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https://www.emerald.com/insight/content/doi/10.1108/JSTP-08-2018-0185
FINTECH: RESEARCH DIRECTIONS TO
EXPLORE THE DIGITAL
TRANSFORMATION OF FINANCIAL
SERVICE SYSTEMS
Preferred Citation
Breidbach, C., Keating, B.W., and Lim, C. (2020). Fintech: Research directions to explore the
digital transformation of financial service systems, Journal of Service Theory and Practice,
doi.org/10.1108/JSTP-08-2018-0185.
Fintech: research directions to
explore the digital transformation
of financial service systems
Christoph F. Breidbach
Business School, The University of Queensland, Brisbane, Australia
Byron W. Keating
QUT Business School,
Queensland University of Technology, Brisbane, Australia, and
Chiehyeon Lim
School of Management Engineering, School of Business Administration,
Ulsan National Institute of Science and Technology, Ulsan, The Republic of Korea
Abstract
Purpose –The purpose of this paper is to delineate a research agenda to guide future service research
investigating the digital transformation of financial service systems through Fintech –disruptive innovations
by new market entrants that challenge the position of mainstream financial institutions.
Design/methodology/approach –Rooted in the philosophical foundations of “use-inspired research,”this
paper addresses the managerially and societally relevant phenomenon of Fintech by identifying, and
responding to, the individual challenges and problems associated with the digital transformation of financial
services. This is accomplished through a computational text-mining approach to analyze the corpus of 1,545
published practitioner articles associated with Fintech, identification of managerial challenges therein and
subsequent delineation of a novel research agenda.
Findings –By connecting managerial challenges relating to Fintech with the service literature, this paper develops
a use-inspired research agenda that provides scholarly and managerially relevant research directions (RDs). These
pertain to the complexity of digital financial service systems (micro level), orchestration of value co-creation with
Fintech (meso level), and the development of elastic infrastructures, models and markets (macro level).
Research limitations/implications –Fintech is an emerging phenomenon associated with the digital
transformation of financial services. However, actual guidelines on how service research related to Fintech could
be advanced from a theoretically as well as managerially relevant angle are unavailable to date. Here, the
authors address this challenge and provide the field with 18 tangible RDs toadvance service theory and practice.
Practical implications –The purpose of this paper is to guide future academic research addressing
managerial challenges associated with Fintech and the digital transformation of financial service. Due to the
explicit use-inspired nature of the work, the future research stemming from the agenda that the authors put
forward here will be of benefit to decision makers and society more broadly.
Originality/value –This empirical research contributes to the discourse regarding the role of information
and communication technologies in service in general, and the digital transformation on financial services in
particular. The in-depth computational text-mining analysis is unbiased, replicable and provides the
foundation for a use-inspired research agenda that is subsequently delineated.
Keywords Text mining, Digital transformation, Fintech, Financial service systems
Paper type Research paper
1. Introduction
The Global Financial Crisis (GFC) of 2008 significantly decreased customer trust in financial
services, and helped spark the growth of financial technology or “Fintech”ventures
(Muzellec et al., 2015). Fintech offerings challenge the status quo of mainstream banking
(Zhang et al., 2016), and range from peer-to-peer (P2P) lending (Pena et al., 2018) to
Journal of Service Theory and
Practice
© Emerald Publishing Limited
2055-6225
DOI 10.1108/JSTP-08-2018-0185
Received 29 August 2018
Revised 1 April 2019
7 August 2019
18 September 2019
Accepted 20 November 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/2055-6225.htm
Authors are listed alphabetically and have contributed equally to this paper. Chiehyeon Lim was
supported by the “Human Resources Program in Energy Technology”of the Korea Institute of Energy
Technology Evaluation and Planning (KETEP), granted financial resource from the Ministry of Trade,
Industry & Energy, Republic of Korea. (No. 20184010201680).
Financial
service
systems
cryptocurrencies (Nakamoto, 2008), or applications of blockchain technology that omit
intermediaries in financial service processes (Nofer et al., 2017), and represent a $5bn market
in the USA alone (Zavolokina et al., 2016).
The digital transformation of financial services and the associated growth of Fintech are
enabled through information and communication technologies (ICT). These enhance the
accessibility and availability of resources in service systems (e.g. resource “density”), as well
as their transferability (e.g. resource “liquefaction”), thus resulting in new technology-
enabled value co-creation processes (Breidbach and Maglio, 2016; Lusch and Nambisan,
2015). Given recent technological advances, the pervasive impact of ICT on financial service
is unsurprising, and investigating the implications of ICT in service more broadly
represents a key service research priority (Ostrom et al., 2010, 2015). However, existing
contributions in the service research discipline have been criticized in that they “failed to
offer insights on emerging digital service innovations”(Lusch and Nambisan, 2015, p. 172)
in general, and understanding of Fintech as an emerging service context, in particular
(Breidbach and Ranjan, 2017). This gap in knowledge is partially rooted in the fact that ICT
and service research have traditionally been conducted in disciplinary silos (Brust et al.,
2017), and is further amplified by the increasing speed at which new disruptive technologies
emerge (Christensen, 2006). Consequently, managerially relevant insights on how to manage
Fintech are unavailable to date.
Against this backdrop, we argue that Fintech represents a unique opportunity for service
research to contribute new knowledge about the digital transformation of financial services
more generally, and helps address managerial and societal challenges therein. In addition,
service research exploring Fintech and the digital transformation of financial service
systems provides a unique opportunity to advance theoretical insights about the role of ICT
in service more broadly. Actual guidelines, however, on how to conduct theoretically,
managerially and societally relevant service research related to Fintech, for example,
through systematically identified research priorities, are unavailable to date.
Our present work aims to address this gap in knowledge by delineating an agenda for
service research aiming to investigate the digital transformation of financial services.
To do this, we follow a “use-inspired”research philosophy. This approach intends to address
real-world phenomena (Stokes, 1997), like Fintech and the digital transformation of financial
services, by initially identifying managerial challenges or problems associated with the
phenomenon, before delineating a research agenda that provides pathways to approach the
challenges identified (Tijssen, 2018). Use-inspired research already exists in the context of
service science more broadly, where the need to conduct and promote managerially relevant
research has been recognized (e.g. Gebauer and Reynoso, 2013; Helkkula et al., 2012; Lim, Kim,
Kim, Kim and Maglio, 2018). We build on this established trajectory, and draw on Antons and
Breidbach (2018) as well as Lim and Maglio (2018), to apply computational text-mining
algorithms to a text corpus of 1,545 published practitioner articles. We thereby identify
managerial challenges associated with Fintech and the digital transformation of financial
services, contrast these empirical findings with insights provided in the scholarly literature
and subsequently delineate an agenda for future service researchers. Our work therefore
provides three meaningful contributions to the service research discipline.
First, we provide an empirical contribution by identifying 27 unique managerial
challenges associated with Fintech and the digital transformation of financial services in the
text corpus of 1,545 published managerial articles. We further summarize and categorize
these challenges into six high-order themes, thereby highlighting the problems faced by
practitioners and society more succinctly. This novel conceptualization of managerial
challenges associated with Fintech contributes to the recent discourse regarding the role of
ICT in service in general (i.e. Ostrom et al., 2015), and the impact of digital transformation on
financial services in particular (Breidbach and Ranjan, 2017), through in-depth empirical
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findings that are relevant and replicable, while providing the foundation for a use-inspired
research agenda.
Second, by connecting our empirically derived managerial challenges to the extant
literature, we delineate a use-inspired research agenda that provides not only scholarly, but
also managerially relevant research directions (RDs) related to Fintech. Specifically, it
addresses key issues, including the complexity of digital financial service systems (micro
level); orchestration of value co-creation with Fintech (meso level); and the development
elastic infrastructure, models and markets (macro level), across three distinct levels of
abstraction. We thereby provide managers and policy makers with the necessary
foundation to benchmark their own experiences related to Fintech, help guide future
investments and regulatory frameworks in this area, but also expand prior academic work
that aimed to develop research agendas based on academic literature only (e.g. Breidbach
and Brodie, 2017) –an approach that has been criticized for its misalignment between
academia and practice (Zavolokina et al., 2016).
Third, by applying computational text mining to analyze a corpus of unstructured
natural text documents (i.e. managerial articles associated with Fintech and the digital
transformation of financial service), our work addresses Ostrom et al.’s (2015) call for service
research to investigate how emerging “methods such as text mining [can] uncover […]
service-related needs and preferences that traditional methods cannot”(Ostrom et al., 2015,
p. 138). We achieve this by using unsupervised machine learning algorithms, thus providing
the much-needed interdisciplinary methodological approach needed to leverage the
potential benefits of novel data analytics for service research (Antons and Breidbach, 2018;
Lim and Maglio, 2018), and provide future service scholars with a blueprint of how this can
be accomplished.
2. Conceptualizing Fintech as an emerging context for service science
Finance and technology evolved together for decades (Arner et al., 2016). Starting in the 1950s,
ATMs were introduced to replace human tellers and enabled customer self-service in banking.
Credit and EFTPOS cards eventually aimed to eliminate the need to carry cash, while
pervasive internet connectivity in the late 1990s led to 24/7 online banking, thus rendering
visits to physical branches obsolete for many customers. At the same time, computational risk
management, big data analytics or electronic stock trading were introduced to increase the
effectiveness and efficiency of service operations (Mackenzie, 2015).
Today, the repercussions of the GFC and availability of new technologies ranging from
cryptocurrencies (Nakamoto, 2008) to blockchain (Nofer et al., 2017) have instigated a new
interest in Fintech –the broad intersection of information technology and finance –across
multiple academic disciplines like information systems research (Zavolokina et al., 2016),
finance (Mohan, 2016), marketing (Gimpel et al., 2018) or industrial management (Ryu, 2018).
However, research explicitly exploring the role and impact of new financial technologies on
service systems is lacking, since the majority of contributions to date attempted to study
innovation in financial services more broadly. For example, Frame and White (2014) define
innovation in financial services by differentiating between new products and services, new
production processes, as well as new organizational forms. Lerner and Tufano (2011) link
innovation in financial services to the creation and dissemination of new financial
technologies, institutions and markets, while others emphasized functional (Merton, 1995) or
historical (Miller, 1986) lenses on innovation in financial services.
Ultimately, despite the increased focus on, and relevance of Fintech, “research on the
phenomenon ‘Fintech’is […] in its infancy”(Zavolokina et al., 2016, p. 2), and largely
disconnected from managerial discourse (Dapp et al., 2014). Consequently, there is no clear and
unanimously accepted definition of what Fintech entails (Schueffel, 2016). This represents a
key challenge for service research, because unambiguous definitions and clearly
Financial
service
systems
conceptualized research constructs are a prerequisite to guide future theoretical and empirical
work (Scherer, 2005). Table I provides an overview of current definitions of Fintech, and
identifies key milestones in the existing discourse.
Taking a historical perspective, Arner et al. (2016) states that the term Fintech can be traced
back to Citigroup’s“Financial Services Technology Consortium,”an industry initiative from the
1990s, while Schueffel (2016) explains that the term Fintech was coined in 1972 as “an acronym
which stands for financial technology, combining bank expertise with modern management
science techniques and the computer”(Bettinger, 1972, p. 62). Both Citigroup’sandBettinger’s
(1972) understanding of Fintech emerged during the second half of the twentieth century, a time
when industry incumbents (i.e. banks) began to apply information technology to realize cost
savings and maximize profits of their operations (Basole and Patel, 2018).
Gomber et al. (2018) introduces the term “digital finance”to describe the digitalization of the
financial industry from an incumbent’s perspective. And while the term Fintech initially
emerged to describe how incumbents in financial services used a range of information
technologies to make their existing offerings more efficient, more cost effective or more
Author(s) Definition Key hallmarks
Bettinger
(1972, p. 62)
Fintech is an acronym which stands for financial
technology, combining bank expertise with modern
management science techniques and the computer
Focus on incumbent,
sustaining innovation
Micu and Micu
(2016, p. 380)
Fintech is a new sector in the finance industry that
incorporates the whole plethora of technology that is used
in finance to facilitate trades, corporate business or
interactions and services provided to the retail consumer
Focus on new market entrant,
disruptive innovation
Maier
(2016, p. 143)
New businesses (that) aim to challenge existing financial
institutions by using technology to deliver value to the
customer in an alternative way
Focus on new market entrant,
disruptive innovation
Jun and Yeo
(2016, p. 159)
Recent advances in information and communications
technology (ICT) have led to the rapid development and
expansion of new and innovative financial services, often
termed Fintech
Focus on new market entrant,
disruptive innovation
Kim et al.
