international conference on knowledge management (ickm) 2010, public presentation

THE INTENTION TO SHARE:

PSYCHOLOGICAL INVESTIGATION OF KNOWLEDGE SHARING BEHAVIOR IN ONLINE COMMUNITIES

BYBIBI M. ALAJMIRutgers University

School of Communication & [email protected]

2The Intention to Share Alajmi, B. Oct , 2010

After he had kicked his cocaine habit, Blair Newman, claimed that somebody put a line of

the substance next to his computer while he was logged on in the WELL online community. It dawned on him, several hours later, that the

white crystals were still there, and he had known about it, but had not mustered the energy necessary to sniff them. (Rheingold, 1993)

Introduction

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Introduction

The Intention to Share Alajmi, B. Jan , 2010

http://upload.wikimedia.org/wikipedia/en/1/1d/Theglobelogo.png

http://en.wikipedia.org/wiki/File:Yahoo!_Geocities.png

http://en.wikipedia.org/wiki/File:Flickr_wordmark.svg

http://en.wikipedia.org/wiki/File:Facebook.svg

http://en.wikipedia.org/wiki/File:Twitter_logo.svg

http://en.wikipedia.org/wiki/File:Delicious.svg

http://en.wikipedia.org/wiki/File:Yahoo!Groups.png

http://en.wikipedia.org/wiki/File:Google_groups_logo.png

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Rational & Significance

* Online community members recognized what they could gain by banding together:

* Social Capital Network.* Knowledge Capital.* Communion.

* Knowledge Capital has been emphasized as the main constituent component of any online community… if lacking, the continuity of these online communities was neither guaranteed nor predicted(Chiu,

Hsu, and Wang, 2006).

* Online communities acknowledge and appreciate the knowledge sharing processes required to build their virtual identity.

The Intention to Share Alajmi, B. Oct , 2010

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* Knowledge is power.

* Knowledge is sticky (Szulanski, 2003).

* It is unnatural to share knowledge (Davenport and Prusak, 1998) .


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321.1 million people have a facebook account by 2009.

70,000,000 – number of total videos on YouTube (March 2008).

77% - percentage of active Internet users read blogs.

27,940,000,000 – number of Tweets to date http://popacular.com/gigatweet/ (1407 tweet/second)

72% say they blog in order to share their expertise.

Statistics exported from http://thefuturebuzz.com/


http://popacular.com/gigatweet/

http://thefuturebuzz.com/

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• Natural tendency, willingness, and eagerness to share in online communities (Chiu, Hsu, and Wang, 2006).

•BUT, what motivate individuals to create the rich content by exchanging their expertise and knowledge in this virtual context.

•This research intends to answer the following question,What are the major factors influencing an individual’s

intention to engage in knowledge sharing activities in online communities?


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Theoretical Foundations

The Theory of Reasoned Action (TRA) (Fishbein and Ajzen, 1975).

* Knowledge of the person’s intention toward that object predicts the performance or non-performance of a specific behavior. * Attitudes and subjective norms are predictors of an individual’s intention to behave.

The Theory of Planned Behavior (TpB) (Ajzen, 1991, 2002). * Self-efficacy * Controllability

Knowledge Management Constructs* Knowledge sharing self-efficacy (KSSE) (Hsu et al., 2007).

Sociology Constructs* Descriptive norms (Rivis and Sheeran, 2003).


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Theoretical Framework


H 5

H 4

H 3

H 2

H 6

H 1

Attitude toward knowledge sharing

Subjective norms concerning knowledge sharing

Knowledge sharing behavior

Knowledge sharingself-efficacy

Controllability

Descriptive norms concerning knowledge sharing

Intention to share knowledge

what relevant others themselves do

Individual’s judgment of his capabilities to share knowledge.

Belief about the extent to which the behavior is up to the actor

An Extended Model Representing Motivational and Volitional Factors Influencing Knowledge Sharing Behavior

what significant others think the person ought to do

Feeling of favorableness or unfavorableness toward stimulus .

Person’s subjective probability that he/she will behave.

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Research Hypotheses

Hypothesis 1: The stronger the individual’s intention to share knowledge, the more likely he/she will be to share his/her knowledge with other individuals.

Hypothesis 2: The more favorable an individual’s attitude toward knowledge sharing practices, the stronger his/her intention to share knowledge.

Hypothesis 3: The stronger the individual’s perceived subjective norms toward knowledge sharing practices, the stronger his/her intention to share knowledge.


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Hypothesis 4: The stronger the individual’s perceived descriptive norms toward knowledge sharing practices, the stronger his/her intention to share knowledge.

Hypothesis 5: The greater the individual’s perceived knowledge sharing self-efficacy, the stronger his/her intention to share knowledge.

Hypothesis 6: The greater the individual’s level of control over his knowledge sharing capabilities, the stronger his/her intention to share knowledge with others.


