Towards Digital Transformation: Knowledge Management as an

Enabler in a Public Sector Asset Lifecycle

Viivi Siuko

, Jussi Myllärniemi

and Pasi Hellsten

Faculty of Business and Management, Tampere University, Kalevantie 4, 33014 Tampere, Finland

Keywords: Knowledge Management, Digital Transformation, Enablers, Asset Lifecycle, Project Network.

Abstract: Organisations often have visions of implementing advanced digital technologies, such as digital twins, re-

gardless of whether the organisations are mature enough for these technologies. It is a common misconception

that implementing advanced technologies will automatically lead to digital transformation and solve organi-

sational challenges, such as disruptions in information flows or the inability to learn from recurring mistakes.

The reality is, however, the contrary: emerging advanced technologies and digital transformation demand first

and foremost reliable, high-quality data and the ability to use them. Therefore, organisations with inadequate

information processes need to pay attention to their knowledge management (KM). In this paper, we demon-

strate how KM is an enabler of digital transformation. A case study of a public sector asset lifecycle was

conducted. Data were collected by interviewing 26 people representing the focal case organisation and its

stakeholders. The results highlight the importance of organised KM for digital transformation. We identify

enablers of digital transformation from the KM perspective.

1 INTRODUCTION

A public sector operation is a complex entity with

many routines, stakeholders, and tasks. It has long

been clear that to make an operation run smoothly,

one needs to take into consideration the different

stakeholders, their data sources, and their respective

aspirations (Hellsten & Pekkola, 2020). It has been

claimed that organisations need to evolve constantly

(Osterwalder et al., 2020). Organisations sometimes

aspire to implement advanced digital technologies de-

spite the organisations’ inadequate capabilities or

their lack of the requisite maturity for these technolo-

gies. Similarly, it is common to hear that implement-

ing advanced technologies can automatically solve

organisational challenges, such as troubles in infor-

mation flows, inaccessible information, outdated in-

formation, or recurring mistakes. Emerging technolo-

gies demand reliable and high-quality data to be ben-

eficial (Davenport, 2014; Leonardi & Treem, 2020;).

However, managing data quality is a problem for al-

most every organisation (Berson & Dubov, 2007).

Knowledge management (KM) plays a significant

https://orcid.org/0000-0001-7368-2610

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https://orcid.org/0000-0001-7602-1690

role in data, information, and knowledge processing

(Al-Emran et al., 2018). Therefore, organisations

need to pay attention to their KM before implement-

ing more advanced tools as a way of solving these

challenges. In fact, KM has been integrated – at the

conceptual level, at least – with digitalisation (e.g. Di

Vaio et al., 2021).

We studied a public organisation’s asset lifecycle.

In our study, we found several barriers that hindered

the full exploitation of the emerging tools in this com-

plex lifecycle context. We demonstrate how KM is an

enabler of digital transformation, that is, of significant

organisational changes through combinations of in-

formation, computing, communication, and connec-

tivity technologies (Vial, 2019). Well-organised and

-executed information processes support and form a

part of KM, which enables the information and

knowledge built upon it to be used for organisational

development (Choo, 2002).

Our objective in this research was to provide prac-

tical suggestions about enabling digital transfor-

mation from the KM perspective by recognising KM-

related challenges that hinder the achievement of

Siuko, V., Myllärniemi, J. and Hellsten, P.

Towards Digital Transformation: Knowledge Management as an Enabler in a Public Sector Asset Lifecycle.

DOI: 10.5220/0012164700003598

In Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2023) - Volume 3: KMIS, pages 157-165

ISBN: 978-989-758-671-2; ISSN: 2184-3228

157

digital transformation and implementation of digital

tools. We look at obstacles to attempts to achieve dig-

ital transformation. We enrich the practical findings

with literature on the enablers of digital transfor-

mation. By combining the practical findings and lit-

erature review, we discover why digital transfor-

mation is so difficult and which practical steps can be

taken to achieve such transformation.

Section 2 discusses the background of the study

and related research in this area. Section 3 describes

the case and the data collection. Section 4 presents the

findings of our study, and Sections 5 and 6 discuss the

issues and conclude our paper.

2 BACKGROUND

2.1 The IM Process as a Part of KM

Knowledge management refers to methods of under-

standing, defining, and utilising available knowledge

and information that provides the users, i.e. the deci-

sion-makers, with useful tools for managing their or-

ganisations (Moss, 1999). It is an approach through

which knowledge content in its various forms may be

identified and put into use (Nonaka & Takeuchi,

1995). Knowledge is based on information and expe-

riences.

