Research Roundup: January 2026

Dive into our monthly Research Roundup, showcasing the latest insights from the business education community to keep you informed of new and noteworthy industry trends. Here are this month’s selections:

Why AI Imitates More Than It Imagines

• Researchers: Dawei Wang and Brian Uzzi, Northwestern University; Difang Huang, Chinese Academy of Sciences; Haipeng Shen, The University of Hong Kong
• Output: “A Large-Scale Evaluation of the Collaborative Potential of Human and Machine Creativity,” PsyArXiv, 2025
• Overview: Can machines truly expand human creativity, or do they simply imitate it at scale? This study aims to answer that question by directly comparing human and machine creativity using the Divergent Association Task, a standardized test that measures divergent thinking by asking participants to generate words as different from one another as possible. Unlike prior studies that relied on subjective judgments, the researchers used an objective, algorithm-based scoring method to assess creativity across humans and large language models, or LLMs.
  
  The analysis drew on about 10,000 human participants from diverse cultural and educational backgrounds and nearly 200,000 test results from leading LLMs. The goal was not only to compare average performance but also to understand how creativity varies, peaks, and breaks down across humans and machines. By examining both baseline performance and how models respond to prompts, randomness, and personas, the study aimed to clarify where collaboration adds value and where it falls short.
• Findings: The findings clarify where human and machine creativity overlap and where they meaningfully diverge. Across the experiments, some advanced AI models achieved creativity scores comparable to human averages; however, humans consistently showed a greater spread in their responses, reaching higher levels at the top end of the distribution. This difference was visible in how ideas were generated: machines tended to return to the same abstract words across trials, while humans produced a broader mix of concrete, less predictable terms.
  
  The researchers attempted to push AI beyond this baseline by prompting models to imitate well-known innovators or by increasing randomness, which reduced performance or led to fabricated words, rather than distinctive outputs. These patterns reflect the study’s conclusion that machines rely on strategies such as “creative mimicry” and randomness, which differ fundamentally from human divergent thinking.
  
  In practice, the study suggests that the greatest value comes not from asking AI to replace creative judgment but from using it as a partner that supports early exploration while leaving strategy, imagination, and adaptation to human capability.

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Who Solves the Shopping Problem Matters

• Researchers: Dominique Braxton, Loyola Marymount University; Eric Spangenberg and Cornelia Pechmann, University of California, Irvine; David Sprott, Claremont Graduate University
• Output: “Managing In-Store Shopping Disruptions With Technology: The Impact of Self-Service Technology on Consumer Control and Decision Comfort,” Journal of Business Research, 2025
• Overview: In physical stores, the biggest friction point is often not the checkout line but the moment something goes wrong during the shopping experience. This study examines what happens when shoppers face common disruptions, such as discovering a product is out of stock or realizing an item is misplaced on the shelf. The researchers focused on self-service technologies already familiar to many retailers, including in-store kiosks used to order unavailable items and store-mode mobile apps that help shoppers navigate aisles, check inventory, and make purchases once a shopper enters a store.
  
  They introduce decision comfort, defined as the emotional ease people feel after making small, in-the-moment decisions, as a critical but overlooked part of the shopping experience. Grounded in self-determination theory, the research asks whether these tools restore a sense of autonomy and competence when shopping plans are disrupted. Across five controlled experiments, the study compares using self-service technology with asking an employee for help to see how each approach shapes control and comfort during the shopping trip.
• Findings: Across all studies, shoppers who used self-service tools to resolve disruptions felt more in control and more comfortable with their decisions than those who relied on employee assistance. For example, in controlled experiments where participants were asked to envision an out-of-stock shopping situation, those who used an in-store self-service kiosk reported higher decision comfort than those who asked an employee for assistance. Similar effects emerged when shoppers used wayfinding kiosks to locate misplaced items or store-mode mobile apps to complete purchases while continuing to shop.
  
  Technology self-efficacy, defined as confidence in one’s ability to use digital tools, consistently strengthened these effects, with high-confidence users experiencing the greatest gains in control and comfort. The study cites prior evidence showing that up to 44 percent of shoppers abandon a purchase when they cannot find an item, while 30 percent have used a smartphone to complete a purchase while still inside the store.
  
  These findings suggest that self-service technologies can reduce friction at critical decision points, but only when shoppers feel capable of using them.

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Which Reviews Hold Revenue

• Researchers: Fernando Comiran and Anthony Patino, University of San Francisco; Velitchka D. Kaltcheva, Loyola Marymount University

• Output: “Motion Picture Reviews as Determinants of Box Office Revenue in the Post-COVID Environment,” Journal of Applied Marketing Theory, 2025
• Overview: The post-COVID film market has reshaped how early performance signals influence box office outcomes. With theatrical release periods shrinking from roughly 90 days to about 30 days or less, studios and distributors have less time to build momentum or extend a film’s earning potential. This study examines which early signals matter most in that compressed environment, focusing on the influence of professional critics versus audience reviews.
  
