Journal of Middle East Applied Science and Technology (JMEAST) 


ISSN (Online): 2305-0225 

Issue 1(7S), August 2014, pp. 1-7 







Human capital and economic growth are among main 

factors of development of countries and are as important issues in 

economics, especially in developing countries. Determining effective 

factors on Human capital and economic growth can helps to choose 

relevant economic direction and accelerate developing process. 

In this research we surveyed Fava analyzes in Iranian provinces 

using endogenous growth models in Panel data format at years of 

2004-2011. According to obtained results, Information and 

Communication Technology effect on economic growth of Iranian 

provinces has been positive and significant and also Fava effect on 

human capital in Iranian provinces is negative. Thus, Fava 

development can be applied as effective policy in Iranian 

development and growth process. 




Economic Growth, ICT, Panel Data, Human Capital


I.  I



neimportant and emphatic factor in improvement process of 

production factor technology is ICT and its positive 

consequences on production factor productivity and economic 

growth. The elements of information technology and 

communications are not similar to physical machines as they 

contain programming languages, web sites, conversation 

rooms, MP3, online transaction and look ups, electronic 

money, electronic government and Internet and so on [5]. In 

recent years positive effects of IT have appears in developing 

countries, IT expenditures also increased and as conducted 

researches in developing countries don’t have same results in 

this area, still there is a base to surveying IT phenomena in 


Faculty of Economic & Management, University of 

Sistan&Baluchestan,Zahedan, Iran *Corresponding Author Email:  

Faculty member, University of ShahidBahonarKerman,Iran 

Master of Economic Sciences, Department of Economics and Accounting, 

Islamic Azad University Central Tehran Branch:


these countries which have potential, relevant infrastructures 

and human capital in this area and investment on it. But 

despite of these suitable potentials in developing countries, 

especially in Iran, still Supply deficit and low production are 

among main features of these countries and low productivity 

level is mentioned as main .Some economists tried to explain 

new technologies as growth factor in endogenous growth 

models and in this issue separating human capital from 

technology as coded knowledge is one important issues that 

cause defining information technology as Research & 

Development (R&D) in these endogenous growth models 

which consider long term growth is function of growth of 

Information Technology (IT) [12]. 

2-Theoritical Framework 

Fava sector has been interested in recent years, as we will 

see in continue this sector can survey in two aspects. Fava 

sector in production of goods and services is interested in 

supply aspect that has standard definition on size and industry 

structure, employment, business and value added. So Fava 

sector contains activities which provide Fava goods and 

services. Unlike other industries which have specific 

bordering between goods and services, there is no specific 

border in Fava sector [3].


There are four indices to defining Fava as follow: 

1-  Indices which show size of Fava industry as part of 

total economic. 

2-  Indices that show size and extension Fava 


3-  Indices which measure level of using Fava by firm 

and households. 

4-  Indices which measure preparation, price and quality 

of services.  

  In this sector, we will briefly explain used indices for Fava 

in global level [11]. 

In Solow model technology imagined endogenously and 

considered as gift from paradise which automatically pursue 

its way. But relation in economic growth set thought and 

The Role of Information and Communication 

Technology (ICT) and Human Capital in 

Economic Growth 

Kamran Mahmodpour*, Yaser Sistanibadooei, Saeed Khodabakhshzadeh 




Journal of Middle East Applied Science and Technology (JMEAST) 


ISSN (Online): 2305-0225 

Issue 1(7S), August 2014, pp. 1-7 




exogenous models rose. These exogenous models considered 

technology as one endogenous effective factor in production 

and economic growth and defined the effect of technology in 

different ways such as human capital, improve the quality of 

production and progress in produce variety goods in model. 

Lucas presented his endogenous growth model via defining 

human capital in neoclassic model. Aghion and Hiout in their 

paradigm based on Shompiter viewpoint, focused on 

improving quality of production as sign of new technology 

which surmount old technology producers. Naturally 

Grossman and Helphman and Roomer also, developed 

endogenous growth models which contain new technologies 

that research and development activities lead to produce 

technology and it can predispose for economic growth [1]. 

Primary researches on economic growth more focused on role 

of physical capital but economists make new literary in this 

area by defining research and development (R&D) and  

knowledge and new technologies terms.


Fava Impressments on Economic Growth and Human 


  ICT can impress economic growth in different ways as 

follow (Quah, 2003). 

First way: direct way appears via produce ICT goods and 

services and qualitative & quantitative growth of gross 

domestic product. i.e.  Fava goods and services production is a 

part of added value of economic. 

Second way is applying ICT at production function as 

capital input which lead to economic growth via profundities 

and renewing in technology and production process. 

Third way; ICT create spillover via help to technology 

expanding and predispose for creativity and innovation which 

this leads to appear knowledge economy as well as  more 

productivity of labor force and finally real production will 

increased in this way. 

