Purpose This study aims to provide a conceptual model based on future research methods on the impact of blockchain on audit outputs, to examine the effect of blockchain on audit outputs (audit quality and audit expectation gap) and, finally, to analyze the dimensions and identify components of each aspect of the effectiveness of blockchain technology in the audit profession. Design/methodology/approach This research evaluates and systematically analyzes the results using a qualitative approach and future research tools, particularly the Structural Equation Modeling method. In this research, the opinions of 20 experts regarding the dimensions of blockchain, which have affected the expectation gap and audit quality, have been queried. Findings The findings of this study articulate that blockchain impacts two critical dimensions of audit outputs, including audit quality and expectation gap. Based on the research results, it has been determined that blockchain has a positive and significant effect on audit quality. Conversely, it negatively and significantly impacts the audit expectation gap. This means that using blockchain in Iran’s audit system can lead to an increase in audit quality and a reduction in audit expectation gaps. Originality/value As research has yet to be done so far to provide a model regarding the impact of blockchain on audit outputs in Iran, this study can be considered one of the first in this regard. Also, while presenting conceptual models of the impact of blockchain on audit outputs, this research shows the various issues of the gap between expectations and blockchain, which has not been entirely evident in Iran, then, based on them, analyzes the impact of blockchain. This study deals with audit outputs (audit quality and audit expectation gap).

Purpose This paper aims to systematize and develop theoretical and methodological approaches to understanding mechanisms that ensure national stability amid contemporary challenges and analyze them through organizational-legal, information-technological and socioeconomic dimensions. This study also aims to identify how democratic institutions adapt and maintain functionality while confronting military aggression, economic disruption and fundamental threats to territorial integrity, using Ukraine’s experience as a critical case study for testing theories of institutional resilience under extreme pressure conditions. Design/methodology/approach This study uses a single-case study design focusing on Ukraine as a revelatory case, utilizing systematic analysis of institutional structures, document analysis of regulatory frameworks, system-structural analysis of technological infrastructure and functional analysis of information systems. The methodology integrates J. Sachs’ sustainable development framework while adapting it to national stability contexts through a comprehensive examination of phenomena typically inaccessible to social science inquiry under extreme institutional stress conditions. Findings The research reveals that effective national stability requires integration of three interconnected mechanisms. The organizational-legal mechanism demands coherent institutional frameworks with adaptive regulatory systems and multilevel governance coordination. Information-technological mechanisms require advanced early warning systems, robust cybersecurity measures and artificial intelligence-enhanced predictive capabilities. Socioeconomic stability depends on economic diversification, strong social support systems, civil society engagement and strategic resource allocation. The findings demonstrate that these mechanisms function as interdependent systems where weaknesses in one dimension can undermine overall effectiveness. Originality/value This study offers a novel integrated framework transcending traditional siloed approaches to national stability analysis. By examining interrelationships between organizational, technological and socioeconomic dimensions through Ukraine’s unique crisis experience, it provides empirical evidence for stress-testing theoretical frameworks previously developed under stable conditions. The research contributes original insights into how democratic institutions maintain functionality under existential threats, offering practical guidance for enhancing national resilience capacities and informing policy development for countries facing similar multifaceted security challenges.

Purpose This study is focused on exploring the potency of decision-making in addressing environmental complexity in the business environment. This study aims to develop a sustainability model to support business operational activities in the Nigerian private sector. Design/methodology/approach It relies on literature to develop a critical understanding of the trend of development of the subject of decision-making and strive for sustainability among practitioners in the Nigerian private sector. Over 100 pieces of literature were sourced from various search engines like Scopus, Elsevier, Web reports and authors’ personal and institutional libraries for consideration in this study. Findings Findings highlight critical factors such as the managers’ and decision-makers’ awareness of the business environment, organizational commitment to implementation and continuous improvement and the support of the legal and other institutional stakeholders support, for effective decision-making amid environmental complexity, affecting business practices in the context of the Nigerian private sector. Originality/value This study affirms the overlap between the decision-makers’ assumption and the reality in the process of decision-making that underscores their resilience to operational success for the drive for sustainability through continuous decision-making. This study recommends a comparative view of the topic between the public and private sectors, especially in a developing economic background such as Nigeria.

