Software Ecosystems Governance
A Systematic Literature Review and Research Agenda
Carina Alves
1
, Joyce Oliveira
1
and Slinger Jansen
2
1
Centro de Informática, Universidade Federal de Pernambuco, Recife, Brazil
2
Department of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands
Keywords: Software Ecosystems, Governance, Health, and Systematic Literature Review.
Abstract: The field of Software ecosystems is a growing discipline that has been investigated from managerial, social,
and technological perspectives. The governance of software ecosystems requires a careful balance of control
and autonomy given to players. Orchestrators that are able to balance their own interests by bringing joint
benefits for other players are likely to create healthy ecosystems. Selecting appropriate governance
mechanisms is a key problem involved in the management of proprietary and open source ecosystems. This
article summarizes current literature on software ecosystem governance by framing prevalent definitions,
classifying governance mechanisms, and proposing a research agenda. We performed a systematic literature
review of 63 primary studies. Several studies describe governance mechanisms, which were classified in
three categories: value creation, coordination of players, and organizational openness and control. The
number of studies indicates that the domain of software ecosystems and their governance is maturing.
However, further studies are needed to address central challenges involved on the implementation of
appropriate governance mechanisms that can nurture the health of ecosystems. We present a research
agenda with several opportunities for researchers and practitioners to explore these issues.
1 INTRODUCTION
In the last decade, a large amount of research has
been devoted to investigate the field of software
ecosystems from managerial, social, and
technological perspectives (Barbosa et al., 2013),
(Bosch, 2014). Software ecosystems are sets of
actors functioning as a unit and interacting with a
shared market for software and services, together
with relationships among them (Jansen et al., 2009).
A software ecosystem frequently relies on a
platform on which extenders can build specific
solutions to create complementary value (Jansen et
al., 2012). Independent developers can extend and
enrich the platform while sharing costs and risks
with the platform owner. Examples of successful
software platforms are Apple’s iOS, Google Apps,
and the Mozilla Firefox browser. The leading firm,
typically called the orchestrator (or keystone) firm,
must promote the sustainable development of the
ecosystem by defining strategies and orchestrating
the activities of players. The orchestrator is
responsible for managing the evolution of the
enterprise architecture (Iyer et al., 2007) and the
interactions among all actors within the ecosystem
(Manikas and Hansen, 2013a). The governance of
software ecosystems requires a careful balance of
control and autonomy given to players.
Orchestrators that are able to balance their own
interests by bringing joint benefits for other players
are likely to create healthy ecosystems. Software
ecosystems governance has become a crucial
managerial aspect for proprietary platform owners
and open source communities.
According to Tiwana (2010), governance
mechanisms are employed to establish the level of
control, decisions rights, and scope of proprietary
versus shared ownership. There are several models
to govern software ecosystems. For instance, GNU
Linux is an open source ecosystem with a thriving
community of developers. Apple’s iOS is a
prosperous example of proprietary ecosystem with
tight control mechanisms. Google built a lively
ecosystem around its Android open source
community named the “Open handset Alliance”. On
the other hand, Nokia’s Symbian is an open source
operating system that failed to create a vibrant
ecosystem due to its inability to attract partners and
develop a rich set of apps (West and Wood, 2008).
Alves, C., Oliveira, J. and Jansen, S.
Software Ecosystems Governance - A Systematic Literature Review and Research Agenda.
DOI: 10.5220/0006269402150226
In Proceedings of the 19th International Conference on Enterprise Information Systems (ICEIS 2017) - Volume 3, pages 215-226
ISBN: 978-989-758-249-3
Copyright © 2017 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
215
The examples above show that choosing the right
ecosystem strategies and governance mechanisms
are life-or-death decisions for orchestrator
organizations. In fact, companies engaging in an
ecosystem are mutually dependent on each other for
survival.
