Types of Corporate Innovation System and Innovation Performance in Korea- Transformation Strategy for the Better Types of CIS
in the ICT Service Sector
Junhyup Lee (Ph.D. Candidate, Seoul National University)

Abstract
Based on the Innovation System Approach, this paper establishes a Corporate Innovation System in Korea.
Using latent class analysis with the Workplace Panel Data 2005 provided by Korea Labor Institute, we induced
four types of CIS in Korea: the High-involvement type CIS, the R&D type CIS, the HI+R&D type CIS, and the
Low Developed CIS. A workplace belongs to the HI type CIS was establishing high-involvement institutions
such as well designed work system, motivation system, vocational education and training system, and labor
relations simultaneously. A workplace pertains to the R&D type CIS was engaging in R&D activities withoutestablishing high-involvement institutions; this characteristic is directly oppose to that of the HI type CIS. A
workplace belongs to the HI+R&D type CIS was establishing a virtuous circle including well designed highinvolvement institutions and R&D activities; this characteristic is directly oppose to that of the Low Developed
CIS.
This paper examines the relationship between types of CIS and innovation performances— product/service
innovation, employees-leading innovation, patent application, and labor productivity. The result was that theinnovation performance of the HI+R&D type CIS was dramatically high; the performances of the HI type CIS
and the R&D type CIS following it; and the Low Developed CIS showed significantly poor performance. Thispattern was always discovered in all the cases of innovation performance. In addition, the HI type CIS wassuperior to the R&D type CIS in case of product/service innovation and the employees-leading innovation;
while the R&D type CIS had advantages of the patent application and labor productivity. Furthermore, we
conclude that the main hindrance of transformation from the R&D type CIS to the HI+R&D type CIS is poorly
developed corporate culture. Meanwhile, the main obstacle of systemic transformation from the HI type CIS to
the HI+R&D type CIS is the dissimilar purpose of innovation; that is to say, a workplace belongs to the HI typeCIS usually pursue product/service innovation but not pursue patent application.
Keywords: Corporate Innovation System, Institutional Complementarities, High-involvement Institutions, R&D
activities, Latent Class Analysis

Chapter1. Research Backgrounds and Hypotheses
1. Motivations and Purposes
1.1. Exploring a Corporate Innovation System in Korea

One of the extraordinary strands of economics during the last two decades is to introduce a systemic
approach in the innovation research. Lundvall (1985) introduced the concept of „innovation system‟, and theadjective „national‟ was added to it by Freeman (1987). After that, technological systems (Carlsson &Stankiewics, 1991), sectoral systems of innovation (Breschi & Malerba, 1995), regional systems of innovation(Cooke, 1997), corporate innovation system (Grandstrand, 2000), social systems of innovation and production(Amable, 2003), organizational innovation system (Wagner-Luptacik et al., 2006), and numerous other names of1

innovation systems have been coined.
Innovation system approach (IS approach) is an influential theoretical framework. This approach deals withorganizations, institutions, and their relations in a single framework. From the historical and evolutionary
perspectives, IS approach assumes that various organizations and institutions are co-evolving with interaction,and this co-evolution creates various types of innovation system. This view is a little complex, but it is more
realistic than its alternatives. Most of all, this approach provides a consistent basis for generating hypotheses
about relations among specific variables. Using this approach, we can test these hypotheses and induce policy
implications. Based on the concept of national innovation system (NIS), many researchers have examined
institutional complementarities, and have drawn inspiring innovation policies of nations. With the help ofsectoral systems of innovation (SSI), unique characteristics of each sector have been analyzed.
However, little attention has been focused on corporate innovation system (CIS). Grandstrand (2000)
defined CIS, and conducted qualitative analysis with interview/questionnaire data of 42 large corporation
managers. Wagner-Luptacik et al. (2006) analyzed a firm as an organizational innovation system based oncomplexity theory and social system. These studies treated a firm as an innovation system, but not reached toestablishing corporate innovation system. The first purpose of this paper is to establish a corporate innovation
system in Korea, and empirically analyze the relationship between institutions, organizations, and their activities.

1.2. Ordering CISs on the basis of Innovation Performance

The main function of innovation system is to pursue innovation process such as developing, diffusing, andusing innovation, so measuring innovation performance is crucial. This paper hypothesizes that some types of
CIS are correlated with high level of innovation performances, other types of CIS are correlated with poor
performances. The second purpose of this paper is to test this hypothesis.

1.3. Exploring Transformation Strategy for the Better Types of CIS in the ICT Service Sector in Korea

IS approach underlines organizational change especially organizational innovation. All the research basedon IS approach has emphasized the effect of institutional complementarities in the process of organizationalinnovation. For example, an introduction of job rotation may function well in some workplaces, but not in otherworkplaces. In the former workplace, the newly introduced institution may synchronize with the existing
institutions, thus these new and existing institutions may constitute a virtuous circle. In the latter workplace,
however, the newly introduced institution may be conflicted with the existing institutions, thus constitute a
vicious circle. Therefore, establishing an organization innovation strategy is a challenging mission.
This paper investigates organizational innovation from somewhat novel, different angle: Transformationfrom one CIS type to the other CIS type. If some types of CIS are correlated with high level of performance, allfirms may try to transform toward that types of CIS. In reality, however, various types of CIS may exist, andsome types of CIS may be correlated with poor performances. It means that there would be some factors toprevent this transformation. The third purpose of this paper is to investigate the obstacle, and exploretransformation strategies for the better types of CIS, especially in the ICT service sector.
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2. Research Backgrounds
2.1. Innovation System approachThis paper trails the IS approach based on the Neo-Schumpeterian tradition. IS approach has developed
along the intricate paths, and various branches of research have been conducted. In this section, four branches ofresearch, which are highly correlated with the CIS Model in Korea, are introduced: Knowledge management,competence development, learning organization, and organizational innovation.

2.1.1. Knowledge management

One of the main themes of the IS approach is to define and manage knowledge. In the IS approach,innovation or learning in a firm is considered as a process of cultivating, combining and utilizing quite different
types of knowledge, thus knowledge management has become a central challenging function in the organization.
OECD (2003) defines knowledge management as a function covers any intentional and systematic process ofacquiring, sharing and using knowledge in order to enhance learning and performance in organizations.
The first step to understand knowledge management is to define the various types of knowledge. Lundvall
and Johnson (1994) distinguished knowledge as know-what, know-why, know-how, and know-who. Knowwhat refers to knowledge on facts; know-why relates to causes and effects; know-how refers to competences
and capabilities; and know-who refers to knowledge of who have certain competences and skills. Know-what
and know-why is more explicit, tangible and easy to codify; meanwhile know-how and know-who is more
implicit, intangible and difficult to codify. This difference between explicit versus tacit knowledge is offundamental importance in understanding the challenges of knowledge management.
Lam (2000) combined this tacit/explicit knowledge with individual/collective knowledge. Embrained
knowledge is individual and explicit knowledge, dependent on the person‟s cognitive abilities. Encodedknowledge is explicitly and collectively shared through written rules or procedures in the organization.
Embodied knowledge is tacit knowledge held by the individual. Embedded knowledge is knowledge built into
routines, habits and norms of the organization.
Jensen and Lundvall (2007) defined two types of knowledge according to two modes of learning andinnovation: the STI-mode (science-technology-innovation mode) and DUI-mode (learning by doing, using,interacting mode). Using survey data of 692 Danish firms in the private sector, they resulted that a firm strong inboth of the STI-mode and the DUI-mode knowledge was correlated with 5.1 times of possibilities of
product/service innovation (P/S innovation) than a firm strong in none of the two mode of knowledge. A firm
strong in the STI-mode knowledge was 2.4 times as high, and a firm strong in the DUI-mode knowledge was
2.2 times as high.
In the context of the learning economy hypothesis, the process of knowledge management is critical. The
combination of globalization, information technology and deregulation leads to more and more rapidtransformation and change, in which knowledge gets obsolete with an increasing speed. Relating tacit
3knowledge to explicit knowledge becomes a very important management function. This function must takeplace on all levels in the organization and often with the middle level management as midpoint of this process(Nonaka and Takuechi, 1995). In the perspective of the learning economy, the speed of innovative capabilities,
that can bring new products quickly into the market, becomes more critical. Organizational innovation may
therefore be assumed to take certain directions that shorten the time lag from external change to external
response.

2.1.2. Competence development

IS approach highlights on learning process and competence building. It assumes that organizations andagents have a capability to enhance their competence through learning and interacting with each other. Therefore
the focus is upon how enduring patterns of interaction are established, evolve and dissolve as time goes by. New
competences are built while old ones are destroyed. These patterns characterize the innovation system andchange in a process of creative destruction of knowledge and relationships. A crucial normative issue is how
such patterns affect the creation of new resources and to what degree they support learning among agents.
Organizational learning and competence building is crucial both for a firm and employees. Throughlearning activities, a firm accumulates its structural capability to innovation, and employees also improve theircompetence. In this reason, to assess workplaces as learning sites and to focus on competence development
becomes increasingly important. There is no consent on the concept of competence development. In spite ofthese inconsistencies, however, three dimensions of competence development may be constructed: individualand generic competence, individual and situated competence, collective and situated competence.
Individual and generic competence denies the importance of organizational or work-related circumstances
within which a given competency is used independently from the context of activities. Individual and situatedcompetence, according to Lave and Wenger (1991), means potential possibilities to act in a specific situation orcontext. In this context, competence development is defined as a continuous development of experiences, skills,
and responsibilities related to the job situation. With this definition, competence development becomes closely
connected to the experience-based and situated part of the learning concept and related to the organizational andmanagement context of the work situation (Nielsen, 2006). The last is collective and situated competence. If thecompetence is closely connected to the concrete job situation, it is a logical assumption that it can beheld byindividuals as well as by the group of individuals. The main difference between individual and collective
competence approaches is that the latter attributes more importance to the organizational culture of the firms andpays particular attention to the relations built up between the participants in the labor process.
These relations play an essential role in the ways employees are using and sharing their knowledge, skills
and competences. Thus, it is of crucial importance what kind of organizational practices are being used in thefirms in order to generate and promote these collective competences—job rotation, teamwork, multidisciplinary
planning teams, and other devices to promote collective competences (Makó, Illéssy and Csizmadia 2007).

2.1.3. Learning organization

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Consistent with the learning economy hypothesis, the environment of today‟s firm is characterized by arelatively high degree of complexity, unstableness, and unpredictability. Senge (1992) stated that thesecharacteristics have motivated the concept of a learning organization. Learning organization is defined as anorganization that has been designed, developed, and implemented to hold a capacity to adapt continuously to its
environment. Daft (2001) stated that main characteristics of learning organizations are horizontal structure,empowered employees, shared information, collaborative strategy, and adaptive culture. Heery and Noon (2001)
stated that the learning organization is constantly looking for new ideas and approaches.
There are some organizational traits which speed up both adaptation and innovation: A limited number oflevels in the horizontal hierarchy; horizontal communication supported by teamwork or job rotation acrossdivision border; the delegation of responsibility; external interaction. An interesting analytical issue is weather
each of these traits can be seen as single contributions to enhanced performance, or weather they arecomplementary and have a bigger impact when they appear as a combined package. Nielsen & Lundvall (2006)
showed that a co-operative regime, combining direct and indirect participation, is most effective on thedevelopment of the learning organization and so innovation. Especially in case of potential conflict, the indirect
methods show their importance. Arundel et al. (2007) empirically classified four types of work organizations:the discretionary learning work organization, lean production learning work organization, Taylorist workorganization, and simple work organization. And they resulted that a firm organized to support high levels of
discretion in solving complex problems is correlated with high level of innovation performance. And they
concluded that learning and interaction within organizations are important as same as learning throughinteractions with external agents.

2.1.4. Organizational innovation

In most of empirical research based on IS approach, innovation normally refers to changes in technicalsolutions associated with process or product/service, but rarely associated with the change of organizations.
Organizational change is an intentional process of breaking down regular patterns of behavior in order to create
new patterns that subsequently become institutionalized. And organizational innovation is defined as the changeof organizational processes and structures with the purpose of enhancing the competitiveness or performance ofthe organization. Thus, organizational innovation occurs in cases where: change of organizational processes
leads to change of organizational structures; change of organizational structures leads to change oforganizational processes; and changes of organizational processes and structures occur simultaneously.

2.2. Human Resource Management Theory and Employment Relations Theory

2.2.1. Human Resource Management and Work System Design

Storey (1995) defined human resource management is a distinctive approach to employment management
which seeks to achieve competitive advantage through the strategic deployment of a highly committed andcapable workforce, using an array of cultural, structural and personnel techniques. The importance of5organizational design as frame of managing the human resource is critical to understand the relation between
employers and employees on the basis of the HRM theory. In parallel with the concept of the learningorganization, work system refers to a number of specific work practices which are seen as interrelated. Althougha work system can be decomposed into a number of work practices, its outcomes are most of all determined bytheir integration in a coherent bundle or cluster, because there are complementarities and synergies among them.
Two approaches on how to design work system are introduced: High Performance Work System and Lean
Production and Administration approach.
The main characteristic of a high performance work system (HPWS) is extensive involvement of
employees. This involvement harnesses the potential of people and improves the performance of theorganization. Employees in a HPWS experience greater autonomy over their job tasks or methods of work, andhave higher levels of communication with other employees, functional specialists, managers, and vendors ofcustomers. In the HPWS approach, job is firm-specific, and employees are required more skills to do their job
successfully. Incentives must be provided for employees in order to obtain additional skills and to engage inactivities such as problem solving. Employment security provides employees with a long-term stake in thecompany and a reason to invest in its future, while the payment of quality or other incentives allows them toshare in the fruits of improved performance. Employment security and incentive pay motivate employees tomake an extra effort in developing skills and participating in decisions.
The lean production approach has developed in many countries within both manufacturing and service.
Womack and Jones (2003), who initiated the lean wave, stated the lean principles as follows: precisely specify
value by specific product, identify the value stream for each product, make value flow without interruptions, let
the customer pull value from the producer, and pursue perfection. The aim of lean strategies is improving
performance measured by profits and new product development, and the practical use of lean strategies contains
various issues such as cost reduction, employee empowerment, value chain orientation, and product innovation.
Kochan et al. (1997) examined the diffusion of lean production, and so the concrete interaction between changes
in production systems and employee relations at the plant level. Common trends were greater work organization
flexibility, employee participation, investment in skill development, and reductions in employment security
associated with downsizing. In addition, EPOC research group (1997) showed wide differences between actual
employee participation and skill demands across the groups; less than two percent of workplaces matched the
Scandinavian model of group delegation (high-intensity delegation + qualified workforce + high training
intensity) even though it was judged to be more successful than the Toyota model (low-intensity delegation +medium or low employee skills + low training intensity).

