Business Intelligence and Innovation: An European Digital

Innovation Hub to Increase System Interaction and Value

Co-creation within and among Service Systems

Florian Maurer

Department Business Informatics, Vorarlberg University of Applied Sciences, Hochschulstraße 1, Dornbirn, Austria

Keywords: European Digital Innovation Hub, Business Intelligence & Innovation, Service Science, Service Systems.

Abstract: Due to limited resources (e.g. human, financial, knowledge, etc.), Small- and Medium sized Enterprises run

the risk to miss the Digital Transformation of its systems. Especially the manufacturing industry – a strategic

industry within the European Union that employs millions of workers and provide tremendous Gross

Domestic Product to the partner countries – faces technology changes and increased challenges for

implementation. As reaction to the challenges of the manufacturing industry, the European Union launched

the Factory of the Future programme and the European Digital Innovation Hub programme. Within this article

at hand, the literately and empirically endeavours towards the design and development of the Digital

Innovation Hub: Business Intelligence & Innovation within the region of Vorarlberg are presented. In doing

so, a narrative literature review about the academic discipline of Service Science – the guiding theory to

innovate service systems – and an empirical research about the motivation, status quo, vision and strategy

towards the Digital Transformation and Industry 4.0 paradigm of the manufacturing industry within the region

of the Federal State of Vorarlberg are presented.

1 INTRODUCTION

European Digital Innovation Hubs (EDIH) is a

program launched by the European Commission with

the objective to support European business, industry

and regions to succeed the Digital Transformation. It

is an instrument of the European Commission’s Smart

Specialization Strategy to digitise European

organizations (considered as service systems within

this article) as well as to boost investment through

strategic partnerships and networks within. The EDIH

program provides a broad range of services towards

digital challenges and organizational innovation that

support the design and development of heterogenous

Digital Innovation Hubs within the European regions.

Considered from an academic perspective, services

are about the service interaction and co-creation of

value within and between systems.

Service interaction and value co-creation are the

means of the academic discipline of Service Science,

which was chosen as one of the breakthrough ideas for

2005 by the Harvard Business Review (Chesbrough,

2005). Service Science combines organizational and

human understanding, related to Maglio & Spohrer

(2013), with technological understanding to categorize

and explain service systems: how they interact and

evolve to co-create value.

Services systems are the main abstraction of

Service Science. Service systems are both: providers

and clients of service and can be made up of multiple

independent service systems to interact and co-create

value. Within this article, a Digital Innovation Hub is

considered as a service system – mainly a provider of

services coordinated by a single service system (single

organization) and/or a group of service systems (two or

more organizations) with complementary knowledge

and expertise within the ongoing Digital

Transformation in the manufacturing industry.

Although Service Science introduces concepts to

foster service interaction and value co-creation

mechanisms, these concepts between and among

(vertical and horizontal) systems are less considered

within the empirical field of manufacturing

(organizations its internal and external business

stakeholders). Many systems still act as

organizational silos. As consequence, the systems

face an enormous gap of knowledge combined with

increased cost- and market pressure. Due to the

knowledge gap and the complexity of technological

innovations, opportunities, challenges and threats,

208

Maurer, F.

Business Intelligence and Innovation: An European Digital Innovation Hub to Increase System Interaction and Value Co-creation within and among Service Systems.

DOI: 10.5220/0010255602080217

In Proceedings of the 10th International Conference on Operations Research and Enterprise Systems (ICORES 2021), pages 208-217

ISBN: 978-989-758-485-5

service systems run at risk not to keep up the speed

with the Digital Transformation.

This article at hand presents the activities and

efforts to design and develop a Digital Innovation

Hub – a service hub called Business Intelligence &

Innovation for the long-term sustainability,

survivability and success of the manufacturing

industry within the Federal State of Vorarlberg

(Austria). The objective is to highlight the endeavours

about the first four steps about the European

Commission’s “Guide for a Digital Innovation Hub”

(Rissola & Sörvik, 2018): (1) define regional needs,

characteristics & specialisms, (2) develop a vision for

the regional DIH: vision for digital transformation,

(3) look at what is already available in region as basis

and (4) define the services that the DIH should offer.

In the center of this article is the research question

“how an European Innovation Hub within the region

of the Federal State of Vorarlberg for Business

Intelligence & Innovation can look like?

