Incomplete global integration and regional knowledge-intensive service industries.

27  Download (0)



Knowledge-Intensive Service Industries

Y I - M I N C H E N

The internationalisation of service industries has been a key managerial focus since the late 1980s, and internationalisation became an area of mature research in the international business field in the 1990s. The reason is that service industries confronted a completely new set of chal-lenges such as globalisation. Furthermore, the knowledge-intensive service sectors have developed quickly during the 1990s and became the leading industries in the world through international dealings of service flows. How do the unique features of knowledge-intensive service industries affect global integration and the use of global strategy? This study develops a new approach focused on regional production pat-terns of knowledge-intensive service industries for exploring important but previously untried beliefs regarding global integration. The findings ascertain that most regional knowledge-intensive service industries have incomplete rather than perfect global integration. Incomplete global inte-gration entails the localisation, or customisation, strategy to be suggested to MNEs in communications services, financial institutions, business services, educational services and health services sectors. One exception to incomplete global integration exists in the educational services production of North America, which displays nearly perfect global integration, and suggests the standardisation strategy for global educational services.


‘Most of modern global strategy focuses on minimizing differences between countries. Perhaps it’s time to dust off approaches that exploit those differences as well’ [Ghemawat, 2003a: 77]. Since the statement by Levitt [1983] that a global market for uniform consumer products is widely emerging, the standardisation strategy for globalisation has been taken for granted among global businesses for two decades, including Coca-Cola, Levi’s, McDonald’s, Panasonic, Philip Morris, Star TV,

Yi-Min Chen, Department of Asia-Pacific Industrial and Business Management, National University of Kaohsiung, 700 Kaohsiung University Road, Nan-Tzu District, Kaohsiung 811, Taiwan. Email:

The Service Industries Journal, Vol.26, No.2, March 2006, pp.223–248 ISSN 0264-2069 print=1743-9507 online


Toyota. However, due to problematic events, for example the Asian currency crisis, a decline in company income, and plummeting stock prices, the Coca-Cola corporation had substituted the standardisation strategy, or ‘think global, act global’ programme, in 1996 with ‘think local, act local’ manoeuvres in 1999. ‘Unfortunately, “local” did not seem to be any better a description of Coke’s market space than “global”’ [Ghemawat, 2003a: 76]. In 2002, Coca-Cola announced the ‘think local, act local’ mantra was gone, and the decision-making power in marketing strategy was to return to Coca-Cola’s headquarters in Atlanta.

Therefore, the differences that remain among countries might continue to be wide-ranging and profound, even Coca-Cola, broadly seen as a standard-bearer of global business is sensitive to cultural differences [Ghemawat, 2003a]. Ghemawat [2001] demonstrated a four-dimensional structure, the cultural, administrative or political, geographic, and economic distances, to identify and assess how distance affects various industries. Examples include: cultural attributes, such as language and social norms, creating distance by influencing consumers’ product tastes, are the determining considerations for TV or media services industry; governments, creating administrative and political distance through unilateral policies or preferen-tial trading agreements, intervening to protect telecommunications industries that are viewed as critical to national security, or to set quality standards and control pricing of the health care sector that produces goods and services that governments believe individuals are entitled to as a basic human right; increasing geographic distance can cause cross-border equity flows between two countries to decline considerably due to the level of telephone traffic and the number of branches of multinational banks; economic distance, differences in consumer incomes, or in costs and quality of financial resources, human resources, information or knowledge, substantially affects the distribution or business systems of the insurance sector.

The above examples show that the different distances between countries can affect service industries in evaluating foreign market opportunities as well as trade flows. ‘Service internationalisation will certainly be an important managerial focus in the future’ [Vandermerwe and Chadwick, 1989: 79]. Vandermerwe and Chadwick [1989] built on some of the relevant literature and research by leading academics in the field of services and trade in services to suggest a classification system that goes beyond putting services in boxes. Their work demonstrates approaches and strat-egies of service internationalisation, and then indicates that modes for service inter-nationalisation are shaped by a combination of the nature of the service – the degree of interaction between the service provider and the consumer – and how it is deli-vered – the degree to which services are embodied in or delideli-vered through goods.

Furthermore, as the Organisation for Economic Co-operation and Developmentfs (OECD) [2001] suggested, there is a clear trend in the OECD area towards a knowledge-based economy that is echoed in the economic and innovative perform-ance of high-tech sectors – both in manufacturing and services. By the end of the 1990s, high- and medium-level technology manufacturing sectors accounted for approximately 9 per cent of the total OECD value-added. Knowledge-intensive service sectors, including ‘market’ and ‘non-market’, accounted for about 29 per cent of total value-added in the OECD area. Post and telecommunications, finance


and insurance and business services are generally the most intensive technology users amid ‘market’ services [OECD, 2001]. In many OECD countries, including the United States, the knowledge-intensive service sectors developed quickly over the 1990s and became the leading industries in the world through international trans-actions of service flows. Based on NSB [2002], knowledge-intensive service indus-tries are defined as indusindus-tries comprising science, engineering, and technology in their services or in the delivery of those services. Five of these knowledge-intensive service industries are communications services, financial services, business services, educational services, and health services. Communication services include telecom-munications and broadcast services, and business services include computer software development, data processing, and research and engineering services.

Vandermerwe and Chadwick researched the issue of internationalisation of ser-vices through the representation of modes and strategies in 1989, however, the issue of globalisation of knowledge-intensive service industries has drawn limited notice in empirical research. The knowledge-intensive service sector was an emer-ging industry from the late 1990s. Furthermore, prior research in the field of inter-national business has ignored issues arising regarding global integration and the best regional allocation of knowledge-intensive economic activity, industrial pro-duction [Buckley, 2002; Dunning, 2000a; Guisinger and Brewer, 1998].

After three decades, international competition and internationalisation in indus-tries, including services, has already become a mature research field in the inter-national business research [Guisinger and Brewer, 1998]. The next research area might be the globalisation of services, which is followed by the suggestion made by Courtney C. Brown, editor of the Columbia Journal of World Business, in 1970. Brown [1970] remarked that multinational service enterprises must relocate factors of production and sources of supply to different global locations.

Moreover, for determining the degree of globalisation, whether it is high or low, Ghemawat [2003b] reviewed the empirical evidence on the cross-border integration of different markets: for product market integration (trade flows, foreign direct invest-ment, and price), and factor market integration (capital, labour, and knowledge). Fur-thermore, he signalled that most measures of market integration have scaled new heights in the last few decades, but still fall far short of economic theory’s ideal of perfect integration. He referred to this state of incomplete cross-border integration as semi-globalisation. For the highlights of international business strategy and future research agenda on semi-globalisation, Ghemawat [2003b: 150] concluded:

The diagnosis of semi-globalisation does more than just supply a relatively stable frame of reference for thinking about the environment of cross-border operations. Semi-globalisational also calls attention to the critical role that location-specificity plays in the prospects of distinctive content for international business strategy relative to mainstream business and corporate strategy. In addition, it flags factors/products subject to location-specificity as being salient from the perspective of international business . . . Such considerations motivate the modest proposal that semi-globalisation or location-specificity merits the status of a major research programme in international business. In


other words, that a significant volume of research activity should be directed along lines that take explicit account of both the importance and incompleteness of the integration of markets across borders.

