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Own - The Case of a Blockchain Business Model Disrupting the Equity Market


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Blockchain technology has the ability to disrupt most of today’s markets.We describe the business case of the fintech startup Own that aims to use blockchain technology to disrupt the equity market.We use this case to provide a specific example of how blockchain-based business models work and how they can disrupt markets by cutting out intermediaries.
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Own – The Case of a Blockchain
Business Model Disrupting the
Equity Market
Jan vom Brocke is the
Hilti Endowed Chair of Busi-
ness Process Management,
Director of the Institute of
Information Systems, and
Vice President of Research
and Innovation at the Uni-
versity of Liechtenstein.
Marcus Basalla is a
Research Assistant at the
Institute of Information Sys-
tems of the University of
Lena Franziska Kaiser
is a PhD student and
Institute of Information Sys-
tems of the University of
Blockchain technology has the ability to disrupt most of today’s markets. We
describe the business case of the fintech startup Own that aims to use blockchain
technology to disrupt the equity market. We use this case to provide a specific
example of how blockchain-based business models work and how they can
disrupt markets by cutting out intermediaries.
Jan vom Brocke, Marcus Basalla, Lena Franziska Kaiser, Johannes Schneider, Sascha
Ragtschaa, Florian Batliner-Staber and Ermin Dzinic
1. Introduction
The banking crises of 2008 thrust the current finan-
cial industry into a paradoxical state. Business
owners are struggling to acquire capital to fund
their growth. At the same time, investors are bur-
dened by record low interest rates and are seeking
meaningful returns. This should be fertile ground
for an accessible equity market to grow. However,
the number of shareholders is decreasing, and the
number of initial public offerings is also on the de-
cline. While in 1996 there were 8,025 companies
exchange-listed in the U.S., that number dropped
to 4,102 in 2012 (cf. Doidge et al., 2017, p. 464). Ad-
ditionally, while an average of 310 new companies
went public between 1980 and 2000, only 111 did
so between 2001 and 2015 (cf. Liu et al., 2016).
The traditional equity market relies heavily on
intermediary agents to ensure the validity and le-
gality of transactions. As a result, companies plan-
ning to sell shares on the stock market must go
through a long and expensive process in order to
get listed. Meanwhile, investors are put off by high
trading fees, a lack of transparency, and distrust in
the current system caused by the financial crash of
The term blockchain technology has rapidly
emerged in the public imagination since it was
coined in 2008 (cf. Yli-Huumo et al., 2016, p. 1).
Blockchain technology is a decentralized transac-
tion and data management technology that enables
secure and automated contracts and has the poten-
tial to replace intermediary entities. These smart
contracts are computer protocols that can automati-
cally execute the conditions of a contract. A smart
contract can, for example, make an automatic divi-
dend payout when a predefined condition is met.
Conditions can either depend on internal data on
the blockchain (e.g. minimum number of shares
sold for successful offering) or on external data (e.g.
certain time date, delivery information on a pack-
age) which is queried using so called Oracles. In
case of external information, the contract should
assure, that the source of the queried information
can be trusted. These smart contracts are saved on
the blockchain, which protects them from being
manipulated (cf. Crosby et al., 2016, p. 8). The tech-
nology itself ensures the validity of transactions
while saving them in a publicly accessible and un-
assailable distributed ledger. Consequently, smart
contracts can make trading shares less complicat-
ed, cheaper, and more transparent (cf. Kosba et al.,
2016, p. 839). As such, blockchain technology en-
ables process and business innovation in a number
of ways and is considered to have the ability to dis-
rupt most of today’s markets (cf. Mendling et al.
2018, p. 13).
In this article, we outline the case of Own (for-
merly Chainium), a financial tech (fintech) startup
based in Liechtenstein that allows business owners
to deal directly with investors. By getting rid of the
overhead costs incurred by intermediaries, Own’s
aim is to make the possibilities of the equity market
available to businesses of all sizes, which have so
far been excluded due to high financial barriers and
the complexity of the process. In this regard, Own
follows the tradition of developing technology,
where technology is used to cut out middlemen
30. JAHRGANG 2018 · 5/2018 23
Johannes Schneider is
an Assistant Professor at
the Institute of Information
Systems and the Hilti
Chair of Business Process
Management of the Uni-
versity of Liechtenstein.
