key: cord-0698506-8bws4xpp authors: Dorasamy, Magiswary; Raman, Murali; Kaliannan, Maniam title: Knowledge management systems in support of disasters management: A two decade review date: 2013-01-26 journal: Technol Forecast Soc Change DOI: 10.1016/j.techfore.2012.12.008 sha: fca13f06ebb9a7a23f11e8b073e2d6a9da9e27bb doc_id: 698506 cord_uid: 8bws4xpp Humans are increasingly being challenged with numerous forms of man-made and natural emergency situations. Emergencies cannot be prevented, but they can be better managed. The successful management of emergency situations requires proper planning, guided response, and well-coordinated efforts across the emergency management life cycle. Literature suggests that emergency management efforts benefit from well-integrated knowledge-based emergency management information systems (EMIS). This study presents a systematic review of papers pertaining to the application of knowledge-driven systems in support of emergency management that have been published in the last two decades. Our review presents two major findings. First, only limited work has been done in three EMIS-knowledge management system (KMS) subdomains: (i) definition, (ii) use, and (iii) methods. Second, only limited research has been done in embedding roles in KM systems. We highlight role alignment to the 12 fundamental roles, as called for by Turoff et al. (2004), in the context of creating dynamic systems in aid of emergency management efforts. We believe that these two findings warrant the attention of the research community. Disaster is a common term today. Disaster is defined as 'a social crisis situation' [1] , 'a deadly' event [2] , usually unexpected and unanticipated and cause human suffering [3] . [4] provides a list of attributes of disaster: suddenly occurs, demand quick reactions, creates uncertainty and stress, threaten the reputation of organization and escalates in intensity. Disaster management involves activities such as mitigation, risk reduction, prevention, preparedness, response and recovery [5] . Managing disaster is vital as it threatens organizational goals and permanently impairs the earning power [6, 7] . Prominent issues in disaster management are the need for common platform to enable seamless flow of information and lack of integrated system to support emergency activities. Over the last decade alone (2000 to 2010), the average death toll rose sharply due to the increasing frequency of disasters, especially in developing countries. The United Nations reported that in 2010 alone, 373 earthquakes, floods, cyclones, volcanic eruptions, and droughts occurred, which affected 208 million people around the world, killing nearly 300,000, and costing US $110 billion in losses [8, 9] . Earthquakes in Haiti (12 January), Chile (27 February) , and China (13 April), flooding in Pakistan (July to September), and heat wave in Russia (July to September) were the five most devastating natural catastrophes in 2010, which claimed 280,000 lives and US$52 billion worth of losses [10] . A World Vision report rationalized these phenomena by quoting climate change as a new driver of disaster risk, which increases both hazards and vulnerabilities [11] . Although stopping disasters from occurring is impossible, being prepared with the right knowledge and information on disasters is possible. [15, 16] • Information Management System -IMASH for Hurricane Disasters [17] • Digital Typhoon, a KMS to provide information for typhoons [18] • PeopleFinder and ShelterFinder [19] • Strong Angel III (2006), United Nations Development Program [9] • Tsunami Resource and Result Tracking Systems [20] • Case Management Systems in Singapore used during SARS (Severe Acute Respiratory Syndrome) [21, 22] • NIMS (National Incident Management Systems) in USA [23] • DesInventar System, a historical disaster database and postdisaster damage data collection tool, a project by UNDP and countries such as Latin America, Orissa and South Africa are currently using this system [24] [25] [26] • Google's Person Finder Tool (launched in 2010) that helped in registering and locating earthquake survivors in Japan (2011), Christchurch (2011) and Haiti (2010) [27] . [28] referred to knowledge as a 'justified personal belief' that directly linked with personal capacity of an individual to take effective action. Knowledge can be tacit or explicit [29] . Managing both tacit and explicit knowledge is the challenge of knowledge management (KM). Tacit knowledge is the knowledge that cannot be expressed in words whereas explicit knowledge refers to knowledge that can be expressed in words and numbers [29, 30] . KM is defined as an activity of helping an organization to create, capture, codify, store, share and apply knowledge effectively. KM in information system perspective refers to the effective tool to enable the knowledge management processes. In this context, a knowledge management system (KMS) is the key enabler of KM and is applied in nature. Insights about knowledge and managing knowledge have been described and discussed over the years. However, research on KMS is still limited [30] . [30] assert