Methods

This research approach is based on the principle that knowledge of a social system can only be gained by introducing change into it. This requires the researcher to consciously influence the ‘reality’ of the situation being studied, meaning that their role differs from that of neutral observer defined in traditional research methods. Intervention Research is carried out jointly by researchers in management and representatives from the organisation. Its aim is to help design and implement appropriate management models and tools in the field, as part of a transformation project.

By analysing one or more cases in depth, the issue being examined can be viewed in greater detail, taking into account the background, contexts, and circumstances of the case; this enables the issue to be addressed within a precise, contextual, and specific framework. Case studies are an effective research strategy for addressing complex matters, something that is essential for Corporate Social Responsibility research: they can help shed light on the many players involved in a phenomenon, as well as their respective levels of action and rationales, which can only be accessed and understood through detailed, in-depth analysis of individual cases. There are four types of case study, ranging from single case studies with a single unit of analysis to multiple case studies rooted in different contexts. One of the specificities of IRSI’s research-active faculty is that they design ‘in situ’ case studies, jointly developed with partner organisations, which are involved in defining the issues and are present from the initial stages right through to the presentation of students’ work.

IRSI and INNOV Case Lab (Excelia’s case centre) work together on numerous levels: IRSI members publish case studies and, for the past 5 years, some have been assisting the case centre in the organisation of the RIODD - EXCELIA - CCMP award for the best pedagogical case in Sustainable Development or Corporate Social Responsibility (1st Edition took place in La Rochelle on 26th September 2019).

More about Innov case lab

Experimental Economics is the application of experimental methods to study economic questions. It consists of reconstructing a situation in a controlled laboratory environment (lab experiment) and/or in the field (field experiment) in accordance with economic theory or in a hypothetical context in order to analyse the decision-making practices of individuals. Experimental Economics makes it possible to go beyond the framework of ‘homo economicus’ (perfectly rational decisions and behaviour) by comparing the data obtained using theoretical predictions, assessing the economic impact of the decisions taken, and updating the theory if necessary. Even though it might appear somewhat controversial, Experimental Economics has proven potential in research in Social Responsibility (energy transition, local and regional dynamics, societal innovations, new models of consumption).

Content Analysis: this is a set of techniques designed to understand how people construct the meaning they give to their practices, in particular through consideration of social, cultural, political, and historical contexts, as well as symbols, rules, and the unspoken word. Content Analysis is carried out using data collected from a variety of sources: audio, image, video or text which is obtained from interviews or observations (whether involving participants or not), from field observations, or from institutional or organisational documents (procedures, reports, any kind of document). Content Analysis involves precise techniques such as data organisation, breakdown, coding, links and interpretation.

When it comes to studying the issues associated with management and the theory of organisations, Econometrics, i.e. the application of statistical methods in economics, can have limitations as it fails to appreciate the complexity of human communication and exchanges. Furthermore, qualitative approaches may be impossible or very complicated for data which, with the growing trend towards computerisation of activities, is becoming increasingly vast. Computational Linguistics offers an alternative, with the statistical study of natural language. It can be used to identify trends or the meaning of many documents and is a highly relevant complementary tool, for use alongside other methods.