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We illustrate empirically the use of return-based style analysis for domestic stock funds. We search the optimal style model according to the tracking errors, investigate the consistency of the fund style for the optimally selected model, and finally investigate the relationship between fund styles and their fund performance. We use weekly fund return data of domestic stock funds from January 2, 2002 to June 30, 2008, and do style analyses based on the various style indices. The major findings are as follows.

Firstly, we find that the style index models with constraint which in practice restricts short sale are better than those with no such constraint. Secondly, we find that the style index model which divides stock market with four categorized indices based on the dimension of size and book-to market and includes the bond market index is the most useful if they are evaluated based on the out-of-sample tracking errors. While adding the Fama-French 3 factors to the selected model does not improve the explanation power, adding the industry sector indexes improves the explanation power. Thirdly, we investigate the consistency of the fund style models and find that the better performing funds are more volatile in the change of the fund style. Fourthly, we find that, contrary to the expectation that the growth-oriented funds perform better than the value-oriented one, the fund performance and style are observed to be mixed. This finding shows that the fund styles are frequently changed according to their performances and market conditions.

In this study, the authors want to identify current possible causes for citing and referencing errors in scholarly literature to compare if something changed from the snapshot provided by Sweetland in his 1989 paper.

The authors analysed reference elements, i.e. bibliographic references, mentions, quotations and respective in-text reference pointers, from 729 articles published in 147 journals across the 27 subject areas.

The outcomes of the analysis pointed out that bibliographic errors have been perpetuated for decades and that their possible causes have increased, despite the encouraged use of technological facilities, i.e. the reference managers.

As far as the authors know, the study is the best recent available analysis of errors in referencing and citing practices in the literature since Sweetland (1989).

This paper aims to examine how leadership style in audit firms influences audit quality. The paper further explores the mediating role of knowledge sharing in the relationship between leadership style and audit quality.

The present paper studies the effects of transformational and servant leadership styles on audit quality through knowledge sharing. Data are collected from 396 Iranian external auditors via a questionnaire.

The results show that both transformational and servant leadership style significantly influence audit quality through knowledge sharing. Moreover, the impact of transformational leadership style is stronger than the impact of servant leadership style.

In audit quality literature, little attention has been devoted to both leadership style and knowledge sharing. This paper develops a parsimonious model which shows how leadership style improves audit quality, and how knowledge sharing strengthens the impact of leadership style on audit quality. The results have important implications particularly for audit industry.

本文探討審計公司內的領導風格會如何影響審計質量; 本文亦進一步探索、在領導風格與審計質量的關聯上、知識共享所扮演的調節角色。

本文旨在研究透過知識共享、轉型領導風格和僕人式領導風格會如何影響審計質量。數據取自396名伊朗外聘審計員，方法是透過一份調查問卷而進行的。

研究結果顯示、轉型領導風格和僕人式領導風格兩者均會透過知識共享、影響著審計質量，而且，這影響是頗為顯著的。就影響的程度而言，轉型領導風格的影響則較僕人式領導風格的更為強烈。

在研究審計質量的文獻裡，學者對領導風格和知識共享這兩個課題均沒多大關注。本文建立了一個簡約模型，去顯示領導風格如何能改善審計質量，以及知識共享如何能增強領導風格對審計質量的影響。研究結果給予我們重要的啟示，尤對審計行業而言。

Given the importance of style allocation strategy under the outsourced chief investment officer (OCIO) structure, the authors examine the validity of style allocation strategies in the Korean stock market. The authors find that external investment agencies can improve performance by using newly suggested investment styles such as high dividend yield and low volatility as well as traditional styles. In addition, the authors find that the style combination strategies create economically large and statistically significant returns. Finally, empirical results indicate that factor timing strategies suggested in this study can improve the reward-to-risk ratio. In sum, the empirical findings indicate that external investment agencies under the OCIO structure can improve performance using active style allocation strategies.

A leader plays an important role in the growth of an organization. The leader is a person who influences the standards, structure, culture and behaviour of the individuals employed in the organization. A leader also has effects on the result and productivity of teams. The purpose of this paper is to analyze the effect of transformational leadership style on team performance. This paper will also analyze the existence of a relationship between transformational leadership style and team performance.

For this study, the researcher collected the data from 354 individuals employed in IT organizations in Pune. The team members answered questions asked about the transformational leadership style, and the team leaders answered questions related to team performance. The data has been analyzed using the latest available version of Statistical Product and Service Solutions.

The results of this examination suggest that there is strong and positive relationship between the transformational leadership style and team performance. Further, it was also found that transformational leader helps in a great way in improving team performance which in turn increases the organization’s productivity.

Few limitations of this research work are that the data collected for this research work is non-cognitive in nature and simultaneously respondents may incline to evaluate the positive facets of opinion poll more propitiously than negative facets. Secondly, the data have been collected only from companies located in Pune.

This research study provides empirical data that will be helpful for human resources department of an organization, as it can help them in the development of policies and practices. It will also provide help leaders to support employees who are seeking effective ways to support struggling employees in context to their team performance.

The present study can be differentiated from past studies, as it thinks over an ensemble of transformational leadership style as an essential antecedent of team performance and also enhances the knowledge of the researchers and practitioners about the leadership style that upshot to the team performance. This will also help the managers, researchers, organizational development specialist and employees who are seeking effective ways to support struggling employees in context to their team performance.

