Business model innovation in the era of the internet of things

110 A Business Model Perspective on Innovation Susceptibility Table 1 Overview on activities following a design science research approach.. 200Scenario Planning as a Causal Evaluation To

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

Business Model Innovation

in the Era of the Internet

of Things

Studies on the Aspects of Evaluation,

Decision Making and Tooling

123

Library of Congress Control Number: 2018955918

© Springer Nature Switzerland AG 2019

This work is subject to copyright All rights are reserved by the Publisher, whether the whole or part

of the material is concerned, speci fically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on micro films or in any other physical way, and transmission

or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed.

The use of general descriptive names, registered names, trademarks, service marks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use.

The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made The publisher remains neutral with regard to jurisdictional claims in published maps and institutional af filiations.

This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

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

Dissertation Georg-August Universität Göttingen, 2017

The ability to establish novel business models is essential to ensuring the ongoingsuccess of traditional corporations in a digital era, but novel business models arealso a major theme for startups and SMEs However, business model innovationposes tremendous challenges, particularly in technology-driven industries Despitethe salience of these well-known challenges, present innovation processes do not

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 entitieswhich foster the systematic exploration of new business opportunities and whichprovide an excellent foundation for strategic management decisions

Since joining the Bosch Group in 2011, Dr Jan F Tesch has taken on severalroles in which he has supported the expansion of the business portfolio of variousbusiness units into the digital space In addition, Dr Tesch has had the opportunity

systematic business model innovation, and he has contributed to an enhanced

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

This book serves as a synthesis of seven individual studies dealing with theintersection of research and practice The work outlines an innovation frameworkfor developing IoT-based business models built upon the learnings and insightsgenerated throughout the course of several innovation projects Furthermore, Dr.Tesch introduces novel tools, methods, and best practices to help business modelconsultants support the decision-making of senior management

Stuttgart, Germany

October 2017

Senior Vice President,Head of Corporate Business ModelInnovation, Robert Bosch GmbH

v

The emerging paradigm of the so-called Internet of things (IoT) represents anoverwhelming 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

key to understand the intersection of economics, strategic management,

time, however, it was not clear to me how these subjects merge together as a

Ph.D was to combine the individual knowledge and thus to contribute to anenhanced, interdisciplinary understanding Furthermore, the book at hand also seeks

at providing business model innovation professionals with best practice tools fordecision-making based on experiences in IoT projects

I am deeply thankful that I got the exceptional opportunity to pursue thisendeavor at both Robert Bosch GmbH and at the Chair of Information Management

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

and Prof Dr Indre Maurer for the supervision of the thesis Also, I would like to thank

giving me the chance to pursue this endeavor within the business unit SoftwareInnovations at Bosch Furthermore, my deepest thankfulness is to my departmentsupervisor Dr Marco Lang, who has given me invaluable support, freedom of scope,

vii

and valuable advice Within the Robert Bosch GmbH, I would like to thank

continue working on IoT topics within the newly founded corporate department forBusiness 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 Uwe C M Kirschner, and Miriam Lehmbrink, for the excellent and fruitfulcooperation In the same manner, I would like to thank the students who havewritten their graduation thesis under my supervision, Benedikt Freiherr von

valuable contribution to the overall research project Particular thanks for theirexcellent ideas, thoughts, and dedication to our joint research on IoT businessmodel innovation go to Anne-Sophie Brillinger and Dominik Bilgeri I stronglybelieve that our spirit of working as a team and putting the greater goal above

Apart from all the aforementioned, I would like to thank my colleagues from theChair of Information Management for the excellent working atmosphere and the

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

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 pened, 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

right thing to do, even if it meant a high degree of their own abstinence Withouttheir invaluable commitment and endless love, none of our prosperities would havebeen even close to be achieved

Jan F Tesch

Part II Decisions and Evaluation in IoT Business Model Innovation

IoT Business Model Innovation and the Stage-Gate Process 51

Jan F Tesch, Anne-Sophie Brillinger and Dominik Bilgeri

The Evaluation Aspect of Digital Business Model Innovation 67

Jan F Tesch and Anne-Sophie Brillinger

Part III Studies on the Roles of Tools and Methodologies in IoT BMI

The Business Model Pattern Database: A Tool

for Systematic BMI 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

ix

Scenario Planning as a Causal Evaluation Tool for IoT Business

ADR Action design research

xi

Fig 1 Overview of the book structure 8Theoretical Background

Fig 1 Overview on components of business models from literature

Adapted from Krumeich et al (2012) 24Fig 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) 26Fig 3 The activity system design framework Source Zott and Amit

(2010) 27Fig 4 The RCOV framework Source Demil and Lecoq (2010) 28Fig 5 Identified phases (synthesis) of business model innovation

(own representation) Note Italic font indicates implicit mention

in the original source 34Fig 6 IoT technology stack (based on Porter and Heppelmann

2014, p 7; Wortmann and Flüchter 2015, p 223) 38Fig 7 Value creation layer (based on Fleisch et al 2015) 41IoT Business Model Innovation and the Stage-Gate Process

Fig 1 Two decision points and their occurrence on the

BMI timeline 59The Evaluation Aspect of Digital Business Model Innovation

Fig 1 Overview of the search process (own representation) 72Fig 2 Logic and criteria of evaluation research articles

