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on Project, Program and Portfolio Management |
| By: | Hernan Huwyler |
| Abstract: | Organizations investing in artificial intelligence face a fundamental challenge: traditional return on investment calculations fail to capture the dual nature of AI implementations, which simultaneously reduce certain operational risks while introducing novel exposures related to algorithmic malfunction, adversarial attacks, and regulatory liability. This research presents a comprehensive financial framework for quantifying AI project returns that explicitly integrates changes in organizational risk profiles. The methodology addresses a critical gap in current practice where investment decisions rely on optimistic benefit projections without accounting for the probabilistic costs of AI-specific threats including model drift, bias-related litigation, and compliance failures under emerging regulations such as the European Union Artificial Intelligence Act and ISO/IEC 42001. Drawing on established risk quantification methods, including annual loss expectancy calculations and Monte Carlo simulation techniques, this framework enables practitioners to compute net benefits that incorporate both productivity gains and the delta between pre-implementation and post-implementation risk exposures. The analysis demonstrates that accurate AI investment evaluation requires explicit modeling of control effectiveness, reserve requirements for algorithmic failures, and the ongoing operational costs of maintaining model performance. Practical implications include specific guidance for establishing governance structures, conducting phased validations, and integrating risk-adjusted metrics into capital allocation decisions, ultimately enabling evidence-based AI portfolio management that satisfies both fiduciary responsibilities and regulatory mandates. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2511.21975 |
| By: | Sang-Kyu Lee (Korea Institute for Industrial Economics and Trade) |
| Abstract: | This study is grounded on the premise that, given the transformative advances in artificial intelligence (AI) technologies occurring across the industrial landscape, AI tools should be actively implemented into the design and implementation of industrial policy. We argue that this is especially true for R&D policy, which is central to national competitiveness in science and technology, and which must consider multiple diverse variables, including the global economy, the overall industrial environment, corporate management, and technological capabilities.<p> For this study, I apply machine learning (ML)-based anomaly detection (AD) to analyze high-performing national R&D projects, and specifically assess ML-based AD that considers both input and output variables and analyzes structural patterns. Building on these analytical results, I propose firm-size-specific differentiated policy measures designed to enhance R&D performance.<p> The goal of this study is to establish a policy-decision framework that improves timeliness and precision in the operation and management of national R&D programs and, in the longer term, contributes to the realization of AI-based policy planning and operational management. |
| Keywords: | machine learning; artificial intelligence; AI; anomaly detection; DEA; SHAP; research and development; R&D; government R&D; industrial policy; South Korea |
| JEL: | I23 I28 O32 O38 |
| Date: | 2025–10–31 |
| URL: | https://d.repec.org/n?u=RePEc:ris:kieter:021804 |
| By: | Rivasplata Ramírez, Arnold; Ocola Agüero, Kendy |
| Abstract: | This study analyzes the determinants of public investment project completion in Peru, using a weighted hierarchical logit model to control for heterogeneity at the macro-regional and institutional function levels. The dependent variable is project completion, while the explanatory variables include selection in the Transitory Complementary Provision (DCT), financial progress, project typology, level of government, use of Form 12B, and the Multiannual Investment Programming (PMI). The results show that financial progress and the use of Form 12B significantly increase the probability of project completion, with marginal effects of 0.32 and 0.18, respectively. In contrast, selection under the DCT and the existence of the PMI are associated with lower probabilities of completion, indicating that planning or resource allocation alone does not guarantee effective execution. Additionally, projects under the National and Regional governments have a higher likelihood of completion compared to local government projects, while smaller projects, such as PIP Minor and Investment Projects, face greater challenges in successfully reaching completion. IOARR projects, on the other hand, show completion outcomes comparable to PIP Major projects, without statistically significant differences. These findings highlight the importance of financial execution, management tools, and institutional capacity for the success of public investment projects, providing relevant empirical evidence for improving project management and investment prioritization within the framework of Peru’s public investment system. |
