Special issue editorial: doing the literature review DOI Creative Commons
David Sammon, Stephen McCarthy, B. Veeresh Thummadi

и другие.

Journal of Decision System, Год журнала: 2024, Номер 33(4), С. 531 - 536

Опубликована: Окт. 1, 2024

Язык: Английский

Augmenting research methods with foundation models and generative AI DOI
Sippo Rossi, Matti Rossi, Raghava Rao Mukkamala

и другие.

International Journal of Information Management, Год журнала: 2024, Номер 77, С. 102749 - 102749

Опубликована: Янв. 12, 2024

Язык: Английский

Процитировано

19

New Frontiers in Information Systems Theorizing: Human-gAI Collaboration DOI Open Access
Sirkka L. Järvenpää, Stefan Klein

Journal of the Association for Information Systems, Год журнала: 2024, Номер 25(1), С. 110 - 121

Опубликована: Янв. 1, 2024

The Journal of the Association for Information Systems has long had a reputation promoting theory development. Yet development can be experienced as risky and frustrating because lack divergence convergence—both in terms ideas social dynamics among human theorists. These dichotomies stymie progress lead to unfinished works. Misconceptions about also hamper advances. We examine ways which generative artificial intelligence (gAI) tools may useful developing information systems (IS) through human-gAI collaboration, thus forging new frontiers IS theorizing.

Язык: Английский

Процитировано

10

Generative AI, Why, How, and Outcomes: A User Adoption Study DOI Open Access
Le Van Huy, T. Hien Nguyen, Tan Vo‐Thanh

и другие.

AIS Transactions on Human-Computer Interaction, Год журнала: 2024, Номер 16(1), С. 1 - 27

Опубликована: Март 31, 2024

Drawing on the extended unified theory of acceptance and use technology (UTAUT2) task-technology fit (TTF) theory, we developed an integrated research model to explore factors affecting ChatGPT its subsequent effects whether users continue using recommend it others. We also examined main activities as well moderating role curiosity in relationships between various influencing use. conducted a quantitative study with data that collected from 671 Vietnam. found that, first, most UTAUT2 TTF dimensions affected Interestingly, contrary our expectations, effort expectancy, social influence, trust had no effect Second, directly influenced intention word mouth (WOM). Third, significant WOM. Finally, acted moderator only three paths hedonic motivation, facilitating conditions, performance expectancy With this study, contribute unique combines (including both curiosity) knowledge about users' behavioral process adoption by examining comprehensive process, namely, actual usage– continuance use–recommending. Practical implications for providers, policymakers, business marketers are discussed.

Язык: Английский

Процитировано

9

Can attention detect AI-generated text? A novel Benford's law-based approach DOI

Zhenhua Wang,

Guang Xu, Ming Ren

и другие.

Information Processing & Management, Год журнала: 2025, Номер 62(4), С. 104139 - 104139

Опубликована: Март 21, 2025

Язык: Английский

Процитировано

1

Socio-technical phenomena involving blockchain use: Literature review, conceptual framework, and research agenda DOI Creative Commons
Shuai Wang, Daniel Schlagwein, Mike Seymour

и другие.

The Journal of Strategic Information Systems, Год журнала: 2025, Номер 34(2), С. 101901 - 101901

Опубликована: Апрель 11, 2025

Язык: Английский

Процитировано

1

An Activity System-based Perspective of Generative AI: Challenges and Research Directions DOI Open Access
Fiona Fui‐Hoon Nah, Jingyuan Cai, Ruilin Zheng

и другие.

AIS Transactions on Human-Computer Interaction, Год журнала: 2023, Номер 15(3), С. 247 - 267

Опубликована: Сен. 30, 2023

With its remarkable ability to generate content, generative artificial intelligence (GAI) has been recognized as a milestone in the development of general intelligence. To understand challenges, potential impact, and implications associated with GAI, we adopt socio-technical perspective analyze them. First, identify key characteristics which include content generation, generalization ability, reinforcement learning based on human feedback. Next, address technological, ethical, societal, economic, regulatory, governance challenges. Finally, deploy activity theory explore research directions GAI. Research questions that warrant further investigation how GAI may impact future work, can collaborate effectively humans, improve transparency models well mitigate biases misinformation achieve ethical responsible

Язык: Английский

Процитировано

12

Unpacking the process of conceptual leaping in the conduct of literature reviews DOI Creative Commons
Suzanne Rivard

The Journal of Strategic Information Systems, Год журнала: 2024, Номер 33(1), С. 101822 - 101822

Опубликована: Фев. 19, 2024

Literature reviews serve diverse purposes, including description, understanding, explanation, and testing. Traditionally – before online databases, full-text search availability, AI-based tools identifying relevant sources might have been considered a valuable contribution. However, top-tier information systems (IS) journals now demand more than descriptive reviews; they require authors to move beyond summarizing existing knowledge toward proposing innovative research directions, important questions, new concepts, interesting linkages among concepts. Despite adhering rigorous methodological guidelines, many struggle make conceptual leaps, that is, elevate their literature achieve profound provide explanations, or develop model. Authors may mistakenly prioritize hard work like thorough search, analysis, organization over thinking, which is crucial for advancing theoretical contributions. With this in mind, I adopt the view indeed qualitative data. suggest approaches help leaps can benefit review searching inconsistencies extant developing linkages. Drawing upon (Klag, M., Langley, A., 2013. Approaching leap research. International Journal of Management Reviews. 15 (2), 149–166.), unpack process leaping conduct reviews. This involves navigating dialectic tensions between knowing not knowing, engagement detachment, deliberation serendipity, self-expression social connection. Effectively managing these increase impact innovativeness

Язык: Английский

Процитировано

5

Exploring the scope of generative AI in literature review development DOI Creative Commons
Guido Schryen, Mauricio Marrone, Jiaqi Yang

и другие.

Electronic Markets, Год журнала: 2025, Номер 35(1)

Опубликована: Фев. 5, 2025

Язык: Английский

Процитировано

0

Designing ontology-based search systems for research articles DOI Creative Commons

Sebastian Huettemann,

Roland M. Mueller, Barbara Dinter

и другие.

International Journal of Information Management, Год журнала: 2025, Номер 83, С. 102901 - 102901

Опубликована: Март 15, 2025

Язык: Английский

Процитировано

0

Collaboration with GenAI in Engineering Research Design DOI Creative Commons
Fazel Naghdy

Data & Knowledge Engineering, Год журнала: 2025, Номер unknown, С. 102445 - 102445

Опубликована: Апрель 1, 2025

Язык: Английский

Процитировано

0