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The aim of this paper is to explore the behavior pattern, perceptions, and motivations of students towards academic misconduct in a Business School with a view to mitigating its occurrence.

The survey was conducted among a batch of undergraduate students who responded to various dimensions of plagiarism through a structured questionnaire. Responses were measured on a Likert scale. Some non-parametric tests were done for statistical analysis.

From the perception of the prevalence of plagiarism committed by others, the authors found that the majority tend to believe that it happens in spite of the existence of preventive policies. Based on the findings, the authors conclude that the students who are more prone to cheating/plagiarism are male, with low grade point average, and are not on scholarship. Parental disapproval is found to be one of the dominant deterrent factors that have the potential to restrain unethical behavior.

The findings demonstrate that the managers of graduate programs should include parental roles in the deterrent mechanism to improve the quality of education.

Very little evidence exists about the perception of academic dishonesty among the students of a multicultural academic institution located in a middle-east country. There are not many studies that analyze the effectiveness of deterrents from a student’s perspective. In this paper, the authors have attempted to assess the value of various deterrents and their effectiveness as perceived by the students.

This study aims to explore the factors that contribute to student academic dishonesty through an examination of the misuse of AI language models. Using the fraud triangle theory, which posits that opportunity, rationalization and pressure are key factors for fraudulent behavior, this study investigates how these elements interact and contribute to academic dishonesty among students.

In this study, data on how accounting students used ChatGPT to cheat was acquired from 279 accounting students in Jordanian public universities over the course of two months, from January 2023 to March 2023, through previously tested and validated questionnaires. The main tool for gathering data was a questionnaire distributed online using Microsoft Forms.

The results show that all of the fraud triangle factors are significant determinants of student academic dishonesty and student misuse of ChatGPT. The findings of this research can be used to guide the development of technology-based preventative measures.

This study provides valuable insights into the motivations and factors that drive students to engage in academic dishonesty and sheds light on the broader issue of technology-assisted academic dishonesty and its impact on the educational system. This study’s contribution is significant, as it sheds light on a pressing issue in education and provides valuable information for educators and policymakers to address the problem and improve academic standards.

The use of generative artificial intelligence (genAi) language models such as ChatGPT to write assignment text is well established. This paper aims to assess to what extent genAi can be used to obtain guidance on how to avoid detection when commissioning and submitting contract-written assignments and how workable the offered solutions are.

Although ChatGPT is programmed not to provide answers that are unethical or that may cause harm to people, ChatGPT’s can be prompted to answer with inverted moral valence, thereby supplying unethical answers. The authors tasked ChatGPT to generate 30 essays that discussed the benefits of submitting contract-written undergraduate assignments and outline the best ways of avoiding detection. The authors scored the likelihood that ChatGPT’s suggestions would be successful in avoiding detection by markers when submitting contract-written work.

While the majority of suggested strategies had a low chance of escaping detection, recommendations related to obscuring plagiarism and content blending as well as techniques related to distraction have a higher probability of remaining undetected. The authors conclude that ChatGPT can be used with success as a brainstorming tool to provide cheating advice, but that its success depends on the vigilance of the assignment markers and the cheating student’s ability to distinguish between genuinely viable options and those that appear to be workable but are not.

This paper is a novel application of making ChatGPT answer with inverted moral valence, simulating queries by students who may be intent on escaping detection when committing academic misconduct.

This study aims to address a systematic literature review (SLR) using bibliometrics on the relationship between academic integrity and artificial intelligence (AI), to bridge the scattering of literature on this topic, given the challenge and opportunity for the educational and academic community.

This review highlights the enormous social influence of COVID-19 by mapping the extensive yet distinct and fragmented literature in AI and academic integrity fields. Based on 163 publications from the Web of Science, this paper offers a framework summarising the balance between AI and academic integrity.

With the rapid advancement of technology, AI tools have exponentially developed that threaten to destroy students' academic integrity in higher education. Despite this significant interest, there is a dearth of academic literature on how AI can help in academic integrity. Therefore, this paper distinguishes two significant thematical patterns: academic integrity and negative predictors of academic integrity.

This study also presents several contributions by showing that tools associated with AI can act as detectors of students who plagiarise. That is, they can be useful in identifying students with fraudulent behaviour. Therefore, it will require a combined effort of public, private academic and educational institutions and the society with affordable policies.

This study proposes a new, innovative framework summarising the balance between AI and academic integrity.

This study aims to investigate the situational factors that intensify the impact of leader bottom-line mentality (BLM) on employee pro-self-unethical behavior. In particular, the moderating role of contingent rewards and punishments is evaluated under the lens of situational strength theory.

Data were collected from 218 full-time employees working in the USA in a time-lagged study and analyzed using SPSS Process Macro.

Statistical analysis reveal contingent rewards and punishments significantly moderate the positive relationship between BLM and pro-self-unethical behavior.

This paper highlights the need for more balanced reward systems that incorporate moral conduct into work performance. It also emphasizes the role of robust accountability and monitoring systems in minimizing employees’ unethical behavior.

To the best of the authors’ knowledge, this is the first study to investigate the moderating role of contingent rewards and punishments on the relationship between leader BLM and subordinate pro-self-unethical behavior. Moreover, it provides significant empirical support to situational strength theory.

The study is aimed at analyzing the perceptions of students and teachers regarding the effectiveness of massive open online courses (MOOCs) on learning efficiency of students and also evaluating MOOCs as an ideal tool for designing a blended model for education.

The analysis was carried out by using the data gathered from the students as well as teachers of University of Mysore, Karnataka, India. Two separate sets of questionnaires were developed for both the categories of respondents. Also, the respondents were required to have prior experience in MOOCs. Further, the collected data was analyzed using statistical package for social sciences (SPSS).