that practitioners value KM as it leads to desirable organizational benefits. Fundamentally, KM is enabled by an effective information technology (IT) solution. [31] supports the notion that despite the obvious relevance of IT for KM, there has been relatively little work on the application of software to this area. KM in IS perspective refers to the effective tool to enable the knowledge management processes. In this context, a knowledge management system (KMS) is the key enabler of KM and is applied in nature. Many researches on KM/KMS defined it as IT-based systems developed to support and enhance knowledge creation, storage/retrieval, transfer and application [30, 32, 33] . KMS includes knowledge-based systems, document management systems, semantic networks, object oriented and relational databases, decision support systems (DSS), expert systems and simulation tools [34] . Any one or combination of these tools can be designed as effective KMS. DSS, database, groupware and intranet are among the tool of choice by many researchers. For example, DSS was used by [35, 36] as the overall representation of their KMS. [37, 38, 33] used database concepts to form a KMS. However, literature on EMIS suggests that the designers of a particular system aimed at supporting disaster management, may not necessarily use the terms and theories in the context of KMS. The inherent features of such systems do in real fact support the goals of a KMS for managing emergencies/disasters. A case in point would be the seminal work by [12, 39] who clearly demonstrate that both the ERMIS and the subsequently developed DERMIS were in fact driven by KM dimensions and considerations. In the realm of disaster/ emergency management information system, [12, 13, 39, 40] researches seem to be instrumental to all other research. Dealing with disaster situations such as earthquakes, terror threats and other forms of natural or man-made disasters are examples of complex and dynamic environments [41] . The challenge for an organization is to develop a KMS that can easily adapt to change in dealing with uncertainties [41, 42] . [43] suggests several attributes that KMS should have in helping organizations deal with complex and dynamic environments. These include knowledge management systems that: • Provide a shared knowledge space with use of consistent and well defined vocabulary. • Model and explicitly represent knowledge. • Permit collaborative efforts between employees. • Allow reusable knowledge. • Empower employees based on a knowledge sharing culture. Knowledge management involves various events and activities and there is a significant role for information technology in this effort [44] . IT can support the process of knowledge creation, sharing, dissemination and creation of a useful organizational memory system to enhance emergency planning and response [30] . Knowledge management systems can assist organizations in dealing with dynamic and complex situations such as in dealing with emergencies [41, 42, 45] . For any disaster response center, issues such as managing different stakeholder expectations, priorities, and the various resource and skill sets they bring into an actual crisis response mode, is complex and dynamic. This could lead to difficulties in making accurate decisions, under time-pressured and intense situations, while responding to a particular disaster situation. In this context, we suggest that a KMS can be used for capture and then re-use of specific crisis response knowledge which can support decision making when a crisis actually occurs. The practice of selectively applying knowledge from previous experiences during turbulent moments of decision making, to current and future decision making activities with the express purpose of improving the organization's effectiveness, would be possible via a KMS. In addition, we further add that given the dynamic nature of disaster situations, coupled with different inputs and requirements from various stakeholder groups, a disaster manager and center therein, is subject to information overload, which can prevent timely and accurate decision making. experiences of decision-making to current and future decision making activities with the express purpose of improving the organization's effectiveness. KM is an action discipline; knowledge needs to be used and applied for KM to have an impact. [46] further stress that knowledge about past situations are relevant to generate current procedures and forecast future responses. During an emergency situation, lessons learned and understanding of what works best in given situations (both examples of knowledge) [46] enables emergency managers to be prepared with workable plans to ensure smooth decision making process. Emergency management involves extensive coordination, communication, and integration within a dynamic and ad hoc environment. The unique nature of emergency situations warrants KMS deployment to support dynamic knowledge processes. In the realm of emergency management, KMS enables the collection, retrieval, dissemination, and storage of the right knowledge to be used in the right