The purpose of this paper is to unpack the underlying mechanisms of entrepreneurs' passion, orientation and behavior by investigating the role of rational and nonrational cognitive elements. Building on dual process theory and sociointuitionism, a conceptual model is proposed in order to explore the relationship between entrepreneurial passion, entrepreneurial orientation (EO) and strategic entrepreneurship behavior (SEB). Specifically, entrepreneurs' linear thinking styles (System 2) and nonlinear thinking styles (System 1) are hypothesized as being significant moderators of such a relationship.

Covariance-based structural equation modeling (CB-SEM) is used to empirically validate the proposed conceptual model and test the moderating hypotheses on a sample of 300 entrepreneurs actively involved in European small and medium enterprises (SMEs).

Entrepreneurial passion is shown to be a significant antecedent of EO, which, in turn, strongly influences SEB. Moreover, entrepreneurs' linear thinking style positively moderates the EO-SEB relationship, but not the link between passion and EO. Instead, a nonlinear thinking style positively moderates the relationship between passion and EO, but not the links between EO and SEB.

Entrepreneurs should trust their nonlinear thinking style – related to affective/emotive and intuitive information processing systems – to foster the effect of their entrepreneurial passion on EO. Furthermore, entrepreneurs should rely on a linear thinking style, namely the rational and deliberative cognitive processes, to enhance the impact of their EO on SEB.

Dual process theory and sociointuitionism are integrated to simultaneously investigate the effect of nonrational and rational cognitive mechanisms on entrepreneurs' orientation and behavior. Moreover, the proposed model is empirically tested on a sample of entrepreneurs working in SMEs located in Europe, which have received little attention from entrepreneurship scholars in comparison to their US counterparts. The authors’ findings suggest important implications for entrepreneurs, policymakers and entrepreneurial universities educators.

An individual’s driving style significantly affects overall traffic safety. However, driving style is difficult to identify due to temporal and spatial differences and scene heterogeneity of driving behavior data. As such, the study of real-time driving-style identification methods is of great significance for formulating personalized driving strategies, improving traffic safety and reducing fuel consumption. This study aims to establish a driving style recognition framework based on longitudinal driving operation conditions (DOCs) using a machine learning model and natural driving data collected by a vehicle equipped with an advanced driving assistance system (ADAS).

Specifically, a driving style recognition framework based on longitudinal DOCs was established. To train the model, a real-world driving experiment was conducted. First, the driving styles of 44 drivers were preliminarily identified through natural driving data and video data; drivers were categorized through a subjective evaluation as conservative, moderate or aggressive. Then, based on the ADAS driving data, a criterion for extracting longitudinal DOCs was developed. Third, taking the ADAS data from 47 Kms of the two test expressways as the research object, six DOCs were calibrated and the characteristic data sets of the different DOCs were extracted and constructed. Finally, four machine learning classification (MLC) models were used to classify and predict driving style based on the natural driving data.

The results showed that six longitudinal DOCs were calibrated according to the proposed calibration criterion. Cautious drivers undertook the largest proportion of the free cruise condition (FCC), while aggressive drivers primarily undertook the FCC, following steady condition and relative approximation condition. Compared with cautious and moderate drivers, aggressive drivers adopted a smaller time headway (THW) and distance headway (DHW). THW, time-to-collision (TTC) and DHW showed highly significant differences in driving style identification, while longitudinal acceleration (LA) showed no significant difference in driving style identification. Speed and TTC showed no significant difference between moderate and aggressive drivers. In consideration of the cross-validation results and model prediction results, the overall hierarchical prediction performance ranking of the four studied machine learning models under the current sample data set was extreme gradient boosting > multi-layer perceptron > logistic regression > support vector machine.

The contribution of this research is to propose a criterion and solution for using longitudinal driving behavior data to label longitudinal DOCs and rapidly identify driving styles based on those DOCs and MLC models. This study provides a reference for real-time online driving style identification in vehicles equipped with onboard data acquisition equipment, such as ADAS.

Learning styles based education is becoming influential at higher education institutions around the world. Learning styles are characteristics of how students prefer to learn; they draw their origin from both biological and experiential conditions that make each student unique in the way he/she learns. An important first step in improving learning is to identify or assess students’ learning styles, and there are several instruments that can be used for this purpose. This is necessary for teachers and students who wish to improve learning and study strategies. Students who perform poorly in a conventional educational setting may suffer from a mismatch of learning and teaching styles; for example kinesthetic learners may not adapt to learning by listening or by reading. When we teach tactual and/or kinesthetic students by talking, they focus for only a brief amount of time and then wander off into their own thoughts and quickly forget (Burke & Dunn, 2002). We can improve students’ academic performance by providing them with alternative strategies and activities that respond to their learning style needs (Dunn & Dunn, 1993). In spring 2008, the learning styles of over 700 Zayed University students were assessed using the BE (Building Excellence) survey developed by Rundle & Dunn. The data collected is being analyzed with a view to making recommendations for teachers, students and parents to improve students’ learning. This paper represents the first in a series of publications on this subject; it reviews the survey process, and focuses on the nature and learning preferences of ZU students in perceptual elements (e.g. visual, auditory) and cognitive elements (e.g. Analytic-sequential (left-brain) vs. Global-simultaneous (right-brain) preferences).