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Journal of Purchasing and Supply Management

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Blockchain and supply chain relations: A transaction cost theory perspective Christoph G. Schmidt, Stephan M. Wagner*

Chair of Logistics Management, Department of Management, Technology, and Economics, Swiss Federal Institute of Technology Zurich, Weinbergstrasse 56/58, 8092 Zurich, Switzerland

A R T I C L E I N F O

Keywords: Digitalization Blockchain Supply chain management Boundary conditions Transaction cost theory

Blockchain is projected to be the latest revolutionary technology and is gaining increasing attention from aca- demics and practitioners. Blockchain is essentially a distributed and immutable database that enables more efficient and transparent transactions. The consensus-based record validation can eliminate the need for a trusted intermediary. We utilize the transaction cost theory to create a better understanding of how blockchain might influence supply chain relations, specifically in terms of transaction costs and governance decisions. Conceptually developing a set of six propositions, we argue that blockchain limits opportunistic behavior, the impact of environmental and behavioral uncertainty. Blockchain reduces transaction costs, as it allows for transparent and valid transactions. We explore several areas for future research on how blockchain might shape supply chain management in the future.

1. Introduction

Blockchain is projected to be the latest transformative innovation and is increasingly gaining attention from academics, practitioners and regulators across various industries. The concept of blockchain first emerged as the underlying technology of the cryptocurrency Bitcoin, introduced by Nakamoto (2008). Blockchain is essentially a distributed, consensus-based and (mostly) immutable ledger of transaction records (Notheisen et al., 2017; Pilkington, 2016). The consensus-based vali- dation eliminates the need for a trusted third party. Since enterprises are just starting to understand the technology and explore the potential benefits and challenges, most blockchain initiatives are still in an early stage. Regardless, corporate spending on blockchain solutions is ex- pected to reach $2.1 billion by the end of 2018, up from $945 million in 2017, according to the International Data Corp. Distribution (Nash, 2018). In a recent Gartner survey, two-thirds of the respondents believe that blockchain is a business disruption and plan investments in the future (Burton and Barnes, 2017). Consequently, academic investiga- tion on how and when blockchain might create businesses value is needed.

In the media, blockchain is often called a “game changer” (Johnson, 2018). In fact, the story could be similar to the Internet. For instance, both technologies are inherently transformative, yet foundational. While the Internet was revolutionizing global information transfer, al- ternative approaches, such as Electronic Data Interchange (EDI) pro- tocols, were already widely adopted (Boyer and Olson, 2002). In

contrast to the established approaches, the Internet did provide a new layer of functionality and became accessible to and usable for everyone. Similarly, almost every company maintains a system of databases storing transactions and other firm data (Elmasri and Navathe, 2015). However, blockchain potentially adds transparency and immutability across firm boundaries to current database functionalities and may re- volutionize how we transact digital and physical goods and services, just like the Internet changed how we exchange information. While the Internet did connect people globally, blockchain might change funda- mentally how we trust on a global scale. Luhmann (1979) distinguishes two forms of trust, personal trust, as in individual but also organiza- tional relationships, in contrast to system trust. Blockchain facilitates the declaration of a true system state via networked computation and consensus rules, thus replacing the need for human intervention and personal trust, affecting the characteristics of every transactional ex- change relationship (Zhao et al., 2016). In other words, system trust replaces personal trust with a wide range of implications. The Economist (2015) even talks about “the truth machine”.

In reality, examples of successful blockchain applications are scarce. Only 8% of the 26,000 blockchain projects started in 2016 were still actively developed in 2017 (Browne, 2017). Technological uncertainty, scalability issues and development cost create major challenges. The technology seems far from reaching its ascribed potential. In 2018, blockchain shows symptoms similar to the Internet bubble, which burst in 2000. The Internet then went on to become a mainstream technology after the initial difficulties were overcome. Blockchain could follow a

https://doi.org/10.1016/j.pursup.2019.100552 Received 7 May 2018; Received in revised form 31 January 2019; Accepted 9 July 2019

* Corresponding author. E-mail address: [email protected] (S.M. Wagner).

Journal of Purchasing and Supply Management 25 (2019) 100552

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similar path (Babich and Hilary, 2019; Treiblmaier, 2018). We believe that academia and practice should join forces to take the technology through the sea of challenges to a productive stage by exploring the technology's strength and weaknesses and developing its potentials in the context of various application domains.

Blockchain might substantially affect supply chain management, its relations and governance structures (Kshetri, 2018). Blockchain also influences the purchasing and supply management (PSM) function, as global transactions are non-transparent and prone to delays, in- efficiencies and human errors (Casey and Wong, 2017; Rosenbush, 2018). Tracking goods, such as food or diamonds, through the pro- duction and delivery process to ensure quality and authenticity or au- tomated compliance to freight and trade regulations, exemplify just two promising applications of blockchain. Walmart, for example, has 1.1 million items, mostly food products, on its blockchain and traces their journey from manufacturer to retailer (Mims, 2018). Maersk, a global shipping company, cooperates with IBM and uses their blockchain cloud services to track its shipping containers, making the customs process significantly faster and more secure (Moise and Chopping, 2018). Research on the effects of blockchain on supply chain manage- ment and the PSM function is called for explicitly (Foerstl et al., 2017; Treiblmaier, 2018).

The rising interest in blockchain is part of a greater global digita- lization trend, in a business context sometimes referred to as “Industry 4.0”. Digitalization is understood as a bundle of disruptive technolo- gies, including big data analytics, machine learning, 3D printing, ro- botics and drones, which are expected to radically transform the busi- ness landscape (Vendrell-Herrero et al., 2017). Information and communication technologies have always played an important role in supply chain and PSM innovation (e.g. Akın Ateş et al., 2018; Blome et al., 2013; Wagner and Bode, 2014). The digitalization trend is al- ready influencing the supply chain. It is crucial for academia and practice to understand the impact of digitalization technologies. We focus on blockchain, as a prominent component of the digital trans- formation, and advance knowledge on supply chain relations under a digital paradigm.

In the context of the digitalization, new information and commu- nication technologies will influence supply chain structures and pro- cesses (Srai and Lorentz, 2019), as they have done in the past (Schoenherr and Speier-Pero, 2015; Waller and Fawcett, 2013). New technologies can exert disruptive power on a more fundamental level and thus drive changes in governance structures. Governance structures are at the core of any supply chain relation creating the setting for interactions between buyer and supplier and facilitating their value creation process (Fawcett et al., 2006; Gereffi et al., 2005). Shifts in governance structures pose a major challenge for firms in highly dy- namic and complex supply chain networks (e.g. Ashenbaum, 2018; Brito and Miguel, 2017; Huang and Chiu, 2018). Consequently, un- derstanding how new technologies can fundamentally change govern- ance structures in the supply chain is becoming increasingly important for academia and practice. Given its novel functionalities, blockchain holds the potential to reduce governance cost and shift the optimal governance structure under given conditions. Following the above line of argument, the objective of this article is to answer the following question:

Research question. How does blockchain affect supply chain re- lations?

