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This study aimed to evaluate the potential of artificial intelligence (AI) as a tool for knowledge synthesis, the production of written content and the delivery of coaching conversations.

The research employed the use of experts to evaluate the outputs from ChatGPT's AI tool in blind tests to review the accuracy and value of outcomes for written content and for coaching conversations.

The results from these tasks indicate that there is a significant gap between comparative search tools such as Google Scholar, specialist online discovery tools (EBSCO and PsycNet) and GPT-4's performance. GPT-4 lacks the accuracy and detail which can be found through other tools, although the material produced has strong face validity. It argues organisations, academic institutions and training providers should put in place policies regarding the use of such tools, and professional bodies should amend ethical codes of practice to reduce the risks of false claims being used in published work.

This is the first research paper to evaluate the current potential of generative AI tools for research, knowledge curation and coaching conversations.

The objective of this research is to investigate the capabilities of the ChatGPT GPT-4 model, a form of artificial intelligence (AI), in comparison to human experts in the context of construction project risk management.

Employing a mixed-methods approach, the study draws a qualitative and quantitative comparison between 16 human risk management experts from Finnish construction companies and the ChatGPT AI model utilizing anonymous peer reviews. It focuses primarily on the areas of risk identification, analysis, and control.

ChatGPT has demonstrated a superior ability to generate comprehensive risk management plans, with its quantitative scores significantly surpassing the human average. Nonetheless, the AI model's strategies are found to lack practicality and specificity, areas where human expertise excels.

This study marks a significant advancement in construction project risk management research by conducting a pioneering blind-review study that assesses the capabilities of the advanced AI model, GPT-4, against those of human experts. Emphasizing the evolution from earlier GPT models, this research not only underscores the innovative application of ChatGPT-4 but also the critical role of anonymized peer evaluations in enhancing the objectivity of findings. It illuminates the synergistic potential of AI and human expertise, advocating for a collaborative model where AI serves as an augmentative tool, thereby optimizing human performance in identifying and managing risks.

The purpose of this paper is to examine and compare the in situ place experiences of people in Luton and Darlington.

The study used 109,998 geotagged tweets from Luton and Darlington between 2020 and 2022 and conducted topic modelling using latent Dirichlet allocation. Lexicons were created using GPT-4 to evaluate the eight dimensions of place experience for each topic.

The study found that Darlington had higher counts in the sensorial, behavioural, designed and mundane dimensions of place experience than Luton. Conversely, Luton had a higher prevalence of the affective and intellectual dimensions, attributed to political and faith-related tweets.

The study introduces a novel approach that uses AI-generated lexicons for place experience. These lexicons cover four facets, two intentions and two intensities of place experience, enabling detection of words from any domain. This approach can be useful not only for town and destination brand managers but also for researchers in any field.

This qualitative work aims to explore the university students’ attitude toward advantages, drawbacks and prospects of ChatGPT.

This paper applies well accepted Colaizzi’s phenomenological descriptive method of enquiry and content analysis method to reveal the ChatGPT user experience of students in the higher education level.

The study’s findings indicate that ChatGPT enhances the quality of learning and facilitates faster learning among university students. However, despite numerous positive outcomes, it is noted that ChatGPT may diminish students' creativity by swiftly addressing their critical queries. Over time, students may experience a decline in patience and critical thinking skills as they excessively rely on ChatGPT, potentially leading to ethical misconduct.

This paper primarily explores the advantages and drawbacks of using ChatGPT in the university context of Bangladesh. The present study creates a platform for future research in this domain with comprehensive study design. The study results alert the policy makers to improve upcoming version of ChatGPT with convenient user experience and academicians as this paper unleash several positive as well as negative consequences of using this AI-enabled chatbot.

This paper aims to provide a comprehensive analysis of the transformative impact of Artificial Intelligence (AI) and Large Language Models (LLMs), such as GPT-4, on the real estate industry. It explores how these technologies are reshaping various aspects of the sector, from market analysis and valuation to customer interactions and evaluates the balance between technological efficiency and the preservation of human elements in business.