We define software ecosystem governance
mechanisms as managerial tools of participants in
software ecosystems, i.e., orchestrators and platform
extenders that have the goal of influencing an
ecosystem's health. Ecosystems are healthy when
they exhibit longevity and propensity for growth
(Den Hartigh and Visscher, 2006).
Selecting appropriate governance mechanisms is
not a trivial task. The challenge is to bound players
actions without excessively constraining the desired
level of innovation and value creation in the
ecosystem. This situation creates fine tension
between control and autonomy. Balancing these
tensions is one of the main goals of software
ecosystem governance. The correct implementation
of governance mechanisms can accommodate these
tensions towards a sustainable and healthy
ecosystem. On the other hand, ineffective
governance can result in a declining growth of the
ecosystem (Wareham et al., 2014). The challenge of
selecting ecosystem governance strategies that
contributes towards the ecosystem health has driven
us to conduct a systematic literature review. Our
review aims at synthetizing the increasing number of
studies in the field of software ecosystem
governance.
This article is organized as follows. Section 2
describes the research method. The results of the
review are presented in Section 3. To discuss the
results of our review and propose future areas for
investigation, a research agenda containing six areas
of interest is proposed in Section 4. Then, we discuss
threats to validity in Section 5. Finally, Section 6
concludes this article.
2 RESEARCH METHOD
A Systematic Literature Review (SLR) is a means
for answering specific research questions, examining
a particular research topic, or phenomenon of
interest by systematically identifying, evaluating,
and interpreting available relevant research. Our
review protocol follows guidelines from Kitchenham
and Charters (2007). We undertook the review of
studies following these activities: defining research
questions, searching relevant studies, applying
inclusion/exclusion criteria, assessing the quality of
studies, analysing data, and synthesis.
2.1 Research Questions
We specified two research questions to guide our
study:
RQ1. How is governance characterized in
software ecosystems literature?
RQ2. What are the mechanisms proposed to
govern software ecosystems?
Governance is a well-established concept
primarily associated with the needs to protect
investment and ensure the sustainability of
businesses through time (Hoogervorst, 2009).
Corporate governance refers to the mechanisms,
processes, and relations by which corporations are
controlled and governed (OECD, 2004). Governance
involves a set of principles to direct the distribution
of rights and responsibilities among stakeholders. In
RQ1, we present and discuss available definitions
for software ecosystems governance proposed by
primary studies. Then, we compare the definitions
available and propose an integrated definition for the
term.
Traditional corporate governance mechanisms
include monitoring actions, policies, and decisions
by aligning the interests of different stakeholders.
According to Croteau et al. (2013), IT governance
can be organized by the attributes: structure, process,
and participants. In this SLR, we opted not to follow
a pre-existing classification. Instead, we classify the
governance mechanisms based on the data gathered
from the primary studies following a thematic
analysis approach (Cruzes and Dybå, 2011). Our
goal to answer the second question (RQ2) is to
identify the mechanisms proposed by current
literature to govern software ecosystems.
2.2 Search Process
To guide the systematic literature review, a protocol
was developed to specify the steps and criteria to
undertake the review. The review protocol includes
details of how different types of studies will be
located, appraised, and synthesized (Brereton et al.,
2007).
The strategy to collect studies included the
following steps: (i) automatic search of electronic
databases (ii) manual search of journals,
conferences, and workshops (iii) analysis of
reference lists from other secondary studies in
software ecosystems. The automatic search was
executed on the following databases: ACM Digital
Library, IEEE Xplore Digital Library, Science
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Direct, and SpringerLink. We used two independent
search strings: “software ecosystem”, “platform
ecosystem”. We opted to use generic terms to avoid
over restricting the search process. In the early
stages of our research we tried to use the search
string “software ecosystem AND “governance”.
However, we considered that using these combined
keywords the results retrieved from the search
engines were very limited. In addition, we conducted
a manual search in the following journals,
conferences, and workshops:
Information and Software Technology;
Journal of Software Systems;
International Conference on Software Business;
International Workshop on Software
Ecosystems.