While previous researchers [e.g. Ghemawat, 2003b; Kim et al., 2003; Makhija et al., 1997] heavily emphasised measuring global integration at the national, indus-try, and business levels, this research indicates several important limits based on an empirical literature review. First, take the recent procedure of regionalising global trade [Helliwell, 1998; McCallum, 1995]. For example, Canada and the United States share a common land border and language and have extremely close relations. Ghemawat [2001] indicated that all the effects in terms of four dimensions of distance are fairly subtle, therefore building the biggest bilateral trade relationship in the world [McCallum, 1995] this work implements the regional blocs approach, which is based on natural borders between regions [Ohlin, 1935] – for example, North America, East Asia, European Union, Latin America, and the rest of the world – rather than just examining at the national, industry, and business levels as most previous studies do. Second, as regional blocs have mutual rather than unilateral advantages, this study employs a systems approach to investigate how value-added activities are related within the industry between regional blocs by recognising industrial production as the driver of the global integration of regional industries, rather than using conven-tional quantity-based tests of cross-border market integration, for example the share of world trade divided by global GDP [Ghemawat, 2003b], or the standard Grubel and Lloyd index of intra-industry trade for measuring how much total exports in a individual industry are counteracted by imports in the same industry [Greenaway and Milner, 1986; Grubel and Lloyd, 1975; Makhija et al., 1997]. Finally, by examining the extent of global integration on the industries of regional blocks, this study concentrates on the knowledge-intensive service industries, rather than on manufacturing industries examined by Makhija et al. [1997], or on product and factor markets investigated by Ghemawat [2003b]. The approach adopted in this work focuses on the knowledge-intensive service industries of the regional blocs, which can then be combined across countries to measure industrial production in regions.

For investigating global integration in the regional knowledge-intensive service industries, this work specifies global integration at the regional level as the degree to which industry firms execute different value-added activities across regions, chiefly from the explanation of Makhija et al. [1997] and Yip [1992]. This section first describes why the global integration of regional knowledge-intensive service industries is an emerging concern, following which the remainder of this study is separated into six main segments. The first section talks about the inadequate evi-dence concerning the global integration of regional knowledge-intensive service industries. These insufficiencies lead to this study applying a fresh approach to assess the global integration of regional knowledge-intensive service industries, an approach focused on industrial production patterns.

The second section explores the theoretical foundation of interregional trade to advance global integration, and Ohlin [1935] was the first to concurrently study the


space and time essentials in analysing interregional trade. Therefore, this work employs the basic proposition of Ohlin, specifically that consumption minus imports equals production minus exports, and uses this to explain a theoretical relationship demonstrating regional economic activities for model development in the next section. The third section of this study employs the theoretical groundwork of Ohlin, and exhibits the further proposition that intraregional production of a region is reliant on the production of the other regions by substituting for intraregional con-sumption and interregional linkages, exports and imports.

The fourth section explains that the sample data is from the United States National Science Board (NSB) Science and Engineering Indicators – 2002, 2004 database, and the statistical methodology, which includes bivariate correlation, multiple regression, and model-building processes. The fifth section examines the level of global integration for the knowledge-intensive service industries of five regions. The evidence on incomplete global integration from regression analysis is also presented. In the final section, the results on incomplete global integration for the knowledge-intensive service industries are used to advocate managerial implications for the benefit of international business practitioners and policy-makers, and also to benefit the academic community interested in conducting future theoretical and empirical work in this area.


Over the last two decades, increased liberalisation procedures have led to a boom in services and the possibility for firms to become international and expand their business across geographic boundaries in a way never previously done [Frits, 1987]. Governments are opening up their markets and making them more competitive in many service business areas [Vandermerwe, 1987]. Therefore, in the conven-tional context, the literature offered two broad streams of internaconven-tionalisation of services. One stream highlights the differences among services and the resultant strategic and operational marketing implications [Lovelock, 1983; Schemenner, 1986; Vandermerwe and Chadwick, 1989; Patterson and Cicic, 1995]. Lovelock [1983], while not dealing in particular with the issue of services in an international framework, reviewed an assortment of variables to classify services: the character-istics of the service act; the nature of the relationship a firm had with its customers; the degree of customisation or standardisation; the nature of supply and demand for the service; and the approach taken to performing the service, to find differences that have important strategic implications. Schemenner [1986] used two elements to clas-sify different kinds of service businesses: the degree of labour intensity and the degree of interaction and customisation in service delivery. Vendermerwe and Chadwick [1989] selected two axes, the nature of the service (the degree of interaction between service provider and consumer) and the way service is delivered (the degree to which services are incorporated in or delivered through goods), to develop a classification system for service internationalisation to provide strategies for managers taking their services into world markets.


The other stream looks mainly at trade-related issues and displays how different categories of services are internationally conducted [Boddewyn et al., 1986; Dahringer, 1991; Enderwick, 1990; Erramilli, 1990, 1992; Erramilli and Rao, 1990, 1993; Grubel, 1987; Porter, 1990; Terpstra and Yu, 1988; Trondsen and Edfelt, 1987]. The concepts of comparative and competitive advantages and the value-added chains [Kogut, 1985] can also provide this stream of research on assessing the competitive status of service internationalisation. Comparative advantage, which corresponds to the concept of locationally specific factors, influences decisions on where to source factors and where to market output. Comparative advantage is largely influenced by factor and market-related, particularly relative factor cost, avail-ability, intensity and quality, and the size, growth, and accessibility of markets, such as strategic issues of entry mode choice [Erramilli, 1990, 1992; Erramilli and Rao, 1990, 1993]; obstacles to internationalisation of services [Dahringer, 1991]; or inter-national trade policies [Trondsen and Edfelt, 1987].

Competitive advantage, related to the idea of the firm-specific asset, describes the proprietary elements of the firm that ascertain what activities are undertaken and what differentiates them from competitors. Product differentiation is one of the most com-monly used competitive strategies within the service sector [Heskett, 1986]; or the function of service firms and industries in creating national competitive advantage [Enderwick, 1990; Porter, 1990].

The value-added chain that links the various stages of production of services to subsequent stages of marketing, distribution, and after-sales provision provides the third string of competitive analysis of services internationalisation. Establishing information networks and integrating different stages of the value-added chain provide both proprietary competitive advantages and barriers to the entry of compe-titors [Enderwick, 1989], implying that comparative, competitive advantages, and value-added chains are not independent of each other. ‘A company that is able to take advantage of spatial differences in factor cost or quality through the existence of a global network is likely to enjoy a stronger competitive position’ [Enderwick, 1990: 23 – 4]. Dunning [1988] indicated that the well-organised management of such a global network could defer economics of common governance that reinforces competitiveness. Terpstra and Yu [1988] recognised that the value-added process of internationalisation exists in specific service industries such as legal, advertising, or retailing.

However, international competition and internationalisation of service industries have already become an area of mature research in the field of international business [Guisinger and Brewer, 1998]. Most of the above research has focused either on why and how service firms internationalise or on various modes of internationalisation. As the 1990s approached, service industries confronted a completely new set of challenges such as globalisation. ‘How do the distinctive characteristics of services businesses affect globalisation and the use of global strategy?’ [Lovelock and Yip, 1996: 64]. Therefore, developing global strategies for service industries has become a major topic in the international business research agenda since the late 1990s [Lovelock and Yip, 1996; Trebing and Estabrooks, 1995; McLaughlin and Fitzsimmons, 1996; Morgan, 1992].


