Relative importance of knowledge portal functionalities

Expert Systems with Applications 36 (2009) 3662–3670

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Expert Systems with Applications journal homepage: www.elsevier.com/locate/eswa

A contingent approach on knowledge portal design for R&D teams: Relative importance of knowledge portal functionalities Hong Joo Lee a, Jong Woo Kim b,*, Joon Koh c a

Department of Business Administration, The Catholic University of Korea, South Korea School of Business, Hanyang University, 17 Haengdang-dong, Seongdong-gu, Seoul 133-791, South Korea c College of Business Administration, Chonnam National University, South Korea b

a r t i c l e

i n f o

Keywords: Knowledge portal R&D team Team characteristic Knowledge management

a b s t r a c t Many research and development (R&D) organizations and teams currently use a specialized knowledge portal (KP) for research collaboration and knowledge management. However, R&D organizations adopt whole portal functionalities without considering their R&D team or the team’s task characteristics. The motivation of this study comes from this typical lack of consideration. This study proposes that the degree of importance of specific KP functionalities may be affected by the particular context in which R&D teams handle knowledge. The objectives of this research are to identify functionalities that are relatively important of KPs based on the specific team and the team’s task characteristics. This research attempts to provide implications that can be used to design and implement KPs for R&D teams. Based on a field survey with 142 researchers in government-sponsored research organizations in Korea, we found that researchers perceive communication, collaboration, and connection functionalities as being important when their team sizes are large or their team members are distributed. Also, the coordination functionality is more important when the research type relates to commercialization projects than when the team is involved in basic level research projects. We discuss interpretations of the results and implications on KP design. Ó 2008 Elsevier Ltd. All rights reserved.

1. Introduction As the importance of utilizing knowledge resources increases and the amount of information and knowledge becomes overwhelming, adopting a knowledge portal (KP) has been one of the important issues for research and development (R&D) organizations in the last decade (Collins, 2003; Firestone, 2002). Since many research organizations have been representing themselves as knowledge organization (Smith, 2000; Sveiby, 1997), organizing the whole knowledge process and integrating diverse knowledge resources through a KP is crucial to the effectiveness of their R&D activities (Barthès & Tacla, 2002; Collins, 2003; Kouzes, Myers, & Wulf, 1996). Most of the researchers and practitioners agree that structuring and enlarging the knowledge base, and improving its use will contribute to the effectiveness of R&D processes (Armbrecht et al., 2001; Collinson, 2001; Kerssens-Van Drongelen, De Weerd-Nederhof, & Fisscher, 1996; Parikh, 2001). Currently, R&D organizations use either a general or customized KP, or a set of general application systems such as basic messaging systems and document management systems for research collaboration and knowledge management (KM). These general KP appli* Corresponding author. Tel.: +82 2 2220 1067; fax: +82 2 2220 1169. E-mail address: [email protected] (J.W. Kim). 0957-4174/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.eswa.2008.02.061

cations, used in many business organizations, have focused on knowledge organization, and integrating and searching distributed knowledge. As a consequence, there are several studies that suggest R&D KPs reflecting the characteristics of the R&D process and of the R&D teams (Barthès & Tacla, 2002; Kouzes et al., 1996; Ramesh & Tiwana, 1999). These systems perform as a portal for distributed information resources and applications. They provide team interaction features for promoting research activities such as project space for sharing project information, document management systems, project management systems, and communication facilities. Applications and functions of KP have been considered universally appropriate and important to every situation and context. R&D organizations tend to only adopt all of the KP functionalities without considering their KM capabilities and team characteristics. These may increase the cost of a KP and cause the complexity of functionalities in use. The motivation of this study comes from this. This study proposes that the importance of KP functionalities can be affected by the particular context in which R&D teams handle knowledge and interact with each other. The objective of this study is to identify the most salient KP functionalities that will best facilitate R&D teams in their ability to share and distribute knowledge and explore its relationship with team and task characteristics. An empirical investigation

H.J. Lee et al. / Expert Systems with Applications 36 (2009) 3662–3670

has been performed with government-sponsored research organizations in Korea. This paper is organized as follows. Section 2 introduces a review of related literature on R&D teams as well as the KP and KM. Section 3 presents a research model and related hypotheses. Section 4 describes research methods and results. Section 5 presents discussion and implications of the results, and Section 6 includes some concluding remarks.