This article is structured among five sections.

Section one introduces the article at hand and presents

the research motivation as well as the research

question. Section two introduces the applied research

methods about the research into Service Science

literature, the European Digital Innovation Hub

initiative and the empirical field of the manufacturing

industry in the region of Vorarlberg. Section three

presents the results of the narratively literature review

into the academic field of Service Science and the

European Digital Innovation Hub “community”.

Section four presents the empirically investigation

into the needs, incl. the motivation, status quo, vision

and strategy, of the manufacturing industry within the

region of the Federal State of Vorarlberg towards an

European Digital Innovation Hub: Business

Intelligence & Innovation. Section five concludes the

article and provides an outlook of the future strategies

to design and develop the hub.

2 RESEARCH METHOD

Applied research method is case study research. Case

study research is a research method to focus on

contemporary events, especially when the boundaries

between the phenomenon explored and the context

may not clearly evident Yin (2014). The case study

research method fits best to bring together the

research endeavours: a) to narratively analyse the

theoretical base of the academic field of Service

Science and to narratively analyse the semi-

theoretical base of Digital Innovation Hubs with the

aim to build up of a sophisticated knowledge base

about the field of interest and b) to empirically

explore the needs of business and industry towards a

digital service hub for business intelligence and

innovation. Finally, case study research method

captures a broad repertoire of tools to combine

theoretically and empirically knowledge to formulate

and develop new theory and artifacts about the

investigated research question.

As depicted in figure 1, applied case study

research method is complementary to the design and

development guideline of the European Commission.

Case study research augments and extends the guide

by the integration of literature reviews to explore

what is already known within the field and to develop

more purposefully and tailored questions for

empirical research.

Figure 1: Structure of the research endeavour – a guide for

a Digital Innovation Hub (adapted from the European

Commission).

2.1 Analysis of Service Science

Literature and the European

Digital Innovation Hub Programme

The analysis of the Service Science literature bases on

a narrative literature review (Baumeister & Leary,

Business Intelligence and Innovation: An European Digital Innovation Hub to Increase System Interaction and Value Co-creation within and

among Service Systems

209

1997). In doing so, the article database of the Service

Science Worldwide Community for Service Science

Education and Research is sighted. This article

database consists of 306 scholarly articles, published

in international scientific journals and conferences.

The meta-data of all these articles were exported into

a Microsoft Excel table. In this table, data got

corrected (for example, the database hosts multiple

entries for one and the same author, e.g. Spohrer, J.

and Spohrer, J. C.), structured and codified for further

analysis. Codified data were uploaded into a

Microsoft Access SQL database, consisting of seven

tables. Five tables provide meta/master-data (codes

and information about authors, category, journal,

title, year). Remaining two tables provide operational

data (including information about articles and co-

authors). Afterwards, Standard Query Language

(SQL) select statements were executed to structurally

explore these meta-data. The use of SQL allows to

join and exclude data and enables to detect patterns

that are not possible with conventional and/or not

computer assisted methods.

The articles recommended by the Service Science

Worldwide Community are (co-) authored by 543

unique authors. Most frequent listed authors are

Spohrer, J. C. (31 publications), Maglio, P. P. (15),

Vargo, S. L. (11), Alter, S. and Polese, F. (10 each).

Taken together, 20,5 % or 63 unique articles out of

this database are published by these authors. These 63

articles are the basis for the narrative literature review

about the academic field of Service Science. In doing

the review about European Digital Innovation Hubs

programme, a more “pragmatically” method is

chosen: the narrative analysis of the European

Commission’s homepages and its uploaded

documents. The results of both reviews are presented

in section 3 – contextual embedment: digital

innovation hubs as service systems.

2.2 Empirically Research into the

Manufacturing Industry within the

Region of Vorarlberg

The investigation into the manufacturing industry

within the region of Vorarlberg bases on a smart

digital questionnaire accompanied with oral expert

interviews. Experts, in this sense, are the managers

and organizational decision makers from randomly

chose organization within the field of manufacturing

and accompanied sectors. For example, 14,81% of

interviewees state that their organizations are active

in the sector “computer programming, consultancy

and related activities” (NACE). Following sectors in

which integrated organizations are active are

“machinery and equipment” (11,11%), “computer,

electronic and optical products” (8,64%), “metal

products, except machinery” (8,64%), “engineering

and architectural activities” (7,41%) and “plastics

materials” (7,41%).

