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Business model innovation in the era of the internet of things

Progress in IS

Jan F. Tesch   Editor

Business Model
Innovation in the
Era of the Internet
of Things
Studies on the Aspects of Evaluation,
Decision Making and Tooling


Progress in IS


More information about this series at http://www.springer.com/series/10440


Jan F. Tesch
Editor


Business Model Innovation
in the Era of the Internet
of Things
Studies on the Aspects of Evaluation,
Decision Making and Tooling

123


Editor
Jan F. Tesch
Stuttgart, Germany
Dissertation Georg-August Universität Göttingen, 2017

Supervisory board
First supervisor: Prof. Dr. Lutz M. Kolbe
Second supervisor: Prof. Jan Muntermann
Third supervisor: Prof. Indre Maurer
Date of oral examination: 24th of October 2017

ISSN 2196-8705
ISSN 2196-8713 (electronic)
Progress in IS
ISBN 978-3-319-98722-4
ISBN 978-3-319-98723-1 (eBook)
https://doi.org/10.1007/978-3-319-98723-1
Library of Congress Control Number: 2018955918
© Springer Nature Switzerland AG 2019
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Foreword

The ability to establish novel business models is essential to ensuring the ongoing
success of traditional corporations in a digital era, but novel business models are
also a major theme for startups and SMEs. However, business model innovation
poses tremendous challenges, particularly in technology-driven industries. Despite
the salience of these well-known challenges, present innovation processes do not
yet reflect the requirements necessary for managing the ever-increasing complexity
of connected products, solutions, and their attendant ecosystems in a future world
of the Internet of things (IoT). In this regard, it is critical to form designated entities
which foster the systematic exploration of new business opportunities and which
provide an excellent foundation for strategic management decisions.
Since joining the Bosch Group in 2011, Dr. Jan F. Tesch has taken on several
roles in which he has supported the expansion of the business portfolio of various
business units into the digital space. In addition, Dr. Tesch has had the opportunity
to collaborate with numerous scholars, leading to many practical findings regarding
systematic business model innovation, and he has contributed to an enhanced
scientific understanding of the field. Dr. Tesch’s work has been published in
numerous peer-reviewed scientific journals, and he has participated in several
conferences on the topic of business model innovation. In his current role, Dr.
Tesch is supporting the development of IoT business model innovation and has
contributed to the company’s future direction with his findings.
This book serves as a synthesis of seven individual studies dealing with the
intersection of research and practice. The work outlines an innovation framework
for developing IoT-based business models built upon the learnings and insights
generated throughout the course of several innovation projects. Furthermore, Dr.
Tesch introduces novel tools, methods, and best practices to help business model
consultants support the decision-making of senior management.
Stuttgart, Germany
October 2017

Dr. Johannes Sommerhäuser
Senior Vice President,
Head of Corporate Business Model
Innovation, Robert Bosch GmbH
v


Acknowledgements

The emerging paradigm of the so-called Internet of things (IoT) represents an
overwhelming opportunity to entrepreneurs, SMEs, and corporations alike.
Thereby, the ability to develop innovative new business models is seen as one
of the most challenging tasks. This topic has sparked my enthusiasm from as early
as I wrote my thesis graduating from Karlsruhe Institute of Technology in 2011,
where I was assigned to determine a viable business model for connected EV
charging equipment for Bosch. I discovered that for professionals in this field, it is
key to understand the intersection of economics, strategic management,
entrepreneurship, operations research, finance, and information systems. At this
time, however, it was not clear to me how these subjects merge together as a
whole—a circumstance also reflected by scientific literature’s emphasis on further
clarification of the topic business model innovation. Hence, my idea of pursuing a
Ph.D. was to combine the individual knowledge and thus to contribute to an
enhanced, interdisciplinary understanding. Furthermore, the book at hand also seeks
at providing business model innovation professionals with best practice tools for
decision-making based on experiences in IoT projects.
I am deeply thankful that I got the exceptional opportunity to pursue this
endeavor at both Robert Bosch GmbH and at the Chair of Information Management
at the University of Göttingen—a setting allowing for ideal conditions for
practice-oriented research. Within the following, I express my utmost gratitude
to all those who believed in and largely contributed to this endeavor along the way.
First and foremost, I would like to thank Prof. Dr. Lutz M. Kolbe, Dean of the
Faculty of Economic Sciences of the University of Göttingen, Prof. Dr. Jan Muntermann
and Prof. Dr. Indre Maurer for the supervision of the thesis. Also, I would like to thank
Reinhold Mörder, Thomas Schmidt, Christoph Erbacher, and Dr. Mark Müller for
giving me the chance to pursue this endeavor within the business unit Software
Innovations at Bosch. Furthermore, my deepest thankfulness is to my department
supervisor Dr. Marco Lang, who has given me invaluable support, freedom of scope,