(own representation) 74The Business Model Pattern Database: A Tool for Systematic BMI

Fig 1 Taxonomy development method

(Nickerson et al 2013, p 345) 101

xiii

Fig 2 Development of dimensions for the business model

pattern taxonomy 102Fig 3 Dimensions, characteristics, and number of business

model patterns per characteristic 107

A Business Model Perspective on Innovation Susceptibility

Fig 1 Phases of the business model innovation process Adapted

from Frankenberger et al (2013) 149Fig 2 General methodological approach 151Fig 3 Action design research to design, development, and valuation

of the artifact Adapted from Sein et al (2011) 153Fig 4 Strategic perspective on innovation potential in the market 161Profit Driving Patterns for Digital Business Models

Fig 1 The research design 168Fig 2 Procedure of data analysis based on Creswell’s data analysis

spiral (1998) 169Customer Surveys as a Quantitative Evaluation Tool for Digital BMI

Fig 1 The Internet of Things-products-services logic Adapted

from Fleisch et al (2015) 180Fig 2 Smart Home BM adapted from Tesch (2016) and

Osterwalder et al (2010) 190Fig 3 Identification of solution features and attributes 192Fig 4 Viable business models for addressing Customer Segments

1 and 2 in the schemed by value network diagrams

(Bilgeri et al 2015) (Simplified) 199Scenario 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) 215Fig 2 Overview of the business model Adapted from

Osterwalder et al (2010) 219Fig 3 Driving factors from PESTE analysis for the smart home case,

illustrated by the impact uncertainty grid (Schoemaker and

van der Heijden 1992) 221Fig 4 Using correlations between driving factors to identify scenario

dimensions (simplified) 222Fig 5 Key scenarios for the smart home platform and identified

key success factors (KSF) to differentiate from potential

competitors 222

Fig 6 Stakeholder network diagram (Bilgeri et al 2015) for the

“lifestyle” (left) and the “hidden revenue” (right) smart home

scenario 223Implications—An Integrative Framework for IoT Business

Model Innovation

Fig 1 The integrated framework for IoT business model innovation 246

Table 1 Overview of studies included in this book 9

Table 2 Overview of research design of studies included in this book 12

Table 3 Overview of anticipated contributions to research 14

Table 4 Overview of anticipated contributions to practice 15

Theoretical Background Table 1 Definitions of the term “business model” 21

Table 2 Perspectives on business models 23

Table 3 Overview on components of business models (Osterwalder et al 2010, pp 20–21) 25

Table 4 Definitions of business model innovation 31

Table 5 Summary of the identified 21 IoT business model patterns by Fleisch et al (2015) 41

IoT Business Model Innovation and the Stage-Gate Process Table 1 List of case studies and interview partners 57

Table 2 Two main decision points and underlying criteria 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 93

Table 2 Definitions of business model patterns 95

Table 3 Research design overview 97

Table 4 Original sources of business model patterns 98

xvii

Table 5 Reviews of business model pattern literature 105Table 6 Usage of the pattern database during the business model

innovation process 110

A Business Model Perspective on Innovation Susceptibility

Table 1 Overview on activities following a design science research

approach 154Table 2 Detailed overview of the innovation levers 156Profit Driving Patterns for Digital Business Models

Table 1 Leading questions for the interview 168Table 2 Summary of the identified 21 IoT patterns including

the nine profit driving patterns 170Customer Surveys as a Quantitative Evaluation Tool for Digital BMI

Table 1 Phases of digital BMI processes (based on Tesch

and Brillinger 2017, p 10) 182Table 2 Overview on publications applying conjoint analysis in context

of business model innovation 186Table 3 Conjoint Survey Results Sheet 194Table 4 Overview of business model choice options 200Scenario 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) 216Table 2 Overview of the key steps of the scenario-planning artefact 218Findings and Results

Table 1 Integratedfindings of Study 1 and 2: framework to innovate

business models in the era of the internet of things (IoT) 236Table 2 Integratedfindings: the roles of BM evaluation methodologies

in the era of the IoT 240Implications—An Integrative Framework for IoT Business Model

Innovation

Table 1 Overview of major contributions to research 244Table 2 Features of the phases of the integrative IoT business model

innovation framework 248

Part I

Foundations

Part I of this cumulative dissertation comprises two chapters It begins with anintroduction of the emerging economic paradigm of the Internet of things (IoT) and

Subsequently, the theoretical background gives an overview of the relevant

research contribution

Jan F Tesch

The following chapter outlines the motivation of the research endeavour, followed byconcrete research gaps and research questions Afterwards, the introduction provides

an overview of the structure of the book, further elaborates on the research designand anticipated contributions

In the wake of rapid advances in information technology (IT) and the increasingpervasiveness of digitalization, today’s companies are facing highly dynamic busi-

of Things (IoT) is seen as the major driver of economical and societal changes in the

everyday-life “things” get equipped with computational capability and internet

with sensors, actuators, computing and connectivity units to become smart

this sense, the Internet of Things enables a variety of innovative ways of offeringnew value propositions to customers, suppliers and partners: in other words, multiplethings 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

Hence, especially with costs for computing and connectivity declining tremendously,

