Business Model Innovation - Drivers and Outcomes
A thesis proposal
THI PHUONG VAN
Supervisors: Christina Öberg, Johan Kask, Nina Hasche and Per Carlborg
OCTOBER 31, 2019 ÖREBRO UNIVERSITY
School of Business Business Administration Department
701 82 Örebro
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Table of Contents 1. Introduction ....................................................................................................................... 2
Research purpose and questions ......................................................................................................... 4 The expected contribution .................................................................................................................. 4
2. Theoretical Background .................................................................................................... 6 2.1 Business model ............................................................................................................................. 6 2.2 Business model innovation ........................................................................................................... 8
2.2.1 BMI conceptualization .......................................................................................................................... 8 2.2.2 The importance of BMI ...................................................................................................................... 10
2.3 Business model innovation and firm performance ..................................................................... 11 2.4 AI & Machine learning - a new technique in digital revolution ................................................ 13
3. Methodology .................................................................................................................... 14 3.1 Research context ......................................................................................................................... 14 3.2 Research method ........................................................................................................................ 14
4. Working papers ................................................................................................................ 16 Paper 1: Business Model Innovation: A Systematic Literature Review and Guide for Future Research ........................................................................................................................................... 16 Paper 2: Business Models, Ecosystem and Adaptive Fit: The Case of Electric Utilities ................. 16 Paper 3: BMI and firm performance in electric utilities: a new scale of measurement ................... 17 Paper 4: Leveraging AI/Machine Learning techniques to predict changes in environment to navigate directions of Business Model Innovation .......................................................................... 17
5. Working plan ................................................................................................................... 18 References ............................................................................................................................... 19
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1. Introduction The term “business model innovation” (BMI) has attracted considerable attention in both
practice and recent academic as a new growing subfield of the business model. BMI is defined
as "the action of modifying the firm’s existing activity system and renewing its core business
logic, to enact and exploit opportunities" (Cucculelli and Bettinelli, 2015, p.329). While
business models are typically concerned with firm-level value creation and capture, business
model innovation raises the additional complex and challenging questions about the novelty in
customer value proposition as well as the reconfiguration of firm’s logic and structure (Spieth
et al., 2014). Since business model has been recognised widely as a powerful and essential tool
to appropriate value from technological innovation, now it is potentially the object of
innovation themselves to allow firms getting significant advantages in the market competition
(Chesbrough, 2010, Demil and Lecocq, 2010). Netflix is a well-known example of a company
adapt continuously business model innovation (Mudaly, 2017). Moving from convenient
DVD-hiring company to on-demand streaming service and recently original television show
content provider, Netflix shows the flexibility in their business model resulting in financial
success and huge competitive advantages compared to their competitors such as Blockbuster
and Amazon.
Business model innovation research has experienced continuous development. The early
publications on BMI mostly are conceptual or case-based studies that focus on the definition,
the difference or relation between BMI and similar concepts and the process of BMI ((Johnson
et al., 2008, Chesbrough, 2007, Teece, 2010, Sosna et al., 2010)). Following research on BMI
highlights the importance of causal analysis of antecedences and effects of BMI ((Guo et al.,
2016, Visnjic et al., 2016, Bouncken and Fredrich, 2016, Kim and Min, 2015)) as well as
focuses on sustainable BMI that help firms to achieve their sustainability ambitions such that
to create an innovative way of delivering value while still having positive impacts and reducing
negative impacts for the society and the environment (Bocken et al., 2019, Frishammar and
Parida, 2019, Geissdoerfer et al., 2018).
Despite a large number of emerging research on BMI, it is still young, abstruse and
incomprehensible (Bocken et al., 2014, Bashir and Verma, 2016, DaSilva and Trkman, 2014).
BMI lacks theoretical and empirical underpinning, leaving us fundamental unanswered
questions about antecedent conditions and outcomes of BMI which are non-trivial, complex
and have not been well-understood by the literature (Zott and Amit, 2007, Foss and Saebi,
2017, George and Bock, 2011).
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There have been researches focusing on the identification and validation of BMI drivers, with
a particular interest in technology innovation (Björkdahl, 2009, Gambardella and McGahan,
2010, Shomali and Pinkse, 2016, Teece, 2018, Wu et al., 2010), sustainability (Yip and
Bocken, 2018, Yang et al., 2017, Ciulli and Kolk, 2019), external stakeholders (Miller et al.,
2014), competitive environment (Saebi et al., 2017) or internationalization (Teece, 2018).
