decoupling. The phenomena of decoup-

16

ling will be picked up again when we observe the latest trends in technological diversification

and product diversification.

Figure 3. Product Clusters in the Sample (1993-1997 Period)

Divers. Electrical Engineer.Machinery&Equipm.

Telecom.

Computer

Data Processing/IT TelecommunicationsConsumer Electronics

Electrical EngineeringProducts

MechanicalEngineering

Basic Materials

Turbines,Engines,

Machinery

Basic Metals,Metal Components

Non-metallicMaterials

Agro-chemicals

Pharma-ceuticals

Chemicals

NokiaEricssonMotorola

NECSharp

HitachiMitsubishi

Auto-motive

Materials

KyoceraSaint Gobain

Pharma

Merck KgaANovartis

Chemicals

Toray

MedicalProducts

and Services

BayerBASFDow

Kao

Chemical fibres, Oil

DuPont

Akzo

J&JMerck Co.

Metal Products

Alcoa

ThyssenKrupp

Auto-motive

Allied Signal Bosch

Consumer Electr.IBMHP

SonyMatsushita

Phillips

Toshiba

Optical Products, Fine

Mechanics, White Goods

DaimlerFordGM

Toyota

GlaxoLilly

PfizerNovo Nordisk

Roche

Alcatel Siemens

GE SulzerUTC

ABB

Divers. Electrical Engineer.Machinery&Equipm.

Telecom.

Computer

Data Processing/IT TelecommunicationsConsumer Electronics

Electrical EngineeringProducts

MechanicalEngineering

Basic Materials

Turbines,Engines,

Machinery

Basic Metals,Metal Components

Non-metallicMaterials

Agro-chemicals

Pharma-ceuticals

Chemicals

NokiaEricssonMotorola

NECSharp

HitachiMitsubishi

Auto-motive

Materials

KyoceraSaint Gobain

Pharma

Merck KgaANovartis

Chemicals

Toray

MedicalProducts

and Services

BayerBASFDow

Kao

Chemical fibres, Oil

DuPont

Akzo

J&JMerck Co.

Metal Products

Alcoa

ThyssenKrupp

Auto-motive

Allied Signal Bosch

Consumer Electr.IBMHP

SonyMatsushita

Phillips

Toshiba

Optical Products, Fine

Mechanics, White Goods

DaimlerFordGM

Toyota

GlaxoLilly

PfizerNovo Nordisk

Roche

Alcatel Siemens

GE SulzerUTC

ABB

Measures and Trends in Technological Diversification (1983-1997)

In our study we understand technological diversification as the extent of the spread of the

firms’ technological activities across the 30 different fields of technology defined by the

OST/INPI/ISI-classification. As described above, these technology fields aggregate into 5

technology areas. The degree of technological diversification is captured with the entropy

measure of diversification. The single entropy measure grasps the degree of unrelated or

total technological diversification and considers the spread of the patent filings across the 30

different technology fields (i=1...N; N ≤ 30). Let Ti be the share of the ith technology field in

the total patent filings of the firm. For each sample company then the degree of unrelated

technological diversification (DT) is computed as follows:

)/1ln(1

i

N

ii TTDT ∑

=

= .

17

This measure takes into consideration two elements of technological diversification: the

number of technological fields in which a firm operates and the relative importance of each of

these fields compared to the total number of patent filings. To include the degree of re-

latedness among the various technology fields in which the firms are active, we assume that

technological activities in different technology areas are unrelated, and that technological

activities belonging to different technology fields but in the same technology area are related

(Markides 1995). Let Tij be the share of the field in technology area j in the total patent filings

of the firm. DRj is then defined as the related technological diversification arising out of the

patent filings in several technology fields within one technology area j:

∑=

=N

i ijijj T

TDR1

)1ln(

Since the firm has filed patents in several technology areas (j=1…M, ≤ 30), its total degree of

related technological diversification is equal to

∑=

=M

jjjTDTDTR

1

where Tj is the share of the jth technology area in the total patent filings of the group.

Finally, we control for technology-specific differences in the propensity to patent, caused by

differences in the relative importance of patenting as a protection against imitation, and firm-

specific differences in the propensity to patent, caused by differences in firm-size and the

country-of-origin effect, by the use of another diversification measure that is based on the

Revealed Technological Advantage (RTA) index. The RTA of a sample company in a par-

ticular field of technology is given by the firm’s share in that field of all EPO patent filings of

the sample companies, relative to the firm’s overall share of all patents filed by the sample

companies. If Pix denotes the number of patent filings of company x in technology field i, the

RTAix is then defined as:

⎟⎟⎠

⎞⎜⎜⎝

⎛=

totalx

itotalixix PP

PPRTA .

The index varies around unity, such that a value in excess of one shows that the firm is

comparatively advantaged in that technology field in relation to other firms. In this manner

technology-specific and firm-specific differences in the propensity to patent are normalized.

We have chosen to use the inverse value of a sample firm’s coefficient of variation of the

RTA index across all technology fields as the RTA-based measure of technological diversifi-

cation (RTAD):

18

( )⎟⎟⎠

⎞⎜⎜⎝

⎛=

⎟⎟⎟⎟⎟

⎠

⎞

⎜⎜⎜⎜⎜

⎝

⎛−

=

∑=

x

x

RTA

RTA

x

N

ixix

x

RTA

RTARTAN

RTADσµ

1

211

Figure 4 provides an overview of the trends in unrelated technological diversification differ-

entiated by industries of the sample companies. In the 1980s, the sample companies have

(slightly) increased their degree of (unrelated) technological diversification. However, at the

beginning of the 1990s, this trend has come to a halt. In the 1990s the sample companies

began to refocus their technology portfolios. This observation is new: In contrast to the find-

ings of prior empirical studies of previous periods, there has been a decrease in technologi-

cal diversification by more than three per cent. Figure 4 also reveals that there exist con-

siderable differences between the sample companies from different industries. Companies

from the telecom cluster have dramatically refocused their technology portfolio in the 1983-

1997 period. Like the companies from the pharmaceutical cluster, telecom firms manage a

technology portfolio that is considerably less diversified than the sample average. In contrast,

companies from the automotive, diversified electric engineering and chemicals/materials

clusters are engaged in a spectrum of technological activities that is high above the

average.4

4 There also exist regional differences in the sample. Firms from the U.S. are less diversified than firms from

Japan and Germany. On the average, U.S. firms began to refocus their technology portfolio already in the 1980s, whereas firms from Japan have still been broadening their activities during the 1990s.

