The impact of sharing economy practices on sustainability performance in the Chinese construction industry

Resources, Conservation & Recycling 150 (2019) 104409

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Full length article

The impact of sharing economy practices on sustainability performance in the Chinese construction industry

T

Ying Lia, Ronggui Dinga, Li Cuib, Zhimei Leic, , Jian Moud ⁎

a

School of Management, Shandong University, 27 Shanda Nan Road, Jinan, 250100, PR China School of Business, Dalian University of Technology, 2 Dagong Road, Panjin, 124010, PR China c College of Mechanical Engineering, Chongqing University, 174 Shazhengjie, Chongqing, 400044, PR China d School of Economics and Management, Xidian University, 266 Xinglong Section of Xifeng Road, Xian, 710126, PR China b

ARTICLE INFO

ABSTRACT

Keywords: Sharing economy Sustainability performance Construction projects Digital platform Structural equation modelling

The sharing economy is gradually reshaping the construction industry. This study identifies the use of digital platforms, internal sharing practices with project stakeholders, and external sharing practices with unfamiliar companies as three critical elements of sharing economy practices from a socio-technical perspective. The impacts of these three elements on sustainability performance, including economic performance, environmental performance and social performance, are investigated. Based on a survey of the Chinese construction industry, proposed hypotheses are tested using structural equation modelling. The results indicate that the use of digital platforms can promote both internal and external sharing practices in the construction industry. While internal sharing practices have positive impacts on the three dimensions of sustainability performance, external sharing practices can positively influence only environmental performance. The findings enhance the understanding of sharing economy practices and provide empirical evidence of the relationships between sharing economy practices and sustainability performance in the construction sector.

1. Introduction The sharing economy is gradually reshaping the construction industry (Haas, 2017). In particular, the development of information systems and technologies makes sharing economy practices in the construction sector more appealing. Online platforms such as Dozr in Ontario, Ramirent in Finland, Yard Club and Getable in San Francisco, and EquipmentShare in Missouri provide peer-to-peer equipment rental marketplaces for contractors and enable sharing practices among project stakeholders and other companies. Faber in Canada offers construction companies a software platform to automatically connect with construction workers with appropriate skills and empowers construction workers to find instant jobs with standardized pay at a fair wage. In China, Emoding establishes a cloud platform for “sharing designers” to connect architectural designers and project owners. Sharing economy practices promote the optimal allocation of under-utilized and idle resources, such as construction materials, labour and machinery equipment, in each unique construction project. However, a very limited number of studies focus on sharing economy practices in construction projects. Scholars and practitioners have recognized the rise of the sharing economy in the construction

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industry (Haas, 2017), but they still have no idea what sharing economy practices should be included in the construction project context. This insufficient understanding impedes the implementation and promotion of sharing economy practices. Hence, a theoretical framework to understand sharing economy practices should be established. Prior studies have noted that the sharing economy is mainly characterized by a platform for collaboration and sharing under-utilized or idle resources (Habibi et al., 2016a; Frenken and Schor, 2017; Muñoz and Cohen, 2017). From the socio-technical perspective, sharing resources within the social system relies on the development of digital platforms in the era of the sharing economy. Accordingly, this study identifies the use of digital platforms, internal sharing practices with project stakeholders, and external sharing practices with unfamiliar companies as three critical elements of sharing economy practices in construction projects. The sharing of construction workers, materials and equipment presents both opportunities and threats for construction firms. The question of how sharing economy practices influence sustainability performance, including economic, social, and environmental dimensions, remains unanswered. It seems that sharing idle materials, labourers and equipment can help construction firms save resources,

Corresponding author. E-mail address: [email protected] (Z. Lei).

https://doi.org/10.1016/j.resconrec.2019.104409 Received 10 December 2018; Received in revised form 24 April 2019; Accepted 11 July 2019 0921-3449/ © 2019 Elsevier B.V. All rights reserved.

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reduce waste, and lower costs when implementing construction projects. However, information about the quality of shared under-utilized assets is often asymmetric, which may lead to opportunistic behaviour, moral hazards and other potential risks (Weber, 2014). Contractors also opt to hold back due to the difficulty of defining who takes responsibility for equipment failure or the health and safety of workers. Hence, it is necessary to empirically validate how sharing economy practices in construction projects influence sustainability performance, including economic performance, social performance and environmental performance. Against this backdrop, our study intends to explore two research questions: (1) What sharing economy practices should be incorporated in the construction industry? (2) What are the relationships between sharing economy practices and sustainability performance? Based on a survey in the Chinese construction industry, we empirically investigate the effects of sharing economy practices on economic, environmental and social performance. The results contribute to sharing economy research in two ways. First, three dimensions of sharing economy practices are identified from a socio-technical perspective, which can enhance the understanding of sharing economy practices in the construction sector. Second, this study empirically tests the relationship among three dimensions of sharing economy practices and three aspects of sustainability performance in the construction industry, which provides empirical evidence for the performance effect of the sharing economy. The remainder of this paper is organized as follows. We first review the literature on the sharing economy in Section 2 and develop research hypotheses in Section 3. Section 4 describes the research methods, followed by an analysis of the results in Section 5. Based on the results, we discuss the major findings, theoretical implications and managerial implications in Section 6. Finally, in Section 7, we conclude the study and outline limitations and future research directions.

