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Article

Ranking the Barriers to the Energy Upgrading of Buildings Using the Best-Worst Method

by
Fani Antoniou
* and
Theofilos Mageiropoulos
Department of Environmental Engineering, International Hellenic University, 57400 Sindos, Thessaloniki, Greece
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(22), 10143; https://doi.org/10.3390/su162210143
Submission received: 13 September 2024 / Revised: 1 November 2024 / Accepted: 15 November 2024 / Published: 20 November 2024
(This article belongs to the Special Issue Innovative Risk Management and Sustainable Practices in Construction)

Abstract

:
The global need to reduce energy demand has led European governments to accelerate their endeavors to achieve their targets regarding nearly zero-energy buildings. Despite the implementation of funding initiatives for the energy upgrading of buildings in EU member states and other European countries, research has shown that the absorption rates of the offered funds remain low. This research aims to assess the significance of the barriers to improving the energy efficiency of Greece’s building stock. This is achieved by ranking the identified barriers using the best-worst method (BWM). The innovation provided by this study is that the data obtained are based on the experience of three categories of stakeholders, including professionals in the field, i.e., engineers and skilled workers, and homeowners. The results show that all three groups are discouraged from performing the energy upgrading of buildings due to economic barriers but also technological barriers related to a lack of training in the use of and slow development of related new technologies.

1. Introduction

Recent research on global energy consumption has identified that the industrial, transport, and building sectors consume the most energy [1]. More specifically, the building sector in the European Union (EU) is responsible for 40% of the EU’s total energy consumption and 10% of its total CO2 emissions [2]. The high energy consumption and increased levels of greenhouse gases produced by this sector come primarily from the increased needs of buildings for heating, cooling, lighting, and using electrical appliances. Hence, the energy upgrading of buildings (EUoB) is one of the most critical areas that needs to be focused on to achieve the EU’s sustainability targets regarding the reduction in energy consumption.
In order to align its policies with the EU directives, Greece first made it mandatory to obtain an energy performance certificate based on the methodology defined in the Greek Regulation for the Energy Efficiency of Buildings [3] for new buildings and the sale or renting of existing buildings, and then proceeded to develop the National Energy and Climate Plan (NECP) for 2030 [4] and the Long-Term Strategy (LTS) for 2050 [5]. The LTS is a guide for the transition to a climate-neutral economy by 2050 based on the EU’s targets. Its main priorities are to improve energy efficiency, develop renewable energy sources, promote the electrification of transport and heating, and develop alternative domestic fuels, including biomass gas.
To promote these policies for the EUoB, the Greek government has launched a series of energy-saving programs, some of which are co-financed by EU funds. The main objective of these programs is to provide financial assistance to encourage people to invest in the improvement of the energy efficiency of their property. The first program for the energy upgrading of residential homes in Greece was implemented in 2012. A total of seven programs have been implemented so far for the EUoB. These programs differed in terms of the grant or loan amounts, as well as in terms of the income categories of the beneficiaries. A common factor was the eligible expenditure (e.g., the replacement of door and window frames, external insulation, heating system improvements) for the purpose of upgrading the energy performance of buildings. It should also be noted that one of the programs targeted young people with a larger grant (Exoikonomo-Renovate for the young). In addition to the above, a program for public buildings has recently been initiated (Electra, 2022, budget: EUR 640 million), and a program for the energy upgrading of businesses is planned (budget: EUR 200 million).
However, research has shown that the absorption rates of the offered funds remain low [6,7]. Indicative barriers to the EUoB in Greece are the lack of efficient program publicity, the lack of incentives, and the bureaucratic process to be subsidized [6]. In addition, Antoniou et al. [6] found that the reluctance of owners to proceed to the EUoB is also due to their distrust in the capability of workers in using modern eco-materials. These observations are similar to those made by Mulligan et al. [8] regarding barriers to green building policies in the US and particularly the state of Michigan.
This research aims to identify and assess the significance of the barriers that appear in the effort to improve the energy efficiency of Greece’s building stock. This is achieved by ranking the barriers identified in the literature and rated by survey participants by using the best-worst method (BWM), a multi-criteria decision-making (MCDM) method. The innovation provided by this study is that the data obtained are based on the experience of three categories of stakeholders through questionnaires, including professionals in the field, i.e., engineers and skilled workers, and homeowners. It was considered particularly important to record the owners’ opinions, as they have a significant role in the dissemination of the need for and the implementation of the EUoB, and it was found that only 5 out of the 50 articles reviewed considered their opinions on the challenges involved.
Therefore, the research questions that were formulated are as follows:
  • What are the most significant barriers to the EuoB, according to professional engineers?
  • What are the most significant barriers to the EuoB according to skilled workers?
  • What are the most significant barriers to the EuoB according to homeowners?
  • How do the results compare to international research?
The following section includes a description of the literature review that determined the gap in this literature and provided a comprehensive list of potential barriers to be rated by the survey participants, as elaborated in Section 3. Section 4 describes the BWM and how it was applied to the research problem, including data collection, analysis, and results. Section 5 discusses the results, while the final section includes the conclusions, proposals, limitations, and ideas for further research.

2. Literature Review

Initially, a review and content analysis of the existing literature was carried out to identify the most frequently documented barriers to the EUoB. The literature review was conducted by searching through the scientific research databases Scopus, Science Direct, and Google Scholar. Three searches using the following phrases as keywords were conducted: “Green buildings barriers”, “energy efficiency buildings barriers”, and “energy-efficient buildings barriers”. The first returned 890, the second returned 1068, and the third returned 697 documents, thus verifying the observations of Cristino et al. [9], who found that research in the field of energy efficiency in the construction industry has been particularly prolific in the last decade showing an increasing trend over the last twenty years (Figure 1).
Initial observations included the fact that, in the last two decades, there has been a large amount of research in the field of sustainable development and the EUoB. In addition, terms such as “green buildings”, “near-zero net carbon buildings (nZCB)”, and “near-zero energy buildings (nZEB)” have appeared. Researchers such as Wilson and Tagaza [10], Richardson and Lynes [11], Mokhtar Azizi et al. [12], and Zhang et al. [13] investigated these issues, while others dealt with the energy efficiency rating systems [14,15].
A total of 50 publications, which included references to barriers encountered in the effort to upgrade the energy performance of buildings, were selected and underwent a detailed content analysis. The inclusion criteria for the selection of the 50 publications were articles that were published in journals and that examined barriers encountered in the EUoB, excluding industrial buildings. The chronological distribution of publications studied in this research is shown in Figure 2.
Five of the fifty papers studied that were published from 2014 onwards attempted to rank barriers. Each study grouped the barriers differently into three to six categories. After categorization, the barriers are ranked according to their significance but with a different methodology in each study [9,16,17,18,19]. As far as the evaluation and rating of the significance of the barriers are concerned, these studies used different methods to derive their conclusions. In most studies, the opinion of experts in the building construction sector, whether they were engineers, contractors, or researchers in the field of energy efficiency, was requested to verify the existence of the observed barriers. In addition, publications were found that focused on a specific category of barriers, such as institutional barriers [20] and market barriers [21]. Other publications investigated those factors that prevent the EUoB in a specific region, such as China [22,23], the UK [24], and Ghana [17]. The gap found in these studies is that the opinion on the significance of the barriers was rarely sought from building owners who might be interested in upgrading the energy performance of their properties. Of the papers studied, only five [6,25,26,27,28] referred to owners.
As Greece has a 73.3% owner-occupancy rate, which is above the European Union average of 69.9% [29], the opinion of homeowners should be acknowledged. Also important is the opinion of the skilled workers, as they will be entrusted with the implementation of new methods for the EUoB, and according to the literature, skilled workers are considered one of the barriers to energy upgrading, as they are not considered adequately qualified in the use of green technologies [6].
These gaps were addressed in this paper by first collecting and categorizing the barriers that appear in the literature and then analyzing the data from the questionnaire survey by using the best-worst MCDM method. The questionnaires were distributed to engineers with experience in energy retrofitting (architects, civil engineers, energy inspectors), to skilled workers with experience in specific upgrading jobs (insulation, heating-plumbing installations, window frames, shading systems), and to homeowners.