The conduction of the empirical research was

characterized by two phases: in the first phase, a

smart digital questionnaire was we distributed to

organizations within the Federal State of Vorarlberg

and its neighbouring regions in Austria, Germany,

Liechtenstein and Switzerland. However, due to low

responses, in the second phase, bi-lateral interviews

about business needs, strategies and technologies

about the Digital Transformation with managers and

decision makers (primarily within the region of

Vorarlberg) were organized. An interview lasted 35-

45 minutes in average.

3 CONTEXTUAL EMBEDMENT:

DIGITAL INNOVATION HUBS

AS SERVICE SYSTEMS

The academic discipline of Service Science act as

guiding scientific theory of the research endeavours

within this article at hand. In the centre of this

Information System related theory are service

systems. Service systems are considered as socio-

technical systems (Böhmann et al., 2014) and thus

service systems “dynamic value cocreation

configurations of resources (people, technology,

organizations, and shared information)” (Maglio &

Spohrer (2007); including language, laws, measures,

methods). Service systems are both: providers and

clients of service that are connected by value

propositions in service networks of value-creating

systems. Value creation in service systems is enabled

via the configuration of actors and resources

(Böhmann et al., 2014) as well as the service

interaction between. Service interaction are joint

activities that depends on increased communication

between the service systems (Maglio & Spohrer,

2013) to build up sustainable value propositions.

Service interactions and value propositions are “not

only data and physical components, but also layers of

knowledge, communication channels and networked

actors” (Böhmann et al., 2014). Service interactions

and value propositions coordinate and motivate

resource access across service system entities

(Maglio & Spohrer, 2013).

Service systems are everywhere (Parbs et al.,

2016): the smallest service system, related to Maglio

& Spohrer (2007), “centres on an individual as he or

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she interacts with others, and the largest service system

comprise the global economy […]”. Digital Innovation

Hubs, in the sense of this article, are a bundle of service

systems – (vertical and horizontal) organizations and

other stakeholders from business and industry – that

interact, collaborate, cooperate and co-create to gain

services: new knowledge and expertise.

Within the theory of Service Science, the Service-

Dominant Logic, SSMED, Viable System Approach

and the Work System Theory could be identified. As

Maurer (2020) summarizes, Service-dominant logic

increases value co-creation with and among service

system stakeholders: clients, providers, suppliers, etc.

Service-Dominant Logic aims to improve the potential

to launch services and service innovation and is part of

Marketing Theory. SSMED – an abbreviation for

Service Science, Management, Engineering and

Design – focuses on increased services, service

systems and its service interaction mechanisms by

continuous service system development, (re-) design

and (re-) engineering. It is about innovation and

evolution by use of knowledge gained from the service

systems ecologies. Viable system approach focuses on

the service system's viability, sustainability and

survivability through dynamic stakeholder interaction

and value co-creation mechanisms. It is closely related

to Service-Dominant Logic. Work system theory, a

core-intervention of Alter (2013), focus on the

resources base of service systems to design and

develop valuable, rare, inimitable and non-

substitutable (VRIN) resources. As depicted in figure

2, in the centre of the Work System Theory is the Work

System Framework – a framework and guide to

execute service, service system and service ecosystem

renewal and innovation. Central idea of the Work

System Theory is to support service system thinking.

Service systems are made of nine resources, best

presented in the Work System Framework (cf. figure

2).

Figure 2: Work system framework.

The Work System Theory (main protagonist:

Seven Alter, e.g. Alter (2013)) is a business process

approach and focuses on service systems and its

participants rather than on (information and

communication) technologies. The Work System

Theory and its Work System Framework are relevant

for system analysis: analyzing, describing, designing,

or evaluation of service systems (and its

improvement) – towards both: planned and

unplanned changes within and among service systems

(internal & external). The Work System Theory

supports system participants to develop new services

and service systems as well as to improve and

innovate the existing systems towards organizational

challenges, opportunities and trends.

