1 Introduction

Smart contracts are technology-driven, tamper-evident agreements that can self-execute a negotiated contract through a computer protocol [1]. Smart contracts are mostly blockchain-based and can automatically transfer digital assets based on arbitrary pre-specified logic specified as rules without a trusted third party [2]. While a vending machine is the oldest demonstrated example of a smart contract [3], technological advancements have made more sophisticated implementations possible. Smart contracts are deployed in various sectors, including medical care, finance, energy, and the Internet of Things (IoT) [4,5,6]. IoT is a connected ecosystem of virtual and physical objects that automatically generate and communicate big data [7]. Smart contracts aid the interconnectivity between devices by managing such interactions without requiring that the objects trust each other.

A literature search of databases (Scopus and Google Scholar) confirms that both ‘smart contracts’ and the ‘IoT’ have become topics discussed extensively, with interest increasing significantly since 2015 onwards. Scholars have undertaken several literature reviews exploring the integration of blockchain with adjacent technologies, including edge computing [8], artificial intelligence [9] and the IoT [10]. Other studies include an exploration of blockchain as a technology [11], sector-focussed evaluations such as in healthcare [12], and a detailed exploration of smart contracts [13]. These studies discuss the current state of research, the challenges/risks of integration, and directions for future research. However, they do not explore the intellectual structure of the respective areas to understand the foundation. Database-assisted studies in this area are further limited; studies such as [14] have investigated blockchain-based digital twins in asset lifecycle management and [15] identified the developmental trajectories of blockchain. [16] evaluated supply chain visibility with blockchain, [17] explored decentralised access control, and [18] assessed cyber-physical smart contracts. These studies also explored the current and future status but did not explore the foundation. The authors of such studies have leveraged databases such as Scopus, Web of Science, IEEE Xplore, Google Scholar, Springer, and ACM in their studies. The methods include systematic reviews using the PRISMA guidelines, mapping reviews, citation analysis, and bibliometric analysis. However, none of these studies leveraged the TCM (Theme-Context-Method) framework utilised in previous reviews such as [19].

An analysis of the extant literature confirms that only a few (five) database-assisted literature reviews of SC-IoT have been conducted. The existing studies discuss the current state of research and identify future research directions using methods such as systematic literature reviews and bibliometric analyses. However, they do not explore the foundations of this emerging topic. Motivated by this research gap, the authors propose a Scopus-based narrative review of the smart contract-IoT combination (SC-IoT) using the TCM framework. Unlike the previous studies, this narrative review examines the past, the present, and the future in the same study. This study identifies the foundational roots of the literature on the SC-IoT combination (past), examines the current state of research (present), and identifies directions for further research (future). In addition, this study also profiles the existing research. To the best of the authors’ knowledge, this is the first study in the SC-IoT space that utilizes this approach. Specifically, the following research questions are addressed by this review: 1) RQ1: What has the publication performance been in terms of authors, journals, and countries? 2) RQ2: What are the foundational research topics in smart contracts and the IoT? 3) RQ3: Which themes are the focus of current research? and 4) RQ4: What are the implications for future research and practice?

Our study builds upon and expands the extant SC-IoT literature. The main contributions of our study can be summarized as follows: 1) Synthesises and organises the existing SC-IoT knowledge base; 2) Provides a strong foundation for future scholars to conduct further research in this inter-disciplinary topic; and 3) Serves as an informed reference point for other stakeholders such as consumers, practitioners, governments, and policymakers. Our study profiles the existing research by shortlisting 227 relevant peer-reviewed articles and identifies the influential articles, journals, authors, countries, and publication trends. It further comprehends the intellectual foundation of the related literature by analysing the shortlisted articles’ references. The authors subsequently review the current state of research by critically examining the contributions of the 227 articles and identifying future directions for research, practice, and society. The findings of this research study are presented by utilizing the TCM framework.

The remainder of the article is organised as follows. Firstly, the authors explain the concepts of blockchain, smart contracts, and the IoT, followed by an analysis of the existing literature reviews. Secondly, the authors discuss the method adopted by this study to conduct the analysis. Thirdly, the authors profile the shortlisted research papers, discuss the foundation on which the SC-IoT research is based, and analyse the current research status and directions for future research. The study ends with the Limitations of the study and the Conclusion. Figure 1 explains the organisation of this review, similar to the one followed in [20].

Fig. 1
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Organisation of this Review

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2 Literature review

The following section briefly explains the three topics of interest – blockchain, smart contracts, and the IoT, and the reviews undertaken so far. This section has been structured along the lines of the review in [21] to enable the reader to better appreciate the concepts and their relationships.

2.1 Blockchain

Blockchain is a distributed system comprising a network of peers that can read or write and a consensus protocol specifying the basis of adding new transactions to the chain [22]. In such a linked list of records, new blocks validated by peers using cryptographic means are appended to the end of the list, with each block pointing to the previous block through a hash value [23, 24]. In addition to the hash value, each block contains a timestamp and a random number used to verify the hash. Consensus algorithms in blockchain ensure the integrity, confidentiality, and security of the platform – they enable the blockchain to reach a “consensus” on the order in which the transactions are listed in the block. While several consensus algorithms exist for different blockchains, the prominent ones are Proof of Work (POW), Proof of Stake (PoS), Byzantine fault-tolerant (BFT), Proof of Authority (PoA), and Proof of Elapsed Time (PoET), Among them, POW is the most popular. In POW, which is used for permissionless blockchains, the miner solves mathematical computations on the new block before validating the block [25]. POW is intentionally made compute-intensive and is key to making the blockchain immutable. Any node that finds the right random number (nonce) in the block header by solving the puzzle earns the right to validate the next block [22, 26]. Blockchain facilitates a network of computers to periodically arrive at a consensus on a distributed ledger’s actual state that contains shared data secured through cryptography without the need for any trusted nodes [27]. The result is an immutable chain of records or blocks that can be either public or private. Some industries amenable to blockchain implementation include banks, finance, money transfers, micropayments, identity/privacy, and the IoT. Blockchain offers several advantages, such as eliminating the need for separate reconciliation, ensuring data provenance, quick settlement of transactions, and a robust security model [28]. Addressing the adoption barriers such as security risks, privacy risks, higher investment costs, lack of organisational policies/structure, and inadequate knowledge management systems could open further avenues for expansion [29]. A blockchain that supports Bitcoin-style transactions can facilitate asset transfers; however, one that supports smart contracts may extend the support for transactions between parties that do not trust each other [26].