Although these studies have enriched the discipline's knowledge of BMI, this line of research
is still at an infant stage, and such work is usually post-analysing and inductive for a particular
case study rather than predictive and theoretically general (Foss and Saebi 2017).
The outcomes of BMI are investigated in previous studies that primarily focus on firm
performance (Giesen et al., 2007b, Huang et al., 2013, Kim and Min, 2015, Visnjic et al., 2016,
Bouncken and Fredrich, 2016), value creation (Sorescu et al., 2011), firm sustainability
(Pedersen et al., 2018) and firm survival (Velu, 2015). Due to the high availability of public
economic and financial data of firms, firm performance, especially financial performance
(Giesen et al., 2007b, Huang et al., 2013, Kim and Min, 2015, Visnjic et al., 2016) has been
prioritized as the primary business model innovation outcomes to measure. Even so, there are
still limited well-defined study on the relationship between BMI and firm performance (Spieth
et al., 2014, Schneider and Spieth, 2013, Foss and Saebi, 2017) due to the high complexity in
measuring BMI and different dimensions of performance during BMI process (Foss and Saebi,
2017). Furthermore, most recent studies have focused on BMI and its effect on firm
performance in the manufacturing sector because of the ease of database access. This suggests
further researches to develop a comprehensively validated measurement scale in BMI to
understand the link between BMI and firm performance in various industry sectors.
To systematically address the complex questions about BMI’s drivers and outcomes, or in other
words, to understand comprehensively why and when a business model needs to innovate,
greater attention must be paid to the embedded environment within which the BM is enacted
as a business model in different environments may give completely different outcomes (Zott
and Amit, 2007, Giesen et al., 2007a). The success or failure of a business model must be
related to how well it fits in, adapt and contributes to the environment, even more important
when the environment is disruptive and about to undergo change. An existing well-established
business model running smoothly in an environment may become unfit with the new one.
Therefore, by early anticipating potential changes in the environment where BM operates,
firms could potentially identify when and how to innovate their BM to adapt and position it
better with the new environment.
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Research purpose and questions
The overarching aim of the thesis is to advance the conceptualisation and theory of BMI by
investigating and analysing its main drivers and outcomes as well as to propose and develop a
measurement scale for BMI.
More specifically, this thesis aims to gain a deeper insight into the concept of business model
innovation by reviewing comprehensively the literature of BMI, studying the main drivers and
outcomes of BMI and investigating how and when firms, if possible, need to innovate business
model through predicting changes in its environment at the industry level. Moreover, this thesis
aims to examine the link between business model innovation and firm performance in which a
new scale for measuring business model innovation as well as for measuring firm performance
during the business model innovation process is developed.
The purpose of this thesis is anatomised into the following research questions:
1. What are the main drivers and outcomes of business model innovation?
2. How and to what extent, if even possible, to predict environment changes in order to
draw conclusions and guide on what future business models should have and when
firms should innovate their business models?
3. How to measure comprehensively and thoroughly the business model innovation
process and the effects of business model innovation on firm performance?
The expected contribution This thesis is expected to contribute to the development of Business Model Innovation research
and open up new opportunities for future research directions. Considering the contributions
from my papers to the overall purpose and the research questions of this thesis, Table 1 will
illustrate the expected contributions of the papers. The first paper is a literature review that
provides a systematic overview of the current state of the art of BMI, resolves definitional
ambiguities and outlines the scope of BMI research. More specifically, this review paper
focuses on systematising the drivers and potential outcomes of BMI from existing studies. The
second paper is an empirical study that explores how changes in the environment (industry
level) including proactive and reactive factors such as climate change, technology innovation,
change in customer behaviour and political context can potentially enable changes in firm's
business model. The third paper is an empirical study that investigates the effect of BMI on
firm performance by using data from electric utilities. This paper contributes to BMI literature
by developing a new scale for measuring business model innovation as well as measuring firm
performance during the business model innovation process. The paper 4 is also an empirical
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study that proposes a novel AI/Machine learning technique to predict potential changes in the
environments in electric utilities industry as a case study so that firms are able to understand
thoroughly how and when they need to innovate their business model to adapt to changes in
their embedded environment.
Paper Main contribution The link to RQ
Paper 1 Proposing a systematic overview of the current state of the
art of BMI, resolves definitional ambiguities and outlines
the scope of BMI research.
