Int. J. Technology Management, Vol. 28, Nos. 7/8, 2004 667

Copyright © 2004 Inderscience Enterprises Ltd.

Managing knowledge in new product and service development: a new management approach for innovative research organisations

Somchai Numprasertchai Department of Computer Engineering, Faculty of Engineering, Kasetsart University, 50 Phaholyothin Rd. Chatujak, Bangkok 10900, Thailand E-mail: snp@ku.ac.th

Barbara Igel School of Management, Asian Institute of Technology, P.O. Box 4, Klong Luang, Pathumthani 12120, Thailand E-mail: igel@ait.ac.th

Abstract: In developing countries, academic research units are regarded as the main agents that create new knowledge for innovation in commercial products and services. This paper presents a research framework for analysing the role of Knowledge Management (KM) in improving and sustaining research activities in those units that led to important product or service innovation in the local market. KM practices used effectively in the product or service innovation process are illustrated with the case study of a very successful R&D laboratory at Kasetsart University in Bangkok, Thailand. Findings indicate that:

• KM practices are embedded in the innovation process and thus, have a strong impact on the success of research projects.

• A distinguished research idea is most important in achieving outstanding research and commercialisation results.

• Online video conferences and web-based knowledge repository are highly effective tools for capturing, transferring, storing and integrating knowledge among local researchers and external experts from research partners abroad.

Keywords: innovation; technological innovation; knowledge management; knowledge transfer; academic research unit.

Reference to this paper should be made as follows: Numprasertchai, S. and Igel, B. (2004) ‘Managing knowledge in new product and service development: a new management approach for innovative research organisations’, Int. J. Technology Management, Vol. 28, Nos. 7/8, pp.667–684.

Biographical notes: Somchai Numprasertchai is an Assistant Professor in the Computer Engineering Department at Kasetsart University, Thailand and a PhD candidate of the Management of Technology (MOT) Programme at Asian Institute of Technology, Thailand. His fields of interest are knowledge management, computer operating system, and parallel processing and he has published books on these subjects. He is a member of National Research Council of Thailand.

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Barbara Igel is an Associate Professor of Industrial Economics and Management of Technology, and Coordinator of Tech-Ventures in the Management of Technology (MOT) Programme, at the School of Management, Asian Institute of Technology, Thailand. Her research projects deal with the management of innovation in complex technology systems and entrepreneurship development in new, technology-based firms in Asia. She has published several papers in international journals.

1 Introduction

Knowledge is considered one of the important sources of innovation that leads to new product and service development (Nonaka and Takeuchi, 1995; Gurteen, 1998; Johannessen, Olsen and Olaisen, 1999; Kandampully, 2002). Knowledge Management (KM) is the management of information to support productivity and efficiency through steering of strategy; identifying and communicating explicit knowledge and transferring tacit knowledge that resides in processes, people, products and services (Duffy, 2000; De Gooijer, 2000; Matensson, 2000; Bollinger and Smith, 2001). Integrating the key features of KM identified in previous research, we define KM as the process of managing knowledge that is critical for achieving new product and service innovation.

An effective KM system helps the organisation to create, retain, transfer, and use and re-use knowledge. How successful an organisation is in managing its knowledge depends largely on how effectively and efficiently it can perform such processes. Academic research organisations in a developing country, such as Thailand, have limited in-house resources and the ability to capture and absorb tacit knowledge through participating in external collaboration networks is especially critical (Cohen and Levinthal, 1990; Freeman, 1999).

One of the primary mandates of Thai academic institutions, especially the public and state owned ones, is to discover new areas of knowledge, conduct research, to enrich and to contribute to the development of the economy as well as the society. Such activities are essential for the competitiveness of the institutions, government, and the country as a whole. The R&D budget of many developing countries is a fraction of most developed countries. As a result, most university R&D units in Thailand have adopted a systematic approach to manage research processes for new knowledge creation that helps to cope with a multitude of demand under substantial resource limitations.