vii


viii

Acknowledgements

and valuable advice. Within the Robert Bosch GmbH, I would like to thank
Dr. Johannes Sommerhäuser and Doris Grammer for giving me the opportunity to
continue working on IoT topics within the newly founded corporate department for
Business Model Innovation (C/BM). Your leadership is a true inspiration to me.
Further thanks are to the co-authors of the studies within this book,
Dr. Gerrit Remané, Dr. André Hanelt, Monika Streuer, Kirstin E. Bosbach,
Dr. Uwe C. M. Kirschner, and Miriam Lehmbrink, for the excellent and fruitful
cooperation. In the same manner, I would like to thank the students who have
written their graduation thesis under my supervision, Benedikt Freiherr von
Ziegesar, Ronja Lamers, and Hardy Killus, for their magnificent work and their
valuable contribution to the overall research project. Particular thanks for their
excellent ideas, thoughts, and dedication to our joint research on IoT business
model innovation go to Anne-Sophie Brillinger and Dominik Bilgeri. I strongly
believe that our spirit of working as a team and putting the greater goal above
everyone’s incentive made the outcome a lot greater than the sum of each individual’s efforts. This is what true teamwork is all about.
Apart from all the aforementioned, I would like to thank my colleagues from the
Chair of Information Management for the excellent working atmosphere and the
valuable scientific feedback: Dr. Alfred Benedikt Brendel, Benjamin Brauer,
Björn Hildebrandt, Dr. Carolin Ebermann, Daniel Leonhardt, Dr. Everlyn Piccinini,
Prof. Dr. Johann Kranz, Dr. Johannes Schmidt, Dr. Markus Mandrella,
Dr. Matthias Eisel, Muhammad Raheel, Dr. Patrick Urbanke, Patryk Zapadka,
Dr. Sebastian Zander, Dr. Simon Trang, Sromona Chatterjee, and Dr. Thierry Ruch.
I am also very gifted to enjoy deep and long-lasting friendships with some very
great minds: Anika Schweizer, Ann-Kathrin Schuon, Dominik Kollmuß,
Eva Zimmer, Dr. Ilja Nastjuk, Janine Flöter, Dr. Konrad Zimmer, Konstantin
Ohlert, Dr. Lukas Arenz, Dr. Martin Arenz, Matthias Feth, Michael Christophers,
Moritz Fanti, Oliver Biwer, Sabine Fuchs, Sarah Barkow, Sebastian Martens,
Steinar Vinne, and Thomas Meier. I know many of you for more than two decades.
We have gone through ups and downs of life together, and no matter what happened, we have always been there for each other. This is what really counts in life.
Last, but most important, I wholeheartedly thank my parents, Christa and Frank,
and my sister, Anna-Teresa Tesch. My parents have always sought for giving my
sister and me all freedom and infinite support to pursue whatever we found was the
right thing to do, even if it meant a high degree of their own abstinence. Without
their invaluable commitment and endless love, none of our prosperities would have
been even close to be achieved.
Jan F. Tesch


Contents

Part I

Foundations

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Jan F. Tesch

3

Theoretical Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Jan F. Tesch

19

Part II

Decisions and Evaluation in IoT Business Model Innovation

IoT Business Model Innovation and the Stage-Gate Process . . . . . . . . .
Jan F. Tesch, Anne-Sophie Brillinger and Dominik Bilgeri

51

The Evaluation Aspect of Digital Business Model Innovation . . . . . . . .
Jan F. Tesch and Anne-Sophie Brillinger

67

Part III

Studies on the Roles of Tools and Methodologies in IoT BMI

The Business Model Pattern Database: A Tool
for Systematic BMI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Gerrit Remané, Andre Hanelt, Jan F. Tesch and Lutz M. Kolbe

89

A Business Model Perspective on Innovation Susceptibility . . . . . . . . . 145
Kirstin E. Bosbach, Jan F. Tesch and Uwe C. M. Kirschner
Profit Driving Patterns for Digital Business Models . . . . . . . . . . . . . . . 165
Monika Streuer, Jan F. Tesch, Doris Grammer, Marco Lang
and Lutz M. Kolbe
Customer Surveys as a Quantitative Evaluation Tool
for Digital BMI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
Jan F. Tesch, Miriam Lehmbrink, Gerrit Remané and Lutz M. Kolbe

ix


x

Contents

Scenario Planning as a Causal Evaluation Tool for IoT Business
Model Innovation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
Jan F. Tesch
Part IV

Contributions

Findings and Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
Jan F. Tesch
Implications—An Integrative Framework for IoT Business
Model Innovation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
Jan F. Tesch
Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 251
Jan F. Tesch
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257


Acronyms

ADR
BM
BMC
BMF
BMI
DSR
IIoT
IoT
KPI
KSF
MSP
MVP
NFC
NPD
RBV
SH
SMEs
VPC

Action design research
Business model
Business model canvas
Business model framework
Business model innovation
Design science research
Industrial internet of things
Internet of things
Key performance indicator
Key success factor
Multi-sided platform
Minimum viable product
Near-field communication
New product development
Resource-based view
Smart home
Small and medium enterprises
Value proposition canvas

xi


List of Figures

Introduction
Fig. 1 Overview of the book structure . . . . . . . . . . . . . . . . . . . . . . . . . . .
Theoretical Background
Fig. 1 Overview on components of business models from literature.
Adapted from Krumeich et al. (2012) . . . . . . . . . . . . . . . . . . . . .
Fig. 2 Perspective on business models a result of strategic choices.
Adapted from Casadesus-Masanell and Ricart (2010, p. 204)
and Gassmann et al. (2016, p. 18) . . . . . . . . . . . . . . . . . . . . . . .
Fig. 3 The activity system design framework. Source Zott and Amit
(2010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Fig. 4 The RCOV framework. Source Demil and Lecoq (2010) . . . . . .
Fig. 5 Identified phases (synthesis) of business model innovation
(own representation). Note Italic font indicates implicit mention
in the original source . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Fig. 6 IoT technology stack (based on Porter and Heppelmann
2014, p. 7; Wortmann and Flüchter 2015, p. 223) . . . . . . . . . . .
Fig. 7 Value creation layer (based on Fleisch et al. 2015) . . . . . . . . . .

8

..

24

..

26

..
..

27
28

..

34

..
..

38
41

IoT Business Model Innovation and the Stage-Gate Process
Fig. 1 Two decision points and their occurrence on the
BMI timeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

59

The Evaluation Aspect of Digital Business Model Innovation
Fig. 1 Overview of the search process (own representation) . . . . . . . . . . .
Fig. 2 Logic and criteria of evaluation research articles
(own representation) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
The Business Model Pattern Database: A Tool for Systematic BMI
Fig. 1 Taxonomy development method
(Nickerson et al. 2013, p. 345) . . . . . . . . . . . . . . . . . . . . . . . . . . . .

72
74

101
xiii


xiv

Fig. 2
Fig. 3

List of Figures

Development of dimensions for the business model
pattern taxonomy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Dimensions, characteristics, and number of business
model patterns per characteristic . . . . . . . . . . . . . . . . . . . . . . . . . . .

A Business Model Perspective on Innovation Susceptibility
Fig. 1 Phases of the business model innovation process. Adapted
from Frankenberger et al. (2013) . . . . . . . . . . . . . . . . . . . . . . . .
Fig. 2 General methodological approach . . . . . . . . . . . . . . . . . . . . . . .
Fig. 3 Action design research to design, development, and valuation
of the artifact. Adapted from Sein et al. (2011) . . . . . . . . . . . . .
Fig. 4 Strategic perspective on innovation potential in the market . . . .

102
107

..
..

149
151

..
..

153
161

Profit Driving Patterns for Digital Business Models
Fig. 1 The research design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Fig. 2 Procedure of data analysis based on Creswell’s data analysis
spiral (1998) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Customer Surveys as a Quantitative Evaluation Tool for Digital BMI
Fig. 1 The Internet of Things-products-services logic. Adapted
from Fleisch et al. (2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Fig. 2 Smart Home BM adapted from Tesch (2016) and
Osterwalder et al. (2010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Fig. 3 Identification of solution features and attributes . . . . . . . . . . . . . . .
Fig. 4 Viable business models for addressing Customer Segments
1 and 2 in the schemed by value network diagrams
(Bilgeri et al. 2015) (Simplified) . . . . . . . . . . . . . . . . . . . . . . . . . . .
Scenario Planning as a Causal Evaluation Tool for IoT Business
Model Innovation
Fig. 1 Design, development and evaluation of the artifact: Action Design
Research (ADR). Adapted from Sein et al. (2011) . . . . . . . . . . . . .
Fig. 2 Overview of the business model. Adapted from
Osterwalder et al. (2010) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Fig. 3 Driving factors from PESTE analysis for the smart home case,
illustrated by the impact uncertainty grid (Schoemaker and
van der Heijden 1992) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Fig. 4 Using correlations between driving factors to identify scenario
dimensions (simplified) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Fig. 5 Key scenarios for the smart home platform and identified
key success factors (KSF) to differentiate from potential
competitors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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180
190
192

199

215
219

221
222

222


List of Figures

Fig. 6

xv

Stakeholder network diagram (Bilgeri et al. 2015) for the
“lifestyle” (left) and the “hidden revenue” (right) smart home
scenario . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

223

Implications—An Integrative Framework for IoT Business
Model Innovation
Fig. 1 The integrated framework for IoT business model innovation . . . .

246


List of Tables

Introduction
Table 1 Overview of studies included in this book . . . . . . .
Table 2 Overview of research design of studies included
in this book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Table 3 Overview of anticipated contributions to research .
Table 4 Overview of anticipated contributions to practice .

...........

9

...........
...........
...........

12
14
15

Theoretical Background
Table 1 Definitions of the term “business model” . . . . . . . . . . . . . . . . .
Table 2 Perspectives on business models . . . . . . . . . . . . . . . . . . . . . . .
Table 3 Overview on components of business models
(Osterwalder et al. 2010, pp. 20–21) . . . . . . . . . . . . . . . . . . . .
Table 4 Definitions of business model innovation . . . . . . . . . . . . . . . . .
Table 5 Summary of the identified 21 IoT business model patterns
by Fleisch et al. (2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

..
..

21
23

..
..

25
31

..

41

IoT Business Model Innovation and the Stage-Gate Process
Table 1 List of case studies and interview partners . . . . . . . . . . . . . . . . . .
Table 2 Two main decision points and underlying criteria . . . . . . . . . . . .

57
60

The Evaluation Aspect of Digital Business Model Innovation
Table 1 Logic and criteria of evaluation research articles
(own representation) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

79

The Business Model Pattern Database: A Tool for Systematic BMI
Table 1 Elements of a business model . . . . . . . . . . . . . . . . . . . . . . . . .
Table 2 Definitions of business model patterns . . . . . . . . . . . . . . . . . . .
Table 3 Research design overview . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Table 4 Original sources of business model patterns . . . . . . . . . . . . . . .

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.
.
.
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.
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xviii

Table 5
Table 6

List of Tables

Reviews of business model pattern literature . . . . . . . . . . . . . . . .
Usage of the pattern database during the business model
innovation process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

A Business Model Perspective on Innovation Susceptibility
Table 1 Overview on activities following a design science research
approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Table 2 Detailed overview of the innovation levers . . . . . . . . . . . . . . . . .
Profit Driving Patterns for Digital Business Models
Table 1 Leading questions for the interview . . . . . . . . . . . . . . . . . . . . . . .
Table 2 Summary of the identified 21 IoT patterns including
the nine profit driving patterns . . . . . . . . . . . . . . . . . . . . . . . . . . .
Customer Surveys as a Quantitative Evaluation Tool for Digital BMI
Table 1 Phases of digital BMI processes (based on Tesch
and Brillinger 2017, p. 10) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Table 2 Overview on publications applying conjoint analysis in context
of business model innovation . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Table 3 Conjoint Survey Results Sheet . . . . . . . . . . . . . . . . . . . . . . . . . . .
Table 4 Overview of business model choice options . . . . . . . . . . . . . . . . .
Scenario Planning as a Causal Evaluation Tool for IoT Business
Model Innovation
Table 1 Overview on activities following a Design Science Research
approach based on Peffers et al. (2007) . . . . . . . . . . . . . . . . . . . .
Table 2 Overview of the key steps of the scenario-planning artefact . . . .

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110

154
156

168
170

182
186
194
200

216
218

Findings and Results
Table 1 Integrated findings of Study 1 and 2: framework to innovate
business models in the era of the internet of things (IoT) . . . . . .
Table 2 Integrated findings: the roles of BM evaluation methodologies
in the era of the IoT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

236

Implications—An Integrative Framework for IoT Business Model
Innovation
Table 1 Overview of major contributions to research . . . . . . . . . . . . . . . .
Table 2 Features of the phases of the integrative IoT business model
innovation framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

244

240

248


Part I

Foundations

Part I of this cumulative dissertation comprises two chapters. It begins with an
introduction of the emerging economic paradigm of the Internet of things (IoT) and
the importance of a firm’s ability of superior business model innovation (BMI).
Subsequently, the theoretical background gives an overview of the relevant terminologies and provides the reader with existing scientific research for the intended
research contribution.


