BLOCKCHAIN TRUST AND APPLICATION A GROUNDED THEORY STUDY ON AUSTRALIAN INFORMATION SERVICES

BLOCKCHAIN TRUST AND APPLICATION: A GROUNDED THEORY STUDY ON

AUSTRALIAN INFORMATION SERVICES

Chapter 1: Introduction

Asset data warehousing, transactions, and governance are critical to maintaining a fluid

information technology operation (Manoharan et al., 2021). As the world becomes more

connected through the internet and mobile, the distinction between businesses and governments

moves towards alignment. The push for digitization and newer technologies fuels changes in an

evolving digital landscape necessitated by consumer demand. Blockchain technology and its

adoption are critical infrastructure components for modern governments and large corporations

(Woodside et al., 2017). It serves as a public ledger or an easily accessible, transparent record of

transactions or data, with the potential as a decentralized digital repository, encompassing a

variety of assets, ranging from tangible to intangible, such as votes, software, health data,

financial, and ideas (Xu et al., 2019). Created as a solution to address the fragmentary nature of

future data systems, blockchain technology has faced difficulty in gaining consumer acceptance,

consequently rendering the implementation process problematic for both small businesses and

larger corporate entities (Saadé et al., 2019). Blockchain technology operates through a secure

group of connected computers sharing information and resources based on mutual trust where

databases manage and store data, hosting it and distributing it across a network characterized by

direct connections, commonly known as a peer-to-peer (P2P) network (Kim, 2020). This

research project focuses on the technology of blockchain as separate from any application that

may use blockchain as its foundation. The analogy would be similar to the Internet and e-mail.

This is to make clear that blockchain is distinct from cryptocurrencies, with the latter

representing merely a minor application facilitated by blockchain technology (Zamfiroiu &

Pocatilu, 2021). Furthermore, Li et al. (2019) asserted that stakeholder trust in blockchain

technology as a secure, transparent, and efficient system for data management, coupled with the

provision of a standardized method, as discussed in Chapter 2, necessitates a unified framework

for its implementation, interaction, and governance. Without such a framework, Australia’s

information services industries risk losing a competitive edge in the global effort to provide

blockchain services.

Background of the Problem

Business owners and the public face the challenges of securely accessing, managing,

integrating, and sharing data (Attaran, 2020). Current technologies in use by the Australian

information services industries do not adequately address these requirements due to privacy,

security, and existing computer ecosystem interoperability limitations (Ritchie, 2021). Moreover,

modern computer systems and networking are complex, fragmented, and non-standardized

(Attaran, 2020). Underlying core operating systems and their interfaces offer various levels of

unification. However, the freedom given to software developers allows computers to be built,

maintained, and configured in any form (Eisty & Carver, 2021). Standardization is complicated

based on the number of variables in building a system, including software options, hardware

options, budgets, and personal choices from technology designers. There are no universal

standardization requirements that compel technology designers to follow a specific criterion that

can be accepted or adopted universally. Therefore, lack of policy and procedures in the

information service industries creates problems with different data storage mechanisms, data

privacy, transparency, and user acceptance of existing data systems.

Standardization problems are prevalent for businesses and government entities (Jakobs,

2017). For example, businesses using blockchain strategies find it challenging to implement a

model accepted by consumers while operating in a seamless shared environment. To secure and

reduce implementation apprehension, government agencies tasked with information protection

create best practice frameworks for other government agencies and businesses to secure data

from unlawful third-party hackers and unintended access (Khou et al., 2017). Consequently,

individual companies and government agencies are responsible for implementing the suggested

frameworks within their timelines and budgets, but the process offers no guarantee of uniformity

or concerted efforts to unify a single standard.

Challenges of Change in Business

Wiatt (2019) states that numerous banks and government agencies rely on large

mainframe computers using programming languages and software built over fifty years ago.

Deemed too risky, complex, and expensive, upgrading computer systems is not a priority for

government agencies and corporations. For example, the Mexican-based bank Citibanamex

maintains a Cobol mainframe system for their underlying banking technology with custom

middleware built to facilitate communications between the legacy and modern IT technology

such as mobile devices (Citibanamex improves market position by expediting their mobile first

strategy, 2021). Cobol is a computer programming language invented in 1959 (Guzdial & du

Boulay, 2019). Legacy systems are computer systems in operation years or decades after their

expected lifespan. These systems usually maintain critical functions within an organization

where the risk of their function not being available outweighs the cost of replacement with

modern technology (Rana & Rahman, 2018).

Gornov et al. (2019) state that these problems are not new, and there has been ongoing

research showing government agencies and corporations’ efforts to bridge legacy and new

systems through middleware software and interface bridges. Such interfaces offer a solution to

patch systems manually in the short term but offer no flexibility in the long term since their

implementations are ad hoc. In addition, middleware is custom-written for its unique technology

environment, as traditional computer networks are independently isolated with various

configurations in place, hindering uniformity.

As consumer demand for an increase in digital services and offerings grows, businesses

must adapt their strategies accordingly (Dannenberg et al., 2020). Attempts to connect systems

through Application Programming Interfaces (APIs) have had limited success but ultimately rely

on intermediary protocols to synchronize data. Moreover, APIs are a single private

implementation of software code with no transparency layers or methods to establish data

immutability has been achieved. A framework defines the ability for a computer system to

communicate using an established protocol. When a computer system does not understand the

requested protocol, to alleviate misinformation, the computer system will ignore or reject the

communication attempt. Therefore, it is paramount that any framework or policy defines the

protocol methods and a uniform implementation.

Increased demand further complicates the exponential consumer demand for computer

resources, service expectations, and networking (Berisha et al., 2022). In addition, digital

transformation efforts of businesses and governments experienced an acceleration effect through

world events such as the COVID-19 epidemic (Sultan & Islam, 2020), which shifted large

numbers of employees to work from home (Bick et al., 2020) in the process generating greater

reliance on connected systems and the internet. The complexities arising from this increased

demand and digital transformation highlight the potential of blockchain technology to enhance

the security and efficiency of these expanded computer systems.

Blockchain Limits in Business

Blockchain’s integration in business, influenced by evolving technological, regulatory,

and market factors, is a complex process with the potential for both beneficial and adverse

outcomes (Treiblmaier, 2021). Given its immutable and trust-centric properties, blockchain

applies to various business domains, including logistics chains, hospital network clinic records,

property deeds, customer care history, stock investments, financial systems, product traceability,

and criminal records (Martinez, 2022). Blockchain offers a robust, tamper-proof, and secure

distributed digital ledger supported by consensus mechanisms, making it a suitable option for

various business applications, particularly when combined with existing computer systems to

fulfill essential business use case requirements (Hassija et al., 2021). However, blockchain is not

suitable for all businesses; it is not a panacea for all technological challenges in the business

world. Its effectiveness depends on specific use cases and situations, highlighting the need for

careful consideration of its applicability (Wan, 2020). Applying blockchain in business

necessitates careful evaluation, ensuring alignment with specific business contexts and

requirements.

Bureaucracy and Trust

Blockchain technology is a modern solution to help eliminate obstacles in computer

systems, but as previously discussed, it is not the silver bullet to fix all problems (Pillay &

Njenga, 2021). Jun (2018) maintains that blockchain adoption and implementation closely

resemble government bureaucracy. Bureaucracy establishes rule sets and working methods that

mirror blockchain’s underlying technology based on predetermined rules and trust models

programmed into blockchain architectures. The consequence of various bureaucratic processes

and rules further fragmenting connected computer systems presents the problem of how a

government agency or corporation can accurately store and present historical data as immutable.

Australia

As of June 2021, Australia has a population of over 25 million people with an annual

growth rate of 0.2% (National, state and territory population, 2021). Australia’s economy is

diverse and robust, with an unemployment of 4.6%. In addition, the country boasts a substantial

information media and telecommunications industry, with approximately 220,000 people fully

employed as of 2019 (Vandenbroek, 2019). In the last five years, several blockchain initiatives

have been launched to increase the awareness and use of blockchain technologies. An example is

the Australian National Blockchain Roadmap (National blockchain roadmap, 2020) which

appointed industry and academic leaders to contribute to its creation. Some of the outcomes of

the study included uses for blockchain in the supply chain for the Australian wine industry and

calls to develop a common blockchain framework.

Another significant contribution to Australian blockchain is the work of the CSIRO and

Data61, which produced the Blockchain 2030 paper in 2019 (Bratanova et al., 2019). The work

mapped out the current maturity of the Australian blockchain industry. Figure B1 shows the

breakdown of blockchain by industry within Australia. Particularly noteworthy is the maturity of

the information services industries in Australia, which boast the second-largest deployment of

blockchain technology. Despite this, Malik et al. (2021) note that Australian organizations exhibit

low blockchain adoption despite sufficient technological infrastructure and robust support from

the government and private associations, owing to a dearth of in-depth empirical research on the

factors influencing their intentions to adopt blockchain. This indicates both an opportunity and a

knowledge gap in the existing understanding of blockchain technology within Australia,

presenting an opportunity for this study.

Problem Statement

A general problem exists with consumer trust in data storage for blockchain technology

implementation (Rabby et al., 2022). Despite business entities’ attempts to implement unified

blockchain digital frameworks, the problem continues with no essential structure and guidance

on blockchain procedures and policies (Lykidis et al., 2021). This negatively affects Australian

businesses and consumers, as data integrity and immutability, pivotal to trust, have become

primary concerns for government and business organizations (Kaja et al., 2022). The specific

problem is Australian consumer reticence in the information services industries (Rabby et al.,

2022). A possible cause of the problem lies in the public and business acceptance of security,

trust, and data transparency within a blockchain system. This acceptance impacts the widespread

adoption of blockchain technology, without which Australian industries may struggle to keep

pace with global counterparts in the blockchain services sector. This study investigated the

challenge of establishing consumer trust in blockchain implementations within the information

services industries in Australia using a grounded theory research method to provide potential

solutions.

Purpose Statement

This qualitative grounded theory study focused on understanding how consumer trust in

blockchain implementation affects the overall performance and adaptability of Australia’s

information services industries in a rapidly evolving global blockchain industry (Namasudra et

al., 2021). The data, collected through one-on-one interviews with industry and academic

professionals in the Australian blockchain sector, includes video and audio recordings,

transcriptions of the audio, and notes. These materials were analyzed using methods described in

Chapter 3 to identify emerging trends, patterns, and recommendations.

Nature of the Study

This study utilized a qualitative research method and a grounded theory design. A

qualitative research method was appropriate because this study focused on collecting

nonnumerical data to solve the problems of the research questions under consideration (Mweshi,

2020). The nature of the study warranted the selection of a qualitative design utilizing grounded

theory design based on the literature review for this study and the variety of scenarios the

researcher addressed during data collection. This design selection arises from the varied

blockchain implementation methods planned and currently employed in Australia’s information

service industries, coupled with the baseline questions that guided the interview toward a

flexible, partially directed format, as outlined in Chapter 3 and Appendix C (Dyball &

Seethamraju, 2022). Moreover, qualitative research design is further suited as it employs

interpretive and constructivist paradigms to gain a profound understanding of a research subject

instead of predicting outcomes (Denzin & Lincoln, 2008). The study focused on industry and

academic professionals within the Australian blockchain sector, collecting data through

interviews. This approach renders qualitative research most appropriate, owing to its capacity for

delving into complex, context-specific insights and perspectives within the topic of blockchain.

The design benefits investigations into multifaceted phenomena that simple yes, no, or other

straightforward answers cannot adequately capture (Singh, 2022).

This research study used grounded theory design because of the design’s adaptability

through a variety of sampling techniques, coding, comparative analysis, and theoretical sampling

(Chun Tie et al., 2019). In qualitative research, sampling techniques such as snowball,

convenience, purposive, and quota sampling, as well as less frequently used methods like

stratified, theoretical, extreme case, typical case, systemic, and intensity sampling are employed,

their selection contingent upon the research aims and questions (Rana et al., 2023). This research

study, detailed in Chapter 3, opted for the snowball sampling method, a recruitment approach

wherein research participants aid in identifying other potential participants. Grounded theory

aims to construct or uncover theory from data obtained and analyzed systematically using

comparative analysis. Despite its inherent flexibility, grounded theory’s objective is to come to a

conclusion firmly based on the collected data through its complex methodology (Chun Tie et al.,

2019). A grounded theory design was appropriate for this study because of its flexibility and

capacity to form recommendations grounded in theory collected from interviews. The interview

questions asked baseline questions (see Appendix C) to elicit a broader discussion aimed at

collecting blockchain data trends and concepts to form a theory. This data pertained to the current

state of blockchain implementation, types of implementations, future plans for implementation,

and aspects related to budget, regulation, privacy, and user acceptance of blockchain technology

in the Australian information services industry.

Research Questions

This study addressed the following research questions:

Research Question 1

What are the key regulatory challenges hindering the implementation of blockchain

technology in Australia’s information services industries?

Research Question 2

How does the absence or inadequate implementation and communication of blockchain

data processes pose risks to Australia’s information services industries?

Research Question 3

What challenges do businesses face in understanding and accepting blockchain systems,

and how can these challenges be effectively addressed?

Theoretical and Conceptual Framework

Theories selected for this study must reflect the nature of the current digital environment,

the data within it, and the business stakeholders required to implement recommendations (Saura,

2021). Selected for this study are chaos theory (Oestreicher, 2022), consensus theory (Weller,

2007), and bureaucracy theory (Lutzker, 1982). These theories offer a comprehensive framework

for understanding the complex interactions between blockchain, technology, data, and

governance.

Chaos Theory

Chaos theory integrates qualitative thinking and quantitative analysis to investigate

behaviors in dynamic systems, necessitating a comprehensive continuous approach rather than a

singular data relationship for accurate explanation and prediction (Luo et al., 2022). In qualitative

research, the notion of observed randomness within a large set of variables provides a chaotic

behavior characteristic. Chaotic observations are all around, from the movement of water to the

evolution of the stock market; these all produce seemingly random outcomes from nearinfinite

inputs (Biswas et al., 2018). Thietart and Forgues (1995) state that a change in even one of the

billions of variables in a chaotic state leads to predictable outcomes for only a concise duration.

Over time, in a chaotic environment that inherently fosters exponential instability, a single input

multiplies and evolves, leading to diverse outcomes where even a minor alteration can

profoundly impact the entire system.

Chaos theory effectively applies to digital environments characterized by numerous

options and configurations (Nan et al., 2020). In this setting, interconnected computer systems

can receive inputs from various sources, including databases, the internet, and manual user

inputs. It is crucial to ensure these sources are reliable and well-managed to prevent bottlenecks

or performance issues, especially in blockchain applications. The many possible combinations in

such systems mirror a chaotic environment where numerous rules simultaneously influence

outcomes.

Consensus Theory

Consensus theory defines truth as social and majority agreement (Horowitz, 1962).

Rather than choice and options, the theory rejects differentiation and uniqueness and considers

them incorrect. Truth, as defined by the majority, is problematic because there is an assumption

of truth by numbers. Conclusions lead to cases where actual truth has been replaced with what

the majority consider the truth, offering no ability to quantify truth based on other facts.

Public blockchains utilize a consensus mechanism to establish trust, which functions

when a substantial number of blockchain server nodes independently verify and agree on the

legitimacy of a new data to be stored, thereby allowing its addition to the public ledger of data

stored within the blockchain (Alzahrani & Bulusu, 2018). Central to the blockchain’s integrity

and dependability, this consensus process guarantees transactional accountability, irrespective of

the anonymity of ledger participants (Alzahrani & Bulusu, 2018). The system’s strength lies in its

collective validation approach, instead of relying on individual verification, forming the

foundation of trust in the blockchain network. For example, blockchains, where one actor

controls more than 51% of all nodes on the blockchain, could theoretically claim incorrect facts

(Sayeed & Marco-Gisbert, 2019). In this scenario, the blockchain diverges temporarily into two

distinct versions of the ledger, known as a fork (Nijsse & Litchfield, 2020). The version that

eventually emerges as the ‘accepted truth’ is determined by the fork that gains the majority of

consensus votes. The single source of truth concept is vital for information technology

businesses, as it guarantees uniform usage of a centralized data source among employees and

automation tools (Walther & Jovicic, 2023). Within blockchain, the networked computer servers

or nodes and the consensus process are integral to maintaining trust and the integrity of the

blockchain network.

Bureaucracy Theory

Bureaucracy Theory, or Max Weber theory, states that organizational bureaucracy benefits

an organization or task (Lutzker, 1982). The theory’s properties include that bureaucrats’ values

and actions, influenced by their origins and backgrounds, significantly impact their decision-

making processes (Dhillon & Meier, 2022). Furthermore, the theory differentiates between

passive representation, in which bureaucrats mirror the demographic composition of the

population they serve, and active representation, wherein they advocate for the interests of their

constituents, potentially improving outcomes for these groups (Dhillon & Meier, 2022). This

theory method has the advantage of a divide-and-conquer approach where task assignments are

allocated for exact skill sets, leading to greater efficiency. Weber argued that bureaucratic

structures are superior to other forms of organization because the structure relies on a rational

and systematic approach to decision-making (Derakhshan & Fatehi, 1985). In describing

blockchain, Talat et al. (2022) state that blockchain provides advantages such as data

immutability, fault tolerance, increased security, the execution of smart contracts, and the

verification and distinctiveness of transactions. Similar to consensus theory, where blockchain

requires consensus for block validation, all nodes function within a defined bureaucratic

framework or set of rules, enabling collective operation.

Operational Definitions

Definitions listed within this section may be familiar to some readers. The inclusion is to

provide clarity to the reader.

Application Programming Interface (API), represents a software product comprising a

collection of well-defined methods for facilitating communication among distinct components

(Ogorodnyk et al., 2021).

Bit, is the smallest value on a computer system, representing a single value that can be

either ‘off’ or ‘on’ or stored on a computer as a one or zero (Roquet & Lu, 2014).

Byte, commonly comprising eight bits, is a data unit in computing that usually represents

a single character (Verma et al., 2021).

Bitcoin, although this study is not about cryptocurrencies, can be defined as a safe haven

store of wealth against global financial stress (Wang et al., 2019). However, while Bitcoin can be

used for financial purchases, it performs more like an asset or security (Katsiampa, 2017).

Block, represents a fixed data structure that consolidates numerous smaller transactions

into one appropriately sized block format (Singh & Vardhan, 2020).

Blockchain, can be defined as a distributed ledger database system for recording

transactions between third parties that are verifiable and permanent (Perboli et al., 2018).

Buzzwords, are language units that characterize different periods, arising either from

gradual changes in a relatively stable but closed society or sudden changes in an unstable open

society (Ossokina & Murzalina, 2019).

Cryptocurrency, although this study is not about cryptocurrencies, can be defined as a

decentralized alternate value exchange. Each cryptocurrency has its own set of rules that define

its value, which “incorporates cryptography and in most cases utilizes blockchain technology”

(Horvat et al., 2020).

Distributed Ledger Technology (DLT), is a technology that allows the use of highly

available, append-only databases that are maintained by physically distributed storage and nodes

under untrustworthy conditions (Kannengießer et al., 2020).

Fork(ing), is when blockchain nodes encounter disagreement on consensus, which leads

to a bifurcation of the data chain, during which both data branches remain valid temporarily;

however, over time, one branch gradually grows longer, establishing consensus and

automatically eliminating the other fork (Nijsse & Litchfield, 2020).

Hashing or a cryptographic hash is a means for securing public data on or off the

blockchain by creating a mathematical digital fingerprint to verify the content it protects

(Konashevych & Poblet, 2018).

Nodes, or interconnected nodes, are server infrastructures that establish a vast, secure,

and decentralized network for information exchange on a blockchain network (Tzoulia, 2022).

They perform multiple functions, including data archival, transaction handling, and mining,

while adhering to the consensus protocol’s rules (Tzoulia, 2022).

Off-chain is information as data residing outside the blockchain network, not within it

(Zemler, 2019).

Open-source or open-source software allows its source code to be used, copied, and

distributed with or without modifications and offered either for a fee or free of charge (Margan &

Čandrlić, 2015).

Public ledger (Blockchain), comprises a continuously expanding block sequence that

records data similarly to a conventional financial accounting public ledger, listing all transactions

and safeguarding against unauthorized modifications and revisions (Sarode et al., 2021).

Single Source of Truth (SSOT) is a data management concept where a single,

authoritative data source ensures consistency and accuracy. This approach counters the common

practice of data replication among business entities, which often leads to inconsistencies and

interoperability challenges.

Smart contracts are “a self-executing contract that utilizes blockchain technology to

digitally enforce, verify, or facilitate the performance or negotiation of a contract” (Nzuva,

2019). Contracts are written in several computer scripting languages and are logical and

mathematical.

Tokens or financial tokens are a specific implementation of blockchain technology,

abstract from its complexities. Their features, such as value transfer and community building,

and their impacts, like customer satisfaction and loyalty, operate on a higher protocol level,

making them easier to integrate into existing frameworks, models, and theories (Treiblmaier,

2023).

User experience (UX), is a person’s perceptions and responses that result from the use or

anticipated use of a product, system, or service and is viewed as a holistic concept encompassing

all emotional, cognitive, and physical reactions formed before, during, and after the actual or

anticipated usage of a product (Hinderks et al., 2022).

Zero-knowledge proofs (ZKPs), are a technique to limit the amount of information

transferred from a prover A to a verifier B in a cryptographic protocol (Feige et al., 1988).

Assumptions, Limitations, and Delimitations

In academic research, establishing assumptions, limitations, and delimitations is crucial to

ensure the validity and reliability of a study, as without these components, the study’s validity

and reliability remain questionable (Alkadash & Aljileedi, 2020). These boundaries must be

clearly defined to comprehend the current limitations and constraints inherent in the existing

study. Moreover, documenting assumptions, limitations, and delimitations in a study fosters

clarity, transparency, and academic responsibility regarding the choices made in its structural

design.

