Strategies for Supporting Blockchain Technologies to
Enable Resilient Systems
Section 1: Foundation of the Study
Background of the Problem
Many leaders and technology professionals view blockchain as the next
significant technological advancement after the internet. Blockchain is a shared,
decentralized, secure, and unchangeable digital ledger that brings increased trust and
efficiency to business networks (Weber, 2018). Some popular cryptocurrency
technologies that run on blockchains include Bitcoin and Ethereum. Enterprise
blockchains are hailed as the key to secure and transparent processing of complex
transactions within and between organizations (Goldsby & Hanisch, 2022). The resiliency
of these distributed networks is one of the benefits many technologists wish to explore
within existing platforms. The potential losses from downtime include hourly costs of
information technology (IT) service outages ranging from hundreds of thousands to even
millions of U.S. dollars (Wang & Franke, 2020). With the potential resiliency that
blockchain technologies can offer existing platforms, IT professionals must have a solid
understanding of the strategies needed to support these technologies, especially in health
care and supply chain systems. In this study, I explored the strategies enabling IT
professionals to use blockchain technologies to support system resiliency.
Problem Statement
IT professionals are responsible for ensuring resiliency within the platforms that
they support. However, the existing technologies that organizations use are still resulting
in outages. For example, the U.S. economy had a US$ 20-55 billion loss due to severe
weather-related outages from 2003 to 2012 (Taimoor et al., 2020). When considering the
types of systems that could benefit from the resiliency built into blockchain technologies,
the health care sector suffers from inefficiencies in data handling due to resiliency and
data sharing between organizations (Alzahrani et al., 2022). The general IT problem that
prompted me to search the literature is that many organizations lack strategies that enable
IT professionals to use blockchain technologies to support system resiliency. The specific
IT problem is that some IT professionals lack strategies to support blockchain
technologies to enable resilient systems.
Purpose Statement
This qualitative, multiple case study was conducted to examine the strategies IT
professionals use to support blockchain technologies to enable resilient systems. The
population group of this study is IT professionals in the blockchain industry from the
development and infrastructure teams within the United States. The findings from this
study may benefit organizations by showing examples of resiliency gaps within existing
IT systems and the potential to use blockchain technology to mitigate the risk. This may
also indicate the need for business leaders to build a resilient IT architecture that
addresses the potential gaps in the IT infrastructure and processes. Social change includes
reducing the downtime of vital information technology platforms, such as hospital
systems, critical supply chains, and utility services. Social change may also involve shifts
in consumer behavior, evolving societal expectations, changes in regulations and policy,
or emerging technological trends and innovations.
Nature of the Study
When considering the appropriate research method, I looked at qualitative,
quantitative, and mixed methods. I thought of these approaches in the context of my
study. As a result of my analysis, I determined that a qualitative research method was the
best fit for my study. This approach has a rich history of helping researchers appreciate
revelatory cases, build grounded theories, and coin new concepts to describe emerging
phenomena (Monteiro et al., 2022). When harnessed to their full potential, qualitative
research methods support theorizing, the problematization of rigid or engrained ways of
thinking, questioning of taken-for-granted knowledge, exploration of little-known
phenomena, samples, or context, and co-creation of learning and sense-making, among
many other purposes (Köhler et al., 2022). In other words, engaging qualitative
methodology allows for expanding the field with research questions that are more general
and open than adjusting the emerging story throughout data collection as new information
comes forward (Clare, 2022). In contrast, by integrating qualitative and quantitative
procedures, mixed methods research offers the power of numbers and stories for
investigating complex social and behavioral questions (Hou, 2021). Mixed-method
research is a quantitative methodology that requires countable research objects, whereas
qualitative methodology describes and interprets its research objects (Stoecker & Avila,
2021). I chose a qualitative study over a mixed method study because it allowed for a
deeper, more detailed exploration of the subjective experiences and meanings, which
were critical for understanding the nuances of the research problem.
I chose a multiple case study as the most appropriate for my research topic. A case
study is used to explore a real-time phenomenon within its naturally occurring context,
considering that context will create a difference (Stoecker & Avila, 2021). The case study
approach facilitates the investigation and understanding of the underlying principles in
the real-world phenomena involved in constructing the future vision in the backcasting
study (Aalbers et al., 2020). The case study design supports my research goals because I
intended to understand the resiliency practices of IT professionals.
I also considered other qualitative approaches like ethnography, phenomenology,
and narrative research. The ethnography approach is used to explore complex cultural
norms and phenomena through long-term engagement in the field of research
(Andreassen et al., 2020). My research focused on IT professionals’ experience
supporting resilience, which is unrelated to cultural norms. Additionally, phenomenology
focuses on the experiences of individuals, but I was not focused on the lived experiences
but rather the resiliency practices of IT professionals. The narrative design systematically
codes individual differences in how they tell their stories about significant life events to
understand how they create meaning and purpose (Grysman & Lodi-Smith, 2019). My
study did not focus on an individual’s life but on their professional technology
experience.
Research Question
What strategies do IT professionals use to support blockchain technologies to
enable resilient systems?
Interview Questions
1. What is your current role with your company?
2. How significant is IT resiliency to your company?
3. How does your current role contribute to resiliency?
4. Are you familiar with distributed blockchain networks?
5. Are you familiar with the concepts of smart contracts on blockchain
networks?
6. What are resiliency issues you have encountered in the past?
7. What are your responsibilities when a resiliency event occurs?
8. What are the impacts of these resiliency events?
9. How do you think blockchain platforms can resolve these resiliency issues?
10. Why do you think these resiliency events occur?
11. What type of architecture is used within these platforms to enable resiliency?
12. Why would you consider or not consider blockchain technology a solution to
resiliency issues?
13. What procedures should organizations consider when migrating to blockchain
technologies?
14. Are there any other thoughts you have on this topic?
Theoretical or Conceptual Framework
The conceptual framework I applied to my study was the change management
(change iceberg) theory, developed by Kruger. The logical connections between the
framework presented and the nature of my study include the challenges IT professionals
face when adopting new technologies within organizations, such as blockchain. It
requires massive organizational changes to adopt new technologies like blockchain. This
change must be initiated at the top of leadership to profoundly alter the organizations’
underlying technologies and directly impact the management of perceptions and power
and politics management (Kruger, 2022). In this context, leadership is crucial in
addressing overt challenges and instigating and sustaining transformative shifts in values
and principles, ensuring successful adoption and alignment with the new technological
paradigm (Bedrii, 2020). Within this submerged domain, leadership emerges as a pivotal
force, with the meticulous orchestration of the overt technological transition and the
concurrent management of subterranean shifts in organizational perceptions and politics.
Within this underlying layer, comprised of attitudes, fears, and organizational culture,
significant challenges to, or facilitators of, technological adoption reside. One of the key
benefits of blockchain technology could be the resiliency they build into systems.
However, IT professionals will need to have strategies to support blockchain
technologies, and this may only be accomplished by leadership influence from the
perspective of management of perceptions and power and politics management.
Definition of Terms
Blockchain: Blockchain is a linked arrangement of records, called blocks, each
block stores the previous block’s hash, timestamp, and transactions, and the instance of
linked blocks are replicated on every node in a network (Sreenu et al., 2022).
Bitcoin: Bitcoin blockchain application is a public peer-to-peer payment
application that stores the transaction history on a digital blockchain database and is
independent of an intermediary, such as a national bank (Mattke et al., 2021).
Cryptocurrencies: A digital cash that uses cryptography to secure its transactions
and verify the transfer of digital assets through blockchain and over the internet without
using a centralized banking system (Andriole, 2020).
Digital ledger: A record of transactions maintained by consensus among a
network of peer-to-peer nodes that may be geographically dispersed (Kuhn et al., 2019).
Ethereum: Ethereum is the successor to Bitcoin and is a decentralized, censorship‐
resistant, incorruptible platform that runs on smart contracts (Sabalionis et al., 2021).
Smart contracts: Smart contracts are deterministic computer programs that may
be invoked when a transaction is recorded on the blockchain, affecting the transaction’s
outcome (Neiheiseret et al., 2023).
Assumptions, Limitations, and Delimitations
Assumptions
Assumptions are some aspects of a topic or research that do not have evidence of
validity (Helmich et al., 2015; Hufford, 1996). In this study, I assumed the IT
professionals I interviewed have experience supporting infrastructure and developing
applications within blockchain technologies. This experience would lead to lessons on
how they enabled resiliency in these platforms. I also assumed that they would participate
in a 1-hour interview and know existing strategies to increase resiliency in systems.
Another assumption I made is that companies would grant me access to documentation
showing resiliency strategies in their organizations.
Limitations
When considering assumptions, researchers usually have control over this aspect.
However, with a limitation, the researcher does not have control, which may directly
impact the study. Limitations of any study concerned potential weaknesses that were
usually out of the researcher’s control and were closely associated with the chosen
research design (Theofanidis & Fountouki, 2019). One of the risks of a qualitative study
is that some participants might have answered the interview questions in a manner that
pleased the researcher, which is considered a limitation in case study research (Yin,
2014). Since I performed a multiple case study with four participants, this was a
limitation because I might not have obtained enough research data.
Delimitations
The use of delimitations in my study ensured that my research was focused while
also reinforcing my objectives. Delimitations are the boundaries or limits of a
researcher’s work so that the study’s aims and objectives do not become impossible to
achieve (Theofanidis & Fountouki, 2019). One of the delimitations in my study was that I
only performed four cases with IT professionals from the development and infrastructure
teams. These IT professionals had experience supporting enterprise applications and were
restricted to the United States. Another delimitation was that the IT professionals were
required to have at least eight of experience supporting enterprise applications with
blockchain experience. I explored IT professionals’ strategies to enable resilient systems.
Significance of the Study
Contribution to Information Technology Practice
This study was significant because the results provide examples of resiliency gaps
within existing IT systems and the potential to use blockchain technology to mitigate the
risk. The results indicated the need for business leaders to build a resilient IT architecture
addressing potential IT infrastructure and processes gaps. This led to support strategies
for blockchain technologies to enable resilient systems and boosted the body of
knowledge within organizations.
The change management theory, often called the change iceberg, underscores the
importance of looking beyond the apparent, superficial aspects of organizational change.
Though the observable changes—like those within executive leadership—are usually
measured in cost, quality, and time, the theory posits that deeper, hidden aspects play a
critical role in successful change implementation. These less visible facets, which include
shifts in teams’ behaviors and values, can significantly influence the redistribution of
power and political dynamics within the organization. This understanding is crucial,
especially when considering the adoption of novel technologies like blockchain, which
promises operational efficiency and demands a transformation in underlying
organizational culture and values. Grounded in Kruger’s change management principles,
organizations can navigate the multifaceted challenges of change, ensuring surface-level
and profound adjustments align for greater resilience (Bedrii, 2020).
Implications for Social Change
This study provides best practices for supporting resilient platforms using
blockchain technology. Some of the industries that could benefit from this enhanced
resiliency include health care, vital supply chains, and utility services. For instance,
securely storing personal health information is crucial to ensuring patients receive quality
care in health care settings. Blockchain technologies could lead to more resilient
platforms as the technology is distributed across numerous nodes within an organization.
Personal health records could be securely shared among various organizations, resulting
in higher care since health care providers can access a complete patient history. Patients
and health care organizations are frustrated by the multiple obstacles in obtaining current,
real-time patient information (Alzahrani et al., 2022).
Another industry that could benefit from the resiliency of blockchain technology
is critical supply chain systems. One example of such a system is a vaccine delivery
network for medical facilities. These supply chain systems necessitate the transportation
of vaccines in temperature-controlled vehicles. Blockchain technology could help ensure
vaccines are delivered on time over vast areas, such as the United States. According to
the Department of Health and Human Services, 7 billion people require, on average, one
to two doses, totaling 15 billion doses for equitable distribution worldwide (Wang et al.,
2020). Amidst this, vaccine wastage amounts to 20 to 30 percent due to cold storage and
logistics disruptions during transit (Gupta et al., 2022). The social impact highlights the
importance of the resiliency of critical data used in health care and critical supply chain
management systems, as well as the potential for public blockchains to facilitate reliable
data retrieval, ultimately benefiting society as a whole.
A Review of the Professional and Academic Literature
In gathering the critical literature for this study, I considered the technology of
blockchain and the objective of using blockchain to increase resiliency in existing
applications. This led me to focus on two important keywords: blockchain and resiliency.
Utilizing these keywords, I collected relevant literature from various sources, including
the Walden University Library, Google Scholar, OpenAI, and references from other
academic papers. I focused primarily on peer-reviewed journal articles published within
the last 5 years. However, there were instances in the research when I referred to books
within the Walden University curriculum and articles older than 5 years to provide a
clear, foundational understanding of a concept rather than to examine a phenomenon
within business or technology. This comprehensive approach to literature gathering
ensured a well-rounded knowledge of the subject matter and provided a solid foundation
for further analysis and discussion.
In total, I collected 161 articles and 14 books for the literature review, of which
148 were peer-reviewed articles, using the Ulrich search engine to verify their
authenticity. As stated earlier, my primary key terms were resiliency and blockchain.
Numerous articles focused on one of the topics but not necessarily both within a single
work. More broad terms used to find relevant articles included change management
theory, downtime, change iceberg, and strategies. To refine the search, I employed these
terms: blockchain applications, enterprise platforms, project management, support, IT
support, operations, organizational strategy, and outages. While searching with these
terms, I identified a recurring theme: Organizations had to change the underlying
technology to address weaknesses within enterprise platforms. This theme was prominent
within the health care, supply chain, and utility industries, where system uptime is crucial
for meeting user needs. The overarching theme discovered within these articles is that
current enterprise systems are not adequately addressing users’ needs in terms of
resiliency, and IT professionals lack the strategies to support new technologies that could
potentially resolve this issue. This insight highlights the importance of developing
effective strategies and embracing innovative technologies to enhance resiliency across
various industries.
This literature review allowed me to examine existing enterprise systems and the
ways in which IT professionals support these systems from both development and
infrastructure teams’ perspectives. Drawing on my experience supporting applications
from an infrastructure standpoint, I ensured that the strategies discussed were viable and
executable within an enterprise organization. The literature review is divided into three
sections. The first part delves into the change management theory and the adoption of
new technology, the second part offers an overview of blockchain technology and its
existing applications, and the third part investigates current resiliency practices and how
blockchain could enhance resiliency. These three sections collectively address the change
management theory and its potential role in driving organizational changes toward
utilizing blockchain technology to support resilient systems. This comprehensive analysis
demonstrates the significance of understanding and adopting new technologies, such as
blockchain, in strengthening the resiliency of enterprise systems in various sectors.
Change Management Theory and Organizations
The change management theory, also known as the change management iceberg,
was initially proposed by Kruger (Bedrii, 2020). According to F. Kruger’s observations,
many project managers focus primarily on the visible part, overlooking the fact that the
main levers of political power, project constraints, and group dynamics do not lie on the
surface (Bedrii, 2020). The surface level encompasses the management of costs, quality,
and time. In contrast, at the deep control level, management of changes and
implementations occurs, including perceptions and culture, power, and political
dynamics. Fundamental changes necessitate profound shifts in team members’ behavior
and values, which, in turn, affect the redistribution of power. A fuzzy evaluation
approach, integrated into the change management process, can effectively navigate the
subtleties and the “hidden” elements beneath the project’s surface (Cragg & Chraibi,
2020; Vlasenko et al., 2019). By incorporating such nuanced assessment techniques,
project managers can gain a more comprehensive understanding of the factors influencing
the success of change initiatives, thereby improving their ability to manage complex
projects.
Kruger’s change management theory is a valuable framework for understanding
and managing change within organizations. By considering both the visible and hidden
aspects of the iceberg, organizations can develop more effective change strategies and
enhance the likelihood of success. This comprehensive approach to change management
can help organizations adapt to new challenges, improve overall performance, and foster
a culture of continuous improvement and growth.
The three aspects of the change management iceberg visible to leadership and
project resources are time, cost, and quality. Time schedule control in projects is often
perceived as activities carried out at the beginning of a project with limited information
that can accurately predict each detailed activity’s duration (Fewings & Henjewele,
2019). The time aspect is tracked when determining the progress of an initiative or
project. Further, time management is a cluster of behavioral skills essential for the
organization regarding project execution; empirical evidence suggests that effective time
management is associated with strategies that allow individuals to negotiate competing
demands (Adams & Blair, 2019). Time management can also be described as the
selforganization of people toward successful career development and identifying
opportunities and ways of self-organization for initiatives (Gladkova & Gordeev, 2022).
Furthermore, time management does not require a person to learn to do as many things as
possible in a short period, but it instead ensures that the person does what needs to be
done, addressing the issues that require attention (Bucata et al., 2021). These
interpretations of time management consider the behavioral aspects of completing either a
project or an initiative. Though these elements of time may be necessary for the success
of a project, it is important to balance competing aspects such as communication and
project resources. Adopting a holistic approach to time management can help
organizations enhance their productivity and optimize resources.
