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Welcome to the Era of ChatGPT et al.: The Prospects of Large Language Models
Open accessAbstract
The emergence of Large Language Models (LLMs) in combination with easy-to-use interfaces such as ChatGPT, Bing Chat, and Google’s Bard represent both a Herculean task and a sublime opportunity for Business and Information Systems Engineering . The technology and its applications already have considerable impact in many domains directly related to the design, operation, and application of information systems. In this editorial, we seek to explore this new reality as researchers, practitioners, and legislators will – in some form or another – have to deal with it. Our goal is to provide insights and encourage research in this new, exciting, and rapidly developing field.
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In the citing paper
“Assessment and evaluation emerged as the primary pattern, with faculty using GenAI to generate NCLEX-style questions and provide automated student feedback”
From Patterns, advances, and gaps in using ChatGPT and similar technologies in nursing education: A PAGER scoping review (2025) · cites this paper as Teubner et al., 2023
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“In line with scholars such as Teubner et al. (2023), experts in our study voiced concerns that ChatGPT and other LLMs have the potential to widen the digital divide between researchers who possess technical know-how and researchers who do not.”
From Friend or foe? Exploring the implications of large language models on the science system (2025) · cites this paper as Teubner et al. (2023)
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Citations
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Feuerriegel, S., Hartmann, J., Janiesch, C., & Zschech, P. (2024) · Business & Information Systems Engineering · doi:10.1007/s12599-023-00834-7 · Cited by 2,267
Generative artificial intelligence
Banh, L., & Strobel, G. (2023) · Electronic Markets · doi:10.1007/s12525-023-00680-1 · Cited by 879
“Closing with the initial quote by ChatGPT, generative AI indeed holds transformative the potential to redefine innovation boundaries of the digital landscapes.”
BackgroundInfluentialWach, K., Duong, C. D., Ejdys, J., Kazlauskaitė, R., Korzynski, P., Mazurek, G., Paliszkiewicz, J., & Ziemba, E. (2023) · Entrepreneurial Business and Economics Review · doi:10.15678/eber.2023.110201 · Cited by 584
“Finally, the unregulated AI market might lead to legal ambiguities related to ownership, privacy, and intellectual property rights (Teubner et al. , 2023).”
BackgroundStrzelecki, A. (2024) · Innovative Higher Education · doi:10.1007/s10755-023-09686-1 · Cited by 477
“ChatGPT in university education presents challenges to the academic community wherever ChatGPT is available (Teubner et al., 2023).”
Bozkurt, A., Xiao, J., Farrow, R., Bai, J. Y. H., Nerantzi, C., Moore, S. L., Dron, J., Stracke, C. M., Singh, L., Crompton, H., et al. (2024) · Open Praxis · doi:10.55982/openpraxis.16.4.777 · Cited by 320
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“Hence, ChatGPT, built on the GPT-4 framework, became the internet’s trendiest topic at the end of 2022 and entrenched itself as a ‘ cultural phenomenon ’ (Thorp, 2023).”
BackgroundJanson, A. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107954 · Cited by 187
“…to the recent development in AI and algorithms, such as transformer-based models in chatbots like ChatGPT (Dwivedi et al., 2023; Haque et al., 2022; Teubner et al., 2023), that are able to resemble more empathic and social conversations with users, additional rich appearances such as 3D-animated…”
MethodTemsah, M.-H., Aljamaan, F., Malki, K. H., Alhasan, K., Altamimi, I., Aljarbou, R., Bazuhair, F., Alsubaihin, A., Abdulmajeed, N., Alshahrani, F. S., et al. (2023) · Healthcare · doi:10.3390/healthcare11131812 · Cited by 179
Harnessing the power of AI in qualitative research: Exploring, using and redesigning ChatGPT
Zhang, H., Wu, C., Xie, J., Lyu, Y., Cai, J., & Carroll, J. M. (2025) · Computers in Human Behavior Artificial Humans · doi:10.1016/j.chbah.2025.100144 · Cited by 357
“ChatGPT, an advanced language model developed by OpenAI, has been recognized for its versatility across a wide range of language tasks, making it a powerful tool for various applications [4, 92].”
Wang, M., Wang, M., Xu, X., Yang, L., Cai, D., & Yin, M. (2023) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2023.3324714 · Cited by 199
“ChatGPT has attracted an impressive 100 million active users in a mere two months since its inception [34].”
