Analyzing energy poverty with Fuzzy Cognitive Maps: A step-forward towards a more holistic approach

Papada, Lefkothea; Katsoulakos, Nikolas; Doulos, I.G.; Kaliampakos, Dimitris; Damigos, D.

doi:10.1080/15567249.2019.1634162

Cited by 20 publications

(8 citation statements)

References 83 publications

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“…Citizen engagement can help understand how the transition can be "just" (Papada et al 2019), building on recent analyses of the importance of social dialogue to achieve procedural and distributional justice (Gambhir, Green, and Pearson 2018) and gender equality (Sorman et al 2020) in such transitions. The EU Platform on Coal Regions in Transition to support heavily coal-dependent nations assists communication among national, regional and local stakeholders regarding the modernization of these regions' economies; and enables people working in the lignite sector to obtain new skills and become capable of working in a "greener" reality (European Commission 2018).…”

Section: Where Are We Now?mentioning

confidence: 99%

Sustainable and socially just transition to a post-lignite era in Greece: a multi-level perspective

Νίκας

Neofytou

Karamaneas

et al. 2020

Energy Sources, Part B: Economics, Planning, and Policy

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Section: Where Are We Now?mentioning

confidence: 99%

Sustainable and socially just transition to a post-lignite era in Greece: a multi-level perspective

Νίκας

Neofytou

Karamaneas

et al. 2020

Energy Sources, Part B: Economics, Planning, and Policy

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“…Some of these are, indicatively, adequate warmth at home [13,14]; adequate meeting of all domestic energy needs [15][16][17]; excessive energy cost, e.g., the 2M indicator [18]; excessive energy cost in relation to household income, e.g., the 10% indicator [19] and the "Stochastic Model of Energy Poverty" (SMEP) indicator [20]; low household income, e.g., the M/2 indicator [18] and the "Minimum Income Standard" (MIS) [21][22][23][24]; poverty combined with high energy cost, e.g., the "Low Income High Cost" (LIHC) indicator [19]; compression of energy needs [25]; qualitative aspects of the problem, i.e., inability to keep home adequately warm, damp/mold problems, arrears on energy bills, e.g., [26][27][28][29][30]; composite indicators, e.g., [31,32] and many others. Apart from targeted-to-indicators approaches, some studies attempt to capture a holistic picture of the problem by integrating micro-and macro-drivers, e.g., [33] and others address the wider notion of energy vulnerability and deprivation, e.g., [34][35][36][37][38][39]. In any case, and whatever the indicator chosen to approach energy poverty, it is generally agreed that the problem mainly arises as a combination of three drivers: low income, high energy cost, and low energy efficiency of the house [40][41][42][43].…”

Section: Introductionmentioning

confidence: 99%

Fighting Energy Poverty Using User-Driven Approaches in Mountainous Greece: Lessons Learnt from a Living Lab

et al. 2021

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The experience of operating an energy-related Living Lab (LL) in mountainous Greece is presented in this paper in an attempt to explore the dynamics of such initiatives to address energy vulnerability. The LL is situated in Metsovo, which is a typical mountainous town of Greece with increased vulnerability issues identified in previous studies. Since Greek mountainous societies have proved to be particularly exposed to energy poverty, the LL aimed to function as an exemplary case on how to tackle energy poverty issues in mountainous regions, mainly through reducing energy consumption and improving energy efficiency. The methodological context was based on a holistic LL approach consisting of various activities, such as conduction of energy cafés, questionnaire surveys, home visits from Energy Advisors, installation of monitoring equipment, ICT tools and processing, etc. In particular, the LL consisted of three independent rounds, each of which involved 50 households, with 30 of them being equipped with monitoring tools. Energy advisors repeatedly visited households to collect information (on heating expenses, behavioral aspects, etc.) and offer household-specific advice on potential energy savings measures. Overall, the LL operation proved to have benefited most participants (76%), especially households with monitoring equipment, as 85.5% of the last ones already applied energy-efficiency measures and 80% made further plans for future investments. Through the particular LL example, apart from the benefits delivered to the local society, useful information can be provided to policy-makers toward addressing more effectively energy vulnerability in mountainous societies.

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“…Overall, there are several factors involved. Papada et al [4] attempted to give a holistic picture of the EP "system", focusing on Greece, combining the most decisive micro-and macro-drivers and the ways these drivers interact with one another. At a macrolevel, energy poverty is affected by drivers relating to energy requirements and climatic conditions, degree of urbanization, broader socioeconomic characteristics (e.g., sociopolitical system, physical and built environment and local services), and socio-spatial vulnerability variables (e.g., access, flexibility, affordability and needs) [5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Does Energy Poverty Affect Energy Efficiency Investment Decisions? First Evidence from a Stated Choice Experiment

et al. 2021

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Energy poverty is a multidimensional and continuously growing societal problem, with political roots. In pursuit of mitigating the problem, the European Commission has adopted a bundle of policies, such as consumer protection measures, short-term financial interventions, motivations for energy efficiency (e.g., energy retrofits and replacement of old household appliance) and information campaigns, among others. There is no doubt, however, that increasing the income of vulnerable households would be the most preferred and effective option. Focusing on energy efficiency, a measure typically incorporated in the National Energy and Climate Plans (NECPs) of many Member States as a means to fight energy poverty, this paper aims to shed light on the need to gradually move towards more localized—not to say personalized—actions. In this direction, a labeled choice-based experiment is used, which involves a hypothetical selection between three alternative energy interventions, i.e., house retrofit, upgrading of heating system and upgrading of household electrical appliances. The research aims to integrate the preferences of households from the choice experiment with indicators of energy poverty and establish a connection between energy poverty and energy efficiency investment decisions. The results demonstrate that households’ preferences are affected by qualitative and quantitative aspects of energy vulnerability and sociodemographic characteristics. Furthermore, vulnerable households seem to be more prone to the so-called “discounting gap”, as previous studies also suggest. These findings are worrisome because, without tailor-made support, these households may never escape the vicious circle of energy poverty. To this end, the survey could provide useful information to policy-makers towards developing more robust policies of energy poverty alleviation.

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Analyzing energy poverty with Fuzzy Cognitive Maps: A step-forward towards a more holistic approach

Cited by 20 publications

References 83 publications

Sustainable and socially just transition to a post-lignite era in Greece: a multi-level perspective

Sustainable and socially just transition to a post-lignite era in Greece: a multi-level perspective

Fighting Energy Poverty Using User-Driven Approaches in Mountainous Greece: Lessons Learnt from a Living Lab

Does Energy Poverty Affect Energy Efficiency Investment Decisions? First Evidence from a Stated Choice Experiment

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