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By Bill Peters

CEO highlights a ‘lively’ consumer, as results and forecast send shares higher after hours

People shop at an Urban Outfitters store in New York on Black Friday in 2017.

As bargain hunting dominates the retail landscape, Urban Outfitters Inc. on Tuesday said shoppers were waiting longer for expected holiday-season deals, but added that customers were still snapping up plenty of the retailer’s clothing at full price.

Executives for the clothing retailer – which along with its namesake stores owns the women’s clothing chains Anthropologie and Free People – made those remarks as its third-quarter results and fourth-quarter outlook sent shares rallying 17.4% higher after hours.

Chief Executive Richard Hayne, during Urban Outfitters’ (URBN) earnings call, said “customer engagement was lively” during the third quarter, as its efforts to expand Anthropologie and recharge its namesake stores start to pay off. But he said customers were also showing a willingness to hold out for more generous holiday-season discounts to emerge.

“We believe customers were waiting a bit longer this year to make their purchases until seasonal promotions began,” he said. However, he added: “We successfully met this shift with strong results in our early holiday events.”

But full-priced items still helped results at Anthropologie and Urban Outfitters stores. Those chains, along with Free People, put up positive same-store sales during the third quarter, led by a 12.5% increase at the Urban Outfitters segment.

Tricia Smith, Anthropologie’s global CEO, said there had been little pushback on the small, targeted price increases the chain had made in response to the U.S. tariffs on imports.

“We’re really planning very little incremental price increases over and above what we’ve already implemented this fall and holiday,” she said. “We really don’t anticipate price resistance.”

Hayne added that he felt there was “little need” to raise prices next year.

Over the past two weeks, Wall Street has been zeroed in on the condition of the U.S. consumer, who has been more aggressive in seeking out discounts to manage higher costs of living elsewhere. Other retailers have suggested that even as low-income customers feel those effects more directly, they haven’t seen a huge impact on business.

Urban Outfitters Chief Financial Officer Melanie Marein-Efron said the retailer was planning for total company revenue to grow in the high single digits for the fourth quarter, with same-store sales potentially up by mid-single digits. Wall Street expected same-store sales growth of 4.4% in the fourth quarter, which encompasses the final weeks of the holiday shopping season.

Urban Outfitters on Tuesday said it earned $1.28 a share for the third quarter, with $1.53 billion in sales and retail same-store sales gains of 8%.

All three figures topped Wall Street analysts’ estimates. Women’s denim helped at Urban Outfitters, while Anthropologie recently launched its popular Maeve clothing line as a standalone brand.

Urban Outfitters reported the results as the company – like Gap (GAP), which issued quarterly results last week – tries to regain relevance at its namesake stores. When Urban Outfitters reported results over the summer, management said that younger consumers were returning to those stores, following efforts to make them more welcoming.

However, at that time, some analysts wondered how much upside was left for the company. Shares are still up more than 24% this year as of Tuesday’s close.

-Bill Peters

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  11-25-25 2018ET
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China has overtaken the US in the global market for “open” artificial intelligence models, gaining a crucial edge over how the powerful technology is used around the world. 

A study by the Massachusetts Institute of Technology and open-source AI start-up Hugging Face found that the total share of downloads of new Chinese-made open models rose to 17 per cent in the past year.

The figure surpasses the 15.8 per cent share of downloads from American developers such as Google, Meta and OpenAI — the first time Chinese groups have beaten their American counterparts.

Open models — which are free to download, modify and integrate by developers — make it easier for start-ups to create products and researchers to improve them. Widespread adoption will confer outsized influence over AI’s future.

China’s push to release open models comes in stark contrast to the “closed” approach of most of the biggest US tech companies.

OpenAI, Google and Anthropic have preferred to maintain full control of their most advanced technology, profiting from them through customer subscriptions or enterprise deals.

By contrast, Chinese groups — which have been cut off from advanced AI chips made by Nvidia — have been encouraged by Beijing officials to offer wider access to their models.

“In China, open source has been sort of a more mainstream trend than in the US,” said Wendy Chang, senior analyst at think-tank Mercator Institute for China Studies. “US companies have chosen not to play that way. They’re making money on these high valuations. They don’t want to open source their secrets.” 

DeepSeek and Alibaba’s Qwen models make up the vast majority of downloads of Chinese models, according to MIT and Hugging Face’s data. 

DeepSeek shocked Silicon Valley when it introduced its powerful AI reasoning model R1, which was on par with US competitors despite using a fraction of the cost and computing power.

The release raised questions about whether better resourced US AI labs could defend their competitive edge. It also raised doubts over the billions of dollars being spent to build the data centres needed to operate powerful models.

The Trump administration, which is anxious to win the AI race against China, has sought to convince US groups to invest in open-source models with “American values” in its AI Action Plan.

In August, OpenAI introduced its first “open weight” models — which are free to access, but provide less comprehensive information than “open source” models that supply the code and training data required to train a model from scratch.

Meta, whose family of Llama models was the gold standard of open-weight AI development for years, has shifted its strategy by investing more into developing powerful closed models, as it races against the likes of OpenAI, Anthropic and Google to develop “superintelligence”. 

Chinese companies such as DeepSeek and Alibaba Cloud have introduced a “paradigm shifting” way of releasing models, said Shayne Longpre, a researcher at MIT who was part of the study.

He said Chinese companies were shipping models on a weekly or biweekly basis, with many different variations that users can choose from, rather than releasing a series of models every six months or year like US labs.

Other experts said that while China might be restrained in computing power, thanks to US export controls on powerful chips, the country has a wealth of homegrown researchers.

This has allowed the country’s AI groups to be more creative in their approach to model development, using techniques such as distillation to create smaller yet powerful models. The country’s AI labs have also leaned in heavily into developing AI video-generation models.

The popularity of Chinese open models is already influencing the information people receive. Researchers have shown that Chinese models have clear Chinese Communist party biases and ideologies, and generally decline to generate information on controversial topics such as Taiwan or the Tiananmen Square massacre.

Meanwhile, US labs are much more focused on progressing state-of-the-art “frontier” models, with OpenAI and Google DeepMind aiming to build artificial general intelligence, or AI systems that exceed human capabilities.

The US has far fewer big independent players in open source development than China. Its most recent contribution has been by the Seattle-based Allen Institute for AI, which launched its Olmo 3, a fully open source model, in November. 

Janet Egan, senior fellow and deputy director at the Center for a New American Security, a think-tank, said: “It should be of concern to the US that China is making great strides in the open . . . model domain.”

Additional reporting by Eleanor Olcott and Ryan McMorrow in Beijing. Data visualisations by Martin Stabe