Sascha Ragtschaa is
the CEO and co-founder
of Own AG.
Florian Batliner-Sta-
ber is the COO and co-
founder of Own AG.
Ermin Dzinic is the CTO
and co-founder of Own
and thereby disrupts existing markets such as trav-
el booking, apartment searching, and retail. We use
the Own case to provide a specific example of how
blockchain-based business models work and how
they can disrupt markets by cutting out intermedi-
aries. Although Own is at an early stage in their de-
velopment it seems beneficial to analyze their busi-
ness plan for strategies to disrupt the market using
blockchain technology. The fact that they already
reached several milestones, e.g., launching the
Platform 1.0, securing partners and clients and re-
ceiving strong press coverage, indicates that their
business plan was so far successful. Furthermore,
we selected this example because it outlines how
blockchain technology can generally disrupt the
traditional performance management, by using re-
spective technology to monitor businesses of all
sizes. This example shows that new technologies
present a new challenge for performance manage-
ment, which needs to be met.
The remainder of this article is structured as fol-
lows: We first give an overview of the current inef-
ficiencies of the equity market that can be over-
come by blockchain technology. Following this, we
will give an overview of Own’s platform. We de-
scribe use cases for both business owners and in-
vestors, outline why Own has the potential to dis-
rupt the equity market, and show how their busi-
ness model goes beyond offering a marketplace for
company shares. Finally, we derive lessons learned
from the Own case that might also inspire other
blockchain-based business models.
2. Equity Market
The Own case departs from the deficiencies of the
equity market. Importantly, the equity market puts
a large financial burden on companies that plan to
go public due to its complex structure of intermedi-
aries and strict regulations required to ensure trust.
In 2012, U.S. companies had to pay, on average,
more than US$1 million to convert to a public com-
pany (cf. Strategy&, 2012). Due to complex legal,
risk, and compliance requirements, the average in-
cremental costs of being a public company were
even higher, at US$1.5 million (cf. Strategy&,
2012). Doidge et al. (2017, p. 465) find evidence
that the cost increase of being listed and the de-
crease in benefits of being listed have caused a de-
crease in the number of listed companies as well as
an increase in their size. In other words, the finan-
cial burden of being listed only allows large compa-
nies to profit from the equity market.
In 2008, over 99 % of companies in the EU were
micro, small, or medium-sized entities (MSMEs),
which contribute to 58.6 % of the value added, and
they employed 66.7 % of the entire workforce. This
illustrates a large part of the market that has been
neglected so far (cf. Eurostat, 2011). In emerging
markets, the unmet need for credit among MSMEs
was estimated by the World B ank to be US$2.1 to
2.5 trillion in 2013 (cf. The World Bank Group,
Raising capital traditionally challenges entities
in various aspects (cf. Chainium, 2018). Barriers to
capital raising and investing are high since only a
small number of powerful intermediaries (e.g.,
banks, business angels) exist who decide which en-
tities receive access to capital. A lack of alterna-
tives enables intermediaries to charge high fees for
investors and business owners and provide rather
poor customer service. Moreover, business owners
cannot reconstruct company valuations due to the
fact that they are highly subjective and not trans-
parent. Since investors and business angels are of-
ten only interested in a significant number of
shares, business owners are forced to give away
large parts of their equity and lose control of their
companies. These challenges complicate the capi-
tal-raising process or even make it impossible for
MSMEs to raise capital.
While the traditional equity market ignores
MSMEs, these entities provide a large, untapped
investment possibility that can be harnessed by re-
ducing the financial burden of listing a company.
