Decision Science Digest: March 8, 2022

BALTIMORE, MD, March 8, 2022 –

EDITOR’S NOTE: Decision Science Digest is a periodic communique highlighting recent peer-reviewed research published by INFORMS, the largest association for the decision and data sciences, across its 17 journals. This issue highlights four press releases based on the findings of new peer-reviewed articles.

  • Being Popular on Dating Apps May Hinder Your Chances at Finding Your Perfect Match (INFORMS journal Marketing Science)
  • New Research Says Online Ratings Are a Better Predictor of Restaurant Failures Than Traditional Metrics (INFORMS journal Marketing Science)
  • New Model Identifies Where to Put Bikes Lanes Resulting in a Drastic Reduction in Cycling Fatalities (INFORMS journal Manufacturing & Service Operations Management)
  • Online Stores and Brick-and-Mortars Can Co-exist: How a Partnership Can Help Both Businesses Flourish (INFORMS journal Manufacturing & Service Operations Management)

New Research Finds Popularity on Dating Apps May Not be a Good Thing

If you’re popular on a dating app, your potential “perfect match” may not pursue you. A new study in the INFORMS journal Marketing Science finds that people avoid popular users in dating apps because they fear being rejected. This behavior is most often seen in users who have not had many successful conversations in the past. The study, “Star-Cursed Lovers: Role of Popularity Information in Online Dating,” finds that popularity information can lead to strategic behavior if users have post-match rejection concerns. These findings suggest managers of online dating platforms should take this into consideration when designing their user interface. Displaying popularity information can simplify users’ search processes in evaluating potential partners, but it can also have unintended consequences for popular users. Link to full article.

New Research Finds Online Ratings Can Predict Restaurant Failures Months in Advance 

Bad news is good news. New research in the INFORMS journal Marketing Science finds that online ratings can predict restaurant failures months in advance. Hence, giving managers a monitoring tool to assess how they’re doing early enough to intervene and save their restaurant from failure. The study, “I Will Survive: Predicting Business Failures from Customer Ratings,” looked at restaurant ratings from Yelp. The model correctly predicted 7 out of 10 business failures. The researchers find that if the warnings from these monitoring tools are put into action, every second failure could be predicted and potentially prevented. This work makes clear that online ratings are a much better predictor than traditional performance metrics, such as costs, on the success of a business. Link to full article.

New Model Identifies Where to Put Bike Lanes, Resulting in a 50% Drop in Cycling Fatalities in China 

New research in the INFORMS journal Manufacturing & Service Operations Management leverages bike trajectory data to help city planners decide where to build dedicated bike lanes. The study, “Urban Bike Lane Planning with Bike Trajectories: Models, Algorithms, and a Real-World Case Study,” finds that building bike lanes on the most popular roads may not work. Instead, looking at travel patterns from real-world bike trajectory data is essential to bike lane network design. The study results reveal the importance of understanding cyclists’ route choices in bike-lane planning. This model was implemented in China and resulted in access to safer and more convenient cycling lanes for tens of thousands of riders and reduced cycling fatalities by 50%-90%. Link to full article.

The End May Not be in Sight for Brick-and-Mortar Stores: How A Refund Partnership with Online Stores Can be a Win-Win for Everyone

New research in the INFORMS journal Manufacturing & Service Operations Management finds a way to help online stores while creating a new value for brick-and-mortars. It’s a win-win for businesses. The study, “Value of Online-Offline Return Partnership to Offline Retailers,” finds that partnerships with online and third-party retailers with physical stores generates additional value to location partners. Research shows that customers express that a return process is the least favorite part of online shopping, so online retailers have started to collaborate with third-party retailers with physical stores to offer a convenient store-return option. The results: a win-win for everyone. The authors find that this partnership increases the number of unique customers, items sold and net revenue in both store and online channels by 6%-8%. Traditionally, online and offline retailers view each other as competitors, but this research shows they can both succeed by working together. Link to full article.




INFORMS advances and promotes the science and technology of decision-making to save lives, save money, and solve problems. As the largest association for the decision and data sciences, INFORMS members support organizations and governments at all levels as they work to transform data into information, and information into insights that lead to more efficient, effective, equitable and impactful results. INFORMS’ 10,000+ members are comprised of a diverse and robust international community of practitioners, researchers, educators, and students from a variety of fields. 





Ashley Smith


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Decision Science Digest: March 8, 2022

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Ashley Smith
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Catonsville, MD
[email protected]

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