To complement our manual search, we analysed
the references of the following reviews in the field
of software ecosystems: (Barbosa et al., 2013;
Franco-Bedoya et al, 2014; Manikas and Hansen,
2013a; Manikas, 2016). Although the scope and
research questions of these reviews are different
from ours, we examined the list of articles to correct
any eventual omission of studies from the other
search procedures. 7 studies [S13, S17, S18, S25,
S26, S41, S61] were obtained from the analysis of
secondary studies described above. Finally, we
collected additional three studies [S31, S53, S57]
that were recommended by experts in the field.
2.3 Inclusion and Exclusion Criteria
We adopted the following inclusion criteria to select
articles: (i) studies written in English, (ii) studies
that answer at least one research question. The
exclusion criteria adopted was: (i) secondary studies
(e.g. mapping studies and systematic literature
reviews), (ii) technical reports, abstracts, and
whitepapers, (iii) duplicate reports of the same
study.
The literature collection started with 997 articles
returned from the electronic and manual search. The
automatic search was conducted on the 5th of
January 2016. We did not restrict year range in our
search. Then, we excluded articles based on titles
and abstract that did not satisfy our inclusion
criteria. In practice, we assessed if the title and
abstract are likely to answer at least one RQ.
Whenever we were in doubt we included the article
for further analysis of its full content. After this step,
we included 592 studies. Then we read the full
content of the articles and selected 67 primary
studies. In a final step, a quality assessment of each
article was conducted and we finally selected 63
articles (studies are listed in the Appendix).
The quality assessment criteria based on Brhel et
al., (2015) are described below:
Is there a clear statement of the research goals,
e.g. in an explicitly verbalized research question?
Is there an adequate description of the context in
which the research was carried out?
Only applicable to empirical research articles:
- Is the research method explicitly stated?
- Which research method was chosen?
2.4 Data Extraction and Analysis
We used a database to store data from the selected
studies. Two researchers extracted data from the
studies. Several discussion meetings were held with
all authors to compare extractions, clarify
uncertainties, agree on discrepancies, and perform
sanity checks. To answer RQ1, we simply searched
the term “governance” in the primary studies and
checked if the article provided a definition for
governance in the context of software ecosystems.
To answer RQ2, we used thematic analysis as
synthesis method, following the recommended steps
proposed by (Cruzes and Dybå, 2011). We identified
the relevant codes from primary studies. Then, we
merged the codes into key themes. We considered
that governance mechanisms were encapsulated in
related terms, such as: “manage”, “govern”,
“control”, “strategy”, “orchestration” and “critical
factors”.
3 RESULTS
3.1 Overview of Studies
63 studies were identified in our systematic literature
review, as listed in the Appendix. Our final list
included articles published between 2002 and 2016.
We observed an increasing number of studies
published over the last few years, where the peak
publication period is from 2012 to 2015 (36 articles,
57%).
The most popular publication channels are:
ICSOB (8 articles, 13%), IWSECO (5 articles, 8%),
ECSA (3 articles, 5%), IST (5 articles, 8%), JSS (2
articles, 3%). In particular, the following events are
dedicated to the field of ecosystems: IWSECO,
MEDES, EWSECO, WEA, DEST. These results
confirm that the field of software ecosystems has
been receiving a growing attention from the
academic communities of information systems,
software business, and software engineering.
Software Ecosystems Governance - A Systematic Literature Review and Research Agenda
217
Figure 1 presents the main software ecosystems
investigated by the primary studies. Apple and
Android are the most frequent ecosystems examined
(with 4 studies both ecosystems), followed by
Siemens, IBM, GX Software and Eclipse (3 studies
each ecosystem).
Figure 1: Software ecosystems investigated by the studies.