referred to as “collaborative consumption”, the “collaborative economy”, “access-based consumption”, and the “peer-to-peer economy”, is regarded as an umbrella term for a wide spectrum of nonownership consumption activities, such as swapping, bartering, trading, renting, sharing, and exchanging (Habibi et al., 2016a). Scholars mostly emphasize the essentially contested and umbrella nature of the sharing economy and become enmeshed in debates about “what it is, what it fails to be, and what it should be” (Acquier et al., 2017). Until now, the definition of the sharing economy has been specified more clearly. Frenken and Schor (2017) define the sharing economy as “consumers granting each other temporary access to under-utilized physical assets (“idle capacity”), possibly for money”. Similarly, Mair and Reischauer (2017) develop a definition of the sharing economy based on how the phenomenon manifests, that is, “a web of markets in which individuals use various forms of compensation to transact the redistribution of and access to resources, mediated by a digital platform operated by an organization” (p. 125). Furthermore, scholars propose a different framework of aspects, characteristics or dimensions to enhance the understanding of the sharing economy. For example, Hamari et al. (2016) suggest scrutinizing the sharing economy from four aspects, namely, online collaboration, social commerce, the notion of sharing online, and consumer ideology. Frenken and Schor (2017) differentiate the sharing economy from the on-demand economy, second-hand economy and productservice economy in terms of consumer-to-consumer interactions, temporary access and physical goods, while Acquier et al. (2017) position the sharing economy as resting on the foundational core of the access economy (sharing under-utilized assets to optimize their use), platform economy (intermediating decentralized exchanges through digital platforms), and community-based economy (coordinating through social interactions). Muñoz and Cohen (2017) identify seven distinct dimensions of the sharing economy, including platforms for collaboration, under-utilized resources, peer-to-peer interactions, collaborative governance, a mission-driven approach, alternative funding, and leveraging technology. Through configurational comparative analysis, Muñoz and Cohen (2017) reveal five sharing economy business model typologies, i.e., the crowd-based tech model; collaborative consumption model; business to crowd model; space-based, low-tech sharing model; and utopian sharing outlier model. Frenken and Schor (2017) emphasize that the impacts of sharing economy practices on the economy, society and the environment are generally complex and largely unknown. Sharing is always thought to be eco-friendly and less resource intensive and to provide stronger social ties. Some scholars suggest that sharing economy practices can lead to environmental benefits, social benefits and positive economic effects (Frenken and Schor, 2017). Martin (2016) notes that regime and niche actors employ conflicting framings for the development of a sharing economy. The former insists on framing the sharing economy as an economic opportunity and an unregulated marketplace for commercial goals, while the latter tend to frame the sharing economy as sustainable consumption and a decentralized and equitable economy for social and environmental values. However, the sharing economy is also associated with moral hazards and uneven distributions of income and welfare. Malhotra and Van Alstyne (2014) indicate the dark side of the sharing economy and note that sharing “creates a subtle tug-of-war between the primary producer and secondary sharer”. Cheng (2016) suggests that a sharing economy will result in disposable workers with no social security coverage despite increasing income. Due to the disability in compliance regulations, some innovative sharing practices raise concerns about consumer rights, public health and safety, the quality of goods and services, and unfair competition (Ranchordas, 2015). Indeed, Zervas et al. (2013) find that a 1% increase in Airbnb listings leads to a 0.05% decrease in quarterly hotel revenues. Fang et al. (2016) confirm that the entry of the sharing economy (Airbnb) can contribute to the tourism industry by attracting more tourists and hence generating new job opportunities. However, the marginal effect of Airbnb decreases due

2. Literature review 2.1. The rise of the sharing economy With the increasing attention paid to the sharing economy, scholars have made great efforts to define the term “sharing” and to establish a framework of sharing economy practices. Sharing indicates “the act and process of distributing what is ours to others for their use and the act and process of receiving or taking something from others for our use” (Belk, 2007, p. 127). Belk (2010) suggests understanding sharing from several conceptual dimensions, including possessiveness and attachment to possessions, independence versus interdependence, privacy, the leaky self and the stranger, and utilitarianism. Accordingly, Habibi et al. (2016b) propose a sharing-exchange continuum to measure where a business model falls based on a number of sharing-related characteristics (such as being non-reciprocal, involving social links, involving shared ownership, being money irrelevant, being networked, being inalienable and personal, involving dependent relationships, and involving love and caring) and exchange-related characteristics (such as being reciprocal, involving balanced exchange, involving no extended obligations, being monetary, involving calculation and inspection, and being alienable, impersonal, and independent). Sharing practices, dual model practices and pseudo-sharing practices in the sharing economy are identified by Habibi et al. (2016a). While true sharing is mainly driven by social concerns, pseudo-sharing aims at economic gains, and dual model practices emphasize both social concerns and economic gains (Belk, 2010, 2014). The present study considers all these practices from a broad perspective. The development of online platforms brings the sharing economy concept into public media. People now have access to rooms through Airbnb and Roomorama; tools through SnapGoods; cars and bikes through RelayRides, Zipcar, Wheelz and Mobike; and taxi services through Uber, Lyft and Didi. The sharing economy, which is also 2

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to the replacement of low-end hotels (Fang et al., 2016). In addition, some literature describes the negative influence of Uber on the labour market (Hall, 2016). We argue that, considering the mixed findings of previous studies, it is necessary to obtain additional empirical information about the relationships between sharing economy practices and sustainability performance.

participating in external sharing practices may not have any prior trading experiences or connections with one another. The sharing of construction materials or equipment among unfamiliar companies is identified as possessing more exchange-related attributes (Belk, 2014; Habibi et al., 2016a). The practices of renting and bartering are expected to follow the market norms of supply, demand, and efficiency (Habibi et al., 2016a). Moreover, external sharing practices are characterized by salient money exchanges, short interactions and being profit-oriented. Construction firms are involved in external renting, bartering and other sharing practices with strong profit-seeking motivations and explicit expectations of reciprocity. The use of digital platforms such as EquipmentShare and Dozr is another critical aspect of sharing economy practices in construction projects. Acquier et al. (2017) suggest that the platform economy constitutes one core of the sharing economy. Martin (2016) indicates that internet peer-to-peer platforms connect consumers to a service or commodity and enable consumers to share access to their under-utilized assets. In this case, the under-utilized assets can be used more efficiently. Botsman and Rogers (2010) indicate that peer-to-peer platforms can help reduce the costs of accessing products and services and consumer demand for resources. Construction firms can not only release and update the supply information related to their idle resources through online platforms but also use the platforms to place reservations, arrange payments, and implement rating systems. The use of digital technologies further enables platforms to remotely coordinate, manage and control monetary or non-monetary sharing practices through algorithms such as evaluations, information flows, pricing, rating and insurance (Acquier et al., 2017).

