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.

16

● 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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