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Accounting earnings and economic growth, trends, and challenges: a bibliometric approach

dc.contributor.authorSun, Mu
dc.contributor.authorUrquía Grande, María Elena
dc.contributor.authorChamizo-González, Julián
dc.contributor.authorDel Campo Campos, Cristina
dc.date.accessioned2024-04-11T06:49:35Z
dc.date.available2024-04-11T06:49:35Z
dc.date.issued2022-08-10
dc.description.abstractIn recent years, studies have been conducted to quantify the relationship between microeconomic and macroeconomic development. Macroeconomics is the orientation of microeconomic development. Existing research hopes to quantify the relationship between macroeconomics and micro-firms, rather than just focusing on economic indicators. And some empirical studies try to use the relationship between them to discuss its usefulness for micro-firm decision-making. This article focuses on applying and developing aggregate earnings in connecting microenterprise earnings and macroeconomic development. To achieve this goal, this research did a comprehensive bibliometric analysis on macro-accounting on the two most influential databases, namely, Web of Science and Scopus. It used the information visualization software VOSviewer to draw knowledge maps to sort research lines. We also analyzed the research hotspots of macro-accounting in recent years according to the year scale and combined it with the neural network PSO-LSTM model to predict their future development. It turns out that the research on aggregate earnings related to economic growth has become a research hotspot in recent years. Scopus research and development potential is better than Web of Science in this field.
dc.description.departmentDepto. de Economía Financiera y Actuarial y Estadística
dc.description.departmentDepto. de Administración Financiera y Contabilidad
dc.description.facultyFac. de Ciencias Económicas y Empresariales
dc.description.refereedTRUE
dc.description.statuspub
dc.identifier.citationSun, M., Urquía-Grande, E., Chamizo-González, J., & del Campo, C. (2022). Accounting earnings and economic growth, trends, and challenges: a bibliometric approach. Computational Intelligence and Neuroscience, 2022, 7352160.
dc.identifier.doi10.1155/2022/7352160
dc.identifier.essn1687-5273
dc.identifier.issn1687-5265
dc.identifier.officialurlhttps://www.hindawi.com/journals/cin/2022/7352160/
dc.identifier.urihttps://hdl.handle.net/20.500.14352/102976
dc.journal.titleComputational Intelligence and Neuroscience
dc.language.isoeng
dc.page.initial7352160
dc.publisherHindaw
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.ucmContabilidad (Economía)
dc.subject.ucmBibliometría
dc.subject.unesco5303 Contabilidad Económica
dc.titleAccounting earnings and economic growth, trends, and challenges: a bibliometric approach
dc.typejournal article
dc.type.hasVersionVoR
dc.volume.number2022
dspace.entity.typePublication
relation.isAuthorOfPublication6dab246f-23d5-4793-b89c-fb43c168ff43
relation.isAuthorOfPublication6c714f02-4316-4960-ac6a-4cbbf3e7f233
relation.isAuthorOfPublication.latestForDiscovery6dab246f-23d5-4793-b89c-fb43c168ff43

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