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ISBN 978-952-62-2687-3 (Paperback)ISBN 978-952-62-2688-0 (PDF)ISSN 1455-2647 (Print)ISSN 1796-2269 (Online)

U N I V E R S I TAT I S O U L U E N S I SACTAG

OECONOMICA

G 116

AC

TAJulius Francis G

omes

OULU 2020

G 116

Julius Francis Gomes

EXPLORING CONNECTED HEALTH BUSINESS ECOSYSTEMS THROUGH BUSINESS MODELS

UNIVERSITY OF OULU GRADUATE SCHOOL;UNIVERSITY OF OULU,OULU BUSINESS SCHOOL;MARTTI AHTISAARI INSTITUTE OF GLOBAL BUSINESS AND ECONOMICS

ACTA UNIVERS ITAT I S OULUENS I SG O e c o n o m i c a 1 1 6

JULIUS FRANCIS GOMES


Academic dissertation to be presented with the assent ofThe Doctoral Training Committee of Human Sciences,University of Oulu for public defence in the Arinaauditorium (TA105), Linnanmaa, on 25 August 2020, at 12noon

UNIVERSITY OF OULU, OULU 2020

Copyright © 2020Acta Univ. Oul. G 116, 2020

Supervised byDocent Petri AhokangasProfessor Minna Pikkarainen

Reviewed byProfessor Marko KohtamäkiAssistant Professor Marco Montemari

ISBN 978-952-62-2687-3 (Paperback)ISBN 978-952-62-2688-0 (PDF)

ISSN 1455-2647 (Printed)ISSN 1796-2269 (Online)

Cover DesignRaimo Ahonen

PUNAMUSTATAMPERE 2020

OpponentProfessor Christopher L. Tucci

Gomes, Julius Francis, Exploring connected health business ecosystems throughbusiness models. University of Oulu Graduate School; University of Oulu, Oulu Business School; MarttiAhtisaari Institute of Global Business and EconomicsActa Univ. Oul. G 116, 2020University of Oulu, P.O. Box 8000, FI-90014 University of Oulu, Finland

Abstract

The World Health Organization recognized that the global population is rapidly ageing andeffecting the global demographics. Among other effects of a growing ageing population,additional stress on healthcare services is a serious concern for policy makers. There is parallelpositive relation observable between advancements in information and communicationtechnologies (ICT) and advancements in healthcare services. To deal with the issues raised bygrowing ageing population, global healthcare sector has been using ICT advancements adeptly.One such emerging healthcare model is known as “Connected Health”. Connected health is amulti-stakeholder context, where more private institutes are entering rapidly. This study attemptsto explore Connected Health Business Ecosystems through Business Models.

While business model conceptualizations are evident in various ICT sectors, the healthcaredomain seems to have underutilized the value of business model conceptualizations up untilrecently. In European context, one of the underlying reasons could be that the healthcare sector iswidely perceived as public good. Through a structured literature review, this study offers aframework to look at ecosystemic contexts through the business model lens. The study highlightsthree key elements of business model relevant to ecosystemic contexts; namely: Opportunity,Value, and Advantage. Similarly, the study identifies three broad characteristics of businessecosystems; they are: Structure, Interaction, and Value re-configuration.

The study utilizes three qualitative case studies in the four original publications. The results ofthe study include: 1) business models relate to the business ecosystems through opportunityexploration and exploitation, value creation and capture, and advantage exploration andexploitation; 2) the process of exploring Business Ecosystems through business models caninclude Visioning, Mapping, Understanding causal interaction, and Understanding valuereconfiguration; 3) In emerging business ecosystems, complementarity between stakeholders’business models gives rise to the ecosystemic business model; 4) Interaction is about variation,selection, and retention of stakeholders’ business models in the business ecosystem’s evolution.

Keywords: business ecosystem, business model, connected health, digital health,ecosystemic business model

Gomes, Julius Francis, Liiketoimintamallit, ekosysteemit ja digitaalinen integroituterveydenhuolto. Oulun yliopiston tutkijakoulu; Oulun yliopisto, Oulun yliopiston kauppakorkeakoulu; MarttiAhtisaari InstituuttiActa Univ. Oul. G 116, 2020Oulun yliopisto, PL 8000, 90014 Oulun yliopisto

Tiivistelmä

Maailman terveysjärjestö WHO:n mukaan ikääntyminen vaikuttaa väestörakenteeseen globaalis-ti. Ikääntyvä väestö tuo lisää paineita poliittiselle päätöksenteolle erityisesti terveydenhuollonpalveluihin liittyen. Terveydenhuollossa digitalisaatio ja erilaiset informaatioteknologian ratkai-sut ovatkin nousseet entistä tärkeämpään rooliin palveluiden kehittämisessä. Yksi näistä uusistaterveydenhuollon toimintamalleista on digitaalinen integroitu terveydenhuolto, josta tässä tutki-muksessa käytetään englanninkielistä termiä Connected Health. Digitaalinen integroitu tervey-denhuolto voidaan nähdä monitoimijakontekstina tai liiketoimintaekosysteeminä, johon myösyksityisen sektorin toimijat ovat tulleet mukaan. Tässä tutkimuksessa keskitytäänkin liiketoimin-tamalleihin digitaalisen integroidun terveydenhuollon ekosysteemeissä.

Liiketoimintamallinäkökulmaa on perienteisesi käytetty digitaalisten palveluiden yritystoi-minnassa ja ekosysteemeissä, mutta terveydenhuollossa on liiketoimintamallien hyödyntämi-seen herätty vasta viime aikoina. Euroopassa tähän on vaikuttanut se, että terveydenhuolto onlaajalti nähty julkisena palveluna ennemminkin kuin monitoimijaekosysteeminä. Tällaista moni-toimijaekosysteemiä varten tutkimuksen kirjallisuusosiossa rakennetaan liiketoimintamalliajatte-luun perustuva analyysikehikko. Tässä kehikossa keskeisinä käsitteinä ovat liiketoimintamah-dollisuudet, arvonluonti, ja kilpailuetu. Lisäksi tutkimuksessa kiinnitetään huomiota monitoimi-jaekosysteemien rakenteeseen, toimijoiden vuorovaikutukseen sekä muutoksiin arvonluonninprosesseissa.

Työn empiirinen osa koostuu kolmesta tapaustutkimuksesta ja sisältää neljä alkuperäisjulkai-suartikkelia. Työn keskeisenä kontribuutiona esitetään prosesseja joissa 1) liiketoimintamahdol-lisuuksien, arvonluonnin ja kilpailuedun etsintä ja hyödyntäminen yhdistää liiketoimintamallitekosysteemeiksi ja joissa 2) visiointi, kartoittaminen, vuorovaikutussuhteiden ymmärtäminensekä arvonluonnin prosessit nähdään keskeisinä terveydenhuollon ekosysteemien jäsentämises-sä. Lisäksi 3) alkuvaiheen ekosysteemeissä toimijoiden liiketoimintamallien tulee täydentää toi-siaan jotta syntyisi ekosysteemitason yhteinen liiketoimintamalli, jonka evoluutioon vaikuttaa 4)ekosysteemin toimijoiden liiketoimintamallien varioituminen, valintaympäristön piirteet sekä lii-ketoimintamalleja säilyttävät mekanismit.

Asiasanat: digitaalinen integroitu terveydenhuolto, ekosysteeminen liiketoimintamalli,liiketoimintaekosysteemi, liiketoimintamalli

To my parents, Eugene and Ranu, you are all the reasons for my being.

To my siblings, Francis, Cyprian and Christina,

you are all the inspiration for my doing.

To my wife, Flora, for supporting all the way through.

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Acknowledgements Every dissertation is unique in their own rights; however, every dissertation has the mutual story of ups and downs along the way. Mine is nothing different. I am thankful to all the “good Samaritans” that without their help, guidance, and inspiration the ship wouldn’t approach dock. I was never meant to be an author. My first full-time job was at a large multinational bank in Bangladesh, where I was often working 12 hours a day. I was destined to be an operational workhorse in the Banking industry in Bangladesh. Then one day I asked myself “what am I doing here?” A bit more than 7 years fast forward, I am somehow completing my doctoral dissertation and still asking the same question. Although this time around I have a better idea of what I am doing.

I got into academia and conducted my master’s thesis under the supervision of Adjunct Professor Petri Ahokangas. He introduced me to the realm where technology and business meets in academia. At first, I stumbled with the vast number of new concepts and ideas to grasp, but eventually focused on digital health and the futures business models. I got so intrigued by the topic that upon completing the master’s thesis, I immediately started building the idea for my doctoral studies. In some way, it felt that the master’s thesis was not the end. Soon enough, Adjunct Professor Petri Ahokangas and Connected Health Professor Minna Pikkarainen agreed to jointly supervise my doctoral studies. From digital health to connected health, from business models to ecosystemic business models; I made some basic choices for my dissertation quite early in the journey. This helped me in planning the original publications and how to collect relevant data. As a result, I managed to publish the 4 original publications included in this dissertation quite smoothly. However, the place where I struggled was writing out the “kappa”, the introductory part of this dissertation. Subconsciously I knew this is final piece and it must be perfect, which I was hesitant to dare starting. Both my supervisors have been excellent source of inspiration to help me get started and to keep at it.

The world of academia is often demanding and tedious, but never lonely. The struggle and desire to create new knowledge brings academics together; in the form of nerdy coffee-chats, in the form of co-authoring papers, or in the form of constructive criticism. I have been surrounded by numerous kind people to whom I wish to express my gratitude.

First, I would like to thank my supervisors. Adjunct Professor Petri Ahokangas has been more than just a supervisor to me, he has been a friendly father-figure in my short research career. Without his continuous guidance and support, the

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possibility of me completing this dissertation would be close to none. He is an inspiration for anyone who writes about business models, I feel myself lucky to be writing my dissertation under his supervision. Connected Health Professor Minna Pikkarainen has her role divided between multiple faculties and multiple research organizations at the same time, making her one of the busiest academics I have ever come across. Despite her very rigorous schedule, she would always make regular time to discuss about projects and my PhD work. I am thankful to both for taking me on board and providing an opportunity to work in numerous interesting projects. Both of you showed immense faith in me, I hope I did not disappoint.

I wish to extend my gratitude to the pre-examiners of my dissertation, Professor Marko Kohtamäki and Assistant Professor Marco Montemari for your insightful and thought-provoking comments during the pre-examination. A special thanks to Professor Christopher L. Tucci for acting as the opponent of the public defence ceremony. Professor Tucci’s contribution in the business model literature has paved some of the foundation of the overall stream. My sincere thanks to Professor Joan Enric Ricart for hosting me as a visiting researcher at the IESE Business School, Barcelona. The time I spent in Barcelona was as good an academic experience, as it was for getting to know the amazing city that I fell in love with.

Since the start of my doctoral studies, I have been employed at the Martti Ahtisaari Institute. My special thanks for Professor Veikko Seppänen who is an exceptional people manager and a great mentor. Besides all the professional support, I have had many unscheduled meetings just by walking through his doors and always found help and guidance. I would like to appreciate the prompt support and guidance that I received from the members of my follow-up group. Thank you Professor Timo Koivumäki, Professor of Practice Maritta Perälä-Heape, and Dr. Anne Keränen.

I wish to thank some of my colleagues with whom I have fond memories. Thank you, Dr. Marika Iivari, for all the research and not-so-much-research talks that we had. I learnt a lot from you about life in Finland. Thank you, Dr. Yueqiang Xu, for your kind support in taking forward a lot of project proposal tasks and guiding in the way. Some of the most enjoyable memories of my doctoral journey includes my trips to the conferences and project meetings in Venice, Florence, New York, Bodø, Udine, Brussels, and Oxford. I enjoyed the company of all my colleagues who were there, I thank each of you for those memories. I would also like to thank Dr. Irina Atkova, Sari Perätalo, and Raushan Aman.

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I am grateful for the financial support that I have received during my doctoral studies in the form of grants and scholarships from Martti Ahtisaari Institue, Tauno Tönning Foundation, and HPY Research Foundation.

I would like to thank the Bangladeshi community in Oulu for making the life in north a little Bangladesh with so many events and gatherings. I would like to thank Dr. Helal Chowdhury, Dr. Shahriar Shahabuddin, Dr. Ehsanul Haque Apu, Gagan Mazed, Md. Shah Emran, Jahangir Alam, Sakhawath Hossain, Arman Hossain, S M Tawhid Rahaman, Sadiqur Rahman, Noushed Ahmed Ron, Sharmin Farah, Limon Hossain, Atiq Mahmud, Shariful Alam, Sharif Ullah, Helal Hossain, Ehsan Lenin, Z.I. Jony, Rafi Sheikh, Hasan Shahriar Rhiday, Delowar Hossain, AHM Forhadul Islam, Ashikur Rahman, Muhammad Fayjus Salehin. All of you have in some way helped me to stay sane and stroll through the difficult periods. Thanks to every member of the Oulu Knights futsal and volleyball group, you guys make the long winter season bearable and enjoyable. I would like to thank my dear friends Victor Pavlov, Mirja Lahti and Samuel Waheeb.

My parents, Eugene and Ranu, thanks for raising us siblings in the best way possible. Baba, you are the example for so many in our extended family for your hard work and perseverance. Maa, you are the one who has been continuously inspiring me to this doctoral degree from day one. Baba and Maa, your love and blessings have made it possible to what I am achieving. Special thanks to my siblings and their better halves, Francis and Bernadette, Cyprian and Tazzy, and Mary and Ronald for your continuous love and support. To the little ones, Martin, Sara, and Anthony; I love you all and I cannot wait to meet you guys in person.

Finally, to my loving wife Flora D’ Costa, I cannot thank you enough for tolerating my routineless days and nights. Thanks for being there for me every day when I almost lost it. You are made of the strongest material; your mental strength gives me strength. You have gone through a lot in the last couple of years, yet you pulled through as the Wonder Woman. My love and respect for you is endless. Without your love, support and care, this achievement would have been impossible. I dedicate this dissertation to my parents, my siblings, and my loving wife.

Working from home during Corona Crisis In Oulu, 29th of May, 2020 Julius Francis Gomes

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Abbreviations etc. et cetera i.e. id est e.g. exempli gratia et al. et alia cf. Conferatur RQ Research Question ICT Information and Communications Technologies WHO World Health Organization VC Venture Capital CR Critical Realism CLA Causal Layered Analysis IoT Internet of Things SoA Service oriented Architecture SME Small and Medium Enterprise MDM Mobile Device Management 4C Connection, Content, Context, Commerce 5G Fifth generation of telecommunications network

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Original publications This thesis is based on the following publications, which are referred throughout the text by their Roman numerals:

I Gomes, J. F., and Moqaddemerad, S. (2016). Futures Business Models for an IoT Enabled Healthcare Sector: A Causal Layered Analysis Perspective. Journal of Business Models, 4(2), 60-80.

II Gomes, J. F., Pikkarainen, M., Ahokangas, P., and Niemelä, R. (2017). Towards business ecosystems for connected health. Finnish Journal of eHealth and eWelfare, 9(2-3), 95-111.

III Gomes, J. F., Iivari, M., Pikkarainen, M., and Ahokangas, P. (2018). Business Models as Enablers of Ecosystemic Interaction: A Dynamic Capability Perspective. International Journal of Social Ecology and Sustainable Development (IJSESD), 9(3), 1-13.

IV Gomes, J. F., Iivari, M., Ahokangas, P., Isotalo, L., and Niemelä, R. (2017). Cybersecurity Business Models for IoT-Mobile Device Management Services in Futures Digital Hospitals. Journal of ICT Standardization, 5(1), 107-128.

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Contents Abstract Tiivistelmä Acknowledgements 9 Abbreviations 13 Original publications 15 Contents 17 1 Introduction 19

1.1 Scope of the study ................................................................................... 21 1.2 Research gap ........................................................................................... 23 1.3 Purpose, research questions and contributions of the study .................... 25 1.4 Structure of the dissertation .................................................................... 29

2 The context of connected health 31 2.1 Application areas and scope of connected health .................................... 33 2.2 Stakeholders in connected health ............................................................ 35 2.3 The connected health ecosystem ............................................................. 36

3 Theoretical foundations 39 3.1 Business ecosystems as an interdependent multi-stakeholder

environment ............................................................................................ 41 3.1.1 Stakeholders and roles in business ecosystems ............................ 42 3.1.2 Interdependent and interaction properties in business

ecosystems .................................................................................... 44 3.1.3 Evolution of business ecosystems and the search for

generic and non-generic value complementors ............................ 45 3.2 Business model approach ........................................................................ 48

3.2.1 Origin and definitions ................................................................... 48 3.2.2 Key elements of business models in ecosystemic context:

opportunity, value, advantage ....................................................... 51 3.3 Towards exploring connected health business ecosystems

through business models ......................................................................... 56 4 Research design and methodologies 59

4.1 Research philosophy ............................................................................... 59 4.2 The qualitative case study method .......................................................... 62 4.3 Research process and data collection ...................................................... 64 4.4 Data analysis ........................................................................................... 69

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5 Overview of original publications 73 5.1 Paper I: Futures business models for an IoT enabled healthcare

sector: a causal layered analysis perspective ........................................... 75 5.2 Paper II: Towards business ecosystems for connected health ................. 76 5.3 Paper III: Business models as enablers of ecosystemic

interaction: A dynamic capability perspective ......................................... 77 5.4 Paper IV: Cyber security business models for IoT-MDM services

in futures digital hospitals ....................................................................... 79 6 Discussion and conclusions 81

6.1 Results of the study ................................................................................. 81 6.2 Theoretical contributions......................................................................... 91 6.3 Practical and policy implications ............................................................ 95 6.4 Reliability, validity, and research ethics .................................................. 96 6.5 Limitations and future research avenues ................................................. 97

List of references 101 Original publications 113

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1 Introduction “In the long history of humankind (and animal kind, too) those who learned to

collaborate and improvise more effectively have prevailed.” (Charles Darwin in The Descent of Man.)

In the age of information, the cost of information processing has plunged drastically, which has led to a shift in innovation from focal organizations to value chains, networks and even business ecosystems (Baldwin, 2012). Like many other tech intensive sectors, the healthcare sector in general is also reaping the results of advancements in information and communication technologies (Balandin, Balandina, Koucheryavy, Kramar, & Medvedev, 2013). If these advancements are compared to the advancements in eHealth and mHealth services, a certain positive parallel pattern can be observed. Innovations and advancements in the healthcare sector can also be observed to cross organizational boundaries in ecosystemic contexts (Gomes & Moqaddemerad, 2016) where boundaries are blurred and multiple stakeholders are involved through loose-couplings of value accumulation (Iivari, 2016).

It is important to understand the necessity behind the inventions which require substantial efforts and investments. A gross change in global demography is reported, moving towards an increase in proportion of the elderly in the overall population. The World Health Organization (WHO, 2015) states, “The number of people aged 60 years or older will rise from 900 million to 2 billion between 2015 and 2050 (moving from 12% to 22% of the total global population). Population ageing is happening more quickly than in the past.” The growth of elderly population comes with a rise in chronic diseases too (Agboola, Ball, Kvedar, & Jethwani, 2013; Barr, McElnay, & Hughes, 2012). This imminent growth of the elderly proportion inevitably leads to added healthcare needs and costs and questions the adequacy of existing health and social care models (Chouvarda, Goulis, Lambrinoudaki, & Maglaveras, 2015).