In summary, academic research units in Thailand should benefit tremendously from a systematic KM approach in order to help them overcome resource and knowledge constraints. However, most research studies deal with KM in large business corporations in the developed countries (Chiesa and Manzini, 1996; Coombs and Hull, 1998; Cho, 1996). Few studies have investigated the contribution of KM in managing the innovation process in university R&D units, and hardly any has looked at the situation in developing countries (Spivey, Munson and Wolcott, 1997).

This paper focuses on specific aspects of KM practices and their impact on the success of research projects used by the Parallel Research Group (PRG), a new and small technological research group that has been acknowledged as one of the most successful research units in Thailand in comparison with similar domestic research units. The PRG has applied KM practices to overcome resource constraints and meet its research targets.

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It has developed technological tools to implement effective KM practices that support external knowledge transfer and help to improve the quality of products innovated by PRG. Other researchers may use the success of this case study as an inspiration to improve information exchange and new knowledge transfer to their own research units.

2 Managing knowledge in the innovation process

2.1 KM and innovation management

KM is the process to capture the collective expertise and intelligence in an organisation and to use it to create innovation through collective learning. KM processes consist of knowledge construction, knowledge embodiment, knowledge dissemination and knowledge use/benefit (Demarest, 1997), while for others (Beckett, Wainwright and Bance, 1999) the concept of KM processes include knowledge acquisition, knowledge retention and knowledge exploitation. However, there seem to be a consensus on common activities in the KM processes that capture, store, share/distribute, develop, integrate and use the knowledge (Nonaka, 1991; Probst, Raub and Romhardt, 2000; Von Krogh, Ichiro and Nonaka, 2000; Linde, 2001). In summary, KM processes can be generally categorised beyond different sets of activities in terms of knowledge identification, knowledge acquisition, knowledge development, knowledge integration, knowledge transfer, knowledge utilisation and knowledge storage (Numprasertchai and Igel, 2003).

Management of innovation is defined as the ability to manage and control the factors that drive the innovation processes, namely creation and development of new products (Touminen et al., 1999). The innovation process consists of a set of processes that aim at developing and commercialising or utilising an innovative product, process or service (Tang, 1998). The innovation process consists of many sub processes, such as opportunity identification and goal setting, need assessment, idea generation, product design, evaluation and selection, process design, manufacturing, and marketing introduction and sales (Touminen et al., 1999). The innovation processes of academic R&D units in universities are different from innovation processes in industry, as they encompass only the first set of stages of the entire innovation process, namely developing the basic technology that is then transferred to industrial companies for the production and commercialisation. Managing the innovation process in academic R&D units consists of the following phases: idea generation, research design, evaluation and selection, development process, knowledge/research output integration, production design for creating research prototypes, testing and overall evaluation. In some cases, the R&D units have additional phases, namely production and market entry in their innovation process (Numprasertchai and Igel, 2003).

In summary, KM sets up processes to identify, acquire, create, use, transfer, integrate and store knowledge for personal or organisational purposes. Innovation management is an activity that transforms new knowledge into a product or service by selecting, applying and integrating technological and business knowledge and skills. However, KM processes do support the management of innovation through creating, transferring and integrating new knowledge with the existing knowledge in order to increase the organisation’s ability to achieve product or service and process innovation.

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2.2 Knowledge as a catalyst for innovation

Innovation that leads to the commercialisation of new products or services is perceived as a competitive strength of successful organisations. KM contributes to an organisation’s ability to innovate new products and services, and ultimately to be competitive (Braganza, Edwards and Lambert, 1999; McAdam, 2000). The core process of innovation is enabled by people’s knowledge, skills and motivation (Tang, 1998). The organisation can increase innovation by turning tacit knowledge into explicit knowledge through externalising and sharing it with others (Nonaka and Takeuchi, 1995). In summary, a clear and sound KM strategy is an important catalyst in the process of managing innovation successfully.

