14,507 research outputs found

    The Impact of Artificial Intelligence on Strategic and Operational Decision Making

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    openEffective decision making lies at the core of organizational success. In the era of digital transformation, businesses are increasingly adopting data-driven approaches to gain a competitive advantage. According to existing literature, Artificial Intelligence (AI) represents a significant advancement in this area, with the ability to analyze large volumes of data, identify patterns, make accurate predictions, and provide decision support to organizations. This study aims to explore the impact of AI technologies on different levels of organizational decision making. By separating these decisions into strategic and operational according to their properties, the study provides a more comprehensive understanding of the feasibility, current adoption rates, and barriers hindering AI implementation in organizational decision making

    A transdisciplinary-based coupled approach for vulnerability assessment in the context of natural resource-based conflicts using remote sensing, spatial statistics and fuzzy logic adapted models

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    This thesis presents a new approach for investigating vulnerability assessment in the context of natural resource-based conflicts (NRBCs). It develops SEFLAME-CM (A Spatially Explicit Fuzzy Logic Adapted Modeling for Conflict Management). SEFLAME-CM is an innovative tool that improves the holistic vulnerability assessment (the external and the internal driver components) of NRBCs at a community scale towards co-creating scenarios for future conflict management (CM) strategies. It was perceived specifically that a methodology with the worldviews and the knowledge of the actors is capable of understanding conflicts better than the previous linear models such as the Multiple Linear Regression Model (MLRM) and the Multinomial Logistic Regression Models (MNLR). SEFLAME-CM, an adapted model proved to be a reliable modeling tool for capturing the non-linearity, uncertainty, and ambiguity characteristics of the vulnerability assessments of NRBCs. The spatial extent of the study was limited to selected test sites within Ogoni and Okrika territories of the Niger Delta region of Nigeria. These comprise of LGAs/communities and villages. Despite the uncertainty involved in real-world problems such as the Socio-ecological Systems (SES), the NRBCs, the increase in the computational power in the last decades has enabled the modeling of the complexities involved. Issues that cut across social-economic and biophysical interfaces, such as NRBCs, require both the knowledge of the experts and that of the local actors. This is thus following the recommendation of Seidl et al. (2013) on science with social research in the Anthropocene: “A systems perspective on coupled human-environmental systems (HES) help to address the inherent complexities. Additionally, a thorough interaction between science and society (i.e., transdisciplinarity) is necessary, as sustainable transitions are sometimes contested and can cause conflicts. In order to navigate complexities regarding the delicate interaction of scientific research with societal decisions these processes must proceed in a structured and functional way” (: 5). The main sections of the thesis after the introduction and the study area description began by reconceptualizing NRBCs. Current publications indicate that the study of NRBCs in the era of the Anthropocene needs to be reconceptualized to be able to explore strategies for conflict management which are beyond the hitherto military strategies often employed in the different international interventions on conflicts in the developing countries, particularly in Africa and Asia (Section 3). Multilateral agencies such as the United Nations, the North Atlantic Treaty Organization (NATO) and other peacekeeping international organizations, often embark on the use of military strategies which have proved to be unsustainable. This is because NRBCs are complex and “wicked” in nature (Brauch, 2003a, Spring et al., 2009, Brauch, 2010, Brauch, 2016b, Brauch, 2016a). By reconceptualizing NRBCs, the research firstly clarifies the concepts of risk, risk perception resilience, vulnerability assessment, and the “Vulnerability Cube”. Secondly, the bridging of the gap between the concepts of a holistic vulnerability assessment (HVA) and the NRBCs was discussed. Thirdly, the integration of HVA of NRBCs into fuzzy logic theory was presented. This was implemented in Section 5. The main argument of