@article{MTMT:34037156,
	title = {A FUZZY GROUP DECISION-MAKING MODEL FOR MEASUREMENT OF COMPANIES' PERFORMANCE},
	url = {https://m2.mtmt.hu/api/publication/34037156},
	author = {Martina, PAVLAČKOVÁ and Ondřej, PAVLAČKA and Tereza, HORČIČKOVÁ},
	journal-iso = {ECON COMPUT ECON CYB},
	journal = {ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH},
	volume = {2},
	unique-id = {34037156},
	issn = {0424-267X},
	year = {2023},
	eissn = {1842-3264},
	pages = {119-134}
}

@article{MTMT:34666541,
	title = {FACTORS INFLUENCING THE PERCEPTION OF ACADEMIC RESEARCHERS ON ETHICS IN MARKETING RESEARCH AND ITS IMPACT ON OPEN SCIENCE ACCEPTANCE},
	url = {https://m2.mtmt.hu/api/publication/34666541},
	author = {Constatinescu, Mihaela and Florescu, Margareta Stela and Caescu, Stefan-Claudiu and Acatrinei, Carmen and Orindaru, Andree and Ciuca, Andrei Relu},
	journal-iso = {ECON COMPUT ECON CYB},
	journal = {ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH},
	volume = {57},
	unique-id = {34666541},
	issn = {0424-267X},
	keywords = {Survey; ETHICS; Marketing; open science; academic research},
	year = {2023},
	eissn = {1842-3264},
	pages = {57-74}
}

@article{MTMT:34650076,
	title = {THE INTERPLAY BETWEEN NATURAL GAS CONSUMPTION, OIL CONSUMPTION, AND ECONOMIC GROWTH: AN EMPIRICAL EVIDENCE},
	url = {https://m2.mtmt.hu/api/publication/34650076},
	author = {Grigore, George-Eduard and Musetescu, Radu-Cristian and Nicolae, Simona and Vladut, Oana and Ionescu, Adriana-Mihaela},
	journal-iso = {ECON COMPUT ECON CYB},
	journal = {ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH},
	volume = {57},
	unique-id = {34650076},
	issn = {0424-267X},
	keywords = {energy consumption; economic growth; Energy security; Feedback hypothesis; causality relationships; cointegration tests; Caspian countries},
	year = {2023},
	eissn = {1842-3264}
}

@article{MTMT:34153500,
	title = {Inflation and Main Determining Factors in Non-Euro CEE Countries during the Period 2020-2022. An Empirical Analysis},
	url = {https://m2.mtmt.hu/api/publication/34153500},
	author = {Dumitru, MIRON and Ion, PANESCU},
	doi = {10.24818/18423264/57.3.23.14},
	journal-iso = {ECON COMPUT ECON CYB},
	journal = {ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH},
	volume = {57},
	unique-id = {34153500},
	issn = {0424-267X},
	year = {2023},
	eissn = {1842-3264},
	pages = {235-250}
}

@article{MTMT:34181133,
	title = {CLUSTER HEAD SELECTION ALGORITHM ON THE BASIS OF MASS DEFENSE OF BEES IN IOT},
	url = {https://m2.mtmt.hu/api/publication/34181133},
	author = {Chanpa, R. and Jamali, M.A.J. and Hatamlou, A. and Anari, B.},
	doi = {10.24818/18423264/57.3.23.11},
	journal-iso = {ECON COMPUT ECON CYB},
	journal = {ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH},
	volume = {57},
	unique-id = {34181133},
	issn = {0424-267X},
	abstract = {Clustering is one of the methods which bring about efficiency boost, energy reduction, and longevity in Internet of Things (IoT). One of the key challenges in IoT clustering is optimal cluster head selection. Unintelligent selection and improper distribution of cluster head selection are critical problems rooted in the random nature of classical methods. Thereupon, meta-heuristic methods are used to solve such problems. The present study presents a new clustering method as well as an optimal cluster head selection applying the Mass Defense of Bees algorithm. This method simulates honey bees’ behaviour in fighting against the red bee invader, defending a hive, detecting the invader, resistance against the invader and displaying coordination performance. The proposed method achieves the optimal head selection through fitness function introduction. Compared to PSO and leach methods, the proposed simulation method demonstrates the IoT network clustering, around 9.45% energy improvement and 13.2% residual energy development, respectively. © 2023, Bucharest University of Economic Studies. All rights reserved.},
	keywords = {IoT; Cluster head; Mass Defense of Bees Algorithm; Reduction of Network Energy Consumption},
	year = {2023},
	eissn = {1842-3264},
	pages = {187-202}
}

@article{MTMT:33954942,
	title = {HEDGING STRATEGIES OF SUPPLY CHAIN UNDER RISK AVERSION},
	url = {https://m2.mtmt.hu/api/publication/33954942},
	author = {Xu, Guangye and Weng, Xinlan and Dan, Bin and Duan, Huawei},
	doi = {10.24818/18423264/57.1.23.05},
	journal-iso = {ECON COMPUT ECON CYB},
	journal = {ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH},
	volume = {57},
	unique-id = {33954942},
	issn = {0424-267X},
	abstract = {This study investigates the effects of risk aversion factors and opportunity cost on the hedging decisions of supply chain members. We develop a two-stage model consisting of a risk-averse manufacturer and an equally risk -averse retailer. We consider four strategies from the perspective of the supply chain as a whole, where neither side hedges (NN), only the supplier hedges (HN), only the manufacturer hedges (NH), and both sides hedge (HH). Then, we applied the mean-variance model and solved and compared the four strategies using the inverse solving method. The results show that the hedging strategies among the supply chain members are consistent. When both parties have high-risk aversion and opportunity cost, both parties choose to hedge the risk; when both parties have a low-risk aversion, the party with lower opportunity cost should choose to hedge.},
	keywords = {risk aversion; Supply chain; hedging; Mean-variance},
	year = {2023},
	eissn = {1842-3264},
	pages = {73-88}
}

