Fuzzy cognitive model of agricultural economic growth

Anokhina, Marina Yegorovna

doi:10.1080/09535314.2022.2065466

Cited by 2 publications

(1 citation statement)

References 29 publications

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“…Economic growth is a long-term process of increasing per capita production. The higher a country's economic growth, the greater its ability to meet the demands of its people and, therefore, the greater its capacity to prosper its people (Anokhina, 2022). A prior study also noted that economic growth is recognized as expanding economic activity that increases the production of products and services in society (Widarni & Bawono, 2021).…”

Section: Introductionmentioning

confidence: 99%

Analysis of South Korea's Macroeconomic Development with the Vector Error Correction Model

Ahman,

Machmud,

Agus Triansyah

2023

JPEB

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This study examines the relationship between Gross Domestic Product (GDP), Import (IMP), Inflation (INF), and Unemployment (UNP) in South Korea using the panel vector error correction model (VECM), cointegration, and Granger. VECM is used to analyze the relationship or causality between variables involved in this research in the short and long run. From the estimation results, especially on the variables of interest, there is a positive and statistically significant relationship between Gross Domestic Product, Import, Inflation, and Unemployment, which refers more to short-term causality. Impulse Response Function analysis is used to determine the impact between variables where the results that had a positive effect during the Covid-19 pandemic were import shocks to GDP and unemployment shocks to GDP, while those that had a negative impact were inflation rate shocks to GDP in South Korea during the Covid-19 pandemic.

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Section: Introductionmentioning

confidence: 99%

Analysis of South Korea's Macroeconomic Development with the Vector Error Correction Model

Ahman,

Machmud,

Agus Triansyah

2023

JPEB

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Cognitive model of the ESG transformation of the organization

Anokhina¹,

Kolesnikov²,

Максимов³

2023

E3S Web Conf.

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A universal model of ESG (Environmental, Social, Governance) transformation is proposed as a basis for developing an organization’s ESG strategy. Fuzzy cognitive logic technologies were used as the instrumental base of the study. A fuzzy cognitive map (FCM) of the organization’s ESG transformation has been developed with a substantiation of a set of parameters (concepts) in the environmental, social and managerial spheres. Based on the static analysis of the fuzzy cognitive model (FCM) and the calculation of its system indicators, it was determined that the factors of the level of ESG-corporate culture, ESG-motivation and integration into the practice of corporate management methodology of strategic management have the greatest positive impact on the target concepts and on the process of ESG transformation as a system. The system experiences a significant negative impact from the factor of resistance to changes in the organization. Collectively, these factors are identified as the main control actions for the organization’s ESG transformation.

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Fuzzy cognitive model of agricultural economic growth

Cited by 2 publications

References 29 publications

Analysis of South Korea's Macroeconomic Development with the Vector Error Correction Model

Analysis of South Korea's Macroeconomic Development with the Vector Error Correction Model

Cognitive model of the ESG transformation of the organization

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