iBlockchain’s Open IoT Marketplace: Order-Controlled Production
Order-controlled production is the working title of a marketplace which connects producers and clients in the manufacturing industry globally, making use of several IT objects to guarantee optimal functionality and necessary transparency while providing required privacy and identity for each participant. This article showcases the iBlockchain project and its core use-case which promises to tackle emerging platform monopolists in the manufacturing industry. We discuss the motivation, technical specifications, and governance. The consortium is currently working on its realization.
Authors: Marcel Kaiser, Daniel Kunz, Matthias Binzer, Philipp Sandner
Overview
Order-controlled production describes a flexible production. Thanks to a cross-company connection of manufacturing capabilities (see figure 1) it can quickly adapt to changing market demands and by this, optimize and efficiently use manufacturing capacities and material. As a result, value chains can be optimized by costs and time (Anderl, 2016).
There are two main aspects of this scenario in the Industry 4.0 domain:
- Standardization of the manufacturing process including single steps and self-description for capabilities of resources. This enables a flexible combination of single modules/manufacturing steps. (Anderl, 2016)
- The automatic planning, assignment, and control of a production order through an intermediary.
Companies are then able to offer production capabilities to 3rd parties by increasing their own utilization. As a result, a network of flexible manufacturing capabilities will arise, including nested and highly dynamic value chains (Bauer, 2017).
The focus of the iBlockchain project is not the standardization of the manufacturing process as described under point one of the main aspects, but to solve the cross-company coordination aspect of the production order in a fair manner by avoiding information asymmetries and resulting monopolies. This cross-company coordination for production orders can be solved by using a marketplace, which has to provide the following basic functionalities to its participants:
- Ensure the authenticity of the request for proposal (RFP) based on the requestor’s identity.
- Provide the optimal economic match function for the RFP, based on the offer inputs from the suppliers.
The role of the so-called matchmaker, which is the marketplace operator or owner, is highly attractive in the digital era. Several resulting de-facto monopolistic structures in the B2C (Business to Customer) area are already available, which needs to be avoided in the industry domain. Available samples of these matchmakers showed that it is easy for them to make a profit of their position, also by actively manipulating the market. As they consist of strong basic effects, like network effects and open market knowledge, the resulting information asymmetry in this central point needs to be avoided by applying a coopetition based approach on organizational as well as the technical level (Kölbel, 2020).
Which effects can occur in the specific case of platform monopolies?
The formation of a certain amount of market power is considered natural in highly interconnected network-like markets. Imposing other degrees of market power concentrations on them has been proven to fail and even lower competition (Selwyn, 1994). However, monopolies are rarely beneficial for anyone but the monopolist as she has a natural incentive to consolidate her position in the market at the cost of consumers and innovation (Holmes, 2008). Thus, monopolies on large markets should be avoided at a high cost. Moreover, conventional government intervention might not always be the most welfare-enhancing measure possible (Sherman, 2001).
Since they bring together supply and demand and a unified platform is found, GAFA companies do solve coordination problems and thus create welfare for participants by reducing the required effort for business, right? Partly correct. The example of Amazon as a two-sided marketplace structure is a shining one. Amazon brings together private consumers and all types of sellers. It is an intermediary economic platform. Its marketplace function decreases prices and effort for goods as there is more competition internally. Externally, however, there are barely real competitors. This can have consequences for the acquired rents by e.g. the charging of higher transaction and usage fees for participants. As long as fees remain lower than the costs for similar client exposure for companies, they might be accepted. The argument of competitors entering the market which charge lower fees does not apply here since Amazon has consolidated its monopoly by accruing an enormous degree of brand recognition and a massive network. These network effects result in a higher willingness to participate in the network, it becomes higher in value as its user base grows (Eisenmann, Parker, 2006). This is an unconventional situation since economic insights dictate that there are diminishing returns after a critical threshold of growth is passed. This results in lock-in and the winner of the platform competition taking almost all of the market (Eisenmann, Parker, 2006). Once such a monopoly has emerged and is stable, the loss of control for all participants is significant. To better understand this, a glance at the coordination function of such a construct has to be taken: A marketplace brings together different kinds of groups and their interests by enabling them to perform transactions and exchanges. Therefore they provide the so-called coordination function, which is responsible to create a matching between a given request and given offers. It acts as an intermediary, which needs to have access to all available inputs to guarantee the highest benefit for all the parties (Kölbel, 2020). This effect is distorted if the central coordinator has ulterior motives.