BackgroundGhafarollahi, A., & Buehler, M. J. (2024) · Advanced Materials · doi:10.1002/adma.202413523 · Cited by 330
ChatGPT: Challenges and Benefits in Software Programming for Higher Education
da Silva, C. A. G., Ramos, F. N., de Moraes, R. V., & dos Santos, E. L. (2024) · Sustainability · doi:10.3390/su16031245 · Cited by 196
Σιγάλα, Μ., Ooi, K., Tan, G. W., Aw, E. C., Buhalis, D., Cham, T., Chen, M.-M., Dwivedi, Y. K., Ulrike Gretzel, B., Inversini, A., et al. (2024) · Journal of Hospitality and Tourism Management · doi:10.1016/j.jhtm.2024.08.004 · Cited by 165
ChatGPT: ethical concerns and challenges in academics and research
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“ChatGPT is an artificial intelligence powered conversational chatbot variation of GPT-3 and a 175 billion parameter large language model (LLM) trained on 570 GB data including Wikipedia, books, news and journal articles, blogs and other web sources available on the internet until 2021 [6].”
BackgroundLarge Language Models for Business Process Management: Opportunities and Challenges
Vidgof, M., Bachhofner, S., & Mendling, J. (2023) · Lecture notes in business information processing · doi:10.1007/978-3-031-41623-1_7 · Cited by 168
Large Language Models Can Accomplish Business Process Management Tasks
Grohs, M., Abb, L., Elsayed, N., & Rehse, J.-R. (2024) · Lecture notes in business information processing · doi:10.1007/978-3-031-50974-2_34 · Cited by 119
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Generative Artificial Intelligence in Education, Part One: the Dynamic Frontier
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“One prominent GenAI example, ChatGPT, gained immense popularity since its public release in November 2022, attracting 1 million users within 5 days (Chartr, 2022) and reaching 100 million users in just two months (Teubner et al., 2023).”
BackgroundSchneider, J., Meske, C., & Kuss, P. (2024) · Business & Information Systems Engineering · doi:10.1007/s12599-024-00851-0 · Cited by 145
“Through this pre-train and adapt approach they expedite the development of innovative AI products and services and accelerate the accessibility of high-performance AI solutions in various industries (Teubner et al. 2023).”
Artificial Intelligence (AI) Chatbots in Medicine: A Supplement, Not a Substitute
Altamimi, I., Altamimi, A., Alhumimidi, A. S., Altamimi, A., & Temsah, M.-H. (2023) · Cureus · doi:10.7759/cureus.40922 · Cited by 102
“Within a mere five days of its launch, ChatGPT amassed an impressive one million users, and its user base expanded to 100 million users in just two months [4].”
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Schlagwein, D., & Willcocks, L. (2023) · Journal of Information Technology · doi:10.1177/02683962231200411 · Cited by 97
“It is not emotional; it fakes emotions, etc. Generative AI provides an illustrative example of successful faking, and likely – the future will show – so do many AI many business cases (Dwivedi et al., 2023; Siegel, 2023; Teubner et al., 2023).”
InfluentialBarman, D., Guo, Z., & Conlan, O. (2024) · Machine Learning with Applications · doi:10.1016/j.mlwa.2024.100545 · Cited by 127
ChatGPT, Üretken Yapay Zeka ve Algoritmik Paradigma Değişikliği
BOZKURT, A. (2023) · Alanyazın · doi:10.59320/alanyazin.1283282 · Cited by 95
Role and Challenges of ChatGPT and Similar Generative Artificial Intelligence in Business ManagementPreprint
Rane, N. L. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4603227 · Cited by 103
Friend or foe? Exploring the implications of large language models on the science system
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“Prompt engineering, i.e., developing and producing prompts for conversational AI systems like ChatGPT, is often discussed as a new competence that is required from researchers (e.g., Teubner et al. 2023).”