Assumptions

Assumptions, recognized as statements presumed accurate without evidence, are crucial

in simplifying social-ecological interactions and scientific research (Schröter et al., 2021). There

was an assumption that responses from interviewees during the interview process were not

confidential, therefore inaccessible to the public and could be used to taint the study’s

conclusion. Furthermore, throughout the interview, it was assumed that the individuals

participating in this study would provide truthful responses and recommendations. Additionally,

it was assumed that participants possessed the necessary expertise to adequately answer the

questions asked of them.

Limitations

Limitations are beyond researchers’ control and can compromise a study’s internal and

external validity (Fawole, 2022). They are inherent in all types of research and may obstruct

addressing specific questions or making certain conclusions or inferences from findings (Fawole,

2022). Blockchain technology continuously evolves, adapts, and advances, meeting changing

business and commercial needs and embracing new applications (Colomo-Palacios et al., 2020).

Consequently, the first limitation of the study is that the results will have finite practicality as

current technology will further increase, rendering some of the conclusions made in this study

potentially invalid. Furthermore, the scope of a localized study might limit its global appeal, and

the outcomes derived may not be applicable in some contexts. Lastly, the data provided by

participants, being self-reported and subjective, depends on their memory and recall, and may be

influenced by various factors, such as time, context, emotions, motivation, and social norms.

Delimitations

Delimitations refer to the factors and characteristics that a researcher intentionally

excludes, thereby defining the scope and establishing the boundaries of a study (Tocaven

Gonzalez & Kasteren, 2021). The study confines its research to professionals and academics

working and operating within the information services industries in Australia. Moreover, the

study is centered on blockchain technology, not cryptocurrency, with the latter discussed only in

terms of its technological aspects and not as a financial instrument. As outlined in the population

and sample section, the participants require specific knowledge and experience to be deemed

professional or academic experts and able to contribute to the study. Lastly, due to personal

preferences or technical issues, the study will exclude participants who cannot participate in a

recorded interview, as the absence of a complete dataset would pose challenges to the coding

methods outlined in Chapter 3.

Contribution to Practice or Stakeholder Groups

Despite exhibiting low adoption, businesses demonstrate a strong appetite for

implementing blockchain solutions, primarily aimed at reducing costs and risks associated with

using the technology (Elliot et al., 2021). The proposed research study intends to examine current

technology policy standards and the deployed technology to assess the present state of the

environment. In the analysis phase of the study, the objective is to identify the various types of

blockchain systems currently in use or pending deployment, to understand the business functions

they fulfill, to ascertain their shared characteristics, and how these systems currently attempt to

communicate. This will facilitate the formulation of recommendations on data immutability,

privacy, trust, and storage, all crucial aspects for businesses wishing to implement blockchain

technology. From a technical and functional perspective, the beneficiaries of this research include

information technology professionals and executive decision-makers. From the standpoint of

consumer rights, trust, and privacy, consumer watchdog groups and political organizations stand

to gain valuable insights from the study’s findings. Moreover, the study focuses on Australia’s

information services industries, aiming to determine the implementations best suited for

blockchain technology. Furthermore, it also seeks to identify situations where blockchain may

not be well-suited.

Summary

Chapter 1 highlights a high-level overview of the concepts of blockchain technology and

its associated challenges. Blockchain may provide a viable solution to these challenges; however,

using blockchain requires a structured set of rules that may lose focus in bureaucracy and a mix

of different solutions. Chapter 2 will outline the relevant literature that surfaced during the

research process and bring forth additional information about unified systems, establishing trust

and data immutability. Chapter 3 will present information about the study’s method and design.

Finally, also identified in Chapter 3 is the information about the study’s population and sample,

as well as how the study identifies and treats its participants.

Chapter 2: Literature Review

This literature review scrutinizes prior research on particular subjects about the

integration of blockchain technologies in Australia and its effect on government and business.

It employed multiple methods of research collection: integrating Google Scholar with California

Southern University library links and peer review, Springer and ProQuest databases,

ResearchGate.net articles, and standard Google search. ResearchGate facilitated connections to

article authors, allowing for requests for full-text versions when research was not publicly

accessible. The study used Google Search to cite news articles and observe general trends, not as

a source for peer-reviewed studies. This chapter references 133 studies, with 93% originating

after 2016.

The digital landscape in Australia is well-developed but is grappling with a range of

issues in information technology, security, data management, and computer networking (Ali et

al., 2016). The Australian government, recognizing the business need to address the different

multifarious challenges, is proactively embarking upon a concerted endeavor to curtail the

problem through budgetary allocations. AlDaajeh et al. (2022) state that Australia plans to invest

1.67 billion Australian dollars to secure networks and online activity for Australians, their

businesses, and critical Australian infrastructure in the coming decade. The increasing

interconnectivity of systems necessitates a commensurate escalation in the demand for

heightened levels of security, enhanced awareness, diligent adherence to safe data practices, and

the establishment of robust security frameworks. From mounting security vulnerabilities to

subpar data management practices and networking complications, these challenges put a strain

on the integrity and efficiency of Australia’s digital ecosystem (Fahd et al., 2019).

Existing legislation to secure Australian data is fragmented, with their application

between departments and businesses described as having substantial dissimilarities or

overlapping legislation (Anwar et al., 2018). Data protection is crucial when protecting privacy,

yet individual Australian data centers are responsible for implementing the most appropriate

privacy and security measures (Flack & Smith, 2019). These measures must align with their

organizational, legislative, and technological requirements. However, no enforced rules or checks

are mandating such alignment (Flack & Smith, 2019). Priding itself on being a leader in e-

government service development, the Australian government faces the concerning reality of

being the most targeted country for cybersecurity attacks in the Asia Pacific region (Thompson et

al., 2020).

Implementing and integrating emerging technologies like blockchain pose unique

complexities, regulatory uncertainty, and business data risks (Prewett et al., 2020). Even though

its potential to revolutionize sectors by enhancing security and transparency, adopting blockchain

technology is not without its hurdles. Meva (2018) explores a myriad of challenges that confront

the adoption of blockchain technology, encompassing complexities, network scale, transaction

costs, network velocity, human fallibility, political considerations, interoperability, and data

mutability, among others. Successfully resolving these significant and demanding challenges

requires the application of specialized skill sets and acquiring expert knowledge, highlighting the

need to address and overcome them effectively.

Within the Australian context, the challenges predominantly center on the intricate

process of seamlessly integrating blockchain technology into established systems while

concurrently addressing the vital aspects of regulatory compliance and societal acceptance

(Malik et al., 2020). This chapter illuminates these multifaceted challenges, providing a

comprehensive understanding of their profound implications for advancing the nation’s digital

landscape.

The Modern Evolution of Information Technology

New challenges in designing network architecture for information technology, blockchain

implementations, data inferences, privacy, security, and trust are emerging significantly beyond

the physical boundaries of companies (Mourtzis et al., 2023). The profound impact of

information technology’s evolution on various domains, encompassing networking, security,

privacy, databases, the internet, and the recent emergence of blockchain, has been propelled by a

confluence of factors. These factors include the ever-evolving societal need for the betterment of

technology and continuous advancements in computing capabilities that push the boundaries of

what is possible and foster innovation in technological advancements (Schaper et al., 2022). The

technological landscape has undergone a notable paradigm shift, enhancing daily personal

interaction with technology through mobile devices. (Raja et al., 2019). While social media

content trends might change, Bae (2021) asserts that technology development has shifted towards

improving the human experience, convenience, and overall happiness, in addition to the previous

information technology focal points such as mass production, automation, or cost reduction.

On the other hand, mobile devices have brought instant communications to consumers’

pockets worldwide (Ahmed et al., 2021). This ever-connecting world and pace of technological

progress generates 2.5 quintillion bytes or 2.5 million terabytes of data per day and is growing

daily (Eberendu, 2016). According to Berisha et al. (2022), every minute, Snapchat users share

527,760 photos, LinkedIn adds 120 new profiles, YouTube 4,146,6000 video views, Twitter posts

456,000 messages, Instagram users contribute 46,740 photos, and Facebook adds 208,000 photo

uploads.

When considering the amalgamation of these external data pressures, a comprehensive

portrayal of extensive data creation across diverse devices emerges, accompanied by the

consumer demand for real-time accessibility (Ataei et al., 2023). In this context, security assumes

a crucial role in safeguarding the data, encompassing aspects of validation and storage (Ataei et

al., 2023). Treiblmaier (2019) noted that in recent years, two significant drivers of technological

innovation, namely blockchain technology and the physical internet, have garnered considerable

attention from practitioners and academics to solve many of these issues.

Blockchain Theoretical

Blockchain technology originated from the 2008 whitepaper titled “Bitcoin: A Peer-

toPeer Electronic Cash System,” authored by an individual or group known as Satoshi Nakamoto

(Nakamoto, 2008). Nakamoto’s true identity continues to be widely regarded among scholars and

experts as a pseudonym, thereby giving rise to persistent debates and disputes surrounding the

actual individual or individuals behind the creation of blockchain (Khalilov & Levi, 2018).

Kuriakose (2022) writes that Nakamoto self-identified as a Japanese man, leading to concerns

regarding their exemplary command of English displayed in the paper. On the other hand, Porras

(2023) claims the identity of Nakamoto as Australian technology entrepreneur Dr. Craig S.

Wright, citing several patents and copyright claims. It is important to note that within the context

of this study, the actual identity of Nakamoto does not constitute a contributing factor or variable

in answering the research questions.

Although the concept of blockchain as a distributed ledger occurred in 2008, researchers

proposed the underlying concepts and ideas behind the technology as early as 1970 (Devulkar &

Awwad, 2020). Charandabi and Kamyar (2021) write that David Chaum in 1983 introduced the

idea of digital cash via cryptography through a research paper (Chaum, 1982) proposing a

blockchain-like system. Devulkar and Awwad (2020) state that in 1979, Ralph Merkle introduced

the concept of hash trees and hash chains, now recognized as merkle trees, as data structures that

enable the representation of multiple hashes using a single hash. These early conceptualizations

of blockchain constituted the foundational ideas upon which modern blockchain technology has

been constructed.

An Overview of Blockchain Technology

Blockchain is a modern technology that has gained significant attention in academic and

industry circles in the last fifteen years since its creation in 2008 (Zou et al., 2020). Blockchain is

a decentralized, immutable digital ledger system that enables secure, transparent, and

tamperresistant transactions and data management, thereby eliminating the need for validation by

third parties and fostering trust through a consensus of computer miner nodes (Rawat et al.,

2019).

Alternatively, Al-Saqaf and Seidler (2017) describe blockchain as simply a “distributed system

for cryptographically capturing and storing a consistent, immutable, linear event log of

transactions between networked actors.” Mas’ud et al. (2021) offer a more straightforward view,

stating that blockchain is an open, distributed ledger capable of efficiently recording transactions

between two parties in a verifiable and permanent manner.

Within all portrayals of blockchain technology, the shared characteristics of immutability

and decentralization emerge as common denominators (Politou et al., 2019). Nevertheless, it is

essential to note that these attributes do not encompass the full diversity of blockchain systems.

Several known and documented blockchain architectures exist, including public permissionless,

consortium, private, and hybrid, with the latter integrating public and private blockchains in a

single implementation (Alkhateeb et al., 2022).

The Functionality of Blockchain

Blockchain enables the secure and transparent recording of transactions and data across

multiple computers or nodes in a network (Helo & Hao, 2019) and operates through a chain of

digital blocks, each containing a list of transactions, and utilizes cryptographic algorithms to

ensure the immutability and integrity of the data (Andi, 2021). Transactions are verified and

added to the blockchain through a consensus method that utilizes different calculation methods or

proofs. Some such methods include proof-of-work, proof-of-stake, proof-of-burn, proof-

ofidentity, or proof-of-importance, providing various methods to prove to the network that they

are operational and providing valid data to the network (Miraz et al., 2021).

Depending on the consensus method, a node on the network is awarded or selected,

receiving a predetermined amount of tokens for that type of network and taking responsibility for

creating the block (Kaur et al., 2021). After adding a block to the chain, altering previous blocks

becomes nearly impossible, rendering the blockchain immutable and ensuring an auditable and

trustworthy record of all transactions (Yaqoob et al., 2020). Blockchain’s capability to provide a

distributed data store or ledger that is immutable, allowing only for reading and not alteration,

offers the potential for a permanent and transparent source of truth, complete with timestamping.

Hashes

Blockchain consists of a data chain with integrity and validation ensured through computer

hashes (Bonsón & Bednárová, 2019). Hashes are 64-character numbers that represent the current

state of the data and serve as critical elements for mathematical content verification in

blockchain and many content verification and data signature systems. Any changes to a hash

lead to a divergence in the data the hash represents, ultimately compromising its integrity

(Sathya & Banik, 2020). If a hash cannot validate the intended data, it may indicate potential

issues such as alterations, damage, invalidity, or an incorrect data-hash pairing. Figure B3

depicts a blockchain system and the hashing function. Various computer functions use hashes,

Gayoso Martinez et al. (2020) describe a hash function as a unidirectional function applied to a

variable-sized message that is an indispensable tool for verifying data integrity. Sathya and

Banik (2020) describe additional features that hashing provides blockchain as ensuring security

and enabling efficient data storage since it fixes the size of the hashing output. Utilizing hashes

within blockchains is fundamental for preserving data integrity, verifying content, and enhancing

security while maintaining efficient data storage.

Merkle Trees and Digital Signatures

Merkle trees are a hierarchical structure that utilizes cryptographic hash functions to

aggregate data into a series of interconnected blocks, thereby providing an efficient and secure

means of verifying content within large datasets (Elbaz et al., 2009). The Merkle tree’s leaf nodes

represent individual transactions, and non-leaf nodes contain the hash values of their respective

child nodes (Liu et al., 2020). When describing Merkle trees, Ozcelik et al. (2021) wrote that the

Merkle tree root represents the initial node and embodies the accumulated hash value of all non-

root nodes in the tree, calculated in a pairwise approach.

A unique hash value emerges by recursively synthesizing these hashes from the leaves to

the root, representing the entire set of transactions within a block (Canto et al., 2023). Therefore,

any alteration to a single transaction alters the root hash, enabling rapid detection of

inconsistencies. According to (Fraga-Lamas & Fernández-Caramés, 2019), this mechanism

ensures data integrity and authentication in blockchain systems, underpinning its trustworthiness

and robustness in various applications, such as cryptocurrencies and distributed ledger

technologies.

The concept of hashing a data segment or cluster of information is not unique to

blockchain. Hashing serves multiple use cases in ensuring the integrity of a message or text,

verifying that it remains unaltered across various forms, including communications and digital

files (Farid, 2021). This type of hashing is sometimes called signatures or digital signatures (Chi

& Zhu, 2017) and is advantageous both inside and outside the blockchain context for data

integrity. It aligns with the findings of Maetouq et al. (2018), who assert that in scenarios where

one must detect an altered document or message or during financial transactions, practitioners

employ hashing and commonly utilize digital signatures. Cryptography, hashing, and digital

signatures predated blockchain technology and are crucial in bolstering data integrity and

security across diverse contexts, including blockchain applications.

On and Off-Chain

In public blockchain systems, data stored directly within the blockchain is classified as

on-chain data, while conversely, data stored externally but potentially referenced by the

blockchain is off-chain data. Off-chain data can take various forms and be stored using different

methods; Zemler (2019) describes off-chain information as data, or the general payload, residing

outside the blockchain network, not within it. Similarly, Liu et al. (2023) state that combining on-

chain and off-chain methods improves performance by placing the transaction within the

blockchain and the payload of the data off-chain.

In scenarios where data bifurcation occurs, the immutability of the off-chain data becomes a

subject of scrutiny because, primarily, off-chain data is presumed to be accurate, and solely the

transactional component is accessible on the public blockchain. Silva et al. (2020) state that

blockchain design encompassing off-chain information is restrictive because it cannot be

deterministically verified or provide cryptographic evidence of its truthfulness. Although the

data methods on and off-chain may seem contrary to the foundational principles of trust and

consensus within a blockchain, there are justifiable reasons for this data split. Ye et al. (2022)

assert that not all data is sensitive or demands a high level of security; storing such data off-

chain can conserve blockchain capacity, thereby augmenting transaction speed and reducing

associated costs. While there are advantages and disadvantages to employing this architecture,

achieving an effective integration into existing infrastructures and realizing the benefits of

blockchain necessitates a balanced consideration of trust, governance, speed, reliability, and

security.

DLT and Private Blockchain

Distributed Ledger Technology (DLT), as a subset of blockchain technology, facilitates

decentralized transaction recording across a computer network and is applied in sectors such as

finance, education, and e-democracy (Anthony Jnr, 2023). DLT enables untrusted entities to

achieve consensus on shared data in a fully distributed manner using a cryptographically secure

and immutable ledger (Anthony Jr, 2023). When deployed, DLT uses systems to distribute, store,

and disseminate data across public or private networks and broadly categorizes it into

permissionless and permissioned platforms based on their accessibility and consensus

mechanisms. When defining permissionless and permissioned platforms, Kadam (2018) states

that permissionless DLT platforms, such as Bitcoin and Ethereum, facilitate public consensus

participation; in contrast, permissioned platforms grant consensus participation exclusively to

registered members, providing accelerated validation and heightened privacy.

Utilizing DLT for private data storage allows companies to safeguard confidential

information while ensuring its verification and immutability through internal verification

methods. However, due to the inherently non-public nature of this approach, it is challenging to

verify the immutability independently or in a public manner. Public blockchains like Bitcoin

provide a publicly auditable ledger that allows transaction analysis and investigation. Gokoglan

et al. (2022) noted that blockchain’s capability to verify and examine transactions without

thirdparty intervention offers exceptional transparency and trustworthiness in online transactions.

Despite the openness of public networks, Schmitz and Leoni (2019) note that just because

a blockchain records an asset transfer does not ensure the actual transfer or exchange of the asset,

the completion of payments, or the accurate recording of transactions in the real world. To

validate private or internal data, organizations should implement validation systems such as

mobile applications, websites, or application programming interfaces (APIs) in addition to

leveraging blockchain’s DLT capabilities for public verification.

Immutable Data and Off-Chain Data Storage Pattern

Blockchain implementors store data defined as immutable in a manner that prohibits

modification, or any attempt to alter it becomes immediately apparent (Xu et al., 2020). Data

within a blockchain remains immutable; Cappelletti et al. (2023) note that upon validating the

block through widespread consensus, the blockchain protocol adds it to the blockchain, making it

immutable. Blockchain fundamentally operates as a private or public ledger technology

(Franciscon et al., 2019), but while aspects like speed and costs are significant, the governance

and trustworthiness of the information are paramount. Absent these attributes, blockchain offers

no distinct advantage over traditional database technologies. Describing immutable data Han et

al. (2023) said blockchain engenders trust by ensuring records are tamper-resistant and

immutable due to their distributed nature and hashed representation.

Lacking privacy, adequate storage, and immutability, a blockchain becomes suited

predominantly for logging minimal data fragments such as financial transactions, necessitating

references from off-chain systems that remain inaccessible to the public (Six et al., 2022). A

balance is required for a blockchain system that integrates the trust inherent in blockchain

technology with the storage and privacy mandates of governmental entities and large companies.

One method to balance the requirements is the Off-chain data storage pattern. Putz et al. (2021)

describe it as a method to address data volume and latency concerns, with a recommendation to

share only non-nominal or aggregated data on-chain to mitigate storage space challenges. Six et

al. (2022) states that using this method, storing substantial data off-chain and saving its hash

onchain reduces costs while preserving the ability to verify data integrity using the on-chain

hash. The Off-chain data storage pattern represents a strategic amalgamation of decentralized

trust and optimized storage, underscoring its potential to reshape data management paradigms.

This approach allows data to remain private and secure, while providing public validation

methods through a hash signature stored on a public blockchain.

Blockchain: Financial

While this study does not target cryptocurrency as its primary research objective, one

must not overlook the financial facet of blockchain. It forms a public, open, and pivotal

component of the blockchain ecosystem, and thus, its contribution merits inclusion. This study

does not focus on the financial element of cryptocurrency but on the underlying data storage and

immutability methods they can provide businesses. When stating the importance of the financial

element of Blockchain, Pakenaite and Taujanskaite (2019) write that as a prospective technology,

it can significantly enhance the traditional banking sector by facilitating faster, more affordable

transactions and offering cost and time efficiencies. Additionally, Demirkan et al. (2020) notes

that Blockchain actively enhances financial security and cybersecurity, and its application in

financial accounting proves instrumental in monitoring and identifying financial misconduct. In

both scenarios, these viewpoints show the transparency and introduce modern technological

enhancements that blockchain can provide to traditional banking components.

Blockchain Cryptocurrencies as Public Ledgers

This study does not focus on the financial element of cryptocurrency but on the

underlying data storage and immutability methods, they can provide businesses. However, due to

their decentralized nature, blockchain cryptocurrencies remove the necessity for central

authorities or intermediaries, yielding faster, more cost-effective, and transparent financial

transactions and data storage (Dashkevich et al., 2020). Moreover, cryptocurrencies hold the

potential to provide financial services to underserved and unbanked demographics, facilitating

their participation in global e-commerce, savings, and investment opportunities (Afzal & Asif,

2019). Wątorek et al. (2023) states there are over 10,000 cryptocurrencies, including inactive and

currencies with zero monetary value.

Bhatia et al. (2023) noted that in 2021, the overall market capitalization of

cryptocurrencies peaked at 2.4 trillion United States dollars (USD), and the capital allocated to

cryptocurrencies equates to higher than the gross domestic product of several nations. (Coutinho

et al., 2023). Three examples of cryptocurrencies that exceeded 10 billion in market cap in March

2023 are Bitcoin, Ethereum, and Ripple (Howarth, 2023), each offering different market uses.

The financial stake associated with enabling trading sustains the operation of the blockchain

nodes and facilitates the maintenance of a transparent public ledger. Notably, these blockchains

were selected based on their size and public utilization, not their financial value.

