BUSINESS MODELS IN THE AGE OF PERVASIVE DIGITIZATION
Institute of Technology Management
University of St Gallen
Dufourstrasse 40a, 9000 St Gallen, Switzerland
JAN VOM BROCKE
Institute of Information Systems
University of Liechtenstein
Fürst-Franz-Josef-Strasse, 9490 Vaduz, Liechtenstein
Institute of Technology Management
University of St Gallen
Dufourstrasse 40a, 9000 St Gallen, Switzerland
Address all comments to Stefanie Turber: email@example.com
Citation: Turber, S., Vom Brocke, J., Gassmann, O. (2015). Designing Business Models in the Age of Pervasive
Digitization, Proceedings of the 75th Annual Meeting of the Academy of Management, Vol. 2015.
BUSINESS MODELS IN THE AGE OF PERVASIVE DIGITIZATION.
A REFERENCE FRAMEWORK FOR PRODUCT-DEVELOPING COMPANIES.
The increasing pervasiveness of digital technologies, also referred to as "Internet of
Things" (IoT), offers new business model opportunities, which often involve an ecosystem of
partners. Hence, product-developing companies are required to look at business models be-
yond a firm-centric lens and respond to changed dynamics. However, extant literature does
not provide actionable approaches for business models in inter-connected IoT-enabled busi-
ness environments. Our research addresses the need for a business model framework that cap-
tures the specifics of digitization to enable managers to build business models in IoT in a
structured way. The suggested framework builds upon the activity system perspective, and is
confirmed and enriched by central tenets of the service-dominant logic and insights from digi-
tal innovation research. The enhanced dimensions in the framework include (1) the network
of value co-creating partners, including customers and third-party developers (structure); (2)
the sources of value creation by recognizing the organizing logic of digital technology (activi-
ties); (3) the reasons and conditions of collaboration for value co-creators (governance). To
the author's knowledge, the suggested business model framework is the first, which incorpo-
rates the nature of digital technology as an endogenous part to convey that the physical and
the digital world are intricately intertwined in IoT.
Keywords: Business models; Internet of Things; digitization; value networks; service-
dominant logic; digital ecosystem; generativity;
BUSINESS MODELS IN THE AGE OF PERVASIVE DIGITIZATION.
A REFERENCE FRAMEWORK FOR PRODUCT-DEVELOPING COMPANIES.
Today companies are exposed to highly dynamic, interconnected business environments,
spurred by rapid developments and increasing pervasiveness of digital technologies. A driv-
ing force is that digital technology gets increasingly weaved in previously non-digitized
products, such as bikes, clothes and everyday household appliances. This trend, often referred
to as the "Internet of Things" (IoT) (Atzori et al. 2010), reshapes the nature and architecture
of industrial-age products (Yoo et al. 2010), which leads to major implications on industry
dynamics (I. C. L. Ng, Vargo, & Smith, 2012) as well as firms' business models (BM) (Yoo
et al. 2012) – i.e., the distinct organizing logic for value creation and value appropriation
(Chesbrough and Rosenbloom 2002; Sorescu et al. 2011; Teece 2010; Zott and Amit 2001,
2010) "in response to (its) environmental and strategic imperatives" (Sambamurthy & Zmud,
Nest, a digitized thermostat for private homes, is a prime example demonstrating the
transformative implications of IoT: Equipped with sensors and connected to the Internet, Nest
can be controlled remotely via a mobile app and can track the energy use of a household over
time. Those features open up numerous opportunities for novel services and business models
within a dynamic ecosystem of heterogeneous collaborators across industries. One Nest cam-
paign for example includes energy providers as partners to reward users, when they let their
Nest device switch off the HVAC1 during peak times2. Moreover, based on Nest's open appli-
cation program interface (API) and software development kit (SDK), third parties are invited
1 HVAC: Heating, ventilating, air conditioning
3 https://developer.nest.com; https://nest.com/works-with-nest
4 Normann's approach is here framed as part of the S-D logic stream for proven similarities (Michel, Vargo, et al., 2007)
to freely build applications upon Nest products and data to enhance them in an unforeseen
way3. In a nutshell: Physical products get generative (Zittrain, 2008) and turn into platforms,
which brings multiple actors together to co-create and exchange valuable services (cf. Yoo et
al. 2010, Barrett et al. 2010; Sambamurthy and Zmud 2000; El Sawy and Pereira 2013) –
provided firms flank their digitized products with a suitable organizing logic of value creation
and capturing that unleashes this generative potential (Yoo, Henfridsson, & Lyytinen, 2010).
Hence, especially product-developing companies feel increasingly compelled to revise
their existing business models in response to new competitive dynamics and to tap into IoT
inspired opportunities (Altman, Tushman, & Nagle, 2013; Chesbrough & Appleyard, 2007;
Dahlander & Gann, 2010, EIU 2013). However, many of them have difficulties to capture the
unprecedented business model complexity around digitized products in a structured way and
fail to create value beyond the physical product (Altman & Tripsas, 2013; Van Alstyne,
2014). The reason is, that the product-centricity of the industrial age is deeply imprinted in
firms' business models as well as management cognitions which is simply incompatible with
networked configurations and dynamics in the digital age (Henfridsson et al. 2014;
Sambamurthy and Zmud 2000; Svahn 2012, Rifkin 2013). It is therefore important that man-
agers work with business model tools and frameworks that support mental models for the dig-
ital era to unleash the opportunities of digitization (Tripsas and Gavetti 2000; Yoo,
Henfridsson, et al. 2010).
Although business model research has gained notable momentum over the last decade,
the field has also remained understudied in the context of IoT (Priem, Butler, & Li, 2013). In
fact, received business model concepts often reinforce mental models of the industrial age
(Altman et al., 2013; Keen & Williams, 2013) and miss to integrate the attributes of digital
technology and thereof inspired dynamics as integral part of strategy formulation (Yoo et al.,
3 https://developer.nest.com; https://nest.com/works-with-nest
2010). This resonates with the challenges our research team experienced by employing exist-
ing business model approaches in workshops with product-developing firms to help them de-
signing business models around digitized products.
The present paper addresses this need for a business model framework that guides prac-
titioners in designing business models in the age of IoT. We specifically look at how the ex-
isting business model concept can be empowered to recognize the specifics of digitization and
disruptively changed market dynamics, and to help transition managerial cognition.
To our knowledge the suggested business model framework is the first, which incorpo-
rates both the nature of digital technology as an endogenous part to convey that the physical
and the digital world are intricately intertwined in the digital age (Lusch & Nambisan, 2014;
Zott & Amit, 2008) and digitally enabled new market dynamics. In the final analysis our re-
search aims to contribute to the adaptation and continuing development of the business model
concept, so that it can keep fulfilling its purpose of "helping to comprehend and analyze the
current business logic of a company as well as to plan strategic decisions by designing and
simulating new business concepts" (Burkhart et al. 2011, cf. Osterwalder et al. 2005; Shafer
et al. 2005) in the digital economy.
Method and Structure of the Paper
In the following sections, we begin by outlining the current state of business model re-
search, coined by three major perspectives, i.e. the activity system perspective, choice per-
spective and normative perspective. In section three we set out related research, i.e. the ser-
vice-dominant logic as well as the emerging body of literature on digital technology, to devise
the design requirements for the intended business model framework for IoT. We use these
derived requirements in two ways: First, they help evaluating the applicability of received
business model approaches in IoT in more detail (section four). Second, they help building a
new integrated business model framework, which we describe and illustrate in section five.
We conclude by outlining key features and limitations of the proposed business model
framework, as well as implications and an outlook on future research. The overall research
approach and structure of the article is inspired by the design science research paradigm
(DSR), commonly used in the information systems domain (Gregor & Hevner, 2013). This
approach enables us to place emphasis on achieving clarity in the underlying theoretical con-
structs for the new business model framework.
