This is the author’s version of a work that is accepted at the following source:
Tobias Kölbel*, Marcel Linkenheil, and Christof Weinhardt (2023): “Requirements
and Design Principles for Blockchain-enabled Matchmaking-Marketplaces in
Additive Manufacturing” in Hawaii International Conference on System Sciences
(HICSS) 2023 (forthcoming).
* The author of this publication was partially funded by the German Federal Ministry of Education and Research
(BMBF) as part of the iBlockchain project under grant number 16KIS0904. The author is responsible for the
content of this publication.
Please note: Copyright is owned by the author and / or the publisher.
Commercial use is not allowed.
© 2022. This manuscript version is made available under the
CC-BY-NC-ND 4.0 license
Requirements and Design Principles for Blockchain-enabled
Matchmaking-Marketplaces in Additive Manufacturing
Karlsruhe Institute of Technology
Bosch Corporate Research
Karlsruhe Institute of Technology
Karlsruhe Institute of Technology
Blockchain-enabled marketplaces offer considerable
potential for cross-company networks. The area of
additive manufacturing appears particularly promising.
However, the practical impact of business-to-business
marketplaces in today’s organizations are still scarce,
and academic literature contains limited design
guidelines. Synthesizing knowledge from literature,
practice, and qualitative expert interviews, our study
explores 27 mandatory requirements, six optional
requirements, and 12 design principles.
Keywords: B2B, Marketplace, Blockchain,
Manufacturing, Design Science Research
A proliferation of IT-driven digitization presents
new business opportunities and marks a shift toward a
more technology-driven instead of an industry-driven
economy (Weinhardt et al., 2021). Over the past decade,
sub-economies such as platform economy, sharing
economy, gig economy, or blockchain (BC) economy
have emerged (Weinhardt et al., 2021). They yield
great successes and quickly disrupt industries. Affected
areas include lodging (e.g., Airbnb), transportation (e.g.,
Uber), and shopping (e.g., Amazon), to name a few.
The impact of these new sub-economies slowly
extends to the business-to-business (B2B) sector
(Cusumano, 2015; European Commission, 2020),
which is challenged by megatrends like Industry
4.0 and Cyber-Physical Systems (Wee et al.,
2015). Manufacturers face a business environment
characterized by complex market dynamics and
uncertainty for future demands, while modern
production strives for maximum efﬁciency and
cost reduction along the supply chain (Lund et al.,
2020). To respond ﬂexibly and adaptively to changing
conditions, manufacturers alter their monolithic
production concepts towards dynamically deﬁned value
networks (Wee et al., 2015; Woods, 2015). One option
here is the intra- and inter-organizational sharing of
production capacities via marketplaces (European
Commission, 2020), an approach that is predicted to
proliferate (Mourtzis et al., 2020). Xometry, a company
that operates a marketplace for efﬁciently matching
supply (capacities) and demand (service requests), is
a prime example of that paradigm shift. Its recent
valuation of around $3 billion (Taulli, 2021) indicates
the relevance of this application domain. However,
researchers, regulators, and practitioners recognize
downsides of centralized marketplaces controlled by
dominant ﬁrms that hinder B2B adoption. These range
from trust issues, to transparency of business-relevant
data, and manipulations by matching orchestrators
(European Commission, 2017; K¨
olbel et al., 2022).
With BC technologies aiming to prevent
intermediaries (Nakamoto, 2008), a stream of research
has emerged that seeks to overcome these concerns.
Relying on cryptographic methods and open protocols,
BC networks are governed by communities and operate
across distributed networks. The information systems
(IS) community explores this avenue with publications
on BC-enabled marketplaces (BEMs) that aim to
strengthen self-determined, privacy-preserving, and
trusted B2B interaction (Dann et al., 2020; Hofmann
et al., 2021; Notheisen et al., 2017). Yet – in contrast
to research on centralized marketplaces, which relies on
concepts based on previously identiﬁed requirements
(Freichel et al., 2019) – a literature review on BEMs
notes a paucity of structured approaches, including
principles for designing BEMs (K¨
olbel et al., 2022).
Against this backdrop, we set out to address three
research appeals: First, we respond to a more general
proposition to explore the interconnections between
novel sub-economies (Weinhardt et al., 2021) by linking
facets of marketplace sharing with the BC economy.
Second, we concentrate on the BC infrastructure of
electronic markets (Alt, 2020) and speciﬁcally study
requirements and principles for the structured design of
BEMs, that represents a striking research gap (K¨
et al., 2022). Third, we focus on the use case of additive
manufacturing (AM), as it allows for more ﬂexibility
than traditional mass production, is an innovative and
fast-growing industry (Wohlers Associates, 2019), and
thus represents an optimal starting point for this research
endeavor (Freichel et al., 2019). Collectively, this study
is driven by the following research question: Which
requirements and principles should be considered when
designing BEMs for matching AM supply and demand?
Our paper proceeds as follows. Section 2 presents
foundations and related work on BEMs in AM. Section
3 introduces our methodology. Section 4 reports our
research results by proposing requirements and design
principles. Section 5 concludes with contributions,
limitations, and future research opportunities.
2. Foundations and Related Work
We position our research question at the intersection
of three topics in IS: capacity sharing in production
networks, AM marketplaces, and BEMs in business.
Following the spirit of the sharing economy, the
inter- and intra-organizational sharing of production
resources via marketplaces combines digital markets
with production networks. Marketplaces act as logical
central points (K¨
olbel & Kunz, 2020) and Matchmakers
(Evans & Schmalensee, 2016) between two (or more)
customer segments, usually represented by a supply and
demand side (Cusumano, 2015). They coordinate the
interaction of these two sides and strive for optimal
resource allocation. Previously underutilized resources
can effectively be shared among users, dynamizing
production networks. This multilateral connectivity
of business partners leads to improved performances
and lower costs, as machines do not remain idle
(Hofmann et al., 2021; Stein et al., 2019). At the
center of this ecosystem is the digital infrastructure
of a marketplace, which is typically operated and
controlled by a dominant company. Their role is to
provide transparency about the market situation and
orchestrate market participants’ interactions. From a
generic perspective, different marketplace mechanisms
can be distinguished. These include the matchmaking
function as a control mechanism (K¨
olbel & Kunz, 2020)
and the distinction of marketplace interaction phases –
information and approach, intention and agreement, and
clearing and settlement (Veit, 2003).
While there are concepts for matching
manufacturing resources at the machine level, we
concentrate on the higher-level matching of supply
(manufacturing capacity) and demand (service requests)
at an organizational level. Speciﬁcally, we focus on
AM marketplaces as a real-world use case that enables
the transformation of 3D digital models into products
(Weller et al., 2015). While this process may not
substitute for mass production methods in all industries
(Holweg, 2015), it enables well-known applications
such as rapid prototyping, small-batch, or spare parts
manufacturing (Ben-Ner & Siemsen, 2017) and has
widely been studied in research on manufacturing
marketplaces. Examples include Rayna et al. (2015),
who provide an overview of AM service providers;
Stein et al. (2019), who developed a market mechanism
for efﬁcient resource optimization; and Freichel et al.
(2019), who propose requirements and a metamodel for
a centralized marketplace that facilitates AM capacity
trading between companies.
Alongside concepts for centralized marketplaces,
numerous publications exploit novel technologies like
BC and pursue decentralized marketplace concepts.
Similarly, they connect consumers who want to print
3D models with a network of manufacturers who offer
printing capacities. However, through cryptographically
secured mechanisms, these decentralized concepts
eliminate centralized intermediaries, thus strengthening
the individual sovereignty of consumers (K¨
olbel et al.,
2022). In line with the perspective of Notheisen
et al. (2017), BEMs may be deﬁned as a multi-layered
construct with four dimensions: The ﬁrst describes
external market constraints, the second an infrastructure
layer with BC-speciﬁc protocols, the third involves
economic value creation, and the fourth an agent
layer characterizing economic actors’ behavior. In this
context, Herm and Janiesch (2021) study requirements
for BC-based collaboration platforms. In addition,
we encounter publications with technical frameworks
for BEMs in manufacturing (Hasan & Starly, 2020;
Hofmann et al., 2021; Roˇ
zman et al., 2021), although
previously identiﬁed requirements do not substantiate
these. For a more detailed overview of publications on
BEMs in business ecosystems, we refer to a literature
review by K¨
olbel et al. (2022). Overall, they regard
research to be at an early stage, noting the paucity that,
in the context of using BEMs for AM, a structured
deduction of requirements and design principles, the
fundamental basis of any marketplace design (Gimpel
et al., 2008), represents a striking research gap.
© MHP Management- und IT-Beratung GmbH | Digital Platforms & Solutions 129.04.2022 |
Design Science Research
Artifact and Process:
▪Evaluate current knowledge
▪Problems and opportunities
▪State-of-the-art expertise and
▪Existing artifacts and processes
Relevance Cycle Rigor Cycle
Figure 1. Hevner’s three-staged DSR approach (Hevner, 2007) and applied research methods
3. Methodological Approach
Our paper employs Design Science Research
(DSR) methods to explore requirements and articulate
principles for BEMs in AM. We argue that this approach
is particularly suitable as it combines practical relevance
with scientiﬁc rigor (Hevner, 2007) and allows to
design and rigorously evaluate our artifacts iteratively.
As illustrated in Figure 1, we fall back on Hevner’s
three-stage approach: the rigor cycle, the relevance
cycle, and the design cycle (Hevner, 2007).
The rigor cycle focuses on the existing knowledge
base and ensures that state-of-the-art research is
reﬂected in our endeavour. With a structured
literature review (SLR) following the methodological
approaches suggested by Webster and Watson (2002),
we collect and review the existent body of research.
Our initial literature base builds on querying a wide
range of interdisciplinary databases1concerning several
topic-related key terminologies2. We conducted the
ﬁrst database search in October 2021 and repeated
the process in January 2022. To ensure that only
high-quality and topic-relevant literature is considered,
we applied the following criteria: First, we concentrate
on peer-reviewed publications available in English.
Second, we include literature that concentrates on BEMs
and explicitly or implicitly addresses requirements. This
comprises frameworks and prototypical concepts, and
simulations that provide insights regarding mediating
supply and demand through BC and other web3
technologies. Third, we focus on literature in the ﬁeld
of AM. Consequently, we exclude studies that consider
BC as a database (i.e., for traceability along supply
chains) and do not conceptualize a marketplace in terms
of resource allocation between supply and demand. The
search returned a total of 705 hits. Screening all papers’
1ScienceDirect, EBSCOHost, ACM DL, Emerald Insight,
IEEEXplore DL, AIS eLibrary
2(Decentral* OR Web3 OR Blockchain) AND (Additive
Manufacturing OR 3D-printing) AND (Platform OR Marketplace)
titles and abstracts results in 39 articles that meet our
inclusion criteria, including ﬁve removed duplicates. By
analyzing main texts, we exclude six publications from
the analysis corpus. An iterative backward and forward
search with the remaining 29 publications yield seven
additional articles, resulting in a ﬁnal set of 36 articles.
For the relevance cycle, which links design
activities to real-world problems and enhances the
practical relevance of artifacts, we opted for a twofold
approach: Firstly, we analyzed companies that provide
marketplace solutions in AM, and secondly, we
conducted qualitative expert interviews.
The dataset for the company analysis relies on
CrunchBase, the world’s largest database for young
companies. We ﬁrst considered all companies listed
for the keywords ”Blockchain; Marketplace; Additive
Manufacturing” in the ”3D Printing (Manufacturing)”
industry and identiﬁed 319 companies. To ensure
that our sample includes only relevant companies, we
applied the following selection criteria. First, companies
are relevant if they had already been mentioned in
our LR (i.e., Xometry, Shapeways, 3YOURMIND).
Second, to consider potentially successful companies,
we only selected ﬁrms that already received funding.
Companies that went bankrupt or did not have an
English homepage were excluded. In addition, we
only considered companies that operate a marketplace
for AM. Startups that do not provide a matchmaking
marketplace but represent 3D printing manufacturers
were excluded. Finally, we excluded companies that
did not provide information on the aforementioned
criteria. Considering all criteria, the ﬁnal set of analyzed
companies covered nine cases (see Table 1).
To collect data for the second iteration of the rigor
cycle, we followed a qualitative approach conducting
semi-structured interviews. This approach aimed
to complement requirements derived from literature
and company analysis and identify further necessities
through exploratory interviews with experts and
Table 1. Analyzed Companies
ID Name Website
C1 Xometry https://www.xometry.com/
C2 Shapeways https://www.shapeways.com/
C3 Essentium https://www.essentium.com/
C4 LINK3D https://www.link3d.co/
C5 Inkbit https://www.inkbit3d.com/
C6 3YOURMIND https://www.3yourmind.com/
C7 Origin https://www.origin.io/
C8 Jiga https://www.jiga.io/
C9 AstroPrint https://www.astroprint.com/
e, 2004). We selected the interviewees
(Table 2) with focus on ensuring that all experts have
experience in the ﬁeld of interest, represent different job
tenure, and cover a diverse group of industries, research
institutions, and company sizes. The time frame for
conducting eight interviews spanned from January 2022
to February 2022, lasting on average 58 minutes, with a
total of 461 interview minutes included in the analysis.
Characteristics of the interviewees and the duration of
the interviews are listed in Table 2.
We started the interviews by brieﬂy presenting the
research team and project and asked the interviewees
to introduce their professional backgrounds. For
the subsequent interview process, we developed an
interview guideline and based our questions on
preliminary considerations (Mayring, 2014). First, they
align with inductive dimensions identiﬁed during the
SLR (Corbin & Strauss, 2008). Second, we integrate
deductive information (Mayring, 2014) and align our
questions with the model of Veit (2003), that structures
marketplace interactions (see Section 4). Due to the
semi-structured nature, experts could also add novel
e, 2004), and we were able to ask follow-up
questions when interviewees mentioned interesting and
unexpected insights (Par´
e, 2004). For data collection
and analysis, we followed an iterative process (Corbin
& Strauss, 2008). First, after conducting the interviews
and obtaining informed consent, we transcribed the
recorded interviews, presented them to the interviewees
for approval (Brink, 1993), and analyzed the interview
transcripts as we continued interviewing. Second, we
analyzed the data and classiﬁed important aspects using
codes (Corbin & Strauss, 2008) based on the qualitative
content analysis guideline by Mayring (2014). As data
collection and analysis progressed, we continuously
reconciled and modiﬁed our codes and dimensionalized
codes and concepts (Corbin & Strauss, 2008). In total,
we derived 302 open-ended codes, which we group
into seven categories with 55 sub-codes. For interview
transcription and analysis, we used MAXQDA 2020.
Table 2. Details on Expert Interviews
ID Job title Job
E1 Head of CIO 31 years 74 min
E2 CEO & Founder 23 years 56 min
E3 Managing Director 27 years 58 min
E4 Research Engineer 17 years 53 min
E5 Project Director 30 years 65 min
E6 Product Development 4 years 47 min
E7 Innovation Manager 18 years 49 min
E8 Head of BC Research 11 years 59 min
Hevner’s third step is the design cycle. It builds on
the rigor and relevance cycles and is at the heart of any
DSR project. Here, all previously identiﬁed ﬁndings are
iterated as input to the design of an artifact. In our case,
the artifact consists of synthesizing requirements and
then articulating principles for BEM designs in AM. We
gather the required input for this endeavour through the
methodological steps above and describe core aspects as
design rationales (DRs) in the following section.
4. Design Rationales for
Next, we focus on DRs for BEMs in AM that emerge
from our LR, company analysis, and expert interviews
(see Table 3). We derive 27 mandatory requirements
(MRs), six optional requirements (ORs) and formulate
12 design principles (DPs) using the structure proposed
by Chandra et al. (2015). To capture and communicate
our design knowledge, we align our propositions with
Veit’s model, which structures marketplace interactions
along the following phases (Veit, 2003): information
and approach, intention and agreement, clearing and
settlement, and add suggestions for BEM governance.
4.1. Information and Approach Phase
The ﬁrst phase involves approaching potential
transactions and identifying agents who share
information on offered or demanded services (Veit,
2003). Participating agents include organizations, their
employees, and machines (Angrish et al., 2018). To
interact with each other and be identiﬁable, BEM agents
require digital identities (IDs). In AM scenarios, ID
attributes (MR1) include both company IDs (MR1.1)
(Al-Jaroodi & Mohamed, 2019) and 3D printer machine
IDs (MR1.2) (Angrish et al., 2018; Hofmann et al.,
2021). To track product histories (e.g., origin, process
parameters), product identities (MR1.3) are also
required (Ghimire et al., 2021, E2). They may be linked
to digital twins (OR1) (Ghimire et al., 2021; M. Li et al.,
zman et al., 2021, E2, E4, E8). ”I think there
are many cases where a real-time connection is not
crucial and an implementation would cost you a lot of
money. I do look at ﬁnished products and in hindsight on
the manufacturing parameters but I don’t need the data
from the last four milliseconds. You should carefully
assess whether you need a real-time synchronization
or if a discrete or sporadic synchronization is enough”
(E8). Consequently, we identiﬁed several ID features
(MR2) that are particularly important for BEMs in B2B
contexts. First, IDs should be able to map possible
afﬁliation constructs (e.g., subsidiaries) and hierarchy
levels (e.g., procuration levels) (MR2.1) (E2-4).
Second, the level of stakeholder anonymity is essential.
Although it should not be transparent to every market
participant who interacts with whom or how market
participants’ supplier relationships are structured
(MR2.2) (E2-7), ﬁrms should know direct business
partners (Herm & Janiesch, 2021, E6, E7). In addition,
independent third parties (e.g., auditors) should be able
to trace relationships in a rule-based process (MR2.3)
(E1, E2, E4). Potentially, an identiﬁable company
brand also represents a certain value as it conveys trust
(OR2) (E5, E7). Consequently, experts [E1, E4-7]
suggest pseudonymous and sovereign identities by
means of Self-Sovereign Identities (SSI) to be viable
for BEMs. By applying this concept, companies
could independently and seamlessly be represented
by SSI wallets holding ID credentials and certiﬁcates
(Engelmann et al., 2018; Kaynak et al., 2020). In
addition, wallets may be linked to a commercial registry
record to enable ID authentications (E5).
DP1: Design BEMs that allow each actor to manage
their sovereign and pseudonymous IDs.
DP2: Design BEMs that support sovereign wallets
that may hold certiﬁcates and other ID credentials to
qualitatively and quantitatively describe actors.
Another vital element involve the data exchange,
where security (Lu et al., 2018) and integrity (Barenji
et al., 2018) are crucial (MR3). Especially in AM
scenarios, sensitive and competition-relevant data (e.g.,
CAD product designs) are shared (E1-5) and must reach
their destination without tampering (MR3.1) (Ghimire
et al., 2021; Z. Li et al., 2018, E3-8). Consequently,
data storage and exchange design should ensure that
only the most necessary data – depending on individual
requirements or use case (Herm & Janiesch, 2021) –
are stored on-chain (E1, E4-7) (MR3.2). This approach
may also circumvent transaction costs (E5) and limited
storage capacity issues of BC protocols (Kurpjuweit
et al., 2021; Lu et al., 2019).
DP3: Design BEMs to prevent unauthorized access
to sensitive business data and store only a necessary
minimum as a persistent BC trust anchor.
Status updates of production processes and
visualizations of real-time data (OR2), as proposed by
several researchers (Engelmann et al., 2018; Ghimire
et al., 2021) and applied in cloud manufacturing
projects (C1, C2, C4, C8, C9), represent a helpful
feature that mainly brings convenience in BEMs (E4,
E5, E7). Examples include better-estimated delivery
dates (E3) and allowing supply chain actors to access
product-speciﬁc information (E7). Several interviewees
further mention traceability (MR4) requirements
and note that ex-post transparency about production
parameters (MR4.1) such as temperatures during
printing processes and humidity in pressure chambers
are essential for quality assurance (E1, E4, E5, E8).
Consequently, they must be documented persistently
and be accessible to authorized actors (e.g., customers,
producers, auditors, regulators) (E2, E7).
DP4: Design BEMs that require manufacturers to
persistently log manufacturing data.
4.2. Intention and Agreement Phase
This phase concerns offer and request coordination
and terms and conditions negotiation (Veit, 2003).
The supply side shall provide information about
their materials and processes to manufacture a
product (MR5) (Freichel et al., 2021, E2, E4,
E5), thereby accounting for DP3. This includes
material origin (C3, C7), material properties (C5, C7),
printer-speciﬁc information like run time, maintenance
status, and service performance (E1, E4-6), and if
used materials and processes are certiﬁed (MR5.1)
(E1, E2, E4-6). General information on corporate
certiﬁcations (MR5.2) might also be of interest (C1-3,
E5). Additionally, suppliers could specify which
complementary post-processing procedures they offer
to reﬁne a product (OR4) (E2). Depending on the
BEM target customer group, producers need to be able
to bid on requests (i.e., supplier-centric marketplaces)
or indicate their available production capacities and
processes (i.e., demand-centric marketplaces) (Freichel
et al., 2021; Stein et al., 2019) and index possible
delivery dates (MR5.3) (E6).
DP5: Design BEMs that require manufacturers to
provide information about their service offerings and
specify their individual preferences.