  The researchers analyzed 535 wide-release films shown on at least 1,500 screens between 2016 and 2024, comparing four pre-COVID years with four post-COVID years. They focused on the percentage decline in revenue from week 1 to week 2, a period increasingly treated by industry professionals as a key indicator of commercial viability. To capture early influence, the study relied on ratings from two leading film review sources—Rotten Tomatoes and CinemaScore—which were completed within the film’s first week of release.
• Findings: The results reveal a clear shift in which early signals are associated with sustaining box office performance. Prior to COVID-19, higher Rotten Tomatoes Top Critics scores significantly reduced the percentage decline in revenue from week 1 to week 2, indicating that professional reviews play a measurable role in moderating early revenue loss. After the pandemic, that effect was no longer statistically significant. Audience sentiment, measured through CinemaScore, was associated with smaller week 1 to week 2 revenue declines both before and after the pandemic. It was the only review measure that remained a meaningful predictor in the post-pandemic period.
  
  This shift aligns with a broader decline in theatrical revenue, with average annual U.S. box office totals falling from 11.5 billion USD between 2016 and 2019 to 8.3 billion USD between 2022 and 2024 and post-opening declines now often reaching 50 percent or more.
  
  In this context, the findings indicate that early audience feedback is more closely associated with maintaining short-term revenue stability than professional critical assessments when release windows are limited.

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The Many Futures of Digital Responsibility

• Researchers: Hannah Trittin-Ulbrich, Markus P. Zimmer, Stefanie Habersang, and Elke Schüßler, Leuphana University of Lüneburg; Leonhard Dobusch, University of Innsbruck; Maren Gierlich-Joas, Copenhagen Business School; Benjamin Mueller, University of Bremen; Cristina Mihale-Wilson, Goethe University Frankfurt; Julia Zeller-Lanzl, University of Hamburg; Stephan Bohn and Georg von Richthofen, Freie Universität Berlin and Humboldt Institute for Internet and Society; Marc-Fabian Körner, University of Bayreuth; Ali Aslan Gümüsay, Humboldt Institute for Internet and Society
• Output: “Digital Responsibility: Building Bridges Between Organization Theory and Information Systems,” Schmalenbach Journal of Business Research, 2025
• Overview: Digital technologies increasingly shape how organizations create value, coordinate work, and interact with society, while also introducing new ethical and social tensions. The study examines corporate digital responsibility (CDR), which defines how organizations account for the ethical, social, and environmental consequences of digital technologies and data use. Rather than treating CDR as a single policy or compliance mechanism, the authors explore how responsibility is understood and discussed across organization studies and information systems research.
  
  The article addresses the fragmentation in how digital responsibility is conceptualized, which has led to a limited shared understanding across various fields. Drawing on prior research and expert perspectives, the authors aim to establish a clearer conceptual foundation. Their focus is on clarifying how responsibility is framed in digitalization research, not on prescribing organizational practices.
• Findings: The researchers found that digital technologies expand what they call “responsibility potentialities,” meaning they widen the range of possible outcomes without determining which ones will occur. These potentialities are evident in how digital systems can enable both responsible and irresponsible forms of action, depending on how they are designed and used. The study highlights tensions, such as the need for AI for sustainability versus the pursuit of sustainable AI, noting that while AI can improve energy efficiency or resource allocation, its development and operation are themselves energy- and resource-intensive.
  
  The authors also emphasize that digital technologies can increase or decrease transparency, autonomy, and control, illustrating that outcomes are not fixed by the technology itself. Responsibility, in the study’s framing, does not reside solely in technology or policy but emerges through ongoing organizational choices that shape how digital tools are applied over time.
  
  For organizations navigating digital transformation, the findings position responsibility as a continuous managerial challenge rather than a fixed standard.

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How Opportunity Recognition Becomes Action

• Researchers: Mohammed Awad Alshahrani, Abdullah Alsabban, and Muhammad Zafar Yaqub, King Abdulaziz University
• Output: “From Opportunities to Ventures Creation: A Moderated Mediation Model of Entrepreneurial Alertness, Intention, and Education on Entrepreneurial Behavior,” Future Business Journal, 2026
• Overview: Why do some people spot a viable business opportunity yet never take the first real step? This study examines entrepreneurial alertness, defined as an individual’s ability to notice opportunities that others overlook, and how it translates into entrepreneurial action in Saudi Arabia.
  
  Using survey data from 405 aspiring entrepreneurs, the researchers investigate how alertness relates to entrepreneurial intention, meaning a person’s commitment to starting a venture, and entrepreneurial behavior, defined as concrete startup activities. Entrepreneurial behavior is measured through actions such as gathering market or competitor information, developing a business plan, initiating product or service development, and beginning marketing or promotion efforts. The study also tests whether engagement in entrepreneurial education strengthens the relationships between alertness, intention, and behavior.
• Findings: The results show that higher entrepreneurial alertness is associated with higher entrepreneurial intention and entrepreneurial behavior among aspiring entrepreneurs in the sample. Entrepreneurial intention plays a linking role, meaning alertness relates to behavior both directly and through intention. In practical terms, individuals who are more alert to opportunities are more likely to engage in early venture activities measured in the study, such as collecting market or competitor information, developing a business plan, or beginning product or service development.
  
  Together, alertness and intention account for nearly 37 percent of the variation in entrepreneurial behavior observed in the data. The study also reports that 57 percent of participants had taken entrepreneurship courses before, and that education strengthens the connection between alertness and intention. The study further shows that the indirect pathway from alertness to behavior via intention is stronger among those engaged in entrepreneurial education than among those who are not.
  
  These findings suggest that sustained entrepreneurial action most likely occurs when opportunity recognition is paired with clear commitment and structured learning that reinforces decision-making and execution.

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