ANALYSIS OF THE FINNISH MOBILE CLUSTER – ANY POTENTIAL IN MOBILE

SERVICES?

FOREWORD

For many years, Finland has been a pioneer in mobile telephony. In order to maintain this status quo, the Ministry of Transport and Communications has initiated “Mona” – a mobile services development program. Mona’s purpose is to bring together mobile operators, software developers and companies that apply mobile applications, with the aim of creating productive conditions for mobile application development in Finland.

This report, which focuses on an analysis of the Finnish mobile cluster, is one of the first concrete results of the Mona program. The goal of the report is to analyze the structure of the Finnish mobile cluster, identify the main drivers and obstacles to the success of mobile services, and assess the competitive potential of Finnish mobile services production.

Commissioned by the Ministry of Transport and Communications, this study was carried out by Mr. Ilkka Leppävuori of EPStar Ltd. His previous studies in this area, the cluster analysis report published in autumn 2001 and his Master of Science Thesis at the Tampere University of Technology, form the basis of this report. I wish to express my thanks to the author for conducting this interesting study and hope that it will be of help to industry observers both in Finland and abroad.

Helsinki, May 2002

Harri Pursiainen Director General, Communications Department Ministry of Transport and Communications

TABLE OF CONTENTS

FOREWORD

TABLE OF CONTENTS

ABBREVIATIONS AND DEFINITIONS

1 INTRODUCTION TO CLUSTER ANALYSIS...............................................................1

1.1 The mobile hype in Europe has vanished......................................................................1

1.2 Analysis leads to assessment of competitive potential ................................................1

1.3 Main emphasis on mobile services, not terminals ........................................................2

2 CLUSTERS AND NATIONAL COMPETITIVENESS..................................................3

2.1 Competitiveness at national level..................................................................................3

2.1.1 National advantage consists of four main determinants....................................................4

2.1.2 The determinants affect each other in a complicated way................................................7

2.1.3 Critique: Porter ignores globalization..............................................................................9

2.1.4 Critique: Porter ignores entrepreneurship......................................................................14

2.2 Networks and geographical clusters ...........................................................................15

2.2.1 Value network widens the concept of value chain.........................................................15

2.2.2 Industrial clusters – groups of interconnected companies...............................................17

2.2.3 Cluster dynamics – the development of ‘hot spots’ .......................................................20

3 ANALYZING THE FINNISH MOBILE CLUSTER.....................................................25

3.1 Mobile network technologies are developing rapidly.................................................25

3.2 Mobile environment – traditional and new models .....................................................27

3.2.1 The Finnish national diamond in the European Union.....................................................27

3.2.2 Step 1: identifying the players in the mobile cluster........................................................29

3.2.3 Step 2: presenting the traditional cluster map ................................................................31

3.2.4 Step 3: constructing the value chain of mobile services..................................................31

3.2.5 Step 4: developing the value network of mobile services...............................................32

3.3 The attitudes of mobile cluster companies..................................................................35

3.4 Several problematic issues and open questions ..........................................................41

3.4.1 Regulatory issues in privacy, e-commerce, and e-signature ...........................................42

3.4.2 Standardization problems concerning interfaces and architectures................................. 44

3.4.3 Biggest problems in business cooperation.................................................................... 46

3.5 Mobile services – a business customer viewpoint ..................................................... 47

3.5.1 Total of 50 companies in five industries were interviewed............................................. 48

3.5.2 Mobile services in use today, realistic plans for the future ............................................. 49

3.5.3 Mobile e-mail and industy-specific applications are interesting...................................... 51

4 CONCLUSIONS AND DISCUSSION........................................................................... 53

4.1 There is no business for chargeable end-user applications ....................................... 53

4.2 Nokia brought mobile communications into national focus........................................ 53

4.3 The conservative attitudes must change .................................................................... 54

4.4 Dangerous to rely on a single technology................................................................... 54

4.5 Potential in platforms and B-to-B applications ........................................................... 54

REFERENCES ........................................................................................................................ 55

ABBREVIATIONS AND DEFINITIONS

3G. The third generation of mobile networks, refers usually to UMTS technology.

Absolute advantage. Absolute advantage occurs when a producer requires a smaller quantity of inputs to produce a good than another producer requires.

Agglomeration economies. Positive externalities between firms that arise from spatial concentration. These externalities make firms in large cities more productive.

Cluster. Geographically proximate group of interconnected companies and associated institutions in a particular field, linked by commonalities and complementarities.

Comparative advantage. Comparative advantage occurs when a producer has a smaller opportunity cost when producing a good compared to another producer.

Economies of scale. Economies of scale occur when mass-production results in lower average cost than producing small batches.

D/MVN. Distance/magnitude value network. An extension to traditional value network models, showing also the distances between and the magnitudes of the actors.

DRM. Digital Rights Management. A technology that enables the secure distribution, promotion, and sale of digital media content on the Internet.

EDGE. Enhanced Data Rate for GSM Evolution. A faster version of GSM that boosts the data transmission speed up to 384 kbits/s with the help of a new modulation scheme.

FDI. Foreign Direct Investments, made by international firms in a country.

GDP. Gross Domestic Production. The market value for all final goods and services produced within a nation in a given time period.

GPRS. General Radio Packet Service. An extension of GSM that allows packet-switched data transmission with speed up 115 kbits/s and always-on connectivity.

GSM. Global System for Mobile Communication. A digital mobile telephone system that is used in more than 170 countries and allows data transmission rates up to 14 kbits/s. In Europe, the GSM system operates at the 900 MHz and 1 800 MHz frequency band.

Hot spot. Regional cluster of firms that grow more rapidly than other industry participants and have the same or very similar immobile physical resource requirements in the long run.

HSCSD. High-Speed Circuit Switched Data. An extension of GSM that allows data transmission speed up 58 kbits/s by using several time slots instead of only one time slot.

ICT cluster. Information and communications technology cluster. An industrial cluster where knowledge capital plays central role and other production factors are rather insignificant.

MDS. Multidimensional Scaling. A set of multivariate statistical methods for estimating the parameters in and assessing the fit of various spatial distance models for proximity data. MDS is also sometimes referred to as ‘perceptual mapping’.

Mobile Cluster. The fast-growing core of the Finnish telecom cluster that focuses on the mobile side of telecommunications.

MNE. Multinational enterprise. Companies established in different countries and so linked that one or more of them is able to exercise a significant influence over the activities of others and, in particular, to share knowledge and resources with the others.

Necessity entrepreneurship. Entrepreneurship caused by the situation where people have no better choices for work than being entrepreneur.

OMA. Open Mobile Architecture. An initiative to create a non-fragmented, interoperable global market for the next generation of mobile services.

Opportunity entrepreneurship. Entrepreneurship reflecting the situation where people voluntarily become entrepreneurs.

Punctuated equilibrium. Evolutionary change that is not gradual but rather proceeds in fits and starts. Long periods of stasis (equilibrium) are interrupted (punctuated) by sudden brief periods of rapid change. During the period of stasis, selection pressure is conservative, maintaining roughly constant organism designs. During the punctuation period, large shifts in organism designs take place.

SBU. Strategic Business Unit. A unit within the overall corporate entity for which there is an external market for its goods and services that distinct from that of other SBUs.

SMS. Short Message Service. A service for sending messages of up to 160 characters to GSM mobile phones.

UMTS. Universal Mobile Telecommunications System. A mobile communication system that supports a wide range of voice, data and multimedia services and allows data transmission speed up to 2 Mbits/s. Compared to GSM, UMTS offers a new air interface operating at around 2 GHz and a packet-based network architecture that supports both voice and data services.

Value Chain. The set of activities performed one after another to create value to the final customer.

Value Network. Multienterprise network of relationships, focused on integration of information flows to exploit information and knowledge in the network for strategic business objectives.

Value System. Larger stream of activities in which the value chain of a single company in a particular industry is embedded.

WAP. Wireless Application Protocol. An open, global protocol specification that empowers mobile users with wireless devices to easily access and interact with information and services.

1

1 INTRODUCTION TO CLUSTER ANALYSIS

This study analyzes the current situation of the Finnish mobile cluster, putting special emphasis on assessing the competitiveness of mobile services development. The analysis is part of the Finnish mobile cluster development program Mona, financied by the Ministry of Transport and Communications Finland and coordinated by EPStar Ltd.

1.1 The mobile hype in Europe has vanished

The cluster concept was made popular by Porter (1990) and introduced in Finland by Penttinen (1994). At that time, the focus of cluster discussion was on the Finnish forest cluster. Recently, the focus of cluster discussion has shifted into the Finnish ICT cluster, dominated and made famous by Nokia. The Finnish ICT cluster has been in center of attention in many studies (see for instance Steinbock 2000, Rönkkö 2001, and Paija 2001).

During the last year, the hype around telecommunications industry has vanished. The huge fees paid for 3G licences in Europe have brought teleoperators into trouble as the launching of 3G services has been delayed. Also the many content providers, once highly overvalued in the market, are having hard times when fighting for survival. The whole ICT industry can now be studied in a realistic way, as the market again has its “feet on the ground”.

The Finnish mobile cluster is characterized by the dominance of Nokia. The role of the world’s largest mobile phone manufacturer can naturally not be bypassed. Still, we try to focus on other factors in the cluster development than the presence of a single dominant firm. This aims at creating a balanced mobile cluster, including strong international manufacturers, operators, as well as application developers.

1.2 Analysis leads to assessment of competitive potential

The goal of this study is to analyze the structure of the Finnish mobile cluster, identify the main drivers and obstacles for the success of mobile services, and assess the competitive potential of the Finnish mobile services production.

From the above-mentioned goal, we can derive the main objectives for this study. In analyzing the structure of the cluster, we (1) identify the relevant mobile cluster players, (2) construct traditional mobile cluster and value chain models of these cluster players, and (3) develop a new value network model that provides us with more information than the traditional ones.

In the second part, we identify the main obstacles for the success of mobile services production by (1) mapping the current attitudes of mobile cluster companies towards the current conditions, (2) presenting the problems concerning regulation, standardization, as well as business cooperation, and (3) studying the current and future use of mobile services in Finland.

Finally, the main conclusion of the study is an assessment of the competitive potential of the Finnish mobile services production. This assessment is mainly based on the traditional SWOT-model.

2

1.3 Main emphasis on mobile services, not terminals

The focus of this study is in the provision of content and mobile network access. This is illustrated in figure 1, which shows the center of attention in the three-layer value chain. We are thus putting only minor emphasis on the terminal manufacturing business.

Focus of this study

Platform developer

Customer

Terminalretailer

Distributionchannel

Terminalvendor

Contentservices

Terminal

Access services

Networkvendor

Networkoperator

Serviceoperator

Content providerContent owner

Figure 1. The focus of the study, defined with the help of the value chain.

The technology used in mobile services is not in the focus of this study. Therefore, we present the past, present and future mobile network technologies very briefly, just to support the reader in understanding other parts of the analysis. We are thus not limiting ourselves into a single dominant technology, such as GPRS or UMTS, but focusing instead on other, more relevant success factors.

Also the characteristics of successful mobile services are excluded from this study. In other words, we are not giving detailed recommendations for companies on how to build successful applications, what the customers value, how much the are willing to pay for mobile services, and so on. Instead, we focus on making the Finnish mobile cluster as a whole more competitive.

3

2 CLUSTERS AND NATIONAL COMPETITIVENESS

“Why do some nations succeed and others fail in international competition?” This was the main question Porter (1990) wanted to be answered, when he started studying national competitiveness. By ‘national competitiveness’ Porter means simply the nation’s productivity, because it is the prime determinant of a nation’s standard of living in the long run. Here, we will first present the relevant foundations in national competitiveness. After that, we will discuss the role of value networks, clusters, and hot spots.

2.1 Competitiveness at national level

Competitiveness at national level is a complex issue, where most of the classic explanations have been both insufficient and conflicting. Competitiveness is not only a macroeconomic phenomenon driven by such variables as exchange rates, interest rates and government deficits. Neither does it depend only on having cheap and abundant labor or possessing bountiful natural resources. Not even efficient government policy, including export promotion and subsidies, can exclusively help a nation to be competitive. A final popular but still lacking explanation has been that competitiveness depends on a nation’s management practices, including labor-management relations. These explanations are based on classical trade theories, i.e. ‘absolute advance’ discovered by Adam Smith and ‘comparative advantage’ defined by David Ricardo. (Porter 1990, pp. 3–5)

In many industries, however, comparative advantage has long been an incomplete explanation for trade. This is particularly true in those industries involving sophisticated technology and highly skilled employees, precisely those most important to national productivity. This incompleteness is mainly caused by technological change and globalization, but also fleeting advantages: the lowest-cost source for a natural resource can shift overnight as new technology allows the exploitation of resources in places previously deemed uneconomical or impossible. (Porter 1990, pp. 12–15)

A range of new explanations for trade has been proposed during the 20th century. One is ‘economies of scale’, which give the nation’s firms a cost advantage that allows them to export. Another explanation is that of ‘technology gap’, claiming that nations will export in industries in which their firms gain a lead in technology. Also early demand in a nation’s home market has been used as an explanation for success in trade, for instance by Vernon (1966). A final explanation suggests that national success is increasingly based on that the nation operates as home base for leading multinational companies, instead of only for domestic firms. (Porter 1990, pp. 16–18)

Considering all these explanations as insufficient, Porter (1990, pp. 19–20) summarizes the subjects that should be covered in the theory of national competitiveness. It should explain why firms from particular nations choose better strategies than those from others, as well as why a certain nation is home base for successful global companies. Moreover, it should explain why some nations are better than others at creating advantages that are essential to high productivity and, finally, how a nation provides an environment in which its firms in a particular industry are able to improve and innovate faster than their foreign rivals. This chapter goes first through this theory, called Porter’s ‘diamond model’, and then complements the model with aspects of globalization and entrepreneurship.

4

2.1.1 National advantage consists of four main determinants

Porter’s (1990) ‘diamond’ of national advantage is illustrated in figure 2. The diamond consists of four determinants: (1) factor conditions, (2) demand conditions, (3) related and supporting industries, and (4) firm strategy, structure and rivalry. The diamond is completed by two more factors that influence all the determinants: change and government.

Factor conditions

Related and supporting industries

Firm strategy, structure and rivalry

Demand conditions

Government

Chance

Figure 2. The determinants of national advantage as presented by Porter (1990, p. 127).

The factor conditions of a country are formed by various factor endowments that can be divided into a number of different categories: (1) human resources, i.e. the quantity, skills and cost of personnel available, (2) physical resources, including the abundance, quality, accessibility and cost of the nation’s physical traits, (3) knowledge resources: the nation’s stock of scientific, technical and market knowledge bearing on goods and services, (4) capital resources, meaning the amount and cost of capital available to finance industry, and (5) infrastructure: the type, quality and user cost of the transportation system, mail delivery, health care and so on. (Porter 1990, pp. 74–75)

While the above-mentioned groups are broadly speaking equally important, factors can also be divided hierarchically in at least two different ways. First, there is a distinction between basic factors and advanced factors. Basic factors, including natural resources, climate, location, semiskilled labor and debt capital, are important mainly in agriculturally based industries and in those with modest technological and skill requirements. In contrast, advanced factors – such as data communications infrastructure, highly educated personnel and university research in sophisticated disciplines – are today the most significant ones for competitive advantage. The second distinction can be made between generalized factors and specialized factors. Generalized factors include things like the highway system or supply of debt capital that can be deployed in a wide range of industries. Specialized factors involve narrowly skilled personnel, specific knowledge base and other factors with relevance to only a limited range of industries. (Porter 1990, pp. 77–80)

Factors can also be divided into those inherited by a nation and those that are created. Porter (1990, pp. 80–81) states that those factors most important in achieving higher-order and more sustainable competitive advantage are created, not inherited. Furthermore, he pinpoints that no nation can possibly create and upgrade all types of factors through investments. Actually,

5

competitive advantage can grow out of having disadvantages in some factors, which forces the nation’s firms to ‘invent around’ them.

The second determinant, home demand, has been studied already by Marshall (1920), who stated that the most important influence of home demand on competitive advantage is through the mix and character of home buyer needs. Porter (1990, pp. 87–92) presents three characteristics of home demand composition. The first is the segment structure of home demand, meaning that the size of segments may be important in industries where economies of scale can be achieved and, more importantly, the significance of certain segments at home shapes the attention and priorities of a nation’s firms. The sophistication of domestic buyers forms the second characteristics of home demand – a nation’s firms gain competitive advantage if domestic buyers are among the world’s most sophisticated and demanding buyers for the product of service. Third, anticipatory buyer needs, meaning that home demand provides an early warning indicator of buyer needs that will become widespread, is also a way to gain national advantage.

