For countries pursuing sustainable development and energy efficiency, the use of smart meters is considered a first step in allowing residential consumers to control their energy consumption remotely and a promising solution for the problem of limited energy resources. However, despite the growing interest in smart meters, many consumers are still skeptical due to their limited awareness, knowledge, and understanding of these devices. Therefore, this study developed an index of consumer propensity to adopt smart meters in residential buildings. Data obtained in a survey of energy use by Indonesia households were analyzed by structural equation modeling to determine the interacting factors in consumer acceptance of smart meters. Consumer perceptions, expectations, and intentions regarding the potential use of smart meters in Indonesia were also discussed. The findings of this research provide a better understanding of consumer perceptions and behaviors which can help decision makers and energy utility companies develop policies and strategies for a “one-size-fits-all” program related to smart meter applications in future residential buildings.

For countries pursuing sustainable development and energy efficiency, the use of smart meters is considered a first step in allowing residential consumers to control their energy consumption remotely and a promising solution for the problem of limited energy resources. However, despite the growing interest in smart meters, many consumers are still skeptical due to their limited awareness, knowledge, and understanding of these devices. Therefore, this study developed an index of consumer propensity to adopt smart meters in residential buildings. Data obtained in a survey of energy use by Indonesia households were analyzed by structural equation modeling to determine the interacting factors in consumer acceptance of smart meters. Consumer perceptions, expectations, and intentions regarding the potential use of smart meters in Indonesia were also discussed. The findings of this research provide a better understanding of consumer perceptions and behaviors which can help decision makers and energy utility companies develop policies and strategies for a “one-size-fits-all” program related to smart meter applications in future residential buildings.

A.Hayduk, L. (1987). Structural Equation Modeling with LISREL, the Johns Hopkins University Press.
Agarwal R., P. J. (1999). "Are Individual Differences Germane to the Acceptance of New Information Technologies?" Decision Sciences, 30(2), 361-390.
Aghaei, J., and Alizadeh, M.-I. (2013). "Demand response in smart electricity grids equipped with renewable energy sources: A review." Renewable and Sustainable Energy Reviews, 18, 64-72.
Alahmad, M. A., Wheeler, P. G., Schwer, A., Eiden, J., and Brumbaugh, A. (2012). "A comparative study of three feedback devices for residential real-time energy monitoring." IEEE Transactions on Industrial Electronics 59(4), 2002-2013.
Anderson, J. C., and Gerbing, D. W. (1988). "Structural Equatin Modeling in Practice: A Review and Recommend Two-Step Approach." Psychological Bulletin, 103(3), 411-423.
B.Kline, R. (2011). Priciples and Practice of Structural Equation Modeling (Third Edition), The Guilford Press, New York.
Baron, R. M., and Kenny, D. A. (1986). "The moderator-mediator variable distriction in social psychological research: Conceptual, strategic, and statistical considerations." Journal of Personality and Social Psychology, 51(6), 1173-1182.
Bollen, K. A. (1989). "A New Incremental Fit Index for General Structural Equation Models." Sociological Methods and Research, 17(3), 303-316.
Carman, J. M. (1990). "Consumer perceptions of service quality: An assessment of the SERVQUAL dimensions." Journal of Retailing, 66(1), 33-55.
Cho, K., Hong, T., and Hyun, C. (2009). "Effect of project characteristics on project performance in construction projects based on structural equation model." Expert Systems with Applications, 36(7), 10461-10470.
Chou, J.-S., and Kim, C. (2009). "A structural equation analysis of the QSL relationship with passenger riding experience on high speed rail: An empirical study of Taiwan and Korea." Expert Systems with Applications, 36(3, Part 2), 6945-6955.
Comrey, A. L., and Lee, H. B. (1992). A First Course Factor Analysis, Taylor & Francis Group.
Cronin Jr, J. J., Brady, M. K., and Hult, G. T. M. (2000). "Assessing the effects of quality, value, and customer satisfaction on consumer behavioral intentions in service environments." Journal of Retailing, 76(2), 193-218.
Davis, F. D. (1989). "Perceived usefulness, Perceived ease of use, and user acceptance of information technology." MIS Quarterly, 13(3), 319-340.
Davis, F. D., Bagozzi, R.P., Warshaw, P.R. (1989). "User acceptance of Computer Technology: A Comparison of Two Theoritical Models." Management Science, 35(8), 982-1003.
Depuru, S. S. S. R., Wang, L., and Devabhaktuni, V. (2011). "Smart meters for power grid: Challenges, issues, advantages and status." Renewable and Sustainable Energy Reviews, 15(6), 2736-2742.
DeSanctis, G., and Poole, M. S. (1994). "Capturing the complexity in advanced technology use: Adaptive structural theory." Organization Science, 5, 121-147.
Faruqui, A., Sergici, S., and Sharif, A. (2010). "The impact of informational feedback on energy consumption—A survey of the experimental evidence." Energy, 35(4), 1598-1608.
Fisbein, M., and Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research, Addison-Wesley.