This drastic change in population demographics clarifies “Why” the healthcare sector across the world is being reshaped rapidly; but to understand “how” technology-aided healthcare organizations can solve the problems of the future together, this research focuses on the business ecosystems in the healthcare domain and the business models of participating stakeholders. This study addresses the emerging phenomenon of ecosystemic collaboration in healthcare domain (i.e., connected health). Business ecosystems are considered to be a network of

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interconnected business models (Jansson, Ahokangas, Iivari, Perälä-Heape, & Salo, 2014). Business models are considered to connect abstract strategies to implementation (Casadesus-Masanell & Ricart, 2010) as a boundary-spanning unit of analysis (Zott, Amit, & Massa, 2011).

Chouvarda et al. (2015) suggests research is needed on newer integrative and sustainable healthcare models that require multifaceted approaches, such as technological development, advancements in care processes, and advancements in care delivery. The need to cut costs and improve care delivery at the same time is forcing changes in the healthcare systems globally through new models.

“Connected health” is a recently introduced, comprehensive, sociotechnical model for managing healthcare (Carroll, 2016), used as an umbrella term for concepts such as telemedicine, telehealth, telecare, mHealth and eHealth (Barr et al., 2012; Galbraith, Mulvenna, McAdam, & Martin, 2008; Iglehart, 2014). Extended research efforts on connected health are concerned with chronic diseases and the global ageing problem (Barr et al., 2012; Caulfield & Donnelly, 2013; Christensen, Doblhammer, Rau, & Vaupel, 2009; Galbraith et al., 2008). Some studies discuss the impact of connected health on cost efficiency (Agboola et al., 2013), especially with regard to preventive medicine (Agboola et al., 2013), the role of pharmacists (Barr et al., 2012), and patient-professional electronic communication (Niemi, Hupli, & Koivunen, 2016), among other aspects. Pitkänen & Pitkäranta (2016) identify digitalized work-flows of healthcare professionals as enablers of improvement in the healthcare services of the future. Pang et al. (2015) and Gomes & Moqaddemerad (2016) point out the necessity and potential of ecosystemic business development in the futures healthcare sector.

Healthcare is predominantly a public-funded sector. However, Gomes & Moqaddemerad (2016) state that there are an increasing number of private players in the healthcare-related business sector who are interested in the revenue streams as well as the service provisioning. With the rise of more business entities with a service offering, this dissertation looks at the empirical context of connected health as a business environment. More specifically, this research focuses on the connected health business ecosystems where various business models are in constant interaction for greater opportunity exploration and exploitation, value creation and capture, advantage exploration and exploitation.

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1.1 Scope of the study

This dissertation adopts Dowd et al.’s (2018) summary on connected health as a new model for healthcare management by connecting technologies for data integration for various stakeholders; where the data is shared between patients, caregivers, medical experts in a way that the integrated technologies together with the data can support faster and more efficient decision-making related to patient health and wellbeing.

ICT-intensive business environments tend to adopt an ecosystemic approach, where the digital aspects are becoming more intertwined with non-digital aspects of the business world (Turber & Smiela, 2014). In an ecosystemic approach, organizational activities (i.e., innovation, product development, etc.) cross organizational boundaries into the boundaries of partnering stakeholders. In the connected health context, this phenomenon is also observable. The concept of a “business ecosystem” is used as a metaphor to explain multi-stakeholder, co-dependent, blurred-boundary business environments (Adner, 2012; Moore, 1993). Thus, from a practicality and sustainability point of view, it can be argued that a business ecosystems perspective can contribute to the literature on how different stakeholders in the connected health business ecosystem can improve collaboration in different phases of the business ecosystem lifecycle.

The topic of this study is to explore the phenomenon of business ecosystems in the context of connected health. Van De Ven & Poole (1995) notes that the processes or sequences of events unfolding in organizations undergoing change are often problematic. According to Van De Ven & Poole (1995), to understand organizations undergoing change, management scholars have borrowed various concepts as metaphors or even as theories from other disciplines. Business ecosystems have been historically used as a metaphor to reflect complexity, dynamism, collaboration, co-evolution and interdependence between stakeholders (Adner, 2012). The business ecosystem as a concept is rooted in biological ecosystems.

Extending Jansson, Ahokangas, Iivari, Perälä-Heape, & Salo’s (2014) view of business ecosystems as a network of business models, this study confers business models as the strategic vehicle that connects abstract organizational strategies to practical implementation in business environments (Lambert & Montemari, 2017), such as business ecosystems. Business models as a boundary-spanning unit of analysis (Zott et al., 2011) connect organizations with their business environments, competitors, complementors, customers, individuals and society as well; hence the

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overall ecosystem (Gomes, Iivari, Pikkarainen, & Ahokangas, 2018; Teece, 2010). This research utilizes business models as the boundary-spanning unit of analysis to explore and understand dynamisms and interdependencies inside the complex connected health business ecosystem.

Chesbrough, Vanhaverbeke, & West (2006) indicate the importance of “purposive inflows and outflows of knowledge” between business entities to foster innovation and to have an impact on business. Further, Faems, Van Looy, & Debackere, (2005) highlights the notion of knowledge sharing and collaboration between entrepreneurs and other stakeholders for better innovation management as a cluster. In an ecosystemic context, such notions as purposive knowledge sharing, collaboration, co-creation can foster interaction between stakeholders, leading to sustainable performance.

Figure 1: Scope of the study.

“An ecosystem” as a metaphorical concept has entered different fields in academia and in practice. First, the concept of healthcare ecosystems depicts various involved stakeholders and their relationship levels. Predominantly these include: provider-payer relationships, provider-pharmacist collaboration, medical device manufacturer-clinician communications, employer/payer relationships, and a consumer relationship across the board (BHR, 2014). Although, healthcare ecosystems in the past used to mainly encompass the multi-stakeholder aspect of the environment, the meaningful utilization of data and dependency on data and

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digital solutions are becoming more customary; while consumer/patient centrism is becoming dominant (Copeland, 2018).

Second, the concept of digital ecosystems is relevant to digital business and technology evolution. Digital ecosystems, conceptually, utilize computerized space and tools to extend collaboration between individuals, and between organizations; often in forms of digital platforms or cloud services. In practice, digital ecosystems have enabled most of the digital disruptions in most industries (Weill & Woerner, 2015). Further, business ecosystems are conceptualized as interdependent multi-stakeholder business environments that enable co-evolution and mutual development of stakeholders (Dedehayir, Mäkinen, & Ortt, 2018; Iivari, 2016; Moore, 1993; Turber & Smiela, 2014).

Figure 1 depicts the scope of this study, based on the discussion in the previous paragraph. In the figure a Venn diagram shows where the concepts of the healthcare ecosystem, digital ecosystem, and business ecosystem overlap. In the overlapping areas, new concepts can be observed which are also discussed in the literature, such as digital business ecosystems, healthcare business ecosystems, and digital/connected healthcare ecosystems. However, the scope of this research is where all three concepts overlap. I perceive this overlapping part of the Venn diagram as the connected health Business Ecosystem. Connected health is a new and more holistic approach to digital transformation that focuses on support for making timely decisions using state-of-the-art technologies (i.e., the collection of sensor-based data, artificial intelligence etc.). A key predisposition based on the reviewed literature is that business environments in connected health tend to adopt a business ecosystem approach, and there can be several connected health business ecosystems in play at a given time. In the scope of this research, I study single business ecosystems in different original publications to delineate different characteristics of the business ecosystem.

1.2 Research gap

Novillo-Ortiz et al. (2018) states that the importance of the healthcare sector is more than evident at the social level, but the importance at the economic level has just started to be more visible through research efforts. Future scholarly works are asked to justify the economic value of the healthcare sector and how to further improve the economic value. Gualtieri, Phillips, Rosenbluth, & Synoracki (2018) discuss the need to design future connected health services in a more inclusive manner that will improve scalability. This notion hints at the application of

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ecosystemic approaches and adoption of open business models where potential customer segments are trained in order to create and culture the market demand. The domain of connected health is inherently a multi-stakeholder arena, which requires the development of frameworks for contextualization and coordination of decisions to increase collaboration (Chouvarda et al., 2015).

Since connected health technologies aim at developing personalized services, Chouvarda et al. (2015) additionally emphasize that rather than focusing on single solutions it would be more fruitful to focus on ecosystems to increase collaboration. In this sense, exploring the connected health business ecosystem through business models offers a novel approach on how sustainable collaboration can take place.

Barr et al. (2012) note the necessity of adopting a multidisciplinary approach which involves a multi-stakeholder perspective for connected health to succeed in the longer run. Barr et al. (2012) also raise the need for further research around the infrastructure needed for the successful implementation of connected health. While successful implementation requires suitable technological infrastructure, it also requires business infrastructure for sustainability and feasibility especially in a multi-stakeholder and complex environment from the business ecosystems perspective.

In the age of digital revolution, Chaher, Belaud, & Pingaud (2017) note that many healthcare organizations utilize collaborative approaches and open innovation strategies to improve their performance. While open innovation strategies and ecosystemic approaches go hand in hand, inherent complexity in these processes impedes their mass adoption. The inherent complexities of business ecosystems relate to the fact that they have not been extensively broken down and explained in the healthcare context from a business process perspective (cf. Ahokangas, Perälä-Heape, & Jämsä, 2015). In open innovation, distributed business and innovation processes (cf. Tucci, Chesbrough, Piller, & West, 2016) take place based on managed inflows and outflows of knowledge across organizational boundaries in line with the organization’s business model (Chesbrough & Bogers, 2014). In connected health, the complex and intertwined business processes are relevant to discussions of business models and business ecosystems (Chaher et al., 2017).

From a business models research perspective, Foss & Saebi (2018) pointed out some promising future research directions that still need significant attention from academics in their work on business models. From a complexity perspective (Levinthal, 1997), Foss & Saebi (2018) suggests for further research endeavors to explore interdependencies with the business model and what these imply for the

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transformation/innovation. Foss & Saebi (2018) further suggest focusing more broadly on how a change in the firm’s business model affects the business models within its ecosystem (Berglund & Sandström, 2013). Involving an open innovation perspective in business model research (Chesbrough, 2006), Foss & Saebi (2018) also suggest studying the application of business models and typologies that are conducive in broader business environments.

1.3 Purpose, research questions and contributions of the study

Following on from the background discussion and identified research gaps, the purpose of this study is to explore and describe the business ecosystems in the context of connected health, using business models as a unit of analysis (Zott et al., 2011). Business models are often perceived to be context-oriented (Ahokangas, Juntunen, & Myllykoski, 2014; Atkova, 2018), meaning the characteristics of any business model often tend to depend on the context around which they are designed to operate. While Jansson et al. (2014) view business ecosystems as a network of complementary business models, this research attempts to understand the value of business model conceptualizations in exploring the contexts they are embedded in, i.e., connected health business ecosystems. More specifically, how complementary business models relate to the business ecosystem.

While connected health is the core research context in this dissertation, the theoretical objective of this dissertation is to design a conceptual framework to explore the connected health business ecosystem by using the business model perspective. In doing so, first, this study attempts to summarize the theoretical conceptualization of business ecosystems and build a generic framework on which business model conceptualization can be reflected. Second, the evolving literature on business models is reviewed in understanding how the concept of business model relates to business ecosystems. Further, the empirical objectives of this study are related to the theoretical objectives. This dissertation seeks to develop empirically grounded knowledge on connected health business ecosystems structure, interaction, and re-configuration from a business models perspective. The empirical objectives include applying the developed conceptual framework through a qualitative exploratory case study approach (Streb, 2012) in order to present the empirically grounded results. Business ecosystems are multi-layered, and involve multiple stakeholders with blurred and constantly evolving boundaries (Iivari, Ahokangas, Komi, Tihinen, & Valtanen, 2016). The notion of evolving boundaries also suggests the evolution of business models within the business ecosystems

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originating from opportunities identified/created/discovered though the business ecosystem. The exploration of connected health business ecosystem in this study thus involves evolutionary perspective as well. Considering the research setting and the identified research gaps, this study seeks to answer the following two research questions:

RQ I: How do business models relate to the business ecosystem in connected health?

RQ II: How can the business ecosystem in connected health be explored through business model conceptualizations?

Exploratory case studies are usually applied to study phenomena characterized by the lack of pre-existing knowledge through scientific research (Streb, 2012). The results can bring answers to questions such as what, how, where and why in regards to the research phenomena. As such, exploratory case study based research should have an expansionist approach, instead of a reductionist approach (Stake, 1978). The inductive approaches can be implemented in various ways. This study, as an exploratory research, utilizes multiple research methodologies (foresight methodology, single case study, multiple case study) and different business model tools (business model wheel, 4C business models, mixed-source business models) in the original publications to capture various essences of the connected health business ecosystem.

As a part of this dissertation, four original research papers have been published, which approach different aspects of connected health business ecosystems through business models. As an article-based dissertation, the main RQs are partly answered through the original publications. Although the original publications have their own areas of interest and scope of study, they contribute to the core topic of this dissertation. The research questions addressed in the original publications are as follows:

Paper I RQ: How can the business model framework be applied to CLA to study the future of an industry?

Paper II RQ: How could a connected health business ecosystem be mapped using a business model framework?

Paper III RQ: How do ecosystem stakeholders calibrate their interdependent activities through their business models?

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Paper IV RQ: How could generic and non-generic complementors be identified in an ecosystemic context through business model conceptualizations?

The study attempts to explore different properties of the emerging phenomenon of connected health business ecosystem through business models. Van de Ven (2016) highlights the importance of grounding the research phenomenon in phenomenon-driven research by finding answers to basic questions of who, what, when, why, and how. During the last decade (when), connected health (what) has emerged as a new healthcare model to address the potential problems of future healthcare sector (why). Public and private stakeholders (who) are increasingly adopting business ecosystems approach to organize the services and solutions in connected health through business models (how). This research addresses the emerging phenomenon of connected health business ecosystem, where business models are the vehicle for interactions between participating stakeholders.

Schwarz and Stensaker (2016:245) have observed that phenomenon-driven research focuses on capturing, documenting, and conceptualizing an observed phenomenon of interest in order to facilitate knowledge creation and advancement. Von Krogh, Rossi-Lamastra, & Haefliger (2012:277) further state that phenomenon-driven research tackles problems that are relevant to management practices but fall outside the scope of existing theories. As an exploratory study of an emerging phenomenon, the phenomenon of business ecosystems and business models themselves lead the theoretical approaches in this research. This study builds the conceptual understanding using the literature on connected health, business ecosystems and business models.

Specifically, for each of the original articles, the phenomena of connected health business ecosystem and business model conceptualizations guide the theoretical approaches rooted in their own literature. In this dissertation, to formulate an overarching sense-making of the results from the original publications, components from the theory of evolution are borrowed.

This study sees business models as context-specific and exploring broad environments such as business ecosystems requires multiple methodical approaches to increase the depth and breadth of the exploration. Hence, this article-based dissertation includes four business model facilitated methodological approaches from the original publications as a means to explore the connected health business ecosystem. Table 1. presents author’s contribution in the original publications and key contributions of each paper to this dissertation.

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Table 1: Author’s contribution in original publications.

Original publication Contribution of the author Answers 1 Gomes, J. F., and Moqaddemerad, S.

(2016). Futures Business Models for an

IoT Enabled Healthcare Sector: A Causal

Layered Analysis Perspective. Journal of

Business Models, 4(2), 60-80.

The author was the main

responsible researcher for

planning, coordinating and

writing the paper.

How business model

approaches can be combined

with foresight techniques to

create a vision of futures

business ecosystems.

2 Gomes, J. F., Pikkarainen, M.,

Ahokangas, P., and Niemelä, R. (2017).

Towards business ecosystems for

connected health. Finnish Journal of

eHealth and eWelfare, 9(2-3), 95-111.




writing the paper. Part of

the data was collected by

co-authors in the research.

How to map the connected

health business ecosystems

through business model

conceptualization.

3 Gomes, J. F., Iivari, M., Pikkarainen, M.,

and Ahokangas, P. (2018). Business

Models as Enablers of Ecosystemic

Interaction: A Dynamic Capability

Perspective. International Journal of

Social Ecology and Sustainable

Development (IJSESD), 9(3), 1-13

.




writing the paper.

How ecosystem stakeholders

interact and calibrate

interdependent activities

through their business models.

4 Gomes, J. F., Iivari, M., Ahokangas, P.,

Isotalo, L., and Niemelä, R. (2017).

Cybersecurity Business Models for IoT-

Mobile Device Management Services in

Futures Digital Hospitals. Journal of ICT

Standardization, 5(1), 107-128.




writing the paper. Part of

the data was collected by

co-authors in the research.

How to identify generic and

non-generic value

complementors for

ecosystemic contexts through

business model

conceptualizations.

An article-based dissertation needs to portray the logic of how the papers are connected to the overarching topic of the dissertation. Figure 2 depicts the relationship between these papers as a series of different methods of exploring the connected health business ecosystems through business models. These methods are organized in a chronological order. The strategic foresight with a business model conceptualization in Paper I helped to create a vision of the futures connected health business ecosystem. Paper II, aims to understand the selective environment of the connected health business ecosystem, a method for mapping the complex business ecosystem. Paper III, develops a conceptual framework on how ecosystem stakeholders calibrate their interdependent activities through business models as a

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dynamic capability. Lastly, Paper IV displays how to identify generic and non-generic complementors for the business ecosystem.

Figure 2: Original publications in relation to the topic of this dissertation.

1.4 Structure of the dissertation

This dissertation consists of two main parts. First, the introductory part that explains the background of the research, presents a literature review of the research context and theoretical concepts. The introductory part of the dissertation also discusses the research philosophy, strategy, design and methodologies adopted in this study. A summary of included original publications is further presented. The first part of the dissertation ends with a discussion and conclusions of the study. The second main part of the dissertation contains the four original publications.

The structure of the first main part of the dissertation is as follows. Following the introduction (Chapter 1), the empirical context of the study, connected health, is briefly presented based on a literature review. The review presents application areas, stakeholders and the notion of ecosystems in connected health. The chapter is summarized with a conceptual framework comprised of the key concepts from the literature review.

Next, for developing the theoretical framework, Chapter 3 addresses the conceptual characteristics of business ecosystems and business models. To create an overarching understanding of evolutionary logic in ecosystemic contexts, this thesis borrows concepts from evolutionary theory. The overall summary of the theoretical literature review is captured in the theoretical framework depicted in

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Figure 6. Chapter 4 addresses the methodological issues of the research, by explaining the research philosophy, strategy, techniques, data collection and analysis.

The original publications are introduced in Chapter 5. While summarizing the results of the original publications, this chapter also aims to display how the results contribute to answering the research questions of the dissertation. The concluding chapter (7) of the dissertation includes a discussion part that aims to take the results of original publication towards a more holistic understanding of how to explore connected health business ecosystems through business models. This chapter also presents the theoretical and managerial implications of the study. It further outlines the reliability and limitations of the study and proposes future research avenues.

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2 The context of connected health “Art imitates nature, and necessity is the mother of invention.”

(Richard Franck – Northern Memoirs, Calculated for the Meridian of Scotland)

The review of key literature for this dissertation is separated into two sections, the research context and the theoretical foundations. This chapter presents the literature review of the research context: connected health.

Advancements in information and communications technologies (ICT) has continuously affected innovations in the healthcare sector (Gomes, Pikkarainen, Ahokangas, & Niemelä, 2017). The advancements in ICT can be identified as the Internet revolution during the mid-1990s, then the mobile phone technology revolution in the early 2000s and again from the later part of the last decade when online social networking paradigm started to reshape the global data dissemination and information-processing scenario (Coetzee & Eksteen, 2011; Gomes, Ahokangas, & Moqaddamerad, 2016). Along with technological advancements, the rise of different health and wellness related services emerged, which fall under eHealth, mHealth, telehealth and telemedicine paradigms (Atzori, Iera, & Morabito, 2010; Domingo, 2012).