3. Barriers to the EUoB

From the content analysis of the 50 selected articles, 289 barriers were recorded. After removing duplicates and performing an in-depth investigation of the remaining barriers to combine similar ones, 19 barriers emerged. Then, the barriers were divided into five categories, namely economic, institutional, professional and social, market, and technological barriers, in accordance with those used by Cristino et al., Djokoto et al., and Gupta et al. [9,17,18]. Table 1 shows all the papers and the barriers that each one referred to, while Table 2 presents their final categorization.

3.1. Economic Barriers

Economic barriers are one of the most critical categories, especially in Greece, as the country is struggling to return to growth after more than a decade of economic crisis. More specifically, high initial costs (E1) are defined as the funds required to start the works and purchase the materials for the EUoB. Indeed, these costs may be high as the replacement of heating units, for example, may require a complete replacement rather than a simple retrofit. In addition, the installation of solar water heaters and insulation and other works are also considered expensive.
Nevertheless, another economic barrier is the low return on investment (E2). This is because retrofits are costly, resulting in the properties needing more time to recoup these high costs. In addition, the homeowners may not live in the energy-upgraded property, so they may not benefit directly. For example, even if they increase the rental price, it still is not guaranteed that there will be a profit from this action. Instead, the tenant will feel immediate benefits with lower heating costs for example. Considering the above, it can be observed that landlords remain reluctant to upgrade the energy efficiency of their property investments. This problem (split incentives) is much more common in other EU countries, especially in larger cities, as there are lower rates of owner-occupation in these countries compared to Greece.
Greece’s socio-economic situation is at a different level than before the economic crisis. As a result, incomes have fallen significantly, and the funds available to citizens for investments such as in the EUoB are limited (E3). In addition, the financial crisis has also limited the frequency of bank loans. The last economic barrier is the final cost for the EUoB (E4). Upgrading older buildings carries the risk of additional work that may have yet to be foreseen. Also, secondary costs such as design fees and energy performance certificate costs have nothing to do with the required work but increase the final cost. It is also necessary to calculate the maintenance costs of the new improvements so that the rate of depreciation of the initial investment is minimized over the years.

3.2. Institutional Barriers

In addition to economic barriers, institutional barriers are also significant as they refer to the institutions, rules, and policies that can hinder investment. The political instability of previous years has resulted in governments not having the capacity to eliminate institutional barriers. Such barriers include insufficient incentives, a lack of guidelines, instructions, and evaluation standards, weak political will, different priorities, and the absence of a suitable building database.
Sometimes governments need to be able to provide the necessary incentives, either in the form of subsidies or tax exemptions, to make it easier for those concerned (E5). In other cases, the incentives provided have strict inclusion criteria with limited beneficiaries The European Union also assists by providing various funding programs, although the demand still needs to be met.
Varying governmental priorities may have led to the most prevalent barrier in the literature, which is the need for more guidelines and instructions (E6). This barrier, investigated in 28 out of the 50 studies, may discourage someone who expresses interest in energy upgrading but needs help in understanding the actions required. The absence of strict regulations when constructing or renovating buildings allows buildings to be built without the necessity of making them energy efficient. The primary objective in such cases is obtaining low construction or renovation costs rather than energy upgrading. According to the literature, in many parts of the world, there is no system for classifying buildings according to their energy performance, nor are there the necessary tools for their evaluation. Indeed, this is the case in less developed countries such as Ghana and Nigeria [17,34,36,37] or in countries with different priorities, such as China [52]. In the EU, stringent regulations and standards have now been set for both new buildings and the upgrading requirements for old buildings put to new uses.
Weak political will and different priorities (E7) are barriers to the EUoB in Greece because of the economic crisis and the COVID-19 pandemic, in accordance with the second most frequent barrier found in the literature. Different priorities that existed, such as reductions in labor costs and tax increases on materials and services, significantly reduced the construction of new buildings. However, the subsequent increase in energy prices because of the war between Ukraine and Russia brought to the forefront the need to limit energy consumption globally. Consequently, the climate regarding this barrier is beginning to reverse.
The last of the institutional barriers is the absence of building databases (E8). This is considered particularly critical as their use would enable more targeted upgrades. However, the absence of a database with the characteristics and requirements of each region, which are different (mountainous, island regions), and of a database with the architectural, structural, and construction characteristics of buildings in Greece makes it difficult to upgrade them more efficiently in terms of energy consumption.