Totally both endogenous and exogenous growth theories are 

unanimity on Fava impressments but their affectivity and 

interpretation methods are different. Thus, we can conclude 

that Fava helps economic growth of each country via 

profundities of capital, improve productivity of labor-force 

and technical progress, increase in network effects and 

spillover to economic growth of countries. And this 

phenomena will more appear when time goes and accepted by 

economic activitists. It can be mentioned that Fava effect is 

not same in all sectors and depends of Fava degree of sector 

and economic of countries  

In macroeconomic level there are two main approaches 

toward Fava impressments. First one consider the growth 

model which increased via increasing in size and more 

productivity in Fava sector and in this approach we consider 

just the effect of production that directly made by Fava sector 

(not indirectly) as this sector has quick growth, thus producing 

process has increasingly trend and consequence is increase in 

direct gross production. So this approach ignores the topic that 

Fava is a part of other sectors (they are more encounter to 

spillover sector or product of Fava). The second approach 

focused on Fava institutions and applicable Fava sector 

aspects and comes back to those explanations in theoretical 

framework which were on profundities and increasing in total 

productivity. Researchers of this area believe that produce per 

capita increased via increase in Fava investment. Here 

theoretical background is Solow theory which mentioned 

before and specified that Solow had separated Fava capital 

from non-Fava one. It can be mentioned that here its own 

problems are exist such as no ability to access to data in 

developing countries in this area. Empirical researches can be 

divided into three main sets as growth accounting paradigm, 

growth theories and stability paradigm [3]. 



3-Emperical Researches 

Empirical Researches on Growth Accounting Paradigm                 

These studies had used abroad Solow production function 

which contain physical capital, Fava capital, labor-force and 

technology. Fava capital divided to three main sets as soft-

ware, hard-ware and communication. Jergenson, Ho and Stiro 

(2006) showed that Fava explain 37% of US economic growth 

in 1995-2003. Davari (2002) show that Fava share of 

economic growth had been further in second-half of 1990 

decade in compare with first-half at some European countries. 

Whereas positive correlation between Fava investment and 

growth of productivity has not been proved in these countries, 

it per se resonator the productivity puzzle is some surveyed 

European countries. Piatoscky and Argi (2005) compare role 

of Fava in Eastern European countries with western countries 

and show that Fava has strongly increased work productivity 

in eastern and central European countries and its most effect 

was in 1990 decade. Hyun-Joon Jung (2013) investigate Fava 

direct effect on economic growth by focused on its effect on 

industry using accounting method and finally confirm Fava 

positive effect on industry. 

Empirical Researches on Growth TheoriesParadigm                 

 In growth accounting method, to measure growth, we used 

production function in focus on production factors and their 

role in production, but in growth theories unlike above 

explained mechanical separation in accounting, we pursue 

factors which are affect economic growth. For example 

openness trade degree of countries is not a production factor 

but its positive effect on economic growth has been proved in 

researches. So in this method we consider both production 

factors in growth and a set of other variables which affect on 

economic growth. 

Dowan and Crammer in another work, studied panel data of 



Journal of Middle East Applied Science and Technology (JMEAST) 


ISSN (Online): 2305-0225 

Issue 1(7S), August 2014, pp. 1-7 




seventeen countries (they divide them in two set of developed 

and developing countrie) in years of 1985-1992 to test the 

positive effect of Fava and finally they conclude that results 

for developing countries are accurately inverse with results for 

developed countries. Lee et al (2005) survived causality 

relationship between gross domestic product (GDP) and Fava 

beside Solow residuals for twenty developed and developing 

countries using Cob-Doglass function in years of 1980-2000 

and showed that unlike developed countries, developing 

countries cannot use Fava investment to improve productivity. 

Erbikam (2005) by applying statistic data in 153 countries 

(more focus on developing countries) using substitute indices 

and Fava distribution in years of 1995-2003 and finally strong 

relationship confirmed between them. Blorgi et al (2006) 

evaluated growth factors and more focus on Fava in 25 

countries using syncretistic and GMM methods in 1992-2000 

time period. They finally observe the positive relationship of 

both Fava production and Fava expenditure with economic 

growth. Corrado and Hulten (2010) surveyed effect of 

productivity of implicit capital and conclude that Fava has 

considerable effect on labor-force productivity and 

consequently on economic growth.  

Mahmoodzadeh and Asadi (2007) surveyed ICT effects on 

labor-force productivity growth in Iran using ordinary least 

squares (OLS) method and time series data in 1971-2004 as 

time period. 

Empirical Researches on Production Level in Stability 



In two previous methods we used data in country level to 

calculate growth than in growth accounting focused on 

institutions in production function as well as institution subject 

and some more factors such as trade openness degree of 

countries which have control role and to show more better 

economic growth of countries in growth theories method. But 

in stability paradigm that extracted from Mnico model and for 

the first time used by Pojola to show the relationship between 

growth and Fava, we pursue different method. The advantage 

of this paradigm is considered  priority economic situation of 

countries as well as provide capability to empirical estimation 

without need to data of human capital, Fava and non-Fava 

variables. The main problem of two growth accounting and 

growth theories approaches is the need to Fava and non-Fava 

capitals data is necessary and to solve this problem we can use 

growth paradigms in stability paradigm  which constant return 

to scale is regarded in them, when these data are not exist. 