Research in globalisation of service industries has focused on the following: (1) developing global strategies for service industries by identifying industry globalisa-tion drivers and factors [McLaughlin and Fitzsimmons, 1996; Lovelock and Yip, 1996]; (2) analysing the effect of the global volatile regulatory environment of specific service industries such as telecommunications, or of the new regulatory framework for global trade in services set up under the 1996 General Agreement on Trade in Services (GATS), to assist practitioners in conducting service businesses at the worldwide level [Bauer, 1994; Daniels, 1995; Hibbert, 2003; Trebing and Estabrooks, 1995]; (3) designing suitable organisational structures and support systems such as knowledge management systems for global professional service MNEs to create sustainable competitive advantage [Aharoni, 1996; Greenwood and Lachman, 1996; Ofek and Sarvary, 2001].

Furthermore, by examining core services from an operational viewpoint, Love-lock and Yip [1996] allocated core services to one of three broad categories depend-ing on the nature of the process (whether services are primarily tangible or intangible) and whether customers must be present during service production. First, people-processing services involve tangible actions to customers in person. Examples include passenger transportation, health care, food services, and lodging services. Second, possession-processing services involve tangible actions to physical objects to improve their value to customers. Examples include freight transportation, ware-housing, equipment installation and maintenance, car repair, and laundry. Finally, information-based services are creating, manipulating, interpreting, and transmitting data to create value. Examples include accounting, banking, consulting, education, insurance, legal services, and news.

After reviewing economic data on the global integration of markets, Ghemawat [2003b] indicated that the possible cross-border integration of markets, or the possible location-specificity of key activities, has received less attention. That study then exam-ined the global integration of factors market, capital, labour, and services to assess whether the markets are completely isolated or integrated across borders. However, neither the above literature on the internationalisation or globalisation of services tries considers the extent of global integration of knowledge-intensive service indus-tries, communication services, financial institutions, business services, educational services, and health services, between a particular region and other regional blocs.

Moreover, mergers, acquisitions, takeovers, and buy-outs have become extensive in service industries in the late twentieth century. The notable mergers appear in finance services (Citicorp and Travelers), or in media services (Disney and ABC, Viacom and CBS). These cross-border deals demonstrate a widespread belief that industries will inevitably become more concentrated as the world’s markets become more globalised [Ghemawat and Ghadar, 2000; Warf, 2003]. This trend to globalisa-tion of service industries leads many business scholars to assume that the theory of comparative advantage points toward industry concentration, which basically predicts the geographic concentration of production [Ghemawat and Ghadar, 2000]. Moreover, Krugman and Obstfeld [2000] examined what happens to an industry when two producing countries integrate their economies, and the results show up a significant concentration of producers from theoretical model development.


Therefore, following the recent theoretical prediction of the geographic concen-tration on production, this investigation devises a novel approach focused on patterns of regional industrial production for examining important but previously unproven notions related to global integration of knowledge-intensive service industries.


‘The granddaddy of all globalisation models is the theory of comparative advantage, which was laid out by David Ricardo at the beginning of the nineteenth century’ [Ghemawat and Ghadar, 2000: 66]. An essential perceptiveness about comparative advantage and international trade is that trade between two countries can benefit both countries if each country exports the goods in which it has a comparative advan-tage [Krugman and Obstfeld, 2000]. As the Ricardian model’s followers have stressed for generations, international trade promotes growth through a myriad channels: increased specialisation, efficient resource allocation according to comparative advantage, diffusion of international knowledge through trade, and heightened domestic competition as a result of international competition; for example Lucas [1988] and Young [1991] ascertained that normal trade theory predicts an effect of openness on the level of GDP. Moreover, an openness level effect can appear as a growth effect for long periods. For instance, Grossman and Helpman [1991], Lee [1993], and Young [1991] introduced various forms of increasing returns to scale, ensuring that openness can affect long-term growth as well as the level of income in their theoretical development.

Regarding interregional and international trade, Ohlin [1935] was the first to simultaneously consider the space and time elements in analysing interregional trade, meaning that before Ohlin [1935] the problem of industry localisation in most treatises on general economics never arises. Consequently, Ohlin [1935] first developed a simplified form of the one-market theory, then extended the simple theory to cover several markets by introducing a simple form of geographical immobility of the productive factors. Some of the fundamental influences of space thus are laid bare, and light is thrown upon certain aspects of the localisation of industry and certain characteristics of interregional trade. As Ohlin [1935: 18 – 19] indicated:

Now assume two regions trading with one another. What will the price system be like? Evidently it is not much changed in character. The total demand for each factor of production (no.2) springs not only from production for domestic consumption but also from production for export. On the other hand, a part of the domestic consumption is supplied by imported goods; consequently demand is not equal to production (no.1). Instead we posit: demand minus imports is equal to production minus exports. The demand for productive factors is consequently changed.

If we know imports and exports, the equations in (1) and (2) can easily be adjusted. But they are not known.


Based on the proposition of Ohlin [1935], i.e. demand minus imports equals pro-duction minus exports, this study recognises propro-duction as the driver of globalisation and applies this relationship to developing a model for the main global regions.


The home market of a region is frequently considered the natural destination for the goods and services produced by intraregional and interregional firms. Based on the argument of Buckley and Casson [1998], a feature of numerous global markets is the use of regional production and distribution hubs, in which several neighbouring countries are serviced from the same location. This work defines regions of the world as groups of nation states located in a geographical neighbourhood. The regional classification used in this study is based on the five major global regions, that is North America, East Asia, European Union, Latin America, and the rest of the world.

The starting point in model development follows the proposition of Ohlin [1935]: demand (consumption) minus imports equals production (supply) minus exports, to determine the relationship between intraregional production (supply), intraregional consumption (demand), and interregional economic linkages (exports and imports) for the five major global regions. Restated, the size of intraregional production in North America (NA), is the balance between intraregional consumption and inter-regional economic linkages,

NAPrk,t ¼NACok,tþNAExk,tNAImk,t (1)

where the k subscript denotes five components of knowledge-intensive service indus-tries – communications services, financial institutions, business services, educational services, and health services, all for the time period t. Furthermore, the production is represented as the superscript Pr, with exports denoted by Ex, imports represented by Im, and consumption being Co.

Similarly, the size of the intraregional production for the other regions, or indus-trial production of regional knowledge-intensive service industries for East Asia (EA), European Union (EU ), Latin America (LA), and the rest of the world (RW ), can also be represented in terms of intraregional consumption plus interregional exports and minus interregional imports. Thus, expanding Equation (1) to the other regions of the world:

EAPrk,t¼EACok,t þEAExk,tEAImk,t (2)

EUk,tPr¼EUk,tCoþEUExk,tEUk,tIm (3)

LAPrk,t¼LACok,tþLAExk,tLAImk,t (4)


Along with the argument of Ostry [1998] and Dunning [1998]: globalisation is driving the creation of a single global market, this investigation designed a concep-tual framework, shown in Figure 1, of supply (industrial production) and demand (industrial consumption) which creates a system of general equilibrium, in which the principle of mutual interdependence among the main global regions is funda-mental. Naturally, the connecting bridge by which regional industrial production reaches other regional markets is based on interregional linkages (exports/ imports). Therefore, based on this initial framework, this work performs a major effort to systematise interregional linkages and production for specifying the network by which the knowledge-intensive service industries serve interregional and intraregional markets.

