Blockchain technology is one of the emerging innovative technologies making waves globally, and it has been adjudged to have the capability to transform businesses. With the different capabilities of the technology, such as immutability of information and decentralisation of authority attributes, the built environment is slow in its adoption. This study aims to explore the barriers to the implementation of blockchain technology in the construction using a principal component analysis (PCA) approach.
This research took a post-positivist philosophical stance, which informed a quantitative research approach through a questionnaire survey. From the South African built environment and information technology sector, 79 respondents were drawn through a snowballing sampling technique. The built environment professionals include architect, construction project manager, construction manager, quantity surveyor and engineer. Retrieved data were screened and analysed by adopting the descriptive analysis and PCA while Cronbach alpha evaluated the reliability. Also, Kruskal–Wallis H non-parametric test was used to determine the differences in the opinion of the respondent groups.
The analysis revealed that all the identified barriers ranked above the average mean with lack of clarity, scalability risks and lack of skills or knowledge ranking top three. PCA clustered the identified barriers into three components: organisational barriers, social barriers and technological barriers.
This study was carried out in the Gauteng province of South Africa, leaving out other provinces due to accessibility, cost and time constraints.
Built environment organisations need to be kept abreast of the capabilities of blockchain technology as the major barrier observed was the lack of clarity of blockchain technology. Also, the technological barriers identified from this study need to be addressed by information technology experts to give consumers the desired value for money in implementing blockchain technology for the built environment.
The blockchain technology capabilities are incomparable to any other invention thus far. Therefore, it is very important that the numerous stakeholders in the built environment be made aware of the blockchain technology capabilities while formulating a solution to the identified barriers. This will aid its implementation in the built environment and help the industry measure up with its counterparts.
Akinradewo, O.I., Aigbavboa, C.O., Edwards, D.J. and Oke, A.E. (2022), "A principal component analysis of barriers to the implementation of blockchain technology in the South African built environment", Journal of Engineering, Design and Technology, Vol. 20 No. 4, pp. 914-934. https://doi.org/10.1108/JEDT-05-2021-0292
Emerald Publishing Limited
Copyright © 2022, Opeoluwa Israel Akinradewo, Clinton Ohis Aigbavboa, David John Edwards and Ayodeji Emmanuel Oke.
Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Organisations in the built environment are experimenting and developing innovative tools and technologies as the support for the fourth industrial revolution market is progressing (Smith and O’rourke, 2019). One of the main problems standing as a barrier to modernisation in the industry is the failure to adopt technological developments that could have helped up the industry’s achievements as obtained in the automobile, manufacturing and mechanical engineering sectors (Barima, 2017; Merschbrock, 2012). In its 2018 Digital World Report, the Institution of Civil Engineers (2018) reported that industries globally are gravitating into a world of networking, technology and data abundance. This move gives a potential increase in profitability, quality and competitiveness of the industry, thereby allowing development. Productive and efficient improvements are necessary for the competitiveness of the built environment. The UK Government in 2013 recognised the importance of this and published a “construction 2025 joint government-industry strategy”, which set the target of reducing greenhouse gas emissions by 50%, delivering projects faster by 50%, exports improvement by 50% and cost reduction by 33%. Blockchain technology (blockchain technology) is one of the emerging innovative technologies making wave globally. It has been adjudged to have the capabilities to transform global markets in which the built environment is not an exception (Smith and O’rourke, 2019). Bitcoin (the world’s first cryptocurrency), a unit of payment that uses blockchain technology platform, was developed in 2008 (Rasoloharijaona et al., 2003). According to research, blockchain technology is termed a more significant technology than the breakthrough of the internet with its potential to reduce costs, improve efficiency and increase profitability (Smith and O’rourke, 2019). The blockchain serves as an encrypted ledger allowing transactions to be carried out in a shared way. Blockchain-based applications are growing in a wide range of sectors, including financial markets (Zheng et al., 2017). Since the introduction of blockchain, smart contracts became one of the key common innovations due to their strong customisability to transactions. Owing to their development, smart contracts also face several problems for the parties who deal with them: consumers, developers and companies that are based on smart contracts (Zykov, 2018). A smart contract is an enforceable algorithm that operates on the top of the blockchain to negotiate, implement and enforce an arrangement among untrusted parties without the intervention of a trustworthy third party (Hasan et al., 2019).
According to Busby (2018), organisations across industries are making attempts to figure out the influence of blockchain technology on businesses. Blockchain technology was tagged business buzzword of the year by The Guardian and some other outlets in 2017, and it prompted organisations to start assessing the different application, so blockchain technology without having a full understanding of its working principle (Popper, 2018). Accenture (2017) carried out a study that estimated that blockchain technology can save investment banks up to half of the world’s annual gross domestic product. This was misunderstood by the general public as they equate Blockchain with Bitcoin. However, Leibson (2018) stated that “Bitcoin is not Blockchain and Blockchain is not Bitcoin”. Smith and O’rourke (2019) buttressed this further by stating that “Blockchain is to Bitcoin what the internet is to email; a vast electronic system on which various application can be built and the currency is just one”. Blockchain technology has its advantages built on its redefinition of the trust, openness and inherent immutability. These characteristics give safe and fast solutions to transactional issues both in private and public business dealings (Underwood, 2016). To clarify further, O’Boyle (2017) explained blockchain technology to be an “internet of value” because of its decentralising and irrevocability nature such that it would continue to have an impact on businesses for about 20 years (Khaqqi et al., 2018). According to Akinradewo et al. (2021) and Tapscott and Tapscott (2017), using blockchain to streamline contractual procedures and the numerous paperwork supporting complex building projects will save time, free up limited funds and hasten project completion in the construction industry. There has been a recent confluence between blockchain with industry 4.0 technology (i.e. big data, artificial intelligence, the Internet of things and robots). This collaborative effort can result in a shared economy, transparent operations and environmentally friendly supply chain (SC) management in the built environment (Sadeghi et al., 2021). With the different capabilities of blockchain technology highlighted, the slow adoption of this technology in the built environment begs for questions. To seek answers to these questions, this study explores the barriers to the implementation of blockchain technology in the construction using a principal component analysis (PCA) approach. This is with the view to categorise the barriers into clusters to assist in finding solutions to the identified barriers. A similar study has been conducted by Biswas and Gupta (2019), which took a broad approach with a general overview of different industries. This could be applied to the built environment; however, due to the peculiarity and distinct nature of the built environment, there is a need to evaluate these barriers in the built environment industry context.
2. Characteristics of blockchain technology
Blockchain works with a group of nodes connected via a network. Once a transaction is initiated, it is communicated through the network for the network nodes to validate and check the transaction by carrying out predefined tests concerning the transaction layout and activity (Karafiloski and Mishev, 2017). Blockchain technology offers various features that categorise it as a revolutionising technology across various sectors of the economy. These features include autonomy, decentralisation, peer-to-peer relationship, timestamping and immutability (San et al., 2019). Blockchain technology possesses the characteristics of being autonomous such that once the blockchain application is programmed and launched, transactions are completed without having to involve the programmer (Swan, 2015). Automation entails the implementation of algorithms and guidelines that can systematically activate the performance of smart contracts through self-containment, self-enforcement, self-execution and self-verification (Aste et al., 2017). Therefore, the digital aspect of blockchain technology is programmed such that the transactions are bound to computational coded rules to automatically trigger transactions between nodes without needing the intervention of humans (Heap, 2017).
