=Paper=
{{Paper
|id=Vol-1938/paper-kuu
|storemode=property
|title=Barriers and Facilitators of Digitalization in Organizations
|pdfUrl=https://ceur-ws.org/Vol-1938/paper-kuu.pdf
|volume=Vol-1938
|authors=Markku Kuusisto
|dblpUrl=https://dblp.org/rec/conf/sqamia/Kuusisto17
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==Barriers and Facilitators of Digitalization in Organizations==
https://ceur-ws.org/Vol-1938/paper-kuu.pdf
9
Barriers and Facilitators of Digitalization in
Organizations
MARKKU KUUSISTO, Tampere University of Technology
Digitalization has transformed industries and societies in profound manner. Some changes have been documented as increased
productivity and reduced costs of communications and information processing, to name a few. However, new technologies are
not always fully embraced by organizations. This paper delves into barriers and facilitators surrounding adoption of digital
technologies. The study was done as a systematic literature review. The paper introduces the most common technology
acceptance models. Even while not being directly facilitators or inhibitors of use of new digital assets in organization, these
models help to explain how the technology is accepted in organizations. The paper also introduces main inhibitors of
digitalization and use of novel digital solutions in organizations. Moreover, the most significant facilitating factors are
presented in the paper.
General Terms: Digitalization, Organizations
Additional Key Words and Phrases: Technology Acceptance
1 INTRODUCTION
Digitalization is a hype word of the decade. Not by accident, when thinking about how much digital
technologies have altered the way we live and function. The profits and alterations caused by
digitalization have been studied and shown convincingly. Even if the effects are clear, the ways to
adapt to digitalization and the organizational prequisites for adaptation are not thoroughly studied. It
is thus an interesting topic. In this article, a literature review of the barriers and facilitators of
digitalization in organizations is presented. In this article digitalization is defined as the automation
of tasks accomplished by digital technologies like business information systems and as the change in
the way of working.
There are a few studies regarding the inhibiting effects of organizational inertia and incumbent
systems [Haag 2004, Polites and Karahanna 2012], and large body of research on how innovations
diffuse and are adopted in companies [Jeyarajaj et al. 2006, Jones et al. 2010, Yao et al. 2009, Scupola
2012). Main theoretical models featured in these studies are technological acceptance model (TAM),
the unified theory of acceptance and usage of technology (UTAUT) and technology-organization-
environment framework (TOE).
Each one is further explained in their own sections. In addition, there is small stream of extant
literature on drivers and barriers of IT adoption in organizations. Beyond these points, however, no
literature was found with the applied methodology. Managerial perspective on how to facilitate
digitalization seems to be almost white area in the map – even though many studies suggest top
management support is a key issue in IT adoption and diffusion.
This literature review was inductively created beginning with keywords “digitalization” “barrier”
and “facilitator” mixed in different combinations in scopus, andor and google scholar. After selecting
articles back- and forward reference searches were conducted on each article to attain fuller picture of
the phenomenon. Articles were selected on same basis as the ones in first round from the search
engines. This reference search was iteratively repeated for every new article selected this way until no
new articles surfaced. Only articles from peer-reviewed journals or conferences were selected to
provide rigor for the research.
Author's address: M. Kuusisto, Pohjoisranta 11, P.O. Box 311, 28100 Pori Finland; email: markku.kuusisto@tut.fi.
Copyright © by the paper’s authors. Copying permitted only for private and academic purposes.
Proceedings of the SQAMIA 2017: 6th Workshop of Software Quality, Analysis, Monitoring, Improvement, and Applications, Belgrade, Serbia,
11-13.09.2017. Also published online by CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073)
9:2 • Markku Kuusisto
The article proceeds as follows: Organizational Inertia is discussed in section two. Section three is
about TAM. UTAUT is presented in section four. Fifth section brings forth TOE-model. Facilitators of
Digitalization are discussed in section six and finally Information Systems strategic alignment is
addressed in section seven. Section eight concludes the article.
2 ORGANIZATIONAL INERTIA
The Organizational inertia is seen as a barrier for adopting digitalization in organizations. Polites and
Karahanna [2012] define inertia as: “inertia in an IS context as user attachment to, and persistence
in, using an incumbent system (i.e., the status quo), even if there are better alternatives or incentives
to change.” Haag [2004] further conceptualizes organizational inertia to have five sub-dimensions.
These are cognitive, behavioral, socio-cognitive, economic and political aspects. Cognitive dimension
refers to managerial tendency of using incumbent systems even while knowing there are better
alternatives available. Key manager having much resistance to new systems can easily hold back the
whole organization.
Behavioral inertia is the tendency to keep doing things in certain way, just because they have
always been done that way. Socio-cognitive dimension consists of change-inhibiting culture in
company making changes hard to implement. Economic inertia entails both sunk costs in legacy
systems as well as costs of adopting the new system. Political inertia refers to environmental reasons
– partners and customers holding back the adoption of new innovation as it would affect them as well
[Haag 2004]. Polites and Karahanna [2012] find support for their claim that individual working habits
lead to organizational inertia. Habits can be considered to be a good thing since carrying out habitual
tasks requires less concentration and leaves the employee’s mind available to think other tasks while
shortening decision times. However, in the context of adopting new systems or advancing
digitalization, habitual working methods need to be broken in order to advance with the new way of
working.