BUSINESS MODEL RESEARCH
The use of the term business model (BM) has proliferated in both strategy and infor-
mation systems research since mid 1990s, catalyzed by rapid advances of information and
communication technologies (ICT), which enabled novel types of interactions and rich data
sources (Geoffrion & Krishnan, 2003; Zott & Amit, 2008).
Definition and Current Status
Broadly speaking the term business model is used to describe "deliberate configuration of
foundational elements and activities" (Ladd 2014, cf. Zott et al. 2011) and captures the core
logic for creating and capturing value (Chesbrough and Rosenbloom 2002; Morris et al. 2005;
Osterwalder et al 2005; Sorescu et al. 2011) "in response to (its) environmental and strategic
imperatives" (Sambamurthy & Zmud, 2000). Literature acknowledges that business models
are closely associated with firm performance and strategic success (Afuah & Tucci, 2001;
Afuah, 2004; Zott & Amit, 2007), which reinforces the exceptional interest in business mod-
els among practitioners (Priem et al., 2013). However, business model research is yet a nas-
cent research stream. To date it offers relatively little exploration of the theoretical underpin-
nings of the construct and is predominantly driven by mainstream research (Priem et al. 2013;
own review) – only a small fraction of relevant articles are published in A-journals (e.g. Amit
and Zott 2001; Zott and Amit 2007, 2008). In this light literature has not yet congealed in a
commonly accepted definition and conceptualization (Teece 2010) and provides a myriad
number of business model concepts and what elements it consists of (Zott et al. 2011).
Three BM streams
Despite the variety of meanings three major BM streams stand out: (1) The choice per-
spective (2) the activity system perspective, and (3) the normative perspective (Kalinowski
and Vives, 2013), briefly described as follows: The choice perspective conceives of business
models as systems of interaction between managerial choices including their consequences.
Within this perspective, fit among choices is a central concept: Desirable is a high level of
coherence and consistency among choices. In contrast, the activity system perspective looks at
business models as systems of interdependent activity, whereby an activity is regarded as "the
engagement of human, physical and/or capital resources of any party to the business model"
(Zott and Amit, 2010). Within this perspective a business model is outlined by strategically
and/or technically relevant activities of the firm's activity system, and it is evaluated by the fit
among linkages between activities. Finally, the normative perspective describes a fixed set of
elements or building blocks a business model should consist of. It often involves a graphical
representation, while the elements shall merge into a consistent whole. The most popular one
among practitioners is the business model canvas by Osterwalder (2004).
IoT in Business Model Research
Notably, as a consequence of research in silos, IoT's transformative impact has largely
remained a black box (Yoo, Lyytinen, et al., 2010), as business model scholars have not yet
responded to encouragements from the IS community to develop new theoretical frameworks
for IoT – those that integrate the distinct attributes of IoT business ecosystems and digital
technology to guide practitioner's efforts to organize for generative innovations in the digital
age (El Sawy & Pereira, 2013; Yoo, 2013).
To confirm this stated gap, we screened existing business model concepts published in
leading IS and strategic management journals. These journals included MIS Quarterly (MIS
Q), Information Systems Research (ISR), European Journal of Information System (EJIS),
Journal of the Association for Information Systems (JAIS), Journal of Management Infor-
mation Systems (JMIS) and Information Systems Journal (ISJ) for information systems jour-
nals, and Academy of Management Journal (AMJ), Academy of Management Review (AMR),
Administrative Science Quarterly (ASQ), Journal of Management (JOM), Journal of Man-
agement Studies (JMS), Management Science (MS), MIS Quarterly, Organization Science
(OS), and Strategic Management Journal (SMJ) for strategy research journals. As our initial
list of the most prominent academic journals of both domains revealed only a small number
of articles, we added the most frequently cited business model concepts to the analysis from
both academic and practitioner journals. Additional selection criteria were that (1) the busi-
ness model concept is elaborated in a non-trivial way, (2) relates to business firms and (3) the
article is listed in the ISI Web of Knowledge (cf. Zott et al. 2011). The analyzed sample as
presented in this paper includes 20 articles across all three BM streams (table 2, column 2).
To be able to profoundly evaluate whether and to what extent received business model ap-
proaches are applicable in IoT (section four), we clarify the requirements, which are devel-
oped in the following section.
ADJACENT THEORIES FROM MARKETING AND INFORMATION SYSTEMS TO
DEVISE REQUIREMENTS FOR A BM FRAMEWORK IN IOT
This section outlines two relevant knowledge sources – i.e., (a) the service-dominant (S-D)
logic paradigm and (b) insights on the nature of digital technology – to extract relevant as-
pects from each to inform the requirements of a business model framework in IoT. These re-
quirements shall reflect the specifics of digitization and convey updated mental models.
Service-Dominant Logic to Reframe the Manufacturing Logic
Why useful. Pervasiveness of digital technology is closely linked with the separation
of service and information from physical goods (Yoo, Lyytinen, et al. 2010). This affordance
is a major reason for the emergence of inter-connected market dynamics and complex activity
webs between market partners. As stated, management research and tools appear to lag be-
hind these trends. However, in marketing research the S-D logic has evolved as a new para-
digm (Vargo and Lusch 2004, 2007; Lusch and Vargo 2006), which depicts important princi-
ples of inter-connected business environments in IoT (Ng et al. 2012). It supplants the so-
called good-dominant logic of the industrial age as it gets increasingly obsolete in the light of
digitization (Barrett, Davidson, & Vargo, 2012). The service-dominant logic will therefore be
the first valuable source to inform the intended business model framework. We therefore
translate central tenets of the S-D logic into applicable design requirements for BM frame-
works to reflect today's IoT-driven market environments.
Central Tenets. (1) Meaning of Networks. A first important cornerstone of S-D logic is
its network-centric view: The focus is put on relationships between market partners and cus-
tomers, which together build value creation networks. The single firm appears, in the first
place, as organizer of value creation (Michel, Vargo, & Lusch, 2007; Normann, 2001) by in-
tegrating and transforming specialized competencies into complex market offering (Lusch &
Vargo, 2006). The more resources a company integrates the more it evolves from a specialist
to a solution provider (Michel, Brown, & Gallan, 2007). In this light, a firm's collaborative
competence becomes a core premise for competitive advantage (Lusch, Vargo, & O’Brien,
2007). This view acknowledge the internal and external network of multiple stakeholders as
important source of value creation (Amit & Zott, 2001; Lusch & Vargo, 2014). They center
"on boundary-spanning transactions between a focal firm and its ecosystem of partners, cus-
tomers and suppliers", which are framed as "co-creators of value" by the S-D Logic. The total
value consists of the values appropriated by stakeholders engaged in a transaction
(Brandenburger & Stuart, 1996; Michel, Vargo, et al., 2007).
(2) Transcending the Consumer/Producer Divide. A second distinctive aspect of the S-
D logic is the assumed role of the customer. While traditional value creation models regard
firms as the only value creators due to their production and distribution activities, the S-D
logic ties in with the opposing literature stream, which conceives the customer as an indis-
pensible part in the value creation process: The customer as co-creator and co-producer of
value (Normann 2001)4. The traditional producer/consumer divide becomes consequently
obsolete (Lusch & Nambisan, 2014). In this light, the customer is no longer viewed as mere
receiver of value, but as actively participating and co-producer of value (Lusch & Vargo,
2006). This is especially relevant for product-developing firms in the IoT context (Leavy
2014). For example, a digitized thermostat can learn its users' behavior by analyzing heating
and presence behavior based on their individually generated usage data. This way the device
is able to predict and adapt to individual user needs, e.g., by automatically regulating room
temperature. The benefit for the user is comfort and energy saving potentials, which moti-
vates it to contribute by sharing data. Overall, the reason or incentives for customers to partic-
ipate in the collaborative value creation process – as for all other actors - can be of (3) mone-
tary as well as non-monetary nature (Lusch, Brown, & Brunswick, 1992; Vargo & Lusch,
(4) Re-Conceptualizing Resources. The S-D logic also offers a fresh view on resources:
The fact that firms always co-create value with the external environment implies that not only
internal resources shall be regarded as relevant – as the prevalent resource-based view sug-
gests (Penrose, 1959), yet also external resources that the firm can draw upon. Instead of an
internal/external categorization, S-D logic rather classifies resources as "operant" or "oper-
4 Normann's approach is here framed as part of the S-D logic stream for proven similarities (Michel, Vargo, et al., 2007)
and". The primacy is put on operant resources: They are dynamic and able to cause effects
(trigger), such as knowledge, skills and technologies, and usually intangible. Operant re-
sources are employed to act on other resources, while operand resources are acted on. Oper-
and resources are primarily static and tangible resources, and include raw materials and
goods. (Lusch & Nambisan, 2014; Vargo & Lusch, 2004). In S-D logic a firm's external envi-
ronment, its "ecosystem" of co-creating actors, is therefore seen as operant resource and im-
portant source of competitive advantage.
