The Effects of Knowledge Characteristics and Absorptive Capacity on the Performance of Knowledge Transfer for SMEs: The Moderation Views of Organizational Structure

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The Journal of Human Resource and Adult Learning, Vol. 8, Num. 1, June 2012 30

The Effects of Knowledge Characteristics and Absorptive Capacity on the Performance of Knowledge Transfer for SMEs: The Moderation Views of Organizational Structure

Dr. Shin-Tien Chen, professor of Mingchi University of Technology, Taiwan Dr. Bao-Guang Chang, professor of Tamkang University, Taiwan

ABSTRACT

Following the perspective of organizational structure and knowledge management, this paper is to discuss two research questions: (1) how knowledge characteristics affect staff ’s absorptive capacity, and afterwards influences on the Performance of Knowledge Transfer; (2) whether organizational structure will mediate the relationship between knowledge characteristics and staff ’s absorptive capacity. Based on the sample of 171 SMEs, the empirical results showed that: (1) The higher the level of knowledge complexity, and the higher the staff’s absorptive capacity, the better the performance of knowledge transfer within the organization. (2) An organization structure with higher levels of coordination is more likely to affect positively the relationship between tacit knowledge and absorptive capacity. (3) An organization structure with higher levels of specialization is more likely to affect negatively the relationship between tacit knowledge and absorptive capacity. (4) An organization structure with higher levels of specialization is more likely to affect positively the relationship between knowledge complexity and absorptive capacity.

Keywords: knowledge characteristics, organizational structure, absorption capacity, knowledge transfer performance

INTRODUCTION

The characteristics of being flexible and hardworking of the small and medium enterprises (SME) contribute considerably to the economic development of Taiwan. In particular, for small and medium enterprises, being in the knowledge-based economic environment, knowledge seems to surpass traditional production factors, such as land, capital, and labor, and becomes a major driving force for business development. Therefore, being able to quickly access the knowledge needed for long-term business development, so as to enhance competitive advantages, becomes one of the major directions of SME’s strategic considerations. Currently, government is continuously pushing policies and measures, such as the Small Business Innovation Research Program (SBIR), the Service Sector Research Development Assistance Program and the SME Incubator Center, in order to encourage SMEs to play an active role in innovation research and development, and to implement knowledge management.

Knowledge transfer is one of the major sources for SME to access knowledge. Looking back at the research literature on knowledge transfer, it generally agreed that knowledge characteristics impact staff’s absorptive capacity, thereby affecting the performance of knowledge transfer. In this regard, this research believes that any SME inevitably possesses the knowledge in line with its survival and development, and each department within the enterprise holds the knowledge of its own special property. To a certain extent, knowledge transfer between various departments contributes to the overall enhancement of an enterprise’s

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The Journal of Human Resource and Adult Learning, Vol. 8, Num. 1, June 2012 31 management performance. In it, the key to a successful knowledge transfer lies in staff’s absorptive capacity. Therefore, this study suggests that concerning knowledge transfer within an enterprise, that although knowledge characteristics affect the performance of knowledge transfer, perhaps a staff’s absorptive capacity is really the key that affects the performance of knowledge transfer. On the other hand, from the organizational structure point of view, this study believes that the type of organizational structure plays a role in the factors of enhancing, or weakening, a staff’s absorptive capacity in the process of knowledge transfer. Furthermore, regardless of the vertical layering, or horizontal dividing of labor, it can simplify the complex knowledge needed for the job content and can balance employee interaction (Mintzberg, 1979), thereby contributing to the enhancement of a staff’s absorptive capacity in the process of knowledge transfer (Reed & Defillippi, 1990; Simonin, 1999).

As previously described, a SME’s knowledge characteristics and the absorptive capacity of the staff affect the performance of knowledge transfer. Interestingly, the type of organizational structure may enhance, or weaken, the staff’s absorptive capacity in the process of knowledge transfer within an enterprise. However, relevant literature on knowledge transfer from the past rarely involves exploration in this field. For this reason, this study combines relevant theories on knowledge management, from the organizational structure point of view, to further clarify the relationship between knowledge characteristics, absorptive capacity and the performance of knowledge transfer.

LITERATURE REVIEW AND HYPOTHESES ESTABLISHMENT

The Meaning of Knowledge and Knowledge Transfer

Knowledge is the result of information transfer (Nonaka, 1994). Davenport and Prusak (1998), in Working Knowledge, define knowledge as a complex body of information flow that contains various elements, including framed experiences, value, contextual information, expert insights, new experiences and information integration.

