Exploring data-driven innovation: What’s missing in the relationship between big data analytics capabilities and supply chain innovation?

Sabeen Hussain Bhatti (), Wan Mohd Hirwani Wan Hussain (), Jabran Khan (), Shahbaz Sultan () and Alberto Ferraris ()
Additional contact information
Sabeen Hussain Bhatti: Bahria University Islamabad
Wan Mohd Hirwani Wan Hussain: Universiti Kebangsaan Malaysia
Jabran Khan: Bahria University Islamabad
Shahbaz Sultan: Putra Business School
Alberto Ferraris: University of Torino

Annals of Operations Research, 2024, vol. 333, issue 2, No 12, 799-824

Abstract: Abstract Data-driven innovations (DDI) have significantly impacted firms’ operations thanks to the massive exploitation of huge data. However, to leverage big data and achieve supply chain innovation, a variety of complementary resources are necessary. In this study, we hypothesise that supply chain innovation (SCI) is dependent on firms’ big data analytics capabilities (BAC). Furthermore, we propose that this relation is mediated by two crucial capabilities of agility and adaptability that enable firms to efficiently meet the challenges of supply chain ambidexterity. Finally, we also test the moderating role of technology uncertainty in our research model. We collected data from 386 manufacturing firms in Pakistan and tested our model using structural equation modelling. The results confirmed our initial hypotheses that agility and adaptability both mediated our baseline relationship of BAC and big data innovation in supply chains. We further found support for the moderating role of technology uncertainty. Furthermore, technology uncertainty moderates the relationship between BAC and SCI. This study extends the current literature on digital analytics capabilities and innovation along the supply chain. Practically, our research suggests that investment in big data can result in affirmative consequences, if firms cultivate capabilities to encounter supply chain ambidexterity through agility and adaptability. Accordingly, we suggest that managers belonging to manufacturing firms need to build up these internal capabilities and to monitor and assess technology uncertainty in the environment.

Keywords: Big data analytics capabilities (BAC); Supply chain agility (SAG); Supply chain adaptability (SAD); Technology uncertainty (TUC); Supply chain innovation (SCI) (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10479-022-04772-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:333:y:2024:i:2:d:10.1007_s10479-022-04772-7

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-022-04772-7

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().