More useful to you: Believing that others find the same objects more useful
Ignazio Ziano & Daniel Villanova
Journal of Experimental Social Psychology, forthcoming
People routinely evaluate how useful objects are to themselves and to others. Seventeen experiments (with U.S. American and French participants, total N = 8016) show that people believe others find the same objects more useful than they themselves do. Using both mediation analysis and causal chain designs, the authors show that overestimating usefulness to others is caused by a self-serving bias in perceived materialism and by the belief that others need the same object more. The effect is reduced if participants own the object in question, for target others who are well-known, and for objects considered less indicative of materialistic values. The effect also drives overestimation of others' willingness-to-pay. The authors find evidence against alternative explanations involving perceived sophistication or specifically thinking of object users. The authors discuss theoretical implications for self-other biases and materialism, as well as practical implications for proxy decision-making, gift-giving, and negotiation.
Negativity drives online news consumption
Claire Robertson et al.
Nature Human Behaviour, forthcoming
Online media is important for society in informing and shaping opinions, hence raising the question of what drives online news consumption. Here we analyse the causal effect of negative and emotional words on news consumption using a large online dataset of viral news stories. Specifically, we conducted our analyses using a series of randomized controlled trials (N = 22,743). Our dataset comprises ~105,000 different variations of news stories from Upworthy.com that generated ∼5.7 million clicks across more than 370 million overall impressions. Although positive words were slightly more prevalent than negative words, we found that negative words in news headlines increased consumption rates (and positive words decreased consumption rates). For a headline of average length, each additional negative word increased the click-through rate by 2.3%. Our results contribute to a better understanding of why users engage with online media.
Does Setting a Time Limit Affect Time Spent?
Jackie Silverman, Shalena Srna & Jordan Etkin
Duke University Working Paper, March 2023
New technologies have made it easier than ever before to consume content online. Consumers spend hours browsing social media, playing games, and watching videos. To aid in consumers’ time management, many companies (e.g., TikTok, Instagram, YouTube) have recently introduced the option to set a “time limit” on their platforms. These features ask consumers to select an amount of time after which they would like to receive an alert. But while giving consumers this option may be well intended, how does it actually impact time spent? Contrary to expectations, rather than leading consumers to spend less time on an activity, five pre-registered experiments demonstrate that setting a time limit can have the opposite effect. This occurs because consumers implicitly treat time limits like budgets, perceiving time up to the limit as earmarked for the activity and facilitating such spending. Consequently, setting a time limit (vs. not) can increase time spent. The findings further understanding of the impact of new technologies, how consumers mentally budget time, and the effects of limits. Further, they have clear implications for the use of limits as a time management tool: merely providing the option to set a time limit may be insufficient to protect consumer wellbeing.
Examining the outcomes of entrepreneur pitch training: An exploratory field study
David Clingingsmith, Will Drover & Scott Shane
Small Business Economics, March 2023, Pages 947–974
With the rise of accelerators, angel groups, and business plan competitions, pitching has become an important step for most entrepreneurs raising capital. In this exploratory study, we investigate the effects of pitch training, exploring a variety of outcomes over two time horizons. We conducted a field experiment that randomly assigned 271 would-be entrepreneurs at four elevator pitch competitions to receive one of four pitch training treatments or a null treatment. We observe that pitch training — when received the day of the competition — leads entrepreneurs to improve their pitches, although it causes short-term disruption to pitch delivery. Over the following 30 months, all varieties of pitch training cause entrepreneurs to work more on their pitches, to participate in more business plan competitions and accelerator programs, and to engage in entrepreneurial learning beyond the pitch itself. Entrepreneurs who receive pitch training also are less likely to have employees and are more likely to abandon their initial ventures and founder roles. We discuss the implications of these exploratory observations for the development of theory about pitch training.
Platform Governance in the Presence of Within-Complementor Interdependencies: Evidence from the Rideshare Industry
Hyuck David Chung, Yue Maggie Zhou & Sendil Ethiraj
Management Science, forthcoming
Existing studies suggest that platform access restriction may cause restricted complementors to switch to competing platforms, which will increase complement quantity on competing platforms. We re-examine this prediction by accounting for the impact of economies of scope on complementor responses to platform access restriction. We argue that restricting a complementor’s access on a platform may prevent it from achieving economies of scope from multi-homing, thereby incentivizing it to abandon both the restricted and (unrestricted) competing platforms. Using rideshare data in New York City, we compare the numbers of trips made by Lyft and Uber drivers, respectively, before and after Lyft restricted drivers’ access on its platform. We find that Lyft’s access restriction reduced trip numbers not only on Lyft but also on Uber. In addition, both Lyft’s and Uber’s trip numbers decreased not only during the restricted low-demand periods (e.g., non-rush hours) but also during the unrestricted high-demand periods (e.g., rush hours). In contrast, after a substantial number of multi-homing drivers left both platforms following Lyft’s access restriction, a subsequent access restriction by Uber led to an increase in trip numbers on Lyft. These results highlight the importance of accounting for interdependencies across complementor activities when designing platform governance policies.
Machine Talk: How Verbal Embodiment in Conversational AI Shapes Consumer-Brand Relationships
Anouk Bergner, Christian Hildebrand & Gerald Häubl
Journal of Consumer Research, forthcoming
This research shows that AI-based conversational interfaces can have a profound impact on consumer-brand relationships. We develop a conceptual model of verbal embodiment in technology-mediated communication that integrates three key properties of human-to-human dialogue -- (1) turn-taking (i.e., alternating contributions by the two parties), (2) turn-initiation (i.e., the act of initiating the next turn in a sequence), and (3) grounding between turns (i.e., acknowledging the other party’s contribution by restating or rephrasing it). These fundamental conversational properties systematically shape consumers’ perception of an AI-based conversational interface, their perception of the brand that the interface represents, and their behavior in connection with that brand. Converging evidence from four studies shows that these dialogue properties enhance the perceived humanness of the interface, which in turn promotes more intimate consumer-brand relationships and more favorable behavioral brand outcomes (greater recommendation acceptance, willingness to pay a price premium, brand advocacy, and brand loyalty). Moreover, we show that these effects are reduced in contexts requiring less mutual understanding between the consumer and the brand. This research highlights how fundamental principles of human-to-human communication can be harnessed to design more intimate consumer-brand interactions in an increasingly AI-driven marketplace.