technology transfer effectiveness in knowledge- … · technology transfer authorities should...

March 2014. Vol. 4, No.7 ISSN 2305-1493 International Journal of Scientific Knowledge

Computing and Information Technology

© 2012 - 2014 IJSK & K.A.J. All rights reserved www.ijsk.org

24

TECHNOLOGY TRANSFER EFFECTIVENESS IN KNOWLEDGE-

BASED CENTERS: PROVIDING A MODEL BASED ON

KNOWLEDGE MANAGEMENT

MOSTAFA JAFARI, PEYMAN AKHAVAN, ABBASS RAFIEI

Faculty, Iran University Of Science And Industry 1

Associate Professor, Malik Ashtar University Of Technology2

Postgraduate, Industrial Engineering, Iran University Of Science And Industry 3

1 [email protected], [email protected] , [email protected]

Abstract

The Present paper attempts to identify factors and variables affecting designing technology in knowledge-

based centers in order to study their relations and; ultimately, to provide a model based on research data.

To achieve this aim, technology transfer process capabilities, knowledge management, technology transfer

effectiveness and constituting variables/indicators should be preliminarily and separately identified , and

then the impact of knowledge management on capability of technology transfer process and its effectiveness

should be measured in Iranian universities. . The research method is descriptive of correlation type. In this

research, using a simple stochastic method, 151 active people in technology transfer were selected from

among Iranian knowledge-based centers . The data for the research were collected through

questionnaires. Confirmed construct and factorial analysis were used to determine the validity, and for

reliability, Chronbach alpha was employed. In order to study the relationship between research variables

and to study hypotheses, the modeling of structural equations has been used with the help of SPSS and

AMOS software. Findings indicate that knowledge management impacts on technology transfer

effectiveness in knowledge-based centers. Likewise, knowledge management relates to technology transfer

effectiveness via technology transfer capabilities. Studying the impact of each variable on technology

transfer effectiveness indicates that knowledge capability followed by knowledge management and

technological capabilities are the key factors and facilitators, and as a mitigating factor, organizational

capability has the highest impact on technology transfer effectiveness.

Keywords: knowledge management, organizational capability, technological capability, knowledge

capability, technology transfer

1. INTRODUCTION

Technology transfer is in fact the movement of

technology from one point to another. For instance,

technology can be transferred from one

organization to another, from university to an

organization and from one country to another

(Reisman, 2005). Technology transfer is a dynamic,

complicated and long-term process whose success

owes to factors stemmed from other sources.

Concerning high rate of failure in technology

transfer projects (Guan, 2006), the most important

challenges in the success of technology transfer

projects is to identify these factors and their

sources. According to Santer and Saparteau (2006),

knowledge does not flow automatically from

university to industry; rather it needs facilitating

factors. Hence, it is important to analyze factors

affecting technology design and transfer in

universities and research centers. Therefore,

identifying both special and general factors that

impact on the success and effectiveness of

technology transfer can mitigate technology transfer

risks and can increase the success of technology

transfer projects (Johnson, 1998; Harrington, 2005).

The main challenge for organizational decision

makers is that they do not know how, needed

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knowledge to resolve organizational problems in

employees’ minds is developed. Research centers

with technology transfer on their agenda are among

those which should do their best to identify,

fascinate and utilize their employees’ organizational

knowledge effectively due to the scope and

complexity of technology transfer processes.

Knowledge management has a direct relationship

with technology transfer effectiveness, and plays a

mediating role in this regard. Knowledge

management creates the necessary opportunity to

improve factors related to technology transfer

process and organizational performance ;

ultimately, acquiring competitive advantage.

The Present study attempts to identify

organizational, relational, technological and

knowledge factors which impact on technology

transfer effectiveness in several Iranian universities

and research centers. Likewise, the impact of

knowledge management and technology transfer

effectiveness in the surveyed population is

measured.

In the present paper, factors related to

technology transfer processes are called

“capabilities”.

Concerning the aims of the research, one

can point out the identification of factors related to

technology transfer and constituting variables of

technology transfer effectiveness in the studied

centers. In the meantime, computing the amount of

knowledge management impacts on technology

transfer process and technology transfer

effectiveness variables in such industries are, inter

alia, the main aims of the present study.

2. LITERATURE REVIEW

Academic researches and transferring them to

industry are highly respected in knowledge and

technology management. Since early 1980, authors

and policymakers have paid special attention to the

relations between university and industry. Overall,

technology transfer literature can be categorized

into three main segments: a segment which studies

technology transfer process factors, one for

knowledge management and another one focusing

on technology transfer effectiveness. In technology

transfer process factors segment, all factors

affecting technology transfer including

organizational, relational, technological and

knowledge factors are studied.

