The Role of Digital Artifacts in Fostering Ecosystem Creation

Edoardo Meraviglia, Jacopo Manotti, Davide Moiana, Antonio Ghezzi and Andrea Rangone

Politecnico di Milano, Department of Management, Economics and Industrial Engineering,

Via Lambruschini 4B, 20156, Milan, Italy

Keywords: Digital Artifact, Ecosystem, Value Creation, Value Capture.

Abstract: Since 2008, blockchain has slowly entered our lives in different ways: from Bitcoins and crypto currencies to

platforms like Ethereum, to NFTs and Fan Tokens. There is often still speculation about these issues, but there

are successful use cases that have revitalized traditional industries: this is the case in the sports industry. Many

sports teams, particularly football teams, have always tried to monetize their fans in various ways to create

new sources of revenue; and thanks to Fan Tokens this has been possible. Consequently, an exploratory

multiple case studies was conducted in order to analyze how a digital artifact (Fan Token) can create an

ecosystem that helps sports companies to innovate and monetize through increased fan engagement. As a final

result, this research has led to the definition of an empirical model that demonstrates how the intrinsic

characteristics of a digital artifact can be harnessed to create an ecosystem to create and capture value from

fan-customers.

1 INTRODUCTION

In the increasingly dynamic and interconnected

context of contemporary digital society,

technological evolution has generated new forms of

digital tools that not only reflect technological

progress, but also actively influence the way people

interact with the world around them. In the field of

sport, in fact, we are faced with a reality characterized

by universal appeal and emotional involvement. Sport

represents a common language that overcomes

cultural and language barriers. The passion

surrounding sporting events provides fertile ground

for experimenting and implementing technologies

that amplify this emotional connection between fans

and teams (Fonti et al., 2023). Sports teams also

enjoy a large supporter base that, thanks to

globalization and digital connectivity, can be reached

and engaged with globally offering a unique

opportunity to implement technology solutions that

amplify fan engagement.

One of the most important examples of the latter

is the introduction of Fan Tokens, which have opened

a new frontier in fan engagement, transforming the

traditional passive relationship into an active and

personalized involvement. These tokens, usually

based on blockchain technologies, allow fans to

directly participate in the dynamics of the team and

access exclusive benefits. Thanks to this opportunity,

to exploit the affordances generated by these Fan

Tokens, which were identified in digital artifacts

objects (Kallinikos et al., 2013), entrepreneurs and

established firms can create new way to monetize

from their customers and new services and value

propositions to offer to them (Autio et al., 2018).

However, despite the recent start of explorations

in the literature on the potential of digital artifacts

(Kallinikos et al., 2013, Ojala et al., 2023) and the

analysis of ecosystems and their internal dynamics

(Adner, 2017; Felch & Sucky, 2022), the assessment

of the impact of a digital artifact on the creation of an

ecosystem is still an unexplored area of research.

Therefore, this research aims at providing its

contribution to the connection between digital

artifacts and ecosystems with the research question:

“How do digital artifacts enable the creation of

ecosystems?”. In particular, through an exploratory

multiple case study, this research evaluates how the

implementation of Fan Tokens has enabled the

creation of ecosystems that cross the traditional

boundaries between sport and technology, combining

technology providers, sports clubs, and fans in a

fruitful synergy.

This study contributes to prior literature in three

ways. Firstly, the study explores, how the inherent

characteristics of the digital artifact (e.g. Fan Token)

Meraviglia, E., Manotti, J., Moiana, D., Ghezzi, A. and Rangone, A.

The Role of Digital Artifacts in Fostering Ecosystem Creation.

DOI: 10.5220/0012594400003690

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 26th International Conference on Enterprise Information Systems (ICEIS 2024) - Volume 2, pages 667-674

ISBN: 978-989-758-692-7; ISSN: 2184-4992

667

have created new business opportunities and opened

up new avenues of interaction for technology

providers. Secondly, it provides an understanding of

how traditionally game-oriented sports clubs have

approached the world of technology through the

adoption of these innovations and what activities and

resources come into play. Thirdly, how the digital

artifact has a positive impact on fan engagement and

consequently what sources of value are created and

captured, within and outside the ecosystem, as a result

of the development and use of the digital artifact.