The demand side must specify its request (MR6) to
match it with possible suppliers. Product and production
speciﬁcations (MR6.1) include desired material
properties (Stein et al., 2019) and post-processing
methods (Freichel et al., 2021), product quality,
Table 3. Synthesizing Description of Design Rationales
Dimension Requirement Design Principle
MR1 ID Attributes Company, Machine, Product IDs Design BEMs that allow each actor to manage
their sovereign and pseudonymous IDs.
MR2 ID Features
Afﬁliation & Hierarchy Constructs
Distinctive Anonymity Levels
Design BEMs that support sovereign wallets that
may hold certiﬁcates and other ID credentials to
qualitatively and quantitatively describe actors.
MR3 Data Security
Design BEMs to prevent unauthorized access to
sensitive business data and store only a necessary
minimum as a persistent BC trust anchor.
Traceability Ex-Post Transparency Design BEMs that require manufacturers to
persistently log manufacturing data.
MR5 Supply Side
Production & Material Parameters
Capability, Capacity & Bids
Design BEMs that require manufacturers to
provide information about their service offerings
and specify their individual preferences.
MR6 Demand Side
Product & Production Speciﬁcation
Willingness to Pay
Design BEMs that enable consumers to specify
their service requests.
MR7 User Interface Filtering Options
M2M & HMI
Design BEMs with ambidextrous user interfaces
and a functionality to screen marketplace data.
Individual Preference Prioritization
Design BEMs with a reputation system where
consumers can ﬁlter different criteria according
to their individual preferences.
Design BEMs as demand-driven marketplaces
with semi-automated matchmaking functions
where consumers receive suggestions for
matching producers and choose to select the ﬁnal
producer based on their individual preferences
without disclosing sensitive data.
Agreement Hybrid Pricing & Negotiation Design agreements in BEMs as hybrid systems
that support individual pricing and negotiation.
MR11 Terms &
Automated Contract Execution
Dual Incentives & Payments
Design BEMs that allow for automated contract
execution with cryptographic token incentives
and payment options using ﬁat currencies.
Open & Transparent
Cooperation & Competition
Design BEMs to support interoperability and free
market access to those who follow consortially
deﬁned standards and rules.
certiﬁcation, and delivery date (Freichel et al., 2021;
Hofmann et al., 2021), maximum dimensions (Stein
et al., 2019), and an indication of the highest price
(Hofmann et al., 2021, E2, E3, E5, E6) consumers are
willing to pay (MR6.2). Having an optional ability to
ﬁlter by geographic location (OR4) allows producers to
specify their preferred venue (Zhu et al., 2020, E4, E6).
DP6: Design BEMs that enable consumers to specify
their service requests.
Given that BEMs purpose is to enable
cross-company and multilateral cooperation, they
should be designed with customizable functionalities
and a user interface (UI) (MR7). To ensure a
customer-centric approach for supplier matching,
experts suggest ﬁlter options (e.g., lot size, production
location) (MR7.1) (E6, E7). Furthermore, BEMs should
have UIs with visualized information on offers, requests,
manufacturing metrics, and transactions (Barenji et al.,
2021). Here, users should be able to enter data manually
(via a human-machine interface HMI) or monitor
automated processes (via a machine-to-machine M2M
interface) (MR7.2) (E1, E5).
DP7: Design BEMs with ambidextrous user interfaces
and functionality to screen marketplace data.
Another element of BEMs include
non-discriminating and transparent reputation systems
(MR8) for customer relationship management (Leng
et al., 2020; Zhu et al., 2020, E3, E4, E6, E7). As 
notes, ”you need a very sophisticated rating system to
ensure that the necessary quality is provided across
the platform.” Demand-side customers might utilize
reputation metrics as a ﬁlter option and selection aid
for potential suppliers in terms of trustworthiness and
reliability (E3, E4, E6, E7). Besides a company’s
reputation on quality, delivery time, communication
behavior, and general user satisfaction (E6, E7), the
rating of individual printers (E1, E2, E4, E6) and the
option to individually prioritize speciﬁc reputation
criteria are regarded relevant (E7). In the case of an
automated reputation mechanism using smart contracts,
updateable real-time data is required (Leng et al., 2020).
