Real Manipulation Research Articles

Combination impact of managerial ability and power on real earnings management practices: Evidence from Indonesia

The purpose of this study is to examine the combination impact of managerial ability and power on real earnings management. First test between CEO ability to real earnings management. Second between CEO power to real earnings management and third impact of combination independent variables. Deploying three real earnings management indicators, the ability of managers tends to significantly influence the operating cash flow and corporate discretionary expenditure and so the combination of both. Analysis on 468 observations of Indonesian manufacturing firm utilized fixed-effect approach. The finding of this study are first CEO ability less likely to engage with real earnings management as expected while lesser CEO power has no significant relation with real earnings management and combination of managerial ability and power has more impact on real earnings management. This research has extended the analysis of CEO attribute on real manipulation activities in firm practice. The practical consequence of the research, it is more likely to considering the cash flow and discretionary expenditure rather than managing inventory through decreasing production costs.

Impact of Real Manipulation and Tax Compliance on Strategy Model: A Simulative Prediction of The Future Certainty

High awareness of obedience and compliance is a fundamental requirement in monitoring going concerned, reflecting a critical role of meaningful accounting information. This research tested earnings quality to measure belief and faith in achieving a sustainable business as optimism and confidence in the better one. The collecting data concerned the listed manufacturing company during 2010-2021, where purposive sampling and moderated regression with dummy variables were to capture the strategy topologies. The causal research observed amounted to 214 companies, illustrating that the number of valid observations has been 1.278 samples. The finding depicts the mapping of the investor reaction to quality accounting information related to this rational decision model in predicting the high future certainty as a positive signal. Bayes Teorema and Decision Tree Model are used to distinguish the prospective company as a highly guaranteed information; the social responsibility of the regulator is to minimize the distortion by implementing the going-private procedure for the low-prospected one; pragmatically, one platform of financial reporting service is to deduct a minimum chance for opportunity accruals. As a new insight into the literature in accounting, this simplex-linear programming has been modified into an innovative portfolio as an artificial intelligence model to maximize each utility.

Training Scene Construction and Motion Realization of Unmanned Craft based on Unreal Engine

Aiming at the problems of the traditional training system, such as the unrealistic simulation of 3D animation effects and the inability to meet the demand of real-time manipulation response of simulation training based on the original mechanical calculation, this paper puts forward a method of unmanned craft training scene construction and motion realization based on Unreal Engine. The method makes full use of Unreal Engine's powerful graphic rendering ability and physics engine function, and combines 3D MAX to realize the rapid construction of unmanned craft training scene, environment simulation, and unmanned craft motion simulation and control. The developed unmanned craft training software has the characteristics of smooth and clear picture, realistic and delicate scene, strong training immersion, and real manipulation experience, which can effectively improve the training efficiency and training safety, reduce the training cost, and have significant economic benefits.

Ensemble of supervised and unsupervised deep neural networks for stock price manipulation detection

Illegal practices that cause stock prices to vary from their fair values are known as stock price manipulations. Our prior study used unsupervised deep learning to detect these unlawful activities, in which the autoencoder model could catch five out of six cases in the Stock Exchange of Thailand (SET). Trading actions of good governance equities in a limit order book format were used to train the model, and abnormalities were viewed as manipulation. This unsupervised technique has the strength of discovering never-before-seen patterns, although it has a low recall rate. In this work, the findings were improved by incorporating knowledge about the popular pump-and-dump pattern into another supervised deep learning model, which has a strength in catching known patterns. To combine the advantages of both models, an ensemble of supervised and unsupervised deep neural networks was proposed. The main contribution of this paper is to demonstrate that the new ensemble model achieved a higher detection rate than the unsupervised model alone. The supervised learning model used was a long short-term memory (LSTM) network, the unsupervised learning model used was an LSTM-based autoencoder, and the stack classifier in the ensemble model was a support vector machine (SVM). The proposed method was evaluated on six real manipulation cases from the SET. The empirical results showed that our ensemble model could improve the detection strength, achieved high accuracy on pump-and-dump unseen data, and could identify six out of six real manipulation cases with low false alarm rates.

