A Mapping Study about Digital Transformation of Organizational
Culture and Business Models
Eduardo C. Peixoto
, Hector Paulo
, César França
and Geber Ramalho
Cesar School, Avenida Cais do Apolo, 77, Recife, Brazil
Federal University of Pernambuco, UFPE, Av. Prof. Moraes Rego, 1235 - Cidade Universitária, Recife, Brazil
Keywords: Digital Transformation, Digital Companies, Organizational Culture, Business Models, Maturity Models,
Literature Mapping.
Abstract: According to some predictions, investments in Digital Transformation (DT) may reach US$ 6.8 trillion in
2023. Nevertheless, about 70% of DT initiatives struggle for success. In fact, few agree about what DT is,
how a company becomes digital and how to measure its progress towards it. Organizational Culture and
Business Models, however, are seen as key companies’ dimensions. Then, in this article, we report a literature
mapping study on the characteristics of Organizational Culture and Business Model in the context of DT. We
also investigate how these dimensions are assessed by Digital Maturity Models (DMM). Our data reveal that
the most frequent cited Organizational Culture characteristic is Organizational Learning, and that Data and
People are companiesBusiness Models key resources in the context of DT. The selected studies did not
provide enough information about how the characteristics of these two dimensions are evaluated by DMM.
We concluded that companies’ dimensions characteristics have not been exhaustively explored and further
studies on how to evaluate them in the context of DT are needed.
In August 2011, the founder of Netscape and
investment fund Andreessen Horowitz published in
The Wall Street Journal the article “Why Software Is
Eating the World” (Andreessen, 2011). In the article,
Andreessen pointed out the growing appreciation of
purely software companies and the increased use and
dependence on software in the operating model of
many companies in different sectors. Less than 10
years later, in 2018, Apple, Alphabet/Google and
Microsoft already figured as the main companies in
the US capital market, dethroning the then-
traditional, top of the ranking companies from a
decade ago. During this period, many other digital
companies caused a rapid migration of value from
analog to digital markets. Nowadays, to stay
competitive and defend against new entrants, being
digital has become an imperative (Boulton, 2018).
Nevertheless, going through a Digital
Transformation (DT) process has not been an easy
task for any company. According to Tabrizi et al.
(2019), 70% of all digital transformation initiatives
A possible reason why companies and managers
struggle in their DT initiatives is that going through a
DT process is complex and therefore it affects
simultaneously many company dimensions.
Teichert et al. (2019), for example, in a systematic
review of the literature about Digital Maturity Models
identified 15 company dimensions commonly used to
evaluate a company status regarding DT.
Organizational Culture (OC) and Business
Models (BM) were among the most relevant of these
dimensions. "Several surveys reported that company
culture is considered as the number one hurdle to
digital transformation. Hence, cultural change is a
prerequisite and can become a bottleneck for digital
transformation" (Teichert, 2019). BMs, on the other
hand, are strategic drive (Salviotti et al., 2019).
Peixoto, E., Paulo, H., França, C. and Ramalho, G.
A Mapping Study about Digital Transformation of Organizational Culture and Business Models.
DOI: 10.5220/0010991600003179
In Proceedings of the 24th International Conference on Enterprise Information Systems (ICEIS 2022) - Volume 2, pages 408-417
ISBN: 978-989-758-569-2; ISSN: 2184-4992
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
According to Rogers (2016), the transformation is
about new growth strategies and business models
replacing old ones as established companies learn
new ways of operating”. Other researchers associate
DT with the transformation of BMs (Morakanyane et
al., 2017; Schallmo et al., 2020) as well.
However, few studies explore the characteristics
of these two dimensions of companies in DT. In this
study, we followed guidelines for conducting a
systematic mapping with aims to answer the
following research questions:
1. RQ1:
What are the characteristics of
organizational culture (OC) associated to
digital transformation?
2. RQ2:
What are the characteristics of
business model (BM) associated to digital
3. RQ3: How are these characteristics evaluated
on Digital Maturity Models (DMM)?
By investigating what is in the literature about the
characteristics of OC and BMs of in the context of
DT, we aim to extend knowledge to help practitioners
enhance their chance to succeed on DT initiatives.
The results may also contribute to the elaboration of
more accurate assessment of these two dimensions on
digital maturity models.
