MIS Quarterly

Announcement:

As some of you may have noticed, we haven't been posting on Facebook recently. We will be shuttering this channel for the time-being as we look to focus on opening new formats for communication.

If you follow us here but not on LinkedIn, it is highly recommended you head over and drop a follow. Lots of great content surrounding the Management Information Systems discipline, beyond just the papers themselves (but those too!).

https://www.linkedin.com/company/mis-quarterly/

See you there!

We kick off Volume 49, Issue 4 of MIS Quarterly with the compelling editorial "Beyond Green IT: From Digital Sustainability to Responsible Technology" by MIS Quarterly Editor-in-Chief Sue Brown (The University of Arizona) exploring the effects posed by AI on our efforts to build a sustainable digital future.

A responsible technology agenda for the modern era must consider the trifecta of people, profits, and planet, and the trade-offs that AI introduces across all three.

Take for example Microsoft’s disclosure that water usage rose 34% with the rollout of OpenAI models. A significant statistic that is exemplary of a growing tension seen around the world: AI’s enormous potential to improve education, health, and work, versus the equally monumental environmental and societal costs that accompany it.

From mental health and job design to misinformation, energy consumption, and civic trust. AI is reshaping every dimension of digital sustainability.

And IS researchers are uniquely positioned to lead this effort: designing responsible systems, evaluating sociotechnical trade-offs, and expanding our research questions from “can we build it?” to “for whom does it work, and at what cost?”

Shifting this mindset towards responsible technology isn’t optional. It’s the critical foundation for our sustainable digital future.

Read the full editorial for free at MIS Quarterly:
https://doi.org/10.25300/MISQ/2025/494E1

🎉 MIS Quarterly Volume 49, Issue 4 is out now!

As we head into the holiday season, we’re excited to share the final MISQ issue of the year — featuring new research that advances the field of information systems and sparks fresh conversations across the community.

In this issue, you’ll find:

- Insights into the role of chatbots in providing judgment-free mental health support
- Research on how real-time sales data shapes the behavior and strategies of livestream sellers
- New theories on how to design effective guardrails within human–AI ecologies

📅 Release date: December 1, 2025
📖 Volume 49, Issue 4
🖥️ https://misq.umn.edu/misq/issue/49/4
👁️‍🗨️ Full Table of Contents below

Check it out!

When It Pays to be Targeted: How Investors React to Ransomware Hits and Near Misses

In theory, any ransomware attack should make investors nervous: being targeted by hackers is well-known to cause a disastrous disruption to operations, eroding trust and often costing millions.

But a surprising find by researchers Sebastian Schuetz (University of Colorado Boulder), Yan Chen (Florida International University), Jens Forderer (University of Mannheim), and Yusi Ma (LSU) shows that is not always the case.

Their latest publication in MIS Quarterly establishes businesses that are able to narrowly avoid ransomware and hacking attempts often see investor confidence bolstered.

The team examined U.S. firms that disclosed ransomware incidents and found a striking pattern:

📉 Firms hit by ransomware suffered an average –4.4% stock price drop after disclosure.

📈 Firms that narrowly avoided disruptions—so-called near misses—actually saw +2.9% gains.

But why?

The researchers point to norm theory and outcome bias. Investors tend to compare what happened to what could have happened.

So when a company reports that it avoided major damage, investors see that as proof of resilience—even though the firm was still vulnerable in the first place.

However, the paper asserts that such optimism can also be dangerous. Near misses may mask real risks and systems that barely held up this time around might fail the next.

The researchers warn, these positive stock reactions represent a “call for caution”: firms and investors alike should resist the temptation to treat near misses as victories.

In an age of escalating cyber threats, this research reminds us that markets don’t always respond rationally to risk. Averted disasters can look like success stories—but sometimes they’re just lucky escapes.

📖 Read the full paper: Does Ransomware Make Investors “WannaCry”? On Investors’ Divergent Reactions to Ransomware Hits and Near Misses https://lnkd.in/g7hPepwJ

The Complementor’s Dilemma: How Partners Become Platform Leaders

In platform ecosystems, not all players start in the spotlight. Many begin as complementors, businesses that build on another platform’s foundation such as app developers on Apple’s App Store or merchants on Amazon.

But what happens when a complementor grows so powerful that it starts to challenge the platform itself? This is the tension at the heart of the complementor’s dilemma.

A new study by Shiyuan (Eric) Liu (Wenzhou-Kean University), Ola Henfridsson (University of Miami), Jochem Hummel, and Joe Nandhakumar (University of Warwick), published in MIS Quarterly, unpacks how complementors can pursue growth without losing the platform support they depend on.