2.2.2. Employment Relation Theory

A theoretical merge between the Human resource management and the Industrial Relation approach hastaken place in the Employment Relation Theories. (Gallie et al., 1998) The role of unions and collective
interests is a core aspect of the relation between employer and employee at firm level, and especially insituations of organizational change or restructuring of the employment relationship.
Employment relation theory states that the main challenges of new employment relations since the eighties
6are four: First, a rapid development of new information and communication technology (ICT) leads to atransformation of work toward up-skilling than deskilling; more towards increased responsibility than control.
Second, industrial relations shift from sectoral level to firm level with human resource management perspective.
Third, employment contract is more flexible and fragmented: growth in non-standard work contracts such as
temporary work, self employment and part-time work. Fourth, job security decreases as result of downsizing,outsourcing and structural changes. Employment relation theory thus examines the employment relationship in
the context of these changing external and internal environments and establishes a framework which includes
the employee focused Industrial relations and the employer focused HRM analytically at firm level,incorporating the interests of the firm‟s stakeholders.
The upcoming of human resource management and employment relation theories means growing priority
to developing work organizational frames supporting involvement, responsibilities and continuous competencedevelopment of the individual employee as well as groups of employees in the firm.

3. Hypotheses
3.1. Hypothesis 1. Various Types of CIS in Korea

3.1.1. Hypothesis 1-1 Institutional Complementarities Hypothesis

All the literature based on IS approach has emphasized institutional complementarities, but much of theresearch has failed to demonstrate them. Institutional complementarities have been largely assumed or statedrather than demonstrated. Establishing the CIS Model in Korea, two kinds of institutional complementarities are
considered. The main institutional complementarities are between direct participation and indirect participationof employees in innovation activities; and the subordinate institutional complementarities are between
direct/indirect participation and motivation/VET system.
The interdependence between indirect participation and direct participation has been investigated in somestudies: In this context, indirect participation means the participation through employee representatives such aslabor union; and direct participation means the participation through work system without passing by employee
representatives.
Utilizing British Workplace Employment Relations Survey data, Sisson (1993) showed that individual newwork practices do occur more frequently in organizations with a union presence. EPOC survey (1997), with dataof 10 EU countries, concluded that workplaces which had no participative culture were significantly
outperformed by workplaces which had direct or representative participation. On the basis of the EPOC survey,
the OECD (1999) concluded that one of the main factors being linked to a greater application of highinvolvement working practices within countries is an industrial relations system which facilitates negotiations
and cooperation between managers and employees. Black and Lynch (2000) reported that employee voice andinvolvement has a larger positive effect on productivity when it is done in the context of unionizedestablishments. Bidge (2002) concluded that a specific type of works council, namely one which is frequently
asked to play a strong cooperative role in organizational or technological changes, has a positive effect on the7innovation performance. Nielson & Lundvall (2006) insisted that while indirect forms of participation becomeless frequent in Danish firm, they seem to remain important in learning organizations. However, rare empiricalstudies have quantitatively demonstrated the complementarities between indirect and direct participation.
Subordinate institutions such as motivation system and VET system are also important components. Welldesigned motivation system and VET system enforces employees to involve in innovation activities.
Motivation theory sheds light on the institutional complementarities in the IS approach. McClelland (1961)
classified needs, and treated affiliation, power and achievement. Herzberg (1968) tried to build motivation in theorganization design by job enrichment and job enlargement. Hackman and Oldham (1980) linked job
characteristics such as skill variety, task significance, autonomy and feedback to responsibility and knowledgeof results, which together gives high internal work motivation. In Vroom‟s expectation theory, motivation is afunction of each employee‟s expectation that her behavior will result in outcomes of high individual value.
Pinnington and Edwards (2000) insisted that work should be designed in such a way that high performance leads
to outcomes desired by the employees. Monetary reward or compensation systems are an important part ofmotivation theory.
In the case of VET system, there is a general academic consent on the importance of vocational training.
VET system is considered as an institution for improving employability and mobility as well as firms‟
performance, and it plays a key role in the transfer of those knowledge, skills and competencies.
We assume that high-involvement institutions such as work system, motivation system, VET system, andlabor relations are considerably interacting and interdependent with each other, so we derive the institutional
complementarities hypothesis as follow.

Hypothesis 1-1 (Institutional Complementarities Hypothesis) Well designed high-involvement work
system makes employees to involve in innovation activities; well designed motivation system and VET system
deepens and widens the involvement of employees; and well designed cooperative labor relations guarantee
these systems to operate well. Meanwhile, a workplace without high-involvement work system has no welldesigned motivation system or VET system, and cooperative labor relations does not been established.

3.1.2. Hypothesis 1-2 Relatively Autonomous R&D Hypothesis

Vast majority of empirical research based on IS approach has focused on R&D activities, but less attention
has been paid on the activities related to learning by doing, using, and interacting. Of course, R&D activities are
one of the main factors in the innovation system. R&D activities are not only a learning process but also an
activity of competence building. Through R&D activities, a firm accumulates its structural capability toinnovation, and employees also improve their competence participating in the R&D activities. However, R&D
activity is not the only factor of innovation system. A firm can create innovations without R&D activity, and canaccumulate its competence without R&D activity. A well designed work system guarantees continuousinteraction among employees, consumers, suppliers, and other actors related to innovation activities. This
constant learning process improves the competence of a firm and employees; thus creates innovation without
R&D activities. The CIS Model in Korea contains not only R&D activities but also institutions that support8

learning process and competence building.
But two activities have fundamentally different characteristics. The activities of learning by
doing/using/interacting may be deeply correlated with high-involvement institutions such as work system,
motivation system, VET system, and labor relations. Without these institutions, the activities of learning by
doing/using/interacting may be realized. That is to say, these institutions are considerably interacting andinterdependent each other. In contrast, R&D activities are not so deeply correlated with these institutions. Even
though R&D activities may be pursued on the basis of institutional environment, but rarely limited by it. R&D
activities recall Schumpeter‟s entrepreneurship in the sense that these are energetic activities going beyond theinstitutional constraints. In other words, R&D activities are relatively autonomous from institutions such as
work system, motivation system, VET system, and labor relations. It means that, if we see from other angle,
there exists a workplace engaging in R&D activities without establishing well designed high-involvement
institutions; or a workplace establishing well designed high-involvement without engaging in R&D activities.
This idea constitutes hypothesis 1-2.

Hypothesis 1-2 (Relatively Autonomous R&D Hypothesis) Even though R&D activities are influenced
by institutional environment, these activity are less restricted by institutions such as work system, motivation
system, VET system, and labor relations. In other words, there exists a workplace that engages in R&D
investment without establishing innovation-related institutions; or a workplace that have highly developed
innovation-related institution without R&D investment.

If hypothesis 1-1 and 1-2 are true, the strategy engaging in R&D activities may be relatively simple in thesense that this strategy is not limited by other institutions; but the strategy establishing well designed highinvolvement institutions may be relatively complex and dependent on corporate culture.

3.1.3. Hypothesis 1-3 Learning Economy Hypothesis

Lundvall & Johnson (1994) defines learning economy as a dynamic concept: it involves the capability tolearn and to expand the knowledge base, which refers not only to the importance of the science and technology
systems, but also to the learning implications of the economic structure, the organizational forms and theinstitutional set-up. The learning economy gets firmly established through the combination of widespread ICTtechnologies, flexible specialization and innovation as a crucial means of competition in the new technoeconomic paradigm.
Some studies have investigated the relationship between learning economy hypothesis and forms oforganization. Christensen & Lundvall (1999), with the descriptive statistics of the DISKO (Danish Innovation
System) Data, insisted that increased competition drives firms toward forms of organization that are functionally
flexible with the characteristics of delegation of responsibility, integration of functions, and job rotation.
Laursen (2001) showed that the more knowledge-intensive is the sector, the higher is the outcome engaging in
the application of new HRM practices.
This paper goes further. This paper assumes that market change or uncertainty affects to the determination9

of the types of CIS. A workplace establishing well designed high-involvement institutions is well adapting tomarket change or uncertainty. Therefore,

Hypothesis 1-3 (Learning Economy Hypothesis) A firm facing enormous market change or uncertainty
has more propensity to evolve toward establishing well designed high-involvement institution, thus constituteunique types of CIS. Meanwhile, a firm facing no market change or uncertainty has less motivation to establish
well designed high-involvement institutions.

If hypothesis 1-3 is true, the main strategy of a workplace facing enormous market change of uncertainty
may be to establish well designed high-involvement institutions.

3.1.4. Hypothesis 1-4 Sectoral Dissimilarity Hypothesis

Service sector has fundamentally different characteristics to the manufacturing sector. The first dissimilar
characteristic of service is the absence of outputs that are independent physical entities. In manufacturing there
is no confusion between the process of production and the product. In services, however, the process is often
indistinguishable from the product. Secondly, service involves interrelationship between producer and consumer.
There is no producer without a consumer. Hill (1999) stated that a service must be provided to another economic
unit. Gallouj and Weinstein (1997) emphasized the interactive aspects of services, and suggested that consumers
actively participate in the provision of service, that is, service co-production.
These two characteristics of service sector are somewhat similar to the characteristic of learning by
doing/using/interacting, especially with consumers. From this similarity, we assume that a workplace belonging
to the service sector has different types of innovation system from a workplace belonging to the manufacturingsector, and we induce hypothesis 1-4.

Hypothesis 1-4 (Sectoral Dissimilarity Hypothesis)

In the service sector, a workplace has propensity toestablish well designed high-involvement institutions rather than to engage in R&D activities. Meanwhile, in the
manufacturing sector, a workplace has propensity to engage in R&D activities rather than to establish highinvolvement institutions.

If hypothesis 1-4 is true, the innovation strategy of a workplace belonging to the service sector should be
different from that of a workplace belonging to the manufacturing sector.

3.2. Hypothesis2. Types of CIS and Innovation Performance

3.2.1. Hypothesis 2-1 Performance Ordering Hypothesis

We assume that each firm has its own unique clusters of institutions and activities, so has dissimilarcompetence to create innovation.
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Innumerable studies have demonstrated that a workplace engaging in R&D activities yields high level ofinnovation performance. However, relatively less research has investigated the innovation performance of aworkplace establishing well designed high-involvement institutions.
Among studies on the effect of well designed high-involvement institutions, some studies have examined
the relationship between direct/indirect participation and innovation performance. The result of previous studies
was that indirect participation usually affected to the innovation performance differently from countries tocountries: negative in the USA or Canada, but positive or no effect in Germany or the UK. In trying to explain
this difference, Schnabel and Wagner (1994) pointed to the difference in style; more cooperative labor relationsin Germany may well facilitate innovation. And Friedrich-Ebert Stiftung (1998) stated that indirect participation
could make the following positive contributions to innovation and change: as a communication infrastructure it
simplifies and structures communication between management and personnel; co-determination leads to ahigher quality of decision-making by management, because management has to justify its actions more
systematically; once convinced, the employee representation can help to overcome employee resistance and tobuild trust, even in the case of job losses.
Meanwhile, direct participation is usually positive, from different countries and with different forms ofinnovation performances, and the evidence is becoming more and more convincing. From theses results weassume that the adoption of high-involvement work systems, flanked by new HRM techniques, is correlatedwith high level innovation performance. With regard to innovation, high levels of direct employee participation
can be seen as stimulating in four different ways: forms of direct participation increase the level ofdecentralization, which creates a better and more spacious environment for the discovery and utilization of local,
practical knowledge in the organization; team work or job rotation give workers better insights into the tasks andproblems of other workers, which can lead to a better coordination of innovative activities; group forms of direct
participation bring together knowledge and skills which until then existed separately within the company; direct
participation and its possible effect on the quality of working life might encourage greater effort andcommitment on the part of the workers to perform in ways over and above what is formally and normally
expected. In addition the interaction between direct and indirect participation also showed positive relations withproduct/service innovation and labor productivity. From these results of previous studies we induce hypothesis
2-1.

Hypothesis 2-1 (Performance Ordering Hypothesis) A workplace, engaging in R&D activities withestablishing well designed high-involvement institutions, is correlated with considerably high innovation
performance; a workplace engaging in R&D activities without establishing high-involvement institutions, or aworkplace establishing high-involvement institutions without engaging in R&D activities, are following it; and aworkplace having neither R&D activities nor high-involvement institutions are correlated with considerablypoor performance.

If hypothesis 2-1 is true, we may consider the transformation strategy for the better types of CIS: form the
CIS with low level of performance to the CIS with high level of innovation performance.

113.2.2. Hypothesis 2-2 Dissimilar Innovation Target Hypothesis

Exploring the CIS Model in Korea, we consider two modes of activities: R&D activities and activities
related to learning by doing, using, and interacting. These two modes of activities reflect two types ofknowledge management strategies. These two activities have particular process of learning, competencebuilding, and employee participation; thus deeply interdependent with particular organizations and institutions.
R&D activities are accordant with R&D laboratory, external knowledge network, competent specialists, andamount of R&D expenditure; while learning by doing/using/interacting activities can be conducted with
employee participation and well designed institutions supporting employee participation. For this reason,
innovation performance must reflect these two modes of activities: innovation performance related to R&D
activities; innovation performance related to learning by doing, using, and interacting activities.
From the viewpoint of HRM strategy, engaging in R&D activities is better strategy to an employer who
pursues R&D related innovation; establishing high-involvement institutions is better strategy to an employer
who purposes innovation related to learning bi doing, using, interacting. And from the viewpoint of firm‟scompetence, we assume that a firm establishing R&D laboratory, competent specialists, external knowledge
network, and amount of R&D expenditure, is considerably correlated with R&D-related innovations. A firm,
establishing well designed high-involvement institutions, is considerable correlated with innovation related tolearning by doing, using, interacting. Thus,

Hypothesis 2-2 (Dissimilar Innovation Target Hypothesis) A workplace establishing well designed highinvolvement institutions is advantageous to the innovation related to the activities of learning by
doing/using/interacting. Meanwhile a workplace engaging in R&D activities is strong in the science-technology
innovation.

