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The primary objective of this research is to conceptualize the integration of enterprise risk management (ERM) as a mechanism to enhance the connection between corporate sustainability (CS) reporting and financial performance. This study suggests that future researchers should validate the proposed conceptualization by conducting a comprehensive content analysis of sustainability reports of Malaysian oil and gas companies. This analysis will allow for the collection of pertinent data regarding CS reporting and ERM implementation. The present study takes a comprehensive approach by integrating legitimacy, stakeholder, and resource-based view (RBV) theories, proposing a robust conceptual design that emphasizes the role of ERM in the connection between CS reporting and firm performance. Drawing on theoretical foundations, this study proposes that CS reporting will have a direct effect on financial performance. Moreover, the integration of ERM serves to strengthen the nexus between CS reporting and financial performance. This study offers valuable insights for stakeholders in the oil and gas sector by providing strategic guidance to enhance financial performance not only through CS reporting but also by implementing ERM. Moreover, the framework proposed in this study is expected to bring tangible and intangible benefits to corporations, including reducing information asymmetry, improving the quality of disclosure, and creating value within the field of CS. The proposed conceptual framework holds great significance as it enhances the applicability of legitimacy, stakeholder, and RBV theories, while also creating value for stakeholders through CS reporting and the adoption of risk management practices to enhance financial performance.

The purpose of this study is to examine how companies integrate cyber risk into their enterprise risk management practices. Data breaches have become commonplace, with thousands occurring each year, and some costing hundreds of millions of dollars. Consequently, cyber risk has become one of the gravest risks facing organizations, and has attracted boardroom-level attention. On the other hand, companies already manage many kinds of difficult and growing risks, and that firms lose less than 1% of annual revenues as a result of cyber incidents. Therefore, how should firms appropriately address cyber risk? Is it indeed a materially different kind of risk area, or is it simply just one more risk that can seamlessly be integrated into existing enterprise risk management (ERM) practices?

The authors performed thematic analysis based on semi-structured interviews, with non-probabilistic, purposive sampling, to answer two main questions. First, how do firms manage enterprise risks, generally? And second, how are they integrating cyber risk into these existing processes?

The authors find that there is considerable variation in the approach and sophistication in ERM practices, such as whether they are driven more like an auditing function, or as a risk champion. The authors also find that despite the novelty of cyber risk, it can be integrated like other enterprise risks, and that cyber risk is most often seen as an operational risk (similar to workplace accidents or fraud), rather than a strategic risk, emerging from, for example, technology innovation and R&D.

The generalization of the results is limited by the sample size and variation of firms interviewed. While the authors attempted to interview enterprise risk managers across a wide variation of firms, there were clear limitations in the scope. That being said, the authors were fortunate to be able to examine ERM and cyber risk practices across small and large, private and publicly traded companies, from a variety of business sectors.

The authors believe these finding are important because they present evidence that while cyber risk may be new, it does not require specialized handling or processes to track it at the enterprise level. While some firms may choose to provide special accommodations or attention because of their data collection or business practices, this approach is neither necessary nor required of all firms in all situations.

This research is one of the only papers that, to the best of the authors’ knowledge, examines how cyber risk is integrated at an enterprise level.

This systematic literature review analyzes the academic literature to understand SC risk and resilience across different organizational sizes and industries. The academic literature has well discussed the causes of supply chain (SC) risk events, the impact of SC disruptions, and associated plans for SC resilience. However, the literature remains fragmented on the role of two fundamental elements in achieving SC resilience: the firm's size and the firm's industry as firms' contingent factors. Therefore, it is important to investigate and highlight SC resilience differences by size and industry type to establish more resilient firms.

Building upon the contingent resource-based view of the firm, the authors posit that organizational factors such as size and industry sector have important roles in developing organizational resilience capabilities. This systematic literature review and analysis is based on the structural and systematic analysis of high-ranked peer-reviewed journal papers from January 2000 to June 2021 collected through three global scientific databases (i.e. ProQuest, ScienceDirect, and Google Scholar) using relevant keywords.