We noted that both open source and proprietary
ecosystems have been equally analysed. It is a good
sign that researchers are focusing on the specific
managerial issues faced by open source and
proprietary ecosystems. The diversity of ecosystems
being investigated reinforces the wide perspective
that the software ecosystems community is gaining
regarding the differences between open source and
proprietary ecosystems.
Figure 2 shows the research type followed by the
studies. We adopted the classification proposed by
Wieringa et al., (2006). Petersen et al., (2015)
provides helpful decision criteria on how to classify
the studies. According to the classification, studies
can be classified into six research types, namely:
Solution Proposal – The article proposes a novel
solution or a significant improvement of an existing
technique without a full validation.
Philosophical Paper – The paper proposes a
conceptual framework and a new way to look at
things.
Opinion Papers – The paper presents the
author’s opinion about something.
Experience Paper – The paper describes the
practical experience of the author who is generally
an industry practitioner.
Validation Research – The paper describes an
empirical validation of a solution done in the lab.
Examples of studies include: student case study,
mathematical analysis, prototyping, laboratory
experiments, and simulation.
Evaluation Research – The paper presents a real-
world industrial evaluation of a solution. It includes:
industrial case study, controlled experiments with
practitioners, practitioner targeted survey, action
research, and ethnography.
Figure 2: Research design adopted by the studies.
The most common type of study identified in our
review is evaluation research (27 studies). This
result suggests that the majority of studies explore
the field from a practical perspective by conducting
empirical studies of real ecosystems. 21 studies are
classified as philosophical papers. 11 studies
propose a solution such as new techniques, models,
and methods. 2 studies present validation research.
Finally, we identified 2 experience papers. We did
not include any opinion paper in our list of primary
studies.
3.2 Answering RQ1: How is
Governance Characterized in
Software Ecosystems Literature?
Our results show that the concept of governance is
gaining importance in software ecosystem literature.
9 studies [S1, S4, S20, S21, S28, S32, S51, S54,
S62] explicitly define what is software ecosystem
governance. Jansen [S34] proposes that governance
is one of the key domains of the Open Software
Enterprise Model. The study adopts the definition of
governance given by Dubinsky and Kruchten [S12],
who consider governance as “the way an
organization is managed, including its powers,
responsibilities, and decision-making processes”.
According to Jansen et al. [S32], it also involves the
assignment of roles and decision rights, measures,
and policies. A fundamental governance decision
that orchestrators must make is how much power is
given to the community and how much control it
keeps for itself. Jansen and Cusmano [28] and van
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Angeren et al. [S54] consider that ecosystem
governance “involves the use of strategic procedures
and processes to control, maintain, or change the
ecosystem”. Study [S54] also states that software
ecosystems governance “encompasses both
technical and managerial aspects, including the
management of the software platform and its
interfaces, definition of business and partnership
models, and establishment of entry barriers”.
Baars and Jansen [S4] propose a framework for
software ecosystems governance. They define
software ecosystems governance as: “procedures
and processes by which a company controls,
changes or maintains its current and future position
in a software ecosystem on all different scope
levels”. Studies [S1], [28] and [S62] adopt the same
definition. Albert and colleagues [S1] present a
software ecosystem governance approach for
enabling IT architecture based on software asset
management. In [S28], Jansen and Cusumano
propose a governance model for ecosystem health
preservation and improvement. Wnuk et al., [S62]
evaluate the model proposed in [S28] by means of a
case study in a hardware-dependent software
ecosystem.
We noted that several primary studies discuss the
classical tension between open and closed
governance models. Jansen et al., [S32] suggest that
companies benefit from opening-up their business
models. It includes sharing strategic knowledge,
making the ecosystem strategy explicit to all players,
and coordinating actions. The authors propose an
openness degree to assess how open a company is.
In [S13], the authors do not define what is
governance in the context of ecosystems, but they
provide a rich discussion on the tensions between
open and closed governance models as platforms
mature. The study proposes that hybrid governance
models are more suitable for both proprietary and
shared platforms. Such model is characterized by the
centralized control over platform technology and
shared responsibilities for the ecosystem
community.
