Distributed Ledger Technology (DLT), or blockchain (BCT), is a decentralized database and shared computing infrastructure. The primary mission of DLT/BCT is generating, verifying, updating, sharing, transferring, and storing transactions within distributed ledgers without any trusted intermediaries (Nakamoto, 2008). Ozdemir et al. (2020) summarized key features of blockchains in speed, traceability, trust, security, disintermediation, immutability, transparency, and automation. According to Mougayar and Buterin (2016), DLT’s features are crucial for basic functions like smart assets, timestamping, multi-signature transactions, smart contracts, and smart oracles. To date, this technology has experienced four consecutive versions: Blockchain 1.0 (cryptocurrency), Blockchain 2.0 (smart contracts), Blockchain 3.0 (distributed applications), and Blockchain 4.0 (interoperability among industry 4.0-based applications (Bodkhe et al., 2020). This evolutionary trend shows that DLT can play a critical role in the ‘internet of value.’ Within distributed ledgers, any real-world value _ including i) intangible (i.e., trust, ownership, and identity), ii) tangible (i.e., real estate, equipment, and currency), and iii) obligations (i.e., contracts and agreements) _ can be digitalized and exchanged (Nawari and Ravindran 2019).
Blockchain is a well-recognized type of DLT. Other alternatives, with the similar underlying technology, are hash graph, directed acyclic graph (DAG), Tangle, Holo-chain, and Radix (O’Dair, 2018). Hence, throughout the current study, the terms ‘DLT’ are referred to as any form of distributed ledgers, including blockchain technology. In the context of the DLT implementation, Hilton et al. (2019) proposed a roadmap with defined deliverables, such as i) assessing viability and feasibility of use-cases, ii) developing a minimum viable product (MVP), and building ‘proof of concept,’ and iii) continuous scaling and running pilot blockchain solution in a real environment. Janssen et al. (2020) discussed a conceptual model for blockchain adoption based on process, institutional, market, and technological dimensions (PIMT). In the same line of thinking, Yang et al. (2020) presented an application framework for the construction industry. The authors asserted that four aspects of the regulation, industry trust, business, and technique, should be considered for a successful DLT adoption.
The previous studies show that there are various areas for DLT application, such as i) smart cities and built environment (Marsal-Llacuna, 2018), ii) logistics, procurement, and supply chain management (Fosso Wamba et al., 2020; Kouhizadeh et al., 2021), iii) smart homes, as microgrids in energy trading (Petri et al., 2020), iv) project value delivery, payments, finance management, and investment consistency (Penzes, 2018; Hunhevicz and Hall, 2020), v) dispute resolution, tendering, and construction bid competition (Barima 2017; Leng et al. 2020), vi) real-estate and land registry (Bürer et al., 2019), vii) project bank accounts (PBAs) (Li et al., 2019) and decentralized autonomous organization (DAO) (Nawari and Ravindran 2019).
DLT promises to enhance time efficiency, quality, productivity, cost savings, and transparency within processes and activities (Mougayar and Buterin 2016). Considering DLT’s features and potentials, this technology can be employed for sustainable development goals (SDGs). Early application in the finance and banking industry shows that DLT/BCT has been a driving force of a new economic structure. With that in mind, DLT becomes highlighted for social and environmental sustainability, as well. However, this technology is relatively nascent, and it takes a while for companies to find out how to utilize DLT potentials for the sake of sustainability. The research works by De Giovanni (2020), and Kouhizadeh et al. (2021) emphasized the role of blockchain and smart contracts in the sustainability of supply chain management (SCM). Wamba & Queiroz (2020) stressed the convergence of blockchain and industry 4.0 technologies (i.e., big data, artificial intelligence (AI), internet of things (IoT), robotics, and so forth). This combined effort can result in a sharing economy, transparent operations, and sustainable supply chain management (OSCM). Nandi et al. (2020) discussed how blockchain technology and the circular economy principle contribute to the localization, agility, and digitization (LAD) and sustainability of supply chain management.
Related studies show that DLT, directly or indirectly, contributes to sustainability. In this regard, we identified 30 sustainability attributes in the following clustering: two project sustainability, twelve social attributes, eight environmental attributes, eight economic attributes. Detailed information and definitions are provided in Appendix A, Table A2. These criteria will be analyzed later in a case study (Sect. 5) using the OPA.
2.2. Barriers facing DLT implementation in the AEC ecosystem
As mentioned in the introduction, some studies were discussing barriers facing DLT implementation in various sectors. According to Yang et al. (2020), one of the high-potential areas for future research directions is the challenges of adopting blockchain technology in the construction industry. We still need further surveys to assess general and (non)construction-specific challenges and their applicability in the AEC industry. In this regard, we identified challenges from previous studies. Based on their roots and time of occurrence, we categorized them in project, organization, market, and industry levels.
Project level: Although employing blockchain systems for project management activities is still too early (Yang et al., 2020), it seems that some challenges emerge from operations, project activities, and processes. In this regard, 11 barriers have been identified, mostly in project integration, procurement, communication, time, and cost.
