Full Length Research Paper
Enhancing knowledge management for R&D innovation and firm performance: An integrative view
Chechen Liao
1, Hsiu-Yu Wang
1, Shu-Hui Chuang
2*, Meng-Lin Shih
1and Chuang-Chun Liu
11
Department of Information Management, National Chung Cheng University, Taiwan.
2
Department of Business Administration, Asia University, Taiwan.
Accepted 31 August, 2010
Previous researches have examined the relationships among variables such as knowledge management (KM), innovation and performance. However, most empirical studies have investigated the relationships among these variables in isolation. A gap thus exists in the literature and to fill this gap, the current study develops a research model that links these variables. The model establishes the relationships among KM capability, research and development (R&D) innovation and firm performance.
The findings suggest that CEOs should manage knowledge-based resource and assess whether the firm has the KM capability to create, maintain and exploit the knowledge-based synergies for superior innovation of R&D departments.
Key words: Knowledge management, innovation, firm performance.
INTRODUCTION
In a discussion on knowledge management (KM), it seems as though the firms that could manage the know- ledge resources embedded in their organization would own the future, while those firms that isolate KM risk losing innovation of research and development (R&D) departments. In recent years, some studies have dealt with the relationship between KM and innovation (Gilbert and Cordey-Hayes, 1996; März et al., 2006; Popadiuk and Choo, 2006; Singh, 2008). However, most studies have not empirically investigated how firms can enhance KM capability for improving innovation of R&D departments (R&D innovation).
Given these general arguments regarding the im- portance of KM capability for improving R&D innovation, additional foundation is required in exploring which KM enabler can be adopted to enhance KM capability. Lee and Choi (2003) indicated that KM enablers such as structure and culture are used to influence the knowledge creation processes more effectively. Grover and Davenport (2001), from the KM perspective, held that KM initiatives are the key determinants of a firm’s KM. Four
*Corresponding author. E-mail: joyce@asia.edu.tw. Tel: + 886- 4-2332-1176 ext. 48014. Fax: + 886-4-2332-116.
Abbreviation: KM, Knowledge management.
variables may enhance KM capability, namely, knowledge-based technology, structure, culture and human resource. In our study, these four variables served as the KM related antecedents of KM capability and were examined to assess the potential of facilitating KM capability for R&D innovation.
Applying KM to R&D innovation suggests that broad, universal conclusions cannot be made regarding the nature of the relationship between innovation and firm performance. This is because innovation speed and magnitude vary according to the circumstances, such as the industry environment, to which they are applied (Gopalakrishnan, 2000). Researchers and practitioners have not tried a research model. Therefore, the primary objectives of this study are to delineate an integrative view of facilitating KM capability for improving R&D innovation and in turn for achieving firm performance, to seek which KM enablers can enhance KM capability and to provide strategic guidelines.
RESEARCH BACKGROUND AND LITERATURE REVIEW
Theoretical background
Innovation is treated as a strategic choice; a firm’s
behavior that is an outcome of its characteristics and a
determinant of firm performance (Kaul, 2002). This approach integrates elements of business strategic and knowledge-based theory. The strategic management emphasizes the importance of context while the knowledge-based view (Whitehill, 1997) places central importance within the firm. Competitive advantage is a management of the knowledge a firm has at its disposal and the capabilities it has to deploy its strategic assets (Whitehill, 1997). Managing knowledge refers to identifying and leveraging the collective knowledge in an organization to help innovation (Hall and Andriani, 2003).
Thus, studies in strengthening firm competition have emphasized three major factors: KM, innovation and performance (Thornhill, 2006). KM is an organizational mechanism for fostering consistent innovation (Hargadon, 1998). KM can be thought of as a structured coordination for effective innovation, represents the basic input of innovation (Gilbert and Cordey-Hayes, 1996;
Tarafdar and Gordon, 2007) and provides the infrastructure necessary for organization to increase the performance. Two major components (KM infrastructure and KM process) compose KM and an understanding of their interaction is important and useful for KM effective- ness (Gold et al., 2001). Thus, in order to improve inno- vation, organizations need an integrated model to depict the relationships among KM enablers, KM capability, innovation and firm performance.
Previous researches
Previous studies can be roughly classified into four categories depending on how the research identifies the relationships: (1) relationships between KM enablers (2) relationships between KM enablers and KM capability (3) relationships between KM capability and innovation (4) relationships among KM capability, innovation and firm performance.
The first category focuses on examining the effect of KM enablers. To identify this effect, Gold et al. (2001) investigated various KM infrastructures such as technological, structural and cultural aspects.
The second category examines the relationship between KM enablers and KM capability. A central propo- sition is that KM enablers should influence KM capability.
Gold et al. (2001) proposed that KM infrastructures and KM processes are essential organizational capabilities for effective KM. Some researches have specifically focused on the relationship between KM enablers and KM capabi- lity (Grover and Davenport, 2001; Lee and Choi, 2003) and indicate that KM enablers such as strategy, structure, culture and IT may facilitate KM such as acquisition, codification and transfer to generate KM results efficiently.