2.2 Smart contracts

Smart contracts are mostly deployed on blockchains, as they provide a decentralised architecture enabling multiple technologies and communication patterns [18]. Conceptualised by Nick Szabo in the ‘90 s, smart contracts are programs running on blockchain nodes, and correspond to the protocols and user interfaces that formalise and secure relationships over computer networks [3]. Although introduced in 1994, some objectives such as verifiability, enforceability, observability, and privity were described in 1996 [30]. Smart contracts started gaining increased attention after Satoshi Nakamoto introduced Bitcoin in 2008. Multiple definitions of smart contracts exist today—from a technological perspective, they may be defined as event and state-driven programs that run on a platform to administer assets [31]. From a legal perspective, smart contracts may be defined as self-executing, tamper-proof agreements [32]. Smart contracts are utilised in a variety of industries such as real estate (e.g., purchase and lease agreements), finance (e.g., stock trading), healthcare (e.g., electronic health record management), construction (e.g., automated payments) and energy (e.g., electricity trading) [33]. Smart contracts offer several benefits including accuracy, autonomy, cost savings, and execution speed [34]. Although smart contracts are promising, several challenges remain to enhance their adoption, such as performance issues (low throughput, data storage difficulties), privacy issues (artificial stealing, node vulnerabilities), and security issues (contract loopholes, leakage of users’ information) [35].

Based on preliminary investigation, smart contracts are more suited to industries with quantifiable terms of engagement and built on a system with clear rules [36]. While smart contracts enable general-purpose transactions, they add the most value in managing data-driven interactions between multiple non-trusting entities within a network. Once hosted and verified on the network, the smart contract will provide the same result for the same input each time, and the execution cannot be stopped, in theory. The execution also leaves an audit trail, and the potential of a dispute is minimised since the contracting parties would have agreed on the terms before the contract’s execution. Not surprisingly, one of the most prominent applications of smart contracts is in the context of the IoT.

2.3 Internet of things

The Internet of Things (IoT), first coined by Kevin Ashton in 1999, refers to embedded computing devices that collect and store information without human intervention [37]. The IoT is an interconnected network of objects that are identified by an exclusive identifier and communicate over a network [38]. The IoT network consists of four layers: sensors (primary identification and tracking), networking (sharing of information between devices), services (integration of services and applications through middleware), and the user interface (user interaction) [37]. The technological advancement in communication protocols and the rapid advancements in adjacent technologies have enabled these devices to communicate and generate large amounts of data. Some common applications of the IoT are seen in the smart city, retail, healthcare, agriculture, and manufacturing sectors [39]. Several challenges must be resolved to improve adoption, including data privacy, network/IoT security, scalability, energy efficiency, and interoperability [40].

Security and privacy-related attacks on IoT devices are becoming more sophisticated and prominent with each passing day due to the increased availability of computing power [41]. The attacks impact not just the physical security (e.g., node capture, replay, side channel) but also the network (e.g., spoofing, man-in-the-middle attack, and denial of service) and application (e.g., phishing, trust management, malicious scripts) security too [42]. Instances of users being impacted include situations where users receive images from other people’s homes in smart security cameras, and hackers play disturbing music and change the room temperature in smart homes. Researchers have also demonstrated the vulnerability of IoT devices by stealing device passcodes through an acoustic side channel attack on a smartphone’s microphone, stealing data from a fax machine, and hacking a smart speaker during a live demonstration at the DEFCON security conference [43].

A secure IoT system must ensure the confidentiality of data, integrity of data, and network availability. Several approaches have been deployed to resolve security and privacy-related issues, including the use of blockchain, artificial intelligence, cloud, fog computing, edge computing, and various combinations of the above [20, 41, 44, 45]. Owing to its immutable, decentralized, and transparent properties, blockchain offers a promising solution to address security and privacy-related issues [46]. Blockchain records data securely on blockchain and facilitates safe and transparent data sharing between connected devices [47]. Blockchain-related solutions that have gained traction include secure unique identification (assigning a unique blockchain-based address to each IoT device using public keys) and secure communication (using lightweight protocols since no key management or key distribution needs to be maintained in the blockchain). Other measures include enabling privacy through authorization (implementing data access policies through a smart contract) and ensuring data integrity (the immutable nature of blockchain makes refuting a committed transaction difficult and enables non-repudiation) [42]. However, several challenges remain, such as the lack of consensus protocols resulting in limited adaptability of the integrated blockchain-IoT (BC-IoT) paradigm and transaction validation challenges owing to IoT devices’ distributed nature and heterogeneity. Other challenges include implementing frequent software/firmware updates due to the decentralized nature of blockchain, limited interoperability due to the varying properties of blockchains / IoT devices, and sub-optimal network performance on parameters such as timeliness and power consumption.

Blockchain aids the development of a secure, decentralised, and trustworthy IoT ecosystem. Smart contracts and consensus protocols are foundational components of blockchain technology. Smart contracts and PoW share a supportive relationship as both rely on a common platform – blockchain, but serve different purposes. While smart contracts automate participant interactions based on the data collected, consensus protocols such as PoW are the backbone of block propagation and facilitate secure and transparent interactions between the objects. Smart contracts are not solely dependent on PoW as other alternatives exist (such as PoS), and PoW cannot independently make or manage smart contracts—PoW facilitates a secure environment, and smart contracts utilize this to enhance the IoT ecosystem [48, 49]. A smart contract is a powerful multiplier for the capabilities of the IoT devices since both the code and agreements are replicated across the network elements. It is well-positioned to harness the large amount of data that is transmitted over the network and, at the same time, facilitates a set of actions based on predefined rules.

2.4 Existing literature reviews

Both ‘smart contracts’ and the ‘Internet of Things’ (generally written as IoT) have recently become topics discussed extensively in the academic and practitioner world. A simple search (during early 2022) of Scopus’s journal articles on the ‘Internet of Things’ returned 311,047 results, and ‘smart contracts’ returned 19,006 results. More than 99% of the articles on ‘smart contracts’ and 92% on the ‘Internet of Things’ were published after 2015, indicating recent significant levels of interest. A similar search in Google Scholar revealed comparable observations—80% of the articles on "smart contracts" and 71% on the "Internet of Things" were published after 2015. A search on the Scopus database (during early 2024) for reviews or surveys on the combination of smart contracts and the Internet of Things returned 81 records [Scopus search query: TITLE-ABS-KEY ("smart contract" AND ("internet of thing" OR "iot") AND (survey OR review)) AND (LIMIT-TO (DOCTYPE, "ar")) AND (LIMIT-TO (LANGUAGE, "English"))]. The authors reviewed the titles and abstracts of these articles carefully for alignment with the topic and 45 were apt. Table 1 provides a summary of the papers.