There are two different basic strategic approaches for managing knowledge: codification and personalisation (Hansen, Nohria, and Tierney, 1999). Codification strategy aims at explicit knowledge that can be codified and stored in the knowledge repositories, such as databases, for sharing among the organisation members. Personalisation strategy targets knowledge as something to be shared through person-to-person contacts. The valuable target in this strategy is tacit knowledge that is difficult to capture, transfer and manage. To foster the personalisation strategy, an organisation has to build a network of people. Both KM strategy types are necessary and should thus be deployed in combination. Besides vision and strategy, the success of KM in the organisation also depends on factors, such as the responsibility given to the people, the organisational policy, incentives, leadership style and cross-disciplinary teamwork. Key factors most critical for the performance of Thai research laboratories, were found to be a supportive organisational culture and a clear policy, substantial incentives and resources, motivation, teamwork and good time management (Numprasertchai and Igel, 2002).

2.3 KM practices in the innovation process

KM practices are specific routines that shape the knowledge base of the firm and make it accessible in the innovation process (Coombs and Hull, 1998). KM practices include the following processes: identification, altering the format, validation, contextualising, generation, transfer, utilisation and closure. Knowledge creation is considered a key input for the innovation process within organisations (Amidon, 1998; Carneiro, 2000). The integration of employees’ knowledge is a fundamental enabler for innovation (Tang, 1998). Knowledge sharing allows organisations to access the basic knowledge inputs and to transform those inputs into new knowledge. Leonard-Barton (1988) concludes that the innovation process can be understood as an integration of knowledge with action.

A major challenge for the organisation to manage those processes that create new knowledge is the tacit knowledge, as is difficult to communicate, but very critical for creating innovation (Johannessen, Olsen and Olaisen, 1999). Braganza, Edwards and Lambert (1999) analysed the relationship between knowledge projects and innovation in more detail by dividing knowledge projects into four domains: exploring, exploiting, expediting, and enhancing. Each domain has its own purpose and contribution to innovation. All four domains taken together are called ‘knowledge-innovation diamond’. This model explains the relationship between knowledge projects and innovation.

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However, it does not clarify the interface between managing specific innovation process phases and the different related processes of knowledge creation, transfer, use and re-use. Also missing in this knowledge-innovation diamond is the important issue of collaboration for acquisition and integration of knowledge from sources outside the organisation’s boundaries.

McAdam (2000) analysed the relationship between KM processes and innovation based on the model proposed by Demarest (1997) that considers scientific and social paradigms as inputs to KM processes. He suggested that effective KM systems should incorporate innovation drivers for increasing business and employee benefits. However, this analysis explores only the relationship among the KM processes without looking at the contribution of specific KM processes to managing the innovation process effectively.

In summary, none of the models described above is satisfactory in depicting the relationship between managing new knowledge and the different innovation process phases. Some studies focus only on the relationship among different KM processes. Others look only at the impact of selected KM processes on innovation, such as knowledge creation and knowledge transfer, and only within the organisation. There is neither a study that discusses the integration of existing knowledge and new knowledge transferred from external sources, nor do any of the models mentioned above depict the impact of the different, individual KM practices on the innovation process.

3 Technological R&D units in universities

The innovation processes of academic research units differ in several aspects from innovation in industry. University research is typically occupying the early stages of the whole innovation process that can be summarised under the phase called Technology Development and is basically confined to R&D. Harryson (2000) suggested that technology development and product development processes are interdependent and critically linked. Acquiring external knowledge helps the research units to speed up resource acquisition, to solve research problems and to expand the potential research scope through the integration of partners’ knowledge. This is because knowledge integration is most effective when it draws on diverse sources of knowledge, through organisational partnerships with government agencies, universities, and leading corporations (Carayannis, Alexander and Ioannidis 2000; Wen and Kobayashi 2001). Thus, it is not surprising that the number of research collaborations between academic research units, government agencies, and industries has been increasing fast (Bollinger and Smith, 2001; Hagedoorn, 1993). The role of university R&D leading to technology development that provides the basis for new product and service development (NPSD) is shown in Figure 1.

