cooling and domestic hot water

Renewable Energy 142 (2019) 591e603

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Renewable Energy journal homepage: www.elsevier.com/locate/renene

Factors affecting willingness to adopt and willingness to pay for a residential hybrid system that provides heating/cooling and domestic hot water Spyridon Karytsas*, Olympia Polyzou, Constantine Karytsas Centre for Renewable Energy Sources and Saving (CRES), Geothermal Energy Department, 19th km Marathonos Av., Pikermi, 19009, Athens, Greece

a r t i c l e i n f o

a b s t r a c t

Article history: Received 19 November 2018 Received in revised form 10 April 2019 Accepted 20 April 2019 Available online 25 April 2019

The present study examines, through a behavioral survey, the self-reported intentions of consumers in Greece, Portugal and Spain, in relation to a residential hybrid system that offers heating/cooling and domestic hot water (DHW); the system combines ground source heat pumps, solar thermal panels and thermal energy storage. A positive attitude concerning the adoption intention of the system has been recorded, while the results on Willingness to Pay (WTP) and acceptable payback period reveal that there is a potential market for the hybrid system in the three countries. The analysis indicates that consumers’ intentions are similar among the three countries, with the only statistical significant difference occurring between Spain and Portugal on the subject of WTP for the system. The socioeconomic factors that are identified to have an effect on consumers’ intentions in relation to the hybrid system are gender, income, educational level, occupation, past investments in thermal energy systems and percentage of income spent on household energy needs; the corresponding residence characteristics include location, building type, dwelling size, year of construction and existing system for space heating and DHW. The study’s findings can contribute to the broader understanding of consumers’ behavior concerning the adoption of residential heating/cooling and DHW systems. © 2019 Published by Elsevier Ltd.

Keywords: Hybrid system Ground source heat pump Solar thermal Thermal energy storage Willingness to adopt Willingness to pay

1. Introduction Energy is consumed by the industrial, residential, commercial and transport sectors. Worldwide, the residential sector is responsible for the consumption of 18% of the total energy consumption [1]; the corresponding percentage for the European Union (EU) is 25%, while for Greece it is 29%, for Portugal 16% and for Spain 19% [2]. Furthermore, the global residential energy consumption is expected to increase over 50% between 2010 and 2040, mainly due to the increased demand from non-OECD1 (Organization for Economic Co-operation and Development) countries [4]. According to Eurostat, in 2011 natural gas represented 36% of total energy consumption of EU’s residential sector, electric energy 25%, Renewable Energy Sources (RES) 14%, oil products 14%, heat

* Corresponding author. E-mail address: [email protected] (S. Karytsas). 1 The OECD consists of 36 Member countries, including many of the world’s most advanced countries, as well as some emerging countries. A full list of Member countries is provided at http://www.oecd.org/about/membersandpartners/[3]. https://doi.org/10.1016/j.renene.2019.04.108 0960-1481/© 2019 Published by Elsevier Ltd.

recovery 7% and solid fuels 4% [2]. Concerning the residential sector, space heating is responsible for the largest share of consumed energy, while the activities that follow are space cooling, cooking, lighting and Domestic Hot Water (DHW) production [1,5e8]. The factors that can affect residential energy consumption are family income, level of energy prices, location, building and household characteristics, climate characteristics, type and efficiency of appliances, access to energy supply, availability of energy sources and energy policies [9,10]. Based on the above, it is clear that the residential sector, dominated by space heating energy needs, is responsible for a large part of global energy consumption. These needs are mainly covered through the utilization of fossil fuels, as also indicated by CastilloCalzadilla et al. [11]. Among the technologies that can contribute to the reduction of fossil fuel consumption in the residential sector are geothermal [through the use of Ground Source Heat Pumps (GSHPs)] and solar thermal energy, as well as their combination into an integrated hybrid system. The use of two RES such as geothermal and solar thermal energy can offer several benefits, with the most significant being that they a) are practically inexhaustible and contribute to the reduction of dependence on

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Nomenclature Adj. Sig ASHP B C.I. CE CADM CPV CV DHW DoI EU GHG GSHP LL OECD

Adjusted significance Air source heat pump Standardized regression coefficient (beta) Confidence intervals Choice experiment Comprehensive action determination model Consumer perceived value Contingent valuation Domestic hot water Diffusion of innovations European Union Greenhouse gases Ground source heat pump Log likelihood Organization for economic co-operation and development

conventional fuels, b) are environmentally friendly, c) have low operating costs and are not affected by fossil fuel prices fluctuations, d) are local energy sources and e) can contribute to the development of economically and socially challenged areas. Hybrid system solutions offering heating, cooling and DHW can benefit from the best features of each involved technology. Such systems can lead to higher performance [12], stability [13,14], economic benefits [14], resolution of possible system operation imbalances [15] and environmental benefits [16]; as Qi et al. (2014) [15] mention, “Hybrid energy systems facilitate the efficient utilization of renewable resources and sustainable energy, and they are expected to be more prevalent in the future”. More specifically, the combination of GSHPs with solar thermal collectors can create systems of higher performance [17,18], reliability [19] and economic benefits [20], and lower operation cost [21] and environmental degradation [20,21] compared to conventional systems as well as systems applying only GSHPs. Moreover, the combination of heating systems with heat energy storage can lead to even higher performances [22,23], indoor thermal comfort levels [22] and economic benefits [22], while assisting the system to operate more flexibly, effectively, and stably [23]. An innovative residential hybrid system combining GSHPs, solar thermal panels and thermal energy storage [enhanced with Phase Changing Material (PCM)] is being designed, developed and demonstrated within the Thermal Energy Storage Systems for Energy Efficient Buildings (TESSe2b)2 project (Fig. 1). The project has duration of four years, is financed by the European Commission (Horizon 2020) and is based on the collaboration of academia, researchers, manufacturers and installation companies from eight EU countries. The compact and modular system requires a small outdoor space (e.g. small garden) for the drilling of the boreholes, as well as free space eusually on the roof- for the installation of the solar thermal collectors. The system includes a smart control system which automatically reduces energy consumption in different operating conditions. Due to the smart control system and the user friendly interface, no special knowledge or skills are required from the side of the user for the efficient operation of the system. The simple payback period for the system has been estimated to be 5.5e8.5 years in Greece, 5 years in Portugal and 6e9 years in Spain [25]. After that, the consumers can economically benefit from the

2

Project website http://www.tesse2b.eu/ [24].

p PCA PCI PCM RET RES S.E. SD Sig SPSS TAM TES TESSe2b TPB WTA WTP

c2

Probability value (p-value) Principal component analysis Perceived characteristics of innovations Phase changing material Renewable energy technologies Renewable energy sources Standard error Standard deviation Significance Statistical package for the social sciences Technology acceptance model Thermal energy storage Thermal energy storage systems for energy efficient buildings Theory of planned behavior Willingness to adopt Willingness to pay Chi-square statistic