The key feature of blockchain technology is decentralisation, which separates it from the conventional centralised standard database system or platform that we are using. Decentralisation ensures that no broker or central body, such as a money transfer agent or a prosecutor, is required to validate the terms of the contract (Koutsogiannis and Berntsen, 2017). Every participant or chosen participant on a blockchain has access, without the assistance of an intermediary (Heap, 2017), to check its transaction partners’ records and access the full database and its complete background directly. Basically, by eliminating the need for the position of trust protection intermediary, blockchain eliminates the criteria for centralised authority (Alcazar, 2017). In other words, there is no one database or organisation or group on which it relies solely on managing data or information (Heap, 2017; Koutsogiannis and Berntsen, 2017). Another core aspect of blockchain is its notion of peer-to-peer networks that facilitate the activity of data or monetary transactions from one wallet to another wallet without the intermediary of a trustworthy third party or central authority. It was pointed out that “Both the private and public sectors have great expectations for blockchain technology because it provides the bedrock for developing peer-to-peer platforms for exchanging information, assets, and digitized goods without intermediaries” (Swan, 2015). The recording of transactions or information within the blockchain network is timestamped. This allows for chronological and historical fulfilment, especially in the smart contract of blockchain technology 2.0, which is currently evolving broadly across numerous industries. Blockchain can be used to timestamp as a proof of existence of a digital or digitalised commodity at a given moment (Swan, 2015). Since blockchain technology is a decentralised network, the same information or transaction record is exchanged and owned by any user or node in the blockchain organisation. This varies somewhat from conventional networks or centralised parties, owned entirely by central servers or trustworthy third-party officials. When the central position is compromised and hijacked, critical documents and monetary transaction records are destroyed. However, blockchain retains an eternal database of the ledger system transactions, rendering it impossible to be falsified after the event (Apte and Petrovsky, 2016) because the evidence is not stored in one location, yet encrypted and separated across everyone in the network (Ramage, 2018).
Blockchain technology’s immutability, traceability and transparency result in improved accountability, auditability and decreased bureaucracy. This can change the built environment methods to promote technology improvements and align it with other automotive, mechanical engineering and logistics industries. As a result, the sector will be able to manage resources better and save costs, project durations and payment conflicts (Nanayakkara et al., 2021; Perera et al., 2020; Li et al., 2019). Despite the numerous advantages of implementing blockchain technology in the business process of the built environment, blockchains are not as scalable as conventional centralised systems. Transactions are delayed on blockchain technology due to network congestion. This issue is connected to blockchain network scalability concerns. Simply said, the more users or nodes that join the network, the greater the odds of it slowing down. However, the way blockchain technology works is changing at an accelerating rate. Scalability alternatives are also being incorporated with the proper growth of technology. The idea is to conduct transactions off-chain and just store and access data on the blockchain. Aside from that, new approaches to scalability exist, such as permissioned networks or using a different architectural blockchain solution, such as Corda (Singh et al., 2020; Ismail and Materwala, 2019). The miners must solve issues every time the ledger is updated with a new transaction, which requires a lot of energy. Not all blockchain systems, however, function in the same way. Other consensus methods have successfully handled the problem. Permissioned or private networks, for example, do not have these issues since the number of nodes in the network is limited. They also use efficient consensus procedures to obtain consensus because there is no requirement for global consensus (Woo et al., 2020, 2021).
2.1 Blockchain technology in built environment
The launch of Industry 4.0 technologies has been both fashionable and appealing due to its potential benefits and its role in the real world (Frank et al., 2019). However, businesses and SCs require further analysis to appreciate these exponential and growing developments better, particularly where Business 4.0 technology presents unique operational advantages and tangible business opportunities (Frank et al., 2019). One of the most common technologies that can effectively be used for all Industry 4.0 SC management applications is the blockchain (Osterwalder and Pigneur, 2010). Firms should consider how their business model can be affected by rapidly growing blockchain implementations (Pournader et al., 2020). Also, creating a digital identity enables individuals to exchange the related knowledge approved by the awarding institution. Identities of individuals and companies in the construction industry can be safely registered in the blockchain and used to create credibility over time for work or contracts. This identity and credibility scheme would make it easier for individuals who do not already recognise or have trust in each other to do business (Hughes and Hughes, 2017). Most of the emphasis on blockchain today focuses on the ability to change the financial services sector fundamentally. However, the reach of blockchain technology goes beyond the financial market (Hughes et al., 2019). Thus, blockchain is projected to challenge existing business structures and generate opportunities for new value creation. Blockchain technology has the potential to address several of the industry’s concerns regarding building information modelling (BIM) adoption, including confidentiality, provenance tracking, disintermediation, non-repudiation, multiparty aggregation, traceability, inter-organisational record-keeping, change tracing and data ownership (Turk and Klinc, 2017). There are numerous applications of blockchain technology in the construction industry in general, which include recording digital property, timestamping transactions, multi-signature of transactions, smart contracts (computer programmes that monitor and execute themselves) and smart oracles (real-world repositories of information used in conjunction with smart contracts) (Li et al., 2019; Turk and Klinc, 2017).
Blockchain-based BIM implementation is an administrative task that has experienced significant changes over the years. In this system, modelled information on the BIM platform is managed using blockchain technology, ensuring the information is secured while all the professionals involved have access to them (Sinenko et al., 2020). The electronic document management (EDM) platform was developed only before blockchain technology was established. It has been modified from time to time over the past years. EDM in the construction industry plays a major role in simplifying the added complexity of construction and procurement projects (Ogunde et al., 2017). Blockchain technology is expected to deliver a more robust and cheaper technological alternative to the existing EDM system. Blockchain can provide a secure information storage infrastructure across the life cycle design processes of a construction project. With the introduction of blockchain technology, each record may be stored in a digital database, allowing for a complete signature of its formation, deletion and update. Record of relevant design records, including sketches, site instructions, certificates, variation orders and construction work, program can be done in a decentralised setting where certain records require confirmation of participants in the blockchain platform (Hung et al., 2009).
2.2 Barriers to blockchain technology implementation
The introduction of blockchain technology into businesses involves high costs as emerging technology procurement, and deployment costs are always high (Heilig et al., 2017). Also, the preparation of workers to deal with these shifts is often costly but necessary (Rohleder, 2017). Therefore, to incorporate blockchain technology into a business, significant investments have to be made at the outset, after which profits can be made by reducing workload and time saves, but only after the technology has been used efficiently for a prolonged time span (Dobrovnik et al., 2018; Hinckeldeyn, 2019). Casey and Wong (2017) pointed attention to the organisational, logistics and political challenges of blockchain technology. The authors pointed out the absence of regulatory frameworks, the lack of legal protections, the lack of standardisation and the lack of a roadmap for market growth. There is also a new allocation of roles that comes with the adoption of blockchain technology. Companies have to take on different and unfamiliar positions, especially in the deployment process, which can negatively impact businesses (Seebacher and Schüritz, 2020). The predefined block size of the sent information, the speed of transmission via the network, the underlying proof-of-work protocol and the verification of miner information on every node are important factors in blockchain use (Gervais et al., 2016). The size of each block is currently restricted to 1 MB (Abramova and Böhme, 2016; Beer and Weber, 2015), since the inventors of blockchain feared that bigger blocks would bring centralisation in network operations, jeopardising the entire core of blockchains (Nakamoto, 2008). On the other hand, the increased block size will allow for a bigger number of transactions right away, as well as a scalable blockchain application in sectors and services other than cryptocurrencies (Biswas and Gupta, 2019).
