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This paper aims to examine the association between perceived firm risk and two reporting mechanisms: risk disclosure and earnings smoothing in the UK context.

This study juxtaposes three competing views, the “null”, the “divergence” and the “convergence” hypotheses, and empirically investigates whether risk disclosure and earnings smoothing affect firm perceived risk for a sample of large UK firms with rich and poor information environments. This study also uses the global financial crisis as an external shock on overall risk in the economy to investigate when and how managers use these two reporting mechanisms to shape the firm perceived risk.

This paper documents that risk disclosures have no significant effect on investors’ risk perceptions, consistent with risk disclosures containing boilerplate and generic statements about firm risk. This paper also finds that earnings smoothing reduces investors’ risk perceptions, reflecting investors’ interpretations about future firm performance. Additional tests reveal that earnings smoothing is not associated with perceived firm risk for firms with rich information environments and expanded risk disclosures. Furthermore, reporting smooth earnings decreases perceived firm risk following the global financial crisis. These findings are robust to alternative specifications and measures of earnings smoothing as well as post-filing perceived firm risk.

This study does not distinguish between the garbling role and the informational role of earnings smoothing. The risk disclosure measurement used in this study, developed based on UK annual reports, may limit the generalizability of findings to other countries.

The findings suggest that managers should revise their risk disclosure strategies to provide in-depth details on firm risk. Investors might require information and thorough assessment to evaluate investment risks when firms provide generic risk disclosures and smoothed earnings by consulting sources like financial intermediaries. Regulators should keep an eye on firms reporting boilerplate risk disclosures and on how smoothing earnings impacts the firm perceived risk following economic turmoil, to guide interventions that promote market stability.

The findings provide new insights into when and how managers use their financial reporting discretion to make firms appear less risky and, therefore, influence investors’ risk perceptions.

The objective of this study is to investigate how the implementation of an Emission Trading Scheme (ETS) influences an ETS-regulated firm’s level of earnings smoothness.

Using a staggered difference-in-differences model based on China’s ETS pilots commencing in 2013, this study investigates how the implementation of ETS pilots affects regulated firms’ earnings smoothing relative to non-regulated firms. The sample period spans from 2008 to 2019. This model incorporates time-invariant firm-specific heterogeneity, time-specific heterogeneity, and a series of firm characteristics to establish causality. Robustness tests justify findings.

The results show that after implementing an ETS pilot, regulated firms increase their earnings smoothness relative to non-regulated firms. Regulated firms strategically smooth their earnings to obtain additional financial resources and meet compliance costs arising from an ETS. Further analysis reveals that regulated firms’ earnings smoothing activity is a function of environmental regulations, managerial integrity, and capital market incentives.

This study deviates from past research focusing on the environmental consequences of ETS by indicating that an ETS affects regulated firms’ financial reporting decisions. Specifically, regulated firms resort to earnings smoothing as a short-term exit strategy from financing concerns arising from environmental regulations. This finding expands prior literature primarily focusing on the effect of tax and financial reporting regulations on earnings smoothness. This study also indicates that firms utilize earning smoothing to lower their short-term cost of capital, which enables them to access additional financing at a lower cost and reconfigure their operations to meet stakeholder environmental demands.

This paper aims to present a new trajectory scheduling method to generate a smooth and continuous trajectory for a hybrid machining robot.

The trajectory scheduling method includes two steps. First, a G3 continuity local smoothing approach is proposed to smooth the toolpath. Then, considering the tool/joint motion and geometric error constraints, a jerk-continuous feedrate scheduling method is proposed to generate the trajectory.

The simulations and experiments are conducted on the hybrid robot TriMule-800. The simulation results demonstrate that this method is effectively applicable to machining trajectory scheduling for various parts and is computationally friendly. Moreover, it improves the robot machining speed and ensures smooth operation under constraints. The results of the S-shaped part machining experiment show that the resulting surface profile error is below 0.12 mm specified in the ISO standard, confirming that the proposed method can ensure the machining accuracy of the hybrid robot.

This paper implements an analytical local toolpath smoothing approach to address the non-high-order continuity problem of the toolpath expressed in G code. Meanwhile, the feedrate scheduling method addresses the segmented paths after local smoothing, achieving smooth and continuous trajectory generation to balance machining accuracy and machining efficiency.

This paper examines the determinants of bank income smoothing using loan loss provisions in the United Kingdom or Great Britain from 1999 to 2017.

