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E-Thesis 86 views

Big Data Analytics in Innovation Context / Abdullah Hamadi

Swansea University Author: Abdullah Hamadi

  • E-Thesis – open access under embargo until: 24th August 2025

DOI (Published version): 10.23889/SUthesis.60983

Abstract

The potential of big data analytics (BDA) in enabling improvements in business processes has urged researchers and practitioners to understand whether and under what combination of conditions, such novel technologies can support innovation, competitive advantage, and firm performance. Although the e...

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Published: Swansea 2022
Institution: Swansea University
Degree level: Doctoral
Degree name: Ph.D
Supervisor: Hajli, Nick ; Ibrahim, Fahad ; Mulyata, John
URI: https://cronfa.swan.ac.uk/Record/cronfa60983
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Abstract: The potential of big data analytics (BDA) in enabling improvements in business processes has urged researchers and practitioners to understand whether and under what combination of conditions, such novel technologies can support innovation, competitive advantage, and firm performance. Although the extent of research in this area is substantial, research on the influence of the BDA components such as effective use of big data analytics tools and big data management on innovation process (IP), competitive advantage (CA), and financial performance (FP) must be conducted. This research examines the impact of effective use of BDA tools and big data management on the innovation process, competitive advantage and financial performance based on the resource-based view (RBV). Based on this conceptualisation, the current study examines the relationship between the BDA components (effective use of BDA tools and big data management) on the innovation process, competitive advantage, and financial performance. A questionnaire was designed to measure the influence of the effective use of big data analytics tools and big data management on the innovation process and its drivers on competitive advantage and financial performance. Quantitative data collected using an online survey method, and (n= 174) samples were gathered from top managers working in firms operating in the United Kingdom and the United States of America. The hypotheses and model fitness were tested in SPSS, AMOS v.26 using structural equation modelling (SEM). The findings indicate that applying the significant data analytics components (effective use of BDA tools and big data management) has a significant positive impact on the innovation process capabilities (β = .317, p = 0.000 and β = .490, p = 0.000), competitive advantage (β = .322, p = 0.000 and β = .298, p = 0.000), and financial performance (β = .188, p = 0.000 and β = .444 and p = 0.000). There is also a significant positive impact of the innovation process on competitive advantage (β = .485, p = 0.000), and the competitive advantage led to a financial performance (β = .397, p = 0.000). Statistical findings also show that the innovation process as mediator has a significant positive impact on financial performance (β = .333, p = 0.000). Surprisingly, firm mediators such as age (β = -.002 and p = 0.000), size (β = -.003 with p = 0.000), type of industry (β = -.008 with p = 0.000), and environment turbulence (β = -.001 with p = 0.000), were found not to positively impact a firm’s financial performance.This work provides an original contribution to knowledge by extending and validating a new model and the factors affecting the innovation process, competitive advantage, and financial performance.
Item Description: ORCiD identifier: https://orcid.org/0000-0002-2101-2276
Keywords: Big Data, Big Data Analytics, Innovation, Innovation process, Competitive Advantage, Firm Performance, Financial Performance
College: Faculty of Humanities and Social Sciences