# Work-from-home and its implication for project management, resilience and
innovation - a global survey on software companies

Anh Nguyen-Duc<EMAIL_ADDRESS>Dron Khanna<EMAIL_ADDRESS>Des
Greer<EMAIL_ADDRESS>Xiaofeng Wang<EMAIL_ADDRESS>Luciana
Martinez Zaina<EMAIL_ADDRESS>Gerardo Matturro<EMAIL_ADDRESS>Jorge Melegati<EMAIL_ADDRESS>Eduardo Guerra<EMAIL_ADDRESS>Giang Huong Le<EMAIL_ADDRESS>Petri Kettunen
<EMAIL_ADDRESS>Sami Hyrynsalmi<EMAIL_ADDRESS>Henry
Edison<EMAIL_ADDRESS>Afonso Sales<EMAIL_ADDRESS>Didzis Rutitis
<EMAIL_ADDRESS>Kai-Kristian Kemell<EMAIL_ADDRESS>Abdullah Aldaeej<EMAIL_ADDRESS>Tommi Mikkonen<EMAIL_ADDRESS>Juan Garbajosa<EMAIL_ADDRESS>Pekka Abrahamsson
<EMAIL_ADDRESS>Department of Business and IT, University of South
Eastern Norway  Faculty of Computer Science, Free University of Bozen-Bolzano,
Italy  Queenś University Belfast, Northern Ireland  Universidade Federal de
São Carlos, São Carlos, Brazil  Universidad ORT Uruguay, Montevideo, Uruguay
Faculty of Social Sciences, Oslo Metropolitan University, Norway  University
of Helsinki, Finland  University of Southern Denmark, Odense, Denmark
University in Lappeenranta, Finland  Pontifícia Universidade Católica do Rio
Grande do Sul, Brazil  University of Maryland Baltimore County, USA  BA School
of Business and Finance, Latvia  Universidad Politécnica de Madrid, Spain
University of Jyväskylä, Finland

###### Abstract

[Context] The COVID-19 pandemic has had a disruptive impact on how people work
and collaborate across all global economic sectors, including software
business. While remote working is not new for software engineers, forced Work-
from-home situations come with both constraints, limitations and opportunities
for individuals, software teams and software companies. As the ”new normal”
for working might be based on the current state of Work From Home (WFH), it is
useful to understand what has happened and learn from that. [Objective] The
goal of this study is to gain insights on how their WFH environment impacts
software project and software companies. We are also interested in
understanding if the impact differs between software startups and established
companies. [Method] We conducted a global-scale, cross-sectional survey during
spring and summer 2021. Our results are based on quantitative and qualitative
analysis of 297 valid responses. [Results] We observed a mixed perception on
the impact of WFH on software project management, resilience and innovation.
Certain patterns on WFH, control and coordination mechanisms, and
collaborative tools are observed globally. We find that team, agility and
leadership are the three most important factors for achieving resilience
during the pandemic. Although startups do not perceive the impact of WFH
differently, there is a difference between engineers who work in a small team
context and those who work in a large team context. [Conclusion] The result
suggests a contingency approach in studying and improving WFH practices and
environment in future software industry.

###### keywords:

Innovation , Work From Home(WFH) , Innovation Resilience , COVID-19 ,
Resilience

††journal: Information and Software Technology

##  1 Introduction

Work from home (WFH) is increasingly being recognized as a popular work
arrangement due to its many potential benefits for both companies and
employees (e.g., increasing job satisfaction and retention of employees). WFH
has been known in many different terms, such as remote work [1, 2], virtual
teams [3, 4], and teleworking [5, 6, 7]. Working remotely is not new in the
software industry, and it is quite common to have team members from remote
locations. However, with the recent COVID-19 pandemic, millions of people
around the world were forced to adopt the WFH model, regardless of suitability
to their business model, product nature, the current setting of teams and
organizations [8]. As estimated recently, there might be close to 40% people
working in the EU who began to telework full-time as a result of the pandemic
[9].

Furthermore, many companies decided to switch to long-term remote work. In May
2020, Twitter’s CEO informed their staff that they can work from home forever
111https://www.forbes.com/sites/danabrownlee/2020/05/18/twitter-square-
announce-work-from-home-forever-optionwhat-are-the-risks/. Coinbase has become
a “remote-first” company, allowing most staff who want to work remotely to do
so indefinitely. Dropbox too will let all employees work from home
permanently222https://www.businessinsider.com/what-spotify-twitter-goldman-
sachs-said-about-long-term-remote-working-2021-3and Amazon has stated that
employees whose positions allow them to work from home can do so two days a
week 333https://www.flexjobs.com/blog/post/companies-switching-remote-work-
long-term/. While teleworking is not new in many organizational settings,
recent studies in the context of COVID-19 agree that significant changes to
the workplace or way of working will occur in post-pandemic times [10, 11,
12]. Organizations might face various configurations of WFH, from hybrid mode
of office and online work to working from anywhere [12].

On one hand, research about the relationship between working conditions and
individual characteristics, i.e. productivity, well-being and work-life
balance have been quite well explored in software project context [13, 14, 15,
16, 17, 18]. These studies conceptualize constructs, such as well-beingness,
fear, stress, distractions, communication and happiness and relate them to
individual performance on different software engineering activities. It is
shown that adopting WFH has a significant impact on individual well-being and
is connected to their productivity and organizational support is needed to
ensure better work-life balance for their employees [19, 20].

On the other hand, research exploring WFH and organizational characteristics
is relatively less explored in software engineering. The lockdown measures as
a response to the pandemic threaten the existence of many innovative companies
[21]. Particularly, for small businesses and software startups, it is
essential to stay resilient during the pandemic period. Organizational
resilience can be defined as the capability to handle challenging conditions
in a way that secure an organization’s existence and prosperity [22]. In many
cases, the implementation of WFH practices can enable organizations to
continue operation and exist during the pandemic. However, some special
working contexts cannot simply be shifted to WFH, rendering some organizations
less resilient and potentially unable to operate [23]. Bai et al. found that
WFH practices are critical for companies to maintain their operations. This
effect might be heightened in scale for startup and small companies, due to
their vulnerability to macro environmental changes. However, little is known
about the resilience of startups during the shift to adopting WFH during the
pandemic. Inspired by this research gap, we are interested in exploring the
working conditions of software engineers that was caused by the pandemic, and
its implication to the operation and management of projects and companies.
Besides managerial activities and resilience, we will look at how software
companies maintain their innovation level during WFH circumstances. Tidd and
Thuriaux-Alemán define innovation management practices as any structured
administrative or technical help used to affect the effective implementation
of the innovation process [24]. As collaboration and communication drive
innovation behaviour, forced change by way of collaborating could affect
companies’ innovation management practices and other creative activities. In
innovative sectors like the software industry, it is critical to understand
how organizational innovation is affected by the new working situation.

Deriving from our multiple objectives, we will explore the following research
questions, RQ1-RQ4 related to the effects of WFH on software companies. We are
also interested in exploring the WFH situation in a software startup context.
Consequently, the RQ5 is introduced to investigate if any special phenomenon
can be observed in software startup companies.

  * 1.

RQ1 - How does the way of working in software projects change when WFH is
adopted?

  * 2.

RQ2 - How is software project management impacted when WFH is adopted?

  * 3.

RQ3 - How are innovation activities in software companies impacted by the WFH
situation?

  * 4.

RQ4 - How is resilience achieved by software companies when WFH is adopted?

  * 5.

RQ5 - Is there any difference between startups and established companies
regarding the above impact?

##  2 Related work

This section briefly reviews existing work on the three key concepts: work-
from-home, innovation management and resilience.

