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Abstract

Widespread mis- and disinformation during the COVID-19 social media “infodemic” challenge the effective response of Emergency Management Agencies (EMAs). Conversational Agents (CAs) have the potential to amplify and distribute trustworthy information from EMAs to the general public in times of uncertainty. However, the structure and responsibilities of such EMAs are different in comparison to traditional commercial organizations. Consequently, Information Systems (IS) design approaches for CAs are not directly transferable to this different type of organization. Based on semi-structured interviews with practitioners from EMAs in Germany and Australia, twelve meta-requirements and five design principles for CAs for EMAs were developed. In contrast to the traditional view of CA design, social cues should be minimized. The study provides a basis to design robust CAs for EMAs.
International Journal of Information Management 63 (2022) 102469
Available online 13 January 2022
0268-4012/© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Research Article
Design principles for conversational agents to support Emergency
Management Agencies
Stefan Stieglitz
a
,
*
, Lennart Hofeditz
a
, Felix Brünker
a
, Christian Ehnis
b
, Milad Mirbabaie
c
,
Bj¨
orn Ross
d
a
Digital Communication and Transformation, Department of Computer Science and Applied Cognitive Science, Faculty of Engineering, University of Duisburg-Essen,
Forsthausweg 2, 47057 Duisburg, Germany
b
The University of Sydney Business School, The University of Sydney, Rm 4053, Level 4, Abercrombie Building H70, NSW 2006, Australia
c
Paderborn University, Warburger Str. 100, (Q3.128), 33098 Paderborn, Germany
d
University of Edinburgh, Informatics Forum, 10 Crichton St, Edinburgh EH8 9AB, UK
ARTICLE INFO
Keywords:
Conversational agents
Chatbots
Design principles
Crisis communication
ABSTRACT
Widespread mis- and disinformation during the COVID-19 social media infodemicchallenge the effective
response of Emergency Management Agencies (EMAs). Conversational Agents (CAs) have the potential to
amplify and distribute trustworthy information from EMAs to the general public in times of uncertainty. How-
ever, the structure and responsibilities of such EMAs are different in comparison to traditional commercial or-
ganizations. Consequently, Information Systems (IS) design approaches for CAs are not directly transferable to
this different type of organization. Based on semi-structured interviews with practitioners from EMAs in Ger-
many and Australia, twelve meta-requirements and ve design principles for CAs for EMAs were developed. In
contrast to the traditional view of CA design, social cues should be minimized. The study provides a basis to
design robust CAs for EMAs.
1. Introduction
In crisis situations, people use social media alongside traditional
news sources to search for information about the event or to share their
experiences with friends or the public (Nabity-Grover, Cheung, &
Thatcher, 2020; Stieglitz, Mirbabaie, Ross, & Neuberger, 2018). This is
due to a high amount of uncertainty and ambiguity particularly in the
early stages of a crisis (Mirbabaie, Bunker, Stieglitz, Marx, & Ehnis,
2020). Problems of information overload, rumors, conicting informa-
tion, and mis- or disinformation (Mirbabaie et al., 2020) can result from
this behavior. Whereas misinformation means propositional content
that is false but unintentional, disinformation is propositional content
that is false on purpose (Mingers & Standing, 2018). Previous research
showed that the virality of misinformation increases during crisis events
(King & Wang, 2021).
Past crises such as massive bushres in Australia or California
(Beydoun, Dascalu, Dominey-Howes, & Sheehan, 2018), oods (Tim,
Pan, Ractham, & Kaewkitipong, 2017), storms (Mirbabaie et al., 2020),
terrorist events (Mirbabaie, Stieglitz, & Brünker, 2021), or the Covid-19
pandemic sparked broad discussions on various social media channels.
The avalanche of information mixed with misinformation on social
media was in the early phase of the COVID-19 pandemic referred to as
an Infodemic (Zarocostas, 2020), which illustrates the issues which
need to be dealt with in crisis social media communication. The un-
controlled diffusion of mis- and disinformation leads to an increased
demand for reliable and up-to-date information by the general public
(Elbanna, Bunker, Levine, & Sleigh, 2019). Emergency Management
Agencies (EMAs) are struggling to cover the demand (Ehnis & Bunker,
2020), and thus, sophisticated solutions for lling the information gap
are needed. This is also due to challenges in information exchange and
management such as inaccessibility of information, inconsistent for-
mats, inadequate information streams, a low priority of information
diffusion, a difcult source identication, a media storage misalign-
ment, unreliability or unwillingness of stakeholders (Altay & Labonte,
2014). As governmental actors (Aladwani & Dwivedi, 2018), EMAs need
resources or approaches to interact with a large quantity of concerned
citizens (Zhang, Fan, Yao, Hu, & Mostafavi, 2019). The social media
communication pattern is a one-to-many (EMA-to-public) and
* Corresponding author.
E-mail addresses: stefan.stieglitz@uni-due.de (S. Stieglitz), Lennart.hofeditz@uni-due.de (L. Hofeditz), felix.bruenker@uni-due.de (F. Brünker), christian.ehnis@
sydney.edu.au (C. Ehnis), milad.mirbabaie@uni-paderborn.de (M. Mirbabaie), b.ross@ed.ac.uk (B. Ross).
Contents lists available at ScienceDirect
International Journal of Information Management
journal homepage: www.elsevier.com/locate/ijinfomgt
https://doi.org/10.1016/j.ijinfomgt.2021.102469
Received 3 November 2020; Received in revised form 18 December 2021; Accepted 29 December 2021
International Journal of Information Management 63 (2022) 102469
2
many-to-one (public-to-EMA) communication for which robust practices
and solutions still need to be developed.
One important solution space to improve crisis response and emer-
gency management is the use of information and communication tech-
nologies and articial intelligence (AI) (Fan, Zhang, Yahja, & Mostafavi,
2021). AI can be used not only for direct crisis response during natural
disasters, but also to support long-term aims such as sustainability
(Nishant, Kennedy, & Corbett, 2020). During hard to predict crisis sit-
uations such as during the Covid-19 pandemic, AI-based systems can
assist managers and leaders in making effective and efcient decisions
(Dwivedi et al., 2020). Thus, AI-based systems can be used to analyze
crisis-relevant images and assign them to a region using semantic con-
tent classication or to assess damage to specic objects, such as bridges
or roads. Furthermore, Natural Language Processing (NLP) and data
mining techniques can be applied to detect and predict critical events
and identify patterns based on social media data (Fan et al., 2021).
Another approach of applying NLP is the use of Conversational agents
(CAs) (Balakrishnan & Dwivedi, 2021a, 2021b). They can not only
interact with users in natural language (McTear, Callejas, & Griol, 2016)
but also provide an enjoyable user experience (Diederich, Brendel, &
Lichtenberg, 2019). CAs are capable of assisting users in a variety of
tasks such as answering frequently asked questions or providing ideas
and inspiration at the workplace (Lembcke, Diederich, & Brendel,
2020).
In crisis communication they could solve problems such as providing
real-time translation for outgoing and incoming messages via social
media channels, provide location-specic information, answering
frequently asked questions of citizens regarding ongoing disasters fast
and accurately, or autonomously collecting and analyzing disaster
relevant data (Hofeditz, Ehnis, Bunker, Brachten, & Stieglitz, 2019). CAs
have already been tested to autonomously answer questions from
members of the public (Ahmady & Uchida, 2020) or to coordinate
spontaneous volunteers (Gerstmann, Betke, & Sackmann, 2019). First
studies indicate that they can be applied to disseminate and collect in-
formation in crisis situations such as water-related crises (Tsai, Chen, &
Kang, 2019) or the Covid-19 pandemic (Maniou & Veglis, 2020).