19

Figure 4. Trends in (Unrelated) Technological Diversification in the Sample Differentiated by Industry Clusters

1,2

0,5

0,6

0,7

0,8

0,9

1

1,1

1993 - 19971988 - 19921983 - 1987

Divers. Electr.Engineering

Automotive

Single Entropy Measure

ConsumerElectronics

Pharma

Telecommunications

Chemicals/Materials

Metal Products/Machinery

IT/Computer

Total Sample

1,2

0,5

0,6

0,7

0,8

0,9

1

1,1

1993 - 19971988 - 19921983 - 1987

Divers. Electr.Engineering

Automotive


ConsumerElectronics

Pharma

Telecommunications

Chemicals/Materials


IT/Computer

Total Sample

Measures and Trends in Product Diversification (1983-1997)

Analogue to the measure of technological diversification, the degree of product diversification

is captured with the single entropy measure. This International Standard Industrial Clas-

sification (ISIC) based index grasps the degree of unrelated product diversification. We dif-

ferentiate between 68 industry segments that are based on 4-digit ISICs (k=1...S; S ≤ 68).

Let Pk be the share of the kth industry segment in the total sales of the firm. For each sample

company then the degree of unrelated product diversification (DP) is computed as follows:

⎟⎟⎠

⎞⎜⎜⎝

⎛= ∑

= kkk P

PDP 1ln68

1.

The entropy measure takes into consideration two elements of diversification: the number of

segments in which the firm operates and the relative importance of each of these segments

in the total sales of the firm. Figure 5 visualizes the trends in product diversification differen-

tiated by industry of the sample companies.

20

Figure 5. Trends in (Unrelated) Product Diversification in the Sample Differentiated by Industry Clusters

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

1,1

1993 - 19971988 - 19921983 - 1987

Pharma

Automotive

Chemicals/Materials

Telecom-munications

IT/Computer


Consumer Electronics

Diversified Electrical Engineering


Total Sample

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

1,1

1993 - 19971988 - 19921983 - 1987

Pharma

Automotive

Chemicals/Materials

Telecom-munications

IT/Computer


Consumer Electronics

Diversified Electrical Engineering


Total Sample

At first sight, differences between the overall trends in product diversification and technologi-

cal diversification become evident: the sample companies have constantly reduced their de-

gree of product diversification. This observation corresponds to the findings of previous em-

pirical studies: In the 1980s and 1990s, companies have been refocusing their product port-

folios. Differences in the trends by industries are even more striking. In the automotive in-

dustry cluster for example, the companies have constantly expanded their technology portfo-

lio in the 1980s and 90s. Contrary to this trend, the automotive sample companies have re-

focused their product portfolios in the 1990s. Furthermore, concurrent divergences have

been ascertained in the chemicals/materials cluster, whereas reverse divergences exist in

the consumer electronic industry cluster. Consumer electronic firms have increased the span

of their products/businesses and at the same time decreased the spectrum of their techno-

logical activities. The divergences confirm the suspicion made earlier in the paper: there ex-

ists a considerable degree of decoupling between technological diversification and product

diversification, at least in some industries.

21

Measures and Trends in International Market Diversification (1983-1997)

In contrast to the measures of technological and product diversification there is no agree-

ment among scholars in the international business domain on how to measure international

diversification (Sambharya 1995). A big variety of measures of international diversification

have been employed in previous empirical studies. A prominent and simple form has been a

unidimensional measure of international sales as a percentage of total sales (see e.g.

Geringer et al. 1989). Others have criticized using unidimensional measures, recommending

instead more sophisticated multidimensional measures (e.g. Vachani 1999 and Sullivan

1994). However, the paucity of data limits the applicability of such measures at present.

Other measures, like the ones used by Kim et al. (1989, 1993), suffer for our purposes from

the fact that they combine the product dimension and international dimension of corporate

diversification. With regard to these concerns and to achieve homogeneity in the measures

employed, we again used an entropy approach to measure the degree of international diver-

sification of our sample companies. International diversification may be defined as expansion

across the borders of countries and (global) regions into different geographic markets. Thus,

a firm’s level of international diversification is reflected by the number of different markets in

which it operates and their importance to the firm as measured, for instance, by the per-

centage of total sales represented by each market (see also Hitt et al. 1997). The entropy

measure reflects the extent of the dispersion of the firms’ sales across the major global mar-

kets. As mentioned above, we differentiate between 6 geographical market areas (m=1...R;

R ≤ 6). Let Gm be the share of the mth geographical market area in the total sales of the firm.

For each sample company then the degree of international market diversification (DG) is

computed as follows:

⎟⎟⎠

⎞⎜⎜⎝

⎛= ∑

= mmm G

GDG 1ln6

1

Again, the entropy measure takes into consideration two elements of diversification: the

number of the geographical markets in which the firm operates and the relative importance of

each of these markets in the total sales of the firm. Nearly all of the sample companies had

already globalized their businesses to a considerable degree at the beginning of the 1980s.