Information asymmetries can be massively exploited. The usage of a two-sided market brings valuable market insights to the platform (only) which can be capitalized on by actively supplying the market using the gained insight. This results in further increased market power for the monopolist who initially only intermediated markets (so-called hybrid platforms) (Johnson, 2019). The additional competitor comes at the cost of regular producers who provided them in the first place with their data. Furthermore, residual data can drive business models which further increase the relevance of the monopolist. In order to make the upcoming Internet of Things an open market, decentralized and transparent solutions are an opportunity to relieve economic agents from possible future network monopolies and massive market failures. While harnessing positive network effects, the avoidance of negative externalities comes at the relatively low cost of participation in decentralized marketplaces as the one proposed.
Currently, research is going into that direction to identify certain possible control points, where it would be possible for one party either to gain beneficial knowledge or to actively manipulate rules. Having such a point identified, the crucial thing is to get it to work in that way, that it is still possible to fulfill all expectations but avoid possible misuse of created metadata.
In the long run, not only supplying companies are rewarded by open, more neutral marketplaces like the proposed one but also customers. While they might face higher prices in the short term due to delayed profit realization of participating companies and eliminating market participants who distort the markets to their benefit, they keep markets open and independent. The cost of dependent markets is not only loss of control for individuals but might also result in higher prices in the mid and long term. Furthermore, the creation and acceptance of the proposed model does not generally eliminate competition for established companies but rather opens up this possibility to those using data which is shared consensually. This incentivizes innovation by protecting business intelligence from being shared with future competitors. Innovation will drive down prices for products and enables technological progress.
Marketplace in the industry domain
According to Currier (2018), a marketplace brings mainly together 2 kinds of groups:
- Supplier / Manufacturer in industry terms
- Buyer / Customer in industry terms
A special role is the marketplace operator (matchmaker), as he provides the matching function and the platform to use. (Kölbel, 2020) argued that it is crucial to achieving that none of the participating parties is able to get an advantage on its own based on available information, which will result in information asymmetry. Therefore an applied solution for the industry sector, like the marketplace for order controlled production, has to provide a solution for the following requirements coming from the participating roles:
Buyer / Customer:
- The buyer has the main expectation to get the optimal match based on his requests, like the optimal price on the market or other factors like delivery reliability, quality or sustainability
- Variations of orders as well as utilization
- Protecting intellectual property, like CAD data
Supplier / Manufacturer:
- Protection of manufacturing know-how
- Avoiding open knowledge of sales trend and price offering, which can be of interest of competitors/investors
- Avoiding openness of supply chains and business connections based on available transaction data
Common Interests:
- Easier trading partner onboarding
- Replace complex market studies by marketplace coordination algorithms
- Automate exchange of master data
- Better utilization of manufacturing capacity
In the end, any provided solution must implement the gap between privacy concerns as well as provide a function, which is able to get the best result out of the complete market knowledge. Therefore, based on these requirements, mainly product development, purchasing, finance, and production planning are affected. In a high degree of automation, that implies agents acting on behalf of these organizational units and on behalf of the whole organization. Details on how autonomous agents will act on marketplaces and their degree of economic decision-making freedom need to be elaborated separately.
Components
As introduced in the overview section, two main components can be identified in an industry-focused marketplace, one to ensure the authenticity of participants and their activities and the other to achieve high automation regarding planning, assignment, and control of production orders, in short term guarantee the best available match. Figure 2 also shows an interaction scheme. A short introduction to the respective components will be given in this section.