Table 1 Surveys/Reviews on SC-IoT
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While many referred to integrating blockchain with concepts such as artificial intelligence, edge computing, or the IoT, some focussed on sectors such as healthcare, agriculture, and smart homes. Only a few articles explored the development, challenges, and languages of smart contracts in detail, and some explored blockchain in general. [10] investigated the integration between blockchain and the IoT, the challenges in developing applications, and ideated on how blockchain could better enable the IoT ecosystems. [49] considered BC-IoT integration as a new paradigm, introduced an architecture for the Blockchain of Things (BCoT), and discussed potential issues regarding future implementations. [8] reported on the progress of edge intelligence-blockchain integration and the associated benefits of computing power management, data administration, and model optimization. More recently, authors have considered the integration of artificial intelligence with blockchain – [9] reviewed federated learning methods for holistically securing the IoT ecosystems; [50] examined federated learning frameworks from process decentralisation and reward mechanism perspectives and [51] conducted an in-depth evaluation of ensemble learning methodologies in the blockchain network.

Authors have also conducted sector-specific explorations—[12] reviewed applications of blockchain technology in healthcare and proposed workflows for better data management using Ethereum, and [52] explored concepts such as explainable blockchains while evaluating blockchain-based healthcare systems. Agriculture-focussed studies such as [53] studied blockchains in the agricultural sector, including technical elements, categorised the existing blockchain applications, and identified key challenges, and [54] evaluated the potential of blockchain to enable food traceability, protect workers’ rights, limit the power of intermediaries, and protect market prices. Authors have also investigated the applicability of blockchain in aerospace and oil and gas sectors; [55] explored the potential of blockchain to revolutionise aerospace using multiple usage cases such as battlefield operations management, border protection, and swarm assistance for rescue operations and [56] discussed the applicability of blockchain in managing the exploration, production, supply chain, and logistics in the oil and gas industry.

Some studies have explored blockchain technology in general and smart contracts specifically—[11, 57] discussed the taxonomy, consensus algorithms, categories, applications, and technical challenges of blockchain; [13] discussed the application of smart contracts in Industry 4.0, [58] reviewed the development and opportunities of smart contract deployment through an explanation of the working principles and the status of application research, and [59] examined recent developments in smart contracts across the categories of platforms, risks, and solutions. Other studies have included applications of blockchain in the metaverse [60] and how blockchain can resolve issues in governance [61].

The authors further filtered the review articles to identify database-assisted studies that explored the SC-IoT combination—summarised in Table 2. [14] explored blockchain-based digital twins in asset lifecycle management and established that blockchain-based digital twins can support digitalisation initiatives through a systematic literature review supported by a quantitative survey. [15] identified blockchain’s developmental trajectories and themes through citation analysis. Four stages of development included the challenges to Bitcoin, smart contract issues, opportunities, challenges, and development in blockchain, and smart contract applications; themes included e-healthcare, energy, Bitcoin, security of Bitcoin, financial applications of Bitcoin, Ethereum smart contracts, security, and privacy in the IoT. While [16] evaluated supply chain visibility with blockchain through a bibliometric analysis identifying five knowledge clusters, [17] explored decentralised access control through a study of the challenges of centralised access control on securing the IoT devices, and [18] assessed cyber-physical smart contracts through a mapping review of the underlying architectures from the dimensions of cyber-physical architectures, infrastructure failures, and the technical challenges. The databases explored for the studies include Scopus, Web of Science, IEEE Xplore, Google Scholar, Springer, and ACM. The authors have adopted systematic reviews using the PRISMA guidelines, citation or cluster analysis, and mapping reviews. However, none of the studies used the TCM (Theme– Context–Method) framework.

Table 2 Database-assisted studies that explore SC-IoT combination
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3 Research method

An effective review of prior, relevant literature builds a strong base to advance existing knowledge and, at the same time, facilitates theory development [62]. A stand-alone literature review creates a starting point for scholars interested in a particular field [63]. Such a review could be undertaken for several reasons in order – to evaluate the progress of a specific research stream, aggregate the findings by previous studies, review the application of a theory or methodology. or to enable theory building. Some commonly undertaken literature reviews include narrative reviews, systematic reviews, meta-analyses, and bibliometric analyses. While systematic literature reviews are often performed manually on a narrow set of articles, meta-analyses, and bibliometric analyses rely on quantitative tools to cover more articles. Meta-analyses are commonly used as theory extension tools, while bibliometric analyses summarise the bibliometric and intellectual structure by analysing the social and structural relationships between different research constituents [64]. In contrast, narrative reviews attempt to uncover what has already been written about a particular subject.

The authors chose narrative review since they found this to be the most suitable review method, given the status of research on SC-IoT. The extant literature is not mature enough to warrant a systematic literature review. Furthermore, it includes only a few empirical studies; hence, meta-analysis is not preferred. Since the literature has picked up the pace only during the recent decade, a bibliometric analysis may not help glean relevant insights. This narrative review is divided into four sections – the first profiles the existing research, the second uncovers the intellectual foundations of the research, the third analyses the current state of research, and the fourth discusses some implications for future research. The authors reviewed the articles referenced in the shortlisted papers to determine the foundations of SC-IoT. Then, they reviewed the shortlisted articles to understand the current state of research. While reviewing, the articles were grouped into themes based on the observed commonalities. The resultant groupings helped determine the individual clusters in each of the areas. While one author reviewed and identified the themes, the other authors evaluated the themes and suggested revisions to the groupings and themes. The authors conducted brainstorming sessions based on the identified themes to determine the implications for future research and practice. For each of the three sections, the authors also identified the relevant context in which the research was conducted and the methods employed.

The authors chose the Scopus database to conduct the narrative review. Scopus is among the largest citation and abstract databases of scientific peer-review literature, including 23,000 titles from publishers, and guarantees the data’s completeness and reliability [65]. The search was conducted in January 2022 using the search string ‘smart contract’ AND ‘internet of thing’; it was limited to English, and the period was set as all research artefacts published until December 31, 2021. The search returned 1,072 records that included 596 conference papers, 385 articles, 32 book chapters, 28 conference reviews, 27 reviews, two books, one editorial, and one note. Research articles from only the following fields were used for further analysis to ensure relevance to the Information Systems field: ABDC—Information systems, Management, Marketing/Tourism/Logistics, Accounting, Other commerce, management, tourism, and services; Scopus—Business Management & Accounting, Social Sciences, Decision Sciences, Economics, Econometrics, and Finance; Scimago—Information Systems, Information Systems and Management, Management Information Systems, Business Management and Accounting (Miscellaneous), Decision Sciences (Miscellaneous); Web of Science—All categories/sub-categories containing Information system and Information science. The above shortlisting process resulted in 227 articles for further review.

4 Research profiling

This section addresses RQ1—What has the publication performance been in terms of the authors, journals, and countries?