2 LITERATURE REVIEW

Ecosystems. Due to the multiplicity of concepts

related to the ecosystem theory, there is redundancy

and overlapping of theoric fields that raised confusion

about what an ecosystem is and where an ecosystem

perspective, of a specific environment, can or cannot

add value (Adner, 2017). Adner (2017, p. 4) defined

an ecosystem as “the alignment structure of the

multilateral set of partners that need to interact in

order for a focal value proposition to materialize”.

Adner (2017) added another important contribution to

the ecosystem theory, distinguishing between

ecosystem-as-affiliation, which sees the ecosystem as

a community of associated actors, and ecosystem-as-

structure, which views ecosystem as a configuration

of activities defined by a focal value proposition.

From the definition provided by Adner, four elements

characterize ecosystems: activities, actors, positions,

and links.

In the ecosystem theory the locus of value creation

lies in the presence of interdependencies and

complementarities among actors, whose contribute to

the creation of a focal value proposition for customers

(Kapoor, 2018). While complementarities represent

an economic relationship between offers in terms of

value creation potential (Felch and Sucky, 2022),

interdependencies constitute a structural relationship

between offers in terms of how they are

interconnected for value creation and how a change

in one offer can affect the contribution of other offers

to value creation (Kapoor, 2018). Another important

contribution of Kapoor (2018) is the identification of

three objects that are fundamental for an ecosystem,

which are: bottlenecks, complementors, and

platforms. All these aspects, technology architecture,

interdependencies, and integration systems, have a

fundamental impact on how value is created in an

ecosystem (Kapoor, 2018).

Value creation mechanisms received attention by

a different perspectives (e.g., Amit and Zott, 2001),

Zott and Amit (2010) and Amit and Zott (2001)

defined the 4 sources of value creation: novelty, lock-

in, complementarities, and efficiency. Later, Amit

and Han (2017) discussed the new sources of value

creation in a digitally enabled world in which digital

platforms and ecosystems play a significant role.

Another important study on the different types of

value was conducted by Lepak et al. (2007), in which

there is a distinction between the use and exchange

value. Respectively, the former is the quality

perceived by the customers in relation to their needs

(Bowman and Ambrosini, 2000), whereas the latter is

the monetary amount realized at a certain point in

time (Bowman and Ambrosini, 2000).

Digital Artifacts. Several authors tried to give a

clear definition of what is a digital artifact (Ekbia,

2009; Zittrain 2008), but only Kallinikos et al. (2013)

explicitly pointed out the characteristics of digital

artifacts. Following other authors (e.g., Ekbia, 2009;

Zittrain, 2008), Kallinikos and colleagues (2013)

highlight how digital artifacts differ from physical

entities of non-digital constitution along a number of

dimensions/characteristics, namely: editability,

openness, distributedness, and interactivity.

Moreover, digital artifacts are often embedded in

mutable interdependencies with other entities in

broader digital ecosystems, and digital artifacts can

generate other digital objects often distributed in the

same or other ecosystems, therefore making the

connection with ecosystem theory (Kallinikos et al.,

2013). These findings suggest that digital ecosystems

will never settle due to the incomplete and mutant

nature of these digital artifacts (Kallinikos et al.,

2013). Based on these characteristics, Ojala et al.

(2023) created a framework on which exploiting the

digital artifacts characteristics to internationalize new

ventures (Ojala et al., 2023).

Therefore, we can notice how clear the concept of

"ecosystem" has become an important topic among

scholars and practitioners particularly in the past two

decades (Adner, 2017, Jacobides et al., 2018).

Furthermore, several authors agree on the crucial role

that digital artifacts (Kallinikos et al., 2013, Ojala et

al., 2023) play in the development of ecosystems.

However, although the literature has clearly defined

what an ecosystem is, how it is structured and what

the internal dynamics are, the question of how actors

within an ecosystem (Adner, 2017) interact and align

to create value in the presence of a digital artifact

(Kallinikos et al., 2013) is missing. Therefore, this

research will focus on how the digital artifact, through

its characteristics, is the enabler of an ecosystem. All

this is encompassed in the research question: How do

digital artifacts enable the creation of ecosystems?