Bitcoin

Bitcoin is the pioneer of blockchain and the most valuable cryptocurrency by market

capitalization as of 2023 (Khosravi & Säämäki, 2023). It has primarily been seen as a type of

pseudo-digital gold and store of value but has limited uses outside of a store of value (Kumar,

2021). Bitcoin’s initial intention was as a function of transfer of value, but as a point of data

storage, Bitcoin is only useable for storing small amounts of data. Bitcoin operates with a simple

stack-based machine that executes scripts consisting of instructional operation codes (opcodes)

loaded into a stack and executed sequentially (Bellaj et al., 2022). Vaghela and Suthar (2020)

state the limitations as utilizing the blockchain’s OP_RETURN opcode to embed arbitrary data in

transactions, which, though initially set at 80 bytes, was decreased to 40 bytes in February 2014.

The constraint of 40 bytes may appear to be limited, yet it is sufficient to house a

SHA256-bit hash, given that the latter necessitates only 32 bytes. SHA-256 is a cryptographic

hash function using a verifiable, secure secret key that produces an output value of 256 bits in

length (Hakim & Vaze, 2021). The residual 8 bytes could serve as an identifier or delineate a

specific data type. Likewise, Asghar et al. (2023) refer to the method as Proof of Existence,

stating that a fingerprint hash of a document is generated using the SHA-256 algorithm and is

subsequently embedded in the Bitcoin blockchain to authenticate documents off-chain.

Ethereum

Ethereum is an open-source, distributed decentralized blockchain network that supports

smart contract functionality, allowing for the development of decentralized applications

(Jyothilakshmi et al., 2022). Similar to Bitcoin, Ethereum can utilize the proof of existence

method by hashing data off-chain and storing that hash with the Ethereum blockchain as proof of

existence. Ethereum can execute actions and store data in code via multiple advanced languages,

including Solidity and Serpent (Wang et al., 2018), stored in on-chain smart contracts. For the

actions and code to execute, the Ethereum smart contract code is composed in a stack-based

bytecode language and executed within the Ethereum Virtual Machine (EVM) (Wang et al.,

2018). The EVM is an isolated environment on the computers of participants nodes in the

Ethereum network (Alshahrani et al., 2023). It has limited data access, allowing smart contracts

to collect and process data and adopt specific solutions (Alshahrani et al., 2023). Describing the

functionality of a smart contract and how it operates, Kushwaha et al. (2022) note that a smart

contract, defined as self-executable code deployed on the blockchain, automatically executes

upon a triggering condition, fostering trust among parties in a no-trust contracting environment.

Smart contracts are public open source, and the conditions and triggers within the contract can be

viewed publicly at any time, but data storage can be expensive for large pieces of data, and

Ethereum requires a fee called gas to prioritize transactions and store large amounts of data

onchain. Jiahua Xu et al. (2023) describe the Ethereum gas requirement as each interaction with

the protocol occurring as an on-chain transaction and incurring a gas fee, consistent with all

transactions on the underlying blockchain. On the Ethereum network, one cost unit is referred to

as Ether (Preece et al., 2019). Ether can be represented in a smaller unit called Gwei (Giga

Weight), which denotes the ninth power of fractional Ether, also known as nanoether.

Ethereum storage operates through slots where the “EVM storage is a key-value mapping

of 2256 slots of 32 bytes each” (Bellaj et al., 2022). Similarly to Bitcoin’s opcode storage, 32 bytes

is precisely the length of an SHA-256-bit hash, creating a well-defined location to store a hash of

offline data for a proof of existence on-chain. Buterin (2014) states in their whitepaper that the

storage cost of 256 bits, or 32 bytes, is 20,000 gas, with the cost of gas for August 2023

averaging 26.23 Gwei or 0.00000002623 Ether ("Ethereum Average Gas Price," 2023) with the

average cost of Ether in 2022 being USD$1,700 (De Vries, 2023). Therefore, the total extra cost

to store a 32-byte hash is calculated as 0.00000002623 x 20000 x $2,139.42 = USD$0.89. While

this value only represents the additional data storage cost and not the transaction’s cost, it

provides an additional trusted and decentralized blockchain validation solution. Therefore,

considering the relatively low cost of storing a single hash and the adequate size of an Ethereum

slot, one can demonstrate that hashing a large off-chain dataset ensures its immutability at a point

in time by providing a public hash of the data itself.

Ripple

Ripple is an alternative payment method for banks and financial institutions through

which companies can cheaply and quickly transfer various assets (Bezpartochnyi, 2023). Ripple

has a slightly different use case than other blockchains, such that when describing Ripple, Akcora

et al. (2022) state that Ripple’s terminology substitutes “ledger” for “block,” and transactions

within this system encompass various categories, including financial instruments like checks,

user-issued currencies such as the United States Dollar (USD), and path-based settlement

mechanisms. With Ripple holding such a large market cap, there is less chance the network will

falter as the failure of a public decentralized system may come about if the network is not used.

Ripple can store data, such as a hash, within transactional memos (Dervishi et al.,

2022); however, in August 2023, Ripple’s focus is aimed as a financial tool, and its

appropriateness for serving as a data store appears to be suboptimal.

Fee-Based

This document focuses not on cryptocurrencies per se but instead on the blockchain’s

public ledger mechanism that they provide. Consequently, it is imperative to factor in the

expenses of conducting public transactions when proposing any framework or methodology

(Mohammad Hashemi et al., 2020). As previously highlighted, blockchain technology is

constantly evolving, and it is advisable to conduct additional research into emerging methods. It

is essential to acknowledge that this research document cannot comprehensively encompass all

conceivable approaches to interact with the multitude of available blockchains, but it has

provided insights into interactions within prominent blockchain ecosystems.

Effect on Government and Business

Blockchain, along with the high speed of globalization and the general connectivity of the

internet, has influenced Australian governments and businesses by revolutionizing data security,

streamlining supply chains, and fostering innovation in financial services (Karim, 2020). Via

blockchain technology, traditional legacy banking systems have modernized along with

transaction speed, supply chains have tracked end-to-end materials and goods, and the

immutability of documents has allowed for the accountability and transparency required of a

government and businesses. The utilization of blockchain technology in Australia is apparent,

Almatarneh (2020) states blockchain use in Australia as a shared tamper-proof peer-to-peer

ledger that assertively provides an irrefutable and immutable source of transactional truth for all

parties involved. Moreover, describing an Australian real-estate-based blockchain system,

Almatarneh (2020) says the platform will incorporate smart contracts to facilitate property

transactions and automated payment systems while also storing additional information related to

the duration of the tenancy, vacancy periods, and other relevant details. Providing a higher level

of detail and enhanced transparency compared to current capabilities, this approach allows for

real-time data access without the delays typically associated with statewide data collection.

Blockchain has enhanced Australian supply chains’ efficiency and transparency (Lindley,

2022). Perera et al. (2020) discuss a project underway with Australia’s beef as it is in high

demand, particularly in the Asian markets; however, a substantial presence of counterfeit

Australian beef exists, prompting Australia’s CSIRO’s Data61 to actively pursue the adoption of

blockchain technology as a means to reduce the costs associated with food fraud in Australia.

Similarly, Andoni et al. (2019) note that Australia is developing a blockchain-based residential

peer-to-peer electricity trading marketplace that facilitates interactions between prosumers and

local consumers.

Blockchain as a financial instrument has also introduced risks. Islam et al. (2018) note

that an Australian university has presented compelling evidence linking terrorist groups and their

supporters to multiple terror attacks in Europe and Indonesia, with certain websites collaborating

with terrorist organizations to facilitate Bitcoin-based donation collection. On the other hand, due

to the transparent and public nature of Bitcoin and other blockchain ledgers, identifying such

groups’ digital wallets and tracing transactions to and from them can be employed for

identification purposes. While blockchain presents financial risks, its transparency can also be

harnessed for identifying and tracking digital wallets associated with illicit activities, offering a

dual-edged sword in the fight against terrorism and illicit uses of assets.

Before Blockchain

The concept of decentralization in technology used for business has existed for over 60

years. The precursor of the internet as a distributed network of computers Hauben (2007) note

that in 1967, computer scientists affiliated with ARPA were actively engaged in deliberations on

critical aspects pertinent to the planning and establishment of the ARPANET. The ARPANET

went on to launch in 1968 and continued to evolve into the Internet as it is known today. Local

computer networks or LANs were commercialized; Collen (1994) notes that in 1973, Robert

Metcalfe and his team at Xerox Palo Alto Research Center introduced Ethernet, an early

baseband coaxial cable network designed for high-speed communications. These pivotal

developments physically formed the foundation for the modern interconnected environments of

data sharing, networking, and decentralization in which blockchain is built.

Physical elements of computer systems have advanced over the years with

decentralization (Bodkhe et al., 2020). Physical hard drive RAID setups stripe or split the data

they store over multiple local hard drives for speed and redundancy. In the mid-1980s, David

Patterson, Garth Gibson, and Randy Katz from the University of California, Berkeley, played

instrumental roles in developing the first systems that would eventually be recognized as RAID

(Redundant Array of Independent Disks) (Leventhal, 2009). In their 1988 white paper titled “A

case for redundant arrays of inexpensive disks (RAID)” (Patterson et al., 1988) outlined the need

to decentralize data from one centralized data store to multiple drives to improve availability,

reliability, and performance.

Decentralization has significantly impacted computer code and software, with BitTorrent

serving as an excellent example of a decentralized protocol. BitTorrent was created in 2001 by

Bram Cohen (Salmon et al., 2008) as a decentralized file system that allowed connected swarms

of users to download bits of data to form files effectively. Analogous to RAID drives, multiple

connected decentralized users distribute a file, with each user providing “bits” that collectively

assemble into the complete file. The distributed filesystem acts like a simplified blockchain

distributed ledger system where clients use MD5 and SHA hashes (Teing et al., 2017) to verify

each copy of the file. Firdaus et al. (2019) suggest that Bitcoin’s creation was influenced by

BitTorrent, noting that blockchain technology presents the notable advantage of distributed

computing, a feature that had already demonstrated its robust functionality through its effective

utilization by BitTorrent before the emergence of blockchain. Moreover, both technologies

incorporate the prefix “bit” and employ decentralization and hashing to address distinct features.

The influence of BitTorrent’s decentralized file-sharing system on the development of blockchain

technology underscores the significance of distributed computing in shaping modern computer

systems.

Establishing Trust and Data Immutability

In computing, establishing trust and ensuring data immutability is crucial for the integrity

and security of digital systems. Blockchain uses decentralized, tamper-resistant ledgers,

cryptographic hash functions, and consensus mechanisms to establish user trust and ensure data

permanence. These principles have wide-ranging applications across industries, including supply

chain management, healthcare, and finance, where transparency, accountability, and data

integrity are paramount. Although trust is not automatic, Mehraj and Banday (2020) note that

trust represents a complex social phenomenon wherein one party relies on another in a diverse

environment, involving risk and dependency to foster confidence-based relationships. Trust on

the blockchain is unique; Werbach (2018) points out that blockchain enables participants to place

trust in the system’s outcomes without needing to trust any individual participant.

Nevertheless, it is essential to note that even if the code functions flawlessly, humans craft,

execute, and utilize the blockchain systems, and the platforms leave them susceptible to selfish

behavior, attacks, and manipulation (Werbach, 2018). In other words, one can establish a

mechanism that instills trust, although the actions executed within the trusted blockchain may not

necessarily guarantee trustworthiness. For instance, an unauthorized individual could assume

control of a computer system and transfer all the cryptocurrencies from one user’s wallet to

another.

Australian Blockchain

Within Australia, a vibrant and thriving blockchain community has emerged in the last ten

years, encompassing both public and private sectors and various industry groups and

associations. This community is actively engaged in exploring blockchain technology and

collaboratively advancing its adoption across diverse domains. It is not feasible to cover every

blockchain initiative; therefore, several governments and leading Australian blockchain

businesses have been highlighted in this review.

Both state and Australian governments are vested in exploring blockchain technologies

and offer several viewpoints. In 2020, the Australian government released the Australian

Blockchain Roadmap ("Australia's National Blockchain Roadmap," 2023), which proposed 12

signposts or action items that should be addressed to fulfill the information requirements.

The list consists of the establishment of a national blockchain roadmap steering

committee; working with groups of industry, the research sector, and the government to progress

analysis on the subsequent use cases; progressing the three use cases in the roadmap; a group of

government blockchain users; identify examples of countries using blockchain to provide

efficient government; engage with the Business Research and Innovation Initiative (BRII)

program; increase management capability around digital technologies; develop common

frameworks and course content for blockchain qualifications; capability development program

for Australian blockchain start-ups; deliver a blockchain focused inbound investment program;

leverage existing bilateral agreements to consider pilot projects; and Australian businesses can

connect to emerging digital trade infrastructure.

As of September 2023, seven of the twelve posts have been met, with other stages listed

as in progress.

Some of the reported ("Australia's National Blockchain Roadmap," 2023) items

completed are the establishment of the National Blockchain Roadmap Steering Committee;

production of discovery reports by working group into blockchain applications in credentialing,

supply chains, cyber security, and regtech; launch of the APS Blockchain Network, funding for

two pilot projects for companies to demonstrate blockchain’s potential for reducing business

compliance costs; a start-up capability program delivered by Austrade and Blockchain Australia

with a landing pad in Israel; and 11.4 million Australian dollars (AUD) committed to support

new regulatory technology innovation challenges through business research and innovation

initiatives (BRII).

As the research questions posed in this study aim to establish a framework for

incorporating blockchain utilization, it is essential to note that, as of September 2023, no

Australian recommendation or framework has been officially established or published in the

Australian Blockchain roadmap.

Till Payments

Till Payments is an Australian-based financial company that won Blockchain Australia’s

2019 Blockchain Startup and Business of the Year (Munro, 2019). Till’s blockchain technology

centers around patented distributed ledger technology that intercepts digital point-of-sale

transactions to determine goods and services tax (GST) compliance (VAT Monitoring Command

Centre, 2018). Till’s method of storing data on the blockchain utilized the off-chain data storage

pattern or proof of existence method to store and verify data. Haddad (2019) describes the

method as “a hash or digital signature derived from the transaction details (which) are then stored

in a blockchain or similar immutable data store.” In this scenario, one can retrieve verification

data from the blockchain and subsequently compare it with the transaction data to ensure the

authenticity and integrity of the transaction data (Haddad, 2019). Till Payment’s opportunity to

enhance enforcement of a taxation device around an established business function shows a

unique approach to blockchain.

Red belly blockchain

Red belly blockchain (RBBC) is an Australian-built unique blockchain developed by The

University of Sydney and Australia’s CSIRO Data61 (Redrup, 2018). RBBC differs from

existing blockchains by tackling networking scaling, speed, and security as its primary

objectives. Crain et al. (2021) note that Red Belly Blockchain represents the first secure

blockchain capable of scaling to accommodate hundreds of geo-distributed consensus nodes. In

testing, Mendling et al. (2018) note that it has been designed specifically for private or

consortium blockchains and has successfully achieved a throughput of over 400,000 transactions

per second in a laboratory test. The technology underpinning RRBC is the fact that it uses the

Democratic Byzantine Fault Tolerance (DBFT) consensus protocol (Wang et al., 2022) rather

than Byzantine Fault Tolerant used in other blockchains. When describing the method, Crain et

al. (2018) said the fundamental concept is to enable processes to conclude asynchronous rounds

as soon as they receive a threshold of messages rather than waiting for a potentially slow

message from a coordinator. This approach enables RRBC to attain a high transaction-persecond

capability, providing governments and businesses with the assurance of scalability and efficient

handling of large volumes of data.

Virtually Human

Virtually Human is an Australian-based blockchain game developer most notably known

for their NFT horse breeding and racing game Zed Run (Laker, 2022). Describing the game

concept, Hackl (2021) states that in Zed Run, users engage in the purchase, sale, and breeding of

digital racehorses, each possessing distinct bloodlines and genotypes, with the additional

opportunity to actively participate in horse races against other collectors and place bets. What

makes this unique is the concept of passing information and traits to a new generation of NFTs.

Discussing this further, Lorenz (2021) writes that NFT horses possess individualized traits such

as breeding capability, distinct bloodlines, racing abilities, genetic inheritance, and unique

characteristics derived from an algorithm, allowing for a diverse population of horses, and

owners have the option to breed their horses in the platform’s stud farm. The Australian company

distinguishes itself by enabling the amalgamation of traits from two distinct horses to create a

new Blockchain NFT game horse with inherited traits from the preceding generation.

Blockchain Bureaucracy

Blockchain is not a silver bullet that can solve every data-sharing problem and should

have strong use and justification cases to implement. As government and business priorities shift,

several blockchain entities within Australia have moved focus to other initiatives. In 2022, a

change of government in Australia brought a shift in priorities, policy, and budgetary spending

(Karp, 2022), which had a ripple effect on companies and government departments that depended

on government budgets. Government entities such as the Australian Department of Foreign

Affairs ("Australia’s Blockchain Roadmap," 2021), which previously had relevant sections on

their website dedicated to blockchain research, in September 2023 have a website with broken

links or no longer exist. Previously prominent blockchain companies such as Everledger

(Bennett, 2023) filed for bankruptcy due to poor management and dependence on government

grants. In November 2022, the Australian Stock Exchange (ASX) announced the termination of

its blockchain-based solution intended to replace its legacy stock trading platform due to external

vendor management issues and its unsuitability for operational use. (Eyers, 2022). Although

blockchain can accomplish numerous objectives, political and bureaucratic factors may impede

its progress.

Furthermore, in the past five years, artificial intelligence (AI) has seen growth and

interest from the government, industry, and consumers (Sousa et al., 2023). Rabah (2018) notes

that AI and blockchain are two pivotal technologies propelling innovation and catalyzing

profound changes across diverse industry sectors, each distinguished by its distinct technical

intricacy and business ramifications. Nonetheless, the synergistic application of these

technologies holds the capacity to fundamentally redefine the entire technological and human

paradigm. The shift or convergence by formerly prominent Australian blockchain companies,

such as Area 61, focuses on publishing AI reports and articles over blockchain. The trend has

resulted in a talent shift, with developers, investors, and businesses relocating to interest areas

where government priorities align with current government politics, grants, and budgets.

Australia, a culturally rich nation with a democratic foundation, may experience shifts in

governments and politics over time, and blockchain is likely to be employed in various

capacities. Nevertheless, the underlying challenges of data transparency, immutability, and

validation will persist, irrespective of utilizing blockchain technology. The evolving blockchain

technology landscape reflects the need to consider its practicality and alignment with changing

governmental and business priorities, as demonstrated by recent shifts and challenges within the

ecosystem.

Chaos Theory

One of the most recognized tenets of chaos theory is the butterfly effect, posited as “the

flap of a butterfly’s wings in Brazil might set off a tornado in Texas” (Lorenz, 1963). This

assertion elucidates an initial event’s profound consequences on subsequent outcomes, which

analogous to blockchain, says its initial state parameters or consensus are pivotal in determining

how it will perform, operate, and ultimately establish its utility. When discussing interconnected

systems and blockchain, Kohler (2021) states that a system’s current state dictates its future, but

inherent interconnections, threshold effects, and feedback loops mean an approximate present

state does not necessarily predict its approximate future state. Parameters such as methods for

storage, size of blocks, number of nodes, and even which blockchain to fork are all initial

parameters critical to shaping the chaotic outcome of the blockchain.

A cornerstone of blockchain technology lies in its decentralized structure, with nodes

operating independently on a global scale, complemented by the consensus mechanism. As a

blockchain expands, the stability of the entire network concurrently increases; however, with

insufficient nodes, the blockchain can falter and stagnate (Wan et al., 2020). Stapleton et al.

(2006) address this network effect, positing that the absence of predictability might induce

sporadic and severe demand variations, intensifying system instability. Expanded

decentralization of any blockchain network can stabilize a chaotic, uncontrollable system.

Blockchain functions deterministically, wherein preceding immutable and irrevocable

events establish the parameters for current events; specifically, the Merkle Root in a block,

derived from a Merkle Tree of transactions, is influenced by its hash of the previous block.

Shukla et al. (2015) describe both chaotic theory and encryption systems operating on

deterministic principles, wherein specific initial conditions or inputs entirely determine their

future states or outcomes without any random elements or interventions.

Overall, given the intricate dynamics of blockchain and its sensitivity to initial

parameters, drawing parallels to the principles of chaos theory offers a profound lens through

which we can explore the unpredictability and emergent complexities of decentralized systems.

The literature consistently underscores the multifaceted nature of blockchain technology and its

potential intersections with chaos theory. Scholars have elucidated the deterministic attributes of

blockchains while highlighting areas of unpredictability and emergent behavior reminiscent of

chaotic systems (Liu et al., 2022). Furthermore, chaotic computer models display extreme

sensitivity to initial conditions, meaning that minor variations in the starting state can result in

significantly different outcomes (Zhang & Liu, 2023). Given the intricate dynamics of

blockchain and its sensitivity to initial parameters, parallels with chaos theory offer a theoretical

framework and practical insights for future blockchain developments.

It is evident from the reviewed works that an interdisciplinary approach, merging

principles from both domains, could pave the way for innovative solutions, addressing the

challenges and harnessing the potentialities of decentralized digital systems. As knowledge

expands, future research would benefit from delving deeper into these intersections, potentially

establishing a foundational nexus between blockchain mechanics and chaos theory.

Consensus Theory

Consensus theory holds that a group considers the prevailing norm as the correct answer,

asserting that if a sufficient number of people believe it, they regard it as correct. In the context

of blockchain, the consensus layer sometimes called the protocol layer, represents the single most

crucial element for the blockchain’s existence as it is the element where validation and

recordings of transactions occur (Jie Xu et al., 2023). When describing blockchain, Neudecker

and Hartenstein (2018) note that for the consensus layer to function correctly, all peers must

possess knowledge of the information set for which they seek consensus. In other words, a

specific set of rules enables the processes of validation and consensus, and once a participant

arrives at an answer, that individual collaborates with other participants to form the consensus.

Unlike other consensus flocking models (Lizzio et al., 2022), blockchain participants do not

merely accept the existing consensus; each independently verifies transactions, using consensus

for validation and immutability.

