# The Impact of Working From Home on the Success of Scrum Projects: A Multi-
Method Study

Adrian-Alexandru Cucolaș  Aalborg University, Denmark.
<EMAIL_ADDRESS>Daniel Russo  Aalborg University, Denmark.
<EMAIL_ADDRESS>
###### Abstract

The number of companies opting for remote working has been increasing over the
years, and Agile methodologies, such as Scrum, were adapted to mitigate the
challenges caused by the distributed teams. However, the COVID-19 pandemic
imposed a fully working from home context, which has never existed before.
This paper investigation a two-phased Multi-Method study. In the first phase,
we uncover how working from home impacted Scrum practitioners through a
qualitative survey. Then, in the second phase, we propose a theoretical model
that we test and generalize using Partial Least Squares - Structural Equation
Modeling (PLS-SEM) through a sample study of 200 software engineers who worked
from home within Scrum projects. From assessing our model, we can conclude
that all the latent variables are reliable and all the hypotheses are
significant. Moreover, we performed an Importance-Performance Map Analysis
(IPMA), highlighting the benefits of the home working environment and the use
of Scrum for project success. We emphasize the importance of supporting the
three innate psychological needs of autonomy, competence, and relatedness in
the home working environment. We conclude that the home working environment
and the use of Scrum both contribute to project success, with Scrum acting as
a mediator.

###### keywords:

Scrum , working from home , project success , multi-method study

} }}}

##  1 Introduction

With the recent COVID-19 pandemic, millions of people around the world were
suddenly forced to either work from home or not at all, and companies were
forced to allow their employees to work from home where possible in order to
keep their businesses afloat [1]. Remote work has always been an alternative
to being present in an office, especially within Software Development. A
global survey shows that 56% of companies allow remote working and 52% of
employees work from home at least once a week [2]. Now, with the rapid spread
of the virus globally, countries imposed specific guidelines and restrictions
regarding, for example, the number of people allowed in indoor spaces and
their conduit, policies that, in this case, made working from home the only
viable solution for many companies. However, despite apparent advantages such
as reducing commute time and being able to spend more time with the family
[3], working from home is not an easy endeavor. It requires personal skills
that allow the person to organize and carry his work without any form of
direct supervision and that the job, i.e., the workplace, has a culture that
supports and encourages remote work [4].

Within Software Development, the rise of Agile methodologies in the latest
decades has changed how people perceive and go about their work, as well as
how companies encourage their employees to behave [5]. According to the annual
State of Agile report, Scrum was the most practiced Agile framework of all,
and many companies already had some form of distributed Scrum within their
organizations [6]. Furthermore, the rate of project success using Scrum was
reported to be 60% higher than projects utilizing the traditional approach [7,
8]. However, the pandemic caused many companies to adapt to a fully remote
work environment, putting Scrum practices under different strains.

Studying the existing literature, we found that Scrum used for remote work has
mainly been studied in the context of Distributed and Global Software
Development, the focus being on how Scrum can be adapted to support a
distributed working environment, commonly among co-located teams [9]. However,
the literature is scarce on how Scrum and the projects’ success were affected
by organizations switching to working fully from home to adhere to the new
pandemic restrictions. That being said, our study aims to identify the impact
that working from home had on software project success through Scrum
practices. In our paper, the terms remote work and working from home are used
interchangeably, as there is no other way of remote working than working from
home during the pandemic. Hence, we want to clarify that throughout this
study, our focus is on working from home rather than remote working.

Through a Multi-Method approach, we performed a qualitative survey with people
working from home within software development Scrum projects to understand the
phenomenon better. We proposed a theoretical model that we attempt to
generalize through a sample study with 138 Scrum workers using Partial Least
Squares Structural Equation Modeling.

In the remainder of this paper, Section 2 discusses related work. First, the
research design is presented in Section 3, illustrating the methodology this
paper is based on. After that, Section 4 encapsulates the qualitative phase,
referring to the exploratory study’s data collection and analysis. Followed by
the quantitative phase in Section 5, where the model is constructed and
evaluated. Next, the findings of our study are presented in Section 6,
together with its limitations. Finally, Section 7 discusses future work as
well as our conclusions.

##  2 Related Work

In the official Scrum Guide, Sutherland and Schwaber [10] do not mention if
Scrum can or cannot be used in the context of remote working. However, the
literature on the topic argues that Agile practices, including Scrum, are
meant for co-located working environments and that they present challenges in
a distributed context, causing the necessity to adapt Scrum accordingly [11,
12]. Moreover, prior research has shown that “only a small number of
guidelines are systematically followed, and that some guidelines are rarely
followed consistently” [13], suggesting that each organization’s Scrum
implementation might differ from the guideline recommendations.

Prior research investigating Scrum concerning remote work targets distributed
projects, also called Distributed Software Development and Global Software
Development, where the focus is on how Scrum can be adopted and why it can be
a good fit considering its benefits and challenges [14, 15]. The majority of
papers discuss the challenges that distributed work creates in software
engineering and how Scrum, with or without modifications, can address and
mitigate these challenges [16]. The predominant theme is centered around co-
located teams, mainly providing offshore software development services, which
commonly implies working from different geographical locations within
different time zones [17, 18]. This requires Scrum to be adapted to support
the coordination of the teams despite the challenges bridged by the
geographical dispersion and the size of the projects [19, 20, 21].

Another general topic in the literature is how Scrum can be scaled for Global
Software Development since it generates new challenges such as communication
and coordination overhead [22]. Some of the solutions found for mitigating the
issues, as mentioned above, between multiple teams include: adding new events
such as Scrum of Scrums for larger teams [23], regularly visiting other sites
for better process alignment [16], using online tools for keeping the backlog
and documentation up to date within teams [24] and conducting meetings online
or via phone between remote teams [21].

Throughout the literature, researchers display ways of adapting and expanding
Scrum practices to mitigate the challenges generated by distributed software
development of geographically dispersed co-located teams [25]. However, the
perspective of everyone involved in a Scrum project working remotely, even
within co-located teams, is missing from the literature. Some papers bring
forward suggestions that could be adapted for this situation, such as virtual
meeting rooms and fully remote Scrum events [16]. However, how the Scrum
practices were impacted by the entire company working remotely remains to be
thoroughly researched. For example, a recent action research study within a
Brazilian start-up portrays how they managed to migrate to being fully remote
to accommodate the COVID-19 restrictions [26], yet a theoretical model remains
to be developed and evaluated.

Moreover, most of the literature on distributed Scrum focuses either on
successfully adapting or adopting the framework in a remote context, without
accounting for the project’s success. For example, Hassani-Alaoui et al. argue
that “if Scrum is easy to learn but difficult to master, scaled scrum is even
more difficult to master, and conducting it improperly could have consequences
for project success” [13], suggesting that the adjustments made to accommodate
the remote context may alter the project success.

Shared understanding, a challenge seen in the remote Scrum contexts caused by
the communication impediments, has a significant effect on project success
[27]. However, Hummel et al. “did not find a significant moderation effect of
team distribution on the effect of shared understanding on project success”
[27], indicating that co-location is not necessary for effective communication
as long as the proper tools are in place [27]. This finding suggests that
besides the adaptions to Scrum, organizations must provide appropriate
technological resources for remote contexts [28].

Thus, our study differentiates from the existing literature by analyzing how
Scrum practices are related to project success and what is the impact caused
by the sudden change to remote working, which imposed everybody on working
from home and eliminated the possibility of a co-located working environment.

##  3 Research Design

Our study aims to get a better understanding of the impact of working from
home on Scrum and if it affects the project’s success. For that, we employ a
Multi-Method research approach, consisting of two phases as seen in Figure 1.
The benefit of using a Multi-Method approach is profiting from a research
strategy’s advantages while mitigating its weaknesses through the usage of
another strategy [29].

Figure 1: Design of the two-phased study

For Phase I, we employed an exploratory qualitative survey approach as
described in the ACM SIGSOFT empirical standards [30], consisting of semi-
structured interviews with Scrum practitioners. As the prior knowledge about
the topic under research is limited, the inductive technique is suitable [31].
We aim to collect enough data in order to understand the phenomenon and
quickly draw our findings directly from the responses [32]. The semi-
structured approach allows us to respond to and then ask further questions
regarding what the interviewees answered, instead of completely following a
predefined set of questions [33]. The responsive dynamic of semi-structured
interviews aids in connecting with the interviewees and treating them as
conversational partners rather than research objects [33]. To synthesize and
analyze our findings, we use Gioia [34] as a data analysis technique. The
qualitative phase is detailed in Section 4.

Phase II complements and validates the qualitative study from the first phase
by developing a theory and evaluating it through a quantitative sample study
[35]. Within this phase, we employ a theory-building method to construct on
the findings of the exploratory study as well as the literature, culminating
in a theoretical model consisting of a set of hypotheses that are evaluated
using Partial Least Squares - Structural Equation Modeling (PLS-SEM) [36]. The
hypotheses are evaluated on a sample study consisting of 138 Scrum workers.
During this stage of research, the researcher is distanced from the observed
constructs and statistically examines them [37]. As the investigation’s point
of view is objective, and the hypotheses have been empirically validated, the
study’s findings are generalizable and independent of time, and context [37,
38]. We discuss the quantitative phase in Section 5.

We employ this research design to address the following research question:

######  RQ.

Do Scrum practices affect software project success while working from home?

##  4 Phase I: Qualitative Study

In the first phase, we followed ACM SIGSOFT empirical standards [30] for
conducting qualitative surveys and used Gioia [34] as the data analysis
technique. This section presents the qualitative data collection and analysis.

###  4.1 Qualitative Data Collection

The pandemic context affected the data gathering process because the enforced
lockdowns made it impossible to perform face-to-face interviews with
participants even where geographically possible. For this reason, we had to
adjust and create an online strategy for gathering interviewees and conducting
the interviews.

The data is comprised of 12 interviews with people working remotely with Scrum
within software development departments. To make it more enticing for people
to participate in our study, we devised a small sign-up questionnaire (found
in the Appendix, Figure 7) that was meant to both filter out people who did
not meet one of the requirements (i.e., having worked remotely within a Scrum
project), and also let the participants choose their preferred interview time
via a Calendly111https://www.calendly.com link received upon completing the
questionnaire and passing the criteria.

