The next big video game Easter Egg is … O.R.?

Ashley Kilgore:

Historically, baseball has been described as America’s national pastime. However, there might be another activity better suited to this title and that is playing video games. That’s right, video games. Over 227 million people in the US play video games for at least one to a few hours per week, which equals out to about 70% of all Americans are video-game fans. But what I’d bet most gamers don’t know, is the role that operations research plays in nearly every aspect of video-game development from design to production to selling.

Joining me today to dive into the world of OR in video games is Xiao Lei, assistant professor with the University of Hong Kong. A self-confessed lover of video games who is also lucky enough to get to help advance the role of OR in gaming. Xiao thanks so much for joining me. It sounds like you are essentially the living embodiment of if you do what you love, you don’t work a day in your life. Would you agree?

Xiao Lei:

Thank you for having me, Ashley. I totally agree with you. I feel incredibly fortunate to combine my passion for video games with my expertise in operations research. It’s truly satisfying to utilize analytics and optimization to enhance video games, while pushing the boundaries of OR simultaneously.

I’m sure many young gamers have dreamed of merging their interests and skills, and I think it’s pretty awesome that I’m one of the first people in the OR community to make it happen. It is motivating and also fulfilling to know that my work impacts not only the experiences of gamers, but also the practices of major industry players and even influences regulators.

Ashley Kilgore:

Xiao, I wanted to share with our listeners, that this interview stems from a post you made on INFORMS Connect. About leveling up video gains with operations research in order to connect with others in the INFORMS community who share your love of OR and video games. In addition to my request to discuss this on the podcast, it also looks like you connected with a few other INFORMS members on that post. Could you share a bit about the different perspectives and experiences that were shared with you?

Xiao Lei:

Absolutely. Actually, when I made the post on INFORMS Connect, I wasn’t sure if I could receive any responses, but I was delighted to see several positive reactions. It was fascinating to hear from various INFORMS members who have different perspectives and experiences in this area. Some members shared their work in scheduling for video games and sports tournaments. Others from gamers’ perspective, found that many decision-making aspects in video games can be viewed as optimization problems.

There are also some people who had industry experience and shared potential applications of OR in server-capacity planning and monetization strategies. I also received some private emails discussing ideas on designing video games to ensure balance and diversified play strategies. The diversity of these perspectives and experiences, highlights the potential for our field to contribute in many ways to the gaming industry. It was truly inspiring to see the passion among INFORMS members thanks to this great forum.

Ashley Kilgore:

Now before we really dive in, I have to ask what came first? A love of video games or a love of operations research?

Xiao Lei:

Well, for me, my love for video games came first. I’ve been playing video games since I was a child and they have always been a significant part of my life. I started studying operations research as a junior in college. And after a few years later when I began my doctoral study at Columbia University, I realized the unique research opportunity in video games from an OR perspective.

This realization opened up a whole new world for me, and I’ve been excited to explore the intersection of these two passions ever since. In fact, my first research project in video games led to an internship at Activision, which is the largest video-game company in the United States.

The industry experience I gained, deepened my understanding of the gaming industry from a company perspective and inspired more research projects later on. Since then, my love for games and OR have mingled together, generating a positive feedback loop and filling my passion for both fields. This unique combination has allowed me to delve deeper in both areas and uncover interesting and valuable insights. I’m eager to see where this journey takes me next.

Ashley Kilgore:

Now with that said, do you have a favorite game and are you playing anything fun now?

Xiao Lei:

Oh, that’s a tough question. There are so many games that I have enjoyed throughout the years, but if I had to pick a favorite it would be Delta 2. Delta 2 is a multiplayer, online, battle-arena game that emphasizes teamwork, strategy and quick decision-making. I’ve been playing it for more than 10 years and I’m still actively playing it now.

In fact, my experience with Delta 2 has inspired me in my research. Particularly because this game has experimented with various monetization strategies and matchmaking methods over these years. These aspects are closely related to our research in revenue management and online marketplaces, but they also present unique challenges specific to the gaming industry. My experience with these strategies has provided me valuable insights that I can apply to my research.

Ashley Kilgore:

I’d love to know, has OR been a part of video-game development since the beginning, or are these fairly new applications?

