Content uploaded by Nader Naderpajouh
Author content
All content in this area was uploaded by Nader Naderpajouh on Nov 09, 2023
Content may be subject to copyright.
International Journal of Project Management 41 (2023) 102544
Available online 2 November 2023
0263-7863/© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Guest Editorial
Resilience science: Theoretical and methodological directions from the
juncture of resilience and projects
Nader Naderpajouh
a
,
*
, Juri Matinheikki
b
, Lynn A. Keeys
c
, Daniel P. Aldrich
d
, Igor Linkov
e
a
School of Project Management, John Grill Institute for Project Leadership, Faculty of Engineering, The University of Sydney, Greater Sydney Area, NSW 2037, Australia
b
School of Business, Aalto University, Ekonominaukio 1, 02150 Espoo, Finland
c
Project Management Institute, South Africa Chapter, PO Box 1625, Witkoppen, Johannesburg 2068, South Africa
d
Department of Political Science, Northeastern University, 215K Renaissance Park, 360 Huntington Avenue, Boston, MA 02115, USA
e
Environmental Laboratory, US Army Engineer Research and Development Center, Carnegie Melon University, Vicksburg, MS 39180, USA
ARTICLE INFO
Keywords:
Research methodology
High reliability organisations
Crisis
Disaster
Climate change
ABSTRACT
Increasing concerns about disruptions and the need for adaptation to drastic changes in social and ecological
systems is reected in the growing interest in resilience science. At the same time, the surge in medium to large
scale projects around the world, known as projectication of societies, has resulted in considerable interest in the
discipline of project studies. The disciplinary idiosyncrasies of project studies motivate a reection on theoretical
and methodological considerations in resilience science. This reection rests on the experience of instigating
research at the juncture of resilience and projects in this special collection. Specically, we framed these ob-
servations as a set of principles that can inform resilience science, including the need for theoretical parsimony,
deliberate attention to system boundaries in conceptualization of resilience, as well as critical considerations in
measuring resilience. We posit that in its essence, project studies has to navigate a paradox through: (i) inves-
tigating projects as efcient form of organizing for a resilient, sustainable and just future, while (ii) unpacking
the governance and accountability limitations of temporary organizing within projects that aim to ensure these
long-term goals. The proposed principles are core to the broader research stream that we call “projects of future,”
a collective inquiry to unpack these paradoxes and a research stream to engage project scholarship with the
contemporary phenomena in Anthropocene.
1. Introduction
Over the past few decades, research on the topic of resilience has
gained signicant interest across a range of disciplines (Williams et al.,
2017; Folke et al., 2021). This interest is often associated with the need
to understand performance of systems within societies in the face of a
range of expected and unexpected disruptions. Specically, the
anthropogenic activities have resulted in overshooting tipping points in
the earth systems (Ritchie et al., 2021; IRGC, 2018), and in increasing
instability of social, ecological, and technical systems (Rockstr¨
om et al.,
2023; Hynes et al., 2022). In this context, communities, businesses, and
government agencies organize around ensuring performance of these
systems through actions that are categorized as plannig, absorbing, re-
covery and adaptation (Naderpajouh et al., 2020).
Through these decades, resilience science is epitomized by two
distinct features: (i) the multi-disciplinary nature of the research on the
concept of resilience (Baggio et al., 2015), and (ii) the complexity and
dynamic nature of the context of the study (Walker, 2020). As a result,
there is an interest in exploring resilience science to probe how theories
are developed, concepts are formed, and research methodologies are
designed to understand complex world phenomena such as global grand
challenges. Building on the experience of this special collection on the
topic of resilience in the discipline of Project Studies, we discuss the
nuances of resilience science and specically theoretical and methodo-
logical consideration, especially from the unique perspective of project
studies, for future research in this well-studied and critical research
topic. This uniqueness stems from the idiosyncrasies of the discipline
such as the diversity and plurality of project studies (Geraldi &
S¨
oderlund, 2018) that span from management and organization studies
to engineering and social sciences (Wood et al., 2019). It further stems
from the proximity of the discipline to practice (Geraldi et al., 2021),
and its emerging disciplinary boundaries (Locatelli et al., 2023).
* Corresponding author.
E-mail address: nader.naderpajouh@sydney.edu.au (N. Naderpajouh).
Contents lists available at ScienceDirect
International Journal of Project Management
journal homepage: www.elsevier.com/locate/ijproman
https://doi.org/10.1016/j.ijproman.2023.102544
International Journal of Project Management 41 (2023) 102544
2
Within this context, projects are dened as nested systems in a form
of temporary organizing to achieve an end goal (Lundin & S¨
oderholm,
1995). While cross-fertilization of resilience science is emerging within
the discipline of project studies (see Bredillet & Tywoniak; 2016), there
are several overlaps and informal use of concepts at the juntcture of
resilience and projects (Naderpajouh et al., 2020). This essay serves two
purposes, rst, to introduce the papers published as part of the special
collection as examples of the “resilience research,” and then to provide
the path forward by discussing theoretical and methodological consid-
erations within such inquiries. These theoretical and methodological
considerations need to be problematized (cf. Alvesson & Sandberg,
2011) to advance the growing stream of research at the juncture of
resilience and projects towards the research stream of “projects of
future.” More importantly, and beyond project scholarship, these prin-
ciples can inform broader interdisciplinary body of resilience science.
2. Background of the special collection and summary of articles
The special collection “Resilience in project studies: An interdisci-
plinary discourse” sought to establish research at the juncture of the
concepts of resilience and projects. Specically, the collection was
formed and initiated while we were facing disruptions such as the
impact of extensive natural hazards, social unrests, and a global
pandemic, while during this time we also faced major geopolitical
conicts, as well as continuous biodiversity loss and intensifying ineq-
uity and injustice. What we call “resilience projects” in the initial essay
at the start of this special collection (Naderpajouh et al., 2020) has been
central in the context of these disruptions, whether projects to deliver
vaccines or healthcare facilities in the face of the COVID-19 pandemic,
projects to build resilience in the face of conicts, peacekeeping pro-
jects, projects to build resilience of communities and their built envi-
ronment to natural hazards, projects to address inequity and injustice, or
projects to prevent biodiversity loss.
At the same time, we see major projects facing disruptions, which
signies the need to research resilience of projects themselves. For
example, the volatile context in a changing world highlights the
importance of psychological resilience of individuals in project-based
industries (Akkermans et al., 2020), supply chain resilience of capital
projects in the face of disruptions (Naderpajouh et al., 2015), or the calls
for widening the scope of project plans (e.g., by Gil, 2023) that can be
explored through exibility and adaptability through resilience lens. To
ensure rigor in this growing research stream, we observed the impor-
tance of discussing theoretical and methodological nuances in resilience
science. That is, it is imperative to reect on the use or misuse of concept
of resilience in this needed research stream, and how to ensure engaged
scholarship (see ,e.g., Van de Ven, 2007) in future of this research
stream.