Looking at historical situations when potentially disruptive technologies emerged,firms were challenged to develop new ways of delivering value to customers (Ches-

understood by incumbents As an illustrative example, companies such as Nokia or

signifi-cant loss in market share Despite having developed the superior technology withintheir R&D-departments, these incumbents failed to speed up the redesign of value

proposition to the customer became inferior compared to those of emerging

mar-ket 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

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

such as Amazon, Microsoft, IBM or SAP, players in traditional physical industriesare urged to develop new ways of creating and capturing value Recent research,

that once viewed from a purely technological perspective, major enabling factors ofbusiness success are considered increasingly within the orchestration of ecosystems

of partners and multilateral value chains The emerging paradigm of the IoT leads to achange from the traditional world of business—characterized by stability and linearvalue chains—to an emerging realm of digital business, which is more complexand distinguished by increasing levels of uncertainty and multilateral value chainnetworks 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

Within science, researchers already widely investigated managerial aspects ofcases of companies struggling in situations when changes in their ecosystems arise

advancements as discussed above, changes in political, economic, societal, ecologic

or legislative circumstances (PESTEL) may be cause for a shift in market conditionsfostering the incumbent’s need to innovate its business model (Osterwalder et al

their potential outcomes can lead to “white spots” and thus failing to initiate aninnovation process altering the incumbent’s business model adequately (Christensen

innovation potential of such new business opportunities may not only imply a missedgrowth opportunity, but also a threat to the core business as a leverage point forcompetitor firms or new market entrants to disrupt the incumbent’s business model

In sum, the emergence of the Internet of Things represents a new economicparadigm to corporations and start-ups, which bears the potential to offset tradi-tional rules of competition among several markets and industries This challengesincumbents to initiate and execute adequate processes to change their way of doingbusiness, i.e the innovation of an incremental, radical, or even disruptive new busi-ness model Thereby, both researchers and practitioners emphasize a gap in the aspect

develop-ment (NPD), where there are several established methodologies for dealing with

of value, and the interplay between business partners becomes increasingly

the Internet of Things, the validity of acknowledged means of evaluation stemmingfrom traditional strategic management, i.e tools, methodologies and procedures, arequestioned under this newly arising economic paradigm

Motivation of the dissertation project is to shed light upon the role of tools andmethodologies that might foster the evaluation aspect of IoT business model inno-vation In a scientific manner, the book aims to investigate the characteristics ofhow firms may systematically innovate their business models subject to the arisingprerequisites as schemed above To make a significant contribution, the dissertation

busi-ness models, who state that the innovation process consists of strategic and tactical

choices Drawing from this perspective bears the opportunity to elaborate an

inte-grative 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 tioners, particularly for professionals in business model innovation, the dissertationproject seeks to provide guidance to when and how decisions in a BMI process arebest made Particularly, with the elaborated tools and methodologies supporting thedecision making, the dissertation project endeavors to enable professionals to con-tribute to a firm’s success with an enhanced ability to evaluate and predict futurebusiness models within an innovation project

Within existing research on business model innovation, three previously fied research streams are bearing significant opportunities to contribute to research

pro-cess and elements of business model innovation, and (3) effects of business model

on the role of tools and methodologies within business model innovation processes,particularly, the second stream emphasizes the scientific field of BMI research cor-responding to the outlined motivation stemming from the emergence and influence

of the new economic paradigm around the Internet of Things

Within the second research stream (Schneider and Spieth2013), previous researchmainly dealt with the qualitative exploration of the overall process of BMI In particu-lar, the continuous discovery-driven and learning-oriented characteristics were inves-

iden-tification of business opportunities for the initiation of BMI or its design and the

particular markets and industries However, despite their valuable findings in severalcases, the authors emphasize the importance of pursuing research on BMI in othercontexts to then contribute to generalization attempts The findings explicitly statethat different types of BMI need to be distinguished Additionally, the continuation

to seek an enhanced understanding of the possibility to support firms throughout theprocess is crucial for further BMI research This is due to the challenging nature ofbusiness model innovation both scholars and practitioners are facing

under-standing of the process and elements of business model innovation for future research

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 modelinnovation and in particular concerning the elements comprising business modelinnovation, the main objective of further research in this field should be to pro-vide analytical support for business model innovation’s discovery-driven process”

studies have already provided initial insights on the influence of the Industrial Internet

of Things (IIoT) on existing business models of manufacturing incumbents (Arnold

large-scale insights on the innovation process (a) and support methods (c) remain largelyunclear

In terms of the research field of the BMI process and elements in the specific text of the IoT (a), the aspect of decision-making as recurring characteristics depicts apromising field of analysis Other than existing approaches to derive a process model

view on key decisions in IoT may serve as a separator between different ‘stages’ ofevaluation Learnings from the decision behavior itself may then draw insights onkey factors and aspects, which in turn allows for a derivation on requirements for

means supporting the decision making An integrative framework to structure theprocess of the new type of IoT business models helps both scholars and practitioners

to understand how “new network- and activity system–based value creation nisms” can be utilized “to achieve the sources of competitive advantage” (Zott et al

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 allowsfor a better understanding of the systematic applicability and use of existing BMItools and methodologies in the different stages of IoT business model innovation (c)

indicate that only some publications deal with the aspect of evaluating business els as a part of an innovation process Corresponding to the research question in Part

mod-II, several researchers highlight the importance of continuous business model

