Hasil untuk "Accounting. Bookkeeping"

Matthew Stewart

Algorithmic accountability scholarship has focused heavily on explanation, helping affected parties understand why decisions were made. We argue this focus is insufficient. Explanation without evidentiary access does not enable meaningful contestation. A person told "your risk score was 0.73" understands the decision but cannot verify the score, test alternatives, or produce counter-evidence. We introduce a taxonomy of contestation failures, showing that most accountability interventions address only one failure mode (opacity) while leaving four others unaddressed. Drawing on analysis of 168 legal cases spanning algorithmic decision-making contexts, we find that contestation faces a two-gate structure: a procedural gate (evidentiary access) and a doctrinal gate (substantive liability rules). Among litigated cases, those without evidence access almost never succeed (9%); those with access succeed at rates approaching 97% in domains without liability shields. Where doctrinal immunities apply (e.g., Section 230), even full evidentiary scrutiny produces no liability. This association almost certainly reflects selection effects; our empirical contribution is diagnostic rather than causal. The data identify where contestation fails among observable cases, not whether providing access would change outcomes for currently-excluded cases. We propose evidentiary rights as the missing procedural component, and develop counterfactual interrogation rights that allow affected parties to probe decision systems with modified inputs and observe whether outcomes change, without requiring disclosure of model internals. This reframes algorithmic accountability from a transparency problem to a procedural rights problem.

Haileleol Tibebu

Existing accountability frameworks for AI systems, legal, ethical, and regulatory, rest on a shared assumption: for any consequential outcome, at least one identifiable person had enough involvement and foresight to bear meaningful responsibility. This paper proves that agentic AI systems violate this assumption not as an engineering limitation but as a mathematical necessity once autonomy exceeds a computable threshold. We introduce Human-Agent Collectives, a formalisation of joint human-AI systems where agents are modelled as state-policy tuples within a shared structural causal model. Autonomy is characterised through a four-dimensional information-theoretic profile (epistemic, executive, evaluative, social); collective behaviour through interaction graphs and joint action spaces. We axiomatise legitimate accountability through four minimal properties: Attributability (responsibility requires causal contribution), Foreseeability Bound (responsibility cannot exceed predictive capacity), Non-Vacuity (at least one agent bears non-trivial responsibility), and Completeness (all responsibility must be fully allocated). Our central result, the Accountability Incompleteness Theorem, proves that for any collective whose compound autonomy exceeds the Accountability Horizon and whose interaction graph contains a human-AI feedback cycle, no framework can satisfy all four properties simultaneously. The impossibility is structural: transparency, audits, and oversight cannot resolve it without reducing autonomy. Below the threshold, legitimate frameworks exist, establishing a sharp phase transition. Experiments on 3,000 synthetic collectives confirm all predictions with zero violations. This is the first impossibility result in AI governance, establishing a formal boundary below which current paradigms remain valid and above which distributed accountability mechanisms become necessary.

Victor Ojewale, Harini Suresh, Suresh Venkatasubramanian

Large language models (LLMs) are increasingly embedded in consequential decisions across healthcare, finance, employment, and public services. Yet accountability remains fragile because process transparency is rarely recorded in a durable and reviewable form. We propose LLM audit trails as a sociotechnical mechanism for continuous accountability. An audit trail is a chronological, tamper-evident, context-rich ledger of lifecycle events and decisions that links technical provenance (models, data, training and evaluation runs, deployments, monitoring) with governance records (approvals, waivers, and attestations), so organizations can reconstruct what changed, when, and who authorized it. This paper contributes: (1) a lifecycle framework that specifies event types, required metadata, and governance rationales; (2) a reference architecture with lightweight emitters, append only audit stores, and an auditor interface supporting cross organizational traceability; and (3) a reusable, open-source Python implementation that instantiates this audit layer in LLM workflows with minimal integration effort. We conclude by discussing limitations and directions for adoption.