In literature, the importance of organizational

structure in universities’ organizational

performance is highlighted. Gopalakrishnan and

Santro (2004) believe that organizational structure

is an effective internal factor in knowledge

acquisition and transfer from academic institutes.

Siegel et al (2003) believe that lack of allocating

sufficient resources to knowledge transfer

initiatives by university, bureaucracy and

inflexibility of university executive management

are among the barriers of knowledge and

technology transfer from university to industry

(Siegel et al, 2003). Concerning organizational

technological capability, Acha has introduced

technological capability as technological know-how

and necessary skills to identify, develop and utilize

necessary techniques (Tsai, Keven, 2004).

Regarding relational capability, its role in

innovation, new product development and time of

introducing new products to market are studied

(Jonker, 2006; Griffith, 2004). Adams, Fesfield

(1991) and Rosenberg & Nelsen (1994) indicate

that academic researches have important impacts on

industrial productivity increase, and any increase in

cooperation between university and industry would

cause the transfer of academic implicit and explicit

knowledge (Bekkers and Freita, 2008; Hong, 2008).

With regard to knowledge capability, its role in the

capacity of designing and utilizing new technology

(Mu et al, 2010, Pertusa – Ortega et al, 2010;

Bishop et al, 2011). Maglitta (1995) and Cole

Gomolski (1997) assert that knowledge

management is an effective way to improve the

performance, the productivity , competitiveness,

and techniques and processes of decision making, to

distribute appropriate information in the

organization,and and to make us aware of the best

patterns and successful experiences of other people.

Concerning technology transfer effectiveness,

Yuling Wang (2010), Carolina Lopez (2011) and

Wi Wen Wu (2012) have studied the role of

economic, qualitative, operational, learning, and

HR in successful technology transfer.





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2.1. Factors Affecting Technology Transfer

Technology transfer is a complicated and hard

process which is not fruitful without investigation,

and it may waste capitals and weaken technology

(Asghari et al, 2013). Many authors emphasize that

technology transfer is impacted by technology

sending resource, technology receiver and the route

and type of transferred technology and knowledge.

To this end, efficient technology transfer requires a

full understanding of capabilities of technology

senders/receivers as well as other

facilitating/limiting factors (Mu et al, 2010;

Strachand and Everett, 2006). Technology transfer

process enjoys some preventive and contingent

factors that should be considered before taking in to

account technology transfer models including

awareness of needed radical factors to transfer

technology and the factors of past technology

transfer failures.

The necessary condition for technology transfer

is to be aware of radical and effective factors.

Technology transfer authorities should always be

aware of main factors. These factors should be

respected before technology transfer in order to

achieve the benefits of technology for both

technology resource and receiver. Concerning broad

studies on technology transfer literature, affecting

factors or capabilities in technology are identified

and classified into four major measures as follows.

2.1.1. Organizational Capability

Organizational capability refers to innovating

and reshaping internal resources (Hawawini, 2004).

Structural organization of the university is a factor

affecting new technology designing. Generally,

organizational structure of a university should be

homogeneous to new technology and respond its

needs (Rouner, 2003; Trafdar, 2006).

To facilitate knowledge flow, research centers

should design structures and systems by which one

can generate, aggregate, integrate, disseminate, and

manage the knowledge effectively. Chen and

Huang (2007) and Pertusa – Ortega (2010) have

determined the traits of organizational structure as

the critical factors in affecting knowledge transfer

process and innovation in companies. Most

researches on organizational theory confirm that

organizational structure plays a vital role in the

capability of an organization to adapt, create and

integrate knowledge and innovation in the

organization.

Some authors claim that adaptation between

organizational knowledge and structure to achieve

flexibility and efficiency of competitive

environments is very vital (Liao et al, 2010; Chen

and Huang, 2007).

Siegel et al (2003) believe that academic

executives in US universities should focus on five

organizational and managerial factors in order to

grow an entrepreneurship and commercialization

climate. They include developing an awarding

system to expand technology transfer cooperation,

modifying the ways of employing personnel in

technology transfer offices, devising flexible

academic policies to facilitate academic technology

transfer, devoting more resources to technology

transfer, and removing cultural and informational

barriers that prevent knowledge and technology

transfer.

2.1.2. Relational Capability

Another factor affecting successful technology

transfer less respected in the literature is the role of

rivals, customers, supportive organizations and

scientific centers. Overall, one can call it

“organizational relational capability.” Such

technology should have a right interaction with

customers, suppliers and rivals.

In his research, Jonker (2006) introduced

relational capability as the “ability of relationship”,

and measured it by such metrics as relation with

customers, rivals, suppliers, financial firms,

technical/vocational organizations, research centers

and universities. In another research by Ritter on

German firms, he defined relational capability as

interactions of an organization with customers,

suppliers, rivals and research institutes.