(5) Transcending the Traditional Goods/Service Divide. The concept of customer as co-
creator as part of the S-D logic leads also to a revised notion of offerings, by which the latter
are no longer conceived as output of a manufacturing process. Instead, offerings are seen as
input feeding into the value co-creation process, or what Normann calls "artifacts designed to
more effectively enable and organize value co-production" (Normann 2001). Offerings can be
composed of a variety of "artifacts", such as services or goods. In abstract terms, they all rep-
resent "carriers" of certain competences (Michel et al. 2007), and ideally serve as "a service
platform that enables service exchange and value co-creation" (Lusch & Nambisan, 2014). In
this light, physical products are conceived as medium to provide service. The traditional dis-
tinction between goods and services is finally transcended by the S-D logic (Lusch &
Nambisan, 2014) as it refers to all type of artifacts equally as services.
(6) Ecosystems as complex adaptive systems. The S-D logic emphasis the inherently
dynamic and complex nature of ecosystems by explicating them as "relatively self-
contained self-adjusting systems of resource-integrating actors connected by shared
institutional logics and mutual value creation through service exchange (Lusch &
Vargo, 2014). Within these dynamic webs of exchange those enterprises with a high level of
adaptive competences develop a competitive advantage as they are able to adjust to changing
circumstances and to encourage shared knowledge among ecosystem actors which will in turn
increase their competency (Lusch et al., 2007)
Digital Technology as Nucleus of Networked Business Models in IoT
Why useful. "Shifts in product architecture cause shifts in the organizing logic of a
firm" (Yoo, Henfridsson, et al. 2010). The overall market dynamics and how companies or-
ganize is closely linked with product architecture (Henfridsson et al. 2014; Langlois 2007;
Yoo, Henfridsson, et al. 2010). Just as the modular product architecture has manifested in
organizing logic during the industrial age (Baldwin and Clark 2000), now the modular-
layered architecture of digitized products is assumed to become imprinted in firms' overall
business models over time (Yoo, Henfridsson, et al. 2010). This suggests that the emerging
body of literature on digital technology and innovation is a second valuable source to devise
requirements for a business model framework that supports product-developing firms in de-
signing business models the digital era.
Central Tenets. (1) Generativity. In general, the incorporation of digital material into
physical objects, such as clothes, furniture and other everyday things, causes them to adopt all
characteristics of digital technology in addition to their physical materiality: They become
programmable, addressable, sensible, communicable, memorable, traceable, associable and in
"myriad ways, the digital materiality of artifacts enables generativity" (Yoo, Lyytinen, et al.,
2010). (2) Modular-layered architecture. Moreover, digitized objects feature a modular-
layered architecture, consisting of four distinct layers (IoT stack): The device layer comprises
hardware, which can be any kind of devices, and an operating system to control the hardware;
the network layer involves both the logical transmission including network standards, and the
physical transport; the service layer features direct interaction with the users through applica-
tion programs, e.g., as the user creates or consumes content; the content layer hosts data, such
as texts, images or meta-data like geo-time stamps (Yoo, Lyytinen, et al., 2010). A key fea-
ture in the context of IoT business models is, that these four layers of digitized objects are
modular and can be de-coupled, as a result of the inherent properties of digital technology.
Insert Figure 1 around here
This way the digitized object, such as the Nest thermostat or Philips hue, represents a
combination of elements across these layers, which are only loosely interconnected through
specified interfaces. "De-couplebility" of content, devices and information infrastructures
allows multiple stakeholders to contribute across the four layers in an unforeseen and genera-
tive way (Eaton et al. 2011) under the precondition of interoperability (Palfrey and Gasser
2007). In the business model context, the four layers can therefore be regarded as a source of
innovation and value creation, through which multiple heterogeneous stakeholders can "en-
gage in rich open-ended processes of (value) co-creation and distributed innovations" (Eaton
et al., 2011). As such, the layered-modular architecture provides the nucleus of business mod-
els, which distributively exist in multiple sites. It moreover provide clarity about the different
roles among "value co-creators" (Lusch & Nambisan, 2014), i.e. firms, customers, developers
etc. Therefore, the four-layered architecture delivers a valuable concept to naturally structure
and organize value creation across multiple partners within a focal firm's activity system and
business model in IoT.
Notably, this modular layer model of digital innovation features an important parallel
with the transcending view of the S-D logic: The S-D logic conceives of all types of artifacts
(goods, information, services etc.) as services to be exchanged, which serves as platforms to
create value upon. This view perfectly corresponds with the concept of digital technologies
by which each layer serves as platform for other actors to build modules in other layers upon
(Tiwana, Konsynski, & Bush, 2010).
Derived Business Model Requirements
Summarizing the previous outline, we reach at a list of tenets across the S-D logic and
digital innovation literature, which translate into following design requirements R1 to R6 as
listed in Table 1.
Insert Table 1 around here
EVALUATION OF EXISTING BM APPROACHES' APPLICABILITY IN IOT
In this section we continue the review of existing business model approaches from section
two to clarify in detail whether and to what extent existing business model approaches reso-
nate with the emerging dynamics of IoT driven business environments. For this, we investi-
gate existing BM approaches against the identified set of requirements R1-6 (cf. Brocke et al.
2009; Webster and Watson 2002) as derived in the previous section. The analysis is based on
the concept matrix (table 2), which allows us to evaluate each business model concept in
terms of its fit with proposed requirements . Moreover, the matrix helps to make overarching
trends explicit for each requirement, e.g. by analyzing shifts over time and differences across
both business model perspectives and origins.
Insert Table 2 around here
Results by Requirements
R1: Network as locus of value creation. The S-D logic describes value creation as a
clearly collaborative process, which involves a network of multiple actors beyond firm
boundaries. In business model literature however, the locus of value creation has remained a
divisive subject for debate: First approaches, which arose until 2000 along the advent of the
internet and e-business, describe business models as only meaningful at a network level
(Tapscott et al. 2000; Timmers 1998, also Mason and Spring 2011). Since 2001 many authors
look at business models as a concept nested between network and firm to describe a firm's
position within its value network (e.g. Amit and Zott 2001; Chesbrough 2002; Hedman and
Kalling 2003). These contribution are mainly rooted in e-business/IS and innovation man-
agement research. With increasing adoption of the business model concept by strategy re-
search it evolved into a predominantly firm-centric concept in this domain (e.g. Magretta
2002, Casadesus-Masanell and Ricart 2011; McGrath 2010). One reason for that can be seen
in the fact that strategy scholars have a traditional focus on firm-level research (Zott and
Amit, 2008), and only recently started to expand its boundaries towards an ecosystem view
(Adner and Kapoor, 2010; Priem et al., 2013). Business model approaches that fall into the
activity-system perspective mostly tie in with the networked or nested view, whereas con-
cepts within the normative perspective mostly feature a firm-centric view. Choice perspective
related approaches mostly take a nested view.
R2: Customer as co-producer of value. The S-D logic conceives customers as active
co-producers of value rather than pure receivers of a product or other sources of business.