this Section 3 is that the complex characteristics of vulnerability to NRBCs require the use of a non-linear theoretical model that is adaptable and capable of addressing the complexities of NRBCs research. After the reconceptualization of NRBCs in Section 3, the thesis then followed the three phases of the transdisciplinary research approach proposed by Mauser et al. (2013) (see also Section 1.4 and Section 5.1). This phase dealt with a joint problem framing. This helped to operationalize NRBCs for simulation (see Section 4). The problem of NRBCs was framed by integrating the problem structuring methods (PSMs) (e.g GIS) with the qualitative method (e.g discourse analysis). The results of this joint problem framing showed the different drivers of NRBCs which were selected by the actors. With the aid of GIS, the actors’ mental maps were presented based on the different dimensions of NRBCs vulnerability. The results also show the similarities in the interest of local actors. The joint problem framing equally helped to organize and operationalize the input variables that were used for the modeling phase of the research. Hence the operationalization of the conflict drivers/factors generated from the joint problem framing is seen as a critical step in the transdisciplinary-based coupled approach to NRBCs. The second phase of the research after the joint problem phase is a co-production of knowledge for managing the NRBCs with the integration of knowledge from the actors. Here the overall research methodology and the algorithm of SEFLAME-CM were presented in Section 5. This was validated following a rigorous validation process (see Section 6). Prior to the validation of SEFLAME-CM, a non-spatially explicit model, Fuzzy Logic Adapted Modeling for Conflict Management (FLAME-CM) was developed, improved and validated following an iterative process using scores like R2, p-values, RMSE. The results of the validated FLAME-CM was conducted at village scale as a test site, but this was transferred to a spatially explicit context using a resolution of 200 x 200m2. The content of the FLAME-CM helped to establish a SEFLAME-CM. The validation of SEFLAME-CM is, therefore, an extension of FLAME-CM validation result (Figure 6.7). As seen in Figure 6.7, the result of the validated SEFLAME-CM is the final output of the model and the process does not have to go back to the FLAME-CM process. Figure 6.7 shows the schematics of the overall validation process. SEFLAME-CM was firstly validated by comparing outputs with spatial multi-criteria evaluation for conflict management (SMCE-CM) and secondly by using satellite remote sensing data. The result of the latter proved that the model result corresponds with the real world data (remote sensing). The result of the former shows that SEFLAME-CM performed better even when compared with the already established model of SMCE-CM. However, the advantage of SEFLAME-CM is that it accepts weighted inputs by the actors or stakeholders right from the problem framing phase. The entire methodological procedure of the research, therefore, shows a blend of methodology from the natural sciences and the social sciences, and integration of integration co-created knowledge with the actors. The third and the last phase of the research process of this thesis is the outlook and conclusion (see Section 7). It dealt with the research proposal for co-construction of scenario pathways for long-term conflict management strategies. The scenario construction, when applied in the future, would address the positive potential of collective natural resource management for longer-term peacebuilding and sustainable peace (Bruch et al., 2009, Ratner et al., 2013). It was conceived that after developing and validating an innovative spatially explicit component of the simulation model, SEFLAME-CM, the next logical step of the thesis is to apply the methodology for future conflict management. The “scenario” proposal for future CM is a period from 2016 to 2060. The justification is that while global scenarios cover time horizons of say 50–100 years, local scenarios focus on shorter periods, 20–30 years (Folhes et al., 2015). The choice of a scenario time frame that is longer than 20–30 years is because the study outcome is considered to be applicable to regional or national governance. When the co-constructed scenarios are implemented, they would help to explore CM options and strategies that can influence policy and decision making over natural resource management (NRM). For example, in the Niger Delta, the investments in CM can be re-channeled from military strategies and the current unsustainable Presidential Amnesty