Decentralized

While most public blockchains function decentralized, they may still have a central group

of developers or a principal leader. However, the onus of agreeing on system changes and

determining their implementation lies with the nodes in the blockchain network. Chaudhry and

Yousaf (2018) note that the consensus mechanism, a core concept in blockchain, ensures a

tamper-free environment where all nodes within a decentralized network acknowledge a single

version of the truth regarding the state of the blockchain. An independently operated, distributed

ledger with a single source of truth allows blockchain to operate with integrity, transparency, and

unparalleled security.

Conflict Resolution

Blockchain employs multiple methods to process transactions on the consensus layer.

However, challenges arise when two nodes simultaneously solve a reward, leading each to

initiate two consensus versions or a fork or when malicious actors attempt a double-spend attack

(Nicolas et al., 2020). Conflict resolution varies based on the specific blockchain

implementation; however, when a blockchain forks, the longer of the two emergent chains

establishes itself as the predominant source of truth. In this scenario, a secondary layer of

consensus within blockchain transactions occurs. Natoli et al. (2019) describe this as the longest

chain typically reflects the most work performed, operating on the premise that most of the

network’s computational power resides with honest participants. In the case of consensus and

Bitcoin, it “always accepts/recognizes the longest chain, which ensures that the majority of nodes

on the network will eventually reject and eliminate unintended forked chains” (Murray, 2019).

Blockchain technology is a powerful example of consensus theory that elegantly solves the

complex problem of achieving agreement across a distributed network. As a decentralized data

ledger, it maintains data veracity and transparency across disparate entities. This is made possible

through consensus mechanisms, which ensure that diverse network participants can collectively

arrive at a unified version of truth without centralized oversight. These mechanisms, derived

from foundational tenets of consensus theory, guarantee that the honest majority upholds the

system’s integrity. As such, the intersection of blockchain and consensus theory showcases the

importance of collaborative agreement in distributed systems and underscores the profound

implications for future technological advancements and societal shifts.

Bureaucracy Theory

Bureaucracy theory, articulated by Max Weber, emphasizes establishing administrative

structures with a hierarchy of authority, enhancing efficiency in organizations by implementing a

clear division of labor, establishing set defined roles and offices with continuity of job roles, and

adhering to a structured set of procedural specifications (Nhema, 2015). When describing

blockchain Talat et al. (2022) state that blockchain offers benefits such as data immutability, fault

tolerance, enhanced security, the execution of smart contracts, and the verification and

uniqueness of transactions. Analogous to consensus theory, where blockchain necessitates

consensus for block validation, all nodes operate under a specified bureaucracy or rule set to

function collectively.

Distributed ledger

The data is an enduring public record, emphasizing a transition to system-based trust.

Drawing a parallel, Jordan-Makely (2019) asserts that bureaucracies emerged when society and

individuals began to place greater emphasis on rational action, systematic planning, and technical

procedures. Furthermore, Sulieman (2019) notes that bureaucracy theory requires the need to

formally document and securely store information for future reference when necessary, mirroring

that of a blockchain’s permanent, unchangeable data storage system. The blockchain’s distributed

ledger function and bureaucracy theory emphasize the importance of standardized procedures

and eliminating arbitrary decision-making. Whereas bureaucracy aims to achieve this through a

structured hierarchy and rigorous documentation, blockchain achieves a similar end by providing

an immutable, transparent record of transactions, ensuring consistent and verifiable processes

throughout the network.

Status Quo

One of the critiques of bureaucracy is its potential for inefficiency and delays. Similarly,

concerns arise with blockchain concerning scalability, transaction speed, and consensus delays.

Blockchain can slow when there is an increase in transaction volume, Das and Patra (2019) state

that as the number of transactions increases, blockchain has precipitated a scalability issue; given

that each transaction undergoes a validation process, many transactions languish in a queue for

extended periods, leading to protracted response times and exacerbating scalability concerns.

Similarly, when describing the bureaucratic decision-making processes, Riggio and Newstead

(2023) state that it can vary in speed; however, they must be consistently grounded in the most

robust available evidence and consider a comprehensive evaluation of the implications for

diverse stakeholders. In this context, blockchain prioritizes the accuracy and integrity of data,

potentially compromising public efficiency and speed. Many blockchain users uncritically accept

these trade-offs as the technology’s inherent characteristics.

Summary

Blockchain technology is multifaceted, with the ambition of addressing numerous

challenges. However, this multifaceted nature represents both its advantages and drawbacks. It

can gain widespread adoption only by simplifying intricate details and specific use cases and

delivering a framework simultaneously without imposing a substantial burden on existing legacy

structures. However, implementing change is inherently challenging and should be carefully

managed across various dimensions, including regulatory, political, technological, sociological,

and budgetary aspects. Existing blockchain communities should prioritize problem-solving

through practical use cases rather than solely relying on government grants. At multiple levels,

encouraging, enhancing, and supporting existing and emerging blockchain technologies should

occur.

The impact of blockchain on business and government should foster enhanced

transparency and trust. Approaches like proof of existence and off-chain data storage patterns

could be considered without causing significant disruptions to existing systems. With their

impressive speed and high transaction throughput, technologies like Red Belly Blockchain

deserve consideration as primary blockchain contenders. However, it is essential to recognize

that blockchain’s association with financial aspects, particularly cryptocurrencies, plays a

substantial role in public blockchain adoption. Without a financial incentive, blockchain could

face obsolescence as another passing product.

Chapter 3 will introduce the qualitative research methodology, elucidate the study’s

design, outline the research and theoretical framework, and expound upon the criteria employed

in participant selection. Additionally, this chapter will provide an overview of the data collection

process, interview questions and deliberate on the sample selection.

Chapter 3: Methodology

According to Wang et al. (2021), blockchain has become a significant academic focus,

with substantial advancements in research garnering attention from scholars, practitioners, and

policymakers. The purpose of this qualitative study is to analyze consumer trust in blockchain

implementation and its effect on information services industries within Australia. This chapter

will provide an overview of the research design followed by further insight into the general

utilization of blockchain and offer meaningful and feasible implementation solutions. The

procedure for data collection followed security practices, anonymized and stored both on the

researcher’s password-protected personal computer and within Google Cloud service as a

backup, protected by 2-factor authentication. Instrumentation was one-on-one interviews

utilizing field notes and audio transcribed from the video conferences. Data collection from the

interviewees required informed consent documents explaining the purpose of the research and

how the data would be collected, recorded, and stored.

Research Design

Research design encompasses the methodology for planning and conducting empirical

research, encompassing quantitative and qualitative approaches for collecting cross-sectional and

time series data (Mweshi & Sakyi, 2020). When examining the research designs employed in this

study, the researcher scrutinized various qualitative, quantitative, and mixed methods. The nature

of the study ultimately warranted the selection of a qualitative design utilizing grounded theory

design based on the literature review for this study and the variety of scenarios the research may

address during data collection. Moreover, enriching qualitative research with first-hand data

facilitates theory construction, whereas strictly adhering to objectivity, validity, reliability, and

replicability canons may impede theorizing (Charmaz & Thornberg, 2021). Furthermore, the

qualitative research design is significant in evaluating thoughts, viewpoints, and perspectives to

collectively present information (Alamri, 2019). Applied to blockchain and the number of

existing systems within Australian businesses, an adaptive and varied research method was

required.

Grounded theory bridges the divide between theory and empirical research by allowing

theory to emerge organically from the collected data (Maupa & Abidin, 2020). Achieving this

involves inductive reasoning, data collection, analysis, theory construction, comparison, memo

writing, and employing theoretical sampling (Rieger, 2019). Grounded theory was selected for

this study to facilitate theory development and provide flexibility for the research to form its

conclusion. Blockchain adaptability and multiple use cases within information technology and

service industries necessitate an open approach to the research and the data collection process.

One notable advantage of grounded theory methodology lies in its provision of a

systematic and rigorous framework encompassing procedures and techniques for the collection,

analysis, and interpretation of data, facilitating the development of a substantive theory that

offers a conceptual explanation of a human phenomenon (Brunet et al., 2022). However, Yu and

Smith (2021) argue that pre-conceived knowledge developed during the literature review can

taint grounded theory research. Furthermore, Yu and Smith (2021) describe a divide among

researchers using this method, whether the optimal approach involves commencing research with

a clear mind or equipping researchers with preliminary knowledge. Mfinanga et al. (2019)

describe that the design’s data will vary based on the participants’ descriptions, opinions, and

feelings rather than scientific facts. Grounded theory is a research design that, if not employed

correctly, has the potential to introduce researcher bias and subjectivity into the study, thereby

impeding the objectivity and generalizability of the study’s findings.

Grounded Theory and Blockchain

Within the context of this study, grounded theory equips the researcher to conduct a

systematic research investigation into various facets of blockchain technology and unveil the

primary factors influencing blockchain implementation (Tyan et al., 2020). Combining this

design with the snowball interview method enables exploratory questioning and helps uncover

concepts and applications that a rigid line of questioning may neglect. Moreover, grounded

theory aids in addressing the research questions to risks associated with blockchain

implementations in the information services industries while additionally gaining insights into

entities currently employing blockchain technology.

In grounded theory, the maxim “all is data” implies that all phenomena and insights the

researcher encounters while examining the topic of concern are considered data (Conlon et al.,

2020). Similarly, inductive reasoning involves synthesizing probable conclusions by examining

and integrating observations or an array of diverse types of evidence, often accumulated from

many sources or experiences over time (Davidson, 2019). Within this study, methods that permit

exploratory questioning of different concepts within the same subject will prove valuable during

the research phase. These methods drove the study towards yielding reasonable and replicable

findings under similar conditions.

Quantitative Research

Quantitative research was not selected as the research design as it employs statistical,

mathematical, or computational techniques to obtain precise results with data collected through

closed-ended questionnaires in numerical formats, allowing for the development and application

of mathematical models, theories, and hypotheses to achieve desired outcomes (Mohajan, 2020).

Moreover, it evaluates a hypothesis, which posits a specific relationship between dependent and

independent variables by selecting a representative sample from a defined population,

quantifying the variables, and subjecting them to statistical analysis (Bloomfield & Fisher, 2019).

When considering the data collection requirements for interviews, quantitative research becomes

unsuitable for a study aiming to answer the research questions if the data gathered does not seek

to establish binary categorizations or definitive conclusions.

Other Designs

Simply put, a research design is the overall strategy employed to conduct a research study

(Bloomfield & Fisher, 2019). For the researcher, the research design serves as a foundational

blueprint established before data collection, guiding the process toward validly achieving the

research objectives (Asenahabi et al., 2019). Therefore, selecting the most suitable research

design is critical to yield optimal, valid, and reproducible results. When establishing the study,

considering and eliminating alternative research designs is crucial in determining the best method

to gather research data. For this study, when considering research designs, both Case Study

Design (Duggleby et al., 2020) and Phenomenological Research (Vidyantari et al., 2022) were

evaluated but ultimately not selected.

Case Study Design

A case study design offers significant value in examining the interconnections among

personal, social, behavioral, psychological, organizational, cultural, and environmental factors

that influence the study (Halkias & Neubert, 2020). A case comprises various pertinent

dimensions constructed from single or multiple observations, from which one can understand a

broader class of observed phenomena (Turnbull et al., 2021). A case study examines existing

research, focusing on structured results that were selected based on previous criteria other

researchers deemed relevant. The research questions necessitated a comprehensive exploration of

diverse levels of human behavior, investigatory questioning, information discovery, and data

gathering from various environments that case study design was not suited to provide.

Phenomenological Research

Phenomenological research represents a methodological approach focused on capturing

the essence of a phenomenon by examining experiences from the viewpoints of those who have

encountered it (Becker & Schad, 2022). It operates on the principle that by setting aside personal

opinions, it becomes feasible to arrive at a singular, fundamental, and descriptive representation

of a phenomenon (Ivan, 2019). The data collection predominantly concentrates on personal

narratives and lived experiences, typically obtained through comprehensive, in-depth interviews.

While this research study conducted interviews, the data collection does not reflect personal

opinions or lived experiences with blockchain technology. Blockchain research,

implementations, and future planning require a broader range of data types that

phenomenological research cannot provide.

Grounded Theory

Grounded theory represents an extensively exploratory research methodology designed to

develop a theory grounded in empirical data, encompassing qualitative and quantitative aspects

(Meijer & Ubacht, 2018). Moreover, grounded theory will guide the data analysis, directly

addressing the research questions and marking a critical contribution to the study (Della Valle &

Oliver, 2021). The exploratory nature of grounded theory design permits diverse lines of

questioning and reasoning and enables the collection of varied reflections of experiences through

interviews. In the context of blockchain research, grounded theory proved to be a versatile and

insightful methodology, facilitating a comprehensive and contextually rich understanding of the

intricate subject matter.

Research Questions

This study addressed the following research questions:

Research Question 1

What are the key regulatory challenges hindering the implementation of blockchain

technology in Australia’s information services industries?

Research Question 2

How does the absence or inadequate implementation and communication of blockchain

data processes pose risks to Australia’s information services industries?

Research Question 3

What challenges do businesses face in understanding and accepting blockchain systems,

and how can these challenges be effectively addressed?

Population and Sample

Comprehending populations and samples equips researchers with the ability to offer

valuable insights and make informed decisions, enhancing human understanding in diverse fields

(Ahmad et al., 2023). For this study, the location of the participants is a selection of academic

and industry professionals living and working throughout Australia, primarily coming from the

two most populous business city centers, Sydney and Melbourne. The selection of the

participants started with the researcher’s existing network of contacts within the blockchain field

and then utilized the snowball effect in gathering recommendations for potential new

interviewees. The researcher selected and initiated contact between twenty and twenty-five

participants, expecting to disqualify some who failed to achieve a sufficient score on the

qualification test using the radar chart method done after the interview. From there, a core group

of eight to twelve participants will be chosen based on their eligibility as interviewees, which

was determined using a radar chart (see Figure B2). This method ranked each potential candidate

on a scale of 0 to 10, evaluating their technical understanding, familiarity with government and

regulatory frameworks, theoretical knowledge, and financial expertise.

Utilizing grounded theory enabled the researcher to establish a set of baseline questions,

which had the effect of sparking and examining new lines of inquiry while allowing the

interviewee to open up to new concepts. These baseline questions began with introductory

queries and led the interview into a flexible, partially guided style (see Appendix C).

Upon receiving approval from the Institutional Review Board (IRB) for the study, the

researcher initiated data collection by emailing potential interviewees. This communication

included a letter of invitation to participate in the study (see Appendix C). Individuals who

express their willingness to participate voluntarily were emailed an informed consent form

detailing the study’s ethical guidelines, outlining the rights of the participants and any potential

risks involved (see Appendix D).

Grounded theory operates through an inductive methodology, analyzing data and deriving

concepts directly from this data (Pieterse, 2020). The study focuses on data collection and

permits the data to shape the research and its direction of questioning. The researcher achieved

data saturation when the data gathered yielded consistent responses and ceased producing new

information.

Data Saturation

Saturation in data collection occurs when additional data ceases to reveal new issues or

insights, indicating redundancy and signifying the adequacy of the sample size, thereby serving

as a crucial marker of content validity by demonstrating that the collected data encompass the

diversity, depth, and nuances of the studied phenomenon (Hennink & Kaiser, 2022). In

semistructured interviews, where researchers use a predetermined list of base questions, such as a

grounded theory design, data saturation is recognized when interviewers repeatedly obtain the

same information from subjects, suggesting no further data collection is necessary (Mwita,

2022a). Achieving saturation in semi-structured interviews not only confirms the

comprehensiveness of the data in reflecting the studied phenomenon but also marks the point at

which additional data collection becomes superfluous, underscoring the efficiency and

effectiveness of the research methodology.

Role of the Researcher

In qualitative studies, the researcher aptly assumes the role of an instrument within a

scene, maintaining specific parameters and a degree of separation from themself (Collins &

Stockton, 2022). Furthermore, the researcher as an instrument is pivotal for data collection and

interpretation, typically employing direct observation, interviews, and document analysis

(Amelia et al., 2023). In this study’s context, the researcher, acting as the interviewer and guided

by grounded theory, formulates the questions and directs data collection during interviews. To

minimize bias, the researcher initiated participant recruitment through their network, focusing on

prominent figures in the Australian blockchain community without a pre-existing business or

personal relationship to the researcher. To further mitigate bias, the research design includes a

clearly established set of initial evaluation criteria to determine suitability of a candidate. Finally,

the researcher remains vigilant against assumptions, consciously aware of potential personal

biases, and self-reflected on the nature of questions and data collected.

Australia’s cultural diversity is a vibrant mosaic, rooted in rich Indigenous traditions and

enriched by a broad spectrum of global influences due to its history of immigration and colonial

past (Pham et al., 2021). However, it is essential to note that cross-cultural research mainly

focuses on testing the applicability of psychological measures developed in the United States

across different cultures, frequently neglecting unique cultural aspects absent in these

Westerncentric measures. The combined etic-emic approach, developed to address this issue,

evaluates the universality of similar constructs across various cultures. It integrates the etic

approach’s broad applicability with the emic approach with the in-depth cultural specificity of

the emic approach. (Gardiner et al., 2020). Exploring Australia’s cultural tapestry necessitates a

nuanced understanding and application of etic and emic perspectives, ensuring that research

accurately reflects the country’s unique cultural landscape alongside universal human

experiences.

Geographical or Virtual Location

The interviewees were geographically located within Australia, more specifically

targeting the two largest cities, Sydney and Melbourne. Interviews were conducted one-on-one

through video conferencing, requiring all interviewees to activate their video feeds. In addition,

all interviews were recorded visually and audibly, with the audio component transcribed into text

and saved as an individual Microsoft Word file. The researcher saved each participant’s video,

audio, and data files in individual folders, labeling them interviewee_X, where X represents a

numerical number assigned in order of interviews. Individual files placed within these folders

have a format of “type_ interviewee_X_YYYYMMDD” where type refers to the data type,

audio, video, or other; and YYYY, MM, and DD denote the year, month, and day, respectively.

An organized and well-structured file system effectively prevents errors related to misplacement

of documents and significantly facilitates more accessible and more efficient searching, thereby

enhancing overall productivity and data management.

Participants were anonymized and categorized following the methods outlined in the

research design. The researcher structured a pilot study as an open-label and single-arm trial

based on the initial probing questions to ensure that location and other biases’ will not influence

the results (Okada et al., 2021). In addition, the researcher conducted the pilot study to validate

the line of questioning and assess its effectiveness in gathering the intended data for the study.

The pilot study provided a preliminary understanding of the study’s feasibility, and any necessary

adjustments to the methodology or questions were made before proceeding to the complete data-

gathering research part.

Procedure

The researcher sent invitations to participate in the study via email or direct InMail

messages on LinkedIn, targeting both individuals identified within their network and candidates

recommended through the snowball method. Initially, the researcher selected and initiated

contact between twenty and twenty-five participants, expecting to disqualify some who failed to

achieve a sufficient score on the qualification test using the radar chart method done after the

interview. After establishing interest with the eight to twelve individuals, the researcher sent an

invitation letter via email to each participant outlining the study’s objectives (see Appendix C).

The study’s data collection methods were exclusively digital, involving personal

computers, high-speed internet access with minimum upload and download speeds of 5mbit,

video conferencing software, and connected cameras and microphones. The study utilized video

conferencing software such as Zoom, Microsoft Teams, and Google Meet, which were selected

based on the interviewee’s familiarity and personal preference. This approach ensured that

participants from various locations could easily contribute and share their knowledge, providing

a rich and diverse dataset for analysis. The researcher stored all data recorded, including video,

audio, notes, and transcriptions, from the interviews on a biometric password-protected personal

computer and maintained an offsite backup in private Google Cloud services. All accounts,

including cloud services, use a strong password with activation of 2-factor authentication for

enhanced security.

Instrumentation

Recent technological advancements, coupled with the Internet’s widespread accessibility

and acceptability, have significantly simplified the collection of a broad range of data on

demographics, knowledge, attitudes, behaviors, and other constructs, allowing researchers to

connect with interviewees and respondents more rapidly and effortlessly than ever before (ElDen

et al., 2020). A study’s validity and reliability are crucial, with validity ensuring unbiased

observation of the phenomenon and reliability concerning the consistent reproducibility of

research findings (Haseski & ]li^c, 2019). Therefore, a researcher must ascertain the reliability

and validity of an instrument by verifying its successful application in previous studies with a

similar population, as initial usage of the instrument without such verification poses significant

challenges in reliability (Fagarasanu & Kumar, 2002).

Data symbolizes a systematic aggregation of information organized to allow for efficient

processing, analysis, and interpretation (Sharma, 2022). Instruments are essential tools that

empower researchers to systematically collect data on designated subjects or conduct in-depth

research in a specific area. For this study, the researcher employed semi-structured interviews

conducted through video conferencing software as the main instrument. The study selected this

method for its efficiency in obtaining detailed answers and data vital for tackling the research

questions within a grounded theory research design.

In grounded theory, data collection and analysis occur concurrently, with ongoing

analysis directing the inquiry’s trajectory, as emerging concepts in the generated data inform

decisions about where to seek additional data, from whom to collect it, and for what specific

purpose (Foley et al., 2021). Moreover, the quality of the interview instrument is crucial as the

conclusions drawn from the research depend on the information garnered from this instrument

(Gani et al., 2020). Thorogood and Green (2018) affirm that in qualitative studies, using

interviews as the instrument is a widely recognized approach, being the most frequently used

method for data collection. Therefore, the effectiveness of grounded theory research hinges on

the robustness and adaptability of the interview instrument, a critical tool that shapes the

research’s direction and extracts valuable insights from the data.

Pilot Testing

To ensure any data collection model functions optimally, conducting a pilot test evaluates

the instruments’ efficiency, assesses the application of the questionnaires or interviews, and

anticipates potential failures (Pinto et al., 2023). Grounded theory, through its open-ended

questioning approach, enables the establishment of detailed responses while uncovering new,

previously unexplored information, thereby facilitating a comprehensive understanding of the

subject matter. The researcher conducted a pilot test with a select group of participants in a

controlled testing environment in order to assess the effectiveness of the initial base questions

and determine the need for additional queries to encourage interviewees to discuss more details

(see Appendix C). The base questions created an environment where the interviewee could

elaborate, enabling the researcher to pursue new lines of inquiry and unearth additional data. An

invitation letter for the pilot study’s participants (see Appendix C), accompanied by a consent

letter (see Appendix C) outlining their rights and responsibilities, was sent to two individuals.