Pojola (2001) evaluate the effect of Fava on 39 developing 

and developed countries using Mnico et al model and include 

Fava investment at his model in years of 1980-1995. He also 

used GDP on Total active labor-force ratio, Fava investment 

and non-Fava investment on GDP ratio and registration in post 

elementary coerces rate as human capital index and population 

growth rate. Fava coefficient in OECD countries has been 

significant and most of cases Fava capital production elasticity 

is more than non-Fava one. In Iran, Moshiri and Jahangard 

(2004) used Pojola model and add some control variables such 

as inflation and time series data on 1369-2001 time period, 

estimated space-case model for Iran. Their ssults show that 

there is positive and significant relationship between 

investment in communication sector and economic growth in 

Iran. Komeijani and Mahmoodzadeh (2008) in their two joint 

works, used growth accounting and stability paradigms to 

study developing countries at Fava and economic growth 

aspects in years of 1995-2003 and finally confirmed the 

positive relationship between these variables (in these two 

studies, their samples contain Iran and growth accounting 

paradigm was just for Iran). Porfaraj, Esazadeh and Cheraghi 

(2008) surveyed the Fava relation with economic growth and 

tourism industry in years of 2000-2006 for more than 70 

countries and showed that more share of Fava expenditure on 

GDP in sub-sectors of computer, financial, education and 

transportation in tourism industry lead to more edtourists 

absorption in country. Osar-e-Arani and Khondabi (2008) 

studied the relationship between ICT and economic growth for 

OPEC countries using panel data in years of 1998-2004 and 

confirmed the positive relationship between them. Najarzadeh, 

Khondabi and Talati (2007) surveyed the relationship between 

ICT and economic growth for organization of Islamic 

countries (OIC) members using panel data in years of 1996-

2004 and confirmed the positive relationship between these 

two variables. 

Shojaei and Beigi (2010) studied Fava relation with 

economic growth using endogenous model for Iran. And more 

accurately by time series analyzes and autoregressive 

distributed lags (ARDL) model and error correction 

mechanism. They conclude that there is no significance 

relationship in Fava sector respect to non-Fava ones. Jafari in 

his master dissertation surveyed Fava investment relation with 

added value in transportation sector for Iranian provinces at 

2002-2004 as time period using panel data method. Finally, 

he, confirmed Fava effect on added value of transportation 

sector with special details. In recent studies in Iran, Fava has 

been title for some of them and they found that there is no 

relationship between Fava and economic growth and in 

following we very briefly introduce some of them. Asgharpoor 

and Mohammadzadeh (2011) surveyed development 

indicators effects on accept and use of Fava in Asian 

countries. Ziarati, Mohammadpour and Manochehri (2010) 

surveyed importance of Fava infrastructure developments in 

globalization process as well as Poorfaraj and Eisazadeh that 

in their last work study the Fava effect on economic growth 

and development for 14 countries at 2000-2006 time period 



Journal of Middle East Applied Science and Technology (JMEAST) 


ISSN (Online): 2305-0225 

Issue 1(7S), August 2014, pp. 1-7 




and used Jini coefficient as proxy for development and digital 

opportunity index for economic growth of percapita 


4-Model Specification 

By consider above mentioned matters in theoretical 

framework and overview on empirical researches in this area, 

to estimation Fava effects on value added in Iranian provinces, 

three methods have introduced that contain production 

function method, growth accounting method and applied 

growth theory and here for obtain inclusive model we use 

Pojola (2001) paradigm: 


Y =  A�








Where Y is production, L: labor-force, H: human capital, K: 

non-Fava investment, C: Fava investment, A is technology 

level and exponents is representative of their elasticity. Taking 

logarithm of production function, the model will be linear as 



���� = ���� + �

���� + �

���H + a

Log� (2)      


 Here we suppose that data on these variables are access and 

we follow to time series analyzing of one country or in 

international level (or for one province or provinces of 

country) by this model, but as there are some problem in level 

of these variables often we applied growth rate them. So take 

dereviation respect to time, we have: 



= A


+ a



+ a



+ a


+ �




This paradigm is estimable for time series data and 

international analyzes. Thus we consider the constant return to 

scale assumption and payment to production factors should be 

based on their marginal production. In this case a coefficient 

show the share of factor of total income and this is growth 

accounting for determining share of production factors from 

product growth.  

All factors are observable in above equation except change 

of technology (A) and these changes obtain as Solow residuals 

and usually imply as total productivity of factors (Jafari, 2010, 

p98). As in empirical estimations, we are encounter to such 

problems like not accessibility of Fava capital and its share of 

national income (these data are access in just a few developed 

countries), so we have to use proxy or some estimations for 

existence capital and Fava investment (Davari, 2002). 

Existence capital obtained by applying growth paradigm and 

developed neoclassical growth models by Solow contain more 

than one type of capital (Mncio et al, 1992). 