The questionnaire was posted on various social media websites, ranging from
LinkedIn (and specialized Scrum-oriented LinkedIn Groups) to Facebook, and we
also used our networks of family and friends to find interviewees. In
addition, we contacted over 30 local Danish companies to participate, but
unfortunately, none were interested.

The questionnaire was completed by 26 people, out of which four did not meet
the requirements to participate. The 12 participants signed up through the
link, and the rest of the ten qualified people received personal invitation
e-mails but chose not to participate. An overview of the participants can be
seen in Table 1, and a snapshot of the questionnaire is available in A. The
interviews lasted between 20-35 minutes and were conducted and recorded via
Zoom or Microsoft Teams, and then transcribed for analysis using
Konch222https://www.konch.ai. The transcripts were all further manually
checked for possible errors created by the software, such as misinterpreted or
missing words.

P# | Scrum Role | Years of Scrum | Country
---|---|---|---
|  | experience |
1 | Scrum Master | 1-3 | India
2 | Developer | 1-3 | Romania
3 | Developer | 1-3 | Denmark
4 | Scrum Master | 3-5 | Indonesia
5 | Scrum Master/Product Owner | 5+ | USA
6 | Developer | 1-3 | Denmark
7 | Developer | 1-3 | Denmark
8 | Developer and Scrum Master | 3-5 | Denmark
9 | Developer | 5+ | Hungary
10 | Developer | <1 | Romania
11 | Developer | 1-3 | Spain
12 | Developer | 1-3 | Denmark
Table 1: Participants distribution in the exploratory study

The interview questions were designed to cover all aspects of Scrum -
artifacts, events, and roles in comparison with working from home and on-site.
Within the interviews, all the participants were asked about themselves, their
workplaces and to describe their usual way of doing Scrum (most common before
the lockdown), followed by a simulation of a current sprint, in the hopes of
creating a space for them to think about and reflect upon their current Scrum
process. The interview structure can be found in B.

###  4.2 Qualitative Data Analysis

To analyze the data, we used Gioia methodology [34] as a data analysis
technique. However, given the qualitative exploratory direction of our
research, throughout the process, we did not iterate between data collection
and analysis or used theoretical sampling [30]. Instead, we aimed to
investigate how working from home affects Scrum projects inductively. For this
reason, our goal in employing Gioia is to provide a systematic strategy that
proved effective when performing our study and to assist readers in perceiving
the rigor of our concept creation and progression to our conclusions.

We have begun the analysis by iteratively going through the transcripts and
condensing information from the text in medium-sized codings while keeping
informant terms (using participant’s own words in the codings) to construct
the 1 order concepts [34]. The transcripts were coded with the research
question in mind, focusing on what the participants voiced impacted their
Scrum project the most while working from home. As such, each code summarizes
the actual impact the interviewees observed, felt, or experienced remote work
had regarding any role, event, or artifact of Scrum, as compared to how these
practices were enacted before the COVID-19 pandemic.

During the 2-order analysis, we begin to look for similarities and contrasts
across the several concepts (akin to Strauss & Corbin’s [39] concept of axial
coding) in order to reduce their amount to a more manageable number [34]. The
emerging themes will help us describe and explain the phenomena we observe
[34]. Our analysis yielded a set of 17 2-order themes seen as the underlying
impacted areas, which were further distilled into six aggregate dimensions.
The result is a data structure presented in Figure 2 and Figure 3. The data
structure not only helps us to construct our data into an understandable
visual aid, but it also gives a graphic depiction of how we proceeded from raw
data to 1-order concepts, 2-order themes and aggregate dimensions while
completing the analyses, which represents an important component of proving
rigor in qualitative research [34].

The use of Scrum, project success and home working environment were each
compiled as different dimensions (Figure 2) together with three additional
ones (Figure 3) which reflect the impact of working from home on the
individual through three innate psychological needs, further identified within
the Self-Determination theory [40], i.e. need for autonomy, need for
competence and need for relatedness.

Figure 2: Data structure of use of Scrum, project success and home working
environment  Figure 3: Data structure of the three innate psychological needs

We uncovered that the impact of remote work was most visible on the Scrum
Team, more specifically on the individuals comprising the Scrum Team. This
finding allowed us to look at the events and artifacts through a different
lens, making it clear that what the participants voiced about events or
artifacts were simply manifestations of the affected individuals. In addition,
we uncovered that the impact felt at the individual’s level had implications
in how the events were carried out, which also contributed to how the
individuals were affected, creating a cycle that either positively or
negatively affected Scrum as a whole. This concept in which working from home
indirectly affected Scrum through its people was brought to life through the
three psychological needs. The analysis made it more evident that working from
home involves challenges for the individual, portrayed as three innate
psychological needs: autonomy, competence, and relatedness. Russo et al.
identified the exact three needs to be predictors of well-being and
productivity among software developers working from home during the COVID-19
pandemic [41]. Moreover, together, the three psychological needs are
”essential for facilitating optimal functioning of the natural propensities
for growth and integration, as well as for constructive social development and
personal well-being” [40] as defined by Ryan et al. in their Self-
Determination theory. Thus, the impact of working from home on the individual
can be rightfully reflected through the three psychological needs.

Furthermore, the three dimensions related to the psychological needs indicate
that working from home had a considerable effect on the individual, which is
emulated into the use of Scrum and the project’s success. Therefore, the
remainder of this subsection details each dimension individually.

####  4.2.1 Use of Scrum

It cannot be generalized how the Scrum practices were impacted by working from
home, as most companies have different ways of implementing and using Scrum
within their organization [42]. However, many interviewees voiced that their
Daily Scrums were extended compared to the on-site version, which can be seen
as a generalizable finding.

> Since the pandemic, the team decided to extend the time for daily Scrum. So
> after 15 minutes, they will close the daily Scrum and have extended 15
> minutes to have a discussion as a confirmation session.  (P4)

While some companies only extended the scheduled duration of the Daily Scrum,
other added additional events. The common reason being to enforce team
communication and maintain the transparency of what everybody is doing, which
is one of the three pillars of Scrum [10]. Other reasons include allowing
people from different teams to see each other using additional events such as
Scrum of Scrums or just giving people the possibility of having an informal
conversation before starting the workday. Although seen as something new as an
effect of the sudden change to remote working by many people, additional and
extended Daily Scrums are a common adaptation of using Scrum in a remote
context, as noted in the literature [25]. Furthermore, daily Scrums are an
essential part of a healthy Scrum implementation; they ”improve
communications, eliminate other meetings, identify impediments to development
for removal, highlight and promote quick decision-making, and improve the
Development Team’s level of knowledge” [10].

> There are days in which I have been maybe working from home where out of the
> three people in the team, maybe with one or two of them, we didn’t talk at
> all in the rest of the day after the daily.  (P11)

Given that the communication between the co-workers decreased throughout the
day [43], Daily Scrums became even more critical as some people would only get
to communicate and share their progress through this event.

Regarding the other events, the interviewees perceived that their output was
affected because of the decreased engagement and motivation of the
participants. More particularly, the online experience of the Sprint
Retrospective was not as pleasant as the on-site version for many
interviewees. For this reason, Scrum Masters had to improvise and create new
games to motivate the Development team and keep them engaged during the event.

> Um, I don’t like that (remote Retrospectives). We have done it a couple of
> times using online tools. But there’s a component missing for me, like the
> human aspect, where you want to be honest and you got to express your
> feelings and all that.  (P12)

Moreover, the Sprint Planning meetings were also affected by the decreased
engagement of the Development Team caused by the communication channel. Some
interviewees voiced that their planning meetings were not as detailed as
before because people would not pay attention.

> You can hide easier and do something else when you’re remote and when you’re
> here (on-site office), you kind of have some sort of obligation to listen to
> the people in front of you.  (P12)

The biggest challenge of the remote events perceived by the individuals in
maintaining their focus on the topic and trying to engage in the conversation
has its challenges while looking at or talking to a screen. Whereas in the on-
site environment, the engagement is kept by a face-to-face conversation
between the team, when working from home, it is very easy to get distracted
and do something else on your machine while the other participants are
talking.

The increased number of meetings had equally impacted the Product Owner and
the Scrum Master.

> What impacted me as Scrum Master. The level of my confidence dropped because
> I feel like I don’t contribute anything to the company. And this happened
> because I need to have more meetings than before. For example, I cannot do
> something big because I have to accompany my product manager to have an
> ideation session. […] So most of my days, I have a call rather than create
> something or observe the process.  (P4)

Both roles struggled to accommodate the new communication channels, which
initially caused an increase in scheduled meetings. This, in turn, caused
people to lose their confidence when unable to perform their role’s duties due
to the increased amount of meetings required to carry to support the business.
Remote work has had a multi-sided impact on the Developers, consisting of many
different underlying impacted areas. One element that was consistently missed
by the participants is the physical interaction provided by sharing office
spaces. Some argued that the interaction between the Developers changed
because of working remotely:

> There was less interaction or less direct interaction, and you couldn’t
> always see what everyone was doing, and they couldn’t see what we were
> doing. Sometimes we had to wait until the demo or until the daily stand up
> next day to see progress.  (P3)

This has also resulted in a decrease in the quality of shared information and
transparency among Developers, which has resulted in a decrease in the quality
of the ambient knowledge intrinsic within teams.

