safeguarding measures in blockchains: how participants
TRANSCRIPT
Safeguarding measures in blockchains: How participants weigh the
trade-off between security and transparency in blockchain networks
Master Thesis MSc-BA Change Management
By
Ruhi Chatterjee S3206106
Thesis supervisor: Marvin Hanisch
University of Groningen
Faculty of Economics and Business
Thesis completed with IBM CIC Groningen
Date: 10/08/21
Word count: 9,652
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Abstract
Blockchains represent a decentralised solution to governance issues across networks, however,
significant issues still lie in the governance of the blockchains themselves. Since a blockchain is
transparent, all transaction information is shared between different network nodes. The
information shared between the nodes may be misused by the blockchain participants, creating a
need for privacy measures at each node. However, such misappropriation of knowledge
negatively impacts the trust required to run a blockchain project. On the other hand, blockchains
create efficiency by lowering transaction costs and cutting out the “middleman”. This paper
explains how the participants in a blockchain network would react to joining a network and how
their perception of blockchain safety could trigger more serious attempts at information
protection. Next, this paper considers knowledge spillovers in the blockchain context and aids
further understanding of how blockchain governance should develop based on the reaction of the
participants. Further, this paper attempts to illustrate how protective or opportunistic behaviour
by participants can negatively impact the value of the blockchain and influence others within the
blockchain project. More importantly, this research suggests a direction for a practical balance
between security measures and transparency to achieve the purpose of trust within the
blockchain network
Keywords: Blockchain, Network governance, Transparent hand, Natural selection and
Safeguarding measures.
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Table of Contents
Abstract 1
Introduction 3
Theoretical model 8
Background on blockchain technology and governance 8
Blockchain projects in practice 9
The translucent hand perspective 10
The invisible hand and natural selection 11
Blockchain Governance 12
Research hypotheses 13
Safeguarding issues of blockchains 13
Absorptive capacity 15
Competitive intensity 17
Firm network embeddedness 18
Control variables 19
Conceptual model 20
Methodology 22
Study Measures 22 Dependent variable safeguarding measures 22 Independent variable network embeddedness 23 Independent variable absorptive capacity 24 Independent variable competitive intensity 24 Control variables 24 Data collection procedures 25 Validity and reliability 26
Analysis 26
Results 28
Correlation and descriptive statistics 29
Regression results and hypothesis testing 33
Further insights based on interviews 37
Discussion and conclusion 38
Research limitations and future research 40
References 42
Appendices 45
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Introduction
Blockchains may famously promise immutability and transparency for participants, however, a
certain level of uncertainty still exists in terms of their governance (Ziolkowski et al., 2020).
Blockchains represent a decentralised solution to governance issues across networks but
significant issues are still prevalent in the governance of the blockchains themselves (van Pelt et
al., 2020; Ziolkowski et al., 2020). Blockchains work by recording a transaction occurring at one
node of a network within a blockchain which is then confirmed by all the participating nodes in
the project, after which this transaction gets recorded as a block and is added to the pre-existing
chain of blocks or starts a new blockchain (Quinou & Debonneuil, 2019). Blockchains allow
various use cases such as transparency and traceability but this also implies that various
organisations taking part in the project may have access to each other's transaction information
(Quinou & Debonneuil, 2019). To keep such collaborative interactions in check, governance
mechanisms beyond what automatically occurs in a blockchain code may be needed (Shermin,
2017). Therefore, the question of how participants could effectively behave in this situation
arises as they would have the opportunity to either create safeguards for themselves in a project
or potentially exploit information that they might come across in a blockchain project. Therefore,
this paper focuses on the participant opportunism issues in relation to network composition and
proposes the question: How do blockchain participants weigh the tradeoff between safeguarding
and transparency in a blockchain network?
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When a blockchain network is made, one must consider issues pertaining to how the network
should be composed, controlled, what kind of legal affairs it entails, and what technology should
be associated with it (Hanisch et al., 2021). Due to the fact that a blockchain is transparent, a lot
of information is shared between different network nodes (Quinou & Debonneuil, 2019). This
blockchain feature can allow efficiency across industries through an interconnected network. A
higher number of blockchain participants could imply more collective information for the
network and more efficiency as transaction costs diminish (Quinou & Debonneuil, 2019).
However, the inclusion of an entire supply chain or network could also mean including
competitors in the blockchain network. Moreover, the misappropriation of the shared
information is a significant risk in such networks (Murray et al., 2019). Even though a
blockchain promotes the idea of “trustless trust” this is only valid as long as blockchain
participants have trust in the blockchain itself (Murray et al., 2019). Therefore, including
competing participants to have an effective network and securing the intellectual property at the
same time is difficult.
Leakage of intellectual property may happen naturally in the form of employee mobility, social
network embeddedness, and the reciprocity of knowledge sharing in an industry (Inkpen, 2019).
A blockchain only shares information regarding transactions and information storage that takes
place in the project while sharing a copy of this information with every participant (Cong & He,
2019). However, one must consider that this still provides the opportunity to possibly gain
organisational information that would not be available outside a blockchain project under normal
circumstances. Contractor (2019) explains how highly networked industries may have a net
benefit of disclosing or leaking information which outweighs the drawbacks. Moreover, Alnuami
and George (2016) illustrate how information leakage may not be the worst possible scenario as
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knowledge retrieval may be a way to gain from knowledge spillovers. Companies may have the
opportunity to repurpose the information they gain to their own advantage. However, the factor
of trust within the network would not work if every participant attempts to make use of
knowledge from other companies within the network for personal gain (Murray et.al, 2019).
Gains can be made from participating in a blockchain network without appropriating
information, but one may feel the need to protect their information and take safeguarding
measures against knowledge leakage.
