Journal of Business Research, Год журнала: 2025, Номер 192, С. 115320 - 115320
Опубликована: Март 21, 2025
Язык: Английский
The Journal of Technology Transfer, Год журнала: 2024, Номер unknown
Опубликована: Сен. 16, 2024
Язык: Английский
Процитировано
7
Deleted Journal, Год журнала: 2024, Номер 1(1), С. 21 - 32
Опубликована: Март 1, 2024
The research aims to determine the prospects for improving innovation management in business using artificial intelligence (AI). To achieve goal, author examined international experience of 33 countries as end 2023, relevant at beginning 2024, with reference IMD statistics. As a result, developed an econometric model AI and alternative digital technologies. has shown that instead risks, implementing generates advantages business. main conclusion is application preferable compared technologies because it makes possible significantly increase results reduce costs such management. Therefore, authors proposed new approach business, which achieves high level automation based on first time. theoretical significance obtained author’s conclusions explained by fact they revealed cause-and-effect relationships managerial this lies will efficiency
Язык: Английский
Процитировано
6
IEEE Transactions on Engineering Management, Год журнала: 2024, Номер 71, С. 11522 - 11532
Опубликована: Янв. 1, 2024
Язык: Английский
Процитировано
6
ESIC MARKET Economic and Business Journal, Год журнала: 2024, Номер 55(2), С. e333 - e333
Опубликована: Май 31, 2024
Objective:This study investigates the transformative potential of Generative Artificial Intelligence(GenAI) within business domain and entrepreneurial activity.Methodology:A comprehensive research design is adopted, integrating text-mining techniques to analysedata obtained from publicly available innovation repositories. A systematic literaturereview (SLR) developed based on literature all databases indexedin Web Science (WoS), incorporating preprints arXiv, alongside industry-relatedinnovation data in form patents Google Patents. This method enables derivationof valuable insights regarding impact prospective developments GenAIacross diverse sectors industries by leveraging Natural Language Processing(NLP) network analysis.Results:The outcomes highlight significant GenAI enabling informeddecision-making, enhancing productivity, revealing new growth opportunities inthe landscape. The continuously evolving environment examined,emphasising GenAI's role as a catalyst for data-driven innovation. However, there are stillrelevant limitations overcome.Limitations:The selection sources period may have excluded relevant or recentlypublished articles scope present research. language ofthe analysed only English.Practical Implications:The practical implications this carry weight, serving valuableresource decision-makers, researchers, practitioners navigating constantlyshifting terrain through lens GenAI. Understanding thepotential advantages challenges associated with adoption equips stakeholdersto make informed decisions develop future strategies.
Язык: Английский
Процитировано
6
Human Technology, Год журнала: 2024, Номер 20(1), С. 131 - 154
Опубликована: Май 27, 2024
The launch of ChatGPT in November 2022 revolutionized the accessibility generative Artificial Intelligence, enabling conversational interactions. Extensively tested by millions, its influence on management has become a subject debate. In digital revolution, Intelligence possesses transformative potential, automates tasks, delivers novel goods and services, generates valuable insights. However, challenges such as data quality, human oversight, ethical considerations arise context transformation. This research employs qualitative methods to examine current understanding predict knowledge within organizations. By conducting survey among industry experts, this paper aims provide insights into integration implications for paradigm.
Язык: Английский
Процитировано
5
Computers and Education Artificial Intelligence, Год журнала: 2024, Номер 7, С. 100329 - 100329
Опубликована: Ноя. 5, 2024
Язык: Английский
Процитировано
5
The Clearing House A Journal of Educational Strategies Issues and Ideas, Год журнала: 2025, Номер unknown, С. 1 - 8
Опубликована: Янв. 11, 2025
This paper examines the transformative potential of Generative AI (GenAI) in enhancing data collection and analysis methodologies within educational research. By utilizing automated techniques such as web scraping sentiment analysis, researchers can efficiently gather substantial amounts while minimizing human error bias, thereby improving validity their findings. Furthermore, advanced analytical approaches, including predictive analytics natural language processing, enable deeper insights into complex phenomena that traditional methods may overlook. The underscores ethical considerations associated with GenAI, particularly concerning privacy, informed consent, bias mitigation. It advocates for ongoing innovation research to adapt these technological advancements highlights importance interdisciplinary collaboration refining practices. responsibly integrating enhance outcomes promote equitable learning experiences. Ultimately, this work encourages scholars reflect on future integration GenAI practices consider how innovations reshape landscape.
