Làm cho năng lượng trở nên rõ ràng: các khía cạnh xã hội tâm lý liên quan đến việc sử dụng công tơ thông minh

Energy Efficiency - Tập 8 - Trang 1149-1167 - 2015
Susana Guerreiro1, Susana Batel1, Maria Luísa Lima1, Sérgio Moreira2
1Instituto Universitário de Lisboa (ISCTE-IUL), Cis-IUL, Lisbon, Portugal
2University of Lisbon, Lisbon, Portugal

Tóm tắt

Nghiên cứu này nhằm cải thiện hiểu biết về các khía cạnh xã hội tâm lý và công nghệ ảnh hưởng đến việc sử dụng công tơ thông minh—các công tơ điện năng tiên tiến cung cấp dữ liệu theo thời gian thực về mức tiêu thụ và có vai trò quan trọng trong việc tăng cường hiệu quả năng lượng. Chưa có nhiều nghiên cứu xem xét các yếu tố xã hội tâm lý ảnh hưởng đến việc sử dụng chúng. Chúng tôi lập luận rằng Lý thuyết Hành động Có lý (TRA), Mô hình Chấp nhận Công nghệ (TAM), và các yếu tố cụ thể khác từ tài liệu tâm lý xã hội, chẳng hạn như công bằng quy trình cảm nhận và nhận thức rủi ro, có thể giúp hiểu điều gì xác định việc sử dụng công tơ thông minh. Để kiểm tra điều này một cách thực nghiệm, trước tiên một cuộc khảo sát định lượng đã được thực hiện với 515 hộ gia đình có công tơ thông minh được lắp đặt. Kết quả cho thấy việc sử dụng công tơ thông minh bị ảnh hưởng bởi các quy chuẩn chủ quan, tiện ích cảm nhận, nhận thức rủi ro liên quan đến sức khỏe, công bằng quy trình, và thời gian sử dụng. Trong một nghiên cứu thứ hai, các blog trên internet thảo luận về công tơ thông minh đã được phân tích. Nghiên cứu này xác nhận một số kết quả của nghiên cứu đầu tiên và gợi ý các yếu tố bổ sung—chẳng hạn như công bằng phân phối cảm nhận và mất kiểm soát cùng với nhận thức rủi ro liên quan đến quyền riêng tư—có thể ảnh hưởng đến việc sử dụng công tơ thông minh.

Từ khóa

#công tơ thông minh #lý thuyết hành động có lý #mô hình chấp nhận công nghệ #xã hội tâm lý #hiệu quả năng lượng

Tài liệu tham khảo

Abrahamse, W., Steg, L., Vlek, C., & Rothengatter, T. (2005). A review of intervention studies aimed at household energy conservation. Journal of Environmental Psychology, 25(3), 273–291. doi:10.1016/j.jenvp.2005.08.002.

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

Bauer, M. (1997). Resistance to new technology: nuclear power, information technology and biotechnology. Cambridge: Cambridge University Press.

Bertoldi, P., & Atanasiu, B. (2007). Electricity consumption and efficiency trends in the enlarged european union. DG Joint Research Center, Institute for Environment and Sustainability.

Billig, B. (1985). Prejudice, categorization and particularization: from a perceptual to rhetorical approach. European Journal of Social Psychology, 15, 79–103.

Billig, M. (1997). Rhetorical and discursive analysis: How families talk about the royal family. In N. Hayes (Ed.), Doing qualitative analysis in psychology (pp. 39–54). Hove: Psychology Press.

Bonnes, M., & Bonaiuto, M. (2002). Environmental psychology: from spatial–physical environment to sustainable development. In R. G. Bechtel & A. Churchman (Eds.), Handbook of environmental psychology (pp. 28–54). New York: Wiley.

Boyatzis, R. E. (1998). Transforming qualitative information: thematic analysis and code development. Thousand Oaks: Sage.

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.

Castro, P. (2012). Legal innovation for social change: exploring change and resistance to different types of sustainability laws. Political Psychology, 33(1), 105–121.

Castro, P., & Batel, S. (2008). Social representation, change and resistance: on the difficulties of generalizing new norms. Culture & Psychology, 14, 477–499.

Clayton, S. (2000). Models of justice in the environmental debate. Journal of Social Issues, 56(3), 459–474.

Clayton, S., & Opotow, S. (2003). Justice and identity: changing perspectives on what is fair. Personality and Social Psychology Review, 7(4), 298–310.