ICEIS 2024 - 26th International Conference on Enterprise Information Systems

668

3 METHODOLOGY

This research employs a qualitative (Gartner and

Birley, 2002) and exploratory study based on a

multiple case study (Yin, 1984; Eisenhardt, 1989;

Eisenhardt & Graebner, 2007) to investigate the

creation of ecosystems by digital artifacts. This

method suits research questions responding to a

“why” or “how” when the investigator does not have

control over events and when the focus is on

contemporary events. In particular, a multiple case

study approach has been chosen because the literature

has recognized that it is more robust compared to a

single one (Yin, 1984), and it allows to obtain

generalized results, enabling comparisons among

different manifestations of the phenomenon

(Eisenhardt & Graebner, 2007).

The digital artifact (Kallinikos et al., 2013) acts as

a unit of analysis (Yin, 1984), central to the creation

of an ecosystem in which actors collaborate around a

shared value proposition (Adner, 2017). In this

research, the Fan Token, which is a utility token

(Glossario blockchain, 2022) created through

blockchain technology (Glaser, 2017; Nakamoto,

2008), is seen as digital artifact. The Fan Token is

composed of two basic components: on the one hand,

immutable pure computing elements related to the

blockchain structure, and on the other hand,

modifiable computing components, which are linked

to related services, such as redeemable experiences in

terms of “rewards” and the possibility of voting, both

of which can be modified over time. This second

component emphasizes the connection and similarity

between the Fan Token and digital artifact

characteristics (Kallinikos et al., 2013).

3.1 Case Sampling

In the approach chosen for case selection in this

study, a heterogeneous approach was taken. This

means that the goal is to include cases representing

different patterns of behaviour, outcomes, decisions,

and evolutionary stages of the analyzed process.

Heterogeneity aims to identify and compare different

types related to the same phenomenon, providing a

comprehensive view of the dynamics involved (Yin,

1984). To implement this approach, it was essential

to establish in advance the number and type of cases

to examine (Yin, 1984). After defining the research

question that our research focuses on, it was identified

the key players involved in this ecosystem, such as

technology providers, responsible for the creation and

sale of Fan Tokens, sports teams that collaborate with

technology providers to increase the engagement of

their fans, and finally, the sports team supporters

themselves who constitute the end users of digital

artifacts. Among all the types of sports teams that

participate to the Fan Tokens initiatives, it was

decided to select only the football firms. This choice

is due to the fact that football is the most popular and

followed sport in the world in fact has about 3.5

billion sports team supporters and about 250 million

players in more than 200 countries. Moreover,

football is responsible for 40% of the overall market

value of sports business, which was more than $500

billion in 2022.

During the initial phase of the case study selection

process, a geographical criterion was adopted. The

selection was deliberately limited to European

football clubs. This geography-based approach was

deemed to be of significant importance as the

dynamics and opportunities in the Fan Token industry

can vary considerably between different regions. To

ensure that the selection of cases was accurate and

reliable, the official FIGC database was used, which

contains detailed information on a wide range of

European football clubs. The research led to 70

football teams operating with Fan Token platforms.

In order to refine the selection process, the selection

focus shifted to the technological providers to first

understand which one is considered to be the most

important and most established, so as to also narrow

the selection field to football teams. In this case, the

criteria chosen was to select the technology providers

with the highest Fan Token market cap (sum of

market value of all the Fan Tokens traded in the

platform) in the Europe landscape. Following this

selection criteria, Bitci was excluded due to the too

low market cap. The selection of Socios and Binance

will allow a focus on companies with greater

relevance and impact in the industry, making the

analysis more meaningful and representative of the

dynamics at play, particularly in the European

context. Moreover, for the heterogeneity of the

sample, Socios and Binance have been selected due

to the different case studies, respectively a more

diversified player, and a more focused player. From

the numerous teams associated with Socios, Juventus

FC, AC Milan and Lega Serie A were selected as

objects of study for this research. This selection was

based on a targeted strategy to examine very

heterogeneous cases in order to obtain a diverse

representation of the context of Fan Tokens in

football. Among the two European teams partnered

with Binance, FC Porto was selected over S.S. Lazio,

in order to introduce a foreign team into the set of

cases studied for research. This strategic decision

aimed to provide a comprehensive and diversified

The Role of Digital Artifacts in Fostering Ecosystem Creation

669

overview of interactions between the platform and

football teams, both domestically and internationally.

In addition, for AC Milan, Juventus FC, and FC

Porto, supporters were selected in order to understand

better the overall environment built around the Fan

Token. Instead, it did not select any sports team

supporters for Lega Serie A since this firm does not

own specific passionate sports team supporters due to

its nature of league for the highest Italian football

championship.

