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With the emergent focus on human-centered artificial intelligence (HCAI), research is required to understand the humanistic aspects of AI design, identify the mechanisms through which user concerns may be alleviated, thereby positively influencing AI adoption. To fill this void, we introduce "Situation Awareness" (SA) as a conceptual framework for considering human-AI interaction (HAII). We argue that SA is an appropriate and valuable theoretical lens through which to decompose and view HAII as hierarchical layers that allow for closer inquiry and discovery. Furthermore, we illustrate why the SA perspective is particularly relevant to the current need to understand HCAI by identifying three tensions inherent in AI design and explaining how an SA-oriented approach may help alleviate these tensions. We posit that users' enactment of SA will mitigate some negative impacts of AI systems on user experience, improve human agency during AI system use, and promote more efficient and effective in-situ decision-making. [ABSTRACT FROM AUTHOR]

This paper shows that the link between debt restructuring and enterprise investment in emerging economies hinges critically on the political connections. Taking Chinese A-share listed enterprises from 2005 to 2016 as samples, we examine whether and how political connections affect the relationship between debt restructuring and enterprise investment based on the DID method. The results show that compared with nonpolitically connected enterprises, debt restructuring effectively improves the investment efficiency in enterprises with political ties, which is mainly due to alleviating the overinvestment and underinvestment. Furthermore, the positive effect of debt restructuring on investment is more prominent in enterprises with weak strength of political connection. It is worth noting that as the strength of political connection increases from weak to strong, the positive impact of debt restructuring on investment turns to negative impact, which reflects the heterogeneity of connection strength on the relation between debt restructuring and investment. This paper provides new evidence for understanding the investment behaviour of debt restructuring enterprises and provides some policy implications for managers and decision-makers intending to improve the investment efficiency and enhance the sustainable development of enterprises from the perspective of political connections. [ABSTRACT FROM AUTHOR]

By integrating the survival problem into the theory of real option valuation under incomplete markets, we analyze an entrepreneurial firm's optimal survival probability and the joint decisions of business investments and portfolio choices when the business investment opportunity has undiversifiable idiosyncratic risks. Based on the theory of stochastic control, we derive the semi-closed-form solutions for the firm's optimal survival probability, its investment thresholds and the implied option value. The results show that the goal of maximizing the survival probability greatly changes the entrepreneur's business investment strategies, the pattern of asset allocation and the correlation between the option value and the project risks. The comparative statics analysis shows that public authorities should subsidize entrepreneurs and maintain stabile financial markets in order to encourage entrepreneurship. [ABSTRACT FROM AUTHOR]

• AI explainability (XAI) plays opposing roles on human decision-making. • Users' epistemic uncertainty matters when understanding XAI's impacts. • As users' uncertainty increases, only providing prediction rationale is beneficial. • Providing alternative advice may hinder users' advice acceptance. • Showing prediction confidence scores may also hinder users' advice acceptance. In recent years, AI explainability (XAI) has received wide attention. Although XAI is expected to play a positive role in decision-making and advice acceptance, various opposing effects have also been found. The opposing effects of XAI highlight the critical role of context, especially human factors, in understanding XAI's impacts. This study investigates the effects of providing three types of post-hoc explanations (alternative advice, prediction confidence scores, and prediction rationale) on two context-specific user decision-making outcomes (AI advice acceptance and advice adoption). Our field experiment results show that users' epistemic uncertainty matters when understanding XAI's impacts. As users' epistemic uncertainty increases, only providing prediction rationale is beneficial, whereas providing alternative advice and showing prediction confidence scores may hinder users' advice acceptance. Our study contributes to the emerging literature on the human aspects of XAI by clarifying XAI and showing that XAI may not always be desirable. It also contributes by highlighting the importance of considering user profiles when predicting XAI's impacts, designing XAI, and providing professional services with AI. [ABSTRACT FROM AUTHOR]