Managing Transformation within Service Systems Networks: A System Viability Approach

Abstract

Information technologies and massively increased connectivity drive service‐based organizations towards collaboration‐driven innovation activities. From a systems theory viewpoint, a formal structure for observing these developments is service system networks; that is, networks of resource‐integrating systems that co‐create value through service exchange. Given their dynamic nature, service systems networks may need to reconfigure themselves, as systems join, leave or change their role in the network, thus potentially jeopardizing the network's viability. By following a design science research methodology, our research aims to address this challenge through a novel two‐dimensional model that maps a service system's options (‘roles’) for positioning itself within a service systems network. Roles are defined as viability‐inducing states, described in terms of three sets of attributes (role elements) that correspond to critical success factors of network viability: service innovation, collaboration and resilience. Hence, a move to a new role is acceptable if and only if network viability is satisfied.

Keywords: service, innovation, digital, transformation, change, change management, management, service systems, service science, business ecosystems, business, management, value

Full text

■Research Paper
Managing Transformation within Service
Systems Networks: A System Viability
Approach
George Bithas
1
, Konstadinos Kutsikos
1
*, Alan Warr
2
and
Damianos Sakas
3
1
Growth Transformation and Value Engineering (WAVE) Lab, Business School, University of the Aegean,
Chios, Greece
2
KPMG, London, UK
3
University of Peloponnese, Tripoli, Greece
Information technologies and massively increased connectivity drive service-based orga-
nizations towards collaboration-driven innovation activities. From a systems theory view-
point, a formal structure for observing these developments is service system networks;
that is, networks of resource-integrating systems that co-create value through service ex-
change. Given their dynamic nature, service systems networks may need to reconfigure
themselves, as systems join, leave or change their role in the network, thus potentially
jeopardizing the network’s viability. By following a design science research methodology,
our research aims to address this challenge through a novel two-dimensional model that
maps a service system’s options (‘roles’) for positioning itself within a service systems net-
work. Roles are defined as viability-inducing states, described in terms of three sets of at-
tributes (role elements) that correspond to critical success factors of network viability:
service innovation, collaboration and resilience. Hence, a move to a new role is acceptable
if and only if network viability is satisfied. © 2018 John Wiley & Sons, Ltd.
Keywords service systems; value co-creation; system viability; service innovation; system roles
INTRODUCTION
Driven by digital technologies and ubiquitous in-
terconnectivity, the global service economy has
been moving beyond narrowly defined indus-
tries built around vertically integrated corpora-
tions. New means of creating value emerge
through collaborative networks, such as digital
platforms; that is, hubs of digital content and/or
services. These platforms act as ‘innovation mag-
nets’for new partners with whom platform
owners collaborate on unlocking growth options.
* Correspondence to: Konstadinos Kutsikos, Growth Transformation
and Value Engineering (WAVE) Lab, Business School, University of
the Aegean, Chios Island Campus, Michalio Hall, Chios GR-82100,
Greece.
E-mail: kutsikos@aegean.gr
© 2018 John Wiley & Sons, Ltd.
Systems Research and Behavioral Science
Syst. Res 35, 469–484 (2018)
Published online in Wiley Online Library
(wileyonlinelibrary.com) DOI: 10.1002/sres.2543

Together, they aim to co-create innovative busi-
ness models that combine cross-industry knowl-
edge and capabilities, and redefine competitive
advantage; thus, paving the way for the next
wave of disruptive services (Accenture, 2016).
From a systems theory viewpoint, a service-
based organization is a service system: a com-
plex, value co-creation configuration of re-
sources, including people, shared information
(language, laws, measures, methods) and tech-
nology, all connected internally and externally
to other service systems by value propositions
(Maglio and Spohrer, 2008; Vargo et al., 2008;
Demirkan et al., 2011). This interconnectivity
leads to the creation of a service systems network
(Vargo and Lusch, 2011): ‘a relatively self-
contained, self-adjusting system of resource-
integrating actors connected by shared institu-
tional arrangements and mutual value creation
through service exchange’. Vargo and Lusch
(2011) further indicate that the main reason ser-
vice systems join efforts is for boosting
innovation.
Unfortunately, such collaboration-driven inno-
vation and value co-creation must be balanced
against viability—both the network’s and the
network participants. In order to achieve this bal-
ance, de Waal and Suchak (2010), Brosnan (2011)
and Tomasello (2014) indicate that success in col-
laboration depends on one being able to under-
stand how to collaborate and thus to
understand the role of its partners in the collabo-
ration process. Barile et al. (2016) further state
that system viability depends on a system’s abil-
ity to adapt to changes in an environment by
identifying a role to play in each resulting con-
text—that is how to ‘serve’a need—then satisfy-
ing the expectations of other viable systems.
