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    Abstract Web 2.0 is a set of Internet-based applications that harness network effects by facilitating collaborative and participative computing. In this research we study the relationship between the use of Web 2.0 in KM and its effect on the tacit knowledge sharing and perceived learning. We also study the effects of KM context variables on these relationships. Our findings shows that use of Web 2.0 for KM can positively affect tacit knowledge sharing and perceived learning.58989

     

    Keywords: Web 2.0, knowledge management, case study, inpidual, tacit knowledge, perceived learning.

     

    I. INTRODUCTION

     

    Knowledge management (KM) is the process through which organizations generate value from their intellectual and knowledge-based assets (Levinson, 2006). Currently, organizations utilize Internet- based technologies as KM tools to manage organizational knowledge. A new generation of Internet-based collaborative tools, commonly known as Web 2.0, has increased in popularity, availability and power in the last few years (Kane & Fichman, 2009).

     

    Web 2.0 is a set of Internet-based applications that harness network effects by facilitating collaborative and participative computing (O’Reilly, 2006). Web 2.0 has the potential to deliver rich peer-to-peer interactions among users, enable collaborative value creation across business partners and create dynamic new services and business models (Ganesh & Padmanabhuni, 2007). Web 2.0 technologies include wiki, blog, RSS, aggregation, mash ups, audio blogging and podcasting, tagging and social bookmarking, multimedia sharing, and social networking. Rich user experience is a critical aspect of Web 2.0 and plays an important role in encouraging collaborative information exchange. Web 2.0 attracts a large number of participants by enabling rich interactions between them. These interactions have significant impact on customer-driven innovation, maintaining market orientation, addressing customer concerns and development of the product-service mix (Eccleston & Griseri, 2008). Web 2.0 technologies, through rich peer to peer user interactions to support collaborative value creation, combine the best elements of traditional KM such as suitability for business environment and avoid many of disadvantages like limited opportunities for simultaneous collaboration (Wagner & Majchrzak, 2006).

     

    Traditional KM tools, such as expert systems, essentially capture the explicit knowledge of a single expert or source of expertise in order to automatically provide conclusions or classifications within a narrow problem domain. This is in stark contrast to the Web 2.0 KM paradigm (Lee & Lan, 2007) which enables knowledge communities to share knowledge of a more practical or experiential nature to enable inpiduals and groups to arrive at their own conclusions (Richards, 2009). To capture tacit knowledge an effective

     

    Assistant Professor, Dept. of Business and Economics, Elizabeth City State University, United States. Email: aknath@ecsu.edu.

     

    12 Nath/Journal of Accounting – Business & Management vol. 22 no. 2 (2015)

     

    way is to enable knowledge creation through conversation (Von Krogh, 2000). Web 2.0 technology like wiki facilitates such required conversational KM through social interactions (Wagner, 2006). For example, through wiki multiple people with different expertise and different roles can interact “socially” and work towards a common goal (Mindel & Verma,

     

    2006). Hence, Web 2.0 has great potential to solve one of the great challenges of KM-capturing tacit knowledge and converting it into explicit knowledge (Wagner, 2006).

     

    Conceptually, Web 2.0, with its ability to combine traditional KM tools’ features with social computing where knowledge is evolved through social interactions (Parameswaran & Whinston, 2007), has been identified as an effective KM paradigm (Mindel & Verma, 2006; Fitch, 2007).With such capability Web 2.0 technology has the potential to address many of the challenges for KM of the organizations (Wagner, 2006; Minocha & Thomas, 2007).

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