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Building Digital Resilience Against Major Shocks
Waifong Boh
Nanyang Business School, Nanyang Technological University,
SINGAPORE {awfboh@ntu.edu.sg}
Panos Constantinides
Alliance Manchester Business School, University of Manchester,
Manchester, U.K. {panos.constantinides@manchester.ac.uk}
Balaji Padmanabhan
Muma College of Business, University of South Florida,
Tampa, FL, U.S.A. {bp@usf.edu}
Siva Viswanathan
University of Maryland, USA
{sviswan1@umd.edu}
Abstract
Major shocks such as the Covid-19 pandemic create unique and exceptional
challenges for different entities, including individuals, groups and organizations. In
this special issue editorial, we introduce the concept of digital resilience, which
refers to the capabilities to absorb major shocks, adapt to disruptions caused by the
shocks, and transform to a new stable state, where entities are more prepared to deal
with major shocks. The individual papers in this special issue offer compelling
examples of how digital resilience is exhibited and how the process of digital
resilience can unfold in response to specific major shocks. Drawing upon and
extending these papers, we present an integrated framework of how digital
technology can help build resilience capabilities that has been missing in past
research, but which is needed in mitigating and managing future major shocks
including financial recessions and climate change. We conclude with four important
themes for future IS research.
Keywords: Digital resilience, major shocks, resilience capabilities, complex systems and
connected ecosystems
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INTRODUCTION
The world stopped in March 2020. Whole countries went into lockdown, stores and factories shut
down, streets emptied and the skies were clear from airplanes flying into and out of destinations.
The SARS-CoV-2 virus shocked the world and caused a major pandemic that has come to be
known as Covid-19. This was certainly not the first pandemic the world has experienced. There
was the plague of Athens in 430 BCE, the Black Death in 1347 and the Spanish flu in 1918, among
many more (Christakis, 2020; Snowden, 2019). There were also two world wars and numerous
regional conflicts including the recent Russian invasion in Ukraine, as well as human-triggered
technological disasters (e.g., the Deepwater Horizon oil spill at the Gulf of Mexico) that devastated
humanity and our environment and disrupted everyday life.
Such major shocks, which we define as existential threats that pose continuous and long-term
risks to different entities, from individuals, groups, organizations, and institutions, and the
complex systems in which such entities live and function, are the focus of this special issue. Defined
in this way, major shocks will not have simple, predictable effects. Rather, as past research into
ecological and human-triggered disasters show, their effects will depend on how various entities
respond to such major effects over time (Constantinides 2013; Kwon & Constantinides, 2018;
Vogus & Sutcliffe, 2007). This naturally raises the question of how different entities can build the
capabilities to become resilient to major shocks.
Resilience is a concept first advanced in ecology (Holling, 1973). Early work on resilience focused
on resource management failures (e.g., in fisheries and animal habitats (see Armitage et al., 2007;
Gunderson & Holling, 2002)). It is associated with work on averting tragedies concerning common
pool resources (Hardin, 1968) through collective action and polycentric governance (Ostrom,
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1990, 2010). Whether through an emphasis on ‘natural’ evolutionary shocks (e.g. dominance of a
species in a habitat) or through human interventions into ecological systems (e.g. deforestation),
this early work placed emphasis on the ways by which entities dependent on those ecological
systems for common resources were able to achieve resilience. They did so by developing
capabilities to absorb the shocks while ensuring their survival and continued ability to function;
adapt to the shocks by making changes to adjust to the new environment; and transform their
resource management practices with new innovations to avert collapse while positioning
themselves to thrive in a fundamentally changed environment (Armitage et al., 2007; Gunderson
& Holling, 2002). Drawing on this work, we define resilience as the capabilities entities develop
to absorb a major shock, adapt to disruption caused by such a shock, and transform into a new
stable state, where entities are more prepared to deal with major shocks. Resilient entities can
survive in the face of adversity and can even take advantage of opportunities from the shock to
reform structures and processes in both themselves and in the complex system within which they
operate (Home III & Orr, 1997). Clearly, not all entities will be resilient; some will be fragile.
Fragility refers to succumbing to disruptions in ways that entities are left worse than before the
major shock. For example, during Covid-19, we have seen supply-chain disruptions hurt retailers,
digital divides hurt children and schools, cybersecurity attacks hurt businesses and governments,
and socioeconomic divides hurt health outcomes (Rai, 2020). In such situations, it is incumbent
on larger entities such as state or national governments and international organizations to provide
appropriate digital and other resources that can help smaller entitiesbuild resilience. Clearly, in
many cases, single entities by themselves may not be able to build the required resilience and will
often require ecosystems of entities to take actions.
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Resilience must be understood with respect to the specific threats and challenges of a major shock
(Allenby & Fink, 2005). Each major shock will lead to cascading effects and consequences, as in
the case of the Covid-19 pandemic that has led to national lock-downs, movements towards greater
protectionism, impacts on supply chain operations, global inflation, and disruptions to the social
and work lives of different entities. While we cannot address all these effects in this editorial, we
focus here on the role of digital technologies and specifically on the process of building digital
resilience.
Digital Resilience
With the increasing reliance on digital data as a critical resource, digital technologies with which
to collect and analyze such data become a natural tool to help manage knowledge about emergent
major shocks and build resilience. Digital resilience refers to the capabilities developed with the
use of digital technologies to absorb major shocks, adapt to disruptions, and transform to a new
stable state.
Many digital technologies can be involved in building digital resilience, including but not limited
to intelligent hardware such as IoT devices and sensors, databases and digital infrastructures, and
intelligent algorithms. Of course, digital technologies are not all implemented solely to achieve
digital resilience. For example, the Covid-19 pandemic forced organizations to use numerous
digital technologies to continue offering their services and products while complying with new
rules of global health (e.g., reducing contact with customers and increasing social distancing
amongst employees). Although some digital capabilities developed in earlier digital
transformation initiatives were no doubt important in building digital resilience, these capabilities
were often motivated and developed to achieve other objectives such as operational efficiencies
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and competitive advantages. These contrast with digital capabilities motivated and developed to
achieve digital resilience.
The case of just-in-time supply chains helps us clarify this distinction between digital
transformation and digital resilience. Prior to the Covid-19 pandemic, many industries were
adopting just-in-time supply chain strategies that prioritize short-term, flexible contracts with low-
cost suppliers usually in offshore locations, while relying on low stock inventories in home
locations. During and following the pandemic, companies employing just-in-time strategies
encountered huge disruptions in their supply chains due to unpredictable demand shocks, disrupted
manufacturing supplies, shipping bottlenecks, and global inflation of raw material prices.
Optimizing efficiencies in supply chain management has actually increased the fragility of these
supply chains, as opposed to building resilience. In light of new geopolitical shocks such as the
war between Russia and Ukraine, and also the looming shock of climate change, entities are now
increasingly building capabilities for resilience, focused on ‘just-in-case’[1] fluctuations in supply
and demand, price volatility, and social and environmental disruptions.
The IS literature on resilience has already emphasized the need for complex systems to build digital
capabilities to respond to and recover from disturbances, maintain system properties and core
practices, and rebound to an earlier state or move to a forward state (Floetgen et al., 2021; Heeks
& Ospina, 2019; Park et al., 2015). Capabilities such as diversifying products and services,
adapting business models, and scaling resources by quickly developing and deploying new digital
technologies are thought to be critical in building resilience for different entities. At the individual
level, no single entity can determine outcomes in a complex system (either their own, or a systemic
outcome), since each entitys decisions affect and are affected by others’ decisions and the external
environment (Benbya et al., 2020; Merali, 2006). Individual entities may be able to influence or
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guide emergent outcomes (Prawesh & Padmanabhan, 2021), but they will still be dependent on
the actions of other entities. At the same time, entities can utilize digital technologies to augment
their resilience capabilities of absorbing, adapting, and transforming in a manner that increases the
likelihood of desirable outcomes.
