Presentation on theme: "The case of the Ghana Cocoa Industry By Albert Gyamfi (PhD Fellow-AAU-CPH) THE MEDIA RICHNESS PERSPECTIVE OF SOCIAL WEB USAGE FOR KNOWLEDGE TRANSFER."— Presentation transcript:
The case of the Ghana Cocoa Industry By Albert Gyamfi (PhD Fellow-AAU-CPH) THE MEDIA RICHNESS PERSPECTIVE OF SOCIAL WEB USAGE FOR KNOWLEDGE TRANSFER
Introduction Motivation Research question Theoretical background Conceptual model Conclusion
Ghana was #1 global cocoa producer by 1911 #1 producer of premium quality beans Ghana achieved a production target of I million metric tons/annum in 2011 The industry is valued at $1.5 billion and employing 1.5 million people including 400,000 famers Cocoa together with other crops contributed 15.6% to GDP as the largest economic activity in 2013 (Minister of Food and Agiculture)
The Ghana Cocoa Board (COCOBOD) is the main regulating body of the cocoa industry in Ghana It has five divisions divided into pre-harvest and post harvest sectors Post-harvest: Quality Control Unit (QCU) Cocoa Marketing Company (CMC) Pre-harvest: Seed Production Unit, Cocoa Research Institute of Ghana (CRIG), Cocoa Swollen Shoot Virus Disease Control Unit (CSSVDCU)
New agricultural technologies; Diagnostic information about plant and animal disease and soil related problems; Weather and climatic conditions, Market information on inputs and sales (prices, seller, buyers, retailers); Market demand and quality of products required for these markets; Access to funds, and government policies
The lack of creation and transfer of knowledge is more critical in agriculture than in other areas of human endeavor (Baah, 2009; ISNAR, 1991). Cocoa farmers need knowledge that is timely and cost effective Are existing mechanisms cost effective?
Existing mechanisms need to be supplemented with interactive technological platforms Most organizations are adopting social media tools for effective knowledge sharing Would The cocoa industry be well-served by introducing social media technologies? Factors that can influence social media usage need to be investigated
To What extent can social media usage influence knowledge transfer in the cocoa industry in Ghaha? What impact can media richness have on social web usage for knowledge transfer? What is the effect of task characteristics and media richness on knowledge transfer success?
The research model is grounded in : Theory of Organizational Knowledge Creation Media Richness theory Agricultural Knowledge and information systems (AKIS) Communication Model
AKIS should reflect some sort infomation flow and influence of technology users Knowledge flows from resource community to user community via a meta- communication The process of knowledge transfer is a communication process involving the transmission of messages from a source to a recipient (Dima & Stancove, 2008) Transferring knowledge from a source to recipient involves stages, processes and categories of factors (Szulanski, 1993; 1996; Dinur, 2009) Factors include the knowledge itself, the source and recipient of knowledge and the context of transfer (Dinur, 2009)
New knowledge begins with the individual and transcends to groups, and embed in the organization This happens through four processes each of which represents a type of transfer Each type of transfer requires specific mechanisms which has to be supported by a form of media Media type can be face-to-face or virtual tacit explicit tacit explicit tacit
Richness of media depends on: Ability to receive feedback number of cues related to face-to-face communication, e.g. tone of voice and body language availability of different language types and level of conveyance of feelings and emotions Selection of media depends largely on: its richness and characteristics of the task to be performed
Independent variables Socialization: tacit-to-tacit Externalization: tacit-to-explicit Internalization: explicit-to-tacit Combination:explicit-to-explicit Dependent variables Knowledge transfer:tacit and explicit Knowledge transfer success: time, cost and satisfaction Moderating variables Media Richness Media Usage ( task characteristics + media richness)
Media richness: Exchangers (Skype) Aggregators (Facebook and YouTube) Collaborators (wikis) Task characteristics Craft (unanalyzable + low variety) Non-routine (unanalyzable + high variety) Routine (analyzable + low variety) Engineering (analyzable + high variety)
The model will assist In gain a better understanding of the impact of media richness on knowledge transfer in the social media space (KT in SMS) To ascertain social media applications that can best support the existing transfer mechanisms for successful knowledge transfer In gaining understanding in the relationships among the characteristics of knowledge transfer, media usage and transfer success.