Pojola used that Moncio idea and present a model as follow: 

Y = C









Where it difference with previous model is this is workfare 

type as well as constant return to scale and can be limit by 

hoarding all three type of capitals (physical, Fava and human 

capitals). Solow model assume that constant part of production 

invested in three types of capitals. In this paradigm C, K and 

H are existence of physical capital, Fava and human capital 

respectively and L is labor-force. Also in this model assumed 

that following relation are holds: 

5) y=Y/AL 

6) c=C/AL 

7) k=K/AK 

8) h=H/AL 

9) n  e 





  = N

10) g e 







Production per each unit of labor-force 

Physical capital per each unit of 

effective labor-force 

Fava capital per each unit of effective 


Human capital per each unit of 

effective labor-force 

Labor-force growth during the time 

with growth rate 

Growth of technology during the time 


Here it is necessary calculate the equations of change in all 

types of capital: 










− �














+ �








− �











We suppose that investment (change in existence capital 

respect to time) is percentage of production (sY) plus a part of 
capital that will be depreciated, 



= �

� − �

�, so in this 

case we will have: 


= �

�(�) − (� + � + �





= �




= � 


Based on this growth equation method, other capitals are 




= s

Y(t) − (n + g + δ



= s

Y(t) − (n + g + δ




Where S coefficients are saving rate of each type of capitals 

and & is their depreciation rate, so by use of production 

function we can write: 


� = �





→ � = �



Using all equations for existence of capitals, we can obtain 

optimum value for each of capital as follow: 



Journal of Middle East Applied Science and Technology (JMEAST) 


ISSN (Online): 2305-0225 

Issue 1(7S), August 2014, pp. 1-7 




� = (




� + � − �






� = (




� + � − �






ℎ = (




� + � − �









 By substituting (16-18) equations in (15) and solve it based 

on � =

, we have: 


Log y = a


+ �


1 − β

� Log S

+ �


1 − β

� Log S

+ �


1 − β

� Log S

− �




1 − β

� Log (n + g + δ) 





log (0)










a a






. Also 

depreciation rate 


 is equal for all types of capitals and 

assumed that 



. As a result it can be mentioned that 

stable level of production per capita has positive relationship 

with saving rate of each type of capitals as well as negative 

relationship with population growth rate and depreciation rate. 

Thus, per capita production will be further in provinces that 

have more investment in FavaIf data on investment rates (or 

saving rates) be access for each type of capital, we can 

calculate above relation. In majority of researches sum of 

growth of technology, population and depreciation rate 

considered 5%. Three point on above model, first Doglass 

specification of technology signify earned income should 

cover constant share of national income by existence Fava 

capital as this case will be problem in increase of Fava case. 

Secondly considering depreciation is not true as Fava 

equipments have short lifetime in compare of other capitals 

and finally as third point implicit assumption of this model is 

that all provinces are at stable situation. For first two points 

not much work can be done, but Pojola (2002) solve third one 

with convergence modeling into stable case. Convergence 

topic in growth is meaningful when growth is surveyed in 

international (or between provinces) level as poor country (or 

province) has more quick growth than rich country (or 

province). I.e. poor country is going to obtain favorable 

growth rate. Different countries have various favorable growth 

rate and we can calculate effective factors in this stability via 

equation (19). Here necessary point is we can consider 




n g


δ β


+ +

 as convergence rate in growth. 

According to Barro and Salay, Martin (2004) which 

investigate effect of 67 variable on economic growth, there is 

no possibility to survey all variable because of statistical 

limitation and degree of freedom subject. Above model is 

most possible inclusive model as we can both its parts to 

estimate growth accounting and some parts as growth theories 

and finally its some other parts for stability paradigm. In 

following, we suggest a model to estimate the growth rate in 



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Introduce of Variables 

Gross Domestic Product (Value Added): in economics 

point of view it is difference between output value and input 

value. In our model, we used gross domestic product data and 

gross domestic product per capita data for each province (in 

present price) which published by Iranian Statistics Center 


Existence Physical Capital (None-Fava):  one of 

important factor that allocate much share of income (product) 

of country is existence capital and in majority of researches 

used constant capital formation ratio as proxy for it. We by 

consider this implicit assumption that capital of country 

proportionally distributed in provinces and used non-Fava 

formation ratio on production in Iran by extracted data from 

Iranian Statistics Center (ISC). 

Existence Fava Investment: Fava investment like non-

Fava investment is production factor which divided to several 

sectors such as communication sector capital, hard-ware sector 

capital (Fava infrastructure), soft-ware sector capital (applied 

Fava) and product sector capital (Fava spillover). So indices 

like capital formation of communication on production ratio 

for first sector that its data published by ISC and we can 

estimate it for each province but for other three factors there is 

no data even in country level. 

Employment:  labor-forceis one of the most important 

productions factor that its combination with other inputs 

especially with capital can be value created. To access data of 

this variable we used Iranian labor-force information data 


Human Capital: knowledge and skills that labor-force 

earned via education, training and experience called as human 

capital. Many proxies have been used as proxy to human 

capital in different studies and here we used education 

expenditure on gross domestic product ratio and its data as 

well as other variables extracted from ISC annually reports. 