Own recognized the need and the potential of small
and medium-sized companies to raise capital and
provides a solution for any company to raise capi-
tal. By doing so, they disrupt the traditional equity
market. Disruption characterizes the process
whereby a small company has the chance to chal-
lenge established incumbent entities (cf. Christen-
sen et al., 2015, p. 47). Incumbents often focus on
their most profitable customers by providing ever-
improving products and services but ignoring less-
demanding customers. Disruptive innovation tar-
gets the bottom of the market – people who cannot
or do not want to pay extra for additional improve-
ments that are not necessary. Innovative companies
can win this customer base with cheaper and lower
quality services or products and then use this foot-
hold to improve their products further, until they
can offer a comparable but cheaper alternative to
the incumbent. Other ways to disrupt a business in-
clude creating a new market, targeting a new cus-
tomer group, or transforming non-customers into
customers (cf. Christensen et al., 2015, p. 47).
3. The Own Solution
Business Model
Own AG is a company based in the Principality of
Liechtenstein that provides a platform for any enti-
ty that wants to raise capital. On their platform, in-
vestors and business owners can directly interact
with each other. Investors can purchase shares, and
business owners can sell shares. This process is im-
plemented in a simple and secure way using block-
chain technology, especially smart contracts. By re-
moving expensive intermediary layers, Own is able
Emitter’s View Investor’s View
Direct Equity
Fig. 1: Emitters’ and investors’ platform interface
Central Conclusion
Blockchain technology has a high potential to disrupt a multitude of markets.
Blockchain technology should be enhanced by other state-of-the-art technologies.
to offer these services for free. The platform is open
to any business, from small family businesses to
large companies.
By cutting out intermediaries such as advisors,
brokers, banks, and other administrators, the plat-
form brings benefits for both business owners and
investors. Business owners can sell shares in a listed
or non-listed entity using a simple mobile applica-
tion. Furthermore, non-listed entities do not need to
implement an initial public offering (IPO) or rely on
venture capitalists to raise capital. The platform al-
lows business owners to sell shares directly to in-
vestors and build a relationship with them.
At the same time, Own also enables investors to
buy shares directly from entities they believe in. In-
vestors are no longer limited to listed companies;
they can also invest in non-listed companies. Con-
sequently, investors can invest in any share offer-
ing on the platform.
Platform Description
At the core of the platform lies a dual blockchain.
This new architecture is based on the interaction of
two separate blockchains one hosted publicly, one
privately. All transactions, in this case on the pri-
mary and secondary equity market, are handled by
the public blockchain. This ensures, that the infor-
mation on companies’ share offerings and of who
owns shares in which companies are publicly ac-
cessible. At the same time the fact that anyone can
host a copy of and mine this public blockchain en-
sures that attackers cannot create false transaction
data without the computation power to do so being
more expensive then the financial gain.
All sensitive information about the investors and
companies such as their banking details and contact
information, are saved on the private blockchain.
The private chain is only hosted on local nodes that
are controlled by Own and equity providers using
Own’s platform. This ensures that sensitive informa-
tion cannot be accessed by outsiders. By hosting this
data on a distributed blockchain, it is harder for an
attacker to change or erase user data. In theory the re-
striction of possible node owners, which are mostly
affiliated, increases the possibility for manipulations
on the blockchain by a majority of these parties.
However, given that all node owners are companies
whose business depends on the trust in the dual
blockchain this risk is extremely low. Should such a
manipulation still occur, it could only change infor-
mation on a user owning equity coins. The transac-
tion and ownership data and the users access to his
coins would stay intact, due to them being saved on
the public blockchain. To ensure compatibility of the
chains, transactions in the dual blockchain system
are only possible between parties that have an exist-
ing record on both blockchains.
In addition to the trading mechanism, the plat-
form offers a host of different services for both
emitters of equity and investors. While some of
these services (such as the trading itself) are free of
charge, others require a paid premium account.
Emitter Use Cases
The services offered to businesses cover several im-
portant requirements for the equity process. To make
their services available to businesses of all sizes,
Own offers a step-by-step process for creating an of-
fer. Business owners can select an investor base ac-
cording to their own preferences; for example, they
can choose the investor type, country, region, and
trading volume. Companies can even choose to hold
a private sale, using the platform only to ensure the
legality of the sale as well as transparency and secu-
rity. Additionally, companies can use paid premium
services to promote their sale to prospective inves-
tors. Figure 1 shows an illustration of the emitters’
and investors’ platform interface. Emitters can create
an offer for equity in their company. Investors can
view these offers and decide whether to buy equity at
the given price.
Another key feature of the platform is sharehold-
er interaction. Companies can use the platform to
inform shareholders of important events and devel-
opments. Through a voting tool, shareholders can
be directly included in strategic decisions without
the need for large-scale meetings. A perk system
can help increase shareholders’ loyalty by offering
additional equity at a reduced price or turn share-
holders into customers by offering discounts or free
items at a company’s retail store.
Knowing exactly who holds equity in a company
is essential. With all transaction data saved on the
blockchain, Own can offer business owners real-
time, deep insight into the demographics of their
investors. This feature not only provides a list of all
investors and their shares in the company but also
allows exploration of all dimensions of the investor
base such as their trading volumes and their distri-
30. JAHRGANG 2018 · 5/2018 25
Implications for practice
Blockchain technology can disrupt markets in that it cuts out intermediaries and thus lowers
transaction costs by connecting supply and demand directly supported by technology.
Blockchain technology alone is not sufficient to create new business models and market
structures, but solutions need to carefully take into account human behavior and related re-
Blockchain technology needs to be combined with other technologies in order to create com-
prehensive value-adding solutions.
bution among countries as well as other demogra-
phic factors.
Investor Use Cases
Investors can use a mobile app to buy shares of
companies. Based on investor profiles, the app re-
commends relevant investment offers based on an
investor’s location, preferences, previous search
queries, and the preferences of investors with simi-
lar profiles. An investor with a technical back-
ground may be recommended mostly technology
companies because this person’s knowledge allows
them to better estimate the prospects of an invest-
ment in this sector. Other users might prefer locally
based or socially beneficial businesses.
As soon as the transaction is complete, it is enco-
ded on the blockchain by a smart contract. The in-
vestor can then see the shares on a personal portfolio
dashboard. This dashboard gives an overview of all
the shares a user holds and allows users to further
analyze their shares’ performance. Investors’ perfor-
mance is analyzed using machine learning methods.
This allows Own to make valid recommendations ba-
sed on the investors’ preferences. In addition, it can
be used to improve investors’ trading strategies.
The blockchain’s smart contracts make it easy to
trade shares between any two parties on the plat-
form. Buyers and sellers can be directly matched,
removing the need for costly intermediaries. There-
fore, Own can offer a secondary equity market wi-
thout any transaction costs. As soon as an offer is
completed, shares can be freely traded among in-
vestors in this secondary market. Due to the block-
chain’s transparency, investors do not rely on bro-
kers to access the market, saving them additional
investment costs. Such a free secondary market
should result in improved price discovery and the-
reby a more accurate valuation.
Third-party use cases
To allow their platform to grow and offer additional
services from the core product, Own supports the
integration of third-party services. Third parties
can use an open application programming interface
(API) provided by Own to develop additional ap-
plications and services on the platform. This al-
lows players from the old stock market to participa-
te in the new equity market as well as new players
to offer their own services. By including players
and services from the old stock market, Own lowers
the barrier for larger companies to enter their plat-
form while still being able to rely on the service
providers they know.
Certified brokers can use this service to recom-
mend investment opportunities to their customer
base. Registrar services can use the API to access
transaction and released investor data. They can of-
fer these data directly to Own’s customers using a
platform app and can use them to complement
their existing registry service. To query data, these
third parties have to pay a fee. Users can decide for
themselves which data they make accessible to
third parties; however, withholding some data
might come at the cost of a platform fee.
Most blockchains are, by their nature, unregula-
ted. While this is beneficial for cryptocurrencies
that are an alternative to regulated national curren-
cies, it might throw off investors and business ow-
ners when it comes to large and important transac-
tions such as the sale of company shares. With their
company headquarters in Liechtenstein, Own can
profit from the unique advantages the country of-
fers for fintech companies. A high level of political
continuity and stable legal and economic conditi-
ons ensure long-term legal security. Liberal and
progressive economic policies along with a govern-
ment that offers pragmatic support and fast decisi-
on times allow for quick adaptations to new regula-
tions (cf. Lenherr/Stahl, 2017). In addition, Liech-
tenstein’s government is actively supporting block-
chain companies and is currently working on a le-
gal framework. As a further step, the company
plans to engage with additional financial authori-
ties outside the EU to comply with their standards
and offer a legal, secure, and regulated platform to
additional markets.