Nevertheless, most of the companies have further increased their degree of international

diversification during the period of investigation. Figure 6 visualizes the trends in international

diversification differentiated by home country of the sample companies.

22

Figure 6. Trends in International Diversification in the Sample Differentiated by Home Country

0,4

0,45

0,5

0,55

0,6

0,65


1993 - 19971988 - 19921983 - 1987

Japan

USA

Total Sample

Europe

Germany

0,4

0,45

0,5

0,55

0,6

0,65


1993 - 19971988 - 19921983 - 1987

Japan

USA

Total Sample

Europe

Germany

Figure 6 shows that companies have continuously increased the degree of geographical di-

versification in the 1980s and 1990s, irrespective of their country of origin. However, figure 6

also reveals that there exist considerable differences in the degree of internationalization

between the different country clusters. On average, companies headquartered in Germany

lead the pack in terms of geographical diversification, although, the degree of internationali-

zation has stagnated in the German cluster at the beginning of the 1990s as a consequence

of strong domestic growth in the course of the reunification. In contrary, companies from

Japan rank far below the sample average. Considerable differences also exist between the

industry clusters in the sample. On the average, multinational corporations from the pharma-

ceutical, telecom and machinery clusters have spread their sales more equally across global

markets than other companies –automotive companies, in particular, have focused their

sales on a limited number of core markets. Figure 7 visualizes the trends in international di-

versification differentiated by the industry clusters of the sample companies.

23

Figure 7. Trends in International Diversification in the Sample Differentiated by Industry Clusters

0,45

0,47

0,49

0,51

0,53

0,55

0,57

0,59

1993 - 19971988 - 19921983 - 1987

Automotive

Telecom

Pharma

Total Sample

Electronics

Chemistry

Computer/Electronics

Metals/Machinery


0,45

0,47

0,49

0,51

0,53

0,55

0,57

0,59

1993 - 19971988 - 19921983 - 1987

Automotive

Telecom

Pharma

Total Sample

Electronics

Chemistry

Computer/Electronics

Metals/Machinery


To sum up, this threefold, isolated analysis of recent trends in corporate diversification has

shown a considerable degree of homogeneity within the company clusters. At the same time

the analysis has also revealed considerable differences between the different diversification

levels. Obviously, these dimensions are (partially) decoupled from each other. In the follow-

ing section we will analyze the degree of decoupling more thoroughly, in order to shed some

light on the relationship between the diversification levels.

Empirical Results on the Relationship between Technological Diversification, Product and International Diversification Strategies

The results of the simple correlation analysis between technological diversification, captured

with three diversification measures, and product diversification are shown in table 1. With

highly significant correlation-coefficients amounting up to 0,615, the results strongly confirm

our proposition 1a for all three five years periods. The influence of the coefficients has

proofed to be remarkably stable over time. Furthermore, the results also confirm proposition

1b. The strongest coefficients in the matrix of table 1 suggest that there exists a time lag of at

least one period between technological diversification and product diversification: Companies

that plan to diversify their range of businesses first tap into new technological resources.

24

Table 1: Results of Correlation Analysis between Technological Diversification and Product Diversification (1983-1997)

Technological Diversification Technological Diversification Technological DiversificationPeriod 1 Period 2 Period 3

Entropy Measure of

unrel.Divers.

Entropy Measure of rel.Divers.

RTA-Diver-sification Measure

Entropy Measure of

unrel.Divers.



Entropy Measure of

unrel.Divers.



Product Div. 0,4158 -0,0047 0,5476 0,3354 0,0647 0,5732 0,2108 0,0102 0,471Period 1 [**] p=0,0041 [ns] p=0,9751 [***] p=0,0001 [*] p=0,0227 [ns] p=0,6693 [***] p=0 [ns] p=0,1597 [ns] p=0,9466 [***] p=0,001

Product Div. 0,467 0,0459 0,55 0,4214 0,1398 0,615 0,319 0,1071 0,5311Period 2 [***] p=0,0011 [ns] p=0,7617 [***] p=0,0001 [**] p=0,0035 [ns] p=0,3542 [***] p=0 [*] p=0,0307 [ns] p=0,4789 [***] p=0,0001

Product Div. 0,4226 0,0469 0,4813 0,4529 0,1936 0,6016 0,4152 0,2247 0,5522Period 3 [**] p=0,0034 [ns] p=0,7571 [***] p=0,0007 [**] p=0,0016 [ns] p=0,1974 [***] p=0 [**] p=0,0041 [ns] p=0,1333 [***] p=0,0001

In contrast to propositions 1a and 1b, the correlation analysis between international diversifi-

cation and technological diversification does not support our proposition 2. Proposition 2 on

the relationship between technological diversification and international diversification has

been rejected. With even negative values of the correlation coefficients across all diversifica-

tion measures it is clearly indicated that for our sample companies international diversifica-

tion and technological diversification are not complementary strategies, as suggested by

contemporary international management research. Diversifying the technology base and ex-

panding the geographical scope seem to be substitutes rather than complements to corpo-

rate growth and development. The result supports the findings of Cantwell and Piscitello

(1999a) who suggested that there is a trade-off between geographical complexity and tech-

nological complexity in managing international networks. Firms which have developed inter-

nationally integrated networks have tended to concentrate either on a wider geographical

dispersion of competence creation, or alternatively instead on a wider dispersion of compe-

tencies across technology fields but in a more confined set of geographical locations. A sup-

plemental explanation could be that at least some of the sample companies already had the

advantage of having established a base level of international networks and technological re-

source base at the beginning of the period of investigation, and so were able to expand

through a restructuring of their international networks, which took the form of concentrating

more specialized lines of activities in each major center in accordance with their respective

comparative advantages.