Despite the product and sprint backlogs being two different artifacts within
Scrum, no participant differentiated the two in our discussions. For most
participants, the terms were interchangeable, and working with either backlog
was also interchangeable due to the backlogs being in digital format in Jira
or Trello. This is also why many participants felt no difference in
interacting with the backlogs, as they were using online tools for managing
their backlogs since before remote working, even though everybody used to have
physical backlogs. However, some individuals miss the physical activity of
interacting with the backlog, as having it in a digital format prevents them
from having some sort of physical activity within a desk-job, as well as
keeping them from quickly seeing a status of the Sprint, what each member is
doing and who is available:

> I can see that there was a difference being done to physical activity like
> an on-site used to perform. I mean, sticking on the board, seeing what
> everyone was doing, like story points. […] So that is the part which is
> missed.  (P1)

> Before, in office, I created a physical board, right? So we can see other
> people, what they are doing—and moving the ticket, so they have some
> physical activity. But during this pandemic, they cannot see other people -
> what are they doing at this time? And when they need help, it’s hard to get.
> (P4)

Thus, the impact that working from home had on the use of Scrum is requiring
the Scrum Team to consolidate and adapt the events, roles, and artifacts to
mitigate the challenges caused by the remote context. The adaptations
regarding extended events, introducing new ones such as Scrum of Scrums, and
employing online tools for task management are similar with the ones seen in
the distributed Scrum literature [16]. This implies that Scrum can be applied
to remote projects with no significant changes as long as people adhere to the
framework’s values and principles, but the official guidelines must be
modified to better depict how Scrum can be used in a remote context.

####  4.2.2 Need for autonomy

The need for autonomy is an important aspect of having motivated employees. An
autonomy-supportive context allows the individuals to feel competent, related,
and autonomous, positively affecting their performance [40]. In addition,
working from home brings more flexibility over how and when the employees are
completing their tasks, which is associated with more productivity and more
engaged work to reward the employer for the flexible work arrangement [43].

> I am more relaxed when I get up in the morning, and this seems weird, but
> there is the option where you can say ”I’m working from home,” and then you
> can sleep one more hour because that’s usually what you would spend to go to
> work. I think actually it gives you like a nice space buffer in your head
> saying like ”OK, I’m going to work from home today because it seems like
> it’s pretty windy”.  (P12)

Many people are forced to work outside of their prime hours by having to be
present in the office at predefined hours, but working from home offers the
freedom some seek in managing their own schedule and working when they feel
more inclined to.

> I see a huge time saving by not having to commute because it usually adds up
> to almost two hours every day. So, well, then I save two hours from my life
> every day.  (P6)

> Something as simple as having 40 minutes of commute either way. And so those
> 40 minutes are spent working when I work from home.  (P8)

Many interviewees voiced that working from home saves precious time each day,
which can be used for either working or doing something else not work-related.
For those whose commuting time takes more than two hours, it eventually adds
up to at least 10 hours spent on work-related activities in a day. Thus,
working from home brings a great benefit by removing commuting altogether from
the equation, allowing people to have more time for their personal life.
Moreover, the flexibility and better time management resulted from working
from home allows people to intertwine work and family life, giving them an
advantage in meeting household needs [44].

On the other hand, working from home hinders the individual’s interaction with
his co-workers and the ability of the management to monitor the employees,
creating more significant opportunities for work avoidance [43]. Thus,
organizations should ensure contextual supports of autonomy for their
employees and portrait working from home as an alternative to on-site
development, rather than an escape from a controlled environment [40].

####  4.2.3 Need for competence

Together with optimal challenges, contexts related to social events, such as
feedback and communication that aid the feeling of competence while doing a
task, can intensify the motivation to complete the task [40]. Working from
home impacted the individual’s motivation and feeling of achievement,
challenging their perceived competence levels. As part of the Self-
Determination theory, the need for competence and need for autonomy facilitate
the vital expression of human growth tendency [40].

> My confidence level dropped because I feel like I don’t contribute something
> to the company, and my work is becoming smaller and smaller.  (P4)

The reduced amount of social interactions made people feel disconnected from
the process and project objectives, leading them to detach even more from
their work which they believed is insignificant. Other people perceived their
tasks as boring when having to do them from home.

> They were bored at home; they couldn’t work from home anymore. They needed
> the office.  (P2)

For some people, the seclusion makes them lose interest and motivation to
complete their tasks and perceive their work as boring [41]. This is
understandable for those working in functions or projects that require
continuous communication, but it is also understandable for those who are
lonely at home and miss the social context of the office, as lonely people
report higher levels of boredom [45]. Either way, boredom is a result of their
reduced motivation which affects their perceived competence.

> I ask one person all the time and then imagine I make some code that’s
> causing a problem. And it’s not until the moment when this other person in
> the team, that knows about these corner cases, has to review it, and then he
> would give his feedback, and I would need to go back and redo and then show
> again. […] It is more difficult to gather all the knowledge or all the
> feedback that you need until you know that the product is good.  (P11)

The async communication between fewer people impacts the individual’s
perceived competence, as feedback is received late in the process. The
struggle to gather all of the necessary information and the lower quality
feedback received throughout the completion of a task delays and obstructs the
entire process of formulating and solving a task, perceived as difficult by
the individual whose sense of competence is hampered.

####  4.2.4 Need for relatedness

The need for relatedness was challenged for some remote workers. Individuals
are more likely to carry out activities that present interest for them or
other individuals with whom they relate to [40]. While working from home, most
people perceived a great impact on the communication with their colleagues,
which spawned different discrepancies in their usual way of working. For
example, the ad-hoc conversations from the office became more formal. Given
that just tapping on someone’s shoulder and asking for help was no longer
possible, meetings had to be scheduled and sustained through an online
communication tool. Another observed impact was on individuals feeling left
out or alone or needing someone to talk to. The Developers started initiating
one-on-one meetings with their peers, but also with the Scrum Master or
Product Owner in an attempt to maximize their well-being as individuals.

> We have more regular one-on-one sessions; even between the teams, they
> create a regular session with their peers. Before, when working from the
> office, they have rarely done that. I think they have one on one sessions
> because they need someone to talk to.  (P4)

The number of people an individual would have a conversation with during the
day decreased to only a few close colleagues, or superiors [43], forming more
closed circles and increasing the bond between some people. However, affecting
the overall transparency and the quality of the project’s shared information
while also discouraging individuals from starting conversations with other
people outside their close circle. Moreover, some Developers’ way of relating
to the Scrum Master has also been changed compared to the on-site environment.

> There were times when he (Scrum Master) would have meetings and stuff like
> that, and he would just disappear from our place. This made us feel like he
> was way more superior or something like that, the fact that he could always
> leave the office. But during working from home, I didn’t get that feeling at
> all because I wasn’t seeing anyone around to notice if they’re missing.
> (P2)

As previously mentioned, while working from home, the individual interacts
less with his co-workers [43], making the perceived superiority of other
people hinder as the individual is more focused on their work and also
creating a sense of equality among the co-workers [46]. Another form of
equality was brought up by the whole team communicating through
telecommunication tools from their home, which made people relate more to
their peers by having a small glimpse into everybody else’s private life
through seeing their home office set-up. Thus, the social aspects present in
the office were diminished by people working from their homes. The findings
are also supporting the literature, as the Self-Determination theory requires,
besides the autonomy and competence needs, a third innate psychological need
for relatedness to produce motivation [40].

####  4.2.5 Home working environment

For many people, before COVID-19 caused everyone to work from home, they would
not have an appropriate designated space for a home office set-up, making it
harder to accommodate remote working at first. For this reason, people had to
create a home working environment from where they can adequately do their job.
Depending on their household situation, some people were forced to improvise
an office and work from their sofas, beds or even kitchen tables [47].
However, even though ergonomics are not significantly related to well-being or
productivity [41], improving comfort can help avoid future health issues. More
importantly, to do their job, employees must have access to the proper virtual
tooling.

> Since our way of working was already entirely digitized, we had a digital
> scrum board, held meetings online, and so on, it wasn’t big of a change.
> (P6)

Luckily, most organizations were already using online tools for communicating
and task management, which made the transition to working from home smoother
[48]. However, one big challenge of working from home is to avoid getting
distracted and stay motivated [41].

> If I’m on a call, we’ll do our sprint planning, and just trying to get
> everybody’s attention for more than an hour is hard. You have kids working
> at home, you know, on their schoolwork. You have dogs barking and all kinds
> of noises. Doorbell’s ringing Amazon deliveries. So it’s a lot more
> distracting, and then it’s harder to get everybody back together if we have
> questions or need more information.  (P5)

The participants voiced that it is difficult to avoid being distracted by what
is going on around them unless they live alone or can appropriately seclude
themselves from the rest of the people in their house. Everyone is focused on
working at the office; however, this does not apply to the home working
environment. The distractions can deteriorate the communication between the
team members and have consequences on the overall project success. Another
effect of the way people communicate when working from home is an increase in
the number of formal meetings [41], as time has to be better managed between
people who only see each other through online tools. Meetings became more
formal and scheduled to accommodate the asynchronous way of communicating
online and avoid overlapping schedules. This gives people the impression that
the number of meetings has increased because the previously ad hoc
conversations have now become a time slot in their calendar.

> And then you also, of course, have the people that are late because they
> have children and their children have to go to school, or maybe they are
> arriving home, so they have to break it up in the middle of the daily stand
> up.  (P7)

The formal meetings are very defined on a topic and have to be scheduled to
accommodate everyone’s household duties schedule, particularly for the
individuals living with their family. Another challenge brought up by working
from home is the disruption of the work-life balance.

> I’ve had colleagues who said that they liked going to the office because it
> made it easier for them to have a schedule, and it brought more balance in
> their work and personal life in the sense that when they were working from
> home, they lost track of time. And most often, they worked too much, and
> they didn’t realize that it was eight p.m. and they were still working.
> (P10)

More particularly, without a clear working schedule, people got sucked in
their work and stopped keeping track of how much they are working or used
working as a coping mechanism for the ongoing pandemic [41]. This produced a
spike in their perceived productivity as they were completing more tasks, but
it affected their work-life balance. The ritual of having to commute to work
and back was a clear delimiter for when to stop working for the day, yet it
lacks in the home working environment.

####  4.2.6 Project success

The project success was also affected by the communication impact, as online
communication is not as expressive as face-to-face, people had to optimize the
way they share information between them. The communication became more formal
and had to be more efficient and on point, but it affected some individuals’
feelings. Especially making it harder for introverts to be included in social
events as the former casual conversations and water cooler banter almost
disappearing in the remote environment [41].