To capture the extent to which the various value-added activities of knowledge-intensive service industries are globally integrated through interregional linkages, this work assumes the distinction between exports and imports of North America, for example, to and from other regions depends on the difference between aggregate exports and imports of those regions being expressed in Equations (6) and (7): NAExk,t ¼EAImk,tþEUk,tImþLAImk,tþRWk,tIm (6) NAImk,t ¼EAExk,tþEUk,tExþLAExk,tþRWk,tEx (7) F I G U R E 1 C O N C E P T U A L F R A M E W O R K O F G L O B A L I N T E G R A T I O N O F K N O W L E D G E - I N T E N S I V E S E R V I C E I N D U S T R I E S


Equations (6) and (7) then are put into Equation (1), producing Equation (8), below:

NAk,tPr ¼NACok,t þEAImk,tþEUk,tImþLAImk,tþRWk,tIm EAExk,tþEUk,tExþLAk,tExþRWk,tEx


However, recognising that interregional trade flows are a necessary, but an insuffi-cient condition for industry globalisation [Kobrin, 1991], an in-depth analysis based on supply (industrial production) and demand (industrial consumption) relationships is needed to identify the occurrence of global integrated marketplaces. Furthermore, with respect to Equation (8), global production networks are certainly not limited to North America [Hanson, 2001]. This leads this study to consider other regions together with North America in discussing the degree of interdependence between each intraregional economic activity (production and consumption) of the knowledge-intensive service industries in facing global competitive pressure. Therefore, putting Equations (2) to (5) into Equation (8), or replacing the exports and imports of each region with intraregional production and consumption, the intraregional production of the North American knowledge-intensive service industries during a certain period will depend positively on the consumption of each region, and negatively on the production of each region. Restated:

NAPrk,t ¼NACok,tEAPrk,tþEACok,tEUPrk,tþEUCok,tLAk,tPrþLACok,tRWk,tPr

þRWk,tCo (9)

Recently, there has been a trend towards the geographic concentration of industrial production based on the belief that the globalisation of production raises the incentive to produce in regions with relatively low-cost access to foreign markets in the field of international business. Moreover, knowledge-intensive service industries may rely more heavily on economies of agglomeration as opposed to economies of scale, and location provides a critical consideration in both sourcing and marketing. Therefore, to further explain the concept of globalisation, the issue of integration or fragmentation of regional production in the knowledge-intensive service industries is becoming an important research topic in the international business.

Following this argument of global location of value-added production activities, this investigation would reduce the variables of consumption of each region in Equation (9) and then represent the dominance of the intraregional production of five regions from the perspective of global integration of industrial production. Then Equation (9) becomes

Model 1:

NAPrk,t¼aEAEAPrk,tþaEUEUk,tPrþaLALAPrk,tþaRWRWk,tPr (10)

WhereaEA,aEU,aLA,aRWdenote the regression parameters with respect to the


been recognised as an approach different from conventional measurement methods, e.g., trade flows/GDP, for investigating the degree of global integration of intraregio-nal production of the North American knowledge-intensive service industries in relation to the industrial production of other regions. Markedly, Model 1 is a regression model with both a response variable and four explanatory variables. Thus, this leads to the employment of regression analysis as a statistical methodology for exploring how the response variable and explanatory variables are statistically related for investigating the degree of integration among the main global regions.

Following the explanation of Model 1 as a regression model, other regression models that accompany Model 1 should be implemented through the association of the other response variables, or intraregional production of the other regions based on the perspective of the global integration of regional production. Equally, by reor-ganising Equation (10), the intraregional production of a region, EA, EU, LA, or RW, will be regressed on the production of the other regions. Therefore:

Model 2: EAPrk,t¼aNANAPrk,tþaEUEUk,tPrþaLALAPrk,tþaRWRWk,tPr (11) Model 3: EUk,tPr¼aNANAPrk,tþaEAEAk,tPrþaLALAPrk,tþaRWRWk,tPr (12) Model 4: LAPrk,t¼aNANAPrk,tþaEAEAk,tPrþaEUEUk,tPrþaRWRWk,tPr (13) Model 5: RWk,tPr¼aNANAPrk,tþaEAEAk,tPrþaEUEUk,tPrþaLALAPrk,t (14)

This study develops a set of integrated production networks and interregional linkage models which have a spatial connotation and embrace all global markets to intensify levels of interaction, interconnectedness or interdependence between the regions and societies that constitute the global community.

Restated, the study of different extents of product, activity, and region specificity for industry globalisation indicates two different phenomena: five knowledge-intensive service industries and five main regions for scope; supply (production) variables for intensity. The main characteristic of this kind of regional industry approach is that it adopts a systematic and holistic approach towards its global production oper-ations, and treats its interregional counterparts as part of a network of interrelated activities – particularly within regionally integrated areas, designed to promote the interests of the global integrated industry in toto.


The first section of this study explained the reason for selecting knowledge-intensive service industries as the research focus. To ensure uniform definitions of


knowledge-intensive service industries across regions/countries, the International Standard Industrial Classification (ISIC) codes are employed to classify the five knowledge-intensive service industries, as illustrated in Appendix Table A.

Furthermore, for intraregional and interregional value-added activities occurring inside knowledge-intensive service industries, this study required industrial pro-duction data for each region, which can be aggregated based on the data of each country in a region. The country data was obtained from the NSB Science and Engin-eering Indicators – 2002, 2004 database, which classifies production, consumption, exports and imports data for five knowledge-intensive service industries in 68 countries, and accounts for over 97 per cent of global economic activity [NSB, 2002, 2004], the key reason that the NSB world industry and trade database is adopted in this study.

The time period covered in the analysis included the years from 1980 to 2001, representing a 22-year period. This sample set represented a full global economic cycle: growth in the late 1980s followed by recession in the early 1990s and then renewed growth in the later 1990s and in the early 2000s. According to Neter et al. [1996], the number of cases gathered in this kind of exploratory regression depends on the size of the pool of potentially useful explanatory variables available. A general rule of thumb holds that at least 6 to 10 cases should exist for every variable in the pool. For this reason, 11 years are considered for each variable in the pool of potentially useful explanatory variables and for the response variable in each period, 1980 – 90 and 1991 – 2001. The separation of these two periods is consistent with the designation of ‘The Past’ and ‘The Present’ in the financial industry as noted by Scholes (1998) in his Alfred Nobel Memorial Prize address.

Data for the five global regions is analysed, namely North America (NA), East Asia (EA), European Union (EU ), Latin America (LA), and the rest of the world (RW ). These regions are selected based on them being major counterpart regions around the globe. Notably, NA includes the United States, Canada, and Mexico. Regarding the precise makeup of the regions used for the analysis: EA includes Japan, China, South Korea, Taiwan, Singapore, Hong Kong, India, Malaysia, Thailand, Philippines, and Indonesia; EU includes the 15 member states, Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, The Netherlands, Portugal, Spain, Sweden, and the United Kingdom; LA includes Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Ecuador, Honduras, Jamaica, Panama, Peru, Uruguay, and Venezuela. The rest of the world (RW ) region includes all of the other countries besides those belonging to North America, East Asia, the European Union, and Latin America.

Statistical Methodology

Bivariate correlation. To measure the relationship between variables, this investi-gation employed the bivariate correlations procedure, particularly Pearson’s corre-lation coefficient. Pearson’s correcorre-lation coefficient, which is based on the assumption that each pair of variables is bivariate, with a normal distribution, is a measure of the linear association for symmetric quantitative variables. Notably,


correlation coefficients range in value from – 1 (a perfect negative relationship) to þ1 (a perfect positive relationship). A value of 0 indicates no linear relationship.

