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This study aims to use gray models to predict abnormal stock returns.

Data are collected from listed companies in the Tehran Stock Exchange during 2005-2015. The analyses portray three models, namely, the gray model, the nonlinear gray Bernoulli model and the Nash nonlinear gray Bernoulli model.

Results show that the Nash nonlinear gray Bernoulli model can predict abnormal stock returns that are defined by conditions other than gray models which predict increases, and then after checking regression models, the Bernoulli regression model is defined, which gives higher accuracy and fewer errors than the other two models.

The stock market is one of the most important markets, which is influenced by several factors. Thus, accurate and reliable techniques are necessary to help investors and consumers find detailed and exact ways to predict the stock market.

This paper aims to explore the drivers behind the accuracy of self-reported home valuations in the Warsaw (Poland) housing market.

In order to achieve the research goal, firstly, unique data on subjective residential property values estimated by their owners were compared with market-justified ones. The latter was calculated using geographically weighted regression, which allowed for taking into account spatially heterogeneous buyers' housing preferences. An ordered logit model was then used to identify the factors influencing the probability of the occurrence of bias towards over or undervaluation.

The results of the study revealed that, on average, homeowners overvalued their properties by only 1.94%, and the fraction of interviewees estimating their properties accurately ranges from 20% to 68%, depending on the size of the margin of error adopted. The drivers of the valuation bias variation were the physical, locational and neighbourhood attributes of the property as well as the personal characteristics of the respondents, for which their age and employment situation played a key role.

In contrast to previous studies, this is the first to examine drivers behind the accuracy of self-reported home valuations in a Central and Eastern Europe country. In addition, this work is the first to consider heterogeneous housing preferences when calculating objective property values.

The present study seeks to shed further light on the effectiveness of Basu (1997) and Khan and Watts' (2009) differential timeliness metrics in detecting predictable differences in conservatism following corrections of restated earnings.

Using cross-sectional and time-series analyses for companies listed on the Tehran Stock Exchange during 2009–2013, the results indicate lower conservatism for restating firms as compared to their counterparts during prerestatement period.

Using cross-sectional and time-series analyses for companies listed on the Tehran Stock Exchange during 2009–2013, the results indicate lower conservatism for restating firms as compared to their counterparts during prerestatement period. In contrast, our findings are indicative of higher conservatism among these restating firms during the years of restatements. Moreover, the time-series approach captures a higher conservatism for the restating firms during restatement years than prerestatement periods. Overall, these results provide insight into the usefulness of the metrics used in the restatement setting.

Similar to recent papers, the present study seeks to shed further light on the ability of Basu-based coupled with Khan–Watts-based measures of conservatism to detect situations in which companies' earnings are known to be significantly restated.

This paper aims to find out if there is a relationship between access to climate change information and student activism.

Exploratory study focused on the survey of 400 [n = 400] students from 10 universities in Spain from April to May 2022. A questionnaire with 19 questions was divided into blocks of knowledge, awareness, and action and bivariate analysis with a margin of error of ±5% and a confidence level of 95%.

The greater the degree of information received, the greater the activism of university students, who tend to use digital media and social networks to get informed. However, they perceive that the university generates little information and a low number of activities related to climate change. Students demand that universities implement informal, formal, and service-learning environmental education strategies on sustainable consumption.

Given the results of previous studies showing the variable “type of degree” does not show differences at the beginning and end of studies, it has not been considered in this research. Nevertheless, it would be convenient to introduce it in future investigations to confirm if this may have an impact on informational habits.

This paper urges universities to act as sources of environmental education, given the relationship between the information received and the pro-environmental attitudes of students.

The universities are powerful social actors that can shape public and political discourses for eco-social transition.

This research adds the variable access to information in studies on pro-environmental attitudes. Furthermore, this research provides data about student perceptions of the university, government, industry, and NGO climate actions.

Experiments are the backbone of the development process of data-driven predictive models for scientific applications. The quality of the experiments directly impacts the model performance. Uncertainty inherently affects experiment measurements and is often missing in the available data sets due to its estimation cost. For similar reasons, experiments are very few compared to other data sources. Discarding experiments based on the missing uncertainty values would preclude the development of predictive models. Data profiling techniques are fundamental to assess data quality, but some data quality dimensions are challenging to evaluate without knowing the uncertainty. In this context, this paper aims to predict the missing uncertainty of the experiments.

This work presents a methodology to forecast the experiments’ missing uncertainty, given a data set and its ontological description. The approach is based on knowledge graph embeddings and leverages the task of link prediction over a knowledge graph representation of the experiments database. The validity of the methodology is first tested in multiple conditions using synthetic data and then applied to a large data set of experiments in the chemical kinetic domain as a case study.