The World Health Organization (WHO) has identified a gross change in global demography in multiple domains, highlighting the increase in the proportion of the elderly in the overall population. WHO mentions that compared to a global elderly population of 12% in 2015, by 2050 there will be a global elderly population of 22%. The growth of the elderly population comes with rises in chronic diseases as well (Agboola et al., 2013; Barr et al., 2012) and other unforeseeable burdens on the healthcare sector. This imminent change in demographics inevitably leads to added healthcare needs and costs and further questions the adequacy of existing health and social care models (Chouvarda et al., 2015). Scholarly works have identified the need for new inclusive models to battle such challenges in order to better manage resources and deliver care efficiently (Agboola et al., 2013; Chouvarda et al., 2015).

Prevalent concepts such as ‘ehealth’, ‘mhealth’, ‘telehealth’, or ‘telemedicine’ have been incorporated for designing resilient and inclusive healthcare models for the future in existing studies (Galbraith et al., 2008; Gomes, Pikkarainen, et al., 2017; Pitkänen & Pitkäranta, 2016). Connected health is one of such inclusive model of future healthcare that has attracted significant attention from academics, healthcare professionals and business organizations.

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With its roots in the prevalent models of digital transformation in healthcare (e.g., eHealth, mHealth, telemedicine, etc.), connected health has since progressed as a model in recent years and has become an overarching and comprehensive model. Connected health connects the care providing party with the care receiving party in numerous ways and intermediary parties in the care path, mostly through software solutions. While bringing together the prevalent digitalized models of healthcare management and harnessing the potential of sensor-based data collection and artificial intelligence aided data analytics in futuristic scenarios (Gomes, Pikkarainen, et al., 2017).

Chouvarda et al. (2015) notes that the aim of connected health is to bring the right information to the right person at the right time, and this aim will set the basis for deployment of integrated care models. Connected health fosters timely health/ wellness related decisions based on platform-oriented communication and collected data.

Chouvarda et al. (2015) defines connected health to be based on advancing healthcare technologies that aim for optimal access, sharing, analysis and use of collected data. This helps different actors (citizens, patients, clinicians and, policy makers) to make better health and care decisions across stakeholder levels. Agboola et al. (2013) mentioned that connected health utilizes technologies ranging from short text messages to more advanced technologies (e.g., artificial intelligence, machine learning, chatbots, etc.) for patient-centric care. One of the most important aspects of connected health identified by them are the continuously active “feedback loops” that enable better and more timely decision making. This utilization of data and feedback loops engages more participants and affects behavioural change on a social level (Agboola et al., 2013).

The impact of connected health for improving healthcare systems is multifaceted. First, direct communication between patients and caregivers through real-time services will be present using connected solutions (Pikkarainen, Pekkarinen, Koivumäki, & Huhtala, 2018; Solad, Patel, Hsiao, & Atreja, 2018). Second, sensor-based data collection and virtual reality services improve care giving in emergency cases and as well in general cases (DeClercq et al., 2018). Third, high-definition and need-specific video conferencing is another use case that enables the delivery of various types of virtual care services to remote areas (Wade, Karnon, Elshaug, & Hiller, 2010). So far, such ideas have been around, but the potential has not been realized to a great extent, largely due to the lack of complementary technical and business infrastructures. Fourth, the decision-support aspect and feedback loop characteristics of connected health make the model more

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scalable as it demonstrates the value for different stakeholders within the healthcare sector (Agboola et al., 2013; Serbanati, Ricci, Mercurio, & Vasilateanu, 2011). Finally, the idea of building a connected health model focused on patients’ needs and the efficient use of patient data through digital analytics promises valuable results (Pikkarainen et al., 2018; Wimmer, Yoon, & Sugumaran, 2016).

The conceptual definitions of connected health have been briefly discussed in the previous chapter. The following part of this chapter will describe connected health as the empirical context of the research depicting the application areas and scope of connected health. Further, a sub-chapter discusses the various stakeholders involved in connected health. Additionally, the ecosystem concept is briefly reviewed as it appears in the connected health related literature.

2.1 Application areas and scope of connected health

Chouvarda et al. (2015) identify three (3) main areas of scope and application for connected health. These are: 1) management of chronic diseases and comorbidities, 2) lifestyle, prevention and rehabilitation for the citizen and the patient, and, 3) frailty and ambient assisted living. In addition to these, this research identifies “futures digital hospitals” to be another core application area of connected health that will help in facilitating various digital-intensive services within the boundaries of hospitals.

In the age of a growing elderly population, chronic disease is identified as the main reason for hospitalization. Since its inception, initiatives in connected health have focused on patients with chronic disease (Barr et al., 2012). Chouvarda et al. (2015) noted that, connected health aims to help chronic disease patients by: a) enabling disease management from home and facilitating the fine-tuning of treatment, b) preventing hospitalization by making on-time decisions and c) by training the patient for self-care and compliance.

Patient engagement and active self-management within chronic disease groups has been reported to be dramatically improved by using connected health (Agboola et al., 2013). Agboola et al. (2013) highlighted the great value of connected health in managing chronic diseases, but also mentioned its limited application in preventing these diseases. However, more connected health services are appearing which fall under the lifestyle and rehabilitation area of application and these offer preventive practices as well (Chouvarda et al., 2015).

Although lifestyle management is sometimes observed as a separate stream by healthcare professionals in different contexts, its relationship with healthy living

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and the prevention of disease has been established in the literature (Chouvarda et al., 2015). Under the overarching theme of disease prevention, more specific connected health projects are in progress for pediatric surgery and rehabilitation cases (Wille, 2017), healthy nutrition, prevention of obesity, sleep hygiene and quality, maintenance of adequate levels of physical activity , orthopaedic surgery and rehabilitation cases (Icory, 2018). The abovementioned list reflects the scope of connected health in numerous domains that are related to lifestyle and prevention. The application of connected health solutions is suitable for facilitating rehabilitation processes for affected patients as well as other cases.

The ambient assisted living applications address needs of frailty and focus mainly on the elderly population for home care for independent living and quality of life (Memon, Wagner, Pedersen, Aysha Beevi, & Hansen, 2014). This includes multifaceted approaches including monitoring vital signs and movement, physical and cognitive coaching, self-assessment and social support. Smart home technologies are advancing through experimentation in this domain (Dawadi, Cook, Schmitter-Edgecombe, & Parsey, 2013).

As another emerging stream of connected health’s application, futures digital hospitals will consist of various advanced technologies, such as critical medical devices, intelligent information systems and digital communication tools which are fully integrated to improve staff productivity, hospital operations, patient safety, and the overall patient experience (Himidan & Kim, 2015). Among these, many will be wireless mobile devices, wireless wearables and thousands of smart IoT devices for various kinds of measurements (Gomes, Iivari, Ahokangas, Isotalo, & Niemelä, 2017; Himidan & Kim, 2015).

In future, hospitals and surgical tools will be revolutionized with intelligence and connectivity, i.e., providing more assistive functions by utilizing sensors, processors, data collection, software algorithms and interfaces that will be, embedded in tools that will support surgeons in their decision-making (Himidan & Kim, 2015). Robotic-assisted surgery (RAS) is considered a good example of this kind of transformation. The rapid adoption of minimally invasive surgery (MIS) and today’s information revolution not only improves surgical outcomes and the patient’s life but also changes the patient-physician relationship.

‘Smart’, i.e., IoT-based technologies are going to transform medical devices and service systems into smart hospitals. Smart hospitals will be able to extrapolate data from totally digitalized and automated data collection procedures and devices. This will involve tracking and delivery between systems, devices, patients, and healthcare professionals and organizations (Sutherland & Van Den Heuvel, 2006).

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In future, virtual hospitals and personalized medication will become part of patient care. Patients will be able to visit virtual hospitals or e-clinics for clinical purposes without the presence of healthcare professionals, while procedures and communication can be managed via remote management and connected health solutions (Haq, 2008).

2.2 Stakeholders in connected health

From a general perspective on the connected health context, Chaher et al. (2017) identify at least four categories of stakeholders: patients, technology suppliers, healthcare practitioners, and public policy institutions. The service design, development, innovation and deployment process becomes more complex due to the multi-stakeholder human factors. In the existing literature (Cafazzo, Casselman, Hamming, Katzman, & Palmert, 2012; Chouvarda et al., 2015; Craven, Young, Simons, Schnadelbach, & Gillott, 2014; Dennis & O’Toole, 2014; Gualtieri et al., 2018; Imbeault, Bouchard, & Bouzouane, 2011; Keung, Lee, Lu, & O’Keefe, 2013; McCallum, 2012; Miloff, Marklund, & Carlbring, 2015; Sardi, Idri, & Fernández-Alemán, 2017) authors explored the patient segment to identify more suitable target groups for connected health.

The connected health model includes human-centrism in decision making for both personalized and public healthcare (Chouvarda et al., 2015). The human-centrism aspect is depicted in the involvement of patients and citizens in the process of data-collection and result dissemination. Although studies concerning connected health use cases are still emerging; some examples focus on patients and citizens in the adult population (Gualtieri et al., 2018), pediatric patients (Gomes, Pikkarainen, et al., 2017), dementia sufferers (McCallum, 2012), and chronic disease patients (Sardi et al., 2017). As one form of connected health services, gamified applications address various kinds of patients and citizens (Sardi et al., 2017). Some examples of this are discussed in the literature including: type 1 diabetes patients (Cafazzo et al., 2012), Alzheimer’s patients (Imbeault et al., 2011), citizens interested in fitness and outdoor activities (Keung et al., 2013), mental health (Craven et al., 2014; Dennis & O’Toole, 2014; Miloff et al., 2015), mental disorders in children, and obese citizens (Pereira, Duarte, Rebelo, & Noriega, 2014).

Gualtieri et al. (2018) identified the older adult population as one of the key stakeholder groups for connected health. They further saw adoption challenges and barriers to connected health among this stakeholder group to be high. Although the lack of digital literacy is identified as a key challenge, it has been observed to have

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been surmounted by providing proper orientation, coaching and training programs. Chouvarda et al. (2015) notes that improvements in digital literacy across different demographic groups positively influence the gathering of continuous health-data that can be used for analysis.

While general physicians, specialist physicians and, nurses are obvious stakeholders because they are core stakeholders in the healthcare processes, Barr et al. (2012) discuss the value of pharmacists as healthcare practitioners in connected health who can play an intermediary role. In a UK based study, they marked the frequency of patients visiting doctors and nurses were less than half the times patients visited pharmacists. Hence, deploying different types of connected health interventions through the pharmacist channel would reduce substantial amount of strain on other healthcare professionals in the system.

Chaher et al. (2017) mentioned public policy institutions as the third key stakeholder in connected health. It is conceivable that policy institutions will play a pivotal role in the sustainability of many sectors, which applies to connected health as well since it is an emerging model of healthcare. For sustainable and successful deployment of connected health on a mass level, policy formulation and documentation that fosters such an approach is required (Chaher et al., 2017). Existing use cases and available technologies have paved the path for promising results and innovations are breaking ground frequently in this context. In such case, policy institutions from different domains such as health, wellness, education, social welfare, etc. need to be lobbied to create policies that support the infrastructural development for connected health.

Finally, the technology suppliers are business entities bringing connected health interventions to other stakeholders (Chaher et al., 2017; Gomes, Pikkarainen, et al., 2017). The interventions range quite variedly depending on use cases and application areas. However, these technology suppliers will eventually create the building blocks of connected health in a specific society. In doing so, the technology suppliers will also play a vital role in the formation of the connected health business ecosystem.

2.3 The connected health ecosystem

The literature on the digital transformation of healthcare discusses technical ecosystems in the scope of connected health ecosystem (Chouvarda et al., 2015; Janjua, Hussain, Afzal, & Ahmad, 2009; Serbanati et al., 2011). While the main focus of this dissertation is on business ecosystems for connected health, it is

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worthwhile to briefly review the existing literature on how the concept of an ‘ecosystem’ is approached and perceived in discussions of connected health, digital healthcare, digital health, etc.

Chouvarda et al. (2015), in their short paper, briefly discuss the outlook of connected health ecosystems from a service provider perspective by identifying three key aspects. These are: 1) sensor systems, 2) data management, and, 3) data analytics, with the integration of intelligence and modelling. Janjua et al. (2009) identified that the challenge of data sharing between heterogeneous systems within the digital healthcare sphere calls for a technical ecosystemic approach. In their technical study, eight elements were identified as key to the ecosystem. These were web portals for doctors, lab information systems, pharmaceutical networks, office manager systems for doctors, web portal for patients, counterfeit medicine verification, accounting and billing systems, and hospital management systems.

Serbanati et al. (2011) stressed the ongoing paradigm shift in global healthcare from organization-centric to patient-centric forms and note that this requires a collaborative, multidisciplinary, and cross-organizational approach. A platform-based service infrastructure is presented as an ecosystem in their study (Serbanati et al., 2011:623). Covering most of the elements proposed by Janjua et al. (2009), Serbanati et al. (2011) note that a digital healthcare ecosystem could connect general practitioner’s offices, hospitals, pharmacies, laboratories, and different units as well. These established connections would enable seamless decision-making with feedback loops and make way for new service creation utilizing the availability of data.

Although the technical perspective can be observed in the existing literature on ecosystemic approaches in digital healthcare or connected health, there are some key insights which can be translated from technical viewpoints into business or practice perspectives. As Janjua et al. (2009) noted, there is a need for a combination of services that requires the utilization of heterogeneous data and that this can be solved by interoperablity techniques. From a business and innovation perspective, the potential of an ecosystemic business context rises in such areas. Based on expert interviews, Gomes & Moqaddemerad (2016) identified that the future of healthcare would need to move towards ecosystemic business contexts where smart services and solutions would enable patient-centric healthcare services.

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Figure 3: Summarizing the central elements of Connected Health context.

Figure 3. summarizes the central elements of the literature review presented in this chapter surrounding the Connected Health context. The following chapter focuses on the theoretical aspects of this research and presents a literature review on business ecosystems and business models which contributes towards designing the theoretical framework of this study.

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3 Theoretical foundations “Walker, there is no road, the road is made by walking.” (Antonio Machado)

Chapter 3 summarizes the literature review on the theoretical foundations of this research. As a phenomenon-driven and exploratory piece of research, this study applies basic logic from the theory of evolution. Further, building on the existing literature on business models and business ecosystems the author attempts to build a theoretical framework.

Van De Ven & Poole (1995) summarized four main schools of theories to understand and explain organizations in change and the processes of change; life-cycle, evolutionary, dialectic and teleological. According to the authors, life-cycle models and evolutionary models are prescriptive. Further, dialectic and teleological models are constructive. On the one hand, life-cycle models are simplistic, they reduce complex systems of change to an over-simplified sequence of stages and the organization needs to go through each stage to arrive at the next. A life-cycle model is often used by practitioners for strategy design and goal setting. On the other hand, the evolutionary model highlights scarcity, environmental selection and competition within certain ecosystems. The evolutionary perspective also captures change on a collective level. Charles Darwin (1859) described evolution as the process through which the variety of organisms living in the earth emerged, and the process of evolution continues through the natural selection of organisms based on the variations among them. Darwin additionally described the importance of several ecological conditions such as competition, predation, and climate as influencers of natural selection for species evolution.

Although evolution and ecosystems have not been directly linked in the previous literature, Nakajima (2017) highlights the growing research interest linking evolutionary processes of populations and ecosystem dynamics. The field of eco-evolutionary dynamics focuses on the ecological dynamics of communities, or ecosystems, in connection with evolutionary processes of component species (Hendry, 2016). Although in the management and international business literature concepts such as evolution and ecosystems are used as metaphors and are borrowed from different disciplines, the utilization of these metaphors in the business studies domain maintains some basic tenets of the theoretical assumptions. In this research, an evolutionary perspective is used to explore the business ecosystem in the connected health context by analyzing stakeholder business models.

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In Darwinian evolution, four elements are of importance: 1) a particular environment or the so-called selective environment; 2) a variation of organismal traits in the population, which includes the generation of new genetic types; 3) organisms with different traits exhibiting differential survival and reproduction (i.e., natural selection); and 4) the heritability of organismal traits. Although critical, Nakajima (2017) has also emphasized the importance of holism, stating that whole entities are more than mere sum of their parts and that there is a natural tendency toward forming “wholes” in the universe. Based on the holism aspect, Nakajima (2017) extended the four elements of Darwinian evolution to outline the adaptive evolution of populations existing in ecosystems of interaction. From the adaptive evolution perspective: 1) ecosystems generate selective environments for their component species through ecosystem dynamism; 2) ecosystems generate new genetic types through lateral gene transfer, hybridization, and symbiogenesis among the population of the ecosystem; 3) ecosystems generate mechanistic processes of replacement of an old type with a new type. This study assumes that in the business ecosystems context, these notions can be related to business environments, variation between the stakeholders, sustainability and re-configuration, and replicability (Dedehayir et al., 2018; Nakajima, 2017).

Dawkins (1981) wrote, “in the beginning was simplicity”, and the complexities were built upon the simplicities. In the same line, business models1 need to be conjectured as depicting the simple logic of doing business in the business environments. Industries have experienced replications of similar business models in patterns (i.e., unbundling business models, the long-tail business model, multi-sided platform business models, the freemium business model, open business models) (Osterwalder & Pigneur, 2010). The tendency of successful business models to spread can be considered as memetic replication (Dawkins, 1981). However, the unit of such replication is not clearly understood, and it is not certain whether it is the business model itself or whether it is some parts (elements) of the business model. In a digital-intensive era, business ecosystem stakeholders often enable the replication of one business model in different locations (Martins, Rindova, & Greenbaum, 2015). For example: in the case of ride sharing applications, once Uber succeeded in various markets, different ride sharing apps started to emerge using very similar (if not the same) business model, with different

1 A business model can be perceived as a boundary-spanning unit of analysis (Zott et al., 2011) from the conceptual perspective, or practically as a vehicle to exploit a business opportunity (Zott & Amit, 2010). A detailed review on business model is presented in section 3.2.

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logic, using the same platforms to reach to their customers. Focusing on alliance capabilities, Kohtamäki, Rabetino, & Möller (2018), highlighted the importance of integrating and learning from strategic alliances. In business ecosystems too, such capabilities that can be sourced through business models are important.

Business models are innovated (BMZ, 2015) and they mature over time through evolution (Dunford, Palmer, & Benveniste Jodie, 2010); yet, the basics are built on an existing (either previously owned or borrowed) business model. Several types of business models have been observed to have existed over the centuries throughout history (e.g., the Catholic Church model, the mafia mode, the colonial model, etc.). Several business models populate the business environments and are functional, yet most business model research tend to focus on focal firms rather than studying the holistic phenomenon astride the building blocks (Iivari, 2016). Although the business model concept can be seen as a boundary-spanning unit of analysis (Zott & Amit, 2010), this characteristic value of business models is underutilized in boundary-spanning, ecosytemic contexts (Gomes, Iivari, et al., 2017; Iivari, 2016). According to Van De Ven & Poole (1995), in biological evolution, change occurs through a continuous cycle of variation, selection, and retention. The business ecosystems literature admits that ecosystems evolve over time, however, the life-cycle model (Moore, 1993) utilized in extant research emphasizes a single-entity perspective of the multi-stakeholder environment to address change. This study applies the evolutionary perspective to business ecosystems by focusing on selection, variation and retention (Van De Ven & Poole, 1995).