###  2.1 Work from home

WFH has been referred to using many different terms, such as teleworking,
remote work and virtual team. Working from home is not a new phenomenon.
Studies on the phenomenon has dated back to the 70s, when the motivation for
WFH is either resource shortage and the will to reduce daily communication
[25, 7, 3, 26, 27]. WFH has been characterized as needing minimum physical
requirements, individual control over work pace, defined deliverables, a need
for concentration, and a relatively low need for communication [1].

In general, WFH is often claimed to improve productivity [28, 29] and
teleworkers consistently report increased perceived productivity [30, 31]. WFH
gives people more flexible working time and provides better work-life balance,
save cost of central working place and might give better job satisfaction.
While increasing productivity, WFH is found to be associated with greater
levels of both work pressure and work-life conflict [32] because work intrudes
into developers’ home lives through working unpaid overtime, thinking about
working hours, exhaustion and sleeplessness [33]. However, many organisations
lack appropriate plans, supportive policies, resources or management practices
for practising WFH.

###  2.2 Work from home and software engineering

Bao et al. conducted a quantitative analysis based on a dataset of developers’
daily activities from Baidu Inc [18]. The authors found that WFH had both
positive and negative impacts on developer productivity in terms of different
metrics, e.g., the number of builds/commits/code reviews. Forsgren et al.
studied open source projects in Github and showed that developer activity in
terms of the number of pushes, pull requests, code reviews and commented
issues remained similar or slightly increased compared to the pre-pandemic
year [34].

Ralph et al. performed an extensive study of the pandemic impact on
programming, including productivity in the early months of WFH [15]. They
concluded that perceived productivity has declined (admitting a marginal
effect size) as a result of negatively affected well-being and that
organizations need to accept that expecting normal productivity under crisis
circumstances is unrealistic. Ford et al. conducted a two-wave study on
productivity in Microsoft [10]. Both surveys indicated that the productivity
increased among some participants and stayed the same or decreased among the
others, which led the authors to conclude that the productivity during the
COVID-19 pandemic was dichotomous.

Russo et al. performed a two-wave longitudinal study with a diverse group of
professionals, diving into the impact of over 50 psychological, social,
situational, and physiological factors and their ability to predict the
variance in well-being and productivity [16]. The study concludes with a few
associations between the studied factors and perceived productivity Oliveira
et al. gathered data from two online surveys of Brazilian professionals [35].
The authors found that perceived productivity in WFH when comparing with the
office times has increased. Another important finding made regarding the
changes in perceived productivity during the pandemic was that the number of
positively affected respondents grew from 40% in the first wave to 60% in the
second wave.

Smite et al. studied 13 surveys in the literature finding that on average
perceived productivity had not changed significantly, there are developers who
report being more productive, and developers are less productive when working
from home [11]. Also, positive trends are found in longitudinal surveys, i.e.,
developers’ productivity in the later months of the pandemic show better
results than those in the earlier months. Nolan et al. conducted a qualitative
study on software engineering during the COVID-19 pandemic [13]. The authors
showed that software companies will derive tangible benefits from supporting
their employees during this uncertain time through ergonomic home offices,
listening to their concerns, as well as encouraging breaks and hard stops to
boost long term well-being and productivity. Machado et al. explored gendered
experiences of eoftware engineers during the COVID-19 crisis [36] and found
that women face particular challenges during social isolation, as they lacked
support with household and child care responsibilities.

###  2.3 Software startups

Berg et al. summarized a common definition on software startups as companies
with innovation focus, lack of resources, working under uncertainty and
time–pressure, highly reactive and rapidly evolving [37]. Steve Blank
describes a startup as a temporary organization that aims to create high-tech
innovative products without having a prior working history [38]. The author
further highlights that in a startup context, the business and its product
should be developed in parallel. Eric Ries defines a startup as a human
institution that is designed to create a unique product or service under
extreme uncertainty [39]. Rather than a formal company, a startup should be
considered as a temporary organizational state, that seeks a validated and
scalable business model [40]. A company with a dozen employees can still be in
a startup state to validate a business model or a market.

Startups are found to be different from established companies in the strong
presence of entrepreneurial personalities, behaviors, decision-making and
leadership [41, 42, 43]. Software engineering literature also showed evidence
on unique characteristics of product development in startup contexts. Giardino
et al. revealed reasons for project failure in startups, in which many are not
relevant to established companies [44]. Nguyen-duc et al. conceptualized the
co-development of product and business in startups as hunting and gathering
activities [45]. Tripathi et al. found that entrepreneurs’ background
influence how startups’ products are developed [46]. Melegati et al. also
showed evidence that startup founders have special kind of influences on
requirement engineering activities [47]. Nguyen-duc et al. characterize the
sense making processes in software startups, which is unique to the
organizational states [43].

###  2.4 Innovation Activities in Software Companies

The process of innovation is defined as a way whereby novel and creative ideas
are implemented to obtain business value for customers. It is the process of
implementing external and internal ideas of the company and making them
available to the market to advance the technology [48]. Innovation activities
are not straightforward and involve several iteration cycles of many internal,
external, and coupled activities [49]. The mechanism which should be quickly
adapting to the changes happening with respect to the market situation [50].
Design thinking is one example of an innovation process often seen in a
startup context [51, 39]. Software teams implementing the process of design
thinking follow a creative and flexible way to create a solution to the
problems elicited from the customers. In software projects, requirement
elicitation is the process from which innovative ideas are built, as directly
obtained from the customer [52]. These innovative ideas could be related to a
software product, services, processes, and tools.

###  2.5 Resilience

In organizational contexts, resilience can be seen as a perseverance of
systems and their ability to adapt to ongoing changes during the phase of
disturbance [53]. The major emphasis is on the persistence of the company, in
other words to be able to survive in difficult situations [54],[55], [56]. A
turbulent period or critical situation can occur due to a technological
change, an uncertain period in the company, complex regulatory problems, law
or legal circumstances that affects the business [54], and innovation project
failure [55]. The six resilience constructs that are outlined by Moen et al.
are: self-efficacy, outcome expectancy, optimism, hope, self-esteem and risk
propensity [55]. The response to a critical situation can be either via
adaptive fit or robust transformation. If the critical situation is
predictable i.e. can be foreseen, the solution is an adaptive fit; otherwise a
robust transformation is required [57]. Software startups in particular tend
to excel at adaptability and flexibility [43] and we should expect them to
demonstrate that in response to the COVID-19 crisis. During the pandemic, it
seems more appropriate for innovative startups to embrace iterative and
flexible approaches such as effectual logic [58, 43].

##  3 Conceptual Framework

Collin et al. reviewed and discussed different roles of theory in empirical
work, and one of them is to provide focus and organization to the study [59].
Maxwell et al. refer to a conceptual framework as ”an idea context of the
study” [60]. The conceptual framework should assist the researcher in refining
goals, developing research questions, discerning methodological choices,
identifying potential threats to validity, and demonstrating the relevance of
the research. The primary source of the conceptual framework, from his
perspective [60], does not necessarily need to be an existing theory. Four
primary sources are options from which to derive a conceptual framework: (1)
knowledge based on experience, (2) existing theory, (3) exploratory research,
and (4) “thought experiments” [59].

Figure 1: Conceptual framework

Figure 1 describes five theoretical blocks in which we are interested in our
research: (1) Engineers’ working condition (RQ1), (2) project management
(RQ2), (3) Innovation activities (RQ3), (4) Resilience factors (RQ4) and (5)
Context factors (RQ5). We also collected inputs on Software Engineering
activities and Performance metrics. However these elements are not included in
the scope of this work. WFH setting and coordination mechanisms; (2) software
engineering; 3) Innovation and Resilience; and (4) Performance.

