The Nature of Digital Innovation and

What Can Be Learned for Information Systems Management

Stefanie Kaczmarek

, Martin Benedict

and Marcel Susky

Chair of Wirtschaftsinformatik, esp. Systems Development, Technische Universität Dresden, Dresden, Germany

Keywords: Digital Innovation, Information Systems Management, Systematic Literature Review, Quantitative/

Qualitative Analysis.

Abstract: In all spheres of life, the ongoing digital transformation has led to an increasing variety of definitions, types,

and characteristics of digital innovation. However, the diversity of terminology regarding digital innovation

may cause confusion about the general concepts in this context. Therefore, the objective of this study is to

provide a descriptive insight into the nature of digital innovation. Our paper shows how digital innovation has

altered since its emergence in the field of information systems re-search. This change of understanding has

an impact on the design of information systems. Following a systematic literature review, a quantitative and

qualitative analysis of the identified vocabulary was conducted to gain types and characteristics of digital

innovation. Based on these characteristics, we describe how digital innovation influences information systems.

We focus on hospital information systems as a case example from the healthcare sector.

1 INTRODUCTION

The use of novel digital technologies, such as virtual

reality, cloud computing, and artificial intelligence,

leads to changes in business models, internal com-

pany processes, products, and services. For compa-

nies and their customers, new opportunities in infor-

mation acquisition, communication and consumption

arise through digital technology (Rachinger et al.,

2018). These changes by novel digital technology are

named as Digital Innovation (DI). Not only tradi-

tional IT companies such as Apple or Google are in-

volved in the development of DI, but also companies

in finance, mobility and other industries (Fichman,

Dos Santos & Zheng, 2014). Well-known success sto-

ries for business models based on DI include Airbnb,

Uber, and Spotify, which conduct their business ac-

tivities via digital peer-to-peer platforms. While

SAP’s Simple Finance Add-on is a highly automated

and standardized solution for digitizing business pro-

cesses, Fitbit and Amazon’s Kindle are examples of

digital product innovations (de Reuver et al., 2018).

The term “Digital Innovation” was coined by

Yoo, Henfridsson & Lyytinen (2010) and refers to the

possibility of developing new products by combining

https://orcid.org/0000-0001-8204-7010

https://orcid.org/0000-0003-4262-9029

physical components with digital technologies. Since

digitalization offers the opportunity to fundamentally

change former product experiences, DI are an essen-

tial step and foundation for competitive advantage for

companies (Yoo, 2010). It is undisputed that DI plays

a central role in the context of companies and in re-

search on business information systems too (Hevner

et al., 2019). However, as several different defini-

tions, types, and characteristics of DI have prevailed,

there is still confusion about the nature of DI and what

DI means in the context of specific information sys-

tems. This diversity needs to be considered when aim-

ing to improve existing information systems through

DI. Different objectives may arise from different un-

derstandings of DI in different sectors of the econ-

omy.

For example, the healthcare domain is essential

for every society and economy, but the potential for

integrating DI into this domain has not been fully ex-

ploited yet (Jung & Padman, 2015). Especially hospi-

tals, as major medical care providers, are affected by

DI. However, it is less researched which aspects of DI

may improve the success and utility of information

systems in hospitals.

Addressing this gap, this paper analyses the na-

ture and understanding of DI in information systems

Kaczmarek, S., Benedict, M. and Susky, M.

The Nature of Digital Innovation and What Can Be Learned for Information Systems Management.

DOI: 10.5220/0009311607870797

In Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2020) - Volume 5: HEALTHINF, pages 787-797

ISBN: 978-989-758-398-8; ISSN: 2184-4305

787

research. Based on this analysis, the paper derives im-

plications for the management of Information Sys-

tems (IS) in hospitals. Consequently, the paper ad-

dresses the following research question:

RQ: How have Digital Innovations changed in

the course of digital transformation and

what implications can be derived for the

management of Information Systems in hos-

pitals?

The remainder of this paper is structured as fol-

lows. After this introductory chapter, the research

method used for the study is explained in chapter 2.

The results of the systematic literature review are pre-

sented in chapter 3 and discussed in chapter 4. The

paper concludes with a conclusion and gives an out-

look on further research needs.

2 METHOD

2.1 Literature Analysis and Review

In order to gain a comprehensive understanding of DI,

we conduct a systematic literature review following

Fettke (2006) and Cooper & Hedges (1994). We ana-

lyze the existing literature using a quantitative de-

scription of the literature and a qualitative analysis of

the full texts to conceptualize the understanding of

DI. The knowledge gained from the quantitative and

qualitative data analysis contributes both to a broader

conceptualization of DI and to the provision of impli-

cations for theory and practice in the management of

HIS. The quantitative analysis supports understanding

of the context, in which DI is used and conceptualized.

Therefore, we analyze the meta-data of the papers.

For a broader overview of papers, we searched in

the electronic databases Scopus and Web of Science.

These interdisciplinary databases were selected be-

cause DI is a phenomenon that can be found in all sci-

entific disciplines. Hence, the search term “digital in-

novation“ was used in title, abstract and keywords.