Quality is another aspect visible on the surface within the change management
theory. Quality can be defined as the totality of characteristics of an entity that bear on its
ability to satisfy stated or implied needs; in simpler terms, quality refers to “fitness for
use” or “meeting or exceeding customer expectations” (Kerzner, 2017). Quality can also
be described as the process of ensuring that the project delivers the expected results and
meets the requirements and expectations of the stakeholders (Mishra et al., 2020).
Maintaining high-quality standards is essential for the successful implementation of
projects, as it contributes to stakeholder satisfaction and the overall value of the project
outcomes. Furthermore, quality management in projects often involves setting clear
objectives, establishing suitable processes, and continuously monitoring and improving
performance. By prioritizing quality, organizations can minimize risks, reduce costs, and
enhance their reputation in the long term, ultimately leading to more successful projects
and satisfied stakeholders.
The final aspect on the surface of the change management theory iceberg is cost.
Cost management encompasses the processes required to ensure a project is completed
within the approved budget, which includes resource planning, cost estimation,
budgeting, and cost control (Project Management Institute, 2017). In the context of the
change management theory, understanding and managing project costs is essential for
successfully implementing change initiatives within organizations (Krueger, 2017).
Effective cost management can help organizations minimize risks associated with project
overruns and enhance overall efficiency in the change process (Kerzner, 2017). Visible
cost elements, such as labor, materials, and equipment, are relatively straightforward to
quantify and manage. However, hidden cost elements, such as the impact of change on
organizational culture, power dynamics, and employee morale, can be more challenging
to measure and control (Leflar, 2021). Organizations should be aware of the change
process’s potential direct (e.g., personnel, technology) and indirect (e.g., lost productivity,
turnover) costs when implementing change initiatives (Mishra et al., 2020). To effectively
manage project costs concerning the change management theory, organizations should
adopt a comprehensive approach that considers both the visible and hidden aspects of
change:
1. Establish a realistic project budget: A well-defined budget should consider the
direct and indirect costs of the change initiative, including the potential impact
on organizational culture and employee morale (Project Management
Institute, 2017).
2. Implement effective cost control measures: Regular monitoring and control of
project costs can help organizations identify potential issues early in the
change process, enabling them to take corrective action and minimize the risk
of cost overruns (Kerzner, 2017).
3. Engage stakeholders in the change process: By involving stakeholders in the
development and implementation of change initiatives, organizations can
foster a sense of ownership and commitment, which can help reduce
resistance to change and minimize indirect costs associated with employee
turnover and lost productivity (Zacharias et al., 2021).
4. Foster a culture of continuous improvement: Encouraging continuous learning
and progress can help organizations identify opportunities for cost
optimization and enhance overall efficiency in the change process (Mishra et
al., 2020).
By adopting a comprehensive approach that considers the visible and hidden aspects of
change, organizations can better manage project costs, minimize risks, and enhance
overall project success.
In addition to time management, quality, and cost, the hidden layer of the iceberg
comprises cultural issues within an organization. Culture is a unique characteristic of
human groups created to fulfill the basic need for finding shared meanings of events
(Zacharias et al., 2021). Organizational culture is a pattern of basic assumptions invented,
discovered, or developed by a given group (Duan et al., 2023). As the group learns to
cope with its problems of external adaptations and internal integration, that approach has
is taught to new members as the correct way to perceive, think, and feel about these
problems. This aspect of change management theory can be crucial to the success of a
project or initiative within an organization. However, some leaders and project resources
may not understand what makes a project or initiative successful. The leading causes of
project failures include lack of commitment by top management, resistance to change,
inadequate rewards and recognition mechanisms, inconsistent monitoring and control of
the projects, and poor communication (Antony et al., 2022). Despite meeting cost, time,
and quality criteria, projects can still suffer from stakeholder dissatisfaction, misaligned
expectations, and limited benefits realization (Atkinson, 1999). Organizations must
recognize the importance of addressing cultural issues and fostering a positive work
environment, which can contribute significantly to successfully implementing change
initiatives and overall performance.
Change Management Theory and Information Technology
Change management theory may be a critical aspect of successful Information
Technology (IT) implementation, as it assists organizations in navigating the complex
process of adopting new technologies. Effective change management practices consider
the human factor and organizational dynamics, recognizing that technology adoption is
not merely a technical process but also involves shifts in corporate culture and individual
behaviors (Madsen et al., 2020). As explained by Špundak & Šeric (2019), change
management practices are essential for achieving desired results in IT implementation, as
they address the people side of change, helping to overcome resistance and fostering a
positive attitude towards new technology.
Adopting new technologies may require a comprehensive understanding of the
interplay between various factors, such as user acceptance, training, and support.
Technology Acceptance Model is a widely used framework to explain how individuals
accept and use new technologies, emphasizing perceived usefulness and ease of use as the
primary determinants of technology acceptance (Tarhini et al., 2021). Employing TAM
within the context of change management theory can help organizations identify potential
barriers and enablers to technology adoption, enabling them to design targeted
interventions that facilitate a smoother transition to new IT systems (Hosseini et al.,
2020).
In a study by Tiron-Tudor et al. (2021), this fusion of agile change management
principles and change management theory is further explored in the context of
accountancy organizations implementing blockchain technology. Their systematic
literature review underscores the importance of agile principles in managing change,
particularly in navigating the complexities of adopting cutting-edge technologies such as
blockchain. They echo Denning’s (2020) perspective on the value of cross-functional
teams, iterative planning, and continuous feedback loops, emphasizing how these
principles foster a culture of learning, adaptation, and innovation. Their findings suggest
that by integrating these agile principles with change management practices, accountancy
organizations, and potentially others, can better align technology implementations with
strategic goals, enhancing the overall effectiveness and value of such initiatives.
Change management theory may be crucial in successful IT implementation by
helping organizations navigate the complexities of adopting new technologies. It
addresses technology adoption’s human and organizational aspects, focusing on
overcoming resistance and fostering a positive attitude towards new technology. The
technology acceptance model can be employed within the change management theory
context to identify barriers and enablers to technology adoption, allowing for targeted
interventions and smoother transitions to new IT systems. The agile approach to change
management has gained prominence in IT for its flexibility and responsiveness to
evolving technology and market demands, emphasizing cross-functional teams, iterative
planning, and continuous feedback loops. By integrating agile principles with change
management theory, organizations can successfully adopt new technologies while
aligning with strategic goals and enhancing IT implementation effectiveness.
Supporting Theories
To better understand the change management theory by Kruger, let’s discuss some
supporting theories. The first supporting theory is Lewin’s change management Model.
Kurt Lewin’s model emphasizes three main stages of change - Unfreeze, Change, and
Refreeze (Islam, 2023). The model emphasizes the need to prepare an organization for
change, implement the difference, and solidify the organizational culture shift (Islam,
2023). Lewin’s Change Management Model posits that successful change occurs by
unfreezing the existing equilibrium, moving to a new state, and then refreezing the
system in the desired shape, embedding the change within the organization’s structures,
processes, and culture (Serrat, 2017). In the context of organizational change, Lewin’s
model of change has been widely used as a basis for understanding change processes and
designing change interventions (Bărbulescu & Boitan, 2019). Lewin’s Change
Management Model and Kruger’s change management theory share similarities in their
organizational approach to managing change. Both theories emphasize the importance of
addressing barriers to change and recognizing that change is a process that requires
attention at different stages. As this relates to adopting new technologies such as
blockchain in an organization, it may be vital to address the barriers above with these two
frameworks to change the enterprise applications.
Another theory similar to the change management theory by Kruger is Kotter’s
8step change model. This theory offers a step-by-step approach to managing
organizational change. The eight steps include creating a sense of urgency, forming a
powerful coalition, creating a vision for change, communicating the vision, removing
obstacles, creating short-term wins, building on the change, and anchoring the change in
the corporate culture (Haas et al., 2019). A well-known change management model is
Kotter’s 8-Step Change Model, which includes: (1) creating a sense of urgency; (2)
forming a guiding coalition; (3) creating a vision and strategy; (4) communicating the
change vision; (5) empowering broad-based action; (6) generating short-term wins; (7)
consolidating gains and producing more change; and (8) anchoring new approaches in the
culture (Raineri, 2017). According to Ali et al. (2020), Kotter’s 8-Step Change Model is a
widely recognized framework for implementing organizational change.
Kotter’s 8-Step Change Model and the change management theory by Kruger
address the process of managing change within organizations. However, they approach
the topic from different perspectives and offer other frameworks for facilitating change.
Kruger’s change management theory focuses on identifying and overcoming barriers to
change within organizations. It highlights the importance of understanding and
addressing visible (cost, quality, and time) and invisible (perceptions, beliefs, and power
dynamics) barriers to facilitate successful change initiatives. On the other hand, Kotter’s
8-Step Change Model provides a more structured, step-by-step approach to implementing
change. It emphasizes the importance of creating a sense of urgency, developing a clear
vision and strategy, and securing buy-in from various stakeholders. The model also
consolidates gains and embeds change within the organization’s culture. While both
models aim to help organizations navigate change, their emphasis and approach differ.
Kruger’s change management theory focuses on identifying and addressing barriers to
change, while Kotter’s 8-Step Change Model provides a more detailed, step-by-step
process for implementing change. In practice, organizations may find value in combining
elements of both models to create a more comprehensive change management strategy.
From the perspective of changing the technical landscape of an organization, the change
management theory by Kruger is focused on barriers that may better suit the adoption of
new technologies such as blockchain.
Yet another theory that is similar to Kruger’s theory is the ADKAR Model.
ADKAR is an acronym representing the five sequential building blocks individuals
experience during successful change (Hiatt & Creasey, 2018). The ADKAR model stands
for Awareness, Desire, Knowledge, Ability, and Reinforcement. This model focuses on
individual and organizational change, emphasizing the need to address each component
for successful implementation. Bhattacharya and Kaur (2019) argue The ADKAR Model
is a practical and goal-oriented change management framework that helps individuals and
organizations to manage change effectively.
The ADKAR Model and Kruger’s change management theory emphasize
managing and facilitating organizational change but approach the subject differently.
While both theories address the challenge of managing change in organizations, Kruger’s
change management theory concentrates on identifying and overcoming barriers to
change, while the ADKAR Model emphasizes the individual’s experience and
progression through the change process. These theories can complement each other, as
understanding and addressing individual and organizational barriers to change are crucial
for successful implementation. Again these theories may be critical to changing the
technology within an organization to ensure high resiliency and meet a user’s needs more
wholly.
Another theory that supports the change management theory is Bridges’
Transition Model. Developed by William Bridges, this model focuses on people’s
psychological transitions during change; the model consists of three stages - Ending,
Neutral Zone, and New Beginning - and aims to help organizations manage the human
aspects of change (Hemmeter et al., 2015). According to Fernandez and Shaw (2017),
organizational change will not be successful unless individuals transition through each
stage, adjusting to the new environment and their roles within the organization.
Mikkelsen and Plotnikof (2021) describe the Bridges’ Transition Model as focusing on
the psychological aspects of change, emphasizing the need to manage the emotions and
reactions of people during a transition. While both models aim to facilitate change within
organizations, Kruger’s change management theory targets organizational barriers and
structures, while Bridges’ Transition Model emphasizes the individual experience and
psychological aspects of change. The lean toward Kruger’s theory is present within the
technology space since barriers from the structural level may be more beneficial in
comparison to an individual.
The last theory to discuss is McKinsey 7S Framework and how it supports the
change management theory by Kruger. Tom Peters and Robert Waterman developed the
McKinsey 7S Framework, and this model addresses seven critical aspects of an
organization that need to be aligned for successful change: Strategy, Structure, Systems,
Shared Values, Skills, Style, and Staff (Subiyanto, R., & Hatammimi, J., 2023). The
framework highlights the interconnectedness of these elements and the need for a broad
approach to change management. Razali et al. (2018) argue the model posits that an
organization’s success depends on the alignment and interdependence of these factors. By
focusing on the seven elements, leaders can take a holistic view of their organization,
understanding how changes in one area may affect others (Zhang, Y., & Liu, Y. (2017).
Furthermore, Al-Swidi and Al-Hosam (2018) contend that this framework suggests that
these seven elements must be aligned and mutually reinforcing for an organization to
perform well.
Both models encourage a holistic view of organizational change, recognizing that
addressing barriers or aligning elements in isolation may not be sufficient for achieving
the desired outcome. The McKinsey 7S framework can be seen as complementary to
Kruger’s change management theory, as it provides a more detailed roadmap for
assessing and aligning an organization’s various components during change initiatives.
Organizations can more effectively plan and execute change initiatives by considering
both the barriers to change identified by Kruger’s theory and the alignment of the seven
elements in the McKinsey 7S Framework.
In order to better understand the change management theory by Kruger, it’s
essential to discuss supporting theories, such as Lewin’s Change Management Model,
Kotter’s 8-Step Change Model, the ADKAR Model, Bridges’ Transition Model, and the
McKinsey 7S Framework. Lewin’s model emphasizes three main stages of change:
Unfreeze, Change, and Refreeze, which prepares an organization for change, implements
the change, and solidifies the organizational culture shift (Bărbulescu & Boitan, 2019;
Serrat, 2017). Kotter’s 8-Step Change Model offers a structured approach to managing
organizational change, focusing on urgency, vision, communication, and anchoring
change within the corporate culture (Ali et al., 2020; Raineri, 2017).
The ADKAR Model, focusing on Awareness, Desire, Knowledge, Ability, and
Reinforcement, highlights the importance of addressing each component for successful
change implementation (Bhattacharya & Kaur, 2019; Hiatt & Creasey, 2018). Bridges’
Transition Model emphasizes people’s psychological transitions during change,
consisting of an Ending, Neutral Zone, and New Beginning, aiming to manage the human
aspects of change (Fernandez & Shaw, 2017; Mikkelsen & Plotnikof, 2021). Finally, the
McKinsey 7S Framework targets seven critical elements of an organization that need an
alignment for successful change: Strategy, Structure, Systems, Shared Values, Skills,
Style, and Staff (Al-Swidi & Al-Hosam, 2018; Zhang, Y., & Liu, Y., 2017).
These theories complement each other in their focus on managing change in
organizations, offering various frameworks for facilitating change, addressing barriers,
and understanding the individual and organizational experiences of change. Organizations
may find value in combining elements of these models to create a comprehensive change
management strategy, particularly when adopting new technologies, such as blockchain.
Contrasting Theories
It is also essential that we discuss the theories that contrast with Kruger’s change
management theory. One contrasting theory is the Complexity Theory. Complexity
theory challenges traditional linear and reductionist approaches to change management by
emphasizing the inherent uncertainty, nonlinearity, and unpredictability of change
processes in organizations (Albsoul et al., 2021). According to complexity theory,
organizations are complex adaptive systems that continuously evolve and self-organize in
response to internal and external stimuli (Estrada-Jimenez et al., 2021). Change
management should therefore focus on fostering adaptability and resilience rather than
seeking to control and predict change outcomes (Cilliers, 2019). Burnes and Cooke, B.
(2019) define the complexity theory as offering an alternative view of change
management by focusing on the self-organizing nature of organizations and the emergent
properties arising from the interactions between organizational actors.
When contrasting the complexity theory, Kruger’s change management theory
focuses on overcoming barriers to change by addressing visible and invisible factors,
such as cost, quality, time, perceptions, beliefs, and power dynamics. In contrast,
complexity theory emphasizes the unpredictable and adaptive nature of change in
organizations, suggesting that change management should prioritize adaptability and
resilience over control and predictability.
Another contrasting theory is the Appreciative Inquiry Theory. Appreciative
Inquiry (AI) offers an alternative approach to change management, focusing on
identifying and building upon an organization’s strengths rather than fixing problems or
overcoming barriers (Whitney et al., 2019). AI encourages organizations to engage in
collaborative, strengths-based conversations to co-create a shared vision of the future and
develop strategies for achieving that vision. The AI process typically involves four
phases: Discover, Dream, Design, and Destiny (Bushe & Marshak, 2018). Furthermore,
Cooperrider and Godwin (2019) define Appreciative Inquiry as a strengths-based,
positive approach to change that emphasizes the generative power of inquiry and dialogue
to create new possibilities and sustainable growth within organizations.
Kruger’s change management theory aims to identify and address barriers to
change in organizations, whereas Appreciative Inquiry takes a more positive approach by
focusing on building upon existing strengths and fostering collaborative, future-oriented
conversations. While Kruger’s theory emphasizes overcoming obstacles, AI highlights
the potential for growth and improvement by tapping into the organization’s strengths
and resources.
Another contrasting theory to Kruger’s change management theory is action
research. Action research (AR) is a participatory, democratic process concerned with
developing practical knowledge to pursue worthwhile human purposes, grounded in a
participatory worldview. It seeks to bring together action and reflection, theory and
practice, in participation with others, in the pursuit of practical solutions to issues of
pressing concern to people (Coghlan and Brannick, 2019). Coghlan and Shani (2020)
state action research is an approach to creating organizational change and development,
which involves a family of research methodologies that pursue action (or change) and
research (or understanding) at the same time,’ emphasizing collaboration, participation,
and reflection in the pursuit of practical solutions to pressing organizational issues.