place and at the right time. An integrated knowledge solution will greatly improve disaster management efforts, especially in the context of disasters in a highly turbulent environment. However, an adequate coping mechanism must be present to enable such knowledge to transform into life-saving knowledge. Such a mechanism was evident in various KMS tools that were used for emergency management during Hurricane Katrina in North America [19, 47, 48] and the Indian Ocean tsunami [49] [50] [51] , both in 2004. Hence, the research aims to delve deeper into the literature in the KMS context for disasters and explore the research gaps. We examined 141 papers pertaining to knowledge management systems (KMS) in support of disasters, and suggest that two main gaps exist in the current literature in this domain. First, only limited work has been done in three EMIS-KMS subdomains: (i) definition, (ii) use, and (iii) methods. Second, we examined to ascertain if prior works on KMS applied to disaster management relate to the 12 fundamental roles required in a dynamic system to support disasters, as called for by [12] . Our findings suggest that a significant gap exists in this area. We believe that these two findings warrant the attention of the research community. Our literature review was based on the five stages of systemic review proposed by [52] , which entails five phases: • Planning the review-reported in Section 2; • Identifying and evaluating studies-reported in Section 2; • Extracting and synthesizing data-reported in Section 3; • Reporting descriptive findings-reported in Section 3; and • Utilizing the findings to inform research and practicereported in Section 4. The main goal of this review is to ascertain the nature and form of research in relation to applied KMS in aid of disaster. We aim to offer researchers a comprehensive review of previous works related to applying KMS to support disaster management, particularly in the types of tools that have been developed and tested and the works done to map these systems to the roles that emergency responders require in relation to system use. The review process outcome is to offer emergency management/KM communities a series of research ideas to move the field forward. One main issue that hindered the identification of all papers that analyzed the KMS role for disasters is that most of the papers do not explicitly call the type of information systems used as KMS. The systems are referred to based on their role for business, such as decision support system (supports decision making), expert systems (guide novice users), database systems (systematically organize data), document management systems (manages documents), semantic web/ontology (organizes the terms), and Intranets (provide various services to members), among others. However, the KMS definition covers all of these roles and the combination of the different roles to support knowledge process [34, 53] . Therefore, as the first step, we decided to examine the number of papers for the selected keywords. The keywords include key concepts that are general (KM) toward more specific keywords (KMS for disaster/emergency). Our focus for this review is to analyze KMS applied research. Applied-KMS is referred to as studies based on an actual/real KMS for disaster that exists. We further classified the applied-KMS concept to systems that were either self-developed (by the author and project team) or developed by authors who examined the use of such systems to prove their propositions in mapping KM ideals to the emergency management context. The following are the inclusion and exclusion criteria for the paper search: Fig. 1 summarizes our criteria for the inclusion/exclusion of papers for our analysis. We only selected papers that were published in the last two decades, peer-reviewed, linked to EMIS, focusing on either man-made or natural disasters, of scholarly origin, and applied in nature (i.e., actual systems developed or examined in a KM context). We focused on two main research areas: (1) Knowledge Management Systems and (2) Disaster/Emergency. For the first area, we included terms such as "knowledge management," "knowledge management systems," "knowledge management system (without "s")," and "KMS" and "KM" (abbreviations) that many authors interchangeably use in relating their research toward KM concepts. The next key terms used were "disaster" and "emergency" [12, 54] . Each keyword set was searched individually, and later, combined with other keywords. Table 1 presents the keyword sets used for this research. We set out three strategies to sift through papers that discuss applied KMS for disasters. The first strategy is to search in online databases. We first searched two online databases that encompass a vast range of IS research, as well as disaster-related research. i. Association of Information Systems Electronic Library Table 1 . We gathered all peer-reviewed papers within the time period selected. We realized that our search for "KMS+disaster" or "KMS+emergency" did not list all papers that contain the two sets of keywords; instead, the list yielded many irrelevant