Journal
JOURNAL OF MECHANICAL DESIGN
Volume 138, Issue 10, Pages -Publisher
ASME
DOI: 10.1115/1.4034084
Keywords
sustainable design; design methodology; design for the environment; behavioral analysis; user behavior categorization; living laboratory study
Categories
Funding
- Singapore University of Technology and Design (SUTD) through the Energy Innovation Research Program (EIRP) Singapore [NRF2012EWT-EIRP002-045]
- SUTD-MIT International Design Centre (IDC)
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User behavior can determine over one third of the energy consumed in the residential energy market. Thus, user behavior has become a primary focus in sustainable mechanical device, appliance, and smart-energy systems design. Wasteful user behaviors, termed energy overuse failure modes (EOFMs), offer an opportunity for design engineers to direct users toward more sustainable behavior through design strategies. There are fundamentally two intervention strategies: (1) product or systems solution led or (2) behavioral led. Both are used to achieve increased sustainable user behavior. To ensure expected intervention outcomes, it is equally important to both identify the EOFMs as well as their underlying causes. However, the prevailing sustainable design approaches, such as design for sustainable behavior (DfSB) and ecodesign, depend on stated responses to elicit underlying causes of behavior. Consequently, the outcomes of these approaches are susceptible to response biases. In this paper, a new revealed behavior based framework is introduced to elicit underlying causes of EOFMs and to propose potential intervention strategies to address them. We focus on uncovering two underlying causes that correspond to the intervention strategies: (1) high energy consuming habits and (2) lack of energy awareness. In the proposed framework, user behavior categorization matrices are formulated using a two-phase user study approach with a request to lower the energy use in-between the phases. Based on the observed behavior, each EOFM is matrix categorized on two axes of change and correctness. With this data, the matrices thereby indicate the dominant underlying causes of EOFMs. The EOFMs and proposed interventions can then be prioritized based on the likelihood of occurrence, severity, magnitude or a combinatorial strategy to suit the sustainability objectives. A case study is presented with seven EOFMs that are found in typical day-to-day household electromechanical appliance use including inefficient appliance setup, inefficient selection, inefficient operation, standby energy consumption, and inefficient settings of conditions. Lack of user awareness of energy and power interactions among appliances and household settings is identified as the key underlying cause of considered EOFMs. Potential design solution strategies are also considered to overcome the EOFMs based on likelihoods, severities, and magnitudes, respectively. Each solution strategy carries a varying level of knowledgeable decision-making required of the user, compared with alternatively designing into the product or systems restrictions on use.
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