Studies of change detection suggest that people tend to overestimate their ability to detect visual changes. In a recent laboratory study of change detection and human intention, Beck et al., found that individuals have an inadequate understanding that intention can improve change detection performance and that its importance increases with scene complexity. We note that these findings may be specific to unfamiliar situations such as those generated routinely in studies of change detection. In two questionnaire studies, we demonstrate that when (...) participants consider real world scenarios such as driving, people are well aware that the intention to detect changes improves detection performance, especially in complex scenes. We suggest several reasons why change detection findings like Beck et al.’s do not generalize to real world situations. More broadly, we suggest a possible way to bridge the gap between lab and life. (shrink)

Studies of change blindness indicate that more intentional monitoring of changes is necessary to successfully detect changes as scene complexity increases. However, there have been conflicting reports as to whether people are aware of this relation between intention and successful change detection as scene complexity increases. Here we continue our dialogue with [Beck, M. R., Levin, D. T., & Angelone, B. . Change blindness blindness: Beliefs about the roles of intention and scene complexity in change detection. Consciousness and Cognition, 16, (...) 31–51; Beck, M. R., Levin, D. T., & Angelone, B. . Metacognitive errors in change detection: Lab and life converge. Consciousness and Cognition, 16, 58–62] by reporting two experiments that show participants do in fact intuit that more intentional monitoring is needed to detect changes as scene complexity increases. We also discuss how this dialogue illustrates the need for psychological studies to be grounded in measurements taken from real world situations rather than laboratory experiments or questionnaires. (shrink)

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We consider the problem of pricing in a network industry focussing in particular on the issue of cross-network pricing (e.g. cross-network cell phone charges). Economic theory tells us in relation to cross-network pricing that collusion or network monopoly may yield welfare as well as profit benefits although any welfare benefits from cross-network collusion may be more than offset by a reduction in competition elsewhere. To address this, we introduce a new regulatory concept: the independent profit-maximising agent. The agent sets prices (...) on cross-network goods taking either (i) a complete, or (ii) an arbitrarily small, share of the associated profit. We examine welfare and profits with and without agent type (i) and (ii) with collusion (network monopoly) between the non-agent firms and without collusion (independent network duopoly). We show that splitting up the network monopoly (creating independent network duopoly) may be inferior for both society and firm(s) compared with a network monopoly ‘regulated’ by an agent and that society always prefers any of the four agent regimes over network monopoly and network duopoly. Indeed, employing the agent may reduce welfare losses by a large proportion while having relatively little effect on profit. (shrink)