Service-oriented Business Model Framework

A Service-dominant Logic based Approach for

Business Modeling in the Digital Era

Andreas Pfeiffer

, Karl-Heinz Krempels

1,2

and Matthias Jarke

1,2

Chair of Computer Science 5, Information Systems, RWTH Aachen University, Ahornstr. 55, 52056 Aachen, Germany

Fraunhofer Institute for Applied Information Technology Fit, c/o RWTH Aachen, Ahornstr. 55, 52056 Aachen, Germany

Keywords: Business Model, Digital Transformation, Digital Technology, Digitalization, Service-Dominant Logic.

Abstract: The business model (BM) concept has been described as an intermediating tool for managing the transition

from technology’s potential value into market outcomes. Unfortunately, current business modeling

methodologies do not meet specific needs of modeling value (co-)creation in digitally transforming

ecosystems (DTE). Based on desktop research and empirical findings this paper proposes a Service-oriented

Business Modeling (SoBM) framework to advance the development of market solutions in these

environments. Adopting a service-dominant logic’s (S-D logic) perspective a service-centric,

network-oriented, and transcending solution proposal is presented. It has been designed to identify and

leverage digital technology’s potential value and to improve the conceptualization of value creation and

capturing in a digitally connected physical world.

1 INTRODUCTION

Business practitioners and scholars have described

the intense and progressive transformation of

organizations, industries, and the overall economy

through digital technology implementation in

products, services, and BMs. This calls for

constantly questioning, newly defining and

transforming BMs to ensure sustainable business

success. Hereby, the convergence of digital and

physical value networks as well as an increased

importance of service business can be seen as key

challenges for digital business strategy and the

design of contemporary BMs (Kane, 2016; Lucas et

al., 2013; Zolnowski, 2015).

Among the many reasons, the change in the role

of information strategy as an integral part of a digital

business strategy (Bharadwaj et al., 2013) forces

information systems research (ISR) to give

guidance, and concrete recommendations for

business modeling in DTEs (Berman, 2012;

Bharadwaj et al., 2013; Iansiti and Lakhani, 2014;

Veit et al., 2014). This is particularly important as it

has been observed that not only products and

services, but even more BMs have to promote the

generative characteristics of digital artifacts that

make use of them. Hence, there is a necessity to

develop a transcending and flexible approach to

provide a supportive environment for developing

viable market solutions in a digitally connected

physical world (Kallinikos et al., 2013; Lusch and

Nambisan, 2015; Pfeiffer and Jarke, 2016; Turber et

al., 2014; Yoo, 2010; Yoo, 2013).

By elaboration of digital technology’s

characteristics as well as its influences on economic

exchange this paper presents a set of requirements

for developing market solutions in DTEs. Following

these requirements and by taking a S-D logic

perspective a new business modeling approach is

presented. Enriched by Service-oriented

Architecture’s (SOA) well-proven modeling

principles the framework provides a flexible,

networked, and agile modeling process for

constantly changing and evolving DTEs.

This paper is structured as follows. First, the

research methodology is briefly introduced. Second,

a literature overview on the related work is given.

Third, based on the related work the requirements on

business modeling in DTEs are elaborated. Fourth,

we present the SoBM framework as an appropriate

solution proposal for the identified context of

application. Finally, the findings are discussed based

on case study results and a conclusion including

limitations and future work is given.

Pfeiffer, A., Krempels, K-H. and Jarke, M.

Service-oriented Business Model Framework - A Service-dominant Logic based Approach for Business Modeling in the Digital Era.

DOI: 10.5220/0006255103610372

In Proceedings of the 19th International Conference on Enterprise Information Systems (ICEIS 2017) - Volume 3, pages 361-372

ISBN: 978-989-758-249-3

361

2 METHODOLOGY

Our research pursues a design science research

methodology (Hevner et al., 2004; Peffers et al.,

2007). It is in line with existing discussions in

design science (Niederman and March 2012) and

business model research (Veit et al., 2014) by

advancing knowledge about BMs in DTEs.

The development of our SoBM approach has

been an iterative process involving construction and

evaluation phases. A series of case studies (Pfeiffer

and Jarke, 2016; Pfeiffer, 2016) was a fundamental

part of the research to gain insights into the research

problem and evaluate the developed artifact. This

artifact has been discussed and refined in diverse

expert workshops and international conferences

(e.g., Pfeiffer, 2016), which finally led to the present

version of the SoBM framework.

3 RELATED WORK

The artifact “SoBM framework” is built upon

relevant extant work, which was founded in three

domains: ISR, BM research, and marketing research.

ISR delivers insights into digital technology’s

nature, its layered modular architecture (LMA) and

digital technology’s influence on value creation

processes. BM research provides knowledge on the

relevant building blocks of BMs and a common state

of the art in business modeling. Marketing literature

contributes by providing S-D logic as an underlying

philosophy for the interpretation economic exchange

in DTEs.