25

Table 2: Results of Correlation Analysis between Product Diversification and Geographical Diversification (1983-1997)

Product DiversificationPeriod 1 Period 2 Period 3

Entropy Measure of unrel. Divers.



Geogr.Div. -0,0644 0,0048 -0,0304Period 1 [ns] p=0,6707 [ns] p=0,9748 [ns] p=0,8412

Geogr.Div. -0,0609 -0,0308 -0,0728Period 2 [ns] p=0,6875 [ns] p=0,8391 [ns] p=0,6309

Geogr.Div. -0,0168 -0,0149 -0,0324Period 3 [ns] p=0,912 [ns] p=0,9216 [ns] p=0,8306

Finally, the data in table 3 on the relationship between product diversification and interna-

tional diversification does not hold our proposition 3. For all three periods the analysis pro-

duced insignificant correlations with coefficients ranging around zero. These results indicate

that there seems to be no significant relationship between international diversification and

product diversification. Obviously our sample companies view product diversification and in-

ternational diversification strategies as independent ways to corporate growth and develop-

ment. This is in line with the view that product diversification and international diversification

strategies require different types of resources and competencies. Resources and competen-

cies developed to implement product diversification strategies are not directly intended to

implement international diversification, and vice versa.

Table 3: Results of Correlation Analysis between Technological Diversification and Geographical Diversification (1983-1997)

Technological Diversification Technological Diversification Technological DiversificationPeriod 1 Period 2 Period 3

Entropy Measure of

unrel.Divers.



Entropy Measure of

unrel.Divers.



Entropy Measure of

unrel.Divers.



Geogr.Div. -0,2784 0,0792 -0,0045 -0,2782 -0,1222 -0,0778 -0,2119 -0,1229 -0,0736Period 1 [*] p=0,061 [ns] p=0,6007 [ns] p=0,9761 [*] p=0,061 [ns] p=0,4186 [ns] p=0,6074 [ns] p=0,1574 [ns] p=0,4157 [ns] p=0,6271

Geogr.Div. 0,2891 -0,0496 -0,0384 -0,2611 -0,1975 -0,1351 -0,2307 -0,1818 -0,1427Period 2 [*] p=0,0531 [ns] p=0,7433 [ns] p=0,8002 [*] p=0,0797 [ns] p=0,1883 [ns] p=0,3706 [ns] p=0,123 [ns] p=0,2265 [ns] p=0,3442

Geogr.Div. -0,2651 -0,0188 -0,013 -0,2396 -0,1784 -0,1075 -0,2252 -0,1652 -0,124Period 3 [*] p=0,075 [ns] p=0,9012 [ns] p=0,9317 [*] p=0,1087 [ns] p=0,2356 [ns] p=0,4769 [ns] p=0,1324 [ns] p=0,2725 [ns] p=0,4118

The results of our analysis of corporate diversification are deflating. Only one of our three

propositions has been confirmed by the empirical data. By recapitulating the results we may

conclude that our sample companies pursue different approaches with respect to the three

corporate diversification levels. Apart from a tight coupling between technological diversifica-

tion and product diversification we were not able to identify homogenous patterns across all

sample companies. In the following section we take a closer look at the individual diversifica-

tion patterns of the sample companies and try to identify different phenotypes of corporate

diversification.

26

Patterns and Phenotypes of Corporate Diversification

To identify different phenotypes of corporate diversification we merge the individual diversifi-

cation levels in a single frame of analysis. However, product diversification, technological

diversification and geographical diversification cannot be compared directly on the basis of

the entropy values. Although we have employed identical measures to calculate the degree

of input, output and regional diversification, comparability is hampered by differences in

scaling (different maximum values). This in turn is caused by differences in the underlying

classification indices (ISIC vs. OST/INPI/ISI vs. geographical market areas). To bypass the

‘apples and oranges’ problem, we simply relate both the degree of product diversification, the

degree of technological diversification and the degree of international diversification of each

company to the sample average. With relational data we are able to compare technological

diversification, product diversification and international diversification within the same frame

of analysis and without biases. For the present we use a two-dimensional view on corporate

diversification to keep the analysis clear. We start with the firm-level comparison of relational

technological diversification data and relational product diversification data. Figure 8

visualizes the corporate input and output diversification patterns at the end of the

investigation period (1993-1997).

Figure 8: Phenotypes of Technological and Product Diversification (1993-1997)

-40%

-20%

20%

40%

-80% -60% -40% 20% 40% 60% 80%

Glaxo

Novo Nordisk

Eli Lilly

Kao

ToyotaFord

Roche

Pfizer

GM

Merck KgaA

Merck Co.

NokiaEricsson

Akzo

HP

J&J

Alcoa

Dow

Daimler

Novartis

Bayer

BASF

Toray

Motorola

IBM

Saint Gobain

SharpKyocera

Bosch

Allied Signal

DuPont

Sony

Sulzer

NEC

Alcatel

UTC

Phillips

Krupp

ABB

Matsushita

Siemens

Thyssen

Toshiba

Mitsubishi

GE

Hitachi

Product Diversificationin Relation to Sample

Average

Technological Diversificationin Relation to Sample

Average

-20%

Phenotype 1Diversified Technology PortfolioFocused Product Portfolio

Phenotype 2Diversified Technology Portfolio

Diversified Product Portfolio

Phenotype 3Focused Technology Portfolio


Phenotype 4Focused Technology PortfolioFocused Product Portfolio

-40%

-20%

20%

40%

-80% -60% -40% 20% 40% 60% 80%

Glaxo

Novo Nordisk

Eli Lilly

Kao

ToyotaFord

Roche

Pfizer

GM

Merck KgaA

Merck Co.