Organisation and governance, identification of in-

formation needs, information acquisition, infor-

mation organisation and storage, information prod-

ucts, information sharing, and information use form a

continuous information management (IM) process

(Choo, 2002). This process provides a framework for

deriving knowledge and insights from data and infor-

mation from organisations’ own experiences and in-

formation sources, and it supports the use of infor-

mation and knowledge in problem solving, decision-

making, and strategic planning (Lake & Erwee,

2005). Information gets its final meaning and trans-

forms into knowledge when it is used in decision-

making, for instance, and changes in organisational

activities take place. By adjusting operations and

adapting behaviours, organisations create new infor-

mation needs, and the cycle starts over.

Choo’s (2002) process model of IM is one way to

structure the knowledge process: knowledge is pro-

cessed from data through information into

knowledge. IM forms the backbone of efficient KM.

However, to adopt such a model, an organisation

needs not only the appropriate technical, structural,

and cultural factors (cf. Gold et al., 2001) and the nec-

essary processes in place but also the proper mindset

for employees – attitudes combined with the skills to

make things happen (Jääskeläinen et al., 2022). IM

has been criticised because of its limitations and nar-

rowness in focusing only on data and information.

IM’s limitations become particularly clear when de-

livering tangible results in organisations (Kebede,

2010). This has led to an expansion of IM towards the

management of tacit knowledge that occurs in the

forms of, for example, experience, know-how, and

competence, so that IM integrates a conception of

KM (Kebede, 2010).

2.2 KM as an Enabler of Digital

Transformation

Digital transformation refers to significant organisa-

tional change achieved through combinations of in-

formation, computing, communication, and connec-

tivity technologies (Vial, 2019). The extent of digital-

isation, success of its implementation, and realisation

of its benefits depend strongly on the organisation’s

attitude towards renewals and readiness to participate

in developing itself (Ding et al., 2014). Alvarenga et

al. (2020) state that KM is a critical factor in the suc-

cess of digital transformation in a public organisation.

We use the IM process (Choo, 2002) as a framework

for categorising the KM-related enablers of digital

transformation.

Organisation and Governance. Bojesson and

Fundin (2020) have identified five enablers of digital

transformation: a sense of positivity, dedicated re-

sources and commitment, cooperation and combined

competences, lessons learned, and communication of

visions and goals. Understanding the business strat-

egy, the goal, behind the transformation is the first

step of digital transformation (Upadrista, 2021). Re-

source allocation is emphasised in the literature. For

example, Zhao et al. (2018) emphasise the importance

of knowledge-based resource allocation for improv-

ing knowledge flows within networks. Data,

information, and knowledge resources are key factors

that determine an organisation’s value creation

potential (Kianto et al., 2014). Xie et al. (2016) point

out that data, especially big data, are a primary driver

of the digital era’s changes. Mindsets and attitudes to-

wards data, information, and knowledge must be

changed to see them as valuable resources (Bojesson

& Fundin, 2020; Myllärniemi et al., 2019).

Identifying Information Needs. Upadrista

(2021) highlights the importance of understanding

customers and their needs in the digitalisation jour-

ney. Hellsten and Myllärniemi (2019) claim that con-

tinuous feedback and active updating of information

needs at all levels of operation, e.g. in customer rela-

tionship management, support KM activities, such as

KMIS 2023 - 15th International Conference on Knowledge Management and Information Systems

158

processing qualitative information products and mak-

ing knowledge processing more fluent; these pro-

cesses also support digitalisation. Visibility and com-

munication of information needs are crucial in digital

transformation. Kretschmer and Khashabi (2020)

point out the relevance of documenting organisations’

information flows. Identifying organisations’ infor-

mation needs is a starting point for the development

of knowledge processes but also guides the subse-

quent phases of the process (Choo, 2002; Myllä-

rniemi et al., 2019).

Information Acquisition. Agrawal (2021) points

out that knowledge capture and creation are essential

enablers of KM implementation. According to Al-

Emran et al. (2020), an individual’s competence for

acquiring knowledge affects their ability to adopt and

use new technologies. As shown by Turulja and Ba-

jgorić (2018), knowledge acquisition has a direct re-

lationship with product and process innovation and

with business performance. Al-Emran et al. (2020)

have found that knowledge acquisition has a positive

effect on perceived ease of use and usefulness. Digital

services, as a concrete example of digitalisation, can

offer value to customers and work as a channel for the

acquisition of data and information (Frank et al.,

2019).

