Blockchain Governance of University Knowledge Transfer

21 min readAug 25, 2021


Seminar Paper for Assigment in TU Dortmund-Ali Tarım

Table of Content

1. Introduction and Research Questions.

1.1 Motivation

2. Conceptual background and literature review

2.1 What is Governance?

2.1.1 Definition of Governance

2.1.2 Governance Actors

2.1.3 Types of Different Governances

2.2 Governance of University Knowledge Transfer

2.2.1 What is Knowledge Transfer and Processes of University Knowledge Governance?

2.2.2 Governance of University Transfer in Europa

2.2.3 Main Governance Actors in Knowledge Transfer in Germany

2.2.4 Main Problems of Governing University Knowledge Transfer

2.3. Blockchain Governance of University Knowledge Transfer

2.3.1 Blockchain Technology

2.3.2 Blockchain Governance: Decentralized Autonomous Organization (DAO)

2.3.3 Blockchain Governance of University Knowledge Transfer

3. Methodology: Explanatory Research

4. Data and Findings

5. Conclusion

5.1 Discussion of Findings

5.2 Solving the Problems of Governance University Knowledge Transfer in Europa with DAO

6. List of References

1. Introduction and Research Questions

First of all, the concept of governance will be discussed in the study. Secondly, university transfer and governance of university transfer will be explained. Thirdly, the subject of university transfer and governance in Europe will be examined and the subject will be addressed specifically in Germany and the main problems of governing university knowledge in Europa will be investigated. Finally, it will be discussed whether the decentralized autonomous organization technology developed with the blockchain infrastructure can solve these problems.

Research questions are as follows:

1-What is governance, what are governance actors, types of different governance?

2-What is University transfer? How is university knowledge transfer governed in Europa in general and in Germany in particular?

3-What is the main governance in knowledge transfer in Germany? What are the main problems of governing university knowledge transfer in Europa?

4-What is Blockchain Technology and Decentralized Autonomous Organization (DAO)? Can governance of university transfer main problems in Europa be solved with DAO?

1.1 Motivation

Blockchain technology and the transformation of information are topics that I am very curious about. Knowledge Transfer (KT) is a concept that mediates the transformation of knowledge. It has a complex management mechanism. KT is basically a facilitating, accelerating magnet for interaction between actors. I think that the Decentralized Autonomous Organization (DAO) technology, which is included in the blockchain technology, can prevent the governance complexity experienced in KT. I think DAO will speed up interaction in KT. That’s why I chose the topic ‘Blockchain Governance of Knowledge Transfer’. The reason why I take Germany as an example in this regard is that it is a country with a very developed KT ecosystem and is interested in blockchain technologies at all levels.

2. Conceptual Background and Literature Review

2.1 What is Governance?

2.1.1 Definition of Governance

To understand knowledge transfer governance, we need to define what governance is. With the wind of political change that emerged in the 1980s, the concept of governance emerged. Governance can be defined as the set of networks in the pursuit of common goals. In fact, the concept of governance emerged by focusing on the process of good and stable management of organizations. There are six types of governance: Participatory or Democratic Governance, Global Governance, Good Governance, Corporate Governance, Environmental Governance, E-Governance (Biswas, A.; 2020, October 2).

In this article, as an example of good governance and e-governance, DAOs for the Knowledge Transfer Ecosystem will be considered as a governance model in other sections. Therefore, in the article, governance models are briefly explained to complete the research.

2.1.2 Governance Actors

According to each governance area, actors are the main decision-makers. For example, the actors in the Knowledge Transfer (KT) process are the state, universities, academics, knowledge transfer organizations, business, industry, and other organizations.

Figure 1: Governance Actors in the Knowledge Transfer

2.1.3 Types of Different Governances

In general, there are six types of management. The types of governance in the literature are constantly increasing.

Figure 2: Types of Different Governances

Two governance distinctions have been found for KT and Knowledge Transfer Organizations (KTO). Geuna et al. made a distinction between personal and corporate governance, emphasizing personal relationships that predominated in the old model. Milagres and Bruchart, on the other hand, made a triple distinction by focusing on process and operation. Structural governance refers to formal contracts. Procedural governance refers to information sharing routines. Finally, it refers to relational and cognitive governance values, unwritten codes of conduct, norms, and culture.