As there is limited literature on the topic and rarely any mature implementations in practice, we take a conceptual approach to answer our research question. Spina et al. (2016) explicitly encourage the use of established grand theories when exploring new supply chain phe- nomena to advance theoretical maturity of the field and pave the way for the development of more specific mid-range theories. Specifically, we extend transaction cost theory, which examines business decisions on the optimal governance structure that minimizes transaction costs

under a set of conditions (Coase, 1937; Williamson, 1981), to a blockchain environment. The approach is deemed appropriate since blockchain and transaction cost theory demonstrate significant con- ceptual overlap. First, transactions and their cost are a key construct for supply chain relations (Ellram et al., 2008; Tate et al., 2011) and blockchain is most fundamentally a ledger of transactions (Notheisen et al., 2017). Second, transaction cost theory is concerned with any problem that can be posed directly or indirectly as a contracting pro- blem (Williamson, 1987) and blockchain provides a new approach to digital contracting in the form of smart contracts (Christidis and Devetsikiotis, 2016).

Blockchain does not fundamentally change or invalidate transaction cost theory. The theory is still fully applicable to supply chain gov- ernance decisions. However, the outcome of its application, the optimal governance structure, may be different with blockchain. We attempt to synthesize the characteristics of blockchain with drivers and assump- tions of the transaction cost theory in order to explore how blockchain can affect transaction costs and thus influence governance decisions. Deriving a set of six propositions, we find that blockchain can reduce transaction costs and enable more market-oriented governance struc- tures for buyer-supplier transactions. Specifically, blockchain limits opportunistic behavior, environmental and behavioral uncertainty, which drive transaction costs. Reducing costs and allowing for im- mutable and transparent transactions as well as validated records, blockchain can enable more market-oriented supply chain relations.

Our contribution to the literature is threefold. First, we are among the first to theoretically link blockchain and transaction cost theory in detail. We add to the literature by discussing the elements of transac- tion cost theory under a new technological paradigm. Second, we conceptually develop a framework of how blockchain characteristics influence transaction costs and supply chain governance. The frame- work provides a starting point to understand the blockchain phenom- enon and its implications, as the supply chain community moves to- ward building new theory. Our framework provides a reference for practitioners trying to evaluate potential applications and the useful- ness of blockchain for their organization. Third, we present an overview of critical issues deriving an agenda for future research at the inter- section of blockchain and supply chain management in general.

2. Distributed ledger technology and blockchain

Blockchain is a particular instance of the Distributed Ledger Technology (DLT) and understood as “a database architecture which enables the keeping and sharing of records in a distributed and de- centralized way, while ensuring its integrity through the use of con- sensus-based validation protocols and cryptographic signatures” (Benos et al., 2017, p. 1). Other DLT types include Hashgraphs and Directed Acyclic Graphs (DAG). Ethereum1 and Hyperledger2 are the most pro- minent active blockchain platforms in 2018. Since blockchain is a complex stack of various computational algorithms and cryptographic approaches, we will only provide a brief overview of its core design principles and elements. See Beck et al. (2016), Hilary (2018), and Notheisen et al. (2017) for more details on blockchain.

Blockchain is, in essence, a database of transactional records (Christidis and Devetsikiotis, 2016). In traditional databases, records are kept at a single location, usually within an organization. A central authority controls the database, ensures the integrity of the transactions and manages user access (Redmond and Wilson, 2012). A distributed database acts as one physical database, where all nodes (entities in a network) have equal rights (Elmasri and Navathe, 2015). Blockchain is an advanced type of distributed ledger with a set of unique qualities. First, maintaining a historical record of all valid transactions at each

1 https://www.ethereum.org/. 2 https://www.hyperledger.org/.

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node prevents any central authority from “owning” the ledger (Mainelli and Smith, 2015). Second, a decentral voting-based consensus me- chanism, most commonly a ‘Proof-of-Work’ or ‘Proof-of-Stake’ approach (Gervais et al., 2016), enables the network to self-validate incoming transactions, without a trusted intermediary (Glaser and Bezzenberger, 2015; Lustig and Nardi, 2015). The process also ensures the integrity and security of the records and manages the synchronization process between nodes. The specific difference between blockchain and other distributed ledgers is that blockchain broadcasts new transactions across the network and groups them into blocks for validation (Christidis and Devetsikiotis, 2016; Notheisen et al., 2017). Crypto- graphic hash algorithms chronologically link new blocks to the previous ones creating a chain of transaction blocks. Hence the name – Block- chain.

Different configurations of the blockchain architecture enable fun- damentally different use cases in a business context (Swanson, 2015). Two common ways of differentiating blockchain configurations exist. First, who is part of the blockchain network? In its initial con- ceptualization by Nakamoto (2008), the blockchain is permissionless. Since no prior authorization is needed, everyone is allowed to partici- pate in the network, validate and conduct transactions. In contrast, in a permissioned blockchain setting, a central entity authorizes and reg- ulates nodes and users. Second, who can access what information? The originally intended blockchain is public. A public ledger allows ev- eryone to view all recorded transactions at any time (Cachin, 2016). In a private blockchain, one entity manages and controls access to the recorded transactional data.

Blockchain also supports more advanced concepts, such as smart contracts and smart property, also known as tokenized assets (Seijas et al., 2016; Zhao et al., 2016). Smart contracts are “a computerized transaction protocol that executes the terms of a contract” (Szabo, 1997). They enable the implementation of complex business logic and might be the most transformative blockchain concept yet (Christidis and Devetsikiotis, 2016). The contract automatically self-enforces when the blockchain reaches a pre-specified state. Smart contracts can utilize external data sources. Since smart contracts are entities on the dis- tributed blockchain network, the need for a trusted authority to enforce the contract is (theoretically) eliminated (Luu et al., 2016). In general, smart contracts create a programmable and thus more dynamic and versatile type of blockchain, which can enable a plethora of new business applications.

Blockchain can record economic transactions between any kind of assets (Tapscott and Tapscott, 2016). Smart property is understood as “controlling the ownership of a property or asset via blockchain” (Crosby et al., 2016, p. 8). In addition to digital assets and information, digital representations of real-world physical goods, linked to uniquely identifying serial numbers, bar codes, sensors or RFID chips, can be created and recorded (Christidis and Devetsikiotis, 2016; Glaser and Bezzenberger, 2015). The process of creating a ‘digital twin’ of a phy- sical good on a blockchain is called tokenization. Users can exchange the ownership of these digital representations, or tokens, in blockchain.

In summary, the novel and specific functionalities and character- istics of blockchain create a plethora of potential advantages but also pose many new challenges for organizations and supply chains. Table 1 summarizes the technology's key advantages and challenges that will inform our propositions and framework development. Blockchain holds permanent and tamperproof records, enables transactions in an en- vironment without personal trust between the involved parties, and fosters transparency and data sharing. However, there are significant drawbacks. First, blockchain requires all participants to share in- formation on transactions (at least to a certain degree), even in private blockchain configurations. Many firms might have a strong interest to keep this kind of data private, even forfeiting smaller efficiency gains. Second, blockchain is a database (Babich and Hilary, 2019). While blockchain mechanisms can verify and validate transactions, once in- formation or tokenized assets are registered on the blockchain,

verifying the authenticity and quality of input data is the critical step. In other words, the initial link between the real world and blockchain poses the most prominent security challenge. Blockchain provides no protection against intentionally manipulated input data, even stemming from sensors or RFID tags. Third, blockchain only creates value for its participants given sufficient diffusion of the technology to create net- work effects. The network effect states that the more entities partici- pate, the more valuable a system is. Finally, blockchain is not an es- tablished technology yet. New DLTs with unique qualities are developed constantly and existing ones are extended. Committing to, investing in, or even implementing technologies in such an early stage is very risky for organizations. When technological maturity increases, adoption is expected to increase as well.