Systematising the drivers and potential outcomes of BMI
from existing studies.
RQ 1
Paper 2 Studying and analysing various factors that enable BMI.
Investigating how and when firms need to innovate
business model by anticipating changes in the embedded
environment within which the BM is presented (industry
level).
RQ 1, 2
Paper 3 Examining explicitly the effects of BMI on firm
performance.
Proposing and developing a new scale for measuring BMI
and firm performance during BMI process.
RQ 3
Paper 4 Investigating main drivers of BMI.
Offering a novel AI/machine learning approach to predict
more in-depth the impending changes/disruptions in the
electricity industry.
The accurate prediction of changes in the environment
(industry level), for example customer behaviour as a main
driver, will help to guide firm managers to identify early
sights of industry disruption, find new ways to leverage
these advances to transform their business model.
RQ 1, 2
Table 1: Expected contributions of papers and the link to research questions
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2. Theoretical Background
2.1 Business model
The term “business model” has been used widely in management practices and studied
extensively in academic literature; however, it is still lack of a standardised definition (Zott et
al., 2011, Teece, 2010).
Table 1 below presents a selection of fundamental definitions about a business model that have
been advanced in this research stream. In general, most of these definitions suggest that a
business model articulates how a firm creates and delivers value for their customers and how
it appropriates this value.
Author Definition
Chesbrough and
Rosenbloom (2002)
A business model represents “The heuristic logic that connects technical
potential with the realization of economic value” (p.529)
Magretta (2002) Business models are “stories that explain how enterprises work. A good
business model answers Peter Drucker’s age-old questions: Who is the
customer? And what does the customer value? It also answers the
fundamental questions every manager must ask: How do we make money in
this business? What is the underlying economic logic that explains how we
can deliver value to customers at an appropriate cost?” (p. 4)
Morris, Schindehutte, and
Allen (2005)
A business model is defined as a “concise representation of how an
interrelated set of decision variables in the areas of venture strategy,
architecture, and economics are addressed to create sustainable competitive
advantage in defined markets” (p. 727)
Johnson, Christensen, and
Kagerman (2008)
Business models “consist of four interlocking elements, that, taken together,
create and deliver value” (p. 52)
Zott and Amit (2010) A business model is “a system of interdependent activities that transcends
the focal firm and spans its boundaries. The activity system enables the firm,
in concert with its partners, to create value and also to appropriate a share of
that value” (p. 216)
Teece (2010) “A business model articulates the logic and provides data and other evidence
that demonstrates how a business creates and delivers value to customers. It
also outlines the architecture of revenues, costs, and profits associated with
the business enterprise delivering that value.” (p. 173)
Osterwalder and Pigneur
(2010)
“A business model describes the rationale of how an organization creates,
delivers, and captures value.” (p.14)
Table 1: Selected definitions of a business model
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Business models have been seen as essential features of market economies where there exists
consumer choice, transaction costs, competition and heterogeneity amongst producers and
targets (Teece, 2010). Business models provide an analytical and systematic tool for firms to
acknowledge and address challenges imposed by new technology, help them to identify the
key capabilities they need to acquire as well as the necessary changes to current activities in
order to achieve their desired economic value (Osterwalder, 2004). In that sense, business
model plays a critical role in any firm's existing and development in its environment.
In this thesis, business model is defined such that it is characterized by four interconnected
components: (1) customer value proposition, (2) profit formula, (3) key resources and (4) key
processes (Johnson et al. 2008). On the one hand, four elements are interdependent from each
other in consistent and complementary ways and when combined together, they allow business
models to create and deliver value to firms and customers (Figure 1). On the other hand, each
of these components includes varying sub-elements inside that might have different importance
across industries.
Customer value proposition focuses on the target customers and how to create value for them
by understanding the multi-dimensional complex problems of customers and finding a solution
to fulfil their needs which is supposed to be better and lower in price compared to the existing
alternative solutions. Profit formula is the financial foundation of the business model that
defines the ways a firm makes profits and creates value for itself through the process in which
it provides value to customers. Key resources are assets and capacities such as products,
technology, people, channels, partnerships and brand required to deliver the value proposition
to customers, focusing on the key components that create value and the way how they interact
with each other. Key processes component accommodates how the business is operated and
managed under repetitive tasks and processes which can be repeatedly leveraged to increase
the scale firms deliver value to customers. Four important elements: customer value
proposition, profit formula, key resources, key processes form a foundation of any business.
