Search results for: empirical measure

Authors: Helena Baffoe

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Context: In the United States, there have been significant advancements in programs aimed at improving the lives of individuals with mental health disorders and substance abuse problems. However, public attitudes and beliefs regarding these issues have not improved correspondingly. This study aims to explore the perceptions and beliefs surrounding mental health disorders and substance abuse in the context of data analytics in the field of social work. Research Aim: The aim of this research is to provide empirical evidence on the beliefs and perceptions regarding mental health disorders and substance abuse. Specifically, the study seeks to answer the question of whether being diagnosed with a mental disorder implies a diagnosis of substance abuse. Additionally, the research aims to analyze the specific roles that social workers can play in addressing individuals with mental disorders. Methodology: This research adopts a data-driven methodology, acquiring comprehensive data from the Substance Abuse and Mental Health Services Administration (SAMHSA). A noteworthy causal connection between mental disorders and substance abuse exists, a relationship that current literature tends to overlook critically. To address this gap, we applied logistic regression with an Instrumental Variable approach, effectively mitigating potential endogeneity issues in the analysis in order to ensure robust and unbiased results. This methodology allows for a rigorous examination of the relationship between mental disorders and substance abuse. Empirical Findings: The analysis of the data reveals that depressive, anxiety, and trauma/stressor mental disorders are the most common in the United States. However, the study does not find statistically significant evidence to support the notion that being diagnosed with these mental disorders necessarily implies a diagnosis of substance abuse. This suggests that there is a misconception among the public regarding the relationship between mental health disorders and substance abuse. Theoretical Importance: The research contributes to the existing body of literature by providing empirical evidence to challenge prevailing beliefs and perceptions regarding mental health disorders and substance abuse. By using a novel methodological approach and analyzing new US data, the study sheds light on the cultural and social factors that influence these attitudes.

Keywords: mental health disorder, substance abuse, empirical evidence, logistic regression with IV

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Authors: Shumaila Zeb

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The proposed study aims to investigate insolvency risk of commercial banks of Pakistan. Furthermore, it empirically estimates the effect of already implemented financial regulations on the insolvency risk of banks. To carry out the empirical analysis, a balanced bank-level panel data covering the period 2008-2016 is used. The Z-score is used for calculating the insolvency risk of each bank. The panel regression is used to investigate the relationship between financial regulations and insolvency risk of banks. The empirics reveal that the financial regulations enforced by State Bank of Pakistan have significant impacts on the insolvency risk of banks. The results further indicate that loan ratio and reserve ratio are positively and significantly related to the insolvency risk of banks.

Keywords: insolvency risk, Z-score, financial regulations, banks

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Authors: Wlodzimierz Ogryczak, Michal Przyluski, Tomasz Sliwinski

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In problems of portfolio selection, the reward-risk ratio criterion is optimized to search for a risky portfolio with the maximum increase of the mean return in proportion to the risk measure increase when compared to the risk-free investments. In the classical model, following Markowitz, the risk is measured by the variance thus representing the Sharpe ratio optimization and leading to the quadratic optimization problems. Several Linear Programming (LP) computable risk measures have been introduced and applied in portfolio optimization. In particular, the Mean Absolute Deviation (MAD) measure has been widely recognized. The reward-risk ratio optimization with the MAD measure can be transformed into the LP formulation with the number of constraints proportional to the number of scenarios and the number of variables proportional to the total of the number of scenarios and the number of instruments. This may lead to the LP models with huge number of variables and constraints in the case of real-life financial decisions based on several thousands scenarios, thus decreasing their computational efficiency and making them hardly solvable by general LP tools. We show that the computational efficiency can be then dramatically improved by an alternative model based on the inverse risk-reward ratio minimization and by taking advantages of the LP duality. In the introduced LP model the number of structural constraints is proportional to the number of instruments thus not affecting seriously the simplex method efficiency by the number of scenarios and therefore guaranteeing easy solvability. Moreover, we show that under natural restriction on the target value the MAD risk-reward ratio optimization is consistent with the second order stochastic dominance rules.