This core principle is yet rarely reflected in received business model literature. Only Amit and
Zott (2010) indicate that customer can be involved as active part in the value creation process
within a business model by stating "business model, that is, (…) a set of activities, as well as
the resources and capabilities to perform them - either within the firm, or beyond it through
cooperation with partners, suppliers or customers." This contribution is rooted in e-business
research and represents the activity-system perspective. Other analyzed approaches mostly
regard the customer as solely value consuming rather than co-creating (e.g. Magretta, 2002;
Johnson et al., 2008; McGrath, 2010).
R3: Monetary and non-monetary incentives / benefits. S-D logic assumes service as
fundamental basis of exchange, rather than money, which would represent an indirect case of
service exchange (Vargo & Lusch, 2007). The incentives for actors to participate in the eco-
system can therefore be both monetary and non-monetary. In business model literature this
view is mostly reflected by approaches within the activity-system perspective and those root-
ed in e-business, such as Gordjin's (2001) stating the "actors exchange value objects, which
are services, products, money, or even consumer experiences". Likewise, Timmers (1998)
emphasizes that business models include "a description of the potential benefits for the vari-
ous business actors", which indicates that the type of benefits vary among different actors.
Demil and Lecocq (2010) moreover state that a focal company has to determine various bene-
fits (i.e. 'value propositions') depending on the kinds of customer in a wider sense, such as
end consumers, suppliers, complementors etc. In contrast, firm-centric approaches within the
choice and normative perspectives focus exclusively on customers' willingness to pay in ex-
change for the focal firm's offerings (e.g. Johnson, Christensen, & Kagermann, 2008;
McGrath, 2010; Priem et al., 2013).
R4: Internal and external resources. The S-D logic regards all those resources as po-
tentially relevant to a focal company, which the firm can draw upon, regardless whether in-
ternal or external. Business model approaches give heterogeneous answers to the question
which resources to include as a logic consequence to their prevalent locus of value creation:
The solely firm-centric approaches within the strategy domain look exclusively at resources
within a firm's boundaries, while nested and network-centric approaches comprises both in-
ternal and external resources.
R5: IoT stack as source of value creation. The S-D logic offers a revised notion of of-
ferings, which transcends the traditional good/service divide as it conceives both equally as
input feeding into the value co-creation process: Goods and services are both seen as "service
platform enabling service exchange and value co-creation" (Lusch & Nambisan, 2014;
Michel, Vargo, et al., 2007). This view corresponds with the layer concept of digital technol-
ogies by which each layer serves as platform for other actors to build modules in other layers
upon (Tiwana et al., 2010). In IoT the value stack can be conceptualized as a four-layered
model consisting of the device, connectivity, service and content layer (Yoo, Lyytinen, et al.,
2010). In business model literature, we identified only one article, Gordijn & Akkermans
(2001), which explicitly outlines the digital value stack in e-business, yet – as published prior
to the advent of IoT – e.g. does not include the device layer. This approach falls into the class
of activity-system based approaches. Within the same category we moreover identified the
business model approach by Zott & Amit (2001, 2010) as "receptive" to the IoT value stack,
as it equally overcomes the good/service divide by introducing the transcending term "activi-
ties", which can bear all types of core activities and their combinations (Amit and Zott 2001).
In IoT it could be loaded with service-, product-, data- and technology- related activities
(Amit and Zott 2001). Therefore, the activity system perspective is able to reflect business
models in IoT as special case, although its specifics are not explicit. In strategic choice and
normative approaches and strategy literature respectively no indication of the IoT value stack
R6: Dynamic view. According to the S-D logic, value is co-created within a diverse
ecosystem of actors, which is inherently dynamic with emergent properties (Ng et al. 2012).
Business model research offers two different pictures. Approaches representing either the
choice perspective or the activity perspective are "inherently dynamic" (Kalinowski & Vives,
2013). For the first, as choices always trigger consequences which again require choices.
Casadesus-Masanell moreover emphasizes that chosen components of the business model get
strengthened with each iteration through a "virtuous cycle" of consequences. Example: Ryan
Air's choice for low fares leads to increased volume, which leads to a higher bargaining pow-
er with its suppliers, which again allows Ryan Air to offer even lower fares (Casadesus-
Masanell & Ricart, 2010). The second type of approaches representing the activity-system
perspective are mostly dynamic, e.g. as a purposeful design of activities and links between
them may generate complementarities or efficiencies (Amit & Zott, 2001) or as new elements
within an activity system may require alignment Chesbrough, 2002). In contrast, approaches
representing the normative perspective are mostly static, and mainly evaluate a business mod-
el by its overall stability based on the consistency of its elements (e.g. Johnson et al. 2008;
Osterwalder et al. 2005)
Overall Evaluation and Trends
From an overall perspective, the majority of business model approaches does not suffi-
ciently integrate the attributes of digitized business environments and digital technologies.
Most of them show a fit with less than half of the proposed requirements, which underpins
their assumed limited applicability in IoT. However, an analysis across the three BM provides
a picture with more light and shade:
Applicability of the activity system perspective. Strikingly, all investigated approaches
within the activity system perspective feature at least 50 % of the criteria. Especially Amit
and Zott's approach (2001; 2010) integrate 4 of 6 criteria explicitly: First, it is worth mention-
ing, that the activity-based approaches are network-centric without exception, which may
trace back to their origin in e-business or IS research with an early focus on digitally inter-
connected business relationships: The network-centric view is inherent to the activity system
perspective by defining the ecosystem of partners rather than formal firm boundaries as locus
of value creation and as corresponding unit of analysis. Moreover, novel configurations with
partners beyond firm-boundaries are seen as wellspring of business model innovation. Se-
cond, by focusing on ever changing configurations within the activity system with partners,
the activity system perspective is intrinsically dynamic. Third, Amit and Zott (2001, 2010)
offer a transcending view on activities, which allows for incorporating all types of core activi-
ties – service-, product-, data- and technology-related activities as well as their combinations
(Amit & Zott, 2001). The activity system perspective can therefore embed and reflect busi-
ness models in IoT as special case, although its specifics are not explicit.
Limited applicability of strategic choice and normative perspective. In contrast, ap-
proaches that fall into the choice or normative perspective show a significantly lower level of
consistency with suggested requirements. Especially the predominantly firm-centric view of
the choice and normative perspective, which defines formal firm-boundaries as locus of value
creation and unit of analysis, limits the applicability for business models in IoT. In addition,
the normative perspective is static and does not provide room for IoT typical dynamics and
The concept matrix in table 2 visualizes these findings, with the gray-cultured boxes in-
dicating an approach's consistency with requirements.
As a result of the literature review we identified the activity system approach by Amit
and Zott (2001, 2010) as most applicable basis to develop it into a business model framework
for IoT by extending and adaptation (Gregor & A. R. Hevner, 2013). (The parallels between
activity-system perspective and S-D logic are outlined in more detail in the appendix, table
A1 column 1-3)
INTEGRATED BUSINESS MODEL FRAMEWORK FOR IOT
In the following, we present the integrated business model framework in IoT, which is
based on insights from previous sections, i.e., grounded in theory and integrating relevant
aspects from cross-disciplinary research.
Activity System Perspective as Basis.
As the activity system perspective by Amit and Zott (2001) has appeared as useful basis
for business models in IoT in the previous analysis, we selected its constitutive design ele-
ments as basic dimensions for the framework. These dimensions are confirmed and/or further
enriched by insights from S-D logic and digital innovation literature. As illustrated in figure
2, the basic design elements comprise activities5, structure and governance (Amit and Zott
2001). In their original meaning activities refer to the selection of activities to be performed,
which spans goods and services to be exchanged including the resources and capabilities re-
quired to enable the transaction. Structure describes the actors who participate in the activity
exchange as well as how they and their activities respectively are linked, and in what se-
quence. Governance refers to the ways in which flows of activities are controlled, and in-
cludes relevant governance arrangements, such as the legal form of organization, as well as
the incentives for the participants in transactions (Amit & Zott, 2001, 2012; Zott & Amit,
Insert Figure 2 around here
In the following, we explicate each dimension of the proposed business model frame-
work within the IoT environment including a short rationale and by referring to the require-
ments. We illustrate the dimension by the "Nest" thermostat case, as introduced in the first
section, which likewise demonstrates the frameworks applicability.
