Accept or reject? Predicting ideation outcomes through enterprise social media - Rozaidi, Nik Ahmad; Gibbs, Jennifer L.; Eisenberg, Julia (2017)
Implementing social media in the workplace may make it easier for employees to participate in knowledge sharing activities such as Q&A and ideation.However, vetting the quality of answers and ideas becomes more complex when anyone in the company can contribute. Research on the use of social media for Q&A has shown that certain characteristics and reputation algorithms can help determine the best answers.Less is known about the ideation process and the way it plays out in social media.This paper explores the use of enterprise social media (ESM) for ideation by employees in a large Russian organization distributed across nine time zones.In particular, we explore which characteristics of both ideas and their contributors predict whether ideas get accepted or rejected.Our analysis is based on logistic regression analysis of a sample of 488 ideas contributed in an ESM tool used in the organization as well as a content analysis of the types of ideas generated.Our results suggest that rather than being truly democratic and decentralized, ideation in ESM is driven by those in (or proximate to) positions of organizational power.