Presented by: Dr. Hyun Joo Kwon, Mira Ahn, Suk-Kyung Kim, Sung-Jin Lee
Introduction People over 55 spend 8.1% of their annual expenditure on energy; this percentage rises as income falls (Cashin, 2006). Since most seniors desire to remain in their home as long as possible, a home that uses less energy to provide the same service (i.e., energy-efficiency) will both reduce greenhouse gas emission and permit older people to age affordably in place (Maqbool, Viveiros, & Ault, 2015). However, many older adults in the US live in old and less energy-efficient homes (U.S. Energy Information Administration, 2013). To encourage older adults to make their homes energy-efficient and to provide knowledge about potential clients’ perceptions on energy-efficient homes to interior designers, it is important to understand how older adults make those decisions. The goal of this study is to examine older adults’ decision making process of choosing energy-efficient home though their attitudes and subjective knowledge based on the theory of planned behavior (TPB)(Ajzen, 1991). This study incorporates subjective knowledge of energy-efficient home into the classic attitudinal constructs (attitudes, subjective norm, and perceived behavioral control) in the TPB model as predictors of choosing an energy-efficient home (intention to choose, and actual behavior to choose an energy-efficient home). Methods The target population was homeowners aged 55 and over (N = 328). A self-administered questionnaire was developed and data were collected through online survey in 2015. Descriptive statistics, factor analysis, and path analysis were used. SPSS and AMOS were used to analyze data. Results Average age of the respondents was 65.75 (SD=6.85). Almost half were male and half were female. Path analysis results show that participants had positive attitudes towards energy-efficient homes, intended to choose an energy-efficient home, and reported a moderate-to-high actual behavior to choose an energy-efficient home (M=5.53 out of 7); however, scores for subjective norm and perceived behavioral control were relatively low and subjective knowledge showed the lowest score (M=5.00 out of 7). A path model revealed that attitudes, subjective norm, and subjective knowledge were significantly positively related to intention to choose an energy-efficient home. Among them, subjective knowledge was the strongest indicator of intention to choose an energy-efficient home. In addition, significant relationships between subjective knowledge and actual behavior to choose energy-efficient home were found. As hypothesized in the TPB, significant relationship between intention to choose an energy-efficient home and actual behavior to choose an energy-efficient home were confirmed. However, there was no significant relationship between perceived behavioral control and intention to choose energy-efficient home. Conclusion This study partially supports the theory of planned behavior by confirming the relationships between the attitudinal constructs (attitudes and subjective norm) and behaviors (intention and actual behavior of choosing energy-efficient home). Older adults who have more positive attitudes and stronger social norm towards an energy-efficient home are more likely to intend to and then choose the house. One of the notable findings is the role of subjective knowledge and perceived behavioral control. Even though subjective knowledge was the strongest indicator of intention and actual behavior of choosing an energy-efficient house, its score was lower than that of others. Regarding the insignificant impact of perceived control to the intention, we might claim current house conditions or financial status of participants. Thus, in future studies, adding variables such as housing unit quality or income, to the proposed model is recommended to understand older adults’ decision to live in an energy-efficient home. This study has important implications for interior designers, and interior design educators and researchers.
- Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
- Cashin, D. B. (2006). Household energy expenditures, 1982-2005. Chicago Fed Letter, June 2006.
- Maqbool, N., Viveiros, J., & Ault, M. (2015). The impacts of affordable housing on health: A research summary. Insights from Housing Policy Research, April 2015.
- U.S. Energy Information Administration. (2013, September, 18, 2016). Newer U.S. homes are 30% larger but consume about as much energy as older homes. Today in Energy. from http://www.eia.gov/todayinenergy/detail.cfm?id=9951&src=‹ Consumption Residential Energy Consumption Survey (RECS