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Forecasting the success of International Joint Ventures (2024)
Presentation / Conference
Nikolopoulos, K., Hamo Younes, A., & Phan, M. (2024, July). Forecasting the success of International Joint Ventures. Poster presented at INFORMS Advances in Decision Analysis Conference (ADA 2024), Aalto University, Helsinki-Espoo, Finland

Forecasting and Planning for a critical infrastructure sector during a pandemic: empirical evidence from a food supply chain (2024)
Journal Article
Aljuneidi, T., Punia, S., Jebali, A., & Nikolopoulos, K. (2024). Forecasting and Planning for a critical infrastructure sector during a pandemic: empirical evidence from a food supply chain. European Journal of Operational Research, https://doi.org/10.1016/j.ejor.2024.04.009

The meat supply chain (MSC) – a key constituent of the ‘Food & Agriculture’ CISA critical infrastructure sector, was among the most impacted by the COVID-19 pandemic. The witnessed successive demand and supply shocks uncovered the f... Read More about Forecasting and Planning for a critical infrastructure sector during a pandemic: empirical evidence from a food supply chain.

Forecasting and planning for special events in the pulp and paper supply chains (2024)
Journal Article
Brookes, T., Nikolopoulos , K., Litsiou, K., & Alghassab, W. (2024). Forecasting and planning for special events in the pulp and paper supply chains. Supply Chain Forum: an International Journal, https://doi.org/10.1080/16258312.2024.2315029

Due to global warming, flood is an increasing threat to companies operating in the pulp and paper industry. The impact of this threat needs to be managed. We deploy a qualitative investigation into how paper manufacturers can forecast and mitigate th... Read More about Forecasting and planning for special events in the pulp and paper supply chains.

Forecasting the Effective Reproduction Number during a Pandemic: COVID-19 Rt forecasts, Governmental Decisions, and Economic Implications (2023)
Journal Article
Nikolopoulos, K., & Vasilakis, C. (2023). Forecasting the Effective Reproduction Number during a Pandemic: COVID-19 Rt forecasts, Governmental Decisions, and Economic Implications. IMA Journal of Management Mathematics, https://doi.org/10.1093/imaman/dpad023

This research empirically identifies the best-performing forecasting methods for the Effective Reproduction Number Rt of COVID-19, the most used epidemiological parameter for policymaking during the pandemic. Furthermore, based on the most accurate f... Read More about Forecasting the Effective Reproduction Number during a Pandemic: COVID-19 Rt forecasts, Governmental Decisions, and Economic Implications.

Intermittent demand, inventory obsolescence, and temporal aggregation forecasts (2023)
Journal Article
Sanguri, K., Patra, S., Nikolopoulos, K., & Punia, S. (2023). Intermittent demand, inventory obsolescence, and temporal aggregation forecasts. International Journal of Production Research, https://doi.org/10.1080/00207543.2023.2199435

Forecasting for intermittent demand is considered a difficult task and becomes even more challenging in the presence of obsolescence. Traditionally the problem has been dealt with modifications in the conventional parametric methods such as Croston.... Read More about Intermittent demand, inventory obsolescence, and temporal aggregation forecasts.

Social Collateral and consumer payment media during the economic crisis in Europe (2023)
Journal Article
Litsioua, K., & Nikolopoulos, K. (in press). Social Collateral and consumer payment media during the economic crisis in Europe. Journal of Quantitative Finance and Economics,

In this research paper we investigate the relationship between economic crises and the changes in levels of social collateral, as well as the indirect changes in the use of payment media from consumers as a result of the latter. The scene is Europe i... Read More about Social Collateral and consumer payment media during the economic crisis in Europe.

Insights into accuracy of social scientists' forecasts of societal change (2023)
Journal Article
Grossmann, I., Rotella, A., Hutcherson, C. A., Sharpinskyi, K., Varnum, M. E., Achter, S., …Collaborative, T. F. (2023). Insights into accuracy of social scientists' forecasts of societal change. Nature Human Behaviour, 7(4), 484-501. https://doi.org/10.1038/s41562-022-01517-1

How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing accuracy of predictions of societal change in domains commonly studied in the... Read More about Insights into accuracy of social scientists' forecasts of societal change.

The EU project RAMONES – continuous, long-term autonomous monitoring of underwater radioactivity (2022)
Book Chapter
Nikolopoulos, K. (2022). The EU project RAMONES – continuous, long-term autonomous monitoring of underwater radioactivity. In P. Batista, D. Cabecinhas, L. Sebastião, A. Pascoal, T. Mertzimekis, K. Kebkal, …L. Maigne (Eds.), . Hydrographic Institute

While radioactivity has always existed in the marine environment due to natural phenomena, artificial sources have made their way into the oceans more recently, either through low-level liquid discharges from reprocessing plants, more threatening lar... Read More about The EU project RAMONES – continuous, long-term autonomous monitoring of underwater radioactivity.

Fathoming empirical forecasting competitions’ winners (2022)
Journal Article
Alroomi, A., Karamatzanis, G., Nikolopoulos, K., Tilba, A., & Xiao, S. (2022). Fathoming empirical forecasting competitions’ winners. International Journal of Forecasting, 38(4), 1519-1525. https://doi.org/10.1016/j.ijforecast.2022.03.010

The M5 forecasting competition has provided strong empirical evidence that machine learning methods can outperform statistical methods: in essence, complex methods can be more accurate than simple ones. This result, be as it may, challenges the flags... Read More about Fathoming empirical forecasting competitions’ winners.

RAMONES and Environmental Intelligence: Progress Update (2022)
Book Chapter
Mertzimekis, T., Lagaki, V., Madesis, I., Siltzovalis, G., Petra, E., Nomikou, P., …Maigne, L. (2022). RAMONES and Environmental Intelligence: Progress Update. In GoodIT '22: Proceedings of the 2022 ACM Conference on Information Technology for Social Good (244-249). ACM. https://doi.org/10.1145/3524458.3547255

RAMONES is an EU H2020 FET Proactive Project which aims to offer a new fleet of instruments to perform continuous and in situ measurements of natural and artificial radioactivity in the marine environment as part of its main objectives. Those instrum... Read More about RAMONES and Environmental Intelligence: Progress Update.

Statistical, Machine Learning and Deep Learning forecasting methods: Comparisons and ways forward (2022)
Journal Article
Makridakis, S., Spiliotis, E., Assimakopoulos, V., Semenoglou, A., Mulder, G., & Nikolopoulos, K. (2023). Statistical, Machine Learning and Deep Learning forecasting methods: Comparisons and ways forward. Journal of the Operational Research Society, 74(3), 840-859. https://doi.org/10.1080/01605682.2022.2118629

The purpose of this paper is to test empirically the value currently added by Deep Learning (DL) approaches in time series forecasting by comparing the accuracy of some state-of-the- art DL methods with that of popular Machine Learning (ML) and stati... Read More about Statistical, Machine Learning and Deep Learning forecasting methods: Comparisons and ways forward.