Programmes to achieve both peacebuilding and sustainability. Since social resilience is a “naturally emergent” response to harm or disaster, it is argued that conflict management plans must recognize and build on community adaptive capacities, while the areas of high resilience in terms of peace should be priority areas for future NRM. In a nutshell, the thesis enables the application of a transdisciplinary-based coupled approach that is based on co-creation of knowledge between the experts and the local actors in the management of NRBCs. Both the external and internal vulnerability drivers of NRBCs were assessed. The results demonstrate that environmental degradation, socio-economic and political drivers of resource conflict can be addressed holistically as well as being treated as separate drivers in the interplay of natural resources and conflicts at the community scale. Though there are limitations, relating to cost, time and the complex social processes involved in modeling a real-world process, the results at a fine-grained spatial and temporal scale proved to be very useful and form the basis for supporting integrated coastal zone management (ICZM) strategies for the future management and development of the Niger Delta region. The model remains very adaptable to other NRBCs cases in Africa and other regions of the world. This is especially where both natural resource extraction and conflicts intertwine, and particularly when there is either data scarcity or the available data sets are imprecise.Diese Arbeit demonstriert eine neue Herangehensweise zur Analyse von Vulnerabilität gegenüber Konflikten, die auf natürlichen Resourcen beruhen (Natural Resource Based Conflicts: NRBCs). Gezeigt wird die Entwicklung von SEFLAME-CM-A, ein räumlich explizites Fuzzy Logic Modell für Konfliktmanagement. SEFLAME-CM-A ist ein innovatives Tool, welches an co-konstruierte Klimamodellszenarien unter verschiedenen Bedingungen anpassbar ist. Im Speziellen wurde festgestellt, dass eine Methode mit weltweitem Blick und Expertenwissen besser dazu in der Lage ist Konflikte zu erklären, als die bisherigen linearen Modelle, wie etwa multivariate lineare Regressionen (MLRM) oder multinomiale logistische Regressionen (MNLR). SEFLAME-CM zeigte sich als verlässliches Tool um die Nicht-Linearitäten, Unsicherheiten, fehlende Präzision und Mehrdeutigkeiten abzufangen, welche Vulnerabilitätsanalysen prinzipiell mit sich bringen. Das räumliche Ausmaß der Studie ist auf ausgewählte Gebiete im Niger Delta begrenzt, die in LGAs/Communitys und Dörfer strukturiert sind. Trotz Unsicherheiten, welche bei realen Anwendung der NRBCs eine Rolle spielen, z.B. sozial-ökonomische Systeme, ermöglichte die zunehmende Leistungsstärke von Computern in den vergangenen Jahrzehnten auch Modellierungen von Sachverhalten höherer Komplexität. Probleme, die sozio-ökonomische und biophysikalische Räume spalten, schaffen eine Notwendigkeit sowohl für Expertenwissen, als auch für Mitwirken der lokal Beteiligten. Seidl et al. (2013) empfehlen für eine Wissenschaft mit Sozialforschung im Anthropozän, dass die Perspektive auf gekoppelte Mensch-Umwelt-Beziehungen dabei helfe, die damit einhergehende Komplixität besser berücksichtigen zu können. Zusätzlich sei eine gewissenhafte Interaktion zwischen Wissenschaft und Gesellschaft (also Interdisziplinarität) notwendig, da nachhaltige Umstellungen manchmal umstritten seien und Konflikte hervorrufen könnten. Um sich in der Komplexität zurechtzufinden, welche die heiklen Interaktionen zwischen wissenschaftlicher Forschung und gesellschaftlichen Entscheidungen mit sich bringen, müssten diese Prozesse auf strukturierte und funktionale Art und Weise ausgeführt werden. Das Hauptkapitel dieser Arbeit, welches sich an die Einleitung und die Beschreibung des Untersuchungsgebiet anschließt, begann mit der Entwicklung eines neuen Denkansatzes bezüglich NRBCs. Aktuelle Veröffentlichungen zeigen, dass die Untersuchung dieser Konflikte neue Strategien des Konfliktmanagements erforderlich macht, die jenseits der bisherigen militärischen Lösungen liegen, wie sie derzeit in Entwicklungsländern vor allem in Afrika und Asien eingesetzt werden. Obwohl sie sich im Anthropozän als nicht nachhaltig erwiesen, da die Ursachen der Konflikte eindeutig in Umweltproblemen zu suchen sind, sind zahlreiche multilaterale Vertretungen wie die Vereinten Nationen, NATO oder internationale Organisationen zur Friedenswahrung auf die militärischen Strategien aufgesprungen (Brauch, 2003a, Spring et al., 2009, Brauch, 2010, Brauch, 2016b, Brauch, 2016a). Aus diesem Grund klärt diese Studie erstens die Konzepte von Risiko, Risikowahrnehmung, Resilienz, Vulnerabilitätsanalysen