2. Literature review 2.1. Knowledge management and knowledge portal Facing knowledge-based competition, many organizations have recognized that managing knowledge is crucial for their competitiveness (Bock & Kim, 2002; Choi & Lee, 2002; Gold, Malhotra, & Segars, 2001; Leonard, 1998; Spender, 1996; Teece, 1998; Von Krogh & Roos, 1995a), and these organizations have tried to secure various types of knowledge assets (Liebowitz & Wright, 1999). Recently, knowledge management has been considered as a means of maximizing the strategic value of organizations. According to Venzin, Von Krogh, and Roos (1999), knowledge is important for the theoretical realm of strategic management. The reasons for its importance are: (1) knowledge facilitates sustainable, heterogeneous resource distribution; (2) knowledge changes the nature of resource investment decisions; (3) knowledge changes the nature of work and property; and (4) knowledge emphasizes the social context. Venzin et al. (1999) also saw knowledge as a source of competitive advantages, which makes it necessary to reconsider strategic concepts fundamentally. Further Von Krogh and Roos (1996a) argued that the three domains of knowledge, competence, and competitive advantage can be interplayed. Organizational knowledge is created from individual experiences and learning in embedded routines such as business processes, tasks, domain-specific problem-solving activities, and organizational culture (Argyris & Schon, 1978; Nass, 1994; Nonaka, 1994). However, most of outcomes of individual experiences and learning remain as organizational members’ tacit knowledge or in a pile of personal documents. Von Krogh and Roos (1995b) noted that organizational knowledge resides both in the individual members and in the relations among organizational members, that is, in the social context. Sveiby (1997) also considered transferring knowledge as the key activity in knowledge organizations. Learning occurs at individual and organizational levels based on social understanding and mutual trust (Brown & Duguid, 1991). Thus, recently, firms are increasingly adopting interaction promoting strategies for KM such as online communities-of practices (CoPs). CoPs encourage members to actively interact with other members for knowledge creation as well as knowledge sharing using information technologies (Wenger & Snyder, 2000). Orr (1990) who investigated Xerox, found that stories shared by the personnel who were responsible for servicing complex machinery were an integral and essential aspect of their activity. Formal classroom instruction was discovered to have limitations in alerting maintenance staffs to the mix of technological problems they encounter. Instead of formal classroom instruction, stories of experience provided by peer technicians and engineers helped community members develop their problem-solving skills. By contributing their stories, technicians may enhance their knowledge sharing as well as knowledge creation. Von Krogh and Roos (1996b) also emphasized conversation management for knowledge development, distinguishing strategic discussions from operational discussions. Due to such social characteristics of organizational knowledge, KM supporting systems with collaboration functions such as KPs are considered as mandatory in order to manage organizational

