=Paper=
{{Paper
|id=Vol-3223/paper15
|storemode=property
|title=Digital Servitization in Electric Power Industry
|pdfUrl=https://ceur-ws.org/Vol-3223/paper15.pdf
|volume=Vol-3223
|authors=Amirhossein Gharaie
|dblpUrl=https://dblp.org/rec/conf/bir/Gharaie22
}}
==Digital Servitization in Electric Power Industry==
https://ceur-ws.org/Vol-3223/paper15.pdf
Digital Servitization in Electric Power Industry
Amirhossein Gharaie
Linköping University, Linköping, Sweden
Abstract
This proposal focuses on digital servitization in the electric power industry from an ecosystem
perspective. In each section, the main concepts will be elaborated. By doing so, the significance
of the topic and the need for further research will be clear. Four research gaps and their
corresponding research questions are suggested as follows respectively. 1.existence of value
creation and destruction among actors: What is the value creation and destruction of digital
servitization among different actors in electric power ecosystem? 2. The role of new actors
such as aggregators in service business models with other stakeholders: What is the role of
emerging actors such as aggregators in delivering the service value to the users (customers) in
different phases of ecosystem transformation? 3. Impact evaluation of service business models
on users: How have service business models impacted users so far? 4. Interactions of
newcomers and incumbents in the electric power ecosystem: How do service business model
startups compete and cooperate with established utility companies?
Keywords 1
Digital servitization, Electric power industry, ecosystem perspective, Service business model
1. Introduction
In this proposal, I will introduce my research around digital servitization (DS) in the electric power
industry (EPI). Digital servitization defined as the shifting from product to service-based value
proposition by the help of digital technologies, has been creating new business ecosystems for
companies in EPI particularly in distribution part of the value chain where most of the transformation
of traditional grids to smart gids is happening [1]. During this transformation, novel technologies are
introducing such as smart meters, industrial electric storage, etc., and consequently, utilizing data
analytics to release the potential of new services (e.g., energy auditing, maintenance and energy
efficiency improvement, energy trading) to the customers [2].
Additionally, new roles for actors are being defined (e.g., aggregators), new value creation and value
destruction among companies are happening, the previous actors’ role is changing (e.g., involvement
of energy consumers in smart grids, energy traders) and new service business models including X as a
service, marketplace and platforms are increasing.
An example of value creation2 can be the state where the electricity suppliers are able to make the
hourly price contract with the consumers and fulfill their promises and the consumers in turn show the
willingness to have this type of contract rather than fixed contract. In contrast, if the companies could
not deliver the benefits promised on the hourly price contract, consumers will not find it attractive,
thereby not being satisfied with the service provided by the suppliers [3]. In such situation,
dissatisfaction is not itself the value destruction but interpreted as a possible sing of the value destruction
where the suppliers’ promises did not materialize.
These changes mentioned above, make us expand our understanding about the EPI and particularly
smart grids.
While the research on DS is increasing, the scope of the research has been limited to a single or
dyadic perspective and therefore the ecosystem perspective and the changes thereof is neglected [4].
1
BIR 2022 Workshops and Doctoral Consortium, 21st International Conference on Perspectives in Business Informatics Research (BIR 2022),
September 20-23, 2022, Rostock, Germany
EMAIL: Amirhossein.gharaie@liu.se
ORCID: 0000- 0001- 5049- 6145
©️ 2020 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
2
In this study, I consider value creation and value destruction equal to value co-creation and value co-destruction respectively.
158
Adopting an ecosystem lens in studying the DS facilitates the understating of new actors and their
corresponding roles and unravel the complexity of challenges among the actors including interest or
resource allocation conflicts. Considering the EPI, existence of specific restricting regulation for
instance for peer-to-peer transactions, prosumers and energy monopoly are some of the reasons why
DS has the potential to be investigated in this context through an ecosystem perspective.
In the following section, a short explanation about servitization and digital servitization will be
provided followed by an elaboration on DS in EPI. Section 4 and 5, will focus on the importance of
ecosystem lens in studying of DS and the significance of EPI in particular respectively. In the last
section, some possible ideas for the future research will be presented.
2. Servitization and digital servitization
Servitization for the first time used by [5] who defined it as adding services such as support,
maintenance and finance to products. Despite the vagueness of the evolution of servitization in the
literature [6], this concept has been widely recognized to describe shifting from product to service-
based value proposition [7], [8].