Fornell, C., and F.Larcker, D. (1981). "Evaluating Structural Equation Models with Unobservable Variables and Measurement Error." Journal of Marketing Research, 18(1), 39-50.
Fornell, C., Johnson, M., Anderson, E., Cha, J., and Bryant, B. (1996). "The American Customer Satisfaction Index: Nature, Purpose, and Findings." Journal of Marketing, 60(4), 7-18.
Garson, G. D. (2012). "Factor Analysis." Statistical Associates Publishers North Carolina.
Guadagnoli, E., and Velicer, W. F. (1988). "Relation of sample size to the stability of component patterns." Psychological Bulletin, 103, 265-275.
Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R. E. (2010). Multivariate Data Analysis: A global perspective, Pearson Education International, New Jersey.
Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R. E. (2010). Multivariate Data Analysis: A global perspective (Seventh Edition), Pearson Education International, New Jersey.
Hargreaves, T., Nye, M., and Burgess, J. (2013). "Keeping energy visible? Exploring how householders interact with feedback from smart energy monitors in the longer term." Energy Policy, 52, 126–134.
Hartway, R., Price, S., and Woo, C. K. (1999). "Smart meter, customer choice and profitable time-of-use rate option." Energy, 24(10), 895-903.
Hatcher, L. (1994). A Step-By-Step Approach to Using the Sas System for Factor Analysis and Structural Equation Modeling, SAS Inst.
Kenapa harus hemat listrik? Available from: <http://earthhour.wwf.or.id>
Penduduk Indonesia Menurut Provinsi Tahun 2010. Available from: <http://www.bps.go.id>
Hung, S.-Y., Chang, C.-M., and Kuo, S.-R. (2013). "User acceptance of mobile e-government services: An empirical study." Government Information Quarterly, 30(1), 33-44.
Iacobucci, D. (2010). "Structural equations modeling: Fit Indices, sample size, and advanced topics." Journal of Consumer Psychology, 20(1), 90-98.
Jackson, C. M., Chow, S., and bitch, R. A. (1997). "Toward an Understanding of the Behavioral Intention to Use an Information System." Decision Sciences, 28(2), 357-389.
Javed, F., Arshad, N., Wallin, F., Vassileva, I., and Dahlquist, E. (2012). "Forecasting for demand response in smart grids: An analysis on use of anthropologic and structural data and short term multiple loads forecasting." Applied Energy, 96, 150-160.
Johnson, A. M. "The technology acceptance model and the decision to invest in information security." Proceedings of the 2005 Southern Association of Information Systems Conference, 1-5.
Kim, H.-J., Mannino, M., and Nieschwietz, R. J. (2009). "Information technology acceptance in the internal audit profession: Impact of technology features and complexity." International Journal of Accounting Information Systems, 10(4), 214-228.
Kline, R. B. (2011). Principles and Practice of Structural Equation Modeling, The Guilford Press.
Krishnamurti, T., Schwartz, D., Davis, A., Fischhoff, B., de Bruin, W. B., Lave, L., and Wang, J. (2012). "Preparing for smart grid technologies: A behavioral decision research approach to understanding consumer expectations about smart meters." Energy Policy, 41, 790-797.
Lean, H. H., and Smyth, R. (2013). "Will policies to promote renewable electricity generation be effective? Evidence from panel stationarity and unit root tests for 115 countries." Renewable and Sustainable Energy Reviews, 22, 371-379.
Lee, D. Y., and Lehto, M. R. (2013). "User acceptance of YouTube for procedural learning: An extension of the Technology Acceptance Model." Computers & Education, 61, 193-208.
Lee, S.-K., and Yu, J.-H. (2012). "Success model of project management information system in construction." Automation in Construction, 25, 82-93.
Li, H., Fang, D., Mahatma, S., and Hampapur, A. "Usage analysis for smart meter management." Proceedings of the 8th International Conference & Expo on Emerging Technologies for a Smarter World (CEWIT), 1-6.
Lima, C. A. F., and Navas, J. R. P. (2012). "Smart metering and systems to support a conscious use of water and electricity." Energy, 45(1), 528-540.
Lin, F., Fofanah, S. S., and Liang, D. (2011). "Assessing citizen adoption of e-Government initiatives in Gambia: A validation of the technology acceptance model in information systems success." Government Information Quarterly, 28(2), 271-279.
Liu, W., Wang, C., and Mol, A. P. J. (2013). "Rural public acceptance of renewable energy deployment: The case of Shandong in China." Applied Energy, 102, 1187-1196.
Lu, Y., Zhou, T., and Wang, B. (2009). "Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory." Computers in Human Behavior, 25(1), 29-39.
M.Byrne, B. (2009). Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming, Taylor & Francis Inc, New York.
MacCallum, R. C., Widaman, K. F., Zhang, S., and Hong, S. (1999). "Sample Size in Factor Analysis." Psychological Methods, 4(1), 84-99.
Mah, D. N.-Y., van der Vleuten, J. M., Hills, P., and Tao, J. (2012). "Consumer perceptions of smart grid development: Results of a Hong Kong survey and policy implications." Energy Policy, 49, 204-216.