Hence, roles in service systems networks are
critical for the viability of both the network and
the system itself. However, defining and manag-
ing roles in dynamic networks is a significant
challenge. Service networks may be reconfigured
as often as needed, in order to (i) achieve their
own goals; (ii) react to external pressures (e.g.
competition from other ecosystems). Such
changes occur when actors interact, share infor-
mation, knowledge and other resources, and thus
‘contaminate’and even transform each other
(Letaifa et al., 2016). In addition, a service system
may move to a new role within a service systems
network, causing further reconfigurations within
the network.
This challenge is the core of our research. By
following a design science research (DSR) meth-
odology (van Aken and Romme, 2009), we ex-
plored the link between viability and
transformation-inducing activities within a ser-
vice systems network (stemming from role mo-
bility). Our efforts were based on two key
assumptions and three research questions:
(1) Assumptions
•A system that wants to join and operate within
a service systems network may have to under-
take roles and responsibilities that require sig-
nificant transformation.
•Transformation is usually driven by (i) avail-
able resources (owned, or to be acquired); (ii)
transformation states and (iii) state-to-state
transitions.
(2) Research questions
•How can a service system contribute to service
innovation within a service systems network;
that is, what roles can it undertake?
•How can a service system capitalize on re-
sources (acquire—integrate—provide) within
a service systems network; that is, how does
value co-creation vary across different net-
work roles?
•How can a service systems network balance
collaborative activity for service innovation
against potential resource capitalization con-
flicts and opportunities undertaken by indi-
vidual service systems; that is, how can
potential (or even necessary and required)
change of roles by service systems can be man-
aged for limiting negative equilibrium effects
in a systems network?
The main outcome of our research approach is
a conceptual model for helping a service system
decide how to position (as well as reposition) it-
self within a service systems network, by
attaining a specific role. In our model, roles are
defined as viability-inducing states: they are
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DOI: 10.1002/sres.2543
470 George Bithas et al.

described in terms of three sets of attributes (role
elements), which correspond to critical success
factors (CSFs) of network viability, namely, ser-
vice innovation, collaboration and resilience. Dif-
ferent values for these attributes clearly
differentiate one role from another. When a ser-
vice system plans to move from one role to an-
other, it can use our model as a sign-posted
transformation path: a move to a new role will
be successful (in viability terms; both for the ser-
vice system and the network) if the attribute
values of the target role can be safely reached
and sustained. In other words, a move to a new
role is acceptable if and only if network viability
can be satisfied.
In the remainder of this article, we first provide
the theoretical background of our research, focus-
ing on service systems networks and system roles
within them. We then describe the steps of the
DSR methodology that guided our activities,
followed by an extensive discussion of our re-
search findings. The article concludes with a de-
scription of new research paths that were
uncovered during an ongoing application of our
model in an actual business context (the Lake
District tourism ecosystem, UK).
LITERATURE REVIEW
Service Systems
Systems thinking has been present in many man-
agement disciplines for quite some time
(Checkland, 1981; Yolles, 1999; Ritter et al.,
2004; Golinelli, 2010). In an ever more complex
business context, a systems approach offers re-
searchers and practitioners an intriguing view-
point: exploring business entities as systems,
with a focus on analysing their relationship with
their environment (Burns and Stalker, 1961; Law-
rence and Lorsch, 1967; Aldrich, 1979). This
viewpoint has received particular attention in
the realm of service research, due to its contribu-
tion to understanding service-related, complex
phenomena, such as co-creation and service ex-
change (Beinhocker, 2006; Barile and Polese,
2010a; Polese, 2010; Ng et al., 2012; Wieland
et al., 2012).
As a result, in recent years, Service Science
emerged as an interdisciplinary scientificfield
for studying service-based organizations as ser-
vice systems (Maglio et al., 2010; Demirkan
et al., 2011; Vargo and Lusch, 2011). A service sys-
tem is defined as a complex, value co-creation
configuration of resources, including people,
shared information (language, laws, measures,
methods) and technology, all connected inter-
nally and externally to other service systems by
value propositions (IfM and IBM, 2008; Vargo
et al., 2008; Maglio and Spohrer, 2008; Maglio
et al., 2009; Vargo and Akaka, 2009; Mele and
Polese, 2011). This definition highlights certain
key properties/characteristics of service systems.
Dynamic Environment/Context
A service system is composed of various ele-
ments, interconnections and stakeholders, such
as partners, employees and customers (Spohrer
et al., 2008). Service development entails a contin-
uous reconfiguration of actions, interactions and
collaborations among service systems—a combi-
nation that highlights the importance of viability
for a system operating in a dynamic context
(Golinelli, 2010).