However, past systematic and comprehensive information systems
(IS) research on the design of CAs mainly focused on the deployment in
commercial organizations for customer support (Gnewuch, Morana,
Adam, & Maedche, 2017), virtual collaborative work (Brachten,
Brünker, Frick, Ross, & Stieglitz, 2020), or learning environments
(Graesser, Li, & Forsyth, 2014). In contrast, EMAs facing crisis situations
have unique requirements such as speed, effectiveness and efciency
(Fan et al., 2021) that directly or indirectly affect the safety of human
lives. This makes it problematic to rely on knowledge about CA design
that was solely developed in the context of commercial organizations
and businesses. We think that existing knowledge cannot simply be
adopted in an emergency management environment but needs to be
carefully transferred and developed. The requirements of EMAs for
structure, responsibilities and operationsmanagement signicantly
differ from those of commercial organizations (Ehnis & Bunker, 2020;
Hofeditz et al., 2019). Thus, it is crucial to derive specic design prin-
ciples of CAs in crisis communication so that they can suit the needs of
EMAs in crisis situations. We therefore aim to answer the following
research question from a lens of interpretivism and a constructivism
ontology (Goldkuhl, 2012):
RQ: How should conversational agents be designed to improve social
media crisis communication of EMAs?
We adopted an interpretivist philosophy in order to gather empirical
evidence from employees of several organizations from two countries
(Australia and Germany) (Kwayu, Abubakre, & Lal, 2021). Our aim was
to understand how CAs need to be designed to support EMAs in their
crisis communication. For this, we needed to conduct data for further
interpretation. We conducted 16 semi-structured interviews with crisis
management experts in Australia and Germany. Through this research,
this study will enrich knowledge about CAs in crisis situations and about
ghting disasters by revealing the special requirements that EMAs have
for CAs, and by comparing these against current CA design principles in
IS research. Furthermore, by introducing specic design principles for
CAs in crisis situations, this study provides a foundation which practi-
tioners may use to develop more sophisticated CAs, and thereby help the
ght against Infodemics by reducing information overload and
reducing false information during large scale crisis events.
2. Literature review
2.1. Specicities of Emergency Management Agencies
EMAs are typically government organizations with the focus of
minimizing the effects of crisis events. Their main premise is to save lives
and to minimize damage. Such organizations do not have a prot-driven
focus, but their operations are limited by the funding they are receiving.
The members of EMAs can be paid professionals, such as in most city re
departments, predominantly volunteers, such as in the NSW State
Emergency Service in Australia, or a mixture of both, such as the
Country Fire Authority Victoria in Australia.
EMAs are hierarchically structured with clear command and control
systems and practices in place (Bunker, Levine, & Woody, 2015; Gupta,
Starr, Farahani, & Matinrad, 2016). EMAs are operating in two distinct
modes, an operational mode, when they are responding to a crisis event,
and a non-operational mode in between crisis events (Ehnis and Bunker
2020). Although cooperation between different EMAs is highly impor-
tant during crisis events, prior research showed that EMAs often lack
interoperability due to vastly different goals among organizations
(Shareef et al., 2019). Altay & Pal (2014) therefore examined, how in-
formation diffusion can be increased by establishing trust and a high
level of information quality. Following an agent-based modeling
approach, they concluded that cluster leads should act as hubs and
establish long-term relationships in order to facilitate and lter infor-
mation between agencies. For this, humanitarian operations also need to
lead complex interaction between deployed technology and humani-
tarian groups. Considering the complex character of humanitarian op-
erations that arises, among crisis-related issues, from rapidly formed
teams, intergroup leadership might reduce complexity and increase
performance among the various subgroups (Dubey et al., 2020; Salem,
Van Quaquebeke, Besiou, & Meyer, 2019).
It is well known that social media is an inuential communication
channel during crisis events (Tim et al., 2017). EMAs realized the value
social media can provide and adopted various social media platforms to
their communication portfolio to provide timely trustworthy informa-
tion, counter rumors and misinformation, and provide recommenda-
tions for individual actions (Elbanna et al., 2019; Hofeditz et al., 2019).
Previous research highlighted that demographic characters and ethnical
groups differ in responses and behaviors during crisis events, resulting in
different communication strategies for EMAs (Yuan, Li, Liu, Zhai, & Qi,
2021). While EMAs have adopted social media platforms for commu-
nication with the public, they often lack the ability to systematically
track and analyze social media data (Ehnis and Bunker, 2020). However,
activities such as identifying and analyzing potential emergency and
crisis situations, developing coping strategies, and initiating and
tracking countermeasures are crucial for successful crisis management
(Mirbabaie et al., 2021). While some of these strategies overlap to some
extent with the approaches used by commercial organizations to engage
with their audiences, a distinction must be made between the motives of
commercial and EMA organizations. In contrast to traditional commer-
cial organizations whose actions are mainly based on their own eco-
nomic needs, EMAs overriding goal is to protect people and the
common good. To this end, various strategies are applied by EMAs such
as (local) community management, volunteer management and research
(Fischer-Preßler, Schwemmer, & Fischbach, 2019). These emergency
management strategies are aligned to the prevention, preparedness,
response, and recovery phases of a crisis (Wenger, 2017). Emergency
S. Stieglitz et al.
International Journal of Information Management 63 (2022) 102469
3
management activities include the provision of reliable real-time in-
formation during and between crises. EMAs use social media to provide
information to the public and only to a much lesser extent to protect
their own reputation. Commercial organizations, on the other hand,
focus in their crisis communication predominantly on the protection of
their own reputation.
Compared to the need of providing rapid and reliable information in
a public crisis event by EMAs, research has shown that for traditional
commercial organizations the absence of communication is a strategy
that could fulll the organizations needs (Stieglitz, Mirbabaie, Kroll, &
Marx, 2019).
2.2. Crisis communication and technology use of Emergency Management
Agencies
During crises, the publics need for information is closely related to
the crisis itself as well as the degree of individual involvement. At the
same time, EMAs need information from the public, for example, to
maintain supply chains during crisis events (Shareef, Dwivedi, Kumar,
Hughes, & Raman (2020). Furthermore, EMAs need to adapt to the
ongoing development of the situation and may change communication
strategies over time. Therefore, EMAs can distribute information to-
wards non-institutional actors (Abedin & Babar, 2018), such as members
of the general public, and institutional actors, such as media organiza-
tions (Mirbabaie et al., 2020). In this context, it is important that policy
makers of the involved (non-) governmental organizations do not only
consider crisis response and preparedness but also pursue the prevention
of potential crises as well as the reconstruction of the damaged economy
(Shodhi, 2016). The planned operations still need to be communicated
and coordinated between the participating parties. For example, Shodhi
& Knuckles (2021) highlight the various ows of information, money,
and materials among several stakeholders of a development-aid supply
chain. The number of different stakeholders including different re-
quirements emphasizes that proper information technology is pressingly
needed for successful coordination and collaboration. EMAs are often
information starters within the emerging communication networks
during a crisis (Nabity-Grover et al., 2020), whereas individuals are
often information ampliers and information transmitters (Mirbabaie
et al., 2020). While social media technologies are benecial to support
emergency management-relevant tasks (Oh, Eom, & Rao, 2015), EMAs
still seem to struggle with adopting these technologies into their
crisis-related operations (Ehnis & Bunker, 2020). Resources, particularly
in the early stages of an event, are limited (Power & Kibell, 2017), and
many tasks rely on manual processes (Ehnis & Bunker, 2020).