Company value assessment
For a successful offer on a digital equity platform, it
is essential to set a fair value of shares. It is Own’s
philosophy that the business owner can freely deci-
de at which price to sell his or her shares. Investors
can then decide to accept or decline the offer. Ho-
wever, it might be difficult for an investor to set his
company’s value in a reasonable range while inves-
tors might have problems deciding whether an of-
fer comes at a fair price. To ensure mutual trust,
Own is cooperating with researchers from the Uni-
versity of Liechtenstein in developing a dashboard
that allows investors to evaluate an offer and busi-
ness owners to set a reasonable price in the first
place (Figure 2). In this case, business owners can
upload financial data and access web data from so-
cial media platforms. Through sentiment analysis
tools, investors can view a summary of the compa-
ny’s hard and soft facts as well as prognosis for its
future development.
Investors should be able to get all the necessary
information they need to decide on investing in a
Experience: 10 years
Connections: 1100
Skills: …
Qualifications: …
Financial Performance
Data Analytics
Company Value
2,050,000 CHF
profit dev sales dev
Brand Product Team
very positive
slightly negative
very negative
very positive
slightly negative
very negative
Profit growth Value growth Returns
+ 11.8 % + 13.2 % + 9.8 %
2016 2017
Financial Performance
Data Analytics
Company Value
… CHF - …. CHF
Log in with:
Emitter’s View Investor’s View
Fig. 2: Mockup of the company valuation dashboard
company’s shares from such a dashboard. Most tra-
ditional valuation methods are based solely on
hard financial facts. It is essential to provide the
necessary financial factors to investors so they can
estimate the value of the company themselves or
use a valuation model to compare its results to the
offered value. To decrease the workload of business
owners, state-of-the-art text mining methods will
be investigated to extract the necessary information
from already existing financial documents such as
end-of-year reports and balance sheets.
However, non-financial soft facts often have
as much influence on a company’s chances of suc-
cess, especially in smaller businesses. Among
the most influential of these soft facts are the expe-
rience of the managerial staff and the company’s
reputation. Cassar (2014, p. 137) shows that busi-
nesses run by entrepreneurs with industry experi-
ence in general and high-tech industry experience
in particular are significantly more likely to meet
their growth expectations. This information has
even been used in predicting bankruptcies (cf.
Tobback et al., 2016, p. 79). Most professionals al-
readyhaveapublicr´esum´e on social media sites
such as LinkedIn or Xing. Afunctionthatparses
these services allows business owners to provide
information on their qualifications with almost no
extra work.
Publications in traditional and social media are
good indicators of a company’s public reputation
and can even be used to predict stock market devel-
opments (cf. Schumaker et al., 2009, p. 2). There
are already several services that offer a range of op-
tions to analyze online publications about a certain
entity. By offering an easy way to integrate the re-
sults of these third-party services into Own’s plat-
form, business owners can make a better case for
their companies while investors can get a better
idea of the reputation of the company they plan to
invest in.
It is often difficult for non-experts to predict a
company’s future prospects from raw financial da-
ta. Therefore, this dashboard should make use of
machine learning tools to predict the general devel-
opment of a company from its financial data. There
is already extensive work on the use of machine
learning to predict bankruptcy and financial risk
(cf. Tobback etal.,2016,p.73).Therefore,itseems
plausible that these techniques can be modified for
the purpose of predicting a company’s general de-
This avalanche of information can easily over-
whelm investors, especially if they are not finan-
cial experts. While raw financial data can be diffi-
cult to interpret, it is just as difficult to determine
which of the soft facts actually matter. Therefore,
an important part of developing this dashboard
will be investigating how to present and arrange
this information in a way that it entails the highest
grade of usefulness for the investor. The investors
should be presented with as much information as
possible. At the same time, this information should
be condensed and presented in a way that does not
overwhelm inexperienced investors.
