Knowledge Transfer in the Social Sciences and Humanities (SSH) – Definition, Motivators, Obstacles, and Visions

Daniel Wutti,Markus Hayden

doi:10.23963/cnp.2017.2.1.7

Abstract

While knowledge transfer in economic and technical sciences is a matter of frequent research, knowledge transfer in social sciences and humanities (SSH) has not been examined sufficiently in the last few decades. In order to fill the research gap, this paper presents results from a study conducted at an Austrian university. Eighteen scientists were interviewed with regards to a definition, common examples, motivators and obstacles as well as visions of SSH knowledge transfer. Interview transcripts have been analyzed qualitatively. Results were compared with quantitative data derived from the research documentation system of the university. A comprehensive definition of SSH knowledge transfer is presented. Motivators turned out to be closely linked to perceived personal and civic duties. Obstacles were described as being attributable to a focus on ‘science to science’ achievements within the scientific community.

Highlights

Apart from teaching and researching, universities are required to complete other tasks as well
The topic of sciences and humanities (SSH) knowledge transfer seemed quite new to most subjects, in most interviews subjects quickly found themselves in medias res
Another result was that technical knowledge transfer, or knowledge transfer in the field of STEM sciences, is easier to define and to measure

Summary

Introduction

Apart from teaching and researching, universities are required to complete other tasks as well. This so called ‘third mission’ includes the transfer of knowledge to non-academic communities (Trencher et al 2014). Many different scientific papers exist on the transfer of knowledge from universities into the economy (for an overview, see for example Geuna and Muscio 2009). These pieces of research mainly focus on the commercialization of academic knowledge and teaching as well as on links between university and industry. Common examples include for example ‘knowledge transfer’, ‘knowledge exchange’, ‘knowledge mobilization’ or ‘knowledge translation and transfer’ (Phipps, Jensen, and Myers 2012)

Objectives

Methods

Results

Discussion

Conclusion