The analysis results of different test case scenarios suggest that knowledge graph embedding can be used to predict the missing uncertainty of the experiments when there is a hidden relationship between the experiment metadata and the uncertainty values. The link prediction task is also resilient to random noise in the relationship. The knowledge graph embedding outperforms the baseline results if the uncertainty depends upon multiple metadata.

The employment of knowledge graph embedding to predict the missing experimental uncertainty is a novel alternative to the current and more costly techniques in the literature. Such contribution permits a better data quality profiling of scientific repositories and improves the development process of data-driven models based on scientific experiments.

The pandemic has enhanced the global phenomenon of disinformation. This paper aims to study the false news concerning COVID-19, spread through social media in Spain, by using the LatamChequea database for a duration from 01/22/2020, when the first false information has been detected, up to 03/09/2021.

A quantitative analysis has been conducted with regard to the correlation between fake news stories and the pandemic state, the motive to share them, their dissemination in other countries and the effectiveness of fact checking. This study is complemented by a qualitative method: a focus group conducted with representatives of different groups within the society.

Fake news has been primarily disseminated through several social networks at the same time, with two peaks taking place in over a half of the said false stories. The first took place from March to April of 2020 during complete lockdown, and we were informed of prevention measures, the country’s situation and the origin of the virus, whereas the second was related to news revolving around the coming vaccines, which occurred between October and November. The audience tends to neither cross-check the information received nor report fake news to competent authorities, and fact-checking methods fail to stop their spread. Further awareness and digital literacy campaigns are thus required in addition to more involvement from governments and technological platforms.

The main limitation of the research is the fact that it was only possible to conduct a focus group of five individuals who do not belong to generation Z due to the restrictions imposed by the pandemic, although a clear contribution to the analysis of the impact of fake news on social networks during the COVID-19 pandemic in Spain can be seen from the privileged experiences in each of the fields of work that were identified. In this sense, the results of the study are not generalizable to a larger population. On the other hand, and with a view to future research, it would be advisable to carry out a more specific study of how fake news affects generation Z.

This research is original in nature, and the findings of this study are valuable for business practitioners and scholars, brand marketers, social media platform owners, opinion leaders and policymakers.

As online course enrollments increase, it is important to understand how common course features influence students' behaviors and performance. Asynchronous online courses often include a discussion forum to promote community through interaction between students and instructors. Students interact both socially and cognitively; instructors' engagement often demonstrates social or teaching presence. Students' engagement in the discussions introduces both intrinsic and extraneous cognitive load. The purpose of this study is to validate an instrument for measuring cognitive load in asynchronous online discussions.

This study presents the validation of the NASA-TLX instrument for measuring cognitive load in asynchronous online discussions in an introductory physics course.

The instrument demonstrated reliability for a model with four subscales for all five discrete tasks. This study is foundational for future work that aims at testing the efficacy of interventions, and reducing extraneous cognitive load in asynchronous online discussions.

Nonresponse error due to the unincentivized, voluntary nature of the survey introduces a sample-related limitation.

This study provides a strong foundation for future research focused on testing the effects of interventions aimed at reducing extraneous cognitive load in asynchronous online discussions.

This is a novel application of the NASA-TLX instrument for measuring cognitive load in asynchronous online discussions.

The purpose of this paper is to develop a structural relationship model to study the relationship between causes and effects of poor communication and information exchange in construction projects using Smart-PLS.

The first method of this research is to identify the causes and effects factors of poor communication in construction projects from the extant of literature. The data used to develop the model was collected using a questionnaire survey, which targeted construction practitioners in the Malaysian construction industry. A five-point Likert type scale was used to rate the significance of the factors. The factors were classified under their relevant construct/group using exploratory factor analysis. A hypothetical model was developed and then transformed into Smart-PLS in which the hypothetical model suggested that each group of the cause factors has a direct impact on the effect groups. The hypothesis was tested using t-values and p-values. The model was assessed for its inner and outer components and achieved the threshold criterion. Further, the model was verified by engaging 14 construction experts to verify its applicability in the construction project setting.

The study developed a structural equation model to clarify the relationships between causes and effects of poor communication in construction projects. The model explained the degree of relationships among causes and effects of poor communication in construction projects.

The published academic and non-academic literature introduced many studies on the issue of communication including the definitions, importance, barriers to effective communication and means of poor communication. However, these studies ended up only on the general issue of communication lacking an in-depth investigation of the causes and effects of poor communication in the construction industry. The study implemented advanced structural modeling to study the causes and effects. The questionnaire, the data and concluding results fill the identified research gap of this study. The addressed issue is also of interest because communication is considered one of the main knowledge areas in construction management.