Ghazawne et al., [S20] argue that the governance
of platform ecosystems involves “a delicate balance
act of the platform owner, trying to keep control of
the platform while simultaneously seeking to expand
the diversity of potential developers”. According to
Tiwana et al. [S51], governance broadly refers to
who decides what in an ecosystem”. Study [S51]
investigates the evolution of platform-centric
ecosystems and proposes that governance can be
analyzed from three facets: i) how decision rights
are divided between the platform owner and app
developers, ii) what types of formal and informal
control mechanisms are used by the platform owner,
and iii) how ownership is regulated if the platform is
property of a single company or shared by multiple
owners. [S51] also states that ecosystem governance
involves sharing responsibilities and authority,
aligning incentives, and sharing stakes”. Goldbach
and Kemper [S21] adopt the same definition of
platform governance given by study [S51] to
understand how control mechanisms imposed by the
platform owner affects the platform stickiness. All
primary studies that answer this research question
suggest that a key challenge faced by platform
owners is balancing their own strategic objectives
with the goals and activities of players within the
platform. Such delicate balance becomes critical for
software ecosystems to thrive.
7 studies [S10, S28, S32, S41, S54, S55, S62]
indicate that ecosystem governance influences the
health and sustainability of ecosystems. This means
that governance strategies and managerial decisions
taken by orchestrators will affect the healthy
evolution of the entire ecosystem. The primary
studies suggest that health metrics provide
operational indicators on how software ecosystems
are governed. For instance, if an open governance
model is adopted by the ecosystem, more autonomy
will be given to players to shape their future growth
and expansion. Otherwise, in a closed governance
model, the orchestrator holds substantial power and
control over the players. Consequently, the
orchestrator has more responsibility towards the
prosperity and overall health of the ecosystem.
Defining the openness strategy is an important
decision that orchestrators must make when
structuring the governance model for their software
ecosystems. This decision will have a significant
impact on the evolution of the enterprise architecture
of integrated systems. In particular, players must
decide if their enterprise architecture will follow a
centralized, federated or decentralized organizational
structure (Rychkova et al., 2013). We conclude this
section by proposing an integrated definition for
software ecosystems governance: all processes by
which a player creates value, coordinates
relationships, and defines controls.
3.3 RQ2: What are the Mechanisms
Proposed to Govern Software
Ecosystems?
We define software ecosystem governance
mechanisms as managerial tools of players in
software ecosystems that have the goal of
Software Ecosystems Governance - A Systematic Literature Review and Research Agenda
219
influencing an ecosystem's health. We observed that
frequently authors use terms such as “orchestration”
and “management” to refer to what can be
understood as a governance mechanism. To classify
the 63 studies, we propose three main categories of
governance mechanisms:
Value Creation – involve mechanisms to
generate and distribute value for the whole
ecosystem. Value creation mechanisms are generally
proposed and nurtured by the orchestrator (i.e.
platform and/or marketplace owner), who must
understand how to create value that is appreciated
both by partners and customers. In this context, it is
important to identify sources of value (such as
licenses and revenue models), and stimulate the co-
creation of value among players, by means of
innovation, investments, and cost sharing. As a
result, the ecosystem can attract and retain partners
who will mutually benefit from the value distributed
within the ecosystem. This category covers all the
incentives and benefits that players can gain from a
software ecosystem.
Coordination of Players – describe mechanisms
to maintain the consistency and integration of
activities, relationships, and structures of the
ecosystem, for both customers and partners, leading
to a harmonious and effective coordination with
players in the ecosystem. We identified mechanisms
to stimulate partnership models, define roles and
responsibilities for players, improve communication
channels within the ecosystem, and nurture
collaborations. In addition, primary studies propose
mechanisms to manage critical issues, such as:
conflicts, resources, risks, and expectations. This
category focuses on the coordination aspects of
governance, whereas the next focuses on strategic
decisions of openness and control.