While the first two components define value for the customer and the firm respectively, the
latter, which consist of path-dependent routines and experiences that form the codes and
mindsets to instruct the practice and values of the business model, help to describe how the
value will be delivered to the customer and the firm.
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Figure 1: Components of a business model
2.2 Business model innovation
While the concept of business model is still being developed in the literature, business model
innovation has recently attracted significant attention as a new growing subfield of the business
model. As business models are typically concerned with firm-level value creation and capture,
business model innovation raises the additional complex and challenging questions about the
novelty in customer value proposition as well as the reconfiguration of firms’ logic and
structure which have not been well understood and need to be studied thoroughly both in
breadth and depth. Business model has been recognised widely as a powerful and essential tool
to appropriate value from technological innovation, now it is potentially the object of
innovation themselves with an aim to allow firms getting significant advantages in the market
competition (Chesbrough, 2010, Demil and Lecocq, 2010).
2.2.1 BMI conceptualization
BMI has been examined by the literature under different perspectives. From resource-based
view perspective, BMI is defined as the discovery of a fundamentally different business model
in an existing business” (Markides, 2006, p.20) or as "a change in the value creation, value
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appropriation, or value delivery function of a firm that results in a significant change to the
firm’s value proposition"(Sorescu, 2017, p.629). This perspective emphasis on the effective
exploitation of resource-capability combinations that enhance competitive advantage and
ultimate profitability (Bouncken and Fredrich, 2016, Huang et al., 2012, Visnjic et al., 2016).
Resources or organisational and managerial capabilities in combination within a business
model may become valuable even if they are initially not when standing by itself (Miller, 2003,
Newbert, 2008).
From strategic entrepreneurship perspective, BMI is defined as "the action of modifying the
firm’s existing activity system and renewing its core business logic, to enact and exploit
opportunities" (Cucculelli and Bettinelli, 2015, p.329). This perspective emphasis on the
importance of entrepreneurial opportunity-seeking and strategic advantage-seeking from a
firm’s particular perspective (Ketchen Jr et al., 2007, Ireland and Webb, 2009). Following that,
the uncertainty within firms’ environments could potentially become sources of opportunities
on which firms need to explore and exploit efficiently (Hitt et al., 2001). Using strategic
entrepreneurship perspective, research on BMI urges the needs from firms exposed to
uncertainty to respond and react to changing sources of value creation by reconfiguring their
conventional and established ways of doing business (Zott and Amit, 2010, Kim and Min,
2015, Cucculelli and Bettinelli, 2015).
I think both these perspectives are suitable theoretical foundations on BMI research although
each perspective looks at the phenomenon from a different angle. The resource-based view
focuses on "how firms employ extant resources and competencies to gain competitive
advantage and ultimate profitability" while the strategic entrepreneurship perspective addresses
the question of "how firms explore and exploit potential opportunities in its environment"
(Spieth et al., 2014). Both perspectives may not be conflict and can be complementary in BMI
research.
This thesis will adopt strategic entrepreneurship perspective, in which BMI is interpreted as
the process of improvements or changes in innovative ways in at least one element of the
business model to enact and exploit opportunities. The reason for this is that existing well-
established business model running smoothly at the moment may become unfit with the
dynamic changing of its environments in the future. Therefore, firms need to early identify and
explore potential opportunities in its environment along with emerging challenges in order to
position it better and more flexible with the future changes as well as enhance the capability to
anticipate forthcoming developments.
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2.2.2 The importance of BMI
BMI has been considered as an essential factor of success (Chesbrough, 2010, Sosna et al.,
2010, Teece, 2010) and a promising approach for firms to respond and adapt to changing
sources of value creation in the time of uncertainty (Pohle and Chapman, 2006). Research from
the Economist Intelligence Unit (2005) has shown that firms preferred BMI over product and
service innovation in order to gain competitive advantages. The outcomes of BMI is explored
in previous studies that primarily focus on firm performance (Giesen et al., 2007b, Huang et
al., 2013, Kim and Min, 2015, Visnjic et al., 2016, Bouncken and Fredrich, 2016, Schneider
and Spieth, 2013, Foss and Saebi, 2017), value creation (Sorescu et al., 2011), firm
sustainability (Pedersen et al., 2018) and firm survival (Velu, 2015). Velu (2015) conducted a
study about the effect of BMI’s degree on firm survival and the author argued that there is a
significant U-shaped relationship between the degree of BMI and firm survival. More
specifically, the survival time of firms adopting both incremental and radical BMIs is likely
longer than those adopting moderate BMIs. Furthermore, when the degree of BMI increase,
partnering with third-party firms with complementary assets will reduce the survival of new
firms. This gives a suggestion that firms should try to avoid over-partnering to leverage
complementary assets in the case of radical BMI. Pedersen et al. (2018) conducted a study to
explore the link between business model innovation, corporate sustainability, and the
underlying organisational values within the fashion industry. They found that firms with high
levels of BMI are more likely to address corporate sustainability.
