Demographic and Social-Psychological Variables Affecting the Intention to Use Home Energy Management Systems (HEMS) Priscilla Cho 1 , Xiaojing Xu 2 , James Brannon 2 , Jacqueline Adams 2 , Chien-fei Chen 2 1 Bearden High School, 2 The University of Tennessee, Knoxville ⧫ Home Energy Management System (HEMS) refers to any hardware and/or software system that can monitor and provide feedback about a home’s energy usage, and/or enable advanced control of energy-using systems and devices in the home. ⧫ HEMS can show daily electricity consumption, help users reach the goal of energy saving by managing home appliances, and reduce the amount of carbon emissions ⧫ The purpose of this study is to research the significance of demographic variables and social-psychological variables in affecting one’s intention to use HEMS. ⧫ The social-psychological variables were derived from the technology acceptance model (TAM) and the theory of planned behavior (TPB); additional variables were also included. INTRODUCTION Survey Design DATA ANALYSIS APPLICATION This work was supported in part by the Engineering Research Center Program of the National Science Foundation and the Department of Energy under NSF Award Number EEC-1041877 and the CURENT Industry Partnership Program. ⧫ A 10-minute online survey was given to the residents in New York and Tokyo. ⧫ Survey topics included basic questions (age, gender, etc), background of HEMS, additional services, attitudes towards HEMS, household and energy habits, and demographics. Linear Regression AGE (NY) INCOME LEVEL (NY) REFERENCES AGE (Tokyo) INCOME LEVEL (Tokyo) Less than $34,999 13% $35,000-$99,999 49.8% $100,000+ 37.2% Less than $34,999 38.4% $35,000-$99,999 45% $100,000+ 16.6% 30-39 years old 27.4% 40-49 years old 19.5% 50-59 years old 25% 60-69 years old 28.1% 30-39 years old 13% 40-49 years old 30.2% 50-59 years old 33.3% 60-69 years old 23.5% Intention to Use HEMS in both cities Intention to Use HEMS with Additional Services Age Income Household Size Habits New York 15.010* 6.723* 5.436* 4.584* Tokyo 0.824 5.486* 2.881* 5.404* F-values One-Way ANOVA Independent Samples T Test Gender New York 2.869* Tokyo -3.213* t-values Intention (Age x Location) Intention (Gender x Location) http://www.theecoexperts.co.uk/home-energy-management-systems-a- comprehensive-guide p-value < .05 p-value < .01 p-value < .001 * ** *** Smart Home Management System (HEMS): A Useful Tool for the Future ⧫ HEMS can serve many functions including: ● Providing extra security to your home. ● Providing tele-medical services. ● Saving money on electricity. ● Adopting an environmentally-friendly lifestyle. ⧫ It is expected that over $4,000 million will be spent on HEMS in 2017. Install HEMS to be included in the trend. Smart Home Management System (HEMS): Now You Have Control ⧫ Easy to use You can access HEMS on your smartphone, quickly and efficiently. ⧫ You have the power to control how much money you spend on your electricity. ⧫ Money Saved > Money Spent The money you will save while using HEMS outweighs the money you will spend on HEMS New York Tokyo ⧫ A total of 2544 people participated, with 1228 (48.3%) from New York and 1316 (51.7%) from Tokyo. ⧫ 611 females (49.8%) and 617 males (50.2%) from New York participated; 669 females (50.8%) and 647 males (49.2%) from Tokyo participated. Participants METHOD CONCLUSION 1. Age → Intention Younger people are more likely to use HEMS in New York. Age did not affect the intention to use HEMS in Tokyo. 2. Income → Intention People with higher levels of income are more likely to utilize HEMS in New York. 3. Gender → Intention Males are more likely to use HEMS in New York. Females are more likely to use HEMS in Tokyo. 4. Out of the variables from TPB, two were significant for NY (Attitudes and Social Norms), and three were significant for Tokyo (Attitudes, Social Norms, and Perceived Behavioral Control). 5. Out of the variables from TAM, two were significant for Tokyo (Perceived Ease of Use and Cost), and one was significant for New York (Usefulness). 6. Additional variables: Dependence was significant for both locations, and habits were significant for New York. Using these results, utility companies can make flyers to promote the use of HEMS in each location. Chien-fei Chen, Xiaoxing Xu, Arpan, Laura. (2016). Between the technology acceptance model and sustainable energy technology acceptance model: Investigating smart meter acceptance in the United States. Volume 25: Energy Research & Social Science. doi: 10.1016/j.erss.2016.12.011 Bojanczyk, K. (2013, September 11). Redefining Home Energy Management Systems. Retrieved June 17, 2017, from https://www.greentechmedia.com/articles/read/home-energy- management- systems-redefined Chen, Chien-fei, Xiaojing Xu, and Julia K. Day. (2017). Thermal Comfort or Money Saving? Exploring Intentions to Conserve Energy among Low- income Households in the United States. Volume 26: Energy Research & Social Science. doi: 10.1016/j.erss.2017.01.009 I.Ajzen, The theory of planned behavior, Organ. Behav. Hum. Decis. Process. 50 (1991) 179-211. Miziolek, C. (n.d.). Home Energy Management Systems. Retrieved from http://www.neep.org/initiatives/high-efficiency- products/home-energy- management-systems/ One-way ANOVA. (n.d.). Retrieved June 17, 2017, from https://statistics.laerd.com/statistical-guides/one- way-anova- statistical-guide.php SPSS Annotated Output Regression Analysis. UCLA: Statistical Consulting Group. From https://stats.idre.ucla.edu/spss/output/regression-analysis/ (Accessed June 17, 2017)
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Demographic and Social-Psychological Variables Affecting the Intention to Use Home Energy
Management Systems (HEMS)
Priscilla Cho1, Xiaojing Xu2 , James Brannon2 , Jacqueline Adams2, Chien-fei Chen2
1 Bearden High School, 2 The University of Tennessee, Knoxville
⧫ Home Energy Management System (HEMS) refers to any hardware and/or software system that can monitor and provide feedback about a home’s energy usage, and/or enable advanced control of energy-using systems and devices in the home. ⧫ HEMS can show daily electricity consumption, help users reach the goal of energy saving by managing home appliances, and reduce the amount of carbon emissions⧫ The purpose of this study is to research the significance of demographic variables and social-psychological variables in affecting one’s intention to use HEMS.⧫ The social-psychological variables were derived from the technology acceptance model (TAM) and the theory of planned behavior (TPB); additional variables were also included.
