Laypeople roles at road traffic crash scenes: a systematic review

This study aimed to identify the roles of laypeople at road traffic injuries (RTIs). A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The key words of ‘laypeople’, ‘layman’, ‘layperson’, ‘bystander’, ‘first responder’, ‘lay first responder’, ‘road traffic’, ‘road traffic injury’, ‘crash injury’, ‘crash scene’, ‘emergency’, ‘trauma care’, and ‘prehospital trauma care’ were used in combination with the Boolean operators OR and AND. We did electronic search on Google Scholar, PubMed, ISI Web of Science, CINAHL, Science Direct, Scopus, ProQuest. Based on the reviewed studies, some factors such as cultural conditions, knowledge, relief agencies, and demographic factors affect the interventions of laypeople at the crash scene in functional areas. Regarding the permanent presence of people at the crash scene, the present study can provide an opportunity to reduce different side effects of RTIs imposed on the society.     

An Investigation of the Association between Cultural Dimensions and Variations in Perceived Use of and Compliance with Internal Auditing Standards in 19 Countries

Using a large sample of chief audit executives and internal audit managers from 19 countries, we investigate potential associations between cultural dimensions and variations in perceived use/compliance with the internal auditing standards. We find uncertainty avoidance to be inversely related to both use and compliance. We also find assertiveness and human orientation to be positively related to compliance but not to use of Standards. Among control variables, we find positive associations for the length of Institute of Internal Auditors (IIA) membership, professional certification in internal auditing, and hours of continuing professional education (CPE) training on both perceived use and compliance. Finally, we find “Cost of compliance” and “Compliance not expected in my country” to be inversely related to perceived use/compliance. Implications of these findings are discussed.     

Mixture of MLP-experts for trend forecasting of time series: A case study of the Tehran stock exchange

A new method for forecasting the trend of time series, based on mixture of MLP experts, is presented. In this paper, three neural network combining methods and an Adaptive Network-Based Fuzzy Inference System (ANFIS) are applied to trend forecasting in the Tehran stock exchange. There are two experiments in this study. In experiment I, the time series data are the Kharg petrochemical company’s daily closing prices on the Tehran stock exchange. In this case study, which considers different schemes for forecasting the trend of the time series, the recognition rates are 75.97%, 77.13% and 81.64% for stacked generalization, modified stacked generalization and ANFIS, respectively. Using the mixture of MLP experts (ME) scheme, the recognition rate is strongly increased to 86.35%. A gain and loss analysis is also used, showing the relative forecasting success of the ME method with and without rejection criteria, compared to a simple buy and hold approach. In experiment II, the time series data are the daily closing prices of 37 companies on the Tehran stock exchange. This experiment is conducted to verify the results of experiment I and to show the efficiency of the ME method compared to stacked generalization, modified stacked generalization and ANFIS.     

State of the art in business analytics: themes and collaborations

In this study, we illustrate the most recent stage in the scholarly development of the field of Business Analytics. Using around 23,000 research publications collected from the Web of Science, we network-analyzed four types of dataset that include keywords, titles, institutions, and countries. It is noteworthy that we found a thematic cluster focusing on analytical techniques and tools, particular with the rapid dissemination of “big data”-related studies. It is not surprising that universities and institutions in advanced countries in the West still occupy the central position of the collaboration network. However, we can discern a global shift toward certain developing and transitional economies in the world science base.     

Corporate commitment to climate change action,carbon risk exposure,and a firm's debt financing policy

Motivated by the rising consensus that corporate engagement in climate change actions holds the key for society's transition into environmentally resilient economy, the study examines whether a firm's commitment to climate change action and its carbon risk exposure shape the firm's debt financing policy. Based on insights drawn from signaling, corporate reputation, and agency theories, we develop models that link corporate commitment to climate change actions and a firm's carbon risk exposure with its debt financing decisions. Using data drawn from S&P 500 companies, for years 2015 to 2019, we find a robust evidence that firms that engage in higher levels of commitment to climate change actions issue a higher proportion of debt with longer terms to maturity, even after controlling for their carbon risk exposure. However, we do not find a robust evidence corroborating an association between firms' carbon risk exposure and their debt financing policy. These findings are consistent with arguments that high-commitment firms enjoy positive reputation, better credit rating, and reduced agency and information asymmetry costs, allowing them to gain easier access to long-term debt markets.     

