Keywords

Knowledge Management Process, Learning Habitat, T-Shaped Skill, Information Technology, Knowledge-Intensive Company, Indonesia

Introduction

The process of managing individual knowledge into organizational knowledge for creating new knowledge is well explained by Nonaka & Toyama (2015). Those knowledge management processes are described as socialization, intensification, combination, and internalization (SECI) processes. However, an effective knowledge management process is unlikely to work without the establishment of a conducive learning habitat (Kristinawati & Tjakraatmadja, 2017). This study examined two Indonesian knowledge-intensive manufacturing companies. The company A produces aerospace products while the company B produces defense and military vehicles. The majority of both companies’ employees are skilled-labor, therefore the companies’ most valuable asset is the workers’ knowledge and how it can be managed to be an organizational knowledge. The companies collaborate with external parties for the development, manufacturing and marketing of its products. Therefore, T-shaped skill employees are desirable knowledge workers. The vertical bar of the letter “T” refers to knowledge in a particular area, while the cap of the letter “T” (horizontal) refers to ability for collaboration with knowledge workers in other disciplines. It also reflects a willingness to use the knowledge resulted from the collaboration (Leonard, 1995). Another factor contributing for effectiveness of knowledge management process is information technology (IT) support. Companies attempting to implement knowledge management are often focused in investing in information technology infrastructure (Lee & Choi, 2013). This also happened in the companies we studied. Therefore, it needs to be further investigated how strong the influence of IT for knowledge management process.

With the sample of 239 employees from two knowledge-intensive manufacturing companies in Indonesia, the study is expected to provide an insightful explanation of the effective knowledge management process influenced by learning habitat, t-shaped skill and information technology.

Literature Review and Hyphotheses

Learning Habitat and Knowledge Management

The core of knowledge management process is to effectively manage the transfer of knowledge through processes of socialization, extensification, combination and internalization (Nonaka &Takeuchi, 1995). Socialization is the process of sharing experiences and skills that reflects sharing tacit knowledge. Tacit knowledge is passed on between people or person to person. Externalization is the process of articulating or codifying tacit knowledge into an explicit one. Combination is a set of activities of utilizing explicit knowledge through different media. Internalization is “learning by doing process” in which explicit knowledge is embodied into tacit knowledge. From those processes, individual knowledge gained from either inter or intra organization are expected become organization knowledge. However, attracting employees to participate in SECI process requiring conducive learning habitat where people inside the organization have both willingness and ability to involve in learning and sharing of knowledge.

A flourishing learning habitat will grow valuable knowledge for organization. Hartanto (2009) defined a flourishing habitat for learning is characterized with mutual trust between employees, free from fear and suspicious of each other, that will stimulate knowledge sharing. A flourishing learning habitat is also manifested in living learning culture where employees show knowledge sharing, discussion of their tacit knowledge. Tacit knowledge is embedded inside the head of the people, mostly un-codified, specific and subjective. However, the tacit knowledge will be common knowledge if the knowledge is well communicated and becomes common understanding. At this point, common understanding only can be developed between people who actively interact and communicate in the working place. Previous study shows the effectiveness of knowledge management required the formation of conducive learning habitat (Tjakraatmadja, 2006). Therefore, we argue that learning habitat is positively related to effective KM process:

H₁ Learning Habitat has an effect on Knowledge Management process

Learning Habitat and T-shaped skill

As described above, a flourishing learning habitat characterized with mutual trust and living learning culture so that discussion and sharing both explicit and most importantly tacit knowledge will stimulate the development of unique organization knowledge. The process of sharing, discussion, interaction occurs both formal and informal where research shows informal interaction contribute significantly for the effectiveness of knowledge transfer (Jewels et al., 2003). The richness of informal channel for knowledge sharing through informal interaction will exercise employees to become T-shaped skill knowledge worker. T-shaped skill attributes for desirable knowledge workers. The vertical bar of the letter ‘T’ refers to knowledge or skill in a particular area, while the cap of the letter ‘T’ (horizontal) refers to ability for collaboration with knowledge workers in other disciplines. It also reflects a willingness to use the knowledge resulted from the collaboration. We argue that encouragement and facilities for continuous learning, as well as conducive environment to the establishment of a mutual trust will result in the collaborative manners for the development of T-shaped skills.