Knowledge transfer is a communication process between knowledge transfer and the staff, while the aim is to amplify the value and the function of knowledge (Awad & Ghaziri, 2006). In business, the overall effectiveness of knowledge transfer is not only exhibited in the internal performances of the cost reduction of knowledge transfer within the organization, the heightened satisfaction in the transferring process, and the continued accumulation of knowledge assets, but also in the external performance of service quality improvement brought to stakeholders like customers, or partners, and the enhancement of market effectiveness (Alavi & Leidner, 1999). Relevant literature in the past generally supports that, in the process of knowledge transfer, the skill level of information technology, absorptive capacity of the knowledge staff, and the type of organizational structure, affect the performance of knowledge transfer (Autio & Laamanen, 1995; Katz et al., 1996; Tan, 1996; Calabrese, 1997).

The Influence Factors of Knowledge Transfer Performance

Knowledge transfer performance refers to the staff’s performance in strengthening the corporate body, improving profitability, developing new product, and adopting technology, after the knowledge transfer (Tan, 1996). Past discussion on factors that affect knowledge transfer performance can be summarized as follows: (1) When technology is tacit, complex, and systematic, the performance of technology transfer is poor; when technology is explicit, simple, and independent, the performance of technology transfer is high. (2) The more the technology provider is involved, the higher the performance of the technology transfer (Zander & Kogut, 1995). (3) When the scale of the receiving technology is

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large (Ambrosio, 1995), and the experience of technology transfer is more sophisticated (Burgelman &

Rosenbloom, 1989), for those inclined to take initiative to import technology (Williams & Gibson, 1990), their technology transfer performance is better (Pucik, 1991). (4) When both parties of the technology transfer have good cooperation experience in the past, the technology transfer performance is better. (5) Staff intensive transfer performs better than documentation intensive transfer (Ounjian & Carne, 1987;

Cutler, 1989). (6) The performance of organizational learning affects the performance of knowledge management (Huber, 1991).

The Factors that Impact Staff’s Absorptive Capacity

The absorptive capacity of the knowledge staff is his ability to evaluate, internalize, and apply knowledge (Cohen & Levinthal, 1990; Zahra & George, 2002). The staff’s knowledge base, experiences, attitude, and ability, determine the level of absorptive capacity (Williams & Gibson, 1990; Pucik, 1991).

Szulanski (1996) points out that the knowledge staff’s lack of absorptive capacity will hinder the possibility of perceiving knowledge, and lower the performance of knowledge transfer. Minbaeva et al.

(2003) believes that a staff’s ability and motivation are the key factors in determining absorptive capacity.

In the process of organizational development, many empirical findings show specific human resource management activities have positive influence over the development of absorptive capacity (Minbaeva et al., 2003; Owen-Smith & Powell, 2004). Lenox and King (2004), on the mining research of absorptive capacity development, assert that if management makes information directly available to an agent in the organization, it may enhance enterprise absorptive capacity. While Lane and Lubatkin (1998) raise the concept of absorptive capacity to a dual-level, and propose that organizational absorptive capacity is determined by the similarity between knowledge provider and knowledge staff on knowledge base, organizational structure and incentive, and the dominant logic.

The relationship between Knowledge Characteristics, Absorptive Capacity and the Performance of Knowledge Transfer

In this study, knowledge characteristics include tacit knowledge and complex knowledge.

Tacit knowledge, in general, refers to personal beliefs, experiences and values. It is difficult to convey in words, difficult to share with others, and likely to cause difficulties in knowledge transfer, and thus becomes a learning barrier to the staff (Inkpen, 1996). Within an enterprise, tacit knowledge is an organizational experience accumulated over a long period of time, and is usually embedded in daily routines and operation processes (Nonaka, 1994). It can only be accumulated, or absorbed, through on-the-job training, apprenticeship, or learning by doing (Leonard-Barton, 1995).

For SME, because of their small in scale, their ability to access information is relatively weak, which leads to a shortage of information and a lack of knowledge accumulation, thereby weakening absorptive capacity of the company trained staff. When confronted by a great amount of knowledge, they have difficulties in decoding the more obscure knowledge with common language, which indirectly impacts innovation capacity, resulting in SME’s lagging behind as market followers. However, due to the SME characteristics of high flexibility, high mobility, and easy transformability, when they expand on their core capacity, and master some professional expertise, or key technologies, they can surpass peers and become market leaders. In the same industry, leaders usually inhabit professional technology that is difficult to imitate, or possess professional talents along with superb marketing ability. While the knowledge is highly tacit, it is the characteristic of this type of knowledge transfer within the organization to take longer, and the cost is higher, however, it is also difficult to absorb and to imitate by competitors

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The Journal of Human Resource and Adult Learning, Vol. 8, Num. 1, June 2012 33 in a short time. Thus, although highly tacit knowledge brings a competitive advantage to the enterprise, it relies on the absorptive capacity of the staff, in absorbing and applying in it a short time, to have an impact on the performance. Based on the above arguments, this study proposes hypothesis 1:

Hypothesis 1: In the process of knowledge transfer for SMEs, if tacit knowledge is high, and absorptive capacity of the staff is low, the performance of knowledge transfer is low.