InfluentialInnovating by prompting: How to facilitate innovation in the age of generative AI
Sundberg, L., & Holmström, J. (2024) · Business Horizons · doi:10.1016/j.bushor.2024.04.014 · Cited by 85
University Students’ Insights of Generative Artificial Intelligence (AI) Writing Tools
Gasaymeh, A.-M. M., Beirat, M. A., & Abu Qbeita, A. A. (2024) · Education Sciences · doi:10.3390/educsci14101062 · Cited by 74
Conversational Process Modelling: State of the Art, Applications, and Implications in Practice
Klievtsova, N., Benzin, J.-V., Kampik, T., Mangler, J., & Rinderle‐Ma, S. (2023) · Lecture notes in business information processing · doi:10.1007/978-3-031-41623-1_19 · Cited by 89
Wangsa, K., Karim, S., Gide, E., & Elkhodr, M. (2024) · Future Internet · doi:10.3390/fi16070219 · Cited by 91
“For instance, ChatGPT has been criticised for exhibiting a perceived political bias, which can distort its outputs [43].”
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Generative AIPreprint
Feuerriegel, S., Hartmann, J., Janiesch, C., & Zschech, P. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4443189 · Cited by 65
Conceptualizing generative AI as style engines: Application archetypes and implications
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Large language models reduce public knowledge sharing on online Q&A platforms
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Are Large Language Models a Threat to Digital Public Goods? Evidence from Activity on Stack Overflow
del Rio-Chanona, M., Laurentsyeva, N., & Wachs, J. (2023) · arXiv · doi:10.48550/arxiv.2307.07367 · Cited by 62
“The remarkable effectiveness of ChatGPT is reflected in its quick adoption (Teubner et al., 2023) and application across diverse fields including auditing (Gu et al.”
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Systematic literature review on bias mitigation in generative AI
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“This stage is related to the concept of prompt engineering, which involves an iterative process of improving the input to an AI tool to enhance its output [34].”
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Computer says ‘no’: Exploring systemic bias in ChatGPT using an audit approach
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“…of several large language models (LLMs), such as OpenAI’s Generative Pre-trained Transformer (GPT) or Google’s Pathways Language Model (PaLM), has recently sparked scholarly and public debate on their implications (Nature, 2023; Teubner et al., 2023; The Economist, 2023a, 2023b; Thorp, 2023).”
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Cheng, W., Zhang, Y., Zhao, X., Zeng, Z., Wang, Z., Lin, J., Guan, Q., & Yu, W. (2024) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2024.2438937 · Cited by 60
Automated safety risk management guidance enhanced by retrieval-augmented large language model
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Ai-Based Chatbot Interactions and Critical Thinking Skills: An Exploratory Study
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“Its ability to understand and generate text coherently and contextually has paved the way for a wide range of applications (Teubner et al., 2023).”
Between tech and text: the use of generative AI in Palestinian universities - a ChatGPT case study
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“Teubner et al. (2023, 98) suggest that ‘ low-effort prompts will yield low-quality results ’ .”
Peykani, P., Ramezanlou, F., Tănăsescu, C. R., & Ghanidel, S. (2025) · Applied Sciences · doi:10.3390/app15148103 · Cited by 64
AI-empowered scale development: Testing the potential of ChatGPT
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Generative AI: a double-edged sword in the cyber threat landscape
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“For example, they make use of readily available tools like ChatGPT (Teubner et al. The emergence of phishing attacks via Microsoft Teams, coupled with the application of GenAI by groups like Midnight Blizzard, represents a significant escalation in cyber threats.”
Applicability of large language models and generative models for legal case judgement summarization
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“Additionally, the recent times have seen the advent of general-domain Large language models (LLMs) which can be used for a wide variety of NLP tasks including summarization, translation, question answering, and so on [10].”
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“For instance, DL-based large language models (LLMs) such as ChatGPT [186] have demonstrated remarkable capabilities in handling SE tasks, comparable to human performance.”
BackgroundPAIGE: A generative AI-based framework for promoting assignment integrity in higher education
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“Generative AI, including revolutionary models like ChatGPT, Google Bard, and Bing Chat, represents an impressive breakthrough in artificial intelligence [1,2].”
MethodFrom assistance to reliance: Development and validation of the large language model dependence scale
Li, Z., Zhang, Z., Wang, M., & Wu, Q. (2025) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2025.102888 · Cited by 47
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“Though human feedback can be used to provide the quality of its outputs (Teubner et al., 2023), ChatGPT itself cannot distinguish between false and factual information and will often generate inaccurate data with a high degree of confidence (Metz, 2022).”
Cassinadri, G. (2024) · Philosophy & Technology · doi:10.1007/s13347-024-00701-7 · Cited by 54
“Like many other technologies and generative AI systems, ChatGPT gave rise to a problem of whether to ban this tool from school altogether, or promote, regulate, and teach its virtuous use (Teubner et al., 2023).”
