Teacher opinions regarding the perception management levels of school administrators

The purpose of this research is to determine the levels and use of perception management by school administrators. The study group consists of teachers working in Private Primary School and Secondary Schools affiliated to the Ministry of National Education in Nicosia, the Turkish Republic of Northern Cyprus in the 2016–2017 academic year. The sample of the study is composed of 282 teachers representing the universe selected by the method of easy reachable case sampling. As a means of collecting data in the survey, “Personal Information Form” by Kline (An easy guide to factor analysis, Routledge, New York, 1994) and “Manager Perception Management ent Scale” developed by Uylas (Yönetici Alg? Yönetimi Ölçe?i, Türkiye Ölçme Araçlar? Dizini, 2017a, Okul Yöneticilerinin Sosyal-Duygusal E?itim Liderli?i ve Alg? Yönetimine ?li?kin Ö?retmen Görü?leri, T.C. Abant ?zzet Baysal Üniversitesi, E?itim Bilimleri Enstitüsü, Bolu, 2017b) was used. The obtained data were analyzed in an analysis program. In the research, the values of perception management use levels of managers according to teacher opinions were examined. According to the results and comments obtained from the research, some of the proposals developed for researchers and educators working in the field of education management are as follows. Towards practical; trainings can be given on how school administrators can use perception management for successful perception management practices in educational organizations. In interviews to select school administrators, choosing school administrator with high perception management skills can be prioritized. Towards newstudies; including multidimensional evaluation of all elements of educational organizations such as managers, parents and servants in new researches to be conducted and comparison of teachers ‘and administrators’ views. This study has brought out suggestions that can be implemented in other stages of education.     

Development of a voice recognition based system to help physically disabled people use the facebook

Social network sites (SNSs) have become so popular that the number of people joining and actively participating on such sites is increasing on a daily basis. Although there are several SNSs, Facebook is currently the most popular and most commonly used. SNSs have primarily been developed with able-bodied people in mind and as a result of this, people with disabilities find it difficult to join and participate on these sites. Furthermore, this topic has received little attention by researchers around the world. Facebook pages usually consist of text, graphics, and sound where the users navigate through the pages using a mouse. As a step towards addressing this need and finding a possible elegant solution, the authors have developed a voice-activated PC-based system (called NEU-FACE) in the form of an interface to Facebook. With the aid of this system, a person with a physical disability can join and participate in Facebook by giving voice commands to manage the typical Facebook activities.

     

Mandatory disclosure,greenhouse gas emissions and the cost of equity capital: UK evidence of a U-shaped relationship

This paper examines the effects of disclosing greenhouse gas (GHG) information mandatorily on the cost of equity capital (COC) using a longitudinal unbalanced panel database of the United Kingdom's FTSE 350 firms for the period 2011–2016. We use a nonlinear panel quantile regression (PQR) model to examine the relationship between GHG disclosure (GHGD) and COC in the United Kingdom. This technique was supplemented by conducting a two-step generalised method of moment (GMM) estimation to address any concerns related to the potential existence of endogeneity problems. Our findings suggest that high-level GHGD appeared to be negatively associated with COC up to a certain level, which is known as the turning point; then, any increase in GHGD is likely to increase the COC. This means that the nonlinear association between GHGD and COC is evidenced in our study and takes a U shape. Likewise, our findings are associative of a moderating effect of the 2013 carbon disclosure regulation (CDR) on the GHGD–COC nexus. We argue that mandatory GHGD and GHG risk are linked so that those companies that are associated with higher GHG risk have a tendency to be better disclosers. Consequently, we urge regulators to design GHGD regulations in a way that mirrors corporate environmental risk and leads to a lower COC in order to align the interests of corporations with those of the society at large.     