Working condition of software engineers depends on the policy and setting of
their companies. There are three important aspects of a virtual working
condition that have been explored in Global software development research [61,
62], namely the distribution setting [63], the usage of tools [64], and the
coordination and control practices and mechanisms and approaches for control
and management [63]. The configuration of a virtual team is usually seen from
the combination of the extent that a team spreads over geographical locations
and timezones [65, 63]. Collaboration tools are essential in a virtual team.
Various common tools that are reportedly common in global software development
[64] should be revisited in the context of forced virtual collaboration. We
also take input from control and coordination practices that are previously
reported in global teams [66, 67, 68, 69].

Project Management. Communication, collaboration and coordination, the major
managerial activities in a software project, is expected to be significantly
affected by the shift to a new working condition. It would also be reasonable
to observe the impact of WFH on other aspects of project management, i.e
planning and execution. COVID-19 added more challenges to project management,
and more effort on managing overview of tasks, team members, maintaining team
commitment is important for project managers in the new context [70]. After
initial studies on project management and COVID-19, we selected core parts of
project management that might be relevant, which are time management, scope
management, resource and competence, and leadership.

Innovation activities. As stated in Section 2.4, it is important to understand
how the innovation activities are influenced during the shift to a new working
condition. It is mentioned in a recent report from Mc Kinsey that innovation
is important to unlock post-crisis growth to high-tech companies [71].
However, the report also showed that commitment to innovation in many
companies has decreased as companies work through the COVID-19 crisis and
focus on short-term issue. Dogan et al. highlighted the possible difference
between improvisational change and planned change in work environment in order
to support strategic innovation processes [72]. The important elements of a
business, such as commitment to innovation, financial and resource investment
to innovation activities, Intellectual Properties, and business models are
surveyed in connection to the perceived change of working conditions in this
study.

Resilience factors. As stated in Section 2.5, resilience is an interesting
factor that can be significantly influenced by the change of working
conditions due to the pandemic [73]. During the pandemic, it seems more
appropriate for innovative startups to embrace iterative and flexible
approaches such as effectual logic [43, 58]. To confirm our intuition or
otherwise, we asked which factors are perceived as resilience factors
according to participants. We collected known factors from organizational
resilience literature, namely, team, agility, leadership, financial capitals,
social capitals, process and working practices and tools and infrastructure as
the options with which to answer the question.

Besides, these key aspects, we are also interested in various context factors,
such as:

  * 1.

Company types: startups vs. established

  * 2.

Team size

  * 3.

Geographical location (national and continental levels)

  * 4.

Application domains

  * 5.

Participants’ roles

##  4 Methodology

The goal of the survey was to gain insights into how the way of working has
changed into WFH and how it impacts software engineering, project management,
innovation and resilience.

Figure 2: Research process

###  4.1 Survey Design

We designed a structured cross-sectional only survey to answer our questions.
The survey design process started in October 2020 and ended in Mar 2021. The
initial foundation for the studies was a set of few studies about COVID-19 and
startups or software engineering. It is noted that at the time the study was
designed, there are not many papers found in this topic. The literature was
updated gradually during the analysis and report writing. The study design was
influenced by a large group of researchers. Typically, a brainstorming section
for study design involved between 15 to 25 researchers from Brazil, Norway,
Italy, Finland, Sweden, UK, Portugal, Germany, Australia, Canada, China and
Vietnam. Many of these people are co-authors of this work. We conducted bi-
monthly meetup via video-conference, either for brainstorming or focus-group
to design the survey, discuss and work on the project. The result of this
design process is three major versions of the survey (details on piloting and
validating these versions are shown in Table 1).

Ver. |  Major Activities |  # meetings |  sample size |  Tools
---|---|---|---|---
1 |  Testing and validating theoretical elements |  5 meetings |  5 internal participants |  Paper based
2 |  Reducing the number of questions, adding opt-out options |  3 meetings |  25 pilot companies |  Google form
3 |  Adding more open-text questions, Removing one-person companies |  2 meetings |  5 internal participants |  Lime survey
4 |  Revising questions, correcting inviting text,languages |  2 meetings |  517 responses |  Lime survey
Table 1: Major versions of the survey

The study’s target population is software developing companies anywhere in the
world who switched from working in an office to working from home because of
COVID-19. Stakeholders who had been working remotely before the pandemic are
also important, but this study is about the switch, and the questions are
designed for people who switched from working on-site to WFH. The unit of
analysis in this study is a software company, whether it is a startup or an
established company. We implemented several approaches to making sure each
participant can validly represent their companies. In principle, the
questionnaire was open to a wide range of software development stakeholders,
from business analysts, designers, software developers, testers, Scrum masters
to startup-specific roles, such as CEOs or CTOs.

###  4.2 Instruments

The overall instrument used in this research constitutes in total 45
questions. The survey includes sections designed to (1) understand the current
working conditions of the participants, (2) the contextual background of the
participants, including the company and individual characteristics, (3) the
perception of the participants about the impact of COVID-19 on software
engineering activities in their team and companies and (4) the perception of
the participants about the impact of COVID-19 on their companies’ innovation
and resilience and (5) perceived performance.

We used both yes-no questions, multiple-choice questions (application domains,
digital tools, team size and etc.), and five-point Likert scale multiple-
choice questions. Some questions, for example, regarding digital tools
participants are using, employed a free text option, e.g., “tool names” or
“other” so that the respondents can specify their choice better. We also use
several open text questions to get more details from the participants. In a
Likert ordinal-scale question we have five standard choices: (1) Strongly
disagree, (2) Disagree, (3) Neither disagree nor agree, (4) Agree Strongly and
(5) Agree. Additionally, we added the sixth option (6) Not applicable so the
participants can opt-out of the question.

The interview questionnaire was developed in three months (as shown in Table
1). An initial draft (version 1) of the survey was first created based on the
literature in software engineering and COVID-19. The first survey was created
in Google forms. The second version of the survey was made after taking into
account comments and adjustment from the whole author team. Some changes in
later versions of the survey, for instance, re-coding scale labels of some
questions, removal of few questions for better focus, adding team size/
company size value of 1 for filtering, adding open-text questions, and adding
option ”Not applicable” in questions.

A pilot data collection was done in April 2021. We gathered responses from 25
companies to validate our constructs, scales and questions. We also asked for
expert opinions from senior researchers in software engineering who conducted
survey research before [74, 15]. The final survey was made ready on May 2021
and available via the Lime survey tool. The major changes to versions of the
survey is shown in Table 1. The details of the questions are available online
444https://covidnse.limesurvey.net/561361?lang=en.

We have several questions helping us to determine whether a company is a
startup or an established one.

We also implemented filtering questions to make sure only people who feel the
impact of COVID-19 on their professional activities will continue filling in
the survey: “Do you experience or observe an impact of COVID-19 to your work/
your company to any extent?”

The English version of the survey was translated into seven languages, which
are Italian, Spanish, Portuguese, Norwegian, Arabic, Indonesian and
Vietnamese. The translation was done by seven core members of the author team.
The number of responses in each language is shown in Table 2.