If the composition of home demand has the right characteristics, its size and pattern of growth can reinforce national advantage in an industry. Large home market size can lead to competitive advantage in industries with economies of scale, by encouraging a nation’s firms to invest aggressively. Furthermore, the presence of many independent buyers instead of just one or two dominating customers creates a better environment for innovation. The rate of growth is also important: it leads firms to adopt new technologies faster and to build efficient facilities with the confidence that they will be utilized. Provided that it anticipates buyer needs in other country, early local demand for a product or service in a nations creates advantage for local firms compared to their foreign rivals. The same applies also in early market saturation – it creates pressures to push down prices, introduce new features, improve product performance and provide other incentives to replace old products with newer versions. (Porter 1990, pp. 93–96)

Internationalization of domestic demand is also a factor that shapes a nation’s home demand conditions. First, mobile or multinational buyers that operate both in local and international markets increase the international sales of local firms and thereby create an advantage for the nation’s firms. Another situation that is favorable for local firms is when domestic needs and desires get transmitted to foreign buyers, for instance through exports that spread the country’s culture. (Porter 1990, pp. 97–98)

Related and supporting industries form the third determinant of national advantage. The importance of complementarities and linkages among industries, primarily through providing demand for one another’s products, was emphasized already by Hirschman (1958). Internationally competitive supplier industries create advantages in downstream industries for instance via efficient, early and rapid access to the most cost-effective inputs. More importantly, home-based suppliers can help firms to perceive new methods and to apply new technology by quick access to information and new innovations, provided that the firms have close working relationships. The optimal situation for a nation’s firms is when their suppliers themselves are global competitors. (Porter 1990, pp. 101–104)

The presence of strong related industries, meaning firms that coordinate and share activities when competing or have complementary products, often leads to new competitive industries. It provides opportunities for information flow and technical interchange. However, the benefits of

6

both home-based suppliers and related industries depend on the rest of the national ‘diamond’. (Porter 1990, pp. 105–107)

The fourth determinant of national competitive advantage is formed by the way that firms are created, organized and managed, as well as the nature of domestic rivalry. No one managerial system is universally appropriate; nations tend to succeed in industries where management practices favored by the national environment are best suited. The differences among nations in firm strategies and structures are numerous: the strength of individual initiative, the relationship between labor and management, general attitudes toward authority and willingness to operate globally are just some of the major issues. (Porter 1990, pp. 107–109)

The goals of companies, individuals and entire nations is also an issue where sharp differences exist. Nations will succeed in industries where goals and motivations are aligned with the sources of competitive advantage. Usually these industries get the status of national priority and are able to gather the most talented people and make them strongly committed to their work. Company goals are determined by ownership structure, the nature of the corporate governance and several other things mainly reflecting the characteristics of the nation’s capital markets. Concerning the factors that affect the goals of individuals, Porter (1990, pp. 113–114) emphasizes the various economic incentives, such as reward systems or tax structure. However, especially in Nordic countries, the individual motives are usually something else than just financial – simply being respected and recognized as a competent person is valuable for most individuals.

Competitive nations often have a number of strong local rivals, who push each other to lower costs, improve quality and service, and create new products and processes. Domestic rivalry needs not to be restricted to price; rivalry in other forms such as technology may well lead to more sustainable national advantage. A number of domestic competitors is not itself sufficient to determine success. If there is no effective rivalry among the competitors, the advantages of domestic competition are nullified. Also new business formation is vital to the upgrading of competitive advantage, because it feeds the process of innovation in an industry. New companies serve new segments and try new approaches that older rivals fail to recognize or to which they are too inflexible to respond. (Porter 1990, pp. 117–122)

Also chance events have played a role in the history of most of the successful industries. Some examples of chance events influencing competitive advantage are acts of pure innovation, major technological discontinuities, significant shifts in world financial markets or exchange rates, and wars. Chance events are important because they create discontinuities that allow shifts in competitive position. They can nullify the advantages of previously established competitors and help new firms to achieve competitive advantage in response to new and different conditions. Chance events play their role partly by altering conditions in the ‘diamond’. They often have asymmetric impacts on different nations. (Porter 1990, pp. 124–125)

Finally, the government’s role in national competitive advantage is in influencing the four determinants, either negatively or positively. The government can, for instance, affect factor conditions through subsidies or act as a major buyer for some industries. Government policy, in turn, can be influenced by the determinants. Early home demand for a product, for example, may lead to early introduction of government standards considering the product. (Porter 1990, pp. 126–128)

7

The studies concerning national competitiveness have resulted in a number of implications for both companies and government. The main implications for companies, proposed by Porter (1998, pp. 191–194), include the following: (1) create pressures for innovation instead of avoiding them, (2) to stay dynamic, seek out the most capable competitors as motivators, (3) establish early-warnings systems to get early-mover advantages, (4) improve the national diamond by helping the domestic buyers, suppliers, and distribution channels to upgrade their competitive advantages, (5) welcome domestic rivalry, (6) globalize to tap selective advantages in other nations, (7) use alliances only as a selective tool on a temporary basis or involving noncore activities, and (8) locate the home base to support competitive advantage.

For government, Porter (1998, pp. 184–190) has compiled another list of the implications of his cluster studies. Government’s proper role is as a catalyst and challenger; it is to encourage companies to raise their aspirations and move to higher levels of competitive performance. The agenda for government includes the following: (1) focus on advanced, specialized factor creation, (2) avoid intervening in factor and currency markets, (3) enforce strict product, safety, and environmental standards to pressure companies to improve quality, upgrade technology, and to respond to consumer and social demands, (4) sharply limit direct cooperation among industry rivals; allow cooperative research only under certain limited conditions, (5) promote goals that lead to sustained investment in human skills, in innovation, and in physical assets, (6) deregulate competition by enforcing strong domestic antitrust policies, and (7) reject managed trade, such as orderly marketing agreements or voluntary restraint agreements.

Porter’s diamond model is the first framework that combines the aspects of national competitiveness in a structured way. The model has been heavily criticized; this criticism is presented thoroughly in chapters 2.2.3 and 2.2.4. Also, the credibility of Porter’s national studies is threatened because of his unprofessional statements like “Finland’s environmental cluster emerged from pollution problems created by local process industries” (Porter 1998, p. 238). Still, the model is useful and easy to understand, and leads to concrete implications for both companies and governments.

2.1.2 The determinants affect each other in a complicated way

The individual determinants of national advantage combine into a dynamic system. They reinforce each other and grow over time in fostering competitive advantage in an industry. Every determinant can affect every other determinant, though some interactions are stronger than others. (Porter 1990, pp. 131–132)

Virtually every nation invests in factor conditions – what varies is a nation’s rate of investment, its desired standard of performance, and how well the institutions involved creating factors are administered. Factor creation is stimulated by strong domestic rivals and perceived national challenges. Home demand influences priorities for factor-creating investments. Finally, related and supporting industries stimulate the creation of transferable factors, e.g. skilled personnel or related educational programs. (Porter 1990, pp. 132–135)

Home demand conditions for an industry reflect many national attributes such as population, climate, social norms, and the mix of other industries in the economy. Yet the other determinants play an important role as well. Domestic rivalry has perhaps the most important influence; intense rivalry makes home demand larger and more sophisticated. Also, a group of rivals builds

8

awareness and recognition of the industry, which stimulates home demand. Sophisticated factor-creating mechanisms attract foreign students and participation by foreign firms, which pulls through the nation’s products. The image of world-class related and supporting industries spills over to benefit an industry. Moreover, internationally successful industries producing complementary products pull through foreign demand for the industry’s product. (Porter 1990, pp. 136–138)

The presence, breadth, and international success of related and supporting industries in a nation is also influenced by other determinants. Factor-creating mechanisms are usually transferable to related and supporting industries. A group of domestic rivals encourages the formation of more specialized suppliers and related industries. Finally, large or growing home demand stimulates the growth and deepening of supplier industries. (Porter 1990, pp. 138–140)

Domestic rivalry is influenced by other determinants as well, particularly in terms of the number, skills, and strategies of domestic rivals. Factor abundance or specialized factor-creating mechanisms spawn new entrants, usually start-ups, into an industry. New entrants also emerge from related and supporting industries, bringing with them skills and resources from their core businesses. In addition, world-class users themselves may enter supplying industries and early market penetration of a product feeds entry to an industry. (Porter 1990, pp. 140–143)

In the most successful national industries, it is often hard to know where to start in explaining competitive advantage: the interplay and self-reinforcement of the determinants are usually very complex and the system is constantly in motion. Advantages in the entire ‘diamond’ are not always necessary for competitive advantage in simple and resource-intensive industries or industry segments. Competitive advantage in more sophisticated industries and segments, however, rarely results from only a single determinant. Still, a nation does not always need to have advantages in all determinants to succeed internationally. For instance, in small nations like Finland, missing domestic rivalry may sometimes be offset by openness to international competition and global strategies in which the nation’s firms meet foreign rivals. (Porter 1990, pp. 144–146)

Some determinants of the ‘diamond’ provide a more sustainable basis for advantage than others. Conditions that provide dynamic advantages – such as faster innovation, early mover advantages, and pressures for upgrading – are more important than those conferring static advantages, as for example low factor costs. Foreign competitors can sometimes duplicate one advantage or another, but the entire system is difficult and time-consuming to copy. Therefore, sustainable national advantage arises when the system is unique. (Porter 1990, pp. 147–148)

As industries evolve, a nation’s firms risk the loss of competitive advantage. Porter (1990, pp. 166–170) lists various reasons for eroding advantage. First, factor conditions can deteriorate e.g. if a nation falls behind in the rate of creation and upgrading of factors. Second, local needs may diverge from those in other advanced nations, thus pulling a nation’s firms in the wrong directions. Third, firms will face difficulties in maintaining advantage if domestic buyers lose their sophistication. Fourth, technological change can lead to compelling specialized factor disadvantages or the need for new and missing supporting industries. Fifth, if goals in a national industry are inconsistent with sustained investment, competitive advantage will be lost. Sixth, even if a nation’s firms know how they should change to sustain competitive advantage, they might become inflexible to adjustments. The seventh, and often the most fatal, cause of lost national advantage is the ebbing of domestic rivalry.

9

As the diamond model itself is clear and easy to understand, Porter’s statements about the relationships among the determinants are confusing. Obviously, as the global environment is dynamic and blurred, there is no easy way to study and present the ‘big picture’. The main message is, however, made clear: nations should focus on creating dynamic, sustainable advantages instead of practicing traditional, investment-driven industrial policy.

2.1.3 Critique: Porter ignores globalization

Even though Porter’s ‘national diamond’ is the best-known foundation in the field of national competitiveness, the scope of his theory is too narrow to be applied globally. Despite using various countries as case studies, his point of view is very American and does not suit well for small countries.

Dunning (1993) argues that Porter’s view underestimates the significance of the globalization of production and markets for the competitive advantage. He presents some distinguishing features of the global economy of the 1990s, which point out that “almost all the points on Porter’s domestic diamond have to be reconsidered”. These are listed below.

• The value generating assets of most industrial countries in a global economy are increasingly taking the form of creating assets rather than having natural assets. Many of these created assets are intangible and belong to commercial enterprises, not to countries or governments.

• Multinational enterprises (MNEs) play an increasing role in the global economy. Instead of focusing on traditional foreign direct investments (FDI), these MNEs are becoming more pluralistic in their ways of global involvement. An increasing proportion of the assets of firms of a particular country are acquired from or located in another country.

• The role of government needs to be re-evaluated as a result of the globalization. Like the strategy of firms of one nationality has to take account of their foreign rivals’ behavior, also governments need to take account of the strategies of other governments.

The main problem in Porter’s diamond is that “rather than considering the domestic influences on the diamond as a special case of the global influences, he prefers to consider the latter as an ‘add-on’ to the former.” The principle of the diamond may still be good, but its geographical constituency has to be established on another criteria than national political borders. In short, Porter has underestimated the role of the modern MNE as an integrating force in the global economy. (Dunning 1993) The diamond model complemented with international business activity (IBA), presented by Dunning (1990), is shown in figure 3.

10

Factor conditions

Related and supporting industries

Firm strategy, structure and rivalry

Demand conditions

Government

ChanceInternational

business activity

Figure 3. The diamond model and international business activities, adapted from Dunning (1990).

Rugman & D’Cruz (1993) criticize Porter’s narrow view on FDI. Porter defines only outward FDI as being valuable in creating competitive advantage and does not fully understand the nature of two-way FDI. Moreover, Rugman & D’Cruz (1993) believe that multinational activity cannot be included as third exogenous variable in the diamond, as proposed by Dunning (1990), nor added into any of the four determinants. Instead, they present a ‘double diamond’ model based on their experience of North American trade, as illustrated in figure 4.

Canadian-basedresources

North Americanbusiness

Supportinginfrastructure

Canadian customers

Canadiangovernment

U.S.-basedresources

Supportingindustries and

institutions

U.S. customers

U.S. governmentExports outside North America

Exports outside North America

Figure 4. The North American ‘double diamond’ as presented by Rugman & D’Cruz (1993).

This ‘double diamond’ model treats the United States and Canada as a single market. As a result, a strategy for a company in North American diamond would include: (1) developing innovative new products and services that simultaneously meet the needs of U.S. and Canadian customers, (2) drawing on the support industries and infrastructure of both U.S. and Canadian diamonds, and (3) making free and full use of the physical and human resources in both countries. The main conclusion is that a mechanical application of Porter’s methodology to Canadian situation would

11

result in an erroneous evaluation of the sources of Canada’s international competitiveness. (Rugman & D’Cruz 1993)

Another critic of Porter’s diamond is Hodgetts (1993). He has found some important facts that have to be realized when applying Porter’s foundations to international business strategy. These are presented in the following list.

• The government is of critical importance in influencing a home nation’s competitive advantage. However, government actions can backfire and end up creating a “sheltered” domestic industry that is unable to compete in the worldwide market (Rugman & Verbeke 1990).

• While chance is a critical factor in international business strategy, it is extremely difficult to predict and guard against.

• In the study of international business Porter’s model must be applied in terms of company-specific considerations and not national advantages.

• Since most countries of the world do not have the same economic strength or affluence as those studied by Porter, it is highly unlikely that his model can be applied to them without modification.

• A final questionable statement in Porter’s framework is that reliance on natural resources is insufficient to create worldwide competitive stature.

The validity of Porter’s theory is also questioned by Cartwright (1993), based on the experiences in New Zealand. He denotes that in Porter’s view, the customer requirements and competitive pressures faced by firms at home are held to be the principal reason for international success. However, similar stimulation and learning processes achieved by firms through their offshore activities are not considered to be sources of competitive advantage.

In addition to a nation’s home diamond, Cartwright (1993) argues that small, open countries also have an ‘offshore diamond’. It consists of five determinants: (1) capture of offshore factor creation, (2) linkage to related and supporting industries in the offshore environment, (3) access to demanding customers in offshore markets, (4) access to rivalry in offshore markets, and (5) the extent to which the industry has international goals and structures. In a study made among firms in New Zealand, all these were considered as additional sources of competitive advantage.

Rugman & Verbeke (1993) state that Porter’s treatment of foreign-owned subsidiaries in smaller countries is incomplete and misleading. They argue that the core competencies of large MNEs and the innovative processes occurring within these firms need not depend upon the characteristics of a single home base. Moreover, the strategic management of subsidiaries is much more complex than portrayed in Porter’s framework. Figure 5 illustrates four possibilities as to the potential impact of national diamonds on the global competitiveness of MNEs. The horizontal axis measures the impact of the initial home country diamonds on the global competitiveness of MNEs, whereas the vertical axis assesses the impact of other nation’s diamonds. This shows how narrow Porter’s view is, as he only focuses on quadrant 4 in the figure.

12

1. 2. “Also foreign diamonds have impact” (Rugman & D’Cruz 1993)

3. “Large MNEs are independent”(Bartlett & Ghoshal 1989; Ohmae 1990)

4. “Porter’s view”(Porter 1990)

Impact of other nation’s diamonds on global competitiveness

Impact of initial home country diamond on global competitiveness

High

Low

HighLow

Figure 5. The impact of national diamonds on global competitiveness according to Rugman & Verbeke (1993).

