Thesis: Drivers for adoption of eco-innovation and enhancement of food companies’ environmental performance

Although the importance of innovation and sustainability for industries is evident, apparently in the food sector those concepts are being considered separately. The Organization for Economic Co-operation and Development (OECD) defines eco-innovation as “the development of products, processes, marketing methods, organizational structure, and new or improved institutional arrangements, which, intentionally or not, contribute to a reduction of environmental burdens in comparison with alternative practices” (OECD, 2009, p. 2). The main goal of this PhD Thesis is to identify how Brazilian food companies integrate innovation and sustainability, verifying what are the conditions (drivers) for adoption of eco-innovation and enhancement of environmental performance due to this action. The method applied included the following phases: In addition to an extensive literature review, that permeates the whole study, a systematic review in the literature was applied to identify main constructs that could be part of the final conceptual model. An exploratory research included in-depth interviews with eco-innovative food companies’ representatives, and validation process for data collection was crucial for data collection instrument development. To analyse the descriptive phase, structural equation modelling was applied. The aim was to verify empirical causal relationships among given drivers for adoption of eco-innovation and the enhancement of performance in Brazilian food companies. The quantitative data from this stage was analysed with SPSS (Univariate statistics) and Amos (Multivariate statistics – SEM). The empirical results from this study shed light on the drivers of eco-innovation based on a final dataset with 525 Brazilian food companies, revealing some relevant new insights. In terms of the influence of drivers to enhance the environmental performance of Brazilian food companies, it was found out that environmental performance is directly affected by environmental strategy, environmental regulations, environmental managerial concern, and very weakly, both in magnitude and in significance, by technology. Environmental managerial concern become a central concept in this study, both as an important direct influential factor for increasing companies` performance due to the adoption of an eco-innovation, and as a mediator of other important factors. Environmental managerial concern is positively influenced by environmental capability, environmental strategy, environmental regulation, and by technology. Practical implications include the importance of understanding what motivated companies to eco-innovate to help policy makers to guide and predict company’s behaviour and develop tools to induce a more environmental management. Such result also highlights the need for more education for sustainability in the business world, as well as for consumers. In addition, the key role of environmental management concern to boost adoption of eco-innovation and increase environmental performance raise awareness on the importance of further include sustainability in business schools’ curriculum. This thesis brought an innovative approach, with robust literature support via systematic review, exploratory research and test of hypotheses with structural equation modelling. This allowed to develop a comprehensive conceptual model, gathering and investigating all relevant factors in the literature, and using those factors with parsimony in the final model for the empirical investigation. The selected drivers were previously tested in the literature but not as a whole and to investigate its influence on environmental performance. The empirical test of the model with all the selected factors was therefore tested with a representative sample. The model fit was adequate, as well as measures used, being the model considered as meaningful and should be tested with different sectors, since theoretical assumptions are not restricted to a given sector. Therefore, with a robust theoretical framework, it was possible to use the proposed confirmatory analysis.

Author: Bossle, Marília Bonzanini

Advisor: Barcellos, Marcia Dutra de

Level: Doctorate Degree

Published Study: