Platform Patterns—Using Proven Principles toDevelop
MarvinDrewel1 · LeonÖzcan1· JürgenGausemeier1· RomanDumitrescu1
Received: 27 February 2020 / Accepted: 14 February 2021
© The Author(s) 2021
Hardly any other area has as much disruptive potential as digital platforms in the
course of digitalization. After serious changes have already taken place in the B2C
sector with platforms such as Amazon and Airbnb, the B2B sector is on the thresh-
old to the so-called platform economy. In mechanical engineering, pioneers like GE
(PREDIX) and Claas (365FarmNet) are trying to get their hands on the act. This
is hardly a promising option for small and medium-sized companies, as only a few
large companies will survive. Small and medium-sized enterprises (SMEs) are
already facing the threat of losing direct consumer contact and becoming exchange-
able executers. In order to prevent this, it is important to anticipate at an early stage
which strategic options exist for the future platform economy and which adjustments
to the product program should already be initiated today. Basically, medium-sized
companies in particular lack a strategy for an advantageous entry into the future
The paper presents diﬀerent approaches to master the challenges of participating in
the platform economy by using platform patterns. Platform patterns represent proven
principles of already existing platforms. We show how we derived a catalogue with
37 identiﬁed platform patterns. The catalogue has a generic design and can be cus-
tomized for a speciﬁc use case. The versatility of the catalogue is underlined by
three possible applications: (1) platform ideation, (2) platform development, and (3)
Keywords Digitalization · Digital platforms· Platform economy· Foresight·
Strategic product planning· Multisided markets· B2B-platforms· Platform markets
* Marvin Drewel
Extended author information available on the last page of the article
/ Published online: 10 March 2021
Journal of the Knowledge Economy (2021) 12:519–543
The Disruptive Potential ofDigital Platforms
In the course of digitization, the concept of digital platforms or IT platforms has
been the subject of a veritable hype in recent years (Engels etal.,, 2017) and
is experiencing an impressive renaissance (Linz etal., 2017). Digital platforms
are putting established companies across industries under pressure. Former well-
established enterprises like Nokia or Blackberry are now dominated by platform
enterprises like Apple. Based on these changes, van Alstyne etal. have formu-
lated the somewhat bold thesis that “only those who understand the principle
and transform their business model will survive” (Alstyne etal., 2016). Up to
now, this thesis has been mainly applied to the business-to-consumer (B2C) sec-
tor. There, digital platforms such as Uber, Airbnb, or Amazon have radically
changed their industries and displaced formerly established companies (Libert
etal., 2016). At present, such a development is also apparent in the B2B sector
and here in particular in mechanical engineering and related sectors such as the
electronics industry, automotive industry, or medical technology (Lerch et al.,
2019). Leading companies are stepping out of their core business and develop
own platforms. Additionally, agile start-ups begin to build platform solutions
and services for digital platforms (Koldewey etal., 2019). Driven by digitization,
such platforms can link actors who have never been in contact with each other
(Altman etal., 2013).
Following Parker etal., the disruptive potential of digital platforms is based
on two major economic advantages: (1) marginal costs and (2) network eﬀects.
These advantages enable companies to expand their platform businesses with rel-
atively low investments compared with traditional businesses (Cusumano etal.,
2019; Parker etal., 2017). Marginal costs describe the additional costs that occur
if an additional unit of a certain product or service is being produced (O’Sullivan
& Sheﬀrin, 2003). For instance, if the Hilton Worldwide Holdings Inc. decides to
expand to a new market, they need to invest in new buildings and new personal
staﬀ. Contrary to this, if Airbnb decides to expand to a new market, they do not
need such investments. The new accommodations are provided by private home
owners who also act as staﬀ for the consumers of Airbnb. The additional costs
for these new accommodations are almost not existing which allows platforms
to expand their business with minimal costs, once their platforms are established
and running (Alstyne etal., 2016).
The network eﬀect describes how the consumer value of a product changes
when the number of consumers of the same product or complementary products
changes. A distinction is made between the direct and indirect network eﬀect.
The direct network eﬀect was described in 1986 by Katz and Shapiro and states
that a product’s value changes with the total number of consumers of that prod-
uct (Farrell & Saloner, 1992; Funk, 2009; Katz & Shapiro, 1986). Often referred
examples for this eﬀect are telephones and fax machines. Within the context of
digital platforms, the direct network eﬀect occurs, e.g., on social media platforms
such as Facebook. The indirect network eﬀect occurs when the value of a product
changes as soon as the number of consumers of another product changes without
520 Journal of the Knowledge Economy (2021) 12:519–543
a direct relationship between these products (Shapiro & Varian, 1998). The indi-
rect network eﬀect is characteristic for two- or multisided markets. Thereby, an
increased number of participants on the one side of the market tends to increase
the number of participants on the other side of the market. This eﬀect is the driv-
ing force behind digital platforms like Airbnb or Uber. Positive network eﬀects
are the foundation for digital platforms. Thus, the more participants a platform
has, the more attractive it becomes for other participants. This is referred to as
self-reinforcing “chain reactions” which—once initiated—lead to the rapid
growth of digital platforms. This is the reason why for each market only a very
limited number of platforms can economically exist (Eisenmann etal., 2006). An
analysis of the historical development of the most valuable companies world-
wide impressively visualizes the disruptive potential of digital platforms (Fig.1).
While classic companies dominated the ranking in 1995, six of the ten most valu-
able companies were platform companies in 2018.1 It is striking that the number
of valuable platform companies has increased rapidly in recent times.
Companies can conduct classic activities along an input/output process and cre-
ate a platform ecosystem while doing so. For example, the development, produc-
tion, and distribution of Apple’s iPhone follow a classic value chain. At the same
Fig. 1 The ten most valuable companies from 1995 to 2018 by market capitalization in billion US dollars
(fortiss Gmbh, 2016; Kempe, 2011; Payment & Banking, 2019)
1 In order to distinguish classic companies from platform companies, the term pipeline company has
established itself in the scientiﬁc literature. Classic companies operate according to the value chain
described by Porter in 1985. The dominant activities of these companies take place in a classical input/
output process (Porter, 1985). Platform companies on the other hand place the operation of a digital plat-
form at the center of their business activities and pursue the goal of maximum ecosystem value (Parker
521Journal of the Knowledge Economy (2021) 12:519–543
time, Apple has created a platform ecosystem around its iOS operating system in
which the iPhone is embedded. With the introduction of the iOS platform in 2007,
Apple was able to capture a signiﬁcant share of the global smartphone market within
just a few years. Apple’s core business is the sale of hardware components, which
accounts for 80% of its revenues. However, the success of the company and thus
also the sale of the hardware is signiﬁcantly inﬂuenced by the platform character of
the company (Reillier & Reillier, 2017). In the following section, we will discuss
the way digital platforms work in order to understand the reasons for the success of
The Way Digital Platforms Work andWhy Established Enterprises
The success of a digital platform is not based on internal resources, but on the eco-
system in which the platform is embedded. The acatech–National Academy of Sci-
ence and Engineering takes up the concept of the platform ecosystem and states that
a platform ecosystem describes the economic mechanisms behind digital platforms
as well as the stakeholders involved and their relationships (Engels etal., 2017).
According to Evans and Schmalensee, these stakeholders include all persons, com-
panies, institutions, and other environmental factors that inﬂuence the value created
by a platform (Evans & Schmalensee, 2016). This value is created by platforms
using stakeholder data to orchestrate physical and digital resources across the eco-
system (Choudary, 2015). We therefore understand a digital platform as a two or
multisided market in which the diﬀerent actors are brought together by an interme-
diary and propose an arrangement of roles within a digital platform as shown in
Fig.2. The diﬀerent actors are assigned to the category platform core, platform par-
ticipants, and platform environment (Drewel etal., 2018). If, for example, the num-
ber of producers increases, the platform becomes more attractive for consumers and
vice versa (Eisenmann etal., 2006).
The core value of a platform company is not a classic physical value unit, but
an infrastructure that enables interactions between producers and consumers. The
design of the key interaction is therefore the core of each digital platform. The
key interaction is the reason why participants use digital platforms (Jaekel, 2017;
Parker etal., 2017). The anatomy of a key interaction consists of four characteristics
(Choudary, 2015), (Moazed & Johnson, 2016):
(1) Value creation: Each key interaction involves at least one producer who creates
the value unit. The production of value units by the producer marks the starting
point of a platform interaction (Parker etal., 2017), (Jaekel, 2017), (Moazed &
(2) Connection: The connection of producers and consumers is enabled through
ﬁltering and individualization of the platform content. Filtering ensures that
only high-quality value units are oﬀered. Filter mechanisms support desirable
and punish undesirable behavior (Choudary, 2015; Jaekel, 2017). With the help
of ﬁlters, a speciﬁc consumer gains access to the content relevant to him. Digital
522 Journal of the Knowledge Economy (2021) 12:519–543
platforms that are able to provide their consumers with individualized content
encourage them to continue participating (Parker etal., 2017).
(3) Consumption: Each key interaction involves at least one platform participant
who consumes the value unit that is relevant for him or her. Consumption can
take diﬀerent forms depending on the value unit. For example, the consumption
of digital value units often takes place directly via the platform (Choudary, 2015;
Jaekel, 2017; Moazed & Johnson, 2016).
(4) Compensation: The key interaction is completed with compensation. It is char-
acteristic that the consumer transmits a return service to the producer for the
value unit received (Moazed & Johnson, 2016).
In a key interaction, information, value units, and payments are exchanged
between the platform participants. A producer and a consumer ﬁrst exchange
information. Then, the producer transmits a value unit to the consumer and
receives a payment in return. The payment does not always have to be mone-
tary, but can also take the form of data, evaluations, etc. The payment can also
be made in form of a payment slip. The number of key interactions increases
with the scope of services/products oﬀered and the number of participants in the
platform ecosystem. The constantly repeating key interactions are made possible
by three basic functions of a platform (Choudary, 2015; Cusumano etal., 2019;
Moazed & Johnson, 2016; Parker etal., 2017):
Fig. 2 Roles in a digital platform (Baums, 2015; Drewel etal., 2018; Tiwana, 2014)
523Journal of the Knowledge Economy (2021) 12:519–543
• Match: The most relevant value units must always be provided for the consum-
ers. With an increasing number of producers, the scope of the platform oﬀerings
increases, making it more diﬃcult for consumers to identify the desired oﬀer.
Filters are suitable for merging the value unit provided by the producer with the
• Facilitate: Platform companies do not control value creation, but provide an
infrastructure that enables value creation. Programs are introduced and poli-
cies established that regulate interactions and promote desired behavior. Filter
mechanisms ensure that high-quality content is provided on the platform and that
desirable interactions are enabled.
• Pull: Key interactions are made possible by luring participants to the platform
and keeping them there. Platforms have to overcome the chicken and egg prob-
lem (Who joins the platform ﬁrst? Producer or consumer?). The aim is to make
participation on the platform as easy as possible for potential participants. Since
the focus of business activities is on repetitive interactions, it must be ensured
that the participants are regularly active. In order to prevent unwanted behavior
of the platform participants, membership checks can be useful.
In summary, the pull eﬀect enables the quantitative scaling of a platform by pro-
moting production and consumption. Filter mechanisms ensure that the quality of
the consumer experience is guaranteed as the platform grows (Jaekel, 2017). On the
basis of the ﬁltered and individualized content, suitable producers and consumers
can interact in key interactions and initiate the exchange. Figure3 shows an aggre-
gated representation of the functionality of a digital platform.
While the awareness of the economic potential of the platform model is grow-
ing (Evans & Gawer, 2016), many established companies have considerable dif-
ﬁculties mastering the challenges of developing own platforms and initiating the
Fig. 3 Aggregated representation of the functionality of a digital platform
524 Journal of the Knowledge Economy (2021) 12:519–543
powerful chain reactions based on network eﬀects (Parker etal., 2017). Two rea-
sons for this are the lack of knowledge concerning the development of digital
platforms and new ways to monetarize the platform business (Engels etal., 2017).
Evans and Schmalensee underline the lack of knowledge concerning multisided
markets and the connected diﬃculties in understanding how digital platforms
work as a central challenge (Evans & Schmalensee, 2016). Choudary describes
three primary shifts in the way towards multisided markets (Choudary, 2015):
(1) Shift in markets: Traditionally, the consumer was at the end of a pipeline where
producers produced the good for the consumer. Digital platforms do not create
the end value but enable value creation between various producers and consum-
ers. As a result, participants on digital platforms can take on production as well
(2) Shift in competitive advantage: Pipeline enterprises compete through manag-
ing resources and intellectual property. This does not apply to digital platforms.
Platform enterprises focus on orchestrating and enabling value-exchanging
interactions and using data about the various participants within the ecosystem.
The management of ecosystems is therefore the key competitive advantage in
(3) Shift in value creation: The value in pipeline markets is created through pro-
cesses that organize a company’s labor and resources. Such markets focus on
the eﬃciency of business processes. The value creation in platform markets,
however, is focused on the number and quality of interactions. It is based on
orchestrating these interactions between consumers and producers.
The three described shifts show that the rules in platform markets are com-
pletely diﬀerent from pipeline markets. The way companies interact with markets,
build competitive advantage, and create value is new for the majority of tradi-
tional companies. The disruptive potential of digital platforms is promising for
those companies that are able to establish a digital platform, but involves some
risks that are connected to the development of a platform:
• Reaching critical mass is a prerequisite for entering the lucrative growth phase
of a digital platform. To achieve this, platform owners must overcome the
chicken-and-egg problem, which has already caused many platforms to fail
(Caillaud & Jullien, 2003).
• Digital platforms require high investments in the underlying IT infrastructure.
Furthermore, in the ﬁrst phases of a platform’s life, a considerable marketing
eﬀort is necessary to attract suﬃcient participants. Platform operators need a
high amount of money to bridge the initial costs (Libert etal., 2016).
• The platform owner must be aware of the risk of liability issues. The unclear
legal situation currently leads to an increased liability of platform operators
• Digital platforms are changing the way companies create value. For traditional
pipeline activities, the focus is on maximizing consumer value; for platform
525Journal of the Knowledge Economy (2021) 12:519–543
activities, the focus is on maximizing ecosystem value. This may require sub-
sidizing certain consumer groups to attract others. These changes are often
confronted with opponents within your own company (Parker etal., 2017).
• Building a digital platform requires new skills (e.g., developing platform busi-
ness models) and resources (new IT systems), which are often not available in
established companies. Especially for small- and medium-sized enterprises, the
development of the necessary skills represents a risk when entering the platform
economy (Engels etal., 2017).
The development of a platform is associated with signiﬁcant opportunities such
as increased sales and consumer loyalty. However, companies must also be aware
of the risks. Many platforms fail to achieve critical mass and the high initial costs
of successful platform operation. Small- and medium-sized companies in particular
lack opportunities to enter the platform economy. These companies need knowledge
of existing platforms and best practices to master the leap into the platform econ-
omy. These knowledge deﬁcits of companies can be eliminated by using patterns.
Platform patterns represent proven principles of already existing platforms. There-
fore, they are considered in the following analysis of approaches to develop digital
Approaches toDevelop Digital Platforms
There are several approaches in the scientiﬁc literature that are dedicated to the
entry into the platform economy. These can be roughly divided into three categories:
(1) canvas-based approaches to design a platform business, (2) speciﬁc approaches
to develop digital platforms, and (3) pattern-based approaches to develop digital
(1) Canvas-based approaches: In holistic framework models, several relevant
elements of digital platforms are considered in aggregated form. The aim of these
framework models is to support companies in planning and building their own
digital platforms. An example is provided by Choudary, who describes a four-stage
process for building a digital platform based on key interaction. This construction
process is tangled by a platform canvas, which shows all elements relevant for the
platform construction (Choudary, 2015). Similar canvas-based approaches for plat-
form construction are provided by Walter and Lohse as well as Cicero (Walter &
Lohse, 2018; Boundaryless S.r.l., 2019). The approaches of Cicero as well as Walter
and Lohse include a comprehensive portfolio of tools to analyze the needs of plat-
form participants in detail and to develop a validated concept for a digital platform.
The high level of interactivity through supporting software solutions as well as the
comprehensive analysis of the platform potential are to be positively emphasized.
However, the multitude of tools and the required comprehensive know-how make
the application considerably more diﬃcult for the practitioner.
(2) Speciﬁc approaches to develop digital platforms: In order to successfully
complete the platform construction, more than mere knowledge of a corresponding
procedure is required. Against this background, approaches have been incorporated
526 Journal of the Knowledge Economy (2021) 12:519–543
into the analysis of the state of the art, which deal in detail with the process of devel-
oping digital platforms. Zhu and Furr provide an approach to change products into
platforms within four steps. The process for transforming products into platforms
is preceded by an extensive analysis, which provides interesting orientation knowl-
edge. On the positive side, the existing products and services of a company are taken
into account and a step-by-step transformation is made possible. However, the four
steps are only described superﬁcially, which leaves some detailed questions open
(Zhu & Furr, 2016). Cusumano etal. provide another approach for the systematic
development of a digital platform. Knowledge is made available in the form of prin-
ciples for overcoming the chicken-and-egg problem. Especially companies with a
low level of knowledge in the context of digital platforms can proﬁt from this. An
analysis of the initial situation is completely lacking; the authors rather assume a
“green ﬁeld” which is bypassing entrepreneurial practice. Moreover, the approach
often remains relatively vague and lacks numerous details. For example, in the con-
text of the business model, only the revenue model is considered (Cusumano etal.,
(3) Pattern-based approaches to develop digital platforms: Patterns are pre-
sent in many diﬀerent domains. They occur wherever people are confronted with
similar problems that can be solved with the same solution. An application of the
pattern concept that is frequently mentioned in literature goes back to the architec-
tural theorist Alexander, who developed 253 patterns for the design of cities and
buildings in the 1970s (Alexander, 1979; Alexander etal., 1977). Since then, this
idea has been taken up regularly, for example in software development. Software
developers can use patterns to build on the knowledge of other and more experi-
enced developers to solve their own problems (Kohls, 2014). Another example of
the use of patterns is the design of business models. Through business model pat-
terns, the success of particularly proﬁtable companies becomes transparent and
other companies are provided with the solution knowledge of these successful com-
panies with the help of patterns (Amshoﬀ etal., 2015).
For digital platforms, the pattern-related scientiﬁc literature has been domi-
nated by approaches to the acquisition of platform participants—often also referred
to as approaches to overcoming the chicken-and-egg problem. Leading works in
this ﬁeld come from Moazed and Johnson, Hagiu and Altman, as well as Evans
and Schmalensee (Moazed & Johnson, 2016; Hagiu & Altman, 2017; Evans &
Schmalensee, 2016). The authors describe diﬀerent ways to convince producers and
consumers to use a platform. Another topic that is intensively discussed in the litera-
ture is the monetization of platforms. Leading works on this topic come from Parker
etal. as well as L. C. Reillier and B. Reillier and Cusumano etal. (Cusumano etal.,
2019; Parker etal., 2017; Reillier & Reillier, 2017). From these works, patterns for
the beneﬁt-maximizing pricing of platform participants can be derived.
The mentioned and further approaches from the state of the art were examined
for a possible utilization for the pattern-based development of digital platforms and
were incorporated into the developed framework. The framework at hand was devel-
oped at the Heinz Nixdorf Institute using the Design Research Methodology (DRM)
according to Blessing and Chakrabarti (2009). In the ﬁrst phase of the research,
the goal has been clariﬁed including the theoretical foundation and the state of the
527Journal of the Knowledge Economy (2021) 12:519–543
art. In the second phase, a ﬁrst descriptive study consisting of 40 interviews with
management personalities within the machine building industry has been conducted
(Engels etal., 2017). This study leads to a deeper understanding of the mechanisms
of digital platforms and of the problems companies face while establishing own
platforms or entering existing platforms. Following the interviews, we conducted a
literature analysis which led to 79 potential platform patterns. The actual framework
was developed in the third phase of the research within a prescriptive study. It is
based on the ﬁndings of the ﬁrst phase as well as further research (e.g., existing liter-
ature and best practices). The last phase of the work was a second descriptive study
in which the developed methodology was evaluated. Eight companies participated
in the validation and excluded 10 potential platform patterns because of their lack
of practical and content-related relevance. The ﬁrst phase of the validation led to
69 potential patterns. In order to eliminate redundancies in the remaining 69 poten-
tial patterns, these were bundled which led to the actual framework of 37 platform
Proven Principles fortheDevelopment ofDigital Platforms
“The Way Digital Platforms Work and Why Established Enterprises Struggle with
It” shows that established companies are not familiar with the way digital platforms
work (Engels etal., 2017; Parker et al., 2017). In order to overcome the lack of
knowledge in the platform economy and the resulting challenges, established com-
panies can use patterns (see “Approaches to Develop Digital Platforms”). Patterns
are connecting elements in a problem-solution relationship. Problems are obstacles
that have to be overcome in the transition from an initial situation to a desired target
state. If the transition is successful, the path to it is a solution. By using patterns,
applying users can increase the eﬃciency of problem solving by using existing and
abstract solutions for recurring problems (Amshoﬀ etal., 2015). The present anal-
ysis takes up the deﬁnition of Alexander etal. A platform pattern therefore con-
sists of a problem that companies have to overcome again and again when building
digital platforms and a solution with which this problem can always be overcome
(Alexander etal., 1977). These patterns are derived from reality and then documented
in order to externalize the identiﬁed patterns. With the documentation, third parties
gain access to the patterns and can apply them in reality (Kohls, 2014) (Fig.4).
We use design ﬁelds of digital platforms to identify, classify, and diﬀerentiate
between proven principals. Design ﬁelds of digital platforms are a homogeneous
platform area in itself and can be designed separately from other ﬁelds. Existing
frameworks and approaches for the development of digital platforms can be used
to identify relevant design ﬁelds. We conducted a synthesis of existing literature
concerning the process of establishing a digital platform and found seven design
ﬁelds of digital platforms which could be tackled by using proven principals (see
(Choudary, 2015; Walter & Lohse, 2018; Edelmann, 2015)):
528 Journal of the Knowledge Economy (2021) 12:519–543
Participant acquisition: This design ﬁeld includes measures that the owner of
a platform has to take to convince producers and/or consumers of the beneﬁts of a
platform participation. In addition, the role of the acquired participants on the plat-
form and the underlying motivation are determined within this design ﬁeld.
Platform infrastructure: In order to enable high-quality transactions between
the platform participants, the owner of the platform has to provide the necessary
infrastructure. This guarantees the quality and relevance of the oﬀerings and sup-
ports the participants in value creation and consumption.
Further ecosystem participants: The enterprise that develops a platform
decides how to position itself in regard to third parties and whether an integration
of certain third parties is necessary. With regard to the partners, it must be decided
which functions the owner has to provide and which can be obtained by any third
party producers. Possible advantages and disadvantages are to be included in the
platform structure, so that the relationship of the platform owner to its ecosystem is
Anatomy of transaction: Enabling value adding transactions is the core value
proposition of digital platforms. On a digital platform, information, value units, and
payments are transferred between producers and consumers. The object of the plat-
form structure is therefore, among other things, the design of a suitable transaction
Monetarization: In order to ensure the long-term competitiveness of a digital
platform, it is necessary to determine how activities on the platform can be monetar-
ized. The platform owner determines which participant pays for a platform usage
and which price structure is applied.
Value units: The object of every transaction is the exchange of a value unit
between producers and consumers. The value unit must be characterized within the
framework of the platform structure.
Channels: Channels describe which technical instruments are used by produc-
ers and consumers to access the platform. Possible channels are APIs, browsers, or
The value units of a platform and the participant acquisition are undisputed in
the existing literature. All approaches address these two design ﬁelds. The platform
infrastructure and anatomy of transaction are not taken up without restriction by all
approaches but are nevertheless mentioned by the majority. The design ﬁelds further
Fig. 4 Relationship between
obstacles, solution, and proven
529Journal of the Knowledge Economy (2021) 12:519–543
ecosystem participants, monetarization and channels are controversially discussed
by the existing approaches. We used our knowledge of 40 conducted interviews with
management personalities (Engels etal., 2017) within the machine building indus-
try to decide which design ﬁelds we could tackle by using existing approaches. The
interviews and explorative projects within the machine building industry showed
that the channels producers and consumers use to access the platform are relatively
easy to choose. We therefore decided not to search for proven principles for this
design ﬁeld. The six remaining ﬁelds are shown in Fig.5.
We used these design ﬁelds to search for proven principles. The goal was a cata-
logue consisting of patterns (Alexander etal., 1977). We researched and compiled
Fig. 5 Design ﬁelds of a digital platform
Fig. 6 Exemplary pattern “cooperation”
530 Journal of the Knowledge Economy (2021) 12:519–543
potential patterns in a collection and eliminated those of low relevance. A cluster
algorithm bundled the remaining content so that proven principles could be derived.
We documented the determined platform patterns in a uniform notation scheme.
