Exploiting organizations' innovation performance via big data analytics: an absorptive knowledge perspective
Exploiting organizations' innovation performance via big data analytics: an absorptive knowledge perspective
Purpose: the advantages of applying big data analytics for organizations to boost innovation performance are enormous. By collecting and analysing substantial amounts of data, firms can discern what works for their customer needs and update existing products while innovating new ones. Notwithstanding the evidence about the effects of big data analytics, the link between big data analytics and innovation performance is still underestimated. Especially in today's fast-changing and complicated environments, companies cannot simply take big data analytics as one innovative technical tool without fully understanding how to deploy it effectively.
Design/methodology/approach: this study tries to investigate this relationship by building on the knowledge absorptive capacity perspective. The authors conceptualized effective use of big data analytics tools as one general absorptive capacity rather than a simple technical element or skill. Specifically, effectively utilize big data analytics tools can provide values and insights for new product innovation performance in a turbulent environment. Using online survey data from 108 managers, the authors assessed their hypotheses by applying the structural equation modelling method.
Findings: the authors found that big data analytics capacity, which can be conceptualized as one absorptive capacity, can positively influence product innovation performance. The authors also found that environmental turbulence has strong moderation effects on these two main relationships.
Originality/value: these results establish big data analytics can be regarded as one absorptive capacity, which can positively boost an organization's innovation performance.
Big data analytics, Environmental turbulence, Knowledge absorptive capacity, Product innovation
Tseng, H.T.
3b3c3750-e297-4d18-9b05-03d5c76e481a
Jia, S.
626716a5-f0ea-4c87-8ef2-9ebb6067f6e5
Nisar, T.M.
6b1513b5-23d1-4151-8dd2-9f6eaa6ea3a6
Hajli, N.
380952fd-67ae-4798-bc7a-f80d6c8c84c5
Tseng, H.T.
3b3c3750-e297-4d18-9b05-03d5c76e481a
Jia, S.
626716a5-f0ea-4c87-8ef2-9ebb6067f6e5
Nisar, T.M.
6b1513b5-23d1-4151-8dd2-9f6eaa6ea3a6
Hajli, N.
380952fd-67ae-4798-bc7a-f80d6c8c84c5
Tseng, H.T., Jia, S., Nisar, T.M. and Hajli, N.
(2023)
Exploiting organizations' innovation performance via big data analytics: an absorptive knowledge perspective.
Information Technology & People.
(doi:10.1108/ITP-03-2022-0237).
Abstract
Purpose: the advantages of applying big data analytics for organizations to boost innovation performance are enormous. By collecting and analysing substantial amounts of data, firms can discern what works for their customer needs and update existing products while innovating new ones. Notwithstanding the evidence about the effects of big data analytics, the link between big data analytics and innovation performance is still underestimated. Especially in today's fast-changing and complicated environments, companies cannot simply take big data analytics as one innovative technical tool without fully understanding how to deploy it effectively.
Design/methodology/approach: this study tries to investigate this relationship by building on the knowledge absorptive capacity perspective. The authors conceptualized effective use of big data analytics tools as one general absorptive capacity rather than a simple technical element or skill. Specifically, effectively utilize big data analytics tools can provide values and insights for new product innovation performance in a turbulent environment. Using online survey data from 108 managers, the authors assessed their hypotheses by applying the structural equation modelling method.
Findings: the authors found that big data analytics capacity, which can be conceptualized as one absorptive capacity, can positively influence product innovation performance. The authors also found that environmental turbulence has strong moderation effects on these two main relationships.
Originality/value: these results establish big data analytics can be regarded as one absorptive capacity, which can positively boost an organization's innovation performance.
Text
ITP-03-2022-0237.R2_Proof_hi
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Accepted/In Press date: 6 August 2023
e-pub ahead of print date: 4 September 2023
Additional Information:
Publisher Copyright:
© 2023, Emerald Publishing Limited.
Keywords:
Big data analytics, Environmental turbulence, Knowledge absorptive capacity, Product innovation
Identifiers
Local EPrints ID: 482294
URI: http://eprints.soton.ac.uk/id/eprint/482294
ISSN: 1758-5813
PURE UUID: 69600085-e77d-4beb-86cc-8e4fe63ef9e1
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Date deposited: 26 Sep 2023 16:36
Last modified: 18 Mar 2024 02:53
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Contributors
Author:
H.T. Tseng
Author:
S. Jia
Author:
N. Hajli
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