Survey language |  No. (digital or paper-based responses)
---|---
Italian |  5
Arabic |  7
Indonesian |  11
Chinese |  12
Spanish |  13
Vietnamese |  42
Portuguese |  90
English |  394
N= |  574
Table 2: Responses in different languages

###  4.3 Sampling Strategies

Our sampling strategy is convenient and localized. We have tried several ways
to purposefully gather the sample that can represent our target population. At
the country level, we have had contact from 13+ countries, and we expect to
get 10-20 responses per country via these personal channels. Conveniently, we
invited participants through our professional and social networks. The
invitation message was shared through co-authors’ social media, i.e. LinkedIn,
Twitter, Reddit, Quora, and Facebook. We also published the call for
participation in several academic communities, i.e. SEWorld, ICSOB, Software
Startup Research Network, etc. We also explored our professional connections
by asking co-authors to send invitation emails to those who they think likely
able to participate. We capitalized on each author’s local knowledge to reach
more people in their jurisdiction. Rather than a single, global campaign, we
used a collection of local campaigns. Each localization involved small changes
in wording. In some cases, authors printed out the survey and disseminated the
paper-based version instead. We also recruited participants from professional
channels, such as Prolific 555https://prolific.co/.

###  4.4 Data Collection

The data collection process started in March 2021 and ended in August 2021. In
an invitation-based approach, we invited one respondent as a representative of
the company. In a broad call for participation, we tried to control the sample
representatives. Invitations led to a central survey tool, which can be
configured to a suitable language version. The survey was spread in five
online pages. As shown in Figure 2, a total number of 574 responses were
collected. 324 respondents were able to complete the survey (missing data rate
is 43.55%). The completion time ranges from 4 minutes to 155 minutes.

Figure 3: Awareness of COVID-19 impact on work

A screening question was asked in the first place before other questions. If a
respondent did not observe an impact of COVID-19 to their working environment
in some ways, he or she is navigated to the end of the survey. In this way,
the survey only gathers opinions from people who actually experienced the
change to their working setting. As shown in Figure 3, 290 people (50.5%)
answered ’Yes’, while 90 people (15.7%) answered ’No’ to the questions. The
rest had either no answer or answered ’do not know’. As shown in Figure 4, the
responses came from 35 countries, and dominated by respondents from Brazil,
UK, Vietnam, USA and Poland. After filtering irrelevant and invalid responses
in data preprocessing step (Section 4.5.1), the number of valid responses for
analysis is 297 responses.

Figure 4: Graphical distribution of participants

###  4.5 Data Analysis

We received 574 total responses, and after data pre-processing steps, 297
valid responses remained.

####  4.5.1 Data pre-processing

The following steps were taken for data pre-processing:

  1. 1.

Remove responses with almost all empty answers,where the respondent apparently
answered the filter question correctly, then skipped all other questions.

  2. 2.

Remove responses with almost all default answers, meaning that questions were
not read properly

  3. 3.

Remove responses with outlined completion time. During pilot study, we know
that the survey needs at least 3 minutes to be completed, and probably no more
than 155 minutes. All answers that took less than 3 minutes or longer than 155
minutes are removed for quality reasons.

  4. 4.

Remove responses from one-person companies (we had one question to identify
company size)

  5. 5.

Filter responses that do not experience any changes due to the pandemic

  6. 6.

Move all free-text responses to a separate file for qualitative analysis

  7. 7.

Re-code raw data. We re-coded team size to categorize them into either small
team versus large team context. We re-coded the company type (startup vs.
established company), as described in Section 4.5.2.

  8. 8.

Re-code all quantitative answers to numeric value for quantitative analysis

####  4.5.2 Identifying startup companies

To allow comparative analysis, we need to have a way to identify startup
companies. A challenge is that the term startup can be interpreted differently
by people, especially when respondents are spread around the world. We asked
different questions to identify the company’s situations. Table 3 shows the
result of the classification with 97 startups and 181 established companies.
We have 19 participants who answered Unknown about the company type, and 277
who did not give their answers.

Company type | No. of responses
---|---
Startup | 97
Established | 181
Unknown | 19
Missing | 277
N= | 574
Table 3: Number of startups vs. established companies Figure 5: Occupational
distribution among participants

Based on our definition (Section 2.3), we determined if a company is
classified as a startup basing on the respondent’s perception, the state of
their main product and the company size. The classification rules are shown in
Table 4.

Company types |  What is the last known state of the product/service created in your company? |  Status
---|---|---
Established |  A product prototype is developed and has not yet been released to market. |  Startup
Established |  Not Applicable |  Established
Established |  Other |  Established
Established |  Product is rather stable, the focus is on gaining customer base. |  Established
Established |  Product is stable, market size, share and growth rate are established. Focus is set on launching new variations of the product. |  Established
Established |  Product was released to the market and is actively developed further with customer input. |  Established
Startup |  A product prototype is developed and has not yet been released to market. |  Startup
Startup |  Not Applicable |  Startup
Startup |  Other |  Startup
Startup |  Product is rather stable, the focus is on gaining customer base. |  Startup
Startup |  Product is stable, market size, share and growth rate are established. Focus is set on launching new variations of the product. |  Established
Startup |  Product was released to the market and is actively developed further with customer input. |  Startup
Not sure |  A product prototype is developed and has not yet been released to market. |  Startup
Not sure |  Not Applicable |  Unknown
Not sure |  Other |  Unknown
Not sure |  Product is rather stable, the focus is on gaining customer base. |  Established
Not sure |  Product is stable, market size, share and growth rate are established. Focus is set on launching new variations of the product. |  Established
Not sure |  Product was released to the market and is actively developed further with customer input. |  Startup
Table 4: Classification rules for determining startups

####  4.5.3 Quantitative analysis

For most of the questions, we conducted descriptive statistics to describe the
distribution of respondents’ answer. To answer RQ5, we need to compare
respondents’ answer among different categories. Because the dependent variable
and independent variables are measured as categories at ordinal level, a Chi-
square test will be used to examine the significant difference between groups.
(https://stats.idre.ucla.edu/other/mult-pkg/whatstat/)

####  4.5.4 Qualitative analysis

We applied a thematic analysis, which is commonly seen in empirical SE
research [75]. The objective of our thematic synthesis process was to add
further details on the observations from quantitative analysis. Braun et al.
suggest six steps for a thematic analysis: (1) familiarizing with data, (2)
generating initial codes, (3) searching for themes, (4) reviewing themes, (5)
defining and naming themes and (6) producing the report [76].

  * 1.

Familiarising with data: the first and second authors of the paper read
through all texts extracted from respondents to evaluate the quality level and
possible themes. A total of 446 codes were obtained that were in English,
Portuguese, Italian, Spanish, and Vietnamese languages. Text that was not
relevant or did not give any useful content was excluded.

  * 2.

Searching for themes: Instead of open coding that was done in SE research [77,
78], we looked for texts that explain further why participants choose the
answers for quantitative questions. For example, why one would choose Agility
as the important factor for resilience, or why one would disagree on the
increased role of IP during pandemic time. We identified 121 codes for Work-
from-home, 84 codes for Project Management, 134 codes for Innovation, and 107
codes for Resilience mentioned in Figure 6.

Figure 6: Qualitative analysis and reference codes

  * 3.

Reviewing themes: We revised the codes and merged them into higher-level order
codes. The codes that are not related to our quantitative findings will not be
explored in this study.

  * 4.

Producing the report: We created thematic maps for each theme, for instance,
WFH (Figure 7), Project management (Figure 9), Innovation (Figure 12),
Resilience (Figure 14).

##  5 Results

This section presents answers to our RQs presented in Section 1 (Section 5.1
to RQ1, Section 5.2 to RQ2, Section 5.3 to RQ3, Section 5.4 to RQ4 and Section
5.5 to RQ5).

###  5.1 RQ1 - How does the way of working in a software project change when
WFH is adopted?

Our data reveals the change to way of working in four different ways (1) shift
in the collaborative working mode, (2) the usage of collaboration and
communication tools, and (3) new coordination and control mechanisms.

