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This paper empirically demonstrates the major organizational events of a rolling forecasting process and the roles of controllers therein. In particular, this study aims to investigate how the understanding of a “realistic forecast” is translated and questioned by various mediators in the rolling forecasting process and how it affects the quality of planning as the ultimate accuracy of forecasts is seen as important.

This study follows an actor-network theory (ANT) approach and maps the key points of translation in the rolling forecasting process by inspecting the roles of mediators. This qualitative case study is based on interviews with controllers and managers involved in the forecasting process in a single manufacturing company.

The paper identified two episodes of translation in the forecasting process, in which the forecast partially stabilized to create room for managerial discussion and debate. The abilities of controllers to infiltrate various functional groups and calculative practices appeared to be one way to control the accuracy of forecasting, although this was built on a façade of neutrality.

Prior literature identifies the aims of interactive planning processes as being to improve the quality of planning. The authors apply ANT to better understand the nature of mediators in constructing an entity called a “realistic rolling forecast”.

This paper aims to examine the dynamism of causal relationships among cloud computing (CC) adoption factors in the Indian context, considering the perspectives of both the cloud adopter and cloud provider.

The case-study method has been used to understand the dynamics among the factors. Using data from specific cases in India, causal loop diagrams (CLDs) have been developed. System dynamic modeling (SDM) and simulation are used to study the relationships and their effect on the adoption rate.

The results revealed that adoption of CC depends on various factors such as persuasion (time-saving, cost-saving and word of mouth) and constraint factors (security and financial loss). However, it is seen that the adoption rate is very sensitive to changes in adoption per contact and word of mouth. Further, the adopter firm has a quicker time to market, which gives an added advantage to the firm. Also, with CC services, a firm can fulfill its projects or clients' requirements with little to no upfront investment in information technology (IT) services.

Lack of security, standardization and undefined service-level agreements are a few pressing issues that make it difficult for firms to evaluate the performance and reliability of services. Hence, immediate attention is needed to make transparent policies on CC and its services, thereby building trust.

This is the first and only work that has tried to explore and empirically test the dynamics of critical factors while making an adoption decision, considering both the adopter and provider perspectives. This study shows the journey of a firm, starting from being a prospective adopter to an adopter and continuous user. The work also empirically tested how adopters of technology benefit from the technology.

This paper examines the impact of International Financial Reporting Standards (IFRS) 9 on earnings management (EM) using data from 2011 to 2019 of 100 commercial banks in Europe.

Using data from 2011 to 2019 of 100 commercial banks in Europe, the authors conducted several empirical investigations to test the mediating role of IFRS 9 on earnings manipulation through loan loss provision (LLP) by banks.

The result shows that the new accounting standards (IFRS 9) significantly affect the way banks report LLP. This paper provides evidence that non-listed banks in the EU engage in EM through LLP following IFRS 9 but experience less volatility of net income following the adoption. The findings indicate that such behaviour by banks cannot be suppressed by level of audit quality; suggesting that an improvement in accounting standards might not always guarantee accounting quality.

This finding has some policy implications; and regulators will need to identify additional tools to regulate or supervise EM behaviour.

The purpose of this study is to examine how US farm sector performed in 2020, the first year of the pandemic. There were significant supply and demand shocks due to the pandemic. Furthermore, there was significant fluctuation in commodity prices and record high government payments in 2020. This study aims to examine the performance and position of US farm sector (financially) to system (and global economy) wide shocks.

The authors examine 2020 values for farm sector financial ratios before and after the onset of the Coronavirus (COVID-19) pandemic using the data from the United States Department of Agriculture to understand the financial position and performance of the US farm sector.