Self Sovereign Identity (SSI)
Self Sovereign Identity (SSI) is a mechanism that brings back control of the identity to the entities without relying on an administrative authority. It allows interaction in the digital world like it is already possible in the offline world (Sovrin, 2018). The main principle is based on proofs, trust, and verifiable credentials, also known as the trust triangle.
In the end, the SSI networks are providing a common trust network. This is the fundamental base to provide verifiable ID’s in the industry domain for companies as well as for machines.
At the company level, it is crucial to identify a company as a company, like it is done using the commercial register. In addition, a company owns several quality management certificates, like ISO. Such certificates, like commercial register and quality management, are crucial to attend in an industry marketplace, as these are then used to ensure the authenticity of requests and offers and can be used for further filter criteria. Another aspect is the machine-to-machine (M2M) communication, as this can also make use of SSI to ensure integrity and authenticity. Machines can also prove their identity, ownership, and also corresponding interfaces coming from an administration shell.
System governance: mechanism design and incentives
Governance describes a logic in which rules, norms, values, and actions are designed, enforced, and regulated. For a cooperatively operated marketplace as suggested, this requires a thorough understanding of affected players, mechanisms, and technologies. To maintain governance and improve it, an instance might have to be instantiated. In our special case, this becomes particularly important considering that different legal bodies with possibly different international origin get in contact and will be coordinated in order to solve their respective problems. This can affect individual and corporate entities locally, nationally, and internationally (United Nations, 2009). When dealing with DLT systems (which will be a core component in the suggested use case), governance is one of the fundamental aspects since it defines mechanisms by which design changes can be implemented and regulated (ListedReserve, 2018). Also for the remaining systems, a clear logical and simple set of rules will be required in order to be internationally recognized. Weill introduced an IT-governance framework in 2004. It is based on three dimensions: decision rights, accountability, and incentives. These cornerstones can be applied to the system at hand as well.
Moreover, avoiding information asymmetry and information surplus as described above is vital. However, it is crucial for the marketplace as it is a logical central point. This maintains the coordinative function. The simplest way to meet the requirement of openness is to open up all information to everyone (like Bitcoin) so that all parties end up with all (and thus equal) information. However, it is not always beneficial to disclose all information, as control over the own data is a precondition for the use case itself. Consequently, privacy-enhancing combinations of different types of cryptographic protocols (such as multi-party computation (MPC), homomorphic encryption, zero-knowledge proofs (ZKP) and zkSNARKs), could be applied to resolve issues (Kölbel, Kunz 2020).
The core goal, besides creating an easy-to-use environment, is eliminating incentives for misbehavior. The science dealing with such topics is mechanism design which is closely related to game theory. Once an agent has an incentive (i.e. a positive payoff) to perform an action not beneficial to anyone, the system is no longer incentive compatible. This is especially important when the ambition of international recognition and a free, efficient decentral market system is to be established. Thus, to ensure the long-term sustainability of order-controlled production, it might be necessary to create, on top of the technically specified framework, another governance structure that empowers market participants to coordinate democratically, which future steps can be taken (De Filippi, 2016). This guarantees that major changes in the world do not necessarily have to break the system and gives market participants the opportunity of a certain amount of control. Accountability will be guaranteed by the SSI and the decentral approach which makes sure that data is tamper-proof. Trust-reduced systems have the perk of high accountability. We make sure that it is maximized in order to incentivize good usage of the system.
An example of good governance will be to allow for different aggregations of economic actors. While individual smart machines participating in markets as rational agents is often an image applauded in the IoT and blockchain sphere, it can be less than optimal in very realistic situations. For example, if individual machines of a firm do participate in the marketplace, they might end up cutting each other’s prices for a service, ultimately causing unrealized profits for the company. As a consequence, fleet or even branch or company affiliation has to be considered when designing the system. This way, it remains a strategic decision of the respective company, how far aggregation will go.
Conclusion
As discussed, platform monopolists are on their way to further capitalize on their central market positions. The research project iBlockchain tries to tackle this issue by creating an open IoT marketplace structure which is decentralized and thus creates no information asymmetries. Digital marketplaces are required to be technologically and logically sound IT structures. Ours is a multi-component approach using DLT and SSI systems where they are applicable. Its governance remains transparent and by including companies in its creation, we make sure that each participant has incentive-compatible mechanisms in place.