Figure 7: Thematic map of work-from-home and its reference codes

####  5.1.1 Shift in collaborative working mode

Working | Virtual | Before | During
---|---|---|---
modes | setting | the pandemic | the pandemic
|  | (in % ) | (in % )
Collocated | Same office | 51.9 | 16.9
Same building | Different offices | 24.7 | 13.8
Closely with | Same |  |
stakeholders | city | 21.9 | 21.5
Closely with | Different |  |
stakeholder | cities | 22.3 | 33.5
Closely with | Different |  |
stakeholders | countries | 11.3 | 10.6
Working | Same |  |
together | time zone | 30.3 | 37.1
$<$ 8 hours | Different |  |
differences | time zones | 10.2 | 14.5
$\geq$ 8 hours | Different |  |
differences | time zones | 6.7 | 8.5
Table 5: Collaborative working mode across geographical locations and
timezones

There is a shift in working situation before and during the COVID-19 pandemic,
as described in the Table 5. As expected, there is a significant reduction in
the percentage of people who collocated in the same office (from 51.9% to
16.9%) and in the percentage of people who collaborate physically in the same
building (from 24.7% to 13.8%). The virtual collaboration with stakeholders
(i.e. customers, vendors, etc.) who are in the different cities or same time
zones has increased significantly (from 22.3% to 33.5% and from 30.3% to 37.1%
correspondingly). There is little change regarding whether collaboration
occurred in the same city, collaboration across country boundaries or time
zones.

Working from | (in % )
---|---
Home (fully) | 56.2
Home (mostly) | 18.02
Home (partially) & Office (partially) | 18.4
Office (mostly) | 6.36
Office (fully) | 8.8
others | 0.7
Not applicable | 2.09
Table 6: WFH porfolio of respondents at March 2021

PO1: Collaboration across different cities and across different time-zones
increased. Collaboration across the same city, and across different timezones
tended to remain the same.

####  5.1.2 The usage of collaboration and communication tools

Digital tools | Examples | (in % )
---|---|---
Video Conferencing | Teams, Zoom, Meet | 87.27
Instant Messaging | Slack, Viber, Whatsapp | 79.8
Cloud Storage | Private, One drive, | 57.95
| Google drive, Dropbox |
Calendar Sharing | Outlook, Google Calendar | 55.12
Project Management Board | Team, Trello, Jira | 48.4
File Sharing and | Github, Bitbucket | 45.22
Version Control |  |
Collaborative tools | Facebook | 24.02
for socializing |  |
Collaborative tools | Adobe Illustrator for UX design | 18.02
for specialized tasks | Overleaf for text editing |
Not applicable |  | 1.76
Table 7: Digital collaborative tools

We also observed the WFH profile of respondents at the time the data was
collected, as shown in Table 6. 56.2% of the total number of respondents were
fully WFH and only 8.8% remained working in their physical offices. The
respondents took to WFH in a positive way, evident from the 20 reference codes
in Figure 7 e.g. “ Employees do not have to spend hours to commute” indicating
that employees stayed home and utilized the commuting time in more effective
manner. Other examples are: “Overall, it will be growth of our business” and
“Companies could reduce spending on office infrastructure”. For some it
already provided improved results e.g. “It has sharpened our focus on delivery
and generally been positive output”.

While WFH employees used a variety of digital tools as presented in the Table
7. This shows that 82.3% of number of respondents frequently use video
conferencing tools, for example Teams, Zoom, and Google Meet. It is probably a
new way of working with increased usage of instant messaging software (79.8%
of total respondents), calendar sharing (55.1%) and social media for
professional socializing (24.2%). It is also no surprise to see the adoption
of cloud storage and specialized development tools in collaborative modes.

Figure 8: Most popular video conferencing tools and repository tools

Respondents shared how digital tools become more important for their
companies:

  * 1.

“Tools for remote work have given a boost to a movement ” (Figure 7)

  * 2.

“We are embracing more collaborative tools for documentation; with so much
communication online, people are more likely to use email/chat instead of
calling meetings, allowing clients and devs to communicate more flexibly”
(Respondent389)

  * 3.

“Increased use of chat and social media tools means developers facing issues
can ask any colleagues regardless of their location for input/advice”
(Respondent371)

Figure 8 shows that Teams, Zoom and Google Meet are the most common tools for
meeting when people working from distance. Other tools are also used, such as
Skype, Whereby, Webex, Discord and Facetime. Regarding version control
systems, almost all respondents reported the usage of a cloud-based solution.
The most popular ones are Github, Bitbucket, Gitlab and Azure DevOps.

Regarding calendar sharing options, the most common tools are Google Calendar
and Microsoft 365/ Microsoft Outlook.

Regarding project management tools, Trello, Jira and Teams are the most common
ones. Besides that, respondents also reported the usage of Asana, Asure
DevOps, Monday, Redmine, Miro, and company internal tools.

Regarding socializing solutions, the popular social media tools are used, for
example, Facebook, Linkedin, Twitter, Discord, Yammer, Sharepoint, and
Instagram.

PO2: There are a wide range of tools being used to support collaboration,
communication and project management during WFH.

####  5.1.3 New coordination and control mechanisms

We gathered feedback from respondents on what new coordination and controls
mechanisms are implemented as parts of their new working environment. It could
also be an existing mechanism but has been adopted in a new frequency or
format. Many respondents agreed about a significant change of coordination and
control approaches in their companies:

  * 1.

“Members of my team are now, more than ever, required to document everything
they do, in order to let other members of the team know what they are working
on. That’s positive. On the other side, brainstorming and interviewing people
takes place remotely, making it harder to do effectively” (Respondent380)

  * 2.

“We had calls and meetings before COVID-19, a lot of informal meetups and
syncs were done in office but now they have to be planned, scheduled, and
organized. It slowed down some stuff that usually was very easy to solve”
(Respondent17)

  * 3.

“Our work system are robust, with more planned meeting” (Figure 7)

New mechanisms | (in % )
---|---
Changed and/or flexible times for working & meeting | 55.1
Daily reports | 26.5
Changing the frequency of communication | 22.3
via written documents e.g. emails, wikis, etc. |
Assigned new roles or responsibilities in the team | 21.9
Changing the frequency of retrospective meetings | 20.1
Adopting of online team coaching/ training | 19.8
Daily clocking in/out | 18.7
Using social media for team collaboration | 14.5
Camera on while working | 6.3
Others | 6.7
Not Applicable | 10.6
Table 8: Coordination and control mechanisms

Table 8 shows the most adopted practices were to ease working and meeting
times. More than half (55.1%) of the respondents reported a change in working
and meeting times implying more flexibility in managing their working time.
Formal control mechanisms, for example regular reports (26.5%), written
documents (22.3%), daily time registration (18.7%) are in some cases adopted
as a measures to the new working situation.

PO3: Various new coordination and control mechanisms are introduced and
implemented for WFH, most of them based on formal procedures.

###  5.2 RQ2: How is software project management impacted when WFH is adopted

####  5.2.1 Scope, time and task awareness

We asked whether respondents find it more difficult to have an overview of who
does what in their current projects. 37.5% of all respondents agreed while
28.7% did not agree. 13.4% answered neither agreed nor disagreed and 3.7% did
not see the question as applicable. We asked whether it became difficult to
plan for resources, time, risk, and milestones. 41.2% of all respondents
agreed while 21.8% did not agree. 18.1% answered neither agree nor disagree
and 2.8% did not see the question as applicable. One respondent mentioned
“Covid has had a n impact on manufacturing process, some products, additional
resources” (Figure 9).