Analyzing the various aspects of business model innovation from a practitioners’

mostly focused on the descriptive analysis of existing business models or the ratherqualitative 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 ate business model designs, particularly within the paradigm of the IoT, it is widelyagreed that a rather iterative evolvement of business models is the most appropriate

proto-typing and the ability to learn from the customer by offering and testing a minimumviable product (MVP) already in an early stage is the most appropriate in such com-plex settings In this context, the term “effectuation” is coined, meaning to evaluate aprototype business model “in effect” with customer-centric interaction in a test-bed

decision on developing a first tangible prototype On the contrary, analytical means ofevaluation primarily stemming from former economic paradigms following a causallogic, still bear immense potential for the innovation of business models (Bouwman

innovation, the explicit use and outcomes of causal and effectual means of evaluationare yet to be explored in greater detail Furthermore, research widely emphasizes that

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?

3 Structure of the Book

The book at hand is written in a cumulative nature to incorporate seven interrelated

first and the last framing the context of the innovation of business models in the era ofthe Internet of Things The middle parts of II and III seek to answer the correspondingresearch questions as outlined in the previous chapter Although all studies addressthe topic of IoT business model innovation, not all of them were conducted withinthe explicit context of IoT projects Nevertheless, each study contributes to the twooutlined research questions and has important implications for the IoT paradigm Two

of the studies were published in a scientific journal for Technology and InnovationManagement (TIM), while 2 further studies appear in the proceedings of the EuropeanConference on Information Systems (ECIS) Two further studies were published inconference proceedings of the International Society of Professionals in InnovationManagement (ISPIM) Currently, another study is under review

1 IoT Business Model Innovation and the Stage-Gate process: An exploratory analysis (Study 1)

Part II: Decisions and Evaluation Tools in IoT Business Model Innovation

Part I: Foundations

1 Introduction 2 Theoretical Background

Part IV: Contributions

1 Findings and results 2 Implications 3 Concluding Remarks

Part III: Studies on the Roles of Tools and Methodologies in IoT BMI

2 The Evaluation Aspect of digital Business Model Innovation: A Literature Review on Tools and

Methodologies (Study 2)

Drawing Analogies as an effectual evaluation

tool for BMI

1 The Business Model Pattern Database – A

Tool for Systematic Business Model Innovation

(Study 3)

3 Profit Driving Patterns for Digital Business Models

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)

Fig 1 Overview of the book structure

Table 1 Overview of studies included in this book

No Outlet Status Ranking Chapter Core research

What criteria are applied to make decisions

at each gate?

Identification

of key decisions and decision criteria in business model innovations

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

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

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)

of firms?

Categorization

of relevant patterns and criteria for application

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

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 tical aspects for the overall research project Based on the overall goal towards anenhanced understanding of IoT business model innovation, theoretical backgroundinformation and identified avenues for scholars, two major research questions areelaborated The chapter sets the research project in the context of the applicationwithin IoT business model innovation projects Further, the structure and logicalinterrelation of the studies is explained Subsequently, an overview and classifica-tion of the studies in the context of the Philosophical sciences is provided The partcloses 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

located at the intersection of Information Systems (IS), Technology and InnovationManagement (TIM) and Strategic Management The studies in these parts were pub-lished in outlets of corresponding research communities Part II answers the researchquestion on how business models may be systematically developed and innovated inthe era of the Internet of Things In order to contribute, Study 1 elaborates on evi-dence 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 drovethe decision making and what role means of evaluation played to prepare a deci-sion 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

through Study 1, an enhanced understanding on how tools and methodologies areused within IoT business model innovation is fostered Hence, several stages of IoTbusiness model innovation process are identified, with a clear implication on howtools may effectively and efficiently contribute to a robust business model design.Furthermore, identified avenues for further research guide the path for the subsequentpart of the book.

Based on these findings, which sets a solid foundation to discover the differentaspects of evaluation means, Part III represents a systematic endeavor to elaborateand test novel tools To answer the research question on the role of the diverse eval-uation tools and methodologies within the process of IoT business model innovation

as outlined above, three dominant modes of business model evaluation are fied: effectual evaluation, quantitative (causal) and qualitative (causal) For each ofthese modes, a corresponding tool is elaborated and tested in real-world IoT inno-vation projects The explorative and iterative use, testing, validation and redesign oftools and methodologies lead to a robust functionality the invented tool/methodology

anticipates to investigate on business model patterns as a means of systematicallydrawing analogies from past BMI projects Thereby, Study 3 invents the first holisticdatabase of identified business model patterns, and further proposes a taxonomy inorder to structure the field Based on these groundworks, Study 4 elaborates on BMIlevers, as a sorting dimension of patterns from a strategic choices view (Casadesus-

analytical stage of IoT BMI Study 5 investigates the role of patterns in a stage of IoTprojects, which has the overall aim to scale and roll-out the business model into at

view on the use of effectual means throughout all stages of an IoT business model

by being the first of its kind to applying conjoint analysis to an analytical strategicchoices stage of BMI within a single case Study (study 6) For the investigation on

tool with an action design research approach and sheds light upon its use based onevidence from 3 IoT innovation projects

