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Der Einsatz von künstlicher Intelligenz im digitalen Marketing – eine Analyse mithilfe der Trust-Commitment Theorie, der Expectation-Confirmation Theorie und des Technology Acceptance Modells

  • The trend of digitalization has fundamentally changed numerous industries. The field of marketing in particular has changed significantly in recent years. Technological progress makes it possible to reach new customer groups individually with the targeted use of artificial intelligence. It is highly relevant for companies to know how modern marketing can be used profitably with the help of artificial intelligence and which hurdles and challenges need to be considered. The numerous applications of artificial intelligence in marketing include, for example, sales forecasts, personalization of websites or chatbots. This bachelor thesis focuses on the use of artificial intelligence in marketing and analyses the effects on customer loyalty. In order to explain the success of the use of artificial intelligence in marketing, three established theories are considered. The trust-commitment theory emphasizes the role of trust and commitment in the process of developing relationships between buyers and sellers. Several studies show that customers trust a company or a deployed artificial intelligence technology more when the services are personalized, convenient and of high quality. A high level of trust in turn has a positive impact on the overall service experience. The expectation-confirmation model consists of three determinants to explain users' intention to continue using the artificial intelligence enabled service: confirmation of expectations, perceived usefulness and satisfaction. When users' expectations are met or even exceeded, this has a positive impact on customer satisfaction, which in turn has a positive impact on the intention to reuse a technology. The technology acceptance model predicts an individual's attitude towards technology use, taking into account two main determinants: perceived usefulness and perceived ease of use. Various studies show that perceived usefulness and perceived ease of use are necessary preconditions for user satisfaction and intention to reuse the artificial intelligence technology. These results are also in line with the findings from the expectation-confirmation model.

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Metadaten
Author:Benedict Laufer
Advisor:Paul Taylor
Document Type:Bachelor Thesis
Language:German
Year of Completion:2021
Granting Institution:Hochschule Furtwangen
Date of final exam:2021/02/28
Release Date:2021/04/08
Tag:Digitales Marketing; Künstliche Intelligenz KI; Marketing KI
Pagenumber:63
Degree Program:IBW - Internationale Betriebswirtschaft
Functional area:Marketing
Open Access:Innerhalb der Hochschule
Licence (German):License LogoEs gilt das UrhG