(2016, p. 1058)
Fintech is a service sector which uses mobile-centered IT
technology to enhance the efficiency of the financial system.
It …refers to industrial changes forged from the
convergence of financial services and IT
Focus on new market entrant,
disruptive innovation
Gimpel et al.
(2018, p. 247)
Fintech characterizes the usage of digital technologies such
as the internet, mobile computing, and data analytics to
enable, innovate, or disrupt financial services
Focus on new market entrant
and industry incumbent
Basole and
Patel (2018, p. 1)
Services traditionally offered by incumbents are now
rapidly unbundled by a growing set of start-ups, leading to
new models of collaboration and a significant shift in power
Focus on new market entrant,
disruptive innovation
Schueffel
(2016, p. 15)
Fintech is a new financial industry that applies technology
to improve financial activities
Focus on new market entrant,
disruptive innovation
Gomber et al.
(2018, p. 540)
Fintech refers to innovators and disruptors in the financial
sector that make use of the availability of ubiquitous
communication, specifically via the internet and automated
information processing. Such companies have new business
models that promise more flexibility, security, efficiency,
and opportunities than established financial services
Focus on new market entrant,
disruptive innovation
Table I.
Existing Fintech
definitions
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customer centric (Dapp et al., 2014), Philippon (2016) provides an alternative viewpoint which
asserts that Fintech should be conceptualized using characteristics similar to disruptive
innovations (Christensen, 2006). Following this perspective, the term Fintech encompasses a
“new sector in the finance industry”(Micu and Micu, 2016, p. 380), characterized by
“innovators and disruptors”(Gomber et al., 2018, p. 540), who typically emerge in the form of
new market entrants, including dedicated start-ups, or even technology companies previously
unaffiliated with financial services like Apple (Gimpel et al., 2018), thus resulting in “new
models of collaboration and a significant shift in power”(Basole and Patel, 2018, p. 1).
The perspective of Fintech as disruptive new market entrants further suggests that, unlike
industry incumbents, Fintechs are able to unbundle financial service offerings through new
technologies because they are unaffected by legacy systems, regulatory constraints and
typically display a higher willingness to take on risk (Kumar, 2016). To this end, Philippon
(2016) found that the cost of financial intermediation in the USA remained constant at
approximately 2 percent of each transaction for the past 130 years, and that potential
technology-driven cost savings have not been passed through to customers by industry
incumbents. Thus, Fintechs offer identical value propositions as banks, but at lower cost.
Today, new market entrants compete in the tightly regulated, and previously unattainable,
financial service market (Muzellec et al., 2015). This has altered the former perception of Fintech
as a type of incremental innovation used by industry incumbents (Basole and Patel, 2018), to one
where the dominant emerging definition of Fintech is as a type disruptive innovation by new
market entrants that challenge the position of mainstream financial institutions.
Despite the increasing interest in Fintech, empirical studies are just emerging
(e.g. Breidbach and Ranjan, 2017). Unfortunately, this means that theoretical insights and
managerial guidelines are limited (Zhang et al., 2016). We aim to address this gap in
knowledge by delineating a theoretically and managerially relevant service research agenda
related to Fintech by using a “use-inspired”research philosophy (Stokes, 1997).
3. Methodology
Use-inspired research philosophy
The role of science in society today is shifting from discovery-oriented “basic”research, which
focuses on pure knowledge creation, to one where research is aligned with specific socioeconomic
needs, including managerial challenges (Tijssen, 2018). Such “use-inspired”research is not to be
mistaken for “applied”research, which is inherently motivated by commercial outcomes,
technology development or business interests. Instead, any scientific inquiry prescribing to the
“use-inspired”research philosophy aims to be discovery-oriented and theoretically grounded but
is, unlike basic research, equally user oriented in that it addresses a real-world phenomenon,
socioeconomic need or managerial challenge –like the digital transformation of financial services
(Stokes, 1997). As such, “use-inspired”research aims to shape the co-evolution of science and
managerial practice, and does so, for example, by developing long-term research agendas that
represent application-oriented work for managerial and theoretical impact (Tijssen, 2018).
Investigating Fintech from a use-inspired angle is an emerging area of inquiry for service
science. Prescribing to the use-inspired research philosophy necessitated that we initially
identified real-world managerial challenges associated with Fintech, before delineating a
research agenda for service science that extends extant literature and provides pathways to
address the challenges identified. We followed the precedence set by Lim and Maglio (2018),
and identified managerial challenges associated with Fintech, using a four-step text-mining
approach. Figure 1 provides an overview.
Data collection
We identified and downloaded general press and practitioner articles related to Fintech
using the LexisNexis database (Step 1 in Figure 1). Specifically, we searched for articles
Financial
service
systems
published between January 1, 2016 and July 12, 2018, querying for “ATLEAST5 ( fintech)
AND (platform) AND (business) AND (consumer)”in the “Business & Industry News”
section of LexisNexis. The decisions underpinning this query were based on Zavolokina
et al. (2016), who found that the term “Fintech”gained substantial trajectory from 2016
onwards, thus representing the key period where we expected relevant managerial
challenges to be discussed for further inquiry. We downloaded 2,118 articles, but removed
573 duplicates published in multiple outlets, thus resulting in a text corpus of 1,545 articles
or 2,394,641 words for analysis.
Data pre-processing
Text pre-processing (Step 2 in Figure 1) aimed to prepare the text corpus for subsequent
analysis by removing any potential sources of bias. It involved eliminating “stop words”
(e.g. “it,”“and”or “for”), any words containing letters not found in the alphabet, changing all
text to lowercase (e.g. from “Fintech”to “fintech”), lemmatizing all words (e.g. from
“processes”to “process”), as well as customized rules (e.g. we deleted words commonly used
in business news articles, but that are non-contextual, such as “Inc.”and “Corp.”). We then
focused on word-feature selection. Words in a corpus of business news publications can be
categorized into the three types: specific words developed by the authors or specific
companies, such as acronyms and business names; contextual words relevant to the topic,
such as “financial,”“bank”or “payment”; and general words frequently used in business
publications, such as “operational,”and in English documents, such as “within”and “over.”
Word-feature selection requires the inclusion of Type 2 words and exclusion of Type 1 and 3
words. Based on the algorithm and metric proposed by Lim and Maglio (2018), we
eliminated Types 1 and 3 words from the original data set, and identified Type 2 words
representing Fintech.
Data analysis
We applied spectral clustering (Von Luxburg, 2007), which is based on graph partitioning
and uses Laplacian matrices, to identify key topics that are representative of managerial
challenges common in Fintech. We used the mean of Silhouette Coefficient values
(Rousseeuw, 1987) of the entire data to determine the number of clusters in the text corpus.
In interpreting each cluster (Step 3 in Figure 1), we used the non-negative matrix
factorization (NMF) (Lim and Maglio, 2018; Lin, 2007), to identify words representative of
each cluster, and interpreted results using Longabaugh’s (2012) visualization method. Step 3
in Figure 1 shows a binary adjacency matrix. Each cluster is highlighted by a yellow square.
1Collection of text big data on
the topic in question
Semi-automatic semantic identification
of significant word-features
Unsupervised learning of the
data with selected word-features
Interpretation
Managerial issues of digital financial services
1. Improving the value proposition of industry incumbents with Fintech
2. Managing sharing economy and P2P Fintech solutions
3. Categorizing new B2C Fintech solutions
4. Implications of cryptocurrencies
5. Categorizing ICTs as enabler of Fintech
6. Regulating Fintech to constrain or facilitate innovation
7. Managing Fintech incubators and startups
Topic 12: Blockchain
Blockchain
Technology
Fintech
Business
Service
Transaction
Platform
Cryptocurrency
Security
Payment
Blockchain
Technology
Fintech
Business
Service
Bank
Bitcoin
Transaction
Security
Payment
1,545
×
36,283
1,545
×
382
Top words by the five
metrics (Lim and Maglio, 2018)
Top words by the NMF topic
modeling (Pedregous et al., 2011)
2
3
4
43
21
Figure 1.
Data collection and
analysis process
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The density of each cluster indicates the level of homogeneity (i.e. text similarity), whereas
its size indicates the amount of data. We subsequently validated the outcome from spectral
clustering (i.e. hard clustering) using the Latent Dirichlet Allocation (Blei et al., 2003) and
NMF topic modeling algorithms (i.e. soft clustering) to check if any topics were missed by
the analyses. This was not the case.
Finally, we identified 27 unique topics in our text corpus associated with Fintech and
the digital transformation of financial services. We categorized these into six high-order
managerial challenges, thus highlighting the challenges with Fintech faced by
practitioners and society more broadly. In this process, we excluded the three topics of
general financial news as these are non-Fintech specific, namely, “company report,”“event
report”and “market report.”The selection of six categories was based on an iterative
process involving all authors. Specifically, we followed Kandampully et al. (2014), where
authors grouped topics, before giving consideration to delineating further service research
priorities in a Delphi-like process of reclassification until agreement was reached. Table II
provides an overview.
4. Analytical framework and research directions
We now delineate an analytical framework to theoretically underpin and structure our RDs,
and to highlight the link between empirical data (i.e. managerial challenges pertaining to
Fintech), and the extant literature. Specifically, our framework integrates prior work
associated with technology-enabled service (Breidbach et al., 2018), the role of individual
actors in service exchanges (Storbacka et al., 2016) and the microfoundations of value co-
creation (Barro, 1993; Conduit and Chen, 2017; Kleinaltenkamp et al., 2017), thus culminating
in three complementary perspectives and level of abstraction (see Figure 2).
First, at the micro level, we consider the ways in which Fintech is used as a tool for
managing service system complexity. All service systems are complex configurations
of people, information, organizations and technologies that create value together
(Maglio et al., 2009). This is especially true for financial services and Fintech, where
new technology-enabled value co-creation processes shape new customer experiences by
connecting previously distinct digital, physical and social realms (Bolton et al., 2018; Briscoe
et al., 2012). The issue of system complexity becomes particularly prominent as industry
incumbents like banks or insurances aim to improve their value propositions with
technology which, in turn, may further perpetuate complexity. For example, industry
incumbent ANZ Bank responded to new Fintech platforms allowing millennials to become
micro-level property investors (e.g. by purchasing small percentages of existing physical
dwellings), by acquiring these new market entrants in an attempt to reduce the intensity of
its competitive environment. Other technological advances used to manage system
complexity include the collection of data for efficient decision making (Lim and Maglio,
2018), or the automatic assessment of a prospective customer’s credit worthiness, borrowing
capacity or automated stock purchasing and selling.
Second, at the meso level, we explore the orchestration of value co-creation through the
lens of resource configuration. The role of service orchestrators (usually human) can be
distinguished from the practice of service orchestration, which may be accomplished by
technology (Breidbach et al., 2016). In this way, the concept of service orchestration
resembles network orchestration, which is defined as the process of assembling and
managing an inter-organizational network to achieve a collective goal (Paquin and
Howard-Grenville, 2013), where the legitimacy of different roles are only established when
accepted by other network members (Müller-Seitz, 2012). As industry incumbents in the
financial service industry aim to improve their value propositions through Fintech, matters
of orchestration of value co-creation processes with and between customers become
relevant. This is especially true as new Fintech solutions like cryptocurrencies or financial
Financial
service
systems
Managerial
challenge Description
Relevant topics identified
from the 1,545 articles
Improving the
value proposition
of industry
incumbents with
Fintech
The attempt to alter traditional financial services with
technology by industry incumbents as a response to the threats
of disruptive new financial services. However, the rapid speed
of technological advancement and the limitations of existing
regulations make it particularly difficult for industry
incumbents to improve existing value propositions. Examples
include insurances aiming to benefit from blockchain, banking
services with Chatbots, or credit cards with the quick response
(QR) codes
Insurance, banking, credit
union
Managing P2P
Fintech
operations
New peer-to-peer (P2P) services emerge that aim to better
connect customers, for example, through online lending
platforms. However, lending is not restricted to money, but
includes real estate, and the sharing economy more broadly.