This paper aims to introduce a novel method for the analysis of open cell porous components fabricated by laser-based powder bed metal additive manufacturing (AM) for the purpose of quality control. This method uses photogrammetric analysis, the extraction of geometric information from an image through the use of algorithms. By applying this technique to porous AM components, a rapid, low-cost inspection of geometric properties such as material thickness and pore size is achieved. Such measurements take on greater importance, as the production of porous additive manufactured orthopaedic devices increases in number, causing other, slower and more expensive methods of analysis to become impractical.

Here the development of the photogrammetric method is discussed and compared to standard techniques including scanning electron microscopy, micro computed tomography scanning and the recently developed focus variation (FV) imaging. The system is also validated against test graticules and simple wire geometries of known size, prior to the more complex orthopaedic structures.

The photogrammetric method shows an ability to analyse the variability in build fidelity of AM porous structures for use in inspection purposes to compare component properties. While measured values for material thickness and pore size differed from those of other techniques, the new photogrammetric technique demonstrated a low deviation when repeating measurements, and was able to analyse components at a much faster rate and lower cost than the competing systems, with less requirement for specific expertise or training.

The advantages demonstrated by the image-based technique described indicate the system to be suitable for implementation as a means of in-line process control for quality and inspection applications, particularly for high-volume production where existing methods would be impractical.

Sexual harassment is a pervasive and damaging issue that affects the physical and mental health and well-being of employees in the workplace. It is a serious public health concern that requires urgent attention and action and very dangerous problem in management. Our studies have shown that women are more likely to be the victims of sexual harassment and are more dissatisfied with the situation, organizations have a moral and legal obligation to take proactive measures to prevent and address sexual harassment, including implementing effective policies, providing employee training and fostering a culture of respect and accountability. By doing so, we can create safer, healthier and more productive work environments for all the employees.

This study consisted of 344 individuals from the Syrian community who completed a questionnaire, that contained statements about harassment to gauge each gender’s perception and sensitivity toward it. The questionnaire was carefully designed to include 30 questions, including daily situations in the work environment that may occur and how they are classified by males and females. Is it harassment or not, and about the HR department have personal safety and security standards such as the code of conduct and the rules regulating these behaviors or not and our research project was a collaboration between the two nongovernmental organizations (NGOs): Stemosis and Institute of Human Resources Management (IHRM).

Our research reveals a distinction between the thinking patterns and coping mechanisms of females and males when it comes to dealing with this phenomenon. We presented various scenarios to our respondents, depicting situations that an individual might face in their everyday life and asked them questions related to the definition of harassment, its root causes and strategies for addressing it. Research has shown that women are at a higher risk of experiencing feelings of fear and dissatisfaction when subjected to sexual harassment. This unfortunate reality highlights the need for greater awareness and action to combat such reprehensible behaviors. Save Women!

The study faced several limitations in collecting data due to the sensitive and shameful nature of the topic for both men and women in the Syrian Arab Republic. This caused embarrassment for some participants, leading to their unwillingness to participate in the research. Additionally, the study encountered difficulties in dealing with companies, as they did not accept exposure to such situations and failed to show any codes of conduct under the name of their company, and the participants did not consider certain factors as reasons for harassment. Specifically, 71.2% of participants did not consider inappropriate outfits as a reason for harassment. However, there was a significant difference between the opinions of men and women on this matter (p-value < 0.05). Additionally, political, social and psychological reactions were not considered a reason for harassment by 64.8% of participants.

In our study, there was a situation that one of the respondents (male) was exposed to by the HR manager (female) who was pretending to be a professional, after he confronted her, she threatened him with expulsion from work and despite his annoyance, he ignored her because it was pointless to talk with her and during the study, (44.7%) of the participants had experienced sexual harassment.

Victims of sexual harassment experience a similar condition to post-traumatic stress disorder, which can lead to many mental and psychological issues. The overall organizational environment plays a critical role in the well-being of employees. It is widely accepted that victims of violence suffer from a lack of well-being. Employee well-being is based on feelings of happiness and satisfaction that come from a sense of security. According to the Maslow’s theory of needs, security is fundamental to people and a toxic workplace environment can destroy an individual’s sense of security, negatively impacting their well-being In Syria.

In Syria, society is considered closed about sexual issues and considers it a sensitive issue despite its presence and spread in work environments, as the results showed, and this is one of the challenges we face. Therefore, our study is the first in Syria and the largest that sheds light on this phenomenon clearly, strongly, deeply and directly.