Knowledge Sharing Practices among Academicians: Assessing the Role of Demographic Variables

International Journal of Business

Management & Research (IJBMR)

ISSN 2249-6920

Vol. 3, Issue 4, Oct 2013, 113-124

© TJPRC Pvt. Ltd.

KNOWLEDGE SHARING PRACTICES AMONG ACADEMICIANS: ASSESSING THE

ROLE OF DEMOGRAPHIC VARIABLES

G. NAGAMANI1 & J. KATYAYANI

2

1Research Scholar, Department of Business Administration, Sri Padmavathi Mahila Viswa Vidyalayam, Tirupathi,

Andhra Pradesh, India

2Research Supervisor, Department of Business Administration, Sri Padmavathi Mahila Viswa Vidyalayam, Tirupathi,

Andhra Pradesh, India

ABSTRACT

This research paper tries to probe the influence of Demographic Variables (individual characteristics) such as age,

gender, qualification, designation and working experience on knowledge sharing behaviour. The data is sourced from

academicians of private engineering colleges in YSR district, Andhra Pradesh. Research instrument for measuring

knowledge sharing behaviour are developed from an extensive literature review. The study results revealed the significant

but weak relationship exists between demographic factors such as age, designation, educational qualification, working

experience and knowledge sharing behaviour. Gender is found to be insignificant with knowledge sharing behaviour of

academicians.

KEYWORDS: Demographic Variables, Knowledge Sharing, Knowledge Sharing Behaviour

INTRODUCTION

The present economy is identified as knowledge based economy because knowledge is the driving force for social

and economic development and it is becoming as the important resource for all sectors. In order to survive in this intensive

competitive environment the organizations need to clearly recognize the knowledge as an important asset for individuals as

well as for organizations (Syed-Ihksan (2004); Alavi & Leidner (1999); Vanden Hoof & De Ridder (2004); Yang

(2007)). Also various studies have concentrated on the significance of knowledge management initiatives to enhance the

organizational performance. Educational institutions, like other organizations, produce knowledge from their operations,

i.e. the process of teaching and learning. In developing countries like India knowledge sharing in educational institutions

plays a vital role in knowledge management since an individual’s knowledge will not have much impact on the

organization unless it is transferred to other individuals. However, learning institutions are struck by the same challenge

encountered by other organizations, complexity in managing the creation and diffusion of knowledge within their

organizations (Carroll et al, 2003). Knowledge sharing is observed as one of the most vital practice of knowledge

management framework, which is the contribution made by individuals to the collective knowledge of an organization.

Hence in the new economy the wise move of knowledge to create greatest value is becoming the core consideration.

Knowledge sharing facilitates the organization to avoid mistakes and help them to better prepare to grab the opportunities

as they arise. Knowledge sharing practice also provides the firm to transfer the knowledge across the departments and

organizations themselves (Ipe 2003). Many researchers have studied the significance of various factors like culture,

climate, technology etc., in enhancing the knowledge sharing behaviour among individuals (Gupta & Govindarajan

(2000) Davenport et al (1998); Nevis et al (1995); Delong and Fahey (2000)). Apart from the those factors the

demographic factors like age, gender, occupation, experience also may also have an impact on knowledge sharing

114 G. Nagamani & J. Katyayani

behaviours of individuals. Whilst the body of empirical literature on the correlates of knowledge sharing behaviour is

growing, literature that focuses on the role of demographic variables remains scarce. This study is intended to identify any

relationship between individual characteristics and knowledge sharing behaviour of academicians of private institutions.

LITERATURE REVIEW

Knowledge Sharing Defined: Several researchers have emphasized that knowledge sharing is a vital value

creating practice of knowledge management process (Sanchez, 1997; VonKrogh, 1998; Davenport & Prusak, xp1998).

Knowledge sharing is a critical process of knowledge management for an organization to manage and leverage its

knowledge (Wasko and Faraj 2000; Jarvenpaa and Staples 2000; Nahapiet and Ghoshal 1998).