Keywords: portfolio optimization, reward-risk ratio, mean absolute deviation, linear programming

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Authors: Arkadiusz Gut, Joanna Afek

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The first issue that we discuss in this paper is a battery of research demonstrating that culture influences children’s performance in tasks testing their theory of mind, also known as mindreading. We devote special attention to research done within Chinese culture; namely, studies with children speaking Cantonese and Mandarin natively and growing up in an environment dominated by the Chinese model of informal home education. Our attention focuses on the differences in development and functioning of social abilities and competences between children from China and the West. Another matter we turn to is the description of the nature of Chinese early childhood education. We suggest that the differences between the Chinese model and that of the West reveal a set of modifiers responsible for the variation observed in empirical research on children’s theory of mind (mindreading). The modifiers we identify are the following: (1) early socialization – that is, the transformation of the child into a member of the family and society that set special value by the social and physical environment; (2) the Confucian model of education – that is, the Chinese alphabet and tradition that determine a certain way of education in China; (3) the authoritarian style of upbringing – that is, reinforcing conformism, discouraging voicing of private opinions, and respect for elders; (4) the modesty of children and protectiveness of parents – that is, obedience as a desired characteristic in the child, overprotectiveness of parents, especially mothers; and (5) gender differences – that is, different educational styles for girls and boys. In our study, we conduct a thorough meta-analysis of empirical data on the development of mindreading and ToM (children’s theory of mind), as well as a cultural analysis of early childhood education in China. We support our analyses with questionnaire and narrative studies conducted in China that use the ‘Children’s Social Understanding Scale’ questionnaire, conversations based on the so-called ‘Scenarios Presented to Parents’, and questions designed to measure the ‘my child and I’ relation. With our research we aim to identify the factors in early childhood education that serve as moderators explaining the nature of the development and functioning of social cognition based on mind reading in China. Additionally, our study provides a valuable insight for comparative research of social cognition between China and the West.

Keywords: early childhood education, China, mindreading, parenting

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Authors: Francesco Paolone

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This paper investigates the role of Operating Cash Flow (OCF) and accruals in firm valuation analyzing financial statement information from the largest European companies and evaluating their relation to firm market value. Using a dataset of 500 largest European companies in 2018, the study investigates the relative value-relevance of equity, net income and operating cash flow (OCF). Findings show that the cash flow measure has the same explanatory power and intensity as equity and earnings to explain the market value. This study contributes to the debate on the value relevance of OCF incremental to book value and earnings. It also extends the literature, showing that OCF has information content (value relevance) superior to earnings and book value in the main European markets (Bepari et al., 2013). Finally, the study provides a support that accounting method choice may confuse investors, who have reduced confidence in accounting earnings and book value; in other words, nowadays European investors rely more on cash flows instead of accruals numbers.

Keywords: Cash Flow Statement, Value Relevance, Accounting, Financial Statement Analysis

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Authors: Hsiao-Wen Hsu

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It is generally believed that the teacher’s use of motivational strategies can enhance student motivation, especially in a place like Taiwan where teacher usually dominates student EFL learning. However, only little empirical studies support this claim. This study examined the connection between teachers’ use of motivational teaching practice and observed student motivated behavior in rural junior high schools in Taiwan. The use of motivational strategies by 12 teachers in five recognized rural junior high schools was investigated observed using a classroom observation instrument, the Motivation Orientation of Language Teaching. Meanwhile, post-lesson teacher evaluations accomplished by both the researcher and the teacher were functioning as part of the measure of teacher motivational practice. The data collected through observation scheme follows the real-time coding principle to examine observable teacher motivational practice and learner motivated behaviors. The results support the previous research findings that teachers’ use of motivational strategies is associated with the student motivated behaviors as well as the students’ level of motivation regarding English learning.

Keywords: English learning, motivational strategies, student motivation, teacher motivational practices

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Authors: Wen-Shai Hung

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This paper examines the factors influencing euthanasia issues in Taiwan. The data used is from the 2015 Survey Research on Attitudes towards the Death Penalty and Related Values in Taiwan, which focused on knowledge, attitudes towards the death penalty, and the concepts of social, political, and law values. The sample ages are from 21 to 94. The method used is probit modelling for examining the influences on euthanasia issues in Taiwan. The main empirical results find that older people, persons with higher educational attainment, those who favour abolition of the death penalty and do not oppose divorce, abortion, same-sex relationships, and putting down homeless’ cats or dogs are more likely to approve of the use of euthanasia to end their lives. In contrast, Mainlanders, people who support the death penalty and favour long-term prison sentences are less likely to support the use of euthanasia.