Finally, Part III closes the book by reflecting the theoretical findings and tions of the combined studies within the IoT paradigm Subsequently, an integrativeframework is elaborated in order to make the findings directly accessible to practi-tioners and business model innovation professionals The book ends with concludingremarks, considering limitations and avenues for future research

The field of research on business models and business model innovation is of ciplinary nature, as it may be located in the intersection of Information Systems (IS),Technology and Innovation Management (TIM) and Strategic Management (Zott

necessary to consider a variety of research designs and methods (Veit et al.2014;

chap-ters of the book sequentially build upon the findings of each other, the data collectionfor providing evidence was required to be completed individually for each study An

In general, next to the choice of an adequate methodology, a research approachencompasses the epistemological positioning as a further element (Becker et al

Table 2 Overview of research design of studies included in this book

question(s)

Epistemology Paradigm Methodology Data coll Data analysis

Expert interviews

Literature

104)

Data analysis with concept matrices

Mixed-methods approach

Literature

28)

Taxonomy building

Mixed-methods approach

Structured secondary data collection

Coding and design science research

Single case study

Cross-sectional conjoint survey

Confirmatory case study methodology

Action design research

User interviews

Confirmatory multiple case study methodology

objective truth (Hudson and Ozanne 1998), and it is also independent from the

real-ity is constructed socially and depends on experiences of the researcher As thedissertation project seeks to uncover explanations and guidance for scholars andprofessionals universally valid in IoT business model innovation, all studies under-gone are of positivistic nature

Next to epistemology, two different research paradigms for scientific studies can

justifying theories, principles and laws, explaining and predicting how humans areanalyzing and managing tasks, technologies and resources On the other hand, itseeks to design science research, which aims at building artifacts providing utility by

science paradigm, the major objective lies within the analysis on the effectiveness

of the created artifact As Part II of the dissertation project was designed to set

a knowledge base for further scientific investigations upon business model toolsand methodologies, both Study 1 and 2 follow a behavioral science approach Withthis foundational understanding on causal and effectual logics of evaluation, PartIII continues with exploratory and explanatory research approaches to discover therole of tools and methodologies In this part, the research studies underlie both thedesign and behavioral oriented paradigm The evaluation tools are to be created anddesigned corresponding to the requirements of the features of IoT business models(design oriented paradigm), and their use and effectiveness must be observed inreal-world contexts (behaviorally oriented paradigm)

Both research paradigm and epistemology determine the choice of an adequate

combines exploratory and explanatory research methods, i.e a mixed methodsapproach, in order to secure tangible findings into the research inquiry (Venkatesh

eco-nomic sciences and the overall approach follows a pluralistic research design

Although several researchers have emphasized the importance of BMI in IoT,

prac-titioners also lack understanding of the role of business model innovation in the era

of the Internet of Things, resulting in a slow spread of technological advancements

To date, only little research has been conducted on how companies might

Further-more, the authors claim that novel tools are necessary In line with that, Zott et al

Information Systems (IS), Technology and Innovation Management (TIM) and

Table 3 Overview of anticipated contributions to research

Main purpose of the discipline towards business model research (Zott et al.

2011, p 23)

Anticipated research contribution of the book

internet-based ways of “doing business”

To offer typologies or taxonomies”

To explain gestalts of emerging IoT-based business models

To uncover typologies of prevailing patterns within IoT-based business models

activity system–based value creation mechanisms and sources of competitive advantage”

To provide an understanding

on cause and effects of systematic value creation within the economic paradigm

of the IoT

To explain how companies may systematically innovate business models in order to develop competitive advantages and to capture value thereof

Technology and innovation

management

“To understand how technology is converted into market outcomes”

To provide insight how BM tools and methodologies may help to convert new technologies into differentiating competitive advantages

models as a part of an innovation process Major research gaps in this field havebeen identified, as there are “limited insights on criteria and metrics for an appro-priate evaluation of business models.” Furthermore, no “tool for the management

of business model can be found so far, neither for visualization, evaluation or

a nutshell, “understanding, explaining, predicting, and designing IT-based businessmodels holds immense contributions to both research and the business community”

by describing new gestalts of emerging IoT-based business models

Within strategic management, there is insufficient testimony regarding the

the same time, the importance of identifying the target customer and a tion concerning its value propositions is emphasized as a way to gain more preciseassumptions for the business case calculation as a decision basis for management

propo-sitions are also assumed to be crucial for designing partner roles in business model

Table 4 Overview of anticipated contributions to practice

• To provide an integrative framework considering characteristics of different phases of IoT business models, prevailing decision points, and major aspects driving decision-making as a guideline for management

• To review the use, effectiveness, impact and outcome of different types of tools and

methodologies regarding their respective of the different characteristics of IoT business model innovation processes

• To elaborate and validate novel tools and methodologies specifically designed to enable consultants and BMI professionals to develop and evaluate novel business models in the IoT era

to contribute with an enhanced understanding on systematic value creation withinIoT ecosystems

Towards Technology and Innovation Management, iterative trial-and-error uation is a means of counteracting the lack of information about future market con-

eval-uation are especially high for complex BMI with great uncertainty, particularly indisruptive BMI’s Thus, funding for prototypal evaluation may only be released ifmanagement receives some kind of analytical pre-evaluation of the business modelinnovation project This implies the necessity of novel, analytical means of evalua-tion at an early point in time within the BMI process However, in both the theory andpractice of innovation processes, it is emphasized that the aspect of analytical assess-ment of business model ideas is often based on less scrutinized assumptions (Wirtz

understanding upon timing and means of BMI evaluation, particularly when in thecontext of the complexity of overcoming mutual interdependencies (chicken-and-egg-problem) that come with digitalization and the Internet of Things (Bilgeri et al

and methodologies for business modeling can help to convert new technologies intocompetitive advantages

Additionally, the book also aims at contributing to a practitioner’s audience

business model innovation in the IoT era

References

Andersson, P., & Mattsson, L.-G (2015) Service innovations enabled by the “internet of things”.