One observation to justify such a need is the signicant interest in
this special collection with 52 initial abstract submissions, which
eventually resulted in only six accepted publications. But before
unpacking the observations to guide future resilience research based on
this experience in the discipline of project studies, we would like to
provide an overview of the accepted articles as a snapshot of potential
future research directions. In general, the accepted articles cover a
diverse set of methodologies including analysis of survey data, grounded
theory elaboration of data, and case study; in contexts ranging from
construction projects, innovation projects, development projects, and
major events.
Meeting challenges with resilience – How innovation projects deal
with adversity – Fey and Kock (2022) seek to empirically capture how
innovation resilience behavior relates to the success of innovation pro-
jects and if that same behavior can compensate or mitigate the negative
effects of adverse situations. The authors gathered data on 87 projects
through an online survey within a large German logistics service pro-
vider with more than 320,000 employees. For the projects, they
measured project success in terms of management (being on time, scope,
and budget), (2) product success (quality of the product and satisfaction
of stakeholders), and (3) learning success (knowledge transference).
They measured project team-level innovation resilience behavior (Oeij
et al., 2016) through Likert questions such as, "We actively look for risks
and try to understand them," "We are keen for cues why our expectations
are not met," and "When members spot potential risks, we discuss them
extensively." A regression analysis showed that resilience behavior
positively correlated with project success. Importantly, as teams faced
high levels of adversity (that is, setbacks and shocks), resilient networks
demonstrated success. A critical takeaway is that by being preoccupied
with failure - potential setbacks and challenges - teams create a culture
of resilience which can navigate through major hurdles.
Antecedents to bounce forward: a case study tracing the resilience
of inter-organizational projects in the face of disruptions – Iao-J¨
or-
gensen (2023) seeks to illuminate how transformative resilience
emerges in inter-organizational projects (IOPs) in the face of disrup-
tions. Focusing on an international development project hosted by a
Swedish government agency during the COVID-19 pandemic, the author
uses 18 anonymized surveys along with 15 semi-structured interviews
with stakeholders to better understand the dynamics of cross-individual
and cross-institutional interactions. Iao-J¨
orgensen argues that three so-
cial mechanisms, that is, types of interactions, were crucial in deter-
mining whether the network actors could move beyond incremental
change and standard outcomes to more transformative ones. The rst
was contextual, meaning that project managers had to proactively set up
a shared, common picture and centralize their linkages for efciency.
The second was behavioral, so that, despite ambiguity, stakeholders
needed to engage, commit, and distribute agency and decision making
throughout the network. The third was cognitive embeddedness, which
involved acknowledging the impact of diversity and reexivity of ac-
tions on bias, tensions, and trade-offs. An important take away from this
research is that despite the non-centralized structure of the institutions
involved here, a distributed system was able to enhance inter-project
coordination and take on resilience management.
Understanding project resilience: designed, cultivated or emergent?
– Resilience can be a complex, dynamic, evolving, and irregular process,
grounded not only on designed robustness and cultural governability,
but also exceptional organizing through ad hoc and creative responses
that take a variety of paths. In the article, “Understanding project
resilience: Designed, cultivated or emergent?," Piperca and Floricel
(2023) consider three perspectives to develop a process-based model of
evolving resilience—management of risk, systems and safety engineer-
ing, and the organizing process of projects. They adopt an integrated
process ontology along with a theory elaboration approach to propose a
conceptualization of project resilience as a complex outcome of antici-
patory, ongoing and exceptional organizing processes. The authors
develop a conceptual framework from these integrated concepts and
create a practitioner roadmap for managing resilient responses, driven
from four case studies from two industries on three continents. The
model demonstrates how projects move from the original trajectory as a
result of perturbations to bouncing back to the original trajectory and
jumping to a new trajectory (major changes in the project) in the event
of disruptions.
Strategic responses to external stakeholder inuences – Disruption
can affect and be caused by both internal and external stakeholders,
whose considerations are extremely important for enhancing project
resilience. Unfortunately, stakeholder considerations are rarely inte-
grated, not only in project resilience, but also in other related elds.
Nguyen et al. (2023) aims to bridge this gap and propose an approach for
considering stakeholder-related issues and connect it to management
responses. The authors conducted in-depth interviews with 25 project
managers in Vietnam. Based on these data, they proposed several con-
ceptual models integrating stakeholder views in resilience consider-
ations as well as practical inputs in management alternative evaluation.
Large-scale construction programme resilience against creeping
disruptions: towards inter-project coordination – Shen and Ying (2022)
N. Naderpajouh et al.
International Journal of Project Management 41 (2023) 102544
3
address an important question of scalability in project resilience.
Traditionally, project management is considered at one project at a time,
but what often matters is not a single project management, but execution
of multiple projects together (at programmatic level). It is especially true
in construction projects where supply chains, limited post-COVID labor
availability and other factors severely impaired execution of construc-
tion projects. The author provided theoretical foundation and applica-
tion case studies for consideration of resilience of project portfolios in
construction industry under stress. Data from a large-scale construction
programme was used to illustrate proposed conclusions related to the
importance of coordination mechanisms across multiple projects,
including preparation, mobilization, and response phases. Pull, match,
and push mechanisms are proposed as resilience enhancement mecha-
nisms for managing cascading failures.
Building megaproject resilience with stakeholders: the roles of
citizenship behavior and critical transition mechanisms – Morkan,
et al. (2023) demonstrate how stakeholders are a resource for resilience
in megaprojects. Megaproject citizenship behavior (MCB) includes
diverse stakeholders who are non-contractual, voluntary, internal/-
external, and who operate in extra-role behaviors and are agents and
resources in the pursuit of project success and resilience. This behavior
happens through collective and collaborative responses to unexpected
events at the inter-organizational level. The authors, Morkan, et al.
(2023), identify the elements of megaproject citizenry behavior and the
transitions needed at scale to bring about resilience through a case study
of a soccer stadium construction. Through grounded theory, the authors
build a theoretical model that shows how megaproject citizenship
behavior affects project-level resilience. The three mechanisms that
transform citizenship behavior of an individual stakeholder to collective
and collaborative actions are (1) power of citizenship behavior in
numbers, i.e., collective action; (2) boosting, i.e., getting the issue to the
right person to act); and (3) mindset shift, i.e., engaging with stake-
holders to create group awareness and collective culture. Project resil-
ience through citizenship behavior requires scaling the impact of this
behavior to collective behavior and shared responsibility. Using these
mechanisms as a management lever can be a critical transition during
the megaproject lifecycle to build resilience.
3. Some theoretical considerations in resilience science
Discussion of resilience science cannot start without considering the
extensive use of the term “resilience” with different implications across
theory and practice. In this sense, the term resilience has been prone to
misuse or misunderstanding across academic disciplines and elds of
practice. The observed pattern of misuse is often rooted in lack of clear
denition within the theoretical and practical eld related to the focus
of research. The clear denition within the focus area gets more
complicated with a missed opportunity to go beyond the primary eld of
focus and diligently explore potential engagement of the pluralistic
denition of the term as a boundary or bridging concept for an inter-
disciplinary inquiry. In this sense, often studies within resilience science
are prone to get lost in vague denitions at the immediate disciplinary
focus, that continues with unclear conceptualizations, and lack of well-
structured theoretical underpinning, and eventually a missed opportu-
nity to engage the clear denition established in the primary discipline
towards an interdisciplinary inquiry if needed. This is further unpacked
in the next section.