Blockchain users are constantly concerned about whether payment merchants would use the new instrument effectively in the future (Böhme et al., 2015). Otherwise, the whole exercise of establishing blockchains as a transformative platform for many businesses may be rendered fruitless. If existing users are unsure about the success of blockchains, the current buzz around their adoption becomes suspect (Biswas and Gupta, 2019). Furthermore, blockchain users confront a distinct shallow market issue due to the relatively limited availability of blockchain-based instruments in the real market (Urquhart, 2016). As a result, if a person wants to trade or withdraw a substantial number of such instruments, he or she would most likely disrupt the general market. Because of the present market’s volatility, consumers may be tempted to hoard their assets. This behaviour obstructs the successful flow of the blockchain through peer-to-peer networks and delays a smooth trading process in the open market (Zohar, 2015). While running blocks via the network or processing transactions, blockchains might present unique issues (Beer and Weber, 2015). Furthermore, it is very hard to reverse a user’s decision to communicate information over blockchain to another user (Beer and Weber, 2015). When two or more miners simultaneously publish blockchains containing transactions with the same previous block, this situation is known as a fork16 in the blockchain (Sapirshtein et al., 2017). Other miners in the network eventually accept the longest chain and continue mining with it (Biswas and Gupta, 2019).
Blockchains, unlike conventional application software and operating systems, have significant technological obstacles. Installing large software changes across all mining machines, for example, is difficult. Protocol updates are often hampered by the existence of a software defect or inconsistencies in a single user’s blocks, which may cause the whole blockchain to split needlessly (Zohar, 2015). In such cases, all users on the network must revert their upgrades to maintain blockchain consistency. Intentional software protocol changes are also difficult to perform, and experienced network users must be careful of, if not outright block, such behaviour (Biswas and Gupta, 2019). Other identified barriers are presented in Table 1 with the accompanying authors.
3. Research methodology
This research took a post-positivist philosophical stance with a view to unearthing the barriers to the implementation of blockchain technology in the built environment through empirical evidence. This philosophical perspective informed the use of a quantitative research approach conducted using a questionnaire survey as indicated in Figure 1. According to Creswell (2014), the quantitative research method gathers numerical data, which can be placed in rank order, classified or evaluated using units of measurements. For this study, a close-ended questionnaire was designed to retrieve data from the target population using information from reviewed literature on barriers to implementing blockchain technology. The questionnaire was divided into two separate sections, and section A retrieved information about respondents’ background information, while section B focused on the barriers to the implementation of blockchain technology. The premise of using the questionnaire was that it covers a wide range of respondents within a short time and has been widely used in most construction-related studies (Oke et al., 2020). Participants answered the questionnaires using the five-point Likert scale given in the survey to rate their level of agreement or disagreement with the variables as identified in Table 1. To boost response rate and quality while lowering respondents’ “frustration level”, a five-point Likert-type scale was adopted (Joshi et al., 2015). Due to the statistical approach of the research study, a target population was drawn, which includes both government and private sector professionals in Gauteng province of South Africa. The selected professionals are quantity surveyors, architects, engineers, construction managers, construction project managers and information technologist. These professional groups were selected as they are directly involved in the construction process as well as the decision process in the built environment. However, information technologists were introduced because blockchain technology is an innovation that most professionals in the built environment are not familiar with yet, and there is a need to verify the authenticity of their opinion on the research objective. Thus, a pilot study was conducted using six professionals with one each from the identified professional groups for the study. The pilot study responses indicated that the designed survey instrument is standardised and sufficient for the study objective, which therefore validates the data collection instrument adopted for the study.
Due to the nature of the study, a snowballing sampling technique was adopted to ensure only constructions professionals who know blockchain technology are used for the study. Snowball sampling techniques is a system of data collection in which research respondents help in recruiting other respondents for the study, which has been used in studies with few identified respondents (Mould-Millman et al., 2017). To achieve this, three construction professionals were identified from a blockchain technology sensitisation workshop, and they further identified their colleagues who have met the requirements and qualified to be a respondent for the study. A total of 79 questionnaires were distributed online as directed by the ethics clearance approval obtained for the study due to the COVID-19 pandemic, and all of them were retrieved. All the retrieved questionnaires were vetted and ascertained to be suitable for analysis.
Given that blockchain technology is a new research area in the built environment, the 79 responses retrieved for the study were considered adequate for this research study with the study area being a developing country (Etz and Arroyo, 2015). Based on their responses, statistical conclusions were drawn with the use of tables and charts. The retrieved responses were analysed using Microsoft Excel and the Statistical Package for Social Science software. Percentiles and frequencies, mean item scores (MIS) and PCA were determined from the retrieved data. Percentiles and frequencies were adopted to analyse the respondents’ demographic information, while MIS ranked the variables according to the respondents’ responses. PCA is a statistical analysis tool useful for reducing large data into clusters by exploring the fundamental theoretical structure of the variables (Marzoughi et al., 2018). It helps point out the relationship structure between the respondents and each variable (Pallant, 2011; Yong and Pearce, 2013). The principal component decomposition (T) of a variable X is expressed mathematically as shown in equations (1) and (2):
where W is a p-by-p matrix of weights whose columns are the eigenvectors of XTX.
Further to the descriptive analysis carried out, there is a need to examine the differences in the opinion of the different groups of respondents to understand how they perceive the barriers to the implementation of blockchain technology in the built environment. To achieve this, the Kruskal–Wallis H test was used, which is suitable for determining the difference in respondents’ opinion that belongs to more than two groups (Yong and Pearce, 2013). The reliability of the research instrument was carried out using Cronbach’s alpha, and the result revealed an alpha value of 0.966, which confirms that the data retrieved using the questionnaire survey can be relied upon.
4. Research findings
4.1 Demographic information of respondents
From the analysis of the respondents’ background information as shown in Table 2, the majority of the respondents have bachelor’s degree as their highest educational qualification (36.7%), followed by honours’ degree (30.4%), while 15.2% possess technical certificate. From Table 2, quantity surveyors formed the largest respondent group with 31.6% of the total population, followed by construction managers with 25.3%, while engineers are 17.7%. Also, from Table 2, most of the respondents have about seven–nine years of experience (82.3%), followed by four–six years of experience (12.7%), while only 3.8% have one–three years of experience. From the foregoing, it is evident that the respondents possess a handful of years of experience in their area of expertise with some educational qualifications. The respondents recorded a high level of academic qualification on average, which might have influenced their knowledge of blockchain technology. It can also be deduced from the findings that quantity surveyors in the study area are equipped with knowledge of blockchain technology than other categories of respondents. This could be attributed to the sensitisation workshops on blockchain technology held by the professional body in the study area. This shows that they are capable of providing the needed information to achieve the objective of this study.