Introduction
Jan F. Tesch

Keywords Internet of Things · IoT · Business Model · Innovation · Strategy

The following chapter outlines the motivation of the research endeavour, followed by
concrete research gaps and research questions. Afterwards, the introduction provides
an overview of the structure of the book, further elaborates on the research design
and anticipated contributions.

1 Motivation of the Book
In the wake of rapid advances in information technology (IT) and the increasing
pervasiveness of digitalization, today’s companies are facing highly dynamic business environments (Porter and Heppelmann 2014). Thereby, the so-called Internet
of Things (IoT) is seen as the major driver of economical and societal changes in the
coming years (Rifkin 2014). A preliminary understanding of the IoT is that ordinary,
everyday-life “things” get equipped with computational capability and internet connectivity (Fleisch 2010). Once purely physical, things become increasingly coupled
with sensors, actuators, computing and connectivity units to become smart (Miorandi et al. 2012). Thus, smart things are merging into hybrid solutions that offer a
wide range of services beyond the original physical function (Atzori et al. 2010). In
this sense, the Internet of Things enables a variety of innovative ways of offering
new value propositions to customers, suppliers and partners: in other words, multiple
things combined may offer higher value to stakeholders than the sum of their parts.
J. F. Tesch (B)
University of Göttingen, Göttingen, Germany
e-mail: mail@jan-tesch.de
© Springer Nature Switzerland AG 2019
J. F. Tesch (ed.), Business Model Innovation in the Era of the Internet of Things,
Progress in IS, https://doi.org/10.1007/978-3-319-98723-1_1

3


4

J. F. Tesch

Hence, especially with costs for computing and connectivity declining tremendously,
the Internet of Things represents a novel economic paradigm (Atzori et al. 2010).
Looking at historical situations when potentially disruptive technologies emerged,
firms were challenged to develop new ways of delivering value to customers (Chesbrough 2007). Thereby, possible impacts of such technologies were not always fully
understood by incumbents. As an illustrative example, companies such as Nokia or
Kodak (Lucas and Goh 2009) as dominant industry leaders experienced a significant loss in market share. Despite having developed the superior technology within
their R&D-departments, these incumbents failed to speed up the redesign of value
creation processes to meet customer’s new demand (Markides 2006; Johnson et al.
2008). Hence, in fear of cannibalizing their traditional business, their original value
proposition to the customer became inferior compared to those of emerging market entrants. In essence, these incumbents failed to develop an innovative business
model, i.e. a novel “rationale of how an organization creates, delivers and captures
value” (Osterwalder et al. 2010, p. 14).
The development of new innovative business models (BM) in the era of the Internet
of Things is a central challenge for incumbents in several industries (Andersson and
Mattson 2015): facing new fields of competition from non-traditional market players
such as Amazon, Microsoft, IBM or SAP, players in traditional physical industries
are urged to develop new ways of creating and capturing value. Recent research,
such as from Westerlund et al. (2014) and Bilgeri and Wortmann (2017), emphasizes
that once viewed from a purely technological perspective, major enabling factors of
business success are considered increasingly within the orchestration of ecosystems
of partners and multilateral value chains. The emerging paradigm of the IoT leads to a
change from the traditional world of business—characterized by stability and linear
value chains—to an emerging realm of digital business, which is more complex
and distinguished by increasing levels of uncertainty and multilateral value chain
networks. In conclusion, it is emphasized that a lack of profound understanding in
business model innovation (BMI) is the main reason for the failure of IoT projects
(Schneider and Spieth 2013; Andersson and Mattson 2015).
Within science, researchers already widely investigated managerial aspects of
cases of companies struggling in situations when changes in their ecosystems arise
(Yoo 2013; Ghazawneh and Henfridsson 2015). In general, next to technological
advancements as discussed above, changes in political, economic, societal, ecologic
or legislative circumstances (PESTEL) may be cause for a shift in market conditions
fostering the incumbent’s need to innovate its business model (Osterwalder et al.
2010). From a practitioner’s point of view, however, insufficient understanding of
their potential outcomes can lead to “white spots” and thus failing to initiate an
innovation process altering the incumbent’s business model adequately (Christensen
and Overdorf 2000; Lucas and Goh 2009). Ignoring or underestimating the inherent
innovation potential of such new business opportunities may not only imply a missed
growth opportunity, but also a threat to the core business as a leverage point for
competitor firms or new market entrants to disrupt the incumbent’s business model
(Johnson et al. 2008).