Shapira, Youtie, Yogeesvaran and Jaafar, (2005) defined knowledge sharing as the process to the extent to

which knowledge is being shared among people. According to Willem, (2003) knowledge sharing is the exchange of

knowledge between at least two parties in a reciprocal process allowing reshape and sense making of the knowledge in the

new context. Volker Mahnke, (1998) expressed the knowledge sharing as a process of converting the knowledge into

manifest (explicit knowledge), gathering of de central explicit knowledge and making it accessible to others in the firm.

From the above given definitions it is inferred that knowledge sharing may occur voluntarily or conditionally. The

knowledge sharing is especially people oriented activity where knowledge is sourced from one intellect to another and to

organizational knowledge bases where different knowledge can be captured, stored, distributed and accessed by the needy.

Stimulating knowledge sharing among individuals is an important activity for any organization to sustain and develop.

Knowledge Sharing Behaviour among Academicians

Meenakshi (2002) and Sundari (2003) carried out a survey to know the perceptions of school teachers in

Singapore schools about sharing their knowledge in schools. The research revealed that knowledge sharing among

colleagues is a worthful activity and it was very helpful in enhancing individual learning.

The empirical investigation of Ingrida & Dalia (2005) emphasized the significant influence of IT both to

individual and to organizational levels of knowledge exchange. Syed Shah Alam (2009) surveyed key factors of

knowledge sharing behaviour of employees in the SMEs in Malaysia. The study emphasized on reward system, culture,

trust and technology are the four key factors that influence the knowledge sharing behaviour of employees in the firms.

Shi-Jer Lou, Yun-Shiue Yang, Ru-Chu Shih & Kuo-Hung Tseng (2007) examined the knowledge sharing

behaviour of instructors from information management departments at technological universities. The study emphasized

the importance of self-motivation, incentive mechanism, environmental equipment and information technology for sharing

knowledge.

The work performed by Keramati, and M. A. Azadeh (2007) shows the importance top management

commitment factors including strategic plan, communication, and training for the successful implementation of knowledge

management in academia.

Demographic Variables

According to Shi-Jer Lou et al., (2007) socio demographic factors such as the age, educational background,

seniority in teaching, job title, marital status, number of children and location have showed significant difference regarding

the knowledge sharing behaviour of management instructors of technological Universities at southern Taiwan. The aspects

of knowledge sharing between instructors were correlated with their demographic information.

Knowledge Sharing Practices among Academicians: Assessing the Role of Demographic Variables 115

Isaac C. Mogotsi1, J.A. (Hans) Boon1 Lizelle Fletcher (2011) investigated the relationships between

knowledge sharing behaviour and the demographic variables such as gender, age, organisational tenure and professional

tenure. This study is carried out among secondary school teachers around Gaborone, Botswana. The work revealed that

there is no statistically significant relationship between knowledge sharing behaviour and gender, age, or professional

tenure. Only organisational tenure observed to be weakly negatively correlated with knowledge sharing behaviour.

In tune with the literature the present study is mainly focused on identifying the relationship between individual

characteristics and knowledge sharing behaviour of faculty. The individual characteristics considered for this study are

gender, age, working experience, educational qualification and job designation. For the purpose of framing research

hypotheses extensive literature review is made and provided.

CONCEPTUAL MODEL

This study investigates the relationship between knowledge sharing and individual Characteristics (gender, age,

working experience, qualification, designation) in the context of the private educational institutions (engineering colleges)

in a developing country like India. For the present study Knowledge sharing behaviour is conceptualised by considering

different experiences, information, knowledge, opinions, and documents shared by academicians.

Figure 1: Relationship between Individual Characteristics and KSB

RESEARCH METHODOLOGY

This study is a part of doctoral research work, and is intended to examine the influence of individual

characteristics on knowledge sharing behaviour of academicians. The study is considered to be descriptive in nature. The

study is quantitative approach and survey method. The respondents for the study are from various private engineering

colleges located in Rayalseema region of Andhra Pradesh. The colleges have been selected through stratified random

sampling method. Through literature review a well structured questionnaire containing 23 items to measuring knowledge

sharing behaviour of respondents is developed. The items prepared on sharing of teaching related knowledge (4 items),

administration related (2 items), institution opinions (2 items), technology oriented knowledge (8 items), student oriented

knowledge (4 items) and research related knowledge (3 items). The items in the questionnaire are rated using 1 to 5 score,

i.e. strongly disagree to strongly agree, using 5 point Likert scale. The structured questionnaire is distributed among the

entire faculty of selected institutions and 334 filled questionnaires are collected within the specified period. Out of 786,


only 386 questionnaires are collected. Out of which 52 questionnaires are found to be invalid due to incompleteness. The

response rate is 42.5 %. For the purpose of analysis SPSS 16.0 version software is used. Descriptive statistics such as

frequency, percentages are used for demographic factors.