Figure 9: Thematic map of software project management and its reference codes

We asked whether the new working condition leads to a delay for their current
projects. As shown in Table 9, 47.2% of all respondents admitted some delays
occurring in their current projects due to the shift. 13.4% experienced
significant delays and 3.2% had their projects terminated. There was only 25%
who saw no impact on their project timeline. One respondent mentioned “We have
to close down parts of the business, there was a slowdown” (Figure 9).

PO4: It is a mixed picture on how project planning and execution are
perceived. However, the major tendency was to experience delays due to the
working environment shift.

Status of software projects | Percentage
---|---
Projects finished earlier than it would have been | 5.1%
Projects finished on time | 25%
Projects with some delays | 47.2%
Projects with significant delays | 13.4%
Projects terminated | 3.2%
Not applicable | 6%
Table 9: Status of software projects

####  5.2.2 Leadership, culture and resource

We also collected perceived responses about the impact of WFH on team-level
aspects, such as team culture, leadership style and competence demands. Figure
10 shows that regarding organizational culture, the respondents perceived
little negative impact on team culture (31.9% stated a little negative impact
while 17.6% answered a little positive). Regarding leadership styles and
competence needs, there is no clear tendency observed. A respondent staed that
“Leadership has been high churn, very important” (Figure 9). About teamwork a
project respondent mentioned “We have a strong team spirit and collaboration
efforts” (Figure 9).

PO5: The perception of the shift to the new working environment on maintaining
organizational culture tends more to negative impact.

Figure 10: The perceived impact of WFH on competence demand, leadership style
and organizational culture

####  5.2.3 Software Engineering roles

We asked according to the respondent’s experience, how are the Software
Engineering Roles affected due to the new working environment. The result is
shown in Figure 11. For all SE roles that were named, there are a large number
of answers (from 37.4% to 51.2%) saying no impact. Among these roles, the
negative impacts are mostly reported for project lead or project manager
(31%), business analyst (26.6%) and tester (24.6%). Among these roles, the
positive impacts are mostly reported for software developer (30%).

Figure 11: The impact of WFH on Software Engineering roles

Regarding manager’s position, it seems that more managerial work and
responsibility occur during the shift of team working conditions: About
management work, it is harder to co-ordinate activity and to communicate with
everyone.(Respondent70)

PO6: Project managers and business analysts seem to be roles that are most
impacted by the change to the new work environment. Software developers seem
to be least impacted.

Business analysts reported both negative and positive about their impact of
new working conditions on their job, both within their team and with
customers/ users:

  * 1.

“The good thing is that customers now arrive at a better distributed frequency
throughout the day ” (Respondent46)

  * 2.

“People are less formal and easier to access, to listen. During the meeting
because we see each other on cameras, BO are less distracted with their phones
and more focused in what we discussing. Validations are faster and people more
open, more real, more productive in general. There is a learning curve, but we
are learning different ways to share the information better.” (Respondent318)

  * 3.

“The pandemic has taken its toll on us so everything is a little more
difficult than it used to be, including communication, the feel of being a
team, interviews about a place in our company.” (Respondent82)

  * 4.

“For customers, soliciting feedback has become laborious when done remotely,
so mainly a time issue” (Respondent60)

  * 5.

“Not being physically in the same room impinges upon the sharing of ideas and
suggestions, it feels less natural and so it seems slightly stifled as a
creative working environment” (Respondent260)

  * 6.

“Hard to get hold of stakeholders/customers since they are not in their
office” (Respondent140)

  * 7.

“We think that making an interview or understand our clients problems by using
programs as Zoom instead of meeting in person may reduce the effectiveness of
the reunions” (Respondent247)

###  5.3 RQ3 - How are innovation activities in software companies impacted by
the WFH situation?

We found 134 coding references that refer to innovation activities in software
companies. 119 coding references point out innovation was “affected” due to
COVID and 15 references mentioned they were “not affected”with one respondent
replying ”It has not changed innovation activities” (Figure 12). Among
affected respondents, 14 said “little”, 9 were affected a “lot” while 24 were
affected in a “negative” way and 72 affected in a “positive” way. An
interesting finding reveals that various codes were similar under the category
of affected a “lot and positive” as replied by same respondents, while the
codes were similar under the category of affected “little and negative” for
the same respondents.

Figure 12: Thematic map of innovation and its reference codes

Figure 12 shows 24 “negative affected” respondents and some specified the
reasons. For example, for “Client, Finance, Resources, Activities slow down
Team” the respondents said:

  * 1.

“Due to COVID innovation process was slow but it did not completely stop”

  * 2.

“Much of the innovation is somewhat stalled”

Another respondent reported that an additional cost was involved for resources
and materials:

  * 1.

“There are not enough resources and new materials are not easy to find”

Among 72 references who responded with “positive affected” innovation also
named “challenges” with working from home and team effectiveness. 50 aggregate
coding references stated an “online-remote-home office” preference which
helped the companies to innovate but also included challenges like “internet
connection, product delivery, finance, working spaces”.

11 aggregate references show that the “teams” were a key ingredient for a
company although the challenge was that the “effectiveness of the meetings”
was affected. As one respondents said “It really affects our scheduled
meetings and the effectiveness of our meetings, and face to face meetings”. 15
aggregate coding reference outlined that Innovation was “not affected”.
Typical responses were: “It has not changed innovation activities”,“not
affected by COVID 19”,“did not influence company much”. This was in some cases
attributed to the fact that respondents “were already working from home at the
beginning of the start up”. Even if the team members did not work at home in
the beginning, they adapted to the work from home culture e.g. “Since we work
from home COVID did not impact innovation”. Further, some companies already
had a digital working environment e.g.

  * 1.

“My financial education company has always been digital, I believe that in
some points the pandemic has not affected this area”.

Five dimensions of innovation are investigated, namely commitment to
innovation, investment on infrastructure, investment on internal R&D,
Intellectual Property (IP), and the changing business model. Figure 13 shows
how respondents perceived the impact of working environment to these aspects.

Regarding commitment to innovation, 41.4% of all respondents agree or strongly
agree about a decrease in commitment to innovation, i.e. individual
willingness to perform innovation activities within their teams. Examples are:

  * 1.

“Our client base substantially decreased over the last 12 months, subsequently
much focus was on business profitability and continuation than innovation”
(Respondent56)

  * 2.

“Maybe the greatest impact occurs in the low performance for the creation of
new ideas. It has taken a lot for people to have new developments without
being together and without generating synergies” (Respondent101)

Only 31% of respondents disagree or strongly disagree with this statement.
e.g.:

  * 1.

“We have been developing new ways of communicating with customers. We have to
innovate or we will go bust” (Respondent140)

Regarding investment on infrastructure, 53.7% of all respondents agree or
strongly agree that there is an increase in companies’ efforts and money to
acquire new technologies and infrastructure. Only 13.3% disagree or strongly
disagree with this assertion. Some respondents said:

  * 1.

“The pandemic did not change the company’s plans. However, it required to
change some internal aspects of the organization and this led to investing in
new technologies and infrastructures. even if imho, once the pandemic is over,
everything will return to the way it was before” (Respondent42)

  * 2.

“By COVID-19 my company needs investments, for example for equipment for
employees who need to work outside the office, and additional resources for
masks and disinfectants” (Respondent25)

  * 3.

“So much money has been spent on buying new software and equipment for when
we’re working from home, so less is now available for funding elsewhere”
(Respondent15)

Regarding investment on internal R&D activities, 46.8% of all respondents
agree or strongly agree that there has been an increase in companies’ efforts
and money for internal research and development. Only 13.6% disagree or
strongly disagree with this position.E.g.:

  * 1.