In this paper, we report a literature mapping study
on the characteristics of Organizational Culture and
Business Model in the context of DT and investigate
how these dimensions are assessed by Digital
Maturity Models (DMM). In Section 2, we review
some important theoretical background. In Section 3,
we describe the method and procedures used for this
mapping study. We also discussed the threats of our
study. In Section 4, we present the results: an
overview of the selected articles and our answer to the
research questions. In Section 5, we present our
conclusion, final considerations and give suggestions
for future research. In Section 6, we list the articles
used as references in this study
2.1 Digital Transformation
A clear understanding of what Digital Transformation
(DT) is remains in considerable confusion and
misconceptions. The failure to distinguish between
digital transformation and its related terms
(digitization and digitalization) has created
difficulties for practitioners to claim authority and
responsibility for the strategy and implementation of
the digital transformation of their organizations
(Gong, & Ribiere, 2021; Morakanyane et al., 2017).
There are certain convergences though.
Morakanyane et al. (2017) conducted a systematic
literature review to reconcile several definitions on 1-
what DT is; 2- what characteristics DT has; 3- what
drives DT; 4- what DT impacts and 5- what are the
organization transformed areas. Henceforth, we refer
to DT with the semantics they have proposed:
An evolutionary process that leverages digital
capabilities and technologies to enable business
models, operational processes and customer
experiences to create value.
2.2 Organizational Culture (OC)
Schein, E. (2010) defined OC as a collection of
assumptions, norms, values, beliefs, and rules of
behavior shared by employees of an organization to
portray culture. It is how employees of an
organization obtain a sense of identity (Alvesson &
Sveningsson, 2015).
Other authors say that culture factor is how the
traditions, language, and laws (or rules of behavior)
held in common by a nation, a community, or other
defined group of people affect people on how they
behave regarding digital transformation. It is a topic
of organizational behavior, which commonly
includes employee attitudes, engagement,
identification, commitment, motivation, and climate
(Trenerry et al., 2021). Many authors say that the
culture of an organization is reflected in the behavior
of its employees (Al-Faihani et al., 2020).
Schein, E. identifies three different levels of OC
(Artifacts, Espoused Beliefs and Values, Underlying
Assumptions). Underlying assumptions are the
essence of culture and represent the belief system
towards behavior, relations, and reality are
manifested in values that become apparent in visible
artifacts such as behavior, language, or technology
(Hartl, & Hess, 2017).
Artifacts describes any organizational attributes
that can be observed, felt, and heard in an OC (Duerr,
2018). Exposed Beliefs and Values, in turn, refer to
goals, ideals, norms, standards, and moral principles.
In the context of digital transformation, Culture is
seen as the perspective of the human being in relation
to changes in the digital age, both in the role of leader
and author of transformations as in the role of an
instrument in the new configurations of societies and
businesses (CESAR, 2021).
A Mapping Study about Digital Transformation of Organizational Culture and Business Models
Morakanyane et al. (2017) noticed that culture is
an essential driver of successful DT in organizations.
According to Schallmo et al. (2018), incompatible
culture is one of the main reasons why DT initiatives
fail. Some studies even suggest that the most
prominent barriers to digital transformation are
managerial and cultural (Jones, Hutcheson, &
Camba, 2021).
2.3 Business Models (BM)
Many authors produced definitions of what a BM is
(Dasko & Sheinberg, 2005), and despite the academia
effort to capture its core it has been frequently
confused with other popular terms in the management
literature (Dasilva & Trkman, 2014). Al-Debei, El-
Haddadeh and Avison (2008) reconciled several
definitions, from different basis (such as value
proposition, revenue sources, business logic, current
and future business reality simplification, among
others) to produce the following definition:
The business model is an abstract representation
of an organization, be it conceptual, textual,
and/or graphical, of all core interrelated
architectural, co-operational, and financial
arrangements designed and developed by an
organization presently and in the future, as well
as all core products and/or services the
organization offers, or will offer, based on these
In the 2010's, Osterwalder (2010) proposed a
graphical representation named Business Model
Canvas (BMC), which became later standard to
represent and explain the BMs.
The BMC remains a well-known and easy to
interpret representation of a BM. Therefore, for the
purposes of this mapping, we considered the nine
BMC elements to characterize BMs and seek for the
literature on how they are cited in the context of DT.