Dimensions of the Proposed Framework
Dimension "structure" to span the ecosystem of value co-creators. The first dimen-
sion "transaction structure" encompasses the value co-creating actors within an ecosystem
around digitized products. In IoT, this regularly includes complementary partner firms, users,
service providers, and third party developers provided an API/SDK as boundary resource
5 originally called "content" (Amit & Zott 2001, 2010), yet due to word overlap with "content" in the 4 layer model (Yoo et
al 2010) in information systems research, we will refer to this dimension as activities in the remainder of the paper.
(Ghazawneh & Henfridsson, 2013) is released. The actors are listed one by one.
Rationale: The explicit itemizing of all participants reflects the service-dominant logic's
view that a company's external environment represents an "operant resource" offering the
inherent opportunity for each participant to co-create value with other external participants as
collaborators (Lusch et al., 2007). Moreover, customers are listed together with other collabo-
rators on a single dimension, which conveys the philosophy, that value is always co-created
with the customer, often even co-produced, especially in the digital context (Vargo & Lusch,
2004). A distinction between partners and customers reflected by different dimensions was
therefore redundant. Moreover, the dimension is expandable, as over time new collaborators
may join reflecting the generative, dynamic character of ecosystems around digitized prod-
ucts. Requirements considered: R1, R2, R4, R6.
Illustration "Nest": In the "Nest" case the value co-creators are the following: (1) Nest
Labs, the focal company which provides home owners with the "Nest", i.e. a learning thermo-
stat plus an app, to remotely control the device (2) The "Nest" user, who contributes first in a
monetary way by purchasing the "Nest" and later by using it as "Nest" feedbacks real-time
data about the user's heating habits to Nest Labs (data layer). Nest Labs processes the data to
customize the "Nest", i.e. adjusts it to the user's habits, to increase the overall user experience.
As NestLabs “owns” valuable user data, also other partners are interested to collaborate and
enhance the value-creation net- work: (3) Energy providers, who reward Nest users based on
individual consumption data (data layer). E.g. if users run their “Nest” in the "rush hour re-
ward" mode, so that the HVAC gets switched off during peak times. (4) Finally third party
developers, who build valuable services upon Nest data, since NestLabs has released a soft-
ware development kit (SDK).
Dimension "activities" to orchestrate value co-creation. The dimension "transaction
activities" is enhanced by the four-layered modular architecture of digitized products to clari-
fy and orchestrate the different roles by which potential value co-creators can contribute.
Rationale: We enhanced the activity dimension by the four-layer architecture as the nu-
cleus of business models in the IoT context. The layers naturally structure the actors accord-
ing to their kind of contribution in the value creating process. Each layer represents a distinct
source of opportunities for actors to contribute to the value co-creation process (Yoo,
Henfridsson, et al., 2010), i.e. by device-, connectivity-, service- and/or content-specific ac-
tivities. With increasing digitization, those four modular layers of innovation and value crea-
tion get increasingly separated. Product developing firms, which usually build capabilities
and resources predominantly on the device layer over time, start adopting distributed models
of innovation to tap into value creating resources across layers beyond firm boundaries
(Selander, Henfridsson, & Svahn, 2013). From an activity system perspective, this shall en-
hance the total value created in transactions, i.e., the "overall size of the value pie" related to
the focal firm's offering (Zott & Amit, 2010).
Another benefit is, that the four layers are able to depict "co-opetition" aspects within the eco-
system landscape: Two players can be partners at one layer and compete on another layer in
the same ecosystem (Yoo, Henfridsson, et al., 2010). Requirements considered: R5
Illustration "Nest": Along the four-layered structure, Nest Labs contributes on the device
layer with the "Nest" thermostat, on the service layer by providing the app as interface to the
"Nest" thermostat and finally on the data layer by providing valuable user data (through data
analytics) to third parties via an API/SDK. The user contributes on the device layer by pur-
chasing the "Nest", on the content layer by feedbacking real time data. Concerning co-
opetition: Playing on different layers, Nest Labs and the energy provider are complimentary
in the described scenario. Would the energy provider come up with an own internet-
connected thermostat, they may still partner on the service layer, yet compete on the device
Dimension "governance" to control and incentivize value co-creators. The dimension
"governance" outlines all monetary as well as non-monetary governance mechanisms to mo-
tivate and control actors' participation in the ecosystem. In IoT this dimension is especially
coined by the design of boundary resources such as API/SDK as they have an important im-
pact on the ecosystem evolution (Ghazawneh & Henfridsson, 2013).
Rationale: Reflecting a network-centric view and the importance of the value co-creating
network in IoT, it is essential to pay attention to governance aspects, i.e. the rules and condi-
tions under which (potentially) co-creating actors are supposed to contribute. Their elaborate
design is a pre-condition of a healthy ecosystem, which can be an important competitive ad-
vantage for the focal firm. In this context, the design of boundary resources, i.e. software
tools and regulations such as APIs or SDKs play a critical role: They build the interface be-
tween the focal firm – the owner of the IoT product as platform – and third-party application
developers, and are mean to cultivate a platform ecosystem (Ghazawneh & Henfridsson,
2013). Attracting third-party development is a powerful lever to increase the overall attrac-
tiveness of a digitized product. It helps discovering new use cases and applications, i.e. in-
creasing the user's value, which in turn instigate new demand. More users again will attract
more developers, as with an increasing number of users the "product platform" gets an in-
creasingly attractive market place for their applications. The mechanisms set off reflect the
generative, self-reinforcing processes of digital infrastructure evolution (Henfridsson 2013).In
general terms, or say in BM jargon, this dimension reflects the value propositions for all ac-
tors from a focal firms point of view. Requirements considered: R1, R3
Illustration "Nest": Nest users are motivated in myriad ways to use Nest, e.g. by haptic
benefits (pleasant temperature), ethical benefits (saving energy), economic benefits (saving
money) or psychic benefits (image). Moreover, NestLabs adds value for Nest users in two
ways: First, by integrating a learning algorithm through which the device "learns" to antici-
pate users' behavior based on previous individual usage data. Second, NestLabs released an
SDK, once a sufficiently large number of users existed, so as to provide the digitized product
as marketplace to third party developers to build applications and services upon. In both
ways, the device gets increasingly useful over time for the users. The design of the SDK is
essential to NestLabs to unleash the generative potential of its digitized thermostat, i.e. to in-
spire innovation beyond its original meaning and boundaries (cf. Zittrain 2006).
Digitization of products offers new opportunities of value creation for product-
developing companies, and requires them to rethink established organization and architec-
tures of value creation. To help them to take full advantage of new digital opportunities up-
dated strategy frameworks are needed as "cognitive devices" (Baden-Fuller & Haefliger,
2013) which convey the new organizing logic of digital technology (Yoo, Henfridsson, et al.
2010). Although many business model approaches exist for different purposes, we found
none of it applicable for product-developing firms to analyze and design business models re-
volving around digitized products. Seen in this context, we argue that our research and the
resulting business model framework for IoT are an important contribution to both business
model theory and practice.
