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A new generation of information systems based on artificial intelligence (AI) transforms the way we work. However, existing research on human-AI collaboration is scattered across disciplines, highlighting the need for more transparency about the design of human-AI collaboration in organizational contexts. This paper addresses this gap by reviewing the literature on human-AI collaboration through the lens of human teamwork. Our results provide insights into how emerging topics of human-AI collaboration are connected and influence each other. In particular, the review indicates that, with the increasing complexity of organizational settings, human-AI collaboration needs to be designed differently, and team maintenance activities become more important due to increased communicational requirements of humans. Our main contribution is a novel framework of temporal phases in human-AI collaboration, identifying the mechanisms that need to be considered when designing them for organizational contexts. Additionally, we use our framework to derive a future research agenda. [ABSTRACT FROM AUTHOR]

The increasing application of Conversational Agents (CAs) is rapidly changing the way customers access services. In practice, however, CAs are frequently flawed, such as they often misinterpreting users' requests. Even through future advancements in technology, it remains unlikely that a CA will be flawless and error-free. Thus, understanding how to design CAs so that users are more willing to overlook errors constitutes an important area of research. In this regard, our study positions the human-like design of CAs as a potential way to ensure service satisfaction when errors occur. We examined the effect of human-like designed flawed CAs by conducting a two-condition experiment with 421 participants, analyzing its effect on users' emotional state and service satisfaction. Our results show that the human-like design of flawed CAs leads to more positive emotions, which improve users' service satisfaction. Therefore, designers should adopt a humanlike design to prevent dissatisfaction with flawed CAs. [ABSTRACT FROM AUTHOR]

Conversational Agents (CAs) are becoming part of our everyday lives, whether in the form of voice assistants (such as Siri or Alexa) or as chatbots (for instance, on Facebook). When looking at CAs, users frequently start to display aggressive behavior towards CAs, such as insulting it. However, why some users tend to harass CAs and how this behavior can be explained remains unclear. We conducted a two-conditions online experiment with 201 participants on the interrelation of human-like design, dissatisfaction, frustration, and aggression to address this circumstance. The results reveal that frustration drives aggression. Specifically, users with high impulsivity tend to severely insult a CA when it makes an error. To prevent such behavior, our results indicate that human-like design of CA reduces dissatisfaction, which is a driver of frustration. However, we also discovered that human-like design directly increases frustration, making it a double-edged sword that has to be further investigated. [ABSTRACT FROM AUTHOR]

Incidents of security breaches have increased and caused immense damage, affecting the stock price. Data breaches are particularly problematic as they have fatal consequences on customer relations. By applying recovery actions after a data breach, a company is able to mitigate these consequences. However, there is a controversy: The recovery actions offered to customers are perceived differently by the company's investors. While customer loyalty can be maintained, the value of the company's stock is damaged. This study examines this controversy through an event study. Real response strategies to data breaches are coded and their effects on investor behavior are examined on the basis of stock value. The results show that apologizing a data breach has harmful effects on investor behavior. The opposite might occur if the response is whitewashed. Further effects can be determined by the affected group and the year of the data breach. [ABSTRACT FROM AUTHOR]

Companies around the world are faced with challenges in dealing with data breaches. While in Germany companies need to notify the affected and fear to lose their valuable customers, in Bolivia, where rapid digital globalization increases vulnerability, data security overall is not a publicly present topic, and customers are directly exposed to the consequences of security incidents. Our study examines the cultural difference in addressing the digital challenge of recovering from data breaches. We investigate through a scenario-based experiment the effect of compensation and remorse on the customer-company relationship. Our results show that German customers are more likely to demand compensation for a data breach as a recovery action, whereas Bolivian customers are satisfied with an apology. We discuss this finding in the context of crosscultural values and practical implications for countries that are currently undergoing a rapid rise in technology and are therefore exposed to substantial security risks. [ABSTRACT FROM AUTHOR]