In university research, certain innovation process elements are often omitted, namely market research, before conducting projects and the commercialisation of research results. However, many universities have established specific organisations to support and promote research activities, such as the Kasetsart University R&D Institute (KURDI) at Kasetsart University, Thailand. These types of research units manage innovation process phases quite similar to industrial firms, and their research process shares most characteristics of the fourth generation innovation process model that Rothwell (1994) called the integration model. This innovation process is characterised by parallel

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processes involving simultaneously elements of R&D, prototype development and manufacturing that are managed by integrated teams. However, a few outstandingly successful research units manage their research project in a way that seems to match closer to the fifth generation, or Strategic Integration and Networking (SIN) model. The SIN process features found in leading Thai R&D units have many projects in parallel and joint research collaborations with partners from other faculties, local companies as well as research units of leading international companies and overseas universities. These collaboration networks are coordinated mainly via communication through the computer network, such as e-mail, and online videoconferences rather than telephone calls or face-to-face meetings.

Figure 1 The relationship between university research (technology development) and the NPSD process

Source: Harryson (2000)

4 Research methodology

Technological research units were selected as case studies, because new technologies are very important to Thailand and other developing countries that spend a lot for new technological systems, equipment, and software imports. Indicators to measure the success of R&D units are research output, such as awards, honours, patents, publications, and new products or systems commercialised, and the contribution of those new products to solving major national problems. Honours and awards to researchers and research teams from national academies and government committees are the signs of high potential of researchers and research output’s performance (Werner and Souder 1997). The KM practices found in the research units were assessed conceptualised with the help

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office experts. Three of these experts are senior academic researchers who have received the National Researcher/Scientist Awards. The fourth expert is a senior researcher of the High Performance Computing R&D Division at National Electronics and Computer Technology Center (NECTEC), while the last is a senior executive in the largest research funding organisation in Thailand.

The two technological R&D units are selected as case studies. The first case is the Parallel Research Group (PRG) at Kasetsart University. It is selected in this study because of its strong record of successful research that has resulted in the creation of many new products, and scientific publications. In addition, PRG researchers are well accepted by other peers in computer engineering research fields in Thailand and abroad. The second case, selected for comparison, is a technological R&D unit in the same university. However, the identity of this research unit must be kept confidential and it is anonymously referred to as STRG (Software Technology Research Group).

Information was obtained by conducting in-depth interviews with research heads, researchers, department head, users, as well as through observations in both research units. The KM practices of the PRG research units that enhance the research routines from generating research ideas to the transfer of knowledge and research outputs to commercialisation or other public utilisation. The cases of the units called PRG and STRU are analysed in-depth to determine how the KM practices contributed to the innovation process efficiency and research management performance.

5 Managing new knowledge in academic research: the cases of PRG and STRG units

Each technological research unit in the Thai Government universities has a small number of professors, research staffs and research students with relevant academic background and/or research experience in the field. The unit heads define the research direction based on their knowledge, research experience and information obtained from internal and external sources. Successful research units usually have their own policies to select researchers based on high responsibilities and excellent skills, and to collaborate with well-known companies to increase the research potential through acquisitions of funds, infrastructure and external knowledge. These policies allow research units to handle more complex projects and reach their research targets on time.

5.1 Parallel research group and software technology research group

The Parallel Research Group (PRG) was established at Kasetsart University in 1996 to explore cluster computing technology and its applications. Since then, this research group has built many cluster software tools, which have been used around the world. The PRG seeks to contribute to our knowledge in terms of new findings and new products related to parallel and distributed computing and scientific computing. Also, one of the main contributions is to build software tools and technology that allows scientists and engineers to easily use high performance computing systems and cluster computing systems to explore new territories in scientific discovery and to strengthen the advancement of industry that benefits human society. In 1999, this research team integrated 72-nodes Beowulf cluster called PIRUN (Pile of Inexpensive and Redundant Universal Nodes) at Kasetsart University (Uthayopas, Sa-nguanpong, and Poovarawan,

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2000; Uthayopas and Sriprayoonsakul, 2001). PIRUN is also the name of the Thai god of rain and the image of god that is shown in the Kasetsart University’s logos. This machine is currently the most powerful supercomputer in Thailand. The PRG is promoted as a research centre by the university since 2003.