This special issue aims to advance our understanding of digital resilience by publishing path-
breaking studies of how different entities respond to major shocks using digital technologies.
During Covid-19, we have seen how digital technologies have played a major role in helping firms
build resilience in multiple domains from public health to remote work to innovation. This special
issue provides new theoretical and empirical insights that significantly enhance our understanding
of digital resilience. Our goal in this special issue editorial is to provide an overview of these
papers and lay out a research agenda to accelerate this work in further research.
The Special Issue Papers and Key Themes on Digital Resilience
The four empirical studies in this special issue each highlight the role of digital technologies in
enabling resilience across different entities – from individual physicians building resilience by
moving their patient consultations online; to universities reconfiguring their IT governance to
respond to the changing demands of remote and hybrid teaching; to online communities of open
source software developers adapting their contributions to different projects, and to state-wide
resilience in response to major health shocks including the opioid crisis and the Covid-19
pandemic.
As evidence from the special issue papers show, the absorb, adapt, and transform capabilities do
not have to be sequentially developed, but can, and indeed likely will, overlap during and after the
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shock. Indeed, some entities may jump from absorb to transform capabilities, while others will
only develop absorb or adapt capabilities. This process will vary depending on the underlying
characteristics of digital technologies as well as the organizational conditions for building digital
resilience. We explore these points in detail in the next section where we develop an integrated
framework for understanding digital resilience.
The key themes on digital resilience from each of the four special issue papers are summarized in
Table 1 and discussed below.
Table 1. Special Issue Papers and Key Themes on Digital Resilience
Empirical Study
Key Themes
Liu et al., 2022: A natural experiment
in a healthcare setting that matches two
longitudinal datasets collected from a
digital platform as well as offline (i.e.
physical) channels, spanning 26 weeks
before and after the first Covid-19
outbreak in China. The study
distinguishes between physicians who
use a digital platform to provide
services in addition to offering offline
services to their patients, and
physicians who provide only offline
services to their patients. Using
difference-in-difference models and
propensity score matching, the study
causally estimates the impact of using
digital vs offline services.
Absorb shock: Physicians who adopted a digital platform in
addition to providing services offline to their patients were able to
acquire new patients who transferred from the offline channel as
well as totally new online patients who had not consulted with the
physician previously. In contrast, physicians who only provided
offline services were less able to absorb the shock.
Transform to a new state: Physicians that were keen to
reconfigure their services with digital platforms and provide
online services were able to not only scale online consultations
but also increased their number of offline consultations by
transferring patients from the digital to the offline channel.
Conditions for building resilience
Only physicians who had a high positive sentiment in their online
interactions with patients and a high online reputation exhibited a
strong ability to absorb the disruption.
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Park et al., 2022: This study uses data
about IT spending for 463 US Higher
Education Institutions (HEI) combined
with student satisfaction ratings to
examine how centralized IT
investments help build resilience. The
study posits that centralized IT helps
organizations maintain satisfaction by
enhancing coordination of information
and resources, streamlining the
transition to emergency operational
mode; and by helping to prioritize the
resources across the organization to
provide technical support needed for
service operations. Using difference-
in-difference analyses the study
compares how the impact of the
pandemic on student ratings differs
across HEIs with higher and lower
centralized IT investments.
Absorb shock: HEIs with a larger investment per student in
centralized IT were more successful in absorbing the shock and
maintaining their student ratings.
Adapt to disruptions: The study finds that HEIs that invested more
in centralized IT adapted better to the transition to emergency
remote teaching (ERT) as measured by student satisfaction ratings
during the pandemic.
Conditions for building resilience
Higher levels of resilience are not driven by IT applications that
are specific to unique needs in the educational sector (e.g.,
educational technology and research computing), but instead are
related to aspects that help facilitate the processes of making
organizational changes and coordinate and support internal
operations across an organization. Qualitative interviews with
CIOs of HEIs find that the centralized IT investments for
facilitating organizational coordination and providing
instructional support application and technical support, rather than
educational software and applications for facilitating student
learning, drive the success of ERT as measured by student
satisfaction
Malgonde et al., 2022: Using data on
the contributions of over 18,000 open
source software (OSS) community
members, this study examines how
major shocks impact developers’
contributions to other projects vis-a-vis
their own projects. Using a large
dataset comprising over 1.4 million
observations, the study carries out
panel regression models and
difference-in-difference analyses of the
changes in contribution behaviors of
OSS community members in response
to two different types of major shocks
– the Covid-19 pandemic, as well as
unemployment.
Absorb shock: The pandemic shock increased the OSS community
members’ contributions to others’ projects relative to their own
projects, while the unemployment shock decreased the OSS
community members’ contributions to others’ projects relative to
their own projects. Contributions to others’ projects typically
require an individual member to invest significantly more effort as
compared to contributing to one’s own project. If OSS community
members maintain and/or increase their contributions to others’
projects relative to their own in the face of major shocks, this
would have significant implications for the resilience of the OSS
community as a whole.
Conditions for building resilience
Depending on the type of major shock faced, motivations will
vary. While a pandemic leads to primarily a loss of interaction and
is more likely to evoke prosocial behaviors in community
members, the potential loss of a job threatens economic security
leading to a greater focus on oneself and career.
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Tremblay et al., 2022: An in-depth,
mixed-methods study using interviews,
participant observation and statistical
data into how the Commonwealth of
Virginia (COVA) made use of data and
analytical capabilities to respond to
two challenging health crises – the
Opioid crisis and the Covid-19
pandemic.
Absorb shock: Ensuring data availability in a timely manner
allows decision makers to intelligently sense their environment,
achieve data integration across sources, and give decision-makers
the tools to absorb shocks by balancing between the conflicting
objectives and trade-offs of diverse domains (e.g. health vs
economics).
Adapt to disruption: Based on data, COVA was able to adapt its
practices to address both health needs (e.g. increasing hospital bed
capacity, and testing centers) and economic demands (e.g.
providing tax reliefs to individuals that lost their jobs)
Transform to a new state: designed and implemented new data
sharing agreements between agencies and private organizations
that enabled de-identified data to be exchanged at scale and on
demand. This provides the capabilities for the organizations to
share the required data when affected by the next major shock.
Conditions for building resilience
Data exchange is very much dependent on building trust between
collaborating parties first and in reinforcing such trust with robust
governance structures and mechanisms
Individual Physicians Transforming their Practices During the Covid-19 Pandemic
Liu et al (2022) examine the role and effectiveness of online healthcare communities (OHCs) in
increasing individual physicians’ resilience to the shock created by the first wave of the Covid-19
pandemic in China. A significant contribution of this study is the characterization of digital
resilience. Drawing upon prior work that highlighted the need to consider different phases of the
disruption caused by the major shock – the pre-disruption period, the disruption period, and the
post-disruption period – Liu et al (2022) primarily focus on the immediate and subsequent periods
post-disruption and the role of OHCs in the resistance and the recovery aspects of resilience.
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According to this, resistance focuses on the immediate period post-disruption and involves an
individual’s ability to minimize the initial loss created by the disruption; recovery, a measure of
the individual’s ability to rebound quickly from the disruption, involves minimizing the amount
of time taken to return to normal performance levels in the subsequent period. Thus, resistance and
recovery highlight the need for explicitly taking into consideration the temporal aspect of the
disruption created by the major shock. In their study, Liu et al (2022) examine the effectiveness of
OHCs in contribution to resistance by mitigating the production loss caused by the pandemic for
individual physicians, and the effectiveness of OHCs in enabling recovery by analyzing the extent
to which physicians used the OHCs to enable rapid resumption of their healthcare services. These
correspond to the absorb and transform capabilities of digital technologies as described in the
framework in Table 2.