References
Anderl et al, 2016: Fortschreibung der Anwendungsszenarien der Plattform Industrie 4.0, Bundesministerium für Wirtschaft und Energie, BMWi.
Bauer et al, 2017: Anwendungsszenario trifft Praxis: Auftragsgesteuerte Produktion eines individuellen Fahrradlenkers, Bundesministerium für Wirtschaft und Energie, BMWi.
Chukalov, 2017: Horizontal and vertical integration, as a requirement for cyber-physical systems in the context of industry 4.0, Stume Journals.
Currier, 2018: The network effects manual: 13 different network effects (and counting), Medium.
De Filippi et al. 2016: The invisible politics of bitcoin: governance crisis of a decentralized infrastructure. Internet Policy Review.
Eisenmann et al, 2006: Strategies for two-sided markets, Harvard Business Review.
Johnson, 2019: Platform vs. linear — business models 101, Applico.
Kölbel et al, 2020: Mechanisms of intermediary platforms
ListedReserve, 2018: Blockchain governance, Medium.
Miller 1982: Intermediate microeconomics: theory, issues, applications, McGraw-Hill Companies.
Sovrin Foundation, 2018: What is self sovereign identity, Sovrin.org.
Staab, 2019: Wenn der Markt zur Ware wird, Wirtschaftswoche 49.
United Nations. 2009: United nations economic and social commission for Asia and the Pacific: what is good governance?
Weill et al, 2004: Don’t just Lead, govern: How top-performing firms govern IT, MIS Quarterly Executive.
Zühlke, 2010: SmartFactory — towards a factory-of-things, IFAC Annual Reviews in Control 34, Issue 1 (129–138).
Remarks
This research and development project was funded by the German Federal Ministry of Education and Research (BMBF) within the funding number 16KIS0906 and implemented by the VDI/VDE Innovation + Technik GmbH. The authors are responsible for the content of this publication.
If you like this article, we would be happy if you forward it to your colleagues or share it on social networks. More information about iBlockchain can be found here.
Marcel Kaiser is a project manager and research assistant at the Frankfurt School Blockchain Center (FSBC). His expertise is primarily decentralized finance (DeFi) and industrial blockchain applications. He analyzes the impact of blockchain technology on the economy in his master thesis. He speaks at public events about topics like Libra, DeFi and blockchain in general. Feel free to contact him via mail (marcel.kaiser@fs-blockchain.de), LinkedIn or Xing.
Daniel Kunz is a Research Engineer at Robert Bosch GmbH with experience in Software development and Industrial IoT applications. He’s working on a strategic project in the field of “Economy of Things”. Find out more:
https://www.bosch.com/research/updates/economy-of-things/
https://www.linkedin.com/in/daniel-kunz-76417214a
Matthias Binzer is a Software Engineer at Robert Bosch GmbH with experience in Mobile and Embedded Device development and Industrial IoT applications. He’s working on a strategic project in the field of “Economy of Things”. Find out more:
https://www.bosch.com/research/updates/economy-of-things/
https://www.linkedin.com/in/matgunther/
Prof. Dr. Philipp Sandner is head of the Frankfurt School Blockchain Center (FSBC) at the Frankfurt School of Finance & Management. In 2018, he was ranked as one of the “Top 30” economists by the Frankfurter Allgemeine Zeitung (FAZ), a major newspaper in Germany. Further, he belongs to the “Top 40 under 40” — a ranking by the German business magazine Capital. The expertise of Prof. Sandner, in particular, includes blockchain technology, crypto assets, distributed ledger technology (DLT), Euro-on-Ledger, initial coin offerings (ICOs), security tokens (STOs), digital transformation and entrepreneurship. You can contact him via mail (email@philipp-sandner.de) via LinkedIn (https://www.linkedin.com/in/philippsandner/) or follow him on Twitter (@philippsandner).
