=Paper=
{{Paper
|id=Vol-3049/paper20
|storemode=property
|title=How is Digitalization Legitimised in Government Welfare Policies? An Objectives-Oriented Approach
|pdfUrl=https://ceur-ws.org/Vol-3049/Paper20.pdf
|volume=Vol-3049
|authors=Marcus Heidlund,Leif Sundberg
|dblpUrl=https://dblp.org/rec/conf/egov/HeidlundS21
}}
==How is Digitalization Legitimised in Government Welfare Policies? An Objectives-Oriented Approach==
https://ceur-ws.org/Vol-3049/Paper20.pdf
How is Digitalization Legitimised in Government
Welfare Policies? An Objectives-Oriented Approach
Marcus Heidlund*, Leif Sundberg**
*Department of Information Systems and Technology, Mid Sweden University, Sweden,
marcus.heidlund@miun.se
**Department of Information Systems and Technology, Mid Sweden University, Sweden,
leif.Sundberg@miun.se
Abstract: Digitalization is associated with structural changes in society, and a variety of policies
on the topic have emerged on different levels of government (EU, national, regional, local) in
recent years. Research suggests that government policies on digitalization are often overly
optimistic about the transformational effects of technology. Hence, there is a need to scrutinise
such policies. The purpose of this paper is to examine how objectives are expressed in
digitalization policies in the welfare sector. To do so, an objectives-oriented approach is utilised
to analyse four Swedish welfare policies. A directed content analysis was conducted using a
theoretical framework based on five types of objectives from decision theory. The results reveal
that common objectives in the policies studied were to change the status quo or use the people
involved (citizens and healthcare staff) as a point of departure. At times, the policies combine
goals of increased efficiency and better care, with a discourse that makes digitalization resemble
a strategic goal (in itself). Moreover, few alternatives to digitalization presented in the material
studied. Hence, although a range of actors is presumed to be part of changing the status quo, the
results suggest that these actors have little choice due to a lack of alternatives to the prescribed
path towards a digital welfare society. The results of this research have implications for both
theory and practice. The absence of alternatives ought to be considered in future policy making.
An interesting area for further research is to investigate how these policies are enacted in
practice.
Keywords: Digitalization, Welfare, Policy, Decision-Making, Objectives
1. Introduction
Digitalization is associated with structural changes in society (Brennen and Kreiss, 2016), and a
variety of policies on digitalization have emerged on different levels of government (EU, national,
regional, local) in recent years. The rationale for these policies has been subject to research. Schou
and Hjelholt (2019) studied Danish digitalization strategies from 2002 to 2015 and found that the
strategies were built on an ideal citizen associated with certain needs. Elsewhere, the need to
prioritise market-led values and technological perspectives over human needs has been discussed
(Mansell, 2010). Buhr (2017) stated that, while significant research has focused on productivity and
Copyright ©2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
200 Ongoing Research
economic growth or the risks for labour markets, little research has been conducted on the in-depth
effects of digitalization on the welfare state. Toll et al. (2020) argued that such policies are often
characterised by (over-)optimistic assumptions regarding the value associated with technologies
such as artificial intelligence (AI). Hence, there is a need to scrutinise such policies from different
perspectives. This paper discusses this subject using decision theory and objectives as a theoretical
framework.
Sundberg and Larsson (2017) investigated decision-making in e-government theory and practice
and suggested that e-Government may benefit for further research on the topic. Decision theory
involves the study of descriptive, prescriptive and normative approaches to how decisions are and
should be made (Eisenführ et al., 2010). Although we make decisions regularly from a young age,
few people are formally trained in decision-making (Keeney, 2004). A central component in decision
theory is objectives (e. g., Keeney, 1996 and Eisenführ et al., 2010). In a structured decision process,
the decision-maker faces several objectives (or alternatives) and must choose one over the other
based on their preferences (Eisenführ et al., 2010).
Against this backdrop, the purpose of the present paper is to examine how objectives are
expressed in digitalization policies in the welfare sector. The study was conducted as a policy
analysis in the Swedish policy sector using the objectives formulated by Eisenführ et al. (2010; see
Section 2). In doing so, this paper contributes to the research on the motivations behind the
digitalization of the welfare sector.
2. Analytical Framework: Types of Objectives
In this paper we argue, in line with Eisenführ et al. (2010), that objectives are important parts of
policy documents. By studying objectives in digitalization policies we expect to gain insights in
narratives of what is considered important in a future society. As we will describe in this section
objectives can be of different types, and by studying these types we expect to achieve an
understanding of how digitalization is legitimized in Swedish welfare policies. As explained by
Sundberg and Gidlund (2017), decision theory and e-Government research share several features,
such as a focus on values, stakeholders and issues related to assessment and evaluations. Hofmann
et al. (2020) presented a comprehensive framework for analysing and comparing e-Government
(digital government) policies, in which goals are an important feature. In this paper, an objectives-
oriented approach is used as an analytical lens.