3.2 Data Collection

The data collection phase of the research utilized a

comprehensive strategy involving primary and

secondary sources to ensure data triangulation.

Secondary sources such as YouTube videos,

podcasts, whitepapers, and press releases provided

additional context, while primary sources included in-

depth semi-structured interviews with key

informants. The 10 interviews, divided into sections

based on the topics of the literature review, were

recorded, transcribed, and conducted in an interactive

competence (Langley et al., 2013; Collins, 2004)

involving technology providers, sports teams, and

sport team supporters, as shown in Table 1. The data

collection phase involves interviews with different

actors in the ecosystem, maintaining a neutral stance

to ensure objectivity. Informants are considered

knowledgeable agents, and the research aims at a

generalizing analysis, treating the case studies as

multiple experiments (Gioia et al., 2013). Following

Yin's approach (Yin, 1984), “analytical

generalization” integrates existing theories with

empirical evidence, contributing to a comprehensive

understanding of the impact and dynamics of the

digital artifact on the ecosystem. Such approach

allowed some flexibility for spontaneous exploration

of emerging themes. The richness of the dataset was

further enhanced by the inclusion of secondary data

from external documents, ensuring a robust

foundation for subsequent analysis.

Table 1: Overview of the case studies.

Sports teams Technology

providers

Sports team

supporters

Juventus FC

Socios

Sub

ect A

AC Milan Sub

ect B

a Serie A /

FC Porto Binance Subject C

3.3 Data Analysis

After the data collection phase, the research

continued with the analysis and interpretation of the

collected data, focused on the development of a

discussion based on the results. Following the “logic

of replication” (Eisenhardt and Graebner, 2007), each

case was treated as an independent experiment in both

internal and cross-case analyses. The focus was on

understanding the ecosystem mechanisms and

interactions facilitated by the digital artifact. After the

analysis of the individual cases, a cross-case

comparison identified similarities and differences,

answering the research question. The analysis made

use of coding, using an inductive Grounded Theory

methodology (Glaser and Strauss, 2017). An

inductive coding tree, incorporating constructed and

in vivo codes (Glaser and Strauss, 2017; Gioia et al.,

2013), reflected the language of the informants. The

iterative process consolidated the codes into first-

order concepts, followed by a second-order analysis

that aggregated the categories into overarching

themes. This process culminated in an empirical

model (Eisenhardt, 2023) which illustrates how the

digital artifact enables the creation of an ecosystem.

4 RESULTS

Following a comprehensive analysis of the results

derived from interviews conducted with key

stakeholders across the ecosystem, a systematic

process has been elucidated regarding the

development of Fan Tokens and their associated

Ecosystem by the firms involved. The process is

divided into two macro-phases: Phase 1 – Focal

Value Proposition Design, in which the main actors

involved in the ecosystem – Technology Provider

(e.g., Binance and Socios) and Sports Teams (e.g., FC

Porto, AC Milan, Juventus FC) – align with each

other, in terms of creation of connection of activities,

resources and competences, envisioning, and effort

on added value to the focal value proposition; Phase

2 – Ecosystem Alignment, in which there is the

introduction and activation of sports team supporters,

which from the use of Fan Tokens create value for the

technology provider (e.g., Binance and Socios) and

for sports teams (e.g., FC Porto, AC Milan, Juventus

FC). Moreover, there is the establishing of new

relationships with other actors (e.g., NFT Kings and

Lega Serie A) for the supply of resources and inputs

for the creation of complementary products to deliver

to the sports team supporters.

ICEIS 2024 - 26th International Conference on Enterprise Information Systems

670

4.1 Focal Value Proposition Design

The trigger point that fosters the creation of this type

of ecosystem is the Fan Token. Both the technology

providers interviewed (Binance and Socios) have

claimed that the Fan Token has been the starting point

for the creation of a new business. For example, the

Socios’ Partnership Manager claimed: “As far as the

token [Fan Token] is concerned, it was the simplest

and most easily applicable decision at the time

because it did not require a lot of effort”. Moreover,

the Socios’ CEO, during a YouTube interview

claimed: “So, we decided to create an ecosystem

based on blockchain in order to engage and monetize

sports fans all over the world”. In this phase the

technology providers identify the Fan Token as an

opportunity to create a new business unit (e.g.,

Binance) or a new digital startup from scratch (e.g.,

Socios). Then, they decide which technological

infrastructure to use, whether to exploit the existing

one (e.g., Binance) or to create a completely new one

(e.g., Socios). As explained by the Binance’s Head of

Marketing and BD: “There is not separate technical

department. The technicians in Binance are general,

then they do the tasks. As I said before, it's not that at

a technical setting level the fantoken part is different

from the Binance core, it's the same thing more

vertical on the fantoken…”.