3.1 Digitization and Digital

Transformation

In nearly every industry sector, customer

expectations, operational needs and technological

evolution force business leaders to rethink business

strategy with regard to the role of digital

technologies. In many cases, digital technology has

shown to be central in making new BM technically

feasible and economically viable (Berman, 2012;

Bharadwaj et al., 2013; Yoo et al., 2010; Yoo et al.,

2013). To take advantage of digital technology’s

application in the business context, it is essential to

firstly understand what digital technology is and

secondly how it can be transformed into economic

output.

Digital technologies are defined as

“combinations of information, computing,

communication, and connectivity technologies”

(Bharadwaj et al., 2013, p. 471). Within our

approach, they cover both digital and digitized

artifacts. Digital artifacts are continuants combined

with structure, an agentive function imposed by

human communities and a nonphysical mode of

being (Faulkner and Runde, 2013). They result from

digitization in the narrow sense, i.e., „the encoding

of analog information into digital format“ (Yoo et

al., 2010, p. 725). Digitized or sometimes also

referred as digitalized artifacts, however, are

structured and organized arrangements of

nonmaterial (digital) and material objects (Yoo et

al., 2010). They are the outcome of digitization in

the broader sense, i.e., the embedding of digital

artifacts into material technological objects.

Kallinikos et al. (2013) introduced editability,

interactivity, re-programmability/ openness and

distributiveness as key attributes of digital artifacts.

Yoo et al. (2010) point out, that the incorporation of

digital artifacts causes physical objects to adopt

these digital characteristics. Thus, also digitized

artifacts are programmable and the design of new

functionality can be integrated at any time, even

after the physical production. Further, economics of

scale during production become less relevant as the

marginal costs of reproduction and distribution of

digital artifacts are next to nothing (Henfridsson et

al., 2014). Overall, digitized artifacts are perceived

as having an ambivalent ontology (Kallinikos et al.,

2013), being intentionally incomplete, and

perpetually in the making (Zittrain, 2008).

Digitization enables resource dematerialization

in form of resource unbundling and liquification.

The latter concept entails the separation of

information from its physical carriers. Resource

unbundling implies the dissolvement of boundaries

which are holding together activities in time, place

and actors. Resource dematerialization enhances

economic exchange by increasing resource density

within value creation providing benefit to the actors

and improving the viability of the ecosystem (Lusch

and Nambisan, 2015; Normann, 2001). These

improvements are facilitated through optimization in

resource integration (i.e., digital technology’s role as

enabler) or through the creation of new sources of

value (i.e., digital technology’s role as initiator)

(Lusch and Nambisan, 2015).

Yoo et al. (2010) pointed out that with

digitization a new “layered modular architecture”

(LMA) of digital technology emerged. This LMA

consists of four loosely connected but

interdependent layers: device, network, service, and

content. Through its "de-couplability" a LMA

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facilitates a free and individual design between the

different layer levels. “The components represent

[a] bundled set of specialized knowledge and skills

appearing in the form of tangible or intangible

components that easily interface with heterogeneous

product forms and types” (Lusch and Nambisan,

2015, p. 164 f.). Hereby, the service layer of a

specific digital technology (i.e., a combined set of

components) provides functionality for actors to

create, manipulate, store, and consume information

independent of the upper or lower layers. Thus, it

unites “physical” and “intangible” functionality and

represents the freely combinable value provision

elements of a specific digital technology (Pfeiffer

and Jarke, 2016; Yoo et al., 2010). As many digital

artifacts are application agnostic, they allow multiple

actors (incl. non-human actors) to interact, share,

and contribute across the four layers independent of

the embedding material objects or actual ownership

(Storbacka et al., 2012; Yoo et al., 2010). This can

be seen as one key enabler for generativity and

digitally invoked transformation processes–an

unforeseen and unprecedented field of possible

“innovative” services provided by and with digital

technology (Pfeiffer and Jarke, 2016; Tilson et al.

2010; Yoo et al., 2010). Based on the combinatorial

evolution of existing technological artifacts (Arthur,

2009) the potential of digitization-based innovation

is transcending product/service and industry borders.

This increases by the widespread use of digital

technology applying the LMA and ecosystems

embedding it into supportive environments. These

have been characterized by a modular and granular

architecture (Kallinikos et al. 2013; Lusch and

Nambisan, 2015; Yoo et al. 2010).

However, digitization and digital technology

only provide chances to optimize and enhance value

creation and capturing. These chances must be

transferred into the context of ecosystems to capture

improvements in actor’s resource density. This

process is called digitalization or synonymously

digital transformation. Tilson et al. (2010) define

digitalization as “a sociotechnical process of

applying digitizing techniques to broader social and

institutional contexts that render digital technologies

infrastructural” (Tilson et al., 2010, p. 2).