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knowledge. With the effort of integrating distributed information and knowledge, and accessing diverse applications, the enterprise information portal (EIP) and EKP have gained popularity for providing users a single gateway to personalized information (Benbya, Passiante, & Belbaly, 2004; Ruggles, 1998; Shilakes & Tylman, 1998). Though the terms of an enterprise portal, corporate portal, EIP, and (E)KP, which have subtle differences to their definitions (Detlor, 2000; Dias, 2001; Firestone, 2002), they are generally used reciprocally (Detlor, 2000; Dias, 2001). While other definitions related to EIP focused on information and application integration, and personalized gateways, a KP emphasizes knowledge organization. The following is the definition of EKP from Collins (2003, pp. 77): ‘‘[A] personalized interface to online resources for knowledge workers to organize and integrate applications and data. The solution (EKP) allows knowledge workers to access information, collaborate with each other, make decisions, and take action on a wide variety of business-related work processes regardless of the knowledge worker’s location or business unit affiliation, the location of the information, or the format in which the information is stored.” A KP supports KM processes and KM activities as well as features of an enterprise portal such as integrating disparate applications and data, accessing both external and internal sources, and transmitting information through a standardized web interface. In next section, we discuss features of a KP in detail. 2.2. Functionalities of a knowledge portal Researchers have identified many key features of KP: coding and sharing of best practices, creation of corporate knowledge directories, and creation of knowledge networks (Alavi & Leidner, 2001); collaboration and communities, content management, profiling and personalization, integration, presentation, and search (Collins, 2003); knowledge portal, collaboration services, discovery services, a knowledge map, and knowledge repository (Woods & Sheina, 1999). From the reviews of these various features, we have classified them into seven functional categories summarized in Table 1. Communication: Communication features support internal and external communication among members for sharing and transferring knowledge. Communication technology is considered as infrastructure for exchanging data and sharing information (Liao, 2003). Electronic mail, groupware, instant messaging, video conferencing, and threaded discussion belong to the communication feature. As the level of knowledge transferring and sharing increases by use of the KP, the internalization of knowledge may increase (Alavi & Leidner, 2001). Collaboration: KM is inherently collaborative. Collaboration services in a KP such as virtual meetings on the Web, workspace, and screen sharing can establish an environment where knowledge can be created, organized, and transferred among members (Bair, Fenn, Hunter, & Bosik, 1997; Majchrzak, Rice, King, Malhotra, & Ba, 2000). Collaborating allows team members to meet more often and share knowledge more easily, thereby increasing socialization and internalization of knowledge among the members. Contents: Many key features of a KP that have been identified by researchers belong to the contents category such as storage, structure and navigation, the knowledge map, and knowledge repository. Advanced content management technology and sophisticated retrieval techniques can be effective tools in enhancing knowledge organization and retrieving relevant knowledge (Alavi & Leidner, 2001; Liebowitz, 2001). The contents’ functionality supports organizing and structuring knowledge to enhance the content’s use and to guide users to available knowledge resources. The knowledge map, which is one of the contents’ functionalities, within a KP provides an organizational schema for knowledge classification that provides the link between explicit knowledge and the knowledge process (Woods & Sheina, 1999).

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Table 1 Functional categories of knowledge portal Category

Descriptions

Functions

Communication

Supporting internal and external communication among members for sharing and transferring knowledge

Asynchronous communication Threaded discussion Intranet Extranet

Collaboration

Technologies are used for sharing ideas, sharing creation, and sharing a work space

Collaborative space for team work Virtual meetings on the Web Simple telephone conference call functionality Screen sharing

Contents

Organizing and structuring knowledge to enhance its use and to guide users to available knowledge resources

Knowledge map, domain ontology Knowledge repository Structuring and navigating knowledge

Coordination

Maintaining consistency within a work product or managing dependencies between activities

Calendar Work scheduling Work control and progress monitoring Routing of information

Customization

Searching knowledge and delivery of more relevant knowledge to users

Discovery service Push service to provide filtered delivery of knowledge

Community

Building and managing communities to activate communication and sharing among researchers

Member management Asynchronous communication Threaded discussion Availability and scheduling

Connection

Creating and managing knowledge networks, and finding relevant experts

Experts’ directories Finding people Mapping people to knowledge map

Coordination: Coordination activities, such as managing shared resources, segmenting and assigning tasks, and managing information flows, are required to maintain consistency within a project or to manage dependencies between activities to perform tasks (Malone & Crowston, 1990, 1994). Coordinating functionalities for team members include calendaring, scheduling, routing of information, and progress monitoring of activities. Customization: Customization is composed of two main features: discovery services and personalization. Discovery services help users retrieve and browse knowledge in the knowledge repository (Woods & Sheina, 1999). Personalization of knowledge means filtered deliveries of knowledge based on a user profile for providing relevant knowledge to a user (Bair et al., 1997). Through the use of intelligent systems to develop interest profiles of organizational members, the systems can determine which members might be interested in topics or categories of knowledge, and then, deliver personalized knowledge among all of the new knowledge in a KP (O’Dell and Grayson, 1998). Community: A community composed of a group of people who have similar interests and skills focuses on socializing and amplifying important knowledge and best practices in their interest areas (Wenger & Snyder, 2000). Community functionalities usually include threaded discussion, member management, information notification, availability checking, and schedule functions within communities. Wenger and Snyder (2000) provided several important ways that CoPs can add value to organizations: helping drive strategy, starting new lines of business, solving problems quickly,

