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Dynamic pricing can optimize profits but alienate customers

In addition to taking supply or production costs into account, companies increasingly use customer-level data to make pricing decisions, often with the help of artificial intelligence.

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If you’ve ever seen a steep increase in the fare for an Uber to the airport on a Friday, or you’ve checked an item’s cost on Amazon, only to see it has changed hours later, you might have experienced algorithmic pricing.

That’s the practice of using algorithms to automatically adjust the price of goods or services based on factors such as demand, competitor pricing, inventory levels, or data about the customer.

While such pricing practices can squeeze out extra profit, they can also carry a marketing risk if not carefully implemented, according to Gizem Yalcin Williams, assistant professor of marketing at Texas McCombs. In 2012, Uber was widely criticized for raising ride prices during Hurricane Sandy. More recently, customers have expressed outrage over concert ticket surge pricing.

In a paper, co-written with an interdisciplinary group of 12 other researchers, Williams examines algorithmic pricing and the challenges companies can face when integrating it with their other objectives. The researchers offer some preliminary dos and don’ts for aligning pricing with marketing strategy, regulations, and avoiding customer backlash.

One potential factor in customer backlash, Williams says, is driven by feelings of unfairness.

“Let’s say that I just got myself something from Amazon, for my dorm, and then a couple of days later, I saw that the price changed,” she says. “I now feel like I overpaid for it, regardless of how good the product is.”

By the same token, seeing a price increase later might trigger elation, she says. “If I feel like I bought it at a lower price, I feel like I was smart.”

When Prices Get Personal

If pricing sometimes feels a bit more personal when algorithms are involved, Williams says, that’s because it is.

In addition to taking supply or production costs into account, companies increasingly use customer-level data to make pricing decisions, often with the help of artificial intelligence.

The exact data that go into the algorithm might not be always known, Williams says. “But what if the price I receive is different than others because of my own data, such as my shopping history, demographics, or location? Shoppers might react to the same price differently, depending on which data they think affected the price set by the company’s algorithm.”

Besides eroding customer loyalty, companies can face regulatory or legal attention when dynamic or surge pricing goes awry. Last year, the grocery chain Kroger was scrutinized by members of Congress over its plans to introduce algorithmic pricing at its stores.

Practical advice on pricing

As part of its research, Williams’ team surveyed pricing managers and conducted in-depth interviews with five strategic-pricing experts. They offered several pieces of advice.

  • Companies should be aware of how accepting their customers are — or are not — of dynamic pricing to avoid potential reputational damages.
  • Opening the “black box” and increasing transparency about how algorithms work can help managers and employees adopt and oversee them effectively.
  • Companies need guardrails to make sure they can effectively and carefully navigate the competitive and regulatory environment.

For Williams, one takeaway, she notes, is clear: Many companies slap the AI label on their operations, to cut costs or boost efficiency, without comprehensive planning for its design, integration, and monitoring.

 “Managers need to be deliberate about when, where, and whether to integrate AI into their operations,” she says. “And even when decisions are automated, it’s critical to have mechanisms that keep humans in the loop.”

Algorithmic Pricing: Implications for Marketing Strategy and Regulation” is published in International Journal of Research in Marketing.

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Profit alone is a poor measure of success, study shows companies can look efficient while harming the planet

Firms that appear highly efficient at generating revenue can perform far worse when their environmental footprint are included in the calculation.  

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Companies celebrated for strong financial performance may actually be inefficient once their environmental impact is taken into account, according to new research from the University of Surrey. 

The study, published in the European Journal of Operational Research, shows that firms that appear highly efficient at generating revenue can perform far worse when their environmental footprint are included in the calculation.  

To tackle this problem, researchers developed a new way to measure “sustainable corporate efficiency”, combining traditional financial metrics with environmental data such as energy consumption, carbon emissions and revenues generated from environmentally friendly products and services.  