2.4 Digital Maturity Models (DMM)
Maturity Models are tools generally designed to assess
and evaluate the development of a company towards
high-level productive processes. The term “maturity”
refers to a state of being complete, perfect, or ready and
is the result of progress in the development of a system
(Morakanyane, Grace, & O’Reilly, 2017). They have
become a popular management tool because they help
to determine the baseline level of a company’s maturity
(Williams et al., 2019).
In the same sense, a Digital Maturity Model
(DMM) specifically reflects the status of a company’s
digital transformation (Morakanyane, Grace, &
O’Reilly, 2017). It compares the company state to the
ready or perfect state of a Digital Company and helps
to identify gaps and can be used by practitioners to
plan actions to overcome these company gaps to the
digital mature state.
A DMM can be prescriptive, descriptive, or
comparative. Prescriptive DMM needs to, by
definition, provide actionable plans. A Descriptive
DMM gives a good overview on the historical
development of a company but offers little guidance
on how to proceed (for planning, it is used in
combination with a roadmap). In addition, a
Comparative DMM allows for internal or external
benchmarking and provides the opportunity to
compare the maturity levels of similar business units
or organizations (Kretzschmar, 2021).
Usually, a DMM has levels, dimensions, and
attributes (or characteristics). Attributes are the
elements of the dimension used to gauge the state of
the company in relation to the perfect state of a
dimension. The combined results of the state in each
dimension point to the overall state, the level of the
company in relation to what is being measured.
In his literature review, Teichert et al. (2019)
describes 22 different DMMs, which shows that
DMMs are abundant in the literature. OC and BMs
appear in that work as two of the most common
digital maturity dimensions.
According to Templier and Paré (2015) and Paré, G.
et al. (2015), we can define literature reviews based
on the review’s purpose, which needs to be
determined before the work is done. These ones can
be to describe, test, extend, and critique.
For this article, our purpose is to examine the state
of the literature as it pertains to a specific research
question. Therefore, this kind of literature reviews
better known as Mapping Studies do not aim to
expand upon the literature, but rather provide an
account of the state of the literature at the time of the
We followed the literature review guidelines
proposed by
Kitchenham, B., & Brereton, P. (2013) and
adopted a qualitative approach centered on a content
analysis of the literature (Schaller et al., Vatananan-
Thesenvitz, Pulsiri, & Schaller, 2019).
The review steps are detailed in the following
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3.1 Search Strategy
The search process started with a manual search in
specific database chosen for their relevance to the
subject, such as IEEE Xplore Digital Library,
ScienceDirect, Emerald, Scopus. We basically
searched for “Digital Transformation”.
From this initial search, we selected a small set of
candidate articles, according to their potential to
answer our research questions. This initial step was
conducted by two researchers, and the selection was
made by consensus, based on title and abstract.
From this initial set of articles, we analyzed
frequency and relevancy of technical terms that could
help us to build a more comprehensive search string.
These words were grouped by meaning (e.g., firm,
organization, enterprise) to assemble blocks of
terms. After that, we simulated different
combinations of search strings, checking if our initial
set of articles were reached in the resulting lists, as a
search quality control mechanism. We ended up with
the search strings as shown in Table 1: Search String.
Table 1: Search String.
("review" OR "survey" OR "roadmap" OR "mapping")
AND "digital" AND ("maturity" OR "levels" OR "phases"
OR "progress" OR "states" OR "transformation")
Finally, applying Publish-OR-Perish (POP)
, we
used the search string (Table 1: Search String.) to
perform an automatic search on “Title words” on
Google Scholar and found 553 candidate articles for
our research.
For this stage, we did not apply any temporal
coverage, nor did we apply snowballs. All searches
were automatic.
3.2 Selection Strategy
As selection criteria, we determined that the papers
included in the review had to (E1) be written in
English; (E2) published in peer reviewed conferences
or journals, or as book chapters; (E3) be focused on
OC and BM associated to digital transformation. For
viability purposes, we limited our research on the
period between 2017 and 2021 (the initial list with
553 studies contained 231 papers, 223 unique, that
were published before 2017).
After removing duplicates, 69 articles remained,
and were submitted to a full-text analysis. In this
phase 12 articles were excluded because they either
(E4) do not contain answers to any of our research
questions; or (E5) full text was not available.