The volume of relations between research

institutes and industry would increase knowledge

and technology transfer to companies. Intensity of

relations between a company and knowledge

suppliers or generators is very important for

constant learning and is considered as the

infrastructure of innovation process (Bramwell and

Wolfe, 2008; Herrera et al, 2010). Mohnen and

Hwario (2003) found that there is a positive

relationship between introducing basic product





27

innovations and reliance on research organizations

(Fontana et al, 2006).

2.1.3. Technological Capability

Walsh (2002) defined technological capability

as technological inventions and being aware of

technological future needs.

Santoro and Bierly (2006) assert that

technology transfer would be increased if the

technological capabilities of both sender and

receptor are interrelated. Some authors believe that

organizational capability to internalize external

knowledge will be increased by learning methods

like internal R&D, technology level, and technical

training (Santoro and Bierly, 2006).

Overall, the common point in all definitions is

the emphasis on developing, assimilating and

utilizing technical skills in scientific inferences to

create competitiveness in an organization (Tsai,

Keven, 2004). In another research by Wang (2004)

in Chinese high – tech, companies, the author used

indicators such as investment in R&D, constant and

high level in-service training, high capacity to

employ elites by organization, high capacity to

predict technological changes, the capability of

utilizing new technologies in resolving internal

problems and improving new technological

standards to measure technologically capability of

studied organizations.

2.1.4. Knowledge Capability

Knowledge capability is an important factor in

knowledge and technology transfer. Knowledge

capability is the ability of a company to recognize

the value of new external information and to

integrate it with internal organizational knowledge

(Bishop et al. 2011; Kodama, 2008; Mu et al, 2010;

Pertusa – Ortega et al, 2010).

Knowledge capability includes the abilities of

acquiring and merging the knowledge and utilizing

it in an organization. Innovation process in

companies is the process of aggregation and

generation of new knowledge. Its performance

highly depends on the capacity of the company in

using knowledge management and their human

resources. Many authors believe that a company’s

innovation capacity has a close association with its

capability in acquiring advantages from knowledge

and in integrating it with other elements of internal

knowledge (Herrera, et al, 2010).

According to Hamel (1991), someone’s past

experience would impact on the ability of

knowledge sharing and new knowledge

institutionalization. Cohen and Levinthal (1990)

emphasize that past aggregative knowledge

promotes both the capability of storing, reviving,

and using new knowledge (Albino et al, 1999).

Existing literature has used such indicators as the

ability to conceive the value of new knowledge and

information, to attract new knowledge in

organizational current knowledge treasure, to

integrate new knowledge with existing

organizational knowledge, to use organizational

knowledge for business purposes, to convert

internal accumulated experience into applied

business knowledge, to convert implicit and explicit

knowledge into job procedures and norms, and to

use current organizational knowledge to generate

new knowledge to measure firms’ learning and

knowledge (Chen and Huanj, 2009; Bishop et al,

2011; Decter et al, 2007; Carayannis et al, 2000).

In their studies, some authors have considered

company’s attraction capacity (technology level,

training, T&D activities) and the existence of

technology-related basic knowledge (technological

knowledge, technical and organizational skills and

receptor’s tacit knowledge) important for successful

technology and knowledge transfer (Bishop et al,

2011; Kodama, 2008; Mu et al, 2010; Pertusa –

Ortega et al, 2010).

2.2. Knowledge Management

Knowledge management is a new term with

different definitions. US Center for Quality and

Productivity defines it as strategies and processes to

identify, acquire, and utilize knowledge

(Monavvarian et al, 2013). Maglitta (1995) and

Cole-Gomolski (1999) believe that knowledge

management is an effective way to improve the

performance, to increase the productivity and

competition power, to distribute information in

organization properly, to improve decision-making

methods and processes, and to be aware of others’

successful patterns and experiences.

Daruch (2003) defined knowledge management

as processes that generate knowledge and manage

its sharing, dissemination and utilization inside the





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organization. Davenport et al (1998) believe that

knowledge management is to manage

organizational knowledge through special and

systematic processes to attain, organize, retain, use,

share, and extend both implicit and explicit

knowledge of employees to improve organizational

performance and to generate value. Gupta et al

(2000) believe that knowledge management is a

process which helps organizations explore,

organize, disseminate and transfer important

information and necessary experiences for such

activities as problem solving, dynamic learning,

strategic planning and decision making. Knowledge

management can effectively facilitate fast

accessibility to commonly and properly needed

knowledge for different tasks in order to improve

decision making and to permit the dissemination

and sharing of necessary knowledge and

information in the organization (Bohhn, 1994;

Davenport and Prusak, 1998).