3. Blockchain and transactions

3.1. Transaction cost theory

Transaction cost theory is concerned with the optimal governance structure to minimize total cost under certain exogenous conditions regarding the nature of the transaction (Coase, 1937; Geyskens et al., 2006; Williamson, 1975). The theory is well-established within opera- tions and supply chain management (Grover and Malhotra, 2003; Ketchen and Hult, 2007) and purchasing and supply management (Arnold, 2000; Ellram et al., 2008). Prior studies examine, for example, decisions on outsourcing and vertical integration (Bals and Turkulainen, 2017; Gulbrandsen et al., 2009; McIvor, 2009), IT pro- curement (Ruth et al., 2015; Wynstra et al., 2018), and public-private partnerships (Parker and Hartley, 2003). Wynstra et al. (2018), for example, utilize transaction cost theory in IT procurement to examine the difference between transactions involving only goods and those including additional services. They confirm the assumption that ser- vices induce more uncertainty and thus generate extra costs to mitigate this uncertainty throughout the procurement process. Marshall et al. (2007) challenge multiple governance propositions of the transaction cost theory, as they find collaborative relationships to increase perfor- mance in the context of outsourcing telecommunication services.

The transaction is the theory's unit of analysis and understood as an exchange of information, goods or services between subsequent stages of a production process (Williamson, 1975, 1985). For example, a transaction is any exchange between value-adding stages within a firm, but also any purchase made by a buyer from its supplier (Williamson, 1985). The constant need to gather and process information, draft and (re-)negotiate contracts and arrangements, monitor and enforce agreements, and manage and maintain relationships generates trans- action costs (Dyer, 1997; Rindfleisch and Heide, 1997). In this section, we briefly introduce the theory's key assumptions, constructs, and prescriptions related to our research question, as illustrated in Fig. 1. See Grover and Malhotra (2003) and Rindfleisch and Heide (1997) for a detailed overview of the transaction cost theory and its empirical evi- dence.

Two key assumptions about human behavior are fundamental to transaction cost theory: bounded rationality and opportunism (Williamson, 1975). First, bounded rationality, introduced by Simon (1972), takes cognitive restrictions into consideration when conducting human behavior. An individual might want to act rationally, but the inability to process all available information limits the rationality of a decision (Grover and Malhotra, 2003). Even though bounded ration- ality is a natural phenomenon, transaction cost theory ensures a pro- blem in conjunction with high uncertainty (Williamson, 1981). Under such conditions, it is impossible to consider all contingencies sur- rounding a future exchange. Second, opportunism denotes the risk that the other party seeks primarily self-interest. Opportunistic behavior includes withholding information, cheating or any other form of con- tract violation (Gulbrandsen et al., 2009; Morgan et al., 2007).

Three key constructs within transaction cost theory directly

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influence the transaction costs of an economic exchange: asset specific investments, transaction characteristics and uncertainty (Williamson, 1975, 1987). First, asset specific investments (relationship-specific in- vestments) have little to no value outside of that specific exchange re- lationship (Ellram et al., 2008; Rindfleisch and Heide, 1997). Williamson (1975) mentions site, physical and human asset specificity, among others. Second, transaction characteristics mainly include the frequency and volume of a transaction. These are often neglected in empirical studies on transaction costs (Rindfleisch and Heide, 1997). Third, uncertainty refers to “unanticipated changes in circumstances surrounding a transaction” (Grover and Malhotra, 2003, p. 460). Transaction cost theory considers two forms of uncertainty to drive costs. Environmental uncertainty, due to potential regulatory, political or economic changes, increases the difficulty to draft sufficient agree- ments prior to an exchange (Holcomb and Hitt, 2007; Ireland and Webb, 2007). Behavioral uncertainty occurs if one party's performance after a transaction is difficult to measure, often due to implicitly or explicitly generated information asymmetry.

Transaction cost theory prescribes governance structures to minimize costs under given exogenous conditions. Governance is about co- ordinating the flow of materials and services throughout the value creation process (Grover and Malhotra, 2003). The original framework focuses on the choice between market and firm (hierarchical) governance (Williamson, 1975, 1981). Geyskens et al. (2006, p. 521) understand the firm as a governance structure “based on enforcement by means of le- gitimate authority, either through an employment relation or a con- tractual arrangement that provides decision-making authority.” The

market is an environment of competitive forces, where the principles of supply and demand determine the flow of goods and services (Grover and Malhotra, 2003). As the global economy changes and managers in- creasingly engage in collaborative partnerships, relational governance structures (alliances) are also integrated into the transaction cost fra- mework (Dyer, 1997; Geyskens et al., 2006). Subsequent theoretical extensions conceptualize a diverse and complex spectrum of governance mechanisms between the market and the firm, such as joint ventures or R&D partnerships (Ellram et al., 2008). We will only focus on the main governance structures due to the conceptual nature of this study.

Three distinct transaction governance problems originate from the transaction cost theory (Rindfleisch and Heide, 1997). Specifically, organizations have to solve the safeguarding, performance measure- ment and adaptation problem by selecting an appropriate governance structure (Geyskens et al., 2006). These conceptual problems will guide our theoretical exploration for the remainder of this section, as each of them uniquely informs the question of how blockchain potentially af- fects governance decisions in supply chain relations.

3.2. Safeguarding

The safeguarding problem arises when one party of a transaction has to invest in specific assets that have little to no value outside that one particular relationship (Williamson, 1975). Common examples include specialized production equipment, or unique sustainability requirements (Touboulic and Walker, 2015). The substantial investments create a ‘locked in’ state for both parties in a buyer-supplier relationship with a high degree of mutual dependence. On the one hand, the specificity of assets and the associated costs limit a buyer's ability to switch suppliers (Ellram et al., 2008; Grover and Malhotra, 2003). On the other hand, the supplier has to rely on transactions with that buyer to turn up-front in- vestments into profit. The resulting situation referred to as ‘small num- bers bargaining’, invites the exploitation of dependencies. Literature suggests that long-term buyer-supplier relationships build trust (Cao and Zhang, 2011; Wagner and Bode, 2014), ideally to prevent opportunistic behavior (Handfield and Bechtel, 2002; Ireland and Webb, 2007; Özer et al., 2014). However, trust is hard to achieve and easy to breach. Power asymmetry and dependence allow for heavy supplier squeezing that can even lead to supplier bankruptcy (Schleper et al., 2017). Setting up safeguarding mechanisms generates substantial governance costs.

Consider an example with high power asymmetry. Small farmer co- operatives in Indonesia depend on selling their crops to big corpora- tions. Buyers often leverage their power and informational advantage to dictate prices and exploit suppliers. The current paper-based system fosters lying, graft and corruption due to a lack of access to market price information and limits the farmer's safeguarding options. The app AgUnity3 makes twofold use of blockchain and its inherent character- istics to limit opportunistic behavior. First, information provision, as

Table 1 Blockchain advantages and challenges.

