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Family firms, client importance, and auditor reporting behavior: evidence from China
No full textPurpose: This study aims to investigate whether auditors compromise their independence for economically important clients in family business settings. Design/methodology/approach: The authors empirically examine the research question based on China for the years 2011 to 2020. The dependent variable is the auditors’ propensity to issue modified audit opinions, which is a proxy for auditor independence. The authors use relative client audit fees as a proxy for client importance. To address endogeneity issues in the selection of family firms, the authors use the two-stage least squares regression model and, subsequently, the propensity score matching and Hausman firm fixed effect modeling. Findings: This study reveals that the propensity to issue modified audit opinions is positively correlated with client importance. Big-N auditors are more likely to issue modified audit opinions for their economically important family firm clients, whereas such evidence is not found for non-Big-N auditors. Results are consistent and robust to endogeneity test and sensitivity analysis. Originality/value: This study enriches the literature on auditor independence and the effect of family firms’ ownership structure factors on audit reporting behavior for their economically important clients. Findings may prove useful for managers and practitioners interested in family business
The Performance and Error Analysis of LSTM Model Combined with Various GARCH Models in Stock Forecasting
No full textVolatility is a measure of the asset return rate\u27s estimated level of uncertainty and may be used to assess the riskiness of financial assets. We use the market capitalization of 200 stocks representing Korea as the primary analytical aim and evaluate the accuracy between them by analyzing the impacts of different hybrid models\u27 hybrid neural networks, which are based on the returns of the KOSPI 200 stock index. By measuring the effectiveness of these models using four dissimilarity measures, we contrasted the performance of hybrid models that combine a single neural network and a single GARCH type model with that of hybrid neural networks that combine multiple GARCH models (MAE, MSE, HMAE, and HMSE). They are applied to anticipate the KOSPI 200 index data\u27s actual volatility. Among these, hybrid neural networks that integrate more than one GARCH-type model have much better forecasting performance than neural network models that mix two or more or more GARCH-type models. GW-LSTM makes the least accurate forecast. We note that the hybrid model combining the three GARCH models shows a minor increase in predicting ability based on merging two and three models
Clough’s Theorem
No full textSummary: We offer a visual proof of Clough’s theorem on the semiperimeter of an equilateral triangle
Fear During Pandemic Promoted Holistic Cognitive Style: The Moderating Role of Uncertainty
No full textThe present study explored the link between fear and holistic cognitive style and the moderating role of uncertainty. We examined these effects in a real-life situation: the long-term, global COVID-19 pandemic, which provided a natural context of fear and uncertainty. The current study comprises three studies recruiting N = 1,310 participants. Study 1 compared the link between fear and holistic style in the United States (a relatively uncertain situation presented by the COVID-19 pandemic) and China (a pandemic situation with relative certainty) in the early days of the pandemic. Study 2 examined the moderation effect of uncertainty in the relationship between fear and holistic style by manipulating participants into a fearful (vs. control) condition. Study 3 employed a longitudinal design to demonstrate the effect of fear-related emotions on holistic style change over a 3-month period. Across three studies, the moderation effect of uncertainty in the relationship between fear-related emotions and holistic style during the COVID-19 pandemic was consistently observed. In sum, this study provided an ecological and explanatory mechanism for understanding the impact of individuals’ fear on holistic cognitive styl
Testing Computational Assessment of Idea Novelty in Crowdsourcing
No full textIn crowdsourcing ideation websites, companies can easily collect large amount of ideas. Screening through such volume of ideas is very costly and challenging, necessitating automatic approaches. It would be particularly useful to automatically evaluate idea novelty since companies commonly seek novel ideas. Four computational approaches were tested, based on Latent Semantic Analysis (LSA), Latent Dirichlet Allocation (LDA), term frequency–inverse document frequency (TF-IDF), and Global Vectors for Word Representation (GloVe), respectively. These approaches were used on three set of ideas and the computed idea novelty scores, along with crowd evaluation, were compared with human expert evaluation. The computational methods do not differ significantly with regard to correlation coefficients with expert ratings, even though TF-IDF-based measure achieved a correlation above 0.40 in two out of the three tasks. Crowd evaluation outperforms all the computational methods. Overall, our results show that the tested computational approaches do not match human judgment well enough to replace it
Pre-K and Kindergarten Teacher Perception of School Readiness During the COVID-19 Pandemic
