Big Data Adoption, Information Security Enforcement and Decision-Making Efficiency

Autores/as

  • Yi Chen School of public administration Beihang University Beijing, 100191, China
  • Wei Shan School of Marxism Beihang University Beijing, 100191, China

DOI:

https://doi.org/10.3145/epi.2024.ene.0519

Palabras clave:

Information Security Enforcement, Big Data Adoption, Decision-Making Efficiency.

Resumen

Information security enforcement aims to reflect the organizational practices while ensuring the confidentiality and availability of the relevant information within the organization. Such acts also help make some strategic and efficient decision-making at different levels of the organization. Moreover, by using big data technologies, organizations make decisions more efficiently by allowing them to process and analyze large amounts of information quickly. This study focused on several indicators relating to information security enforcement, big data adoption, and decision-making efficiency by collecting data from eight industries in China. The study developed a concise questionnaire using the Five point Likert scale, for which descriptive and regression analysis were applied. The study results show a significant relationship between information security enforcement, big data adoption and decision-making efficiency. Additionally, the study results revealed the reliability and monitoring of such initiatives like whistleblowing programs, disciplinary employees for security violations, quick investigations, and accountability for infractions, as key indicators of information security enforcement, which also cause an improvement in the decision-making efficiency of the targeted industries. The results further suggest policy implications and recommendations to improve decision-making using information security enforcement and extensive data adoption. A few limitations also discuss the future directions.

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Publicado

2024-12-17

Cómo citar

Yi Chen, & Wei Shan. (2024). Big Data Adoption, Information Security Enforcement and Decision-Making Efficiency . Profesional De La información, 33(5). https://doi.org/10.3145/epi.2024.ene.0519

Número

Sección

Artí­culos de investigación / Research articles