Journal of Middle East Applied Science and Technology (JMEAST) 


ISSN (Online): 2305-0225 

Issue 1(7S), August 2014, pp. 1-7 




Model Estimation 

After extracting related data for explanatory variables for 

years of 2008-2011, we select pane data methods to estimate 

of model as fit model. Here the point is in majority of 

conducted researches unbalanced data have been used, but we 

tried to solve this problem (i.e. problem that data of middle 

years created) then to select between fixed or random effect 

estimation, we used Husman test. 

Panel data analyzes have different ways in estimation of 

model that fixed effect method and random effect method are 

important ones. Fixed effect term means that despite variety in 

intercepts in length of lags, but intercept of each lags is 

constant during the time and often we used pool method of F-

test to choose this method. In fixed effect model as there are 

too dummy variables, degree of freedom will decrease and to 

solve this problem random effect model has been suggested 

and to identify fixed effect from random one we can use 

Husman test. The null of Husman is fixed effect are efficient 

and stable and alternative hypothesize is fixed effects are not 

efficient and stable.




Dependent variable is Gross Domestic Product Per Capita 







Log (K/Gdp) 



Log (Kh/Gdp) 



Log (Kc/Gdp) 



Log (N) 













Investment in Fava coefficient is positive and acceptable in 

statistical manner as according to model results its coefficients 

during 2004-2007 is 0.08 and also as we used Log function of 

variables in estimation, obtained coefficients are elasticity of 

variables. Obtained coefficient for Fava proxy (ICT 

combination index) is equal to 0.36 that is acceptable in 

statistical manner. To test Fava effects on production (Value 

added) we consider total investment in Fava respect to total 

value added for each province as well as using human capital 

expenditure index on production as proxy for human capital 

situation and its estimated coefficient is negative. This 

negative coefficient is not far from expectation for developing 

countries. To explanation of human capital coefficients we 

should notice that education in each situation is not motivated 

and effectible on economic growth especially in developing 

countries that have weak economical and social structures and 

institutions and economic policies create much limitation for 

free trade and market activities. While education in each level 

lead to positive private return to everyone in all countries, but 

it is possible to don’t have positive and significant effect in 

macroeconomic level as results show this is true for university 

educations. If we look for answer to why university educations 

have different results in compare of high school education on 

economic growth and information technology, is interesting 

subject in economic growth and economic development 

literary. As education need mass investments in different 

sectors of infrastructure and institutions to become effective 

capital in production and it is not sustentative in developing 

countries, especially in Iran, these results are justifiable. Open 

economic countries (often developed countries) can access to 

more widespread markets, high technology level, more 

dynamic market, more competitiveness, better division of 

work, more flexible institutions and structures and totally 

more efficient economy by taking free economic policies. In 

these economics there are relevant infrastructure and 

institutions to transform education into capital in production 

process. For more study in human capital and economic 

growth in Iran we refer to Ebrahimi and Farjadi (2009) which 

their results are confirm ours and also is a comprehensive 

work in this area. In obtained empirical results of limited F-

test to pursue whether separate intercepts for each province or 

not, in other word to specify choosing generalized least 

squares and fixedt effect method we used F-test as well as 

Husman test to select between fixed or random effects 

methods. Obtained results show that fixed effect choose for 

both variables of Fava and with Husman test value are shown 

in above table. 


Obtained results of growth paradigm estimation show that 

ICT effect on growth of country’ provinces by using panel 

data is significant as well as positive coefficient of non-Fava 

investment which show that non-Fava investment has been 

affective on economic growth of Iranian provinces. 

Coefficient of human capital investment is negative and 

meaningless in statistical point of view and this result is 

expected in developing countries and especially in Iran. Other 

variable is number of employees in each province which its 

positive and significant effect on both types of Fava substitute 

variables is apparent. For obtained results of estimation of 

model we should notice that effect of Fava proxy on economic 

growth of provinces has been positive and significant. 


[1] Jahangard,esfandiar(2004) Effect of information 

Technology on manufacturing production in Iran  



Journal of Middle East Applied Science and Technology (JMEAST) 


ISSN (Online): 2305-0225 

Issue 1(7S), August 2014, pp. 1-7 




[2] Mahmoudzadeh,Mahmoud and Asadi,Farkhondeh(2007) 

Effect of ICT on labor productivity growth in the Iran 


[3] Komeijani,Akbar and Mahmoudzadeh,Mahmoud(2007) 

Impact of ICT on economic growth in Iran.The growth 

accounting approach 

[4] Mahmoudzadeh and Asadi(2007) ICT impact on labor 

productivity growth in the country 

[5] Najarzadeh,Khoundabi and Talati(2007) ICT impact on 

labor productivity growth in Islamic countries 

[6] Pourfaraj,cheraghi and Roshan (2008) Relationship 

between ICT and economic growth in the tourism industry 

for selected countries 

[7] AssariArani and Khoundabi(2008) ICT relationship with 

economic growth in Opeccontries 

    [8] AssariArani,Abas and Khoundabi,Majidaghaei(2008) 

