As academics actively involved in teaching and researching accounting for the natural environment and nonhuman animals in our home institutions, we often experience mixed feelings on the meaningfulness and usefulness of our educational and scholarly activities. We take this Special Issue as an opportunity to reflect on the feelings of cognitive dissonance we experience when trying to respond to the urgency posed by multiple ecological crises. We complement our reflections through real-life examples from our professional experience that illustrate misalignments between our ecologically driven values and our actions. We hope that our exploration of the coping strategies adopted to navigate such inconsistencies will spark further discussion in the academic world.

The aim of the paper is to investigate the main differences between the accounting systems in Romania and Poland, since the countries of Central and Eastern Europe (CEE) have undergone many political, structural, social and economic changes in the last 50 years. The research methodology is based on a critical analysis of specialized works that have developed a professional framework, on the analysis of Polish and Romanian accounting standards, respectively on the analysis of legal acts necessary to complete the general accounting. On the basis of deductive reasoning, the paper reveals key determinants and differences of accounting frameworks in Romania and Poland. The paper demonstrates that it is crucial to consider economic and cultural differences in comparative international accounting research. Our choice was influenced by the lack of research on our country, although other CEE countries benefit from a significant presence. Notably, we have discovered a broad research on Poland's state of economy which has been compared to Czehia, Slovakia, Hungary and so on. Therefore, it would be a beneficial intake in our field to discover the differences in comparison to Romania.

This study proposes an AI-based model to predict corporate management performance by combining financial data with strategic information extracted from CEO messages in sustainability reports. Using a dataset of 1,271 listed companies on Korea's KOSPI and KOSDAQ markets (2016-2023), we applied eight machine learning and deep learning classifiers: KNN, SVM, GBM, CatBoost, GAN, RNN, LSTM, and Transformer. Financial variables were selected based on prior accounting research, while strategic variables were derived via text mining of CEO messages and categorized using the Sustainable Balanced Scorecard (SBSC) framework. Results show that models incorporating both financial and strategy-based variables outperformed those using financial data alone. Notably, the Transformer model achieved the highest predictive accuracy, followed by LSTM and RNN. These findings provide actionable insights for investors and corporate stakeholders while advancing interdisciplinary research between accounting and AI. Under 5-fold cross-validation, the best-performing hybrid model (Transformer with SBSC features) achieved Accuracy = 0.8467, AUC = 0.8481, and F1 = 0.8572, and adding SBSC strategy indicators improved mean performance across models (ΔAccuracy=+0.0121; ΔAUC=+0.0092; ΔF1=+0.0119).

Purpose This study aims to examine accounting scholars’ engagement with the United Nations’ Sustainable Development Goals (SDGs), based on Carnegie et al.’s (2021) multidimensional definition of accounting. Design/methodology/approach Applying a framework adapted from Carnegie et al. (2023), a qualitative content analysis approach is adopted to examine 24 SDG-focused articles published across eight high-profile accounting journals from 2016 to 2024. Findings Accounting scholars’ engagement with the SGDs remains low and peripheral, rather than mainstream. Analysis reveals three critical gaps in research on the SDGs: it disproportionately attends to the technical dimension (disclosure) while largely neglecting the social (social and policy implications) and moral (stakeholder and planetary interests) dimensions; it concentrates on limited, specific SDGs and on developed countries; and it approaches SDGs as routine rather than potentially transformative. Practical implications This study identifies specific pathways for advancing SDG accounting research: embracing interdisciplinary approaches; extending beyond organisational boundaries; focusing on developing countries and under-represented SDGs; addressing social and moral considerations and implications; promoting SDG accounting education; collaborating with other stakeholders; and increasing SDG publications by accounting journals. Social implications By highlighting both social and moral dimensions, this study encourages scholarship that advances accounting’s social functions, policies and engagement with stakeholder and planetary interests. Originality/value This study reveals systematic imbalances in how accounting scholarship engages with the SDGs. Addressing this critical issue requires a fundamental reorientation for accounting scholarship to meaningfully contribute to sustainable development.