2.2. Sharing economy practices in the construction industry Although a few online platforms, such as EquipmentShare, Dozr, Yard Club, Faber, and Emoding, are continuously evolving to promote the sharing of materials, labour and equipment among construction firms, a very limited number of empirical studies focus on sharing economy practices in the construction industry. The construction sector is characterized by high capital inputs, high energy consumption, and high labour intensity (Chang et al., 2018). It is widely accepted that the construction industry is responsible for a significant portion of energy and material resource consumption. For example, Casanovas-Rubio and Ramos (2017) note that the construction industry produced 35% of total waste in Europe and hence call for improvements in resource utilization efficiency and increases in recycling. With the rise of a sharing economy, under-utilized and idle resource sharing within the construction industry should be regarded as another efficient path to sustainability (Haas, 2017; Kupriyanovsky et al., 2017). Following prior literature on the sharing economy (Acquier et al., 2017; Frenken and Schor, 2017; Muñoz and Cohen, 2017), our study adopts a socio-technical perspective to understand sharing economy practices in the construction sector. The processes of sharing can be understood in terms of the social interactions between community members. The sociological perspective emphasizes community-based interactions, which involve both internal sharing practices among construction project stakeholders and external sharing practices with unfamiliar companies outside the project networks. Moreover, Hamari et al. (2016) regard the sharing economy as a technological phenomenon. The development of information systems and technologies make sharing economy practices more appealing (Frenken and Schor, 2017). The technical perspective implies that both internal and external sharing practices rely on the use of digital platforms. Therefore, this study highlights internal sharing practices, external sharing practices, and digital platform applications as three aspects of sharing economy practices in construction projects. It should be noted that the notion of sharing idle capacity and under-utilized assets is central to the definition of the sharing economy (Frenken and Schor, 2017). Hence, we consider internal sharing practices as practices in which project stakeholders, such as subcontractors and contractors, grant each other temporary access to idle capacity or under-utilized assets during project implementation, mainly for reasons of social concern. For example, subcontractors at a work site can share one tower crane and other machinery to execute their tasks. In particular, information management systems and smart site platforms further promote information and resource sharing among project stakeholders (Braglia and Frosolini, 2014). Internal sharing practices possess more sharing-related attributes, as suggested by Habibi et al. (2016a), which are regarded as not-for-profit initiatives. Through internal sharing practices, stakeholders involved in a construction project intend to establish social capital and links or collaborative relationships so that the project can be successfully delivered. Money is often irrelevant to sharing practices among project stakeholders. External sharing practices are defined as sharing with unfamiliar companies, which promotes temporary access to idle capacity or underutilized assets for monetary benefits, leading to a reduced need for the ownership of these assets. For example, contractors can rent idle machinery from unfamiliar construction firms, such as excavators and bulldozers, to implement their projects rather than purchase such equipment from the market. As another example, construction firms can arrange a trade in spare or idle construction materials. The firms

3. Hypotheses development This study focuses on the impact of sharing economy practices on sustainability performance in the construction sector. The sharing economy practices in construction projects include internal sharing practices, external sharing practices, and the use of digital platforms. Moreover, three dimensions of sustainability performance are considered, including economic performance, environmental performance, and social performance. Fig. 1 presents the conceptual model of this study. We analyse the relationships between the use of digital platforms and internal and external sharing practices from an information processing perspective. Sharing idle and under-utilized resources with both project stakeholders and unfamiliar companies is identified as a highly information-intensive practice. Construction firms have to exchange information about the quality, quantity, available timeframe, price, location, logistics and insurance issues of shared resources. Digital platforms, such as EquipmentShare, Dozr and project management information systems, act as third-party information service platforms, integrating the information from both resource owners and users (Haas, 2017). Firms can directly access the integrated and extensive information about idle and under-utilized resources through digital platforms (Botsman and Rogers, 2010; Martin, 2016), which reduces asymmetry in information flow. Furthermore, the application of data analysis algorithms provided by the platform can even automatically match demand and supply information (Acquier et al., 2017), which enhances information processing capabilities and supports decisionmaking processes for construction firms. Therefore, we argue that the use of digital platforms can promote internal and external sharing practices in a construction project context. H1. The use of digital platforms has a positive impact on (a) internal sharing practices and (b) external sharing practices. Sharing economy practices, including internal sharing practices and external sharing practices, are supposed to promote the economic performance of a construction project. Prior studies have confirmed that partnering with project stakeholders, which is characterized by 3

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Fig. 1. Conceptual model.