Mah, D. N.-Y., van der Vleuten, J. M., Ip, J. C.-M., and Hills, P. R. (2012). "Governing the transition of socio-technical systems: A case study of the development of smart grids in Korea." Energy Policy, 45, 133-141.
Mah, N., van der Vleuten, D., Johannes Marinus, J., Hills, P., and Tao, J. (2012). "Consumer perceptions of smart grid development: Results of a Hong Kong survey and policy implications." Energy Policy, 49, 204-216.
McKenna, E., Richardson, I., and Thomson, M. (2012). "Smart meter data: Balancing consumer privacy concerns with legitimate applications." Energy Policy, 41, 807-814.
Likert Scale. <http://www.simplypsychology.org/likert-scale.html>. Available from: <McLeod, S. A.> (2008).
Molenaar, K., Washington, S., and Diekmann, J. (2000). "Structural Equation Model of Construction Contract Dispute Potential." Journal of Construction Engineering and Management 126(4), 268-277.
Ning, S. K., Yeh, S. C., Chen, J. C., Hung, M. C., Lin, Q. G., Cai, Y. P., and Yeh, Y. H. (2013). "Identification of optimal strategies for sustainable energy management in Taiwan." International Journal of Energy Research, 37(3), 268-282.
Parasuraman, A. (2000). "Technology readiness index (Tri): A multiple-item scale to measure readiness to embrace new technologies." Journal of Service Research, 2(4), 307-320.
Priatna, D. S. (1999). "Theft of Electricity in Indonesia." Ph.D Dissertation, University of Wisconsin, Madison.
Quinn, E. (2009). "Smart Metering & Privacy: Existing Law and Competing Policies." Electronic Frontier Foundation.
Ratchford, M., and Barnhart, M. (2012). "Development and validation of the technology adoption propensity (TAP) index." Journal of Business Research, 65(8), 1209-1215.
Ratchford, M., and Barnhart, M. (2012). "Development and validation of the technology adoption propensity (TAP) index." Journal of Business Research, 65, 1209-1215.
Rossiter, J. R., and Braithwaite, B. (2013). "C-OAR-SE-based single-item measures for the two-stage Technology Acceptance Model." Australasian Marketing Journal (AMJ), 21(1), 30-35.
Shibl, R., Lawley, M., and Debuse, J. (2013). "Factors influencing decision support system acceptance." Decision Support Systems, 54(2), 953-961.
Son, H., Park, Y., Kim, C., and Chou, J.-S. (2012). "Toward an understanding of construction professionals' acceptance of mobile computing devices in South Korea: An extension of the technology acceptance model." Automation in Construction, 28, 82-90.
Stromback, J., Dromacque, C., and Yassin, M. H. (2011). "The potential of smart meter enabled programs to increase energy and systems efficiency: a mass pilot comparison." VaasaETT, Global Energy Think Tank. European Smart Metering Industry Group, Helsinki, Finland.
Tewolde, M., Longtin, J. P., Das, S. R., and Sharma, S. (2013). "Determining appliance energy usage with a high-resolution metering system for residential natural gas meters." Applied Energy, 108, 363-372.
Udo, G. J., Bagchi, K. K., and Kirs, P. J. (2010). "An assessment of customers’ e-service quality perception, satisfaction and intention." International Journal of Information Management, 30(6), 481-492.
Usman, A., and Shami, S. H. (2013). "Evolution of Communication Technologies for Smart Grid applications." Renewable and Sustainable Energy Reviews, 19, 191-199.
Vagias, W. M. (2006). "Likert-type scale response anchors." Clemson International Institute for Tourism & Research Development, Department of Parks, Recreation and Tourism Management, Clemson University.
Venkatesh, V., Davis, F.D. (2000). "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies." Management Science, 46(2), 184-204.
Venkatesh V., D., F.D. (1996). "A Model of Antecedents of Perceived Ease of Use: Development and Test." Decision Sciences, 27(3), 451-480.
Wang, W., Xu, Y., and Khanna, M. (2011). "A survey on the communication architectures in smart grid." Computer Networks, 55(15), 3604-3629.
Wood, G., and Newborough, M. (2007). "Influencing user behaviour with energy information display systems for intelligent homes." International Journal of Energy Research, 31(1), 56-78.
Xingang, Z., Jiaoli, K., and Bei, L. (2013). "Focus on the development of shale gas in China—Based on SWOT analysis." Renewable and Sustainable Energy Reviews, 21, 603-613.
Yang, H.-D., and Yoo, Y. (2004). "It's all about attitude: revisiting the technology acceptance model." Decision Support Systems, 38(1), 19-31.
Zahedi, A. (2011). "A review of drivers, benefits, and challenges in integrating renewable energy sources into electricity grid." Renewable and Sustainable Energy Reviews, 15(9), 4775-4779.
Zhifeng, Q., and Deconinck, G. "Smart Meter's feedback and the potential for energy savings in household sector: A survey." Proceedings of the IEEE International Conference on Networking, Sensing and Control (ICNSC). 281-286.