During this phase, the technology provider starts

to establish collaborations with other actors in order

to co-create the Fan Token, as explained by Socios’

Partnership Manager: “Together with the

collaborative teams we propose a poll and when we

decided it and when the team gives me its approval

we will upload every time on the platform that poll

with all the experiences and rewards connected.”.

During the alignment between the technology

provider and the actors, there is the establishing of

interdependencies and of what a firm will give to the

other side and viceversa, as claimed by AC Milan’s

Associate Strategy Manager:“…what we give Socios

when we enter into a partnership with them is access

to a fanbase of hundreds of millions of fans around

the world… They have resources dedicated to Milan,

we have a resource dedicated to Socios, and then we

agree on what activities to do, when to do them...”

4.2 Ecosystem Alignment

In this phase, the overall ecosystem architecture is

almost complete thanks to the activation of sports

team supporters and the introduction of other actors

(e.g., Lega Serie A) which provide inputs that are still

relevant to the ecosystem, as explained by Lega Serie

A’s Partnership Manager: “To conclude, with Socios,

which is a very active partner and wants to activate a

lot of users to make them interact in their platform,

we did the activity related to matchball, so the NFC

ball.”. In this phase, there is the constitution of the

overall alignment structure on which actors interact

with each other to materialise a focal value

proposition.

Thanks to the activation of sports team supporters,

the sports teams can engage their fans thanks to the

interaction that the Fan Token allows, as explained by

the Juventus FC’s Head of Operations and Strategy:

“Then over time we saw that it works more what it

involves. In fact, as we did on 'design your own shirt'

which we then made, marketed and so on, you leave

the grids much more open, but the ingredients you go

for are controlled. So you leave space and you leave

freedom…”. In addition, they can reach fans all over

the world, who previously were unable to interact

with their favourite football team, as explained by AC

Milan’s Associate Strategy Manager: “Now we are

able to reach foreign fans such as fan from Turkey,

Indonesia, etc., that previously was impossible to

reach.”; and FC Porto’s Marketing Manager: “So, for

our fans across the world, we do think it will bring us

new fans and share our image throughout the

world…”.

Due to the possibility to interact with and to reach

more fans, both, sports teams, other actors,

technology providers, can capture value through the

use of Fan Tokens and other digital objects (e.g.,

Matchball NFC of Lega Serie A, or NFTs) as claimed

by Juventus FC’s Head of Operations and Strategy:

“On an economic level there was a huge benefit

because we did a very important revenue sharing

…So we benefit economically and in terms of value

from what? From the fans! That's something we like

anyway, it's a more direct channel…”. On the other

side, also sports team supporters are more engaged

due to the interaction possibility created by the Fan

Token, as claimed by Subject A: “I do believe that

fan tokens can open an incredible door to the sporting

world and not just to fans. As I said before, the ability

to access luxury areas … made me realise the power

of constant work and commitment in using tokens”.

5 DISCUSSION

In our rapidly evolving digital age, in which digital

artifacts are replacing physical objects (Kallinikos et

al., 2013; Ekbia, 2009), and the creation of

ecosystems (Adner, 2017; Jacobides et al., 2018) is

needed by established and new firms, it is important

The Role of Digital Artifacts in Fostering Ecosystem Creation

671

to shed light on the connection between these two

previously unconnected research streams. Moreover,

it is crucial to study this new phenomenon that is

revitalising the sports industry with some success

cases, which innovate their relationship with

customers (sports team supporters) and create new

revenue streams beside the typical ones in this

“traditional” industry. So, the topic is attractive not

only from a theoretical point of view but also from a

managerial and practical perspective.