Servitization started from simple forms such as add-on service on products e.g., after sale services
[9] and low level of interaction between the supplier and the customer [10]. Meanwhile the increasing
desire for entangling service-based value in products, emergence and widespread utilization of digital
technologies in social life [11] and businesses i.e., digitalization [12] have provided new opportunities
for companies [13], [14], two of which are facilitating the servitization process by creating a foundation
for new service-based offerings [15]–[17] and augmenting the value and experience that customers
receive from products [18], [19].
Acknowledging the interrelation of digitalization and servitization [20] the convergence between
these two is known as digital servitization [21]. Even, some studies, by using the word “servitization”,
factually refer to digital servitization by admitting the role of digital technologies as an inherent
characteristic and enabler of servitization (e.g., [2], [7], [22]). In this research proposal, I adopted the
term “digital servitization” since it conveys the digital characteristic of servitization.
Additional to the shifting from product to service-centric value proposition, DS by the specific help
of IoT and cloud computing[23] has led to creating new business models in which what is valued by
the customers is the service even if what companies have to offer is a product. In this case, the service
is not the embedded part of the product, but the product is what makes the delivery of the service
possible [2]. These business models can be shown as X as a service (XaaS) which X can be substituted
by different things covering a vast range of business models which in various contexts have been
developing [24]. For instance, data as a service (DaaS), analytics as a service (AaaS) [25], software as
a service (SaaS) [26], mobility as a service (MaaS) [8], energy as a service (EaaS), battery as a service
(BaaS) [22] etc.
Needless to say, these types of businesses are changing the business ecosystems particularly when
growing number of startups by developing XaaS enter the competition with well-stablished companies
[27].
Given that, DS and specifically XaaS are components of my research. In the following sections, by
explaining a specific context, the importance of further investigation of DS in the EPI will be illustrated.
3. Digital servitization in electric power industry
Over time, EPI the same as other industries, has gone through a transformation over the past years
and the effect of DS can be seen more than before specifically by presence of different types of service
business models over the energy value chain from generation to consumption [2]. However, most of
the emerging service business models are in the distribution of energy value chain where a large portion
of transformation of traditional grid to smart grid has occurred [1].
In the beginning, the electricity produced was purchased and used by the customers without any
other services in between. After a while, the number of energy service companies aiming at reducing
energy-related cost by energy auditing, maintenance and energy efficiency improvement has grown
[28]. Utilization of new technologies e.g., substituting meters with smart meters or even renewing them,
159
increasing distributed energy resources e.g., microturbines, photovoltaic systems, wind systems, etc.
[1] and liberalization of market in some counties [22] are some reasons why the number of newcomers
as startups with service business models particularly in the form of X as a service is increasing [2], [22].
It seems; however, XaaS are not the only type of the service business models, they have been in the
focus of scholars, so that even [2], represents the XaaS as the outcome of servitization without stating
explicitly the role of other services including platform, service marketplace, etc. Similarly,[22] created
their focal explanation about XaaS although they acknowledged the presence of other types of service
business models such as marketplace and platform. They introduced 10 types of XaaS business models
run by startups as the outcome of servitization. These ten types comprise “Charging”, “Software”,
“Flexibility”, “Energy”, “Solar”, “Comfort”, “Battery”, “Microgrid”, “Trading”, “Heating” as a
Service.
As a further step, [22] classified these 10 types into six categories based on their value proposition
to the end customers. For example, comfort and heating as a service, despite the difference in their
service range, both can aim for providing services related to temperature adjustment for households.
Therefore, this commonality could be the reason to combine these two business models as “comfort
and heating”. These six categories are comfort and heating, flexibility and trading, energy efficiency
and management, solar and microgrid, charging and battery and lastly, energy software solutions.
Aforementioned study showed that the UK, Netherlands, Germany, Spain, and France are five
pioneers with the highest number of startups in service business models. Moreover, Scandinavian
countries i.e., Sweden, Norway, Finland, and Denmark constitute 10.3% of startups in EPI.
Figure 1 shows how distribution of service business models in each category is different.
Additionally, the percentage of each type of business model in each category is specified. For instance,
solar and microgrid has the largest number of startups despite XaaS and platform comprise a small
portion of it. Interestingly, startups providing services related to energy software and solutions, and
flexibility and trading reported as the largest XaaS and platform business models.