Cronick, K. (2002). The discourse of President George W. Bush and Osama bin Laden: a rhetorical analysis and hermeneutic interpretation. Forum: Qualitative Social Research, 3(3) p. 282.

Dahlbom, B., Greer, H., Egmond. C. Jonkers, R. (2009). Changing energy behaviour, guidelines for behavioural change programmes. IDAE - Instituto para la Diversificacióny Ahorro de la Energía, Inteligent Energy Europe.

Darby, S. (2006). The effectiveness of feedback on energy consumption: a review for Defra of the literature on metering, billing and direct displays. Oxford: Environmental Change Institute, University of Oxford.

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

Denzin, N. K. (1970). The research act: a theoretical introduction to sociological methods. Chicago: Aldine.

Devine-Wright, P., & Howes, Y. (2010). Disruption to place attachment and the protection of restorative environments: a wind energy case study. Journal of Environmental Psychology, 30, 271–280.

Directive 2009/28/EC of the European parliament and of the council of 23 April 2009 on the promotion of the use of energy from renewable sources.

Directive 2009/72/EC of the European parliament and of the council of 13 July 2009 concerning common rules for the internal market in electricity and repealing Directive 2003/54/EC.

Directive 2009/73/EC of the European parliament and of the council of 13 July 2009 concerning the internal market in natural gas and repealing Directive 2003/55/EC.

Faruqui, A., Sergici, S., & Sharif, A. (2010). The impact of informational feedback on energy consumption—a survey of the experimental evidence. Energy, 35(4), 1598–1608. doi:10.1016/j.energy.2009.07.042.

Federal Energy Regulator Commission. (2008). Assessment of demand, response and advanced metering. USA: Federal Energy Regulator Commission.

Feinberg, R. (2009). Achieving customer acceptance of the smart grid. The Intelligent Project (Apr. 15): http://theintelligentproject.org/assets/does/061509_achieving-customeracceptance.pdf.

Field, A. (2005). Discovering statistics using SPSS for windows: advanced techniques for the beginner. London: Sage.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: an introduction to theory and research. Reading: Addison-Wesley.

Flick, U. (2009). An introduction to qualitative research (4th ed.). London: Sage Publications.

Folger, R. (1987). Distributive and procedural justice in the workplace. Journal of Social Justice, 1(2), 143–159.

Gamberini, L., Spagnolli, A., et al. (2014). Combining implicit and explicit techniques to reveal social desirability bias in electricity conservation self-reports. Energy Efficiency, 7(6), 923–935.

Giordano, V., Meletiou, A., Covrig, C.F., Mengolini, A. Ardelean, M., Fulli, G., Jiménez, M.S., Filiou, C. (2012). Smart grid projects in Europe: lessons learned and current developments. Joint Research Centre, European Commission.

Gross, C. (2007). Community perspectives of wind energy in Australia. The application of a justice and community fairness framework to increase social acceptance. Energy Policy, 35, 2727–2736.

Hargreaves, T., Nye, M., & Burgess, J. (2010). Making energy visible: a qualitative field study of how householders interact with feedback from smart energy monitors. Energy Policy, 38, 6111–6119.

Heffner, G. (2011). Smart grid—smart customer, policy needs. IEA paper submitted to the energy efficiency working party. Paris: OECD\IEA.

International Energy Agency. (2003). Cool appliances—policy strategies for energy efficient homes. Paris: OECD / IED.

Jensen, L., Mulvad, L., Katan, S. H., & Sundahl, N.V. (2012). Researching motivational factors towards a sustainable electricity consumption. Paper presented at SMART 2012: The First International Conference on Smart Systems, Devices and Technologies (pp. 44–47).

Jones, M., & Alony, I. (2008). Blogs—the new source of data analysis. Issues in Informing Science and Information Technology, 5, 433–446.

Karlin, B. (2012). Public acceptance of smart meters: integrating psychology and practice. Proceedings of ACEEE 2012.

Kerrigan, D., Gamberini, L., Spagnolli, A., & Jacucci, J. (2011). Smart meters: a users’ view. Psychnology, 9, 55–72.

Kleijnen, M., de Ruyter, K., & Wetzels, M. (2004). Consumer adoption of wireless services: discovering the rules, while playing the game. Journal of Interactive Marketing, 18(2), 51–61.

Kranz, J., Gallenkamp, J., Picot, A. (2010). Power control to the people? Private consumers’ acceptance of smart meters. Proceedings of the 18th European Conference on Information Systems (ECIS), June, Pretoria, South Africa.