DP8: Design BEMs with a reputation system where
consumers can ﬁlter different criteria according to their
Supply and demand matchmaking (MR9) can
be designed in different conﬁgurations depending on
a market design, the complexity of requests, and
the technical knowledge of demanders (E5). Either
consumers specify their requests according to DP4
and producers submit offers related to these service
requests (E6, E7), or producers present their offerings
(e.g., available machines with speciﬁcations and prices
per utilization period), and consumers select a service
provider according to their preference (Baumung &
Fomin, 2019; Liao et al., 2020). In both supply-centric
and demand-centric marketplaces, it is necessary to
comply with DP2 by not disclosing sensitive data
until the matchmaking process is complete (MR9.1)
(Hofmann et al., 2021, E5, E7). Here, the process’s
degree of automation through IS depends on a product’s
manufacturing complexity (E1) and the customer’s
production knowledge (E5). In principle, fully
automated matching seems technically possible (C1, C2,
C6); however, experts consider it rather critically in B2B
(E4, E6). Therefore, they advocate designing BEMs
as demand-side marketplaces with partially automated
processes, where consumers receive suitable matches
for their requested services, but they manually select the
ﬁnal producer (MR9.2) (Hofmann et al., 2021, E1-7).
DP9: Design BEMs as demand-driven marketplaces
with semi-automated matchmaking functions where
consumers receive suggestions for matching producers
and choose to select the ﬁnal producer based on their
individual preferences without disclosing sensitive data.
To reach a transaction agreement (MR10) in the
matchmaking process, BEMs should further be capable
of hybrid pricing and negotiation mechanisms such as
bulk pricing (MR10.1) (E3-5, E7, C2). In addition,
artiﬁcial intelligence-based instant bidding mechanisms,
where service requests are ﬁrst checked for feasibility
followed by the calculation of an indicative price
for service requests, may also be a feature of AM
marketplaces (E2, E4-7, C1, C2, C6). However, experts
adhere that – depending on users’ security needs and
trust in the B2B context – fully automated instant
bidding should be an optional feature that does not
represent an essential part of BEMs (OR6) (E5, E7).
DP10: Design agreements in BEMs as hybrid systems
that support individual pricing and negotiation.
4.3. Clearing and Settlement Phase
This phase involves the execution of consented
agreements and the process of payment (Veit, 2003).
BEMs are supposed to ensure the execution of terms
and conditions (MR11) via smart contracts that are
automatically and reliably triggered when predeﬁned
conditions are met (MR11.1) (Hasan & Starly, 2020;
Kaynak et al., 2020; Leng et al., 2020, E2, E3). In
terms of payment methods, different options prevail, that
need to be considered in bidirectional and multilateral
business interactions (MR11.2). On the one hand,
tokens and cryptocurrencies such as Ether can be used
to provide both payments and incentive mechanisms
(Angrish et al., 2018; Kaynak et al., 2020). On the
other hand, some experts doubt the maturity of token
systems for current B2B applications (E2, E4, E5)
and, therefore, suggest that BEMs should offer classic
payment options with ﬁat currency, especially at the
very ﬁrst stages of a BEM (E1-5, E8, C1, C2). As [E8]
states: ”At least, these are the questions we face. It’s
not either ’or’, but often an ’and’, especially in the early
days.” As an evolutionary step between ﬁat systems and
cryptocurrencies, it might be helpful to use stable coins
pegged to currencies such as the dollar, thus increasing
exchange rate stability (Hofmann et al., 2021, E3-5).
DP11: Design BEMs that allow for automated contract
execution with cryptographic token incentives and
payment options using ﬁat currencies.
4.4. Suggestions on Governance
Shaping the governance openly and transparently
(MR12) – along with the design of the marketplace
interaction phases – has a critical importance for the
success of BEMs in B2B contexts (E1, E2, E6).
Particularly relevant are open standards that enable
interoperability (MR12.1) with other marketplaces and
avoid user lock-in (E2, E8). ”If BEMs use common
standards to identify users and enable interactions
among them, the marketplace is fully interoperable with
others. If a A-language and a B-language exist, users
get locked-in. This is exactly what we want to prevent.
It’s a K.O. criterion for decentralized marketplaces. If
this happens, we could use a centralized marketplace.
But nobody (or at least not our company) wants
that in business relationships. Sovereignty is king”
(E8). Similar to researchers in BC-based B2B logistics
(Beck et al., 2020), experts (E2, E5) argue that BEM
governance and interoperability should be provided
and observed by a consortium of industry leaders that
creates a legally binding framework for interaction and
monitors compliance (MR12.2). This would include
standards and rules that are jointly established with
the participation of all interested stakeholders (E1, E2,
E6). Companies would need to be able to pursue their
interests within these boundaries and compete based on
the jointly established infrastructure (MR12.3) (K¨
& Kunz, 2020, E5). Having consortial structures
at the organizational level would reﬂect the idea of
decentralization as realized at the technological level
through the operation of distributed nodes (E5).
