Factors influencing the application of prefabricated construction in China: From perspectives of technology promotion and cleaner production

Factors influencing the application of prefabricated construction in China: From perspectives of technology promotion and cleaner productionContents lists avai
Factors influencing the application of prefabricated construction in China: From perspectives of technology promotion and cleaner production
Guobin Wu a, Ru Yang a, Ling Li a, Xing Bi a, Bingsheng Liu b, *, Shaoyan Li c, Shixiang Zhou d
a College of Management and Economics, Tianjin University, 92 Weijin Road, Nankai District, Tianjin, 300072, PR China b School of Public Affairs, Chongqing University, 174 Shazheng Street, Shapingba District, Chongqing, 400044, PR China c Urban Planning and Design Institute, Tianjin University, 92 Weijin Road, Nankai District, Tianjin, 300072, PR China d Hainan Province Construction Group Corporation Limited, 63 Qiongyuan Road, Hainan, 570204, PR China
a r t i c l e i n f o
Article history: Received 5 September 2018 Received in revised form 16 December 2018 Accepted 11 February 2019 Available online 11 February 2019
Keywords: Cleaner production Influencing factors Prefabricated construction Relative importance Technology promotion
* Corresponding author. E-mail addresses: [email protected] (G.
(R. Yang), [email protected] (L. Li), [email protected] (X com (B. Liu), [email protected] (S. Li), zsx901019@1
https://doi.org/10.1016/j.jclepro.2019.02.110 0959-6526/© 2019 Elsevier Ltd. All rights reserved.
a b s t r a c t
It has been proven that prefabricated construction plays a significant role in cleaner production in the construction industry due to its capacity for energy conservation, emissions reduction, low-carbon development and environmental protection. Although prefabricated construction was introduced in China decades ago, it still faces some problems during the application stage. In order to improve the application of prefabricated construction in China, this research explores its influencing factors from the perspectives of technology promotion and cleaner production. Twenty-one types of factors are identified through a literature review, and a questionnaire survey is conducted for the purpose of collecting empirical data. Factor analysis establishes an influencing factor model composed of industry factors, company factors, technology factors, government factors and market factors. The relative importance of each cluster and factor is revealed by its index of relative importance (IRI): the dominant player is the government, and the top five factors in the promotion of prefabricated construction in China are tech- nology lock-in (76.42%), incentive policies (75.91%), standardization (73.70%), cost (73.70%) and entre- preneurial cognition (73.13%). Additionally, the process of conducting semi-structured interviews with experts provides suggestions. The findings will benefit researchers, practitioners and policymakers who want to promote the application of prefabricated construction, and provide references for other cleaner production technologies in China.
© 2019 Elsevier Ltd. All rights reserved.
1. Introduction
The construction sector is deemed to be one of the highest energy-intensive sectors (Lai et al., 2016). It accounts for 25e33% of all waste generated in the EU (EU, 2015) and more than 30% final global energy consumption (IPCC, 2014). The intensive energy consumption is expected and feasible to be reduced through recent advances in technologies (IPCC, 2014). Traditional on-site con- struction technology contributes serious pollution to the sur- rounding environment and is no longer able to adapt to the low-
Wu), [email protected] . Bi), bluesea_boy_1979@163. 26.com (S. Zhou).
carbon development model of modern society (Dixit et al., 2010). As a good alternative to the conventional method (Jeong et al., 2017), prefabricated construction technology has the basic char- acteristics of standardization, prefabrication in factories, and sci- entific management (Wang et al., 2018). Moreover, it plays a significant role in cleaner production in the construction industry, including energy conservation, emissions reduction, low-carbon development and environmental protection (Cao et al., 2015; Zhu et al., 2018). For example, Cao et al. (2015) concluded the pre- fabricated construction building has many environmental advan- tages (e.g., 35.82% reduction in resource depletion; 6.61% reduction in health damage; 3.47% reduction in ecosystem damage) over on- site construction. Hong et al. (2016) indicated that the prefabricated construction can achieve 16%e24% energy reduction from recycling process and 4%e14% energy saving of the total life-cycle energy
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consumption. Prefabricated construction has been already well developed and widely used in many developed countries. For instance, the prefabrication level in Germany, the Netherlands, Denmark and Sweden already were reported to be 31%, 40%, 43% and 80% respectively (Mao et al., 2013; Cheng et al., 2017). However, since its introduction in China in 1950s, it has not been widely extended to date.
