Author
Listed:
- Christine Balagué
(LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - UEVE - Université d'Évry-Val-d'Essonne - Université Paris-Saclay - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], IMT-BS - MMS - Département Management, Marketing et Stratégie - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], CONNECT - Consommateur Connecté dans la Société Numérique - IMT-BS - DEFI - Département Droit, Economie et Finances - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris] - IMT-BS - MMS - Département Management, Marketing et Stratégie - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris])
- Zeling Zhong
(LITEM - Laboratoire en Innovation, Technologies, Economie et Management (EA 7363) - UEVE - Université d'Évry-Val-d'Essonne - Université Paris-Saclay - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris], IMT-BS - MMS - Département Management, Marketing et Stratégie - TEM - Télécom Ecole de Management - IMT - Institut Mines-Télécom [Paris] - IMT-BS - Institut Mines-Télécom Business School - IMT - Institut Mines-Télécom [Paris])
Abstract
Generally, we expect Machine Learning (ML) in marketing to provide efficient recommendation systems, improvement in advertising with real time bidding, more accurate customers' behaviors predictions, and better CRM. This research focuses on the role of ML ethics, which is a combination of four ethical concepts: data privacy and security, fairness, accountability, and transparency of ML algorithms. The results show that ML ethics play a key role on consumer's behavior by positively influencing AI services appropriation. We use a PLS model to quantitatively measure AI services appropriation, as well as its antecedents (ML ethics and trust) and consequences (perceived value and NPS). We also reveal that fulfillment of contract obligations has a mediating role between ML ethics and trust in AI services. This research shows that marketers need to be responsible by focusing on the ethics of ML to answer AI users' needs and to enter in the Artificial Intelligence era.
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