Understanding the importance of BMI with firms in today’s fast-paced business environment
and the rapid market changes, many researchers have paid attention to exploring how firms can
innovate business model efficiently as well as identifying which are the main drivers of BMI.
Most authors suggested that BMI often takes shape through a process of experimentation. In
more details, firms could innovate their business model through business model
experimentation by creating a template and examining alternative business models
methodically and routinely (Sinfield et al., 2012, Sosna et al., 2010). BMI through
experimentation, evaluation and adaptation in a trial-and-error learning approach at different
levels (individual, group, organizational) of the firm is an essential organizational renewal
mechanism (Sosna et al., 2010, Desyllas and Sako, 2013). Moreover, BMI could be either the
adaptation of its existing (core) business model or the development and introduction of a new
business model adjacent to its core business (Osiyevskyy and Dewald, 2015, Schneider and
Spieth, 2013). In both cases, BMI requires firms to adapt, renew, acquire, or build up new
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resources and competences and (re)combine these in novel ways (Zott and Amit, 2007, Foss
and Saebi, 2017, George and Bock, 2011).
Regarding drivers of BMI, there are researches focus on the identification and validation of
BMI drivers, with a special interest in technology innovation (Björkdahl, 2009, Gambardella
and McGahan, 2010, Shomali and Pinkse, 2016, Teece, 2018, Wu et al., 2010), sustainability
(Yip and Bocken, 2018, Yang et al., 2017, Ciulli and Kolk, 2019), external stakeholders (Miller
et al., 2014), competitive environment (Saebi et al., 2017) or internationalization (Teece, 2018).
Although these studies have enriched the discipline's knowledge of BMI, this line of research
is still at an infant stage, and such work is usually post-analysing and inductive for a particular
case study rather than predictive and theoretically general (Foss and Saebi 2017). Hence,
exploring drivers of BMI is still one of the vital directions for the research on BMI.
2.3 Business model innovation and firm performance Many researchers have recognised that BMI is related positively to firm performance (Giesen
et al., 2007b, Huang et al., 2013, Kim and Min, 2015, Visnjic et al., 2016, Bouncken and
Fredrich, 2016, Schneider and Spieth, 2013, Foss and Saebi, 2017), however, there are still
limited number of articles that study explicitly on this relationship.
In order to explore the relationship between BMI on firm performance, Denicolai et al. (2014)
argued that the combinations of internal and external knowledge in ways that create and capture
value are the main feature of BMI. They examined the effects of these combinations and the
interplay on sale growth by collecting data from 310 companies in the UK, Germany, France
and Italy. The result showed that firms with low levels of internal knowledge benefit most from
an ‘optimal’ investment in externally generated knowledge, but the influence on sales growth
is very sensitive to the degree of external knowledge acquired. By contrast, knowledge-
intensive firms are relatively freer in defining their knowledge sourcing strategy. Only focusing
on creating and capturing value of BMI is the limitation of this study. The emphasis should be
extended and linked to other components of BMI such as value delivery, revenue models.
Guo et al. (2017) introduced a new insight into the value of BMI. Their study found that BMI
mediates the effect of opportunity recognition on firm performance. This indicates that BMI is
supportive for firms to take advantage of recognized opportunities. Therefore, in order to
translate opportunity recognition into higher performance, firms should innovate their business
model to exploit recognized opportunities.
Bustinza et al. (2019) carried out a study on the relationship between product-service
innovation (servitization) and firm performance as well as explored the roles of strategic
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partnerships and R&D intensity in this relationship. They suggested that there is a positive link
between product-service innovation and firm performance. It is evidence that non-servitized
manufacturers can enhance firm performance through business model innovation.
