A step-by-step method to classify corporate sustainability practices based on the Signaling Theory

The “Signaling Theory” is a theoretical framework that investigates the content reported in sustainability reports, considering that through signaling, companies can influence stakeholders’ perceptions, create a competitive advantage and positively impact their corporate image. Signals can be classi...

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Bibliographic Details
Main Authors: Norbey Amaya, Mónica López-Santamaría, Yonni Angel Cuero Acosta, Merlin Patricia Grueso Hinestroza
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:MethodsX
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2215016121003307
Description
Summary:The “Signaling Theory” is a theoretical framework that investigates the content reported in sustainability reports, considering that through signaling, companies can influence stakeholders’ perceptions, create a competitive advantage and positively impact their corporate image. Signals can be classified into three types: camouflage, intent and necessity. By analyzing their sustainability reports, this study presents a step-by-step approach to classifying sustainability practices reported by companies according to the aforementioned types of signals. We propose a step-by-step approach based on a thematic and qualitative analysis that encourages replication by the research community. Details in the study will validate the proposed method and consider the lessons learned. • A method is proposed that allows the sustainability practices reported by companies to be classified into camouflage, intent and necessity signals through their sustainability reports. • A seven-step process for thematic analysis is described based on a qualitative research approach for achieving the above-mentioned goal. • The classification of sustainability practices into the camouflage typology is a challenging process, as it tends to be biased, hence the identification of this type of signals in comparison with those of intent and necessity requires the adoption of measures that guarantee the reduction of bias on the part of the researcher.
ISSN:2215-0161