This systematic literature review of 230 high-quality articles shows that SC risk events can be categorized into demand, supply, organizational, operational, environmental, and network/control risk events. This study suggests that the SC resilience plans developed by startups, small and mdium-sized enterprises (SMEs), and large organizations are not necessarily the same as those of large enterprises. While collaboration and networking and risk management are the most crucial resilience capabilities for all firms, applying lean and quality management principles and utilizing information technology are more crucial for SMEs. For large firms, knowledge management and contingency planning are more important.

This study provides a comprehensive review of the literature on SC resilience plans across different organizational sizes and industries, offering new insights into the nature and dynamics of startups', SMEs', and large enterprises' SC resilience in different industries. The study highlights the need for further investigation of SC risk and resilience for startups, SMEs, and different industries on a more detailed level using empirical data. This study’s findings have important implications for researchers and practitioners and guide the development of effective SC resilience strategies for different types of firms.

Social media data from financial websites contain information related to enterprise credit risk. Mining valuable new features in social media data helps to improve prediction performance. This paper proposes a credit risk prediction framework that integrates social media information to improve listed enterprise credit risk prediction in the supply chain.

The prediction framework includes four stages. First, social media information is obtained through web crawler technology. Second, text sentiment in social media information is mined through natural language processing. Third, text sentiment features are constructed. Finally, the new features are integrated with traditional features as input for models for credit risk prediction. This paper takes Chinese pharmaceutical enterprises as an example to test the prediction framework and obtain relevant management enlightenment.

The prediction framework can improve enterprise credit risk prediction performance. The prediction performance of text sentiment features in social media data is better than that of most traditional features. The time-weighted text sentiment feature has the best prediction performance in mining social media information.

The prediction framework is helpful for the credit decision-making of credit departments and the policy regulation of regulatory departments and is conducive to the sustainable development of enterprises.

The prediction framework can effectively mine social media information and obtain an excellent prediction effect of listed enterprise credit risk in the supply chain.

This study aims to explore how earnings management techniques are affected by corporate financial debt risk (FDR), internal control (IC) effectiveness and CEO education.

The study uses a sample from listed firms in China from 2010 to 2017, comprising different industries, including agriculture, forestry, livestock farming and fishing; mining; manufacturing; electric power, gas and water production and supply; construction; transport and storage; information technology; the real estate industry; social services; and communication and cultural. The regression analysis is used to test the hypotheses. The two-stage least squares technique is used to check for endogeneity issues.

The study finds that firms are less likely to manage real earnings when they have more robust IC and FDR. Likewise, companies with weak ICs are more likely to manipulate real earnings. Besides, the study finds an influence of CEO education on the relationship between IC, FDR and real earnings management (REM). These results can be applied to the sectors in the sample covered by the research, and the authors do not overlook the energy industry sector for the importance of its role in the economy.

There are some limitations for the researcher when performing any research, and this study is no exception. Researchers are urged to take these circumstances into consideration when generalizing or comparing the results because the methods used to calculate the measurement variables in each study may differ somewhat from those used in other research. In addition, expanding the current research design to incorporate additional nations may be an area of interest for future research and could aid in evaluating the effects of nation-specific elements (such as inflation, culture, legal systems and political considerations) on the usefulness of IC and decreasing FDR. Second, the current study focuses on the impact of IC and FDR on REM; this paper does not dissect the “black box” of IC and consider how each element affects earnings management. Future research may need to focus specifically on how effective IC would affect earnings management and precisely what IC mechanisms would discourage the management of earnings.

Helping companies listed in China to make decisions and improve investors’ vision of the results of real companies’ businesses, as well as helping management to avoid falling into debt risk and the consequent effects and manipulation of earnings.

By highlighting the significance of IC and debt risk in enhancing information quality in China, the results contribute to the body of work examining the relationship between IC, FDR and REM. In addition, this study uses a CEO’s education to moderate this link.