To reveal the difference between selected individual attributes and knowledge sharing behaviour, inferential

analyses such as independent sample t-test and ANOVA are applied, while to identify any relationship between selected

demographic factors and knowledge sharing behaviour and to know the strength of relation, statistical analysis such as

Pearson correlation was used.

Research Questions

Particularly, the paper tries to answer the following research questions:

Is there any relationship between demographic variables and knowledge sharing behaviour?

Is there any behavioural difference towards knowledge sharing among intellectuals with different demographics?

Research Objectives

To assess the relationship between demographic variables and knowledge sharing behaviour of academicians.

To analyse the knowledge sharing behavioural differences among various groups categorized according to

demographic factors.

Research Hypotheses

The study has hypothesized the relationship between the knowledge sharing behaviour and the demographic

variables.

H1: There is a behavioural difference towards Knowledge sharing behaviour between the gender groups.

H2: Knowledge sharing behaviour of different age groups differs.

H3: Knowledge sharing behaviour differs among the different Educational qualification groups.

H4: There is a significant difference between knowledge sharing behaviour and designation

H5: Knowledge sharing behaviour is different among the individuals with different working experience

ANALYSIS

A total of 334 respondents are participated in the study from various private engineering colleges across

Rayalseema region of Andhra Pradesh. Table 1 details the frequencies and percentages of respondents. Among the

Respondents 79.9 % (167) are Male and 20.1% (67) are female.

The respondents of different age groups have participated in the study, 50% are of between 25-30 years, 37.1%

are 31-40 years, 9.6% of 41-50 years, and 3.3% are above 50 years. The educational qualification of the respondents 20.7%

B.Tech, 1.2% B.Tech(M.Tech), 46.4% M.Tech, 18.9% M.Tech(Ph.D) and 12.9% of the respondents are Doctorates.

Respondents of different job titles have participated, among them 12.9% are Professors, 24% are Associate Professors and

63.2% are Assistant Professors. Table 1 depicts that 41.6% of respondents have 1-5 years of experience, followed by

38.6% possess 6-10 years, 11.7% have 11-15 years, 3.9% of the respondents have 16-20 years, 2.1% have 21-25years, and

2.1% have above 25 years of working experience (Professional tenure).


Table 1: Demographic Profile of Respondents

Variables Frequency

N

Percentage

% Mean

Standard

Deviation

Gender Male 67 20.1

Female 267 79.9

Age Group

25 – 30 167 50

32.53 yrs 7.1 31 – 40 124 37.1

41 – 50 32 9.6

Above 50 11 3.3

Educational

qualification

B.Tech 69 20.7

B.Tech(M.Tech) 4 1.2

M.Tech 155 46.4

M.Tech (Ph.D) 63 18.9

Ph.D 43 12.9

Designation

Assistant

Professor 211 63.2

Associate

Professor 80 24

Professor 43 12.9

Professional

Tenure

1 – 5 years 139 41.6

7.61 yrs 5.57

6 – 10 years 129 38.6

11 – 15 years 39 11.7

15 – 20 years 13 3.9

21 – 25 years 7 2.1

Above 25 years 7 2.1

The following Table 2 details the skewness and Chronobach’s alpha of knowledge sharing behaviour of the

respondents. It is observed that the respondents have an agreeable knowledge sharing behaviour with a mean of (3.86). The

skewness of data (.233) states that the data is normally distributed which is essential for further analysis. The results

revealed that the data is within the standard norms of -1 to 1. The internal coherence of knowledge sharing behaviour

variables are measured using a Chronobach’s alpha is found to be reliable with a value of 0.804.

Table 2: Descriptive Statistics of Knowledge Sharing Behaviour (KSB)

KSB

N Minimum Maximum Mean Std. Deviation Skewness Chronobach’s

Alpha Statistic Statistic Statistic Statistic Statistic Statistic Std.

