Extending behavior change efforts to the realm of global sustainability is a complex task. Conventional behavior analytic research leverages tightly controlled research demonstrations to convince peers and skeptics that behavior is influenced by the designed intervention. But what about circumstances when tightly controlled experimentation isn’t possible? Convincing as they are for those well-versed in behavioral science, are small-sample demonstrations enough to appeal to policymakers or their constituents?
This blog post serves as an introduction to the behavioral economic framework, a tool for better understanding sustainable choice. As a complement to the gold-standard small-n design, operant behavioral economics and its application can offer novel insights and a flexible framework to collect data in historically difficult-to-study contexts.
Operant Behavioral Economics: Foundations and Principles
Operant behavioral economics, a synthesis of conditioning principles and economic theories, provides a robust framework for understanding and influencing choice. This work is born from the classic operant laboratory, a hybrid approach championed by the many behavioral economists that have extended the encompassed frameworks to better understand decision-making as a function of reinforcer constraint. Two primary frameworks emerge within the landscape of operant behavioral economics:
Discounting
Just as the size of a reinforcer can control the behavioral response, so too does the immediacy of reinforcer delivery. Discounting posits that, with some exceptions, organisms prefer immediate rewards so much so that they are willing to forego objectively larger reinforcers if a waiting period is required. Consider your own preferences: Are you more tempted by a $500 payout available right now, or a $1000 payout in five years? A slice of pizza now, or the whole pie in a month?
We can expand this basic concept to better understand preference reversal, or the tendency for individuals to backtrack on their previously held values due to the muddying effects of reinforcer delays. Many of us value financial health and stability, an objectively valuable albeit often delayed outcome. Yet, when Apple releases their next iPhone model, how many will splurge to the detriment of their long-term financial stability? The immediate value of the iPhone—a lesser reinforcer, for sure—is sufficient to shift behavior away from this temporally distant goal because the delay imposed on financial security reduces the currently perceived value of that reinforcer. Generally speaking, delayed rewards can be tough to wait for.
Of course, delay discounting is not the only discounting framework. Just as increasing delays can negate reinforcer value, so too can increasing odds against contact (as in the preference for a 100% chance to receive $500 as opposed to a 50/50 shot at $1000). There are numerous research lines examining discounting as a stable yet modifiable aspect of human decision-making that is transdiagnostic—a conversation for a different blog.
Operant Demand
So, if reinforcer delays matter, what about the behavioral cost required to obtain a reinforcer? Operant demand is a composite measure of reinforcer efficacy, or the extent to which a given reinforcer maintains behavior. Said differently, demand examines how much work an organism is willing to emit to remain engaged with a reinforcer, particularly if we make it harder to do so.
Folks versed in economics might note similarities between the conventional supply/demand curves of microeconomics and how operant behavioral economics gauges reinforcer “demand.” For instance, the demand curve depicts behavior—unit consumption—as a function of increasing behavioral cost, where costs might be determined by environmental support, relative supply, or an arbitrarily set unit cost. As the required behavioral cost increases, we generally expect to see expenditure (i.e., how much behavior is actually emitted) increase to a point, after which both this expenditure and the corresponding reinforcer contact precipitously decline. The degree to which reinforcers maintain behavior as a function of increasing cost is notably unique to the commodity and, to some extent, the organism.
As an example, consider two commodities: Toilet paper and luxury cruises. Most of us probably recognize the value of the former—there’s not much of a viable alternative for TP, or at least not that serves quite the same function (in an economic sense, there isn’t a great substitute for this commodity). Within reason, if there was a dire global shortage of toilet paper (for instance, if pandemic-related activities result in panic buying and “toilet paper scalping”), many of us would still find ourselves shelling out significant sums to secure some 1 or 2-ply scraps. In contrast, luxury cruises are just that—a luxury. Sure, plenty of us would opt in if the price was incredibly low, but at the first price beyond our budget, we wouldn’t be exhausting our savings. We’d simply abstain. For many of us, the relative reinforcing efficacy simply isn’t there, in part because there are so many other things we can do with that time.
Briefly, it should also be noted that the operant behavioral economic approach discussed here (sometimes referred to as “Big B,” emphasizing the behavioral aspect) is distinct from the much-popularized behavioral economics (similarly deemed “Big E”). This latter behavioral econ is more firmly grounded in the economics of human decision-making and includes the very popular nudging approach to behavior change (something we’ll detail in a later blog). For now, we can acknowledge a primary difference in the philosophy of behavior change: Big E examines the context and organism, deems the most “logical” outcome for that organism, and laments the irrationality of choices that seem at odds with this most objectively logical choice. On the flip, as Big B is a product of behaviorist thinking, it deems any decision as the most “logical” for the organism, being that it is a byproduct of that individual’s unique context, biology, and learning history. In short, the organism is doing what is most rationale for it at the time of deciding.
Conceptualizing Sustainable Behavior via Operant Behavioral Economics
Given the frameworks laid out, we can draw some interesting insights as to the behavioral mechanisms maintaining behavior we might view as problematic to the global sustainability agenda.
For starters, let us consider the delay discounting viewpoint. As individuals reading a blog about sustainable behavior, we might surmise that this audience is one concerned with global climate change and its fallouts. The value of a sustainable human presence on the planet is vast … but delayed. So delayed that we—as enactors of change—may never actually see the fruits of our labors. The result? Many instances in which we “throw in the towel” and opt for the less sustainable choice, despite knowing that this is the poorer choice. Now, consider the actions of those who may be less concerned with sustainable outcomes. “Why should I stop eating meat? Switch to a renewable fuel source? Advocate for sustainable policy? I won’t live to see a time when that matters.” From policymaker behavior to that of everyday Joes, the daunting temporal distance with which we’re grappling can be a major hurdle for increasing the salience of sustainable outcomes.
A research example might help to further make this point. Kaplan and colleagues (2016) examined the ability of episodic future thinking to reduce the rate of discounting and improve health-related decision making among study respondents. Briefly, episodic future thinking is a procedure whereby study respondents envision the future—themselves, their family, their health—to temporarily increase the value of temporally distant reinforcers. To really hit home, the researchers in this study used software to create age-progressed images of their respondents: Those completing the study had to look at their future selves while indicating the likelihood they would engage in a range of future-altering health-related choices. Their results suggested that those respondents who engaged in the episodic future thinking activity exhibited “improved” decision making via more stable discounting preference (i.e., greater valuation of future rewards). This could serve as a powerful tool for shifting preference in favor of sustainable behavior with potential to solely benefit future generations.
Operant demand can offer similarly powerful insights. Consider the transportation sector and its impact on carbon emissions. Reed and colleagues (2013) showed, using archival per-barrel fuel oil purchasing data, that petrol consumption is remarkably resilient to increasing unit cost. We might consider our own behavior at the pumps—irrespective of gas prices, the tank must be filled. One option to curb excessive gasoline consumption (at least in the private sector) is to encourage public transportation. Yet, if the public doesn’t view these options as viable substitutes—if we aren’t willing to expend behavior at the same rate to secure these options—how then can we expect individuals to make such a change? By targeting modifiable factors like convenience, comfort, and speed, we can bring public transit options into the same frame as private transportation (particularly if fuel prices are to see a jump in cost).
Conclusions
In the next installment in this blog series, we will examine the utility of behavioral economic tasks to measure behavior change in historically difficult-to-study contexts. Indeed, researchers are already making strides in dissecting some of the sustainability agenda’s most critical behaviors, leveraging these behavioral economic insights for novel approaches to shift behavior at a community scale.
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