Fig. 1. Design of the TESSe2b system [24].

lower operation cost of the system, compared to conventional and RES technologies. The successful market diffusion of such a system requires raising awareness on the system and its benefits, as well as achieving an acceptable installation cost -which is usually one of the main installation barriers of similar systems. To our knowledge, and based on the literature survey presented in Section 2, little research has been performed so far to empirically examine the factors affecting Willingness to Adopt (WTA) and Willingness to Pay (WTP) for renewable energy technologies such as GSHP and solar thermal systems on a residential level, let alone, the combination of the two technologies in a hybrid system. Therefore, the present study makes a significant empirical contribution towards a better understanding of these issues, through the analysis of consumers’ perceptions in three EU countries (Greece, Portugal and Spain) in relation to a) potential benefits of the proposed hybrid system, b) WTA the system, c) WTP for the system (in V) and d) acceptable payback period (in years) in order to be willing to invest in the system. In addition, a more detailed knowledge of the causal dimensions behind WTA and WTP for this type of systems can also assist the better design of policy tools and market strategies that could contribute to their market uptake. Findings of the research for the three countries can be also transferred, at least on a qualitative level, to other countries with the same

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environmental and energy targets. The paper proceeds as follows: Section 2 reviews relevant studies on the WTA and WTP for residential heating, cooling and/or DHW production systems, with a focus given on GSHP and solar thermal technologies. Section 3 outlines the survey design and implementation and provides an overview of the analytical procedure followed. In Section 4, the results of the statistical analysis are presented. In Section 5, the findings are discussed and implications for policy-making and business are explored; in addition, the limitations of this study and suggestions for future research are presented. Finally, Section 6 provides the main conclusions of the study. 2. Theoretical background Through the thorough examination of the relevant literature, it is indicated that work related to willingness to adopt and willingness to pay has been performed mainly concerning residential heating systems; when referring to DHW production, these themes have been investigated in very few cases, while cooling is examined only in the case that the main heating systems under analysis offer this function as well (e.g. heat pumps). Investigation of the factors that affect the selection of a residential heating system was first performed using Census data from the US in order to examine the effect that socioeconomic and demographic characteristics, and factors related to the installation and operation cost of the system, can have on the selection process [26e29]. During the last years, from 2000 until now, the number of relevant studies has increased significantly, with the studies focusing mainly on heating systems utilizing RES technologies [30]. In this context, the most commonly studied countries are Germany, Norway, USA, Sweden, Finland and the UK [30]. These studies examine not only the effect of socioeconomic, residence and spatial characteristics, but consumers’ behavior, preferences and attitudes for specific heating system attributes as well; Table 1 presents an overview of the factors that have been found to affect the selection of residential heating systems, based on the literature review performed by Karytsas and Theodoropoulou [30]. In the context of developing a theoretical basis and describing the background related to consumers’ residential heating system selection process, many studies apply theories on innovation and technology diffusion and consumer behavior. Mahapatra and Gustavsson [31] and Tapaninen et al. [32] have based their work on the Diffusion of Innovations (DoI) model [33], which presents the factors (relative advantage, compatibility, complexity, trialability and observability) that can have a positive effect to the diffusion of an innovative technology. Nyrud et al. [34] and Bjørnstad [35] have put into use the Theory of Planned Behavior (TPB) [36], which deals with the connection between beliefs and behavior, stating that attitude toward behavior, subjective norms, and perceived behavioral control form the behavioral intentions and behaviors of an individual. Additionally, other theories that have been applied in this context include the Consumer Perceived Value (CPV) [37], the

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Technology Acceptance Model (TAM) [38], the Perceived Characteristics of Innovations (PCI) [39] and the Comprehensive Action Determination Model (CADM) [40,41]. Willingness to pay is a subject that has been taken under consideration by a number of studies dealing with consumers perceptions on residential heating systems’ adoption. Scarpa and Willis [42] investigate households’ WTP for micro-generation Renewable Energy Technologies (RET) (solar photovoltaic, microwind, solar thermal, heat pumps, biomass boilers and pellet stoves) through a Choice Experiment (CE) approach in the UK (excluding Northern Ireland); the results suggest that although adoption of RET is significantly valued by households, the value is not large enough, in the majority of the households, in order to cover the higher capital costs of micro-generation RET. Another study, involving the same area, applies CEs in households with residents aged
65 years, indicating that age has a negative effect on WTP for micro-generation RET (solar thermal, solar voltaic, and wind power) [43]. Claudy et al. [44] examine consumers’ WTP for microgeneration technologies (micro wind turbines, wood pellet boilers, solar panels and solar water heaters) in Ireland, by applying a Contingent Valuation (CV) method, evaluating the effect that consumers’ perceptions of product characteristics, normative influences and sociodemographic characteristics can have on WTP. Results point out that WTP varies significantly among the different technologies, while homeowners’ beliefs about the respective technologies influence their WTP on a significant level. A study performed by Stolyarova et al. [45] applies a discrete CE on French respondents, regarding the theoretical replacement of their existing space heating system; results indicate that French households are willing to pay V5000 - V8000 more for RES than for natural gas or electricity and that WTP for attributes that control energy consumption depends on thermal comfort preferences (e.g. coldsensitive households are willing to invest more in RES and devices to manage indoor temperature). A research on low temperature Air Source Heat Pump (ASHP) technology in China, applying the CV method, notes that the socioeconomic and perception factors that affect WTP are gender, income, science literacy, local environmental concern, area type and house heating area [46]. Ortega-Izquierdo et al. [47] examine WTP for renewable heating/ cooling systems in Spanish households. According to the results, the majority of the respondents being aware of these systems would pay more for them, and specifically up to 10% more compared to a conventional system. People of younger age, higher education, higher income and residing in rural areas are more willing to pay for renewable heating/cooling systems. A small number of studies have been performed on the factors affecting adoption of residential GSHP systems; the studies focus mainly on systems’ attributes, while very little work has been presented concerning the effect of socioeconomic, residence and spatial characteristics. The first work related to these subjects deals with the case of Sweden, noting that bedrock heat pumps are viewed as better systems than pellet boilers, resistance heaters and district heating, with regards to Greenhouse Gas (GHG) emissions,

Table 1 Factors affecting residential heating system selection. Socioeconomic characteristics Residence characteristics Spatial characteristics Characteristics related to consumers’ behavior, attitudes and system attributes preferences Source: Modified from [30].