Social media CAs, in particular chatbots, have the potential to sup-
port EMAs with their social media activities (Hofeditz et al., 2019).
However, EMAs are a subset of traditional command and control orga-
nizations, and therefore, bring together their proven organizational
structures, processes, technologies, and IS (Ehnis & Bunker, 2020).
Consequently, EMAs cannot just unreectively implement chatbots
which were designed for commercial organizations; there is a need to
rethink and critically assess the design requirements which are neces-
sary to successfully utilize social media chatbots in an emergency
management environment. As CAs are part of the multidisciplinary
perspectives of articial intelligence, challenges and opportunities need
to be addressed (Dwivedi et al., 2019).
2.3. Conversational agents for crisis communication in Emergency
Management Agencies
For conversational technologies such as CAs, some inconsistencies
exist in prior research regarding terminology being used and the cor-
responding meaning (Brachten, Kissmer, & Stieglitz, 2021). The term
CA, in the current body of knowledge, is often seen as an umbrella which
includes different types of human-computer interaction systems such as
chatbots (Duan, Edwards, & Dwivedi, 2019), digital assistants, virtual
assistants (Mirbabaie et al., 2021) or voice assistants (Laumer, Gubler,
Racheva, & Maier, 2019). CAs are ISs which can communicate with
human users by using and processing natural language (Laumer et al.,
2019). They have been examined in areas such as healthcare (Denecke,
Vaaheesan, & Arulnathan, 2020), education (Demetis & Lee, 2018) or
customer service (Gnewuch et al., 2017). In research, the terms CA,
chatbots and digital assistants are sometimes used synonymously
(Gnewuch et al., 2017). Nowadays CAs can act more sophisticatedly and
they are applied to several tasks and processes using machine learning
(Mirbabaie et al., 2020). CAs can be embodied which means that they
have an animated visual representation that engages face-to-face with
users (Norman & Kirakowski, 2018). CAs are actively used to assist
companies in communicating with customers and have been tested in
many different cases such as medicine and education (Griol, Carb´
o, &
Molina, 2012; Laumer et al., 2019). In a commercial context, CAs are an
established technology and they have been found to be very helpful in
automating tasks and communication.
However, crisis communication and EMAs have different re-
quirements which need to be addressed separately. Thus, during most
crisis events such as natural disasters (Hofeditz et al., 2019) or terrorist
attacks (Gupta, Starr, Zanjirani Farahani, & Ghodsi, 2020), it is very
important to receive assistance in resource allocation. In the context of
crisis communication and emergency management, the literature in-
dicates that CAs are used on various social media channels in the form of
chatbots.
There are examples of prototype chatbots which provide crisis-
relevant information to individuals in affected areas. To reduce the
problems of rumor spreading and increase reliable information on social
media, Ahmady & Uchida (2020) examined the utilization of chatbots
providing earthquake-related information in Japan to foreigners. This
application showed that chatbots could be used to reduce language
barriers and provide reliable real-time information to a specic audi-
ence. Furthermore, Tsai et al. (2019) evaluated a CA that is connected to
a crisis-related data base. They showed that the CA can help
crisis-affected people by providing personnel access to crisis-related data
in a ood context. This allowed individuals to follow corresponding
response strategies. By this, people mitigate potential harmful infor-
mation related to the individual decision-making process. Beside the
problems of conicting information, rumors, or information overload,
spontaneous volunteers are often a crucial factor for saving lives during
a crisis. Gerstmann et al. (2019) investigated the role of CAs for coor-
dinating the behavior of spontaneous volunteers. The scholars empha-
sized the potential of CAs being applicable for individual assignment and
scheduling of volunteers during a crisis. This automated coordination
may reduce the work-load of EMAs in crisis situations. Regarding
research about CAs and task-support showed that CAs are able to reduce
the cognitive load of an individual (Brachten et al., 2020) that may lead
to an improved crisis management. CAs such as social media chatbots
are already applied and evaluated (Maniou & Veglis, 2020). The authors
investigated a working CA that disseminate accurate, timely as well as
customized information. They argue that the CAs ability of providing
customized information to the public is helpful to t the individual
preferences of information selection.
However, the research on the application of bots in crisis commu-
nication by EMAs is still very young. Evaluated frameworks or estab-
lished design approaches in this eld do not exist at this time.
2.4. Design principles for conversational agents in IS research
In their essence, design principles are statements that contain in-
formation and practices that need to be embedded in the design and
development of IS (Chandra, Seidel, & Gregor, 2015). They consist of
relevant knowledge and decisions that need to be manifested in arte-
facts, methods, processes, or whole systems (Mirbabaie et al., 2020). As
already described in the previous sections, CAs are particularly suitable
to counter challenges related to the dissemination and collection of
S. Stieglitz et al.
International Journal of Information Management 63 (2022) 102469
4
reliable information (Ahmady & Uchida, 2020; Tsai et al., 2019) or
support EMAs in real-time crisis management (Gerstmann et al., 2019;
Maniou & Veglis, 2020). In these application elds, CAs are subject to
crisis-specic requirements. Thus, we need to develop design principles
aiming at alleviating crisis-related issues.
Radziwill & Benton (2017) developed a high-level list of quality at-
tributes which should be embedded in the design of a chatbot. (1) Per-
formance, which involves the timely and robust interaction with a user.
The CA should be particularly able to handle unexpected input. (2)
Functionality, which includes the functions of the CA as well as the
linguistic capabilities. (3) Humanity refers to the realism of the con-
versation and potential ability to pass the Turing Test. (4) Affect, which
encompasses the emotional capabilities of the CA. (5) Ethics, which
refers to security and privacy as well as cultural knowledge and practices
towards the user audience. (6) Accessibility, which refers to the ability
to be operated by a diverse set of users.
At their core, CAs in the crisis management sector need to provide a
comprehensive and clear human-computer interaction. Subsequently,
they need to apply to interaction principles (Misiura & Verity, 2019) as
outlined by Molich & Nielsen (1990): The interaction should consist of
simple and natural dialogue, use language which is familiar to the
intended user, use simple instructions, minimize the users memory
load, be consistent, provide feedback, provide shortcuts, and have a
design that prevents errors. Further research in the context of citizen
participation derived distinct design principles describing that CA
should provide social cues and conversational capabilities to ensure
goal-oriented facilitation as well as display messages in simple and un-
derstandable language (Tavanapour, Poser, & Bittner, 2019). Likewise,
Meier, Beinke, Fitte, Behne, & Teuteberg (2020) suggest that CA should
meet the users expectation to enable goal-oriented conversation. To this
end, distinct input and output devices should be supported by the CA
that is based on an information-focused interface. Regardless of the
place of application, Strohmann, H¨
oper, & Robra-Bissantz (2019)
postulate that a VA should provide a robustness to errors and should not
pretend to be human.
However, as CAs interact with their audience through natural lan-
guage, which is a quasi-social interaction where information and
meaning are transferred between a human actor and a technological
actor, the interaction should be able to support social triggers. Feine,
Gnewuch, Morana, & Maedche (2019) identied a taxonomy of verbal,
visual, auditory, and invisible social cues from the literature. Cues as a
form of social signals (Feine et al., 2019) show that the meaning of the
communication in CA-to-user interaction is not just transferred through
the text which is provided but on multiple levels of social communica-
tion. Applying the concept of social cues towards CAs in enterprise
communication, Table 1 outlines design principles for CA in IS
literature.
