Research Roundup: June 2024
Article
When Consensus Clashes With Conviction
The Researcher: Derek Rucker, professor of marketing at Northwestern University, Kellogg School of Management
The Output: The allure of consensus: people (over)seek consensus in selecting group persuasion strategies, Journal of Personality and Social Psychology, 2024
The Focus: When persuading a group, do people prioritize gaining the support of a larger majority or focus on securing a smaller group of true advocates?
The Findings
- Through a series of "persuasion game" experiments, Rucker and his team found that two strategies emerge in group settings: seeking consensus to convince the largest number of supporters toward a given cause, and adopting an extreme position to attract fewer but stronger advocates.
- The study revealed that 88 percent of participants initially favored the consensus approach, driven by a "safety in numbers" mental shortcut.
- However, when encouraged to think more deeply about their choices, 73 percent shifted to the extremity strategy.
The Implications
- Findings suggest that individuals’ instinctive preference for consensus is a safe response, even when it is not the best option.
- Consensus can be an effective strategy, but people can become attached to it and misuse it.
- The research team plans to further study these “persuasion games” in real-world situations.
A New Frontier in Social Media Fact-Checking
The Researcher: Richard Staelin, professor of marketing at Duke University, Fuqua School of Business, and Yiting Deng, professor of marketing and analytics at University College London, School of Management
The Output: Modeling misinformation spread for policy evaluation: a parsimonious framework, Mark Lett, 2024
The Focus: What are the consequences of social media users sharing unverified information on social platforms?
The Findings
- Users often share information without fully understanding its content or ensuring its accuracy, which can lead to the spread of distorted or “fake” news.
- Staelin and Deng propose an innovative model in which social media users anonymously assess the integrity of a post before sharing it.
- This mechanism would provide a "veracity score" for each article, guiding readers to credible content.
The Implications
- Staelin suggests that platforms integrate machine learning to predict the accuracy of posts, further strengthening the fight against viral falsehoods.
- Policymakers could encourage social media companies to adopt anti-misinformation policies.
Revealing Strategic Bias in Peer Evaluations
The Researcher: Linus Dahlander, professor of strategy at ESMT Berlin, Heldge Klapper, assistant professor of management at Purdue University, Mitchell E. Daniels, Jr. School of Business, and Henning Piezunka, associate professor of entrepreneurship and family enterprise at INSEAD
The Output: Peer evaluations: evaluating and being evaluated, Organization Science, 2023
The Focus: How does the desire for a positive self-image affect peer evaluations, especially with the potential to offend colleagues?
The Findings
- Two design features emerged from the study: transparency—colleagues monitoring how their peers have evaluated others in the past and self-selection—colleagues choosing who they evaluate.
- People were more likely to evaluate peers if they were being evaluated but were reluctant to participate if their feedback might offend colleagues.
- People tended to participate in peer evaluations primarily out of self-interest, not to help their peers improve their performance. For example, members may adjust their feedback to appear favorable after seeing others' responses and anticipating their own evaluation.
The Implications
- While transparency can promote accountability, the researchers warn that employees may use such openness to their advantage. For example, an employee may self-select to comment on another employee only when it benefits them rather than providing helpful, constructive feedback.
- Leaders are advised to remain vigilant and find the right balance between ensuring transparency to detect dishonest responses and preventing employees from distorting their evaluations to appear more favorable.
Pregnancy Prejudice in the Workplace
The Researcher: Rachael Potter, research fellow at Justice and Society at the University of South Australia, UniSA Business
The Output: National review: work conditions and discrimination among pregnant and parent workers in Australia, University of South Australia, 2024
The Focus: Are inclusive policies for expectant and parenting workers supported in the Australian workplace?
The Findings
- Potter’s research at UniSA Business uncovered that pregnant workers face the highest levels of discrimination.
- According to the survey results, 64.8 percent of participants reported having excessive workloads during their pregnancy, and 50.8 percent were not informed of workplace changes that could affect them during their leave.
- Furthermore, many respondents reported continued discriminatory treatment after returning to work from leave.
The Implications
- The authors of the study propose recommendations to address this situation, including mandatory external audits to review conditions for pregnant employees.
- They advocate for regular consultations between employers and expectant workers.
- Findings show that organizational management can foster a gender-equal workplace by implementing flexible work arrangements for partners' parental leave and ensuring ergonomic adjustments for pregnant workers to minimize injury risks.
Unlocking Organizational Productivity Potential with Generative AI
The Researcher: Pearson
The Output: Pearson skills outlook: reclaim the clock, Pearson, 2024
The Focus: Can Generative AI (GenAI) play a role in the modern workplace beyond being a tool for creation?
The Findings
- Pearson's Skills Outlook research reveals the potential of GenAI to reallocate millions of employee work hours across five countries.
- By 2026, GenAI could assist workers in saving the following amounts of hours per week: 19 million hours in the U.K., 6 million hours in Australia, 6 million hours in Brazil, 51 million hours in India, and 78 million hours in the U.S.
- In the U.K. specifically, the top three tasks where GenAI could save the most time are maintaining expert knowledge (679,000 hours), developing educational programs and procedures (665,000 hours), and creating visual designs (525,000 hours).
The Implications
- By using GenAI for these tasks, companies can free up employees to focus more on strategy, collaboration, decision-making, problem-solving, and empathy—activities that are better suited to humans.
- GenAI can also contribute to a better work-life balance by enabling faster project completion, giving employees more time for creativity, and helping them avoid burnout.
- Companies could invest in AI training or certifications for their employees. This will also encourage employees to understand the ethical guidelines and company policies for AI.
- This evolving technology represents a significant shift in work processes, allowing organizations to maximize their workforce while boosting productivity and innovation.
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