Error

Knowledge

sharing

behaviour

334 2.65 4.91 3.8621 .34881 .233 .133 0.804

Valid N

(listwise) 334

Table 3 presents the means of knowledge sharing behaviour based on selected demographic variables. To test the

hypotheses H2, H3, H4, H5, i.e. to examine the knowledge sharing behavioural differences among different demographic

groups’ inferential analyses such as one-way Analysis of Variance (ANOVA) was performed. The results of ANOVA are

depicted in Table 3.

Table 3: Influence of Demographic Variables on Knowledge Sharing Behaviour

Variables Knowledge Sharing Behaviour

Mean Std. Dev F Value Sig.

Gender Male 3.88 .333

1.234 .267 Female 3.81 .402

Age Group

25 – 30 3.83 .368

1.613 .186 31 – 40 3.88 .341

41 – 50 3.92 .274


Above 50 4.00 .282

Educational

qualification

B.Tech 3.83 .410

3.120 .015

B.Tech(M.Tech) 3.66 .461

M.Tech 3.82 .326

M.Tech(Ph.D) 3.91 .365

Ph.D 4.00 .232

Designation

Professor 4.00 .232

8.998 .000

Associate

Professor 3.94 .366

Assistant

Professor 3.80 .349

Professional

Tenure

1 – 5 years 3.86 .364

2.633 .024

6 – 10 years 3.85 .332

11 – 15 years 3.94 .328

15 – 20 years 4.10 .371

21 – 25 years 3.89 .123

Above 25 years 4.04 .358

Source: Field Information, *. The mean difference is significant at the 0.01, 0.05 level. MEANS

From the information provided by Table 3 interpretations are as follows:

It is observed from the study that both men and women respondents have agreeable knowledge sharing behaviour

(KSB = 3.8621). (Mean for men = 3.88, mean for women = 3.81). From the means it is inferred that men are more

participating in KSB than women.

Respondents of different age groups gave positive response towards knowledge sharing behaviour

(KSB = 3.8621). Respondents of age group above 50years scored highest mean (4.00), followed by 41-50 years

(3.92), 31-40 years (3.88) and lowest mean for age group of 25-30 years (3.83).

From the study it is revealed that the respondents of various educational backgrounds have positive knowledge

sharing behaviour (KSB = 3.8621). the respondents possess doctoral degree recorded the highest mean score for

knowledge sharing behaviour (4.00) than those who are pursuing doctor degree (3.91), possess Master’s (3.82)

and Bachelor’s degree (3.83).

The results of the study revealed that the respondents occupying different designations (job titles) represent

agreeable level of knowledge sharing behaviour. (Mean for KSB = 3.8621). (Mean = 4.002 for professors, 3.94

for Associate Professors, 3.80 for Assistant Professors). Professors are contributing more towards KSB than

Associates followed by Assistant professors.

Respondents those have high, moderate or low Working experience (professional tenure) also exhibited positive

knowledge sharing behaviour. (Mean for KSB = 3.8621). The respondents of 1-5 years 6-10 years and 21-25

years were exhibited almost equal level of knowledge sharing behaviour. The respondents who have 16-20 years

of working experience represent highest knowledge sharing behaviour (4.10) followed by the respondents with

more than 25 years of experience.

Interpretation of Hypotheses

Presents the details on significance levels of knowledge sharing behaviour and F value against the selected

demographic variables. Analysis of variance (ANOVA) test revealed the results for the predicted hypotheses.


Hypothesis H1 predicted that there is a behavioural difference towards Knowledge sharing behaviour between the

gender groups. From the results it is observed that there is no behavioural difference towards knowledge sharing between

the gender groups (F = 1.234, p = .267). And there is no significant influence of gender on knowledge sharing behaviour.

Hence hypothesis H1 is rejected.

Hypothesis H2 testing revealed that among different age groups the knowledge sharing behaviour is homogenous.

Influence of different age groups on knowledge sharing behaviour is found to be insignificant (F = 1.613, p = .186). Hence

H2 is rejected.

