Institutional pressures on setting up big data analytics capability

Authors

  • Luciana Klein Universidade Federal do Paraná, Setor de Ciências Sociais Aplicadas, Departamento de Ciências Contábeis, Curitiba, PR, Brazil https://orcid.org/0000-0001-6815-1831
  • Ana Paula Sano Guilhem Universidade Federal do Paraná, Setor de Ciências Sociais Aplicadas, Departamento de Ciências Contábeis, Curitiba, PR, Brazil https://orcid.org/0000-0002-3892-9515
  • Henrique Adriano de Sousa 1 Universidade Federal do Paraná, Setor de Ciências Sociais Aplicadas, Departamento de Ciências Contábeis, Curitiba, PR, Brazil / 2 Universidade Paranaense, Departamento de Administração, Cascavel, PR, Brazil https://orcid.org/0000-0002-7740-3946
  • Everton Lucio Soares de Oliveira Independent researcher currently unaffiliated, São Manoel do Paraná, PR, Brazil https://orcid.org/0000-0003-3586-651X

DOI:

https://doi.org/10.1590/1808-057x20231591.en

Keywords:

institutional pressures, big data analysis, Resource-Based Theory, big data organizational resources, Industry 4.0

Abstract

This article aims to analyze the setting up of tangible resources and human big data skills, in the face of institutional pressures, in the big data analytics capability in Brazilian companies. Innovation influences the environment in which companies are inserted, increasing uncertainties, resulting in behavioral changes of social players. In response to individual efforts to rationally deal with uncertainties and constraints, organizational homogenization emerges. However, the institutional pressures that influence the setting up of specific resources are still not fully understood in the literature. The replication of the study by Dubey (2019b) is considered, seeing big data technology as an innovation that has caused changes in the social context, thus we seek to grasp the setting up of organizational big data resources in Brazilian companies to build BDA capability, due to institutional pressures. The study makes it possible to see how institutional pressures set up BDA capability, thus being able to provide means to investment allocation decisions in data technology or improve technical management skills in the business intelligence team. The study brought to light the environmental response, resulting from the technological innovation of big data, in Brazilian companies. This demonstrates that organizations adhering to big data technology select their resources in the face of various pressures, in order to build big data analytics capability. This research has a descriptive and quantitative nature, and its operationalization took place through a survey. The research population consists of Brazilian companies that use technology with a large volume of structured and/or unstructured data, to generate results and insights, which support decision making. The survey participants were employees of Brazilian companies that have positions related to building big data analytics capability, located through the LinkedIn platform. 136 valid responses were obtained. To test the hypotheses, the Structural Equation Modeling technique was used by means of the software Smartspls v. 3.2.3. This study contributes by bringing an understanding of organizational behavior in the face of institutional pressures (coercive, normative, and mimetic) when selecting tangible resources and human big data skills to build BDA capability, using Resource-Based Theory. It is observed that the setting up of BDA capability is influenced by tangible resources and human skills. Tangible resources are selected due to formal pressures, competitive conditions, and by imitating existing standards in the market. Meanwhile, the required human skills are impacted, through legitimation and professional networks of decision makers.

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Published

2023-10-09

Issue

Section

Original Articles

How to Cite

Klein, L., Guilhem, A. P. S., Sousa, H. A. de, & Oliveira, E. L. S. de. (2023). Institutional pressures on setting up big data analytics capability. Revista Contabilidade & Finanças, 34(92), e1591. https://doi.org/10.1590/1808-057x20231591.en