Social performance indicates the satisfaction of relevant stakeholders in a construction project, such as the client, end user, government and community (Carter and Jennings, 2002; Govindan et al., 2013). We propose that internal and external sharing practices can contribute to the improvement of social performance through establishing social bonds. Acquier et al. (2017) highlight that the sharing economy, as a way to facilitate less expensive access to goods or services, can be regarded as a new form of collaboration among participants. Sharing with both familiar project stakeholders and weakly connected unfamiliar companies in the construction marketplace can enhance social interaction, promote social networking, and stimulate social learning (Belk, 2010; Gregory and Halff, 2016). Scholars have identified the sharing economy as an incoherent field of innovation (Martin, 2016) through which public, private and non-profit actors collaborate with each other to facilitate social transformation. In this case, intensive sharing practices lead to mutual understanding among relevant stakeholders within a social network. Therefore, the following hypothesis is proposed.

resource sharing practices, has positive effects of reducing costs and improving returns on resources (Larson, 1997; Black et al., 2000; Eriksson, 2015; Kim and Nguyen, 2018). Shared resources among project stakeholders, such as contractors and subcontractors, could include related resources that reduce sub-additive costs or complementary resources that bring super-additive values. Hence, internal sharing practices during project implementation can promote economic performance. Moreover, Martin (2016) indicates that the cost of renting is much lower than the cost of ownership. It can be easily understood that construction firms can save a certain amount of investment by renting equipment from others and swapping reused materials to implement their projects. Firms can also rent out their idle or under-utilized resources to gain additional income. Indeed, both internal and external sharing practices contribute to the improvement of resource utilization efficiency, which implies lower costs and higher revenues for construction firms. Therefore, this study proposes the following hypothesis. H2. (a) Internal sharing practices and (b) external sharing practices have a positive impact on economic performance.

H4. (a) Internal sharing practices and (b) external sharing practices have a positive impact on social performance.

On the environmental side, the inefficiency of resource utilization is known as a major source of construction waste, which leads to environmental pollution. The sharing economy is thought to be less resource intensive and, therefore, an eco-friendly solution (Firnkorn and Müller, 2011). Martin (2016) indicates that a sharing economy enables the more efficient utilization of resources and thus can create environmental value. Construction firms can realize a more intensive and better leverage of resources, such as construction materials and equipment, through sharing with project stakeholders and unfamiliar companies. On the other hand, the owners of under-utilized or idle resources are always responsible for environmental externalities. Owners who decide to engage in sharing economy practices should monitor and control the negative environmental effects of their resources (Acquier et al., 2017). Additionally, sharing practices can lead to environmental performance through “reducing the demand of new goods or the construction of new facilities” (Frenken and Schor, 2017) (p.7). In the construction sector, sharing and renting practices can decrease the consumption of materials and equipment. Based on the above discussion, we propose the following hypothesis.

4. Research methods 4.1. Sampling and data collection It should be noted that sharing economy practices may vary for each construction project due to its one-off and unique nature. Hence, the unit of analysis is the project level in this study. With the rapid rate of economic development, the gross output value of the Chinese construction industry accounted for 25.87% of GDP in 2017. The value of newly signed contracts reached more than 25 trillion CNY. At least 80,000 construction companies are engaged in construction activities in China. Furthermore, the rapid development of the internet and digital technology provides sharing platforms and atmosphere for large or small construction firms and promotes the transformation from a traditional to a modern and sustainable construction industry. Therefore, the Chinese construction industry is identified as an appropriate context for our study on sharing economy practices. We developed a structured questionnaire based on the prior literature using a back translation method. Then, a series of exploratory interviews with practitioners and researchers were undertaken to help

H3. (a) Internal sharing practices and (b) external sharing practices have a positive impact on environmental performance.

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contextualize and formalize the measurement items for each related concept within the questionnaire. We also conducted a pilot study by inviting 10 project managers to refine the questionnaire. In the final version of our questionnaire, the first section required respondents to provide general information about their job title, work experience, the name of the project they were involved in, the role of their company in the project, project duration, and project type. In the second section, the respondents were asked to indicate the degree to which they agree with the statements about the implementation of sharing economy practices in the project. The third section investigated the economic performance, environmental performance, and social performance brought about by the construction project. Then, an online structured questionnaire survey was conducted with respondents from the construction industry in China. The potential respondents were employees in managerial positions in construction projects who had a good understanding of sharing economy practices, such as project managers, department managers, top managers, and project chief engineers. Given that limited direct access to target respondents often leads to a poor response rate through random sampling in the Chinese construction industry, we used the convenience sampling method, which has been confirmed as effective for increasing response rates and is widely used in the construction industry (Wu et al., 2015; Zhang and Qian, 2016). We contacted a famous Chinese research institution, which has more than 1300 registered corporate members from the construction industry. The institution helped us send the questionnaire to targeted respondents from different construction projects. A total of 214 completed responses were received. After removing 6 invalid responses, we had a total of 208 responses. To test non-response bias, we compared the mean difference of the constructs between early and late respondents through a t-test (Lindner et al., 2001). No significant evidence of non-response bias was found. We also assessed the possibility of common method bias by conducting Harman’s one-factor test (Podsakoff and Organ, 1986). This analysis revealed five distinct factors with eigenvalues above 1.0, explaining 52.76% of the total variance. The first factor accounted for 25.63% of the data, which was not the majority of the total variance. Therefore, common method bias was not a problem in this study. Table 1 provides the general information about the respondents and projects. Fifty-eight (27.8%) of the 208 respondents had 4 to 6 years of work experience. Seventy-one (34.1%) of the respondents had 7 to 10 years of work experience. Seventy-five (36.1%) of the respondents had more than 10 years of work experience. In addition, 171 (82.2%) respondents were in managerial positions (i.e., department manager, top manager, and project manager), and the rest were from the operational