An alternative approach to detect earnings management to meet or beat benchmarks

PurposeThe authors propose an alternative robust technique to test for discontinuities in distributions and provide consistent evidence of discontinuities around zero for both scaled and unscaled earnings levels and changes. The advantage of the proposed test is that it does not rely on arbitrary choice of bin width choices.Design/methodology/approachTo evaluate the power of the test, the authors examine the density function of non-discretionary earnings and detect no evidence of discontinuities around zero in levels and changes of these non-discretionary earnings. As robustness, the authors use pre-managed earnings excluding accrual and real manipulation and find similar evidence.FindingsThe finding using our technique support the Burgstahler and Dichev (1997) interpretation on earnings management, even for smaller sample sizes and reject the theory that discontinuities arise from scaling and sampling methods.Originality/valueThe study provides an overview of those studies that support and those that oppose using “testing for discontinuities” as a way to examine earnings management. The authors advance the literature by providing an alternative methodology supporting the view that the kink in the distribution represents earnings management.

The role of hope and attitude in luxury counterfeit purchase intention

Purpose – This study aims to investigate the emotion hope for social status and attitude toward counterfeit goods as predictors of consumers’ intention to purchase counterfeit products.. Design/methodology/approach – We conduct an experiment with 45 undergraduates (51% female) from different universities, which design was a 2 (hope for social status; hopeful vs non-hope) x 2 (attitude towards counterfeit goods; positive vs negative) full factorial, between-subjects. Findings – Results confirmed that people felt hopeful after manipulation; however, future steps of this investigation should consider the use of another instrument of manipulation even more effective. However, respondents also pointed out they felt happiness, which makes us believe that it is important to use an instrument of manipulation even more effectively to guarantee the achievement of the real manipulation, without the interference from extraneous variables. Theoretical/methodological contributions – Although originated in categories such as apparel and luxury accessories, counterfeiting now affects a wide range of industries, representing a major economic threat. This great amount of counterfeit trade worldwide is shocking, and leads us to argue: what are the factors that influence the intention to purchase these products, especially regarding the consumption of luxury counterfeit brands? We believe that emotion may represent an important role in people’s intention to purchase counterfeit goods. Besides, the attitude towards counterfeit goods may also imply variations of intention to purchase, playing a moderator role. The inclusion of emotion in consumer behavior studies presents a significant opportunity to develop theory and practice in this area of study. Originality/value – The explanations of whether emotions may represent antecedents of the purchasing of counterfeits are quite limited, and the understanding of the motivations behind the purchase of such products remains undefined in the marketing literature. Analysis of the study shows that hope and attitude can simultaneously offer opportunities for consumer behavior research.

Detecting earnings management: a comparison of accrual and real earnings manipulation models

PurposeThe use of models for detecting earnings management in the academic literature, using accrual and real manipulation, is commonplace. The purpose of the current study is to compare the power of these models in a United Kingdom (UK) sample of 19,424 firm-year observations during the period 1991–2018. The authors include artificially-induced manipulation of revenues and expenses between zero and ten percent of total assets to random samples of 500 firm-year observations within the full sample. The authors use two alternative samples, one with no reversal of manipulation (sample 1) and one with reversal in the following year (sample 2).Design/methodology/approachThe authors include artificially induced manipulation of revenues and expenses between zero and ten percent of total assets to random samples of 500 firm-year observations within the full sample.FindingsThe authors find that real earnings manipulation models have lower power than accrual earnings manipulation models, when manipulating discretionary expenses and revenues. Furthermore, the real earnings manipulation model to detect overproduction has high misspecification, resulting in artificially inflating the power of the model. The authors examine an alternative model to detect discretionary expense manipulation that generates higher power than the Roychowdhury (2006) model. Modified real manipulation models (Srivastava, 2019) are used as robustness and the authors find these to be more misspecified in some cases but less in others. The authors extend the analysis to a setting in which earnings management is known to occur, i.e. around benchmark-beating and find consistent evidence of accrual and some forms of real manipulation in this sample using all models examined.Research limitations/implicationsThis study contributes to the literature by providing evidence of misspecification of currently used models to detect real accounts manipulation.Practical implicationsBased on the findings, the authors recommend caution in interpreting any findings when using these models in future research.Originality/valueThe findings address the earnings management literature, guided by the agency theory.

Keypoint-Based Planar Bimanual Shaping of Deformable Linear Objects Under Environmental Constraints With Hierarchical Action Framework

This letter addresses the problem of contact-based manipulation of deformable linear objects (DLOs) towards desired shapes with a dual-arm robotic system. To alleviate the burden of high-dimensional continuous state-action spaces, we model DLOs as kinematic multibody systems via our proposed keypoint encoding network. This novel encoding is trained on a synthetic labeled image dataset without requiring any manual annotations and can be directly transferred to real manipulation scenarios.Our goal-conditioned policy efficiently rearranges the configuration of the DLO based on the keypoints. The proposed hierarchical action framework tackles the manipulation problem in a coarse-to-fine manner (with high-level task planning and low-level motion control) by leveraging two action primitives. The identification of deformation properties is bypassed since the algorithm replans its motion after each bimanual execution. The conducted experimental results reveal that our method achieves high performance in state representation and shaping manipulation of the DLO under environmental constraints.