Hong Joo Ryoo

Modern physics proposals present deep tensions between seemingly contradictory descriptions of reality. Views of wave-particle duality, black hole complementarity, and the Unruh effect demand explanations that shift depending on how a system is observed. However, traditional models of scientific explanation impose a fixed structure that fails to account for varying observational contexts. This paper introduces context-dependent mapping, a framework that reorganizes physical laws into self-consistent subsets structured around what can actually be observed in a given context. By doing so, it provides a principled way to integrate complementarity into the philosophy of explanation.

Antoine Bret

It is argued that the Vlasov equation cannot fully account for collisionless shocks since it conserves entropy, while a shock does not. A rigorous mathematical theory of collisionless shocks could require working at the Klimontovich level.

Ifin Naim, Wa Ode Nursaadha Rajuddin

This study investigates the effect of content marketing on customer loyalty through the mediating role of customer engagement in the context of culinary MSMEs in the digital era. Using a quantitative approach and structural equation modeling (PLS-SEM) with data from 200 respondents, the results reveal that content marketing does not directly influence customer loyalty. However, it significantly impacts customer engagement, which in turn positively affects loyalty. Furthermore, customer engagement fully mediates the relationship between content marketing and loyalty. These findings highlight the critical role of engagement in transforming content strategies into long-term customer relationships. The study offers valuable implications for MSME practitioners aiming to optimize digital content to build loyalty.

Tiara Sea Misa, Umiaty Hamzani, Khristina Yunita

This study investigates the influence of external pressure, tax digitalisation, and corporate social responsibility (CSR) disclosure on financial statement fraud in manufacturing companies listed on the Indonesia Stock Exchange (IDX) during the 2020 to 2023 period. A quantitative approach was employed using purposive sampling, with secondary data from annual and sustainability reports. CSR disclosure was measured using the CSRI index based on GRI standards, while financial statement fraud was measured using the Beneish M-Score model. The findings indicate that external pressure significantly affects financial statement fraud, whereas tax digitalisation and CSR disclosure have significant adverse effects. These results highlight the importance of implementing digital taxation systems and CSR practices to mitigate the risk of financial statement fraud.

Hamidreza Asili, Mohammadreza Abdoli, Hassan Valiyan

The purpose of this study is Presenting a model of Dunning-Krueger syndrome characteristics with the aim of evaluating auditors' professional frustrations. The methodology of this study is mixed, so that in the qualitative part, through systematic screening, the main and thematic axes of the causes of auditors' professional frustration are identified based on the Dunning-Krueger syndrome model. Then, during two stages of Delphi analysis, an attempt is made to check the reliability of the identified dimensions. Finally, in the quantitative part, it seeks to evaluate the phenomenon of auditors' professional disillusionment through FDEMATEL analysis and interpretive rating. The results of the study in the qualitative part of the existence of three main axes and 22 themes were selected as a model of Dunning-Krueger syndrome characteristics. Then, in the first quantitative section, it was determined that occupational causes are the most important axis of Dunning-Krueger syndrome, which is considered the main driver of auditors' professional frustrations. It was also found that the authoritarian leadership and management style in the role of the audit partner is considered an effective theme in the occurrence of professional frustration in auditors based on the Dunning-Kruger syndrome model. The result of this study shows that occupational causes are the most effective as a frustration process in stressful jobs. Because the stimuli that cause the audit profession to erode auditors through job pressure are usually extensive and often uncontrollable.

M. K. Volkov, A. A. Pivovarov, K. Nurlan

In the $U(3) \times U(3)$ quark NJL model, $τ$ lepton decays with the production of scalar mesons $f_0(π,K])$ and neutrinos are studied, where $f_0=f_0(500), f_0(980)$. It is shown that these decays mainly occur via contact channels and channels with axial-vector mesons $a_1$, $K_1(1270)$ and $K_1(1400)$. All mesons are considered as quark-antiquark states in this case. The obtained results can be considered as predictions for future experiments. The obtained estimates for the branching fractions of the $τ\to π^-2π^0 ν_τ$ decay taking into account the contributions of the $ρπ$ and $f_0(500)π$ states are in satisfactory agreement with experimental data.