level, such as team members and engineers. Most of the respondents were engaged as contractors (38.9%), consultants (33.7%), suppliers (10.1%) and clients (7.7%). The sample also varied widely by the type and duration of the project. The responses covered industrial projects (14.4%), public projects (8.6%), infrastructure projects (16.3%), commercial projects (28.4%), and residential projects (32.3%). Approximately 63.0% of the projects in this survey lasted less than 3 years, and the duration of the rest was greater than 4 years. 4.2. Measures This study investigates the relationship between sharing economy practices and sustainability performance in the context of construction projects. Table 2 presents the measurement items for each related construct. Each of the items is measured by a five-point Likert scale of 1–5, ranging from ‘strongly disagree’ to ‘strongly agree’. We identify three critical elements of sharing economy practices, i.e., the use of digital platforms, internal sharing practices and external sharing practices, based on the literature of Habibi et al. (2016a), Frenken and Schor (2017), and Muñoz and Cohen (2017). Construction firms post or receive requests for information about materials, labour or equipment through digital platforms, particularly open-access internetbased platforms (Habibi et al., 2016b; Acquier et al., 2017; Fraccascia and Yazan, 2018). As shown in Table 2, three items are proposed to measure the use of digital platforms. Internal sharing practices include sharing idle and under-utilized resources, such as construction materials, mechanical equipment and workers, and intangible assets such as information and knowledge, with internal project stakeholders (Black et al., 2000; Habibi et al., 2016b). Hence, we have three items to capture internal sharing practices in construction projects. External sharing practices are defined as sharing idle and under-utilized resources with unfamiliar companies (Habibi et al., 2016a, b; Acquier et al., 2017). For example, construction firms may lease equipment and materials from unfamiliar firms when implementing their projects. Furthermore, construction firms may lease their idle equipment or materials to unfamiliar firms. We also consider another item “using outsourced labour service” to measure external sharing practices. Sustainability performance includes three dimensions, i.e., economic performance, environmental performance and social performance (Keeble et al., 2003; Govindan et al., 2013; Morioka and Carvalho, 2016). Economic performance indicates that construction projects can contribute to the cost objectives and financial objectives of the organization (Govindan et al., 2013; Musawir et al., 2017). Environmental performance is measured by three items, including reductions in energy consumption, reductions in construction waste and decreases in the frequency of environmental accidents (Govindan et al., 2013). Social performance refers to the relationship with local communities and other relevant stakeholders (Carter and Jennings, 2002; Govindan et al., 2013). This paper identifies social performance as the satisfaction of stakeholders, such as the client, end user, government and the public (Keeble et al., 2003; Govindan et al., 2013). Hence, four measurement items in Table 2 are used to capture social performance in this study. In addition to considering sharing economy practices, which may influence the sustainability performance of a construction project, this study controls for project duration and project type in the model. Generally, a construction project with a longer duration may have greater impacts on economic, environmental and social performance than does a shorter-duration project (Suprapto et al., 2016). Project type, categorized as industrial, public, infrastructure, commercial, or residential project, was considered in the model as a potential influence on performance outcomes (Wang et al., 2017). Four dummy variables were designed to measure project type.

Table 1 The background information about the respondents and projects. Working experience (year)

Frequency

Company type

Frequency

1-3 4-6 7-10 > 10 Total job title top manager department manager project manager project team member chief engineer others Total

4 58 71 75 208 Frequency 35 44 92 17 17 3 208

client supplier contractor consultant designer Total Project duration (years) 1-3 4-6 >7 Total Project type industrial project public project infrastructure project commercial project residential project Total

16 21 81 70 20 208 Frequency 131 56 21 208 Frequency 30 18 34 59 67 208

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Table 2 Measurement items for all the relevant constructs. Construct and measures

Item loading

The use of digital platforms (DP) (Acquier et al., 2017; Muñoz and Cohen, 2017; Fraccascia and Yazan, 2018) DP1 We often browse, follow and use the open access internet-based platforms. 0.616 DP2 We post our requests for information (e.g., materials, equipment and labour service) on the 0.742 open access internet-based platforms. DP3 We obtain information requests (e.g., materials, equipment and labour service) from the open 0.789 access internet-based platforms. Internal sharing practices (IS) (Black et al., 2000; Habibi et al., 2016a; Acquier et al., 2017) IS1 We shared project related information with our partners. 0.777 IS2 We shared equipment and materials with our project partners. 0.672 IS3 We shared knowledge and experience with our project partners. 0.745 External sharing practices (ES) (Habibi et al., 2016a, b; Acquier et al., 2017; Muñoz and Cohen, 2017) ES1 We leased reusable equipment and materials from other construction firms. 0.635 ES2 We would lease reusable equipment and materials to other projects or companies. 0.704 ES3 We used outsourced labour service rather than hired full-time workers. 0.840 Economic performance (EcP) (Govindan et al., 2013; Musawir et al., 2017) EcP1 Our project successfully met the budget goals. 0.730 EcP2 Our project successfully achieved the organization’s financial objectives. 0.721 EcP3 Our project successfully satisfied project investors’ objectives. 0.743 Environmental performance (EnP) (Govindan et al., 2013) EnP1 Our project successfully reduced energy consumption. 0.673 EnP2 Our project successfully reduced construction wastes. 0.768 EnP3 Our project successfully decreased the frequency of environmental accidents. 0.697 Social performance (SP) (Carter and Jennings, 2002; Govindan et al., 2013) SP1 Our project successfully satisfied the client’s needs. 0.808 SP2 Our project successfully satisfied the users’ needs. 0.657 SP3 Our project successfully satisfied the government’s needs. 0.600 SP4 Our project successfully satisfied the public’s needs. 0.682

S.E.

t value

Reliability/ validity

0.086 0.059

7.149 12.651

Cronbach's α = 0.533, CR = 0.761, AVE = 0.517

0.064

12.288

0.040 0.067 0.046

19.419 10.040 16.200

Cronbach's α = 0.565, CR = 0.776, AVE = 0.536

0.143 0.130 0.088

4.437 5.408 9.500

Cronbach's α = 0.604, CR = 0.773, AVE = 0.535

0.073 0.071 0.064

10.033 10.227 11.701

Cronbach's α = 0.567, CR = 0.775, AVE = 0.535

0.068 0.047 0.079

9.919 16.456 8.803

Cronbach's α = 0.518, CR = 0.757, AVE = 0.510

0.037 0.081 0.075 0.063

21.678 8.073 8.014 10.873

Cronbach's α = 0.632, CR = 0.783, AVE = 0.477

subsamples.