Contribution to Theory
For theory, the business model framework enhances existing knowledge in business
model research in several ways. First, our research clarifies to what extent received business
model approaches are applicable to value creation dynamics in IoT. The choice and norma-
tive perspectives for example define the firm as locus of value creation and therefore have
limitations when applied in the context of highly interconnected market environments as in-
stigated by pervasive digitization. In contrast, we identify the activity system perspective as
suitable basis for a business model framework in IoT: This stream is network-centric, as it
views the locus of value creation as boundary-spanning (Zott & Amit, 2010). Second, we of-
fer a new way of integrating information systems, marketing and business model literature by
building on the activity system perspective to overcome isolated "research in silos" (Burkhart
et al., 2011; Zott et al., 2011). Our observation is that all three domains are highly comple-
mentary and each of it offers valuable insights into value creation in IoT: The activity system
provides a suitable, theoretically grounded basis for the intended framework, information sys-
tem research clarifies the reshaped architecture of value creation, and, likewise as the service-
dominant logic, enriches and expands the activity system. The applied procedure enables us
to develop an integrated framework, which is triggered by real world phenomena and brings
together adjacent theoretical themes and concepts across marketing, strategy and IS. Third,
the enhanced framework contributes to business model research as exaptation (Gregor &
Hevner, 2013), which transfers the previous business model framework into the new context
of pervasive digitization. The framework is theoretically founded, which researchers can
readily use to analyze IoT business models in an efficient and structured way to further deep-
en the understanding of new business model phenomena. In the final analysis, the framework
provides business model research with a fresh perspective and further theoretical foundations.
Implications for Practice
For practitioners, specifically managers from product-developing firms, the framework
serves as strategy tool for depicting, analyzing and designing business models in IoT. A sig-
nificant benefit of the framework is that it makes recent IoT-driven market dynamics and spe-
cifics of digitization explicit. For example, the incorporation of the layer model helps manag-
ers to navigate through the complexity of value streams in a structured way. Moreover, it
supports decision makers in visualizing and understanding their own position within the IoT
ecosystem configuration, as a precondition to build sustainable, well thought-through busi-
ness models upon. Therefore, while Porter's value chain model takes linear value creation of
the physical product into pieces, we argue our model is its counterpart for horizontal value
creation in the case of digitization. We assume the framework to be especially helpful for
product-developing companies to get familiar with digital materiality. From this perspective,
the framework supports reframing manufacturing-pregnant managerial cognitions, which may
else represent barriers to tap into digital opportunities (Yoo, Henfridsson, et al. 2010).
Moreover, the framework can facilitate the communication between strategists and tech-
nologists within the company and may nurture mutual understanding between current and
future ecosystem partners. Lastly, the framework can help to provide MBA students from the
get go with a basic understanding of the applied organizing logic of digital technologies.
Limitations and Future Work
There is considerable potential for future research to enhance the overall understanding
of business models in the age of pervasive digitization. For example, the link between IT and
business model has remained a black box, and although IT’s important role in enabling and
triggering value creation is widely recognized (e.g., Amit and Zott 2012, Teece 2010), the
topic has received limited attention by research in both information system and strategy re-
search. The present paper gives a first overview of the role of the technology and/or IT within
business models seen as activity systems. Future studies could build on the suggested classifi-
cation and analyze its impact on value creation mechanisms in a more granular fashion, e.g.,
to reveal further design themes specific to IoT.
Moreover, the presented business model framework is theoretically grounded in the ac-
tivity system perspective and enhanced by the service-dominant logic and insights from IS
research. In addition, we successfully tested the framework in business model workshops
with incumbents as well as with startups across "smart" industries. However, future studies
could dig deeper into the limitations and advantages for practitioners by formally evaluating
the framework, e.g., by applying design science research methods.
Other ways in which the integrated business model perspective we developed in this pa-
per can be extended by future research include (1) classifying different boundary resource
strategies by empirical evidence and evaluating their impact on the overall activity system
performance (2) exploring the technology adaptation processes for IoT technologies within
activity systems (3) the impact of "updated" strategy tools on managerial cognition patterns.
(4) further identifying and integrating relevant literature to continuously enhance the business
model knowledge base on a cross-disciplinary level. We regard these as promising directions
that can contribute to a more comprehensive understanding and theory of digital business
models and ecosystems grounded in activity system theory.
Although many business model approaches exist, there is no framework or theory that re-
flect the specifics and dynamics of digital technologies with implications for product-
developing firms. We see this gap in sharp contrast to the overall importance and omnipres-
ence of the topic. Our research attempts to address this gap. In this article, we offer a business
model framework that seeks to guide managers of product-developing companies through the
complexity of value creation in the age of generativity and pervasive digitization. Conceptual-
ly, the framework builds upon the activity system perspective (Zott & Amit, 2010), which
conceives business models as purposeful configurations of strategically or technically distinct
activities, and is enriched and extended by valuable insights from information systems and
marketing research. By incorporating the nature and organizing logic of digital technologies –
rather than taking IT as separate entity – the framework resonates with opportunities enabled
by digitization. It supports managers in overcoming mental frames that are deeply imprinted
in managerial minds and models after a century of product-centricity and that are still barriers
to tap into the rich and new value creation opportunities offered by pervasive digitization. For
theory, our research acknowledges the critical role of IT in context with value creation and
business model innovation, and contributes new aspects to the discussion. Moreover, by the
integration of received literatures from different domains, we hope to inspire further cross-
disciplinary research in the field of business models so as to advance the understanding and
theoretical underpinning of this powerful concept
Thank you for your feedback.
Adner, R., & Kapoor, R. 2010. Value creation in innovation ecosystems: How the structure of
technological interdependence affects firm performance in new technology generations.
Strategic Management Journal, 31: 306–333.
Afuah, A. 2004. Business models: A strategic management approach. New York.
Afuah, A., & Tucci, C. 2001. Internet Business Models and Strategies. New York McGraw.
Altman, E. J., & Tripsas, M. 2013. Product to Platform Transitions: Organizational Identity
Implications. Harvard Business School, Working Paper Series.
Altman, E. J., Tushman, M. L., & Nagle, F. 2013. Innovating without Information
Constraints: Organizations, Communities, and Innovation When Information Costs
Approach Zero. Harvard Business School, Working Paper Series.
Amit, R., & Zott, C. 2001. Value creation in E-business. Strategic Management Journal,
Amit, R., & Zott, C. 2012. Creating Value Through Business Model Innovation. MIT Sloan
Management Review, 53: 41–49.
Atzori, L., Iera, A., & Morabito, G. 2010. The Internet of Things: A survey. Computer
Networks, 54(15): 2787–2805.
Baden-Fuller, C., & Haefliger, S. 2013. Business Models and Technological Innovation.
Long Range Planning, 46(6): 419–426.
Baldwin, C. Y., & Clark, K. B. 2000. Design Rules: The Power of Modularity. Academy of
Management The Academy of Management Review: 471.
Barrett, M., Davidson, E., Prabhu, J., & Vargo, S. L. 2010. Service Innovation in the Digital
Age. Call for Papers-MIS Quarterly Special Issue on Service Innovation in the Digital
Barrett, M., Davidson, E., & Vargo, S. L. 2012. Being innovative about service innovation:
Service, design and digitalization: 1–6.
Ben Eaton, Silvia Elaluf-Calderwood, & Carsten Sørensen, and Y. Y. n.d. Distributed Tuning
of Boundary Resources: The Case of Apple’s iOS Service System. (under review).
Boudreau, K. J., & Hagiu, A. 2008. Platform Rules: Multi-Sided Platforms as Regulators.
Working Papers -- Harvard Business School Division of Research, 1–29.
Boudreau, K. J., & Lakhani, K. R. 2009. How to Manage Outside Innovation How to Manage
Outside Innovation, (50413).
Brandenburger, A. M., & Stuart, H. W. 1996. Value-based Business Strategy. Journal of
Economics Management Strategy, 5: 5–24.
Brocke, J. Vom, Simons, A., Niehaves, B., & vom Brocke, J. 2009. Reconstructing the giant:
On the importance of rigour in documenting the literature search process. European
Conference of Information Systems 2009.
Burkhart, T., Krumeich, J., Werth, D., & Loos, P. 2011. Analysing the business model
concept - A comprehensive classification of literature. International Conference on
Information Science: 1–19.
Casadesus-Masanell, R., & Ricart, J. E. 2010. From Strategy to Business Models and onto
Tactics. Long Range Planning, 43(2-3): 195–215.
Casadesus-Masanell, R., & Ricart, J. E. 2011. How to design a winning business model.
Harvard Business Review, 89(1/2): 1–9.
