The question of merging individual (or organizational) decision-making with infrastructure design and management is supremely interesting, though not often engaged by the engineering community. For urban infrastructure, social systems are a key component of function. Individual decisions are influenced by personal views, interactions with peers, and larger social trends. This may not have a lot to do with the design of public infrastructure, such as a bridge, but it does highly influence design and performance for privately-managed infrastructure. Green buildings that are energy and water efficient are an intriguing example. What drives people to follow through on energy efficient designs? Research indicates that while green building approaches save money in the medium- to long-term, it may cost a bit more upfront, which impacts our cost-averse psychology (although the upfront cost picture is changing).
Traditional economic theory describes individuals as rational beings with supercomputer capabilities, capable of analyzing streams of limitless information for any number of decisions. Rational actors, as they might be called, seek to maximize their utility through actions that increase their benefits to the greatest extent possible. These rational actors have broad access to information through which they can make informed decisions regarding benefits and costs. Not all utility, though, is monetary, for some actors may derive benefit in the good feeling they receive from particular actions even if costly. Game theory effectively described how humans may not seek to greatest overall benefits in some situations, especially negotiations, but it leaves open the question of how actions that might otherwise be seen as altruistic gravitate into the general populace. For instance, does the recent rise in the popularity of sustainability represent a collective irrational behavior? On the contrary, is it actually a gigantic good feeling for guilty societies? What combination of selfish and altruistic motivations spur individuals to undertake an energy efficiency retrofit for their home? Why do these people exist in the “tails” of behavior when everyone else is just fine with the status quo? For these questions of private, distributed infrastructure management, traditional economics may not suffice.
Behavioral economics is a relatively new approach that draws on a variety of economic, sociological, and scientific areas to explain why individuals do not always follow rational decision-making processes. The field seeks to understand how various limitations in perception and willpower can create anomalous “behavioral failures,” or deviations from expected behavior, that may explain some market failures. In the area of environmental economics, behavioral economics may provide insights into individual motivations for seemingly altruistic decisions to undertake activities that result in broader environmental benefits. Further, literature characterizes behavioral economics as describing the “tails” of behavior (Shogren and Taylor 2008), which has significant implications for changes in lifestyles and behavior often sought by sustainability professionals. Distributed infrastructure systems for energy and water provide a unique opportunity to test the ability of behavioral economic approaches to predict changes in behavior. As system managers seek to develop policies that successfully integrate distributed and centralized infrastructure systems, behavioral economics and evolutionary biology can play an important role in understanding the motivations of early technology adopters critical to the success of the system.
Behavioral economics seeks to understand the human limitations in decision-making by individuals represented by deviations models of rational choice (Mullainathan and R. H. Thaler 2000). Herbert Simon (1959) laid the foundation for the field by synthesizing economics and psychology to describe how individuals display bounded rationality in decision-making. He argued that simply knowing an individual’s desired outcome for some decision is unlikely to provide sufficient insight into the likely decision path. Instead, one must understand the simple and more complex adaptive processes of the individual in a rapidly changing environment, including internal thought processes and structure. For economics, this means that the simplistic notion that consumers will maximize utility at the lowest cost does not sufficiently incorporate the social, psychological, and other factors that also dominate decision-making for spending and investment. Kahneman, Slovic, and Tversky (1982) described how basic associations to known events, known as the availability heuristic, can affect the decisions of consumers. Behavioral economics research has grown significantly in recent years, with applications in law, psychology, public policy, finance, and education. In general, however, it follows in a line of critiques of rational individual behavior assumptions in economic decision models.
Numerous behaviors could be considered irrational and would not be predicted by theories of rational choice that dominate economic analysis. Humans often prefer to maintain the status quo, even when changes could increase utility. Individuals often place greater value on possessions they maintain than those they do not even if they are of equal monetary value, a phenomenon known as the endowment effect. Other analogous behaviors include averseness to loss, framing effects, anchoring, and preference reversals (McFadden 1999). The likelihood of these behaviors, however, creates an important distinction for behavioral economics. Are such behaviors frequent enough in economic decision-making so as to merit wide exploration of behavioral economic critiques of the rational model? Alternatively, are such behaviors infrequent so as to represent fringe behaviors “at the tails” of the overall set of decisions? Shogren and Taylor (2008) argue that the role of behavioral economics is to understand the size and nature of these tails without displacing the usefulness of the entire rational model. Empirical work has documented that these deviations from rational models are too significant to be ignored (Tversky and Kahneman 1986).
For environmental economics, behavioral economics has provided significant insight into several difficult questions. First, the behavioral economics approaches have influenced non-market valuation for environmental goods. In many instances, individuals may not exhibit rational behavior for environmental preferences. For instance, there is a significant gap in an individual’s Willingness to Pay (WTP) for environmental benefits and Willingness to Accept (WTA) some level of degradation. In many instances, the WTP is lower, indicating that actors value an environmental asset higher than they are willing to contribute to its persistence. Behavioral economics has explored the role of endowment effects to explain these results, whereby individuals expect environmental benefits because they were previously “gifted” (Knetsch and Sinden 1984; Knetsch 1989). In another example, research has described how game theory does not fully explain some observed behaviors regarding environmental issues and collective management. Under game theory involving rational actors, free-riding would exist in situations where enforcement regimes are weak and participants have little incentive for enforcement. Documented instances exist, however, where groups manage resources collectively in the absence of established enforcement regimes and a variety of enforcement mechanisms emerge (Ostrom 1995; Poteete, Janssen, and Ostrom 2010). Thus, these examples show how incorporating behavioral economic approaches can help environmental economics to fill in gaps in existing models that predict behavior.