Additionally, the results also show that collaborative partnership and high R&D intensity play
a role in increasing the positive effect of product-service innovation on firm performance.
Cucculelli and Bettinelli (2015) study explored the link between the extent BMI and firm
performance in small and medium enterprises in the clothing sector and how this relationship
is moderated by investment in intangibles. The results showed that BMI is related positively to
firm performance and intangibles are significant positive moderators of this relationship. In
specific, the more innovative of the BM change, the greater the effects on performance and the
more robust the positive moderation role of intangibles.
Huang et al. (2012) conducted a research to examine the effect of target costing implementation
and BMI on firm performance by collecting data from 189 electronics and information industry
manufacturers in China. They found that the implementation of target costing was positively
associated with both business model innovations and firm performance. The results also
showed that the business model innovation was positively related to firm performance.
In summary, the number of articles that study explicitly on the relationship between BMI and
firm performance is still few and studies on this relationship use different measurement scale
of BMI. For example, Guo et al. (2016) use a nine-item scale based on Zott and Amit (2007)
to measure BMI; meanwhile, Huang et al. (2013) used a four-item scale that modified from
Johnson et al. (2008b) to measure BMI. In a different way, Cucculelli and Bettinelli (2015)
measured BMI by ranking the level of BMI from low, medium to high. Measuring BMI is
very important in examining its effect on firm performance, so it is necessary to develop a
common and validated measurement scale for BMI. In term of firm performance measurement,
these articles mainly focus on the effect of BMI on financial performance (sales growth,
profitability) while firm performance should be measured through 4 perspectives: financial,
customer, innovation and learning, and internal processes (Kaplan and Norton, 1992).
Nevertheless, evaluating only financial performance and neglecting other aspects of service
performance make firms miss the opportunity to capitalize on service market potential (Kastalli
et al., 2013). Therefore, future studies should explore the effect of BMI on firm performance
by measuring firm performance in various perspectives rather than just financial results.
Finally, typical studies on BMI and firm performance relationship focus on BMI in the
manufacturing sector and its effect on firm performance. This suggests further research on BMI
in other sectors to fulfil understanding the effect of BMI.
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2.4 AI & Machine learning - a new technique in digital revolution Early anticipating possible changes in the embedded environments could potentially allow
firms to identify when and how to innovate their BM to adapt and position it better with the
new environment. Nowadays, the digital revolution leads to significant changes in business
environments, especially changes in customer behaviour due to the explosive amount of data
and increasingly developing new technologies. In order to cope with the disruptive changes,
emerging AI/Machine learning techniques have been used across many different areas in order
to make sufficiently accurate predictions for different context by learning from massive amount
of data. (Tongur and Engwall, 2014, Velu, 2015). AI and machine learning techniques,
especially deep (neural) learning (LeCun et al., 2015) which is a subset of machine learning
has been receiving a lot of attention in both the industry and academia as its capability to solve
more complex problems and predict in a highly accurate manner by learning from huge amount
of raw data. It has shown outstanding performance on learning and (trend) prediction in
different applications such as financial crisis prediction, price prediction, computer vision,
speech recognition, fraud detection, providing recommendations, and natural language
processing.
The inspiration of artificial intelligence (AI) is to create an autonomous machine (or
computers) that mimic cognitive human functions associated with the human mind, such as
learning and problem solving (Russell and Norvig, 2016). The unprecedented growth of
massive data available today, increase of data connectivity and access, as well as the steady
improvements of computational capacity and algorithms have generated numerous applications
of AI across many diverse industries (Lee et al., 2019). The explosive growth of AI is
contributed significantly by machine learning techniques which involve using algorithms to
perform a specific task without using explicit instructions, relying on patterns generated from
sample data. Machine learning approaches can be classified into three basic paradigms (Bishop,
2006): (1) supervised learning that involves learning from labelled data; (2) unsupervised
learning that involves learning and mining information from unlabeled (raw) data; and (3)
reinforcement learning concerns with how agents in an environment take action to maximize
their cumulative rewards.
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3. Methodology
3.1 Research context
In this thesis, I study business model innovation in the context of electric utility industry which
is currently on the verge of disruption since the industry emerged and formed its incumbent
business model (PAConsulting, 2016, PwC-Reports, 2014, Saba, 2014, Sioshansi, 2014). The
traditional model that dominated energy delivery for decades may become obsolete and will
potentially be substituted by the new business model in the near future through the convergence
of distributed technology and customer engagement (Nillesen and Pollitt, 2016).