Multiple regression. When presenting various models in the previous section, the consideration of using the regression model for the analysis was explained. Then the first-order multiple regression model with a response variable and four explana-tory variables is introduced, that is:


or Yi¼a0þ

X4 k¼1



As usual, Yidenotes the response in the ith trial, while X1,i, . . . , X4,irepresent the

values of the four explanatory variables in the ith trial. The five model parameters are a0,a1, . . . ,a4and the error term is 1i. The parametersa0,a1, . . . ,a4are sometimes

termed partial regression coefficients because they reflect the partial effect of one explanatory variable when the other explanatory variables are included in the regression model and held constant. Thus, the first-order multiple regression model is designed for explanatory variables whose effects on the mean response are cumu-lative. The method of ordinary least squares (OLS)is employed for finding ‘good’ esti-mators of the regression parametersa0,a1, . . . ,a4. If the same units are involved in all

variables of the regression model, the OLS regression coefficients can be compared to indicate which explanatory variables are most important to the response variable. To test the existence of a regression relation between the response variable and the set of explanatory variables, F-test statistics are used to test whether or not ak¼ 0 for

the first-order regression model. The adjusted coefficient of multiple determination, represented by Adj. R2, measures the proportionate reduction of total variation in the response variable associated with the use of the set of explanatory variables X1, . . . , X4.

The above statistical methodology can be implemented using the SPSS statistical software.


Based on Models 1 to 5, indicating the proposed relationship between intraregional production and the other regions’ production, and the above statistical methodology, in this section, this study is going to investigate the degree of global integration for five regions’ knowledge-intensive service industries, communications services, finan-cial institutions, business services, educational services, and health services.

Bivariate Correlation Analysis

By examining the bivariate correlation, for example, for each pair of variables, the production for five knowledge-intensive service industries of each region, as well as the results of Pearson correlation coefficients, are listed in Table 1. Taking any


T A B L E 1 D E S C R I P T I V E S T A T I S T I C S A N D B I V A R I A T E C O R R E L A T I O N S F O R K N O W L E D G E -I N T E N S -I V E S E R V -I C E -I N D U S T R -I E S Mean S.D. 1 2 3 4 Communications services Variable/1980 – 1990 1. NA (Pr) 214,539 39,467 2. EA (Pr) 112,147 19,447 0.95  3. EU (Pr) 102,085 16,792 0.98  0.99  4. LA (Pr) 12,451 1,825 0.75  0.77  0.79  5. RW (Pr) 100,091 19,580 0.98  0.99  0.99  0.76  Variable/1991 – 2001 1. NA (Pr) 485,970 136,582 2. EA (Pr) 207,713 80,060 0.99  3. EU (Pr) 276,218 92,309 0.99  0.99  4. LA (Pr) 46,808 12,963 0.98  0.98  0.98  5. RW (Pr) 188,132 23,221 0.97  0.97  0.97  0.94  Financial institutions Variable/1980 – 1990 1. NA (Pr) 852,428 253,014 2. EA (Pr) 178,230 53,338 0.98  3. EU (Pr) 343,490 73,844 0.95  0.97  4. LA (Pr) 72,169 20,269 0.77  0.79  0.81  5. RW (Pr) 212,773 48,500 0.96  0.99  0.99  0.80  Variable/1991 – 2001 1. NA (Pr) 1,176,210 197,867 2. EA (Pr) 543,055 59,530 0.96  3. EU (Pr) 733,624 94,282 0.99  0.95  4. LA (Pr) 209,383 68,481 -0.54 -0.57 -0.51 5. RW (Pr) 193,858 12,010 0.96  0.96  0.95  -0.64 Business services Variable/1980 – 1990 1. NA (Pr) 553,755 64,137 2. EA (Pr) 235,147 45,773 0.97  3. EU (Pr) 323,557 62,518 0.95  0.99  4. LA (Pr) 55,234 12,498 0.70 0.70 0.62 5. RW (Pr) 199,539 26,402 0.96  0.99  0.97  0.67 Variable/1991 – 2001 1. NA (Pr) 1,145,806 248,026 2. EA (Pr) 601,834 98,695 0.98  3. EU (Pr) 1,195,995 220,488 0.99  0.98  4. LA (Pr) 88,657 13,494 0.43 0.50 0.42 5. RW (Pr) 224,490 24,360 0.97  0.99  0.97  0.50 Educational services Variable/1980 – 1990 1. NA (Pr) 128,558 10,989 2. EA (Pr) 57,219 10,036 0.95  3. EU (Pr) 94,875 6,078 0.97  0.90  4. LA (Pr) 68,165 4,145 0.71 0.73 0.62 5. RW (Pr) 137,447 11,860 0.94  0.98  0.87  0.74  (Continued )


variable as random, or with no one variable automatically designated as the response variable, the communications services industry has highly significant ( p , .01) cor-relation coefficients between regional production of each region, and most corcor-relation coefficients are near 1, indicating a nearly linear relationship between the two vari-ables. Similarly, most of the correlation coefficients for the other knowledge-intensive service industries are also highly significant ( p , .01), or significant ( p , .05). Overall, the significant and higher (near 1) correlation coefficient indicates a linear relation between variables.

Building the Fitted Regression Model

This work is an exploratory observational study that searches for explanatory vari-ables that may be related to the response variable. To further complicate matters, five theoretical models developed above involve explanatory variables that are not directly and previously measurable, for example regional production. In each regression model, the bigger and more significant regression coefficients can be said to be more important in terms of the response variable. Therefore, the strategy of building the fitted regression model comprises four phases: data collection and preparation, which is described in the earlier section, reduction of explanatory vari-ables, model refinement and selection, and model validation.

All-possible-regressions procedure for variables reduction. Based on the above bivariate correlation analysis, most of the explanatory variables are highly intercorre-lated. Additionally, in this exploratory observational investigation, numerous expla-natory variables are used to formulate the regression model. Consequently, this study

T A B L E 1 C O N T I N U E D Mean S.D. 1 2 3 4 Variable/1991 – 2001 1. NA (Pr) 167,379 8,966 2. EA (Pr) 258,496 18,140 0.97  3. EU (Pr) 411,871 32,301 0.97  0.91  4. LA (Pr) 20,208 1,384 20.54 20.49 -0.60 5. RW (Pr) 69,549 3,539 0.93  0.92  0.84  20.24 Health services Variable/1980 – 1990 1. NA (Pr) 616,527 60,402 2. EA (Pr) 324,936 31,271 0.97  3. EU (Pr) 212,646 6,891 20.23 20.42 4. LA (Pr) 73,111 3,479 20.08 20.09 20.15 5. RW (Pr) 186,967 6,379 20.74  20.84  0.57 0.19 Variable/1991 – 2001 1. NA (Pr) 661,318 20,897 2. EA (Pr) 480,937 35,778 0.88  3. EU (Pr) 430,579 51,441 0.82  0.87  4. LA (Pr) 78,929 8,869 20.52 20.50 20.66 5. RW (Pr) 154,658 8,943 0.81  0.84  0.64 20.14 p ,.05; p ,.01


aims to reduce the number of explanatory variables to be used in the final model. Several reasons exist for this. A regression model with a limited number of explana-tory variables is easier to work with and understand in relation to cost and speed. Fur-thermore, the presence of numerous highly intercorrelated explanatory variables may significantly increase the variation of the regression coefficients, detract from the descriptive ability of the model, and fail to improve the predictive ability of the model, and may even worsen it.