2.2 Governance of University Knowledge Transfer

2.2.1 What is Knowledge Transfer and Processes of University Knowledge Governance?

University is a knowledge organization. Knowledge transfer (KT) mainly means providing mutually beneficial cooperation between universities, the public sector and businesses. According to the University of Cambridge, KT can be split into six types: People, Publication and Events, Collaborative Research, Consultancy, Licensing, New Businesses (University of Cambridge; 2009, May 27).

(Source: Gopalakrishnan; Santaro, 2004; p. 59)

Knowledge Transfer (IT) and Technology Transfer (TT) are often used interchangeably… The literature suggests that the relationship between knowledge and technology is both complex and open to many interpretations… In its simplest form, technology is more about knowing how things are done, while knowledge is more about knowing why things happen (Gopalakrishnan; Santaro, 2004; p. 57–58). Therefore, Knowledge Transfer is used in this article to include the concept of Technology Transfer. The differences between technology and information differ from each other in their relative weight and include information technology knowledge.

Figure 3: Third Mission/Stream

Knowledge transfer activities of universities are expressed as ‘third mission’ or ‘third stream’.

Figure 4: Old Model-New Model Knowledge Transfer (Genua and Muscio; 2008, p. 6–7)

Genau and Muscio divide KTs into new models and older models, defining patenting (and disclosure disclosures), licenses (copyrights), and spin-offs as the local framework of the KTs. According to them in the old model, governance of KT activities was shaped by the personal relationships between academic researchers and industry and government (local or national). They start the new model with the emergence of the knowledge-based economy (Genua and Muscio; 2008, p. 6–7) and Knowledge Transfer Organizations (KTOs). In the article’s updated 2009 publication, they list the historical factors of this transition as follows; Universities creating competitive advantages, the emergence of technology-oriented industries, the increase of higher education students and the need for skilled human resources, the increasing cultural appeal of higher education, the view that universities can be a driving force in local development and national innovation system (Genau and Muscio; 2009, p. 97). Thus, a mechanism that ensures the flow of information between the university and the society, organizations and the state with knowledge transfer and knowledge transfer organizations has been developed.

Figure 5: Knowledge Transfer Main Actors and Activities

Whereas the old model began with academia and personal governance of the chemical industry, the new model began with the establishment of a Research Park at Stanford University. Bayh-Dole Law, which provided mutually beneficial cooperation with patent regulations in 1980, has created the Knowledge Transfer (KT) ecosystem today. From the 80s, KTOs spread around the world.

The old model gained speed with industrialization, but today’s new knowledge transfer model thanks to the institutionalization steps of the knowledge-based economy that emerged at Stanford University in the 1960s and the examples of Bayh-Dole Law, which enabled cooperation for mutual benefit with patent regulations in 1980, the Knowledge Transfer (KT) ecosystem was formed today. In the aftermath of this landmark legislation, almost all research universities in the United States established TTOs to manage and protect their intellectual property. TTOs, Research Parks and Institutes etc. facilitate commercial knowledge transfers of intellectual property originating from university research (Link, A. N.; Siegel. D. S; 2007, p. 109). Thanks to knowledge transfer organizations such as TTOs and intellectual property protection mechanisms, knowledge transfer institutions and regulations have made great progress in licensing, patenting and spin-offs between university and industry.

As a result, all knowledge transfer approaches applied are to accelerate and improve the innovation process and to establish a solid foundation as well as their economic contributions. In this respect, knowledge transfer organizations can be compared to magnets created to innovate individually, locally, nationally, regionally and globally.

It did not take long for the knowledge transfer ecosystem, which emerged in America as a new model, to spread to the world. The transfer of scientific and technological know-how into valuable economic activity has become a high priority for many nations and regions (Link, A. N.; Siegel. D. S; 2007, p. 132).

Although it is not clear exactly when Knowledge Transfer emerged, the intertwining of production, innovation and technology in the industrial revolution process has led to an increase in the importance of science. Thus, links were established between the university and the private sector. With the increase in the bond between science and technology and the importance of the knowledge economy, KT developed further in line with the needs. The development of KT has been with its organizations (Research, Technology Transfer Offices, etc.). Organizations have been a magnet for KT. At the same time, the concepts of national innovation system, clustering and technological convergence are also very important in the emergence of KT organizations.