papers for the aforementioned keywords. Another problem that we encountered was the results were mostly from conference proceedings, and very few were from journals. ii. Emerald We proceeded to search the Emerald online database, which has a large number of disaster-related papers. Emerald has more than 35,000 full-text articles encompassing over 100 reputable management journals. We recorded the journal results to ensure that we collect only peer-reviewed papers, as the advanced search of Emerald does not separate papers based on peer-review status. We had to search based on keyword combination within the journal repository. We recorded all results in the keywords table. Results for "KMS + disaster" and "KMS + emergency" were very large. We went through each listed paper so as not to miss the important ones. We also faced problems similar to those we faced when we used AISeL. The search using Emerald did not list papers with the given keywords only. Our selection criterion, Is the paper about IS for disaster? Fig. 3 . Percentage of papers within the selected categories. therefore, was to accept all papers that discussed KMS/ IS for disasters and reject all papers that discussed either KMS or disasters only, without one relating to the other. Although the search by disaster/emergency yielded a large number of papers from the total number of papers listed in AISeL for disaster and emergency, only 0.7% were related to "KMS + disaster" and only 0.4% were related to "KMS + emergency." The Emerald list has slightly more relevant papers than AISeL, with 5% of the papers for "KMS+ disaster" and 5% for "KMS+ emergency". The overall search results by online databases are shown in Table 2 . We then searched for KMS papers on disasters to include special issues. We searched through Google with the same keywords. We added "special issue" to obtain special issues only. We only checked up to the second page of the Google search results due to many irrelevant hits. We found that combined-keyword search such as "special issues+knowledge management systems+disaster/emergency" gives less relevant hits compared to search with combined keywords that are more general, such as "special issue+disaster/ emergency." We collected 11 special issues and from which, only five have published papers that are IS-related. The rest are either non-IS papers, general disaster issues, or engineering papers. The total number of relevant papers from this source is 19. The results based on all the abovementioned sources and keyword sets in Table 1 are shown in Table 3 . A total of 8408 papers were listed when the keyword "KM" was used. When we searched for KMS, the number dropped to 751. When we used the keyword sets "KMS+disaster" and "KMS+emergency," 123 papers were generated. After a careful selection based on the inclusion and exclusion criteria, which is described in the following section, 141 papers pertaining to KMS and disaster/emergency were identified. We extracted papers from the various sources mentioned above based on the following extraction process in Fig. 2 . Fig. 2 recaps the basis of selecting papers for our review. As mentioned from the main databases and other options that were utilized, only KMS papers that were applied in System actually developed by Author(s) 69% System not selfdeveloped by Author 31% Fig. 4 . Categories of applied KM systems. Table 3 , and as further summarized in Table 4 , only 751 papers are KMS papers (9%), 103 papers are KMS for disaster papers (1%), and 20 papers for KMS for emergency (0.2%) from the total of 8408 KM papers. These percentages clearly highlight a lack of research in the area of KMS for disaster or emergency management. Based on the inclusion conditions and the extraction process mentioned above, 141 papers were potential units of analysis. In this part, we further categorized the papers to indicate their respective types of studies. The number of units is indicated in the parentheses, and a pie chart is presented to reflect the percentages (Fig. 3 This paper will present an analysis of the 51 applied-KMS for disaster/emergency papers. We aim to highlight the research gaps in applied-KMS for disaster research and "roles" as an important component for emergency management information systems (EMIS). The 51 papers will be our final units of analysis. Table 5 lists the 51 papers sampled for this paper. The information presented includes the following: if the authors of the 51 papers developed a system (1= Yes, 0 = No), and viceversa, the name of the EMIS, a brief description of the system, and emergency management focus and method used. Twenty-three of the total number of papers were from the United States, followed by the Netherlands and the UK with five papers each. Spain, Malaysia, Italy, and Denmark have two papers each. Table 6 summarizes the papers by country. Most of the papers were published in the last decade (2000-2010). Only one paper was published in the 1990s (1993), as shown in Table 7 . The 51 papers selected were from 12 journals/conferences/ special issues. IJISCRAM (14 papers) is the main paper contributor followed by special