These individuals were distinct from the main study participants to ensure a separation between

test and actual research data from the main study in case modifications to the baseline questions

were necessary. Additionally, the researcher obtained Institutional Review Board (IRB) approval

for the pilot study before commencing.

Data Collection

Data collection is a methodical process to gather essential information to address specific

research questions, resolve research issues, or establish grounds for either confirming or refuting

research hypotheses (Mwita, 2022b). Moreover, data collection is a crucial aspect of qualitative

research, which benefits from employing multiple sources to enhance the study’s data credibility

(Rivaz et al., 2019). Technological advancements have made qualitative data collection and

instrumentation use more accessible and functional through Internet-based communications

(Rivaz et al., 2019). Integrating technology in data collection practices streamlines the process

and enriches the depth and scope of qualitative research, leading to more comprehensive and

insightful findings.

The researcher did not commence data collection until the Institutional Review Board

(IRB) approved both the initial pilot study and, subsequently, the main study’s research.

Instrumentation for the study were interviews conducted using Microsoft Teams, Zoom, or

Google Meet with video and audio enabled. Audio parts of the record were transcribed using

transcription software and checked for inaccuracies by the researcher. Interviews were between

45 and 60 minutes, occurring within a six-week consecutive block. Participants received

individual invitation letters and informed consent forms via email, specific to either the pilot

study or the main study. The letter detailed the study’s purpose, interview procedures, methods of

data collection, and the protocols for recording and storing the data.

In qualitative research, member checking, also called participant feedback or validation,

is increasingly considered essential by editors, peer reviewers, and dissertation advisors for

ensuring validity and trustworthiness, as it involves researchers obtaining feedback from their

participants or stakeholders on their data and interpretations (Motulsky, 2021). In this study, the

researcher first verified that the audio recording aligned with the written transcript and then

emailed the text transcript to the interviewees to identify any discrepancies as part of member

checking. This method ensures the accurate recording of factual data and assists in coding

theories derived from the data in factual evidence.

Conducting interviews presents several challenges, problems, and roadblocks the study

must identify, reduce, and overcome. Libaque-Sáenz et al. (2021) state that privacy concerns

represent the most significant obstacle to data and pose critical challenges for ethical business

practices, particularly regarding the processing, storage, sharing, and usage of consumers’ data.

The researcher illustrated the handling of all recorded data to the participants, yet interviewees

might feel uneasy divulging specific details about the questioning, potentially leading to their

withdrawal from the study during the interview or later. Additionally, external workplace politics

beyond the interviewee’s control may limit participation or prohibit responses owing to privacy

or confidentiality concerns.

Another issue in data collection is the inherent bias stemming from the selection of

interviewees as sources. In this instance, bias is a systematic error in sampling or testing due to a

deliberate or inadvertent preference for specific outcomes or responses, where the crucial aspect

is accuracy, notably when the recorded value deviates from the actual one (Hassenstein &

Vanella, 2022). Methods described in Chapter 1 regarding the radar graph provided standardized

evaluation criteria to reduce selection bias. Implementing these methods is essential to enhance

the reliability and validity of the data, ensuring a more accurate reflection of blockchain usage

within Australia.

Ensuring a consistent quality of the collected data is essential to prevent it from becoming

problematic. To counteract critiques regarding the lack of rigor in qualitative descriptive studies,

researchers must consistently maintain rigor by adopting various strategies that integrate

principles of credibility, criticality, authenticity, and integrity (Turale, 2020). Best practice

methods in qualitative research, aimed at enhancing rigor and trustworthiness, encompass clear

justifications for sampling design decisions, ascertaining data saturation, adherence to ethical

research design, member checking, sustained engagement and continuous observation of

participants, and triangulation of data sources (Johnson et al., 2020). By diligently implementing

these best practices, the researcher will uphold the integrity of the study and ensure that the

insights derived are credible and valuable.

Data collection for this study focused entirely on one-on-one interviews with industry

experts and academics within the Australian blockchain community. The interviews aimed to

investigate the experiences, perspectives, opinions, ideas, beliefs, and motivations of entities or

individuals regarding specific objects, issues, or phenomena (Islam & Aldaihani, 2022). The

grounded theory research method, aiming to yield specific clarification, integrates data collection

about a phenomenon’s effect on a condition, the resulting interactions, and the ensuing

consequences to formulate theories and conclusions without generalizing (Lianto, 2019).

Additionally, the research questions ask the phrases “What regulatory obstacles?”, “What are the

risks?” and “What is the best approach?” allowing candidness in the data collection process. The

scope of the questions enables interviewees to impart their professional experiences and

knowledge of the topic of blockchain, thereby justifying and validating the choice of a grounded

theory research design.

The collected data is in a digital format, without physical or external media; notes were

typed and stored securely in a location accessible only through the researcher’s password and

biometrically protected personal computer. In addition, this data was synchronized and backed up

to the researcher’s personal Google Cloud account, which is protected by two-factor

authentication, while confirming that the version control of documents is not enabled, ensuring

data has been saved and shrubbed of personal identifying information. Each interviewee’s data

was de-identified and assigned a sequential number for reference. All de-identified recorded data

may be accessible for up to five years.

Data Analysis

Qualitative data analysis, a multifaceted and iterative process, necessitates significant

engagement from researchers in reading, thinking, and reflecting on deciphering meanings and

systematically involves coding, categorizing, and theme development while emphasizing the

accurate representation of participants’ accounts (Ravindran, 2019). Within this study, the

researcher collected data using three methods: video and audio recordings through the video

conference software, transcriptions of the audio component of the interview, and notes taken by

the researcher during the interview. The study centers around a grounded theory approach that

can illuminate previously concealed cause-and-effect relationships between themes (Snodgrass et

al., 2020). Moreover, this research design enables the data to convey the narrative, allowing the

researcher to determine findings and conclusions. The researcher will analyze the data to identify

emerging trends or patterns, which may manifest as diverse points of view, directions of

responses, identification of problems, and areas of interest. This methodical and reflective

approach to qualitative data analysis will provide a rich, nuanced understanding of the subject

matter, uncovering layers of insights and perspectives that would otherwise remain hidden.

Descriptive Statistics

Descriptive statistics comprise central tendency, variability, and distribution, with central

tendency measures as the primary components for data analysis, creating graphs, and grasping

the distribution concept (Chan et al., 2016). While this study is qualitative, descriptive statistics

organize and summarize data by delineating the relationships among variables within a sample or

population (Kaur et al., 2018). After the Institutional Review Board (IRB) approval and the

primary interviews commenced, the researcher compiled statistical data, encompassing factors

such as sex, age range, industry or academic field, and area of blockchain experience. It is also

conceivable that new descriptive statistics may emerge as interviews progress, ultimately proving

valuable to the findings.

Coding

Coding represents a crucial structural process in qualitative research, facilitating data

analysis and subsequent steps to fulfill the study’s objectives (Williams & Moser, 2019). It is

essential for analysis as it establishes foundational blocks that require validation to reduce

researcher bias by justifying phrase selection, enabling inter-rater comparisons, and grouping

codes into themes for review and potential subdivision (Jnanathapaswi, 2021). The study uses

interviews as its primary instrument and conducted coding in three stages. First, coding occurred

for each interview after recording to identify unique patterns and trends from the individual

interview. Second, a collective analysis of interviews compared to those already completed to

identify emerging trends or data, guiding future interviews. Lastly, coding was applied to the

complete dataset once all interviews were conducted.

When coding open-ended responses through a standard codebook, there is a risk of biased

outcomes and semantic validity issues, as this approach may misinterpret respondents’ intended

statements, leading to a misrepresentation of the actual opinions of a significant, non-random

portion of the sample (Glazier et al., 2021). The research employs three stages of coding to

counteract this unintended bias: open coding, axial coding, and selective coding.

Open Coding

In the open coding phase of data analysis, data is dissected into smaller segments for

detailed examination, aiming to identify and conceptualize core ideas within each segment,

thereby categorizing phenomena and creating descriptive codes that encapsulate the essence of

these segments (Vollstedt & Rezat, 2019). This process also involves constantly comparing these

segments and their associated codes to ensure consistency and to uncover underlying themes and

variations within the data.

Axial Coding

Axial coding re-establishes connections among categories, encompassing conditions,

context, reasons, causes, and effects, compiled based on each category’s criteria and

subcategories (Lianto, 2019). This stage further involves refining these connections to construct a

more complex and nuanced understanding of the data, thereby facilitating the development of a

more comprehensive and integrated theoretical model.

Selective Coding

Selective coding in qualitative research aims to synthesize and validate the diverse

categories previously developed and interlinked in the axial coding phase, thereby constructing a

unified and cohesive theoretical framework from these elaborated results (Vollstedt & Rezat,

2019). In this final stage, the researcher focuses on identifying core categories that represent the

central theme of the data, integrating all other categories to form a well-rounded and

substantiated narrative or theory.

Through the integrated use of open, axial, and selective coding, this research

methodically dissects, reconnects, and synthesizes data from instrumental interviews, thereby

systematically transforming it into a coherent, evidence-based theory that accurately reflects the

studied phenomena.

Coding Software

Computer-Assisted Qualitative Data Analysis Software (CAQDAS) enhances qualitative

research by integrating diverse data and coding methods through synchronizing transcripts with

audio and video for a multimodal representation and while synchronizing annotations, memos,

and codes with interview transcripts to enhance reflexivity, improve analysis rigor, and

credibility (Craig et al., 2021). This study utilized CAQDAS software to assist with data coding

and analysis. The software selected for this study to aid in coding strategy was ATLAS.ti

("ATLAS.ti," 2024). ATLAS.ti emerged as the preferred choice due to its comprehensive

features, compatibility with various computer platforms, available support, and favorable student

pricing options. The researcher purchased a student six-month subscription to the full paid

version to aid coding for this study. The selection process of comparable software also

considered other packages, such as CDC EZ-Text and QDA Miner, but ultimately found them

unsuitable due to their lack of updates, limited features, or prohibitive student pricing.

Triangulation

Triangulation enhances research credibility and validity, where credibility signifies the

study’s trustworthiness and believability, and validity pertains to the accurate reflection or

evaluation of the investigated concepts or ideas (Noble & Heale, 2019). Moreover, triangulation

allows researchers to gain a more comprehensive and deeper understanding of the phenomenon

under investigation (Jentoft & Olsen, 2019). Data source triangulation prioritizes gathering data

from multiple sources within a single collection method to obtain a more comprehensive

perspective (Moon, 2019). The study’s use of interviews, participant qualification methods, and

coding structures allows the researcher to gather data from multiple sources within an industry,

thereby achieving substantial triangulation in data collection.

Triangulation, when employed for completeness in researching lesser-explored problems,

offers a key advantage in the qualitative research paradigm by generating rich data that can aid

researchers (Hussein, 2009). Furthermore, it allows scholars to enhance their research and

advance knowledge by adding depth and complexity to their investigations, surpassing the

pursuit of a purely objective account of reality (Aguilar Solano, 2020). The inherent flexibility of

grounded theory, which accommodates emerging concepts, synergistically complements the

triangulation method, as both methodologies prioritize the assimilation of data from diverse

sources, thereby collaboratively facilitating the triangulation of results for a more robust and

empirically validated conclusion.

Data triangulation through interviews in qualitative inquiry may lead to a more

comprehensive understanding of the phenomenon of interest. However, relying solely on one

method could exclude eligible participants and reduce the breadth of results by providing only

partial insight into the phenomenon (Carter et al., 2014). The strategic application of

triangulation in research fortifies the integrity and depth of qualitative inquiries and significantly

broadens the scope and richness of the findings, ensuring a more nuanced and holistic

understanding of the studied phenomena.

Informed Consent Process and Ethical Concerns

In qualitative research, most ethical issues are intrinsically linked to the initiation,

maintenance, and conclusion of research relationships, often emerging during the preparatory

phase, underscoring the importance of ethical conduct in upholding these relationships (Kang &

Hwang, 2021). Prior to starting data collection, the researcher informed interviewees about the

purpose and methods of data collection and analysis through an email invitation, emphasizing

that participation is voluntary and can be discontinued at any time without repercussions. The

interviewees were informed of the methods of maintaining their confidentiality and privacy as

per the consent form (see Appendix D). Before research began, the study obtained the necessary

human research ethics approval from the Institutional Review Board (IRB).

Informed Consent

All participants received an informed consent form as a PDF attachment via email, with

the option to use written or digital signatures, eliminating the need for a separate form and

ensuring easy completion for each interview. Participants were provided with the researcher’s

valid email address and phone number, enabling them to ask questions at any stage of the

interview process and access the results of the inquiry. The interview data was anonymized,

devoid of any identifying marks related to the participant, and protected identifiers pertaining to

institutions, participants, or collaborative efforts. Identifying information was not recorded in the

final data, and any such information obtained during the interviews was scrubbed and removed

from the record. Interviewees were designated using a numerical system, for example,

interviewee 1 and interviewee 2. No contact information, names, email addresses, or other

identification marks were retained in a publicly accessible format, and no identifying phrases

were included in the data to ensure privacy during the interview process.

Site Permissions

The study was conducted exclusively online, utilizing video conferencing recording and

software, thereby obviating the need for site permissions.

Ethical Concerns

In research, ethics pertain to the norms and values that direct decisions related to data

collection, analysis, and dissemination of findings (Mirza et al., 2023). However, researchers

must recognize that ethical decision-making varies among individuals, who differ in their

approaches, information considered, and decision-making rules (Nneoma et al., 2023).

Researchers must consider diverse viewpoints and follow governing principles to remove ethical

concerns. "Universal Declaration of Ethical Principles for Psychologists" (2008) states that the

four levels of ethical principles are respect for the dignity of persons and people, competent

caring for the well-being of persons and peoples, integrity, and professional and scientific

responsibilities to society. When applied to research, Mirza et al. (2023) state that ethical

principles to consider are ethics of respect, the relationship with participants and conflict of

interest, informed consent, incentives, confidentiality and anonymity, reporting back to the

participants, trustworthiness of research, and issues of translation. These principles shape the

ethical conduct of researchers, ensuring responsible and respectful handling of data throughout

its collection, analysis, and reporting.

The study’s pilot and main interview processes rely entirely on voluntary participation,

reflecting the human subject’s ability to exercise free will in deciding whether to participate.

Moreover, ensuring the study’s integrity requires balancing voluntary participation and the

potential impact of inducements on autonomous decision-making. Inducement can arise when an

individual faces incentives that impair their capacity for autonomous decision-making (Millum &

Garnett, 2019). At any time, the interviewee can stop and withdraw from the interview for any

reason. Participants can refrain from responding if they do not wish to answer a question or

cannot elaborate, providing respect for their privacy. Furthermore, the absence of financial

incentives or opportunities for notoriety due to the anonymity of participants ensures that these

factors do not influence interviewees to include or exclude any aspects of their responses.

After deidentifying the data and publishing the future study, the collection and analysis of

this deidentified data, by definition, do not fall under the category of human subjects research.

Consequently, such activities are not subject to the regulations of the Common Rule (Crystal et

al., 2020). During the data collection stage, data will be deidentified immediately after the

interview and scrubbed of any metadata to uphold confidentiality, anonymity, and privacy

concerns. Furthermore, by sending the informed consent document to participants before starting

the interview, the study demonstrates an approach that focuses on understanding and

implementing respect for the individuals involved. Moreover, the research requirements, not

convenience, determined the criteria for selecting participants. The study established specific

inclusion and exclusion criteria to ensure fairness in the selection process, as detailed in the

population and sample section within this Chapter 3. These criteria aimed at providing equal

opportunities for all participants.

Trustworthiness of the Study

Qualitative content analysis frequently establishes its trustworthiness through criteria

including credibility, dependability, conformability, transferability, and authenticity (Kyngäs et

al., 2020). These methods encompass prolonged engagement with subjects, continuous

observation, ensuring referential adequacy, member checking for validation, employing

triangulation, analyzing negative cases, providing detailed contextual descriptions, conducting

external audits or maintaining an audit trail, and practicing reflexivity and transparency (Amin et

al., 2020). Additionally, qualitative inquiry commonly relies on the researcher’s reflexivity,

underscoring that experiences and data span multiple realities, including the researcher’s, thereby

situating data interpretation and theory development partially within the researcher’s perspectives

in contextual situations (Shufutinsky, 2020).

This study systematically addresses considerations for these cases by employing various

methodologies and approaches. A systematic and transparent literature review has been written to

bolster credibility and offer valuable guidance for future research, necessitating not only an

organized design and sound execution but also a straightforward elucidation of the methods

employed (Cram et al., 2020). Research design centered around rigor is essential from the

beginning of the study, forming the foundation of the early stages of its design (Stratford &

Bradshaw, 2021). The study implements a rigorous radar graph selection process to validate

participants’ effectiveness in contributing data. The study focuses on interviews as the primary

instrumentation method and will conduct a pilot test to assess the base questions and their

effectiveness in eliciting responses from interviewees.

This chapter here outlines the minimization of researcher bias, achieved through three

coding stages. The study methodically analyzes trends and data patterns at different interview

stages: individually, collectively, and continuously. This method acknowledges the potential for

researcher bias and effectively reduces it. This study attempts to embody repeatability,

replication, and trustworthiness in qualitative research through its research design, selected

methodologies, and bias minimization strategies.

Summary

In Chapter 3, the study’s grounded theory research design and methodology are outlined,

along with an examination of how that applies to the research questions, population and sample,

the researcher’s role, methods of data collection, and the research instrument employed. This

chapter also addresses ethical considerations and quality assurance measures pertinent to data

collection while affirming the study’s trustworthiness centered around blockchain within

Australia. Chapter 4 will present the data and findings derived from the interviews. The pairing

of the research methodology and the data analysis is crucial for moving toward answering the

research questions. Chapter 5 will amalgamate the insights from the literature review and the

research findings. This final chapter aims to conclude the study, offering reflections,

recommendations, and charting pathways for subsequent research.

Chapter 4: Findings

Chapter 4 presents the data collected for this study. This qualitative grounded theory

research focuses on consumer trust in blockchain implementation and its impact on the

information services industries in Australia. The researcher interviewed eleven Australian

professional or academic blockchain experts, ultimately excluding one, in the data collection

process. Data was gathered through instrumentation from in-depth interviews, enriching the

study’s literature review of previous work and scholarly articles in the blockchain industry. The

base questions were the initial line of inquiry for the interview process, adding additional

questions based on the interviewees’ responses or insights from previous interviews, generating

broad and descriptive examples from all collected data. The study systematically captured and

coded these elements using the ATLAS.ti software suite to pinpoint common themes, focusing on

addressing the research questions. Themes that emerged from coding the interviews included the

influence of decentralization, efficiency, user experience, and leadership within business

practices; the presence of skepticism and distrust as significant challenges; evolving technology

trends; privacy concerns and secrecy shaping the digital landscape; and the crucial roles of clarity

and supportive structures in providing support (see Appendix A4).

General Description of Participants

In this grounded theory study, interviewees who consented to participate and were

subsequently selected had an average age of 45.1 years, comprising 90% male and 10% female.

Of all the participants selected to be interviewed, only one was ultimately disqualified for not

having enough years of experience and failed to achieve a sufficient score on the qualification

test using the radar chart method outlined in Chapter 3 (see Figure B4). The age range of

participants ranged from 30 to 57 years. Regarding their professional backgrounds, 10%

selfidentified as academic professionals, 60% as professionals, and 30% as both. Table A1

presents the count of full-time job titles for all participants regardless of whether they identified

as professional or academic, outlining the diversity and experience when providing feedback to

questions. In terms of educational attainment, 10% did not possess any formal tertiary degree,

30% held a bachelor’s degree, 30% held a master’s degree, and 30% had earned a Ph.D. or

higher in a relevant field. Concerning experience in the Australian blockchain industry, 100% of

the professional experts selected in this study had over five years of experience in the sector.

State names are used further to anonymize the participants, especially those from smaller cities,

revealing that participants came from the Australian states of New South Wales, Queensland, and

Victoria.

Unit of Analysis and Measurement

In this qualitative grounded theory research study, the interviews served as the unit of

analysis. Each interview commenced with base questions (see Appendix C) that prompted

participants to provide detailed responses. Further probing questions, tailored to the participant’s

responses and insights from earlier interviews, supplemented the interviews. Throughout this

process, several themes and patterns surfaced, enabling the collection of more intricate data.

Recurring statements, examples, and trends within these interviews allowed for their

reconfirmation in subsequent interviews with other participants, thus further substantiating the

data and confirming data saturation. The unit of measurement in this qualitative grounded theory

study were codes, themes, and sub-themes generated from the transcripts and notes taken during

the interviews, which were meant to address the research questions.

Sample Size

The recruitment of interviewees was exclusively carried out on the LinkedIn platform to

assess qualifications via individual profiles. Seventy-eight invitations were sent directly to

individuals via private message who either maintained a first-degree connection with the author

or were contacted through the platform’s paid Premium InMail service, targeting those who

seemed qualified to participate based on their profile and qualifications. The author sought to

involve professional leaders and academics but found that most had limited time availability.

Given the lengthy nature of the formal invitation and the time required to read such a long

message, an adjustment was made to the initial contact approach. As the first contact, a short

message of interest (see Appendix G) was sent, asking about their willingness to participate and

proposing to send them the detailed invitation along with the consent form via email if they were.

This method allowed potential participants to quickly understand the nature of the request and

respond with a short reply indicating their acceptance to receive a formal invite or decline. This

revised strategy markedly increased engagement, eliciting a more significant interest level from

potential participants. Moreover, the multi-stage invitation approach allowed the study to receive

high-quality Australian-based participants, including C-level professionals and top university

professors, as outlined in Table A1.