3. Material and methods
Research that matches the unquestionable need of EMAs for more
automated communication and the IS literature stream of CAs is very
limited. Therefore, we followed an exploratory approach to identify
design principles for CAs that can be applied by EMAs to improve their
crisis communication. As this qualitative research takes the perspective
of an "interpretivist" ontology, we argue that individuals do not passively
react to an external reality but, rather, impose their internal perceptions and
ideals on the external world and, in so doing, actively create their realities
(Suddaby, 2006, p.636). Thus, to obtain and understand the individual
perspectives and relationships (Morgan & Smircich, 1980), we con-
ducted 16 semi-structured interviews (Myers & Newman, 2007) with
representatives of EMAs from Australia and Germany. Two trained re-
searchers coded the transcripts of the interviews. Based on a random
interview sample including 62 code segments, a reliability score for
coding data of κ =0.95 could be reached (Cohen, 1960). Based on the
strength of agreement classication by Landis & Koch (1977), this score
can be understood as almost perfect agreement.
Furthermore, information the interviews provide may be biased, and
thus, the principle of triangulation is essential in terms of validity of the
study. Triangulation is used to refer to the observation of the research
issue from (at least) two different points (Flick, 2004, p.193). In order to
address multiple perspectives in our research issues observations, we
adopted a multiple triangulation approach (Denzin, 2009).
We chose Australia and Germany as two countries because of their
federal structure and contrasting risk prole of different crisis events
building the prerequisite for the triangulation of data in qualitative
research. Furthermore, we conducted interviews from two different
countries, at different times, in different places and from different
Table 1
Design principles for CAs in the existing IS literature.
Design Principle Description Source
(1) Sociability Provide the CA with the ability
to adapt its conversation style
in order to communicate in the
users preferred way.
Feine et al. (2019),
Tavanapour et al. (2019),
Meier et al. (2019),
Radziwill & Benton (2017),
Misiura & Verity (2019)
Design the agent with
appealing social cues in order
to contribute to the perception
of humanness, social presence
and enjoyment in the
interaction without fostering
feelings of uncanniness.
Diederich et al. (2020),
Tavanapour et al. (2019),
Meier et al. (2020),
Strohmann et al. (2019),
Radziwill & Benton (2017)
(2) Proactive
Communication
Provide the CA with the ability
to use proactive messages in
order to automatically notify
users about changes.
Feine et al. (2020), Misiura
& Verity (2019)
Equip the agent with
conversational capabilities for
intent detection in order to
increase its usefulness, given
that the input of the user can
be anticipated by the designer.
Diederich et al. (2020);
Tavanapour et al. (2019),
Radziwill & Benton (2017)
(3) Transparency Provide the CA with functional
transparency so that users can
understand its functions and
decisions.
Feine et al. (2020)
Self-identify the agent as a
machine, present exemplary
capabilities and offer the
possibility to get in touch with
a human representative in
order to manage user
expectations and decrease
potential feelings of
uncanniness.
Diederich et al. (2020),
Strohmann et al. (2019),
Radziwill & Benton (2017)
(4) Flexibility Provide the CA with
conversational exibility in
order to react to changing
contexts, tasks, and data
requests.
Feine et al. (2020),
Radziwill & Benton (2017)
(5) Usability Provide the CA with user-
friendly interactive
capabilities in order to create
an effective, efcient, and
satisfying communication
experience.
Feine et al. (2020), Meier
et al. (2020)
Guide the user in a
conversation where required,
foster context-specic
handling of fallbacks, and
iteratively extend the agents
conversational abilities from
dialogue data in order to
increase the agents
responsiveness.
Diederich et al. (2020);
Tavanapour et al. (2019),
Radziwill & Benton (2017)
(6) Error Handling Provide the CA with the ability
to handle errors of any kind
and to save them for future
improvements.
Feine et al. (2020),
Strohmann et al. (2019),
Misiura & Verity (2019),
Radziwill & Benton (2017),
S. Stieglitz et al.
International Journal of Information Management 63 (2022) 102469
5
people to further ensure proper triangulation of data that allows the
transferability of our ndings by not focusing on a single source (Patton,
1999). To balance out subjective inuences of individuals, we also
aimed for investigator triangulation using two different interviewers
(Flick, 2004). The perspective of a researcher can have a signicant
inuence on the entire research design (Clarke & Davison, 2020). We
therefore discussed ndings and coding among the individual authors
perspectives to further balance subjective inuences. Regarding the
triangulation of theories, we aggregated design principles based on
various IS research perspectives as referred in Table 1. This juxtaposition
ensures considering multiple perspectives on the design of CAs.
Furthermore, the researchers could get access to experts from several
emergency management organizations through existing collaborations
in these countries. We consulted experts that work in the area of crisis
communications, social media crisis communication, intelligence, and
operational response on a state level as their agencies are in charge
during large scale crisis situations. The organizations we considered
included EMAs that are in charge or at least involved during major crisis
situations such as natural disasters (pandemics, forest res, oods, etc.)
or man-made disasters (terror attacks, oil spills, nancial crises, ect.). A
complete list of all interviewees can be found in the Appendix in Table 4.
For conducting the interviews, we used two interview guides (one in
German and one in English) divided into six main sections. For the
interview guides we considered different categorizations of crisis situ-
ations (Imran, Mitra, & Castillo, 2016; Wenger, 2017) and provided a
denition of CAs (Gnewuch et al., 2017). After the introduction part, the
use of social media by EMAs was queried. We asked concrete questions
related to social media goals, guidelines, strategies, and types of mes-
sages that they publish during disasters. To determine the interviewees
role in crisis communication, the third section of the interview dealt
with questions about concrete disaster cases. This included aspects like
subjectsinvolvement and participation (Kamboj, Sarmah, Gupta, &
Dwivedi, 2018). We focused on their practical work as EMAs, but also on
their crisis communication during these events.
As a transition to the next part of the interview, the participants were
asked if they knew of any chatbot activities during disasters. If not, they
were asked what they generally imagined when they thought of bots and
if they had ever recognized any automated accounts on social media
platforms. We then asked if the subjects used CAs in their organization
and if so, how they used them. To examine suitable application elds of
chatbots in respective disaster phases, the fth part of the interview
emphasized the occurring problems and needs of organizations who use
online communication for disaster management. Afterwards, we asked
about challenges of social media emergency management. Interviewees
were asked to highlight areas in which CAs could be applied, based on
their knowledge of missing aspects and problems with the crisis
communication. In the last interview section interview partners were
asked to name the most important tasks in online communication during
a disaster. Based on this, they were then asked which specic tasks CAs
could take over to support the EMAs. Finally, we asked the interviewees
whether they saw problems in the use of chatbots or if there were areas
that should not be adopted. Overall, the approximately one-hour in-
terviews contained 18 main questions with several subquestions.
The interviewees were recruited by email and through existing
contacts via phone. They received an information sheet in advance and
they were informed about the general conditions of the interview on the
interview consent form, which ensured that they agreed that the in-
terviews were recorded and notes taken. All interviews were conducted
by two researchers each. We interviewed all experts at their usual
workplaces and conducted the interviews when there was no acute crisis
situation, so that the emotional, cognitive and motivational condition of
the subjects could be described as stable. The interviews were tran-
scribed manually.