The search carried out in July 2019 yielded in a total

of 677 (Scopus) and 318 (Web of Science) hits. After

the removal of duplicates and incomplete sources,

792 publications remain for further consideration.

The aim was to analyze the most important publica

The area Science covers Mathematics; Biology; Psychol-

ogy; Physics and Chemistry. Humanities and Social Sci-

ences consists of Social Sciences (SS); Education, Linguis-

tics; Cultural Studies, Arts and Humanities (CSAH) as well

as Law and Public Administration. Computer Science (CS);

Engineering (E) and Mechanical Science belong to the su-

tions regarding DI. Therefore, we sorted and recorded

the literature sources according to their citation fre-

quency. Publications cited at least 50 times were in-

cluded in a detailed qualitative analysis. In this case,

50 was chosen as the reference value, since the cita-

tion frequency of subsequent publications was rapidly

decreasing. After examining the full-text of the most

frequently cited publications, two of them were ex-

cluded. Thus, 12 publications remain (see Table 1, up-

per part). To expand the data basis for analysis, further

papers were searched from the resulting list of the da-

tabase search. Six additional publications (see Table 1,

lower part) were identified. These were selected by

their title. In the backward search, we selected papers

that directly treat digital innovation in the title.

Table 1 shows the publication year and the num-

ber of citations of the twelve most frequently cited

publications in the field of DI. The number of cita-

tions of publications from the reference list search re-

fers to the citation frequency of Scopus. In addition,

the subject areas to which the publications can be as-

signed are presented. According to the two selected

databases, it is possible to search/classify document

results by subject area. Since both databases use dif-

ferent categories in relation to the subject areas, a new

classification has been created for reasons of compa-

rability. For this purpose, five superordinate areas –

Science, Humanities and Social Sciences, Engineer-

ing Sciences, Civil and Environmental Engineering,

Medicine – were identified, to which 17 newly cre-

ated classes of subject areas can be assigned.

The next step is to evaluate the identified litera-

ture, i.e. the check for relevance, the processing and

systematization, as well as the analysis and interpre-

tation of the results against the background of the

problem (Fettke, 2006). In the full-text analysis, we

analyzed the definitions of DI and screened the papers

for DI characteristics.

2.2 Case Study

The characteristics of DI are used to systematize im-

plications for Hospital Information Systems argumen-

tatively. As a case study, we selected the healthcare

sector because this sector is faced with a lot of barriers

and issues regarding the implementation of digital

technology (Alkraiji et al., 2013; Lluch, 2011).

perordinate area Engineering Sciences. To Civil and Envi-

ronmental Engineering count Architecture, Civil Engineer-

ing; Transportation and Traffic Sciences; Business, Man-

agement and Economics and also Environmental Sciences

(ES). The fifth area includes Medicine.

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As a specific digital innovation, we selected the

implementation of the Health Level Seven Fast

Healthcare Interoperability Resources (HL7 FHIR)

standard in Hospital Information System (HIS). A

HIS is a comprehensive and integrated subsystem of

a hospital that includes information on administrative,

financial and clinical aspects. The HIS serves to map

all information acquisition, information processing

and information storage processes resulting from the

interaction between human and machine actors. It

supports the people involved in clinical everyday life

in carrying out daily work processes, such as planning

bed occupancy, optimal utilization of operating

rooms or diagnosis, in all functional areas of the hos-

pital (Khalifa & Alswailem, 2015; Moghaddasi et al.,

2018; Moser, 2013; Winter et al., 2011). The goal of

a HIS is to contribute to adequate patient care that

considers the concept of cost-effectiveness on the one

hand and satisfies legal framework conditions on the

other hand. The HIS has the task of providing the

right information about patients to the right recipient

at the right time, at the right place, in the required

quantity and quality. The automated subsystems of

HIS are referred to as Hospital Application Systems

(HAS). Examples of HAS are the Clinical Documen-

tation and Management System (CDMS), the Labor-

atory Information System as well as the Picture Ar-

chiving and Communication System (Haux, Winter,

Ammenwerth & Brigl, 2013; Moser, 2013). We se-

lected HIS because they are important for the imple-

mentation of DI in the healthcare sector (Scheplitz et

al., 2019). They are a focal point of data management

in integrated care settings and store versatile data

about the patient’s treatment chain.

Besides the installation of new digital devices, the

integration of DI into HIS is also the implementation

of software or the reconfiguration of existing HAS

and the integration of them. For example, the imple-

mentation of a generic and reusable Application Pro-

gramming Interface (API) for third party applications

can be treated as DI. The HL7 FHIR standard pro-

vides such an approach (Bender & Sartipi, 2013). It

describes a generic resource-oriented representation

of clinical data structures. Like a building block sys-

tem, these resources can be combined for different

use cases. A CDMS could publish such resources and

another HAS can use them for different use cases.

3 RESULTS

3.1 Quantitative Analysis

A total of 792 publications with regard to time per-

spective, the geographical perspective, and the sub-

ject area were examined in the course of the quantita-

tive analysis. For this purpose, data sets from Scopus

and Web of Science were recorded in spreadsheets.

Afterward, the data sets were graphically processed

using diagrams.

