Moi University, Kenya
* Corresponding author
Moi University, Kenya
Moi University, Kenya

Article Main Content

Knowing the determinants of household utilization and changing behaviour is an important element in understanding the pathways towards clean, sustainable and modern household energy sources. This study, therefore, examines the drivers of household energy usage and choices in Western Kenya using structural equation modelling from 560 sampled households. The research was carried out in Western Kenya (Uasin Gishu and Bungoma counties) from a target household of 663,000. Data was collected using a structured questionnaire and were analyzed to find standard estimate (path coefficients), standard error, critical ratios and the level of significance using AMOS version 23. SEM analysis found that education level, income, residential status, peri urbanization, house size, house composition, age and gender of the household head were the determinants of household energy choices and changing behaviour among households both for cooking. On the other hand, SEM showed that household energy choices for lighting are significantly influenced by income level, family size, location, education level, and residential status. High income and more educated households residing in peri-urban were more likely to use cleaner cooking (LPG, electricity) while lesser households living in rural areas use firewood and agricultural residues for cooking. Rural households mostly adopt solar energy for domestic use because rural areas are isolated and detached from the power grid. Though income and education are the major factors, the research finds that numerous non-income factors similarly play a key role in determining household energy utilization and changing behaviour. This study offers the understanding of improving household energy planning and designing policy and interventions in Kenya and sub-Saharan African countries.

References

  1. Estiri H, Zagheni E. Age matters: Ageing and household energy demand in the United States. Energy Research & Social Science. 2019; 55: 62-70.
     Google Scholar
  2. Muller C, Yan H. Household fuel use in developing countries: Review of theory and evidence. Energy Economics. 2018; 70: 429-39.
     Google Scholar
  3. Bailis R, Ezzati M, Kammen DM. Mortality and greenhouse gas impacts of biomass and petroleum energy futures in Africa. Science. 2005; 308(5718): 98-103.
     Google Scholar
  4. Carvalho RL, Lindgren R, García-López N, Nyambane A, Nyberg G, Diaz-Chavez R, Boman C. Household air pollution mitigation with integrated biomass/cookstove strategies in Western Kenya. Energy Policy. 2019; 131: 168-86.
     Google Scholar
  5. Bar R, Reinhard J, Ehrensperger A, Kiteme B, Mkunda T, von Dach SW. The future of charcoal, firewood, and biogas in Kitui County and Kilimanjaro Region: Scenario development for policy support. Energy Policy. 2021; 150: 112067.
     Google Scholar
  6. Mukoya E. Strengthening the Legal and Institutional Framework for Air Pollution Control in Kenya. Ph.D. Thesis. University of Nairobi; 2019.
     Google Scholar
  7. Kimutai S, Kiprop A, Snelder D. Household energy utilization and changing behaviours: evidence from Western Kenya. 2019.
     Google Scholar
  8. Johnson M, Piedrahita R, Pillarisetti A, Shupler M, Menya D, Rossanese M, et al. Modeling approaches and performance for estimating personal exposure to household air pollution: A case study in Kenya. Indoor Air. 2021; 31(5): 1441-57.
     Google Scholar
  9. Choumert-Nkolo J, Motel PC, Le Roux L. Stacking up the ladder: A panel data analysis of Tanzanian household energy choices. World Development. 2019; 115: 222-35.
     Google Scholar
  10. Van der Kroon B, Brouwer R, Van Beukering PJ. The energy ladder: Theoretical myth or empirical truth? Results from a meta-analysis. Renewable and Sustainable Energy Reviews. 2013; 20: 504-13.
     Google Scholar
  11. Toole R. Energy Ladder: A Valid Model for Household Fuel Transitions. Journal of Tropical Medicine and International Health. 2015: 1-04.
     Google Scholar
  12. Dash M, Behera B, Rahut DB. Understanding the factors that influence household use of clean energy in the Similipal Tiger Reserve, India. Natural Resources Forum. 2018; 4281): 3-18.
     Google Scholar
  13. Andadari RK, Mulder P, Rietveld P. Energy poverty reduction by fuel switching. Impact evaluation of the LPG conversion program in Indonesia. Energy Policy. 2014; 66: 436-49.
     Google Scholar
  14. Zhu X, Yun X, Meng W, Xu H, Du W, Shen G, Cheng H, Ma J, Tao S. Stacked use and transition trends of rural household energy in mainland China. Environmental Science & Technology. 2018; 53(1): 521-9.