Figure 1: Distribution of various service business models in electric power industry [22]
[1] elaborates on the transformation of traditional power grid to smart grids and the corresponding
explains the challenges of electric utility in smart grids as illustrated in the figure 2.
160
Figure2: Utilities challenges in smart grids [1]
Among these challenges, emergence of new technologies at an unprecedented pace (D), new players
(E) and retail market and choice (F) are related to DS. Utilization of new technologies e.g., distributed
energy resources management systems, expedites the innovation pace in power grids and changes the
old paradigm where regulators and utilities controlled the environment. In the new paradigm, the
utilities implement these technologies by themselves. Moreover, implantation of new technologies by
customers such as solar panels and electric vehicles is increasing that oblige the utilities to respond with
the proper services.
Regarding the new players, it is stated that introducing microgrids and new players such as
aggregators are changing the way electricity is delivered to customers which is a challenge for utilities.
Finally, creation of retail market implies that the growth of distributed energy resources and storage,
diversified the ways of creating and delivering the electricity to customers by the presence of new
service providers. As a result, it gives more options to the customers to choose the retailers which
endanger the utilities’ monopoly and the dynamics between utilities and their consumers.
DS is one of the topics has the potential for further research in different industries particularly in
EPI due to the importance thereof and the highly pace growth of DS in this sector [2].
4. Digital servitization in ecosystem
Although the convergence of digitalization and servitization opened new doors for the businesses to
benefit, many studies have investigated the companies’ behavior and internal elements of the companies
such as business strategies, operations and capabilities which are arguably in the organizational level
(e.g., [29], [30]). For instance, by adopting the dynamic capabilities perspective, [29] examined how
pursuing exploration and exploitation strategies can affect the firm’s attitude toward DS.
[30] described the influence of four interdependent digital technologies, including IoT, cloud
computing, big data, and data analytics, on DS through the lens of business model innovation. In this
161
type of research, the scope has been limited to the single-firm or dyadic perspective, and the holistic
picture of the DS by considering an ecosystem perspective is missing [4].
Business Ecosystem refers to the “community of organizations, institutions, and individuals that
impact the enterprise and the enterprise’s customers and supplies” [31, p. 1325]. The mechanism for
coordination among the actors in business ecosystems is based on non-generic complementarities
without a full hierarchical control. Not generic refers to the fact that the collaboration between the
companies have a specific complementarity for a common purpose so that the outcome of one actor
depends on other actors’ outcome. Absence of hierarchical control means that the collaboration between
companies should not be necessarily based on any formal contract or obligations [32].
These characteristics of ecosystem is one of the aspects differ ecosystem form other business
constellations such as business network (ibid).
According to [33] one of the required types of research for DS is adopting the ecosystem perspective.
Despite the efforts of different scholars to move from a single firm to a network approach in scrutinizing
the DS [7], [30], [33]–[36], there is still room to explore the ecosystem issues of the DS.
The importance of adopting an ecosystem perspective, which obliges more exploration, can be
summarized as follows:
First, the ecosystem perspective helps to have a holistic picture of companies working together to
handle a business as a company is not always run alone. Through this perspective, the investigation of
the interaction among firms helps to understand the possible challenges, barriers, contingencies [34]
and provide an appropriate response to eliminate the issues respectively. As not all collaborations
among firms lead to success thus, the cognition of the contingencies at an ecosystem level might be
helpful.
Second, as DS might lead to creating new business ecosystems where the open flow of data plays a
crucial role in the survival of the businesses, exploring the emergence of new actors, related functions,
and services seems essential [37], [38].
Third, the collaboration between private and public sectors is one of the challenges that the new
service-oriented business models have faced (e.g., in the mobility context). Digital technologies have
contributed to the development of platforms facilitating the collaboration of public and private sectors.
However, underlying complexities comprising non-standards application programming interfaces
(APIs) [37], conflicts in allocating new responsibilities, different uncertainties, concerns and
governance structure in private and public sectors [38] have complicated this collaboration.
Lastly, the involvement of private data (customers’ own data, individuals, etc.) and public data for
the development of such businesses make companies consider ethics [39], privacy and security [37],
[40] more than ever as one of the requirements for digital services is procurement and processing the
data [41]. Therefore, an ecosystem perspective can lead to a comprehensive understanding of what DS
might encounter when it comes to utilizing different types of data provided by various ecosystem actors.