Blockchain participation benefits clients by coordination amongst participants in a network, with
automated execution, transparency, ease of scalability, safeguarding in terms of automated
enforcement, verification, automated adaptation, fast reactivity, and increased reliability
(Hanisch et al., 2019; Shermin, 2017). Additionally, this online medium allows these benefits in
comparison to the traditional contracts which may be much more costly and time consuming
with the need to include lawyers and other parts of the organisation (Murray et al., 2019). In the
case of blockchain participation, the transaction costs may be lower considering that they would
be shared throughout the network (Shermin, 2017). However, we must consider that even
blockchains making digital contracts and implementing them can be expensive (Murray et al.,
2019). Further costs can arise from the inflexibility of blockchains, accuracy of information used
for a digital or “smart contract”, and the possibility of an attack on the blockchain before the
information is saved in a block (Murray et al., 2019). More importantly, additional costs that
may arise from firms trying to tighten securing measures while participating in a blockchain have
not been considered. This factor should be considered when the governance of these blockchain
projects is planned.
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While blockchain technology poses many benefits, many questions still lie with regards to how
they should be governed. Enough research has not been conducted on the topic of how
blockchains self-regulate and how do managers with low knowledge on the topic feel about the
effectiveness of this governance method (Shermin, 2017). Managers need to trust experts on
what form of governance is established based on the code they write and determine how this
automated governance method should be updated. Moreover, this process of governance may
need more than standardised code to govern this novel area for organisational applications.
Consequently, the trend of governance structure in an external environment such as blockchain
projects would be appealing to managers. This is also an important consideration, taking into
account the potential of blockchain solutions automating processes not only within firms but also
across industry networks. As technology gets integrated further into businesses, managers and
researchers must think of an optimal governance solution for all participants to facilitate
coordination and exchange. Moreover, the paper by Altman et. al (2017) identifies a deficiency
in research on the tensions created when multiple methods of governance structures could be
implemented. This paper adds to the field of research by combining the translucent hand
approach by Altman et.al (2021) to the field of blockchain governance which will be discussed
further in the following section.
This paper further contributes to several aspects of network governance within blockchains.
While blockchain technology has become a popular topic of discussion, little research has been
done on the impact of safeguarding measures of the blockchain network. Firstly, this paper
explains how the participants’ perception on blockchain safety could trigger more serious
attempts at information protection. This paper considers knowledge spillovers in the blockchain
context and aids further understanding of how blockchain governance should develop based on
7
the reaction of the participants. Subsequently, the paper attempts to illustrate how protective or
opportunistic behaviour by participants can negatively impact the value of the blockchain and
impacts others within the blockchain project. More importantly, this research should suggest a
direction for a practical balance between security measures and transparency for the purpose of
trust within the blockchain network. Finally, this would further contribute to Network theory in
relation to blockchains which has been sparsely researched, and the specific behaviour of firms
while joining blockchain projects which is even more uncommon. Managers may use this
research to determine what they should expect while participating in blockchain projects and to
understand the governance effects behind blockchains. Finally, the paper aims to explain
governance mechanisms as multiple layers that can be implemented on blockchain projects
which can be impacted by social and firm related variables.
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Theoretical model
Background on blockchain technology and governance
Blockchain technology has been described as a decentralised ledger that is immutable, traceable,
and transparent (Lumineau et al., 2020). However, firms that participate in a blockchain may
have the opportunity to make use of external information available to them through this system.
They may not have had access to such information without their participation in such a
blockchain project. The features of the autonomous blockchain solution would go on by itself
considering that an automated program cannot react to breaches in governance or confidence by
participants means that there is room for concern or doubt during firm participation in a project.
Jones et.al, (1997) indicated that network governance comprises two essential factors: patterns of
interactions or exchange; and the flow of resources taking place between organisations.
Furthermore, the need to effectively manage a network to find benefits from it without
opportunism is relevant to the management of blockchain projects (Altman et.al, 2021). The
paper further argues that there is a need to move beyond tightly controlled systems for the
protection of intellectual property especially since there may be multiple approaches applications
that may need varied approaches to governance (Altman et.al, 2021).
One of the many use cases of blockchains includes supporting the paradox of a decentralised
automated solution with a centralised procedure (Altman et.al, 2021). Possible agency issues
may also lie in any adjustments that contracts may need within blockchains as they require a
majority consensus from participants in the network to implement the change (Sherman, 2017).
Moreover, most clients in blockchain projects must rely on the expertise of the people who set up
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the blockchain technology for the automated governance mechanisms of majority consensus or
other governance techniques (Sherman, 2017). While blockchains focus on the decentralisation
of transactions and processes within the project, a lead organisation may influence the
implemented governance structure and additional governance, or security measures implemented
in the blockchain project.
In a digital environment such as that of blockchain projects, with regulatory governance
methods, the social interactions and dynamics within the network may be overlooked. Therefore,
further exploring the idea of such managed ecosystems without opportunism can be investigated
in terms of blockchain. Additionally, the idea of highly networked industries making gains from
information sharing may also be prevalent within blockchain networks (Inkpen et al., 2019).
Blockchain projects in practice
Projects that fell under the scope of this research paper were similar in blockchain participant
behaviour as described in the article by Sherman (2017). More specifically, while lead
organisation influence was present in making the code for the blockchain project, it was not
adjusted when new participants joined pre-existing projects. New participants trusted to join
existing projects based on existing regulations. Project changes or adjustments were made only
when the project was revised for further development. Unless the project was ended or
abandoned, these blockchain projects continued indefinitely based on the originally written
project code. Consequently, the unique nature of these projects with a certain degree of
automated governance is taken into account while delving deeper into the theoretical background
on blockchain governance.
