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When financial statements are public, the choice between alternative reporting regimes constitutes a signal that addresses external stakeholders. Generally, the choice of more complex regimes acts as a complement of firms' transparency. However, in the absence of audits, opportunistic behaviors could be incentivized. This study aims to test whether SMEs' choice between alternative accounting regimes is associated with earnings quality.

Drawing on the literature about accounting choices and earnings quality, this study investigates whether the same conclusions are confirmed for SMEs. Using a sample of 4,054 Italian companies and 12,114 observations, it compared four earnings quality proxies of a group of companies that opted for the “Full” rules and those of a subsample of the population of companies that applied the Simplified rules.

The results suggest that the signaling power of accounting rules' choice could lead to wrong conclusions for SMEs. Indeed, a positive relationship emerged (H1) between the choice of the “Full” rules and income smoothing behaviors, while the same choice appears to reduce the probability to disclose SPOS. Moreover, the results suggest that opportunistic behaviors are more frequent for firms that have settled in a “non-cooperative” social environment (H2).

This study could foster research on financial reporting quality in private firms.

Comparing the quality of financial statements drawn up according to two alternative accounting regimes could provide useful suggestions for both users and regulators.

The results contribute to the limited literature on the implications of differential reporting. Finally, it enriches the literature about heterogeneity in accounting quality within private firms.

The purpose of this paper is to provide insights into the implications of board human capital heterogeneity for company innovation by focusing on the educational and the functional background of directors. Moreover, it examines the moderating effect of the CEO expertise-overlap within the innovation domain on the relationship between board human capital heterogeneity and firm innovation.

The hypotheses are tested through a set of ordinary least squares regressions on a unique dataset of 149 Italian high-tech companies observed between 2012 and 2015.

Findings show that the educational and the functional background heterogeneity of directors increase both the innovation input and output. However, results highlight that these relationships are negatively moderated by the CEO expertise-overlap within the innovation domain.

The paper emphasizes the importance of appointing directors with different and specific educational and functional backgrounds to foster the company innovation.

The paper fills a gap in the literature as it has devoted limited attention to the performance implications of board human capital heterogeneity in the high-tech industry where knowledge and skills are the primary sources of value. Moreover, the paper integrates the research on the CEO-board interface by shedding light on how the CEO expertise within the innovation domain affects the contribution of heterogeneous boards to company innovation.

This study reviews and discusses the accounting literature that analyzes the role of auditors and enforcers in the context of fraud.

This literature review includes both qualitative and quantitative studies, based on the idea that the findings from different research paradigms can shed light on the complex interactions between different financial reporting controls. The authors use a mixed-methods research synthesis and select 64 accounting journal articles to analyze the main proxies for fraud, the stages of the fraud process under investigation and the roles played by auditors and enforcers.

The study highlights heterogeneity with respect to the terms and concepts used to capture the fraud phenomenon, a fragmentation in terms of the measures used in quantitative studies and a low level of detail in the fraud analysis. The review also shows a limited number of case studies and a lack of focus on the interaction and interplay between enforcers and auditors.

This study outlines directions for future accounting research on fraud.

The analysis underscores the need for the academic community, policymakers and practitioners to work together to prevent the destructive economic and social consequences of fraud in an increasingly complex and interconnected environment.

This study differs from previous literature reviews that focus on a single monitoring mechanism or deal with fraud in a broadly manner by discussing how the accounting literature addresses the roles and the complex interplay between enforcers and auditors in the context of accounting fraud.

This study aims to explore how small and medium-sized accounting practices (SMPs) make sense of and position themselves against the changing demand for services. It is argued that changing demand for services from pure compliance to advisory acts as a trigger for sensemaking among SMP owners.

A qualitative multiple case study research approach is adopted, including semistructured interviews with key informants from seven Norwegian SMPs as well as document analysis.

