IDEAS home Printed from https://ideas.repec.org/a/zbw/afmpwm/335555.html

Künstliche Intelligenz trifft Marketing: Ein generativer Review-Ansatz zur Analyse aktueller Forschungstrends

Author

Listed:
  • Buchkremer, Rüdiger

Abstract

Die vorliegende Arbeit untersucht den Einfluss der Künstlichen Intelligenz (KI) auf das Marketing anhand einer automatisierten Analyse von 344 Abstracts aus der Fachliteratur. Durch den Einsatz von KI-Methoden wie Topic Modeling und Sprachmodellen werden zehn zentrale Themenfelder identifiziert, die das breite Spektrum der Anwendungsmöglichkeiten von KI im Marketing aufzeigen. Die Ergebnisse verdeutlichen das enorme Potenzial von KI zur Optimierung von Marketingprozessen und Kundenerlebnissen, werfen aber auch kritische Fragen zu Ethik, Kompetenzen und der Rolle des Forschers auf. Der Artikel liefert wertvolle Impulse für die weitere Erforschung und verantwortungsvolle Gestaltung von KI im Marketing.

Suggested Citation

  • Buchkremer, Rüdiger, 2024. "Künstliche Intelligenz trifft Marketing: Ein generativer Review-Ansatz zur Analyse aktueller Forschungstrends," PraxisWissen - German Journal of Marketing, AfM – Arbeitsgemeinschaft für Marketing, vol. 9(01/2024), pages 6-33.
  • Handle: RePEc:zbw:afmpwm:335555
    DOI: 10.15459/95451.64
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/335555/1/1950057100.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.15459/95451.64?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Akira Matsui & Daisuke Moriwaki, 2022. "Online-to-offline advertisements as field experiments," The Japanese Economic Review, Springer, vol. 73(1), pages 211-242, January.
    2. Delphine Caruelle & Poja Shams & Anders Gustafsson & Line Lervik-Olsen, 2022. "Affective Computing in Marketing: Practical Implications and Research Opportunities Afforded by Emotionally Intelligent Machines," Marketing Letters, Springer, vol. 33(1), pages 163-169, March.
    3. Akter, Shahriar & Dwivedi, Yogesh K. & Sajib, Shahriar & Biswas, Kumar & Bandara, Ruwan J. & Michael, Katina, 2022. "Algorithmic bias in machine learning-based marketing models," Journal of Business Research, Elsevier, vol. 144(C), pages 201-216.
    4. Zhiqin Chen & Zhihao Liao & Deming Qian & Jie Li & Man Fai Leung, 2022. "Design and Analysis of Intelligent Agricultural Monitoring System Based on Biological Intelligence Optimization Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-8, June.
    5. Djonata Schiessl & Helison Bertoli Alves Dias & José Carlos Korelo, 2022. "Artificial intelligence in marketing: a network analysis and future agenda," Journal of Marketing Analytics, Palgrave Macmillan, vol. 10(3), pages 207-218, September.
    6. Yuping Liu-Thompkins & Shintaro Okazaki & Hairong Li, 2022. "Artificial empathy in marketing interactions: Bridging the human-AI gap in affective and social customer experience," Journal of the Academy of Marketing Science, Springer, vol. 50(6), pages 1198-1218, November.
    7. Philippe Mongeon & Adèle Paul-Hus, 2016. "The journal coverage of Web of Science and Scopus: a comparative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 213-228, January.
    8. Youngkeun Choi & Jae W. Choi, 2023. "Assessing the Predictive Performance of Machine Learning in Direct Marketing Response," International Journal of E-Business Research (IJEBR), IGI Global Scientific Publishing, vol. 19(1), pages 1-12, January.
    9. Zahra Ghorbani & Sanaz Kargaran & Ali Saberi & Manijeh Haghighinasab & Seyedh Mahboobeh Jamali & Nader Ale Ebrahim, 2022. "Trends and patterns in digital marketing research: bibliometric analysis," Journal of Marketing Analytics, Palgrave Macmillan, vol. 10(2), pages 158-172, June.
    10. Mithun S. Ullal & Iqbal Thonse Hawaldar & Suhan Mendon & Nympha Rita Joseph, 2020. "The effect of artificial intelligence on the sales graph in Indian market," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 7(4), pages 2940-2954, June.
    11. Chen, Shiuann-Shuoh & Choubey, Bhaskar & Singh, Vinay, 2021. "A neural network based price sensitive recommender model to predict customer choices based on price effect," Journal of Retailing and Consumer Services, Elsevier, vol. 61(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mari, Alex & Mandelli, Andreina & Algesheimer, René, 2024. "Empathic voice assistants: Enhancing consumer responses in voice commerce," Journal of Business Research, Elsevier, vol. 175(C).
    2. Maria Petrescu & Anjala S. Krishen, 2023. "Mapping 2022 in Journal of Marketing Analytics: what lies ahead?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(1), pages 1-4, March.