Income, age, educational level, household size (number of residents), children in the household, number of children, gender, occupation Residence size (or number of bedrooms), type of residence, year of construction, ownership, years living in the residence, infrastructure, renovations or retrofits for energy efficiency improvement Region, area type (urban/rural), climate, existence of “green” in the area Economic aspects, environmental considerations and energy saving, energy supply security, comfort considerations and aesthetics, general attitude, social reasons and information/knowledge aspects, supplier issues

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house market value, environmental benignity, fuel supply security and operation cost; as a result of these relative advantages, consumers would recommend the use of heat pumps over other heating systems [48,49]. A study concerning the UK reports that consumers using GSHPs identify reliability, satisfaction from using low carbon energy, appearance and operation/maintenance cost as the main advantages of the system [50]. Additionally, a more recent work from the same country mentions that technical support, supplementary heating and consumers’ knowledge and understanding of GSHPs are important factors that have an effect on the systems’ performance [51]. Doody and Becker [52,53] note that in New Zealand GSHPs were recognized as the residential heating system with the highest potential, with users reporting efficiency, heating/cooling mode, ease of use, convenience, safety and indoor air quality as the system’s main assets. A study in Ireland performed by Kennedy and Basu [54] indicated that geothermal technologies are more appealing for new constructions, thus explaining the low diffusion level of the technology, while consumers consider GSHP systems as a technology of high investment cost. In Finland there is a preference towards GSHP systems, with factors such as income, installation and operation cost, CO2 emissions and factors that cannot be recorded (e.g. reputation, reliability) affecting its adoption [55]. Another study from Finland also supports the finding that GSHPs are more favorable than other heating systems, due to comfort use, environmental friendliness and reliability; however it was noted that the technology presents sensitivity to investment cost increases [56]. Two studies from Greece indicate that the adoption intention for GSHP systems is around 8% and is affected by socioeconomic (age, income, education, occupation, environmentally friendly behavior and awareness) and residence (connection to natural gas network, money spent on heating oil) characteristics, as well as by factors related to the consumers’ preferences and attitudes for specific heating system attributes (relative advantages over other systems, observability and trialability, available capital); main sources of information are the internet and conversations with peers, while main adoption barriers are high installation cost, lack of capital and residing in buildings were it would be difficult to install such a system [30,57]. The initial study examining the factors affecting adoption of residential solar thermal systems was performed in the UK; environmental characteristics are identified as a positive asset of the system by consumers, while financial, economic and aesthetic characteristics are perceived as limiting aspects [58]. A research in the same country applying the diffusion of innovations theory indicates that “innovators” overlooked the element of observability of the innovation and installed the system without having seen it in advance [59]. A study performed by Mills and Schleich [60] examines the geographic, residence and household characteristics that affect the adoption of solar thermal water and space heating technologies in German households. The results indicate that adoption of solar water heating systems is related to solar radiation levels, heating degree days, year of building construction, existence of incentive programs, number of storeys of the building, residence size, type of existing water heaters and space heating systems, dwelling ownership, existence of specific amenities (pool or sauna), family size, age of household head, consumption of DHW (showers, baths) and room temperature. On the other hand, adoption of solar space heating systems is related to city size, number of storeys of the building, type of existing water heaters and space heating systems, dwelling ownership, family size, education and room temperatures. Further research involving Germany indicates that the diffusion of residential solar thermal systems can be affected by environmental attitude and knowledge, age, household income, property and peer group behavior [61,62]. The work of Schelly [63] investigates the socioeconomic circumstances, environmental

concerns and ecological conditions that can affect residential solar thermal technology adoption in the USA; results show that education, occupation, income, and environmental concerns are factors that can have such an effect. A study performed by Claudy et al. [44] indicates that environmental friendliness, annual energy cost savings, support for microgeneration technologies from significant others (e.g. friends and family), knowing someone who operates such a system and residing in urban areas have a positive effect, while performance uncertainty of the technology can have a negative effect on WTP of Irish consumers for solar water heaters. The work of Kim et al. [64] on solar energy technologies (i.e. solar thermal electric, heating/cooling, and photovoltaic) indicates that public’s attitudes are affected positively by system quality, perceived benefits and trust, while intention to use is specified by public attitude and satisfaction (positively) and cost (negatively). Finally, a research focusing on Taiwanese students examines the impact of environmental value, ecological lifestyle and customer innovativeness on intention to install residential solar power systems, including both solar thermal and photovoltaic technologies [65]. Similar work to the above has been performed concerning solar assisted heating systems. Willis et al. [43] examine the adoption of solar thermal to supplement existing heating systems, in households with residents aged
65 years in the UK (excluding Northern Ireland); results indicate that these households are less probable to adopt such technologies. In addition, the selection of solar thermal technology is negatively affected by capital cost and annual maintenance cost, and positively affected by energy savings, low income and recommendations from a technician. Two different studies concerning the adoption of gas- and oil-fired condensing boilers with solar thermal support by German households have been performed. The first one, indicates that the adoption of such systems can be influenced by socioeconomic (income, age, education, gender), residence (year of construction, dwelling size, energy consulting) and spatial characteristics (location), as well as by specific attributes of heating systems (comfort, independence from fossil fuels, energy savings) [66]. The second study examines the drivers and barriers that lead homeowners to shift from fossil fuel to solar assisted systems; main barriers are high dependency on oil and natural gas, energy cost and total life-cycle cost, while factors such as ease of installation, ease of use, energy consumption and maintenance costs are not seen as barriers against the adoption of this technology [67]. A study performed by Ruokamo [56] examines attitudes in Finland, regarding innovative hybrid home heating systems that combine main heating alternatives with supplementary heating systems; the results indicate that solar-based supplementary heating systems are viewed favorably. 3. Materials and methods 3.1. Survey development and implementation In order to deal with the issues under investigation, a survey was arranged, examining the self-reported behavioral intentions of the respondents. A questionnaire was developed including four sections of questions: a) personal interests about environmental and energy issues, b) WTA and WTP for the TESSe2b hybrid system, c) residence characteristics and d) socioeconomic characteristics. The construction of the questionnaire was based on the findings described in Section 2 “Theoretical framework”. The survey, which aimed at the general public without any demographic restrictions, was conducted in Greece, Portugal and Spain. The online questionnaire survey was conducted between June 2016 and February 2017. Different communication channels were used to promote the survey and collect responses from the public: a) the TESSe2b

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project website, b) project partners’ websites from the three corresponding countries, c) email lists and d) websites and local events (e.g. trade fairs) aiming to consumers and related to heating/cooling systems, energy efficiency and building constructions.