Two researchers carried out the selection process,
both of whom independently analyzed each paper.
The exclusion criteria (E1 … E5) were carefully
noted, and meetings were held to resolve any
disagreements. Figure 1: Overview of the Selection
Method depicts the search process, indicating
numbers of papers at each step, for this review.
Figure 1: Overview of the Selection Method.
3.3 Validity Threats
There is a risk that we might have missed some good
material because, in this specific subject, we would
expected that the industry has advances as relevant as
those documented in specific literature. Industry
focused databases such as DUP, MIT SMR and HBR
were not included in our research. To explore further
and exhaust the possibilities, there are even other
scientific databases not yet explored such as Emerald,
Springer, JSTOR, SCOPUS, PsycINFO and ACM
Digital Library that may bring different findings. Due
to the novelty of the subject and the lack of
confidence about the best scientific bases to search
such a transversal subject, we decided on Google
Scholar, because its ability to index several databases.
We cannot guarantee that this is the best set of articles
to look at, nor that the search will be exactly
reproducible, but it returned a sensible number of
articles (553).
The initial manual selection was quite arbitrary
and represents another validity threat to our Method
and Procedure of articles selection.
A Mapping Study about Digital Transformation of Organizational Culture and Business Models
4.1 Selected Studies Overview (N=57)
At the end of the search and selection process, 57
studies remained for analysis. They originated from
institutions in 31 different countries, distributed in
five continents. Figure 2 shows the number of articles
per countries, with two or more articles. The country
with the most publications was Germany (n=10),
followed by Croatia (n=5) and the United Kingdom,
Portugal, and Russia (n=3).
Figure 3 shows the distribution of studies per year
of publication. It shows a steady increase in
publications in recent years. We consider 2017 a
tipping point year, because 39% more articles were
published after 2017 (2017 included) than in all years
prior to 2017.
Figure 4 shows the number of articles per those
scientific databases, only two or more articles. We
can see that the most important databases were
ResearchGate, IEEE Xplore, Springer, Elsevier and
Frontiers which indicates that this subject spreads in
several relevant research forums.
Finally, Figure 5 shows the number of articles per
publication type. Most selected papers have been
published in Journals (n=27) and Conferences
(n=22). A few of them were published like books
(n=4), dissertations (n=2) and thesis (n=2).
The complete list of selected articles can be
downloaded from https://doi.org/10.5281/zenodo.57
Figure 2: Number of Articles per Country.
Figure 3: Distribution of Papers Included in the Review
across Years.
Figure 4: Studies Selected in per Database.
Figure 5: Articles per Type.
4.2 RQ1: What Are the Characteristics
of Organizational Culture (OC)
Associated to Digital
Our analysis found several characteristics of OC
associated to digital transformation, which means that
companies’ digital transformation efforts are driven
to design environments that value these cultural
aspects. Nevertheless, with the data we collect it is
not possible to infer which factors have the greatest
impact (see the complete list of OC characteristics
associated to digital transformation in Table 2:
Characteristics of OC associated to digital
transformation.). Seventeen studies provided answers
to RQ1 on a perspective of OC characteristics. We
adopted the framework of Edgar Schein to organize
these characteristics data according to their cultural
In terms of artifacts, OC is described based on the
use of new digital technologies (social media, mobile,
analytics or embedded devices) to enable major
business improvements, like enhancing customer
experience, streamlining operations, or creating new
BMs and ICT competencies of employees.
Employees must know how to extract the best from
technologies at work as we can see in the following
excerpts: “Use of new digital technologies, such as
social media, mobile, analytics or embedded devices,
in order to enable major business improvements like
enhancing customer experience, streamlining
operations or creating new business models [S54,
p7] and employees need to know how technologies
can be used to work, as well as how they can be used
to improve the work” [S34, p8].
ICEIS 2022 - 24th International Conference on Enterprise Information Systems
The use of data science and analytics to guide
business decisions (Schallmo et al. 2020) and sharing
knowledge and assets (Bumann & Peter, 2019) are
other examples of cultural artifacts associated to
digital transformation.
Regarding culture values and beliefs, the
research identified that about 80% of the examined
studies include mention goals, ideals, norms,
standards, and moral principles. For these studies,
attributes like organizational learning, innovation,
collaboration, customer centricity, agility and
flexibility, empowerment and openness towards
change are the most important characteristics.
