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The purpose of this paper is to explore citizens’ willingness to invest in photovoltaics.

To meet the aim of the research, a questionnaire survey was conducted in the island of Evia in Greece using the method of random stratified sampling. A total of 366 responses were analyzed using both descriptive and inductive statistics methods, such as principal components analysis, K-means cluster analysis, discriminant analysis and binary logistic regression.

The research results indicate that 73per cent of the respondents would invest in renewable energy sources, whereas 55per cent of them would specifically invest in photovoltaics. Regarding their views on photovoltaics, three components were extracted; photovoltaics positive effects, facilitations for investments in photovoltaics and photovoltaics’ performance. Area of residence, annual income and the above-mentioned three components of views on photovoltaics were found to be statistically significant for the dichotomous variable of willingness to invest in photovoltaics. Among the examined variables, photovoltaics performance found to contribute the most in increasing respondents’ willingness to invest in photovoltaics.

The study filled the literature gap concerning citizens’ willingness to invest in photovoltaics in Greece. Furthermore, the research results made feasible to understand the factors that can lead in an investment decision for photovoltaics.

The design of a biomass supply chain is a problem where multiple stakeholders with often conflicting objectives are involved. To accommodate the aspects stakeholder, the supply chain design should incorporate multiple objectives. In addition to the supply chain design, the management of energy from biomass is a demanding task, as the operation of production of biomass products needs to be aligned with the rest of the operations of the biomass supply chain. The purpose of the paper is to propose a mathematical framework for the optimal design of biomass supply chain.

An integrated mathematical framework that models biomass production, transportation and warehousing throughout the nodes of a biomass supply chain is presented. Owing to conflicting objectives, weights are imposed on each aspect, and a 0-1 weighted goal programming mixed-integer linear programming (WGP MILP) programming model is formulated and used for all possible weight representations under environmental, economic and social criteria.

The results of the study show that emphasis on the environmental aspect, expressed with high values in the environmental criterion, significantly reduces the level of CO₂ emissions derived from the transportation of biomass through the various nodes of the supply chain. Environmental and economic criteria seem to be moving in the same direction for high weight values in the corresponding aspect. From the results, social criterion seems to move to the opposite direction from environmental and economic criteria.

An integrated mathematical framework is presented modeling biomass production, transportation and warehousing. To the best of the authors’ knowledge, such a model that integrates multiple objectives with supply chain design has not yet been published.