Solar and Bio-mass based Hybrid Power System for Rural Areas

Lakshmi, G. Sree; Harivardhagni, S.; Divya, G.; Lavanya, V.

doi:10.1109/hydcon48903.2020.9242786

Cited by 6 publications

(2 citation statements)

References 2 publications

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“…The product and services awareness refer to the extent to which a consumer of rural area knows about biofuel and solar power energy products and services (Bailey, 2005). The knowledge of product includes basic features of products (Ambali & Bakar, 2014), functions (Kane et al, 2003), usability and usages (Lakshmi et al, 2020), main brands or manufacturer (Marselina, 2019) and prices (Irfan et al, 2019) while services aspect of product includes retailers' promotion techniques of installing, repairing and provision of any extra information that can enhance basic utility of product (Pokharel, 2003;Mishra et al, 2019). Product and services awareness is crucial in developing intention and adopting the alternative energy products such as biofuel and solar power (Akroush et al, 2019).…”

Section: Product and Services Awareness Factorsmentioning

confidence: 99%

The Rural Consumer Adoption of Sustainable Energy: A PLS-SEM-ANN Approach of Conceptual Model Development and Cross Country Validation of Pakistan and Malaysia

Yin

Ahmed

Yong

et al. 2022

Preprint

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Sustainable and alternative energy sources of biofuel and solar power panel have been revolutionizing the lives and economy of many countries. However, these changes mainly occur in the urban areas and the rural population section has long been ignored by policy makers and government in the provision of energy. It is only recently that solar and biofuel are finally making in road to provide cheap and clean energy sources to rural population. As a result, literature on consumer behavior of rural population towards sustainable energy sources are still very scarce. The present research aims to fulfil this gap by developing a conceptual model to investigate the adoption of solar power and biofuel energy resources in the cross-cultural setting of Malaysia and Pakistan. The data was collected from the rural areas of Pakistan and Malaysia. The two-stage data analysis method of partial least square structural equation modeling (PLS-SEM) and artificial neural network (ANN) have been applied to satisfy both linear and non-linear regression assumption respectively. The results show that consumer in rural areas of Pakistan are willing and possess intention to adopt both biofuel and solar power for commercial and domestic use. Additionally, the results confirm that Branding, Economic and Altruistic factors are important in yielding intention to use towards biofuel and solar power panel in Pakistan which are validated by the results obtained in Malaysia. Other factors such as climate change awareness, retailer services quality and ease of use are also important. The results offer wide ranging theoretical and managerial implications.

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Section: Product and Services Awareness Factorsmentioning

confidence: 99%

The Rural Consumer Adoption of Sustainable Energy: A PLS-SEM-ANN Approach of Conceptual Model Development and Cross Country Validation of Pakistan and Malaysia

Yin

Ahmed

Yong

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

Section: Product and Services Awareness Factorsmentioning

confidence: 99%

The rural consumer adoption of sustainable energy: a PLS-SEM-ANN approach of conceptual model development and cross-country validation of Pakistan and Malaysia

Yin

Ahmed

Yong

et al. 2022

Environ Sci Pollut Res

View full text Add to dashboard Cite

Sustainable and alternative energy sources of biofuel and solar power panel have been revolutionizing the lives and economy of many countries. However, these changes mainly occur in the urban areas and the rural population section has long been ignored by policy makers and government in the provision of energy. It is only recently that solar and biofuel are nally making in road to provide cheap and clean energy sources to rural population. As a result, literature on consumer behavior of rural population towards sustainable energy sources are still very scarce. The present research aims to ful l this gap by developing a conceptual model to investigate the adoption of solar power and biofuel energy resources in the cross-cultural setting of Malaysia and Pakistan. The data was collected from the rural areas of Pakistan and Malaysia. The two-stage data analysis method of partial least square structural equation modeling (PLS-SEM) and arti cial neural network (ANN) have been applied to satisfy both linear and nonlinear regression assumption respectively. The results show that consumer in rural areas of Pakistan are willing and possess intention to adopt both biofuel and solar power for commercial and domestic use. Additionally, the results con rm that Branding, Economic and Altruistic factors are important in yielding intention to use towards biofuel and solar power panel in Pakistan which are validated by the results obtained in Malaysia. Other factors such as climate change awareness, retailer services quality and ease of use are also important. The results offer wide ranging theoretical and managerial implications.

show abstract

Performance Analysis of Low Voltage Ride Through Techniques of DFIG Connected to Grid Using Soft Computing Techniques

Gangikunta,

Venkateshwarlu,

Laxmi

2024

Communications in Computer and Information Science

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Solar and Bio-mass based Hybrid Power System for Rural Areas

Cited by 6 publications

References 2 publications

The Rural Consumer Adoption of Sustainable Energy: A PLS-SEM-ANN Approach of Conceptual Model Development and Cross Country Validation of Pakistan and Malaysia

The Rural Consumer Adoption of Sustainable Energy: A PLS-SEM-ANN Approach of Conceptual Model Development and Cross Country Validation of Pakistan and Malaysia

The rural consumer adoption of sustainable energy: a PLS-SEM-ANN approach of conceptual model development and cross-country validation of Pakistan and Malaysia

Performance Analysis of Low Voltage Ride Through Techniques of DFIG Connected to Grid Using Soft Computing Techniques

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