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Exploring Consumers' Discernment Ability of Autogenerated Advertisements
Högskolan i Skövde, Institutionen för informationsteknologi. Högskolan i Skövde, Forskningsmiljön Informationsteknologi. Department of Information Technology, University of Borås, Sweden.ORCID-id: 0000-0002-3553-5983
Department of Information Technology, University of Borås, Sweden.ORCID-id: 0000-0003-4308-434X
Department of Information Technology, University of Borås, Sweden.ORCID-id: 0000-0002-9685-7775
Department of Information Technology, University of Borås, Sweden.ORCID-id: 0000-0002-5814-9604
Visa övriga samt affilieringar
2023 (Engelska)Ingår i: Machine Learning, Multi Agent and Cyber Physical Systems: Proceedings of the 15th International FLINS Conference (FLINS 2022) / [ed] Qinglin Sun; Jie Lu; Xianyi Zeng; Etienne E. Kerre; Tianrui Li, World Scientific, 2023, s. 322-329Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Autogenerated Advertisements (AGAs) can be a concern for consumers if they suspect that Artificial Intelligence (AI) was involved. Consumers may have an opposing stance against AI, leading companies to miss profit opportunities and reputation loss. Hence, companies need ways of managing consumers’ con-cerns. As a part of designing such advices we explore consumers’ discernment ability (DA) of AGAs. A quantitative survey was used to explore consumers’ DA of AGAs. In order to do this, we administered questionnaires to 233 re-spondents. A statistical analysis including Z-tests, of these responses suggests that consumers can hardly pick out AGAs. This indicates that consumers may be guessing and thus do not possess any significant DA of our AGAs.

Ort, förlag, år, upplaga, sidor
World Scientific, 2023. s. 322-329
Serie
World Scientific Proceedings Series on Computer Engineering and Information Science, ISSN 1793-7868, E-ISSN 2972-4465 ; 13
Nyckelord [en]
Autogenerated ads, Discernment ability, Marketing
Nationell ämneskategori
Datavetenskap (datalogi)
Forskningsämne
Informationssystem (IS)
Identifikatorer
URN: urn:nbn:se:his:diva-23230DOI: 10.1142/9789811269264_0038ISBN: 978-981-126-925-7 (tryckt)ISBN: 978-981-126-927-1 (digital)OAI: oai:DiVA.org:his-23230DiVA, id: diva2:1799035
Konferens
Conference on Machine learning, Multi Agent and Cyber Physical Systems (FLINS 2022), Tianjin, China, 26 – 28 August 2022
Forskningsfinansiär
KK-stiftelsen, 20160035, 20170215
Anmärkning

Partly funded by The Knowledge Foundation, grants nr. 20160035, 20170215

Tillgänglig från: 2023-09-20 Skapad: 2023-09-20 Senast uppdaterad: 2023-10-10Bibliografiskt granskad
Ingår i avhandling
1. Designing Advertisement Systems with Human-centered Artificial Intelligence
Öppna denna publikation i ny flik eller fönster >>Designing Advertisement Systems with Human-centered Artificial Intelligence
2023 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

Practitioners are urging using Artificial Intelligence (AI) to improve advertisements. Advertisers recognize the importance of incorporating AI into their strategies to remain competitive. In response to this demand, a Design Science Research (DSR) initiative has been started to create a Human-Centered AI (HCAI) tool to enhance advertisement suggestions by analyzing consumer behavior. This dissertation aims to build an advertisement optimization system with HCAI and produce an Information System Design Theory (ISDT) of that class of system. Through architectural models, methods, technological rules, and design principles, nascent Design Theory (DT) is created and serves as an initial stage towards achieving a more abstract design knowledge known as the ISDT. The action design research method is employed to construct and analyze the implemented system instance. The process involves multiple cycles of building, intervening, and evaluating. These cycles are conducted iteratively and incrementally, allowing for the gradual development of the suggested system while simultaneously generating valuable design knowledge. The system is developed and abstracted for design knowledge from both the development process and the actual tool. The dissertation presents nascent design knowledge in the form of models, technological rules, and design principles. Moreover, the dissertation places the nascent DT within the broader context of a more abstract design knowledge called ISDT. The results are then scrutinized based on various components of the DT, including purpose and scope, constructs, principles of form and function, artifact mutability, justificatory knowledge, testable propositions, principles of implementation, and expository instantiation. This dissertation discusses the DSR process, compared to various challenges encountered throughout the research project. Theoretical, empirical, and artefactual research contributions are outlined, and their implications for research and practice are discussed toward the end of the dissertation. The quality of the research is examined, considering the relevance, novelty, usefulness, feasibility, design rigor, evaluation rigor, and transparency of the artifacts produced throughout the dissertation. The dissertation concludes that it delivered ISDT. Moreover, the system serves as a valuable example of how AI can be utilized for optimizing digital advertisements. The dissertation ends with providing recommendations for future research.

Ort, förlag, år, upplaga, sidor
Skövde: University of Skövde, 2023. s. xiv, 361
Serie
Dissertation Series ; 54
Nyckelord
Digital Advertisement Optimization, Design Knowledge, Information System Design Theory, Artificial Intelligence, Reinforcement Learning, Human-centered AI
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
urn:nbn:se:his:diva-23234 (URN)978-91-987906-8-9 (ISBN)
Disputation
2023-11-01, Insikten, Kanikegränd 3B, Skövde, 10:00
Opponent
Handledare
Forskningsfinansiär
KK-stiftelsen, 20160035, 20170215
Anmärkning

Partly funded by The Knowledge Foundation, grants nr. 20160035, 20170215

Två av sex delarbeten (övriga se rubriken Delarbeten/List of papers):

Sahlin, Johannes, Håkan Sundell, Gideon Mbiydzenyuy, and Jesper Holgersson (2023). “Managing Consumer Concerns of Model-generated Advertisements.” In: Expert Systems with Applications, Submitted.

— (2024). “Nascent Design Theory for Advertisement Optimization Systems with Human-centered Artificial Intelligence.” In: European Conference on Information Systems, Draft.

Tillgänglig från: 2023-10-02 Skapad: 2023-09-21 Senast uppdaterad: 2023-10-03Bibliografiskt granskad

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Sahlin, JohannesHolgersson, Jesper

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Sahlin, JohannesSundell, HåkanGideon, MbiydzenyuyAlm, HåkanHolgersson, Jesper
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