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the two Likert scale variables. 4. Results 4.1. Descriptive statistics

3.2. Statistical methods A database including 400 fully completed responses was created: 159 from Greece, 109 from Portugal and 132 from Spain. Statistical analysis was conducted separately for each country using SPSS 24 (Statistical Package for the Social Sciences); simple descriptive statistics were used for the initial analysis, while ordinal logistic regression analyses were conducted in order to examine the influence of socioeconomic and residence characteristics on perceived benefits, WTA, WTP and acceptable payback period of the hybrid system. In addition, Kruskal-Wallis H tests were applied to evaluate the existence of any statistical significant differences between the responses from the three countries. Furthermore, it should be mentioned that although several different socioeconomic and residence characteristics were examined in the different tests and analyses, in the context of this paper only statistically significant results (p-values 0.010) are presented. The development of the ordered regression models is based on the findings of chi-square tests (correlations between nominal variables) and non-parametric Mann-Whitney tests (correlations between nominal and ordinal variables) performed in advance, while the regression models include only statistically significant variables (p-values 0.010). In addition, in order to select the best fitted models, the criteria of a) Model fitting, b) Goodness-of-fit, c) Pseudo R-Squares [57], and d) Test of Parallel Lines [68] were taken into account and are presented for each different model in Tables 6e8. The Likert scale questions concerning “perceived benefits” and “perceived adoption behavior” related to TESSe2b hybrid system were created through the combination (using the mean value of each case) of two sets of Likert items. Regarding the “perceived benefits” variable, the items combined were: life quality improvement, energy expenditure reduction, disposable income increase, energy security empowerment and creating a mentality of selfsustainability for the building. In the case of the perceived adoption behavior, the Likert items combined were: confident with the idea of adopting, comfortable with the idea of adopting, ease to adopt, intend to use, predict to use. In order to examine if the combination of the two sets of Likert items would create reliable Likert scale variables, a Cronbach’s alpha reliability test was conducted for each country and variable (six cases: three different countries, two different sets of Likert items). Prior to the reliability tests, Principal Component Analyses (PCAs) were performed in order to check that all Likert items (in each different case) are included in a single component, as it is a parameter that Cronbach’s alpha reliability test does not take into account. Accordingly, the performed PCAs indicated that in each one of the cases the five Likert items represent the same dimension, while the Cronbach’s alpha reliability coefficient was in each case over 0.800 (Tables 2 and 3), thus making acceptable the creation of

Table 2 Reliability statistics of the two sets of Likert items. Perceived benefits

Greece Portugal Spain

Willingness to adopt

Cronbach’s Alpha

No. of items

Cronbach’s Alpha

No. of items

0.884 0.902 0.854

5 5 5

0.904 0.909 0.904

5 5 5

The main findings in relation to the socioeconomic and residence characteristics of the sample are presented in Table 4. For each characteristic, the answer with the highest percentage per country is presented. Concerning socioeconomic characteristics, the three countries present quite similar answers in terms of gender, age, education, involvement in energy/environmental fields and general feel about household’s income; on the other hand, type of occupation differs among the three countries (based on the answer with the highest percentage), while respondents from Spain state to have a higher monthly income compared to the Greeks and the Portuguese. Residence characteristics are also found to be very similar between the three countries: area and type of residence, type of ownership, year of construction and income used for energy costs are comparable in all three cases; the only identified difference has to do with the dwelling size (larger for Greeks compared to Spaniards and Portuguese. The main differences between the three countries can be identified when examining household heating/cooling/DHW systems: the predominant energy sources used for the provision of these amenities for the residence are totally different in all three cases. Concerning the use of specific RES technologies, Greece has a higher percentage than the other two countries regarding the use of solar thermal panels, while the percentages for the use of geothermal systems are similar (near 0%) in all three countries. In addition, the three countries present similar results concerning previous investments in thermal energy systems/storage, with Greece having slightly higher values in relation to the other two countries. In all three countries, the majority of the respondents agree that the hybrid system can offer benefits (operation cost, life quality, energy security and building sustainability) compared to the existing systems (Fig. 2), while there is a positive attitude concerning willingness to adopt the system (Fig. 3). The majority of the respondents state that they would be willing to pay up to V6000 for the installation of the system (Fig. 4), while an acceptable payback period ein order for the consumer to be willing to pay for the installation cost of the system-would be up to five years (Fig. 5). 4.2. Kruskal-Wallis H tests Kruskal-Wallis H tests were performed in order to examine the existence of statistically significant differences between different countries regarding participants’ views on the main issues under investigation. In addition, post-hoc tests were applied in order to identify the existing differences between each pair of countries (Greece/Portugal, Greece/Spain and Portugal/Spain). The results of these tests are presented in Table 5. The results indicate that there are no differences between the pairs of Greece/Portugal and Greece/Spain. On the other hand, it is indicated that the participants from Portugal would be willing to pay less for the hybrid system compared to the participants from Spain, on a statistically significant level of a ¼ 0.01. The same result occurs in relation to Greece, but on a statistically significant level of a ¼ 0.10. 4.3. Ordinal logistic regression models Ordinal logistic regression models were developed for each country and each issue under investigation, in order to identify the different socioeconomic and residence characteristics affecting on a statistically significant level the examined themes (Tables 6e8).

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Table 3 Cronbach’s Alpha if item deleted in relation to the two sets of Likert items.

Perceived benefits

Willingness to adopt

a. The adoption of the hybrid system will improve my quality of life b. The adoption of the hybrid system will reduce my energy expenditure c. The use of the hybrid system will increase my disposable income d. The use of the hybrid system will contribute to my energy security, autonomy and freedom of choice e. The adoption of the hybrid system will create a mentality of self-sustainability for the building a. I feel confident with the idea of adopting the hybrid system b. I feel comfortable with the idea of adopting the hybrid system c. I think it will be easy for me to adopt the hybrid system d. I intend to use the hybrid system e. I predict that I will use the hybrid system

Greece

Portugal

Spain

0.856 0.844 0.884 0.849 0.863 0.892 0.888 0.882 0.871 0.877

0.877 0.872 0.878 0.880 0.893 0.883 0.894 0.906 0.878 0.879

0.835 0.797 0.827 0.824 0.836 0.876 0.881 0.889 0.869 0.896

Table 4 Descriptive statistics.

Gender Age Education Occupation Involved in energy and/or environmental fields Monthly income Feel about household’s income Area of residence Type of residence House ownership House size Year of construction (or large renovation) Household income used for energy costs Energy sources for heating Energy sources for cooling Energy sources for DHW Use of solar thermal panels Use of geothermal energy Invested in thermal energy systems in the past 5 years Invested in thermal energy systems using RES in the past 5 years Invested in thermal energy storage in the past year a b c

Greece

Portugal

Spain

66%: male Mean: 42 years (SDa: 10) 45%: 2nd stage of tertiary 30%: self-employed 63% 48%: 500e1500V 53%: coping on present income 50%: big city 57%: flat 70%: own house 39%: 100e150 m2 26%: 1970e1989 38%: 5e10% 48%: heating oil 74%: electric energy 50%: thermal solar panels 40% 2% 48% 33% 11%

63%: male Mean: 42 years (SD: 10) 59%: 2nd stage of tertiary 40%: employed in public sector 62% 44%: 500e1500V 52%: coping on present income 45%: big city 57%: flat 74%: own house 41%: 50e100 m2 25%: 1970e1989 44%: 5e10% 50%: electric energy 57%: does not use 28%: otherb 27% 1% 39% 23% 10%

76%: male Mean: 43 years (SD: 12) 42%: 2nd stage of tertiary 36%: employed in private sector 64% 56%: 1000e2000V 53%: coping on present income 40%: big city 60%: flat 72%: own house 50%: 50e100 m2 27%: 1970e1989 33%: 5e10% 46%: natural gas 52%: does not use 54%: same as space heatingc 24% 0% 49% 25% 14%

Standard deviation. Other than electric energy, solar thermal panels and district heating. Mainly natural gas, electric energy and heating oil.