In this exploratory observational investigation, when the potential explanatory variables are correlated with one another, the following criteria can assist in reducing the number of potential explanatory variables. An explanatory variable: (1) may not significantly influence the response variable, (2) may be small in relation to the response variable, and/or (3) may be subject to estimation errors.

Based on these criteria, the all-possible-regressions procedure can be used to con-sider all possible subsets of the pool of potential explanatory variables, select for detailed examination a few ‘good’ subsets, and then choose the ‘best’ set to be a fitted regression model.

Model refinement and selection. At this stage in the model-building process, the ten-tative regression model in this exploratory observational study must be checked for multicollinearity, and so on [Neter et al., 1996]. The key problem of multicollinearity is that no single set of regression coefficients can be chosen as reflecting the effects of different explanatory variables. Furthermore, the high degree of multicollinearity among the explanatory variables causes raised variability of the estimated regression coefficients.

A formal method of detecting the presence of multicollinearity that is widely used is via variance inflation factors (VIF). These factors measure the inflation of the var-iances of the estimated regression coefficients compared to the situation where the explanatory variables are not linearly related. The largest VIF value among all expla-natory variables is frequently used to indicate multicollinearity severity. A maximum VIF value exceeding 10 is frequently taken to indicate that multicollinearity may unduly influence the estimates of OLS regression coefficients. When no explanatory variable is linearly related to the other explanatory variables in the regression model, VIF equals 1 [Neter et al., 1996].

As listed in Table 2, all of the significant explanatory variables for the knowledge-intensive service industries have VIF values between 1 and 10, indicating low presence of multicollinearity. These phenomena indicate little difference between the estimated and true standardised regression coefficients, as well as high appropri-ateness of the fitted regression model for estimating mean responses.

Model validation. Model validity describes the stability and reasonableness of the regression coefficients, and the ability to generalise inferences based on the regression analysis [Neter et al., 1996]. Consequently Table 3 analyses the significance of the models, and demonstrates that most knowledge-intensive service industries models have both larger F-test values and near perfect (near 1) adjusted coefficients of mul-tiple determination, providing strong evidence of a fitted regression model.


When considering the significance of ordinary regression coefficients based on the specified criteria, this work found that each regression model varies for each knowledge-intensive service industry. For example, the regression model for the financial institutions industry has either only one or no significant explanatory vari-able, while the regression model for the other knowledge-intensive service industries has three, two, one, or no significant explanatory variables. In the communications services industry, the production of both East Asia and the European Union for the years 1980 – 90 have the same significant explanatory variable: the production of the rest of the world, while the production of North America, East Asia, and the

T A B L E 2

V I F O F O L S R E G R E S S I O N C O E F F I C I E N T S F O R K N O W L E D G E - I N T E N S I V E S E R V I C E I N D U S T R I E S


80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91-01 80 – 90 91 – 01

Variable Model 1 Model 2 Model 3 Model 4 Model 5

Communications services NA(Pr) EA(Pr) 1.00 EU(Pr) 2.69 2.69 LA(Pr) 2.69 8.47 2.36 8.47 2.36 8.47 2.69 RW(Pr) 8.47 2.36 8.47 2.36 8.47 Financial institutions NA(Pr) 2.42 1.41 1.41 1.41 EA(Pr) 2.68 EU(Pr) 9.56 2.93 LA(Pr) 2.68 2.42 1.41 2.73 1.41 2.93 1.41 RW(Pr) 9.56 2.73 Business services NA(Pr) 1.23 EA(Pr) 1.96 1.96 1.96 1.34 EU(Pr) 1.22 1.61 LA(Pr) 1.96 1.22 1.61 1.34 1.96 1.23 1.96 1.34 RW(Pr) 1.34 Educational services NA(Pr) 8.62 1.41 8.62 7.40 7.40 1.41 EA(Pr) 2.13 EU(Pr) 4.13 8.14 LA(Pr) 2.49 1.41 2.13 1.41 RW(Pr) 4.13 5.54 8.62 8.62 7.40 7.40 Health services NA(Pr) 2.66 EA(Pr) 3.67 1.33 1.22 1.33 EU(Pr) 1.70 1.96 1.71 1.71 1.22 LA(Pr) 1.19 1.02 1.21 1.33 1.33 RW(Pr) 4.89 1.02 4.14 1.71 1.71

Note that time period 80 – 90 indicates the years 1980 – 1990 and time period 91 – 01 indicates the years 1991 – 2001.


V A R I A B L E C O E F F I C I E N T S O F O L S R E G R E S S I O N R E S U L T S F O R K N O W L E D G E - I N T E N S I V E S E R V I C E I N D U S T R I E S Communications services

Period 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01

Variable Model 1 Model 2 Model 3 Model 4 Model 5

NA(Pr) EA(Pr) 0.28   EU(Pr) 2.45   1.23  LA(Pr) 21.70 5.61  0.26 3.61  0.85 3.89  20.81 RW(Pr) 2.78  0.97  1.47  0.79   1.83  F 91   216   396   370  369   227   323   167  Adj. R2 0.95 0.98 0.99 0.99 0.99 0.98 0.99 0.94 Financial institutions Period 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01

Variable Model 1 Model 2 Model 3 Model 4 Model 5

NA(Pr) 0.19  0.28   0.48   0.05   EA(Pr) 4.74   EU(Pr) 1.67   0.67  LA(Pr) 20.32 0.26 20.07 0.43 0.05 20.06 20.03 RW(Pr) 3.43 1.44   F 97   370   107   49  256   278   239   69  Adj. R2 0.95 0.99 0.96 0.91 0.98 0.98 0.98 0.93 Business services Period 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01

Variable Model 1 Model 2 Model 3 Model 4 Model 5

NA(Pr) 0.89   EA(Pr) 1.32   1.49   0.60  0.25   EU(Pr) 1.11   0.65  LA(Pr) 0.23 0.26 0.56 0.06 20.74 20.17 20.12 0.04 RW(Pr) 4.00   F 68   562   258   259  210   556   263   258  Adj. R2 0.93 0.99 0.98 0.98 0.98 0.99 0.98 0.98 (Continued ) KNOWLEDGE-INTENSIVE SERVICE INDUSTRIES 241



Educational services

Period 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01

Variable Model 1 Model 2 Model 3 Model 4 Model 5

NA(Pr) 0.24 2.02  0.72   4.95  20.36  0.44  EA(Pr) 1.11   EU(Pr) 1.13  0.13   LA(Pr) 20.92 0.64 0.17 0.93 RW(Pr) 0.37  1.31   0.62  20.18 23.98 0.74  F 184   339   118   66   86  121   14   97   91   Adj. R2 0.97 0.99 0.96 0.93 0.95 0.96 0.72 0.95 0.95 Health services Period 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01 80 – 90 91 – 01

Variable Model 1 Model 2 Model 3 Model 4 Model 5

NA(Pr) 0.43   EA(Pr) 2.23  1.04  20.15 0.26  EU(Pr) 1.73 20.73 0.39  21.17 0.24 LA(Pr) 0.38 20.97 20.14 21.73 0.37 RW(Pr) 1.13 1.75  20.63 1.93 0.47 F 134   18   186   34   19   5 13   17   Adj. R2 0.98 0.78 0.99 0.87 0.78 0.46 0.71 0.76 p ,.05; p ,.01; fsp ,.001 a

Unstandardised coefficients are reported.

Note that time period 80 – 90 indicates the years 1980 – 1990 and time period 91 – 01 indicates the years 1991 – 2001.



