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Smart energy for Robinson Crusoe: an empirical analysis of the adoption of IS-enhanced electricity storage systems

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Abstract

A lack of social acceptance of large-scale infrastructure projects hampers the necessary transformation of the current energy system. However, besides such large projects, the decentralized generation of electricity is becoming increasingly important and may in the future be accompanied by green IS in the form of IS-enhanced distributed electricity storage systems (ESS). Thus, the aim of this study is to advance the understanding of factors that are necessary for the acceptance and adoption of ESS in private households. We propose a conceptual model and empirically test it with survey data gathered from 339 decision-makers for modifications of privately owned houses in Germany. The statistical analysis confirms that social norms, affinity toward autarky, and concerns about the security of supply influence ESS adoption. We recommend adopters of photovoltaics as first target customers. Moreover, our findings have important implications for utility companies, policy-makers, and for the design and marketing of IS-enhanced ESS.

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Notes

  1. In this study, we use the term customer for customers as well as for potential customers that might adopt the ESS.

  2. Additionally, for cross checking, we used STATA 10 to estimate our hypotheses and significances using a multiple linear regression with the ordinary least square estimator. Our results did not differ from those of the SmartPLS analysis.

References

  • Abbott, M. (2001). Is the security of electricity supply a public good? The Electricity Journal, 14(7), 31–33.

    Article  Google Scholar 

  • Adamek, F., Aundrup, T., Glaunsinger, W., Kleimeier, M., Landinger, H., Leuthold, M., Benedikt, L., Moser, A., Pape, C., Pluntke, H., Rotering, N., Sauer, D.U., Sterner, M., and Wellfoß, W. (2012). Energiespeicher für die Energiewende - Speicherungsbedarf und Auswirkungen auf das Übertragungsnetz für Szenarien bis 2050. Energietechnische Gesellschaft im VDE: Verband der Elektrotechnik, Elektronik, Informationstechnik e.V., Frankfurt am Main.

  • Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived usefulness, ease of use, and usage of information technology: A replication. MIS Quarterly, 16(2), 227–247.

    Article  Google Scholar 

  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.

    Article  Google Scholar 

  • Allcott, H. (2011). Social norms and energy conservation. Journal of Public Economics, 95, 1082–1095.

    Article  Google Scholar 

  • Alt, R., & Klein, S. (2011). Twenty years of electronic markets research—looking backwards towards the future. Electronic Markets, 21(1), 41–51.

    Article  Google Scholar 

  • Andrews, D. W. K., & Bushinsky, M. (2000). A three-step method for choosing the number of bootstrap repetitions. Econometrica, 68(1), 23–51.

    Article  Google Scholar 

  • Armstrong, S. J., & Overton, T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14(3), 396–402.

    Article  Google Scholar 

  • Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 244–254.

    Google Scholar 

  • Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Academy of Marketing Science, 16(1), 74–94.

    Article  Google Scholar 

  • Bamberg, S. (2003). How does environmental concern influence specific environmentally related behaviors? A new answer to an old question. Journal of Environmental Psychology, 23, 21–32.

    Article  Google Scholar 

  • Bang, H.-K., Ellinger, A. E., Hadjimarcou, J., & Traichal, P. A. (2000). Consumer concern, knowledge, belief, and attitude toward renewable energy - an application of the reasoned action theory. Psychology and Marketing, 17(6), 449–468.

    Article  Google Scholar 

  • Benbasat, I., & Barki, H. (2007). Quo Vadis, Tam? Journal of the Association for Information Systems, 8(4), 211–218.

    Google Scholar 

  • Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: A theoretical model and longitudinal test. MIS Quarterly, 28(2), 229–254.

    Google Scholar 

  • BMU. (2011). Renewable Energy Sources in Figures - National and International Development. n.C.a.n.S.B. Federal ministry for the Environment (ed.). Berlin: Public Relations Division.

  • Brown, S. A., Venkatesh, V., & Bala, H. (2006). Household technology use: Integrating household life cycle and the model of adoption of technology in households. The Information Society, 22, 205–218.