Value Co-Creation
Value is co-created through the integration of
existing knowledge, the development of new
knowledge (and other resources) and is influ-
enced by the context, or environment, as well as
the resources of others (Vargo and Akaka, 2012).
Maglio et al. (2009) further point out that value
is expressed as an improvement in a service sys-
tem’s well-being (Wieland et al., 2012), directly
impacting the system’s ability to adapt to an en-
vironment (Barile et al., 2016). In other words,
value co-creation can be a key determinant of a
system’s viability (Vargo et al., 2008; Spohrer
and Maglio, 2010a).
Resources and Value Propositions
Service systems engage in their
environment/context for value co-creation
through value propositions. A value proposition
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Managing Transformation within Service Systems Networks: A System Viability Approach 471

can be defined as a request from service system A
to service system B, so that the latter can apply its
resources for the benefit of service system A
(Maglio and Spohrer, 2013). Hence, we can think
of service systems as open systems that are capa-
ble of improving (i) the viability of another sys-
tem through application of its resources (i.e. the
other system considers the interaction to be valu-
able); (ii) its own viability, by acquiring external
resources (i.e. the system itself considers the in-
teraction with other systems to be valuable)
(Maglio et al., 2009).
Service System Networks
The aforementioned characteristics of services
systems share a common CSF: service system vi-
ability as a function of value co-creation in dy-
namic collaborative environments. Allee (2000)
indicated that systems collaborate with other sys-
tems via networks, determined by resource allo-
cation, distribution, collaborative advantages
and cooperative strategies. Within such net-
works, systems combine their strengths through
direct and indirect connections to establish com-
petitive advantages for the network (Polese
et al., 2009).
This is a critical viewpoint because it leads to a
key insight: a service system’s value is viewed as
an improvement in its ability to interact, adapt
and operate within a dynamic business environ-
ment. As Mele and Polese (2011) state, the value
creation capacity of a service system is not only
attributed to its core competences and resources.
It is more importantly linked to its capability to
collaborate with other service systems and con-
tribute to joint viability goals, processes and
outcomes.
At a higher level of abstraction, Vargo and
Lusch (2011) and Vargo and Akaka (2012) indi-
cate that the main reason that resource integrat-
ing service systems join efforts is for boosting
innovation. Lusch and Nambisan (2015) actually
defined service innovation in the context of col-
laborating service systems: ‘it is the re-bundling
of diverse resources that create novel resources
that are beneficial to some actors in a given
context; this almost always involves a network
of systems’.
Based on the aforementioned, a service sys-
tems network can be defined as a ‘relatively
self-contained, self-adjusting system of resource-
integrating actors connected by shared institu-
tional arrangements and mutual value creation
through service exchange’(Vargo and Lusch,
2011). Mele and Polese (2011) further indicate
that a service system network is a ‘network of re-
lationships which may have one or more associ-
ated value propositions’(IfM and IBM, 2008). A
service system network assembles certain assets
together, but it requires the integration of the par-
ticipating systems’resources according to their
expectations, needs and capabilities. As a result,
participating service systems strive to reach a bet-
ter matching of resources, activities and
processes.
Although a service systems network is a sys-
tem itself, we deliberately separate and follow
its conceptual definition throughout this article.
This separation enables further mapping of our
findings in actual business contexts and draws
attention to multiple levels of interaction and in-
stitutions (social norms, collective meanings and
other coordinating heuristics) as drivers of inno-
vation (Chandler and Vargo, 2011; Akaka et al.,
2013).
Hence, the aforementioned CSF for service sys-
tems can be extended and enriched for service
systems networks: network viability as a func-
tion of service innovation capacity in dynamic
collaborative environments.
It is important to note that tackling this CSF is
not only a scientific challenge. Businesses around
the world are increasingly mindful of its signifi-
cance. For some of them, the rise of service sys-
tems networks is an opportunity to explore new
paths for establishing competitive advantage
over their competitors. For example, in the tour-
ism sector, Ogulin et al. (2016) pointed out that
the successful operation of a service systems net-
work is characterized by the network’s ability to
consistently arrange all its participating systems’
resources (such as technologies, accommodation,
restaurants, entertainment and landscapes) into
innovative tourism experiences, in order to sat-
isfy the needs of increasingly knowledgeable
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tourists who demand authentic experiences
(Gilmore and Pine, 2007; Yeoman et al., 2007).
Roles in Service Systems Networks
The main question that emerges from the afore-
mentioned discussion is yet another challenge:
what is the driver of the aforementioned CSF;
that is, what can significantly affect service sys-
tems networks viability?
de Waal and Suchak (2010), Brosnan (2011) and
Tomasello (2014) indicate that success in collabo-
ration depends on one being able to understand
how to collaborate and thus to understand the
role of its partners in the collaboration process.