Figure6 shows the design ﬁeld participant acquisition with the exemplary pattern
cooperation. The design ﬁelds are characterized by a classiﬁcation, a description,
and guiding questions. The classiﬁcation speciﬁes the sequence in which the design
ﬁelds should be dealt with (see “How to Use Patterns for Digital Platforms”). Each
associated pattern is characterized by a description and at least one successful appli-
We transferred the identiﬁed patterns into a structure-giving catalogue which
serves as an orientation framework for the pattern application. The catalogue is uni-
versally valid and can be used independently from the task at hand. Furthermore,
new patterns can be added once they are identiﬁed which makes the catalogue a
growing source of knowledge. We identiﬁed 37 platform patterns (see Fig.7).
How toUse Patterns forDigital Platforms
A superordinate process is used as an orientation framework for the platform
patterns. The process is based on the six design ﬁelds of digital platforms and
systematizes the application of the patterns. The starting point is the value unit
Fig. 7 Catalogue of consisting patterns with design ﬁeld participant acquisition on front
531Journal of the Knowledge Economy (2021) 12:519–543
of the key interaction (ﬁrst layer) as the platforms central promise of value.
The key interaction is based on an exchange of value units between producers
and consumers (see Fig.3). The second layer is the acquisition of participants,
which is crucial for the scaling of a digital platform. Besides the value unit and
the participant acquisition, the anatomy of transaction is part of the key interac-
tion. To determine a suitable anatomy of transaction, the exchange of informa-
tion, value units, and payments is worked out in the third layer. After designing
the key interaction, the platform infrastructure needs to be shaped. The infra-
structure contains corresponding functions which are combined to bundles. Sub-
sequently, the design of the monetarization (ﬁfth layer) of the platform is car-
ried out with the objective of ensuring the long-term viability of the platform.
For this purpose, parts of the created values must be retained by the owner of
the platform. The process ends with the decision as to how openly the platform
owner will position the platform for further ecosystem participants (sixth layer).
This sequence of designing a digital platform is based on the key interaction
and describes a platform development directed from the inside to the outside
(Choudary, 2015). The sequence is presented in Fig.8.
The presented sequence enables companies to decide in which order they
should implement the platform patterns. Each design ﬁeld is characterized by
guiding questions which help to decide which patterns are applicable. In the fol-
lowing, approaches for the application of platform patterns are presented. First,
we describe how platform ideas can be generated by using platform patterns.
Building on this, we describe a pattern-based development of a platform con-
cept. In addition, platform concepts and already existing digital platforms can be
characterized in detail with the help of platform patterns.
Fig. 8 Sequence of application for platform patterns
532 Journal of the Knowledge Economy (2021) 12:519–543
Platform Patterns asaWay toGenerate New Ideas
The developed patterns can be used as a creativity technique to generate new ideas
for digital platforms. As stated by Csik, patterns have a positive eﬀect on the results
of creativity processes. The eﬀect is based on the fact that patterns cause certain
stimuli which promote creativity (Csik, 2014). In extension of Gassmann etal., the
generation of ideas by means of patterns is based on two principles: (1) pattern asso-
ciation and (2) pattern confrontation (Amshoﬀ etal., 2015; Gassmann etal., 2014).
The principles are shown in Fig.9.
Pattern association: Here, an idea for a digital platform is already available in
advance, which can be assigned to a pattern from the framework. In this way, exist-
ing ideas can be further concretized (Amshoﬀ etal., 2015).
Pattern confrontation: With this principle, a pattern is chosen at random and
presented to the persons involved. This provocation allows existing thought patterns
to be broken through; completely new ideas for digital platforms with the potential
for radically new functions emerge (Gassmann etal., 2014).
We used our framework for both principles within various workshops and vali-
dated its applicability to generate new ideas for digital platforms. The validation was
carried out as part of a research project to initiate a digital marketplace for artiﬁcial
intelligence applications for product engineering. In the following, an exemplary
approach to pattern association and pattern confrontation is presented.
The starting point of the pattern association is an idea provided in advance. In our
workshops we discussed the idea of a marketplace for applications of artiﬁcial intel-
ligence in product engineering. The aim of the workshop was to concretize this idea
on the basis of the identiﬁed patterns. The workshop was carried out with 35 par-
ticipants from SMEs, research institutes and associations and federations within
the ﬁeld of product engineering. Figure10 shows the concept of the workshop. The
workshop participants used characteristic platform participnts of the marketplace
and their problems to generate and improve their ideas to form a holistic concept for
Fig. 9 Principles to generate ideas for platforms in accordance with Amshoﬀ etal., (2015)
533Journal of the Knowledge Economy (2021) 12:519–543
We conducted a second workshop with 30 participants with the same task.
Within the second workshop, we did not use the patterns for digital platforms
but also the characteristic platform participants of the digital marketplace. We
found that the group without the patterns had considerable diﬃculties in develop-
ing ideas for such a marketplace. The concept of digital marketplaces had to be
explained more than once and in much more detail. Moreover, the generated ideas
were often not applicable for a digital marketplace but rather for a “simple” appli-
cation for a potential marketplace. The diﬀerences between the idea generation
with patterns and without patterns are presented in “Diﬀerences in the Generation
of Ideas with and Without Patterns”.
We conducted another workshop to generate ideas for a digital platform based
on the concept pattern confrontation. The ideas were generated with 38 partici-
pants from research institutes and employees of machine learning companies.