NokiaEricsson

Akzo

HP

J&J

Alcoa

Dow

Daimler

Novartis

Bayer

BASF

Toray

Motorola

IBM

Saint Gobain

SharpKyocera

Bosch

Allied Signal

DuPont

Sony

Sulzer

NEC

Alcatel

UTC

Phillips

Krupp

ABB

Matsushita

Siemens

Thyssen

Toshiba

Mitsubishi

GE

Hitachi


Average


Average

-20%







27

The comparison of technological diversification and product diversification enables us to de-

rive a typology of four different phenotypes of input-/output-diversification (IO). Each IO-phe-

notype is characterized by a specific pattern of corporate diversification.

IO-Phenotype 1 is characterized by a focused product portfolio and by a diversified tech-

nology portfolio: this pattern is symptomatic for companies with complex products, for in-

stance in the automotive industry. Companies like GM or DaimlerChrysler (Daimler Benz)

have (re)focused their product portfolios and have outsourced significant proportions of

their production to external suppliers, while they simultaneously maintain a diversified

technology base in-house.

IO-Phenotype 2 exhibits both a broadly diversified product and a broadly diversified tech-

nology portfolio. The link between the technology and product base is complex: Diversified

electronic and machinery companies like GE, Siemens, Hitachi, UTC, ABB or Mitsubishi

Electric are engaged in a large number of product fields, with varying degrees of techno-

logical relatedness. At the same time, the companies use their broad spectrum of tech-

nologies in a variety of different businesses.

IO-Phenotype 3 is defined by a quite narrow technology portfolio and a diversified product

base: This pattern is symptomatic for companies following a ‘technology based’ product

diversification strategy. Companies, such as Sony or Philips in the consumer electronics

industry, use their generic technological resource base to develop new products for a va-

riety of markets.

IO-Phenotype 4 is characterized by focused technology and product portfolios: This pat-

tern is typical for companies from the pharmaceutical cluster. Almost all pharmaceutical

companies in the sample have focused on the drug business and divested other business,

like chemicals, agro and food. At the same time they have concentrated their activities on

a few related technology fields, such as organic chemistry, pharmaceutical technologies

and biotechnologies.

Analogue to the analysis of the input/output diversification patterns in the sample we can now

investigate the relationship between geographical and product diversification diversification

(GO). Figure 9 visualizes the corporate product and geographical diversification patterns at

the end of the investigation period (1993-1997).

28

Figure 9: Phenotypes of Corporate Product and Geographical Diversification (1993-1997)

-40%

-20%

20%

40%

-80% -60% -40% 20% 40% 60% 80%

GlaxoNovo

Nordisk

Eli Lilly

Kao

Toyota

Roche

Pfizer

GM

Merck KgaA

Merck Co.

Nokia

Ericsson

Akzo HP

J&JAlcoa

Dow

DaimlerNovartis

Bayer

BASF

Toray

Motorola

Saint Gobain

Sharp Kyocera

Bosch

Allied Signal

DuPont

Sony

Sulzer

NEC

Alcatel

UTC

PhillipsKruppABB

Matsushita

Siemens

Thyssen

Toshiba

Mitsubishi

Hitachi

Product Diversi-fication in Relationto Sample Average

Geographical Diversificationin Relation to Sample

Average

-20%

Phenotype 1Diversified Geo. PortfolioFocused Product Portfolio

Phenotype 2Diversified Geo. Portfolio


Phenotype 3Focused Geo. Portfolio


Phenotype 4Focused Geo. PortfolioFocused Product Portfolio

Ford

GE

IBM

-40%

-20%

20%

40%

-80% -60% -40% 20% 40% 60% 80%

GlaxoNovo

NordiskNovo

Nordisk

Eli LillyEli Lilly

KaoKao

ToyotaToyota

RocheRoche

PfizerPfizer

GMGM

Merck KgaAMerck KgaA

Merck Co.Merck Co.

NokiaNokia

EricssonEricsson

AkzoAkzo HPHP

J&JJ&JAlcoaAlcoa

DowDow

DaimlerDaimlerNovartisNovartis

BayerBayer

BASFBASF

TorayToray

MotorolaMotorola

Saint GobainSaint

Gobain

Sharp KyoceraKyocera

BoschBosch

Allied SignalAllied Signal

DuPontDuPont

SonySony

SulzerSulzer

NECNEC

AlcatelAlcatel

UTCUTC

PhillipsPhillipsKruppKruppABBABB

MatsushitaMatsushita

SiemensSiemens

ThyssenThyssen

ToshibaToshiba

MitsubishiMitsubishi

HitachiHitachi

Product Diversi-fication in Relationto Sample Average

Geographical Diversificationin Relation to Sample

Average

-20%

Phenotype 1Diversified Geo. PortfolioFocused Product Portfolio

Phenotype 2Diversified Geo. Portfolio


Phenotype 3Focused Geo. Portfolio


Phenotype 4Focused Geo. PortfolioFocused Product Portfolio

FordFord

GEGE

IBMIBM

Again, the comparison of geographical diversification and product diversification enables us

to derive a typology of four different phenotypes (GO). Each GO-phenotype is characterized

by a specific diversification pattern.

GO-Phenotype 1 is characterized by a focused product portfolio and by a diversified geo-

graphical portfolio: This pattern is symptomatic for companies that have focused on a lim-

ited number of products that require considerable investments in R&D and/or marketing.

Since these investments are highly product specific, the companies are not able to realize

economies of scope. For that reason they will not engage in product diversification acitivi-

ties but focus on geographic diversification. GO-Phenotype 1 is typical for companies from

the pharmaceutical and specialty chemicals clusters.

GO-Phenotype 2 exhibits both a broadly diversified product and a broadly diversified geo-

graphical portfolio: Diversified electronic and machinery companies, typically European

companies like Sulzer, Alcatel or ABB, are engaged in a large number of product fields

and market their technologically competitive (niche) products on a global scale.

