SKiM - Estimating the Value of Knowledge Management in the Context of Agricultural Research Priority Setting

Abstract

Measurement of value is complicated because KM impacts can be diffuse and easily confounded. While impacts of knowledge transmission to end users such as farmers can be measured using experimental techniques such as randomized delivery of the message (Larochelle et al. 2017), effects of non-randomized knowledge transmission to decisionmakers within an institution are difficult to measure because of the many confounders. These include differences in unobserved individual characteristics that may affect both the decision to use the system and the decision to make a policy change. As a result, studies of KM in complex organizations have relied on corporate results measurement where a package of factors including organizational responsibilities, management styles, etc. also have influence.