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The translucent hand perspective
The translucent hand entails a governance solution falling between the visible hand of the market
and invisible hand of company hierarchy (Altman et. al, 2021). This proposed governance
structure allows a varying level of governance implemented by an organisation, meaning that the
level of implemented governance measures may determine the level of translucency (Altman et.
al, 2021). This is an interesting concept in relation to blockchain governance since the locus of
control may be influenced by a lead organisation for a blockchain project but is automated for
the program to run automatically making this a case partly governed by both the visible hand of
the market and the invisible hand of the company hierarchy.
While Altman et.al explain the concept of managed ecosystems, this does not exactly apply to
blockchain cases as the locus of activity or value creation may or may not be actively led by
people outside the organisation in this case (Altman et. al, 2021). However, the concepts of
multiple governance mechanisms and incumbent transitions can be seen as relevant to the
blockchain case. This is because the incumbent transitions would refer to the adaptation of the
blockchain participants to the governance methods which are a part of the blockchain project as
opposed to the governance that would traditionally be enforced upon their firm and inter
organisational projects.
Blockchain projects have arguably an external locus of control, while it entails automated
regulation, it is only as efficient as the “expert” or joint effort that makes the program for
automated governance (Sherman, 2017). Locus of control in this case means the rules that would
be asserted for blockchain participants. As mentioned in the article by Sherman (2017), users
joining a blockchain project mostly comply with the pre-existing rules set by the lead
organisations of the blockchain project. While the lead organisations can influence the rules that
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make the blockchain project, in principle once the code is written, the project runs on its own
outside the immediate control of the blockchain lead organisation. Further applying this to the
model by Altman et.al (2020), as seen in appendix F, the external locus of control is also not
exactly comparable to the governance structures as seen in the upper left quadrant of the model.
In a blockchain context, multiple governance mechanisms may entail the choice to include layers
and pieces of additional security measures.
The invisible hand and natural selection
Here, the concept of natural selection implies that organisations in a group or ecosystem show
variability and the wealth of favourable variability can be learned by others for their own
improvement and advancement opportunities (Carey, 1998). In the blockchain context, the
importance of including this theory promoting self-regulating natural order may display the
downsides of naturally selective behaviour that may occur within blockchain projects or
networks. More clearly, a blockchain participant learning the “wealth” of an organisation that
makes it unique may lead to the loss of its competitive advantage. Moreover, the idea of other
participants possibly learning of their organisational information possibly leading to loss of
competitive advantage may be a legitimate concern for possible blockchain participants.
Therefore, this concerns the “visible” activity or the activity that is not automatically controlled
by blockchain code.
The theoretical perspective as explained above regarding the translucent hand and its ties to
natural selection through the invisible hand seem appropriate to describe the combination of the
nature of blockchain governance measures while addressing conscious competitiveness as
Darwinian.
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Blockchain Governance
The concepts of bounded rationality and opportunism must be considered for the purpose of
coordinating transactions amongst various organisations. Lumineau et.al (2021) explain
governance measures for coordination and collaboration through binding legal contracts and
relational mechanisms. Here, legal contracts would fall under the “visible hand” of the
organisation. On the other hand, self-regulated relational mechanisms fall under the invisible
spectrum of the market. Within blockchains, the complexity and added governance structures
may take place in the visible part of blockchain code. Relational mechanisms may comprise of
trust and relational norms, with more socially embedded organisations being more trustworthy
for the purposes of information exchange and reduced concerns about opportunistic behaviour by
collaborators. While Lumineau et.al (2021) separately classify blockchain governance as a self-
contained and automated system using formal rules, which are not legally enforced; they do not
make considerations for the level of governance measures enforced which may be of the
“visible” or “transparent” kind. Moreover, they emphasize that the identities of blockchain
participants do not matter. Contrastingly, the paper by Sherman (2017) describes the need for
knowing organisations as it involves joining existing blockchain projects without implementing
any changes for individual participants who join. This phenomenon of joining prominent projects
without demanding changes in security measures was also noticed in the projects studied for the
purpose of this paper and will be discussed further in the following sections.
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Research hypotheses
Drawing from the concept of the translucent hand and opportunism in transactions, the concepts
of competition, capabilities and additional governance measures can be considered. The article
by Sherman (2017) highlights the standardised transactions for governance associated with
blockchains, moreover, the theory of blockchain governance under the translucent hand theory as
described in the previous section describes the paradox of some level of centralisation in
decentralised blockchain projects. Consequently, this phenomenon may be described in terms of
security measures, absorptive capacity, Network embeddedness and competitive intensity. These
variables sufficiently describe the concept in terms of blockchains describing the possibility of
multiple governance mechanisms and concepts described from the theoretical framework. The
proposed hypotheses are further described below.
Safeguarding issues of blockchains
The issue of having a decentralised blockchain network while relying on a consultant or lead
organisation, among other variables shows how “translucent” an organisation can be. Mitigating
the issue of having no control over governance problems immediately once the automated
governance system is in motion may entail the addition of governance or security measures in
blockchain projects.