Information Organisation and Storage. KM

and related processes have an important role in the

implementation of various information systems (ISs)

(Al-Emran et al., 2018). Knowledge processes as well

as their backbone, ISs, must be integrated with other

processes within the organisation, as otherwise, daily

operations, high-quality information, and information

products do not create value for the decision-makers.

(Myllärniemi et al., 2019). As information technology

evolves further, the technological solutions approach

the stage at which the features can feasibly be

executed automatically, which not only streamlines

actions but diminishes possible human errors (Tang

et al., 2010).

Information Products. In the digital era, data

and information offer organisations new ways to co-

create value with their customers. Xie et al. (2016)

have studied the transformation of digital resources,

such as big data, into value assets, i.e. information

products. This requires, for example, cooperative ca-

pabilities among customers and participating organi-

sations (Xie et al., 2016). The outcomes of valuable

and qualitative information products are remarkable.

Upadrista (2021) summarises the significance of data

by saying that data are the first thing to look at when

making any business decisions.

Information Sharing. Individuals’ readiness to

share their implicit knowledge is a central prerequi-

site for prolific KM (Hislop, 2013). Individual capa-

bilities, such as trust, motivation, and especially the

enjoyment taken in helping each other, are KM ena-

blers (Cavaliere, 2015). Information, and especially

knowledge sharing, has a positive impact on the adop-

tion and use of different information systems (Al-

Emran et al., 2020). Tools that support information

and knowledge sharing are relevant enablers of digital

transformation (Al Nahyan et al., 2019). Al Nahyan

et al. (2019) point out that holding regular and well-

defined meetings to share relevant information and

knowledge is essential.

Information Use. To ensure successful KM, it is

essential that an organisation share its understanding

of information and knowledge assets as highly valua-

ble resources. Choo (2002) and Sergei et al. (2023)

emphasise that managing the information process is

an important enabler. This, of course, requires

seamless cooperation among different stakeholders.

As an example, Antunes and Pinheiro (2020) point

out that an organisation’s ability to use and leverage

knowledge is dependent on its human resources and

collaborative practices. Another example of

cooperation between stakeholders is feedback.

Bojesson and Fundin (2020) state that integrating

feedback – and, more generally, lessons learned – into

knowledge creation is an important enabler of digital

transformation.

3 CASE DESCRIPTION AND

DATA COLLECTION

Data were collected by interviewing 26 employees in

5 different organisations, as shown in Table 1 below.

The focal case is a public infrastructure asset owner,

i.e. a medium-sized city. The other four organisations

cooperate with the focal case in shared projects, form-

ing a project network with an asset lifecycle. Organi-

sation D is a public organisation, and the others are

private companies. As illustrated in Table 1below, the

case organisation manages its assets for the whole

lifecycle – from design to construction and mainte-

nance. Maintenance may take place for centuries in

old cities in which streets are redesigned, recon-

structed, and continuously maintained. The actual de-

sign and construction are carried out by consultancies

and contractors, who were included in the interviews

(Organisations A–C) to gain more a holistic view of

the IM process of the case. Maintenance of assets, on

the other hand, is a mixture of outsourced and in-

Towards Digital Transformation: Knowledge Management as an Enabler in a Public Sector Asset Lifecycle

159

Table 1: Interviewees by organisation.

Organisation

Work description Inter-

viewees

Case organisation Project managers

in design

Case organisation Project managers

in construction

Case organisation Maintenance

management

Case organisation Management 2

Case organisation IT administration 3

Partner A Site managers

in construction

Partner B Design engineers 2

Partner B

Site managers

in construction

Partner C

Site managers

in construction

Partner D

Project managers

in design

house maintenance, but only the in-house mainte-

nance staff was interviewed due to accessibility is-

sues. In addition, the focal case organisation practices

interdependent cooperation with another asset owner

in the design phase (Organisation D). The focal or-

ganisation makes for an interesting case, as they have

a vision of implementing collaborative BIM (building

information modelling) and dig-ital twins in the asset

lifecycle to make their work easier. They wish for the

information models and digital twins to be constantly

updated through the asset lifecycle. While digitalisa-

tion may mean digitising existing tools, digital trans-

formation includes the wider business process

changes that implementing these technologies for the

whole lifecycle would require. Both technologies are

dependent on high-quality data (Gould, 2010; Moretti

et al., 2022). However, previous research (e.g., East-

man et al., 2011; Siuko et al., 2022) has found that

organisations in the infrastructure construction sector

struggle with the organisational processes that must

be in place for the successful implementation of ad-

vanced digital tools.