European Union for the years 1991 – 2001 have the same significant explanatory variables: the production of both Latin America and the rest of the world. For the financial institutions industry, the production of East Asia, European Union, and the rest of the world for the years 1991 – 2001 have the same significant explanatory variable: the production of North America, while the production of North America in the time periods 1980 – 90 and 1991 – 2001 can be explained by the production of East Asia and European Union, respectively.

In the business services industry, the intraregional production of North America, the European Union, and the rest of the world for the years 1980 – 91 have only one significant explanatory variable: the production of East Asia, while during 1991 – 2001 the production of North America and the production of European Union depend on each other. Note that during 1980 – 90 and 1991 – 2001 the intraregional production of Latin America in communications services, financial institutions, and business services industries have no significant variable. Additionally, the most complex case of investigating global integration occurs in the educational services industry. The production of North America during 1991 – 2001 has three significant explanatory variables: the production of the European Union, Latin America, and the rest of the world, in other words indicating nearly perfect global integration. In the same period, the production of East Asia, European Union, Latin America, and the rest of the world have the same significant explanatory variable: the production of North America. The production of Latin America in the educational services indus-try for the time period 1981 – 90 is not markedly connected to any other explanatory variable.

Finally, the more interesting cases of examining global integration with comparing two time periods happen in the health services industry. For example, the production of North America is considerably dependent on the production of East Asia and European Union for 1980 – 90, while it is markedly connected to the production of Latin America and the rest of the world for 1991 – 2001. A similar situation holds for the health services production of East Asia. The production of East Asia in 1980 – 90 is strongly linked with the production of North America and European Union, while it is significantly related to the production of the European Union and the rest of the world for 1991 – 2001. Moreover, the production of the rest of the world is strongly reliant on the production of East Asia for both time periods. Both the health services production of the European Union and Latin America for 1980 – 90 is not significantly related to any other explanatory variable.


This investigation created a new approach to measuring the global integration of the knowledge-intensive service industries in five global regions, with a focus on the patterns of industrial production, and with the goal of examining important but pre-viously untested notions regarding global integration. This procedure has allowed the relationship between intraregional economic activities and interregional linkages to be identified based on the proposition of Ohlin [1935], thus differentiating between multiple levels of regional production hubs [Buckley and Casson, 1998],


and also enables the assessment of global integration across spatial and temporal differences.

Based on the empirical evidence of this study, most regional knowledge-intensive service industries are incompletely integrated across regional borders, not perfectly globally integrated. As emerging concerns regarding the global integration of industries and multiple global regions are becoming central to new lasting paradigms [Guisinger and Brewer, 1998], this work addressed the postulations of Dunning [2000b] and Buckley [2002] regarding whether regionalisation is best conceived as an integral part of globalisation, or an alternative. The result of this investigation demonstrates that most regional economic activities, including production, of knowledge-intensive service industries can be characterised based on a state of incomplete global integration. This state of incomplete global integration corresponds to the diagnosis of semi-globalisation mentioned by Ghemawat [2003b], who indicated that international market integration still falls short of economic ideals regarding perfect integration. This condition of incomplete interregional integration is more difficult to comprehend than the extremes of perfect insulation and perfect integration because it highlights the crucial role of possible location specificity of key activities in the prospects of distinctive content for international business strategy, and also the coordinating role of international and interregional institutions in determining where the barriers to market integration at borders are high, but insufficient to completely insulate countries from each other.


In international business strategy of the knowledge-intensive service industries, the state of incomplete global integration has resulted in the ongoing debate between two opposing perspectives: (1) complete isolation at the borders, which would dictate localisation, and (2) complete integration, which would dictate standardisation. Cases intermediate to ‘one region’ and ‘one world’ present business practitioners of knowledge-intensive service industries with strategic options, and therefore these cases require some higher-level decisions regarding how the MNEs of knowledge-intensive service industries will compete to add value.

The critical role of incomplete global integration can be illustrated by measuring the impact of distance, which is proposed by Ghemawat [2001]. Geographic distance affects the cost of communications services, so it is of particular importance to companies whose operations require a high degree of coordination among highly dispersed people or activities. Ghemawat [2003a] provided an example of the impact of incomplete global integration on communications services industry. The valuable part of Cable & Wireless (C&W), once a cutting edge and renowned telecom company headquartered in London, is its regional rather than global unit. The crucial reason is that its regional unit consists of subsidiaries providing a full range of telecommunications services to consumer and business customers in 33 small countries around the world, mainly islands, whose communications services links with the outside world C&W still dominates. Additionally, economic distance affects the cost differentials of capital across borders, indicating how incomplete


global integration affects the financial institutions. The same situation exists for the incomplete global integration of the business services and health services.

As the core competencies of MNEs become knowledge intensive, this empirical finding demonstrates that selecting regional market access and incomplete global integration in the production and organisation of knowledge assets is becoming a crucial competitive advantage [Porter, 1994, 1996, 2000]. The empirical evidence illustrates that each knowledge-intensive service sector is likely to have its distinctive locational characteristics and, thus, industrial structure will differentially impact on the geography of economic activity.

As MNEs who produce knowledge-intensive services become multiregional, this investigation provides evidence of appropriate localisation, or customisation, strategy that can access the optimal regional mix for the utilising and operation of geographi-cally dispersed resources and capabilities, and for the supplying of knowledge-intensive services to end markets. Such a strategy, which embraces not only all the production and global market-serving activities of the MNEs, but also those of their competitors, suppliers, and customers, is becoming increasingly complex. Moreover, the locational choices of MNEs could become more critical to their overall competitive advantages.

Some exceptions to incomplete global integration in the knowledge-intensive service industries exist. One of these is the production of communications services, financial institutions, and business services industries. Those of Latin America are isolated from the other regional production, no matter which time period is examined. The same circumstance exists for the educational services and health services pro-duction of Latin America, and for the health services propro-duction of the European Union for 1980 – 90. The phenomenon of complete isolation implies the localisation of regional knowledge-intensive service industries.

Conversely, in the educational services industry, production of North America during 1991 – 2001 is markedly linked with the production of three regions, which indicates nearly perfect global integration. This example shows that the creation of competitive advantage is derived by firms from high coordination of geographically dispersed value-added activities, such as global production network. The level of edu-cational services standardisation would be high, with substantially less adjustment of these services to specific markets. Owing to the fact that firms must manage compli-cated linkages among cross-border operations, the type of the educational services industry of North America is therefore characterised as the most globally integrated.


For national and regional policy-makers, the state of incomplete global integration implies that governments create administrative and political distance to cross-border competition of knowledge-intensive service industries. For national security, governments might intervene to protect telecommunications services sector. Moreover, because of basic human rights, governments are prone to intervene to set quality standards and control pricing in the health services and educational services industries.



For academics, regionally related studies of global integration are at the progressive end of interdisciplinary research, and research is under way by trade and evolutionary economists, economic geographers, industrial sociologists, and business strategists. Owing to the empirical evidence of incomplete global integration among regional knowledge-intensive services production, future work can examine each region in depth in order to explore the global integration of national knowledge-intensive service industries. The relationship between international economic activities, indus-trial production and consumption, and international linkages, indusindus-trial exports and imports dominates the likelihood to national knowledge-intensive service industries.


Aharoni, Y. (1996) The organisation of global service MNEs, International Studies of Management and Organization, 26(2), pp.6 – 23.