The second case, the Software Technology Research Group (STRG) was established in 1993 to conduct software research on several platforms, such as Microsoft windows, Linux and web-based applications, such as edutainment applications, business applications and simulation programmes. Its main research objectives are to create skilful researchers and produce new applications which support and display in the Thai language for local users. Researchers in this group focus on developing application programmes that have a promotional/positive impact on Thai education. Therefore, their research output is mostly software applications, such as internet-IT dictionary programme, edutainment games for learning English vocabulary for Thai students (cross word, hangman, and word zap), Thai chess game, research notes, web filtering for kid, automatic shopping mall generator, and parallel traffic simulation programme, which contribute to the Thai society.

Some applications of this research group have received awards in national software contests. Some applications have also been assessed as excellent applications by various Thai funding organisations. But none of the applications have been developed into commercial products. Most applications have stopped at the level of beta versions or tested versions that are submitted to funding organisations. Only a few useful applications, such as the IT-internet dictionary and games for education called ‘edutainment applications’, were made available to the public as freeware through free software websites and funding organisations. . This is because STRG has faced problems to continue supporting its products after students have graduated. They also lack external partners to provide the practical specifications that are required by the market.

5.2 KM practices in the academic technological research units

To achieve their research goals on time, units have to manage the research process efficiently. One of the efforts towards efficient research management is to apply KM practices systematically in the following phases: idea generation, research design, evaluation and selection, managing in parallel multiple R&D processes, integration of knowledge and research outputs, prototype creation, testing and overall evaluation, and, in some cases, also production, and commercialisation (see Table 1).

As technological research is competing across geographic borders, research units in the developing countries have many disadvantages when compared to the research budgets, equipment, professionals and so on in the developed countries. Therefore, research units in developing countries, such as Thailand, have to create their own management strategy to increase research efficiency if they want to compete with research peers worldwide.

5.2.1 Idea generation The PRG research head joined local and international conferences, meetings, and research consortia with experts and other researchers. He obtained multiple information, opinions, ideas, and knowledge for new research projects. Research head and researchers of STRG, on the other hand, develop applications for which they share a common interest.

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Table 1 KM practices in the new product and service development

NPSD Process KM Practices in R&D at PRG

KM Practices in R&D at STRG

Idea generation

Several sources, such as conferences, journals, magazines, research projects, from leading research laboratories abroad Observe new technology trends, such as open source concept Discussions with researchers from other fields and brainstorming with research partners and other experts via online videoconference

Discussions about common interest among researchers and students Observing the gap between current applications and market needs

Research design

In-house development Guidance from previous research projects for designing research plan in terms of costing, timing and impacts.

In-house development Guidance from previous research projects for designing research plan in terms of costing, timing and impacts

Evaluation and selection

Selected projects are related to parallel research Discussions with researchers, experts and executives from research-funding organisations to confirm suitability of selected research plans Analysis of the team’s readiness for each research plan to opt for in-house development or joint research with partners

Analysis of each team’s readiness Project selection based on decision by research head

Multiple R&D processes in parallel

Joining research with many partners from leading R&D units in Thailand and aboard Transferring tacit knowledge by sending researchers to high potential partners’ laboratories, such as Argonne National Research Laboratory and San Diego Supercomputer Center ‘Access Grid Videoconference System’ to collaborate among local researchers and experts ‘Web-based Knowledge Repository’ to store, transfer, share and reuse knowledge

In-house training by research head and senior students In-house knowledge development through discussion among researchers Project is conducted and managed by a team that consists of senior and junior students