The semi-structured interviews had three themes:

everyday work, current IM in everyday work, and

ideal IM in everyday work. Following the suggestion

of Galletta (2013), the first theme had two goals: es-

tablishing a level of comfort and creating an under-

standing of the interviewee’s perspective, Therefore,

the interviewees were asked about their work, their

work routines, and decisions they make during work.

The goal of the second theme was to link their every-

day experiences to our research questions (Galletta,

2013). For example, by asking how the interviewee

knows what they should do and when, and where they

get the information they need, we could map the in-

formation and KM processes. The last theme concen-

trated on an ideal future scenario, and we tried to

make the interviewees think about solving the chal-

lenges that came up during the second theme.

The data were analysed using thematic analysis

and coding. First, the transcribed interviews were

browsed to obtain a holistic view of the data, and the

data were then coded iteratively with Atlas.ti; finally,

the codes were grouped into predetermined themes,

following the suggestions of Clarke and Braun (2017)

and Grbich (2013). The predetermined themes were

chosen based on the IM and KM processes (Choo

2002). Finally, the data were linked to digital trans-

formations through collaborative BIM.

4 FINDINGS

Collaborative BIM was seen as a solution to infor-

mation-related challenges. IT management and

maintenance management staff from the chosen or-

ganisation and a design engineer from Organisation B

agreed that shared information models would ease

their work. However, the design engineer added that

Figure 1: Chosen organizations in the infrastructure asset lifecycle.

KMIS 2023 - 15th International Conference on Knowledge Management and Information Systems

160

gaining access to common information systems

would make a difference. In addition to having col-

laborative BIM, the case organisation management

team wished for a digital twin.

The project managers from the main organisation

were the only group that raised concerns about the ex-

penses of collaborative BIM. According to them, mis-

takes made in design are more expensive to rectify

when linked to information models. On the other

hand, a site manager from Organisation A suggested

that information models could reveal design mistakes

before construction, which saves money in the con-

struction phase. Overall, the empirical findings re-

vealed multiple barriers to collaborative BIM.

According to a construction manager and a design

project manager from the focal organisation, re-

sources were limited, affecting the quality of the

work, including the quality of the information pro-

duced. It was also mentioned that tasks emerged that

were not their responsibility, and according to a site

manager from Organisation B, the project guidelines

were inadequate. Therefore, it seems that the roles

and responsibilities were undefined. A site manager

in Organisation A suggested that when the roles and

responsibilities were better defined in their organisa-

tion, human resources could be better allocated and

the amount of unnecessary or duplicated work would

decrease. The management team from the focal case

organisation also identified that a lack of resources

makes implementing new information systems and

policies challenging.

Both management and IT management from the

focal organisation raised concerns about collecting

indispensable information and not concentrating on

valuable information. According to the IT manage-

ment, valuable information had not been identified

when their information systems were built. They also

stated that the instructions for collecting the infor-

mation and the form in which it was to be collected

were unspecified. The management admitted that the

organisation’s information needs were not communi-

cated well enough to their partners that collect the in-

formation. A design project manager in the focal case

organisation wondered which information they

should provide to their partners, and a site manager in

Organisation B stated that they did not know pre-

cisely what information was needed from them,

which indicates that the lack of awareness of infor-

mation needs goes both ways.

A design project manager from Organisation D

stated that managing materials, documents, and data

manually is too burdensome. They desired machine-

readable codes that enable automatic, systematic, fast,

and reliable information collection. A site manager

from Organisation C added that information was

sometimes unreliable since the information acquisi-

tion tools were dependent on internet access. Accord-

ing to a site manager from Organisation B, the focal

organisation wanted to collect information repeatedly

for it to be compatible with their information system.

The maintenance management added that some infor-

mation would get lost in the previous stages, so they

would need to collect the same information again.