3.3. Professional and Social Barriers

This category includes all those barriers that are related to people directly involved in the EUoB. They refer to difficulties that arise for professionals and homeowners. They are related to the inexperience of professionals in the application of new methods, new techniques, and the choice of materials necessary for the upgrading of buildings (E9). Regarding owners, there are problems of low awareness and information (E10), fear of failure and doubt about achieving the efficient EUoB (E11), and prejudice against new practices (E12). In addition, both professionals and owners may be discouraged by the increased time required (E13) and by the need for cooperation between multiple worker groups (E14).
The increasing demand for new types of energy-efficient materials, which require the necessary expertise to be applied and installed, has raised the problem of training professionals (E9). Both skilled workers and engineers need to be informed and trained in new techniques so that neither they nor the building owners who employ them feel insecure.
Lack of public awareness (E10) about energy efficiency of buildings, green buildings and all these new terms is the third most frequent barrier found in the literature. Efforts have recently been made to overcome this barrier prompted by the rise in energy prices, which has encouraged people to seek more environmentally friendly forms of energy for their economic benefit.
The fear of failure and doubt about achieving the desired energy efficiency goals of an energy upgrade plan is an emotional problem (E11), which can have a significant influence on the decision to proceed with energy upgrading because it causes anxiety and inhibitions. Furthermore, many owners, considering the size of the investment they will have to make to perform energy upgrading and needing to know the benefits, find it difficult to decide to upgrade their home.
A further cultural and social factor that has been recorded as having an impact on energy upgrading is the perceptions and attitudes of a community (E12). For example, some communities may need help adopting new technologies or techniques as they are used to and trust their traditional practices.
Delays in the work schedule are a problem frequently observed in all construction projects (E13). This is due to the number of complex activities involved. It is also considered a deterrent for cases where energy upgrading activities need to be executed in occupied buildings, which require additional coordination and communication skills.
Finally, a perceived professional barrier is the need for successful cooperation between different groups of workers (E14). For example, if there is no interaction between the external insulation contractor and the contractor who is to replace the door and window frames, they may not be installed correctly. This has the consequence of creating confusion, resulting in delays and poor quality.

3.4. Market Barriers

The category of barriers arising from the difficulties encountered in the market sector also makes an essential contribution to the obstructions to the EUoB. Companies are reluctant to invest in new products since consumer interest is low (E15). Customers are not interested in using new materials and techniques such as smart windows, vacuum insulating panels, or green roofs [6] to reduce the energy consumption of their homes or believe that they do not need them. The availability, cost, durability, and reliability of materials (E16) are also mentioned in the literature as a barrier. The availability of materials in local markets can be a significant risk during the construction stage. A lack of domestic suppliers may further complicate things, since it raises the cost of already more expensive environmentally friendly materials when they need to be imported. In addition, there is doubt about their reliability and durability over time as compared to the standard materials. The last market barrier concerns the lack of product promotion by companies to consumers (E17). Consumers are defined as the engineers and skilled workers who will use the materials and recommend them to the owners. Their lack of information means that they do not choose and do not trust newer products and tools [6].

3.5. Technological Barriers

Technological barriers include the incompatibility of systems (E18), which refers to the case where the required new technologies are not compatible with the existing infrastructure. Older buildings and infrastructure may need additional design and planning to support green technologies. Finally, the absence of exhibitions promoting green technologies (E19) can lead to insufficient knowledge and information about green technologies and their potential. Therefore, the lack of exhibitions could make it more difficult for the public and professionals to accept and adopt green technologies. Also, the absence of exhibitions may limit the development and improvement of green technologies.

4. Methodology

4.1. Best-Worst Method

MCDM methods are an essential part of the science of decision-making. Their purpose is to develop techniques and models for analyzing and solving problems in which decisions must be made based on multiple criteria. Through these methods, the comparison of options based on multiple criteria is achieved, allowing analysts and decision-makers to make more focused choices [59]. MCDM methods involve a process of gathering, evaluating, and comparing criteria to reach the final decision. Expert experience, judgment and input are used to evaluate each alternative against each criterion. By using these methods, it is possible to achieve a balanced and informed decision that considers the various aspects and priorities involved in the problem. Furthermore, MCDM methods have contributed significantly to the development of risk assessment methods by allowing the ranking of a list of occupational safety risks [60], delay factors [61] or environmental impacts [62]. By using MCDM methods, the decision-maker can evaluate the different options (in this case, barriers) to achieve a ranking in terms of their significance.
The BWM is one such method, introduced by Rezaei [63] to address some issues presented by the analytical hierarchy process (AHP), which until then was the most widely used method [64]. As Malek and Desai [65] noted, AHP leads to consistent and reliable results when there are many options to consider, and consequently, many comparisons are required. In contrast, in the BWM, fewer comparisons are made. The decision-maker first selects the best and worst criteria (barriers) and conducts pairwise comparisons between them and the other criteria. By solving this problem, the weights of the criteria are found. By using the same procedure, when comparing alternatives against each criterion, partial scores of the alternatives are calculated. The final scores of the alternatives are derived from the overall evaluation of the criteria weights and the alternative partial scores per criterion. A consistency check of the evaluations is also performed to ensure the reliability of the comparisons.
Compared to other MCDM methods, the BWM has certain features that set it apart and make it very popular among researchers [66]. First, it requires a smaller number of comparisons as the decision-maker compares and evaluates only the best and worst criteria relative to each other. Moreover, continuous comparisons are made with more reliable results. Based on statistical analyses, the BWM has a significantly better performance compared to the AHP [67].
The process begins with the identification of the criteria (c1, c2, …, cn) against which alternative options will be compared to arrive at a decision. In this study, the five barrier categories served as these criteria. Secondly, the decision-maker chooses which of the criteria is the best/most significant and which is the worst/least significant. In this step, no comparison is made using a numerical scale; only the selection of these two criteria is made. Essentially, this process can also be considered a comparison, since to select the best and the worst criteria, the options must be compared intuitively. In this study, the “best” category was the category that posed the most significant barriers to the EUoB, while the “worst” included the least significant barriers. Next, every other criterion (category) was compared against the best and worst ones using the numerical scale as defined in Table 3, adapted for this research.
It is noteworthy that the scale used in the BWM is the same as the scale used in the AHP. The evaluation of the best criterion against all other criteria is carried out using this scale. As a result, the best-to-others vector, AB = (aΒ1, aΒ2, …, aΒn), is produced, where aΒj indicates the preference of the best criterion (B) over the j criterion. Similarly, the evaluation of the other criteria (j) against the worst criterion (W) is again achieved using the numerical scale of 1 to 9, resulting in the others to worst vector, Aw = (a1W, a2W, …, anW) where ajW indicates the preference of the j criteria over the worst W.
Finally, the optimal weights for each criterion are those where for each pair wB/wj and wj/ww, we have wB/wj = aBj and wj/ww = ajW. To determine the weights, the following equation must be solved:
Min   Max   j   w B w j a BJ , | w j w W a j W |
subject to
j = 1 n w j = 1 , w j 0 , f o r   e v e r y   j
The above Equation (1) can be transformed into the following equation:
min ξ
subject to
w B w j a B j ξ , f o r   e v e r y   j
w j w w a j W ξ , f o r   e v e r y   j
j = 1 n w j = 1 , w j 0 , f o r   e v e r y   j
A pairwise comparison model is considered consistent
i f   a B j   ×   a j W = a B W , f o r   e v e r y   j
where aBW is the preference for the best against the worst criterion.
However, it is expected to allow a pairwise comparison system to deviate to some extent from the absolute consistency of the above relationship. For this reason, it is necessary to have a ratio that indicates the degree of coherence or consistency ratio in the decision-maker’s responses. The degree of consistency in the original BWM is measured by determining ξ*, which is the optimal value (the output) of the optimization model. Hence, it was named by Rezaei [63] output-based consistency measurement. The output-based consistency ratio (CRO) is given as follows:
C R O = ξ * ξ m a x
where ξ* is the optimal value of Equation (2) and ξmax is the maximum ξ from the solutions to Equation (5)
ξ 2 1 + 2 a B W ξ + a B W 2 a B W = 0
The range of CRO is [0.1]. The closer the CRO value is to 0, the more consistent the answers are. More specifically, if CRO = 0, then the responses are perfectly consistent.
The consistency ratio of the responses calculated in the initial BWM could only be obtained after the process was completed, which did not give the decision-maker an immediate insight into the consistency of their responses. To overcome this problem and to provide an immediate insight into the level of consistency of responses to the decision-maker, Liang et al. [68] proposed the measurement of consistency based on input. This is achieved using the input provided (i.e., their preferences) without the need to complete the consistency check process. Hence, it was called the input-based consistency ratio (CRI).
The consistency ratio based on the CRI is expressed as follows:
C R I = m a x j   C R j I
where
C R j I = a Bj   ×   a jW a BW a BW   ×   a BW 0 a BW     a BW   >   1 a BW = 1
CRI is the overall degree of consistency based on the inputs for all criteria.
CR I J represents the level of consistency associated with criteria j.