> The backend developers, we are cooperating less because someone is always
> working from home. We’re not doing a lot of pair-programming, and we started
> taking on bigger tasks individually and working on those alone during the
> Sprint because then you don’t really need to communicate a lot to each
> other.  (P7)

Since the communication between people was affected, their collaboration also
presented some discrepancies. Popular on-site pair-programming sessions are
less common remotely because people may better focus on their job and may no
longer require assistance or find it more difficult to reach out to others for
help. The collaboration discrepancies directly impact the project’s success,
as the shared feedback between co-workers decreased due to always having to
communicate and collaborate through an online communication tool. When people
are not in the same office, they tend to reach out less often for help as they
never know what their colleagues are doing at that time [43]. Even if they do
seek assistance, there is no way of predicting when the recipient will respond
due to the async nature of the communication.

> I don’t have to drive into the office anymore. I mean, I can turn my laptop
> on at seven a.m. and, you know, some days I finish off at four, some days I
> just work, maybe don’t take a lunch. I mean, where am I going to go? So I
> think people are more productive because they can dedicate more time to
> working.  (P5)

People also observed a productivity improvement when working from home, which
can be explained in various ways. A big struggle for most remote workers was
to separate their work, and personal life [41]. Working from home created a
shift in their work-life balance, and some people felt so connected to their
work that they did not know when to stop working for the day. When working
from the office, there is a clear distinction of when the workday ends, but
working from home allows for more flexibility, which was hard to manage. Thus,
one reason for the productivity spike is that people worked more hours [49]
and the overall productivity of the project increased. However, this cannot
guarantee if people were actually more productive or they had to work more to
achieve the same results. Another reason is that working from home provides
for better time management and helps employees to organize their work better.
Because there were fewer work interruptions, the planned meetings, rather than
ad hoc discussions, helped people focus on work for longer periods of time.

> The productivity even has increased because the colleagues are even happier
> while working from home and are given more hours.  (P1)

> I am more productive, that’s for sure. These two things are connected
> because I’m more productive, which might boost myself because I’ve got this
> much amount of work done, and then I will work more because I’m boosted by
> this experience.  (P9)

Moreover, people felt better when they worked from home, and because well-
being is related to productivity, the home environment had an influence on
people’s productivity, which is strongly tied to project success. One obstacle
that can endanger the project’s success is the reduced amount of shared
information resulting from the collaboration discrepancies.

> I think you’re more prone to be the middleman where you kind of you write
> something to someone, and then you get a response and you write something to
> someone else and then you’re the one sitting with all the information.
> (P12)

Especially in a Scrum project, where transparency is one of the framework’s
pillars [10], the decreased amount of shared information can negatively affect
its success. On the other hand, a streamlined communication method in which
shared information is clear to all team members decreases the odds of errors
and does not prolong the feedback process, boosting the quality of the
development process and the project’s likelihood of success.

##  5 Phase II: Quantitative Study

In the second phase, we used existing Scrum literature and previous phase
findings to develop a set of hypotheses that are integrated into a single
theoretical model to improve our understanding of the relationship between
working from home and the success of Scrum projects. The model is evaluated
using Partial Least Squares – Structural Equation Modeling (PLS-SEM) following
Russo & Stol’s guidelines [36]. The goal is to use quantitative analysis to
triangulate the findings of our qualitative phase. This section depicts the
specification of the model and its assessment using a sample study and PLS-
SEM.

###  5.1 Theory Development

The first goal of the quantitative phase is to develop the theoretical model,
which will be evaluated with PLS-SEM.

####  5.1.1 Partial Least Squares – Structural Equation Modeling

Partial Least Squares – Structural Equation Modeling (PLS-SEM) is a
multivariate statistical analysis used to evaluate latent and unobserved
variables, also called constructs, using multiple observable indicators or
items [50]. It is an emerging inquiry approach in empirical software
engineering [36, 51, 37] and is best suited for exploratory theory development
investigations [52].

Every PLS-SEM model has two sub-models: a structural model and a measurement
model [36]. The structural model, as shown in Figure 4, is made up of several
constructs and their relationships define the research hypotheses. The latent
variables might be exogenous (predecessor), endogenous (target construct) or
mediators [36, 37]. The items are measured through the measurement model using
data collected, most often, through a survey.

We chose PLS-SEM for this study given its suitability for exploratory studies
[52] and to allow us to not only observe the direct relation between our
constructs but also understand what causes the relation. Furthermore, we can
evaluate the mediation effects between our latent variables, making PLS-SEM
the best choice for our study.

####  5.1.2 Specification of the Structural Model

The first step in PLS-SEM is to specify the structural model by defining a set
of hypotheses [36]. The hypothesis formulation draws from both the literature
and the qualitative study.

The working environment has an impact on the individual’s motivation and
productivity [53, 54]. Working from home has both positive and negative
aspects. The positive ones include enabling employees to focus more on their
tasks, as the contact with their co-workers is significantly reduced [43].
Research shows that while working from home, employees are interrupted less
often [55]. Furthermore, teleworking gives employees more flexibility in terms
of where they work from, how much work they do, and how they organize their
time to complete their tasks even outside of the official office hours [56].
The results of the first phase show that employees felt more productive while
working from home, which can be attributed to the autonomy that teleworking
provides [57]. While the findings from the exploratory study show that some
employees did not feel motivated when working from home, this can be seen as a
result of the ongoing pandemic, and the sudden change to enforced working from
home [41]. Studies show that mixing online and offline working environments
can help increase employees’ motivation and engagement and that online
communication tools are seen extremely well, especially by the Millennials who
are now joining the workforce [53]. As such, the hypotheses associating the
three psychological needs with the home working environment are:

######  Hypothesis 1a.

Need for autonomy is positively associated with the Home working environment.

######  Hypothesis 1b.

Need for competence is positively associated with the Home working
environment.

######  Hypothesis 1c.

Need for relatedness is positively associated with the Home working
environment.

The findings of the qualitative study show that working from home impacted the
use of Scrum, particularly on some of its events. The literature on the topic
argues that Agile practices, including Scrum, are meant for co-located working
environments and that they present challenges in a distributed context,
causing the necessity to adapt Scrum accordingly [11, 12]. As previously
mentioned, the adaptations some Scrum events undergone while people had to
work from home are similar to the adaptations that a distributed Scrum team
has to enforce to support the communication between geographically dispersed
co-workers [19]. The working environment plays a big role in how people
interact which each other, and working from home impacted the transparency
between the people in the Scrum team, causing Daily Scrums to be extended or
even requiring better documentation practices, effects also seen on
distributed Scrum projects [25]. The remote context has repercussions on the
freedom and frequency of communication between team members, growing the
chance of individualism, which threatens the use of Scrum [58]. Moreover,
working from home brings difficulties related to teamwork, collaboration, and
collective responsibility [58]. The 2 hypothesis is:

######  Hypothesis 2.

Home working environment is negatively associated with the Use of Scrum.

Project success is an important theme in project management literature, but it
lacks a widely agreed definition of what success is [59]. Traditional criteria
such as time, budget, and quality, forming the ”iron triangle,” can be a good
representation of the success of the management of the project but cannot
necessarily reflect the success of the project itself [59]. Shenhar et al.
argue that between the three traditional dimensions of project efficiency
(time, budget, and scope), the scope has the largest contribution in shaping
the success of a project [60]. Thus, besides scope being an aspect of project
efficiency, it also has an impact on the customer, and their satisfaction
[61]. In software development, the success metrics can also include
stakeholder success [62, 63], including satisfaction of the customer [64],
team, meeting organizational goals [65] and strategic success/value [64].
According to a global report [7], it was found that the percentage of project
success using the Scrum approach was 60% greater than projects that use the
traditional approach in 2018 [8]. While the above metrics are important to
define the success of a project formally, the success factors of an Agile
project might be nuanced differently as indicated by Russo [37].

In an Agile project, such as Scrum, the success factors include Product Owner
involvement, Scrum Master leadership, top management commitment, and
Developers’ skills [37]. Ken Schwaber and Jeff Sutherland, the creators of
Scrum, promote that ”the essence of Scrum is a small team of people” [10] and
that Scrum is ”a framework within which people can address complex adaptive
problems, while productively and creatively delivering products of the highest
possible value” [10]. There is no silver bullet recipe for implementing Scrum,
and each company can have varied ways of using Scrum [25]. Moreover, even
though there should be a Scrum Master to promote and support the good use of
the framework within the project, the self-organizing Development Team
(Developers) is responsible for managing their own work [10]. Thus, the use of
Scrum within a company is associated with the project success, stemming the 3
hypothesis:

######  Hypothesis 3.

Use of Scrum contributes to Project success.

The home working environment influences the way employees sustain their day-
to-day work activities, which may, in turn, affect the project success.
Building on the qualitative study, the communication, and collaboration
between employees present challenges when people are working from home,
findings also confirmed by the literature on remote Scrum projects [21, 16].
However, working from home is not always seen as a challenge for software
engineers [41], which was also the case for the people interviewed who
indicated increased productivity while working from home. Moreover, people
spend more time working instead of commuting when they are remote, which is
directly affecting project success [66]. Thus, the 4 hypothesis states:

######  Hypothesis 4.

Home working environment contributes to Project success.

The literature suggests that using Scrum can help mitigate the challenges
brought by remote contexts [18], indicating that the use of Scrum can be seen
as a mediator between the home working environment and project success, rising
the 5 hypothesis:

######  Hypothesis 5.

Use of Scrum mediates the relationship between Home working environment and
Project success.

Figure 4: Proposed theoretical model

Figure 4 presents our theoretical model, where ovals represent the constructs
and the hypotheses are represented by single-headed arrows.

####  5.1.3 Specification of the Measurement Model

The second step is to specify the measurement model, that is, identify
suitable measurement instruments for each non-observable variable [36]. The
model’s constructs are defined below, indicating what each construct entails
and what is its measurement instrument. The complete list of each construct’s
items together with the references used to frame the questions can be found in
LABEL:table:items in the Appendix.

All the responses were given on a 7-point scale ranging from 1 (strongly
disagree) to 7 (strongly agree).