The quality of the sample, and consequently the data collected, was considered

acceptable, as the radar graph demonstrated a sufficient breadth across all areas for each

participant regarding evaluating criteria such as technical understanding, familiarity with

government and regulatory frameworks, theoretical knowledge, and financial expertise. The

sample size was sufficiently large, engaging enough participants to achieve research saturation

when responses to questions and discussions exhibited similarity. The consistency of the

participants’ responses underscored the robustness and reliability of the findings, affirming the

adequacy of the sample size and the breadth of the data collected.

Pilot Testing

A pilot test was conducted to assess the effectiveness of the baseline questions (see

Appendix C) in eliciting further discussions and elaborations. Interviewees 1 and 2 participated

in the pilot test; both were academics with master’s degrees and held professional senior

leadership positions. The objective of the pilot test was not to obtain direct answers to the

questions but to determine if the questions would prompt further discussions and lead to

subsequent knowledge transfer in future interviews. Both subjects of the pilot test stated that the

questions were general in nature and anticipated that further questions would stem from these

initial queries, which aligns with the desired outcome of the grounded theory study (see

Appendix H1 to H2). Additionally, the pilot test evaluated the efficiency of using video

conferencing software to facilitate interviews as an instrument and its transcription functionality,

focusing on recent advancements in Microsoft Teams for audio transcription and the generation

of time-coded WebVTT transcription files. This evaluation with the pilot test’s subjects affirmed

that utilizing Teams and the university’s login credentials was an efficient tool for recording and

transcribing interviews. This approach enhanced the study’s credibility because the researcher

sent invitations from a university email address and conducted the interviews on the university’s

Teams account. Furthermore, the coding software suite ATLAS.ti can directly import WebVTT

transcription files and videos, thus streamlining the coding process and developing themes. As a

result, Microsoft Teams was chosen and utilized to conduct all interviews within the main study.

Data Collection

Data collection commenced after obtaining Institutional Review Board (IRB) approvals

(see Appendix F). Data collection occurred through interviews, serving as the primary

instrument, conducted solely via the university-provided Microsoft Teams account, which offers

audio transcription capabilities. The study suggested and approved a six-week window for

conducting all interviews but reached data saturation in just four weeks. Owing to the complexity

of arranging interviews, which involves securing a date for the interview and signing the consent

form across multiple applicants and considering that these applicants could be at any stage of the

interview setup process, a matrix was developed to monitor the current status and dates to ensure

nothing was missed.

The researcher conducted eleven interviews, selecting ten for the study and rejecting one,

with each interview averaging 43 minutes. The shortest interview lasted 27 minutes, and the

longest lasted 64 minutes, with Table B2 documenting the total data collected. At each

interview’s start, the researcher confirmed that they had received the interviewee’s signed

consent form and explained that the session would be recorded. Before initiating the recording,

the interviewer explained the study’s grounded theory approach and clarified the general nature

of the base questions, encouraging interviewees to elaborate or explore topics in-depth, a process

one interviewee described as “going down information rabbit holes”. The interviewees were

instructed that although they could guide the conversation in answering the questions, the study

specifically focuses on blockchain technology, not cryptocurrencies.

Lastly, a crucial factor communicated to participants was the need for the interview to

remain neutral and unbiased. The researcher explained that they would maintain a “poker face”,

merely nodding to acknowledge understanding of the statements without showing emotion,

neither agreeing nor disagreeing with the replies nor offering their perspective or insights.

Furthermore, the researcher committed not to finish the participants’ sentences, interrupt them, or

stop them from talking at any point. Upon completing the interview, the researcher downloaded

the video recordings and generated and downloaded the transcriptions. As a final step, the

researcher emailed the interviewee a Microsoft Word version of the transcript for confirmation.

The researcher saved all data files following the methods outlined in Chapter 3.

Codebook Creation

The researcher created a codebook to facilitate the capture of qualitative data, which will

be considered and reviewed in the data analysis section of the study. During the study, the

researcher documented relevant data, patterns, verbiage, and examples that interviewees shared

during the interview process in the codebook. This codebook was a reference for the researcher

to notate and document insights throughout these interviews. Moreover, it acted as a continual

resource during the data analysis phase. The researcher employed two methods for data analysis:

grouping based on the frequency of word usage (see Figure B9) and codifying codes and themes

(see Table A4), both derived from the researcher’s handwritten notes. Subsequently, the analysis

utilized the ATLAS.ti software suite for examining these grouped and codified elements. A word

count can provide a snapshot of frequently mentioned topics in the interviews, but it may not

fully capture conversational meaning due to the nuances of natural human speech, where, for

example, a subject might refer to a topic in a sentence as “it is.” The codification of codes and

themes considers meaning, and both methods were employed throughout the interviews to

identify emerging themes and data topics.

The data analysis via word count set parameters with a threshold of seven occurrences for

inclusion in the analysis and established 130 as the maximum frequency of any word across all

notes. Furthermore, the researcher created a stop-and-go list that omits commonly used and

function words, which, although essential for constructing sentences, lack meaningful content

within the study. This list (see Table A3) enhances the study’s findings’ replicability by indicating

the words omitted. Using these parameters, the researcher generated a word cloud of 116 unique

words, as shown in Figure B9. While removing the apparent word of Blockchain from the word

cloud, other frequently used words were people, problem, government, Australia, trust,

technology, industry, security, and change. Recurring blockchain concepts pertinent to the study

and research questions include education, decentralization, knowledge, change, consensus,

complexity, and significance.

In the grounded theory data collection process of interviews, creating the codebook

facilitated the identification of new lines of questioning, encouraging interviewees to provide

elaborations or contributions to evolving codes or themes. Following data collection, analysis,

and coding, a comprehensive list of codes, axial codes, and themes emerged, as detailed in Table

A4. Furthermore, the researcher achieved data saturation after conducting interviews with eight

participants but consistently pursued additional interviews, thereby enhancing the qualitative

depth of the study with more comprehensive insights. This approach of intertwining data

collection with analysis of questions and continuous refinement of the codebook ensured the

research dynamically adapted to emerging insights, ultimately enhancing the depth and richness

of the qualitative findings presented.

Qualitative Results

The researcher collated all handwritten notes, transcriptions, and responses acquired

during the interview timeframe and analyzed the data using qualitative grounded theory coding

methods to substantiate the results. The study aimed to assess blockchain application and usage

within Australia’s information services industry and identify any prevailing issues or problems

necessitating solutions to ensure Australia keeps pace with the rest of the world. The interviews

targeted data collection processes involving ten selected blockchain professionals or academic

participants to garner a comprehensive understanding of the nuances and complexities within the

Australian blockchain ecosystem. The objective of the interviews was not to gather personal or

individual real-life experiences but to acquire substantial data through the interviewees’

expertise, ultimately aiming to address the research questions. This strategic approach ensured

that the research could yield insightful and significant findings pertinent to the dynamics and

intricacies of the Australian blockchain ecosystem, thereby effectively addressing the research

questions posed.

Grounded theory aims to construct or uncover theory from data obtained and analyzed

systematically using comparative analysis (Chun Tie et al., 2019). Ensuring high-quality data

acquisition necessitated confirming that participants possessed essential expertise for addressing

inquiries, a process achieved by compiling skill-based radar graphs for each interviewee (see

Figures B10 to B19). Additionally, achieving data saturation was crucial to guarantee that the

collected data was sufficient for thorough validation (Hennink & Kaiser, 2022). In support of this

approach, a comprehensive literature review further validates the identified codes, themes, and

their correlating connections, thereby strengthening the methodological framework of the

research.

The multifaceted nature of blockchain technology and the researcher’s bias mitigation

strategy of not interrupting the interviewees enabled the dialogues to initiate in one thematic area

but possibly evolve into another. All topics and themes, even those considered off-topic or

unrelated to blockchain, were codified but not included in the final codification lists. After

coding, the most significant codes identified were business, challenges, technology trends, digital

landscape, and support as applied to the research questions. Each of these codes generated

themes or axial codes, as shown in Table A4 and discussed in this chapter.

Research Question 1 (RQ1): What are the key regulatory challenges hindering the

implementation of blockchain technology in Australia’s information services industries?

RQ1 – Theme 1: Challenges - Skepticism and Distrust

Interviewees openly expressed areas of public sentiment of distrust and skepticism

towards the blockchain industry. Many highlighted the industry’s rapid growth and pace, which,

in their view, creates a technical barrier to entry, emphasizing that people fear what they do not

understand. Each interviewee recounted stories of computer hacking, scams, or money

laundering issues, pointing out that news outlets and media often amplify these stories, instilling

fear around the technology. Several interviewees discussed bad actors within the industry who

launched ambitious projects and gathered investment without developing a product or service,

often lacking the necessary skills or team to deliver it. The participants observed that the

blockchain industry attracts individuals who have a fear of missing out or “FOMO,” leading to

hasty investments and a loss of money. Interviewee 3 comments on this phenomenon, stating,

“(the blockchain industry) has a bad reputation, there are a lot of scams and tech vectors, (along

with the) frequency of these events and in the news, mostly from the US”. However, Interviewee

11 maintained a positive outlook on the technology but warned of customer data privacy issues,

stating, “(blockchain is) generally revolutionary. (It) solves many issues; (but) in Australia, we

have privacy issues, loss of data, for example, the Optus hacks.” Referring to the 2023 incident

where unknown computer hackers stole millions of customer information from one of Australia’s

largest telecommunications companies. Interviewee 11 had a more direct comment concerning

businesses’ perspective of blockchain, saying, “People do not change their minds (about

blockchain); it will take something external to make this happen.” Both professional and

academic blockchain experts commented on the importance of education in the field but

expressed uncertainty about the best method to implement it.

RQ1 – Theme 2: Challenges - Disappointment and Incompetence

Interview participants frequently mentioned blockchain’s initial promise and

“buzzwordyness” several years ago, only for it to be implemented incorrectly, technically scoped

inadequately, or never tested for product fit and ultimately failing. Interviewees highlighted a

significant knowledge gap from theory to real-world implementation, noting that many

individuals in the industry have not kept up with technological advancements and are discussing

blockchain facts that are “over five years old” and no longer relevant. Interviewee 11 was

particularly vocal about having the wrong people in inappropriate positions and described a

clique of groups unwilling to collaborate, seeming to assist only their close friends. Interviewee

12 observed blockchain companies’ fragmented nature, noting that they sponsored community

events only when the discussions served their interests. Other participants shared stories of

blockchain projects characterized by excessive management and “project managers,” as well as a

shortage of qualified blockchain software developers capable of completing project work.

Interviewee 4 highlighted the abundance of technically capable blockchain developers but

emphasized the scarcity of those with the experience necessary to implement and maintain

blockchain systems securely and at scale effectively. Interviewee 7 summarizes this by saying,

“One of the problems is the people; there isn’t enough skilled people around the applied side of

blockchain.” Interviewee 7 noted the blockchain failure in management, saying, “(the company)

hiring people who were supposed to be professionals - but they didn’t really know what they

were doing.” Participants were careful to discuss the knowledge gap; interviewee 7 noted that

“(Blockchain) terminology needs to be upskilled at the C-suite level - they are not 18-year-old

kids. Managers/planners need to be upskilled.” Interview 10 mentioned, “There is a generation

gap; there are people aged 30 – 35 (who understand blockchain), and those who are older (who

do not). Some people don’t even know what blockchain is.”

RQ1 – Theme 3: Challenges - Risk Aversion

Technical and regulatory interviewees discussed the challenges of integrating legacy

systems with newer, modern blockchain systems. They mentioned the mentality of enterprise

businesses: “If it is not broken, why change it?” regarding the cost of integration and the

perceived lack of benefit. Interviewee 6 listed ways to make blockchain more accessible to

businesses and users, saying, “Public perception (of blockchain), (create blockchain) fit for

purpose, and the consolidation that might come with that. (In addition), working with the

traditional systems will lead to trust.” Several participants noted the recent shift in the Australian

government, observing that the ruling Labor Party is perceived as risk-averse and leans towards

traditionalism. They reported numerous blockchain initiatives, among many projects led under

the former Liberal Party, were seemingly paused for reevaluation. Interviewee 7 noted the

current blockchain climate when dealing with businesses: “There are people that know

(blockchain), and there are people that think they know (blockchain), then there are people who

are just scams.” Uncertainty emerged as a common thread among participants, where traditional

businesses and government shifts responded to public perception, favoring quick wins and what

was perceived as best for the community. On the other hand, blockchain companies operating in

legal grey areas of blockchain, where regulation has not caught up with technology or

uncertainty prevails, choose to operate silently to avoid risk. Interviewee 8 said, “Many people

are doing (blockchain) under the radar and building and not telling anyone, waiting until the

license information comes out.”

Research Question 2 (RQ2): How does the absence or inadequate implementation and

communication of blockchain data processes pose risks to Australia’s information services

industries?

RQ2 – Theme 1: Business - Decentralization and Efficiency

All interviewees remarked on blockchain implementation and decentralization, noting its

positive and negative aspects. Interviewee 10 addressed the communications issues in Australian

businesses: “From a user perspective, there is a lack of understanding; education is a problem.

People do not understand decentralization.” A recurring concept that touched on many aspects

throughout the interview was the importance of education and understanding what blockchain

can achieve. Several interviewees remarked that although blockchain tools are becoming more

accessible, the technical knowledge required to enter the blockchain field remains high. Less

technical interview participants commented from a traditional business view that decentralized

networks convey an image that companies cannot retain control over data or users within such

systems. Interviewee 10 mentions that businesses struggle to grasp the methods of implementing

blockchain, stating, “(implementing blockchain) seemed dangerous because it is implementing

centralized systems on decentralized platforms and anyone can use it and there are no barriers to

entry.”

All participants were professional or academic experts in blockchain and understood the

increased efficiencies blockchain could offer in Australia but felt it needed to be implemented

correctly. Interviewee 3 said, “Blockchains enable everyone to participate.” Interviewee 13

emphasized the opportunity of blockchain, stating, “(traditionally) Australia has been a long way

away, but technology data packets do not care that we are in Australia.” Frequently, interviewees

highlighted the opportunities available to Australia and others worldwide. Interviewee 10 noted

that Australia could risk being left behind because “the European Union is moving faster (in

blockchain) to regulate and ensure that things are progressing as well.” Participant 13 highlighted

global trends, stating, “Countries that suffer from much greater waste, shrinkage, corruption or

otherwise will be the material disadvantage to those that are able to incorporate (blockchain)

technology that makes them more efficient in what they are doing.” Furthermore, the interviewee

highlighted, “Lowering the costs associated with the transfer of data packets, having greater

success in eliminating requirements for things like privacy.” This trend continued with

interviewee 13 stating, “(blockchain has) all sorts of untold opportunities in the development of

this technology.” Interviewee 10 stated, “The challenges for blockchain providers are efficiency,

reliability, and user interfaces.”

RQ2 – Theme 2: Business - User Experience

All interviewees noted that marketability and ease of use underpin everything on the

internet, and blockchain technology is no exception. Participant 12 said, “(users) have this

assumption when they go into a user interface because the way that a user interacts with a lot of

these protocols is through their wallet, they connect it, and then it has a user interface.” All

participants commented that blockchain tools are becoming more accessible; for example, simple

tools, including websites, enable the creation of wallets with just a button. Interviewee 8 reported

that even creating a new blockchain network has been simplified to simply pushing a button

through specialized and dedicated web services. However, interviewee 8 warned, “You cannot

just slap (blockchain) on something and it then will be a profound project that will solve the

world’s problems.” All participants agreed that the current blockchain user environment had

evolved significantly: whereas blockchain technology was heralded as a solution for various

technical projects five years ago, epitomized by marketing catchphrases such as “built on

blockchain,” contemporary consumer attitudes have shifted. Interviewee 11 commented that the

specifics of the underlying technology attract little concern from customers, “Blockchain is

backoffice technology. It is a type of database; for example, you don’t advertise your company is

importance of User Experience (UX), stating, “(Businesses) are building and no one cares as

long as the UX is good. The customers do not need or care it is blockchain”. Interviewee 10 also

agreed, stating, “People should not care about what is under the hood, and it is a big mistake to

present it usually as well.”

RQ2 – Theme 3: Business - Leadership and Communication

Communication, education, and expectations were frequently mentioned in interviews at

various levels, from government policy to business implementation, necessitating clear use cases,

governance, and guidance. Comments around blockchain technology that it is constantly

evolving, continually reinventing itself, finding applications in new areas, and undergoing

expansion. A “knowledge gap” was mentioned several times; interviewee 13 reasoned, “The

language is difficult in blockchain. But it is being created in real-time, it’s not meant to be hard,

but development has progressed quickly. It is being formed in real-time”. Interviewees pointed to

different areas where education is required, participant 7 noted, “The problem is it so hard to

upskill the schools and the teachers, and they don’t like to change because they cannot keep up

with the pace of emerging technologies.” When asked about obstacles surrounding businesses

using blockchain, interviewee 13 stated, “How do you explain (blockchain) to those who don’t

have tech backgrounds? Things need to be simpler for users”. They continued by stating that the

issue is twofold, saying, “If you are constantly trying to change the language to accommodate

someone’s level of understanding, you are on a road to nowhere.” Interviewee 7 warned of

regulatory oversite issues and double handling, stating “The Australian Bureau of Statistics and

Home Affairs are not communicating very well.”

Interviewees noted the change in policy from the government as within the last 12

months, Australia experienced a government change where the Labor Party replaced the Liberal

Party. Participant 13 mentioned, “The change of government meant there was a sort of revisiting

of many of the assumptions upon which the industry was being considered.” They reasoned that

“The new government transition was impacted by the fact that, much like the government that

just been put out of power, they have not a lot of domain experience.” Interviewee 11 pointed to

a similar issue, “The previous government was not that excited (about blockchain), and this

government is not that excited.” Interviewee 7 mentioned, “From an education side, I would say

right now it is the current government that’s a real problem.” Interviewee 9 stated, “With a fast

turnover of politicians, it is quite hard to educate them to address the shift in blockchain. For

example, the latest people in government are risk-averse and slow”. Interviewee 8 discussed how

uncertainty created an environment where Australian businesses are pausing their blockchain

projects, stating, “When there is uncertainty around (blockchain) or is our business going to need

a license even though we do not believe that our tokens are financial products. So, what has

happened is they have paused.”

RQ2 – Theme 4: Support - Clarity and Broad Statements

Uncertainty and lack of clarity commonly emerged as topics frequently mentioned

throughout the interviews. Interviewee 9 said, “We need to provide clarity because it is inhibiting

and stifling innovation and growth until we have that clarity.” In agreement, interviewee 8 said,

“There is apprehension about building because of the uncertainty, and that is a barrier.” Several

participants also discussed how Australia does not have the appropriate legal frameworks or

regulatory mechanisms in place. Participant 9 said, “You know where you have got very mobile

businesses (blockchain and people) that are moving to places that have greater clarity or are

attracting (those people).” Participant 9 continued, “I think because Australia does not have that

clarity, it is losing some very good talent.” Participants commented that generalization does not

help and mentioned the use of buzzwords and people who merely repeat them as a significant

contributing factor in building on blockchain. Interviewee 10 said, “It is not necessary that the

best technology succeeds or is adopted.” Several interviewees commented on the current trend of

using “Artificial Intelligence” (AI) as a buzzword, partially joking that attaching the word “AI”

to any project, governmental or otherwise, was often seemingly sufficient for project approval.

They observed that blockchain had also been the case several years ago. Interviewee 7 spoke

about “light papers” instead of “white papers,” describing how buzzwords seemingly approved

budgets. They explained, “People just jump on the bandwagon of throwing in the word Bitcoin

or metaverse, or you know any NFTs or whatever the buzzword happens to be that week, and

then when you read their white paper or their light paper, you can see the holes in it.”

RQ2 – Theme 5: Support - Supportive

Support was divided, with participants noting that blockchain communities provided

positive support while state or Australian governments demonstrated a seeming absence of

support, with participants frequently noting that the change in government was a potential

catalyst. Interviewee 12 said, “People, through social media or whatever means on the Internet,

shared consensus on information.” Interviewee 4 commented, “From my point of view, I think

the communities play a vital role in blockchain adoption and utilization because there are a lot,

even the blockchain for Bitcoin itself, was created basically as a discussion in a community.”

Interviewee 8 gave an example of community support, saying, “Blockchain is accessible in the

way that if you have an idea and you want to build on a blockchain, you go out and look for (the

blockchain you want to build on), and you let (that community) know that you are keen to build

on their blockchain and they will welcome you with open arms and give you the support that you

need because it benefits everyone.” Conversations nearly always highlighted a seeming lack of

support from the government and, consequently, from businesses, with Interviewee 13

commenting, “Australia is not a fast follower because we do not tend to follow people who move

quickly.” They continued, saying, ”(Australia) waits for the US, and we wait for the UK to see

what they do, which is probable and not without some common sense.” Interviewee 11

commented on some reasoning behind this, stating, “(Blockchain) is an industry in the process of

scaling, and that creates all sorts of sometimes quite tedious logistical challenges when people

are trying to implement applications.”

Research Question 3 (RQ3): What challenges do businesses face in understanding and

accepting blockchain systems, and how can these challenges be effectively addressed?

RQ3 – Theme 1: Technology Trends - Technological Advancements

Blockchain is a digital technology all participants understand has advanced and improved

significantly over the past 10 years. Many commented that blockchains now handle transactions

per second faster than most traditional credit card companies. Interviewee 8 commented that

blockchain is “a foundational technology,” interviewee 11 described blockchain as “a backoffice

technology gone through hype cycles.” Participant 9 mentioned that businesses “should be

encouraging the use of the technology, not scared of it because most of the rules that we already

have (for financial and privacy regulation) apply.” When discussing technological advancements,

interviewee 3 said, “Everything is going to be ultimately digitalized. However, what we need to

solve is for privacy.” Participant 12 talked about the future of blockchain, saying, “When we get

zero-knowledge proof technology, it becomes super important to marry off-chain data into

blockchain machine-readable sets like strings and sets.” Interviewee 11 articulated the future of

blockchain, stating, “(blockchain) does new things, and we are going to see more and more

applications just built into our day-to-day lives.”