transferring best practices, developing professional skills, and helping companies recruit and retain talent. Connection: Functionalities, such as finding relevant experts and managing experts’ networks (Woods & Sheina, 1999), for creating and managing knowledge networks are important for knowledge sharing and transferring between experts. The connections are central to the knowledge diffusion process because such networks enable individuals to locate the experts who have the knowledge that might help them solve a current problem and expose individuals to more new ideas (Alavi & Leidner, 2001; Robertson, Swan, & Newell, 1996). In many organizations, the primary content of a KP is a set of expert profiles containing a directory of the backgrounds, skills, and expertise of individuals who are knowledgeable on various topics. 2.3. R&D team and task characteristics There are a variety of factors which relate to team successes (summarized in Table 2). These factors can be classified into two categories: task and team characteristics (Becerra-Fernandez & Sabherwal, 2001; Dailey, 1978; Scott, 1997). Task characteristics represent the nature of tasks performed by R&D teams. Thus, a number of task characteristics have been identified at the level of R&D teams such as task certainty, task interdependence, importance of the research project, research type, and project duration (Dailey, 1978; Keller, Julian, & Kedia, 1996). Becerra-Fernandez and Sabherwal (2001) provided a contingency theoretic view that the impact of a KM process on organizational performance is moderated by task characteristics in which knowledge is being used. These three task characteristics are examined in this study as influencing the perceived importance of KP functionalities: research type, project duration, and research importance. Table 2 Characteristics of R&D teams Literature

Characteristics

Dailey (1978)

Task certainty, task interdependence, team cohesiveness, and team size

Oh et al. (1991)

Communication patterns (official and non-official), leadership type

Levi and Slem (1995)

Evaluation and rewards, social relations, organizational support, task characteristics, self-management, leadership

Kerssens-Van Drongelen et al. (1996)

Structure

Culture

Physical distance between units/team members, performance appraisal system, project coordination mechanism, transfer mechanisms, and group constitution Inter-functional climate, informal contacts communication, management attention (e.g. knowledge transfer explicitly encouraged), and people roles

Keller et al. (1996)

Participation and cooperation Satisfaction with pay and advancement

Work importance participation/ cooperation Pay/advancement satisfaction supervision satisfaction

Scott (1997)

Team process

Team cohesiveness, level of external communication Members’ social identification Management support and recognition, organizational influence of the project leader, members’ time dedication, functional diversity

Team identity Team structure

Becerra-Fernandez and Sabherwal (2001)