No full textIn 2020, the COVID-19 pandemic caused a mandatory shift from in-person instruction to online learning for many young children. Teachers needed to adjust to virtual teaching, children were isolated from their peers, and parents played a bigger role in learning during the pandemic. In 2021, the shift back to in-person learning occurred. Research has already shown the negative influence COVID-19 had on students’ mental health; however, limited research has examined the impact of the pandemic on school readiness. In this study, using the Head Start domains of school readiness, 154 Kindergarten and Pre-K teachers compared current student school readiness to the readiness of their students prior to the pandemic. Results showed that nearly 80% of teachers felt that overall student functioning was Worse or Much Worse than before the pandemic; no teachers reported functioning was overall much better. Teachers most frequently identified the Ready to Learn and Social-Emotional Development domains as the areas of greatest struggle for their students; Physical Development was the least frequently reported. Chi-square tests were used to examine the association between teacher demographics and overall school readiness and domain of greatest struggle; no significant relationships were found. Future directions and limitations of these results are discussed
Undergraduate capstone projects in information technology course: bridging the gap between theory and practical skills
No full textThis study was conducted in the School of Computing at a public university in Malaysia to identify the current issues in the existing undergraduate capstone project and to identify ways to improve the existing capstone project framework to make it more effective. Data was collected through in-depth, semi-structured interviews of faculty members and students who had recently completed the capstone project and focus group discussions. The findings reveal issues that could be categorised into: 1) lack of orientation; 2) role ambiguity between the supervisor and the lecturer; 3) misalignment between technical skills, project requirement, and support; 4) students’ prior educational background. Formal orientation, clear role allotment for lecturers and supervisors, more projects for each major subject, project-based experiences during courses, and inculcation of soft skills among students were some of the suggestions identified through data. The implications for various stakeholders and the limitations of the study have been discussed
The control of tax corruption: evidence from nonfungible token market in China
No full textPurpose: In 2021, nonfungible token (NFT) has emerged and grown as a new digital asset and became a carrier for cryptocurrency holders in China. NFT opens the door of the digital world for creators’ rights and the realization of economic interests. However, potential problems such as money laundering, terrorist financing and tax avoidance risks have increased in China due to the lack of regulations. As tax control is an important tool used by the government to adjust the economy and market, this study aims to investigate the future market capitalization of NFT and provide value orientations to control the NFT market in China with a tax control approach based on the positive experience of other countries. Design/methodology/approach: In this study, least squares and expert estimation are applied to predict the future market capitalization based on the global market, which can provide an understanding of the current NFT market and the significance of its tax control. In addition, the tax control and interpretation of Chinese taxation institutions and structures are also explored. Findings: Results include the probable tax structure or policy that national institutions can carry out over different transactions. Conclusions show that introducing tax control to regulate and monitor the rise of state revenue and decline of illegal financing activities. Establishing tax control in the Chinese NFT market can provide a centralized guarantee to ensure the safety and legality of transactions and enable further progress. Originality/value: This study puts forward new ideas on the future development of nonprofitable tokens based on blockchain technology from the perspective of taxation in China
Computing Basis and Dimension of Chloroquine and Hydroxychloroquine by Using Chemical Graph Theory
No full textDiscovering a vaccine with reliable and effective treatment for the new corona virus disease 2019 (COVID-19) is indeed a long way off, and there seems to be a critical need to research additional viable medications that could save countless lives in the event of the COVID-19 pandemic. Scientists from all over the world are actively developing medical or anti-virus medications, which are safe and effective for COVID-19. The anti-viral drugs of chloroquine (CQ) and hydroxychloroquine (HCQ) have proved to be an efficient inhibitory effect by preventing the binding of spike covid protein. The determination of a pharmaceutical structure using a topological index allows researchers to have a better understanding of the physiological as well as bio-organic properties of drugs. The goal of this study is to employ molecular graph theory to determine some graph-theoretic parameters related to the molecular graph of CQ and HCQ. In this paper, we present some resolvability parameters such as metric dimension (MD), edge metric dimension (EMD), fault-tolerant metric dimension (FTMD), and fault-tolerant edge metric dimension (FTEMD) of CQ and HCQ. We prove that these resolvability parameters for CQ and HCQ are bounded and constant
Social capital and regional innovation: evidence from private firms in the US
No full textIn this study we investigate whether and to what extent social capital may affect regional innovation by focusing on private firms in the United States. We document that regional social capital is positively associated with the quantity, quality and novelty of county-level innovation by private firms. In addition, we find that the positive relation between social capital and regional innovation is more prominent in counties with a lower supply of financial capital. We also report that social capital is complementary to investments in research and development to produce inventive outcomes in local areas. Using a spatial Durbin model, we provide evidence that regional social capital has significant spillover effects in boosting the innovation activities of neighbouring counties