Higher Education Institutions and the role of IT Governance in Building Digital Resilience
Park et al (2022) examine the role of IT governance in enabling organization-level digital
resilience to the disruption caused by the pandemic in the context of Higher Educational
Institutions (HEIs). While prior studies have highlighted the trade-offs between the coordination
efficiency of centralization and the responsiveness enabled by decentralization and suggested
that decentralized governance of IT is better for organizations to be nimble and responsive to
dynamic and uncertain environments, Park et al (2022) find that the opposite is true in the case of
the severe disruption and extreme levels of turbulence and uncertainty caused by the Covid-19
pandemic. The magnitude and unprecedented nature of the disruption forced many HEIs into a
rapid emergency response mode that heightened the importance and benefits of centralized
coordination as compared to the benefits of flexibility enabled by decentralization. The empirical
findings of this study highlight the need for further studies that examine the boundary conditions
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of these trade-offs imposed by different types of IT governance structures and their role to build
digital resilience.
Open Source Software Communities’ Contributions to Build Collective Digital Resilience
Malgonde et al (2022) examine community level resilience with a specific focus on Open Source
Software (OSS) communities and how they can stay resilient in the face of major natural and
economic shocks through adaptations at the individual level by community members. Their
findings provide interesting insights about how different types of major shocks could impact
individual motivations and behaviors in different ways with significant consequences for the
community at large, giving great insights into how communities absorb and adapt to different types
of external shocks. The study adds to our understanding of digital resilience by broadening the
discourse on digital resilience beyond the effects of digital technologies by examining how major
shocks can impact individuals’ motivations and contributions to the creations of public digital
goods. This study also emphasizes the importance of understanding the motivations behind
individual behaviors, and how they may change in response to different major shocks.
State Governments’ use of Data Analytics in Building Digital Resilience
The Covid-19 pandemic has unequivocally underscored the important role that governments play
in ensuring the resilience of citizens. Local and national governments have responded to the
pandemic with wide ranging regulations and measures that have significant trade-offs– while
saving lives and ensuring the health of the population are critically important, such measures often
compromise the freedom of populations and cause significant disruptions to how people live, work,
and learn. Similarly, governments have to make important decisions about how they should
allocate their limited resources. The pandemic has made great demands across countries on their
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healthcare expenditures and requirements for economic subsidies for jobs, businesses, and
individuals who are affected by the measures imposed by governments. The case presented by
Tremblay et al (2022) aptly illustrates how data and digital resources help to create digital
resilience by allowing decision-makers to make decisions that manage these trade-offs. Overall,
this paper presents important contributions to the literature by fleshing out how the intelligent
sensing capabilities of an entity helps in building digital resilience.
A THEORETICAL FRAMEWORK FOR DIGITAL RESILIENCE RESEARCH
Building on the key themes of the special issue papers, we propose a theoretical framework that
can help us to understand how entities can build digital resilience. This framework integrates prior
IS research on resilience by elaborating on how the capabilities of absorb, adapt, and transform
can be developed while leveraging on different characteristics of digital technologies, as
summarized in Table 2. The framework also elaborates how developing these resilience
capabilities will be conditioned by organizational structures, processes, and the motivations of
different entities. Together, the characteristics of digital technologies and organizational
conditions provide an integrated framework of how entities can build resilience and mitigate major
shocks. We offer empirical evidence from the special issue papers, as well as examples of how
other entities responded to major shocks.
Table 2. A Theoretical Framework for Digital Resilience Research
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RESILIENCE CAPABILITIES
Absorb
Adapt
Transform
Digital Technology
Characteristics
• Redundancy:
Creating diversity of
options for
continuity.
• Intelligent Sensing:
Gathering and
analyzing data to
anticipate and
withstand the shock
• Ubiquity and
Accessibility:
Responding quickly to
disruptions
• Experimentation:
Engaging in rapid
learning, development,
and implementation
• Reconfigurability:
Leveraging the
modularity and
recombinability of
digital technologies
• Scalability:
Leveraging the
power of digital
platforms
Conditions for
Building Resilience
• Coordination:
Facilitating internal
operations,
identifying redundant
(or slack) resources
and supporting their
swift utilization
across a collective
• Data Governance:
Organizing
structures for
ensuring trust on the
use of data between
collaborating entities
• Organizational
restructuring:
Enacting
organizational routines
to leverage available
technologies (e.g. move
from offline to digital
activities)
• Adaptive culture and
positive mindset:
Being open and flexible
to experimenting (and
failing) with new ways
of working
• Business model
innovations:
Assessing the impact
of reconfigured
technologies on
existing and new
business
opportunities
• Ecosystem
strategies: Building
multilateral
complementarities
that can enable scale
and stronger
resilience against
future shocks
Absorbing a Major Shock
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Absorption refers to the capability to withstand shocks while preserving the original structure and
operations of an entity (Martin & Sunley, 2015; Sutcliffe & Vogus, 2003). This may entail
minimizing the initial loss immediately after the occurrence of a shock to ensure the continued
survival of the entity. There are plenty of examples of entities that have taken such a big hit from
the Covid-19 pandemic and the subsequent measures that they eventually succumbed. Others
exhibited a greater ability to absorb major shocks and are still operational. The absorb capability
serves to loosen the coupling between the entity and the changed environment, attempting to
reduce variations through changes that enable entities to cope with the major shocks.
A good example of entities’ capability to absorb the shock by the Covid-19 pandemic come from
the airlines industry, which was particularly hard hit. Some declared bankruptcy, while others
worked hard to absorb the shock to survive the pandemic. Singapore airlines came up with a series
of creative approaches to generate alternative revenue streams. These include providing dining
experiences for customers on stationary planes and flights to nowhere, which proved to be highly
popular for travel-deprived individuals, home delivery of flight meals and even flying lessons in
simulators. Singapore airlines also redeployed their cabin crew to the healthcare sector as “care
ambassadors” and refitting their passenger planes to carry cargo rather than passengers. [2] While
these initiatives certainly do not present systemic changes to their business models, they present
an attempt to use otherwise idle resources in innovative ways to absorb the shock presented by the
pandemic to ensure the survival of the airline.
This idea of using idle resources or “slack” has been extensively discussed in the literature on
supply chain management and is the opposite of just-in-time strategies we discussed earlier. For
example, slack in inventory and cash can potentially help organizations to absorb fluctuations in
inventory availability and resource requirements caused by major shocks (Kovach et al., 2015).
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This slack in physical resources often goes hand in hand with redundancy enabled by digital
technologies, which we describe next.
Redundancy: Creating diversity of options for continuity
The redundancy associated with digital technologies helps entities to ensure continuity while
absorbing shocks (Sahebjamnia et al., 2015; Wang et al., 2010). We highlight the importance here
of both redundancy of digital technologies, and redundancy enabled by digital technologies, since
both have played major roles in absorbing the shock during the Covid-19 pandemic.
As most organized activities moved online, many entities (e.g. universities with cloud e-learning
systems in place) benefited from inherent redundancies provided by cloud computing
infrastructures that supported the sudden increase in the use of computational and data resources.
These infrastructures are designed to be redundant, scalable, to have increased fault tolerance, and
to lower switching costs of firms, so that if one data storage or computing facility goes down in a
major shock alternate facilities can take over (Cheraghlou et al., 2016), which can help during a
major shock[3]. Cloud service contracts can provide significant redundant capacity for businesses,
which can help during a major shock.