4.3. Data analysis technique Structural equation modelling (SEM) was applied for data analysis in this study. SEM involves both observable variables, which are directly measured, and latent variables, which are inferred from the observable variables. In addition, SEM includes measurement and structural models. A measurement model examines the relationships between each latent variable and its respective observable variables, whereas a structural model shows relationships among latent variables (Zhao and Singhaputtangkul, 2016). SEM executes confirmatory factor analysis and path analysis simultaneously in a single structural equation model and hence can enable maximally efficient fit between the data and a structural model (Lim and Loosemore, 2017). Previous studies have applied two types of SEM: covariance-based SEM (CB-SEM) and partial least-squares SEM (PLS-SEM). In the present study, PLS-SEM was selected instead of CB-SEM for three reasons. First, PLS-SEM can address more complex models than can CB-SEM and achieve high levels of statistical power with a small sample size (Fornell and Bookstein, 1982). Hence, it is an appropriate method to test the complex relationships among the three aspects of sharing economy practices and the three dimensions of sustainability performance in the present study. Second, PLS-SEM is appropriate for the exploratory nature of this study and is oriented towards predictive application (Lim and Loosemore, 2017). Third, PLS-SEM is a distribution-free method, lacking the requirement for normally distributed data (Hair et al., 2016). Since the measurement items in this study are perception based and have unknown distributions, PLS-SEM is more appropriate than CBSEM for our purposes. PLS-SEM has been widely used by construction researchers, including Aibinu et al. (2011); Suprapto et al. (2016); Lim and Loosemore (2017), and Wang et al. (2017). We followed the guidelines of Hair et al. (2016) to evaluate the measurement model and structural model based on PLS-SEM. The measurement model indicates the reliability and validity of the constructs, and the results of the structural model with path coefficient provide evidence for the validation of the hypothesized relationships. To assess the significance of the factor loadings and path coefficients, we further used a bootstrapping procedure with 208 cases and 5000

5. Results 5.1. Measurement model results The measurement model results indicate the reliability and validity of the constructs. Each construct in this study is composed of at least three measurement items to ensure content validity. Internal consistency reliability can be confirmed when the Cronbach’s α is larger than 0.50 in an exploratory study (Nunnally et al., 1978). In our study, the Cronbach’s α for external sharing practices and social performance is 0.604 and 0.632, respectively, which are greater than 0.60. The Cronbach’s α for the use of digital platforms, internal sharing practices, economic performance, and environmental performance is 0.533, 0.565, 0.567, and 0.518, respectively. Although these values of Cronbach’s α are low, the composite reliability (CR) values are all above 0.70 (Hair et al., 1998). Moreover, as shown in Table 2, all the factor loadings for the constructs in our study are greater than 0.600 (Comrey, 1973) and are significant at p < 0.01 (Anderson and Gerbing, 1988), indicating an acceptable construct reliability. The estimates of average variance extracted (AVE) are greater than 0.50 (Fornell and Larcker, 1981) for all the constructs except social performance (with a value of 0.477). Since our study satisfied the more detailed criteria, such as the Cronbach’s α, factor loadings and CR, as indicated above, the convergent validity can be ensured. This study applied the Fornell-Larcker criterion to validate discriminant validity (Fornell and Larcker, 1981). The results presented in Table 3 indicate that the square root of the AVE for each construct in our study is greater than its correlation with other constructs. Additionally, the Heterotrait-Monotrait ratio of correlation (i.e., HTMT) values should be below 0.90 (Henseler et al., 2015). Furthermore, Table 4 shows the results of the cross loadings. According to Table 4, all the items have stronger loadings (> 0.600) on their respective constructs and lower loadings (< 0.500) on other constructs, which provides further evidence of discriminant validity. 6

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of the effects of digital platforms on internal and external sharing practices are interpreted based on effect size (f2). The results indicate that the use of digital platforms has a stronger effect on internal sharing practices (f2 = 0.325) than on external sharing practices (f2 = 0.040). Moreover, H2(a), H3(a), and H4(a) are supported, with path coefficients of 0.426 (p = 0.000, f2 = 0.166), 0.442 (p = 0.000, f2 = 0.217), and 0.507 (p = 0.000, f2 = 303), respectively. Hence, internal sharing practices are confirmed to have positive effects on economic performance, environmental performance, and social performance. The effect sizes indicate that internal sharing practices have the strongest effect on social performance. Additionally, external sharing practices are positively related to environmental performance, with a path coefficient of 0.162 (p = 0.011, f2 = 0.034). H3(b) is therefore supported. However, the influence of external sharing practices on economic performance and social performance is not significant. H2(b) and H4(b) are not supported. By comparing the values of f2, we find that internal sharing practices have stronger effects on sustainability performance than do external sharing practices. We also conducted a post hoc analysis to test the indirect effect of the use of digital platforms on sustainability performance. According to the results of the indirect effects shown in Table 6, the path coefficients for “DP→IS→EcP”, “DP→IS→EnP”, and “DP→IS→SP” are 0.211 (p = 0.000), 0.219 (p = 0.000), and 0.251 (p = 0.000), respectively. However, the path coefficients for “DP→ES→EcP”, “DP→ES→EnP”, and “DP→ES→SP” are not significant. The results indicate that the use of digital platforms can influence economic performance, environmental performance and social performance only indirectly through internal sharing practices.