In the centre of SSMED are to launch productive

service interactions, increase labour productivity and

innovation measuring productivity. In accordance to

Spohrer et al. (2010), measures to increase service

interaction and productivity (such as: efficiency,

effectiveness, performance and sustainability as well

as renewal and innovation) include the (1)

identification of all the stakeholder system entities in

a network under study (e.g. a network ecology

analysis), (2) examination of existing relationships

and value cocreation mechanisms with the target to

understand the challenges and opportunities the

service system stakeholders have identified, (3)

improve existing value cocreation mechanisms (that

may include the freeing up of resources from existing

service system entities and its redistribution), (4)

creation of new service system entities to address

them (if challenges and opportunities remain)

(Spohrer et al., 2010). As depicted in table 1, SSMED

makes use of four propositions that are:

Table 1: SSMED’s four propositions.

Propositions Source

1 Service system entities

dynamically configure

(transform) people,

technology, organizations

and shared information

Spohrer et al.

(2012);

Maglio &

Spohrer

(2013)

Service system entities

compute and calculate value

from multiple stakeholder

perspectives

Spohrer et al.

(2012);

Maglio &

Spohrer

(2013)

Service system entities

reconfigure access rights to

resources by mutually agreed

to value propositions resp.

the access rights associated

with entity resources are

reconfigured by mutually

agreed-to value propositions

Spohrer et al.

(2012);

Maglio &

Spohrer

(2013)

Business Intelligence and Innovation: An European Digital Innovation Hub to Increase System Interaction and Value Co-creation within and

among Service Systems

211

Table 1: SSMED’s four propositions (cont.).

Propositions Source

Service system entities

compute and coordinate

actions with others through

symbolic processes of

valuing and symbolic

processes of communicating

Maglio &

Spohrer

(2013)

However, the European Digital Innovation Hub is a

research, innovation and investment programme of

the European Commission. It can be considered as the

supplement of the “Factory of the Future” (FoF;

European Factories of the Future Research

Association (2016)) programme, which was launched

firstly in 2008 with the aim to develop a sustainable

and competitive EU manufacturing. In first iteration,

this initiative included the development of high added

value manufacturing technologies, which

additionally are clean, highly performing,

environmentally friendly and social sustainable (e.g.

European Commission; European Commission

(Multi-Annual Roadmap). However, FoF is a

narrative and under its roof, this term describes a

factory as a fully integrated plant, incl. the use and

application of smart cyber-physical systems.

Especially in the German speaking countries Industry

4.0 approach is in close relation to FoF. It interlinks

human resources, technology and information equally

to establish more performant and more efficient but

also more intelligent and self-managing service

systems in overall value co-creation chains.

Related to the Draft Working Programme of the

European Commission (2019), EDIH’s are one-stop

shops that help companies become more competitive

with regard to their business/production processes,

products or services using digital technologies, by

providing access to technical expertise and

experimentation. Organizations should be able to

“test before invest”. Further services assigned to

EDIH’s are, for example, provision of innovation

services, incl. to better organise the innovation

support system in the region, start-up support (assist

start-ups who are based on digital technologies) and

innovation in more established companies (support

more mature companies with the development of new

products and services that are not fully exploiting the

digital opportunities yet), matchmaking and

connection of actors and stakeholders, financing

advice and training and skills development that are

needed for a successful Digital Transformation of

business, industry and/or the region. Actors and

stakeholders of Digital Innovation Hubs are, for

example, RTOs, universities, technological

companies, governmental institutions, etc. (DIH,

Smart Specialisation Platform, 2020) and their main

service is to support the Digital Transformation of

business and industry and the regional ecosystem

(European Commission, 2016). It is a concept that

builds upon previous experiences and organisations

to digitalize business, industry and the regional

ecosystem.

4 INDUSTRY NEEDS & VISION

TOWARDS THE DIGITAL

TRANSFORMATION

As highlighted in theory of Service Science, industry

experiences a strong shift form Goods-Dominant

Logic to the Service-Dominant Logic. This is true too

for the investigated field of manufacturing industry

within the Federal State of Vorarlberg: old processes

and services get renewed, changed and adopted by

new, technology-based processes and services to

increase service interaction and value co-creation.

The Digital Transformation, as observed in the field,

additionally impacts and challenges the human

resources and the requirements into them. A

continuous qualification and upskilling of their

competences are needed. The following chapters

present the motivation for the Digital Transformation

within investigated organizations, the status quo

about the use of Industry 4.0 technology, a future

prospection and the strategy towards this future.