Table 1: Digital Innovation papers and their publication year, number of citations, country, subject area.

No. Reference year # citations Subject area

1 Yoo, Henfridsson & Lyytinen 2010 545 CS, SS, BME

2 Yoo, Boland, Lyytinen & Majchrzak 2012 428 BME

3 Lusch & Nambisan 2015 240 CS, CSAH, BME

4 Boudreau 2012 198 BME

5 Fichman, Dos Santos & Zheng 2014 169 CS, BME

6 Y. Yoo 2013 103 CS

7 Barrett, Oborn, Orlikowski & Yates 2012 92 BME

8 Nylén & Holmström 2015 84 BME

9 Nambisan & Lyytinen 2017 66 CS, CSAH, BME

10 Nambisan 2013 65 CS, SCAH, BME

11 Svahn, Mathiassen & Lindgren 2017 51 CS, BME

12 de Reuver, Sørensen & Basole 2018 50 CS, SS, BME

13 Lee & Berente, 2012 38 BME

14 Huang, Henfridsson, Liu & Newell 2017 36 CS, BME

15 Henfridsson, Mathiassen & Svahn 2009 27 CS

16 Sørensen & Landau 2015 23 SC, BME

17 Svahn & Henfridsson 2012 23 E

18 Selander, Henfridsson & Svahn 2010 21 CS

19 Svahn, Lindgren & Mathiassen 2015 7 E

20 Yoo, Lyytinen, Boland, Berente, Gaskin,

Schutz & Srinivasan

2010 not speci-

fied

CS, BME

The Nature of Digital Innovation and What Can Be Learned for Information Systems Management

789

Time Perspective. Figure 1 shows the development

of the number of public ations over time. The number

of publications increased continuously, especially

since 2010. Since 2010, the number of publications

almost increased by thirty times and has had a strong

increase up to 202 papers in 2018.

Geographical Perspective. In total 881 authors were

counted from 58 different countries of origin. For

56 authors (about 6 percent) no assignment to a given

country was possible due to missing information. Fig-

ure 2 shows the continental distribution of authors

with the region of origin and publications devoted to

DI (n = 825). Nearly 61 percent (n = 507) of the au-

thors originate from Europe, followed by North

America with about 20 percent (n = 164) and Asia

with about 11 percent (n =88). The remaining 8 per-

cent (n = 66) of authors originate from Australia, Af-

rica and South America. At the level of countries, the

five topmost are: United States (about 18 percent,

n = 145), United Kingdom (12 percent, n = 99), Ger-

many (about 10 percent, n = 79), Italy (about 7 per-

cent, n = 54) and Sweden (about 6 percent, n = 48).

Subject Area. Figure 3 depicts the number of assign-

ments per subject area and highlights the five super-

ordinate subject areas build from the 17 created sub-

ject areas shown. As the figure illustrates, most of the

publications on DI are found in the superordinate sub-

ject areas Engineering Sciences (white, n = 514),

Civil and Environmental Engineering (middle gray,

n = 437) and Humanities and Social Sciences (light

gray, n = 386). By comparison, those in the areas of

Figure 1: Number of Publications focusing on Digital Innovation per Year.

Figure 2: Regional distribution of publications focusing on Digital Innovation.

Figure 3: Number of Publications focusing on Digital Innovation per subject.

1111212

454467

40 40

101

142

202

132

100

150

200

250

1983 1996 1999 2000 2001 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

507

164

100

200

300

400

500

600

Eu ro pe No rt h Am erica As ia Au str alia Afr ica Sou th Am erica

287

353

150

366

100

150

200

250

300

350

400

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tudi

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ties

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usiness,

M ana gem en t

and Econo

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di cin e

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Science (dark gray) and Medicine (black) are low.

With respect to the illustrated disciplines, publica-

tions on DI are mainly found in Business Manage-

ment and Economics (n = 366), Computer Sciences

(n = 353) as well as Social Sciences (n = 287).

3.2 Qualitative Analysis

A total of 20 publications with regard to the underly-

ing definition of DI, type of innovation and character-

istics of DI was examined in the qualitative analysis.

Table 2 depicts the seven distinct definitions found,

except those that refer repeatedly to the fundamental

publication by Yoo, Henfridsson & Lyytinen (2010)

or without novelty content with respect to the other

publications analyzed.

Definition and Types of DI. Seven of the 20 publi-

cations propose an own definition of DI (Fichman,

Dos Santos & Zheng, 2014; Huang, Henfridsson, Liu

& Newell, 2017; Lusch & Nambisan, 2015; Nam-

bisan & Lyytinen, 2017). Among them are three def-

initions by Yoo et al. (2010; 2010; 2012)

which differ

marginally. They define DI as a product innovation

in which physical and digital components merge.

They see the advancing digitalization as a necessary

prerequisite for this. In the other 13 cases, their defi-

nition was reused. As adoption to the fundamental

definition, Lusch & Nambisan (2015) as well as

Huang, Henfridsson, Liu & Newell (2017) emphasize

the aspect that DI can create a new kind of benefit or

value in a certain context. The advantage of this defi-

nitional approach is that it is not the value of the result

Table 2: Definitions, types, and characteristics of Digital Innovation.