     Google Scholar
  15. Ali A, Mottaleb KA, Aryal JP. Wealth, education and cooking-fuel choices among rural households in Pakistan. Energy Strategy Reviews. 2019; 24: 236-43.
     Google Scholar
  16. Shankar AV, Quinn AK, Dickinson KL, Williams KN, Masera O, Charron D, et al. Everybody stacks: Lessons from household energy case studies to inform design principles for clean energy transitions. Energy Policy. 2020; 141: 111468.
     Google Scholar
  17. Baiyegunhi LJ, Hassan MB. Rural household fuel energy transition: evidence from Giwa LGA Kaduna State, Nigeria. Energy for Sustainable Development. 2014; 20: 30-5.
     Google Scholar
  18. Masera OR, Saatkamp BD, Kammen DM. From linear fuel switching to multiple cooking strategies: a critique and alternative to the energy ladder model. World Development. 2000; 28(12): 2083-103.
     Google Scholar
  19. Bisaga I, Parikh P. To climb or not to climb? Investigating energy use behaviour among Solar Home System adopters through energy ladder and social practice lens. Energy Research & Social Science. 2018; 44: 293-303.
     Google Scholar
  20. Ochieng CA, Zhang Y, Nyabwa JK, Otieno DI, Spillane C. Household perspectives on cookstove and fuel stacking: A qualitative study in urban and rural Kenya. Energy for Sustainable Development. 2020; 59: 151-9.
     Google Scholar
  21. Bailis R, Ghosh E, O’Connor M, Kwamboka E, Ran Y, Lambe F. Enhancing clean cooking options in peri-urban Kenya: a pilot study of advanced gasifier stove adoption. Environmental Research Letters. 2020; 15(8): 084017.
     Google Scholar
  22. Gitau KJ, Mutune J, Sundberg C, Mendum R, Njenga M. Factors influencing the adoption of biochar-producing gasifier cookstoves by households in rural Kenya. Energy for Sustainable Development. 2019; 52: 63-71.
     Google Scholar
  23. Baek YJ, Jung TY, Kang SJ. Analysis of Residential Lighting Fuel Choice in Kenya: Application of Multinomial Probability Models. Frontiers in Energy Research. 2020; 8: 70.
     Google Scholar
  24. Fairchild AJ, MacKinnon DP. A general model for testing mediation and moderation effects. Prevention Science. 2009; 10(2): 87-99.
     Google Scholar
  25. Toth-Király I, Morin AJ, Bőthe B, Orosz G, Rigó A. Investigating the multidimensionality of need fulfillment: A bifactor exploratory structural equation modeling representation. Structural Equation Modeling: A Multidisciplinary Journal. 2018; 25(2): 267-86.
     Google Scholar
  26. KNBS VI. Population by county and sub-county. Kenya National Bureau of Statistics. 2019.
     Google Scholar
  27. Kimutai SK, Talai SM. Household Energy Utilization Trends in Kenya: Effects of Peri Urbanization. European Journal of Energy Research. 2021; 1(2): 7-11.
     Google Scholar
  28. Bujang MA, Baharum N. A simplified guide to determination of sample size requirements for estimating the value of intraclass correlation coefficient: a review. Archives of Orofacial Science. 2017; 12(1).
     Google Scholar
  29. Muller D, Judd CM, Yzerbyt VY. When moderation is mediated and mediation is moderated. Journal of Personality and Social Psychology. 2005; 89(6): 852.
     Google Scholar
  30. Preacher KJ, Rucker DD, Hayes AF. Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research. 2007; 42(1): 185-227.
     Google Scholar
  31. Zhang MF, Dawson JF, Kline RB. Evaluating the use of covariance‐based structural equation modelling with reflective measurement in organizational and management research: A review and recommendations for best practice. British Journal of Management. 2021; 32(2): 257-72.
     Google Scholar
  32. Mohamed CW, Hui H, Binti NA, Jenatabadi HS. Family Food Security and Children’s Environment: A Comprehensive Analysis with Structural Equation Modeling. Sustainability. 2017; 9(7): 1-9.
     Google Scholar
  33. Smith TD, McMillan BF. A Primer of Model Fit Indices in Structural Equation Modeling.
     Google Scholar
  34. Schreiber JB, Nora A, Stage FK, Barlow EA, King J. Reporting structural equation modeling and confirmatory factor analysis results: A review. The Journal of Educational Research. 2006; 99(6): 323-38.
