Drivers for, and barriers to solar energy use by manufacturing Micro Small and Medium Enterprises (MSMEs) in Tanzania
Abstract
Choice of solar energy by manufacturing Micro, Small and Medium Enterprises (MSME’s) has been associated with manufacturing sustainability. In this study, the Structural Equation Modeling (SEM) technique was employed to establish drivers for, and barriers to solar energy use by manufacturing MSME’s in selected districts in Morogoro region. The SEM results revealed three main drivers for manufacturing MSME’s use of solar energy for different purposes like manufacturing MSME’s intention to use solar energy, risk perception on solar energy use, and self-effectiveness perception. Also, the results indicated that there are several factors that hinder manufacturing MSME’s use of solar energy for different operations including the environmental concern (i.e., staff/employers’ concern about air pollution resulted from energy use, and staff/employers’ concern about climate change); solar energy awareness (i.e., experience in previous use of solar energy, and understanding of different types of solar PV which can be used at industry level), and lastly, solar energy generation cost (i.e., the generation of solar energy may cause additional cost, and solar energy requires high initial investment cost). Hence, the results of this study can be used by energy policymaking instruments to make informed decisions for renewable energy investment in the country’s manufacturing sector for manufacturing sustainability.
Received: 04 April 2023
Accepted: 06 June 2023
Published: 20 June 2023
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Ali, K. A., & Ahmad, M. I. (2020). Issues , Impacts , and Mitigations of Carbon Dioxide Emissions in the Building Sector.
Chen, L., Savalei, V., & Rhemtulla, M. (2020). Two-stage maximum likelihood approach for item-level missing data in regression. Behavior Research Methods, 52(6), 2306–2323. https://doi.org/10.3758/s13428-020-01355-x
Connelly, L. M. (2016). Cross-Sectional Survey Research. 25(5), 2016.
Council, O. F. T. H. E. (2009). L 140/16. 16–62.
Deng, Z., & Davis, S. J. (2022). COmmEnT Monitoring global carbon emissions. 3(April), 217–219. https://doi.org/10.1038/s43017-022-00285-w
Elasu, J., Ntayi, J. M., Adaramola, M. S., & Buyinza, F. (2023). Drivers of household transition to clean energy fuels: A systematic review of evidence. Renewable and Sustainable Energy Transition, 3(January), 100047. https://doi.org/10.1016/j.rset.2023.100047
Eleftheriadis, I. M., & Anagnostopoulou, E. G. (2015). Identifying barriers in the diffusion of renewable energy sources. Energy Policy, 80, 153–164. https://doi.org/10.1016/j.enpol.2015.01.039
Hasan, A. S. M. M., Kabir, A., Hoq, T., Maria, T., Hasan, A. S. M. M., Kabir, A., Hoq, T., & Maria, T. (2022). Drivers and barriers to the implementation of biogas technologies in Bangladesh Drivers and barriers to the implementation of biogas technologies. Biofuels, 13(5), 643–655. https://doi.org/10.1080/17597269.2020.1841362
Höhne, N., de Villafranca, M. J., Nascimento, L., Kuramochi, T., Hans, F., Luna, L., Fekete, H., & Warnecke, C. (2019). A possible 2050 climate target for the EU. August, 1–17. https://newclimate.org/wp-content/uploads/2019/09/EU2050_Target_Adequacy.pdf%0Ahttp://newclimate.org/publications/%0Ahttps://newclimate.org/2019/09/23/a-possible-2050-climate-target-for-the-eu/%0Ahttps://newclimate.org/wp-content/uploads/2019/09/EU2050_Ta
Lee, C., Peters, O., & Enders, C. (2002). modelling software, traditional linear model analyses (eg regression, ANOVA) can be performed with these packages. MAXIMUM LIKELIHOOD MISSING DATA ESTIMATION. 11, 81–95.
Lowe, R. J., & Drummond, P. (2022). Solar, wind and logistic substitution in global energy supply to 2050 – Barriers and implications. Renewable and Sustainable Energy Reviews, 153(September 2021), 111720. https://doi.org/10.1016/j.rser.2021.111720
Lyakurwa, F. S. (2022). Achieving Sustainability in Manufacturing Micro , Small and Medium Enterprises ( MSMEs ’) in Tanzania Through Adoption of Solar Energy. 3(2), 77–89.