Purpose This paper aims to explore how responsible artificial intelligence (AI) technology can enhance various aspects of academic achievement, benefiting institutions, teachers, students and society in creating productive and better educational systems. Design/methodology/approach Data were collected through interviews using convenience sampling involving students, university managers and lecturers. An inductive approach was applied among academic stakeholders in China. Findings The results show that students and lecturers use and emphasize AI technology in academics. Considering the responses, this study found that human-machine integration significantly improves the learning experience, including independent learning, better suggestions, ideas for solutions, module checking, curriculum setup and others. This study identifies the challenges associated with academic integrity and the unethical use of AI to enhance the learning experience and achieve better academic results. Practical implications The findings of this study help better understand the parameters that affect college students’ and educators’ confidence in and acceptance of AI systems. This paper has provided a theoretical foundation for developing AI systems that help students succeed academically and in various other learning contexts. Originality/value This paper has proposed a framework of responsible AI usage for academic integrity that can be used as the basis for understanding best practices. The study has identified the challenges and proposed a solution for the benefit of AI utilization in academia. AI technology is continuously developing, and its utilization will evolve in the future compared to how people are currently using it. In this study, the authors conclude that AI will certainly be widely used and could not be avoided. Educational stakeholders must adhere to clear standard guidelines and fairly assess AI and plagiarism-related work using expert human judgment, free from personal bias. As AI continues to advance, instructors and students will need to develop skills in identifying, evaluating, and investigating various aspects of AI in academic contexts.

Purpose The epistemological and institutional legitimacy of futures studies/foresight has been a long-standing topic of debate. This paper explores how the field can generate reliable knowledge about plural and uncertain futures, not through prediction or certainty, but through reliable processes of knowledge production and a commitment to the institutional norms, mechanisms and structures of science. Drawing on developments in social epistemology – particularly social reliabilism – this paper aims to provide a robust theoretical foundation for futures studies and related foresight practices, helping to strengthen their scientific credibility. Design/methodology/approach The study adopts a conceptual approach, engaging with theories of truth and knowledge from epistemology and science and technology studies. It critically analyzes how social process reliabilism can serve as a framework for evaluating the reliability of futures methodologies. It also considers the institutional norms required for legitimate scientific knowledge production in the futures field. Findings The analysis shows that futures studies/foresight can generate reliable knowledge when its methods are grounded in consistent procedural and structural standards, even in the absence of predictive accuracy. The integration of social reliabilism supports a shift from forecasting to exploring possible, probable and preferable futures in ways that remain epistemically reliable. The paper also identifies key institutional shortcomings and proposes pathways for aligning the field with broader scientific standards. Research limitations/implications As a conceptual paper, this work does not present empirical findings but lays the groundwork for future research testing the epistemic robustness of futures methodologies. It also highlights the need to carefully distinguish between exploring preferred futures and advocating for them, emphasizing that the process must be methodologically reliable and institutionally accountable to maintain scientific legitimacy. Practical implications This paper proposes how to enhance the reliability and scientific character of knowledge production in futures studies at three levels: individual, methodological and structural. At the individual level, the field needs tools to assess and improve the reliability of participants involved in futures studies processes. At the methodological level, existing methods should incorporate reliability indicators and be evaluated comparatively to identify ways to improve their epistemic robustness. At the structural level, futures studies must revisit and reorganize its scientific infrastructure to better support reliable and institutionally grounded processes of knowledge production focused on the futures. Social implications By enhancing the scientific foundations of futures studies, the field can more effectively support decision-making in critical areas such as climate policy, technological governance and long-term innovation. A commitment to reliable knowledge production and institutional standards may also increase public trust and societal impact. Originality/value This paper contributes to the theoretical foundations of futures studies by applying the lens of social reliabilism to the challenge of generating reliable knowledge about the futures. It presents a novel argument for aligning participatory foresight methods with the institutional and epistemic standards of scientific inquiry, helping to position futures studies as a rigorous and reflexive academic field.