The third category explores the relationships between KM capability and innovation. Hall and Andriani (2003) describe how to bridge knowledge gaps to achieve
innovation; gaps occur between existing knowledge and knowledge requirements, particularly when a firm is trying to introduce new processes or products. The knowledge gaps concerned KM capability in the context of organization. Hall and Andriani (2003) noted that KM consists of externalization, dissemination, internalization, socialization and discontinuous learning associated with innovation of firms. Brand (1998) proposed that if a firm’s objective is to become the most innovative firm in the world, the firm requires the effective use of KM. März et al. (2006) described that the effective development of innovation focuses on underlying creating and sharing knowledge.
The fourth category examines the relationships among KM capability, innovation and firm performance. The primary objective of these studies is to identify KM capability for increasing innovation and firm performance.
Gilbert and Cordey-Hayes (1996) proposed a conceptual framework depicting how knowledge transfer helps achieve competitive success. The relationship between knowledge application process and innovation was also investigated. Thornhill (2006) noted that knowledge has an impact on innovation and revenue growth, as well as KM serves as an efficient support for the relationship between innovation and competitiveness.
RESEARCH MODEL
Figure 1 presents the integrated research model. In the research model, KM enablers, such as knowledge-based technology, structure, culture and human resource, are proposed to have an impact on the KM capability. The KM capability in turn affects R&D innovation, which consists of innovation speed and magnitude. The innovation speed and magnitude would then influence the firm performance. The rationale for these factors and the relationship among them is described in the following sections.
Definition of research variables KM enabler
KM enabler refers to firm’s infrastructure to enhance efficiencies of KM (Sarvary, 1999). KM enabler is a multi-dimensional construct; it requires the identification of the most strategic positions that differentiate KM capability. The four variables, that is, technology, structure, culture and human resource, can serve as a starting point in identifying the most strategic positions for firms (Lee and Choi, 2003). Starting with these variables, Lee and Choi (2003) proposed that the enablers could be analyzed by focusing on knowledge development in four primary strategic positions of the firm.
Therefore, this study started with the same strategic thinking.
However, it conceptualized the four variables quite differently. The traditional conceptualization viewed technology as general IT, structure as organizational structure, culture as organizational culture and human resource as general employees, which cannot suffice to create and explore knowledge resources. Therefore, as detailed below, this study redefined, expanded and transformed technology, structure, culture and human resource and proposed knowledge-based technology, knowledge-based structure, knowledge-based culture, and knowledge-based human resource as the four major dimensions of a firm’s KM enabler.
Figure 1. Research framework.
Knowledge-based technology is defined as the technical systems within a firm, which determine how knowledge travels throughout the enterprise and how knowledge is accessed. It includes information technology (IT) and its capabilities (Scott, 1998). IT contributes to knowledge management effectively (Sher and Lee, 2004). For example, business intelligence technologies enable a firm to generate knowledge regarding its competition and the broa- der economic environment. Knowledge application technologies enable a firm to use its existing knowledge. Knowledge-based structure refers to the extent of an organization’s structural disposition toward encouraging knowledge-related activities. The structures must be possible to encourage these vital interactions, as well as to give the firm the ability to adapt to an ever-changing environment (Sanchez and Mahoney, 1996). Knowledge-based culture describes the degree to which organization culture provides support for viewing knowledge as valuable assets and resources.
Culture is the most important factor for successful KM. For example, Dialogue between individuals or groups are often the basis for the creation of new ideas and can therefore be viewed as having the potential for creating knowledge. Knowledge-based human resource describes the extent to which employees specialize in a particular domain and demonstrate the capability of applying that knowledge to interact with others. The human
resource is at the heart of creating knowledge resources (Holsapple and Joshi, 2001).
KM capability
The KM enabler constructs developed focus on the firm’s strategic positions which capture whether the firm pursues a strategy of knowledge-based perspective. Pursuing a strategy of knowledge- based perspective holds a potential for improving R&D innovation.
However, performance potential of this strategy cannot be converted into actual R&D innovation results unless the firm has the capability to implement the strategy. Knowledge creation or transfer would benefit companies more than knowledge itself because knowledge is not primarily about facts but more about context- specific characteristics. Therefore, both strategic positions and knowledge activities (e.g., knowledge creation) are critical for improving R&D innovation. In order to implement strategy of knowledge-based perspective and to utilize knowledge resources, the firm needs a capability to manage knowledge resources.
The knowledge management capability of a firm is defined as the degree to which the firm creates, shares and utilizes knowledge resources across functional boundaries. This definition focuses on the firm’s KM activities at the organization level rather than at the department, team, or individual levels because the purpose of this study is to understand how the firm, that is, the organization, adds value to its departments. In this study, we examine firms’ KM capability in terms of their emphasis on three KM activities:
knowledge creation, sharing and utilization (Argote et al., 2003).