Lyakurwa, F. S., & Mkuna, E. (2018). Political-institutional barriers to energy access and efficiency in Tanzania : a case study of Mvomero District. 31(1), 173–186.
Ren, L., Zhou, S., Peng, T., & Ou, X. (2021). A review of CO 2 emissions reduction technologies and low-carbon development in the iron and steel industry focusing on China. Renewable and Sustainable Energy Reviews, 143(October 2020), 110846. https://doi.org/10.1016/j.rser.2021.110846
Republic, T. U., Bureau, N., Ministry, S., & June, F. (2013). Tanzania in Figures 2012.
Sahoo, M. (2019). Structural Equation Modeling: Threshold Criteria for Assessing Model Fit. Methodological Issues in Management Research: Advances, Challenges, and the Way Ahead, 269–276. https://doi.org/10.1108/978-1-78973-973-220191016
Saleh, C., Immawan, T., Hassan, A. B., & Zakka, M. N. (2019). Profit Optimization Through the Application of Theory of Constraints (TOC): A Case Study in Printing Company. IOP Conference Series: Materials Science and Engineering, 530(1). https://doi.org/10.1088/1757-899X/530/1/012045
Schoeneberger, C. A., McMillan, C. A., Kurup, P., Akar, S., Margolis, R., & Masanet, E. (2020). Solar for industrial process heat: A review of technologies, analysis approaches, and potential applications in the United States. Energy, 206, 118083. https://doi.org/10.1016/j.energy.2020.118083
Seetharaman, Moorthy, K., Patwa, N., Saravanan, & Gupta, Y. (2019). Breaking barriers in deployment of renewable energy. Heliyon, 5(1), e01166. https://doi.org/10.1016/j.heliyon.2019.e01166
Shi, D., Lee, T., & Maydeu-Olivares, A. (2019). Understanding the Model Size Effect on SEM Fit Indices. Educational and Psychological Measurement, 79(2), 310–334. https://doi.org/10.1177/0013164418783530
Sjølie, H. K. (2012). Reducing greenhouse gas emissions from households and industry by the use of charcoal from sawmill residues in Tanzania. Journal of Cleaner Production, 27, 109–117. https://doi.org/10.1016/j.jclepro.2012.01.008
Sonter, L. J., & Kemp, S. (2021). Connecting the UNESCO Sustainable Development Goals with Australian Early Childhood Education Policy to Transform Practice. International Journal of Early Childhood Environmental Education, 9(1), 11.
https://en.unesco.org/sustainabledevelopmentgoals
Tanzania, U. R. of. (2010). National Strategy for Growth and Reduction of Poverty II: NSGRP II. Ministry of Finance and Economic Affairs Tanzania, July, 168. http://www.acdi-cida.gc.ca/INET/IMAGES.NSF/vLUImages/Tanzania/$file/NATIONAL-STRATEGY-FOR-GROWTH-AND-REDUCTION-OF-POVERTY-TANZANIA.PDF
Tollefson, J. (2021). IPCC climate report: Earth is warmer than it’s been in 125,000 years. Nature, 596(7871), 171–172. https://doi.org/10.1038/d41586-021-02179-1
URT. (2000). The Tanzania Development Vision 2025. In Ministry of Planning (pp. 1–20). http://www.tzonline.org/pdf/theTanzaniadevelopmentvision.pdf%0Ahttp://www.mof.go.tz/mofdocs/overarch/Vision2025.pdf
URT. (2021). National Five Year Development Plan 2021/22-2025/26: Realising Competitiveness and Industrialisation for Human Development. The United Republic of Tanzania, June, 321.
Van der Stede, W. A. (2014). A manipulationist view of causality in cross-sectional survey research. Accounting, Organizations and Society, 39(7), 567–574. https://doi.org/10.1016/j.aos.2013.12.001
Zulu, S., Zulu, E., & Chabala, M. (2022). Factors influencing households ’ intention to adopt solar energy solutions in Zambia : insights from the theory of planned behaviour. 11(4), 951–971. https://doi.org/10.1108/SASBE-01-2021-0008
DOI: http://dx.doi.org/10.21622/resd.2023.09.1.021
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Copyright (c) 2023 Felichesmi S. Lyakurwa
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Renewable Energy and Sustainable Development
E-ISSN: 2356-8569
P-ISSN: 2356-8518
Published by:
Academy Publishing Center (APC)
Arab Academy for Science, Technology and Maritime Transport (AASTMT)
Alexandria, Egypt