H₂ Learning habitat has an effect on T-shape skill

T-shaped Skill and Knowledge Management

Employees are source of knowledge, yet that knowledge only creating high value for both company and customer if there is an integration of synergistic or complementary knowledge. Through synergy collaboration between employee who has common goal and commitment, value can be created. When new knowledge is formed from various sources, it will have unique characteristic that in turn will become company’s competitive advantage. From the description above, T-shaped skill workers are valuable for knowledge creation, since they can assimilate and combine potential divergent knowledge asset (Leonard, 1995). Knowledge workers with the T type of skill will be valuable as company’s asset for their deep competence and flexibility to work cross unit. Also according to Lee & Choi (2013), T-shape skill will contribute to knowledge management process. Therefore, we argue:

H₃ T-shape skill has an effect on KM Process

Information Technology and Knowledge Management

As mentioned before, many companies attempting to implement knowledge management are often focused in investing in information technology infrastructure regardless their comprehension about knowledge management (Lee & Choi, 2013). This also happened in the companies we studied. Therefore, it needs to be further investigated how strong the influence of IT for knowledge management process. How knowledge is managed by investing in information technology infrastructure to enable explicit knowledge searching, documenting, and sharing [4]. Some authors have found that IT is a necessary aspect of KM process (Lee & Choi, 2013; Raven & Prasser, 1996; Davenport & Prusak, 1998). IT facilitates information’s acquiring and storing. Therefore, we argue:

H₄ IT has an effect on KM process

A research model proposing relationship among constructs can be depicted in Figure 1 below:

Methods

Research Context and Sample

This study examined two Indonesian knowledge-intensive manufacturing companies. The company A is a state-owned Enterprise that focuses on making transportation modes and aircraft components. The company has the ability to develop aircraft, including developing aircraft structures, aircraft assembly, and aircraft maintenance both for civil and military aircraft. The journey taken for developing aircraft requires decades of process. The company B produces military and defense equipment for Indonesian National Army and exports, such as arms, rocket, gun, turrets, tank, commando, and commercial explosive.

After obtaining permission from the senior management and conducting the initial interview, a sample of 200 employees for each company was planned, followed by questionnaires distribution. The level of employees is entry level with minimum of two years’ experience until mid-career professional with more than ten years of experience. A cover page explaining the aim of the study and confidentiality assurance is included in the questionnaires. The survey was sent to respondents directly through paper-based. The responses were submitted to top manager from each department, and then researchers take the responses in an average of two weeks after distribution. From the 400 questionnaire papers distributed, 140 were returned from company A, and 170 were returned from company B reflecting a high effective response rate of 77%. Examination of responses revealed that there were 109 and 130 usable responses from company A and company B respectively. Test managed on responses from the two companies revealed that there is a non-response bias problem. Respondent’s demographic analysis from both companies showed the main categories of management functions were manufacturing 41%, human capital 25%, training and development 16%, and quality assurance 18%.

Research Instruments

The variables were measured in instruments that had been previously developed or used in order to maintain the validity and reliability, as described in the discussion below. However, to accommodate study objectives the modification of wording was made to the research instruments.

For Knowledge Management Process, we asked the respondents to point out their level of agreement using a 5-point Likert type scale, ranging from strongly disagree to strongly agree. The following six items are adopted from the previous study by Lee & Choi (2013): (1) the company frequently facilitates dialogue forum between worker for knowledge transfer; (2) the company facilitates dialog between manager and worker for knowledge transfer; (3) company has documented senior worker’s knowledge in written or video form; (4) company has documented the result of dialogue forum in written or video form; (5) company has documented solution of technical problem in written or video form; (6) company has documented customer inputs in written or video form. Related to SECI, the first and second question reflected socialization and internalization process in which employees are facilitated to meet face to face dialogue in formal and or informal occassions. The third, fourth, fifth and sixth question indicated externalization process to codified organization knowledge. The fifth question also reflected combination process since the solutions of technical problem are combination of both tacit and explicit knowledge acquired from learning process.