Chesbrough, H. 2002. The role of the business model in capturing value from innovation:
evidence from Xerox Corporation’s technology spin-off companies. Industrial and
Corporate Change, 11(3): 529–555.
Chesbrough, H., & Appleyard, M. 2007. Open innovation and strategy. California
management review, 50: 57–77.
Chesbrough, H., & Rosenbloom, R. S. 2002. The role of the business model in capturing
value from innovation: evidence from Xerox Corporation’s technology spin-off
companies. Industrial and Corporate Change, 11: 529–555.
Dahlander, L., & Gann, D. M. 2010. How open is innovation? Research Policy, 39: 699–709.
Demil, B., & Lecocq, X. 2010. Business Model Evolution: In Search of Dynamic
Consistency. Long Range Planning, 43(2-3): 227–246.
Eaton, B., Elaluf-Calderwood, S., Sorensen, C., & Yoo, Y. 2011. Dynamic Structures of
Control and Generativity in Digital Ecosystem Service Innovation: The Cases of the
Apple and Google Mobile App Stores. http://eprints.lse.ac.uk/47436.
El Sawy, O. a., & Pereira, F. 2013. Business Modelling in the Dynamic Digital Space.
Springer Berlin Heidelberg.
Fichman, R. G., & Nambisan, S. 2009. Information Technology and Product Development.
(S. Nambisan, Ed.), 5: 19–47.
Fleisch, E. 2010. What is the Internet of Things? What is the Internet of Things - An
Economic Perspective. Whitepaper.
Geoffrion, A. M., & Krishnan, R. 2003. E-Business and Management Science: Mutual
Impacts (Part 2 of 2). Management Science.
Ghazawneh, A., & Henfridsson, O. 2013. Balancing platform control and external
contribution in third-party development: the boundary resources model. Information
Systems Journal, 23(2): 173–192.
Gordijn, J., & Akkermans, H. 2001. Designing and evaluating e-business models. IEEE
Intelligent Systems, 16(4): 11–17.
Gregor, S., & Hevner, A. R. A. 2013. Positioning Design Science Research for Maximum
Impact. Management Information Systems Quarterly, 37(2): 337–355.
Hedman, J., & Kalling, T. 2003. The business model concept: theoretical underpinnings and
empirical illustrations. European Journal of Information Systems, 12(1): 49–59.
Henfridsson, O. 2013. The generative mechanisms of the digital infrastructure evolution, MIS
Quarterly, 37(3): 907–931.
Henfridsson, O., Mathiassen, L., & Svahn, F. 2014. Managing technological change in the
digital age: the role of architectural frames. Journal of Information Technology, 29:
Iansiti, M., & Levien, R. 2004. The keystone advantage. Networks. Wiley.
Johnson, M. W., Christensen, C. M., & Kagermann, H. 2008. Reinventing Your Business
Model. Harvard Business Review, 86(12): 50–59.
Kalinowski, M., & Vives, L. 2013. Multi-perspective View on Business Models: Review and
Research Agenda. Academy of Management Proceedings, 2013(1): 17403.
Kaplan, S., & Tripsas, M. 2008. Thinking about technology: Applying a cognitive lens to
technical change. Research Policy, 37(5): 790–805.
Keen, P., & Williams, R. 2013. Value Architectures for Digital Business: Beyond the
Business Model. MIS Quarterly, 37: 643–648.
Kominers, P. 2012. Interoperability Case Study Internet of Things (IoT). Berkman Center
Research Publication, 7641.
Langlois, R. N. 2003. The vanishing hand: the changing dynamics of industrial capitalism.
Industrial and Corporate Change, 12(2): 351–385.
Langlois, R. N. 2007. The dynamics of industrial capitalism: Schumpeter, Chandler, and
the new economy. The Graz Schumpeter lectures: 122 p.
Leavy, B. 2014. Venkat Ramaswamy – how value co-creation with stakeholders is
transformative for producers, consumers and society. Strategy & Leadership, 42(1): 9–
Lusch, R. F. 2006. Service-dominant logic: reactions, reflections and refinements. Marketing
Lusch, R. F., Brown, S. W., & Brunswick, G. J. 1992. A general framework for explaining
internal vs. external exchange. Journal of the Academy of Marketing Science, 20(2):
Lusch, R. F., & Nambisan. 2014. Service Innovation. Mis Quarterly (forthcoming).
Lusch, R. F., & Vargo, S. L. 2006. The Service-dominant Logic of Markeing: Dialog, Debate,
and Directions. The Servicedominant Logic of Markeing Dialog Debate and
Lusch, R. F., Vargo, S. L., & O’Brien, M. 2007. Competing through service: Insights from
service-dominant logic. Journal of Retailing, 83(1): 5–18.
Lusch, R., & Vargo, S. L. 2014. Service-Dominant Logic: Premises, Perspectives,
Possibilities. What it is, what it is not, what it might be.
Magretta, J. 2002. Why business models matter. Harvard business review, 80(5): 86–92, 133.
Mark W. Johnson, Clayton M. Christensen, and H. K. 2008. Reinventing your Business
Model. Harvard business Review, 59–67.
Mason, K., & Spring, M. 2011. The sites and practices of business models. Industrial
Marketing Management, 40(6): 1032–1041.
McGrath, R. G. 2010. Business Models: A Discovery Driven Approach. Long Range
Planning, 43(2-3): 247–261.
Michel, S., Brown, S. W., & Gallan, A. S. 2007. An expanded and strategic view of
discontinuous innovations: deploying a service-dominant logic. Journal of the Academy
of Marketing Science, 36(1): 54–66.
Michel, S., Vargo, S. L., & Lusch, R. F. 2007. Reconfiguration of the conceptual landscape: a
tribute to the service logic of Richard Normann. Journal of the Academy of Marketing
Science, 36(1): 152–155.
Morris, M., Schindehutte, M., & Allen, J. 2005. The entrepreneur’s business model: toward a
unified perspective. Journal of Business Research, 58(6): 726–735.
Ng, I. C. L., Vargo, S. L., & Smith, L. A. 2012. Reconceptualising service through a service-
Ng, I., Vargo, S. L., & Smith, L. 2012. Reconceptualising Service through a Service-
Normann, R. 2001. Reframing Business: When the Map Changes the Landscape. Wiley.
Osterwalder, A., Pigneur, Y., & Tucci, C. L. 2005. Clarifying business models: Origins,
present and future of the concept. Communications of the Association for Information
Systems, 15: 1–40.
Palfrey, J., & Gasser, U. 2007. Mashups Interoperability and eInnovation. Berkman
Publication Series. https://cyber.law.harvard.edu/interop/pdfs/interop-mashups.pdf,
December 28, 2013.
Penrose, E. T. 1959. The Theory of the Growth of the Firm. New York: John Wiley & Sons
Inc. Penrose, E. T, 1: 1–23.
Priem, R. L., Butler, J. E., & Li, S. 2013. Toward Reimagining Strategy Research:
Retrospection and Prospection on the 2011 AMR Decade Award Article. Academy of
Management Review, 38(4): 471–489.
Rifkin, J. 2011. The Third Industrial Revolution: How Lateral Power Is Transforming
Energy, the Economy, and the World. Palgrave Macmillan.
Sambamurthy, V., & Zmud, R. W. 2000. Research Commentary: The Organizing Logic for
an Enterprise’s IT Activities in the Digital Era?A Prognosis of Practice and a Call for
Research. Information Systems Research.
Sanchez, R., & Mahoney, J. T. 1996. Modularity, flexibility, and knowledge management in
product and organization design. Strategic Management Journal, 17: 63–76.
Sawy, O. A. El. 2003. The IS Core – IX The 3 Faces of IS Identity: Connection, Immersion,
and Fusion. Communications of the Association for Information Systems, 12: pp. 588–
Sawy, O. El, & Francis, P. 2013. Business modelling in the dynamic digital space. Springer
Selander, L., Henfridsson, O., & Svahn, F. 2013. Capability search and redeem across digital
ecosystems. Journal of Information Technology, 28(3): 183–197.
