Jiaqi Wang

We investigate whether the altruistic motivations of investors in the context of socially responsible investment (SRI) are the result of pure altruism (i.e., impact-seeking) or warm-glow altruism, and we explore gender differences in these motivations based on two experimental studies. Study 1 tested university students who were asked to perform a stock bidding task; in this context, a theoretical model was used to distinguish pure altruism from warm-glow altruism. Study 2 involved nonprofessional investors who were asked to perform a simulated stock investment task; the aim of this study was to assess the external validity of the findings obtained in Study 1. Our results reveal that altruistic motivations in SRI generally include both pure altruism and warm-glow altruism. Among female investors, SRI is driven primarily by warm-glow altruism rather than pure altruism, whereas male investors are driven less by warm-glow altruism and more by pure altruism. This study contributes to the SRI literature by innovatively distinguishing among different altruistic motivations through its experimental design and theoretical modeling and by providing the first examination of SRI motivations to focus on the role played by gender in this context. It also offers practical insights for policymakers, managers, and SRI product developers seeking to enhance investors’ altruistic motivations and promote SRI.

This paper concentrates on the event-triggered H ∞ filter design for the discrete-time Markovian jump neural networks under random missing measurements and cyber attacks. Considering that the controlled system and the filtering can exchange information over a shared communication network which is vulnerable to the cyber attacks and has limited bandwidth, the event-triggered mechanism is proposed to relieve the communication burden of data transmission. A variable conforming to Bernoulli distribution is exploited to describe the stochastic phenomenon since the missing measurements occur with random probability. Furthermore, seeing that the communication networks are vulnerable to external malicious attacks, the transferred information via the shared communication network may be changed by the injected false information from the attackers. Based on the above consideration, sufficient conditions for the filtering error system to maintain asymptotically stable are provided with predefined H ∞ performance. In the end, three numerical examples are given to verify the proposed theoretical results.