If hypothesis 2-2 is true, innovation strategy should be different following the innovation target. A
workplace emphasizing employees-leading innovation or product/service innovation should pursue the strategy
establishing well designed high-involvement institution. Meanwhile, a workplace emphasizing patentapplication should pursue the strategy engaging in R&D activities. If we consider hypothesis 2-1 and 2-2
together, the best strategy is to engage in R&D activities with establishing well designed high-involvement
institutions.

Chapter2. Various Types of CIS in Korea
1. Model: A Corporate Innovation System in Korea
1.1. Innovation System based on the Neo-Schumpeterian Tradition

Before establishing a CIS in Korea, defining innovation system is required. Various definitions of12

innovation system have been made by many researchers. Freeman (1987) defined NIS as the network of
institutions in the public and private sectors whose activities and interactions initiate, import, modify and diffuse
new technologies. Nelson and Rosenberg (1993) defined system as a set of institutions whose interactions
determine the innovative performance of national firms. Lundvall (1992) defined NIS as all parts and aspects ofthe economic structure and the institutional set-up affecting, learning as well as searching and exploring: theproduction system, the marketing system and the system of finance present themselves as subsystems in whichlearning takes place. Edquist (1997) defined innovation system as all the important economic, social, political,
organizational, institutional and other factors that influence the development, diffusion and use of innovations,as well as the relations between these factors. Granstrand (2000) defined CIS as the set of actors, activities,
resources and institutions and the causal interrelations that are in some sense important for the innovative
performance of a corporation.
No consents are on the definition of innovation system, but vast majority of researchers approve that an
innovation system, based on the Neo-Schumpeterian tradition, has its unique constituents, function, andactivities. Edquist (2005) states that an innovation system consists of two kinds of constituents: components andrelations among them. Main components are organizations and institutions. Organizations are formal structurethat are consciously created and have an explicit purpose; they are players or actors. Institutions are sets ofcommon habits, norms, routines, established practices, rules, or laws that regulate the relations and interactions
between individuals, groups, and organizations; they are the rules of the game. The specific structure oforganizations and institutions, however, varies among systems.
The main function of Innovation system is to pursue innovation processes such as developing, diffusing,and using innovations; and activities in innovation system are related to that function. Edquist (2005) presents
10 crucial activities: R&D investment; competence building in the labor force such as provision of educationand training, creation of human capital, production and reproduction of skills, and individual learning;articulation of quality requirements emanating from the demand side with regard to new products; creating andchanging organizations needed for the development of new fields of innovation; creating and changing
institutions; networking through markets and other mechanisms, including interactive learning between different
organizations involved in the innovation processes; formation of new product markets; incubating activities;
financing of innovation processes and other activities that facilitate commercialization of knowledge and its
adoption; and provision of consultancy services for innovation processes, e.g. technological transfer,commercial information, and legal advice.

1.2. The Corporate Innovation System in Korea

This paper establishes a corporate innovation system in Korea based on Neo-Schumpeterian tradition.
Employer and employees are the basic actors in a firm, so the two main organizations are the board of
director and a labor union. Employer or the board of director is the agent of R&D investment, and one of themain agents creating/changing organizations and institutions related to competence building, the involvement of
employees in innovation activities, quality management, and the other management activities. Employees orLabor Union is the agent of labor relations, innovation activities such as R&D, quality management,
13competence building, and organizational transformation. In addition, the workplace including R&D laboratory,
production plant, head office and branches functions as a crucial organization, which is also a site of learning
activities.
The main institutions of this CIS are work system, motivation system, VET system, and labor relations.
Two types of work system are assumed in this Model: Well designed high-involvement work system and lessdeveloped work system. Well designed work system makes employees to involve in innovation activities; welldesigned motivation system and VET system deepens and widens the involvement of employees; and highly
developed cooperative labor relations guarantee these systems to operate well. A workplace with this virtuous
circle is considerably correlated with high level of innovative performance. In contrast, a workplace with poorly
designed work system, motivation system, VET system, and labor relations is considerably correlated with lowlevel of innovative performance.
The two main activities of this CIS are R&D activities and competence building. R&D activity, which is not
only a learning process but also an activity of competence building, has been a central activity in IS approach.
Through R&D activity, a firm accumulates its structural capital, and employees participating in the R&D
activity improve their competence. However, R&D activity is not the only activity of competence building. A
firm can accumulate its competence without R&D activity. A well designed work system guarantees continuousinteraction among employees, consumers, suppliers, and other actors related to innovation activities. This
constant learning process improves the competence of a firm and employees. Moreover, the combination of
R&D activity and the other competence building activities may yield spillover effect.
In this Model, R&D activity is treated as an innovation strategy of an employer; which means that, eventhough the activity of R&D investment is influenced by employees‟ reaction, this activity is less restricted byother institutions. Meanwhile, the other activities of competence building are assumed to be deeply correlatedwith other institutions such as work system, motivation system, VET system and labor relations.
Beside the two main activities, this Model includes quality management activities emanating from thedemand side. This activity is a process of interaction with consumers, and the process of communication among
employees to satisfy consumers‟ demand and to track the change of consumers‟ preference. The change ofmarket demand is also explicitly included in the model to investigate the relationship between the types of CIS
and market environments. Lastly, this paper explores the transformation activities for the better types of CIS.
In order to establish a better CIS, we need to consider external knowledge networks with universities,
government research institutes and other agents related to knowledge transfer. For the precise analysis oncompetence building of a firm and employees, external social systems such as labor market, employment
protection law, and unemployment protection law are also needed to be included. The characteristics oftechnological regime—such as technological opportunity, cumulativeness, and uncertainty—also influence on
the innovation activities of a firm and employees. Nevertheless, these factors are not included in this Model.

Figure 2-1 The Corporate Innovation System in This paper

14

2. Data and Variables
2.1. Data

The data used in this paper is the 'Workplace Panel Survey 2005', a sample survey based on workplace
units, provided by Korea Labor Institute. The population of the WPS 2005 includes workplaces with 30 or more
employees, and 1905 workplaces are sampled to represent workplaces in Korea using stratified sampling. The
WPS 2005 contains large amounts of information including work organization, human resource management,compensation and assessment, labor relations, and other labor-related variables. This paper uses 1350
observations, which have financial data provided by Korea Information Service.

2.2. Variables

The choice of variables is based on the IS approach, human resource management theory, work systemdesign, and employment relations theory.

2.2.1. Indicators for Latent Class Analysis

Indicators are dependent variables that are used to define or measure the latent classes in a Latent Class
Cluster Model.
Eight variables are used as indicators for corporate innovation system. Among them, six indicators are for
institutions related to employee participation such as work system, motivation system, VET system, and labor15relations; and the other two indicators are for innovation activities. The corporate innovation system of thispaper is composed of these innovation-related institutions and R&D activities; and the configuration of thoseeight indicators determines the type of the corporate innovation system.
Work system is defined as an institutional device to manage working process in workplace. Threeindicators are used in describing a work system: regular job rotation, enterprise-wide quality management
program, and proposal system. Regular job rotation makes workers perform multiple functions and gain
different types of experience and knowledge. As vitalized as a regular job rotation, more knowledge are diffusedand created in firm‟s level. Through this process, the competence of a firm and employees are improved.
Enterprise-wide quality management program, such as 6-sigma, aims to achieve quality innovation andcustomer satisfaction through minimizing defects in product design, manufacture and service quality. A system
for receiving suggestions connects employees‟ ideas to innovations.
Motivation system is critical in making employees participate in innovation activities with great efforts.
Whether or not the workplace enforces a performance sharing system, which is based on the management
performance at the enterprise or workplace or division level, is used as an indicator. VET system is recognized
as a crucial indicator determines not only worker‟s ability to innovate, but also the possibility of worker‟s
promotion and employment. Manager training, professional skilled personnel training, sales and service
personnel training, site supervisor training, and production worker training constitute a VET system. Labor
relations are the most fundamental factors that guarantee harmonious operation of all these innovation-related
institutions. Whether labor union exists or not is used as an indicator describing labor relations.
The last two indicators are for R&D activities, which contain considerably different characteristics frominnovation-related institutions. R&D activities would be pursued on the basis of institutional environment, butrarely limited by it. Innovation strategies recall Schumpeter‟s entrepreneurship in the sense that these areenergetic activities going beyond the institutional constraints. R&D expenditure is the typical indicator for
innovation strategy. This paper divides R&D into two types: explicit R&D and tacit R&D. Explicit R&D is the
R&D expenditure written on a balance sheet and an income statement; whereas, tacit R&D is written on aschedule of manufacturing cost. In the sense that the R&D expenditure written on a schedule of manufacturing
cost cannot be separated from production activities, tacit R&D may be more correlated with work organizationand the other innovation-related institutions than explicit R&D.

Table 2-1 Indicators for a Corporate Innovation System
Indicators
Work system

Motivation system
VET system
Labor relations
Innovation strategy

Explaining indicators
Regular job rotation
Quality management program
Proposal system
Performance sharing system
Vocational education training system
Labor union
Explicit R&D investment
Tacit R&D investment

2.2.2. Covariates for Latent Class Analysis
16

1=exist (#592), 0=not exist (#758)
1=exist (#645), 0=not exist (#705)
1=exist (#1003),0=not exist (#347)
1=exist (#785), 0=not exist (#565)
1=exist (#1270),0=not exist (#80)
1=exist (#570), 0=not exist (#780)
1=exist (#704), 0=not exist (#646)
1=exist (#239), 0=not exist(#1111)

When we classify types of CIS using latent class analysis, we can control some exogenous variables, suchas sector and firm size. These exogenous variables, which are called as covariates in the latent class analysis, areused to predict or describe the CIS. Controlling these exogenous variables, classification error is reduced.
Sector, firm size, and the trend in market demand are controlled in this paper. We give value 1 if theworkplace belongs to the service sector, 0 if belongs to the manufacturing sector; we give value 1 if theworkplace employs more than 100 workers, 0 if the workplace‟s employees are less than 100; we give value 1 if
the market demand for the workplace‟s main product/service is increasing, 0 if steady or decreasing.

Table 2-2 Covariates for a Corporate Innovation System
Covariates

Explaining covariates

SectorFirm size
Market demand trend

1=Services(#604), 0=Manufacturing(#746)
1=over 100 employees (#922), 0=less 100 employees (#428)
1=increasing, 0=steady or decreasing

3. Statistical Methodology: The Latent Class Cluster Analysis
One of the major challenges for IS approach is to develop analytical techniques studying how different
factors interact in a systemic context. Hypotheses should be formulated on the basis of the IS approach, andthese hypotheses should be tested by using qualitative as well as quantitative observations. The historical andevolutionary perspective of the IS approach assumes that organization, institutions, and their relations aredifferent from system to system; and that diversity is fundamental for the dynamics of the system. In this reason,clustering method such as latent class analysis harmonizes well with the systemic approach of innovation.
Latent class analysis has numerous merits as follows. First, it is based on a statistical model, so the goodness-offit of the model can be measured and tested. Next, latent class analysis can control some exogenous variables
affecting the classification result of the latent variable, which is similar to control some exogenous variables in aregression analysis. These two merits, which are the main differences to the previous methods such as cluster
analysis and factor analysis, enable to build a parsimonious model to analyze the real world. Third, latent classanalysis can treat data that are measured on a nominal, ordinal, count, and continuous measurement scale in a
one model. Last, it is possible to estimate the cluster membership based on the modal probabilities given a firm
has implemented a particular set of practices. The last characteristic is used in the logistic regression analysis
and OLS in the section 4 of this chapter.
The first step of clustering procedure is to divide populations into different sub-clusters with common
characteristics. The next step is to investigate the patterns of interdependency for each cluster, and the last stepis to relate these results to innovation performances.

3.1. Three kinds of Variables in the Latent Class Cluster Analysis

Three kinds of variables are in the Latent class cluster analysis: indicators, covariates, and latent variable.
17

Already mentioned, indicators are dependent variables that are used to define or measure the latent classes in a
Latent class cluster model; and covariates are variables that can be used to describe or predict the latent classes
and used to reduce classification error.
General Latent class cluster model is consists of; a single nominal latent variable x with k classes, 1≤x≤K;
T indicators yit , 1≤t≤T; R covariates zircov affecting x. In this model, all the eight indicators and threecovariates are nominal; valued 1 or 0.

Figure 2-2 The Latent class cluster model in this paper
y1 , y2 , y3 , y4 , y5 , y6 , y7 , y8xz1cov , z2cov , z3cov
Here, the indicator y1 is the enterprise-wide quality management system, y2 is the proposal system, y3
is the regular job rotation, y4 is the VET system, y5 is the labor union, y6 is the performance sharing system,
y7 is the tacit R&D, and y8 is the explicit R&D. Covariates z1cov , z2cov , z3cov are sector, firm size, and the trendof market demand, respectively.

3.2. Two Components of the Latent Class Cluster Analysis

Latent class cluster analysis has two components. First, the assumed probability structure, which defines therelevant set of conditional independence assumptions among the variables in the model. Second, the assumed
distributional forms for the indicators and a latent variable, which will depend on the scale types of the variables
concerned.
First, in this model, the assumed probability structure of each observation i, 1≤ i ≤1350, is,𝐊

𝐟 𝐲𝐢 𝐳𝐢𝐜𝐨𝐯

𝐊

𝐏(𝐱|𝐳𝐢𝐜𝐨𝐯 )𝐟(𝐲𝐢 |𝐱, 𝐳𝐢𝐜𝐨𝐯 ) ==𝐱=𝟏

Here, f yi zicov

𝐇

𝐏(𝐱|𝐳𝐢𝐜𝐨𝐯 )
𝐱=𝟏

𝐟(𝐲𝐢𝐡 |𝐱, 𝐳𝐢𝐜𝐨𝐯 )𝐡=𝟏

is the probability density corresponding to a particular set of yi values given a particular

set of zicov values. P(x|zicov ) is the probability of belonging to a certain latent class given an individual‟srealized covariate values. f(yih |x, zicov ) is the probability density of yih given x and zicov , yih is a set ofindicators.
Here, one point is noteworthy. One of the main assumptions in the latent class cluster analysis is local
independence. Appendix B-2 shows the bivariate residuals for z-y, y-y pairs. If the value of bivariate residuals isover 3.84, we interpret the local independence assumption is unfair. In this paper, eight bivariate residuals were18

over 3.84: performance sharing system-VET system; performance sharing system-labor union; sector-VET
system; sector-performance sharing system; firm size-VET system; firm size-labor union; firm size-explicit
R&D; market demand trend-labor union. Therefore we discarded the local independence assumption in theseeight fairs. In other words, among eight indicators, three indicators—y4 (VET system), y5 (labor union), andy6 (performance sharing system)—constitute one h, and the other five indicators constitute the other five h.
Second, the assumed distributional forms for each indicator yih are a (joint) binomial distribution, because
the each indicator yih is a categorical variable with two categories m; 1 or 0. The (joint) binomial probability
P yih = m x, zi

is parameterized as follows;

P yih = m x, zi = πm |h,x,z i =exp⁡(ηhm |x,z )i( ηhm |x,z )m=1 exp⁡i

Where, linear term with categorical indicators and local dependencies equals
Rηhm |x,z =it∈h{βtm 0 + βtm x0 +ttβtm r × zircov } +
t

r=1

βtt
m m
t∈h,t ∈h,t<tttWhere, βtm t 0 is the intercept, βtm t x0 is the effect of clusters on yit , βtm t r is the direct effect of covariate r
on the indicator concerned, and the term btt
m t m t captures the association between indicators t and t in set h.
And the appropriate indentifying constraint istK
x=1 βx0 = 0,

t
β10
= 0.