Table 5 Results of Kruskal-Wallis H tests on differences between the three countries regarding the issues under investigation. Hypothesis

Sig.

Pairwise comparison

Adj. Sig.

Distribution of perceived benefits is the same across the three countries Distribution of WTA is the same across the three countries Distribution of WTP is the same across the three countries

0.906 0.354 0.001

Distribution of acceptable payback period is the same across the three countries

0.113

e e Greece - Portugal Greece - Spain Portugal - Spain e

e e 0.072 0.283 0.001 e

Additionally, the values of the criteria used for the selection of the best fitting model (see Section 3.2) are presented for each model. 5. Discussion There is a strong agreement among the respondents of the three countries that the installation of a hybrid system -such as TESSe2b system- can offer significant economic, environmental and energy benefits; thus, it should be of no surprise that more than half of the respondents have a positive view towards the adoption of the system. This result is consistent to the work of Ruokamo [56], according to which hybrid heating seems to be generally accepted among households. However, it should be noted that the high percentages towards adoption may be affected by the sample’s characteristics (e.g. high level of education and involvement in

energy/environment areas), as well as by the hypothetical nature of the questions. The examination of WTP and acceptable payback period may present a more clear view of the intentions of the consumers. In all three countries the majority of the respondents are willing to pay up to 6000V for the installation of such a system. When comparing this result to the estimated cost of the system (approximately 15000V [25]) it is indicated that around 5e10% of the respondents would be willing to install the system, based on its estimated installation cost. Nonetheless, it should be mentioned that the installation cost has been estimated based on preliminary data involving the development of pilot installations of the system; the installation of the system on a commercial level would lead to the decrease of the installation costs. Furthermore, when comparing the estimated payback period of the system (5e9 years) [25] to the

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Table 6 Ordinal logistic regression models for Greece: Socioeconomic and residence characteristics affecting the issues under investigation related to the hybrid system. Ba

Estimate

S.E.b

Wald

Sig.c

95% C.I.d Lower

Perceived benefits

Willingness to adopt

Willingness to pay

Acceptable payback period

a b c d e f g

Construction 1990e1999: No Construction 2000e2005: No Heating oil: No Heating natural gas: No Model Fitting

0.760 0.756 0.631 0.936 Goodness-of-Fit

0.395 3.698 0.365 4.286 0.325 3.764 0.407 5.274 Pseudo R-Square

2 LLe ¼ 110.869 c2f ¼ 11.161 pg ¼ 0.025

Pearson c2 ¼ 36.362 p ¼ 0.677

Cox & Snell ¼ 0.068 Nagelkerke ¼ 0.071 McFadden ¼ 0.023

Invested in thermal energy systems in the last 5 years: No Type flat: No Type detached single: No Income 2500e3000V: No Model Fitting

0.483 0.692 0.472 2.036 Goodness-of-Fit

0.285 2.870 0.392 3.114 0.443 1.132 0.855 5.673 Pseudo R-Square

2 LL ¼ 123.912 c2 ¼ 13.285 p ¼ 0.010

Pearson c2 ¼ 49.807 p ¼ 0.707

Cox & Snell ¼ 0.080 Nagelkerke ¼ 0.083 McFadden ¼ 0.024

Involved in related fields: No Residence countryside: No Type detached single: No Bedrooms up to 1: No Heating natural gas: No Income difficult to cope with: No Income <500V: No Gender: Female Model Fitting

1.146 1.981 0.787 2.031 0.813 1.270 1.570 0.938 Goodness-of-Fit

0.377 9.225 1.165 2.892 0.375 4.407 0.646 9.880 0.451 3.258 0.420 9.142 0.738 4.523 0.391 5.755 Pseudo R-Square

2 LL ¼ 131.723 c2 ¼ 50.750 p ¼ 0.000

Pearson c2 ¼ 69.273 p ¼ 1.000

Cox & Snell ¼ 0.273 Nagelkerke ¼ 0.304 McFadden ¼ 0.140

Residence countryside: No Construction 1950e1969: No Construction 1990e1999: No Construction 2000e2005: No Use solar: No Model Fitting

3.260 1.835 0.692 1.163 0.743 Goodness-of-Fit

1.285 6.438 0.678 7.336 0.411 2.839 0.395 8.675 0.306 5.909 Pseudo R-Square

2 LL ¼ 85.444 c2 ¼ 31.994 p ¼ 0.000

Pearson c2 ¼ 29.215 p ¼ 0.558

Cox & Snell ¼ 0.182 Nagelkerke ¼ 0.194 McFadden ¼ 0.071

Upper

0.054 0.038 0.052 0.022

0.015 1.535 0.040 1.473 0.006 1.268 0.137 1.734 Test of Parallel Lines 2 LL ¼ 93.094 c2 ¼ 17.775 p ¼ 0.337

0.090 0.078 0.287 0.017

1.043 0.076 0.077 1.460 0.397 1.340 3.711 0.361 Test of Parallel Lines 2 LL ¼ 93.689 c2 ¼ 30.223 p ¼ 0.066

0.002 0.089 0.036 0.002 0.071 0.002 0.033 0.016

1.885 0.406 4.264 0.302 1.522 0.052 3.297 0.765 0.070 1.696 0.447 2.093 0.123 3.017 1.704 0.172 Test of Parallel Lines 2 LL ¼ 129.426 c2 ¼ 2.297 p ¼ 1.000

0.011 0.007 0.092 0.003 0.015

5.778 0.742 0.507 3.163 0.113 1.498 0.389 1.938 1.342 0.144 Test of Parallel Lines 2 LL ¼ 79.071 c2 ¼ 6.373 p ¼ 0.973

Standardized regression coefficient (beta). Standard error. Significance. Confidence intervals. Log likelihood. Chi-square statistic. Probability value (p-value).