2.3. Technology And Its Transfer

Technology is a tool or skill, a product or

process, physical equipment or execution methods

by which human’s capability increases. In

operational terms, technology is technical

knowledge that increases the capability of an

organization to produce goods and services (Stock,

2000). Technology concept is like a bridge between

science and new products (Asghari et al, 2013).

Technology transfer is a process that allows

technology transfers from one source to a receptor.

The source can be the owner of technology like an

organization or a country (Radosevik, 1999).

Another specialist believes that technology transfer

is from a location to another e.g. from an

organization to another, from a university to an

organization, or from one country to another

(Reisman, 2005).

In most cases, technology transfer requires

physical processes related to knowledge (physical

elements such as digital components) as well as

know-how or advanced skills on installments.

Knowledge is divided into two implicit and explicit

categories (Nonka and Takeuch, 2001). Explicit

knowledge refers to detailed plans, designs,

diagrams, attributes, etc. Therefore, information is

transferred more easily by technological support

(Antonelli, 1997) while implicit (tacit) knowledge

is hardly devised and is not basically devised in

organization. Implicit knowledge was coined by

Ploanyi in 1967. Antoneli (1997) asserted that since

IT has a limited capacity for implicit knowledge

transfer, we generally use it to transfer explicit

knowledge. By using knowledge management,

organizations are able to create an environment

where one can regularly identify implicit

knowledge, and where explicit knowledge is

transferred more easily and rapidly with the help of

IT tools.

2.4. Technology Transfer Effectiveness

To identify important factors in technology

transfer effectiveness, the relevant literature was

initially reviewed, and then these important factors

were extracted in Iranian elites’ views. In a research

by Wang (2004) in Taiwanese companies,

technology transfer effectiveness was measured. In

this research, the amount of aims achievement was

already determined (Wang, 2004). In another

research, Stock (2001) introduced operational

effectiveness and economic effectiveness to

measure technology transfer effectiveness.

In his study on Croatian firms, Shaojie (2006)

measured technology transfer effectiveness through

three factors: “receptor’s technical knowledge

learning”, “dependency of receptor to sender in

order to conduct the operations” and “using

transferred technology on other projects to improve

the operations”.

In most technology transfer projects in Iran,

technical aspects and, to a lesser extent,

organizational aspects are considered more

(Movahedi, 2003) while the role of knowledge

management in technology transfer process is not

respected. Therefore, the present paper studies the

impact of knowledge management on knowledge

capability and technology transfer effectiveness in

knowledge-based centers and manufacturing

companies.

2.5. Technology Transfer And Its Experiences

In Iran

In the present research, numerous doctoral and

M.A theses are studied in the field of technology

transfer in different Iranian organizations, and those

closer to the research title were finally gathered.

The most important barriers in successful

technology transfer in Iranian organizations are

“lack of specialized manpower, serious managerial





29

problems, disrespect to R&D, problems in

cooperating with suppliers, disrespect to specialized

training and retraining, lower attraction capacity,

lack of motivations among personnel, and using

license path in most technology transfer contracts

(Movahedi, 2003).

Table 1: Demographic distribution of respondents

The

numbers

of

responde

nts

% Aggregat

ive

percentag

e

Job

experien

ce

Less than

5 years

58 38.

7

38.7

5 – 10

years

30 20 58.7

10 – 15

years

27 18 76.7

15 – 20

years

16 10.

7

87.3

+20

years

20 12.

6

100

Degree B.A. 7 4.7 4.7

M.A. 46 30.

7

35.4

Ph.D. 95 63.

2

98.6

Other 3 1.4 100

Scientifi

c degree

Research

er

45 29.

8

29.8

Coach 8 5.3 35.1

Assistant

prof.

78 51.

7

86.8

Associat

e prof.

12 7.9 94.7

Professor 8 5.3 100

Educatio

nal field

Basic

sciences

5 3 3

Engineer

ing and

technical

24 16 19

Liberal

arts

106 71 90

Other 16 10 100

The

number

of

scientific

papers

Less than

10

83 55.

3

55.3

10 – 20 27 18 73.3

20 – 30 12 8 81.3

Over

than 30

29 18.

7

100

2.6. General Model And Hypotheses

In the model provided in the theoretical

literature, the sequence of technology transfer is

addressed more while the capabilities of technology

sender (university), technology receptor (industry),

knowledge management and its role on technology

transfer from university to industry are not

considered.

The conceptual model provide in the present

study constitutes dependent variables (technology

transfer effectiveness) and independent variables

(knowledge management, organizational, relational,

and technological and knowledge capabilities).