    3. Nurhafizah Zainal & Norshima Humaidi & Sharidatul Akma Abu Seman & Siti Fazilah Hamid, 2025. "Unleashing Trends of Artificial Emotional Intelligence: A Bibliometric Analysis Using VOS Viewer," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(9), pages 2413-2434, September.
    4. Maribel Vega-Arce & Gonzalo Salas & Gastón Núñez-Ulloa & Cristián Pinto-Cortez & Ivelisse Torres Fernandez & Yuh-Shan Ho, 2019. "Research performance and trends in child sexual abuse research: a Science Citation Index Expanded-based analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1505-1525, December.
    5. Serhat Burmaoglu & Ozcan Saritas, 2019. "An evolutionary analysis of the innovation policy domain: Is there a paradigm shift?," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(3), pages 823-847, March.
    6. Marek Kwiek & Wojciech Roszka, 2022. "Academic vs. biological age in research on academic careers: a large-scale study with implications for scientifically developing systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3543-3575, June.
    7. Mohd Rizaimy Shaharudin & Azyyati Anuar & Preecha Wararatchai & Natapat Areerakulkan & Wissawa Aunyawong, 2025. "Drivers and Constraints of Remanufacturing: A Global Bibliometric Review," Information Management and Business Review, AMH International, vol. 17(4), pages 141-163.
    8. Mike Thelwall, 2020. "Mid-career field switches reduce gender disparities in academic publishing," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(3), pages 1365-1383, June.
    9. Nasrabadi, Mohamadreza Azar & Beauregard, Yvan & Ekhlassi, Amir, 2024. "The implication of user-generated content in new product development process: A systematic literature review and future research agenda," Technological Forecasting and Social Change, Elsevier, vol. 206(C).
    10. Pantea Kamrani & Isabelle Dorsch & Wolfgang G. Stock, 2021. "Do researchers know what the h-index is? And how do they estimate its importance?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5489-5508, July.
    11. Yves Gingras & Mahdi Khelfaoui, 2018. "Assessing the effect of the United States’ “citation advantage” on other countries’ scientific impact as measured in the Web of Science (WoS) database," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 517-532, February.
    12. Théodore Nikiema & Eugène C. Ezin & Sylvain Kpenavoun Chogou, 2023. "Bibliometric Analysis of the State of Research on Agroecology Adoption and Methods Used for Its Assessment," Sustainability, MDPI, vol. 15(21), pages 1-18, November.
    13. Maurer, Moritz, 2025. "Wild Experiments? Restricting Narratives in Research on Alternative Food and Agriculture Networks," OSF Preprints u2tyv, Center for Open Science.
    14. María Fernanda Carnero Quispe & Lucciana Débora Chambilla Mamani & Hugo Tsugunobu Yoshida Yoshizaki & Irineu de Brito Junior, 2025. "Temporary Facility Location Problem in Humanitarian Logistics: A Systematic Literature Review," Logistics, MDPI, vol. 9(1), pages 1-27, March.
    15. Abdulkarim. K. Alhowaish, 2025. "The Blue Economy in the Arabian Gulf: Trends, Gaps, and Pathways for Sustainable Coastal Development," Sustainability, MDPI, vol. 17(19), pages 1-24, October.
    16. Manuel Sánchez-Pérez & Nuria Rueda-López & María Belén Marín-Carrillo & Eduardo Terán-Yépez, 2021. "Theoretical dilemmas, conceptual review and perspectives disclosure of the sharing economy: a qualitative analysis," Review of Managerial Science, Springer, vol. 15(7), pages 1849-1883, October.
    17. Stephen, Dimity & Stahlschmidt, Stephan, 2021. "Performance and structures of the German science system 2021," Studien zum deutschen Innovationssystem 5-2021, Expertenkommission Forschung und Innovation (EFI) - Commission of Experts for Research and Innovation, Berlin.
    18. Simon Zaby, 2019. "Science Mapping of the Global Knowledge Base on Microfinance: Influential Authors and Documents, 1989–2019," Sustainability, MDPI, vol. 11(14), pages 1-21, July.
    19. Ana Batlles-delaFuente & Luis Jesús Belmonte-Ureña & José Antonio Plaza-Úbeda & Emilio Abad-Segura, 2021. "Sustainable Business Model in the Product-Service System: Analysis of Global Research and Associated EU Legislation," IJERPH, MDPI, vol. 18(19), pages 1-33, September.
    20. Katarzyna Piwowar‐Sulej, 2021. "Core functions of Sustainable Human Resource Management. A hybrid literature review with the use of H‐Classics methodology," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(4), pages 671-693, July.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:afmpwm:335555. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://arbeitsgemeinschaft.marketing/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.