acceptable payback period, it is indicated that around 30%e40% of the respondents would be willing to invest in the system. This is a result that takes into account not only the installation cost, but the operation & maintenance costs of the system as well. The advantage of the hybrid system, in terms of higher efficiency and lower operation cost compared to conventional systems, leads to quite favorable results when referring to acceptable payback period. In any case, the above results highlight that consumers are favorable towards the adoption of the system; the low operation cost of the system ecompared to conventional systems- is one of the main assets of the system, however its installation cost can create a barrier for its adoption, as it is higher than the installation cost that most consumers would be willing to accept. The above outcome confirms the findings of previous works [42,44], according to which WTP for microgeneration technologies is significantly lower than actual market prices; as Scarpa and Willis [42] mention: “renewable energy adoption is significantly valued by households,

this value is not sufficiently large, for the vast majority of households, to cover the higher capital costs of micro-generation energy technologies”. The results of the study indicate that the diffusion of the hybrid system in households requires some additional actions; public policy financial incentives or a reduction of the installation cost of the technology could offer a boost to the system’s promotion. Nevertheless, as noted by Claudy et al. [44], these policies can be proven costly and non-viable, while options that are more marketbased (consumer finance, leasing and fee-for-service models) could be more feasible. Furthermore, focusing in the installation of the system in new constructions can lead to a lower installation cost compared to attempting to adjust the system in existing buildings. The attitudes of the respondents on the issues under investigation are common between the three countries; the only difference identified indicates that the Portuguese have a lower WTP compared to the Spaniards and the Greeks. The common intentions

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Table 7 Ordinal logistic regression models for Portugal: Socioeconomic and residence characteristics affecting the issues under investigation related to the hybrid system. Estimate

B

S.E.

Wald

Sig.

95% C.I. Lower

Upper

Perceived benefits

Residence village: No Size <100m2:No Construction <1999: No Income very difficult to cope with: No Education postsecondary: No Education first tertiary: No Profession unemployed: No Model Fitting 2 LL ¼ 111.164 c2 ¼ 49.868 p ¼ 0.000

1.695 1.428 0.962 1.949 3.079 1.191 2.519 Goodness-of-Fit Pearson c2 ¼ 79.772 p ¼ 0.999

0.839 4.079 0.413 11.963 0.401 5.758 0.904 4.651 1.021 9.087 0.418 8.113 1.012 6.199 Pseudo R-Square Cox & Snell ¼ 0.367 Nagelkerke ¼ 0.387 McFadden ¼ 0.154

0.043 0.001 0.016 0.031 0.003 0.004 0.013

3.339 0.050 0.619 2.237 1.747 0.176 3.721 0.178 5.081 1.077 20.011 0.372 0.536 4.502 Test of Parallel Lines 2 LL ¼ 89.038 c2 ¼ 22.126 p ¼ 0.775

Willingness to adopt

Type detached single: No Construction <1999: No Heating solar: No DHW electricity: No Income 1000e1500V: No Income 1500e2000V: No Education: Lower secondary or second stage of basic Education: Upper secondary Education: Post-secondary, non-tertiary Education: First stage of tertiary Profession self-employed: No Model Fitting 2 LL ¼ 222.148 c2 ¼ 51.580 p ¼ 0.000

0.939 0.914 2.470 1.046 1.234 1.088 20.273 0.142 2.309 0.402 0.869 Goodness-of-Fit Pearson c2 ¼ 248.104 p ¼ 1.000

0.463 4.114 0.384 5.664 0.785 9.896 0.453 5.336 0.480 6.612 0.514 4.481 0.000 e 1.171 0.015 0.956 5.829 0.416 0.933 0.455 3.642 Pseudo R-Square Cox & Snell ¼ 0.380 Nagelkerke ¼ 0.395 McFadden ¼ 0.148

0.043 0.017 0.002 0.021 0.010 0.034 e 0.903 0.016 .334 0.056

1.846 0.032 1.666 0.161 0.931 4.010 1.934 0.159 0.293 2.175 0.081 2.095 20.273 20.273 2.437 2.152 0.435 4.183 0.414 1.218 1.762 0.023 Test of Parallel Lines 2 LL ¼ 165.644 c2 ¼ 56.504 p ¼ 0.604

Willingness to pay

Size 50e100m2: No Income >3000V: No Income <1000V: No Income for energy <10%: No Profession public sector: No Model Fitting 2 LL ¼ 77.515 c2 ¼ 26.195 p ¼ 0.000

1.270 1.578 1.741 1.279 0.914 Goodness-of-Fit Pearson c2 ¼ 38.275 p ¼ 0.784

0.484 6.876 0.730 4.671 0.633 7.565 0.451 8.036 0.464 3.881 Pseudo R-Square Cox & Snell ¼ 0.214 Nagelkerke ¼ 0.252 McFadden ¼ 0.128

0.009 0.031 0.006 0.005 0.049

2.219 0.321 3.009 0.147 0.501 2.982 0.395 2.164 0.005 1.823 Test of Parallel Lines 2 LL ¼ 68.879 c2 ¼ 8.635 p ¼ 0.567

Acceptable payback period

Invested in thermal energy systems in the last 5 years: No Size <100m2: No DHW same as heating: No Income >3000V: No Model Fitting 2 LL ¼ 88.148 c2 ¼ 21.821 p ¼ 0.000

0.777 1.454 1.021 1.444 Goodness-of-Fit Pearson c2 ¼ 26.874 p ¼ 0.944

0.377 4.250 0.399 13.297 0.407 6.295 0.676 4.564 Pseudo R-Square Cox & Snell ¼ 0.181 Nagelkerke ¼ 0.194 McFadden ¼ 0.072

0.039 0.000 0.012 0.033

1.516 0.038 2.236 0.673 1.819 0.223 2.768 0.119 Test of Parallel Lines 2 LL ¼ 74.747 c2 ¼ 13.401 p ¼ 0.341

between the three countries are based on the similar conditions between them, in terms of climate, economic, housing and market conditions. These findings indicate that a common approach towards the diffusion of hybrid systems in the three countries could be feasible. In this context, best practices related to awareness activities, regulations, installation licensing and financial tools (e.g. grants, subsidies) could be exchanged between the three countries. The results of the behavioral survey indicate that there are specific socioeconomic and residence characteristics that affect consumers’ perceptions regarding the hybrid system’s benefits, WTA, WTP and acceptable payback period. Not all characteristics have a statistically significant impact in all countries and on all issues under investigation; however, the effect (positive or negative) of each characteristic has been identified to be the same in all cases. First of all, gender has been found to affect some of the issues under investigation, with male respondents being willing to pay a higher amount and accept a longer payback period for the hybrid system. The level of education is a factor that has been found to positively affect all issues under investigation, especially in Portugal and Spain; respondents with a higher education level are more likely to positively perceive the benefits of the system, more likely to be

willing to adopt the system, more receptive to higher installation costs and payback periods. This finding might be related to the fact that people of higher education being more aware of the long-term benefits of such systems, thus making them more willing to pay more, or wait for a longer period to have their investment paid back. Furthermore, type of occupation (self-employed) and involvement in energy and/or environmental fields are factors that affect positively WTA and WTP; these results can be parallelized with the result of a previous study, according to which science literacy is a factor that leads to higher WTA and WTP [46]. The above findings make clear the need of communication and dissemination activities in the context of the diffusion of such a system, in order to reach people with a lower educational level or with an occupation or interests not related to the environmental and energy sectors. Total monthly income has been identified to positively affect all examined issues; as expected, consumers with a higher than average income, living comfortable on their present income, are more likely to be positive towards the adoption of the hybrid system, accept a higher installation cost and a longer payback period. These results confirm Jingchao et al. [46], which state that income

