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Can Artificial Intelligence Help Used-Car Dealers Survive in a Data-driven Used-Car Market?


Eckhardt, Sven; Sprenkamp, Kilian; Zavolokina, Liudmila; Bauer, Ingrid; Schwabe, Gerhard (2022). Can Artificial Intelligence Help Used-Car Dealers Survive in a Data-driven Used-Car Market? In: DESRIST 2022: 17th International Conference on Design Science Research in Information Systems and Technology, St Petersburg, FL, USA, 1 June 2022 - 3 June 2022, University of South Florida.

Abstract

The used-car market is notoriously untrustworthy and shady. Certifie data has been shown to help mitigate the information asymmetry, one of the major factors to an untrustworthy market. In recent times, more and more used-car dealers have had problems surviving in this competitive data-driven market. In this study, we conduct 12 interviews with used-car dealers and several meetings and workshops with employees and executives from the AMAG Group, one of the largest automotive companies in Switzerland. This creates insight into current problems for used-car dealers and how artificial intelligence can help. The problems can be abstracted to the problem of high transaction cost and its subcategories. In reducing transaction costs by utilizing artificial intelligence, new secondary problems arise. People need to trust the certificate, the analytics, and the predictions. Additionally, the data and analytics need to be transparent and understandable, and privacy concerns must be addressed. The implications of this study are manifold. First, we define the problems for used-car dealers on the used-car market and introduce artificial intelligence approaches to the current data-driven used-car market. Afterward, we stress that artificial intelligence needs to follow a human-centered perspective and be designed for trust.
Keywords: Used-Car Market, Transaction Costs, Trust, Artificial Intelligence

Abstract

The used-car market is notoriously untrustworthy and shady. Certifie data has been shown to help mitigate the information asymmetry, one of the major factors to an untrustworthy market. In recent times, more and more used-car dealers have had problems surviving in this competitive data-driven market. In this study, we conduct 12 interviews with used-car dealers and several meetings and workshops with employees and executives from the AMAG Group, one of the largest automotive companies in Switzerland. This creates insight into current problems for used-car dealers and how artificial intelligence can help. The problems can be abstracted to the problem of high transaction cost and its subcategories. In reducing transaction costs by utilizing artificial intelligence, new secondary problems arise. People need to trust the certificate, the analytics, and the predictions. Additionally, the data and analytics need to be transparent and understandable, and privacy concerns must be addressed. The implications of this study are manifold. First, we define the problems for used-car dealers on the used-car market and introduce artificial intelligence approaches to the current data-driven used-car market. Afterward, we stress that artificial intelligence needs to follow a human-centered perspective and be designed for trust.
Keywords: Used-Car Market, Transaction Costs, Trust, Artificial Intelligence

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
08 Research Priority Programs > Digital Society Initiative
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Theoretical Computer Science
Physical Sciences > General Computer Science
Uncontrolled Keywords:Used-Car Market, Transaction Costs, Trust, Artificial Intelligence
Scope:Discipline-based scholarship (basic research)
Language:English
Event End Date:3 June 2022
Deposited On:04 Jul 2022 16:28
Last Modified:06 Mar 2024 14:37
Publisher:University of South Florida
OA Status:Green
Publisher DOI:https://doi.org/10.1007/978-3-031-06516-3_9
Related URLs:https://www.usf.edu/business/desrist/venue.aspx
Other Identification Number:merlin-id:22541
  • Content: Published Version