The Relationship between Knowledge Complexity, Absorptive Capacity and the Performance of Knowledge Transfer

Being in a dynamic environment where technology changes constantly, the management of a SME requires not only a knowledge for its core competency, but also the support of management knowledge in the relevant fields (Hansen, 1999). In particular, much of the current knowledge is highly correlated and interdependent, and the technology, the process, and the professionals involved, are more complex than before (Teece, 1998). Under such circumstance, the complexity of knowledge can easily affect the staff’s understanding of overall knowledge, causing difficulties in absorption, and damaging the mobility of knowledge as well, while causing knowledge transfer within the organization to become inefficient (Kogut & Zander, 1993; Inkpen & Tsang, 2005). Based on the above arguments, this study proposes hypothesis 2:

Hypothesis 2: In the process of knowledge transfer for SMEs, if knowledge complexity is high, and absorptive capacity of the staff is low, the performance of knowledge transfer is low.

The Relationship among Knowledge Characteristics, Organizational Structure and Absorptive Capacity

The organizational structure named in this study includes four variables: the degree of formalization, the degree of centralization, the degree of specialization, and the structure of coordination.

The degree of formalization of an organization refers to the degree of standardization in job implementation processes (Robbins, 2003). High tacit knowledge of an organization is usually absorbed through apprenticeship, learning by doing, and frequent exposure, in order to accumulate knowledge.

Therefore, a highly formalized organization has difficulty in transferring tacit knowledge. Similarly, a highly centralized organization lacks communication and involvement with and between staff, and so the staff’s willingness to engage in works outside of their own is low. Under such circumstance, tacit knowledge is more difficult to absorb by these employees than those in other departments. Based on this argument, this study proposes hypotheses 3, 4.

Hypothesis 3: For SME, in an organization with higher degrees of tacit knowledge and higher degrees of formalization, its absorptive capacity in the process of knowledge transfer is lower.

Hypothesis 4: For SME, in an organization with higher degrees of tacit knowledge and higher degrees of centralization, its absorptive capacity in the process of knowledge transfer is lower.

The degree of specialization of an organization refers to the degree of labor divisions of organizational functions. An organization with a high degree of specialization can categorize complex knowledge, so that employees can easily understand and absorb. Coordination refers to interaction and communication between departments within an organization. A highly coordinated organization has frequent inter-department communication and good interaction, making inter-departmental knowledge flow smoothly. Therefore, highly tacit knowledge, through frequent interdepartmental staff exposure, and

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the specialization of various types of knowledge, can be easily transferred and absorbed. Based on this argument, this study proposes hypotheses 5, 6.:

Hypothesis 5: For SME, in an organization with higher degrees of tacit knowledge and higher degrees of coordination, its absorptive capacity in the process of knowledge transfer is higher.

Hypothesis 6: For SME, in an organization with higher degrees of tacit knowledge and higher degrees of specialization, its absorptive capacity in the process of knowledge transfer is higher.

The Relationship between Knowledge Complexity, Organizational Structure and Absorptive Capacity

An organization with a higher degree of formalization has clear documentation on any business activity, so in the situation of transferring knowledge with high complexity, it is easier for employees to absorb knowledge. An organization with a high degree of centralization usually mandates business learning within the organization, which lowers the participant’s resistance to the process of transferring complex knowledge, and enhances staff’s absorptive capacity of complex knowledge. An organization with a high degree of specialization has a more refined labor division, complex knowledge is thereby simplified, and the knowledge absorption is naturally faster. An organization with a high degree of coordination has a high frequency of communication between employees, and through an excellent coordination mechanism, knowledge absorption is naturally easier. Thus, this study proposes hypotheses 7-10:

Hypothesis 7: For SME, in an organization with higher degrees of complex knowledge and higher degrees of formalization, its absorptive capacity in the process of knowledge transfer is higher.