Substantial questions remain unresolved, such as if
individual customers should be given the autonomy to set
interest rates on loans, select the borrower and lenders, or
how to assess the quality of shared assets
Online lending platform
Developing new
B2C Fintech
solutions
New financial services in the business-to-customer (B2C)
context emerge, for example, mobile payment solutions or
retirement planning services. However, many of these new
services are in an experimental stage. Competing against
traditional incumbents is challenging for new market
entrants, not only because of the competition, but also due to
the inertia of customers. For example, start-ups develop new
payment solutions to help consumers make payments in a
mobile and secure way, but struggle when introducing their
solutions to existing markets
Mobile payment solution,
asset management and
retirement plan, Fintech
service in general, new
business
Managing the
proliferation of
cryptocurrencies
New cryptocurrencies promise to enable and increase the
efficiency and security of digital financial transactions, and
to fundamentally change financial markets by removing the
need for governments as issuers of legal tender, as well as
that of banks as financial intermediaries. However, given the
importance of currencies as mediums for economic exchange
in any economy, identifying the boundary conditions to
govern and regulate the appropriate use of cryptocurrencies
has become one of the most critical challenges in financial
services to date
Cryptocurrency
Regulating
Fintech to
constrain or
facilitate
innovation
Financial regulations differ across countries, especially as
they relate to new technologies. All financial institutions
face, and should be able to deal with, a degree of uncertainty
within a local or global regulatory environment. However,
the development of appropriate Fintech regulations is
challenging, especially since regulators generally do not
keep up with technological developments. This regulatory
vacuum makes it difficult to facilitate innovation and to
ensure market performance
Federal regulation,
regulation in more general,
financial services in the
UK, Fintech in Singapore/
Abu Dhabi/China/Hong
Kong
Managing
Fintech
incubators and
start-ups
Fintech start-ups operate in a rapidly changing context.
However, uncertainties arise from the rapid development of new
technologies and the conservative development of regulations.
This impacts new market entrants more so than industry
incumbents. New approaches are needed to foster the incubation
and support of Fintech start-ups, especially considering the
unique contexts of different countries and regions
Fintech start-ups, Paribas,
Finastra, Yapstone
Table II.
Managerial challenges
mapped to topics
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planning software emerge in business-to-customer (B2C) contexts, while crowdfunding
(Shah and Shah, 2017), humanoid robots (SoftBank Robotics America, 2018) or automatic
fraud detection (Wozniak, 2016) emerge in B2B contexts. Service orchestration, therefore,
responds to the increased complexity of service operations by facilitating resource
integration, and thereby value co-creation between other interdependent actors
(Breidbach et al., 2016).
Third, at the macro level, we consider the need for elastic infrastructure and market
conditions that facilitate and support Fintech, especially their emergence in incubators and
start-ups. Elasticity describes the extent to which the relationships among actors and
resources within service systems are interdependent, exchangeable and flexible (Moldovan
et al., 2018). Breidbach et al. (2018) argue that elasticity represents a critical capability when
managing service ecosystems where the goal is to optimize an ecosystem as a whole, rather
than optimizing individual processes and sub-systems. Elasticity, therefore, views Fintech
platforms, enabled by smart devices, hybrid computing, and adaptive, autonomous and
intelligent systems, as environments for value co-creation, with traditional boundaries
among computers, people and things increasingly blurred. Elasticity can be viewed in terms
of three core dimensions –resource elasticity, cost elasticity and quality elasticity (Dustdar
et al., 2011). Resource elasticity concerns processes used to allocate human and computing
resources to achieve desired needs. Cost elasticity concerns the trade-off between cost and
efficiency. Quality elasticity concerns decisions that contribute to the effectiveness of the
ecosystem given available resources.
In what follows, we apply our analytical framework to the managerial challenges
associated with Fintech and the digital transformation of financial services that we identified
through our text-mining approach. By comparing these managerial challenges with emerging
Elastic infrastructure, models and markets
Orchestration of value co-creation
Macro
Meso
Micro
Financial infrastructure, models and markets
Insurance
Banking Retirement plan
Payment solution
Fintechs for value co-creation
Blockchain Cloud platform
Artificial
intelligence
Actors Service firm A
Service firm B
Service firm C
Credit union …
…
…
Managing service system complexity
Figure 2.
Analytical framework
to explore
digital financial
service systems
Financial
service
systems
service research priorities (e.g. Ostrom et al., 2015) and other relevant perspectives (e.g.
Breidbach et al., 2018; Lim, Kim, Kim, Heo, Kim and Maglio, 2018; Lim, Kim, Kim, Kim and
Maglio, 2018), we delineate a use-inspired agenda for future service research addressing the
key challenges associated with Fintech. Table III provides an overview.
Research directions to improve the value proposition of industry incumbents
Industry incumbents like banks, insurances or credit unions attempt to alter their traditional
financial services with technology in response to new disruptive Fintech offerings. However,
the rapid speed of technological advancement and established organizational structures
make this challenging, thus opening up substantial research opportunities.
RD 1: understanding customers through big financial data. Today, massive amounts and
varied kinds of data are collected from individual customers, and have emerged as a key
variable in digitized financial service systems (Atzori et al., 2010). The proliferation of (big)
data resulted in financial services where data use and artificial intelligence provide
significant new opportunities for value creation, such as data-driven insurance (OECD,
2018) and automatic trading (Ferrara et al., 2016). Yet, despite such widespread application
in practice, academic insights into the wider implication of data-driven financial services are
largely limited. Prior studies related to use of customer data are mostly focused on
identifying the behavioral patterns (Lim et al., 2019) or recommendable items (Lee and
Pilkington, 2017), with little or no attention given to actively understanding the consumer’s
financial preferences, needs and overall financial well-being. Such understanding would
require an integration of data on financial service experience and spending patterns. We
argue that future research related to a customer’s financial well-being could benefit from
insights in other service contexts such as hospitality and healthcare, which have typically
human well-being, rather than organizational profit motives in mind (Kandampully et al.,
2014). This is especially true since financial data from electronic purchases enable
Levels of aggregation
Managerial challenge
Managing complexity of
digital financial service
systems
Orchestration of value
co-creation with Fintech
Developing elastic
infrastructure, models and
markets
Improving the value
proposition of industry
incumbents with Fintech
RD 1: understanding
customers through big
financial data
RD 2: understanding
open data for value co-
creation
RD 3: understanding
changing role of traditional
financial intermediaries
Managing P2P Fintech
platform operations
RD 4: integrating multi-
platform services
RD 5: advancing
platform orchestration
RD 6: explore platforms and
markets in specific countries
Developing new B2C
Fintech solutions
RD 7: managing the
quality of digital
financial services
RD 8: understanding
new value creating
resource configurations
RD 9: understanding hybrid
Fintech business models
Managing the
proliferation of
cryptocurrencies
RD 10: facilitating the co-
creation of value without
intermediaries
RD 11: understanding
value co-creation with
cryptocurrencies
RD 12: cryptocurrency as
elastic infrastructure of
financial services
Regulating Fintech to
constrain or facilitate
innovation
RD 13: regulating value
co-creation processes
without intermediaries
RD 14: regulating
financial institutions
RD 15: managing the
deregulation of financial
systems
Managing Fintech
incubators and start-ups
RD 16: designing
customer-centric Fintech
services
RD 17: designing
communities of practice
RD 18: developing support
systems for SMEs
Table III.
Research directions
mapped to managerial
challenges and level of
aggregation
JSTP
institutions to “map”the entire life of customers, their behavior, as well as personal
preferences. As such, new questions related to the ethical implications of data analytics arise
that service research to date has not adequately addressed (Breidbach et al., 2019).
RD 2: understanding open data for value co-creation. Uncertainties resulting from novel
interactions of things, network elements, cloud resources, as well as humans create challenges
for complex Fintech service systems. To improve governance in this context, Nastic et al.
(2015) introduced a declarative policy language to simplify the development of rules to control
uncertainty. A key enabling requirement for this capability is agreement on open data
standards that are driving the open banking initiatives, which will provide financial
institutions access to even more sources of customer data. However, for Fintech platforms and
incumbents alike, constrained and inaccessible data are the key barrier to the development of
new data-driven value propositions, service innovations and new approaches to value co-
creation. Beyond the question of access, future research is needed to develop a universally
accepted ontology for the format of Fintech data, to ensure the seamless transfer of
information between humans and things across institutional and national borders. Blockchain
technologies would appear to provide a very promising line of enquiry in this regard, as the
technology presents an opportunity to ensure data integrity while limiting self-interest and the
potential for restriction of institutional and government intervention.
RD 3: understanding changing role of traditional financial intermediaries. The reliability,
security and privacy of interactions within systems need to be managed as the roles and
boundaries of financial intermediaries change due to advances in technology (Lim, Kim, Kim,
Kim and Maglio, 2018). However, while the need to manage financial security and risk can
result in inefficient service operations and unnecessary transaction costs, emerging
technologies such as blockchain have the potential to reduce these. Technology thereby
increases the efficiency of service systems by enabling direct and secure interactions among its
actors through the removal of traditional intermediaries (Risius and Spohrer, 2017). From its
initial application in cryptocurrencies (Nakamoto, 2008), it is possible to see how blockchain
can substantially reduce the complexity and inefficiency in service systems, and dramatically
change the landscape of Fintech services (Guo and Liang, 2016). However, in the new context of
P2P value co-creation enabled by blockchain, the important key question that arises is where
does the traditional financial service firm and the traditional accredited intermediary fitinto the
future of Fintech? Traditionally, in disconnected networks with centralized intermediaries (e.g.
banks), customers depended on the economic activities and role of firms. Therefore, improving
the operations of firms was important to gain efficiencies and competitive advantage. However,
as Fintech enables the emergence of connected, decentralized service systems, the benefits of
such operational dependency are diminishing, thus raising the question of how incumbents
may facilitate value co-creation without operations (Breidbach et al., 2018).
Research directions to manage P2P Fintech platform operations
New P2P financial services aim to better connect economic actors. Today, P2P Fintech
platforms offer value propositions ranging from lending to real estate investment,
insurances, and are affiliated with the sharing economy more broadly (Breidbach and
Brodie, 2017). This raises a number of new challenges and research opportunities.
RD 4: integrating multi-platform services. Managing the operations of service systems
requires users to understand the needs of multiple stakeholders (Maglio and Breidbach, 2014),
even when their needs are hard to model and study. The complexity of digital financial service
systems, in particular, is reflected in the physical, informational and interpersonal interactions
among people, organizations and technologies (Glushko, 2010). In this respect, resource
integration and resource exchange is not always constrained to single platforms, but requires
the effective integration of multiple physical and virtual platforms that, collectively, form
Financial
service
systems
engagement ecosystems (Breidbach et al., 2014; Breidbach and Brodie, 2016). Future research
is needed to identify and understand the role of different platform archetypes and, in
particular, co-created value as a distinct outcome within complex service ecosystems.
Ultimately, such work could help improve service design processes (Patrício et al.,2011),but
also add to the understanding of technology-enabled value co-creation processes more broadly
(Breidbach and Maglio, 2016) at a time when organizations without any banking background
(i.e. Apple) are shifting into the financial service space.
RD 5: advancing platform orchestration. Value co-creation in digital financial service
systems set in P2P contexts is characterized by the multi-level, multi-agent and multi-disciplinary
nature of such interactions (Maglio and Spohrer, 2008). In addition, any value co-creating
activities between actors using P2P platforms needs to be orchestrated by the firm or platform
owner. In this context, business marketing and organizational studies typically refer to
organizational stakeholders (lead firms, hub firms, etc.) when discussing orchestration activities.
Research on orchestration of intentionally created networks (i.e. Fintech platforms) assumes that
the firm is able to purposefully influence and manage interactions within the network (Müller-
Seitz, 2012), that is, orchestrating value co-creating interactions of other actors through deliberate
activity. This perspective, therefore, resonates with studies of networks that adopt an actor-
defined perspective, such that a central network actor strives to configure its business
relationships through networking activities (e.g. Perks et al., 2017). Prior service research
investigated the roles of dedicated employees targeted with orchestrating value
co-creation in contexts like consulting (Breidbach and Maglio, 2016). However, no contribution
to date has explicitly described or explored the role of service orchestrators, or the practice of
service orchestration within financial services. Beyond the role of the orchestrator, organization
studies have also identified several orchestration processes that contribute to value creation
within complex service systems, including the management of knowledge mobility, innovation
appropriability, innovation leverage, innovation coherence, network membership and network
stability (Dhanaraj and Parkhe, 2006; Nambisan and Sawhney, 2011). Effective orchestration
requires processes and institutional arrangements that enhance the ease with which stakeholders
can access the knowledge and expertise of others (Kale et al., 2000), promote the equitable
distribution of costs as well as benefits (Teece, 2000), and preserve the stability of the network
(Kenis and Knoke, 2002). These practices and processes are equally applicable to Fintech
platforms, and we encourage future service researchers to explore them.
