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In this study, the power of vibrational genetic algorithm (VGA) for transonic airfoil design and optimisation problems, which are generally characterized by multi‐model topology in the design parameter space, has been introduced. This type of problem is characterized by search and computational time to achieve satisfying solutions. In order to obtain more robust and faster algorithm, vibration concept, our earlier study, is further developed. This developed VGA is coupled with a full potential flow‐field solver for inverse design and airfoil optimisation problem in transonic case. The performance of this implemented strategy is compared with that offered by a classical or more commonly used genetic algorithm.

The purpose of this paper is to empirically examine capital structure determinants of small- and medium-sized enterprises (SMEs) during and after the global financial crisis.

Statistical methods, including ordinary least squares and the generalised method of moments, were used to analyse a sample of over 40,800 Swedish SMEs operating in four industries during the 2008–2015 period.

The results indicate that the independent variables – i.e. financial crisis, profitability, size, tangibility and industry affiliation – to various degrees explain changes in short-term debt (STD) and long-term debt (LTD) ratios. In particular, the empirical findings indicate that the sampled SMEs tended to rely more on STD and LTD during (2008–2009) than after (2010–2015) the financial crisis.

Due to data availability, the current study is limited to a sample of Swedish SMEs in four industries covering eight years. Further research could examine the generalisability of these findings by investigating other firms operating in other industries and other countries.

This study is one of few examining determinants of short- and long-term SME debt during and after the global financial crisis, using data from a large-scale cross-sectional database.

This paper tries to shed light on the international progress regarding the adoption of International Public Sector Accounting Standards (IPSAS), to accentuate the benefits resulting from the application of IPSAS, and to highlight the main differences between IPSAS and IFRS.

A comprehensive literature review is conducted which focuses on issues concerning the factors that induce the adoption of IPSAS, the obstacles that must be overcome, the degree of IPSAS’ proliferation worldwide, the repercussions from adopting IPSAS, the benefits of IPSAS, and the differences between IPSAS and IFRS. The selection process of the cited articles focuses on journals with high rankings in the ABS list.

It is accentuated that IPSAS carry significant benefits regarding the improved quality of the financial information reported by the public sector, the enhancement of transparency and accountability, the upgrading of the decision-making process and the restored trust in public finances. However, there is more work that needs to be done toward the global proliferation of IPSAS.

This study provides insights regarding the implementation process of IPSAS, which should be useful to all the parties engaged in the reform of the public administration, such as national governments, local or international regulators, accounting standard setters and institutional organizations.

The current study clarifies whether the public sector should move from using the business focused IFRS, as it is frequently the case, to the adoption of IPSAS. In addition, this study comprehensive literature review can be used by academics and researchers as a basis for further research on the issue. More importantly, policymakers and other officials who need to make informed decisions about financial reporting issues at the government level and the public sector in general can benefit from this study.

We introduce the Vibration concept for real coded Genetic Algorithm and its implementation to inverse airfoil design, which decreases the number of CFD calculations. This concept assures efficient diversity in the population and consequently gives faster solution. We used the Vibration concept as vibrational mutation and vibrational crossover. For the mutational manner, a sinusoidal wave with random amplitude is introduced into population periodically from the beginning of the initial step of the genetic process. This operation spreads out the population over the design space and increases exploration performance of the genetic process. This makes passing over local optimums for genetic algorithm easy. In order to apply this new concept at the crossover stages, Double Directional Alpha (DDA) approximation in BLX‐α as a new crossover technique which was already presented in our earlier study is used. In the developed technique, the value of α oscillates systematically during the genetic process. Implementation of the Vibration concept to the inverse airfoil design makes the convergence faster.

To attempt to relate the mean returns and price volatility of a selected sample of 30 companies listed in Athens stock exchange (ATHEX), to the introduction of the legal framework concerning corporate governance.

The essence of this approach is segmenting our whole sample into three subsamples with their key dates being the actual dates on which two legal frameworks related to the corporate governance has been introduced, we perform mean and variance equality tests to assess whether stock market returns and price volatility change, in a statistically significant way, in the three sub-periods.

From our empirical study, it can be concluded that the volatility has been altered both during the sample periods used and the companies for which our methodology has been implemented.

Our empirical research can be further extended including a larger sample of companies in order to draw more safe conclusions. In addition, and although our argument for high liquidity for selecting our sample of companies is rational, we believe that our research can be further enriched by first constructing a ranking for all listed companies based on various corporate governance measures.

One of the reasons that may have impacted on the volatility may be the introduction of corporate governance; however, other factors may have also resulted to lower volatility, argument that can be further researched in future studies.

This paper provides evidence on the relation between volatility and corporate governance. The implication is that the volatility has been altered during the period under investigation.

This paper attempts to investigate the effect of corruption on the real and accrual earnings management of target firms in the process of mergers and acquisitions.

The sample includes target firms from the European area that participate in mergers or acquisitions announced during 2010–2020. The preliminary empirical part estimates the level of earnings management during the period two years before the deal's announcement to identify whether the sample follows the manipulation behavior that the literature suggests for target firms. The primary empirical analysis focuses on the impact of corruption on real and accrual-based earnings management proxies, employing regression models and two alternative proxies for corruption. The existing literature points out that the combination of low levels of corruption and an integrated legal system reduces earnings manipulation.