| Keywords: | public investment, investment projects, hierarchical logit model, marginal effects, random effects, investment closure. |
| JEL: | C25 H54 H72 O22 R58 |
| Date: | 2025–11–28 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:127047 |
| By: | Pilz, Madlen; Haupt, Wolfgang; Rößler, Stefanie; Renz, Lilly Sophie |
| Abstract: | Neue Arbeitsfelder, die aufgrund ihrer Komplexität die Arbeit verschiedener Ressorts berühren und deren Zusammenarbeit bedingen, wie Integration, Klimaschutz oder Klimaanpassung, werden in städtischen Verwaltungen in der Regel als Querschnittsaufgaben angelegt. In den Kommunen kann eine Vielzahl von Ansätzen im Umgang mit Querschnittsaufgaben beobachtet werden, es gibt jedoch keine klar definierten Standards, die Kommunen Hilfe und Orientierung bieten. Da die Aufgaben häufig auch keine Pflichtaufgaben sind, können Kommunen selten die zur Umsetzung notwendigen finanziellen Ressourcen mobilisieren. Die Folge ist, dass die Aufgaben häufig mit wenig Personal und geringem Ressourcenaufwand in den Verwaltungen realisiert werden, was jedoch selten der Komplexität der Aufgaben gerecht wird und von verschiedenen Seiten als unzureichend kritisiert wird. Wissenschaftler*innen am Leibniz-Institut für Raumbezogene Sozialforschung - IRS und am Leibniz- Institut für ökologische Raumentwicklung - IÖR haben in zwei transdisziplinären Forschungsprojekten, StadtumMig und ExTrass Umsetzungsstrategien und -praktiken von Integrations- und Klimaaufgaben als Querschnittsaufgaben in städtischen Verwaltungen untersucht. Ausgehend von Beobachtungen zu Hürden, aber auch erfolgversprechenden Ansätzen, haben die Wissenschaftler* innen transdisziplinäre Dialoge zur vertieften Reflexion mit Verwaltungsmitarbeitenden organisiert. Das Ziel war einerseits, einen Austausch über Ressortgrenzen und zwischen Kommunen zu initiieren, andererseits gemeinsam Wege zum Abbau von Hürden und Handlungsempfehlungen zu diskutieren. Die vorliegende Projektdokumentation richtet sich in erster Linie an Mitarbeitende kommunaler Verwaltungen, Kommunalpolitiker*innen und Akteur*innen der Zivilgesellschaft und Sozialarbeit, die häufig mit Verwaltungen zusammenarbeiten. Sie soll zu einer Diskussion über die Herangehensweisen und Umsetzungsmöglichkeiten von Arbeitsfeldern als Querschnittsaufgaben in Verwaltungen anregen. Sie soll Empfehlungen geben, wie über diese Aufgaben nachgedacht und Strategien zur Umsetzung entwickelt werden können. |
| Abstract: | In municipal administrations, new areas of work that are characterized by high complexity and that require cross-departmental cooperation are typically classified as cross-cutting tasks. Examples of such cross-cutting tasks include integration or climate mitigation and adaptation. A variety of approaches can be observed in how municipalities handle cross-cutting tasks; however, there are no clearly defined standards to guide or support them. Since these tasks are often not mandatory, municipalities rarely have the necessary financial resources to implement them. As a result, these tasks are often carried out with limited personnel and minimal resources, which rarely meets the complexity of the challenges and is frequently criticized as insufficient from various perspectives. Researchers at the Leibniz Institute for Regional Social Research (IRS) and the Leibniz Institute of Ecological Urban and Regional Development (IOER) have studied the implementation strategies and practices of integration and climate-related tasks as cross-cutting tasks in municipal administrations through two transdisciplinary research projects: StadtumMig and ExTrass. Based on the observations of numerous obstacles, but also promising approaches the researchers set up transdisciplinary dialogues for reflection with administrative staff to promote deeper reflection. The aim was both to foster exchanges across departmental boundaries and between municipalities, and to jointly discuss ways of overcoming obstacles and formulate actionable recommendations. This project documentation is primarily intended for municipal administration staff, local politicians, and actors from civil society and social work who frequently collaborate with public administrations. Its aim is to stimulate discussion on approaches and implementation strategies for cross-cutting tasks within local governments and to provide recommendations on how these tasks can be conceptualized, along with strategies for their implementation. |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:zbw:irsdia:331858 |
| By: | Chen, Qianmiao |
