“There is nothing either good or bad, but thinking makes it so”
William Shakespeare, Hamlet
To provide context for this publication, it is useful to lay a philosophical foundation explaining the basic concepts and ideas that shape much of the conversation around energy efficiency and user behavior.
The story begins in the 1950s when economist Herbert A. Simon introduced the concept of “bounded rationality.” This model of human cognition represented a deviation and challenge to the long-established view of humans as “rational agents”- that is, people make decisions with a full understanding of the available options and choose the option that provides optimal value at the least cost (utility maximization). This “homo economicus” had been the standard Enlightenment era model of man as an idealized, purely self-interested party.
Except, as Simon noted, this is not how humans actually behave. Much to the chagrin of the likes of John Stuart Mills and other utilitarian thinkers, individuals are not omniscient of all possible worlds, and make decisions under circumstances of limited knowledge. Furthermore, we are subject to psychological influences that confound our preferences, meaning we do not always act in ways that maximize the intended outcome (money, prestige, etc.). Thus the origins of “bounded rationality.”
As suggested, bounded rationality conceives of man as an agent of imperfect understanding of available options (or affordances), fallible to the seductions of outside influence each vying for his attention.
As Simon writes:
“Broadly stated, the task is to replace the global rationality of economic man with the kind of rational behavior that is compatible with the access to information and computational capacities that are actually possessed by organisms, including man, in the kinds of environments in which such organisms exist.”
H.A. Simon “A Behavioral Model of Rational Choice,” Quarterly Journal of Economics, 1955
This construct allows for decision-makers to model outcomes accounting for missing information and logical errors. Or, to quote Donald Rumsfeld, assessing the landscape for “known unknowns.”
How might a decision-maker go about this task? One well-trodden area of research uses game theory to simulate situations, or “games” that demonstrate how people can be led to make decisions that do not suit their best interests. The most famous example is probably the “Prisoner’s Dilemma,” in which two prisoners, each with damning evidence on the other one, can be coaxed by a skilled investigator to rat on each other, when they both would have done best to remain silent. More recently, the rise of high powered computers have contributed significantly to our understanding of decision making in dynamical systems, and have been instrumental in designing agent-based models and the linear regression algorithms that assist our everyday tasks and hobbies (Netflix, anyone?)
But it is perhaps the domain of behavioral economics that is most relevant to the consumer in making choices for their everyday household and business energy usage. Enter economists Amos Tversky and Daniel Kahneman, who first described and popularized the usage of heuristics in describing types of behaviors that affect our ability to judge probabilities and logically address problems we encounter in everyday life. Their 1974 paper, “Judgment Under Uncertainty: Heuristics and Biases,” is now a seminal work for scholars working in the field of decision-making, and Kahneman was awarded the Nobel Prize in Economics for this work in 2002 (Tversky passed away in 1996). Kahneman later helped popularize these ideas for the masses in his 2011 book, “Thinking, Fast and Slow.”
So what were these ideas that revolutionized the way theorists and policymakers think about decision-making? The following are brief descriptions of the main concepts introduced by Tversky and Kahneman:
Framing Effect
The framing effect occurs when decision-makers view a choice either positively or negatively, based on how the choices and contextual information were presented, or framed. For example, given an event where 600 people were infected with a deadly disease, more respondents chose a treatment framed as saving 200 people (72%), rather than one framed as stating 400 people would die (22%), even though the outcomes are identical.
Loss-Aversion
Closely linked to the framing effect is loss-aversion, or the idea that people are more sensitive to potential losses than to potential gains. Cognitive scientists and evolutionary psychologists posit that our ancestral brains evolved to avoid risks that, in our early days as hunter-gatherers on the African savannah, could have been fatal. This theory underpins the reason why we modern humans have a much stronger response to losing $100 in our stock portfolio than an identical gain. Together, the framing and loss-aversion effects constitute what Tversky called Prospect Theory: an account of how people’s perceptions of risk under uncertainty lead them to make decisions heavily weighted towards avoiding risk.
Availability Heuristic
This heuristic (a simplified model of the world that helps us make quick, often involuntary decisions) states that people are more likely to make choices based on recent experiences or recollections. For example, viewing a TV show featuring your favorite character, Mary, may predispose you to choose a candidate named Mary for a job in your department.
Representativeness Heuristic
The representativeness heuristic usually appears when we unwittingly rely on stereotypes to make judgments about other people. For example, we may view people who wear glasses as more intelligent than others, due the cultural association that wearing glasses is a signal for someone smart and bookish.
Anchoring Bias
The anchoring bias occurs when we use the first piece of information (or anchor) to color our perception of later information, using the initial input as the preferred point of comparison. Anchoring biases explain the first mover advantage, where a company that is first to bring a new product to market enjoys additional opportunities to create brand loyalty and influence product design and market strategy of players who enter later.
Endowment Effect
Endowment effects result from the propensity of people to prefer the things they already have than those they do not possess. Our dogs are all the “best boys and girls.”
So what does any of this have to do with energy consumption? As you may have guessed, understanding how researchers and policymakers theorize, conceptualize and operationalize ideas about behavior and decision-making given uncertainty and competitive choices is key to also understanding how utilities create incentive programs that influence your everyday energy usage. As the saying goes, you might not be interested in politics (of energy), but politics are interested in you!
The next pieces in this series will build on the ideas presented in this post to help you make informed decisions about your home and business energy use, in the context of the myriad choices available to us in product choice, utility savings plans, and more.
Electrically yours,
K.T.