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MOTIVES FOR SOCIAL COLLABORATION IN KNOWLEDGE SHARING PORTALS Farzad Sabetzadeh Eric Tsui Department of Industrial and Systems Engineering The Hong Kong.

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Presentation on theme: "MOTIVES FOR SOCIAL COLLABORATION IN KNOWLEDGE SHARING PORTALS Farzad Sabetzadeh Eric Tsui Department of Industrial and Systems Engineering The Hong Kong."— Presentation transcript:

1 MOTIVES FOR SOCIAL COLLABORATION IN KNOWLEDGE SHARING PORTALS Farzad Sabetzadeh Eric Tsui Department of Industrial and Systems Engineering The Hong Kong Polytechnic University

2 Its the people who are riding on the technology, NOT the technology riding on the people People Need MOTIVATION Technology Needs INFRASTRUCTURE

3 What Motives People to Collaborate Online? Tangibles Intangibles Social Values Social Reciprocity Benevolence

4 Business Innovation Social Innovation Technology Innovation Moving from mechanistic models to complex holistic system analysis Challenges Moving beyond teams to knowledge networks and communities of practice Technologies for codification, organization and integration Network Pattern Value Knowledge Technology Adopted from Allee and Taug (2006)s 3 level innovation model How do People bring Value to knowledge societies by their participation? + =

5 Personal Benefits Name Branding Money Making What is in it for me? (WIIIF Rule)

6 Altruism Impure Pure

7 Reciprocity and Conditional Cooperation

8 Social Norms (Culture)

9 Research Framework Personal Benefits Tangible Rewards Intangible Rewards Reciprocity Society size Perceived participation Benevolence Intrinsic Rewards Perceived Efficacy Knowledge Sharing Behavior Social Norm Social Identity Learned Lessons

10 Study Group 130 Respondents from almost 40 countries Within first quarter of year 2008 The majority of the studied population has higher education degrees. The studied population is almost equally divided between the genders. The majority of the population is in the age range of 20 to 30 years. Almost half the population has basic job experience with a minimum 2 years. The majority of the population has internet usage history of more than 4 years. The majority of the population has a high internet connection frequency per day. The majority of the population owns a computer device, and almost half of the population has their own laptops showing a high connection mobility. The majority of the population are registered with at least one of the social networking sites, and most of the studied population check their s on first connecting to the internet. Chatting and VOIP is the preferred communication tool for the greater portion of the population, followed by in the second place. The majority of the studied population use forwarding as a preferred tool to share online content with others.

11 Hypothesis Testing Conditions Strongly AgreeStrongly Disagree Normal Test (NT) : µ Positively Neutral Test (PNT) : μ 2.5

12 Results HypothesisTested FactorsNTPNT H1. Personal Benefit influences knowledge sharing behavior positively Tangible Rewards RNR Intangible Rewards RNR H2. Voluntary (Benevolent) behavior creates positive impact on knowledge sharing behavior. Intrinsic Rewards NR Perceived Efficacy NR H3. Favorable social reciprocal expectancy influences knowledge Sharing behavior positively Society Size RNR Perceived Participation NR H4.Favorable social norms expedite knowledge sharing behavior positively Social Identity RNR Learned Lessons RNR More than 60% of the motives are Rejected within Normal Test!!!!

13 Findings 1.Altruism is a key factor as it inherits the social nature of the shared benefits under ubiquitous participation. 2.Reciprocity in the form of perceived participation from others is needed for knowledge sharing reinforcement. 3.Social norms (culture) finds its meaning as a sharing catalyst when people are directed from neutral position into agreement. proper policy and strategies 4.Last but not the least, people are potentially optimistic about what they can benefit from the online world, yet this needs proper policy and strategies that can move them from neutral position into an acceptance level.

14 Conclusion 1.Identifying the motives alone does not guarantee their usefulness for online communities. 2.There are a lot of motives that encourage people to share but not all of them work for communities all the time. 3.Many motives might be potential (ulterior) that can only work when proper context is provided through appropriate policy and strategies

15 Future Work Previously researchers have tried to identify many of the social motives (WHATs) Were trying to identify the ways these motives work and benefit the online communities (HOWs) There is a huge uncovered space under so-called Social Complexity to identify the reasons behind these motives (WHYs)

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