The following part of this chapter is divided into two sections. The first section describes business ecosystems as a concept as it is discussed in the existing literature. The second section presents a brief review of the business models literature regarding the ecosystemic context. Finally, the chapter summarizes the overall theoretical framework of this research.

3.1 Business ecosystems as an interdependent multi-stakeholder environment

A growing trend in the current global economy, aided by digital technology, is that these digital technologies are becoming intertwined with traditional non-digital products and services (Iivari et al., 2016; Turber & Smiela, 2014). The concept of ‘ecosystems’ in business related contexts comes from biological sciences, which similarly to biological ecosystems depict multiple interdependent networks of

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organizations in a specific context (Dedehayir et al., 2018). There is an endless reciprocal cycle of evolution where interdependent species affect each other in the process of natural selection, which is true for both natural ecologies and social systems as business ecosystems (Moore, 1993). Perceiving business ecosystems as network of complementary business models, stakeholder business models can be viewed as the “digital species” (Wang & De Wilde, 2008) which represent and connect the different stakeholders in the business ecosystem.

Although business ecosystems as a concept first became prominent in the high-tech and information-intensive industries, the concept has gained popularity in multiple industries since then (Baldwin, 2012). Ahokangas, Boter, & Iivari (2018) comments on the overall research endeavors on business, entrepreneurship and innovation ecosystems are quite versatile, as there are numerous interpretations of what they are and how to approach them.

In extant literature, business ecosystems are considered as networks of firms that together produce a holistic and integrated technological system that eventually serves the overall customer set of the intended sector (Ågerfalk & Fitzgerald, 2008; Bahrami & Evans, 1995; Basole, 2009; Dedehayir et al., 2018; Lusch, 2011). One of the earliest authors on business ecosystems, J. F. Moore, (1993) noted that in business ecosystems, organizations do not only compete neither do they merely cooperate, rather with the presence of both mindsets, organizations co-evolve their capabilities around new innovations. Based on this, Dedehayir et al. (2018) notes that the management literature uses the constructs of “business ecosystems” and “innovation ecosystems” interchangeably.

Ecosystems usually evolve into existence due to either or both endogenous and exogenous forces (Mäkinen & Dedehayir, 2012). On one hand, business ecosystems evolve because of traditional cooperation-based business networks which can be considered an endogenous force. On the other hand, an exogenous force of ecosystem evolution can be observed in the case of structuring or orchestrating the evolution from the start with a clear vision.

3.1.1 Stakeholders and roles in business ecosystems

Business ecosystems are considered to comprise suppliers, complementors, system integrators, distributors, advertisers and also finance providers (VCs, corporate investors, governmental funding agencies, investment banks, etc.), universities, other research bodies, regulatory authorities, standardization authorities and customers (Adner & Kapoor, 2010; Iyer & Davenport, 2008; Li,

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2009; Meyer, Gaba, & Colwell, 2005). Simply, business ecosystems (e.g., platforms) enable connections between multiple suppliers with their customers (Kohtamäki, Parida, Oghazi, Gebauer, & Baines, 2019). In an ecosystemic context there are many roles to be played by the participating stakeholders. Some key roles that are discussed in the literature are often described as a: keystone, platform leader, ecosystem leader, niche player, complementor, wannabe or dominator (Cusumano & Gawer, 2002; Iansiti & Levien, 2004; Mäkinen & Dedehayir, 2012; Moore, 1993).

The Keystone plays the role of orchestrating the overall ecosystem activities in general and as a consequence their decisions in turn affect the performance of other stakeholder to some extent as well as their own (Mäkinen & Dedehayir, 2013). Tiwana, Konsynski, & Bush (2010) highlight one of the key activities of the keystone to be designing the overall platform/architecture of the ecosystem, which can play a pivotal role in defining the purpose and scope of the ecosystem.

Although the keystone is supposed to be the leader of a network of companies for a specific objective; it is often the case that another participating firm challenges the keystone by supplanting other members of the network through vertical and horizontal integration and thus become more powerful. This type of rival firm is known as a wannabe. If a wannabe succeeds in its challenging role, they are also often described as dominators (Cusumano & Gawer, 2002). Both wannabe and dominator roles are usually negatively perceived in a cooperative partnership contexts, however some level of challenge and disagreement can be useful for faster evolution of the ecosystem (Gomes, Pikkarainen, et al., 2017).

Finally, despite being mostly unnoticed for their direct contribution to the ecosystem building and evolution, niche players (or complementors) form the biggest population of the ecosystem. Niche players are there to support the keystone in order to create and capture ultimate customer value (Mäkinen & Dedehayir, 2012). In doing so, these complementors are responsible for creating two kinds of value: generic value and non-generic value (Dedehayir et al., 2018). Generic value complementors are those who can be replaceable comparatively easily. However, complementors with unique value propositions tends to offer non-generic value for the keystone that becomes difficult to replace or substitute. While the keystone orchestrates the overall ecosystem value creation, without proper inputs from these niche players/complementors, the goal of co-evolution could fail. Moore (1993) states that keystone firm play an important role in an ecosystem’s value creation, value capture and even value sharing within the ecosystem. Thus, they can attract more complementors to the ecosystem to participate further.

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3.1.2 Interdependent and interaction properties in business ecosystems

Innovation is sometimes seen as a cure-all medicine for all kinds of issues that firms face, including profitability, revenue boosting, market share growth and also to increase their efficiency (Adner, 2012). Adner (2012) further notes that in a world which has become increasingly interdependent, isolated innovation does not meet the same success rate compared to shared innovation, co-creation or distributed innovation according to Baldwin (2012). Moore (1993) states that companies and other stakeholders’ capabilities usually co-evolve in business ecosystems around new innovations. They work collaboratively and competitively to innovate new ideas, products and services to provide customer value and strive for the next iterations of innovations. Over the past several decades, competition between standalone corporations has faded and has moved towards competition between ecosystems, where in many cases large corporations lead the ecosystems. This ecosystemic co-evolution and competition is mainly powering today’s industrial transformation (DeAgonia, Gralla, & Raphael, 2013; Kelly, 2015).

In this same vein, Farrell & Saloner (1984) noted that building on compatibility and standardization is one of the drivers for shared innovation. Farrel and Saloner noted standardization is voluntary, not always forced by governments or big corporations; instead, it could arise from adaptation in the market. Compatible services and products seem to arise to support the value of standardized services and products. Innovation based on standardization and compatibility leads to modularity of services and products. Jacobides, Macduffie, & Tae (2016) marks that modularity allows ecosystem emergence as it enables a set of distinct yet interdependent firms to coordinate without a full hierarchical setup.

Baldwin (2012) notes that autonomy in problem selection and control over their own innovation/creation by individual participants remains one of the key enablers for distributed innovation and hence ecosystemic evolution. During the lifecycle stages of an overall business ecosystem, such autonomy will play an important role in the competition that takes place between the ecosystem participants and also with outside players. The overall system keeps evolving by bringing in new opportunities for recombination and re-configuration.

While compatibility and standardization relate to the generic value complementor roles in business ecosystems, to maintain a competitive market advantage, ecosystems’ players need to identify unique value propositions by

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involving non-generic value complementors. The balance between standardization and specialization in business ecosystems results in longer sustainability.

3.1.3 Evolution of business ecosystems and the search for generic and non-generic value complementors

In Moore’s observation, just like biological ecosystems, a business ecosystem also gradually moves from a random collection of elements towards a more structured community. While self-governance is argued to be a key characteristic of business ecosystems, as the ecosystem matures over time it is observed to become more structured due to collaborative and interaction-based decision making as a form of natural selection in business ecosystems. Moore (1993) identified four stages in the life cycle of a business ecosystem. These are: 1) birth, 2) expansion, 3) leadership, and, 4) self-renewal or death. These life-cycle stages reflect the potential growth-path of a business ecosystem as heuristics, which does not completely capture the essence of evolution.

During the first stage, birth, larger corporations who usually develop the main technology around which the ecosystem would likely emerge wait to observe how the market sorts itself out. The main objective that is achieved in the birth stage is identifying a customer value proposition which is adopted by a community of stakeholders for product/service innovation. This leads to the accumulation of multiple stakeholders to work towards a shared goal for value creation and capture in the longer run, hence the first attempt in searching for generic and non-generic value complementors. (Moore, 1993)

When there are a substantial number of interested generic and non-generic value complementors to collaborate towards a shared goal, the business ecosystem moves onto the second stage, expansion, to attract more stakeholders and strengthen their market position in comparison to rival ecosystems. This can be done in two ways. First, this is done by extending the customer value proposition to an extent which becomes an obvious preference for customers to counter the rival ecosystem’s customer value proposition. Second, by attracting a sufficient number complementors so that rival ecosystems will not have enough ground to continue with their shared goal without sufficient stakeholders sharing the same goal. Thus, they squeeze out rival ecosystems from the market competition. However, practically, competing ecosystems will continue to survive in market conditions, as absolute triumph is not feasible since rival ecosystems will attempt to continue with innovation activities to revive their market position. (Moore, 1993)

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Ecosystem leadership as noted by Moore (1993) is the key in the third phase, which becomes an issue when the ecosystem is strong and profitable enough and when fighting over the leadership makes sense. Often, ecosystem starters seem to lose ground during this phase and wannabes seem to take advantage with their collaborative actions with other complementors and take charge of the ecosystem. It is also a strategic decision on the part of the ecosystem leader, who needs to decide whether it is wise to lead the pack. Does it serve a sustainable or temporary competitive advantage, or whether leadership brings an unnecessary burden that can outweigh the competitive advantages. (Moore, 1993)

Moore (1993) notes that none of the business ecosystems like their biological counterparts are immortal. When ecosystems as a whole overestimate the customer value propositions and the market prefers something else than their offering, the said business ecosystem will start declining. In the process of decline, if the business ecosystem fails to undertake self-renewal action, it will eventually perish. Failure to comprehend the necessity for continuous innovation in an ecosystemic context will not allow growth. Moore (1993) further states that natural ecosystems sometimes collapse when environmental conditions change too rapidly. This can also happen for business ecosystems similarly if the environmental changes are not properly understood and considered in strategic decision making.

In the literature on business ecosystems, there have been limited contributions to Moor’s life-cycle model. However, Dedehayir et al., (2018) expanded the birth/ emergence phase and identified three more phases as preparation, formation, and operation. Throughout the four phases of ecosystemic life cycle, one key aspect is constant, the search for more generic and non-generic value complementors. While the search for generic complementors is fairly well structured, identifying a non-generic value complementor requires the formulation of frameworks.

Unlike biological ecosystems, business ecosystems are social systems, in which individual people are involved in decision making. Furthermore, numerous business models which are designed based on organizational needs are in play and multiple complex networks are maintained by conscious choice, all of which comes down to social awareness. Instead, an ecosystemic perspective in comparison to a traditional industrial boundaries perspective provides us with a lens to examine the boundary-spanning properties of stakeholders and co-evolution, co-creation, and co-competition that is taking place.

The business ecosystem terminology is often used in parallel with concepts such as “clusters” or “networks”, which also leads to a degree of confusion over why we emphasize ecosystems instead of “networks”, “clusters”, or “meta-

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organizations”. The ecosystems perspective stems from ecology, whereas networks stem from strategy (Lehto, Hermes, Ahokangas, & Myllykoski, 2013), while the “meta-organizations” perspective stems from organization studies. Networks are purposefully built, while ecosystems are at first emergent and constantly evolving. Networks map the relationship between necessary and involved stakeholders from a focal firm’s point of view, whereas ecosystems cross the boundaries of traditional industry, products, organizations and services (Ahokangas et al., 2018); so, it is difficult to map clear boundaries for ecosystems (Jansson et al., 2014). In practice, multiple networks can be present in a business ecosystem and beyond its blurred boundaries. It is this aspect that also enables cooperation between business ecosystems. Clusters in most cases are identified by their geographical proximity (Peltoniemi, 2004); while for ecosystems value proximity is a more important notion.

Lappi (2017) considered multifaceted theoretical foundations in order to study the context of business ecosystems. In his view these are: organization and strategy, business networks, customer and service dominant logic, and project business. Based on the above mentioned theoretical foundation, Lappi (2017) further identified important perspectives and characteristics related to business ecosystems that need deeper qualitative understanding, including: mapping, actor roles and relationships, value creation and operational logic, ecosystem healthcare and success, ecosystem evolution, and lastly interconnectedness and governance.

Figure 4: Summary of business ecosystems literature review.

Figure 4 presents a summary of the literature review presented in this chapter. Combining the overall discussion can be brought down to three key theoretical aspects. First, business ecosystems as constructs in which stakeholder are connected through different roles. Second, these stakeholders are in constant interdependence and interaction-based decision-making enables the survival of the

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firm and the ecosystem. Third, there is a continuous recombination and re-configuration of generic and non-generic value through stakeholder complementation. These three aspects of business ecosystems are further analyzed in the scope of this dissertation.

3.2 Business model approach

3.2.1 Origin and definitions

In this brief chapter, I attempt to consolidate the business model conceptualization for ecosystemic contexts. In doing so, I briefly review the existing business model literature to understand how the concept has grown over the past decades and additionally argue the lack of attention paid to ecosystemic contexts by business model scholars. A business model can be perceived as a boundary-spanning unit of analysis (Zott et al., 2011) from the conceptual perspective, or practically as a vehicle to exploit a business opportunity (Zott & Amit, 2010) and thus related to opportunity exploration and exploitation, advantage exploration and exploitation, as well as value creation and capture (Ahokangas et al., 2014).

The term “business model” was first coined in the literature by Bellman and Clark in 1957 (Wirtz, 2013) and gained popularity during the 1990s (Amit & Zott, 2001). Until the 1990s most of the publications mentioning the term or concept of business models were scantly relevant to management, strategy or business studies (Wirtz, 2013). However, since the turn of the new millennium, studies on business models as a research stream has been continuously growing. Surveying the previous literature on business model research, it is evident that academics are yet to decide on a uniform understanding of the concept (Alt & Zimmermann, 2001; Zott et al., 2011).

Linder & Cantrell (2000) argue that there are many publications where the term is used with varied meanings. Zott et al. (2011) further state that researchers often adopt the concept as they see fit to their purpose. On one hand, leading business model authors agree to the fact that business models are yet to become a theory per se (Demil & Lecocq, 2010; Lambert & Montemari, 2017), so the diversified use of the term proves the concept is multifaceted (Lambert & Davidson, 2013; Lecocq, Demil, & Ventura, 2010). On the other hand, the lack of a uniform understanding of the concept poses potential confusion, and thus hinders cumulative research efforts on business models (Zott et al., 2011).

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Table 2 highlights some of the most prominent definitions of business models in the literature. Additionally, I have added a few remarks for each definition, to explain how they have defined the business model concept from the perspective of this dissertation.

Table 2: Perspective of different business model definitions in previous literature.

Author Definition Perspective

Timmers

(1998)

The business model is an architecture of the product, service

and information flows, including a description of the various

business actors and their roles; a description of the potential

benefits for the various business actors; a description of the

sources of revenues.

Product/service

innovation.

Focal firm view.

Tapscott,

Ticoll, &

Lowy (2000)

Business model is a distinct system of suppliers, distributors,

commercial service providers and customers that use the

Internet for their primary business communication and

transactions.

Internet based

businesses.

Value chain network

view.

Weill & Vitale

(2002)

Business model as the roles and relationship between a firm’s

consumers, customers, allies and suppliers that identifies the

major flow of product, information and money, and the major

benefits to participants.

Mentions value chain

network.

Emphasizes the focal

firm view.

Transaction identification.

Chesbrough

&

Rosenbloom

(2002)

The business model is the heuristic logic that connects

technical potential with the realization of economic value.

Technology

advancements for

economic value.

Focal firm view

Magretta

(2002)

Business models are stories that explain how enterprises work.

A good business model answers Peter Drucker’s age-old

questions: Who is the customer? And what does the customer

value? It also answers the fundamental questions every

manager must ask: How do we make money in this business?

What is the underlying economic logic that explains how we can

deliver value to customers at an appropriate cost?

Business model as

narrative.

Focal firm view

Chesbrough

(2003)

Business model is a cognitive map across domains, able to help

managers in identifying a target market, articulating the value

proposition, building the value chain and the costs/margins

structure, describing the position of the firm in the value network

and formulating the competitive strategy.

Focal firm view.

A cognitive map of the

competitive field.

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Author Definition Perspective

Morris,

Schindehutte,

& Allen,

(2005)

It is a concise representation of how an interrelated set of

decision variables in the areas of venture strategy, architecture

and economies are addressed to create sustainable competitive

advantage in defined markets. It has six fundamental

components: Value proposition, customer, internal processes/

competencies, external positioning, economic model, and

personal/ investor factors.

Business model as set of

decision variables.

Focal firm view.

Osterwalder,

Pigneur, &

Tucci (2005)

A business model is a conceptual tool containing a set of

objects, concepts and their relationships with the objective to

express the business logic of a specific firm. Therefore we must

consider which concepts and relationships allow a simplified

description and representation of what value is provided to

customers, how this is done and with which financial

consequences.

Focal firm view.

Shafer,

Smith, &

Linder (2005)

Business model as a representation of firm’s underlying core

logic and strategic choices for creating and capturing value

within a value network.

Focal firm view

Baden-Fuller,

Macmillan,

Demil, &

Lecocq

(2008)

Business model is “the logic of the firm, the way it operates and

how it creates value for its stakeholder”.

Focal firm view

Logic model view

Amit & Zott

(2001)

and Zott &

Amit (2010)

The business model depicts “the content, structure, and

governance of transactions designed so as to create value

through the exploitation of business opportunities” (2001: 511).

Based on the fact that transactions connect activities, the

authors further evolved this definition to conceptualize a firm’s

business model as “a system of interdependent activities that

transcends the focal firm and spans its boundaries” (2010: 216).

Focal firm view (2001).

Discusses value chain

logic with the idea of the

“boundary spanning”

argument (2010).

Teece (2010) A business model articulates the logic, the data, and other

evidence that support a value proposition for the customer, and

a viable structure of revenues and costs for the enterprise

delivering that value. It is about the benefit the enterprise will

deliver to customers, how it will organize to do so, and how it

will capture a portion of the value that it delivers.

Focal firm view.

Onetti,

Zucchella,

Jones, &

McDougall-

Covin (2012)

The business model is the way a company structures its own

activities in determining the focus, locus and modus of its

business.

Focal firm view.

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A significant stream observable in the list of definitions above is that most of the authors based their definition of business model on the focal firm (Amit & Zott, 2001; Baden-Fuller et al., 2008; Chesbrough, 2003; Chesbrough & Rosenbloom, 2002; Magretta, 2002; Morris et al., 2005; Onetti et al., 2012; Osterwalder et al., 2005; Shafer et al., 2005; Teece, 2010; Timmers, 1998; Weill & Vitale, 2002). Additionally, even the few authors who mention the value chain/ supply chain perspective in defining the business model do not necessarily stress the application or suitability of the concept as a holistic enabler for the whole network (Tapscott et al., 2000; Weill & Vitale, 2002; Zott & Amit, 2010). Although there have been limited academic publications on business models in business ecosystems, or even business models of the business ecosystem, in the following sub-chapter I attempt to conceptualize business models in ecosystemic contexts.

