We've recorded a number of podcasts discussing the environmental impact of food production, and the food choices made by individuals. But how aware of all this are consumers? How do they make sense of such information? This is but part of the work that occupies our guest Richard Larrick.
About Richard Larrick
Rick Larrick is professor of Management and Organizations at the Fuqua School of Business at Duke University. His research explores individual, group, and organizational decision-making as specific areas of research. He has examined the wisdom of crowds, environmental decision making and de-biasing techniques to help people make better decisions.
So you've published some fascinating work recently on consumers and their perceptions of the environmental impact of food. What did you find?
So we were interested in seeing how well do people understand both the energy and the carbon emissions associated with their food. And based on prior research that looked at people's understanding of the energy that's used by their appliances, we thought that people aren't going to be very good at this. And that they're likely to underestimate the energy that goes into their food. And so we built on previous research that has shown that people know roughly that refrigerators use more electricity than light bulbs, but they really don't understand by how much. And we thought that the problem might even be worse for food, mainly because food and its energy use is kind of hidden from consumers. We have a bit of an Old MacDonald's Farm view of how our food gets on our table. Whereas with cars, and with light bulbs, we can see the energy being used. So we did a study looking at people's estimates of how much energy and greenhouse gas emissions were associated with their food. But we also asked about the energy use by appliances as a way of kind of calibrating their accuracy relative to this other standard. And we did find what we expected, which is that people know that beef has more energy and greenhouse gasses associated with it compared to, you know, corn or something like that. But they don't estimate it to be that much higher. And what they also do as a big mistake is estimate that both are much lower than their actual values, and much lower than comparable appliances that generate the same amount of energy or a carbon emissions.
So Rick, can you put this in context like between corn and beef, for example? How much do people think there is a difference in energy and carbon emissions and then how does that compare, for example, with the refrigerators that will use?
Sure. Let me try to put some numbers together. So beef is about a hundred times more consequential for greenhouse gas emissions. So, it has a very big impact and I think those who really follow this closely know that it's not just issues of turning grain into a protein--which is one of the things that you're doing when you produce meat. But, t's also things like there's natural gas used in fertilizer and there is the basic biology of cows. Beef, I should say, produces methane as kind of part of their digestive process. And that's a very potent greenhouse gas. So beef is about a hundred times as bad as corn, holding constant on the serving size.
How much of a difference do people believe there is?
Just a fraction. They think it’s twice as bad. So it's a pretty big underestimation.
So do you think there are reasons that people come to these under estimates beyond the obvious fact that they don't know or they haven't been informed?
I mean, I do think it is because a lot of the food system is hidden from them. And we were motivated in this line of argument by previous research that has shown that if you ask people: do you understand how a zipper works or how a toilet works. They say yes, and they're very confident about it. And when you actually ask them to explain it, they actually can't do it, and their confidence goes down. So I think it's just one of those everyday things that we encounter and we think we know what's behind it, but we've just never had to sit down and articulate it.
And in fact, in other research we had found that if you force people to try to draw out the system by which food gets to their table, they actually do become more accurate and understanding how much energy is in their food.
Oh, that's interesting. So do you think knowing this information will be helpful to consumers ultimately?
I do feel like we're kind of in an early stage in terms of helping make people aware. So I recognize that people's intrinsic concern for the environment does vary and there's probably portions of the population that are eager to learn this kind of information. But it's not readily available at this point. And so I think there's a kind of blind spot that exists at this point in society and we just have to think of creative ways of getting that information to people. One way to do it is just, you know, having articles written on the fact that people should pay attention to their food. But you know, another one that we were motivated to try, as a part of this research is, what would it look like to try to put a carbon label on food? And this is clearly something other countries besides the US have tried to do. And I'll say with mixed success, which we can come back to.
But we just wanted to see what's the benefit of giving people the information directly. We actually did a study in a lab here at Duke where we had subjects come in. We gave them some money, we brought them into a little room that was set up like a grocery store and told them that we wanted them to buy some soup. And then we gave them some information about vegetable soup and beef soup, holding lots of things constant to the degree that we could. And then for some of them they looked at and had access to a label that described the carbon consequences of the different soups. And we use kind of the state of the art knowledge of trying to convey it in a way that makes it easy to understand. Which is also something we can come back to and talk about. But the key thing we found was if they had access to the carbon label and understood it by having it be made simple for them, it did shift their preferences. So they both had an accurate understanding of the carbon in the beef soup, which was higher than in the vegetable. And it affected their preferences when they literally walked out of the lab with soup that they had purchased that day. They walked out with more cans of vegetable and fewer of beef after they had seen the label.