RQ3 – Theme 2: Technology Trends - Industry Trends and Technological Enthusiasm

The interviewees noted blockchain trends of convenience, speed, and convergence. Many

expressed that blockchain will blend into existing systems as a tool, not a primary function.

Regarding blockchain trends, Participant 13 said, “(Blockchain is) for me faster, cheaper, more

accessible.” When asked about the placement of those trends, they stated, “Emerging economies

are very well placed to take advantage of at least part of the development of this tech stack.”

Interviewee 11 commented, “(Blockchain) provides international trend trading, and I would

argue that we have got a huge range of killer (blockchain) apps.” Interviewee 10 commented on

that trend: “(Blockchain) will continue to be useful for formal verification or zero knowledge

work outside of the blockchain industry.” Interviewee 12 remarked, “I think that the next wave,

and this is going to be a result of the main coin push in one direction, in my opinion, is people

are going to become more comfortable holding tokens of which they do not have a value that is

associated to a dollar value.”

RQ3 – Theme 3: Digital Landscape - Privacy Concerns and Secrecy

Privacy concerns dominated the conversations during the interviews. The discussion of

newer blockchain zero-knowledge proof (ZKPs) concepts in the technical interviews received a

positive reaction. The topic discussion evoked excitement among some technically minded

interviewees as they discussed the concept. Conversely, non-technical participants raised privacy

concerns, indicating that solving these issues may require more time and more mature solutions.

Interviewee 8 said, “Privacy and security are the highest priority in the digital economy,

particularly when everyone’s data is flying around super speed.” Interviewee 11 warned, “Right

now in Australia, we have a privacy and hacking crisis.” Participant 4 added, “People should

have the right to decide what they want to share and what they want not to share.” Interviewee

12 raised concerns about data on the blockchain, saying, “When we are talking about securitized

and personally identifiable data, you do not want to put that as metadata on a blockchain.”

Interviewee 7 had a grim statement, “The government has so much data, and they have gotten

very, very, very crap security holding that data.”

RQ3 – Theme 4: Digital Landscape - Digital Identity

While decentralized blockchains facilitate anonymous usage, the concept of data

immutability was prominently featured in all interviews. Several interviewees commented that

using digital identification on an immutable blockchain was a compelling use case. Interviewee 3

said, “We need private transactions in a blockchain context that provide an entity verification or

some identity verification.” Furthermore, they mentioned that “Identity verification on a

blockchain is very suited.” Interviewee 6 discussed use cases for blockchain, saying, “Supply

chain management, identity security, anywhere where value is transferred and having an

immutable ledger is beneficial so that there is a record of those steps.” Interviewee 9 mentioned,

“Part of the problem with the adoption of blockchain over the years has been digital identity.” In

addition, interviewee 3 identified identity verification as a business challenge: “We need to be

able to have private transactions in the context of blockchain in which some (method) provides

an entity verification or some identity verification.” In further discussions, they offered a

solution, mentioning, “Having private knowledge, for example, a zero-knowledge proof of your

age is above a certain age, or you have a certain nationality, if you can prove the information

without revealing the exact information, that could be super useful for identity.”

RQ3 – Theme 5: Digital Landscape - Blockchain Technology and Virtual Assets

Asset identification and ownership emerged as central themes in the discussions, with

numerous interviewees emphasizing their significance during the conversations. These topics

were frequently highlighted as critical areas of interest and concern. When asked about

challenges and use cases, interviewee 12 said, “Supply chain management, verification, and

credential management like identity, but it is unclear whether or not this will be just

cryptocurrency or if it will utilize real-world assets.” Interviewee 11 discussed digital uses of

blockchain assets, saying, “I am not a gamer by any means, but you know we have got

generations of people used to exchanging digital assets, buying digital assets without ever

actually owning them such as NFTs or other sorts of infrastructure.” Interviewee 13 talked about

opportunities for Australian businesses, saying, “I think for the short and the medium term, much

more of a sort of rapid development and deployment of alternative frameworks that

accommodate digital assets.” Participant 11 discussed government regulatory challenges, saying,

“There are legislative proposals in Australia at the moment with the Australian Treasury working

through a project to develop (some regulations around) cryptocurrency exchange companies,

particularly around how they custody assets.” Interviewee 10 discussed taxation of assets:

“Cryptocurrency taxation, which has been a new implementation within Australia, has been put

down, along with a new draft regarding the taxation of assets is coming out later in the year.”

Outliers

The initial validation of potential participants for interviews occurred through LinkedIn

and proved highly effective, as it provided a list of their current positions and years of

experience. However, this method did not offer the in-depth knowledge required for the

interviews. Out of eleven interviews, one participant was ultimately rejected due to insufficient

knowledge or experience in blockchain. Interestingly, interviewee 8 was highly knowledgeable

about regulatory information and data but lacked up-to-date technical knowledge regarding

blockchain, stating, “Blockchain is old and slow, and it has limitations; it costs too much money.”

This discrepancy became apparent when the researcher compared their statements with other

participants’ opinions, using lines such as “in my research, I have found that…” to check for

consistency of statements among different interviewees. During the anonymous interviews, many

participants spoke “off the record” and were very candid in their responses. All interviewees

posited that Australia is lagging in progress and attributed this to governmental response time,

except Participant 13. This individual diverged from the consensus, saying, “The criticism has

changed,” and contended that Australia is not being left behind due to the government.

Furthermore, while most participants highlighted the application of blockchain technology within

supply chains, participant 13 criticized this as an “oversold use case.” They argued that it fails to

function effectively due to the complexities and variations inherent in realworld supply chain

elements.

Summary

Chapter 4 provided a comprehensive overview of the participant sample and conducted a

detailed analysis of their demographics, including age, industry, education level, and years of

professional work experience. The chapter further elucidated common themes from the in-depth

interviews, delved into different knowledge areas, and questioned existing knowledge from the

interviewee’s professional and academic experience. By documenting these rich qualitative

results, Chapter 4 enriched the scholarly literature related to the research topic. Chapter 5 will

introduce a final theory derived from the data and expand upon the themes and subthemes

directly linked to the research questions addressed in this grounded theory qualitative study. It

will conclude the study by summarizing the research and interview findings and proposing areas

for future research.

Chapter 5: Concluding the Study

Chapter 5 concludes this qualitative grounded theory study by presenting findings, ethical

issues, limitations, conclusions, and the final grounded theory model. The data collected from the

interviews indicate that Australia has taken an inhibiting consensus-driven approach to policy

and implementation. Nonetheless, Australia harbors the potential and talent to emerge as a

leading force and pivotal hub for blockchain development. While this study does not explicitly

focus on cryptocurrency, the connection between the value of cryptocurrencies plays a role in the

technology’s perceived adoption value and use cases.

Moreover, as interviewee 3 discussed, the technical benefits of blockchain are being

overshadowed by fears that it is a fraudulent system when, in fact, it is a technology designed to

organize data within a decentralized ledger. Education and regulatory guidance are significant

elements that the Australian blockchain industry needs to prioritize to lead the world in the

digital revolution. Newer generations of consumers are moving toward perceiving value as

purely digital in various forms, such as art, music, video games, or currency, as the trend toward

the digitization of value accelerates. Data collected from interviewee 11 suggests that blockchain

technology, characterized by its decentralization, immutability, and ability to store value, is

pivotal in enabling and facilitating this significant digital transformation.

Summary of the Study

As blockchain technology evolves, business requirements and developers consistently

introduce new functionalities and features (Colomo-Palacios et al., 2020). As interviewee 7

suggested, the continuous evolution of blockchain development necessitates frequent updates to

regulatory frameworks, upskilling, education, and security measures to maintain relevance.

During the interviews, participants consistently identified several critical challenges requiring

appropriate assurances. These challenges encompass trust, data privacy, technology scalability,

appropriate use cases and market fit, and legacy computer systems integration. The researcher

utilized a qualitative grounded theory research design, supported by an extensive literature

review, engaging ten industry and academia blockchain professionals through in-depth

interviews. The researcher used a set of base questions with each interview, incorporating

additional queries responsive to the participants’ answers and emerging themes from earlier

interviews. This study enriches the field of blockchain knowledge by offering insights into the

current state of blockchain technology in Australia and proposing potential enhancements, thus

serving business professionals, academics, government policymakers, and the broader

blockchain community.

Ethical Dimensions

The researcher conducted the study in strict adherence to the guidelines set forth by the

Institutional Review Board (IRB) and the procedures outlined in Chapter 3. The study treated all

participants equitably, allowing them to express their thoughts freely. An interview matrix

ensured the collection and return of all consent forms before the commencement of each

interview. At the beginning of the interview, the researcher reminded each interviewee of their

rights, including the option to withdraw from the study at any time. The researcher anonymized

all participant names, designating them as “interviewee X,” with X denoting a specific number.

The data collected comprised video recordings, transcriptions, and the researcher’s notes. All text

documents and notes had personally identifying information redacted, and the videos were

deleted. The author stored all data in a cloud storage data store protected by a strong password

and two-factor authentication. The data will be kept securely for five years, after which it will be

destroyed.

Removing bias from the interviews was crucial for the study (Korteling et al., 2021). At

the beginning of each interview, the researcher informed the interviewees that they would

maintain a “poker face” and show no emotional response to their answers. Furthermore, the

researcher refrained from commenting on the interviewees’ replies, interrupting them, providing

insights, or expressing agreement or disagreement. When referencing facts uncovered in

previously conducted interviews, the researcher consistently used the phrase “in my research”

and did not disclose the source of the facts or discuss other participants in the interview process.

Upon concluding the interviews, the researcher thanked the participants for their valuable

contributions to the data findings. Given that the study has received Institutional Review Board

(IRB) approval for utilizing data from anonymous sources, the researcher underscored the

importance of maintaining the anonymity of the interviewees and that the researcher could not

publicly confirm the inclusion of any participant’s data. Nonetheless, the interviewees were free

to disclose their participation, although the researcher could not verify their involvement. The

data collected reflects only the interviewees’ opinions and responses.

Overview of the Population and Sampling Method

The study involved ten Australian professionals and academics specializing in

blockchain, each with at least five years of experience and substantial expertise in one or more

areas of blockchain knowledge, as detailed in the individual skill radar graphs (see Figures B10

to B19). The researcher utilized the LinkedIn social media platform, employing first-level

contacts and InMail messages to reach potential participants. LinkedIn enabled the initial

verification of participants’ qualifications and experience through their online profiles before

making first contact. After participants agreed to participate and signed a consent form, the

interviewer used a set of base questions (see Appendix C), supplemented by additional inquiries

within a grounded theory framework, to gather data from the interviewees.

Limitations

During the participant recruitment phase, a higher-than-expected number of individuals

ignored or did not respond to interview requests. Moreover, after the first week of unsuccessful

interview requests and no agreements, the author adjusted the initial approach by sending a

shorter interview request before the more formal interview request email (see Appendix G).

Other limitations included one potential interviewee expressing dissatisfaction with the

anonymity of the interview, questioning its purpose, and saying, “What good is an interview

without receiving credit?” Another asked about the topic of the research study and then declined

to participate. One participant ultimately did not meet the required scores on the radar test and

lacked sufficient years of experience, leading to their exclusion (see Figure B4). Additionally,

concerns arose when this individual inaccurately reported their age by a significant margin and

later corrected it.

The researcher recommended, and the Institutional Review Board (IRB) approved, a

sixweek interview schedule, informing individuals who agreed to participate after this period that

they were outside the study window, thanking them for their interest and time, and expressing

hope they would consider future research requests. Furthermore, this study on blockchain

encompassed several critical areas of blockchain understanding: technical, governmental and

regulatory frameworks, theoretical knowledge, and financial expertise. The researcher

acknowledges that no individual might possess substantial knowledge in all areas. Therefore, it

was crucial to ensure that a certain level of knowledge saturation was achieved in each

blockchain area, as illustrated by the radar graphs in Figures B5 to B8, which show that the

desired breadth of knowledge across all interviewees was attained.

Findings

The researcher conducted a qualitative grounded theory study that systematically

explored and documented blockchain technology’s current state and potential in Australia,

highlighting its implications for the Australian information service industry. This study utilized

in-depth, grounded theory-based interviews to collect data, employing a set of base questions that

enabled the researcher to interject other questions to gather further participant data. The data

collected from the interviews suggests a further need for comprehensive and continued research

within Australia’s blockchain industry to understand further and exploit its potential benefits and

challenges.

The interview instrument, coupled with an open-ended grounded theory approach to

questioning, served as a robust tool for data collection, given the broad utility of blockchain

technology and the necessity to comprehensively explore all its facets (Gad et al., 2022). This

methodological approach enabled the posing of inquiries concerning emergent technologies that

were absent from the literature review, facilitated the clarification of data, and permitted the

pursuit of follow-up and in-depth probing questions. Furthermore, it supported the validation of

findings from previous interviews, the classification of emerging codes, the corroboration of

facts with insights from other professionals, and the acquisition of a broader array of data points

than fixed questionnaires or surveys could achieve. This enriched data set provided a robust

foundation for applying theoretical concepts. This grounded theory qualitative research study

addresses the following research questions:

Research Question 1 (RQ1): What are the key regulatory challenges hindering the

implementation of blockchain technology in Australia’s information services industries?

During the study, interview participants from various professional and academic

backgrounds consistently highlighted regulatory challenges, emphasizing the necessity for more

explicit governmental guidelines on blockchain industry regulations. They identified

complexities associated with blockchain technology and regulatory matters, such as data privacy,

security, financial, and transparency issues, all exacerbated by general apprehension about

regulatory inaction or public perception and further underscored by significant concerns

regarding trust and technical integration within the Australian Information Services Industries.

These complexities raise questions, impede business decision-making, and cast doubt,

complicating regulations’ definition. Furthermore, the deliberate approach to blockchain

regulation indicates a broader national tendency, reflecting a general hesitance across various

blockchain and information technology sectors to embrace rapid technological changes without

extensive oversight and deliberation. Additionally, as a global system, blockchain transcends

local boundaries, a point Interviewee 13 highlighted by noting, “Data packets do not care that we

are in Australia.”

Accordingly, working in the blockchain industry has exposed all interviewees to

European, Asian, North American, and other regulatory environments. The interviewees

contrasted Australia’s stance with that of other nations, noting that, unlike its peers, Australia

does not quickly adapt to new trends and is labeled “not a fast follower” but instead adopts a

wait-and-see approach. The researcher observed that Australians demonstrated a reluctance to

pioneer despite having the potential to lead on the global stage and be a hub for existing and

emerging blockchain talent and innovation. Instead, the approach adopted was based on

consensus theory, aligning policies and methodologies with those of larger territories such as the

United States, the United Kingdom, and Europe.

Regulatory Challenges

A combination of a knowledge gap or lack of skills and the rapid pace of technological

advancement exacerbated these issues, seemingly outpacing the deliberate pace and ability of

regulations to keep up. This rapid evolution of technology illustrates a broader systemic

sensitivity, where changes in one area can cascade throughout the entire system, echoing chaos

theory’s principle that a disturbance in one part of a process can influence all other elements

(Nan et al., 2020). As a result, the implementation of, or even the apprehension about, incorrect

or overly broad regulatory policies could stifle technological innovation or drive it to regions

with more favorable legal frameworks for blockchain products. Furthermore, a significant

implementation and project delivery capability gap exists in addition to the previously identified

issues. Data collected from interviews indicated a shortage of hands-on software code developers

with practical skills and an overabundance of C-Level management or individuals reliant on

jargon and outdated information, lacking current hands-on experience. Common themes in the

research gathering phase included instances where experts were not genuinely knowledgeable, or

projects were improperly built for mass scaling, real-world situations, or measured for market fit.

Bureaucracy

Bureaucracy plays a role, as various interest groups operate within seemingly exclusive

cliques, though they would benefit from a more collaborative industry effort to identify solutions.

Bureaucracy Theory properties include that values and actions, influenced by their origins and

backgrounds, significantly impact decision-making processes (Dhillon & Meier,

2022). While risk aversion is frequently viewed as a prudent strategy within the business context,

pursuing progress often necessitates accepting certain risks. Quoting a common adage, “to make

an omelet, one must break a few eggs.” This philosophy underscores the tension within the

Australian blockchain sector, where the potential for innovation clashes with a cautious

regulatory environment. Research data collected and codified from the interviewees suggests

Australia possesses the talent, desire, and willingness to innovate and try new blockchain

approaches; however, the fear of making mistakes in a political or bureaucratic context

significantly hinders its ability to compete globally.

Consensus and Time

Consensus theory is primarily concerned with perpetuating and stabilizing social order

within society (Orjiako & Igwe, 2022). Achieving consensus and regulatory change presents

inherent challenges and must balance being comprehensive enough to encompass the entire

industry, compelling enough to facilitate adoption, and flexible enough not to stifle industry

growth. Maintaining group harmony, ensuring all inclusion, and reducing the risk of alienation of

specific groups or sectors may prove time-consuming, leading to Australia taking no action and

further delaying blockchain implementation. Achieving complete consensus may prove

impossible for all aspects, with some blockchain industry groups not receiving full consideration.

However, consensus does not require unanimous agreement but rather the support of a vast

majority (Thomson, 2023). Australia faces a significant consensus problem; if regulatory creators

attempt to garner complete consensus from all Australian blockchain industry groups, they will

experience delays. Conversely, if they wait to observe global actions, Australia risks falling

behind while other countries take the lead. This dilemma highlights the necessity for a strategic

approach that balances domestic consensus-building with timely, decisive action.

Research Question 2 (RQ2): How does the absence or inadequate implementation and

communication of blockchain data processes pose risks to Australia’s information services

industries?

Although regulation and policy are essential components, they alone do not dictate the

progression of Australian blockchain enterprises. Therefore, developing thoughtful regulations

and assuring their practical implementation is imperative for fostering substantial progress

(Zwitter & Hazenberg, 2020). A potential risk stems from the disparity between thoughtful

regulations’ development and practical implementation. Regulations must be practical and

achievable, reflecting the blockchain environment’s current and possible future states. If

regulations are not thoughtfully developed and practically implemented, businesses could face

operational challenges, legal uncertainties, and compliance issues, which could hinder their

ability to leverage blockchain technology effectively and safely. The literature review further

emphasizes this need for effective regulation, identifying various data storage methods within

blockchain technology.

Independent Verifier

Due to its decentralized architecture, blockchain technology is an effective

communication channel and repository for storing hashes derived from off-chain data (Suzuki &

Murai, 2017). This functionality substantially strengthens its capacity to act as an independent

verifier, thereby enhancing the transparency and security of stored off-chain data. This

enhancement of transparency and security is crucial, particularly as purpose-built blockchain

implementations, when meticulously planned, can achieve significant interoperability with

existing and legacy systems. Furthermore, such strategic planning is imperative not only to

ensure scalability and cost-effectiveness but also to evaluate and confirm the market fit of the

technology. Businesses seeking to maintain trust with consumers should consider implementing

decentralized consensus verification functions such as blockchain to mitigate the risk of losing

consumer trust, which often relies on third-party verification.

Interoperability

The researcher introduced in Chapter 2 smart contracts as self-executable code or

programs deployed on the blockchain that automatically execute upon a triggering condition

(Kushwaha et al., 2022). The smart contract platform enables businesses to develop

interoperability gateways through application programming interfaces (APIs) dependent on

realworld communications and logic conditions. Effective communication to validate code and

code standards implementation, auditing, and regulation of smart contract capabilities requires

further investigation. The potential risks introduce security, privacy, and trust issues if smart

contracts do not function as intended. The researcher mentioned in the literature review that even

if the code functions flawlessly, code is ultimately crafted by humans (Werbach, 2018).

Blockchain as a Tool

As indicated by the interviews, blockchain should be considered a supportive tool for

businesses, particularly effective in solving data transparency and trust issues, rather than a

universal solution for all data challenges. Blockchain is unnecessary in controlling or managing

every business information system within an organization. Business use cases requiring trust,

transparency, security, and reliability merit consideration for blockchain implementation.

Furthermore, interview evidence underscores the need for robust solutions in critical areas,

demonstrating the reliability of blockchain’s decentralization and technical consensus layer.

Real-world examples collected during the interviews of decentralization and the technical

consensus layer of blockchain show that no single party can manipulate data within a blockchain,

thus maintaining the integrity and trustworthiness of the information stored. Establishing trust

and ensuring data immutability is crucial for the integrity and security of digital systems and the

businesses operating them. Accordingly, Australian businesses should consider researching and

adopting these technologies to enhance operational efficiency and maintain a competitive

advantage in the global market.

Inadequate Implementation and Communication

For effective implementation, it is essential to establish a standard, a framework, and

transparent regulations, accompanied by efficient communication of these elements (Zwitter &

Hazenberg, 2020). In Australia, numerous attempts at collaborative initiatives to achieve

regulatory consensus on establishing frameworks and guidance often suffered from insufficient

business support or were too fragmented to bring about significant change. Businesses and

policymakers can better understand blockchain technology’s specific business functions by

engaging in dialogue with established blockchain organizations and academic institutions. Active

communication between all parties, including regulators, academics, professionals, and industry

bodies, is essential to create a well-rounded and effective regulatory framework that is fit for

purpose. Consensus theory assumes a functionally integrated system in equilibrium (Wasilah,

2023). However, the absence of such policies has fostered an environment where some

businesses are reluctant to disclose their blockchain projects publicly and operate in secret until

authorities establish more definitive policies. Interviewee 8 directly points to the problem, saying

that companies are “doing (blockchain) under the radar and building and not telling anyone,

waiting until the license information comes out.” Regulation is necessary to ensure that any

companies operating secretly wishing to provide legitimate services operate transparently.

The researcher discusses in the literature review the removal of the Australian Blockchain

Roadmap ("Australia's National Blockchain Roadmap," 2023), which outlines 12 signposts or

action items to address the information requirements. As of May 2024, this roadmap seems

abandoned as website links to documentation and website searches do not yield results. Formal

rules and regulations are a core principle of bureaucracy theory (Rai, 2022). However, this

official communication ambiguity and the loss of the Australian Blockchain Roadmap have left

businesses navigating a precarious landscape, where the absence of clear guidelines forces them

to tread carefully with their blockchain developments. The industry requires updated regulatory

guidance to ensure clarity and support ongoing innovation.

