Fuzzy TOPSIS Method for Ranking Barriers to Passive House:Environmental, Social and Economic Perspectives*

XUE Meihui, WANG Jianxing, YUE Xiaofang

(1. School of Civil Engineering, North China University of Technology, Beijing 100144, China; 2. School of Enginnering Science, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract：This paper presents the topsis method for capturing various planning activities barriers to migrate into a greener and more eco-efficient building systems. In order to mitigate these barriers, the ranking of barriers is very essential to address the issue more effectively within the availability of resources and capacity to improve environment. Twelve barriers have been identified and grouped as environmental, economicand societal barriers.

Key words：TOPSIS; passive house; comprehensive evaluation

1 Introduction

As resources are scarce and the population continues to increase, the protection of environmental quality becomes critical. Although some people have recognized the green issues for decades[1], the current environmental model has changed the Earth and its biology, including humans[2-3]. In this regard, many energy-saving strategies have evolved and integrated into operations and management in our real life[4-7]. Similarly, changing consumption patterns, growing population, increasing urbanization, environmental degradation and varying energy systems present an increasing challenge to climate change while impacting the industrial sectors. The Passive House (PH) is proved to be more energy efficient than the conventional version house[6]. Typically, three "R" (rebuilding, reduction and reuse/recycling) are a major strategy for PH, including reducing the amount of hazardous waste, reducing coolant consumption during processing, and calculating the appropriate mix of energy to ensure sustainability. In order to improve awareness of sustainability issues, the PH is an example for such innovations that manage to bridge the energy efficiency gap[7]. China is one of the most populous countries, ranking fourth in terms of CO2emissions in 2012 (Global CO Trend 2 emissions, 2012). In general, balancing the creating shared prosperity, safe guarding the environment and advancing economic competitiveness, the effective use of resources for practice are triggered by external, internal, social, and commercial factors (called drivers)[8-10]. These drivers help to make the PH industry voluntarily or forcefully adapted to the industry. More than 50% of solar-powered houses in China are designed with the help of the International Solar Energy Centre for Technology Promotion and Transfer (ISEC) which works to establish research & development bases and testing centers for solar technology industrialization in selected regions and enterprises in the world.

However, the implementation of PH is not an easy task. Governments and industry play an important catalytic role in the areas of energy and climate change. Green industry is the industry of the future. Sustainable industrialization made inclusive development possible and empowered, while addressing many aspects of life, from job creation to economic development, from security to the empowerment of women, sustainable industry was at the heart of all national interests. There is a need to understand the role of potential motivations (drivers) in promoting the implementation of PH values, which will help to emphasis and leverage several key drivers to work under limited resources. The purpose of this paper is to collect common drivers of these PH from a variety of sources and to use TOPSIS for analysis in a multi-standard decision.

2 Passive House Drivers Strategy

2.1 Passive House Efficiency

Source is assets, producing the same product with less resources or energy is a good strategy in life circle analyses. In PH, the solar radiation transmission through the windows, the heat transfer through the high thermal inertia element are implemented. Moreover, the low thermal inertia is also used as common practice control strategies compared with regular buildings, which is the key issues. Improving efficiency by preventing waste is double win both for ecological and effective. The cost of a PH building plan will be paid through more efficient system savings, such as passive solar heating system, the active solar heating system and a ground heat exchanger, which in turn will have a positive impact.

2.2 Passive House Market Share

With market needs, higher social awareness and more severe global competitive pressures, construction companies need to review their strategies. Passive homes are ideal for minimizing energy demand and achieving comfortable indoor environmental conditions, which should be seen as an opportunity in this dynamic environment. Advanced building construction techniques and materials can effectively utilize existing internal heat and reduce energy consumption.

Fig. 1 Structure of Passive House Strategy

A deep understanding of PH building system strategies and technologies will make manufacturers aware that, PH strategy has a positive impact on competition unlike other competitive regular building strategies (the advantages can be seen fig. 1). Overall, the advantage of using a passive energy approach to transform a home is to achieve lower energy consumption and good heat comfort. Moving green in the construction industry will also improve the quality of the production process, which will affect product quality and will be more attractive to customers who are increasingly looking for green manufacturers and products.