Organizational Openness and Control – these
mechanisms capture the notorious tension between
open versus closed organizational models and
represent how control will be retained by the
orchestrator to guarantee its power position and how
autonomy will be given for the community to make
their own decisions independently. On the one side,
orchestrators can support autonomy, distribute
power, and share knowledge regarding technological
roadmaps and architectural decisions. On the other
side, orchestrators can keep control by defining
entry requirements, establishing quality standards,
and through certifications.
Table 1 shows the classification of governance
mechanisms proposed by the primary studies. We
observed that the most cited mechanisms are: attract
and maintain partners (28 articles, 44%), share
knowledge (20 articles, 31%), promote innovation
(25 articles, 39%), manage licenses (21 articles,
33%). We do not claim that these are the most
important governance mechanisms, as several
studies suggest that the governance must match the
specific context and market drivers involved in the
ecosystem [S4, S13, S25 S32, S43].
4 DISCUSSION AND RESEARCH
AGENDA
The synthesis provided by our literature review
enables further analysis and insights regarding the
future role of software ecosystems governance in
software producing organizations. We express the
following needs, which are requirements that should
to be met to advance the field of software
ecosystems governance. The following statements
can contribute to the overall research agenda on
software ecosystems and serve as an addendum to
the works of Jansen et al (2009), Barbosa et al
(2013), Manikas (2016), and Axelsson and Skoglund
(2016).
1. The Need for a Common Vocabulary in
Software Ecosystems Governance - The numbers
of publications in this domain emphasize that the
field of software ecosystems governance is
maturing. Increasing numbers of work take positions
on definitions of the concepts central to software
ecosystems: health (Manikas and Hansen, 2013b),
governance (this work), open source ecosystems
[S34], developer ecosystems [S33], and quality in
software ecosystems (Axelsson and Skoglund,
2016), each of these concepts is settling in as an
established term in the ecosystems discourse. We
identified that several studies adopt related terms
such as management and orchestration to refer to
governance mechanisms. Therefore, we suggest the
need to establish a common glossary and conceptual
framework that collects these definitions into one
tome of ecosystems governance knowledge.
2. The Need for Practical Governance Guidance
- Even though there exists an extensive body of
knowledge on software ecosystems governance, it is
hard for practitioners to extract practical and
strategic guidance from the works under study.
There is a need for more consumable and practical
knowledge for practitioners. Other relevant studies
for practitioners interested on creating health
ecosystems dashboards, include Goeminne and
Mens (2013) on GitHub analysis, collecting
intelligence on the progress of particular ecosystems.
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Table 1: Governance Mechanisms in Software Ecosystems.
Governance Mechanisms Studies Number of Studies
Value Creation
Promote innovation S61, S7, S32, S50, S40, S48, S52, S9, S47, S3, S7, S45, S10, S8, S35,
S27, S18, S17, S19, S61, S38, S57, S24, S43, S44
25 (39%)
Manage licenses S16, S32, S41, S40, S1, S3, S6, S58, S28, S2, S51, S63, S8, S27, S18,
S13, S17, S57, S31, S22, S24
21(33%)
Create revenue
models
S7, S3, S45, S58, S4, S5, S7S6, S28, S10, S62, S30, S23, S27, S61, S38,
S53, S57, S23, S36, S39
20 (31%)
Attract and maintain
varied partners
S61, S32, S29, S52, S47, S45, S15, S58, S4, S6, S10, S62, S55, S46, S63,
S35, S27, S18, S17, S61, S38, S53, S57, S42, S19, S23, S26, S36
28(44%)
Stimulate partner
investments and
share costs
S61, S56, S3, S45, S8, S27, S22, S23, S43 9 (14%)
Coordination of Players
Create partnership
models
S32, S56, S54, S4, 28, S62, S55, S49, S30, S8, S27, S53, S31, S19, S24 15 (23%)