Hypothesis H3 predicted that knowledge sharing behaviour among intellectuals of different educational

qualification is different. Results revealed that Educational qualification of respondents has significant influence on

knowledge sharing behaviour (F = 3.120, P = .015 (<.005)). Hence H3 is accepted. Further post hoc test is conducted to

determine that differences exist among the means.

**Note: Columns in the Post hoc test represents as follows.

Designation (I): Denotes the designation taken for comparison with the remaining designation groups.

Designation (J): Denotes the designation groups being compared with designation (I).

Table 4: Post Hoc Test for Knowledge Sharing Behaviour with Respect to Designation

Dependent

Variable

(I)

Designation (J) Designation

Mean Difference

(I-J) Std. Error Sig.

Knowledge

Sharing

Behaviour

professor Associate Professor .05963 .06443 .625

Assistant Professor .19881* .05701 .002

Associate

Professor Professor -.05963 .06443 .625

Assistant Professor .13918* .04474 .006

Assistant

Professor Professor -.19881

* .05701 .002

Associate Professor -.13918* .04474 .006

Source: field information, *. the mean difference is significant at the 0.01 level

Table 4 shows the post hoc test results for knowledge sharing behaviour for different designated groups. The

results reveal that there is a significant relationship between professor and Assistant professor (mean difference=.19881*,

p<0.01 (0.002)) associate professor and assistant professor. (Mean difference=.13918*, p<0.01 (0.006)).

H4 assumed there is a significant behavioural difference towards knowledge sharing and designation. The overall

knowledge sharing behaviour of respondents is found to be correlated with their different designations. The significant

difference is prevailing between different designation levels of respondents and their knowledge sharing behaviour

(F = 8.998, P = .000, (<.005)). Hence hypothesis H4 is accepted. Further post hoc test is conducted to determine that

differences exist among the means.

**Note: columns in the Post hoc test represents as follows.

Educational qualification (I): Denotes the Educational qualification taken for comparison with the remaining

Educational qualification groups.

Educational qualification (J): Denotes the Educational qualification groups being compared with Educational

qualification (I).


Table 5: Post Hoc Test for Knowledge Sharing Behaviour with Respect to Educational Qualification

Dependent

Variable

Educational

Qualification (I)

Educational

Qualification (J)

Mean

Difference (I-J) Std. Error Sig

Knowledge

Sharing

Behaviour

M.Tech

B.Tech -.00407 .04985 1.000

B.tech(M.Tech) .16024 .17444 .890

M.Tech(Ph.D) -.08976 .05147 .408

Ph.D -.17874* .05937 .023

Source: Field information the mean difference is significant at the 0.05 Level

Table 5 shows the post hoc test results for knowledge sharing behaviour for different educational groups. The

results revealed that there was a significant relationship between M.Tech group and individuals with PhD degree

(mean difference= -.17874*, p<0.05 (0.023)). Rest of the educational groups are not significant with any other.

According to hypothesis H5 knowledge sharing behaviour is differs with respect to working experience. Results

proved the hypothesis as respondents those have different working experience exhibited different knowledge sharing

behaviour. Hence there is a significant influence of working experience on knowledge sharing behaviour (F = 2.633,

p = .024, (<.005)), thus supporting hypothesis H5. Further post hoc test is conducted to determine that differences exist

among the means. Post hoc results revealed a significant relationship between the group having experience 16-20years and

0-5years (mean difference=.29157*, p<0.05 (0.043)).

RELATIONSHIP BETWEEN KNOWLEDGE SHARING BEHAVIOUR (KSB) AND DEMOGRAPHIC

VARIABLES

Table 6: Pearson Correlation Analyses for Demographic Variables and KSB

Variable Pearson Correlation

Coefficient (r)

Significance

Level (p)

Gender .081 .141

Age .119 .029

Designation .223 .000

Educational qualification .144 .008

Working experience .168 .002

The results of table 6 depicts there exists a very weak positive relationship between knowledge sharing behaviour

and demographic variables like age group, educational qualification, designation and working experience with Pearson

correlation analysis (for age and KSB r = .119, p = .029(<.005); for working experience r =.168, p = .002(<0.001); for

qualification r = .144; p = .008 (<0.001); for designation r = .223, p =.000 (<0.001)). Gender do not have any relation with

KSB (r = .081, p= .141(>0.001)).