Knowledge creation refers to the degree to which the firm develops or creates knowledge resources across functional boundaries. The creation of knowledge resources does not occur in abstraction from the current knowledge and capability of the firm (Alavi and Leidner, 2001) since knowledge is path dependent (Cohen and Levinthal, 1990). The creation of knowledge across functional boundaries requires the capability to generate new applications from existing knowledge and to exploit the unexplored potential of new skills.
Knowledge sharing refers to the degree to which the firm shares knowledge resources across functional boundaries. To the extent that they can distribute each other’s knowledge and learning, departments can do things better together over time (Prokesch, 1997). The ability of sharing and distributing knowledge resources across functional boundaries enables the firm to fundamentally change its business processes. The sharing of knowledge resources not only facilitates cross-functional interaction but also allows the sharing of knowledge repositories among process partici- pants, thereby allowing greater collaboration and understanding of the entire process rather than having fragmented parts of the process.
Knowledge utilization refers to the degree to which the firm applies the knowledge resources that are shared across functional boundaries. It allows the firm to reap returns on its knowledge resource. A firm may have capabilities in creating, sharing and utilizing knowledge resources, but these capabilities are irrelevant if the firm cannot ultimately utilize the knowledge resources efficiently (Argote et al., 2003). The capability to utilize a related knowledge base in producing new products allows the firm to respond more effectively to changes in R&D environments, which, in turn, has positive R&D innovation effects such as new product launching. In the absence of firm capabilities to use and act on knowledge, knowledge resources cannot have a positive effect on R&D innovation.
These three KM activities collectively enable the firm to create new knowledge, to share and distribute existing knowledge across functional boundaries and to utilize the shared knowledge for improving R&D innovation. They co-exist, co-vary and overlap with each other and collectively define the firm’s KM capability. In a KM Enablers
Knowledge- based Technology
Knowledge- based Structure
Knowledge- based Culture
Knowledge- based Human Resource KM Capability
Creation
Sharing Utilization
R and D Innovation Firm Performance
Innovation
Speed Innovation Magnitude R &D innovation
review of KM studies in IS literature (Tanriverdi, 2005), four interrelated activities (that is, creation, transfer, integration and leverage of related knowledge) have been identified to enable a firm to develop and employ KM capability. KM capability enables the firm to create and realize knowledge-based synergies across functional boundaries so that individual departments are worth more under its governance than they would be under the governance of separate departments.
R&D innovation
Generally, firms’ sustainable competitive advantage requires that the firms continuously differentiate their products and services from competitors (Chen et al., 2009; Koellinger, 2008). In other words, firms must constantly undergo innovation. This innovation requires a well-planned KM capability that will enable the firm to excel in knowledge-based synergies. These synergies may enhance a firm’s chances of creating and implementing innovation (King and Zeithaml, 2003). They can constrain and direct an R&D department’s ability to take action and differentiate itself from competitors. Several definitions of innovation were made by Garcia and Calantone (2002). They proposed that if an idea has not been developed and transformed into a product, process, or service, or if it has not been commercialized, then it would not be classified as an innovation. Innovation comprises the speed and magnitude and this categorization provides an effective method of investigating the link between innovation and firm performance (Gopalakrishnan, 2000). In this study, Innovation speed reflects an R&D department’s quickness to generate a product or process relative to its competitors within the industry. Innovation magnitude refers to the degree to which the R&D department generates a number of new ideas, products, processes, or services. Meyer (1993) argued that organizations increase the pace of innovation to enhance business value. In order to investigate the impact of innovation on firm performance, our research model incorporated innovation speed and magnitude, which are the seeds of all innovations (Gopalakrishnan, 2000) and which are at the very core of KM.
Firm performance
The measurement of firm performance can include financial measures, tangible and intangible benefits and intellectual capital.
No single measure may fully explicate all aspects of performance.
Adopting perceptual measures as a proxy for objective measures of IT business value is still open to debate (Ford and Schellenberg, 1982). However, in the absence of objective data on IT payoffs, executives’ perceptions can at least pinpoint where IT is creating value for the firm. Moreover, research has succeeded in alleviating the concerns by showing that the perceptual measures of firm performance correlate strongly with more traditional objective measures including sales growth, net income growth and return on investment (Tallon et al., 2000). For this reason, in our study, firm performance was assessed using subjective measures such as market share (Ford and Schellenberg, 1982; Subramanian and Nilakanta, 1996), sales growth (Lee and Choi, 2003; Subramanian and Nilakanta, 1996), profitability (Lee and Choi, 2003;
Subramanian and Nilakanta, 1996), efficiency of operations (Gopalakrishnan, 2000), and quality of services (Gopalakrishnan, 2000) in comparison with key competitors.
Hypotheses
Knowledge-based technology is essentially an organizational capability for effective KM. Organizations should establish an appropriate IT that encourages people to generate knowledge. IT
can facilitate rapid knowledge collection, storage and exchange (Sher and Lee, 2004); thus, it does not only integrates fragmented knowledge flows (Gold et al., 2001) but also conserves existing knowledge and helps to create new knowledge. Therefore, we expect that knowledge-based technology should have a positive impact on KM capability.
