Data literacy and the cognitive challenges of a data-rich business environment: an analysis of perceived data overload, technostress and their relationship to individual performance

Abstract

PurposeConsidering the cognitive challenges associated with a data-rich business environment, this research aims to investigate the relationship between data literacy (DL), perceived data overload (PDO), and technostress (TS), besides the effect of these constructs on professional's individual performance (IP).Design/methodology/approachThrough survey research, the authors collected data from 321 professionals who work in data-rich and highly technological business environments. To test the hypotheses proposed, the authors developed the partial least squares structural equation modeling (PLS-SEM) procedures.FindingsThe results showed that DL is positively associated with IP and negatively with PDO. PDO is positively associated with TS and negatively with IP. The authors found no significant negative association between TS and IP.Research limitations/implicationsWith this research, the authors seek to contribute to the gap in the literature concerning two cognitive challenges associated with data-rich business environments: PDO and TS, analyzing from the point of view of the individual, and highlighting the importance of DL in this context.Practical implicationsThe results can assist managers in effectively being concerned with the DL level of their workforce. This is important considering not only the professionals' IP but also the cognitive challenges such as PDO and TS.Originality/valueThe innovation of this study lies in the empirical analysis of DL in the business context and its relationship with two cognitive challenges inherent in data-rich environments: PDO, and TS. Besides, the authors highlight the importance of understanding such phenomena in terms of IP.

Overcoming the “Dark Side” of Technology—A Scoping Review on Preventing and Coping with Work-Related Technostress

“…Moreover, in line with our results, a recent review by Virone et al has identified, inter alia, autonomy, time pressure, understanding of roles and attitude as relevant factors for coping with technostress among healthcare employees [ 121 ]. Other study results affirm our findings that a promotion focus [ 122 ] and data literacy [ 123 ] can reduce technostress creators.…”

The mediating effect of data literacy competence in the relationship between data governance and data-driven culture

“…The empirical evidence from this research supports the hypothesis that DL enables DDC (H3). These findings highlight the importance of skill factors in data processing, confirming that the use of DL contributes to the development of conceptualizations on improving cognitive abilities when dealing with BD (Giudice da Silva Cezar and Maçada, 2021; Maja and Letaba, 2022; Ongena, 2023; Prado and Marzal, 2013). Moreover, the culture further enhances DL's ability to foster data analysis maturity (Park and Cho, 2021).…”

Decision Making Performance of Business Data Analytical Capabilities: The Mediating Effect of Analytics Competency

“…The ability of an enterprise to effectively deploy data analytics-driven resources with a combination of other related resources and capabilities to make better, more informed, and faster decisions, and enable the ability to leverage all available information, thus becoming a highly capable capability and important for organizational success [21,48,56). Consequently, AC in the analytical ability to generate DMP, by making it more effective to interpret some of this data to convert it into business value [28,58,68].…”

“…Similarly, data originating outside the organization, such as public information from other regulators, grows exponentially. When determining the wiggle room for data utilization, organizations need to interpret some of this data to turn it into business value [28,58,68]. Thus, it highlights the importance of data and analytical skills for guiding and generating potential data, leading to improved decision-making performance (DMP) within the organization [8,11,69,70,71].…”