For Learning Habitat, comprises of trust and learning culture as described in Tjakraatmadja & Lantu (2006) & Kristinawati & Tjakraatmadja (2017). We adopted four items: (1) teamwork is given opportunity and trust to adjust target; (2) teamwork believe their recommendation is taken seriously by the company; (3) worker is given enough time to learn; (4) each team member would review their opinions (learning) after information is collected and conducted a team dialogue.

For T-shape Skill, we adopted the criteria for T-shaped skill from Lee & Choi (2013) with four items as follows: (1) employees can give advice to the duties of other employees; (2) employees can communicate well inside and between division/department; (3) employees are experts in their field; (4) employees not only understand their own duties but also duties to other employees. For Information Technology, we used the criteria for IT support from Lee & Choi (2013) with four items: (1) company provides IT tools for collaboration; (2) company provides IT tools to support communication with fellow workers; (3) company provides IT devices to be able to locate and access important information; (4) company provides IT tools for simulation and prediction.

Statistical Test

A structural equation modeling with partial least square (PLS) was employed to test the hypotheses, because of its ability to handle multiple dependent and independent variables simultaneously. WarpPLS version 5.0 software is used for the study. The measurement model is exercised to evaluate the relationship between measures and constructs by checking the reliability of indicators relating to specific constructs (Chenhall, 2005). To assess construct validity, two measurements of convergent and discriminant validity are used. Convergent validity is assessed by extracting the factor and cross loading of all item indicators to their respective latent constructs. Discriminant validity objective was used to evaluate whether answers from different individuals to question-statements are either lightly or not correlated at all with other latent variables.

Result and Discussion

WarpPLS version 5.0 software is used for the study. To estimate t-statistics for the PLS structural path coefficient, a bootstrapping re-sampling procedure is employed (Hair et al, 2006). This study used a bootstrap sample of 500. To assess construct validity, two measurements of convergent discriminant validity are used. Convergent validity is evaluated by the average variance extracted (AVE) to be more than 0.50 for adequate convergent validity (Hulland, 1999; Fornell & Larcker, 1981). As can be seen in Table 1, the AVEs for all constructs are more than 0.50 for this study, therefore, indicating adequate convergent validity. The composite reliability coefficients for the constructs are all above accepted level of 0.70 (Nunnally, 1967).

Table 1 Assessment of the Measurement Model
Latent Variable	Composite Reliability	Average Variance Extracted (AVE)
KM Process	0.902	0.606
T-shaped Skill	0.834	0.557
Learning Habitat	0.840	0.568
Information Technology	0.865	0.616

Measurement model analysis reveals that all measures are significant and above 0.60 loading level, indicating the measures share more common variance with their respective constructs than with the error variance (Chin, 1998a; Chin, 1998b). The results presented in Table 2 showed that all item loaded are all higher than any other on their respective construct. Each item’s factor loading was highly significant (p<0.001) on its respective construct, as indicated by T-statistics of outer model loading output.

Table 2 Structure Loading and Cross Loading Assessment of the Measurement Model
INDICATORS	KM	T-shaped Skill	Learning Habitat	IT
KM1	0.746	0.273	0.426	0.389
KM2	0.755	0.337	0.454	0.403
KM3	0.766	0.288	0.419	0.322
KM4	0.820	0.323	0.361	0.280
KM5	0.815	0.321	0.354	0.296
KM 6	0.763	0.333	0.482	0.412
T-shape Skill 1	0.345	0.734	0.500	0.336
T-shape Skill 2	0.329	0.793	0.405	0.340
T-shape Skill 3	0.337	0.761	0.395	0.469
T-shape Skill 4	0.180	0.694	0.353	0.323
Learning Habitat 1	0.456	0.525	0.688	0.466
Learning Habitat 2	0.380	0.364	0.768	0.407
Learning Habitat 3	0.329	0.416	0.779	0.370
Learning Habitat 4	0.448	0.378	0.776	0.366
IT 1	0.351	0.357	0.422	0.737
IT 2	0.299	0.497	0.396	0.790
IT 3	0.377	0.365	0.429	0.808
IT 4	0.377	0.328	0.421	0.802