GO-Phenotype 3 is defined by a quite narrow geographical portfolio and a diversified

product base: This pattern is symptomatic for diversified Japanese electronic companies,

29

like Mitsubishi Electric, Hitachi, NEC or Toshiba. The majority of their products is designed

for the domestic market. Only a small number of the products competes on a global scale,

e.g. in the European and North American marketplace.

IO-Phenotype 4 is characterized by focused geographical and product portfolios: This pat-

tern is typical for only a few companies. In our sample, for instance, both U.S.-based

automotive manufacturers are characterized by this diversification pattern.

Finally, we can investigate the relationship between geographical diversification and techno-

logical (input) diversification (GI). Figure 10 visualizes the corporate technological and geo-

graphical diversification patterns at the end of the period of investigation (1993-1997).

Figure 10: Phenotypes of Corporate Geographical and Technological Diversifica-tion (1993-1997)

-40%

-20%

20%

40%

-20% 10% 20% 30% 40%

Glaxo

Novo Nordisk

Eli Lilly

Kao Toyota

Ford

Roche

Pfizer

GM

Merck KgaA

Merck Co.

Akzo

HP

J&J

Alcoa

Dow

Daimler

NovartisBASF

Motorola

IBM

Gobain

Sharp

Kyocera

BoschDuPont

Sulzer

Alcatel

UTC

Sony

Phillips

Krupp

ABB

Matsushita Siemens

Thyssen

ToshibaMitsubishi

Hitachi

-10%

-40%

-20%

20%

40%

-40% -30% -20% 10% 20% 30% 40%

GlaxoGlaxo

Novo Nordisk

Novo Nordisk

Eli Lilly

Kao Toyota

Ford

RocheRoche

Pfizer

GMGM

Merck KgaA

Merck Co.

NokiaNokiaEricsson

AkzoAkzo

HP

J&J

Alcoa

Dow

Daimler

NovartisNovartisBayer

BASFBASF

Toray

MotorolaMotorola

IBMIBM

Gobain

Sharp

Kyocera

Bosch

Allied Signal

DuPontSulzer

NECNEC

AlcatelAlcatel

UTC

SonySony

Phillips

KruppKrupp

ABBABB

MatsushitaMatsushita Siemens

Thyssen

ToshibaToshibaMitsubishi

GE

HitachiHitachi

-10%

Phenotype 1Divers. Technology PortfolioFocused Geo. Portfolio

GeographicalDiversification in

Relation to SampleAverage


Average

Phenotype 2Divers. Technology Portfolio

Diversified Geo. Portfolio

Phenotype 3Focused Technol. Portfolio


Phenotype 4Focused Technol. PortfolioFocused Geo. Portfolio

-40%

-20%

20%

40%

-20% 10% 20% 30% 40%

GlaxoGlaxo

Novo Nordisk

Novo Nordisk

Eli Lilly

Kao Toyota

Ford

RocheRoche

Pfizer

GMGM

Merck KgaA

Merck Co.

AkzoAkzo

HP

J&J

Alcoa

Dow

Daimler

NovartisNovartisBASFBASF

MotorolaMotorola

IBMIBM

Gobain

Sharp

Kyocera

BoschDuPont

Sulzer

AlcatelAlcatel

UTC

SonySony

Phillips

KruppKrupp

ABBABB


Thyssen


HitachiHitachi

-10%

-40%

-20%

20%

40%

-40% -30% -20% 10% 20% 30% 40%

GlaxoGlaxo

Novo Nordisk

Novo Nordisk

Eli Lilly

Kao Toyota

Ford

RocheRoche

Pfizer

GMGM

Merck KgaA

Merck Co.

NokiaNokiaNokiaEricssonEricsson

AkzoAkzo

HP

J&J

Alcoa

Dow

Daimler

NovartisNovartisBayerBayer

BASFBASF

TorayToray

MotorolaMotorola

IBMIBM

Gobain

Sharp

Kyocera

Bosch

Allied SignalAllied Signal

DuPontSulzer

NECNECNEC

AlcatelAlcatel

UTC

SonySony

Phillips

KruppKrupp

ABBABB


Thyssen


GEGE

HitachiHitachi

-10%

Phenotype 1Divers. Technology PortfolioFocused Geo. Portfolio

GeographicalDiversification in

Relation to SampleAverage


Average

Phenotype 2Divers. Technology Portfolio


Phenotype 3Focused Technol. Portfolio


Phenotype 4Focused Technol. PortfolioFocused Geo. Portfolio

Again, we can derive a typology of four different phenotypes of corporate geographical and

technological diversification (GI-phenotypes):

GI-Phenotype 1 is characterized by a diversified technology portfolio and by a concen-

trated geographical portfolio: This pattern is symptomatic for companies from the U.S. and

Japan that have focused on a limited number of geographical areas. At the same time

these companies are highly diversified, both in terms of technologies and products. These

30

companies concentrate their resources on product and technological diversification

strategies and focus only on a limited number of geographical markets, that fit their tech-

nologically competitive products.

GO-Phenotype 2 exhibits both a broadly diversified geographical portfolio and a broadly

diversified technology portfolio: Phenotype 2 is dominated by European firms that are en-

gaged in a broad span of technologies. Some of the firms, typically from the electronics

and machinery clusters, are also highly diversified in terms of products. Others, like the

automotive firms, concentrate on few business lines and use their broad technology base

for their limited number of technologically complex product lines.