Evolucija prakse upravljanja dobitkom - nova pretnja kvalitetu finansijskih izveštaja

Profit management mechanisms can be realized by applying accounting techniques or by undertaking real transactions. In the first case, opportunistic behavior is directed towards the calculation components of accounting results, while manipulations of real transactions have repercussions on cash flows. Based on a qualitative analysis of relevant international and domestic literature related to the problem of profit management, the paper presents the consequences, limitations and risks associated with different profit management techniques. In many researches conducted in developed economies, the evolution of profit management practices from accounting manipulations to manipulations through real transactions has been confirmed. As methodological instruments for assessing real manipulations are still scarce, the aim of the paper is to draw the public's attention to the practice of profit management through real transactions because it is a more perfidious form that significantly reduces the risk of detection. In addition, the paper contributes to the definition of a new area of research towards which the academic accounting community should direct its efforts in the future.

The Impact of Real Manipulation and Tax Management on Future Market Value: An Artificial Intelligence Simulation of High Earnings Quality

Providing empirical proof of the negative impact of manipulation activity pushed management to adhere to the available regulation by publishing high financial reporting quality. This one has a significant effect negatively on a volatile market price movement because of illustrates the actual earnings. It is not an obstacle for the investor in predicting the future return with high accuracy when there is a minimum chance for the opportunity behavior. This causal research has developed a new variable to measure the investor's perception, and it is the future market value as a proxy for future return. The observation data used the samples on the listed company in the industrial manufacturing sector from 2015 until 2020, which amounted to 384 observations. The management's effort to deduct the manipulation activity can be interpreted as the minimum level of misleading information. When the investor has no tolerance for manipulation activity, the management should be "prudent" in designing the accounting treatment policy to illustrate real earnings. It is a sign of high probability in reaching out to the better prospect, proving the interactive feedback between management and investor through the Decision Tree Model and Bayes Theorem. This research has adopted the maximum simplex models as an Artificial Intelligence simulation for maximizing each party's maximum utility as implication game theory, like investors and management in making their strategic decisions. Principally, the regulator should force management to level up the quality of financial reporting because of no tolerance for any infringement on the legal regulations.

Realization of Swing Manipulation by 3-DOF Robot Arm for Unknown String via Parameter Estimation and Motion Generation

Dynamically manipulating flexible objects using robots is difficult. Some studies have been conducted that only considered one type of object with known properties or that needed an identification test for string properties in advance. We propose a method to realize the dynamic manipulation of a string with unknown characteristics. We use a mass-spring-damper model for the string and repeat three steps: motion generation, real manipulation, and parameter estimation. The proposed method estimates the string properties to realize the motion objective via the real manipulation of the string. An identification test in advance was not necessary. In this study, we focus on swing manipulation. This can increase the motion energy of a string without a high-power actuator. After making a large swing, the robot can throw strings to a more distant target, such as a hammer throw. This motion is useful for explanation robots, rescue robots, and so on. We modified the proposed method to generate a swing manipulation. Then, we investigate whether swing manipulation can be performed by the proposed method and demonstrate its effectiveness via experiments with various strings with unknown characteristics.

Disección animal y digitalización, alternativa para la enseñanza de anatomía cuando la disección de cadáveres no es posible

IntroductionCadaveric dissections are common training strategies to teach anatomy, which require an infrastructure that is not always available in all educational centers. Information and communication technologies (ICT) offer alternatives though they do limit student‘s real manipulation. The present study analyzes a training strategy, based on the dissection of animal viscerae and the digitalization of images in the subject of human anatomy. Material and methodsA quasi-experimental design, where the impact of the strategy is verified in a sample of 211 first-year nursing students, selected through an intentional non-probabilistic sampling. ResultsAcademic results were superior after the workshop compared to just the masterclass (4.31 vs. 5.70; P<0.0001). Satisfaction was higher in all aspects evaluated (organization, perception of knowledge acquired, type of activity and university teaching staff). ConclusionThe use of ICT coupled with the dissection of anatomical parts of animal origin is a strategy with a positive academic impact and has proven to be largely successful, and can therefore be considered as an alternative to cadaveric dissections.