3.2.2 Key elements of business models in ecosystemic context: opportunity, value, advantage

“Elements” or “components” of business models are a common theme of discussion in the business model literature. Similar to the definitional ambiguity of the concept, the literature holds ample examples of “elements” or “components”. To name a few, while Hamel’s (2000) business bridge model identifies four main building blocks (i.e., customer logic, strategy, resources, and networks), the business model canvas (Osterwalder & Pigneur, 2010) presents nine elements of business models. Similarly, the lean canvas presents nine elements for lean startups (Maurya, 2012), and the business model wheel comes up with twelve questions to constitute a business model (Ahokangas et al., 2014). While the definitional ambiguity in the business model literature is an area of agreement among researchers, few studies have made an effort to address the lack of a generally accepted definition through systematic literature reviews to point out common themes (Massa, Tucci, & Afuah, 2017; Morris et al., 2005; Onetti et al., 2012; Shafer et al., 2005).

Interestingly, while these systematic literature review-based papers present overviews of the literature, they consequentially display a common theme in that the business model definitions are tied to the contexts they operate in (i.e., e-business, strategy, supply chain management, technology, information systems). Further, Shafer et al. (2005) identified forty-two different elements/components of business models that appear in the articles they reviewed. While many of the elements/components are often overlapping, the presence of similar and

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overlapping concepts is not considered problematic but useful. However, the fact that there are many overlapping elements mentioned in the literature is because the context plays an important role in how to conceptualize business models.

In view of the above, a conceptualization of business models and elements in an ecosystemic context is overdue. This section, hereafter, presents a brief overview of the existing business model literature that covers ecosystemic contexts. The brief review will assist in identifying the key elements of business models in ecosystemic contexts. As mentioned previously, academic work on business models in ecosystemic contexts is still emerging and there are a limited amount of resources to reflect on.

Ahokangas et al. (2014) present the business model wheel where they argue that business opportunities should be at the center of business modelling. This perspective on business models considers the way a company does business depends on what opportunities there are in the market to explore and exploit. Often companies find an opportunity that suits their resources and competencies. However, rarely does a single opportunity sustain a business for long in today’s highly competitive and volatile market conditions. In such cases companies need to find new opportunity and align their overall business model keeping business opportunities at the center. Since this tool acknowledges the expiry of opportunities and the renewal of the business model by finding new opportunities, it could be described as an action oriented transformational and dynamic tool. Ahokangas et al. (2014) argue that value propositions need to be based on market conditions and business opportunities.

Based on Onetti et al.’s (2012) work, the Business Model Wheel also considers the focus, locus and modus in designing a business model. The four sections in the Business Model Wheel are what, how, why and where. Usually the “what” section finds the value proposition, offering, customer segments and differentiation. Thus, this section covers the value creation and value capture logic of the business model. The “how” section typically concerns key operations, activities, partnership, marketing, mode of delivery, sales. So, this section mostly relates to opportunity exploration and exploitation. “Why” elements include cost drivers, cost elements, the basis for pricing, ways of charging etc. Finally, the fourth section, “where”, is about the locus of each actions and whether they are internal or external to the organization. The elements in the “why” and “where” differentiators can further define the advantage exploration and exploitation logic of the business model.

The Business Model Wheel provides us with an action-oriented way to design business models in volatile environments. This action-oriented approach considers

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uncertainty and renewal of opportunities which are relevant in an evolving ecosystemic context. This helps managers consider the overall changes an ecosystem might undergo and how the opportunities might change over time. It suggests that organizations need to revisit the core, the business opportunity, in order to remain profitable and competitive by making sure the opportunity they are exploiting still exists.

Ballon (2007) states that business models enable organizations to extend their organizational boundaries through vertical and horizontal integration in industries, conceivably in business ecosystems. Around this, Wirtz, Schilke, & Ullrich (2010) offers four mutually exclusive Internet-based business models. According to Wirtz et al. (2010), these business models are present in Web 2.0 and are related to connections, contents, context, and commerce. Building further, Yrjölä, Ahokangas, & Matinmikko (2015) interpreted these business models as parallel layers that can be present in the same business ecosystem, where “lower” layer business models are pre-requisites for the “higher” layer business models to exist.

The first layer is concerned with the connection-related business model in which a stakeholder provides connection services. Connection-related business models are relevant to connectivity for all sorts of devices and nodes through various communication channels (e.g., PCs, smartphones, tablets, IoT devices, etc.). The second layer is the business model focusing on monetizing content. In the content layer, all sorts of online content services (e.g., mobile video streaming, on-demand gaming) are classified and are accessible conveniently for the end user. The content might be peer-to-peer / user-oriented contents (i.e., exchange of personal content), and web browsing content (audio, video, text etc.).

The third, context, layer concerns the ability to create and monetize user content, equipment / user devices and system profiles and turn (big) data into meaningful information and knowledge through systemic virtual contextualization. The fourth layer concerns commerce, the ability to monetize any or all of the connections, contents, or context specific resources, actors or activities related to the ongoing communications. The 4C archetypes of the ICT business model present a framework that helps to understand the structure of a complex business ecosystem. From an ecosystemic perspective, the framework further enables delineating the opportunity, value, and value logic the business ecosystem (and the business models in the business ecosystem) is addressing.

Casadesus-Masanell & Llanes’ (2011) mixed-source business model approach offers a view of how various business model options can be generated and considered before implementing one in a business ecosystem environment.

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According to the mixed source software business model approach, services can be: open source (open core - open extension), open core (open core - closed extension), open extensions (closed core - open extension) and proprietary (closed core - closed extension). Although this model was offered specifically for the software industry, I perceive that a similar approach could be useful in other ICT contexts to scale up the value offering by adjusting the cooperation and industrial partnering model.

First, openness or closeness of a business model in business ecosystems will depend on opportunity exploration and exploitation. Second, depending on an organization’s choice of mixed source options, it should eventually translate the value creation and value capture logic of the firm. Further, the openness-closeness decision in conjunction with organizational resources and competencies will define the type of advantage exploration and exploitation that the company engages in. Casadesus-Masanell & Llanes (2011) argue that purely proprietary models result in higher captured value for organizations but lessen the scope of value creation for users. In contrast, purely open source models can deliver the maximum value to customers but reduce the captured value. In ecosystemic contexts, the key for organizations is to locate the best mix of openness and closeness to achieve an optimum level of value capture and creation (often value sharing among ecosystem stakeholders). From a strategic perspective, this approach to business modeling helps an organization to find a way to scale its business activities up or down through opening or closing its “core” or “extension” business activities.

On a different but related note, the notion of a business model as a dynamic capability has emerged with significant importance due to research advancements (Juntunen, 2017; Teece, 2018). Teece (2007) identified business models as a key micro-foundation which is relevant to “seizing” dynamic capabilities, and reaffirmed (Teece, 2018) the interdependence between the concepts of business models and dynamic capabilities. In this vein, Juntunen (2017) explored how business model change can be viewed through the dynamic capability perspective. Business models can be considered and implemented as a dynamic capability to operate in business ecosystems (Gomes et al., 2018).

The importance of interaction with the business environment along with knowledge creation, exchange and transfer has been mostly overlooked and the few studies conducted in this domain have utilized an abstract level of analysis (Haslam, Tsitsianis, Andersson, & Gleadle, 2015). While business models are considered to connect abstract strategies to implementation (Casadesus-Masanell & Ricart, 2010), this study recognizes that business models connect a firm with ecosystem stakeholders (Teece, 2010) through one or more of the following three broad

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activities in combination: opportunity exploration and exploitation, value creation and capture, advantage exploration and exploitation. Considering business models as a set of interdependent activities (Zott & Amit, 2010), a firm’s business model can include opportunity exploration and exploitation, value creation and capture advantage exploration and exploitation. Nielsen, Byrge, & Lund (2016) state that new entrepreneurs often struggle with opportunity spotting due to lack of experience of the business environment and processes formalized within it. This study argues that the business model is a higher-level strategic capability that can serve as a tool for sensing, seizing and transforming in business ecosystems through opportunity exploration and exploitation, value creation and capture, advantage exploration and exploitation functions to respond to environmental changes. Through these three business model functions, firms can identify suitable means of collaboration and alignment of activities. Based on when, how and why a firm forms an alliance with another participant in the ecosystem, they need to assess through which combination of functions alliances should be formed, i.e., opportunity exploration and exploitation, value creation and capture, advantage exploration and exploitation.

Figure 5: Summary of the business models literature review.

To summarize the discussion, this study considers opportunity, value, and advantage (Figure 5) to be the key elements of business models in an ecosystemic context. These identified key elements will further be used in this dissertation to define the theoretical framework.

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3.3 Towards exploring connected health business ecosystems through business models

This brief sub-chapter aims to summarize the lessons learned and put it all into a single theoretical framework. This theoretical framework will further be utilized in summarizing original publications included in this dissertation and for the analysis presented in the discussion chapter. The theoretical framework for this dissertation as it stands is based on the key concepts from the business ecosystem and business model perspectives, while keeping the research context of the study on the background. The key concepts together provides the basis for an analysis to explore connected health business ecosystems through business models and to understand how business models relate to business ecosystems. Figure 6 summarizes the key concepts of the theoretical framework. The connected health concept is defined in the literature as an overarching framework for patient centric digital healthcare of the future. Connected health technologies also help to build tech-aided scalable solutions. Key aspects of connected health have been identified as including: feedback loops, decision support, and ecosystemic co-innovation.

Rooted in the theory of evolution and field of ecology, the business ecosystems literature suggests business ecosystems as constructs (structures) in which multiple stakeholders are in constant interaction for survival and sustainability of the overall ecosystem. The interactions are often driven by the need for a re-configuration of generic and non-generic value complementation as a means of variability. Also, due to the ecosystemic proliferation in business environments, the competitive paradigm is observed to be shifting from corporations competing against corporations towards ecosystems competing against other ecosystems.

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Figure 6: Theoretical framework for this research.

Although the application of business models as a conceptual tool is scantly used in ecosystemic contexts, a growing stream of literature has acknowledged its potential as a boundary-spanning unit of analysis (Iivari, 2016; Zott et al., 2011). The various meanings and definitions of the concept proves its breadth in application. However, the application and relation of business models in ecosystemic contexts is still evolving. Surveying the literature, this study confers three main characteristics of business models as key elements in ecosystemic contexts. These are namely: opportunity, value, and advantage. Similarly, this study also identifies three key characteristics of business ecosystems as essential for the purpose of exploration. These are: the structure of the business ecosystem, interaction within the business ecosystem, and value re-configuration of generic and non-generic complementors in the business ecosystem.

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4 Research design and methodologies “Through reason man observes himself; but he knows

himself only through consciousness.” Leo Tolstoy, War and Peace)

This chapter aims to outline the ontological and epistemological assumptions that this study has relied upon. The chapter discusses the methodological choices made during this research including the research design, data collection and data analysis.

4.1 Research philosophy

A researcher’s philosophical standpoint regarding the body of science is reflected in this selection and it has important implications on the execution of the study. In social and human sciences, four philosophical distinctions are commonly acknowledged. These are positivism, post-positivism, constructivism and critical realism (Guba & Lincoln, 1994). These distinctions are relied upon in different ontological, epistemological and methodological choices. While the form and nature of reality is defined in the ontological principles, the epistemological principles explain the relationship between the researcher and the reality (Guba & Lincoln, 1994; Morgan, 1983).

Noor (2008) describes positivism as an approach aiming at creating knowledge through research that emphasizes the model of natural science. Thus, the researcher adopts the position of an objective scientist to collect facts about the social world and explain the facts by arranging them in a chain of causality, often through experiments. Easterby-Smith, Thorpe, & Lowe (1991) described post-positivism as an approach that concerns a socially constructed reality rather than an objectively explained one. The task for social scientists in the post-positivist approach is not necessarily to identify and measure the frequency of occurring patterns, but to appreciate the different constructs and meanings that people place upon their experience. In contrast to the positivist philosophy, the constructivist approach emphasizes understanding and exploration rather than explanation (Given, 2008). In doing so, human agency and sense-making require different ontological and epistemological approaches and importance compared to positivist and post-positivist schools of thoughts.

While the critical realist approach differs in some ways from the above-mentioned philosophical schools, it uses components from these approaches to

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provide a detailed account of ontology and epistemology. Emerging from the positivist versus constructivist ‘paradigm wars’ of the 1980s (Denzin & Lincoln, 2011), it resulted in a more comprehensive alternative to both as a philosophy of science (Brown, Fleetwood, & Roberts, 2002). In the CR approach, ontology (what is real, the nature of reality) is not reducible to epistemology (our knowledge of reality). CR admits that human knowledge only captures a portion of a deeper and vaster reality. CR treats the world as theory-laden, rather than theory-determined (Fletcher, 2017). Fletcher further mentions that in CR philosophy all knowledge can be true in variable degrees, while some is closer to reality than other knowledge.

Fletcher (2017) states that reality is arranged into three layers in CR ontology; the empirical level, the actual level and, the real level. The empirical level consists of the all the general events as we experience them. Events or objects are empirically measurable and can be explained through common sense, but these events are always filtered through human experience and interpretation. The middle level, actual, has no filter of human experience. It holds all the events that occur whether or not we experience or interpret them. Danermark, Ekström, & Karlsson (2019) note that true occurrences on the actual level can often contradict the observations at the empirical level. Finally, at the real level, causal mechanisms and causal structures are visible. These causal mechanisms eventually produce the events that are observable on the previous levels. In exploring a phenomenon, the goal of CR is to explain social events through these causal mechanisms.

The core aim of this study is to understand how to explore connected health business ecosystems through business models. The exploratory nature of this study spells the need to understand a phenomenon: “the connected health business ecosystem”. This is further facilitated by utilizing the concept of ecosystemic business models as a boundary-spanning unit of analysis through which stakeholders in business ecosystems connect with collaborating stakeholders. This study explores the “connected health business ecosystem” phenomenon by analyzing business models with an inside-out approach. From a research philosophy perspective, this research relies mainly on a critical realist perspective (Alvesson & Sköldberg, 2017; Fleetwood & Ackroyd, 2004; Fletcher, 2017). In critical realism, an entity or phenomena can exist without our identification of it (Fleetwood, 2005). This means that things can exist even when they are not being observed. This also applies to processes that take place in order to shape specific constructs, for example. In this study, this perspective is utilized to closer examine the business models and explore the big picture, the business ecosystem as a whole.

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Quantitative research designs dominate the fields of international business and strategic management research, although often the addressed research phenomena are dynamic, and the environments are volatile. This is surprising as the research methodology-related literature strongly points out that qualitative approaches are more appropriate for studying multidimensional, fuzzy, non-linear phenomena (Sinkovics, Penz, & Ghauri, 2008:6). However, studies focusing on business models are predominantly conducted with qualitative approaches considering the multimodality of environment issues. Similarly, the domain of business ecosystems research also seeks qualitative viewpoints to explore novel characteristics of the phenomena. Against this backdrop, the qualitative research approach was regarded to both suit this study and contribute to the international business and strategic management field from business models perspective.

Qualitative research approaches better facilitate the perception of linkages between events, actors and activities. Additionally, it is argued to enable the interpretation of factors that contribute to the connections between events, actors and activities (Bryman, 1999). Furthermore, qualitative research approaches enable deeper study of the examined phenomenon (Emory & Cooper, 1991), which is also important in this study. This relates to examining the same set of data from multiple analytical and theoretical angles. More specifically, to explore the various underlying logic of the connected health business ecosystem, the collected research data in this study is analyzed through multiple theoretical lenses to make collective sense.

According to Lee (1999:38), when new theoretical or managerial propositions can be expected but the details of the phenomenon are not fully known, qualitative research methodologies fit properly. To justify the suitability of qualitative methodologies in fuzzy and dynamic contexts, Bryman (1999:42) argued, “quantitative research conveys a view of social reality which is static in that it tends to neglect the impact and role of change in social life”.

Qualitative research approaches are particularly suitable for studying both business ecosystems and business models. This is because business ecosystems result from complex and lengthy evolutionary interaction processes throughout their lifecycles (Moore, 1993), in a network of complementary business models (Jansson et al., 2014) and are hence significantly difficult to code through quantitative research. Perceiving business models as dynamic capabilities (Juntunen, 2017), while dynamic capabilities are quite often embedded into organizations (Eisenhardt & Martin, 2000), so, it becomes more useful to apply qualitative methods with a critical realist approach to study the overall ecosystem.

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4.2 The qualitative case study method

Relying on qualitative methodologies, the researcher is able to retain flexibility and sensitivity to a context that has been scantly explored before. To achieve the objective of any research, the researcher needs to identify a research strategy to answer the research questions in relation to the theoretical foundations and the research context. The research strategy also needs to suit the philosophical standpoint of the researcher. Yin (2009) states a research strategy not only includes the plan on how to answer the research question, but also the propositions, units of analysis and the logic that links the data to the propositions and the criteria for interpreting the findings. The previous sub-chapter argues the use of qualitative research methodology in this study with a critical realist approach. This sub-chapter is designed to specifically discuss the appropriateness of a case study design for this research.

Denzin & Lincoln (2011) state that qualitative methodologies imply an emphasis on processes and meanings where researchers are interested in gaining insight, discovery and interpretation rather than hypothesis testing. Yin (2003) links a case to an event, an entity, an individual or even a unit of analysis. Yin (1981) also stated a case study can be conducted using both quantitative and qualitative evidence. The evidence may arise from various origins, such as fieldwork, archival records, verbal reports or observations. In practice, cases studies are empirical enquiries that investigate a phenomenon within its real-life context, rather than experimentation, using multiple sources of evidence.

Anderson & Arsenault (1998) observed case studies to be concerned with exploring how and why events occur, allowing the exploration of differences between actual and intended outcomes. Although the literature suggests that case studies do not need to study entire organizations to make sense of a phenomenon, studying a broader phenomenon that crosses the boundaries of organizations requires studying specific parts of the organization. Stake (1978) noted that a case in case studies does not necessarily need to be a person or an enterprise, “it can be whatever bounded system is of interest”.

Among various applications of case study methodology in research, Stake (1978) points out that in social and human sciences it helps to describe phenomena that are complex, holistic, and involve countless not well-isolated variables.

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Yin (2017) identifies three types of case studies: exploratory, explanatory, and descriptive. Exploratory case studies investigate distinct phenomena characterized by the lack of pre-existing knowledge through scientific research (Streb, 2012). Quite often exploratory case studies are applied as a preliminary step of an overall causal or explanatory piece of research in a relatively new field of scientific investigation. Explanatory case studies include identifying and explaining various causal natures and mechanisms which are in play within the phenomenon of interest (Harder, 2012). Finally, descriptive case studies focus on the description of events that occur (Noor, 2008), such as what the sales impacts are of a new marketing campaign. Pre-existing knowledge is usually well established for descriptive case studies that are utilized to specify the boundaries of the case.

Figure 7: The case study design in this research.

From a theory building and generalization of results perspective, authors such as Eisenhardt (1989) have lauded case studies as a useful methodology. However, Stake (1978) mentions that case studies suit more expansionist than reductionist purposes. To generalize and create new theoretical knowledge, the process of theory building from case study research becomes an iterative one that requires repetition of similar or varied approaches to justify the new meaning. In a similar vein, Yin (1981) notes, where cross-case analysis is the major goal of the research, the need to report single-case reports weakens the broader goal of achieving a cross-case analysis from the cases to determine generalized results.