Figure 1 indicates research conceptual model along

with the elements of each part. To study the

relationship between the impacts of knowledge

management on organizational and knowledge

capabilities and technology transfer effectiveness,

the above mentioned indicators were initially

devised by referring to elites’ opinions as well as

reviewing the relevant literature. In this vein,

technology transfer indicators are categorized in

four aspects. Different aspects of technology

transfer capabilities, its constituents and sources are

depicted in Appendix 1. Knowledge management

constituents, technology transfer effectiveness and

its resources are outlined in Appendix 2.

Concerning the above-mentioned points and the

aims discussed earlier, the following hypotheses are

provided:

H1. There is a positive and significant relationship

between knowledge management and technology

transfer capabilities in knowledge-based centers.

H2. There is a positive and significant

relationship between technology transfer

capabilities and technology transfer effectiveness in

knowledge-based centers.

H3. There is a positive and significant

relationship between knowledge management and

technology transfer capabilities and technology

transfer effectiveness in knowledge- based centers.





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3. METHODOLOGY

3.1. Research Proposal

In the present study, important factors in

measuring technology transfer process capabilities

and technology transfer effectiveness in Iranian

universities under study are identified by precise

and multilateral reviewing of technology transfer

literature, organizational structure literature,

knowledge management, interviews with academic

elites, authors and managers of technology transfer

projects and knowledge management skillful

authors in two separated steps. To achieve this aim,

the relevant literature was broadly and precisely

reviewed, and then a preliminary questionnaire was

devised in three separate parts based on existing

indicators in the literature.

The first part of the questionnaire was devoted

to questions on organizational, relational,

technological and knowledge capability in

universities while the second part covered questions

on knowledge management and the third part

consisted of questions on technology transfer

effectiveness. Likert five-scale spectrum was

utilized to devise the questions from very low to

very high. This questionnaire which was based on

relevant literature was submitted to 20 academic

elites as well as technology transfer authors and

knowledge management researchers. After face-to-

face interviews and concluding their opinions, some

questions were deleted and some others that had

interferences were merged, and indicators related to

organizational, technological, and technology

transfer effectiveness factors in Iranian industries

were added to the preliminary questionnaire.

Likewise, the clarity of questions in each part

and their relevance to knowledge management and

capabilities as well as technology transfer

effectiveness in universities under study was

confirmed by elites and authors.

In the second step, the revised questionnaire

with the results of the first step was devised in three

separate steps and submitted to 20 technology

transfer project managers, senior experts, authors

and faculty members of the universities, and

surveyed manufacturing industries. In this step and

in addition to questionnaire, semi-structured

interviews with project managers were conducted,

and their experiences on knowledge management

and technology transfer were gathered and

recorded. In these interviews, special points as well

as their suggestions/needs to accelerate technology

transfer process and the role of knowledge

management in improving technology transfer

process were all determined. The questionnaire was

severally evaluated and revised in terms of validity

and reliability. According to Iranian elites, all three

parts enjoy proper validity. Chronbach’s alpha was

also measured to compute internal compatibility

with confidence level. Table 2 depicts the reliability

of the questionnaire after modifications. As

observed, all values are greater than 0.7 (acceptable

level). Thus, responses to all three parts of the

questionnaire are reliable (Gallivan, 2005).

Table 2: Questionnaire and KMO statistic

The

quantity

of

constitu

ents

Chronba

ch’s

alpha

KM

O

Technolo

gy

transfer

capabiliti

es

Organizat

ional

capability

4 0.82 0.7

8

Technolo

gical

capability

4 0.80 0.7

9

Relational

capability

6 0.88 0.8

8

Knowledg

e

capability

4 0.81 0.7

9

Technology transfer process capabilities

Figure 1: Research conceptual model

Organi

zationa

l

capa

bility Relational

capability

Technologica

l capability

Knowledge

capability

Transfer

effectiveness

Knowledge

management





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Total 18 0.93 0.9

3

Knowled

ge

manage

ment

10 0.92 0.9

2

Technolo

gy

transfer

effective

ness

5 0.90 0.8

6

Total

question

naire

33 0.96 0.9

4

Research population consists of Iranian

universities and research centers with technology

transfer experience. 4 universities and research

centers were randomly selected from them. After

devising the questionnaire and initial sampling,

confirming the reliability and validity of the

questionnaire and final modifications, 500

questionnaires were distributed among researchers

and faculty members of which 168 (34%) were

returned. 17 of the returned questionnaires were

omitted due to information deficiencies and,

ultimately, 151 questionnaires were used to analyze

data.

However, efforts were made to respect the

condition of at least 10 questionnaires for each

studied variable (Gullivan, 2005) in order to use

path analysis technique for data analysis.

Furthermore, KMO1 estimates shown in table 2

indicate that sample volume adequacy Table 1

shows the demographic distribution of collected

samples.