BackgroundChatGPT in supply chains: exploring potential applications, benefits and challenges
Haddud, A. (2024) · Journal of Manufacturing Technology Management · doi:10.1108/jmtm-02-2024-0075 · Cited by 39
CE-CoLLM: Efficient and Adaptive Large Language Models Through Cloud-Edge Collaboration
Jin, H., & Wu, Y. (2025) · IEEE International Conference on Web Services (ICWS) · doi:10.1109/icws67624.2025.00046 · Cited by 39
“However, the common practice of deploying LLMs to the cloud suffers from several critical issues, including (1) high latency due to the inherent data transmission delay between the cloud and edge [10, 17, 64], (2) unstable responsiveness potentially attributed to unstable network connections,…”
Unraveling the landscape of large language models: a systematic review and future perspectives
Ding, Q., Ding, D., Wang, Y., Guan, C., & Ding, B. (2023) · Journal of Electronic Business & Digital Economics · doi:10.1108/jebde-08-2023-0015 · Cited by 51
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The philosophical foundations of digital twinning
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“The 20th Century saw multiple parallel developments of AI based on, for example, Turing machines, and computational complexity (Li et al., 2008), biologically inspired natural computing techniques (Worden et al., 2011), symbolic AI (Dingli and Farrugia, 2023), pattern recognition & machine learning (Bishop, 2006), and…”
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The impact of generative AI on management innovation
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ChatGPT’s applications in marketing: a topic modeling approach
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Exploring the Ethical Implications of Using Generative AI Tools in Higher Education
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“ChatGPT debuted publicly, reaching 1 million users in just five days from its launch and 100 million users in two months which set the record for the fastest-growing consumer application in history [1,2].”
Berti, A., Kourani, H., Häfke, H., Li, C.-Y., & Schuster, D. (2024) · Lecture notes in business information processing · doi:10.1007/978-3-031-61007-3_2 · Cited by 38
“Recently, LLMs have emerged as conversational interfaces trained on extensive data [33], achieving near-human performance in various general tasks [45].”
BackgroundLee, J., Jung, W., & Baek, S. (2024) · Applied Sciences · doi:10.3390/app14052096 · Cited by 36
Saleh, Y., Talib, M. W. A., Nasir, Q., & Dakalbab, F. M. (2025) · Frontiers in Computer Science · doi:10.3389/fcomp.2025.1523699 · Cited by 46
Tuning Machine Learning to Address Process Mining Requirements
Ceravolo, P., Barbon, S., Damiani, E., & van der Aalst, W. M. P. (2024) · IEEE Access · doi:10.1109/access.2024.3361650 · Cited by 33
“Currently, there is a notable focus on leveraging Large Language Models (LLM) to seamlessly interface PM algorithms with natural language [5], [6], [7], as illustrated in point (3) of Figure 1.”
BackgroundTowards human-AI collaborative urban science research enabled by pre-trained large language models
Fu, J., Han, H., Su, X., & Fan, C. H. (2024) · Urban Informatics · doi:10.1007/s44212-024-00042-y · Cited by 31
Global North-South science inequalities due to language and funding barriers
Turba, R., Thoré, E. S. J., Bertram, M. G., Bridg, H., Sabet, S. S., Gamboa, M., Ríos-Orjuela, J. C., Takola, E., Salinas, J. C., Franco, A. C. S., et al. (2026) · Peer Community Journal · doi:10.24072/pcjournal.677 · Cited by 38
“Indeed, human verification remains indispensable (Teubner et al., 2023), which has led authors like Khelifa et al. (2022) to propose the use of an integrated peer language proofing and translation systems in preprint platforms as a solution to overcome language barriers.”
Mapping the Landscape: Exploring Large Language Model Applications in Business Process Management
Estrada-Torres, B., del–Río–Ortega, A., & Resinas, M. (2024) · Lecture notes in business information processing · doi:10.1007/978-3-031-61007-3_3 · Cited by 24
A Framework for Agricultural Intelligent Analysis Based on a Visual Language Large Model
Yu, P., & Lin, B. (2024) · Applied Sciences · doi:10.3390/app14188350 · Cited by 26
“Among them, large language models (LLMs) [3–5] have obtained outstanding achievements in the field of natural language processing, providing a new viewpoint and method for analyzing agricultural text data.”