In addition, the values on the latent variables given a person‟s covariate values are assumed to come from amultinomial distribution, because x is the single nominal latent variable with k categories. It means that x
yields a standard multinomial logit model. The multinomial probability P(x|zicov ) is parameterized as follows;exp⁡(nx|z i )K(nx |z i )x =1 exp⁡

P x zi = πx|z i =Where, linear term in the multinomial logit model for the latent classes equalsRγxr × zircov

ηx|z i = γxo +r=1

Where, γxo is the intercept parameters, γxr is the slope parameters, and the appropriate indentifying
constraint isK
x=1 γxr = 0,

γ1r = 0.

4. Types of Corporate innovation system: Testing Hypothesis 119

4-1. The Result of Latent Class Cluster Analysis

Before examining the relationship between types of CIS and innovation performance, we first classified
corporate innovation system applying latent class analysis. As can be seen in Table 3-4, four types of CIS was
induced by latent class analysis: R&D type CIS (cluster1), High-involvement + R&D type CIS (cluster2), Highinvolvement type CIS (cluster3), and Low Developed CIS (cluster4). The analysis for the goodness-of-fit of themodel is shown in Appendix B.

Table 2-3 Four Types of Corporate innovation system based on Latent Class Analysis

Types of CIS(Cluster 1)
R&D type
CIS(Cluster 2)
HI+R&D type
CIS

(Cluster 3)
HI type
CIS(Cluster 4)
Low developed
CIS

Total

Cluster Size

#393
(29.11%)#376(27.85%)#309(22.89%)#272(20.15%)#1350(100%)

Variables

z-valuez-valuez-valuez-valuep-val.

Indicators
y1
0.4509***7.8770
0.6595***-5.7044 4.8e-14 0.3769
y2***-5.0358*1.8562***4.0548***-7.8481 1.5e-13 0.3470
y3***-3.8143
0.6198***7.4288***-5.3615 9.6e-16 0.1500-0.38161.1301**2.0603***-4.1496 1.8e-4 0.1009
y4***-4.5030***2.9040***4.7947**-2.0123 2.3e-6 0.1450
y5**-2.0152***4.6932**2.3334***-6.1670 4.7e-15 0.1658
y6***3.1454***5.1763*-1.9030**-2.2349 4.7e-6 0.1335
y7***3.0189***5.0113*-2.2321***-5.9236 4.0e-15 0.1632
y8
Covariates
z1cov**-2.3966***-6.0133***3.0830***4.1151***-4.4730***3.1999*1.6886***-2.7319
z1cov-0.58760.1679**2.4314***-3.2449
z1cov
Note: The indicator y1 is the enterprise-wide quality management system, y2 is the proposal system, y3 is
the regular job rotation, y4 is the VET system, y5 is the labor union, y6 is the performance sharing system,
y7 is the tacit R&D, and y8 is the explicit R&D. Covariates z1cov , z2cov , z3cov are sector(service=1), firmsize(over 100 employees=1), and the trend of market demand(increasing=1)
Note: For each indicator the Wald statistic tests the restriction that each estimate in the set of beta parameter
estimates associated with that indicator equals zero. A non-significant p-value associated with this Wald statisticmeans that the indicator does not discriminate between the clusters in a statistically significant way. Statisticalsignificance at the level of 99%, 95%, and 90% are displayed by ***, **, and *, respectively. Standard errors
and Wald statistics are robust.
indicates how well an indicator is explained by the model.
Note: These log-linear parameters utilize effect coding, which means that for each indicator the estimates sum
to zero over the categories of that indicator (columns). Since effect coding is also used for the clusters, the effectestimates also sum to zero across the clusters (rows).
Table 2-4 Frequency of Sector, Firm Size, Market Demand Trend, Management System, Business Group, Public
sectorCovariates

Cluster 1

Cluster 2

Cluster 3

20

Cluster 4NSectorManufacturing
Services

293 (74.6%)
100 (25.4%)

364 (96.8%)
12 ( 3.2%)

29 ( 9.4%)
280 (90.6%)

60 (22.1%)
212 (77.9%)746 (55.3%)
604 (44.7%)

176 (44.8%)
217 (55.2%)

328 (87.2%)
48 (12.8%)

261 (84.5%)
48 (15.5%)

157 (57.7%)
115 (42.3%)

922 (68.3%)
428 (31.7%)

331 (84.2%)
62 (15.8%)286 (76.1%)
90 (23.9%)

152 (49.2%)
157 (50.8%)

218 (80.1%)
54 (19.9%)987 (73.1%)
363 (26.9%)

43 (10.9%)350 (89.1%)

110 (29.3%)
266 (70.7%)64 (20.7%)245 (79.3%)

20 ( 7.4%)
252 (92.6%)

237 (17.6%)1113(82.4%)

Public sector
Public sector
Private Firm

10 ( 2.5%)383 (97.5%)

21 ( 5.6%)355 (94.4%)

110 (35.6%)
199 (64.4%)27 ( 9.9%)245 (90.1%)

168 (12.4%)1182(87.6%)

Market Demand
Increasing
Not Increasing

187 (47.6%)
206 (52.4%)

180 (47.9%)
196 (52.1%)

207 (67.0%)
102 (33.0%)

107 (39.3%)
165 (60.7%)681 (50.4%)
669 (49.6%)

N. of employees
Over 100
Less 100
Management Sys.
Owner
Professional CEO
Business Group
Yes
No

4.1.1. Cluster1: R&D type CIS

The first cluster is engaging in R&D activities without establishing innovation-related institutions. A
workplace belonging to this cluster is significantly positive with both tacit R&D and explicit R&D in the 99%
significance level. Meanwhile, work systems such as proposal system and regular job rotation are significantly
negative in the 99% significance level; performance sharing is significantly negative, and VET system and labor
union are also negative even though not significant. Considering these characteristics, we identify the firstcluster as the R&D type CIS.
The R&D type CIS encompasses 393 workplaces of 1350 (29.11%). Among them, 293 workplaces (74.6%)
belong to the manufacturing sector, which is significantly higher than the average of the whole sample 55.3%;
and 217 workplaces (55.2%) are employing less than 100, which is significantly higher than the average of thewhole sample 31.7%; 383 workplaces (97.5%) are belong to private sector, which is significantly higher than
the average of the whole sample 87.6%; 43 workplaces (10.9%) are affiliated to the business group, 10
workplaces (2.5%) are public sector, which is lower than the average of the whole sample.

4.1.2. Cluster2: High-involvement + R&D type CIS

The second cluster, which we refer to as the High-involvement + R&D type CIS (hereafter, HI+R&D typeCIS), is characterized by well designed high-involvement institutions and extraordinary rate of R&D investment.
Quality management program, proposal system, performance sharing, and labor union are significantly positive;
and tacit R&D and explicit R&D are also significantly positive. The HI + R&D type CIS may be interpreted tohave a virtuous circles that the aggressive R&D investment strategy is well concordant with these highly
developed institutions.
The HI+R&D type CIS encompasses 376 workplaces of 1350 (27.85%). Among the 376 workplaces, 364
21

workplaces (96.8%) belong to the manufacturing sectors; 328 workplaces (87.2%) are hiring more than 100
employees. Among the 237 workplaces affiliated to the business group, 110 workplaces (46.4%) belong to thistype of CIS, which is higher than the average of the whole sample. Among the 168 workplaces belong to public
sector, 21 workplaces (5.6%) belong to the HI+R&D type CIS.

4.1.3. Cluster3: HI type CIS

The third cluster has highly developed institutions, but the rate of R&D investment is not that high.
Proposal system and regular job rotation are significantly positive in the 99% confidence level; performance
sharing, VET system and labor union are also significantly positive. Meanwhile, the tacit R&D and explicit
R&D are negative in the 90% confidence level. These characteristics are the direct opposite to those of the R&D
type cluster. We identify the second cluster as the High-involvement type CIS (hereafter HI type CIS).
This result may be interpreted that highly developed work system makes employees to involve ininnovation activities; well designed motivation system and VET system deepens and widens the involvement of
employees in innovation activities; and highly developed cooperative labor relations guarantee these work
system and motivation system to operate well. However, a workplace belong to the HI type CIS did not create
the virtuous circle with R&D investment.
Among 309 workplaces belong to HI type CIS, 280 workplaces (90.6%) are service sectors; 261
workplaces (84.5%) are employing more than 100; the market demand trend of 207 workplaces (67.0%) isincreasing; 157 workplaces (50.85) have professional management system, which is considerably higher than
the average rate of 26.9%; 110 workplaces (35.6%) are public sector, which considerable higher than the
average of whole sample.

4.1.4. Cluster4: Low Developed CIS

Lastly, the fourth cluster has neither highly developed institutions nor high rate of R&D investment. All thesix indicators related to the innovation-related institutions are negative and statistically significant, and the two
indicators related to the R&D investment are also significantly negative. These characteristics are the direct
opposite to those of the HI+R&D type cluster. We refer to this cluster as the Low Developed CIS. Among 272
workplaces (20.15%) belonging to the Low Developed CIS, 212 workplaces (77.9%) are in the service sectors;
20 workplaces (7.4%) are non-business-group; the market demand of 165 workplaces in decreasing, which islower than the average of the whole sample 50.4%.

4.2. Testing Hypothesis 1: Various Types of CIS in Korea

This classification result shows that the hypothesis 1-1 (institutional complementarities hypothesis) are true.
Work system, motivation system, VET system, and labor relations are considerably correlated with each other.
A workplace belonging to the HI type CIS and HI+R&D type CIS has well designed high-involvement
institutions simultaneously; while, in the case of a workplace belonging to the R&D type CIS and the low
22developed CIS, all the high-involvement institutions are not developed. Furthermore, the other types of CIS
were not discovered in Korea; for example, a workplace that work system is developed but motivation system orlabor relations was not observed; a workplace that labor relations and motivation system are developed but work
system was not observed.
Of course, this correlation does not directly mean the interaction or interdependence. However, thestatistical methodology of this paper, i.e., latent class cluster analysis, is more inclusive of interdependence andinteraction than the other statistical methodology such as regression model. Using latent class analysis, we
induced four types of CIS on the basis of innovation-related indicators with controlling exogenous variables. It
means that workplaces having the same characteristics of work system, motivation system, VET system, andlabor relations are assumed to come from the same types of CIS. In other words, workplaces belonging to thesame types of CIS have the same types of institutional clusters.
Furthermore, numerous studies of IS approach, human resource management theory, work system design
theory, and employment relations theory—which are the background of this paper—are showing the interactionof the institutions and organizations both theoretically and empirically. Based on these theories, we mayinterpret the classification results as follows: Well designed high-involvement work system makes employees toinvolve in innovation activities; well designed motivation system and VET system deepens and widens theinvolvement of employees in innovation activities; and highly developed cooperative labor relations guarantee
these systems to operate well. Meanwhile, a workplace without high-involvement work system does not havewell designed motivation system and VET system; so cooperative labor relations does not been established inthis type of workplace.
Table 2-3 also showed that hypothesis 1-2 (relatively autonomous R&D hypothesis) is true. All theindicators related to innovation-related institutions are always appearing simultaneously. Meanwhile, theindicators related to R&D activities and the indicators related to institutions are not always appearing
simultaneously. The HI type CIS has well designed institutions, but not have high level of R&D investment. The
R&D type CIS is engaging in R&D investment without establishing innovation-related institutions. Table 2-5 isthe summary.
From hypothesis 1-1 and 1-2, we conclude that the strategy engaging in R&D activities may be relatively
simple, but the strategy establishing well designed high-involvement institutions may be relatively complex anddependent on corporate culture.

Table 2-3 shows that hypothesis 1-3 (learning economy hypothesis) is somewhat reasonable. A workplacebelonging to the HI type CIS was significantly correlated with magnificent change of market demand, but aworkplace belonging to the HI+R&D type CIS showed no significant relations with market demand trend. A
workplace belonging to the Low Developed CIS was significantly correlated with no change of market demand,
but a workplace belonging to R&D type CIS showed no significant relations with market demand trend. From
hypothesis 1-3, we conclude that the main strategy of a workplace facing enormous market change of
uncertainty is to establish well designed high-involvement institutions.
Table 2-4 shows that hypothesis 1-4 (sectoral dissimilarity hypothesis) is true. Among 746 workplaces
belonging to the manufacturing sector, 657 workplaces (88.1%) were pertained to the R&D type CIS or
23

HI+R&D type CIS. Among 604 workplaces belonging to the service sector, 492 workplaces (81.5%) werepertained to the HI type CIS or Low Developed CIS. From hypothesis 1-4, we conclude that the innovation
strategy of a workplace belonging to the service sector should be different from that of a workplace belonging to
the manufacturing sector.

Chapter3. Types of CIS and Innovation performance
In this chapter, we investigate the relationship between the types of CIS and innovation performance, andtest four hypotheses about this relationship.

