The aims of this paper are (i) to identify which documents are the most influential when analyzing socially responsible funds, and (ii) to identify the conceptual structure of the field of research through co-word analysis. To achieve the proposed objectives, the VOS Viewer and two databases, Web of Science (WOS) and Scopus, were used for the period 1988–2018, and a total of 209 research papers were analyzed. This analysis provides an insight into the nature and trends of research on socially responsible investment (SRI) funds.

The current concern with sustainability issues pervades all scientific fields. Sustainable investment is not an exception judging by the significant increase in the literature. This work provides an extensive up‐to‐date overview of studies on sustainable investment, revealing current trends, identifying gaps and future research topics. A total of 1091 documents are reviewed and bibliometric analysis is used with two approaches: data analysis and conceptual structure of the field. Additionally, a classification into 12 categories by topic is proposed. The results show that more than 40% of the publications belong to analysis of classical investment tools with a gradual evolution towards the concept of “green” instruments. Socially Responsible Investment (SRI) strategies have changed over time from “screening” to the current “best‐in‐class”, “Environmental, Social and Governance (ESG) integration” and “impact investing.” The results of the study are valuable for academics and practitioners, as they show the current state of knowledge, evolution paths and emerging topics.

Climate change has become a risk that companies, governments and stakeholders must consider. Climate risk affects everything from people's health to the performance of companies. The European Union has approved various legislations and action plans to counteract the effects of climate change in a pioneering strategy. Companies can play a critical role in mitigating climate change and creating a more sustainable future by integrating environmental considerations into their decision-making processes. However, this integration may impact their performance. This paper aims to analyse the effect of climate change on the stock returns of European companies. The study sample consists of 265 companies listed in the Stoxx 600 index between 2015 and 2021 and the methodology used is the econometric method for panel data. The results show that carbon emissions have a negative effect on the performance of companies. Oppositely, a good rating in the environmental pillar has a positive impact on returns.

Purpose: The purpose of this paper is to investigate the influence of organizational factors on individual decision-making under conditions of uncertainty and time pressure. A method to assess the impact of individual and organizational factors on individual decisions is proposed and experimented in the context of triage decision-making process.Design/methodology/approach: The adopted methodology is based on the bias-variance decomposition formula. The method, usually applied to assess the predictive accuracy of heuristics, has been adjusted to discriminate between the impact of organizational and individual factors affecting heuristic processes. To test the methodology, 25 clinical scenarios have been designed and submitted, through simulations, to the triage nurses of two Spanish hospitals.Findings: Nurses’ decisions are affected by organizational factors in certain task conditions, such as situations characterized by complete and coherent information. When relevant information is lacking and available information is not coherent, decision-makers base their assessments on their personal experience and gut feeling.Research limitations/implications: Discriminating between the influence of organizational factors and individual ones is the starting point for a more in-depth understanding of how organization can guide the decision process. Using simulations of clinical scenarios in field research does not allow for capturing the influence of some contextual factors, such as the nurses’ stress levels, on individual decisions. This issue will be addressed in further research.Practical implications: Bias and variance are useful measurements for detecting process improvement actions. A bias prevalence requires a re-design of organizational settings, whereas training would be preferred when variance prevails.Originality/value: The main contribution of this work concerns the novel interpretation of bias and variance concepts to assess organizational factors’ influence on heuristic decision-making processes, taking into account the level of complexity of decision-related tasks.