Referring to Muscio’s old model, it is possible to divide knowledge transfer governance into 2 in terms of governance model, corporate and personal governance model. In the survey conducted by Maria, Genua and Rossi with Piedmont Chamber of Commerce companies, 82.2% of companies in the Small-Medium Enterprise (SME) category do not cooperate with universities. The remaining 9.9% engage in institutional collaboration and the remaining 7.9% engage in contractual collaboration with a specific researcher (Geuna, A., Bodas Freitas, I. M., & Rossi, F, 2010; p. 21). Looking at this research, we can say that the old governance model continues among SMEs and KTOs, but there is a tendency towards the new governance model.

According to Federica Rossi, the scope and characteristics of the knowledge transfer process are influenced by the firm’s capacity and willingness to act, as well as the internal workings of the university (especially institutional incentives for university researchers to transfer knowledge) and the broader legal, economic and political environment (Rossi, 2010; p. 5).

Figure 6: A systemic and dynamic model of knowledge transfer in interorganizational partnerships (Milagres; Burchart, 2019; p. 47).

Milagres and Burchart refer to different types of governance in their articles. Their interpretation of the systematic literature review indicates that there are six dimensions anteceding knowledge transfer processes in partnerships, namely, knowledge attributes, the macro context, inter-organizational factors, the source organization, the recipient organization and individual factors. While informal relations continue in the new model, different types of governance are needed to manage complex interactions between organizations. These are expressed in the related article as structural (official contracts), procedural (knowledge sharing routines), relational and cognitive governance (values, unwritten codes of conduct, norms and culture) (Milagres; Burchart, 2019; p. 48).

The importance of participatory or democratic governance is seen in the KT process and the governance of KTOs. The vision of good governance, defined as the ideal of governance, is in question for every KT process and KTOs. With the facilitating tools and management applications of the internet age, remote working and developing video interaction tools during the pandemic process, KT and KTOs have also made progress in the type of e-governance.

2.2.2 Governance of University Knowledge Transfer in Europa

As Formica, Urmas and Varblane quote from the OECD’s 2002 report, the USA emphasizes that strong interactions between science and industry characterize innovation-led economic growth and lead countries to innovation-led growth. Japan, Germany and France mention the importance of creating incentives for relevant actors to join forces in order to deepen industry-science relations (Formica, Urmans and Varblane; 2008, p. 290).

Figure 7: Development of Corporate Governance KTs in Europa (Formica, Urmans ve Varblane; 2008, s. 290)

Compared with the most advanced economies and the key 15 EU countries, according to Formica, Urmas and Verblane, the Czech Republic, Estonia, Latvia, Lithuania, Hungary, Poland, Slovakia, Slovenia and other emerging market economies in Central and Southeast Europe, academia and business They lag behind in putting their world together (Formica, Urmans and Varblane; 2008, p. 290–291). The last 30 years have witnessed the slow but steady process of restructuring European universities to a ‘knowledge-based economy’. Beginning in the UK in the early 1980s, the process has spread to the continent, starting with the Netherlands and the Scandinavian countries, and more recently to southern European countries such as France and Italy (Genua and Muscio; 2008, p. 3).

2.2.3 Main Governance Actors in Knowledge Transfer in Germany

Figure 8: Governance of University Knowledge Transfer in Germany

In Germany knowledge transfer between the science base and industry is promoted by a highly organized division of labor between research institutes and organizations mainly oriented towards basic and strategic research and others with an applied research focus (Mason and Wagner; 1999, p. 87). In Germany, KT organizations are organized as foundations or GMBH and KTs is supported by federal and provincial governments. In addition to the universities examples of KT in Germany are mentioned in Mason and Wagner’s article Leibniz Association (formerly ‘Blue List’), AIF (Working Group of Industrial Research Societies), An-Institut, Stenbeis Foundation, Max Plank Association and Helmholtz Association.

This transition towards a knowledge economy in Germany was due, inter alia, to a number of federal and state policy initiatives, including a series of targeted measures aimed at improving the conditions for research commercialization in research institutions. Secondly, the relatively centralization of state-owned universities and thirdly, the intellectual property regulation (IPR) that came into force in 2001. With this regulation, the interaction between professors and universities increased (Leišytė and Sigl, 2018: p. 7–8). Germany joined this process a little late, but thanks to its ecosystem, it caught up quickly.