     Google Scholar
  35. Zhang M, Hong L, Zhang T, Lin Y, Zheng S, Zhou X, et al. Illness perceptions and stress: mediators between disease severity and psychological well-being and quality of life among patients with Crohn’s disease. Patient Preference and Adherence. 2016; 10: 2387.
     Google Scholar
  36. Bentler PM, Bonett DG. Significance tests and goodness of fit in the analysis of covariance structures. Psychological bulletin. 1980; 88 (3): 588.
     Google Scholar
  37. Thompson B. Exploratory and confirmatory factor analysis. American Psychological Association. 2004.
     Google Scholar
  38. Byrne BM. Structural equation modeling with EQS and EQS/Windows: Basic concepts, applications, and programming. Sage; 1994 Feb 28.
     Google Scholar
  39. Byrne BM. Structural equation modeling with Mplus: Basic concepts, applications, and programming. Routledge. 2013.
     Google Scholar
  40. Kline RB. Principles and practice of structural equation modeling 2nd ed. New York: Guilford. 2005; 3.
     Google Scholar
  41. Cohen J. The effect size. Statistical power analysis for the behavioral Sciences. 1988: 77-83.
     Google Scholar
  42. Gholami Y, Khalaji N. Evaluate the impact of socio-economic consumerism citizens (case study: Kashan). 2017: 119-140.
     Google Scholar
  43. Sarkodie SA, Adom PK. Determinants of energy consumption in Kenya: a NIPALS approach. Energy. 2018; 159: 696-705.
     Google Scholar
  44. Azam M, Khan AQ, Zafeiriou E, Arabatzis G. Socio-economic determinants of energy consumption: An empirical survey for Greece. Renewable and Sustainable Energy Reviews. 2016; 57: 1556-67.
     Google Scholar
  45. Semenya K, Machete F. Factors that influence firewood use among electrified Bapedi households of Senwabarwana Villages, South Africa. African Journal of Science, Technology, Innovation and Development. 2019; 11(6): 719-29.
     Google Scholar
  46. Acharya B, Marhold K. Determinants of household energy use and fuel switching behavior in Nepal. Energy. 2019; 169: 1132-8.
     Google Scholar
  47. Ahmad S, de Oliveira JA. Fuel switching in slum and non-slum households in urban India. Journal of Cleaner Production. 2015; 94: 130-6.
     Google Scholar
  48. Hou B, Liao H, Huang J. Household cooking fuel choice and economic poverty: evidence from a nationwide survey in China. Energy and Buildings. 2018; 166: 319-29.
     Google Scholar
  49. Gatama MN. Factors influencing household energy consumption: the case of biomass fuels in Kikuyu District of Kiambu County, Kenya Ph.D. Thesis. University Of Nairobi. 2014.
     Google Scholar
  50. Arnold M, Persson R. Reassessing the fuelwood situation in developing countries. The International Forestry Review. 2003; 5(4): 379-83.
     Google Scholar
  51. Mwampamba TH. Has the woodfuel crisis returned? Urban charcoal consumption in Tanzania and its implications to present and future forest availability. Energy Policy. 2007; 35(8): 4221-34.
     Google Scholar
  52. Wang J, Dong K. What drives environmental degradation? Evidence from 14 Sub-Saharan African countries. Science of the Total Environment. 2019; 656: 165-73.
     Google Scholar
  53. Hanif I. Impact of economic growth, nonrenewable and renewable energy consumption, and urbanization on carbon emissions in Sub-Saharan Africa. Environmental Science and Pollution Research. 2018; 25(15): 15057-67.
     Google Scholar
  54. Farsi M, Filippini M, Pachauri S. Fuel choices in urban Indian households. Environment and Development Economics. 2007; 12(6): 757-74.
     Google Scholar
  55. Ozcan KM, Gulay E, Ucdogruk S. Economic and demographic determinants of household energy use in Turkey. Energy Policy. 2013; 60: 550-7.
     Google Scholar
  56. Chun-sheng Z, Shu-Wen NI, Xin Z. Effects of household energy consumption on environment and its influence factors in rural and urban areas. Energy Procedia. 2012; 14: 805-11.
     Google Scholar
  57. Behera B, Ali A. Household energy choice and consumption intensity: Empirical evidence from Bhutan. Renewable and Sustainable Energy Reviews. 2016; 53: 993-1009.