Lumineau et.al (2021) state that knowing participants is not required, however, they also contrast
this thought by stating that social relationships are a relevant factor for trust and coordination in
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projects. The possibility of opportunistic behaviour by every person in a network can destroy the
value of the network (Zeng & Chen, 2003). One participant in the blockchain could potentially
make information gains through blockchain participation. However, if every member of the
blockchain does the same, the trust participants would have in the blockchain itself would be
ruined (Zeng & Chen, 2003). Zeng & Chen (2003) The authors further explain problems such as
underinvestment in the alliance in case they do not receive equal value as their partners. In terms
of blockchains, one may recognise unequal value gains in the case of uneven power distribution
in the network (Murray et al., 2019; Shermin, 2017). Unequal power in a blockchain network
would not only mean holding more influence over others but also giving way to the possibility of
a “51% attack” (Quinou & Debonneuil, 2019). A 51% attack means that those participants who
control more than 51% of the blockchain project may launch an attack that can control how
transactions are written and invalidate the blockchain (Quinou & Debonneuil, 2019). Besides a
51% attack and consensus in a blockchain being swayed by influential parties, risks also lie in
the information or delayed data propagation (Zhang et al., 2020). The delayed information
reaching different participants of a blockchain can lead to the creation of different forks of
information being saved in the blockchain (Conti et al., 2018). While one blockchain continues
storing new blocks, an old fork may be tampered with (Conti et al., 2018). A “sibyl” attack may
also occur when fake participants are made and the same strategy as a 51% attack is attempted
(Erbguth & Morin, 2019).
The second risk associated with multiple partner alliances, as explained by Zeng & Chen (2003),
is the possibility of competitors misappropriating leaked information, which may lead to
participants overprotecting any exposed information during alliances. Similarly, this
overprotection and need for safeguarding may occur among partners in a blockchain alliance as
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their transaction information is revealed and an attack would cause them to be left out from the
invalidation of the blockchain.
The paper by Contractor (2019) explains the possibility of the optimal balance between openness
and secrecy for companies. This paper written in response to Inkpen et al.(2019) explains how
the paper by Inkpen and colleagues overestimates the value of knowledge leakage. While Inkpen
and colleagues argue that the benefits of knowledge sharing outweigh the costs, Contractor
(2019) states that in highly networked industries there may be a net benefit of knowledge
sharing. Furthermore, investing in excessive safeguarding measures may end up being very
expensive, invalidating the gains from lowered transaction costs of blockchain participation
(Inkpen et al., 2019). One must also consider that there is a difference between the willingness of
people wanting to participate in the blockchain to benefit from openness and transparency versus
the fact that they would also have to share their own information.
Considering these factors and referring back to the translucent hand theory, participants may
choose to add more or less governance or security measures while participating in a blockchain
project. Here the managers must decide how transparent they wish to be between gaining
information and reducing transaction costs through the involvement of blockchain technology or
adding extra governance measures for protecting their information.
Absorptive capacity
Conceptually, the concept of blockchains eradicates the opportunism problem through its
automated rule process (Shermin, 2017). However, the social wealth that can be picked up by
organisations operating in this market of automated governance can depend on the ability of a
company to absorb information. Drawing from the concept of companies in a free market ruled
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by the invisible hand, companies interacting with each other can also pick up information or
practices (Carey,1998). Absorptive capacity may be used to describe the ability of a firm to
draw information from participants in the market. Absorptive capacity can be defined as the
ability of a company to gather information and repurpose it for their own sustained competitive
advantage (Zahra & George, 2002).
The paper by Striukova (2007) suggests that the intellectual value is embedded in different
entities, systems or structures, and patents. Applying this to blockchains, the information shared
cannot be controlled since it takes place automatically, leaving such embedded intellectual value
vulnerable to attackers. Therefore, the governance of intellectual property such as that existing in
patents is imperative (Striukova, 2007). Managers may choose to take more stringent measures
to safeguard intellectual property, making the governance structure less transparent.
Being aware of the possible combinations of information or value gained from interacting in a
market may mean that firms are willing to be more transparent to gain such information for
competitive advantage. Companies that are capable of gaining such value through the market
may be less concerned about multiple governance measures as they could gain from the
automated governance system of blockchains. Based on these theories of intellectual property
and knowledge leakage, the following may be proposed: companies that have the ability to make
use of such available information and repurpose it for their own competitive advantage would be
more willing to share information. Opposingly, companies with low capabilities to repurpose the
information for their own advantage would be more hesitant to share their information and may
feel the need for more security measures.
Consequently, the following hypothesis was developed:
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H1: Companies with lower absorptive capacity are more likely to take additional safeguarding
measures.
Competitive intensity
Strategic alliance theory by Zeng & Chen (2003) further contributes that misappropriation of
information may allow individual benefit but diminishes value creation and destroys the
established partner cooperation. Furthermore, those who are aware of the knowledge leakage
taking place within the blockchain network may choose to approach this in a strategic manner
and create gains for their organisation (Alnuaimi & George, 2016). In Contrast, industries where
knowledge sharing is prevalent either through the rotation of employees or by the network, may
not feel as opposed to information sharing as compared to industries where information sharing
is less prevalent. Moreover, depending on the industry, the information shared may be more or
less sensitive and may be misused. Such sensitivity and competition in the market can be
described as competitive intensity.
Further, market uncertainty may have negative impacts on operating performance (Jones et.al,
1997). Under such an uncertain market, companies may make the conscious decision of
opportunism in the form of natural selection while interacting with firms in a market (Carey,
1998). However, this absorbed information may or may not be useful as individuals try to
compose a sustained competitive advantage.
Companies operating under such sensitive conditions may feel the need to have higher
safeguarding measures. Blockchain projects under such highly competitive environments may
feel the need to be less transparent as opposed to companies operating in low competitive
intensity environments. This may happen as blockchain participants may be exposed to more
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information about companies in their ecosystem as opposed to information they would normally
receive outside the blockchain project. Again, firms may see this as an opportunity to create a
sustained competitive advantage to survive in highly competitive industries (Alnuaimi & George,
2016).
Therefore, the following hypothesis is proposed:
H2: Companies with higher competitive intensity are more likely to take additional safeguarding
measures.
Firm network embeddedness
A firm can potentially have a better competitive advantage with a better bridging position in the
network (Cohen et.al, 1990). Moreover, the connection of networks can lead to the increase of an
organization's ability to learn. Therefore, the social value embedded in a blockchain network
could potentially be used as a competitive advantage by the recombination of information and
ideas that may be available in a blockchain network. However, an organisation that is more
embedded allows for a smoother transfer of knowledge and collaboration and would be
perceived as less opportunistic (Lumineau et.al, 2021).