3.2. Introducing Organizational Capability,

Knowledge Capability And Technology

Transfer Effectiveness Indicators

After concluding the relevant literature on

technology transfer capabilities, knowledge

management and technology transfer effectiveness

(2.1 – 2.4), some indicators were extracted to

measure technology transfer process capabilities,

knowledge management and technology transfer

effectiveness in Iranian universities. After being

1 Kaiser-Meyer-Olkin Measure of Sampling Adequacy

evaluated and revised by elites, therer were totally

18 indicators for technology transfer capabilities (4

indicators for organizational capability, 6 for

relational capability, 4 for technological capability

and 4 for knowledge capability), 10 for knowledge

management and 5 for technology transfer

effectiveness in Iranian universities.

4. DATA ANALYSIS

To test the above-mentioned hypotheses,

structural equation modeling in AMOS software is

used. Figure 2 shows the model which fits the

standardized ratios to test the 1st hypothesis. In

below figures, variables like TTE, KM, OC, RC,

KC and TC indicate technology transfer

effectiveness, knowledge management,

organizational capability, relational capability,

knowledge capability and technological capability,

respectively. Before interpreting the model

coefficients and understanding the relations among

variables, it is initially necessary to assure good

fitness model. In this model, the value of x2/df is

computed as 1.51. Values less than 3 show proper

fitness of the model. In the meantime, the value of

RMSEA is 0.51. Since in statistical contexts, 0.08

value as cutting point is introduced as a benchmark

for model fitness (Iacobucci, 2010) and values

greater than 0.08 show model weakness, one can

say that based on this benchmark, model fitness is

not proper. In the meantime, desired rates for GFI,

AGFI and CFI are greater than 0.9 which are 0.910,

0.902 and 0.931, respectively in the studied model.

Table 3 outlines the statistics for good to fit model

and other models.

Represented indicators show that on the whole

this is a suitable model properly regenerating

empirical data.





32

Figure 2: Studying the relationship between knowledge

management and technology transfer capabilities

With regard to the above figure, it is certain

that knowledge management has a strong

relationship with technology transfer capabilities.

Table 4 depicts the significance of the above ratios

computed by Boot-Strep resampling method.

Concerning table 4, all the above ratios are

significant in 0.05 level. Therefore, H1 on positive

relationship between knowledge management and

technology transfer capabilities is supported.

Hypothesis 2 reads that there is a positive and

significant relationship between technology transfer

capabilities and technology transfer effectiveness.

For more precise investigation, H2 is divided into

one main and four minor hypotheses:

H2.1. relational capability has a positive and

significant relationship with technology transfer

effectiveness.

H2.2. technological capability has a positive

and significant relationship with technology transfer

effectiveness.

H2.3. organizational capability has a positive

and significant relationship with technology transfer

effectiveness.

H2.4. knowledge capability has a positive and

significant relationship with technology transfer

effectiveness.

H2.5. technology transfer capabilities have a

positive and significant relationship with

technology transfer effectiveness.

To study the above hypotheses, each is fitted

separately and good to fit statistics are shown in

table 3 which shows proper fitness. In the

meantime, fitness for each model and their

significance is depicted in table 4. For instance, the

result of model 2.3 fitness in table 4 indicates that

there is a significant relationship between relational

capability and technology transfer effectiveness.

Standard ratio (correlation coefficient between

hidden variables of relational capability and

technology transfer effectiveness is estimated as

0.54 which shows a positive relationship between

both variables. Since the significance value of this

test is 0.11 which is less than 0.05, we conclude that

the linear relationship between both variables is

significant in 0.05 level (note that such estimation is

achieved in the absence of other capabilities in the

model). Concerning the results estimated in table 4,

one can say that other technology transfer

capabilities also have a significant relationship with

technology transfer effectiveness (in the absence of

other capabilities). Therefore, hypotheses H2.1 to

H4 are supported.

H2.5 addresses the relationship between

technology transfer capabilities and technology

transfer effectiveness, and asks whether each

technology transfer capability (if assumed being

fixed) has any significant relationship with

technology transfer effectiveness or not.

Good to fit statistics in the present model are

shown in table 3 (model 2.5). Concerning standard

ratios shown in table 4, one can say that

technological, relational and knowledge capabilities

have a significant relationship with technology

transfer effectiveness. Additionally, no significant

relationship is observed between organizational

capability and technology transfer effectiveness in

the attendance of other capabilities. To interpret

such parameters, one can say that if relational and

knowledge capabilities in two universities are

identical, then we expect more technology transfer

effectiveness in the university with higher

organizational capability.





33

Ultimately, to study H3 which reads that

knowledge management has a significant

relationship with technology transfer effectiveness

through technology transfer capabilities; the model

devised in figure 3 is used. Its good to fit statistics

has admirable fitness.