Xiao Lei:

There are some general applications such as revenue management and scheduling, but the direct applications of OR tailored specifically for video games are relatively new. If we look at the flagship journals in our field such as Management Science and [inaudible 00:07:35], we find fewer than five papers published on this topic, all appearing after 2020. This indicates that the exploration of OR in the context of video games is still in its early stages.

One of the reasons for the growing interest in OR plus video games, is the increasing complexity of video games and the vast amount of data they generate. As the gaming industry has evolved, games have become more intricate, requiring sophisticated models and techniques to ensure enjoyable game play.

Additionally, the data collected from players’ interactions has grown exponentially, creating a need for a advanced-data analysis method to better understand player behavior and preferences. This relatively unexplored area also presents a blue ocean for researchers. Particularly for young researchers who have grown up with video games and have a deep understanding of their mechanics and appeal. We can shape the future of this field.

Ashley Kilgore:

All right, now let’s dive in a little bit deeper. Can you describe some of the OR applications that are the most common or impactful in video games?

Xiao Lei:

No problem. There are numerous applications in this market, and many such as revenue management and matchmaking share some similarities with other online markets. Here, I’d like to focus on a relatively lesser-known application, which is called dynamic difficulty adjustment. Dynamic difficulty adjustment aims to provide a smooth-gaming experience for players by tailoring the game’s difficulty level in real time.

In most games, players have an inventory of resources like weapons, health points, and bullets, and the game’s difficulty is often influenced by the availability of these resources. To maintain an enjoyable and balanced experience, the game may dynamically adjust the difficulty by providing players with random resources such as health points or bullets as needed.

The classic method for managing this process is essentially an inventory-management model, ensuring the right amount of resources are provided to the players at the right time. This application is surprisingly not readily known in our community, despite its importance to the gaming industry. As games become more complex and required increased interaction between players or one’s knowledge from dynamic control, could be critical for providing a satisfying experience in modern games.

Ashley Kilgore:

Now you’ve published a number of papers on your work, including one in the INFORMS Journal, Management Science. Could you share a little bit about these?

Xiao Lei:

Absolutely. I’ll be happy to share a bit of two of my papers actually, which address two critical problems in the video-game industry. These problems are motivated by my personal experience as a gamer, my industry experience as a data scientist, and also my extensive communication with practitioners. We have been able to deliver many of our findings to regulators and industry professionals, which is truly exciting.

First, let me talk about my paper on revenue management. This paper is the one that was published on management size. As you may know, video games rake in billions of dollars every year, and a big chunk of that revenue comes from something called loot boxes. These are random, virtual items whose contents are hidden until after purchase. Think of it like buying Pokemon or baseball cards. Players pay a small amount, sometimes as low as $1 and get a random item in the game.

Loot boxes alone generated more than $30 billion every year, they’re already a cash cow in the industry. However, there has been no explanation on why loot boxes are popular, and how to price and design loot boxes for revenue maximization. In our paper, we formulate this problem as a stochastic control or problem. And provide insights on how to set prices as well as some design problem, such as whether we should promise that you will never receive a duplicate item. Or if you receive something you don’t like, whether I should offer you a chance to salvage the item.

We also discuss this problem from the consumer side and find many counterintuitive insights. For example, we find that when the seller allows the customer to trade in their unwanted items, it could increase the revenue but barely increase the consumer surplus. This is because when a trading system is offered, the corresponding price also goes up, and their joint effect on consumer surplus is negative in general.

There are also regulatory issues. For example, it is easy for the seller to cheat and manipulate the outcome of loot boxes. In the paper, we also reveal some subtle manipulation strategies that gain substantially more revenue and thus need proper regulation.

The Federal Trade Commission cares about this issue, and we actually got a chance to present this paper to the FTC in 2019, so this is about the first paper. The second paper I’d like to share is a working paper, and it’s about managing player engagement in competitive games like chess or a sports game, so players, they play against each other.