The participants used the platform patterns to directly generate ideas for an
Fig. 10 Pattern association workshop to generate ideas for a digital marketplace
534 Journal of the Knowledge Economy (2021) 12:519–543
AI-Marketplace (see Fig.11). The patterns were randomly selected from the pat-
tern catalogue in order to determine the greatest possible heterogeneity between
the diﬀerent ideas.
We found that the participants of the workshop understood the new concept of
digital platforms much faster and easier than in workshops with a similar task but
without the pattern confrontation. Moreover, the participants were enthusiastic
about the task and developed quite radical new ideas. The diﬀerences between the
two approaches and workshops without patterns are presented in “Diﬀerences in the
Generation of Ideas with and Without Patterns”.
Differences intheGeneration ofIdeas withandWithout Patterns
Within our workshops, we found clear distinguishing factors between the genera-
tion of ideas for a digital platform by pattern association, pattern confrontation, and
without any patterns at all. The analysis of the factors is based on one workshop for
each approach with 30 to 38 participants. Within these workshops, we formed small
groups of ﬁve participants which gives us six to eight data sets for each approach.
The presented ﬁndings are based on the results of the workshops which can be
grouped into three categories:
Hard facts: Number of ideas
Soft facts: Feasibility of the ideas, radicality of ideas, user orientation of ideas
Gut feeling: Understanding of the task, enthusiasm of the participants
Figure12 represents the ﬁndings of the workshops. The qualitative results show
that the application of patterns leads to better results and better workshops. While
both approaches work well, we could still see clear diﬀerences between the pat-
tern association and pattern confrontation. The pattern association generates more
ideas with a high feasibility and user orientation. The pattern confrontation on the
other hand delivers less, but much more radical ideas. Also, the understanding of
the task and the enthusiasm of the participants is a little higher than by pattern asso-
ciation. In order to summarize the ﬁndings, it can be stated that the pattern associa-
tion is particularly suitable for workshops with the goal of many user-oriented ideas.
Fig. 11 Pattern confrontation to generate ideas for a digital marketplace
535Journal of the Knowledge Economy (2021) 12:519–543
Pattern confrontation, on the other hand, should be used to generate more radical
ideas. In addition, both approaches can be combined, e.g., by ﬁrst developing ideas
via characteristic platform participants of a possible marketplace and the association
of patterns. In order to further develop these ideas, new patterns from the catalogue
can then be used.
Pattern‑Based Development ofDigital Platforms
The pattern-based development of digital platforms includes the phases ideation,
conception, and development of digital platforms (Amshoﬀ etal., 2015). The basic
Fig. 12 Distinguishing factors
between the generation of ideas
for a digital platforms by pattern
association, confrontation, and
Fig. 13 Basic principle of pattern-based platform development (Amshoﬀ, 2015)
536 Journal of the Knowledge Economy (2021) 12:519–543
principle is shown in Fig.13. Following Amshoﬀ, an abstract and a speciﬁc area
are distinguished. The speciﬁc area describes the point of view of a company which
wants to realize a platform idea. The abstract area contains the generalization of the
platform in the form of patterns. The diﬀerent phases of the pattern-based develop-
ment of digital platforms are explained below. This process must be conducted every
time a new platform is initiated.
Part of the platform ideation is the formulation of a speciﬁc platform idea, which
is called platformization mission. Subsequently, the process for applying platform
patterns (beginning “How to Use Patterns for Digital Platforms”) is used to assign
patterns to each of the design ﬁelds according to the platform mission described.
The guiding questions provided for this purpose support the applying user when
assigning appropriate patterns to the design ﬁelds. Once all the design ﬁelds are
characterized by answering the guiding questions and applying the patterns, a com-
pany can deﬁne its concept for a digital platform. For this purpose, the individually
selected patterns are brought together, avoiding the combination of conﬂicting pat-
terns and taking into account the choice of patterns that favor each other. This pat-
tern combination corresponds to the core of the platform conception. The result of
this analysis step is an abstract platform concept. The concept is documented and is
exemplarily shown in Fig.14. The platform development addresses the transforma-
tion of the abstract platform concept into an elaborated and company-speciﬁc digital
Characterization ofPopular Platform Enterprises
Platform companies currently have an unprecedented economic dominance. Estab-
lished companies not only ﬁnd it diﬃcult to participate in the economic rise of the
Fig. 14 Concept for a digital platform within the machine building industry
537Journal of the Knowledge Economy (2021) 12:519–543
platform economy. It is often the case that they do not even have the necessary plat-
form knowledge to understand the business activities of major platform companies.