Then In 2002 the so-called university teacher privilege (Hochschullehrerprivileg) was abolished. Following various model contract proposals, the model agreements for R&D cooperation at the Federal Ministry of Economics and Technology prevailed in the 2010s. These model agreements, which are now in their third edition, attempt to reconcile the interests of all parties involved.

2.2.4 Main Problems of Governing University Knowledge Transfer

12 problems were found that focused on by many different authors from many different sources in the World, Europe and Germany. In the literature we have researched, there are many problems in the KT process and in CTOs that are KT agents:

- Increasing political pressures on universities (Genua and Muscio; 2008, p. 4).

- The heterogeneity among universities (reason of success/failure) (Genua and Muscio; 2008, p. 12).

- Commercialization policies dominate science and research (David 2004; Nelson 2004; Geuna and Nesta 2006); (Genau and Muscio; 2009, p. 103).

- There is a “revenue maximization model of technology transfer” that hinders the diffusion of innovation in TTOs (Genau and Muscio; 2009, p.108).

- A key formulation issue is establishing institutional goals and priorities (Link, A.N.; Siegel. D. S; 2007, p. 130).

- The complexity of the Knowledge Transfer process (Link, A.N.; Siegel. D. S; 2007, p. 133).

- In transition countries, nascent entrepreneurs are negatively affected by higher uncertainty (Formica, Urmans and Varblane; 2008, p. 307).

- Organizational inertia and difficulty of bottom-up processes in universities (Leisyte, 2011; p. 447).

- Market failure as a result of the low appropriability of scientific knowledge increases the need for outside intervention and support (Rossi, 2010; p. 7).

- The inherent properties of information such as context-dependence, ambiguity, and tacitness make it sticky, that is, difficult to transfer when such properties require corresponding governance mechanisms (Fang et al., 2013); (Rossi, 2010; p. 7)..

- “A loose link between formal structure and activity structure” (Lange and Krücken 2011: 365) and informal links (Leišytė and Sigl, 2018: p. 17).

-There is currently a discussion in Germany as to whether a separate legal personality should be created for research co-operations (Czychowski; 2019, p. 127).

Basically, there are problems of low appropriability, high complexity of information, uncertainty of results in research (Rossi, 2010; p. 7), external intervention and dominance, complexity brought by heterogeneity, lack of flexibility, and informal interaction in knowledge transfer and knowledge transfer organizations.

2.3. Blockchain Governance of University Transfer

2.3.1 Blockchain Technology

It is thought that the Decentralized Autonomous Organization (DAO) trend, which is developed using blockchain technology, can solve some of the problems of the knowledge transfer process and knowledge transfer organizations. In addition to the problems that DAO can solve, DAO also has disadvantages in terms of traditional KT processes and KTOs. Nevertheless, it is hoped that today, when there are institutional trials on blockchain technologies, investigating the effect of the KT process and the blockchain infrastructure and the DAO trend in KTOs will contribute to the literature from an exploratory perspective.

According to IBM Blockchain is a shared, immutable ledger that facilitates the process of recording transactions and tracking assets in a business network. An asset can be tangible (a house, car, cash, land) or intangible (intellectual property, patents, copyrights, branding). Virtually anything of value can be tracked and traded on a blockchain network, reducing risk (Gupta, 2020). The whole point of using a blockchain is to let people — in particular, people who don’t trust one another — share valuable data in a secure, tamperproof way (Orcutt, 2020). The main purpose of the blockchain is to allow fast, secure and transparent peer-to-peer transactions. It is a trusted, decentralized network that allows for the transfer of digital values such as currency and data (M, Laura, 2021). The key feature of blockchain is that it is transparent, secure, immutable and peer-to-peer (P2P). At its core, blockchain technology is the intersection of P2P networking, cryptography and game theory.