Integration of knowledge and research outputs

Formal and informal meetings for transferring and integrating knowledge among researcher teams Interpret and recombine knowledge into new knowledge White board and web-based knowledge repository are tools for collecting information from different researchers and other sources

Only informal meetings for transferring and integrating knowledge between research team and research head Interpreting and integrating research outputs and knowledge into new ideas/knowledge

Prototype creation process

Team-based research Collecting information and sharing knowledge by tracking errors discovered through unexpected results

Each team creates its own research prototype

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Table 1 KM practices in the new product and service development (Continued)

NPSD Process KM Practices in R&D at PRG

KM Practices in R&D at STRG

Testing and overall evaluation

In-house testing and evaluation External test by users, partners, experts and research-funding organisations All evaluation results are stored in the web-based knowledge centre for reuse

Internal testing and evaluation by researchers External evaluation by users and research-funding organisations

Production Research outputs are located in the format of system installation on the PRG’s website Research outputs are also duplicated for distribution to the public Professionals in a local company support the team in graphic user interfaces for commercial versions

Research outputs are developed in-house and duplicated for distribution to the public

Market entry

Public research outputs through internet: PRG’s website, partners’ websites and well-known download software sites, such as ‘Tucow’ and ‘www.opensrc.org’ Transferred to the public by researchers conducting several technical training classes Presentation in research exhibitions, international conferences and scientific journals Help other academic institutions and companies to create and set up a Beowulf Cluster System Advanced training classes for external users help distributing knowledge and acquiring additional funding

Publication of research outputs through free Thai software websites and a research funding organisation

Source: Information from in-depth interview and self observations

While the PRG research head has discussed about research ideas with experts, in STRG, all research ideas are keep secret until research proposals are submitted to a funding organisation. In summary, the knowledge integration from several sources and experts helps PRG to create research ideas more effectively than STRG does.

5.2.2 Research design

Researchers usually develop detailed reports to evaluate research ideas and construct research project plans. For this they acquire and integrate information from several sources and design detailed costing, material sourcing, timing, impact assessment and evaluation criteria for each project. They also identify the best match between multifunctional projects and research teams based on their skill profile, readiness and knowledge.

Researchers of PRG and STRG use their own previous knowledge as the guideline for designing research plans. However, PRG has stored final research plans as document files in its knowledge repository that all group members can access anytime. STRG, on the other hand, has stored research plans in the shared document files in the research head’s PC and are difficult to search and retrieve when other researchers need to use.

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5.2.3 Evaluation and selection

Research units generate more ideas than they can handle. Idea portfolio management is the process through which these ideas are elicited, identified and funded for R&D. The evaluation and selection process, one of the most critical processes, depends on many factors, such as research experience, trend of technology and impact of research outputs.

PRG selects research plans for conducting projects based on the knowledge integration from the experience, comments and suggestions obtained through experts, while STRG selects projects based on common interest and readiness of its researchers. Consequently, PRG usually makes better decisions in this process than STRG.

5.2.4 Multiple R&D processes

Currently, most research units manage research projects team-based. To improve the overall performance of research projects, each team has to adopt appropriated techniques developed in-house or acquire help from external sources. The choice depends on the management styles of each research group.

PRG has managed projects using the combination of in-house and network development. Many projects are done in collaboration with academic and commercial partners to acquire knowledge and enhance research potential. The research activities have been supported by technologies, such as online videoconference system called ‘Access Grid Videoconference System’ and ‘web-based knowledge repository’. Technologies help the PRG researchers integrate knowledge from various sources to improve their research potential continuously. STRG has been developing research projects purely in-house, which has limitations in terms of tapping new knowledge only among the researchers in this group (Figure 2).

Figure 2 The access grid videoconference system of the PRG

Source: The Parrallel Research Group (PRG)

In summary, the effective knowledge development in the multiple R&D process using research partners that is supported by several IT tools makes PRG more effective in conducting multiple research process.

