Analyzing historical decision-related data can help support actual operational decision-making processes. Decision mining can be employed for such analysis. This paper proposes the Decision Discovery Framework (DDF) designed to develop, adapt, or select a decision discovery algorithm by outlining specific guidelines for input data usage, classifier handling, and decision model representation. This framework incorporates the use of Decision Model and Notation (DMN) for enhanced comprehensibility and normalization to simplify decision tables. The framework’s efficacy was tested by adapting the C4.5 algorithm to the DM45 algorithm. The proposed adaptations include (1) the utilization of a decision log, (2) ensure an unpruned decision tree, (3) the generation DMN, and (4) normalize decision table. Future research can focus on supporting on practitioners in modeling decisions, ensuring their decision-making is compliant, and suggesting improvements to the modeled decisions. Another future research direction is to explore the ability to process unstructured data as input for the discovery of decisions.
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In case of a major cyber incident, organizations usually rely on external providers of Cyber Incident Response (CIR) services. CIR consultants operate in a dynamic and constantly changing environment in which they must actively engage in information management and problem solving while adapting to complex circumstances. In this challenging environment CIR consultants need to make critical decisions about what to advise clients that are impacted by a major cyber incident. Despite its relevance, CIR decision making is an understudied topic. The objective of this preliminary investigation is therefore to understand what decision-making strategies experienced CIR consultants use during challenging incidents and to offer suggestions for training and decision-aiding. A general understanding of operational decision making under pressure, uncertainty, and high stakes was established by reviewing the body of knowledge known as Naturalistic Decision Making (NDM). The general conclusion of NDM research is that experts usually make adequate decisions based on (fast) recognition of the situation and applying the most obvious (default) response pattern that has worked in similar situations in the past. In exceptional situations, however, this way of recognition-primed decision-making results in suboptimal decisions as experts are likely to miss conflicting cues once the situation is quickly recognized under pressure. Understanding the default response pattern and the rare occasions in which this response pattern could be ineffective is therefore key for improving and aiding cyber incident response decision making. Therefore, we interviewed six experienced CIR consultants and used the critical decision method (CDM) to learn how they made decisions under challenging conditions. The main conclusion is that the default response pattern for CIR consultants during cyber breaches is to reduce uncertainty as much as possible by gathering and investigating data and thus delay decision making about eradication until the investigation is completed. According to the respondents, this strategy usually works well and provides the most assurance that the threat actor can be completely removed from the network. However, the majority of respondents could recall at least one case in which this strategy (in hindsight) resulted in unnecessary theft of data or damage. Interestingly, this finding is strikingly different from other operational decision-making domains such as the military, police and fire service in which there is a general tendency to act rapidly instead of searching for more information. The main advice is that training and decision aiding of (novice) cyber incident responders should be aimed at the following: (a) make cyber incident responders aware of how recognition-primed decision making works; (b) discuss the default response strategy that typically works well in several scenarios; (c) explain the exception and how the exception can be recognized; (d) provide alternative response strategies that work better in exceptional situations.
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The value of a decision can be increased through analyzing the decision logic, and the outcomes. The more often a decision is taken, the more data becomes available about the results. More available data results into smarter decisions and increases the value the decision has for an organization. The research field addressing this problem is Decision mining. By conducting a literature study on the current state of Decision mining, we aim to discover the research gaps and where Decision mining can be improved upon. Our findings show that the concepts used in the Decision mining field and related fields are ambiguous and show overlap. Future research directions are discovered to increase the quality and maturity of Decision mining research. This could be achieved by focusing more on Decision mining research, a change is needed from a business process Decision mining approach to a decision focused approach.
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In this thesis several studies are presented that have targeted decision making about case management plans in probation. In a case management plan probation officers describe the goals and interventions that should help offenders stop reoffending, and the specific measures necessary to reduce acute risks of recidivism and harm. Such a plan is embedded in a judicial framework, a sanction or advice about the sanction in which these interventions and measures should be executed. The topic of this thesis is the use of structured decision support, and the question is if this can improve decision making about case management plans in probation and subsequently improve the effectiveness of offender supervision. In this chapter we first sketch why structured decision making was introduced in the Dutch probation services. Next we describe the instrument for risk and needs assessment as well as the procedure to develop case management plans that are used by the Dutch probation services and that are investigated in this thesis. Then we describe the setting of the studies and the research questions, and we conclude with an overview of this thesis.