4.2. Data Collection

Data were collected using questionnaires to allow the researchers to capture the views of people who are not particularly familiar with the use of computers (for example, homeowners). Google Forms was used as a freely accessible application to convert the BWM-solving tool into a questionnaire.
Using the BWM solving tool, it was possible to verify the consistency of the responses directly. However, since responses were obtained through a questionnaire and were not provided by the respondent using the BWM solver tool directly, as most were not familiar with the use of MCDM methods, it was preferred that the questionnaire be completed in the presence of the researcher to check the consistency of the responses and point out any possible mistakes. The questionnaire was distributed to engineers and skilled workers who are professionally involved in EUoB and to homeowners as investors and beneficiaries of funding programs. All skilled workers and most homeowners provided responses in the presence of the researcher to provide immediate explanations at any point in the process where clarification was required. In contrast, the group of engineers answered the questionnaire without the presence of the researcher.
It should be noted that there are advantages and disadvantages to questionnaire-based surveys, where responses are given in the presence of the researcher. The main advantages are the ability of the researcher to clarify the questions and verify how seriously the research was taken by the respondent/interviewee. On the other hand, the disadvantage of this practice is that responses may be inadvertently and unconsciously influenced by the researcher [69]. In the initial stage of the questionnaire design, attention was given to the composition of the questions so that the process of pairwise comparisons would be easy to understand even when the researcher was not present.
A draft was given to two colleagues (1. Surveyor Engineer, MSc; 2. Civil Engineer, MSc) to record any omissions in the structure of the questionnaire and comprehension difficulties. After assessing their feedback, the questionnaire was finalized. It was considered that it would be easier for respondents to make comparisons using a smaller rating scale than the one used in the BWM. The rating scale selected was a 1 to 5 rating scale instead of the 1 to 9 numerical scale used by the BWM. The correlation was as follows:
  • 1 = 1 (Equal significance)
  • 3 = 2 (Moderately more significant)
  • 5 = 3 (Strongly more significant)
  • 7 = 4 (Very strongly more significant)
  • 9 = 5 (Extremely more significant)
Eliminating the intermediate values (2, 4, 6, 8) simplified the process considerably. Of course, it created more challenges in the final processing of the answers, which had to be converted back to the 1 to 9 scale so that the BWM solver could be used.
The questionnaire was distributed to three groups: engineers, skilled workers, and homeowners. In the first group, ten engineers were selected who have experience in the EUoB at various stages of the process, i.e., one architectural engineer with experience in energy design and bioclimatic architecture, seven civil engineers with experience in construction, renovation, and the EUoB, and two mechanical engineers who work as energy inspectors. The group of engineers were given clear instructions on the process of rating and comparing options according to the BWM and were informed about the purpose of the work.
The second group, the skilled workers, consisted of ten (10) people who have various specialties and have been actively involved for several years in various fields. More specifically, the questionnaire responses were provided by four skilled workers involved in residential insulation, three skilled workers involved in energy-efficient window frames, two skilled workers involved in solar water heater and gas installation, and one skilled worker involved in shading systems.
The owners were of all age levels and from different regions. People from urban centers, the countryside, and the Greek islands took part in the survey. In total, 53 responses were obtained from owners who had made energy upgrades to their homes.
Initially, it was considered appropriate to create two questionnaire forms, one for the engineers and skilled workers and another for the owners. This was achieved to make it easier to process the responses later and to clearly separate the responses of the professionals from the owners’ responses. The only difference between the two forms was that the first question asked the professionals (engineers and skilled workers) about their years of experience in the EUoB. In contrast, the homeowners were asked if they had made energy upgrades to their property. Afterwards, the respondent’s email address was optionally asked for in both forms, and before the BWM comparisons began, there was a short informative text about the process explaining the scale on which the pairwise comparisons would be made.
The BWM begins with selecting the best (most significant) alternative. In the case of the present research, which aimed to rank the barriers to the EUoB, the best option was the one that discourages people from undertaking the process of energy upgrading and is considered the most significant obstacle to the EUoB. The first question was “Select which category of barriers to energy upgrading you consider to be the most significant”, with the following options:
  • Economic barriers (Cost, revenue, financing)
  • Institutional barriers (Guidelines-Laws, political determination, databases)
  • Professional and social barriers (knowledge, experience, awareness, doubts about the new)
  • Market barriers (Building materials: availability, cost, durability, reliability)
  • Technological barriers (Slow development and promotion of new technologies)
Next, the method compared the best (most significant) category chosen by the decision-maker with the other alternatives. For the convenience of the respondents, a Google Forms option was used whereby selecting an answer from the previous question, for example, “institutional barriers”, forwarded the respondent to the next question in which the option “institutional barriers” had been eliminated from the answers, i.e., “How much more significant do you consider the Institutional Barriers category compared to the other categories?”, having option to rate and compare the institutional barriers category against the others using a scale of 1–5.
Then, the worst (least significant) category was selected from the rest of the option by responding to the question “Select which category you consider as the least significant category of barriers to energy upgrading”, with the following options to respond:
  • Economic barriers (Cost, revenue, financing)
  • Professional and social barriers (knowledge, experience, awareness, doubts about the new)
  • Market barriers (Building materials: availability, cost, durability, reliability)
  • Technological barriers (Slow development and promotion of new technologies)
As shown above, to avoid confusion, the “Institutional Barriers” option was excluded. The remaining barriers were then compared against the worst (least significant) alternative. For example, if “Market Barriers” was selected as the least significant category in the previous question, the following question was “How much more significant do you consider other categories to be than the Market Barriers category?”, having option to compare the market barriers category against the others using a scale of 1–5.
This procedure was carried out six times in total: one time for ranking the categories (economic barriers, institutional barriers, professional and social barriers, market barriers, technological barriers) and once for ranking the barriers in each of the five categories separately.
To sum up, the data collection stage consisted of the following steps:
  • Identification and categorization of barriers.
  • Converting the BWM solver into a questionnaire.
  • Use of feedback from two engineers to optimize the questionnaire.
  • Finalization of the questionnaire.
  • Questionnaire distribution to 10 engineers, 10 skilled workers, and 53 owners.
  • Conversion of data from a scale of 1–5 to a scale of 1–9 for application of the BWM solver.