Introduction

5

In sum, the emergence of the Internet of Things represents a new economic
paradigm to corporations and start-ups, which bears the potential to offset traditional rules of competition among several markets and industries. This challenges
incumbents to initiate and execute adequate processes to change their way of doing
business, i.e. the innovation of an incremental, radical, or even disruptive new business model. Thereby, both researchers and practitioners emphasize a gap in the aspect
of evaluation in business model innovation projects (Burkhart et al. 2011; El Sawy
and Pereira 2013; Veit et al. 2014). In contrast to ordinary new product development (NPD), where there are several established methodologies for dealing with
these topics (Bucherer et al. 2012), the IoT has enormous impacts on the creation
of value, and the interplay between business partners becomes increasingly complex (Westerlund et al. 2014; Porter and Heppelmann 2014). Thus, within the era of
the Internet of Things, the validity of acknowledged means of evaluation stemming
from traditional strategic management, i.e. tools, methodologies and procedures, are
questioned under this newly arising economic paradigm.
Motivation of the dissertation project is to shed light upon the role of tools and
methodologies that might foster the evaluation aspect of IoT business model innovation. In a scientific manner, the book aims to investigate the characteristics of
how firms may systematically innovate their business models subject to the arising
prerequisites as schemed above. To make a significant contribution, the dissertation
considers Casadesus-Masanell and Ricart’s (2010) theoretical perspective on business models, who state that the innovation process consists of strategic and tactical
choices. Drawing from this perspective bears the opportunity to elaborate an integrative framework to shed light on the role of evaluation within distinct phases of
business model innovation processes in the era of the Internet of Things. For practitioners, particularly for professionals in business model innovation, the dissertation
project seeks to provide guidance to when and how decisions in a BMI process are
best made. Particularly, with the elaborated tools and methodologies supporting the
decision making, the dissertation project endeavors to enable professionals to contribute to a firm’s success with an enhanced ability to evaluate and predict future
business models within an innovation project.

2 Research Gaps and Research Questions
Within existing research on business model innovation, three previously identified research streams are bearing significant opportunities to contribute to research
(Schneider and Spieth 2013): (1) enablers of business model innovation, (2) process and elements of business model innovation, and (3) effects of business model
innovation (Schneider and Spieth 2013). The endeavor of the book is to shed light
on the role of tools and methodologies within business model innovation processes,
particularly, the second stream emphasizes the scientific field of BMI research corresponding to the outlined motivation stemming from the emergence and influence
of the new economic paradigm around the Internet of Things.


6

J. F. Tesch

Within the second research stream (Schneider and Spieth 2013), previous research
mainly dealt with the qualitative exploration of the overall process of BMI. In particular, the continuous discovery-driven and learning-oriented characteristics were investigated in depth (Chanal and Caron-Fasan 2010; Demil and Lecocq 2010; McGrath
2010; Smith et al. 2010; Sosna et al. 2010). However, key aspects such as the identification of business opportunities for the initiation of BMI or its design and the
evaluation of future viability, remain largely unclear (Veit et al. 2014). Several studies, such as from Yunus et al. (2010) or Massa and Testa (2011) analyzed BMI within
particular markets and industries. However, despite their valuable findings in several
cases, the authors emphasize the importance of pursuing research on BMI in other
contexts to then contribute to generalization attempts. The findings explicitly state
that different types of BMI need to be distinguished. Additionally, the continuation
to seek an enhanced understanding of the possibility to support firms throughout the
process is crucial for further BMI research. This is due to the challenging nature of
business model innovation both scholars and practitioners are facing.
Schneider and Spieth (2013, p. 23) outline three starting points for a better understanding of the process and elements of business model innovation for future research
in this field:
a. “What determines the process and elements of business model innovation in
specific contexts?”
b. “Which general types or forms of business model innovation can be identified?
How do distinct forms of business model innovation impact on the underlying
process?”
c. “How can firms be supported in conducting business model innovation in terms
of tools and methods?”
In a nutshell, “providing a deeper understanding of the process of business model
innovation and in particular concerning the elements comprising business model
innovation, the main objective of further research in this field should be to provide analytical support for business model innovation’s discovery-driven process”
(Schneider and Spieth 2013). In this sense, the emergence of the IoT paradigm depicts
a new ‘type’ of business model innovation (Bilgeri et al. 2015). However, very recent
studies have already provided initial insights on the influence of the Industrial Internet
of Things (IIoT) on existing business models of manufacturing incumbents (Arnold
et al. 2016), or types of IoT business models (Laudien and Daxböck 2016b), largescale insights on the innovation process (a) and support methods (c) remain largely
unclear.
In terms of the research field of the BMI process and elements in the specific context of the IoT (a), the aspect of decision-making as recurring characteristics depicts a
promising field of analysis. Other than existing approaches to derive a process model
for general BMI, such as already undergone by, e.g., Teece (2010), Osterwalder et al.
(2010), Frankenberger et al. (2013) or Laudien and Daxböck (2016a), an explicit
view on key decisions in IoT may serve as a separator between different ‘stages’ of
evaluation. Learnings from the decision behavior itself may then draw insights on
key factors and aspects, which in turn allows for a derivation on requirements for