The Influence of Board Composition on Sustainable Development Disclosure

Despite knowing the potential effect of social reporting on firms' continuity, there is limited research into the influence of the composition of boards of directors on CSR disclosure. This paper adds to the emerging CSR literature empirical evidence by examining how board composition relates to a firm's social and environmental disclosure as well as the implementation of social policies. Using a sample of FTSE 350 firms for the period 2007–2012, the results show that higher board independence facilitates the conveying of firms' good citizenship image through enhancing societal conscience. The results also show that female participation on boards is favorably affecting CSR engagement and reporting as well as the establishment of ethical policies. Hence, the research suggests that boards with higher female participation and independence boost the legitimacy of CSR reporting. Board gender diversity and independence facilitates directing part of the firm's scarce resources toward value maximizing social projects and subsequent reporting on these. Copyright © 2017 John Wiley & Sons, Ltd and ERP Environment     

Bounds for the mean residual life function of a <Emphasis Type="Italic">k</Emphasis>-out-of-<Emphasis Type="Italic">n</Emphasis> system

In the reliability studies, k-out-of-n systems play an important role. In this paper, we consider sharp bounds for the mean residual life function of a k-out-of-n system consisting of n identical components with independent lifetimes having a common distribution function F, measured in location and scale units of the residual life random variable X _t  = (X−t|X > t). We characterize the probability distributions for which the bounds are attained. We also evaluate the so obtained bounds numerically for various choices of k and n.     

Bayesian Inference in Auditing: Evidence on the Most Appropriate Assessment Techniques

Interest in the use of the Bayesian statistical method in auditing has been increasing over the past few years. To use this method, however, appropriate prior probability assessment techniques (PPAT) need to be identified. This study uses three evaluation criteria, acceptability, accuracy and concordance, to compare four PPATs in auditing. The four PPATs compared are cumulative distribution function (CDF), probability density function (PDF), equivalent prior sample information (EPS), and hypothetical future samples (HFS). Seventy-three practising auditors were trained to use these four PPATs in their task of compliance error quantification in an audit case study. Results indicate that PDF is the most appropriate PPAT and EPS the least appropriate PPAT for use in practical audit situations. CDF and HFS were in the middle with no clear difference between them. Implications for audit practice and research are discussed.     

Scale Efficiency in the New Zealand Dairy Industry: a Non-parametric Approach

The aim in this article is to measure the scale efficiency of the New Zealand dairy industry and to examine the relationship between farm size and technical efficiency. Data envelopment analysis (DEA) is applied to a sample of 264 dairy farms. The results suggest that 19 per cent of these farms are operating at optimal scale, 28 per cent at above optimal scale, and 53 per cent at below optimal scale. On average, the optimal size for New Zealand dairy farms is estimated at 83 hectares with a herd of 260 animals. Average technical efficiency is estimated at 89 per cent.     

Impact of Financial Development on the Environmental Quality in Iran

In recent decades, undesirable environmental changes, such as global warming and greenhouse gases emission, have raised worldwide concerns. In order to achieve higher growth rate, environmental problems emerged from economic activities have turned into a controversial issue. The aim of this study is to investigate the effect of financial development on environmental quality in Iran. For this purpose, the statistical data over the period from 1970 to 2011 were used. Also by using the Auto Regression Model Distributed Lag （ARDL）, short-term and long-term relationships among the variables of model were estimated and analyzed. The results show that financial development accelerates the degradation of the environment; however, the increase in trade openness reduces the damage to environment in Iran. Error correction coefficient shows that in each period, 53% of imbalances would be justified and will approach their long-run procedure. Structural stability tests show that the estimated coefficients were stable over the period.