No. Definition Type Characteristic

1 „We define digital innovation as the carrying out of new combina-

tions of digital and physical components to produce novel prod-

ucts. […] A necessary but insufficient condition for digital inno-

vation is that the new combination relies on digitization […].”

(Yoo, Henfridsson & Lyytinen, 2010 , p. 725)

product in-

novation

reprogrammability, data

homogenization,

self-referential nature

2 “A defining characteristic of pervasive digital technology is the in-

corporation of digital capabilities into objects that previously had

a purely physical materiality.” (Yoo, Boland, Lyytinen &

Majchrzak, 2012, p. 1398)

product in-

novation

convergence, generativity

3 „Service innovation can then be considered the rebundling of di-

verse resources that create novel resources that are beneficial (i.e.,

value experiencing) to some actors in a given context; […].”

(Lusch & Nambisan, 2015, p. 161)

service in-

novation

service ecosystem, service

platforms, value cocrea-

tion

4 “We define digital innovation quite broadly as a product, process,

or business model that is perceived as new, requires some signifi-

cant changes on the part of adopters, and is embodied in or enabled

by IT.” (Fichman, Dos Santos & Zheng, p. 330)

product,

process,

business

model inno-

vation

not specified, but in ac-

cordance to (Yoo, Hen-

fridsson & Lyytinen,

2010)

5 „We conceptualize digital innovation as the creation of (and con-

sequent change in) market offerings, business processes, or models

that result from the use of digital technology. Stated differently, in

digital innovation, digital technologies and associated digitizing

processes form an innate part of the new idea and/or is develop-

ment, diffusion, or assimilation.“ (Nambisan & Lyytinen, 2017, p.

224)

product,

platform,

service, cus-

tomer expe-

rience, other

value path-

way innova-

tion

malleable, editable, open,

transferable, continue to

evolve, unpredictability,

dynamic

6 “We define digital innovation as the recombination of digital com-

ponents in a layered, modular architecture to create new value-in-

use to users or potential users of a service.” (Huang, Henfridsson,

Liu & Newell, 2017, p. 302)

service in-

novation

separation of function and

form, separation of con-

tents and medium

7 “By digital innovation, we mean an innovation enabled by digital

technologies that leads to the creation of new forms of digitaliza-

tion.“ (Yoo, Lyytinen, Boalnd, Berente, Gaskin, Schutz & Sriniva-

san, 2010, p. 13)

product in-

novation

programmability, address-

ability, senesability, mem-

orability, traceability,

communicability, associa-

bility

The Nature of Digital Innovation and What Can Be Learned for Information Systems Management

791

as such that is considered, but the value perceived by

the customer. The customer, therefore, plays an active

role in the development of digital service innovations.

The bundling of different resources in digital service

innovation depends on the degree of digitization

(Lusch & Nambisan, 2015). According to Fichman,

Dos Santos & Zheng (2014), DI not only refer to

products but also to processes and business models,

which implies a broader view of DI. A further adap-

tation of the initial definition lies in the requirement

that users have to change. Nambisan & Lyytinen

(2017) provide the most comprehensive view by de-

fining DI as the introduction of novel “market offer-

ings”. The term “market offerings” is deliberately

kept open, as it conceals a multitude of outcomes,

such as products, platforms, services, customer expe-

riences, and value pathways. To enable these out-

comes, different digital technologies (digital tools, in-

frastructure) are needed, which themselves represent

an essential component of innovation and “may be

diffused, assimilated, or adapted to specific use con-

texts […].” (Nambisan & Lyytinen, 2017, p. 224).

Furthermore, DI can also be seen as a means for cre-

ating DI, but also as a result of it, and thus lead to new

forms of digitization (Yoo, Lyytinen, Boland, Ber-

ente, Gaskin, Schutz & Srinivasan, 2010).

Most often, DI is associated with product innova-

tion (Fichman, Dos Santos & Zheng, 2014; Nambisan

& Lyytinen, 2017; Yoo, Boland, Lyytinen &

Majchrzak, 2012; Yoo, Henfridsson & Lyytinen,

2010; Yoo, Lyytinen, Boland, Berente, Gaskin,

Schutz & Srinivasan, 2010), but also with service in-

novations (Huang Henfridsson, Liu & Newell, 2017;

Lusch & Nambisan, 2015). Fichman, Dos Santos &

Zheng (2014) define DI more broadly and include

process and business model innovations. Ultimately,

DI are much more than that: they can be product, ser-

vice, process, business model, application software,

platform, customer experience or other value innova-

tions (Nambisan & Lyytinen, 2017).

Characteristics of DI. Yoo, Henfridsson & Lyytinen

(2010) describe an initial set of the key characteristics

of DI. They name reprogrammability, data homoge-

nization, and self-referencing. Reprogrammability

signifies the separation of the form of the physical ob-

ject and its function. This means, that the behavior of

physical products can be changed during their life-

time. An example is the implementation of program-

mable operating systems on different physical de-

vices. Data homogenization offers the opportunity to

capture, process and display any type of digital con-

tent on the same digital device. An example is the use

of smartphones, which allows access to different

kinds of data and services. These can be integrated by

defined technological interfaces. Different digital

data can be combined and accomplish different func-

tions because the content is separated from the me-

dium. These two fundamental aspects are under-

pinned by Huang, Henfridsson, Liu & Newell (2017).