Impact of ICT on growth opec 

[9] Yazdani and Farjadi(2009) Impact of education on 

economic growth 

[10] Ziarati,Mohammadpour,Manouchehri(2010) The 

importance of ICT infrastructure developmentin the 

globalization process 

[11] Jafari,somayehmasters thesis(2010), value added 

relationship of transport section with ICT 

[12] Shojaei and Beygi(2010) ICT relationship with economic 

growth in Iran with time series [13] Pourfaraj and 

Roshan(2010) ICT impact on economic growth and 

development in developing countries 

[14] Asgharpour and Mohammadzadeh(2011) Adoption of 

development index on ICT acceptation 

[15] Jorgenson, D. W. and Stiroh, K. J., (2000) ; "Raising the 

Speed Limit: U 

[16] Pohjola, M., (2000) ; Information Technology and 

Economic Growth: A 

Cross Country Analysis, UNU/WIDER Working, p.173.

  Economics Research.Discussion Paper No. 2002/67. A. at 

[17] Jorgenson, Dale W. and Stiroh, Kevin J., (2000) ; "US 

Economic Growth and 

the Industry Level", American Economic Review, 90 (2) , 


[18] Pohjola M., (2002) ; "New Economy in Growth and 

Development", United 

Nation University, WIDER (Word Institute for Development) 

[19] Quah, D. (2002) Technology dissemination and 

Economic Growth : Some Lessons for the New Economy; In 

Technology and the New Economy, (ed.) Chong-En Bai and 


[20] Barro, R. J. and Sala-i-Martin, X. (2004) ; Economic 

Growth, 2nd Edition, MIT Press, London, Chap. 12, pp. 511-


[21] Jorgenson, DW., HO and Stiroh KJ., (2005) ; 

"Information and American 

Growth Resurgence", Cambridge, MIT Press. 

[22] Orbicom (2005) ; the Digital Divide to Digital 

Opportunities: Measuring Info 

State for Development, Published by Claude-Yves Charron. 

[23] Jorgenson, D. D., Ho, M. S. and Stiroh, K. J., (2006) ; 

"Potential Growth of 

the U. S. Economy: Will the Productivity Resurgence 


Journal of Business Economics, pp. 7-16. 




Review ofIncomeandWealth, 55, 661–685. Dolage, 




manufacturing industry. Economic Modeling, 27, 395–403. 

[26] Hyun-JoonJung(2013)The role of ICT in Korea’s 

economic growth: Productivity changes across industries since 

the 1990s 




Journal of Middle East Applied Science and Technology (JMEAST) 


ISSN (Online): 2305-0225 
Issue 1(7S), August 2014, pp. 8-12 





This study is examined the role of knowledge 

management on the creativity of secondary school principals of 
Mazandaran. The method of this research is descriptive and the 
correlation type. The statistic study community are consisted of 617 
individuals, all which are secondary schools principals of 
Mazandaran. The sample size determination was done by using a 
table of Kerjessi and accordingly, 238 individuals were selected by a 
stratified random sampling method. The data collection tools were 
included the questionnaire of the lavson management knowledge with 
23 questions and the Rendsyp questionnaire containing 50 questions 
which were answered by principals. The currency and reliability of 
questionnaires contents were confirmed by experts and  the ending 
(reliability) coefficient by using the Cronbach Alfa coefficient for 
each of questions was counted 0.72 and 0.84 respectively. The data 
collected were tested by using the Pearson correlation coefficient, 
multivariables regression test and the Z Ficher test. The results of 
survey are showed that there are a positive and significant correlation 
between knowledge management and creativity of principals, and the 
gender don't have any influences on knowledge management  on 
principals' creativity


creativity, knowledge management, Mazandaran 

province, principals, secondary schools. 


I.  I



Today, most experts in education believe that an education is 
the main Learning-Teaching organization in community in 
order to meet the new ages challenges needs to shift and 
transfer the learning community and enjoying an efficiency 
management strategy [15].  so that, principals become aware 
of the importance of knowledge and managing it in 
organizations, and many of them are looking to implement 
knowledge management in their organization, but also they are 
considering this case  that they fail to implement knowledge 
management in their organizations, and the knowledge 
management in their organization fails, after considering the 


 F. A. Author is with the M.A of The Educational Management of The  Azad 

Slamic University of Sari, e-mail: 