Task characteristics

Task orientation and task domain

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Research type: For successful R&D research projects, research activities and ways of performing activities are different as the type of research projects. The ways of communication that are critical to project success are different dependent on the research type (Kerssens-Van Drongelen et al., 1996). For example, in the case of development projects, communication with other members of the company may be more important while communication with people outside might be more important in the case of basic research projects (Kerssens-Van Drongelen et al., 1996). Project duration: Project duration can affect the probability of technical success in a project; the probability of technical success increases when the duration of the project increases (Bizan, 2003). Bizan (2003) showed that as the size of the project increases – e.g., budget and duration – organizations tend to allocate better resources to the project. Researchers have enough time to discuss their ideas and create and share their knowledge when they are assigned to a project which has long duration. Research importance: This factor implies recognition by the researchers of the importance of their project to their research field or their organization. Keller et al. (1996) identified the fact that a climate of high work importance is associated with higher R&D team productivity. Team characteristics represent the structure and culture of R&D teams. The structure of a team describes the organization of team members, the coordination mechanism, and performance appraisal system. Team culture includes cohesiveness of team members, team climate, research experience, and leadership types (Dailey, 1978; Oh, Kim, & Lee, 1991; Rousseau, 1990; Scott, 1997). The four team characteristics are examined in this study as factors that can have influence on the perceived importance of KP functionalities: team size, dispersion of members, cohesiveness of team, and research experience. Team size: Because team size influences the amount of participation, the distribution of group members, and the probability that the group will achieve consensus, R&D team size is negatively related to team cohesiveness and team productivity (Dailey, 1978). According to Dailey (1978), ‘‘the literature on groups broadly supports the negative effects of increasing team size on team cohesiveness, participative processes, and cooperation.” Dispersion of members: Dispersion of team members describes physical and organizational distance between researchers. As IT advances rapidly, physically distributed members can form a R&D team and also R&D teams can be composed of researchers who are from different R&D organizations. Kerssens-Van Drongelen et al. (1996) included physical distance between researchers as one of the influential characteristics of the R&D strategy on knowledge accumulation and dissemination, because physical distance can affect communication and knowledge transfer between members. Cohesiveness of team: Cohesiveness reflects interpersonal interactions and attraction among team members. Dailey (1978) saw cohesiveness as ‘‘the strength of the force acting on members to maintain group affiliation.” One of the main advantages for promoting teamwork in R&D teams results from the nature of their tasks. In most cases, the complexity of the R&D task requires multiple skills and mutual interdependence (Levi & Slem, 1995). In addition, team cohesiveness has positive relationships with a collaborative problem-solving process and team productivity (Dailey, 1978). Research experience: The research experience factor describes the level of research experience in a team. R&D teams which have a higher level of experience in a domain may focus on more knowledge utilization rather than knowledge accumulation and organization because researchers have enough knowledge on a particular research domain (Bergen & Pearson, 1983). Hence, the level of research experience is expected to influence researchers’ IT usage behaviors and communication in their teams.

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The R&D team characteristics mentioned above, however, may not only affect the level of requirement of interaction between team members but also the change mechanism of knowledge flow and activities. Thus, designing or introducing an EIP or a KP relevant to team characteristics helps R&D team members to promote knowledge creation and knowledge sharing. This in turn, can ultimately lead to high team performance. One of the main purposes of a KP is to capture knowledge so that it is accessible and reusable to the organization and teams. 2.4. Knowledge management and portal in R&D teams In R&D teams, individual researchers concentrate on engaging in knowledge creation, knowledge transfer, and knowledge sharing (Gassmann, Reepmeyer, & Zedtwitz, 2003). Most of these people may be called knowledge workers. Focusing on knowledge workers, Cramton (2001, 2002) suggested several problems that result in failures connected to managing mutual knowledge: (1) failures to communicate and retain contextual information between members, (2) unfitness between distributed information and team collaboration, (3) differences in evaluating the relevance of information, (4) differences in speed of access to information, and (5) difficulties in interpreting the meaning of silence of communication. Cramton (2001) also argued that these failures have negative effects on collaboration among dispersed team members. In general, R&D activities involve creative work which requires ad hoc communication between team or project members. This implies that computer-mediated communications which encourage more spontaneous interactions between members can be used for the performing of creative tasks. These technologies include shared workspace, email, and desktop video conferencing. Kratzer, Leenders, and Engelen (2005) found that R&D teams that employ only one or a few modes of communication are less creative. They also argued that teams with one way of coordinating the team task cannot expect to reach high levels of creative performance consistently. Furthermore, we discern two types of knowledge: explicit knowledge and tacit knowledge (Nonaka & Takeuchi, 1995). Explicit knowledge is easily documented while tacit knowledge is not articulated so that it is very difficult to transfer to other people. In R&D teams, both tacit knowledge and explicit knowledge must be freely communicated between team members in order to facilitate new learning and ultimately to increase R&D performance. In the context of R&D teams, owing to rapidly increasing complex, complicated, and mutual knowledge (Smith, 2000; Snowden, 2002), team members require more face-to-face contact. However, IT tools and a R&D intranet site – a KP, complementing or substituting for face-to-face contact, can play a critical role in problem-solving and discussion on research issues that members face. Moreover, by such IT support, tacit knowledge can be transformed into explicit knowledge by an externalization process (Nonaka & Takeuchi, 1995). IT collaboration tools and CoPs together may be used for enhancing access to the tacit knowledge of the team. Thus, for effective R&D activities of R&D team members, a research portal, including collaboration tools, is essential. Especially if a R&D team is a dispersed or virtual team, it should consider these IT factors as more important since portal and web technologies make it possible to overcome geographical and organizational barriers to collaboration and knowledge sharing in dispersed networks (Ahn, Lee, Cho, & Park, 2005; Becker, 2001; Corso, Martini, Pellegrini, Massa, & Testa, 2006). In summary, the use of a KP is a major means for encouraging knowledge sharing and collaboration in R&D teams. A KP can influence the success of R&D projects and the effectiveness of R&D teams (Armbrecht et al., 2001).