@article{MTMT:33789812,
	title = {IS CORPORATE ENVIRONMENTAL RESPONSIBILITY A MEANINGFUL FACTOR FOR ROMANIAN CONSUMERS?},
	url = {https://m2.mtmt.hu/api/publication/33789812},
	author = {Strat, V.A. and Grosu, F.S. and Murafa, C. and Chicu, N. and Zgura, I.D.},
	doi = {10.24818/18423264/56.4.22.04},
	journal-iso = {ECON COMPUT ECON CYB},
	journal = {ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH},
	volume = {56},
	unique-id = {33789812},
	issn = {0424-267X},
	abstract = {The article explores Romanian customers' perceptions and behavior regarding enterprises' involvement in sustainability-related processes and actions geared towards climate action. Based on the 2 hypotheses outlined by the authors, the study uses a hierarchical clustering methodology having a sample of 1002 consumer data points collected at the national level. The authors grouped Romanian counties into 5 clusters by addressing 4 dimensions and 11 individual items on socio-economic characteristics such as: Economic development, education and culture, health and infrastructure. The main results showed that companies are being perceived by citizens from all development clusters as bearing the highest responsibility for the wellbeing of the planet, yet their green messages have the highest appeal in clusters with higher general development levels. However, surprisingly, from a double materiality viewpoint, corporations' good influence on the environment and society appears to be rewarded the most by customers with relatively little socio-economic capital - the biggest number of consumers who use their wallets to reward corporate sustainability are the ones with low socioeconomic development. © 2022, Bucharest University of Economic Studies. All rights reserved.},
	keywords = {sustainability; Environment; customer behavior; green deal; Eco-friendly consumers},
	year = {2022},
	eissn = {1842-3264},
	pages = {55-70}
}

@article{MTMT:33253496,
	title = {A Novel Model for Stock Closing Price Prediction Using CNN-Attention-GRU-Attention},
	url = {https://m2.mtmt.hu/api/publication/33253496},
	author = {WENJIE, LU and JIAZHENG, LI and JINGYANG, WANG and SHAOWEN, WU},
	doi = {10.24818/18423264/56.3.22.16},
	journal-iso = {ECON COMPUT ECON CYB},
	journal = {ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH},
	volume = {56},
	unique-id = {33253496},
	issn = {0424-267X},
	year = {2022},
	eissn = {1842-3264},
	pages = {251-264}
}

@article{MTMT:32978535,
	title = {BUSINESS FORMATION DURING THE CORONAVIRUS PANDEMIC. A REGIONAL ANALYSIS CONSIDERING KNOWLEDGE AND TECHNOLOGICAL INTENSITY},
	url = {https://m2.mtmt.hu/api/publication/32978535},
	author = {Popescu, Alina Irina},
	doi = {10.24818/18423264/55.4.21.13},
	journal-iso = {ECON COMPUT ECON CYB},
	journal = {ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH},
	volume = {55},
	unique-id = {32978535},
	issn = {0424-267X},
	abstract = {The topic of business formation is especially relevant today when humankind faces the biggest global crisis since World War II. The protection of jobs and workers is vital, and a plethora of measures have been implemented since the outburst of the coronavirus pandemic in 2020. Remote activity interactions, whether forced or voluntary, shaped the economic landscape, restructured organizations, and reallocated the workforce across industries. In such context, this study investigates the dynamics of business formation in Romania throughout the first year of the coronavirus pandemic. Business formation registered significant growth in the second half of 2020, surpassing the level of the previous year. The analysis is performed at regional level, for 42 administrative regions, considering the intensity of knowledge and technology levels of industries in which new business was formed, according to the Eurostat classification of industries. The score of Knowledge and Technology Intensity (KTIRS) is calculated at regional level. The clustering of regions resulted in 6 cluster templates, given the industrial structure of new business formation.},
	keywords = {Cluster Analysis; Entrepreneurship; Business formation; Regional analysis; Knowledge and Technology Intensity Score (KTIRS); Coronavirus pandemic (COVID-19)},
	year = {2021},
	eissn = {1842-3264},
	pages = {199-214}
}

@article{MTMT:33028767,
	title = {Evolution of right ventricular dysfunction markers in patients with intermediate-high risk pulmonary thromboembolism},
	url = {https://m2.mtmt.hu/api/publication/33028767},
	author = {Ion, A.C. and Busnatu, Ș. and Badiu, C.D. and Partas-Ciolan, R.-V. and Sinescu, C.J. and Andrei, C.L.},
	doi = {10.24818/18423264/55.3.21.20},
	journal-iso = {ECON COMPUT ECON CYB},
	journal = {ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH},
	volume = {55},
	unique-id = {33028767},
	issn = {0424-267X},
	year = {2021},
	eissn = {1842-3264},
	pages = {315-330}
}