DISCUSSIONS

The results and analysis of the present study provided acceptable support to the proposed conceptual model

(figure 1). In this section we discuss the implications of means and each of the hypothesesThe first hypothesis of this study

postulated a relationship between gender and knowledge sharing behaviour. The hypothesis testing through ANOVA

rejected that assumption. The analysis through means revealed that the knowledge sharing behaviour of men (3.88) is

slightly more than women (3.81). But there is no significant influence of gender on knowledge sharing behaviour. This is

contrary with the findings of Taylor(2004), who found the significant influence of gender on knowledge management

system where men recorded highest score by reflecting intense positive knowledge sharing behaviour through emails, data

mining, using important aspects of KMS and contributing to knowledge management system (KMS) than women. And

also contrary to the study of Boardia et al. (2006), & Lin (2006) who investigated the influence of gender on knowledge


sharing behaviour and revealed that Women exhibit higher perceptions of the benefits of knowledge sharing than men. In

contrary to the previous studies, in the present context the mean KSB of men is just higher than women or can be expressed

as almost equal behaviour. This may be cited to the reason that both men and women may have a perception that they are

in the education field and their prime activity is to share knowledge for the individual as well as institutional benefit

irrespective of their gender.

There is a very weak or almost negligible relationship is exists between age group and knowledge sharing

behaviour. But no significant behavioural differences are observed towards knowledge sharing by different age group

respondents. This is contrary to the investigations of Garg and Rastogi (2006), which proved that older teachers are more

pro-social than their younger colleagues. In the present study the respondents of 25-30 age group are recorded less KSB

score than the respondents of age groups 31-40, 40 -50,and above 50 respectively. This finding is in tune with the findings

of Shi-Jer Lou et al.,(2007) who found that respondents of age group 30-39 express more knowledge sharing behaviour

than 40-49.

This study found that academicians of doctorate degree contributed more to the behaviour than others with post

graduation and graduation degree holders. This finding is in line with the study of Shi-Jer Lou et al., (2007) who also

proved the same. The results can be explained that academicians with doctorate degree might have acquired more

knowledge through more advanced education and research activities than academicians with master’s and Bachelor’s

degree, thus willing to involve more in knowledge sharing activities. Designation of the respondents also influences their

KSB positively. This is similar to the finding of Shi-Jer Lou et al., (2007), where job title differences fetched different

knowledge sharing behaviours. Unlike their conclusions, in the present study Professors exhibited more KSB than

Associate Professors and Assistant Professors. The results may be explained that academicians occupying highest

designation may perceive more responsibility to develop their colleagues with lower designations and may like to help

them to achieve their research and teaching goals.

Working experience played a key role in influencing the knowledge sharing behaviour of academicians. The study

revealed that the Academicians those have 16-20 years of working experience exhibit more KSB than those who have

above 25 years of experience followed by respondents of 21-25 years, 11-15 years, 1-5 years, 6-10 years. There is

significant difference between respondents of 6-10 years and 16-20 years experienced respondents.

CONCLUSIONS

Since knowledge sharing is a critical activity for academicians it has to be enhanced by stimulating individuals to

share their knowledge voluntarily with other individuals and contribute to the organizational knowledge base. The results

of this study suggest that the knowledge sharing behaviour of academicians do vary according to the difference in their

demographic factors irrespective of gender. Hence institutions should focus on motivating the academicians to share

knowledge among themselves, across the departments, across the institution and industry and contributing to the

knowledge base. Motivational factors may be considered according to the different age, designation, educational

background, working experience of the academicians. The content based motivational theories such as Maslow’s theory;

Herzberg’s two factor theory will help the institutions to design motivating system.

LIMITATIONS AND FUTURE RESEARCH IMPLICATIONS

The present study findings are limited to the colleges in Rayalseema region only, cannot be generalized to the

entire state. The prospective direction for future research is to concentrate on the investigation of academicians’


demographics and knowledge sharing behavioural outcomes as well as situational aspects which influence their KSB, i.e.

to know when, which groups are willing to share knowledge.

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Knowledge Sharing Practices among Academicians: Assessing the Role of Demographic Variables

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