When Tourists Turn to Algorithm for Fair Pricing

New study delves deeper to find why consumers feel better if algorithms, instead of humans, offer the best rate

By Pan Jingyi, Principal Writer, China Business Knowledge@CUHK

Have you ever booked a hotel room or a flight ticket at what you thought was the cheapest price, only to find a lower one the next day? It is not uncommon for prices of hotel rooms or flight tickets to fluctuate due to various reasons such as demand, availability, and promotions.

Nonetheless, comparing prices from different sources is always a good idea. Many industries, including hospitality and tourism, apply algorithms to determine and utilise price discrimination strategies to optimise revenue and occupancy rates.

Price discrimination is a sales tactic that charges consumers different prices for the same product or service, depending on what the sellers believe the consumer is willing to pay. While it is an effective strategy for maximising revenue, studies have shown that its positive impact will be short-lived if consumers perceive it as unethical and unjust.

Unfortunately, consumers generally view price discrimination as unfair, and their perception of price fairness affects their willingness to pay and overall attitudes towards the brand.

“Consumers favour algorithms being applied to objective tasks and utilitarian consumption because they perceive them as unbiased and not intentionally trying to take advantage of them.”

Prof. Choi Sungwoo

Given consumer feedback greatly impacts business success, a group of scholars, including Choi Sungwoo, Assistant Professor of the School of Hotel and Tourism Management at The Chinese University of Hong Kong (CUHK) Business School, conducted a study to examine how hospitality and tourism firms can reduce such negative views.

The study titled Let Your Algorithm Shine: The Impact of Algorithmic Cues on Consumer Perceptions of Price Discrimination was conducted by Prof. Choi, in collaboration with Prof. Song Myungkeun and Dr. Jing Luo from Dong-A University in South Korea. The researchers proposed that when consumers are presented with an algorithmic cue, where they learn that an algorithm determines the price, their negative response to price discrimination is expected to diminish.

To test this hypothesis, Prof. Choi and his collaborators conducted a tweet analysis and four experiments. They first analysed nearly 900 tweets and found that, in general, when hospitality and tourism companies employ algorithm-driven dynamic pricing strategies, consumers tend to view these practices in a more positive light.

“Consumers favour algorithms being applied to objective tasks and utilitarian consumption because they perceive them as unbiased and not intentionally trying to take advantage of them,” says Prof. Choi.

Does Algorithmic Cue Work?

The researchers then examined how perceived price fairness mediated the effect of an algorithmic pricing cue by randomly assigning adult U.S. consumers to a few scenarios.

The first experiment asked a group of participants to read news about the use of pricing algorithms in the airline industry, while other participants in the control group read similar-length news regarding the industry’s post-pandemic recovery. The result showed that participants reacted less negatively to price discrimination after learning that algorithms were used.

The next experiment used the same flight ticket purchase scenario on a website, and the respondents were presented with a sentence explicitly stating that the price was decided by an algorithm. At the same time, this information was not presented in the control group. Similar to the previous results, participants had fewer negative reactions when the algorithmic cue was presented.

The team then investigated whether the algorithmic cue effects still existed when participants did not directly experience price discrimination. In the third experiment, one group of participants read a news article stating that a fictitious hospitality firm used algorithms to determine its optimal prices, while other participants in the control group read an article stating that the company’s revenue management team was the one deciding the prices.

As expected, the participants perceived the price discrimination as fairer when they knew the price was determined by algorithms rather than humans, even when they were not in a purchase scenario.

Humanoid Features Are Not Always Beneficial

The debate on whether the utilisation of algorithms is good or bad is ongoing. However, the findings of this study challenge the common assumption that consumers are reluctant towards algorithms. The study found that, contrary to popular belief, objective algorithms have an advantage when consumers encounter negative information, such as a post-purchase price reduction.

Prof. Choi notes that the results can be explained through intentionality theory, in which algorithms are considered lacking in mind, meaning they have a lower level of agency compared to humans in terms of thinking, reasoning, and fulfilling intentions.

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How ‘Human’ Should Robots Be?

The researchers further investigated how consumers’ reactions changed based on how human-like the price algorithm appeared. In the fourth experiment, different groups of participants used the live chat to book a hotel room with the assistance of three entities: a guest service algorithm depicted as a robot, a guest service algorithm depicted as a woman named Sam, and a guest service manager named Sam. The participants were then informed that the hotel offered a lower rate for the same room after completing the booking.

The results showed that participants had fewer negative reactions when the less human-like algorithm decided the price. Additionally, their reactions were similar toward the human agent and the human-like algorithm.

Apply Algorithmic Cues Wisely

To achieve the desired result of the price discrimination strategy, researchers suggest the company minimise consumers’ negative perceptions. However, hospitality and tourism managers are unaware of the potential benefit of leveraging algorithms in their pricing practices. In a field analysis of 14 international hotel chains, the team found that none of the hotels presented algorithmic cues to the customers, even though they all used pricing algorithms in their systems.

There were various reasons why hotel managers did so. About 72 percent of the managers predicted a negative or no effect of an algorithmic cue on consumer satisfaction in terms of price discrimination. However, Prof. Choi notes that the study repeatedly found that presenting an algorithmic cue can help reduce perceptions of unfairness regarding price discrimination and improve consumer responses.

“We encourage firms to consider presenting algorithmic cues through various channels, such as a website, news article, or even a live chat, to let more consumers be aware of the use of algorithms,” he says. “This can improve not only revenue management performance but also customer satisfaction.”

But there is a caveat, as Prof. Choi highlights that the algorithmic cues should be applied with caution. “If the algorithm looks and talks more like a human, consumers may perceive it as having a certain level of intention or purpose behind its actions.”

The findings provide insights into how pricing algorithms can be used to improve customer perceptions of price fairness. However, Prof. Choi notes that the actual effects in practice need to be examined as the present study used online experiments to test the impact of algorithmic cues.

“If we want to ensure the robustness of the algorithmic cue effects, external factors such as booking lead time and trust toward algorithms should be examined,” he adds.