H1: Knowledge-based technology has a significant positive influence on KM capability.
The organizational structure within a firm may encourage or inhibit knowledge creation, sharing, and application (Nonaka and Takeuchi, 1995). Our study examines the knowledge-based struc- ture within a firm that may encourage knowledge, a practice seen as vital in the effective management of knowledge. The structure must be appropriate to the firm in order to adapt to an ever- changing environment. Therefore, we expect that knowledge-based structure should have a positive impact on KM capability.
H2: Knowledge-based structure has a significant positive influence on KM capability.
An appropriate culture within a firm can encourage people to create and share knowledge (Holsapple and Joshi, 2001; Leonard-Barton, 1995). A knowledge-based culture fosters this knowledge dissemination so that employees understand the value and significance of knowledge (Leonard-Barton, 1995). Therefore, we expect that knowledge-based culture should have a positive impact on KM capability.
H3: Knowledge-based culture has a significant positive influence on KM capability.
The knowledge embodied in humans is most often associated with KM capability. For example, Iansiti (1993) insisted that humans possess knowledge of not only being competent with a discipline but also of knowing how the discipline interacts with other disci- plines. Humans possess knowledge that is extremely valuable for creating further knowledge because they are capable of integrating diverse knowledge resources (Leonard-Barton, 1995). Therefore, we expect that knowledge-based human resources should have a positive impact on KM capability.
H4: Knowledge-based human resources have a significant positive influence on KM capability.
KM plays an important role in innovation ability (Chen and Huang, 2009; Popadiuk and Choo, 2006). Through KM capability, knowledge resources add most value to organizational activities, such as innovations (Holsapple and Joshi, 2001). Effective knowledge generation mechanisms enable the R&D department to innovate rapidly (Nieto and Quevedo, 2005). Research also indicates that innovation speed to market, which is essential for business success, will become increasingly critical in the future. KM capability is thus considered to be knowledge-based synergies, which might accelerate innovation speed. Based on these arguments, we hypothesize the following:
H5: KM capability has a significant positive influence on innovation speed.
With a growing interest in the literature concerning the significance and implications of KM capability, previous studies have proven the
impact of KM on innovative activity (Hall and Andriani, 2003).
Questions have then been raised regarding whether R&D departments adopting KM are receptive to the idea of innovation, or whether they continually develop new products or new processes. If this reasoning should prove true, then KM should enable R&D de- partments to promote innovation magnitude. Innovation magnitude is not necessarily related to employee knowledge but rather to the manner in which knowledge is created, shared and used. KM capability is thus considered as knowledge-based synergies, which may lead to improved innovation magnitude. Based on these arguments, we hypothesized the following:
H6: KM capability has a significant positive influence on innovation magnitude.
Innovations provide a key to understand the link between innovation and firm’s effectiveness and performance (Irwin et al., 1998; Thornhill, 2006). Robinson (1990) has demonstrated that over a broad cross-section of industries, firms that stress innovation speed increase their market share. Additionally, when an R&D department produces innovations faster than its competitors, the organization is able to erect market segments because knowledge contained in these innovations is not readily available to com- petitors (Lieberman and Montgomery, 1988). The early adoption of product innovations increases the market segment in association with service quality and operating efficiency. Therefore, based on these arguments, we test the following hypothesis:
H7: Innovation speed has a significant positive influence on firm performance.
Gopalakrishnan (2000) describes that a higher magnitude of innovation involves synonymously adopting numerous new products, processes and practices across a broad cross-section of organizational activities. Such new product development requires firms to create synergies among these multiple activity domains.
However, such synergies must be created in a manner that is inimitable and encourages competitiveness. Other studies have found that organizations benefit from increased ideas and more innovative R&D are more effective in achieving firm performance than less innovative R&D (Chesbrough and Crowther, 2006). Based on these arguments, we test the following hypothesis:
H8: Innovation magnitude has a significant positive influence on firm performance.
METHODOLOGY
This section presents a brief description of the sample and an overview of the survey procedure used in this study. It then describes how the research variables are operationalized and measured.
The sample and data collection procedure
The subjects of this study are the companies in manufacturing industry in Taiwan, all of which are in the top 1000 ranking in terms of sales revenues. These firms maintain similar applications and organization resources, alleviating moderating effects of the economy and industry. In addition, the manufacturing industry has fundamentally changed during recent years owing to an increasingly turbulent environment. The manufacturing environment is evolving from homogenous national markets towards heterogeneous global markets. Traditionally, firms compete in
homogeneous markets with competitors that have access to the same capital resources and the same knowledge asset base.
Recently, firms have begun competing in heterogeneous markets where competitors have access to diverse capital and knowledge asset conditions and must implement various management prac- tices (e.g., knowledge management) to improve competitiveness.
This study investigated informants who are most knowledgeable, able and willing to report about knowledge-based technology, structure, culture and human resource, management of creation, sharing and utilization knowledge and firm performance at the firm level, as well as innovation speed and magnitude at the R&D department level. Therefore, senior managers and R&D managers were identified as the most appropriate informants for this study.