Define rules to
manage relationships
S32, S40, S29, S56, S52, S9, S3, S4, S5, S46, S2, S63, S35, S27, S57,
S42, S36
17 (26%)
Establish roles and
responsibilities
S41, S50, S40, S56, S3, S15, S4, S5, S49, S46, S51, S63, S27, S13, S42,
S26, S37
17 (21%)
Enable effective
communication
channels
S41, S29, S48, S52, S9, S3, S11, S14, 28, S16, S27, S31, S37 13 (20%)
Manage conflicts S32, S52, S15, S8, S27, S57, S31, S42, S19 9 (14%)
Manage resources S1, S52, S9, S47, S3, S15, S10, S46, S20, S35, S42, S26, S36, S44 14 (22%)
Manage risks S50, S40, S56, S52, S58, S46 , S30, S8, S18, S17, S57, S22, S39, S43 14 (22%)
Manage expectations S47, S49, S16 3 (4%)
Nurture
collaborations
S61, S50, S52, S46, S58, 28, S62, S55, S49, S46, S35, S17, S42, S44 14(22%)
Organizational Openness
and Control
Support autonomy S7, S50, S52, S3, S48, S4, S7, S46, S20, S51, S35, S18, S17, S61, S42 15(23%)
Share knowledge S16, S32, S50, S40, S29, S48, S52, S3, S4, S11, S62, S30, , S20, S35,
S18, S17, S61, S57, S31, S37
20 (31%)
Distribute power S32, S50, S52, S3, S15, S46, S16, S51, S27, S37 10 (15%)
Define entry
requirements
S54, S45, S4, S28, S62, S30, S18, S38, S53, S24, S36 11 (17%)
Share architectural
decisions
S16, S29, S48, S1, S52, S9, S47, S3, S5, S58, S28, S62, S2, S51, S27,
S11, S14
17 (21%)
Share roadmaps S52, S58, S28, S27, S57, S31 6 (9%)
Define quality
standards and
certifications
S32, S41, S50, S40, S56, S58, S28, S62, S55, S30, S38, S57, S22 13 (20%)
These tools can form the basic groundwork under
mature evaluation mechanisms and tools for large
open and commercial software ecosystems.
3. The Need for Analysing the Interplay between
Governance Mechanisms and Health Metrics –
Our study indicates that health metrics provide
operational indicators on how software ecosystems
are governed. Therefore, by selecting appropriate
health metrics, players can govern the ecosystem
towards a sustainable path. A challenge remains on
how to implement governance to foster innovation
and encourage autonomous behaviour for diversity,
without undermining the quality of software and
accountability of players’ actions [S20]. The tension
between control and autonomy must be
appropriately balanced. Understanding how the
implementation of specific governance mechanisms
affects the success of ecosystems and the underlying
enterprise platform is an exciting problem for
scholars in the field.
4. The Need for Understanding the Governance
of Developer Ecosystems - The developers’ and
niche players’ impacts in ecosystems are amplified
by the success of the ecosystem. Examples like
Farmville for Facebook and Angry Birds for iOS
illustrate how ecosystems grow immensely through
the success of its constituents. The developers are
the starting point for any software ecosystem; hence
the recent increase of interest in developer
ecosystems. There is a need for further
understanding developers interests and behaviours
[S38]. Barriers to entry, platform stickiness, and
developer attraction are factors that require further
research. An extension to this perspective is a need
for further study of enterprise architecture and
delivery mechanisms that enable software
ecosystems [S33]. Orchestrators must understand
developers’ motivations and expectations to adopt
Software Ecosystems Governance - A Systematic Literature Review and Research Agenda
221
appropriate governance mechanisms.
5. The Need for Studying Governance in Open
Software Ecosystems - Open source ecosystems
exhibit different properties than more traditional
closed and commercial ecosystems. The openness of
a platform permeates through every aspect of an
ecosystem, whether it is about ownership of the code
or about mechanisms around supporting tools, such
as application stores. These openness questions also
play a part in the architecture of a platform itself:
without an open platform architecture, extenders
cannot extend it. In our SLR, we found no study that
presented a comparative analysis of governance
mechanisms employed by open source versus
proprietary ecosystems. This is a promising line of
research.
