An introduction to grey influence analysis (GINA): Applications to causal modelling in marketing and supply chain research

Abstract

The study proposes a novel influence analysis technique called as the Grey Influence Analysis (GINA), which can be used to analyse the influence relations among a set of factors, when there are large number of responses, particularly with any survey based or expert response based studies. The proposed methodology can be particularly useful in marketing and supply chain related studies, where there is often need for causal or influence relations among factors need to be tacked. Cumulative aggregation of responses using the GINA methodology can avoid loss of data, while aggregating responses. A novel practical problem, considering a marketing research environment to analyze the influence relations among drivers of Greenwashing for firms, is also solved using the proposed GINA methodology. The results from a survey based study concludes that firm characteristics is observed as the most influential driver of Greenwashing for firms, considering an overall or total influence score, followed by uncertain regulatory environment and optimistic bias at the second position. This is again followed by ethical climate occupying the third position, among the list of most influential drivers. The proposed method offers researchers, a robust means to perceive the prominent influence relations in a set of factors, where causal relations are prevalent. Based on the values of grey importance coefficients, as obtained from the GINA analysis, it can be inferred about the level of influence that a factor plays in a system and managers and practitioners can find means to control (increase/decrease) it.