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3. Research model and hypotheses

Table 3 Concepts, constructs, and measures

The research model, which is presented in Fig. 1, is about relationships between the perceived importance of KP functionalities and team/task characteristics. This model is devised from a conjecture that the perceived importance of KP functionalities is affected by the task and team characteristics. Concepts, constructs, and measures for the research models are summarized in Table 3. The hypotheses derived from the research model are that the perceived importance of each function is affected by the task and team characteristics. There are seven hypothesis groups (H1–H7) related with task and team characteristics. Each hypothesis group has seven sub-hypotheses corresponding to seven functional categories of KP as stated in Table 1. For example, the first row of Table 4 is a list of seven sub-hypotheses (H1a–H1g) of the first hypothesis group H1. Other hypothesis groups from H2 to H7 are defined in a similar way and described in the second row of Table 4.

Concepts

Research constructs

Variables and measure description

Team characteristics

Team size Dispersion of members Cohesiveness of team Research experience

Number of team members Locations and organizations of members Consensus of team team member relations Experience level of research fields

Task characteristics

Research type

Classification of research – Basic – Application – Development – Commercialization Months devoted to research projects Research relevance fit to organizational core competence

Project duration Research importance Importance of KP functionalities

4. Empirical analysis 4.1. Research method 4.1.1. Sample and data collection An empirical survey has been performed following the steps in Fig. 2. A pilot study to obtain detailed insights of current research practices was conducted by semi-structured interviews with R&D teams. The initial survey questionnaire was re-evaluated and refined according to the interview results. At the pre-study stage, we surveyed some researchers with an initial questionnaire. Sample survey data were analyzed and then the analysis results were used to refine the questionnaire. Selecting target audiences was supported by Korea Research Institute of Standards and Science (KRISS), Korea Research Institute of Bioscience and Biotechnology (KRIBB), and other governmentsponsored research organizations that allowed contact with their researchers and provided contact names and addresses of researchers. We called all of their R&D team members by phone before distributing our survey questionnaires, and with a brief introduction of our survey we asked if they would be able to respond to the survey. Under their acceptance, we sent the questionnaires to them with small gifts via mail. From 211 distributed questionnaires, the survey yield complete data sets for 142 respondents after several were eliminated for incomplete data (69.7%). The relatively high response rate of

Users’ perception of importance of KP functionalities

Subjective evaluation of importance on KP functionalities (rated on a 1–5 scale)

69.7% seemed to be due to our calling for their permission prior to distribution of questionnaires and participant incentives. The distribution of respondents by their organizations and research domains are summarized in Table 5. 4.1.2. Reliability of measures All the items of the survey, except the research type and dispersion of members, were measured by a five-point Likert type scale with same intervals. The variables representing research type and dispersion of members are measured at the nominal level. Some research variables such as research importance are measured by multi-items, which are needed for reliability tests. Other actual data such as team size, research experience, and project duration were gathered in the form of ratio scale. Such single-itemed achieve data variables do not need reliability tests (Hair, Anderson, Tatham, & Black, 1998). Table 6 shows research variables which were measured by multiple items, and their reliability level is represented by Cronbach’s alpha. If we exclude some items of measure, we may get a higher value of Cronbach’s alpha. Research variables, initial Cronbach’s alpha, and their Cronbach’s alpha value after excluding one item are summarized in Table 6. The

Fig. 1. Research model.