5. Ecosystem of Electric power
By reading the literature of servitization whether through the ecosystem perspective or not, the focus
has been on the manufacturing industries when shifting from a product to service centric view (e.g.,
[21], [42]). Even the premise of the studies on servitization ecosystem implies that manufacturing
companies are the focal point of the servitization ecosystem.
To end this proposal, this section will aim to specify some characteristics of ecosystem of electric
power which explains why DS in this ecosystem is occurring un-der certain settings that can be different
from manufacturing industry. Therefore, more investigation is needed when DS is happening in EPI.
1. Regulation: Energy sector is under certain regulations [43], [44] that influence the
innovativeness of the electric power ecosystem and impede the empowerment of consumers
[45]. For example, despite the efforts to eliminate the technological e.g., blockchain [46]
and regulatory issues of energy transactions after 2010, it is not widespread for peer-to-peer
transactions to be done where individuals can trade their energy in the energy markets [47].
2. Service-based: The servitization literature, most of the attention is focused on
manufacturing industries (e.g., [9], [21]). However, servitization is not confined to
162
manufacturers [48]. regardless of the essence of electricity as a good or service [49] the way
electricity is delivered to the customers is considered as a service [2].
It means that servitization will not change the application of electricity in contrast to
servitization in other context that the application of product can shift to a service. for
instance, in mobility as a service business model (e.g., Uber) the value proposition is not the
car as a product, but as a service aiming to provide mobility for the travelers [50].
In this example, the main value of the car is not received due to the product-based nature of
it but due to the service i.e., mobility provided. In energy industry, despite having
manufactures for technological part or infrastructure, servitization does not necessarily
change the application of electricity but the way this electricity and the respective services
can be delivered is diversified.
Therefore, the typical definition of servitization i.e., shifting from product to service
proposition might not work fully in electric power context. As a result, servitization research
can be conducted differently since the companies’ behaviors and the practice for
servitization might be different in such ecosystem.
3. Prosumers: Another aspect of the smart power grids is that the consumer alongside the
consuming electricity can have the role of micro producers, which refers to the concept of
prosuming [51]. According to [52] utilization of digital technologies, distributed energy
resources and prosumers are the elements affecting the increasing service business models.
However, the presence of prosumers in the power grids ecosystem created various
challenges [53]. For instance, reaching an agreement on involvement of main stakeholders
including utility companies, technology providers, energy producers and prosumers for
energy sharing mechanism.
4. Monopoly: Energy monopoly is not a new topic to discuss but the competition in this
monopoly to certain degree has been in the focus of the EPI specifically in the distributed
part of the value chain [22]. One of the actions to make this monopolized environment
competitive is market liberalization [54]. However, according to [43], it is still on debate if
this action could really facilitate the liberal market to achieve its objective specifically after
the radical technological improvement, changes in electricity consumer and energy
transition. As a result, the asymmetry of the power in the electric power ecosystem arises
many questions about the entrance of newcomers in such ecosystem and how they
collaborate with well-established companies [43].
6. Research ideas
Based on what was explained in the previous sections, this proposal, offers four re-search ideas (see
table 1). The first one, is the research topic that will be pursued after this proposal. Therefore, it will be
elaborated in more details. The three remaining ideas might be the alternative for the follow up research
in the later stages.
1. The first research will investigate the value creation and destruction that different actors in
the ecosystem of EPI might counter by DS.
In this regard, role of different technologies to mitigate the value conflict in ecosystem can
be studied.
This study will be exploratory/qualitative based on multiple case studies aiming to shed light
on the degree to which the electric utility ecosystem has constructive/destructive
interactions. In addition, it will specify if digital technologies can provide a better setting
for such ecosystem.