Purpose This study aims to set out to challenge the prevailing assumption in the Technology–Organization–Environment (TOE) framework that process automation and analytics invariably enable further digital progress. Drawing on the notion of technological path-dependency, the study investigates whether – and under which conditions – automation, analytics and digital readiness reinforce or undermine one another across accounting functions. Design/methodology/approach A cross-sectional survey of 819 German accounting professionals (2020) covering financial accounting (FA), management accounting (MA) and tax/audit was analyzed with Partial Least Square Structural Equation Modeling (PLS-SEM). The study develops and validates a formative multi-item DIGITAL READINESS scale and executes multi-group analyses to test boundary conditions for the ANALYTICS resp. AUTOMATION–READINESS link across functions, firm sizes and industries. Additional robustness checks are used. Findings Evidence confirms a positive impact of several technology and organizational factors on the implementation of automation and analytics but also reveals an automation-rigidity paradox: higher levels of process automation are negatively related to an accounting function’s capability to absorb subsequent digital innovations. The new DIGITAL READINESS scale shows satisfactory reliability and validity and can be interpreted as adaptive capacity for further digital transformation. Research limitations/implications The single-country, cross-sectional design limits causal inference and generalizability. Future studies should track organizations longitudinally, replicate in other institutional contexts and examine curvilinear or time-lagged effects of automation. Practical implications Chief financial officer (CFOs) should balance automation gains with modular governance and workforce upskilling to avoid rigidity traps. The validated scale offers a diagnostic tool for benchmarking digital readiness before investing in next-wave technologies such as generative artificial intelligence. Originality/value The study confirms several findings of prior research concerning the impact of TOE factors on digitalization, uncovers and theorizes a negative automation effect that contradicts core TOE expectations, refines the TOE framework by integrating a flexibility/path-dependency lens and mapping its boundary conditions and contributes a newly validated digital readiness measure for reuse in accounting and IS research.

ABSTRACT We synthesize evidence from six papers presented at the 2025 Journal of Accounting Research Conference on how generative artificial intelligence (GenAI) is reshaping capital‐market information flows. Our discussion is organized around an economic framework with three layers: information production by firms and accounting professionals, information dissemination through intermediaries, and information processing by investors. Across these layers, the conference papers show that GenAI can lower preparation costs, improve intermediary productivity, and reduce investors’ processing costs. At the same time, they point to a common constraint: whether GenAI improves the information environment depends critically on information verification costs. We also highlight gaps in current evidence and outline future research opportunities within and across the three layers.

Purpose The circular economy has become an established pathway toward sustainability. The purpose of this study is to understand how management accounting and control support the triple bottom line (TBL) approach in the context of the circular economy. Design/methodology/approach The authors draw on the theory of loose coupling to understand how the multiple perspectives of the TBL are balanced. They present a multiple-case study of four forerunner circular-economy startup companies in Finland, two platform-economy companies that provide services to support the circular economy and two manufacturing companies with circular material flows. Findings They found that the loose coupling of the TBL element enables flexibility and balancing of sustainability goals. In addition, they found that despite limited resources and standardized frameworks, management accounting and control practices enabled startups to balance economic, environmental and social objectives by facilitating transparency, prioritization and responsiveness across the TBL dimensions. Practical implications The findings present real-life practices to develop sustainability management control in small businesses. Originality/value They contribute to the circular economy and management accounting and control research by increasing understanding about the ways in which the TBL framework is loosely coupled in small businesses.