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H.J. Lee et al. / Expert Systems with Applications 36 (2009) 3662–3670 Table 4 Research hypotheses Hypothesis H1: Perceived importance of each function is affected by team size H1a: Perceived importance of contents is affected by team size H1b: Perceived importance of customization is affected by team size H1c: Perceived importance of connection is affected by team size H1d: Perceived importance of communication is affected by team size H1e: Perceived importance of collaboration is affected by team size H1f: Perceived importance of coordination is affected by team size H1g: Perceived importance of community is affected by team size H2: Perceived importance H3: Perceived importance members H4: Perceived importance H5: Perceived importance team members H6: Perceived importance H7: Perceived importance

of each function is affected by research type of each function is affected by the dispersion of of each function is affected by project duration of each function is affected by the cohesiveness of of each function is affected by research experience of each function is affected by research importance

Cronbach’s alpha values of each research variable were over 0.7 demonstrating the satisfactory reliability of the research variables (Nunnally, 1978).

4.2.2. Test of hypotheses Hypothesis groups from H1 to H7 of the first research model were tested by one-way ANOVA with the significant level of 0.05. Test statistics and p-values of accepted hypotheses from the research model are summarized in Table 7. Test results of hypothesis groups, H1–H7, were classified into three categories. First, H1d (the perceived importance of communication is affected by team size) and H1e (the perceived importance of collaboration is affected by team size) were accepted. As the team size increased, communication and collaboration were perceived as more important. That is, communication and collaboration functions were considered important when R&D teams consisted of many members for executing research tasks. Second, H2f (the perceived importance of coordination is affected by research type) was accepted at the significant level of 0.05. Researchers of commercialization level projects, which applied basic and fundamental research outcomes to

Table 5 Distribution of respondents Organization

Number of respondents

Research domain

Number of respondents

A

56 (39.44%)

60 (42.25%)

B

45 (31.69%)

C D E

15 (10.56%) 11 (7.75%) 9 (6.34%)

F

6 (4.22%)

Electronics and telecommunications Resources, energy and nuclear Mechanics Material science Biology and bio engineering Environmental science

10 (7.04%)

Total

142

Total

142

4.2. Results 4.2.1. Perceived Importance of KP functions in R&D organizations As represented in Fig. 3, the most important KP functionality in research projects is communication, followed by contents and customization. On the other hand, collaboration is the lowest in terms of importance among the seven categories regardless of the team characteristics.

Fig. 2. Research method and survey steps.

28 (19.72%) 17 (11.97%) 14 (9.86%) 13 (9.16%)

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Table 6 Reliability of the research variables Variable

Research importance Cohesiveness of team members Perceived importance of knowledge management functions

Table 7 Accepted hypotheses and test statistics

Before excluding

After excluding

Cronbach’s alpha

Number of items

Cronbach’s alpha

Number of items

0.7004 0.9268 0.8214

3 4 7

0.7004 0.9458 0.8214

3 3 7

Functions

Test statistics (F)

p-Value

Team size

Communication Collaboration

13.21 9.552

0.01 0.04

Research type

Coordination

9.497

0.05

Dispersion of members

Connection Communication

12.04 11.15

0.02 0.04

5. Discussion

tionalities of connection, communication, collaboration and coordination (that is, significant dependent variables in this study) all involve ‘‘user interaction” supporting functions of a KP, rather than working alone functions such as content or customization. This gives a hint that we need to concentrate on developing elaborate ways of encouraging R&D team members to actively interact when we design a KP for R&D teams. Knowledge results from networking which can be understood as interactions in social networks that allow knowledge creation and transfer among individuals (Back, Krogh, Seufert, & Enkel, 2005). Consequently, in a R&D portal, effective management of interactions and collaboration among team members seems to be more crucial for KM success than that of knowledge or content itself. This, practically, may provide us future research motivation on how ‘‘social interaction related functionalities” such as CoPs (Wenger & Snyder, 2000) can be embedded in a KP when we design and implement the KP.