GO-Phenotype 3 is defined by a quite narrow technology portfolio and a diversified geo-

graphical portfolio: This pattern is symptomatic for pharmaceutical companies, like Glaxo,

Roche, and Eli Lilly, as well as for consumer electronics firms, like Sony and Phillips. Al-

though the degree of technological diversification of these companies is quite narrow in

relation to the sample average, these companies invest considerable amounts in R&D

(companies from the pharmaceutical and electronic clusters are characterized by the

highest R&D-intensities in the sample). These companies try to recover their R&D expen-

ditures through serving a wider range of markets.

GO-Phenotype 4 is characterized by relatively focused a geographical portfolio and a fo-

cused technology portfolio: Again, this pattern characterizes only a very small number of

firms in the sample. In fact, only the two Japanese companies NEC and Toray can be at-

tributed to this type of diversification pattern.

Conclusions - Paths in the Evolution of Corporate Diversification Patterns

The differentiated analysis of corporate diversification has revealed that there is no one ho-

mogeneous diversification pattern across the whole sample. Rather, there exist several

clusters of companies that pursue similar diversification strategies with regard to the input,

output and geographical dimensions. A number of companies follows on an overall diversifi-

cation strategy. The “overall diversifier” is typically a European electronics or engineering

company (like ABB, Siemens or Sulzer) that is actively engaged in a large number of product

lines and technology fields. The “overall diversifier” tries to benefit from economies of scope

on a global scale. In contrast, the “two-sided diversifier” concentrates on two diversification

dimensions, typically on the technology/geographical dimension or on the product/ geo-

graphical dimension. Most interestingly, companies that are diversified both in terms of

products and technologies are also likely to be diversified in terms of geographical markets

and thus tend to follow the “overall diversifier” strategy. Finally, the “single-sided” diversifier

concentrates on one of the three diversification dimensions. E.g., companies from the phar-

31

maceutical industry focus largely on the geographical diversification strategy with compara-

tively narrow product and technology portfolios. None of the sample companies is of a “non-

diversifier” kind.5

We conclude our phenomenological analysis with a more dynamic view on the corporate di-

versification patterns. From a dynamic perspective the question arises how these diversifica-

tion patterns evolved over time. In the course of the three five years periods of investigation

the static patterns of corporate diversification translate into distinct paths of evolution. It can

be shown that there are concurrent paths in the evolution of corporate diversification among

the sample companies. E.g., companies that belong to the same technology clusters exhibit

a considerable degree of homogeneity in their paths of evolution. As a representative exam-

ple for all diversification pairings (IO, GO, GI), figure 11 gives an overview of the paths of

evolution of corporate IO-diversification. For reasons of lucidity we have visualized the paths

for a limited number of 20 sample companies.

Figure 11: Paths in the Evolution of Corporate Product and Technological Diversification (1983-1997)

-40%

-20%

20%

40%

-80% -60% -40% 20% 40% 60% 80%

Ford

Merck KGaA

Nokia

Ericsson

J&J

Bayer

Alcatel

GE

-20%

DuPont

Siemens

Daimler

GM

Eli Lilly

Roche

Glaxo

11

12

2

2

3

3

3

2

33

2

1

12

3

132

32

1

Sony

Phillips

32

1

1

3

1

2

1

32

1

3

2

1

2

3

1

2 3

3 2

1

321

3

12








Average


Average

2

1

3Toyota

Hitachi3

21

1 2 3Dow

-40%

-20%

20%

40%

-80% -60% -40% 20% 40% 60% 80%

Ford

Merck KGaA

Nokia

Ericsson

J&J

Bayer

Alcatel

GE

-20%

DuPont

Siemens

Daimler

GM

Eli Lilly

Roche

Glaxo

11

12

2

2

3

3

3

2

33

2

1

12

3

132

32

1

Sony

Phillips

32

1

1

3

1

2

1

32

1

3

2

1

2

3

1

2 3

3 2

1

321

3

12








Average


Average

2

1

3Toyota

Hitachi3

21

1 2 3Dow

5 Although in this context the term “non-diversifier” is a misnomer since it only indicates the degree of

diversification of the companies in relation to the sample average.

32

From all three perspectives (IO, GO, GI), the paths in the evolution of the corporate diversifi-

cation patterns can be assigned to two different categories: On the one hand, we have iden-

tified paths of evolution that evolve only slowly over ,time and on the other hand we have

spotted trajectories that change more radically. In the case of stable diversification patterns,

both the degree of product diversification, the degree of technological diversification and the

degree of international diversification remain more or less stable over time in relation to the

sample average. Stable diversification patterns apply to the majority of the sample compa-

nies and can be found in the chemical cluster, in parts of the pharmaceuticals cluster, in the

computer and electronics cluster as well as in the systems engineering cluster. Most of the

companies have expanded their range of activities and changed their technology and product

portfolios only gradually. In contrast to continuity, some companies with dynamic diver-

sification patterns, like Nokia and Ericsson, have shifted the range of their product and/or

technology and/or geographical portfolio more dramatically. Clear signs of shifts in the range

of products become also evident in the pharmaceuticals cluster.

References

Almeida, P. (1996). Knowledge Sourcing by Foreign Multinationals: Patent Citation Analysis

in the U.S. Semiconductor Industry. Strategic Management Journal 17, 155-165.

Barnett, WP, Burgelman, RA. (1996). Evolutionary Perspectives on Strategy. Strategic Man-

agement Journal 17/5, 5-19.

Birkinshaw, J, Hood, N. (2001). Unleash Innovation in Foreign Subsidiaries. Harvard Busi-

ness Review: March, 131-137.

Breschi S, Lissoni, F, Malerba, F. (1998). Knowledge Proximity and Technological Diversifi-

cation. CESPRI Discussion Paper. Universita L. Bocconi: Milan.

Cantwell, JA. (1995). The Globalization of Technology: What Remains of the Product Cycle

Model? Cambridge Journal of Economics: 19, 155-174.