Barile et al. (2016) state that system viability de-
pends on a system’s ability to adapt to changes
in an environment by identifying a role to play
in each resulting context—that is how to ‘serve’
a need—then satisfying the expectations of other
viable systems. Mele and Polese (2011) further
observed that the value creation potential of a
service system does not only arise from its core
competences and distinctive resources but also
from its capability to join a systems network
and contribute to its viability.
Hence, roles in systems networks are critical
for the viability of both the network and the sys-
tem itself. Understanding such roles has been a
focal point for many research efforts in various
systems-driven disciplines. For example, collabo-
rative structures in natural ecosystems often in-
volve a diversity of species, as in the case of
plant–animal networks, where organisms from
different species are engaging in mutually benefi-
cial collaborations (Bascompte and Jordano,
2014). Members of these systems play different
roles, based on the characteristics of each species
(Stouffer et al., 2012). Gillaranz et al. (2012) cate-
gorize these roles based on the number of collab-
orative engagements for a species: the most
connected species are ‘generalists’, whereas ‘spe-
cialists’have few interactions with others
(Bascompte and Jordano, 2006; Gilarranz et al.,
2012; Eichhorn, 2016; Palacio et al., 2016). Dun-
stan et al. (2011) assign roles based on the similar-
ity of lifestyles or resources requirements of a
species. For example, ‘ecosystem engineers’are
species whose activities create or modify their
habitat, thus creating new opportunities for col-
laboration with species that live alongside them.
The characteristic (and intrinsic limitation) of
these role definitions is that they are mostly fo-
cused on the species (i.e. system) itself, defining
rather static role categories. Although they can-
not directly provide strong explanations for net-
work viability, they have nevertheless driven
this quest in the business word. Iansiti and
Levien (2004a, 2004b) indicate that collaborative
network evolution in business settings is a dy-
namic process: a business firm (i.e. a service sys-
tem) may strategically shift to another role
within a network. In such collaborative environ-
ments, the membership and roles of participating
systems may change, but the service systems net-
work persists. In this context, Iansiti and Levien
(2004a, 2004b) defined a number of roles. Two
of them are of particular interest.
Keystones
These are service systems that drive the develop-
ment of innovative value propositions and pro-
mote incorporation of innovation throughout
the service systems network. They also aim to in-
crease its resilience and diversity.
Niche Players
They are service systems that offer specialized ca-
pabilities and resources to the other service sys-
tems of the service systems network. Innovation
is a must for their own viability and they contrib-
ute to the differentiation of the whole network.
Although these roles take into account the pro-
pensity of service systems to innovate, they are
still referring to an essentially steady state of a ser-
vice systems network. More importantly, no in-
sights are provided on network viability in cases
of role mobility (i.e. when a service system moves
into a new role). In other words, the CSF that we
are exploring becomes a key research challenge:
(i) how can transformation-inducing activities
within a service systems network (stemming from
role mobility) impact its viability? (ii) Can we ex-
plore this impact, by linking role mobility to the
aforementioned functional components of service
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Managing Transformation within Service Systems Networks: A System Viability Approach 473

systems network viability (service innovation,
collaboration, dynamic context)?
METHODOLOGY
Classic research methodologies (qualitative and
quantitative) have produced a vast knowledge
base. However, this knowledge base has been
criticized as having too little relevance for prac-
tice (Beyer and Trice, 1982; Daft and Lewin,
1990; Hambrick, 1994; Tranfield and Starkey,
1998; Rynes et al., 2001) and for being too
fragmented (Koontz, 1980; Whitley, 1984; Pfeffer
1993; Van Maanen 1995; Whitley 2000). Particu-
larly for systems development, Nunamaker
et al. (1991) advocate the integration of the pro-
cesses of traditional research and systems devel-
opment. Peffers et al. (2007) promote the idea of
multimethodological approaches, which include
the formation of theories in the development of
systems through experimentation or observation.
In this context, March and Smith (1995) and
Hevner et al. (2004) propose the use of DSR meth-
odology in the realms of computer science and
information systems. Banathy (1996) uses DSR
for studying organizations from a system-like
viewpoint. DSR is interested in systems that do
not yet exist or in improved performance of
existing systems (van Aken and Romme, 2009).
These systems or performance improvements
come into being by creating new practices from
scratch or by changing present practices and situ-
ations into desired ones (Simon, 1996; Romme,
2003). DSR aims at developing scientifically
sound solutions (in the form of constructs,
models, methods or instantiations) that can be
applied not only in strong theoretical problems
but also in real-life situations (March and Smith,
1995; Hevner et al., 2004; van Aken, 2005).
