Big data, oriented-organizational culture, and business performance: A socio-technical approach

Knowledge Management (KM) implementation is as much a challenge as it is a great opportunity for businesses worldwide in several sectors. The controversy over its worthwhile application persists among practitioners and scholars, with claims having arisen that business opportunities and performance are enhanced through KM adoption. Conversely, challenges regarding effective implementation of KM concerning individuals’ behaviors, beliefs, and practices prompt significant questioning regarding its complex basis: individual-technology-process-production. The purpose of this work is to shed light on some perspectives for the effective adoption of knowledge management technology, the consolidation of a favorable and aligned organizational culture, and patterns of use and retrieval of information in organizations. This study brings into focus the concept of knowledge management and technology, and culture in the organization through a systematic literature review and based on the researcher’s hypothesis and observations that successful KM implementation results from a clear understanding of its multidisciplinary, complex, and multifaceted process, which requires a methodical and strategic business practice concerning the application of technological tools, the establishment of a learning culture through shared vision of business’ and individuals’ needs, and consequential enhancement of processes and solutions. It concludes that investment in KM practice and the consolidation of a learning culture are correlated, reflecting a type of leadership that is favorable to the flow of information, generation, and sharing of knowledge (the intellectual capital) and optimization of decision making and business performance.

Regardless of the nature, size, or business sector, organizations are now collecting burgeoning various volumes of data in different formats. As much as voluminous data are necessary for organizations to draw good insights needed for making informed decisions, traditional architectures and existing infrastructures are limited in delivering fast analytical processing needed for these Big Data. For success organizations need to apply technologies and methods that could empower them to cost effectively analyze these Big Data. However, many organizations in developing countries are constrained with limited access to technology, finances, infrastructure and skilled manpower. Yet, for productive use of these technologies and methods needed for Big Data analytics, both the organizations and their workforce need to be prepared. The major objective for this study was to investigate developing countries organizations’ readiness for Big Data analytics. Data for the study were collected from a public sector in South Africa and analyzed quantitatively. Results indicated that scalability, ICT infrastructure, top management support, organization size, financial resources, culture, employees’ e-skills, organization’s customers’ and vendors are significant factors for organizations’ readiness for Big Data analytics. Likewise strategies, security and competitive pressure were found not to be significant. This study contributes to the scanty literature of Big Data analytics by providing empirical evidence of the factors that need attention when organizations are preparing for Big Data analytics.

Retracted on the 15th of October, 2020 by the Journal’s Editor-in-Chief request dated October 12, 2020. The type of retraction – plagiarism.
The journal was asked to retract this article because of plagiarism. The request came from the author of the article. The author informed the journal that original idea published in this paper wasn’t his and asked to remove the article.