Accordingly, it is not only necessary to

understand digital technology’s nature and its

potentials for value creation. The perception of a

sociotechnical process requires to analyse the

application of technology as resources in specific

contexts. This application is characterized by

interdependencies between resources (e.g.,

technology, knowledge, institutions) and various

actors creating value through the integration of

digital technology. Thereby, the establishment of

shared institutions and common social practices

becomes central to the development of new market

solutions. This perspective focuses attention on

“what” an actor actually realizes through digital

technology and how digital technology changes his

capabilities to create value for himself or another

actor. Even more, the recognition of digital

technology’s initiator role within value creation

leads to the question how to conceptualize its dual

role in business modeling (Chesbrough, 2007; Lusch

and Nambisan, 2015; Storbacka et al., 2012; Yoo,

2010). Following this logic means to question

established views on economic exchange,

institutions and ecosystems’ architecture to cope

with and proactively utilize changes in scale, scope,

speed and sources of value through digitization

(Bharadwaj et al., 2013; Storbacka et al., 2012;

Turber et al., 2014; Zolnowski, 2015).

3.2 Service-dominant Logic

S-D logic was introduced by Lusch and Vargo in

2004. It derived from debates in marketing theory

concerning the applicability of a goods-oriented

interpretation of economic exchange against the

background, among other things, of the increasing

prevalence of digital technology’s “intangible” value

creation contribution (i.e., service as a process).

S-D logic addresses the generative nature of

digital technology and offers a perspective on

economic exchange transcending the boundaries of

products, services and actor networks. Hereby, it

provides an adequate perspective for analyzing and

conceptualizing economic exchange in DTEs (e.g.,

Lusch and Nambisan, 2015; Storbacka et al., 2012;

Vargo and Lusch, 2016; Zolnowski, 2015). Five

axioms are fundamental basis of the concept (see

Table 1).

Table 1: Service-dominant logic’s five axioms, Vargo and

Lusch, 2016.

In S-D logic terminology service is fundamental

basis of exchange and is defined as “the application

of specialized competences (operant resources–

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knowledge and skills), through deeds, processes and

performances for the benefit of another entity or the

entity itself” (Lusch and Vargo, 2014, p. 43). Value

is always determined by the beneficiary (e.g., the

customer) and co-created through actors by

integrating (internal or external) resources through

the exchange of service. Thus, value is seen as

dynamic, experiential and contextual, rather than as

a unit of output or embedded in a good or service

(Vargo and Lusch, 2016). This shifts attention from

goods–as inert, tangible passive operand resources–

to skills and knowledge–as intangible operant

resources applied through service provision.

Operant resources are acting on other resources

to produce effects and are of a dynamic and difficult

to transfer nature. Thereby, they are a central source

of strategic benefit. “The most fundamental operant

resource is knowledge and the technology it fosters.

Technology is the practical application of

knowledge.” (Lusch and Nambisan, 2015, p. 159).

Explicitly highlighting the dual role of digital

technology as an operand (enabling) and operant

(initiating) resource characterized by institutional

components improves the analysis and explanation

of the necessities and opportunities through digital

transformation (Lusch and Nambisan, 2015).

Service ecosystems as units of analysis are

defined as “a relatively self-contained, self-adjusting

system of resource integrating actors connected by

shared institutional arrangements and mutual value

creation through service exchange” (Lusch and

Vargo, 2014, p. 161). This highlights the

coordinating function of institutions and institutional

arrangements (Lusch and Nambisan, 2015), as well

as their role in being resources integrated by the

involved actors. Using “oscillating foci” a service

ecosystem can be analyzed at various levels of

aggregation. Individual and dyadic structures and

activities are studied at the micro level (e.g.,

internal, B2B or B2C), midrange structures and

activities (e.g., industry, markets) at the meso level,

and wide-ranging societal structures and activities at

the macro level (Vargo and Lusch, 2016).

Providing relevant elements and relations for

understanding economic exchange processes in DTE

S-D logic can be taken as an explanatory approach

and basis for the development of business activities

in networked markets (Lusch and Nambisan, 2015;

Storbacka et al., 2012; Turber et al., 2014;

Zolnowski, 2015).

3.3 Business Model Concepts and

Business Model Frameworks

The pace and impact of digitalization has recently

initiated a renaissance of the BM concept, a

theoretical model describing the components and

fundamental mechanisms of value creation and

capturing in organization. There exists a large

variety of BM concepts and frameworks. This

derives, inter alia, from the fact that the BM concept

origins from diverse disciplines such as ISR,

strategy, business management, economics (Fielt,

2014; Pozzi et al., 2016).

Within the substantial research on BMs in ISR

and BM research in S-D logic, scholars have

recently reviewed the literature (Fielt, 2014; Frow et

al., 2014; Pozzi et al., 2016; Storbacka et al., 2012;

Turber et al., 2014; Zolnowski, 2015).