RD 6: explore platforms and markets in specific countries. Financial services are inherently
context dependent. The main factor influencing existing and prospective value propositions is
the regulatory and cultural environment in which the service takes place. We therefore
encourage future service researchers to engage in cross-country comparisons, as well as to
conduct in-depth case studies from different cultural and regulatory environments. As such,
future studies could help governments manage the change processes, develop new regulatory
frameworks and enable successful foreign market entries. For example, developing
regulations for cryptocurrencies and AI is a critical and controversial issue, because individual
nations have adopted vastly different approaches. As a case-in-point, some European
countries are open to cryptocurrencies, the South Korean Government takes a conservative
stance, but Venezuela recently launched its own cryptocurrency, the “petro,”to overcome
domestic economic challenges and hyperinflation of its current currency, the “bolivar.”The
wider implications of these policies, however, are unknown, and sufficient managerial
recommendations or governance frameworks are unavailable to date.
Research directions to develop B2C Fintech solutions
New financial services in the B2C context include, for example, mobile payment
solutions or retirement planning services. Competing against traditional incumbents is
JSTP
challenging for new market entrants, not only because of the competition, but also due to
the inertia of customers. This managerial set of challenges represents a significant service
research opportunity.
RD 7: managing the quality and experience of digital financial services. Finding ways to
improve service quality and customer experiences remains one of the most important
research priorities in service research (Ostrom et al., 2015), particularly in the area of
financial services where image has been shown to be influenced by quality perceptions
(Saleh et al., 2017). Various studies have addressed quality issues of multiple types of service
(e.g. Ladhari, 2010; Parasuraman et al., 1988), typically by comparing customer expectations
with perceptions of outcomes and actual experiences. However, despite the rapidly changing
context of digital financial service systems, insights related to the quality of digital financial
services, either Fintech based, or rooted in traditional services improved by technology, are
rare. For example, more research is required to investigate customer perceptions of
emerging technologies such as cryptocurrency. The same is true for Fintech applications in
ecommerce, such as mobile payment solutions (Gai et al., 2018). Today, we can observe how
mobile apps like WeChat integrate purchasing and payment in a single-stop solution.
However, their use, shifting adoption and influence especially in cross-cultural contexts
from China to the western world remain largely uninvestigated. Another phenomenon in the
ecommerce space is novel credit-offerings like Afterpay that effectively offer customers
instant consumer credits. All of these technological developments provide ample
opportunities to investigate how customer experiences of digital financial services can be
improved and managed, and how organizations adopt and change their business models
(Lee and Shin, 2018). In addition, further research is needed to understand, evaluate and
eventually improve blockchain-enabled P2P financial services, including matters of trust
from the perspective of customers. To address such research questions, future researchers
may need to develop new measurement models that better reflect the service setting, and
move beyond simple dyadic conceptualizations of service exchange.
RD 8: understanding new value creating resource configurations. In keeping with the
actor-resource perspective, future research is needed to understand how actors balance their
self-interest against the needs of other actors, and importantly, how individual actors
configure resources provided by the digital financial services ecosystem to design new value
creating resource configurations. Examples for actors may include traditional banks, start-
ups, government institutions, organizational customers and individual consumers (Lee and
Shin, 2018). Examples for resources may include big financial data sets from various
sources, systems for data collection and management, artificial intelligence for data
analytics and service content generation, telecommunications networks, and application
systems for service content delivery (Lim, Kim, Kim, Heo, Kim and Maglio, 2018). Another
important issue to understand is how the multiple forms and mechanisms for resource
configuration emerge, and are used. As such, future service research should to consider how
Fintech platforms contribute to customer satisfaction and customer involvement in value
co-creation using newly available financial data, thus contributing to operational efficiency
and productivity of financial service firms.
RD 9: understanding hybrid business models. Digital financial service systems are
cyber-physical systems. There have been attempts to emphasize the need to move beyond the
human computing view where humans conceive and direct machines to control outcomes
(Copil et al., 2013). While humans define the rules and norms in connected Fintech systems
today, in the future, the various levels of connectivity among actors, as well as the rules and
laws of their interactions are likely to be managed and controlled by machines thus realizing
new and unexpected value propositions (Breidbach et al., 2013). In this sense, Fintech enables
the emergence of new value propositions via elastic reconfigurations of existing resources
Financial
service
systems
(Copil et al., 2013). Ultimately, we expect this to result in new business models that not only
traditional market incumbents, but also Fintech start-ups employ in existing and entirely new
financial services markets. For example, while banks traditionally focused on the provision of
loans, savings accounts or mortgages, transaction processing charges have grown to
represent an increasingly important part of their revenue model. Future research is needed to
explore new business models that are less reliant on transaction costs because it is unlikely
that these will continue to reside within the domain of financial service firms in the future.
There is also scope for new socially oriented business models where emerging technologies
are used as tools for greater democratization of financial services, thus representing an
opportunity for our discipline to provide further contributions to the transformative service
research discourse. Similar to previous studies on internet-based e-commerce business models
in early 2000s (e.g. Mahadevan, 2000; Lee, 2001), we encourage service researchers to explore
emerging business models associated with Fintech.
Research directions to manage the proliferation of cryptocurrencies
Cryptocurrencies ranging from Bitcoin to Ether are fueled by Blockchain technology and smart
contracts (Risius and Spohrer, 2017) that promise to increase the efficiency and security of digital
financial transactions, and to fundamentally change financial markets by removing the need for
intermediaries –be it governments as issuers of legal tender, or banks as brokers of currency.
However, identifying the boundary conditions to govern and regulate the appropriate use of
cryptocurrencies has become one of the most critical challenges in financial services to date.
Exploring their wider role and impact represents a significant research opportunity.
RD 10: facilitating the co-creation of value without intermediaries. Traditional financial
services like insurances, banks or credit unions have operated in a previously unchallenged
market environment. However, the evolution of Fintech is challenging their current role as
intermediaries. Today, cryptocurrencies and blockchain technologies have the potential to
make banks, insurances and credit unions as institutional intermediaries obsolete, and to
remove them from the market altogether. Bitcoin is the most prominent cryptocurrency
today (Nakamoto, 2008). Its inventor, Satoshi Nakamoto, aimed to challenge financial
institutions, stating: “what is needed is an electronic payment system based on
cryptographic proof instead of trust, allowing any two willing parties to transact directly
with each other without the need for a […] third party”(p. 1). Cryptocurrencies and
blockchain technologies enable direct and secure interactions among peers in financial
service systems, which changes the context of value co-creating interactions, the roles of
actors therein, their perceptions of these processes (i.e. engagement with a brand), and
thereby provides ample opportunities for service research to re-assess the foundational
premises of value co-creation by questioning patterns of resource integration and resource
exchange in service systems (Khaitan, 2017; Yurcan, 2017). In this context, new
opportunities exist to investigate P2P markets for cryptocurrencies (Mild et al., 2015), or the
intersection of crowdfunding –a precursor to systems without intermediaries –and
cryptocurrencies (Ordanini et al., 2011).
RD 11: understanding value co-creation with cryptocurrencies. Despite Bitcoin’s recent
rise to prominence, the important question of how actors co-create value in
cryptocurrency-enabled service systems remains unanswered. Early work by Beck and
Müller-Bloch (2017) provided insights through a case study of industry incumbents, but the
roles of customers as co-creators of value in cryptocurrency-enabled service systems remain
an entirely unexplored area to date. This is a fundamental problem because understanding
customer roles is considered a necessary prerequisite when attempting to explore digital
transformation processes more broadly (Lusch and Nambisan, 2015). Future research could
address this question by utilizing service-dominant logic (i.e. Vargo and Lusch, 2008), which
JSTP
provides an explanation of the factors driving customer value co-creation in financial
services associated with cryptocurrencies that minimize and change the role of traditional
intermediaries. Future studies should equally investigate the transformational drivers of
cryptocurrencies for Fintech platforms and industry incumbents. Potential areas of interest
include the development of new value propositions, service innovations or challenges
industry incumbents face through cryptocurrencies (Tana et al., 2019). In this context, the
key question to investigate will be how cryptocurrencies impact the intermediary role many
financial service providers currently perform. It will be important to understand whether or
not new cryptocurrency-enabled services represent a sufficient substitute to maintain
current market positions, or if entirely new value propositions are needed.
RD 12: cryptocurrencies as elastic infrastructure of financial services. Physical currencies
issued by governments or other political rulers have enabled economic exchange for
thousands of years. The emergence of cryptocurrencies has changed this paradigm by
removing the need for any government or other centralized intermediary to act as a
guarantor of trust and stability. As such, for the new context of future digital financial
services, a critical RD is to develop knowledge about how cryptocurrencies function as an
elastic infrastructure of financial services. For one, future studies may address how
cryptocurrencies overcome the limitations of physical and digital currencies. Here, future
studies should aim to provide managerial relevant insights related to the implementation,
use and eventual transformation of financial service systems. This includes answering
questions ranging from trust in cryptocurrencies, use cases, their scopes of economic
exchange to the development of new service innovations that facilitate elasticity of
resources, costs and quality (Dustdar et al., 2011).
Research directions to regulate Fintech and manage innovation
Financial regulations differ across countries, especially as they relate to new technologies.
All financial institutions face, and should be able to deal with, a degree of uncertainty within
a local or global regulatory environment. However, the development of appropriate Fintech
regulations is challenging, especially since regulators generally do not keep up with
technological developments. This regulatory vacuum makes it difficult to facilitate
innovation and to ensure market performance. Future research is therefore needed to
address this challenge.
RD 13: regulating value co-creation without intermediaries. Regulations are particularly
important in the financial service industry because of its importance to economies. In the
USA, the current debate is centered over the question of whether federal regulations
should address the rapidly changing context of financial service system at all (Clozel,
2017; Vartanian, 2016), while the Royal Commission in Australia has taken a much
tougher stance on the financial services sector altogether. Any regulation therefore first
depends on the specific context of a country. However, all financial regulations are
necessarily incomplete and must be altered whenever new technologies and paradigms
emerge. In particular, our findings indicate that current regulations do not adequately
address recent technological advances associated with Fintech. Any service innovation
efforts are thus being hindered by the slow pace of regulatory change. This requires
financial service firms and Fintech start-ups to adhere to outdated regulations based on
historic notions of financial markets and exchange. New regulations are therefore needed
to prevent unexpected problems, and to facilitate innovation in financial services.
Investigating and devising regulations related to Fintech should therefore be a key
priority for service research.
RD 14: regulation of financial institutions. The cost of leveraging knowledge and
resources increases as service systems grow (Iansiti and Levien, 2004). Consequently,
Financial
service
systems
more effective processes are needed to ensure openness and transparency when sharing
information (Lorenzoni and Lipparini, 1999), and when managing the coherence and
coordination of actors across the system. Such coordination can be facilitated via
institutional processes and formal agreements; however, in some cases regulatory
intervention may be required. This is especially true when the incentives of some actors
are diametrical to the needs of others (i.e. profit interests of banks vs financial well-being
of customers). And while there has been considerable attention given to the
over-regulation of traditional financial institutions vis-à-vis new Fintech start-ups,
further research is needed to understand both the need for regulation of Fintech platforms
and how regulation facilitates and hinders the orchestration of value, as well as innovation
in financial services.
RD 15: managing the deregulation of financial service systems. A key consideration for
elastic service systems in the Fintech context relates to the challenge of governance via
task definition and allocation. This is because the design and management of complex
Fintech service systems requires new models of orchestration and governance, since the
roles of computers, people and things are fluid and now better able to capture the
particularities and capabilities of the various elements of the network (Moldovan et al.,
2018). Against this backdrop, technology itself could lead to further deregulation of
financial service markets, as the capacity of technology to govern complex interaction
among actors reduces the need for regulatory intervention by government entities. Future
research is needed to establish the boundary conditions for technology-mediated
regulation. Given that technology like AI is essentially devoid of human bias and self-
interest, a key challenge for future digital financial services research is to advance the
development of the rules of operation, and the security of Fintech service systems to
ensure that they are not subject to manipulation by rules and regulatory advances that are
diametrical to the democratization of financial services.
Research directions to manage Fintech incubators and start-ups
Fintech start-ups operate in a rapidly changing context. However, uncertainties arise from
the rapid development of new technologies and the conservative development of
regulations. This impacts new market entrants more so than industry incumbents.
New approaches are needed to foster the incubation and support of Fintech start-ups,
especially considering the unique contexts of different countries and regions.