The findings suggest that there is heterogeneity in the small practitioner segment of the accounting profession in making sense of changing demand for the nature of services. Three different situations emerged due to sensemaking, thus, the three distinct positions. Metaphors, namely, chameleons, turtles and bulls, are used to represent the positioning of SMPs. The sensemaking of actors as an adaptation led them to act as chameleons while distancing and resistance resulted in their positioning as turtles, and bulls, respectively.

Despite the richness of data indicating a clear variation in interpretation among actors, the study is case based, with a limited number of SMPs, and caution should be exercised when generalising its conclusions.

The centrality of people as a driving force for positioning among SMPs and diversity among SMPs in value creation provide insights for both SMPs and their customers.

This study highlights the meaning and patterns of value creation and the positioning of accounting firms according to their sensemaking within an under-studied segment of the accounting profession.

Prior studies have shown that heterogeneity plays a crucial role in addressing soft issues linked to a firm’s corporate social responsibility stance. The purpose of this paper is to extend the prior literature on the effect of gender heterogeneity on environmental, social and economic performance dimensions, specifically, whether the female boardroom presence weakens or strengthens the performance along the three dimensions, commonly referred to as the corporate sustainability.

The study from a positivist philosophy adopts a quantitative approach, and the final sample consisted of forty-six companies listed on the Nigerian Stock Exchange for the year 2011–2018. The final sample was a balanced panel of 344 firm years. The dependent variables were return on assets (ROA), environmental performance (ENV) and donations made for social causes (SOP). The ENV was measured using a content scoring system, with range of 1 to 5. The data were analysed using the fixed effects and GLM regression models. To further address the issue of endogeneity, a two-stage least squares regression was conducted.

The findings show a positive relationship between gender heterogeneity and ROA, which was also confirmed for the environmental performance index. However, the sign reversed in the SOP model and showed a negative relationship between gender heterogeneity and donations, the proxy for SOP. The results are in tandem with the stakeholder axioms that argue that commitment to other stakeholder groups strengthens firm performance in the long run.

An implication of this study is the fact that information availability has been rapidly escalating in the country, leading to rising social movements and civic unrest; therefore, corporations that face negative castigations may pay the huge price of product boycott and loss of market value.

The findings of this study provide additional insight into the influence of female boardroom presence on the environmental, social and economic performance of firms. The findings suggest the relevance of the resource dependence theory, especially from a developing country context, to ensure an improved corporate governance structure in Nigerian manufacturing firms.

The monetary valuation of cultural heritage of a selection of 16 major public, not-for-profit Australian cultural institutions is examined over a period of almost three decades (1992–2019) to understand how they have responded to the paradoxical tensions of heritage valuation for financial reporting purposes.

Accounting for cultural heritage is an intrinsically paradoxical practice; it involves a conflict of two opposite ways of attributing value: the traditional accounting and the heritage professionals (or curatorial) approaches. In analysing the annual reports and other documentary sources through qualitative content analysis, the study explores how different actors responded to the conceptual and technical contradictions posed by the monetary valuation of “heritage assets”, the accounting phraseology of accounting standards.

Four phases emerge from the analysis undertaken of the empirical material, each characterised by a distinctive nature of the paradox, the institutional responses discerned and the outcomes. Although a persisting heterogeneity in the practice of accounting for cultural heritage is evident, responses by cultural institutions are shown to have minimised, so far, the negative impacts of monetary valuation in terms of commercialisation of deaccessioning decisions and distorted accountability.

In applying the theoretical lens of paradox theory in the context of the financial reporting of heritage, as assets, the study enhances an understanding of the challenges and responses by major public cultural institutions in a country that has led this development globally, providing insights to accounting standard setters arising from the accounting practices observed.

Critics say cryptocurrencies are hard to predict and lack both economic value and accounting standards, while supporters argue they are revolutionary financial technology and a new asset class. This study aims to help accounting and financial modelers compare cryptocurrencies with other asset classes (such as gold, stocks and bond markets) and develop cryptocurrency forecast models.