Introduction

7

means supporting the decision making. An integrative framework to structure the
process of the new type of IoT business models helps both scholars and practitioners
to understand how “new network- and activity system–based value creation mechanisms” can be utilized “to achieve the sources of competitive advantage” (Zott et al.
2011). Hence, the research question of Part II is derived as follows:
How can business models be developed and innovated systematically in the era
of the Internet of Things?
With insights on the first research question at hand, the dissertation then allows
for a better understanding of the systematic applicability and use of existing BMI
tools and methodologies in the different stages of IoT business model innovation (c).
Structured literature reviews (Burkhart et al. 2011; Veit et al. 2014; Wirtz et al. 2016)
indicate that only some publications deal with the aspect of evaluating business models as a part of an innovation process. Corresponding to the research question in Part
II, several researchers highlight the importance of continuous business model innovation (Frankenberger et al. 2013) versus a more linear approach (Bilgeri et al. 2015).
Analyzing the various aspects of business model innovation from a practitioners’ perspective (Osterwalder et al. 2010) and reviewing theoretical literature concerning the
innovation process outlined (Zott and Amit 2010; Baden-Fuller and Morgan 2010;
Heikkilä and Heikkilä 2013) reveals that research on tools and methodologies has
mostly focused on the descriptive analysis of existing business models or the rather
qualitative ideation of new ones. To date, the explicit role of tools and methodologies,
both within ordinary and the IoT paradigm, remains unclear.
However, despite the few insights on how to systematically elaborate and evaluate business model designs, particularly within the paradigm of the IoT, it is widely
agreed that a rather iterative evolvement of business models is the most appropriate
means of securing the viability of the business model designs (Sosna et al. 2010). A
practical approach to this is outlined by Blank (2013), who argues that rapid prototyping and the ability to learn from the customer by offering and testing a minimum
viable product (MVP) already in an early stage is the most appropriate in such complex settings. In this context, the term “effectuation” is coined, meaning to evaluate a
prototype business model “in effect” with customer-centric interaction in a test-bed
(Sarasvathy 2001). In a BMI process, effectual evaluation thus takes place after the
decision on developing a first tangible prototype. On the contrary, analytical means of
evaluation primarily stemming from former economic paradigms following a causal
logic, still bear immense potential for the innovation of business models (Bouwman
et al. 2012). However, in light of an integrative framework for IoT business model
innovation, the explicit use and outcomes of causal and effectual means of evaluation
are yet to be explored in greater detail. Furthermore, research widely emphasizes that
novel tools are necessary (Westerlund et al. 2014). The research question for Part III
is therefore formulated as follows:
What is the role of the diverse evaluation tools and methodologies within the
process stages of IoT business model innovation?


8

J. F. Tesch

3 Structure of the Book
The book at hand is written in a cumulative nature to incorporate seven interrelated
studies (see Fig. 1 and Table 1). Thereby, the book is structured in four parts, with the
first and the last framing the context of the innovation of business models in the era of
the Internet of Things. The middle parts of II and III seek to answer the corresponding
research questions as outlined in the previous chapter. Although all studies address
the topic of IoT business model innovation, not all of them were conducted within
the explicit context of IoT projects. Nevertheless, each study contributes to the two
outlined research questions and has important implications for the IoT paradigm. Two
of the studies were published in a scientific journal for Technology and Innovation
Management (TIM), while 2 further studies appear in the proceedings of the European
Conference on Information Systems (ECIS). Two further studies were published in
conference proceedings of the International Society of Professionals in Innovation
Management (ISPIM). Currently, another study is under review.