Table 3: Good to fit indices in fitted model

Mod

el

X2/

df

RMS

EA

RM

R

GFI AG

FI

CFI

Mod

el 1

1.5

1

0.051 0.0

48

0.9

10

0.9

02

0.9

31

Mod

el 2

2.1

RC

2.2

TC

2.3

OC

2.4

KC

2.5

Tot

al

1.5

6

1.8

9

1.7

0

2.0

3

2.0

7

0.049

0.057

0.048

0.063

0.066

0.0

36

0.0

42

0.0

34

0.0

40

0.0

58

0.9

23

0.9

46

0.9

48

0.9

38

0.8

91

0.9

08

0.9

16

0.9

14

0.9

08

0.8

61

0.9

74

0.9

78

0.9

73

0.9

61

0.9

06

Mod

el 3

1.5

8

0.056 0.0

48

0.9

05

0.8

99

0.9

14

Desir

ed

value

<3 <0.08 <0.

05

>0.

9

>0.

9

>0.

9

Table 4: The estimation of path ratio and its significance

in fitted models

Model RC TC OC KC KM

Model

1

KM (0.006)

0.83

(0.016)

0.79

(0.008)

0.86

(0.13

)

0.74

Model

2

2.1

TTE

2.2

TTE

2.3

TTE

2.4

TTE

Total

TTE

(0.11)

0.54

(0.045)

0.33)

(0.009)

0.57

(0.037)

(0.28)

(0.24)

0.47

(0.355)

-0.17

(0.00

5)

0.60

(0.14

)

0.42

Model

3

TTE (0.361)

0.19

(0.210)

0.24

(0.029)

-0.46

(0.01

5)

0.33

(0.019)

0.61)

In the fitted model, the direct impact by

knowledge management on technology transfer

effectiveness is estimated as 0.41 (significant in

level 0.05) and the indirect impact is estimated as

0.20 (significant in level 0.05). The overall by


effectiveness shown in table 4 (model 3) is

estimated as 0.61 (significant in level 0.05).

Therefore, one can say that knowledge management

relates to technology transfer effectiveness

indirectly via technology transfer capabilities.

Concerning the above points, path ratios in

table 4, and studying each variable in technology

transfer effectiveness, one can conclude that

knowledge capability and knowledge management

and, finally, technological capability have the

highest impact on technology transfer effectiveness.

Regarding the fitted model, total impact of


effectiveness is estimated as 0.61 which is

significant based on table 4 in significant level 0.05.

Therefore, H3 is supported.

Figure 3: The relations between knowledge management

and technology transfer process capabilities and

technology transfer effectiveness





34

5. DISCUSSION

The conducted research indicates that

technology transfer is a multilateral phenomenon in

whose success many factors are involved. In this

line, some factors are more important than others.

Development and progress of societies is the

result of scientific and industrial development links.

By linking university and research centers as the

incumbents of scientific centers development to

industry as the incumbent of industrial

development, one can achieve very positive results

in economic development that would lead the

country to progress and dynamism constantly.

Studying relevant literature indicates that all

countries have acknowledged the role of technology

and knowledge in economic growth, and that they

have conducted broad initiatives to build a bridge

between research and industry sections. Concerning

research results that show direct impact by

knowledge management on successful technology

transfer, it is appropriate that domestic research

center managers pay more attention to technology

transfer and pave the ground for executing its

processes and mechanisms. In the meantime, they

should make technology transfer projects and

projects easier and more suitable to facilitate

technology transfer flow and to enhance

researchers’ performance in technology transfer

activities by devoting sufficient resources to such

activities.

Likewise, managers at research centers should

improve the capacity of technology designing

through increasing specialists’ skill levels, training

levels, devoting sufficient resources to research

activities and proper organizational structure. Such

initiatives not only promote knowledge and

technical levels of technology receptors, but also

make it possible for research centers to transfer

concerned knowledge and technology in a shorter

time and at lower costs.

6. CONCLUSION

Due to new technology generation and transfer,

universities are seen as one of the largest resources

to acquire technology in manufacturing industries.

Hence, it is very important to study technology

transfer from university to industry. Technology

transfer is influenced by the traits of both

technology sender and receptor.

Concerning the above discussion, the present

study was conducted. Initially, variables affecting

on technology transfer from universities and

research centers to industry were identified and then

the relationship between knowledge management

and these variables and their impacts on successful

technology transfer were evaluated. To this end,

technology transfer literature was widely and

precisely studied, and then technology transfer

related factors called as technology transfer process

capabilities like organizational, relational, and

technological and knowledge capabilities were

identified as the factors affecting on technology

transfer. In the meantime, indicators to measure

their impact on successful technology transfer were

determined. In the provided model, the relations

between research variables were studied by

structural equation model. The findings indicated

that knowledge management directly impacts on

technology transfer effectiveness (41%) and its

indirect impact is only through knowledge

capability as a facilitator (33%) and organizational

capability as a mitigating factor (-0.46%).