3 TECHNOLOGY ACCEPTANCE MODEL
The Technology acceptance model (TAM) has been widely used in organizational studies. Gangwar et
al. [2013] consider it being the dominant model for explaining technology adoption at all organization
levels and at individual level. It was adapted from the theory of reasoned action. Since it has been
used extensively, it has developed some advantages such as well-researched and validated inventory
of psychometric measurements [Gangwar et al 2013].
TAM assumes that the more accepting users are to use a new system, the more likely they are to
use time and effort on learning and adopting the new system over the old one [Jones et al. 2010]. TAM
conceptualizes two key antecedents for adoption of new system. First one is perceived ease of usage.
Perceived ease of usage is defined as “the degree to which the prospective user expects the target
system to be free of effort”. This is rather intuitional – the easier a new system is to use, the happier
persons are to adopt it. Another antecedent is perceived usefulness. Its definition is as follows: “the
prospective user’s subjective probability that using a specific application system will increase his or
her job performance within an organizational context” [Gangwar et al 2013]. Perceived ease of use
affects the perceived usefulness as well as the attitude of user.
These perceived notions of the technology to be adapted form individuals attitude toward using the
new technology. This attitude then motivates a behaviour intention which in turn initiates the actual
behavior [Williams et al 2015]. Conceptual model of TAM is shown in Figure 1.
Some forms of TAM take out attitude, arguing that the antecedents affect the behavior intention
directly. These are called parsimonious models of TAM. Key thing in TAM is that it does not make
any assumptions about the actual quality of the new technology or innovation but focuses on what the
user perceives of it. In their study of forced technology situations Jones et al. [2010] found that
managerial support has major influence over perceived ease of use. In all cases it should be possible to
influence the perceived ease of use with proper education during implementation of the technology.
Barriers and Facilitators of Digitalization in Organizations • 9:3
Fig. 1: Conceptual model of TAM [Venkatesh et al 2003]
4 THE UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY
Past research on user acceptance of technology has been rich in volume and also in theories generated
[Williams et al 2015]. The unified theory of acceptance and use of technology (UTAUT) was combined
from several theories in 2003 by Venkatesh et al [2003]. They reviewed and integrated eight dominant
models of the time to create one with more explanation power. Theories included in forming UTAUT
are: Theory of Reasoned Action, the Technology Acceptance Model, the Motivational Model, the
Theory of Planned Behavior, a combined TBP/TAM, the Model of PC Utilization, Innovation Diffusion
Theory, and Social Cognitive Theory [Tornatzky and Fleischer 1990]. In their study, Venkatesh et al.
[2003] show that UTAUT outperforms the theories it has been based on. Since its creation, UTAUT
has been widely used in variety of fields [Williams et al 2015].
Fig. 2. Conceptual model of UTAUT [Venkatesh et al 2003]
As can be seen from Figure 2, UTAUT has some degree of similarity with TAM. This is not surprising
as TAM is one of the theories UTAUT has been based on. UTAUT adds six new constructs in addition
to those found from TAM – and discards attitude. The new construct in direct determinants of
behavioral intention added is social influence. Another new construct is facilitating conditions, which
is seen as direct determinant of use behavior [Williams et al 2015].
The other four constructs that the model adds are conceptualized as moderators for the direct
determinants. These are user’s gender, age, experience and voluntariness of use. These moderating
9:4 • Markku Kuusisto
constructs are not applicable for organizational research as such. However, it can be argued that these
constructs can be applied to organization as well by calculating mean values of all the employees of
the organization. Indeed, few studies have been made on organizational context with UTAUT
[Gangwar et al 2013]
5 TECHNOLOGY-ORGANIZATION-ENVIRONMENT FRAMEWORK
In their meta-analysis of research conducted between 2010 and 2012 Gangwar et al. [2013] identify
Technology-Organization-Environment (TOE) framework as one of the more widespread frameworks
when researching IT adoption. TOE framework was originally developed by Tornatzky and Fleischer
[1990]. Main benefit of TOE is that it is free from industry and company size restrictions. Critics of
TOE state that the framework is just taxonomy and does not really offer any conceptual depth. It
contains three contexts, which are explained in the next paragraphs and elaborated in Figure 3.
Technological context holds all the variables influencing adoption of innovation. Gangwar et al.
[2013] found that: “The studies found that system assimilation, trailability, complexity, perceived
direct benefits, perceived indirect benefits and standardization are significant variables while
observability is found insignificant” Organizational context is the most interesting one considering the
scope of this thesis. It refers to organizational characteristics and resources of company. The studies
identify several significant aspects of organization: degree of formalization, managerial structure,
trust, human resources, organizational slack, innovation capacity, knowledge capability, linkages
among employees, financial resources, firm structure, operational capability, strategic use of
technology, technological resources, top management support, quality of human capital,
organizational knowledge accumulation, expertise and infra-structure and organizational readiness
[Gangwar et al 2013, Bradford et al. 2014].