3.1. Conceptual clarity and distinction from related concepts
The lack of clear understanding of the concept may start from un-
clear level of analysis, lack of engagement with the extensive literature
of resilience (initially within the immediate discipline), then unclear
denition that extends to unengaged implications for the context of
research. Such misconceptions can be in the form of: (i) stretching the
use of the term “resilience” in contexts that concepts such as risk were
sufciently appropriate and suitable for the studied phenomenon, (ii)
oscillating between different denitions rather than selection of an
appropriate denition for the context of research, or (iii) not clearly
conceptualizing the level of analysis, which in resilience research is
often determined through the question of “resilience of what system in
the face of which disruption?” (Carpenter et al., 2001). Discussing
practical implications of such conceptualizations is specically
important.
For example, a study might focus on “resilience of a stakeholder
network of projects,” without unpacking the practical implications of
this focus. That is, one might question the rigor and depth of empirical
observations, and ultimately the process of problematization of this
research question. In this specic example, the inquiry faces concerns
such as: why should a stakeholder network be resilient? And to what
events? What are the practical and theoretical implications of the
resilience of stakeholder network? What is the acceptable threshold of
that resilience, in the sense that until what point it is desirable and when
it becomes undesirable? What are the boundaries, for example, are there
any parts of the stakeholder network where resilience might not be
favorable and parts that may be favorable? For example, highly resilient
opposition to a social housing project may disrupt the project imple-
mentation. Withouth taking a normative stance about when opposition
is justied and when it is not, this example shows that more resilience is
not always favorable as discussed in more details below and it is nec-
esary to clarify the theoretical and practical implications of the bound-
ary of the problem.
While the concept of resilience can be used for any specic topic such
as the stakeholder network, its application requires clear problem-
atization and rigorous theoretical underpinning, which is followed by in-
depth empirical grounding, and practical implications. While the critical
need for resilience science has resulted in its extensive use and specially
contribution to understanding the challenges we are facing in Anthro-
pocene, there is a ip side of misappropriating the concept in contexts
for which more suitable theories and concepts can be used. Specically,
there is a tendency to conate the research through the use of the
concept of resilience, which often results in unclarity of the conceptu-
alization and lack of theoretical and practical depth.
For example, the established research streams on concepts such as
risk and uncertainty provide a rich theoretical lens to study a range of
phenomena in the face of grand global challenges. As a result, it is
imperative to form a theoretical underpinning based on these estab-
lished theories and then extend them with the concept of resilience. For
example, the concept of uncertainty is more relevant than resilience
when the focus of the studied phenomena is related to lack or absence of
scientic knowledge about the potential scenario (Renn & Klinke,
2012). On the other hand, the concept of risk is more relevant than
resilience in cases where the focus of research is on variations and un-
certainties of an event’s consequences (Aven, 2012). In such studies, the
concepts of uncertainty and risk provide a range of theoretical under-
pinning that can be used to unpack the understudied phenomenon. Such
focus should extend to the use of the concept of “resilience,” when there
are cases in which the context is on an entity (a system) and how it
performs in view of variations (Naderpajouh et al., 2020). Therefore,
within the “resilience research” there is a need for in-depth conceptu-
alization of uncertainty and risk (Galaitsi et al., 2021; Linkov & Trump,
2019; Logan et al., 2022) to have an informed and holistic theoretical
underpinning for the study.
In addition, literature increasingly calls for epistemological distinc-
tion between the concepts of “resilience” and “robustness” (Walker,
2020). In this sense, resilience refers to variations of the performance in
view of expected and unexpected disruption rather than resisting change
or maintaining the status quo. Similarly, there is a need for epistemo-
logical distinction between the concepts of “resilience” and “vulnera-
bility” (Miller et al., 2010), as the latter refers to sensitivity and capacity
of the system to respond. Such demarcations are important to maintain
the focus of research, especially in the study of a phenomenon that by
N. Naderpajouh et al.
International Journal of Project Management 41 (2023) 102544
4
itself is complex and dynamic (Choi et al., 2017). For example, the
concept of vulnerability is more appropriate than resilience for a study
that focuses on exposure and sensitivity of a project to disruptions. Clear
conceptualization and well-dened theoretical underpinning in resil-
ience science has implications both for the theoretical contribution of
the research as well as its practical implications. Beyond the importance
of clarity of conceptualizations in interpretation of results, the practical
implications of a well-dened theoretical underpinning is necessary to
understand the performance of an understudied system in view of var-
iations in addition to clear understanding of uncertainties, risks, con-
tingencies, or even the traditional view of return to status quo.
3.2. Avoiding normative denitions
Another specic observation in resilience science relates to consid-
eration of resilience as a favorable property of a system. Resilience can
be unfavorable, for example, resilience of a planning regime in projects
that do not integrate social and ecological considerations is not favor-
able. This consideration is specically important in project studies
considering a parallel and now disputed conceptualizations of project
success, which is similarly questioned and problematized. That is,
project scholars are increasingly challenging the simplistic and tradi-
tional conceptualizations of project success in terms of staying within
budget and schedule and call for project plans and associated metrics of
success to consider more extended needs of stakeholders. This simplistic
view is extended in an increasing number of studies that aim to connect
project resilience to project success. In this context, it is important to
consider that: (i) both concepts should be dened with a broader and
more problematized denitions, (ii) resilience may be favorable or un-
favorable depending on the context and sub-system at hand (as
mentioned above, resilience of one component may hamper resilience of
another), and (iii) success and resilience in the context of projects
depend on the point of view of different stakeholders. All together, these
considerations will also address the need for theoretical parsimony in
resilience science, specically given the complexity of the context of the
problem. The rst step to achieve this theoretical parsimony is to clarify
the level of analysis as discussed in the opening essay of this special
collection (Naderpajouh et al., 2020). This clarication should continue
with the measurement of resilience and clarication of the conceptual
boundaries. It is imperative that the research team explores questions
including: What elements of the studied system are being measured in
view of its resilience? Does conceptualizing and measuring resilience
add value or can it be framed within other theoretical concepts such as
risk? Can the discussion about underlying elements provide a more ac-
curate and practically meaningful holistic understanding of the under-
studied phenomena or should the analysis focus at the granular level?
That is, discussion around “sub-components” of the understudied
phenomena is specically important in perspective of its resilience. For
example, a study that focuses on team management, project manage-
ment or stakeholder management may choose measurements such as
number of interactions between individuals as a measure of resilience.
But there is a need to critically examine what theoretical and practical
novelty does the concept of resilience offer. Or if the sub-components
have emergent properties, which together create resilience, that is, if
the system is greater than sum of its parts, is resilience just a fancy smoke
screen to cover “whatever topic?” We further unpack these questions in
the next section through methodological considerations.