Low profitability and high failure rates remain chronic challenges within the restaurant industry. Despite the strategic importance of cost management, scholars have noted the limited attention this topic has received in restaurant-related research. This study aims to map the conceptual structure, methodological approaches, and key research gaps in cost and management accounting studies within the restaurant context. A comprehensive systematic literature review was conducted following the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol. Searches were performed in the Scopus and Web of Science databases; however, given the limited number of retained articles, the dataset was expanded using a forward snowballing technique. The study finally comprises 107 documents. The findings reveal that research activity remained minimal until 2007, after which publications increased, though inconsistently. Methodologically, most studies adopt descriptive or exploratory approaches, with case studies being the predominant method to address practical issues, which constrains the generalisability of findings. A co-word analysis identified five thematic clusters: cost by nature, variable costing, activity-based costing (ABC), efficiency, and absorption costing. The results indicate that advances in contemporary management accounting have not yet been fully incorporated into the restaurant management literature. Furthermore, key research trends in management accounting—particularly behavioural and organisational approaches—have received limited attention. Empirical evidence remains scarce concerning the management accounting practices (MAPs) adopted by restaurant managers, the factors influencing their implementation, and the impacts of MAPs and management systems on efficiency and performance. Accordingly, this study advances knowledge by clarifying how cost and management accounting research in the restaurant industry has evolved, identifying dominant and underexplored research streams, and highlighting key theoretical and methodological gaps that constrain the development of the field.

Shaping new horizons in management accounting with artificial intelligence: an exploration of information networks

Radiography research has traditionally prioritised quantitative approaches, which are less suited to examining complex practice-based phenomena such as professional judgement, ethical tension, and relational aspects of care and education. Reflective analysis has been used to explore these issues but remains poorly defined as a research method in radiography, leading to inconsistency in application and reporting. This paper aims to establish reflective analysis as a recognised qualitative research method by defining its epistemic foundations, analytic procedures, and reporting requirements, and by distinguishing it from reflective writing for learning. A methodological synthesis drawing on qualitative research methodology literature, reflective practice theory, and radiography scholarship was undertaken. Within the included radiography literature (n=24), reflexive thematic analysis was the most commonly used analytic approach (n=15), followed by narrative inquiry (n=4), reflective analysis (n=2), analytic autoethnography (n=2), and interpretive description (n=1). Examination of these approaches clarified key differences in data sources, analytic focus, and methodological intent, highlighting the distinct contribution of reflective analysis. Reflective analysis is defined as a qualitative method that uses systematically documented first-person professional experience as data and applies explicit analytic procedures to generate practice-facing insights. From this synthesis, a seven-stage analytic workflow, Reflective Analysis for Radiography (RAD-RA), and discipline-specific reporting guidance aligned with established qualitative standards were developed. Reflective analysis provides a structured qualitative approach for examining complex aspects of radiography practice, education, and professional decision-making not readily captured through quantitative or multi-participant qualitative designs. The RAD-RA framework supports rigorous, transparent, and ethically accountable reflective research, enabling radiographers to examine professional judgement and practice-based challenges while supporting consistent peer review and qualitative scholarship within the discipline. As artificial intelligence increasingly shapes clinical workflows, decision support, and professional roles in radiography, reflective analysis provides a structured qualitative method for examining how practitioners interpret, negotiate, and respond to AI-supported practice. The RAD-RA framework offers a defensible approach for analysing these emerging interactions, supporting qualitative inquiry into human-AI relationships, professional accountability, and practice implications within radiography.

This study provides a bibliometric review based on 1,891 Scopus-indexed records to integrate the trends and conceptual framework discussed in environmental accounting and corporate disclosure research. The results show intensive research growth since 2015, mainly led by Chinese, American, and Australian authors. Three categories were generated through thematic analysis: environmental strategies, corporate social responsibility, and accountability modes. Environmental accounting has developed from reporting to a strategic management tool, which is closely related to corporate governance, reputation, and sustainability performance. Additional findings show that the strength of international collaboration networks has increased over time, especially with Chinese and European institutions, reflecting a trend towards increasingly globalized research collaboratives. The keyword co-occurrence map indicates a shift in research priorities, from early attention to environmental cost accounting to the latest emphasis on climate-related disclosure, ESG integration, and low-carbon transition strategies. It also shows an increasing academic focus on regulatory drivers, including IFRS S2, the EU CSRD, and national emission policies. The cross-cluster comparison of differences implies a growing similarity in environmental responsibility accounting, corporate strategy, and stakeholder expectations, which underlines a move towards more consistent and decision-useful sustainability reporting systems.