Keywords: euthanasia, homosexual, death penalty, and probit model

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Authors: Nihal Kartaltepe Behram, Göksel Ataman, Dila Okçu

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With the development of foreign direct investments, the social, cultural, political and economic interactions between countries and institutions have become visible and they have become determining factors for the strategic structuring and market goals. In this context the purpose of this study is to investigate the effects of cultural distance and institutions on foreign direct investment choices in terms of location and investment model. For international establishments, the concept of culture, as well as the concept of cultural distance, is taken specifically into consideration, especially in the selection of methods for entering the market. In the researches and empirical studies conducted, a direct relationship between cultural distance and foreign direct investments is set and institutions and effective variable factors are examined at the level of defining the investment types. When the detailed calculation strategies and empirical researches and studies are taken into consideration, the most common methods for determining the direct investment model, considering the cultural distances, are full-ownership enterprises and joint ventures. Also, when all of the factors affecting the investments are taken into consideration, it was seen that the effect of institutions such as Government Intervention, Intellectual Property Rights, Corruption and Contract Enforcements is very important. Furthermore agglomeration is more intense and effective on the investment, compared to other factors. China has been selected as the target country, due to its effectiveness in world economy and its contributions to developing countries, which has commercial relationships with. Qualitative research methods are used for this study conducted, to measure the effects of determinative variable factors in the hypotheses of study, on the direct foreign investors and to evaluate the findings. In this study in-depth interview is used as a data collection method and the data analysis is made through descriptive analysis. Foreign Direct Investments are so reactive to institutions and cultural distance is identified by all interviews and analysis. On the other hand, agglomeration is the most strong determiner factor on foreign direct investors in Chinese Market. The reason of this factors, which comprise the sectorial aggregate, are not the strongest factors as agglomeration that the most important finding. We expect that this study became a beneficial guideline for developed and developing countries and local and national institutions’ strategic plans.

Keywords: China, cultural distance, Foreign Direct Investments, institutions

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Authors: Muhammad Shafiq

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In accelerated life testing approaches life time data is obtained under various conditions which are considered more severe than usual condition. Classical techniques are based on obtained precise measurements, and used to model variation among the observations. In fact, there are two types of uncertainty in data: variation among the observations and the fuzziness. Analysis techniques, which do not consider fuzziness and are only based on precise life time observations, lead to pseudo results. This study was aimed to examine the behavior of empirical acceleration functions using fuzzy lifetimes data. The results showed an increased fuzziness in the transformed life times as compare to the input data.

Keywords: acceleration function, accelerated life testing, fuzzy number, non-precise data

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Authors: S. Brahmi, S. Aitouche, M. D. Mouss

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Every modern company should measure the value of its intellectual capital and to report to complement the traditional annual balance sheets. The purpose of this work is to measure the intellectual capital in an Algerian company (or production system) using the Weightless Wealth Tool Kit (WWTK). The results of the measurement of intellectual capital are supplemented by traditional financial ratios. The measurement was applied to the National Company of Wells Services (ENSP) in Hassi Messaoud city, in the south of Algeria. We calculated the intellectual capital (intangible resources) of the ENSP to help the organization to better capitalize on its potential of workers and their know-how. The intangible value of the ENSP is evaluated at 16,936,173,345 DA in 2015.

Keywords: financial valuation, intangible capital, intellectual capital, intellectual capital measurement

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Authors: Syed Hassan Amjad

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In today’s competitive environment, in order for a company to exist, it must continually improve its Performance by reducing cost, improving quality and productivity, and easy access to market.The purpose of this thesis is to check the firm financial growth and performance and which type of factors affect the firm financial performance. This paper examines the key determinants of firm financial performance. We will differentiate between financial and non financial drivers of the firm financial performance. For the measurement of the firm financial performance there are many ways but all the measure had been taken in aggregation, such as debt, tax rate, operating expenses, earning per share and economic conditions. This study has also been done in developed countries but these researches show that foreign companies face many difficulties inimproving the firm financial performance. In findings we found that marketing expenditures and international diversification had a positive impact on firm valuation. In research also found that a firm's ownership composition, particularly the level of equity ownership by Domestic Financial Institutions and Dispersed Public Shareholders, and the leverage of the firm, tax rate and economic conditions were important factors affecting its financial performance.