Advantages Description

Permanent Blockchain always holds the entire transaction history (differs in other DLTs). Every transaction, once verified, is always retraceable. Immutable Transactions on the blockchain cannot be tampered with, once the network has validated them. Trust Transactions can be conducted without personal trust between the parties, as blockchain provides consensus mechanisms to establish a valid state of truth. Transparent Every participant on the blockchain network can access and view all previous transactions (in a permissionless setting).

Challenges Description

Privacy Blockchain requires every participant to share information on transactions (at least to a certain degree), even in private configurations. Data quality Blockchain is essentially a database and its value is highly dependent on the quality of input data. Network effect Blockchain only creates value for participants given sufficient diffusion of the technology. Uncertainty The technology has not reached a mature state yet and technological uncertainty is high.

Fig. 1. The transaction cost theory framework (boxes depict key constructs, ovals illustrate assumptions).

3 http://www.agunity.com/.

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the app delivers transparent information on market prices and past transactions to smaller farmers. Second, blockchain eliminates the need for personal trust among the involved parties (Beck et al., 2016; Cachin, 2016). The network itself takes on the role of a trusted third party that validates transactions and suggests prices. AgUnity suggests prices and both parties have to agree to the set price mutually to confirm the transaction. The example illustrates how system (computational) trust in a formal tamperproof system replaces personal (relational) trust, which inherently is exposed to exploitation (Lustig and Nardi, 2015; Luhmann, 1979).

However, the example also implies a critical issue with blockchain. In order to generate any effects, everyone is required to participate in the network. Blockchain adoption, especially the “when” and “how”, is a prominent topic in academia and practice. How can we incentivize firms that intend to behave opportunistically to be part of a blockchain? In our example, why should the buyer care? Creating an environment where trust is in the system and its process scares away those that benefit from power asymmetries and breaking trust. While we ac- knowledge the importance of the issue, we do not have an answer. Depending on the context, the government and other policymakers might need to take action. The current lack of incentive systems illus- trates the complexities of blockchain.

In general, blockchain can prevent direct misbehavior and at least deteriorate elaborate forms of opportunistic behavior. Blockchain cre- ates a (mostly) tamperproof and permanent record of past transactions, thus making misbehavior visible and traceable. A verified audit trail of past behaviors may even be legally enforceable (Cachin, 2016). Con- sequently, the thread of exposure might prevent at least the more ob- vious ways of theft, fraud, or manipulation, since hiding in sloppy processes and incomplete paper trails is eliminated (Mims, 2018). In addition, smart contracts can limit opportunistic behavior, as the smart contract can determine exchange parameters and enforce its execution (Lu and Weng, 2018). For instance, a smart contract can set prices under dynamic conditions negating any pressure by the power party. In summary, blockchain might create system trust and prevent opportu- nistic behavior to a certain extent. Drawing from the above discussion, we propose:

Proposition 1. Blockchain limits opportunistic behavior in transactional relationships.

Given high asset specificity, transaction cost theory suggests an in- house governance solution, where the firm undertakes the investments. The costs of safeguarding against opportunistic behavior, such as unfair pricing, and dependency issues do not justify a market solution (Williamson, 1987). Firms frequently employ a relational governance structure and rely on personal trust, risk sharing and mutual interests as safeguarding mechanisms (David and Han, 2004; Geyskens et al., 2006).

Consider 3D printing, the most common form of additive manu- facturing, as an example. Sizeable investments in required production equipment on an industrial scale are a high specificity asset (Durach et al., 2017; Wagner and Walton, 2016). In the aerospace industry, for example, suppliers might be pressured to deliver low volume spare parts with minimal lead-time (Attaran, 2017). Suppliers undertake substantial additive manufacturing investments catering to major buyers. Dependency creates related vulnerabilities for the supplier. Several platform providers, like the Genesis of Things project,4 aim at connecting firms and independent printing providers (Blechschmidt and Stöcker, 2017). The resulting spot-markets allow firms to discover quickly suitable business partners and partially avoid the high de- pendency on major buyers. Genesis of Things envisions a distributed, shared factory system enabling firms to shift production capacity ac- cording to market demand (Durach et al., 2017; Wagner and Walton,

2016). The more efficient capacity utilization allows for faster invest- ment amortization. Overall, blockchain can facilitate the creation of ad hoc markets, without the need for a trusted relationship, reducing the associated risks of investing in highly specific assets. A shared factory system might also reduce safeguarding cost. As illustrated, blockchain might foster more market-oriented governance structures for supply chain relations. Specifically, it might change how PSM professionals purchase goods and services depending on asset specificity.

However, one of the major challenges of blockchain adoption is the lack of standardization (Babich and Hilary, 2019). Beyond general implications for blockchain adoption, early spot markets would likely form on an industry level (Durach et al., 2017). In practice, many firms, such as 3D printing providers, are likely part of multiple blockchain systems. It is unclear how this might affect an organization and their technological infrastructure, but we expect added governance cost due to the lack of standardization and thus interoperability. Being part of multiple supply chains might ensue additional concerns about data privacy. Blockchain based production systems need to reach a critical mass of participants, both buyers and suppliers, in order to generate value. We anticipate high expenses associated with promoting network participation. The future will decide how these developments affect governance cost.

In general, blockchain reduces the prevailing risk of opportunistic behavior in exchange relationships. The safeguarding problem is characterized uniquely by high levels of power asymmetry and de- pendency. Power asymmetries are always a challenge in every supply chain relationship (Brito and Miguel, 2017; Wagner and Bode, 2014). While the technology can theoretically prevent opportunistic behavior to a certain degree, safeguarding mechanisms will always be needed in such extreme situations. We believe that the appropriate range of governance structures from internal solutions to relational governance relying on long-term trust will not significantly change with blockchain.

3.3. Performance measurement

The performance measurement problem is a result of behavioral uncertainty due to one party's inability to evaluate performance during a transaction (Geyskens et al., 2006). Information asymmetry arises, since “there is public information available to all parties but also pri- vate information which is only available to selected parties, meaning that all parties to the transaction no longer possess the same levels of information” (Hobbs, 1996, p. 18). Especially under the assumption of opportunism, information asymmetry poses a critical issue in any buyer-supplier relationship (David and Han, 2004; Ireland and Webb, 2007). Information asymmetry can lead to ex ante or ex post opportu- nistic behavior (Hobbs, 1996; Rindfleisch and Heide, 1997).

Ex ante, firms withhold information and influence transaction parameters to their advantage (Ireland and Webb, 2007). Using blockchain, entering a transaction relationship requires a firm to share the same information as all other participants. This provides a way of equalizing initial information levels at the start of a transactional re- lationship. The available record of past actions enables suppliers as well as buyers to signal credibility and quality to prospective business partners (Babich and Hilary, 2019). Firm reputation is an important decision factor for engagement in long-term transaction agreements. The firm's behavior in past exchange relationships is transparent to potential partners. Negative reputation has negative effects on firm performance and future exchange relationships (Lienland et al., 2013; Touboulic and Walker, 2015). Signals can reduce governance cost of vetting and selecting appropriate supply chain partners.

