41st International Conference on Mathematical Methods in Economics
September 13–15, 2023, Prague, Czech Republic

Participation

The conference will be held in person only. Participation is possible in three variants:

• Passive participation (as a co-author or without a contribution)
• Active participation with submitted abstract and on-site presentation
• Active participation with submitted abstract, submited full paper, and on-site presentation

All participants are required to register and pay the conference fee, which is the same for all three variants.

PhD Competition

Czech Society for Operations Research organizes a competition for the best paper authored by PhD students presented on the conference Mathematical Methods in Economics 2023. All participants enrolled in PhD studies can participate in the competition. All papers will be peer-reviewed and the papers with positive referee reports will be further evaluated by the conference Programme Committee.

Only papers authored by a PhD student or a collective of PhD students are eligible for the PhD students competition. Papers authored or co-authored by a person that is not a PhD student will be disqualified from the competition and regarded as regular conference paper submissions.

First prize	Czech Society for Operations Research Award and 10 000 CZK
Second prize	5 000 CZK
Third prize	3 000 CZK
Fourth, fifth, sixth prize	1 000 CZK

The winners will be announced at the ceremony on September 14 during the conference dinner.

Important Dates

February 15	Submission opening
April 17	Abstract submission deadline
April 30	Notification of abstract acceptance
May 15	Registration opening
May 22	Full paper submission deadline
June 19	Notification of full paper acceptance
July 15	Registration and payment deadline
September 13–15	Conference

Conference Fees

Regular fee: 7 500 CZK / 330 EUR

Fee for Ph.D. students: 4 500 CZK / 200 EUR (The participant should send a scanned copy of their valid confirmation of study to mme2023@vse.cz before the payment to be entitled as students' fee)

The conference fee covers:

• Publishing one abstract as a first author in the Book of Abstracts
• Publishing one full paper (which extends the abstract) as a first author in the Conference Proceedings after a successful review
• Presenting the abstract/full paper at the conference
• Access to all conference sessions and keynote speeches
• Conference materials
• Refreshments (two dinners, three lunches, and coffee breaks)
• Traditional social programme

The accommodation and transport is not included in the registration fee. Participants should make accommodation reservations individually, directly to the selected hostel/hotel. Participants have to arrange visa at their own.

The fee must be paid at registration, which is opened from May 15 to July 15.

Previous Conferences

• MME 2022 (7. 9. 2022 – 9. 9. 2022, Jihlava)
• MME 2021 (8. 9. 2021 – 10. 9. 2021, Prague)
• MME 2020 (9. 9. 2020 – 11. 9. 2020, Brno)
• MME 2019 (11. 9. 2019 – 13. 9. 2019, České Budějovice)
• MME 2018 (12. 9. 2018 – 14. 9. 2018, Jindřichův Hradec)
• MME 2017 (13. 9. 2017 – 15. 9. 2017, Hradec Králové)

Professor Dimitris K. Despotis, Ph.D.

Network Data Envelopment Analysis: The Prevalent Methodological Approaches and Some Recent Developments

Network data envelopment analysis (NDEA) is an extension of standard data envelopment analysis (DEA) that models the efficiency assessment of DMUs by considering their internal structure. While in standard DEA the DMU is regarded as a single process, in NDEA the DMU is viewed as a network of interconnected sub-processes (stages, divisions), where the flow of the intermediate products (measures) is essential in the efficiency assessment. In the prevalent conventional methodological approaches to NDEA, the sub-processes are assumed as distinct entities with distinct inputs and outputs. Thus, each sub-process has its own production possibility set (PPS), which can be derived axiomatically from a set of assumptions using the minimum extrapolation principle. The PPS of the overall system is defined as the composition of the individual PPSs. We outline in this presentation the basic NDEA methods established in the literature, and we discuss their limitations, merits, and drawbacks.

doc. RNDr. Ing. Miloš Kopa, Ph.D.

Decision Making in Finance via Stochastic Dominance

Stochastic dominance is a statistical tool developed for comparing the random variables among each other. In financial applications, these random variables represents random returns of the considered assets or portfolios. The paper focuses on portfolio selection problems with stochastic dominance constraints for various orders of stochastic dominance relations. Firstly, the tractable necessary and sufficient conditions for particular probability distributions are discussed. Secondly, these conditions are employed in the portfolio selection problems. Finally, the extensions for the case of endogenous randomness are presented. The theoretical results are accompanied by numerical examples.