4.3. Data Analysis

Table 4, Table 5, Table 6, Table 7 and Table 8 below show the responses given by each engineer, after conversion to a scale of 1–9. For each group of responses, we used the BWM solver, except for the technological barriers group, since it included only two barriers for comparison. The BWM solver calculates the weights for each barrier category and the partial scores for each barrier in each category. Also, the BWM solver gives us the input-based consistency ratio (CRI) for each response, as shown in Table 4, Table 5, Table 6, Table 7 and Table 8. The results consistently provided a low CRI, close to 0, indicating consistent responses throughout.
Following this conversion process, these values were then used in the BWM solve-linear version-Excel file, as provided by the developer of the method, Rezaei (2016), to calculate the weights for the categories and the partial barrier scores per category for each respondent. Table 9 shows the resulting weights for each category by each engineer and the average result for all engineers. Similarly, Table 10, Table 11 and Table 12 present the resulting partial scores for each barrier per category and per engineer and the resulting average score.
Finally, to calculate the total score for each barrier so that they could be ranked based on their significance, each barrier’s partial score was multiplied by the weight of its category. For example, barrier E5, insufficient incentives, was calculated to have an average score of 0.321 (Table 10). Its category, K2, institutional barriers, has a weight of 0.209 (Table 9). Therefore, the final significance score for barrier E5, insufficient incentives, is 0.321 × 0.209 = 0.067 or 6.7%. Table 13 shows the final significance score of the barriers according to the aggregate opinions of the 10 engineers.
The same procedure as above was carried out for the other two categories of respondents (skilled workers and owners, resulting in Table 14, which shows the top 10 barriers in each group ranking, as well as the barriers with the highest frequency of occurrence in the literature survey).

5. Discussion

According to the survey results, financial barriers are the most significant for the EUoB. All group results show that the top three barriers, E1, E2, and E4, are related to costs, i.e., high initial costs, a lack of funds, and high final and maintenance costs. This is an expected result because of the country’s financial situation, as described in Section 3.1. An interesting observation is that the barrier in fourth place is different in each category. The homeowners and the engineers are consistently concerned with economic barriers, and therefore the homeowners rate the low rate of return on their investment as the fourth most important barrier, while the engineers support this opinion. Finally, in contrast with the other two categories, the skilled workers believe that two technological barriers, incompatible technology (E18) and the absence of exhibitions promoting new technologies (E19), are the next two most significant barriers. It is also noteworthy that the other two categories of respondents place these barriers in fifth place. When comparing these findings to the research carried out in the international literature, it can be observed that in other countries, institutional barriers and a lack of public awareness appear more often, followed by economic barriers. A common feature is that in both the literature review and in the current survey, the need for proper skills among professionals in the field is pointed out.
It is noteworthy that it was easier to explain the required pairwise comparison process to people who had higher levels of academic education. Despite the use of a smaller scale (1–5 instead of 1–9) in the questionnaire and the presence of the researcher during the completion of the questionnaire by the skilled workers and homeowners, challenges were encountered. A high degree of inconsistency was observed in the responses of the 10 homeowners who completed the questionnaire without the presence of the researcher. On the contrary, there was no difficulty in understanding or incorrect completion of the questionnaire on the part of the engineers.
Consequently, although it was essential to record the homeowners’ opinions on the barriers they have faced or that prevent them from upgrading the energy performance of their property, it was understood that a very large sample was not necessary. Therefore, the qualitative characteristics of the individuals (educational level) were the most crucial factor.
As far as MCDM methods are concerned, the BWM is more direct than other similar methods, such as AHP. An initial comparison between the alternatives is carried out “unconsciously”, selecting the best and the worst. Pairwise comparisons are then made using these initial choices as a measure. In contrast, in AHP, many more comparisons are made, which may result in more errors in the consistency of the answers. Nevertheless, like other MCDM methods, it has limitations in its application to more complex decision-making problems that could lead to misleading conclusions. For example, in the homeowners’ responses, the barrier (E18) “Incompatible technology, slow development” had a weighting factor of 0.609, and the group/category in which it is located, “Technological barriers” (K5), had a weighting factor of 0.095. The final significance rate of barrier E18 was calculated as 0.609 × 0.095 = 0.058 or 5.8%. As can be seen in this example, despite the fact that the category in which the barrier is located (K5) was given a low weighting rate, the barrier was ranked high because, in this category, there were only two alternatives (barriers) that had a cumulative weighting rate of E18 + E19 = 1.