4.2 Barriers to blockchain technology implementation in built environment
Having subjected the retrieved data to descriptive analysis, the result as presented in Table 3 reveals the respondents’ ranking of the barriers to the implementation of blockchain technology in the built environment. In Table 3, the MIS of each barrier was indicated to show respondents’’ level of agreements to each barrier. At the same time, the Kruskal–Wallis test was adopted to check the differences in the opinions of the various groups of respondents. In the Kruskal–Wallis H test, asymp. Sig. values below 0.05 indicate that there is a significant difference in the opinion of the respondents. Notably, all the identified barriers have an MIS above the average of 3.00 of a five-point Likert scale used for this study. This indicates that respondents agree that these barriers affect the implementation of blockchain technology in the built environment. Also, only vulnerability of smart contracts and transactional-level uncertainties have asymp. sig. values lower than 0.05, indicating that the group of respondents ranked these barriers differently. This can be attributed to the nature of these barriers as they can be fully understood by information technologists and blockchain technology professionals only.
A further analysis using PCA was conducted on the identified barriers to help determine correlation patterns within them. According to Pallant (2011), to determine the factorability of the variables, the correlation matrix should show some correlations of r = 0.3 or greater, and this data set was found suitable as the coefficient values are above 0.3. Kaiser–Meyer–Olkin Measure of Sampling Adequacy indicates how the distribution of values is adequate for PCA, and it was found to be 0.925 for this study, which is greater than 0.6 (the acceptable threshold), while Bartlett’s test of sphericity has a value of 0.000, revealing that there is statistical significance in the variables. Figure 2 shows the steep slope of the components which broke below 1.0 after the third component to show only three components met the requirement using the Kaiser’s criterion eigenvalues. These three components explained a cumulative percentage of 73.436 of the variables.
For the PCA rotation, direct Oblimin rotation was used since there was a correlation among the 19 identified barriers. The results of the percentage of variance, communalities extraction and pattern matrix are presented in Table 4, showing the three-component classifications of the variables based on their interrelationships.
From the analysis presented in Table 4, there are three clusters generated from the identified barriers. These clusters are therefore named based on the characteristics common to them as shown in the following subsections.
5.1 Cluster one – organisational barriers
A total of six barriers loaded onto this cluster and they are “intellectual property concerns” (89.1%), “lack of skills or knowledge” (79.9%), “lack of clarity” (69.7%), “audit concerns” (62.9%), “poor/absence of collaboration” (57.7%) and “market-based risks” (57.1%). These factors relate to the barriers from organisations in the built environment, and they explain a cumulative variance of 62.438% of the total variance. The findings agree with the studies of Farooque et al. (2020) and Vidan and Lehdonvirta (2019), who found that having trained experts in blockchain technology for the built environment is a real challenge at the moment. This proves that there is a lack of skills and knowledge about blockchain technology in the built environment. According to Hawlitschek et al. (2018), many organisation executives have a limited grasp of blockchain technology and its improvements to the industry, while some executives limit blockchain technology to cryptocurrencies. To ensure the implementation of blockchain technology, it is necessary to have an exchange of knowledge between the information technology professionals and construction professionals. Also, the findings indicated that there is a lack of clarity, which according to Kajinami et al. (2018), the study of C-level corporate executives revealed that 23% of its respondents were worried about the lack of consistency in blockchain guidelines. The findings further revealed that market-based risk is a major barrier to blockchain technology implementation in the built environment. According to Sivarajah et al. (2017), the launch of transformative technology in every field brings several difficulties and uncertainties in the commercial market, especially in technological, regulatory, social and adoption-related fields. Also, Kshetri (2018) opined that organisations flourish in their commercial structure and only enter into contracts to purchase innovative products that comply with their business processes to produce value.
5.2 Cluster two – social barriers
A total of seven barriers loaded onto this cluster and they are “social acceptance” (88.8%), “high energy consumption” (85.5%), “legal and regulatory uncertainties” (78.1%), “system complexity and cost” (78.0%), “transactional-level uncertainties” (77.7%), “vague supportive data regulation” (72.6%) and “poor economic behaviour” (63.9%). These factors relate to the societal barriers at large, and they explain a cumulative variance of 5.756% of the total variance. Social acceptance is an identified barrier from the study, which aligns with the conclusion of Stefanini (2020), who opined that people should begin exploring blockchain technology regardless of when they plan to adopt it. This was based on Gartner’s proposed growth framework for blockchain technology, which shows that for social acceptance to be achieved, there must be “a strong view of the market prospects challenges of blockchain technology; the possible effects of blockchain technology on the industry; a strong view of the strengths and weaknesses of blockchain technology; a reassessment of individual company and industry confidence in blockchain technology architecture; and a commitment to adopt blockchain technology” (Stefanini, 2020). The findings also revealed that high energy consumption is one of the major barriers encountered in the implementation of blockchain technology, which synchronises with the findings of Farooque et al. (2020) and Petri et al. (2020). These authors submitted that the high computational power required for significant blockchain technology consensus frameworks consume a large amount of energy. High energy utilisation implies higher carbon emissions, which have been a key challenge globally, because it leads to temperature increase, ozone depletion, environmental change, thereby affecting human well-being and the biological system. In the same vein, the high computing power required by blockchain technology leads to substantial costs (Cohen and Zohar, 2018). Also, the findings indicated that there is vague supportive data regulation. Bhuvana and Aithal (2020) posited that the General Data Protection Regulation does not adapt well to the unchanging data records on a blockchain network. Another finding from the study showed that transactional-level uncertainties are a barrier to implementing blockchain technology in the built environment. A popular issue associated with blockchain technology transactions is known as fork, whereby two or more miners publish a block containing the same previous transactions concurrently (Sapirshtein et al., 2017). In such a situation, subsequent miners will follow the longest chain, and a transaction record can be missed in the abandoned block. Nofer et al. (2017) pointed out that a miner can be blacklisted together with a mined block, leading to all transactions held in the block being forfeited by the owners. Also, legal and regulatory uncertainties affect blockchain technology’s implementation as most countries do not have a regulation in place for its usage. In a submission by Abramova and Böhme (2016), the government cannot charge value-added services and income tax on blockchain technology transactions, while a monetary policy cannot be imposed.
5.3 Cluster three – technological barriers
A total of six barriers also loaded onto this cluster, and they are “scalability risks” (99.2%), “vulnerability of smart contracts” (85.4%), “interoperability issues” (78.6%), “security issues” (67.2%), “authorisation issues” (64.8%) and “lack of standardisation” (61.1%). These barriers relate to the technological issues of blockchain technology, and they explain a cumulative variance of 5.242% of the total variance. Also, the finding about scalability risks is in line with the submission of Nakamoto (2019) that some recently developed blockchain systems are helpless against attacks (such as the 51% attack) because they lack participating hubs and they have little processing pool. Thus, some undesirable data needs to be recorded on the blockchain network, which is difficult to eliminate or reverse because of the immutability characteristics of blockchain technology (Ateniese et al., 2017). These are part of the vulnerability of smart contracts, which consumers are afraid of. Sompolinsky and Zohar (2015) added that the issue of blockchain technology governance is still a global debate as the decentralisation of the platform does not give power to a particular entity in the network. This makes authorisation of transactions within the blockchain network the responsibility of miners who can operate from anywhere, and proper identity might not be known.