IMP Journal, 9(1), 85–106.

Arnold, C., Kiel, D., & Voigt, K.-I (2016) How the industrial internet of things changes business

models in different manufacturing industries International Journal of Innovation Management,

20(08), 1640015.

Atzori, L., Iera, A., & Morabito, G (2010) The internet of things: A survey Computer Networks,

54(15), 2787–2805.

Baden-Fuller, C., & Morgan, M S (2010) Business models as models Long Range Planning,

43(2–3), 156–171.

Becker, J., Grob, H L., Klein, S., Kuchen, H., Müller-Funk, U., & Vossen, G (2003).

Forschungsmethodische Positionierung in der Wirtschaftsinformatik, Arbeitsbericht.

Bilgeri, D., Wortmann, F (2017) Barriers to IoT business model innovation In J M Leimeister

& W Brenner (Hrsg.), Proceedings der 13 Internationalen Tagung Wirtschaftsinformatik (WI

Bouwman, H., de Reuver, M., Solaimani, S., Daas, D., Haaker, T., Janssen, W., Iske, P., &

Walenkamp, B (2012) Business models tooling and a research agenda Bled eConference, Vol 25.

Bucherer, E., Eisert, U., & Gassmann, O (2012) Towards systematic business model innovation:

Lessons from product innovation management Creativity and Innovation Management, 21(2),

183–198.

Burkhart, T., Krumeich, J., Werth, D., & Loos, P (2011) Analyzing the business model concept—A

comprehensive classification of literature In ICIS 2011 Proceedings, no 12 (pp 1–19), Shanghai,

China.

Carson, D., Gilmore, A., Perry, C., & Gronhaug, K (2001) Qualitative marketing research London:

Sage.

Casadesus-Masanell, R., & Ricart, J E (2010) From strategy to business models and onto tactics.

Long Range Planning, 43(2–3), 195–215.

Chanal, V., & Caron-Fasan, M L (2010) The difficulties involved in developing business models

open to innovation communities: The case of a crowdsourcing platform Management, 13(4),

El Sawy, O A., & Pereira, F (2013) Business modelling in the dynamic digital space: An ecosystem

approach, SpringerBriefs in digital spaces Berlin, New York: Springer.

Fleisch, E (2010) What is the internet of things? An economic perspective Economics,

Manage-ment & Financial Markets, 5(2), 125–157.

Frankenberger, K., Weiblen, T., Csik, M., & Gassmann, O (2013) The 4I-framework of business

model innovation: A structured view on process phases and challenges International Journal of

Product Development, 18(3/4), 1–18.

Ghazawneh, A., & Henfridsson, O (2015) A paradigmatic analysis of digital application

market-places Journal of Information Technology, 30(3), 198–208.

Hagiu, A (2014) Strategic decisions for multisided platforms MIT Sloan Management Review,

55(2), 71.

Heikkilä, M., & Heikkilä, J (2013) Collaborative business model innovation process for networked

services Co-created effective, agile, and trusted eServices (pp 133–147).

Hevner, A R., March, S T., Park, J., & Ram, S (2004) Design science in information systems

research MIS Quarterly: Management Information Systems, 28(1), 75–105.

Hudson, L., & Ozanne, J (1998) Alternative ways of seeking knowledge in consumer research.

Journal Consumer Research, 14(4), 508–521.

Johnson, M W., Christensen, C M., & Kagermann, H (2008) Reinventing your business model.

Harvard Business Review, 86(12), 57–68.

Laudien, S M., Daxböck, B (2016a) Business model innovation processes of average market

players A qualitative-empirical analysis R&D Management.

Laudien, S M., & Daxböck, B (2016b) The influence of the industrial internet of things on business

model design: A qualitative-empirical analysis International Journal of Innovation Management,

20(8), 1640014.

Lee, I., & Lee, K (2015) The internet of things (IoT) Applications, investments, and challenges

for enterprises Business Horizons, 58(4), 431–440.

Lucas, H C., & Goh, J M (2009) Disruptive technology: How Kodak missed the digital

photog-raphy revolution The Journal of Strategic Information Systems, 18(1), 46–55.

Markides, C (2006) Disruptive innovation In need of better theory* Journal of Product Innovation

Management, 23(1), 19–25.

Massa, S., & Testa, S (2011) Beyond the conventional-specialty dichotomy in food retailing

business models: An Italian case study Journal of Retailing and Consumer Services, 18(5),

476–482.

McGrath, R G (2010) Business models: A discovery driven approach Long Range Planning,

43(2–3), 247–261.

