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The purpose of this paper is to investigate the effect of family control on the association between related party transactions (RPTs) and different forms of accrual-based earnings management (AEM) and real earnings management (REM), analyzing the effect of board characteristics on the possible association.

This paper studies a sample of Italian non-financial listed firms over the 2014–2019 period, by GLS regression models, controlling for the fixed effects of the company's sector of operation and the year.

Results indicate a different association between RPTs and earnings management (EM) in family and non-family firms. They point out that family firms use RPTs in association with downward AEM and REM perpetrated by abnormal discretionary expenses as well as a substitute of REM via abnormal production costs. For non-family firms, findings indicate only a substitution effect between RPTs and AEM. Furthermore, CEO duality, board gender diversity and the presence of the family on the board positively moderate the association between RPTs and, respectively, REM implemented through sales manipulations, downward AEM and upward AEM.

This study suggests that the socioemotional wealth (SEW) differently affects the relationship between RPTs and EM, according to the form of the latter. It also points out family firms' heterogeneity in earnings manipulations, by providing evidence of the moderating role of board characteristics on the association between RPTs and the various forms of EM.

This study aims to explore how the integration of augmented reality (AR) filters into English as a second language (ESL) can enhance speaking fluency teaching. The study sheds light on how AR filter can be best implemented in speaking fluency teaching by the innovative opportunities to transform language learning experiences. In this study, ESL teachers' perceptions and experiences with AR filters in speaking fluency instructions were examined through qualitative research method.

This study is an evaluation stage study within a bigger study which utilized design and developmental research (DDR) approach. In this third phase of DDR which is the evaluation phase, this study involved semi-structured interviews with six ESL teachers from six different public secondary school settings. Thematic analysis was conducted on the interview transcripts.

Data analysis revealed several key findings regarding the utilization of AR filters in ESL speaking fluency teaching. Firstly, participants reported that AR filters can be best used in various educational settings. Secondly, AR filters were found to provide supports for various students’ levels. Thirdly, participants identified that AR filters can be best used to cater students with diverse learning styles.

The work aims to help ESL educators in using AR filters in their speaking fluency teaching. The limitation of this study is that it includes only the experience of teachers from a public secondary school setting without taking into consideration other secondary institutions such as ESL teachers from private schools or boarding schools. The generalizability of our findings may be affected due to our reliance on self-reported data from a small sample size.

The implications of these findings for ESL pedagogy and teacher professional development are discussed. By incorporating AR filters into ESL speaking fluency instruction, educators can create speaking fluency teaching in various settings such as formal and informal settings. Furthermore, ESL teachers may immerse students in environments that cater to the diverse language learners' styles and language levels through the use of AR filter. Overall, this research contributes to a deeper understanding of the potential of AR filters to transform ESL teaching and learning practices, paving the way for future innovations in language education.

Available studies exploring AR in English teaching exist, but very limited of those utilized markerless AR, in the form of AR filters with speaking fluency teaching. Also, this paper focused on teachers’ experience with AR filters in contrast to students’ experience in public secondary school settings.

Governments around the world instituted guidelines for calculating energy efficiency of vehicles not only by models, but by the whole universe of new vehicles registered. This paper compiles Multi-criteria decision-making (MCDM) studies related to automotive industry. We applied a Systematic Literature Review on MCDM studies published until 2015 to identify patterns on MCDM applications to design vehicles more fuel efficient in order to achieve full compliance with energy efficiency guidelines (e.g., Inovar-Auto). From 339 papers, 45 papers have been identified as describing some MCDM technique and correlation to automotive industry. We classified the most common MCDM technique and application in the automotive industry. Integrated approaches were more usual than individual ones. Application of fuzzy methods to tackle uncertainties in the data was also observed. Despite the maturity in the use of MCDM in several areas of knowledge, and intensive use in the automotive industry, none of them are directly linked to car design for energy efficiency. Analytic Hierarchy Process was identified as the common technique applied in the automotive industry.