From this study emerges that digital artifacts can

foster the creation of an ecosystems. Particularly, the

characteristics of digital artifacts (Kallinikos et al.,

2013) foster the creation of an ecosystem (Adner,

2017; Jacobides et al., 2018) thanks to their

connections with the sources of value creation (Amit

and Zott, 2001) and with value capture mechanisms

(Lepak et al., 2007). Each of these characteristics, and

their connections with the value creation and capture

mechanisms, are specific for each of the two phases

described in the previous section.

5.1 Theoretical Contribution

The empirical model derived sheds light on how the

intrinsic characteristics of digital artifacts (Kallinikos

et al., 2013) can foster the activation of value creation

and capture mechanisms (Amit and Zott, 2001; Lepak

et al., 2007) for each of the phases represented. In

other words, the characteristics of digital artifacts can

foster the creation of an ecosystem thanks to the

connection between these characteristics and the

value creation and capture mechanisms.

Proposition 1: The editability and openness

characteristics of digital artifacts foster the

activation of novelty and efficiency sources of value

creation during the creation of interdependencies

among actors for the design of the focal value

proposition.

The editability and openness characteristics of

digital artifacts (Kallinikos et al., 2013) are the

possibility to modify and update the elements of a

digital artifact and to be accessible and modifiable by

a program. Those characteristics can activate the

sources of value creation, novelty and efficiency

(Amit and Zott, 2001), during the establishment of

interdependencies among actors in the first phase

“Focal Value Proposition Design”. Thanks to the two

characteristics of digital artifacts (editability and

openness), the firms, involved in the creation of a

focal offer, can create value in a novel and efficient

way (digital artifact) through which they will conduct

transactions with the customers. Moreover, these

characteristics (editability and openness) allow the

design and arrangement of all the elements that

constitute the focal value proposition (digital artifact).

Editability and openness guarantee the increase of

efficiency and novelty in the following ways:

Decreasing transaction costs due to the higher speed

and facility through which the information will be

transmitted and increasing the efficiency of the

transactions thanks to the possibility to

instantaneously update and modify the focal offer for

the customers; Creation of a novel product that

enhances new way through which transactions will be

conducted and structured with previously

unconnected parties, eliminating inefficiencies and

creating new markets.

Proposition 2: The interactivity and

distributedness characteristics of digital artifacts

foster the activation of lock-in and complementarities

sources of value creation during the overall

ecosystem alignment among all the actors involved.

The interactivity and distributedness

characteristics of digital artifacts (Kallinikos et al.,

2013) are the possibility, for the customers, to interact

and activate functions embedded in the digital artifact

and the nature of being borderless and distributed in

a broader digital ecosystem. Those characteristics can

activate the sources of value creation, lock-in and

complementarities (Amit and Zott, 2001), during the

“Ecosystem Alignment” phase (Adner, 2017).

Thanks to these two characteristics of digital artifacts

(interactivity and distributedness), the firms that

operate in the ecosystem can create value for

customers through lock-in and complementarity

sources (Amit and Zott, 2001). The interactivity

characteristic fosters the increase of lock-in source of

value creation thanks to the possibility of creating

retention and loyalty in repeat transactions with

customers. Whereas the distributedness characteristic

fosters the increase of complementarity source of

value creation due to the opportunity to reach several

actors (e.g., customers, partners, etc.), without any

boundary obstacles, with whom the firms, already in

the ecosystem, can create a new network of partners

for the co-creation and supply of relevant inputs for

complementary products.

Proposition 3: The interactivity and

distributedness characteristics of digital artifacts

foster the capture and appropriation of value for the

firms involved in the ecosystem.

Thanks to the interaction of customers and the

possibility to access to complementary products

worldwide, the firms, in the ecosystem, can capture

value (Lepak et al., 2007) from the customers’ usage

of digital artifacts. Thanks to the utilisation of the

digital artifact by customers, the firms can capture

ICEIS 2024 - 26th International Conference on Enterprise Information Systems

672

different types of value to increase their revenues,

acquire new customers, and understand better their

audiences through data analysis.

To resume all of these propositions into the

proposition that answers the question on which this

study is grounded:

Proposition 4: The intrinsic characteristics of the

digital artifacts allow the creation of an ecosystem

thanks to their connections with the mechanisms of

value creation and capture for each of the phases

needed to create the respective ecosystem.