The field has identified three major ways that humans deviate from rational decision-making (Mullainathan and R. H. Thaler 2000). First, as mentioned above, humans display bounded rationality. Departures from rationality can include both judgments and choices. Individuals can display a variety of behaviors that do not necessarily support rational decision-making, such as optimism, overconfidence, and available information in the context of prior experience (Kahneman, Slovic, and Tversky 1982; Simon 1959). Humans can also misperceive situations, which would result in irrational behavior (Camerer 2003). Second, humans show bounded willpower. Outcomes such as obesity, debt, and drunkenness are common examples that reveal how humans are often unable or unwilling to end unproductive behavior. Third, humans display bounded selfishness. The field describes how people can take selfless actions, such as giving to charity or doing volunteer work. Together, these limitations to decision-making in humans form the basis of behavioral economic models.
The question of bounded selfishness suggests close ties with the concept of altruism, which has been explored in biology and psychology for centuries. Darwin viewed the existence of altruistic behavior as a complication to his theory of evolution, as actions that decrease likelihood of survival should not be undertaken by individuals. It was not until the twentieth century, however, that a genetic basis for altruistic behavior was described (Harman 2010). Evolutionary biology defines altruistic behavior as actions from an individual that increase the total population of a species, but decrease the likelihood that the individual will live (Ridley 2004). Some species such as ants and bees have close genetic similarities between organisms due to their unique method of transferring genetic material to offspring. Known as haplodiploidy, it results in females that share 75% of their genetic material with their mothers, while a typical diploid species shares only 50%. This evolutionary trait can result in highly cooperative and social communities that exhibit uniquely high rates of altruistic behavior. While humans would be less likely show altruistic behavior than ants, altruistic behavior in humans can still be explained by potential to increase populations due to a behavior. The likelihood of altruistic behavior correlates with genetic similarities. A mother may sacrifice her life to save her offspring in order to further the genetic line, but she would be less likely to do the same for a distant cousin. Nevertheless, a few documented instances of truly altruistic behavior in humans exist, fueling a continued debate regarding the nature and origins of altruistic behavior in populations (Lehrer 2012).
The nature of altruism as defined in evolutionary biology presents intriguing questions for environmental policies that seek to integrate ecological goals in economic policy-making. Environmental awareness and sustainability are two social movements that could be considered to have started “in the tails” of mainstream behavior. Early advocates of such movements were seen as fringe and in conflict with economic structures that supported livelihoods, even to the point of conflicting with core genetic drives to maximize offspring. In reality, however, integrating ecological goals into social and economic programs is vital to societal self-interest and may not actually be altruistic (Arrow et al. 2010; Braungart, Mcdonough, and Bollinger 2007; McKibben 2007). Just as seemingly selfless actions such as donating to charity provide non-monetary benefits for individuals (i.e. a warm glow), selfless actions of “protecting the planet” are actually largely self-interested. While this argument is often made, it gains limited traction compared to economic outcomes and institutional inertia.
Behavioral economics can address the above question across many sectors, such as understanding the future of energy and water infrastructure systems. Infrastructure design is increasingly emphasizing distributed approaches to reduce energy and water use, exemplified by U.S. Green Building Council (USGBC) LEED Certifications for buildings as well as low-impact development landscape treatments that reduce urban stormwater pollution. In distributed approaches, market valuation of such amenities combines with increased utility derived from comfort to provide individuals benefits of localized infrastructure improvements. But building and homeowners face associated costs. In residential home energy retrofits, for example, homeowners must spend significant upfront capital to implement treatments, even as later benefits are uncertain due to energy prices and long payback periods. Similarly, homeowners who implement low-impact development treatments to reduce runoff in their personal yards are investing time and money to reduce pollutant loads in local watersheds, an uncertain and disproportionate benefit. In both cases, individuals may receive a monetary benefit such as reduced energy costs along with a “warm glow” of helping the environment, but the benefits are uncertain. Further, the relationship between benefits and motivations of individuals is little understood. As these activities move from the fringes to the mainstream over time, other noted behavioral failures associated with adoption may reduce, such as endowment effects and bias towards the status quo. This inertia of social norms is an important driver of technology and infrastructure processes. A greater understanding of individual behavior as it relates to distributed infrastructure adoption will be necessary and behavioral economics literature can contribute.
Integrated economic-engineering models of future infrastructure systems can contribute to our understanding of the role of individual behavior in distributed systems management. Behavioral economics can be useful in this regard to understand “irrational” behavior. It seems likely that in a hyper-networked world, we have an elementary understanding of individual decision-making and our existence as social beings. Understanding the motivations of consumer to undertake potentially selfless behaviors can assist system designers in building infrastructure that actually connects people, the landscape, and the built environment.
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