Based on the findings of this study, a model was generated to depict the cluster of barriers to the implementation of blockchain technology in the built environment, as shown in Figure 3.
6. Conclusion and recommendation
Blockchain technology is an innovative technology that is expected to transform businesses across different industries. There are quite several identified barriers to its implementation in the other sectors that were evaluated in this study regarding the built environment. Through the use of a questionnaire survey, respondents ranked the barriers according to their severity. From the analysed data, the major barriers include lack of clarity, scalability risks, lack of skills or knowledge, social acceptance and lack of standardisation. Other identified barriers also have an MIS value above the average 3.00, which indicates that they are all bottlenecks to the implementation of blockchain technology in the built environment. A further analysis was carried out to factorise the barriers into clusters, and three clusters were generated, namely: organisational barriers, social barriers, and technological barriers. These three clusters explain how the respondents view these barriers in the implementation of blockchain technology in the built environment.
In the built environment, organisations operate differently, and their business processes differ, which makes collaboration tasking. This could be linked to the challenge of implementing blockchain technology. Also, there are various considerations at the organisational level before an innovation can be adopted, which most organisations cannot achieve in developing countries like South Africa. The cost of acquiring the needed technological infrastructure for the implementation of blockchain technology is high. This poses a significant challenge to its adoption in the built environment. Therefore, it is very important that the numerous stakeholders in the built environment be made aware of the blockchain technology capabilities while formulating a solution to the identified barriers. This will aid its implementation in the built environment and help the industry measure up with its counterparts. As a recommendation, it is proposed that built environment organisations be kept abreast of blockchain technology’s capabilities as the major barrier observed was the lack of clarity of blockchain technology. Also, the technological barriers identified from this study need to be addressed by information technology experts to give consumers the desired value for money in the implementation of blockchain technology for the built environment. Organisations in the built environment need to improve their business culture to allow for the adoption of innovations, which will help promote the organisation’s profit margin. With the implementation of awareness programmes by professional bodies in the built environment, social acceptance of innovative technologies such as blockchain can be achieved. This will help the industry in adopting blockchain technology for its business processes. The study was carried out in South Africa using only Gauteng province due to time and cost constraints. Also, the accessibility of professionals from other provinces of South Africa limited the reach of this study. Therefore, the findings of this study cannot be generalised for the South African built environment. Also, the study could not investigate the interrelationships of the barrier categories identified from the analysis, which is a further limitation of this study. In this regard, further studies can be conducted using other provinces of South Africa to have a general knowledge of how blockchain technology is perceived by built environment professionals and the barriers encountered in its adoption. Also, further study can be carried out to assess the benefits of blockchain technology implementation in the built environment.
Barrier to the implementation of blockchain technology in the built environment
Background information of respondents
|What is your highest educational qualification?|
|What is your profession?|
|Construction Project Manager||5||6.3|
|How many years of experience do you have?|
|10 years and more||1||1.3|
Barriers to the implementation of blockchain technology in the built environment
|S/No.||Barriers||Mean||Kruskal–Wallis H||Asymp. Sig.||Rank|
|1||Lack of clarity||3.53||5.137||0.399||1|
|3||Lack of skills or knowledge||3.47||10.737||0.057||3|
|5||Lack of standardisation||3.41||9.306||0.097||5|
|6||Poor economic behaviour||3.34||5.958||0.310||6|
|8||High energy consumption||3.32||6.694||0.244||8|
|10||Vulnerability of smart contracts||3.29||14.288||0.014||10|
|11||Legal and regulatory uncertainties||3.29||6.070||0.299||10|
|16||System complexity and cost||3.11||4.982||0.418||16|
|17||Vague supportive data regulation||3.09||5.224||0.389||17|
|19||Intellectual property concerns||3.06||9.251||0.099||19|
PCA extraction for barriers to BT implementation in the built environment
|Barriers||Communalities extraction||% of variance||Component|
|Intellectual property concerns||0.541||62.438||0.891|
|Lack of skills or knowledge||0.609||0.799|
|Lack of clarity||0.680||0.697|
|High energy consumption||0.757||0.855|
|Legal and regulatory uncertainties||0.685||0.781|
|System complexity and cost||0.613||0.780|
|Vague supportive data regulation||0.605||0.726|
|Poor economic behaviour||0.750||0.639|
|Vulnerability of smart contracts||0.750||0.854|
|Lack of standardisation||0.700||0.611|
|Kaiser–Meyer–Olkin Measure of Sampling Adequacy = 0.925|
|Bartlett’s test of sphericity sig = 0.000|
|Extraction method: principal component analysis
Rotation method: Oblimin with Kaiser Normalization
|a. Rotation converged in 13 iterations|
BT = Blockchain technology
Abramova, S. and Böhme, R. (2016), “Perceived benefit and risk as multidimensional determinants of bitcoin use: a quantitative exploratory study”, in Thirty-Seventh International Conference on Information Systems, ICIS 2016, Dublin, pp. 1-20, doi:10.17705/4icis.00001.
Accenture (2017), “Blockchain banking for investment banks”, available at: www.accenture.com/lv-en/insight-banking-on-blockchain (accessed 1 January 2020).
Akinradewo, O., Aigbavboa, C., Oke, A. and Mthimunye, I. (2021), “Applications of blockchain technology in the construction industry”, Lecture Notes in Networks and Systems, Vol. 276, pp. 275-282, doi: 10.1007/978-3-030-80094-9_33.
Alcazar, C.V. (2017), “Data you can trust”, Air and Space Power Journal, Vol. 31 No. 2, pp. 91-101.
Ametrano, F.M., Barucci, E., Marazzina, D. and Zanero, S. (2016), “Response to ESMA/2016/773:’the distributed ledger technology applied to securities markets”, available at SSRN 3265776.
Apte, S. and Petrovsky, N. (2016), “Will blockchain technology revolutionize excipient supply chain management?”, Journal of Excipients and Food Chemicals, Vol. 7 No. 3, p. 910.
Aste, T., Tasca, P. and Di Matteo, T. (2017), “Blockchain technologies: the foreseeable impact on society and industry”, Computer, Vol. 50 No. 9, pp. 18-28.
Ateniese, G., Magri, B., Venturi, D. and Andrade, E. (2017), “Redactable blockchain–or–rewriting history in bitcoin and friends”, 2017 IEEE European Symposium on Security and Privacy (EuroS&P), April, IEEE, pp. 111-126.
Barima, O. (2017), “Leveraging the blockchain technology to improve construction value delivery: the opportunities, benefits and challenges”, Construction Projects, Nova Publishers, New York, NY, pp. 93-112.
