Previous embodied cognition research suggests that “up” is associated with positivity (e.g., good, divine), whereas “down” is associated with negativity (e.g., bad, evil). We focus on the effect of vertical movements on consumer behavior and go beyond investigating mere affective associations of verticality. In five studies, we provide evidence that the mental simulation of vertical movements has counterintuitive effects on behavior—that is, imagining moving up hampers motivation and performance by boosting self‐worth. A pilot study shows that the imagination of vertical movements affects self‐worth. Studies 1, 2 and 3 show that imagining upward movements (e.g., taking an elevator ride up or taking off in an airplane) diminishes motivation as well as performance. Studies 4 and 5 show that imagining moving upward (downward) makes people feel better (worse) about themselves which, in turn, decreases (increases) their motivation to succeed on a subsequent task, hence worsening (improving) performance. This occurs independently of respondents' mood.
With the growth of worldwide e-commerce, companies are increasingly targeting foreign online consumers. However, there is a dearth of evidence as to whether global consumers prefer to browse and buy from standardized global web sites or web sites adapted to their local cultures. This study provides evidence from five different countries as to whether global consumers prefer local web content or standardized web content. The study also measures how the degree of cultural adaptation on the web affects consumer perception of site effectiveness.
Algorithms have been the subject of a heated debate regarding their potential to yield biased decisions. Prior research has focused on documenting algorithmic bias and discussing its origins from a technical standpoint. We look at algorithmic bias from a psychological perspective, raising a fundamental question that has received little attention: are people more or less likely to perceive decisions that yield disparities as biased, when such decisions stem from algorithms as opposed to humans? We find that algorithmic decisions that yield gender or racial disparities are less likely to be perceived as biased than human decisions. This occurs because people believe that algorithms, unlike humans, decontextualize decision-making by neglecting individual characteristics and blindly applying rules and procedures irrespective of whom they are judging.In situations that entail the potential for discrimination, this belief leads people to think that algorithms are more likely than humans to treat everyone equally, thus less likely to yield biased decisions. This asymmetrical perception of bias, which occurs both in the general population and among members of stigmatized groups, leads people to endorse stereotypical beliefs that fuel discrimination and reduces their willingness to act against potentially discriminatory outcomes. Public Significance StatementThis research suggests that replacing human with algorithmic decision-making might contribute to legitimize discrimination. In situations that entail the potential for discrimination, algorithmic decisions that yield disparities are less likely than human decisions to be perceived as biased. The presumed objectivity of algorithms might foster stereotypical beliefs about stigmatized groups and make people less likely to take action against disparities that could be discriminatory.
The growing awareness about environmental issues places greater responsibility on firms to transmit information about the environmental quality of their products. One of the most innovative ways to achieve this objective is through the 'environmental product declaration'. Unfortunately, from an operating viewpoint, there is a very little evidence on the effects associated with the introduction of this label.In lieu of this context, the paper suggests operating guidelines and a methodological approach for managers who aim to understand under which conditions the EPD can represent a useful tool for the company's competitiveness. In particular, the paper will identify (1) the specific peculiarities and requirements of the EPD; (2) the EPD parameters of attractiveness, related to its potential costs and benefits; (3) an operational framework in order to assess the EPD target audience.In this respect, an empirical analysis on 17 Italian firms will be carried out. Copyright
As algorithms increasingly replace human decision-makers, concerns have been voiced about the blackbox nature of algorithmic decision-making. These concerns raise an apparent paradox. In many cases, human decision-makers are just as much of a black-box as the algorithms that are meant to replace them. Yet, the inscrutability of human decision-making seems to raise fewer concerns. We suggest that one of the reasons for this paradox is that people foster an illusion of understanding human better than algorithmic decision-making, when in fact, both are black-boxes. We further propose that this occurs, at least in part, because people project their own intuitive understanding of a decision-making process more onto other humans than onto algorithms, and as a result, believe that they understand human better than algorithmic decision-making, when in fact, this is merely an illusion.
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