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5.2.5 Integration of knowledge and research outputs

In the team-based project, research units obtain the advantage of sharing different knowledge and skills among several sources. Researchers have to understand, interpret and integrate the information they receive.

The PRG research head usually monitors knowledge during the research activities through meetings and research progress report sent to the knowledge repository. These practices help to integrate new and existing knowledge more efficiently. The research head of STRG joins in the final project stages at consolidating knowledge and research outputs. This approach makes it more difficult to integrate all new and existing research knowledge together and risks at losing some new insights developed in earlier phases.

5.2.6 Prototype creation process

Technological research units need knowledge integration for creating prototypes as their final output. Creating prototypes requires multiple field expertise, research experience and skills.

Storing new knowledge in a repository helps researchers not only to improve the quality of prototypes, but also to reduce time and avoid errors made by others already. Researchers at STRG have to learn to create prototypes by themselves. This approach has extended the implementation time. Through its knowledge storage and knowledge utilisation system, PRG has been more successful in creating new research prototypes than STRG.

5.2.7 Testing and overall evaluation

Research units need experience in the stage of testing and evaluating overall performance for deciding whether to take the next step or to go back to the previous process. Many research units have done in-house testing and overall evaluation for their projects. A few leading research units have done a more comprehensive in-house and external testing and overall evaluation. External evaluation is regarded as a source of invaluable feedback to researchers to improve their performance.

External usage, testing, and overall product evaluation by its famous partners, such as consortium members, has helped PRG not only reduce errors, but also build trust in its research products that attracts new users. STRG relies only on internal evaluation, which makes it difficult for the same persons who developed a new product to find errors in their own work. In conclusion, PRG’s external testing and overall evaluation process involving its partners make this unit more effective in discovering areas for improvement than STRG.

5.2.8 Production

Most Thai academic research units cannot produce commercial prototypes themselves and limit their projects to creating research prototypes. They usually transfer this prototype to partners for production. However, computer system research can launch in-house developed applications through the internet more easily. The complexity of many products is hidden by the friendly Graphical User Interfaces (GUIs).

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Although the production of computer application is not difficult to develop in-house, it requires, in addition to technical knowledge, the skills to build friendly GUIs. PRG gets help from professionals of a local company who help to design and create attractive GUIs for commercial applications. Joint research with professionals has helped. PRG has gained external knowledge for GUI and effectively produce final products, while STRG tries to do everything with taking help from external sources.

5.2.9 Market entry

Recently, some Thai universities adopted a new policy to support commercialisation of research results. Research units may contact companies to join as partners. Apart from company partnerships, the internet helps to effectively launch products online via websites .

PRG has developed new applications and systems required by the market. It also has many distribution channels, such as a local company, universities and research consortia. Therefore, it is easy for PRG to diffuse its research results into applications by the public. STRG has only two channels for distributing its applications. One is through funding organisations and the other is through free local software websites. In summary, research partners have helped PRG to become more effective than many other R&D units in launching final products in the market.

5.3 KM platform and entrepreneurship

Even though, PRG targets new technology development more than commercial results, the impact of its successful Beowulf cluster system diffusion has influenced many academic laboratories and organisations in Thailand and abroad. The cluster computer system has replaced the imported large computer systems and expensive applications. Thus, it is no surprise that the PRG research head and his team have been invited as keynote speakers to present their research projects in many international clustering conferences. The Beowulf cluster prototype was selected to receive an appreciation award in the National Invention Competition from National Research Council of Thailand (NRCT) in 2000, and was also acknowledged as a success story by Advance Micro Devices (AMD) (2001) in November.

Therefore, in terms of building a solid KM platform and developing entrepreneurial activities, PRG can be considered as a model case for other academic research units. PRG has managed research knowledge using a combination of personalisation and codification strategies. PRG has several types of research partners and many forms of collaboration for different purposes. Details are as shown in Table 2.