Miorandi, D., Sicari, S., de Pellegrini, F., & Chlamtac, I (2012) Internet of things: Vision,

appli-cations and research challenges Ad Hoc Networks, 10(7), 1497–1516.

Osterwalder, A., Pigneur, Y., & Clark, T (2010) Business model generation: A handbook for

visionaries, game changers, and challengers (1st ed.) Hoboken, NJ: Wiley.

Porter, M E., & Heppelmann, J E (2014) How smart, connected products are transforming

com-petition Harvard Business Review, 92(11), 11–64.

Rai, A., & Tang, X (2014) Research commentary—Information technology-enabled business

mod-els: A conceptual framework and a coevolution perspective for future research Information

Sys-tems Research, 25(1), 1–14.

Rifkin, J (2014) The zero marginal cost society The internet of things, the collaborative commons,

and the eclipse of capitalism.

Sarasvathy, S D (2001) Causation and effectuation: Toward a theoretical shift from economic

inevitability to entrepreneurial contingency Academy of Management Review, 26(2), 243–263.

Schneider, S., & Spieth, P (2013) Business model innovation Towards an integrated future research

agenda International Journal of Innovation Management, 17(01), 1–35.

Smith, W K., Binns, A., Tushman, M L (2010) Complex business models: Managing strategic

paradoxes simultaneously Long Range Planning, 43(2–3), S 448–461.https://doi.org/10.1016/ j.lrp.2009.12.003.

Sosna, M., Trevinyo-Rodríguez, R N., & Velamuri, S R (2010) Business model innovation through

trial-and-error learning: The Naturhouse Case Long Range Planning, 43(2–3), 383–407 Teece, D J (2010) Business models, business strategy and innovation Long Range Planning,

43(2–3), 172–194.

Veit, D., Clemons, E., Benlian, A., Buxmann, P., Hess, T., Kundisch, D., et al (2014) Business

models Business & Information Systems Engineering, 6(1), 45–53.

Venkatesh, V., Brown, S A., & Bala, H (2013) Bridging the qualitative-quantitative divide:

Guide-lines for conducting mixed methods research in information systems Management Information

Systems Quarterly, 37, 21–54.

Westerlund, M., Leminen, S., & Rajahonka, M (2014) Designing business models for the internet

of things Technology Innovation Management Review, 4(7), 5–14.

Wieringa, R (2009) Design science as nested problem solving In Proceedings of the 4th

Interna-tional Conference on Design Science Research in Information Systems and Technology (pp 1–12).

Wirtz, B W., Schilke, O., & Ullrich, S (2010) Strategic development of business models:

Impli-cations of the Web 2.0 for creating value on the internet Long Range Planning, 43(2), 272–290.

Wirtz, B W., Pistoia, A., Ullrich, S., & Göttel, V (2016) Business models: Origin, development

and future research perspectives Long Range Planning, 49(1), 36–54.

Yoo, Y (2013) The tables have turned: How can the information systems field contribute to

technol-ogy and innovation management research? Journal of the Association for Information Systems,

14, 227–236.

Yunus, M., Moingeon, B., Lehmann-Ortega, L (2010) Building social business models: Lessons

from the Grameen experience Long Range Planning, 43(2–3), S 308–325.

Zott, C., & Amit, R (2010) Business model design: An activity system perspective Long Range

Planning, 43(2–3), 216–226.

Zott, C., & Amit, R (2013) The business model: A theoretically anchored robust construct for

strategic analysis Strategic Organization, 11(4), 403–411.

Zott, C., Amit, R., & Massa, L (2011) The business model Recent developments and future

research Journal of Management, 37(4), 1019–1042.

Jan F Tesch

This chapter provides an overview of the foundations of the underlying theoretical

business models is briefly introduced Next, background on business model

innova-tion—as a transformational perspective on business models—is outlined, followed

by the paradigm of the Internet of Things (IoT) The chapter concludes by laying out

a synthesized understanding

The terminology around business models (BM) emerged as buzzwords in various

com-mon high-level understanding of business models is their function as an

models’ importance to both scholars and practitioners has been rising precipitouslyever since the topic emerged The terminology was, therefore, particularly shaped

by practical investigations concerning the core logic of how (dot-com) companies

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_2

19

The term has since been subjected to broader scientific scrutiny (Al-Debei et al.

no consensus on a universally valid definition has been reached Nonetheless, as Wirtz

converging, especially in recent years In the following section, the state of businessmodel research is outlined to provide a broad overview of the theoretical foundationsunderpinning business models Several researchers from various fields have profferednumerous definitions Using these definitions as a foundation, this chapter outlines

researchers based on their scientific perspectives

1.1 Definitions

publica-tions in the field of business models

Several similarities and overlaps exist among the various definitions, which can

often be traced back to the different perspectives on business models (Gassmann

models in Long Range Planning, a revived journal edited by Charles-Baden-Fuller,

noted a milestone of a converging scientific consensus concerning business modelterminology The different perspectives are discussed in the following subsection

1.2 Perspectives on Business Models

Various research contributions to the phenomenon of business models were often

a result of differing perspectives on the terminology itself The initial focus ofresearchers mainly was on viewing business models from a strategy perspective—Therole of business models was perceived as an intermediator between strategy and

technology, such as digitalization, also caused academics to consider other tives, as the phenomenon’s increasingly complex aspects could not be adequately

per-spective of viewing business models as a set of components has emerged as the

to make the concept more tangible and thus comprehensible Having a particular

Table 1 Definitions of the term “business model”