Table 2: Classifications in Blockchain

There are 2 basic classifications in blockchain, general and permission-based. According to the general classification, blockchain is divided into 4 as public, private, federated and hybrid. In a private blockchain, there is only one organization in the network. Anyone can see the public ledger. It is also completely transparent and supports user authentication. There will be more than one organization in the Federation. Hybrid is somewhat similar to federated blockchain, but they are definitely different. Here it shows freedom and controlled access at the same time. Hybrid blockchains are not public, they are customizable, but they offer the same level of transparency, security and integrity. You can make any data and transaction you want public. In permission-level classification, blockchain is divided into permissioned and unauthorized. In this permissioned blockchain, the network remains in a closed environment. Typically, centralized industries favor such blockchain technology implementations because they can at least restrict other users. In a permissionless network, all nodes can participate in the authentication process. Therefore, there are no restrictions (Iredale, 2020).

Blockchain can be exemplified in the simplest way as follows. When someone creates a document or spreadsheet in Google Docs, they can share it across a corporate network. In doing so, multiple people can visit the document and edit a Word document at once without the hassle of emailing it. Google Docs isn’t technically a blockchain, but it’s similar to blockchain. At its core, a blockchain is a decentralized database shared over a network. The database contains blocks of information that are the same across the entire network. If some add a new block, the entire network will see the change, as in Google Docs. The difference between blockchain and Google Docs is that once the transaction has been executed, no one can edit the transaction (Sikich, 2018).

Academic studies on blockchain technology started in 1991. Previously, developments in cryptography evolved with Stuart Haber and W. Scott Stornetta in 1991 with the aim of creating a decentralized structure. With the emergence of Bitcoin, the first decentralized work, theoretical and practical studies have increased. The journey of the blockchain world, which started to transform the decentralized payment system, continued with smart contracts. Thanks to smart contracts, decentralized applications have been paved, and blockchain continues its journey, which started only as a payment system, by decentralizing the internet and services.

You can see how the blockchain works in the figure below:

Figure 9: How blockchain work (Dummies, 2017)

As you can see in the figure above, there is no center in the blockchain and any transaction takes place in a decentralized manner.

2.3.2 Blockchain Governance: Decentralized Autonomous Organization (DAO)

Figure 10: Traditional Organization and Decentralized Autonomous Organization (Blockchainhub; 2020, 10 Dec)

DAO originated as a blockchain technology idea. With Blockchain, peer-to-peer transactions are carried out without the need for any intermediary (bank, etc.) in data transfer. Well, while transactions are made peer-to-peer with blockchain technology without intermediaries, peer-to-peer decisions can also be made within an organization. This is DAO. With the idea of ​​DAO blockchain technology, the rules of the organization are coded and an organization’s decision mechanism can work entirely on blockchain technology.

In traditional companies, all agents of a company have employment contracts that regulate their relationship with the organization and with each other. If anything goes wrong, or someone does not stick to their end of the bargain, the legal contract will define who can be sued for what in a court of law. DAOs, on the other hand, involve a set of people interacting with each other according to a self-enforcing open-source protocol. There is only one governing law — the protocol or smart contract — regulating the behaviour of all network participants (Blockchainhub; 2020, 10 Dec).

DAOs, on the other hand, involve a set of people interacting with each other according to a self-enforcing open-source protocol. Keeping the network safe and performing other network tasks is rewarded with the native network tokens. Everyone are steered by incentives tied to the network tokens, and fully transparent rules that are written into the piece of so ware, which is enforced by machine consensus. There are no bilateral agreements. There is only one governing law — the protocol or smart contract — regulating the behaviour of all network participants.

2.3.3 Blockchain Governance of University Knowledge Transfer

The subject of Blockchain Governance of University Knowledge Transfer proposes a decentralized governance way to achieve the ideal of good governance for the KT process and KTOs and to provide more effective and efficient information transfer with digital, algorithmic, e-governance governance.

Figure 11: Blockchain DAO Governance and Examples

According to CB Insight data, sectors that will be disrupted by blockchain include public, education and information service.

In 2016, Learning Machine collaborated with MIT Media Lab to launch the Blockcerts toolset, which provides an open infrastructure for academic credentials on the blockchain.

Sony Global Education, for example, has developed an educational platform in partnership with IBM that uses blockchain to secure and share student records.

Currently, blockchain technology is used for certificate/degree verification, student assessments and exams, credit transfer, data management, admissions, review papers in education.

In European countries, blockchain technology applications at the European Union, State and Industry level are tested and discussed in education.