Figure 6 assesses the impact of a subsidiary/SBU or its country diamond on the corporate strategy of an MNE. The vertical axis reflects the role of the host country diamond on the development of core competencies of the MNE. The horizontal axis measures the extent to which the activities of the subsidiary/SBU are integrated with other parts of the MNE. This illustrates that Porter – only focusing on cells 1, 2 and 3 – does not include the possibility of multinational, linked diamonds in his framework. Thus, the framework needs to be modified to take account the current nature of multinational enterprises. (Rugman & Verbeke 1993)

1. “Subsidiaries to overcome tariff barriers etc.” (Porter 1990)

2. “Higher coordination; host country diamond is of little relevance” (Porter 1990)

3. “New home base, little coordination required” (Porter 1990)

4. “Globally rationalized operations” (D’Cruz 1986)

6. “The MNE is a network of exchange relationships among subunits”(Ghoshal & Bartlett 1990)

5. “Polycentric firms where individual subsidiaries control the core competencies”(Doz & Prahalad 1981)

Integration of subsidiary/SBU operations with other parts of the MNE

Role of host country national diamond on development of core competencies of MNE

HighLow

None

High

Diamond network

Figure 6. Assessing the strategic impact of a subsidiary/SBU host country diamond on the MNE’s corporate strategy, presented by Rugman & Verbeke (1993).

In the case of small, open economies, like Finland, the relevance of Porter’s diamond model is still open for discussion. In Finland, the distinguishing driver to internationalization is the smallness and openness of domestic markets, which does not allow the use of domestic diversification as a

13

sustainable growth strategy. (Luostarinen 1991) Obviously, the need of one strong home base for internationally successful companies initially located in small country partly loses its relevance.

Lahti (2000) presents an additional reason for the international success of the Nordic companies. Having their long history as state-owned research laboratories, the core units of the Nordic IT companies have been able to combine the university type of organization culture with the competitive behavior. In the new arenas of mobile commerce, this kind of entrepreneurial culture is powerful. Finally, Penttinen (1994) summarizes in table 1 the criticism that Porter has faced with his diamond model.

Table 1. Summary of the main points of critique, modified of the one presented by Penttinen (1994).

Issue Porter’s view The core of the critique Porter’s answer

Where is competitive advantage created?

Created in a geographically limited area within the nation. The MNE needs a home base.

No longer created in the nation – the determinants of the diamond are sourced all over the world. The MNE does not need a home base.

The geographic scope of competition is global, but the geographic locus of competitive advantage is the home base.

Foreign direct investments (FDI)

Outward FDI is more valuable than inward FDI. Local ownership creates greater benefits than foreign ownership.

Inward FDI is as valuable as outward FDI and foreign firms are as important to a nation as domestic firms. There is no capital loyal to the home base.

In the case of a weak diamond, foreign subsidiaries can more easily be drawn out of a country than domestic firms.

Small open economies

The diamond applies to all nations; demand and rivalry have to be present in the home base. Mergers and acquisitions are a threat to domestic rivalry.

The diamond does not suit small open countries, where home demand is insufficient to gain economies of scale. Mergers and acquisitions are needed e.g. to be able to f inance R&D projects.

Sophistication of home demand is more important than its size. Even in small countries the successful industries usually have significant local rivalry.

Resource-based industries

The importance of basic factors such as natural resources is low; competitive advantage based on natural resources is unsustainable.

Resource-based industries can also have substantial, sustainable competitive advantage.

There are firm-specific advantages in resource industries; competitive advantage based on natural resources can sometimes be sustained for a time.

National culture

National culture is one of the local circumstances in the diamond; firms should reinforce their unique national cultures.

National culture is the base on which the national diamond rests; culture is exogenous to firms and cannot be changed.

National culture works through the four determinants of the diamond; culture is not necessarily exogenous to firms and it can be changed.

Macro variables

Studying macroeconomic variables is not enough to explain the competitive advantage; unit labor cost is not a good measure of competitiveness.

Unit labor cost is a better measure in assessing competitiveness than only output per hour emphasized by Porter; also exchange rates affect unit labor cost.

The increasing value of currency and high interest rates may exacerbate competitiveness problems but they are not the cause of them.

Dynamism The points of the diamond are self-enforcing and they create a system.

Porter’s study concentrates on existing clusters and does not explain how to create a new diamond.

Competitive advantage is most easily established in industries with existing strength or entering related fields.

14

The table reveals seven areas where Porter’s diamond model has been criticized, concerning geographic location, FDI, small open countries, resource-based industries, national culture, macroeconomic variables, and dynamism. Porter has also answered to critics, as shown in the last column.

The main conclusion of the discussion around the diamond model and the impact of globalization is that Porter’s framework is slightly old-fashioned. Still, it is an appropriate base for studying national competitiveness even in the 21st century. The critics have presented a wide array of modifications and alternative models, but the core of the framework remains the same.

2.1.4 Critique: Porter ignores entrepreneurship

Another aspect of competitiveness, almost totally ignored by Porter and his critics, is the role of entrepreneurship. Lintunen (2000) pinpoints that Schumpeter’s (1934, 1942) view on entrepreneurship has been undervalued and ignored by many writers in the field of economics, including Porter. At least two of Schumpeter’s arguments, adapted from Lintunen (2000), should be taken into account when trying to explain the sources of national competitiveness: (1) “an entrepreneurial function is a source of evolution in a whole society” and (2) “entrepreneurial leadership is the source of creative energy for innovation and evolution”.

The ignorance of the role of entrepreneurship has been taken into discussion by several writers. Silver (1985) states that “Economic theory that ignores the entrepreneur as a key player is absurd. Yet a search through economic history indicates that no major economist has ever defined the role of entrepreneurship as the creator of the goods and services that make the markets that create economic prosperity and decline.”

According to Lahti (2000), the absence of entrepreneurship from the theories of markets, firms and organizations makes our understanding of the business landscape incomplete. “In the highly dynamic environment of today, any kind of company or region that relied on ‘porterian cluster determinism’ is a potential loser.” Also Dahmen (1986) emphasizes the entrepreneur’s own vision instead of the deterministic assumption that “firms only innovate when they have to”.

Reynolds et al. (2001) have found a linkage between entrepreneurship and economic growth, although the relationship is complex. In the international Global Entrepreneurship Monitor 2001 study, the prevalence of ‘necessity entrepreneurship’ was positively associated with national economic growth, particularly in countries highly dependent on international trade. On the other hand, the prevalence rate of ‘opportunity entrepreneurship’ was not associated with any measure of national economic growth.

To enhance entrepreneurship, Reynolds et al. (2001) propose a list of implications for government. This list includes for instance: (1) enhance general and entrepreneurship-specific education, (2) simplify government regulations, (3) strike a balance between economic security and self-sufficiency, (4) encourage technology commercialization, (5) emphasize economic adaptation as a collective responsibility, (6) encourage toleration of diversity in personal income and wealth, and (7) accept the inevitability of business failures.

As the recent studies show, we must not ignore the impact of entrepreneurship in studying competitiveness on macroeconomic level. A framework that includes the full impact of

15

entrepreneurship is still missing. Porter’s deterministic view, which classifies entrepreneurial actions as chance events in the diamond, is highly questionable.

2.2 Networks and geographical clusters

The role of geographic concentration in competitiveness was first studied by Marshall (1920), who identified three reasons for localization. First, the concentration of several firms in a single location offers a pooled market for workers with industry-specific skills, ensuring lower probability of both unemployment and labor shortage. Second, localized industries can support the production on nontradable specialized inputs. Third, informational spillovers can give clustered firms a better production function than isolated producers.

Later, Porter (1990, p. 154) stated that competitors in many internationally successful industries, and entire clusters of industries, are often located in a single town or region within a nation. Porter (1998, pp. 209–210) argues that location affects competitive advantage mainly through its influence on productivity. The sophistication and productivity with which companies compete in a location is strongly influenced by the quality of business environment. Cluster thinking thus assumes an important role in both company strategy and economic policy.

A cluster-based approach to economic development is sometimes confused with industrial policy (Porter 1998, p. 248). To avoid this confusion, the main differences between cluster thinking and traditional industrial policy are presented in table 2.

Table 2. The main differences between cluster thinking and traditional industrial policy, adapted from Porter (1998, pp. 248–249)

Sectoral approach Cluster approach

Organizations within an industry sector form a value network.

Organizations in different industrial sectors form a cross-industrial value network.

Some industries offer greater wealth-creating prospects and should thus be supported.

All clusters are desirable and have the potential to contribute to prosperity.

”Wasteful” domestic competition and foreign rivals are eliminated until the supported industries reach sufficient economies of scale.

Both domestic and international rivals are welcome to enhance cluster externalities and productivity.

This chapter first presents a broader scope for interactions among organizations, i.e. the general framework of value networks. After that, we proceed into the specific case of value networks that of our interest: industrial clusters. Finally, we present the theory of dynamic clusters called ‘hot spots’.

2.2.1 Value network widens the concept of value chain

Groups of interconnected companies can be called as value networks, value nets, or value webs. According to Timmers (1999), value networks can be defined as “multienterprise networks of relationships focused on integration of information flows to exploit information and knowledge in the network for strategic business objectives”. The common feature of value networks is to

16

realize external economies of scale and of scope by relying on fragmented rather than vertically integrated forms of industry organization (Berger et al. 1999).

The value network attempts to broaden the strategic perspective of Porter’s (1985) value chain and to consider links with both upstream and downstream value chains. Value creation consists of sets of activities that jointly participate in the creation of value by using tangible, intangible, and human resources. These activities are linked to each other by flows of material, information, and financial resources as well as influence relationships. The activities of the value network can be seen in the form of nodes linked together with relationships, as illustrated in figure 7. The nodes represent value creation or consumption activities while the arrows symbolize the significant relationships between the activities. (Parolini 1999)

Consumption

Figure 7. The value network, adapted from Parolini (1999).

Berger at al. (1999) see three types of value networks that play important roles in the world economy today. First, there are ‘captive value networks’ that rely on dominant lead firms coordinating tiers of largely captive suppliers. The advantages of captive value networks include efficiency and close coordination, while the main negative aspect is that strong interdepence makes it difficult to begin and end supplier relationships. Captive value networks are typical in Japan, where the suppliers are usually highly dependent on a few key customer firms (Aoki 1987, Sako 1989).

Second, there are highly fragmented ‘relational value networks’ that are built on social proximity and long-term contracting relationships between firms. These networks can adapt to volatile markets rapidly, while the drawbacks are high barriers to entry and geographic boundedness. (Berger et al. 1999) Examples of relational value networks include the industrial districts of Italy (Brusco & Righi 1989) and even Silicon Valley (Saxenian 1996).

The third network type consists of ‘turn-key value networks’, which are based on highly qualified suppliers with the capability to provide customers with end-to-end solutions (Sturgeon 1997). In these American-centered networks the suppliers are of merchant character, which is achieved through the development of a large and diverse pool of suppliers. To facilitate this, turn-key suppliers often specialize in a cross-cutting base process, base component, or base service. Turn-key value networks are highly flexible systems characterized by fluid relationships, geographic flexibility, low costs, and rapid technological diffusion. In these networks, the brand-name firms are in a risky position: they may lose their expertise after extensive outsourcing and, as a result, the turn-key suppliers might take their business. (Berger et al. 1999)

17

The concept of value network successfully broadens the original view of value chain. With the help of the value network, relationships between companies can be described in a realistic way. This generic concept forms the basis for studying its subsgroups, i.e. clusters and hot spots.

2.2.2 Industrial clusters – groups of interconnected companies

Porter (1998, p. 199) defines a cluster as “a geographically proximate group of interconnected companies and associated institutions in a particular field, linked by commonalities and complementarities”. Clusters often include: (1) end-product and service companies, (2) suppliers of specialized inputs, components, machinery and services, (3) financial institutions, (4) firms in related industries, (5) firms in downstream industries, i.e. channels or customers, (6) producers of complementary products, (7) specialized infrastructure providers, (8) government and other institutions providing specialized training, education, information, research and technical support, and (9) standard-setting agencies.

Identifying a cluster involves starting with a large firm or concentration of similar firms and then looking upstream and downstream in the vertical chain of firms and institutions. The next step is to look horizontally to identify industries passing through common channels or producing complementary products and services. Additional horizontal chains of industries are identified based on the use of similar specific inputs or technologies or with other supply-side linkages. After this, the institutions that provide the cluster with specialized skills, technology, information, capital, or infrastructure and eventual collective bodies covering cluster participants are isolated. The final step is to look for government or other regulatory bodies that considerably influence the participants in the cluster. Drawing cluster boundaries is a creative process that requires understanding the most important linkages and complementarities across industries and institutions. Cluster boundaries should encompass all firms, industries, and institutions with strong linkages – whether vertical, horizontal, or institutional. (Porter 1998, pp. 200–202)

Clusters occur in many types of industries, in both larger and smaller fields. They are present in large and small economies, in rural and urban areas, at different geographic levels, and in both advanced and developing economies. They also vary in size, breadth, and state of development. Cluster boundaries rarely conform to standard industrial classification systems, which usually fail to capture many important actors and linkages. (Porter 1998, pp. 203–204)

In analyzing clusters, Jacobs & de Man (1996) have identified seven different dimensions that can be used as a way to approach: (1) geographical: the spatial clustering of economic activity, ranging from quite localized clusters to really global ones; (2) horizontal: several industries/sectors can be part of a larger cluster; (3) vertical: adjacent phases in the production process, forming a value system, can be present in clusters; (4) lateral: different sectors can share certain capabilities and achieve economies of scope, leading to new combinations; (5) technological: a collection of industries which share a basic technology; (6) focal: a cluster of firms around a central actor that can be a firm, an extended family, a research center or an educational institute; and (7) quality of network: not only the question of whether firms really cooperate is of interest here, but also the way in which they do so.

There are several reasons why Porter (1998, p. 205) prefers talking about clusters rather than industries or sectors. First, clusters align better with the nature of competition and the sources of competitive advantage. Second, clusters capture important linkages, complementarities and

18

spillovers of technology, skills, information, marketing and customer needs that cut across firms and industries. Third, viewing a group of companies and institutions as a cluster highlights opportunities for coordination and mutual improvement in areas of common concern without threatening or distorting competition or limiting the intensity of rivalry.

Clusters represent mainly one facet of the national diamond – related and supporting industries – but are best seen as a sign of well-functioning interaction among all four determinants. Many cluster advantages rest on external economies or spillovers across firms and industries. A cluster thus constitutes a system of organizations whose value as a whole is greater than the sum of its parts. Clusters affect competition in three broad ways: by increasing the productivity of the firms and institutions, by increasing their capacity for innovation, and by stimulating new business formation that supports innovation and expands the cluster. (Porter 1998, p. 213)

Porter (1998, pp. 214–220) has found five ways how productivity is increased in a cluster. First, the firms can get superior or low-cost access to specialized inputs such as component, machinery, business services, and personnel, as compared to vertical integration or formal alliances. Geographically concentrated firms often gain ‘economies of agglomeration’, which has been even mathematically modeled by Krugman (1991). Second, clustered firms get better access to information: extensive information about markets and technology accumulates within a cluster. A good example of how cluster participants share information is Silicon Valley, studied by Saxenian (1996). Third, a cluster facilitates complementarities between the activities of cluster participants. Joint marketing such as trade fairs or mutually dependent services in tourism are some examples of complementarities. Fourth, the firms get access to institutions and public goods, e.g. locally educated employees, specialized infrastructure, or advice from experts in local institutions. Fifth, the competitive pressure in a cluster improves the incentives within companies for achieving high productivity.

Many of these productivity advantages involve location-specific public goods or benefits that depend on physical proximity, face-to-face contact, close and ongoing relationships, and “insider” access to information. The benefits of cluster membership can thus be difficult or impossible to access unless the firms are actively involved, with a significant local presence. (Porter 1998, p. 220)

Also Ciccone and Hall (1996) have studied the impact of geographic concentration, mainly focusing on labor productivity. They found that increasing returns to density play a crucial role for explaining the large differences in average labor productivity across U.S. states – doubling employment density on a county seems to increase average labor productivity by six percent.

Compared to productivity gains, clustering can be even more beneficial in creating innovative atmosphere. There is evidence that firms located in strong clusters are more likely to innovate – knowledge externalities and spillovers, especially those associated with new technological knowledge, tend to be geographically localized (Baptista & Swann 1998). These knowledge externalities are more prevalent in industries where new economic knowledge plays a greater role (Audretsch & Feldmann 1996). Also Jaffe et al. (1993) and Harrison et al. (1996) highlight the geographic dimension of innovation and knowledge spillovers.