Shafer, S. M., Smith, H. J., & Linder, J. C. 2005. The power of business models. Business
Sorescu, A., Frambach, R. T., Singh, J., Rangaswamy, A., & Bridges, C. 2011. Innovations in
Retail Business Models. Journal of Retailing, 87: S3–S16.
Svahn, F. 2012. Digital Product Innovation: Building Generative Capability through
Tapscott, D., Lowy, A., & Ticoll, D. 2000. Digital capital: Harnessing the power of business
Teece, D. J. 2010. Business Models, Business Strategy and Innovation. Long Range
Planning, 43(2-3): 172–194..
Timmers, P. 1998. Business Models for Electronic Markets. Research Note.
Tiwana, A., Konsynski, B., & Bush, A. a. 2010. Research Commentary —Platform
Evolution: Coevolution of Platform Architecture, Governance, and Environmental
Dynamics. Information Systems Research, 21(4): 675–687.
Tripsas, M., & Gavetti, G. 2000. Capabilities, cognition, and inertia: evidence from digital
imaging. Strategic Management Journal, 21: 1147–1161.
The Economist 2013. The Internet of Things business index: A quiet revolution gathers pace.
The Economist Intelligence Unit, 2013.
Van Alstyne, M. 2014. The Economics of the Internet of Things. Technology Review, 117(4).
Vargo, S., & Akaka, M. 2012. Value Cocreation and Service Systems (Re) Formation: A
Service Ecosystems View. Service Science, 4: 207–217.
Vargo, S. L., & Lusch, R. F. 2004. Evolving to a New Dominant Logic for Marketing.
Journal of Marketing, 68(1): 1–17.
Vargo, S. L., & Lusch, R. F. 2007. Service-dominant logic: continuing the evolution. Journal
of the Academy of Marketing Science, 36(1): 1–10.
Webster, J., & Watson, R. T. 2002. Analyzing the past to prepare for the future: Writing a
literature review. Management Information Systems Quarterly, 26(2).
Yoo, Y. 2013. The Tables Have Turned: How Can the Information Systems Field Contribute
to Technology and Innovation Management Research? Journal of the Association for
Information Systems, 1–17.
Yoo, Y., Henfridsson, O., & Lyytinen, K. 2010. Research Commentary —The New
Organizing Logic of Digital Innovation: An Agenda for Information Systems Research.
Information Systems Research, 21(4): 724–735.
Yoo, Y., Lyytinen, K., Boland, R., Berente, N., Gaskin, J., & Schutz, D. 2010. The Next
Wave of Digital Innovation: Opportunities and Challenges. Research Workshop:
“Digital Challenges in Innovation Research”: 1–37.
Zittrain, J. 2006. The Generative Internet. Harvard Law Review, 119: 1975–2039.
Zittrain, J. 2008. The Future ofthe Internet and How to Stop It. New Haven, CT: Yale
University Press. echo chamber.
Zott, C., & Amit, R. 2007. Business Model Design and the Performance of Entrepreneurial
Firms. Organization Science, 18(2): 181–199.
Zott, C., & Amit, R. 2008. The fit between product market strategy and business model:
implications for firm performance. Strategic Management Journal, 29(1): 1–26.
Zott, C., & Amit, R. 2010. Business Model Design: An Activity System Perspective. Long
Range Planning, 43(2-3): 216–226.
Zott, C., Amit, R., & Massa, L. 2011. The Business Model: Recent Developments and Future
Research. Journal of Management, 37(4): 1019–1
Design Requirements for a Business Model Framework in IoT
Central Tenets of S-D Logic and Digital Innovation
Requirements (R) for a BM Framework in IoT
• Meaning of Networks: Collaboration is essential, and
a focal firm's ecosystem is lever of advantage
R1: Network-centric, rather than firm-centric:
Value network as locus of value creation
• Transcending the Consumer/Producer divide: Cus-
tomers and partners are co-producer and co-
creator of value
R2: Considers customer as co-producer, rather
than solely receiver
• Service is the basis of all exchange: Incentives to
participate in the ecosystem can be monetary and
R3: Considers monetary and non-monetary
benefits for actors from participating in the
• Reconceptualizing Resources: Relevant resources
are all those which a firm can draw upon
R4: Considers external & internal resources (re-
lated to R1)
• Transcending the Goods/Service Divide: Both are
equally means/"service platforms" to further co-
create value and services upon
R5: Reflects all layers across the IoT value stack
(Yoo et al., 2010) as sources of value crea-
• Ecosystems as complex, adaptive systems
R6: Features a dynamic perspective
Concept Matrix: Do Existing Business Model Approaches Integrate IoT-Relevant Attributes?
Role of the
nested (co-creator) open in & external (receptive) dynamic 83%
in & external no dynamic 50%
strategy firm/nested receiver open in & external no dynamic 67%
nested receiver n.a. in & external no dynamic 50%
Gordijn et al.
e-business network n.a. open n.a. yes static 50%
Timmers (1998) e-business network n.a. open in & external n.a. dynamic 67%
inn.mgt firm receiver
in & external no dynamic 33%
Shafer (2005) strategy nested receiver n.a in & external no dynamic 50%
strategy firm receiver
internal no dynamic 17%
strategy firm receiver n.a. internal no dynamic 0%
McGrath (2010) strategy firm receiver
internal no dynamic 17%
Priem (2013) strategy firm receiver
internal no static 0%
Weill and Vitale
e-business nested n.a. open in & external n.a. static 50%
e-business firm receiver
n.a. no static 0%
strategy firm receiver
internal no static 0%
Teece (2010) strategy firm receiver
internal no static 0%
Magretta (2002) strategy firm receiver
internal no static 0%
IoT Relevant BM Attributes
Modular-Layered Architecture of Digitized Products
(Yoo et al, 2010)
Integrated Framework for Business Models in IoT
Logical T ransmission
Logical C apability
APPENDIX A: Table A1
S-D Logic and Digital Innovation Literature Parallel and Enrich the Activity-Based System
Activities as transcending
model, comprise infor-
mation and goods ex-
changed as well as re-
sources and capabilities
required for exchanges
Business models are
outlined by strategically
and/or technically rele-
vant activities of the
firm's activity system
Activities can be horizon-
tal as well as vertical
Services or activities as
transcending model, com-
prise all activities that make
new relationships and con-
figurations of elements pos-
sible. Includes goods and
non-goods as well as oper-
ant and operand resources.
Economy as web of activities
Physical goods are carriers
of competences and/or me-
dium to provide service
Activities across 4 layers:
Device, Connectivity, Ser-
vice, Content. Each layer
serves as platform to cre-
ate value upon, i.e. are
source of value creation
Boundary resources of
strategic importance, pre-
condition of "generative"
Ways in which actors are
linked and exchange is
Order and timing of ex-
Flexibility and adaptability
of transaction structure
Ability to link/re-link activities
and assets within the activity
Level of interactivity and
reciprocity between econom-
Degree to which mobilization
of resources for a
time/space/actor unit can
Value constellations: Coop-
erative networks of providers
and customer communities
IT is used to transform
vertical hierarchies into
Boundary resources enable
and determine linkage
between third party activi-
ties, activities of the focal
firm and/or other third par-
Nature of control mecha-
nism: Incentives, trust
Locus of control of flows
of information, goods,
Exchange mechanism: all
exchange is service-for ser-
vice exchange (resource-for-
resource exchange respec-
Money, goods, organizations
etc. as intermediaries in
exchange -"exchange vehi-
Reason to collaborate: Mon-
etary & non-monetary,such
as control, trust, psychic or
economic rewards etc.
Boundary resources come
with contractual/ technical
rules as part of their de-
sign, e.g. access to user
data, revenue sharing
model between actors.
Balancing between control
and generativity via bound-
ary resources ("resourcing"
Value creation and innova-
tion can spring up inde-
pendently at any layer,
leading to cascading ef-
fects on other layers