4. Some methodological considerations in resilience science
In this special collection, all except one of the accepted papers are
qualitative case studies, which was not unexpected given that resilience
research in project studies is still in a rather emergent stage. However,
the natural continuum of the research streams at the juncture of resil-
ience and projects would be to seek generalization by exploring multiple
projects in different organizational and national contexts. Despite the
efforts of even the most diligent researchers, there are natural limits in
qualitative research when the sample size grows. Therefore, the inquiry
for empirically generalized theory often goes hand in hand with quan-
tication of the phenomenon. As we conceptualized in a previous essay
(Naderpajoh et al., 2020), resilience is fundamentally a dynamic and
multi-level concept. This multi-level nature of the concept results in
fundamental methodological issues that need to be considered in the
process of quantication. Next, we will briey discuss some potential
pitfalls which researchers need to carefully consider and hopefully
overcome in their future research. We also attempt to provide some
suggestions on how to address these issues.
4.1. Measuring resilience
The starting point of any quantication process is the determination
of what is the objective and scope of measurement. With resilience, this
is especially difcult since as we (in Naderpajouh et al., 2020) and the
authors of the accepted papers in the special collection have showcased,
resilience is fundamentally a characteristic of a complex
social-ecological-technical systems. Within the focus of project studies,
resilience has been always conceptualized to either be enhanced in a
social, ecological, or technical system via a project (i.e., labeled as
resilience project in the essay) or capability of a temporary nested and
multi-actor project organization to perform in view of expected or un-
expected variations (i.e., project resilience). These two research streams
already require quite different quantication frameworks and tools. In
the following, we mainly focus on project resilience since it appears to
be the next victim in the altar of quantication.
The aim of any quantication should be an empirically generalized
theory, which is simply a logical yet parsimonious statement about the
relationships between certain key theoretical concepts or constructs
shown empirically to apply and hold in reasonably many settings
creating the boundary conditions of the theory (Bacharach, 1989).
Quantication or simply measurement is nothing more than transforming
the chosen concepts or constructs (dened in the stage of conceptuali-
zation) into measurable variables through a rigorous process, which the
researchers often call operationalization (Singleton & Straits, 2005, Ch.
5).
The operationalization is often equalized to developing items for self-
reported scales (see DeVellis & Thorpe, 2021) aimed to measure con-
structs that cannot be directly observed, i.e., latent variables often (but
not always) used in survey research. Self-reported scales are viable when
measuring psychological characteristics on an individual level (Keto-
kivi, 2019). However, they are not always the best approach for orga-
nizational phenomena, a point we will return to later. Reliable as well as
valid measurement of latent variables through multi-item scales is a
rather complex process involving a range of technical methods and
nuances going beyond the scope of this essay. However, we generally
recommend applied researchers to follow the principles based on mea-
surement theory (see e.g., Allen & Yen, 2002), albeit there are consid-
erable developments and even intense debates in this area, for instance
in terms of formative measurement (see e.g, Aguirre-Urreta et al., 2016).
Instead of paying too much attention to the technical details of mea-
surement, we would like to emphasize a few essential aspects, which
make resilience an especially challenging phenomenon to grasp
quantitatively.
4.2. On measuring psychological resilience
As discussed, resilience is often depicted as a system’s capability to
perform in view of expected and unexpected variations (Hollnagel et al.,
2006; Naderpajouh et al., 2020). In terms of measurement, the crux is in
the term system and how to draw its boundaries. To clarify the point
through an example of psychological resilience, there is a long research
tradition in individual or psychological resilience, which embarks from
the child and adolescent development literature (Masten & Reed, 2002)
N. Naderpajouh et al.
International Journal of Project Management 41 (2023) 102544
5
and has increasingly been adopted to general psychology. In this
research tradition, psychological resilience is often dened as a trait and
a process to deal with adversities, inuenced by multiple psychological
characteristics (see e.g., Fletcher & Sarkar, 2013). Alternative deni-
tions do exist going as far as adopting analogies from material science
(Den Hartigh & Hill, 2022). Thus, despite some degree of maturity (in
fact few decades), there is still ongoing debate even around conceptu-
alization of psychological resilience and new review papers with
evolving denitions are published steadily (see e.g., Sisto et al., 2019).
It is not surprising that if conceptualization of psychological resilience
is still a somewhat open expedition, the measurement of psychological
resilience still resembles the wild west with new resilience scales
popping up as bounty hunters in the saloon. Over a decade ago, Windle
et al (2011) found 15 different psychological resilience measures, none
of which provided very strong psychometric properties. Given that
multiple scales can be found in published works, there is a high risk that
the scales start to live the life of their own, when a researcher with
limited resources (read all researchers) casually utilizes scales used in a
published empirical study (isn’t this what we are told to do by re-
viewers?) without carefully assessing the psychometric properties of the
used scale. This creates the vicious cycle or a so-called broken telephone
effect, which can be further heightened by the author’s own seemingly
small adaptations to the scale (Shang & R¨
onkk¨
o, 2022). Given that
measuring psychological resilience already showcases so many issues,
measuring project resilience is even a more daunting task due to its
aforementioned multi-level nature. Thus, the researcher needs to care-
fully decide and explicitly demonstrate the assumptions behind the
chosen conceptualization of project resilience.
For instance, Fey and Kock (2022) argued that innovation projects
facing adversities require resilience from the whole project team and
thus innovation resilience behavior of the project team contributes to
project success. They then measure resilience on the individual level via
a survey to project team members and construct a team-level measure by
averaging individual responses. This argument and measurement
approach is at least implicitly based on the idea of methodological
reductionism meaning that team (or project resilience) can be decom-
posed to smaller entities, i.e., team members or individuals. In other way
around, individual resilience accumulates to team resilience. There is
nothing inherently wrong in this assumption and approach, yet, it may
fail to capture resilience as an emergent phenomenon, which indicates
that a system is greater than its parts. However, the chosen approach is
fundamentally a philosophical question, which has methodological im-
plications and thus it is recommended for the future researchers to
explicitly address such questions to justify their choices. Such an open
debate will benet scientic progress.
As discussed, these assumptions also carry a methodological burden.
In principle, theoretical and empirical units of analysis should match.
But it is rather hard to “survey” an organization. Thus, the question is:
Can a single employee act as an informant for the whole organization
(Ketokivi, 2019)? We that, in most cases, no. In a single person’s rm or
relatively simple project, this might be the case, but most likely not in a
multinational enterprise or a multibillion megaproject. Therefore, it is
better to have multiple informants as done in Fey and Kock’s (2022)
study.
However, this yields hierarchical data (e.g., individuals nested in
projects). The methodological challenge is then how to deal with vari-
ance within the groups (i.e., between respondents of a single project)
and between groups? The easy way out is to “average out” the within
group variance (as done by Fey and Kock, 2022), yet one may lose some
relevant insights in the later stages of analysis. For instance, group-level
associations cannot anymore be used to infer individual-level associa-
tions without committing an ecological fallacy (for a practical example
see, e.g., Brewer and Venaik., 2014) and it may also change the meaning
of measurement (i.e., does individual resilience aggregate to team level
resilience?). Another but thus far less applied approach is to utilize and
model within and between group variance simultaneously using
multi-level modelling techniques (see, e.g., Antonakis et al., 2021;
Holcomb et al., 2010). Again, the technical review of all potential
modelling approaches is beyond the scope of this essay, but it is
important for a researcher interested in resilience (or any other
multi-level phenomenon) in project studies to carefully acknowledge the
nested nature of the data and approach it accordingly.