The dominant utility business models are based on large-scale grids that distribute electricity
to great distances to serve end customers attached to the meters. In this model, customers play
a passive role while the utilities control and monitor the whole process from production to
electricity distribution. However, different factors, either reactive or proactive, such as changes
in the political context, technology innovation, climate change and customer engagement are
potentially drivers that challenge the current order in the electric utility industry by creating a
seedbed and bringing ideas to develop new forms of business model with an aim to help electric
utilities get significant advantages in the era of disruptive changes. In order to survive and stay
competitive, electric utilities might need to innovate their business model to fit into the new
industrial order.
Research on business model innovation is well-fitted within the electric utility industry context
that can provide a rich empirical description to investigate the phenomenon (Yin, 2003). This
thesis will take electric utility as a research context, in which data from the electric utilities will
be used in my empirical papers (as discussed in the methodology section).
3.2 Research method This section discusses and justifies the methodology selected for this thesis in order to answer
the research questions. There are three fundamental research methods: quantitative, qualitative
and mixed methods research design, each of them has a different set of plans a study will use.
The selection process of appropriate method is predominantly influenced by substantive
research questions (Kelle, 2006). In this thesis, mixed method will be used as the combination
of qualitative and quantitative method instead of using either single method as it helps to
overcome and compensate for the limitations of these two “mono-method” research (Kelle,
2006) as well as provides better ways to answer the research questions by allowing to shed
light on different aspects of sociological phenomena (Tashakkori and Teddlie, 2010).
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In this thesis, quantitative methods and qualitative methods are used in complementary purpose
such that qualitative approach will be applied in the 1st and 2nd paper while quantitative
approach will be used in the 3rd and 4th paper. On the one hand, by starting the research process
with qualitative studies, local knowledge will be studied and obtained that helps to develop the
most appropriate theoretical concepts and hypotheses as well as to construct standardized
research instruments later on in order to cover relevant phenomena by meaningful and relevant
items. On the other hand, quantitative studies will help to corroborate my findings from the
qualitative studies and transfer these findings to other domains.
The data collection method consists of primary and secondary research (Saunders et al., 2017).
The data used in this thesis are both primary and secondary data that are collected from
different sources:
● Secondary data in the form of peer-review articles, published literature was used to
theorise and conceptualise the study as seen in the literature review paper (paper 1) and
a literature review section in each paper.
● Delphi panel: Delphi study method used in this thesis aims to gain insights electric
utilities and their activities in terms of business model innovation. Specifically, paper
1 focuses on exploring changes coming from the overlaying ecosystem (industry level)
that become triggers affecting the business model as its subsystem. To grasp as many
important triggers as possible, we have formed an expert group based on experts in the
area of electricity utility as well as professionals in adjacent field which fit well to the
overarching issue of changes the ecosystem. This group of 10 experts has been the core
of a Delphi panel which has answered open questions of the development of future
ecosystems. The Delphi panel is planned to answer questions in three rounds where the
later rounds build on answers from the previous. All the answers are analysed in parallel
to map the ecosystem changes to come.
● A survey: In order to evaluate the effect of BMI on firm performance (paper 3), I plan
to do a survey to gather data on BMI and firm performance. This study will use Likert
scale questions in questionnaires to collect data about BMI and firm performance.
Primary data by doing survey allows to get the latest and recent data directly from the
sampling population for the purpose of their research (Bryman and Bell 2011) and data
will be more reliable because it's collected objectively with careful planning and
controls from the researcher in order to gather the data for the original purpose of the
study.
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● Documents: documents such as firm annual reports, business plans, websites, brochures
etc. will be used in this thesis. In paper 1, particularly, secondary data from statistical
agencies (national and European level) and firms reports are used. Based on that data,
we can develop trend curves for battery capacity, battery prices, development of solar
energy, production of electric vehicles and more.
4. Working papers Paper 1: Business Model Innovation: A Systematic Literature Review and Guide for
Future Research
Author: Thi Phuong Van, Per Carlborg Nina Hasche and Johan Kask
Abstract:
In recent years, business model innovation (BMI) has attracted significant interest in both
practice and academia. The emerging BMI literature has addressed an important phenomenon
but is still young, incomprehensible and lacks theoretical underpinning as well as cumulative
empirical inquiry. Hence, it is warranted to have an updated, concerted and worthy overview
of current BMI literature. Accordingly, this study provides a systematic overview of the current
state of the art of BMI with a review sample size is 161 peer-reviewed articles published
between 2000 and 2019. It resolves definitional ambiguities and outlines the scope of BMI
research. As a result, we reconcile and extend past research as well as identify the main gaps
in the literature and give suggestions for further research in the field.