Data Augmented Deep Behavioral Cloning for Urban Traffic Control Operations Under a Parallel Learning Framework

It is indispensable for professional traffic signal engineers to perform manual operations of traffic signal control (TSC) to mitigate traffic congestion, especially with complicated scenarios. However, such a task is time-consuming, and the level of congestion mitigation heavily relies on individual expertise in engineering practice. Therefore, it is cost-effective to learn traffic engineers’ knowledge to enhance the problem-solving skills for a large-scale urban traffic network. In this paper, a data augmented deep behavioral cloning (DADBC) method is proposed to imitate the problem-solving skills of traffic engineers. The method is under a conceptual framework, parallel learning (PL) framework, that incorporates machine learning techniques for solving decision-making problems in complex systems. The DADBC method enhances a hybrid demonstration by exploiting a generative adversarial network (GAN) and then uses the deep behavioral cloning (DBC) model to learn traffic engineers’ control schemes. According to the validation results using the real manipulation data from Hangzhou, China, our method can imitate complex human behaviors in intervening traffic signal control operations to improve traffic efficiency in urban areas.

Is there any interaction between real earnings management and accrual-based earnings management?

This research aims to investigate whether firms employ real earnings management (REM) and accrual-based earnings management (AEM) as substitutes for each other when managing earnings to meet earnings benchmarks. It specifically looks at the sequential nature of both forms of earnings management. REM is proxied by an abnormal amount of operating cash developed by Dechow et al. (1998), while AEM is proxied by the discretionary accrual model by Dechow, Sloan, &amp; Sweeney (1995). The data was obtained from the Economics and Business Data Center, Faculty of Economics and Business, Gadjah Mada University, focusing on manufacturing and mining companies during the period from 2005 to 2013, which resulted in 754 firm-years data. Using correlation tests and an empirical model developed by this research, which captures the interaction between REM and AEM, this research shows that firms use both forms of earnings management sequentially; managers more often engage in accrual-based earnings management if the earnings produced by real manipulations do not meet the earnings target. This finding is important as REM and AEM occur sequentially instead of simultaneously, and earnings performance is not only driven by accrual-based earnings management but also by real earnings management.

Stock Price Manipulation Detection Using Deep Unsupervised Learning: The Case of Thailand

Detecting stock price manipulation is a cat-and-mouse game. Manipulators have constantly devised new techniques to avoid detection. The majority of the related work employed supervised learning techniques, which necessitated known manipulation patterns as examples for their models to recognize. To catch unknown and never-before-seen manipulation, we used unsupervised learning to train deep neural networks for detecting stock price manipulation in order to detect unknown and previously unseen manipulation. The models were trained to recognize normal trading behaviors that were expressed in a limit order book. Anomaly trading actions that did not follow to the learned patterns were identified as manipulated. The strength of our method is that it does not require prior knowledge about the characteristics of manipulation. As a result, it is best suited for detecting new or unknown types of manipulation. Two model architectures were evaluated: autoencoder (AE) and generative adversarial networks (GANs). They were put to the test on six prosecuted real manipulation cases from the Stock Exchange of Thailand (SET). With a low false-positive rate, both models could identify five out of six cases. For practical application of the models, a strategy called “MinManiMax” was also proposed to optimize the decision boundary.

Leverage, Corporate Governance and Real Earnings Managem ent: Evidence from Korean Market

Purpose: This study examines how corporate governance (CG) and leverage simultaneously influence real earnings management (REM). Methodology: We employed CG score (CGS), total, short-term, and long-term debt ratios as independent variables, and REM metrics as dependent variables. We include ordinary least-squares (OLS) panel data regressions, residual test, and interaction analysis in our study. Findings: While a significant positive relationship existed between leverage and REM, CG had a negative effect on real manipulations. Our results from the interaction analysis and residual test show that CG is a key player in explaining the relationship between leverage and REM. We also find that firms with a low-level of CG were more likely to conduct REM activities than those with a high-level CG. Research limitations/implications: These results imply that the reduction in opportunistic behavior of managers in the presence of strong CG could decrease the leverage of firms and REM activities and improve the quality of their earnings. Moreover, shareholder rights and audit organizations were the prominent CG characteristics influencing REM activities, as they enforce additional monitoring of financial reporting quality and increase audit standards. CG strategies mitigate the corporate corruption scandals through the adoption of high-quality accounting and financial norms in reporting and management. Thus, executives decrease their incentives to conduct REM activities and leverage cannot be used freely as a mechanism to manipulate earnings, given firms’ leverage position is audited and reviewed by the financial committee in firms with strong CG. For future research, the authors suggest including the degree of leverage as a disaggregation sample and adding the degree of cost stickiness. Originality/value: Several s tudies have investigated e ither the relationship between ( 1) REM and leverage, or ( 2) REM and CG, including leverage as a control variable. Our study, extends this bilateral relationship to simultaneous relationship between leverage, CG, and REM. Moreover, we investigate the predominant CG characteristics that influence the association among leverage and REM. We conduct interaction analysis and residual effect to investigate if CG should be considered as a determinant variable in the recurrence of REM activities of managers. We include firms with high- and low- levels of CG to show which firms are leveraged.