To be precise, value creation and value destruction are recognized in different approaches
and show two sides of a coin that constitute an umbrella word of value formation [55]. If
the value formation is in the direction of increasing the well-being among the system
(ecosystem) actor(s), value creation occurs and declining in actors’ well-being is referred to
value destruction [56]. In the context of EPI, value creation and destruction occur in various
circumstances. For instance, if the consumer’ data which contains the patterns of the
consumer behavior, ends up in misusing by any organization or even hackers, not only the
163
expected services will not be delivered but the privacy of the consumers will be violated. At
the same time, the reluctance of the consumers in cooperation with aggregators who carry
the responsibilities associate with demand response management, flexibility market, etc.,
will result in a negative well-being in the whole service ecosystem. In this example, value
destruction is a result of an imperfect resource integration between service provider and
consumers and destruction is created by both sides reciprocally. The resources can be
tangible (technology, contract, etc.,), or intangible (knowledge, service quality, etc.)
It should be noticed that value creation and destruction are not bound to business to
consumers, but it can occur in business-to-business market. For example, the conflicts of
interest between balance responsibility parties (BRP) and aggregators in some
responsibilities can potentially lead to value destruction (see [57] for more information).
The candidate actors for collection of data will be shown in the figure 3.
Since the focus of the study will be on the customer side of the EPI, the actors who possibly
can be contacted by the electricity consumers for different services are selected. However,
during the conducting the study, if necessary, more ecosystem actors such as regulatory
organizations or transmission and distribution system operators will be added. Suppliers as
the actors who are responsible for the providing electricity contracts will be selected from
different electrical areas in Sweden (S1 (Luleå), S2 (Sundsvall), S3 (Stockholm), S4
(Malmö)). The reason is that due to considerable electricity price difference among these
areas, the way the value is created or destructed might be different. After selecting the
suppliers their corresponding online consumers reviews will be analyzed. Two possible
types of aggregators will be opted depends on the availability of these emerging actors in
the Swedish electric power industry.
Fig. 3: Selected ecosystem actors in my research
Furthermore, one type of service business model (can be one type of XaaS but not defined for now)
can be added to the ecosystem actors for this study to capture the business complexities of this
ecosystem. However, the feasibility of considering all actors in one study must be determined in the
further step.
The interviews with each of this business entities will be the data collection method. The result of
this study can generate hypotheses that form the basis for the subsequent research.
164
Table 1
Research ideas based on my proposal
No. Gap Research question Research design Contribution
Clear picture of
What is the value
interactions that
creation and
Existence of value affect the electric
destruction of digital Exploratory/
creation and destruction utility
1 servitization among qualitative study,
among ecosystem.
different actors in multiple case studies
actors Role of digital
electric power
technologies in this
ecosystem?
regard.
What is the role of
emerging actors such as
The role of new actors
aggregators in Clarity on formation
such as
delivering the service Qualitative case of such actors and
aggregators in service
2 value to the users study, literature their business
business
(customers) in review models in smart
models with other
different phases of grids
stakeholders
ecosystem
transformation?
Better
understanding of
service business
Impact evaluation of How have service
Explanatory/ models not only as
3 service business models
quantitative economic entities
business models on users impacted users so far?
but as
sociotechnical
entities
Illustration of the
Interactions of How do service business real picture of
newcomers and model startups Qualitative, coopetition among
4 incumbents in electric compete and cooperate Mulitiple case ecosystem
power with established utility studies actors in electric
ecosystem companies? utility
ecosystem
2. This research will investigate the role of aggregators in service business models and their
interactions with related stakeholders by adopting a qualitative research design using one
case or multi cases. The result of this study will improve the comprehension of aggregator
concept in electric utility services and their responsibilities toward the rest of emerging
service business models
3. This research will evaluate to what degree service business models have been successful in
their goal for social benefits and explore the impact of consumers on these business models
for the better implementation. This study will be quantitative based on a survey as a data
collection method which draws on the result of the research 1 and 2. One of the expected
contributions can be the expanding the understanding of service business models not only
as economic entities but as sociotechnical entities.
4. Fourth research will elaborate on the cooperation and competition among service
newcomers and the incumbents in electric utility companies. This qualitative
165
research contributes to depicting the nuances in coopetition among newcomers and well-
established companies in electric utility context.
In total, the future research can potentially facilitate studying DS from a sociotechnical perspective,
which ameliorates respective challenges thereof [40], [58], [59].
7. References
[1] S. Vadari, Smart Grid Redefined: Transformation of the Electric Utility. Artech House, 2018.
[2] C. Park, “Expansion of servitization in the energy sector and its implications,” Wiley
Interdisciplinary Reviews: Energy and Environment, vol. e434, 2022.