P1. Abuse and fraud: Installing faulty systems and software bugs can increase intentional abuse, fraudulent activities, and human error at the application level (i.e., payment and procurement practices) (Helliar et al., 2020).
P2. Manual processes and traditional practices: Digitalizing will challenge manual processes (e.g., purchase order, accounting, invoicing, and payments) and traditional practices controlled by centralized systems (Hofmann et al., 2018).
P3. Irreversibility and immutability of the process: By employing smart contracts and automated processes, the chance for human intervention in changing coded documents and transactions will be reduced significantly (Biswas and Gupta, 2019; McNamara and Sepasgozar, 2021).
P4. Authenticity, consistency, and legitimacy of data: The excellent performance of distributed ledger is closely related to the availability and reliability of uploaded data to prevent any fraudulent activities (Li et al., 2019).
P5. Infrastructure for data management: In projects, there is a high need for robust devices and collaborators with minimum malfunctions, manipulation, and cyber-attacks. This paves the way for collecting, clustering, synchronizing, and storing data with maximum integrity and consistency (Penzes, 2018).
P6. Contractual standards: When technology embeds into project management practices/processes, a standard contractual model with detailed milestones, deliverables are required to develop a smart contract (Penzes, 2018).
P7. Multiple chains and private systems: When multiple blockchains versions and systems (i.e., enterprise resource planning (ERP)) engaged in a blockchain-based solution, poor integrity hampers cross-transactions and causes attacks, human errors, data loss, and fragmentation (Hofmann et al., 2018; Helliar et al., 2020).
P8. Fragmentation and complexity of activities: DLT implementation for the complicated and fragmented process (i.e., procurement and supply chain activities) requires significant effort, time, and resources (Hofmann et al., 2018).
P9. Scalability problems: Several factors intensified scalability issues: i) data transmission latency, ii) transaction processing rate (throughput), and iii) duplicate information storage (Biswas and Gupta, 2019; Yang et al., 2020).
P10. Lower external accountability control: Blockchain-based financing tools carries uncertainty and risks due to lower external accountability controls on them (Mougayar and Buterin, 2016).
P11. Financing models and debt instruments: There are various novel mechanisms to raise funds through blockchain-based platforms, such as supply chain finance (SCF). Lack of managerial perception and mindset about new fundraising tools in distributed platforms explain why decision-makers and practitioners hesitate and resistant to adopt these novel DLT-based solutions for their businesses’ needs (Hofmann et al., 2018).
Organization level: Organizational factors are often considered the most influential determinants of IT innovation adoption in firms and organizations (Clohessy and Acton, 2019). Having this in mind, 13 barriers and challenges have been identified, majorly in men, machines, methods, materials, and money (5Ms) aspects.
O1. Organizational considerations: To reap DLT/blockchain’s benefits, there is a high to managerial support, staffs’ cooperation and mind-sets, stakeholders’ trust, and organizational maturity (Clohessy and Acton, 2019).
O2. New business model: Organizations should determine the necessity of blockchain technology as their strategic needs and enhance services/products for customers accordingly (Penzes, 2018; Clohessy and Acton, 2019).
O3. Shared governance: The governance model is an integral part of an intra-/inter-organizational collaboration that determines how the platform is structured and controlled by parties (Penzes, 2018; Helliar et al., 2020).
O4. Financial constraints and cost of adoption: Although platforms are mostly free open-source, it is required to consider initial investment, costs breakdown structure, and prediction of cost-savings (Sawhney et al., 2020).
O5. Uncertain return of investment (ROI): Construction companies need a clear picture of the value proposition and (non)financial benefits offered by DLT adoption (Sawhney et al., 2020).
O6. Digital representation of real-world objects: A wide range of stakeholders and assets are involved in a construction ecosystem. For easy value exchange, organizations need to give access to people, create a native smart asset, or connect physical assets to the blockchain using RFID tags and digital identity (Mougayar and Buterin, 2016; Yang et al., 2020).
O7. Negative perception and insufficient understanding: Organizations may take a wait-and-see attitude and postpone adoption until they gain in-depth knowledge of DLT/blockchain’s potential (Barima, 2017; Kshetri, 2017; Saberi et al., 2018).
O8. Scarcity in multidisciplinary experts and developers: Organizations need multi-disciplined professionals and fresh new talent in cryptography science, smart contract and legal affairs, construction projects, and DLTs for successful implementation (Li et al., 2019; Yang et al., 2020).
O9. Legacy systems: Organizations need modern computer architecture and specialized equipment to reap DLT’s benefits. This can be obtained through replacing or upgrading existing systems (Mougayar and Buterin, 2016).
O10. System robustness and full technology stack: Adoption needs a set of technology stack (i.e., software, hardware, middleware, and infrastructure) and continuous internet connectivity (Mougayar and Buterin, 2016; Li et al., 2019).
O11. Lack of advanced applications and archetypes: The underlying technology is nascent; and, producing a killer-applications and successful archetypes takes a while (Mougayar and Buterin, 2016).