4. What we can learn from the Own case
Drawing from the Own case and complementing
prior research (cf. vom Brocke et al., 2018), we can
conclude that there are some lessons learned,
which may be beneficial for other organizations to
capitalize on blockchain technology.
(1) Own uses blockchain technology for dis-in-
termediation. The startup removes expensive and
time-consuming intermediaries, which allows Own
to offer their services at a much lower price (essen-
30. JAHRGANG 2018 · 5/2018 27
tially for free). On the other hand, the removal of
these trusted intermediaries will probably mean
that Own’s services will not immediately meet the
considerable requirements placed by high-value
companies. However, it is sufficient for smaller
(2) Own focuses on a specific market segment to
start with. Own clearly follows a disruptive busi-
ness model as stated by Christensen et al. (2015, p.
3). They focus on a low-foothold market – small
and medium sized companies – that was previous-
ly ignored by incumbents, who are focused on a
few high-value customers, i.e., large listed compa-
nies. By offering a cheap alternative to the incum-
bent’s services, Own can build a base of customers
that allows them to further grow and improve their
(3) Own has aimed at continuously improving
their service from the very beginning. From the be-
ginning, Own has already taken steps that aim to
improve their service to a point where it can com-
pete with the incumbent’s solution while still being
cheaper. To overcome the shortcomings of trust and
legal security that Own might face compared to the
traditional equity market, they are in close contact
with financial regulators to ensure that their prod-
uct complies with all regulations. At the same time,
they use a team that is highly experienced in finan-
cial and equity solutions to ensure that their prod-
uct can meet the functional requirements of the
(4) Own combines blockchain technology with
data analytics and machine learning. By using ma-
chine learning and data analysis, Own can auto-
mate more services of the old equity market such as
investment recommendations and company valua-
tion. With this strategy, they can close the gap in
the services offered by the incumbents while still
keeping the price of their product low. In addition,
they provide an API for third parties. Using this
API, existing players from the traditional equity
market can also offer their services on the Own
platform, bringing trusted entities from the incum-
bent into the new market. These trusted entities
can in turn lower the barrier for established compa-
nies to change from the incumbent equity market to
the new platform.
(5) Own chooses Liechtenstein as the seat of
their headquarters. The Principality of Liechtens-
tein enables flexible legal regulations and is cur-
rently developing a legal framework for the use of
blockchain technology. As a member of the Europe-
an Economic Area, Liechtenstein offers access to
the European market and a supportive environ-
ment for companies and individuals interested and
active in blockchain technology.
(6) Own ensures transparency while protecting
sensitive data. By introducing the concept of a dual
blockchain, Own found a way to use blockchain
technology, while separating public and private in-
formation. Storing all transaction data on a public
blockchain ensures the transparency and security
of the exchanges and allows for easy oversight. At
the same time, sensitive information is stored on an
encrypted private blockchain, ensuring the users’
5. Conclusion
By focusing on Own, we have described a company
that is using blockchain technology to disrupt the
equity market. We have shown how their model
makes use of the advantages of blockchain technol-
ogy and how they deal with the drawbacks of the
new technology. We have outlined how technolo-
gies can change the way performance management
has been done. From this analysis, we can find gen-
eral principles that can help businesses use block-
chain technology in a disruptive way.
Blockchain technology is ideal for automating
applications where the execution of transactions
relies on trusted intermediaries that ensure its va-
lidity. Any industry that fits this profile can poten-
tially profit from the use of blockchain technology
by cutting out the intermediaries and directly con-
necting supply and demand. Even when offering a
comparable product at a lower price, it is difficult
to take an incumbent head on. It is better to focus
on a low- or no-foothold market. With such a foot-
hold established, it is much easier to improve a
product and target higher value customers that
have been previously served by the incumbent.
Any new technology, no matter how great it is,
does not make a good business strategy or a good
product on its own. Solutions based on these mod-
els need to take the market and the customers into
account. Therefore, one of the most important qual-
ities needed to disrupt a market with blockchain
technology, is experience in the target market. Usu-
ally only part of a product or service can be auto-
mated using blockchain technology. To create com-
prehensive value-adding solutions that can com-
pete with incumbents’ products, blockchain tech-
nology must be combined with other technologies.
