Experimental methods in innovation research

Abstract

This paper discusses the possible applications of different types of experiment methods in innovation research. The paper argues that the experiment as a research method has been a largely missed opportunity in innovation research, in particular for creating applicable knowledge for businesses and organisations in the shape of new innovation tools and methods. The paper applies an analytically based limitation of the experiment method which includes an array of both quantitative and qualitative approaches. The use of experiments for such purposes is illustrated through a comparative study of four experiments concerning open innovation in service businesses and organisations. The case studies show how different experiment methods provide new opportunities for innovation research and how they can create new and applicable knowledge about open innovation. Thus the paper argues for applying experiments as an addition to other research methods in innovation research.

Introduction

This paper argues that the experiment as a research method has been given too small a role in innovation research and that the method may present an important avenue for attaining knowledge complementary to that which is provided by the traditionally applied methods in innovation research, i.e. survey methods and (to a certain degree) case studies. Surveys and other quantitative approaches have proved adequate to measure and understand innovation processes following fixed patterns and case studies have succeeded in providing prescriptive models of how to design and control relatively simple consecutive stages of innovation processes. However, recent theories of, for example, open innovation (Chesbrough, 2003) and innovation systems (Carlsson et al., 2002) indicate that innovation processes consist of complex social interactions which these earlier models cannot embrace. Open innovation can be defined as an interactive process where ideas and inputs to innovation come from many sources: users, suppliers, competitors, spin-offs from large firms, knowledge intensive service firms or other services (Chesbrough, 2003). Therefore new and practically applicable knowledge about complex open and interactive innovation processes is needed. The paper argues that the experiment is a promising approach to gain such practically applicable knowledge.

The paper approaches the experiment not as one method in the form of a positivist laboratory experiment, but rather as a particular analytical approach which includes an array of methods and data collection techniques. The benefits of experiments in innovation research are discussed against the background of case studies of four different types of experiments concerning innovation in service organisations. These experiments formed part of a larger innovation research project. This so-called ICE (Innovation-Customers-Employees) project involves researchers from Roskilde and Aalborg Universities in Denmark. In this research project a number of experiments using new tools and procedures, hypothesised to improve service companies’ innovation processes, are being carried out. The aim of this is to test and develop such innovation tools and procedures that service companies will be able to apply in the future (ICE, 2008). The companies in question are varied—they provide different kinds of services; they are large and small, and they work with local and international markets. Thus the paper discusses and exemplifies the application of the experiment method at a general service company level.

The paper is structured as follows: first, the nature of innovation and innovation research is briefly discussed. This is followed by an outline and discussion of the experiment method as it has been applied in social science which leads to an alternative analytically based delimitation of the method. This is followed by a discussion of how experiments may be applied to study innovation processes and by the presentation of the experiment cases. The paper finalises with a discussion of the findings and their implications for innovation research.