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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During the past two decades the implementation and adoption of information technology has rapidly increased. As a consequence the way businesses operate has changed dramatically. For example, the amount of data has grown exponentially. Companies are looking for ways to use this data to add value to their business. This has implications for the manner in which (financial) governance needs to be organized. The main purpose of this study is to obtain insight in the changing role of controllers in order to add value to the business by means of data analytics. To answer the research question a literature study was performed to establish a theoretical foundation concerning data analytics and its potential use. Second, nineteen interviews were conducted with controllers, data scientists and academics in the financial domain. Thirdly, a focus group with experts was organized in which additional data were gathered. Based on the literature study and the participants responses it is clear that the challenge of the data explosion consist of converting data into information, knowledge and meaningful insights to support decision-making processes. Performing data analyses enables the controller to support rational decision making to complement the intuitive decision making by (senior) management. In this way, the controller has the opportunity to be in the lead of the information provision within an organization. However, controllers need to have more advanced data science and statistic competences to be able to provide management with effective analysis. Specifically, we found that an important skill regarding statistics is the visualization and communication of statistical analysis. This is needed for controllers in order to grow in their role as business partner..
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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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Although education programmes are constantly being renewed, innovation does not always lead to anchored changes in educational practice. One explanation is that educational innovation evolves more dynamics than often is assumed. Instead of following a well-designed plan, the core activities of innovation leaders hinge on the ability to swiftly identify and interpret situations with which they are confronted. This suggests that the Volatile, Uncertain, Complex, Ambiguous (VUCA) innovation process requires a specific repertoire from innovation leaders, including a better understanding of their internal decision-making processes. In our search for a fitting repertoire, we discovered the capacity for “situational awareness” as a concept to help understand complex situations and to determine very quickly what needs to be done. Additionally, we focus on how innovation leaders make decisions at significant moments during the innovation process in higher education. We describe how our discovery leads to the development of a lens for innovation leaders, with situational awareness as a starting point, and supplemented with the filtering, framing and guiding function of beliefs as steering principles of internal decision making-processes. This allows to gain a better understanding of how the innovation leader identifies critical situations and responds in terms of interpretation and action.
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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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In urban planning, 3D modeling and virtual reality (VR) provide new means for involving citizens in the planning process. For municipal government, it is essential to know how effective these means are, to justify investments. In this study, we present a case of using VR in a municipal process of civic participation concerning the redesign of a public park. The process included codesign activities and involved citizens in decision-making through a ballot, using 3D-rendered versions of competing designs. In codesign, 3D-modeling tools were instrumental in empowering citizens to negotiate design decisions, to discuss the quality of designs with experts, and to collectively take decisions. This paper demonstrates that, in a ballot on competing designs with 1302 citizens, VR headsets proved to be equally effective compared to other display technologies in informing citizens during decision making. The results of an additional, controlled experiment indicate that VR headsets provide higher engagement and more vivid memories than viewing the designs on non-immersive displays. By integrating research into a municipal process, we contribute evidence of cognitive and engagement effects of using 3D modeling and immersive VR technologies to empower citizens in participatory urban planning. The case described in the paper concerns a public park; a similar approach could be applied to the design of public installations including media architecture.
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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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This thesis focuses on topics such as preterm birth, variation in gross motor development, factors that influence (premature) infant gross motor development, and parental beliefs and practices. By gaining insight into these topics, this thesis aims to contribute to clinical decision-making of paediatric physiotherapists together with parents, and with that shape early intervention.
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