[3] Y. Huang, E. Grahn, C. J. Wallnerström, L. Jaakonantti, and T. Johansson, “Smart meters in
Sweden-lessons learned and new regulations,” Current and Future Challenges to Energy Security,
vol. 177, 2018.
[4] H. Gebauer, M. Paiola, N. Saccani, and M. Rapaccini, “Digital servitization: Crossing the
perspectives of digitization and servitization.” 2021.
[5] S. Vandermerwe and J. Rada, “Servitization of business: Adding value by adding services,”
European Management Journal, vol. 6, no. 4, pp. 314–324, Dec. 1988, doi: 10.1016/0263-
2373(88)90033-3.
[6] T. S. Baines, H. W. Lightfoot, O. Benedettini, and J. M. Kay, “The servitization of manufacturing:
A review of literature and reflection on future challenges,” Journal of manufacturing technology
management, 2009.
[7] M. Kohtamäki, V. Parida, P. Oghazi, H. Gebauer, and T. Baines, “Digital servitization business
models in ecosystems: A theory of the firm,” Journal of Business Research, vol. 104, pp. 380–392,
2019, doi: 10.1016/j.jbusres.2019.06.027.
[8] X. Zhao, B. Vaddadi, M. Sjöman, M. Hesselgren, and A. Pernestål, “Key barriers in MaaS
development and implementation: Lessons learned from testing Corporate MaaS (CMaaS,”
Transportation Research Interdisciplinary Perspectives, vol. 8, p. 100227, 2020, doi:
10.1016/j.trip.2020.100227.
[9] L. Mastrogiacomo, F. Barravecchia, and F. Franceschini, “Definition of a conceptual scale of
servitization: Proposal and preliminary results,” CIRP Journal of Manufacturing Science and
Technology, vol. 29, pp. 141–156, 2020.
[10] V. Martinez, M. Bastl, J. Kingston, and S. Evans, “Challenges in Transforming Manufacturing
Organisations into Product-service Providers,” Journal of Manufacturing Technology
Management, vol. 21, pp. 449–469, 2010.
[11] A. Colbert, N. Yee, and G. George, “The digital workforce and the workplace of the future.” 2016.
[12] T. Ritter and C. L. Pedersen, “Digitization capability and the digitalization of business models in
business-to-business firms: Past, present, and future,” Industrial Marketing Management, vol. 86,
p. 180190, 2020.
[13] A. Engelbrecht, J. Gerlach, and T. Widjaja, “Understanding the anatomy of data-driven business
models– towards an empirical taxonomy.” 2016.
[14] R. Hilbig, B. Etsiwah, and S. Hecht, “Berlin start-ups–the rise of data-driven business models,” in
ISPIM Innovation Symposium, 2018, pp. 1–19.
[15] W. Coreynen, P. Matthyssens, and W. Bockhaven, “Boosting servitization through digitization:
Pathways and dynamic resource configurations for manufacturers,” Industrial marketing
management, vol. 60, pp. 42–53, 2017.
[16] R. Schüritz, S. Seebacher, G. Satzger, and L. Schwarz, “Datatization as the Next Frontier of
Servitization – Understanding the Challenges for Transforming Organizations.” 2017.
[17] J. Bosch and H. H. Olsson, “Digital for real: A multicase study on the digital transformation of
companies in the embedded systems domain,” Journal of Software: Evolution and Process, vol.
e2333, 2021.
[18] V. M. Story, C. Raddats, J. Burton, J. Zolkiewski, and T. Baines, “Capabilities for advanced
services: A multi-actor perspective,” Industrial Marketing Management, vol. 60, pp. 54–68, 2017.
[19] B. Kühne and T. Böhmann, “Requirements for Representing Data-Driven Business
ModelsTowards Extending the Business Model Canvas.” 2018.
166
[20] F. Vendrell-Herrero, O. F. Bustinza, G. Parry, and N. Georgantzis, “Servitization, digitization and
supply chain interdependency,” Industrial Marketing Management, vol. 60, pp. 69–81, 2017.
[21] T. Paschou, M. Rapaccini, F. Adrodegari, and N. Saccani, “Digital servitization in manufacturing:
A systematic literature review and research agenda,” Industrial Marketing Management, vol. 89,
pp. 278–292, 2020.