Even in cases where slack resources are not readily available, cloud infrastructures provide low
switching costs and swift scalability. In this case, digital technologies enable redundancy. In retail,
for instance, traditional stores were able to support customer interactions through alternate digital
channels (e.g. Instacart) as well as mobile payment apps. In the case of universities in-person
teaching was supplemented or replaced by virtual or hybrid classes, as Park et al., (2022) show in
their study. This redundancy was enabled by existing digital technologies (e.g. Zoom, MS Teams)
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as well as combinations of other apps for virtual classroom interaction (e.g. Miro, Kahoot!), all of
which were enabled by cloud computing infrastructures.
At the same time, as Park et al., (2022) show in their study, the capability to absorb requires
processes for facilitating internal operations, identifying redundant (or slack) resources, and
supporting their swift utilization across a collective. Swiftly switching to an alternative operational
mode is paramount to absorbing the shock. Liu et al (2022) show that despite the sudden drop in
the number of offline consultations for all physicians, physicians who had adopted the online
health community (OHC) portal prior to the onset of the pandemic, were able to resist the
disruption and absorb the shock much better than the physicians who primarily stayed with the
offline channel. While the OHC portal would have served as a secondary channel for physicians
and their patients prior to the pandemic, this redundancy proved to be a lifeline during the
pandemic, helping physicians effectively absorb the shock caused by the sudden and significant
disruption in offline visits. Liu et al (2022) also show that specific attributes of the digital channel
such as the visibility of the physicians’ online reputation and the positivity of their online
interactions were key drivers of their ability to absorb the shock caused by the pandemic.
Intelligent Sensing: Gathering and Analyzing Data to Anticipate and Withstand the Shock
Another important attribute of digital technologies that enables organizations to build capabilities
for absorbing major shocks is the intelligent sensing characteristics of digital technologies. We see
greater use of real-time analytics and decision-making utilizing intelligent algorithms. As shown
in the COVA case described in Tremblay et al (2022), intelligent sensing helped entities make
informed decisions that considered important trade-offs in a highly uncertain environment,
enabling targeted strategies, rather than one-size fits all approaches that come at a high cost.
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The increasing analytical power of digital technologies enable entities to monitor changes in the
environment and to record, store, communicate, and analyze the data collected (Yoo, 2010). For
example, countries like Taiwan and Singapore have made use of contact tracing apps that leverage
mobile devices to collect information about the locations of individuals and their interactions with
other nearby devices. Such devices and apps equip entities to collect different types of information
in an unobtrusive manner, increasing the context awareness of individuals and facilitating contact
tracing when the need arises (Dourish, 2001). The greater the information collection and analytical
capabilities of digital technologies, the greater the specificity of information and focus it enables
(Nambisan, 2017). Thus, entities can better identify novel interactions and strategies to adopt in
response to emergent major shocks.
During the Covid-19 pandemic for instance, as consumers flocked online, ecommerce faced many
challenges including having to adapt to new consumer queries on search engines, as consumers
are now using online channels to buy products they might have previously purchased at a store
(Guthrie et al., 2021). Google Analytics tools provide the real time capability to sense such
changing queries, allowing online retailers to change their search engine advertising strategies to
adapt and respond to consumers. Given how tight margins in retail often are, such ability to sense
in real time can help firms withstand the shock.
Healthcare itself was managed more effectively during the crisis thanks to intelligent sensing. For
instance, Tampa General Hospital[4] partnered with other hospitals in Florida early on during the
pandemic to construct a real-time dashboard using shared data to monitor resource (beds/ICU)
availability and patient volume and trends, helping all the hospitals in the region. The University
of Minnesota also launched a comprehensive hospitalization tracking dashboard that provided a
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real-time glimpse of how hospitalizations were trending across the US. [5] Hospitals and
governments were better able to absorb the shock by using such information to proactively plan
for resource needs.
Many firms also faced increased inventory costs and supply chain disruptions due to difficulties
in forecasting demand as consumer behaviors changed and supply chains were disrupted. Nike,
for example, faced problems related to labour shortages and in calibrating their supply and
demand[6]. In pursuit of a more dynamic supply chain network the firm relied on RFID
technologies to increase inventory visibility, along with increased predictive analytics to better
forecast demand and bring their products to the right places. While these examples show the
importance of building intelligent sensing capabilities to effectively adapt to changing demand and
supply during a major shock, the importance of robust governance structures to ensure effective
sharing and usage of data is critical. As Tremblay et al., (2022) show, barriers related to data
sharing and use can only be overcome if such governance structures are in place that ensure
trustworthiness and relationship building between collaborating entities.
Adapting to Disruption Caused by a Major Shock
In addition to absorbing a major shock, resilience also entails the capability to adapt to adversity
(Hollnagel et al., 2006). Researchers have also referred to adaptation as rebounding – to the
previous or to a better state (Woods, 2015). To do so, entities need to function in an environment
which may be significantly different from the original state, and established operations, processes,
models, or assumptions will have to change to adjust to the changed environment. Entities can
adapt by responding quickly to disruptions through ubiquitous and accessible technologies, as well
as by learning, developing, and implementing changes through experimentation.
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Ubiquity & Accessibility: Responding Quickly to Disruptions
Advances in computer storage, communication hardware and software have made digital
technologies highly ubiquitous – such that the functioning of social and business systems are
inseparable from the use of technology (Yoo, 2010). This ubiquity and accessibility of digital
technologies – such as end-user computing devices (phones/ipads), intelligent algorithms, robotic
systems, cloud-enabled enterprise systems and data analytics - have made a significant difference
in enabling organizations to adapt to major shocks. Such ubiquitous and accessible technologies
are increasingly augmenting our financial transactions, power grids and transportation systems,
healthcare services, and supply chain and logistics networks.
For example, one medium enterprise in Singapore that distributed and installed manufacturing
technology for clients found that they were able to ship the machinery to clients overseas, only to
have the technology sitting on clients’ shop floors as their engineers could not travel to the clients’
premises to help them with the installation. The company adopted augmented reality glasses - by
shipping the glasses to clients, their engineers could see what the local engineers saw and they
could give the clients’ engineers detailed instructions to help them to install the technology.
Similar examples have shown up in other sectors as well. In social service for instance, the Greater
Boston Food Bank[7] used widespread access to devices and technology to switch to contactless
service and curb side pickups to continue to battle (increased) food insecurity during the Covid-19
pandemic. To combat the fear of exposure to the virus, the food bank used robots to clean and
sanitize places that may have had exposure. These initiatives highlight that ubiquity and
accessibility of technology during the crisis was critical to enable adaptation to disruptions.
21
While digital technologies and tools may be ubiquitous and accessible, organizations must be
prepared to make internal organizational changes to tap on these digital technologies. To leverage
the widespread availability of digital technologies to quickly convert their usual offline activities
to online ones, organizations need to make changes to multiple aspects of their internal processes
and staff capabilities and to make quick pivots in their business. This suggests that firms that are
better equipped to make rapid adaptations and who are more digitally prepared may be in better
shape to make the adaptations needed to leverage such digital technologies. For example,
American Eagle Outfitters acquired a digital fulfilment operator to enable them to take greater
control of its supply chain. [8] The digital fulfilment operator supplements their digital capabilities
with robots that aid them in fulfilling shipping orders for digital apparel and lifestyle brands. Such
capabilities are increasingly required as retailers turn to online platforms that require them to
prioritise rapid delivery to homes and minimize shipping costs where possible. This example
shows that while digital technologies are ubiquitous and the adoption and shift to such technologies
may be logical during the pandemic, organizations need to acquire wider capabilities to effectively
leverage such digital technologies.
