Latent segmentation of older adults in the use of social networks and e-banking services

Introduction. This study analyses heterogeneity in the online behaviour of elderly people. Previous research has centred on the socio-demographic segmentation of the elderly regarding their Internet use. Method. The novelty that this study adds is in determining this segmentation through variables that have been especially chosen for studies of the elderly and which are related to their utilitarian use of e-banking, compared to the more hedonic nature of using online social networks. Analysis. The sample was collected using 474 students over 55 years old enrolled in a class of experience in a University in the South of Europe (Spain). We use a latent class cluster model which is appropriate in situations of a posterior segmentation. Results. In dealing with such behaviour in situations of the elderly using these technologies, we have detected the presence of five groups or segments with highly differentiated use-related profiles concerning the variables analysed: venturesomeness, technology anxiety and selfconfidence in information and communication technologies use. Conclusion. We discover the existence of heterogeneity in the behaviour of the elderly regarding services available in Internet. The results support the idea proposed. The stereotype of the elderly cut off from technology is mistaken, as is shown by the different segments found

The Effects of Discrete Emotions on Risky Decision Making

Contrary to the dominant view that generally equates feelings with poor thinking, converging evidence indicates that decisions – including those involving risk – are influenced by affective experiences. Research, however, is limited to studies on undifferentiated, global positive versus negative mood states; less is known about the influence of discrete emotions. The purpose of this research was to extend the affect-cognition literature by (a) examining the effects of discrete emotions varying along the dimensions of valence and arousal, and (b) identifying the systematic ways that discrete emotions underlie risky decision making. We used a set of emotion-laden IAPS images to elicit and compare the impact of incidental emotions on risky decision making. One hundred and twenty-two undergraduate students were randomly assigned to one of the four affective conditions: excitement, contentment, fear, and sadness. Following the emotion induction procedure, participants completed the Choice Dilemmas Questionnaire (CDQ) to assess their risk-taking propensity. Results indicated an interaction effect between valence and arousal for positive emotions, such that excited participants were significantly more risky in their decision making compared to contented participants. The discussion focuses on the theoretical and practical health implications of these findings. We recommend that future research capitalize on the insights gained from emotion research and use it favorably to improve decision making under risk

Corruptive Tendencies, Conscientiousness, and Collectivism

This research investigated the relation between conscientiousness, collectivism, and corrupt tendency–which is represented by moral emotions (shame and guilt proneness). The study was conducted on 117 students (76 male, 41 female; M = 18.93 years old; SD = 1.67 years old) in Jakarta. The result shows that collectivism has positive predictive correlation with the tendency of not doing corruption and that conscientiousness is not able to predict corrupt tendencies. Collectivism of which every group member has as a strong moral identity is suggested to be the ideal ecological situation which need to be built to prevent corruption in Indonesia

DECISION ENVIRONMENTS TO ENCOURAGE MORE SUSTAINABLE INFRASTRUCTURE OUTCOMES

Physical infrastructure (i.e. roads, pipelines, airports, dams, landfills, and water treatment systems) contributes directly to sustainability outcomes such as energy and water use and climate changing emissions. The infrastructure built today will likely impact future generations for many years. Planning, design and development decisions about infrastructure are critical to the future performance of these systems. Such decisions about infrastructure are complex with multiple variables, alternative options, and design stages. To manage decisions that exceed cognitive capacity to consider all options, decision makers often create mental shortcuts (heuristics), and accompanied errors (biases). The potential cognitive biases when dealing with complex decisions about infrastructure are examined and an approach to reframe the decision process during infrastructure planning is explored. A more critical analysis is then provided for decision aids, like energy codes and rating metrics (e.g. LEED and Envision), which are intended to reduce complexity and improve decision making using set goals and scaled points for achieving predefined objectives in sustainability. However, unintentionally, these tools may create additional biases that limit the higher achievements in sustainability that are possible. For instance, framing a decision as a loss, rather than a gain, in value can reduce the decision makers\u27 acceptance of risk and, in turn, influence the outcome. The Envision rating system for sustainable infrastructure is presented to measure the influence of framing effects on engineering decision environments. Envision\u27s current framework, starts users with zero points and points are achieved when design considerations move beyond conventional construction standards. In a modified version of Envision, a higher benchmark is set. Users are endowed points and can lose points for not maintaining high consideration for sustainability. Students (n=41) and professional engineers (n=65) were randomly assigned the replica Envision software or the modified version endowing points. Participants were asked to make design considerations for a redevelopment project using Envision. The results indicate, the endowed version significantly improved students\u27 and professional engineers\u27 consideration for sustainability design achievement. The student participants that were endowed points (n=16) scored 63 percent of possible points compared to the standard group\u27s (n=25) 44 percent (p=0.002). The professional engineers that were endowed points (n=32) achieved 66 percent of possible points compared to the standard group\u27s (n=33) 51 percent (p=0.002). Both students and professional engineers that were endowed points acted loss averse trying to maintain the initial points in sustainability given. These findings suggest engineers\u27 process design decisions by comparing alternative options. And options framed as a loss or gain in value affects the decision outcome. This research underscores the advances possible at the intersection of behavioral science and engineering for sustainability. Slight changes in framing decision aids can lead to greater achievement in sustainability, and at a relatively low cost to implement. Future research should continue to explore how engineers make decisions and what behavioral and decision theories can merge with engineering to encourage more sustainable infrastructure outcomes

Peer Effects in Pro-Social Behavior: Social Norms or Social Preferences?

We compare social preference and social norm based explanations for peer effects in a three-person gift-exchange game experiment. In the experiment a principal pays a wage to each of two agents, who then make effort choices sequentially. In our baseline treatment we observe that the second agent's effort is influenced by the effort choice of the first agent, even though there are no material spillovers between agents. This peer effect is predicted by a model of distributional social preferences (Fehr-Schmidt, 1999). As we show from a norms-elicitation experiment, it is also consistent with social norms compliance. A conditional logit investigation of the explanatory power of payoff inequality and elicited norms finds that the second agent's effort can be best explained by the social preferences model. In further treatments with modified games we find that the presence/strength of peer effects changes as predicted by the social preferences model. As with the baseline treatment, a conditional logit analysis favors an explanation based on social preferences, rather than social norms following for these treatments. Our results suggest that, in our context, the social preferences model provides a parsimonious explanation for the observed peer effect.peer effects, social influence, gift-exchange, experiment, social preferences, inequity aversion, measuring social norms

Technology as a scapegoat

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