RD 16: designing customer-centric Fintech services. The proliferation of new Fintech
ventures aiming to improve human well-being exemplifies the potential and need for
service design to shape currently emerging service systems. For example, dedicated
Fintech lenders now target undocumented Latin American migrant communities who
traditionally could not obtain financial services in the USA due to a lack of credit scores
and social security numbers. Though commercially oriented, these emerging
organizations exemplify how service design research can help resolve real-world
challenges associated with Fintech. This is done by adopting a human-centric perspective
to understand customers, contexts and social practices (Kimbell, 2011), as well as
customer interactions and experiences (Zomerdijk and Voss, 2010). However, we are
particularly concerned with the lack of new service design knowledge associated with
Fintech (e.g. Comuzzi et al., 2018). Indeed, prior work investigated the unique nature of
service design in specific service contexts, such as information-intensive services
(Lim and Kim, 2014), IT-enabled services (Yang and Hsiao, 2009), smart service systems
(Maglio and Lim, 2016), experience-centric services (Zomerdijk and Voss, 2010) or
prevention services (Sandler et al., 2005). And while all of these studies may serve as a
starting point when designing digital financial services, specific challenges associated
JSTP
with Fintech like new business models, failed Fintech ventures, customer value or
customer loyalty are deserving of further investigation, especially as they pertain to the
design of new customer experiences.
RD 17: designing communities of practice. Fintech companies such as PayPal
and Finastra have already generated new value propositions and advanced existing
financial services with technology; moreover, new start-ups like Lendingclub.com are
emerging and continuing to evolve financial service. However, the survival and growth of
start-upsintheFintechareaismoredifficult than ever, due to uncertainties related to
technology and the overly conservative approach regulators have taken. Faced with this
ever-increasing difficulty of orchestration, the need for firms and customers to collaborate
when developing and advancing innovative financial services will become more
important. One collective basis may be the formation of communities of practice.
Prior studies on enterprise networks (Karaev et al., 2007) and consumer networks
(Füller et al., 2008) demonstrate that developing such networks can mitigate the difficulty
of orchestration and promote innovation. Future research investigating networks in
the context of digital financial services can contribute to a better understanding of
value co-creation, but more importantly, the development of the entire new financial
service systems.
RD 18: developing support systems for SMEs. The Fintech innovations that emerged
in recent years have predominantly been driven by start-ups and new market entrants. In
order to advance innovative outcomes related to financial services for society more
broadly, future research is needed to better understand the specific needs of Fintech
start-ups, the drivers of effective incubation for these new service innovators and the
market conditions that lead to growth and survivability. For example, government
support systems for Fintech SMEs can be investigated. Given the economic aspect,
governments play an essential role in managing the financial industry, and in providing
an environment that both encourages and protects fledgling firms as they seek to
establish a foothold in established markets or even create new markets, as is the case with
many Fintech start-ups. Currently, different governments are attempting different
strategies and paths to incubate Fintech SMEs and innovate the financial industry. Case
studies on these projects will be able to fill the current research gap by developing
reference models by identifying key success factors for incubation and innovation. In
addition, future work could adopt the perspective of Fintech entrepreneurs, with future
studies exploring their individual characteristics, motivations and backgrounds to
ultimately delineate new policies intended to support these individuals in their efforts to
disintermediate financial service systems.
Table IV summarizes the key use-inspired research questions identified here.
5. Conclusions
Fintech represents an emerging area of interest for service science. However, the
disciplinary silos, ambiguous definitions, a-theoretical work and disconnect between current
academic research associated with Fintech and managerial practice resulted in a knowledge
vacuum. Though challenging, we see this situation as a unique opportunity for service
research to contribute to the societal understanding of a truly disruptive technological
phenomenon, while also advancing theoretical knowledge in our discipline. This present
work aimed to address the unique challenge of stimulating theoretically and managerially
relevant research by adopting a use-inspired research philosophy. As such, we perceive our
study not as an end, but rather as a starting point toward a novel line of inquiry that
advances knowledge about Fintech and the digital transformation of financial service
systems in service research.
Financial
service
systems
Managerial challenges Key research questions
Improving the value
proposition of industry
incumbents with Fintech
If, how, and to what extent are the value propositions of incumbents like
insurances, banks, or credit union changing in response to Fintech? How could
these be improved to maintain competitiveness?
How can data analytics be used to understand customer’s financial preferences,
needs and well-being? How can these insights be translated into service
innovations and new service experiences?
What data ontology is useful for Fintech and new approaches to value
co-creation today?
How should incumbents as traditional intermediaries in financial service respond
to new decentralized blockchain solutions?
Managing P2P Fintech
operations
How do P2P Fintech platforms evolve and facilitate value co-creation? How should
these processes be managed?
How can firms effectively integrate multiple physical and virtual platforms within
engagement ecosystems for resource exchange and value co-creation?
How does the practice of service orchestration, including the roles of orchestrator and
the processes of orchestration, impact the performance of P2P Fintech platforms?
What are the implications of Fintech policiesacross different cultural and regulatory
environments for operational performance?
Developing new B2C
Fintech solutions
How should mobile payment, asset management, or retirement planning Fintech
solutions designed to improve service experiences?
How can we measure and manage the quality of new digital financial services,
such as AI-based e-commerce and payments?
How do actors (e.g. banks and individual consumers) reconfigure resources
(e.g. financial big data and AI) provided by digital financial services ecosystems?
How do new Fintech-based business models evolve in regard to transaction
costs and societal inclusion? How should these be developed to democratize
financial services?
Managing the
proliferation of
cryptocurrencies
How do different cryptocurrencies evolve? How should their diffusion be managed?
Do patterns of resource integration and resource exchange evolve with
cryptocurrencies that no longer rely on intermediaries? How do cryptocurrencies
challenge roles of traditional intermediaries, such as insurances, banks, or
credit unions?
What are the roles of customers as co-creators of value in cryptocurrency-enabled
service systems? How do new value propositions and service innovations need to be
developed in the context of cryptocurrencies?
Do cryptocurrencies overcome the limitations of physical and digital currencies and
function as a truly elastic infrastructure of financial services, challenging
governments or other political rulers that previously enabled economic exchange?
If so, how do these processes emerge and embody?
Regulating Fintech to
constrain or facilitate
innovation
Investigate if, how, and to what extent governments should regulate Fintech.
How can regulation prevent unexpected problems while simultaneously
facilitating innovation in financial services?
How should governments regulate financial incumbent’s use of new technology
(i.e. data analytics)? Should governments regulate technology that could
democratize financial service systems while continuing to deregulate established
financial service markets?
Managing Fintech
incubators and start-ups
How do Fintech start-ups grow and disrupt financial service markets?
How can firms design customer-centric Fintech services?
How can we utilize and develop the community networks of digital financial
services to mitigate the difficulty of service orchestration and promote innovation?
What are the specific needs of Fintech start-ups, and how should governments
support Fintech SMEs to advance innovative outcomes related to financial
services for society more broadly?
Table IV.
Key research
questions associated
with individual
managerial challenges
JSTP
References
Antons, D. and Breidbach, C.F. (2018), “Big data, big insights? Advancing service innovation and
design with machine learning”,Journal of Service Research, Vol. 21 No. 1, pp. 17-39.
Arner, D.W., Barberis, J. and Buckley, R.P. (2016), “The evolution of Fintech: a new post- crisis
paradigm”,Georgetown Journal of International Law, Vol. 47 No. 4, pp. 1345-1393.
Atzori, L., Iera, A. and Morabito, G. (2010), “The internet of things: a survey”,Computer Networks,
Vol. 54 No. 15, pp. 2787-2805.
Barro, R. (1993), Macroeconomics, Wiley, New York, NY.
Basole, R.C. and Patel, S.S. (2018), “Visualizing the global Fintech ecosystem”,Service Science, Vol. 10
No. 4, pp. 1-18.
Beck, R. and Müller-Bloch, C. (2017), “Blockchain as radical innovation: a framework for engaging with
distributed ledgers as incumbent organization”,50th Hawaii International Conference on System
Sciences,Maui, HI,January 4–7, pp. 5390-5399.
Bettinger, A. (1972), “Fintech: a series of 40 time shared models used at manufacturers Hanover trust
company”,Interfaces, Vol. 2 No. 4, pp. 62-63.
Blei, D.M., Ng, A.Y. and Jordan, M.I. (2003), “Latent Dirichlet Allocation”,Journal of Machine Learning
Research, Vol. 3 No. 1, pp. 993-1022.
Bolton, R.N., McColl-Kennedy, J.R., Cheung, L., Gallan, A.S., Orsingher, C., Witell, L. and Zaki, M. (2018),
“Customer experience challenges: bringing together digital, physical and social realms”,Journal
of Service Management, Vol. 29 No. 5, pp. 776-808.
Breidbach, C., Choi, S., Ellway, B., Keating, B., Kormusheva, K., Lim, C. and Maglio, P. (2018),
“Operating without operations: how is technology changing the role of the firm?”,Journal of
Service Management, Vol. 29 No. 5, pp. 809-833.
Breidbach, C.F. and Brodie, R.J. (2016), “Nature and purpose of engagement platforms”, in Brodie, R.J.,
Hollebeek, L. and Conduit, J. (Eds), Customer Engagement: Contemporary Issues and Challenges,
Routledge, New York, NY, pp. 124-126.
Breidbach, C.F. and Brodie, R.J. (2017), “Engagement platforms in the sharing economy: conceptual
foundations and research directions”,Journal of Service Theory and Practice, Vol. 27 No. 4,
pp. 761-777.
Breidbach, C.F. and Maglio, P. (2016), “Technology-enabled value co-creation: an empirical analysis of
actors, resources, and practices”,Industrial Marketing Management, Vol. 56 No. 7, pp. 73-85.
Breidbach, C.F. and Ranjan, S. (2017), “How do fintech service platforms facilitate value co- creation?
An analysis of twitter data”,38th International Conference on Information Systems,Seoul,
December 10–13.
Breidbach, C.F., Antons, D. and Salge, T.O. (2016), “Seamless service? On the role and impact of service
orchestrators on human-centered service systems”,Journal of Service Research, Vol. 19 No. 4,
pp. 458-476.
Breidbach, C.F., Brodie, R. and Hollebeek, L. (2014), “Beyond virtuality: from engagement platforms to
engagement ecosystems”,Managing Service Quality, Vol. 24 No. 6, pp. 592-611.
Breidbach, C.F., Kolb, D.G. and Srinivasan, A. (2013), “Connectivity in service systems: does
technology-enablement impact the ability of a service system to co-create value?”,Journal of
Service Research, Vol. 16 No. 3, pp. 428-441.
Breidbach, C.F., Davern, M., Shanks, G. and Asadi-Someh, I. (2019), “On the ethical implications of big
data in service systems”, in Maglio, P.P., Kieliszewski, C.A. and Spohrer, J. (Eds), Handbook of
Service Science, Vol. 2, Springer, New York, NY, pp. 661-674.
Briscoe, G., Keränen, K. and Parry, G. (2012), “Understanding complex service systems through
different lenses: an overview”,European Management Journal, Vol. 30 No. 5, pp. 418-426.
Brust, L., Breidbach, C.F., Antons, D. and Salge, T.O. (2017), “Service-dominant logic and information
systems research: a review and analysis using topic modeling”,38th International Conference on
Information Systems,Seoul,December 10–13.
Financial
service
systems
Christensen, C.M. (2006), “The ongoing process of building a theory of disruption”,Journal of Product
Innovation Management, Vol. 23 No. 1, pp. 39-55.
Clozel, L. (2017), “Arrival of final bank regulator could speed up easing of rules”,The Wall Street
Journal, available at: www.wsj.com/articles/arrival-of-final-bank-regulator-could-speed-up-
easing-of-rules-1522143001 (accessed August 20, 2018).
Comuzzi, M., Unurjargal, E. and Lim, C. (2018), “Towards a design space for blockchain-based system
reengineering”, in Matulevicous, R. and Dijkman, R. (Eds), International Conference on Advanced
Information Systems Engineering, Lecture Notes in Business Information Processing, Springer,
Cham, pp. 138-143.
Conduit, J. and Chen, T. (2017), “Transcending and bridging co-creation and engagement: conceptual
and empirical insights”,Journal of Service Theory and Practice, Vol. 27 No. 4, pp. 714-720.
Copil, G., Moldovan, D., Truong, H.L. and Dustdar, S. (2013), “Multi-level elasticity control of cloud
services”, in Basu, S., Pautasso, C., Zhang, L. and Fu, X. (Eds), International Conference on
Service-Oriented Computing, Lecture Notes in Computer Science, Springer, Berlin and
Heidelberg, pp. 429-436.