    Article  Google Scholar 

  • Chandran, S., & Morwitz, V. G. (2005). Effects of participative pricing on consumers’ cognitions and actions: A goal theoretic perspective. Journal of Consumer Research, 32(2), 249–259.

    Article  Google Scholar 

  • Chen, M.-F. (2009). Attitude toward organic foods among Taiwanese as related to health consciousness, environmental attitudes, and the mediating effects of a healthy lifestyle. British Food Journal, 111(2), 165–178.

    Article  Google Scholar 

  • Chen, H., Cong, T. N., Yang, W., Tan, C., Li, Y., & Ding, Y. (2009). progress in electrical energy storage system: A critical review. Progress in Natural Science, 19, 291–312.

    Article  Google Scholar 

  • Chin, W.W. 1998. Issues and opinion on structural equation modeling. MIS Quarterly 22(1).

  • Chin, W. (2000). Partial least squares for is researchers: An Overview and presentation of recent advances using the Pls approach. International Conference on Information Systems, 2000, 741–742.

    Google Scholar 

  • Chiou, J.-S., & Shen, C.-C. (2012). The antecedents of online financial service adoption: The impact of physical banking services on internet banking acceptance. Behaviour & Information Technology, 31(9), 859–871.

    Article  Google Scholar 

  • Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334.

    Article  Google Scholar 

  • Damigos, D., Tourkolias, C., & Diakoulaki, D. (2009). Households’ willingness to pay for safeguarding security of natural gas supply in electricity generation. Energy Policy, 37(5), 2008–2017.

    Article  Google Scholar 

  • Darke, P. R., Chattopadhyay, A., & Ashworth, L. (2006). The importance and functional significance of affective cues in consumer choice. Journal of Consumer Research, 33(3), 322–328.

    Article  Google Scholar 

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

    Article  Google Scholar 

  • De Young, R. (1986). Encouraging environmentally appropriate behavior: The role of intrinsic motivation. Journal of Environmental Systems, 15(4), 281–292.

    Article  Google Scholar 

  • Dickinger, A., & Kleijnen, M. (2008). Coupons going wireless: Determinants of consumer intentions to redeem mobile coupons. Journal of Interactive Marketing, 22(3), 23–39.

    Article  Google Scholar 

  • EC. (2012). Energy - sustainable, secure and affordable energy for Europeans. In: The European Union explained, European Commission, Publications Office of the European Union, Luxembourg, pp. 1–14.

  • EIB. (2007). An efficient, sustainable and secure supply of energy for europe - meeting the challenge (pp. 1–172). Luxembourg: European Investment Bank.

    Google Scholar 

  • Ek, K. (2005). Public and private attitudes towards “green” electricity: The case of swedish wind power. Energy Policy, 33(13), 1677–1689.

    Article  Google Scholar 

  • Feng, H.-Y. (2012). Key factors influencing users’ intentions of adopting renewable energy technologies. Academic Research International, 2(2), 156–168.

    Google Scholar 

  • Fishbein, M., & Ajzen, I. (1975). Belief attitude, intention and behavior (1st ed.). New York: Addison-Wesley.

    Google Scholar 

  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.

    Article  Google Scholar 

  • Fulk, J., Steinfield, C. W., Schmitz, J., & Power, J. G. (1987). A social information processing model of media use in organizations. Communication Research, 14(5), 529–552.

    Article  Google Scholar 

  • Ha, S., & Stoel, L. (2009). Consumer E-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565–571.

    Article  Google Scholar 

  • Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). Pls-sem: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–151.

    Article  Google Scholar 

  • Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414–433.

    Article  Google Scholar 

  • Harris, L. C. (2008). Fraudulent return proclivity: An empirical analysis. Journal of Retailing, 84(4), 461–476.