Hypothesis 8: For SME, in an organization with higher degrees of complex knowledge and higher degrees of centralization, its absorptive capacity in the process of knowledge transfer is higher.

Hypothesis 9: For SME, in an organization with higher degrees of complex knowledge and higher degrees of coordination, its absorptive capacity in the process of knowledge transfer is higher.

Hypothesis 10: For SME, in an organization with higher degrees of complex knowledge and higher degrees of specialization, its absorptive capacity in the process of knowledge transfer is higher.

RESEARCH METHOD

Conceptual Framework

Knowledge transfer means the interactivities of passing knowledge between two or more entities (Zander & Kogut, 1995). If knowledge is highly tacit, or if the interdisciplinary knowledge is highly complex, then, during the course of knowledge transfer, there will be knowledge ambiguity, increasing the difficulty of knowledge transfer. In essence, during the course of knowledge transfer, the experiences, learning motivation and absorptive capacity of the staff will affect the effectiveness of knowledge transfer (Szulanski, 1996; Simonin, 1999; Minbaeva, 2003). Literature reviews on knowledge transfer in the past, mainly focused on the relationship between knowledge characteristics and the performance of knowledge transfer. This kind of research approach ignores, in the process of knowledge transfer, that perhaps man is the main element of the key factors. Therefore, the first question this study intends to answer is: Is it

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The Journal of Human Resource and Adult Learning, Vol. 8, Num. 1, June 2012 35 through the absorptive capacity of the knowledge staff that knowledge characteristics affect the performance of knowledge transfer?

Personal beliefs, experiences, and values, or accumulated experiences of teams, departments, and organizations (Inkpen, 1996) are usually embedded in daily routines, or operational processes, within an organization (Nonaka, 1994). Knowledge staffs can only absorb this type of knowledge through on the job training, apprenticeship or learning by doing, communications between employees and frequent exposure. From the structure-affect-behavior point of view, whether the type of organizational structure should be formalization, centralization, coordination, or specialization, it is certain that they all affect absorptive capacity of enterprise employees. Does the organizational structure adjust the relationship between knowledge characteristics and absorptive capacity of the staff, thereby affecting the performance of knowledge transfer? Therefore, the second question this study intends to answer is: Can the organizational structure moderate the relationship between knowledge characteristics and absorptive capacity of the staff, thereby affecting the performance of knowledge transfer?

Combining the two previously proposed research questions, this study presents conceptual framework shown in Figure 1.

Figure 1: Conceptual Framework

THE OPERATIONAL DEFINITION AND MEASUREMENT OF VARIABLES

Knowledge characteristics are composed of two variables: tacit knowledge and complex knowledge.

Tacit Knowledge

This study adopts viewpoints from Zander and Kogut (1995) and Simonin (1999), in which the main argument highlights the knowledge embedded in the daily work routines, or operational process, that is difficult to convey with explicit written documentation. The measurement questions designed for this variable include four items, such as: Your company knowledge can be clearly conveyed, without personal experience, by documentation, and reports; Your company knowledge can only be understood through the passing of time … etc.

Formalization Centralization Specialization Coordination

Tacit Knowledge Complex Knowledge

Performance of Knowledge

Transfer Knowledge

Characteristics

Organizational Structure

Absorptive Capacity

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Complex Knowledge

This study adopts viewpoints from Howells (1996), Simonin (1999) and Hansen (1999), in which the main argument highlights that much of the technological knowledge within an organization depends on individuals, or groups, with various experiences for its existence, while the knowledge possessed by various individuals or groups is highly interdependent. The measurement questions designed for this variable include four items, such as: The continuation of your company knowledge requires experts, technology and resources of various fields; Your company knowledge encompasses knowledge of various fields, … etc.

Absorptive Capacity

This study mainly references definitions by Szulanski (1996), and Lane and Lubatkin (1998). It refers to company staff’s capacity to hold relevant knowledge and the ability to apply the knowledge. The measurement questions include four items, such as: The ability of your company to engage in a number of R & D activities on its own; The extent of new product development your company can produce by applying external new technology in a short amount of time, … etc.

Organizational Structure

This study refers the definition by Robbins (2003), designating organizational structure into four different aspects, the degree of formalization, the degree of coordination, the degree of centralization, and the degree of specialization. To measure, questions on the degree of formalization include three items:

The extent of detail provided in the company on division of authority and administrative process; The extent of detail on employee job descriptions and operation standards, … etc. Questions on the degree of coordination include four items, such as: The occurrence of employees frequently developing projects together between departments within the company; The occurrence of exchanging ideas between departments within the company, … etc. Questions on the centralization include three items, such as: The occurrence of participation and discussion by staff below the basic management on the decision making process of new products/services implementation, the occurrence of participation and discussion by staff below the basic management on the decision making process of entering important new markets, … etc.