Purpose This study aims to assess whether BRICS+ currencies are sufficiently interconnected to reduce their sensitivity to external shocks, thereby enabling prospects for future de-dollarization. It explores how currency shocks within the BRICS+ bloc influence one another during periods of crisis, identifying which currencies consistently act as sources or absorbers of economic stress. Through this analysis, the study evaluates the inherent stability and shock-resilience of individual BRICS+ currencies. Design/methodology/approach This study examines the interconnectedness of daily returns and volatility among BRICS+ currencies, exploring their responses during the Global Financial Crisis (GFC) and COVID-19 crisis through a time-varying parameter vector autoregression (TVP-VAR) approach by Antonakakis et al. (2020). Findings Understanding these spillover effects is critical due to the significant global economic influence and diverse structures of BRICS+ economies. Notably, the Brazilian Real (BRL) and South African Rand (ZAR) frequently emerge as net transmitters, particularly during the GFC and COVID-19 crises, signaling their role as dominant economic influencers. Conversely, currencies such as the Chinese Yuan (CNY) and UAE Dirham (AED) predominantly act as net receivers, suggesting a relative vulnerability to external shocks. This study addresses the broader implications for enhancing economic resilience, informing policy and mitigating financial contagion among economies with varied structures and significant global influence. The findings indicate that volatility primarily drives spillovers during the GFC, while returns play a more dominant role during the COVID-19 crisis. The ZAR emerges as a consistent transmitter of shocks. At the same time, the AED largely remains a shock receiver despite the UAE’s role as a global business hub. Originality/value BRICS+ can transform global currency dynamics; hence, these pattern sheds light on key economic relationships, such as those between oil-trading partners like India, Russia and Iran, and highlight how currency interactions may shape strategic economic decisions. These insights are invaluable for policymakers, regulators and investors aiming to navigate risks effectively during financial uncertainty. Regulators’ understanding of the direction and intensity of risks in BRICS+ countries enables the use of policy tools to promote regional and international policy coordination and reduce the likelihood of severe risks in the future.

Purpose The purpose of this paper is to analyze the impact of various external risk factors on companies operating in the technology sector. By understanding these impacts, companies can better prepare and adapt their strategies to mitigate potential negative impacts and take advantage of emerging opportunities. Design/methodology/approach In the research, the evaluation of non-business risk factors was made with the F-DEMATEL method. While carrying out these procedures, 10 expert opinions were taken. Experts work in companies operating in the technology sector. All of them have university education or above. A total of 4 participants are female and 6 participants are male. The oldest participant is 57 years old and the youngest is 34 years old. When looking at the time spent working in the sector, the most senior expert said that he has been in the sector for 33 years. The participant with the least seniority has been working in the sector as a manager for 4 years. Findings The analysis reveals many notable findings regarding the impact of external risk factors on technology companies. In particular, the fact that changes in demand conditions emerge as the second most effective factor underlines the importance of market dynamics in shaping company performance. Additionally, the country’s political situation and changing competitive conditions have been identified as important determinants of risk exposure, highlighting the interconnection between macro-level factors and company-level outcomes. Additionally, natural risks and sudden changes in input prices are highlighted as persistent threats, necessitating proactive risk management measures to mitigate possible disruptions. Research limitations/implications Despite its contributions, this study has some limitations that should be considered. First, the findings are based on expert opinions in the technology sector and may not fully reflect the diversity of risk perceptions across different industries or regions. Future research may therefore benefit from including a larger sample of companies or using quantitative methodologies to validate the findings. Practical implications Companies that are aware of external risk factors can proactively develop risk management strategies to minimize risk exposure and protect their operations. For example, strategies such as diversifying foreign exchange risk, closely monitoring market demand trends and investing in disaster preparedness measures can help mitigate the negative consequences of external risks. Additionally, understanding the relative importance of risk factors should be taken into account by companies in effectively prioritizing their resource allocation and decision-making efforts. Originality/value In particular, the research adds original insights to existing knowledge by empirically examining the relative importance of external risk factors within the technology sector. Synthesizing the perspectives of industry experts, the research provides a nuanced understanding of the multifaceted risks facing technology companies and offers practical implications for strategic decision-making. Hierarchical ranking of risk factors adds value by guiding companies to prioritize risk mitigation efforts and allocate resources effectively, thereby increasing corporate resilience and long-term sustainability.