    Article  Google Scholar 

  • Hartmann, P., & Apaolaza-Ibanez, V. (2012). Consumer attitude and purchase intention toward green energy brands: The roles of psychological benefits and environmental concern. Journal of Business Research, 65, 1254–1263.

    Article  Google Scholar 

  • Helm, D. (2002). Energy policy: Security of supply, sustainability and competition. Energy Policy, 30, 173–184.

    Article  Google Scholar 

  • IEA, I.E.A. (2012). World energy outlook 2012 – Renewable energy outlook. Paris: International Energy Agency.

    Book  Google Scholar 

  • King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information and Management, 43(6), 740–755.

    Article  Google Scholar 

  • Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 13(2), 205–223.

    Article  Google Scholar 

  • Kranz, J., and Picot, A. (2011). Why are consumers going green? The role of environmental concerns in private green-is adoption. Proceedings of the 19th European Conference on Information Systems.

  • Kranz, J., and Picot, A. (2012). Is it money or the environment? An empirical analysis of factors influencing consumers’ intention to adopt the smart metering technology. Proceedings of the 18th American Conference on Information Systems (AMCIS), Seattle.

  • Kulviwat, S., Brunner, G. C., II, & Al-Shuridah, O. (2009). The role of social influence on adoption of high tech innovations: The moderating effect of public/private consumption. Journal of Business Research, 62, 706–712.

    Article  Google Scholar 

  • Lieb-Dóczy, E., Börner, A.-R., & MacKerron, G. (2003). Who secures the security of supply? European perspectives on security, competition, and liability. The Electricity Journal, 16(10), 10–19.

    Article  Google Scholar 

  • Likert, R. (1932). A technique for the measurement of attitudes. Archives of Psychology, 22(140), 1–55.

    Google Scholar 

  • Lindenberg, S., & Steg, L. (2007). Normative, gain and hedonic goal frames guiding environmental behavior. Journal of Social Issues, 63(1), 117–137.

    Article  Google Scholar 

  • Longo, A., Markandya, A., & Petrucci, M. (2008). The internalization of externalities in the production of electricity: Willingness to pay for the attributes of a policy for renewable energy. Ecological Economics, 67(140–152), 140.

    Article  Google Scholar 

  • MacKenzie, S. B., & Lutz, R. J. (1989). An empirical examination of the structural antecedents of attitude toward the ad in an advertising pretesting context. Journal of Marketing, 53(2), 48–65.

    Article  Google Scholar 

  • Malhotra, A., Melville, N. P., & Watson, R. T. (2013). Spurring impactful research on information systems for environmental sustainability. MIS Quarterly, 37(4), 1265–1274.

    Google Scholar 

  • Mallett, A. (2007). Social acceptance of renewable energy innovations: The role of technology cooperation in urban Mexico. Energy Policy, 35, 2790–2798.

    Article  Google Scholar 

  • Maphisa, E., Marcelle, G., & Perrot, R. (2012). Nuclear Energy Technology Adoption by Intensive Energy Industrial Users in South Africa. International Journal of Technological Learning, Innovation and Development, 5, 158–183.

    Article  Google Scholar 

  • Maruyama, Y., Nishikido, M., & Iida, T. (2007). The rise of community wind power in Japan: Enhanced acceptance through social innovation. Energy Policy, 35, 2761–2769.

    Article  Google Scholar 

  • Mayrhofer, P., & Römer, B. (2013). Germany’s transition toward an energy system based on renewable resources: An overview. In E. Noam, L. M. Pupillo, & J. Kranz (Eds.), Broadband networks, smart grids and climate change (pp. 103–118). New York: Springer.

    Chapter  Google Scholar 

  • Mazis, M. B., & Adkinson, J. E. (1976). An experimental evaluation of a proposed corrective advertising remedy. Journal of Marketing Research, 13(2), 178–183.

    Article  Google Scholar 

  • Melville, N. P. (2010). Information systems innovation for environmental sustainability. MIS Quarterly, 34(1), 1–21.