##### Need for autonomy, Need for competence and Need for relatedness

The autonomy, competence and relatedness needs of the Self-Determination
theory [40] were measured using the 18-item balanced measure of psychological
needs scale [67].

##### Home working environment

The home working environment construct concerns distractions, noise, comfort,
ergonomics, ambient, tooling, office set-up, and the social aspect of working
from home. It is measured using nine items adapted from The Work Design
Questionnaire (WDQ) [68], Danielsson et al. study of office environment
satisfaction [69] and Russo et al. study of predictors of well-being and
productivity of software professionals [41] to reflect the home working
environment.

##### Use of Scrum

The use of Scrum concerns the implementation within an organization of Scrum’s
roles, events, and artifacts as defined in the official guide. It is measured
using 15 items created from the Scrum guide [10]. The responses reflect the
extent to which the participants’ Scrum implementation relates to the
statements.

##### Project success

The project success construct concerns the process, deliverable, and business
success. It is measured using three items from Russo’s Agile Success Model
[37].

###  5.2 Sample Study

After specifying our research model, we can concentrate on the empirical
confirmation of our study hypotheses. Thus, we conducted a sample study, which
is the best research strategy for generalizing a research model [70].

####  5.2.1 Survey Data Collection

We used G*Power [71] to do a priori power test to determine the minimal sample
size. According to this analysis, the smallest size for six predictors with an
effect size of 15%, significance of 5% and power of 80% is 98 (Figure 8).

Prolific333https://www.prolific.co/, a data collection platform meant for
academic purposes with over 146,000 active users, was used to gather the data
using a cluster sampling approach [72, 37]. Prolific offers various benefits
over other data collecting platforms, such as email lists, replicability, data
quality, and reliability [73, 74], and is widely used in computer science as a
data collecting platform [37, 75]. To reduce response bias, the survey was
conducted using Qualtrics444https://www.qualtrics.com/ with randomized
questions within their blocks [72, 76]. Following The Day Reconstruction
Method (DRM) by Kahneman et al. [77], the questions within the survey were
phrased such that people would reflect on their last project where they used
Scrum while working from home.

To ensure the quality of the data, we added competence screening questions and
random attention checks. The competence screening part included questions from
Danilova et al. [78] and aimed to filter out people who do not meet the
software engineering knowledge requirement. Attention checks were randomly
inserted between questions to ensure the reliability of the answers. From a
total of 200 completed responses, we filtered out 62 candidates who either
failed the attention checks or the competence screening, summing up to 138
valid responses, which is above the minimum sample size.

####  5.2.2 Sample Description

D presents a detailed overview of our sample description. The gender
distribution of the 138 respondents (Table 14) includes one non-binary
respondent, while women make up 18.1%, which is slightly higher than earlier
sample studies that reported just 10% of women participants [79, 80].
According to Table 15, the great majority of the participants are from Western
Europe.

In terms of Scrum, 86.2% of the participants are part of the Development team
(Table 16), and most of them have more than one year experience of working in
Scrum teams, $\approx$ 60% even having at least three years experience (Table
17). This suggests that our participants are somewhat experienced with the
Scrum practices. Moreover, Table 18 shows that most participants first started
working from home when the COVID-19 pandemic restrictions were enforced. This
benefits the study, allowing us to oversee the early impact that switching to
working from home had on Scrum and the individuals of companies used to
practice Scrum in an on-site environment.

####  5.2.3 Assessment of the Measurement Model

Following Russo & Stol’s recommendations, the measurement model is evaluated
before the structural one to ensure variables’ reliability and robustness of
the results [36]. This section discusses internal consistency reliability,
convergent validity, and discriminant validity.

##### Internal Consistency Reliability

The tests ensure that the latent variables are measured in a reliable and
consistent manner across their items. It aims to determine if the correlations
between the items are high enough, indicating resemblance between the items of
the same construct [36]. We performed the Cronbach’s alpha [81], Composite
Reliability [82] and Consistent Reliability Coefficient (rho_A) [83] tests.
Values between 0.6 - 0.7 are acceptable in exploratory researches, while
values between 0.7 - 0.9 are recommended, as they reflect satisfactory to good
results [84]. On the other hand, values below 0.6 indicate a lack of internal
consistency reliability, and values above 0.95 indicate that the items are
similar, decreasing validity [36]. As seen in Table 2, most constructs’ tests
fall within the recommended range of 0.7 - 0.9. The only exceptions are need
for autonomy and use of Scrum with a Cronbach’s Alpha and rho_A above 0.6,
which is acceptable given the exploratory nature of the research.

Construct | Cronbach’s | rho_A | Composite | AVE
---|---|---|---|---
| Alpha |  | Reliability |
Need for autonomy | 0.600 | 0.620 | 0.831 | 0.712
Need for competence | 0.808 | 0.828 | 0.885 | 0.720
Need for relatedness | 0.709 | 0.741 | 0.836 | 0.632
Project success | 0.725 | 0.731 | 0.845 | 0.645
Use of Scrum | 0.611 | 0.612 | 0.793 | 0.561
Home working environment | 0.789 | 0.803 | 0.862 | 0.610
Table 2: Construct Reliability and Validity

##### Convergent Validity

This validity assessment measures the degree to which different items of the
same construct correlate positively with one another [36]. Given that all the
model’s latent variables are reflectively measured, the items should share a
significant proportion of variance, meaning that they converge. To assess this
assumption, two tests were performed: Average variance Extracted (AVE), which
calculates the grand mean value of the squared loadings of the latent
variable’s indicators, and another one to check if the outer loadings of each
construct share at least 50% of their variance using the indicator’s
reliability [36]. The AVE should score higher than 0.5 [85] and the outer
loading of an item onto its construct should be higher than 0.7 [86]. Several
items did not share a proper amount of variance and were removed in a stepwise
manner. Hair et al. suggest discarding all the items with an outer loading
below 0.3 and consider discarding the ones with values between 0.4 - 0.7 if it
leads to an increase in the AVE [87]. Therefore, in turn, each lowest scoring
indicator was discarded, then the model was re-run and verified that indeed
the AVE value improved. We repeated this process until all the outer loadings
passed the 0.7 threshold. Table 2 shows that all AVE values are above the 0.5
threshold and Table 3 displays the retained indicators’ reliability scores,
also passing the 0.7 threshold, through the cross-loadings.

Item | Need for | Need for | Need for | Project | Use of | Home Working
---|---|---|---|---|---|---
| Autonomy | Competence | Relatedness | Success | Scrum | Environment
AN_3 | 0.804 | 0.295 | 0.268 | 0.232 | 0.100 | 0.286
AN_5 | 0.881 | 0.323 | 0.220 | 0.264 | 0.215 | 0.360
CN_1 | 0.361 | 0.875 | 0.368 | 0.201 | 0.165 | 0.432
CN_3 | 0.273 | 0.802 | 0.477 | 0.310 | 0.265 | 0.361
CN_5 | 0.299 | 0.866 | 0.386 | 0.397 | 0.198 | 0.508
RN_1 | 0.141 | 0.295 | 0.703 | 0.174 | 0.095 | 0.279
RN_2 | 0.326 | 0.441 | 0.854 | 0.223 | 0.188 | 0.392
RN_3 | 0.176 | 0.382 | 0.819 | 0.231 | 0.157 | 0.275
PS_1 | 0.292 | 0.310 | 0.171 | 0.757 | 0.288 | 0.350
PS_2 | 0.258 | 0.339 | 0.261 | 0.838 | 0.362 | 0.356
PS_3 | 0.173 | 0.231 | 0.201 | 0.813 | 0.423 | 0.350
US_12 | 0.029 | 0.213 | 0.163 | 0.370 | 0.766 | 0.174
US_15 | 0.160 | 0.205 | 0.095 | 0.296 | 0.734 | 0.175
US_5 | 0.244 | 0.130 | 0.160 | 0.339 | 0.746 | 0.260
HWE_2 | 0.237 | 0.422 | 0.331 | 0.367 | 0.148 | 0.766
HWE_4 | 0.373 | 0.431 | 0.353 | 0.422 | 0.269 | 0.836
HWE_5 | 0.256 | 0.408 | 0.267 | 0.177 | 0.084 | 0.746
HWE_6 | 0.321 | 0.368 | 0.306 | 0.351 | 0.309 | 0.772

Table 3: Cross loadings of the retained items on the constructs

##### Discriminant Validity

This final validity test measures to which extent each construct uniquely
captures different concepts about other constructs. We assessed this using the
Heterotrait-Monotrait ratio of correlations (HTMT), which has been proven to
outperform other tests, such as the Fornell-Larcker criterion [88]. It can be
seen in Table 4 that all the cut-off values are below 0.9, which is the
suggested threshold [88], indicating that each construct is capturing a
different phenomenon.

Construct | Need for | Need for | Need for | Project | Use of
---|---|---|---|---|---
| Autonomy | Competence | Relatedness | Success | Scrum
Need for competence | 0.524 |  |  |  |
Need for relatedness | 0.419 | 0.627 |  |  |
Project success | 0.454 | 0.469 | 0.365 |  |
Use of Scrum | 0.306 | 0.354 | 0.274 | 0.664 |
Home working environment | 0.546 | 0.641 | 0.526 | 0.557 | 0.368

Table 4: Heterotrait-Monotrait ratio of correlations (HTMT)

####  5.2.4 Assessment of the Structural Model

We can conclude, from assessing the measurement model, that all our latent
variables are reliable. The next step is to assess the structural model by
discussing the predictive power and the significance of the relationships
between the constructs [36]. This evaluation is important for accepting or
rejecting the proposed hypothesis [36].

##### Collinearity

Our structural model consists of six constructs, out of which three are
exogenous (need for autonomy, need for competence, and need for relatedness).
The correlation between the exogenous variables with the endogenous ones
should be independent; for that, we assess their collinearity using the
Variance Inflation Factor (VIF) [89]. A widely accepted cut-off value for VIF
is 5, but Hair et al. suggests a more conservative cut-off value of 3 [87], as
collinearity issues may appear between VIF values of 3 to 5. We report VIF
values ranging from 1.245 (RN_1) to 2.031 (CN_1), which are below the more
conservative cut-off value, indicating that our model does not present
collinearity issues.

