DOI: https://doi.org/10.14710/ijred.2021.32311

Public Participation of Renewable Energy (PPRED) Model in Malaysia: An Instrument Development

1Faculty of Business Economics and Social Development, Universiti Malaysia Terengganu, Malaysia

2Faculty of Science and Technology, Universiti Sains Islam Malaysia, Malaysia

3Institute of Energy Policy and Research, Universiti Tenaga Nasional, Malaysia

Received: 20 Aug 2020; Revised: 9 Oct 2020; Accepted: 30 Oct 2020; Available online: 4 Nov 2020; Published: 1 Feb 2021.
Editor(s): H Hadiyanto
Open Access Copyright (c) 2021 The authors. Published by Centre of Biomass and Renewable Energy (CBIORE)
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

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Abstract
Lack of an established measuring instrument for public participation towards renewable energy (RE) development has become a crucial concern for the researchers. Therefore, this research aims to develop and validate the instruments that measure public participation towards renewable energy development (PPRED) in Malaysia. This study incorporates degree of knowledge on RE (KRE), environmental concern (EC), public awareness on RE (ARE), attitude towards RE usage (AURE), and willingness to adopt RE technology (WTA) in the PPRED model, with an aim to predict public willingness to pay (WTP) for energy generated from RE sources. Using data of 172 usable responses, this study conducts an exploratory factor analysis (EFA) to analyse the factor structures. In addition to this, using data from 154 usable responses from a second sample frame, this study also conducts confirmatory factor analysis (CFA) to examine the unidimensionality of the measurement model. Correlations are used to measure discriminant and convergent validation of the items whereas Cronbach’s Alpha is used to measure internal consistency among different items. Specifically, EFA is used for variable extraction and CFA is used to test dimensionality, validity, and reliability of the PPRED model. The results proved validation of the PPRED model, indicating that all instruments included are reliable and valid to be used in the research. This study is also pertinent to initiate targeted campaigns and public education policies to improve awareness among Malaysians relating to renewable energy development

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Keywords: Confirmatory Factor Analysis; Exploratory Factor Analysis; Renewable Energy; Willingness to pay