Eisenführ et al. (2010) stated that an objective is not something that can be found; rather, it is
generated through the thought process. A decision-maker must be aware of how the object in mind
was generated, particularly before making an important decision. Theses authors provided a
framework consisting of the following themes: shortcomings of the status quo, comparison of
available alternatives, strategic goals, external guidelines and the people involved (see Table 1).
Ongoing Research 201
Table 1: Type of objectives
Type of objective Description
Shortcomings of the status quo The objective is generated through a wish to
change an existing condition.
Comparison of available alternatives When considering a set of alternatives that
differ from each other, an objective is generated
by choosing the option that is important for the
specific case (Eisenführ et al., 2010). Keeney
(1996) highlighted the importance of
alternatives in a decision-making situation.
Strategic goals Strategic goals are goals that an organisation
pursues. A goal is identified as important based
on which values are most important to the
decision-maker. Keeney (1996) identified
strategic objectives as the ultimate objectives
based on the fundamental values of an
organisation or decision-maker.
External guidelines These guidelines are usually established by
superordinate divisions that the subordinate
entities in the organisation must follow. An
objective is, therefore, generated through
external guidelines.
The people involved The decision-maker should ask themselves who
will be affected by a certain decision and what
objectives the people involved may have.
Essentially, this type of objective involves
stakeholder-centred approaches. As the public
sector consists of a range of heterogeneous
stakeholders, previous research has adapted
stakeholder theory (Freeman, 2010) to the e-
Government field (see, e.g. Flak and Rose,
2005).
In the present paper, these five types of objectives are used as a lens through which four Swedish
welfare policies are analysed.
3. Method and Materials
In this paper utilises a document analysis of national policies that focus on welfare or healthcare in
Sweden. These policies are presented in Table 2. As stated by Hasselblad and Sundberg (2020),
digital technologies are a means of enabling a (future) welfare society, but the logic behind this
development consists of conflicting and, at times, contradicting rationalities. The policy analysis was
carried out using five types of objectives presented, and the policies were chosen, as they a) offer
202 Ongoing Research
narratives of the welfare society and b) target a large range of actors, which may make them
important as a basis for decision-making regarding investments of fiscal funds.
Table 2: Policy name and publishing organisation
Policy name (translated) Publishing organisation Policy#
Artificial intelligence possibilities for welfare Swedish Association of 1
Local Authorities and
Regions (SALAR)
AI and automation for first line of care Inera AB 2
Vision E-health 2025 Ministry of social affairs 3
and SALAR
Automation of work SALAR 4
The analysis was conducted through a directed content analysis (e.g., Wei & Watson, 2019 and
Hsieh & Shannon, 2005). A directed content analysis uses existing theory to guide the researcher
(Wei & Watson, 2019) and enables key concepts and variables to be identified (Hsieh & Shannon,
2005). In this paper, we used five types of objectives. When reviewing the policies, the objectives
were identified and coded to the certain types presented by Eisenführ et al. (2010). The presence of
certain objectives in a policy was analysed using an interpretative methodology based on 'how' it
was described. For example, if 'the people involved' was used as an objective, we identified how
they were represented in the text, particularly in relation to other frequently mentioned objectives
(e. g., what kind of action space do these stakeholders have?).
4. Results
4.1 Shortcoming of the Status Quo
In policy #1, there was no mention of a shortcoming of the status quo. Policy #2 was based on a
demographic challenge. This challenge puts pressure on the healthcare system in Sweden via the
number of elderly citizens increasing while the working force decreases:
'Swedish healthcare stands before big challenges with an aging and increasing population while
retirement and savings in the healthcare sector decreases the personnel count. In just a couple of years,
fewer health and social care workers will need to be able to help more citizens' (p. 6)
This issue was also mentioned in Policy #3 and #4. Policy #4 stated the possibilities created by
artificial intelligence (AI) and automation must be utilised for the welfare sector to continue to
function optimally in future. The policy describes a need for change in organisational and work
processes using technology while prioritising the need to be able to handle future competency
requirements.
Ongoing Research 203
4.2 Comparison of Available Alternatives
No alternatives were identified in Policies #1, #2 and #3. For example, AI was not compared with
other alternatives in Policy #1. In Policy #4, no comparisons were made. Creating sufficient new jobs
was ruled out, as the healthcare sector would require need 166% of the total new jobs created yearly
in Sweden.