##### Significance and relevance of path relations

The hypothesized relationships among the constructs are represented by path
coefficients, which have standardized values ranging from -1 to 1 (for highly
negative or positive correlations, respectively), while values close to 0
indicate a weak association [36]. Because PLS-SEM does not make any
distributional assumptions, parametric tests cannot be used to determine
significance. For this reason, we used a 5,000-subsample bootstrapping
approach with replacement, reported in Table 5, where the bootstrapping
coefficient, mean, standard deviation, T statistics, and p-values are
displayed for each of our six hypotheses.

Hypothesis 4 proposed that use of Scrum mediates the relationship between home
working environment and project success. To evaluate mediating relationships,
we must compare the mediators’ suggested indirect paths to the direct paths
[90, 91]. Variables can have no mediating impact (the indirect effect is
insignificant), a partial mediating effect (if the direct effect is
significant), or a full mediating impact (if the direct effect is
insignificant) [51].

Both the direct (p=0.000) and indirect (p=0.006) paths are significant,
indicating that use of Scrum has a partial mediating effect between home
working environment and project success. Moreover, all the associations have
p-values less than 0.05, and the T statistic is more than 1.96 (for a
significance of 5%) [87]. We conclude from this analysis that all our
hypotheses are significant, thus supporting our research model.

Hypothesis | Coefficient | Mean | STDEV | T | p
---|---|---|---|---|---
Direct Effects
H1a: NA $\,\to\,$HWE | 0.204 | 0.207 | 0.074 | 2.769 | 0.006
H2a: NC $\,\to\,$HWE | 0.360 | 0.360 | 0.081 | 4.448 | 0.000
H1c: NR $\,\to\,$HWE | 0.176 | 0.189 | 0.077 | 2.280 | 0.023
H2: HWE $\,\to\,$US | 0.274 | 0.286 | 0.087 | 3.159 | 0.002
H3: US $\,\to\,$PS | 0.357 | 0.365 | 0.068 | 5.240 | 0.000
H4: HWE $\,\to\,$PS | 0.340 | 0.343 | 0.069 | 4.942 | 0.000
Indirect Effects
H5: HWE $\,\to\,$US $\,\to\,$PS | 0.098 | 0.104 | 0.036 | 2.743 | 0.006
Table 5: Path coefficients, bootstrap mean, standard deviation, T statistics
and p-values (NA = Need for autonomy, NC = Need for competence, NR = Need for
relatedness, HWE = Home working environment, US = Use of Scrum)

##### Coefficients of determination and predictive relevance

In this step of the analysis, we are interested in the endogenous variables’
predictive qualities, depicted in Table 6. The $R^{2}$ value, or the
coefficient of determination explained variance, is an essential metric in
PLS-SEM since it determines the model’s explanatory ability by determining how
much of the variance is explained by each endogenous variable [36]. Because
the $R^{2}$ value is proportional to the model size, it is a good practice to
account for the Adjusted $R^{2}$ criteria, which adjusts the $R^{2}$ value
based on the model size [92]. The resultant number, which ranges from 0 to 1,
indicates the amount of explanatory power. Threshold values are impossible to
supply since they are dependent on the subject matter and the model’s
complexity [36]. We also computed Stone-Geisser’s $Q^{2}$ to see how
predictive a given endogenous construct is [93]. Finally, a blindfolding
procedure was applied to compute $Q^{2}$ [87]. The $Q^{2}$ must be greater
than 0 to be relevant [93], which is the case for all endogenous constructs in
our study. As a result, we draw the conclusion that our model is both
predictively relevant and accurate.

Construct |  $R^{2}$ |  $R^{2}$ Adjusted |  $Q^{2}$
---|---|---|---
Home working environment | 0.338 | 0.323 | 0.191
Project success | 0.309 | 0.299 | 0.187
Use of Scrum | 0.075 | 0.068 | 0.036
Table 6: Coefficients of determination

##### Predictive performance

To evaluate the predictive performance, we used the PLS predict algorithm
developed by Shmueli et al., which provides an assessment regarding a model’s
predictive power by mimicking the evaluation of the predictive power for out-
of-sample data [94]. The process consists of dividing the data into $k$ equal-
sized subsets, out of which $k-1$ are used to train the model, then its
predictive power can be evaluated to assess whether the model can predict the
$k^{th}$ subset [36]. The goal of PLS predict is to see if the model can
outperform the most naïve linear regression benchmark (referred to as $Q^{2}$
predict). Thus a $Q^{2}$ predict value greater than 0 indicates that the PLS
path model’s prediction error is less than the naïve benchmark’s prediction
error [36]. We divided our sample into 10 folds and used 10 repetitions to
compute the PLS predict statistics, following the guidelines by Shmueli et al.
[95] to analyze the results. The predictive performance of the constructs is
shown in Table 7. The positive values of $Q^{2}$ predict suggest a high
predictive performance of the entire model. Moreover, all the indicators of
the endogenous constructs were checked using the mean absolute error (MAE) as
the prediction error, then double-checked using the root mean squared error
(RMSE) against the naïve benchmark, and our conclusion does not change. Thus,
the PLS prediction error for all items is lower than the naïve benchmark. As a
result, we conclude that our model as a whole has a high predictive
performance.

Construct | RMSE | MAE |  $Q^{2}$ predict
---|---|---|---
Home working environment | 0.860 | 0.664 | 0.293
Project success | 0.960 | 0.708 | 0.131
Use of Scrum | 0.991 | 0.765 | 0.053
Table 7: Constructs prediction summary

##### Predictive Stability

The final assessment considers the model’s predictive stability by analyzing
the effect sizes ($f^{2}$). Table 8 displays the effects of the different
relations in the model. The effect size thresholds are 0.02, 0.15, and 0.35
for small, medium, and large effects, respectively [93]. As such, the effect
sizes in our model are all relevant, three of the relations having small
effects and the other three medium effects.

Construct | Home Working | Project | Use of
---|---|---|---
| Environment | Success | Scrum
Need for autonomy | 0.053 |  |
Need for competence | 0.140 |  |
Need for relatedness | 0.036 |  |
Use of Scrum |  | 0.171 |
Home working environment |  | 0.155 | 0.081
Table 8: Effect sizes ($f^{2}$)

Throughout this section, our research model was confirmed and validated
through a PLS-SEM analysis. The computed model can be seen in Figure 5.

Figure 5: Measurement and Structural model with outer loadings, $R^{2}$, and
path coefficients (*p<0.05, **p<0.01, ***p<0.001)

####  5.2.5 What is most important for success: an Importance-Performance Map
Analysis

This investigation focuses on the characteristics of project success in Scrum
projects performed while people are working from home. “The Importance-
Performance Map Analysis (IPMA) is particularly useful for generating
additional findings and conclusions by combining the analysis of the
importance and performance dimensions in practical PLS-SEM applications” [96].
Furthermore, it enables determining the extent to which other latent variables
improve project success. As a result, it gives managerial guidance in
identifying the most important aspects of achieving project success in remote
Scrum projects.

Table 9 shows that all latent variables have good performance, ranging between
$\approx$60% and 75%. This result is noteworthy, given that well-consolidated
models, such as the technology acceptance model, exhibit construct performance
ranging between 50% and 70% [37, 97].

Construct | Construct Performances
---|---
Need for autonomy | 60.506
Need for competence | 70.801
Need for relatedness | 59.577
Project success | 68.913
Use of Scrum | 65.994
Home working environment | 75.477
Table 9: Constructs Performance referred to project success

The importance of individual constructs can be seen in Table 10. The values
are comparable with those of other mature models (between 0.10 and 0.35) [37,
97]. On a relative basis, we observe that home working environment is the most
critical construct to project success (0.365), followed by use of Scrum
(0.268).

Construct | Home working environment | Use of Scrum | Project success
---|---|---|---
Need for autonomy | 0.171 | 0.052 | 0.062
Need for competence | 0.388 | 0.118 | 0.142
Need for relatedness | 0.127 | 0.039 | 0.046
Use of Scrum | 0.000 | 0.000 | 0.268
Home working environment | 0.000 | 0.305 | 0.365

Table 10: Constructs Importance (Unstandardized Total Effects)

The association between concept importance and performance is seen in Figure
6. This figure’s practical significance is that a one-unit point increase in
home working environment’s performance increases the performance of project
success by the value of home working environment’s total effect on project
success, which is 0.365 (ceteris paribus) [96, 37]. More precisely, if home
working environment’s performance would increase with one unit from 75.477 to
76.477, the performance of project success would increase by 0.365 points from
68.913 to 69.278. Thus, to increase project success, organizations should
primarily focus on enhancing their employees’ home working environment.

Figure 6: Importance-Performance Map Analysis of project success (NA = Need
for autonomy, NC = Need for competence, NR = Need for relatedness, HWE = Home
working environment, US = Use of Scrum)

##  6 Discussion

The first phase (Section 4), consisting of the qualitative research, helped us
in better understanding how working from home affects the individuals within
Scrum teams and how this translates into an impact on project success. We drew
from these findings, together with the literature on software engineering,
psychology, and project success, to develop our theoretical model in the
second phase (Section 5). Our model illustrates how these constructs relate to
each other and helps us understand the role of Scrum within projects where
people are working from home. Finally, we performed a sample study to
generalize our findings and test our hypotheses. Following the most recent
guidelines for software engineering research by Russo & Stol [36], we analyzed
the collected data through a PLS-SEM analysis as it is well-suited for
evaluating a model’s predictive abilities [37, 52]. All necessary statistical
tests were passed by our model, demonstrating the significance and relevance
of the results. LABEL:table:qualitative_implications provides a summary of our
findings and implications.