Ex post opportunism is characterized by a firm hiding its true actions throughout the transaction process (Carter and Hodgson, 2006; Hobbs, 1996). For example, a firm could deliberately withhold information about their quality management procedures to avoid responsibility and blame for faulty consumer goods. Given sufficient blockchain depth4 http://www.genesisofthings.com/.

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including, for example, manufacturing processes, the permanent and immutable system records a trail of all activities related to the trans- action (Notheisen et al., 2017). The data eliminates information asymmetry after the transaction and provides a solid base for perfor- mance evaluation, benchmarking and auditing. Given a fully public infrastructure, even the consumer can potentially retrace the firm's actions, providing a completely new level of product and service transparency.

In practice, product provenance is the most prominent blockchain use case. The food supply chain is especially vulnerable to hidden in- formation, as food adulteration is rising with potential implications for consumer health and safety (Nash, 2016). For example, Walmart has entered a consortium with IBM and traces their food's journey from farm to retailer using blockchain (Mims, 2018), most prominently mangos and Chinese pork (Nash, 2016). Other industry solutions exist for authenticating the origin of coffee or ensuring the cool chain for fish.5 These solutions could prevent food waste and provide customers with fresher food. Outside the food industry, Everledger6 has recorded the provenance of over 2 million diamonds using blockchain, pre- venting fraud and counterfeit diamonds. Counterfeit pharmaceuticals also pose risks for customers and society that could be alleviated par- tially by blockchain networks (Wall, 2016). Transparent product pro- venance can prevent fraud and counterfeit and thus save costs related to controlling and monitoring current and potential suppliers and ensuring product or service quality.

The provenance use case also illustrates a major weakness of blockchain. As discussed in Section 2, blockchain is in its core a data- base and not designed to govern data acquisition (Babich and Hilary, 2019). Transferring real-world data onto the blockchain is the most critical security challenge, with no sufficient solution in sight. Even seemingly secure input data stemming from sensors or RFID tags can easily be manipulated prior to their validation on the network. The fundamental problem might even foster a new business model. Firms, such as ChainLink,7 provide reliable input data. Alternatively, asserting initial data can be part of the blockchain provider's business model, as is the case with Everledger, who initially scan and verify every diamond manually before its data is stored on the blockchain. While blockchain offers a range of benefits to the performance measurement problem, opportunistic behavior persists at the earliest stages of data input, po- tentially adding unforeseen governance cost. The need for safeguarding might just shift within the process, and it is hard to foresee the tradeoff in governance costs.

In a special case, performance is just inherently difficult to assess (Tate et al., 2011; Williamson, 1987). Consider highly specific niche products, where assessing product quality involves specialist knowl- edge that the buyer may not possess and is very costly to acquire. While blockchain does not change the issue at hand, the data is easily avail- able to external experts, which potentially reduces auditing costs. Further, the programmability of blockchain may even enable “auto- mated quality control” and performance evaluations based on machine learning tools. Overall, we believe the potentials outweigh drawbacks and current uncertainties. Drawing from the above discussion, we propose:

Proposition 2. Blockchain reduces behavioral uncertainty in transactional relationships.

3.4. Adaptation

The adaptation problem originates from the difficulty to draft complete agreements under conditions of high environmental

uncertainty. Main sources of uncertainty in the business environment include supply, demand, technologies, regulations and economic shifts (David and Han, 2004; Williamson, 1981). In a long-term exchange relationship, the terms and conditions for ongoing exchanges are more difficult to negotiate when, for instance, supply and demand parameters are largely unknown. Decision makers cannot anticipate all possible scenarios, especially given their bounded rationality. The exchange agreements thus always render incomplete (Grover and Malhotra, 2003; Simon, 1972). Continuously renegotiating and adapting the conditions for a series of transactions generates additional costs (Grover and Malhotra, 2003).

Prior studies find that information sharing and transparency reduces the impact of uncertainty in the supply chain (Foerstl et al., 2018; Wagner and Bode, 2008). Blockchain creates transparency in providing reliable real-time and historical data and facilitating secure corporate data warehousing (Crosby et al., 2016; Korpela et al., 2017). While there will always be uncertainty in the business environment, block- chain supports the firm, for example, to minimize supply and demand related uncertainties in two ways. First, internal transparency improves, as the state of the firm and its operations, for example regarding in- ventory and production processes, becomes fully accessible. Block- chain, in turn, facilitates better decision-making. Operational efficiency increases and frees up resources that can be used to soften the effects of supply and demand variance. Process optimization facilitates supply chain flexibility, which mitigates the consequences of uncertainties (Christopher and Lee, 2004; Tang and Tomlin, 2016). Improved in- ternal monitoring and control capabilities may eradicate the impact of uncertainties with internal causes.

Second, blockchain potentially improves transparency along the supply chain, since it enhances information sharing between business partners and creates supply chain visibility beyond Tier 1 (e.g. Wilhelm et al., 2016). Improved data exchange facilitates a more efficient flow of goods and services, finances and information. Babich and Hilary (2019) specifically elaborate on the Bullwhip effect, as a traditional problem in supply chains. Data analytics capabilities and transparent information enhance a firm's forecasting and planning functions. Big data and ma- chine learning approaches paired with smart contracts are able to de- termine optimal parameters with speed and accuracy (Carbonneau et al., 2008). Parameters, such as order quantity or price, could be processed autonomously to save time and money (Christidis and Devetsikiotis, 2016). Information aggregation and automated measures can certainly reduce the impact of supply and demand uncertainty.

Similar forms of information sharing were already possible using EDI based systems. What contingencies render the blockchain solution superior? Traditionally, some of this data can be shared through the EDI systems commonly used in the supply chain industry but these systems are inflexible, complex, and cannot share data in real-time, as IBM puts it (PRNewswire, 2016). Companies still regularly share documents via email attachment, fax and courier. Blockchain can track critical data about every shipment in a supply chain and offers an immutable record among all parties involved.

However, we imagine a crucial trade-off between data sharing on blockchain and corporate data privacy. For example, blockchain's po- tential to reduce the Bullwhip effect depends on all participants equally sharing information on transactions. As Babich and Hilary (2019) argue, both buyers and suppliers might have a strong interest to keep some transactional data private, even when forfeiting smaller monetary gains. When is it beneficial for both buyer and supplier to share in- formation?. Despite some strong counterarguments, we propose:

Proposition 3. Blockchain reduces the impact of environmental uncertainty in transactional relationships.

Transaction cost theory prescribes that the firm should govern transactions under high levels of environmental uncertainty internally to avoid adaption and renegotiation costs (Carter and Hodgson, 2006; David and Han, 2004). Information sharing and transparency in supply

5 https://sawtooth.hyperledger.org/examples/seafood.html. 6 https://www.everledger.io/. 7 https://chain.link/.

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chain relationships are the preferred measures to reduce uncertainty and decrease coordination efforts and costs (Brito and Miguel, 2017; Huang and Chiu, 2018). Blockchain can improve those capabilities and provide additional functionalities to reduce the influence of an un- certain business environment. Blockchain can help reduce costs asso- ciated with transacting in an uncertain environment. The firm can benefit from the advantages without building a long-term relationship since blockchain directly facilitates contractual flexibility and trans- parency. In addition, the advantages of blockchain require minimal setup cost compared to engaging in traditional long-term supply chain partnerships.