As an applied methodological guideline related to measurement, we
argue that one should utilize self-reported scales only in situations in
which one strongly believes and can demonstrate that individual-level
(read psychological) resilience is the main contributor to the project
resilience. In such cases, one needs to ensure the validity and reliability
of the chosen scale by going to the original source and not just referring
to the latest empirical application. An applied researcher is rarely the
master in scale development, but it is still recommended to at least
sanity check that the scale development process does hold the water
(Lamber & Newman, 2022 provide an excellent support) before
committing tremendous amount of time and other resources in utilizing
the scale in one’s own data collection. One should also cease from
adopting the scale or at least being completely transparent about the
adoptions (see Shang & R¨
onkk¨
o, 2022). If there is no readily available
scale, the recommended solution is to develop one. However, this re-
quires methodological expertise going easily beyond the skillset of an
applied researcher. Simply put, reading the book by DeVellis & Thorpe,
2021 provides a good and mandatory starting point.
4.3. On measuring project or organizational resilience
When one climbs the ladder from the individual (and potentially
team) levels to the levels of a project and/or an organization, the use of
self-reported measures becomes less recommended. One can evaluate
the suitability of self-reported measures by simply asking “can an indi-
vidual or even group of respondents evaluate the characteristic of a
complete organization?” Therefore, measuring project or organizational
resilience poses serious challenges for future research. It may well be that
there is no single measurement item for such a complex phenomenon,
but one needs to combine multiple sources of data (even from multiple
levels) to form an overall measure for project resilience.
In their review of organizational resilience, Hillmann and Guenther
(2021) similarly point out that organizational resilience suffers from
lack of coherent measures and argue that it is ultimately a sum of
multiple different characteristics. Their recommendation is the use of
formative measures to capture these multiple levels. We again recom-
mend careful approach since formative measurement per se is not a silver
bullet (see, e.g., Edwards, 2011) and in many cases does not pass simple
causal evaluations, as for example, how can measures such as survey
items cause constructs such as an individual’s resilience. However, in
some cases (such as cross-country comparisons) it might make sense to
create aggregate indices by combining interchangeable indicators as
composites (Shang & R¨
onkk¨
o, 2022).
In an organizational resilience domain, there are multiple commer-
cial bodies providing various resilience indices. There is nothing
inherently wrong in such efforts, but if their development protocol and
underlying data remains as a black box, one should approach them with
care. An avid index developer and user is recommended to consult OECD
Handbook of Index Development (Nardo et al., 2008) before engaging
into serious research around that domain. Such indices often are very
effective tools to facilitate communication through proxies of a
real-world phenomenon and are not intended to provide a multi-layer
analysis to show causation (Field et al., 2022).
The nal option would be to accept resilience as a multi-dimensional
phenomenon requiring multiple measures and sources of data to capture
these dimensions. This takes us back to the stage of conceptualization,
that is, what are the conceptual building blocks of resilience in projects?
If project resilience is the sum of multiple parts, such as stakeholders’
cognitive characteristics (Iao-J¨
orgensen, 2023 this special collection),
rightly timed management actions and decisions (Piperca & Floricel,
N. Naderpajouh et al.
International Journal of Project Management 41 (2023) 102544
6
2023 this special collection) or coordination mechanisms (Shen & Ying,
2022 this special collection), it might be worthwhile to capture each
dimension separately rather than trying to forcefully squeeze them into
a single seemingly objective measure. This also indicates that there is
and never will be one nal scale of resilience and in the perfect world of
science, the novel qualitative evidence constantly feeds into the process
of quantication. However, in the practical world of science some as-
sumptions should be held constant at least for sufciently long periods of
time.
4.4. On causality
Another important methodological issue to consider in resilience or
any research is the concept of causality. For example, we are tempted to
say that resilience will improve project success but quite often forget to
account that this is fundamentally a causal claim, i.e., resilience (x) will
cause project success (y) or at least sufcient proportion of it. If we pose
such a claim, we should better warrant it by being at least relatively
certain that:
a There truly is a positive association between resilience and project
success and we are not just observing a false positive. That is, in
technical terms, x reliably correlates with y.
b It is resilience that causes project success and not vice versa. That is,
in technical terms x should precede y.
c It is resilience and not some other unknown (or unmeasured) factors.
That is, in technical terms, x is exogenous or there is no omitted
variable z correlating with both x and y.
In methodologists’ jargon, one needs to address the problem of
endogeneity (Antonakis et al., 2010), that is simply put the “hidden
variable” problem. Technically, for instance an ordinary least square
(OLS) regression produces unbiased (causal) estimates if and only if
there exist no unknown variables that correlates with the independent
variable x (e.g., resilience) and dependent variable y (e.g., project suc-
cess) so called zero conditional mean assumption (see Wooldridge, 2019
p. 42). Yet, it should be noted that even in such a perfect case of esti-
mation, the estimate is unbiased but indifferent to direction, which
means that we need to have sufcient evidence that it is truly x that
causes y. This is one reason why randomized controlled trials are the
golden standard of science, i.e., we compare cases where we have done
an intervention to those where we have not (or done only a placebo
intervention). In the domain of resilience, this is more difcult especially
if we need to trust in measured scales, because it is quite natural and
highly likely that success can drive resilience.
It should also be noted that the multi-level problem applies also in
terms of endogeneity (Antonakis et al., 2021), that is, if one is interested
in the resilience of individual team members, who are ‘nested’ in project
teams. If one fails to account for team specic factors (such as project
managers’ management style), one may face an endogeneity bias.
But what should be done then to avoid the endogeneity trap? The
purist’s solution would be favor only randomized controlled trials but as
an applied social scientist knows, this is nearly impossible in the given
domain of project management. However, fortunately our neighboring
elds (e.g., psychology and economics) have developed multiple quasi-
experimental methods to choose from (see e.g., Antonakis et al., 2010
and Angrist and Pischke, 2014).
Again, reviewing all these techniques is beyond the scope of this
essay but it can be stated that given the dynamic nature of resilience, the
crucial element here without a doubt is time. In other words, if we want
to demonstrate causality, we need to move away from measuring
everything at once or in other words using only cross-sectional designs.
For instance, one could measure resilience before and after the project to
see how project success potentially affects resilience. In this case, one
should naturally have reliable and valid measurement scales for resil-
ience (see discussion above) but also attain project success measures
from external sources such as company’s accounting systems (this is in
general advised to avoid so called common method bias, see Podsakoff
et al., 2003). Another approach would be to adopt so called instrumental
variable and two-stage least squares design (Wooldridge, 2019, p. 495).
However, we leave it to the reader to study and essentially to ponder
from where to nd a suitable instrument variable to study resilience and
project success (i.e., a variable z that correlates with resilience x but not
with project success y).