In the global context, artificial intelligence (AI) technology and environmental, social and governance (ESG) have emerged as central drivers facilitating corporate transformation and the business model revolution. This paper aims to investigate whether and how the application of AI enhances the ESG performance of enterprises.

This study uses panel data from Chinese A-share listed companies spanning the period from 2012 to 2022. Through a multivariate regression analysis, it examines the impact of AI on the ESG performance of enterprises.

The findings suggest that the application of AI in enterprises has a positive impact on ESG performance. Internal control systems within the organization and external information environments act as mediators in the relationship between AI and corporate ESG performance. Furthermore, corporate compliance plays a moderating role in the connection between AI and corporate ESG performance.

This paper underscores the pivotal role played by AI in enhancing corporate ESG performance. It explores the pathways to improving corporate ESG behavior from the perspectives of internal control and information environments. This discussion holds significant implications for advancing the application of AI in enterprises and enhancing their sustainable governance capabilities.

The vulnerability of the tourism industry to an array of risks, encompassing family-related, small- and medium-sized enterprise-specific, strategic, tourism-specific and external factors, highlights the landscape within which small and medium family enterprises (SMFEs) operate. Although SMFEs are an important stakeholder in the dynamic tourism sector, they are not one homogenous group of firms, but have different strategic orientations. This study aims to investigate the interplay between strategic orientation and risk perception to better understand SMFEs risk perception as it is impacting their decision-making processes, resilience and long-term survival. The authors investigate how different strategic orientations contribute to different perspectives on risk among owner-managers.

Based on a qualitative data corpus of 119 face-to-face interviews, the authors apply various coding rounds to better understand the relationship between strategic orientations and the perceptions of risks. Firstly, the authors analysed the owner–manager interviews and identified three groups of different strategic orientations: proactive and sustainability-oriented SMFE, destination-affirmative and resilience-oriented SMFE and passive SMFE. Secondly, the authors coded the interviews for different risks identified. The authors identified that the three groups show differences in the risk perceptions.

The data unveil that the three groups of SMFEs have several differences in how they perceive risks. Proactive and sustainability-oriented SMFEs prioritize business risks, demonstrating a penchant for innovation and sustainability. Destination-affirmative and resilience-oriented SMFEs perceive a broader range of risks, tying their investments to destination development, emphasizing family and health risks and navigating competitive pressures. Passive SMFEs, primarily concerned with external risks, exhibit limited awareness of internal and strategic risks, resist change and often defer decision-making to successors. The findings underscore how different strategic orientations influence risk perceptions and decision-making processes within SMFEs in the tourism industry.

The authors contribute to existing knowledge include offering a comprehensive status quo of perceived risks for different strategic orientations, a notably underexplored area. In addition, the differences with respect to risk perception shown in the paper suggest that simplified models ignoring risk perception may be insufficient for policy recommendations and for understanding the dynamics of the tourism sector. For future research, the authors propose to focus on exploring the possible directions in which strategic orientation and risk perception influence one another, which might be a limitation of this study due to its qualitative nature.

Varying strategic orientations and risk perceptions highlight the diversity within the stakeholder group of SMFE. Recognizing differences allows for more targeted interventions that address the unique concerns and opportunities of each group and can thus improve the firm’s resilience (Memili et al., 2023) and therefore leading to sustainability destinations development. The authors suggest practical support for destination management organizations and regional policymakers, aimed especially at enhancing the risk management of passive SMFEs. Proactive SMFE could be encouraged to perceive more family risks.

Viewing tourism destinations as a complex stakeholder network, unveiling distinct risk landscapes for various strategic orientations of one stakeholder has the potential to benefit the overall destination development. The proactive and sustainability-oriented SMFEs are highly pertinent as they might lead destinations to further development and create competitive advantage through innovative business models. Passive SMFEs might hinder the further development of the destination, e.g. through missing innovation efforts or succession.