The findings provide strong evidence for systematic downwards accounting manipulation practices, whereas the findings for real earnings management are not significant. The findings of the main empirical part show that corruption is positively associated with accrual-based manipulation and negatively related to real earnings management. In essence, in economies with a high level of transparency, managers adopt the manipulation of operating activities as a less detectable practice of earnings management instead of engaging in accounting procedures.

This study contributes to the literature highlighting the diversification of these firms' manipulation strategies according to the national level's corruption status.

This paper aims to assess the factors that may explain the International Public Sector Accounting Standards (IPSAS) convergence, considering Hofstede’s cultural dimensions as the theoretical reference for the cultural approach proposed. Additional factors include countries’ contextual and macroeconomic characteristics.

Logistic and probit regression models were used to identify the factors that may explain the IPSAS (fully or adapted) use by countries, including 166 countries in this assessment (59 for those whose cultural dimensions are available).

The findings consistently indicate collectivism and indebtedness levels as explanatory factors, providing insights into cultural dimensions along with macroeconomic characteristics as a relevant factor of countries’ convergence to IPSAS.

There are different levels of IPSAS convergence by countries that were not considered. This aspect may hide different countries’ characteristics that may explain those options, which could not be distinguished in this paper.

As a result of this paper, the International Public Sector Accounting Standards Board may gain insights that can be applied within the IPSAS due process to overcome the main challenges when collaborating with national authorities to achieve a high level of convergence. This analysis may include how to accommodate countries’ cultural differences as well as their contextual and macroeconomic characteristics.

There is a trend of moving toward accrual-based accounting standards by countries. Because the public sector embraces a new culture following the IPSAS path, it is relevant to assess if there are cultural factors, besides contextual and macroeconomic characteristics, that may explain the countries’ convergence to those standards.

To the best of the authors’ knowledge, this is the first cross-country analysis on the likely influence of cultural dimensions on IPSAS convergence as far as the authors’ knowledge.

In this study, dynamic mesh method is implemented on a real coded genetic algorithm to demonstrate gain in computational time as well as in higher performance for optimized parameters. Since the differences developed at each step in geometries of new members are not significant, therefore, it is possible to use dynamic mesh methods for new members. In this work, because the population members are obtained by modifying the pervious ones, each member is considered as one step of geometry‐change of a deforming body, for examples, a wing inflating, deflating or cambering.

This paper aims to analyse the Portuguese companies’ determinants of capital structure. To reach this objective, the authors used data from 37 non-financial Portuguese large enterprises and from 4,233 non-financial small and medium enterprises for the period 2010-2016. Additionally, the authors selected a sub-period from 2010 to 2014 for a deeper understanding of the impact of the sovereign debt crisis and the Economic Adjustment Programme of Troika on the capital structure of those companies.

Three dependent variables were tested according to debt maturity, and a dynamic panel data model, namely, the generalised method of moments system estimator, was used to test the formulated research hypotheses following Arellano and Bover (1995) and Blundell and Bond (1998) to capture the dynamic nature of the firm’s capital structure decisions.

In general, the results point out that the capital structure decisions depend on a set of firm-specific factors, and that the effects of the determinants of the debt maturity ratios differ according to the type of firm, i.e. large/small firms, and the economic cycle.

To the best of the authors’ knowledge, this is the first study that has been carried out in Portugal by using two samples of large and small companies for analysing the effects of the Economic Adjustment Programme of Troika on the capital structure of companies. The authors seek to understand which type of companies suffered more because of the effects of the Economic Adjustment Programme of Troika during this period, and which are the capital structure determinants that present greater change. Contrary to what might be expected, large companies are the firms that suffer most from the Economic Adjustment Programme. Probably, because these companies are the most immediate, most scrutinised and those that must show abroad that the bank did not fund them in the long term, because of the imposition and limits to grant credit faced by the banks themselves.

Big Data analytics (BDA) and its implications for the accounting profession continue to be a key issue that requires more research and evaluation. As a result, the purpose of this study is to evaluate the impact of BDA on financial reporting quality, as well as to assess the accounting challenges associated with Big Data. It provides qualitative evidence from Canada.

This study used a qualitative approach to ascertain the thoughts and perceptions of auditors, financial analysts and accountants at Canadian audit and accounting firms in BDA and its impact on financial reporting quality, using semi-structured interviews. To obtain their consent to participate in the interview, 127 auditors, financial analysts and accountants from Canadian audit and accounting firms were initially approached. The final number of respondents was 41, representing a response rate of 32%.

The authors’ findings underscored the relevance of Big Data and BDA in affecting financial report quality and revealed that BDA had a significant effect on improving financial reporting quality. Big Data improves accounting reporting and expert judgment by providing professional. In summary, participants agreed that when analytical methods in Big Data are implemented effectively, businesses may possibly achieve a variety of benefits, including customized goods, simplified processes, improved risk assessment process and, finally, increased risk management.

The authors’ findings indicate that BDA may help predict investment returns and risks, estimate future investment opportunities, forecast revenues, detect fraud and susceptibility early and identify economic growth opportunities. As a result, auditors, financial analysts, accountants, investors and other strategic decision-makers should be aware of these findings to make informed choices.

Big Data has become the norm in recent years; accountants and other decision-makers have struggled to analyze massive amounts of data. This limits their capacity to profit from such data even more. Therefore, this study is motivated by the lack of research on Big Data’s influence on financial report quality.