Time is also a relevant factor because resilience is not a static
property, at least when researched on the organizational level. In fact,
the articles in this special collection identify many different manage-
ment processes and actions seeking to improve project resilience and
thus contribute to project success. Therefore, the goal of an ambitious
applied researcher is not to show that resilience matters but instead
provide strong evidence that certain management approaches and
practices really improve project performance (so called evidence-based
management). The focus should be on analyzing the impact of such
practices and simultaneously to estimate the route via the impact occurs.
For instance, in their qualitative study in this collection, Shen and
Ying (2022) showcase the positive effect coordination mechanisms on
project resilience and (at least implicitly) on project success. The next
step would be to show that this effect can pass a so-called counter factual
argument that it was the coordination mechanisms and not something
else that lead to project resilience, or that would the same projects
without those mechanisms would have performed worse. In the
quasi-experimental framework, this could be achieved, e.g., through
difference-in-differences design (see e.g., Angrist and Pischke, 2014 p.
178), where one compares in time two sets of similar projects: those
where the coordination mechanisms are in place to those where they are
not. Naturally, this would involve measuring resilience before and after
the projects in both sets, as well as project success. By doing so, one
could not just see how project success affects resilience (and vice versa)
but also to see how a certain management mechanism affects project
resilience and project success.
As we have indicated, researching resilience in project studies while
accounting for multiple potential methodological pitfalls is a daunting
task requiring all of us to constantly update our methodological exper-
tise. We still see this as a positive challenge which fundamentally derives
from the progress of the discipline or in other words, we have already
compiled signicant amount of qualitative evidence. Now it is time to
separate the wheat from the chaff and start to compile the evidence on
which project management practices can pass the acid test of causality in
the spirit of evidence-based management. In this sense, rigor is
relevance.
5. Conclusions and future directions
Resilience science increasingly informs a range of disciplines in
response to emerging disruptions associated with climate change and
consequent social and ecological disruptions. The multi- and anti-
disciplinary increase in resilience science requires reection on theo-
retical and methodological idiosyncrasies of the context of this body of
research. This essay reects on observations in this special collection as
an attempt to formalize and establish future applications of resilience
science in project studies and beyond.
The main aim of the essay is to provide a critical reection on these
observations and provide a set of theoretical and methodological con-
siderations for future direction of resilience science. The recommenda-
tions are framed as a set of 13 principles that are proposed to inform
resilience science in Table 1, while the patterns of these principles are
elaborated through examples of scientic inquiry at the juncture of
projects and resilience.
In addition to these considerations, this special collection informs
potential future direction of research at the juncture of resilience and
projects. In one direction, the main aim of the “project resilience”
research stream will be to use the concept of resilience to study process
N. Naderpajouh et al.
International Journal of Project Management 41 (2023) 102544
7
perspective of projects (Brunett et al., 2021). Project resilience includes
exploring the evolution of project plans from need realization and
conceptualization to operation and decommissioning, sensemaking in
projects, non-linearity and dynamic nature of projects, and how project
plans are adapted in the face of disruptions. This research stream will
specically provide a novel angle into complexity and dynamism of
projects and how the planning paradigm can change to encourage
exibility and adaptability in view of a range of future scenarios. As
elaborated in the reections and considerations above, the concept of
resilience will build on the foundation and basis of extensive literature of
uncertainty and risk within and beyond project studies to extend our
understanding of performance of projects and project practitioners in
the face of disruptions.
On the other hand, the research stream of “resilience projects” can
direct the unique project scholarship to study the roles of projects in the
face of global grand challenges including social equity and justice,
climate crisis, social and political conicts, biodiversity loss, health and
well-being threats, or mass immigrations among others. This research
stream is specically important, since compared to more established
organizing, projects and temporary organizing have proven to be more
effective vehicles to ensure preparedness, response, recovery, and
adaptation activities (H¨
allgren et al., 2018). Some examples of research
topics among a wide range of potentials include cross-fertilizing the
extensive literature of agile project management that is rooted in IT
projects to disaster management (Galaitsi et al., 2023), extensive liter-
ature of stakeholder engagement (e.g., Aaltonen et al., 2021) for
community resilience building, projects to ensure mental health and
trauma in the face of climate change (Aldrich 2019; Longman et al.,
2023), projects to ensure resilience of energy systems and transitions to
net-zero, projects as interventions to natural systems (Whyte and Motee,
2022), projects in response to biodiversity (e.g., Willemsen, 2020) or
ensuring multi-species justice (e.g., Celermajer et al., 2021).
However, the dark side of projects as effective mechanisms to
enhance resilience is the temporary nature of organizing that has im-
plications for long-term goals and accountability of the involved actors
(e.g., in retrot projects, Izaddoost et al., 2023) as well as potential
resilience traps (Rachunok & Nateghi, 2021) that lock the impacted
communities in certain future scenarios. In this context, project scholars
can go beyond studying the potential of projects in response to global
grand challenges, but also critically review how projects did or did not
deliver the long-term intended targets, what is the impact of projects in
future scenarios, and if there were effective accountability mechanisms
to ensure long-term resilience driven goals through temporary and
ephemeral organizing. Conceptualization of such paradoxes (see Gaim
et al., 2022; and Seidl et al., 2021) is central to the future direction of
research in project studies, a collective inquiry to navigate the tensions
of efciency versus accountability for resilient, sustainable and just
goals through temporary organizing. Navigating these tensions will
involve understanding: (i) the important role of projects as efcient
vehicles to ensure resilience in the face of expected and unexpected
disruptions, and at the same time (ii) the inherent limitations of projects,
including inadequacy of governance and accountability mechanisms of
temporary organizing in the quest for long-term resilient, sustainable,
and just goals.
We posit that project scholarship has a signicant opportunity to
engage its theory and practice to such paradoxes at the juncture of
projects and resilience and extend what we labeled as “resilience pro-
jects” to the broader research stream that we call “projects of future”: A
research agenda engaging project scholarship into the contemporary
phenomena in Anthropocene.
Declaration of Competing Interest
The authors declare that they have no known competing nancial
interests or personal relationships that could have appeared to inuence
the work reported in this paper.
Acknowledgments
We thank all the authors who submitted their abstracts to be
reviewed for this special collection. The work by those authors clearly
indicates that this research stream has gained the attention it desires. We
specically thank the authors of the articles published in this special
collection for their diligent work during the review process. More
importantly, we thank all the reviewers who generously provided their
expertise in assisting the authors to improve their papers, while we
extend our thanks to the editor-in-chief, Prof Martina Huemann, for her
support and guidance.
References
Aaltonen, K., Derakhshan, R., Di Maddaloni, F., & Turner, R. (2021). Call for papers:
Project stakeholder management. International journal of project management, 39(6),
709–711.
Aguirre-Urreta, M. I., R¨
onkk¨
o, M., & Marakas, G. M. (2016). Omission of causal
indicators: Consequences and implications for measurement—A rejoinder.
Measurement: Interdisciplinary Research and Perspectives, 14, 170–175.
Akkermans, J., Keegan, A., Huemann, M., & Ringhofer, C. (2020). Crafting project
managers’ careers: Integrating the elds of careers and project management. Project
Management Journal, 51(2), 135–153.