Keywords: debt, tax rate, firm financial performance, operating expenses, dividend per share, economic conditions

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Authors: I GD Yudha Partama, A. Kanno, Y. Akamatsu, R. Inui, M. Goto, M. Sekine

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The aerial photogrammetry of shallow water bottoms has the potential to be an efficient high-resolution survey technique for shallow water topography, thanks to the advent of convenient UAV and automatic image processing techniques Structure-from-Motion (SfM) and Multi-View Stereo (MVS)). However, it suffers from the systematic overestimation of the bottom elevation, due to the light refraction at the air-water interface. In this study, we present an empirical method to correct for the effect of refraction after the usual SfM-MVS processing, using common software. The presented method utilizes the empirical relation between the measured true depth and the estimated apparent depth to generate an empirical correction factor. Furthermore, this correction factor was utilized to convert the apparent water depth into a refraction-corrected (real-scale) water depth. To examine its effectiveness, we applied the method to two river sites, and compared the RMS errors in the corrected bottom elevations with those obtained by three existing methods. The result shows that the presented method is more effective than the two existing methods: The method without applying correction factor and the method utilizes the refractive index of water (1.34) as correction factor. In comparison with the remaining existing method, which used the additive terms (offset) after calculating correction factor, the presented method performs well in Site 2 and worse in Site 1. However, we found this linear regression method to be unstable when the training data used for calibration are limited. It also suffers from a large negative bias in the correction factor when the apparent water depth estimated is affected by noise, according to our numerical experiment. Overall, the good accuracy of refraction correction method depends on various factors such as the locations, image acquisition, and GPS measurement conditions. The most effective method can be selected by using statistical selection (e.g. leave-one-out cross validation).

Keywords: bottom elevation, MVS, river, SfM

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Authors: Iannick Gagnon, Alain April

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The performance of a metaheuristic on a given problem class depends on the class itself and the choice of parameters. Parameter tuning is the most time-consuming phase of the optimization process after the main calculations and it often nullifies the speed advantage of metaheuristics over traditional optimization algorithms. Several off-the-shelf parameter tuning algorithms are available, but when the objective function is expensive to evaluate, these can be prohibitively expensive to use. This paper presents a surrogate-like method for finding adequate parameters using fitness landscape analysis on simple benchmark functions and real-world objective functions. The result is a simple compound similarity metric based on the empirical correlation coefficient and a measure of convexity. It is then used to find the best benchmark functions to serve as surrogates. The near-optimal parameter set is then found using fractional factorial design. The real-world problem of NACA airfoil lift coefficient maximization is used as a preliminary proof of concept. The overall aim of this research is to reduce the computational overhead of metaheuristics parameterization.

Keywords: metaheuristics, stochastic optimization, particle swarm optimization, exploratory landscape analysis

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Authors: Tea Poklepović, Zdravka Aljinović, Mario Matković

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Modern Portfolio Theory (MPT) according to Markowitz states that investors form mean-variance efficient portfolios which maximizes their utility. Markowitz proposed the standard deviation as a simple measure for portfolio risk and the lower semi-variance as the only risk measure of interest to rational investors. This paper uses a third volatility estimator based on intraday data and compares three efficient frontiers on the Croatian Stock Market. The results show that range-based volatility estimator outperforms both mean-variance and lower semi-variance model.

Keywords: variance, lower semi-variance, range-based volatility, MPT

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Authors: Jonardan Koner

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The study attempts to find out the impact of infrastructural investment on state economic growth in India. It further tries to determine the magnitude of the impact of infrastructural investment on economic indicator, i.e., per-capita income (PCI) in Indian States. The study uses panel regression technique to measure the impact of infrastructural investment on per-capita income (PCI) in Indian States. Panel regression technique helps incorporate both the cross-section and time-series aspects of the dataset. In order to analyze the difference in impact of the explanatory variables on the explained variables across states, the study uses Fixed Effect Panel Regression Model. The conclusions of the study are that infrastructural investment has a desirable impact on economic development and that the impact is different for different states in India. We analyze time series data (annual frequency) ranging from 1991 to 2010. The study reveals that the infrastructural investment significantly explains the variation of economic indicators.

Keywords: infrastructural investment, multiple regression, panel regression techniques, economic development, fixed effect dummy variable model

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Authors: G. L. C. Yap

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Modelling realized volatility with high-frequency returns is popular as it is an unbiased and efficient estimator of return volatility. A computationally simple model is fitting the logarithms of the realized volatilities with a fractionally integrated long-memory Gaussian process. The Gaussianity assumption simplifies the parameter estimation using the Whittle approximation. Nonetheless, this assumption may not be met in the finite samples and there may be a need to normalize the financial series. Based on the empirical indices S&P500 and DAX, this paper examines the performance of the linear volatility model pre-treated with normalization compared to its existing counterpart. The empirical results show that by including normalization as a pre-treatment procedure, the forecast performance outperforms the existing model in terms of statistical and economic evaluations.