The methodology of the change management theory often relies on frameworks
and models that provide structured approaches to manage and implement change. While
the action research theory follows a cyclical process in which researchers and
practitioners actively engage in identifying problems, designing and implementing
interventions, observing the results, reflecting on the outcomes, and refining the approach
as needed. Furthermore, change management theory is primarily concerned with
addressing barriers to change within organizations; the action research theory focuses on
problem-solving and learning through collaborative, iterative processes. Change
management theory provides frameworks and models for managing change, whereas
Action research emphasizes an ongoing cycle of planning, action, observation, and
reflection to generate practical solutions and insights.
Yet, our final contrasting theory is the dynamic capabilities theory. Dynamic
capabilities theory suggests that organizations can achieve a competitive advantage by
developing and deploying capabilities that enable them to sense, seize, and transform
themselves in response to rapidly changing environments (Teece, Peteraf, & Leih, 2016).
Wilden and Gudergan (2020) describe the dynamic capabilities theory as an
organization’s capacity to purposefully create, extend, or modify its resource base,
enabling it to adapt and reshape its operations in response to changing market conditions
and environmental turbulence.
Change management theory by Kruger emphasizes recognizing and overcoming
these barriers is essential for successfully implementing change initiatives. On the other
hand, the dynamic capabilities theory highlights an organization’s ability to create,
extend, or modify its resource base to adapt to changing market conditions and
environmental turbulence. The focus is on the organization’s capacity to develop and
leverage its resources, skills, and capabilities to respond to external changes and maintain
a competitive advantage. Both theories are essential for understanding and managing
change in organizations, but they approach the topic from different perspectives and
emphasize different aspects of the change process.
In summary, while Kruger’s change management theory focuses on identifying
and addressing barriers to change within organizations, contrasting theories like
complexity theory, appreciative inquiry, action research, and dynamic capabilities theory
offer alternative perspectives on managing change. These contrasting theories emphasize
various aspects, such as the unpredictable nature of change, building upon organizational
strengths, problem-solving through iterative processes, and adapting to external
modifications to maintain a competitive advantage.
When considering the importance of building resilient applications with
blockchain technology, these contrasting theories may provide valuable insights into
managing change effectively. Blockchain technology can introduce new challenges and
opportunities, requiring organizations to be adaptable, resilient, and agile in their
approach to change. For instance, complexity theory highlights the need for adaptability
and resilience in unpredictable changes, which can be essential when adopting blockchain
technology. Likewise, dynamic capabilities theory underlines the importance of
developing and leveraging organizational resources, skills, and capabilities to respond to
external changes, such as the rapidly evolving blockchain landscape. Organizations
seeking to implement blockchain technology should consider these contrasting theories in
their change management strategies. By combining the insights from Kruger’s change
management theory and these alternative perspectives, organizations can develop a more
comprehensive understanding of change processes, ultimately facilitating the successful
adoption of resilient blockchain applications.
Criticism of the Change Management Theory
There has been criticism of Kruger’s change management theory. For example,
Alvesson and Sveningsson (2015) argue that the focus on visible and invisible barriers to
change does not capture the full range of factors that affect change initiatives, such as the
role of organizational culture and power dynamics. While these two factors are included
underneath the iceberg, some believe they are not adequately represented in the change
management theory. This may apply to all organizational changes, from the business side
to the technology side.
Furthermore, Burnes (2015) criticizes the change management iceberg theory for
its limited focus on individual-level resistance to change. The author emphasizes that the
framework needs to consider group and organizational-level resistance to provide a more
comprehensive understanding of the barriers to change. Considering these multiple levels
of resistance is crucial for organizations to develop strategies that address the complex
nature of change resistance. This can enable organizations to make more informed
decisions and better anticipate the challenges that may arise during the change process.
Cameron and Green (2015) also argue that the change management iceberg theory
does not provide a detailed roadmap for addressing the barriers to change. The authors
suggest that a more comprehensive approach, such as Kotter’s 8-Step Process, may be
more helpful in guiding organizations through change initiatives. They emphasize the
need for a clear, actionable plan to overcome resistance and promote the successful
implementation of change. By adopting a more structured approach, organizations can
ensure they are better prepared to navigate the complexities of change and achieve their
desired outcomes.
More criticism can be found from Hayes (2018), who discusses that the change
management iceberg theory does not adequately address the role of emotions in
organizational change. The author emphasizes that emotions, such as fear and anxiety, are
critical drivers of resistance to change and must be considered in any change management
framework. These emotions may directly impact an organization’s ability to adopt new
technology, advance business processes, and improve customer satisfaction. It is essential
for change management approaches to consider the emotional aspects of change, as this
enables organizations to develop targeted strategies for addressing employees’ concerns
and fostering a supportive environment.
Another example of criticism can be found in Worley and Mohrman (2014), who
argue that the change management iceberg theory and other traditional change
management approaches may be obsolete in today’s rapidly changing business
environment. The authors suggest organizations adopt more agile and continuous change
approaches to stay competitive. They emphasize the need for organizations to embrace a
culture of adaptability and innovation, which allows them to respond more effectively to
emerging challenges and opportunities. By doing so, organizations can be better
positioned to capitalize on new market trends and maintain a competitive edge in an
increasingly dynamic landscape. This shift towards more flexible and responsive change
management approaches highlights the limitations of the Change Management Iceberg
theory in addressing the complex and fast-paced nature of modern organizational change.
In summary, the criticism of Kruger’s change management theory mainly revolves
around its inability to capture the full range of factors affecting change initiatives, its
limited focus on individual-level resistance, the absence of a detailed roadmap for
addressing barriers, the lack of emphasis on emotions, and its potential obsolescence in
today’s rapidly changing business environment. These limitations can affect an
organization’s ability to adopt new technology, such as blockchain, and improve its
processes and customer satisfaction. Building resilient applications with blockchain
technology requires organizations to be agile and adaptable to change. However, the
criticism of Kruger’s change management theory suggests that it may not be sufficient for
managing change in organizations implementing blockchain technology.
Organizations may consider adopting more comprehensive change management
approaches, such as Kotter’s 8-Step Process, to guide them through change initiatives. By
doing so, organizations can respond more effectively to emerging challenges and
opportunities, ensuring they stay competitive and implement blockchain technology in
their processes. In conclusion, while Kruger’s change management theory has its
limitations, organizations can still benefit from understanding the barriers to change and
adopting more comprehensive, agile, and emotionally aware change management
approaches to build resilient applications with blockchain technology successfully.
Blockchain Overview
Blockchain technology is a decentralized, distributed ledger system that allows for
secure, transparent, and tamper-proof record-keeping of transactions across a distributed
network (Casino, Dasaklis, & Patsakis, 2019). This chain creates an immutable history of
transactions that cannot be altered without the network’s consensus (Nakamoto, 2008).
Consensus is a process by which a group of participants in a decentralized
network agree on data validity, such as transactions, within a distributed system like a
blockchain. In blockchain technology, consensus mechanisms ensure that all nodes in the
network maintain a consistent and accurate view of the shared ledger, thus fostering trust
and security (Bano et al., 2017). Cryptographic hash functions ensure the integrity and
security of the data stored in the blockchain, making it resistant to unauthorized
modifications (Tschorsch & Scheuermann, 2016). Additionally, blockchain technology
fosters trust among participants by ensuring transparency and providing a single source of
truth for all recorded transactions (Lin, Shen, & Zhang, 2019).
In their 2021 study, Elo et al. (2021) shed light on this phenomenon within the
Internet of Things (IoT) context. They argue for integrating Distributed Ledger
Technology, a type of blockchain technology, in IoT systems, suggesting that this could
significantly enhance system resiliency. They propose that the elimination of a central
authority, enabled by blockchain’s inherent consensus mechanisms, can serve to
strengthen IoT federation resilience, a perspective that aligns with the observations of
Bano et al. (2017). Their research further supports the growing trend of adopting
blockchain technology across different sectors, indicating its transformative potential not
just in finance, supply chain management, and health care, but also in bolstering IoT
system integrity and reliability (Kshetri, 2018; Lin, Shen, & Zhang, 2019).
One of the main applications of blockchain technology is in cryptocurrencies,
such as Bitcoin, which was the first and most well-known implementation of a
blockchain-based digital currency (Nakamoto, 2008). Cryptocurrencies leverage the
decentralized nature of blockchain to facilitate peer-to-peer transactions without the need
for a central authority or intermediary, such as banks (Tapscott & Tapscott, 2016). This
has led to the growth of decentralized financial services (DeFi) and applications (DApps),
which aim to transform traditional financial services by offering more accessible,
costeffective, and secure alternatives (Zohar, 2020).
Smart contracts, self-executing agreements with the terms of the contract directly
written into code, are another prominent application of blockchain technology. These
contracts automatically enforce the terms and conditions specified in the code when
predefined conditions are met, eliminating the need for intermediaries and reducing the
risk of fraud and disputes (Christidis & Devetsikiotis, 2016). The Ethereum platform,
which introduced the concept of smart contracts, has paved the way for numerous
blockchain-based applications, including decentralized autonomous organizations and the
tokenization of assets (Buterin, 2014).
Despite its potential benefits, blockchain technology faces several challenges and
limitations, such as scalability, energy consumption, and regulatory issues. The scalability
of blockchain networks, particularly those employing Proof of Work (PoW) consensus
mechanisms, is limited due to the computational power required to maintain the network
and validate transactions (Croman et al., 2016). Furthermore, the energy consumption
associated with PoW-based systems, like Bitcoin, has raised environmental concerns and
led to the development of alternative consensus mechanisms like Proof of Stake (PoS)
(Mora et al., 2018). Regulatory issues also need to be addressed to ensure the responsible
and lawful implementation of blockchain technology across industries
(Yermack, 2017).
Proof of Work is a consensus algorithm utilized in various blockchain networks to
maintain their security and validity, requiring participants to complete complex
computational tasks before adding new blocks to the chain (Akbar et al., 2021). This
process, known as mining, not only deters potential attackers by making it
computationally expensive but also ensures that no single entity controls the entire
network. As noted by Alzahrani & Bulusu (2020), the PoW consensus mechanism is
designed to provide the network’s security, as the difficulty of the cryptographic puzzle
makes it infeasible for any single attacker to take control of the network. This approach,
however, has been criticized for its high energy consumption and environmental impact.
According to Mora et al. (2021), the Bitcoin network, which predominantly relies on the
Proof of Work mechanism, was estimated to consume 121.36 terawatt-hours per year in
2021, comparable to the energy consumption of a mid-sized country like the Netherlands.
As a result, alternative consensus mechanisms have been proposed to address these
concerns.
Proof of Stake (PoS) is an alternative consensus mechanism employed in some
blockchain networks to address the environmental and energy consumption concerns
associated with Proof of Work systems. Instead of relying on computational power to
secure the network, PoS utilizes the ownership of digital assets (i.e., cryptocurrency) as
the primary factor in determining who validates new blocks. According to Kwon et al.
(2020), in a PoS-based blockchain, validators are chosen based on the amount of
cryptocurrency they hold and are willing to stake as collateral, creating a more
energyefficient system compared to PoW. This approach not only promotes a more
environmentally sustainable model but also reduces the risk of centralization due to the
distribution of assets. Nguyen et al. (2021) explain that PoS provides a more equitable
distribution of rewards and lowers the barrier to entry for participation in the consensus
process, thus reducing the risk of centralization. As such, Proof of Stake has gained
traction as a viable alternative to Proof of Work in developing new blockchain networks.
Blockchain technology is a decentralized, distributed ledger system that enables
secure, transparent, and tamper-proof record-keeping of transactions across a network of
computers. Consensus mechanisms, like Proof of Work (PoW) and Proof of Stake (PoS),
ensure the network’s security and data integrity. While PoW requires participants to
perform complex computational tasks, PoS chooses validators based on the amount of
cryptocurrency they stake, making it more energy-efficient. Blockchain’s key advantages
include eliminating the need for a central authority, increasing trust and transparency, and
fostering various applications like cryptocurrencies, decentralized financial services, and
smart contracts. Despite its potential, blockchain faces challenges like scalability, energy
consumption, and regulatory issues, leading to the development of alternative consensus
mechanisms like PoS.
Current Blockchain Technology Uses
One prominent use case is in the field of finance, where blockchain has been
employed to facilitate secure and transparent transactions through cryptocurrencies like
Bitcoin and Ethereum (Nakamoto, 2008). Additionally, blockchain-based platforms such
as Ripple and Stellar have been developed to enable faster, more efficient cross-border
payment and remittance services, bypassing traditional intermediaries and reducing
transaction costs (Hawlitschek, Notheisen, & Teubner, 2018). These platforms have the
potential to reshape the global financial landscape, making transactions more accessible
and cost-effective for individuals and businesses alike (Tapscott & Tapscott, 2017).
Fernandez-Vazquez et al. (2022) present an in-depth exploration of blockchain’s
application in sustainable supply chain management. Using the Analytical Hierarchical
Process methodology, they examine blockchain’s potential to enhance traceability,
security, and efficiency within supply chain networks. They underscore blockchain’s
ability to provide an immutable, decentralized ledger that allows all parties to track
goods’ movements and ensure their provenance, aligning with the observations of
Kamble, Gunasekaran, & Arha (2019). Moreover, they highlight the value of
blockchainenabled smart contracts in automating processes, thus reducing human errors
and increasing overall efficiency. Their research supports the idea that this heightened
visibility, coupled with the automation capabilities, can significantly boost trust and
collaboration among supply chain partners, ultimately leading to more sustainable and
resilient supply chains (Saberi, Kouhizadeh, Sarkis, & Shen, 2019).
In the health care sector, blockchain technology offers significant potential for
improving data security, interoperability, and patient privacy. By creating a decentralized
and tamper-proof ledger for storing patient records, blockchain can enable secure and
transparent sharing of medical information among health care providers, improving
coordination and facilitating better treatment outcomes (Kuo, Kim, & Ohno-Machado,
2019). Furthermore, blockchain can empower patients by granting them greater control
over their data, allowing them to selectively share information with authorized entities
and ensuring their privacy. This patient-centric approach to health information
management has the potential to transform health care delivery by promoting patient
engagement and personalized care (Metcalfe, 2020).
Lastly, blockchain technology has been applied to enhance the security and
transparency of voting systems. By leveraging the immutable nature of blockchain, it is
possible to create an auditable and tamper-proof record of votes, reducing the risk of
electoral fraud and manipulation (Hardwick, Akram, & Markantonakis, 2019).
Additionally, blockchain-based voting platforms can enable remote voting, making the
process more accessible and convenient for citizens while maintaining the integrity of the
electoral process. The adoption of such systems could lead to increased voter
participation and trust in the democratic process, ultimately contributing to more
inclusive and representative governance (O’Reilly & Janssen, 2020).
Blockchain technology has shown promise in various sectors, including finance,
supply chain management, health care, and voting systems. In finance, it facilitates secure
transactions through cryptocurrencies and enables efficient cross-border payments. In
supply chain management, it enhances traceability and efficiency, helping to prevent
fraud and improve collaboration. In health care, blockchain can improve data security and
patient privacy, promoting better treatment outcomes and patient engagement. Finally, in
voting systems, blockchain can increase security and transparency, potentially leading to
greater voter participation and trust in the democratic process.
Traditional Resiliency Strategies
Current technology resiliency practices focus on ensuring the continuity of
business operations and minimizing downtime in the face of disruptions, such as natural
disasters, cyber-attacks, or system failures. These practices involve implementing robust
strategies that encompass backup, recovery, and redundancy plans, as well as
incorporating risk management methodologies (Alali & Gao, 2021). In the age of digital
transformation, organizations across various industries are increasingly reliant on
technology, thus making the need for resilient systems more critical than ever before
(Suri & Pal, 2020). Ensuring the resilience of technology infrastructure helps maintain
customer trust and satisfaction and safeguards an organization’s valuable data and
resources.
Database Resiliency
Traditional database resiliency practices have evolved to address the challenges
associated with ensuring the availability, integrity, and accessibility of data in a
continuously changing technological landscape. One such practice is the implementation
of distributed databases, which involve partitioning data across multiple servers or
locations. This approach increases fault tolerance by reducing the likelihood of a single
point of failure and improving data recovery capabilities (Ceri & Pelagatti, 2021).
Additionally, distributed databases can balance the workload among the servers, resulting
in increased performance and responsiveness, especially when data access and processing
demands are high.
Another practice in enhancing database resiliency is backup and recovery
strategies. Regular and comprehensive data backups help organizations recover from data
loss or corruption events, such as hardware failures or cyber-attacks (Tariq & Aslam,
2020). In addition to traditional full and incremental backup techniques, modern solutions
offer continuous data protection mechanisms, which capture changes in real time,
enabling recovery to any point in time. In simpler terms, continuous data protection
systems constantly record every change that occurs in your data, similar to a live video
recording, allowing you to restore data from any specific moment, unlike traditional
backups, which only allow you to restore from the last backup time. Organizations can
further improve recovery capabilities by storing backup data offsite or in the cloud,
providing additional protection against disasters affecting the primary data center.