Firms within a cluster are often able to more clearly and rapidly perceive new buyer needs and preferences (von Hippel 1998). Cluster participation also offers advantages in perceiving new technological, operating, or delivery possibilities. The potential advantages of clusters in

19

perceiving both the need and the opportunity for innovation are significant, but equally important can be the flexibility and capacity they provide to act rapidly on these insights. Firms within a cluster can also experiment at lower cost and can delay large commitments until they are more assured that a new product will pan out. (Porter 1998, pp. 220–221)

Most new businesses form within existing clusters rather than at isolated locations. Clusters provide inducement to entry through better information about opportunities – barriers to enter are thus lower in a cluster than elsewhere. While local entrepreneurs are likely entrants to a cluster, entrepreneurs based outside a cluster frequently relocate, sooner or later, to a cluster location. Because of the new business formation, clusters often grow in depth and breadth over time, further enhancing cluster advantages. (Porter 1998, pp. 224–225)

The mere presence of firms, suppliers, and institutions in a location creates the potential for economic value, but it does not automatically ensure the realization of this potential. Social glue ties clusters together, contributing to the value creation process. While some cluster advantages are largely independent of social relationships, most of them have at least a relationship component. The social structure of clusters is thus of central importance. (Porter 1998, pp. 225–226)

Specialization characterizes the economic geography of cities, states, and nations – especially of prosperous ones – and appears to increase as an economy becomes more advanced. A relatively small number of clusters usually account for a major share of the economy within a geographic area. Clusters can be divided into three types of business: (1) outward-oriented clusters, which constitute the area’s long-run source of economic growth and prosperity, (2) localized industries and clusters that do not compete with other locations, and (3) local subsidiaries of competitive firms based elsewhere that primarily serve the local market. In identifying clusters, outward-oriented industries must be distinguished from those that primarily serve the local market. (Porter 1998, pp. 227–228)

While international trade and investment are usually recognized as powerful forces for productivity growth, the role of internal trade and investment has been largely ignored. Trading within a nation, however, provides an excellent stepping-stone from which firms can build the skills needed to internationalize. In internal trade – particularly in developing countries, but also in advanced economies – the economic activity may be too concentrated in a few areas, whereas little or no activity takes place in outlying areas. A transition from a concentrated to a dispersed economy, with specialized industries and clusters, represents an essential challenge of economic development. An economic geography characterized by a number of metropolitan areas, each specializing in a group of clusters, appears to be a far more productive industrial organization than one based on one or two huge, diversified cities. (Porter 1998, pp. 234–236)

It has been widely recognized that changes in technology and competition have weakened many of the traditional roles of location. Still, the enduring competitive advantages in a global economy are often heavily local, arising from concentrations of highly specialized skills and knowledge, institutions, rivals, related businesses, and sophisticated customers in a particular region. As Porter (1998, p. 237) states, “location matters, albeit in different ways at the turn of the twenty-first century than in earlier decades”.

Porter’s cluster theory presents an extensive framework that combines economics, geography, and business strategy. It provides an array of valid reasons why clustering is so common in the

20

industrial world. However, the dynamics of clustering, i.e. the development pattern of clusters, is inadequately covered in the initial cluster theory. The next chapter presents a model of ‘hot spots’ that complements Porter’s cluster theory.

2.2.3 Cluster dynamics – the development of ‘hot spots’

Pouder & St. John (1996) refer to fast-growing regional clusters as ‘hot spots’. According to their definition, hot spots are “regional clusters of firms that compete in the same industry, begin as one or several start-up firms that grow more rapidly than other industry participants and have the same or very similar immobile physical resource requirements in the long run”. A group of geographically concentrated firms is not automatically a hot spot – for instance firms that are located near each other in order to capture a local market opportunity, e.g. hotels, retail establishments and restaurants, would not constitute a hot spot (Baum & Mezias 1992).

A clustered subgroup of competitors within an industry will likely move through three evolutionary phases that pattern the model of ‘punctuated equilibrium’ (Gersick 1991). These phases are: (1) origination of the cluster and emergence of hot spot identity, (2) convergence of clustered firms, and (3) firm reorientation, which includes a decline in the performance of the cluster or hot spot (Tushman & Romanelli 1985). As illustrated in figure 8, the hot spot initially grows faster than the overall industry, but then it experiences declines not felt by the competitors outside of the hot spot. (Pouder & St. John 1996)

Clustered firms Non-clustered firms

Gro

wth

Hot spot failureReorientation

ConvergenceOrigination

Jolt

Figure 8. Hot spot versus non-hot spot growth, as presented by Pouder & St. John (1996).

According to Pouder & St. John (1996), the major forces affecting the evolution of hot spots are resource conditions, institutional processes, management’s mental models, competitive behavior, and innovation performance. The relationships between these forces constitute a framework that is illustrated in figure 9 and later used in analyzing the different evolution phases of hot spots.

21

Competitive behavior

1. Origination: increased entry, competitive parity, differentiation

2. Convergence: stabilized entry, myopic competitive practices

3. After jolt: declining number of firms in the former hot spot

Management’s mental models

1. Origination: emerging influence of local competitors

2. Convergence: cognitive bias, homogeneity

3. After jolt: cognitive inertia, entrenchment

Resource conditions

1. Origination: agglomeration economies

2. Convergence: no agglomeration economies

3. After jolt: emerging agglomeration diseconomies

Innovation performance

1. Origination: increasing levels of hot spot innovation

2. Convergence: decreasing level of hot spot innovation

3. After jolt: industry innovations arise outside of the former hot spot

Institutional processes

1. Origination: enhanced legitimacy

2. Convergence: mimetic behavior, isomorphism

3. After jolt: organizational inertia, inflexible structure

Figure 9. Key forces affecting the different phases of hot spot evolution, adapted from Pouder & St. John (1996).

In the origination phase of hot spots, the role of resource conditions remains partly unclear (Pouder & St. John 1996). As Scott (1992) noted, it is difficult to identify the emergence of cluster before it occurs. Extensive studies how cluster creation is affected by, for instance, government efforts or economic fluctuations would be interesting.

According to Porter (1998, pp. 237–238), one prominent reason for the formation of early companies is the availability of factor pools, such as specialized skills, university research expertise, an efficient physical location, or particularly good infrastructure. Clusters may also arise spontaneously from a single, fast-growing and successful start-up firm (Saxenian 1996) or a group of innovative companies. There seems to be an element of chance to the origin and initial location of geographical clusters of firms (Rauch 1993). Still, what looks like chance may well be a result of pre-existing local circumstances (Porter 1998, 238–239). The nature of key forces affecting the development in the origination phase, according to Pouder & St. John (1996), is listed below.

1. Resource conditions in the origination phase. As the first firm becomes successful, qualified suppliers, skilled workers, and informed investors become available, which lowers the cost of entry for subsequent firms, making the area relatively more attractive than other areas. These cost advantages are called ‘agglomeration economies’.

2. Institutional processes in the origination phase. Firms have an incentive to cluster to enhance legitimacy and avoid the liability of newness (Aldrich & Fiol 1994, Singh et al. 1986). An increased number of organizations leads to increased legitimacy (Hannan & Freeman 1989). Thus, once firms begin to amass in one area, they will experience greater cost economies and legitimacy than industry competitors outside the cluster.

3. The mental models in the origination phase. The mental models of managers and employees are likely to be somewhat similar even at the earliest stages of the hot spot. In

22

geographical clusters, proximity makes information about local competitors more available and creates frequent social and professional interactions. As a result, managers of clustered firms will be more attuned to the strategies and capabilities of competitors inside the cluster compared to competitors outside the cluster. Managers of non-clustered firms will not show a similar tendency.

4. Competitive behavior in the origination phase. Competitors within the cluster will experience agglomeration economies and availability of shared resources. This helps to ensure the survival of clustered firms by creating competitive parity (Barney 1991) and increasing the probability of economic survival of the whole cluster (Porter 1990). The rate of growth in numbers of competitors within the cluster will then exceed the rate of growth in numbers of competitors outside the cluster, leading to the hot spot identity.

5. Innovation performance in the origination phase. Conditions are ripe for high levels of innovation, thanks to: (1) the increasing number of competitors within the hot spots, (2) the proximity and shared resources among competing firms within the hot spot, and (3) the mental models that emphasize the resources and capabilities of hot spot firms. The clustered firms will thus be responsible for an increasing proportion of industry innovations, compared to non-clustered firms.

While the birth of clusters has many causes, the development of clusters is more predictable. The development process – that often starts as causal chain reaction and quickly becomes blurred – depends heavily on efficacy of the national diamond’s arrows and feedback loops. Three particular areas deserve special attention: intensity of local competition, the location’s overall environment for business formation, and the efficiency of formal and informal mechanisms for bringing cluster participants together. It appears that clusters often require at least a decade to develop depth and to gain real competitive advantage – one reason why government attempts to create clusters usually fail. (Porter 1998, pp. 240–241)

Cluster development often becomes especially energetic at the intersection of clusters, when insights, skills, and technologies from different fields merge, sparking new businesses. Cluster development can be further accelerated by attracting cluster participants from other areas and nations. Cluster participants often play a role in this process, seeking out people, technologies, and suppliers from elsewhere. As a cluster evolves, cluster participants tend to develop increasingly global strategies. This opens up more growth opportunities but also enriches knowledge and stimulates new ideas. (Porter 1998, pp. 241–243) There is, however, a pattern of convergence in the evolution of clusters or hot spots, which affects the key forces in a way described below by Pouder & St. John (1996).

1. Resource conditions in the convergence phase. The size, congestion, and saturation within the hot spot may begin to “choke off” the agglomeration economies. Diseconomies of agglomeration may occur as the cost of living, real estate prices, and salaries of technical personnel rise (Arthur 1990, Grove 1987). Over time, the hot spot firms will then experience cost economies similar to competitors outside the hot spot.

2. Institutional processes in the convergence phase. The high level of awareness among competitors within the hot spot and tendencies to monitor closely the firms’ direct competitors likely leads to imitation (Haveman 1993, Porac & Thomas 1990). The majority of hot spot firms will be governed by norms of acceptable conduct, which makes firms susceptible to institutional forces that encourage homogeneity.

23

3. The mental models in the convergence phase. The mental models of strategists within hot spot firms will exhibit biased assessments of competitors’ capabilities and place too much emphasis on hot spot competitors and too little emphasis on non-hot spot competitors. Managers outside the hot spot will not exhibit the same bias. Strategists within hot spots will be more homogeneous in their perceptions about competitors and industry opportunities than will managers outside the hot spot.

4. Competitive behavior in the convergence phase. The hot spot industry subpopulation will stabilize compared to the larger industry population, experiencing similar patterns of entry and exit. Firms will be no more likely to enter the cluster than to begin business elsewhere.

5. Innovation performance in the convergence phase. The hot spot firms will exhibit higher levels of organizational inertia and imitative competitive behavior compared to outside competitors. Consequently, the collective level of innovation emanating from the hot spot will decrease over time.

The convergence of clustered firms can continue indefinitely. Once the rates of growth and innovation stabilize, the cluster will no longer fulfill the definition of a hot spot in terms of growth, but it will continue to survive as a tight cluster of competitors (Pouder & St. John 1996). A cluster decline may be caused by either internal or external reasons. The internal sources of decline – such as restrictive union rules, overconsolidation, cartels, or patterns of groupthink – stem from internal rigidities that diminish productivity and innovation. Examples of external threats include technological discontinuities, inappropriate expertise or market information, and shifts in buyer needs. (Porter 1998, pp. 243–244)

The clustered firms will be slower to recognize and respond to industry-wide environmental jolts, or Schumpeterian shocks (Schumpeter 1934, Barney 1991), than will competitors outside the hot spot. These shocks tend to occur in three phases: (1) an anticipatory phase that includes perceptible warning signals, (2) a responsive phase when the primary impacts are absorbed, and (3) a readjustment phase (Meyer 1982). The implications of a jolt, stated by Pouder & St. John (1996), are presented next.

1. Resource conditions after a jolt. The resource base and interrelationships of the geographical area may have little value after a jolt, particularly if new suppliers or technologies ar needed for such a change. At this point, the former hot spot firms will most likely experience emerging agglomeration diseconomies.

2. Institutional processes after a jolt. When organizations perceive that the value of compliance with institutional norms is low and that those norms are not compatible with new organizational goals, the organization will either dismiss or ignore the norms (Oliver 1991). Only those firms that undergo a significant change in their organization’s structure and processes will survive a hot spot failure.

3. The mental models after a jolt. The mental models of managers tend to persist – even when their environment changes (Fiske & Taylor 1991) – exhibiting cognitive inertia and entrenchment that hinder firm-level reorientation following an environmental jolt. Within those former hot spot firms that initiate a radical response to the environmental jolt, the

24

mental models of strategists will be realigned with new assumptions about competitors, markets and industry boundaries.

4. Competitive behavior after a jolt. The local rivalry tends to ebb – there will be declining number of firms in the former hot spot. The subpopulation with former hot spot identity is separated from the total population and will likely face an evolutionary destruction (Hannan & Freeman 1989).

5. Innovation performance after a jolt. As the growth of cluster declines, the former hot spot will experience disproportionate losses also in innovation rates. Instead, industry innovations will arise outside of the hot spot.

As the three-stage-model presented here shows, clusters are not static entities that necessarily succeed indefinitely. Instead, the convergence of clusters results in vulnerability that non-clustered firms can avoid. It still remains unclear how probable the above described environmental jolts are in the real world, i.e. whether there are any real cases showing that clustered firms, in some external conditions, have succeeded poorly compared to firms outside a cluster.

25

3 ANALYZING THE FINNISH MOBILE CLUSTER

After going through the relevant theoretical frameworks, we can proceed in the analysis phase. In this chapter, we will first present the current mobile network technologies so that the reader can more easily understand the mobile environment. After that, we will present traditional models of the Finnish mobile cluster as well as develop a new model. Third, we will go through the main results of the cluster analysis made by Leppävuori & Kiuru (2001), including (1) the attitudes of the Finnish mobile cluster companies, (2) the present and prospected future use of mobile services in five different branches, and (3) the classification of issues that hinder the development of mobile services.

Before analyzing the mobile cluster, we must define the terms ICT cluster, telecom cluster, and mobile cluster. “The ICT (information and communications technology) cluster is an industrial cluster where knowledge capital plays central role, and other production factors are rather insignificant” (Ali-Yrkkö et al. 2000). ICT cluster is then a broad concept that includes everything concerning both information technology and telecommunications. The telecom cluster includes the classic telecommunications industry that gave rise to the mobile communications industry, thus excluding the IT-part of the ICT cluster. Mobile cluster is the fast-growing core of the telecom cluster that focuses on the mobile side of telecommunications. (Steinbock 2000, pp. 13–14)

3.1 Mobile network technologies are developing rapidly

In this chapter, we will briefly go through the relevant mobile network technologies in order to better understand the current status and future potential of mobile services. A brief summary of past, present, and future mobile network technologies is presented in table 3.