Discriminant validity evaluates whether a construct shares more variance with its measures than with other constructs, by comparing the square roots of AVEs to the correlation between constructs. For this study, the result is shown in Table 3. The square root of AVE of a construct is greater than the correlation between the construct indicating adequate discriminant validity.

Table 3 Discriminant Validity
	KM Process	Learning Habitat	IT	T-shaped skill
KM Process	0.778
Learning Habitat	0.533	0.754
IT	0.447	0.531	0.785
T-shaped skill	0.402	0.553	0.493	0.746

The structural model is depicted in Figure 2. The results show that learning habitat has an effect on knowledge management process (coefficient 0.380; p<0.01), which supported hypothesis H₁. Learning habitat also has an effect on T-shape skill (coefficient 0.580; p<0.01), which supported hypothesis H₂. Therefore, encouragement and providing facilities for continuous learning, as well as flourishing conducive environment to the establishment of a mutual trust will result in the collaborative manners for the development of T-shaped skills. While conducive learning habitat contribute to the effectiveness of knowledge management process, T-shaped skill has no significant effect to IT (p=0.03), which is not supported hypothesis H₃. This indicates that type of workers whether T-shaped skill or not, does not influence significantly to the process of knowledge management. IT has an effect knowledge management process (coefficient 0.190; p<0.01), thus it supported hypothesis H4. Information Technology is supporting element as a part of operation or production and channel of codified knowledge sharing.

Based on the findings, learning habitat and IT are two influencing factors for increase of KM process in organization. However, practically for an organization, focusing on one significant factor is more effective rather than focusing on two factors, as increasing one factor requires costs. The practical significance of the study is evaluated by effect size test as suggested by Hair et al.(2006) that used to estimate the extent to which our statistical findings exist in the population. The effect size of path learning habitat to KM Process is 0.203 According to Cohen (1988), this figure shows a medium to large effect, accordingly suggest practical significance. Path IT to KM Process has effect size 0.085, suggest small effect for practical significance. Therefore it is important for organization to prioritize their effort on learning habitat.

Conclusion

Employing a sample of 239 employees within two Indonesian knowledge intensive manufacturing companies, the study reveals that supportive learning habitat is required for effective knowledge transfers. It manifests in the mutual trust between employees that will stimulate knowledge sharing. A flourishing learning habitat is also manifested in living learning culture where employees show knowledge sharing, discussion of their tacit knowledge. Our study also shows that IT has a positive relationship with knowledge management process, which is reasonable since IT facilitates knowledge acquiring and storing (Lee & Choi, 2013; Davenport & Prusak, 1998).

From the study, we found a different result in the relationship between T-shaped skill and knowledge management process compared with the previous study of Lee & Choi (2013). They argue that the typical T-shaped skill worker is an enabler to effective knowledge management process, in which they have more tendencies to collaborate with others for knowledge sharing. Our study shows the insignificant result (p=0.03), meaning that for our context of study, there is no significant relationship of T-shaped skill to knowledge management process. By crosschecking with the interview, we examine it is caused by the majority of our samples (41%) are within the manufacturing department with infrequent job rotation. Majority of workers in manufacturing department do manufacturing routines in their entire tenure. Therefore, their opportunity to expand skill breadth is low, and collaborative engagement with cross-department is rare. This also becomes one limitation of our study, thus we suggest future research to proportionate the sample and reach out more departments involved in the survey. Regardless of the limitations above, we believe that this study provides empirical evidence on the importance of flourishing conducive learning habitat and providing Information Technology support for the effectiveness of knowledge management process.

Acknowledgement

The authors wish to acknowledge the Ministry of Higher Education for providing research grant, also the assistance of the two companies during data collection.

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