Keywords: Gaussian process, long-memory, normalization, value-at-risk, volatility, Whittle estimator

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Authors: Amit Bhattacharyya

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The economic scenario of any region does not show the real picture for the measurement of overall development. Therefore, economic development must be accompanied by social development to be able to make an assessment to measure the level of development. The spatial variation with respect to social development has been discussed taking into account the quality of functioning of a social system in a specific area. In this paper, an attempt has been made to study the spatial distribution of social infrastructural facilities and analyze the magnitude of regional disparities at inter- block level in Barddhman district. It starts with the detailed account of the selection process of social infrastructure indicators and describes the methodology employed in the empirical analysis. Analyzing the block level data, this paper tries to identify the disparity among the blocks in the levels of social development. The results have been subsequently explained using both statistical analysis and geo spatial technique. The paper reveals that the social development is not going on at the same rate in every part of the district. Health facilities and educational facilities are concentrated at some selected point. So overall development activities come to be concentrated in a few centres and the disparity is seen over the blocks.

Keywords: disparity, inter-block, social development, spatial variation

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Authors: Ahmad Mohsin, Irfan Raza Naqvi, Syda Fatima Usamn

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Applications with higher fault tolerance index are considered more reliable and trustworthy to drive quality. In recent years application development has been shifted from traditional desktop and web to native and hybrid application(s) for the web and mobile platforms. With the emergence of Internet of things IOTs, cloud and big data trends, the need for measuring Fault Tolerance for these complex nature applications has increased to evaluate their performance. There is a phenomenal gap between fault tolerance metrics development and measurement. Classic quality metric models focused on metrics for traditional systems ignoring the essence of today’s applications software, hardware & deployment characteristics. In this paper, we have proposed simple metrics to measure fault tolerance considering general requirements for Web and Mobile Applications. We have aligned factors – subfactors, using GQM for metrics development considering the nature of mobile we apps. Systematic Mathematical formulation is done to measure metrics quantitatively. Three web mobile applications are selected to measure Fault Tolerance factors using formulated metrics. Applications are then analysed on the basis of results from observations in a controlled environment on different mobile devices. Quantitative results are presented depicting Fault tolerance in respective applications.

Keywords: web and mobile applications, reliability, fault tolerance metric, quality metrics, GQM based metrics

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Authors: Arun Goel

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The present paper attempts to investigate the prediction of air entrainment rate and aeration efficiency of a free over-fall jets issuing from a triangular sharp crested weir by using regression based modelling. The empirical equations, support vector machine (polynomial and radial basis function) models and the linear regression techniques were applied on the triangular sharp crested weirs relating the air entrainment rate and the aeration efficiency to the input parameters namely drop height, discharge, and vertex angle. It was observed that there exists a good agreement between the measured values and the values obtained using empirical equations, support vector machine (Polynomial and rbf) models, and the linear regression techniques. The test results demonstrated that the SVM based (Poly & rbf) model also provided acceptable prediction of the measured values with reasonable accuracy along with empirical equations and linear regression techniques in modelling the air entrainment rate and the aeration efficiency of a free over-fall jets issuing from triangular sharp crested weir. Further sensitivity analysis has also been performed to study the impact of input parameter on the output in terms of air entrainment rate and aeration efficiency.

Keywords: air entrainment rate, dissolved oxygen, weir, SVM, regression

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Authors: Dongqi Sun, Juan Tao, Yingying Wu

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This paper reexamines the appropriateness of contrarian trades as a proxy of informed trades, using high frequency Chinese stock data. Employing this measure for 5 minute intervals, a U-shaped intraday pattern of probability of informed trades (PIN) is found for the CSI300 stocks, which is consistent with previous findings for other markets. However, while dividing the trades into different sizes, a reversed U-shaped PIN from large-sized trades, opposed to the U-shaped pattern for small- and medium-sized trades, is observed. Drawing from the mixed evidence with different trade sizes, the price impact of trades is further investigated. By examining the relationship between trade imbalances and unexpected returns, larges-sized trades are found to have significant price impact. This implies that in those intervals with large trades, it is non-contrarian trades that are more likely to be informed trades. Taking account of the price impact of large-sized trades, non-contrarian trades are used to proxy for informed trading in those intervals with large trades, and contrarian trades are still used to measure informed trading in other intervals. A stronger U-shaped PIN is demonstrated from this modification. Auto-correlation and information advantage tests for robustness also support the modified informed trading measure.