Two surveys were used to collect the primary data. Questions aiming to measure R&D innovation were organized in a survey entitled “R&D survey” and were sent to R&D managers of the largest manufacturing firms in Taiwan. Meanwhile, questions aiming to measure KM enabler, KM capability and firm performance were organized in a separate survey entitled “business survey.” The package contained a cover letter, a questionnaire and a prepaid reply envelope. Discussions with content experts and practitioners indicated that the questions of the business survey are generic enough to be answered either by a Chief Executive Officer (CEO) or a senior manager. In order to increase the chances of receiving a response from a firm, the business survey was sent to both officers.
The original sample of this study consisted of Taiwan’s top 1000 enterprises from Common Wealth Magazine. However, 405 of these firms were dropped from the sample either because they are non manufacturing firms or they do not have an R&D department. Out of the remaining 595 firms, 156 firms responded to the business survey (26% response rate), whereas 195 firms responded to the R&D surveys (33% response rate). Moreover, 118 firms responded to both the business and R&D surveys (20% response rate). To check the diversity of responding firms within the manufacturing sector, two key characteristics were analyzed: industry type and organizational size. A profile of the responding firms in terms of these criteria is shown in Figure 2 (a, b and c). The traditional dominance of the textile, machinery and electric equipment industries in Taiwan is reflected in the industry profile. In Figure 2a, for example, vertical and horizontal axis is labeled as “industry type”
and “numbers of firms” respectively to reflect the distributions of our samples on the industry types. In addition, almost 64% of the firms had revenues ranging from $3.1 billion to 20.1 billion and four of the firms had fewer than 100 employees.
Measurement of the variables
A multiple-item method was used to construct the questionnaires.
All of the items were rated on a seven-point Likert scale ranging from strongly disagree (1) to strongly agree (7).
KM enabler
KM enablers were operationalized based on the works of Gold et al.
(2001) and Grover and Davenport (2001). The index measures organizational resources by focusing on four dimensions such as knowledge-based technology, knowledge-based structure, knowledge-based culture and knowledge-based human resource.
Knowledge-based technology was measured using six items. The items assessed the applications of technology-related resource to knowledge activities such as daily operations and abilities to retrieve and use knowledge. Knowledge-based structure was mea- sured using three items which reflect an organization’s structural facilitation for knowledge discovery, knowledge creation, and know- ledge sharing. Knowledge-based culture was measured using three items, which reflect an organization’s cultural support for viewing
Figure 2. (a). Industry type (b). Sales revenue (c) Organizational size.
for viewing knowledge as value assets. Knowledge-based human resource was measured using three items, which reflect employees’
domain knowledge and their application of this knowledge in various tasks.
KM capability
KM capability was measured by three interdependent KM activities:
the creation of knowledge resources across functional boundaries,
the sharing of knowledge resource across such functional boundaries and the utilization of knowledge resource.
Therefore, this study evaluates KM capability by measuring the extent to which the organization engages in or supports the creation, sharing and utilization of knowledge resources across functional boundaries.
Knowledge creation was operationalized by asking the informants about the degree to which the organization engages in or supports the creation of knowledge resources across functional boundaries. Meanwhile, knowledge sharing is determined by
b c
Less than $3 Billion
$.3.1 Billion to below $4.1 Billion
$4.1 Billion to below $6.1 Billion
$6.1 Billion to below $8.1 Billion
$8.1 Billion to below $10.1 Billion
$10.1 Billion to below $20.1 Billion
$20.1 Billion and above
0% 20% 40% 60% 80% 100%
inquiring from the informants about the degree to which the organization engages in or supports the sharing and distribution of knowledge of individual function, which may also be applicable across other functional boundaries. Lastly, knowledge utilization was operationalized by asking the informants about the degree to which the organization engages in or supports the utilization of knowledge across functional boundaries.
R&D Innovation
Innovation measurement was adapted from Gopalakrishnan’s study. The innovation of R&D departments includes speed and magnitude. Innovation magnitude was measured using five items which reflect the total number of new products, processes, and practices. Innovation speed was operationalized using five items;
these items reflect firm quickness to generate a product or process.
Chen and Hambrick (1995) have used similar measures to operationalize firm response speed to competitive actions initiated by other firms.
Firm performance
Firm performance includes market share gain, sales growth, profitability, efficiency of operations and quality of services. This study adopts a specific measure, which is developed and validated by Deshpande et al. (1993). This measure can be regarded as a variation of the balanced scorecard method. The balanced scorecard retains financial performance and supplements it with measures on the drivers of future potential.
All the measures used in this study are reported in Appendix A.
RESEARCH ANALYSES AND RESULTS Reliability and validity analyses
Table 1 shows the results of reliability and validity tests.