We started analyzing our data with open coding (Glaser & Strauss,
2017). We then carried out a qualitative content analysis according to
Mayring (2015) to code the data and to derive a category system. The
goal of the content analysis was to identify specic requirements for
chatbots that can improve the crisis communication of EMAs. Therefore,
the analysis form of reduction was selected, to summarize the interview
materials to the essential components and to provide appropriate cate-
gories suitable for the research questions. We created a codebook with
eight coding categories including:
1. Contextual requirements of chatbots in crisis communication
2. Technical requirements of chatbots in crisis communication
3. Organizational requirements of chatbots in crisis communication
4. Legal requirements of chatbots in crisis communication
5. Reasons for EMAs to apply a chatbot for their crisis communication
6. Existing implementation approaches for chatbots in EMAs
7. Possible challenges and problems of using chatbots in an EMA
8. Reasons not to use chatbots in an EMA
After categorizing the interview data according to our codebook, we
extracted meta requirements for CAs in crisis communication and
management. For this, we followed Gnewuch et al. (2017).
4. Results
We found that all interviewees were very receptive to CAs and other
forms of automated crisis communication and some were already using
or testing the application of chatbots for their crisis communication. Our
interviewees mentioned common requirements for CAs as a support in
their organizations such as the ability to answer frequently asked
questions in the context of disasters such as bushres or oods (RMM).
However, we found that in crisis communication there are also specic
requirements for CAs to support both organizations and the public. For
example, three interviewees (CL, EMI, REC) stated that CAs supporting
crisis communication should actively ask users for further information
about the crisis in their environment: Then you might have a bot that
might go, Hey, your photo looks really interesting to us. Wed like to
use it to help respond better. Could you please tell us when you took the
photo, where you took it?(EMI). This led us to MR1, the CA should
actively ask for further information on the crisis (e.g., a re, ood or
storm) in the users environment.
Another important requirement we identied was the reduction of
social cues to a minimum. It was important to the interviewees that
communication with a CA was purely functional and focused on content:
But making sure that what youre putting out is, like I said, [.] its not
confusing, and its concise and clear (PCB). This was mentioned espe-
cially in the context of short-term crisis events such as bushres in
Australia (PCB). This led us to MR2, social cues should be reduced to a
minimum (see Table 1).
Another specic requirement for a CA in crisis communication that
we identied is to label the source and how up-to-date the information
is. As interviewee CL said: This [information] is from [re department],
the ofcial site. This [information] is the update. The information
source could be linked to allow users to be directed to the source (CL,
REC). This requirement was mentioned in the context of many different
disaster types and led us to MR3, the CA should indicate the source and
timestamp of each piece of information it provides.
It should also be clearly indicated whose opinion the CA represents:
[if] its not labeled as a social media thing but its an ofcial advice
from [re department] or police or whatever then people will trust it.
For this purpose, the CA must also be clearly marked as non-human.
With one exception, the interviewees agreed on this point: make sure
that people do know that theyre talking to a bot(CL). This requirement
was mainly mentioned in the context of res and led us to MR4.
Another requirement (MR5) that we identied was that the CA
should also clearly communicate how the user data is processed: Its
about privacy(EMI). Since user inputs are partly used by organizations
to improve their response to a crisis, the user must be informed about
how they are used. These three requirements MR3, MR4 and MR5 thus
S. Stieglitz et al.
International Journal of Information Management 63 (2022) 102469
6
aim to create trust among users through transparency.
It was also very important to the interviewees that users could not
only enter text as input, but also pictures, videos and spatial informa-
tion. One interviewee, as an example, stated that it would be very
helpful if [.] there is somebody there with a phone or whatever posting
a video [.](REC) he or she could send it through a CA. Location-based
information was also considered necessary as an input during res and
oods, because EMAs need it to be able to send targeted messages
regarding a crisis. This led us to MR6.
The EMAs we considered have the option of disseminating infor-
mation in a local area in crisis situations via technology such as an app or
SMS: Yes, an emergency alert originally came out and it would go to
hardlines and mobile phones with– Where people have an address in an
area. Then it progressed to where people are in the area(PCB). Ac-
cording to our interviewees, a CA should also have the ability to send
this location-based information to users, because some warnings and
recommendations for action only apply in certain areas while in other
areas they could lead to uncertainty: A chatbot automates that. What is
my re district? It knows that based on your location. [.] this is what you
need to know based on your district, because of your district and because
of your re danger rating today this is what you can do, this is what you
cannot do, all of those(EMS). Based on these requirements in the
context of res, we derived MR7 described as the CA should be able to
provide location-based information.
Not only the ability to provide location-based information was
mentioned frequently, but also the capability to process and respond to
multiple languages. Our interviewees stated that during a bushre in
Australia a wide range of different groups of people can be affected such
as tourists, immigrants or even indigenous communities which all speak
different languages. According to our interviewees (RMM, EMS), an
essential requirement for a CA is to understand the most common lan-
guages in the local area, because a manual answer would be too slow and
too time consuming for the EMAs. That led us to MR8: the CA should be
able to process multiple languages such as local languages and lan-
guages of minorities.
It was especially important to our interviewees and their organiza-
tions that the systems and databases already in use have to be connected
to the CA. One interviewee said that it would be important to provide
chatbots that we would then plug in to our own systems. [.] if things are
connected into each other that adds a greater value to it (RMM). This
led us to MR9.
In crisis situations, it is often difcult to reach people, because not
everyone uses the same information channels. Therefore, EMAs rely on
different contact points, such as different social media channels, web-
sites or apps, to reach the largest possible percentage of the affected
population. Therefore, a requirement for CAs to improve crisis
communication was to place the same CA on different channels simul-
taneously: It could be something that is trusted by the user who has a
le or a presence on the internet, but it is actually visible in a number of
different ways on different platforms but its the same bot (EMI). This
led us to MR10 that emphasizes it should ensure that the CA can be
accessed not only at one, but at multiple contact points. Both MR9 and
MR10 point out a need for interoperability and integration into different
systems.
Even though CAs can relieve EMAs of their work in crisis situations,
there was a consensus for the context of different disaster types that
there should always be the option of a user being referred to a real
person (MR11).
The CA should also be able to answer questions that are not directly
related to the current crisis situation (CL, REC) in order to prevent users
who may need help from running into a dead end (MR12). However, in
such cases, according to our interviewees, the contact to a human should
Table 2
Meta requirements derived from interviews.
Meta requirement Interviewees
MR1: The CA should actively ask for further
information on the crisis in the users environment.
CL, EMI, REC, VSM,
MAN, FFC, DRN
MR2: Social cues should be reduced to a minimum. REC
MR3: The CA should indicate the source and timestamp
of each piece of information it provides.
ASE
MR4: It should be clearly visible to users whose opinion
the CA represents and that they are communicating
with a CA.
CL, REC, EMS, VSM, JJN
MR5: The CA needs to clearly communicate how the
users input/data is processed.
EMI
MR6: The user should be able to input not only text, but
also pictures, videos and location data.
EMS, EMI, VSM, FFS
MR7: The CA should be able to provide location-based
information.
PCB, CMM, REC, FFS
MR8: The CA should be able to process multiple
languages such as local languages and languages of
minorities.
RMM, FFS
MR9: It should be ensured that the CA is connected to
the systems and databases of the EMAs in order to
retrieve information and store user inputs.
CL, VSM, FFS
MR10: It should be ensured that the CA can be accessed
not only at one, but at multiple contact points.
PCB, CL, EMS, VSM, JJN,
FFS
MR11: It should always be possible that the user is
forwarded to a human.
CL, VSM, MAN, DRN, FFS
MR12: The CA should also be able to answer questions
not directly related to the crisis.
REC, JJN, FFC, DRN
Table 3
Derivation of the design principles based on identied meta-requirements.