In these games, the matchmaking system plays a crucial role in shaping the customer experience and engagement. The industry current approach is called skill-based matchmaking, which pairs players with similar skills to ensure fair matches. However, this doesn’t always lead to the best experience for casual players, who might just want to relax after a long day and not be pushed to their limits. In our paper, we developed a dynamic-optimization framework for matchmaking, that considers player skill levels and engagement stakes, aiming to improve the long-term engagement.

We also investigated the controversial pay-to-win feature, where players can pay for in-game advantages. Surprisingly, our findings suggest that in some cases, offering a pay-to-win feature can actually increase the overall engagement and even benefit non-paying players. We presented this research to industry leaders like NetEase, ByteDance and Riot Games who showed great enthusiasm for our results. These two papers are highly complete projects and I also have several ongoing projects. I can’t wait to share those findings with both the industry and academic community once they’re complete.

Ashley Kilgore:

I have to say, I like that term casual player. That’s the speed that I play at. I’d always just refer to myself as not very good, and I’m going to use casual player moving forward to describe my abilities. I have to think-

Xiao Lei:

Yeah. We can save your engagements, yeah, we can save you from leaving.

Ashley Kilgore:

I have to say, this all sounds so exciting. What do you think the next big advancement will be in OR in video-game design and production?

Xiao Lei:

This is a great question. I believe the future can be categorized into three main steps. The first step is to better understand the player behavior and preferences. This requires advanced-econometric models and better experiment designs, particularly due to the unique context and repeated interactions in video games.

For example, when companies conduct AB tests, control players and test players may interact through the matchmaking process, which would lead to a systematic bias in estimating the treatment effect, so we need better methodology to identify these patterns. Once we identify player behavioral patterns, the second step is to dynamically monitor their experiences over their lifetime. As I mentioned earlier, one thing we can do is to optimize the matchmaking system. However, there are many other aspects we can consider, such as keeping the game fresh by planning seasonal events strategically to prevent player satiation.

Finally, we shouldn’t forget about the ethical side of things. We need to strike the right balance between keeping players engaged and preventing digital addiction. Plus, there’s also a code trend called gamification, where we apply gaming elements to enhance engagement in education or productivity in teamwork. I think that’s definitely something worth exploring further, as it aims to promote social good by incorporating fun elements from games. These are from the topic perspective.

From a technical perspective, AI is going to play a huge role in all of this. AI can help us adapt to and make use of the vast amount of data generated by players, while OR can assist us in monitoring and controlling the game experience more effectively. For instance, imagine using AI to generate content based in a game, which is super cool. Right?

But then we can take it one step further and use OR models to sequence and schedule that content, making sure it is introduced to players in a well organized and engaging manner. When we combine the power of AI with the precision of OR, we can create truly amazing and immersive-gaming experiences that adapt to players need and preferences, it will be a real game changer.

Ashley Kilgore:

Xiao, thanks so much for joining me and sharing this fun and informative look inside OR and video games. You can really tell, and hearing you talk about the work you do, your excitement for it. It really comes through. Any final thoughts or other examples of OR in action and gaming before we go?

Xiao Lei:

Well, thank you so much for having me. It’s been a real pleasure to chat with you and share my insights with the INFORMS audience. Before we wrap up, I’d like to give a shout out to my advisor, Adam, for his invaluable guidance and support throughout this journey. I’m also grateful to my amazing co-authors who have contributed their expertise and helped bring these research projects to life.

I would also like to thank my former colleagues in the industry. Their knowledge and input have been extremely valuable, giving me essential insights into research topics and model settings. To sum up, OR has so much to offer the gaming industry, and there are many untapped areas for research and collaboration.

It’s an exciting frontier for operations researchers, especially young researchers who have grown up with extensive gameplay experience. I’m sure that as more or professionals and game developers work together, we will continue to see groundbreaking advancement in video games. Once again, thank you for having me and I hope our conversation has sparked some interest in this fascinating field.

Ashley Kilgore:

Want to learn more? Visit ResoundinglyHuman.com for additional information on this week’s episode and guest. The podcast is also available for download or streaming from Apple Podcasts, Google Play, Stitcher, and Spotify. Wherever you listen, if you enjoy Resoundly Human, please be sure to leave a review to help spread the word about the podcast. Until next time, I’m Ashley Kilgore and this is Resoundingly Human.