S. Karytsas et al. / Renewable Energy 142 (2019) 591e603

599

Table 8 Ordinal logistic regression models for Spain: Socioeconomic and residence characteristics affecting the issues under investigation related to the hybrid system. Estimate

B

S.E.

Wald

Sig.

95% C.I. Lower

a

Upper

Perceived benefits

Invested in TES in the last year: No Residence village: No Size 50e100m2: No Bedrooms 3: No Income 2500e3000V: No Model Fitting 2 LL ¼ 114.167 c2 ¼ 21.159 p ¼ 0.001

1.045 1.138 0.646 0.725 1.293 Goodness-of-Fit Pearson c2 ¼ 66.840 p ¼ 0.834

0.485 4.643 0.664 2.935 0.330 3.824 0.350 4.295 0.763 2.870 Pseudo R-Square Cox & Snell ¼ 0.148 Nagelkerke ¼ 0.155 McFadden ¼ 0.052

0.031 0.087 0.051 0.038 0.090

1.995 0.094 0.164 2.439 0.001 1.293 1.410 0.039 0.203 2.789 Test of Parallel Lines 2 LL ¼ 91.694 c2 ¼ 22.473 p ¼ 0.608

Willingness to adopt

Invested in TES in the last year: No Residence village: No Construction 2000e2005: No Construction after 2010: No DHW solar: No Income for energy<10%: No Education up to postsecondary: No Model Fitting 2 LL ¼ 190.716 c2 ¼ 38.482 p ¼ 0.000

0.622 2.129 1.305 1.498 0.862 0.927 0.868 Goodness-of-Fit Pearson c2 ¼ 193.950 p ¼ 0.211

0.467 1.774 0.699 9.270 0.421 9.608 0.660 5.149 0.395 4.764 0.335 7.671 0.411 4.466 Pseudo R-Square Cox & Snell ¼ 0.253 Nagelkerke ¼ 0.261 McFadden ¼ 0.084

0.183 0.002 0.002 0.023 0.029 0.006 0.035

1.537 0.293 0.758 3.499 0.480 2.130 0.204 2.792 1.636 0.088 0.271 1.583 0.063 1.672 Test of Parallel Lines 2 LL ¼ 156.510 c2 ¼ 34.207 p ¼ 0.506

Willingness to pay

Bedrooms up to 2: No Construction <1949: No Construction <1989: No Coping on present income: No Income <2500V: No Education up to upper secondary: No Model Fitting 2 LL ¼ 114.518 c2 ¼ 26.156 p ¼ 0.000

0.990 1.325 1.207 0.636 0.929 1.387 Goodness-of-Fit Pearson c2 ¼ 70.624 p ¼ 0.524

0.422 5.498 0.604 4.814 0.376 10.315 0.345 3.394 0.439 4.475 0.648 4.579 Pseudo R-Square Cox & Snell ¼ 0.180 Nagelkerke ¼ 0.199 McFadden ¼ 0.084

0.019 0.028 0.001 0.065 0.034 0.032

0.162 1.817 0.141 2.509 1.944 0.471 0.041 1.314 0.068 1.789 0.117 2.658 Test of Parallel Lines 2 LL ¼ 108.013 c2 ¼ 6.505 p ¼ 0.889

Acceptable payback period

Bedrooms 2: No Construction <1949: No Construction <1989: No Heating solar: No Income 500e1000V: No Gender: Female Education up to upper secondary: No Model Fitting 2 LL ¼ 157.945 c2 ¼ 29.627 p ¼ 0.000

1.034 1.191 0.979 1.063 1.049 1.004 1.164 Goodness-of-Fit Pearson c2 ¼ 125.469 p ¼ 0.085

0.425 5.923 0.575 4.292 0.361 7.357 0.557 3.640 0.524 4.012 0.404 6.185 0.572 4.141 Pseudo R-Square Cox & Snell ¼ 0.201 Nagelkerke ¼ 0.212 McFadden ¼ 0.075

0.015 0.038 0.007 0.056 0.045 0.013 0.042

0.201 1.866 0.064 2.318 1.686 0.271 2.154 0.029 0.023 2.075 1.795 0.213 0.043 2.285 Test of Parallel Lines 2 LL ¼ 157.448 c2 ¼ 0.497 p ¼ 1.000

a

Thermal energy storage.

35%

31% 29%

30%

29%

Strongly Disagree Disagree

25%

Slightly Disagree

20%

Neither Agree nor Disagree Slightly Agree

15% 10%

Agree

5% 0% Greece

Portugal

Spain

Strongly Agree

Fig. 2. Perceived benefits from the adoption of the hybrid system.

has a positive effect on WTA and WTP. Consumers offering a low percentage of their income for energy expenses are less likely to be willing to adopt and be willing to pay a higher amount for the hybrid system; this can be related to the fact that consumers using a small part of their income for energy costs are not so probable to

benefit ein economic terms- from the installation of such a system. Moreover, residence-related factors have been found to significantly affect consumers’ intentions. These results contribute to the findings of previous studies [60,66,69e72], suggesting that adoption of heating systems is related to socioeconomic and residence

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30%

27%

27%

27%

Strongly Disagree Disagree

20%

Slightly Disagree

10%

Neither Agree nor Disagree Slightly Agree Agree

0% Greece

Portugal

Spain

Strongly Agree

Fig. 3. Willingness to adopt the hybrid system.

60%

0-3000€

65%

70%

3000-6000€

52%

50%

42%

40%

6000-10000€ 10000-20000€

30% 20%

>20000€

10% 0% Greece

Portugal

Spain

regardless of the price

Fig. 4. Willingness to pay for the installation of the hybrid system.