Язык: Английский
Процитировано
0
European Journal of Innovation Management, Год журнала: 2025, Номер unknown
Опубликована: Янв. 27, 2025
Purpose This paper aims to contribute the discussion on integrating humans and technology in customer service within framework of Society 5.0, which emphasizes growing role artificial intelligence (AI). It examines how effectively new generative AI-based chatbots can handle emotions explores their impact determining point at a customer–machine interaction should be transferred human agent prevent disengagement, referred as Switch Point (SP). Design/methodology/approach To evaluate capabilities managing emotions, ChatGPT-3.5, Gemini Copilot are tested using Trait Emotional Intelligence Questionnaire Short-Form (TEIQue-SF). A reference is developed illustrate shift Findings Using four-intelligence (mechanical, analytical, intuitive empathetic), this study demonstrates that, despite advancements AI’s ability address service, even most advanced chatbots—such ChatGPT, Copilot—still fall short replicating empathetic (HI). The concept emotional awareness (AEA) introduced characterize AI understanding triggering SP. complementary rather than replacement perspective HI proposed, highlighting Research limitations/implications exploratory nature requires further theoretical development empirical validation. Practical implications has only an character with respect possible real introduction collaborative approaches integration 5.0. Originality/value Customer Relationship Management managers use proposed guide adopt dynamic approach HI–AI collaboration AI-driven service.
Язык: Английский
Процитировано
0
Journal of Workplace Learning, Год журнала: 2025, Номер unknown
Опубликована: Янв. 29, 2025
Purpose The purpose of this study was to explore employees’ perceptions and firsthand experiences the impact generative artificial intelligence (AI) productivity tools, specifically Microsoft 365 Copilot, on individual collective learning processes within a multinational corporation. In doing so, provides insights into how these tools can shape workplace dynamics, fostering both skill development collaborative knowledge-sharing practices. Design/methodology/approach authors collected responses from 357 participants through survey that included multiple-choice open-ended questions. This focuses exclusively qualitative responses. reflexive thematic analysis method used capture interpret role Copilot – AI-powered assistant integrated suite applications (e.g., Word, Excel, PowerPoint, Outlook, Teams) in enhancing their work opportunities workplace. Findings results highlight four key themes contributing learning. At level, Task Support illustrates extent which AI transform practices facilitate formal informal pathways, while Meaningful Work underscores tools’ foundational knowledge enriched information. organisational culture suggests importance supportive environment for integration, socialisation highlights its influence team cohesion essential effective collaboration among members. Practical implications offer actionable organisations integrating Understanding inform design targeted training programmes promote foster sharing. Furthermore, positions as complementary resource improve employee engagement, reduce resistance new technologies encourage growth-oriented mindset, ultimately driving personal development. Originality/value shifts narrative around by examining enhance at levels, rather than focusing solely potential disrupt displacement automation. By positioning AI-based human work, approach enablers development, sharing job enrichment, more adaptive learning-oriented environment.
Язык: Английский
Процитировано
0
Information - Wissenschaft & Praxis, Год журнала: 2025, Номер unknown
Опубликована: Фев. 4, 2025
Zusammenfassung Generative künstliche Intelligenz (GenAI) hat das Potenzial, die Wissensarbeit und damit Innovationsmanagement zu revolutionieren. Um erwarteten Veränderungen beschreiben können, wurde eine umfassende Befragung unter Expertinnen Experten aus der Industrie Forschung durchgeführt. Viele Befragten sehen derzeit keine relevante Rolle von GenAI im Innovationsmanagement. Die Befragungsergebnisse deuten darauf hin, dass mehr Aufgaben übernommen werden könnten, denn es wird ein hohes bis sehr Unterstützungspotenzial durch in allen Phasen des Innovationsprozesses erwartet. Gleichzeitig aktuell auch Herausforderungen beim Einsatz gesehen. Es ist davon auszugehen, einige dieser Hindernisse den technologischen Fortschritt überwunden werden. Empfehlenswert für Unternehmen daher, proaktiv GenAI-Fähigkeiten entwickeln, um frühzeitig Komplexität Technologie verstehen sich bietenden Chancen nutzen. Aufgrund begrenzten Anzahl an Teilnehmenden deren zufälligen Auswahl Studie nicht repräsentativ. Dennoch liefern Ergebnisse Ansatzpunkte weitere Forschungen. So stellen z. B. Vergleiche Potenziale Einsatzes zwischen Weltregionen oder longitudinale Erhebungen tatsächlich eintretenden Forschungsansätze dar.
Процитировано
0