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Rural-Urban Contextual Data Triangulation Proposal for International Engineering Project Work
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: 2020 ASABE Annual International Virtual Meeting 2001220.(doi:10.13031/aim.202001220)
Authors: Alexandra Timmons, Ann-Perry Witmer, Dr, Luis F Rodriguez, Dr
Keywords: Contextual engineering, international engineering, rural, urban.
Abstract. Literature in the field of international engineering indicates that project failure is very commonly a direct result of the exclusion of the community during important project and design decisions. This failure appears to be especially prominent for projects attempted in rural communities. The current emerging solution to address this community exclusion and resulting project failure is through a purposeful on the ground study of community conditions beyond solely technical considerations. However, this process is quite cost and time intensive for foreign engineers to engage with. This research acknowledges that including the voice of the community is crucial to project success and studies the hypothesis that this process can be attempted remotely through the use of urban data triangulation, potentially saving both time and project funds. By selecting the three urban cities, where data is plentiful, in closest proximity by travel-distance to the rural community in question and weighting them appropriately, it is hypothesized that a contextual engineering data triangulation analysis can be performed to approximate the conditions of the rural community. This remote effort is contrasted against an on the ground contextual engineering analysis, which measures the community-specific impacts of five critical and non-technical influences, culture, economics, education, mechanical aptitude, and politics. The preliminary results show that while there is potential for this remote analysis to provide a useful early understanding of a community, it will not be able to fully replace on the ground analyses with the current selection of available data.
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