Table 3. Summary of past, present, and future mobile network technologies. Source: Forrester (2000)

Technology Usage years Bandwidth Main features

NMT - Nordic Mobile Telephony

1982–2000 9,6 kbits/s - Analog voice service - No data capabilities

GSM - Global System for Mobile Communication

1990– 9,6–14,4 kbits/s - Digital voice service - Advanced messaging - Global roaming - Circuit-switched data

HSCSD - High-Speed Circuit Switched Data

2000– 9,6–57,6 kbits/s - Extension of GSM - Higher data speeds

GPRS - General Radio Packet Service

2001– 9,6–115 kbits/s - Extension of GSM - Always -on connectivity - Packet-switched data

EDGE - Enhanced Data Rates for GSM Evolution

2002– 64–384 kbits/s - Extension of GSM - Always -on connectivity - Faster than GPRS

UMTS - Universal Mobile

2003– 64–2048 kbits/s - Always -on connectivity - Global roaming

26

Telecommunications System - IP-enabled

GSM (Global System for Mobile Communications) is an open, non-proprietary mobile telecommunications system. One of its strengths is the international roaming capability that gives consumers seamless and same standardized number contactability in more than 170 countries. GSM differs from first generation wireless systems (for example NMT) in that it uses digital technology and time division multiple access transmission (TDMA) methods. Voice is digitally encoded via an encoder, which emulates the characteristics of human speech. This method of transmission permits an efficient data rate/information content ratio. Maximum data transmission speed, however, with normal GSM is limited to modest 14,4 kbits/s, which limits the use of mobile services. (GSM World 2002)

HSCSD (High Speed Circuit Switched Data) is an enhanced way of circuit switched data transmission within the GSM environment. HSCSD will enable the transmission of data over a GSM link at speeds of up to 57,6 kbits/s. This is achieved by cocatenating, i.e. adding together, consecutive GSM timeslots, each of which is capable of supporting 14,4 kbits/s. Up to four GSM timeslots are needed for the transmission of HSCSD. In using HSCSD a permanent connection is established between the called and calling parties for the exchange of data. As it is circuit switched, HSCSD is more suited to applications such as videoconferencing and multimedia than “bursty” type applications such as email, which is more suited to packet switched data. (GSM World 2002)

GPRS (General Packet Radio Service) is a new nonvoice value added service that allows information to be sent and received across a mobile telephone network. It supplements today's circuit switched data and SMS (Short Message Service). GPRS will provide an improvement to mobile data usage and usefulness. That much seems assured from its flexible feature set – its latency, efficiency, and speed. The only question is how soon it takes off in earnest and how to ensure that the technical and commercial features do not hinder its widespread use. (GSM World 2002)

EDGE (Enhanced Data rates for GSM Evolution) represents the final evolution of data communications within the GSM standard. EDGE uses a new modulation schema to enable data throughput speeds of up to 384 kbits/s using existing GSM infrastructure. As 384 kbits/s is the data speed being offered in the first phase of third generation deployment, EDGE could offer an alternative route for GSM operators who will not have third generation licences. (GSM World 2002)

UMTS (Universal Mobile Telecommunications System) is the European member of the IMT2000 family of third generation cellular mobile standards. The goal of UMTS is to enable networks that offer true global roaming and can support a wide range of voice, data and multimedia services. The theoretical data rates offered by UMTS are: (1) vehicular 144 kbits/s, (2) pedestrian 384 kbits/s, and (3) in-building 2 Mbits/s. The first stage of service and network evolution is from today’s GSM systems, through the implementation of GPRS, to commercial UMTS networks. Many of the original goals of UMTS are being met by the evolving GSM standard such as global roaming and personalized service features. The major differentiators of UMTS are (1) a new air interface operating at around 2 GHz which will offer superior performance to GSM in terms of higher data rates and capacity, and (2) a packet-based network architecture that supports both voice and data services. (GSM World 2002)

27

WAP (Wireless Application Protocol) is an open, global protocol specification that empowers mobile users with wireless devices to easily access and interact with information and services instantly (WAP Forum 2002). WAP is an important development in the wireless industry because of its attempt to develop an open standard for wireless protocols, independent of vendor and air link. (GSM World 2002)

It is obvious that the technological development in mobile network technologies is rapid and unpredictable. Whereas the success of GSM has been far better than expected, the adaption rate of WAP applications, GPRS, and UMTS has been surprisingly slow. In order to be successful, the development of the Finnish mobile cluster can therefore not solely rely on a single technology. Instead, the success should be built on cumulative, general mobile technology knowledge and agility to adapt new competencies.

3.2 Mobile environment – traditional and new models

This chapter focuses in describing the “big picture” of the Finnish mobile cluster. First, we will use the findings of Rugman & D’Cruz (1993) and Paija (2001) to develop a diamond model of the Finnish national diamond in the European Union. After that, we will develop a new concept for presenting the core of the Finnish mobile cluster. This is done in four steps, including identifying the key actors, developing a value chain and a value network, and using multidimensional scaling (MDS) to develop the new concept, called the ‘distance/magnitude value nework’ (D/MVN).

To give some perspective, it might be good to first review some statistical facts about the Finnish ICT cluster. The share of the Finnish ICT cluster is approximately 6,4 % of the total GDP (FiCom 2002). The Finnish companies in information and communications technology currently employ a total of 115 000 people (Tilastokeskus 2002). In terms of total revenues, the biggest companies in the cluster are Nokia, Sonera, Elisa Communications, Tellabs, L M Ericsson Finland, Soon communications, and Teleste.

3.2.1 The Finnish national diamond in the European Union

The Finnish ICT cluster has been on focus in many recent studies (see for instance Steinbock 2000, Rönkkö 2001). A descriptive study of the competitive advantage is provided by Paija (2001, pp. 28–44). The facets of competitive advantage of the Finnish ICT cluster is briefly presented here; we dare to state that the same conditions apply also when we limit us into the mobile side of the cluster.

Factor conditions have improved substantially during the last decade. Liberalization of capital markets in the 1980s and successful investment cases in the 1990s have made venture capital the most common source of capital for start-ups. The improved access to capital has drawn more professional and growth-oriented entrepreneurs to the field, which has resulted in better potential for international success. Moreover, R&D expenditure as a share of GDP has been rising continuously in Finland since the 1980s and was approximately 3,6 % in year 2001 (Tilastokeskus 2002). Education is a critical factor in the cluster development – currently there is a structural mismatch in available skills within the ICT cluster. It has proven difficult to rapidly increase the amount of well-educated IT experts. (Paija 2001, pp. 31–33)

28

Demand conditions for mobile communications are exceptionally favorable in Finland. During the 1990s, Finland has been one of the leading countries in mobile penetration and, in the end of 2001, 78 % of the Finnish population had a mobile phone (MinTC 2002). The enthusiasm of the Finns adopting the mobile phone has been explained by the technology-oriented nature of the people and the global breakthrough of Nokia, currently the world’s leading mobile phone manufacturer. (Paija 2001, p. 34)

Supporting industries for the Finnish mobile cluster include primarily companies that provide specialized inputs for the original ICT equipment manufacturers (OEMs). The growth of production volume and the increasing amount of outsourcing have generated a growing number of new suppliers. Related industries are the industries producing complementary products for the ICT infrastructure, particularly the so-called ‘content providers’ that are converting their service products into digital form. There are numerous signs of an emerging content provision industry, but innovative enterprises often lack the skills crucial in professional business development and large-scale market penetration. (Paija 2001, pp. 35–38)

Firm strategy, structure, and rivalry in Finland can be described briefly: in terms of business value, nearly everything in the field of mobile communications depends on Nokia. The teleoperator business, dominated by Elisa and Sonera, is going through a major structural change. First, the revenue from basic telephony services is declining, forcing companies to refocus their operations. Second, as network capacity is accessible to any service provider, network services and infrastructure provision are separating as operator business areas. Third, new business opportunities have motivated the largest operators to make investments in international markets. (Paija 2001, pp. 28–31)

The Finnish government policy has changed from an interventionist approach during the 1960s and 1970s to a more liberal one during the 1980s. The cluster approach, introduced in the early 1990s, has been reflected in government actions emphasizing inter-organizational cooperation as well as accumulation and transfer of know-how. In technology policy, the main executor is the National Technology Agency (Tekes) that coordinates and partly finances various technology programs with a yearly budget of 387 million euros (Tekes 2002). The competition policy in telecommunications policy is based on pro-competitive policies, light-handed regulation, and technology-neutral competition. In educational policy, the government reacted in the rapid growth of electronic industry by increasing openings in higher education institutions. (Paija 2001, pp. 39–42)

Chance events have also played a role in the Finnish national diamond. The traditionally monopolistic telecommunications markets have been globally liberalized as a result of agreements within the EU and the WTO. The opening of East European market has further boosted the demand for mobile equipment. In contrast, the collapse of the Soviet Union severely hit ICT cluster demand in early 1990s. (Paija 2001, pp. 43–44)

The Finnish national diamond is not, however, solely dependent on the domestic circumstances. As a member in the European Union, Finland is part of the EU market. The situation is, as illustrated in figure 10, almost analogous to the North American ‘double diamond’ presented by Rugman & D’Cruz (1993).

29

Finnish-basedresources

WesternEuropeanbusiness

Supportinginfrastructure

Finnish customers

Finnishgovernment

EU-basedresources

Supportingindustries and

institutions

European customers

Europeangovernments

Exports outside European Union

Exports outside European Union

The EUgovernment

Figure 10. The Finnish national diamond in the European Union.

The Finnish mobile cluster companies can benefit from the EU-based resources, institutions, and supporting industries. Moreover, customers within the EU are potential customers also for the Finnish companies. Compared to the North American double diamond, the Finnish situation is fundamentally different in at least two ways. First, Finland is one of the fifteen countries involved in the EU, whereas Canada and USA form together the North American diamond. Second, the EU has its own government in addition to the national governments.

3.2.2 Step 1: identifying the players in the mobile cluster

The first step in developing a value network or cluster map is to identify the relevant players in the mobile industry. Saurio (2001a, 2001b) presents complex value networks with more than 20 types of players. These kinds of ‘industry space’ descriptions do not provide any information about structural boundaries between the companies (Hamel & Prahalad 1994, p. 45) but form an appropriate basis for player identification. The following list of definitions includes all the relevant actors that are involved in the Finnish mobile cluster. In many cases, we follow the definitions provided by Durlacher (2001).

• Application developers – companies that develop mobile applications to be used by content owners and applying industries. Examples of Finnish application developers include Springtoys, LPG Innovations, and Ionific.

• Applying industries – companies that use mobile applications in their business processes. Metso and ABB are some examples of the numerous companies using mobile applications.

• Certification authorities (CA) – trusted companies that produce, distribute, and administer electronic certifications needed for secure data transmission. Novotrust, Certall Finland, and Väestörekisterikeskus are some examples of certification authorities in Finland.

30

• Component manufacturers – suppliers for terminal manufacturers. Elcoteq Network, Aspocomp, and Perlos are some of the biggest Finnish component manufacturers.

• Consultancies – companies that help operators, manufacturers, and content providers with business development issues. EPStar and Omnitele are examples of Finnish consultancies specialized in mobile communications.

• Content owners – companies that own the content distributed via mobile network, for example Ilmatieteenlaitos, Yleisradio, and Alma Media.

• Content providers – companies that aggregate the mobile content and distribute it to end-users. Even though this group is emphasized by Durlacher (2001), we did not find any such companies in Finland.

• Educational institutions – universities and other schools that provide competent labor for the mobile cluster companies. Helsinki University of Technology and Tampere University of Technology are some examples of important sources of educated people for the whole ICT cluster in Finland.

• End users – employees, business customers, or consumers that use and pay for the mobile services.

• Financial services providers – banks and other institutions that provide the backbone system for mobile payments. Nordea, Sampo, and Luottokunta are some examples of Finnish financial institutions involved in mobile payment architecture.

• Network equipment manufacturers – companies that produce the equipment needed for mobile networks. Nokia is the dominant Finnish network equipment manufacturer.

• Network operators – teleoperators that operate physical mobile communication networks. Radiolinja Origo and Suomen 2G are some examples of pure network operators in Finland.

• Platform developers – companies that develop software to be used in various network or application platforms. Some examples of platform developers are Comptel and F-Secure.

• Portals – mobile web sites that aggregate content from various sources into a single portal, for instance Sonera Zed and 2ndHead.

• Regulatory authorities – institutions that regulate the mobile communications market, i.e. Ministry of Transport and Communications, as well as Finnish Communications Regulatory Authority (Ficora).

• Service operators – teleoperators that provide mobile access to users and lease the needed network capacity from a network operator. Radiolinja, Sonera, and DNA Finland are the largest service operators in Finland.

• Standardization organizations – cooperation organizations that define standards at national level, for instance FiCom (Finnish Federation for Communications and Teleinformatics).

• Terminal manufacturers – companies that produce mobile phones. The dominant player in this field is Nokia; Benefon is the other Finnish mobile phone manufacturer.

• Terminal retailers – retail companies that distribute and sell mobile phones to end customers. The largest Finnish terminal retailers are Mäkitorppa and Päämies.

31

• Venture capitalists – companies that provice venture capital for small, growing firms. Eqvitec Partners and CapMan Capital Management are some examples of private Finnish venture capital companies.

As the list above shows, there is a huge number of players that contribute to the success of the Finnish mobile cluster. In the next step, we try to classify these actors in some relevant ways.

3.2.3 Step 2: presenting the traditional cluster map

After identifying the relevant cluster players, we can construct a traditional cluster map of the Finnish mobile cluster. This stage includes classifying the above-mentioned players into different core industries and supporting activities. Our view of the Finnish mobile cluster is illustrated in figure 11, other versions of cluster maps can be found in Paija (2001), Rönkkö (2001), Saurio (2001a), and Steinbock (2001).

Core industries

Supporting industries

- component manufacturers

Commercial supporting services

- consultancies- financial institutions- retailers- certification authorities- venture capitalists

Applying industries

- content owners- content providers

Public supporting services

- regulatory authorities- standardization - educational institutions

Software houses

- application developers- platform developers- portals

Operators

- network operators- service operators

Mobile services

End users

Manufacturers

- terminal manufacturers- network manufacturers

Figure 11. Cluster map of the Finnish mobile cluster.

In our view, there are three core industries in the mobile cluster: (1) terminal and network manufacturers, (2) mobile software houses, and (3) network and service operators. Around the core industries of the cluster, there are groups of supporting activities. These are: (1) supporting industries, including e.g. component manufacturers, (2) commercial supporting services, containing consultancies, financial institutions, terminal retailers, certification authorities, and venture capitalists (3) public supporting services, consisting of regulatory authorities, standardizing organizations, and educational institutions, and (4) applying industries, including the whole array of industries that use mobile applications and possibly own the content used in the applications.

3.2.4 Step 3: constructing the value chain of mobile services

Constructing a value chain model of the telecommunications industry has been very popular among researchers. Kajanto (1997), Durlacher (1999, p. 15), and Saurio (2001a, pp. 33–36)

32

provide some examples. Common to most of these value chain models is that they are one-dimensional, and therefore, not only simplify but also strongly mispresent the reality.

We share the view with Davine & Holmqvist (2001, p. 21) that the customer of mobile services gets three different services: the mobile terminal, the mobile access, and, in some cases, the mobile content. The three services combine into a single package experienced by the customer, but are produced separately. As a result, we construct a mobile services value chain model that consists of three layers: content services, access services, and the mobile terminal. This three-layer value chain model is presented in figure 12.

Focus of this study

Platform developer

Customer

Terminalretailer

Distributionchannel

Terminalvendor

Contentservices

Terminal

Access services

Networkvendor

Networkoperator

Serviceoperator

Content providerContent owner

Figure 12. A simplified value chain of the Finnish mobile services production.

The three-layer value chain gives a better picture of the reality than the traditional, simple value chain models. Still, it provides only a little information about the linkages between the actors. This problem is tackled next in the final step of the value network construction.

3.2.5 Step 4: developing the value network of mobile services

The value network concept is modern way to present various actors in a combination of several value chains. A value chain can be constructed in a way that provides us with information about linkages between the actors. An excellent example of a value network is the ‘mobile data value web’ presented by Durlacher (2001). This value network model is presented in figure 13.

33

NetworkEquipment

NetworkOperator

Device

EnablingTechnology

VirtualOperator

Portal

ApplicationDeveloper

ContentProvider

ApplicationProvider

End-User•Consumer•Business

Service area Application area Technology area

Figure 13. The mobile data value web, presented by Durlacher 2001.

Even this model can, however, be improved to include more information about a cluster of companies. The mobile data value web shows the actors and the linkages between these actors. But it does not show the strength of the actors and the linkages between them. In other words, (1) all the actors are shown as equally large, (2) the positions of the actors seem to be random, and (3) the distances from end-users to companies and between the companies seem to be arbitrary.

To improve the informational value of these kinds of models, we have developed the ‘Distance/magnitude value network’ (D/MVN) concept. It is based on the models presented in the previous steps, but goes further in describing the actors and the linkages between them.

After identifying the core actors of the mobile cluster, we have defined the size of the value network nodes by gathering data from the largest companies. For instance, the total revenues in 2001 of the Finnish mobile phone manufacturers, i.e. Nokia Mobile Phones and Benefon, determine the size of the ‘terminal manufacturers’ node. In the same way, the revenues of the largest teleoperators define the size of ‘network operators’ and ‘service operators’. In the case of teleoperators, when only aggregate financial numbers are available, we have estimated that 50 % of the teleoperator revenues come from service operator business and the other 50 % from network operator business.

The linkages between the actors are defined by multidimensional scaling (MDS) A detailed description of this method can be found in Green et al. (1988, pp. 599–631). First, we made an approximation of the distances between all the core actors. As we found nine core actors in the cluster, there were altogether 1 + 2 + 3 + 4 + 5 + 6 + 7 + 8 = 36 linkages to be assessed. Each of these linkages were given a grade from 1 to 9, where 1 indicated that the actors in question are very close each other. Correspondingly, grade 9 indicated that the actors do not have any cooperation. It is important to note that the value network presented here is based on the subjective evaluations of the author. A test with other experts in this field showed, however, that the differences in the perceptions of different persons were only minor.