Drawing on the in-depth case study of Douyin (the Chinese version of Tiktok), researchers show how it navigated dependency on dominant platforms like Weibo and WeChat—transforming from a small complementor in 2016 to a focal actor with over 200 million users by 2018.

Their findings highlight that successful complementors:
✅ Balance dependence and independence by leveraging the focal platform’s reach while slowly building their own user base.
✅ Time their moves strategically and avoiding direct competition until they have sufficient traction.
✅ Manage relationships, not just technology by nurturing alliances that reduce friction as they scale.

Why it matters:
Understanding and managing this relationship is a critical step for businesses from start-ups to those whose services seem like natural complementors. Navigating growth and timing means walking a fine line between collaboration and competition.

It isn’t just a strategic challenge, its what separates those who stay dependent from those who become platforms in their own right.

📖 Read more: The Complementor’s Dilemma: Navigating Growth Ambitions and the Dependency on Focal Actors in Platform Ecosystems
https://lnkd.in/gbC9AdXj

Organizing for AI Innovation: Why Traditional IT Models Fall Short

As AI innovation accelerates across industries, many organizations are discovering a hard truth: you can’t manage AI the same way you manage IT.

A new study by Yu-Kai Lin and Likoebe Maruping (Georgia State University), published in MIS Quarterly, explores this distinction and its deeper implications by casting U.S. patents for both AI and IT innovations under the microscope.

Their findings reveal a crucial pattern:
- AI innovations tend to be less radical—they evolve existing systems rather than completely reinvent them.
- They’re also more process-oriented—focused on improving how things work, rather than introducing brand-new products.

These insights have major implications for how firms organize their R&D, structure teams, and allocate resources for AI-driven projects. The authors propose a new organizing logic for AI innovation—one that recognizes AI’s distinct nature and integrates iterative, process-focused experimentation rather than top-down, one-off initiatives.

Why this matters for leaders and innovation managers:
➡️ Treating AI like traditional IT innovation can stall progress and waste investment.
➡️ Success in AI requires cross-functional collaboration between data science, operations, and strategy.
➡️ The future of digital transformation depends on designing organizations for AI—not just adding AI to them.

📖 Read the full paper: Organizing for AI Innovation: Insights from an Empirical Exploration of U.S. Patents https://doi.org/10.25300/MISQ/2025/18765

The role of AI Automation in Transforming Faster Evidence-based Medical Decisions

A well-paced single systematic review in medicine can easily take over a year to complete. It require assembling teams of experts to comb through thousands of studies in order to find reliable evidence for clinical decisions. It’s painstaking but essential work. And it's a major bottleneck for advancing evidence-based medicine.

A new study by Rong Liu (Florida International University), Jingjing L. (University of Virginia), Marko Zivkovic (Genesis Research Group), and Ahmed Abbasi (University of Notre Dame)—published in MIS Quarterly—shows how AI can speed up this process without cutting corners on expertise.

Their system, called FastSR, uses 'few-shot learning', a form of AI that learns from very limited data, to automate key parts of the systematic review process. Unlike typical machine learning models that need thousands of labeled examples, FastSR learns from a handful of expert-labeled samples and replicates the logic and judgment of clinicians.

The results prove promising:
✅ 65% faster completion of systematic reviews
✅ Higher accuracy than other machine learning methods
✅ Expert-augmented, not expert-replaced

This work demonstrates the power of AI in high-expertise, low-data environments—a frontier for digital transformation in healthcare, law, finance, and other complex domains.

The takeaway:
The most impactful AI systems work best when they're not designed to replace experts but to amplify them instead.

📖 Read the full open access paper: Automating in High-Expertise, Low-Label Environments: Evidence-Based Medicine by Expert-Augmented Few-Shot Learning https://doi.org/10.25300/MISQ/2024/18573

Mobile Advertising in a World of Distraction: How Attention Shapes Ad Effectiveness

Marketers have long chased the golden balance of how to deliver the right message to the right person at the right time. But in today’s reality of multiscreen, distraction-filled environments the reality is that our attention is constantly being pulled in a million directions. So how can advertisers break through the noise without annoying users or wasting impressions?

A new study by Siddharth Bhattacharya (George Mason University), Heather Kennedy (University of Guelph), Vinod Venkatraman (Temple University), and Sunil Wattal (Temple University) explores how environmental distractions and dual-task interference affect mobile advertising performance.

Using a series of controlled lab experiments with a custom-built app, the researchers examined how pop-up ads perform when users are already engaged in another task—like texting, browsing, or watching TV—amid additional background distractions.