Many markets are, like the finance sector, highly
regulated and largely dependent on trust. When us-
ing blockchain technology, it is therefore important
to ensure legal security to customers and to make
sure the service adheres to all regulations.
Given that the Own company is still at an early
stage of their development it will be beneficial to
watch their progress and to further refine the in-
sights we gained from this case based on how suc-
cessful each of them turns out to be in a practical
business environment. Further work should also
compare this case to other blockchain ventures
with similar goals to see how these factors general-
In conclusion, we can see that blockchain tech-
nology has a high potential for disrupting a multi-
tude of markets. However, for this potential to be
fully harnessed, its use must be based on a thor-
ough understanding of the market, the customers,
and the legal environment. To further increase this,
potential blockchain technology should be en-
hanced by other state-of-the-art technologies such
as data analytics and human-machine interaction.
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# Aktienmarkt # Blockchain # Innovationen
# Marktstörung
# Blockchain # Disruption # Equity # Innova-
Blockchain-Technologien können durchaus als dis-
ruptive Faktoren für bestehende Märkte bezeichnet
werden. In dem vorliegenden Beitrag wird das Fin-
Tech Startup Own betrachtet, welches Blockchain-
Technologien einsetzt und damit den Aktienmarkt
revolutionieren will. Der Fall ist ein konkretes und
praktisches Anwendungsbeispiel, wie Geschäfts-
modelle funktionieren können, die auf Blockchain-
Technologien basieren, und wie der Wettbewerb
dadurch verändert werden kann. Ein wesentlicher
Aspekt ist dabei das Umgehen von Intermediären,
was ein typisches Muster für FinTech-Unterneh-
men ist.
30. JAHRGANG 2018 · 5/2018 29
Full-text available
This is a multi-disciplinary research based position paper being prepared for Government of India on means of promoting sustainable seed innovations, i.e., promoting research and in situ innovations with agrobiodiversity by all stakeholders, especially small farmers, with the aim of enhancing their income, supporting the cause of conservation and sustainable use of agrobiodiversity, and maintaining local cultures and traitions. To accomplish this end, the paper recommends the adoption of a three pronged approach comprising of (i) reviving Traditional Ecological Knowledge based farming systems (as a means, inter alia, of diversifying the types of agricultural systems that small farmers can choose from, enriching beneficial soil microbial diversity, and enhacing productivity not only of 'improved' 'uniform' seeds, but also of indigenous, heterogenous seeds), (ii) amending educational curriculums for farmers and their teachers and (iii) adopting a blockchain/DLT and AI supported solution to enhance traceability and trust and ensure that equitable remuneration is recieved by (small) farmers (or farmer communities) engaged in in situ conservation and innovation with agrobiodiversity, so that they are incentivized to continue this work and to share their knowledge and PGRs. A preliminary theoretical framework/outline (non-technical) of the blockchain/DLT and AI solution is provided as Annex 3 of the Position Paper to encourage discussion and initiate mutli-disciplinary research and development of a solution. The research is funded by the UK Arts and Humanities Research Council's Global Challenges Research Fund (PI: Gregory Radick; Co-I and Corresponding author of position paper: Mrinalini Kochupillai)
Full-text available
Process Management. This research has been conducted by an impressive amount of 32 co-authors, led by Jan Mendling and Ingo Weber (Mendling et al. 2018). Based on this work, we derive eight recommendations for companies to capitalize on blockchain technology. In this Column, we derive the recommendations referring to each of the eight BPM lifecycle phases (Dumas, M. et al. 2018). In a separate article (vom Brocke, Mendling, Weber 2018), we derive further recommendations referring to the impact blockchain as regarding the six BPM capability areas (Rosemann, vom Brocke (2015). We advise readers to also refer to the original Column (Mendling et al. 2018), which is more comprehensive and detailed in nature. This Column intends to report on the research conducted and to highlight the most relevant implications of Blockchain technology for Business Process Management research and practice.