Finally, implementing database replication and clustering techniques contribute
significantly to ensuring database resiliency. Replication involves the synchronization of
data across multiple database instances, allowing for seamless failover in case of a system
failure or disruption (Ceri & Pelagatti, 2021). Clustering, on the other hand, groups
several servers together to act as a single unit, providing redundancy and load balancing.
Both replication and clustering help maintain data consistency and high availability,
which is essential for organizations with mission-critical applications and services that
require uninterrupted access to their data.
Network Resiliency
Network resiliency practices aim to ensure the uninterrupted functioning of
communication and data transfer across an organization’s infrastructure. One crucial
practice in achieving network resiliency is the implementation of redundant network
paths and components, which help mitigate the impact of a single point of failure (Bilal et
al., 2020). Organizations can maintain network availability by incorporating redundant
routers, switches, and connections in case of hardware failures, cable damages, or other
disruptions. This redundancy can be achieved through diverse routing, where multiple
paths are established between network nodes to provide alternate routes for data traffic
during outages or periods of congestion.
Another practice in enhancing network resiliency is using network monitoring and
management tools, which provide real-time visibility into the performance and health of
the network infrastructure (Peng et al., 2021). These tools can help identify and address
potential issues before they escalate into critical problems, enabling administrators to
optimize network performance and resource allocation. Furthermore, advanced
monitoring solutions can incorporate machine learning and artificial intelligence
capabilities, allowing for the detection of unusual network patterns or behavior that may
indicate security threats or vulnerabilities.
Finally, implementing robust network security measures is essential for ensuring
network resiliency, as cyber-attacks can lead to significant disruptions and data breaches
(Alrawais et al., 2020). Organizations can adopt a multi-layered security approach, which
includes the deployment of firewalls, intrusion detection and prevention systems (IDPS),
and secure access control mechanisms. Additionally, regular security assessments,
vulnerability scanning, and penetration testing can help identify and address potential
weaknesses in the network infrastructure, ultimately contributing to a more resilient
network environment.
Cloud Computing
Cloud computing has revolutionized the way organizations manage and consume
IT resources, offering a range of practices that enhance flexibility, scalability, and
costefficiency. One such practice is the adoption of Infrastructure-as-a-Service (IaaS)
models, which provide virtualized computing resources over the internet, eliminating the
need for organizations to invest in physical hardware and maintenance (Hashem et al.,
2020). IaaS enables businesses to provision computing resources on-demand, allowing
them to scale infrastructure up or down according to their requirements, thereby
optimizing costs and resource utilization. Adding to this narrative, Zou et al. (2022)
explore the synergistic integration of blockchain technology with cloud computing
systems, including IaaS models. Their systematic survey suggests that leveraging
blockchain technology’s decentralized, transparent, and secure attributes can add an extra
layer of trust and reliability to cloud-based systems. For instance, this combined approach
could ensure data integrity and privacy in IaaS models while facilitating secure, auditable
transactions.
Another cloud computing practice is the utilization of Platform-as-a-Service
(PaaS) offerings, which provide a complete development and deployment environment in
the cloud, enabling developers to build, test, and deploy applications without the
complexity of managing the underlying infrastructure (Khan and Al-Yasiri, 2020). PaaS
solutions often include a suite of tools, libraries, and frameworks that streamline the
development process and support multiple programming languages and architectures.
This approach can significantly reduce the time-to-market for new applications and
promote organizational innovation.
Finally, Software-as-a-Service (SaaS) is a popular cloud computing practice that
delivers software applications over the internet, allowing users to access and interact with
them through a web browser, without the need for local installation or maintenance (Liu
& Mao, 2020). SaaS providers handle all aspects of software management, including
updates, security, and scalability, offering organizations a subscription-based model that
eliminates upfront costs and reduces the burden on IT teams. SaaS solutions have gained
traction across various industries due to their ease of use, accessibility, and the potential
for seamless integration with other cloud services.
Technology resiliency practices focus on ensuring business continuity,
minimizing downtime, and protecting valuable data and resources in the face of
disruptions (Alali & Gao, 2021; Suri & Pal, 2020). Key practices include distributed
databases, backup and recovery strategies, and replication and clustering techniques for
database resiliency (Ceri & Pelagatti, 2021; Tariq & Aslam, 2020); redundant network
paths and components, network monitoring and management tools, and robust network
security measures for network resiliency (Bilal et al., 2020; Peng et al., 2021; Alrawais et
al., 2020); and IaaS, PaaS, and SaaS practices for cloud computing (Hashem et al., 2020;
Khan and Al-Yasiri, 2020; Liu & Mao, 2020). Blockchain technology can address these
resiliency practices by providing a decentralized, tamper-proof, and transparent
infrastructure, which can enhance data integrity, security, and fault tolerance (Casino,
Dasaklis, & Patsakis, 2019). Blockchain-based solutions can be integrated into various
aspects of technology resiliency, such as database management, network security, and
cloud services, ensuring a more resilient and secure environment (Mollah, Karim, &
Rahman, 2021).
Blockchain Resiliency Strategies
One aspect of resiliency addressed by blockchain is data integrity, ensuring that
information stored on the blockchain remains unchanged and verifiable (Casino,
Dasaklis, & Patsakis, 2019). By creating a tamper-proof and distributed ledger,
blockchain technology eliminates single points of failure and mitigates the risk of data
manipulation, ultimately contributing to a more secure and reliable infrastructure. The
table by Chowdhury (2018) compares centralized databases to blockchain databases:
Table 1
Blockchain Versus Centralized Databases
Issue Block chain Central database Advantage
Trust building Can operate without any
trusted party
Need a central trusted party Blockchain
Confidentiality of data (by default) All nodes have
visibility of the data
Restricts access to
authorized person
Database
Robustness/fault
tolerance
Data are distributed among
nodes
Data are stored in central
database
Blockchain
Performance Takes time to reach concensus
(e.g., 10min for Bitcoin)
Immediate execution/update Database
Redundancy (by default) each participating
node has latest copy
Only the central party has
copy
Blockchain
Security (by default) use cryptographic
measures
Uses traditional access
control
Blockchain
Note. From “Blockchain versus database: a critical analysis,” by M. J. M. Chowdhury, A.
Colman, M. A. Kabir, J. Han, & P. & Sarda, 2018, IEEE international conference on big
data science and engineering.
(https://doi.org/10.1109/TrustCom/BigDataSE.2018.00186).
Another way blockchain technology enhances resiliency is through the use of
smart contracts, which are self-executing contracts with the terms of agreement directly
written into the code (Christidis & Devetsikiotis, 2016). Smart contracts can automate
various processes, such as payments and inventory management, reducing delays and
human errors while increasing overall efficiency. The automation capabilities provided
by smart contracts not only streamline operations but also contribute to the resiliency of
systems by minimizing the potential impact of human intervention or errors on critical
processes (Saberi, Kouhizadeh, Sarkis, & Shen, 2019).
Furthermore, blockchain technology enables greater transparency and traceability,
which are essential components of resiliency in sectors like supply chain management
and finance. By providing an immutable and decentralized ledger, blockchain allows all
parties involved to track the movement of goods or transactions in real-time, facilitating
trust and collaboration among stakeholders (Kamble, Gunasekaran, & Arha, 2019). This
enhanced visibility and traceability can lead to improved detection and response to
potential disruptions, ultimately resulting in more sustainable and resilient systems.
Finally, blockchain technology can improve resiliency by enhancing security and
privacy. The cryptographic mechanisms employed in blockchain networks ensure secure
and verifiable transactions, while also providing privacy through techniques such as
zeroknowledge proofs and ring signatures (Zohar, 2020). This combination of security
and privacy features not only protects sensitive data from unauthorized access but also
ensures that the system remains resilient against cyber-attacks and other potential threats.
Overall, blockchain technology presents a viable solution for addressing resiliency
challenges in various domains, providing a foundation for more secure, transparent, and
reliable systems.
Blockchain technology addresses resiliency in several ways, including enhancing
data integrity, streamlining processes through smart contracts, promoting transparency
and traceability, and improving security and privacy. By creating a tamper-proof and
distributed ledger, blockchain ensures information remains unchanged and verifiable,
contributing to a more secure and reliable infrastructure (Casino, Dasaklis, & Patsakis,
2019). Smart contracts automate processes, reducing delays and human errors while
increasing efficiency and system resiliency (Saberi, Kouhizadeh, Sarkis, & Shen, 2019).
Additionally, blockchain’s immutable and decentralized ledger enables transparency and
traceability in sectors like supply chain management and finance, promoting trust,
collaboration, and more resilient systems (Kamble, Gunasekaran, & Arha, 2019). Lastly,
blockchain technology improves resiliency by enhancing security and privacy through
cryptographic mechanisms and techniques such as zero-knowledge proofs and ring
signatures, protecting sensitive data and ensuring system resilience against potential
threats (Zohar, 2020).
Transition and Summary
This research explores Kruger’s change management theory and how it relates to
blockchain resiliency. This theory highlights the crucial understanding of both observable
and hidden factors in project management. Observable factors, such as time, cost, and
quality, are transparently managed in projects, while hidden elements—underlying
cultural, power, and political dynamics—are frequently disregarded due to their
intangibility but are essential for project success. The theory broadens the concept of time
management beyond initial planning to include vital behavioral skills and considers both
direct and indirect costs under cost management. The use of delimitations in the study
ensured focus and alignment with research objectives, as they were described as
consciously set boundaries by the researcher, including restrictions on the number and
location of cases and specific qualifications for IT professionals, all within the context of
exploring strategies for resilient systems among IT professionals with blockchain
experience.
Another cornerstone of this section is the exploration of resiliency, specifically
through blockchain technology. Blockchain bolsters resiliency via data integrity, process
automation using smart contracts, and enhanced transparency, traceability, security, and
privacy. By forming a tamper-proof, distributed ledger, blockchain assures that
information stays consistent and verifiable, creating a secure, reliable framework. Smart
contracts streamline various processes, diminishing delays and errors, hence fortifying
overall efficiency and system resiliency. Following this exploration of blockchain and
traditional resiliency strategies, subsequent sections will discuss data collection and
analysis to answer the research question.
Section 2: The Project
In the section below, I will further explore the purpose of this research and my
role as the researcher. This will be from the perspective of an IT professional with
experience supporting enterprise applications and blockchain experience. Furthermore, I
will discuss this study’s research method and design to ensure the proper alignment with
the research question and the problem being addressed. A deep dive into the data
collection methods will be undertaken, with specifics outlined regarding instrumentation,
collection techniques, and organizational strategies. I also aim to highlight potential
challenges and their respective solutions throughout the data collection and analysis
process. I will end this section by discussing this study’s reliability and validity.
Purpose Statement
The purpose of this qualitative multiple-case study is to examine the strategies IT
professionals use to support blockchain technologies to enable resilient systems. The
study’s target population comprises IT professionals hailing from development and
infrastructure teams across the United States. Insights derived from this study could assist
organizations by illustrating resiliency deficiencies within their IT systems and
showcasing the capacity of blockchain technology to alleviate such risks. This could
further suggest business leaders need to construct a resilient IT architecture that tackles
potential shortcomings in IT infrastructure and procedures. By doing so, there may be a
societal impact by potentially reducing downtime of essential IT platforms, including
hospital systems, vital supply chains, and utility services.
Role of the Researcher
I have been employed in the technology industry since 2005, beginning as a
desktop technician for an enterprise organization and then transitioning to server
technical support. Currently, I am a technologist in an operations team that supports
webfacing applications. Over the last 5 years, my focus has shifted from creating and
maintaining applications in the operational space to enabling resiliency and optimal
application performance. This focus spurred my interest in considering blockchain as a
data layer for enterprise applications. Originally, my interest in blockchain technology
was purely financial; however, my perception shifted as I noticed operational gaps within
existing technologies. I aimed to explore these possibilities through my work and
contribute to the ongoing dialogue on leveraging blockchain for operational efficiency
and resilience.
As the researcher in this study, my role in the data collection process is central
and multifaceted. I was responsible for designing and implementing the research
methodology, selecting suitable participants, conducting interviews, collecting relevant
documents, and overseeing the data collection process. Furthermore, my extensive
experience in the technology industry has afforded me a valuable understanding of the
context and nuances of the work of the IT professionals participating in this study, which
enabled me to ask insightful questions and interpret responses with depth and accuracy.
Although I did not work directly with the study participants, I ensured they had the
relevant experience to explore the topic.
It was also crucial to recognize the potential for my personal experiences and
perspectives to influence the research process. A researcher’s personal
involvement at various stages of qualitative research presents an ethical bias,
which can influence study results(Bispo, 2022; Mackieson et al., 2019; Sanjari et
al., 2014). To mitigate bias, I strived to maintain reflexivity throughout the data
collection process, continually reflecting on my assumptions, biases, and
influences and taking steps to ensure they did not unduly shape the research
outcomes (Berger, 2015). This included strategies such as maintaining a research
journal to document reflections and decisions made during the research process
and seeking peer debriefing to gain external perspectives on the data and findings.
Moreover, recognizing the inherent power dynamic between researcher and
participant, I aimed to foster a respectful and collaborative relationship with
participants, valuing their experiences and perspectives and striving to give voice
to their experiences fairly, accurately, and respectfully.
My research employed video conferencing software for data collection, with both
audio and video, which can reduce bias and enhance reliability (Johnson et al., 2020). I
also planned to employ the member checking method to avoid misinterpretations of
participants’ responses (see Motulsky, 2021). This method, used in qualitative research,
increased the credibility and validity of the collected data. I also planned to utilize
triangulation methods in my study (see Farquhar, 2020).
To uphold ethical research standards, I used the Belmont Report as a framework,
embodying its three fundamental ethical principles as described by Siddiqui and Sharp
(2021): respect for persons, beneficence, and justice.
1. Respect for persons: This principle implies that individuals should be treated
as autonomous agents capable of making decisions for themselves.
Additionally, individuals with diminished autonomy (for example, children,
prisoners, or mentally impaired persons) should be afforded additional
protections.
2. Beneficence: Researchers should aim to maximize benefits and minimize
harm to participants. This means they must strive to design and conduct
research in a way that ensures potential benefits significantly outweigh
potential risks.
3. Justice: This involves ensuring a fair distribution of the benefits and burdens
of research. For example, one group should not bear the brunt of research
risks while another group reaps all the benefits.
These principles were implemented to ensure that participants could freely provide
information and understand they could exit the study anytime.
First, I demonstrated respect for persons by treating all participants as autonomous
individuals who can make informed decisions about their participation. I communicated
all the necessary information about the study to the participants in a clear and
understandable manner. This includes the study’s purpose, methodology, potential
benefits, possible risks, and their right to withdraw from the study at any time without
any negative repercussions.
Second, beneficence was carefully considered in my research design and
execution. I ensured that the benefits of the research, such as gaining insights into IT
strategies and the potential improvements to enterprise application resilience,
significantly outweighed any potential risks, like time taken away from their usual duties
or discomfort in sharing professional experiences. Additionally, I strived to minimize any
potential harm by maintaining strict confidentiality and anonymity measures, ensuring
that all participant information and responses were securely stored and used solely for the
purpose of this study.
Lastly, the principle of justice was upheld by ensuring a fair distribution of the
benefits and burdens of research. I carefully selected participants from different roles,
levels, and team compositions, ensuring that no one group was overburdened with the
demands of participation or excluded from the potential benefits. The insights gained
from this study were intended to contribute to the professional development and
knowledge of all participants and their teams, not just a specific subset. By diligently
implementing these ethical research standards, I aimed to conduct a study that respected,
protected, and benefited all participants in a fair and equitable manner.
Participants
The participants in this study were IT professionals from either infrastructure or
development teams, each with a minimum of 8 years of experience supporting enterprise
systems. This study employed a multiple-case approach, ensuring the participants came
from diverse organizations with varied sector experiences. The sectors included in this
study encompassed financial technology, health care, and local government. Although
these participants had a basic understanding of blockchain technology, they had not
directly used it in their current roles. The goal was to gather individuals with operational
and developmental experience in enterprise applications to understand the resiliency gaps
in these platforms. By focusing on these gaps, insights were gleaned about areas for
improvement and the potential benefits of implementing blockchain technology.
Additionally, a diverse pool of participants contributed to a comprehensive understanding
of the issue.
To find participants, I utilized LinkedIn and attended relevant conferences. Many
researchers have successfully leveraged social media to locate participants. With over 450
million users worldwide, LinkedIn has become a hub for exchanging knowledge, ideas,
and opportunities (Matei et al., 2017). As a professional networking platform,
LinkedIn provides invaluable resources for researchers seeking interview participants.