Unfortunately, these reviews reveal that neither a

commonly accepted definition of BMs nor regarding

their conceptual components exists. The concept

boundaries of applications differ according to the

context and conditions defined in the approaches

(Fielt, 2014). Nevertheless, scholars identified

commonalities in definitions and regarding basic

elements of BM as they seem to oscillate around

value proposition, value architecture, value network

and value finance (Fielt, 2014; Frow et al., 2014;

Pozzi et al., 2016; Storbacka et al., 2012; Zott et al.,

2011). Therefore, we base our further work on the

Zott et al.’s (2011) conclusions regarding the BM

concept: “(1) there is widespread

acknowledgement—implicit and explicit—business

model is a new unit of analysis that is distinct from

the product, firm, industry, or network; it is centered

on a focal firm, but its boundaries are wider than

those of the firm; (2) business models emphasize a

system-level, holistic approach to explaining how

firms “do business”; (3) the activities of a focal firm

and its partners play an important role in the

various conceptualizations of business models that

have been proposed; and (4) business models seek to

explain both value creation and value capture” (Zott

et al., 2011, p. 1020).

Further, frameworks or representations of BMs

are widely used tools for analyzing and developing

current or future business ventures. They are

substantiating or operationalizing the BM concept:

“a useable business model framework captures the

ways in which key decision variables are integrated,

including the need for unique combinations that are

internally consistent.” Moreover, a BM framework

is “more than the sum of its parts, the model

captures the essence of how the business system will

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be focused” (Morris et al., 2005, p. 47). According

to Morris et al. (2005) a framework needs to be

simple, logical, measurable, comprehensive, and

operationally meaningful. According to results of

recently conducted reviews most BM concepts lack

relational and process-oriented attributes that are

characteristic for service logic and supporting the

understanding of digital technology’s opportunities

for BMs (Fielt, 2014; Frow et al., 2014; Pozzi et al.,

2016; Storbacka et al., 2012; Zolnowski, 2015).

Overall, many of the well-known business modeling

approaches tend to focus on strategic aspects of

BMs. “They provide “an exploded view”, showing

the “parts of an engine”” (Westerlund et al., 2014,

p. 9), presenting monolith and static views while

focusing on the architecture of value creation and

capturing rather than a relational- and process-

oriented perspective. With this approach, they fail to

explain the dynamics between BM components and

the surrounding ecosystems (Fielt, 2014). In this

line, existing approaches do not sufficiently support

a transcending view on value creation in networked

relational and interdependent partnership (Turber et

al., 2014; Zolnowski, 2015). Building on S-D logic

and service science, first attempts to create such

models emerged adapting existing BM approaches

(e.g., Ojasalo and Ojasalo, 2015; Turber et al., 2014;

Viljakainen et al., 2013; Zolnowski, 2015).

The results reflect general challenges in mapping

networked relations to focal company’s business

thinking and in identifying new opportunities for

co-creation to increase resource density based on

digital technology’s LMA (see Viljakainen et al.,

2013; Frow et al., 2014). Further, existing approach

seem to fail in coping with the complexity emerging

from the interactive, fluid and borderless attributes

of digital resources. They seem to focus on physical

or digital materiality (good-like characteristics)

rather than on digital technology’s potential to

enhance, extend, and redefine value co-creation in

value networks.

4 REQUIREMENTS FOR

BUSINESS MODELING IN

DIGITALLY TRANSFORMING

ECOSYSTEMS

As pointed out in the previous sections, digitization

and digital transformation force companies to

question established views on economic exchange,

proactively use the chances of digital transformation

and built viable market solutions.

We elaborated that the formation of market solutions

in digital transformation has to take “digital nature”

(i.e. editability, interactivity, openness and

distributiveness) and its LMA (i.e. networked,

loosely coupled, service-centric) into account.

Especially, a development environment

characterized by modularity and granularity has

been considered as supportive to create and capture

value from digitization.

The BM concept appears to provide an

appropriate unit of analysis for shaping business

activities while S-D logic presents an explanatory

perspective on economic exchange in DTEs.

Further, the discussion has shown that the concept

used to describe and manage value creation and

capturing must be adapted to an interactive and

networked perspective that transcends

product/service boundaries and focuses on value co-

creation.

Building on these findings we propose following

requirements for business modeling in DTEs

substantiated in two categories (see Figure 1):

Figure 1: Requirements for business modeling in digitally

transforming ecosystems–own diagram based on Lusch

and Nambisan, 2015; Morris et al., 2005; Vargo and

Lusch, 2016.

Business Model Elements: Following our findings, a

comprehensive BM concept builds on S-D logic

ecosystem elements and their relations. Specifically,

we see the value context and operant resources (e.g.,

institutions and digital technology) relevant for

developing viable solutions in DTEs. They cover

relevant ecosystem's aspects transcending focal

actor’s sphere to partners and foremost

beneficiaries’ value perception (value-in-context) in

value co-creating activities (see also Zolnowski,

2015). The value-in-context is seen as direct related

to interrelating value propositions as they are

“phenomenologically determined based on existing

resources, accessibility to other integratable

resources, and circumstances” (Vargo and Akka,

2009, p. 39).