Beer, C. and Weber, B. (2015), “Bitcoin – the promise and limits of private innovation in monetary and payment systems”, Monetary Policy and the Economy, No. Q4, pp. 53-66.
Bhuvana, R. and Aithal, P.S. (2020), “Blockchain based service: a case study on IBM blockchain services & Hyperledger fabric”, International Journal of Case Studies in Business, IT, and Education (IJCSBE), Vol. 4 No. 1, pp. 94-102.
Biswas, B. and Gupta, R. (2019), “Analysis of barriers to implement blockchain in industry and service sectors”, Computers and Industrial Engineering, Vol. 136, pp. 225-241, doi: 10.1016/j.cie.2019.07.005.
Böhme, R., Christin, N., Edelman, B. and Moore, T. (2015), “Bitcoin: economics, technology, and governance”, Journal of Economic Perspectives, Vol. 29 No. 2, pp. 213-238, doi: 10.1257/jep.29.2.213.
Boudguiga, A., Bouzerna, N., Granboulan, L., Olivereau, A., Quesnel, F., Roger, A. and Sirdey, R. (2017), “Towards better availability and accountability for iot updates by means of a blockchain”, 2017 IEEE European Symposium on Security and Privacy Workshops, (EuroS&PW), IEEE, April, pp. 50-58.
Busby, M. (2018), “Blockchain is this year’s buzzword – but can it outlive the hype?”, The Guardian.
Casey, M.J. and Wong, P. (2017), “Global supply chains are about to get better, thanks to blockchain”, Harvard Business Review, Vol. 13, pp. 1-6.
Cohen, S. and Zohar, A. (2018), “Database perspectives on blockchains”, arXiv preprint arXiv:1803.06015.
Creswell, J.W. (2014), Research Design_Qualitative, Quantitative, and Mixed Method Approaches, 4th ed., SAGE Publications, doi: 10.2307/3152153.
Cuccuru, P. (2017), “Beyond bitcoin: an early overview on smart contracts”, International Journal of Law and Information Technology, Vol. 25 No. 3, pp. 179-195.
De Kruijff, J. and Weigand, H. (2017), “Understanding the blockchain using enterprise ontology”, International Conference on Advanced Information Systems Engineering, Springer, Cham, pp. 29-43.
De Smith, M.J. (2018), Statistical Analysis Handbook A Comprehensive Handbook of Statistical Concepts, Techniques and Software Tools/Dr Michael J de Smith, The Winchelsea Press.
Dobrovnik, M., Herold, D.M., Fürst, E. and Kummer, S. (2018), “Blockchain for and in Logistics: what to adopt and where to start”, Logistics, Vol. 2 No. 3, p. 18.
Etz, K.E. and Arroyo, J.A. (2015), “Small sample research: considerations beyond statistical power”, Prevention Science, Springer, pp. 1033-1036, doi: 10.1007/s11121-015-0585-4.
Farooque, M., Jain, V., Zhang, A. and Li, Z. (2020), “Fuzzy DEMATEL analysis of barriers to blockchain-based life cycle assessment in China”, Computers & Industrial Engineering, Vol. 147, pp. 66-84.
Fernández-Caramés, T.M. and Fraga-Lamas, P. (2018), “A review on the use of blockchain for the internet of things”, Ieee Access, Vol. 6, pp. 32979-33001.
Frank, A.G., Dalenogare, L.S. and Ayala, N.F. (2019), “Industry 4.0 technologies: implementation patterns in manufacturing companies”, International Journal of Production Economics, Vol. 210, pp. 15-26, doi: 10.1016/j.ijpe.2019.01.004.
Gervais, A. et al. (2016), “On the security and performance of proof of work blockchains”, Proceedings of the ACM Conference on Computer and Communications Security, pp. 3-16, doi: 10.1145/2976749.2978341.
Hasan, H., AlHadhrami, E., AlDhaheri, A., Salah, K. and Jayaraman, R. (2019), “Smart contract-based approach for efficient shipment management”, Computers and Industrial Engineering, Vol. 136, pp. 149-159, doi: 10.1016/j.cie.2019.07.022.
Hawlitschek, F., Notheisen, B. and Teubner, T. (2018), “The limits of trust-free systems: a literature review on blockchain technology and trust in the sharing economy”, Electronic Commerce Research and Applications, Vol. 29, pp. 50-63.
Heap, I. (2017), “Blockchain could help musicians make money again”, Harvard Business Review, Vol. 5, pp. 1-12.
Heilig, L., Lalla-Ruiz, E. and Voß, S. (2017), “Digital transformation in maritime ports: analysis and a game theoretic framework”, Netnomics: Economic Research and Electronic Networking, Vol. 18 Nos 2/3, pp. 227-254.
Heister, S. and Yuthas, K. (2020), “The blockchain and how it can influence conceptions of the self”, Technology in Society, Vol. 60, pp. 10-18.
Hinckeldeyn, J. (2019), Blockchain-Technologie in der Supply Chain: Einführung und Anwendungsbeispiele, Springer-Verlag.
Huang, K., Zhang, X., Mu, Y., Rezaeibagha, F. and Du, X. (2020), “Scalable and redactable blockchain with update and anonymity”, Information Sciences, Vol. 546, pp. 25-41.
Hughes, D. and Hughes, D. (2017), The Impact of Blockchain Technology on the Construction Industry, Animal Media.
Hughes, A., Park, A., Kietzmann, J. and Archer-Brown, C. (2019), “Beyond bitcoin: what blockchain and distributed ledger technologies mean for firms”, Business Horizons, Vol. 62 No. 3, pp. 273-281, doi: 10.1016/j.bushor.2019.01.002.
Hung, S.Y., Tang, K.Z., Chang, C.M. and Ke, C.D. (2009), “User acceptance of intergovernmental services: an example of electronic document management system”, Government Information Quarterly, Vol. 26 No. 2, pp. 387-397, doi: 10.1016/j.giq.2008.07.003.
Institution of Civil Engineers (2018), “Shaping a Digital World POST EVENT REPORT: harnessing digitally enabled innovation”, available at: www.ice.org.uk/ICEDevelopmentWebPortal/media/Events/Lectures/Shaping-a-Digital-World-Report-1.pdf (accessed 15 June 2021).
Ismail, L. and Materwala, H. (2019), “A review of blockchain architecture and consensus protocols: use cases, challenges, and solutions”, Symmetry, Vol. 11 No. 10, doi: 10.3390/sym11101198.
Joshi, A., Kale, S., Chandel, S. and Pal, D. (2015), “Likert scale: explored and explained”, British Journal of Applied Science and Technology, Vol. 7 No. 4, pp. 396-403, doi: 10.9734/bjast/2015/14975.
Kajinami, K., Ozaki, A., Tajima, Y., Yamashita, S., Arai, H. and Teramoto, T. (2018), “Real-world data to identify hypercholesterolemia patients on suboptimal statin therapy”, Journal of Atherosclerosis and Thrombosis, Vol. 5, pp. 46-52.
Karafiloski, E. and Mishev, A. (2017), “Blockchain solutions for big data challenges: a literature review”, IEEE International Conference on Smart Technologies, EUROCON 2017 – Conference Proceedings. V. 2017, pp. 763-768. doi: 10.1109/EUROCON.2017.8011213.