We found support for the hypotheses (H1a, H1b, H1c) which proposed a positive
relation between the three innate psychological needs and the home working
environment. However, need for autonomy and need for relatedness had weak
relationships with small effect sizes (both $\approx$0.05), while only need
for competence had a significant relationship with medium effect size (0.14).
This may be explained by the fact that the need for competence involves the
need for autonomy [41]. It is simpler to satisfy one’s demand for competence
while remaining relatively autonomous [41, 40]. Moreover, the weak
relationship of the need for relatedness can be explained by the fact that,
while working from home, people are less in contact with their peers [43].
Organizations must ensure that their employees’ working environments, whether
at home or on-site, support the three needs, according to the suggestions of
the Self-Determination theory [40]. Such an environment should encourage
autonomy rather than control [40], offer employees the resources and training
they need to feel competent about their work and make everyone feel heard and
involved in the process.

We found a positive relationship between home working environment and use of
Scrum, which does not support the proposed negative association of H2. This
finding confirms that Scrum can be adapted for distributed projects [14] and
it helps mitigate the challenges brought by the remote context [16]. Even
though 72% of our sample study participants first worked from home during the
COVID-19 lockdown, most of them reported having the needed equipment and
software to do their work, which suggests that the maturity of home working
within the company is not related to the use of Scrum. Instead, it is crucial
to have the right online tools in place, such that the employees have a smooth
transition to remote working [98]. Moreover, the findings are consistent with
the latest version of the Scrum Guide (2020) [10]. The Scrum Guide became less
prescriptive with the 2020 version, allowing more flexibility [37]. For this
reason, our paper contributes to the Scrum community by supporting the
experience-based update of the framework [37]. We recommend that businesses
encourage their staff to experiment with various internet tools before
deciding on the best ones. This is necessary to guarantee that the employees
who work remotely are determined and find it simple to utilize these
technologies to conduct their jobs.

As expected, we found a considerable positive contribution of the use of Scrum
on project success. This finding is consistent with the literature, which
shows that Scrum projects have a higher success rate than other traditional
methods [61, 7]. However, as also emphasized earlier, with the Scrum Guide
2020 [10] being less prescriptive in terms of its practices and knowing that
many organizations do not fully adhere to or adapt the practices [13], it is
essential to follow the framework’s values and pillars. Hassani-Alaoui et al.
suggest that “teams that frequently respected the pillars and values of scrum,
even when modifications were made, appeared to achieve better outcomes” [13]
in terms of project success.

Home working environment also has a considerable positive contribution on
project success. This can be explained through the three innate psychological
needs, which are also positively associated with home working environment.
Ryan et al. state in their Self-Determination theory that “employees’
experiences of satisfaction of the needs for autonomy, competence, and
relatedness in the workplace predicted their performance and well-being at
work” [40]. Moreover, Russo et al. found that, among other predictors, need
for autonomy and need for competence predicted the well-being of software
developers during the pandemic [41]. Similarly, the IPMA suggests that the
home working environment’s performance related to project success is above
75%, and its importance is the highest of the constructs (0.365). Thus, the
home working environment offers a suitable setting in which developers may
thrive, and enterprises should place a greater emphasis on improving their
employees’ working environments to achieve project success.

Finally, we found a partial mediating effect between home working environment
and project success through the use of Scrum. Looking at IPMA, home working
environment and use of Scrum had the highest importance levels related to
project success with performance values of 75% and 65%, respectively. These
findings support the literature’s contention that Scrum aids in mitigating the
difficulties associated with remote working [25] while maintaining high rates
of project success [13]. Using a framework, such as Scrum, has the benefit of
regulating the organization’s process and, in the home working environment, it
supports the employees to structure and plan their work around Scrum’s events.
This is important because employees could quickly lose focus and slack more
while working from home without a straightforward process and defined goals.
However, a controlled context hinders the competence and autonomy needs,
affecting the performance of the employees [40]. One way to cultivate a
beneficial setting is to ensure that the current Scrum implementation within
the projects adheres to the framework’s core values (commitment, focus,
openness, respect, and courage) [10], which support the three needs. As
described in the Scrum Guide, “the Scrum Team members are open about the work
and the challenges; respect each other to be capable, independent people; and
are respected as such by the people with whom they work and dare to do the
right thing, to work on tough problems” [10]. In other words, the ideal Scrum
Team is made up of autonomous, competent people who can take on challenging
tasks and collaborate to reach their planned goal and attain project success.
As a result of its flexibility in implementation and ability to accommodate
changes, Scrum is well-suited to creating a beneficial home working
environment that contributes to project success, as long as its values and
pillars are followed.

Table 11: Summary of findings and implications Hypothesis |  Findings |  Implications
---|---|---
H1a: Need for autonomy $\,\to\,$Home working environment |  Supported. With a low path coefficient (0.2), need for autonomy is positively associated with home working environment, even though the effect size is small (0.05). |  The autonomy of working from home can result in more productivity and more engaged work. Organizations should ensure an autonomous context, rather than a controlling one.
H1b: Need for competence $\,\to\,$Home working environment |  Supported. This relationship is stronger than H1a, with a considerable path coefficient (0.36) and a medium effect size (0.14). |  While working from home, people took on more individual tasks which challenged their competence. Organizations should establish a streamlined feedback process with high degree of shared information.
H1c: Need for relatedness $\,\to\,$Home working environment |  Supported. Weak relationship between the need for relatedness and home working environment with a low path coefficient (0.17) and small effect size (0.03). |  People did not relate as much with their colleagues when working remotely. Organizations should devise more social events to keep people connected.
H2: Home working environment $\,\to\,$Use of Scrum |  Not supported. Home working environment is not negatively associated with use of Scrum. However, there is a positive association through a moderate path coefficient (0.27) with small effect size (0.08). |  Scrum can successfully be adapted for remote working. Organizations have to accommodate the remote challenges by adopting and training their employees to use online communication and task management tools.
H3: Use of Scrum $\,\to\,$ Project success |  Supported. Use of Scrum has a statistically significant and considerable positive association with project success (path coefficient of 0.35 and moderate effect size of 0.17). |  Scrum comes in many flavors depending how it is used to achieve project success. However, organizations must ensure that their Scrum implementation respects the pillars and values of Scrum.
H4: Home working environment $\,\to\,$Project success |  Supported. Home working environment also has a statistically significant and considerable positive association with project success (path coefficient of 0.34 and moderate effect size of 0.15). |  The workers’ experience in achieving the needs for autonomy, competence and relatedness predicts their work performance and well-being. Organizations can do better by enhancing their employees’ home working environment.
H5: Home working environment $\,\to\,$Use of Scrum $\,\to\,$Project success |  Supported. Use of Scrum has a partial mediating effect between home working environment and project success (path coefficient 0.09, p = 0.006). |  Using Scrum helps mitigate the remote working challenges which could hinder project success. Organizations should consider using Scrum within their remote teams to take advantage of the framework’s benefits which are also reflected on project success.

###  6.1 Threats to Validity

Both qualitative and quantitative validity paradigms are used to discuss the
limitations of the study. First, the qualitative dimension is analyzed by
considering the credibility, transferability, dependability, and
confirmability following the Criteria for assessing the trustworthiness of
naturalistic inquiries [99]. Second, for the quantitive dimension, its
evaluation investigated the statistical conclusion, internal, construct, and
external validity as suggested by Wohlin et al. [100].

##### Credibility

Our findings are based on a qualitative survey approach as described in the
ACM SIGSOFT empirical standards [30], consisting of 12 interviews with
individuals from three continents and seven countries, with various Scrum
experience levels, working in all existing Scrum roles. The participants were
screened before the survey, and those who did not meet the requirements of
working from home within a Scrum project were filtered out. Additionally, the
sample size is in line with other studies applying a Mixed Methods approach
[37].

##### Transferability

According to Gioia et al., the findings of a study based on this methodology
are transferable as long as the study “generates concepts or principles with
obvious relevance to some other domain” [34]. Although we only used Gioia as a
data analysis technique, based on this notion, the findings within this paper,
while limited in its sample size, can be considered transferable, as the
underlying impacted areas discovered throughout the study are human-centric,
therefore branching out into other sciences such as social sciences,
psychology or anthropology. As such, the findings of this study can be used as
a basis for further investigation of similar matters, therefore enriching the
academic understanding of how working from home impacts Scrum knowledge
workers. However, this study focuses on Scrum practices; thus, we cannot make
any assumptions for projects using other Agile frameworks or a combination.

##### Dependability

The research process is consistent, and the data is stable. An external
auditor can examine the process following the “audit trail” [99] consisting of
documentation gathered by the authors throughout the process, along with the
actual data.

##### Confirmability

We guided ourselves by the ACM SIGSOFT empirical standards [30], which
provided a broader understanding of what a qualitative study entails, allowing
us to be less constrained in our analysis process. As such, our study provides
a transparent explanation of our analysis process, with a clear chain of
evidence from the participant (data) to the proposed concepts [30].

##### Internal

We used a cluster-randomized probability sampling strategy to validate our
model [72]. Thus, we only used a cluster, namely the Prolific community,
instead of the entire world population, which would not be feasible. We
recognize that cluster sampling is less precise compared to random sampling,
but it is far more cost-effective than other sampling strategies [37].
Furthermore, we added screening questions and random attention checks to
filter out inadequate responses to enhance the data quality. With this
strategy, we filtered out 62 candidates out of 200 who did not meet our
requirements, concluding to 138 valid responses. However, as most of our
informants are from Europe, we recognize that our sample is not representative
of the software engineering population employing Scrum.

##### External

Because sample studies are ideally suited for theory generalization, the
fundamental goal of the PLS-SEM study has been the generalization of our
findings [70]. We received 138 valid responses, which was more than acceptable
given the results of the priori power test we conducted using G*Power [71]
before the data collection (suggesting a sample size of 98 participants).
However, our model only accounts for Scrum projects, thus cannot be
generalizable for projects using other Agile frameworks.

##### Construct

Using a single-informant approach, the latent variables were measured to
reflect a Scrum worker’s perspective [37]. We solely employed self-reported
metrics, asking our informants to rate their level of agreement with
literature-derived indicators. To compensate for questions not being correctly
answered, we added random attention checks to filter out dishonest candidates.
Furthermore, we adapted existing measurement instruments from the literature
[37] and also created the use of Scrum measurement instrument from the
official Scrum guide [10], as no validated scale was identified. For this
reason, 26 out of 45 indicators were discarded from the model due to their
poor loadings.

