Usage intention, attribute preferences and economic value of green electricity in Pakistan

The huge reliance on thermal power for electricity generation, power sector of Pakistan has become significant contributor to GHG emissions. The Government has plans to improve and upgrade the electricity infrastructure through generating more electricity from renewable energy sources. In order to evaluate the economic benefits which people are expected to gain if the green electricity sources are increased in the system, their intentions and preferences for any specific renewable energy sources are considered in this study. This thesis aims to explore usage intention, attribute preferences and economic value of green electricity in Pakistan. The objectives of this study were explored by employing three different methods namely; contingent valuation method (CVM), choice experiment (CE) and Partial least squares structural equation modelling (PLS-SEM). The respondents were divided into two broad categories of urban and rural. A total of 400 respondents from urban and 405 respondents from rural areas were selected for this study. The PLS-SEM method was utilised to investigate the factors, which influence the consumer’s intention to use green electricity. The moral obligation (Perceived moral obligation), New Ecological Paradigm scale (General environmental attitudes) and theory of planned behaviour (Attitudes, Subjective norms and Perceived behavioural control) were used to measure these factors. Moreover, the CVM calculated the overall price of green electricity for environmental improvement through increasing the share of electricity from renewable energy sources. The widely used WTP measure doublebounded dichotomous was utilised to elicit the appropriate value of green electricity from the bid price. Whereas, a choice experiment (CE) method employed to estimate willingness to pay for different sources of green electricity. The three main sources of green electricity (Hydroelectricity, wind and solar) along with load shedding attribute was explored. The Conditional Logit Model and Mixed Logit Models were employed to identify the consumer’s preferences and estimation of the marginal values. The PLS-SEM results showed that all these factors have a positive relationship with the intention to use green electricity, except for urban consumers who do not think that they are morally obliged to use green electricity. Whereas, results from the logit regressions showed that the respondents with high income and a higher level of education are willing to pay more for green electricity in both urban and rural models. Moreover, CVM results also revealed that the willingness to pay for green electricity is high in younger people than older people are. The mean willingness to pay has found 0.33 cents per kWh in the urban model, while it is 0.24 in the rural model. The results provided a guideline to the government to charge an appropriate surcharge for the green electricity from consumers. The results from CE further showed that the urban and rural consumers chose the solar source of green electricity as the most preferred source and marginal values for this source is 0.17 cents per kWh and 0.19 cents per kWh in urban and rural models respectively. Finally the above findings and their implications have some policy relevance in that the development and promotion of green electricity in the renewable energy policy has been found to be pragmatic and workable. These findings are useful information for the policy makers, government and other agencies to enhance greater stakeholder participation in developing the green electricity. The results of economic valuation and choice experiment aid the government to gain insight about real value and the preferences of the sources of green electricity in Pakistan.

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