Daily data from 12/31/2013 to 08/01/2020 (including the COVID-19 pandemic period) for the top six cryptocurrencies that constitute 80% of the market are used. Cryptocurrency price, return and volatility are forecasted using five traditional econometric techniques: pooled ordinary least squares (OLS) regression, fixed-effect model (FEM), random-effect model (REM), panel vector error correction model (VECM) and generalized autoregressive conditional heteroskedasticity (GARCH). Fama and French's five-factor analysis, a frequently used method to study stock returns, is conducted on cryptocurrency returns in a panel-data setting. Finally, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to a portfolio makes a difference.

The seven findings in this analysis are summarized as follows: (1) VECM produces the best out-of-sample price forecast of cryptocurrency prices; (2) cryptocurrencies are unlike cash for accounting purposes as they are very volatile: the standard deviations of daily returns are several times larger than those of the other financial assets; (3) cryptocurrencies are not a substitute for gold as a safe-haven asset; (4) the five most significant determinants of cryptocurrency daily returns are emerging markets stock index, S&P 500 stock index, return on gold, volatility of daily returns and the volatility index (VIX); (5) their return volatility is persistent and can be forecasted using the GARCH model; (6) in a portfolio setting, cryptocurrencies exhibit negative alpha, high beta, similar to small and growth stocks and (7) a cryptocurrency portfolio offers more portfolio choices for investors and resembles a levered portfolio.

One of the tasks of the financial econometrics profession is building pro forma models that meet accounting standards and satisfy auditors. This paper undertook such activity by deploying traditional financial econometric methods and applying them to an emerging cryptocurrency asset class.

This paper attempts to contribute to the existing academic literature in three ways: Pro forma models for price forecasting: five established traditional econometric techniques (as opposed to novel methods) are deployed to forecast prices; Cryptocurrency as a group: instead of analyzing one currency at a time and running the risk of missing out on cross-sectional effects (as done by most other researchers), the top-six cryptocurrencies constitute 80% of the market, are analyzed together as a group using panel-data methods; Cryptocurrencies as financial assets in a portfolio: To understand the linkages between cryptocurrencies and traditional portfolio characteristics, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to an investment portfolio makes a difference.

This paper reviews the current literature on theoretical and methodological issues in discrete choice experiments, which have been widely used in non-market value analysis, such as elicitation of residents' attitudes toward recreation or biodiversity conservation of forests.

We review the literature, and attribute the possible biases in choice experiments to theoretical and empirical aspects. Particularly, we introduce regret minimization as an alternative to random utility theory and sheds light on incentive compatibility, status quo, attributes non-attendance, cognitive load, experimental design, survey methods, estimation strategies and other issues.

The practitioners should pay attention to many issues when carrying out choice experiments in order to avoid possible biases. Many alternatives in theoretical foundations, experimental designs, estimation strategies and even explanations should be taken into account in practice in order to obtain robust results.

The paper summarizes the recent developments in methodological and empirical issues of choice experiments and points out the pitfalls and future directions both theoretically and empirically.

This paper theoretically and empirically analyzes the effects of the elderly’s physical health status on their need for care and the choice of care models in China.

Empirically, the estimation results of a large-sample randomized intervention trial with chronic obstructive pulmonary disease (COPD) patients through the difference-in-difference method indicated the following: (1) After the COPD intervention trial, the physical health status of the elderly in the treatment group improved significantly, the need for care was substantially reduced and the health improvement led to a 35.5% reduction in the probability of using elderly care. (2) The reduction in the need for care regarding the treatment group occurred mainly in social care. The probability of using social care decreased by 67.8% due to the elderly’s health improvement, while that of home care remained unchanged generally. (3) Further heterogeneity tests suggested that families with fewer potential internal resources for caregiving had a more pronounced decline in the need for social care.

Theoretically, these empirical results support the existence of the “pecking order” theory in the family’s choice of elderly care model, that is, families tend to employ all internal resources for caregiving before resorting to social care, resulting in a higher sensitivity of social care to health.

The main policy implication of this paper is that ex ante preventive health intervention policies can significantly alleviate the burden of care, especially social care, on families. And preventive health intervention policies are particularly effective in reducing the burden of the families with relatively few resources for informal internal care.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.