Dapp, T., Slomka, L. and Hoffmann, R. (2014), “Fintech –the digital (r)evolution in the financial sector”,
Deutsche Bank Research, Frankfurt am Main.
Dhanaraj, C. and Parkhe, A. (2006), “Orchestrating innovation networks”,Academy of Management
Review, Vol. 31 No. 3, pp. 659-669.
Dustdar, S., Guo, Y., Satzger, B. and Truong, H.L. (2011), “Principles of elastic processes”,IEEE Internet
Computing, Vol. 15 No. 5, pp. 66-71.
Ferrara, E., Varol, O., Davis, C., Menczer, F. and Flammini, A. (2016), “The rise of social bots”,
Communications of the ACM, Vol. 59 No. 7, pp. 96-104.
Frame, W.S. and White, L.J. (2014), “Technological change, financial innovation, and diffusion in
banking”, in Berger, A.N., Molyneux, P. and Wilson, J.O.S. (Eds), The Oxford Handbook of
Banking, Oxford University Press, Oxford, p. 271.
Füller, J., Matzler, K. and Hoppe, M. (2008), “Brand community members as a source of innovation”,
Journal of Product Innovation Management, Vol. 25 No. 6, pp. 608-619.
Gai, K., Qiu, M. and Sun, X. (2018), “A survey on Fintech”,Journal of Network and Computer
Applications, Vol. 103, pp. 262-273.
Gebauer, H. and Reynoso, J. (2013), “An agenda for service research at the base of the pyramid”,Journal
of Service Management, Vol. 24 No. 5, pp. 482-502.
Gimpel, H., Rau, D. and Roglinger, M. (2018), “Understanding Fintech start-ups –a taxonomy of
consumer-oriented service offerings”,Electronic Markets, Vol. 28 No. 3, pp. 245-264.
Glushko, R.J. (2010), “Seven contexts for service system design”,Handbook of Service Science, Springer,
Boston, MA, pp. 219-249.
Gomber, P., Kauffman, R.J., Parker, C. and Weber, B.W. (2018), “On the Fintech revolution: interpreting
the forces of innovation, disruption, and transformation in financial services”,Journal of
Management Information Systems, Vol. 35 No. 1, pp. 220-265.
Guo, Y. and Liang, C. (2016), “Blockchain application and outlook in the banking industry”,Financial
Innovation, Vol. 2 No. 1, pp. 2-24.
Helkkula, A., Kelleher, C. and Pihlström, M. (2012), “Characterizing value as an experience: implications
for service researchers and managers”,Journal of Service Research, Vol. 15 No. 1, pp. 59-75.
Iansiti, M. and Levien, R. (2004), The Keystone Advantage: What the New Dynamics of Business
Ecosystems Mean for Strategy, Innovation, and Sustainability, Harvard Business School Press,
Boston, MA.
Jun, J. and Yeo, E. (2016), “Entry of Fintech firms and competition in the retail payments market”,Asia-
Pacific Journal of Financial Studies, Vol. 45 No. 2, pp. 159-184.
Kale, P., Singh, H. and Perlmutter, H. (2000), “Learning and protection of proprietary assets in strategic
alliances: building relational capital”,Strategic Management Journal, Vol. 21 No. 3, pp. 217-237.
JSTP
Kandampully, J., Keating, B.W., Kim, B., Mattila, A.S. and Solnet, D. (2014), “Service research in the
hospitality literature: insights from a systematic review”,Cornell Hospitality Quarterly, Vol. 55
No. 3, pp. 287-299.
Karaev, A., Lenny Koh, S.C. and Szamosi, L.T. (2007), “The cluster approach and SME competitiveness:
a review”,Journal of Manufacturing Technology Management, Vol. 18 No. 7, pp. 818-835.
Kenis, P. and Knoke, D. (2002), “How organizational field networks shape interorganizational tie-
formation rates”,Academy of Management Review, Vol. 27 No. 2, pp. 275-293.
Khaitan, Y. (2017), “Digital transformation in insurance: consumer centric approach to lead you into the
future”, available at: www.sapientrazorfish.com/news/2017/digital- transformation-in-insurance
(accessed August 20, 2018).
Kim, Y., Park, Y.J. and Choi, J. (2016), “The adoption of mobile payment services for fintech”,
International Journal of Applied Engineering Research, Vol. 11 No. 2, pp. 1058-1061.
Kimbell, L. (2011), “Designing for service as one way of designing services”,International Journal of
Design, Vol. 5 No. 2, pp. 41-52.
Kleinaltenkamp, M., Plewa, C., Gudergan, S., Karpen, I.O. and Chen, T. (2017), “Usage center –value
cocreation in multi-actor usage processes”,Journal of Service Theory and Practice, Vol. 27 No. 4,
pp. 721-737.
Kumar, S. (2016), “Relaunching innovation: lessons from Silicon Valley”,Banking Perspective, Vol. 4
No. 1, pp. 19-23.
Ladhari, R. (2010), “Developing e-service quality scales: a literature review”,Journal of Retailing and
Consumer Services, Vol. 17 No. 6, pp. 464-477.
Lee, C.S. (2001), “An analytical framework for evaluating e-commerce business models and strategies”,
Internet Research, Vol. 11 No. 4, pp. 349-359.
Lee, I. and Shin, Y.J. (2018), “Fintech: ecosystem, business models, investment decisions, and
challenges”,Business Horizons, Vol. 61 No. 1, pp. 35-46.
Lee, J.H. and Pilkington, M. (2017), “How the blockchain revolution will reshape the consumer
electronics industry”,IEEE Consumer Electronics Magazine, Vol. 6 No. 3, pp. 19-23.
Lerner, J. and Tufano, P. (2011), “The consequences of financial innovation: a counterfactual research
agenda”,Annual Review of Financial Economics, Vol. 3 No. 1, pp. 41-85.
Lim, C. and Maglio, P.P. (2018), “Data-driven understanding of smart service systems through text
mining”,Service Science, Vol. 10 No. 2, pp. 154-180.
Lim, C., Kim, M.J., Kim, K.H., Kim, K.J. and Maglio, P.P. (2018), “Using data to advance service:
managerial issues and theoretical implications from action research”,Journal of Service Theory
and Practice, Vol. 28 No. 1, pp. 99-128.
Lim, C., Kim, M.J., Kim, K.H., Kim, K.J. and Maglio, P.P. (2019), “Customer process management: a
framework for using customer-related data to create customer value”,Journal of Service
Management, Vol. 30 No. 1, pp. 105-131.
Lim, C., Kim, K.H., Kim, M.J., Heo, J.Y., Kim, K.J. and Maglio, P.P. (2018), “From data to value: a nine-
factor framework for data-based value creation in information-intensive services”,International
Journal of Information Management, Vol. 39, pp. 121-135.
Lim, C.H. and Kim, K.J. (2014), “Information service blueprint: a service blueprinting framework for
information-intensive services”,Service Science, Vol. 6 No. 4, pp. 296-312.
Lin, C.J. (2007), “Projected gradient methods for nonnegative matrix factorization”,Neural
Computation, Vol. 19 No. 10, pp. 2756-2779.
Longabaugh, W.J. (2012), “BioTapestry: a tool to visualize the dynamic properties of gene regulatory
networks”, in Deplancke, B. and Gheldof, N. (Eds), Methods in Molecular Biology (Gene
Regulatory Networks), Humana Press, Lausanne, pp. 359-394.
Lorenzoni, G. and Lipparini, A. (1999), “The leveraging of interfirm relationships as a distinctive
organizational capability: a longitudinal study”,Strategic Management Journal, Vol. 20 No. 4,
pp. 317-338.
Financial
service
systems
Lusch, R.F. and Nambisan, S. (2015), “Service innovation: a service-dominant logic perspective”,MIS
Quarterly, Vol. 39 No. 1, pp. 155-175.
Mackenzie, A. (2015), “The Fintech revolution”,London Business School Review, Vol. 26 No. 3, pp. 50-53.
Maglio, P.P. and Breidbach, C.F. (2014), “Service science: toward systematic service system
innovation”, in Newman, A., Leung, J. and Smith, J.C. (Eds), Bridging Data and Decisions,
INFORMS, Catonsville, MD, pp. 161-170.
Maglio, P.P. and Lim, C. (2016), “Innovation and big data in smart service systems”,Journal of
Innovation Management, Vol. 4 No. 1, pp. 11-21.
Maglio, P.P. and Spohrer, J. (2008), “Fundamentals of service science”,Journal of the Academy of
Marketing Science, Vol. 36 No. 1, pp. 18-20.
Maglio, P.P., Vargo, S.L., Caswell, N. and Spohrer, J. (2009), “The service system is the basic
abstraction of service science”,Information Systems and e-Business Management, Vol. 7 No. 4,
pp. 395-406.
Mahadevan, B. (2000), “Business models for internet-based e-commerce: an anatomy”,California
Management Review, Vol. 42 No. 4, pp. 55-69.
Maier, E. (2016), “Supply and demand on crowdlending platforms: connecting small and medium-sized
enterprise borrowers and consumer investors”,Journal of Retailing and Consumer Services,
Vol. 33, pp. 143-153.
Merton, R.C. (1995), “A functional perspective of financial intermediation”,Financial Management,
Vol. 24 No. 2, pp. 23-41.
Micu, I. and Micu, A. (2016), “Financial technology (Fintech) and its implementation on the Romanian
non-banking capital market”,SEA-Practical Application of Science, No. 11, pp. 32-54.
Mild, A., Waitz, M. and Wöckl, J. (2015), “How low can you go? Overcoming the inability of lenders to
set proper interest rates on unsecured peer-to-peer lending markets”,Journal of Business
Research, Vol. 68 No. 6, pp. 1291-1305.
Miller, M.H. (1986), “Financial innovation: the last twenty years and the next”,Journal of Financial and
Quantitative Analysis, Vol. 21 No. 4, pp. 459-471.
Mohan, D. (2016), “How banks and Fintech startups are partnering for faster innovation”,Journal of
Digital Banking, Vol. 1 No. 1, pp. 13-21.
Moldovan, D., Copil, G. and Dustdar, S. (2018), “Elastic systems: towards cyber-physical ecosystems of
people, processes, and things”,Computer Standards & Interfaces, Vol. 57, pp. 76-82.
Müller-Seitz, G. (2012), “Leadership in interorganizational networks: a literature review and
suggestions for future research”,International Journal of Management Reviews, Vol. 14 No. 4,
pp. 428-443.
Muzellec, L., Ronteau, S. and Lambkin, M. (2015), “Two-sided internet platforms: a business model
lifecycle perspective”,Industrial Marketing Management, Vol. 45 No. 4, pp. 139-150.
Nakamoto, S. (2008), “Bitcoin: a peer-to-peer electronic cash system”, available at: https://marketing.
binary.com/crypto/Binary.com_WhatisBitcoin.pdf (accessed August 20, 2018).
Nambisan, S. and Sawhney, M. (2011), “Orchestration processes in network-centric innovation:
evidence from the field”,Academy of Management Perspectives, Vol. 25 No. 3, pp. 40-57.
Nastic, S., Copil, G., Truong, H.L. and Dustdar, S. (2015), “Governing elastic IoT cloud systems under
uncertainty”,7th International Conference on Cloud Computing Technology and Science,
November 30–December 3,Vancouver, pp. 131-138.
Nofer, M., Gomber, P., Hinz, O. and Schiereck, D. (2017), “Blockchain”,Business & Information Systems
Engineering, Vol. 59 No. 3, pp. 183-187.
OECD (2018), “Digitalisation and finance: financial markets, insurance and pensions”, Organisation for
Economic Development and Cooperation, Paris, available at: www.oecd.org/finance/
private-pensions/Financial-markets-insurance-pensions-digitalisation-and-finance.pdf (accessed
August 20, 2018).
JSTP
Ordanini, A., Miceli, L., Pizzetti, M. and Parasuraman, A. (2011), “Crowdfunding: transforming
customers into investors through innovative service platforms”,Journal of Service Management,
Vol. 22 No. 4, pp. 443-470.
Ostrom, A., Parasuraman, A., Bowen, D., Patricio, L. and Voss, C. (2015), “Service research priorities in
a rapidly changing context”,Journal of Service Research, Vol. 18 No. 2, pp. 127-159.
Ostrom, A.L., Bitner, M.J., Brown, S.W., Burkhard, K.A., Goul, M., Smith-Daniels, V., Dermikan, H. and
Rabinovich, E. (2010), “Moving forward and making a difference: research priorities for the
science of service”,Journal of Service Research, Vol. 13 No. 1, pp. 4-36.