The study showed that MOOCs have a more positive influence on learning efficiency, as opined by both teachers and students. Negative views such as cheating during the assessment, lack of individual attention to students and low teacher-student ratio were also observed.

Many educational institutions view that the MOOCs do not influence learning efficiency and also do not support in achieving their vision. However, this study provides evidence that MOOCs are positively influencing the learning efficiency and also can be employed in a blended model of education so as to promote collaborative learning.

Technology is playing a pivotal role in all fields of life and the education sector is not an exception. It can be rightly said that the technology-based education models such as MOOCs are the need of the hour. This study may help higher education institutions to adopt MOOCs as part of their blended model of education, and, if already adopted, the outcome of the present study will help them to improve the effectiveness of the MOOCs they are offering.

Because of the various advantages of reinforcement learning (RL) mentioned above, this study uses RL to train unmanned aerial vehicles to perform two tasks: target search and cooperative obstacle avoidance.

This study draws inspiration from the recurrent state-space model and recurrent models (RPM) to propose a simpler yet highly effective model called the unmanned aerial vehicles prediction model (UAVPM). The main objective is to assist in training the UAV representation model with a recurrent neural network, using the soft actor-critic algorithm.

This study proposes a generalized actor-critic framework consisting of three modules: representation, policy and value. This architecture serves as the foundation for training UAVPM. This study proposes the UAVPM, which is designed to aid in training the recurrent representation using the transition model, reward recovery model and observation recovery model. Unlike traditional approaches reliant solely on reward signals, RPM incorporates temporal information. In addition, it allows the inclusion of extra knowledge or information from virtual training environments. This study designs UAV target search and UAV cooperative obstacle avoidance tasks. The algorithm outperforms baselines in these two environments.

It is important to note that UAVPM does not play a role in the inference phase. This means that the representation model and policy remain independent of UAVPM. Consequently, this study can introduce additional “cheating” information from virtual training environments to guide the UAV representation without concerns about its real-world existence. By leveraging historical information more effectively, this study enhances UAVs’ decision-making abilities, thus improving the performance of both tasks at hand.

The role of academic libraries in dissemination of information and facilitating research of academic community is well-established world over. However, a significant role of libraries in ensuring fair use of information to promote an ethical research culture at the higher education institutes is also flourishing. This study aims to explore the perceived causes of unethical use of literature by university scholars and deterrents to plagiarism in universities of Pakistan.

The design of the study was qualitative, and interviews were conducted on nine university library heads in Pakistan who were officially administrating anti-plagiarism (Turnitin) software service at their universities and were providing “similarity index certification” of PhD and MPhil research work through the software. They were purposively selected for the interviews because of their direct interaction with the researchers and faculty on matters of information searching as well as its ethical use. The study is based on PhD thesis work of the first author.

The findings of the study depicted that conceptual unawareness of plagiarism, lack of information skills, socio-cultural factors and weak policies were the prime reasons for unethical research practices among graduate scholars. Participants were positive that a role of university library in combating plagiarism through provision of anti-plagiarism software and guidance could prove more beneficial for both the researchers and libraries.

Multiple studies have been conducted, in and out of south Asian region, to gather the views of the students and faculty on the matters of academic misconduct. However, no study was found presenting the views of the other stakeholders in promotion of academic integrity. To the best of the authors’ knowledge, this study is first of its kind in South Asian context and provided observation-based views of a group of university library heads who are also administrating anti-plagiarism service in their universities on the causes and deterrents to plagiarism.

In recent years, negative spokesperson incidents have raised significant concerns in academia and industry. While several studies have addressed celebrity endorser scandals, comprehensive analyses of current knowledge are lacking. Therefore, this study systematically reviewed the related literature to better understand trends and suggest future research directions for advancing this field.

This study employs the theory–context–characteristics–methodology (TCCM) framework to examine 76 articles on celebrity endorser scandals.

Utilizing the TCCM framework, this study presents a comprehensive research framework, revealing that (1) the celebrity endorser scandal effect primarily includes associative learning, attribution of responsibility, and moral reasoning; (2) entertainment celebrities and athletes have received significant research attention; (3) both individual- and relationship-level characteristics serve as crucial moderators, with focal brand and related brand being the primary outcome variables. Additionally, this study outlines enterprise response strategies, encompassing the reformation of existing spokesperson relationships and the establishment of future spokesperson connections; and (4) quantitative approaches dominate the field.

This study integrates and expands existing research on celebrity endorser scandals while proposing future research opportunities to advance the field.

The purpose of this study is to propose a world-class good governance ethics framework that leads to better corporate performance. ethics among managers, executives and members of the board of directors working in public-listed companies brings grave concern because of the increasing number of criminal acts reported by the Security Commission of Malaysia.

This study introduces a world-class good governance ethics framework for curbing criminal acts in public-listed companies in Malaysia. This study used a mixed method to gather data, and the methods used are appropriate for answering the research questions based on the World-Class Good Governance Ethics framework.

The finding of this study reveals high expectations for a corporate organization to improve individual and team performance while undertaking their corporate responsibilities, and a matter of choice, to adopt world-class good governance ethics in their policies and practices.

This study could be a reference for corporate management to regulate policies monitoring management's and employees' conduct at the workplace. This study's theoretical and practical significance would guide the stakeholders in corporate management to regulate governance policies based on the right ethical values and promote personalities with high integrity in management conduct.

This study promotes a world-class good governance ethics framework in curbing criminal acts for better corporate performance. This new framework is formulated based on the concept of a caliph and other essential elements envisaged by the Quranic verses.