Lumineau et.al (2021) propose that social embeddedness in relationships are an indicator for
trusting the reliability of potential partner companies. Moreover, the article by Shermin (2017)
further states that having the assurance of an established project may make companies feel more
at ease while participating in group efforts. Moreover, joining such blockchain projects may also
entail reputational incentives as interests would be aligned between the participants.
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Having a connected network could also imply that coordinating misuse of information on the
blockchain would be more difficult with social connectivity. This could possibly damage the
firm's reputation, keeping them from performing in such an opportunistic manner (Cohen et.al,
1990). The assurance of joining larger groups that are socially established or have reputational
benefits may put blockchain participants more at ease as opposed to less socially embedded
firms. While the social embeddedness of a company can be reassuring, having the ability to join
established companies for collaborating in blockchain may provide further psychological relief
for participants. Moreover, this implies joining a project associated with a more socially
embedded company triggers more transparency as firms would be less concerned about
opportunism. Hence, the following hypothesis is proposed:
H3: The stronger the firm embeddedness, the less likely the firm is to take safeguarding
measures.
The hypotheses formulated can be visualised in the following conceptual model presented in
figure 1.1 below.
Control variables
Considering factors that may influence safeguarding measures, the control variables of the
development stage, presence of competition in the network, inter-organisational data sharing
have been taken into account, based on theory adapted from Jones et.al, (1997) regarding social
ties, and the creation of value through networks. The development stage for a blockchain project
may actually entail multiple projects proposing different solutions to clients before an ongoing
self-sufficient solution is placed. The presence of competition may indicate if this project
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occurred in a participant group with apparent competitors. Lastly, the presence of inter-
organisational data sharing implies data is shared outside the organisation.
Conceptual model
Figure 1.1: Conceptual model on Network governance in blockchain projects.
The following relationships have been displayed in the model:
H1: Absorptive capacity is negatively related to safeguarding measures. Higher levels of
absorptive capacity trigger lesser precautions in terms of safeguarding measures in a blockchain
network.
H2: Competitive intensity is positively related to safeguarding measures. Higher levels of
competitive intensity would mean higher safeguarding measures before joining a blockchain
project.
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H3: Network embeddedness is negatively related to safeguarding measures. Larger lead
organisation networks imply more safeguarding measures before joining the blockchain network.
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Methodology
Study Measures
Even though blockchain research may be a relatively new field, many prominent network
theories have not been applied to this field yet. Therefore, this paper uses a theory testing
approach. The paper makes use of concepts proposed in the article by Shermin (2017) to describe
these factors that influence blockchain governance.
The research will be conducted at the firm level. Lead participants in the network would be
analysed for the study. Firstly, linear regression analyses will be conducted for the selected set of
companies to explore relationships between:
1. Competitive intensity and safeguarding measures
2. Absorptive capacity and safeguarding measures
3. Network embeddedness and safeguarding measures
Next, information understood through interviews will be taken into account for the purpose of
explaining observed relationships.
The following variable dimensions have been described with the use of academic articles and
guidance from the interviews of blockchain professionals.
Dependent variable safeguarding measures
As elaborated in the literature review section, in this study the variable safeguarding measures
are being defined as measures taken beyond the normal level of security or safeguarding in a
23
company while being a part of a blockchain (Zeng & Cheng, 2003). Furthermore, this would be
evaluated through questions inquiring about the number of measures the lead organisations took
for the project.
Lead organisations entail companies that largely invest or lead the direction of the blockchain
project, defining the scope of functions for other participating companies as well. Since the
automated process of blockchain governance is influenced by lead organisations, it is appropriate
to consider the measurement of the firm level variables such as network embeddedness and
absorptive capacity to assess the expected social dynamics and creative capabilities while
forming the automated governance system. The dependent variable was measured as the total
number of security measures to suitably indicate the degree to which an organisation takes up
safeguarding measures. The security measures refer to the translucent hands level of
transparency, the larger number of security measures making the translucent hand more
transparent (Altman et.al, 2021).
Independent variable network embeddedness
Network embeddedness entails the social ties and strength an organisation may have (Cohen &
Levinthal, 1990). This would be measured through the number of participants in a blockchain
network, firm age and their firm size. This is developed for Shermin (2017) and Lumineau et.al’s
suggestion that the social relational strength of a network can make it more trustworthy. For the
purpose of this paper, these factors describe the network richness and strength of a lead
organisation. Moreover, it describes this as larger firm sizes measured by total lead organisation
assets are expected to indicate the firm’s strength and reach within the network. Participant
numbers can be quite large when it is a blockchain with a public key or public access to
24
everyone, or a private blockchain where the participants who join are controlled (Quinou &
Debonneuil, 2019). For the purpose of a network based theoretical lens, the number of
participants in private blockchains will be counted to determine network size, and firm size
should add to their possible capabilities as a lead organisation. Firm age may further elaborate
the on level on firm embeddedness and the presence of pre-existing relationships that may aid in
the recombination of knowledge for the purpose of gaining competitive advantage.
Independent variable absorptive capacity
This will be determined by checking the value for the number of granted patent publications.
This paper focuses on determining the ability of a company to create their own intellectual
material, based on Striukova’s (2007) proposition of intellectual value being embedded in
various entities and Chohen et.al’s suggestion of R&D value producing innovation, measured in
granted patents rather than R&D investment to check innovation outcomes.
