Creative accounting has its background since early studies in 1975, until the present time. It continues to be a subject of great interest for the companies and interested parties. Thus, the current paper will aim to answer the following proposed research questions: 1. Which are the most used methods for detecting the manipulation of financial statements in the literature? 2. Which are the terms that are most frequently encountered in the literature associated with “creative accounting? 3. Which are the journals that have the highest frequency of articles written on the topic “creative accounting”? 4. Over time, how did research evolve in the field of creative accounting? 5. Which countries are most preoccupied in publishing regarding this topic? To answer the research question 1, the models published in the literature for measuring manipulation techniques through creative accounting were reviewed and analyzed. For the remaining research questions, a bibliometric analysis for the publications in this area was performed. For collecting the sample, articles on this topic were selected from the international Web of Science database. Following this, a bibliometric analysis of the articles was performed, using the VOSviewer program. A total of 4045 publications on creative accounting were identified. Through the bibliometric analysis we have answered research question 2, by identifying the key words that have the closest proximity to creative accounting. To answer the remaining research questions, we identified the journals with the highest frequency of publication and the countries with the highest interest on the topic. It is especially important to evaluate the quality of this many research papers and to obtain valuable information.

Bankruptcy prediction plays a crucial role, not only for individual companies, but also for the national economy. This helps companies identify financial problems before their situation becomes critical, allowing them to take corrective measures in time. In addition, the development of risk management strategies and the implementation of bankruptcy prevention policies become more effective. A popular method of predicting bankruptcy is the Z-score function, which combines several financial indicators to assess a company's bankruptcy risk. This study examines the use of the Z-score as a tool for evaluating bankruptcy risk for entities in the agrarian sector of the Republic of Moldova and aims to determine whether it can help identify early signs of bankruptcy risk. Through a literature review and the application of a relevant case study, the article highlights the effectiveness and limitations of using Z-score in bankruptcy prediction, offering recommendations for its use in financial analysis. The results suggest that the use of Z-score function in risk assessment models can significantly improve the accuracy of financial forecasts for entities in the agrarian sector of the Republic of Moldova.

The article was prepared as part of participation in the X International Scientific and Practical Conference "Accounting, Control and Taxation on the Way to Post-War Reconstruction of Ukraine and Achievement of Sustainable Development Goals", dedicated to the 100th anniversary of Mykola Chumachenko. Introduction. Bankruptcy prediction is a crucial process within financial analysis, involving the assessment of the likelihood that a company will become insolvent and ultimately enter bankruptcy proceedings. This evaluation is particularly important in an unstable economic environment. Moreover, in the context of increasing emphasis on financial sustainability, timely assessments support the long-term resilience of enterprises. Therefore, there is a clear need for the use of rigorous and effective financial tools capable of signaling imminent risks in time, thus enabling decision-makers to intervene promptly with appropriate corrective measures. Problem Statement. Despite the critical role of agriculture in Moldova’s economy, the sector remains vulnerable to financial instability caused by seasonal income fluctuations, climate-related risks, and limited access to capital. Traditional models of financial distress prediction, such as the Z-Score, are widely applied in corporate finance but have not been sufficiently tested in the context of agricultural enterprises in Moldova. This gap raises concerns regarding the applicability and accuracy of such models for assessing financial sustainability in the regional agrarian sector. Purpose. The purpose of this study is to assess the applicability and predictive accuracy of Altman’s Z-Score models in evaluating the financial sustainability and bankruptcy risk of agricultural enterprises of the Republic of Moldova. The research aims to determine whether these models, originally developed for industrial and commercial sectors, can be effectively adapted to reflect the specific financial dynamics of the agricultural sector within a regional context. Methods. This study employs a quantitative research methodology based on financial ratio analysis and bankruptcy prediction modeling. The Altman Z-Score models (Z-Score, Z’-Score, and Z’’-Score) were applied to a dataset of agricultural enterprises of the Republic of Moldova to evaluate their financial stability and risk of insolvency. Financial statements covering a five-year period were collected from official sources and company records. The selected models were adapted to account for sector-specific characteristics and compared in terms of predictive accuracy. Statistical tools such as descriptive analysis and correlation testing were used to interpret the results and validate the models’ applicability to the regional context. Results. For this research, 12 enterprises were selected whose main activities fall within the agricultural sector. The selection aimed to ensure a representative diversity in terms of financial condition and sustainability potential, enabling a relevant comparative analysis. Comparative analysis of the three models indicates that the Anghel model provides the most consistent and relevant results in the specific context of Moldovan agriculture, demonstrating superior adaptability and greater estimation accuracy. Nonetheless, all three models show inherent limitations when applied to the agricultural sector, which calls for caution in interpretation and the need to complement them with other financial assessment methods. Their application must be accompanied by detailed contextual analysis, accounting for the economic, operational, and climatic specificities of the domain. Without methodological adjustments tailored to the sector’s characteristics—such as income volatility, pronounced seasonality, and external shocks—these models may yield incomplete or misleading interpretations. Conclusions. This study confirms that traditional financial distress prediction models, such as Altman’s Z-Score, require adaptation when applied to the agricultural sector in Moldova. The modified Z’-Score and Z’’-Score models proved to be more suitable for evaluating the financial sustainability of agricultural enterprises, offering more accurate and context-relevant assessments. The prevalence of enterprises within the “gray zone” highlights a widespread exposure to moderate insolvency risk, reinforcing the importance of continuous financial monitoring. Future research should focus on developing sector-specific calibration of bankruptcy models to enhance their reliability and support informed decision-making in regional agroeconomic policy.