Self-reference, as the third unique characteristic,

points to the fact that the usage of digital technology

broadens the availability of digital devices and in con-

sequence leads to lower entry-barriers and higher dif-

fusion rates.

Also, Yoo, Lyytinen, et al. (2010) propose a more

detailed view and introduce six dimensions of DI:

digital materiality (and its properties program-mabil-

ity, addressability, senseability, memorability, com-

municability, traceability and associability), hetero-

geneity, locus of innovation, pace, convergence and

generativity (Yoo, Lyytinen, et al., 2010). Digital ma-

teriality is described as the inseparable integration of

social, physical and digital aspects.

Heterogenity de-

notes the variety of data, knowledge, and tools used

by DI. The locus of innovation draws on the location-

independent development of DI to save communica-

tion and storage costs. The speed at which new solu-

tions could be developed is referred to as pace. This

is possible because existing physical components as

well as established digital infrastructures are reused,

and re-combined. Convergence means the integration

of devices, networks, services and contents enabled

through data homogenization. Generativity is used as

a synonym for the ambiguity of DI due to the fact,

that DI is reinterpreted, expanded and refined perma-

nently. Yoo, Boland, Lyytinen & Majchrzak (2012)

generalized the latter two dimensions, convergence

and generativity, two years later, in 2012. According

to the generalization, convergence suggests the use of

digital technologies that creates a link between previ-

ously separated user experiences and industries as

well as embeds digital technologies into physical

products. Whereas their previous description of gen-

erativity is summarized to the terms dynamic and

malleability. Nambisan & Lyytinen (2017) refer to

the terms malleable, editable, open and transferable

as characteristics of digital artifacts. Further, since the

nature of DI is subject to constant change, they also

characterize DI by unpredictability and dynamism.

Lusch & Nambisan (2015) address central themes of

digital service innovations instead of characteristics.

3.3 Course of Digital Innovation

To show how the nature of DI have changed in the

course of the ongoing digital transformation, Figure 4

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792

illustrates the development of DI over time. The hor-

izontal axis indicates the publication years, whereas

the vertical axis denotes the emerged innovation

types. A number in square brackets represents the ref-

erence and the publication year accordingly. Each of

those is enclosed by an ellipse, covering the innova-

tion types named in the respective publication. The

DI characteristics mentioned in the publication is rep-

resented as label. Ellipse overlaps illustrate the inter-

section of characteristics. Ellipses below the next

higher innovation type mark do not include this inno-

vation type. The central themes of digital service in-

novation have been included to complete the figure

(see dashed ellipse), but are not considered further

(see chapter 3.2).

Figure 4 shows that two papers by the same au-

thors were published almost simultaneously. While

one paper, published as a report, deals very thor-

oughly with six dimensions of DI (Yoo, Lyytinen, et

al., 2010), the other paper focuses on the distinction

between digital and conventional technologies (Yoo,

Henfridsson, Lyytinen, 2010). Two years later, the

authors published a third paper highlighting the char-

acteristics convergence and generativity (Yoo, Bo-

land, Lyytinen & Majchrzak, 2012), which were al-

ready part of the six dimensions of the report. Over a

period of four years, the three characteristics of the

fundamental paper (reprogrammability, data homog-

enization, self-referencing) were considered as the

prevailing view. In 2017, the aspect of dynamism and

unpredictability became prominent, and emphasized

the need for editability, openness, and transferability.

At the same time, the separation of function and form,

as well as the separation of contents and medium, was

established.

Concerning the innovation type, it is obvious, that

DI arise from digital product innovation. In addition,

there is a trend for DI in the direction of digital service

innovation. The innovation types of customer experi-

ence innovation and other value innovation were not

mentioned before its appearance in 2017.

3.4 Implications for the Management

of Information Systems in Hospitals

When questioning how the conceptualization of digi-

tal innovation influences the implementation and

management of HIS, the characteristics of DI can help

to systematize design criteria. In the following, we

use the characteristics of Y

OO ET AL. (2010) as guid-

ing characteristics. The implementation of DI in HIS

is challenging both from a technological and an or-

ganisational perspective. Different barriers exist on

different layers. We mainly focus on the enablers and

barriers at the information, application and infrastruc-

tural layer following S

CHEPLITZ ET AL. (2019). These

layers mainly comprise the view on products and

technological services. Therefore the selection of the

three characteristics of Y

OO ET AL. (2010) is adequate

as they focus on digital innovation with a product fo-

cus. The implementation of FHIR addresses the ena-

bler of the concerted definition of contents of medical

records and the barrier of faulty and incompatible

data models.

Reprogrammability in HIS implies that the HIS

must be able to react at any time to changing require-

ments by adapting HAS functions. The requirements

resulting from new tasks and goals in care of patients.

These are formulated by the healthcare professionals.