Concerning Organizational Learning,
companies in the context of DT may translates this
value to practice through educational activities and
investing in continuous learning to enhance digital
skills and capabilities of employees: Plan and
pursue massive educational activities/programs for
both clients and employees [S06.2] and
empowerment of employees, working in teams, and
enhancing digital skills and capabilities” [S27].
In addition, these companies pursue stimulating
environments that encourages employees to
experiment and learning through small, incremental,
and iterative changes.
As innovation value, we can find the prevalence
of behaviors that support risk-taking, disruptive
thinking, and the exploration of new ideas: “The
culture in digitally mature firms is collaborative and
more risk taking” [S37]. These companies often fund
innovation, and innovation is carried out regularly
through open innovation programs extent of
partnerships with external networks such as third-
party vendors, startups, or customers: “... using agile
methods, involving customer into innovation process,
funding innovation, innovation conducted regularly.
Collaboration appears associated to teamwork,
cross-functional collaboration, concentrates on
eliminating a sense of hierarchy to focus more on
horizontal collaboration, and readiness for
cooperation with external partners: eliminates a
sense of hierarchy to focus more on horizontal
collaboration that cuts across organizational
boundaries.” [S05, p9].
A client-centric approach refers to the
orientation to focus on, and continuously adapt to,
customer needs. It may imply practices such as
personalized products/services, customer experience
analysis, co-creation for new products, and others:
focus on customer choice, flexibility and agility
required to adjust as the customer preferences[S37]
and tracking of customers' experiences, prediction
of their needs. [S34].
Table 2: Characteristics of OC associated to digital
[S02], [S06], [S11], [S28],
[S34], [S37], [S42], [S49],
[S01], [S18], [S30], [S66]
[S01], [S11], [S26]
Sharing assets [S39], [S64]
[S01], [S06], [S11], [S14],
[S19], [S23], [S27], [S28],
[S34], [S39], [S49], [S64]
[S11], [S19], [S23], [S26],
[S27], [S28], [S30], [S31],
[S34], [S37], [S39], [S49],
[S05], [S11], [S19], [S23],
[S26], [S27], [S28], [S31],
[S02], [S06], [S11], [S27],
[S31], [S34], [S37], [S64]
[S01], [S05], [S11], [S19],
[S27], [S28], [S39]
Agility and
[S05], [S11], [S19], [S23],
[S27], [S31], [S34], [S37],
[S49], [S64]
[S01], [S05], [S11], [S27],
[S28], [S37]
Moreover, it is possible to identify
empowerment elements, in decision-making process
that are taken together, allowing employees to pursue
ideas and developing their capabilities: culture
should be transformed into a culture of involvement,
in which decisions are taken together ...[S19] and
allowing employees to pursue ideas in an
interdisciplinary and decentralized way ...” [S39].
As a value of OC, agility and flexibility can be
viewed as the organization's acceptance to change,
and efforts applied to act and re-structure, being
flexible and adaptable. Companies in the context of
DT have a quickly sensing/responding to changes as
strategy to gain market share and sustain their
competitive advantage: Agility and Open Innovation
are considered an essential factor for maintaining
competitiveness and ultimately for the survival of a
company” [S19].
A Mapping Study about Digital Transformation of Organizational Culture and Business Models
Openness towards new ideas refers to readiness
to accept, implement and promote change. This kind
of company maintain supportive environments for
changing ways of work [S28].
Concerning values and beliefs the research
identified leadership, failure culture, creativity,
digital-first mindset, startup mentality and problem-
solving culture.
4.3 RQ2: What Are the Characteristics
of Business Model (BM) Associated
to Digital Transformation?
The BM characteristics associated to digital
transformation have several distinct characteristics,
but one appears in intensity above all the others: it is
how data appears in most elements of the BM.
Moreover, the study revealed that data and people are
indisputable key resources. BM characteristics were
extracted from 33 papers, (see the complete list in
Table 3: Characteristics of business model associated
to digital transformation.).
Other characteristics of the BMs in the context of
DT are also worth mentioning and are depicted in the
paragraphs that follows.
