Unveiling the effects of big data analytics capability on innovation capability through absorptive capacity: why more and better insights matter. Issue 2 (31st January 2023)
- Record Type:
- Journal Article
- Title:
- Unveiling the effects of big data analytics capability on innovation capability through absorptive capacity: why more and better insights matter. Issue 2 (31st January 2023)
- Main Title:
- Unveiling the effects of big data analytics capability on innovation capability through absorptive capacity: why more and better insights matter
- Authors:
- Lozada, Nelson
Arias-Pérez, José
Henao-García, Edwin Alexander - Abstract:
- Abstract : Purpose: Despite the increase in studies focused on analyzing the potential of big data analytics capability (BDAC) as a driver of product and process innovation, it is still necessary to understand how the use of insights generated by BDAC in innovation may be maximized through articulation with individuals' intellect and other processes involving the assimilation and transformation of knowledge. This study thus aims to analyze the impact of BDAC's deployment on innovation capability (IC – process and product innovation capabilities), taking absorptive capacity (AC) as mediating variable in this relationship. Design/methodology/approach: Structural equations were used to test the research model with survey data from 112 firms located in an emerging country that is one of the digital transformation leaders in the region. Findings: The results show that 37% of process IC variance is explained by the indirect relationship via the variable mediator (AC), while in the case of product IC this percentage is 34%. Originality/value: These results allow us to ascertain the extent to which individuals continue to be relevant to generating product and process innovation in the digital age at a time when the literature anticipates a total loss of prominence due to the arrival of new digital technologies. However, in the case of the relationship between BDAC and ICs, the existence of a partial mediation of AC indicates that individuals continue to play a role that, albeit notAbstract : Purpose: Despite the increase in studies focused on analyzing the potential of big data analytics capability (BDAC) as a driver of product and process innovation, it is still necessary to understand how the use of insights generated by BDAC in innovation may be maximized through articulation with individuals' intellect and other processes involving the assimilation and transformation of knowledge. This study thus aims to analyze the impact of BDAC's deployment on innovation capability (IC – process and product innovation capabilities), taking absorptive capacity (AC) as mediating variable in this relationship. Design/methodology/approach: Structural equations were used to test the research model with survey data from 112 firms located in an emerging country that is one of the digital transformation leaders in the region. Findings: The results show that 37% of process IC variance is explained by the indirect relationship via the variable mediator (AC), while in the case of product IC this percentage is 34%. Originality/value: These results allow us to ascertain the extent to which individuals continue to be relevant to generating product and process innovation in the digital age at a time when the literature anticipates a total loss of prominence due to the arrival of new digital technologies. However, in the case of the relationship between BDAC and ICs, the existence of a partial mediation of AC indicates that individuals continue to play a role that, albeit not being the most prominent, remains relevant in ensuring that a company maximizes the assimilation and transformation of the insights generated by BDAC in new products and processes. … (more)
- Is Part Of:
- Journal of enterprise information management. Volume 36:Issue 2(2023)
- Journal:
- Journal of enterprise information management
- Issue:
- Volume 36:Issue 2(2023)
- Issue Display:
- Volume 36, Issue 2 (2023)
- Year:
- 2023
- Volume:
- 36
- Issue:
- 2
- Issue Sort Value:
- 2023-0036-0002-0000
- Page Start:
- 680
- Page End:
- 701
- Publication Date:
- 2023-01-31
- Subjects:
- Big data analytics capability -- Absorptive capacity -- Innovation capability -- Product innovation -- Process innovation -- Digital transformation
Management information systems -- Periodicals
Business logistics -- Periodicals
Business -- Data processing -- Periodicals
Management -- Data processing -- Periodicals
658.05 - Journal URLs:
- http://info.emeraldinsight.com/products/journals/journals.htm?id=jeim ↗
http://www.emeraldinsight.com/ ↗ - DOI:
- 10.1108/JEIM-02-2021-0092 ↗
- Languages:
- English
- ISSNs:
- 1741-0398
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4979.291700
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 26093.xml