Public value is an established concept used in different fields like in public management, public administration and public policy. Public value accounting research in particular has mostly focused on its instrumental value on how to measure, control, report and manage public value. There have been little attempts to theoretically advance the concept of public value accounting and how adopting a public value perspective will mould the way accounting is conceptualized and practiced. The aim of this article is to propose a conceptualisation of how public sector accounting and accountability can be framed from a public value perspective and in so doing providing a basis for developing future research as well as for practice. The paper follows an abductive approach where: first, public value accounting is conceptualised in its core-elements drawing from the accounting and public management and public administration literature; and second, a document analysis of the Italian Ministry of University and Research is used to apply the proposed public value accounting framework. The paper contributes to the theoretical development of public value accounting in public services, to foster future research and practice alike in this field.

[Purpose] This study aims to facilitate the integration of emerging technologies intoKorean accounting research by presenting code－based cases that researchers can immediatelyapply or extend across the data collection－processing－analysis workflow. It also highlightsthe importance of IT knowledge acquisition and addresses the risks and controls inherent inAI utilization. [Methodology] Building on a review of prior Korean and international research, the studyorganizes emerging technologies along the procedural axis of collection, processing, andanalysis, and develops case studies on (1) API utilization, (2) AI－based unstructured dataprocessing, (3) AI－assisted variable generation, and (4) AI as a research assistant. R wasadopted as the primary language considering its learning curve and functionality. [Findings] For data collection, the study discloses codes for handling OpenDART andBigKinds API. For text processing, it demonstrates efficiency gains via the OpenAI API andpresents GUI－based sentiment analysis and variable computation outputs using ChatGPT. Italso showcases click automation, data downloading, and web crawling using the Cometbrowser. All developed codes are publicly available on GitHub. [Implications] Integrating emerging technologies into research requires technical knowledgethat remains insufficiently disseminated in Korea. This study bridges that gap by openlyproviding immediately applicable, code－based cases. The code－centric design underscores thatproductivity gains from emerging technologies are largely realized through code implementation,emphasizing the need for systematic dissemination of IT and coding knowledge for long－termdiffusion.

This literature review examines how financial reporting quality affects U.S. banks’ credit allocation to small businesses, focusing on loan approval and interest rate setting in the post-2020 lending environment. It addresses the following research question: how does financial reporting quality affect bank credit approval and interest rates for small U.S. businesses? Synthesizing accounting and finance research, this review argues that higher financial reporting quality reduces lender uncertainty and monitoring costs, increasing approval likelihood and lowering loan pricing, effects that likely amplified under tightening in the U.S. since 2020 as banks reverted to stricter screening following pandemic-era interventions.

Behavioral accounting research plays an critical role in explaining how psychological, social and cognitive factors shape accounting decision making. This study aims to analyze the direction of behavioral accounting research in Indonesia through a literature review of articles published over the past 14 years. Using a systematic literature review (SLR) approach, this study analyzes publications from nationally accredited journals indexed in SINTA 2, 3 and 4 over the 2011 – 2024. This analysis focuses on research topics, methods and subjects. The results indicate that behavioral accounting research in Indonesia is predominantly focuses on religiosity-related topics, commonly employing survey/questionnaire methods and frequently uses academics/students as research subjects. These findins suggest a recurring pattern in topics, methods and research subjects, while also highlighting opportunites for future research development. This study is expected to provide a comprehensive map of development of behavioral accounting research in Indonesia and serve as a foundation for future researchers in formulating more innovative and contextual research agendas.

Abstract Public administration plays a fundamental role in accountability relationships between citizens and the State, but how these take shape in public encounters is remarkably understudied. Analysing relational dynamics within and around public encounters expands the relational perspective on accountability in public administration–challenging core assumptions of the principal-agent model underpinning studies of citizen-State accountability relationships. We conducted a critical-interpretivist ethnography of public encounters in the UK Tax Credits (TC) system and share findings from our Constructivist Grounded Theory Analysis of multiple data sources, including 28 open interviews. We discuss four relational dynamics of account-giving–emerging from the interplay of neoliberal discourse, digital technologies, and communicative practices–that ‘reversed the accountability chain’. We demonstrate how claimants experiencing significant financial and emotional hardship, in their encounters with an unaccountable State, became accountable for their TC obligations and welfare. We explain these findings by mobilising interdisciplinary theory from critical accounting research on relational power to offer original conceptual and empirical insight into the interactive, dynamic, and emergent accountability relationships between citizens and agents of the State.