O12. Wide rollout and large-scale technology adoption: Shifting from ideation to real-world applications needs a list of requirements, such as investment, the firms’ readiness, and training staff (Sawhney et al., 2020; Yang et al., 2020).
O13. Compatibility and inoperability: Different applications/systems work together in construction projects. Poor interoperability and connectivity adversely affect transferring and storing data (Li et al., 2019).
Market/ Industry level: According to Michael Porter’s framework, the main dynamics of industries or sectors are buyers, suppliers, partners, and rivels (Johnson et al., 2008). Considering the construction industry’s state, eight barriers to DLT implementation have been identified considering construction industry’s condition.
M1. Network effects: Blockchain-based platforms need to engage sufficient users in viable business-to-business (B2B) and business-to-community (B2C) ecosystem (Mougayar and Buterin, 2016; Clohessy and Acton, 2019).
M2. Lack of customers’ demand, interest, and tendency: DLT technology requires customers’ interest and stakeholders’ support to flourish in industries and markets (Barima, 2017; Saberi et al., 2018).
M3. Low usability: Low ease of use and high complexity of the DLT/ BCT adversely affect customers’ journey experience and interaction with blockchain applications (Mougayar and Buterin, 2016; Helliar et al., 2020).
M4. Limited access to lesson-learned and practices: Learning from previous mistakes and accessing the best practices of previous experience are necessary to reap DLT’s benefits by industry players (Sawhney et al., 2020).
M5. Technical guidelines and standards: The construction sector needs globally agreed standards to run IT infrastructure for fewer overall risks, easier interoperability, data structure, and lower costs (Sawhney et al., 2020; McNamara and Sepasgozar, 2021).
M6. Lack of insurance mechanism: The inadequate insurance coverage to address the technical and business risks may prevent DLT adoption within the construction industry (Nawari and Ravindran, 2019).
M7. Technological state of the construction industry: The construction industry is not ready to embrace digital transformation due to traditional approaches and long-standing problems (Li et al., 2019; Sawhney et al., 2020).
M8. Market competition and heavily regulated segmentations: Some segmentations (e.g., infrastructure projects) are under pressure of market competition and heavy regulation due to their strategic place in society. These market forces might be barriers to adopt technological innovations (Kshetri, 2017; Saberi et al., 2018; Bürer et al., 2019).
Macro-environment level: Organizations and their projects are influenced by political, economic, social, technological, environmental, and legal (PESTEL) environments (Johnson et al., 2008). Nine barriers have been identified at the macro-environment level.
E1. Technology accessibility: Digital divide varies among societies, countries, and governments in the years of growth, adoption, and acceptance of technology (Saberi et al., 2018).
E2. Lack of government support: Governments and policymakers are not interested in emerging technologies in the particular blockchain. This technology acts independently without the control of governmental entities (Mougayar and Buterin, 2016).
E3. The volatility of cryptocurrency and fluctuating exchange rate: Cryptocurrencies are struggling with high volatility and fluctuations rate in the current years. It seems that underlying technologies of cryptocurrencies are not stable for use-cases and applications in the construction industry (Biswas and Gupta, 2019; Li et al., 2019).
E4. R&D projects and higher training programs: With the arrival of construction 4.0, there is a high need for awareness-raising, investment in R&D projects, and professional training programs (Sawhney et al., 2020).
E5. Lack of incentive and encouragement programs: One reason that dissuades industries from employing green technologies for sustainability is the lack of incentive schemes offered by governmental bodies (Saberi et al., 2018).
E6. High energy consumption: Some consensus algorithms (i.e., Proof-of-Work) are not environmentally friendly due to high energy consumption and greenhouse gas emissions (Biswas and Gupta, 2019; Li et al., 2019).
E7. Legal issues: The construction industry heavily relies on laws and regulations for project execution and operation. Due to technology newness, there is a high need for new policies and technology laws (Li et al., 2019).
E8. Compliance requirements: Compliance requirements_ for Know Your Customer (KYC) and anti-money laundering (AML)_ are critical processes to verify the due-diligence of trading partners. The compliance requirement for onboarding stakeholders to the DLT platforms is accompanied by significant time, cost, and efforts (Hofmann et al., 2018).
E9. Taxation and reporting: Aside from recording transactions, this technology still requires taxation, reporting, and auditing (Mougayar and Buterin, 2016; Biswas and Gupta, 2019).
It is worthwhile to mention that the technical problems are excluded from discussion in this paper. Some of these challenges are i) immaturity of technology (Mougayar and Buterin 2016; Saberi et al. 2018), ii) vulnerability and confidentiality risks (Mougayar and Buterin 2016; Upadhyay 2020), iii) coding of the smart contract (Yang et al., 2020); Sheng et al. 2020), iv) theft of data, security issues, cybercrimes, system hacks, and hard forks (Li et al., 2019; Frizzo-barker et al. 2019), and finally v) misconception between DLT/blockchain and cryptocurrencies (Saberi et al., 2018).