6. Conclusions

According to these results, all three groups (engineers, skilled workers, and homeowners) consider economic barriers more critical. More specifically, high initial costs, a lack of funds, difficulty in securing loans, and high final and maintenance costs were ranked in the first positions. Despite the efforts of governments to promote energy upgrades through economic programs, this survey reflects that economic concerns persist. An essential factor in this is the economic crisis in recent decades, which has significantly reduced the incomes of citizens, and the energy crisis, which has significantly increased the cost of energy. Also, the lack of public information and promotion of materials was ranked high by both skilled workers and homeowners, indicating a need for better training so that workers can be adept in these new skills and better information can be made available to homeowners.
The results of this study show that it is vital to inform the public about the economic benefits of energy upgrades through reduced energy consumption and to promote green materials, which are wrongly perceived by many as expensive. Therefore, governments should take the importance of fully informing the public about all aspects of energy upgrading seriously, instead of just providing financial incentives. It is also necessary to understand that investment in energy upgrading will yield not only economic benefits but also an improvement in the quality of life within energy-upgraded buildings. Furthermore, the financial incentive programs (Exoikonomo) would be more effective if they were targeted at a more significant proportion of citizens. The income criteria that exist discourage families with incomes higher than the predefined incomes of the programs.
The skilled workers report that they need to be sufficiently trained to carry out such work. Furthermore, according to their responses, they need more confidence in new materials and practices to engage in energy retrofitting work. The above issue indicates how important it is to train professionals in the field through seminars to familiarize them with new techniques and materials.
The ranking of barriers to the EUoB was chosen to be carried out using the BWM, an MCDM method. As mentioned above, these methods also have limitations. For example, if a questionnaire had been created to assess the barriers on a scale of 1 to 5, without creating categories and without comparing them with each other, another method of analyzing results, such as the Relative Importance Index or descriptive statistics, could have been chosen. Using the BWM is feasible only if the elements to be compared are less than or equal to 9. As a result, to apply the method, the barriers needed to be split into categories, resulting in categories with more and others with fewer alternatives to be compared. Consequently, the final scores were affected. As noted, the five point rating scale used to facilitate responses from the participants neglected the intermediate values (2, 4, 6, 8). As a result, another limitation of this study is the possible loss of data that, if they had been captured, may have resulted in more distinct differences in the final rankings or better resulting consistency ratios. Finally, another limitation stemming from the chosen method is that the survey had a limited number of respondents because it was considered necessary to have the questionnaire completed in the presence of the researcher for the participant to understand the pairwise comparison process better. Therefore, since the BWM cannot map relationships among barriers, further research should be carried out based on a larger dataset and using other statistical methods such as the F-DEMATEL method employed by Yadav et al. [70] in parallel with the BWM for prioritizing enablers in the manufacturing supply chain in India or factor analysis used by Antoniou et al. [71] to determine relationships between construction contract type selection criteria.
For other future research directions, it would be beneficial to evaluate the success of the incentive programs that have been and are still being implemented. Creating a reliable database with all the characteristics of the economic programs and the energy upgrades carried out through them would make it possible to identify areas for improvement. In addition, conducting a similar survey on a larger scale and in combination with MDCM methods and Geographic Information Systems (GIS) will provide a better view of the whole territory. This would make it possible to better identify the problems encountered in each region of the country.

Author Contributions

Conceptualization, F.A.; Data curation, T.M.; Formal analysis, T.M.; Investigation, T.M.; Methodology, F.A.; Resources, F.A.; Validation, T.M.; Writing—original draft, T.M.; Writing—review and editing, F.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research has received no funding.

Institutional Review Board Statement

The International Hellenic University’s ethics committee confirms that this study does not require ethical approval because it doesn’t involve experiments on humans, etc.

Informed Consent Statement

Informed consent was obtained by all participants in the questionnaire survey.

Data Availability Statement

The original data presented in this study are included in this article; further inquiries can be directed to the corresponding authors.

Acknowledgments

The authors would like to thank all anonymous participants in the questionnaire survey and all reviewers for their constructive feedback that helped improve the quality of the paper.

Conflicts of Interest

The authors confirm that there are no relevant financial or non-financial competing interests to report.