Design Principles: Following common

perception of digital technology’s nature, BM

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365

principles should guide the course of modeling in

the way that the architecture is characterized by a

layered structure reducing complexity in networked

and interrelated system. Further, they should allow

loose coupling and a flexible adjustment of BM

elements. As a modular and granular architecture is

seen as supportive, we see these concepts as

fundamental design principles for the development

of BM. Especially, modularity ensures

mix-and-match of BM elements in different

variations based on the provided granularity of the

system (see also Lusch and Vargo, 2015; Storbacka

et al., 2012).

Business Model Framework Characteristics:

Following Morris et al.’s proposal a business model

framework should be designed to be simple, logical,

measurable, comprehensive, and operationally

meaningful.

5 SERVICE-ORIENTED

BUSINESS MODEL

FRAMEWORK

The results of recently performed literature reviews

and applications in practice (exemplified in section 3

and 6) show, that existing BM frameworks are not

sufficiently addressing the specific needs of

digital-oriented business modeling (see Section 4).

Therefore, we started the development of a solution

proposal based on the deducted requirements

applying S-D logic. Latter provides a feasible

understanding of economic exchange in a digitally

connected physical world. With its transcending,

service-centric and network-oriented perspective it

deems to provide a solid basis for developing new

value creation activities in value networks. Further,

it enabled us to easily transfer well-proven

paradigms of ISR to improve business modeling in

DTEs. The following sections will provide a brief

overview of SoBM framework highlighting some

S-D logic specifics and presenting it as a

comprehensive and flexible BM framework.

5.1 Business Modeling from a Service

Dominant Logic Perspective –

Definition and Concept Map

We identified BM design as a key unit of analysis

for the improvement and shaping of value

co-creation. Taking a S-D logic perspective,

business modeling is part of a structured institutional

work in micro and meso level service ecosystems.

Successful business modeling is leading to

institutionalized market solutions for new or existing

problems of actors. Thus, business modeling should

be understood as co-creational activity undertaken

by actors to increase resource density and to

optimize viability of a service ecosystem (Vargo and

Lusch, 2016). Applying S-D logic we define:

A business model describes a meso level service

ecosystem from a focal actor’s perspective to

explain the value logic of an organization in terms of

how it creates and captures value (i.e. the mutual

value co-creation). It can be represented by an

interrelated set of elements that address service

ecosystem’s actors, value propositions, services,

resources (e.g., technology, knowledge, institutional

logics), and value dimensions (i.e. value-in-context).

Based on this definition we propose a

meta-model for business models grounded in

S-D logic as depicted in the following concept map

(see Figure 2):

Figure 2: Meta-model Service-oriented Business Model

Concept Map–own diagram.

The relational model depicts the main elements and

relations within the BM concept addressing them

from a S-D logic perspective (see Section 3.2). In

line with commonly accepted BM concepts SoBM

takes a system-level, holistic approach from a focal

actor’s perspective to describe and develop value

creation and capturing activities of a firm (Zott et al.,

2011). Within our framework, actor’s roles in

business modeling as well as in service-for-service

exchange are multiple. They change depending on

the nature of service exchange and the type of

resource integration achieved, e.g., actors can take

role as ideators, designer and intermediary (Lusch

and Nambisan 2015). Thus, the term “actor” is used

as a generic construct for all resource integrators.

The “focal actor” takes the role of initiating and

coordinating business modeling. He aims to improve

resource density for both intra-actor and inter-actor

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(e.g., network partners, stakeholder, customers)

through (co-)development of the BM. Nevertheless,

actor’s roles are oscillating between service provider

and beneficiaries depending on position in service-

for-service exchange. (Storbacka et al., 2012).

Following an actor-to-actor perspective the network-

oriented approach extends the boundaries of a BM

and business modeling to the (co-)design of value

co-creation in service ecosystems. Hereby, the

analysis of the interrelated BM elements of all actors

strives for a holistic understanding of service

ecosystem’s viability.

SoBM is a service-centric and value-in-context

oriented BM approach. Services are reciprocally

exchanged by actors to co-create value through

integration of operand and operant resources (e.g.,

digital technology). As value creation is a reciprocal

service-for-service exchange value-in-context is

always perceived by the particular beneficiary. In

general, this value can be measured in different ways

by the recipients and concern multiple dimensions

(e.g., financial, social). Within the SoBM concept,

actors encapsulate operand and operant resources

through service and provide potential benefit for

themselves and/or others.

Thus, actor’s service provision is equipped with

value proposition attributes resulting from resource

integration activities. It is important to note, that

resources in our SoBM concept–in line with

S-D logic–offer value through application in service

and not through specific technology per se. This

reflects the role of LMA’s “service layer” as central

value provisioning element (see Section 3.1). This

service-centric conceptualization enables a BM

development focused on the identification of “what”

beneficiaries (i.e., all type of actors) can do with

digital technology and how digital technology

changes beneficiaries’ capabilities to co-create value

(Vargo et al., 2008).