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Motor learning is particularly challenging in neurological rehabilitation: patients who suffer from neurological diseases experience both physical limitations and difficulties of cognition and communication that affect and/or complicate the motor learning process. Therapists (e.g.,, physiotherapists and occupational therapists) who work in neurorehabilitation are therefore continuously searching for the best way to facilitate patients during these intensive learning processes. To support therapists in the application of motor learning, a framework was developed, integrating knowledge from the literature and the opinions and experiences of international experts. This article presents the framework, illustrated by cases from daily practice. The framework may assist therapists working in neurorehabilitation in making choices, implementing motor learning in routine practice, and supporting communication of knowledge and experiences about motor learning with colleagues and students. The article discusses the framework and offers suggestions and conditions given for its use in daily practice.
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From the article: The ethics guidelines put forward by the AI High Level Expert Group (AI-HLEG) present a list of seven key requirements that Human-centered, trustworthy AI systems should meet. These guidelines are useful for the evaluation of AI systems, but can be complemented by applied methods and tools for the development of trustworthy AI systems in practice. In this position paper we propose a framework for translating the AI-HLEG ethics guidelines into the specific context within which an AI system operates. This approach aligns well with a set of Agile principles commonly employed in software engineering. http://ceur-ws.org/Vol-2659/
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The shift towards a more sustainable circular economy will require innovations. While SMEs can contribute to this development, financing innovations within SMEs is difficult. Various authors have not ed moreover that the concept of the circular economy has further increased the complexity of investment decisions concerning sustainable innovations, due to the multiple value creation and new business models involved . On the other hand
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This report describes "a framework that delivers insight into the tangible and intangible effects of a mobile (IT) system, before it is being implemented".
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Schepen in moeilijkheden op zee leveren vaak besluitvormingsproblemen op tussen de scheepseigenaar/kapitein en de kuststaat. Kuststaten en met name de lokale overheden willen een probleem schip graag zo ver mogelijk weg sturen van hun gebied terwijl de eigenaar/kapitein zijn schip graag zo snel mogelijk naar de kust, een beschutte locatie of haven wil brengen. Het onderzoek geeft onderbouwing voor de besluitvorming rond schepen in moeilijkheden, zowel voor de zeescheepvaart als de betrokken besluitvormers van oeverstaten. Het product van het project is: een, op uitgewerkte scenario’s per scheepstype en lading gebaseerde besluitvormingsprocedure voor zeeschepen in moeilijkheden
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Summary Project objectives This study fits into a larger research project on logistics collaboration and outsourcing decisions. The final objective of this larger project is to analyze the logistics collaboration decision in more detail to identify thresholds in these decisions. To reach the overall objectives, the first step is to get a clearer picture on the chemical and logistics service providers industry, sectors of our study, and on logistics collaboration in these sectors. The results of this first phase are presented in this report. Project Approach The study consists of two parts: literature review and five case studies within the chemical industry. The literature covers three topics: logistics collaboration, logistics outsourcing and purchasing of logistics services. The five case studies are used to refine the theoretical findings of the literature review. Conclusions Main observations during the case studies can be summarized as follows: Most analyzed collaborative relationships between shippers and logistics service providers in the chemical industry are still focused on operational execution of logistics activities with a short term horizon. Supply management design and control are often retained by the shippers. Despite the time and cost intensive character of a logistics service buying process, shippers tendering on a very regular basis. The decision to start a new tender project should more often be based on an integral approach that includes all tender related costs. A lower frequency of tendering could create more stability in supply chains. Beside, it will give both, shippers and LSPs, the possibility to improve the quality of the remaining projects. Price is still a dominating decision criterion in selecting a LSP. This is not an issue as long as the comparison of costs is based on an integral approach, and when shippers balance the cost criterion within their total set of criteria for sourcing logistics services. At the shippers' side there is an increased awareness of the need of more solid collaboration with logistics service providers. Nevertheless, in many cases this increased awareness does not actually result in the required actions to establish more intensive collaboration. Over the last years the logistics service providers industry was characterized by low profit margins, strong fragmentation and price competition. Nowadays, the market for LSPs is changing, because of an increasing demand for logistics services. To benefit from this situation a more pro-active role of the service providers is required in building stronger relationships with their customers. They should pay more attention on mid and long term possibilities in a collaborative relation, in stead of only be focused on running the daily operation.
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