Dr Menelaos Tasiou, co-author of the study and Senior Lecturer in Finance at the University of Surrey, said: “Businesses have long been judged on how efficiently they turn resources into profit. But if those profits come with large environmental costs, the picture changes completely. What we show is that true efficiency means generating revenue while also reducing the environmental damage caused by production. In other words, profitability alone can mask how wasteful a business really is when environmental costs are considered.  

The research analysed more than 2,800 publicly listed companies across 61 countries between 2010 and 2022, creating one of the largest global datasets measuring how sustainable companies are, when both financial performance and environmental impact are assessed together.  

The team combined company financial records, in alignment with the green economy (defined as a low carbon, resource efficient and socially inclusive economy), with environmental disclosures such as energy use and greenhouse gas emissions. They then applied a machine learning technique known as Convexified Efficiency Analysis Trees (CEAT) to estimate how efficiently companies convert resources into revenue while minimising pollution.  

Unlike older approaches, the method models the reality that production creates both desirable outputs, such as revenue, and undesirable ones, such as emissions. This allows companies to be compared on how well they balance profit with environmental performance.  

The results found a moderate link between financial efficiency and environmental efficiency, meaning many firms that are strong financially are not necessarily good at managing their environmental impact.  

The study also found large differences across industries and countries. Firms operating in sectors with high emissions, such as manufacturing and energy, often lagged behind leaders that were better at reducing carbon intensity while maintaining revenue.  

Dr Tasiou continued: “Measuring efficiency in this broader way can help investors, regulators and policymakers identify companies that are genuinely prepared for a low carbon economy. Stronger management capability plays a key role. Firms with more capable management teams were more likely to balance profitability with environmental responsibility, suggesting that leadership decisions can strongly influence sustainable performance.  

“As governments push towards net zero and investors scrutinise environmental performance more closely, companies that fail to integrate sustainability into their operations risk falling behind.” 

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Reminder to marketing people: Missing information can misinform

You don’t need bad actors for people to get the wrong idea. Incomplete information can be enough.

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To get people to pay attention, you have to make it engaging. But what makes content engaging often comes at the cost of detail – shaping what people learn and what they think they’ve learned. The result: People can come away with the wrong idea, even when what they read isn’t factually wrong.

That tension sits at the core of research from Marta Serra-Garcia, a behavioral economist at the University of California San Diego’s Rady School of Management. The study, published in the American Economic Review, examines how incentives in the online attention economy shape the way scientific information is communicated – and what readers ultimately take away from it.

A trade-off in the attention economy

You don’t need bad actors for people to get the wrong idea. Incomplete information can be enough.

Crucially, the research finds that attention-grabbing summaries are not more likely to be factually inaccurate. Instead, they tend to include less information – especially key details about how studies were conducted.

“This is not a simple story that clickbait is bad,” said Serra-Garcia, associate professor of economics and strategy and Phyllis and Daniel Epstein Chancellor’s Endowed Faculty Fellow at UC San Diego’s Rady School. “You need to get people’s attention in order for them to learn something, and it’s good to encourage curiosity. Yet there’s a trade-off: Material designed to engage can also unintentionally contribute to the kinds of misunderstandings that can fuel misinformation.”

The finding comes from a large, multi-stage experimental study in which freelance writers produced nearly 600 summaries of actual scientific research, and more than 3,700 participants were then tested on what they learned from them.

Why “in mice” matters

In one study used in the experiment, a compound in broccoli reduced cancer cell growth – in mice. Leave out those last two words, and the finding can sound far more directly relevant to human health than it actually is.

“Why can’t we say ‘in mice’?” Serra-Garcia said. “It’s not very hard to add. It’s two words. But once you say ‘in mice,’ maybe fewer people will click.”

Study results were consistent. Summaries written to attract attention were shorter, easier to read and more engaging – but included less detailed information, especially about sample sizes and methods.

Given the option to seek out more information, most readers did not. That mirrors real-world behavior: Studies of social media use suggest most content is shared without users ever clicking through to read more.