34

After defining the sizes of the nodes and the distances between them, the linkages were classified into two categories: (1) value-adding linkages and (2) organizational linkages. Also the importances of the linkages were assessed. The outcome of the construction and analysis process – the distance/magnitude value network – is presented in figure 14.

Terminal manufacturers

Terminalretailers

Domesticend users

Network manufacturers

Networkoperators

Serviceoperators

Platformdevelopers

Portals

Applicationdevelopers

Export

Major value-adding linkage

Minor value -adding linkage

Organizational linkage

Figure 14. The distance/magnitude value network of the core actors in the Finnish mobile cluster.

Constructing this value network leads to three major conclusions. First, the size of the nodes in the cluster is far from balance. Nokia dominates the Finnish mobile cluster while the other actors are left in the shadow. A dominant part of the manufacturing goes export, not to domestic end users. The major operators, supported by platform developers, form another group of relatively large actors. But the rest of the cluster, the mobile application and mobile portal developers, do not really exist.

Second, the value is created by network and terminal manufacturers, operators, platform developers, and terminal retailers. The money flow starts from end users and goes through service operators and terminal retailers. Thus, the tiny group of application and portal developers are left aside: mobile service production has not yet provided any value for the Finnish mobile cluster.

Third, there are strong organizational connections in the value network. Terminal manufacturing and network equipment manufacturing are strongly linked together in many of the dominant actors, especially Nokia. Also operators build a strong organizational network that reaches nearly the whole value network. Operator organizations usually include service operators, network operators, platform developers, terminal retailers, and other smaller actors. A good example of this is Elisa Communications, in including the service operator Radiolinja, the network operator Radiolinja Origo, the platform developer Comptel, and the retailer chain Mäkitorppa.

35

3.3 The attitudes of mobile cluster companies

To find out the attitudes of Finnish mobile cluster companies towards the current conditions, we conducted an enquiry in the opening seminar of Mona program, 20.9.2001. The companies were given a questionnaire (appendix 1) with the following nine questions concerning the general conditions of producing mobile services in Finland.

1. The presence of Nokia in Finland.

2. The ability of the Finnish software houses to turn ideas into complete products.

3. The current pricing policy of the Finnish teleoperators.

4. The ability of the Finnish software houses to understand various applying industries.

5. The willingness of Finnish applying industries to use mobile applications.

6. The ease of getting venture capital as a software house in Finland.

7. The availability of educated and competent labor in Finland.

8. The functionality and compatibility of common technology standards.

9. The current communications policy of the Finnish government.

The respondents were given five different options for their answers. Option 1 stood for the opinion that “the current situation in this issue strongly delays the development of mobile services”. Option 2 indicated that, according to the respondent, “the current situation in this issue slightly delays the development of mobile services”. Option 3 was for those who did not have an opinion on the issue. Respondents choosing option 4 felt that “the current situation in this issue slightly promotes the development of mobile services”. Finally, option 5 indicated the opinion that “the current situation in this issue strongly promotes the development of mobile services”.

Totally 172 enquiry sheets were delivered in the seminar, of which 102 were returned. The answering percentage was then 59 %. The results are merely suggestive, i.e. they are not statistically significant. The correlations between the answers indicated that questions 1, 3, and 9 were most successful, as their correlations with all other questions were below 0,2. Questions 4, 6, and 7 were the most unsuccessful ones in terms of providing information, as their correlations with some other questions were above 0,3.

The respondents presented organizations with very differing backgrounds: teleoperators, software houses, applying industries, consultancies, telecommunications manufacturers, and public sector organizations. The total revenues of the companies ranged from 1 to 30 000 million euros. Figure 15 illustrates the shares of the different organizational backgrounds of the respondents.

36

27 %

24 %19 %

13 %

11 %6 %

consultancies

software developers

teleoperators

public sector

applying industriesmanufacturers

Figure 15. The shares of different organizational backgrounds of the respondents.

The presence of Nokia in Finland was considered the most positive thing among the respondents. 82 % of the respondents answered that Nokia’s presence promoted the development of mobile services in Finland. In this question, there were no remarkable differences between the groups of respondents, i.e. respondents with different organizational backgrounds had almost similar answers. The distribution of the answers is shown in figure 16.

0

9 9

45

39

0

10

20

30

40

50

1 2 3 4 5

Figure 16. The distribution of answers: The presence of Nokia in Finland. 1 = strongly delays, 5 = strongly promotes the development.

The ability of the Finnish software houses to turn ideas into complete products was also classified as strength of the cluster: 62 % of the respondents rated it as a promoting factor in the development of mobile services. The differences between different organizational backgrounds were even smaller here than in the previous question. The view of software developers on their own ability was then in line with other respondent groups, as illustrated in figure 17.

37

13

2

25

36

26

0

10

20

30

40

1 2 3 4 5

otherssoftware developers

Figure 17. The distribution of answers: the ability of the Finnish software houses to turn ideas into complete products. 1 = strongly delays, 5 = strongly promotes the deve lopment.

The current pricing policy of Finnish mobile operators was judged negatively: 65 % of the respondents regarded the current the pricing policy as a delaying factor for the development of mobile services. The differences between the respondent groups were considerable in this question. Operators, manufacturers, and applying industries looked quite neutrally at the pricing policy. Instead, 77 % of the others, i.e. consultancies, software developers, and public sector organizations, regarded the pricing policy as a remarkable weakness in the Finnish mobile cluster. The answers in this question are shown in figure 18.

38

2824

9

3

0

10

20

30

40

1 2 3 4 5

software developers,consultancies, public sector

operators, applying industries,manufacturers

Figure 18. The distribution of answers: the current pricing policy of the Finnish teleoperators. 1 = strongly delays, 5 = strongly promotes the development.

In the fourth question, 48 % of the Finnish software houses rated their ability to understand various applying industries as a delaying factor for the development. Other respondent groups had a more positive view on the software houses’ ability to understand applying industries. The answers are shown in figure 19.

38

3

30

37

22

9

0

10

20

30

40

1 2 3 4 5

others

softwaredevelopers

Figure 19. The distribution of answers: the ability of the Finnish software houses to understand various applying industries. 1 = strongly delays, 5 = strongly promotes the development.

The willingness of Finnish applying industries to use mobile applications was deemed as a positive thing: 54 % of the respondents classified it as a promoting factor for the development of mobile services. In this question, there were only minor differences between the respondent groups. The answers are demonstrated in figure 20.

1

17

29

40

15

0

10

20

30

40

50

1 2 3 4 5

Figure 20. The distribution of answers: the willingness of Finnish applying industries to use mobile applications. 1 = strongly delays, 5 = strongly promotes the development.

The ease of getting venture capital for software houses in Finland shared the attitudes of respondents. Software developers and applying industries had the most negative view on this issue: 53 % of them found it hard for software houses to get venture capital. In contrast, 61 % of respondents working for teleoperators thought that getting venture capital for software development is relatively easy in Finland. The scattering of answers in question 6 is illustrated in figure 21.

39

10

2925 25

12

0

10

20

30

40

1 2 3 4 5

others

operators

software developers,applying industries

Figure 21. The distribution of answers: the ease of getting venture capital as a software house in Finland. 1 = strongly delays, 5 = strongly promotes the development.

Different respondent groups had different opinions also in the availability of educated and competent labor in Finland. For instance, 54 % of respondents in public sector organizations considered access to competent labor as a problem, whereas 67 % of respondents in consulting firms had no problems in attracting competent employees. As the answers in figure 22 illustrate, the structural mismatch in available skills within the ICT cluster seems not to be as critical as Paija (2001) claims.

4

22 21

2628

0

10

20

30

1 2 3 4 5

others

public sector

consultancies

Figure 22. The distribution of answers: the availability of educated and competent labor in Finland. 1 = strongly delays, 5 = strongly promotes the development.

A majority (58 %) of the respondents considered the common technology standards both functional and compatible enough. In this question, the respondent groups were quite unanimous. The dispersion of answers is shown in figure 23.

40

11 11

20

41

17

0

10

20

30

40

50

1 2 3 4 5

Figure 23. The distribution of answers: the functionality and compatibility of common technology standards. 1 = strongly delays, 5 = strongly promotes the development.

The general opinion on the current communications policy in Finland is positive: 65 % of the respondents regarded it as a promoting factor the development of mobile services. There were no remarkable differences between different respondent groups in this question. The answers are shown in figure 24.

03

34

46

19

0

10

20

30

40

50

1 2 3 4 5

Figure 24. The distribution of answers: the current communications policy of the Finnish government. 1 = strongly delays, 5 = strongly promotes the development.

Figure 25 provides a summary of answers in all questions. The issues perceived as most positive factors for the development of mobile services in Finland are colored light yellow, neutral issues are colored light brown, and the things considered as negative are colored dark green.

41

3,8

3,4

3,5

3,0

3,5

3,0

2,1

3,7

4,1

1 2 3 4 5

9. Communications policy of government

8. Compatibility of technology standards

7. Availability of competent labor

6. Ease of getting venture capital

5. Willingness to use mobile apps

4. Understanding about applying industries

3. Operators’ current pricing policy

2. Ability to turn ideas into products

1. Nokia’s presence in Finland

Figure 25. The summary of average answers in all questions concerning the development of mobile services in Finland. 1 = strongly delays, 5 = strongly promotes the deve lopment.

In summary, the factors perceived most positive in the development of Finnish mobile services were (1) Nokia’s presence in Finland, (2) the current communications policy of the Finnish government, and (3) software houses’ ability to turn ideas into products. The problematic issues in the development of mobile services in Finland were (1) the current pricing policy of Finnish mobile operators, (2) the difficulties of software houses in getting venture capital, and (3) the software houses’ poor understanding about applying industries.

3.4 Several problematic issues and open questions

In this chapter, we clarify the current situation in mobile service production in terms of regulation, standardization, and business cooperation. The aim is to identify the most remarkable problems that delay the success of mobile services in Finland. The framework for analyzing the subject is presented in figure 26.

42

Business cooperation

Customer/user– willing to use it or even pay for it?

Supporting services– successful cooperation?

Application developer– successful cooperation?

The mobile application– profitable for the provider?

Standardization– non-standardized interfaces between devices, protocols, and companies– standardized but closed interfaces between devices, protocols, and companies– standardization of content

Regulatory issues– privacy and data security in mobile applications– the rights of different actors in electronic commerce– user authentication and data integrity with electronic signature

Content owner– successful cooperation?

Figure 26. The framework for analyzing regulatory, business cooperation, and standardization issues affecting the development of mobile services.

Our analysis is made from the mobile application’s point of view. As the figure shows, it is in the center of the whole process. There are strong linkages between the success of the mobile application and the level of surrounding factors.

3.4.1 Regulatory issues in privacy, e-commerce, and e-signature

Privacy is the first area of regulatory issues that should be taken into account in developing mobile services. The EU directive concerning the processing of personal data and the protection of privacy in the telecommunications sector (Directive 1997/66/EC) gives the general guidelines in this area. It is implemented in Finland by the law concerning personal data (L 523/1999) and the law concerning data security and privcy (L 565/1999). A new EU directive is also expected to be approved during the year 2002. The main points of these laws and directives are presented in the following list.

• Teleoperators must ensure data security in their networks and confidentiality of subscriber data.

• Teleoperators are allowed to use subscriber data only for billing purposes or, if the subscriber has given permission, in marketing the operator’s own services.

• Avertising and direct marketing via telecommunications network are only allowed if the subscriber has given permission for it. In the new EU directive proposal, the parties have not yet agreed whether the implementing mechanism should be (1) ‘opt-in’, where the subscriber has to subscribe advertisements, or (2) ‘opt-out’, where the subscriber has to prohibit the sending of advertisements to him/her. Finland is already using the ‘opt-in’ alternative.

Electronic commerce is the second regulatory issue in the field of mobile services. The EU directive concerning electronic commerce (Directive 2000/31/EC) seeks to ensure the free

43

movement of information society services between the Member States. This directive is to be implemented in Finland by the law concerning electronic commerce (HE 194/2001). The main points of the directive and the draft of proposed law are presented here briefly.

• A service provider is controlled by the government of the country where the company is active, regardless where the servers or web pages of the company are located.

• Service providers have to make available to customers and authorities basic information concerning their activities (e.g. name, address, e-mail address, trade register number, and professional authorization) in an easily accessible and permanent form. In Finland, this is controlled by Finnish Communications Regulatory Authority.

• Intermediaries that play a passive role as a “mere conduit” of information or information storage provider are not responsible for possible illegal content distributed by content providers. Intermediaries that find illegal content in their servers are, however, responsible for prohibiting the distribution of such content.

• Content that infringes copyrights must be removed if the owner of copyrights in a specified form informs the service provider about the infringement.

Organizations sending commercial communication, for instance e-mail, must be identifiable.

Electronic signature is the third and final issue discussed in the area of mobile communications regulation. The EU directive concerning electronic signature (Directive 1999/93/EC) establishes a legal framework for electronic signatures and certain certification-services. This directive is to be implemented in Finland by the law on electronic signatures (HE 197/2001). The following list includes the main points in the directive and in the draft of proposed law.

• Electronic signature is legally as valid as manual signature. Electronic signature provides a way to authenticate the sender of a document and to ensure integrity in data transmission.

• Qualified signature provides a way to ascertain the personality of the sender of a document. Organizations providing qualified certificates are responsible for the validity of the certificates.

• Electronic signature can be implemented with several technological alternatives: the signature can, for instance, be stored in smart card.

The above-mentioned laws, directives, and drafts provide a solid legal framework for the development of mobile services. Still, there are problems with the current laws. According to Rainio (2000 pp. 99–105), there are several unsolved issues that delay the implementation of mobile services, especially location-based ones. First, it is unclear what kind of location data is considered as subscriber data. Second, the owner of location data has to be defined: is it the operator or the subscriber who owns the location data? Third, the market of location-based mobile services would benefit if content providers were allowed to buy location data for commercial purposes from operators. Fourth, the liability of service providers to provide customers with information about the company and the purchased service is difficult in practice: in WAP technology, the customer is usually charged before he/she can read the terms of contract.

Some regulatory issues have arisen also in the projects of Mona program (Mona 2002), coordinated by EPStar Ltd and financed by the Ministry of Transport and Communications Finland. In Taksi project (Leppänen & Riihimäki 2002), the ordering procedure for taxis could

44

be improved by allowing the use of location-based services. Currently, teleoperators are not allowed to provide taxi companies with the customer’s location without first asking the customer’s permission, even though it is technically possible.

There are several regulatory issues to be solved also in mobile payment. For instance, how is the government going to handle micro payments made by company-owned mobile phones used by employees? The current level of expenditure with mobile phones is going to rise in future when people can buy movie tickets, car washes or other products for private use with their company-owned mobile phones. This should be taken into consideration also in the taxation practices of company-owned mobile phones. Another consideration in mobile payment is the general principle that money, even electronic money, should be anonymous. When purchases are done with a mobile phone, the private consumption of people can be tracked and possibly misused. (Leppävuori & Kiuru 2001)

3.4.2 Standardization problems concerning interfaces and architectures

In standardization, there are two distinctive issues that can be influenced on national level. The first issue is the standardization of non-standardized interfaces between devices, protocols, and organizations. The second one is the openness of those interfaces that are already standardized. We are thus exluding issues handled in international level, such as protocol standardization done by IETF and markup language standardization handled by W3C.

Standardized interfaces are needed particularly in the implementation of mobile services that are integrated into other information systems. Most of the mobile service architectures developed today enter new application area and therefore include mainly non-standardized interfaces. Some examples of problems with non-standardized interfaces are listed below. Both national and international cooperation in these kinds of standardization issues are critical to the success of mobile services. The standardization processes have to be supported by appropriate testing and piloting projects.

• A standardized interface between a mobile phone and a computer is needed in many applications. Web-based applications can be transformed into mobile applications only if there are specific standards for bringing data, for instance pictures and databases, into a mobile phone. Today, this transformation is possible with only the most advanced mobile phones and basic applications.

• Electronic ticket is a tempting application that is already piloted in several projects in Finland (Lippupiste 2002, Lippupalvelu 2002). In the current situation, there is a major risk for a fragmented set of non-standardized interfaces, if no cooperation between different actors occurs. A general standard for an electronic ticket could, in best case, be used e.g. in traveling with a bus or a train as well as in sports and entertainment events.

• In the telematics of physical transportation, the general European framework KAREN and the national TelemArk framework form a good basis for standardization. Still, these frameworks are not sufficient; they have to be standardized in detail and implemented. (FITS 2001)

Open interfaces enable competition in different levels of mobile application architectures, and are thus critical to the development and success of mobile services. Today, many operators hold a set of closed standards in the service, terminal, and platform level. Nokia’s ‘Open Mobile

45

Architecture initiative’ (OMA 2002) is a global initiative to solve this problem, which is illustrated in figure 27.

