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1 – 7 of 7Kwadjo Appiagyei and Augustine Donkor
This study examines the effect of the environmental sensitivity of firms on the relationship between integrated reporting (IR) quality and sustainability performance. Prior…
Abstract
Purpose
This study examines the effect of the environmental sensitivity of firms on the relationship between integrated reporting (IR) quality and sustainability performance. Prior research works focus on the nexus between IR quality and sustainability performance with little attention to factors that moderate this relationship.
Design/methodology/approach
Ordinary least squares (OLS) and other robust estimations are employed to analyse the data of firms on the Johannesburg Stock Exchange (JSE).
Findings
This study finds a positive association between IR quality and sustainability performance. However, the strength of this relationship is found to be weaker among environmentally sensitive firms, thereby raising concerns that such firms may be reporting less sustainability information with the mandatory implementation of IR on the JSE.
Practical implications
The findings highlight the need for regulatory bodies to consider additional sustainability disclosure requirements for firms in environmentally sensitive industries.
Social implications
The findings should make regulatory bodies aware of the possible actions of environmentally sensitive firms in relation to sustainability information within a mandatory setting of IR.
Originality/value
The study extends the existing literature on IR and sustainability performance by considering the effect of firm environmental sensitivity as a moderating factor.
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Drew Woodhouse and Andrew Johnston
Critiques of international business (IB) have long pointed to the weaknesses in the understanding of context. This has ignited debate on the understanding of institutions and how…
Abstract
Purpose
Critiques of international business (IB) have long pointed to the weaknesses in the understanding of context. This has ignited debate on the understanding of institutions and how they “matter” for IB. Yet how institutions matter ultimately depends on how IB applies institutional theory. It is argued that institutional-based research is dominated by a narrow set of approaches, largely overlooking institutional perspectives that account for institutional diversity. This paper aims to forward the argument that IB research should lend greater attention to comparing the topography of institutional configurations by bringing political economy “back in” to the IB domain.
Design/methodology/approach
Using principal components analysis and hierarchical cluster analysis, the authors provide IB with a taxonomy of capitalist institutional diversity which defines the landscape of political economies.
Findings
The authors show institutional diversity is characterised by a range of capitalist clusters and configuration arrangements, identifying four clusters with distinct modes of capitalism as well as specifying intra-cluster differences to propose nine varieties of capitalism. This paper allows IB scholars to lend closer attention to the institutional context within which firms operate. If the configurations of institutions “matter” for IB scholarship, then clearly, a quantitative blueprint to assess institutional diversity remains central to the momentum of such “institutional turn.”
Originality/value
This paper provides a comprehensive survey of institutional theory, serving as a valuable resource for the application of context within international business. Further, our taxonomy allows international business scholars to utilise a robust framework to examine the diverse institutional context within which firms operate, whilst extending to support the analysis of broader socioeconomic outcomes. This taxonomy therefore allows international business scholars to utilise a robust framework to examine the institutional context within which firms operate.
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Ada T. Cenkci, Megan S. Downing, Tuba Bircan and Karen Perham-Lippman
Abby Yaqing Zhang and Joseph H. Zhang
Environmental, social and governance (ESG) factors have become increasingly important in investment decisions, leading to a surge in ESG investing and the rise of sustainable…
Abstract
Purpose
Environmental, social and governance (ESG) factors have become increasingly important in investment decisions, leading to a surge in ESG investing and the rise of sustainable investment assets. Nevertheless, challenges in ESG disclosure, such as quantifying unstructured data, lack of guidelines and comparability, rampantly exist. ESG rating agencies play a crucial role in assessing corporate ESG performance, but concerns over their credibility and reliability persist. To address these issues, researchers are increasingly utilizing machine learning (ML) tools to enhance ESG reporting and evaluation. By leveraging ML, accounting practitioners and researchers gain deeper insights into the relationship between ESG practices and financial performance, offering a more data-driven understanding of ESG impacts on business communities.
Design/methodology/approach
The authors review the current research on ESG disclosure and ESG performance disagreement, followed by the review of current ESG research with ML tools in three areas: connecting ML with ESG disclosures, integrating ML with ESG rating disagreement and employing ML with ESG in other settings. By comparing different research's ML applications in ESG research, the authors conclude the positive and negative sides of those research studies.
Findings
The practice of ESG reporting and assurance is on the rise, but still in its technical infancy. ML methods offer advantages over traditional approaches in accounting, efficiently handling large, unstructured data and capturing complex patterns, contributing to their superiority. ML methods excel in prediction accuracy, making them ideal for tasks like fraud detection and financial forecasting. Their adaptability and feature interaction capabilities make them well-suited for addressing diverse and evolving accounting problems, surpassing traditional methods in accuracy and insight.
Originality/value
The authors broadly review the accounting research with the ML method in ESG-related issues. By emphasizing the advantages of ML compared to traditional methods, the authors offer suggestions for future research in ML applications in ESG-related fields.
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Monica Singhania and Gurmani Chadha
As of 2022, the scope of the engagement and interest of debt capital providers in ESG reporting is mainly untapped. However, a vast amount of literature has produced conflicting…
Abstract
Purpose
As of 2022, the scope of the engagement and interest of debt capital providers in ESG reporting is mainly untapped. However, a vast amount of literature has produced conflicting findings about the importance of debt capital (leverage) as a factor in sustainability reporting (SR). This is the first meta-analysis reconciling the mixed results of 85 single country studies containing 131 effect sizes across 24,482 firms conducted over past three decades (1999–2022) investigating the influence of leverage on SR. The study emphasizes the significance of contextualizing research by identifying the macro-environmental elements modifying debt's impact on SR, through the use of the institutional theory. Eleven country variables were tested on the collected dataset, spread across 36 countries.
Design/methodology/approach
Meta-analysis technique for aggregation of existing extant empirical work. Continuous and categorical variable-based moderator analysis to demystify the influence of country characteristics affecting the leverage–SR relationship.
Findings
Results show positive significant impact of debt capital providers on SR. Country's level of development, GDP, extent of capital constraints in a country, financial sector development within a nation, country governance factors and corruption levels, country's culture, number of sustainability reporting instruments operational in a country and geographical location proved to be significant moderators.
Research limitations/implications
The study details relevant meaningful research gaps, worthy of uptake by researchers to produce targeted research.
Practical implications
Governments must increasingly go beyond their mandated disclosure role and acknowledge the important institutional factors that have contributed to the expansion of ESG reporting through the creation of nation-specific tools, incentive structures and disclosure-encouraging regulations. To secure a steady flow of funding and prevent negative effects on company value and cost of capital in the midst of prolonged global economic upheaval, businesses must address the information requirements of lenders. The limited total effect size emphasizes the necessity for debt providers to step up their ESG activism and exercise their maximum power and potential in stimulating extensive SR firm-level practices.
Originality/value
The present study is the first meta-analysis reconciling the mixed results of 85 single-country studies containing 131 effect sizes across 24,482 firms conducted over the past three decades (1999–2022) investigating the influence of leverage on SR and demystifying the macro-environmental factors affecting the leverage–SR association.
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