1. Variables for Regression Analysis
1.1. Dependent Variables

There has been a serious bias in measuring innovation performance. Measures related to science andtechnology, such as patent application and R&D expenditure, have been well designed and accumulated;meanwhile, measures related to learning by doing/using/interacting have less accumulated. When it comes toindicators of knowledge, there has been a strong bias in favor of explicit knowledge; measures for tacitknowledge are rare. In other viewpoint of competence building, the data about R&D related competencebuilding has been much more accumulated than the data about competence building related to learning by doing,
using, and interacting. This situation contributes to a bias toward promoting science-technology based activities
rather than learning by doing/using/interacting activities; which is the main obstacle in innovation activities.
In this paper, the CIS contains both learning by doing/using/interacting activities and science-technologyrelated activities; so the measure of innovation performance must reflect these two kinds of activities.
The WPS 2005 contains variables about employees-leading innovation and P/S innovation. These variables
reflect employees‟ activities of learning by doing/using/interacting, so we utilize those as dependent variables.
We gave value 1 if the level of innovation among employees at the workplace in 2005 was higher than the
average of the same industry; give 0 if not. We gave value 1 if the degree of innovation in the workplace‟s
products/services in 2005 was higher than the average of the same industry; give 0 if not.
As an indicator for science-technology-related innovation, we utilized patent application, which can beobtained through the Korea Intellectual Property Rights Information Services. We gave value 1 if a firm applieda patent in 2005, gave 0 if not. With the support of these three indicators—employees-leading innovation, P/Sinnovation, and patent application—we can investigate the different effect of learning by doing/using/interacting
activities and R&D activities. In addition, we utilize labor productivity as a dependent variable.

Table 3-1 Dependent Variables for Regression Analysis
Dependent variables

Explaining dependent variables

24

Employees-leading innovation
Product/service innovation
Patent application
Labor productivity

1=over average of that sector (#524), 0= if not (#759)
1=over average of that sector (#669), 0= if not (#636)
1=exist (#376), 0=not exist (#974)
Continuous variable

1.2. Control Variables

We utilized three control variables, which reflect the unique characteristic of Korean firms: Management
system and firm ownership such as business group or not, public sector or not.
Management system is classified into two types: ownership management system and professional
management system. A professional management system is completely independent from the influence of theowner, where ownership and management are completely separate. An ownership management system contains
not only a system where the owner has the authority to make most decisions and directly overseas management
activities, but also a system where much management authority is transferred manager but the owner still retains
over major management decisions. Business group contains a business group with limits on equity investment,
and a business groups with limits on mutual investment and loan guarantee of obligation. In 2005, 54 businessgroups exist in Korea. Lastly, public sector means that the largest shareholder is government or public sector
such as public enterprises, government invested enterprises. Among 1350 samples of the WPS 2005, 168
samples (12.4%) belong to the public sector. The innovation competence of a public sector is different from thatof a private firm, so whether public sector or not should be controlled. Sector, firm size, and market demand
trend was utilized not only as covariates in the latent class analysis, but also as control variables in the
regression analysis. The reason is that these two variables directly affect on innovative performance, and also
indirectly influence through the types of CIS. In addition, capital labor ratio (lnK/L) and intermediate input
labor ratio (lnM/L) are used as control variables when labor productivity and the growth rate of laborproductivity are dependent variables.

Table 3-2 Control Variables for Regression Analysis
Control variables
Management system
Firm ownership
SectorFirm size
Market environment
Capital goods
Intermediate goods

Explaining covariates
Who manages the workplace
Business group or not
Public sector or Private firm
Manufacture-Service sectors
Number of employees
Market demand trend
lnK/L
lnM/L

1=owner(#987),0=professional CEO(#363)
1=biz group (#237), 0=not (#1113)
1=public (#168), 0=private (#1182)
1=Service (#686), 0=Manufacturing (#664)
1=over 100 (#922), 0=less 100 (#428)
1=increasing (#681), 0=not (#669)
Continuous variable
Continuous variable

2. Types of CIS and Innovation Performance: Testing Hypothesis 2-1 and 2-2
2.1. The Result of Regression Analysis

2.1.1. Types of CIS and Employees-leading Innovation25

In order to analyze the relationship between types of CIS and employees-leading innovation, we applied
logistic regression analysis as reported in Table 3-3.

Table 3-3 Logistic Regression Analysis: Types of CIS and Innovation among Employees
Model 1Cluster 1(R&D type)
Cluster 2(HI+R&D)
Cluster 3(HI type)
Sector2

Odds ratio(z-value)
1.9651***(3.50)
5.0905***(8.54)
5.0716***(8.14)

Coef(dy/dx)(z-value)
0.1641***(3.51)
0.3854***(9.43)
0.3848***(9.13)

Employees2
Market demand
trendManagement
System2.
Biz_Group2

Model 2
Odds ratio(z-value)
2.8054***(4.74)
9.1453***(8.53)
4.6784***(7.45)
1.9637***(3.57)
0.9715(-0.20)1.2367*(1.74)

Coef(dy/dx)(z-value)
0.2495***(4.86)
0.5028***(10.47)
0.3677***(8.22)
0.1600***(3.64)-0.0069(-0.20)0.0507*(1.75)

Public sector2
Wald
Pseudonumber

106.87 (0.0000)
0.06801283

119.77 (0.0000)
0.0771
1283

Model 3
Odds ratio(z-value)2.6484***(4.48)
7.9563***(7.94)
4.2054***(6.74)
1.7832***(3.06)
0.9009(-0.72)
1.2146(1.56)
0.5601***(-3.90)
1.3801**(2.05)
0.8125(-0.96)

Coef(dy/dx)(z-value)
0.2358***(4.56)
0.4765***(9.46)
0.3444***(7.31)
0.1374***(3.10)-0.0250(-0.71)
0.0464(1.56)-0.1410***(-3.88)
0.0783**(2.03)-0.0487(-0.98)135.45 (0.0000)
0.0892
1283

Note: The cluster 1, 2, 3, and 4 means the R&D type CIS, the HI+R&D type CIS, the HI type CIS, and the
Low Developed CIS, respectively. The values in the parentheses are z-value, and the statistical significance atthe level of 99%, 95%, and 90% are indicated by ***, **, and *, respectively. Table 3-4, 3-5, and 3-5 are thesame.
The dependent variable for this analysis is weather or not the firm‟s level of innovation among employees
in 2005 is higher than the average of the same sector. The independent variables in the Model 1 specification arebinary variables indicating whether or not the workplace belongs to a particular cluster: 1, 2, 3, or 4. In the
Model 2 specification, we include control variables to account for the effect of sector, firm size, and market
demand trend. Then, additional three control variables—types of management system, types of firm ownership(whether it is a business group or not, and whether it is a public sector or private firm)—are added in the Model
3.
Using the cluster4 as benchmark, the Model 1 shows that the probabilities of employees-leading innovationin the cluster 2 and the cluster 3 are more than five times as high, while the probability in the cluster 3 is slightly
less than twice as high; and their odds ratios are statistically significant in the 99% confidence level.
When we add the control variables to account for the effects of sector, firm size, and market demand trend(Model 2), the probabilities of employees-leading innovation of the cluster 1 and the cluster 2 increased, while26

that of the cluster 3 was slightly decreased. After controlling, the gap of employees-leading innovation was
manifest: the HI+R&D type CIS (Cluster2) was considerably high, the HI type CIS (Cluster3) was the second,the R&D type CIS (Cluster1) was the third.
The reason of this change is due to the effect of sector and market demand trend. As can be seen in the
Model 2 specification, the odds ratios of sector and market demand trend are 1.9637 and 1.2367; that is to say,the probability of employees-leading innovation is significantly higher in the service sector and when the market
demand is increasing. The cluster 3, which is almost consist of service sector (96.4%) and the market demand isincreasing (67.05), was overestimated in the Model 1; meanwhile, the cluster 1 and the cluster 2, which has highpercentage of manufacturing sector (66.9% and 96.0%, respectively), were underestimated.
The effect of sector and market demand trend is noteworthy. Service sector was positively correlated with
employees-leading innovation. This result accords with the idea that an employee working at the service site isclosely interacting with users, and these interactions encourage employees to make more innovations. In
addition, as intense as the change or uncertainty of the market, more employees-leading innovation was created.
When three additional control variables was included (Model 3), the effect of CIS type on employeesleading innovation was almost indifferent to the Model 2. The odds ratio of the cluster 1, the cluster 2, and thecluster 3 was 2.6484, 7.9563, and 4.2054, respectively.
A workplace with professional ownership system showed high level of employees-leading innovation, so
did a workplace affiliated to a business group. Public sector showed somewhat low performance, but notsignificant.
An odds ratio has a tendency to overestimate the difference between basis cluster and other clusters. Hence,
we also represented coefficient (dy/dx), which is for discrete change of dummy variable from 0 to 1. In Model 3,
the coefficients of the cluster1, the cluster2, and the cluster3 are 0.2358, 0.4764, and 0.3444, respectively;
coefficient shows exactly equal trend to odds ratio.

2.1.2. Types of CIS and Product/Service Innovation

Table 3-4 Logistic Regression Analysis: Types of CIS and Product/Service Innovation
Model 1Cluster 1(R&D type)
Cluster 2(HI+R&D)
Cluster 3(HI type)
Sector2
Employees2
Market demand
trendManagement
System2.

Odds ratio(z-value)
1.5268**(2.58)
2.7114***(5.97)
2.4816***(5.17)

Coef(dy/dx)(z-value)
0.1049**(2.61)0.2403***(6.38)
0.2185***(5.54)

Model 2
Odds ratio(z-value)
1.6462**(2.57)
3.3248***(5.11)
2.4213***(4.84)
1.2182(1.11)
0.8470(-1.25)
1.2479*(1.93)27

Coef(dy/dx)(z-value)
0.1233**(2.61)
0.2853***(5.61)
0.2130***(5.17)
0.0493(1.11)-0.0414(-1.25)0.0553*(1.93)Model 3
Odds ratio(z-value)1.5649**(2.29)2.9037***(4.46)
2.2266***(4.20)
1.1451(0.75)
0.7987*(-1.66)
1.2398*(1.84)0.7621*(-1.93)

Coef(dy/dx)(z-value)
0.1109**(2.32)
0.2555***(4.81)
0.1939***(4.43)
0.0338(0.75)-0.0560*(-1.67)
0.0537*(1.85)-0.0676*(-1.94)

Biz_Group2

1.5558***(2.85)
0.8924(-0.56)

Public sector2
Wald
Pseudonumber

45.28 (0.0000)
0.02581305

50.71 (0.0000)
0.02941305

0.1090***(2.91)-0.0284(-0.56)62.41 (0.0000)
0.03651305

Table 3-4 shows the relationship between types of CIS and P/S innovation. The dependent variable isweather or not the firm‟s degree of P/S innovation in 2005 was higher than the average of the same sector.
Using the cluster4 as benchmark, the Model 1 shows that the probabilities of P/S innovation of the cluster1, thecluster2, and the cluster3 were 1.5 times, 2.7 times, and 2.5 times higher than that of the cluster4; and thedifferences of those three clusters from the benchmark cluster were statistically significant. The results of theModel 2 and the Model 3 were almost similar to that of the Model 1.
When P/S innovation was used as a dependent variable, the effect of sector disappeared. The effect ofmarket demand trend, management system, business group, and public sector was same as the case whenemployees-leading innovation was used as a dependent variable. Firm size was significantly negative at the 90%
confidence level.

2.1.3. Types of CIS and Patent Application

Table 3-5 Logistic Regression Analysis: Types of CIS and Patent Application
Model 1Cluster 1(R&D type)
Cluster 2(HI+R&D)
Cluster 3(HI type)
Sector2

Odds ratio(z-value)
4.9461***(5.93)
17.8514***(10.87)
2.4681***(3.10)

Coef(dy/dx)(z-value)
0.3275***(5.89)
0.5906***(13.34)
0.1821***(2.91)

Employees2
Market demand
trendManagement
System2.
Biz_Group2

Model 2
Odds ratio(z-value)
6.9850***(6.44)
17.8347***(8.56)
1.9150**(2.20)
1.2790(1.15)
3.2911***(6.66)
1.0114(0.08)

Coef(dy/dx)(z-value)
0.3931***(6.46)
0.5832***(10.03)
0.1253**(2.07)0.0428(1.16)
0.1830***(7.74)
0.0020(0.08)

Public sector2
Wald
Pseudonumber

195.67 (0.0000)
0.14931350

225.37 (0.0000)
0.18151350
28

Model 3
Odds ratio(z-value)
6.2372***(6.00)
13.7158***(7.53)
1.7748*(1.83)
1.1747(0.73)
2.9564***(5.98)
1.0649(0.43)
0.9633(-0.21)
4.3352***(8.25)
0.4750**(-2.46)

Coef(dy/dx)(z-value)
0.3626***(5.86)
0.5281***(8.15)
0.1054*(1.72)0.0272(0.73)
0.1634***(6.81)
0.0106(0.43)-0.0063(-0.20)0.3042***(7.36)-0.1064***(-3.00)

276.30 (0.0000)
0.23341350

Table 3-5 provides the relationship between types of CIS and patent application, which is considered as theresult of science and technological activities. The dependent variable is weather or not the firm applied a patentin 2005. Using the cluster 4 as benchmark, the Model 1 specification illustrates that the probabilities of patentapplication in the cluster 2 was almost 18 times as high; the cluster 1 was almost 5 times as high, the cluster 3
was about 2.5 times as high. And all the differences are statistically significant.
In the Model 2, the odds ratios of the cluster 1, the cluster 2, and the cluster 3 were 6.9850, 17.8347, and1.9150, respectively. The odds ratio of the cluster 1 increased, while that of cluster 3 decreased after controllingthe effect of firm size and sector. The bigger the workplace, the higher was the possibility of patent application.
And, market demand trend showed no correlations with patent application.
After controlling the effect of business group and public sector (Model 3), each odds ratio of the cluster 1,
2, and 3 is 3, 6.2372, 13.7158, and 1.7748, respectively. Business group was significantly positive to the patentapplication; meanwhile, public sector was significantly negative. This result may be interpreted that large
business group is usually investing in R&D activity and patent application based on long-term strategy, notbased on short-term marketing strategy.