4.1 Publication trends

Smart contracts, as a concept have existed for a while; however, their application in the context of IoT has picked up interest recently. While only one article was published in 2016, 45 were published in both 2019 and 2020, and in 2021, the number more than doubled, indicating the increasing interest in this area. Please refer Table 3 for the summary.

Table 3 Number of papers by year
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4.2 An overview of the top authors, journals, and countries

Table 4 represents the most productive authors, journals, and countries, with productivity being measured by their respective total publications (TP). Seven hundred and forty-nine authors have published 227 articles, with 95% having authored two or fewer articles. Sixty-nine Scopus-listed journals have published articles on smart contracts in the IoT context. Of the 69, 12 are IEEE-related journals—IEEE Internet of Things and IEEE Access, and IEEE Transactions on Industrial Informatics journals form the top three contributing journals. These three contribute 44% (99) of the overall number of articles. Like the authors, the journals also exhibited a long tail, with ~ 60% of the journals contributing only one article each. Authors from 51 countries have published articles related to smart contracts in the IoT’s context, with the top three countries represented in ~ 67% of the articles. Cumulatively, China, the United States of America, and the United Kingdom are represented in 151 articles.

Table 4 Top 15 authors, journals, and countries
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4.3 Influential articles

Table 5 lists the top 15 influential papers. With five papers cited more than 250 times; cumulatively, these 15 papers have been cited more than 3.500 times (3,788). [11] stands out, with more than 900 citations. The authors conducted a comprehensive survey on blockchain technology, discussed its taxonomy, consensus algorithms, and reviewed the application areas and technical challenges. The authors also identified five areas for future research, including smart contracts, blockchain testing, centralisation avoidance, artificial intelligence, and big data analytics. [48] introduced a new blockchain-based, fully distributed access control system for the IoT and supported this with a proof-of-concept implementation. [66] proposed an IoT e-business model that helped realize smart property transactions and paid data on the IoT with the help of peer-to-peer trade based on smart contracts.

Table 5 Top 15 Influential papers
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Since blockchain is the platform, and smart contracts reside on the platform enabling functionalities, most papers explore smart contracts from the perspective of blockchain and its integration with the IoT. Hence, few papers provide an exclusive and in-depth focus on smart contracts. Although blockchains and smart contracts have existed for a while, they have only recently captured the imagination of academicians and practitioners.

4.4 Journals as leading sources

Both smart contracts and IoT are based on technological developments as reflected in the list of the most productive journals. The aims/purpose/scope sections of the most productive journals below reveal that they all have a significant technological focus. The articles that have been published include literature reviews, applications in use examples, and the exploration of concepts. Although the journals welcome process, technology, and theory papers, there is little evidence of papers regarding theory development being published.

H-index and average citations per paper (Total citations divided by Total publications; abbreviated as TC/TP) may be considered as key criteria for a journal’s influence [67]. Higher values would identify the most relevant journals published in the literature concerning smart contracts and the IoT. TC/TP and publication output follow a similar trend in journals that have published more than ten papers, (bar one, IEEE Transactions on Industrial Informatics). However, the TC/TP and H-index do not follow the same pattern as the journals. While Sensors and IEEE Access are the top two in terms of H-index, IEEE Transactions on Computational Social Systems and the IEEE Internet of Things Journal are the TC/TP top two among the top 15 journals. Please refer Table 6 for details.

Table 6 Citation structure of top 15 journals
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5 Foundations of smart contracts and the IoT research

The authors have utilised the TCM (Theme-Context-Method) framework to present the findings on the foundations, current state of research and the direction for future research. The themes correspond to the underlying commonalities, the context refers to the sector/industry in which the referenced studies were conducted, and the methods represent the approach followed in conducting those studies. The authors explored the articles listed as references of the shortlisted articles to understand the foundations of the SC-IoT research (RQ2). The authors uncovered five key elements. The foundational articles explore the applicability of blockchain in the context of the IoT– this provides fertile development grounds for smart contracts since blockchain is the platform on which smart contracts reside. While one explores decentralised data management, the second addresses orchestrating the relevant services to achieve a coordinated outcome. The other three pillars addressed the key challenges regarding deployment, relevant usage cases, and decentralised trust management. The following sections explore the themes, contexts, and methods of the foundational aspects.

5.1 Themes

5.1.1 Decentralised data management

IoT applications are characterised by the large amounts of data they generate. While the challenge of storing and processing large volumes of data can be addressed by integrating with cloud technologies, the resultant centralisation leads to concerns regarding security and privacy. Integrating the IoT with blockchain enables decentralised data sharing at scale and addresses security and privacy challenges. The extant literature includes several review and survey articles that studied the integration of blockchain with the IoT—while [68] and [69] focussed on the security and privacy aspects, [10, 70] and [11] analysed the integration of blockchain and the IoT solutions in general, including their development, deployment, and optimisation. Specific solutions to address the security and privacy issues included a distributed secure SDN architecture for the IoT using blockchain (DistBlockNet) [71] and secure key management schemes in vehicular communication systems [72]. Adaptations of the Elliptic Curve Digital Signature Algorithm [73] are implemented in signature schemes, including lattice-based signature schemes that can resist quantum attacks [74] and attribute-based signature schemes [75] that enhance security. In addition to introducing the blockchain architecture, consensus algorithms, and typical applications, the reviews also discuss the technical challenges, limitations of the IoT devices, secure code deployment, and several other factors. The authors have explored blockchain’s data storage and processing capabilities further in sectors such as energy and healthcare and found that the performance of blockchain-based solutions is comparable [76] or superior [72]. Several recent advancements, such as mobile edge computing [77], fog computing [78], and consortium blockchains [79] have improved decentralised data management and applicability of blockchain-enabled IoT devices. Additional research directions have highlighted several aspects that include work on interoperability, standardisation, energy-efficient communications, development of design principles for the future, and organisational/regulatory considerations.

5.1.2 Service orchestration

Services form the building blocks that execute activities of the business process of any ecosystem [80]. Through service workflows, also known as business processes, the ecosystem utilises services to improve dynamic interoperation among its constituents to achieve its functionalities [81]. Functionalities are viewed as services that are orchestrated by service workflows [82]. Service selection in a service workflow (which specifies the composition, sequence, and execution path) is based on several parameters, such as service quality, experience, and reputation. The service requirements are developed through service workflow specification languages (examples include SWSpec and Self-Adaptive Configuration based on HMSFootnote 1BAMFootnote 2 and CTRFootnote 3).