DP12: Design BEMs to support interoperability and
free market access to those who follow consortially
deﬁned standards and rules.
5. Discussion and Conclusion
The decentralization of marketplace models through
BC-enabled peer-to-peer networks is expected to
have disruptive potential, especially in cross-company
applications (Mourtzis et al., 2020). Given its ﬁve times
higher volume compared to the B2C industry, the B2B
context is particularly interesting (Ziegler et al., 2022),
but requires speciﬁc structures in implementation. We
identify these requirements and translate them into
tangible DPs. To this end, our DSR methodology
combines insights from a SLR with an analysis of
practical projects and interviews with domain experts.
In this context, Veit’s (2013) marketplace interaction
phases serve as a model and classiﬁcation guideline.
Our three-fold research approach, incorporating both
theoretical and practical knowledge, results in numerous
managerial and scientiﬁc contributions. They reﬂect
in 12 DPs, 27 MRs, and six ORs that describe
identiﬁed factors for collaborative BEM networks and
embody the core contribution of our work. We
extend current approaches to designing BEMs that
are largely not based on pre-structured requirements
(Hofmann et al., 2021; Stein et al., 2019). Thereby,
we follow the call for a more nuanced approach to
this topic (K¨
olbel et al., 2022), which focuses on the
BC infrastructure of electronic markets (Alt, 2020) and
links the sub-economies of marketplace sharing with BC
economies (Weinhardt et al., 2021). By developing a
schema to describe, classify, and structure this complex
topic, we contribute to exploring this novel research
domain and lay a foundation for future research. With
our DPs, we enable BEM practitioners to design
technical constraints independently. For example, our
expert interviews and startup analysis suggested that
a demand-only market can be considered for BEMs
in AM, where consumers of 3D printing capabilities
communicate their speciﬁcations in return for a quote
with individual preferences. This would imply that
the respective companies’ semantically ambiguous and
historically entrenched production systems would not
need to be connected to the market, thus considerably
reducing complexity. Moreover, we argue that our
proposed DPs can be applied to similar BEM use cases.
Transferring the principles might require adjustments
to certain features (e.g., information provided in
the intention and agreement phase). However, we
provide a baseline for researchers and developers of
inter-organizational IS to draw upon. When interpreting
our results, we acknowledge inherent limitations to
our study, which at the same time open avenues for
future research. First, we encountered the challenge
of keeping DPs generic so that they apply to a class of
artifacts rather than just one instance. Here, we focused
on technical aspects. However, we note that BEMs
need to be considered from different perspectives.
Relevant aspects include, for example, business models,
incentive mechanisms, and legal and organizational
aspects. Governance, which we brieﬂy address in DP12,
should also be considered in more detail. Similarly, it is
worth investigating BEMs from an ecosystem and value
co-creation perspective (e.g., through service-dominant
logic). Second, our work needs to be regarded in
its context, as designing marketplaces depends on
individual use cases. Experts see the potential of
BEMs in AM mainly in on-demand production for
customer-speciﬁc requests and small batch sizes (e.g.,
prototypes, spare parts) rather than mass production (E3,
E4). Our results can serve as a foundation for research
that evaluates our DPs in, for instance, focus groups
or workshops to conﬁrm or iteratively revise them.
Third, we identify subsequent topics for future research.
These include auxiliary services (e.g., quality checks,
certiﬁcation services; E1-4, E7, C1), SSI utilization
(E2, E5, E8), UI design (E6, E8), or chatbots (C2,
C4) complementing BEM ecosystems. While previous
BEM concepts (Freichel et al., 2021; Kurpjuweit et al.,
2021) mainly propose automated payments via crypto
tokens, our interviewees point to various issues when
using tokens in B2B contexts (e.g., legal obstacles) and
propose a hybrid system with ﬁat currencies (E1-5).
Accordingly, further research should investigate the
acceptance of tokens in business transactions. Naturally,
another research avenue involves instantiating a BEM
using our DRs, which contributes to narrowing the
chasm between promised business and the actual value
of BC for organizations.
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