New functionality needs to be included, immediately

when it is needed. The implementation of FHIR in

HIS gives this opportunity because it enables third-

parties to connect to well-defined interfaces and to

add functionality through new applications. Further-

more, FHIR supports the migration of HAS to modu-

larized systems and allows the implementation of

technological decoupled services. As an example, an

architecture for pathway-based patient integration

can be named (Benedict et al., 2019). New applica-

tions can be connected to FHIR interfaces and create

unanticipated functionality. This saves costs since the

interfaces are purchased once, but used multiple times

in different ways.

Data homogenization means that the HIS must

support the acquisition of health-related data with a

high degree of reusability and interoperability. For

example, a smartwatch measures the patient’s heart

rate permanently and sends the data via FHIR Obser-

vations to the vital data API of the CDMS. Due to ho-

mogeneity of data, the measurement data can be

transferred from one digital device to another system,

(in this case from the smartwatch to the CDMS). It

can be directly interpreted by the CDMS, because

FHIR ensures the interoperability. At the same time,

the physician is able to examine and integrate the

findings in a case record, including the patient’s heart

rate. He can use different vital data provided by dif-

ferent sensors via FHIR graphically on his tablet pc.

He can mix data of the patient for individual dossiers

and share them with colleagues. For example, he can

retrieve the data via a web-interface created by the in-

formaticians in the hospital’s IT department. This

web-interface also accesses the FHIR interfaces of the

CDMS to gain the relevant observations which result

from the smartwatch.

The Nature of Digital Innovation and What Can Be Learned for Information Systems Management

793

Figure 4: The Course of Digital Innovation since 2010.

Self-reference in the context of HIS means, that

the availability of reusable technology eases the inte-

gration of new DI into the HIS. The availability of

FHIR interfaces eases the integration of new digital

technologies. For example, the integration of legacy

patient sensor systems can be more facilitated by

providing a standard-based vital data FHIR interface

which is originally created to record the heart rate.

The implementation of FHIR in a hospital eases ac-

cess to machine-readable data. The knowledge about

the existence of standardized interface lowers the bar-

riers for investing in interfaces.

4 DISCUSSION

Based on the findings of the literature analysis de-

scribed in the previous chapter, the results obtained

are discussed in more detail below. The explanation

starts with general or methodological aspects, fol-

lowed by a discussion of the quantitative and qualita-

tive results.

Methodological Aspects. The amount of the most

frequently cited publications which were analyzed

(n = 12) in relation to the total number of identified

articles (n = 792) is 1.5 percent. This amount is com-

paratively too low to be able to draw general conclu-

sions about the nature of DI. Nevertheless, the cita-

tion frequency is an appropriate measure to assess the

relevance of scientific contributions. However, by fo-

cusing on the citation frequency, relevant publica-

tions may have been excluded. In order to address this

problem and to expand the database, a search using

backward references was included in the literature

search process. A detailed analysis of the 18 publica-

tions has shown that the majority (65 percent) of all

contributions refer to the contents published by Yoo,

Henfridsson & Lyytinen (2010).

Quantitative Analysis. The number of publications

on DI has been growing steadily since 2010. This can

be explained by the growing pace of digitalization

and by the seminal work of Y

ENFRIDSSON

YYTINEN

(2010) that has laid the foundation for re-

search in the field of DI. The number of publica-

tions (n = 202) reached a high level in 2018 and the

trend seems to continue. More than 101 publications

have already been published in the first half of the

year 2019. However, it is possible that some publica-

tions of 2018 and the first half of 2019 were not yet

registered in the databases.

The majority of publications descend from Eu-

rope. One possible explanation for this could be the

fact that two of the three authors of the initial paper

(Henfridsson and Lyytinen) come from Scandinavia.

With their ten respectively four publications on DI,

they have made a significant contribution to the re-

search in this field. Most publications have been pub-

lished in the United States and United Kingdom. This

is probably because papers are usually published in

Scale-IT-up 2020 - Workshop on Best Practices for Scaling-Up Digital Innovations in Healthcare

794

the English-speaking field of information systems re-

search and organizational management to be accessi-

ble to a wide audience and there are fewest language

barriers.

The majority of publications are assigned to the

subject area Business, Management and Economics.

Classically, innovations have

been the subject of

Business Administration. Depending on the point of

view, Business Administration is understood as Hu-

manities or Social Science and thus explains the high

number of publications in this field. In addition, there

are numerous publications in the field of Computer

Science. This can be explained by the fact that the au-

thors of the fundamental work have an economical

background, but also explore the field of Computer

Science.

Qualitative Analysis. The seven identified defini-

tions have in common that digitization respectively

the use of digital technologies or IT are necessary pre-

requisites for the creation of DI. While Yoo et al.

(Yoo, Boland, Lyytinen & Majchrzak, 2012; Yoo,

Henfridsson & Lyytinen, 2010; Yoo, Lyytinen, Bo-

land, Berente, Gaskin, Schutz & Srinivasan, 2010) in-

evitably associate DI with a combination of digital

and physical components, other authors do not em-

phasize the physical aspect in their definition. This is

due to the fact that the authors focus on different top-

ics (e.g. product development, business process opti-

mization, business model creation). In contrast, the

definition of Nambisan & Lyytinen (2017) is open so

that any market offering can be regarded as an inno-

vation. The reason for this is that the authors consider

DI as a variable socio-technical phenomenon and that

this character can only be considered by looking at it

very broadly.