In August 2019, Maersk and IBM announced TradeLens,8 a blockchain based global trade platform with over 90 initial partici- pants, including port and terminal operators, carriers, cargo owners, freight forwarders and other logistics companies (PRNewswire, 2016). The platform facilitates spot markets and thus more market-oriented governance structures, as coordination and initiation cost shrink. As one proclaimed goal of the long-term collaboration between Maersk and IBM was to digitize and streamline customs processing, customs authorities are also included on the TradeLens platform. Data ag- gregated on the blockchain, including sensor and RFID data, facilitates an automated and efficient real-time customs process (Groenfeldt, 2017).

In terms of regulatory uncertainty, blockchain can enforce the ad- herence to standards and regulations, either within the validation me- chanism, where “illegal” transactions could be detected and rendered void, or using smart contracts, which would be designed to comply with rules and regulations. For example, if an exchange parameter were subject to new regulations, the blockchain network could update all the smart contracts to comply with new rules automatically. This would mean a system-wide adoption, but without everyone having to sign off on it. Enhanced transparency potentially eases compliance with new regulations in general.

We conclude that exchange partnerships with high uncertainty can become more ad-hoc, as the impact of supply, demand or regulatory uncertainty partially is reduced, and thus propose:

Proposition 4. Blockchain enables more market-oriented governance structures for transactions under high environmental uncertainty.

3.5. Framework of blockchain impact areas

In summary, we conceptually develop a set of propositions on how blockchain might affect governance costs and structures in supply chain relations. We discuss benefits and drawbacks using practical examples and illustrate some of the trade-offs that firms have to be aware of when engaging with blockchain. Fig. 2 illustrates our findings in the context of transaction cost theory. Specifically, we find that blockchain can reduce the impact of opportunistic behavior in situations of both high dependency, for example, due to relationship-specific investments, and behavioral uncertainty, for example in situations where actions and performance of an exchange partner are hard to measure or benchmark. Automated decision-making facilitated by smart contracts can reduce the impact of bounded rationality on transactions. Blockchain provides a permanent and immutable database that might substantially reduce environmental uncertainty, as information sharing is efficient without a long-term relationship.

We explore how blockchain potentially influences the various types of transaction costs that occur in supply chain relations. In summary, we see potential for the technology to reduce transactional complexity, information asymmetry and contractual incompleteness. Supply chain risks decrease due to traceability and openness of transaction and agreement records. The technology reduces costs for gathering and

processing information, drafting and negotiating contracts, monitoring and enforcing agreements, and managing relationships, allowing for more market-based governance structures under certain circumstances. We synthesize our previously developed propositions on a more general level:

Proposition 5. Blockchain reduces transaction costs.

Proposition 6. Blockchain influences governance cost and structure.

4. Future research opportunities

As this article intends to stimulate diverse academic discussion, we widen our scope and go beyond structural implications of blockchain on firm transaction boundaries, as discussed within transaction cost theory, to outline future research opportunities for blockchain in PSM and supply chain management in general.

Due to the early stage of the technology, the respective body of knowledge is just starting to emerge. We thus adopt the generalized scientific theory-building process (Handfield and Melnyk, 1998; Wallace, 1971) to derive an agenda for future research on blockchain in supply chain management. We propose the necessity of both ex- ploratory and explanatory studies to advance the literature. On the one hand, exploratory studies aim to fully outline and understand the blockchain phenomenon and identify relevant characteristics and con- structs. On the other hand, the goal of explanatory studies is to struc- ture relationships, infer causality, and empirically validate and extend mid-range and grand theories. Both approaches complement each other and facilitate theory building in the field.

4.1. Exploratory studies

Since high levels of uncertainty surround the technology and its impact on PSM and supply chain management, exploratory studies provide an appropriate approach to advance the field and initiate an academic discourse. Exploratory studies aim to discover and describe the specific phenomena that arise from blockchain in supply chain management. Building on these findings, researchers build towards a common understanding of blockchain and identify key variables and relationships.

4.1.1. Observing the phenomenon As a premise for any research, early works should create awareness

of and interest in a new phenomenon, problem or event, and justify its examination. Interesting situations and cases should be reported ade- quately for further inquiry, commonly as the development of taxo- nomies or typologies (Handfield and Melnyk, 1998; Wallace, 1971). This step is “concerned with information gathering and identifying key issues” (Handfield and Melnyk, 1998, p. 327). What use cases of blockchain in supply chain management exist? What are the char- acteristics of those? What are the key issues that arise in practice? Several research methods provide valuable insights into these ques- tions, including in-depth case studies, long-term fieldwork, or docu- ment analysis.

However, given the lack of data due to the novelty of the block- chain phenomenon and in line with a call for the application of in- novative research methods (Knight et al., 2016) we propose a design science approach to discover blockchain in supply chain manage- ment. Design science is a practical problem-solving research approach revolving around the development of solution design in the form of an artifact (Gregor and Hevner, 2013; Simon, 1996). In case empirical data is not available on the topic, these artifacts can then become the subject of traditional empirical research (March and Storey, 2008). The design science approach seems especially appropriate to study blockchain. First, operations and supply chain management is a highly practical field (Carter et al., 2015; Holmström et al., 2009).8 https://www.tradelens.com/.

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Design science creates a bridge between practice and theory and al- lows researchers to not only observe but also shape a new phenom- enon or changing boundary conditions. Second, design science is especially prominent in the information systems discipline to deal with high levels of technological uncertainty (Gregor and Hevner, 2013). In general, blockchain is a prime candidate for the creation of functional socio-technological artifacts to explore what the tech- nology could actually accomplish, how firms might use it efficiently, and what the key issues might be. Table 2 summarizes some of the more technical uncertainties suitable for design science research in the early discovery and description phase.

The focus of such research should be on fundamental issues re- garding the technology's functional capabilities as well as the feasibility of certain use cases and applications. New forms of DLT are constantly emerging. To create a solid knowledge foundation for academic dis- course, researchers need to understand different types of DLT and ex- amine their advantages and drawbacks. Hashgraphs and DAGs present viable alternatives to blockchain, but are largely ignored in research. For example, Hedra Hashgraph9 and Swirlds10 are maybe the most prominent Hashgraph based platform providers serving a variety of use

cases. IOTA11 and Fantom12 use a DAG approach to solve inherent technical issues of blockchain, such as scalability, while also offering smart contracts (Natoli and Gramoli, 2017). Thus, many opportunities for future research on other related technologies and their comparison to blockchain arise from the diverse landscape of products and provi- ders.

Even within the blockchain universe, multiple platforms, including Ethereum and Hyperledger, offer different features. How are decision makers affected? What conditions and contingencies might be im- portant? Given the rapid developments, design science can help identify the best technological solutions for practical issues faced by firms. Thereby, the research community creates knowledge on the technology itself as well as its application. We explicitly encourage inter- disciplinary research on this contemporary topic (Sanders and Wagner, 2011) where researchers from computer science and management in- teract.

Design science facilitates research on the firm, but more importantly also on the supply chain or supply network level. The value of block- chain for every organization is dependent on the network of partici- pants (Kshetri, 2018). Blockchain networks follow different archetypes,

Fig. 2. Framework of potential blockchain implications.