Furthermore, confirmatory factor analysis

(CFA) findings indicated that in knowledge-based

centers, indicators such as acquiring and

disseminating specialists’ knowledge and

experience, using individuals’ current knowledge

and experiences, and developing and using

employees’ knowledge in new situations impact

more than other indicators on successful technology

design and transfer. In knowledge capability, such

indicators as experiences, technological know-how,

skill levels, educational levels, and R&D activities

impact on successful technology design, generate

and transfer more than other indicators. On the one

hand, in organizational capability, indicators like

decentralization and granting more independence to

authors and faculty members in relation to industry,

lack of sufficient resources for technology transfer,

improper organizational structure, lack of adopted

regulations on how to protect intellectual properties,

laws and rules governing technology transfer

offices or research offices, and lack of experienced

and specialized managers and personnel in these

offices, dearth of internal laws on how to regulate

authors’ contribution, and lack of a clear strategy as

a set of guidelines for technology transfer

management without any interference in training

missions can weaken the performance of authors in

technology transfer activities more than other

organizational barriers.





35

Studying other important factors on technology

transfer projects effectiveness such as

environmental, cultural, technology transfer paths,

technology nature and technology transfer contracts

are, inter alia, considerable subjects for future

researchers. One can study these factors in terms of

their impact on successful technology transfer or

identify new factors not mentioned in the literature

but influential in technology transfer process from

knowledge- based centers to Industry in the view of

elites.

APPENDICES

Appendix 1: Constituents of technology transfer process

capabilities and their sources

Indicator Source

Organizational capability

Organizational structure

(concentration in decision

making); managers’ skills

in strategy formulation;

transparency in conducting

technology projects

process; establishing

multipurpose and specialty

teams; identifying and

devising processes

proportionate to technology

transfer functions;

awarding methods;

facilitating policies

(domestic laws on

regulating employees’

partnerships and keeping

intellectual property rights)

Santro and GoplaKrishnan

(2002), Chen and Hwang

(2007), Pertusa and Ortega

et al (2010), Ghani et al

(2002), Liao (2010),

Zheng (2010), Abdulghani

(2000), GoplaKrishnan

and Santro (2004),

Aldridge (2010), Santro

and Wiberlely (2006),

Sigel et al (2003), Caldra

and Diandeh (2010)

Relational capability

Fluent flow inside the

organization; fluent flow

outside the organization;

working with supplier,

rivals and customers;

working with research

institutes; networking of

R&D personnel with other

institutes

Hamert (2004),

Abdulghani (2002), Nahm

(2003), Reiter (2004)

Technological capability

Technology changes

predictability; utilizing

advanced ICT; developing

and improving

technological resources

based on market needs;

technical support of

technology transfer

activities; installing,

Betacharia and Arova

(2007), Doctor et al

(2007), Wang (2004),

Reitter (2004), Yum and

Li (2010), Bieshop (2011)

commissioning and

utilizing new technology;

investments in R&D and

labs; the amount of firm’s

technological knowledge;

proper physical

infrastructures; supportive

infrastructures to back up

in terms of finance,

information, skills

development and

technological

intermediaries

Knowledge capabilities

Fascination capacity (skills,

training, R&D activities),

receptor’s technology

knowledge base,

experience in technology

transfer activities,

adaptability and integrating

new knowledge with

current organizational

knowledge – the adequacy

level of knowledge

capabilities and

organizational learning to

design new technology, the

level of structured and

coded knowledge

evidences (against implicit

knowledge) on technology

Mu (2010), Kodama

(2008), Doctor (2007),

Bishop (2011), Pertusa and

Ortega (2010), Santro and

Wieberley (2006), Albraik

and Ernsal (209), Strautch

and Evert (2006), Fabrisio

(2009), Fontana (2006),

Giuliani and Arza (2009),

Chen and Hwang (2009),

Lienberg (2001)

Appendix 2: Constituents of knowledge

management, technology transfer effectivenssand

its sources

Indicator Source

Knowledge management

Knowledge generation and

acquirsition; documentation;

refining, listing and

integrating knowledge

resources; knowledge

storing; revising, evaluating

and updating the knowledge;

knowledge dissemination;

using the knowledge; and

knowledge development

Daruch (2003), Gupta et

al (2000), Yang (2010),

Davenport and Prusak

(1998), Yan (1994),

Atfeh (1999)

Technology transfer

effectiveness

The rate of manufacturing

spare parts inside the

company; dependency of

receptor to technology

sender to perform the

activities; sale growth;

increasing market share;

profitability; developing new

Stock (2005), Reisman

(2005), Shaoji (2006).





36

products; improving the

quality of products

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