Forecasting the Innovation Efficiency of Oil and Gas Industry: remarks about the future in 2030
DOI:
https://doi.org/10.20397/2177-6652/2024.v24i4.2828Palavras-chave:
Previsão;, Análise envoltória de dados, Análise de dados em painel, Petróleo e gás; Estudos do futuro.Resumo
ABSTRACT
Purpose: This paper predictively analyzes the efficiency of oil and gas operators in their innovation process for the year 2030.
Design/methodology/approach: The research design combined two steps, data envelopment analysis (DEA) and panel data analysis, to forecast innovation efficiency by the year 2030. The data envelopment analysis (DEA) method was used to measure efficiency and its evolution. The input was the amount of investment in research and development, and the outputs were net sales and the number of patents. Panel data analysis was used to predict efficiency.
Originality/relevance: Some contributions and innovation efficiency for organizations were identified. This study provides theoretical and managerial implications for future oil and gas industry studies.
Findings: Regarding forecasts, net revenues once again stood out as the primary predictor. On average, efficiency in 2030 will rise from 0.66 (average efficiency between 09-20) to 0.85, with wide heterogeneity when observing the individual behavior of firms.
Theoretical/ /methodological contributions: The future of the O&G industry has become the ground for research with various methods to study the finite life of this resource, global climate change, the prospect of low-carbon economies, and the transition of energy to renewable sources.
Social and management implications: These future identifications can be used in organizations' strategic planning to improve their respective performance based on what firms considered the most efficient have accomplished.
Keywords: Forecasting; Data envelopment analysis; Panel data analysis; Oil & gas; Future studies.
RESUMO
Objetivo: Este artigo analisa de forma preditiva a eficiência dos operadores de petróleo e gás no seu processo de inovação para o ano de 2030.
Metodologia/abordagem: A pesquisa combinou duas etapas, análise envoltória de dados (DEA) e análise de dados em painel, para prever a eficiência da inovação até o ano 2030. O método de análise envoltória de dados (DEA) foi utilizado para medir a eficiência e sua evolução. O insumo foi o montante do investimento em pesquisa e desenvolvimento, e os resultados foram as vendas líquidas e o número de patentes. A análise de dados em painel foi utilizada para prever a eficiência.
Originalidade/relevância: Foram identificadas algumas contribuições e eficiência da inovação para as organizações. Este estudo fornece implicações teóricas e gerenciais para futuros estudos da indústria de petróleo e gás.
Resultados: Em relação às previsões, a receita líquida mais uma vez se destacou como principal preditor. Em média, a eficiência em 2030 passará de 0,66 (eficiência média entre 09-20) para 0,85, com grande heterogeneidade quando se observa o comportamento individual das empresas.
Contribuições teóricas/metodológicas: O futuro da indústria de petróleo e gás tornou-se o terreno para pesquisas com vários métodos para estudar a vida finita deste recurso, as alterações climáticas globais, a perspectiva de economias de baixo carbono e a transição da energia para fontes renováveis.
Contribuições sociais e para gestão: Essas identificações futuras podem ser utilizadas no planejamento estratégico das organizações para melhorar seu respectivo desempenho com base no que as empresas consideradas mais eficientes realizaram.
Palavras-chave: Previsão; Análise envoltória de dados; Análise de dados em painel; Petróleo e gás; Estudos do futuro.
RESUMEN
Objetivo: Este artículo analiza de forma predictiva la eficiencia de los operadores de petróleo y gas en su proceso de innovación para el año 2030.
Metodología/enfoque: La investigación combinó dos pasos, análisis envolvente de datos (DEA) y análisis de datos de panel, para predecir la eficiencia de la innovación hasta el año 2030. Se utilizó el método de análisis envolvente de datos (DEA) para medir la eficiencia y su evolución. El insumo fue el monto de inversión en investigación y desarrollo, y los resultados fueron las ventas netas y el número de patentes. Se utilizó análisis de datos de panel para predecir la eficiencia.
Originalidad/relevancia: Se identificaron algunos aportes y eficiencia de la innovación para las organizaciones. Este estudio proporciona implicaciones teóricas y de gestión para futuros estudios de la industria del petróleo y el gas..
Resultados: En cuanto a las previsiones, los ingresos netos volvieron a destacar como principal predictor. En promedio, la eficiencia en 2030 aumentará desde 0,66 (eficiencia promedio entre 09-20) a 0,85, con gran heterogeneidad al observar el comportamiento individual de las empresas.
Contribuiciones teóricas/metodológicas: El futuro de la industria del petróleo y el gas se ha convertido en terreno para la investigación con diversos métodos para estudiar la vida finita de este recurso, el cambio climático global, las perspectivas de economías bajas en carbono y la transición energética hacia fuentes renovables.
Contribuciones sociales y de gestión: Estas identificaciones futuras se pueden utilizar en la planificación estratégica de las organizaciones para mejorar su desempeño respectivo en función de lo que hayan logrado las empresas consideradas más eficientes.
Palabras clave: Previsión; Análisis Envolvente de Datos; Análisis de datos de paneles; Petroleo y Gas; Estudios futuros.
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