Dubin, J. A., Bains, S. S., DeRogatis, M. J., Moore, M. C., Hameed, D., Mont, M. A., Nace, J., & Delanois, R. E. (2024) · The Journal of Arthroplasty · doi:10.1016/j.arth.2024.04.020 · Cited by 23
Evaluation of ChatGPT's performance in providing treatment recommendations for pediatric diseases
Wei, Q., Wang, Y., Yao, Z., Cui, Y., Wei, B., Li, T., & Xu, X. (2023) · Pediatric Discovery · doi:10.1002/pdi3.42 · Cited by 23
Subscription intentions for ChatGPT plus: a look at user satisfaction and self-efficacy
Jo, H. (2024) · Marketing Intelligence & Planning · doi:10.1108/mip-08-2023-0411 · Cited by 24
Gao, L., Wang, D., & Miao, Y. (2024) · Powder Technology · doi:10.1016/j.powtec.2024.120115 · Cited by 22
Nala2BPMN: Automating BPMN Model Generation with Large Language Models
Eldin, A. N., Assy, N., Anesini, O., Dalmas, B., & Gaaloul, W. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-81375-7_27 · Cited by 26
Zahid, I. A., & Joudar, S. S. (2023) · Applied Data Science and Analysis · doi:10.58496/adsa/2023/014 · Cited by 21
Who is using AI to code? Global diffusion and impact of generative AI
Daniotti, S., Wachs, J., Feng, X., & Neffke, F. M. H. (2026) · Science · doi:10.1126/science.adz9311 · Cited by 57
Huang, L., Zhang, X., Wang, Q., Chen, Z., & Liu, Y. (2024) · Journal of the Knowledge Economy · doi:10.1007/s13132-024-01755-w · Cited by 22
“It can also generate informative content such as summaries, translations, and answers, emphasizing objectivity, credibility, and referentiality (Teubner et al., 2023).”
Coal Mine Accident Risk Analysis with Large Language Models and Bayesian Networks
Du, G., & Chen, A. (2025) · Sustainability · doi:10.3390/su17051896 · Cited by 25
ChatGPT: Cross cultural tourism research imperative
Chen, S., Zhang, K., Li, X., Ye, H., Lin, K. J., & Law, R. (2023) · Journal of Economics and Management · doi:10.22367/jem.2023.45.07 · Cited by 19
“Additionally, by offering free access and a user-friendly interface to individual users, ChatGPT shifts the primary audience of LLMs from business to public (Teubner et al., 2023).”
BackgroundExploring the Role of ChatGPT in Cardiology: A Systematic Review of the Current Literature
Sharma, A., Medapalli, T., Alexandrou, M., Brilakis, E. S., & Prasad, A. (2024) · Cureus · doi:10.7759/cureus.58936 · Cited by 22
Bohara, D. K., & Rana, K. (2024) · SN Social Sciences · doi:10.1007/s43545-024-01003-7 · Cited by 26
“The emergence of AI, especially ChatGPT and Google Bard, has created a new discourse and both algorithms have made a strong presence in the field of education (Teubner et al. 2023).”
Machine learning in biological research: key algorithms, applications, and future directions
Alam, M. N. U., Basava, K., Chitransh, A., Fattah, H. M. A., Garcia‐Verdugo, H. D., Lo, S.-H., Lohchab, T., Martinet, K. M., Román‐Palacios, C., Salazar, J. C., et al. (2025) · BMC Biology · doi:10.1186/s12915-025-02424-3 · Cited by 23
“Recent advances in parallel computing hardware and community-accelerated software development have enabled the construction of gargantuan models comprising billions of parameters, though training speed remains an issue for specialized analyses [109].”
Volk, S. C., Schäfer, M. S., Lombardi, D., Mahl, D., & Yan, X. (2024) · Public Understanding of Science · doi:10.1177/09636625241268910 · Cited by 18
Lewandowski, T., Kučević, E., Leible, S., Poser, M., & Böhmann, T. (2023) · Electronic Markets · doi:10.1007/s12525-023-00662-3 · Cited by 19
“In particular, these models become widely available to (non-technical) users via the release of intuitive and conversational interfaces, such as OpenAI’s ChatGPT or Google’s Bard (Jiang et al., 2022; Teubner et al., 2023).”