2.3 Government Support and Regulations

The pressure from the government to develop PH is growing. Globally, the government and even the United Nations have initiated many regulations, tax incentives, obligations or penalties to become more environmentally friendly. UNIDO is harnessing on innovative technologies and the fourth industrial revolution towards a low emissions-climate resilient industries and infrastructure by taking stock of industry's contribution to economic growth and social prosperity whilst recognizing its impact on global greenhouse gas emissions. Therefore, when manufacturers think globally, PH technology is becoming more and more a task based on the previous aspects, and it is economically justifiable for current manufacturers to become more environmentally friendly. Combine technology drivers with this economic understanding to make future PH a reality.

A list of probable barriers to PH adoption in China can be broadly classified shown in fig. 2 briefly. These barriers are: cost saving (D1), high short-term cost (D2), top management commitment (D3), technology upgradation (D4), standardization (D5), future legislation (D6), incentives (D7), uncertain future (D8), current legislation (D9), customer demand (D10), public pressure (D11), peer pressure (D12).

Fig. 2 Hierarchical Structure of Three Criteria

3 Methodology

The classic multi-standard decision model (MSDM), including TOPSIS and requires precise standard weights[11]. However, in many cases, clear data is not sufficient to simulate real-world situations, because human judgement re often vague and cannot be estimated with accurate values[7, 12].Language variables are the natural manifestation of subjective judgment and the preferences of decision makers in a structured manner. By measuring the essential fuzziness of the subjective judgment of decision makers, fuzzy set theory (FST) provides suitable tools to adapt to uncertain and complex environments, thus reducing the fuzziness of the results. Fig. 3 shows the proposed study's framework. The implementation of FST is proved by many authors successfully to measure the fuzziness of concepts related to human orientation judgment.

The order performance technique is similar to the ideal solution[13]which is one of the classical MCDM methods. The selected alternative should be kept at the shortest distance from the positive ideal solution, i.e. the nearest to the fuzzy positive ideal solution (FPIS); the farthest from negative ideal solutions, i.e. the farthest from the fuzzy negative ideal solution (FNIS)[14]. Various other MCDM methods can be used in this study, such as electrore, analytical hierarchy process (AHP), performance value analysis (PVA). In general, the electrore method is unacceptable, because in some certain, it may use to discard some alternatives to the problem. Another MCDM technique method PVA is unacceptable also, which used to discard some alternatives to the problem, AHP has its limitations when standards are large and time consuming. TOPSIS is picked up for this research not only because it uses linguistic variables to evaluate the standard rating in a convenient and reasonable way to express judgements, but is applied to the model parameters of decision making to sort the obstacles[15-16].

Fig. 3 Proposed Framework for the Study

This article is a typical example of the application of fuzzy topologies because the issues are complex and involve social, economic and environmental standards assessed by Governments, industry and experts. This paper discusses the 12 barriers (fig. 2 ) to PH implementation identified and discussed with government and industry representatives, expert in this area.

Fig. 4 Triangular Fuzzy Number

The constants reflect the fuzziness of the evaluation data. The other steps of the fuzzy topology are as follows:

(1) Selection and assessment of ranking criteria and alternatives. Table 1 provides the linguistic variables and fuzzy ratings for the alternatives and the criteria. The range of language scores signed by environmental, social and economic professionals and the range related to their decisions provided by table 2 and table 3. In this paper, each team member experience in buildings at least serves 5 years. The three expert groups agreed to conduct separate assessments, which were provided for the study.

Table 1 Selection and Assessment for Prioritizing PH Drivers

Table 2 Linguistic Term for Criteria

Table 3 Linguistic Term for Alternatives

Table 4 presents the aggregate fuzzy weights for the criteria s given by the decision makers. The linguistic ratings are assigned to various criteria and alternatives with the help of three decision maker groups named asDM1,DM2, andDM3from people of environmental, social and economic expertise respectively.