Design science research is characterized by the
following interlinked principles:
(1) research questions are driven by field prob-
lems (as opposed to pure knowledge
problems);
(2) there is an emphasis on solution-oriented
knowledge, linking interventions or systems
to outcomes, for addressing stated research
questions;
(3) evaluation outcomes are largely based on
pragmatic validity (i.e. do the actions, based
on this knowledge indeed produce the
intended outcomes?) (van Aken and Romme,
2009). This may generate modifications of re-
search questions and lead to additional cycles
of the research process.
Based on these principles, we followed the DSR
cycle proposed by van Aken and Romme (2009)
and developed our research path along the fol-
lowing stages of activities:
Stage 1. Clarification of field problem to be
addressed
Activities in this stage were triggered by the
search for knowledge gaps regarding service sys-
tems network viability in a business context. Dur-
ing initial problem formulation, the basic
variables involved in the inquiry (value co-
creation, dynamic collaborative environments)
were given both abstract and operational defini-
tions. At the end of this stage, we framed our
broader research goals/questions as a quest
along three axes: (i) what is the relationship be-
tween viability and transformation, within ser-
vice systems network; (ii) whether this
relationship is associational or causal and (iii)
how this combination can create strategic advan-
tage for service systems networks.
Stage 2. Literature-based exploratory research
By aligning with the DSR-based principles pro-
posed by Pawson (2006) and Jesson et al. (2011),
we engaged in the detailed exploration and re-
finement of the aforementioned research goals.
For this stage, we follow a variation of the sys-
tematic literature review (SLR) methodology.
SLR is used across many scientificfields as a ‘sys-
tematic, replicable and transparent process to
synthesize research results and practices’
(Tranfield et al., 2003; Kitchenham et al., 2009).
Given that our research effort aims at creating
mappings between concepts and models in ser-
vice systems networks, we applied a light version
of SLR called systematic mapping study
(Wieringa et al., 2006; Petersen et al., 2008;
Wohlin, 2013; Petersen et al., 2015).
Systematic mapping study is a broad review of
primary studies in a specific topic area that aims
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to identify what evidence is available on the topic
(Kitchenham et al., 2009); that is, map out
existing research findings of primary research in-
cluded in secondary studies, by using different
classifications. In other words, while SLR aims
at synthesizing evidence based on strength of ev-
idence, systematic mapping study is primarily
concerned with structuring a research area
(Petersen et al., 2015).
Given our chosen business context, we first en-
gaged in a preliminary screening of several busi-
ness management disciplines to identify research
efforts linked to service systems networks. The
outcome was a narrower focus on two broad sci-
entificfields: Service Science and Business Trans-
formation. Hence, we created an inventory of
papers in these fields, segmented in the following
categories: service innovation, service system net-
work roles, system viability and business agility.
The critical appraisal process (Pawson, 2006;
Jesson et al., 2011) of the aforementioned activi-
ties and results led us to conclude that the link
between service systems network viability and
transformation requires further exploration. Our
research questions were then defined as follows:
(1) How can an organization (service system)
contribute to service innovation within a ser-
vice systems network; that is, what roles can
it undertake?
(2) How can an organization (service system)
capitalize on resources (acquire—integrate—
provide) within a service systems network;
that is, how does value co-creation vary
across different network roles?
(3) How can a service systems network balance
collaborative activity for service innovation
against potential resource capitalization con-
flicts and opportunities undertaken by indi-
vidual service systems; that is, how can
potential (or even necessary and required)
change of roles by service systems can be
managed for limiting negative equilibrium
effects in a systems network?
Stage 3 Research synthesis—development of a
conceptual model for business transfor-
mation in service systems network
In developing our approach for tackling
the aforementioned questions, we adopted a
research synthesis process for the review findings
(Sandelowski and Barroso, 2006; Cooper, 2017);
specifically, Qualitative Metasummary and Qual-
itative Metasynthesis.
Initially, we clustered our findings in com-
monly accepted knowledge domains. Top-level
domains were Academic and Practitioner.
Second-level domains for Academic were Service
Science, Business Transformation and Service
Systems Networks.
We then synthesized the findings by making
cross-domain connections, based on our research
questions. During this stage, we identified the
underlying conceptual relations signified, albeit
not necessarily explicitly expressed, in all our
findings up to this stage. This resulted in making
the following assumptions for driving the rest of
our approach:
(1) A system that wants to join and operate
within a service systems network may have
to undertake roles and responsibilities that
require significant transformation.
(2) Transformation is usually driven by (i) avail-
able resources (owned, or to be acquired);
(ii) transformation states and (iii) state-to-
state transitions.