0-3 years

50% 40%

40%

38%

36%

3-5 years

30%

5-8 years

20%

8-10 years

10%

10-15 years

0% Greece

Portugal

Spain

regardless of the payback period

Fig. 5. Acceptable payback period in order to install the hybrid system.

characteristics. The type of the dwelling can have an impact, with people residing in building apartments being less probable to be willing to adopt the system and to accept higher installation costs, compared to people living in attached or detached single houses. Year of construction, or large innovation of the building, also has been found to have an effect on all issues under examination. People living in older houses (constructed before 1990) are more likely to have a more positive view towards the hybrid system’s benefits, to be more willing to install the system and accept higher installation costs and payback periods. This finding is related to the fact that consumers residing in newer houses (with newer heating/ cooling/DHW systems) are not so favorable of replacing their existing systems, since a) they may not compare so badly in relation to the hybrid system (in efficiency and economic terms) and b) their investment cost may have not yet paid back. However, in some

cases, when the houses are very old there seems to be a negative effect on WTP and acceptable payback period; perhaps, consumers believe that the investment and application of an innovative hybrid system in very old building is not so feasible in economic and technical terms. The size of the house (measured either in m2 or in number of bedrooms) also has been found to have a significant impact, with people living in larger houses having a more positive view towards the perceived benefits of the system, WTP and acceptable payback period. These findings could be interpreted in many ways: a) larger houses could imply a higher income, which eas mentioned aboveis related to higher WTA, WTP and payback period; b) larger houses are usually constructed in the form of single houses, which again has been found to be a statistically significant factor; c) larger houses have higher heating/cooling eand possibly DHW- needs,

S. Karytsas et al. / Renewable Energy 142 (2019) 591e603

thus making the adoption of the hybrid system more attractive. However, in the case of Portugal, house size has been found to have a negative effect on WTP and acceptable payback period; in this case people living in smaller houses (less than 100 m2) are more likely to be willing to pay a higher amount and to accept a higher payback period for the system’s installation. Area of residence is also a factor that has been found to affect all the issues under investigation. The findings can be related to the work of Ruokamo [56], according to which consumers living in rural areas are not as restricted by heating system space requirements, compared to those living in towns and cities. However, in the present study it is the only factor, alongside with dwelling size, which has been found to have mixed effects (positive/negative) among the different countries and issues under investigation. Specifically, residing in a rural area has a positive effect in the cases of Greece and Portugal, while a negative effect on the case of Spain. Current energy sources used for space heating and DHW also have been found to have an impact on the issues under examination. In the case of Greece, households using heating oil and natural gas for heating are less likely to have a positive perception of the hybrid system’s benefits and less likely to be willing to pay a higher amount for the hybrid system. In the same context, respondents in Portugal using conventional sources (electricity, heating oil, natural gas) for DHW are more likely to be willing to adopt and to accept a higher payback period for the hybrid system. Furthermore, consumers already using solar thermal panels are more probable to be willing to adopt the hybrid system and to accept a longer payback period; this could be explained by the fact that these consumers are more familiar with such technologies, and have seen the benefits that RES systems can offer, thus being more positive towards their adoption. On the same basis, past investments in thermal energy systems/energy storage systems during the last 5 years have a positive effect on perceived benefits, WTA and acceptable payback period. The only result that contrasts all the above mentioned findings is that in the case of Portugal consumers using a solar thermal system for space heating are less likely to be willing to adopt the hybrid system; perhaps they are less willing to adopt an innovative hybrid system, since they are already using an alternative heating system. 5.1. Study limitations and future research The positive views on the issues under investigation in this study may be overestimated compared to the corresponding values of the general populations of the three countries, due to overrepresentation of respondents with high education and high involvement in energy and/or environmental fields. This occurs due to the possibility that internet surveys may not create a sample as representative as a telephone or a face-to-face survey [73,74], making it difficult to generalize conclusions on non-internet populations [75]. However, although this sample is not totally representative of the population, it can provide a good basis for the examination of the factors that affect issues related to the adoption of a hybrid system. Moreover, an overestimation of the examined issues could result due to the hypothetical nature of the survey, based on self-reported intentions of the respondents, rather than real decisions. A future study could focus on the investigation of real decisions on these issues; a qualitative survey could be applied, rather than a quantitative one, in order to overcome the small number of households having installed the specific type of system. This study could also support the conduction of a comparison between installers and non-installers. Another limitation of the study is that it evaluates the effect of socioeconomic and residence characteristics on the issues under

601

examination, without taking into account the characteristics related to consumers’ system attributes preferences. Further research could deal with the investigation of these characteristics, in combination with socioeconomic and residence factors. Apart from the above, future research could examine the factors (financial incentives, regulatory improvements, information/ demonstration activities, etc.) that could assist the diffusion of residential hybrid heating systems. Likewise, further work could deal with all the factors mentioned above, expanding the focus group from residential to commercial installations. These research themes could assist policy makers to identify the best policies in terms of these types of systems. 6. Conclusion The present work investigates the intentions of consumers in Greece, Portugal and Spain, concerning perceived benefits, WTA, WTP and acceptable payback period of a residential hybrid system offering heating, cooling and DHW. Consumers have a positive view towards the benefits and adoption of the system. Additionally, the comparison of the results on WTP and acceptable payback period with the corresponding estimated values [25] reveals that although installation cost of the system may create a barrier for its diffusion, there is a potential market for the hybrid system in the three European countries. The analysis reveals that consumers’ intentions are similar in the three countries, with the only statistical significant difference occurring between Spain and Portugal regarding WTP for the system. Although the results slightly differ for each issue under investigation among the three countries, a general approach is that respondents a) with: a higher than average income, a high level of education, an occupation relevant to energy/environment, b) living in a residence that: is outside urban areas, not newly constructed, not in an apartment building, has an higher than average size, c) using conventional sources for heating and DHW (heating oil, natural gas, electricity), d) spending a higher than average percentage of their income for household energy needs and e) having made investment in thermal energy systems/storage in the past few years, are more likely to have a more positive perspective of benefits and willingness to adopt, and to present a higher level of WTP and acceptable payback period for the hybrid system. The present study provides useful information on the behavior of residents of three different European countries, regarding the adoption of a residential hybrid system offering heating, cooling and DHW production. The results of the study can offer a basis for the successful promotion of RES technologies providing heating/ cooling and domestic hot water in households. Acknowledgements The work is supported by TESSe2b project which has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 680555. The authors would like to acknowledge the project partners -apart from CRES- that contributed to the development of the questionnaire (IPS, TEI STE, ECOSERVEIS and GEOTEAM) and the conduction of the survey in Greece (TEI STE), Portugal (IPS) and Spain (ECOSERVEIS). References [1] N. Isaacs, M. Camilleri, L. French, A. Pollard, K. Saville-Smith, R. Fraser, P. Rossouw, J. Jowett, Energy Use in New Zealand Households. Report on the Year 10 Analysis for Household Energy End-Use Project, HEEP), 2006, pp. 77e78. [2] Eurostat - European Commission, Energy, Transport and Environmental

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