Using the site’s advanced search features and vast user base, researchers could identify
and connect with potential participants with the specific expertise or professional
background relevant to their study.
I initially established a working relationship with potential participants through
direct communication on LinkedIn. I compiled a shortlist of interested participants,
ensuring they had the requisite experience to address the research question. However,
considerable time was dedicated to recruitment. The enlistment of research participants
was impeded by their time constraints, often due to heavy workloads, leading them to
prioritize work over interview participation (Daly et al., 2019). I employed the
elaboration likelihood model to mitigate this risk to facilitate persuasion. The ELM
suggested that the topic’s relevance, the person’s ability to understand the message, and
their motivation to process the message would determine the route they’d take to process
the information (Scannell, 2021). I implemented strategies that respected autonomy and
relied on persuasion and offers, being careful to avoid manipulation and coercion.
Research Method and Design
I established professional connections by contacting numerous potential
participants via email, direct messages on LinkedIn, or video calls. After identifying
those who expressed interest, I organized and classified them based on the criteria I had
established for my participants. I recognized that there might be obstacles in forming
these relationships (Wozney et al., 2019). Additionally, recruitment research,
communication media, and information quality were crucial in attracting potential
participants (Muduli & Trivedi, 2020). Focusing on communication media was one of the
key mitigation strategies I used to find my participants.
Method
The research method that I adopted was qualitative. A qualitative study’s
philosophical point of view is often aligned with interpretivism or constructivism (Van
der Walt, 2020). These perspectives emphasize the subjective nature of human
experiences and the importance of understanding social phenomena within their specific
contexts. Qualitative research is used to explore and understand the meaning and
interpretation of individuals’ experiences, beliefs, and behaviors. It acknowledges that
reality is socially constructed and that multiple variations could exist. As a researcher
conducting a qualitative study, researchers engage in in-depth interviews, observations,
and textual or visual data analysis to gain insights into participants’ lived experiences and
the social processes at play (Liu, 2022). Qualitative methods offer a unique advantage in
capturing the richness and complexity of human experiences, perceptions, and social
phenomena (Hong & Cross Francis, 2020). Through in-depth interviews, observations,
and textual or visual data analysis, qualitative research allows researchers to delve deeply
into individuals’ lived experiences, uncovering the nuances, meanings, and contextual
factors that shape their perspectives (Rapport & Hughes, 2020). This depth of
understanding is often challenging to achieve through quantitative or mixed methods,
which typically focus on measurable variables and statistical analysis. Qualitative
research allows for a more holistic and comprehensive exploration of the subject matter,
providing a deeper understanding of the social and cultural dynamics.
In addition, qualitative research is precious when exploring new or relatively
uncharted areas of study. When little is known about a phenomenon or when existing
theories or frameworks are insufficient, qualitative methods can generate new insights
and ideas (Kyngäs, 2020). Through open-ended interviews or observations, researchers
can uncover unexpected patterns, find hidden factors, or challenge existing assumptions.
Qualitative research allows for exploring diverse perspectives and provides a foundation
for developing theories or hypotheses that can be further investigated using quantitative
or mixed methods. Since I observed the experience of IT professionals, a qualitative best
fits my research question.
Furthermore, qualitative methods excel in understanding the context-specific
nature of social phenomena and the dynamic processes that occur within them (Izogo &
Jayawardhena, 2018). By immersing themselves in the research setting and engaging with
participants, researchers can understand the social, cultural, and environmental factors
that influence individuals and their behaviors. Qualitative research can capture the
temporal and situational aspects of phenomena, allowing for an examination of how
events unfold over time and the interplay between different actors or variables (Spector &
Meier, 2014). This nuanced understanding of context and process is often essential for
informing interventions, policy development, or theory-building efforts. The nuanced
reactions to the interview questions can derive information to address the IT problem.
While mixed methods and quantitative research have strengths and applications,
qualitative methods offer distinct advantages when exploring complex human
experiences, uncovering new insights, and understanding the contextual dynamics of
social phenomena. Researchers may choose qualitative methods when seeking a deep
understanding of subjective experiences, when investigating new or unexplored areas, or
when aiming to unravel the intricacies of social processes (Njie & Asimiran, 2014).
Research Design
I chose to employ a multiple case study approach as the suitable qualitative
method for my study. The primary aim of my research was to understand the specific
strategies experienced blockchain IT professionals employ in supporting enterprise
applications and how blockchain technology can increase resiliency. By examining
multiple cases, I aimed to gain a comprehensive understanding of the diverse strategies
used in different contexts and explore the potential benefits of blockchain technology in
enhancing the resilience of enterprise applications. Given the nature of my objective, a
case study approach is deemed appropriate for investigating these strategies in-depth.
To ensure data saturation in this research, I implemented several strategies. First, I
selected four cases regarding organization size, industry sector, and geographic location.
This maximized the variability of strategies employed by IT professionals and the
contexts in which blockchain technology was utilized, enhancing the richness and depth
of the data collected. Second, within each case, I interviewed multiple IT professionals
with different experience levels and roles within their organization. This allowed for
various perspectives on the strategies employed and the use of blockchain technology in
supporting enterprise applications. Third, the interviews were conducted until no new
themes or insights emerged from the data, which is a standard marker of data saturation.
To ensure this, I continuously analyzed the interview data while data collection was
ongoing, allowing me to identify when saturation had been reached. Lastly, additional
data sources, such as organizational documents and IT professionals’ reflections, further
contributed to achieving data saturation. By employing these strategies, I aimed to collect
comprehensive and detailed data that thoroughly explored the topic at hand and ensured
the credibility and trustworthiness of the research findings.
Several factors drove the choice of a multiple case study design. Firstly, it allows
for an in-depth exploration of the specific strategies employed by experienced IT
professionals in supporting enterprise applications. By examining multiple cases, the
researcher can identify commonalities, differences, and patterns across various contexts,
providing a comprehensive understanding of the topic (Bass et al., 2018). Additionally, a
multiple case study design offers the opportunity to triangulate findings and enhance the
credibility and validity of the research (Bass et al., 2018). By studying multiple cases, the
researcher can strengthen the reliability of the results, as patterns or themes that emerge
across different cases are less likely to be due to chance or specific contextual factors
(Hartley, 2004).
Other research methods, such as surveys or experiments, were not selected for
several reasons. Surveys might provide a broad overview, but they may not capture the
depth and nuances of the specific strategies employed by IT professionals in supporting
enterprise applications. Conversely, experiments typically focus on controlled variables
and may not adequately capture the complexities of real-life contexts (Shamay-Tsoory &
Mendelsohn, 2019). Given the research objective of understanding specific strategies and
exploring the role of blockchain technology, a qualitative approach was deemed more
appropriate for capturing the richness and contextual factors at play.
Lastly, the multiple case study design aligns well with the problem being studied.
It allows for an exploration of the strategies employed by IT professionals in real-life
settings, providing a deeper understanding of the complexities and challenges they face
(Paparini et al., 2020). The design also facilitates examining how blockchain technology
can increase resiliency in these applications, as multiple cases can reveal different ways
blockchain is implemented and its impact on resilience. Moreover, the design allows for a
comprehensive analysis of the interplay between strategies, contexts, and the role of
blockchain, contributing to the development of practical insights and recommendations
for IT professionals and organizations in enhancing the resilience of enterprise
applications.
Overall, the multiple case study design was chosen due to its ability to provide
indepth insights, triangulate findings, capture contextual nuances, and explore the specific
strategies employed by IT professionals in supporting enterprise applications and the role
of blockchain technology in increasing resiliency. In addition, the multiple case study
design allows for a holistic examination of the problem, considering various perspectives
and contexts. It offers a comprehensive and nuanced understanding of the strategies
employed by IT professionals, taking into account the unique challenges and
opportunities that arise in different organizational settings and industry sectors.
Furthermore, this design enables the researcher to identify common patterns, variations,
and potential factors that contribute to the success or limitations of the strategies,
providing valuable insights for practical applications and informing future research in the
field.
Population and Sampling
I used two cases with two participants in each company for a total of four
interviews since my research will be a multi-case study. These two cases provided me
with the information to address the research question concerning IT problems. Boddy
(2016) argues that qualitative research often concerns developing a depth of
understanding rather than a breadth. This led me to believe four interviews were enough
to explore this topic. My participants were all IT professionals from the infrastructure or
development teams with blockchain experience supporting enterprise applications.
Farrugia (2019) posits that in purposeful sampling, the researcher strategically chooses
participants based on predetermined criteria, ensuring that the data gathered is optimally
suited for addressing the research question. The participants for the case studies will be
selected using purposeful sampling. This means that the researcher will strategically
choose participants based on predetermined criteria, such as industry experience and role
relevancy. The objective is to include participants who can offer valuable insights into the
IT problem being studied.
Following Farrugia’s assertion, I carefully selected these participants based on
their industry experience and role relevancy, with the primary objective being their
potential to offer valuable insights into the specific IT problems under consideration. By
focusing on a small but contextually rich set of cases, I was able to delve deep into each
case’s unique circumstances and experiences, thus comprehensively exploring the issue.
As Boddy (2016) advocated, this depth-focused approach will enable me to thoroughly
understand the problem area, revealing nuances and complexities that may have been
overlooked in a broader, less focused study.
In addition to these measures, I implemented an iterative data collection process to
ensure data saturation within my population, in line with the recommendations of
Saunders et al. (2018). This approach involved continually reviewing and analyzing data
throughout the research process, which enabled me to monitor the emergence of new
themes or insights and to determine when data saturation were achieved, defined as the
point where no new information is forthcoming from new sampled units. Moreover, I
utilized triangulation of data sources, as Carter et al. (2014) suggested, collecting and
cross-verifying information from different sources, including direct interviews, company
documents, and participant observations. This approach increased the robustness of my
findings. It helped confirm when data saturation had been reached, enabling me to ensure
that new data collected were consistent with the previously obtained data.
Additionally, I maintained an open dialogue with my participants throughout the
research process, as proposed by Morse (2015). This involved revisiting participants for
follow-up interviews or clarifications when necessary, which ensured I had thoroughly
explored each topic and reinforced the depth and richness of the data collected. Finally, I
also employed member checking, a process whereby participants were allowed to review
and confirm the accuracy of the interpretations made from their data (Birt et al., 2016).
This procedure further ensured the depth and validity of the data collected and
contributed to confirming data saturation. Through these comprehensive and rigorous
measures, I ensured that data saturation was achieved within my population, thereby
strengthening the credibility and reliability of my findings.
Ethical Research
Ethics play a crucial role in research, as ignoring ethical considerations can lead to
various types of harm to participants. It is essential to obtain informed consent from
participants, ensuring they know the study’s purpose, benefits, and potential risks before
agreeing to participate. The conditions for acceptable informed consent are full
disclosure, capacity, and voluntariness (Xu et al., 2020). Full disclosure involves
providing all the required information for participants to make an independent decision,
while capacity refers to their ability to understand the information and make a reasonable
judgment. Voluntariness ensures that participants can freely decide without any undue
influence or pressure (Hyatt & Lobmaier, 2020).
In my study, participants were provided full disclosure and voluntarily chose to
participate. To ensure full disclosure, participants were thoroughly informed about the
purpose, methods, potential benefits, and possible risks associated with their involvement
in the study before they decided to participate. They were also informed that they could
withdraw their participation at any time without facing any consequences, thereby
promoting transparency and ethical integrity in the research process. I adhered to ethical
principles such as respect for persons, benevolence, and justice, as outlined in the
Belmont Report. Participants were informed of their freedom to withdraw from the study
at any point if they felt uncomfortable, with the contact information provided to
communicate their decision. The right to withdraw was communicated at the beginning of
the interview. The right to withdraw is universally recognized to protect participants from
potential harm during the research (Favaretto et al., 2020).
Participants were encouraged to join voluntarily, knowing that their insights could
improve the protection of blockchain applications and add to the IT body of knowledge.
The consent form clarified that participants were only required to share their knowledge
of the research topic and that their involvement carried no risks. To ensure
confidentiality, participant identities were anonymized using codes, with a
passwordprotected Excel spreadsheet and encryption for storage. All collected data were
encrypted and stored securely, following data protection guidelines, and were set to be
destroyed after five years.
Data Collection
Instruments
My study’s data collection tool were the semi-structured interview protocol, a
qualitative instrument designed to gain insights into IT professionals’ experiences, views,
and practices in implementing blockchain technologies (Biasutti et al., 2022). The
protocol included open-ended questions tailored to explore the strategies these
professionals used and the challenges they faced. In a qualitative research interview, the
researcher aims to understand what the participants said to gather their experiences,
perceptions, thoughts, and feelings (Moser & Korstjens, 2018). This tool did not produce
numerical scores; its value lay in the rich, descriptive data it yielded. The validity of this
instrument was assessed through pilot testing, ensuring that the questions were clear,
understandable, and relevant to the research questions. Raw data were available upon
request from the researcher.
Each variable in this study comprised qualitative data derived from the interview
responses. These included, but were not limited to, strategies adopted for blockchain
integration, challenges encountered, perceived impact on system resilience, and
recommended improvements in current practices. These variables provided a rich
understanding of the study’s focal points. For instance, ‘strategies adopted for blockchain
integration’ referred to specific actions or approaches used by IT professionals in
incorporating blockchain technologies into existing systems to increase resiliency.
In qualitative research like this one, traditional psychometric properties associated
with quantitative scales, such as validity and reliability, translate into the trustworthiness
and rigor of the data collection and analysis process. My study employed several
strategies to ensure this trustworthiness. The trustworthiness of the research was one of
those shared realities, albeit subjective, wherein readers and writers found commonality
in their constructive processes (Stahl & King, 2020). For instance, to address the validity
threats, I adopted member checking, where participants were invited to review and
confirm the accuracy of the interview transcripts and preliminary findings. This helped
ensure that the research accurately reflected their perspectives and experiences. In this
context, I also employed consistent coding and interpretation paralleled test-retest
reliability, which is more relevant to quantitative studies. The study used a systematic and
transparent coding process to maintain internal consistency. Revisions to the interview
protocol occurred based on the pilot testing feedback or during the iterative data
collection and analysis process, where new insights necessitated modifications to the
interview guide to better capture the research focus, which was performed in early
courses in the curriculum.
Data Collection Technique
My research question was: What strategies do IT professionals use to support
blockchain technologies to enable resilient systems? To seek an answer, I concentrated on
IT professionals who have supported enterprises for at least eight years in small to
medium organizations with blockchain experience. The goal was to comprehend these
professionals’ strategies to support enterprise applications. This was achieved through
conducting interviews and analyzing organizational documents related to IT support.
A semi-structured interview strategy was employed to facilitate the interviews, a
method known for its inherent flexibility and reciprocity between the interviewer and
interviewee. Eppich et al. argues (2019) that a well-crafted semi-structured interview
guide would include predetermined questions while allowing flexibility to explore
emergent topics based on the research question. This format allowed for spontaneous
follow-up questions based on the responses received, contributing to the depth and
richness of the data collected. Additionally, video interviews provided the interviewer
with valuable social cues such as body language, voice tone, and other non-verbal
information, which aided in a more nuanced understanding of the participant’s
perspectives.
The data collection strategy was divided into several phases. The initial phase
involved establishing the suitability of semi-structured interviews for this research
question, as these interviews are particularly effective in eliciting participants’
experiences, thoughts, and feelings. The semi-structured interview is an exploratory
interview used most often in the social sciences for qualitative research purposes
(Magaldi & Berler, 2020). The subsequent phase involved updating my understanding of
the subject matter through relevant literature and seminar papers and setting a conceptual
groundwork for the interviews. This was followed by developing a semi-structured
interview guide consisting of predetermined open-ended questions and follow-up queries.
This interview guide was tested before implementation to ensure clarity and
effectiveness.
The final phase encompassed the interviews themselves. Participants were given a
thorough briefing and were required to provide their consent before commencing the
interviews. Post-interview, additional meetings were scheduled with participants for
member-checking, a process that facilitated the validation of qualitative results by
allowing participants to confirm the accuracy of their responses. This iterative process
was repeated until no new information emerged.
Data Organization Techniques
It was critical in qualitative research to manage data effectively, as this was key to
the success of any study. Data needed to be analyzed to lend meaning to the research, and
it also needed to be securely stored throughout the study period and appropriately
disposed of afterward. As Saldana (2015) argued, qualitative data analysis searched for
general statements about relationships and underlying themes. In line with this
perspective, I encrypted the data from the study interviews using a robust data protection
software product. These files were then stored on a cloud-based platform for additional
protection against damage or theft. Physical data copies were securely stored in a locked
safe throughout the study and were returned to the participants upon completion.
Following the university’s guidelines, all transcribed data will be disposed of after five
years. Similarly, video and audio recordings were destroyed after transcription to ensure
participant confidentiality.
All collected data forms, including recorded interviews, field notes, and
organizational documents, were organized using a software solution. This software enabled
efficient coding, labeling, categorization, and theme development within one consolidated
platform. The software also provided a logbook feature, a research diary recording the
study’s progression. I used the MAXQDA 2022 software to organize this information.