Experimentation: Engaging in Rapid Learning, Development and Implementation
In adapting to the disruptions caused by a major shock, entities engage in experimentation with
new services and products through agile methods such as DevOps and SCRUM (Abrahamsson et
al., 2017). The uncertainty caused by the major shock, coupled with the need to adopt new
technologies suggest that organizations are faced with multiple possibilities and options, often
without a clear idea of the path forward that can help them to best adapt and recover from the
shock. As digital technologies can enable new product ideas and business models to be quickly
22
formed through new cycles of experimentation, the options facing organizations become much
less bounded (Yoo et al., 2010). For example, with consumer behaviors changing quickly due to
the pandemic (Sheth, 2020), online platforms that have built-in A/B testing capabilities enabling
rapid, real-time experimentation help firms to remain adaptable through rapid experimentation
(Kohavi et al., 2020). Another interesting example is how the Mosaic Youth Theater of Detroit
embraced the idea of “small experiments with rapid intent” to explore different ways of delivering
the same training, coaching, and mentoring services through online channels. The lessons learned
from this are changing the way Mosaic offers its services to budding artists in a post-pandemic
world as well.
While digital technologies can be rapidly adopted and changed, entities need to have an adaptive
culture and positive mindset to engage in experimentation and failing. For example, Liu et al.,
(2022) show that physicians who were able to adapt to disruption had more positive sentiment
about the changes needed to provide medical services on both digital platforms and through face-
to-face consultations. It was their adaptive mindset and personal resilience to the shock that
allowed them to experiment with new ways of working.
Transforming to a New Stable State
A major shock may bring with it a realization of the significance and importance of change that is
needed with a new reality resulting from the shock. Such deep and revolutionary changes may not
be achieved with short term adjustments and quick fixes that organizations use to adapt to the
shock. Rather, these require fundamental transformations (O’Brien, 2012; Pelling, 2010) that may
entail the development of new capabilities, changing organizational structures (Fjeldstad & Snow,
2018), or even new business models (Teece, 2018).
23
The Deepwater Horizon Oil Spill in the Gulf of Mexico was an ecological disaster and served as
a wake-up call for the industry. Over the years, the industry has transformed itself through the use
of a plethora of digital technologies to avert such disasters. These technologies provide mitigation,
detection, characterization, and quick remediation associated with oil spills and gas releases. For
example, the oil and gas industry has adopted “AI Digital Twin” technologies – a digital
representation of the entire process that enables real time analytics of the health of assets, while
enabling “what if” scenario planning to detect faults before an issue arises. In addition, the use of
IoT technologies, more sophisticated predictive modelling of oil spills and ocean currents, remote
sensing technologies, real-time analytics from sensors, and pattern recognition of normal and
abnormal behaviors from different equipment have dramatically improved the industry’s resilience
to such major shocks.
Reconfigurability: Leveraging the Modularity and Recombinability of Digital Technologies
These set of emerging digital technologies used in the oil and gas industry have been characterized
as modular and recombinable. Modularity refers to systems that are designed to be composed of
distinct and relatively self-sufficient units loosely coupled through well-defined interfaces
(Baldwin and Clarke, 2000). Modularity is often desirable because highly integrated and coupled
system designs are hard to understand and change, whereas modular systems are easier to amend
and thus functional modifications can take place more easily (Yoo et al., 2010). Various modules
of digital technologies can thus be readily recombined to generate systems and objects with new
functionalities (Arthur, 2009). Changes in the environment require organizations to adapt existing
technologies in new ways or to quickly repurpose and combine existing technologies to help the
24
organizations recover and rebound from a major shock. The reconfigurability of digital
technologies is thus critical for building digital resilience.
Continuing on an earlier example, the Greater Boston Food Bank was motivated by the crisis to
transform into a “digital first” organization (Baskerville et al., 2020), by leveraging existing
technologies it had (predictive analytics, warehousing technology, mobile devices, collaboration
technologies), and implementing some new ones, in ways that create a digital-first experience for
all their stakeholders (food recipients, donors, distributors and government programs and
agencies). This required them to rethink the entire experience from the perspective of each
stakeholder, and design new solutions that had a mix of using old components and embracing some
new ideas as well.
The reconfigurability of digital technologies may be a boon, or bane, as rapid changes to digital
technologies can be made with deep learning and reflections, or in quick iterations without much
thought. Organizations need to reflect on the key learnings in each phase of their adaptation and
transformation process, to understand how digital technologies should be adapted to help them
prepare for the next shock. This requires organizations to be able to evaluate their options, while
understanding the trade-offs of the reconfigurability of digital technologies on new and existing
business models.
Scalability: Leveraging the Power of Digital Platforms
While the ability to rapidly learn through experimentation accompanied by the ease of
reconfigurability of digital technologies enables organizations to quickly identify ways to adapt to
the external shocks, the successful new configurations would have to be scaled quickly to meet the
needs of the “new normal”. Moving beyond experimentation and pivoting to a new configuration
25
could lead to sudden surges in demand, access to new markets, and influx of new customers with
different needs. The scalability of digital technologies enables firms to handle such sudden surges
in demand. A sudden increase in demand could have ripple effects and impact other processes such
as security, as well as performance metrics such as speed of response.
Digital platforms provide digital resources to enable value creating interactions between different
entities and do so while leveraging demand-side economies of scale (Constantinides et al., 2018;
Parker et al., 2017). During the pandemic several restaurants were forced to close down in-person
dining. However, the availability of platforms such as DoorDash and Ubereats enabled these
restaurants to quickly switch to catering to take-out orders that enabled them to continue their
operations at scale and also gain access to new markets. Other platforms such as Marketboomer
and Fairmarkit have enabled different entities to scale quickly without compromising on key
performance indicators. Both Marketboomer and Fairmarkit incentivize buyers to bring their own
existing suppliers to their sourcing and procurement marketplaces. The appeal for suppliers is
having a better platform for interacting with their existing and potentially new customers (e.g.
managing schedules, payments, records). At the same time, competition between suppliers benefits
buyers across different verticals in relation to search and transaction costs. Digital platforms can
accelerate indirect network effects and help entities scale and expand their deployment as they
identify solutions and approaches that work. This helps entities to transform by injecting new
capabilities to position themselves to cope in the new environment.
The pandemic, for instance, accelerated the transformation of higher education toward remote,
online educational offers by universities. [9] This transformation has been in the making for the
last two decades, as it reflects the complex landscape posed by a generative digital transformation
26
of business activities. Platforms like Coursera, edX and Udemy have started offering Massive
Open Online Courses (MOOC) that are designed to scale on demand as a way to address the
growing skills gap in emerging technologies, while recruiting instructors on demand, on the basis
of their expertise in specific topics. A current strategy of MOOC providers is to become partners
with universities rather than compete with them, by helping them to outsource their online degrees
and thus gain the trust of learners. Universities can choose how much of the total student
experience to outsource to these providers, from marketing and recruitment, admissions, online
course management, curriculum design, and course instruction and assessment. Evidently, just like
other entities, universities face significant disruption at scale that requires partnerships across the
higher education ecosystem. The scalability of digital platforms will likely play a key role in
shaping this future.
IMPLICATIONS FOR RESEARCH, POLICY AND PRACTICE
The proposed framework inspired a set of themes for future research, which we discuss in this
section. In so doing, we build on our theoretical framework but extend the focus into broader areas
where research, policy, and practice might be productively pursued for further research into digital
resilience. We refer to these themes as: (1) the development of public-private ecosystems to build
resilience across entities; (2) the design and implementation of governance structures for
collective action against major shocks; (3) policy reforms to address digital inequalities; and (4)
the temporality of resilience capabilities. Table 3 summarizes these themes.
27
Table 3. Themes for Further Research, Policy and Practice
Theme
Relevance
Possible research questions
The development of
public-private
ecosystems to build
resilience across
entities
Emergent environmental, health, and
business shocks (e.g., climate change, global
inflation) require national governments,
nongovernmental organizations (NGOs), and
private sector firms to work together to build
collective resilience. This requires data
sharing and co-investment in digital
technologies.