INTRODUCTION
Survey Design
DATA ANALYSIS
APPLICATION
This work was supported in part by the Engineering Research Center Program of the National Science Foundation and
the Department of Energy under NSF Award Number EEC-1041877 and the CURENT Industry Partnership Program.
⧫ A 10-minute online survey was given to the residents in New York and Tokyo.⧫ Survey topics included basic questions (age, gender, etc), background of HEMS, additional services, attitudes towards HEMS, household and energy habits, and demographics.
Linear Regression
AGE (NY)INCOME LEVEL (NY)
REFERENCES
AGE (Tokyo)INCOME LEVEL (Tokyo)
Less than $34,999 13%
$35,000-$99,999 49.8%
$100,000+ 37.2%
Less than $34,999 38.4%
$35,000-$99,999 45%
$100,000+ 16.6%
30-39 years old 27.4%
40-49 years old 19.5%
50-59 years old 25%
60-69 years old 28.1%
30-39 years old 13%
40-49 years old 30.2%
50-59 years old 33.3%
60-69 years old 23.5%
Intention to Use HEMS in both cities
Intention to Use HEMS with Additional Services
Age Income Household Size Habits
New York 15.010* 6.723* 5.436* 4.584*
Tokyo 0.824 5.486* 2.881* 5.404*
F-values
One-Way ANOVA
Independent Samples T Test
Gender
New York 2.869*
Tokyo -3.213*
t-values
Intention (Age x Location)Intention (Gender x Location)
http://www.theecoexperts.co.uk/home-energy-management-systems-a-comprehensive-guide
p-value < .05 p-value < .01 p-value < .001
******
Smart Home Management System (HEMS): A Useful Tool for the Future
⧫ HEMS can serve many functions including:● Providing extra security to your home.● Providing tele-medical services. ● Saving money on electricity.● Adopting an environmentally-friendly lifestyle.
⧫ It is expected that over $4,000 million will be spent on HEMS in 2017. Install HEMS to be included in the trend.
Smart Home Management System (HEMS): Now You Have Control
⧫ Easy to useYou can access HEMS on your smartphone, quickly and efficiently.
⧫ You have the power to control how much money you spend on your electricity.
⧫ Money Saved > Money SpentThe money you will save while using HEMS outweighs the money you will spend on HEMS
New York Tokyo
⧫ A total of 2544 people participated, with 1228 (48.3%) from New York and 1316 (51.7%) from Tokyo. ⧫ 611 females (49.8%) and 617 males (50.2%) from New York participated;
669 females (50.8%) and 647 males (49.2%) from Tokyo participated.
Participants
METHOD
CONCLUSION1. Age → Intention
Younger people are more likely to use HEMS in New York.Age did not affect the intention to use HEMS in Tokyo. 2. Income → IntentionPeople with higher levels of income are more likely to utilize HEMS in New York.3. Gender → IntentionMales are more likely to use HEMS in New York.Females are more likely to use HEMS in Tokyo.4. Out of the variables from TPB, two were significant for NY (Attitudes and Social Norms), and three were significant for Tokyo (Attitudes, Social Norms, and Perceived Behavioral Control). 5. Out of the variables from TAM, two were significant for Tokyo (Perceived Ease of Use and Cost), and one was significant for New York (Usefulness).6. Additional variables: Dependence was significant for both locations, and habits were significant for New York.
Using these results, utility companiescan make flyers to promote the use ofHEMS in each location.
Chien-fei Chen, Xiaoxing Xu, Arpan, Laura. (2016). Between the technology acceptance model and sustainable energy technology acceptance model: Investigating smart meter acceptance in the United States. Volume 25: Energy Research & Social Science. doi: 10.1016/j.erss.2016.12.011
Bojanczyk, K. (2013, September 11). Redefining Home Energy Management Systems. Retrieved June 17, 2017, from https://www.greentechmedia.com/articles/read/home-energy- management- systems-redefined
Chen, Chien-fei, Xiaojing Xu, and Julia K. Day. (2017). Thermal Comfort or Money Saving? Exploring Intentions to Conserve Energy among Low- income Households in the United States. Volume 26: Energy Research & Social Science. doi: 10.1016/j.erss.2017.01.009
I.Ajzen, The theory of planned behavior, Organ. Behav. Hum. Decis. Process. 50 (1991) 179-211.Miziolek, C. (n.d.). Home Energy Management Systems. Retrieved from http://www.neep.org/initiatives/high-efficiency-
products/home-energy- management-systems/One-way ANOVA. (n.d.). Retrieved June 17, 2017, from https://statistics.laerd.com/statistical-guides/one- way-anova-
statistical-guide.phpSPSS Annotated Output Regression Analysis. UCLA: Statistical Consulting Group. From
https://stats.idre.ucla.edu/spss/output/regression-analysis/ (Accessed June 17, 2017)
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