As an overarching piece of research, this dissertation combines three separate case studies (depicted in Figure 7) around the same phenomenon of connected health business ecosystems. This study includes two multiple case studies and one

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single case study which are reported in detail in the original publications (Paper I, Paper II, Paper III, & Paper IV). This dissertation aims to combine the perspectives brought in through these case studies for the purpose of generalization and new knowledge building. In nature, this study contains both exploratory and explanatory types of case studies. In this research, hence, to explore the broad connected health business ecosystem, and to use business models as the unit of analysis and evidence for the case study, the research is initially based on individual stakeholder business models.

4.3 Research process and data collection

Cases can have either or both intrinsic and instrumental roles in research (Stake, 1995). On the one hand, Grandy (2012) identifies that the intrinsic role of cases emerge when the case itself is of primary interest in the exploration. The desire to explore unique characteristics is the main product of the intrinsic role of the case, rather than theory building. On the other hand, the instrumental roles of the case arises when a study of a case is intended to provide insight into a particular issue, to redraw generalizations, or to build a theory Grandy (2012a).

The role of cases in this study hence can be conceived as both intrinsic and instrumental. First, exploring the connected health business ecosystem through business models will provide new and unique characteristic descriptions of the studied ecosystem, reflecting the intrinsic role of the case. Second, the core objective of this study, to learn how business models can facilitate the exploration of the connected health business ecosystem involves the instrumental role of the studied cases. The instrumental role and its utilization will help towards the generalization of the results and will contribute to the theory.

As mentioned in the previous sub-chapter, this overarching research comprises three separate case studies that took place over the course of about four years. The report at hand is a result of multifaceted processes. The research data that is used in this study is sourced from mainly primary data in various qualitative forms.

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Figure 8: The research process and data collection.

Figure 8 summarizes the research process and data collection of this study. The research process began in Spring 2015 by studying futures business models concerning the IoT (Internet of things) enabled healthcare sector. As a key result of this multiple case study, the researcher reported futures probable business models for the healthcare sector. More importantly, the need for ecosystemic development for businesses and stakeholders was identified as a key need for the sector. Since the unit of analysis of the initial study were business models, the main stage of the research began to explore the phenomenon of the connected health business ecosystem through business models. Over the course of 2016 and 2017, data collection for the following two case studies was carried out. Each type of data was utilized for various purposes in the scope of the overall research. Table 3 summarizes the use of data in this study.

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Table 3: Use of the data.

Data source Introductory part Article 1 Article 2 Article 3 Article 4

Initial literature review X X X

Focused literature review X X X X

Interview with companies

for future healthcare

business models

X X

Interview, workshops, and

meetings with industry

stakeholders

X X X

Interviews with healthcare

professionals

X X X

Workshops with ecosystem

technology enabler partners

X X

In practice, this research falls into a multi-disciplinary paradigm where part of the data collection was conducted in “management studies” style face-to-face interviews and workshops, and part of the data was gathered through “engineering studies” style collaborative workshops with experts in the field. The following part of this sub-chapter presents the specific research material used for each of the case studies.

Multiple Case Study 1

In the initial stage of this research Multiple Case Study 1 examined futures business models in the IoT enabled healthcare sector. A causal layered analysis (CLA) (Inayatullah, 2005) was used as an analytical tool to conduct the qualitative multiple case study. For this study, five (5) face-to-face semi-structured interviews were conducted during May-June 2015. This data was used to construct three future scenarios for the IoT enabled healthcare sector (short-term, mid-term, and long-term future). Based on the future scenarios, this study further moves to create a business modeling conceptual space that can be useful for both academicians working in the healthcare domain and practitioners working in the healthcare business. Table 4 summarizes the interviews conducted for this study. Among the included list of original publications in this doctoral dissertation, this set of empirical data mainly aided Paper I.

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Table 4: Summary of the data collection for Multiple Case Study 1.

Interviewee Role of the interviewee Date Duration

NV CEO of a wellness startup 26/05/2015 75:26 mins

TK MD of a health tech association 27/05/2015 88:14 mins

SH MD of a medical research organization 29/05/2015 43:50 mins

JH Innovation and business architect, new business

development, leading network and telecommunication

company

03/06/2015 67:36 mins

EK CEO of health innovation academy 30/06/2015 74:37 mins

Multiple Case Study 2

The second multiple case study focused on understanding the connected health business ecosystem, its construct, and the interactions that take place within the ecosystem from a business model perspective. In doing so, two separate sets of data were gathered to support the aims. Firstly, several business model workshops, and meetings with ecosystem stakeholders were conducted. The author of this dissertation was directly involved in all these data collection events. These data collection events are summarized in Table 5. Second, a set of interviews and workshops were organized with healthcare professionals. However, the researcher did not participate personally in these events but analyzed the results to accommodate the viewpoints of healthcare professionals in the study. Table 6 shows this set of data collection events. The above-mentioned combination of collected data aided the authoring of Paper II in the listed original publications.

Table 5: Summary of data collection for Multiple Case Study 2 (BM workshops, meetings with ecosystem stakeholders).

Event Purpose Duration and

date

Respondent remarks

Kick of meeting Introduction to the project

and consortium participants

4 hours

29.01.2016

All participants in the project consortium.

Includes all companies, OuluHealth

representative.

Meeting-

TeliaSonera Understanding BM, role in

ecosystem

1 hour 15 mins

12.02.2016

Head of programs, TeliaSonera Finland.

Meeting – CGI Understanding BM, role in

ecosystem

2 hours

15.02.2016

3 personnel from CGI Finland (Top

management)

Meeting –

Nokia Understanding BM, role in

ecosystem

1 hour 15 mins

18.02.2016

3 personnel from Nokia (Top/middle level

management)

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Event Purpose Duration and

date

Respondent remarks

Meeting –

TeliaSonera Further discussion of

business models. Futuristic

discussion

2 hours

25.02.2016

Head of programs, TeliaSonera Finland.

Meeting – IBM Understanding BM, role in

ecosystem

1 hour 10 mins

18.03.2016

Online discussion with 2 personnel

Meeting –

Haltian Understanding BM, role in

ecosystem

1 hour 40 mins

29.03.2016

2 Personnel including one co-founder (top

management)

Meeting-

Buddy

healthcare

Understanding BM, role in

ecosystem

1 hour

29.03.2016

Online discussion with one of the co-

founders

Training- IBM

Bluemix Training on the IBM product

and conceptualize its

impact on ecosystem

4 hours

30.03.2016

Training session conducted by 2 IBM

specialists

Meeting – Wille

Researchers Ecosystem building

potential related discussion

1 hour 30 mins

08.04.2016

Researchers within the project focusing on

other issues (end user, patient journey,

etc.)

Meeting – Near

real Understanding BM, role in

ecosystem

2 hours

28.04.2016

2 personnel from the startup including co-

founder

Meeting – Wille

Researchers Ecosystem mapping

initiation

2 hour 30 mins

03.05.2016

8 researchers altogether commenting on

ideas for mapping the ecosystem

Meeting –

Nokia Present initial findings and

receive feedback.

2 hours

20.05.2016

4 personnel from Nokia. (Top/middle

management level). Involved in Nokia

networks, Nokia Bel Labs, Nokia business

unit.

Meeting – Tieto Understanding BM, role in

ecosystem

1 hour 30 mins

26.05.2016

2 personnel from the top management of

the organization

Meeting – IBM Further understanding of

IBM’s participation in the e

cosystem

2 hours

06.06.2016

1 personnel from the top management of

IBM Finland.

Workshop-

Overall Wille

Consortium

Present findings, receive

feedback

2 hours

07.06.2016

5 companies’ representative and all

researchers in the Wille consortium

Single Case Study 1

The third case study of this overarching research is framed as a single qualitative case study that aims to identify non-generic value complementors for the evolution and growth of the connected health business ecosystem in the context of a futures digital hospital. The data used for this single case study was partially collected

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during Multiple Case Study 2, in semi-structure interviews with healthcare professionals. In addition, two separate business model workshops were organized with technology enabling service providers for the connected health business ecosystem to identify the various non-generic value and non-generic value complementors. The researcher was directly involved and participated in facilitating these two workshops. Table 6 summarizes the data collection for the Single Case Study 1.

Table 6: Summary of data collection for Single Case Study 1.

Data collection

method

Specialty Viewpoints Focus

Interview 1 Pediatric Surgery Administration, teaching,

hospital development,

technology and innovations

Pediatric surgery patient

journey, concept

development of futures

digital hospital, digitalization

in healthcare.

Interview 2 Anesthesia nurse New hospital development,

hospital ICT inclusion

Same as above

Interview 3 General practice Secondary-primary healthcare,

care process design

Same as above

Interview 4 Pediatric Surgery General surgery Same as above

Interview 5 Pediatric Surgery Specializing, own research Same as above

Workshop 1 Network specialists,

operator service

provider, cybersecurity

expert

Business opportunity creation,

new market exploration,

security aspects

Digitalization in healthcare,

security business

opportunities in health

domain, business modeling.

Workshop 2 Operator service

provider, cybersecurity

expert

Business opportunity creation,

new market exploration,

security aspects

Digitalization in healthcare,

security business

opportunities in health

domain, business modeling.

4.4 Data analysis

Stake (1978) states, data analysis and its representation for case studies can range to take on various forms such as, but not limited to: “… personalistic observation; and a writing style that is informal, perhaps narrative, possibly with verbatim quotes, illustration, and even allusion and metaphor”. Ghauri (2004) also notes that multiple data sources (e.g., interviews, verbal reports, observations and written reports internal and external) need to be reported in a qualitative case study analysis

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to make it comprehensive. These sources are applied to the analysis as mentioned in the data collection section.

The purpose of data analysis in qualitative exploratory case studies is to offer an authentic understanding of a previously scantly explored phenomenon (Streb, 2012). Further, data analysis in a qualitative explanatory case study aims to identify and explain the causal mechanisms that are in play within the studied phenomenon (Harder, 2012). Personalistic observation combined with theoretical learning from existing literature supported the development of conceptual frameworks for the data analysis in this research.

Analyzing data for qualitative case studies does not involve any clear rules, as each research and analysis process are unique (Patton, 2002:433). However, this uniqueness of the data analysis can transform collected data into unique findings that contribute to the literature. The theoretical framework and empirical data of this study in relation to the connected health context, business models and business ecosystems enable numerous potential approaches for analyzing the data. As mentioned previously, the included three qualitative case studies have been reported in four separate original publications. Part of the collected data has been analyzed in overlapping contents in two original publications (Paper III and Paper IV). In addition, the data collected for Multiple Case Study 2 was analyzed using two different approaches published in two original articles (Paper II and Paper III).

Ghauri (2004) lists six general types of data analysis techniques for qualitative case studies. These are chronologies, coding, clustering, matrices, decision tree modelling, and pattern matching. In this overarching research, chronologies, coding, and clustering techniques have been used in varied combination or individually for each of the original publications. For Paper I, chronological descriptions were presented to describe probable futures business models by creating short-term, medium-term, and long-term future scenarios. Although Ghauri (2004) mentions that usually in chronologies, narratives of events that have already taken place are organized by date, in this foresight case study future scenarios were developed through expert interviews and then analyzed using the business model wheel framework as a unit of analysis.

The main objective of Paper II is to understand how to map the connected health business ecosystem. To achieve this, coding and clustering techniques were adopted in combination. The collected data during the business model workshops with industry stakeholders were initially coded into business models for each of the stakeholders. Additionally, a conceptual framework for the clustering was developed based on the 4C business models and IoT-SoA frames. The coded

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business models were then clustered in the conceptual framework to simplistically map the overall connected health business ecosystem.

Paper III is part of the same multiple case study as Paper II, however, the aim here was to explore how and why ecosystemic stakeholders interact through business models. Coding was the key data analysis technique used for this paper, not only to note the business models, but rather to go a step further and to identify linkages between different stakeholders’ business models.

Finally, for Paper IV, as two separate data sources (interviews with healthcare professionals, and workshops with technology enabler experts) were combined, the analysis technique was also a combination. First, the results from interviews with healthcare professionals were thematically analyzed to define the context of futures digital hospitals. Then, the workshop results were also analyzed in two steps. Alternative scenarios were developed through thematic coding. These alternative scenarios then paved the path to identifying non-generic value complementors through cross-clustering using two business model theoretical frameworks.

Throughout the collected data, various viewpoints on the connected health business ecosystem came up from the business model perspective. Data analysis is not a static process (Ghauri, 2004) and it can take place even during the data collection in informal ways (Miles & Huberman, 1994). However, once the data analysis for each of original publications were deemed sufficient to an extent, the findings and summaries of the analysis were compared with the theoretical framework to draw conclusions (Ghauri, 2004). The overall summary of all the original publications is included in this dissertation which presents how business models relate to business ecosystems in the context of connected health.

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5 Overview of original publications This dissertation is composed of four original research papers. As mentioned in the previous chapter, these four original research papers are outcomes of three qualitative case studies. From a general perspective, these research papers offer methodologies to explore business ecosystems in the healthcare sector, more specifically in the connected health context using business model as a boundary-spanning unit of analysis.

Paper I is designed as a foresight case study to research the connected health context (termed the IoT-enabled healthcare sector in the paper) to identify futures scenarios and create a conceptual space for business development in the context. As the business ecosystem literature agrees that the structure of a business ecosystem is complex and overlapping, taking a simplistic approach, Paper II aims to formulate a framework for mapping the connected health business ecosystem using 4C business model typologies. As identified in the literature review, interaction and interdependency are key characteristics in business ecosystems. Paper III aims to develop a conceptual framework from a business model perspective on how the interactions and interdependencies are enabled in connected health business ecosystems. Finally, Paper IV focuses on the recombination and re-configuration of the value complementation aspect of the business ecosystem. From an ecosystemic business model perspective, this was done by identifying viable mixed-source business model options, combining the 4C business model typologies, and adopting a mixed source business model approach.

The papers’ objectives, identified research gaps, main RQs of the papers, results, and contributions to the main RQs are summarized in Table 7.

Table 7: The roles of the original publications in this dissertation.

Focus Paper I Paper II Paper III Paper IV

Objective Exploration of the

connected health

context using foresight

methodology in

combination with

business models

Mapping the

connected health

business

ecosystem as a

construct

Using business

models to explore

the interaction

dynamism that take

place in a connected

health business

ecosystem.

The objective of this

case study is to identify

business potential for

specific connected

health services in

futures digital hospital

context.

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Focus Paper I Paper II Paper III Paper IV

Research

gap

Foresight methodologies

have scarcely been

used in business model

studies despite the

potential for BM

innovation and

transformation.

Business models

are neglected in the

connected health

literature, despite

connected health

innovations aimed

at practical

business

applications.

Empirically based

research evidence

on this interactive

co-development in

business

ecosystems remains

scarce.

Methods of identifying

business model options

for the healthcare

context are limited.

Main RQ of

the paper

How can the business

model framework be

applied to CLA to study

the future of an

industry?

How could a

connected health

business

ecosystem be

mapped using a

business model

framework?

How do ecosystem

stakeholders

calibrate their

interdependent

activities through

their business

models?

How could generic and

non-generic

complementors be

identified in an

ecosystemic context

through business

model

conceptualizations?

Results 3 futures scenarios for

the connected health

context, probable

business models for the

short-term, medium-

term, and long-term.

A service map for

the connected

health business

ecosystem using

the 4C-SoA

framework.

A conceptual

framework depicting

the typology of

ecosystemic

interaction by seeing

business models as

a dynamic capability.

Presents four service

provisioning scenarios

for specific connected

health services in

futures digital hospital

context. Formulates an

array of mixed-source

business model

options.

Contribution

to the

dissertation

RQ

This paper identifies the

ecosystemic

development in the

connected health

context. Foresight

methodology in

combination with the BM

approach offers

methodological tools for

visioning an

ecosystemic future.

Mapping using a

layered perspective

of business

modelling to

simplify the

complex nature of

business

ecosystems.

The replication, co-

innovation, and co-

evolution processes

can be explored

through the

conceptual

framework presented

in this paper.

The method for

developing the mixed-

source business model

options can be used to

identify and re-

configure generic and

non-generic

complementors in

connected health

business ecosystems.

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5.1 Paper I: Futures business models for an IoT enabled healthcare sector: a causal layered analysis perspective

Paper I builds the relationship between the context of the healthcare sector and the theoretical concept of business models through strategic foresight. Although the notion of business ecosystems arise as a finding in the study, the research context of this specific paper, the IoT-enabled healthcare sector broadly represents a connected health business ecosystem. As such, this paper creates the foundation for the overall research presented in the dissertation. The specific aim of the paper is to explore futures business models for an IoT enabled healthcare sector. The rationale for the study is that the digital transformation of the healthcare sector is moving aggressively through technological innovations, however, the business feasibility and economic potential is less explored in the literature. This paper adopts a futures studies technique, i.e., a causal layered analysis, to create futures scenarios in order to identify futures business models in the studied context.

The theoretical framework for this paper is built based on existing literature from three streams; the IoT enabled healthcare sector, business models, and foresight and causal layered analysis. The research data was collected in five face-to-face expert interviews for this exploratory multiple case study. The findings of the paper are presented in a two-fold manner. First, three futures scenarios are built; a short-term future (the ploughed field scenario), a medium-term future (the breaking dawn scenario), and a long-term future (the ant super-colony scenario). Second, based on the interviews and generated futures scenarios, probable business model elements are clustered using the business model wheel tool for the short-, medium-, and long-term future. The collection of business model elements are organized as a conceptual space that can be used to create new business models for the future by recombining different elements.

The main contribution of this empirical paper is that it displays the application of business model conceptualization in strategic foresighting for a broad context in the IoT-enabled healthcare sector, i.e. a connected health business ecosystem. The business ecosystems literature suggests, ecosystems emerge either exogenously or endogenously. For the exogenous emergence of a business ecosystem, such a strategic foresight can enable the exploration of business opportunities for the ecosystem. Although business ecosystems are mostly self-governing, even for endogenously emerged business ecosystems, self-renewal is a key phase in the life-cycle evolution of a business ecosystem. In such cases, strategic foresight through

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business models can be used to visioning the direction of the ecosystem’s future evolution.

5.2 Paper II: Towards business ecosystems for connected health

The research focus of Paper II is the construct of an emerging connected health business ecosystem for which the boundaries are blurred, complex and overlapping. As an emerging business ecosystem, this study aims to understand the business ecosystem construct in a simple form that can enable stakeholder interaction in practice. The rationale of this study is that although business ecosystems are complex and the boundaries are blurred; without any positional clarification between the stakeholders, ecosystemic co-evolution is impeded. Further, the main objective of this paper is to explore how to map a connected health business ecosystem using business model conceptualizations.

This paper adopts an exploratory approach through a multiple qualitative case study. The theoretical framework is rooted in a multidisciplinary literature review encompassing business and innovation ecosystems, the service-oriented architecture of IoT, business models and ecosystemic contexts. The value creation and value capture typologies presented in the theoretical framework are built on 4C business model typologies and the service-oriented architecture of IoT.

Fifteen data collection events (workshops and meetings with ecosystem stakeholders) enriched the study with 27 hours and 50 minutes of qualitative data for analysis. The collected data was first analyzed using the business model wheel tool to capture the business model of each of the ecosystem stakeholders. Further, the business models were compared with the 4C-SoA framework to identify the operating logic within the boundaries of the business ecosystem. The 4C-SoA framework showed four layers of value creation in connected health business ecosystems. These were: connectivity, content, context, and commerce. Further, four layers of value capture were presented. These were: the network, sensing, service, and the interface.