To ensure the rapid provision of goods and
services in anticipation of future external
shocks, public entities may need to build
digital infrastructures and develop
mechanisms that enable better coordination
with private entities.
• How can potentially conflicting
objectives be jointly pursued while
building digital resilience for
diverse entities?
• How can digital technologies be
deployed to support and sustain the
development of public-private
ecosystems for digital resilience?
The design and
implementation of
governance and
regulatory structures
for creating digital
resilience to enable
collective action
against major shocks
Digital tools and platforms enable rapid
experimentation to drive digital
transformation and innovation, helping
entities to adapt and transform. Such tools
and platforms, however, give much power to
platform providers.
In addition, data is also often controlled by a
powerful few, who use such data to innovate
new services and products but also to
prepare for the next major shock.
Centralization and digital platforms tend to
concentrate power, which may pose a threat
to resilience if such power is not
appropriately governed.
More adaptive governance structures are
needed for digital resilience to enable
collective action against major shocks.
• What are appropriate governance
and regulatory structures with
which to counter major shocks
while balancing the needs of
different stakeholders?
The need to institute
reforms and
mechanisms to address
digital inequalities
There are significant digital inequalities
between entities in relation to access to
digital technologies such as connectivity and
mobile devices but also in relation to
entities’ capabilities to gain benefits from
their use of technology.
These digital inequalities become
accentuated during major shocks, with
• How can existing policies be
reformed and mechanisms
introduced to reduce digital
inequalities and help entities to
build resilience?
28
significant negative implications for building
health and economic resilience.
The temporality of
resilience capabilities
Capabilities enabled by digital technology
can help entities become more resilient but
they must exist prior to the major shock.
Preparation is important. Building
capabilities to withstand major shocks is an
important and potentially expensive effort.
Like cybersecurity and disaster recovery
planning, strategizing how exactly this needs
to be done also must be a priority.
• How can entities prepare to build
digital resilience to major shocks?
• How do the absorb, adapt, and
transform capabilities play out in
time to respond to major shocks?
The Development of Public- Private Ecosystems to Build Resilience across Entities
The looming global recession, inflation, and constrained access to affordable raw materials is
creating a tsunami of shocks for the private and public sectors, each struggling to find ways to
circumvent high costs while ensuring the sustainability of everyday operations. This tsunami of
shocks is compounded by the devastating effects of climate change, themselves strangle-holding
access to resources for some entities and causing waves of economic migration to (yet) unaffected
areas. On top of this, the Covid-19 pandemic has not only surfaced the challenges faced by the
global health system, including shortages in basic medical supplies for developing countries, but
has also revealed a complex ecology of pathogens – such as the recent monkeypox re-emergence
– that may break free at any given point, reproduce, and thrive exactly because of our
interconnected social and business lives. Furthermore, supply chain fragility has been a significant
issue in previous major shocks. The supply chain crisis has also been exacerbated by factory
closures, worker shortages, and higher energy costs. These present an urgent need to design and
develop public private partnerships that can help us collectively be more responsive during the
next crisis, and more generally, to help build resilient supply chains.
29
All these emergent major shocks require national, state, and international governments to work
together with private sector firms to build resilience. We term these public-private ecosystems
because they go beyond a single government or group of companies to encompass a wider set of
public and private sector entities. For public-private ecosystems to work together to build
collective resilience, this requires sharing of data and co-investments into digital technologies. As
noted by Trembley et al (2022), such partnerships require the building of trust and relationships,
and conscious building of capabilities. There is, however, greater scope to examine how digital
infrastructure and technologies can enable better coordination in public-private ecosystems and
how to facilitate digital resilience in such partnerships. Further research can more explicitly
examine the role of digital technologies in public-private ecosystems. Some relevant research
questions include: How can potentially conflicting objectives (i.e., private vs public good) be jointly
pursued while building digital resilience for diverse entities? How can digital technologies be
deployed to support and sustain the development of public-private ecosystems for digital resilience?
The Design and Implementation of Governance and Regulatory Structures
for Collective Action against Major Shocks
Digital tools and platforms helped entities ranging from individuals to large and small businesses
adapt and transform themselves in response to the Covid-19 pandemic, leading to rapid
experimentations and adoption of digital technologies and platforms. Such platforms, however,
tend to concentrate much power in the hands of a few powerful providers. As shown by Park et al
(2022), in the case of severe disruption and extreme uncertainty resulting from the Covid-19
pandemic, the requirement for a rapid emergency response mode creates a greater need for
centralized coordination. Such centralization of power may pose a threat to resilience if such powers
30
are not adequately governed and regulated. Equally, power concentration can exclude alternative
viewpoints engendering polarization and “ideological groupthink” (Kitchens et al., 2020).
The need for effective governance of common pools of resources to build resilience for
heterogeneous collections of entities (Ostrom, 1990, 2010) also highlights important inequalities
that need to be tackled for us to achieve resilience, yet there are immense challenges given the
multitude of entities involved and their diverse interests and resource constraints (Constantinides
and Barrett 2015). For example, as the Covid-19 pandemic has shown, the development of new
vaccines to contain the spread of infectious and deadly diseases is infused with value conflicts.
There are critical inequalities when it comes to access and availability of vaccines across the globe
and this has caused stark criticism against patent protection and ownership when the greater public
health good is concerned. [10] While patents and ownership are important incentives for driving
innovation in new drug development, those can also limit inclusive access across the globe.
In addition, data about critical trends in anticipating and containing major shocks are also
often controlled by a powerful few that may exclude smaller entities from opportunities to plan
and prepare for such shocks. In the case of the Covid-19 pandemic, the exact disease prevalence
including how specific variants were spreading was often available to only select governmental
agencies in real time. Similarly, supply chain visibility including the availability of specific goods
was restricted to the few who manufactured and distributed products, or institutions that oversaw
these. In financial markets a handful of entities that facilitate order entry and execution have an
early window into potentially large market collapses, such as recently seen in the crypto markets
worldwide. Today there is a movement aligned with the growth of blockchain ecosystems where
individuals might directly control and monetize their data and social capital by mechanisms such
as individual tokens. [11] If such ideas grow to include other types of data, then we may see a
31
future where blockchain-based solutions for real-time data access can address some of these
inequalities.
In addition to governance mechanisms, regulatory changes are also essential to ensure that
entities adopt technologies and processes that can improve their resilience to future shocks. For
instance, the Deepwater Horizon disaster sparked a series of regulatory actions and reforms
designed to have a more lasting impact on the safety of future operations, including a major agency
reorganization and ultimately new safety and environmental requirements (Vizcara, 2020). The
years following the disaster saw improved regulatory oversight designed to better balance
environmental and safety concerns with energy development, including new certification
requirements, new requirements for systems, additional inspection and testing, among others.
There were also significant reorganization of regulatory agencies and the creation of new agencies
such as the Bureau of Safety and Environmental Enforcement (BSEE), responsible for safety and
environmental enforcement. These coordinated efforts at regulatory reforms have significantly
contributed to building resilience for the industry. However, as Vizcara (2020) notes, constant
vigilance is required for regulatory oversight, based on new technologies, operations, and
developments in the industry.
Further research can more explicitly examine the role of digital technologies in designing
governance structures and the role of regulatory reforms for collective action against major shocks,
including the governance and regulations relating to digital ecosystems that may concentrate
power on some. Some relevant research questions include: What are appropriate governance
structures and regulatory mechanisms with which to counter major shocks while balancing the needs
of the different stakeholders?
