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Regression Model Predicting Electrical Energy Management Practices among Residents in Niger State, Nigeria

Tswanya Moses

Abstract


Abstract

The study predicted electrical energy management practices among residents, using regression model. Three variables used were (Income levels, Age groups and Educational levels) of electrical energy users. The study adopted a cross sectional survey research design. The population of the study was made up of 191,416 heads of households in residential buildings connected to the distribution network in 25 Local Governments of Niger State. The sample for the study consisted of 1,290 heads of households in residential buildings drawn through multistage sampling techniques. The instrument used for data collection was a structured questionnaire. Correlation and multiple regression analysis were used to analyzed hypothesis which determined the no relationship at (P ˂ .05) level of significance on the practices of residents on electrical energy management in residential buildings in Niger State and to show the variable that has effect and the degree of the effect on the electrical energy management practices. The model developed is   this shows that person income level, age group and educational level were significant in predicting ones practices on electrical energy management with significance values of 0.02, 0.00 and 0.00 less than the  of P ˂ .05. Furthermore, age groups have a negative impact on electrical energy management practices in contrast to the income levels and educational qualifications. This is indicated by the values of their coefficient of +0.07, -0.062 and 0.097 respectively. The model significantly predicts electrical energy management practices. The conclusion is strengthen by the significant value of 0.00 less than the  of P ˂ 0.05.

 

KEY WORDS: Model, Predicting, Electrical Energy, Management, Practices and Residents

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References


Abrahamse, W., & Steg, L. (2009). How do socio-demographic and psychological factors relate to households' direct and indirect energy use and savings? Journal of Economic Psychology, 30 (1), 711-720.

Abrahamse, W., & Steg, L. (2011). Factors related to household energy use and intention reduces it: The role of psychological and socio-demographic variables. Human Ecology Review, 18 (1), 30 – 40.

Ajzen, I. (1991). The theory of planned behavior: Organizational Behavior and Human Decision Processes, 50 (1), 179-211.

Bandura, A. (1986). Social foundation of thought and action. New Jersey: Prentice hall.

Becker, L., & Seligman, C. (1981). Welcome to the energy crisis. Journal of Social Issues, 37 (2), 1-7.

Capehart, B. L., Turner, W. C., & Kennedy, W. J. (2005). Guide to energy management. New York: Fairmont Press.

Dincer, I., & Midilli, A. (2007). Energy conservation. In B. L. Capehary (ed) Encyclopaedia of energy engineering and technology. London :Sage Publication.

Eluwa, S. E., & Siong, H. C. (2013). The impact of psychological and socio-economic variables on household energy conservation: a case study of Ibadan city, Nigeria. Journal of Earth Sciences, 2 (3), 10-18.

Hirst, E. & Goeltz, G. (1982). Residential energy conservation actions: Analysis of disaggregated data. Energy Systems and Policy, 6 (1), 135-150.

Kano, C. (2013). Behavioral change for energy conservation: Case study of post- Fukushimaexperience in Japan. Master thesis in Sustainable Development at Uppsala University, No. 121, 45, 30 ECTS/hp. Retrieved on May 20, 2014 from http://uu.diva-portal.org

Kim, M. S., & Hunter, J. E. (1993). Relationships among attitudes, behavioral intentions, and behavior: A meta-analysis of past research. Communication Research, 20 (3), 331–364.

Mohon, H. P., Kiss, M. G., & Leimer, H. J. (1983). Efficient energy management methods for improved commercial and industrial productivity. Englewoods Cliffs.: Prentice-Hall.

Mutua, J., & Kimuyu, P. (2015). Household energy conservation in Kenya estimating the drivers and possible savings. Retrieved on December 12, 2015 from http://www.rff.org/files/sharepoint

Okubo, S., & Tsuchiya, T. (2009). Public opinions for energy and environmental issues in Japan -results of national survey in 2008 and comparison with the past surveys socio-economic Research Center. Retrieved on June 23, 2013 from http://criepi.denkenor.jp/jp/kenkikaku

Poortinga, W., Steg, L., Vlek, C., & Wiersma, G. (2003). Household preferences for energy-saving measures: A conjoint analysis. Journal of Economic Psychology, 24 (1), 49–64.

Saba, T. M., Usman, G. A., Adamu, M. J., & Daniel, B. C. (2018) Techniques of enhancing electrical energy Management in Residential buildings, small and Medium enterprises in Niger State, Nigeria. International Journal of Industrial Technology, Engineering, Science and Education 1 (1) 104-112

Sanyaolu, A. (2013 May, 27). Why Nigerians should imbibe energy saving culture, Business Week, P 37.

Secord, P. & Backman, C. (1974). Social psychology. New York: McGraw-Hill.

Ting, L. S., Mohammed, A. H., Wai, C. W. & Alias, B. (2010). The energy knowledge and conservation behaviour among community in University. International University Social Responsibility Conference and Exhibition. K. Lumpur. Retrieved on January 13, 2014 from www.fksg.utm.my




DOI: https://doi.org/10.37628/ijaem.v6i1.1314

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