Key insights:
- When users are only mildly distracted, well-timed, contextually aligned ads can actually enhance engagement.
- As distractions multiply, attention becomes diffused, making it harder for ads to register or stick in memory.
- The sweet spot? Align ad timing and content with environmental context to boost recall and reduce annoyance.

💡 Takeaway for marketers:
In a world of divided attention, context is the new targeting. Understanding where and how users’ attention flows—across devices and environments—can turn distraction into opportunity.

This research bridges neuroscience, marketing, and information systems to help advertisers design campaigns that resonate in real-life, multiscreen settings by identifying the most impactful timing and mindset of audiences.

📖 Read the full study:
Mobile Advertising in Distracted Environments: Exploring the Impact of Distractions on Dual-Task Interference https://doi.org/10.25300/MISQ/2024/17758

Augmented Reality at Work: When Digital Overlays Help—or Hinder—Performance

As augmented reality (AR) technologies move from novelty to necessity, organizations are exploring how digital overlays can boost productivity in complex, real-world tasks. But when does AR actually help versus hurt performance?

This was the question raised by Runge Zhu (Central University of Finance and Economics), Cheng Yi (Tsinghua University), and Ting Li (Erasmus University Rotterdam) - and their findings offer critical insights.

Conducted in an aircraft maintenance field experiment, the study compared workers using AR headsets versus mobile phones to access task information.

Key findings:
- AR strongly enhances performance when information is used in a physical context (e.g., where to look or what part to fix).
- However, it can reduce effectiveness when complex information leads to cognitive overload.
- Performance impact is linked to influence on attention. Keeping users focused when context matters, but distracting them when detail does.

Takeaway for digital transformation leaders:
AR is most powerful when it simplifies, not complicates, attention. Success is reliant on balancing the right information, the right channel and the right timing.

This research provides a compelling schematic for firms implementing AR in manufacturing, maintenance, or logistics - highlighting the importance of attention management in measuring the ROI of augmented reality.

📖 Read the full study in MIS Quarterly:
Augmented Reality at Work: Attention Management and Its Impact on Work Performance https://doi.org/10.25300/MISQ/2025/18944

Augmented Reality at Work: Attention Management and Its Impact on Work Performance1 Augmented reality (AR) is rapidly emerging as a transformative display technology, blending computer-generated content with the real-world environment in r

💡 When Incentives Backfire: Lessons from Online Health Communities

The rise of online health communities (OHC) have provided healthcare practitioners with a modern means to reach patients and access an additional income stream. As part of recruiting for OHCs, short-term incentives are often used as a tool to build the community of physicians at the core of their digital platforms. But is this model sustainable? Do the physicians still contribute after the lure of short-term incentives expire?

A new study by Xiaofei Zhang (Harbin Institute of Technology), Karen Xie (University of Connecticut), Bin Gu (Boston University), and Xitong Guo (Sichuan University & Harbin Institute of Technology) examined the role of incentives in the long-term rise and fall of physician contributions for a leading online health community.

Their findings:
Doubling introductory incentives drove a temporary boost in physician consultations. But once the incentives ended, contributions fell drastically.

Why? Physicians anchored their expectations to online earnings, not offline salaries—a classic case of mental accounting.

🔑 Takeaway for platform managers:
- Short-term incentives can set expectations in ways that undermine long-term engagement.
- Sustainable participation comes not just from financial rewards, but from intrinsic motivators like professional reputation, community impact, and meaningful connections.

📖 Read the full paper in MIS Quarterly: Engaging Physicians with Introductory Incentives: References to Online and Offline Income https://lnkd.in/gQvmdCB4

Nonbinding contracts are common in industries where uncertainty is high—like trucking freight and construction—but they often underperform because there’s no penalty for refusal.

A new study by Ali Shirzadi Babakan (University of Georgia), He Li (Clemson University), and Bill Kettinger (Clemson University) shows how utilizing a digital platform-enabled spot marketplace can greatly improve the performance of nonbinding contracts.

Examining the Amazon Freight platform, their research found that introducing a digital spot marketplace can effectively:

- Expand carrier capacity
- Lowers spot market prices
- Reduces reliance on fragile contracts for short-haul loads

More vital, the effect is strongest in volatile markets—the very places where reliability is hardest to achieve.

The takeaway? Digital platforms don’t just connect buyers and sellers. They can redesign how contracts function in uncertain scenarios while boosting efficiency across entire industries.

📖 Read the full study: Do Digital Platforms Improve the Performance of Nonbinding Contracts? Evidence from the Amazon Freight Platform https://doi.org/10.25300/MISQ/2025/18678