Aldrich, D. P. (2019). Black wave: How networks and governance shaped Japan’s 3/11
disasters. Chicago: University of Chicago Press.
Allen, M. J., & Yen, W. M. (2002). Introduction to measurement theory. Prospect Heights,
IL: Waveland Press.
Table 1
Summary of theoretical and methodological considerations in resilience science.
Stage of research Theoretical and
methodological
context
Principles
Conceptualization Ambiguity of the
concept
•Is resilience the right concept to
address the studied
phenomenon?
•What is the level of analysis?
Are there any cross-layer dy-
namics to be considered?
•What denition of resilience
suits the context and level of
analysis?
•How is the dynamic nature of
resilience considered? What is
the threshold that resilience
may change from favourable to
unfavourable or vice versa?
•What is the boundary of the
system and how is it
demarcated?
Literature review Supercial theoretical
underpinning
•Can an alternative theoretical
framework (e.g., uncertainty
and risk) elaborate the studied
phenomenon?
•Is it possible to simplify and
reduce other related theoretical
explanations to ensure a more
focused theoretical foundation
of research?
Research design Lack of clear strategy
to measure resilience
•How do the measures represent
the actual phenomena?
•What is the unit(s) and level(s)
of analysis?
•How can one verify, validate,
and ensure reliability of
resilience measures?
•How can one establish causality
between studied concepts?
Interpretation of
results
Unclear practical
implications
•How does the analysis of
resilience impact actions
differently?
•What are the practical
implications of the study?
N. Naderpajouh et al.
International Journal of Project Management 41 (2023) 102544
8
Alvesson, M., & Sandberg, J. (2011). Generating research questions through
problematization. Academy of management review, 36(2), 247–271.
Angrist, J. D., & Pischke, J. S. (2014). Mastering’ metrics: The path from cause to effect.
Princeton university press.
Antonakis, J., Bastardoz, N., & R¨
onkk¨
o, M. (2021). On ignoring the random effects
assumption in multilevel models: Review, critique, and recommendations.
Organizational Research Methods, 24(2), 443–483.
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010). On making causal claims: A
review and recommendations. The leadership quarterly, 21(6), 1086–1120.
Aven, T. (2012). The risk concept—Historical and recent development trends. Reliability
Engineering & System Safety, 99, 33–44.
Bacharach, S. B. (1989). Organizational theories: Some criteria for evaluation. Academy
of Management Review, 14(4), 496–515.
Baggio, J. A., Brown, K., & Hellebrandt, D. (2015). Boundary object or bridging concept?
A citation network analysis of resilience. Ecology and Society, 20(2).
Bredillet, C. N., & Tywoniak, S. (2016). Genesis of the special issue: uncertainty, risk &
opportunity, resilience & anti-fragility. International Journal of Project Management, 7
(34), 1322–1327.
Brewer, P., & Venaik, S. (2014). The ecological fallacy in national culture research.
Organization Studies, 35(7), 1063–1086.
Brunet, M., Fachin, F., & Langley, A. (2021). Studying projects processually. International
journal of project management, 39(8), 834–848.
Carpenter, S., Walker, B., Anderies, J. M., & Abel, N. (2001). From metaphor to
measurement: Resilience of what to what? Ecosystems, 4, 765–781.
... & Celermajer, D., Schlosberg, D., Rickards, L., Stewart-Harawira, M., Thaler, M.,
Tschakert, P., & Winter, C. (2021). Multispecies justice: Theories, challenges, and a
research agenda for environmental politics. Environmental Politics, 30(1-2), 119–140.
Choi, J., Deshmukh, A., Naderpajouh, N., & Hastak, M. (2017). Dynamic relationship
between functional stress and strain capacity of post-disaster infrastructure. Natural
Hazards, 87, 817–841.
Den Hartigh, R. J., & Hill, Y. (2022). Conceptualizing and measuring psychological
resilience: What can we learn from physics? New Ideas in Psychology, 66, Article
100934.
DeVellis, R. F., & Thorpe, C. T. (2021). Scale development: Theory and applications.
Thousand Oaks, CA: Sage.
Edwards, J. R. (2011). The fallacy of formative measurement. Organizational Research
Methods, 14(2), 370–388.
Fey, S., & Kock, A. (2022). Meeting challenges with resilience—How innovation projects
deal with adversity. International Journal of Project Management, 40(8), 941–950.
Field, C., Sutley, E., Naderpajouh, N., van de Lindt, J. W., Butry, D., Keenan, J. M., Smith-
Colin, J., & Koliou, M. (2022). Incorporating socioeconomic metrics in civil
engineering projects: The resilience perspective. Natural Hazards Review, 23(1),
Article 04021064.
Fletcher, D., & Sarkar, M. (2013). Psychological resilience. European psychologist, 18(1),
12–23.
Folke, C., Carpenter, S., Elmqvist, T., Gunderson, L., & Walker, B. (2021). Resilience:
Now more than ever: This article belongs to Ambio’s 50th Anniversary Collection.
Theme: Anthropocene. Ambio, 50, 1774–1777.
Galaitsi, S. E., Pinigina, E., Keisler, J. M., Pescaroli, G., Keenan, J. M., & Linkov, I. (2023).
Business continuity management, operational resilience, and organizational
resilience: Commonalities, distinctions, and synthesis. International Journal of
Disaster Risk Science, 1–9. https://doi.org/10.1007/s13753-023-00494-x
Gaim, M., Clegg, S., e Cunha, & Berti, M. (2022). Organizational paradox. UK: Cambridge
University Press.
Galaitsi, S. E., Keisler, J. M., Trump, B. D., & Linkov, I. (2021). The need to reconcile
concepts that characterize systems facing threats. Risk Analysis, 41(1), 3–15.
Geraldi, J., & S¨
oderlund, J. (2018). Project studies: What it is, where it is going.
International Journal of Project Management, 36(1), 55–70.
Geraldi, J., S¨
oderlund, J., & Marrewijk, A. V. (2021). Bright and dark spots in project
studies: Continuing efforts to advance theory development and debate. Project
Management Journal, 52(3), 227–236.
Gil, N. A. (2023). Cracking the megaproject puzzle: A stakeholder perspective?
International Journal of Project Management, 41(3), Article 102455.
H¨
allgren, M., Rouleau, L., & De Rond, M. (2018). A matter of life or death: How extreme
context research matters for management and organization studies. Academy of
Management Annals, 12(1), 111–153.
Hillmann, J., & Guenther, E. (2021). Organizational resilience: A valuable construct for
management research? International Journal of Management Reviews, 23(1), 7–44.
Holcomb, T. R., Combs, J. G., Sirmon, D. G., & Sexton, J. (2010). Modeling levels and
time in entrepreneurship research: An illustration with growth strategies and post-
IPO performance. Organizational Research Methods, 13(2), 348–389.
Hollnagel, E., Woods, D. D., & Leveson, N. (Eds.). (2006). Resilience engineering: Concepts
and precepts. Ashgate, UK.