Independent variable competitive intensity
Industry competitiveness would be measured through how difficult it would be to enter a
particular industry depending on the country of origin of the lead organisation. This indicator for
world development adapted to assess the competition in the lead organisation industry indicates
how they approach their leading tasks in a blockchain network. This is adapted from the theory
of the invisible hand and natural selection by Carey (1998).
Control variables
Stage of development: This was collected through the survey in the various stages of project
development that occur as shown in Appendix A. Here, IBM participates as a third-party or
25
participant in the blockchain project and collaborates with potential clients for the purpose of
launching blockchain projects. These are:
● No development completed: The project did not go beyond the initial design thinking or
proposal phase.
● Proof of concept: An experimental representation of how the project would run.
● Pilot or production pilot: A pilot of how the project runs.
● Production: A running and fully functional project
● Other: Situations such as the progression of the project continuing in-house, with no
further third-party interactions.
Presence of competitive relationships and presence of inter-organisational data sharing: These
were also measured through the use of a binary variable as seen in Appendix A.
Data collection procedures
This research was conducted together with IBM, where 110 IBM blockchain project managers
were contacted for the purpose of conducting interviews. These project managers were asked to
verify contact information and recommend people for a cross-sectional survey. The survey was
conducted through online interviews using video calls where participants could both explain
which answers they would pick for the survey questions and provide the rationale for their
answers. The survey was then filled in in accordance with their answers. Survey questions
affiliated with this research can be found in appendix A.
26
Validity and reliability
The study avoids common method bias by only measuring the dependent variable of
safeguarding measures through the survey and uses external secondary data for measurement of
the independent variables. Two of the control variables have also been measured using the
survey. Data triangulation takes place from three different sources, being the World bank data for
world development indicators and Orbis data for patent and company size data in addition to the
survey data.
Analysis
Due to the nature of this study and confidentiality requirements, standardised information was
manually entered into the dataset, standard firm specific values were taken from the Orbis and
World bank databases. This study makes use of Stata SE17 for the analysis of the raw data.
The continuous dependent variable of the number of security measures that has a “count” nature
prompts the use of a Poisson regression in Stata. Given the skewed distribution due to the count
nature, the Poisson model is appropriate since the count of security measures range from 0 to 7.
The analysis is conducted through arranging descriptive statistics drawn from the raw data which
can be visualised in appendices B, C, D and E. Next, Stata is used to generate a pairwise
correlation with some descriptive statistics between the independent, dependent and control
variables as seen in Table 1 of the next section. Further, to find possible evidence to support the
hypotheses, a Poisson regression is conducted. Firstly, the dependent variable safeguarding
measures is run against the control variables for model 1. Next, the independent variable
measures are added sequentially for model 2, 3, and 4. These models are then used to discuss the
27
log pseudolikelihood, chi square test of model coefficients and the goodness of fit of the models
in the next chapter.
28
Results
Firstly, the distribution of projects per country can be seen in Table 1. Looking at the distribution
of the kind of blockchain projects from appendix B, it can be seen that the majority of projects
were proof of concepts which means that most projects made an estimation for the required
security measures at this stage. Only 23.3% of projects entailed ongoing autonomous governance
in the form of blockchain technology. Notably, since the largest share of technological maturity
is the “proof of concept” indicating that these projects have room for more participants and
security measures in the future before they are implemented. Appendix C shows that the majority
of the projects used event-based data meaning that all participants would receive information
related to a particular event within the blockchain network. Moreover, Appendix D indicates that
tracing information was the most popular use case and the different types of governance methods
centred around access restrictions followed by authentication, off-chain storage and data-sharing
specifications as seen in Appendix E.
Descriptive statistics and a correlation matrix are produced as seen in table 2. Furthermore, to
determine the validity of the hypotheses, a poisson regression is performed in four parts. Even
with multiple variables measured in a categorical manner, the method of probit regression was
not required as the data was converted into binary measures of “0” and “1”, a linear regression
would have been inappropriate considering the count nature of the dependent variable. The first
model measures the effects of the dependent variable against the control variables as seen in
Table 4 . Next, the independent variables are regressed for model 2. Finally, the effect and size
29
and validity of the relationships are discussed in the next section. Further meaning is derived
from the interview results as seen in appendices B, C, D and E.
Correlation and descriptive statistics
The descriptive statistics indicated that the 60 observations showed weak to moderate correlation
coefficients as seen in table 1. The statistics of mean, standard deviation, minimum and
maximum can be seen in table 1. The average blockchain project consisted of 6.14 participants.
Moreover, a statistically significant positive correlation can be seen between the presence of
competitive relationships and number of security measures at p<0.05 with r= 0.3152. Other
moderate correlation can be seen between the number of participants and security measures (r=
0.3569), presence of competition with the number of participants and data sharing in
organisations, and significant negative correlations with no development completed projects with
the number of security measures, data sharing and presence of competition as seen in table 1.
Furthermore, more development at production was positively correlated to participants, the
number of security measures, competition and the assets of the lead organisation. Finally,
Industry competitiveness seemed to be significantly correlated to firm age and patents granted.
These correlations are significant at 90 and 99% (p<0.05, p<0.01 and p<0.10). Given that none
of the correlation coefficients exceeded the value of 0.59, under the threshold of 0.6,
multicollinearity is not expected. Since the value of r=0.59 is quite close to the threshold, a VIF(
variance inflection factors) test is performed to completely rule out multicollinearity. As seen in
table 2, the mean VIF=3.44 , meaning multicollinearity can be ruled out based on the threshold
value of VIF=10.
