Search results

The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies.

This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible.

The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method.

This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments.

The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development.

To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.

Severe disruptions to maritime supply chains, including port closures, congestion and shortages in shipping capacity, have occurred during the COVID-19 pandemic. This paper’s purpose is to explore flexibility-based countermeasures that enable actors in maritime supply chains to mitigate the effects of disruptions with different characteristics.

Semi-structured interviews were conducted with shipping lines, shippers, forwarders and ports. Data on the COVID-19 pandemic's effects and countermeasures were collected and compared with data regarding the 2016–2017 Gothenburg port conflict.

Spatial, capacity, service and temporal flexibility emerged as the primary countermeasures, whilst important characteristics of disruptions were geographical spread, duration, uncertainty, criticality, the element of surprise and intensity. Spatial flexibility was exercised in both disruptions by switching to alternative ports. During the COVID-19 pandemic, ensuring capacity flexibility included first removing and then adding vessels. Shipping lines exercising service flexibility prioritised certain cargo, which made the spot market uncertain and reduced flexibility for forwarders, importers and exporters that changed carriers or traffic modes. Experience with disruptions meant less surprise and better preparation for spatial flexibility.

Understanding how actors in maritime supply chains exercise flexibility-based countermeasures amid disruptions with different characteristics can support preparedness for coming disruptions.

Comparing flexibility-based measures in a pandemic versus port conflict provides insights into the important characteristics of disruptions and the relevance of mitigation strategies. The resilience of maritime supply chains, although underexamined compared with manufacturing supply chains, is essential for maintaining global supply chain flows.

This paper aims to examine the association between audit quality threatening behaviour (AQTB) and three team equality dimensions: deindividuation, social identity and gender equality. Discrimination among auditors has been experienced in accounting firms across the world, which can lead to behaviour that risks the quality of work. The negative influence of this behaviour can have consequences for clients, audit firms, regulators and the wider society due to the threat on audit quality.

A questionnaire was conducted at a Big 4 audit firm in Sweden. Members of audit teams that worked together on one specific engagement were asked to give their perceptions of their experience of equality and behaviours within the team. Hypotheses were tested using ordered logistic regression and partial least squares structural equation model.

Audit teams that experience deindividuation conduct more AQTBs and audit teams with higher social identity conduct less AQTBs. However, the audit team’s social identity can moderate the audit teams’ experience with deindividuation and reduce AQTB.

With a unique data set of practising audit teams, this study is the first to investigate how audit team equality is related to AQTB. Contributions are made to practitioners about audit team dynamics since the AQTB occurs as part of the audit decision-making process that influences audit quality. Inequality also has recruitment and reputation consequences. Thus, contributions are made to the audit market that is interested in audit quality. The study also contributes empirical evidence from an audit team context about behavioural outcomes and the social identity and deindividuation model theory (Klein et al., 2007; Reicher et al., 1995).