Paquin, R.L. and Howard-Grenville, J. (2013), “Blind dates and arranged marriages: longitudinal
processes of network orchestration”,Organization Studies, Vol. 34 No. 11, pp. 1623-1653.
Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1988), “SERVQUAL: a multiple-item scale for
measuring consumer perceptions of service quality”,Journal of Retailing, Vol. 64 No. 1, pp. 12-40.
Patrício, L., Fisk, R.P., Falcão e Cunha, J. and Constantine, L. (2011), “Multilevel service design: from
customer value constellation to service experience blueprinting”,Journal of Service Research,
Vol. 14 No. 2, pp. 180-200.
Pena, M.V.T., Breidbach, C.F. and Turpin, A. (2018), “Self-organizing service ecosystems: exploring a
new concept for service science”,Proceedings of the Australasian Conference on Information
Systems,Sydney,December 3-5.
Perks, H., Kowalkowski, C., Witell, L. and Gustafsson, A. (2017), “Network orchestration for value
platform development”,Industrial Marketing Management, Vol. 67, pp. 106-121.
Philippon, T. (2016), “The Fintech opportunity”, available at: www.nber.org/papers/w22476.pdf
(accessed August 20, 2018).
Risius, M. and Spohrer, K. (2017), “A blockchain research framework”,Business & Information Systems
Engineering, Vol. 59 No. 6, pp. 385-409.
Rousseeuw, P.J. (1987), “Silhouettes: a graphical aid to the interpretation and validation of cluster
analysis”,Journal of Computational and Applied Mathematics, Vol. 20, pp. 53-65.
Ryu, H.S. (2018), “What makes users willing or hesitant to use Fintech? The moderating effect of user
type”,Industrial Management & Data Systems, Vol. 118 No. 3, pp. 541-569.
Saleh, M.A., Quazi, A., Keating, B. and Gaur, S.S. (2017), “Quality and image of banking services: a
comparative study of conventional and Islamic banks”,International Journal of Bank Marketing,
Vol. 35 No. 6, pp. 878-902.
Sandler, I., Ostrom, A., Bitner, M.J., Ayers, T.S., Wolchik, S. and Daniels, V.S. (2005), “Developing
effective prevention services for the real world: a prevention service development model”,
American Journal of Community Psychology, Vol. 35 Nos 3-4, pp. 127-142.
Scherer, K.R. (2005), “What are emotions? And how can they be measured?”,Social Science Information,
Vol. 44 No. 4, pp. 695-729.
Schueffel, P. (2016), “Taming the beast: a scientific definition of Fintech”,Journal of Innovation
Management, Vol. 4 No. 4, pp. 32-54.
Shah, C. and Shah, P. (2017), “Influence of crowdfunding on innovative entrepreneurship eco-systems
in India”,Journal of Asia Entrepreneurship and Sustainability, Vol. 13 No. 2, pp. 3-28.
SoftBank Robotics America (2018), “HSBC bank and SoftBank Robotics America partner to bring
humanoid robotics to fifth avenue US flagship bank branch”, available at: www.prnewswire.
com/news-releases/hsbc-bank-and-softbank-robotics-america-partner-to-bring-humanoid-
robotics-to-fifth-avenue-us-flagship-bank-branch- 300672008.html (accessed August 20, 2018).
Stokes, D.E. (1997), Pasteur’s Quadrant: Basic Science and Technological Innovation, Brookings
Institution Press, Washington, DC.
Storbacka, K., Brodie, R.J., Böhmann, T., Maglio, P.P. and Nenonen, S. (2016), “Actor engagement
as a microfoundation for value co-creation”,Journal of Business Research, Vol. 69 No. 8,
pp. 3008-3017.
Financial
service
systems
Tana, S., Breidbach, C. and Turpin, A. (2019), “I want a Lamborghini: an ethnography of
cryptocurrency communities”,Proceedings of the 27th European Conference on Information
Systems, Research-in-Progress Papers, Vol. 21,Stockholm,June 8-14, available at: https://aisel.
aisnet.org/ecis2019_rip/21 (accessed August 23, 2019).
Teece, D.J. (2000), “Strategies for managing knowledge assets: the role of firm structure and industrial
context”,Long Range Planning, Vol. 33 No. 1, pp. 35-54.
Tijssen, R.J.W. (2018), “Anatomy of use-inspired researchers: from Pasteur’s Quadrant to Pasteur’s
Cube model”,Research Policy, Vol. 47 No. 9, pp. 1626-1638.
Vargo, S.L. and Lusch, R.F. (2008), “Service-dominant logic: continuing the evolution”,Journal of the
Academy of Marketing Science, Vol. 36 No. 1, pp. 1-10.
Vartanian, T. (2016), “Fintech’s road to regulatory acceptance is just starting”,American Banker,
available at: www.americanbanker.com/opinion/Fintechs-road-to-regulatory-acceptance-is-just-
starting (accessed August 20, 2018).
Von Luxburg, U. (2007), “A tutorial on spectral clustering”,Statistics and Computing, Vol. 17 No. 4,
pp. 395-416.
Wozniak, S. (2016), “Eight Fintech startups enter the Fintech innovation lab Asia-Pacific”, available at:
https://newsroom.accenture.com/news/eight-Fintech-startups-enter-the- Fintech-innovation-lab-
asia-pacific.htm (accessed August 20, 2018).
Yang, H.L. and Hsiao, S.L. (2009), “Mechanisms of developing innovative IT-enabled services: a case
study of Taiwanese healthcare service”,Technovation, Vol. 29 No. 5, pp. 327-337.
Yurcan, A. (2017), “The top tech priorities for banks in 2018”, available at: www.americanbanker.com/
news/ai-development-top-of-2018-list-for-many-banks (accessed August 20, 2018).
Zavolokina, L., Dolata, M. and Schwabe, G. (2016), “Fintech –what’s in a name?”,37th International
Conference on Information Systems,Dublin,December 11–14.
Zhang, B., Baeck, P., Ziegler, T., Bone, J. and Garvey, K. (2016), “The 2015 UK alternative finance
industry report”, available at: www.jbs.cam.ac.uk/fileadmin/user_ upload/research/centres/
alternative-finance/downloads/2015-uk-alternative-finance-industry-report.pdf (accessed
August 20, 2018).
Zomerdijk, L.G. and Voss, C.A. (2010), “Service design for experience-centric services”,Journal of
Service Research, Vol. 13 No. 1, pp. 67-82.
Further reading
Lee, D.K.C. and Teo, G.S.Z.J. (2015), “Emergence of fintech and the LASIC principles”,Journal of
Financial Perspectives, Vol. 3 No. 3, pp. 1-26.
Vargo, S. and Lusch, R. (2016), “Institutions and axioms: an extension and update of service- dominant
logic”,Journal of the Academy of Marketing Science, Vol. 44 No. 1, pp. 5-23.
Corresponding author
Christoph F. Breidbach can be contacted at: c.breidbach@business.uq.edu.au
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Other articles by Byron W. Keating
Scholarly Books
• Keating, B. (2010). Multichannel Service Relationships: Toward an Integrated Model, VDM
Verlag: Germany.
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tourists in Australia, in Li, R (ed), Chinese Outbound Tourism 2.0, Apple Academic Press,
New Jersey, USA.
• Anderson, M., Keating, B. and Kriz, A. (2013). An open systems perspective on mental
health services, in Kandampully, J. (ed), Service Management in Health and Wellness
Services, Kendall Publishing, Dubuque, USA.
• Keating, B. and Godfrey, A. (2013). Study tourism from China: Opportunities and
implications for Australia, in Resources, Energy and Tourism: China Review June 2013,
Australian Government, Canberra.
• Kriz, A. and Keating, B. (2010). Business relationships in China: Lessons about deep trust, in
Warner and Rowley (eds.), Chinese Management in the 'Harmonious Society': Managers,
Markets and the Globalized Economy, Routledge: London, UK.
• Keating, B; Rugimbana, R. and Quazi, A. (2003). Building effective online relationships, in
Singh, M. and Waddell, D. (eds), E-Business: Innovation and Change Management, IDEA
Group, Hershey, USA.
• Keating, B. and Rugimbana, R. (2002). E-business diffusion across cultures, in Rugimbana, R.
and Nwankwo, S. (eds), Cross Cultural Marketing Perspectives, Thompson Learning,
London, UK.
• Rugimbana, R. and Keating, B. (2002). Distribution issues in cross cultural marketing, in
Rugimbana, R. and Nwankwo, S. (eds), Cross Cultural Marketing Perspectives, Thompson
Learning, London, UK.
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•Breidbach, C., Keating, B.W., and Lim, C. (2020). Fintech: Research directions to explore the
digital transformation of financial service systems, Journal of Service Theory and Practice,
doi.org/10.1108/JSTP-08-2018-0185.
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adversarial network for human pose estimation, IEEE Access, 7, 103619-103628.
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Patterns of pre-crash behavior in railway suicides and the effect of corridor fencing: A
natural experiment in New South Wales, International Journal of Injury Control and Safety
Promotion, 26(4), 423-430.
•Breidbach, C., Choi, S., Ellway, B.P., Keating, B.W., Kormusheva, K., Kowalkowski, C., Lim, C.
and Maglio, P.P. (2018). Operation without operations: How is technology changing the
role of the firm?, Journal of Service Management, 29(5), 809-833.
•Keating, B., McColl-Kennedy, J., and Solnet, D. (2018). Theorizing beyond the horizon:
Service research in 2050, Journal of Service Management, 29(5), 766-775.
•Hodgkinson, I., Hannibal, C., Keating, B., Chester-Buxton, R. and Bateman, N. (2017).
Towards a public service management: Past, present, and future directions, Journal of
Service Management, 28 (5), 998-1023.
•Saleh, A., Quazi, A., Keating, B. and Gaur, S. (2017). Quality and image of banking services: a
comparative study of conventional and Islamic banks, Journal of Bank Marketing, 35 (6),
878-902.
•Keating, B., Heung, V., Huang, S. and Kriz, A. (2015). A systematic review of the Chinese
outbound tourism literature, Journal of Travel and Tourism Marketing, 32 (1-2), 2-17.
•Huang, S. Keating, B., Heung, V. and Kriz, A. (2015). Epilogue: Directions for Chinese
outbound tourism scholarship, Journal of Travel and Tourism Marketing, 32 (1-2), 153-159.
•Keating, B., Heung, V., Huang, S. and Kriz, A. (2015). Editorial – Special Issue on Chinese
Outbound Tourism, Journal of Travel and Tourism Marketing, 32 (1-2), 2-17.
•Talukder, M., Quazi, A. and Keating, B. (2014). Virtual systems in Australia: A study of
individual user’s commitments and usage, Journal of Internet Commerce, 13(1), 1-21.
•Aslandzadeh, M. and Keating, B. (2014). Inter-Channel effects in multichannel travel
services: Moderating role of social presence and need for human interaction, Cornell
Hospitality Quarterly, 55(3), 265-276.
• Kandampully, J., Keating, B., Kim, P., Mattila, A. and Solnet, D. (2014). Service and
hospitality research nexus: insights from a systematic review (1998–2012), Cornell
Hospitality Quarterly, 55(3), 287-299.
• Hanafizadeh, P., Keating, B. and Khedmatgozar, H. (2013). A systematic review of internet
banking adoption, Telematics and Informatics, 31(3), 492-510.
• Dale, N., Ritchie, B. and Keating, B. (2013). Understanding constraints and their impact on
school excursion tourism, Tourism Analysis, 17(6), 805-812.
• Richard, P. Coltman, T. and Keating, B. (2012). Designing the IS service strategy: An
information acceleration approach, European Journal of Information Systems, 21(1), 87-98.
• Keating, B., Alpert, F., Kriz, A. and Quazi, A. (2012). Exploring the mediating role of
relationship quality in online services, Journal of Computer Information Systems, 52(2) 33-
41.
• Anderson, E., Coltman, T., Devinney, T. and Keating, B. (2011). What drives the choice of a
third‐party logistics provider? Journal of Supply Chain Management, 47(2), 97-115.
• Coltman, T., Devinney, T. and Keating, B. (2011). Best–worst scaling approach to predict
customer choice for 3PL services, Journal of Business Logistics, 32(2), 139-152.
• Keating, B., Coltman, T., Fossa-Wamba, S. and Baker, V. (2010). The RFID investment
decision: What matters most and least, Proceedings of the IEEE, 98(9), 1672-1680.