Cronbach’s alpha was used for examining the reliability of the instruments. Four factors (technology, structure, culture, and human resource) in KM enabler, two factors (speed and magnitude) in innovation, and KM capability factor all have values higher than the 0.70 cutoff values, ranging from 0.792 to 0.952. The firm performance factor shows Cronbach alpha scores of 0.904 with four items retained. Additionally, factor analysis was used to check discriminant validity. Because each variable was measured by multi-item constructs, factor analysis with varimax was adopted to check the unidimensionality among items. Hair et al. (1998) suggests that items with factor loading values lower than 0.5 may be deleted. One item with factor loading of lower than 0.5 for firm performance was thus deleted. A factor analysis for the KM enabler and innovation is shown in Table 2. Relatively high values of reliability and validity imply that the instruments used in this study are adequate.
Research results
The intent of our study is to prove the relationship among KM enabler, KM capability, R&D innovation and firm
performance. The hypothesized relationships are tested using regression analysis. Table 3 summarizes our regression results.
Hypotheses 1, 2, 3, and 4 examine the effects of KM enabler on the KM capability. To investigate the hypothesis, entering all variables in a single block, we found that the proposed model explains a significant percentage of variance in KM capability (R
2= 55.5%, F- value = 35.274, p < 0.001). Specifically, the study results show that knowledge-based technology has a significant positive influence on KM capability ( = 0.486, t-value = 7.743, p < 0.001). Furthermore, the knowledge-based structure ( = 0.219, t-value = 3.490,
p < 0.01),knowledge-based culture ( = 0.488, t-value = 7.779, p <
0.001) and knowledge-based human resource ( = 0.182, t-value = 2.908,
p < 0.01) variables are all found to beessential for KM capability. Therefore, hypotheses 1, 2, 3 and 4 are supported.
Hypotheses 5 and 6 examine the link between KM capability, and innovation speed and innovation magnitude. Results indicate that KM capability has a positive impact on innovation speed ( = 0.505, t-value = 6.302, p < 0.001), and KM capability also has a positive impact on innovation magnitude ( = 0.581, t-value = 7.628,
p < 0.001). Therefore, hypotheses 5 and 6 aresupported.
In hypotheses 7 and 8, we investigate the influence of innovation speed and innovation magnitude on firm performance. Entering all variables in a single block and eliminating poor predictors, we obtained the model in Table 3 as a result of the multiple regression analysis.
Results show that 58.1% of the variance for firm perfor- mance is explained by innovation speed and innovation magnitude. Innovation speed has a significantly strong and positive influence on firm performance ( = 0.621, t- value = 10.190,
p < 0.001). Also, innovation magnitudehas a significant effect on the firm performance ( = 0.443, t-value = 7.269, p < 0.001). Therefore, Hypotheses 7 and 8 are supported.
DISCUSSION
The advantages that the KM enablers bring can be described using four categories to reflect KM capability:
knowledge-based technology, structure, culture and human resource. The results confirmed that the support of knowledge-based technology affects KM capability.
Knowledge-based technology is important to establish new knowledge and provide rapid retrieval of knowledge innovative in various tasks. For instance, with their expertise, employees can be more capable of creating new knowledge and this would lead to a higher capability of knowledge management. In summary, the results imply that the knowledge-based technology, structure, culture and human resource can facilitate KM capability.
The results of regression analysis showed that KM ca-
pability has a significant impact on innovation speed and
Table 1. Statistics for reliability and validity tests.
Measure Number of items Mean S. D. Cronbach Factor loading
KM enablers
Knowledge-based technology 6 5.46 1.01 0.887 0.766
5.73 0.98 0.662
5.23 1.07 0.633
4.96 1.00 0.579
5.35 0.99 0.833
5.69 0.88 0.758
Knowledge-based structure 3 5.72 0.91 0.792 0.627
5.77 0.91 0.847
5.86 0.87 0.764
Knowledge-based culture 3 5.02 1.17 0.903 0.835
5.01 1.10 0.819
5.45 1.03 0.568
Knowledge-based human resource 3 5.75 0.79 0.868 0.787
5.62 0.94 0.854
5.45 1.14 0.873
KM capability 10 4.87 1.23 0.952 0.851
5.10 1.14 0.921
5.00 1.15 0.923
5.23 1.09 0.777
4.97 1.03 0.813
5.02 1.19 0.854
5.36 1.06 0.869
5.25 1.09 0.887
5.48 0.90 0.782
5.13 1.24 0.712
Innovation
Innovation speed 5 4.84 1.28 0.945 0.621
4.54 1.37 0.872
4.65 1.39 0.901
4.64 1.37 0.870
4.97 1.20 0.779
Innovation magnitude 5 5.02 1.25 0.927 0.870
4.67 1.23 0.774
4.76 1.16 0.746
4.86 1.18 0.805
4.78 1.16 0.818
Firm performance 5 4.82 1.34 0.904 0.867
4.83 1.30 0.921
5.00 3.82 0.233
5.03 1.14 0.890
5.18 1.10 0.848
Table 2. Rotated factor matrixes with varimax rotation.