32
Reforms to Address Digital Inequalities
The Covid-19 pandemic has exposed significant digital inequalities between entities in
relation to access to digital technologies such as the Internet and mobile devices, but also in relation
to their capabilities in gaining benefits from their use of technology (Beaunoyer et al., 2020). Such
capabilities include the “knowledge, motivation, and competence to access, process, engage, and
understand the information needed to obtain benefits from the use of digital technologies, such as
computers, Internet, mobiles devices and applications” (ibid. 1). As many studies have shown,
such digital inequalities are deeply embedded in social, economic, and cultural contexts and have
significant, negative implications for building health (including mental health) and economic
resilience (Brooks et al., 2020; Fernandes, 2020).
Many of the points we raised earlier around the importance of developing public private
ecosystems and designing governance structures for collective action lay the ground for policy
reform and mechanisms to addressing digital inequalities. For example, it has previously been
proposed that cities should be allowed to provide their own broadband and to provide devices for
children[12],[13]. Such policy proposals require not only strong collaborations between the public
and private sectors but also a deeper engagement with market competition frameworks around the
supply of basic utilities. Even if access was provided in an equitable manner to all groups in society
we have seen that the use of these resources could widely vary as well, based on knowledge and
access to other resources. For instance, as the world moved online it was easier to find advanced
tutors who could coach students online; yet, doing so required access to other (financial) resources,
which are unevenly distributed. Given our understanding of how these can play out, what policies
33
might be needed to level the playing field such that future major shocks are not accompanied by
digital inequities of the kind we saw during the Covid-19 pandemic?
More generally, further research can more explicitly examine the role of digital
technologies in designing governance structure for collective action against major shocks. Some
relevant research questions include: How can existing policies be reformed and mechanisms
introduced to reduce digital inequalities and help entities build resilience?
The Temporality of Resilience Capabilities
While digital technology characteristics enable entities to build digital resilience to major shocks,
these characteristics have to (mostly) exist prior to the shock for the entities to absorb, adapt, and
transform. This suggests a “prepare” phase that most entities need, as illustrated in Figure 1. In
(cyber)security, organizations routinely plan for this phase through actions like disaster recovery
and business continuity planning. The special issue papers, as well as the additional examples we
discussed above, show the need for such similar planning to build digital resilience capabilities to
withstand major shocks.
Currently there is little guidance on how exactly entities can prepare (i.e. what a blueprint similar
to a Disaster Recovery and Business Continuity (DRBC) planning might look like for instance) to
build resilience to major shocks. We suggest that this process is in fact likely to be an ongoing one.
Such constant preparation for the next shock(s) that might arise will focus on leveraging the digital
technology characteristics and conditions for building resilience, as summarized in Table 2. The
prepare phase may need to become an explicit component of the ongoing process of building
digital resilience for most entities.
34
Figure 1: The Temporality of Resilience Capabilities
As Figure 1 suggests, the absorb, adapt, and transform capabilities do not have to be sequentially
developed, but can, and indeed likely will, overlap during and after the shock. These may, at the
extreme case, be developed simultaneously, with capabilities to absorb being deployed to ensure
immediate survival, while the collective adaptations and transformations to a new reality take place
post-shock. For instance, the sensing capabilities provided by Google Analytics to understand
evolving customer trends during the Covid-19 pandemic in conjunction with the availability of
alternate digital channels to sell direct to consumers can - simultaneously - help organizations both
absorb and adapt to the major shock.
Further research can more explicitly examine the temporality of resilience capabilities. Some
relevant research questions include: How can entities prepare to build digital resilience to major
shocks? How do the absorb, adapt, and transform capabilities play out in time to respond to major
shocks?
CONCLUSION
With the experience of the Covid-19 pandemic, preparing for the next major shock is a significant
imperative for all entities. In a highly inter-connected world characterized by complex systems, a
35
single entity cannot, in most cases, directly control its outcomes as they are dependent on the
actions of others. Yet, there are things that can be done to increase the chances of not just surviving,
but thriving as well. The characteristics of digital technology present significant opportunities for
entities to develop the resilience capabilities of absorbing, adapting, and transforming to a new
stable state.
This editorial, along with the papers in this special issue, offers some important ideas that can help
entities start to proactively plan for the next major shock that can hit us anytime. Unlike digital
transformation initiatives, digital resilience initiatives do require entities to consider and embrace
important trade-offs regarding short vs long-term planning horizons, efficiency vs flexibility and
independence vs inter-dependence. This special issue shows a path forward, driven by building
and developing specific capabilities enabled by digital technology.
While this editorial emphasized redundancy and intelligent sensing (for absorbing the shock);
ubiquity & access, and experimentation (for adapting); and reconfigurability and scalability (for
transforming), we are not suggesting that these digital technology characteristics are the only ones
that can help build resilience capabilities. Indeed, we expect future research to add to these and
explore specific major shocks for which entities can more easily design mitigation strategies.
In closing, we caution against thinking of technology as a panacea to develop resilience. As we
show, what happens outside of the technology arena is equally important, and this means building
a deeper understanding of how people, processes, and culture collectively act to shape the future
of various entities during the next major shock. We are confident that future research will build on
the themes presented in this special issue to push the boundaries of both theory and practice.
36
References
Abrahamsson, P., Salo, O., Ronkainen, J., & Warsta, J. (2017). Agile software development methods: Review and analysis. arXiv
preprint arXiv:1709.08439.
Allenby, B., & Fink, J. (2005). Toward inherently secure and resilient societies. science, 309(5737), 1034-1036.
Armitage, D., Berkes, F., & Doubleday, N. (2007). Adaptive co-management: collaboration, learning and multi-level governance.
Ecological Economics, 7(3).
Arthur, W. B. (2009). The nature of technology: What it is and how it evolves. Simon and Schuster.
Baldwin, C. Y., & Clark, K. B. (2000). Design rules: The power of modularity (Vol. 1). MIT press.
Baskerville, R. L., Myers, M. D., & Yoo, Y. (2020). Digital first: The ontological reversal and new challenges for IS research.
Beaunoyer, E., Dupéré, S., & Guitton, M. J. (2020). COVID-19 and digital inequalities: Reciprocal impacts and mitigation
strategies. Computers in Human Behavior, 111, 106424.
Benbya, H., Nan, N., Tanriverdi, H., & Yoo, Y. (2020). Complexity and information systems research in the emerging digital
world. Mis Quarterly, 44(1), 1-17.
Brooks, S. K., Webster, R. K., Smith, L. E., Woodland, L., Wessely, S., Greenberg, N., & Rubin, G. J. (2020). The psychological
impact of quarantine and how to reduce it: rapid review of the evidence. The lancet, 395(10227), 912-920.
Cheraghlou, M. N., Khadem-Zadeh, A., & Haghparast, M. (2016). A survey of fault tolerance architecture in cloud computing.
Journal of Network and Computer Applications, 61, 81-92.
Christakis, N. A. (2020). Apollo's arrow: The profound and enduring impact of coronavirus on the way we live. Hachette UK.
Constantinides, P. (2013). The failure of foresight in crisis management: A secondary analysis of the Mari disaster.
Technological Forecasting and Social Change, 80(9), 1657-1673.
Constantinides, P. and Barrett, M., 2015. Information infrastructure development and governance as collective action.
Information Systems Research, 26(1), pp.40-56.
Constantinides, P., Henfridsson, O., & Parker, G. G. (2018). Introduction—platforms and infrastructures in the digital age.
Information Systems Research, 29(2), 381-400.
Dourish, P. (2001). Seeking a foundation for context-aware computing. Human–Computer Interaction, 16(2-4), 229-241.
Fernandes, N. (2020). Economic effects of coronavirus outbreak (COVID-19) on the world economy. SSRN Electronic Journal.
Fjeldstad, Ø. D., & Snow, C. C. (2018). Business models and organization design. Long range planning, 51(1), 32-39.