Cantwell, JA, Piscitello, L. (1999). Accumulating Technological Competence – Its Changing

Impact on Corporate Diversification and Internationalization, University of Reading Dis-

cussion Paper in International Investment and Management, 1999.

33

Cantwell, JA, Piscitello, L. (1999). The Emergence of Corporate International Networks for

the Accumulation of Dispersed Technological Competences. Management International

Review Special Issue 1999/1, 123-147.

Cantwell, JA, Piscitello, L. (1997). A Note on the Causality Between Technological Diversifi-

cation and Internationalisation, University of Reading Discussion Papers in Quantitative

Economics and Computing, No. 52, May 1997.

Cantwell, JA, Piscitello, L. (1997a). Accumulating Technological Competence – Its Changing

Impact on Corporate Diversification and Internationalisation, University of Reading Dis-

cussion Paper in International Investment and Management, No. 232, June 1997.

Chatterjee, S, Wernerfelt, B. (1991). The Link between Resources and Type of Diversifica-

tion: Theory and Evidence. Strategic Management Journal 12/1, 33-48.

Department of Trade and Industry (DTI). (2001). The UK R&D Scoreboard 2001. Company

Reporting Limited: Edinburgh.

Fai, FM. (1999). The evolution of corporate technological diversification 1930-90: An investi-

gation into the concept of technological relatedness. Communication to European

Meeting on Applied Evolutionary Economics. 7-9 June 1999. Grenoble.

Fai, FM., Cantwell, J. (1999). The Changing Nature of Corporate Technological Diversifica-

tion and the Importance of Organizational Capability. In: Dow, S, Earl, PE. (eds). Con-

tigency, Complexity and the Theory of the Firm. Cheltenham.

Gambarella, A, Torrisi, S. (1998). Does Technological Convergence Imply Convergence in

Markets? Evidence from the Electronics Industry. Research Policy 27, 445-463.

Gavetti, G. (1994). Strategies of Multinational Firms in the Patent Domain in Europe. Working

paper for the Commission of the European Communities. Milan.

Geringer, MJ, Beamish, PW, Dacosta, RC. (1989). Diversification Strategy and Internation-

alization: Implications for MNE Performance. Strategic Management Journal 10, 109-

119.

34

Granstrand, O. (1998). Towards a theory of the technology-based firm. Research Policy

27/5, 465-490.

Granstrand, O, Oskarsson, C. (1994). Technology Diversification in „MUL-TECH“ Corpora-

tions. IEEE Transactions on Engineering Management 41/4, 355-364.

Granstrand, O, Sjölander, S. (1990). Managing innovation in Multi-Technology Corporations.

Research Policy 19/1, 35-60.

Jaffe, AB. (1989). Characterizing the technological position of firms, with application to quan-

tifying technological opportunity and research spillovers. Research Policy 18, 87-97.

Kim, WC., Hwang, P., Burgers, WP. (1993), Multinationals’ Diversification and the Risk-re-

turn Trade-off. Strategic Management Journal 14/4, 275-286.

Kodama, F. (1995). Emerging Patterns of Innovation: Sources of Japan's Technological

Edge. Boston, MA.

Kodama, F. (1986). Technological Diversification of Japanese Industry. Science 233, 291-6.

Madura, J., Rose, L.C. (1987). Are Product Specialization and International Diversification

Strategies Compatible? Management International Review, 27 (3), 38-44.

Markides, CC. (1996). Diversification, Refocusing and Economic Performance. Cambridge.

Oskarsson, C. (1993). Diversification and Growth in US, Japanese and European Multi-

Technology Corporations. Chalmers University of Technology: Goeteborg.

Patel, P, Pavitt, K. (1998). The Wide and Increasing Spread of Technological Competencies

in the World’s Largest Firms: A Challenge to Conventional Wisdom. In: Chandler A. et

al. (eds). The Role of Technology, Strategy, Organization, and Regions. Oxford.

Pavitt, KL, Robson, M, Townsend, J. (1989), Technological Accumulation, Diversification and

Organisation in UK Companies 1945-1983. Management Science 35/1, 81-99.

Pavitt, KL. (1988). Uses and Abuses of Patent Statistics. In AFJ van Raan (ed), Handbook of

Quantitative Studies of Science and Technology, Amsterdam.

Piscitello, L. (1998). Corporate Diversification, Coherence, and the Dialectic Relationship

Between Technological and Product Competencies. PhD Thesis, University of Padua.

35

Praest, M. (1998). Processes of Technological Competence Accumulation: A Synthesis. Pa-

per prepared for the DRUID summer conference. 9th-11th of June 1998. Bornholm.

Sambharya, R.B. (1995), The combined effect of international diversification and product di-

versification strategies on the performance of U.S.-based multinational corporations.

Management International Review 35/3, 197-218.

Schmoch, U. (1999). Impact of international patent applications on patent indicators. Re-

search Evaluation 8/August, 119-131.

Sjölander, S, Oskarsson, C. (1995). Diversification: Exploiting the Flow of Technology. A

Swedish comparison. International Journal of Technology Management 10/1, 21-31.

Stephan, M (2002). Akkumulation technologischer Kompetenzen in Unternehmen, in: Ham-

mann, P et al. (eds). Strategisches Kompetenzmanagement, Wiesbaden.

Stephan, M, Pfaffmann, E. (2001). Detecting the Pitfalls of Data on Foreign Direct Invest-

ment: Scope and Limits of Foreign Direct Investment Data, Management International

Review, 41/3.

Zander, Ivo (1997). Technological Diversification in the Multinational Corporation: Historical

Evolution and Future Prospects. Research Policy 26/2, 209-228.

Documents

An Analysis of the Relationship between Product Diversification, … · 2005. 7. 22. · diversification, or they concentrate on input diversification, e. g. technological diversification,