Anticipated, the removal of existing products because

of the Digital Transformation is less expected by the

interviewees – manufacturing get incentivized and

augmented with services.

4.1 Motivation for the Digital

Transformation

The general motivation for the Digital

Transformation of managers within interviewed

organizations is all about internal and external

innovation (renewal, adaption and change of the

manufacturing systems, its underlying technologies,

processes and services) at almost all organizational

levels. Core efforts are the implementation of new

technologies, processes and services within their

manufacturing systems. In doing so, most

interviewed managers expect a reduction of material

consumption within their organization. Further

expectations of interviewed managers are the

adaption, design and development of new products

and services, increased managing quality and

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organizational robustness as well as changed business

models. Additionally, by the Digital Transformation,

managers expect to access to new markets and

business areas as well as to attract and gain new

customers.

The observed examples within the empirical field are

manifold. For example, the managing director of an

involved company specialized in injection moulding

foster the motivation for the Digital Transformation

of its employees by internal value services: increased

transparency of manufacturing processes by use of a

manufacturing info-board (c.f. figure 3). A further

company equips its service employees with Virtual

Reality Glasses to easily download construction plans

during services processes at the customer.

Additionally, by use of the VR Glasses, the service

employees are able to get connected with the

headquarter and to receive real-time support and

advices.

Figure 3: Organizational transparency by use of a

manufacturing info-board.

4.2 Status Quo: Availability of

Emergent Manufacturing

Technologies in Industry and Its

Usage

In analysing the status quo, interviewees had to

evaluate applied Industry 4.0 technologies on a Likert

Scale – ranging from 1 (= no usage at all) until 4 (=

very intensive use). Based on the research of

Schumacher et al. (2016 & 2019), these technologies

are: autonomous robots, simulation, system

integration, (industrial) internet of things,

cybersecurity, cloud technologies, additive

manufacturing, augmented reality and big data &

analytics.

As depicted in table 2 & 3, from a “positive”

perspective, the technologies simulation, system

integration, (industrial) internet of things,

cybersecurity, cloud technologies, additive

manufacturing and big data & analysis passed the

50% hurdle (summary of the results: few usage, good

usage & intense usage, c.f. table 3). This determines

that most of the interviews affirm the use of these

technologies. From a “negative” perspective, it seems

that the technologies autonomous robots and

augmented reality did not gain interest and did not

enter the field of manufacturing yet. For example, any

of the interviews stated that these technologies

experience an intensive use in their organization. The

results about the “positive” and “negative”

perspective – the usage and no usage of Industry 4.0

technologies in investigated organizations – are

depicted in table 2.

Table 2: Usage of manufacturing technologies.

Technology No usage Usage

Autonomous robots 58,06% 41,94%

Simulation 35,48% 64,52%

System integration 41,94% 58,06%

(Industrial) IoT 48,39% 51,61%

Cybersecurity 35,48% 64,52%

Cloud technologies 29,03% 70,97%

Additive

manufacturing

48,39% 51,61%

Augmented reality 83,87% 16,13%

Big data & analysis 29.03% 70,97%

Focusing on the “positive” perspective (usage of

manufacturing technologies), as depicted in table 3,

an intense usage could be identified in cybersecurity,

big data & analysis, simulation and (industrial)

Internet of Things.

Table 3: Detailed visualization of the usage of

manufacturing technologies.

Usage

Technology Few Good Intense

Autonomous

robots

22,58% 19,35%

Simulation 35,48% 19,35% 9,68%

System

integration

29,03% 29,03%

(Industrial) IoT 29,03% 16,13% 6,45%

Cybersecurity 29,03% 22,58% 12,90%

Cloud

technologies

25,81% 38,71% 6,45%

Additive

manufacturing

35,48% 16,13%

Augmented

reality

12,90% 3,23%

Big data &

analysis

45,16% 16,13% 9,68%

Business Intelligence and Innovation: An European Digital Innovation Hub to Increase System Interaction and Value Co-creation within and

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213

Examples of the use of these technologies are, for

example, the integration of external cloud platforms

as Dropbox, SharePoint, etc., server decentralization,

outsourcing of IT processes and IT service-oriented

architectures. Major to the managers is to ‘flexibilize’

the organization and make it more agile to

stakeholder requirements. But also, a few

interviewees stated that they are working on their own

cloud solutions that face increased security measures.