Paper 2: Business Models, Ecosystem and Adaptive Fit: The Case of Electric Utilities
Author: Johan Kask, Thi Phuong Van and Per Carlborg
Abstract:
In the management field, business models have become increasingly discussed. Recent
research in the area suggests that to better understand success and failure of business models,
greater devotion must be paid to the differences and changes in the ecosystem within which
the business models are embedded. Using trend curves and longitudinal data from the electric
utility ecosystem, with a particular focus on Northern Europe, the authors provide a means for
understanding the evolutionary link (adaptive fit) between dynamics at business-model (firm)
level and at ecosystem (industry) level. The paper offers new insights into prediction of
impending change/disruption at ecosystem level and how incumbents can act to renew their
business model fittingly. Based on the punctuated equilibrium model for understanding
ecosystem dynamics and the importance of fit business models, it provides a new twist to
17
evolutionary applications in the management field, as well as guides firm managers to identify
early sights of ecosystem disruption.
Paper 3: BMI and firm performance in electric utilities: a new scale of measurement
(This is just an idea, the aim or the content of the paper may change during the working
process)
Business model innovation has attracted a lot of researchers and practitioner's attention for the
last decades because of its global significance. BMI has been considered as a key driver of
success and a promising approach for firms to respond to changing sources of value creation
in the time of instability. Although there have been studies on the exploration of BMI outcomes
or consequences, the number of articles that study explicitly on the relationship between BMI
and firm performance is still limited and there is a lack of a validated, general measurement
scale for BMI and firm performance during BMI process. In order to fill the gap, this study
will explore the effect of BMI on firm performance and develop a new scale for BMI and firm
performance. Data will be collected by conducting a survey from subsidiaries/ distributors of
4 electric utilities in Sweden to evaluate their activities in terms of BMI and firm performance
during BMI process. The annual reports and documents also will be used. Currently, my
measurement scale is not completely developed yet but my idea is that the scale should measure
BMI and firm performance in a period process, not just at a certain point we collect data or
conduct research because BMI is a long-time process. Furthermore, this new scale can be used
to evaluate how the level of BMI affect firm performance during its process.
Paper 4: Leveraging AI/Machine Learning techniques to predict changes in environment
to navigate directions of Business Model Innovation
(This is just an idea, the aim or the content of the paper may change during the working
process)
This paper will investigate and utilise AI/Machine learning techniques to quantitatively predict
changes in customer behaviour which is possibly considered as one of the main drivers of BMI
in the electric utilities. The paper offers novel machine learning approaches to predict more in-
depth the impending change/disruption and how incumbents can act to renew their business
model fittingly in electric utilities by predicting the trending of customer energy consumption,
changes in the number of prosumers, etc. using different sources of massive historical data.
The successful prediction of changes in the environment (industry level), for example customer
behaviour, will help to guide firm managers to identify early sights of industry disruption, find
18
new ways to leverage these advances to transform their business model into the directions they
had never considered.
5. Working plan I started my PhD in August 2018 and my plan is to complete my licentiate thesis in Autumn
2020 and defend my doctoral thesis in Autumn 2022. My thesis will be written up in
compilation form. The Gantt chart below will show in more detail my working plan in the next
years.
GANTT CHART
Activity October-December
2019
January-June 2020
July- December
2020
January-June 2021
July- December
2021
January-June 2022
July-Decem
ber 2022
1
2
3
4
5
6
7
1. Reading, investigating related literature for the thesis
2. Completing PhD courses (90 credits)
3. Working on and writing paper 1 (Literature review paper), plan to finish and submit as
a journal paper in Spring 2020.
4. Revising and improving paper 2 with intend to submit as a journal paper by Summer
2020.
5. Conducting research for paper 3, prepare survey questions and start to collect data for
this paper in September 2020. Data will be collected in three different time points and
plan to finish in October 2021. This paper is expected to finish and submit a journal
paper by Spring 2022
6. Working on paper 4, plan to finish and submit as a journal paper by Summer 2022.
7. Writing the final thesis.
19
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