6. The Need for Understanding the Interactions
between Ecosystems – Even good governance can
lead to the demise of an ecosystem due to external
factors. When looking at the governance and health
of the Symbian ecosystem in 2007, it would have
been hard to predict its demise. One can speculate
about its poor business support from Nokia and
fundamental faults in the business model of
Symbian. However, it is hard to ignore the
impending doom coming from the iPhone after
2007: its high rate of adoption and superior
technology simply blew the Symbian ecosystem
away. The challenge for governance research in the
next decade will be to analyse and understand the
interplay between large ecosystems. As long as
standards, age-old ecosystems, and settled industry
stacks can be blown away or grow exponentially
through the workings of other ecosystems, we must
develop governance tools and management practices
that focus on the robustness of software ecosystems
that can prepare for surviving in such storms.
5 THREATS TO VALIDITY
Our study faced similar validity threats as any other
systematic literature review. Two of the main
limitations in a review are the bias in selection and
data extraction procedures (Kitchenham and
Charters, 2007). Software ecosystem is a
multidisciplinary field covering studies from
software engineering, information systems,
organization, and management science. To limit the
threat of not including relevant primary studies, we
adopted a search strategy with generic keywords to
retrieve as many articles as possible that were
related to the research topic. We complemented the
automatic search with manual searches in the main
journals, conferences, and workshops where studies
in software ecosystems have been published. In
addition, we also analysed the primary studies of
other literature reviews published in the field.
In order to mitigate the impact of selection bias,
we defined the review protocol with clear inclusion
and exclusion criteria for each selection step. In the
first selection step, a large number of irrelevant
studies were removed by analysing title and abstract.
One author performed this task. In the second
selection step, two authors screened the content of
studies and constantly crosschecked the preliminary
selection results. We also analysed the potential
primary studies against a quality assessment
checklist. With respect to bias in the data extraction,
we had some problems to extract relevant
information from primary studies. This problem was
more critical to answer RQ2. We observed that
studies use different terminologies to describe
aspects related to governance mechanisms and
metrics to operationalize health. This specific
limitation of the software ecosystem literature was
discussed on item 1 of our research agenda
presented in Section 4. In several occasions we had
to interpret the subjective information provided by
the articles. To minimize interpretation bias, we
conducted a very careful reading and had several
discussion meetings among the authors during the
data extraction phase.
6 CONCLUSIONS
The governance of software ecosystems is currently
one of the largest challenges software platform
companies need to deal with for the sake of their
survival. Governance includes technical decisions
regarding the enterprise architecture, social aspects
involving the coordination of players, and business
strategies. Therefore, governance impacts all three
dimensions of software ecosystems (i.e. technical,
social and business).
From 63 studies analysed, we conclude that
software ecosystems governance is defined as all
processes by which a player creates value,
coordinates relationships, and defines controls. An
overview of software ecosystem governance
mechanisms is provided, in which we classify
governance mechanisms as belonging to
mechanisms for value creation, coordination of
players, and organizational openness and control.
We identify approximately 20 governance
mechanisms that can be directly implemented by
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players in software ecosystems and studied by the
research community. To our knowledge there is no
study in the field to systematically structure and
classify governance mechanisms reported in the
literature.
The practical impact of this work is that for
practitioners in the software industry light is shed on
the concept of ecosystem governance. Although we
do not claim that the overview of governance
mechanisms is complete, it provides a useful
strategic tool for practitioners and a conceptual base
for researchers. The scientific impact of the work is
threefold: we provide insight into the concepts of
software ecosystems governance and present
mechanisms to perform governance. In future
research, we aim at developing a governance
conceptual model for software ecosystems.
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