Fabio Marsicano Fagundes, Talles Vianna Brugni, Silvania Neris Nossa

Este estudo objetiva analisar a habilidade gerencial na prática do gerenciamento de resultados, via suavização de resultados e accruals, nas empresas da B3. Para tal, realizou-se uma pesquisa quantitativa e descritiva com os dados obtidos na base de dados da Economática, que perfez uma amostra com 966 observações, no período de 2010 a 2020. Utilizou-se como medida de habilidade gerencial o modelo de Demerjian et al. (2012), que possui como parâmetros de eficiência as características do gerente na utilização dos recursos para gerar receitas. Para medir a suavização e os níveis de gerenciamento de resultados, utilizaram-se os modelos de Leuz et al. (2003) e McNichols (2002), respectivamente. Os resultados demonstraram que, em média, os gestores mais habilidosos tendem a suavizar e gerenciar resultados em níveis maiores do que gestores com menor habilidade, o que sinaliza que no Brasil, em média, os gestores mais hábeis tendem a diminuir a qualidade do lucro das firmas brasileiras. Este trabalho contribui com a literatura e preenche uma lacuna sobre a habilidade gerencial e o impacto dos resultados das empresas brasileiras, pois evidencia que, no Brasil, a habilidade gerencial está associada com práticas de suavização e gerenciamento de resultados e lança uma luz para as partes interessadas a respeito da influência do perfil dos gestores e suas capacidades de influenciarem nos números divulgados no mercado brasileiro.

Ming Chen, Andrew Gunawan, H. Heriyanto

This research was conducted to explore the root of the problem that causes micro-entrepreneurs to want or not to carry out bookkeeping. Bookkeeping itself is the foundation of an effort to record income and expenses in a period. Bookkeeping is the basic foundation for providing accounting information to micro and small scale businesses, especially for decision making, so it is interesting to study. This research will be conducted on micro-enterprises in the city of Palembang, bearing in mind that there are still many micro-enterprises that have not kept bookkeeping. The sample selection technique in this study used a purposive sampling method. This study uses SPSS 23. The results in this study are that behavior has no effect on interest, subjective norms and behavioral control have a positive effect on the interest of MSME actors in the city of Palembang.

U. W. Sagena, Alrifda Salsabilah, Andini Fadelia et al.

Financial bookkeeping is one of the most important things in business and personal activities. However, in practice there are still many parties who have not done financial bookkeeping or are still doing the bookkeeping manually. Therefore, the DIGIKAS & IBUK Dual Program was carried out so that the target financial accounting process could run more easily, be more environmentally friendly (Paperless), and reduce the impact on the environment. The dual program was aimed to 60 UMKM in the Water Settlement Area, 70 participants consisting of Ibu PKK and RT Cadre in Kelurahan Marga Sari. The method used in the IBUK & DIGIKAS dual program are interview, socialization and practice (real action). The results of the activity are that UMKM in Marga Sari Village receive additional information and knowledge about the importance of financial bookkeeping, know the digital financial bookkeeping application, "BukuKas" and know how to use the application that can facilitate financial bookkeeping activities and environmentally friendly (Paperless)

R. R. Dewi, Seto Makmur Wibowo, Mauliddini Nadifah

Abstract Purpose: Bookkeeping is one of the important factors that aim to develop MSMEs. Simple bookkeeping is quite important for the progress of their own business. One of the causes of MSMEs being difficult to develop is a poor accounting system. This is due to the government's lack of attention, and there are still many MSME actors who are reluctant to think about complicated things such as accounting and financial management issues. Currently, MSME actors are only limited to thinking about how to get profits so that their business or MSMEs can run and develop. To that end, the Indonesian Institute of Accountants (IAI) has prepared SAK-EMKM (Financial Accounting Standards for Micro, Small and Medium Entities) to facilitate MSMEs in compiling their financial reports. Method: This community service (PKM) was held online in March 2021 with the participants from business people in the convection and culinary fields. PKM is carried out by lecturers, students, alumni and staff. Result: The results of this PKM activity resulted that members of the KOMPETeN MSME group did not understand well about the types of financial statements and their benefits and how to prepare them, especially the preparation of income statements in accordance with generally accepted accounting standards. Conclusion: This community service (PKM) help the KOMPETeN MSME group to prepare simple financial statement.