Table 3 Fornell-Larcker criterion values. Construct

DP

IS

ES

EcP

EnP

SP

DP IS ES EcP EnP SP

0.719 0.495 0.196 0.450 0.516 0.509

0.732 0.235 0.414 0.480 0.510

0.731 0.067 0.268 0.139

0.732 0.406 0.393

0.714 0.593

0.691

Table 4 Cross loadings. Cross loadings

DP

IS

ES

EcP

EnP

SP

DP1 DP2 DP3 IS1 IS2 IS3 ES1 ES2 ES3 EcP1 EcP2 EcP3 EnP1 EnP2 EnP3 SP1 SP2 SP3 SP4

0.616 0.741 0.789 0.337 0.395 0.357 0.117 0.083 0.200 0.326 0.318 0.342 0.361 0.414 0.328 0.492 0.360 0.191 0.341

0.274 0.405 0.374 0.777 0.672 0.745 0.040 0.211 0.220 0.350 0.288 0.272 0.332 0.386 0.309 0.398 0.272 0.367 0.355

0.151 0.156 0.119 0.167 0.216 0.134 0.635 0.704 0.840 0.011 0.138 0.008 0.186 0.149 0.241 0.072 0.127 0.085 0.115

0.206 0.401 0.337 0.307 0.338 0.267 0.071 0.003 0.069 0.730 0.721 0.743 0.271 0.342 0.253 0.274 0.208 0.302 0.301

0.435 0.378 0.319 0.381 0.340 0.333 0.083 0.209 0.252 0.240 0.330 0.324 0.673 0.768 0.697 0.467 0.349 0.393 0.415

0.419 0.313 0.389 0.383 0.287 0.445 0.073 0.035 0.160 0.160 0.386 0.327 0.381 0.498 0.384 0.808 0.657 0.600 0.682

6. Discussion 6.1. Theoretical implications

5.2. Structural model results

This study investigates the impact of sharing economy practices on sustainability performance in the construction industry. The findings contribute to the literature on the sharing economy from three aspects. First, our study can help scholars enhance their understanding of sharing economy practices by identifying three different dimensions from the socio-technical perspective and further revealing the interrelationships among these dimensions. Prior studies have described some key elements of the sharing economy, such as platforms for collaboration, under-utilized resources and peer-to-peer interactions (Hamari et al., 2016; Acquier et al., 2017; Muñoz and Cohen, 2017). However, a unified theoretical perspective is necessary to establish a framework of sharing economy practices. In our study, the sociological perspective indicates that firms share under-utilized and idle resources within the social network (Martin, 2016). Hence, this study proposes that construction firms are engaged in sharing practices with internal project stakeholders and unfamiliar firms. From a technical perspective, the use of digital platforms extends sharing economy practices (Habibi et al., 2016a; Frenken and Schor, 2017). In addition, the findings of our study demonstrate that the use of

This study performed the full PLS-SEM structural model to estimate the path coefficients between all the constructs. To assess the structural model, we calculated the coefficients of determination of R2 for all the endogenous constructs in this study. The results indicate that the structural model accounts for 24.5% of internal sharing practices, 3.8% of external sharing practices, 17.6% of economic performance, 25.6% of environmental performance, and 26.2% of social performance. Moreover, the construct cross-validated redundancy index (Q2) was estimated for endogenous constructs. All the values of Q2 are greater than 0, indicating the predictive relevance of the structural model according to Hair et al. (2016). Table 5 indicates the structural model results for the hypothesis testing. The significance of all the path coefficients was assessed through a bootstrapping procedure with 208 cases and 5000 subsamples. Accordingly, H1(a) and H1(b) are supported with path coefficients of 0.495 (p = 0.000) and 0.196 (p = 0.007), respectively, which indicate that the use of digital platforms can promote the implementation of internal and external sharing practices. The strengths Table 5 Structural model results. Path

Standardized coefficient

Standard deviation

T statistic

p value

f2

Inference

H1(a): DP→IS H1(b): DP→ES H2(a): IS→EcP H2(b): ES→EcP H3(a): IS→EnP H3(b): ES→EnP H4(a): IS→SP H4(b): ES→SP

0.495*** 0.196** 0.426*** −0.033 0.442*** 0.162* 0.507*** 0.021

0.067 0.071 0.070 0.073 0.069 0.067 0.062 0.067

7.434 2.753 5.382 0.364 6.010 2.433 7.646 0.192

0.000 0.006 0.000 0.716 0.000 0.015 0.000 0.848

0.325 0.040 0.208 0.001 0.249 0.034 0.329 0.001

Supported Supported Supported Not supported Supported Supported Supported Not supported

Note: ***p < 0.001; **p < 0.01; *p < 0.05. 7

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external sharing practices with unfamiliar companies, thereby contributing greatly to the sharing economy literature. Third, our research further indicates that the use of digital platforms indirectly and positively influences sustainability performance through internal sharing practices. The development of internet-based and digital-based technologies provides a new path for sustainability (Wong and Zhou, 2015; Miao et al., 2017). Fraccascia and Yazan (2018) validate that online information-sharing platforms can create both economic and environmental benefits. Indeed, in the era of the sharing economy, platforms use digital technologies to organize and expand marketplaces, which can lower transaction costs for resource owners and users (Botsman and Rogers, 2010). Acquier et al. (2017) indicate that digital platforms provide much broader and less expensive access to products and services and establish social bonds among peers. This study shows that the effects of digital platforms rely on firms’ extensive participation in sharing practices, particularly internal sharing with familiar partners or stakeholders. In other words, the realization of sustainability performance cannot be determined only by the use of digital platforms in the context of a sharing economy. Therefore, although prior studies have widely emphasized the significance of digital platforms (Srineck, 2016), the findings in our study highlight the joint effect of digital platforms and internal sharing practices on sustainability performance.