Woods, Paulus, Atkins, and Macklin (2016) highlighted that "Technological tools can assist
in the organization and analysis of qualitative data, enhancing the rigor and depth of
qualitative research." Coding in MAXQDA 12 was intuitive, and the program offered
multiple options for open and focused coding procedures (Oswald, 2019).
The initial step involved uploading the interview audio files and related data into
the software. I generated verbatim text from the audio using the software’s transcription
capabilities. Data exploration commenced as soon as it was collected and uploaded into
the system. The software’s memo function facilitated the addition of notes and comments
throughout the process. As Silverman (2017) suggested, the software could facilitate data
organization, enhance analytical reflexiveness, and assist in presenting findings. I used
the software’s coding and categorization function, which allowed themes to emerge as
coding and categorization progressed gradually. All processes and steps throughout the
study were meticulously documented using the software’s built-in logbook.
Data Analysis Technique
This research aimed to understand IT professionals’ strategies to support
enterprise applications and how blockchain technology might boost resiliency. These
meanings and understandings were inherently qualitative and procured through a
semistructured interview and other qualitative data sources, such as an organization’s
policy documents (Kallio et al., 2016). I utilized the MAXQDA software to consolidate
all collected data into a single location, thus simplifying access for analysis.
The recorded interview audio was transcribed verbatim to ensure accuracy and
completeness, capturing every spoken word. In addition to interviews, organizational
documents such as policies were captured and stored. These documents were scanned and
converted into an electronic format if they were paper-based and then examined for their
potential to answer the research questions.
The use of method and data triangulation ensured the truthfulness of the analysis
and rigor of the research. Triangulation enabled the use of multiple data sources to gain a
comprehensive understanding of a phenomenon and to ensure the validity of the research.
Triangulation ensured that the information derived from research data accurately reflected
the truth (Moon, 2019). This study used a semi-structured interview and documents to
collect data. This multiple case study involved interviews with different individuals in
various cases, making the use of data triangulation appropriate.
The data set were analyzed using a five-step procedure. These steps included data
logging, creating anecdotes, vignettes, data coding, and thematic analysis. Research
showed that vignettes were useful in disseminating complex and applied information to
practitioners, with research mainly utilizing written and audio vignettes to disseminate
good practices (Szedlak, 2019). Data logging involves documenting the raw data
collected from all sources and identifying all issues. Anecdotes of the collection were
then created to help develop the themes. The next step was to develop vignettes of the
investigation to provide a deeper understanding of the phenomenon. Following this, the
collected data were coded by assigning tags to related themes from different sources. The
MAXQDA qualitative software was used to facilitate this process.
Finally, thematic analysis was used to make sense of the collected data. The goal
of thematic analysis was to identify patterns in a qualitative dataset and to explore an
individual’s understanding or interpretation of a concept. The major themes that emerged
were defined using knowledge gained from literature. Themes were conceptualized from
the categories of codes to create meanings that could be determined based on literature
and interpreted beyond the types of data for more significant purposes by linking the raw
data to research literature. Themes then constituted some form of codebook or template,
which enabled a structured approach to data interpretation (Cassell & Bishop, 2019). The
discussion of these major themes considered inputs from current studies related to the
research topic.
Reliability and Validity
Ensuring research reliability and validity was paramount to creating a high-quality
and practical knowledge base in any subject matter. The capacity of a qualitative study to
effectuate emancipatory goals or facilitate social action could be gauged by its validity
(McCabe & Holmes, 2009). Therefore, robust measures to guarantee the validity of
research were not merely advisable but imperative. Conversely, if the quality of a
qualitative study was compromised, it might result in unreliable data, leading to
inaccurate conclusions and misunderstandings.
Unlike in quantitative research, where the validity and reliability depended on the
instrument’s design, a qualitative research study’s quality largely relied on the researcher,
who played a role similar to the instrument in the research process. Validity and
reliability were inseparable concepts in this context, represented by terms like credibility,
transferability, and trustworthiness (Kettunen & Tynjälä, 2018).
For instance, the concept of reliability, as utilized in quantitative studies, might
not apply to qualitative research, which should preferably adopt consistency instead. On
the other hand, the validity of qualitative studies should have been determined by the
appropriateness of the tools, processes, and data involved. This implied that the research
question, the chosen methodology, the design of the study, the sampling and data analysis
methods, and finally, the drawn conclusions had to all be valid for the intended outcome,
sample, and context.
Various strategies were employed to ensure credibility in this study, including
those that considered most of the reliability and validity definitions, as discussed earlier.
It was also observed that validation procedures needed to be integrated into the ongoing
research process rather than implemented post-facto, allowing potential threats to validity
to be addressed during the study.
Reliability
Reliability in qualitative research refers to the consistency, stability, and
replicability of the researcher’s observations and findings (Tuval-Mashiach, 2021). It’s
about ensuring that the data collection and analysis methods would yield similar results if
the study were replicated under similar conditions. Unlike quantitative research, where
reliability is often tied to metrics like test-retest reliability, inter-rater reliability, or
internal consistency, qualitative research focuses on trustworthiness and authenticity,
ensuring the researchers’ interpretations are true to the participants’ experiences and
perspectives (Curtin & Fossey, (2007).
An essential aspect of achieving reliability in qualitative research is the use of
rigorous methodological procedures. These include triangulation, peer debriefing,
member checking, and keeping a thorough audit trail. Triangulation involves using
multiple data sources, methods, investigators, or theories to cross-verify findings
(Sridharan, 2021). Peer debriefing allows for an external check of the research process,
and member checking entails returning to the participants for confirmation of the findings
or interpretations. The audit trail includes detailed documentation of the steps taken in the
data collection and analysis processes to ensure transparency and reproducibility.
Despite these strategies, critics often argue that the subjectivity inherent in
qualitative research compromises its reliability (O’Connor & Joffe, 2020). However,
qualitative research aims not to achieve statistical generalizability but to delve deeply into
a phenomenon and understand the intricacies of human behavior and experience. The
consistency or reliability of qualitative research should therefore be seen in terms of the
coherence of the findings, the depth of insight generated, and the resonance of the results
with the participants’ experiences. As such, dependability and confirmability are often
used in qualitative research, emphasizing the need for the research process and findings to
be logical, traceable, and documented.
Validity
To enhance the validity of my qualitative study, I employed several strategies.
One such strategy was member checking, where researchers presented their
interpretations to the participants to verify the accuracy of their understanding. However,
the use of member checking was infused with assumptions about reality and knowledge
production that sat (conceptually) uncomfortably with reflexive TA—including the
notion that there was a truth of participants’ experiences that could be accessed if the
potentially distorting effects of researcher influence were kept in check (Braun & Clarke,
2023). Triangulation, which involved collecting data from multiple sources, using various
methods, or employing different theoretical perspectives, was another strategy I
employed to enhance validity. Additionally, I engaged in reflexivity, a process of
continually reflecting on and critically examining my biases, theoretical predispositions,
preferences, and so forth, that might affect the research process and findings. Reflexivity
allowed me to recognize, understand, and control my potential influences on the research,
enhancing its validity (Berger, 2015).
However, there were complexities around validity in qualitative research. Some
qualitative researchers argued that traditional notions of validity did not apply to
qualitative research due to its inherently interpretive and context-dependent nature (Selvi,
2019). Instead, they used alternative terms like trustworthiness, credibility, transferability,
and confirmability. The use of these alternative terms underscored the epistemological
differences between quantitative and qualitative research, with the latter prioritizing deep,
contextualized, and interpretive understanding of human experiences over
generalizability, predictability, and control. Despite these differences, the central concern
for both qualitative and quantitative research remained the same: producing accurate,
credible, and insightful knowledge about the phenomena of interest.
Credibility
I used the triangulation technique to bolster credibility and minimize biases in my
study. This involved incorporating multiple and diverse data sources to achieve
convergence. Combining different methods, like case studies and document analysis,
yielded richer data and heightened authenticity. Triangulation resulted in a
comprehensive set of findings, enhancing the credibility of my research (Carter,
BryantLukosius, DiCenso, Blythe, & Neville, 2014). Furthermore, Fusch and Ness
(2015) asserted there was a direct correlation between data saturation and triangulation,
with data triangulation being a strategy to ensure data saturation.
Member checking served as an effective way to prevent misinterpretation of
participants’ insights. This process involved presenting participants with the data and my
interpretation, allowing them to confirm or correct their intended meanings. This was a
crucial check for validation in qualitative research, as it reflected the socially constructed
reality and depicted what the participants perceived. The benefit of member checking was
that it could reinforce the data and lend more credibility to my study.
Collecting a diverse and detailed data set facilitated a comprehensive
understanding of participants. This data included what participants said, did, wrote, or
produced. In my case, interviews, documents, and field notes were used (Namey, Guest,
Thairu, & Johnson, 2018). Gathering sufficient data provided a complete depiction of the
phenomenon. Furthermore, ensuring rich data granted detailed insight into the cases or
phenomena under study (Bowen, 2020). To reduce research biases and improve my
study, debriefing sessions with a trusted peer were held (Birt, Scott, Cavers, Campbell, &
Walter, 2016). Moreover, sharing the study reports with the participants post-research to
explain the results aided in reinforcing my understanding and interpretation. Such
sessions were known to lessen biases and enhance the truth value (Malterud, Siersma, &
Guassora, 2016).
Transferability
Thick descriptions are critical in rendering a study transferable. These detailed
accounts assist readers in determining the truth-value of the research. Providing rich
details about the context also improves the transferability of the study (Elo, Kääriäinen,
Kanste, Pölkki, Utriainen, & Kyngäs, 2014). Transferability can be further enhanced by
employing purposeful sampling methods and providing a detailed description of the
process. It’s also recommended to transcribe the interview verbatim for future reference,
and ensure the analysis process is documented comprehensively. To ensure
transferability, these suggestions are meticulously adhered to in the study.
Confirmability/Dependability
A transparent and precise description of the research process, starting from the
initial outline to the development of the method and, finally, reporting of findings,
contributes to the confirmability of a study. It is also beneficial to maintain a research
diary, documenting issues and challenges encountered during the process and how they
were resolved (Etikan, Musa, & Alkassim, 2016). This approach strengthens the
connection between the study’s aim, design, and methods. Moreover, discussing
emerging themes with experts in an open process helps challenge assumptions and reach
a consensus.
To enhance dependability and confirmability, tracking and documenting the
research processes from beginning to end is crucial. This thorough documentation
facilitates the production of detailed and transparent reports at the conclusion of the study
(Nowell, Norris, White, & Moules, 2017). An excellent transparent report of the research
steps taken throughout the project enhances the study’s credibility and dependability.
Maintaining an audit trail is a key strategy for establishing the confirmability of
qualitative findings. The confirmability of a study can be improved by incorporating an
audit trail of the research to demonstrate that the study was conducted with substantial
care, thus improving its trustworthiness.
Transition and Summary
This qualitative multi-case study investigates the strategies utilized by IT
professionals to strengthen blockchain technologies, consequently improving system
resiliency. The targeted demographic comprises IT professionals from infrastructure and
development teams across the United States. The research may highlight deficiencies in
the resiliency of IT systems within organizations and the potential of blockchain
technology to mitigate such risks. By demonstrating this, the study may suggest that
business leaders must devise a resilient IT architecture that addresses potential
inadequacies in IT infrastructure and procedures. This, in turn, could have societal
implications by potentially minimizing the downtime of crucial IT platforms, such as
hospital systems, essential supply chains, and utility services. My technology industry
experience and interest in applying blockchain as a data layer for micro-service
applications informed the study’s focus. In Section 3, I will delve into a detailed
discussion of the results derived from the collected interview data. This analysis will aid
in formulating conclusions from the data.
Section 3: Application to Professional Practice and Implications for Change
Introduction
This qualitative, multiple case study was conducted to investigate the strategies
employed by IT security managers for the secure deployment of blockchain technology.
Data for this study were gathered through semistructured interviews with four IT
Professionals from companies specializing in blockchain and a review of company
documents. Data analysis revealed three main themes: (a) decentralization, (b) privacy,
and (c) transaction speed. This study helps to understand how IT professionals can
support blockchain technologies to enable resilient systems. Additionally, it discusses the
role of decentralized architectures in enhancing system resilience and reducing
vulnerabilities associated with centralized models. Furthermore, the study sheds light on
the practical implications and challenges faced by IT professionals in adapting and
implementing blockchain technologies within established IT infrastructures. In this
section, I delve into the findings, their relevance to professional practice, their social
change implications, action recommendations, suggestions for subsequent research, and a
conclusion.
Presentation of the Findings
The research question for this study was “What strategies do IT professionals use
to support blockchain technologies to enable resilient systems?” My target population
was IT professionals from the development and infrastructure teams with blockchain
experience in the United States. I used a purposeful sampling strategy to select and
interview four IT professionals within two companies specializing in blockchain
technology in the smart contract industry, all of whom possess extensive experience in
blockchain systems. Data were collected through semistructured interviews and a
comprehensive review of company documents to achieve triangulation. Member checking
was performed with the participants to validate the interpretations of their input. Data
saturation were confirmed when data collection reached a point where no new themes
emerged. The collected data were analyzed using a five-step procedure comprising data
logging, anecdotes, vignettes, data coding, and a thematic network
(Akinyode, 2018).
All participants were voluntary and consented to join the study by stating “yes” in
the audio recording. Pseudonyms were used to protect the identities of the participants’
names (P1-P4), and their company names (C1-C2) are confidential. Each company
provided two participants. P1 and P2 are in C1, and P3 and P4 are in C2. Each participant
was interviewed for about 45 minutes using Microsoft Teams. The video interviews were
transcribed using Microsoft Teams and Supernormal notetaker. All documentation and
transcription were uploaded into the MAXQDA document system to analyze and develop
themes on the given data. The results align with the literature review’s change
management theory and analysis.
Theme 1: Decentralization
Decentralization is a cornerstone for building resilient systems by eliminating
single points of failure, characteristic of centralized models, which are vulnerable to
attacks and system downtimes (Aoun et al., 2021). In a decentralized system, data and
control are distributed across a network of nodes, ensuring that the compromise or failure
of one node does not jeopardize the entire system. Through a decentralized protocol, the
owners have absolute authority over their resources and have the right to exchange assets
with anyone at any time (Hazari & Mahmoud, 2020). IT professionals leverage this
principle, implementing strategies that distribute data and control to mitigate the risks
associated with centralized models and foster environments that are less susceptible to
attacks. This architecture also fosters enhanced security and robustness, requiring
consensus among multiple nodes to validate transactions or make changes, making it
inherently resistant to fraudulent activities and cyber-attacks. Furthermore, IT
professionals ensure that decentralized systems maintain adaptability and can recover
swiftly from adverse situations, which is paramount for maintaining system functionality
and resilience. By reducing reliance on a central authority and fostering a more
democratic and robust infrastructure, decentralization is pivotal in cultivating system
resilience.
The participants discussed the concept of decentralization and how it can benefit
the resilience of enterprise systems. For example, P1 discussed the uses of
applicationspecific blockchains within a broader blockchain environment: “You can
launch application-specific chains, including those tailored for gaming, all using the C1
Zero technology. These chains can then employ inter-blockchain communication and
zeroknowledge roll-ups to validate transactions.” P2 affirmed this observation by
referencing blockchains having the same underlying technology to enable easier adoption
for enterprise applications by using an open-source platform: “We use an open-source
blockchain protocol named Antelope, developed by a talented team of engineers.” The
shared insights from P1 and P2 highlight the versatility and adaptability of blockchain
technologies, specifically through utilizing application-specific chains and open-source
protocols, which are integral in fostering resilience and facilitating smoother adoption in
enterprise applications.
Another aspect of resiliency discussed was the limitation of blockchain
technologies and data storage. Since the blockchains require that the ledger is duplicated
among a set of decentralized validators, the database exists within each validator to bring
a consensus to each transaction (Yang et al., 2020). For example, P3 provided the
following example: “You’re not going to be able to throw a multi-terabyte database from
an enterprise onto a blockchain quite as easily.” P4 affirmed this limitation with the
following observation:
Not all data needs to be put on chain but can be cross-verified by a piece of data
that is onchained. You can basically spin up a server for the period of time you
need it to be this large amount of data processing.
The reflections from P3 and P4 underscore the challenges of integrating large-scale
databases into blockchain technologies, emphasizing the necessity for selective on-chain
data storage and validation.
The participants’ findings elucidate several strategies IT professionals employ to
harness blockchain technologies for building resilient systems. As highlighted by P1 and
P2, one prominent strategy is the development and utilization of application-specific
blockchains within a broader blockchain environment, leveraging technologies such as
C1 with Antelope. This approach, underpinned by decentralization, inter-blockchain
communication, and zero-knowledge roll-ups, showcases the versatility and adaptability
of blockchain, which are crucial for fostering resilience. Additionally, using open-source
platforms facilitates smoother adoption, especially in enterprise applications, by ensuring
that diverse applications can be easily integrated, thus enhancing the overall resilience
and versatility of the systems.