“The limitations regarding social gathering and face to face meetings, as a
result of COVID-19, has caused the dynamics of the organization to change and
adapt. Some of this is because of the need for advancing technology and some
is because of financial constraints” (Respondent278)

There were neutral options provided when asking about the increase role of IP
in their companies. When asking about the new business models, 57.6% of all
respondents believed that COVID-19 appears as a factor forcing a change in
their companies’ business models. 58.7% of respondents agreed or strongly
agreed that COVID-19 will fundamentally change the way business is done in
their companies’ sectors over the next five years. Only 11.8% and 14.3%,
respectively, take the opposite viewpoint.

PO7: It seems that at the individual level, the majority experienced an
decrease in motivation for innovation. However, at the organizational level,
many agreed that their companies invest more on innovation infrastructure.

Figure 13: The perceived impacts of WFH on their companies’ innovation
activities

###  5.4 RQ4 - How is resilience achieved by software companies?

Figure 14: Thematic map of resilience and its reference codes

We investigated seven factors from literature relating to organizational
resilience, which are team, agility, leadership, financial capital, social
capital, processes and working practices and tool and infrastructures. Figure
15 shows that overall, all of these factors are perceived helpful for
organizational resilience. The most attributed resilience factors for software
companies in our study are ’Team’ (agreed by 71%. E.g.: respondents)

  * 1.

“Luckily, we have a strong team spirit and collaboration efforts which help us
to become more resilient” (Respondent15)

  * 2.

“We have a strong team spirit so that will get us through this difficult time.
however, our financial capitals have been hard hit by the pandemic and
navigating the uncertainty and down time over the past year” (Respondent46)

  * 3.

“We have very nice team we are working together and trying our bests to negate
COVID-19 work problems” (Respondent81)

  * 4.

“I think people are more together than never, even tough they are not
together, they are more friendly” (Respondent85)

Agility (agreed by 59.1% respondents) and Leadership (agreed by 57.6%
respondents) e.g. :

  * 1.

“We are more “flexible”. We’re very small. So we don’t have stuff to do 24/7.
So we take our time, being “flexible”” (Respondent33)

Respondents highlighted the role of leaderhips e.g. :

  * 1.

“Team and Leadership properties have increased due to the management becoming
more trusting and allow staff to work from home and more freedom”
(Respondent382)

  * 2.

“We currently fail as working in teams at the moment but each member is doing
their best to reach the goals of the organisation especially with the strong
leadership in place” (Respondent400)

  * 3.

“We are all part of a big team and working together with good standards of
leadership in place. working practices have changed a little but the team has
become stronger then ever to over come these difficult times” (Respondent404)

  * 4.

“Knowing how to make the right choices during the pandemic has made the
company stronger than before. this above all thanks to a good team and good
leaders who have been working in the sector for generations” (Respondent42)

The factor that came out as least important was social capital (agreed by
38.9% respondents).

The qualitative results explain further the observation from the survey
answers. With 107 coding references, the Figure 14 show 40 “affected” and 67
“Not affected”. Hence in comparison less companies were affected by COVID-19.
Among the affected, the 25 references show “Negatively affected and its
consequences, whereas 7 references had “positively affected” which outlines
“Agile/Flexible, Team and Leadership, Technology and Advancement” as the
consequences to the companies. The “Negative affect” outlines the “activities
slow down, finance and infrastructure, team and leadership, technology and
advancement, and work and experience affects. 67 aggregate coding references
outline “Not affected”. This is due to the fact the companies to a certain
extent had a good operation in relation to “Agile/Flexible, Finance and
Infrastructure,Suppliers, Team and Leadership, Technology and Advancement,
Work and Experience”.

Figure 15: The most perceived resilience factors during WFH

PO8: Team, Agility and Leadership are the most important factors for software
companies to achieve organizational resilience.

###  5.5 RQ5 - Is there any difference between startups and established
companies regarding the above impact?

####  5.5.1 Project management

Startup companies and established companies have only one significant
difference in the influences of covid 19 on the current competence need in the
team/company (p=0.033)

Companies which have less than 10 years, and more than 10 years of operation
show significant differences in:

  * 1.

the impact of WFH on leadership style (p=.024)

  * 2.

current competence need in the team/ company (p=.003)

  * 3.

the way business is done in your company’s sector over the next 5 years
(p=0.018)

Companies located in different continents have the significant differences in:

  * 1.

the impact of WFH on maintaining organizational culture (p=0.015)

  * 2.

the impact of WFH on leadership style (p=0.003)

  * 3.

current competence need in the team/ company (p$<$0.001)

  * 4.

the perception on how some Software Engineering Roles are affected, for
instance Business Analyst/ Requirement Engineer (p=0.001), UX Designer
(p=0.047), Project manager( p=0.023), Software Architect (p=0.017), Software
Developer (p$<$0.001) and Scrum Master (p$<$0.001)

####  5.5.2 Innovation activities

Questions | Startups VS. | Small vs. | Recent vs. | Among
---|---|---|---|---
| Established | Large | Long-time | Continents
|  | Team | Companies |
changed commitment to innovation. | 0.520 | 0.005** | 0.757 | 0.317
increased investment on infrastructure. | 0.499 | 0.016* | 0.149 | 0.432
increased investment on internal R&D. | 0.555 | 0.012* | 0.696 | 0.556
increased role of IP. | 0.593 | 0.014* | 0.459 | 0.163
forced change in business model | 0.631 | 0.561 | 0.147 | 0.774
fundamental change in near future | 0.434 | 0.151 | 0.018* | 0.051
Table 10: Perceived changes to Innovation activities across categories

Table 10 reveals that team size is the most useful factor to differentiate the
perception of impact of WFH on innovation activities among our respondents.
There is mostly no difference whether a company is startup or established
about innovation activities.

####  5.5.3 Resilience factors

Table 11 reveals that team size is the most useful factor to differentiate the
perception of resilience factors among our respondents. There is no difference
whether a company is startup or established when considering resilience
factors.

Variables | Small VS. | Small VS. | Recent VS. | Among
---|---|---|---|---
| Established | Large | Long-time | Continents
|  | Team | Companies |
Team | 0.114 | 0.033* | 0.385 | 0.875
Leadership | 0.217 |  $<$ .001** | 0.179 | 0.013*
Financial Capital | 0.444 | 0.045* | 0.022* | 0.372
Social Capital | 0.740 | 0.013* | 0.644 | 0.228
Process & | 0.925 | 0.114 | 0.196 | 0.110
Working Practice |  |  |  |
Tools & | 0.194 | 0.016* | 0.054 | 0.734
Infrastructures |  |  |  |
Agility | 0.119 | 0.012* | 0.565 | 0.060
Table 11: Difference among groups in perceived resilience factors

PO9: There is no difference found in terms of perception of the impact of WFH
to project management, resilience and innovation activities between startups
and established companies. However, there is a statistical difference between
respondents who are in a small team and those is in a large team.

##  6 Discussion

The summary of our findings is given in Table 12. In this section we discussed
how our findings relate to existing studies, threats to validity and
implications for research and practice.

