How insights from the field of information behavior can enrich understanding of knowledge mobilization

Abstract

PurposeThe authors review the literature on information behavior, an autonomous body of work developed mainly in library studies and compare it with work on knowledge mobilization. The aim is to explore how information behavior can contribute to understanding knowledge mobilization in healthcare management.Design/methodology/approachThe authors conducted a narrative review using an exploratory, nonkeyword “double-sided systematic snowball” method. This is especially useful in the situation when the two traditions targeted are broad and relies on distinct vocabulary.FindingsThe authors find that the two bodies of work have followed similar trajectories and arrived at similar conclusions, with a linear view supplemented first by a social approach and then by a sensitivity to practice. Lessons from the field of information behavior can be used to avoid duplication of effort, repeating the same errors and reinventing the wheel among knowledge translation scholars. This includes, for example, focusing on sources of information or ignoring the mundane activities in which managers and policymakers are involved.Originality/valueThe study is the first known attempt to build bridges between the field of information behavior and the study of knowledge mobilization. The study, moreover, foregrounds the need to address knowledge mobilization in context-sensitive and social rather than technical terms, focusing on the mundane work performed by a variety of human and nonhuman agents.

Practicing Impact and Impacting Practice? Creating Impact Through Practice-Based Scholarship

“…According to MacIntosh et al (2017, p. 3), in everyday usage, “impact is defined as the action of one object coming forcibly into contact with another.” In short, “impact” implies the idea of direct linear causality: a stimulus generates a response. This common-sense linear view originates in the instrumental view of research and knowledge (Beyer, 1997; see Nicolini et al, 2023). Because the relationship is linear, impact can be measured in terms of the breadth of adoption over time.…”