The cloud technology, with respect to the academic

field of Service Science as well as the interviews

highlighted, is to boost cooperation, collaboration and

to increase of organizational transparency. It enables

to increase the interaction and value co-creation

among system members on the digital way (e.g.

exchange of documents, edition of documents at the

same time, etc.). Big data & analysis technology, as

observed in the interviews, is in close connection to

simulation. The manufacturing processes and

products, for example, are augmented with

(industrial) internet of things technology: sensors,

chips, etc. These IoT’s are the basis for big data in

manufacturing and its structured analysis at

operational level (e.g. internal cycling times, speed,

maintenance, etc.– as depicted in figure 3). At

strategic level, the organizational supply chains get

observed, forecasted and simulated. The make use of

these (interconnected) big data and its analysis

enables, as the interviewees stated, to identify

patterns and structures for latter decision making. The

use of simulation enables to design and develop

scenarios and incidents, decision making, software

tests, product development and process simulation.

The “organizational shut-down” of a well-known

organization within the region due to a cyber-attack

sits deep within the interviewees’ minds. Probably for

this and globally observed reasons, the technology

cybersecurity is the most applied technology within .

As observed, the protection of IT hard- and software

is at high level and captures, for example,

technological standards, legal protection for digital

products and services, rules for employment in digital

work environment, safety, security & resilience and

control, reliability & robustness.

4.3 Vision for the Digital

Transformation: Future

Prospection

Related to a future estimation of the use of emergent

manufacturing technologies that drive the Digital

Transformation in systems, the interviewees

highlighted a tremendous shift. As observed, all

surveyed manufacturing technologies are on the

agendas of the managers and a more intensive use in

the future is expected by them in their organization.

The comparison between present use, the future

application and the change is depicted in table 4. For

example, 87,10% of the interviewees (instead of

70,97% (as in the status quo section)) planning to

make use of cloud technologies in the future. This is

a shift of +16,13%. The technologies system

integration, (industrial) internet of things and

augmented reality, as the interviews highlight, will

experience the most significant change: +25,81%

each. Nevertheless, more than the half of the

interviewees (58,06%) showed a negative attitude

towards augmented reality.

Table 4: Prospected shift of the usage of manufacturing

technologies.

Prospected shift

Technology Present Future Change

Autonomous

robots

41,94% 67,74% +25,80%

Simulation 64,52% 67,74% +3,22%

System

integration

58,06% 83,87% +25,81%

(Industrial) IoT 51,61% 77,42% +25,81%

Cybersecurity 64,52% 77,42% +12,90%

Cloud

technologies

70,97% 87,10% +16,13%

Additive

manufacturing

51,61% 61,29% +9,68%

Augmented

reality

16,13% 41,94% +25,81%

Big data &

analysis

70,97% 80,65% +9,68%

As observed, an intense usage of manufacturing

technologies is to be expected in cybersecurity (ten

interviewees highlighted the intense usage of this

technology, cloud technologies (7), big data &

analytics and simulation (6 each). The technology

system integration will be used to increase the

system’s collaboration from human-to-human,

human-to-machine and machine-to-human. Applied

fields are manifold and capture, for example,

interfaces (to internal/external ERP systems, MES

systems, CAx systems, etc.), machines and sensors

(to collect noise and additional data about the product

and its cycle times) and -partly- robots and

autonomous driving systems. Centre to the managers

are increased service interaction: automated

information exchange, customer and supplier

integration and value co-creation in product/service

development, utilization of customer and supplier

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related data and IT-collaboration for product

development.

4.4 Strategies for the Digital

Transformation

As observed within the surveyed organizations, the

most promising strategy for the successful

implementation of Industry 4.0 technologies and the

continuous cope with the Digital Transformation are

the developments of an Innovation Strategy and an

Industry 4.0 Strategy. Almost 81% resp. 59% of the

interviewees are positive towards the Innovation

Strategy document and the Industry 4.0 Strategy

document. A further important part, as observed, is

the communication of these documents towards the

system participants (e.g. managers, decision makers,

employees, etc.) and the system stakeholders.