The outcome was the development of our design
proposition: a conceptual model for service inno-
vation within service systems networks. Our
model aims to help business organizations (i.e.
service systems) decide upon strategic
choices/directions that balance their desired role
within a service systems network against the net-
work’s goals for viability; the latter defined as a
function of service innovation, collaboration and
resilience in the face of transformation.
Stage 4. Evaluate our propositions
The goal of this stage was to apply our concep-
tual model in real cases of service innovation
within service systems networks. We were inter-
ested in exploring its application in different ser-
vice sectors, in order to evaluate its design, the
extent of real-life applicability and its limitations.
We are thus following the (van Aken and Romme,
2009) principles for testing a design proposition to
find out whether our model works, through prag-
matic experimentation and action research
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Managing Transformation within Service Systems Networks: A System Viability Approach 475

(Argyris et al., 1985; MacLean et al., 2002), in the
realms of (i) tourism services; (ii) financial ser-
vices and (iii) executive education services.
OUR PROPOSED MODEL
The main outcome of our research approach is a
conceptual model for helping a service system
decide how to position (as well as reposition) it-
self within a service systems network, by
attaining a specific role. In our model, roles are
defined as viability-inducing states: they are de-
scribed in terms of three sets of attributes (role el-
ements), which correspond to the CSF of network
viability discussed in the previous sections—ser-
vice innovation, collaboration and resilience.
When a service system plans to change its role,
it must abide to the values of attributes required
by the target role. In other words, a move to a
new role is acceptable if and only if network via-
bility can be satisfied. Figure 1 provides a graph-
ical representation of our model.
The two axes of our model correspond to the
defining characteristics of service systems net-
works, namely, value co-creation and resources
capitalization.
The vertical axis corresponds to the intensity of
value co-creation within a service systems net-
work. Participating service systems are intercon-
nected through value propositions, in order to
achieve their common goals. A ‘low’value on
this axis implies a static type of value co-creation
among them. A ‘high’value implies that the par-
ticipating service systems work closely together.
Hence, the more they collaborate within the net-
work, the more committed they become to the
value co-creation process, thus creating loyalty
benefits for the service systems network
(Jaworski and Kohli, 2006).
The horizontal axis refers to the intensity of re-
sources capitalization by a service system in-
volved in the network. A service system
participates in a service systems network to ac-
quire resources it needs and contributes re-
sources it owns, so that the network develops
and delivers innovative value propositions. Re-
sources capitalization is then defined as a spec-
trum that covers resources acquisition and
resources integration.
Resources acquisition. A service system that
wants to participate (or is already participating)
in a service systems network identifies the
desired specifications for a needed resource
Figure 1 Our proposed model. [Colour figure can be viewed at wileyonlinelibrary.com]
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476 George Bithas et al.

(access rights, type of resource, bundling with
other resources) (Sakas and Kutsikos, 2014).
Resources integration. A service system inte-
grates the acquired resources with its own, for
developing value propositions.
Different combinations of positions along the
two axes of our model define different roles (or
strategies) that a service system may undertake
when involved in a service systems network.
We define four broad roles.
Role 1 can be undertaken by a service system
that aims to acquire new resources and increase
the variety of its value propositions, but without
any customization. It can engage in value co-
creation activities with other systems within a
service systems network because of low co-
creation intensity. This loose collaboration within
a network makes it an easily replaceable partici-
pant; or vice versa, a Role 1 service system may
easily leave a service systems network.
Axes: the defining characteristics of service sys-
tem networks.
Roles: a service system’s function in a network,
constrained by network viability parameters (i.e.
role elements).
RE 1/2/3 (Role elements): the functional compo-
nents of viability in service systems networks.
Transformation path: a recalibration of a service
system network; an expression of a network’s dy-
namic nature, when a service system moves from
one role to another.
ARole 2 service system engages with other sys-
tems within a service systems network for acquir-
ing new resources and integrating them with its
own, in order to develop unique value proposi-
tions. Like a Role 1 service system, it can engage
in basic collaboration activities, but given its de-
sire for resource integration, it becomes more de-
pendent on other network participants. On the
upside, resource integration implies that a Role
2 service system can create interconnected re-
sources. Such resources are, in theory at least, a
catalyst for developing innovative service value
propositions that may create significant competi-
tive advantage (Madhavaram and Hunt, 2008).
Role 3 refers to a service system that partici-
pates in a service systems network for acquiring
new resources, but it does not want to (or simply
cannot) integrate them with its own. Value co-
creation intensity is high, which means that this
system has close collaboration with other service
systems in the network for co-creating value
propositions. Hence, the degree of customization
and the complexity of the generated value propo-
sitions are high.
ARole 4 service system participates in a service
systems network with the goal of acquiring new
resources and integrating them with its own.