Krueger, J., & Clement, R. W. (1994). The truly false consensus effect: an ineradicable and egocentric bias in social perception. Journal of Personality and Social Psychology, 67, 596–610.

Lauri, M. A., & Lauri, J. (2005). Social representations of organ donors and non-donors. Journal of Community and Applied Social Psychology, 15, 108–119.

Leach, J. (2000). In M. Bauer & G. Gaskell (Eds.), Qualitative researching with text, image and sound (pp. 207–226). London: Sage.

Lima, M. L. (2005). Percepção de Riscos Ambientais. In L. Soczka (Ed.), Contextos Humanos e Psicologia Ambiental (pp. 203–245). Lisboa: Edições Calouste Gulbenkian.

Lima, M. L. (2006). Predictors of attitudes towards the construction of a waste incinerator: two case studies. Journal of Applied Social Psychology, 2(36), 441–466.

Lima, M. L., Barnett, J., & Vala, J. (2004). Risk perception and technological development at a societal level. Risk Analysis, 25(5), 1229–1239.

Lima, M. L., Lopes, D., & Garrido, M. (2009). Relatório final do Estudo de Adesão das Comunidades Locais ao Aproveitamento Hidro-eléctrico do Fridão [final report of the survey to the attitudes of the local communities to the project of Fridão dam]. Lisboa: Centro de Investigação e de Intervenção Social, ISCTE.

Lind, E. A., & Tyler, T. R. (1988). The social psychology of procedural justice. NY: Plenum Press.

Luo, X., Li, H., Zhang, J., & Shim, J. P. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: an empirical study of mobile banking services. Decision Support Systems, 49, 222–234.

Martiskainen, M., & Coburn, J. (2011). The role of information and communication technologies (ICTs) in household energy consumption—prospects for the UK. Energy Efficiency, 4(2), 209–221.

Moser, S., Bruppacher, S. E., & Mosler, H.-J. (2011). How people perceive and will cope with risks from the diffusion of ubiquitous information and communication technologies. Risk Analysis, 31(5), 832–846.

Pyrko, J., & Darby, S. (2011). Conditions of energy efficient behaviour—a comparative study between Sweden and the UK. Energy Efficiency, 4, 393–408.

Renn, O. (1998). Three decades of risk research: accomplishments and new challenges. Journal of Risk Research, 1(1), 49–71.

Sperber, D., & Wilson, D. (1981). Irony and the use-mention distinction. Radical pragmatics, 49, 295–318.

Starlicki, D. P., & Folger, R. (1997). Retaliation in the workplace: the roles of distributive, procedural, and interactional justice. Journal of Applied Psychology, 82(3), 434–443.

Stern, P. C. (2000). Toward a coherent theory of environmentally significant behavior. Journal of Social Issues, 56(3), 407–424.

Stern, S. M. (2011). Smart-grid: technology and the psychology of environmental behavior change. Chicago-Kent Law Review., 86, 139.

Stragier, J. (2010). Introducing smart grids in residential contexts: consumers’ perception of smart household appliances. 2010 I.E. Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply (CITRES)

Syme, G., Nancarrow, B., & McCreddin, J. (1999). Defining the components of fairness in the allocation of water to environmental and human uses. Journal of Environmental Management, 57(1), 51–70.

Tyler, T. R., & Lind, E. A. (1990). Intrinsic versus community-based justice models: when does group membership matter? Journal of Social Issues, 46, 83–94.

Tyler, T. R., & Smith, H. J. (1995). Social justice and social movements. Working paper series. UC Berkeley: Institute for research on Labor and Employment.

van Bavel, R., & Gaskell, G. (2004). Narrative and systemic modes of economic thinking. Culture and Psychology, 10(4), 417–439.

Venkatesh, V. (2000). Determinants of perceived ease of use: integrating control, intrinsic motivation and emotion into technology acceptance model. Information Systems Research, 11(4), 342–365.

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315.

Verbong, G. P. J., Beemsterboer, S., & Sengers, F. (2013). Smart grids or smart users? Involving users in developing a low carbon electricity economy. Energy Policy, 52, 117–125.

Wang, C.-C., Lo, S.-K., & Fang, W. (2008). Extending the technology acceptance model to mobile communication innovation: the existence of network externalities. Journal of Consumer Behaviour, 7, 101–110.

Zhang, T., & Nuttall, W. J. (2012). An agent-based simulation of smart metering technology adoption. International Journal of Agent Technologies and Systems (IJATS), 4(1), 17–38.

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Energy Efficiency

Tập 8

1149-1167

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