Jacob Metcalf, Emanuel Moss, Ranjit Singh et al.

Central to a number of scholarly, regulatory, and public conversations about algorithmic accountability is the question of who should have access to documentation that reveals the inner workings, intended function, and anticipated consequences of algorithmic systems, potentially establishing new routes for impacted publics to contest the operations of these systems. Currently, developers largely have a monopoly on information about how their systems actually work and are incentivized to maintain their own ignorance about aspects of how their systems affect the world. Increasingly, legislators, regulators and advocates have turned to assessment documentation in order to address the gap between the public's experience of algorithmic harms and the obligations of developers to document and justify their design decisions. However, issues of standing and expertise currently prevent publics from cohering around shared interests in preventing and redressing algorithmic harms; as we demonstrate with multiple cases, courts often find computational harms non-cognizable and rarely require developers to address material claims of harm. Constructed with a triadic accountability relationship, algorithmic impact assessment regimes could alter this situation by establishing procedural rights around public access to reporting and documentation. Developing a relational approach to accountability, we argue that robust accountability regimes must establish opportunities for publics to cohere around shared experiences and interests, and to contest the outcomes of algorithmic systems that affect their lives. Furthermore, algorithmic accountability policies currently under consideration in many jurisdictions must provide the public with adequate standing and opportunities to access and contest the documentation provided by the actors and the judgments passed by the forum.

T. Blenski, R. Piron

We propose a model of ion-electron plasma (or nucleus-electron plasma) that accounts for the electronic structure around nuclei (i.e. ion structure) as well as for ion-ion correlations. The model equations are obtained through the minimization of an approximate free-energy functional, and it is shown that the model fulfills the virial theorem. The main hypotheses of this model are 1) nuclei are treated as classical indistinguishable particles 2) electronic density is seen as a superposition of a uniform background and spherically-symmetric distributions around each nucleus (system of ions in a plasma) 3) free energy is approached using a cluster expansion (non-overlapping ions) 4) resulting ion fluid is modeled through an approximate integral equation. In the present paper, the model is described only in its average-atom version.

Oliver Buchholz

Explainable artificial intelligence (XAI) seeks to produce explanations for those machine learning methods which are deemed opaque. However, there is considerable disagreement about what this means and how to achieve it. Authors disagree on what should be explained (topic), to whom something should be explained (stakeholder), how something should be explained (instrument), and why something should be explained (goal). In this paper, I employ insights from means-end epistemology to structure the field. According to means-end epistemology, different means ought to be rationally adopted to achieve different epistemic ends. Applied to XAI, different topics, stakeholders, and goals thus require different instruments. I call this the means-end account of XAI. The means-end account has a descriptive and a normative component: on the one hand, I show how the specific means-end relations give rise to a taxonomy of existing contributions to the field of XAI; on the other hand, I argue that the suitability of XAI methods can be assessed by analyzing whether they are prescribed by a given topic, stakeholder, and goal.

Marcos Ezequiel Mastrangelo, Juan Manuel Salvatierra

La evaluación del desempeño de carteras es una parte muy importante en el análisis de gestión de las inversiones y, generalmente, se realiza evaluando los rendimientos ajustados al riesgo. El presente trabajo analiza el comportamiento de los fondos comunes de inversión (FCI) de renta variable de Argentina que tienen como benchmark financiero al índice ROFEX 20 durante los años 2019 y 2020, empleando indicadores de referencia como Alpha, Alpha ajustado, y los índices Sharpe, Sortino y Treynor. Metodológicamente, se realizan tres análisis: de correlación (entre rentabilidad FCI e índice), de eficiencia (rendimiento diferencial FCI respecto al índice) y de persistencia (sostenibilidad rendimientos). Según los hallazgos, los FCI analizados han obtenido un rendimiento acorde índices o para su uso en operaciones de cobertura con derivados financieros. El artículo constituye un estudio novedoso, dada la reciente creación del índice ROFEX 20 y el contexto de volatilidad durante los años examinados. al riesgo y han sido un buen vehículo para emularlo, tanto para replicar los