Following the rapid economic development, China’s urbaniza- tion process has reached new levels, with the urbanization rate increasing from 17.9% in 1978 to 58.52% in 2017 (National Bureau of Statistics of the People’s Republic of China, 2018), and urban pop- ulation expanded by 4 times from 1980 to 2015 (Fan et al., 2017). On the one hand, the development of construction industry can, to certain extent, address issues associated with urbanization such as high housing price and accommodation for of low- and middle- income population (Cheng et al., 2017). One the other hand, it is not expected that the urbanization is achieved at the cost of long- term sustainability (e.g., high energy consumption, damage to environment) (Ding et al., 2018). Therefore, to provide more houses to citizens while maintaining sustainability, China has targeted at prefabricated construction as shown in Fig. 1. Besides, a series of policies have been made to speed up its application in the con- struction industry, including the “Several Opinions on Further Strengthening the Management of Urban Planning Construction” (State Council of the People’s Republic of China, 2016), the “13th Five-Year Prefabricated Construction Action Plan”, “Management Measures for a Prefabricated Building Demonstration City” and “Management Measures for a Prefabricated Construction Industry Base” (Ministry of Housing and Urban-Rural Development of the People’s Republic of China, 2017).
Although China has made great efforts to promote the applica- tion of prefabricated construction, there are still some problems. Numerous researchers (Cheng et al., 2017; Xiahou et al., 2018; Gan et al., 2018) have investigated the barriers or driving factors of its development in China. However, there are still some limitations that should be further addressed. On the one hand, prefabricated construction is a mean to achieve cleaner production in construc- tion industry. Previous studies pay little if any attention to factors that influence cleaner production adoption. On the other hand, as one type technology promotion, the application of prefabricated construction should also consider technology aspects.
To achieve the goal of cleaner production and to promote this technology in China, this paper provides a prototype study on comprehensively identifying factors that affect the application of prefabricated construction from the perspectives of technology promotion and cleaner production. In addition, an influencing
Fig. 1. 2011e2016 market size and building area of the prefabricated construction industry in China (China Industry Information Network, 2017).
factor model regarding the application of prefabricated construc- tion is proposed in this research. The model is expected to help in understanding the means to promote the application of pre- fabricated construction for stakeholders involved in the pre- fabricated construction industry.
2. Literature review
2.1. Factors influencing technology promotion
There are numerous studies investigated factors influencing technology application, such as market factors, government factors, company factors, and technology factors. Market factors are re- ported as the driving factors and extensively studied by re- searchers. Chen et al. (2003) proposed that market demand can accelerate the diffusion of information technology innovation. Studying the market characteristics of technology diffusion, Allen et al. (2009) found that neither a perfectly competitive market nor a monopoly market is conducive to the diffusion of technology. Furthermore, Vaccaro et al. (2010) proved that some appropriate marketing strategies can spread the information of new products, increase the total number of potential users and promote the application of new technologies. Overall, market demand, market structure, market price and marketing strategy can affect the pro- motion of technologies.
In addition, government plays a key role in technology promo- tion. Government can promote the application of technology by directly or indirectly policies, for example tax incentives for en- terprises (King and Nowack, 2003). Moreover, to promote supply- side innovation policy, government can conduct demand-oriented innovation policy through government procurement (Moon and Bretschneider, 1997). In addition, government should also take the lead in standardization of the technology. Such process will bring benefits to both consumers and firms in terms of cost reduction and resource savings (Farrell and Saloner, 1985).
Companies is another driving force behind technology promo- tion, because they are the main stakeholders to undertake the high research and development (R&D) cost and risk (Askarany and Smith, 2008). Whether or not and to what extend to promote technologies would largely depend on the organization culture of the company. Fuller et al. (2007) argued that organizational culture is the business philosophy of the enterprise and that the dedication and spirit of cooperation of workers and other spiritual factors will affect enterprises’ acceptance of new technologies. Among them, entrepreneurs are the core of the company, and entrepreneurial cognition is one of the key factors for a company to promote technologies (Schumpeter and Backhaus, 2003).
Regarding the technology itself, the greater the advantage of an alternative technology, the more acceptable it is (Rogers, 1983; Hausman et al., 1984). Because of the great risks involved in the whole process of technology promotion from R&D to trans- formation, a large amount of capital investment is necessary for the promotion of technologies (Torbica and Cappellaro, 2010). Besides, researchers neglect the commercial value of the technology, which is not conducive to the promotion of technologies in the later stage (Yu et al., 2016). From R&D to technological achievement trans- formation, the greater the extent and scope of the technologies that can be tested, the more favorable the situation will be for their promotion (Rogers, 1983).