Among those who relied on summaries alone in Serra-Garcia’s study, knowledge dropped by about 6-7 percentage points. Readers were also more likely to draw incorrect conclusions – such as assuming findings applied to humans or reflected firm medical guidance.

Inside the experiments

To isolate these effects, Serra-Garcia conducted a multi-stage experimental study. In the first stage, 149 freelance writers produced nearly 600 summaries of the same set of studies – covering topics such as cancer, sleep, vaccines and climate – under different instructions: to inform readers accurately, or to attract attention by encouraging clicks or shares. 

In the second stage, more than 3,700 participants read those summaries under different conditions, including whether they could click through for more information.

The results held across experiments: Attention-driven summaries increased engagement and prompted some readers to learn more – but left many others with less complete understanding.

AI and the attention economy

The same pattern emerged when a human wasn’t doing the writing. In additional tests, when a large language model was prompted to attract attention, it also produced less detailed summaries – suggesting the effect is driven less by who creates the content than by the objective it’s optimized for.

For Serra-Garcia, the findings point to an ongoing challenge for researchers, journalists and institutions alike.

“How do you make science engaging and important to readers,” she said, “without missing the essentials that convey the full picture?” 

The research was funded in part by National Science Foundation grant no. 2343858. 

Read the full study: “The Attention – Information Trade-off.” 

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If you’re a perfectionist at work, your boss’ expectations may matter more than your own, research finds

Help your employees by clarifying expectations through regular feedback and performance conversations to reduce role ambiguity, as doing so can provide employees with a better understanding of role expectations and enhance mutual understanding of those standards.

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If you’re among the 93% of people who struggle with perfectionism at work, new research suggests that your experience may depend less on your own high standards and more on whether those standards meet your supervisor’s expectations. 

Researchers from the University of Florida Warrington College of Business found that whether perfectionism helps or harms employees depends largely on whether employees’ personal standards align with their supervisors’ expectations. 

Specifically, they looked at the connection between employees’ self-oriented perfectionism, or the expectations of flawlessness they set for themselves, and supervisors’ other-oriented perfectionism, which reflects the extent to which they set excessively high standards for and critically evaluate their employees’ performance. 

Using data from more than 350 employees and about 100 supervisors, the researchers found that perfectionism’s impact depends on whether employees’ standards align with what their supervisors expect and how clearly those expectations are understood. 

When employees’ personal standards are aligned with their supervisors’ expectations, they tend to experience less role ambiguity, meaning they have less uncertainty about the expectations and standards for their role, why those standards matter and the consequences of not meeting them. This clarity in their work is linked to better performance, lower burnout and higher job satisfaction. 

“Problems between employees and their supervisors are more likely to arise when these expectations don’t match,” explained Brian Swider, Beth Ayers McCague Family Professor.

The most difficult situation occurs, Swider and his colleagues found, is when supervisors expect higher levels of perfectionism than employees expect from themselves. In these cases, employees reported greater uncertainty about their roles, along with worse work outcomes including higher burnout and lower job satisfaction.

“If you’re an employee who struggles with perfectionism at work, our findings suggest that understanding your supervisor’s expectations may be just as important as managing your own tendencies towards perfectionism,” Swider said. “Talking to your supervisor about priorities, standards and how your performance will be evaluated can help reduce uncertainty and ensure you both share a clear understanding of what success looks like.”

The researchers have similar recommendations for employers: help your employees by clarifying expectations through regular feedback and performance conversations to reduce role ambiguity, as doing so can provide employees with a better understanding of role expectations and enhance mutual understanding of those standards.

The researchers also recommend that organizations should consider how employees and supervisors are paired, as mismatched expectations can increase stress, reduce job satisfaction and ultimately impact performance. 

The research, “The influence of employee-supervisor perfectionism (in)congruence on employees: a configurational approach,” is published in Organizational Behavior and Human Decision Processes

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