[22] M. Singh, J. Jiao, M. Klobasa, and R. Frietsch, “Servitization of Energy Sector: Emerging Service
Business Models and Startup’s Participation,” Energies, vol. 15, no. 7, p. 2705, 2022.
[23] H. E. Schaffer, “X as a service, cloud computing, and the need for good judgment,” IT professional,
vol. 11, no. 5, pp. 4–5, 2009.
[24] Y. Duan, G. Fu, N. Zhou, X. Sun, N. C. Narendra, and B. Hu, “Everything as a service (XaaS) on
the cloud: origins, current and future trends,” in 2015 IEEE 8th International Conference on Cloud
Computing, Jun. 2015, pp. 621–628.
[25] Y. Chen, J. Kreulen, M. Campbell, and C. Abrams, “Analytics ecosystem transformation: A force
for business model innovation,” in 2011 Annual SRII global conference, Mar. 2011, pp. 11–20.
[26] W. Sun, K. Zhang, S.-K. Chen, X. Zhang, and H. Liang, “Software as a Service: An Integration
Perspective,” in ServiceOriented Computing – ICSOC 2007, vol. 4749, B. J. Krämer, K.-J. Lin, and
P. Narasimhan, Eds. Berlin Heidelberg: Springer, 2007, pp. 558–569. doi: 10.1007/9783-540-
74974-5_52.
[27] A. Hoffmann, Value capture in disintegrated value chains: The hierarchy strategy. Springer, 2015.
[28] A.C.E.E.E., “Emerging opportunities: Energy as a service. American Council for and Energy-
Efficient Economy.” 2019. [Online]. Available: https://www.aceee.org/topic-brief/eo-energy-as-
service
[29] W. Coreynen, P. Matthyssens, J. Vanderstraeten, and A. van Witteloostuijn, “Unravelling the
internal and external drivers of digital servitization: A dynamic capabilities and contingency
perspective on firm strategy,” Industrial Marketing Management, vol. 89, pp. 265–277, Aug. 2020,
doi: 10.1016/j.indmarman.2020.02.014.
[30] M. Paiola and H. Gebauer, “Internet of things technologies, digital servitization and business model
innovation in BtoB manufacturing firms,” Industrial Marketing Management, vol. 89, pp. 245–
264, 2020.
[31] D. J. Teece, “Explicating dynamic capabilities: the nature and microfoundations of (sustainable)
enterprise performance,” Strategic management journal, vol. 28, no. 13, pp. 1319–1350, 2007.
[32] A. Shipilov and A. Gawer, “Integrating research on interorganizational networks and ecosystems,”
Academy of Management Annals, vol. 14, no. 1, pp. 92–121, 2020.
[33] F. Pirola, X. Boucher, S. Wiesner, and G. Pezzotta, “Digital technologies in product-service
systems: a literature review and a research agenda,” Computers in Industry, vol. 123, p. 103301,
2020.
[34] A. Sklyar, C. Kowalkowski, B. Tronvoll, and D. Sörhammar, “Organizing for digital servitization:
A service ecosystem perspective,” Journal of Business Research, vol. 104, pp. 450–460, 2019.
[35] M. Paiola, F. Schiavone, R. Grandinetti, and J. Chen, “Digital servitization and sustainability
through networking: Some evidences from IoT-based business models,” Journal of Business
Research, vol. 132, pp. 507–516, 2021.
[36] L. Linde, D. Sjödin, V. Parida, and J. Wincent, “Dynamic capabilities for ecosystem orchestration
A capability-based framework for smart city innovation initiatives,” Technological Forecasting
and Social Change, vol. 166, p. 120614, 2021.
[37] A. Immonen, M. Palviainen, and E. Ovaska, “Requirements of an open data based business
ecosystem,” IEEE access, vol. 2, pp. 88–103, 2014.
[38] G. Smith, J. Sochor, and I. M. Karlsson, “Public–private innovation: barriers in the case of mobility
as a service in West Sweden,” Public Management Review, vol. 21, no. 1, pp. 116–137, 2019.
[39] C. F. Breidbach and P. Maglio, “Accountable algorithms? The ethical implications of data-driven
business models,” Journal of Service Management, 2020.
[40] M. Granath, K. Axelsson, and U. Melin, “Reflection note: Smart City Research in a Societal
Context,” AScandinavian perspective and beyond?. Scandinavian Journal of Information Systems,
vol. 33, no. 1, p. 516, 2021.