Purpose: This research aims to explore the relationship between the number of business failures and the prevalence of economic and financial crime. First, the study contributes to theory by analyzing the connections among the shadow economy, money laundering, corruption, tax burden and corporate insolvencies across various European economies. Second, it offers practical guidance for economic policymakers regarding the impact of these macroeconomic factors on the frequency of business insolvencies.Design/methodology/approach: This study employs panel regression analysis to examine data from 32 countries, comprising 17 Western European nations and 15 Central and Eastern European nations, over the period from 2013 to 2023.Findings: The findings indicate that an increase in the shadow economy and money laundering, along with a decrease in the fiscal burden, is positively correlated with the number of business failures. Furthermore, empirical evidence shows that the level of innovation has a direct effect on the rate of corporate insolvencies. Therefore, we can conclude that promoting innovation may assist governments in mitigating issues related to bankruptcies.Originality/value: The issue of economic and financial crime goes well beyond mere tax revenue loss; it impacts vital national concerns such as labor protection, fair competition, innovation incentives, and the overall allocation of resources in the economy. Therefore, enhancing institutional efficiency and improving oversight are critical considerations for companies aiming to achieve long-term benefits and ensure business resilience.

This chapter explores the complexities of aligning national policies with the European Union’s objectives in transitioning to a circular economy within the construction sector. While EU directives establish general frameworks, national governments encounter challenges in adapting these directives into coherent and context-specific regulations. The chapter identifies key obstacles to effective policy implementation, including fragmentation, institutional overlap, and inconsistent terminology. Additionally, it examines how governance structures, planning traditions, and institutional cultures influence policy coherence. The analysis is based on survey results collected in 2023. Although subsequent policy and regulatory changes have occurred in the past two years, the data remain relevant, as they capture the main trends and challenges that continue to shape national approaches to circular construction. By analyzing case studies and examples from various member states, the chapter emphasizes the necessity for enhanced multilevel coordination, harmonized regulatory frameworks, and knowledge-sharing platforms. Bolstering policy coherence is crucial to ensure that national initiatives make meaningful contributions to the EU’s circular economy goals and the broader sustainability agenda.

Due to the strong support and help of the government during the recent economic crisis, the number of corporate insolvencies in the Republic of Moldova maintained the same tendency since 2017. This paper focuses on the evolution of firm exit due to bankruptcy in the countries of Central and Eastern Europe, with a special attention to the Republic of Moldova. The study was carried out on a sample of 15 countries in the period 2013-2020. Data was collected from Euler Hermes, Allianz Research and Creditreform reports. The research methods used in this paper are: data collection, data processing, time series trend model estimation and descriptive analysis. Examining trends allows the identification and analysis of the main trends that appear within the analyzed phenomenon. In most cases, the level of fit of the model to the empirical data indicates its practical utility. The obtained econometric tool can be used for forecasting the examined variable.