Abstract
The electronic trade with used goods has been flourishing for many years and is constantly developing. Many private buyers and sellers find themselves able to offer used items or even purchase them below their new value through various market platforms (intermediaries). However, particular problems and challenges in the trade of used goods promote uncertainty and mistrust, especially high-involvement products. The seller of a used object usually has extensive knowledge about its previous use, hidden problems, and thus the current condition of the good. This information asymmetry is difficult to bridge, as the seller usually exploits the opportunity. Therefore, the buyer is dependent on the seller's willingness to release information, which may be incomplete and untrue, or suggest false facts. Especially in the online used-car market, which is the focus of this dissertation, these problems can be observed very distinctly. The seller of a used vehicle knows its history, previous treatment, and possible accidents and damages. At the same time, the buyer has to trust the seller's statements due to the lack of physical checkability. The resulting uncertainty about the seller and the quality of the vehicle results in distrust and a lower appreciation of the car. Akerlof described this in his popular work as the "Market for Lemons" (Akerlof 1970), in which even vehicles in good condition have no chance of being sold at an adequate price.
The key to increase market transparency by reducing information asymmetry, and thus uncertainty and mistrust, is effective and efficient communication among market participants that supports and promotes the exchange of information. This exchange usually occurs during the negotiation phase between buyer and seller and strongly determines the negotiation outcome. The quantity and quality of communication can be enhanced by technical support. Authenticated data, technically immutable and credibly available in a market, has enormous potential here. This data allows the transfer of trust to some extent from the interpersonal level to technology (e.g., blockchain) and enables a better assessment of the actual state of the vehicle without physical inspection. Further, this data can be treated as an asset and be part of the trade in addition to the actual object of negotiation. However, how integration of such data from a data market into a platform can be done to increase the benefit of the participants and the platform has largely not been explored.
This dissertation describes the research project conducted to design and develop features to support party communication and negotiation in the online used-car market to address the named challenges. In addition, a conceptual model of a future used-car market is developed that incorporates these features as well as other features from related research. The thesis is composed of four self-contained essays. The research content thereby builds on each other. It sheds light on the impact of blockchain-based authenticated data on the behavior of market participants in the online used-car market and the benefits that platforms experience by providing the data to all market participants. The underlying research follows the design science activities of the DSR cycle model (Hevner 2007; Briggs and Schwabe 2011): 1) discovering problems and opportunities, 2) designing and building artifacts and processes, and 3) validating artifacts and processes.
The first two essays exploratively examined buyers’ and sellers’ expectations and preferences, and the disclosure and negotiation behavior with the availability of authenticated data. This exploration corresponds with the first DSR activity of discovering problems and opportunities. Essay 1 uses the results of an experiment using a market simulation game of the used-car market, the “car-market game”, to show the requirements of market participants to support their disclosing behavior during negotiation. Essay 2 complements this by examining, also through an experiment, what negotiation behavior participants exhibit currently and under the availability of authenticated data. The focus was on changes in patterns of negotiation procedures in terms of complexity and dishonest and deceptive behavior.
The third essay incorporates the results of DSR activity two and three and elaborates on the design and development of new negotiation support elements, building on the findings and requirements of the first two essays. The elements were integrated into a text-based negotiation chat and evaluated to “authenticated data chat” in an experiment as a result of DSR activity three. The fourth essay shows how the used-car market can evolve while providing authenticated data to support market participants in their communication, information exchange, and trading of data about the vehicle and generate benefits for all market participants and competitive advantages for the platform operators. For this purpose, various artifact evaluations have also been conducted and summarized in related research performed by our research group.
As the used-car market continuously evolves towards e-commerce, support for controlling sensitive information and negotiation between market participants becomes increasingly essential. There is extensive research in the negotiation literature, and textbased communication media such as instant messaging and chat have been extensively studied. But there is still a lack of insight into how dishonest behavior, mistrust, and uncertainty as a result of information imbalances in online negotiations can be reduced through the use of appropriate technology and design. In addition, platforms do not know exactly how they will need to evolve into a future used-car market in order to remain competitive in the long term. This dissertation contributes to fill these gaps.
Engelmann, Andreas