The study used ordinary least square (OLS) regression and applying the HAC robust standard error correction test.

The findings showed that UK banks use loan loss provision for income smoothing purposes. Income smoothing is greater in times of high economic policy uncertainty. The extent of bank income smoothing is reduced by foreign bank presence, UK GAAP adoption, IFRS9 adoption, and high levels of voice and accountability. Also, there is reduced income smoothing using loan loss provisions during a financial crisis and in periods of economic prosperity.

The implication is that economic conditions, institutional governance and accounting disclosure rules can influence the extent of bank income smoothing in the United Kingdom. The findings of the study contribute to several studies that explore the determinants of bank income smoothing.

No study has extensively examined the determinants of bank income smoothing in Great Britain or the United Kingdom. The present study fills this gap in the literature.

This study empirically tests the use of loan loss provisions (LLPs) for earnings and capital smoothing when emphasis is laid on banks' riskiness and adoption of the International Financial Reporting Standards (IFRSs) in Nigeria.

Annual bank-level data are hand-extracted between 2007 and 2017 from annual reports of a sample 16 deposit money banks (DMBs), and analysed using appropriate panel regression models subsequent to a number of diagnostic tests including heteroscedasticity, autocorrelation and cross-sectional dependence. The use of both reported LLPs (TLLP) and discretionary LLPs (DLLP) for earnings and capital management is tested to advance the practice in the literature.

Generally, the study finds that Nigerian DMBs manage capital via LLPs, while mixed results are obtained for earnings smoothing. However, during IFRS, Nigerian DMBs' management of capital is identifiable with TLLP, while smoothing of earnings is peculiar to DLLP. Additionally, evidence of the improvement in loan loss reporting quality expected during IFRS for riskier Nigerian DMBs, could not be attained. This is corroborated by the study's findings of the use of both TLLP and DLLP for earnings and capital management during IFRS by DMBs in solvency crisis against the only use of TLLP to manage capital found for the entire period.

The evidential capital and earnings lopsidedness may subject Nigerian DMBs' going-concern to a lot of questions.

The study sets a foremost record in the empirical test of managerial opportunistic behaviour embedded in earnings and capital concurrently while accounting for loan losses by all categories of Nigerian DMBs in terms of riskiness, following accounting regime change.

House price fluctuations send vital signals to many parts of the economy, and long-term predictions of house prices are of great interest to governments and property developers. Although predictive models based on economic fundamentals are widely used, the common requirement for such studies is that underlying data are stationary. This paper aims to demonstrate the usefulness of alternative filtering methods for forecasting house prices.

We specifically focus on exponential smoothing with trend adjustment and multiplicative decomposition using median house prices for Sydney from Q3 1994 to Q1 2017. The model performance is evaluated using out-of-sample forecasting techniques and a robustness check against secondary data sources.

Multiplicative decomposition outperforms exponential smoothing at forecasting accuracy. The superior decomposition model suggests that seasonal and cyclical components provide important additional information for predicting house prices. The forecasts for 2017–2028 suggest that prices will slowly increase, going past 2016 levels by 2020 in the apartment market and by 2022/2023 in the detached housing market.

We demonstrate that filtering models are simple (univariate models that only require historical house prices), easy to implement (with no condition of stationarity) and widely used in financial trading, sports betting and other fields where producing accurate forecasts is more important than explaining the drivers of change. The paper puts forward a case for the inclusion of filtering models within the forecasting toolkit as a useful reference point for comparing forecasts from alternative models.

To the best of the authors’ knowledge, this paper undertakes the first systematic comparison of two filtering models for the Sydney housing market.

With the development of technology, the application scenarios of mobile robots are becoming more and more extensive, accompanied by a variety of application scenarios suitable and safe path planning algorithms are indispensable for mobile robots.

The purpose of this paper to improve the safety performance of your bot during the execution of tasks. The methods are synthesized in three main areas: setting appropriate safety distances based on the actual radius of the robot, turn penalty reduces the number of turns by applying an additional penalty to the number of turns in a heuristic function and path smoothing is used to improve path reliability by reducing the number of right-angle turns.

A suitable safety distance greatly improves the safety of mobile robots and facilitates their development. Optimization of turns in the path of mobile robots improves the travel efficiency of robots. Enhancing the safety of mobile robots has become a research hotspot for path-planning algorithms.