The representation of the empirical model

obtained is shown in Figure 1. This model represents

the connection between the intrinsic characteristics of

digital artifacts (Kallinikos et al., 2013), the phases

identified for the creation of an ecosystem (Adner,

2017), and the mechanisms of value creation and

capture (Amit and Zott, 2001, Lepak et al., 2007). In

this representation, it can be observed how the

different characteristics of digital artifacts foster

different value creation and capture mechanisms in

different ways along the two phases needed for the

creation of an ecosystem enabled by a digital artifact.

Moreover, in the Phase 1 there are just value creation

mechanisms, due to the need to design a novel and an

efficient way to deliver the digital artifact to the

customers; whereas, in the Phase 2 there is the

introduction of value capture mechanisms to capture

and appropriate value from customers’ interactions.

Figure 1: Empirical model representation.

6 CONCLUSION

This study investigated how digital artifact can foster

the creation of an ecosystem. Particularly, it has been

concluded that digital artifacts, thanks to their

intrinsic characteristics, can foster value creation and

capture mechanisms within an ecosystem. Moreover,

these characteristics are useful for each of the phases

needed to create an ecosystem. Besides this

discovery, this research enriches the Ecosystem

theory. The need to conduct this study stemmed from

the gap identified in the literature between previously

unconnected streams: ecosystem and digital artifact.

Thanks to this research, these two theories are now

matched, and can pave the way for future studies. It

was conducted an exploratory research using multiple

case studies on a sample of four cases identified with

six companies and three sports fans interviewed.

Sports business was chosen as industry of reference

thanks to its specific characteristics (Fonti et al.,

2023) and its big market value. In particular, the

application of Fan Tokens to the football industry (a

segment of sports industry) has been the field on

which this study is grounded to answer the research

question. The outcome of this work is an empirical

model that help to understand how to create an

ecosystem exploiting the characteristics of a digital

artifact. To conclude, this study led to new original

insights, but has some limitations due to the small

sample size and the subjectivity that occurs in

qualitative research. Indeed, Future research could

expand the scope to include other sports and regions.

Incorporating quantitative measures could strengthen

the validity of the proposed model and offer a more

comprehensive understanding of the impact of digital

artifacts in ecosystem creation.

REFERENCES

Adner, R. (2017). Ecosystem as Structure: An Actionable

Construct for Strategy. Journal of Management, 43(1),

39–58.

Amit, R., & Han, X. (2017). Value Creation through Novel

Resource Configurations in a Digitally Enabled World:

Novel Resource Configurations in a Digitally Enabled

World. Strategic Entrepreneurship Journal, 11(3), 228–

242.

Amit, R., & Zott, C. (2001). Value creation in E-business.

Strategic Management Journal, 22(6–7), 493–520.

Autio, E., Nambisan, S., Thomas, L. D. W., & Wright, M.

(2018). Digital affordances, spatial affordances, and the

genesis of entrepreneurial ecosystems: AUTIO ET AL.

Strategic Entrepreneurship Journal, 12(1), 72–95.

Bowman, C., & Ambrosini, V. (2000). Value Creation

Versus Value Capture: Towards a Coherent Definition

of Value in Strategy. British Journal of Management,

11(1), 1–15.

Cavallo, A., Ghezzi, A., & Rossi-Lamastra, C. (2021).

Small-medium enterprises and innovative startups in

entrepreneurial ecosystems: exploring an under-

The Role of Digital Artifacts in Fostering Ecosystem Creation

673

remarked relation. International Entrepreneurship and

Management Journal, 17, 1843-1866.

Cennamo, C., & Santalo, J. (2013). Platform competition:

Strategic trade‐offs in platform markets. Strategic

Management Journal, 34(11), 1331–1350.

Collins, H. (2004). Interactional expertise as a third kind of

knowledge. Phenomenology and the Cognitive

Sciences, 3(2), 125–143.

Eisenhardt, K.M. (1989). Building theories from case study

research. Academy of Management Review, Vol. 14

(4), pp. 532-550.

Eisenhardt, K. M. (2023). Building Theories from Case

Study Research. 127

Eisenhardt, K. M., & Graebner, M. E. (2007). Theory

Building From Cases: Opportunities And Challenges.

Academy of Management Journal, 50(1), 25–32.

Ekbia, H. R. (2009). Digital artifacts as quasi‐objects:

Qualification, mediation, and materiality. Journal of the

American Society for Information Science and

Technology, 60(12), 2554–2566.

Felch, V., & Sucky, E. (2022). In search of a consensus

definition of business ecosystems: A qualitative study.

