When we talk about improving energy efficiency, there are two broad paradigms under which we might consider options for increased efficiencies. The first is a very engineering-centric perspective known as PTEM (which stands for Physical-Technical-Economic Model) which approaches energy efficiency from the perspective that new technologies are the only driver of greater efficiencies so long as they are economically viable. This often requires subsidization because emerging technologies almost always cost more than ones that have already established thmeselves in the market. When we think about this in the context of energy efficiency programs out there today, it makes sense - there are myriad rebate programs and tax credits that aim to reward increases in energy efficiency among residential and commercial users. The purpose of this is to make them less expensive than existing technologies and practices.
But if changing energy consumption were really this cut and dry, we would likely not be in the energy policy conundrum in which we find ourselves as a country today. Economics and numbers work quite well on paper, but people don't always behave in the most economically or technologically rational ways. We're people (not homo economicus), and our behaviors are often irrational and unpredictable, and that extends to our behavior related to energy consumption. Some experts suggest that nearly half of all actual energy use is based on operating behavior, not technologies in place. But changing behaviors is challenging - a seemingly much more daunting task than coming up with new technologies! Think about this - I could give you free LEDs - maybe I even install them in your home for you (and in fact many programs do this, including in Delaware). But how can I influence your decision to leave them on all day and night? This is a tough challenge, even with the economic incentive to conserve energy that we all understand as utility customers. People are creatures of habit, and it's hard to make them (well, us) change our ways for even economic benefits, much less those more tertiary benefits like avoiding catastrophic CO2 levels in our atmosphere. this "overuse" of energy due to behavioral changes after efficiency measures are installed is called "the rebound effect." Some recent research suggests that economy-wide rebound effects often exceed 50% (!) and thus - among other things - can significantly compromise modeling of energy reductions due to decoupling efforts.
Another key consideration in the differences between PTEM and human behavior is the quantifiability. It is no surprise that approaches under the PTEM model are more easily verified. If you use this technology in this way, you can anticipate X savings on your utility bill. Quantifiable reductions are viewed as key indicators for the success of a program. Working with people in more qualitative ways to understand and influence their energy consumption patterns is much more challenging to quantify, and therefore harder to determine if it's working or not. The important thing you should take away from this discussion is that there is no one right or wrong way. Like much of what we've discussed in this course, energy efficiency improvements necessitate a mix of qualitative and quantitative approaches to ensure maximum increases.