5.1. Interpretation of the results

5.2. Implication for KP implementation

Out of the 7C (contents, customization, connection, communication, collaboration, coordination, and community), the most important KP functionality was found to be communication followed by contents regardless of the team characteristics. However, the variances of connection, communication, collaboration and coordination depended upon the team characteristics such as team size and dispersion of members. For example, the bigger the team size is, more important the functionalities of communication and collaboration become. In a big team where R&D team members have difficulty in actively interacting among themselves, they may be sensitive to communication and collaboration. In addition, the more dispersed the team members are, the more important both connection and communication are. These results imply that the approach of designing a general KP may be different from that of planning a KP for R&D teams. Also, it is interesting that the func-

Although implementation of a KP has been one of the most critical issues for R&D organizations in the last decade, R&D organizations have adopted KP functionalities without considering their KM capabilities, team characteristics, and task characteristics. The major finding is that perceived importance of KP functionalities is different by their task and team characteristics: First, as team size increases, communication and collaboration functionalities are perceived as more important than other functional categories. Since communication and collaboration can allow team members to meet more easily and help socialize knowledge between members, the importance of those two features is higher in large size teams than in smaller size teams. Researchers who participated in commercialization level projects considered the coordination functionality as more important for performing project tasks than researchers involved with basic level research projects. From this result, we can infer that commercialization research involves more activities and more complex dependencies between activities than research on other types such as basic, application, and development research. Researchers have the needs of using the coordination functionality more often to coordinate activities, organize members, and maintain consistencies between activities within commercialization research. When team members are dispersed physically and organizationally, connection and communication functionalities are perceived as more important than other KP functional categories. Since team members who are physically separated in dispersed teams and who come from other organizations do not know other members’ expertise, where the experts are and how to communicate with them are important issues. On the result that dispersion of members affects neither collaboration nor coordination, we interpret the results that even in a collocated team, team members tend to coordinate and collaborate with others predominantly by IT tools owing to communication efficiency. Since they become skillful at using a KP for communication and connection, they might prefer a KP to face-to-face contact even when they face complex research problems.

commercial products, thought that the coordination function was more important for performing project tasks than researchers on basic level research projects where they try to find theoretical solutions to logical or academic problems. Finally, both H3c (the perceived importance of connection is affected by dispersion of members) and H3d (perceived importance of communication is affected by dispersion of members) were accepted. More distributed teams – i.e., members from different organizations and working at different places – perceive connection and communication as more important functions than other KP functional categories. Fig. 4 shows the significant relationships between team/task characteristics and perceived importance of KP functionalities.

Fig. 3. Perceived importance of KP functionalities.

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Fig. 4. Significant relationships between team characteristics and importance of KP functionalities.

Therefore, for successful KP implementation and operation, managers should be able to assess the fit between research characteristics and KP functionalities before adoption of a KP. After KP implementation is completed, managers should consider research characteristics for configuring a KP and building a KM strategy to increase utilization of a KP and maximize benefits of KM. Finally, on the result that no independent variable influences any functionality of contents, customization, and community, we can explain to the following: First, contents and customization seem to be common and basic functionalities regardless of team characteristics. The possible evidence may be that the scores on the importance of contents and customization functionalities are all high (see the Fig. 3). As for community functionality, since a R&D team is clearly divided into several sub-teams based on projects and the bonds of project members tend to be already strong, there could be no significant difference in the needs for community services by team characteristics. 6. Conclusions The use of a KP to support research organizations has to be done so that the KP provides knowledge searching and organization features. The KP needs to be integrated with the project process including communicating with members, coordinating research activities, and personalizing knowledge. On the current KP configurations and operations, we found that the perceived importance of KP functionalities to support research projects was contingent on the characteristics of the research tasks and R&D teams. For effective R&D activities, research organizations should be able to align their teams’ characteristics and KM activities facilitated by KP. In particular, practices of interactions among team members through the KP should be configurable based on their situations. Though there are several limitations in this research, three major limitations are mentioned here. First, we focused on a limited number of characteristics for R&D teams. More relevant characteristics such as the organizational support factor, trust, or leadership may be added to improve the understanding of the perceived importance of KP functionalities and R&D teams. Also, we do not think that the three task characteristics we examined in this study cover all of the task characteristics in R&D teams. Second, we only used perceived importance in defining the importance of functionalities, leaving out actual data of using KP functionalities during research projects such as time, shared documents, click events, and other usage logs of KP. This was because of the difficulty in getting the actual data from the participating organizations. Finally, we surveyed only researchers in Korean R&D organizations. For this reason, the research results of this paper have a lack of generaliz-

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