und Vulnerabilitätswürfel. Zweitens wurde eine Brücke zwischen dem Konzept der holistischen Vulnerabilitätsanalyse (holistic vulnerability assessment HVA) und NRBCs geschlagen. Drittens wurde die Integration der HVA von NRBCs in die Fuzzy Logic Theorie vorgestellt. Dies wurde in Section 5 eingebaut. Dessen Hauptargument war, dass die komplexen Eigenschaften der NRBCs einem nicht-linearen theoretischen Modell bedürfen, welches sowohl anpassungsfähig ist, als auch der Komplexität der NRBC-Forschung gerecht wird. Nach der Neukonzeptionalisierung von NRBCs in Section 3, folgte die Arbeit schließlich dem Ansatz der drei Phasen transdisziplinärer Forschung von Mauser et al. (2013, siehe Section 1.4). Diese Phase verfolgte einen vereinten Problemlösungsansatz. Dieses Framework mit seiner Strukturierung ermöglichte die Operationalisierung von NRBCs für Computer-Simulationen. Dabei werden problemstrukturierende Methoden, wie beispielsweise GIS, mit qualitativen Methoden, z.B. einer Diskursanalyse, kombiniert. Die Ergebnisse der Implementierung von Problemabgrenzung und –strukturierung zeigt die unterschiedlichen Treiber von Konflikten über Naturresourcen, die von den Akteuren genannt wurden. Mithilfe von GIS wurden Mental Maps der Akteure basierend auf den verschiedenen Dimensionen des Konflikts und der Vulnerabilität visualisiert. Die Ergebnisse zeigen die Gemeinsamkeiten des Interesses lokaler Aktuere. Gleichwohl half die gemeinsame Problemabgrenzung dabei, die Eingangsvariablen zu organisieren, die in der Modellierungsphase genutzt wurden. Deshalb wird die Operationalisierung der Konfliktfaktoren, welche bei der gemeinsamen Problemabgrenzung erzeugt wurde, als kritischer Schritt im interdisziplinären Modellansatz naturresourcenbedinger Konflikte gesehen. Die zweite Phase nach der gemeinsamen Problemphase war die Koproduktion zwischen Wissen über Konflikte über Naturresourcen und die Integration des Wissens der Akteure. Die Methodik und der Algorithmus von SEFLAME-CM wurde in Section 5 vorgestellt und anschließend einem strengen Validierungsprozess unterworfen (Section 6). Vor der Entwicklung des disziplinübergreifenden Modellansatzes SEFLAME-CM, welcher validiert und in dieser Arbeit angewandt wurde, wurde ein ähnliches, aber räumlich nicht explizites Modell – FLAME-CM – entwickelt, verbessert und einem iterativen Prozess folgend mit Methoden wie R², p-Values und RMSE getestet. Das Ergebnis des validierten FLAME-CM wurde auf lokaler Skala durchgeführt, aber dann auf räumlich expliziten Kontext mit einer Auflösung von 200x200 Metern übertragen. Wie in Abbildung 6.7 gezeigt, ist der Modell-Output von SEFLAME-CM final und der Prozess muss nicht länger auf FLAME-CM zurückgestuft werden. Abbildung 6.7 skizziert den übergreifenden Validierungsprozess. SEFLAME-CM wurde zunächst validiert, indem die Outputs mit einer räumlich multikriteriellen Evaluierung im Konfliktmanagement (Spatial Multi-Criteria Evaluation for Conflict Management, SMCE-CM) verglichen wurden. Die Ergebnisse des zuletztgenannten Verfahrens belegten, dass die Modellergebnisse korrekt mit echten Daten (Fernerkundung) übereinstimmen. Das Ergebnis des erstgenannten Verfahrens zeigt, dass SEFLAME-CM bessere Resultate erzielt, selbst wenn es mit dem existierenden Modell SMCE-CM verglichen wird. Der Vorteil von SEFLAME-CM ist jedoch, dass es ohne Weiteres gewichtete Inputs durch die Akteure und Stakeholder direkt in der Phase der Problemabgrenzung annimmt. Die gesamte methodologische Wissenschaftsprozedur zeigt daher einen Methodenmix aus Natur- und Sozialwissenschaften, wie beispielsweise eine integrative Kooperation der verschiedenen Akteure. Die dritte und letzte Phase der Arbeit beinhaltet den Ausblick und die Schlussfolgerung (Section 7). Sie behandelt die Anwendung der gekoppelten Informationen. Diese finale Wissenschaftsphase umfasst eine gemeinschaftliche Erarbeitung von Szenarien und eine Simulation von Langzeitstrategien zum Konflikt-Management. Die Erstellung der Szenarien behandelt das Potential eines gemeinschaftlichen Management natürlicher Resourcen. Eine Verbesserung der Zusammenarbeit wird im Konflikt-Management zunehmend als wichtiger Bestandteil dauerhafter Friedensschließung angesehen (Bruch et al., 2009, Ratner et al., 2013). Nach Entwicklung und Validierung einer innovativen, räumlich expliziten Modell-Komponente, SEFRAME-CM, war der nächste logische Schritt dieser ArbAeit die Methoden auf zukünftiges Konflikt-Management anzuwenden, indem das Management natürlicher Resourcen in Klimamodelle integriert wurde. Der Vorschlag für ein „Szenario“ für zukünftiges Konfliktmanagement beinhaltet die Zeitperiode von 