(a) Item construction for KM enablers
Variables Factor 1 Factor 2 Factor 3 Factor 4
KT1 0.766 0.173 0.315 0.187
KT2 0.662 0.240 0.278 0.242
KT3 0.633 -0.160 0.501 0.213
KT4 0.579 0.210 0.492 -0.180
KT5 0.833 0.256 0.190 0.093
KT6 0.758 0.269 0.039 0.261
KS1 0.145 0.386 0.360 0.627
KS2 0.113 0.240 0.064 0.847
KS3 0.255 0.133 0.133 0.764
KC1 0.262 0.282 0.835 0.211
KC2 0.264 0.247 0.819 0.183
KC3 0.536 0.092 0.568 0.160
KH1 0.105 0.787 0.277 0.301
KH2 0.331 0.854 0.087 0.231
KH3 0.216 0.873 0.176 0.155
(b) Item construction for innovation
Variables Factor 1 Factor 2
IS1 0.618 0.621
IS2 0.385 0.872
IS3 0.238 0.901
IS4 0.391 0.870
IS5 0.375 0.779
IM1 0.870 0.178
IM2 0.774 0.394
IM3 0.746 0.461
IM4 0.805 0.377
IM5 0.818 0.371
and magnitude. As expected, this study provided empirical evidence that R&D departments with KM, besides having greater willingness to innovate, also commercialize innovations faster than their competitors.
Particularly, a more careful investigation of innovation is of interest. Innovation involves new ideas, processes and products. From this perspective, KM capability may exhibit the spontaneity and freedom of knowledge necessary for innovation. For example, product and process innovations are associated with knowledge that may be embedded and stored in organizational systems.
All knowledge is initially created by individuals and then becomes organizational knowledge when it is transferred and shared throughout the organization. Therefore, R&D innovation is enhanced through KM capability and consequently, R&D innovation is positively influenced by KM capability. In summary, R&D innovation may include the two different aspects of innovation: speed and magnitude. KM capability can facilitate the rapid and continuous adoption of novelty and can also improve the
widespread adoption of novelty.
The influences of R&D innovation on firm performance were addressed as follows from two perspectives:
innovation speed and innovation magnitude. The results
demonstrated that innovation speed affects firm
performance significantly. This result mirrors that of
previous studies (Thornhill, 2006). For example, Thornhill
provided a framework linking innovation and performance
and indicated that knowledge enables people to innovate
more quickly to achieve firm performance. For instance,
the early adoption of process innovations reduces the
costs associated with servicing product innovations and
this in turn allows the organization to improve operating
efficiency. Therefore, firms with KM can considerably
resource. Other studies also revealed information
technology as a facilitator for enhancing KM (Grover and
Davenport, 2001). The knowledge-based structure within
an organization encourages employees’ interactions,
which are regarded as vital practices in the effective
management of knowledge. This structure grants the firm
Table 3. Results of hypothesis tests.
Model R2 t-value
(a) Firm performance (FP)
FP = IS + IM + errors 0.581
IS 0.621 10.190***
IM 0.443 7.269***
(b) Innovation speed (IS)
IS = KC + errors 0.258 0.505 6.302***
(c) Innovation Magnitude (IM)
IM = KC + errors 0.338 0.581 7.628***
(d) KM capability (KC)
KC = KT + KS + KC + KH + errors 0.555
KT 0.486 7.743***
KS 0.219 3.490***
KC 0.488 7.779***
KH 0.182 2.908**
*p < 0.05; ** p < 0.01; *** p < 0.001. FP = firm performance; IS = innovation speed; IM = innovation magnitude; KC = KM capability; KT = knowledge-based technology; KS = knowledge-based structure; KC = knowledge-based culture; KH = knowledge-based human resource.
the necessary capability to adapt to a knowledge- intensive environment. The knowledge-based culture has been proven to be supportive for knowledge-related activities. For example, knowledge is shared since the culture can understand the importance of knowledge.
Knowledge-based employees play a very important role in shaping KM activities because they can be more outperform their competitors by adopting R&D innovations early. Next, the results also demonstrated the significant impact of innovation magnitude on firm performance. This finding generally coincides with that of previous research. In their study, Subramanian and Nilakanta (1996) found that the magnitude of technical and administrative innovation is positively linked to firm performance. Additionally, Yamin et al. (1999) stated that a study of manufacturing firms demonstrated that firm performance differs significantly between high and low innovation index firms. For example, firms with a high magnitude of product innovations tend to capture the largest and the most attractive market segments and the visibility of such innovation efforts results in establishing customer loyalty.
Conclusions
Theoretical implications
This study sought to contribute towards filling the gap in the literature on the capability of KM enablers to enhance KM capability. In particular, statistical evidence was found
that suggests knowledge-based technology, structure, culture, and human resource to enhance KM capability. In other words, the enhancement of KM capability stresses the importance of knowledge-based technology, struc- ture, culture, and human resource as key determinants.
Moreover, an integrated framework was proposed for empirically investigating the link between KM enablers, KM capability, R&D innovation, and firm performance.