Currently, transactions are carried out successfully and benefit from blockchain technology in universities. DAO suggestions regarding the decision mechanism are presented.

Mikroyannidis, Third and Domingue illustrated an online university system with blockchain technology (Mikroyannidis, Allan, Domingue; 2019, 16 Oct):

Figure 12: A Decentralized Model of Educational Transactions (Mikroyannidis, Allan, Domingue; 2019, 16 Oct).

Dan Fowler explained that blockchain can enable the creation of consensus across non-trusting parties, with a use case in IP as a single, distributed, network to aggregate rights (Joint Research Centre; 2018, 1 Jan).

Figure 13: Comparison of Traditional Centralized System and Decentralized Autonomous Organization (Nirolution; 2019, 09 Aug).

The figure you will see below gives information about implementing DAO in a KTO organization. Patenting in the KT process; licensing; spin-offs; education, network, collaboration, etc.; inter-party right, distribution of duties, responsibility; rules and tasks can be provided on the DAO infrastructure based on blockchain.

Figure 14: Decentralized Autonomous Organization Structure (Nirolution; 2019, 09 Aug).

For a DAO to work, we first need rules. We can define rules in code using Smart Contracts. The consensus mechanism ensures that everyone follows our rules. In a decentralized autonomous organization, every action is a transaction. This means a transaction, for example, if you want to submit a higher patent project. Each transaction is one vote. This vote is represented by a coin. Smart Contracts executes the token. As a result, your patent project submission is displayed in the DAO. Anyone with a token can now vote for or against your proposal. If you get the majority, your further patent applications will be accepted. Here, each wallet address represents an employee. Each employee has a certain number of tokens. The more coins you have, the more weight your game will have. Tokens can be distributed according to stakeholder shares or management hierarchy. This also applies to other KTO activities (Nirolution; 2019, 09 Aug).

3. Methodology

Since the subject is current and new, an exploratory research method will be used in the study.

Since there is no study related to my research area in the literature, I will do exploratory research. The closest articles were applied at universities.

Resources accessed through EBSCO, Researchgate and Google Scholar.

4. Data and Findings

Figure 12: Blockchain DAO Governance in University Knowledge Transfer

Today, the needs of the knowledge transfer process and knowledge transfer organization can be met with blockchain technology. Different features are tested and implemented in the education sector. Blockchain DAO Governance offers great opportunities and risks in transferring university knowledge.

Blockchain DAO Governance can eliminate the problems of high information complexity, outside interference and dominance, stakeholder rights, complexity brought by heterogeneity, and informal interaction in information. Lack of flexibility, low relevance, and uncertainty of research results cannot help.

5. Conclusion

5.1 Discussion of Findings

The conclusions drawn from the exploratory research are as follows:

-Blockchain applications for information transfer are still in their infancy.

- Decisions can be made in KTOs with DAO quickly and simply. You do not need any employees for management. Working codes for this are in charge. Costs are greatly reduced and you can work distributed around the world.

-All the benefits of blockchain technology are only achieved through open applications.

-Blockchain has the potential to unleash a wave of innovation around university knowledge transfer organizations.

-For a change to the Blockchain Governance system, you must create the system from scratch as you cannot change any rules you set for blockchain governance.

The weaknesses of the research are:

There are no references in the literature on blockchain DAO governance and university knowledge transfer.

Knowledge Transfer is a topical, diverse, multi-actor issue.

There is little academic research on blockchain, especially in the field of social sciences.

The strengths of the study are:

The study may contribute to future studies.

The study may offer new suggestions to university knowledge organizations.

5.2 Solving the Problems of Governance University Knowledge Transfer in Europa with DAO

Considering the economic, social and institutional benefits of blockchain for KTOs, significant work can be done. The closed attitude still continues in KTOs. This can hinder the efficient use of blockchain in the DAO. In order for KTOs to be organized as decentralized autonomous organizations, it is necessary to increase user experiences, to write management codes perfectly on smart contracts, and to ensure transparency for the efficiency of the system. With the blockchain infrastructure, KTOs can turn into DAOs, but once this decision is made, it must be acceptable, accessible and appropriate for all stakeholders. Thus, good governance will be achieved with the DAO standing between algorithmic governance, e-governance and digital governance.

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