Purpose The purpose of this study is to identify key topics in the scientific literature on sustainable logistics, reveal important interdisciplinary relationships and identify leading researchers in the sector. The relationship between these emerging structures and also the correct understanding of the structures that will evolve in the future is of great importance for the strategic decision-making processes of companies. Design/methodology/approach In the study prepared for this purpose, the Web of Science (WoS) data have been used. It addresses the use of advanced methods such as social network analysis (SNA) and techmining in sustainable transportation and logistics. While SNA focuses on identifying interdisciplinary collaborations and key actors in the scientific world by examining the relationships and interactions between scientific publications, technology mining is used to understand innovative trends and technological developments in this field by extracting technological terms and concepts in scientific texts. SNA highlights the connections between these topics, whereas technology mining is used to uncover new technological trends and innovative solutions. Findings In this study, the researchers focused on a wide range of issues in the fields of logistics and transportation. The findings on logistics, sustainability, supply chain management, machine learning, COVID-19 impacts, the role of China and India, artificial intelligence, innovation, the Internet of Things (IoT), blockchain, uncertainty and case studies reveal a multi-faceted structure. Also, it can be seen that significant emphasis is placed on the complexity of logistics processes. While the association of high aggregate constraints appears to concentrate a significant cumulative importance on certain aspects of logistics, it can be said that these concepts point to potentially critical operational elements. Research limitations/implications The authors did use only WoS records to reach their aim. This study can be extended with other major databases such as Scopus. Practical implications SNA mode and structural hole analysis enable clear visualization of cluster separations and uncover gaps in networks where connections are sparse. By identifying structural holes, researchers can bridge disconnected clusters, fostering collaboration and innovation through the integration of diverse perspectives. Low aggregate constraint values highlight niche topics, supporting deeper exploration and specialized research. Structural hole analysis further identifies key nodes that act as brokers, enhancing connectivity and resource flow. Together, these methods optimize networks, uncover untapped opportunities and contribute to a detailed understanding of research landscapes, driving targeted innovations and impactful advancements in specialized fields. Social implications The study’s findings highlight significant social implications by emphasizing sustainability, collaboration and technological innovation in transportation and logistics. Insights into global collaborations and contributions of key players like China and India underscore the importance of international partnerships in addressing complex challenges. With the integration of machine learning, IoT and blockchain enhances efficiency, transparency and resilience in logistics systems, benefiting societies by improving supply chain reliability. In addition, the focus on sustainability and support strategies for crisis adaptation and long-term resilience, fostering equitable development. Originality/value The authors combined SNA, bibliometrics and machine learning to see collaborations and technological innovations in transportation and logistics. The authors can identify the global collaborations and contributions of key players to underscore the importance of international partnerships in addressing complex challenges.

Purpose Current trends have positioned the specialty coffee chain (SCC) as an axis of interest within the coffee industry, being a prioritized chain in the department of Quindío, Colombia. Considering the planning and execution needs of government programs and policies and the difficulties for decision-making of public and private organizations in the sector, prospective studies are emerging as fundamental tools for anticipating the future. The purpose of this study is to identify priority technologies and future scenarios for the specialty coffee chain in Quindío, Colombia, based on the participation of key stakeholders and sector experts. Design/methodology/approach Two prospective methods were implemented, the scenario method and the two-round Delphi method, to prioritize the key variables, technologies, actors, innovations, objectives and scenarios for the SCC up to 2035. Findings Based on the analysis of 81 variables, 7 key variables were identified and defined by experts through the MICMAC analysis: “Cooperatives, Associations for the process,” “Category Origin,” “Category – Sustainable,” “Production chains,” “Associated crop,” “R&D&I” and “Potential quality”. Based on these, two future objectives and five hypotheses were defined, which served as input to construct the scenarios according to their probability using the matrix of alliances and conflicts: tactics, objectives and recommendations method. The Delphi method addressed 130 topics, classified into 9 thematic categories, and these were rated in the first round and reclassified in the second round according to the criteria of the industry experts who participated in the study. Fifty-eight topics were a priority, 72 were under discussion and 0 were not a priority. Originality/value The novelty of the study consists of the alignment of methods, techniques and tools for scenarios and expert consultation, as well as the implementation of an artificial intelligence code and natural language processing in Python, which allowed validation of several of the results of the methods used.