Many of these organizational topics identified in TOE are tied to findings on the effects of the
digitalization in this research. Environmental context focuses on the environment in which the
company operates. In this case it means mostly factors influencing whole industry, such as
government regulations or incentives. “Significant variables in environmental context include
customer mandate, competitive pressure, external pressure, internal pressure, trading partner
pressure, vendor support, commercial dependence, environmental uncertainty, information intensity
and network intensity while government regulation is not identified as significant variable” [Gangwar
et al 2013].
Fig. 3. The context of technological innovation [Tornatzky and Fleischer 1990]
Barriers and Facilitators of Digitalization in Organizations • 9:5
6 FACILITATORS OF DIGITALIZATION
Some studies have set to find out what drives digitalization. Some of the answers are intuitive and
others maybe not so. Yao et al. [2009] find support for the very intuitive assumption that bigger IT
spending helps in adopting new technologies. Human resources management practices have also been
linked as factors facilitating digitalization [Carroll and Wagar 2010]. Jeyaraj et al. [2006] published a
meta-analysis of the research made in the subject of diffusion of IT-based innovations between 1992
and 2003. In their study of 99 research articles, they find four best predictors for IT application, here
presented in Figure 4. The scores in the figure are calculated as percentage of the times the factor was
found significant from all the studies it was used. External pressure was found being significant
facilitator of IT adoption in all six of the studies it was tested on. External pressure stems from
suppliers, customers or industry standards. Professionalism of IS unit was found significant in 7
studies of the total 8 times it was studied.
This finding is seconded by Scupola [2012], who identifies the lack of knowledge to specify system
requirements and the lack of IT competence as organizational operative barriers. External
information sources was also found to be significant in seven of the eight studies it was studied. Top
management support was studied the most of the best predictors. It had been in 12 studies, of which
10 found it to be significant [Jeyaraj et al 2006].
Fig 4. Facilitators of IT adoption [Jeyaraj et al 2006]
Scupola [2012] studied ITC adoption in facilities management supply chains of Denmark. She
extracted both organizational and technology driven facilitators for the adoption process. These
findings present support to the work of Jeyaraj et al. [2006], offering organizational drivers closely
related to top management support. These drivers include company policy and better strategic and
tactic facilities management decisions. She also identifies seven external drivers and barriers such as
industry characteristics, supplier interdependence, lack of collaboration among software providers and
government regulation.
7 INFORMATION SYSTEMS STRATEGIC ALIGNMENT
A topic that borders the effects of digitalization is information systems (IS) strategic alignment. There
is a large body of research done in this topic ([Preston and Karahanna 2009, Reich and Benbasat
2000, Johnson and Lederer 2010, Alaceva and Rusu 2015), including the barriers and inhibitors of IS
strategic alignment on companies. The results of these studies are included in this thesis, as they offer
reason why information systems are not perceived as working well in companies - something that
should act as a barrier for further digitalization as well.
9:6 • Markku Kuusisto
There is no clear, agreed on definition or model for strategic alignment of IS. Preston and
Karahanna [2009] find two views for the term in their literature review of the subject. First one, the
intellectual dimension of strategic alignment, defines it as alignment between business and IS on
various dimensions such as strategy, plans or infrastructure of processes. The second one, the social
dimension of strategic alignment is defined as the mutual understanding and commitment to
business, objectives and plans between business and IT departments.
Alaceva and Rusu [2015] argue that companies cannot reach intellectual dimension if the social
dimension is not achieved before. They study the social dimension in their case study of a large
Swedish company. They divide this dimension in four subgroups: Shared domain knowledge between
business and IT executives, Successful IT history, Communication between business and IT
executives and connections between business and IT planning. It seems that communication,
connection and shared domain knowledge should be interlinked as concepts, as they are mainly
asserting that the main barrier of IS alignment is lack of communication and understanding between
business and IS departments.
A study by Johnson and Lederer [2010] support the finding of Alaceva and Rusu [2015], with the
result that the prequisite for IT alignment is mutual understanding of CEO (Chief Executive Officer)
and CIO (Chief Information Officer) of the company. Conceptually the results from these two studies
are very close even though the terms used are a bit different.
8 DISCUSSION
Even while digitalization as a word and as a phenomenon has been hyped for the past decade, many
aspects are still unclear. It has no standard definition – in many discussions it is used to convey
different meanings. The main objective of this article is to summarize the state of research made on
understanding how digitalization is advanced or how its progression is halted in organizations. It
seems that the most important factors in software are the ones affecting how user perceives it. This
might be changing a with the introduction of artificial intelligence models which would render most of
the users obsolete and provide a substantial leap forward in productivity of an organization. This
productivity leap should be more imminent in large private organizations where a lot automatizable
office work is being done. Small and governmental organizations might be slower in adapting the new
artificial intelligence based technologies. Management support was unsurprisingly found to have
major effect in advancement of new technologies in organizations. However, majority of the current
studies and of the current explanations are not very fine grained. A fruitful research topic would be
“what are the organizational prequisites for IS adoption” – with the aim of more fine grained
information about the phenomenon than simply “top management support”.
9 REFERENCES
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