The resources integration, in combination with
the high value co-creation intensity, implies that
the system has close collaboration with other ser-
vice systems in the network and it can manage a
web of integrated resources; thus, paving the
way for developing unique value propositions.
Model Attributes
The aforementioned role descriptions highlight a
key challenge for every participant in a service
systems network: achieving own goals while
contributing to the network’s viability. This chal-
lenge is accentuated when we consider the dy-
namic nature of service systems networks:
systems may join or leave a network, or they
may need (or required) to move from one role
to another within the network. Such changes
may result in significant reconfigurations within
the system. They may further affect the structure
and the operation of the whole network, thus po-
tentially creating a chain reaction of
transformations.
Hence, operating successfully within a service
systems network will require (i) system-internal
planning; (ii) network-imposed constraints and
guidelines for ensuring the viability of the net-
work. In order to balance these requirements,
we design our proposed system-relevant roles to
include network-driven parameters for viability.
The main design choice was about the descrip-
tion of roles. In order to ensure that network via-
bility is a ‘built-in’factor, each role is defined in
terms of attributes that correspond to three Role
Elements:
•Role Elements correspond to the network via-
bility parameters described earlier—Collabo-
ration, Service Innovation and Resilience.
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Managing Transformation within Service Systems Networks: A System Viability Approach 477

Table 1 Our proposed model’s attributes
Attribute Description Attribute value (Role 4)
Collaboration C1 Process
development
For successful service innovation, there is a
need to create a supportive environment for
resource integration by focusing on (i)
mechanisms that facilitate interactions
among diverse actors, (ii) adapting internal
processes to accommodate different actors
(roles) and (iii) enhancing the transparency
of resource integration activities in the
service systems network (Lusch and
Nabishan, 2015).
Innovation management processes
Customer offers input in production
processes.
Firms must be prepared to instigate
culture shifts in adopting co-creation
techniques (to see customer as co-designer).
C2 Knowledge and skills
about collaborative
working
The dynamics and complexity of a system
may be influenced by two key variables,
both of which are driven by value co-
creation with customers (Vargo et al., 2008):
first, component knowledge (of each type of
transformation) and second, architectural or
system knowledge (that provides an
understanding of integration and how the
value proposition will enable value co-
creation with customers) (Ng et al., 2011).
High
Portfolio management of a web of integrated
resources
C3
Managing complexity
of service systems
network’s operations
Service systems are physical symbol systems
that compute the changing value of
knowledge in the global service system
ecology (Spohrer and Maglio, 2010b).
Viability of entities within the ecology
depends in part on their strategies for
resource allocation and interaction with
others, which influences their relative
efficiency and capability (Spohrer and
Maglio, 2010a).
High
(Managing a network—dynamic role)
Key skill: Managing multiple third parties
Key knowledge: integration of operations and
technology across parties
Service
innovation
S1 Operant resources
creation
Resources that can be easily transferred or
replicated cannot be the source of
competitive advantage. Distinctive operant
resources (such as human experience,
relational trust, and uncodified knowledge)
are the only foundational basis upon which
the competitive advantages of service
systems can be based (Madhavaram and
Hunt, 2008; Barile and Polese, 2010b).
(a) Interconnected resources
(Continues)
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Table 1 (Continued)
Attribute Description Attribute value (Role 4)
S2 Managing acquired
resources’access
rights
The term ‘access rights’refers to the social
norms and legal regulations that determine
access and use of resources. These norms
and regulations, which depend on relevant
stakeholders, differentiate resources into
several categories (Spohrer et al., 2008): (i)
owned outright, (ii) leased/contracted, (iii)
shared access and (iv) privileged access.
(a) Full ownership
(b) Right to use with change
(Rights are observed and passed to the next
actor. The organization became a member
of a chain.)
S3 Developing value
propositions
The capability of a firm to exploit a business
opportunity does not only arise from its
distinctiveness in resources. It also involves
the harnessing of the firm’s specialized
knowledge and skills in terms of appraisal
and mobilization of these resources for
developing ‘configuration fits’which are
difficult to imitate. Thus, a firm that deploys
such an ability has the potential to develop
unique offerings, as well as to enter into
collaborative ventures for acquiring
complementary or idiosyncratic resources
that further sustain its advantage (Kutsikos
and Mentzas, 2012).
Extensive
Involves multiple stakeholders (ecosystem
actors, service customers)
Attribute Description Attribute value (Role 4)
Resilience R1 Scalability of
participation in a
service systems
network
The interactions and ties among actors
represent an important aspect of any service
system. Service systems are socially
constructed collections of service events in
which participants exchange beneficial
actions through a knowledge-based strategy
that captures value from a provider–client
relationship. In doing so, the service system
is not simply the sum of its parts; rather, the
interactions of the relationship form a higher
order construct that becomes the driver of
value (Lusch et al., 2010). Because actors
need to interact with others, they need to
adapt constantly to each other, and the
system not only becomes more complex but
it also needs to become more adaptive.
