ChatGPT, a language-learning model chatbot, has garnered considerable attention for its ability to respond to users’ questions. Using data from 14 countries and 186 institutions, we compare ChatGPT and student performance for 28,085 questions from accounting assessments and textbook test banks. As of January 2023, ChatGPT provides correct answers for 56.5 percent of questions and partially correct answers for an additional 9.4 percent of questions. When considering point values for questions, students significantly outperform ChatGPT with a 76.7 percent average on assessments compared to 47.5 percent for ChatGPT if no partial credit is awarded and 56.5 percent if partial credit is awarded. Still, ChatGPT performs better than the student average for 15.8 percent of assessments when we include partial credit. We provide evidence of how ChatGPT performs on different question types, accounting topics, class levels, open/closed assessments, and test bank questions. We also discuss implications for accounting education and research.

This paper aims to discuss the current state of Google Trends as a useful tool for fashion consumer analytics, show the importance of being able to forecast fashion consumer trends and then presents a univariate forecast evaluation of fashion consumer Google Trends to motivate more academic research in this subject area. Using Burberry—a British luxury fashion house—as an example, we compare several parametric and nonparametric forecasting techniques to determine the best univariate forecasting model for “Burberry” Google Trends. In addition, we also introduce singular spectrum analysis as a useful tool for denoising fashion consumer Google Trends and apply a recently developed hybrid neural network model to generate forecasts. Our initial results indicate that there is no single univariate model (out of ARIMA, exponential smoothing, TBATS, and neural network autoregression) that can provide the best forecast of fashion consumer Google Trends for Burberry across all horizons. In fact, we find neural network autoregression (NNAR) to be the worst contender. We then seek to improve the accuracy of NNAR forecasts for fashion consumer Google Trends via the introduction of singular spectrum analysis for noise reduction in fashion data. The hybrid neural network model (Denoised NNAR) succeeds in outperforming all competing models across all horizons, with a majority of statistically significant outcomes at providing the best forecast for Burberry’s highly seasonal fashion consumer Google Trends. In an era of big data, we show the usefulness of Google Trends, denoising and forecasting consumer behaviour for the fashion industry.

This study provides an exploratory bibliometric analysis of the emerging literature on Industry 5.0, which is a new visionary concept on the future of industry. Industry 5.0 has in recent years begun to attract the interest of both practitioners and academics, but this new field can still be considered embryonic and not well documented. Therefore, this study aims to map the field and provide a preliminary picture of the emergence and status of the scientific literature on Industry 5.0. Bibliometric data covering the period from 2015 to 2021 were extracted from the Scopus database. Bibliometric analyses of overall publication volume and growth trajectory, influential documents, authors, sources and countries are performed. The exploratory analysis provides a preliminary overview of the birth and emergence of this new research area. The results are discussed in relation to theories on the emergence and evolution of new management concepts. The article closes with some speculations about the future trajectory of Industry 5.0.

The Industry 4.0 (I4.0) concept is concerned with the fourth industrial revolution in manufacturing, in which technological trends such as digitalization, automation and artificial intelligence are transforming production processes. Since the concept’s introduction at the Hannover Fair in Germany in 2011, I4.0 has enjoyed a meteoric rise in popularity and is currently high on the agenda of governments, politicians and business elites. In light of these observations, some commentators have asked the question of whether I4.0 is a concept that is hyped up and possibly just the latest in a long line of fashionable management concepts introduced over the course of the last few decades. Therefore, the aim of this paper is to provide a critical outside-in look at the emergence and rise of I4.0. Theoretically, these processes are viewed through the lens of management fashion, a theoretical perspective well suited to examinations of evolutionary trajectories of management concepts and ideas. The findings indicate that the I4.0 concept has quickly become highly popular and is dominating much of the popular management discourse. The concept has migrated out of the specialized manufacturing discourse to become a more general concept with mainstream appeal and applicability, evidenced by a multitude of neologisms such as Work 4.0 and Innovation 4.0. The numbers 4.0 have spread in a meme-like fashion, evidenced by the fact that the combination of a noun and the numbers 4.0 are used to signal and usher in discussions about the future of business and society. While there is much evidence that clearly shows that the concept has had a wide-ranging impact at the discursive level, the currently available research is less clear about what impact the concept has had so far on industries and organizations worldwide.

HACCP (Hazard Analysis and Critical Control Points) and modern quality management systems have a significant impact on public health in the food industry. These systems ensure that food products are safe for consumption by identifying and managing potential hazards at every stage of the production process. To stimulate ongoing studies in both developing and underexplored areas of inquiry, this research synthesizes and organizes the contributions made in this field. It examines more than 40 years of studies from Scopus data base on HACCP and modern quality management systems in the food industry using the VOSviewer software version 1.6.18 (Leiden University, The Netherlands) and bibliometrix R-package. This represents, to the authors’ knowledge, the first bibliometric analysis undergone in this direction. The graphical framework demonstrates the highest developments in research and the literature review investigates barriers and opportunities of implementing HACCP in food industry organizations. Findings indicate that until the beginning of the 1990s, there was not a large number of scientific production in the field of HACCP and modern quality management systems in the food industry. The USA were the most prolific affiliation terms of scientific production until 2012, when studies from Italy, the United Kingdom, China and Greece intensified. Currently, the most prolific country in terms of publications is Italy. In terms of global cooperation, the United Kingdom, The United States and The Netherlands represent most active nations on this topic Motor themes that reflect the main interest of the researchers include food diseases, quality control, hazards or food supply. The study also provides future research directions regarding food quality and safety management. These should be focused on improving the safety, quality, and sustainability of food products, while also adapting to changing consumer demands, emerging risks, and regulatory requirements.