2016 bis 2060. Dies liegt darin begründet, dass sich lokale Szenarien mit 20-30 Jahren (Folhes et al., 2015) auf kürzere Zeiträume konzentrieren, während globale Szenarien einen Horizont von 50-100 Jahren umspannen. Die Wahl fällt auf einen Zeitraum von 20-30 Jahren, da die Ergebnisse der Studie auf regionaler und nationaler Regierungsführung anwendbar sind. Eine Implementierung der gemeinschaftlich konstruierten Szenarien würde dabei helfen Optionen und Strategien des Konfliktmanagements zu erkunden, welche die Politik und deren Entscheidungsträger im Bezug auf Ressourcenmanagement beeinflussen. Eine Investition in Konflikt-Management, z.B. im Niger Delta, kann durch Neuausrichtung militärischer Strategien und das derzeit nicht-nachhaltige Presidential Armnesty Programm geschehen um Friedensbildung und Nachhaltigkeit zu erreichen. Da soziale Resilienz eine naturgemäße Antwort auf Unheil und Katastrophen darstellt, wird oft so argumentiert, dass Pläne zum Konflikt-Management die adaptiven Möglichkeiten der Communitys anerkennt und auf ihnen aufbaut, während Gebiete mit hohem Potential an Resilienz prioritär für Naturresourcen-Management der Zukunft angesehen wird Zusammenfassend lässt sich sagen, dass die in dieser Arbeit dargestellte Herangehensweise die Anwendung eines interdisziplinären Modells ermöglicht, das auf gemeinsam entwickeltem Wissen von Experten und lokalen Akteuren im Management von NRBCs beruht. Sowohl die externen als auch internen Vulnerabilitätstreiber der NRBCs wurden bewertet. Die Ergebnisse zeigen, dass die Degradation der Umwelt sowie sozio-ökonomische als auch politische Treiber von Resourcenkonflikten jeweils holistisch, aber auch als separate Treiber im Zusammenspiel natürlicher Resourcen und Konflikten auf kommunaler Ebene behandelt werden können. Trotz allem gibt es Limitierungen, die hauptsächlich auf den komplexen sozialen Prozessen der realen globalen Prozesse beruhen. Die Ergebnisse aus räumlich und zeitlich hoch aufgelösten Daten zeigte sich als sehr nützlich und stellt die Basis für die Unterstützung der Strategien des integrierte Management von Küstenzonen dar, wie sie für ein zukünftiges Management in der Region des Niger Deltas Anwendung finden soll. Das Modell bleibt dabei stark anpassungsfähig für ähnliche Fälle von NRBCs in Afrika und anderen Regionen der Welt, bei denen biophysikalische, sozio-ökonomische und politische Verbindungen entzweit werden. Dies gilt besonders dann, wenn die Datengrundlage knapp und die verfügbaren Datensätze unpräzise

    A framework for managing global risk factors affecting construction cost performance

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    Poor cost performance of construction projects has been a major concern for both contractors and clients. The effective management of risk is thus critical to the success of any construction project and the importance of risk management has grown as projects have become more complex and competition has increased. Contractors have traditionally used financial mark-ups to cover the risk associated with construction projects but as competition increases and margins have become tighter they can no longer rely on this strategy and must improve their ability to manage risk. Furthermore, the construction industry has witnessed significant changes particularly in procurement methods with clients allocating greater risks to contractors. Evidence shows that there is a gap between existing risk management techniques and tools, mainly built on normative statistical decision theory, and their practical application by construction contractors. The main reason behind the lack of use is that risk decision making within construction organisations is heavily based upon experience, intuition and judgement and not on mathematical models. This thesis presents a model for managing global risk factors affecting construction cost performance of construction projects. The model has been developed using behavioural decision approach, fuzzy logic technology, and Artificial Intelligence technology. The methodology adopted to conduct the research involved a thorough literature survey on risk management, informal and formal discussions with construction practitioners to assess the extent of the problem, a questionnaire survey to evaluate the importance of global risk factors and, finally, repertory grid interviews aimed at eliciting relevant knowledge. There are several approaches to categorising risks permeating construction projects. This research groups risks into three main categories, namely organisation-specific, global and Acts of God. It focuses on global risk factors because they are ill-defined, less