Bauer, J.M. (1994) The emergence of global networks in telecommunications: transcending national regulation and market constraints, Journal of Economic Issues, 28(2), pp.391 – 402.

Boddewyn, J.J., Halbrick, M.B. and Perry, A.C. (1986) Service multinationals: conceptualization, measure-ment and theory, Journal of International Business Studies, 17(3), pp.41 – 57.

Brown, C.C. (1970) An emerging restiveness, Columbia Journal of World Business, 5(3), p.5.

Buckley, P.J. (2002) Is the international business research agenda running out of steam? Journal of International Business Studies, 33(2), pp.365 – 73.

Buckley, P.J. and Casson, M.C. (1998) Models of the multinational enterprise, Journal of International Business Studies, 29(1), pp.21 – 44.

Dahringer, L.D. (1991) Marketing services internationally: barriers and management strategies, Journal of Services Marketing, 5(3), pp.5 – 17.

Daniels, P.W. (1995) The internationalisation of advertising services in a changing regulatory environment, The Service Industries Journal, 15(3), pp.276– 94.

Dunning, J.H. (1988) The eclectic paradigm of international production: a restatement and some possible extensions, Journal of International Business Studies, 19(1), pp.1 – 31.

Dunning, J.H. (1998) Location and the multinational enterprise: a neglected factor?, Journal of International Business Studies, 29(1), pp.45 – 66.

Dunning, J.H. (2000a) Regions, globalisation, and the knowledge economy: the issues stated. In J.H. Dunning (ed.), Regions, Globalisation, and the Knowledge-Based Economy, Oxford: Oxford University Press, pp.7 – 41.

Dunning, J.H. (2000b) Introduction. In J.H. Dunning (ed.), Regions, Globalisation, and the Knowledge-Based Economy, Oxford: Oxford University Press, pp.1 – 3.

Enderwick, P. (1989) Some economics of service-sector multinational enterprises. In P. Enderwick (ed.), Multinational Service Firms, New York: Routledge, pp.3 – 34.

Enderwick, P. (1990) The international competitiveness of Japanese service industries: a cause for concern?, California Management Review, 32(4), pp.22 – 37.

Erramilli, M.K. (1990) Entry mode choice in service industries, International Marketing Review, 5(7), pp.50 – 62.

Erramilli, M.K. (1992) Influence of Some external and internal environment factors on foreign market entry mode choice in service firms, Journal of Business Research, 25, pp.263 – 76.

Erramilli, M.K. and Rao, C.P. (1990) Choice of foreign market entry modes by service firms: role of market knowledge, Management International Review, 30(2), pp.135– 50.

Erramilli, M.K. and Rao, C.P. (1993) Service firms’ international entry-mode choice: a modified transaction-cost analysis approach, Journal of Marketing, 57(3), pp.19 – 38.

Frits, P.K. (1987) Understanding services complexities, Transnational Data and Communications Report (May), pp.10 – 11.

Ghemawat, P. (2001) Distance still matters: the hard reality of global expansion, Harvard Business Review, 79(8), pp.13 – 47.


Ghemawat, P. (2003b) Semi-globalisation and international business strategy, Journal of International Business Studies, 34(2), pp.13 – 52.

Ghemawat, P. and Ghadar, F. (2000) The dubious logic of global megamergers, Harvard Business Review, 78(4), pp.65 – 72.

Greenaway, D. and Milner, C. (1986) The Economics of Intra-Industry Trade, Boston, MA: Basil Blackwell.

Greenwood, R. and Lachman, R. (1996) Change as an underlying theme in professional service organiz-ations: an introduction, Organization Studies, 17(4), pp.563 – 72.

Grossman, G.M. and Helpman, E. (1991) Innovation and Growth in the Global Economy, Cambridge, MA: MIT Press.

Grubel, H.G. (1987) All traded services are embodied in materials or people, International Executive, 29(3), pp.17 – 18.

Grubel, H.G. and Lloyd, P.J. (1975) Intra Industry Trade, London: Macmillan.

Guisinger, S. and Brewer, T.L. (1998) Introduction to the symposium, Journal of International Business Studies, 29(1), pp.1 – 3.

Hanson, G.H. (2001) The globalisation of production, NBER Reporter (Spring), pp.12 – 15.

Helliwell, J.F. (1998) How Much Do National Borders Matter? Washington, DC: Brookings Institution Press. Heskett, J.L. (1986) Managing in the Service Economy, Boston, MA: Harvard Business School Press. Hibbert, E. (2003) The new framework for global trade in services – all about GATS, The Service

Indus-tries Journal, 23(2), pp.67 – 78.

Kim, K., Park J.-H. and Prescott, J.E. (2003) The global integration of business functions: a study of multinational businesses in integrated global industries, Journal of International Business Studies, 34(4), pp.327– 44.

Kobrin, S.J. (1991) An empirical analysis of the determinants of global integration, Strategic Management Journal, 12(4), pp.17 – 31.

Kogut, B. (1985) Designing global strategies: comparative and competitive value-added chains, Sloan Management Review, 26(4), pp.15 – 28.

Krugman, P.R. and Obstfeld, M. (2000) International Economics: Theory and Policy, 5th edn, Reading, MA: Addison-Wesley.

Lee, J.-W. (1993) International trade, distortions, and long-run economic growth, International Monetary Fund Staff Papers, 40(2), pp.299– 328.

Levitt, T. (1983) The globalisation of markets, Harvard Business Review, 61(2), pp.92 – 102.

Lucas, R.E. Jr., (1988) On the mechanics of economic development, Journal of Monetary Economics, 22(1), pp.3 – 42.

Lovelock, C.H. (1983) Classifying services to gain strategic insights, Journal of Marketing, 47(3), pp.9 – 20. Lovelock, C.H. and Yip, G.S. (1996) Developing global strategies for service businesses, California

Management Review, 38(2), pp.64 – 86.

McCallum, J. (1995) National borders matter: Canada-US regional trade patterns, American Economic Review, 85(3), pp.615 – 23.

Makhija, M.V., Kim, K. and Williamson, S.D. (1997) Measuring globalisation of industries using a national industry approach: empirical evidence across five countries and over time, Journal of International Business Studies, 28(4), pp.679– 710.

McLaughlin, C.P. and Fitzsimmons, J.A. (1996) Strategies for globalizing service operations, International Journal of Service Industry Management, 7(4), pp.43 – 57.

Morgan, G. (1992) The globalisation of personal financial services: the European Community after 1992, The Service Industries Journal, 12(2), pp.193– 209.

National Science Board (NSB) (2002) Science and Engineering Indicators – 2002, Vol.2, NSB-02-2, Arlington, VA: National Science Foundation.

National Science Board (NSB) (2004) Science and Engineering Indicators – 2004, Vol.2, NSB-04-2, Arlington, VA: National Science Foundation.

Neter, J., Kutner, M.H., Nachtsheim, C.J. and Wasserman, W. (1996) Applied Linear Statistical Models, 4th edn, Chicago, IL: Irwin.

OECD (2001) OECD Science, Technology and Industry Scoreboard: Towards a Knowledge-Based Economy, Paris: Organisation for Economic Co-operation and Development.

Ofek, E. and Sarvary, M. (2001) Leveraging the customer base: creating competitive advantage through knowledge management, Management Science, 47(11), pp.1441 – 56.

Ohlin, B. (1935) Interregional and International Trade, Cambridge, MA: Harvard University Press. Ostry, S. (1998) Technology, productivity and the multinational enterprise, Journal of International






相關主題 :