Value propositions are defined as invitations to

participate in value co-creation (Lusch and Vargo,

2014) and seen as a “dynamic and adjusting

mechanism for negotiating how resources are

shared within a service ecosystem” (Frow et al.,

2014, p. 340). Value creation is coordinated through

actor generated shared institutions initiated by the

acceptance of matching value propositions. The

development of value propositions is part of

business modeling (i.e. institutional work). As the

service ecosystem is dynamic in creating and

re-creating needs this development is seen as a

continuous process (Vargo and Lusch, 2016).

5.2 Procedure Model

The SoBM development approach is structured as

follows (see Figure 3). It is based on the conviction

that BMs in DTEs in particular build on

improvements of resource density through resource

dematerialization. Therefore, an analysis of the

service ecosystem and (digital) technology-based

opportunities is the starting point of the SoBM

procedure model.

Figure 3: Procedure Model of the Service-oriented

Business Model Framework–own diagram.

Within the ecosystem analysis distinct ecosystem

elements and their interdependences are elaborated.

Essential result of this step is a layered ecosystem

model (see Figure 4) and a (digital) technology

analysis (based on the LMA). The ecosystem

analysis depicts on the first layer the relevant

operand resources (e.g., physical objects, machines,

rules, norms, other institutions), on the second layer

the distinct operant resources (e.g., human or non-

human capabilities), on the third an abstract

description of the exchanged services and on the

fourth layer an actor model. Central subject of

investigation is the ecosystem’s service portfolio in

the service layer. Services are identified by

combining lower level layers’ elements (e.g., based

on LMA of digital technology). A service represents

the application of operant resources combining

physical objects and/or data (i.e. operand resources)

and/or other operant resources. The integration of

the specific digital technology service portfolio,

derived from an in-depth LMA analysis of digital

technology involved, provides an important basis for

further BM generation.

To keep conformance with the elaborate DTE

requirements (see Section 4) the definition of service

within the analysis follows a distinct set of SOA

design principles: standardization, modularity, loose

coupling, abstraction, reusability, discoverability and

composability (Erl, 2007).

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Figure 4: Ecosystem analysis–own diagram.

Based on the ecosystem analysis a company’s BM

assessment is iteratively conducted to identify

possible market positions and value propositions

(i.e., focal actor’s ability to apply useful knowledge

in service exchange). The company BM assessment

is grounded on an existing structured BM (SoBM)

and the ecosystem analysis. A “value perception

analysis” (VPA) helps in identifying

value-in-context as a starting point for determining

service-based value propositions. As

value-in-context exists on a continuum of actor’s

needs and accessible resources (e.g., capability to

acquire external value propositions) the VPA

acknowledges actor’s needs and its operant and

operand resource base. The method builds on these

ecosystem elements to analyze concrete customer’s

value-in-context. Hereby, service value propositions

represent value co-creation options. These

encapsulate customer’s required external operant

resource access through acquisition of partner’s

services and are building blocks for focal value

propositions.

In the next stage, the derived portfolio of the

BMs is assessed by its probabilities and profits. A

preliminary assessment based on first assumptions

regarding the categories required investments (time,

technology, human resources) and the innovatory

potential as well as the expected profits of the BM is

conducted. Here, BMs with positive profit

estimations, high innovatory potential and low

investments dominate those with negative or lower

profits, low innovatory potential and high

investments (like Scheer, 2016).

Afterwards, high-ranked BMs undergo the

SoBM development cycle (see Figure 6) involving

identified relevant market partners (i.e., value

co-creators like customers, suppliers). In specific

this process step highlights the actual

(co-)development of the SoBM by discussing and

evolving matching reciprocal value propositions and

shared institutions. One key outcome of this process

is the BM-specific service repository related to the

focal firm’s service system in conjunction with

external customer and partner services. A second

important outcome is the relevant information to

perform a “financial” cost-benefit analysis (e.g.,

Brent, 2007). This is grounded on SoBM’s

cost-benefit architecture which can be derived from

the service repository. Herein, the specific

service-based cost and revenue models are captured.

This supports a cost-benefit oriented SoBM scenario

analysis based on service out- or in-sourcing as well

as on service-specific digitization degrees. The

on-demand availability of all information

substantiates BM decision making within the BM

assessment stage significantly.

Having an elaborated SoBM based on service

repository and a set of identified business partners, a

second BM assessment stage can be conducted.

Herein, a proof of concept helps to assess the

business model’s prospects. With a positive

decision, the BM can be transferred into the

operational stage. Taking a new or redesigned

business into operations is a starting point for a

continuous BM improvement process.

5.3 Development Cycle and the

Service-Oriented Business Model

Core of our BM framework is the SoBM. Essential

element is a three-layered modular architecture. As

pictured in figure 5 it is formed by a set of

interconnected business, service and resource layers

for all relevant actors contributing to the execution

of the meso level service ecosystem covered by the

BM description. It takes shape within the SoBM

development stages being completed and optimized

through an iterative co-development process.

First the layered BMs for one or more

beneficiaries (i.e. customers) are defined, second the

focal firm and third the value network partners (i.e.

suppliers) are added.