Questions on the degree of specialization include two items: The extent that the company staff can carry out different types of missions, and the extent that the company staff can perform a variety of jobs.

The Performance of Knowledge Transfer

This study references the definitions by Powell and Dent-Micallef (1997), Alavi and Leidner (1999), as well as Coates (1999). It refers to a concept used to compare and contrast with competitors in every performance indicator. The measurement questions include eight items, such as: the situation that the sales growth rate exceeds competitors’; the situation that the profitability exceeds competitors’; the situation that the profit growth rate exceeds competitors’, … etc.

Research Subjects and Questionnaire Design

The research subjects of this study are small and medium enterprises with capital below 80 million NT dollars, and employee numbers below 200. The scale of a SME organization is small, this type of organization is easily modified, and its mobility is high. In addition, the contribution of SMEs to the economic development in Taiwan is undeniable. Whether it is the industrial structures, or employment numbers, SMEs occupy a very important position. Based on this, the scope of this study focuses on the

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The Journal of Human Resource and Adult Learning, Vol. 8, Num. 1, June 2012 37 small and medium enterprises in Taiwan. The subjects of questionnaire surveys are managers of the upper management level of these enterprises.

The design of the questionnaire references relevant items, developed by domestic and overseas scholars, slightly modified and then compiled together. The questionnaire is divided into six aspects, they are: the measurement of knowledge characteristics, the measurement of absorptive capacity, the measurement of organizational structure, the measurement of information technology and the measurement of the performance of knowledge transfer, and the last part is a SME’s basic information.

The design of the questionnaire, excluding a SME’s basic information, adopts Likert five-point scale to measure each item.

In the case of sample selection, this study chooses convenience sampling, selecting samples from various industries and applying questionnaire surveys to obtain required information. In regards to the low recovery ratio of the questionnaire by way of conventional post, this study exercised personal network connections to obtain access to each enterprise, enabling on-site questionnaire survey and testing.

To ensure research subjects’ full understanding of the questions, and to obtain successful responses, each survey is assisted with the author’s on-site explanation. This process enables not only an improved questionnaire recovery rate for this study, it also provides a better grasp of recovery time. The survey was conducted from October 2009 to August 2010, with a total of 256 questionnaires released. After inspection, the number of valid questionnaires is 171.

METHODS OF DATA ANALYSIS

Reliability Analysis

Reliability can also be referred to as credibility. Reliability is the consistency and the stability of the test results, meaning, if a group of subjects answer the same questionnaire multiple times with consistency, then the reliability of the questionnaire is high; on the other hand, if the two results from the same questionnaire vary considerably, then the reliability is low. This study adopts the most commonly used measurement tool, Cronbach, α coefficient. The measure is created by Cronbach in 1951. The application of α coefficient differs according to the different nature and purpose of the measurement. The purpose of this questionnaire is to compare the viewpoints of each test subject. Its reliability requirement is high. It is only considered good if the coefficient measure is higher than 0.8, or at least higher than 0.6 to meet the requirement of reliability. The α coefficient of each variable in this study is no less than 0.7, as shown in Table 1.

Table 1: Reliability Analysis of the Questionnaire in Each Aspect

Question Items Cronbach’s α

Tacit Knowledge 4 0.79

Complex Knowledge 4 0.78

Absorptive Capacity 4 0.76

Degree of Formalization 3 0.89

Degree of Centralization 4 0.82

Degree of Coordination 3 0.88

Degree of Specialization 2 0.85

Knowledge Transfer Performance 8 0.88

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Validity Analysis

Validity can also be called accuracy. It is used to represent whether the questionnaire can truly measure the desired ability or function, which means, only when the questionnaire obtains the desired purpose can it be considered valid. When building relevant constructs and the correlations between constructs, this study, other than grounding in the context of literature, references relevant measuring questionnaires used by scholars, both domestic and overseas. In compiling question items, to ensure that the questionnaire is applicable to general SMEs, this study invited research scholars of the relevant fields to review and comment on the content of the questionnaire, and performed pre-tests on many SME entrepreneurs, as well as inviting their comments as an opinion source for amending the questionnaire.

Therefore, the content validity of the questionnaire for this study should be fairly considerable.

ANALYSIS AND DISCUSSION

The Distribution of Industries, Regions, and Organizational Cultures of the Study Samples The SME industry distribution of the study samples is shown in Table 2.