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Section: Original Research Article
Language : EN
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  1. Abdul Wahab, H., Saiti, B., Rosly, S. A., & Masih, A. M. M. (2017). Risk-taking behavior and capital adequacy in a mixed banking system: new evidence from Malaysia using dynamic OLS and two-step dynamic system GMM estimators. Emerging Markets Finance and Trade, 53(1), 180-198; doi: 10.1080/1540496X.2016.1162151
  2. Abdullah, W. S. W., Osman, M., Ab Kadir, M. Z. A., & Verayiah, R. (2019). The potential and status of renewable energy development in Malaysia. Energies, 12(12), 2437; doi: 10.3390/en12122437
  3. Abdullah, W. M. Z., Zainudin, W. N. R., & Ishak, W. W. (2018)a. A Proposed Theoretical Model to Improve Public Participation Towards Renewable Energy (RE) Development in Malaysia. Advanced Science Letters, 24(11), 8922-8925; doi: 10.1166/asl.2018.12376
  4. Abdullah, W. M. Z., Zainudin, W. N. R., & Ishak, W. W. (2018)b. The Scale for Assessment of Public Participation Towards Renewable Energy (RE) Development in Malaysia: An Exploratory Factor Analysis (EFA). Advanced Science Letters, 24(12), 9384-9388; doi: 10.1166/asl.2018.12280
  5. Abdullah, W.M.Z, Zainuddin, W.N.R, Ishak, W.W.M. (2018)c. “The Scale Validation of Public Participation of Renewable Energy (RE) Development in Malaysia: An Exploratory Factor Analysis (EFA),” International Journal of Recent Technology and Engineering (IJRTE), ISSN: 2277-3878, Volume-7 Issue-4S2
  6. Abdullah, W. M. Z., Zainudin, W. N. R., & Ramli, N. A. (2018)a. A Proposed Model to Determine Public Acceptance on Willingness to Pay Maximum Demand (MD) Charge in Malaysia. Advanced Science Letters, 24(11), 8917-8921; doi: 10.1166/asl.2018.12375
  7. Abdullah, W. M. Z., Zainudin, W. N. R., & Ramli, N. A. (2018)b. An Exploratory Factor Analysis (EFA) for Developing and Validating a Scale of Public Acceptance on Willingness to Pay (PAWP) Maximum Demand (MD) Charge in Malaysia. Advanced Science Letters, 24(12), 9379-9383; doi: 10.1166/asl.2018.12279
  8. Adebayo, T. S., Awosusi, A. A., & Adeshola, I. (2020). Determinants of CO 2 Emissions in Emerging Markets: An Empirical Evidence from MINT Economies. International Journal of Renewable Energy Development, 9(3); doi: 10.14710/ijred.2020.31321
  9. Ahmad, S., Ab Kadir, M. Z. A., & Shafie, S. (2011). Current perspective of the renewable energy development in Malaysia. Renewable and sustainable energy reviews, 15(2), 897-904
  10. Ahmad, S., & Tahar, R. M. (2014). Selection of renewable energy sources for sustainable development of electricity generation system using analytic hierarchy process: A case of Malaysia. Renewable energy, 63, 458-466; doi: 10.1016/j.renene.2013.10.001
  11. Aini, M. S., & Goh Mang Ling, M. (2013). Factors Affecting the Willingness to Pay for Renewable Energy amongst Eastern Malaysian Households: A Case Study. Pertanika Journal of Social Sciences & Humanities, 21(1)
  12. Alam, S. S., Nor, N. F. M., Ahmad, M., & Hashim, N. H. N. (2016). A survey on renewable energy development in Malaysia: Current status, problems and prospects. Environmental and Climate Technologies, 17(1), 5-17; doi: 10.1515/rtuect-2016-0002
  13. Al-Mulali, U., Fereidouni, H. G., Lee, J. Y., & Sab, C. N. B. C. (2013). Exploring the relationship between urbanization, energy consumption, and CO2 emission in MENA countries. Renewable and Sustainable Energy Reviews, 23, 107-112; doi: 10.1016/j.rser.2013.02.041
  14. Ashnani, M. H. M., Johari, A., Hashim, H., & Hasani, E. (2014). A source of renewable energy in Malaysia, why biodiesel? Renewable and Sustainable Energy Reviews, 35, 244-257; doi: 10.1016/j.rser.2014.04.001
  15. Awang, Z. (2014) A handbook on SEM for academicians and practitioners: the step by step practical guides for the beginners. Bandar Baru Bangi, MPWS Rich Resources
  16. 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 & Marketing, 17(6), 449-468; doi: 10.1002/(SICI)1520-6793(200006)17:6<449::AID-MAR2>3.0.CO;2-8
  17. Bartlett, M. S. (1950). Tests of significance in factor analysis. British journal of psychology. 1950;3 (Part II):77-85