HRMARS - Purpose: This research seeks to analyse bibliometric indicators of Islamic financial technology-related intellectual structures released in scientific journals indexed by the Scopus database. The purpose is to track the development of research in this domain to suggest future research avenues that may be beneficial in contemplating the substantial influence of FinTech on the advancement of Islamic finance. Methodology: Quantitative bibliometric analytic technique has been employed to understand the state-of-the-art in the development of Islamic financial technology literature based on several bibliographic indicators and visualisation. The authors assembled a dataset comprising 279 scientific papers retained from the Scopus database, covering the period from 2016 to 2025. VOSviewer and R bibliometrix (biblioshiny) were employed to examine the gathered data. Findings: A rapid increase in publications in recent years demonstrates the significance attained by this study domain. The bibliometric study identifies research on Islamic FinTech originating from the business, management, and accounting fields. Leading author Hassan M. Kabir and research institutes are at the University of Bahrain. The Journal of Islamic Accounting and Business Research is ranked 1, and Malaysia is leading the sector with the largest number of articles. Several critical research gaps and supplementary recommendations for future studies, together with concrete recommendations for researchers and Islamic finance authorities, are delineated. Originality/value: This research contributes to knowledge about Islamic FinTech by integrating the available literature, underlining that the banking industry must deal with such innovation in the context of the growing relevance of digital transformation aimed at the industrial revolution.

This section examines methodological transparency and interpretability in computational social science through the use of Orange Data Mining. As analytical workflows are often distributed across multiple software environments, key preprocessing and modelling decisions can become difficult to trace, limiting reproducibility and interpretability. The section argues that transparent analytical design is essential, particularly in fields where explanation is as important as prediction. Orange is presented as a visual, open source platform that makes each stage of analysis explicit. By constructing workflows through connected modules, the platform allows researchers to inspect data transformations, parameter settings and evaluation procedures within a single environment. The argument is demonstrated using the Zoo dataset included in Orange. Through a structured sequence of exploratory analysis, dimensionality reduction, interpretable classification and cross validated evaluation, the section illustrates a complete analytical cycle. The example shows how visual workflow design can support methodological clarity and accountable research practice.

Purpose This study explains how the informal sector impacts deal completion and the contingent roles of formal institutions, infrastructure and major restructuring. Using institutional complexity theory, this study aims to propose a new link between the informal sector and deal completion that emerges through the decreasing transaction cost of emerging markets. Design/methodology/approach The authors acquire deal-level data from the China Stock Market and Accounting Research Database (CSMAR) and national-level data from the World Bank Enterprise Survey (WBES). CSMAR includes full information on listed Chinese firms and is one of the most frequently used databases for research in the Belt and Road Initiative context. WBES provides data on the informal sector, formal institutions and infrastructure in 154 countries by administering a series of surveys to enterprises, and these data have been used in a few IB studies. Findings Data from a longitudinal sample reveal the positive effects of the informal sector on deal completion. The findings also show that formal institutions, infrastructure and major restructuring weaken this positive relationship. Practical implications This research has several implications for CEOs, top management teams (TMTs) and managers of emerging firms. First, the findings may reshape CEO entry strategies in emerging markets. Second, the findings indicate that the strategic collaboration of the TMT could maximize the advantages of the informal sector. Third, the strategic collaboration between the CEO and the TMT is based on managers whose work includes communication with the informal sector. Originality/value This investigation seeks to advance the understanding of sector-level informality and its impact on cooperative organizational response. This study deepens the understanding of institutional complexity in the interaction between the informal sector and formal institutions.

Improving the production and reviewing of design science research in accounting