Katsoulacos, Y. and Ulph, D. (2017), “Regulatory decision errors, legal uncertainty and welfare: a general treatment”, International Journal of Industrial Organization, Vol. 53, pp. 326-352.
Khaqqi, K.N., Sikorski, J.J., Hadinoto, K. and Kraft, M. (2018), “Incorporating seller/buyer reputation-based system in blockchain-enabled emission trading application”, Applied Energy, Vol. 209, pp. 8-19, doi: 10.1016/j.apenergy.2017.10.070.
Koteska, B., Karafiloski, E. and Mishev, A. (2017), “Blockchain implementation quality challenges: a literature”, SQAMIA 2017: 6th Workshop of Software Quality, Analysis, Monitoring, Improvement, and Applications, pp. 11-13.
Koutsogiannis, A. and Berntsen, N. (2017), Blockchain and Construction: The How, Why and When, available at: constructionmanagermagazine.com/technology
Kshetri, N. (2018), “Blockchain’s roles in meeting key supply chain management objectives”, International Journal of Information Management, Vol. 39, pp. 80-89.
Leibson, S. (2018), “Blockchain is not bitcoin – bitcoin is not blockchain – EEJournal”, available at: www.eejournal.com/article/blockchain-is-not-bitcoin-bitcoin-is-not-blockchain/ (accessed 1 January 2020).
Li, S. (2018), “Application of blockchain technology in smart city infrastructure”, 2018 IEEE International Conference on Smart Internet of Things (SmartIoT), IEEE, August, pp. 266-276.
Li, J., Greenwood, D. and Kassem, M. (2019), “Blockchain in the built environment and construction industry: a systematic review, conceptual models and practical use cases”, Automation in Construction, Vol. 102, pp. 288-307, doi: 10.1016/j.autcon.2019.02.005.
Marzoughi, F., Arthanari, T. and Askarany, D. (2018), “A decision support framework for estimating project duration under the impact of weather”, Automation in Construction, Vol. 87, pp. 287-296, doi: 10.1016/j.autcon.2017.11.001.
Mendling, J., Weber, I., Aalst, W.V.D., Brocke, J.V., Cabanillas, C., Daniel, F., Debois, S., Ciccio, C.D., Dumas, M., Dustdar, S. and Gal, A. (2018), “Blockchains for business process management-challenges and opportunities”, ACM Transactions on Management Information Systems (TMIS), Vol. 9 No. 1, pp. 1-16.
Menges, F., Böhm, F., Vielberth, M., Puchta, A., Taubmann, B., Rakotondravony, N. and Latzo, T. (2018), “Introducing DINGfest: an architecture for next generation SIEM systems”, Lecture Notes in Informatics (LNI), Vol. 15, pp. 257-260.
Merschbrock, C. (2012), “Unorchestrated symphony: the case of inter-organizational collaboration in digital construction design”, Electronic Journal of Information Technology in Construction, Vol. 17, pp. 333-350.
Mould-Millman, N.K., Dixon, J.M., Sefa, N., Yancey, A., Hollong, B.G., Hagahmed, M., Ginde, A.A. and Wallis, L.A. (2017), “The state of emergency medical services (EMS) systems in Africa”, Prehospital and Disaster Medicine, Vol. 32 No. 3, pp. 273-283, doi: 10.1017/S1049023X17000061.
Nakamoto, S. (2008), “Bitcoin P2P e-cash paper”, available at: http://users.encs.concordia.ca/∼clark/biblio/bitcoin/Nakamoto2008.pdf (accessed 1 June 2021).
Nakamoto, S. (2019), Bitcoin: A Peer-to-Peer Electronic Cash System, Manubot.
Nanayakkara, S., Perera, S., Senaratne, S., Weerasuriya, G.T. and Bandara, H.M.N.D. (2021), “Blockchain and smart contracts: a solution for payment issues in construction supply chains”, Informatics, Vol. 8 No. 2, doi: 10.3390/INFORMATICS8020036.
Nofer, M. et al. (2017), “Blockchain”, Business and Information Systems Engineering, Vol. 59 No. 3, pp. 183-187, doi: 10.1007/s12599-017-0467-3.
O’Boyle, R. (2017), “Block capital: how blockchain could change planning”, available at: www.theplanner.co.uk/features/block-capital-how-blockchain-could-change-planning (accessed 1 January 2020).
Ogunde, A., Olaolu, O., Afolabi, A., Owolabi, J. and Ojelabi, R. (2017), “Challenges confronting construction project management system for sustainable construction in developing countries: professionals perspectives (a case study of Nigeria)”, Journal of Building Performance, Vol. 8 No. 1, pp. 1-11.
Oke, A., Aghimien, D., Akinradewo, O. and Aigbavboa, C. (2020), “Improving resilience of cities through smart city drivers”, Construction Economics and Building, Vol. 20 No. 2, pp. 45-64, doi: 10.5130/ajceb.v20i2.6647.
Osterwalder, A. and Pigneur, Y. (2010), Business Model Generation: A Handbook for Visionaries, Game Changers and Challengers, John Wiley and Sons, New Jersey.
Pallant, J. (2011), SPSS Survival Manual 4th edition: A Step by Step Guide to Data Analysis Using SPSS version 18, Open University Press, Maidenhead, Berkshire.
Parizi, R.M. and Dehghantanha, A. (2018), “Smart contract programming languages on blockchains: an empirical evaluation of usability and security”, International Conference on Blockchain, Springer, Cham, June, pp. 75-91.
Perera, S., Nanayakkara, S., Rodrigo, M.N.N., Senaratne, S. and Weinand, R. (2020), “Blockchain technology: is it hype or real in the construction industry?”, Journal of Industrial Information Integration, Vol. 17, doi: 10.1016/J.JII.2020.100125.
Petri, I., Barati, M., Rezgui, Y. and Rana, O.F. (2020), “Blockchain for energy sharing and trading in distributed prosumer communities”, Computers in Industry, Vol. 123, pp. 10-22.
Popper, N. (2018), What is the Blockchain? Explaining the Tech behind Cryptocurrencies, The New York, NY Times, New York, NY.
Pournader, M., Shi, Y., Seuring, S. and Koh, S.C.L. (2020), “Blockchain applications in supply chains, transport and logistics: a systematic review of the literature”, International Journal of Production Research, Vol. 58 No. 7, pp. 2063-2081, doi: 10.1080/00207543.2019.1650976.
Pouryazdan, M., Fiandrino, C., Kantarci, B., Kliazovich, D., Soyata, T. and Bouvry, P. (2016), “Game-theoretic recruitment of sensing service providers for trustworthy cloud-centric internet-of-things (IoT) applications”, 2016 IEEE Globecom Workshops (GC Wkshps), IEEE, December, pp. 1-6.
Putz, B., Menges, F. and Pernul, G. (2019), “A secure and auditable logging infrastructure based on a permissioned blockchain”, Computers & Security, Vol. 87, pp. 10-16.
Ramage, M. (2018), From BIM to Blockchain In Construction: What You Need to Know, Trimble.