2.1.4. Types of CIS and Labor Productivity

Table 3-6 OLS: Types of CIS and Labor Productivity

Dependent

Model 1Model 2Model 3Model 4Model 5Model 6lnTS/L(t-value)lnTS/L(t-value)lnTS/L(t-value)lnVA/L(t-value)lnVA/L(t-value)lnVA/L(t-value)

Cluster 1(R&D type)
Cluster 2(HI+R&D)
Cluster 3(HI type)

0.0152(0.36)
0.0170(0.41)-0.0604(-1.19)0.1147***(2.84)
0.1781***(3.90)-0.0519(-0.96)

0.1084***(2.69)
0.1790***(3.91)
0.0014(0.03)

0.0152(0.364)0.017(0.414)-0.060(-1.193)0.115***(2.844)
0.178***(3.901)-0.0519(-0.964)0.108***(2.694)
0.179***(3.913)
0.0014(0.026)

lnK/L

0.0776***(6.12)
0.7875***(39.95)

0.0818***(6.33)
0.7810***(38.93)

0.0831***(6.55)
0.7726***(37.63)

0.0776***(6.121)
0.787***(39.95)

0.0818***(6.325)
0.781***(38.93)

0.0831***(6.552)
0.773***(37.63)

0.1725***(5.24)-0.0349(-1.11)-0.0412(-1.62)0.1914***(5.80)-0.0287(-0.92)-0.0266(-1.08)0.173***(5.239)-0.0349(-1.107)-0.0412(-1.619)0.191***(5.796)-0.0287(-0.917)-0.0266(-1.085)

lnM/L
Sector2
Employees2
Market demand
trendManagement
System2.
Biz_Group2
Public sector2

0.0449(1.41)
0.0604**(2.07)-0.1945***(-3.59)
29

0.0449(1.407)0.0604**(2.071)-0.195***(-3.586)

ConstantF-valuenumber

2.2034***(12.83)

2.1208***(12.81)

2.2120***(12.14)

2.203***(12.83)

2.121***(12.81)

2.162***(12.14)

1440.45(0.0000)
0.9256
1266

1206.97(0.0000)
0.92681266

1036.89(0.0000)
0.92871266

233.61(0.0000)
0.55571188

162.45(0.0000)
0.56631188

132.88(0.0000)
0.57771188

In order to analyze the relationship between types of CIS and labor productivity, we applied OLS because
we have only cross-section data. Table 3-3 shows the result. The dependent variable of the first three Models,from 1 to 3, is a labor productivity measured by total sales, while the dependent variable of the last three Models,from 4 to 6, is a labor productivity estimated with value-added.
The Model 1 without control illustrates that all the three clusters was not significant to the laborproductivity. When we introduce control variables of sector, firm size, and market demand trend (Model 2), thecluster 1 and the cluster 2 was significantly correlated to the labor productivity at the 99 percent confidence
level; and the coefficient of the cluster 1 and the cluster 2 was 0.1147 and 0.1781, respectively. The reason isthat the cluster 1 and the cluster2, which has high percentage of manufacturing sector, was underestimated in the
Model 1. Those significant correlations of the cluster 1 and the cluster 2 were remained in the Model 3.

2.2. Testing Hypothesis 2-1 and 2-2

Table 3-7 shows the relationship between types of CIS and the five dependent variables—employeesleading innovation, P/S innovation, patent application, labor productivity measured by total sales, and laborproductivity estimated with value-added.

Table 3-7 Results of Regression Analyses with Five Dependent Variables (Summary)
EmployeesP/S Innovation
PatentLabor
Labor
leading
Application
Productivity with Productivity with
Innovation
Sales
VA
Cluster 1
Odds ratio***2.6484**1.5649***6.2372
Coefficient)***0.2345**0.1109***0.3626***0.1084***0.1080
Cluster 2
Odds ratio***7.9563***2.9037***13.7158
Coefficient***0.4765***0.2555***0.5281***0.1790***0.1790
Cluster 3
Odds ratio***4.2054***2.2266*1.7748
Coefficient***0.3444***0.1939*0.10540.00140.0014
Note: Cluster 1, 2, and 3 are the R&D type CIS, HI+R&D type CIS, and HI type CIS, respectively.
Table 3-7 supports the hypothesis 2-1 (performance ordering hypothesis). When we utilize employeesleading innovation, P/S innovation, and patent application as dependent variables, the performances of the HI
type CIS or the R&D type CIS is higher than that of the Low Developed CIS; furthermore, the HI+R&D typeCIS yields considerably higher performance than the HI types CIS or the R&D type CIS.
When labor productivity was used as a dependent variable, the performance of the R&D type CIS and30

HI+R&D type CIS showed the same patterns; but the performance of the HI type CIS was not significantly
higher than that of the Low Developed CIS. As mentioned previous section, labor productivity has some limits
as an indicator for innovation performance; so we may interpret that the hypothesis 2.a. is true.
Table 3-7 provides the manifest evidence that hypothesis 2-2 (various purpose of innovation hypothesis) istrue. When employees-leading innovation or P/S quality was used as dependent variable, the performance of the
HI type CIS was higher than that of the R&D type CIS; however, when patent application was used as
dependent variable, the performance of the R&D type CIS was higher than that of the HI type CIS. This result is,some extent, correspond to the idea that patent application is highly correlated with explicit knowledge, andR&D investment is also correlated with explicit knowledge.

Chapter4. Transformation Strategy for the Better Types of CIS: Focus on ICT Service
Sector in Korea
1. ICT-related Service and Manufacturing Sector in Korea
1.1. ICT Service Sector

In this paper, ICT service sector contains post and telecommunications (industry code 64), computer andrelated activities (industry code 72), research development (industry code 73), and professional, scientific andtechnical services (industry code 74).
This boundary is somewhat broader than the usual definition of ICT-related service. Two reasons: First,
WPS 2005 contains just two-digit industry code, so we cannot exclude the postal service from two-digit code of64; cannot exclude the research and experimental development on social sciences and humanities from two-digit
code of 73; cannot exclude the legal services from two-digit code of 74. Second, one of the main purposes ofthis paper is to investigate the configuration of R&D activities and innovation related institutions; in other words,
we cannot exclude R&D activities from our analysis, so we adopted this broad boundary. Post andtelecommunications contains postal services and couriers (641) and telecommunications (642). Computer andrelated activities contains computer system design and consultancy (721), software consultancy and supply(722), data processing and computer facilities management services (722), database activities and on-line
information provision services (724), and other computer activities (729). Research and Development contains
research and experimental development on natural sciences and engineering (731) and research andexperimental development on social sciences and humanities (732). Professional, scientific and technicalservices contains legal, accounting and tax preparation services (741), market research and management
consulting services (742), architectural, engineering services (743), scientific and technical services (744),
advertising (745), specialized design services (746), and other professional, scientific and technical services(749).

Table 4-1 ICT service sector
31

ICT-related
Manufacturing/Service Sectors

R&D type
CIS (C1)

HI+R&D
type CIS(C2)

HI typeCIS (C3)Low
Developed
CIS (C4)

Total

Post and Telecommunications (64)

7

3

13

4

27

Computer andRelated Activities (72)
Research andDevelopment (73)Professional, Scientific and Technical
Services (74)

23

17

8

48

2

25

6

37

2

15

12

44

30
(19.2%)

156(100%)

4
15

49
7
70
(31.4%)(4.5%)(44.9%)
Note: The number in the parentheses is the two-digit industry code.
Total

Table 4-1 shows the number of workplaces belonging to the CISs with specific ICT service sectors, which
follows the 8th revision of the Korea Standard Industrial Classification in 2000. Among 604 workplaces belong
to the service sectors, ICT-related workplaces are 156. A workplace belongs to the R&D type CIS, HI+R&D
type CIS, the HI type CIS, and the Low Developed CIS is 49 (31.4%), 7 (4.5%), 70 (44.9%), and 30 (19.2%),
respectively.
The main point to notice is that the HI type CIS and the R&D type CIS was well developed in the ICT
service sector, but not well developed HI+R&D type CIS. One question is arising. The HI type CIS maytransform to the HI+R&D type CIS with engaging in R&D activities, but not realized in reality. The R&D typeCIS may transform to the HI+R&D type CIS with establishing well designed institutions, but not realized inreality. The main purpose of this chapter is to investigate the reason: What obstructs the transformation of CIS
toward the better types of CIS?

1.2. The Other Service Sector

Table 4-2 Other Service Sector
Service Sectors

R&D type
CIS (C1)

HI+R&D
type CIS(C2)

HI typeCIS (C3)Low
Developed
CIS (C4)

Total

Wholesale and Retail Trade (50~52)

20

3

50

35

108

Hotels and Restaurants (55)

4

0

15

7

26

Transport(60~63)Financial Institutions and Insurance(65~67)

7

1

31

49

88

0

49

20

72

Real Estate Activities (70)

1

0

7

5

13

Business Support Services (75)

5

1

12

26

44

Public Administration and Defense (76)

0

0

9

0

9

Education (80)

2

0

4

3

9

Health and Social Work (85~86)

1

0

12

17

30

3

32

Recreational, Cultural and Sporting
Activities (87~88)
Other Community, Repair/Personal
Service Activities (90~93)

3
5

0

11

14

28

0

10

6

21

210
(46.9%)

182(40.6%)

448(100%)

515(11.4%)(1.1%)
Note: The number in the parentheses is the two-digit industry code.
Total

Table 4-2 illustrates the number of workplaces belonging to the CISs with the other service sectors. Among
448 workplaces, a workplace belongs to the R&D type CIS, HI+R&D type CIS, the HI type CIS, and the Low
Developed CIS is 51 (11.4%), 5 (1.1%), 210 (46.9%), and 182 (40.6%), respectively.
The main dissimilarity of the two sub-service sectors is the percentage of the R&D type CIS: 31.4% vs.
11.4%; and the percentage of the Low Developed CIS: 19.2% vs. 40.6%. In Korea, a workplace belongs to the
ICT service sector is more engaging in R&D activities than a workplace belong to the other service sector. The
percentage belongs to the HI type CIS is almost the same: 44.9% vs. 46.9%.

1.3. ICT-related Manufacturing Sector

In this paper, the boundary of the ICT-related manufacturing sector is the two-digit industry code 32: The
manufacture of electronic, components, radio, television and communication equipment and apparatuses. It
contains manufacture of semiconductor and other electronic components (321), manufacture of television andradio transmitters and apparatuses for line telephony and line telegraphy (322), and manufacture of televisionand radio receivers, sound or video recording or reproducing apparatuses, and related goods.
Among 96 workplaces pertain to the industry code 32, a workplace belongs to the R&D type CIS, HI+R&D
type CIS, the HI type CIS, and the Low Developed CIS is 39 (40.6%), 54 (56.3%), 1 (1.0%), and 2 (2.1%),
respectively.

2. Types of CIS and Innovation Performance in the ICT-related Sectors
2.1. The Result of Regression Analysis

2.1.1. Types of CIS and Employees-leading Innovation

Table 4-4 Logistic Regression Analysis: Types of CIS and Employees-leading Innovation

Dependent
Cluster 1(R&D type)
Cluster 2(HI+R&D)
Cluster 3(HI type)

Model 1Model 2Model 3Model 4Model 5Model 6

Employeesleading inno
0.2058(1.48)
0.4562***(3.86)
0.5018***(4.53)

Employeesleading inno
0.2232(1.56)
0.5146***(4.02)
0.4444***(3.61)

Employeesleading inno
0.2126(1.45)
0.5045***(3.83)
0.4428***(3.67)

Employeesleading inno
0.2127(1.46)
0.5042***(3.80)
0.4423***(3.58)

Employeesleading inno
0.1323(0.84)
0.4145**(2.52)
0.4128***(3.24)

Employeesleading inno
0.1315(0.83)
0.4151**(2.52)
0.4140***(3.19)

33

Sector 64
Sector 72
Sector 73
Sector 74

0.1349(0.99)
0.1282(1.02)
0.1445(1.02)
0.0736(0.56)

0.1161(0.85)
0.1194(0.93)
0.1542(0.90)
0.0692(0.51)

0.1158(0.85)
0.1198(0.92)
0.1543(0.90)
0.0693(0.51)

0.0218(0.25)
0.1677**(2.40)0.0114(0.13)
0.1684**(2.41)0.0111(0.13)
0.1684**(2.41)-0.0858(-1.01)0.0122(0.14)-0.0830(-0.64)-0.0857(-1.01)0.0121(0.14)-0.0838(-0.62)0.0023(0.03)

0.0879(0.63)
0.0744(0.57)
0.1267(0.71)
0.0386(0.28)

0.0884(0.63)
0.0731(0.54)
0.1263(0.71)
0.0383(0.28)

Sector 32(dropped)
Employees2
Market demand
trendManagement
System2.
Biz_Group2
Public sector2Labor Union
Tacit R&D
Explicit R&D
Wald χ2

15.14 (0.0000) 33.36 (0.0001) 35.18 (0.0004) 35.19 (0.0008)
0.09110.11740.12130.1213
237
237
237
237

-0.0028(-0.03)0.1762**(2.51)-0.0823(-0.97)0.0021(0.02)-0.0513(-0.37)-0.0020(-0.02)0.1762**(2.51)-0.0824(-0.98)0.0021(0.03)-0.0489(-0.33)-0.0062(-0.07)
0.0943(0.88)
0.0938(1.05)

0.0942(0.88)
0.0933(1.05)
35.94
35.92 (0.0018)(0.0011)0.12680.1268237
237

PseudonumberNote: The values in the parentheses are z-value, and the statistical significance at the level of 99%, 95%, and
90% are indicated by ***, **, and *, respectively.
Note: Sector 64 (Post and telecommunications), Sector 72 (Computer and related activities), Sector 73(Research and development), Sector 74 (Professional, scientific, and technical services), Sector 32 (Manufactureof electronic components, radio, television and communication equipment and apparatuses)
Note: Table 4-5 and 4-6 is the same.
Table 4-4 shows the relationship between CIS type of ICT-related service/manufacturing sector andemployees-leading innovation. Five points are noteworthy about the types of CIS and the direct/indirect effectof R&D activities or labor union.
First, in the Model 6 with ICT-related sample, the coefficient of the cluster 1, the cluster2, and the cluster 3
was 0.1315, 0.4141, and 0.4140, respectively. This result means that the indirect effect of labor union in the
ICT-related sectors was significantly positive to employees-leading innovation. The configuration of labor union
and the other institutions or R&D activities constituted the HI type CIS or HI+R&D type CIS; and these CISs
was significantly correlated with high level of employees-leading innovation.
Second, the indirect effect of R&D activities on employees-leading innovation was somewhat unclear.
When R&D activities configured with well designed institutions, so constituted the HI+R&D type CIS, theindirect effect was significantly positive; but not configured with well designed institutions, so constituted the
R&D type CIS, the indirect effect showed no significant relations even though the coefficient was positive.
34

Third, the performance of the cluster 2 and the cluster 3 showed similar level. The policy implication is that,in the ICT-related sectors, well-designed institutions are significantly positive with employees-leading
innovation, but the configuration with R&D activities shows no significant improvement in employees-leading
innovation.
Fourth, the gap of the performance between the cluster 1 and the cluster 2 is significantly considerable. The
policy implication is that, in the ICT-related sectors, a workplace belonging to the R&D type CIS shows nosignificant relations with employees-leading innovation; but if this workplace establishes well designed
institutions, so constitutes the HI+R&D type CIS, higher level of employees-leading innovation is possible.
Fifth, the direct effect of R&D activities was positive, but not significant; and the direct effect of labor
union was not observed.
Additional point to notice is that the effect of market change or uncertainty was more critical in the ICT
related sectors. In the Model 6 with ICT-related sample, the coefficient of market demand trend was 0.1762 withz-value of 2.51; meanwhile, with the whole 1350 samples, the coefficient was 0.0425 with z-value of 1.40. This
result is concordant with the common idea that the lifecycle of ICT-related product/service is shorter than that of
the other sectors, and this market change or uncertainty encourages ICT related firms to create innovations.