The challenges with repetitive information acqui-

sition were related to challenges with information or-

ganisation and storage, which could lead to outdated,

missing, and unreliable data. The information was un-

organised, and there were inadequate information

storage practices. Thus, information was hard to find,

and the information stored was forgotten and never

updated, according to the responses of IT and design

project managers from the focal organisation. The lat-

ter added that the collected information occasionally

would not be stored. Management from the focal or-

ganisation had noticed that the information stored was

uncoordinated, as they would get different outcomes

from different systems for the same requests. This

might also be due to the lack of interfaces, as a

maintenance manager pointed out.

A site manager from Organisation B mentioned

that the information was shared via various channels,

and the information received might not be what was

requested. The maintenance management in the focal

organisation reported their inability to give feedback

on designs, as they would receive the design docu-

ments too late and thus could suggest changes. On the

other hand, design engineers from Organisation B

wished for more feedback on their designs – which

were successful, which were not, and why. Also, a

site manager from Organisation C expressed a wish

for more feedback, as they felt that they had no way

of knowing whether the main organisation was satis-

fied.

Site managers from Organisations A, B, and C re-

ported that information products created by design are

unreliable, are incompatible, and create additional

costs in the construction phase. They suggested that

site visits should be made and designs checked before

construction to make sure that they do not overlap

with each other, are consistent, and are possible to

construct on-site.

Finally, when it comes to information use, the in-

formation needed might not be available. A site man-

ager from Organisation B reported that they might not

have received requested documents when the con-

struction was supposed to start, and they did not have

access to customers’ asset information systems to

check the documents.

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161

5 DISCUSSION

This research and the related literature (e.g. Daven-

port, 2014; Eastman et al., 2011; Leonardi & Treem,

2020) show that changes in organisational processes

are needed to enable digital transformation. We now

discuss why the implementation of digital tools is dif-

ficult and how a digital transformation can be ena-

bled.

The focal case organisation had challenges with

information and knowledge-related processes. They

had a vision of addressing these challenges with more

advanced digital tools and a digital transformation.

According to Upadrista (2021), the first step of digital

transformation is to link it it to the business strategy

and business objectives. Bojesson and Fundin (2020)

support this idea and emphasise the importance of

communicating the vision and goals to stakeholders.

In other words, the first step is to identify the

needs behind digital transformation and com-

municate them to the organisation and stakehold-

ers.

Our findings show that not enough resources are

allocated to data and information quality, which then

affects the quality of information products. Under-re-

sourced implementation of new digital tools and or-

ganisational changes will fail, our findings indicate.

It seems that allocating too few resources to infor-

mation and knowledge management is caused by not

recognising the value of information and knowledge.

This claim is widely supported by other researchers

(e.g. Bojesson & Fundin, 2020; Myllärniemi et al.,

2019; Upadrista, 2021). Dedicated resources and

commitment are important for information and

knowledge to flow in an organisation (Bojesson and

Fundin, 2020; Kianto et al., 2014; Zhao et al., 2018).

Quality data are a primary driver of digital changes

and enabler of the successful implementation of ad-

vanced digital tools (Gould, 2010; Moretti et al.,

2022; Xie et al., 2016). Cooperation is another ena-

bler (Bojesson & Fundin, 2020), which cannot be

achieved without defining roles and responsibilities:

not knowing who should do what results in redundant

work. Dedicating resources and delegating key re-

sponsibilities to each actor is essential for organis-

ing and governing digital transformation. Data,

information, and knowledge need to be acknowl-

edged as valuable resources.

Documenting information flows and continuously

updating information needs is essential for establish-

ing successful knowledge processes (Choo, 2002;

Hellsten & Myllärniemi, 2019; Myllärniemi et al.,

2019; Kretschmer & Khashabi, 2020). Our findings

support the literature in this regard. The focal organi-

sation had not identified and communicated their in-

formation needs, which makes information acquisi-

tion, storage, and sharing difficult. Upadrista (2021)

highlights the importance of understanding the cus-

tomer’s needs. If stakeholders do not identify infor-

mation needs, they will be unable to deliver the re-

quired information. In the case studied, the customer

organisation had decided to collect the needed infor-

mation themselves rather than requesting it from the

contractor to make sure that the information was com-

patible with their systems. We suggest that digital

transformation is more easily achieved if there is a

shared awareness of all stakeholders’ information

needs. In other words, if information gaps hinder

digital transformation, the organisation must

learn to identify the information needs of key ac-

tors. In addition, the information needs must be

communicated clearly throughout the lifecycle.

