We experimentally investigate whether and how the potential presence of algorithmic trading (AT) in human-only asset markets can influence humans’ price forecasts, trading activities and price dynamics. Two trading strategies commonly employed by high-frequency traders, spoofing (SP) – associated with market manipulation – and market making (MM) – seen as liquidity provision – are considered. These experiments reveal that, first, the mere expectation of SP traders can, at first, impair price convergence towards fundamentals. Second, the expected presence of AT, especially MM traders, induce larger initial price forecasts deviations from fundamentals. Third, despite the absence of AT in our experiments, the information about the presence of AT, employing MM strategy, is sufficient to alter subjects trading behavior over time and the impact of past realized prices on subjects’ order prices.

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More organizations use AI in the hiring process than ever before, yet the perceived ethicality of such processes seems to be mixed. With such variation in our views of AI in hiring, we need to understand how these perceptions impact the organizations that use it. In two studies, we investigate how ethical perceptions of using AI in hiring are related to perceptions of organizational attractiveness and innovativeness. Our findings indicate that ethical perceptions of using AI in hiring are positively related to perceptions of organizational attractiveness, both directly and indirectly via perceptions of innovativeness, with variations depending on the type of hiring method used. For instance, we find that individuals who consider it ethical for organizations to use AI in ways often considered to be intrusive to privacy, such as analyzing social media content, view such organizations as both more innovative and attractive.
FIGUEROA-ARMIJOS Maria - FNEGE |
- Research
- Digital Transformation, Human Resources Management