Table 2 Opportunities for design science research.

Uncertainty Research questions

DLT and other technologies • What alternative DLT approaches are being developed? • What alternative database/data transfer systems are available? • How do they compare to blockchain? • What are the specific areas of application for blockchain? When can the technology actually deliver value?

Blockchain design • What are the different technical design approaches to blockchain? What are the specific characteristics of each type? • Which blockchain implementations benefit specific use cases?

Blockchain network • What forms of blockchain networks, such as public, private, or consortia, exist? • Who initiates the formation of a blockchain? • What is the role of external (technology) service providers?

9 https://www.hedera.com/. 10 https://www.swirlds.com/.

11 https://www.iota.org/. 12 https://fantom.foundation/.

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such as public, private, consortia-driven, industry-level and many others. Either one firm, a consortium, or an external provider can maintain the blockchain infrastructure. For example, Maersk's global supply chain platform was developed and is maintained by IBM, which serve as an IT service provider. Design science would serve as a tool to structure blockchain configurations and their application domains. Valuable insights on how network configuration influences firms' be- havior in different networks could be derived.

4.1.2. Understanding the phenomenon Building on the prior explorative description of a new phenomenon,

problem or event, Handfield and Melnyk (1998) suggest a mapping step to identify the key variables and issues characterizing the phenomenon. Observations become understanding. Structures, concepts and re- lationships only play a minor role during the mapping phase (Holmström et al., 2009). The focus is on deriving factors associated with the phenomenon, without explaining (the ‘why?’). Systematic generalization of prior observations and subsequent factor extraction can facilitate the theory-testing phase and improve the quality of pro- posed theoretical explanations and relationships.

Qualitative empirical research utilizing case study approaches seems an appropriate method for the nascent blockchain technology (Eisenhardt and Graebner, 2007). Content analysis utilizing firm documents are another potentially insightful research approach. Table 3 summarizes a non-exhaustive list of potential high-level factors. We will describe some of the factors mentioned in more detail below.

Industry characteristics are an important factor regarding supply chain management (e.g. Lienland et al., 2013; Marshall et al., 2007). For example, healthcare portraits a prime candidate for blockchain disruption. Healthcare is dealing with sensitive data and the tracking and immutable storing of patient data and physician activities on blockchain would replace the redundant, incomplete and partially in- accessible paper records (Ekblaw et al., 2016). Attention to the poten- tial benefits of blockchain in the future is rising, as, for instance, Wal- mart won a patent for storing patient records on blockchain.13

MedicalChain14 and MedRec15 both use blockchain to store patient health records and manage access by doctors, hospitals, pharmacists and insurance companies. Health records present a multi-stakeholder scenario with diverse interests. Researchers might investigate how this kind of setting influences the formation and success of the blockchain application. How to incentivize the participation of a diverse set of stakeholders? How can any involved party appropriate adequate value? Who is organizing and maintaining the system?

Pharmaceuticals present a good starting point for exploring block- chain's ability to establish provenance in the context of fraud and counterfeit products. Consider Heparin, a widely used blood thinner, as one of the countless examples. In 2008, a counterfeit version of the drug hit the market. The active ingredient was substituted to save production cost, causing unexpected complications with patients resulting in many deaths (Toscano, 2011). The drug supply chain is global and complex and has many entry points for fake products and components. In No- vember 2018, the Drug Supply Chain Security Act (DSCSA) takes effect enforcing every drug batch to be uniquely identifiable, for example using bar codes. The new requirement provides the perfect starting point for recording the movement of every batch on blockchain, creating a valid chain of custody. The information would even be ac- cessible by auditing firms, institutions or customers. Currently, several consortia are pondering the implications of the technology. For ex- ample, the Innovative Medicines Initiative (IMI) is planning a sub- stantial health blockchain project.16 Several blockchain initiatives al- ready aim to comply with DSCSA while preventing counterfeit drugs, such as MediLedger.17 Supply chain compliance, regarding tempera- ture, or humidity, is another issue in the pharma industry that provides multiple research perspectives on the use of IoT devices to track ex- ternal factors across the product life-cycle and smart contracts pro- viding automated detection of critical situations (Leising, 2018).

4.2. Explanatory studies

As the technology matures, more opportunities for theory building and testing will arise. Theories can widely differ in their scope (Spina et al., 2016; Swamidass, 1991). The development of a field of study or research phenomenon is driven mainly by mid-range and grand the- ories. Mid-range theories utilize constructs and relationships estab- lished in the mapping phase to derive frameworks explaining and predicting a new phenomenon in the field (Astbury and Leeuw, 2010). Grand theories, sometimes called unified theories, were developed in mature disciplines, such as management or economics (Astbury and Leeuw, 2010; Spina et al., 2016). They resolve conflicts within and unify multiple mid-range theories, and organize emerging knowledge into a bigger picture (Carter et al., 2015; Swamidass, 1991). A high level of abstraction in its constructs and relationships characterizes grand theories and enables the application in a variety of research disciplines. To develop the field of supply chain management under a blockchain paradigm, we suggest both the development of new and adaption of existing mid-range theories.

Table 3 Opportunities for factor identification.

Factor Research questions

Industry • Who are the early adopters of blockchain? • How does industry influence blockchain initiative success? • How are industry characteristics influencing blockchain design? • What are the implications of service vs. manufacturing firms?

Environment • How does country and cultural context affect blockchain success? • How do local or regional regulations affect blockchain projects? • Under what circumstances are governmental institutions and industry associations engaging with blockchain?

Relationships and networks • Under what conditions are some types of network formation advantageous? • Under what circumstances are firms joining up to explore blockchain? • How are traditional factors, such as power and dependence, affecting blockchain project success? • Is there a difference between upstream and downstream firms?

Organization • What is the effect of firm characteristics, including size, growth and age? • What is the difference between B2B and B2C oriented organizations in terms of blockchain adoption and project success? • What are the characteristics of early adopters?

13 http://fortune.com/2018/06/22/walmart-blockchain-patent-health- records/.

14 https://medicalchain.com/. 15 https://medrec.media.mit.edu/.

16 https://www.imi.europa.eu/. 17 https://www.mediledger.com/.

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4.2.1. Building mid-range theory Blockchain in supply chain management can be studied using a

variety of perspectives, and methods to develop new and adapt existing mid-range theories. Blockchain is Digitalization in general and block- chain in particular constitute a new boundary condition that might facilitate new frameworks and concepts for new business models, or- ganizational forms or governance structures, and alter the common theory predictions (Busse et al., 2017; Holmström et al., 2019). We outline exemplary areas of research on blockchain in supply chain management. Table 4 provides a more detailed overview of research areas and questions.

First, given the novelty of blockchain applications in the supply chain, we specifically suggest that future studies start with examining barriers and success factors in the technology adoption process. We suggest considering the following important aspects. One important milestone of blockchain adoption is reaching the critical mass for the network effect, stating that the more entities participate, the more va- luable a system is. Especially at this early stage of the technology, it is hard to derive any actual value. The ongoing adoption and diffusion process further creates the need for policies, standards and processes regarding the use of blockchain, moving towards technological in- stitutionalization (DiMaggio and Powell, 1991). Smart contracts pro- voke unknown legal implications regarding the real-world validity of such contracts. The lack of legal certainty and regulations may detain many firms from transacting on blockchain.