The impact of traffic sign deficit on road traffic accidents in Nigeria

This study assesses the impact of traffic sign deficit on road traffic accidents in Nigeria. The participants were 720 commercial vehicle drivers. While simple random sampling was used to select 6 out of 137 federal highways, stratified random sampling was used to select six categories of commercial vehicle drivers. The study used qual-dominant mixed methods approach comprising key informant interviews; group interviews; field observation; policy appraisal and secondary literature on traffic signs. Result shows that the failure of government to provide and maintain traffic signs in order to guide road users through the numerous accident black spots on the highways is the major cause of road accidents in Nigeria. The study argues that provision and maintenance of traffic signs present opportunity to promoting safety on the highways and achieving the sustainable development goals.     

FORWARD RISK PREMIA AND THE MATURITY OF CONTRACTS: A NOTE

This paper examines the behavior of the risk premium component of currency forward rates. Analyzing forward rates of one, two and three-month maturity, we find that the power of forward rate as a predictor of future spot rate decreases with the length of contract maturity. Further, we find that the proportion of the variance of the forward premium which is due to the variation of the risk premium is larger than the proportion due to the expected spot rate change for all currencies except for the Canadian dollar. This proportion also increases with the length of maturity.     

On the Role of Futures Trading in Spot Market Fluctuations: Perpetrator of Volatility or Victim of Regret?

We examine the role of index futures trading in spot market volatility. We use the exponential generalized autoregressive conditional heteroskedasticity (EGARCH) approach to measure volatility, analyze causality and feedback relations between volatilities in the spot and futures markets, and test various hypotheses in the context of a multivariate model that incorporates other macrostate variables. Our empirical results suggest index futures trading may not be blamed for the observed volatility in the spot market. Rather, we find stronger and more consistent support for the alternative posture that volatility in the futures market is an outgrowth of a turbulent cash market. We use the regret (cognitive dissonance) theory to explain our results.     

Human capital,investment and growth: Some results from an endogenous growth model

Recent theoretical literature on the sources of economic growth has emphasized the role of human capital as an internal contributing force in the growth process. Empirical results reported in this paper provide support for this theoretical proposition. Cross-country data from 32 developing countries indicate that human capital (as alternatively measured by the primary school enrollment rate or the adult literacy rate) exerts a significant positive impact upon output growth.     

Corporate mergers and union wage premiums

Corporate mergers possibly enhance the labor negotiation advantage of employers. This study investigates the association between wage levels and merger activity to test the employer bargaining strength hypothesis. The results indicate significantly lower union wages as a consequence of merging. Merger activity, however, does not influence wage levels of non-union workers. These findings are supportive of the employer bargaining strength hypothesis.     

Mean–variance and mean–semivariance portfolio selection: a multivariate nonparametric approach

While univariate nonparametric estimation methods have been developed for estimating returns in mean-downside risk portfolio optimization, the problem of handling possible cross-correlations in a vector of asset returns has not been addressed in portfolio selection. We present a novel multivariate nonparametric portfolio optimization procedure using kernel-based estimators of the conditional mean and the conditional median. The method accounts for the covariance structure information from the full set of returns. We also provide two computational algorithms to implement the estimators. Via the analysis of 24 French stock market returns, we evaluate the in-sample and out-of-sample performance of both portfolio selection algorithms against optimal portfolios selected by classical and univariate nonparametric methods for three highly different time periods and different levels of expected return. By allowing for cross-correlations among returns, our results suggest that the proposed multivariate nonparametric method is a useful extension of standard univariate nonparametric portfolio selection approaches.     

An Approach to Security for Unstructured Big Data

Security of Big Data is a huge concern. In a broad sense, Big Data contains two types of data: structured and unstructured. Providing security to unstructured data is more difficult than providing security to structured data. In this paper, we have developed an approach to provide adequate security to unstructured data by considering types of data and their sensitivity levels. We have reviewed the different analytics methods of Big Data to build nodes of different types of data. Each type of data has been classified to provide adequate security and enhance the overhead of the security system. To provide security to a data node, and a security suite has been designed by incorporating different security algorithms. Those security algorithms collectively form a security suite which has been interfaced with the data node. Information on data sensitivity has been collected through a survey. We have shown through several experiments on multiple computer systems with varied configurations that data classification with respect to sensitivity levels enhances the performance of the system. The experimental results show how and in what amount the designed security suite reduces overhead and increases security simultaneously.