Nevertheless, the results out of the survey paints an

ambiguous picture about the strategy for the Digital

Transformation and the application of Industry 4.0

technologies. At the one hand, the willingness of

mangers to pro-actively act manage and master the

Digital Transformation within their organization is

high. At the other hand, the most important resources’

objectives to master the Digital Transformation are

not captured sufficiently yet: less than 42% of the

interviews confirmed that the employees’ objectives

are captured within their roadmap and innovation

strategy towards the Digital Transformation. Related

to the academic discipline of Service Science, it is a

major pitfall of design, development and engineering

(of products, services, processes, technologies, etc.)

since value is always co-created.

Further possible sources of danger are the

organizations central coordination of the activities

and efforts of the Digital Transformation, its

communication to become digitalized and the risk

assessment. For example, only the half of interviewed

managers stated that their endeavours of their Digital

Transformation is centralized. This disables the

capitalization of implemented technologies and

decreases the organizations’ ability to design, develop

and (re-) engineer its processes and services

accordingly as well as to disseminate the adaptions,

changes and innovation to the system stakeholders

(employees, suppliers, customers, etc.). Although the

mangers are aware about the ongoing Digital

Transformation, more than the half of interviewed

managers stated that they did not make an assessment

about future technologies. Currently, it seems that

digital transformation in companies is based on a trial

and error process instead of a structured innovation

process.

5 CONTRIBUTIONS & FUTURE

OUTLOOK

Digital Transformation and Industry 4.0 force

proactive digital adaption, change and innovation of

the system, its infrastructure, resources, processes,

products and services. Considered from a service

perspective – the perspective of the academic field of

Service Science, Digital Transformation and Industry

4.0 not only is about the implementation of new

technology within the organization but also its

management, engineering and design. However, due

to limited resources (e.g. human, financial,

knowledge, etc.), especially Small- and Medium

sized Enterprises run the risk to miss the successful

innovation of its systems.

5.1 Contributions to Research and the

Empirical Field of Manufacturing

From an academic perspective, this article at hand

introduces the academic field of Service Science as

engineering guide to response to and to cope with the

Digital Transformation and Industry 4.0 in the

manufacturing industry. Service Science supports to

increase service system stakeholders abilities to think

systems in services and thus to better design, develop

and (re-) engineer service systems. Especially the

SSMED and the Work System Theory provides

guidelines and frameworks to adapt to, change and

innovate within the Digital Transformation and

Industry 4.0 paradigm. From an empirical

perspective, this paper introduces the European

Commission’s Digital Innovation Hub programme.

This programme is meant to support the European

manufacturing business and industry to cope the

Digital Transformation and Industry 4.0. Centre to the

European Digital Innovation Hub programme is to

establish Digital Innovation Hubs that boost

innovation within business, industry and the

European regions.

Both perspectives, Service Science (incl. SSMED and

Work System Theory) and the European Digital

Innovation Hub programme are key to establish the

Business Intelligence & Innovation Hub within the

region of Vorarlberg.

5.2 Future Outlook

After the analysis and evaluation of the motivation,

status quo, vision and strategies within the empirical

field, as demanded by the European Digital

Innovation Hub programme, next step is to define the

Business Intelligence and Innovation: An European Digital Innovation Hub to Increase System Interaction and Value Co-creation within and

among Service Systems

215

services that the intended Business Intelligence &

Innovation Hub should offer. In doing so, it is

important to analyse the resources, infrastructures,

existing networks, etc. of the region to identify, for

example, the relevant stakeholders within the field of

manufacturing. Target then is to conceptualize the

integration of identified stakeholders into the design

and development processes for later dynamically

configuration and transformation of people/human

resources, technologies, organizations (incl. internal

and external stakeholders) and shared information for

a sustainable, survivable and profitable

manufacturing industry within the region. At the one

hand, it is centre to design and develop services that

meet the needs, vision and strategies of the

manufacturing industry. At the other hand, it is

important to align with the overall strategy of the

region. Thus, the services of the Business Intelligence

& Innovation Hub not only re-combines

infrastructure, technologies, products, services and

production factors – it enables new alignments in the

organizational culture and its management and

contributes to the Smart Specialization Strategy

“Intelligent Production” of the Government of the

Federal State of Vorarlberg.

ACKNOWLEDGEMENTS

This article at hand was made possible by the

financial support of Interreg Central Europe research

project “4Steps” (Towards the application of Industry

4.0 in SMEs; project number: CE1492).

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