Full-text available
(Note that we have updated the paper to the accepted version on 23 Jan 2018) Blockchain technology offers a sizable promise to rethink the way inter-organizational business processes are managed because of its potential to realize execution with- out a central party serving as a single point of trust (and failure). To stimulate research on this promise and the limits thereof, in this paper we outline the challenges and opportunities of blockchain for Business Process Management (BPM). We structure our commentary alongside two established frameworks, namely the six BPM core capabilities and the BPM lifecycle, and detail seven research directions for investigating the application of blockchain technology to BPM.
Full-text available
Blockchain is a decentralized transaction and data management technology developed first for Bitcoin cryptocurrency. The interest in Blockchain technology has been increasing since the idea was coined in 2008. The reason for the interest in Blockchain is its central attributes that provide security, anonymity and data integrity without any third party organization in control of the transactions, and therefore it creates interesting research areas, especially from the perspective of technical challenges and limitations. In this research, we have conducted a systematic mapping study with the goal of collecting all relevant research on Blockchain technology. Our objective is to understand the current research topics, challenges and future directions regarding Blockchain technology from the technical perspective. We have extracted 41 primary papers from scientific databases. The results show that focus in over 80% of the papers is on Bitcoin system and less than 20% deals with other Blockchain applications including e.g. smart contracts and licensing. The majority of research is focusing on revealing and improving limitations of Blockchain from privacy and security perspectives, but many of the proposed solutions lack concrete evaluation on their effectiveness. Many other Blockchain scalability related challenges including throughput and latency have been left unstudied. On the basis of this study, recommendations on future research directions are provided for researchers.
Full-text available
Our research examines a predictive machine learning approach for financial news articles analysis using several different textual representations: Bag of Words, Noun Phrases, and Named Entities. Through this approach, we investigated 9,211 financial news articles and 10,259,042 stock quotes covering the S&P 500 stocks during a five week period. We applied our analysis to estimate a discrete stock price twenty minutes after a news article was released. Using a Support Vector Machine (SVM) derivative specially tailored for discrete numeric prediction and models containing different stock-specific variables, we show that the model containing both article terms and stock price at the time of article release had the best performance in closeness to the actual future stock price (MSE 0.04261), the same direction of price movement as the future price (57.1% directional accuracy) and the highest return using a simulated trading engine (2.06% return). We further investigated the different textual representations and found that a Proper Noun scheme performs better than the de facto standard of Bag of Words in all three metrics.
Bankruptcy prediction has been a popular and challenging research area for decades. Most prediction models are built using financial figures, stock market data and firm specific variables. We complement such traditional low-dimensional data with high-dimensional data on the company’s directors and managers in the prediction models. This information is used to build a network between small and medium-sized enterprises (SMEs), where two companies are related if they share a director or high-level manager. A smoothed version of the weighted-vote relational neighbour classifier is applied on the network and transforms the relationships between companies into bankruptcy prediction scores, thereby assuming that a company is more likely to file for bankruptcy if one of the related companies in its network has already failed. An ensemble model is built that combines the relational model’s output scores with structured data and is applied on two data sets of Belgian and UK SMEs. We find that the relational model gives improved predictions over a simple financial model when detecting the riskiest firms. The largest performance increase is found when the relational and financial data are combined, confirming the complementary nature of both data types.
I theoretically develop and empirically investigate the role of industry and startup experience on the forecast performance of 2,304 entrepreneurs who have started new businesses. Using the Kauffman Firm Survey I show that industry experience is associated with more accurate and less biased entrepreneur expectations. Further, the benefit of industry experience on entrepreneurial forecast performance is greater in high-technology industries. These findings are consistent with knowledge of the setting informing entrepreneurial decision making, especially in highly uncertain environments. However, in contrast to the prevailing view in the literature, I find no significant evidence that startup experience improves entrepreneurial forecast performance.
The equity market is broken -let's start again
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The blockchain model of cryptography and privacy-preserving smart contracts
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Kosba, A./Miller, A./Shi, E./Wen, Z./Papamanthou, C., Hawk, The blockchain model of cryptography and privacy-preserving smart contracts, in: Security and Privacy, 2016 IEEE Symposium, (2016), p. 839-858.