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Figure 1. Number of documents published per year in Scopus-indexed journals returned following the keyword search “Green buildings barriers”.
Figure 1. Number of documents published per year in Scopus-indexed journals returned following the keyword search “Green buildings barriers”.
Sustainability 16 10143 g001
Figure 2. Chronological distribution of publications studied in this research.
Figure 2. Chronological distribution of publications studied in this research.
Sustainability 16 10143 g002
Table 1. Table of barriers per paper.
Table 1. Table of barriers per paper.
Reference Ε1Ε2Ε3Ε4Ε5Ε6Ε7Ε8Ε9Ε10Ε11Ε12Ε13Ε14Ε15Ε16Ε17Ε18Ε19
Antoniou et al. [6]2022
Austin [30]2012
Moktar Azizi et al. [12]2010
Bagaini et al. [19]2020
Berardi [31]2011
Blomqvist et al. [26]2022
Bloom et al. [15]2011
Bruce et al. [32]2014
Bui et al. [33]2022
Chegut et al. [16]2013
Chan et al. [34]2018
Cristino et al. [9]2021
Dadzie et al. [35]2018
Darko et al. [36]2018
Djokoto et al. [17]2014
Ebekozien et al. [37]2021
Gliedt and Hoicka [25]2015
Griffin et al. [14]2010
Gupta et al. [18]2017
Häkkinen et al. [38] 2011
Harmelink et al. [39]2008
Hirst and Brown [40]1990
Jakob [28]2007
Jones [41]2015
Karkanias et al. [42]2010
Landman [43]1999
Langlois-Bertrand [44]2015
Leung et al. [45]2013
Martin and Gossett [46]2012
IEA [21]2007
Moore [47]1994
Peterman et al. [48]2012
Du et al. [22]2014
Pitt et al. [49]2009
Power [50]2008
Li et al. [51]2020
Richardson and Lynes [11]2007
Samari et al. [52]2013
Shen et al. [53]2017
Theodoridou et al. [54]2011
van Bueren et al. [20]2002
Williams and Dair [24]2006
Wilson and Tagaza [10]2006
Richardson and Lynes [11]2016
Winston [55]2010
Wood [56]2007
WBC [57]2007
Yao and Li [23]2005
Zhang et al. [13]2011
Zhang et al. [58]2012
Frequency of occurrence18171418232826821251314610101817133
Table 2. Barriers to the EUoB in Greece.
Table 2. Barriers to the EUoB in Greece.
CategoryCodeBarriers
Economic Barriers (Κ1)Ε1High initial cost
Ε2Low rate of return on investment, low profitability
Ε3Lack of funds and difficulty in securing loans
Ε4High final and maintenance costs
Institutional Barriers (Κ2)Ε5Insufficient incentives
Ε6Lack of guidelines, instructions and evaluation standards
Ε7Weak political will. Different priorities
Ε8Absence of a proper building database
Professional and Social Barriers (Κ3)Ε9Inexperienced and unskilled professionals
Ε10Low awareness and lack of information
Ε11Fear of failure. Doubt about achieving desired goals
Ε12Prejudice against practices
Ε13Delays in work schedule
E14Cooperation between different groups of employees
Market Barriers (Κ4)E15Doubt from the markets about the demand for the products
E16Building materials (availability, cost, durability, reliability)
E17Insufficient public information and promotion of materials
Technological Barriers (Κ5)Ε18Incompatible technology. Slow development
E19Absence of exhibitions promoting new technologies
Table 3. Best-worst method criteria scale adapted for this study.
Table 3. Best-worst method criteria scale adapted for this study.
Numerical ScaleMeaning
1Equal significance
2Somewhere between equal significance and moderately more significant
3Moderately more significant
4Somewhere between moderately and strongly more significant
5Strongly more significant
6Somewhere between strongly and very strongly more significant
7Very strongly more significant
8Somewhere between very strongly and extremely more significant
9Extremely more significant
Table 4. Pairwise comparison ratings of barrier categories by the engineers.
Table 4. Pairwise comparison ratings of barrier categories by the engineers.
SpecialtyExperienceBarrier Categories
BESTΚ1Κ2Κ3Κ4Κ5WORSTΚ1Κ2Κ3Κ4Κ5 C R I
1Architect10+Κ117559Κ5935510.22
2Civil Eng.5–10Κ211353Κ4553130.2
3Civil Eng.5–10Κ231533Κ3331330.2
4Civil Eng.10+Κ113151Κ4333110.2
5Civil Eng.10+Κ117397Κ4937110.17
6Civil Eng.5–10Κ119799Κ2913330.25
7Civil Eng.5–10Κ291555Κ1195550.22
8Civil Eng.10+Κ113797Κ4973130.17
9Mech. Eng.10+Κ117797Κ4533130.17
10Mech. Eng.10+Κ117539Κ5933710.17
Table 5. Pairwise comparison ratings of economic barriers provided by the engineers.
Table 5. Pairwise comparison ratings of economic barriers provided by the engineers.
SpecialtyExperienceEconomic Barriers
BESTΕ1Ε2Ε3Ε4WORSTΕ1Ε2Ε3Ε4 C R I
1Architect10+Ε45751Ε231370.19
2Civil Eng.5–10Ε31313Ε231310
3Civil Eng.5–10Ε31513Ε231310.1
4Civil Eng.10+Ε31713Ε211330.14
5Civil Eng.10+Ε21159Ε479310.08
6Civil Eng.5–10Ε39715Ε113930.17
7Civil Eng.5–10Ε11955Ε291550.22
8Civil Eng.10+Ε35919Ε231930.25
9Mech. Eng.10+Ε39515Ε115750.22
10Mech. Eng.10+Ε35319Ε453910.22
Table 6. Pairwise comparison ratings of institutional barriers provided by the engineers.
Table 6. Pairwise comparison ratings of institutional barriers provided by the engineers.
SpecialtyExperienceInstitutional Barriers
BESTΕ5Ε6Ε7Ε8WORSTΕ5Ε6Ε7Ε8 C R I
1Architect10+Ε63195Ε759150.22
2Civil Eng.5–10Ε67133Ε513330.10
3Civil Eng.5–10Ε51137Ε875510.19
4Civil Eng.10+Ε61131Ε733130
5Civil Eng.10+Ε89591Ε513190.08
6Civil Eng.5–10Ε51735Ε691330.19
7Civil Eng.5–10Ε65159Ε859510.22
8Civil Eng.10+Ε51937Ε691730.17
9Mech. Eng.10+Ε51797Ε773130.17
10Mech. Eng.10+Ε79515Ε513750.22
Table 7. Pairwise comparison ratings of professional and social barriers provided by the engineers.
Table 7. Pairwise comparison ratings of professional and social barriers provided by the engineers.
SpecialtyExperienceProfessional and Social Barriers
BESTΕ9Ε10Ε11Ε12Ε13Ε14WORSTΕ9Ε10Ε11Ε12Ε13Ε14 C R I
1Architect10+Ε14575911Ε125351990.22
2Civil Eng.5–10Ε13335313Ε113313330.2
3Civil Eng.5–10Ε14133511Ε125131570.2
4Civil Eng.10+Ε14117311Ε117515350.19
5Civil Eng.10+Ε12555199Ε135559110.22
6Civil Eng.5–10Ε10111375Ε139973130.10
7Civil Eng.5–10Ε10515595Ε135955150.22
8Civil Eng.10+Ε13795515Ε103155950.22
9Mech. Eng.10+Ε10917777Ε91933330.16
10Mech. Eng.10+Ε10915779Ε143933310.25
Table 8. Pairwise comparison ratings of market and technological barriers provided by the engineers.
Table 8. Pairwise comparison ratings of market and technological barriers provided by the engineers.
Specialty Experience Market Barriers Tech. Barriers
BEST Ε15 Ε16 Ε17 WORST Ε15 Ε16 Ε17 C R I BEST Ε18 Ε19
1Architectural10+Ε16915Ε151730.08Ε1971
2Civil Eng.5–10Ε17731Ε151330.10Ε1813
3Civil Eng.5–10Ε17731Ε151370.05Ε1951
4Civil Eng.10+Ε17531Ε151130.10Ε1817
5Civil Eng.10+Ε15199Ε179110Ε1911
6Civil Eng.5–10Ε17331Ε161130Ε1971
7Civil Eng.5–10Ε16913Ε151950.08Ε1951
8Civil Eng.10+Ε17731Ε151390.048Ε1951
9Mechanical Eng.10+Ε17591Ε163190.08Ε1951
10Mechanical Eng.10+Ε15159Ε175310.08Ε1815
Table 9. Category weights provided by the engineers.
Table 9. Category weights provided by the engineers.
SpecialtyExperienceCategories of Barriers
Κ1Κ2Κ3Κ4Κ5
1Architectural10+0.5740.0990.1380.1380.051
2Civil Eng.5–100.3410.3410.1290.0590.129
3Civil Eng.5–100.1700.3960.0940.1700.170
4Civil Eng.10+0.2820.1280.3330.0770.179
5Civil Eng.10+0.5440.0940.2200.0480.094
6Civil Eng.5–100.6600.0620.1090.0850.085
7Civil Eng.5–100.0490.5520.1330.1330.133
8Civil Eng.10+0.5440.2200.0940.0480.094
9Mechanical Eng.10+0.5900.1080.1080.0840.108
10Mechanical Eng.10+0.5250.0910.1270.2120.046
Sum:4.2802.0921.4861.0531.090