User Experience

User experience plays a pivotal role in technology utilization, including blockchain,

because the simplicity of its software interfaces directly affects how easily people can understand

its potential application. All interviewees indicated that blockchain should be a backend

technology that no longer necessarily needs to be displayed or communicated to customers to

achieve acceptance or usability. One might argue that blockchain’s implementation and

functionality for end users or customers are more important than the effects of its surrounding

branding, jargon, and hype. From a business perspective, the emphasis on practical utility

indicates that blockchain’s actual value, from a consumer perspective, does not arise from its

public image but from its capacity to streamline and simplify complex consumer processes

through user-friendly software interfaces.

Simple is not Chaotic

The ease of use of blockchain functionality creation has significantly simplified the

creation process to merely clicking a button on a web service, demonstrating that practical

considerations become significant as technical features are standardized. If all future blockchains

possess analogous creation code functionalities, their sole distinctions will emerge from external

elements such as user interfaces and marketability, which will play pivotal roles in their

implementation and utilization. Chaos theory investigates behaviors in dynamic systems,

utilizing a comprehensive continuous approach rather than a singular data relationship for

accurate explanation and prediction (Luo et al., 2022). Consequently, businesses must carefully

evaluate the practicality and scalability of blockchain systems over the long term, mirroring the

long-term predictability and short-term unpredictability that are characteristic features of chaos

theory. In this blockchain scenario, determining the systems’ long-term scalability becomes

challenging due to technical complexities and insufficient communication, particularly as the

differentiation between systems hinges increasingly on those aforementioned external factors

rather than core functionalities. This challenge underscores the need to focus on practical and

scalable implementation solutions in light of the predictability and unpredictability that define

the dynamics of chaos theory over different timescales.

Research Question 3 (RQ3): What challenges do businesses face in understanding and

accepting blockchain systems, and how can these challenges be effectively addressed?

Australian businesses encounter numerous challenges across various fronts, including

budgeting, data storage, and public image, and it would be erroneous to claim that a single

system could resolve all these issues (Yuncken, 2022). Chaos theory is more concerned with

questioning the order within disorder (F]l]z, 2024). Therefore, a single change or external factor

can significantly impact a blockchain business and its use case environments, mainly when

dealing with complex and chaotic systems such as blockchain. Events such as media stories,

hacking incidents, or fluctuations in cryptocurrency prices all trigger ripple effects that influence

perceptions and policies regarding the effective use of blockchain. These events and the dynamic

nature of the blockchain ecosystem underscore how sensitive the business environment is to

various external factors, as highlighted by interviewees’ statements from business

decisionmakers, such as “blockchain equals bitcoin equals scam,” which cast doubt on the

industry but more importantly emphasize the need for further education and upskilling. The need

for education points to a more significant vulnerability in the industry: its susceptibility to

misconceptions and the broader political and economic climate. Interviews indicated that

changes in government could trigger widespread effects across many aspects of the Australian

blockchain and information services industries as priorities shift along with new and existing

policies under review. The chaos surrounding blockchain seemingly causes businesses and the

government to rely on “gut feelings” to follow social trends or chase the latest buzzwords in

dictating resource allocation instead of strategically determining the best market fit for the

technology. This approach seemingly results in missed opportunities and suboptimal investment

in transformative blockchain innovations, as it fails to capitalize on rigorous, strategic analysis

and instead succumbs to the whims of fleeting market sentiments and superficial trends. This

lack of a methodical and informed investment strategy can lead to a misallocation of resources

and a failure to fully exploit the potential of blockchain technology in creating sustainable and

impactful business solutions.

Bureaucracy Required

Bureaucracy theory advocates that management should adhere to prescribed rules and

regulations to enhance organizational performance, emphasizing work efficiency and

effectiveness (Rai, 2022). While bureaucracy is necessary and burdensome, the industry seeks

regulation and assistance without hindering technological advancement or sacrificing

blockchain’s decentralization and speed. The demand for newer, faster, and better technologies

drives development and business in the blockchain sector, where there seems to be a combined

“Fear of missing out” (FOMO) and “Fear of the unknown.” This fervor for keeping pace with

emerging trends frequently results in hurried development processes, as interviewees noted the

industry’s rapid pace and upskill requirements, which often lead to mistakes by some

inexperienced developers. An interviewee noted, “People working at companies like Boeing or

Airbus, developing software for airplanes, rockets, or cars, are extremely skilled. In contrast, the

blockchain industry features a vast spectrum of skills.” Although the widely recognized

blockchain principle “code is law” suggests that software will perform as instructed, the reality is

seemingly more nuanced: “Code is law, but a human programmed it,” reflecting that bugs in

software are not the fault of blockchain but their human creators. This rapid pace and a seeming

lack of depth in skills in some areas exacerbate trust and reliability issues for consumers and

businesses for blockchain. Interviewees could not offer short-term solutions outside education

and training; businesses set the requirement pace, and technology and resources follow the

money.

Business Challenges

Data findings from the interview highlight significant concerns and understanding

regarding trust, security, privacy, and technical integration in blockchain implementation within

the Australian Information Services Industries. Complemented by interview insights, the

literature review identifies several accepted blockchain business implementation methods within

supply chain, identity, and data assets. However, businesses should understand that existing data

storage systems may not require a complete overhaul to incorporate blockchain technology but

can function effectively by integrating with legacy systems. This approach involves addressing

and overcoming the commonly accepted mentality of “if it is not broken, why change it?” It also

includes strategically facilitating the integration of legacy computer systems with newer

technologies. Doing so aims to enhance operational efficiency and bolster system security,

privacy, and transparency. This integration allows businesses to adopt advanced technological

methods such as off-chain data storage, proof of existence, and zero-knowledge proofs (ZKPs),

enhancing overall transparency and security.

Overcoming

Zero-knowledge proofs (ZKPs), as mentioned in Chapter 4, are methods that have gained

popularity over the last two years to store data within a blockchain format but off-chain and

provide only a cryptographic hash to the public blockchain as proof of data’s existence (Lavaur

et al., 2023). In this scenario, a cryptographic hash or digital signature facilitates data verification

without revealing or storing the data publicly. The literature review and data collected in the

interviews extensively discuss methods for utilizing cryptographic hashes to solve blockchain

data storage problems that Australian businesses could implement depending on the data type,

size, and speed required to access the data. Businesses must ensure market fit and technical

suitability; however, this blockchain data storage function holds the most significant promise for

balancing business and technological requirements, encompassing privacy, speed, transparency,

security, and reduced operational storage costs. The study introduces these concepts without

fully exploring their practical implementation in a diverse real-world scenario and renders the

topic an area for further exploration within future business application and technical adaptation

studies. Fundamentally, Australian businesses must diligently evaluate the risk associated with

retaining outdated systems, as such a course of action could result in operational inefficiencies or

provide an opportunity for competitors to surpass by embracing newer blockchain technologies.

Understanding Blockchain Real-World Value

One critical area where blockchain distinguishes itself from other technologies is its

direct linkage to a financial asset or instrument via cryptocurrencies. One could argue that the

close tie between the adoption of blockchain and its financial viability exists; without economic

incentives, blockchain could risk becoming obsolete as merely another ephemeral innovation.

The sustainability of blockchain technology heavily depends on the persistent economic

incentives provided by digital value assets, which, in turn, influence its popularity. This situation

is a double-edged sword: while it drives rapid innovation and adoption, it exposes the technology

to volatile market dynamics and speculative pressures. These forces undermine its long-term

stability and development, which are challenges that technologies outside of blockchain do not

encounter.

Misunderstandings and Challenges

Furthermore, contrary to prevalent misconceptions and unfounded skepticism, data from

various studies and statements from interviewees indicate that blockchain technology itself is not

fraudulent. This evidence suggests that the negative perception of blockchain as a scam is a

misunderstanding of its legitimate applications and potential benefits. Fraudulent activity, or

scams, existed long before the advent of blockchain and will continue beyond it. Fraudulent

activities occur outside of blockchain, yet the technology often serves as a payment instrument

and consequently suffers from an unjustly tarnished reputation. However, consensus theory

highlights the challenge of achieving agreement among diverse stakeholders, as their varying

levels of understanding and acceptance of blockchain technology can lead to differing opinions

(Fouad et al., 2022). Additionally, a trust deficit in the technology or the implementing

organizations, combined with misaligned objectives, can significantly hinder a unified approach

to blockchain adoption. For example, criminals commonly use credit and gift cards to conduct

fraudulent activities, yet there is a common understanding that neither credit nor gift cards are

inherently fraudulent (Chaganti et al., 2021). Businesses need to discern this critical distinction to

fully appreciate blockchain technology’s legitimate value and potential, understanding that this

awareness is essential for leveraging blockchain’s capabilities and for businesses to support its

innovative advancements in their operational strategies.

Grounded Theory: Theoretical coding

The process of theoretical coding involves integrating and synthesizing categories

obtained from coding and analysis to construct a comprehensive theory (Chun Tie et al., 2019).

Initial coding disassembles the data, while theoretical codes interconnect the fragmented

narrative, culminating in a cohesive theoretical framework (Chun Tie et al., 2019). For this study,

the theoretical coding process employed the Glaser (1978) Six C’s method for grounded theory,

encompassing cause, consequences, covariance, contingencies, context, and conditions (von

Alberti-Alhtaybat & Al-Htaybat, 2010). This methodology enhances the robustness and depth of

the theoretical constructs, ensuring they are well-grounded in the empirical data and reflect the

interrelations within the studied phenomena.

Constant Comparative Method

The constant comparative method serves as the core approach for producing grounded

theory. This method relies on rigorous qualitative data analysis, achieved through coding - a

process that condenses original data into a few conceptually relevant words, thereby giving rise

to theoretical concepts (Leite et al., 2021). This systematic approach ensured emerging theories

were rooted in data, enhancing their validity and applicability. Chapter 4 outlines the codes

determined from this study and lists them in Table A4. Table A5 outlines the development of the

new emerging themes through the constant comparative method.

Six C’s

Cause

The researcher suggests that the data from all interviewees indicates that moving targets

and lack of or frequently changing policies are primarily to blame for the instability and lack of

consistent progress in the Australian blockchain sector.

Consequences

Ninety percent of the interviewees state that Australia’s current blockchain business

environment has led to a significant shift in talent, and businesses are planning to move their

blockchain projects outside the country. These entities seek regions with favorable policies, clear

guidelines, and better support for blockchain technology and digital innovation.

Covariance

Several covariances emerge from this study, but the most impactful for the blockchain

industry and businesses is the role of public perception in the acceptance of blockchain

technologies. Understanding how public perception shapes blockchain adoption and adapting to

consumer and user expectations can guide strategic communication and educational efforts,

ultimately enhancing acceptance and trust in these technologies.

Contingencies

The regulatory environment influences blockchain innovation and adoption by providing

clarity and consistency. Clear and consistent regulations facilitate innovation and encourage

adoption, whereas ambiguous or restrictive policies hinder technological progress and discourage

new inventions.

Context

Industry standards encompass the established guidelines and benchmarks within a

particular sector that influence the implementation and acceptance of blockchain solutions.

Stability and predictability in these standards are crucial, as they provide a clear framework that

facilitates the adoption of innovative technologies like blockchain, ensuring consistent and

reliable integration across the industry.

Conditions

Conditions within the regulatory environment significantly impact blockchain

technology, as clear and supportive laws can facilitate its adoption and innovation. Conversely,

restrictive or ambiguous regulations can hinder blockchain development and discourage

investment.

Grounded Theory

The data in a grounded theory study inherently articulates insights and revelations that

lead to new information discoveries, a characteristic mirrored by the unfolding discoveries

within the literature review (Foley et al., 2021). The literature review constituted a

comprehensive examination of the historical and contemporary aspects of various factors related

to blockchain technology, closely aligning with the principles of grounded theory design. These

emergent findings within Chapter 2 enabled the researcher to uncover novel insights,

contributing to a deeper understanding of the subject matter. This alignment underscores the

interweaving of the literature review data discovery and the grounded theory methodology

throughout the study, thereby enhancing the coherence and robustness of the research framework

and ultimately developing a theory grounded on data.

When researching Chapter 2, the investigation of legacy data storage problems provided

foundational insights into the challenges associated with traditional data storage methods.

Detailed descriptions of blockchain operations and data storage mechanisms led to the discovery

of efficient techniques for storing and hashing data across multiple blockchains using digital

signatures. The exploration of off-chain data hashing methods culminated in Asghar et al. (2023)

research on the proof of existence blockchain storage concept, which significantly influenced the

researcher’s formulation of further questioning during the data collection interviews. During the

initial interview with a technically proficient participant, the discussion introduced

ZeroKnowledge proofs, prompting the researcher to delve deeper into this topic in subsequent

interviews, as outlined in the Constant Comparative Method (CCM) in Table A5.

Theory Relations

The grounded theory study’s insights and revelations exhibit significant relationships with

chaos, consensus, and bureaucracy theories. This comparative analysis shows the interplay

between emergent blockchain data management techniques and the principles underlying these

theories. Blockchain technology’s unpredictability and dynamic nature align with chaos theory,

while the collaborative and decentralized aspects resonate with consensus theory. Furthermore,

the lack of effective regulation in Australia underscores the necessity of bureaucratic structures,

as highlighted by bureaucracy theory, which, despite its hindrances, remains essential for

establishing effective blockchain governance frameworks. This alignment with established

theories underscores the grounded theory approach, which focuses on data-driven insights. The

chaos, consensus, and bureaucracy theories all involve interactions where changes can lead to

discoveries or hinder progress, allowing researchers to rule out errors and refine their methods

and, ultimately, their findings grounded in data.

Final Theory

It is essential to offer clear regulatory guidance and ensure transparency while

consciously avoiding the influence of fear or trendy buzzwords when conducting business in the

blockchain industry. This need for enhanced regulation closely aligns with the study’s grounded

theory, suggesting that Australia’s slower pace in achieving technological leadership may

partially stem from a landscape marked by regulatory ambiguities and a lack of clear guidelines.

Addressing these regulatory challenges would accelerate the adoption and development of

Australia’s blockchain technology, fostering innovation and growth within the industry. The

researcher’s grounded theory for this study posits that a lack of unambiguous regulation on

blockchain is causing Australia to fall behind the rest of the world.

Reflection

The study’s success was heavily contingent upon the quality of the participants selected

for the interview data collection and the successful application of a grounded theory design,

which enabled the data to shape the study’s theoretical framework (Chun Tie et al., 2019).

Blockchain is incorrectly assumed to be used solely for cryptocurrency, leading to a widespread

lack of awareness about its foundational technology and broader potential as a business tool.

However, blockchain technology has had some successful adoption internationally in the

information service industry (Hooper & Holtbrügge, 2020). For example, Comcast has developed

a blockchain-enabled platform to enhance data control and optimize ad targeting (Hooper &

Holtbrügge, 2020). Facebook is investigating using blockchain-based identities for website

logins to boost user privacy (Hooper & Holtbrügge, 2020). Algebraix uses a blockchainpowered

advertising platform to deliver permission-based advertisements (Hooper & Holtbrügge, 2020).

Nevertheless, blockchain technology remains overly complex for mass adoption, and the

researcher suggests, based on the data, that while the problems are known, efforts to address

them remain ineffective. During the creation of the study, the researcher researched many new

technical and regulatory concepts, aiming to represent an apparent business problem and

solution.

Initially, the study encompassed the blockchain industry as a whole. However, the

extensive volume of existing literature necessitated narrowing the study’s focus to yield more

precise and meaningful results. Undertaking a study of this magnitude was groundbreaking for

the researcher, who required a meticulously structured approach to ensure rigor and validity, an

aspect not foreseen at the outset. The researcher initially anticipated completing the study within

the standard timeframe set by the university. Nevertheless, the COVID-19 pandemic disrupted

global activities for approximately 18 months, extending the duration required to complete the

study. However, this delay allowed newer technologies, such as zero-knowledge proofs (ZKPs)

for blockchain, to mature and be incorporated into the study.

After completing each chapter and gathering more data, the researcher’s opinion on

blockchain and its business applications evolved. The interviews proved more successful than

anticipated, collecting insights from high-ranking academics and industry professionals. Their

opinions, provided anonymously and off the record, offered candid perspectives and allowed

them to explore theories the researcher might not have considered. In the researcher’s opinion,

the data gathered was extremely valuable and interesting, and if the researcher conducts a similar

study again, grounded theory will likely serve as the chosen method.

Several other elements the researcher deemed successful included maintaining anti-bias

measures during interviews and keeping a neutral demeanor. Although it might seem that the

researcher appeared uninterested, this approach allowed interviewees to express themselves

freely, which was crucial in obtaining candid responses. Additionally, the radar graphs proved

helpful in confirming that both knowledge and data saturation had occurred, indicating that the

researcher had gathered sufficient data and that the data quality was adequate.

The researcher gained a greater appreciation for assembling a dissertation and

acknowledged the contributions of all those who assisted along the way. The researcher admits to

an increased self-awareness that “he does not know what he does not know,” recognizing this

more clearly after completing the study and the discussions and interactions with some highly

intelligent participants, university chairs, and committee members. The author understands it is

acceptable not to know something, as lifelong learning and education are essential to personal

and professional growth. The researcher is satisfied that the data and conclusions reached within

this study are of sufficient quality to potentially impact the Australian blockchain industry and

hopes that future researchers will continue to advocate for blockchain business solutions.

Recommendations

The qualitative grounded theory study identifies current challenges within the Australian

blockchain industry and proposes several straightforward solutions for implementation. Firstly,

the researcher shows that the data from the interview indicates that greater education within the

blockchain section is required. It is essential to delineate the various levels of education required,

ranging from broad C-level discussions to fundamental coding skills. By addressing these

educational needs, stakeholders can better understand the diverse applications of blockchain.

Although blockchain includes cryptocurrency and tangible money assets, the rapid pace of

financial transactions often drives technological advancements within the blockchain industry.

However, this should not be at the expense of compromising security and privacy. Businesses

must prioritize privacy and security as their top concerns, approaching projects with these aspects

foremost in mind. Despite insufficient government regulation, Australia has a significant

opportunity due to its wealth of highly skilled blockchain professionals, which presents an

opportunity to position Australia as a blockchain project and investment hub. Furthermore, the

government should complete or update the Australian blockchain roadmap to meet the

requirements of 2024 and beyond.

Based on the interviews and data analysis, the researcher recommends that the

information service industry adopt the concept of zero-knowledge proofs (ZKPs) within

blockchain technology. Zero-knowledge proofs (ZKPs) utilize cryptographic techniques to

ensure privacy by verifying private data without revealing it in its clear form and are suited for

data verification from an off-chain source (Pop et al., 2020). One potential solution is to upgrade

the physical hardware of legacy systems to handle increased workloads while hashes of the data

are stored on-chain and securely maintaining the real data off-chain. Implementing

zeroknowledge proofs will help integrate the benefits of both legacy and digital environments.

This approach, however, requires careful consideration of all relevant factors, as each use case is

unique. This strategy will strengthen trust and ensure data immutability, guaranteeing that data

remains secure and untampered.

Lastly, the future digitalization of assets necessitates a robust infrastructure to support this

transformation (Truong et al., 2023). Assets such as art, money, games, cash, stocks, and even

land ownership documents will require secure technology to ensure data is safe, secure, private,

and immutable. A significant business opportunity for Australian businesses is evident and ready

to be capitalized. Addressing current gaps and challenges within the industry is essential to seize

this opportunity effectively. Accordingly, a comprehensive strategy encompassing education,

regulation, and infrastructure development is crucial for Australia to capitalize on blockchain

technology’s potential.

Suggestions for Future Research

This study is a comprehensive business-oriented investigation targeting Australia’s

blockchain information services industry, with research questions, findings, and conclusions

focused on business-related aspects. The analysis and insights provided inherently relate to the

principles and dynamics of the business sector. However, blockchain is a technology, and

suggestions for future research encompass both technical and business elements. From a

technical perspective, future technical researchers could investigate storage methods and

practical proofs of concept. From a business standpoint, it is imperative for forthcoming research

to identify datasets and business operations suitable for integration with blockchain technology.

The study, which only engaged blockchain professionals and academics rather than consumers,

revealed a recurrent emphasis on user experience and simple software interfaces during

interviews. A critical insight underscored the pivotal role of consumer adoption in ensuring

successful implementation, thus advocating for user-friendly technological solutions.

Consequently, a thorough investigation into consumer expectations, behaviors, and blockchain

utilization emerges as a prudent avenue for future academic inquiry. Finally, with the emergence

of potential future regulations, it is imperative to investigate Australia’s implementation of such

regulations and their consequent impacts, rendering it a valuable recommendation for future

research endeavors.

Concluding the Study

Chapter 5 concludes this quantitative grounded theory study on blockchain trust and its

application within the Australian information services industry. The study aimed to investigate

the current state of blockchain implementation in Australia and identify the elements necessary to

determine if Australia was lagging behind the rest of the world. Moreover, it aimed to describe

the functions of blockchain, explain how it operates, illustrate how data is or could be stored

within several public blockchains, and introduce the concepts of digital signatures and hashing

based on the research derived from the literature. Grounded theory, an exploratory research

methodology, facilitated asking additional probing questions, uncovering new information, and

exploring interviewees’ thoughts. This approach, combined with the data gathering and coding of

the collected interviews, allowed the expectations from the literature review to be confirmed and

refined. The grounded theory method enabled considering different lines of questioning and

perspectives when addressing the research questions.

Implementing the study’s findings may require collaboration among various groups and

the government to leverage Australia’s blockchain talent and develop meaningful and effective

regulatory policies. Such collaborative efforts will ensure Australia remains competitive in the

global blockchain landscape. By fostering innovation and establishing a robust regulatory

framework, Australia can effectively harness the potential of blockchain technology to solve

business problems. Ultimately, these initiatives will contribute to advancing the information

services industry and secure Australia’s position as a leader in blockchain implementation.

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