    Google Scholar 

  • Müller, M. O., Stämpfli, A., Dold, U., & Hammer, T. (2011). Energy autarky: A conceptual framework for sustainable regional development. Energy Policy, 39(10), 5800–5810.

    Article  Google Scholar 

  • OECD. (2007). OECD contribution to the United Nations commission on sustainable development 15 - energy for sustainable development (pp. 1–51). Paris: Organisation for Economic Co-Operation and Development.

    Google Scholar 

  • OECD. (2009). Conference proceedings: ICTs, the environment and climate change. Proceedings of the high-level 27–28 May 2009 OECD Conference,. Helsingør.

  • Osbaldiston, R., & Schott, J. P. (2012). Environmental sustainability and behavioral science: Meta-analysis of proenvironmental behavior experiments. Environment and Behavior, 44(2), 257–299.

    Article  Google Scholar 

  • Park, S. Y. (2009). An analysis of the technology acceptance model in understanding university students’ behavioral intention to use E-learning. Educational Technology & Society, 12(3), 150–162.

    Google Scholar 

  • Pelletier, L. G., Dion, S., Tuson, K., & Green-Demers, I. (1999). Why do people fail to adopt environmental protective behaviors? Toward a taxonomy of environmental amotivation. Journal of Applied Social Psychology, 29(12), 2481–2504.

    Article  Google Scholar 

  • Poortinga, W., Steg, L., & Vlek, C. (2004). Values, environmental concern, and environmental behavior: A study into household energy use. Environment and Behavior, 36(1), 70–93.

    Article  Google Scholar 

  • Rae, C., & Bradley, F. (2012). Energy autonomy in sustainable communities—a review of key issues. Renewable and Sustainable Energy Reviews, 16(9), 6497–6506.

    Article  Google Scholar 

  • Rastler, D. (2010). Electricity energy storage technology options. Palo Alto: Electric Power Research Institute.

    Google Scholar 

  • REN21. (2012). Renewables 2012 global status report. Renewable energy policy network for the 21st century, Paris: REN21 Secretariat.

  • Ringle, C.M., Wende, S., and Will, S. (2005). Smartpls 2.0 (M3) Beta. from http://www.smartpls.de

  • Römer, B., and Lerch, C. (2010). How innovative business models increase the economic feasibility of stationary energy storage systems: Potential, opportunities, risks. In: Proceedings of the 5th International Renewable Energy Storage Conference. Berlin.

  • Römer, B., Reichhart, P., Kranz, J., & Picot, A. (2012). The role of smart metering and decentralized electricity storage for smart grids: The importance of positive externalities. Energy Policy, 50, 486–495.

    Article  Google Scholar 

  • Rosen, D. L., & Olshavsky, R. W. (1987). The dual role of informational social influence: Implications for marketing management. Journal of Business Research, 15, 123–144.

    Article  Google Scholar 

  • Salancik, G. R., & Pfeffer, J. (1978). A social information processing approach to job attitudes and task design. Administrative Science Quarterly, 23(2), 224–253.

    Article  Google Scholar 

  • Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information and Management, 44, 90–103.

    Article  Google Scholar 

  • Shackley, S., Reiner, D., Upham, P., de Coninck, H., Sigurthorsson, G., & Anderson, J. (2008). The acceptability of Co2 capture and storage (Ccs) in Europe: An assessment of the key determining factors. International Journal of Greenhouse Gas Control, 3, 344–356.

    Article  Google Scholar 

  • Späth, P., & Rohracher, H. (2010). ‘Energy regions’: The transformative power of regional discourses on socio-technical futures. Research Policy, 39, 449–458.

    Article  Google Scholar 

  • Stragier, J., Hauttekeete, L., and De Marez, L. (2010). Introducing Smart grids in residential contexts: Consumers’ perception of smart household appliances. In: IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply. pp. 135–142.

  • Troncoso, K., Castillo, A., Masera, O., & Merino, L. (2007). Social perceptions about a technological innovation for fuelwood cooking: Case study in rural Mexico. Energy Policy, 35, 2799–2810.