Keywords: contrarian trades, informed trading, price impact, trade imbalance

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Authors: E. Stylianopoulou, A. K. Fanti

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Object: Children scoring high on Callous-Unemotional traits (CU traits) exhibit lack of empathy. More specifically, children scoring high on CU traits appear to exhibit deficits on affective empathy or deficits in other constructs. However, little is known about cognitive empathy, and it's relation with CU traits in preschoolers. Despite the fact that empathy is measurable at a very young age, relatively less study has focused on empathy in preschoolers than older children with CU traits. The present study examines the cognitive and affective empathy in preschoolers with CU traits. The aim was to examine the differences between cognitive and affective empathy in those individuals. Based on previous research in children with CU traits, it was hypothesized that preschoolers scoring high in CU traits will show deficits in both cognitive and affective empathy; however, more deficits will be detected in affective empathy rather than cognitive empathy. Method: The sample size was 209 children, of which 109 were male, and 100 were female between the ages of 3 and 7 (M=4.73, SD=0.71). From those participants, only 175 completed all the items. The Inventory of Callous-Unemotional traits was used to measure CU traits. Moreover, the Griffith Empathy Measure (GEM) Affective Scale and the Griffith Empathy Measure (GEM) Cognitive Scale was used to measure Affective and Cognitive empathy, respectively. Results: Linear Regression was applied to examine the preceding hypotheses. The results showed that generally, there was a moderate negative association between CU traits and empathy, which was significant. More specifically, it has been found that there was a significant and negative moderate relation between CU traits and cognitive empathy. Surprisingly, results indicated that there was no significant relation between CU traits and affective empathy. Conclusion: The current findings support that preschoolers show deficits in understanding others emotions, indicating a significant association between CU traits and cognitive empathy. However, such a relation was not found between CU traits and affective empathy. The current results raised the importance that there is a need for focusing more on cognitive empathy in preschoolers with CU traits, a component that seems to be underestimated till now.

Keywords: affective empathy, callous-unemotional traits, cognitive empathy, preschoolers

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Authors: Jill Steel

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The interlinked issues of emotional wellbeing and attainment continue to dominate international educational discourse. Reading skills are particularly important to attainment in all areas of the curriculum, and illiteracy is associated with reduced wellbeing and life prospects, with serious ramifications for the wider economy and society. Research shows that reading attainment is influenced by reading motivation and frequency. Reading to Dogs (RTD) is increasingly applied to promote reading motivation and frequency in schools despite a paucity of empirical evidence, specifically examining the influence of RTD on emotional wellbeing and engagement with reading. This research aims to examine whether RTD is effective in promoting these positive outcomes among children aged eight to nine years. This study also aims to inform much needed regulation of the field and standards of practice, including both child and dog welfare. Therefore, ethical matters such as children’s inclusion and safety, as well as the rights and wellbeing of dogs infuse the study throughout. The methodological design is a mixed method longitudinal study. A UK wide questionnaire will be distributed to teachers between January and June 2020 to understand their perceptions of RTD. Following this, a randomised controlled trial (N = 100) will begin in August 2020 in two schools of a comparable demographic, with N= 50 in the intervention school, and N= 50 in a waiting list control school. Reading and wellbeing assessments will be conducted prior to and immediately post RTD, and four weeks after RTD to measure sustained changes. The reading assessments include New Group Reading Test, Motivation to Read Profile (Gambrell et al., 1995), as well as reading frequency and reading anxiety assessments specifically designed for the study. Wellbeing assessments include Goodman’s SDQ, (1997) and pupil self-reporting questionnaires specifically designed for the study. Child, class teacher, and parent questionnaires and interviews prior to, during and post RTD will be conducted to measure perceptions of the impact of RTD on mood and motivation towards reading. This study will make a substantial contribution to our understanding of the effectiveness of RTD and thus have consequences for the fields of education and anthrozoology.

Keywords: animal assisted intervention, reading to dogs, welfare, wellbeing

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Authors: Khlif Hamadi

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Customer Relationship Management has become the main interest of researchers and practitioners especially in the domains of Management and Information Systems (IS). This paper is an overview of success factors that could facilitate successful adoption of CRM. There are 2 factors: the organizational climate and the capacity for innovation. The survey was developed with 200 CRM users. Empirical research is in the positivist paradigm based on the hypothetico-deductive method. Indeed, the approach adopted is the quantitative approach based on a questionnaire complied by Tunisian companies operating in different sectors of activity. For the data analyses, the structural equations method was used to conduct our exploratory and confirmatory analysis. The results revealed that the creative organizational climate and high innovation capacity positively influence the success of CRM practice.