##### Statistical conclusion

The survey findings were computed using the Partial Least Squares – Structural
Equation Modeling method with the well-known statistical tool SmartPLS (v.
3.3.3), which has been used in over 1,000 peer-reviewed studies [37, 101].
Furthermore, all statistical techniques and tests utilized in the PLS-SEM
analysis are in accordance with the most recent recommendations in our area
[37, 36].

##  7 Conclusion

Using Scrum in globally distributed projects can help mitigate the challenges
brought by the remote context. The literature already focused on the best
adoption and adaptation strategies towards distributed Scrum. However, the
pandemic generated a context where the entire organization is working
remotely, which has yet to be researched. Therefore, our study aimed to
uncover the impact of working from home on the success of Scrum projects.

We employed a two-phased Multi-Method approach to better understand the impact
through an inductive qualitative survey with Scrum practitioners who worked
remotely. Then, we formulated a theoretical model drawing from our findings
and the literature. We evaluated the model using Partial Least Squares -
Structural Equation Modeling through a sample study of 138 participants to
generalize our findings. To better understand what drives project success, we
performed an Importance-Performance Map Analysis (IPMA), highlighting the
benefits of the home working environment and use of Scrum for project success.
We found that the home working environment nurtures the three innate
psychological needs of the employees’ autonomy, competence, and relatedness,
making them perform better while working from home. Moreover, the use of Scrum
mediates the home working environment and project success, suggesting that
remote projects using Scrum have higher chances of attaining project success.

This study contributes to the limited literature within software engineering
on working from home and its relation to Scrum and project success. While our
investigation was purely exploratory, future research can build on our
findings to create more fine-grained theories to fully understand the impact
of working from home on the current software engineering community. Moreover,
it would be insightful to expand our model on the Agile methodology to capture
a broader understanding of the current phase of the industry. Finally, future
studies might build on our findings by assessing the relationship between
Scrum’s values and principles and the three innate psychological needs to
provide further suggestions on creating a beneficial working environment for
employees, which also reflects in project success.

## Supplementary Materials

Raw data and computation tables are openly available under a CC BY 4.0 license
on Zenodo, DOI: https://doi.org/10.5281/zenodo.4924061.

## Acknowledgments

This work was supported by the Carlsberg Foundation under grant agreement
number CF20-0322 (PanTra — Pandemic Transformation). The authors would also
like to thank Ioana-Mădălina Gănescu for helping gather and analyzing some
interviews.

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##  Appendix A Qualitative Survey

Figure 7: Qualitative Survey to filter out participants who do not meet the
research requirements

##  Appendix B Interview Structure

Scrum Practice | On-site | Remote
---|---|---
Daily Scrum |  |
Sprint Review |  |
Sprint Retrospective |  |
Backlog Refinement |  |
Sprint |  |
Task Breakdown |  |
Requirements Elicitation |  |
Estimation |  |
Task Assignment |  |
Product Owner |  |
Scrum Master |  |
Developers |  |
Backlogs |  |
Others |  |
Table 12: Interview structure

For each Scrum Event in Table 12, three questions were always asked for both
On-site and Remote contexts:

  1. 1.

What is the process?

  2. 2.

How long does it take?

  3. 3.

Who participates?

  4. 4.

What is the output? Is there a difference between the contexts?

  5. 5.

How do you feel about doing this event in this context?

##  Appendix C Items description

Table 13: Items description. Those prefixed with (*) were dropped because of their insufficient loading onto their latent variable Construct | Item ID |  Questions | Reference
---|---|---|---
Need for | AN_1 |  (*) I was free to do things my own way. | [40]
autonomy | AN_2 |  (*) I had a lot of pressures I could do without. | [40]
| AN_3 |  My choices expressed my “true self”. | [40]
| AN_4 |  (*) There were people telling me what I had to do. | [40]
| AN_5 |  I was really doing what interests me. | [40]
| AN_6 |  (*) I had to do things against my will. | [40]
Need for | CN_1 |  I did well even at the hard things. | [40]
competence | CN_2 |  (*) I experienced some kind of failure, or was unable to do well at something. | [40]
| CN_3 |  I took on and mastered hard challenges. | [40]
| CN_4 |  (*) I did something stupid, that made me feel incompetent. | [40]
| CN_5 |  I was successfully completing difficult tasks and projects. | [40]
| CN_6 |  (*) I struggled doing something I should be good at. | [40]
Need for | RN_1 |  I was lonely. | [40]
relatedness | RN_2 |  I felt a sense of contact with people who care for me, and whom I care for. | [40]
| RN_3 |  I felt close and connected with other people who are important to me. | [40]
| RN_4 |  (*) I felt unappreciated by one or more important people. | [40]
| RN_5 |  (*) I felt a strong sense of intimacy with the people I spent time with. | [40]
| RN_6 |  (*) I had disagreements or conflicts with people I usually get along with. | [40]
Home | HWE_1 |  (*) My home is free from excessive outside noise. | [68]
working | HWE_2 |  My job takes place in a clean environment. | [68]
environment | HWE_3 |  (*) The climate at at my home is comfortable in terms of temperature and humidity. | [68]
| HWE_4 |  The seating arrangements at my home are adequate (e.g.: ample opportunities to sit, comfortable chairs, good postural support). | [68]
| HWE_5 |  My home offers an environment where I can easily focus on my work | [69]
| HWE_6 |  There is enough space for work material and equipment at my home. | [69]
| HWE_7 |  (*) At home, I have the technical equipment to do my work (e.g.: PC or laptop, printer, webcam, microphone). | [41]
| HWE_8 |  (*) The internet connectivity is fast and reliable at my home. | [41]
| HWE_9 |  (*) On the computer or laptop I use while working from home I do have the software and access rights I need. | [41]
Use of Scrum | US_1 |  (*) The Product Backlog is always prioritized. | [10]
| US_2 |  (*) The Scrum Team consists of Product Owner, Scrum Master and Developers (Development Team), composed of 3 to 10 people. | [10]
| US_3 |  (*) Within my Scrum Team, there are no sub-teams or hierarchies. | [10]
| US_4 |  (*) Only the people within the Scrum Team internally decide the work on the Sprint. | [10]
| US_5 |  The Product Owner is the only person responsible of creating and ordering items in the Product Backlog while estimating the items is the Developers’ responsibility. | [10]
| US_6 |  (*) The Scrum Master is responsible to facilitate all the Scrum events. | [10]
| US_7 |  (*) Sprints have fixed lengths that do not exceed one calendar month. | [10]
| US_8 |  (*) Sprint planning is completed at the beginning of each Sprint and the resulting plan is created by the collaborative work of the entire Scrum Team. | [10]
| US_9 |  (*) Daily Scrum is time-boxed to 15 minutes and it is held every day of the Sprint. | [10]
| US_10 |  (*) During the Sprint Review, the Scrum team and the stakeholders collaborate on what was done in the Sprint and what to do next. | [10]
| US_11 |  (*) The Sprint Retrospective occurs after the Sprint Review and prior to the next Sprint Planning and The Scrum Team discusses what went well during the Sprint, what problems it encountered, and how those problems were (or were not) solved. | [10]
| US_12 |  Each artifact contains a commitment to ensure it provides information that enhances transparency and focus against which progress can be measured (Product Backlog - Product Goal, Sprint Backlog - Sprint Goal, Increment - Definition of Done). | [10]
| US_13 |  (*) Only the Development Team can update the Sprint Backlog during the Sprint. | [10]
| US_14 |  (*) Refinement of the Product Backlog items is done at least once each Sprint. | [10]
| US_15 |  Each Increment is checked if it meets the Definition of Done before being deployed. | [10]
Project success | PS_1 |  In light of new business requirements that arose during project execution, the project delivers all desirable features and functionality. | [37]
| PS_2 |  In light of new business requirements that arose during project execution, the Scrum-developed software meets key project objectives and business needs. | [37]
| PS_3 |  In light of new business requirements that arose during project execution, the Scrum-developed software overall is very successful. | [37]

##  Appendix D Sample Study

Figure 8: Sample size estimation based on statistical power of 80% | Frequency | Percent (%)
---|---|---
Man | 112 | 81.2
Woman | 25 | 18.1
Non-binary | 1 | 0.7
Total | 138 | 100.0
Table 14: Population divided per gender | Frequency | Percent (%)
---|---|---
Portugal | 37 | 26.8
United Kingdom | 24 | 17.4
Poland | 16 | 11.6
Italy | 11 | 8.0
Spain | 7 | 5.1
Mexico | 6 | 4.3
Canada | 6 | 4.3
Greece | 4 | 2.9
South Africa | 4 | 2.9
Chile | 3 | 2.2
Austria | 2 | 1.4
Czech Republic | 2 | 1.4
Denmark | 2 | 1.4
France | 2 | 1.4
Germany | 2 | 1.4
Norway | 2 | 1.4
United States of America | 2 | 1.4
Slovenia | 2 | 1.4
Belgium | 1 | 0.7
Hungary | 1 | 0.7
Latvia | 1 | 0.7
Netherlands | 1 | 0.7
Total | 138 | 100.0
Table 15: Country of residence | Frequency | Percent (%)
---|---|---
Developer (Development Team) | 119 | 86.2
Product Owner | 7 | 5.1
Scrum Master | 6 | 4.3
Other | 6 | 4.3
Total | 138 | 100.0
Table 16: Scrum role | Frequency | Percent (%)
---|---|---
Less than 1 year | 39 | 28.3
1-2 years | 40 | 29.0
3-5 years | 43 | 31.2
6-10 years | 15 | 10.9
11-20 years | 1 | 0.7
More than 21 years | 0 | 0.0
Total | 138 | 100.0
Table 17: Scrum experience in years | Frequency | Percent (%)
---|---|---
During the COVID-19 lockdown | 100 | 72.5
Before the COVID-19 lockdown | 38 | 27.5
Total | 138 | 100.0
Table 18: Start working from home