    Article  Google Scholar 

  • Valle, P. O. D., Rebelo, E., Reis, E., & Menezes, J. (2005). Combining behavioral theories to predict recycling involvement. Environment and Behaviour, 37, 364–396.

    Article  Google Scholar 

  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204.

    Article  Google Scholar 

  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.

    Google Scholar 

  • Venkatesh, V., Brown, S., and Hoehle, H. (2012). Understanding technology adoption in the household context: A comparison of seven theoretical models. ECIS 2012 Proceedings. Paper 35.

  • Wade, N. S., Taylor, P. C., Lang, P. D., & Jones, P. R. (2010). Evaluating the benefits of an electrical energy storage system in a future smart grid. Energy Policy, 38(11), 7180–7188.

    Article  Google Scholar 

  • Wang, W. M., Wang, J., & Ton, D. (2012). Prospects for renewable energy: Meeting the challenges of integration with storage. In F. P. Sioshansi (Ed.), Smart grid - Integrating renewable, distributed, and efficient energy (pp. 103–126). Oxford: Academic.

    Google Scholar 

  • Watson, R. T., Boudreau, M.-C., & Chen, A. J. (2010). Information systems and environmentally sustainable development: Energy informatics and new directions for the is community. MIS Quarterly, 34(1), 23–38.

    Google Scholar 

  • Wietschel, M., Arens, M., Dötsch, C., Herkel, S., Krewitt, W., Markewitz, P., Möst, D., & Scheufen, M. (Eds.). (2010). Energietechnologien 2050 - Schwerpunkte Für Forschung Und Entwicklung: Technologienbericht. Stuttgart: Fraunhofer Verlag.

    Google Scholar 

  • Winkler von Mohrenfels, H., & Klapper, D. (2012). The influence of mobile product information on brand perception and willingness to pay for green and sustainable products. Orlando: Thirty Third International Conference on Information Systems.

    Google Scholar 

  • Wiser, R. H. (2007). Using contingent valuation to explore willingness to pay for renewable energy: A comparison of collective and voluntary payment vehicles. Ecological Economics, 62, 419–432.

    Article  Google Scholar 

  • Wolsink, M. (2012). The research agenda on social acceptance of distributed generation in smart grids: Renewable as common pool resources. Renewable and Sustainable Energy Reviews, 16, 822–835.

    Article  Google Scholar 

  • Wu, J., & Lederer, A. (2009). A meta-analysis of the role of environment-based voluntariness in information technology acceptance. MIS Quarterly, 33(2), 419–432.

    Google Scholar 

  • Wunderlich, P., Kranz, J., Totzek, D., Veit, D., & Picot, A. (2013). The Impact of Endogenous Motivations on Adoption of IT-Enabled Services The Case of Transformative Services in the Energy Sector. Journal of Service Research,16(3), 356–371.

  • Wüstenhagen, R., Wolsink, M., & Bürer, M. J. (2007). Social acceptance of renewable energy innovation: An introduction to the concept. Energy Policy, 35, 2683–2691.

    Article  Google Scholar 

  • Yang, H.-D., & Yoo, Y. (2004). It’s all about attitude: Revisiting the technology acceptance model. Decision Support Systems, 38, 19–31.

    Article  Google Scholar 

  • Yi, M. Y., Jackson, J. D., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information and Management, 43, 350–363.

    Article  Google Scholar 

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Acknowledgement

We have presented work connected to this article at the 35th ISMS Marketing Science Conference 2013 in Istanbul and we are thankful for helpful suggestions from the participants of the conference. We also like to thank the editor and anonymous reviewers for helpful comments during the review process.

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Correspondence to Benedikt Römer.

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Römer, B., Reichhart, P. & Picot, A. Smart energy for Robinson Crusoe: an empirical analysis of the adoption of IS-enhanced electricity storage systems. Electron Markets 25, 47–60 (2015). https://doi.org/10.1007/s12525-014-0167-5

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