     Google Scholar
  58. Bisu DY, Kuhe A, Iortyer HA. Urban household cooking energy choice: an example of Bauchi metropolis, Nigeria. Energy, Sustainability and Society. 2016; 6(1): 1-2.
     Google Scholar
  59. Abebaw D. Household determinants of fuelwood choice in urban Ethiopia: a case study of Jimma Town. The Journal of Developing Areas. 2007: 117-26.
     Google Scholar
  60. Sharma A, Parikh J, Singh C. Transition to LPG for cooking: A case study from two states of India. Energy for Sustainable Development. 2019; 51: 63-72.
     Google Scholar
  61. Ouedraogo B. Household energy preferences for cooking in urban Ouagadougou, Burkina Faso. Energy Policy. 2006; 34(18): 3787-95.
     Google Scholar
  62. Link CF, Axinn WG, Ghimire DJ. Household energy consumption: Community context and the fuelwood transition. Social Science Research. 2012; 41(3): 598-611.
     Google Scholar
  63. Heltberg R. Factors determining household fuel choice in Guatemala. Environment and Development Economics. 2005; 10(3): 337-61.
     Google Scholar
  64. Israel D. Fuel choice in developing countries: evidence from Bolivia. Economic Development and Cultural Change. 2002; 50(4): 865-90.
     Google Scholar
  65. Peng W, Hisham Z, Pan J. Household level fuel switching in rural Hubei. Energy for Sustainable Development. 2010; 14(3): 238-44.
     Google Scholar
  66. Ifegbesan AP, Rampedi IT, Annegarn HJ. Nigerian households' cooking energy use, determinants of choice, and some implications for human health and environmental sustainability. Habitat International. 2016; 55: 17-24.
     Google Scholar
  67. Rao MN, Reddy BS. Variations in energy use by Indian households: an analysis of micro level data. Energy. 2007; 32(2): 143-53.
     Google Scholar
  68. Liu Z, Wang M, Xiong Q, Liu C. Does centralized residence promote the use of cleaner cooking fuels? Evidence from rural China. Energy Economics. 2020; 91: 104895.
     Google Scholar
  69. Kemmler A. Factors influencing household access to electricity in India. Energy for Sustainable Development. 2007; 11(4): 13-20.
     Google Scholar
  70. Pandey VL, Chaubal A. Comprehending household cooking energy choice in rural India. Biomass and Bioenergy. 2011; 35(11): 4724-31.
     Google Scholar
  71. Miah MD, Kabir RR, Koike M, Akther S, Shin MY. Rural household energy consumption pattern in the disregarded villages of Bangladesh. Energy Policy. 2010; 38(2): 997-1003.
     Google Scholar
  72. Reddy BS. A multilogit model for fuel shifts in the domestic sector. Energy. 1995; 20(9): 929-36.
     Google Scholar
  73. Behera B, Ali A. Household energy choice and consumption intensity: Empirical evidence from Bhutan. Renewable and Sustainable Energy Reviews. 2016; 53: 993-1009.
     Google Scholar
  74. Edwards JH, Langpap C. Startup costs and the decision to switch from firewood to gas fuel. Land Economics. 2005; 81(4): 570-86.
     Google Scholar
  75. Rahut DB, Mottaleb KA, Ali A, Aryal J. The use and determinants of solar energy by Sub-Saharan African households. International Journal of Sustainable Energy. 2018; 37(8): 718-35.
     Google Scholar
  76. Behera B, Ali A. Factors determining household use of clean and renewable energy sources for lighting in Sub-Saharan Africa. Renewable and Sustainable Energy Reviews. 2017; 72: 661-72.
     Google Scholar
  77. Chen PY, Chen ST, Hsu CS, Chen CC. Modeling the global relationships among economic growth, energy consumption and CO2 emissions. Renewable and Sustainable Energy Reviews. 2016; 65: 420-31.
     Google Scholar
  78. Lay J, Ondraczek J, Stoever J. Renewables in the energy transition: Evidence on solar home systems and lighting fuel choice in Kenya. Energy Economics. 2013; 40: 350-9.
     Google Scholar
  79. Danlami AH, Applanaidu SD, Islam R. Movement towards the adoption of non-traditional household lighting fuel energy in developing areas. Biofuels. 2019; 10(5): 623-33.
     Google Scholar
  80. Buba A, Abdu M, Adamu I, Jibir A, Usman YI. Socio—economic determinants of households’ fuel consumption in Nigeria. International Journal of Research-Granthaalayah. 2017; 5(10): 348-60.
     Google Scholar