| Abstract: | Public procurement is highly susceptible to corruption, especially in developing countries. Although open auctions are widely adopted to curb it, this paper finds that corruption remains prevalent even within this procurement format. Procurement officers can collaborate with firms to manipulate scoring rules, ensuring predetermined winners, while corrupt firms submit noncompetitive bids to meet minimum bidder requirements. Using extensive data from Chinese public procurement auctions, the paper introduces model-driven statistical tools to detect such corruption, identifying a corruption rate of 65 percent. A procurement expert audit survey confirms the tools’ reliability, with a 91 percent probability that experts recognize suspicious scoring rules when flagged. Firm-level analysis reveals that local, state-owned, and less productive firms are favored in corrupt auctions. Lastly, the paper explores policy implications. Analysis of the national anti-corruption campaign since 2012 suggests that general investigations may be insufficient to address deeply ingrained corrupt practices. Using counterfactuals based on an estimated structural model, the paper shows that implementing anonymous call-for-tender evaluations could improve social welfare by 10 percent by eliminating suspicious rules and encouraging broader participation. |
| Date: | 2025–12–02 |
| URL: | https://d.repec.org/n?u=RePEc:wbk:wbrwps:11267 |
| By: | Emre Akusta; Raif Cergibozan |
| Abstract: | The aim of this study is to prioritize renewable energy sources to achieve sustainable development in Turkiye by using fuzzy AHP method. In our study, we used 30 criteria that affect the investment in renewable energy sources. We also calculated the weights of these criteria in investment decisions. In addition, we analyzed the advantageous renewable energy sources according to each criterion. Thus, it was determined which renewable energy source is advantageous according to which criteria. The results show that the most important main criteria for renewable energy investments in Turkiye are economic, political, technical, environmental and social criteria, respectively. The most appropriate renewable energy sources according to economic, political, technical and social criteria are solar, wind, hydroelectric, |
| Date: | 2025–12 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.05444 |
| By: | Paulo Roberto de Melo Barros Junior; Monica Alexandra Vilar Ribeiro De Meireles; Jose Luis Lima de Jesus Silva |
| Abstract: | Our work investigates the economic efficiency of the prevailing "ladder-step" investment strategy in oil and gas exploration, which advocates for the incremental acquisition of geological information throughout the project lifecycle. By employing a multi-agent Deep Reinforcement Learning (DRL) framework, we model an alternative strategy that prioritizes the early acquisition of high-quality information assets. We simulate the entire upstream value chain-comprising competitive bidding, exploration, and development phases-to evaluate the economic impact of this approach relative to traditional methods. Our results demonstrate that front-loading information investment significantly reduces the costs associated with redundant data acquisition and enhances the precision of reserve valuation. Specifically, we find that the alternative strategy outperforms traditional methods in highly competitive environments by mitigating the "winner's curse" through more accurate bidding. Furthermore, the economic benefits are most pronounced during the development phase, where superior data quality minimizes capital misallocation. These findings suggest that optimal investment timing is structurally dependent on market competition rather than solely on price volatility, offering a new paradigm for capital allocation in extractive industries. |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2512.00243 |
| By: | Abeysinghe, Subhashini; Arangala, Mathisha; Siriwardena, Dilushi; Meegoda, Malinda |
| Abstract: | Sri Lanka’s strategic location in the Indian Ocean has placed it at the center of intensifying geopolitical competition and rivalry between China and India. This report examines Sri Lanka’s experience in balancing its own priorities and needs with the competing interests and concerns of India and China through the lens of project financing. It provides a data-driven understanding of the opportunities, challenges, and pitfalls that countries like Sri Lanka face by analysing the grants, loans, and investments made by China and India from 2000 to 2023. Drawing from these findings, the report also sheds light on safeguards countries like Sri Lanka can adopt to overcome the challenges and mitigate risks. The experience of Sri Lanka provides valuable insights and lessons for countries navigating similar dynamics that strive to manage strategic competition and rivalry between global and regional powers with their own development needs and priorities. |
| Keywords: | International Development |
| Date: | 2024 |
| URL: | https://d.repec.org/n?u=RePEc:ags:vererr:373339 |