Blockchain is appropriate for complex workflows [83] such as in an IoT context—with technological advancements, the BC-IoT combination presents several opportunities for automation, effective data sharing, and business transformation [84]. Integrating blockchain into business processes will help to mitigate the risks associated with security, privacy, trust, automation, and interoperability issues—examples include FairAccess [85] and "Bubbles of Trust" [86]. While FairAccess provided a pseudonymous and privacy-preserving authorisation management framework, Bubbles of Trust enabled robust identification and authentication of devices. Blockchain is also architected to integrate with other service (or business process) components to resolve traditional problems of time inconsistency and consensus bias to improve the overall trust levels. BC-IoT integration must be carefully orchestrated, since several challenges must be overcome (please refer to Section 5.1.3). The authors have also identified several open research challenges in this emerging area, including resource limitations of the IoT devices, the heterogenous nature of the IoT devices, hardware/firmware vulnerabilities, development of green IoT technologies, and employment of artificial intelligence and cloud computing [87,88,89].

5.1.3 Deployment challenges

While the BC-IoT combination can help to achieve the true potential of the IoT, close attention needs to be paid to several potential challenges. [26] highlighted several such issues and suggested potential solutions. The inherent nature of blockchain leads to slower transaction processing than a centralised system, hence reduced throughput. Since the transactions are replicated transparently across nodes, sophisticated actors can analyse the transactions to make informed inferences, thereby compromising privacy. As a solution, devices can use separate keys for each transaction or separate keys per transacting party to limit exposure. Homomorphic encryption or Zero Knowledge Proofs can also help to achieve transactional privacy. Miners should be chosen carefully—although miners cannot create fraudulent transactions, they can prevent a truthful one from being recorded. Since regulations are still catching up with this new technology, legally enforcing smart contracts remains challenging. Another issue that needs to be tackled is "complete autonomy.” Smart contracts are executed automatically according to compliance with certain pre-defined conditions. Hence, measures should be taken to avoid unintended consequences such as faulty smart contract coding. Access to the blockchain-integrated IoT system should be monitored carefully– if malicious actors gain unauthorised access, they can create unwanted problems for the entire ecosystem. [48] proposed a scalable and easy-to-access management system and demonstrated its efficiency through a proof-of-concept prototype. The energy consumption by blockchain-based methods is higher than by traditional methods, and development of mechanisms to reduce the energy requirements are ongoing. Additionally, coordination costs of integrating blockchain into the IoT context can sometimes be considerable; thus, optimal methods to reduce these need to be developed. Other key challenges include double-spending [90], transaction malleability, and pooled mining [91]. In addition, significant delays and computational overheads introduce several design challenges that practitioners need to resolve.

5.1.4 Blockchain – IoT usage cases

With its unique advantages, the BC-IoT combination, termed the Blockchain of Things (BCoT) [17], may be applied in many industries. Dai et al. explain that smart manufacturing, supply chain management, food industry, smart grids, healthcare, the Internet of Vehicles (IoV), and unmanned aerial vehicles (UAVs) are prominent among such applications. In smart manufacturing, BCoT aids interoperability by enabling data sharing by forging connections between the IoT systems in a peer-to-peer network, which enables better security and privacy, reduces security maintenance costs, and enhances data quality assurance. In supply chain management, it helps establish the provenance of the parts used in the supply chain and reduces counterfeits. Thus, it reduces the cost and risk elements and increases the velocity of the supply chain. BCoT can enhance the traceability of food products by integrating RFIDs in the food industry. In smart grids, BCoT facilitates secure energy trading among peers, enabling the rise of a new class of prosumers (producers and consumers), reducing trading costs, and protecting the confidentiality of transactions. Integrating blockchain into healthcare data (such as that generated through wearables) helps to preserve privacy and enables tracing the origin of pandemic outbreaks. BCoT also enables secure energy trading in electric vehicles and resolves the challenges of heterogeneity and non-trustworthiness of data compared to traditional implementation in the context of IoVs and UAVs. Blockchain may also be utilized in other usage cases, such as in smart homes [92], authentication systems [86], medical data access/permission management, and implementation of role-based access controls [93]. While Dorri et al. demonstrated through a case study that a blockchain-based smart home framework can ensure the triad of confidentiality, integrity, and availability, Hammi et al. implemented a decentralised authentication system using C +  + and Ethereum and established its capabilities of robust device identification and authentication.

5.1.5 Distributed trust management

The distributed nature of blockchain enables any participant node in a network to transact in a decentralised, trusted manner within various environments, including vehicular networks and electronic health records (EHR). However, confidentiality, scalability, and the reliance on third parties require addressing. [84] proposed a decentralized trust management system for vehicular networks using joint Proof of Work and Proof of Stake consensus mechanisms. The vehicles in the network use the Bayesian inference model to validate the messages received and generate ratings to assess the credibility of the messages. Thus, trust values are generated and aggregated in roadside units (RSUs) that maintain a concurrent, reliable, and consistent trust blockchain. Since data is stored in a decentralised manner, security and access control become crucial. [85] proposed a framework to address the problems of data integrity, security, and management that utilises off-chain storage, enabling scalability, and provides secure storage, and defines granular access rules for EHRs. Along similar lines, [86] introduced a blockchain-based framework for a data integrity service for the IoT that does not rely on third-party auditors. The prototypes are found effective based on the performance evaluation results – authors establish the system’s effectiveness through simulation, and prove that their pay-per-transaction data integrity service provides a reliable and scalable solution that supports decentralised data trading. Another decentralised trust management perspective is integrating two technological ecosystems; blockchain and artificial intelligence [87]. The authors have provided a detailed discussion on the taxonomy, compared common blockchain implementations, and identified challenges in enabling decentralised AI (including privacy, scalability and side chains, security, smart contract vulnerabilities, and AI-specific consensus protocols).

5.2 Context

Table 7 summarises the sectors in which the studies were conducted. More than two-thirds of the studies do not refer to any specific sector. The findings in such studies are likely applicable uniformly across sectors – reviews (discussed in 5.3) constitute more than 40% of such sector-agnostic studies. Some studies refer to multiple sectors such as healthcare, logistics, smart cities, food supply chain, mining production, transportation and logistics, and firefighting. Other prominent sectors referenced in the literature include energy, healthcare, and transportation.

Table 7 Context of Foundational Studies
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5.3 Method

The methods utilised in the foundational studies are provided in Table 8. Frameworks are the most used method among the studies, with circa 40% of the studies utilising this method. The authors have defined architectures, algorithms, or service workflow specification languages. For example, Viriyasitavat and Hoonsopon defined an architecture to integrate blockchain into business process management, and Sharma et al. developed a secure distributed SDN architecture for the IoT using blockchain technology. A considerable number of studies are positioned as reviews. While they may be comprehensive [94], the authors do not explicitly clarify the method used to identify the literature. Many studies have also developed prototypes – a miniature, working version of the artefact. For example, Novo has developed a proof-of-concept implementation for scalable access management in the IoT; Bahga and Madisetti have implemented BPIIoT (Blockchain Platform for Industrial Internet of Things) to enable decentralised, trustless interaction in a peer-to-peer network. Some other articles are positioned as opinions, and one article deployed a multi-criteria decision method (analytical hierarchical processing) to select services in service workflows.