Table 2: Industry Distribution of the Study Samples

Manufacturing Industry Service Industry

Industry Segment Number of Company Industry Segment Number of Company

Electronics 18 Retail 18

Mechanical 24 Education 7

Biochemical 6 Marketing 18

Hardware 26 Finance 14

Others 28 Advertising 6

Food and Beverage 6

Note: The segment, Others, includes garment making, plastic manufacturing, furniture making, forging and manufacturing.

Mean, Standard Deviation and Correlation of the Research Variables

Table 3 shows the relationship between mean, standard deviation and correlation of the research variables in this study. As shown in table 3, the absolute value of the correlation coefficient of all variables in this study is below 0.635, proving that all the variables in this study are independent.

Table 3: Mean, Standard Deviation and Correlation Coefficient of the Research Variables Variables Mean Standard

Deviation 1 2 3 4 5 6 7 8 9 10

1. Tacitness 3.402 0.701 1

2. Complexity 3.654 0.632 0.362^*** 1 3.Absorptive Capacity 3.271 0.704 0.190^** 0.373^*** 1 4. Formalization 3.476 0.845 -0.198^** 0.158^** 0.177^** 1

5.Centralization 3.032 0.826 -0.052 0.020 0.190^** 0.444^*** 1 6.Coordination 3.487 0.701 -0.008 0.029 0.200^*** 0.444^*** 0.624^*** 1 7.Specialization 3.492 0.743 0.036 0.154^** 0.191^** 0.199^** 0.382^*** 0.514^*** 1 8. Knowledge Transfer Performance 3.305 0.527 0.106 0.191^** 0.360^*** 0.374^*** 0.431^*** 0.530^*** 0.517^*** 1 9.Company Size 2.172 1.464 -0.177^** 0.047 0.172^** 0.258^*** 0.006 -0.010 -0.060^* 0.010 1 10.Company Age 17.36 6.538 0.163 0.217^** 0.328^*** 0.447^*** 0.536^*** 0.578^*** 0.326^*** 0.458^*** 0.635^*** 1 Note：N=171；*p<.10; **p<.05; ***p<.01 (2-tailed)

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The Journal of Human Resource and Adult Learning, Vol. 8, Num. 1, June 2012 39 The Mediation Effect of Absorptive Capacity on Knowledge Characteristics and the Performance of Knowledge Transfer

Model 1 in Table 4 is the regression analysis of each control variable on the performance of knowledge transfer. Based on model 1, models 2 through 4 primarily validate the intervening effect of absorptive capacity on knowledge characteristics and the performance of knowledge transfer. The investigative result shows that tacit knowledge’s affect on the performance of knowledge transfer does not reach a significance level (p>0.1), hence overturning hypothesis 1. As shown in Model 2 of Table 4, a positive significance level is reached for the relationship between knowledge complexity and the performance of knowledge transfer, while Model 3 of Table 4 also shows a significance level (p < 0.001) between absorptive capacity and the performance of knowledge transfer. Combining Model 2 and Model 3, this study shows the result in Model 4, that positive significance disappears from the relationship between knowledge complexity and the performance of knowledge transfer, while the relationship between absorptive capacity and the performance of knowledge transfer still exists. Thus, this study infers that knowledge complexity affects the performance of knowledge transfer through absorptive capacity. In other words, highly complex knowledge can produce better performance of knowledge transfer, because of high absorptive capacity. The result supports the proposed hypothesis 2 of this study.

Table 4: The Analysis Table of Knowledge Characteristics and Absorptive Capacity on Knowledge Transfer Performance

Independent

Variable Model 1 Model 2 Model 3 Model 4

Company Size 0.075 0.068 0.012 0.005

Age -0.053 -0.067 -0.027 -0.037

Manufacturing Reference Group Reference Group Reference Group Reference Group

Service 0.046 0.071 0.115 0.118

Taipei & New Taipei Reference Group Reference Group Reference Group Reference Group Areas Outside Taipei

& New Taipei -0.029 -0.034 -0.052 -0.054

Bureaucratic Type Reference Group Reference Group Reference Group Reference Group

Innovative Type 0.430^*** 0.418^*** 0.404^*** 0.404^***

Supportive Type 0.103 0.115 0.120 0.130^*

Tacit Knowledge -0.005 -0.039

Complex Knowledge 0.185^** 0.103

Absorptive Capacity 0.338^*** 0.298^***

Adj. R² 0.167 0.199 0.291 0.287

Note：a. N=171；*p<.10；**p<.05；***p<.001。

b. The age of the organization, Company size, age, industry, location and organizational culture of the respondent groups of this table are control variables.

c. Dependent Variable：Knowledge transfer performance

The Moderating Effects of the Organizational Structure on Knowledge Characteristics and Absorptive Capacity

Similarly, Model 1 in Table 5 shows the influence of all control variables on absorptive capacity, the result is identical to Table 5. Model 4, in Table 5, shows that the moderating effects of formalization, and centralization of organizational structure on knowledge characteristics and absorptive capacity do not reach a significance level (p>0.1), thereby rejecting hypotheses 3 and 4 of this study.