2.1.2. Types of CIS and Product/Service Innovation

Table 4-5 Logistic Regression Analysis: Types of CIS and P/S Innovation

Dependent
Cluster 1(R&D type)
Cluster 2(HI+R&D)
Cluster 3(HI type)
Sector 64
Sector 72
Sector 73
Sector 74

Model 1Model 2Model 3Model 4Model 5Model 6

P/S
Innovation
0.1013(0.94)
0.1114(0.99)
0.2286**(2.16)

P/S
Innovation
0.1168(1.01)
0.2001(1.47)
0.1782(1.50)
0.1682(1.34)
0.0926(0.84)
0.1162(0.85)
0.0919(0.79)

P/S
Innovation
0.0930(0.78)
0.1866(1.34)
0.1930(1.59)
0.1618(1.29)
0.1169(1.05)
0.1677(1.07)
0.1077(0.92)

P/S
Innovation
0.0919(0.77)
0.1891(1.35)
0.1975(1.60)
0.1629(1.30)
0.1137(1.01)
0.1678(1.07)
0.1071(0.91)

P/S
Innovation
0.0995(0.74)
0.2097(1.35)
0.1917(1.53)
0.1628(1.30)
0.1251(1.09)
0.1775(1.16)
0.1151(0.98)

P/S
Innovation
0.0972(0.72)
0.2111(1.35)
0.1957(1.54)
0.1636(1.30)
0.1213(1.04)
0.1773(1.15)
0.1142(0.97)-0.1072(-1.37)0.1729**(2.44)-0.1063(-1.34)0.1734**(2.44)-0.1042(-1.30)0.1729**(2.43)-0.1083(-1.35)0.1697**(2.36)-0.1063(-1.32)0.1692**(2.35)-0.0744(-0.89)-0.0775(-0.89)-0.0751(-0.89)-0.0771(-0.88)-0.0759(-0.90)-0.0758(-0.86)-0.0765(-0.19)-0.0754(-0.86)

Sector 32(dropped)
Employees2
Market demand
trendManagement
System2.
Biz_Group2

35

Public sector2-0.1558(-1.15)

Labor Union-0.1511(-1.09)-0.0167(-0.18)

Tacit R&D

-0.0590(-0.58)0.0085(0.09)

Explicit R&D
Wald χ2
Pseudonumber

-0.1548(-1.13)4.82 (0.1857) 14.61 (0.1022) 17.21 (0.1420) 17.39 (0.1820)
0.01500.04500.05140.0515
239
239
239
239

18.02
(0.2057)
0.0524239-0.1494(-1.05)-0.0172(-0.19)-0.0587(-0.57)0.0102(0.11)
18.20 (0.2523)
0.0526
239

Table 4-5 shows the relationship between CIS type of ICT-related sector and P/S innovation. The first point
to notice is that goodness-of-fit of the Model did not been guaranteed as can be interpreted from the value of
Wald χ2 value. All the six Models with ICT related sample, we could not reject the null hypothesis that all thecoefficients in the Model is zero.
Second, All the coefficients of CISs were not significant. In the model 6 with ICT related sample, thecoefficient of the cluster 1, the cluster 2, and the cluster 3 was 0.0972, 0.2111, and 0.1957, respectively. When
we analyzed with whole 1350 samples, the coefficient of the cluster 1, the cluster 2, and the cluster 3 was
0.0912, 0.2467, and 0.1982, respective. The value of coefficients was almost similar. It means that the decreaseof z-value originated from the reduction of sample size.
Third, nevertheless of this limit, we prudently interpret the indirect effect of R&D activities and labor union.
The performance of the cluster 2 and the cluster 3 showed similar level. The policy implication is that, in the
ICT-related sectors, well-designed institutions are positively correlated with employees-leading innovation eventhough not significant; however, the configuration with R&D activities shows no significant improvement in
employees-leading innovation. In addition, the gap of the performance between the cluster 1 and the cluster 2 issomewhat large. The policy implication is that, in the ICT-related sectors, a workplace belonging to the R&D
type CIS shows no significant relations with employees-leading innovation; but if this workplace establishes
well designed institutions, so constitutes the HI+R&D type CIS, higher level of employees-leading innovation ispossible.
Fourth, the direct effect of R&D activities and labor union was not observed.
Last, the effect of market change or uncertainty was more critical in the ICT related sectors. In the Model 6
with ICT-related sample, the coefficient of market demand trend was 0.1692 with z-value of 2.35; meanwhile,with the whole 1350 samples, the coefficient was 0.0469 with z-value of 1.58.

2.1.3. Types of CIS and Patent Application

Table 4-6 Logistic Regression Analysis: Types of CIS and Patent Application

Dependent

Model 1Model 2Model 3Model 4Model 5Model 6

PatentApplication

PatentApplication

PatentApplication

PatentApplication

PatentApplication

PatentApplication

36

Cluster 1(R&D type)
Cluster 2(HI+R&D)
Cluster 3(HI type)
Sector 64
Sector 72
Sector 73
Sector 74

0.0774(0.72)
0.3589***(3.39)-0.0676(-0.62)0.0895(0.81)
0.2759*(1.89)-0.1094(-1.06)0.2241(1.49)
0.0575(0.47)-0.2469***(-2.91)
0.0615(0.53)

0.1077(0.91)
0.2594*(1.69)-0.0761(-0.59)0.1643(1.03)-0.0144(-0.12)-0.1988*(-1.80)
0.0066(0.06)

0.0912(0.77)
0.2658*(1.78)-0.0554(-0.42)0.1652(1.05)-0.0415(-0.36)-0.2070*(-1.88)-0.0064(-0.06)-0.1958*(-1.83)-0.0480(-0.35)-0.1938*(-1.93)0.0601(0.38)-0.1584*(-1.72)-0.2239**(-2.36)-0.0592(-0.59)-0.1990*(-1.86)-0.0567(-0.40)-0.1945*(-1.93)0.0592(0.38)-0.1603*(-1.74)-0.2259**(-2.41)-0.0612(-0.61)0.3751***(6.95)
0.0333(0.48)

0.3676***(6.72)
0.0370(0.52)

0.3750***(6.98)
0.0335(0.47)

0.3507***(6.58)
0.0249(0.35)

0.3508***(6.58)
0.0259(0.36)

0.0304(0.39)
0.3075***(3.13)-0.1274(-0.99)0.0238(0.30)
0.3117***(3.11)-0.1012(-0.72)-0.1004(-1.33)0.0585(0.76)
0.3123***(3.15)
0.0692(0.36)

0.0582(0.76)
0.3113***(3.13)
0.0683(0.35)-0.1685**(-2.45)
0.0184(0.21)
0.3798***(6.11)

Sector 32(dropped)
Employees2
Market demand
trendManagement
System2.
Biz_Group2
Public sector2Labor Union
Tacit R&D

-0.1691**(-2.48)
0.3795***(6.10)

Explicit R&D
Wald χ2
Pseudonumber

24.24 (0.0000) 40.28 (0.0000) 53.00 (0.0000) 52.24 (0.0000)
0.07840.20610.24640.2510
252
252
252
252

65.69
(0.0000)
0.3233252

65.68 (0.0000)
0.3234
252

Table 4-6 shows the relationship between CIS type of ICT-related sector and patent application. The mostconspicuous result is that the coefficient of the cluster 1, the cluster2, and the cluster 3 was -0.1990 with z-valueof -1.86, -0.0567 with z-value of -0.41, and -0.1945 with z-value of -1.93. This result is remarkably dissimilar tothe case when we utilized employees-leading innovation or P/S innovation. This means that the indirect effect of
R&D activities or labor union is significantly negative.
The second point to notice is that the direct effect of tacit R&D and explicit R&D was adverse. Explicit
R&D was significantly positive at the 99% confidence level, but tacit R&D was significantly negative at the 95%
confidence level. Labor union was also negative, even though not significant.
The implication of this result is that, in the ICT-related sectors, well designed institutions do not helpful topatent application; In addition, explicit R&D is critical to patent application, but not is tacit R&D.
The third point to notice is that firm size was significantly positive to the patent application. As large as afirm, more attach importance to patent application. Meanwhile, market change or uncertainty was not significant.
37

Business group was significantly positive. This result may be interpreted that large business group is usuallyinvesting in R&D activity and patent application based on long-term strategy, not based on short-term marketingstrategy.

2.1.4. Types of CIS and Labor Productivity Measured by Total Sales

Table 4-7 OLS: Types of CIS and Labor Productivity measure by Total Sales

Dependent
Cluster 1(R&D type)
Cluster 2(HI+R&D)
Cluster 3(HI type)
Sector 64

Model 1Model 2Model 3Model 4Model 5Model 6lnTS/LlnTS/LlnTS/LlnTS/LlnTS/LlnTS/L

0.1808*(1.87)0.1884(1.53)
0.0723(0.75)
0.1631(1.57)-0.0340(-0.40)-0.1518(-1.33)0.2570***(2.68)

0.1594(1.62)
0.1796(1.43)
0.1141(1.14)
0.1552(1.55)-0.0032(-0.04)-0.0303(-0.24)0.2713***(2.67)

0.1404(1.40)
0.1858(1.50)
0.1469(1.44)
0.1571(1.56)-0.0213(-0.23)-0.0411(-0.33)0.2714***(2.70)

0.1071(0.93)
0.0616(0.43)
0.1063(1.04)
0.1468(1.50)-0.0414(-0.45)-0.0680(-0.55)0.2298**(2.37)0.0830(0.72)
0.0627(0.44)
0.1378(1.32)
0.1476(1.50)-0.0622(-0.66)-0.0790(-0.65)0.2282**(2.37)

0.0098(0.14)
0.2270(0.43)

0.0218(0.31)
0.0237(0.38)

0.0365(0.49)
0.0187(0.31)

0.0204(0.28)
0.0373(0.58)

0.0344(0.46)
0.0320(0.52)-0.0230(-0.34)-0.0486(-0.61)-0.2243**(-2.11)-0.0280(-0.41)-0.0563(-0.70)-0.1785(-1.63)-0.1422(-1.49)-0.0239(-0.36)-0.0558(-0.72)-0.2210**(-2.12)0.2305***(3.21)
0.0048(0.06)-0.0289(-0.42)-0.0638(-0.83)-0.1728(-1.62)-0.1448(-1.54)0.2330***(3.31)
0.0113(0.15)

82.32(0.0000)
0.9140235

85.28(0.0000)
0.9154235

0.1523*(1.67)0.1526(1.42)
0.0363(0.37)

Sector 72
Sector 73
Sector 74
Sector 32(dropped)
Employees2
Market demand
trendManagement
System2.
Biz_Group2
Public sector2Labor Union
Tacit R&D
Explicit R&D
F-valuenumber188.34(0.0000)
0.9022235

104.77(0.0000)
0.9097235

85.39(0.0000)
0.9114235

86.34(0.0000)
0.9127235

Note: The values in the parentheses are z-value, and the statistical significance at the level of 99%, 95%, and
90% are indicated by ***, **, and *, respectively.
Note: Sector 64 (Post and telecommunications), Sector 72 (Computer and related activities), Sector 73(Research and development), Sector 74 (Professional, scientific, and technical services), Sector 32 (Manufactureof electronic components, radio, television and communication equipment and apparatuses)
Note: lnK/L, lnM/L, constant were not reported.
38

Table 4-7 shows the relationship between CIS type of ICT-related sector and labor productivity measured
by total sales. The first point to notice is that the coefficient of the cluster 1, the cluster2, and the cluster 3 was
0.0830, 0.0627, and 0.1378, respectively. This result means that the indirect effect of labor union in the ICTrelated sectors was positive even though not significant; and indirect effect of R&D activities was also positive
but not significant. What has to be noticed is that the coefficient of the HI+R&D type CIS is smaller than that of
the HI type CIS or R&D type CIS. It means that there is no motivations to transform from the HI type CIS to the
HI+R&D type CIS, and from the R&D type CIS to the HI+R&D type CIS if we do not consider the direct effectof R&D activities.
Second, tacit R&D was significantly positive to the labor productivity at the 99% confidence level, but thedirect effect of explicit R&S was not observed. This is the adverse result comparing to the case of patentapplication. When we used patent application as a dependent variable, explicit R&D activities were significantly
positive, and tacit R&D activities were significantly negative. Meanwhile, if labor productivity was used as adependent variable, tacit R&D activities were more important than explicit R&D activities. Labor union was
negative even though not significant.
The implication of this result is that, considering direct effect and the indirect effect simultaneously, theR&D type CIS has no motivation to transform to the HI+R&D type CIS because both direct effect and indirect
effect of labor union are negative. HI type CIS has some motivation to transform to the HI+R&D CIS withengaging in tacit R&D because the direct effect of tacit R&D is significantly positive even though the indirect
effect is negative.