• Kriz, A. and Keating, B. (2010). Business relationships in China: Lessons about deep trust,
Asia Pacific Business Review, 16(3), 299-318.
• Kriz, A. and Keating, B. (2009). Doing business in China: Tips for an outsider (Lǎo Wài),
China Review International, 16(1), 1-28.
• Keating, B., Kriz, A. and Quazi, A. (2009). The influence of perceived financial risk on service
relationships in the online retail setting, Electronic Markets, 19(4), 237-250.
• Keating, B. (2009) Managing ethics in the tourism supply chain: The case of Chinese travel
to Australia. International Journal of Tourism Research, 11(4), 403-408.
• Keating, B. and Coltman, T. (2009) Marketing and the law: Defending single color
trademarks. Journal of the Academy of Marketing Science, 37(3), 375-380.
• Keating, B., Quazi, A., Kriz, A. and Coltman, T. (2008) In pursuit of a sustainable supply
chain: Insights from Westpac Banking Corporation. Supply Chain Management: An
International Journal, 13(3), 175-180.
• Keating, B. and Kriz, A. (2008) Outbound tourism in China: Literature review and research
agenda, Journal of Hospitality and Tourism Management, 15(2), 32-41.
• Rugimbana, Keating, B. and Quazi, A. (2008) Applying a consumer perceptual measure of
CSR: A regional Australian perspective, Journal of Corporate Citizenship, 29(Spring), 61-74.
• Rugimbana, R., Quazi, A. and Keating, B. (2007). The impact of discontentment on quality of
Life: An exploratory study of a small Australian regional community after bank closures,
Journal of Management and World Business Research, (4:1), 10-21.
• Quazi, A. Rugimbana, R., Muthaly, S. and Keating, B. (2003). Corporate social action
patterns in contrasting markets, Australasian Marketing Journal, 11(3), 28-42.
• Keating, B., Rugimbana, R. and Quazi, A. (2003). Exploring service quality and relationship
quality in cyberspace, Managing Service Quality, 13(3), 217-232.
Refereed Conference Papers
• Wu, S., Campbell, J. and Keating, B. (2017). The Role of Information Systems in Preventing
Railway Suicide: A Service Value Co-Creation Perspective, Australasian Conference on
Information Systems, 4-6 December, Hobart, Tasmania.
• Campbell, J., Keating, B. and Straub, D. (2016). Theorizing Communicative Practices within
Financial Internet Discussion Sites, International Conference on Information Systems (ICIS),
11-14 December, Dublin, Ireland.
• Sterrenberg, G. and Keating, B. (2017). Measuring IS Success of eGovernment: A Case Study
of the Disability Sector in Australia, Australasian Conference on Information Systems, 5-7
December, Wollongong, Australia.
• Simpson, J., Wilkin, C., Campbell, J. and Keating, B. (2016). Iterate Wildly: Is User-Centred
Design and Prototyping the Key to Strategic Alignment? European Conference on
Information Systems (ECIS), Istanbul, Turkey.
• Steele, J., Gregor, S., Campbell, J., Fitzgerald, R. and Keating, B. (2016). Designing Location-
Based Educational Services for School Students, Design Science Research in IS and
Technologies (DESRIST), 24-25 May, Newfoundland, Canada.
• Simpson, J., Wilkin, C., Keating, B. and Campbell, J. (2016). Best Practices or Improvisation
in System Change? An Exploratory Study, Pacific Asia Conference on Information Systems
(PACIS), 27 June – 1 June, Chiayi, Taiwan.
• Wu, S., Liang, TP., Straub, D. (2016). Extending the Governance-Performance Model: The
Impact of Governance Mechanism on Outsourcing Operations in China, Pacific Asia
Conference on Information Systems (PACIS), 27 June – 1 June, Chiayi, Taiwan.
• Keating, B., Mackrell, D. and Campbell, J. (2015). Re-negotiating homeless identity through
technology mediated social interaction, International Conference on Information Systems
(ICIS), 13-16 December, Dallas, TX.
•Simpson, J., Campbell, J., Pham, T., Keating, B. and Wilkin, C. (2015). Towards and
understanding of valence in e-government services, Australasian Conference on
Information Systems (ACIS), 2-4 December, Adelaide.
•Sun, R., Gregor, S. and Keating, B. (2015). Information technology platforms: Definition and
research directions, Australasian Conference on Information Systems (ACIS), 2-4 December,
Adelaide.
•Sun, R., Gregor, S. and Keating, B. (2014) Collaborative IT outsourcing in the public sector: A
case analysis of standard business reporting in Australia, Australasian Conference on
Information Systems (ACIS), 8-10 December, Auckland, NZ.
•Keating, B., Gregor, S., Fitzgerald, R. and Campbell, J. (2014) Information Systems Design
Theory for Location-Based Educational Services in Informal Learning Environments,
Australasian Conference on Information Systems (ACIS), 8-10 December, Auckland, NZ.
•Campbell, J., Keating, B., Yang, R., Zhao, L. and Zou, P. (2014) Achieving building
sustainability through application of information systems and stakeholder alignment,
International Conference on Construction and Real Estate Management (ICCREM), 27-28
September, Kunming, China.
•Keating, B., Zou, P., Yang, R. and Campbell, J. (2014) Stakeholder Alignment and Effective
System Use: Case Study of a Public Sector Information System, International Conference on
Information Systems (ICIS), December, Auckland, NZ.
•Keating, B., Campbell, J. and Raddol, P. (2013). Evaluating a New Pattern Development
Process for Interface Design: Application to Mental Health Services, International
Conference on Information Systems, 15-18 December, Milan, Italy.
•Campbell, J. and Keating, B. (2013). Development of a Decision Support Tool
for Crowdsourcing Stock Market Intelligence, Australasian Conference on Information
Systems, 4-6 December, Melbourne, Australia.
•Campbell, J., Boell, S., Keating, B. and Cecez-Kecmanovic, D. (2013). Temporal Aspects of
Telework and its Impact on Work-Family Conflict, Australasian Conference on Information
Systems, 4-6 December, Melbourne, Australia.
•Keating, B., Gregor, S. and Campbell, J. (2013). Impact of Strategic Alignment on IT
Outsourcing Success in a Complex Service Setting, Americas Conference on Information
Systems, 15-17 August, Chicago, USA.
•Campbell, J., Keating, B., Wilkin, C. and Moore, S. (2013). Multi-level IT Project Alignment in
Government Services: Contracted Employment Services, Americas Conference on
Information Systems, 15-17 August, Chicago, USA.
•Yang, R., Zou, P. and Keating, B. (2013). Analysing stakeholder associated risks in green
buildings: A social network analysis method, CIB World Building Congress, 5-9 May,
Brisbane, Australia.
• Keating, B., Gregor, S. and Theodoulidis, B. (2012). Understanding the nature of service
design research: A theoretical classification and explication, Cambridge Academic Design
Management Conference, 4-5 September, Cambridge, UK.
• Richard, P., Coltman, T., Devinney, T. and Keating, B. (2010). Designing service
architecture: Exploitation and exploration with operational capabilities, Academy of
Management Conference, 6-10 August, Canada.
• Keating, B., Coltman, T., Michael, K. and Baker, V. (2009). Unpacking the ERP investment
decision: An empirical assessment of the benefits and risks, European Conference on
Information Systems, June 8-10, Verona, Italy.
• Coltman, T., Devinney, T. and Keating, B. (2008). What drives logistics provider selection: A
two country comparison, Academy of International Business (AIB) Conference, 30 June – 3
July, Milan, Italy.
• Coltman, T., Keating, B. and Kriz, A. (2007). Do suppliers of third party logistics understand
their customers?, Australian and New Zealand Marketing Academy Conference, 3-5
December, Otago, NZ.
• Keating, B., Coltman, T. and Kriz, A. (2007). Embracing a service-dominant logic in the
supply chain, Australian and New Zealand Marketing Academy Conference, 3-5 December,
Otago, NZ.
• Quazi, A., Rahman, M. and Keating, B. (2007). A developing country perspective on CSR: A
test case of Bangladesh, Australian and New Zealand Marketing Academy Conference, 3-5
December, Otago, NZ.
• Keating, B., Quazi, A. and Kriz, A. (2007). Customer relationship management: Examining
the central proposition in the online context, International Conference on Electronic
Business, 2-6 December, Taipei, Taiwan.
• Coltman, T., Keating, B. and Devinney, T. (2007). Designing 3PL services, Australian and
New Zealand Academy of Management Conference, 4-7 December, Sydney, Australia.
• Coltman, T., Gattorna, J. and Keating, B. (2007). Alignment of buyer and supplier
expectations: An agency theory perspective, Supply Chain Management Educators
Conference, 21-24 October, Pennsylvania, USA.
• Coltman, T., Devinney, T. and Keating, B. (2007). Which logistic service provider attributes
are most and least important, INFORMS Manufacturing and Service Operations
Management Conference, 18-19 June, Beijing, China.
• Rugimbana, R., Strachan, G., Keating, B. and Quazi, A. (2005). Social Impact of Bank
Closures on a Small Rural Community: The Case of Merriwa, Australian New Zealand
Marketing Academy Conference, 5-7 December, Freemantle, Australia.
• Rugimbana, R., Strachan, G., Keating, B. and Quazi, A. (2004). Examining the Applicability of
Novel Model of Social Responsibility to Consumer Banking, Australian New Zealand
Marketing Academy Conference, 4-6 December, Victoria, NZ.
• Carlson, J., Quazi, A. and Keating, B. (2003). A Conceptual Model for Developing Consumer-
Based Brand Equity in the Online Environment: Implications for Professional Sport
Websites, World Marketing Congress, 11-14 June, Perth, Australia.
• Keating, B., Rugimbana, R. and Quazi, A. (2003). Relationship Marketing in Cyberspace,
World Marketing Congress, 11-14 June, Perth, Australia.
• Keating, B., Rugimbana, R. and Quazi, A. (2003). An Enhanced Model for CRM, World
Marketing Congress, 11-14 June, Perth, Australia.
• Keating, B., Rugimbana, R. and Quazi, A. (2003). An Interpersonal Perspective to CRM,
Academy of Marketing Science Conference, 28-31 May, Washington DC, USA.
• Keating, B., Rugimbana, R. and Quazi, A. (2003). Exploring the Chain of Impact in Online
Retail, Australian Services Marketing Workshop, 12-14 March, Melbourne, Australia.
• Coghlan, I., Quazi, A. and Keating, B. (2003). The Differentiating Impact of Beef Cattle
Brands on Auction Prices, Australian New Zealand Marketing Academy Conference, 3-5
December, Adelaide, Australia.
• Keating, B. and Rugimbana, R. (2002). Discriminating between Service Quality and
Relationship Quality in Cyberspace, International Services Marketing Conference, 3-5 July,
Brisbane, Australia.
• Keating, B. and Rugimbana, R. (2002). Cultural Enhancers of e-Business Diffusion,
International Academy of African Business Development Conference, 3-6 April, Port
Elizabeth, South Africa.
• Rugimbana, R., Strachan, G. and Keating, B. (2002). Social Impacts of Bank Rationalisation,
Doing Business Across Borders Conference, 27-28 November, Newcastle, Australia.
• Keating, B. and Rugimbana, R. (2002). Exploring the Efficacy of Traditional
Conceptualisations of Loyalty, Doing Business Across Borders Conference, 27-28 November,
Newcastle, Australia.
• Stevenson, T., Doherty, I., Sacco, J., Flynn, D., Smith, J. and Keating, B. (2002). Identifying
the Factors that Influence the Adoption of E-Business by SMEs, Doing Business Across
Borders Conference, 27-28 November, Newcastle, Australia.
• Carlson, J., Quazi, A., Muthaly, S. and Keating, B. (2002). Enhancing Fan Identification and
Brand Equity in the Online Environment: A Conceptual Framework, Australian New Zealand
Marketing Academy Conference, 3-5 December, Melbourne, Australia.
• Keating, B. and Rugimbana, R. (2001). Capturing the Holy Grail: a Conceptual Model for e-
Loyalty, CollECTeR Conference, 3-5 December, Coffs Harbour, Australia.
• Keating, B. and Rugimbana, R. (2001). Diffusion of e-Business in Developing Countries,
Doing Business Across Borders Conference, 22-23 November, Newcastle, Australia.
• Keating, B. and Rugimbana, R. (2001). Exploring Service Quality and Relationship Quality
in Online Shopping, Doing Business Across Borders Conference, 22-23 November,
Newcastle, Australia.