Although different studies explore business risks (Forgacs and Dimanche, 2016), risks from climate change (Demiroglu et al., 2019), natural disasters (Zhang et al., 2023) or shocks such as COVID-19 (Teeroovengadum et al., 2021), this study shows that it does not imply that SMFE as active stakeholder perceive such risk. Rather, different strategic orientations are in relation to perceiving risks differently. The authors therefore open up an interesting new field for further studies, as risk perception influences the decision-making of tourism actors, and therefore resilience.

Industry 4.0 is characterised by the exponential pace of technological innovations compelling organisations to transform or be displaced. Industry 4.0 transformation of construction enterprises lacks systematic guidance and notable earlier studies have utilised maturity models to map transformation of enterprises. This paper proposes a conceptual maturity model for construction enterprises for business scenarios leading to Industry 4.0.

The requirements for designing maturity models, including comparison with existing models and scientifically documenting the design process, make Systematic Literature Reviews (SLR) appropriate. Two systematic literature reviews (SLRs) are conducted to shortlist a total of 95 papers, which are subjected to subsequent content analysis.

The first SLR identifies the following process categories as critical levers of industry 4.0 maturity; data management, people and culture, leadership and strategy, collaboration and communication, automation, innovation and change management. The second SLR ascertains that the existing maturity models in construction literature do not adequately correspond to Industry 4.0 business scenarios with limited emphasis on data management, automation, change management and innovation. The findings are assimilated to propose a conceptual Smart Modern Construction Enterprise Maturity Model (SMCeMM).

The paper systematises the transformation of construction enterprises in Industry 4.0 and leads to state-of-the-art development of Industry 4.0 and maturity model research in construction. The proposed conceptual model addressed both the demands of the construction industry as well as what is required to navigate Industry 4.0 better.

This study aims to identify the publication phase, performance and scientific contributions of research papers related to enterprise risk management (ERM) and to visualise the emerging themes in addressing volatility, uncertainty, complexity and ambiguity (VUCA).

The biblioshiny technique based on the bibliometrix R package was used to draw journal papers’ performance and scientific contributions by displaying distinctive features from the bibliometric method used in prior studies. The data was extracted from the Web of Science (WOS) and Scopus databases.

Since the 1990s, ERM publication has gained momentum, and it is generally categorised into four main themes. Studies by Miller (1992) and Bromiley et al. (2015) scored the highest in global and local citations, respectively. However, the Economic Outlook ranked first in quality of publications while the Journal of Risk and Insurance topped in quantity of publications. Collaborative research mainly exists between two authors, and the dynamic number of collaborative networks is evident in the USA.

This study is limited by the filtered keywords used to generate the search on journal papers’ in WOS and Scopus. It is imperative to have more comprehensive and rigorous analytics on ERM research to enable a direction for future research. Finally, ERM implementation better equips firms to mitigate risk in a VUCA environment.

This study attempts to fill a vacuum of ERM literature, specifically in business economics, in addressing VUCA. Moreover, it covers a comprehensive predetermined period of from its inception in 1983 until 2022.

This study aims to explore the adoption of enterprise risk management (ERM) in developing and developed countries. Is there a similarity or difference between the two contrasting institutional markets and the reasons behind them?

The adoption of ERM is analyzed on the basis of the institutional framework. The author draws empirical evidence by comparing the cases of a British and an Indian insurance company using evidence from multiple sources. This paper focuses on extra-organizational pressures exerted by economic, social and political situations across two countries that influenced the adoption decision of ERM.

The findings of this research revealed that early adopters of ERM in different institutional markets face coercive and normative pressure but not mimetic pressure. The adoption of ERM in India and the UK is dissimilar. Companies in the British insurance market encounter higher institutional forces than those in the Indian market because of higher coercive and normative pressure. The aspirations to adopt ERM in the Indian and UK markets included improved strategic decision-making to maintain stakeholder expectations and higher standards of corporate governance. In the UK, ERM was adopted to reduce surprises and fluctuations under flexible regulations but with stricter adoption and to improve credit ratings.

Previous literature has discussed ERM adoption in similar markets or within one market with similar institutional pressure. In contrast, this research is a comparative study that explains the analysis of institutional theory in two different institutional environments in the adoption of ERM.