Average:0.4280.2090.1490.1050.109
Table 10. Resulting economic and institutional barriers scores provided by the engineers.
Table 10. Resulting economic and institutional barriers scores provided by the engineers.
SpecialtyExperienceEconomic BarriersInstitutional Barriers
Ε1Ε2Ε3Ε4Ε5Ε6Ε7Ε8
1Architectural10+0.1440.0780.1440.6330.2320.5780.0510.139
2Civil Eng.5–100.3750.1250.3750.1250.0940.4690.2190.219
3Civil Eng.5–100.3750.0940.3750.1560.4310.3450.1720.052
4Civil Eng.10+0.1840.0790.5530.1840.3000.3000.1000.300
5Civil Eng.10+0.4010.4580.0920.0490.0700.1510.0840.695
6Civil Eng.5–100.0650.1090.6740.1520.5780.0710.2200.132
7Civil Eng.5–100.6370.0560.1530.1530.1530.6370.1530.056
8Civil Eng.10+0.1590.0650.6880.0880.6010.0530.2420.104
9Mechanical Eng.10+0.0650.1570.6200.1570.6880.1160.0800.116
10Mechanical Eng.10+0.1390.2320.5780.0510.0650.1570.6200.157
Sum:2.5451.4524.2521.7503.2112.8771.9421.970
Average:0.2550.1450.4250.1750.3210.2880.1940.197
Table 11. Resulting professional and social barriers scores provided by the engineers.
Table 11. Resulting professional and social barriers scores provided by the engineers.
SpecialtyExperienceProfessional and Social Barriers
Ε9Ε10Ε11Ε12Ε13Ε14
1Architectural10+0.0880.0630.0880.0320.3650.365
2Civil Eng.5–100.1450.1450.0810.1450.3390.145
3Civil Eng.5–100.2200.0510.0960.0580.2880.288
4Civil Eng.10+0.2330.2330.0330.1000.1670.233
5Civil Eng.10+0.1240.1240.1240.5140.0460.069
6Civil Eng.5–100.2580.2950.2580.0980.0320.059
7Civil Eng.5–100.1170.4880.1170.1170.0430.117
8Civil Eng.10+0.0870.0450.1210.1210.5050.121
9Mechanical Eng.10+0.0560.5740.0930.0930.0930.093
10Mechanical Eng.10+0.0720.5610.1290.0920.0920.053
Sum:1.4002.5781.1401.3711.9681.543
Average:0.1400.2580.1140.1370.1970.154
Table 12. Resulting market and technological barriers scores provided by the engineers.
Table 12. Resulting market and technological barriers scores provided by the engineers.
SpecialtyExperienceMarket BarriersTechnological Barriers
Ε15Ε16Ε17Ε18Ε19
1Architectural10+0.0910.7400.1690.1250.875
2Civil Eng.5–100.1200.2800.6000.7500.250
3Civil Eng.5–100.1200.2800.6000.1670.833
4Civil Eng.10+0.1500.2500.6000.8750.125
5Civil Eng.10+0.8180.0910.0910.5000.500
6Civil Eng.5–100.2000.2000.6000.1250.875
7Civil Eng.5–100.0670.6800.2530.1670.833
8Civil Eng.10+0.0830.2500.6670.1670.833
9Mechanical Eng.10+0.1650.0770.7580.1670.833
10Mechanical Eng.10+0.7140.1840.1020.8330.167
Sum:2.5283.0324.4403.8756.125
Average:0.2530.3030.4440.3880.613
Table 13. Final overall significance scores per barrier provided by the engineers.
Table 13. Final overall significance scores per barrier provided by the engineers.
Category BarriersBarrier ScoresCategory WeightsFinal Barrier Score
Economic BarriersE1High initial cost0.2550.4280.109
E2Low rate of return on investment, low profitability0.1450.4280.062
E3Lack of funds and difficulty in securing loans0.4250.4280.182
E4High final and maintenance costs0.1750.4280.075
Institutional BarriersE5Insufficient incentives0.3210.2090.067
E6Lack of guidelines, instructions and evaluation standards0.2880.2090.060
E7Weak political will. Different priorities0.1940.2090.041
E8Absence of a proper building database0.1970.2090.041
Professional and Social BarriersE9Inexperienced and unskilled professionals0.1400.1490.021
E10Low awareness and lack of information0.2580.1490.038
E11Fear of failure. Doubt about achieving desired goals0.1140.1490.017
E12Prejudice against new practices0.1370.1490.020
E13Delays in work schedule0.1970.1490.029
E14Cooperation between different employee groups0.1540.1490.023
Market
Barriers
E15Doubt about the demand for the products0.2530.1050.027
E16Building materials (availability, cost, durability, reliability)0.3030.1050.032
E17Insufficient public information and promotion of materials0.4440.1050.047
Technological BarriersE18Incompatible technology. Slow development0.3880.1090.042
E19Absence of exhibitions promoting new technologies0.6130.1090.067
Table 14. Ranking of barriers in terms of significance (top 10 barriers).
Table 14. Ranking of barriers in terms of significance (top 10 barriers).
EngineersSkilled WorkersOwnersLiterature (Table 1)
BarriersFinal ScoreBarriersFinal ScoreBarriersFinal ScoreBarriersNo.
1E3Lack of funds and difficulty in securing loans.18.20E1High initial cost.13.29E1High initial cost.15.49E6Lack of guidelines, instructions and evaluation standards.28
2E1High initial cost.10.89E4High final and maintenance costs12.68E3Lack of funds and difficulty in securing loans.11.26Ε7Weak political will. Different priorities.26
3E4High final and maintenance costs7.49E3Lack of funds and difficulty in securing loans.12.26E4High final and maintenance costs8.48E10Low awareness and need for more information.25
4E5Insufficient incentives.6.72E19Absence of exhibitions promoting new technologies.7.77E2Low rate of return on investment, low profitability.6.58E5Insufficient incentives.23
5E19Absence of exhibitions promoting new technologies.6.68E18Incompatible technology. Slow development.6.42E18Incompatible technology. Slow development.5.80E9Inexperienced and unskilled professionals.21
6E2Low rate of return on investment, low profitability.6.22E16Building materials (availability, cost, durability, reliability)5.63E16Building materials (availability, cost, durability, reliability)5.55E1High initial cost.18
7E6Lack of guidelines, instructions and evaluation standards.6.02E17Insufficient public information and promotion of materials.5.27E17Insufficient public information and promotion of materials.5.04E4High final and maintenance costs18
8E17Insufficient public information and promotion of materials.4.67E9Inexperienced and unskilled professionals.4.84E6Lack of guidelines, instructions and evaluation standards.5.01E16Building materials (availability, cost, durability, reliability)18
9E18Incompatible technology. Slow development.4.22E10Low awareness and lack of information.3.92E5Insufficient incentives.4.84E2Low rate of return on investment, low profitability.17
10E8Absence of a proper building database.4.12E2Low rate of return on investment, low profitability.3.84E8Absence of a proper building database.4.31E17Insufficient public information and promotion of materials.17
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Antoniou, F.; Mageiropoulos, T. Ranking the Barriers to the Energy Upgrading of Buildings Using the Best-Worst Method. Sustainability 2024, 16, 10143. https://doi.org/10.3390/su162210143

AMA Style

Antoniou F, Mageiropoulos T. Ranking the Barriers to the Energy Upgrading of Buildings Using the Best-Worst Method. Sustainability. 2024; 16(22):10143. https://doi.org/10.3390/su162210143

Chicago/Turabian Style

Antoniou, Fani, and Theofilos Mageiropoulos. 2024. "Ranking the Barriers to the Energy Upgrading of Buildings Using the Best-Worst Method" Sustainability 16, no. 22: 10143. https://doi.org/10.3390/su162210143

APA Style

Antoniou, F., & Mageiropoulos, T. (2024). Ranking the Barriers to the Energy Upgrading of Buildings Using the Best-Worst Method. Sustainability, 16(22), 10143. https://doi.org/10.3390/su162210143

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