Beneficiary’s layered BM development (see

Figure 5-1) focuses on beneficiary’ value-in-context

derived through the VPA (see section 5.2). Thus, the

relevant information can be depicted and further be

analyzed from earlier process results. Hereby, the

layered BM already covers all relevant services and

resources integrated in service-for-service exchange.

Elaborated on specific layers they support the

development of the meso level service ecosystem

encapsulating relevant information of lower layers

(e.g., resources) on higher level layers (e.g.,

services). This reduces complexity on higher levels

and enables a mix-and-match of internal and

external layer elements. This builds the basis for the

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further development within the focal (see Figure 5-2

a,b,c,d) and network business model layers (see

Figure 5-3).

Figure 5: Service-oriented Business Model–own diagram.

Focal firm’s layered BM is the core element of the

SoBM. On the business layer, it defines the focal

firm’s value propositions as an answer to the

identified beneficiaries’ value-in-context covering

the service offering. Furthermore, it includes the

corresponding micro level service ecosystems

needed to provide the value proposition. The sum of

micro level service ecosystems is building focal

actors value propositions including the service-for-

service exchanges to execute the specific business

model. Means and methods (i.e. value co-creation

through resource integration) required to form the

micro level service ecosystem are detailed on the

service and resource layer.

The service layer is described by a focal service

repository. This describes and organizes all relevant

internal and external service definitions necessary to

execute the formulated micro level service

ecosystems within the focal business layer. The

development of the repository follows the SOA

design principles which have been proven to be

well-suited to service-oriented business design and

management. As an architectural style, SOA

captures a distinct approach to the analysis, design,

and implementation of service-oriented

environments. Better business-IT alignment,

increased service reusability, significant agility

improvement, and adaptive information utilization in

changing and complex ecosystems are benefits

resulting from SOA (Arsanjani, A. 2004; Choi et al.,

2013; Luthria and Rabhi, 2015). Furthermore,

SOA’s design principles of loose coupling and

standardization foster digital technology capabilities:

reusability, distributiveness and interoperability

(Choi et al., 2013; Luthria et al., 2015).

Service is understood as a conjunction of

economic, functional, emotional, social or technical

activities provided by actors to mutual co-create

value related to micro level service ecosystem. It is

transcending the focal sphere by addressing the

resource integration activities of the involved actors

(e.g. focal, beneficiaries, network partners). Service

is categorized as business process services–high-

level abstract services–coordination services, and

atomic business services.

Service definition in the SoBM implies the

inclusion of distinct service descriptions. These

explain “what” the service provides, but not “how”

in detail it is provided. Thus, they point out, inter

alia, which beneficiary’s expectation, needs, and

capabilities are meet by acquiring the specific

service implying quality of service parameters (i.e.,

service value proposition). By applying financial

values to the service repository

–

including internal as

well as external service costs

–

the financial structure

of value creation and capturing is caught in a

structured and transparent way.

Further, service interfaces point out the

preconditions that have to be fulfilled to obtain the

service. Additionally, service definition contains

indirect relations to organization’s offers through

micro level service ecosystems and direct relations

to encapsulated operand and operant resources

(Mele and Polese, 2011). Latter ones are described

on the resource layer. In coherence with S-D logic,

actors act upon operand resources “to obtain support

(i.e., they enable or facilitate)”. Physical operand

resources are often natural resources e.g., machines,

digital technology infrastructure, actors, norms,

rules. Operant resources “act on other resources to

produce effects—that is, they act or operate on other

things rather than being operated on” (Lusch and

Nambisan, 2015, p. 159). These are enabler and

initiator resources having high impact especially on

business success in DTEs. Operant resources are

often intangible and dynamic like human skills,

IT-applications, business relations, and (digitalized)

information. Business modeling in SoBM puts

emphasis on digital technology as an operant

resource thus it unleashes generativity and generates

new opportunities for resource integration, service

exchange, or innovation in the service systems

(Lusch and Nambisan, 2015).

On network partners’ layered BMs focal firm’s

related value propositions, services and resources are

represented. These are derived through identification

of relevant network partners’ skills, capabilities and

contributions based on focal actor’s needs. Partners’

BM elements are directly mapped to relevant

elements on the focal firm’s business and services

layers. By this, all necessary activities for fulfilling

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369

the value propositions are bundled within the

interrelated service repository.

6 DISCUSSION

As part of a design science research project on

business modeling in DTEs, this contribution is one

step towards finding an answer to the question of

how to facilitate the BM concept to guide managers

in DTEs. Two case studies led to the results

presented here, while ensuring that the artifact

closely links theory and practice.

Following a problem-oriented approach, the first

case study of a provider of electric vehicle services

was based on an enhancement of the Business

Model Canvas (BMC) (Osterwalder and Pigneur,

2010). It aimed to identify the relation between

digitization and digitalization within the eMobility

market setting. The case focused on an elaboration

of general services and resources (physical,

personnel and digital) relations as well as the related

value proposition evolution over time. The study

was designed to test the idea of digital technology

enhanced service identification and the derivation of

business services fulfilling “unknown” customer

needs in business model development.

