Vlerick Repository
The Vlerick Repository is a searchable open-access publication database, containing the complete archive of research output written by Vlerick Business School faculty and researchers.
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Publication Towards implementing new payment models for the reimbursement of high-cost, curative therapies in Europe: insights from semi-structured interviews(Frontiers Media SA, 2025)BACKGROUND: New ways of reimbursement for high-cost, one-shot curative therapies such as advanced therapy medicinal products (ATMPs) are a growing area of interest to stakeholders in market access such as industry representatives, legislative and accounting experts, physicians, hospital managers, hospital pharmacists, patient representatives, policymakers, and sickness funds. Due to the complex nature of ATMPs, new payment models and reimbursement modalities are proposed yet not widely applied across Europe. OBJECTIVES: This study aimed to elicit opinions on and insights into the governance aspect of implementing outcome-based spread payments (OBSP) in Belgium for the reimbursement of innovative therapies. Stakeholders' responsibilities and roles were analysed and proposed solutions or general beliefs were assessed to identify necessary or sufficient conditions to establish outcome-based spread payments. METHODS: Semi-structured interviews (n = 33) were conducted with physicians (n = 2), hospital pharmacists (n = 4), hospital managers (n = 2), Belgian policymakers (n = 6), legislative experts (n = 2), accounting experts (n = 5), representatives of patients (n = 3), of industry (n = 5), and sickness funds (n = 4). The interviews took place between July 2020 and October 2020. The framework method analysis was performed using Nvivo software (version 20.4.1.851). Statements were allocated into six main topics: payment structure, spread payments, outcome-based agreements, governance, transparency, and regulation. RESULTS: Interviews revealed the necessary conditions that, fulfilled together, are seen to be sufficient for the successful implementation of OBSP, including consensus on pricing, payment logistics, robust data infrastructure and financing, clear agreement terms (duration, outcome parameters, payment triggers), long-term patient follow-up solutions, an external multi-stakeholder governance body, and transparency regarding agreement types. CONCLUSION: Despite the interest, the effective implementation of OBSP falls behind due to a lack of consensus on how this new reimbursement method can be a sustainable solution. By stating the necessary conditions that, when fulfilled together, are deemed sufficient for successful OBSP implementation, this study provides a framework towards overcoming implementation barriers and realizing the potential of OBSP in transforming healthcare reimbursement practices.Publication Preparación del plan financiero – Proyecciones(Amazon, 2025)Este capítulo profundiza en los aspectos técnicos de la planificación financiera de una startup. El plan financiero es el punto de partida para cualquier estrategia en esta área. Su primer objetivo es determinar si la empresa requerirá financiamiento externo y, de ser así, qué cantidad de financiamiento necesitará y en qué momento. Además, este plan sirve como base para la valuación de la empresa. Por último, y probablemente lo más importante, brinda al equipo emprendedor y a los inversionistas potenciales la oportunidad de evaluar críticamente y optimizar el modelo de negocio.Publication Understanding ageism in the workplace (Research Summary)(Francisco Manuel dos Santos Foundation, 2024)An aging population has widereaching social, political and economic implications for societies. Changes in the workforce age composition can create social tensions, perceptions of threat and challenging workplace dynamics, especially between younger and older workers. It is crucial to better understand how younger and older workers see each other, and how this affects how they interact. Although the social psychological literature has provided important insights into ageist perceptions, attitudes, and behaviors, the lion’s share of research has focused on how older people are perceived. However, age biases can be directed at both younger and older adults/workers. This research summary presents key findings of a three-year research project on bidirectional ageism in Portugal, supported by the Fundação Francisco Manuel dos Santos. Data were collected from different samples, including a 1,000-person representative sample of the Portuguese population. Over 20 surveys were conducted, and an experiment was run to rigorously show effects of ageism on workplace outcomes. A variety of qualitative and quantitative approaches were used to analyse the data. A thorough review of relevant literature was conducted, and experts within and outside of Portugal were consulted along the way. Recommendations are provided for addressing ageism against both younger and older workers.Publication Understanding ageism in the workplace(Francisco Manuel dos Santos Foundation, 2024)An ageing society and workforce present both challenges and opportunities. The presence of multiple generations in the workplace can lead to age-related tensions, with some workers considered “too young” and others “too old”. How different age groups view and behave toward each other can have important consequences for workplace relationships, attitudes and performance, as well as for the wellbeing of employees. In this research study, we have examined predictors and consequences of ageism aimed at both younger and older workers. The results from a range of qualitative and quantitative studies, including a representative sample of one thousand Portuguese workers, show that ageism can have important, mostly negative, consequences for those targeted, as well as for endorsers of ageism. Based on our findings, we make recommendations for actions that can be taken to reduce bidirectional ageism in the workplace.Publication A multi-module explainable artificial intelligence framework for project risk management: Enhancing transparency in decision-making(Pergamon Elsevier Science Ltd, 2025)The remarkable advancements in machine learning (ML) have led to its extensive adoption in Project Risk Management (PRM), leveraging its powerful predictive capabilities and data-driven insights that support proactive decision-making. Nevertheless, the “black-box” nature of ML models obscures the reasoning behind predictions, undermining transparency and trust. To address this, existing explainable artificial intelligence (XAI) techniques, such as Local Interpretable Model-agnostic Explanations (LIME), Global Priors-based LIME (G-LIME), and SHapley Additive exPlanations (SHAP), have been applied to interpret black-box models. Yet, they face considerable limitations in PRM, including their inability to model cascading effects and multi-level dependencies among risk factors, suffering from inconsistencies due to random sampling, and failure to capture non-linear interactions in high-dimensional risk data. In response to these shortcomings, this paper proposes the Multi-Module eXplainable Artificial Intelligence framework for Project Risk Management (MMXAI-PRM), a novel approach designed to address the unique demands of PRM. The framework consists of three modules: the Risk Relationship Insight Module (RRIM), which models risk dependencies using a Knowledge Graph (KG); the Risk Factor Influence Analysis Module (RFIAM), which introduces a Conditional Tabular Generative Adversarial Network-aided Local Interpretable Model-agnostic Explanations using Kernel Ridge Regression (CTGAN-LIME-KR) to ensure explanation consistency and handle non-linearity; and the Visualization and Interpretation Module (VIM), which synthesizes these insights into an interpretable, chain-based representation. Extensive experiments demonstrate that MMXAI-PRM delivers more consistent, stable, and accurate explanations than existing XAI methods. By improving interpretability, it enhances trust in AI-driven risk predictions and equips project managers with actionable insights, advancing decision-making in PRM.