Uniform telecom standards

Operator 1

Operator 2

Operator 3

Vendor 1

Vendor 2 Vendor 2 Vendor 2

Vendor 1 Vendor 1

Operator 1

Operator 2

Operator 3

Uniform telecom standards

Uniform service platform(numerous suppliers)

Interoperable terminal offering(numerous suppliers)

Operator 1

Operator 2

Operator 3

Service offering

Terminaloffering

Service platform

Telecom layer

Current situation Target situation

Figure 27. The main idea of Nokia’s Open Mobile Architecture initiative. Source: Häyrynen 2002.

In Finland, the current situation with the openness of interfaces is better than internationally. A good example of Finnish cooperation is the FiCom Location API agreement (FiCom 2002), which is compatible with the international LIF API standard (LIF 2001). This standard enables the open interchange of location information between operators, which is critical to the success of location based mobile services.

A practical example of fragmented standards in mobile services is the current situation of mobile payment architectures developed and piloted in Finland. There are currently two competing architectures that can be used in mobile payment (Mobey Forum 2001).

• The dual-chip architecture, presented by Mobey Forum. In this architecture, two chips are installed in a mobile phone. The first chip is the normal SIM card, proved by mobile operator, whereas the other chip includes the WIM module to be used in mobile payment. This WIM module is owned by a bank, a credit card company or other insitution acting as CA.

• The SIM/WIM architecture, presented by the Finnish mobile operator Radiolinja. This alternative mobile payment architecture is based on one chip in a mobile phone. This chip includes both SIM and WIM module and is owned by the mobile operator. In this architecture, the mobile operator acts also as CA.

Both of these solutions have been piloted in Finland. The dual-chip architecture was piloted with 50 special-made mobile phones for a short time, but the piloting phase has now ended. The SIM/WIM architecture is currently available for normal use, provided by Radiolinja.

The problems in standardization indicate the newness of mobile architectures. As long as the market is in the emerging stage, the common pattern of competing technologies (Arthur 1989) occurs: competing organizations are trying to capture the whole market with their own standard. As the market becomes mature, a single standard in each architecture is likely to arise.

This beneficial pattern of evolution should be boosted by sophisticated cooperation between organizations instead of creating a fragmented set of incompatible standards. A concrete action

46

would be to widen the Finnish cooperation in following various international standardizing processes. It it difficult for small companies to continuously follow the standardizing procedures of international organizations. A common way to share this information in Finland, for example via FiCom, would help the situation. (Kujala 2001)

3.4.3 Biggest problems in business cooperation

The third issue in analyzing the conditions for mobile services production is business cooperation. There are usually three types of organizations linked in the development of a mobile application: (1) the organizations enabling the mobile application, i.e. teleoperators, certification authorities, and financial service providers, (2) the application developer, and (3) the owner of the content.

Enabling organizations of a mobile application inevitably include both network operator and service operator. Finnish teleoperators are clearly interested in application development: the presence of various development forums, testing environments, and new ventures organizations is an indication if the positive attitude towards mobile application development. Also the general level of quality and reliability is considered good enough by the application developers.

The main problem is the current pricing policy of mobile network services. The current pricing policy has resulted in a system where (1) prices of the services are higher than the consumers are willing to pay and (2) the application developers and content owners obtain only a minimum share of the revenues (Leppänen & Saikanmäki 2002). However, the emerging shift from GSM data to GPRS transmission lowers the consumer price into an attractive level, when using WAP services (Leppävuori & Kiuru 2001). This change in pricing policy is illustrated in figure 28.

0

40

80

120

0 1 2 3 4 5

Average, GSM data callsAverage, low-end GPRSAverage, hi-end GPRS

Downloaded data per month, Mbytes

Cos

t per

mon

th, e

uros

Figure 28. The average consumer prices of Finnish GSM data and GPRS services.

The figure is based on calculations made by Leppävuori & Kiuru (2001). The basic assumptions in the calculations are that mobile services are used for reading email or browsing web/wap pages, either with a laptop computer connected to a mobile phone or solely with a mobile phone. The user is expected to download data with an approximate speed of 40 kbits/s, which is near the upper limit of HSCSD enabled GSM data services. As the figure shows, the new GPRS services are likely to boost the use of mobile services, since the price level with both high-end and low-end GPRS services are remarkably lower than the price level of GSM data services. The major delaying factor at the moment is the low penetration of GPRS phones.

47

The cooperation with other enabling institutions, i.e. financial institutions and certification authorities is working at a satisfactory level. Still, there are some issues to be solved in the cooperation between financial institutions. In mobile payment, for instance, the distinction between micro and macro payments and the procedures handling these payments are unclear. The same confusion applies also to local payments (with bluetooth or infrared) versus remote payments (via mobile network).

Moreover, the small size of certification service provision market may restrict the development of secured mobile services. Puusola et al. (2001) have found several reasons for the slow development of the certification service provision market. First, the penetration of equipment that enables the use of certificates is too small to support widespread use of certification services. Second, the market is experienced unfair by the commercial certification service providers as the national Population Register Center, supported by government funding, can provide the same services with a remarkably lower price level. Third, the cooperation between public institutions has not been wide enough to support large pilot projects.

Application developers are in the heart of the mobile service development. A conclusion of the opinions of some Finnish experts (Kaasalainen 2001, Kujala 2001, Ottila 2002, Saurio 2001a,) is that there are three distinctive business cooperation problems in the field of application development.

First, the application developers have problems with partnering. Large companies are not willing to become partners with them and, being afraid of information leakages, the small companies do not have the courage to cooperate with each other. Second, the Finnsih venture capital market is too biased towards traditional venture capital provision. Instead of just money, the small companies need more expertise and other support. Third, the immaterial rights have caused problems in the cooperation between small application developers and large companies. However, the successful application developers pinpoint that, instead of selling an idea too early, the companies should develop complete solutions that are difficult to copy.

The owners of the content also have an important role in some mobile applications. To ensure a smooth cooperation between the content owners and the content users, there are some issues to be solved. A common set of Digital Rights Management (DRM) procedures is necessary to ensure that the digital content owners get a proper compensation for the content delivered. A particular problem with pricing and DRM occurs when the content provided by public sector organizations, for instance maps, timetables or news, is turned into commercial mobile service content.

3.5 Mobile services – a business customer viewpoint

In a recent study (Leppävuori & Kiuru 2001), we examined the current and future use of mobile services in Finland from business users’ point of view. The objectives of the study were to (1) map the current mobile applications used by the interviewed companies, (2) map the planned future applications of the interviewed companies, and (3) find the main obstacles that delay the use of mobile applications.

48

3.5.1 Total of 50 companies in five industries were interviewed

In total, 50 companies – ten companies per industry – were interviewed. The questionnaire used in the interviews is shown in appendix 2. The represented industries were health care, trade, tourism, facilities management, and process industry. The interviewed persons were usully those responsible for IT-development of the companies. To provide some background information, the average revenues and the amount of employees of the interviewed companies are shown in table 4.

Table 4. Background of the interviewed companies: average number of employees and average revenues.

Industry Number of companies

Average number of employees

Average revenues (M€)

Health care 10 6 300 380

Trade 10 4 200 1 000

Tourism 10 1 000 190

Facilities management 10 2 100 130

Process industry 10 6 100 1 430

Average 3 900 630

In the first part of the interview, the companies were asked about the fixed network applications they are using. This implicates the readiness for a company to start using mobile applications in their business. The fixed network applications used by the interviewed companies are mapped in table 5.

Table 5. Fixed network applications used by the interviewed companies.

Industry Internet Extranet Intranet E-mail Electronic calendar

Company-wide ERP

Integrated ERP

Health care 10 10 10 10 10 5 -

Trade 10 8 10 10 10 5 1

Tourism 10 8 9 10 10 4 3

Facilities management

10 4 8 10 8 1 1

Process industry

10 9 9 10 9 8 3

Total 50 39 46 50 47 23 8

Share of total 100 % 78 % 92 % 100 % 94 % 46 % 16 %

As the table show, the majority of the interviewed companies were large national companies with more than 1000 employees and revenues more than 100 million euros. All companies were using the most common fixed network applications, the Internet and e-mail. Also extranet, intranet, and electronic calendar applications were used by more than 75 % of the interviewed companies.

49

ERP applications, especially those integrated to suppliers’ or customers’ systems, were currently used quite infrequently but were expected to be more popular in the near future.

3.5.2 Mobile services in use today, realistic plans for the future

Next, the companies were asked about their current and planned use of mobile services. The current use of mobile services, as well as the amount of different services used, are shown in table 6.

Table 6. Number of mobile services currently used by the interviewed companies.

Industry Number of companies

Companies currently using mobile

services

Number of mobile services used

Health care 10 3 7

Trade 10 6 10

Tourism 10 8 12

Facilities management 10 6 7

Process industry 10 6 8

Total 50 29 44

Share of total 100 % 58 %

Majority (58) of the interviewed companies were currently using some mobile applications. The number of mobile services used indicates that some companies had already several different applications in use. The next table (table 7) shows the number of planned mobile services in the same companies.

Table 7. Number of mobile services planned by the interviewed companies.

Industry Number of companies

Companies with

unspecified plans

Companies with specified

plans

Modifications to existing services

Totally new services

Health care 10 1 5 4 9

Trade 10 5 5 4 11

Tourism 10 - 7 6 2

Facilities management 10 1 6 4 12

Process industry 10 4 5 - 6

Total 50 11 28 18 40

Share of total 100 % 22 % 56 %

50

Majority (56 %) of the interviewed companies had specified plans for mobile services usage. In most cases, the planned mobile services were totally new but there were also companies that planned modifications to existing mobile applications. Many companies were also planning to use mobile services but did not yet have specified plans.

In health care, only three organizations of ten were currently using mobile services. These applications were made for employees, and the aim was save time in certain tasks compared to traditional routines. Various alarm systems were some examples of the applications currently in use. The employees have been satisfied with the applications and no major problems have occurred. Most of the interviewed health care organizations have major plans for future mobile services, not only for employees but also for customers. The most remarkable obstacles are linked to data security issues. Digital signature, for instance, has a legal status but cannot be used in documents that have to be filed in manual archives.

Trading companies are currently frequent users of mobile services: six of the interviewed ten companies had some mobile applications in use and any of the companies were also planning some new mobile services. The aim of the applications is usually to save time and enable mobility for both employees and customers. Mobile buying, bidding, reservation, and reporting systems are some examples of mobile applications used by trading companies. The main problems are related to terminal incompatibility, slow data transmission rate, problems in learning to use the system, complexity of processes, and the narrow scope of certain applications. Especially WAP protocol as an application platform was experienced slow, expensive, cumbersome, and unreliable.

Tourism is the most frequent user of mobile services at the moment: eight of the interviewed ten companies used mobile services. In the near future, however, these companies are slowing down the development of new mobile applications and will focus on fixed network applications instead. The current mobile applications are related to booking, price information, timetables, and guiding services. They provide customers with up-to-date information but are quite complex to use, mainly because they are built for fixed network use and are therefore quite difficult to use via mobile network.

In facilities management, the interviewed companies can be divided into two opposite groups. Six of the interviewed ten companies used mobile services and were interested in developing new services, while rest of the companies were very conservative and did not have any plans for mobile services in the near future. Most of the applications were made for employees and were related to guarding, cleaning, and waste disposal services. The benefits of these applications were, for example, more efficient work control and use of resources, reduced workload, and saving time. The problems were related to inadequate terminal functionality, unwillingness and lacking competence to use the applications, and the overall complexity caused by several parallel systems.

In process industry, six of the interviewed ten companies were currently using mobile services. The services are mainly related to “mobile office” applications, i.e. bringing e-mail and calendar into mobile terminal, but there were also some advanced work control systems and even plans to develop a mobile intranet or extranet. The main benefit of these services is, not surprisingly, that

51

they can be used anytime and almost anywhere, in contrast to fixed network services. Among others, there have been problems with supporting services and slow data transmission. A noteworthy observation was that Scandinavian-owned process industry companies seemed to have a much more positive outlook on mobile services than the subsidiaries of their continental rivals.

3.5.3 Mobile e-mail and industy-specific applications are interesting

The interviewed companies were also given some hypothetical, but realistic, examples of mobile services and asked to prioritize them. All industries were given two general mobile service examples: (1) mobile e-mail and calendar, and (2) general company WAP pages, analogous to company web pages. In addition, the companies were given two industry specific mobile service examples. These are listed below.

• Health care: (1) mobile medical treatment/appointment system, (2) mobile access to patient database for ambulance staff.

• Trade: (1) mobile access to customer database or task list for logistics personnel, (2) information to customers about shop locations, opening hours, and special offers.

• Tourism: (1) mobile booking system, including information about delayed departures etc., (2) mobile information databases and task lists for guides or other personnel.

• Facilities management: (1) mobile service instructions and task lists for maintenance staff, (2) mobile application for announcing about faults to be repaired.

• Process industry: (1) mobile remote control of a process or machine, (2) mobile track&trace system for customers about orders to be delivered.

Table 8 shows the priorities of various industries about the given mobile service examples. Industry specific mobile service examples are marked with asterisk (*).

Table 8. Priorities of given mobile service examples among the industries interviewed.

Industry 1st place in priority list

2nd place in priority list

3rd place in priority list 4th place in priority list

Health care Mobile medical treatment*

Mobile access to patient database* Mobile e-mail

and calendar

WAP pages

Trade Mobile e-mail and calendar

Information to customers*

Mobile access to customer database*

WAP pages

Tourism Mobile booking system*

Mobile information database*

Mobile e-mail and calendar

WAP pages

Facilities management

Mobile e-mail and calendar

Mobile service instructions*

Mobile fault announcement*

WAP pages

Process industry

Mobile e-mail and calendar

Mobile remote process control*

Mobile track&trace system*

WAP pages

52

As the table shows, all industries are interested in both general mobile e-mail applications and industry specific mobile services. It becomes also clear that companies are not planning to introduce general WAP pages as complements to their web pages. This indicates that the companies do not expect WAP-based mobile browsing to become popular in Finland in the near future.

In summary, more than 50 % of the interviewed companies had existing mobile services in use and specified plans for future applications. The main obstacle in using mobile services seems to be that current techonology and pricing, based on GSM data, WAP and SMS, are inadequate in professional business applications. Companies in tourism were the most frequent users of mobile services, whereas health care organizations had least mobile applications in use.

53

4 CONCLUSIONS AND DISCUSSION

After analyzing the structure of the mobile cluster and identifying the main drivers and obstacles for the success of mobile services, it is time to present the conclusions of the analysis.

4.1 There is no business for chargeable end-user applications

In studying the structure if the Finnish mobile cluster, the absence of mobile end-user application business is striking. The cluster is dominated by Nokia and supported by the major national teleoperators. There is also a dynamic, emerging market for mobile platform development and a number of business-to-business applications.

Still, there are no successful mobile services targeted for private consumers. Analogous to the fixed network services for private consumers, also mobile portals and other application are expected to be free of charge. It is therefore dangerous to assume that there would ever be any major business opportunities in the field of chargeable end-user services targeted for private customers. Instead, useful business applications and free applications sponsored by the providing companies may have a remarkable business potential.

It is thus likely that the Finnish mobile cluster is going to be dominated by Nokia and the two major teleoperators also in the future. As the mobile application market grows, the biggest business potential lies in the group of fast-growing mobile platform developers and business-to-business application developers.

4.2 Nokia brought mobile communications into national focus

The presence of Nokia is the most remarkable single factor affecting positively in the development of the Finnish mobile cluster. Nokia brought the whole mobile communications into a national priority – and being on national focus is the basic requirement for cluster development.

Liberal regulation is, compared to othe European countries, a major national strength in Finland: very often the Finnish legislation seems to be two steps ahead of EU legislation. This has several times created an advantage for Finnish firms in the field of telecommunications. Hopefully it will do so even in the mobile services development business.

Educated IT-experts form the ground of the mobile cluster development. The mismatch of supply and demand in the labor market of information technology has often been exaggerated. Instead, the availability of educated and competent personnel is considered as strength of the Finnish mobile cluster.

The technology-oriented consumers provide the Finnish companies with a national testing laboratory for both mobile terminals and services. Hardly anywhere else are the consumers as interested in new mobile phones, ringtones, etc. as in Finland. Early home demand creates an advantage for Finnish companies in international markets.