Floetgen, R. J., Strauss, J., Weking, J., Hein, A., Urmetzer, F., Böhm, M., & Krcmar, H. (2021). Introducing platform ecosystem
resilience: leveraging mobility platforms and their ecosystems for the new normal during COVID-19. European Journal of
Information Systems, 30(3), 304-321.
Gunderson, L. H., & Holling, C. S. (2002). Panarchy: understanding transformations in human and natural systems. Island
press.
Guthrie, C., Fosso-Wamba, S., & Arnaud, J. B. (2021). Online consumer resilience during a pandemic: An exploratory study of
e-commerce behavior before, during and after a COVID-19 lockdown. Journal of Retailing and Consumer Services, 61,
102570.
Hardin, G. (1968). The tragedy of the commons: the population problem has no technical solution; it requires a fundamental
extension in morality. science, 162(3859), 1243-1248.
Heeks, R., & Ospina, A. V. (2019). Conceptualising the link between information systems and resilience: A developing country
field study. Information Systems Journal, 29(1), 70-96.
Holling, C. S. (1973). Resilience and stability of ecological systems. Annual review of ecology and systematics, 4(1), 1-23.
Hollnagel, E., Woods, D. D., & Leveson, N. (2006). Resilience engineering: Concepts and precepts. Ashgate Publishing, Ltd.
Home III, J. F., & Orr, J. E. (1997). Assessing behaviors that create resilient organizations. Employment relations today, 24(4),
29-39.
Kitchens, B., Johnson, S. L., & Gray, P. (2020). Understanding Echo Chambers and Filter Bubbles: The Impact of Social Media
on Diversification and Partisan Shifts in News Consumption. Mis Quarterly, 44(4).
Kohavi, R., Tang, D., & Xu, Y. (2020). Trustworthy online controlled experiments: A practical guide to a/b testing. Cambridge
University Press.
Kovach, J. J., Hora, M., Manikas, A., & Patel, P. C. (2015). Firm performance in dynamic environments: The role of operational
slack and operational scope. Journal of Operations Management, 37, 1-12.
Kwon, W., & Constantinides, P. (2018). Ideology and moral reasoning: How wine was saved from the 19th century phylloxera
epidemic. Organization Studies, 39(8), 1031-1053.
Liu, Y., Xu, X., Jin, Y., and Deng, H. (2023). Understanding the Digital Resilience of Physicians During the COVID-19
Pandemic: An Empirical Study. MIS Quarterly 47(1).
Malgonde, O., Saldanha, T., & Mithas, S. (2023). Resilience in the Open Source Software Community: How Pandemic and
Unemployment Shocks Influence Contributions to Others’ and One’s Own Projects. MIS Quarterly, 47(1), 361-389.
Martin, R., & Sunley, P. (2015). Towards a developmental turn in evolutionary economic geography? Regional Studies, 49(5),
712-732.
Merali, Y. (2006). Complexity and information systems: The emergent domain. Journal of Information Technology, 21(4), 216-
228.
37
Nambisan, S. (2017). Digital entrepreneurship: Toward a digital technology perspective of entrepreneurship. Entrepreneurship
theory and practice, 41(6), 1029-1055.
O’Brien, K. (2012). Global environmental change II: From adaptation to deliberate transformation. Progress in human
geography, 36(5), 667-676.
Ostrom, E. (1990). Governing the commons: The evolution of institutions for collective action. Cambridge university press.
Ostrom, E. (2010). Beyond markets and states: polycentric governance of complex economic systems. American economic
review, 100(3), 641-672.
Park, I., Sharman, R., & Rao, H. R. (2015). Disaster Experience and Hospital Information Systems. Mis Quarterly, 39(2), 317-
344. https://doi.org/http://dx.doi.org/10.25300/MISQ/2015/39.2.03
Park, J., Son, Y., and Angst, C. (2003) The Value of Centralized IT in Building Resilience During Crises: Evidence from U.S.
Higher Education’s Transition to Emergency Remote Teaching, MIS Quarterly, 47(1).
Parker, G., Van Alstyne, M. W., & Jiang, X. (2017). Platform ecosystems: How developers invert the firm. Mis Quarterly, 41(1),
255-266.
Pelling, M. (2010). Adaptation to climate change: from resilience to transformation. Routledge.
Prawesh, S., & Padmanabhan, B. (2021). A complex systems perspective of news recommender systems: Guiding emergent
outcomes with feedback models. Plos one, 16(1), e0245096. https://doi.org/https://doi.org/10.1371/journal.pone.0245096
Rai, A. (2020). Editor’s comments: The COVID-19 pandemic: Building resilience with IS research. Management Information
Systems Quarterly, 44(2), iii-vii.
Sahebjamnia, N., Torabi, S. A., & Mansouri, S. A. (2015). Integrated business continuity and disaster recovery planning:
Towards organizational resilience. European Journal of Operational Research, 242(1), 261-273.
Sheth, J. (2020). Impact of Covid-19 on consumer behavior: Will the old habits return or die? Journal of business research, 117,
280-283.
Snowden, F. M. (2019). Epidemics and society. In Epidemics and Society. Yale University Press.
Teece, D. J. (2018). Business models and dynamic capabilities. Long range planning, 51(1), 40-49.
Tremblay, M., Kohli, R., and Rivero C. (2023). Data is the New Protein: How the Commonwealth of Virginia Built Digital
Resilience Muscle and Rebounded from Opioid and COVID Shocks, MIS Quarterly, 47(1).
Vogus, T. J., & Sutcliffe, K. M. (2007). Organizational resilience: towards a theory and research agenda. 2007 IEEE international
conference on systems, man and cybernetics,
Wang, J., Gao, F., & Ip, W. (2010). Measurement of resilience and its application to enterprise information systems. Enterprise
information systems, 4(2), 215-223.
Woods, D. D. (2015). Four concepts for resilience and the implications for the future of resilience engineering. Reliability
Engineering & System Safety, 141, 5-9.
Yoo, Y. (2010). Computing in everyday life: A call for research on experiential computing. Mis Quarterly, 213-231.
Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010). Research commentary—the new organizing logic of digital innovation: an agenda
for information systems research. Information systems research, 21(4), 724-735.
[1] https://www.mmh.com/article/ups_ceo_tome_urges_logisticians_to_take_totally_different_perspective_post
[2] https://www.aerospace-technology.com/comment/singapore-airlines-impact-covid-19-pandemic/
[3]https://www.forbes.com/sites/forbestechcouncil/2021/01/15/how-the-pandemic-has-accelerated-cloud-
adoption/?sh=5be6bb3e6621
[4] https://www.tgh.org/news/tgh-press-releases/2020/april/tampa-general-hospital-unites-with-florida-hospitals-to-
share-data-in-the-fight-against-covid-19
[5] https://www.aacsb.edu/about-us/advocacy/member-spotlight/innovations-that-inspire/2021/university-of-
minnesota
[6] https://www.fm-magazine.com/news/2021/jan/coronavirus-supply-chain-disruptions-kelloggs-nike-hp.html
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[7] https://www.mckinsey.com/featured-insights/food-security/digital-transformation-comes-to-food-banks
[8]https://www.wsj.com/articles/american-eagle-outfitters-to-buy-quiet-logistics-for-350-million-
11635850920?mod=djemlogistics_h
[9] https://hbr.org/2020/09/the-pandemic-pushed-universities-online-the-change-was-long-overdue
[10] https://www.nature.com/articles/d41586-021-01242-1
[11] https://www.theatlantic.com/ideas/archive/2021/11/financialization-everything-investment-system-
token/620804/
[12]https://www.forbes.com/sites/washingtonbytes/2020/05/07/three-policies-to-address-the-digital-
divide/?sh=866343c60145
[13] https://obamawhitehouse.archives.gov/sites/default/files/wh_digital_divide_issue_brief.pdf