The 4C-SoA framework helped the study to create a service map for the connected health business ecosystem. The simplified service map depicted the multilayer complexity of the connected health business ecosystems where various kinds of business models would be positioned. The identified layers were: an ecosystem facilitation layer (orchestration and governance), a connectivity/network layer, a physical context layer (includes sensing services and interface services), a content service layer (includes virtual context services and content processing

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services), and a commerce-oriented business layer. As an extension of the service map, this paper presents a value-flow map between the different layers and stakeholders in the business ecosystem. The value flow map shows the ecosystemic value each layer creates for other layers and the value that is captured in return in the context of the connected health business ecosystem.

One of the core challenges to understanding how a certain business ecosystem creates and captures value lies in how the numerous stakeholders are organized and positioned. As business ecosystems are observed as networks of business models, the results of this empirical study indicate that business models as a boundary-spanning unit of analysis offers practitioners and researchers a tool to simplistically map complex business ecosystem environments through a reverse engineering approach. The value-flow map presented in the paper also provides initial hints on how the interdependent nature of the stakeholders in the studied connected health business ecosystem sustain each other, instead of engaging in predation through vertical integration or acquisition.

5.3 Paper III: Business models as enablers of ecosystemic interaction: A dynamic capability perspective

As Paper II indicated the nature of interdependence in the connected health business ecosystem, Paper III is part of the same multiple qualitative case study where the focus is on creating a conceptual framework on how ecosystem stakeholders may calibrate interdependent activities through their business models. The rationale of this research is that empirically based academic research on the interdependent nature and interactions between ecosystem stakeholders remains scarce.

The theoretical background of this conceptual paper is built on utilizing dynamic capabilities as an approach and sees business models as a dynamic capability. The objective of the studied emerging connected health business ecosystem is innovation sustainability through new service creation, integration of services, and testing for the healthcare sector. Considering this, roles among the ecosystem stakeholders were identified as keystone players (e.g., a hospital environment test lab) and complementors (large industry corporations, SMEs, startups). However, in the context of the specific connected health business ecosystem, since it is still emerging, no wannabe or dominator roles were identified. The paper further identifies key motivators for different kinds of complementors.

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Some of the larger corporations involved in the ecosystem offer an open platform for incoming early-stage ventures in the ecosystem. By doing so, these organizations are locking-in other firms/services to their platforms and thus creating and extending a market advantage. Additionally, the incentive for businesses participating in the ecosystem who are far from the healthcare business (i.e., IoT device manufacturers, sensor manufacturers, mobile network operators, and network infrastructure vendors) is relevant to opportunity exploration and advantage extension by entering a new market. However, the motivation for early-stage startups and SMEs is more towards exploring market opportunities and exploiting them, rather than immediate value capture.

One of the key insights from this paper is that business ecosystems create a selective environment for stakeholders from various industries to participate together and extend their value capture potential. Additionally, the selective environment of the connected health business ecosystem creates a platform for business model innovation, combination, and opportunities for new business model creation.

Based on the empirical results, the paper further attempts to draw a conceptual framework of how ecosystem stakeholders calibrate their interdependent interactions through their business models. In this paper business models are perceived as dynamic capabilities. Dynamic capabilities are most prominently categorized as three broad clusters of activities and adjustments: 1) sensing, 2) seizing, and 3) transforming. This paper recognizes that business models connect a firm with ecosystem partners through one or more of the following three broad activities in combination: opportunity exploration and exploitation, value creation and capture, advantage exploration and exploitation. Reflecting on the empirical case, this paper identifies the emergence of ecosystemic interdependence and interaction through opportunity exploration and exploitation (new market entry, product testing, etc.), value creation and capture (profit maximization, product innovation, etc.), advantage exploration and exploitation (service integration, open platform, lock-in customers, etc.). From a social constructivist perspective, while the opportunity-value-advantage framework provides a basis for analyzing potential ecosystemic collaboration, at the same time the framework can be applied to identify potential challenges in ecosystemic collaboration.

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5.4 Paper IV: Cyber security business models for IoT-MDM services in futures digital hospitals

Paper IV is an empirical essay that is framed as a single qualitative case study. The focus of this paper is the context of futures digital hospitals and the business feasibility of cybersecurity business models for IoT-MDM services. Besides the empirical scope of the paper, conceptually this paper contributes to the dissertation by presenting a method for understanding how to identify generic and non-generic value complementors for an emerging business ecosystem.

The research context of this study is in IoT and mobile device management cybersecurity services in futures digital hospitals. Additionally, the theoretical frame of the study is rooted in two business model approaches: the 4C business model archetypes and the mixed-source business model approach. The main research data that was used for this study was sourced by organizing expert workshops on business modeling and service provisioning. Additionally, part of the data that was used to develop the concept of futures digital hospitals was collected through five interviews with healthcare professionals.

The 4C business model archetypes help to decode the boundaries between multiple business models operating either on the same verticals of the ecosystem or on the same horizontals. These archetypes can provide a basis to classify and analyze the business models of suppliers, competitors, and at the same time, the business models of customers. Consequently, this kind of ecosystem analysis enables managerial practitioners to identify a suitable position for their business models. Further, to expand the understanding of opportunities in the future digital hospital context, four alternative scenarios were developed for 5G cybersecurity service provisioning.

Finally, viable mixed-source business model options for the IoT-MDM service providers presented four business model options rooted in alternative scenarios. The identified business models are further characterized by their openness and closeness of the core and extension businesses. Based on the openness of the business models, interactions and interdependencies between ecosystems will vary.

Business ecosystems are in a constant evolutionary process that involves the inclusion and exclusion of complementors. Substituting generic complementors are gerenerally straight-forward because the value they add is usually standardized. However, for self-renewal of business ecosystems, designing unique value propositions is significant. In relation to this dissertation, this paper exemplifies a

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method to identify both generic and non-generic unique value complementors. The method presented in this paper can be practiced by existing ecosystem stakeholders to recombine and design new unique business models to extend market opportunities and market advantages.

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6 Discussion and conclusions “Mysteries do not lose their poetry when solved. Quite the contrary; the

solution often turns out more beautiful than the puzzle and, in any case, when you have solved one mystery you uncover others, perhaps to inspire greater poetry.”

Richard Dawkins in Mind and the Frontal Lobes: Cognition, Behavior, and Brain Imaging

This chapter summarizes the main findings of the study and conclusions are reached by answering the research questions. The chapter aims to combine the findings and go beyond to create theoretical generalizations and the theoretical and managerial contributions of this research are then presented. The following sub-chapter argues the reliability of this research. The chapter concludes with the limitations of the study and potential future research avenues.

6.1 Results of the study

The rationale behind this study is that although research contributions on connected health mostly focus on technical and medical issues, the literature lacks an understanding of multi-stakeholder interaction in the connected health business ecosystems. It was shown in this study that the importance of the healthcare sector is more than evident at the social level, but the importance at the economic and business level has just started to be more visible through research efforts. Future scholarly works are asked to justify the economic value of the healthcare sector and how to further improve the economic value. Thus, there is a need to design future connected health services in a more inclusive and co-operative manner that will improve scalability of ecosystem services. The domain of connected health is inherently a multi-stakeholder arena, which aim at developing personalized services, instead of analysing single services their needs to be analysis on the ecosystem level.

This study notes that connected health services are mostly innovated and offered in an ecosystemic environment rather than only through large vertically integrated corporations. This corresponds with the fact that digital-intensive industries have identified the positive influences of co-creation and co-development since the early part of the century.

The purpose of this study is to explore and describe business ecosystems in the context of connected health, using business models as a boundary-spanning unit of

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analysis. The theoretical objective of this dissertation is to create a conceptual framework to enable this exploratory study. Hence, this study included literature reviews from three disciplines, namely: connected health, business ecosystems, and business models. This study applied the theoretical framework to understanding the structure, interaction, and selection criterion in the connected health business ecosystem. This results section of the dissertation starts by explaining the findings from a general perspective and then moves on to answer the research questions of the study.

It is shown in this study that connected health business ecosystems can be explained on two distinct levels through business models; the empirical level and the conceptual level. The empirical level reveals the surface issues that are visible, while the conceptual level relates to the causal mechanisms and interactions that take place within the Connected Health business ecosystem ecosystems. At the empirical level, the collected data shows that all the business ecosystem stakeholders have one or more business models. These business models can be seen as strategic vehicles that connect the organization to other organizations within the business ecosystem and also outside the business ecosystem. Often, these individual business models are connected through various forms of partnerships and alliances with other ecosystem stakeholders.

At the empirical level, the research data allows to depicts business ecosystems as constructs where multiple individual business models operate in a multi-layer formation as shown in Paper II. Further, it can be observed that business models are deployed for opportunity exploration and exploitation, value creation and capture, advantage exploration and exploitation. These three broad functions of business models boost the interaction between the ecosystem stakeholders. The interactions and causal mechanisms in the business ecosystem are not completely captured in the “business ecosystems as constructs” view. Rather, this research identifies that business ecosystems can be perceived as result of interactive processes enacted by business models. This perspective can be observed in the results of Paper III and Paper IV.

At the conceptual level, this study identifies that co-operation-oriented business model interactions lead towards an ecosystemic business model. In this study, ecosystemic business models are perceived as a system of interdependent activities that transcend organizations in the ecosystem and span their boundaries. The system of interdependent activities enables business ecosystem stakeholders, in concert with their partners, to create value and to appropriate a share of that value with cooperating stakeholders. Papers II, III, and IV represent this perspective in

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the findings. This study further maintains that, ecosystemic business models are in continuous evolution rooted in the interactions between the stakeholder business models and negotiations between the stakeholder organizations. The overall system of interdependent activities in the business ecosystem is also in a state of continuous evolution enabled by the interaction functions of the stakeholders’ business models (opportunity exploration and exploitation, value creation and capture, advantage exploration and exploitation).

The above-mentioned notion relates to Van De Ven & Poole’s (1995) evolutionary model of change that emphasizes selection, variation, and retention as the central elements of evolution. The findings in this study thus identify an evolutionary relationship between business models and the business ecosystems they belong to. The following section explains the findings related to the research questions of the research. The research questions are answered reflecting on the theoretical approaches of the research and empirical understanding acquired through the original publications. Each of the original publications contributed partly to responding to the two overarching research questions of this dissertation.

Answer to Research Question 1

How do business models relate to the business ecosystem in Connected Health?

The answer to this main research question builds on the theoretical framework presented in section 3.3 and summarized in table 8. It is identified that there are three main activities of business models as key micro-foundations in ecosystemic contexts: opportunity, value and advantage. Although it is evident in the literature that these three elements are essential business model building blocks, it is however necessary to examine their capacity to relate business models to the business ecosystem.

From the business ecosystems perspective, the theoretical framework identifies three main features of the ecosystem as a multi-stakeholder business environment. These are: structure, interaction, and re-configuration. In responding to the main research question, this section attempts to identify how the business model characteristics relate to the business ecosystem features.

Paper I focuses broadly on the context of the digital transformation of healthcare and applies a foresight methodology to identify futures business models. This can be perceived as a stakeholder view on the ecosystem, in which the stakeholder organization attempts to identify business opportunities and find a

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suitable value locus to gain advantage. From an ecosystem orchestrator perspective, the foresight approach is useful in re-configuration strategies, mainly during the self-renewal stage of the business ecosystem. From start-up or SME perspective, who are in most cases niche value complementors in the business ecosystem, the foresight approach can help understand the competitive landscape and assist in positioning and designing value propositions.

Paper II addressed how to map the structure of the connected health business ecosystem through business models. In doing so, this study found that the structure and the complementarities in the stakeholder business models frame the business opportunities that the connected health business ecosystem will address. Furthermore, the research data indicates that the keystone player’s interest often dominates the business opportunities addressed in the business ecosystem. Consequently, this affects the value created in the connected health business ecosystem. The research data shows that in a functional business ecosystem, value creation and capturing activities are distributed between different stakeholders. While some stakeholders act as suppliers of specific services, some stakeholders are more end-user oriented. Large organizations often engage in larger set of value creation and capturing activities compared to niche contributors. The structure of the connected health business ecosystem is defined by what kinds of value creation and capturing activities are internalized or externalized in relation to the keystone and dominator players (large organizations). The ecosystem map and value flow logic presented in the empirical paper show that the stakeholder organizations cross traditional organizational boundaries in an act of ecosystemic collaboration. Starting from this point, Paper III aimed to understand the interaction logic of the ecosystem stakeholders.

Through a multiple case-study, Paper III focused on creating a conceptual framework on how Connected Health business ecosystem stakeholders may calibrate interdependent activities through their business models. Paper III found that stakeholder business models can be deployed for three broad functions for better ecosystemic collaboration. These are: opportunity exploration and exploitation, value creation and capture, advantage exploration and exploitation. Furthermore, this paper shows that the degree of interaction and collaboration between connected health business ecosystem stakeholders affects the ecosystemic value creation, capture and sharing. The research data in Paper II and Paper III also shows that interactions between the stakeholder business models can lead to the discovery or creation of new business opportunities. Business ecosystem stakeholders often address specific business opportunities; however, the collected

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data shows that companies expand their focus on identifying new business opportunities while collaborating in business ecosystems. The identification of new business opportunities can vary between the discovery of unaddressed opportunities to the creation of new opportunities through collaborative functions with other stakeholders in the business ecosystem. In addition, in collaborating through competitive advantages, stakeholder business models can improve the competitive advantage of the connected health business ecosystem.

Table 8: How business models relate to business ecosystems.

Structure Interaction Re-configuration

Opp

ortu

nity

- The structure of the business

ecosystem often frames the

business opportunity that the

stakeholders are addressing

through their business models.

- Business opportunity addressed

by the keystone player affects the

structure of the business

ecosystem.

- Interactions between

business ecosystem

stakeholders can lead to

new business opportunity

discovery or business

opportunity creation.

- New business opportunities

can be addressed through

shared business models.

- Opportunities addressed by

the keystone and other

dominators in the business

ecosystem will affect the re-

configuration of generic and

non-generic value

complementors.

Val

ue

- Distribution (degree of

internalization and

externalization) of value creation

and capturing activities define the


ecosystem.

- Value creation, capture and

sharing in the ecosystem is a

result of the degree of

interaction between

stakeholders.

- Identification of a new vacant

value locus or niche can be

filled by new stakeholder

business models.

Adv

anta

ge

- Competitive advantage

exhibited in a stakeholder

business model will affect the

competitive advantage of the

business ecosystem and

eventually affects the growth and


ecosystem.

- Within the context of a

business ecosystem,

interaction activities can be

turned into a competitive

advantage.

- Re-configuration of business

ecosystems often depends on

the competitive advantages of

the dominators and

challengers.

The business ecosystem literature acknowledges different life cycle stages and highlights that in each stage of the life cycle there is an element of re-configuration in the organization of stakeholders in the business ecosystem. Paper IV contributes to understanding the landscape of the connected health business ecosystem, and

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further by identifying vacant value loci or niches for a given aspect that is not being addressed by any stakeholders. On the other hand, the mixed-source business model options framework presented in the paper can also be useful for managers in the connected health context to identify a suitable business model that is relevant to the business ecosystem’s specific life-cycle phase. The identification of new vacant value loci can be filled by either external stakeholders’ business models or by existing ecosystem stakeholders’ business models. The identified vacant value locus or niche will warrant the type of value complementor required to occupy the locus. The niche can be filled by a generic value complementor, non-generic value complementor, or a unique value complementor. Furthermore, especially in the leadership or self-renewal stages, the competitive advantage and business opportunities addressed by the dominator business model will affect the re-configuration of the business ecosystem.

Answer to Research Question 2

How can the business ecosystem in connected health be explored through business model conceptualizations?

The original publications included in this dissertation provide selected approaches on how to explore the connected health business ecosystem. Paper I connects the context of the healthcare sector and the business model concept by exploring possible future business models. In doing so, the paper examined three futures scenarios for the short-term, medium-term, and long-term future. Furthermore, probable business model elements were identified for each of the future scenarios through strategic foresight.

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Paper II attempted to explore the service map of an emerging connected health business ecosystem. The result reflects the multi-layered nature of the business ecosystem context and further reveals the value-flow logic between different layers of the ecosystem. Although business ecosystems are defined as complex, overlapping and the boundaries are blurred; this empirical research presents a service map of the connected health business ecosystem that is developed based on business model conceptualizations.

Figure 9: The process of exploring connected health business ecosystems through business models.

Paper III extends the findings of Paper II to focus on the interdependencies and interactions between ecosystem stakeholders. More specifically, it examines how the ecosystem stakeholders calibrate their interdependent nature through business models. This conceptual paper presents a framework perceiving business model as a dynamic capability. Building on Teece’s (2006) conception of dynamic capabilities (sensing, seizing, and transforming), this study argues business models are the vehicle for such broad functions in ecosystemic contexts through three distinct activities: opportunity exploration and exploitation (relevant to sensing and seizing through new market entry, product testing), value creation and capture (relevant to seizing and transforming through profit maximization, and product

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innovation), advantage exploration and exploitation (relevant to transforming and seizing through service integration, open platform). Paper III finds that ecosystem stakeholders interact with each other based on these three core functions of business models, in combination or as a single function.

Paper IV, a single qualitative empirical case study, focuses on the business feasibility of cybersecurity business models in the context of futures digital hospitals. The results of this study, first, reveal business model contextualization as an analytical method for practitioners to identify positions in the ecosystem where value complementors are required. Second, this paper proposes a method to identify generic and non-generic value complementors using the mixed-source business model conceptualization.

In relation to Research Question 1, the original publications provide a baseline through their alternative but complementary approaches. This research, being exploratory in nature adopts an inductive approach to the quest of exploring the connected health business ecosystem context through business models. Exploring business ecosystems can be compared to the parable of the blind men and an elephant. There are several alternative ways to explore different aspects of the business ecosystem, however, the application of different methods in combination will help to get a better overview and understanding of the environment for managers. The approaches applied in this research to explore the connected health business ecosystem can be classified into four categories: 1) visioning, 2) mapping, 3) understanding the causal interdependence and interaction, and 4) understanding the re-configuration of generic and non-generic value complementors.

Figure 9 depicts the methodological process of exploring connected health business ecosystems through business models as a cyclic process. While exploring the business ecosystem is of interest in this study, in practice exploration and improving the understanding of the business ecosystems’ characteristics are of value to all of the ecosystem stakeholders, orchestrators, managers, and public agencies. As depicted in Figure 9, the exploration process starts with visioning, that includes the short-, medium-, and long-term. Although business ecosystems are considered to be self-governing, in practice some level of orchestration and governance is visible in all business ecosystems. In this respect, visioning helps business ecosystems during the self-renewal phase of the life-cycle evolution. Further, visioning is related to identifying the selective environment of the business ecosystem.

The second approach, mapping, entails the importance of translating the complex, multi-layered ecosystem construct onto a simplified map that enables

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ecosystem stakeholders to identify a suitable position for individual business models, and also the value flow logic to justify the sustainability of the interactions. The mapping approach helps to understand the selective environment of the business ecosystem and the existing variations of business models in the ecosystem.

Understanding causal interdependence and interactions, the third approach highlights how ecosystem stakeholders interact through business models to calibrate their interdependent activities. These interaction and interactive activities contribute to the variation of business models in the business ecosystem, since business models evolve based on their interactions. Further, interactions enable potential the replication of business models either from within the boundaries of the selective environment or from beyond the blurred boundaries of the business ecosystem.

The fourth approach, understanding the re-configuration of generic and non-generic value complementors, suggests retention strategies for the business ecosystems’ evolution. In this regard, identifying the value locus where the business ecosystem needs complementation will strengthen the differential fitness of the ecosystem. As such, given that a vacant value locus is identified, it can be filled with a generic or non-generic value complementor depending on the identified locus. Re-configuration of value complementors in business ecosystems further contributes to the replication and scalability of the business models.

