SKiM - Value of KM, Knowledge Package

cg.contactalwangj@vt.eduen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerVirginia Polytechnic Institute and State University - Virginia Techen_US
cg.contributor.funderInternational Fund for Agricultural Development - IFADen_US
cg.contributor.projectStrengthening Knowledge Management for Greater Development Effectiveness in the Near East, North Africa, Central Asia and Europeen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.coverage.end-date2022-06-30en_US
cg.coverage.start-date2018-06-08en_US
cg.date.embargo-end-dateTimelessen_US
cg.subject.agrovocknowledge managementen_US
cg.subject.agrovocknowledgeen_US
dc.creatorAlwang, Jeffen_US
dc.date.accessioned2023-08-22T16:36:38Z
dc.date.available2023-08-22T16:36:38Z
dc.description.abstractDecision makers may be reluctant to invest in knowledge management (KM) without understanding the economic value of such investments. KM creates economic value through two direct pathways: (i) reducing the time and other costs of obtaining knowledge needed for decision making; and (ii) reducing the uncertainty associated with decision options (or policy alternatives for policy decision making). The first pathway is relatively obvious, but calculating the value of saved time in large institutions can be difficult. The second pathway creates the main source of value of KM; knowledge and access to it reduces the probability that an improper (wrong) decision is taken. There is a large literature on the value of information in decision making and the main source of economic value comes through reduction in uncertainty about the returns to a specific decision. 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.en_US
dc.formatRARen_US
dc.identifierhttps://mel.cgiar.org/dspace/limiteden_US
dc.identifier.citationSKiM - Value of KM, Knowledge Package.en_US
dc.identifier.statusTimeless limited accessen_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/68573
dc.languageenen_US
dc.subjecteconomyen_US
dc.subjectknowledge valueen_US
dc.titleSKiM - Value of KM, Knowledge Packageen_US
dc.typeOther (Knowledge Package)en_US
dcterms.available2022-08-31en_US
mel.funder.grant#International Fund for Agricultural Development - IFAD :2000001661en_US
mel.project.openhttps://knowledgemanagementportal.org/en_US

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