success of knowledge management is a major competitive 
necessity for organization, it is important to know  whether  
their organization is ready for accepting any knowledge 
management or not? In fact, organizational leaders are asking 
themselves this questions from where should we begin, 
because knowledge management is a systematic issue? [4].  
Therefore, given the great and dramatic changes in 
technologies, management uses a tool called knowledge in 
order to deal with uncertainty factors, to maintain position, 
and to create innovations (creativity) in the field of developing 
their competitive area. All organizations  are needed new and 
wonderful (innovative) ideas for their survival. New and 
innovative ideas were blown like the soul in the organization 
body and were saved it from destroying. For this purpose, 
knowledge has a great and extraordinary importance as a main 
source of knowledge innovative and organizational efficiency. 
The main goal of knowledge management is created and 
organized an area in which people develop their knowledge , 
share knowledge with each other and combine the other 
knowledge with theirs and ultimately apply them [ 9]. since an 
acquisition, development, operational and correct management 
of knowledge were included one of the main responsibilities 
and challenges of organizations  especially an education, in 
other words, knowledge management is more important than 
knowledge, and since (an education) as organizations 
producing knowledge were included the view of knowledge 
management, the rate of application organizational knowledge 
management  factors seems necessary and appropriate for the 
correct orientation and strategy efforts [7]. On the other hand, 
it is one of the most important variables in creativity and 
innovation survey. Generally it could said that creativity is 
indicated (implied) the creation of new  things, and is leaded 
to a new and useful result [3]. Thus the scholars' view is 
different in defining creativity. Therefore, sometimes each 
definitions represents an important  aspect of the creativity 
process. For example, stephen Robbins believes that creativity 
is meaning in a manner unique thoughts or creating unusual 

The study of the role of Knowledge 

management on the creativity of secondary 

schools principals of Mazandaran


Fereshteh chari Seresty 



Journal of Middle East Applied Science and Technology (JMEAST) 


ISSN (Online): 2305-0225 
Issue 1(7S), August 2014, pp. 8-12 



relationship between views [19]. It seems that there is a 
significant correlation between knowledge management with 
creativity and innovation, that this has led to encourage in the 
organization and like a new engine make remove gaps, 
however the efficiency of educational organizations in field of 
knowledge management are supported faster and easier in 
communication and information transmission, it showed the 
importance of creativity, capability, and performance of 
knowledge management in organization particularly schools. 
Therefore, knowledge based on knowledge management  of 
principals are caused a serious survey in this area, and it is 
supposed that honesty and trust of management should be left 
to those who are watching from window of scientific and 
research administrative issues. Using knowledge management 
and creativity is an essential condition of successful 
organization including the organization of education. That 
shows the necessity and importance of knowledge 
management role and mixing up it with creativity that is 
leaded to efficiency and effectiveness of principals skills [17]. 
Knowledge management is a process that helps organizations 
to select, organize, distribute and transmit the most important  
and essential skills and data for performing their activities [1]. 
Nicy defines knowledge management as one of the duties of 
systematic education to improve its efficiency and 
effectiveness in order to survive in the emerging competitive 
environment [13]. From Malhorras point of view, knowledge 
management is a process that organizations get skills in the 
field of learning, (self-knowledge), encoding knowledge, ( 
external knowledge), and the distribution and transfer of 
knowledge by that. Steive Halls knowledge management 
perspective is different. From his point of view, this 
management is a process that organizations have ability due to 
transfer data into information and information into knowledge 
and also be able to operate effectively  achievement g 
knowledge  in their decision. Hanis point of view of 
knowledge management  is a process that is based on four 
following elements. a) Content: that is concerned to the type 
of knowledge (whether explicit or implicit). b) Skill: acquiring 
skills for knowledge extraction, c) Culture: culture of 
organizations should be encouraged to distribute knowledge 
and information. d) organizing: organizing available and 
existing knowledge. Generally,  it be said that knowledge 
management is meaning the creation of necessary processes 
for identifying and capturing and acquiring data. The 
information knowledge is needed  for organizations from 
internal and external environment and transfer them to the 
decision and actions of organizations and individuals that are 
included  organizational employees and managers (internal 
environment) especially schools principals in its territory [18]. 
Studies show that there is many researches on the role of 

knowledge management field of organizational activity, but at 
the discussion of this survey that investigate more the 
relationship between knowledge management with the rate of 
schools principals creativity, has been done a little research. 
The present survey seeks to eliminate this deficiency and 
demonstrate the mechanism of the effect of knowledge 
management on principals' creativity, and a holistic 
perspective to performance frame and relationship of 
knowledge management has provided a better understanding 
of knowledge management for research in creativity field.  
Background research 
-The study results of Ghaedi et al. (2013), as the relationship 
between occupational commitment with the value of creativity 
of secondary schools principals in Bushehr is showed that 
there is a positive and significant relationship between 
occupational commitment and the value of creativity of 
secondary schools principals[6]. 
- Nayer et al. (2012), in a survey as the relationship between 
knowledge management and creativity among academic 
librarian of Shiraz university library concluded that there is a 
positive and significant relationship between two variables 
means knowledge management and creativity. While the 
gender, work experience,  and education have no significant 
effect on librarians creativity[11].  
- NiazAzari (2011), examined a survey as the studying role of 
knowledge management on teachers creativity. The results of 
this study showed that there is a relationship between 
knowledge management with teachers creativity . And also an 
impact of knowledge management has no difference on female 
and male teachers creativity and the variable publication of 
knowledge has the strongest relationship with creativity 
among five variables[12]. 
- Rahimi et al. (2011), a review of research on relationship 
between knowledge  management process and creativity 
among university faculty members of Esfahan university 
reported that there is a positive and significant between 
knowledge management dimensions with the correlation 
creativity, and there is no significant differences between the 
average level education of knowledge management faculty , 
age, and the field of study[14]. 
- Sarchahani et al. (2011), in a research as the studying the 
effect of an individual factor on secondary schools principals 
creativity in four districts of Shiraz concluded that creativity 
of secondary schools principals of Shiraz are relatively 
- Fasih (2008), studied an effect of management styles on 
teachers creativity of Kerman. The results showed that 
management styles and gender will affect a remarkable 
amount of impact on teachers creativity. An environment has a 
considerable and significant impact on the creativity of male 