54

4.3 The conservative attitudes must change

The negative attitudes towards WAP and other mobile services after the hype of 1999 are restricting the development of application development. After being too bullish about future hopes, the operators and content providers are now lacking the credibility. Today, the consumers do not see any meaning for mobile services, as they once got disappointed in the unsuccessful launch of WAP services.

The conservative attitudes of Finnish teleoperators are changing slowly into a more liberal direction. Still, the operators too often have the attitude of “owning” the customer, which makes the cooperation in mobile payment architecture, for instance, more difficult than it should be. Also, even though the pricing policy in mobile services is changing by the launch of GPRS, the other cluster companies consider it as the main obstacle for mobile service development.

The level of taxation affects negatively in the productivity of Finnish IT labor. Having one of the highest levels of income tax, the Finnish working environment cannot provide any major economic incentive for people working hard. Also corporate taxation, once being a strength compared to other European countries, is now sliding back to a moderate level.

4.4 Dangerous to rely on a single technology

The success of UMTS is predicted to give a massive boost to mobile services production. Today’s expections about the third generation of mobile communications are, fortunately, on realistic level compared to the promises two years ago. If UMTS takes off, it will create additional business opportunities for mobile service developers.

Locking into a single technology is, on the other hand, dangerous. As the clustering process always takes several years and the technological development in mobile communications is rapid, the success of the Finnish mobile cluster cannot be built on a single technology. Instead, all possible development paths of the future should be taken into consideration.

4.5 Potential in platforms and B-to-B applications

As the mobile applications for consumers have not yet taken off, the situation is better in business-to-business market. A majority of the companies interviewed in the study were using some kind of mobile applications. In addition, almost all the companies had some plans of using mobile applications in the near future.

The results clearly show that the revolution in the use of mobile services has begun. Not surprisingly, business customers were the first ones to adopt the new mobile applications – for companies, mobile services can provide remarkable savings in time and money. Mobile calendar and email are found particularly appealing. It seems, however, that the largest international business potential for Finnish companies in mobile services lies in developing platforms, not end user applications.

55

REFERENCES

Aldrich, H.E. & Fiol, C.M. 1994. Fools rush in? The institutional context of industry creation. Academy of Mangement Review, Vol. 19, pp. 645–670.

Ali-Yrkkö, J. et al. 2000. Nokia – A Big Company in a Small Country. Helsinki, ETLA – The Research Institute of the Finnish Economy. 55 p.

Aoki, M. 1987. The Japanese Firm in Transition. In Yamamura, K. & Yasuba, Y. (eds.) The Political Economy of Japan. Stanford, Stanford University Press.

Arthur, W.B. 1989. Competing technologies, increasing returns and lock-in by historical events. The Economic Journal, Vol. 99, pp. 116-131.

Arthur, W. 1990. Silicon Valley locational clusters: When do increasing returns imply monopoly? Mathematical Social Sciences, Vol. 19, pp. 235–251.

Audretsch, D.B. & Feldman, M.P. 1996. R&D spillovers and the geography of innovation and production. The American Economic Review, Vol. 86(3), pp. 630–639.

Baptista, R. & Swann, P. 1998. Do firms in clusters innovate more? Research Policy, Vol. 27, pp. 525–540.

Barney, J.B. 1991. Firm resources and sustained competitive advantage. Journal of Management, Vol. 17, pp. 99–120.

Bartlett, C.A. & Ghoshal, S. 1989. The Transnational Solution. Boston (MA), Harvard Business School Press. 391 p.

Baum, J.A.C. & Mezias, S.J. 1992. Localized competition and organizational failure in the Manhattan hotel industry. Administrative Science Quarterly, Vol. 37(4), pp. 580–604.

Berger, S. et al. 1999. Globalization, value networks, and national models. Memorandum prepared for the IPC Globalization Meeting, October 8th, 1999.

Brusco, S. & Righi, E. 1989. Local government, industrial policy and social consensus: The case of Modena (Italy). Economy and Society, Vol. 18, pp. 405–424.

Cartwright, W.R. 1993. Multiple linked “diamonds” and the international competitiveness of export-dependent industries: The New Zealand experience. Management International Review, Vol. 33(2), pp. 55–70.

Ciccone, A. & Hall, R.E. 1996. Productivity and the density of economic activity. The American Economic Review, Vol. 86(1), pp. 54–70.

Dahmen, E. 1986. Schumpeterian Dynamics: Some methodological notes. In Day, R. & Eliasson, G. (eds.) The Dynamics of Market Economics. North Holland, Amsterdam.

Davine, A. & Holmqvist, S. 2001. Mobile Internet Content Providers and their Business Models. Stockholm, Kungliga Tekniska Högskolan. 92 p.

D’Cruz, J.R. 1986. Strategic Management of Subsidiaries. In Etemad, H. & Seguin-Delude, L. (eds.) Managing the Multinational Subsidiary. London, Croom Helm/Routledge, p. 75–89.

56

Directive 97/66/EC. Directive of the European Parliament and of the Council concerning the processing of personal data and the protection of privacy in the telecommunications sector. 15.12.1997.

Directive 1999/93/EC. Directive of the European Parliament and of the Council on a Community framework for electronic signatures. 13.12.1999.

Directive 2000/31/EC. Directive of the European Parliament and of the Council on certain legal aspects of information society services, in particular electronic commerce, in the Internal Market (Directive on electronic commerce). 8.6.2000.

Doz, Y.L & Prahalad, C.K. 1981. Headquarters influence and strategic control in MNEs. Sloan Management Review, Vol 23(1), pp. 15–30.

Dunning, J.H. 1990. Dunning on Porter. Paper presented at the Annual Meetings of the Academy of International Business, Toronto.

Dunning, J.H. 1993. Internationalizing Porter’s diamond. Management International Review, Vol. 33(2), pp. 7–15.

Durlacher 1999. Mobile Commerce Report. Durlacher Research Ltd., London. 76 p.

Durlacher 2001. UMTS Report: An investment perspective. Durlacher Research Ltd., London. 140 p.

FiCom 2002. Finnish Federation for Communications and Teleinformatics. [http://www.ficom.fi].

Fiske, S.T. & Taylor, S.E. 1991. Social Cognition. New York (NY), McGraw-Hill. 728 p.

FITS 2001. Finnish Research and Development Programme on ITS Infrastructures and Services. [http://www.vtt.fi/rte/projects/fits/].

Forrester 2000. Mobile’s High-Speed Hurdles. Forrester Research, Inc., Cambridge (MA). 17 p.

Gersick, C.J. 1991. Revolutionary change theories: A multilevel exploration of the punctuated equilibrium paradigm. Academy of Management Review, Vol. 16(1), pp. 10–37.

Ghoshal, S. & Bartlett, C.A. 1990. The multinational corporation as an interorganizational network. Academy of Management Review, Vol. 15(4), pp. 603–625.

Green, P.E. et al. 1988. Research for Marketing Decisions. Englewood Cliffs (NJ), Prentice-Hall.

Grove, A. 1987. The future of Silicon Valley. California Management Review, Vol. 29(3), pp. 154–160.

GSM World 2002. The World Wide Web Site of the GSM Association. [http://www.gsmworld.com].

Hamel, G. & Prahalad, C.K. 1994. Competing for the Future. Boston (MA), Harvard Business School Press. 357 p.

Hannan, M. & Freeman, G. 1989. Organizational Ecology. Cambrigde (MA), Harvard University Press. 382 p.

57

Harrison, B. et al. 1996. Innovative firm behavior and local milieu: Exploring the intersection of agglomeration, firm effects, industrial organization and technological change. Economic Geography, Vol. 72(3), pp. 233–258.

Haveman, H. 1993. Follow the leader: Mimetic isomorphism and entry into new markets. Administrative Science Quarterly, Vol. 38, pp. 593–627.

HE 194/2001. Hallituksen esitys Eduskunnalle laiksi tietoyhteiskunnan palvelujen tarjoamisesta ja eräiksi siihen liittyviksi laeiksi. 26.10.2001

HE 197/2001. Hallituksen esitys Eduskunnalle laeiksi sähköisistä allekirjoituksista ja viestintähallinnosta annetun lain 2 §:n muuttamisesta. 26.10.2001.

Hippel, E. von 1988. The Sources of Innovation. New York (NY), Cambridge University Press.

Hirschman, A.O. 1958. The Strategy of Economic Development. New Haven (CN), Yale University Press.

Hodgetts, R.M. 1993. Porter’s diamond framework in a Mexican context. Management International Review, Vol. 33(2), pp. 41–54.

Häyrynen, J. 2002. Open Mobile Architecture Initiative. Paper presented at the first meeting of Mona steering group, Helsinki, 5.2.2002.

Jacobs, D. & De Man, A.P. 1996. Clusters, industrial policy and firm strategy: A menu approach. Technology Analysis & Strategic Management, Vol. 8, pp. 425–437.

Jaffe, A. et al. 1993. Geographic localization of knowledge spillovers as evidenced by patent citations. Quarterly Journal of Economics, Vol. 58(3), pp. 577–598.

Kaasalainen, T. 2001. Head of Business Development, Ionific Ltd. Interview 13.9.2001.

Kajanto M. 1997. Strategic Framework for the Interactive Networks Industry. Acta Polytechnica Scandinavica -series. Helsinki.

Krugman, P. 1991. Increasing returns and economic geography. Journal of Political Economy, Vol. 99(3), pp. 483–499.

Kujala, A. 2001. Senior Consultant, EPStar Ltd. Interview 18.10.2001.

L 523/1999. Henkilötietolaki. 22.4.1999.

L 565/1999. Laki yksityisyyden suojasta televiestinnässä ja teletoiminnan tietoturvasta. 22.4.1999.

Lahti, A. 2000. Creative Entrepreneurship and New Economy: The Challenge of the Nordic IT Cluster. Helsinki, Helsinki School of Economics and Business Administration Working Papers. 120 p.

Leppänen, P. & Riihimäki, R. 2002. Mona-ohjelma: Taksi-projekti. Helsinki, EPStar Ltd.

Leppänen, P. & Saikanmäki, A. 2002. Mona-ohjelma: Navitam-mobilesovellus. Tampere, EPStar Ltd.

Leppävuori, I. & Kiuru, P. 2001. Klusterianalyysi – esiselvitys Suomen mobiiliklusterin toimivuudesta. Tampere, EPStar Ltd. 39 p.

58

LIF 2001. Location Interoperability Forum. [http://www.locationforum.org].

Lintunen, L. 2000. Who Is the Winner Entrepreneur? An Epistomological Study of the Schumpeterian Entrepreneur. Helsinki, Helsinki School of Economics and Business Administration.

Luostarinen, R. 1991. Development of strategic thinking in international business: The case of Finland. In Näsi, J. (ed.) Arenas of Strategic Thinking. Helsinki, Foundation of Economic Education, pp. 257–273.

Marshall, A. 1920. Principles of Economics. New York (NY), Promotheus Books, 1997. 319 p.

Meyer, A. 1982. Adapting to environmental jolts. Administrative Science Quarterly, Vol. 27, pp. 515–537.

MinTC 2002. Ministry of Transport and Communications Finland. [http://www.mintc.fi].

Mobey Forum 2001. The Preferred Payment Architecture Technical Documentation. Version 1.0, approved 25.6.2001.

Mona 2002. Mona – Mobile Services Development Program. [http://www.mona-ohjelma.net].

OMA 2002. Open Mobile Architecture Initiative. Nokia Corporation [http://www.nokia.com/oma/].

Oliver, C. 1991. Strategic responses to institutional processes. Academy of Management Review, Vol. 16, pp. 145–179.

Ottila, E. 2002. Director, ICL Invia Oyj. Interview 23.1.2002.

Paija, L. (ed.) 2001. Finnish ICT Cluster in the Digital Economy. Helsinki, ETLA – The Research Institute of The Finnish Economy. 178 p.

Parolini, C. 1999. The Value Net: A tool for competitive strategy. Chichester, John Wiley & Sons. 264 p.

Penttinen, R. 1994. Summary of The Critique on Porter’s Diamond Model. Helsinki, ETLA – The Research Institute of the Finnish Economy. 82 p.

Porac, J. & Thomas, H. 1990. Taxonomic mental models in competitor definition. Academy of Management Review, Vol. 15, pp. 224–240.

Porter, M.E. 1985. Competitive Advantage: Creating and sustaining superior performance. New York (NY), The Free Press. 557 p.

Porter, M.E. 1990. The Competitive Advantage of Nations. New York (NY), The Free Press. 855 p.

Porter, M.E. 1998. On Competition. Boston (MA), Harvard Business School Press. 485 p.

Pouder, R. & St. John, C.H. 1996. Hot spots and blind spots: Geographical clusters of firms and innovation. Academy of Management Review, Vol. 21(4), pp. 1192–1225.

Puusola, K. et al. 2001. Varmennepalvelujen markkinat ja kilpailutilanne. Publications of the Ministry of Transport and Communications Finland 39/2001. 55 p.

59

Rainio, A. 2000. Henkilökohtainen navigointi: markkinat, teknologia ja sovellukset. Helsinki, VTT Information Technology. 124 p.

Rauch, J.E. 1993. Does history matter only when it matter little? The case of city-industry location. Quarterly Journal of Economics, Vol 108, pp. 843–867.

Reynolds, P.D. et al 2001. Global Entrepreneurship Monitor: 2001 Executive report. Global Entrepreneurship Monitor program. 58 p.

Rugman, A.M. & D’Cruz, J.R. 1993. The “double diamond” model of international competitiveness: The Canadian experience. Management International Review, Vol. 33(2), pp. 17–39.

Rugman, A. & Verbeke, A. 1990. Global Corporate Strategy and Trade Policy. London, Routledge.

Rugman, A.M. & Verbeke, A. 1993. Foreign subsidiaries and multinational strategic management: An extension and correction of Porter’s single diamond framework. Management International Review, Vol. 33(2), pp. 71–84.

Rönkkö, P. 2001. Technology-based, New Companies in the Finnish Mobile Cluster. Helsinki, Eficor Consulting. 36 p.

Sako, M. 1989. Competitive Cooperation: How Japanese manage inter-firm relations. London, London School of Economics.

Saurio, S. 2001a. Mobiiliklusterin visiosta kehittämisohjelmaan. Helsinki, Ministry of Trade and Industry. 93 p.

Saurio, S. 2001b. Mobiiliklusterin visiot 2005. Paper presented at the opening seminar of Mona program, Helsinki 20.9.2001.

Saxenian, A. 1996. Regional advantage: Culture and competition in Silicon Valley and Route 128. Cambridge (MA), Harvard University Press. 226 p.

Schumpeter, J. 1934. The Theory of Economic Development: An inquiry into profits, capital, credit, interest and the business cycle. Cambridge (MA), Harvard University Press.

Schumpeter, J. 1942. Capitalism, Socialism and Democracy. New York (NY), Harper & Brothers.

Scott, A.J. 1992. The Roepke lecture in economic geography. The collective order of flexible production agglomerations: Lessons for local economic development policy and strategic choice. Economic Geography, Vol. 68, pp. 219–233.

Silver, A.D. 1985. Entrepreneurial Megabucks. The 100 greatest entrepreneurs of the last twenty-five years. New York (NY), John Wiley & Sons. 467 p.

Singh, J.V. et al. 1986. Organizational legitimacy and the liability of newness. Administrative Science Quarterly, Vol. 31, pp. 171–193.

Tilastokeskus 2002. Statistics Finland. [http://www.stat.fi].

60

Steinbock, D. 2000. Finland’s Wireless Walley: From industrial policies toward cluster strategies. Publications of the Ministry of Transport and Communications Finland 36/2001. 68 p.

Sturgeon, T. 1997. Turn-key production networks: A new American model of industrial organization? University of California at Berkeley, working paper 92A.

Tekes 2002. The National Technology Agency. [http://www.tekes.fi].

Timmers, P. 1999. Electronic Commerce: Strategies and models for business-to-business trading. New York (NY), John Wiley & Sons. 288 p.

Tuschman, M.L. & Romanelli, E. 1985. Organizational evolution: A metamorphosis model of convergence and reorientation. In Cummings, L.L. & Staw, B.M. (eds.) Research in Organizational Behavior. Greenwich (CT), JAI Press, pp. 171–222.

Vernon, R. 1966. International investment and international trade in the product cycle. Quarterly Journal of Economics, Vol. 80, pp. 190–207.

WAI 2001. Web Accessibility Initiative (WAI). The World Wide Web Consortium. [http://www.w3.org/wai/].

WAP Forum 2002. [http://www.wapforum.org].