DI is inseparably associated with the innovation

type product innovation because 67 percent (12 out of

18) of the publications refer to Yoo, Henfridsson &

Lyytinen (2010). The authors consider product inno-

vations opposed to process innovations, which have

already been extensively studied in IT research. Ulti-

mately, innovations can arise in the product or service

area. Software application and platform innovations

are examples of subtypes of service innovations. The

evolution from product innovation type to service in-

novation type over time can be explained by the fact

that service enhancements only become relevant once

a product to which the service relates has been devel-

oped. We observed that the understanding of DI as a

Yoo is a Korean professor of Entrepreneurship and Infor-

mation Systems in Design and Innovation at Weatherhead

School of Management/Case Western Reserve University.

Henfridsson is a Swedish professor at Warwick Business

concept was getting more comprehensive over time.

This can be explained by the ongoing digital transfor-

mation of the economy, which leads to new business

models and a change to service-dominant logics

(Lusch & Nambisan, 2015).

In summary, it can be stated that the characteris-

tics of DI are named differently in almost every pub-

lication. In two publications two characteristics are

proposed, in other publications three or even seven.

Hereby it becomes clear that the categories are some-

times narrower, sometimes broader and often overlap.

Of particular interest is that although two publications

by the same authors were published in 2010, DI char-

acteristics were named differently. The report pub-

lished in January (Yoo, Lyytinen, et al., 2010) distin-

guishes between characteristics of digital technolo-

gies (data homogenization, programmability, self-ref-

erencing), properties of digital materiality and dimen-

sions of DI (convergence, digital materiality, hetero-

geneity, generativity, locus of innovation, pace). The

publication (Yoo, Henfridsson & Lyytinen, 2010) de-

scribes reprogrammability, data homogenization and

self-referencing as key characteristics of DI. In

2012 (Yoo, Boland, Lyytinen & Majchrzak, 2012),

the authors are talking about only two unique charac-

teristics – convergence and generativity. Thus, the use

of terms is not consistent. For example, the separation

of function and form is assigned in (Yoo, Lyytinen,

Boland, Berente, Gaskin, Schutz & Srinivasan, 2010)

to the characteristic digital materiality, in (Yoo, Hen-

fridsson & Lyytinen, 2010) reprogrammability and in

(Yoo, Boland, Lyytinen & Majchrzak, 2012) as gen-

erativity. The two publications from 2017 (Huang,

Henfridsson, Liu & Newell, 2017; Nambisan & Lyyt-

inen, 2017) describe the properties of the characteris-

tics of (Yoo, Henfridsson & Lyytinen, 2010) in other

words and augment them (e.g. malleable, dynamic).

5 CONCLUSIONS

In the last years the understanding of DI has become

more holistic. While the early innovation discussions

focused more on the materiality of DI, the later dis-

cussions investigated networks and logics of innova-

tion. When integrating DI into existing IS, IS manag-

ers need also consider whether their existing subsys-

tems of the IS are “ready for innovation”. Conse-

quently, there is a need to analyze the ability of IS to

School and was once Head of the Information Systems

Group. Kalle Lyytinen is a Finnish professor of Manage-

ment Design and Design and innovation at Weatherhead

School of Management/Case Western Reserve University.

The Nature of Digital Innovation and What Can Be Learned for Information Systems Management

795

both integrate and create DI. This paper contributes

by introducing different fields of DI from which dif-

ferent characteristics for subsystems of IS (e.g. repro-

grammability, data homogenization, self-referencing)

can be derived. These properties may be used to ana-

lyze, evaluate and to re-engineer existing IS. By de-

scribing implications for HIS, the paper shows how

the characteristics of DI can be instantiated in a spe-

cific domain. Since our focus was on the technologi-

cal implications an analysis of organizational impli-

cations for HIS design is outstanding and needs to be

treated in further research.

This paper offers a detailed description of the na-

ture of DI, but also contains limitations that provide

directions for further research. In order to verify and

extend the analysis results, a much larger data basis

should be considered in the following investigation.

In addition, the results of the descriptive analysis of-

fer the potential to find out, through an in-depth in-

ductive analysis, why new definitions and innovation

types have developed and why certain characteristics

emerged or disappeared – even if this is already partly

the case in this paper. An ontology would be an ap-

propriate approach to visualize and clearly distin-

guish the diversity of terminologies used.

ACKNOWLEDGEMENT

This work is part of the ERDF-project “Häusliche Ge-

sundheitsstation” and is funded by the European Un-

ion and the Free State of Saxony.

REFERENCES

Alkraiji, A., Jackson, T., & Murray, I. (2013). Barriers to

the Widespread Adoption of Health Data Standards: An

Exploratory Qualitative Study in Tertiary Healthcare

Organizations in Saudi Arabia. J Med Sys, 37(2), 9895.

