In-situ innovation diffusion rate forecasting

Albert J. Parvin, Mario G. Beruvides

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The rate at which an innovation diffuses is an essential factor in determining, impacting, and dictating the speed at which decisions are made within an organization, affecting an organization’s success. It is easy for an organization to determine a technological innovation’s diffusion rate post-situ (e.g., in hindsight). This, post-situ based, mode of decision making often leads to reactive rather than proactive actions. Although, post- situ examinations are, and can be, useful; it leaves a blind spot to how decision-makers manage resources (labor, equipment, materials, time, and capital). A framework for gaining in-situ knowledge on a technological innovation’s diffusion rate would assist and benefit an organization’s decision-makers in proactively setting strategy, policy, and resource management rather than reactively. The primary objective of this research endeavor is to outline the components required to develop a framework towards determining how accurately a technological innovation’s diffusion rate can be predicted with partial diffusion data. As a prime component of this effort, a review of partial innovation diffusion models is presented.

Original languageEnglish
Title of host publicationASEM 41st International Annual Conference Proceedings "Leading Organizations through Uncertain Times"
EditorsH. Keathley, J. Enos, M. Parrish
PublisherAmerican Society for Engineering Management
ISBN (Electronic)9780997519594
StatePublished - 2020
Event41st International Annual Conference of the American Society for Engineering Management: Leading Organizations through Uncertain Times - Virtual, Online
Duration: Oct 28 2020Oct 30 2020

Publication series

NameASEM 41st International Annual Conference Proceedings "Leading Organizations through Uncertain Times"

Conference

Conference41st International Annual Conference of the American Society for Engineering Management: Leading Organizations through Uncertain Times
CityVirtual, Online
Period10/28/2010/30/20

Keywords

  • Diffusion rate forecasting
  • Technological innovation diffusion rate

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