RQs |  Research Findings |  POs
---|---|---
RQ1 - How does the of working in a software project change when WFH is adopted? |  Collaboration across different cities and across different time-zones tends to increase. Collaboration across the same city, and across different time zones tends to be the same. There is a wide range of collaboration and communication tools available and used among WFH software engineers. Various new coordination and control mechanisms are introduced and implemented for WFH, most of them based on formal procedures. |  PO1, PO2, PO3
RQ2 - How is software project management impacted when WFH is adopted? |  There is a mixed perception on the impact of WFH on project planning and control. The majority tend to experience certain delays due to the new working environment shift. The majority tends to perceive a negative impact of the shift to new working environment on maintaining organizational culture. Project managers and business analysts seem to be the most impacted roles during the shift to WFH, Software developers seem to be least impacted. |  PO4, PO5, PO6
RQ3 - How are innovation activities in software companies impacted by the WFH situation? |  It seems that at the individual level, the majority experienced a decrease in motivation for innovation. However, at the organizational level, many agreed that their companies invested more on innovation infrastructure. |  PO7
RQ4 - How is resilience achieved by software companies under WFH? |  Team, Agility and Leadership are the most important perceived factors for software companies to achieve organizational resilience. |  PO8
RQ5 - Is there any difference between startups and established companies regarding the above impact? |  There is no difference found in terms of perception on the impact of WFH to project management, resilience, and innovation activities between startups and established companies. However, there is a statistical difference between respondents who are in a small team and those in a large team. |  PO9
Table 12: Summary of the findings

###  6.1 Relations to existing studies

Ford et al. conducted both qualitative and quantitative research on software
engineers at Microsoft during Spring 2020. [10]. The authors reported a mixed
experience for software engineers when working from home, and for the same
factor, one engineer can perceive a benefit and another can perceive it as a
challenge. This might be an explanation for the overall mixed picture of
positive and negative impact of WFH on software projects from our dataset.

Gregory et al. discussed challenges for requirement engineers when WFH
practices are enforced in a company [79]. Our findings provide a comparative
view among software engineering roles in projects, and highlight the perceived
challenges especially with the role of project managers and requirements
engineers.

Smite et al. revealed that during WFH context, software engineers continue
committing code and carry out their daily duties without significant
disruptions [11]. This also aligns with findings that developers are found
least impacted by the new situation. Smite et al. and Rodeghero et al.
described socializing, communication and collaboration and onboarding
practices that have been adapted to WFH context [11, 80]. While we cover some
of these practices in our survey, i.e. turn-on camera, social network for
socializing, more meetings, etc. our study show the statistics on how popular
these practices are among our respondents.

Our study shows that while individual motivation tends to decrease during the
WFH context, the investment of companies in innovation infrastructure and
resources tended to increase during this time. This might be explained by the
fact that companies new to a WFH setting may have lacked proper digital
infrastructure, therefore needing to increase investment in that area. [23].

Kettunen et al. conducted a survey on Agile practices during the pandemic in
Sweden and Finland [81]. When asked about the impact of the pandemic impact
their companies, the authors reported that 53% of the respondents had
perceived negative impact and 33% of the respondent had perceived positive
impacts. Our tendency aligns with this observation, however, we provide
specific details on which software engineering roles are affected and which
aspect of companies are perceived either negatively or positively. We also
agree with Kettunen, in finding that Agility is one of the top three factors
for software companies to remain resilient during the pandemic. We have added
evidence on teh strength of the role of agility [82, 83] and leadership [83]
in maintaining software companies’ resilience and performance, both important
in a startup context.

###  6.2 Threats to validity

We will discuss validity according to the four perspectives presented by
Wohlin et al. [84], complemented by survey-specific validity aspects [85, 86].

Construct validity is concerned with the relationship between a theory behind
an investigation and its observation [84]. As the goal of the survey is to
gain industrial insights on WFH and relating practices, we do not aim at fully
developing or validating hypotheses. However, the observations from our study
can give hints for further research about working environment (i.e. WFH) and
different properties of software companies and software startups. To enhance
construct validity, we used validated scales for software engineering
activities and project management. We are also confident about the
confidentiality and anonymity of the respondents, hence reducing as much bias
as possible.

Internal validity deals with the relationship between a treatment and its
results [84]. We have a filtering question so that only respondents who
experienced an impact on their work and their companies can answer questions.

An inherent threat to survey research is that surveys can only reflect
respondents’ perceptions rather than objective measurement. To make questions
understood in the same ways by all respondents, we reviewed and revised
several times (Section 4.2). The survey versions were reviewed by people from
representative countries to reduce the possible misunderstanding due to
language or cultural differences.

Our findings are based on a reasonable but still limited number of
respondents. With 45 questions (including complex questions and open text
questions), our survey is among long questionnaires that are conducted in
software engineering. It takes in average 18 minutes 50 seconds to complete
the survey. Hence, 297 valid data points is a good number for the scope of the
survey. This is comparable with previous survey in software engineering, as
seen in Table 13.

# questions |  # valid responses |  Publ. Year |  Publ. venues |  Ref.
---|---|---|---|---
35 |  228 organizations |  2017 |  Empirical Software Engineering |  [74]
46 |  202 software engineers |  2015 |  Information and Software Technology |  [87]
23 |  101 engineers |  2015 |  IEEE Transaction in Software Engineering |  [88]
25 |  69 practitioners |  2019 |  IEEE Software |  [89]
45 |  297 companies |  2021 |  |  this study
Table 13: Existing industrial surveys in software engineering literature

External validity is concerned with the generalization of the conclusions
[84]. We cannot make a generalized conclusion from our study. Proper sampling
is very difficult to conduct due to no credible sampling frames (population
lists) for the units of analysis in software engineering researchers study
[90, 15]. Our unit of analysis is the software company, but we are not able to
estimate representativeness of our population due to the unavailability of
empirical data from each industry sector and each country. A different result
might be observed with a different sample. However, the survey can be
repeatedly conducted and new results can be synthesized with what is reported
in this study. We note that it is seen as uncommon to have a survey on a
narrow topic in software engineering with more than 100 valid responses [88].

Conclusion validity is concerned with obstacles to draw correct conclusions
from a study [84] . Although we did not conduct random sampling, we have tried
our best to diversify the respondents regarding their geographical locations
(from 35 countries), industrial sectors (more than 18 sectors), company types
(startups and established companies) and team size. Conclusion validity is
further strengthen by data triangulation, having consistent observations from
both quantitative and qualitative data.

##  7 Conclusions

The pandemic has caused a major disruption worldwide. Research started to
reveal what has happened to the software industry, i.e the development of
software product and establishment of software startups. One thing is clear to
many, at the time of writing in December 2021, a return to previous business
and working condition is unlikely, and it is predicted that the future of
software industry will based on Working from home in some way. This study
reports a results from a global-scale, cross-sectional survey on WFH and its
impact on software project, innovation, and resilience. We collected answers
to 46 questions from 297 respondents around the world.

Our result agrees with recent studies on the topic, for instance, the mixed
perceived impact of WFH at individual and team levels, the new coordination
and control mechanisms, important factors for organisational resilience. We
highlighted the difference in perception from different software engineering
roles, and between small and large teams. We also highlighted the role of
team, agility and leadership for achieving resilience in software companies.

In the near future the working environment will have a significant impact in
where, when and how WFH is adopted in software projects, hence it is important
to understand its impact on organizational and team factors besides
productivity or well-beingness. Our study suggests that many current
challenges of WFH can be cured by looking into team, leadership and management
and coordination mechanisms. We believe that companies with a cohesive and
agile team with a suitable leadership approach and appropriate investment on
team coordination and support are likely to stay resilient, innovative and
grow post-pandemic. There might not be a one-size-fit all approach for an
optimal WFH configuration, but at least we can see the effect of team size and
geographical locations on the perceived performance of WFH team.
Alternatively, national, organizational, and cultural dimensions should be
taken into account when defining a WFH strategy.

As future work, we plan to conduct more analysis, i.e. factor analysis or
regression analysis to understand the possible relationship between WFH
practices, context factors and productivity. We aim at conducting the analysis
at both individual, team and organizational level for comparison purpose. In
future work, we also plan to explore the qualitative data to explain what is
observed from the survey.

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