Testing a norm-based policy for waste management: An agent-based modeling simulation on nudging recycling behavior.

The present study uses agent-based modeling (ABM) to examine the effectiveness of a nudge policy for improving recycling behavior. In our simulation, agents' recycling behavior is computed by components of the Theory of Planned Behaviour (i.e., attitudes, perceived behavioral control, social norms) and influenced by other agents as well as their surrounding (i.e., amount of waste in the area). The simulation, based on real data from a Taiwan community district, confirms realistic recycling trends and demonstrates the usefulness and reliability of ABM as a method to examine the effectiveness of waste management policies. An additional step in our simulation was to manipulate the amount of waste in the community to test the effect of a nudge policy based on social norms. Results showed that the policy increases recycling activity, but predominantly in low waste scenarios. This suggests that nudges, in the form of norm-based policies, can be an effective solution to enhancing people's recycling behavior under specific circumstances.

Theories for Computing Prosocial Behavior.

Most relevant theories of prosocial behavior aim at exploring and understanding helping motivations from an evolutionary perspective. This article summarizes findings from research on prosocial behavior from both a socio-economic and psychological perspective. Building on literature exploring the basic processes and determinant variables of helping, we propose a stochastic and dynamic model to simulate prosocial behaviors over time and recreate evolutionary processes of helping behaviors. Such a mathematical model formalizes a procedure for dynamic simulations, including agent-based modeling, which implies non-linear dynamics of prosocial processes underlying helping motivations. Practical implications for organizations and societies are addressed.

Diffusion with social reinforcement: The role of individual preferences.

The debate on diffusion in social networks has traditionally focused on the structure of the network to understand the efficiency of a network in terms of diffusion. Recently, the role of social reinforcement has been added to the debate, as it has been proposed that simple contagions diffuse better in random networks and complex contagions diffuse better in regular networks. In this paper, we show that individual preferences cannot be overlooked: complex contagions diffuse better in regular networks only if the large majority of the population is biased against adoption.

Examiner trust in applicants to the European Patent Office: country specificities.

Indicators based on the probability of applicant citations in patents have been used to emphasize the importance of distinguishing applicant and examiner citations. However, the interpretation of these indicators and of the presence of applicant citations in European Patent Office (EPO) examiner reports is still uncertain. Based on interviews with patent examiners and patent applicants, we develop the idea that applicant citations in EPO examiner reports indicate examiner trust in applicants, and that this trust varies according to national patterns. Using EPO data for over 3,500,000 citations during 1997-2007, we verify that examiner trust in applicants is higher in granted patents. Examiners trust applicants from scientifically or economically strong countries, from member states of the European Patent Organization, and from the same country of the examiners.