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Table5: The Moderating effects of Organizational Structure on Knowledge Characteristics and Absorptive Capacity

Dependent Variable Model 1 Model 2 Model 3 Model 4

Company Size 0.170^** 0.183^** 0.155^* 0.196^**

Company Age -0.019 -0.036 -0.042 -0.064

Manufacturing Industry Reference Group

Reference Group

Service Industry -0.181^** -0.135^* -0.197^** -0.126^*

Taipei City & New Taipei City

Reference Group

Reference Group Areas Outside Taipei City

and New Taipei City

0.069 0.070 0.103 0.100

Bureaucratic Type Reference Group

Reference Group

Innovative Type 0.076 0.042 -0.044 -0.053

Supportive Type -0.039 -0.035 -0.104 -0.145^**

Tacit Knowledge 0.089 -0.319

Complex Knowledge 0.313^*** 0.424

Formalization 0.023

Centralization 0.073

Coordination 0.134

Specialization 0.139^*

Tacitness × Formalization 0.268

Tacitness × Centralization 0.375

Tacitness × Coordination 1.167^*

Tacitness × Specialization -1.034^*

Complexity × Formalization -0.239

Complexity × Centralization 0.423

Complexity × Coordination -0.884

Complexity × Specialization 1.105^**

Adj.R² 0.081 0.204 0.179 0.285

Note：a. N=171；*p<.10；**p<.05；***p<.001

b. The age of the organization, Company size, age, industry, location and organizational culture of the respondent groups of this table are control variables.

c. Dependent Variable：Knowledge transfer performance

Interestingly, if the degree of coordination of organization structure is high, then the relationship between tacit knowledge and absorptive capacity is enhanced positively (p<0.1), as shown in Figure 2. In other words, when the level of tacit knowledge is lower than 2.25, organizations with a low degree of coordination have a higher absorptive capacity than organizations with high degrees of coordination. And the opposite is true. This study presumes the reason lies in that low tacit knowledge usually involves general tasks or, easily learned knowledge that employees do not take too much time to learn, therefore, the issues of communication and coordination between employees are not very relevant. When the level of tacit knowledge is greater than 2.25, organizations with high degrees of coordination have higher absorptive capacity than organizations with low degrees of coordination. It explains that organizations with high degrees of coordination can easily increase absorptive capacity when the level of tacit knowledge is higher. This supports hypothesis 5 proposed by this study.

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The Journal of Human Resource and Adult Learning, Vol. 8, Num. 1, June 2012 41 Figure 2: The Interaction Diagram of various levels of combination of tacit knowledge and

coordination, and their corresponding levels of absorptive capacity

In addition, model 4 in Table 5 indicates that the higher the degree of specialization, the more likely that the relationship between knowledge characteristics and the absorptive capacity is weakened (p<0.05), as shown in Figure 2. To further understand the effects of the interaction between tacit knowledge and specialization on absorptive capacity, this study uses tacit knowledge as independent variable, and uses the mean number 3.49 of the specialization level as the basis of Bisection Method to divide the collected questionnaire into high and low levels of specialization, which are used as the basis for linear definition, and then performs two-way ANOVA on the dependent variable, absorptive capacity. The result is shown in Figure 3. As the level of tacit knowledge gets higher, absorptive capacity of organizations with low levels of specialization is significantly increased, however, in organizations with high levels of specialization, absorptive capacity does not change significantly. Therefore, when confronted with high tacit knowledge, organizations with low levels of specialization have higher absorptive capacity compared to organizations with high levels of specialization. This supports hypothesis 6 proposed by this study.