Design principle Corresponding
meta requirements
Description
DP1: Targeted
communication in Crisis
Situations
MR1, MR2 Provide the CA with a
minimum of social cues and
actively ask people for further
information regarding the
crisis event in order to focus
on providing and distributing
specic knowledge.
DP2: Special transparency
during the Crisis Situation
MR3, MR4, MR5 For every piece of
information, provide a
suitable source (provided
with a URL to further
information) and a time
stamp, explain how the users
input is processed.
Furthermore, label the CA as
a bot of a specic
organization in order to
achieve a high level of trust.
DP3: Appropriate
implementation of the
CAs in EMAs
MR6, MR7, MR8 Provide the CA with location-
based information and the
functionality to allow media
content (text in multiple
relevant languages, pictures,
videos), in a possible
combination with location
data in order to collect more
information about the crisis.
DP4: Interoperable
integration of CAs among
different digital platforms
MR9, MR10 Connect the CA to the
intelligence systems of the
EMAs and provide the CA
platforms (such as social
media platforms and an
ofcial website) in order to
make sure to deliver reliable
and current data and to reach
as many people as possible.
DP5: Take the user
seriously, also if it is not
crisis related
MR11, MR12 Provide the CA with the
functionality to forward
specic requests of a user
which may not be crisis
related to a human encounter
in order to leave no question
unanswered and minimize
uncertainty.
S. Stieglitz et al.
International Journal of Information Management 63 (2022) 102469
7
always be offered directly: They had to put in some pretty clear triggers
for when something like that would activate a real person for them to
then get onboard and to assist them and give them help (EMS).
The summary of our meta requirements can be found in Table 2.
5. Discussion
This paper is at the interchange of emergency management and IS
where practical strategies will contribute to mitigate the impact of a
crisis. The study aims to answer the question of how CAs can be designed
to improve crisis communication of EMAs and thus to ght pandemics.
To this end, ve major design principles revealing specic characteris-
tics of CAs in the context of crisis communication during disasters were
identied.
5.1. Design principles for CA in crisis management
Table 3 shows the derived design principles aligned with the iden-
tied meta requirements. For the derivation of the design principles, we
followed the approach outlined by Lechler, Stoeckli, Rietsche, &
Uebernickel (2019).
The rst design principle, Targeted Communication (DP1), high-
lights the importance of providing the CA with a minimum of social
cues. This may allow affected people to focus on reliable information.
This DP contradicts the ndings of Feine et al. (2019) who emphasize
the importance of CAs social cues for several CAs In the context of di-
sasters, excluding social cues of a CA might lead to a lower application of
stereotypes, e.g., gender stereotypes (Nass, Moon, & Green, 1997).
Following, people focus on the information itself and are less biased by
entrenched stereotypes. This may allow those affected by the crisis to
save cognitive resources and directly convert helpful information into
action. This may help EMAs to receive valuable information in order to
obtain their supply chains during crisis events (Shareef et al., 2020). CAs
can thus also provide important information as a basis for decision
making, which according to Dwivedi et al. (2020) is one of the great
potentials of AI-based systems. However, this could differ between types
and phases of crises as these differ in terms of crisis communication
strategies (Gupta et al., 2016). Furthermore, the CA needs to consider
the EMAs function during the crisis as those might be responsible for
specied activities such as forecasting, the distribution of supplies, or
the coordination with other (non) government organizations (Gupta
et al., 2016).
DP2 aligns with previous IS research (Kim, Park, & Suh, 2020).
Particularly in the context of transparency and AI, it is important to
explain how the usersinput is processed and which source is subject to
the CAs message. This becomes evident, especially during crisis situa-
tions which are characterized by ambiguity and uncertainty (Mirbabaie
et al., 2020), therefore, the CA as a transparent and trustworthy infor-
mation provider is crucial for resolving these issues. Balakrishnan &
Dwivedi (2021a) argue that is important to design the CA transparent in
order to help the users perceive the CA intelligent and competence.
Transparency by indicating sources and timeliness of a CAs information
can also help stakeholders to distinguish real news from fake news,
which is often spread during crisis events (King & Wang, 2021). A next
possible step could be an integrated Fake News Detector, which enables
people to ask the CA whether information is factual or fake news. This
could be realized via a database linked to a fact checking tool. Not only
affected citizens could benet from the implementation of a CA that
follows DP2. A CA with this functionality could also be very useful for
the communication and exchange of information among EMAs, as the
arising trust can lead to a better diffusion of information (Altay & Pal,
2014). It is therefore highly recommended to consider CAs when
developing new and appropriate strategies to deal with crises.
Furthermore, DP3 highlights the importance of location-based in-
formation in crisis situations. Providing the CA with the functionality of
processing multiple input types and languages allows EMA to collect
comprehensive information about the crisis. While users in commercial
applications of CAs are usually not able to send information such as
videos or location data, these rich information sources become essential
in crisis situations (Konicek, Netek, Burian, Novakova, & Kaplan, 2020).
Although our interviews mentioned this in the context of oods in
Germany and bushres in Australia, previous studies also highlighted
the usefulness of location data in other countries ((Holderness & Turpin,
2015)Holderness and Turpin 2015). DP3 is not only relevant for crisis
communication during natural disasters, but also for man-made di-
sasters such as terrorist attacks, where information symmetry,
completeness of information, private information about terrorist secrecy
and deception are important (Gupta et al., 2020). Here, CAs could use
different media types to gather and match information for EMAs. It
should also be emphasized that the combination of location data and
other data such as images or videos is also of great value for emergency
management, since image data of destroyed roads, bridges or other
buildings, for example, can be assigned to specic regions (e.g., by
means of an AI-based system) (Fan et al., 2021). The complex and dy-
namic nature of disaster situations raises the need for supply chain
agility (Dubey et al., 2020) and enhanced cooperation between sub-
groups (Salem et al., 2019) that can be managed by intergroup leader-
ship. In this way, disaster relief material movements can be coordinated
and organized. Taking knowledge from operations research, EMAs may
use AI-based CAs for (inventory) management of relief materials or the
alignment of relief workers (Balakrishnan & Dwivedi, 2021a). However,
collaborative relationships between the various EMAs and relief workers
are crucial as no single organization may manage the crisis by its own.
This becomes apparent regarding the coordination between different
types of organizations such as governmental and non-governmental
organization among the supply chain (Shaheen & Azadegan, 2020).
In this context, DP4 highlights that the CA should be connected to the
intelligence system of the EMA. This allows the organization to better
process and analyze the heterogeneous data, and therefore, quickly
provide reliable information. As demographic characters and ethnical
groups differ in terms of their responses and general behavior during
crisis events (Yuan et al., 2021), people need to access the CA through
multiple contact points such as social media platforms or ofcial web-
sites to reach various target groups as well as the majority of the public.
For example, geographical IS and social media are already used to
organize local response efforts. However, this is often based on a
non-organized open-source approach (Shodhi & Tang, 2014). Deploying
a CA that is connected to EMAssystems can address challenges raised
by Altay & Labonte (2014) such as inaccessibility of information,
inconsistent formats, inadequate information streams, a low priority of
information diffusion, a difcult source identication or a media storage
misalignment by providing a natural communication channel for citi-
zens. Furthermore, it is crucial that gathered information and resources
are stored, veried, and distributed to coordinated collaboration part-
ners. To realize this, the collaboration between different departments
and EMAs needs to be improved initially, since in some cases they do not
function well due to different objectives (Shareef et al., 2019). However,
receiving location-based information raises further challenges on a
governmental level (Aladwani & Dwivedi, 2018) as well as for EMA
(Zhang et al., 2019). This highly sensitive information has to be stored,
processed and provided to align to the legal requirements of the state. At
the same time, the data needs to be protected against abuse.