Research Hypotheses

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Online Community

Learning Hub Professionals Community *

- Knowledge-based community. - launched in 1997. - Voluntary community by educators to educators. - Enhancing the quality of teaching.

- 20.000 members: Education faculty, teachers, librarians, professional development staff, researchers, and other education staff.

* All references to the organization, group, and individuals involved in this research will be represented by pseudonyms to protect the confidentiality of the participants.


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Methodology

SURVEY

Recruiting Mechanisms -An article was published in the LHPs newsletters to introduce the research.-Nine groups (25-100 members) accepted to participate in the research.-214 subjects between the ages of 20 and 80 completed the survey. -158 valid responses (20.8% response rate). -Incentives were provided to the research participants.Survey Instrument-The variables were measured and explicated by adopting items from previous research (3-4 items per variable).

-7-point Likert scale from “strongly disagree” to “strongly agree.” -Data was transferred and analyzed through SPSS quantitative software.

-Multiple Regression Analysis was conducted to test the predictability power of the proposed variables in the extended model.


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Research Results

Multiple Regression Analysis Results

-First StageAttitude IntentionSubjective norms Intention Descriptive norms Intention KSSE IntentionControllability Intention

-Second Stage:Intention Behavior


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Research Results


FIRST STAGE

R² = .56 (56%) * Significance level: p<.05- p<.01

** P >.05


Attitude toward knowledge sharing

Subjective norms concerning knowledge sharing

Knowledge sharing self-efficacy

Controllability

Descriptive norms concerning knowledge sharing Intention to share knowledge

= .21*

= .17*

= .3*

= .2*

= .01**

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Research Results


SECOND STAGE

R² = . 32 (32 %) * Significance level: p<.01


= .58*

Knowledge sharing behaviorIntention to share knowledge

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Research Results


Hypotheses FindingsThe stronger the individual’s intention to share knowledge, the more likely he/she will share his/her knowledge with other individuals.

√

The more favorable an individual’s attitude toward knowledge sharing practices, the stronger his/her intention to share knowledge.

√

The stronger the individual’s perceived subjective norms toward knowledge sharing practices, the stronger his/her intention to share knowledge.

√

The stronger the individual’s perceived descriptive norms toward knowledge sharing practices, the stronger his/her intention to share knowledge.

√

The greater the individual’s perceived knowledge sharing self- efficacy, the stronger his/her intention to share knowledge.

√

The greater the individual’s level of control over his knowledge sharing capabilities, the stronger his/her intention to share knowledge with others.

x

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Research Implications

Theoretical Implications

-To the Knowledge Management Field

-Confirm the Adage that knowledge management is 95% managing people and 5% technology.-Emphasis the social aspect of knowledge sharing reflected in the normative components.

-To the Social Psychology Field-Testing the TRA and TpB to investigate a new type of behavior, i.e. Knowledge Sharing -Testing the extension of TpB framework by including new variables such as descriptive norms and knowledge sharing self-efficacy. -Testing the TRA and TPB in anew context, i.e. virtual communities.


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Practicle Implications

-To the Online Community

-Identifying social and psychological factors influencing the decision-making process will assist the community in developing the best strategies to motive contributions and ensure sustainability.

-Acknowledging the power of the “others” in motivating individuals to share knowledge/expertise in online context.


Research Implications

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Selected Reference

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision processes, 50, 179-211. Ajzen, I. (2002). Perceive behavior control, self-efficacy, locus of control, and the Theory of Planned

Behavior. Journal of Applied Social Psychology, 32(4), 665-683.Chiu, C.-M., Hsu, M.-H., and Wang, E. (2006). Understanding knowledge sharing in virtual communities:

An integrating of social capital and social cognitive theories. Decision Support Systems, 42, 1872-1888.

Davenport, T. and Prusak, L. (1998). Working knowledge: How organizations manage what they know. Boston: Harvard Business School Press.

Fishbein, M., and Ajzen, I. (1975). Belief, attitude, intention and behavior: an introduction to theory and research. Reading, MA: Addison-Wesley.

Hsu, M.-H, Ju, T.L., Yen, C.-H, and Chang, C.M. (2007). Knowledge sharing behavior in virtual communities: The relationship between trust, self-efficacy, and outcome expectations. International Journal of Human-Computer Studies, 65, 153-169.Lee, C. K., and Al-Hawamdeh, S. (2002). Factors impacting knowledge sharing. Journal of Information

and Knowledge Management, 1(1), 49-56. Rheingold, H. (1993). Virtual community: Homesteading on the electronic frontier. MA: Addison-Wesley.Szulanski, G. (2003). The process of knowledge transfer: A diachronic analysis of stickiness. Behavior

and Human Decision Process, 82(1), 9-27.


international conference on knowledge management (ickm) 2010, public presentation

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