2.2. Factors influencing cleaner production adoption
Clear production is widely recognized as the best pathway to achieve sustainable development (Zhang, 2000). Researchers have explored influencing factors regarding the adoption of cleaner
G. Wu et al. / Journal of Cleaner Production 219 (2019) 753e762 755
production which is significantly affected by the government pol- icy. Rabl and Spadaro (2016) claimed that rational environmental policy (e.g., the appropriate level of pollution taxes) will help pro- mote the adoption of cleaner technology. Specifically, Lin et al. (2016) found that the involvement of government policy in capi- tal subsidies and tax rebates is a strong enabler for the industry to adopt cleaner production technologies (e.g., electricity). In addition to compulsory and supportive policy by the government, the awareness and R&D of industry and enterprises will have impacts on the adoption of cleaner production which was claimed by Dong et al. (2018). Li and Hamblin (2016) also held the view that the industry needs to build an environmentally friendly culture to achieve cleaner production and environmental sustainability.
Other researchers discussed the barriers to adopt cleaner pro- duction. Zhang (2000) identified the four main barriers that inhibited cleaner production promotion in China including (1) the lack of pollution prevention and environmental awareness; (2) the lack of governmental programs and cooperation; (3) the lack of financial support; and (4) the lack of research and development. Vieira and Amaral (2016) classified the barriers to apply cleaner production into internal and external aspects and emphasized the importance of resistance to changes (i.e., technology lock-in, an internal aspect) and incentives for cleaner production adoption (an external aspect). In an Indian setting, Govindan et al. (2016) showed that higher costs and lack of customer acceptance are the formi- dable barriers to cleaner production in auto parts remanufacturing.
2.3. Factors influencing the application of prefabricated construction
There have been numerous excellent studies (e.g. Gan et al., 2018; Hwang et al., 2018; Mao et al., 2015) conducted to explore the barriers, constraints or limitations of prefabricated construction systematically. Based on the results of these research, the factors can be summarized into: (1) higher cost of construction or initial investment (Gan et al., 2018; Hwang et al., 2018; Jaillon and Poon, 2008; Pan and Sidwell, 2011); (2) lack of effective incentives and policy (Cheng et al., 2017; Gan et al., 2018); (3) an inadequate level of standardization (Jaillon and Poon, 2008; Gan et al., 2018), (4) incomplete industry chain (Cheng et al., 2017; Hwang et al., 2018; Gan et al., 2018), (5) poor labor quality (lack of skilled or experi- enced workers and technicians, Cheng et al., 2017; Hwang et al., 2018), (6) negative perception of the public (Kamali and Hewage, 2016; Hwang et al., 2018).
On the other hand, other researchers focused on identifying the most critical influencing factors and their impacts on the pre- fabricated construction. For example, Li et al. (2017) and Han and Wang (2017) claimed that the combination of new technologies (e.g., RFID, BIM and Big Data) with prefabrication will not only greatly improve the management level, quality and performance of the construction but also play a positive role in promoting pre- fabricated construction in China. Zhai et al. (2017) ranked supply chain coordination as a critical factor influencing the performance of prefabricated construction, because most delays (Cheng et al., 2017) and cost overruns (Mao et al., 2015) are related to it. Xue et al. (2018) pointed out that the development of prefabricated construction is being hindered by lack of innovation, and analyzed collaborative relationships among industrialized construction technology innovation organizations.
Overall, the literature review summarized 21 types of factors that can influence the promotion of this cleaner production tech- nology - prefabricated construction, as shown in Table 1.
3. Methodologies
Multiple methods of data collection and data analysis were adopted in this research. The process of this research consists of five main steps, as shown in Fig. 2: (1) identifying factors that can in- fluence the development of prefabricated buildings through a literature review, (2) administering a questionnaire to collect empirical data to establish a model of critical factors for the pro- motion of prefabricated construction, (3) establishing an influ- encing factor model utilizing factor analysis, (4) using an index of relative importance to determine the degree of importance of the influence on prefabricated construction promotion of each factor, and (5) discussing the results of the data analysis with experts and providing constructive suggestions to promote the development of prefabricated buildings in China through semi-structured interviews.
3.1. Data collection
This research introduced two methods for data collection pur- poses. First of all, a two-part questionnaire survey was conducted in China to capture the critical factors of promoting prefabricated construction. The first part included basic information, such as gender, age, company type, location and working experience. The second part contained 21 questions concerning the significance level of each factor using a 5-point Likert-type scale from 1 (very little effect) to 5 (very high effect).
Eventually, 215 respondents from 22 provinces in China were involved in the questionnaire survey. These respondents are different stakeholders related to the construction industry, such as government officers (6.98%), developers (10.23%), contractors (23.72%), researchers (14.88%), designers (7.44%), project managers (8.84%), supervision engineering managers (7.91%) and others (20.00%). However, excluding invalid and missing information questionnaires, the answers of 185 respondents were used for further data analysis.