Furthermore, DP5 emphasizes the robustness to unexpected uses of
the CA. In contrast to (Cassell & Thorisson, 1999), the CA should not try
to hide a lack of knowledge and force to provide no or an unsatisfying
answer. The ndings show that in crisis situations the CAs replies need
to be accurate, reliable and transparent. This leads to the CA having to
refer to a human if he cannot give a reliable answer to the user. Relying
on the system gains in importance regarding the ndings of Balak-
rishnan & Dwivedi (2021b) conceptualizing the role of trust as a
system-based belief in the context of CA interaction.
In summary, we found major similarities between the requirements
S. Stieglitz et al.
International Journal of Information Management 63 (2022) 102469
8
of these EMAs from different countries yielding into the ve design
principles. This might be due to a regular exchange with EMAs from
other countries (e.g., from the U.S.).
5.2. Theoretical contribution
The new design principles should be followed when developing CAs
for the use of emergency management agencies during crisis situations.
Previous research had already identied general design guidelines for
CAs in organizations. Our paper contributes to the ongoing discussion
around the use of technology in crisis situations and to the preparation
of EMAs for future crisis situations is that these design principles put the
specic requirements of EMAs in concrete terms. It is necessary to
rethink some of the previously known principles and add important
aspects.
There are certainly similarities. The ability to answer queries unre-
lated to the crisis instead of blindly following a script, and the ability to
speak to a human when the bot fails (DP5), are not entirely new. They
follow from exibility and transparency principles identied in previous
research. However, when transparency was described as an important
goal of CAs (Diederich, Brendel, & Kolbe, 2020; Feine, Adam, Benke,
Maedche, & Benlian, 2020), the authors meant that the agent needs to be
clearly labelled as articial, and users need to be able to understand
what functionalities it offers (functional transparency). Through our
interviews, it additionally became clear how crucial it is that the in-
formation offered by the agent is transparent, for example that its source
is mentioned and that it is accurately dated (informational transparency,
DP2).
A similarly supercial parallel that, under closer scrutiny, reveals
important distinctions can be found in the descriptions of the desired
communication style. Previous research identied the requirements that
the CA is proactive in its communication, for example that it noties
users about information that is relevant for them instead of only taking
input from them (Feine et al., 2020). The requirements identied by our
interviewees go one step further. The CA should actively prompt the user
to provide additional information that it might need (DP1). In combi-
nation with DP3 it further becomes clear that in the crisis context, this
extends to pictures, videos and location information as well as support
for multiple languages.
A key difference lies also in the alleged requirement of sociability
that previous research identied. Social cues were deemed an important
aspect that contributes to the perception of a CA as human-like, to social
presence and to the overall enjoyment of the interaction. In contrast, our
interviewees were much less enthusiastic about cues that they perceived
as superuous. The CA, it was felt, should focus on asking and providing
essential information, and keep the chit-chat to a minimum (DP1).
It is already known that exibility is an important characteristic of
CAs, but previous research used this term to mean exibility within the
conversation: a good CA should not merely follow a script but it should
be able to react to various situations such as unexpected requests from
the user. Our interviews made clear that in the context of crisis
communication, a degree of exibility about the communication chan-
nel in which the conversation takes place and from where the CA draws
its information is also crucial (DP4). This is clearly much more effort for
the developers, because it requires the integration of different systems
that might work with different data formats and software architectures
and might not have well-dened communication interfaces.
5.3. Practical contribution
Chatbots are widely used in various areas, for example in sales and
customer service, to provide a customized experience, handle com-
plaints and answer commonly asked questions. Mobile phone users are
familiar with CAs that answer questions and perform tasks such as
setting reminders. Given the burden that crisis situations place on the
emergency services, it does not come as a surprise that police services,
re departments and others are looking to use similar technologies in the
near future.
However, our research has made it clear that there is still a funda-
mental gap between what current technology can offer and the vision
that decision-makers in emergency service agencies have in mind for
successful CAs in this area. Together, our design requirements show a
vision of the CA of the future that is far more ambitious than anything
that is currently on offer, and this vision has little in common with the
virtual agents and chatbots of today. In this context the CA may improve
the management of relief materials as well as the coordination and
collaboration among the disaster relief workers that could lead to a
reduced complexity of disaster situations.
The emergency CA of the future does not only respond to user-
initiated conversations in the way Siri, Google Assistant and Cortana
focus on answering questions and carrying out tasks after the user has
initiated the conversation. Instead, it purposefully initiates conversa-
tions on its own. For example, it may approach social media users who
have posted relevant content and ask them for more background infor-
mation before passing this information to its owners, or it may approach
social media users in a specic geographic area with relevant informa-
tion or requests for information. Thus, managers in EMAs are well
advised not to simply deploy traditional chatbot applications, but to
adopt more intelligent systems for their crisis communications. That
information could be distributed to eld teams and allow a dynamic
adaption of the specic leadership styles to the current hazardous
situation.
It does not attempt to form an emotional connection, at least not
when an acute emergency is ongoing and an efcient exchange of in-
formation is of the utmost importance. Such attempts may be better
suited to longer running crises, such as the ongoing COVID-19
pandemic. Managers of EMAs need to take this into account.
In addition, the emergency CA of the future is always fully aware of
the current situation by frequent updates of information sources such as
databases or systems. One challenge the CA needs to face is the assim-
ilation of emerging technologies and online communication channels.
The user may be following several media channels (TV, radio, news
apps) alongside social media. The CA needs to understand this context.
Depending on the nature of the situation, a chatbot that is giving advice
which is outdated, even if only by half an hour, may be more harmful
than one that is not giving advice at all.
EMAs can therefore learn much from the interviews we examined
about the opportunities that CAs offer to improve their crisis commu-
nications, but also about their challenges. CAs such as chatbots cannot
simply be implemented in the same way in the context of EMAs as in
other contexts. This implies that when EMAs recruit experts in assistance
systems and CAs or entrust other organizations with their implementa-
tion, the developers cannot simply transfer their existing knowledge and
solutions to the crisis context. Therefore, a rigorous knowledge transfer
is mandatory between managers, disaster relief workers and developers
to further improve collaboration resting upon shared experiences.
However, our design principles can serve as guidance to peculiarities
of the crisis context that have to be addressed before CAs can be used by
EMAs. We further recommend to start step by step and not by trying to
take into account all of our design principles at once. Crisis communi-
cation is a sensible eld where errors can make the difference between
life and death. It is advisable to start with a social media chatbot rst and
then gradually connect the systems of the EMAs. Also, the imple-
mentation within an EMA app might be a good starting point. Subse-
quently, other smart-home applications such as dissemination via smart
speakers (e.g., Amazon Alexa) are also conceivable in order to reach as
many people as possible in crisis situations.
Of course, when doing so, the EMAs should also compare their re-
quirements with the requirements we identied for the Australian and
German EMAs that we focused on in this study, and then determine
whether the identied design principles may need to be modied.
S. Stieglitz et al.
International Journal of Information Management 63 (2022) 102469
9
5.4. Limitations and future research directions
Our qualitative research design imposes specic limitations on our
ndings. We collected enough data to have a diverse sample according
to our interpretative judgement and expertise in qualitative research and
to be able to answer our research question (Braun & Clarke, 2021).
