【推荐2】More and more online shopping platforms now offer consumers a detailed look into products’ historical prices. But how does this information influence buying decisions?

To explore this question, we conducted a series of experiments with a total of more than 5,000 business school students and working adults. We measured the impact of different kinds of price shifts on people’s interest in purchasing products and identified several consistent trends:

First, when consumers saw that the price today was lower than it had been in the past, they were more likely to buy now, because the current price seemed like a good deal.

However, the picture gets more complicated when you consider the frequency of historical price shifts: In our studies, we found that if consumers were shown at least three changes in the same direction, they were likely to assume the price would continue to move in the same direction. While if they were only shown one or two changes in the same direction, they expected the price to change in the opposite direction.

So what does this mean for sellers? It may be tempting to slowly lower the price over time. However, our data shows that this can lead consumers to assume that the price will continue to fall, making them hesitant to buy. But if they just see a single price drop, they ‘re more likely to expect a reversal in the near future, pushing them to buy the product now.

Our findings can also help buyers make more informed decisions about whether and when they choose to make a purchase. As with any irrational bias (非理性的偏见), awareness of the natural tendency to expect trends to continue and single large changes to reverse can help consumers question this assumption before acting on it. Instead of letting this arbitrary (武断的) expectation guide buying decisions, consumers may benefit by doing a bit more research around the underlying factors driving price shifts. Buyers may also benefit from learning more about a product’s longer-term price history, fluctuations (波动), and typical industry-wide price ranges, to avoid being disproportionately influenced by near-term price changes. It’s also always a good idea to think about both how urgent your need for a given product is, and your own risk tolerance for a potential price increase, as this can affect whether it’s worth it for you to wait and see if the price falls.

Of course, there are countless factors that influence both consumers’ decisions around whether and when to buy and sellers’ decisions around how to price their products. But it’s important for both sides to recognize the key role that expectations play in influencing these decisions.

1. Which of the following is true about the experiment?

A．It proves that people’s interest in the product drives the purchasing behavior.

B．E-commerce platforms turn to it to connect with customers and boost sales.

C．It’s designed to figure out the purchasing decision process based on pricing.

D．Business school students make up the whole control group for comparison.

2. Which of the following price trends might tempt consumers to buy on May 8^th?

A．	B．
C．	D．

3. Consumers are advised to      .

A．decide on the assumptions that long-term price trend will continue

B．research longer-term price history, price ranges and hidden factors

C．put off the purchase for better deals because of the unsustainable market

D．cooperate with sellers while putting aside the personal risk and urgency

4. What does the passage mainly talk about?

A．How do price changes influence buying decisions?

B．Why should products’ historical prices be shown?

C．When is the best time for consumers to purchase?

D．What do businesses need to price their products?

【推荐2】More than half a trillion dollars. That's the estimated value of all the stuff that U. S. shoppers bought last year only to return it—more than the economy of Israel or Austria. We tried new brands with unfamiliar sizes after seeing them on TikTok. We overbought for the holidays, and we shopped overly online, where returns are between two and five times more likely than that from stores.

Where does it all go? Take the blanket I bought on holiday sale for example. I opened the package, only to discover it was just too small for my new sofa. So I returned it. Sorry, blanket! What will happen to it?

“Your blanket is very likely to be in a landfill,” says Hitendra Chaturvedi, a supply chain management professor at Arizona State University. “That is what consumers don't realize—the life of a return is a very, very sad path.” Value is the big threshold (门槛): Is the product worth the cost of shipping back and paying someone to inspect, clean, repair or test? Experts estimate that retailers (零售商) throw away about 25％ of their returns. Every year, U. S. returns create almost 6 billion pounds of landfill waste.

Many others get resold in discount and outlet stores. Some go to sellers on websites. Some get donated to charity or recycled. “These options have increased over the past decade, allowing more and more returns to find a new home”, says Marcus Shen, chief operating officer of B-Stock, a platform where retailers can resell their returns, often to smaller stores.

As companies compete on flexible return policies, technology is also slowly playing a part: helping shoppers buy the right-size sweater or picture a new blanket inside their room. Most importantly, She says, shoppers themselves are getting more and more comfortable with buying stuff that's not exactly brand-new.

“The idea of that is no longer scary for us, right?” he says. On his holiday-returns agenda is an electric, self-heating coffee mug that he has never opened, and he feels confident it will find a happy new buyer.

1. What is paragraph 1 mainly about?

A．The challenge facing the American economy.	B．The urgency to cut down on online shopping.
C．The returning problem caused by overbuying online.	D．The cost of finding new homes for returned goods.

2. Why do some returns end up in landfills?

A．It's required by the return policies.	B．It saves retailers 6 billion pounds a year.
C．It's impossible to put returns to other uses.	D．It's more economically efficient for retailers.

3. How does technology contribute to less returning?

A．By helping shoppers make better decisions.	B．By restoring the newness in returned goods.
C．By improving the return policy-making process.	D．By drawing pictures of the goods for the shoppers.

4. Which of the following examples indicates a desirable end-result for returns?

A．TikTok items.

B．The coffee mug.

C．The blanket.

D．A right-size sweater.

【推荐3】How would you feel if you were invited to the moon? If you found a gold coin, would you save it, give it to charity or use it for a holiday? Personality quizzes of this kind, known as “psychometrics”, have bothered many job seekers. Now, it is being applied to the oldest problem in finance: will a borrower repay?

In rich countries, lenders use credit scores to weigh risk. But just 7% of Africans and 13% of South Asians are covered by credit bureaus (征信机构). Bailey Klinger of the Entrepreneurial Finance Lab (EFL), which explores new kinds of credit data, argues that psychometrics could include many more people in the financial system. Everyone has a personality, after all.

Judging character is not new. Psychometrics attempts to make it a science. The model developed by EFL has undergone many tests and adapted to different cultures. Its collected data reflect something unnoticed. For instance, young optimists are risky, but old ones are a safe bet.

Clever design cuts cheating. There are no obvious right answers; responses are cross-checked for consistency. The model monitors mouse movements for signs of indecision or distraction. When borrowers lie to get a loan, they often do so in predictable ways. In an EFL test, people are shown pictures of five drinks and asked which one they would be. Choosing water over something with small bubbles may be a sign of cheating.

This sounds fanciful, but there is evidence that it works. In one Indonesian bank, combining psychometrics with existing customer data cut default (违约) rates for small businesses by 45%. A study by the World Bank found that EFL’s model increased lending to those without a credit history.

The technique needs further development. At present, turning to credit bureaus is still the best way to tell if somebody will repay a loan. But bureaus improve more slowly than technology. Lenders will find ever more ways to look into their customers’ souls.

1. What are the figures intended to show in the second paragraph?

A．Racial discrimination from lenders.

B．Uncertain property of poor people.

C．Great risks brought by credit scores.

D．Current weakness of credit bureaus.

2. What can we learn about EFL’s model in the third paragraph?

A．It has been greatly improved.

B．Its data confirm some ideas.

C．Its effects vary with cultures.

D．It can’t tell character exactly.

3. What does “mouse movements” refer to in the fourth paragraph?

A．Borrowers’ responses.	B．Lenders’ answers.
C．Pictures of five drinks.	D．Drinks with bubbles.

4. What does the last paragraph imply about psychometrics in finance?

A．It will replace credit bureaus.

B．It will be mature in the future.

C．It has won most lenders’ love.

D．It is far from satisfactory.