understood by contractors and difficult to model, assess and manage although they have huge impact on cost performance. Generally, contractors, especially in developing countries, have insufficient experience and knowledge to manage them effectively. The research identified the following groups of global risk factors as having significant impact on cost performance: estimator related, project related, fraudulent practices related, competition related, construction related, economy related and political related factors. The model was tested for validity through a panel of validators (experts) and crosssectional cases studies, and the general conclusion was that it could provide valuable assistance in the management of global risk factors since it is effective, efficient, flexible and user-friendly. The findings stress the need to depart from traditional approaches and to explore new directions in order to equip contractors with effective risk management tools

    Evolving to Digital and Programmable Value Based Economy: General Prospect and Specific Applications over Sustainability

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    [eng] In the fields of economics, business and management, how could Digital Transformation (DT) advance value creation and reliably encourage value capture, exchange and distribution? This thesis aim to fill that gap with a novel framework to support policy-makers, countries, cities and businesses address the potential value that can be generated and captured by digitalization combining DT and Internet of Value theoretical perspectives and practical applications of them over concrete issues such as sustainability in cities, as an example. For this, it is proposed to make new contributions related to DT and Internet of Value in two main aspects: to explore DT countries’ mindsets when it relates to their value progress through Digital Ecosystems and to advance with the potential digital value applications through Programmable Economy advantages when it focus on concrete aspect such as sustainability in cities. Both perspectives, although it will be applied on different dimensions and on different purposes, have in common that they are focus on digital and programable value based economy and management and want to explore the best way to maximize and capture the DT potential in terms of value for organizations and society. Thus, first, it will be analysed the importance of knowing clearly the digital ecosystem in which the agents are operating in order to reinforce the value creation by promoting the inclusivity and connectivity of the endpoints involved in it. Secondly, it will be analysed how the digital value can be captured, exchanged and redistributed in a complex issues such as sustainability by deploying concrete digital applications that include human reinforcement aspects to, finally, closing the circle combining both perspectives in a single framework. To achieve these objectives in this thesis, own models are proposed, inspired by other theoretical models already contrasted, and some proven methodologies are used related to Conditional Probability, Forgotten Effects and Fuzzy Sets. As a main conclusion, Digital Transformation has the potential to generate immense value for economy and society. Although currently the capture of the vast majority of it is not guaranteed and its distribution between agents is no clear, new formulas are being explored supported by the Internet of Value. This thesis defends that if agents want to advance value creation and encourage value capture, they should consider to make their own Digital and Programmable Value Based Economy and Management framework through: - Allowing all functional agents work in a Digital Ecosystem embracing new relationships and ways of collaborating pursuing the same purpose. - Deploying Programmable Economy applications advantages, mixing digital's and analogue's world that can be interlinked and programmed by the blockchain allowing monetization and exploring new human and machine alliances. - Adopting strong and inclusive agents’ commitment in order to exploit the advantages that this smart economy system has from a human centric vision, discovering new forms of value, considering that, although tech can be everywhere, value not

    Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence

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    This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2021R1A2C1011198) , (Institute for Information & communications Technology Planning & Evaluation) (IITP) grant funded by the Korea government (MSIT) under the ICT Creative Consilience Program (IITP-2021-2020-0-01821) , and AI Platform to Fully Adapt and Reflect Privacy-Policy Changes (No. 2022-0-00688).Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated applications, but the outcomes of many AI models are challenging to comprehend and trust due to their black-box nature. Usually, it is essential to understand the reasoning behind an AI mode Äľs decision-making. Thus, the need for eXplainable AI (XAI) methods for improving trust in AI models has arisen. XAI has become a popular research subject within the AI field in recent years. Existing survey papers have tackled the concepts of XAI, its general terms, and post-hoc explainability methods but there have not been any reviews that have looked at the assessment methods, available tools, XAI datasets, and other related aspects. Therefore, in this comprehensive study, we provide readers with an overview of the current research and trends in this rapidly emerging area with a case study example. The study starts by explaining the background of XAI, common definitions, and summarizing recently proposed techniques in XAI for supervised machine learning. The review divides XAI techniques into four axes using a hierarchical categorization system: (i) data explainability, (ii) model explainability, (iii) post-hoc explainability, and (iv) assessment of explanations. We also introduce available evaluation metrics as well as open-source packages and datasets with future research directions. Then, the significance of explainability in terms of legal demands, user viewpoints, and application orientation is outlined, termed as XAI concerns. This paper advocates for tailoring explanation content to specific user types. An examination of XAI techniques and evaluation was conducted by looking at 410 critical articles, published between January 2016 and October 2022, in reputed journals and using a wide range of research databases as a source of information. The article is aimed at XAI researchers who are interested in making their AI models more trustworthy, as well as towards researchers from other disciplines who are looking for effective XAI methods to complete tasks with confidence while communicating meaning from data.National Research Foundation of Korea Ministry of Science, ICT & Future Planning, Republic of Korea Ministry of Science & ICT (MSIT), Republic of Korea 2021R1A2C1011198Institute for Information amp; communications Technology Planning amp; Evaluation) (IITP) - Korea government (MSIT) under the ICT Creative Consilience Program IITP-2021-2020-0-01821AI Platform to Fully Adapt and Reflect Privacy-Policy Changes2022-0-0068

    The Trilogy of Science: Filling the Knowledge Management Gap with Knowledge Science and Theory

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    The international knowledge management field has different ways of investigating, developing, believing, and studying knowledge management. Knowledge management (KM) is distinguished deductively by know-how, and its intangible nature establishes different approaches to KM concepts, practices, and developments. Exploratory research and theoretical principles have formed functional intelligences from 1896 to 2013, leading to a knowledge management knowledge science (KMKS) concept that derived a grounded theory of knowledge activity (KAT). This study addressed the impact of knowledge production problems on KM practice. The purpose of this qualitative meta-analysis study was to fit KM practice within the framework of knowledge science (KS) study. Themed questions and research variables focused on field mechanisms, operative functions, principle theory, and relationships of KMKS. The action research used by American practitioners has not established a formal structure for KS. The meta-data-analysis examined 385 transdisciplinary peer-reviewed articles using social science, service science, and systems science databases, with a selection of interdisciplinary studies that had a practice-research-theory framework. Key attributes utilizing Boolean limiters, words, phrases and publication dates, along with triangulation, language analysis and coding through analytic software identified commonalities of the data under study. Findings reflect that KM has not become a theoretically saturated field. KS as the forensic science of KM creates a paradigm shift, causes social change that averts rapid shifts in management direction and uncertainty, and connects KM philosophy and science of knowledge. These findings have social change implications by informing the work of managers and academics to generate a methodical applied science
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