Rasoloharijaona, S., Rakotosamimanana, B., Randrianambinina, B. and Zimmermann, E. (2003), “Pair-Specific usage of sleeping sites and their implications for social organization in a nocturnal Malagasy primate, the Milne Edwards’ sportive lemur (Lepilemur Edwardsi)”, American Journal of Physical Anthropology, Vol. 122 No. 3, pp. 251-258, doi: 10.1002/ajpa.10281.
Risius, M. and Spohrer, K. (2017), “A blockchain research framework”, Business & Information Systems Engineering, Vol. 59 No. 6, pp. 385-409.
Rohleder, B. (2017), “Digitalisierung der logistik”, Vortrag Vom, Vol. 28, pp. 1-6.
Sadeghi, M., Mahmoudi, A. and Deng, X. (2021), “Adopting distributed ledger technology for the sustainable construction industry: evaluating the barriers using ordinal priority approach”, Environmental Science and Pollution Research, pp. 1-26, doi: 10.1007/s11356-021-16376-y.
San, K.M., Choy, C.F. and Fung, W.P. (2019), “The potentials and impacts of blockchain technology in built environment: a literature review”, IOP Conference Series: Materials Science and Engineering, April, IOP Publishing, Vol. 495, No. 1, pp. 1-20.
Sapirshtein, A., Sompolinsky, Y. and Zohar, A. (2017), “Optimal selfish mining strategies in bitcoin”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). V. 9603 LNCS, pp. 515-532, doi:10.1007/978-3-662-54970-4_30.
Schrammel, F. and Wilhelm, E. (2016), Rechtliche Aspekte im Building Information Modeling (BIM): Schnelleinstieg für Architekten und Bauingenieure, Springer-Verlag.
Seebacher, S. and Schüritz, R. (2020), “Blockchain – just another it implementation? A comparison of blockchain and interorganizational information systems”, 27th European Conference on Information Systems - Information Systems for a Sharing Society, ECIS 2019.
Sinenko, S., Hanitsch, P., Aliev, S. and Volovik, M. (2020), “The implementation of BIM in construction projects”, E3S Web of Conferences, Vol. 164, doi: 10.1051/e3sconf/202016408002.
Singh, M. and Kim, S. (2019), “Blockchain technology for decentralized autonomous organizations”, Advances in Computers, Elsevier, Vol. 115, pp. 115-140.
Singh, A., Click, K., Parizi, R.M., Zhang, Q., Dehghantanha, A. and Choo, K.K.R. (2020), “Sidechain technologies in blockchain networks: an examination and state-of-the-art review”, Journal of Network and Computer Applications, Vol. 149, p. 102471, doi: 10.1016/j.jnca.2019.102471.
Sivarajah, U., Kamal, M.M., Irani, Z. and Weerakkody, V. (2017), “Critical analysis of big data challenges and analytical methods”, Journal of Business Research, Vol. 70, pp. 263-286.
Smith, S. and O’rourke, L. (2019), “Exploring the potential of blockchain technology for the UK construction industry - 2019”, Sustainability, Vol. 1, pp. 1-53.
Sompolinsky, Y. and Zohar, A. (2015), “Secure high-rate transaction processing in bitcoin”, International Conference on Financial Cryptography and Data Security, January, Springer, Berlin, Heidelberg, pp. 507-527.
Stefanini (2020), “Gartner’s top 10 strategic tech trends for 2020: practical blockchain”, Stefanini group, available at: https://stefanini.com/en/trends/news/gartner-predictions-for-the-top-10-strategic-tech-trends-in-2020
Swan, M. (2015), Blockchain: Blueprint for a New Economy, O'Reilly Media.
Tao, F. and Qi, Q. (2017), “New IT driven service-oriented smart manufacturing: framework and characteristics”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 49 No. 1, pp. 81-91.
Tapscott, D. and Tapscott, A. (2017), “How blockchain will change organizations”, MIT Sloan Management Review, Vol. 58 No. 2, pp. 10-13.doi, doi: 10.7551/mitpress/11645.003.0010.
Turk, Ž. and Klinc, R. (2017), “Potentials of blockchain technology for construction management”, Procedia Engineering, Vol. 196, pp. 638-645, doi: 10.1016/j.proeng.2017.08.052.
Underwood, S. (2016), “Blockchain beyond bitcoin”, Communications of the ACM, Vol. 59 No. 11, pp. 15-17.doi, doi: 10.1145/2994581.
Urquhart, A. (2016), “The inefficiency of bitcoin”, Economics Letters, Vol. 148, pp. 80-82, doi: 10.1016/j.econlet.2016.09.019.
Vidan, G. and Lehdonvirta, V. (2019), “Mine the gap: bitcoin and the maintenance of trustlessness”, New Media & Society, Vol. 21 No. 1, pp. 42-59.
Woo, J., Asutosh, A.T., Li, J., Ryor, W.D., Kibert, C.J. and Shojaei, A. (2020), “Blockchain: a theoretical framework for better application of carbon credit acquisition to the building sector”, Construction Research Congress 2020: Infrastructure Systems and Sustainability – Selected Papers from the Construction Research Congress 2020, pp. 885-894, doi: 10.1061/9780784482858.095.
Woo, J., Fatima, R., Kibert, C.J., Newman, R.E., Tian, Y. and Srinivasan, R.S. (2021), “Applying blockchain technology for building energy performance measurement, reporting, and verification (MRV) and the carbon credit market: a review of the literature”, Building and Environment, Vol. 205, doi: 10.1016/J.BUILDENV.2021.108199.
Yong, A. and Pearce, S. (2013), “A beginner’s guide to factor analysis: focusing on exploratory factor analysis”, Tutorials in Quantitative Methods for Psychology, Vol. 9 No. 2, pp. 79-94.
Zheng, Z., Xie, S., Dai, H., Chen, X. and Wang, H. (2017), “An overview of blockchain technology: architecture, consensus, and future trends”, Proceedings – 2017 IEEE 6th International Congress on Big Data, BigData Congress 2017, June, pp. 557-564, doi: 10.1109/BigDataCongress.2017.85.
Zohar, A. (2015), “Bitcoin: under the hood”, Communications of the ACM, Vol. 58 No. 9, pp. 104-113, doi: 10.1145/2701411.
Zykov, S.V. (2018), “The agile way”, Smart Innovation, Systems and Technologies, Vol. 92, Springer Science and Business Media Deutschland GmbH, pp. 1-33, doi: 10.1007/978-3-319-77917-1_1.
Mason, J. (2017), “Intelligent contracts and the construction industry”, Journal of Legal Affairs and Dispute Resolution in Engineering and Construction, Vol. 9 No. 3, p. 04517012, doi: 10.1061/(asce)la.1943-4170.0000233.
Oesterreich, T.D. and Teuteberg, F. (2016), “Understanding the implications of digitisation and automation in the context of industry 4.0: a triangulation approach and elements of a research agenda for the construction industry”, Computers in Industry, Vol. 83, pp. 121-139, doi: 10.1016/j.compind.2016.09.006.
The authors would like to acknowledge the financial support provided by Global Excellence Stature 4.0 PhD Bursary, School of Postgraduate Studies, University of Johannesburg to fund this research.