This paper proposes a path planning scheme for mobile robots with safe distances, which provides readers with a comprehensive and systematic progress of path planning research. It helps readers to get inspiration from enhancing the safety of mobile robots.

This paper studies the association between earnings opacity and corporate social responsibility disclosures of firms listed on the Vietnamese Stock Exchange.

We utilize a dataset comprising a sample of all listed Vietnamese firms for the period of 2014–2022. Data regarding corporate social responsibility information are gathered manually. Following Dechow et al. (1995), Kothari et al. (2005) and Bhattacharya et al. (2003), earnings opacity is measured by using three proxies, including abnormal accruals, earnings smoothing and loss avoidance. Our hypothesis was tested via ordinary least squares (OLS) regressions. To address endogeneity problems, we use the two-stage instrumental variable method (IV-2SLS) as well as the generalized method of moments (GMM) to ensure the robustness of our results.

We find that earnings opacity is positively related to corporate social responsibility disclosures. Cross-sectional analyses indicate that managers of firms disguise their opportunistic behaviour by disclosing more information about corporate social responsibility. The evidence also shows that firms experience long-run underperformance when having higher earnings opacity and greater sustainability disclosures. Our results remain robust even after correcting for endogeneity using the IV approach and the GMM method.

Evidence from this study can serve as a warning signal to the investment community, highlighting that some methods aimed at enhancing a firm’s corporate social responsibility disclosures might be used to obstruct other unethical activities. Moreover, the results of this study can help regulators gain a better comprehension of firms' reporting patterns concerning corporate social responsibility initiatives. It should not only reform the corporate social responsibility regulation but also impose stronger litigation for firms to enhance the quality of corporate social responsibility disclosures.

We are the first to present evidence regarding the relationship between earnings opacity and corporate social responsibility disclosure in Vietnam.

The performance of a bladeless Tesla turbine is closely tied to momentum diffusion, kinetic energy transfer and wall shear stress generation on its rotating disks. The surface roughness adds complexity of flow analysis in such a domain. This paper aims to assess the effect of roughness on flow structures and the application of roughness models in flow cross sections with submillimeter height, including both stationary and rotating walls.

This research starts with the examination of flow over a rough flat plate, and then proceeds to study flow within minichannels, evaluating the effect of roughness on flow characteristics. An in-house test stand validates the numerical solutions of minichannel. Finally, flow through the minichannel with corotating walls was analyzed. The k-ω SST turbulent model and Aupoix's roughness method are used for numerical simulations.

The findings emphasize the necessity of considering the constricted dimensions of the flow cross section, thereby improving the alignment of derived results with theoretical estimations. Moreover, this study explores the effects of roughness on flow characteristics within the minichannel with stationary and rotating walls, offering valuable insights into this intricate phenomenon, and depicts the appropriate performance of chosen roughness model in studied cases.

The originality of this investigation is the assessment and validation of flow characteristics inside minichannel with stationary and corotating walls when the roughness is implemented. This phenomenon, along with the effect of roughness on the transportation of kinetic energy to the rough surface of a minichannel in an in-house test setup, is assessed.

This study aims to thoroughly examine the milling process applied to fused filament fabrication (FFF) parts. The primary objective is to identify the key variables in creating smooth surfaces on FFF specimens and establish trends about specific parameters.

In this study, PLA and ABS samples fabricated by FFF are subjected to side milling in several experiments. Achievable surface quality is studied in relation to material properties, milling parameters, tooling and macrostructure. The surface finish is quantified using profile measurements of the processed surfaces. The study classifies the created chips into categories that can be used as criteria for the anticipated quality. Spectral analysis is used to examine the various surface formation modes. Thermal monitoring is used to track chip formation and surface temperature changes during the milling process.

This study reveals that effective heat dissipation through proper chip formation is vital for maintaining high surface quality. Recommended methodology demands using a tool with a substantial flute volume, using high positive rake and clearance angles and optimizing the feed-per-tooth and cutting speed. Disregarding these guidelines may cause the surface temperature to surpass the material’s glass transition, resulting in inferior quality characterized by viscous folding. For FFF thermoplastics, optimal milling can bring the average surface roughness down to the micron level.

This research contributes to the field by providing valuable guidance for achieving superior results in milling FFF parts. This study includes a concise summary of the theoretically relevant insights, presents verification of the key factors by qualitative analysis and offers optimal milling parameters for 3D-printed thermoplastics based on systematic experiments.