Second out of 8 or Fourth out of 16? Why Ranked List Size Matters

From university rankings to Amazon bestsellers, from Tripadvisor recommendations to employee performance reviews, rankings shape modern life. We rely on them to decide where to study, what to buy, whom to hire, and even which hospital to trust. How do people use rankings when evaluating options?

A recent paper by Uri Barnea (Bocconi Department of Marketing), Alice Moon (Georgetown University), and Jackie Silverman (Vanderbilt University), aims to answer this question. Their research suggests that people consistently prefer items ranked in shorter lists, even when those items are objectively no better than alternatives in longer lists.

For example, a candidate ranked 2nd out of 8 often appears more impressive than one ranked 4th out of 16, despite the fact that both occupy exactly the same percentile position.

Across eight preregistered experiments involving more than 4,400 participants, the researchers found that this effect influences hiring decisions, employee bonuses, restaurant choices, travel planning, and even the selection of everyday products like pens and reusable water bottles.

The hidden psychology of rankings

The paper, titled “How rank position and list length shape people’s evaluations,” explores a simple question: how do people process ranking information?

“We reveal that when people evaluate ranked options, they predominantly base their judgments on the distance from the top-ranked item rather than the distance from the bottom-ranked item or the relative percentile.”

Because people care more about the distance of a ranked item from the top-ranked option, a product ranked “2nd out of 8” (which is only one rank away from the top option) feels superior to an option ranked “4th out of 16”, even though mathematically the relative position is the same.

The study connects these findings to a broader body of research on how people use numeric information to make decisions. Human beings rarely interpret numbers objectively. We rely on mental shortcuts, reference points, and framing cues. In rankings, the top position becomes the dominant anchor. Simply hearing that something is “second” versus “fourth” instantly conveys meaning. But understanding the equivalent percentiles requires additional mental calculation.

Managers are not immune

Companies often rely on ranking systems to make promotion, bonus, and firing decisions. Forced rankings—sometimes called “stack rankings”—are used by many corporations nowadays. Around 30% of Fortune 500 companies now use some form of stack ranking, making understanding this bias quite relevant.

One of the experiments involved real managers with hiring experience. Participants were asked to evaluate job candidates based solely on their internal performance rankings within different departments. One candidate was ranked 3rd out of 12 employees; another was ranked 6th out of 24. Again, both candidates sat at the same percentile.

Yet managers consistently preferred the candidate from the smaller list. The effect remained strong even when participants evaluated both candidates side by side—a particularly surprising result considering that previous research has found that direct comparison often eliminates ranking biases.

In practice, this means that employees in smaller teams may appear stronger simply because their rankings feel psychologically closer to first place. As a result, managers may hire or promote certain employees over others in part because they are ranked within smaller teams. 

Consumers make the same mistake

The effect was not limited to HR decisions. In another experiment, participants chose between hiking trails, restaurants, and tourist attractions presented through realistic Tripadvisor-style images. Once again, people consistently preferred the option ranked in the shorter list.

The bias even survived when participants made real, incentivized choices. In one laboratory study, people selected between two identical black pens from reputable brands. One pen was described as ranked 2nd of 8 in its category; the other as 4th of 16. Most participants chose the first pen.

A seemingly irrational preference emerged even more clearly in another experiment involving reusable water bottles. Here, the shorter-list option actually had a worse percentile ranking than the longer-list alternative. Still, participants preferred it. This finding is especially revealing because it suggests people are not merely simplifying information—they may be systematically making poorer decisions.

How can we overcome this bias?

Based on the underlying psychology, the researchers also discovered that subtle wording changes can dramatically alter judgments.

When participants were reminded how many alternatives an item outperformed—rather than how far it stood from first place—the short-list effect weakened significantly.

Similarly, presenting rankings as percentages instead of absolute positions can affect decisions. When managers saw employees labeled by percentile rather than raw rank, they did not prefer the shorter-list employee.

To avoid this bias, companies could include percentile rankings in any ranked information presented to managers and other decision-makers, which can make ranks across lists of different sizes more equivalent. Companies could also present rankings as a countdown—for instance, starting a “top ten” song list at number 10—to draw attention to just how many other songs those closer to the top of the list are better than. 

A lesson for companies, and for everyone else

The findings are informative for organizations that use rankings, internally or externally. Companies may unintentionally bias hiring or promotion decisions simply through the structure of ranking systems. Consumers may also be nudged by marketers who strategically highlight rankings within narrower categories.

A pizza restaurant advertised as #2 in the small downtown district of a city ” may feel more attractive than one ranked #8 in the entire metropolitan area, even if the latter is objectively superior. That has major implications for digital platforms, university rankings, streaming services, and AI-driven recommendation systems—all environments saturated with ordered lists.

Rankings, in a nutshell, do not merely organize information. They actively shape preferences by leveraging our inherent tendency to care most about how close an option is to the top of the list.