The authors find solvency ratios (which are indicators of the sector's ability to repay financial liabilities via the sale of assets) worsened in 2020 relative to pre-pandemic expectations. Efficiency ratios (which evaluate the conversion of assets into production and revenue) and liquidity ratios (which are indicators of the availability of cash to cover debt payments) showed mixed outcomes for the realized results in 2020 relative to the pre-pandemic forecasts. Four profitability ratios were stronger in 2020 relative to pre-pandemic expectations. All solvency, liquidity and profitability ratios plus 2 out of 5 efficiency ratios for 2020 were weaker than their respective average ratios obtained from 2000 to 2019 data.

This research is one of the first papers to use financial ratios to examine how the US farm sector performed in 2020 compared to expectations prior to the pandemic.

Research questions: Is there a systemic relationship between different methods of screening candidates for predictive maintenance? How do the goals of a predictive project influence the choice of a dropout method? How do the company’s characteristics implementing the predictive project influence the selection of the dropout method?

The authors described and compiled a taxonomy of currently known methods of screening candidate aircraft components for predictive maintenance for maintenance, repairs and overhaul organizations; identified the boundaries of each way; analyzed the advantages and disadvantages of existing methods; and formulated directions for further development of methods of screening for maintenance, repairs and overhaul organizations.

The authors identified the relationship between various screening methods by developing the approach proposed by Tiddens WW and supplementing it with economic methods. The authors built them into a single hierarchical structure and linked them with the parameters of the predictive project. The principal advantage of the proposed taxonomy is a clear relationship between the structure of the screening methods and the goals of the predictive project and the characteristics of the company that implements the project.

The authors of the article proposed groups of screening methods for predictive maintenance based on economic indicators to improve the effectiveness and efficiency of the screening process.

Using a sample of 9,898 firm-year observations from 1,821 unique Chinese listed firms over the period from 2004 to 2019, this study aims to investigate whether the market rewards meeting or beating analyst earnings expectations (MBE).

The authors use an event study methodology to capture market reactions to MBE.

The authors document a stock return premium for beating analyst forecasts by a wide margin. However, there is no stock return premium for firms that meet or just beat analyst forecasts, suggesting that the market is skeptical of earnings management by these firms. This market underreaction is more pronounced for firms with weak external monitoring. Further analysis shows that meeting or just beating analyst forecasts is indicative of superior future financial performance. The authors do not find firms using earnings management to meet or just beat analyst forecasts.

The authors provide evidence of market underreaction to meeting or just beating analyst forecasts, with the market's over-skepticism of earnings management being a plausible mechanism for this phenomenon.

The findings of this study are informative to researchers, market participants and regulators concerned about the impact of analysts and earnings management and interested in detecting and constraining managers' earnings management.

The authors provide new insights into how the market reacts to MBE by showing that the market appears to focus on using meeting or just beating analyst forecasts as an indicator of earnings management, while it does not detect managed MBE. Meeting or just beating analyst forecasts is commonly used as a proxy for earnings management in the literature. However, the findings suggest that it is a noisy proxy for earnings management.

The purpose of this study is to examine how lenders alter their behavior when faced with real earnings management.

This study uses the incremental R-square approach as in Kim and Kross (2005) to examine how much lenders rely on income statement and balance sheet ratios as the degree of real earnings management increases.

As real earnings management affects mostly the income statement, the authors find that lenders rely less on income statement ratios in making credit decisions in the presence of real earnings management. The authors also find that lenders do not alter their reliance on balance sheet ratios when faced with real earnings management.

This paper is the first to study how lenders alter their reliance on financial statements in making credit decisions in the presence of real earnings management. The findings of this paper could help the regulators set standards to improve the usefulness of financial statements. The findings of this paper could also help practitioners (borrowers and lenders) understand how real earnings management affects credit decisions.

Using various proxies for the firms' return on equity (ROE) and retention ratios (b) the authors calculate 36 sustainable growth rates, on a rolling basis, for a comprehensive set of firms over a 52-year period. The authors then assess the ability of these different sustainable growth rates to predict the actual, out-of-sample, five-year growth rates of the firms' earnings.