The research head of PRG is frequently invited to participate in joint projects with the leading R&D labs in the US where he has obtained experience from professionals for improving research output quality and management skills. PRG has also collaborated with many domestic and foreign organisations in research consortia. For example, the Asia-Pacific Grid (ApGrid) consortium, established to build Computational Grid around Asia-Pacific region, has helped to drive outstanding research of members, such as standard applications for using in Beowulf Cluster and Grid system. Many applications developed by PRG have been used, tested, evaluated and accepted as high potential and useful applications by other members. PRG is now considered as one of the leading cluster research units in Asia.

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Table 2 PRG’s collaboration network

Research Network of PRG

Research partners Collaboration

form Purposes Global microprocessor company, Global computer company and Funding organisations in Thailand

Research funding

Obtain research funding, conduct research projects using device and equipment provided by partners

Universities in Thailand Research collaboration

Reduce research costs through parallel systems support for research and computer service in local universities

Leading global research laboratories in US

External knowledge sources

Acquire research knowledge and management skills from world-class professionals through joint research

Asia Pacific Research Consortium Consortium Exchange research ideas Use, test, support and promote applications produced by members

Local company R&D contract

Acquire research specification, market ideas to develop commercial applications for local market

After several research projects had been presented to the public, many organisations, not only research funding organisations but also private companies, provided support to PRG in terms of research equipment and funding. For example, AMD has supported cluster research in this R&D unit. The head of PRG was also invited as a guest speaker to present his research in several Asian countries, such as Singapore, Hong-Kong, the Philippines and so on. However, the research head have selected research partners very carefully. He stated that ‘I care for the quality of research partners more than the number of partners. I do not need temporary partners to collaborate only short term’. He will refuse research funding from external organisations if the conditions for managing intellectual property are unclear.

PRG has its own web-based knowledge repository to support its innovative research. Researchers can acquire, store, retrieve and exchange information, opinions, ideas and knowledge for preparing and conducting research. In addition, there is an online videoconference system for its researchers to communicate with other experts globally.

In summary, the creation of new knowledge and its successful application is achieved through personal initiated collaboration networks that are strongly supported by an IT system. The KM platform of PRG consists of three layers: IT as knowledge enabling tools, KM practices and NPSD. KM practices consisting of personal research skills and research networks for new product and service development process and IT support infrastructures have helped PRG to improve its relationship with partners and finally increase its research performance to a level of international quality (Figure 3).

6 Conclusion

Based upon the assessment of the relationships between managing knowledge processes and research routines in this study, the KM platform consists of several KM practices

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that are supported by in-house development, collaboration networks and information technologies to successfully manage new product and service development. The KM practices are embedded in the innovation process (Figure 4). In both cases, the research units have integrated the new knowledge they need through a combination of in-house development and external acquisition. External collaboration network helps to fill the gaps between existing knowledge and target knowledge required in their research. Conducting research through networks with companies and other external partners has helped, especially the PRG, not only to enhance their potentials and reduce the cycle time, but also to transfer research outputs to commercial product or service applications. The research units have also stored updated knowledge for reuse in future projects and transferred knowledge to their researcher partners.

Figure 3 The KM platform for NPSD of PRG

Figure 4 KM practices for process integration in managing product and service innovation

682 S. Numprasertchai and B. Igel

In the KM platform, information technologies work as supporting tools for improving the performance of the KM practices. Information technologies provide channels for acquiring, transferring, exchanging and distributing knowledge faster and more conveniently, as well as a repository for storing and reusing. It has thus enabled research network partners to collaborate and exchange knowledge more efficiently.

In summary, an effective KM platform will help university research groups to manage their projects more efficiently in terms of time, cost, quality and new product or service commercialisation. There is no doubt that the more successful R&D units in Thailand have usually extended their potential by creating new research knowledge through a strong interaction with external partners. To improve the country’s competitiveness, Thai university research groups must build better KM platforms that allow them to continuously learn from external peers. By doing so, they will be able to create relevant high quality research outputs that can be transformed into important product and service innovation.

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