Table 6 Indirect effects. Path

Standardized coefficient

Standard deviation

T statistic

p Value

DP→IS→EcP DP→IS→EnP DP→IS→SP DP→ES→EcP DP→ES→EnP DP→ES→SP

0.211*** 0.219*** 0.251*** −0.007 0.032 0.004

0.053 0.054 0.051 0.016 0.020 0.015

3.980 4.084 4.945 0.400 1.619 0.275

0.000 0.000 0.000 0.689 0.106 0.783

Note: ***p < 0.001; **p < 0.01; *p < 0.05.

digital platforms as the technical element of sharing economy practices enables both internal and external sharing practices. In the Chinese construction industry, the emergence of digital platforms such as Huizhuiyun (http://www.huizhuyun.com/), SoucaiCN (http://www. soucaicn.com/), and Emoding (https://www.emoding.com/) have greatly advanced the sharing economy with respect to renting, swapping, sharing and exchanging construction equipment, materials and workers. The results indicate that the use of these digital platforms has a greater impact on internal sharing practices with familiar project stakeholders than on external sharing practices with unfamiliar companies. A possible reason for this finding is that Chinese construction firms prefer to share under-utilized and idle resources with familiar partners than to share them with unfamiliar ones. Due to the lack of social bonds and trust between unfamiliar companies, sharing with unfamiliar companies entails higher risk, such as higher risk of moral hazards, opportunistic behaviours, contractual disputes, and warranty issues (Malhotra and Van Alstyne, 2014; Frenken and Schor, 2017). Hence, in construction projects, the impact of digital platforms on external sharing practices is weakened to a certain degree. Overall, the findings of our study complement the study of Martin (2016) by revealing the dimensionality of sharing economy practices in the construction sector and explaining how the sharing economy is being and can be transformed. Second, this study establishes links between sharing economy practices and sustainability performance in the construction project context. Scholars have widely discussed how sharing economy practices influence economic, environmental and social performance (Heinrichs, 2013; Fang et al., 2016; Martin, 2016; Frenken and Schor, 2017; Kumar et al., 2017). However, limited empirical evidence is provided to support the effects. Our study conducted a survey in the Chinese construction industry to explore the relationship between different dimensions of sharing economy practices and sustainability. The results indicate that only internal sharing economy practices promote all three aspects of sustainability performance (i.e., economic, environmental, and social performance). External sharing practices promote only environmental performance. Given the early stage of development of the sharing economy in the Chinese construction industry, effective guarantee mechanisms for sharing practices with unfamiliar companies are presently lacking. Participants in external sharing practices have to carefully evaluate the quality of second-hand shared equipment and materials and negotiate the warranty responsibilities in maintenance and repair. Hence, we argue that external sharing practices may be associated with high levels of transaction costs, such as negotiation and monitoring costs. Moreover, exchange hazards (e.g., opportunism behaviours and moral hazards) caused by the uncertainty and complexity of external sharing practices may damage the interests and decrease the satisfaction of project stakeholders. All these negative effects of external sharing practices in construction projects may offset the positive effects on economic and social performance. Nevertheless, the findings show that sharing with unfamiliar companies can contribute to environmental performance through recycling construction materials that may otherwise contaminate the environment. Our study identifies the different effects of internal sharing practices with project stakeholders and

6.2. Managerial implications The findings also provide some managerial insights for construction firms. Firms can understand sharing economy practices from three dimensions, including the use of digital platforms, internal sharing practices, and external sharing practices. As the sharing economy expands through the construction industry, managers should share underutilized and idle resources with their familiar stakeholders and unfamiliar companies by using digital platforms. Moreover, the results indicate that digital platforms can promote the implementation of both internal and external sharing practices by improving firms’ information collection and processing capabilities. Algorithms such as evaluating, pricing, rating and insurance (Acquier et al., 2017), which are provided by digital platforms, can also help mitigate the potential risks associated with sharing economy practices. With the development of digital-based and internet-based technologies, construction firms are encouraged to fully utilize advanced technologies and platforms to better manage sharing practices. Additionally, internal sharing practices have positive effects on all three dimensions of sustainability performance, whereas external sharing practices with unfamiliar companies are not positively related to economic and social performance. The findings indicate that construction firms can start by sharing with their familiar partners if they are not well prepared to address the sharing economy. Sharing construction materials, equipment and workers with unfamiliar companies is regarded to be associated with higher levels of risk (Malhotra and Van Alstyne, 2014; Frenken and Schor, 2017). We interviewed one project professional from a famous Chinese construction firm, and he expressed concerns about quality issues in regard to the shared resources, complex negotiation processes, and high transaction costs. Therefore, construction firms are rarely able to manage external sharing practices well to achieve sustainability benefits. Particularly in emerging markets such as China, an effective legal system to safeguard external sharing practices is typically lacking. 7. Conclusions This study explores the relationship between sharing economy practices and sustainability performance in the construction industry. The use of digital platforms, internal sharing with familiar stakeholders and external sharing with unfamiliar companies are identified as three key elements of sharing economy practices. Sustainability performance 8

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is divided into economic, environmental and social performance. Based on a survey in the Chinese construction industry, this study finds that the use of digital platforms can promote internal and external sharing practices. Furthermore, internal sharing practices have positive effects on all three dimensions of sustainability performance, while external sharing practices can facilitate only environmental performance. The findings confirm that the use of digital platforms influences sustainability performance through internal sharing practices. This study contributes to an advanced understanding of sharing economy practices and provides empirical evidence on the links between the sharing economy and sustainability performance. The findings also provide managerial insights into how to understand and implement sharing economy practices. Although theoretical and managerial implications are summarized, this study still has some limitations that also indicate future research directions. First, this study conducted a survey in the Chinese construction industry. China, as an emerging market, has been witnessing the rise of a sharing economy in recent years. However, market regulation and technological development differs between emerging and developed markets. The impact of sharing economy practices on sustainability performance may vary between emerging and developed markets. We suggest that additional empirical evidence should be provided in the context of developed markets. Second, the effects of external sharing practices with unfamiliar companies on economic and social performance are not significant in this study. We argue that external sharing practices are characterized by higher levels of risk, which may impede the realization of sustainability performance. Therefore, governance arrangements, such as contracts, trust and relational norms (Gong et al., 2018), are required to match sharing practices. It is worth exploring the moderating effect of governance arrangements on the relationship between external sharing practices and sustainability performance.

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