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.
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..
Both gaming and group (decision) support systems (GDSS) are frequently used to support decision-making and policymaking in multi-actor settings. Despite the fact that there are a number of ways in which gaming and GDSS can be used in a complementary manner, there are only sporadic examples of their combined use. No systematic overview or framework exists in which GDSS are related to the functions of gaming or vice versa. In this article, we examine, why, how and for what purpose GDSS can be used to enrich and improve gaming simulation for decision support, and vice versa. In addition to a review of examples found in the literature, four games are discussed where we combined gaming and GDSS for complex decision-making in a multi actor context: INCODELTA, a game about transportation corridors; INFRASTRATEGO, a game about a liberalizing electricity market; CONTAINERS A DRIFT, a game about the planning of a container terminal, and; DUBES, a game about sustainable urban renewal. Based on the literature and these four experiences, a classification is presented of (at least) four ways in which GDSS and gaming can be used in a complementary or even mutually corrective, manner: the use of GDSS for game design, for game evaluation, for game operation and the use of gaming for research, testing and training of GDSS.
Aanleiding: De elektrische auto wordt steeds populairder en er zijn inmiddels meer dan 5.000 openbare en 5.000 semiopenbare oplaadpunten in Nederland. Professionals bij gemeenten, energiebedrijven, laadpuntexploitanten en netbeheerders missen echter de instrumenten waarmee zij tot onderbouwde besluitvorming omtrent de plaatsing en het aantal laadpunten kunnen komen. De belangrijkste vragen die ze hebben, hebben betrekking op beschikbaarheid en gebruik van de laadinfrastructuur (effectiviteit van de infrastructuur), en het sluitend krijgen van de businesscase (kostenefficiëntie). Doelstelling Het project wil bijdragen aan een van de grote uitdagingen rond elektrisch rijden: het ontwikkelen van een effectieve en kostenefficiënte laadinfrastructuur, gedragen door een sluitende businesscase. Het onderzoek bestaat uit het iteratief ontwikkelen van wiskundige voorspel- en simulatiemodellen voor de uitrol en het gebruik van de laadinfrastructuur. De projectdeelnemers toetsen deze modellen in de praktijk met concrete interventies in door de consortiumpartners geboden proeftuinen. De voorspellingen en simulaties worden vervolgens toegankelijk gemaakt voor de professionals bij gemeenten en bedrijven. Studenten ontwikkelen daarvoor instrumenten zoals kennisdashboards en decision-supportsystemen. Overige deelnemers kunnen bij het project aanhaken door casussen in te brengen die de studenten uitwerken met behulp van een datagedreven productontwikkelingsproces. Beoogde resultaten Concrete resultaten van dit project zijn onder andere: " een set gevalideerde en generiek toepasbare voorspel- en simulatiemodellen; " 10 uitgevoerde casestudies waarin concrete simulaties worden uitgevoerd en adviezen voor ketenpartijen worden gedestilleerd; " minimaal 3 experimenten waarin concrete interventies zijn uitgevoerd en geëvalueerd; " 3 geteste (kennis)dashboards voor te selecteren partijen; " 3 gerealiseerde datagedreven producten/services; " 3 concrete en geteste decision-supportsystemen voor nader te selecteren ketenpartijen.
The COVID19 pandemic highlighted the vulnerability in supply chain networks in the healthcare sector and the tremendous waste problem of disposable healthcare products, such as isolation gowns. Single-use disposable isolation gowns cause great ecological impact. Reusable gowns can potentially reduce climate impacts and improve the resilience of healthcare systems by ensuring a steady supply in times of high demand. However, scaling reusable, circular isolation gowns in healthcare organizations is not straightforward. It is impeded by economic barriers – such as servicing costs for each use – and logistic and hygiene barriers, as processes for transport, storage and safety need to be (re)designed. Healthcare professionals (e.g. purchasing managers) lack complete information about social, economic and ecological costs, the true cost of products, to make informed circular purchasing decisions. Additionally, the residual value of materials recovered from circular products is overlooked and should be factored into purchasing decisions. To facilitate the transition to circular procurement in healthcare, purchasing managers need more fine-grained, dynamic information on true costs. Our RAAK Publiek proposal (MODLI) addresses a problem that purchasing managers face – making purchasing decisions that factor in social, economic and ecological costs and future benefits from recovered materials. Building on an existing consortium that developed a reusable and recyclable isolation gown, we design and develop an open-source decision-support tool to inform circular procurement in healthcare organizations and simulate various purchasing options of non-circular and circular products, including products from circular cascades. Circular procurement is considered a key driver in the transition to a circular economy as it contributes to closing energy and material loops and minimizes negative impacts and waste throughout entire product lifecycles. MODLI aims to support circular procurement policies in healthcare organizations by providing dynamic information for circular procurement decision making.
The postdoc candidate, Sondos Saad, will strengthen connections between research groups Asset Management(AM), Data Science(DS) and Civil Engineering bachelor programme(CE) of HZ. The proposed research aims at deepening the knowledge about the complex multidisciplinary performance deterioration prediction of turbomachinery to optimize cleaning costs, decrease failure risk and promote the efficient use of water &energy resources. It targets the key challenges faced by industries, oil &gas refineries, utility companies in the adoption of circular maintenance. The study of AM is already part of CE curriculum, but the ambition of this postdoc is that also AM principles are applied and visible. Therefore, from the first year of the programme, the postdoc will develop an AM material science line and will facilitate applied research experiences for students, in collaboration with engineering companies, operation &maintenance contractors and governmental bodies. Consequently, a new generation of efficient sustainability sensitive civil engineers could be trained, as the labour market requires. The subject is broad and relevant for the future of our built environment being more sustainable with less CO2 footprint, with possible connections with other fields of study, such as Engineering, Economics &Chemistry. The project is also strongly contributing to the goals of the National Science Agenda(NWA), in themes of “Circulaire economie en grondstoffenefficiëntie”,”Meten en detecteren: altijd, alles en overall” &”Smart Industry”. The final products will be a framework for data-driven AM to determine and quantify key parameters of degradation in performance for predictive AM strategies, for the application as a diagnostic decision-support toolbox for optimizing cleaning &maintenance; a portfolio of applications &examples; and a new continuous learning line about AM within CE curriculum. The postdoc will be mentored and supervised by the Lector of AM research group and by the study programme coordinator(SPC). The personnel policy and job function series of HZ facilitates the development opportunity.