As mentioned previously, on the conceptual level, the emergence of an ecosystemic business model is observable in the context of connected health. This section aims to take the results of the original publications further for theoretical generalization. Next, I discuss how an ecosystemic business model emerges in the context of connected health.

The empirical data in this study suggests, business ecosystems are organized as networks of complementary business models. As such, Figure 10 attempts to conclude the findings of the empirical analysis to depict a business ecosystem in connected health as a construct where multiple business models are in constant interplay within the boundaries of the ecosystem, and also beyond meaning that the boundaries of the connected health business ecosystem become blurred. Through visioning and mapping, the boundaries of the ecosystems become structured. However, as a construct of evolutionary development, the boundaries of the business ecosystem tend to become blurred due to differential fitness present in the ecosystem and re-configuration of generic and non-generic value complementors.

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Figure 10: Emergence of an ecosytemic business model in the connected health context.

The interdependent stakeholder business models in the business ecosystem become calibrated through opportunity exploration and exploitation, value creation and capture, advantage exploration and exploitation. These stakeholder business models exemplify also the variation in the ecosystem. Variation in business ecosystems can mean the different types of value complementors’ business models and how they change within the business ecosystem. The continuous interactions between the business models within the business ecosystem and beyond the boundaries of the business ecosystem drive the selection environment of new business models of the different stakeholders. Consequently, the interactions between stakeholder business models leads to a common system of interdependent activities that transcends each stakeholder in the ecosystem. This common system of interdependent activities depends on the ecosystemic value, ecosystemic innovation strategy, ecosystem orchestration, and ecosystem synergy. The common system of interdependent activities resulting from the interaction, variation, and selection of business models leads to the retention of business models for the business ecosystem’s evolution. Retention of business models in the business ecosystem take place in the overall re-configuration of the business ecosystem. Re-configuration of business ecosystem can involve the selection of new business

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models to fill identified niches and existing business models that sustainably contributes to the value accumulation of the business ecosystem are retained. In Figure 10, while the large octagon represents the business ecosystem as a construct, it further reflects the emergence of the ecosystemic business model through interactions between stakeholder business models.

6.2 Theoretical contributions

This research primarily contributes to the literature of three streams, namely: connected health, business ecosystems, and business models. Novillo-Ortiz et al. (2018) state the need for research contributions on economic and business value in the healthcare sector. Gualtieri et al. (2018) discuss the need for designing future connected health services in a more inclusive manner that will improve scalability. This research contributes to the connected health literature by bringing the business model perspective to the discussion and further by exploring the business environment, e.g., business ecosystems through three case studies. This study shows the changing approach of business practices in the healthcare sector from being a public-organized sector to utilizing, a more distributed, ecosystem approach.

Based on the theoretical framework of the study and the conclusions discussed above, a set of propositions can be developed to present the theoretical contributions of the study that go beyond the general findings of the papers. These propositions include themes such as the stakeholder business model in ecosystems, the ecosystemic business model, governance and intentionality within the connected health business ecosystem, key elements of business models in business ecosystems, the key elements of business ecosystems in evolution, and the multi-methodological approach to exploring business ecosystems.

The business model literature identifies different key elements or components often which are context specific. For example, Maurya’s (2012) lean canvas offers nine key elements relevant to lean startups, while Ahokangas et al.’s (2014) business model wheel focuses on future oriented contexts. Systematic literature reviews (Morris et al., 2005; Onetti et al., 2012; Shafer et al., 2005) in the business model literature also affirm the context-specificity of business model definitions and key elements identified in each definition. However, the existing literature lacks a conceptualization of business models in the context of business ecosystems. In the theoretical frame of this research, it was identified that opportunity, value and advantage are the key elements of business models in business ecosystems. The research data exhibits that it is the nature of these three elements that they enable

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the interaction between business ecosystem stakeholders that make them more important in ecosystemic contexts. The first proposition is as follows:

Proposition 1: Opportunity exploration and exploitation, value capture and creation, advantage exploration and exploitation are driving forces for interactions between stakeholder business models in the business ecosystem.

As well as in other industrial contexts, business ecosystems in the connected health context bring together various stakeholders from both public and private sectors. The theoretical framework of this research assumes that individual stakeholders connect to the business ecosystem through their business models. The structure of the connected health business ecosystem is populated with multiple business models of different stakeholders. Related to proposition 1, this study further notes that all of these stakeholders are connected through business models and their interactions based on opportunity exploration and exploitation, value creation and capture, advantage exploration and exploitation. Interactions, identified as a characteristics of business ecosystems in the theoretical frame, takes place through business models of the stakeholders that starts to form constellations. These interaction-based constellations of business models contribute to the complementarities. Thus, arriving at the second proposition:

Proposition 2: Stakeholder business model interactions in business ecosystems start to form constellations leading to complementarities that further influences ecosystemic collaboration.

Fleetwood (2005) noted that in critical realism thinking, things can be observed that at an empirical level do not seem to exist. The emergence of ecosystemic business models in business ecosystems is such a notion, which is fused within the interactions between business ecosystems stakeholders and it is challenging to extract and display. The theoretical frame of this research notes structure, interaction, and value re-configuration as the key characteristics of business ecosystems. Although business ecosystems’ boundaries are blurred, business ecosystems in the emergence phase can typically be mapped and their boundaries can be identified. The constellations of business models contribute to the complementarities and emergence of ecosystemic business models. Value reconfiguration can be perceived as an iterative process that the business ecosystem needs to deal with in order to be sustainable and competitive. This study suggests that connected health business ecosystems in the emergence phase, aiming to bring products or service to market, create a collaborative interdependent system through

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interaction and negotiation. This collaborative interdependent system is dependent on the structure of the business ecosystem and on the interactions of stakeholder business models. However, the collaborative interdependent system can contribute to the value-reconfiguration of the business ecosystem. The collaborative interdependent system in the business ecosystem often resembles the characteristics of a business model. Thus, the third proposition is:

Proposition 3: In emerging business ecosystems, complementarity between stakeholders’ business models gives rise to the ecosystemic business model.

Governance and orchestration in business ecosystems is another important theme in the literature. While Smorodinskaya, Russell, Katukov, & Still, (2017) noted that much of the ecosystem literature attempts to look at the self-organization and self-governance aspects, Mäkinen & Dedehayir (2012) highlighted that business ecosystems can be influenced by either or both exogenous and endogenous forces. This study recognizes that governance and orchestration in early-stage business ecosystems influences the collaboration and interaction. However, this study proposes that the state of the business ecosystem and the overall number of stakeholders will influence the intentionality of governance and orchestration decisions in later phases.

As previously mentioned, value-reconfiguration as a key characteristic of business ecosystem can be perceived as an iterative process that resembles the evolutionary view of the business ecosystem. From an evolutionary perspective of organizational change, Van De Ven & Poole (1995) stated variation, selection and retention as the key elements. While Van de Ven & Poole’s theory is relevant to the changes happening in the focal organization, this study considers “interaction” to be a vital cog of evolution in the context of multi-organization-based business ecosystems. The fourth proposition is developed as follows:

Proposition 4: Interaction is about variation, selection, and retention of stakeholders’ business models in the business ecosystem’s evolution.

The next proposition is related to the research methods utilized in the process of exploring connected health business ecosystem. Rabetino, Kohtamäki, & Gebauer (2017) explicated that in order to gather “a sufficient variety of perspectives” they continued conducting interviews to explain servitization and highlight manufacturer’s shift of focus from products to customer solutions. In order to explore an emerging phenomenon, the depth and breadth of the collected data needs to present “a sufficient variety of perspectives”. As an exploratory study (Streb,

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2012; Yin, 2017), this research comprises three distinct qualitative case studies (Yin, 2003). Eisenhardt (1989) appreciated qualitative case studies for theory building, and Stake (1978) stressed approaching case studies with an inductive manner rather than a deductive manner to improve the scope of theory building. This study employed three qualitative case studies in order to triangulate the results and combine the findings to create a holistic picture of the business ecosystem. Based on multi-perspective exploration, this study also attempts to capture the process of how ecosystemic business models emerge. The fifth proposition is presented below and relates to methodological approaches in the exploration of business ecosystems.

Proposition 5: Applying multiple perspectives in exploring business ecosystems reduces the risk of misinterpretation and increases the holistic understanding of the business ecosystem and the ecosystemic business model.

The following paragraphs briefly identify how this study complements the existing literature. Ahokangas, Perälä-Heape, & Jämsä (2015) argued for future centrism in the next generation of business modeling research. Thus, the foresight approach in exploring connected health business ecosystems is a novel contribution to the business model literature which combines business model conceptualization with causal layered analysis (Inayatullah, 2005). While Jansson et al. (2014) noted business ecosystems to be networks of complementary business models, they further noted it to be challenging to map the construct of a business ecosystem. Paper II presents a method for mapping the construct of a complex business ecosystem as construct by presenting a service-map reflecting the multi-stakeholder, multilayered and interdependent nature of business ecosystems (Adner & Kapoor, 2010; Iyer & Davenport, 2008; Li, 2009; Meyer et al., 2005). The ecosystem map developed in Paper II is accompanied with a table describing the value-flow logic between the ecosystem stakeholders. The combination of the ecosystem map and the value-flow map provides further grounding and explanation of the studied ecosystem’s structure.

Business models are mainly perceived in this research as a boundary-spanning unit of analysis (Zott et al., 2011). As such, the study further recognizes that a business model can be perceived as a dynamic capability (Juntunen, 2017; Teece, 2018). The conceptual framework on how ecosystem stakeholders calibrate their interdependent nature through business models is presented in Paper III, which captures the interdependence and interaction perspectives of business ecosystems (Cusumano & Gawer, 2002; Iivari et al., 2016; Mäkinen & Dedehayir, 2012). Moore (1993) mentions that throughout the life-cycle evolution of the business

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ecosystem, the construct of the ecosystem is bound to transform the means of inclusion and exclusion of new stakeholders. Further, more importantly, business ecosystems in the self-renewal stage will need to identify new ways to evolve and re-configure in order to maintain their sustainability. Paper IV presents a method to identify a vacant value locus or niche in the business ecosystem and how to identify generic and non-generic value complementors to fill the void.

6.3 Practical and policy implications

First, this study stresses the need to expand the application of business model conceptualizations beyond the focal firm, in broader contexts i.e., business ecosystems. The utility of business model conceptualization in exploring broader contexts is reflected in the results of the study. Ecosystemic business practices are growing, but analytical tools still remain too much on the focal firm or product level.

The empirical results of the study offer multifaceted implications for the connected health context. Change is complex, but necessary facet of the future. Instead of disregarding the future, Paper I illustrates three future scenarios with an attempt to create a more harmonized long-term real future where Finnish companies take the lead globally and operate in an ecosystem that complements local entities in order to provide a complete solution for public health. The service-map and value-flow map for the connected health business ecosystem presented in Paper II fosters ecosystemic planning and development in this context. The result of Paper III will help business managers to decide which activities they should select and why they should start forming alliances in ecosystemic contexts.

Companies working in the connected health domain will also benefit by understanding how they can deploy business models as a dynamic capability to better calibrate and interact within a healthcare business ecosystem, and especially what the dynamics are in data driven ecosystems. Further, Paper IV provides methods for ecosystem orchestrators (such as: public organizations and large corporations) to identify vacant value loci or niches and how to fill the void. The business model options discussed in Paper IV are timely and relevant to the market context and need. The mixed source business model options show how cybersecurity providers can extend their offering for different needs in the hospital context based on their core businesses. This study may prove to be helpful for cybersecurity business entities and at the same time for hospital managers.

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For public organizations, the methods presented in the papers for exploring connected health business ecosystems through business models can be applied to analyze the state of business ecosystems to formulate policies that will improve the sustainability of the business ecosystems.

6.4 Reliability, validity, and research ethics

To justify the acceptability of an piece of scientific research and evaluate the findings, it is important to test the reliability and validity of the research (Denzin & Lincoln, 2000; Kuusi, Cuhls, & Steinmüller, 2015). Valid and reliable research can be trusted for the results it offers to the readers (Shuttleworth & Wilson, 2008). Research validity is earned through the creation of knowledge based on facts, logical assumptions and reasons through argued justifications. The validity of a study can be of two types; internal and external. Internal validity refers to the internal logic and consistent progress of the study, which mainly stresses the construction of the theoretical framework of the study. Based on the internal validity of the study it can only provide externally valid results which are empirically fact supported.

This study has included a wide and relevant base of literature to create a strong foundation of theoretical concepts, and industrial contexts, namely: business ecosystems, business models, and connected health. The literature review helped the author to include different viewpoints in order to consider a “whole picture” of the studied topic. Kuusi et al. (2015) note that scientifically valid exploratory research should always be based on the “whole picture” of relevant concepts and context.

The external validity of a piece of research considers the relationship between the internal structure of the research and the empirical data and how sound the conclusions are. This also means testing the consistency of the results in relation to the empirical dataset. Testing the external validity of a study should consider if the study draws conclusions from the findings which do not reflect the real empirical dataset. This study has gathered all the relevant empirical data through several expert interviews, workshops, and formal meetings in the scope of the three qualitative case studies. All the interviews were transcribed and analyzed with care to remove misinterpretation of expert opinion, and, thus provide a means of maintaining external validity. Further, the results of the workshops and meetings were summarized and shared with the participants in order to review them and to remove any misinterpretations.

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The reliability of a study refers to the repeatability of a specific study without random results. Yin (2003) states that reliability is the goal to minimize errors and biases in a piece of research. In qualitative research, maintaining constant accuracy in applying a specific methodology can enhance the study’s reliability. Consistency in the application of the methodology assures quality of the data collection and analysis for a reliable set of results. The author of this dissertation has done this by planning the overall research process in advance and documenting each step accordingly during this article-based research.

Ethical standards were considered and followed in this research for data collection, data interpretation and analysis. Every participant involved in data collection procedures was treated with respect. Sincere attention was paid in interview sessions to avoid any negative consequences for the people involved. None of the interviews conducted involved any trade secrets or confidential information, which enabled the author to use the whole dataset without omitting any part in the data analysis. Furthermore, to reflect the responsibility of the researcher towards other researchers, this study cites used literature and IPRs extensively to justify the utilization of previous literature and also to point out this study’s theoretical contribution.

Overall, considering the theoretical base, quality and quantity of the empirical dataset and the relationship between the explained results, actual empirical data and the maintained ethical standards; the validity and reliability of the research can be considered to be of a satisfactory level. This dissertation can thus be considered to provide a comprehensive description of the studied topic.

6.5 Limitations and future research avenues

Just like any other scientific study, this research also has limitations. This sub-chapter briefly notes the limitations that have been identified, and how the author attempted to mitigate those limitations.

First, the study converges three literature streams rarely connected in the existing literature. The number of scientific publications reflecting the combined focus (connected health, business ecosystems, and business models) is very limited. The available literature on connected health mostly focuses on technical aspects of healthcare. Although business models as a theoretical concept have gained traction over the last couple of decades, a large part of the literature studies aspects at the level of the focal firm rather than examining the ecosystemic context. In bringing together the three literature streams, it is quite possible that some important

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publications were unintentionally overlooked. All of this in conjunction made the theoretical framework building process challenging. The author adopted an iterative and inclusive approach to update the theoretical framework as new materials were accumulated for the study.

There are couple of theoretical limitations to this study. First, this study does not adopt a single-mainstream business research theory to examine the problem. While business models have emerged as a “research concept”, this has yet to be matured as a research theory. Similarly, the ecosystem concept has been applied in various disciplines without formulating it as a theory, especially in the business literature. As a theoretical choice, this study adopts the basic logic found in the theory of evolution. There is an assumption in the theory of evolution that species evolve from one state of being to another over time. However, since the data collection of this study took place during 2015 and 2017, the research data does not reflect the longitudinal effect of evolution in business ecosystems.

Then, the core objective of the study was to examine how to explore connected health business ecosystems through business models and this had its own limitations and challenges. The business model literature lacks studies which attempt to analyze large contexts. So, the researcher adopted creative reasoning to use business model conceptualizations in combination with other research methodologies (CLA, multiple case studies, single case studies) to make-sense of the collected data in order to achieve the core objective. The choices of methodologies and the analysis tools can be perceived as limitations of the study.

The generalizability of results is not typically a goal in qualitative research. Although the study strictly focuses on the context of connected health, the generalizability of the results to other industrial sectors is untested. Taran, Nielsen, Montemari, Thomsen, & Paolone (2016) suggested that there is evidence of potential imitation in different industries in business model innovation processes, especially in technology-dependent fields. This leads to the notion that similar approaches could be applicable other technology-intensive sectors.

Business models are an emerging field of research in different domains. The notion of ecosystemic business models is only emerging in the business model literature. This research focused on business models and ecosystemic business models in the domain connected health. Concerning future research avenues, first, the ecosystemic business model conceptualization needs more attention from researchers on what it is in various domains. It would be interesting to see how ecosystemic business models evolve from an evolutionary point of view. Another interesting viewpoint would be how ecosystemic business models influence the

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evolution of stakeholder business models over time through longitudinal studies. Similarly, studies from an opposite direction would be interesting to examine the effects of incumbent business models evolution on the ecosystemic business model. Thus, more studies applying the business model conceptualization in an ecosystemic context would be useful for validating the findings of the existing literature. In exploring the connected health business ecosystems, methodologically this research relied on a foresight methodology (CLA) and qualitative case studies. More variation in the methodological approaches (e.g., action research) would bring out additional aspects of the business ecosystem.

Finally, the author recognizes the need to also apply business model knowledge to policy areas that can contribute to improving efficiency in public sectors. The emerging stream of business model literature on smart cities is a good example of how business model research can help public sectors. As business model scholars, it is necessary to identify new contexts where meaningful contributions can be made not only on the focal firm level, but also on a collective level, the business ecosystem level.

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Original publications I Gomes, J. F., and Moqaddemerad, S. (2016). Futures Business Models for an IoT

Enabled Healthcare Sector: A Causal Layered Analysis Perspective. Journal of Business Models, 4(2), 60-80.

II Gomes, J. F., Pikkarainen, M., Ahokangas, P., and Niemelä, R. (2017). Towards business ecosystems for connected health. Finnish Journal of eHealth and eWelfare, 9(2-3), 95-111.

III Gomes, J. F., Iivari, M., Pikkarainen, M., and Ahokangas, P. (2018). Business Models as Enablers of Ecosystemic Interaction: A Dynamic Capability Perspective. International Journal of Social Ecology and Sustainable Development (IJSESD), 9(3), 1-13.

IV Gomes, J. F., Iivari, M., Ahokangas, P., Isotalo, L., and Niemelä, R. (2017). Cybersecurity Business Models for IoT-Mobile Device Management Services in Futures Digital Hospitals. Journal of ICT Standardization, 5(1), 107-128.

Reprinted with permission from Finnish Journal of eHealth and eWelfare (II) and IGI Global (III).

Original publications are not included in the electronic version of the dissertation.

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omes

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Julius Francis Gomes


UNIVERSITY OF OULU GRADUATE SCHOOL;UNIVERSITY OF OULU,OULU BUSINESS SCHOOL;MARTTI AHTISAARI INSTITUTE OF GLOBAL BUSINESS AND ECONOMICS

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UNIVERSITY OF OULU P.O. Box 8000 FI-90014 UNIVERSITY OF ...jultika.oulu.fi/files/isbn9789526226880.pdf · Academic dissertation to be presented with the assent of The Doctoral Training