Table 8 Methods followed in Foundational studies
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6 Current state of research

This section addresses RQ3—Which themes are the focus of the current research? The authors have reviewed the shortlisted articles and uncovered five key themes in the published literature. While the first discusses the convergence of blockchain and the Internet of Things, the following three discuss different aspects of data – data security, data privacy, and how the data generated may be monetized. Sufficient attention is also provided to promising application areas of smart contracts. Each theme is discussed in detail in the following section.

6.1 Themes

6.1.1 Blockchain-IoT convergence

An IoT network comprises several resource-light devices (memory and computing power) [95], which cannot perform extensive computations. Integrating emerging technologies such as blockchain and the cloud-edge paradigm can enable efficient aggregation and processing of the huge data generated by the IoT nodes [96]. Current instances of IoT networks demonstrate a high degree of centralisation [97], often leading to a single point of failure/compromise [98], and the potential for manipulating the IoT data [99]. Integrating blockchain and the IoT is increasingly used to resolve challenges such as centralisation, trust, scalability, security, and privacy [100, 101]. The decentralised blockchain-based approach helps to enable credible information transmission [102], improves authentication efficiency [103], enables autonomous transaction settlement [104], preserves privacy [105], enhances trustworthiness [106], and can contain an IoT security breach in a targeted way after it is discovered [107]. Blockchain can be integrated through service-oriented architectures [108], and services/resources can be orchestrated [109] through workflows to enable interoperability of the IoT services. Blockchain further offers the facility of aggregating users’ evaluation of the various component nodes and computing the reputation of each, thereby establishing a reputation management framework [98]. This framework is, in turn, utilised to ensure an adequate quality of service (QoS) in the network. The identity of nodes can be established through decentralised versions of constructs, such as self-sovereign identity that decouples the digital identity from the owner, to facilitate large-scale cooperation [110]. Other measures to ensure QoS include nonrepudiation service provisioning schemes [111], reporting service quality as penalties based on any differences between the expected and actual values [112], and decentralised QoS measurement through collectively trusted sub-networks [113]. Blockchain can also help resolve the potential issue of siloed storage—the on-chain network is used to process transactions, and an integrated off-chain network is utilised for storage and complex data processing [114]. However, this integration can also lead to performance concerns due to additional storage and computing requirements, and communication overheads. Efforts are underway to create more efficient system designs to address these concerns by leveraging advancements such as zero-knowledge proofs [115].

6.1.2 Data privacy

An IoT ecosystem helps users access personalised services based on analysing the data sensed from the devices, which often includes data shared by the end users, but who are oblivious of how the data may be utilised [116]. While a considerable amount of data is generated owing to the large number of IoT devices, the devices cannot process the data due to resource limitations. Hence, the network depends on external environments, such as cloud-based networks to process this data [117], thereby amplifying privacy-related concerns. Data privacy includes anonymity, untraceability, unlinkability, unforgeability, and confidentiality [118], all needing to be preserved. Several approaches exist to ensure privacy in an IoT network including (i) Segregating the blockchain network into multiple channels, where each channel processes a specific data type and comprises a certain fixed number of authorised organisations; (ii) The use of cryptographic techniques [119], both within a domain and across domains [120]; (iii) The use of a privacy-preserving framework [105] to ensure data authentication and mitigation of data poisoning attacks [121]; (iv) Federated learning where the local data samples at the edges are used to train, and data models are shared instead of sharing raw data [122]; (v) Edge computing architectures in which the processing is moved to the edge of the network [123]; (vi) By storing the sensitive data off-chain [124] and (vii) By defining hierarchical smart-contract based access control [125]. The exchange of data can occur within one IoT network and across various IoT networks where the data sets could be shared to improve the overall efficiency of the ecosystem, such as for IIoT or Internet of Medical Things (IoMT) [126, 127]. Smart contracts can also be used as a governance mechanism, a data attestation service provider, or reputation management to enhance network privacy [128,129,130]. The authors have suggested that increased training for the stakeholders, financial investments in smart contracts, and regulatory support will help address privacy-related concerns in the long run [107].

6.1.3 Security of the ecosystem

The proliferation of intelligent devices has created the security risk of the IoT network being compromised, as bad actors can exploit networks through malicious devices or network capture [131]. A secure IoT system corresponds with the security of physical devices and networks and has a bearing on the relevant processes, technologies, and measures [132]. The network’s security can be assured through several approaches: (i) The use of identity and access management systems that limit access only to authorised devices within the network, implemented through smart contracts [105, 107]. These could be based on measures such as the computed reputation scores of nodes [130, 133], or context-aware authorization management as a service [134], or multi-signature smart contracts [122] (ii) An interoperable trust framework among different blockchains [106] (iii) Lightweight agents at IoT installations to collaboratively detect distributed denials of service [135] (iv) Physical unclonable functions (PUFs) as an authentication barrier [136] and (v) Encryption methods such as two-phase encryption [137], hierarchical cryptographic key generation [138] or interplanetary file system (IPFS) to store ciphertext [126]. While the security of the network is important across all sectors, sectors such as the IoMT, Healthcare IoT, smart city, and agriculture [105, 106, 119, 139, 140] have received much attention of late. Security frameworks in an IoT network are also subject to continuous improvement using emerging technologies such as artificial intelligence [141] through techniques including federated learning [130] and XGBoost [142]. Authorised parties could also be enabled to audit the behaviours of the auditors [143], thereby encouraging the desirable behaviour of the auditors to address post facto concerns regarding security. Implementation of security considerations should achieve an optimal balance between the security and performance of the network and incorporate energy-efficient mechanisms [144]. The security implementation should also explore various mechanisms such as a post-quantum approach given the resource constraints of the IoT devices [13].

6.1.4 Data trading in IIoT

Development of the Industrial Internet of Things (IIoT) has led to large-scale data creation, thereby enhancing the possibilities for data trading [127]. The data generated may be traded by establishing a digital data marketplace [145]. Data trading has assumed considerable significance given its potential economic impact on efficiency, decision making, and the customer’s experience [146]. A good data trading model should establish the trustworthiness of the trading partners, data availability for the consumers, privacy for the data providers, transparent value creation for the suppliers and demanders, and a dispute arbitration model to resolve disagreements [147, 148]. Current data trading models are plagued by high latency, leading to poor service quality [127] and a lack of trading fairness [149]. Fair and efficient data trading protocols [127, 148], which are scalable and autonomous transaction settlement systems [104], should help to overcome such challenges. The data trading platforms can trade data packets and analytic services by utilising public and consortium blockchains [150]. Another commonly cited hindrance in the data trading market is unauthorised access to data. Several blockchain-based approaches can resolve this through measures such as traceable aggregate signature schemes [151], hybrid access control mechanisms [152], multiple access control contracts [153], attribute-based encryption schemes [154], and a combination of security by contracts, manufacturer usage description (MUD) based behavioural fingerprinting and software-defined networking [133]. Artificial intelligence and machine learning techniques are also used to optimise the analytics services in the IIoT landscape. Examples include chatbots and intelligent assistants for public engagement as part of GovTech systems [155], an AI-based data analytics framework integrated with blockchain for 5G networks [141], a deep learning-based anomaly detection engine for smart agricultural UAVs [121], and a cognitive micro natural gas industrial ecosystem [156].