Al-Debei and Avison ( 2010 ), p 373 “[…] abstract representation of an

organization, be it conceptual, textual, and/or graphical, of all core interrelated architectural, co-operational, and financial arrangements designed and developed by an organization presently and in the future, as well as all core products and/or services the organization offers, or will offer, based on these arrangements that are needed to achieve its strategic goals and objectives”

interdependent activities that transcends the focal firm and spans its boundaries”

Baden-Fuller and Morgan ( 2010 ), p 168 A business model is a ‘model’ or the ‘logic’ of

how firms do business: “Business models are not recipes or scientific models or scale and role models they play ANY - or all - these roles, often at the same time”

Casadesus-Masanell and Ricart ( 2007 ), p 15 “A business model […] is a reflection of the

firms realized strategy”

Chesbrough and Rosenbloom ( 2002 ), p 529 “[…] heuristic logic that connects technical

potential with the realization of economic value”

Demil and Lecocq ( 2010 ), p 233 “[…] the logic of the firm, the way it operates

and how it creates value for its stakeholders” Hedman and Kalling ( 2002 ), p 154 “[…] Model integrates firm-internal aspects

that transform factors to resources, through activities, in a structure, to products and offerings, to market”

that, taken together, create and deliver value”

of how an interrelated set of decision variables

in the areas of venture strategy, architecture, and economics are addressed to create sustainable competitive advantage in defined markets”

(continued)

Table 1 (continued)

Osterwalder et al ( 2005 ), p 10 “A business model is a conceptual tool that

contains a set of elements and their relationships and allows expressing the business logic of a specific firm It is a description of the value a company offers to one or several segments of customers and of the architecture of the firm and its network of partners for creating, marketing, and delivering this value and relationship capital, to generate profitable and sustainable revenue streams”

defines how the enterprise creates and delivers value to customers, and then converts payments received to profits”

and information flows, including a description

of the various business actors and their roles; and a description of the potential benefits for the various business actors; and a description

of the sources of revenues”

The following subsections provide a more detailed description of the seven ing perspectives on business models The section draws heavily upon the publication

prevail-Exploring the Field of Business Model Innovation by Oliver Gassmann et al (2016)

Discussion about which components are the most suitable for varying types of ness models has dominated the content of scientific publications in recent years.Despite healthy discussion, the components perspective is the most prevailing andwidespread in both research and managerial practice To design and evaluate busi-ness models, the importance of understanding the underlying components of businessmodels is essential, since they foster a holistic and interlinked illustration Business

value as the most essential component in a business model Keen and Williams

business model itself The emergence of the digital economy is leading to new forms

increases the importance of this interlinked understanding of value components Aseries of studies from holistically analyzed scientific literature has highlighted the

of the components and subcomponents identified in various scientific articles

Table 2 Perspectives on business models

rationale how a company creates, delivers and captures value”

Berkeley

“A business model is a way to commercialize novel technology”

of strategic choices”

Wharton School of Business

“A business model is a set of interdependent activities spanning firm boundaries”

dynamic process of balancing revenue, costs, organization, and value”

‘model’ or the ‘logic’ of how firms do business”

coexist with competing business models and requires ambidextrous thinking” Adapted from Gassmann et al ( 2016 ), pp 7–37

In more recent research, scholars have focused on four main pillars to characterize

creation, value delivery, and value capture Despite this more recent development,

almost a decade ago This, in managerial practice, often refers to the four dimensions

Who, What, How, and Why of a business model, which has proved to be the most

efficient way to communicate a projected business model design idea (Gassmann

Generation and the Business Model Canvas of Osterwalder et al (2010) has emerged

as a de facto standard for the representation of business models Given this prevailingtrend, the authors suggest breaking down the four value pillars into a total of ninesubcomponents

Slywotzky (1996) Linder and Cantrell (200

Value Capturinng Model

Customer and Market Segment

Communication and distribution

Researchers of the technology-driven school refer to business models as a

However, despite contributing to the same stream of research, these researchers fer in the theoretical foundation of their analysis Chesbrough focuses on analyzing

analyzes organizational aspects of the focal company, and focuses on the necessity ofovercoming dominant industry logic as the main barrier to business model adoption

dynam-ics in business models This approach considers the dynamic capabilities of firms

of business models: Henry Chesbrough, by focusing on organizational matters, and

Table 3 Overview on components of business models (Osterwalder et al.2010 , pp 20–21)

company’s bundle of products and services”

outsourced and some resources are acquired outside the enterprise”

performed by key resources”

required to offer and deliver the previously described elements”

several customer segments”

established and maintained with each customer segment”

delivered to customers through communication, distribution, and sales channels”

value propositions successfully offered to customers”

result in the cost structure”

David J Teece, by adopting the theory of dynamic capabilities The driven perspective closely builds upon the consideration of components (see previ-

business model should consider six aspects to capture value from technological vations: the value proposition, the relevant market segment, a value chain, both coststructure and profit potential, a value network, and a competitive strategy

Particularly in the early stages of the emerging research body around business els, scientists emphasized the definition of business models to analyze the wideninggap in the understanding of the delineation between (corporate) strategy and business