4.3 Strategic Goals
No strategic goals could be identified in Policy #1. In Policy #2 it was difficult to distinguish between
means from ends. The value of efficiency, better service and self-care frequently mentioned as part
of the need to create better healthcare in future when faced with demographic challenges. A similar
motivation was noted in Policy #4:
'To be able to offer continued good welfare, also when the demographic challenges increase,
municipalities, country councils and regions need to take advantage of this potential' (p. 36)
In policy #3, the main strategic goal was as follows:
'By 2025 Sweden shall become the best in the world when it comes to utilising the possibilities of
digitalization and E-health in order to facilitate for humans and reach a good and equal health and welfare'
(p. 8)
There was also a call to achieve higher equality for all citizens in terms of healthcare, with higher
efficiency noted as a factor in achieving this.
4.4 External Guidelines
No external guidelines could be identified in Policies #1, #2, #3 and #4. An overarching external
guideline relevant to this research was mentioned in Policy #3, which expressesed the government's
ambition to be the best nation in the world in terms of digitalization.
4.5 The People Involved
All four policies highlighted the people involved. Policy #1 named citizens, patients and personnel.
Two general themes in how the people will be affected emerged: (i) AI provides increased efficiency
to save citizens and personnel time and (ii) AI facilitates higher quality services that are more
accessible or easier to use.
'Several hospitals use and develop systems for advanced decision support for doctors. Support
like this improves both for patients and the healthcare system. When the diagnosis can be made quickly
and with greater sharpness it saves both human suffering and money' (p. 9)
'The system with administrator robots increases availability of the citizen, which will increase
service and increase autonomy. The system also makes the administration process more efficient and will
free up time for the administrator' (p. 10)
Policy #2 detailed what citizens and personnel want, similar to the ideal citizen discussed by
Schou and Hjeholt (2019). The policy explained how, in the future, there will be more self-care, and
204 Ongoing Research
the citizen will increasingly use AI. Policy #3 referred to citizens, special groups, personnel, users,
patients and clients in its discussion of the e-health strategy for 2010. Further, it identified three main
groups: individuals, personnel and decision-makers. Policy #3 also states that there is a need for
more involvement with entrepreneurs and the science community. Policy #4 had similarities with
the other polices that referred to welfare sector individuals (e.g., patients, users, clients and
personnel). The main group referred to in the policy was personnel. The policy often discussed how
AI or automation could help personnel either via decision support or by automating tasks to free up
their time.
5. Discussion
As shown in Table 3, two frequently mentioned objectives in the studied policies were 1) a will to
change the status quo through greater use of technology to tackle future demographic challenges
associated with an ageing population and 2) the use of 'the people involved' as a point of departure.
The frequent mention of stakeholders was interesting, as the policies did not mention any alternative
than to embrace technologies such as AI.
Table 3: Findings
Type of Policy #1 Policy #2 Policy #3 Policy #4
objective / Policy
#
Shortcomings - A A A
of the status quo demographic demographic demographic
challenge challenge challenge
Comparison - - - -
of alternatives
Strategic - To foster To become a To provide
goals greater efficiency world leader in better care
and better service digitalization
External - - To become a -
guidelines world leader in
digitalization
The people Citizens Citizens Citizens Citizens
involved (patients), (patients), (special groups, (patients, users,
healthcare staff healthcare staff users, patients, clients),
(doctors, clients, healthcare staff
administrators) individuals),
healthcare staff
(decision-
makers)
Ongoing Research 205
Extracting clear, strategic goals from the policies proved challenging during the research. The
goal of improved healthcare was mentioned, along with the hope of increased efficiency using
digital technologies. Moreover, Policy #3 emphasised Sweden's goal to be the best nation in the
world for e-health, which resembled the country's national goal to be the best nation in the world at
reaping the benefits of digitalization. Sweden's national goal could be interpreted as an external
guideline that fuels Sweden's strategic goal to be a world leader in e-health. However, these goals
are problematic, as they are expressed in a way that makes the use of digital technology sound like
a goal in itself; this made it difficult to separate means from the ends in the material studied.
It is interesting to examine the action-space the stakeholders mentioned in policies on welfare
people have when different objectives are combined. In several of the policies the people involved
were mentioned in relation to demographic challenges, reduced resources and increased demand,
all of which require technological solutions to improve efficiency for personnel. Personnel must
focus their time on tasks that technology cannot perform, while the citizens and users will demand
more from welfare, such as smarter solutions to obtain care or help. This is in line with Schou and
Hjelholt's (2019) ideal Danish citizen. Returning to personnel, there is no clear need or want from
this group, and the objective to use technology to free up their time appears to be projected onto
them rather than expressed by them.
To conclude, a range of stakeholders is frequently mentioned in the policies; however, these
people do not appear to be significantly involved in formulating objectives. Instead, their wants and
needs are projected onto them, and they are left with no choice but to utilise the new technologies.