  18. Batel, S., Devine-Wright, P., & Tangeland, T. (2013). Social acceptance of low carbon energy and associated infrastructures: A critical discussion. Energy Policy, 58, 1-5; doi: 10.1016/j.enpol.2013.03.018
  19. Biswas, A., & Roy, M. (2015). Green products: an exploratory study on the consumer behaviour in emerging economies of the East. Journal of Cleaner Production, 87, 463-468; doi: 10.1016/j.jclepro.2014.09.075
  20. Biswas, A., & Roy, M. (2016). A study of consumers’ willingness to pay for green products. Journal of Advanced Management Science, 4(3); doi: 10.12720/joams.4.3.211-215
  21. Brown, T. A. (2015) Confirmatory factor analysis for applied research. Guilford publications
  22. Cattell, R. B. (1966). The scree test for the number of factors. Multivariate behavioral research, 1(2), 245-276
  23. Chua, S. C., Oh, T. H., & Goh, W. W. (2011). Feed-in tariff outlook in Malaysia. Renewable and Sustainable Energy Reviews, 15(1), 705-712; doi: 10.1016/j.rser.2010.09.009
  24. Coakes, S., Steed, L., & Ong, C. (2010) SPSS: analysis without anguish: version 17 for Windows Qld. John Wiley & Sons Australia Ltd
  25. Conte, M. N., & Jacobsen, G. D. (2016). Explaining demand for green electricity using data from all US utilities. Energy Economics, 60, 122-130; doi: 10.1016/j.eneco.2016.09.001
  26. COP15. (2009) “The Fifteen Conference of Parties.” United Nations Climate Change, Copenhagen
  27. Curry, T. E. (2004) Public awareness of carbon capture and storage: a survey of attitudes toward climate change mitigation (Doctoral dissertation, Massachusetts Institute of Technology)
  28. Daut, I., Irwanto, M., Irwan, Y. M., Gomesh, N., & Rosnazri, N. A. (2011, June). Potential of solar radiation and wind speed for photovoltaic and wind power hybrid generation in Perlis, Northern Malaysia. In 2011 5th International Power Engineering and Optimization Conference (pp. 148-153). IEEE; doi: 10.1109/PEOCO.2011.5970439
  29. Devine-Wright, P. (2007). Reconsidering public attitudes and public acceptance of renewable energy technologies: a critical review. School of Environment and Development, University of Manchester, Oxford Road, Manchester
  30. Duzan, H., & Shariff, N. S. B. M. (2015). Ridge regression for solving the multicollinearity problem: review of methods and models. JApSc, 15(3),392 404; doi: 10.3923/jas.2015.392.404
  31. Economic Planning Unit (EPU)( 2015) “Malaysia Well- Being Report.” Kuala Lumpur, Malaysia
  32. Faiers, A., & Neame, C. (2006). Consumer attitudes towards domestic solar power systems. Energy policy, 34(14), 1797-1806; doi: 10.1016/j.enpol.2005.01.001
  33. Field, A. (2013) Discovering statistics using IBM SPSS statistics. SAGE
  34. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50; doi: 10.1177/002224378101800104
  35. Gorsuch, R. L. (1983) Factor analysis Lawrence Erlbaum Associates. Hillsdale, NJ
  36. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010) Multivariate data analysis. 7th ed. Englewood Cliffs, NJ: Prentice Hall
  37. Hair, J. F., Anderson, R. E., Tatham, R. L., & William, C. (1995) Black: Multivariate data analysis with readings. 4. Auflage, Englewood Cliffs
  38. Henson, R. K., & Roberts, J. K. (2006). Use of exploratory factor analysis in published research: Common errors and some comment on improved practice. Educational and Psychological measurement, 66(3), 393-416; doi: 10.1177/0013164405282485
  39. Herbes, C., & Ramme, I. (2014). Online marketing of green electricity in Germany—A content analysis of providers’ websites. Energy Policy, 66, 257-266; doi: 10.1016/j.enpol.2013.10.083
  40. Intergovernmental Panel on Climate Change (IPCC) (2011). Summary for Policymakers. In: IPCC Special Report on Renewable Energy Sources and Climate Change Mitigation, Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA
  41. Irfan, M., Zhao, Z. Y., Li, H., & Rehman, A. (2020). The influence of consumers’ intention factors on willingness to pay for renewable energy: a structural equation modeling approach. Environmental Science and Pollution Research, 1-15; doi: 10.1007/s11356-020-08592-9
