Combinatorial analysis of eco-innovation drivers in slaughterhouses (INMR - Innovation & Management Review, 2023)
Purpose – Literature on eco-innovation brings insights that help to understand which factors triggerinnovation focused on sustainability in companies. However, when analyzing the studies that comprise suchdrivers, it appears that most of them were focused only on describing them in isolation. Therefore, this studyaims to understand which are the combinations of drivers that favor the adoption of eco-innovation inslaughterhouses located in the Brazilian state of Rio Grande do Sul.Design/methodology/approach – This study has used the crisp-set qualitative comparative analysis(csQCA) as the data analysis technique, in addition to the previous application of Most Similar DifferentOutcome/Most Different Same Outcome (MSDO/MDSO).Findings – This study identified eight internal and external drivers that explain the differences inperformance of eco-innovative and non-innovative slaughterhouses. These drivers generate 13 combinationsof factors capable of favoring the adoption of five types of eco-innovation.Research limitations/implications – A limitation identified was the difficulty to obtain informationheld by companies on environmental issues. In addition, in each company the authors only approached onerespondent.Practical implications – The use of combinations is identified by companies and governmental and nongovernmental organizations to promote eco-innovation in slaughterhouses.Originality/value – This study may be considered original for its contribution to the improvement of ecoinnovation literature by describing how the drivers identified combine to favor the adoption of certain types ofeco-innovation. In addition, the authors also made an original use of csQCA, linked with MSDO/MDSO, in thefield of eco-innovation.