issues (12) , and ISCRAM and HICSS conference proceedings (8) . The rest of the papers also came from highly ranked IS conference and journals such as TFSC, AMCIS, JITTA, MISQ, and DPM. Table 8 presents the sources of papers. Up to 35 papers (69%) (Fig. 4) are in the category of KM systems that the author(s) actually developed, and the remaining 16 papers (31%) elaborate actual systems for disasters based on organizational cases or review of publicly available KMS tools. Only 20 papers from the 51 papers had actually mentioned KM or the KMS concept explicitly. The rest of the papers did not mention KM or KMS, although the type of IS that they have referred to is categorized within KMS tools (Table 9 ). Literature indicates that various technological tools can be used to enable KM processes. We summarized and synchronized KMS tools enlisted by three papers in KMS. [104] enlisted 12 tools for KMS, [30] with 8 tools, and [105] with 7 tools. A KMS can be a single tool or a combination of many tools to facilitate KM processes [104] . All these tools are listed in Table 8 with an additional number of tools collected based on the 51 papers (Table 10) . We summarized all the above tools into 16 KMS common tools based on the 51 papers. The following are the counts of Table 11 maps the tools that authors used/mentioned in the samples selected. Table 12 and Fig. 5 present the frequency of a particular tool that falls within the KMS classification used by authors in reporting their work. Simulation tools seem to be popular for KMS for disasters. Authors from 12 papers (24%) have tested their propositions using simulation tools. This is followed by DSS (10 papers), distributed hypertext systems/browser/pervasive computing (8 papers), and sensors/wireless sensor network/RFID/mobile system tools (8 papers). The papers were categorized based on the three major dimensions of KM papers of [13] , namely, KM influences, KM activities, and KM resources [106] . The papers categorized as KM influences examined the success factors and KM implementation outcomes. The papers categorized as KM activities discussed KM processes, such as knowledge creation, acquisition, sharing, evolution, and knowledge transfer. Papers grouped as KM resources expounded on the KM components. We have added one more dimension called Knowledge-base, as many applied-KMS for disaster papers Total 3 9 0 2 0 1 1 1 1 3 5 11 12 7 2 3 9 2 constantly indicated this component. Table 13 shows the plots of each paper by the KM dimensions. Based on our extensive and systematic review of the literature pertaining to KM/KMS and disaster management, we highlight two major gaps that we believe warrant the attention of the research community. These two areas are (i) EMIS-KMS definition, use, and methods, and (ii) embedding roles in the KM systems developed. Our review of the 51 papers suggests the following. A number of researchers do not necessarily mention the term KM or KMS in the context of working with (design/ implementation/assessment) of EMIS in relation to disaster management. In this regard, we call for a closer alignment between EMIS and KMS, given that at times, the objectives of both EMIS-and KMS-driven systems are similar in the area of supporting disaster/emergency management. In terms of use, the papers focused on emergency response and rescue (Table 5 ). Another popular use is for decision support. Very few papers describe EMIS-KMS use for pre-disaster stages, such as training, preparedness, mitigation, and prevention. We also find that although the majority of the authors have conducted an exploratory and experimental case study method, a limitation exists on action research that aims to solve real problems by introducing change into the social setting (Table 14) . Hence, more work can be done in this area. In the disaster context, access is needed for a wide range of real-time information and knowledge that requires coordination. Therefore, knowledge management systems can play a pivotal role in enhancing disaster efforts that allow more use of data and faster actions. This section aims to examine how the concept of roles is built into the applied-KMS for disasters and supported by tools to perform human roles. We scrutinized the 51 papers to determine if the authors have somehow built in the concept of human roles within their systems. From the 51 papers, only 22 papers relate the system developed/analyzed to any one or more roles that humans play in using these systems. [12, p. 15] outlined 12 fundamental roles for EMIS. We examined if one or more of these roles are built in the EMIS/KMS. Fig. 6 gives the details of the number of papers that include "roles" for EMIS design. We then plotted the roles that the papers indicated based on the 12 fundamental roles outlined by [12] , as shown in Table 15 . The plot chart clearly suggests that more work can be done to map systems design to support the 12 fundamental roles as called for by [12] . Thus, a scope for more research in this area is also present. Researchers involved in examining the relationship between knowledge-based EMIS and emergency management could