  42. Ismail, S., & Mohd Mokhtar, S. S. (2016). Moderating role of perceived benefit on the relationship between attitude and actual purchase. International Review of Management and Marketing, 6(S7), 17-21
  43. Ismail, S., & Mokhtar, S. S. M. (2016). Linking attitude to actual purchase of herbal product in Malaysia: The moderating role of perceived risk. Journal of Asian Business Strategy, 6(2), 22; doi: 10.18488/journal.1006/2016.6.2/1006.2.22.30
  44. Jacobs, D. (2010). Assessment of the Proposed Malaysian Feed-in Tariff in Comparison with International Best Practise. Environmental Policy Research Centre, Distinguished Visitor under the Brain Gain Malaysia program (Ministry of Science Technology and Innovation), Hosted by the Institute for Energy Policy and Research, IEPRe(UNITEN), 3-20
  45. Kaiser, H. F. (1970). A second generation little jiffy. Psychometrika, 35(4), 401-415
  46. Kaiser, H. F. (1960). The application of electronic computers to factor analysis. Educational and psychological measurement, 20(1), 141-151; doi: 10.1177/001316446002000116
  47. Kardooni, R., Yusoff, S. B., & Kari, F. B. (2016). Renewable energy technology acceptance in Peninsular Malaysia. Energy policy, 88, 1-10; doi: 10.1016/j.enpol.2015.10.005
  48. Lim, X. L., & Lam, W. H. (2014). Public acceptance of marine renewable energy in Malaysia. Energy Policy, 65, 16-26; doi: 10.1016/j.enpol.2013.09.053
  49. Makki, A. A., & Mosly, I. (2020). Factors Affecting Public Willingness to Adopt Renewable Energy Technologies: An Exploratory Analysis. Sustainability, 12(3), 845; doi: 10.3390/su12030845
  50. Malaysia Energy Information Hub (2020) Energy Intensity per capita. Energy Commission. Retrieved from; https://meih.st.gov.my/statistics on 30 September 2020
  51. Malaysia Energy Statistics handbook. (2019) Malaysia Energy Statistics handbook. Energy Commission. Retrieved from; https://meih.st.gov.my/documents/10620/bcce78a2-5d54-49ae-b0dc-549dcacf93ae on 30 September 2020
  52. Mannhart, M. M. T. (2014). Analysis of the Power System of Malaysia. Energy Economics and Application Engineering. Munich: Technical University of Munich
  53. Mekhilef, S., Saidur, R., Safari, A., & Mustaffa, W. E. S. B. (2011). Biomass energy in Malaysia: current state and prospects. Renewable and Sustainable Energy Reviews, 15(7), 3360-3370; doi: 10.1016/j.rser.2011.04.016
  54. Morgil, I., Secken, N., Yucel, A. S., Ozyalcin Oskay, O., Yavuz, S., & Ural, E. (2006). Developing a Renewable Energy Awareness Scale for Pre-Service Chemistry Teachers. Online Submission, 7(1), 63-74;
  55. Mozumder, P., Vásquez, W. F., & Marathe, A. (2011). Consumers' preference for renewable energy in the southwest USA. Energy economics, 33(6), 1119-1126; doi: 10.1016/j.eneco.2011.08.003
  56. Mustapa, S. I., Peng, L. Y., & Hashim, A. H. (2010, June). Issues and challenges of renewable energy development: A Malaysian experience. In Proceedings of the International Conference on Energy and Sustainable Development: Issues and Strategies (ESD 2010) (pp. 1-6). IEEE; doi: 10.1109/ESD.2010.5598779
  57. Nah, N. S. M., Ismail, S., Ramayah, T., Abu Hassan, Z. R., and Hanaysha, J. R. (2019). Modelling the Use of Grabcar Ridesharing Services. International Journal of Recent Technology and Engineering, vol. 8, no. 2, pp. 2277–3878; doi: 10.35940/ijrte.B1055.0782S219
  58. NEM Solar Malaysia (2020) Net Energy Metering solar Malaysia. Retrieved from; https:// http://nemsolarmalaysia.com/category/news/ on 26 October 2020
  59. Ntanos, S., Kyriakopoulos, G., Chalikias, M., Arabatzis, G., & Skordoulis, M. (2018). Public perceptions and willingness to pay for renewable energy: A case study from Greece. Sustainability, 10(3), 687; doi: 10.3390/su10030687
  60. Oh, T. H., Pang, S. Y., & Chua, S. C. (2010). Energy policy and alternative energy in Malaysia: issues and challenges for sustainable growth. Renewable and Sustainable Energy Reviews, 14(4), 1241-1252; doi: 10.1016/j.rser.2009.12.003
  61. Oladokun, M. G., & Odesola, I. A. (2015). Household energy consumption and carbon emissions for sustainable cities–A critical review of modelling approaches. International Journal of Sustainable Built Environment, 4(2), 231-247; doi: 10.1016/j.ijsbe.2015.07.005