Bender, D., & Sartipi, K. (2013). HL7 FHIR: An Agile and

RESTful approach to healthcare information exchange.

Proceedings of the 26th IEEE International Symposium

on Computer-Based Medical Systems, 326–331.

Benedict, M., Schlieter, H., Burwitz, M., Scheplitz, T.,

Susky, M., & Richter, P. (2019). A Reference Architec-

ture Approach for Pathway-Based Patient Integration.

2019 IEEE 23rd International Enterprise Distributed

Object Computing Conference (EDOC), 58–66.

Cooper, H., & Hegdes, L. V. (1994). Research synthesis as

a scientific enterprise.

de Reuver, M., Sørensen, C., & Basole, R. C. (2018). The

Digital Platform: A Research Agenda. Journal of Infor-

mation Technology, 33(2), 124–135.

Fettke, P. (2006). State-of-the-Art des State-of-the-Art.

Wirtschaftsinformatik, 48(4), 257.

Fichman, R. G., Dos Santos, B. L., & Zheng, Z. E. (2014).

Digital Innovation as a Fundamental and Powerful Con-

cept in the Information Systems Curriculum. MIS

Quarterly, 38(2), 329–343.

Haux, R., Winter, A., Ammenwerth, E., & Brigl, B. (2013).

Strategic Information Management in Hospitals: An In-

troduction to Hospital Information Systems. Springer

Science & Business Media.

Hevner, A., vom Brocke, J., & Maedche, A. (2019). Roles

of Digital Innovation in Design Science Research.

Business & Information Systems Engineering, 61(1),

3–8.

Huang, J., Henfridsson, O., Liu, M. J., & Newell, S. (2017).

Growing on Steroids: Rapidly Scaling the User Base of

Digital Ventures Through Digital Innovaton. MIS Q,

41(1), 301–314.

Jung, C., & Padman, R. (2015). Disruptive Digital Innova-

tion in Healthcare Delivery: The Case for Patient Por-

tals and Online Clinical Consultations. In R. Agarwal,

W. Selen, G. Roos, & R. Green (Hrsg.), The Handbook

of Service Innovation (S. 297–318). Springer London.

Khalifa, M., & Alswailem, O. (2015). Hospital Information

Systems (HIS) Acceptance and Satisfaction: A Case

Study of a Tertiary Care Hospital. Procedia Computer

Science, 63, 198–204.

Lluch, M. (2011). Healthcare professionals’ organisational

barriers to health information technologies—A litera-

ture review. Int J Med Inf, 80(12), 849–862.

Lusch, R. F., & Nambisan, S. (2015). Service Innovation:

A Service-Dominant Logic Perspective. MIS Q, 39(1),

155–175.

Moghaddasi, H., Mohammadpour, A., Bouraghi, H., Azizi,

A., & Mazaherilaghab, H. (2018). Hospital Information

Systems: The status and approaches in selected coun-

tries of the Middle East. Electronic Physician, 10(5),

6829–6835.

Moser, H. (2013). Strategisches Projektmanagement im

Gesundheitswesen: Wie Stakeholder auf ein

Sensitivitätsmodell einwirken - eine Analyse. disserta

Verlag.

Nambisan, Satish, Lyytinen, K., Case Western Reserve

University, Majchrzak, A., University of Southern Cal-

ifornia, Song, M., & Xi’an Technological University.

(2017). Digital Innovation Management: Reinventing

Innovation Management Research in a Digital World.

MIS Q, 41(1), 223–238.

Rachinger, M., Rauter, R., Müller, C., Vorraber, W., &

Schirgi, E. (2018). Digitalization and its influence on

business model innovation. Journal of Manufacturing

Technology Management.

Scheplitz, T., Kaczmarek, S., & Benedict, M. (2019). The

Critical Role of Hospital Information Systems in Digi-

tal Health Innovation Projects. 2019 IEEE 21st Confer-

ence on Business Informatics (CBI), 01, 512–521.

Winter, A., Haux, R., Ammenwerth, E., Brigl, B., Hellrung,

N., & Jahn, F. (2011). Health Information Systems: Ar-

chitectures and Strategies. Springer Science & Business

Media.

Scale-IT-up 2020 - Workshop on Best Practices for Scaling-Up Digital Innovations in Healthcare

796

Yoo. (2010). Computing in Everyday Life: A Call for Re-

search on Experiential Computing. MIS Q, 34(2), 213.

Yoo, Y., Boland, R. J., Lyytinen, K., & Majchrzak, A.

(2012). Organizing for Innovation in the Digitized

World. Organization Science, 23(5), 1398–1408.

Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010). The New

Organizing Logic of Digital Innovation: An Agenda for

Information Systems Research. ISR, 21(4), 724–735.

Yoo, Y., Lyytinen, K., Boland, R. J., Berente, N., Gaskin,

J., Schutz, D., & Srinivasan, N. (2010). The Next Wave

of Digital Innovation: Opportunities and Challenges: A

Report on the Research Workshop „Digital Challenges

in Innovation Research“.

The Nature of Digital Innovation and What Can Be Learned for Information Systems Management

797