167
[41] W. A. Günther, M. H. R. Mehrizi, M. Huysman, and F. Feldberg, “Debating big data: A literature
review on realizing value from big data,” The Journal of Strategic Information Systems, vol. 26,
no. 3, p. 191209, 2017.
[42] M. Kolagar, V. Parida, and D. Sjödin, “Ecosystem transformation for digital servitization: A
systematic review, integrative framework, and future research agenda,” Journal of Business
Research, vol. 146, pp. 176–200, 2022.
[43] R. Poudineh, “Liberalized retail electricity markets: What we have learned after two decades of
experience?,” Oxford Institute for Energy Studies, 2019.
https://www.oxfordenergy.org/publications/liberalized-retail-electricity-markets-what-we-have-
learned-after-two-decades-of-experience/ (accessed Jun. 02, 2022).
[44] K. Psara, C. Papadimitriou, M. Efstratiadi, S. Tsakanikas, P. Papadopoulos, and P. Tobin,
“European Energy Regulatory, Socioeconomic, and Organizational Aspects: An Analysis of
Barriers Related to Data-Driven Services across Electricity Sectors,” Energies, vol. 15, no. 6, p.
2197, 2022.
[45] S. Lavrijssen and A. Carrilo, “Radical innovation in the energy sector and the impact on
regulation.” 2017.
[46] S. Kloppenburg and M. Boekelo, “Digital platforms and the future of energy provisioning:
Promises and perils for the next phase of the energy transition,” Energy Research & Social Science,
vol. 49, pp. 68–73, 2019.
[47] M. Matias and J. Stromback, “Energy as a service disruption – White paper,” Optimeyes Energy,
2019, [Online]. Available: https://
[48] C. Kowalkowski, H. Gebauer, B. Kamp, and G. Parry, “Servitization and deservitization:
Overview, concepts, and definitions,” Industrial Marketing Management, vol. 60, pp. 4–10, 2017.
[49] P. O. Pineau, “International trade agreements and the Peruvian electricity sector,” no. 13). 2003.
[50] P. Jittrapirom, V. Caiati, A.-M. Feneri, S. Ebrahimigharehbaghi, M. J. A. González, and J. Narayan,
“Mobility as a Service: A Critical Review of Definitions, Assessments of Schemes, and Key
Challenges,” Urban Plan, vol. 2, p. 13, 2017, doi: 10.17645/up.v2i2.931.
[51] E. Espe, V. Potdar, and E. Chang, “Prosumer communities and relationships in smart grids: A
literature review, evolution and future directions,” Energies, vol. 11, no. 10, p. 2528, 2018.
[52] T. Helms, “Asset transformation and the challenges to servitize a utility business model,” Energy
Policy, vol. 91, pp. 98–112, 2016.
[53] R. Zafar, A. Mahmood, S. Razzaq, W. Ali, U. Naeem, and K. Shehzad, “Prosumer based energy
management and sharing in smart grid,” Renewable and Sustainable Energy Reviews, vol. 82, pp.
1675–1684, 2018.
[54] M. Armstrong and D. E. Sappington, “Regulation, competition and liberalization,” Journal of
economic literature, vol. 44, no. 2, pp. 325–366, 2006.
[55] P. Echeverri and P. Skålén, “Value co-destruction: Review and conceptualization of interactive
value formation,” Marketing Theory, vol. 21, no. 2, pp. 227–249, 2021.
[56] L. Plé and R. C. Cáceres, “Not always co‐creation: introducing interactional co‐destruction of value
in service‐dominant logic,” Journal of services Marketing, 2010.
[57] S. Färegård and M. Miletic, “A Swedish Perspective on Aggregators and Local Flexibility Markets:
Considerations and barriers for aggregators and SthlmFlex together with their potential to manage
grid congestions in Stockholm.” 2021.
[58] W. Serrano, “Digital systems in smart city and infrastructure: Digital as a service,” Smart cities,
vol. 1, no. 1, pp. 134–154, 2018.
[59] B. Anthony Jnr, “Integrating Electric Vehicles to Achieve Sustainable Energy as a Service Business
Model in Smart Cities,” Frontiers in Sustainable Cities, vol. 3, 2021, doi:
10.3389/frsc.2021.685716.
168