Customers are either digital or non-digital, the
company must deal with a much broader customer
spectrum than non-digital companies. Customers,
nevertheless, are embedding digital technology
within their daily routine to become more informed,
independent, and demanding. They can shape opinion
for good of for bad and the decision-making process
of others: “An important implication of these changes
is that customers no longer see themselves as captives
of the firms with which they transact” [S30].
Companies in the context of DT have a Value
Proposition not only for customers, but for itself as
well. At first, the customer in the center of the
business: customer experience is a core value, and
availability and convenience are sought all times:
markets have evolved from organisational
centricity, in which manufacturers and service
providers largely define what to produce and market
to customers; to individual centricity, in which
consumers demand insight driven, customised
experience” [S62]. It delivers value through
personalization and customization. Value is obtained
with co-creation, through explicit actions or implicit,
through data capturing and intelligently data
processing. For the company itself, it uses technology
and data to reduce costs for the customer.
Channels are hybrid, a mixture of physical and
digital, but must be perceived as an omni channel:
boundaries between physical and online industry
structures, including the convergence of physical
products and digital services, merging the physical
world with online content, and creating an
omnichannel environment for the customer [S02].
Companies builds Customer Relationship in the
context of DT for direct and personalized
communication to customers. Customers on their side
demand transparency and need to be in the center of
the companies’ attention: “business transparency has
become an essential requirement, as nowadays”
Table 3: Characteristics of business model associated to
digital transformation.
Business Model
[S01], [S02], [S6.1], [S27], [S30],
[S35], [S37], [S39]
Value Proposition
[S02], [S03], [S05], [S6.1],
[S6.3], [S08], [S11], [S12], [S14],
[S20], [S28], [S30], [S35], [S39],
[S62], [S69]
Channels [S01], [S02], [S6.1], [S35], [S39]
[S01], [S03], [S6.1], [S6.3],
[S11], [S34], [S37], [S69]
Revenue Streams
[S01], [S03], [S6.1], [S6.3],
[S20], [S21], [S37]
Key Resources
[S01], [S02], [S03], [S05], [S6.1],
[S6.2], [S6.3], [S11], [S23],
[S29], [S30], [S32], [S33], [S34],
[S37], [S39], [S42], [S49]
Key Activities
[S01], [S02], [S03], [S05], [S6.1],
[S6.2], [S6.3], [S08], [S11],
[S12], [S14], [S18], [S27], [S28],
[S30], [S33], [S35], [S37], [S39],
[S64], [S66], [S69]
Key Partnerships
[S01], [S02], [S03], [S11], [S30],
[S33], [S37]
Cost Structure [S02], [S05], [S69]
Revenue Streams are based on a service logic,
which also implies lower tickets and continuous
transactions. The dematerialization of physical goods
into a digital remotely monitored asset enables a
company to charge customers for what products
deliver, instead of charging for the product itself:
transform from a pure product business to a service
business and ultimately to data-driven, outcome-
based service models” [S06.3].
Companies’ Key Resources in the DT context are
1- digital technology, 2- data and 3- people (with
digital skills leadership with soft skills). Data
collected through channels, products or services, or
digitized assets is used to perform micro
segmentation (sometimes to the level of an
ICEIS 2022 - 24th International Conference on Enterprise Information Systems
individual), or to constantly reimagine products or
services to create (new) value for customers or for the
company optimization: “for instance, firms adopting
digital technologies consider data streams to be of
paramount importance and assign to them a central
role in supporting their digital transformation
strategies” [S03].
Data is a source for better decision making and
allows for value co-creation with customers or
partners. Educating and training employees for digital
is another Key Activity: organisations should
harness the benefits of digital technologies by
collecting customer data and using customer insights,
for instance to predict customer behaviour and to
provide tailored and personalised products and
services with a better customer experience” [S39].
Knowledge and resources sharing among
companies and Key Partners and value co-creating
with customers are good indicators of a more intense
open innovation activities in DT context. The digital
platforms also changed the sequential organization of
a production value chain to a more dynamic and
flexible network of partners: the value chain has
become far more distributed in times of digital
transformation —particularly value creation and
value capture.” [S01].
Digital assets are easy to carry or replicate, and
data captured allows a better coordination of physical
assets and process optimization, leading to a better
Cost Structure: “with regard to economics, DT may
result in improved firm performance and new forms
of value, caused by an improved service quality or
cost reductions” [S02].