At the same time, two of the policies are driven by future demographic challenges.
6. Conclusion
The purpose of this paper was to investigate how objectives are expressed in digitalization policies
in the welfare sector in Sweden. The present analysis of four Swedish welfare policies highlighted
how common objectives in the studied policies were to either change the status quo or use the
stakeholders (such as citizens and healthcare staff) as a point of departure when formulating
objectives. At times, the policies combine goals of increased efficiency and better care, with a
discourse that makes digitalization resemble a strategic goal (in itself). Moreover, few alternatives
to digitalization presented in the material studied. Hence, although a range of stakeholders is
presumed to be part of changing the status quo, the results suggest that these actors have little choice
due to a lack of alternatives to the prescribed path towards a digital welfare society.
These results contribute to existing research on digital government policies and may also be of
practical use to policymakers, who can use them to devise alternatives in future digitalization
policies. In the policy analysis we have found objectives that portray digitalization as a strategic goal
in itself, as well as objectives that projects certain (technological) needs and wants to a citizen and
government employees. By disclosing these findings, we believe this study has the potential to
generate an increased awareness among policy makers about the use of objectives in welfare policies
on digitalization. An important issue left unanswered in these policies is how they should be
translated into practice. How do policies that appear to narrow the action space for actors rather
206 Ongoing Research
than enabling it through alternatives and a variety of views guide decision-making regarding
digitalization? Hence, policy enactment represents an interesting subject for further research to
explore.
References
Brennen, J. S., & Kreiss, D. (2016). Digitalization. The international encyclopedia of communication theory
and philosophy, 1-11.
Buhr, D. (2017). What about Welfare 4.0?. In CESifo Forum (Vol. 18, No. 4, pp. 15-24). München: ifo Institut-
Leibniz-Institut für Wirtschaftsforschung an der Universität München.
Eisenführ, F., Weber, M., & Langer, T. (2010). Rational Decision Making Springer. Berlin, Germany.
Flak, L. S., & Rose, J. (2005). Stakeholder governance: Adapting stakeholder theory to e-
government. Communications of the Association for Information Systems, 16(1), 31.
Freeman, R. E. (2010). Strategic management: A stakeholder approach. Cambridge university press.
Hasselblad, A., & Sundberg, L. (2020). When Worlds Collide: Comparing the Logic of the Industrial and
Welfare Societies. EGOV-CeDEM-ePart 2020, 317.
Hofmann, S., Madsen, C. Ø., & Distel, B. (2020). Developing an analytical framework for analyzing and
comparing national e-government strategies. In International Conference on Electronic
Government (pp. 15-28). Springer, Cham.
Hsieh, H. F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative health
research, 15(9), 1277-1288.
Keeney, R. L. (1996). Value-focused thinking: Identifying decision opportunities and creating alternatives.
European Journal of operational research, 92(3), 537-549.
Keeney, R. L. (2004). Making better decision makers. Decision Analysis, 1(4), 193-204.
Mansell, R. (2010). The information society and ICT policy: A critique of the mainstream vision and an
alternative research framework. Journal of Information, Communication and Ethics in Society, 8(1), 22-
41.
Schou, J. & Hjelholt, M. (2019). Digitalizing the welfare state: citizenship discourses in Danish digitalization
strategies from 2002 to 2015. Critical Policy Studies, 13(1), 3-22.
Sundberg, L., & Gidlund, K. L. (2017). Value-based decision making: Decision theory Meets e-government.
In International Conference on Electronic Government (pp. 351-358). Springer, Cham.
Sundberg, L., & Larsson, A. (2017). The impact of formal decision processes on e-government
projects. Administrative Sciences, 7(2), 14.
Toll, D., Lindgren, I., Melin, U., & Madsen, C. Ø. (2020). Values, benefits, considerations and risks of AI in
government: A study of AI policy documents in Sweden. eJournal of eDemocracy \& Open
Government, 12(1).
Ongoing Research 207
Wei, H., & Watson, J. (2019). Healthcare interprofessional team members' perspectives on human caring: A
directed content analysis study. International journal of nursing sciences, 6(1), 17-23.
About the Authors
Marcus Heidlund
Marcus is a PhD student in information systems at Mid Sweden University in Sundsvall. He is a part of the
Forum for digitalization research group and his research interests include values and evaluation of
digitalization in the public sector. The research is conducted within the e-Government domain, with a focus
on the Swedish public sector.
Leif Sundberg
Leif Sundberg, PhD, is a researcher at Mid Sweden University. Leif's research interests include perspectives
on value creation associated with the use of digital technology in the public sector. The research is
conducted within the e-Government domain through policy studies, analyzing of benchmarking indexes, and
case studies within the Swedish public administration.