Li, J., Yang, Y., Mao, C., Pang, P. C., Zhu, Q., Xu, D., & Wang, Y. (2025) · Journal of Medical Internet Research · doi:10.2196/66344 · Cited by 19
Amankwaa, I., Ekpor, E., Cudjoe, D., Kobiah, E., Fuseini, A.-K. J., Diebieri, M., Gyamfi, S., & Brownie, S. (2025) · Nurse Education Today · doi:10.1016/j.nedt.2025.106822 · Cited by 20
On Early Detection of Hallucinations in Factual Question Answering
Snyder, B., Moisescu, M., & Zafar, M. B. (2024) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3637528.3671796 · Cited by 46
Chiesa-Estomba, C. M., Speth, M. M., Mayo‐Yáñez, M., Liu, D. T., Maniaci, A., & Borsetto, D. (2023) · European Archives of Oto-Rhino-Laryngology · doi:10.1007/s00405-023-08382-2 · Cited by 16
ChatGPT in Academic Writing and Publishing: An Overview of Ethical Issues
Bakla, A. (2023) · Advances in Educational Technologies and Instructional Design · doi:10.4018/978-1-6684-9893-4.ch005 · Cited by 15
Ng, J. Y. (2025) · Integrative Medicine Research · doi:10.1016/j.imr.2025.101222 · Cited by 19
“106 , 107 In health research, this may involve misrepresented findings, false citations, or inaccurate literature summaries.”
Seok, J., Lee, B. H., Kim, D., Bak, S., Kim, S., Kim, S.-T., & Park, S.-M. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2443263 · Cited by 19
“…notification style, ChatGPT provides sympathetic services such as understanding the context of conversations, delivering real-time, natural responses (Bang et al., 2023; Teubner et al., 2023; Wu et al., 2023), and creative communication (Wu et al., 2023) based on a large-scale language model (LLM).”
Canboy, B., & Khlif, W. (2025) · International Journal of Production Economics · doi:10.1016/j.ijpe.2025.109550 · Cited by 15
Slow Writing with ChatGPT: Turning the Hype into a Right Way Forward
Sirisathitkul, C. (2023) · Postdigital Science and Education · doi:10.1007/s42438-023-00441-5 · Cited by 18
“Scholars across the globe have been fascinated by the positive and negative impacts of ChatGPT on education, research, and professional practices, and the number of dedicated publications has grown rapidly (Gordijn and ten Have 2023; Teubner et al. 2023).”
Evolving Generative AI: Entangling the Accountability Relationship
Elliott, M. T. J., Deepak, P., & MacCárthaigh, M. (2024) · Digital Government Research and Practice · doi:10.1145/3664823 · Cited by 17
Environment and sustainability development: A ChatGPT perspective
Bhaskar, P., & Seth, N. (2024) · CRC Press eBooks · doi:10.1201/9781003471059-8 · Cited by 14
Evaluating AI-generated responses from different chatbots to soil science-related questions
Khanifar, J. (2025) · Soil Advances · doi:10.1016/j.soilad.2025.100034 · Cited by 14
The ChatGPT application on quality management: a comprehensive review
Atalan, A. (2025) · Journal of Management Analytics · doi:10.1080/23270012.2025.2484225 · Cited by 15
Metadata
- Authors
- Teubner, T., Flath, C. M., Weinhardt, C., van der Aalst, W., & Hinz, O.
- Affiliations
- Einstein Center Digital Future (DE)
- University of Würzburg (DE)
- Karlsruhe Institute of Technology (DE)
- Goethe University Frankfurt (DE)
- Corresponding author
- Teubner, Timm
- Venue
- Business & Information Systems Engineering
- Published
- 2023-03-13
- Volume
- 65
- Issue
- 2
- Pages
- 95-101
- ISSN
- 1867-0202 (ISSN-L)
- 2363-7005
- OpenAlex
- W4360980513
- Cited by
- 384
- References
- 11
- Citations by year
- 2026: 78 · 2025: 135 · 2024: 117 · 2023: 54
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Business & Information Systems Engineering (publishedVersion, cc-by)
- RWTH Publications (RWTH Aachen) (publishedVersion)
- Econstor (Econstor) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Journal of the Association for Information Systems (submittedVersion)
- Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt) (submittedVersion, cc-by)
- Funders
- Technische Universität Berlin
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Keywords
- large language models, ChatGPT, Bing Chat, Google Bard, information systems, business applications of AI, AI regulation, research opportunities
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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