consider the main findings of the current study to explore the options for future work. The four major themes for future research consideration include: • Theme 1: Use of terminology • Theme 2: Applied knowledge-based EMIS in actual disaster situations • Theme 3: Extended action research in the context of EMIS and disaster management • Theme 4: Empirical investigation on successful EMIS implementation and use in support of emergency management from the perspectives of both the community (local citizens) and emergency planners/responders. Our study shows that researchers seem to interchangeably use various terms such as emergency management, crisis management, and disaster management. Therefore, we call for researchers to streamline the use of terminologies pertaining to emergency/disaster management, as these terms may neither necessarily reflect similar ideas nor could offer different connotations in different circumstances. A need also exists for researchers to clearly differentiate between EMIS and KMS in aid of emergency management. A knowledge management system refers to any IT-based system that is "developed to support and enhance the organizational knowledge processes of knowledge creation, storage, retrieval, transfer, and application" [30, p. 114 ]. The definition includes various tools described in the earlier sections of the current paper. In this context, the following questions suggest the need for more research: (i) Is there a difference between EMIS and KMS for emergencies? (ii) Do these systems differ based on objectives, functions, and features used in the context of emergency management? (iii) Could different forms of knowledge-based EMIS systems be more relevant for a particular disaster phase? Systems that are well developed and tested in laboratory conditions/simulators but not applied to the real world may seem pointless. More work is also needed in the area of applying KM technologies and systems to actual disasters. This undertaking would require significant efforts and approval from relevant authorities. Nevertheless, findings from such studies would improve disaster response and management. Researchers could continue working with KM systems and conduct tests during actual drills that replicate natural/man-made disasters. We would call for more work on the application of KMS to map the system objectives, functionality, and design to the different phases of a disaster situation. This aspect also applies to mapping the system design to the 3Cs (communication, coordination, and collaboration) in a disaster. Under Theme 3, more research focusing on the use of applied research methodology such as action research will help researchers understand the relevance of EMIS in emergency management. Action research is gaining popularity, particularly within the IS community. Researchers can use the problemsolving nature of action research to better understand issues inherent in the overall communication, coordination, information sharing, and dissemination across the different phases of a disaster. Emergency management efforts require timely interaction and communication of correct information, and applying relevant knowledge to save lives and property. This concept calls for a KMS that can support and sustain data, and allow efficient and effective information and knowledge processes at a very crucial point. IS in the form of knowledge management systems can support timely interactions and communication in disaster management. The integration of knowledge management concepts into a disaster management system is still very limited. Hence, identifying and testing the success factors for using knowledge-based systems in emergency management is timely. Success factors can be examined from the stakeholder viewpoint Source: Adapted from [109, 111] of the following groups involved in or impacted by disasters: local authorities, federal agencies, local communities, emergency responders, planners, social worker groups, and non-government organizations. In this scope of work, researchers can use either a deductive or inductive approach to examine KM success factors in the disaster management context. Our discussions on the use of KMS in aid of disaster management imply the following. Firstly a well-designed KMS can bring a group of experts together-thus offering a powerful platform for sharing prior experience in managing disasters. This knowledge base can in turn be used to aid timely response disaster situations. Although the idea of using a KMS to aid disaster management has attracted some interest in the last decade, the ideas inherent in applying expert knowledge to aid disaster planning and response are arguably not new. [108] introduced the notion of using Delphi, more than three decades ago and suggested the importance of expert viewpoints being brought together to address disaster management issues. The major difference though between this seminal work and contemporary literature/projects on KMS is that while the former systems were predominantly led by structuredmilitary style of disaster management driven by manual procedures, the latter systems can be