Hynes, W., Trump, B. D., Kirman, A., Haldane, A., & Linkov, I. (2022). Systemic
resilience in economics. Nature Physics, 18(4), 381–384.
Iao-J¨
orgensen, J. (2023). Antecedents to bounce forward: A case study tracing the
resilience of inter-organisational projects in the face of disruptions. International
Journal of Project Management, 41(2), Article 102440.
IRGC. (2018). Guidelines for the governance of systemic risks: In systems and organisations in
the context of transitions. ETH Zurich.
Izaddoost, A., Naderpajouh, N., & Heravi, G. (2023). Modelling principal-agency
dilemma for resilience of interdependent infrastructure systems. Reliability
Engineering & System Safety, 238, 109424.
Ketokivi, M. (2019). Avoiding bias and fallacy in survey research: A behavioral
multilevel approach. Journal of Operations Management, 65(4), 380–402.
Lambert, L. S., & Newman, D. A. (2022). Construct development and validation in three
practical steps: Recommendations for reviewers, editors, and authors. Organizational
Research Methods, 26(4). https://doi.org/10.1177/10944281221115374
Locatelli, G., Ika, L., Drouin, N., Müller, R., Huemann, M., S¨
oderlund, J., … Clegg, S.
(2023). A Manifesto for project management research. European Management Review,
20(1), 3–17.
Logan, T. M., Aven, T., Guikema, S. D., & Flage, R. (2022). Risk science offers an
integrated approach to resilience. Nature Sustainability, 5(9), 741–748.
Linkov, I., & Trump, B. D. (2019). The science and practice of resilience. Cham: Springer
International Publishing.
Longman, J., Braddon, M., Verlie, B., Schlosberg, D., Hampshire, L., Hawke, C., …
Saurman, E. (2023). Building resilience to the mental health impacts of climate
change in rural Australia. The Journal of Climate Change and Health, 12, 100240.
Lundin, R. A., & S¨
oderholm, A. (1995). A theory of the temporary organization.
Scandinavian Journal of Management, 11(4), 437–455.
Masten, A. S., & Reed, M. G. J. (2002). Resilience in development. Handbook of Positive
Psychology, 74, 88.
Miller, F., Osbahr, H., Boyd, E., Thomalla, F., Bharwani, S., Ziervogel, G., … Hinkel, J.
(2010). Resilience and vulnerability: complementary or conicting concepts?
Ecology and Society, 15(3).
Morkan, B., Bertels, H. M., Sheth, A., & Holahan, P. J. (2023). Building megaproject
resilience with stakeholders: The roles of citizenship behavior and critical transition
mechanisms. International Journal of Project Management, 41(5), Article 102485.
Naderpajouh, N., Hastak, M., Gokhale, S., Bayraktar, M. E., Iyer, A., & Arif, F. (2015).
Counterfeiting risk governance in the capital projects supply chain. Journal of
Construction Engineering and Management, 141(3), Article 04014084.
Naderpajouh, N., Matinheikki, J., Keeys, L. A., Aldrich, D. P., & Linkov, I. (2020).
Resilience and projects: An interdisciplinary crossroad. Project Leadership and Society,
1, Article 100001.
Nardo, M., Saisana, M., Saltelli, A., & Tarantola, S. (2008). Handbook on constructing
composite indicators: Methodology and user guide. Paris, France: OECD publishing.
Nguyen, T. H. D., Chileshe, N., Rameezdeen, R., & Wood, A. (2023). Strategic responses
to external stakeholder inuences. International Journal of Project Management, 41(1),
Article 102434.
Oeij, P. R., Dhondt, S., & Gaspersz, J. (2016). Mindful infrastructure as an enabler of
innovation resilience behaviour in innovation teams. Team Performance Management,
22(7/8), 334–353.
Piperca, S., & Floricel, S. (2023). Understanding project resilience: Designed, cultivated
or emergent? International Journal of Project Management, 41(3), Article 102453.
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method
biases in behavioral research: A critical review of the literature and recommended
remedies. Journal of applied psychology, 88(5), 879.
Rachunok, B., & Nateghi, R. (2021). Overemphasis on recovery inhibits community
transformation and creates resilience traps. Nature communications, 12(1), 7331.
Renn, O., & Klinke, A. (2012). Complexity, uncertainty and ambiguity in inclusive risk
governance. In TJ Andersen (Ed.), The routledge companion to strategic risk
management (pp. 13–30). New York.
Ritchie, P. D., Clarke, J. J., Cox, P. M., & Huntingford, C. (2021). Overshooting tipping
point thresholds in a changing climate. Nature, 592(7855), 517–523.
Rockstr¨
om, J., Gupta, J., Qin, D., Lade, S. J., Abrams, J. F., Andersen, L. S., … Zhang, X.
(2023). Safe and just Earth system boundaries. Nature, 1–10.
Seidl, D., Lˆ
e, J., & Jarzabkowski, P. (2021). The generative potential of Luhmann’s
theorizing for paradox research: Decision paradox and deparadoxizationIn.
Interdisciplinary Dialogues on Organizational Paradox: Investigating Social Structures and
Human Expression, Part B, 73, 49–64.
Shang, G., & R¨
onkk¨
o, M. (2022). Empirical research methods department: Mission,
learnings, and future plans. Journal of Operations Management, 68(2), 114–129.
Shen, W., & Ying, W. (2022). Large-scale construction programme resilience against
creeping disruptions: Towards inter-project coordination. International Journal of
Project Management, 40(6), 671–684.
Singleton, R., & Straits, B. (2005). Approaches to social research (4th ed.). New York, NY:
Oxford University Press.
Sisto, A., Vicinanza, F., Campanozzi, L. L., Ricci, G., Tartaglini, D., & Tambone, V.
(2019). Towards a transversal denition of psychological resilience: A literature
review. Medicina, 55(11), 745.
Van de Ven, A. H. (2007). Engaged scholarship: A guide for organizational and social
research. Chicago: Oxford University Press.
Walker, B. (2020). Resilience: What it is and is not. Ecology and Society, 25(2), 11.
Whyte, J., & Mottee, L. (2022). Projects as interventions. International Journal of Project
Management, 40(8), 934–940.
Willemsen, M., Pollack, J., & Algeo, C. (2020). The role of project management in
threatened species recovery. International Journal of Managing Projects in Business, 13
(5), 981–998.
Williams, T. A., Gruber, D. A., Sutcliffe, K. M., Shepherd, D. A., & Zhao, E. Y. (2017).
Organizational response to adversity: Fusing crisis management and resilience
research streams. Academy of Management Annals, 11(2), 733–769.
Windle, G., Bennett, K. M., & Noyes, J. (2011). A methodological review of resilience
measurement scales. Health and quality of life outcomes, 9(1), 1–18.
Wood, M. D., Wells, E. M., Rice, G., & Linkov, I. (2019). Quantifying and mapping
resilience within large organizations. Omega, 87, 117–126.
Wooldridge, J. M. (2019). Introductory econometrics: A modern approach (7th ed.). South
West College ISE, New York: Cengage Learning.
N. Naderpajouh et al.