Subsequently, to learn more about measures to promote pre- fabricated construction, semi-structured interviews with experts were conducted, with each individual interview lasting between 30 and 60min. The interviews were recorded and transcribed for further analysis. Fifteen experts accepted the invitation to partici- pate, and the profile of the interviewees is shown in Table 2.
3.2. Data analysis
At the first stage of data analysis, exploratory factor analysis (EFA) was used for the purpose of grouping factors into clusters and establishing an influencing factor model, and the result of the EFA was proven by using confirmatory factor analysis (CFA).
At the second stage of analyzing data, the index of relative importance (IRI) was employed, and the level of working experi- ence of respondents was taken into account in this research. This index was calculated for every factor in each specific working experience set of the respondents using Eq. (1) (Zhao and Chen, 2018):
IRIkð%Þ ¼ 5ðn5Þ þ 4ðn4Þ þ 3ðn3Þ þ 2ðn2Þ þ n1
5ðn5þ n4þ n3þ n2þ n1Þ 100 (1)
where IRIk(%)¼ the working experience percentage of the IRI of each factor, which is calculated separately for each corresponding working experience set (k) of respondents; k¼ a number that represents the working experience of respondents (when working experience is less than 5 years, k¼ 1; when working experience is between 5 and 10, k¼ 2; when working experience is between 10
Table 1 Influencing factors of prefabricated construction.
No. Factors Sources Remarks
1 Marketing strategies Vaccaro et al. (2010) A long-term, forward-looking approach to planning with the fundamental goal of achieving a sustainable competitive advantage (Baker, 2008).
2 Market demand Chen et al. (2003) Quantities of prefabricated construction projects that the clients are willing and able to afford over a given period of time (O’sullivan & Sheffrin, 2003).
3 Market structure Allen et al. (2009) Four types of market structure exist: monopolistic competition, oligopoly, monopoly, and perfect competition.
4 Customer acceptance Govindan et al. (2016) Adoption of innovative products by consumers through a communication process between individual adopters and their environment (Rogers, 1983).
5 Technology R&D Zhang (2000); Yu et al., 2016; Dong et al., (2018); Xue et al., (2018)
Innovative activities undertaken by corporations, governments and institutions in developing new technologies or improving existing technologies (Kainulainen, 2014).
6 Combination with other technologies
Han & Wang, (2017); Li et al., (2017) Application of other technologies, for example, RFID and BIM, in the construction of prefabricated building projects (Li et al., 2017).
7 Cost Jaillon and Poon (2008); Pan and Sidwell (2011); Govindan et al. (2016); Hwang et al., (2018)
Initial investments, construction cost and maintenance cost for developers, contractors or the end users (Hwang et al., 2018).
8 Awareness of environmentally friendly development
Zhang (2000); Vieira and Amaral (2016); Li & Hamblin, (2016); Dong et al. (2018)
Pollution prevention and environmental awareness of the stakeholders involved in prefabricated construction (Zhang, 2000).
9 Technology lock-in Vieira & Amaral (2016) “Lock-in” of incumbent technologies, preventing the uptake of potentially superior alternatives (Arthur, 1989).
10 Company scale Askarany and Smith, 2008 Indicators that imply the scale of the company, including number of employees, annual revenue, and total assets.
11 Industry chain Cheng et al. (2017) Various subsystems constitute a prefabricated construction industry chain, including planning, design, component production, construction, decoration, delivery, and property operation (Han and Wang, 2017).
12 Entrepreneurial cognition Schumpeter and Backhaus, 2003; Dong et al. (2018) Cognition of top leadership who are responsible for valuing prefabricated construction (Liu et al., 2016).
13 Labor quality Cheng et al. (2017); Hwang et al., (2018) Experience in installation, design or other aspects of labors who take part in the construction of prefabricated buildings (Hwang et al., 2018).
14 Supply chain coordination
Cheng et al. (2017) Coordinating the logistics processes which were being controlled by independent entities separately, including off-site production, transportation and on-site assembly (Zhai et al. 2017)
15 Relative superiority of technology
Rogers (1983); Hausman et al. (1984) Advantages of one technology compared to other existing technologies.
16 Technological achievement transformation
Rogers (1983) Follow-up experiments, development, application and popularization of technological achievements obtained from scientific research and endowed with practical value to create or achieve a new technology, a new process, and new products, thus improving productivity (Wu et al., 2016).
17 Mandatory policies King and Nowack (2003); Rabl and Spadaro (2016); Dong et al. (2018)
Policies regarding things that must be done because they are made by the government.
18 Incentive policies King and Nowack (2003); Vieira and Amaral (2016); Lin et al. (2016); Cheng et al. (2017); Dong et al. (2018)
Government policies with the purpose of encouraging the use of prefabricated construction in the construction industry, for example,…