To study the process of technology adoption and diffusion, several theoretical approaches promise interesting insights. The technology acceptance model (TAM), first introduced by Davis (1985), centers around the perceived ease of use and the perceived usefulness of the technology to explain user acceptance and thus adoption behavior of new technologies (e.g. Venkatesh, 2000). The theory has been applied in a wide range of disciplines with extensive empirical support. We believe the theory is a promising starting point to understand block- chain.

Second, future studies should examine the strategic implications of blockchain in supply chain management to yield potentially valuable insights for academia and practice. For example, the technology could improve the strategic supply chain fit (Chen et al., 2009; Wagner et al.,

2012). Blockchain closely relates to multiple key constructs in supply chain management, such as transparency and visibility (e.g. Barratt and Oke, 2007; Foerstl et al., 2018; Johnsen and Ford, 2005), integration and outsourcing (e.g. Bals and Turkulainen, 2017; Marshall et al., 2007), as well as relationships and collaboration (e.g. Brito and Miguel, 2017; Cao and Zhang, 2011; Touboulic and Walker, 2015). Other re- search opportunities include auditing and reporting (Tate et al., 2010), supplier selection and development (Sancha et al., 2015), procurement (Schneider and Wallenburg, 2012; Walker et al., 2012), NGO colla- borations (Dou et al., 2018) and consumer relations (Gualandris and Kalchschmidt, 2014).

Third, in that regard, blockchain might challenge some established findings. For example, Tate et al. (2011) investigate the late adoption of environmental practices in the supply chain using transaction cost theory. They find that suppliers are more likely to adopt environmental practices if their information seeking, bargaining, and enforcement costs are minimized. We have argued that blockchain could sig- nificantly reduce ex ante and ex post governance costs and thus facilitate earlier adoption. Marshall et al. (2007) challenge multiple governance propositions of the transaction cost theory, as they find collaborative relationships to increase performance in the context of outsourcing telecommunication services. We have put forth some reasoning why blockchain might reduce the need for strong trusted collaborations in order to mitigate risks and consequently drive performance. We suggest that blockchain could facilitate similar performance gains, for reasons discussed in Section 3. Luzzini et al. (2012) develop implications for purchasing portfolio management which might be affected by block- chain, as for example, increased transaction speed and the ability to more easily switch suppliers could lead to dynamic spot markets for suppliers. The consequences of governance cost are uncertain and need to be explored in future research.

Investigating the technology's performance implications in terms of operational, financial and market performance is essential. Providing significant performance improvements, blockchain has the potential to influence decision-making on supply chain governance. Going beyond financial and operational performance measures, blockchain, as it provides a permanent and transparent record of corporate action, could enable truly sustainable supply chains (Carter et al., 2015).

Table 4 Research opportunities in adapting and creating mid-range theory.

Area Research questions

Adoption/participation • What are the barriers and challenges regarding blockchain adoption? • Under which circumstances is blockchain preferred over alternative technologies, such as EDI systems? • How do technological, organization and environmental factors influence blockchain adoption? • How is the role of power and dependence changing? • How to incentivize firms in an advantageous position regarding power and dependency to participate?

Information sharing • Under what circumstances are buyers and suppliers willing to share information? • Can blockchain help overcome power and dependency issues regarding information sharing? • What are the downsides of extended supply chain visibility and transparency? • How can blockchain facilitate the Internet of Things?

Purchasing • What are the effects of blockchain on product and service quality in buyer-supplier relationships? • How are outsourcing and offshoring decisions affected by blockchain? • How does the role of purchasing managers change? Is PSM becoming an automated function?

Organizational forms • Can system trust actually replace personal (relational) trust? • How does blockchain shift organizational borders? • Will new forms of organizations emerge? • Under what circumstances do they exist? • How does blockchain facilitate decentralized autonomous organizations? • Under what circumstances can decentralized autonomous organizations become viable?

Sustainability • What are the effects of blockchain on sustainable supply chain management? • How do immutable records of supplier sustainability activity influence supplier selection decisions? • How does blockchain facilitate CO2 emission reduction? • How does blockchain facilitate trading CO2 emission certificates?

Business models • What business models emerge from a wired adoption of blockchain? • Under what circumstances does blockchain make established intermediation business models obsolete? • What new intermediation services may arise?

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4.2.2. Validating grand theories The application and validation of grand theories under novel con-

ditions can help advance a new research topic quickly. Several theories, including but not limited to transaction cost theory (Grover and Malhotra, 2003), agency theory (Zsidisin & Ellram, 2003), network theory (Rinehart et al., 2004) and social exchange theory (Griffith et al., 2006), promise valuable insights for supply chain management and foster theory development. As a starting point, we call for large-scale empirical testing of the propositions we have developed. Table 5 shows alternative grand theories that could inform blockchain in supply chain management.

Agency theory, for example, is conceptually similar to transaction cost theory and closely relates to blockchain. The theory originated from early works on risk sharing behavior (e.g. Arrow, 1971) and is concerned with the agency relationship ubiquitous to supply chain management. The relationship is characterized by one party (the principal) delegating work to another party (the agent) who is per- forming the work (Eisenhardt, 1989). The principal-agent issue is caused by asymmetric information. We believe that blockchain and smart contracts substantially influences the principal-agent relation- ship, as it affects the two inherent problems. First, the agency problem arises when both parties have conflicting interests regarding the out- come of the delegated task and the actions of the agent are not easy to verify. Second, the problem of risk sharing occurs when the principal and agent are in disagreement on how to perform a task due to different risk preferences.

5. Conclusion

As blockchain is a driver of digitalization in purchasing and supply chain management, we utilize the transaction cost theory to derive early insights on how blockchain might influence the future of supply chain relations. Conceptually deriving a set of eight propositions yields two primary findings. First, blockchain might significantly reduce transaction and governance costs of supply chain transactions. Specifically, we find that blockchain can reduce search and information cost, for example in terms of buyer or supplier reputation, (re-)nego- tiation and agreement cost, due to the automation of contracts and their adoption, as well as costs of post-contract control, since the immutable ledger of records can track actions and performance of the contract partner. Second, a blockchain-based economy might significantly push many transactions, even under restrictive conditions, into more market- oriented governance structures. More short-term dynamic relationships and ad-hoc partnerships can result and might challenge established findings regarding supply chain structures and processes.

We must admit that much uncertainty is involved in studying an early phenomenon like blockchain. However, currently, practitioners drive the discussion on blockchain, as companies face pressures to ad- dress the technological trend proactively. Research on supply chain relations can only benefit from involving itself in the discussion at an early stage. If the technology lives up to the hype is to be decided in the distant future, even though we find the first theoretical antecedents for its potential impact on the supply chain. Our theoretical examination of

blockchain in a context of supply chain relations and our derived op- portunities for future research provide a useful starting point for re- searchers to advance the topic.

Acknowledgments

We thank the two anonymous reviewers, the Senior Associate Editor, and the Editors-in-Chief for their helpful comments on previous versions of the manuscript, which helped the authors to substantially improve the article.

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