Figure 3: The Interaction Diagram of various levels of the combination of tacit knowledge and specialization, and their corresponding levels of absorptive capacity

Model 4 in Table 5 shows that the moderating effects of the degrees of formalization, centralization, and coordination of organizational structure on knowledge complexity, and absorptive capacity do not reach significance levels (p>0.1). This result overturns the proposed hypothesis 7, hypothesis 8, and hypothesis 9 of this study. However, specialization enhances the relationship of knowledge complexity and absorptive capacity, and organizations with high levels of specialization have higher levels of

Tacit knowledge

Absorptive capacity

Low Specialization High Specialization

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absorptive capacity, than organizations with low levels of specialization (p<0.05). This result supports hypothesis 10 proposed by this study. In addition, as shown in Figure 4, as the level of knowledge complexity gets higher, organizations with high levels of specialization have relatively higher levels of absorptive capacity, compared to organizations with low levels of specialization.

Figure 4: The Interaction Diagram of various levels of the combination of complex knowledge and specialization, and their corresponding levels of absorptive capacity

CONCLUSION AND MANAGEMENT IMPLICATIONS

Conclusion

Within SMEs, knowledge transfer between departments can promote the sharing of information among employees and between departments, and thereby enhances competitive advantage. But, in the process of transferring knowledge, how to lower the cost, enhance the effectiveness, and thus improve organizational performance, is an important subject currently facing enterprises. The vast majority of literature on knowledge transfer from the past focuses on knowledge transfer outside an organization, while the discussion on knowledge transfer within the same organization is rare. Additionally, a majority of the literature attributes the key factor affecting the performance of knowledge transfer to knowledge characteristics, and ignores that, during the course of knowledge transfer, perhaps the absorptive capacity of the knowledge staff is the possible key to an effective knowledge transfer.

In order to clarify the causes that affect knowledge transfer performance, this study chose middle and top management from SMEs in the Taiwan area, and performed questionnaire surveys, which generated 171 valid questionnaires. The empirical results show four discoveries: (1) The higher the level of knowledge complexity, and the higher the staff’s absorptive capacity, the better the performance of knowledge transfer within the organization. (2) An organization structure with higher levels of coordination is more likely to affect positively the relationship between tacit knowledge and absorptive capacity. (3) An organization structure with higher levels of specialization is more likely to affect negatively the relationship between tacit knowledge and absorptive capacity. (4) An organization structure with higher levels of specialization is more likely to affect positively the relationship between knowledge complexity and absorptive capacity.

Complex knowledge

Absorptive capacity

Low Specialization High Specialization

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The Journal of Human Resource and Adult Learning, Vol. 8, Num. 1, June 2012 43 THE MANAGERIAL IMPLICATIONS FOR SMES

The key to affecting knowledge transfer between various departments within an organization lies in the absorptive capacity of the employees

Generally speaking, having employees with high levels of knowledge implies a higher capital investment in human resources, but the absorptive capacity is usually higher as well. If the average human resource capital per employee within an organization is raised, the process of knowledge transfer is more successful, which is helpful in promoting the enterprise’s overall competitiveness. For this reason, the raising of human resource capital, and the enhancing of a staff’s learning and absorptive capacity are currently the most important issues in managing SMEs.

The level of knowledge complexity is related to staff’s absorptive capacity

For SMEs, in the process of knowledge transfer, the higher the knowledge complexity, the longer it takes to complete the transfer. For employees, although it takes longer to absorb this type of knowledge, it can greatly enhance their knowledge applications. In other words, knowledge with high levels of complexity may improve employee’s absorptive capacity, establishing the basis for innovation, thereby increasing the performance of knowledge transfer.

Organization structure that is high in coordination level may positively affect the relationship between tacit knowledge and absorptive capacity.

This study finds that organizations with higher levels of coordination can improve communications between employees, making it easier to transfer high tacit knowledge, thus, enhancing absorptive capacity.

When an organization is structured to be highly coordinated, the absorption of tacit knowledge accelerates, enabling employees to apply this type of knowledge quickly as the basis for innovation and promote absorptive capacity, thus, improving the performance of knowledge transfer. Therefore, if an SME possesses high tacit knowledge, the enterprise must make good use of this easily adjusted structure characteristic to help increase the coordination level within the organization, so that highly tacit knowledge is transferred and applied quickly within the organization, bringing profit to the enterprise.

Organization structure that is high in specialization may negatively affect the relationship between tacit knowledge and absorptive capacity.

This study finds, that although an organization with high levels of specialization can simplify and modularize complex knowledge, which allows the highly complex knowledge to be divided into simpler forms that employees can absorb, and then at the same time assign employees to their own specialties with simplified work content that is more appropriate to their own skills, and thus provide fewer opportunities for communication and exchange between employees, that this action makes tacit knowledge more difficult to absorb.

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