On the other hand, the insights from P3 and P4 shed light on the limitations and
challenges associated with blockchain technologies, particularly in data storage. The
inherent requirement of blockchain for duplicating ledgers among decentralized
validators poses challenges for integrating multi-terabyte databases from enterprises. This
necessitates a selective approach to on-chain data storage and validation, emphasizing the
need for innovative solutions to manage large-scale data while maintaining the integrity
and security of the system. Strategies such as spinning up servers for temporary data
processing, as suggested by P4, exemplify the adaptive measures taken by IT
professionals to circumvent these challenges and ensure the resilience and functionality
of blockchain-enabled systems.
Navigating the challenges and potentials of blockchain technologies, participant
reflections, and strategies inadvertently intersect with Kruger’s change management
theory or the change iceberg. Kruger framed change management as an iceberg: above
the waterline are visible elements like technical problems, while beneath it are less
observable factors like attitudes and fears that can profoundly obstruct change initiatives.
Participant dialogues articulate strategies, such as selective data deployment onto
blockchains (P3 and P4) and utilizing application-specific chains and open-source
protocols (P1 and P2), which adeptly address visible technical challenges—the iceberg’s
tip. However, these strategies also illuminate sophisticated approaches toward managing
overt technical aspects; their success is fundamentally linked to managing submerged
elements like organizational culture and individual attitudes toward new technologies.
Consequently, a nuanced exploration of Kruger’s iceberg underscores the imperative to
align technical strategies with a thorough comprehension and management of underlying
beliefs and cultural nuances among the IT professional community and organizational
environments to holistically foster and sustain resilient blockchain systems, ensuring
professional strategies to bolster technical robustness and system resilience are
symbiotically harmonized with organizational strategies that navigate and transform the
concealed, human, and cultural dynamics.
The adoption of application-specific blockchains and open-source protocols, as
discussed by P1 and P2, addresses the surface-level of the iceberg by providing technical
solutions that enhance the versatility and adaptability of blockchain technologies. By
employing technologies like Antelope, IT professionals manage change’s visible,
technical aspects, foster resilience, and facilitate smoother adoption in enterprise
applications. Consequently, IT professionals are addressing immediate technological
needs and navigating the broader challenges of integrating blockchain into existing
organizational infrastructures, thereby aligning technical functionality with organizational
strategy and operational flow. However, the insights from P3 and P4 underscored the
need for innovative solutions, as integrating these technological strategies in real-world
applications potentially brings forth hidden challenges. For instance, it can be difficult to
establish trust in these novel approaches, reshape organizational norms around data
storage and security, and redefine roles and responsibilities within the IT professional
community. Hence, though the interviewees did not explicitly mention beliefs and
attitudes, it is implied that successful strategy integration, as alluded to by the technical
solutions of P3 and P4, would require navigating through the submerged aspects of
Krüger’s iceberg to ensure coherent and sustainable implementation within an
organization’s existing cultural and structural paradigm. As organizations navigate the
course toward leveraging blockchain technologies for bolstering resilience, the
integration of technical strategies and the concurrent transformation of underlying
organizational structures and cultural norms emerge not merely as a parallel process but
as a co-evolving phenomenon, where technological solutions and organizational change
are intertwined in a dance, each shaping and being shaped by the other, towards fostering
a resilient, secure, and privacy-preserving decentralized digital future.
Theme 2: Privacy
Blockchain technology stands at the forefront of addressing privacy concerns,
offering myriad solutions to safeguard data and enhance the security of digital
transactions. As the digital landscape evolves, IT professionals are exploring innovative
strategies to harness blockchain’s potential to fortify privacy within systems, thus
contributing to overall resilience (Zhang et al., 2019). The inherent characteristics of
blockchain, such as decentralization, encryption, and immutability, serve as foundational
elements in establishing secure and private environments. Privacy includes links between
transactions that should not be visible or discoverable (Feng et al., 2019). With this in
mind, the research question, “What strategies do IT professionals use to support
blockchain technologies to enable resilient systems?” guides an exploration into the
diverse approaches employed by IT professionals to leverage blockchain’s privacy
features, aiming to uncover how these strategies contribute to the development of robust
and resilient systems. This inquiry explored the intricate balance between transparency
and privacy that blockchain presents, exploring how IT professionals navigate this
dynamic to optimize system security and data protection.
When considering public blockchains, it is important to also consider that the data
stored on this database are publicly exposed. For example, P2 made the following
observation on privacy with blockchain networks:
Privacy concepts in blockchain are often misunderstood. Many assume these
features exist by default, but they currently don’t. While there are technological
methods to introduce some level of privacy, it’s generally a situation where
transactions are anonymous until they aren’t. Consider the traditional banking
systems and regulations like GDPR, which prevent public disclosure of
individuals’ salaries. However, if salaries were distributed via blockchain, once
someone identifies an account with an employee, that salary becomes public
knowledge. Thus, there are certain privacy limitations in current blockchain
technologies. However, emerging tools, like zero-knowledge proofs, may offer
solutions in the future.
P1 affirmed this concern with the following statement: “Large commercial industries see
a lot of value in their data, and they don’t want other people to get access to it.” P4 also
stated, “If your data is intended to be private. Blockchain technologies aren’t going to be
private by default.” P3 further noted, “When using blockchain technology, organizations
must differentiate between information that can be made public and what should remain
private.” And P3 stated that he has not seen any blockchain technologies addressing
privacy concerns.
When interpreting these findings through the lens of Krüger’s change
management (change iceberg) theory, it becomes apparent that addressing the challenges
associated with privacy in public blockchains encompasses both visible and hidden layers
of change (Bedrii, 2020). Krüger’s theory underscores the importance of acknowledging
not just the overt, technical challenges (the tip of the iceberg), but also the covert, deeper
issues related to people’s attitudes, fears, and the organizational culture and norms (below
the surface; Bedrii, 2020). In light of Krüger’s change management theory, which asserts
that observable phenomena (e.g., behaviors or technologies) are frequently underscored
by obscured motivational forces and structures (such as cultural paradigms and implicit
regulations), privacy predicaments inherent to public blockchains may be construed not
merely as a technological difficulty, but as an organizational problem that infiltrates more
profound structural and cultural strata (Kruger, 2022). Participants P1 and P4 underscored
a crucial observation: entities, particularly within expansive commercial sectors,
prioritize their data confidentiality and exhibit an inherent hesitancy toward overt
dissemination. This aversion is not merely a superficial challenge (the overt part of the
iceberg in Krüger’s conceptualization) but also encompasses more cryptic, intangible
apprehensions, including confidence in the technology, organizational preparedness for
transparency, and potential incongruities with prevailing data protection norms, such as
the General Data Protection Regulation and the California Consumer Privacy Act with
implementation dates in 2018 and 2020 (Li et al., 2020).
Within the comprehensive schema of blockchain adoption, safeguarding privacy
transcends the mere implementation of technological solutions. It concurrently demands
an organizational metamorphosis that harmonizes with extant privacy norms and values,
necessitating a navigation and potential modification of the underlying structures and
cultural norms (the submerged portion of Krüger’s iceberg) (Bedrii, 2020). This
necessitates meticulous scrutiny and possible reconfiguration of prevailing systems,
philosophies, and practices pertinent to data privacy within organizations, synchronously
aligning with technological progress to ensure that privacy remains inviolate when
utilizing a public blockchain. Consequently, the interview data unveil a poignant
confluence where technological progression and organizational change management must
amalgamate to navigate the perceptible privacy challenges proffered by blockchain
technologies proficiently.
However, beneath this technical layer lie deeper, more covert challenges. The
participants’ concerns about the potential exposure of sensitive information, such as
salaries, and the reluctance of commercial industries to share valuable data, point to
underlying fears and attitudes that need to be addressed. These sentiments indicate a need
for a shift in perception and understanding of privacy within the blockchain domain,
which aligns with the submerged aspects of the change management theory, emphasizing
attitudes, beliefs, and fears. Navigating through the narratives of P1 through P4, a
palpable apprehension emerges, reflecting a trepidation toward potential inadvertent
disclosure of information, revealing an inherent skepticism towards blockchain’s
capability to safeguard privacy – a fundamental aspect deeply ingrained within
organizational culture and data management beliefs. P2’s observation highlights a
tangible fear: the tension between the theoretical anonymity of blockchain transactions
and the stark reality that, once deciphered, these transactions become irrevocably public,
thereby surfacing beliefs that privacy cannot be unequivocally assured within the current
technological framework. Security and privacy of blockchains continue to be at the
center of the debate when deploying blockchain in different applications (Zhang et al.,
2019). P4’s assertion encapsulates anticipatory anxiety grounded in the belief that despite
the ostensibly private nature of blockchain, in reality, sensitive data is perpetually at risk,
accentuating an overarching belief and fear matrix that privacy within the blockchain, in
its present state, is paradoxically public, highlighting an urgent call for technological and
organizational alignment to mitigate these concerns and navigate the treacherous waters
of privacy assurance.
Moreover, the concerns expressed by P1, P3, and P4 about the limitations of
existing blockchain technologies in addressing privacy reflect an organizational culture
and norms aspect. Organizations and industries must undergo a cultural shift to prioritize
and value privacy, aligning their norms and practices with the evolving capabilities of
blockchain technologies. This transformation aligns with the deepest layer of Kruger’s
iceberg, requiring reevaluating values and norms to manage change successfully (Kruger,
2022). As highlighted by participants, barriers to this requisite cultural shift towards
privacy encompass tangible and intangible facets, such as prevailing misunderstandings
about blockchain’s inherent privacy capacities and an ingrained reluctance to diverge
from traditional data management frameworks due to skepticism toward new
technologies. Moreover, the dichotomy between existing norms, which are primarily
rooted in traditional, centralized data management systems, and the decentralized,
immutable nature of blockchain erects a formidable barrier, necessitating not only a
technological adaptation but also a fundamental reorientation and realignment of
organizational values, beliefs, and norms toward data privacy and management in the
blockchain realm.
Addressing the privacy concerns in public blockchain technologies necessitates a
multifaceted approach, encompassing both technical solutions and shifts in attitudes,
beliefs, and organizational culture, as highlighted by Krüger’s change management theory
(Bedrii, 2020). By considering and addressing both the visible and hidden dimensions of
change, a more comprehensive and effective approach to managing privacy in blockchain
can be realized.
As the discourse regarding privacy in blockchain technologies unfolds, a complex
tableau surfaces, unveiling not just the overt technical conundrums but also the covert
challenges entwined in organizational culture, attitudes, and underlying fears, effectively
illuminated by Krüger’s change management theory (Kruger, 2022). This exploration,
steered by the insights shared by participants P1 through P4, heralds a crucial
appreciation of the privacy challenges in blockchain, which although palpably
technological, are also deeply interlaced with hidden dimensions of change. While
blockchain presents an ostensibly decentralized and secure environment, concerns
regarding the actualization of true privacy pervade, as exemplified by potential exposures
of sensitive data and the tangible apprehension within industries regarding the public
visibility of certain information (Feng et al., 2019).
Addressing these apprehensions and navigating through the murky waters of
privacy assurance within blockchain technologies necessitates a synchronized dance
between advancing technological capabilities and maneuvering through organizational
changes, entailing an alignment of both the visible and submerged aspects of change
(Bedrii, 2020). The subsequent path forward beckons a comprehensive alignment of
technological strategies with cognizant, empathetic navigation through the existing fears,
beliefs, and organizational norms that may otherwise form concealed icebergs,
obstructing blockchain technologies’ seamless adoption and optimization. Therefore, the
task ahead for IT professionals and organizational leaders pivots on conjointly ensuring
technical robustness while also crafting a navigational map that diligently addresses and
steers through the submerged, often unseen, cultural and emotional terrains to holistically
embed and optimize blockchain technologies within a framework that is resilient, secure,
and privacy-assured.
Theme 3: Transaction Speed
In exploring blockchain technologies’ role in fostering resilient systems, a pivotal
consideration emerges around the impact of transaction speeds. This factor is intrinsic to
the performance and efficiency of blockchain networks, influencing how swiftly data can
be processed, validated, and recorded on the ledger. Slow transaction speeds can act as a
bottleneck, potentially compromising the responsiveness and adaptability of the system
(Li et al, 2020). In contrast, faster speeds can enhance the system’s ability to manage high
volumes of data and respond to challenges effectively. With the research question, "What
strategies do IT professionals use to support blockchain technologies to enable resilient
systems?" in focus, this study delves into the significance of optimizing transaction
speeds within blockchain technologies and how IT professionals strategize to balance
speed with decentralization and privacy, thereby contributing to the overall resilience of
the systems they support. This exploration aims to uncover the nuanced strategies
employed and the challenges encountered in harmonizing transaction speeds with the
diverse demands of resilient blockchain-based systems.
Regarding migrating enterprise databases to blockchain technology, P1 makes the
following observation.
When considering migrating a Postgres database to the blockchain, it’s a complex
process and a significant endeavor. While it’s possible to transfer a large amount
of data onto a blockchain, it’s time-intensive. Such a migration would
immediately inflate the data for any indexers. The blockchain we’ve used can
handle up to 15,000 EVM transactions per second.
P2 affirms this conclusion with the statement: “With decentralized execution, that whole
concept of hundreds of nodes having to run all the same transactions and store all the
same data. It’s not really efficient to store large amounts of data on the blockchain.” P3
also references the transaction speeds in comparing enterprise databases such as Postgres,
in comparison with blockchain technologies with the following; “Postgres databases
could process more transactions at once, compared to blockchain technologies.
Resources. P4 then asserts the transaction speed concern with blockchain technologies:
"Within enterprise applications, data needs to be processed within 30 milliseconds.” This
is concerning when considering blockchain technologies process transactions within
seconds to minutes, not milliseconds.
The observations made by the participants about migrating enterprise databases to
blockchain technology can be comprehensively analyzed through Krüger’s change
management theory. This theory posits that successful change involves addressing the
visible, technical aspects (the tip of the iceberg) and the underlying attitudes, beliefs,
fears, and organizational culture and norms (beneath the surface).
At the tip of the iceberg, the technical challenges of migrating databases, such as
data bloat and inefficiency in storing large amounts of data on the blockchain, are readily
apparent. P1’s remark on the complexity and time-consuming nature of the task and P2’s
affirmation of the inefficiency of decentralized execution elucidate these tangible,
technical hurdles. Similarly, P3 and P4’s concerns about transaction speeds further
underscore the practical issues that need addressing.
Diving deeper beneath the surface, we encounter individuals’ attitudes and beliefs.
The participants’ reflections reveal a prevailing skepticism and cautiousness regarding the
feasibility and efficiency of integrating traditional databases with blockchain technology
(Kruger, 2022). Addressing these concerns requires fostering a belief in the potential
benefits and long-term efficiencies that blockchain can bring, even with its current
limitations. Mitigating fears and cultivating a positive attitude toward the change is
essential for successful implementation.
At the deepest layer, we find organizational culture and norms. The participants’
observations suggest a potential clash between the established norms of enterprise
applications, where data needs to be processed swiftly, and the emerging blockchain
technologies. Organizations might need to reassess and realign their expectations and
norms around data processing speeds and efficiency to integrate blockchain technologies
successfully. Therefore, effectively managing the migration of enterprise databases to
blockchain technologies necessitates a multifaceted approach. This involves addressing
the overt technical challenges, transforming attitudes and beliefs about the technology,
and aligning organizational norms and values with the new paradigm, as Krüger’s change
management theory underscored (Bedrii, 2020). A holistic and successful change
management strategy can be developed by navigating through these different layers of the
iceberg.
The given passage highlights the role of transaction speeds in blockchain
technologies as crucial for developing resilient systems. The findings reveal specific
strategies IT professionals implement to enhance transaction speeds within blockchain
technologies. While prioritizing this optimization, they also meticulously navigate the
intricate balance between ensuring decentralization and safeguarding privacy. In
blockchain technology, decentralization refers to the distribution of control and
operations across multiple nodes or participants, eliminating the need for a centralized
authority. Meanwhile, privacy entails securing transactional and participant information
from unauthorized access. Therefore, IT professionals engage in a delicate orchestration
of strategies that amplify transactional efficiency and uphold the pivotal aspects of
decentralization and privacy, ensuring that one does not undermine the other. This
balance is crucial in maintaining the integrity and functionality of blockchain systems
within organizational settings. The optimization of transaction speeds is portrayed as
intrinsic to the efficiency and performance of blockchain networks, affecting the system’s
responsiveness and ability to manage high volumes of data. The passage also references
the complexity of migrating traditional enterprise databases like Postgres to the
blockchain, pointing out the inefficiencies in storing large amounts of data on the
blockchain and the challenges in processing speeds, which are integral to enterprise
applications. The transaction verification process for cryptocurrencies is much slower
than traditional digital transaction systems (Hazari & Mahmoud, 2020).