Arash Tahriri, Soheil Mohamad Hasanzadeh

Objective: Organizations seek to adapt to their environment through mechanisms that help them achieve their goals. Internal control provides reasonable assurance of an organization's goals. Implementation of internal control affects its conduct and the number of weaknesses identified in the evaluation of the system. Therefore the purpose of this study is to identify factors influencing the internal control system deployment.Methods: This research is qualitative and was done using the Multi-Grounded Theory. Therefore, the data was analyzed using experimental and theoretical grounding. Experimental data was obtained from theoretical sampling; 13 semi-structured interviews were conducted with experts with successful experiences in implementing the internal control system from the Iranian calendar year of 2019 to 2020. The theoretical data was derived from reviewing the extant literature.Results: The results of this study showed that inefficiency and effectiveness of procedures, lack of proper segregation of duties, and lack of proper documentation of procedures make deployment inevitable. It was also proved that the implementation process is influenced by audit quality, organizational structure, quality of computer systems, management characteristics, and the quality of the knowledge of the group responsible for the establishment, quality of the board, and external rules.Conclusion: By building trust, training, proper scheduling, continuous monitoring, system recognition, and identifying the needs of the organization, the internal control system can be established according to the size of the company, industry type, time constraints, management support, and employee support.

Elena M. Kantor, Mikhail E. Gusakov, Vasiliy A. Dommes

We calculate the finite-temperature r-mode spectrum of a superfluid neutron star accounting for both muons in the core and the entrainment between neutrons and protons. We show that the standard perturbation scheme, considering the rotation rate as an expansion parameter, breaks down in this case. We develop an original perturbation scheme which circumvents this problem by treating both the perturbations due to rotation and (weak) entrainment simultaneously. Applying this scheme, we propose a simple method for calculating the superfluid r-mode eigenfrequency in the limit of vanishing rotation rate. We also calculate the r-mode spectrum at finite rotation rate for realistic microphysics input (adopting, however, the Newtonian framework and Cowling approximation when considering perturbed oscillation equations) and show that the normal r-mode exhibits resonances with superfluid r-modes at certain values of temperatures and rotation frequencies in the parameter range relevant to neutron stars in low-mass X-ray binaries (LMXBs). This turns the recently suggested phenomenological model of resonance r-mode stabilization into a quantitative theory, capable of explaining observations. A strong dependence of resonance rotation rates and temperatures on the neutron superfluidity model allows us to constrain the latter by confronting our calculations with the observations of neutron stars in LMXBs.

Jiajun Zhou, Chenkai Hu, Shenbo Gong et al.

Blockchain technology has the characteristics of decentralization, traceability and tamper proof, which creates a reliable decentralized transaction mode, further accelerating the development of the blockchain platforms. However, with the popularization of various financial applications, security problems caused by blockchain digital assets, such as money laundering, illegal fundraising and phishing fraud, are constantly on the rise. Therefore, financial security has become an important issue in the blockchain ecosystem, and identifying the types of accounts in blockchain (e.g. miners, phishing accounts, Ponzi contracts, etc.) is of great significance in risk assessment and market supervision. In this paper, we construct an account interaction graph using raw blockchain data in a graph perspective, and proposes a joint learning framework for account identity inference on blockchain with graph contrast. We first capture transaction feature and correlation feature from interaction graph, and then perform sampling and data augmentation to generate multiple views for account subgraphs, finally jointly train the subgraph contrast and account classification task. Extensive experiments on Ethereum datasets show that our method achieves significant advantages in account identity inference task in terms of classification performance, scalability and generalization.