The authors compare the forecast to determine which method of estimating ROE and b produce the lowest mean-squared-errors and then determine the estimation method that works best for firms with different characteristics and for firms in different industries.

Overall, using the median ROE of all firms in the market and the 5-year average of the specific firm's retention ratio produces the lowest, statistically significant, forecast errors. Variations are documented based on firm characteristics, including dividend payout, level of ROE and industry.

The findings can guide practitioners in using the best earnings forecasting method.

Financial textbooks seem universally to suggest that one method of estimating the growth rate of a firm's earnings is to calculate the “sustainable growth rate” by multiplying the firm's ROE by the firm's b. At the same time, multiple methods of proxying for both ROE and b have been suggested; therefore, it is an interesting and useful empirical question, which, heretofore, has not been addressed in the literature, as to which estimation of the sustainable growth rate best approximates the actual future growth of the firm's earnings. The findings can guide practitioners in using the best earnings forecasting method.

Numerous policies are established in Mauritius to attract foreign direct investment, but at the same time, severe concerns were raised concerning the erosion of Mauritian tax base, which is witnessed by the decrease in the percentage of tax revenue to gross domestic product in recent years. To avoid these issues, in 2019, the Mauritian legislator has domesticated the Organisation for Economic Co-operation and Development (OECD) BEPS 2013 Action 3 on controlled foreign company (CFC) in its income tax legislation. As such, the purpose of this study is to critically assess the implications of CFC rules of Mauritius to reduce tax avoidance in the light of international tax competition.

To achieve the research objective, this study will adopt a black letter approach by analysing the rules and regulations of various jurisdiction as well as international standards on CFCs and other tax avoidance legal provisions. A comparative analysis will be conducted between Mauritian laws on CFCs and the corresponding legislation of the UK and the USA, which are selected to assess the developed world’s position on strict CFC rules.

A hasty implementation of CFC rules leads to various complexities like interpretation issues and diminishing the competitiveness of the country to multinationals. In this respect, there is the risk of a trade-off between tax collected and foreign direct investment in the country. Consequently, the research recommends that Mauritius reforms its CFC legislation by extending the scope of tax exemptions for intra-group financing income, for the first year of CFC’s operation with the possibility of offsetting foreign taxes and for the Mauritius Revenue Authority to establish detailed guidelines on the determination of CFC income and its attribution for tax purposes in Mauritius.

Existing literature has to a great extent focused on the role of CFC rules as a tax avoidance measure and on the divergence or convergence between domestic CFC legislation against the OECD recommendations (Dourado, 2015; Xu, 2018; Beebeejaun et al., 2023). However, limited literature is available on the evaluation of the purpose of CFC rules enacted by a developing country being Mauritius in the context of the global competitive market, to which this research aims at filling the gap.

The study aims to investigates which form of classification shifting is preferred by firms to avoid the violation of debt covenants and whether the higher-audit quality constraints the shifting practices of firms incentivized to avoid covenant violations or not.

A sample of 1,644 Bombay Stock Exchange (BSE)-listed firms during the period 2009–2021 has been used in this study and tested through panel data regression models. Two forms of classification shifting, namely expense shifting and revenue shifting have been taken into account. The findings are validated through the propensity-score matching technique.

The findings deduced from the empirical evidence demonstrate that firms prefer revenue shifting over expense shifting to avoid covenant violations, consistent with the notion of the ease-need-advantage-based shifting framework, where firms are found to prefer a shifting tool with greater relative advantage. Further, the author finds that superior audit quality has a constraining effect on expense shifting, but not on revenue shifting, indicating the partial effectiveness of high-quality auditors in curbing the corporate misfeasance of classification shifting. These results are robust to the problem of endogeneity and self-selection bias.

The paper provides new evidence on debt market incentives behind classification shifting, where firms are found to substitute classification shifting forms to avoid covenant violations. Further, the study is among pioneering attempts to investigate the impact of audit quality on revenue shifting and document the non-constraining effect.