Relating to the research question, "What strategies do IT professionals use to
support blockchain technologies to enable resilient systems?" this passage underscores
the significance of addressing transaction speed concerns in blockchain technologies. IT
professionals face the challenge of harmonizing transaction speeds with the demands of
resilient blockchain-based systems, particularly when migrating large enterprise
databases. The insights from different professionals (P1-P4) illustrate the complexities
and affirm the critical nature of transaction speeds, emphasizing the need for strategic
approaches to leverage blockchain’s capabilities for building resilient systems while also
managing the inherent limitations and inefficiencies in data storage and processing.
In navigating the intricacies of optimizing blockchain technologies for resilient
systems, transaction speeds’ pivotal role, especially in migrating large enterprise
databases, has been thoroughly examined. Various participant observations highlight the
complexity, time-intensive nature, and inherent inefficiencies in dealing with expansive
data within blockchain technologies, showcasing tangible technical challenges that IT
professionals meticulously navigate. In amalgamating these insights with Krüger’s
change management theory, it is emphasized that beneath the overt technological
challenges, deeper layers of attitudes, fears, and organizational norms significantly
influence the successful implementation and management of blockchain technologies
(Kruger, 2022).
The pivotal balance between ensuring data processing efficiency while
maintaining decentralization and privacy propels IT professionals to conceive and
implement nuanced strategies that not only address the visible, technical aspects of
blockchain implementation but also gently navigate through the underlying beliefs,
attitudes, and organizational norms, which can either facilitate or hinder the seamless
incorporation of blockchain technologies within enterprise contexts (Bedrii, 2020).
Therefore, the forward path leans towards crafting a holistic approach to implementing
blockchain technologies, one that is firmly rooted in technical robustness while being
tenderly entwined with an empathetic understanding and navigation through the
emotional and cultural undercurrents of organizational change, ensuring that the
technological adoption is not merely efficient but is also harmoniously embedded within
the organizational milieu, thereby fostering genuinely resilient systems.
Applications to Professional Practice
The findings of this study provide a deep understanding of the strategies
employed by IT professionals to leverage the capabilities of blockchain technologies,
particularly in creating resilient systems. A core theme is the value of decentralization,
marking a decisive shift away from vulnerable centralized models. By distributing data
and control, decentralization not only enhances security but also promotes adaptability
(Abimbola, 2019). This is further highlighted by the growing interest in
applicationspecific blockchains and the adoption of open-source protocols, emphasizing
the versatility and adaptability of blockchain technologies.
However, the study does not shy away from recognizing significant challenges.
The integration of large-scale databases into blockchain technologies presents logistical
difficulties due to the inherent requirement of duplicating ledgers across validators.
Innovative solutions, such as temporarily activating servers for data tracking, are among
the approaches used to address these issues. Furthermore, application-specific
blockchains and open-source protocols are viewed as instrumental tools to enhance
adaptability and resilience in the blockchain arena.
Privacy, especially in the context of public blockchains, emerges as a pressing
concern. The transparent nature of these blockchains can inadvertently expose data,
leading to potential breaches of privacy. Technical solutions are being explored to
address these privacy concerns without undermining the decentralized essence of
blockchain. The theory by Krüger, which highlights both overt and covert challenges,
offers a comprehensive perspective. Beyond just technical solutions, such as the
integration of features like zero-knowledge proofs, there’s a broader need to address
societal attitudes, apprehensions, and the prevailing organizational culture surrounding
privacy.
Performance metrics, especially transaction speeds, are vital in evaluating the
practicality and efficiency of blockchain-based systems. Migrating databases presents
unique challenges, and concerns arise about the potential inefficiencies inherent in
decentralized execution. There’s a recognized gap in transaction speeds when comparing
traditional systems to blockchain technologies. Striking a balance between speed,
decentralization, and privacy is a nuanced endeavor that IT professionals strive to perfect
to enhance both the resilience and performance of the systems they oversee.
In the realm of IT, particularly in implementing blockchain technologies, the
applicability of Krüger’s change management theory becomes evident. On the surface, it
might appear that the transition is primarily about technical integration — understanding
the technological underpinnings, ensuring efficient transaction speeds, and optimizing
data storage (Bedrii, 2020). These are akin to the "above water" portions of the iceberg,
the overt challenges that are immediately identifiable. However, beneath these lie the
more intricate, covert challenges. Adapting to blockchain technology might mean
reshuffling organizational structures, addressing latent resistance from employees
unfamiliar or uncomfortable with the new technology, or overcoming traditional mindsets
that favor centralized over decentralized systems.
Furthermore, the deeper submerged issues — deeply ingrained organizational
culture, subconscious fears, and individual concerns — resonate with the privacy
challenges highlighted in the study (Bedrii, 2020). The overt challenge is to ensure data
remains private and secure on the blockchain technically (Zhang et al., 2019). But
beneath that, there lies the need to reassure stakeholders, change attitudes towards data
transparency, and address subconscious fears about the immutability of blockchain
records. In light of Krüger’s theory, the true efficacy of blockchain adoption lies in
addressing the overt challenges and navigating and managing the more profound, hidden
aspects of change.
In conclusion, the evolving landscape of IT and blockchain technologies presents
both immense potential and multifaceted challenges. The value of decentralization,
emphasizing security and adaptability, remains a beacon for innovation. However, as
organizations wade through these uncharted waters, they must confront visible and
submerged challenges, as Krüger’s change management theory articulated (Bedrii, 2020).
While technical challenges demand rigorous solutions, the deeply rooted, often covert,
cultural, and psychological barriers will shape the trajectory of blockchain’s adoption and
integration. A holistic approach, which recognizes and addresses both the explicit and
implicit dimensions of change, will be pivotal in harnessing the full potential of
blockchain technologies, ultimately leading to resilient, efficient, and transparent systems
for the future.
Implications for Social Change
The ongoing evolution of blockchain technologies presents significant
implications for social change, particularly in the domains of resilience, data security, and
privacy. This evolution offers prospects for tangible improvements across individuals,
communities, organizations, institutions, cultures, and societies.
Individuals and Communities
The decentralization inherent in blockchain technologies represents a profound
shift away from traditional centralized systems. For individuals and communities, this
decentralization can be empowering. No longer bound by a single point of control,
individuals can have increased ownership and influence over their data, transactions, and
digital identities (Hazari & Mahmoud, 2020). In community settings, this technology can
foster a more egalitarian atmosphere, as the power and control previously held by a few
can be dispersed across the community. This democratization can enhance transparency,
trust, and collaboration, thereby leading to stronger, more resilient communities.
Organizations and Institutions
For businesses and institutions, the adaptability and resilience offered by
blockchain technologies can lead to more robust and reliable systems. As highlighted by
the research findings, IT professionals are focusing on application-specific blockchains
and open-source platforms to ease adoption. The versatility of blockchain technologies
ensures that organizations can maintain adaptability, recover swiftly from adverse
situations, and have systems less susceptible to cyber-attacks (Feng et al., 2019). By
moving away from single points of failure and employing decentralized structures,
businesses can benefit from reduced downtimes, leading to increased productivity and
profitability. Institutions, especially those that handle sensitive data, can implement
blockchain for heightened security measures, ensuring data integrity and trust among
stakeholders.
Cultures and Societies
On a broader cultural and societal scale, the challenges highlighted, especially
regarding privacy concerns, represent a call for increased awareness and understanding of
the implications of digital technologies. Cultures must evolve to place a premium on data
privacy, demanding that digital solutions, including blockchain, uphold the highest
security standards. As society becomes more digitalized, fostering a culture of privacy
and security becomes paramount, ensuring that individuals’ rights and freedoms are
maintained in an increasingly interconnected world. Additionally, the potential
limitations of blockchain, such as data storage issues and transaction speeds, remind
society of the importance of continuous innovation and adaptation to technological
challenges (Li et al., 2020).
Improving Public Health Outcomes
With blockchain-enhanced EHRs, patient data becomes more accessible and
transparent across various health care providers. This can lead to improved medical
outcomes, as health care professionals get a comprehensive view of a patient’s medical
history, enabling more informed decisions. Better health outcomes at the individual level
can translate to healthier societies, reducing the burden on public health infrastructure and
potentially lowering health care costs for individuals and governments (Abimbola,
2019).
Empowering Consumers
In supply chain systems, blockchain’s transparency gives consumers the power to
make informed choices. Health companies are exploring the use of blockchain, a
tamperproof and distributed digital ledger, to address some of these challenges
(Velmovitsky, 2021). They can trace the origin of products, which can influence
purchasing decisions, especially concerning ethically produced, sustainable, or genuine
products. As consumers become more conscious and demand transparency, businesses
are compelled to adopt ethical and sustainable practices, driving a shift towards more
responsible production and consumption.
In conclusion, the burgeoning potential of blockchain technologies, combined
with the challenges highlighted, offers an intriguing backdrop for social change. While
the technology promises decentralization, enhanced security, and adaptability, it also
brings forth challenges that society must address. By understanding and integrating these
implications, there’s an opportunity to catalyze positive transformations across
individuals, communities, organizations, institutions, cultures, and societies. Blockchain
is not just a technological innovation; it’s a driver for holistic social change.
Recommendations for Action
The findings have unequivocally emphasized the significance of decentralization
in creating resilient blockchain systems. For companies and IT professionals focused on
leveraging blockchain for enhanced security, decentralization should be prioritized. For
increased adaptability, application-specific chains and open-source protocols such as
Antelope (previously EOSIO) should be explored. Enterprises should also consider
training programs to foster deeper understanding and expertise. Blockchain industry
stakeholders, such as software developers, IT managers, and tech entrepreneurs, should
pay close attention to these findings. A possible method for disseminating these results
might be through whitepapers, IT conferences, and webinars tailored for blockchain
specialists.
With respect to data storage limitations on blockchain, the inherent challenge of
incorporating large-scale databases into blockchain systems has been highlighted. IT
professionals and decision-makers in organizations must be selective in deciding which
data should be stored on-chain and which should remain off-chain (Khan et al., 2021).
Block size can affect transaction throughput and latency, which can be indirectly linked
to the consensus model. This calls for developing advanced tools and strategies to
manage large-scale data effectively without compromising blockchain integrity. Given
the technical nature of these challenges, software engineers, database administrators, and
IT strategy heads should be particularly attentive to these findings. Technical workshops
and database optimization seminars might be beneficial to communicate these results.
Privacy has emerged as a critical concern in the public blockchain domain.
Investing in research and development for blockchain technologies that integrate
advanced privacy features, such as zero-knowledge proofs, is imperative to counter this
(Li et al., 2020). Organizations must also undergo a cultural shift to recognize and
prioritize the value of privacy in blockchain systems. Given the wider implications of
privacy, stakeholders ranging from IT professionals to top-tier management should heed
these findings. These results could be shared via industry reports, training programs, and
thought leadership articles emphasizing the importance of privacy in blockchain
ecosystems.
The issue of transaction speed is at the forefront of blockchain efficiency and
resilience. The findings stress the need to strike a balance between speed,
decentralization, and privacy. Blockchain transaction throughput decreases with the
increasing number of peers that validate consensus (Khan et al., 2021). Companies
should consider technological solutions and strategies to optimize transaction speeds
without compromising on the core principles of blockchain. IT professionals should
closely consider these findings, especially those focused on performance optimization
and infrastructure management. Sharing this information through benchmark reports,
performance metric dashboards, and performance improvement workshops could
effectively disseminate the results to the intended audience.
In addressing the research question, "What strategies do IT professionals use to
support blockchain technologies to enable resilient systems?", the findings underscore
four pivotal areas: decentralization’s primacy, challenges in data storage, the imperative
of privacy, and the balance needed between transaction speed, decentralization, and
privacy. Decentralization emerges as a cornerstone for resilience, while data storage on
blockchain necessitates discernment between on-chain and off-chain data. Privacy
concerns in the public blockchain domain call for both technological advancements and
cultural adaptation and transaction speed’s significance is weighed against the
foundational principles of blockchain.
When applied to these findings, Krüger’s change management theory suggests
that the overt challenges, such as privacy and transaction speeds, represent just the tip of
the iceberg. Beneath the surface lie more profound organizational beliefs, perceptions,
and values about decentralization, privacy, and data storage. To harness blockchain’s
potential for resilience, IT professionals must navigate the visible challenges and the
underlying cultural and attitudinal shifts, ensuring a comprehensive, in-depth approach to
blockchain technology adoption and optimization (Bedrii, 2020).
Recommendations for Further Study
This study explored the pivotal role of decentralization in fostering resilience in
blockchain technologies, primarily through implementing application-specific
blockchains and open-source protocols. Participants P1 and P2 shared insights on the
versatility and adaptability of such technologies, highlighting their potential to bolster
system resilience. Given this foundational understanding, future research could delve
deeper into the specific advantages and limitations of various application-specific
blockchains, exploring how they cater to the unique requirements of different industry
sectors. A comparative analysis of decentralized architectures, including C1’s Antelope
and other emerging technologies, could provide a richer perspective on optimizing
resilience across various applications.
A recurring theme from participants P3 and P4 was the challenges of integrating
large-scale databases into blockchain technologies. The inherent duplication of ledgers
among decentralized validators poses a barrier to incorporating vast databases seamlessly
(Hazari & Mahmoud, 2020). This finding points to the need for further study on
innovative solutions that enable selective on-chain data storage while retaining the
integrity, security, and resilience inherent to blockchain technologies. Research could
explore mechanisms like temporary data servers or other adaptive storage solutions,
evaluating their efficiency and scalability in real-world scenarios.
A crucial area that surfaced during this study was the privacy vulnerabilities
inherent to public blockchains. While blockchain technologies promise enhanced security
through decentralization, encryption, and immutability, concerns persist about the
potential exposure of sensitive information, as highlighted by participants P1, P3, and P4.
Further research is warranted to delve into privacy-enhancing technologies within the
blockchain domain, such as zero-knowledge proofs or advanced encryption techniques.
Current blockchain technologies store sensitive data on the blockchain that would be
accessible to anyone, resulting in a lack of privacy (Li et al., 2020). Additionally, a study
could explore how organizational cultures and norms adapt to prioritize privacy in
blockchain implementations, ensuring alignment with the evolving landscape.
The balance between transaction speed, decentralization, and privacy emerged as
pivotal in ensuring blockchain resilience. Slow transaction speeds could compromise a
system’s responsiveness and adaptability, yet increasing speed might risk compromising
other resilience factors (Hazari & Mahmoud, 2019). Participants P1, P2, P3, and P4
highlighted the intricacies and challenges of this balancing act. Given the significance of
this balance, future studies could explore optimization strategies that harmonize these
factors. A particular emphasis could be placed on how emerging blockchain technologies
manage transaction speeds, ensuring rapid data processing while retaining the benefits of
decentralization and enhanced privacy.
Reflections
The research journey has been an exhilarating endeavor from a personal and
professional standpoint. At the outset, I had underestimated the intricacies of identifying
the study’s ideal participants. This task was further complicated by the need to find
participants possessing developer and infrastructure skillsets within a singular
organization. Compounding this challenge was that blockchain technology, being in its
nascent stages of adoption and advancement, meant that experts in the field were rare and
continuously evolving in their understanding. To ensure objectivity and minimize
potential influence over the study’s outcomes, I stayed open-minded and strictly adhered
to the predetermined interview questions. This consistency allowed me to identify
recurring themes within the findings organically, ensuring that the insights drawn were
genuine and uninfluenced by any leading on my part. Furthermore, engaging with such a
dynamic field emphasized the importance of adaptability and resilience in research,
teaching me to expect the unexpected and be prepared to pivot when necessary.
Summary and Study Conclusions
The research sought to understand strategies utilized by IT professionals in the
U.S. to harness blockchain technologies for creating resilient systems. Through
semistructured interviews with security managers from two blockchain-specializing
companies, the study identified decentralization as a key principle, enhancing resilience
by distributing data across a network, thus reducing vulnerabilities. However, challenges
emerged, such as the complexity of migrating large-scale databases to blockchains and
the inefficiencies related to transaction speeds in decentralized models. This was
highlighted by the blockchain’s processing capacity, compared to traditional databases
like Postgres, and the necessity for swift transaction times in enterprise applications.
Additionally, concerns regarding the privacy of public blockchains were raised,
indicating both technical challenges and deeper issues related to attitudes and
organizational culture. The findings revealed limitations in current blockchain
technologies, specifically related to database capacities, privacy measures, and the speed
of transactions. These issues could impede an organization’s transition to blockchain to
establish robust systems. In Krüger’s change management theory context, these
challenges represent the "tip of the iceberg" or the overt technical problems. Beneath the
surface, deeper challenges related to the privacy of public blockchains emerged. These
concerns highlighted the technical difficulties and underlying issues connected to
attitudes, fears, and organizational culture—the submerged aspects of Krüger’s theory.
Overall, while blockchain technologies offer notable advantages for system resilience,
they also present challenges that necessitate multifaceted solutions, balancing technical
adaptations with shifts in perceptions and practices.