However, the transferability to other contexts in crisis communication is
constricted through the organizations and the cultural context they are
situated in; transferability to a broader context needs to be carefully
evaluated and further investigation (Lee & Baskerville, 2012). Also,
some requirements for CAs were mentioned noticeably more often than
others. Even if the quantity of statements is less relevant in qualitative
research, future research should examine more closely if there is a
relationship between frequently mentioned requirements and impor-
tance of these requirements.
We conducted interviews from two different countries (Australia and
Germany) to ensure a broader relevance of our ndings, by not focusing
on a single country. However, our ndings might differ in other coun-
tries and cultures. Future research could consider our ndings in the
context of other countries and disaster management cultures in a cross-
case analysis.
When our interviewees referred to crisis events, they were usually
talking about natural disasters such as res, oods or storms. Although
we interviewed experts from a variety of countries and a wide range of
organizations, our ndings cannot be generalized to all crisis types since
our study applied an interpretationist lens to the experiences of the
experts we interviewed. The requirements and applicability of our
design principles might differ between disaster types. Future research
should therefore examine our design principles in the context of other
crises, such as the Covid-19 pandemic.
Our research highlights differences in the design of CAs for com-
mercial organizations and EMAs. Future research needs to apply these
peculiarities in other contexts and in practice building on our ndings.
6. Conclusions
Current IS literature provides various perspectives for designing CA
in general (e.g., Feine et al., 2019, Diederich et al., 2020). However, the
crisis related requirements for CA reveal the specic need for design
principles considering the perspective of a crisis (Ahmady & Uchida,
2020, Maniou & Veglis, 2020). This study reveals aggregated insights
from two countries suggesting of EMAs across the globe have similar
requirements regarding crisis management. This specic need is
conceptualized by the derived design principles.
In summary, this study uncovered ve actionable design principles
representing concrete but demanding requirements for EMAs. These go
far beyond the previously known requirements for general-purpose CAs
used in organizations (Feine et al., 2020), but they are necessary to
ensure a satisfactory crisis response (Mirbabaie et al., 2021). Arguably,
these requirements also go far beyond what current technology can
offer. The derived design principles form a bridge between research and
practice, with clear implications for what future research can focus on to
ensure that it contributes to future crises, including pandemics, being
managed more effectively.
Funding
The author(s) disclosed receipt of the following nancial support for
the research, authorship, and/or publication of this article: This project
has received funding from the European Unions Horizon 2020 research
and innovation programme under the Marie Skłodowska-Curie grant
agreement No 823866.
CRediT authorship contribution statement
Stefan Stieglitz: Supervision, Funding acquisition, Investigation,
Methodology, Writing original draft, Writing review & editing.
Lennart Hofeditz: Data curation, Investigation, Methodology, Writing
original draft, Writing review & editing. Felix Brünker: Data curation,
Investigation, Methodology, Writing original draft, Writing review &
editing. Christian Ehnis: Conceptualization, Formal analysis, Writing
original draft. Bj¨
orn Ross: Writing review & editing. Milad Mirba-
baie: Writing review & editing, Project administration, Resources.
Declarations of interest
None.
Appendix
See Appendix Table 4.
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List of interviewees.
Pseudonym Organization Position State,
Country
RMM State Level Crisis
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VIC, AU
EMS State Level Crisis
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Social Media and Content
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EMI State Level Crisis
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DA State Police Information & Communications
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PCB State Police Emergency Manager SA, AU
CMM State Police (Former) Police Ofcer SA, AU
REC State Police (Former) Police Commissioner SA, AU
ASE State Emergency
Service
Media Expert NSW, AU
RTC State Fire
Department
Volunteer Coordinator NSW, AU
CL City Fire Service Communications Manager NSW, AU
FFC City Fire Service Communications Manager NRW,
GER
JJN NGO State Association Manger
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NRW,
GER
FFS State Fire
Department
Information and communications
Manager
HE, GER
VSM State Level Crisis
Virtual Support
Board Member NRW,
GER
MAN NGO Press Ofcer NRW,
GER
DRN NGO State Commissioner for Disaster
Control
NRW,
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10.1016/j.ijinfomgt.2019.04.004
Stefan Stieglitz is professor and head of the research group for Digital Communication
and Transformation at the University of Duisburg-Essen, Germany. In his research, he
investigates how to make use of social media data. Moreover, he analyzes user behavior
and technology adaption of collaborative IS in organizational contexts. His work has been
published in reputable journals such as Journal of Management Information System
(JMIS), Business & Information Systems Engineering (BISE), International Journal of So-
cial Research Methodology, and MISQe. His articles was recognized with the ‘AIS Senior
Scholars Best IS Publications Awardand the Stafford Beer Medal.
Lennart Hofeditz is a research associate at the research group of professor Stefan Stieglitz
at the University of Duisburg-Essen, Germany. He studied Applied Cognitive and Media
Science (M.Sc.). At the moment, he is a PhD candidate in Information Systems at the
Department of Computer Science and Applied Cognitive Science at the University of
Duisburg-Essen in Germany. In his research, he focusses on socio-technical systems and
ethical issues related to the application of articial intelligence and anthropomorphic
machines in organizations. He also works in a research project funded by the German
Research Foundation (DFG) on research data management and open science.
Felix Brünker is a research associate at the Department of Computer Science and Applied
Cognitive Science at the University of Duisburg-Essen, Germany. He studied Applied
Cognitive and Media Science at the University of Duisburg-Essen, Germany, and special-
ized in professional communication in electronic media/social media. Felix is a full
member of the research training group User-Centred Social Media(DFG). His work
focusses on CAs, IT identity, and Digital Work. His work has been published in reputable
journals such as Electronic Markets, Business & Information Systems Engineering, Infor-
mation Technology & People, or Information Systems and e-Business Management.
Christian Ehnis is an Honorary Associate at the University of Sydney Business School. He
obtained his PhD from the University of Sydney. His research interests focus on how
technology inuences and impacts organizations and society, particularly the use of social
media during emergency and disaster events. His work has been published in reputable
journals such as the Journal of Information Technology, Information Systems Frontiers,
and Behaviour and Information Technology.
Bj¨
orn Ross is Lecturer in Computational Social Science at the University of Edinburgh
School of Informatics. In his research, he uses computational methods to study social
media and related technologies. A key focus of his research is to explore aspects of social
media, such as misinformation, hate speech, and the malicious use of automation (bots), as
well as how social media can be used effectively for the benet of society, such as in crisis
communication. His articles have been published in journals including the European
Journal of Information Systems and Big Data & Society.
Milad Mirbabaie (milad.mirbabaie@uni-paderborn.de) is junior professor for Informa-
tion Systems at Paderborn University and team leader for Sociotechnical Systems at the
University of Duisburg-Essen, Germany. He studied Information Systems at the University
of Hamburg and received his PhD from the University of Münster, Germany. He has
published in reputable journals such as Journal of Information Technology, Business &
Information Systems Engineering, Electronic Markets, Journal of Decision Systems,
Internet Research, Information Systems Frontiers, International Journal of Information
Management, and International Journal of Human Computer Interaction. His work focuses
on Sociotechnical Systems, Articial Intelligence, Social Media, CSCW, and Crisis
Management.
S. Stieglitz et al.
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... In addition to the practitioners' interest in the implementation of chatbots to provide a unique and personalised customer experience, researchers have begun focusing on chatbot-related issues, especially over the last five years Lim et al., 2021;Selamat and Windasari, 2021;Sheehan et al., 2020;Stieglitz et al., 2022;Sung et al., 2021). A close and careful review of the chatbots literature helps identify the features and aspects that have been considered in prior studies in this area. ...
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