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The number of participants in accounting practices and academia who use English as their second language is significant and growing. Many of them are involved in making ethical judgements based on information provided in English, which is their second language. It is important to know the effect of the second language on their ethical judgement. In this study, using 211 undergraduate accounting students whose native language is Arabic from an Association to Advance Collegiate Schools of Business (AACSB) accredited business school located in the Middle East, we test the effect of second language use on ethical judgement. We find that the ethical judgement is significantly better when the ethical dilemmas are presented in the participants' native language (Arabic) compared to when the same dilemmas are presented their second language (English). The results hold true in both within and between subject designs. Implications are discussed.

Artificial intelligence (AI) has become omnipotent with its variety of applications and advantages. Considering the other side of the coin, the eruption of technology has created situations that need more caution about the safety and security of data and systems at all levels. Thus, to hedge against the growing threats of cybersecurity, the need for a robust AI platform supported by machine learning and other supportive technologies is well recognized by organizations. AI is a much sought-after topic, and there is extolling literature available in repositories. Hence, a systematic arrangement of the literature that can help identify the right AI platform that can provide identity governance and access control is the need of the hour. Having this background, the present study is commissioned a Systematic Literature Review (SLR) to accomplish the necessity. Literature related to AI and Identity and Access Management (IAM) is collected from renowned peer-reviewed digital libraries for systematic analysis and assessment purposes using the systematic review guidelines. Thus, the final list of articles relevant to the framed research questions related to the study topic is fetched and is reviewed thoroughly. For the proposed systematic research work, the literature reported during the period ranging from 2016 to 2021 (a portion of 2021 is included) is analyzed and a total of 43 papers were depicted more relevant to the selected research domain. These articles were accumulated from ProQuest, Scopus, Taylor & Franics, Science Direct, and Wiley online repositories. The article's contribution can supplement the AI-based IAM information and steer the entities of diverse sectors concerning seamless implementation. Appropriate suggestions are proposed to encourage research work in the required fields.

This research attempted to contribute to the development of knowledge within the domain of perceptions of internal audit quality, especially in U.K. private sector firms under Total Quality Management (TQM) regimes utilizing U.K. internal audit standards. The determinants of TQM include continuous improvement, empowerment & teamwork and customer satisfaction. Different analytical and statistical techniques (e.g. rating and ranking, validity as correlations and factor analysis) were utilized. The research found that Auditees perceive 'continuous improvement' of the whole organization as an essential quality factor of the internal audit. In addition, both groups of the internal auditors and auditees value customer satisfaction the same. The important implication of the study is that Auditees welcome a closer involvement in the whole of the internal audit process.

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