Keywords: CRM practices, innovation capacity, organizational climate, the structural equation

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Authors: Mukesh Khadka, Alexander Paz, Hanns de la Fuente-Mella

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Typically, pavement performance models are developed in two steps: (i) pavement segments with similar characteristics are grouped together to form a cluster, and (ii) the corresponding performance models are developed using statistical techniques. A challenge is to select the characteristics that define clusters and the segments associated with them. If inappropriate characteristics are used, clusters may include homogeneous segments with different performance behavior or heterogeneous segments with similar performance behavior. Prediction accuracy of performance models can be improved by grouping the pavement segments into more uniform clusters by including both characteristics and a performance measure. This grouping is not always possible due to limited information. It is impractical to include all the potential significant factors because some of them are potentially unobserved or difficult to measure. Historical performance of pavement segments could be used as a proxy to incorporate the effect of the missing potential significant factors in clustering process. The current state-of-the-art proposes Clusterwise Linear Regression (CLR) to determine the pavement clusters and the associated performance models simultaneously. CLR incorporates the effect of significant factors as well as a performance measure. In this study, a mathematical program was formulated for CLR models including multiple explanatory variables. Pavement data collected recently over the entire state of Nevada were used. International Roughness Index (IRI) was used as a pavement performance measure because it serves as a unified standard that is widely accepted for evaluating pavement performance, especially in terms of riding quality. Results illustrate the advantage of the using CLR. Previous studies have used CLR along with experimental data. This study uses actual field data collected across a variety of environmental, traffic, design, and construction and maintenance conditions.

Keywords: clusterwise regression, pavement management system, performance model, optimization

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Authors: Nahla H. Alaswadko, Rayya A. Hassan, Bayar N. Mohammed

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Empirical deterministic models have been developed to predict roughness progression of heavy duty spray sealed pavements for a dataset representing rural arterial roads. The dataset provides a good representation of the relevant network and covers a wide range of operating and environmental conditions. A sample with a large size of historical time series data for many pavement sections has been collected and prepared for use in multilevel regression analysis. The modelling parameters include road roughness as performance parameter and traffic loading, time, initial pavement strength, reactivity level of subgrade soil, climate condition, and condition of drainage system as predictor parameters. The purpose of this paper is to report the approaches adopted for models development and validation. The study presents multilevel models that can account for the correlation among time series data of the same section and to capture the effect of unobserved variables. Study results show that the models fit the data very well. The contribution and significance of relevant influencing factors in predicting roughness progression are presented and explained. The paper concludes that the analysis approach used for developing the models confirmed their accuracy and reliability by well-fitting to the validation data.

Keywords: roughness progression, empirical model, pavement performance, heavy duty pavement

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Authors: Chokri Slim

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The relative failure of simultaneous equation models in the seventies has led researchers to turn to other approaches that take into account the dynamics of economic and financial systems. In this paper, we use an approach based on vector autoregressive model that is widely used in recent years. Their popularity is due to their flexible nature and ease of use to produce models with useful descriptive characteristics. It is also easy to use them to test economic hypotheses. The standard econometric techniques assume that the series studied are stable over time (stationary hypothesis). Most economic series do not verify this hypothesis, which assumes, when one wishes to study the relationships that bind them to implement specific techniques. This is cointegration which characterizes non-stationary series (integrated) with a linear combination is stationary, will also be presented in this paper. Since the work of Johansen, this approach is generally presented as part of a multivariate analysis and to specify long-term stable relationships while at the same time analyzing the short-term dynamics of the variables considered. In the empirical part, we have applied these concepts to study the dynamics of of the exchange rate in Tunisia, which is one of the most important economic policy of a country open to the outside. According to the results of the empirical study by the cointegration method, there is a cointegration relationship between the exchange rate and its determinants. This relationship shows that the variables have a significant influence in determining the exchange rate in Tunisia.

Keywords: stationarity, cointegration, dynamic models, causality, VECM models

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Authors: Mengjia Zhi, Xingmei Wei, Xiang Gao, Shiyang Liu, Zhiran Huang, Li Yang, Jing Sun

Abstract:

Background: To understand the consumption trend of opioid analgesics and the consumption adequacy of opioid analgesic treatment for moderate to severe pain in China, as well as the pain control level of China with international perspective. Importance: To author’s best knowledge, this is the first study in China to measure the adequacy of opioid analgesic treatment for moderate to severe pain considering disease pattern and with the standardized pain treatment guideline. Methods: A retrospective analysis was carried out to show the consumption frequency (daily defined doses, DDDs) of opioid analgesics and its trend in China from 2006 to 2016. Adequacy of consumption measure (ACM) was used to measure the number of needed morphine equivalents and the overall adequacy of opioid analgesic treatment of moderate to severe pain in China, and compared with international data. Results: The consumption frequency of opioid analgesics (DDDs) in China increased from 13,200,000 DDDs in 2006 to 44,200,000 DDDs in 2016, and showed an increasing trend. The growth rate was faster at first, especially in 2013, then slowed down, decreased slightly in 2015. The ACM of China increased from 0.0032 in 2006 to 0.0074 in 2016, with an overall trend of growth. The ACM level of China has been always a very poor level during 2006-2016. Conclusion: The consumption of opioid analgesics for the treatment of moderate to severe pain in China has always been inadequate. There is a huge gap between China and the international level. There are many reasons behind this problem, which lie in different aspects, including medical staff, patients and the public, health systems and social & cultural aspects. It is necessary to strengthen the training and education of medical staff and the patients, to use mass media to disseminate scientific knowledge of pain management, to encourage communications between doctors and patients, to improve regulatory system for the controlled medicines and the overall health systems, and to balance the regulatory goal for avoidance of abuse, and the social goal of meeting the increasing needs of the people for better life.

Keywords: opioid analgesics, adequate consumption measure, pain control, China

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Authors: Harun Aydilek, Asiye Aydilek, Ali Allahverdi

Abstract:

The total tardiness is a widely used performance measure in the scheduling literature. This performance measure is particularly important in situations where there is a cost to complete a job beyond its due date. The cost of scheduling increases as the gap between a job's due date and its completion time increases. Such costs may also be penalty costs in contracts, loss of goodwill. This performance measure is important as the fulfillment of due dates of customers has to be taken into account while making scheduling decisions. The problem is addressed in the literature, however, it has been assumed zero setup times. Even though this assumption may be valid for some environments, it is not valid for some other scheduling environments. When setup times are treated as separate from processing times, it is possible to increase machine utilization and to reduce total tardiness. Therefore, non-zero setup times need to be considered as separate. A dominance relation is developed and several algorithms are proposed. The developed dominance relation is utilized in the proposed algorithms. Extensive computational experiments are conducted for the evaluation of the algorithms. The experiments indicated that the developed algorithms perform much better than the existing algorithms in the literature. More specifically, one of the newly proposed algorithms reduces the error of the best existing algorithm in the literature by 40 percent.

Keywords: algorithm, assembly flowshop, dominance relation, total tardiness

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Authors: Lynne Soon-Chean Park

Abstract:

Critical Realism (CR) has emerged as an alternative to both the positivist and constructivist perspectives that have long dominated social work research. By unpacking the epistemic weakness of two dogmatic perspectives, CR provides a useful philosophical approach that incorporates the ontological objectivist and subjectivist stance. The CR perspective suggests an alternative approach for social work researchers who have long been looking to engage in the complex interplay between perceived reality at the empirical level and the objective reality that lies behind the empirical event as a causal mechanism. However, despite the usefulness of CR in informing social work research, little practical guidance is available about how CR can inform methodological considerations in social work research studies. This presentation aims to provide a detailed description of CR-informed thematic analysis by drawing examples from a social work doctoral research of Korean migrants’ experiences and understanding of trust associated with their settlement experience in New Zealand. Because of its theoretical flexibility and accessibility as a qualitative analysis method, thematic analysis can be applied as a method that works both to search for the demi-regularities of the collected data and to identify the causal mechanisms that lay behind the empirical data. In so doing, this presentation seeks to provide a concrete and detailed exemplar for social work researchers wishing to employ CR in their qualitative thematic analysis process.

Keywords: critical Realism, data analysis, epistemology, research methodology, social work research, thematic analysis

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Authors: Umang Varshney, Amit Karamchandani, Rohit Kapoor

Abstract:

Practitioners and researchers have realized that Blockchain is not limited to currency. Blockchain as a distributed ledger can ensure a transparent and traceable supply chain. Due to Blockchain-enabled IoTs, a firm’s information management system can now take inputs from other supply chain partners in real-time. This study aims to provide empirical evidence of dimensions responsible for blockchain implemented firm’s growth and highlight how sector (manufacturing or service), state's regulatory environment, and choice of blockchain network affect the blockchain's usefulness. This post-adoption study seeks to validate the findings of pre-adoption studies done on the blockchain. Data will be collected through a survey of managers working in blockchain implemented firms and analyzed through PLS-SEM.

Keywords: blockchain, information management system, PLS-SEM, firm's growth

Procedia PDF Downloads 96