Information acquisition practices and tools have a

notable effect on business performance (Agrawal,

2021; Turulia & Bajgorić, 2020), as also demon-

strated by our findings. We show that, when acquiring

data and documents requires too much manual effort

or the tools are inadequate, the result is unavailable or

unreliable data and lost information. Frank et al.

(2019) suggest that digital tools and services support

information acquisition. Thus, if an organisation

struggles with information being unreliable and

must constantly reacquire it, we suggest investing

in data acquisition tools.

KM, information systems, and daily operations

have an important link to one another (e.g. Al-Emran

et al., 2018; Myllärniemi et al., 2019). If one fails, the

others are affected. Even when daily operations are

automated and human effort is decreased, the im-

portance of human-executed operations and KM does

not decrease (Tang et al., 2010). Our findings show

that it is difficult to keep data accessible, reliable, and

updated with insufficient interfaces and inadequate

data- and information-storing practices. Therefore,

we suggest that reaching the full potential of exist-

ing information systems is more likely after imple-

menting interfaces and making sure that infor-

mation organisation practices are well organised

and communicated.

Analysing data and processing them into usable

information products and services enables better de-

cision-making (Upadrista, 2021). Our findings show

that unreliable data lead to unreliable information

products. In our case, this means unreliable design

documents for construction. The interviewees sug-

gested double-checking information products and

data reliability before distributing the information

KMIS 2023 - 15th International Conference on Knowledge Management and Information Systems

162

products. Xie et al. (2016) add that cooperation be-

tween stakeholders is also required. In sum, infor-

mation products can only be as reliable as the data on

which they are based To improve the quality of in-

formation products, the first priorities are to im-

prove data and information storing and organisa-

tion practices, information acquisition tools, and

the ability to identify the information needs behind

information products in cooperation with stake-

holders.

KM is dependent on individuals being willing to

share, acquire, and store data, information, and

knowledge (Al-Emran et al., 2020; Cavaliere, 2015;

Hislop, 2013). Networking is an important part of

digital transformation, which makes information and

knowledge sharing essential (Al-Nahyan et al., 2019).

Our findings support the idea that even if the organi-

sation studied had defined an ideal information and

knowledge management process and implemented

the most advanced tools, the actual benefit could be

lost if people are not willing to share the information

and knowledge they possess. Information and

knowledge sharing should be encouraged through

regular and topical meetings (Al Nahyan et al., 2019).

Feedback and knowledge creation from past mistakes

enable learning and change (Bojesson & Fundin,

2020; Choo, 2002). It was also clear in our findings

that e.g. improving the quality of information prod-

ucts is very difficult without feedback. To enable

digital transformation, it is essential to ensure the

willingness to share information and ability to

learn from mistakes and to create new knowledge

through constant feedback.

In conclusion, we suggest several KM-related en-

ablers of digital transformation, which are bolded in

this section. With these enablers, we want to highlight

that achieving digital transformation is not only about

implementing new technologies.

6 CONCLUSIONS

The aim of this paper was to research which KM-re-

lated challenges can hinder digital transformation and

to provide suggestions on enabling digital transfor-

mation from the KM perspective. Our case study in

the public sector asset lifecycle provided an oppor-

tunity to study digital transformation empirically in

an organisation that prioritises technological solu-

tions over practices and processes, which is our con-

tribution to the theoretical community.

For the practical community, we aimed to provide

enablers that can be practically implemented. Our

suggestions may help organisations advance digital

transformation in their asset lifecycles. Our study

supports the finding of previous literature (e.g. Dav-

enport, 2014; Eastman et al., 2011; Leonardi &

Treem, 2020) that digital transformation requires

widespread changes in organisational processes. We

recommend more research on digital transformation

in a lifecycle setting in both the public and private

sectors.

According to Yin (2003), a case study’s quality is

evaluated based on its construct validity, external va-

lidity, and reliability. As an effort to ensure construct

validity and include multiple sources of evidence, we

interviewed partner organisations in addition to the

focal organisation. We also presented our findings to

a representative of the focal organisation and another

from a partner organisation. To enhance the external

validity, we complemented our findings with the ex-

isting literature in the discussion section. Finally, re-

garding reliability, we have described our data collec-

tion procedures and introduced the organisation stud-

ied as an exemplary case.

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