Oh, it's so interesting. Now let's get to that issue of what a good label might look like. And I know in the work that we do, there are big differences across the world in the way people use front of package labeling to convey nutrition information on food packages. And you said that in some parts of the world people have been experimenting with these carbon-related labels. So I suspect there's a lot of difference and variability in the way that's being done. What would make for a good label do you think?
Yeah, I think the comparison to nutrition labels is really interesting just because nutrition is so multifaceted and it has so many kinds of things that are expressed like potassium and things like that where I'm not sure most people know what's good and bad, what more or less of it. So nutrition labeling is very challenging and in that respect, both energy and carbon, is actually a bit simpler because if you can make the numbers meaningful. So instead of talking about things like tons of carbon and stuff like that people don't really know what you're talking about. If you're going to make it more interpretable, you're really only expressing kind of one dimension really of impact. And so one of the things we did in creating a label for the soups was to give people what's known as a stoplight label, which I think has also been used in nutrition. You indicate the bad levels with red and good levels with green.
And kind of inherent in that is also just the basic idea that this is a relative comparison. And there's just lots of work in psychology showing the value of people don't know what to make of these kind of dry, unfamiliar numbers. But if you can give them a way of seeing where it falls in a relative range, then they can be sensitive to it and act on it. So one of it was to kind of use the stoplight feature (a traffic light). And the other is to use a translation to a more familiar unit, which is essentially how many minutes of burning a light bulb is this equivalent to. And so, you know, for the beef soup it was equivalent to like a thousand minutes. And for the vegetable soup it was a 10th of that. So it was a way of making the impact of the beef soup kind of get their attention and translate it to a familiar unit for them.
And did you test which of these two approaches work better?
Oh I should say we just did everything. We threw in the kitchen sink to make sure it would work. So we did both of those things.
Are you satisfied that there are good sources out there from which to derive the numbers that would be used to create those labels?
Yeah, and in fact, as I mentioned earlier, there are challenges to creating these labels. And some of them is where does the information come from and what assumptions do you make? And it almost has to be country specific, and perhaps even region specific for countries. Which you know, for, for the US that would be very complicated. And so otherwise we're kind of using averages of how far something had to travel, etc. So there are challenges there. And, and I'll just note another challenge is we that scaled our impact within the category of soup and it meant that beef was high and vegetable was low. But it would not make for easy comparisons across foods. So the same kind of problem arose actually a few years ago when he US was redesigning the car label. The US considered putting grades and colors on it, which is something that they do in Europe. But it's tricky because all the large vehicles, like SUVs would get low grades and colors unless you graded within a category. But then that becomes confusing because some SUVs would be getting A's and some more efficient vehicles to dance would be getting Ds. So anyway, one of the big challenges with labeling is how do you label things that you can compare across product categories. So it's not trivial to do this. We also do know there's an informational benefit if you can help people by pointing them in this direction.
So where do you see this work going in the future?
Yeah, that's a good question. I feel like my kind of main research role has been to raise awareness of where blind spots are. And to try to point in the direction of helping people use the information better. And I, you know, I think at this point the timing of this research coincides with other kinds of papers that I've seen on trying to raise awareness around energy and carbon emissions related to food. And I believe the UK has a governmental unit, a nudge unit, that they've spent a lot of time kind of helping people with making better financial decisions and some energy decisions. I know one of their interests in the last year has been to raise awareness about the carbon consequences of the food that people eat. So in short my own kind of contribution tends to be stimulating the idea and trying to get it out there for the policymakers to be aware of.
Yes, my instincts tell me you're on the cusp of something really important because you just see a lot of trends moving in the direction of consumers paying attention to this kind of information. And the fact that you showed that there are so many errors that people make. And that information can help affect decisions people make, and how to best convey that information--this is really important. So I suspect as we go forward, we will see labels like this on food and the kind of pioneering work you're going will have a lot to say about that.
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