Journal of Modelling in Management.

Fonti, F., Ross, J.-M., & Aversa, P. (2023). Using Sports

Data to Advance Management Research: A Review and

a Guide for Future Studies. Journal of Management,

49(1), 325–362.

Gartner, W. B., & Birley, S. (2002). Introduction to the

special issue on qualitative methods in entrepreneurship

research. Journal of Business Venturing, 17(5), 387–

395.

Ghezzi, A., Georgiades, M., Reichl, P., Le‐Sauze, N., Di

Cairano‐Gilfedder, C., & Managiaracina, R. (2013).

Generating innovative interconnection business models

for the future internet. info, 15(4), 43-68.

Ghezzi, A., Rangone, A., & Balocco, R. (2013).

Technology diffusion theory revisited: a regulation,

environment, strategy, technology model for

technology activation analysis of mobile ICT.

Technology Analysis & Strategic Management, 25(10),

1223-1249.

Ghezzi, A. (2020). How Entrepreneurs make sense of Lean

Startup Approaches: Business Models as cognitive

lenses to generate fast and frugal Heuristics.

Technological Forecasting and Social Change, 161,

120324.

Gioia, D. A., Corley, K. G., & Hamilton, A. L. (2013).

Seeking Qualitative Rigor in Inductive Research: Notes

on the Gioia Methodology. Organizational Research

Methods, 16(1), 15–31.

Glaser, B. G., & Strauss, A. L. (2017). The discovery of

grounded theory: Strategies for qualitative research.

Routledge.

Glaser, F. (2017). Pervasive Decentralisation of Digital

Infrastructures: A Framework for Blockchain enabled

System and Use Case Analysis. Hawaii International

Conference on System Sciences.

Jacobides, M. G., Cennamo, C., & Gawer, A. (2018).

Towards a theory of ecosystems. Strategic Management

Journal, 39(8), 2255–2276.

Kapoor, R. (2018). Ecosystems: Broadening the locus of

value creation. Journal of Organization Design, 7(1),

12.

Langley, A., Smallman, C., Tsoukas, H., & Van De Ven, A.

H. (2013). Process Studies of Change in Organization

and Management: Unveiling Temporality, Activity, and

Flow. Academy of Management Journal, 56(1), 1–13.

Lepak, D. P., Smith, K. G., & Taylor, M. S. (2007). Value

Creation and Value Capture: A Multilevel Perspective.

Academy of Management Review, 32(1), 180–194.

Nakamoto, S. (2008). Bitcoin: A Peer-to-Peer Electronic

Cash System.

Nambisan, S. (2017). Digital Entrepreneurship: Toward a

Digital Technology Perspective of Entrepreneurship.

Entrepreneurship Theory and Practice, 41(6), 1029–

1055.

Ojala, A., Fraccastoro, S., & Gabrielsson, M. (2023).

Characteristics of digital artifacts in international

endeavors of digital‐based INTERNATIONAL NEW

VENTURES. Global Strategy Journal, gsj.1483.

Osservatorio Blockchain & Distributed Ledger, (2022).

Glossario Blockchain.

https://www.blockchainrevolution.it/wp-

content/uploads/2021/05/Glossario-Blockchain.pdf

Sanasi, S., & Ghezzi, A. (2022). Pivots as strategic

responses to crises: Evidence from Italian companies

navigating Covid-19. Strategic Organization,

14761270221122933.

Sanasi, S., Manotti, J., & Ghezzi, A. (2021). Achieving

agility in high-reputation firms: Agile experimentation

revisited. IEEE Transactions on Engineering Manage-

ment, 69(6), 3529-3545.

The London School of Economics and Political Science,

Kallinikos, J., Aaltonen, A., Hanken School of

Economics, Marton, A., & Copenhagen Business

School. (2013). The Ambivalent Ontology of Digital

Artifacts. MIS Quarterly, 37(2), 357–370.

Yin, R. (1984). Case study research. Beverly Hills CA:

Sage.

Zittrain, J. 2008. The Future of the Internet and How to Stop

it, New Haven, CT: Yale University Press

Zott, C., & Amit, R. (2010). Business Model Design: An

Activity System Perspective. Long Range Planning,

43(2–3), 216–226.

ICEIS 2024 - 26th International Conference on Enterprise Information Systems

674