6.1.5 Usage cases of smart contracts

Limited successful prototypes and a lack of critical mass have impeded large-scale adoption of smart contracts in the context of the IoT. However, some prominent applications are beginning to emerge in IIoT and several other sectors (discussed in detail in 6.2). While healthcare, energy, transportation/logistics, smart home, and agriculture show promise, several industry-agnostic applications are also being developed. Several privacy-preserving solutions are being implemented in areas such as authentication protocols [96], medical data sharing [157], parking platforms [158], consortium-based PHR (patient health record) management [126] and smart agricultural UAVs [121]. Smart contracts are also being used to build various scalable access management models [48], including ones based on entitlement [159], attributes, access authority authentication schemes [120], hybrid access [152] and adaptive risk-based access control [160]. Other usage cases include smart grids for energy distribution [161], the use of elastic smart contracts to aid analytics/decision-making both in and between multiple IoT blockchains [162], the design of a smart healthcare system through the integration of Blockchain 3.0 and Healthcare 4.0 [163], peer-to-peer electricity trading [164], and self-tallying voting systems [165]. Smart contracts are also being integrated with other emerging technologies in usage cases such as information sharing in AI-enabled 5G networks [141], spectrum auctions for 6G mobile networks [166], the development of secure fitness frameworks integrated with machine learning approaches [167], and the auditing of the auditors’ behaviour [143]. Although not widespread, usage cases are also being developed in sectors such as government (algorithmic government) [155], engineering/construction (information traceability), and tourism (integrated reservations systems based on smart contracts) [168].

6.2 Context

The sectors in which the studies were conducted are provided in Table 9. Most studies (144) analysed as part of the current state of research do not focus on any specific sector, as in the foundational studies. Most such studies have either developed a framework or a prototype. Many of the remaining 83 studies focussed on healthcare, energy, transportation/logistics, smart city/home, and agriculture. Compared to the foundational literature, while the number of studies focusing on specific sectors has increased, the percentage has reduced marginally from 72% to 63%.

Table 9 Context of Current state of research
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6.3 Methods

The methods utilised in the studies in current state are provided in Table 10. Like the foundational studies, most studies (~ 70%) have developed frameworks, such as architectures [169] (an architecture for monetizing data using smart contracts), protocols [170] (a contractual routing protocol for IoT devices using smart contracts), and algorithms [171] (an algorithm for content caching). Around 15% of the studies have developed prototypes based on platforms such as Ethereum (e.g., [172]), or Hyperledger (e.g., [167]). Sixteen studies have conducted reviews based on the extant literature and identified research opportunities. Other methods include case studies, game theory, systems design, and action research.

Table 10 Methods of Current state of research
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7 Implications for future research and practice

This section addresses RQ4: What are the implications for future research and practice? The implications for future research are discussed using the TCM framework.

7.1 Implications for future research

7.1.1 Themes

The authors present seven themes (Table 11) for developing promising future research questions. Recognising that blockchain-enabled smart contracts and IoT are interdisciplinary topics, the authors have identified these across the technological-organisational-legal triad. While themes one to three (interoperability, technical characteristics, and integration with emerging technologies) correspond to the technology triad element, theme four (legal clarity) corresponds to the legal triad element. Theme five (organisational enablers) comprises research questions on the organization triad element. The concluding themes – six and seven (adoption-related studies and theoretical exploration) comprise cross-sectional questions that may be applied across any of the three triad elements.

Table 11 Future research directions
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Technology

Although the smart contract was introduced in the ‘90 s and offers unique advantages, it is still in the early stages of development [35]. The increasing number of research papers on smart contracts year-on-year points to progressive investigation into smart contracts as a research area [6]. Developments such as advanced cryptographic schemes are leading to improvements in security and privacy considerations, and new IoT-specific protocols, such as IOTA, are focussing on reducing energy consumption, aiding sustainable growth. With the development of several newer and adjacent technologies, such as artificial intelligence [173], quantum computing [10], and 5G/6G, their integration with smart contract/blockchain and the IoT offers enormous potential. In addition, several alternative blockchains exist, and they are expected to consolidate over time. Among the existing options, there are already signs of consolidation and cooperation to enable cross-platform interoperability [174]. The interoperability of smart contracts and blockchain continues to be a relatively less explored but important research area.

Legal clarity

The extant literature does not address smart contracts’ legal and regulatory considerations, specifically in context of the IoT. However, some legal considerations are addressed at the generic level of smart contracts [175]. Areas such as the impact of this new ecosystem on cross-border commerce, its (mis-)alignment with existing legal statutes, and the implications concerning consumer rights have not been fully explored. This offers a fertile area for impactful cross-disciplinary research.

Organisation

From the organisational perspective, limited inquiries into whether the current organisational structure is conducive to new-age industries involving smart contracts and the IoT exist. With this advanced technological intervention, the conduct of business can be expected to transform significantly. Therefore, organisations need to be structured to enable such an industry. Questions about whether the workforce understands (or does it need to?) this area, how can that advance businesses, whether the current structure of the organisations enables such an industry, and how can (positive) awareness be enhanced continue to be interesting exploration areas.

Cross triad

While technological, organisational, and legal dimensions could be traversed to unravel the potential of the SC-IoT combination, some streams run across all the triad components. Given the newness of the topic, adoption-related studies have not taken off. A few have already been undertaken [176, 177], but there is ample scope for furthering this initiative. Similarly, theoretical investigations into smart contracts in general have been very limited, e.g., game theory [177], given the nascent nature of this area.

7.1.2 Context

More than three-fifths of the articles demonstrated a multi-sector focus in both the foundational and current state of research. This multi-sector focus is justified since the smart contract -IoT combination is nascent. In both the foundation and current state, the articles focus on healthcare, energy, and transportation as the next three most focused sectors. As the area matures, studies should take a broader approach by moving away from multi-sector studies and address the nuances of individual sectors. Further studies should build on the groundwork laid in these three sectors and, at the same time, evaluate other sectors suitable for the application of smart contracts and the IoT.