Against this background, the identiﬁed platform patterns can be used to make the
business activities of successful platform companies transparent. The investigation
of these existing platform companies allows to reveal potential gaps in the exist-
ing pattern catalogue. Moreover, established companies gain insights into platform
companies and can understand what they do diﬀerently. This oﬀers the possibility
of generating new ideas, e.g. by addressing the weaknesses of existing platforms
(Köster, 2014). The patterns are then used to generate ideas for better solutions
In the following, it is exemplary presented with which patterns the well-known
B2C platform Uber (see Fig.15) became successful and which patterns were used
for the mentioned B2B platform “AI-Marketplace” (see Fig.16). Uber is a plat-
form for the brokerage of driving services and thus relies on the value unit (level
1) pattern standardized service. In order to attract both drivers and passengers to
the platform, various patterns of participant acquisition were and are used (level
2). One example is the micromarket. By using this pattern, Uber initially set up its
services locally limited in selected cities such as San Francisco to be able to ben-
eﬁt more quickly from positive network eﬀects. In anatomy of transaction (level
3), the pattern information and return is used. This means that only the value unit
(the trip) is directly transmitted between driver and passenger outside the plat-
form. The exchange of information and money takes place via the platform. For
the design of the platform infrastructure (level 4), the exemplary pattern active
ﬁlter is used. Passengers actively transmit data to Uber so that the best driver can
Fig. 15 Characterization of the B2C platform Uber with platform patterns (extract)
538 Journal of the Knowledge Economy (2021) 12:519–543
be provided to the consumer. The ﬁfth level monetization is served with the pat-
tern transaction fees. By using this pattern, Uber retains a portion of the passen-
ger’s compensation payment for each completed transaction between driver and
passenger. At the ﬁnal layer further ecosystem participants, Uber relies on the
pattern partner relationship and oﬀers external partners access to the platform
through APIs to increase the functionality.
In addition to the transport service provider Uber, the AI-Marketplace will be
presented as an example of a B2B platform (see Fig.16). The AI-Marketplace
is a digital platform that connects producers of AI-applications for the product
development with manufacturing companies. For example, manufacturing com-
panies can have existing design drawings optimized using an AI-application (e.g.
in terms of material consumption or stiﬀness). Virtual goods (AI-applications)
and standardized services (AI-Consulting) are the value provided by the market-
place (level 1) of this platform. The platform starts in a small region of Germany
and uses an existing innovation-ecosystem (it´s OWL). The companies within this
ecosystem trust each other and some of these companies are even part of the pro-
ject behind the AI-Marketplace. The pattern micromarket was therefore used to
attract initial participants. Further on, the patterns marketing push and acquiring
Fig. 16 Characterization of the B2B platform AI-Marketplace with platform patterns
539Journal of the Knowledge Economy (2021) 12:519–543
participants were used to attract platform participants from whole Germany (level
2). Producers of AI-Applications and manufacturing companies were already
in contact before the AI-Marketplace came into existence. The AI-Marketplace
has established itself between these actors by facilitating exchanges and oﬀer-
ing complementary value units. For the transaction anatomy (level 3), the pattern
complete ownership is used. Value unit, information, and monetary consideration
are handled via the digital platform. Editorial curating as well as active ﬁlter are
used for the platform infrastructure (level 4). The AI-Marketplace charges trans-
action fees for the procurement of AI-applications. In addition, a listing fee is
charged for selected advertisements and highlighting of oﬀers is made possible
in order to generate further revenues (level 5). The AI-Marketplace is open for
further owners, which will mostly be from the leading edge innovation-ecosystem
it’s OWL. Therefore, the pattern ownership structure is used (level 6).
The presented examples show that the pattern catalogue can be used to character-
ize any given digital platform. We found that by doing so, companies can understand
the business of potential competitors and were even able to develop their own digital
platforms. Moreover, some companies used the characterization of potential com-
peting platforms in order to improve their own solution.
Digital platforms are becoming increasingly widespread in the industry and com-
panies are on their way into the platform economy. While the awareness of the eco-
nomic potential of the platform model is growing, many established companies have
considerable diﬃculties mastering the challenges of participating in the platform
economy. An exemplary challenge is the completely new form of value creation
of platform companies, which is largely unknown to manufacturing companies. To
overcome the challenges of the platform economy, clever strategic action is more
important than ever. A ﬁrst starting point for entering the platform economy is the
methodical approach presented here.
The patterns and methods provided help to master the entry into the platform
economy and to reduce uncertainties. Patterns represent proven principals and can
thereby provide valuable know-how for business activities in the platform economy.
We identiﬁed 37 patterns and structured them in a catalogue which makes the pat-
terns useable. To do so, we provide a process model which systematizes the design
ﬁelds of a digital platform. Due to the high dynamics and short innovation cycles,
the catalogue provided should be regularly reviewed and updated or expanded. It
goes without saying that the entry into the platform economy does not stop with
the development of promising concepts. Further approaches, such as speciﬁcation
techniques to describe platforms, are needed to support companies in coping with
the transformation from pipeline to platform markets. The characterization of the
ﬁrst platforms has yielded promising results. In the future, a large number of estab-
lished platforms will be characterized using the patterns to identify common com-
binations. Moreover, we were able to gain some additional theoretical insights, e.g.,
(a) platform categories are often taken up in the scientiﬁc discussion but a uniform
540 Journal of the Knowledge Economy (2021) 12:519–543
diﬀerentiation does not exist yet. (b) Besides technical knowledge gaps compa-
nies often do not know how to earn money with platforms. (c) The manufacturing
industry is particularly concerned about the loss of consumer access due to digital
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Authors and Affiliations
MarvinDrewel1 · LeonÖzcan1· JürgenGausemeier1· RomanDumitrescu1
1 Heinz Nixdorf Institut, Universität Paderborn, Paderborn, Germany
543Journal of the Knowledge Economy (2021) 12:519–543
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