designed to offer more robust and flexible creation, storage, sharing and ultimately dissemination of a disaster related knowledge base. Secondly, even within the realm of a KMS to support disaster management efforts, literature suggests that these systems can benefit from the utilization of social networking ideas-driven by web 2.0 (and beyond) architectures, to offer a more dynamic and real time use of KMS in an actual disaster situation [12, 54, 77, 109, 110] . Fig. 7 further explains some of our findings based on our assessment of the literature, which can also be used to suggest several core differences between an informational 'vis a vis' knowledge view of systems designed to support disaster management. Researchers working on KMS design to support disaster management should take the following issues into consideration. The KMS design should be designed to: • Facilitate community of practice and cater for the need of diverse stakeholder groups impacted by a particular disaster situation (i.e. going beyond mere structured documentation of structured and organized data) [109] • Allow the creation of an evolving knowledge structure-again implying that while the emphasis of an emergency management information system is largely on the collection of useful information pertaining to disasters, a well-designed KMS caters to the ability of individuals and groups to continuously make changes to the disaster knowledge base seamlessly [109, 111] . [109] in this regard assert that any knowledge structure should support the nature of an ever evolving context, allow flexible alterations and thus classification of meaning in relation to disasters. The authors further add that modern technologies such as wikis, blogs, and other forms of Web 2.0 and beyond architectures support these requirements [109] . • Support both informational and knowledge requirements of different roles played by emergency planners and responders (i.e. allow communities to share both tacit and explicit knowledge domains pertaining to disasters that are highly contextual) [12, 111] . • Handle timely coordination efforts through both synchronous and asynchronous feedback, during the different phases of a disaster situation. In this regard, we propose that an Emergency Management Information System supports mainly structural/organizational requirements in managing disasters. However a KMS is driven by the need to support timely interactions between humans (communities of practice), and support continuously conversations (synchronous/asynchronous) between people involved in disaster management [109] . This study aims to inform the disaster/emergency knowledge community about the research gaps in the application of knowledge-driven systems in support of emergency management that have been published in the last two decades. In this study, we applied the five-stage methodology of [52] in writing papers based on the comprehensive review of literature in a given area. This methodology was used to understand the extent and nature of applied KMS research in aid of emergency/disaster management. From an extensive search of 8408 papers in the KM domain, our search list was narrowed to 51 papers (0.6%) that have examined applied-KMS for disaster/emergency. Our in-depth review of the 51 papers suggests that a scope for more significant research on the four major areas is present. First, an urgent need exists for researchers to streamline the use of terminologies pertaining to emergency/ disaster management. Second, we feel that more work can be done to ascertain if KMS (for emergency management) and EMIS share similar goals or otherwise. The extent of the similarities/differences between KMS-EMIS in this context could also be further explored. Third, only three papers clearly use an action research approach and relate KMS to disaster/emergency management, despite the call for IS researchers to conduct more applied work based on action research methodology [107] . Finally, more empirical work is required to better understand the determinants of KMS success factors in the context of emergency/disaster management. 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Her area of expertise is Information Systems for disaster. To date, she has had a distinguished corporate career in ICT industries and academia career spanning over 17 years and has established herself with extensive experience in consultancy, research and development His other academic qualifications include an MBA from Imperial College of Science Technology and Medicine, London, an MSc in HRM from London School of Economics. Dr. Raman is currently a Professor attached to Graduate School of Management University Malaya, Malaysia. He has served both as lecturer and trainer for the past 20 years. He has conducted various corporate and government training programs for both middle level and senior management teams. On the academic front, he has published his work in both national and international journals and conferences. Dr. Maniam is currently an Associate Professor attached to School of Business and strategy setting (e.g., command and control) 1 Smirnov, A.