30
Country Number of participants
Spain 2
Netherlands 4
Switizerland 3
United States 17
Lithuania 1
Norway 1
Japan 8
France 11
Germany 6
Phillipines 1
UAE 1
Poland 1
Ireland 1
Great Britain 1
India 1
Denmark 1
Total 60
Table 1: distribution of projects per country
31
32
Table 2. Correlation matrix and descriptive statistics. (Number of observations=60, Significant
levels at * p < 0.1; ** p < 0.05; ***p<0.01)
Table 3. Variance inflection factors
33
Regression results and hypothesis testing
The Poisson regression was first conducted with DV safeguarding measures and the control
variables.
Model 1
This model with The dependent variable security measures and control variables presence of
competition, data sharing between organisations and level of technological maturity. It can be
seen that with every value increase in the control variables, the difference in logs would increase
by a very small amount as seen in the coefficients in model 1 with the exception of no
development completed technological maturity. Unfortunately, these values were not significant
at 90%, 95% or 99%. Moreover, upon assessing the goodness of fit, both the pearson and
deviance goodness for fit values are statistically significant implying that the model is not a good
fit with deviance goodness of fit=91.62*** and pearson goodness of fit=71.15**. However, the
result of the chi square fit of the full model over the null model stands significant at p<0.01.
Model 2
Adding the constructs of Social embeddedness by number of participants, firm age and total
assets, small coefficients are once again noted. The values of total assets and firm age stand
significant at p<0.01, however these effects are very weak with their values being less than 0.001
as seen in table 4.
Next, the goodness of fit of the model was conducted. This model is not a good fit with deviance
goodness of fit=89.11*** and pearson goodness of fit=69.97**. However, the result of the chi
square fit of the complete model of model 2 over the null model stands significant at p<0.01.
34
Model 3
This model includes industry competitiveness in the model for the variable of competitiveness. It
can be seen that the variables depict weak effects. The effects of total assets and firm age are
again statistically significant at p<0.01 with the negative weak effect of the constant b being less
than 0.001. Industry competitiveness stands significant at p<0.05 with b=-0.0077 showing
another weak negative relationship.
This model is not a good fit with deviance goodness of fit=88.84*** and pearson goodness of
fit=69.68**. However, the result of the chi square fit of the complete model of model 3 over the
null model stands significant at p<0.01.
Model 4
Finally, patents granted publications is added for the independent variable of absorptive capacity.
Again total assets and firm age show weak negative relationships. The effect of industry
competitiveness is slightly stronger at b= -0.0105 and p<0.05.
The model is not a good fit with deviance goodness of fit=88.38*** and pearson goodness of
fit=68.18**. However, the result of the chi square fit of the complete model of model 4 over the
null model stands significant at p<0.01.
Noting no statistically strong significant results between competitive intensity, absorptive
capacity, network embeddedness and safeguarding measures while observing the statistically
significant correlations in table 1 the hypotheses can neither be confirmed or rejected at this
35
stage. Interesting correlations were seen in table 2 with the positive relationship between
competitive intensity and security measures; technological maturity and investment in security
measures as well as openness to share information with competition; lower technological
maturity and the lack of security measures and collaboration; and finally, the positive unexpected
relationship between industry competitiveness and patents, and firm age. However, these
relationships must be further explored considering correlation does not equate to causation. A
larger data-set would be required for future research to further explain the variation in the dataset
and possibly more significant regression results.
While more investigation is required to further understand the significant regression results, the
weak negative but statistically significant relationships for security measures with firm age and
total assets indicate the need for further investigation on hypothesis 3. Similarly, the negative
relationship between industry competitiveness and security measures indicate cause for
investigating hypothesis 2. Moreover, the surprising result of a positive relationship between
absorptive capacity and security measures must be investigated, giving cause to possibly reject
hypothesis 1.
36
(1) (2) (3) (4)
VARIABLES Totalsecuritymeasures Totalsecuritymeasures Totalsecuritymeasures Totalsecuritymeasures
Datatransaction -0.43 -0.46 -0.44 -0.44
(0.31) (0.32) (0.32) (0.32)
Competition 0.28 0.25 0.24 0.23
(0.20) (0.21) (0.21) (0.21)
Nodevelopmentcompleted -17.21 -17.51 -17.51 -17.65
(-1.11) (-1.28) (-1,28) (-1.36)
PoC -0.55 -0.56 -0.54 -0.52
(0.42) (0.45) (0.45) (0.45)
Pilotproductionpilot -0.18 -0.19 -0.17 -0.14
(0.45) (0.46) (0.46) (0.469)
Production 0.11 0.05 0.0901 0.0928
(0.42) (0.44) (0.439) (0.442)
Other 0.12 0.16 0.156 0.196
(0.65) (0.66) (0.661) (0.665)
Numberofparticipants 0.0059 0.0055 0.0059
(0.00449) (0.00455) (0.00458)
Totalassets -1.72e-13 -0.000049 -0.000091
(-7.21e-13)*** (-0.037)** (-0.0037)**
Firmage -3.51e-04 -4.95e-05 -9.18e-05
(0.0017)*** (0.0018)*** (0.0018)***
Industrycompetitiveness -0.00772 -0.0105
(0.0153)** (0.0157)**
Patentsgrantedpublications 1.05e-06
(1.50e-06)***
Constant 1.40 1.45 1.47 1.46
(0.57) (0.62) (0.62) (0.62)
Log-likelihood 46.79 49.30 49.56 50.03
Prob>chi2 0.00 0.00 0.00 0.00
Pseudo R-squared 0.17 0.18 0.18 0.18
N 60 60 60 60
Table 4: Regression analysis results (Number of observations=60, Significant levels at * p < 0.1;
** p < 0.05; ***p<0.01)
37
Further insights based on interviews
While the relationships could not be proven definitively, the interviews still provided interesting
insights for managers. This included them recommending safeguarding measures based on the
type of information shared within the network regardless of the presence or absence of
competitors. Adding to the interesting correlations, most managers did not consider security
measures as an important part of projects with lower technological maturity. Moreover, project
managers confirmed that projects in sensitive industries required the most security measures. The
security measures centred around the sensitivity of the project rather than the type of sensitive
data such as personal data as can be seen in Appendix E. Furthermore, many participants have
been adopting blockchain technology to test and integrate it into their organisations without any
overarching need. Finally, clients without an understanding of the technology were most likely to
stop their projects before they matured further. More importantly, many interviewees for larger
projects insisted that the blockchain projects themselves have no competitive behaviours, further
supporting hypothesis 3 on the strength of network embeddedness. However, the pairwise
correlation showed a positive correlation between the presence of competition and security
measures. Therefore, these could be interesting avenues for future research, as projects may try
to find a tradeoff between the competitiveness they see in the market and how socially embedded
the firm is.