Part I: Foundations
1 Introduction

2 Theoretical Background

Part II: Decisions and Evaluation Tools in IoT Business Model Innovation
1 IoT Business Model Innovation and the Stage-Gate process: An exploratory analysis (Study 1)
2 The Evaluation Aspect of digital Business Model Innovation: A Literature Review on Tools and
Methodologies (Study 2)

Part III: Studies on the Roles of Tools and Methodologies in IoT BMI
Drawing Analogies as an effectual evaluation
tool for BMI
1 The Business Model Pattern Database – A
Tool for Systematic Business Model Innovation
(Study 3)
2 A Business Model
Perspective on
Innovation
Susceptibility (Study 4)

3 Profit Driving
Patterns for Digital
Business Models
(Study 5)

Customer surveys
as a quantitative
evaluation tool for
IoT BMI
4 The Role of
Quantitative
Evaluation in Digital
Business Model
Innovation: An
Exploratory
Analysis (Study 6)

Scenario Planning
as a causal
evaluation tool for
IoT BMI
5 Discovering the
Role of Scenario
Planning as an
Evaluation
Methodology for
Business Models in
IoT (Study 7)

Part IV: Contributions
1 Findings and results

2 Implications

Fig. 1 Overview of the book structure

3 Concluding Remarks


Introduction

9

Table 1 Overview of studies included in this book
No

Outlet

Status

Ranking

Chapter

Core research
questions

Contribution

#1

International
Journal of
Innovation
Management

Published

B

II.1

What are the
main gates
currently
applied in IoT
business model
innovation?
What criteria
are applied to
make decisions
at each gate?

Identification
of key
decisions and
decision
criteria in
business model
innovations

#2

European
Conference on
Information
Systems 2017

Published

B

II.2

What is the
status quo of
research in
business model
evaluation and
corresponding
tools?
What roles do
evaluation tools
and
methodologies
generally play
in digital
business model
innovation?

Overview and
categorization
of existing
tools and
methodologies
for digital
business model
innovation to
develop a
typology
Elaboration of
an integrative
framework to
evaluate
business
models in IoT
innovation
projects

#3

International
Journal of
Innovation
Management

Published

B

III.1

What are
recurring
archetypes of
successful
business model
innovations?
What
implications
can be drawn
from analogies
for systematic
business model
innovations?

Elaboration of
the first
structured,
holistic
database of
business model
patterns as a
tool for
systematic
business model
innovation

#4

ISPIM
Innovation
Forum 2017

Published

n/a

III.2

How can
‘innovation
susceptibility’
be identified to
trigger the
transformation
of business
models for
incumbents?

Provision of a
strategic-choice
view on
business model
innovation and
development of
a tool for
systematic
ideation in
business model
innovation
(continued)


10

J. F. Tesch

Table 1 (continued)
No

Outlet

Status

Ranking

Chapter

Core research
questions

Contribution

#5

ISPIM
Innovation
Summit 2016

Published

n/a

III.3

Which business
model patterns
directly drive
the profitability
of firms?

Categorization
of relevant
patterns and
criteria for
application

#6

International
Journal of
Innovation
Management

Under review

(B)

III.4

What is the
potential role of
customer
surveys in IoT
business model
innovation?

Methodological
approach to
incorporate
conjoint
analysis in IoT
business model
innovation and
insights from a
smart home
case

#7

European
Conference on
Information
Systems 2016

Published

B

III.5

What is the
potential role of
scenario
planning in IoT
business model
innovation?

Methodological
approach to
incorporate
scenario
planning in IoT
business model
innovation and
insights from a
smart home
case

Note The ranking is based on the VHB Jourqual 3 ranking. Parentheses indicate that the study is in review

Part I starts with the general motivation stemming from both scientific and practical aspects for the overall research project. Based on the overall goal towards an
enhanced understanding of IoT business model innovation, theoretical background
information and identified avenues for scholars, two major research questions are
elaborated. The chapter sets the research project in the context of the application
within IoT business model innovation projects. Further, the structure and logical
interrelation of the studies is explained. Subsequently, an overview and classification of the studies in the context of the Philosophical sciences is provided. The part
closes with an overview on anticipated contributions to science and practice.
With a total of 7 studies, Parts II and III depict the core of the cumulative book. As
Schneider and Spieth (2013) outline, research in business model innovation may be
located at the intersection of Information Systems (IS), Technology and Innovation
Management (TIM) and Strategic Management. The studies in these parts were published in outlets of corresponding research communities. Part II answers the research
question on how business models may be systematically developed and innovated in
the era of the Internet of Things. In order to contribute, Study 1 elaborates on evidence of several IoT cases on decision making and decision points. In that manner,
Study 1 seeks to retrospectively analyze how decisions were made, what facts drove
the decision making and what role means of evaluation played to prepare a decision. Study 2 reviews the state of existing tools and methodologies and investigates
on their use and outcomes within past projects. Combined with the insights gained


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