Limitless learning: Assessing how global firms leverage local knowledge through social media


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Proceedings IFKAD;2014


Institute of Knowledge Asset Management (IKAM) University of Basilicata

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Purpose: This empirical paper assesses the ability to leverage learning within a globally dispersed project environment facilitated by the web 2.0 technology of wiki . Extant research on the knowledge transfer within multinational firms emphasise exchange between HQ and subsidiaries . In contrast , recent developments in organi zational learning theory suggest that learning occur at multiple levels; o rganizational -, group - and individual level. In this paper we explore this tension by e mpirically exploring the research question: How is social media utilized in the global organization in order to leverage local learning between dispersed individual experts ? Design/methodology/approach : The study is ba sed on an exploratory, in- depth single case study of the implementation of an internal wiki in an international professional service firm . Originality/value: The paper extends ear lier research and shows how an international knowledge based organization can utilize web 2.0 technologies to leverage knowledge and experiences from multiple geographically dispersed projects , and how the effects of wiki can be conceived at an organization -, practice- and content level. Practical implications : The findings identify four determinants of the use of the wiki to leve rage local lear ning within a globally dispersed project environment. First, the wiki must directly relate to the daily work carried out in the organizations projects by offering interactive and updated information concerning current project challenges . Second, the system must enable transparency in the daily project work so that on going activities can be searched. Third, the intention with the search is of lesser degree to identify encyclopaedic information than it is to offering visualization of indi vidual competence and expertise, and fourth there needs to be a sort of quality a ssurance of the data posted at the wiki




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