38
Discussion and conclusion
This paper takes a step towards developing a solution for the dilemma between security and
transparency in blockchain networks. This paper takes a step in the direction of assessing both
older and newer governance theories against the changes that have come about with the
digitisation of connections and projects. This paper proposes to further look into Altman et.al’s
(2021) concept of the translucent hand with the idea of blockchain governance falling between
the self governed market and the directly governed firm up to an extent.
While the hypotheses cannot be confirmed at this stage, further investigation would be
appropriate especially for the variables of competition presence and network embeddedness.
Further investigations on this topic could perhaps assess the interaction between the competitive
intensity of the market and the social embeddedness of the lead organisation. While this paper
attempts to combine older network theories into blockchain technology many future avenues for
research still lie in this field as the concepts of new forms of open governance in the digital age
have not been researched thoroughly. The idea of gaining value in blockchain projects for
managers without data misuse will require further investigation.
Linking back to the discussion proposed by Contractor (2019), that there may be a small benefit
of knowledge sharing in highly networked industries, it seems that the projects with higher
number of participants were correlated to more security measures and competition, variables of
absorptive capacity and embeddedness. Moreover, the presence of competition indicates more
security measures. Therefore, the possibility of high competition environments supporting
possibly high absorptive capacities in, or higher competition in more socially embedded
environments possibly leading to higher security measures would be worth investigating.
39
The different layers of governance and different security measures while facing social
embeddedness and competition as seen in the results section could possibly challenge the
concept of clearly distinguishing between blockchain governance, contractual governance and
relational governance as seen by the paper of lumineau et.al (2020). While they suggest that
blockchain governance can severely alter the use of contractual governance and relational
governance, this paper still expects the combined use of them as layers of governance. Referring
to the translucent hand, I further suggest that transparency as a part of relational governance and
the visible hand as a part of contractual governance must be investigated. This especially takes
into mind projects where participants join a pre-existing blockchain system without making their
own additions to the blockchain code proposing a more fluid rather than discrete balance of
governance transparency and safeguarding.
Looking back at network theory and the patterns of interactions and exchange, the correlations
also indicated higher exchanges happening at the most technologically mature project stages with
corresponding correlations to competition presence and security measures. Again, this topic
would have to be further investigated to confirm the proposed hypotheses and provide rationale
for the proposed correlations.
Finally, this study makes many propositions that may be of interest to both researchers and
managers considering the many possibilities of organisational activities that can take place
through blockchain technology. The topics of security measures in relation to network
embeddedness and competitive intensity show promise for the purpose of future research which
is further built upon in the next section.
40
Research limitations and future research
Firstly, the research was supported by data from 60 interviews, however, more data would be
required for the provision of more robust results and to explain the variability in the data .
Secondly, I am aware that any future research in this field will require a sample that requires
more generalisability as the projects were concentrated in Europe and the US as seen in table 1.
Unfortunately, further information on the particular projects cannot be provided due to
confidentiality related reasons. Finally, while this research tries to take governance theory into
account to explain deviations in safeguarding measures, other theories should also be looked into
such as transaction cost economics . Lastly, some projects in the dataset were only proof of
concepts and some occurred around the personal network of one company. While the nature of
such projects is new to many companies to put into practice, data on projects which have reached
complete technological maturity with more variation in the number of blockchain participants
may provide more insight into this topic.
Company specifications cannot be shared for confidentiality purposes, but the majority of the
companies were medium-large businesses as indicated by their asset distributions. Relationships
in smaller blockchain networks have not been investigated yet.
This paper suggests primarily quantitative research, it is recommended that the number of
interviewees should be increased and a qualitative approach could be further investigated to
understand and possibly explain the observed correlations further.
While the differences in technological majority were controlled, the progression of blockchain
projects over the different phases and changes in safeguarding measures as the projects grew
41
would be interesting to investigate. As many clients choose to have blockchains for the networks
of singular companies, the information safeguarding, and sharing would be intriguing to
research. The concepts of competition and social embeddedness under the theory of the
translucent hand and where blockchain governance falls within managed ecosystems should be
further investigated (Altman et. al, 2021). Furthermore, the paper by Altman et.al (2021) also
emphasizes the lack of research in the field of external loci of control and governance, also
providing reason to further investigate where the governance of such blockchain or
technologically related projects fall, especially if the scope of organisations can range from a
single organisation to large networks of multiple organisations. Finally, the infusion of social
interaction and blockchain technology could be investigated in terms of how they will change
corporate boundaries in the future (Lumineau et.al, 2020; Shermin, 2017).
42
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Appendices
Appendix A
IBM blockchain survey: relevant survey questions
46
Appendix B
Level of technological maturity of projects
47
Appendix C
Type of information shared
48
Appendix D
Type of project use cases
Appendix E
Security measures used
49
50
Appendix F
Governance structures: control and activity dimensions Altman et.al (2021)
Figure 1.1 Governance structures: control and activity dimensions as seen in the paper by Altman
et.al (2021)