Within the demonstration and the following

evaluation, key results were the identification of

digital technology’s service-based value provision

through an in-depth LMA assessment. As shown in

Pfeiffer and Jarke (2016) different types of business

models in eMobility are accompanied with digital

technology involvement and value capture options

depend on the realization of a flexible, loosely

coupled digital technology architecture. Further,

practice has shown that BM framework–especially

in fast changing DTEs–has to support continuous

business model development. Finally, the idea of

utilizing the SOA concept for enhancing business

modeling was identified. This not least because the

specific case of an encapsulation of resources

through a service layer helped the participants

engage in open thinking and derive service-based

new value-in-context options.

Based on an updated design concept, the second

case study was conducted with a provider of smart

home technology and platform services. The new

approach covered a procedure model, the layered

and networked BM architecture. It utilized the SOA

concept as a significant methodological

improvement. The ecosystem and technology

analysis firstly enabled discussions and an efficient

solution finding process based on a shared

worldview. Secondly, participants could identify

new business-oriented technology solutions as well

as position the focal firm in a complex ecosystem

context. Thereby, the formulation of value

propositions was enhanced and simplified. The case

study demonstrated the applicability and efficacy of

the SoBM as a novel BM framework for DTEs,

while also providing a service-based cost and

value-in-context related revenue calculation. Further

the collaboration-based IT tool enabled–in

accordance with the participants’ specialization–a

simultaneous editing and visualization of the BM

development process.

The present paper complements these empirical

findings from a theoretical perspective. It shows that

the SoBM framework covers all relevant BM

dimensions to be classified as a BM concept (Zott et

al., 2011). By taking beneficiary’s needs

(value-in-context), focal service-based value

propositions and resource base as well as network

partnership contributions into account it additionally

encompasses a network perspective on value

creation and capturing.

The conceptual modeling approach can be

utilized to describe existing and future business

opportunities. It is coherent because value creation

and capturing can be described on a holistic basis for

the whole value network connected over all SoBM

layers and being orchestrated within a

comprehensive service repository. In addition,

through the connection of value propositions and

service repository elements, value creation and

capturing within the BM is underpinned with

clarifying content. Hereby, it covers a wide range of

business aspects, connects them relationally and

enables flexibility and reusability in business

modeling. The framework is dynamic and flexible

due to its modular and granular SOA-based

architecture, relevant changes (i.e. new value needs,

regulatory demands, shifts in partnerships) in BM

architecture can be identified, analyzed and

performed with minimal effort.

Besides this, existing internal or a partner’s

public service repositories can be used as a starting

point for new business development based on

existing BMs and business partnerships (Löhe and

Legner, 2009). Moreover, SoBM enables the

execution of BMs by providing an elaborated

“ready-to-use” service repository with clear and

measurable preconditions.

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7 CONCLUSIONS

Digitalization is a sociotechnical phenomenon that

has changed the way we interact with our

environment within the last decades. This process is

leading to a smart, data-driven, and connected

economy promising huge benefits for companies

that leverage digital technology potential value

(Hanna, 2015).

The SoBM framework presents a business

modeling approach to manage the transition from

(digital) technology’s potential value into market

outcomes. Overall, it can be classified as fulfilling

the proposed needs of BM representation in DTEs.

Specially, it represents a modular and granular

environment enabling loosely coupled and flexible

networks of resource integrating actors.

For theory, SoBM applies a well-proven ISR

concept of SOA in the field of business modeling.

Thereby, it adds proven paradigms to BM research

complying and positively reinforcing key

characteristics of the LMA to unveil digital

technology’s generativity in BMs. The results are

both theoretically founded and field-tested.

Particularly important, this concept can add to the

research on the digital nature’s influence on BMs

and business modeling in a digitally transforming

world. Finally, the approach adds to S-D logic

theory through development of a meta-model for

business modeling and operationalizes S-D logic in

two business modeling case studies.

For practitioners, the artifact serves as a tool for

describing, analyzing and implementing BMs

delivering a shared worldview for all participants.

As a framework, it not only provides a

representation of BMs but even more so presents a

procedure and development model. Envisioning the

ecosystem and technology value service perspective

it provides a clear view on collaborative value

creation logic. Furthermore, discussions within

possible partnerships become easier–firstly, because

a shared worldview can be elaborated; secondly

because distinct service descriptions for all relevant

aspects are presented; and thirdly, because these

descriptions are modular and granular. Thereby,

there is no need to give “the whole picture” in first

discussions with potential partners or competitors.

The generalizability of the findings is limited by

the fact that they are initially only based on case

study research in the fields of eMobility and smart

home. These are characterized by a specific market

situation. Therefore, the capability to draw

conclusions on business modeling in other

application fields is limited. Extending the scope of

assessed information on applicability, e.g., through

expert interviews, and incorporating a higher

number of cases will increase generalizability.

Additionally, an implementation based on and in

addition to existing company’s SOA would

underline the versatile application of the SoBM

framework.

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