4.4 RQ3: How Are These
Characteristics Evaluated on
Many of the studies investigate DMM dimensions,
and sometimes, the dimension characteristics (or
attributes), but very few describe how these
characteristics are evaluated. From our 57 selected
studies, only 6 ([S31], [37], [S38], [S39], [S42] and
[S43]) contained some description of the
characteristics of the OC in a digital maturity model,
but none describes how those characteristics are used
to evaluate a company maturity regarding digital
The same happened to BMs. Few studies ([S06.2],
[S31], [S39], [S42], [S60] and [S64]) contained some
description of the characteristics of the BM in a
DMM, but none described how they are evaluated to
gauge the maturity of a company regarding digital
We randomly dive into the cited DMM (snowball
on some articles that reviewed DMM) to further
investigate the issue, but without success. So, we
suspect that even the articles describing the DMM do
not document how the dimension and its
characteristics are evaluated.
DT is a relatively new topic that can be studied in
different aspects. In this study, we collected evidence
that OC and BM are company dimensions that seem
to be key to DT and are frequently used on DMM to
gauge DT progress on companies. OC can be a barrier
or a driver to the DT. To many authors, transforming
the company BM is the end goal of DT. To help
practitioners set and follow better transformation
goals and increase DT initiatives chances to succeed,
this mapping study reviewed the literature to find out
how these company dimensions are characterized in
the context of digital transformation. We also
investigate how these dimensions are assessed in
Digital Maturity Models.
This study was carried by systematically selecting
and examining 57 articles. The research results
indicate that several OC characteristics are associated
with artifacts and values. The artifacts are associated
with a use of new digital technologies to enable major
business improvements like enhancing customer
experience, streamlining operations, or creating new
BM and ICT competencies of employees. In addition,
regarding culture values and beliefs, to these studies,
organizational learning, innovation, collaboration,
customer centricity, agility and flexibility,
empowerment and openness towards change are the
most important characteristics.
Furthermore, our study reveals that, in the context
of digital transformation, a successful company is a
true engine that uses digital technology to
continuously capture customer data, directly through
their products or services, or through third-party
products and services or through their customer
channels, to increase customer value. In this sense, it
implements a digital positive feedback loop, fed by
customer data, to continually increase or create value
for their consumers, which in turn allows more data
to be captured. The data captured from the company's
physical assets are also feedback, so that the company
can improve resource usage efficiency. In other
words, data is key as a resource and working with data
(innovating or optimizing through it) is a key activity.
A Mapping Study about Digital Transformation of Organizational Culture and Business Models
To master the use of data, companies constantly train
its employees on digital technologies.
How the characteristics of these two dimensions
are evaluated on DMM could not be investigated, as
the selected articles for the study did not contain
sufficient data to answer RQ3. Then, there is an
indication that the characteristics of company’s
dimensions in the context of DT are not sufficiently
documented in scientific papers. Nevertheless,
knowing how these characteristics are evaluated is an
important source to understand the state of plenitude
regarding companies’ DT. It is also mandatory to
validate or use a digital maturity model.
We collected data from a fair number of studies
from several countries (see Figure 2) and several
industries. We did not selected articles based on any
company characteristics, like revenue amount,
market size etc. Therefore, our finds are, in principle,
applicable, but not specific, to any kind of company.
Researches more fine-tuned to a specific type of
company (like industry or SME) may bring different
Although many selected articles for this study are
literature reviews (and may have used articles
published before 2017), more than 70% of the
selected studies were published after 2018, and then
are updated with the state of the knowledge.
There are some limitations we faced that threaten
the validity of the results found: 1- the use of freely
accessible web search engine such as Google Scholar
with no guarantee that it would provide the best set of
articles, nor that the search will be exactly
reproducible; 2- not exploring gray databases such as
DUP, MIT SMR and HBR and some scientific
databases such as Emerald, JSTOR, SCOPUS,
PsycINFO and ACM Digital Library.
To understand the state of completeness regarding
companies’ DT, future studies should deepen the
analysis on how OC and BM characteristics are
evaluated in DMM. An analysis on companies' other
characteristics in the DT context could also contribute
to the development of a clear and grounded
understanding of what the companies’ characteristics
associated to Digital Transformation are.
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A Mapping Study about Digital Transformation of Organizational Culture and Business Models