Dynamic manipulation of unknown string by robot arm: realizing momentary string shapes

We propose a method to realize the dynamic manipulation of a string with unknown characteristics via a high-speed robot arm. We use a mass-spring-damper model for the string and repeat three steps: motion generation, real manipulation, and parameter estimation. Robot motion is given by the joint angular velocities expressed by the Bezier curves. Their control points are randomly positioned to generate various robot motion for dynamic string manipulation. The generated motion is performed by a wire-driven robot arm and, real string movement is captured by the camera. These time-series images are used for the parameter estimation of string. The best parameter set is determined via comparison between real and simulated string movement after changing parameter randomly and logarithmically. This parameter set is not unique, but it simulates the actual string movement well. Since the estimated string parameter is used for the robot motion generation after repeating the above 3 steps, the motion generation reflects string property and motion objective can success without special tests in advance. This is an advantage of our method because it is difficult to know all of string property with very complicated non-linearity beforehand. We focus on realizing the momentary string shape in 2 dimensions in this paper. We confirmed the effectiveness of our proposed method by realizing five momentary shapes and 3 kinds of string properties. We also discussed the reproducibility and compatibility of estimated parameters and motion generation.

Is there any association between real earnings management and crash risk of stock price during uncertainty? An evidence from family-owned firms in an emerging economy

This research work intends to analyze the association between real earnings manipulation and stock price crash. Further, we also analyze the spillover outcome of the crash as a result of applying real earnings management. It is hypothesized that there is a positive and statistically significant association between real activities manipulation and crash risk. It is also assumed that this spillover outcome is more noticeable during uncertainty. By applying data of family firms for the time period 2005–2018, empirical results provide the proof that real manipulation has a significant impact on stock crash for a developing economy like Pakistan among family-based companies. This research work also gives a statistical insight that spillover outcome is more notable for firms facing uncertainty. Our statistical estimations are in support of the assumed hypotheses of the study. This study has very significant and practical implications for academic researchers, standard setters, and investors.

The effect of earnings manipulation based on real activities to the performance of Indonesian SOEs

The aim of this research is to examine the effect of real earnings manipulation (REM) on the performance of state-owned enterprises (SOEs) in Indonesia. This research was conducted at a state-owned company listed on the Indonesia Stock Exchange (IDX) in 2013-2017. Data obtained from financial reports and annual reports issued by IDX and the Web of each SOEs. Data also comes from the Indonesian Capital Market Directory. The research variables consist of a dependent variable, which is financial performance, and an independent variable that is REM. Financial performance is proxy by net profit margin (NPM) and returns on equity (ROE). Earnings manipulation is proxy by Roychowdhury's model. The type of ownership is used as a control variable of this research. Generally, the least square regression model is used to test the relationship between earnings manipulation and SOEs performance. This research shows that earnings manipulation based on real activities through production costs negatively affects the performance of Indonesian SOEs, government ownership negatively effects on NPM whereas public ownership has a positive effect on performance, as measured by ROE. Improper government policies can reduce the performance and significant disadvantages of SOEs.

Principles of Three-Dimensional Computer Design for Understanding Impossible Figures

For a better understanding of the impossible figures, it is advisable to use modern technological means by which the design of the geometry of the models gives a complete understanding of how they are made. Computer-aided 3D design completely solves this problem. That is, on the one hand, the ultimate visual variant of impossible figures is created, on the other hand, there is the possibility for real manipulation, movement, rotation and other models of space. In this study, 3D models of impossible figures are fully constructed, which are applied in the educational process in order to develop logical thinking. The steps of creating 3D geometry using open source software Blender 3D are described in details.