Journal of Middle East Applied Science and Technology (JMEAST) 


ISSN (Online): 2305-0225 
Issue 1(7S), August 2014, pp. 8-12 




and female teachers. This difference in findings  could be due 
of the culture of education system in the population studied 
that the gender differences play an important role on male and 
female activities[5]. 
- Maldonaldo et al. (2011) in their surveys entitled to examine 
the relationship between knowledge management and 
innovation among small and medium enterprises in Mexico 
concluded that knowledge management has a positive impact 
on products, process and innovation of management 
- Liao (2011) in a research on the impact of knowledge 
management strategy and organizational structure on 
innovation achieved to this results that there is a positive and 
significant effect between knowledge management , 
innovation, and creativity[8]. 
- The study results of Criscuolo et al. (2010) entitled global 
engagement and innovation in enterprise activities suggested 
that innovative multination company not only use researches, 
but also have a better relationship with retailers, vendors, and 
universities, and take advantage from knowledge and 
Thus, due to  this matter that is the development and 
enhancement of creativity as the most important goals and 
mission of educational organizations particularly an education, 
creativity and innovative management factor are affected as 
possible on schools, and enhanced their attitude to creativity 
and novelty new things in themselves and organization, and 
became an education environment into changes and innovation 
center. It could founded the necessity of this issue that if 
schools principals have had management skills 
and also creativity and innovation skill, the area of creation 
and development of creativity in schools especially students 
and teachers will be provided [12]. 
Byconsidering that knowledge management depends on 
capabilities, motivation and opportunities for individuals, and 
increases their creation value and performance by distributing 
and recreating explicit knowledge of principals, and creativity 
has preference  over knowledge  and information of principal, 
we require extensive researches in order to understand the role 
of knowledge management and enhance creativity skills that it 
is possible to boost creativity in environment such as schools 
and other organizations which need to creativity. Therefore, 
the main purpose of this study was to investigate the role of 
knowledge management on secondary schools principals 
creativity of Mazandaran and provided some 
recommendations to an education officials that based on the 
fundamental principles of this survey is included: 
1. There is a significant relationship between knowledge 
management and the secondary schools principals creativity. 

2. The impact of knowledge management on creativity of 
women and men principals are different. 
Materials and Methods 
 This survey is descriptive correlation method. Its population 
of statistic community is all of the secondary schools 
principals in Mazandaran in 1392 that are consisted of 617 
individuals . Morgan and kerjessi table is used to determine 
the sample size  which is based on a sample of 238 individuals  
who were selected by a stratified random sampling method. A 
questionnaire was used to collect data that questions are set 
based on the Five- choice likert scale options ( completely 
disagree, disagree, no option, agree, completely agree). The 
numerical values of this five options are numbered zero to 
four. It means that the numerical value of completely agree is 
zero, and completely disagree is 4. The questionnaire is 
consisted of two parts, Lavson questionnaire that is containing 
23 questions was used to measure knowledge management in 
the first part. Rendesyp questionnaire that is containing 50 
questions, was used for measuring the value of principals 
creativity in the second part, and also was used to express and 
interpret the results by table. Thus, the score from zero to 19 is 
non creativity, 20 to 39 is under average, and 80 to 100 is very 
creativity. Then the total scores are calculated for each 
individuals and the most score is showing to be creative, and 
the less score represented to be non creative in organization 
that this questionnaire are derived from Gholikhani (1388), 
cronbach Alpha coefficient method was used for determining 
the validity test that its conclusion coefficient value for 
knowledge management questionnaire was %84 and for 
creativity questionnaire was %72. Data were analyzed by 
using SPSS soft ware that information obtained in descriptive 
level in the form of frequency distribution tables and column 
charts were provided and in the inferential statistics level, 
Pearson correlation coefficient test were calculated to 
influence and the relationship of knowledge management on 
principals creativity and for the female and male subjects, 
bivariate regression correlation coefficients matrix between 
variables were calculated. 
Findings resulted from demographic specifications  
A total 238 samples, 137 individuals about %57 of 
participations were women, and 101 individuals about %42.4 
were men. Also, in terms of education, 27 individuals (%3) of 
participants were under graduated, 24 individuals (%50) had 
bachelor's degree (B.S), and 61 individuals (%25.6) had  M.A. 
. The results statistical description about employment record 
variable suggests that from total of 238 samples, 10 
individuals ( more than %4) had 5 to 10 years of employment 
records, 68 individuals (%28.6) had 11 to 15 years of 
employment records,  86 individuals (%36.1) had 15 to 20