Table 4 Aggregate Fuzzy Weights for the Criteria

(3) Computing the fuzzy decision matrix

The fuzzy decision matrix for the alternatives is constructed using the following relation (table 5).

Table 5 Aggregate Fuzzy Weights for Barriers

Table 6 Normalized Alternatives

(5) Computing the overall performance evaluation. Calculate the overall performance evaluation for each alternative by multiplying the aggregate weights.

Table 7 Weighted Normalized Alternatives

(6) Computing the FPIS and the FNIS.FPIS and FNIS are computed via

(7) Computing theCCIof each alternative.The distance (d+,d-) of each alternative from FPIS and FNIS are calculated using Euclidean distance formula

Table 8 Distance for Passive House Drivers (from FPIS)

Table 9 Distance for GM Drivers (from FNIS)

The closeness coefficients for aggregate and individual perspectives are presented in table 10.

Table 10 Closeness Coefficient for Alternatives (Aggregate)

(8) Rank the drivers. The best alternative is closest to the FPIS and farthest from the FNIS. Rank the alternatives according to the closeness coefficient (CCI) in decreasing order andselect the alternative with the highest closeness coefficient for final implementation shown in table 11.

Table 11 Ranking of the Barriers

4 Results and Discussion

Fig. 5 shows the closeness coefficients of the fuzzy TOPSIS model of passive house drivers. Based on the results obtained in this study, fig. 6 clearly shows that the driver's Current Legislation is perceived as the most significant barrier factor, not the Top Management Commitment, in the successful implementation of PH practices. This may be because in large companies, the most current legislation has significant influence in the decision-making process compared to top management commitments[19-20]. So if the government wants to promote PH, the implementation of the project, the management of the country adopting a strong policy-driven strategy is essential to promote the implementation of the greenbuilding strategy.

This study also reflects that the next important driver is Uncertain Future (level 2), because of the implementation of new technologies depends on people's future expectation, especially in housing. If you break through the technology level, people are more willing to try.

The third and forth-ranking policy driver is Incentives and Future Legislation, which together promote the smooth implementation process. This is because incentives for loans, government subsidies, tax and other economic benefits can facilitate the ease of adoption of the successful implementation of PH practices[21]. The next important driver for successful implementation is Standardization (level 5), followed by Technical Advancement (level 6), which is important because standardization guidance on pollution control and emissions trading can lead to implementation[22]. In addition, depending on the importance, the next driver is Top Management Commitment (level 7). In order to successfully implement PH practices, High Short-Term Cost (ranked 8) and Cost saving (ranked 12) are not at the forefront as previously envisioned, as the biggest constraint for companies is the shortage of financial resources[23], when the government promotes the promotion of PH through incentives, the incentive factor for High short-term cost will be downgraded[19]. The results further indicate that the Peer Pressure and Public Pressure are ranked 9th. The reason for the driver behind this rather than to embrace it immediately may be the lack of awareness and understanding of the importance of PH in China. Customer Demand (ranked 11th) is a low ranking factor because user demand can only gain a competitive advantage after deploying PH practices in all phases of the organization and winning the market.

A survey of PH drivers and their priorities based on the triple bottom line dimension shows that these results are very useful and interesting. Some suggestions based on the results of the aggregate together are:

(ⅰ) The government should provide incentives for industries to invest in green technologies such as tax rebates and environmental performance awards. The government should encourage various industries to invest in green technology such as PH technology.

(ⅱ) The government should formulate policies (such as public private partnerships) which encourage loans to micro, small and medium-sized enterprises to invest in PH technology and low carbon practices.

(ⅲ) The government should provide the guidance or long-term road map for future legislation, as well as milestones for achievable goals.

(ⅳ) The government should also include publicity activities as mandatory activities funded (by the government and non-governmental organizations, PPP) to promote the importance of environmentalproducts and processes to the community as a whole, which can further increase customer demand for environmental products.