The study is based on an analysis of the strengths and weaknesses of AI as a technology in applications for real estate. It uses this framework to assess the potential of this technology in different use cases. This is supplemented by an emerging literature on the topic, practical insights and industry expert opinions to provide a balanced perspective on the subject.

The paper reveals that AI and LLMs offer significant benefits in real estate, including enhanced data-driven decision-making, predictive analytics and operational efficiency. However, it also uncovers critical challenges, such as potential biases in AI algorithms and the risk of depersonalising customer interactions.

The paper advocates for a balanced approach to adopting AI, emphasising the importance of understanding its strengths and limitations while ensuring ethical usage in the diverse and complex landscape of real estate.

This work stands out for its balanced examination of both the advantages and limitations of AI in real estate. It introduces the novel concept of the “jagged technological frontier” in real estate, providing a unique framework for understanding the interplay between AI and human expertise in the industry.

This chapter critically examines whether it may be possible to create an AI-based authentic leader, questioning the inherent contradiction between artificial and authentic. The authors pose central research questions: Does the application of AI – even just as a powerful resource – challenge the tenets of authentic leadership? What are the possibilities and limitations of the concept of authenticity in AI-based management systems? Moreover, with the help of three vignettes illustrating practical applications of AI-based systems in leadership and management tasks, the authors illustrate how technology may be used to either control or empower workers and leaders. The authors call for research to assess whether the search for authenticity in AI-based leadership could lead anywhere, warning that it could entrap us in unresolvable existential and conceptual ambiguity, ultimately diverting our focus from the essence of leadership altogether.

In this study, the author examines the effect of managers’ perception of product market competition on accruals and real earnings management.

The author develops a new text-based measure of the emphasis managers place on product market competition by conducting a textual analysis of firms’ 10-K filings. Using this measure, the author conducts a battery of econometric analyses and robustness checks to investigate the impact of this measure of product market competition on measures of accruals and real earnings management.

This study finds robust evidence that when management perceives more competitive threats, they are more likely to engage in accruals-based earnings manipulation but are less likely to engage in real earnings management activity. The author argues that these findings are due to managers’ career concerns enticing them to manage earnings via accrual when competition is high, but that greater product market competition discourages real earning management activity as it can diminish firms’ competitiveness.

The findings of this paper have important policy and practical implications since it signals that managers’ perceptions of product market competition is able to affect accounting choices, information environments and economic outcomes in firms.

This study develops a new text-based measure of managers’ perception of product market competition with the aid of GPT-4. The author then using this measure provides firm-level evidence on how this relates to earnings management.

This study examines the impact of generative artificial intelligence (GenAI), particularly ChatGPT, on higher education (HE). The ease with which content can be generated using GenAI has raised concerns across academia regarding its role in academic contexts, particularly regarding summative assessments. This research makes a unique contribution to the literature by examining university student and staff perceptions of current and future issues pertaining to the role of GenAI in universities.

A qualitative method involving five one-to-one semi-structured interviews with four students and a lecturer explored the ethical and practical issues of GenAI text generation in academia. An inductive thematic analysis was chosen as it provided nuanced insights aligned with the study’s goals.

Use of GenAI was discussed within the context of a range of topics, including perceptions of academic misconduct, authorial integrity and issues pertaining to university policies. Participants universally defined traditional classifications of academic misconduct but were unable to provide clear definitions where the use of GenAI was included for writing summative assessments. Students showed a more open engagement with GenAI, considering it a tool for overcoming obstacles rather than a means to plagiarise. Educators were generally more cautious and less optimistic about the academic role of GenAI. Lack of clear institutional policies surrounding such tools also contributed to ethical ambiguities.

The study highlights diverging perspectives between students and academics, which necessitate a forum for dialogue, ensuring the need to develop clear policies to steer the integration of GenAI in a manner that is beneficial for students and academics.