Low
–Integration activities and collaborative
working/high value co-creation
development are the bottleneck, that is,
depends on the number of suppliers.
(Continues)
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Managing Transformation within Service Systems Networks: A System Viability Approach 479

•Each Role Element is further described in
terms of attributes. Each attribute corresponds
to an internal system characteristic (capability,
resource etc.) and takes a value that differs
from role to role. The aggregation of attribute
values for all Role Elements for a role comprise
the targets to be met and sustained by a system
that plans to move to this role, while preserv-
ing the network’s viability.
Table 1 depicts role categories and attributes and
provides indicative values for Role 4 in a busi-
ness context.
CONCLUSIONS AND FUTURE RESEARCH
The major challenge that our research aims to ad-
dress is linked to the dynamic, innovation-driven
nature of service systems networks; in particular,
how to balance (i) the potential need for
reconfigurations of a system’s internal structure,
as it moves to a new role within a service systems
network; (ii) the network’s goals for sustaining
viability, which may require further reconfigura-
tion of the network and/or internal
reconfigurations of other network participants.
In such a scenario of cascading transforma-
tions, success (both for the network and for each
participating system) is a matter of planning
ahead and deciding upon the ‘transformation
maturity gap’—the distance between the current
and the target role for a service system within a
service systems network.
The main outcome of our approach is a two-
dimensional conceptual model for (i) helping a
service system assess what it will take to bridge
this gap; (ii) promoting network viability, by in-
fusing relevant parameters in the definition of
each role. The two axes of the model (value co-
creation, resources capitalization) broadly define
a service systems network, while different combi-
nations of positions along the axes define differ-
ent roles (or strategies) that a service system
may pursuit within the network.
In this context, our proposed model defines
four roles described in terms of three viability-
based attributes: collaboration, service innova-
tion and resilience. Different values for these
Table 1 (Continued)
Attribute Description Attribute value (Role 4)
R2 Complexity of
collaborative IT
platforms
Technology is key operant resource for service
innovation, which digitally enabled service
platforms can liquefy (i.e. decouple from
their original instantiation in physical form)
and mobilize so as to be readily available to
actors engaged in service exchanges (i.e.
increasing resource density) (Akaka and
Vargo, 2014; Lusch and Nabishan, 2015).
Low
(Technology has increased the ability to
liquefy and the transfer of information.)
R3 Enterprise
boundaries
The notion of co-creation is inherently
associated with vanishing boundaries
between actors within markets (Barile et al.,
2012).
There are no boundaries among ecosystem
actors.
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attributes clearly differentiate one role from an-
other. When a service system plans to move from
one role to another, it can use our model as a
sign-posted transformation path, in order to
bridge the aforementioned gap: a move to a
new role will be successful (both for the service
system and the network) if the attribute values
of the target role can be safely reached and
sustained.
We are currently testing our model in various
business contexts, which helps uncover model
limitations, as well as further research paths.
During an ongoing application in a service sys-
tems network in the UK tourism sector (the Lake
District business ecosystem), it has become ap-
parent that further additions and refinement of
our roles and role attributes are important. For
example, managing information flows within a
systems network may be a key contributor to net-
work viability and thus may lead to the introduc-
tion of one or more attributes.
The need for using simulation tools was addi-
tionally uncovered, for visualizing the reconfigu-
ration effects of service systems’decisions
regarding the move to a new role within a net-
work. Thus, our next level of development will
focus on requirements engineering, in order to
account for a range of goals and requirements
that a service system may have for joining in
and operating within a service systems network.
Asafirst step, we are using the e3-value ontology
proposed by Gordijn (2002) and Gordijn and
Akkermans (2003). E3-value is based on a combi-
nation of computer science/management science
concepts, exemplified by two characteristics that
fit our research goals. First, it is driven by eco-
nomic value; in particular, it is focused on
analysing relationships among nodes in a net-
work, in both qualitative and quantitative ways.
Second, e3-values are accounting for multi-
viewpoint requirements engineering and semi-
formal conceptual modelling.
In parallel, we are exploring the role of motives
that may drive a service system to make role-
changing decisions. Our current focus is on the
i* methodology (Yu, 2011) for analysing the co-
herence of a service system’s goals against re-
quirements for operating within a service
systems network. By developing relevant goal
models, we aim to (i) simulate how a system
can assess whether its goals about operating
within a service systems network are met and
to what extent; (ii) describe causal relations
among goals and track them, as a service system
changes roles within a network.
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