7.1.3 Method

While reviews (38%) emerge as the most used method in foundational studies, frameworks (69%) emerge as the most popular option in the current state of research. In the current state of research, prototypes emerge as the second most used method, with reviews taking up the third position. This increased utilisation of frameworks and prototypes serves this area well, and can be interpreted as a sign of increasing maturity. Going forward, authors should focus on theory testing and building, and evaluating the usability of existing theories, as they were developed in an entirely different environment. The pace at which technological interventions are being introduced is unprecedented and calls for developing new theories. More empirical studies and case studies should also be undertaken to evaluate the efficacy of this powerful combination.

7.2 Implications for practice

Blockchain could be considered as one of the most important technological advancements since the Internet [178] that offers fundamentally transformative benefits. However, despite the hype, it is also seen by many as a yet-to-mature technology [179]. The onus is on practitioners to ensure that enterprises can grow this transformative technology, particularly around the applications of smart contracts in the IoT and other contexts, to its full potential – the current adoption levels are not commensurate with the potential. Since the adoption ratio of new technologies hundreds of years ago is believed to impact the current development levels [180], today’s technology adoption will drive the development of tomorrow. Although this combination has applicability across several industries, it has been adopted by only a few. Practitioners should focus on extending the prototypes already developed to full implementations, converting promising usage cases into prototypes, and conceiving interesting applications. Practitioners should also focus on communicating the benefits of smart contracts, given the negative press that the underlying technology has attracted. Given the lack of a critical adoption mass, practitioners could consider forming industry consortiums that help to develop common standards and, thereby drive adoption. Practitioners should also collaborate closely not only with each other but also with academia.

While our work has significant implications for practitioners and academicians, several facets of this work are useful to society. We believe our work will help improve public awareness of the SC-IoT combination. It will make the public aware of the benefits of such a powerful technological intervention and the related considerations (e.g., security, privacy, and interoperability). By highlighting the interdisciplinary nature of the SC-IoT combination, this review is also a call for action for stakeholders to collaborate to enhance its impact. Our work can be a reference point for governments, policymakers, venture capitalists, and ESG (environmental, social, and governance) proponents. The governments of different countries should collaborate to develop a unifying regulatory framework applicable to cross-border transactions. Policymakers should define policies that encourage innovative implementations of this novel technology without exposing the public to too much risk. In the current economic environment where funding is hard to come by, venture capitalists should not avoid investing in meaningful research endeavours and encouraging promising start-ups that address opportunities that can generate long-term value. Given the growing prominence of ESG considerations, ESG proponents could reference our work to ensure that the SC-IoT applications are environmentally friendly (e.g., optimise energy consumption and minimise electronic waste).

8 Limitations of this study

This paper has two primary research limitations. Firstly, blockchain, the platform on which smart contracts currently reside, is a nascent and developing technology. Although the IoT has existed for a long time, the potential benefits of its integration with smart contracts have recently picked up prominence. Consequently, the research topics and directions are yet to mature. Hence, the richness of the body of literature is limited, and as academicians explore other areas, the body of literature will mature. Secondly, the articles for this review were chosen from the Scopus database. Therefore, the compilation may have missed some relevant articles in other databases (e.g., Web of Science). Additionally, this dataset also does not include any conference publications. Since the topic is comparatively nascent, interesting concepts and developments discussed in such publications may have been omitted by this study.

9 Conclusion

Over the next few years, it is reasonable to posit that blockchain-enabled smart contracts and the IoT will transform how consumers and enterprises conduct business. Through this study, the authors have conducted a database-assisted narrative review of the SC-IoT combination and presented their findings based on the TCM framework. Based on 227 articles extracted from Scopus, the authors have profiled the existing research (authors, journals, papers, and countries), explored the intellectual foundation of the literature, reviewed the current state of research, and identified future implications for research and practice.

This area has recently spiked academia’s interest, with more than half of the articles published in 2021. IEEE-related journals emerge as the primary source of related articles, with over half of the articles being authored from China and the USA. The authors identified the fundamental roots of the literature by reviewing the references of the shortlisted articles. Decentralised data management, service orchestration through workflows, deployment challenges of BC-IoT, its usage cases, and distributed trust management comprise the underlying themes in the foundational literature. Most studies in such literature have a multi-sector focus, with a few focussing on energy, healthcare, and transportation. Most studies take the form of reviews, followed by frameworks and prototypes. The current state of research further explored the themes of BC-IoT convergence, data privacy, ecosystem security, data trading in IIoT, and specific usage cases of smart contracts. Like the foundational studies, most studies apply a multi-sector focus. Sector-focussed studies include healthcare, energy, transportation, smart homes, agriculture, and financial services. Most studies in the current state utilise frameworks and prototypes, with reviews at a distant third. Case studies, game theory, systems design, and action research have also been utilised to explore this area.

Being a relatively young area, this offers tremendous potential for further research. The authors propose seven themes across the technology-organisation-legal triad that scholars should research in future studies. Interoperability between different environments, the development of common standards, and defining authentication and security mechanisms present an interesting area of research within the technology element. Technology-related factors such as reducing energy consumption, enhancing transaction speed, scalability, efficient big data management, privacy, and security should also be thoroughly examined. The potential of blockchain to integrate with other adjacent technologies, such as artificial intelligence and cloud computing, should be examined to consider both the advantages and disadvantages. Limited studies have been undertaken in the regulatory space, and further studies should address issues around domiciling and jurisdiction, dispute resolution, consumer rights, and the applicability of existing regulatory frameworks. Through an organisational lens, studies should address how enterprises should restructure themselves to leverage this combination, apply steps to address existing skill gaps, and introduce organisational measures to contain any negative impact by bad press more effectively. Future studies should also focus on adoption-related exploration using existing adoption models, and develop new models better suited to evaluating emerging technologies. Future studies should encourage a more holistic application, testing, and development of the theoretical constructs. While existing theories should be tested and validated, this is also a call for scholars to develop new theories that align with this emerging area. As the area matures, studies should be more sector-focussed and consider nuances of specific industries – they should build on the existing studies (e.g., healthcare, energy, and transportation) and expand to other adjacent and relevant sectors. Work on developing prototypes and evaluating their performance should continue when they demonstrate the suitability of the SC-IoT to address specific gaps.

Given the nascency of the SC-IoT combination, this field will evolve rapidly, and new perspectives will continue to emerge. Hence, the authors plan to work on another study about five years from now to monitor how the technology has evolved. This future study will evaluate the body of knowledge at that point in time and help chart the new direction for research. The authors expect to leverage emerging technologies for data preparation, visualization, and analysis processes by exploring the suitability of newer techniques such as MLOps for data extraction [181], VosViewer for data visualisation, and Python for data analysis.