While being positively affected by KM enablers, an organization’s KM capability was shown to have a positive impact on its innovation speed and innovation magnitude. Advanced R&D innovation was also proven to significantly increase firm performance. However, our framework can help formulate robust strategies and may be used as a stepping stone for further empirical research that KM impact on R&D innovation.
Implications for management
From a practitioner’s point of view, interconnecting these
variables may provide a clue as to which factors can
enhance KM capability to improve R&D innovation and in
turn to achieve firm performance. The results can help
Chief Executive Officers (CEOs) establish distinctive
strategic positions. Knowledge-based strategies can be
described along two dimensions to reflect KM focus. One
dimension refers to knowledge-based perspective,
specifically involving technology, structure, culture, and
human resource of the firm. The other dimension refers to
the KM capability to help create and realize knowledge-
based synergies across functional boundaries. Moreover, the framework enables CEOs to assess whether the firm has knowledge-based perspective and the firm possesses KM capability to exploit existing knowledge- based synergies or to create new synergies. Based on these assessments, CEOs can decide whether the firm should enter into a new R&D organization or exit from an existing R&D organization. In other words, the framework suggests that the firm should enter into a new R&D organization if it has knowledge-based synergies within its existing organizations. Likewise, it suggests that the firm should exit from R&D organizations that do not have any knowledge-based synergies throughout organizations. However, the strategy of knowledge-based perspective does not automatically translate into superior innovation of R&D departments. CEOs should manage technology, structure, culture, and human resource in a knowledge-based way and assess whether the firm has the KM capability to create, maintain, and exploit the knowledge-based synergies for superior innovation of R&D departments. The results also imply that CEOs should pay more attention to R&D innovation in order to achieve firm performance. When CEO decides that innovation speed is a strategic priority, knowledge-based resources and attention should be focused on R&D internal generation processes, which include the product development and commercialization. On the other hand, if innovation magnitude is a strategic priority, the R&D process could be outsourced and the firm can concentrate its efforts on assimilation of innovations that have been developed elsewhere.
Limitations and future lines of study
Although the results are interesting and promising, they need to be viewed with caution because there are limitations in this research. This study focused on manufacturing firms. Thus, caution should be exercised in generalizing the results to other firms that have a different environment and competitive structure. This study also suggests several promising avenues for future research.
One is to explore the extent to which these results can be replicated in other industries, such as the banking industry, in which knowledge appropriation functions differently as compared to the manufacturing industry.
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Appendix A. Questionnaire.
Construct Items
Knowledge-based technology KT1: Our company has clear rules for formatting its product knowledge.
KT2: Our company has clear rules for formatting process knowledge.
KT3: Our company uses technology to cooperate with an inside person.
KT4: Our company uses technology to search for new knowledge in our company.
KT5: Our company uses technology to retrieve knowledge about its products and processes.
KT6: Our company uses technology to retrieve knowledge about its markets and competition.
Knowledge-based structure KS1: Our company structure facilitates the discovery of new knowledge.
KS2: Our company structure facilitates the creation of new knowledge.
KS3: Our company structure facilitates knowledge sharing.
Knowledge-based culture KC1: Employees understand the importance of knowledge.
KC2: Employees are valued for their individual expertise.
KC3: The benefits of sharing knowledge outweigh the costs.
Knowledge-based human resource
KH1: Employees understand not only their own task’s knowledge but also others’ task knowledge.
KH2: Employees perform their own task effectively without regard to environmental changes.
KH3: Employees are specialists in their own part.
KM capability KM1: Our company creates new knowledge for application across functional boundaries.
KM2: Our company creates operation systems for application across functional boundaries.
KM3: Our company creates managerial policies and processes for application across functional boundaries.
KM4: Our company engages in the process of distributing knowledge among departments.
KM5: Our company has a standardized reward system for sharing knowledge.
KM6: Our company designs activities to facilitate knowledge sharing across functional boundaries.
KM7: Our company engages in processes of integrating different sources of knowledge across functional boundaries.
KM8: Our company engages in processes of transferring knowledge to employees across functional boundaries.
KM9: Our company engages in processes which apply experiential knowledge across functional boundaries.
KM10: Our company engages in processes which apply knowledge to solve new problems across functional boundaries.
Innovation magnitude IM1: Our R&D department has produced many novel ideas.
IM2: Our R&D department has produced many new products.
IM3: Our R&D department has produced many new processes of product.
IM4: Our R&D department has produced many new actives of operation.
IM5: Our R&D department has produced many new decision making processes.
Innovation speed IS1: Our R&D department is quick in coming up with novel ideas as compared to key competitors.
IS2: Our R&D department is quick in new product launching as compared to key competitors.
IS3: Our R&D department is quick in new product development as compared to key competitors.
IS4: Our R&D department is quick in new processes as compared to key competitors.
IS5: Our R&D department is quick in problem solving as compared to key competitors.
Firm performance FP1: Our company has a greater market share than its key competitors.
FP2: Our company is growing faster than its key competitors.
FP3: Our company is more profitable than its key competitors.
FP4: Our company has a greater efficiency of operations than its key competitors.
FP5: Our company has a greater quality of services than its key competitors.