2.1.5. Types of CIS and Labor Productivity Measured by Value-added

Table 4-8 OLS: Types of CIS and Labor Productivity measure by Value-added

Dependent
Cluster 1(R&D type)
Cluster 2(HI+R&D)
Cluster 3(HI type)
Sector 64
Sector 72
Sector 73
Sector 74

Model 1Model 2Model 3Model 4Model 5Model 6lnVA/LlnVA/LlnVA/LlnVA/LlnVA/LlnVA/L

0.2494(0.87)
0.5403(1.52)-0.2004(-0.64)0.9215***(3.33)
0.3406(1.42)-0.3174(-0.92)
1.0269***(3.94)

0.1710(0.60)
0.4973(1.39)-0.0471(-0.14)0.8674***(3.19)
0.3287(1.32)
0.1370(0.35)
0.9720***(3.53)

0.1482(0.51)
0.5316(1.47)
0.0398(0.12)
0.8883***(3.26)
0.3132(1.28)
0.1066(0.28)
0.9939***(3.62)-0.2581(-0.82)-0.1916(-0.48)-0.1924(-0.56)
0.7710***(2.85)
0.0643(0.25)-0.0132(-0.04)0.7479***(2.98)-0.2953(-0.92)-0.1680(-0.42)-0.0924(-0.27)0.7935***(2.93)
0.0395(0.16)-0.0532(-0.15)0.7684***(3.07)-0.0151(-0.05)-0.0042(-0.01)-0.4101(-1.26)

Sector 32(dropped)

39

Employees2-0.2421(-1.33)0.0807(0.50)

Market demand
trendManagement
System2.
Biz_Group2
Public sector2-0.2224(-1.28)0.0718(0.44)-0.2074(-1.19)0.0814(0.50)-0.2742(-1.59)0.1146(0.71)-0.2576(-1.47)0.1272(0.79)-0.0390(-0.19)0.1613(0.77)-0.7807**(-2.05)-0.0579(-0.28)0.1399(0.67)-0.6908*(-1.70)-0.2980(-1.13)-0.0464(-0.23)0.1411(0.71)-0.6836*(-1.83)-0.0691(-0.34)0.1149(0.58)-0.5749(-1.47)-0.3539(-1.41)0.8865***(4.94)
0.3660*(1.85)

Labor Union
Tacit R&D

0.8638***(4.79)
0.3583*(1.80)

Explicit R&D
F-value
22.57(0.0000)
numberNote: The values in the parentheses are z-value, and the statistical significance at the level of 99%, 95%, and
90% are indicated by ***, **, and *, respectively.
Note: Sector 64 (Post and telecommunications), Sector 72 (Computer and related activities), Sector 73(Research and development), Sector 74 (Professional, scientific, and technical services), Sector 32 (Manufactureof electronic components, radio, television and communication equipment and apparatuses)
Note: lnK/L, lnM/L, constant were not reported.
Table 4-8 shows the relationship between CIS type of ICT-related sector and labor productivity measured
by value-added. The first point to notice is that the coefficient of the cluster 1, the cluster2, and the cluster 3 was-0.2953, -0.1680, and -0.0924. This result means that the indirect effect of labor union or R&D activities in the
ICT-related sectors was negative even though not significant. What has to be noticed is that the coefficient of
the HI+R&D type CIS is smaller than that of the HI type CIS. It means that there is no motivations to transformfrom the HI type CIS to the HI+R&D type CIS.
Second, tacit R&D was significantly positive to the labor productivity at the 99% confidence level, and the
direct effect of explicit R&S was significantly positive at the 90% confidence level. The value of coefficient isnoteworthy. The coefficient of tacit R&D activities and explicit R&D activities is 0.8865 and 0.3660,
respectively. We may conclude that tacit R&D activities are more important than explicit R&D activities forlabor productivity.
The implication of this result is that, considering direct effect and the indirect effect simultaneously, the HI
type CIS has incentive in transforming to the HI+R&D CIS with engaging in tacit R&D because the direct effectof tacit R&D and explicit R&D is significantly positive, even though the transformation effect is somewhat
negative.

2.2. Result and Implications
2.2.1. Transformation Strategy from the HI type CIS to the HI+R&D type CIS
40

Table 4-9 indicates the introduction effect of R&D activities in the case of transforming from the HI type
CIS to the HI+R&D type CIS.

Table 4-9 Transformation from the HI type CIS to the HI+R&D type CIS through Engaging in R&D activities
Indirect
DirectDirectR&D effecttacit R&D effect
explicit R&D effect
Employees-leading
inno.
P/S
Innovation

Coefficient
From 0.4140 (3.19)
0.0943 (0.88)
0.0938 (1.05)(z-value)
To 0.4151 (2.52)
Coefficient
From 0.1957 (1.53)-0.0587 (-0.57)
0.0102 (0.11)(z-value)
To 0.2111 (1.35)
Coefficient
From -0.1945 (-1.93)
Patent Application
0.0184 (0.21)
0.3798 (6.11)(z-value)To -0.0567 (-0.40)
Coefficient
From 0.1378 (1.32)
lnTS/L0.2330 (3.31)
0.0113 (0.15)(t-value)
To 0.0627 (0.44)
Coefficient
From -0.0924 (-0.27)
lnVA/L
0.8865 (4.94)
0.3660 (1.85)(t-value)To -0.1680 (-0.42)
Note: The value of coefficient, z-value, t-value are based on the Model 6 including direct effect of labor union

and R&D activities. lnTS/L means natural logged total sales per employee, and lnVA/L means natural logged
value-added per employee.

A workplace attaching importance to employees-leading innovation may hesitate transforming from the HI
type CIS to the HI+R&D type CIS by engaging in tacit R&D and explicit R&D. The direct effect of tacit R&D
and explicit R&D was positive, but not significant. Furthermore, there was no transformation effect from the HI
type CIS to the HI+R&D type CIS: the coefficient of the HI type CIS was 0.4140, and the coefficient of the
HI+R&D type CIS was 0.4151.
A workplace laying emphasis on P/S innovation may have no motivation to engage in R&D activities. The
direct effect of tacit R&D and explicit R&D was not observed, and the transformation effect from the HI type
CIS to the HI+R&D type CIS showed no improvement in P/S innovation.
A workplace laying weight on patent application may improve its performance with engaging in R&D
activities. The direct effect of explicit R&D was significantly positive, and the indirect effect was also positive:
from -0.1945 to -0.0567. In addition, Engaging in explicit R&D activities is better than engaging in tacit
activities. The direct effect of explicit R&D activities was significantly positive with coefficient of 0.3798.
A workplace attaching importance to labor productivity measured by total sales, may consider the trade-off
between the direct effect and the indirect effect. The direct effect of tacit R&D activities was significantly
positive with coefficient of 0.2330, but the transformation effect is somewhat negative.
A workplace laying emphasis on labor productivity measured by value-added, may consider transformingfrom the HI type CIS to the HI+R&D type CIS by engaging in tacit and explicit R&D activities. The direct
effect of tacit R&D activities and explicit R&D was conspicuously positive with coefficient of 0.8865 and
0.3660. The implication of this result is that, considering direct effect and the indirect effect simultaneously, theHI type CIS has incentive in transforming to the HI+R&D CIS through engaging in tacit R&D. Even though thetransformation effect is somewhat negative, from -0.0924 to -0.1680, the direct positive effect exceeds this41

negative effect.
Among ICT-related 156 workplaces, 70 workplaces (44.9%) are remaining in the HI type CIS. Only sevenworkplaces (4.5%) are belonging to the HI+R&D type CIS. Most of workplaces belonging to the HI type CIS is
hesitating over transformation toward HI+R&D type.
It is plausible to assume that most of workplaces belonging to the HI type CIS may lay emphasis on
employees-leading innovation and P/S innovation. Four reasons of this assumption may be derived. First, theseworkplaces have already well designed institutions suitable for employees-leading innovation and P/Sinnovation. Based on evolutionary approach, an existing firm may be establishing institutions harmonious with
its own purposes. Second, among 301 workplaces belong to HI type CIS, 280 workplaces (90.6%) were service
sectors; in these sectors, interaction with consumers and among employees is critical. Next, 207 workplaces(67.0%) were facing increasing market demand; this market change or uncertainty encourages workplaces tocreate employees-leading innovation and P/S innovation. Lastly, the HI type CIS has already established welldesigned cooperative labor relations. If a workplace really pursue transforming, it would be possible.
From this analysis, we conclude that the unique purpose of each workplace is the main obstacle oftransformation from the HI type CIS to the HI+R&D type CIS.
But if the purpose of a workplace belonging to the HI type CIS is patent application or labor productivity
measured by value-added, transforming to the HI+R&D type CIS with engaging in R&D activities is a goodstrategy.

2.2.2. Transformation Strategy from the R&D type CIS to the HI+R&D type CIS

Table 4-10 illustrates the effect of establishing labor union in the case of transforming from the R&D type CIS
to the HI+R&D type CIS.

Table 4-10 Transformation from the R&D type CIS to the HI+R&D type CIS through Establishing Labor Union
Indirect
DirectLabor Union effectLabor Union effect
Employees-leading
inno.
P/S
Innovation

Coefficient
From 0.1315 (0.83)-0.0062 (-0.07)(z-value)
To 0.4151 (2.52)
Coefficient
From 0.0972 (0.72)-0.0172 (-0.19)(z-value)
To 0.2111 (1.35)
Coefficient
From -0.1990 (-1.86)
Patent Application-0.1685 (-2.45)(z-value)To -0.0567 (-0.40)
Coefficient
From 0.0830 (0.72)
lnTS/L-0.1448 (-1.54)(t-value)
To 0.0627 (0.44)
Coefficient
From -0.2953 (-0.92)
lnVA/L-0.3539 (-1.41)(t-value)
To 0.1680 (-0.42)
Note: The value of coefficient, z-value, t-value are based on the Model 6 including direct effect of labor union
and R&D activities. lnTS/L means natural logged total sales per employee, and lnVA/L means natural logged
value-added per employee.
A workplace attaching importance to employees-leading innovation may improve its performance bytransforming from the R&D type CIS to the HI+R&D type CIS through establishing high-involvement
42institution, especially labor union. We may induce the effect of transformation from coefficient of CISs; thecoefficient of the R&D type CIS was 0.1315, while that of the HI+R&D type CIS was 0.4151. The direct effectof labor union was not observed. The same result was inducted when we used P/S innovation as a dependent
variable.
A workplace laying weight on patent application may reduce the negative effect of CIS type by establishingwell designed institutions: from -0.1990 to -0.0567. The direct effect of labor union, however, was significantly
negative. This trade-off should be considered when a workplace establishes a transformation strategy.
A workplace attaching importance to labor productivity may have no motivation to establish an institution
enhancing employees‟ involvement. No transformation effect was observed, and the direct effect of labor union
was also negative even though not significant.
Among ICT-related 156 workplaces, 49 workplaces (31.4%) are remaining in the R&D type CIS. Only
seven workplaces (4.5%) are belonging to the HI+R&D type CIS. Most of workplaces belonging to the R&D
type CIS is hesitating over transformation toward the HI+R&D type.
It is plausible to assume that a workplace belonging to the ICT related service sector has motivation to
improve its competence for P/S innovation and employees-leading innovation. The reason may come from theunique characteristics of service sectors: interacting with consumers is critical.
As can be seen in the Table 4-9, a workplace belonging in the R&D type CIS can improve its competence
through establishing well designed institutions, but this transformation was not realized. The main hindrance oftransformation may be the difficulty of establishing well designed institutions. A workplace belonging to the
R&D type CIS has no well designed high-involvement work system, well designed motivation system or VET
system. Most of all, it has no highly developed cooperative labor relations, which guarantee these systems tooperate well. Further research is required on creating virtuous circle including both R&D activities and welldesigned institutions.

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Appendix A. The Questionnaire Used in the Survey
Table A The Questionnaire Used in the Survey
In 2005, how did the level of innovation among employees at your workplace compare with the average forcompanies in the same industry? Very low/Low/Similar/High/Very HighIn 2005, how did the degree of innovation in your workplace‟s goods and services compare with the average forcompanies in the same industry? Very low/Low/Similar/High/Very HighIs your workplace implementing an enterprise-wide quality management program such as six-sigma program?
Yes/NoDoes your workplace have a system for receiving suggestions for work improvement from employees?
In your workplace do employees implement regular job rotation to enable workers to perform multiple functions
and gain different types of experiences? Yes/No
In 2005, did your workplace implement or support training for the development of workers‟ job capabilities?
Yes/NoDoes your workplace implement a performance sharing (variable bonus) system based on the management
performance at the enterprise, workplace or division level? Yes/No
Is there a union in your workplace?

Yes/no/Yes, but it is currently inactive

What is the trend in market demand for your workplace‟s main product/service?
increasing/Increasing/steady/declining/rapidly declining
46

RapidlyAppendix B. Analysis for the goodness-of-fit of the model
Table B-1 Summary Statistics from the Latent Class Analysis
Number of
Degree of
BIC(LL)
Latent Class
Freedomp-valueClassification Error

Cluster 211850.269

1322

0.40

0.1035Cluster 311731.343

1310

1.00

0.1449Cluster 411709.694

1298

1.00

0.2002Cluster 511759.204

1286

1.00

0.2166

Cluster 611831.335

1274

1.00

0.2274In order to determine the cluster numbers of the latent variable, we conducted the two-step procedure. The
first step was the standard chi-squared test with the null hypothesis that the specified model holds true in the
population. A p-value associated with a log likelihood (LL) is a formal assessment of the extent to which themodel fits the data; P<0.05 indicates a poor fit. The p-value of the model with two clusters is 0.15, and the pvalues of the model with three clusters, four clusters and five clusters are all 1.00. This result means that all themodels with two clusters, three clusters, four clusters, and five clusters are fit the data. The second step is to
examine the parsimony of the model with Bayesian Information Criteria (BIC). When comparing models, thelower the value of the BIC, the better the model. The model with four clusters is the lowest value, 11709.694.
Table 3-4 in Chapter 3 is the result of the model with four clusters.

Table B-2 Bivariate Residuals
Variables

12

3

1.Quality management program·

2. Proposal system

1.953

3. Regular job rotation

0.022

0.028

4. VET system

0.074

0.031

0.988

5. Performance sharing system

0.403

0.337

1.481

0.000

6. Labor union

0.251

0.354

0.376

0.008

0.000

7. Tacit R&D

0.628

0.880

0.344

0.214

1.202

0.263

8. Explicit R&D

1.551

0.086

2.456

0.005

0.005

0.199

1.294

Sector (Indus2)

0.331

0.012

0.542

0.000

0.000

0.013

0.233

1.248

# of employees (emp2)

0.532

0.020

0.767

0.000

0.128

0.000

1.618

0.000

47

4

5

6

7

8

Market Demand Trend

0.735

0.693

0.359

0.016

0.010

0.000

1.055

3.767

Another indication, which provides a good fit to the data, is to examine whether there are significant residuals
or not. In general, bivariate residuals larger than 3.84 identify correlations between the associated variable pairsthat have not been adequately explained by the model. When bivariate residuals larger than 3.84 are observed,
we can treat it by including direct relationships between indicators and direct effects of covariates on indicators
in a model. We guaranteed the goodness-of-fit of the model by including direct relationships and direct effects
in eight variable pairs: small group activity and explicit R&D, job rotation and explicit R&D, performance
sharing system and VET system, labor union and performance sharing system, sector and VET system, numberof employees and explicit R&D, number of employees and VET system, number of employees and labor union.

48