  62. Petinrin, J. O., & Shaaban, M. (2015). Renewable energy for continuous energy sustainability in Malaysia. Renewable and Sustainable Energy Reviews, 50, 967-981; doi: 10.1016/j.rser.2015.04.146
  63. Saad, M. A., Ismail, F. A., Fauzi, F. M., & Rahmat, M. K. (2017, September). Consideration for nuclear energy in Malaysia. In 2017 International Conference on Engineering Technology and Technopreneurship (ICE2T) (pp. 1-5). IEEE; doi: 10.1109/ICE2T.2017.8215964
  64. Said, A. M., Yahaya, N., & Ahmadun, F. L. R. (2007). Environmental comprehension and participation of Malaysian secondary school students. Environmental education research, 13(1), 17-31; doi: 10.1080/13504620601122616
  65. Salleh, A. M. (2015) The economic valuation of solar water heating systems and the determinants of its adoption by the Libyan households
  66. Scottish Executive (2003) “Attitudes and Knowledge of Renewable Energy amongst the General Public.” Department of Trade and Industry, August, pp. 1–9
  67. Sebri, M., & Ben-Salha, O. (2014). On the causal dynamics between economic growth, renewable energy consumption, CO2 emissions and trade openness: Fresh evidence from BRICS countries. Renewable and Sustainable Energy Reviews, 39, 14-23; doi: 10.1016/j.rser.2014.07.033
  68. Soon, J. J., & Ahmad, S. A. (2015). Willingly or grudgingly? A meta-analysis on the willingness-to-pay for renewable energy use. Renewable and Sustainable Energy Reviews, 44, 877-887; doi: 10.1016/j.rser.2015.01.041
  69. Stapleton, C. D. (1997) Basic Concepts and Procedures of Confirmatory Factor Analysis; https://files.eric.ed.gov/fulltext/ED407416.pdf
  70. Stern, P. C. (1992). Psychological dimensions of global environmental change. Annual review of psychology, 43(1), 269-302; doi: 10.1146/annurev.ps.43.020192.001413
  71. Stern, P. C., & Dietz, T. (1994). The value basis of environmental concern. Journal of social issues, 50(3), 65-84; doi: 10.1111/j.1540-4560.1994.tb02420.x
  72. Straub, E. T. (2009). Understanding technology adoption: Theory and future directions for informal learning. Review of educational research, 79(2), 625-649; doi: 10.3102/0034654308325896
  73. Swan, L. G., & Ugursal, V. I. (2009). Modeling of end-use energy consumption in the residential sector: A review of modeling techniques. Renewable and sustainable energy reviews, 13(8), 1819-1835; doi: 10.1016/j.rser.2008.09.033
  74. Syed Mohamad, S. F. (2016) Shariah non-compliance risks in shared and outsourced services of takaful operators with insights from maqasid al-Shariah. INCEIF, Kuala Lumpur
  75. Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007) Using multivariate statistics (Vol. 5, pp. 481-498). Boston, MA: Pearson
  76. Tang, S., Chen, J., Sun, P., Li, Y., Yu, P., & Chen, E. (2019). Current and future hydropower development in Southeast Asia countries (Malaysia, Indonesia, Thailand and Myanmar). Energy Policy, 129, 239-249; doi: 10.1016/j.enpol.2019.02.036
  77. Williams, B., Brown, T., & Onsman, A. (2017). Exploratory factor analysis: a five-step guide for novices. Australas J Paramed 8 (3); doi: 10.33151/ajp.8.3.93
  78. World Bank Data. (2020) CO2 emissions. Retrieved from; https://data.worldbank.org/indicator/EN.ATM.CO2E.PC?locations=MY on 30th September 2020
  79. Wüstenhagen, R., Wolsink, M., & Bürer, M. J. (2007). Social acceptance of renewable energy innovation: An introduction to the concept. Energy policy, 35(5), 2683-2691; doi: 10.1016/j.enpol.2006.12.001
  80. Zainuddin, W.N.R, Abdullah, W.M.Z, Ramli, N.A. (2018). A Preliminary Study On Electricity Affordability and Willingness to Pay (WTP) On Maximum Demand (MD) Charge Among Residential Electricity Customers in Malaysia. International Journal of Recent Technology and Engineering (IJRTE), ISSN: 2277-3878, Volume-7 Issue-4S2
  81. Zografakis, N., Sifaki, E., Pagalou, M., Nikitaki, G., Psarakis, V., & Tsagarakis, K. P. (2010). Assessment of public acceptance and willingness to pay for renewable energy sources in Crete. Renewable and sustainable energy reviews, 14(3), 1088-1095; doi: 10.1016/j.rser.2009.11.009

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