| 研究実績の概要 |
The research has focused on the information underlying pricing algorithms. This research has concluded that a distinction needs to be made between information that is either opaque or transparent. Opaque information will make it difficult to achieve tacit collusion, but also explicit collusion. The former is likely only to happen when other software is implemented, eventually based upon reverse engineering of a competitors algorithm. The latter may occur when the users of the algorithm have come to an understanding of the algorithm, and so allowing them to agree on elements that influence the outcome of the algorithm. Transparent information most likely will lead to tacit collusion, whereby the algorithm adjusts the price to the price of a determined competitor. This competitor is usually the lowest price setter. Of course, transparent information does not exclude express collusion, where there has been communication between competitors. Based on the information found, algorithms allow firms to be more efficient. This could eventually make an overall predatory pricing strategy more feasible. These competition law conclusion have been drawn from empirical studies provided by computer experts on Uber and Amazon Marketplace.
The research has further focused on the taxonomy of algorithmic collusion by arguing that the hub-and-spoke collusion includes fundamentally different scenarios. Also, it is not for sure that the predictive algorithm can operate without human intervention making information artificially transparent.
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| 今後の研究の推進方策 |
The research will focus on collecting the necessary information for completing the book project. This will involve the making of a bibliography, proper footnoting of the different chapters and a final reading of the whole manuscript. If everything goes as planned, the manuscript will be submitted to the publisher around July. After this, the manuscript will go into its production process.
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