Author | Focus | Method(s) | outcome |
Trabucchi & Buganza [10] . | Data-driven innovation | Exploratory multiple case study analysis | Big data drives innovation in firms |
Bresciani et al. [16] . | Big data and co-innovation | Systematic literature review | Big data and intentional collaborations with external parties drives innovation |
Babu et al. [11] . | Data-driven innovation | Systematic literature review | The seven data-driven innovation steps are significant to innovation |
Lerena et al. [17] . | Big data and innovation at the firm level | Social Network Analysis and Text Mining techniques | There exist multiple and heterogeneous dimensions in firm-level data mining |
Ghasemaghaei & Calic [7] . | Big data’s main characteristics and innovation performance | Structural Equation Model | Data velocity is significant in firm innovation performance compared to other big data characteristics |
Wright et al. [8] . | Big data in innovation and market leadership in B2B relationships | Conceptual and Case studies | Big data represents organizations’ ability to respond to market opportunities through innovation |
Niebel et al. [19] . | Big data analytics and product innovation performance | Knowledge production function framework | Big data analytics stimulates innovation |
Mikalef & Krogstie, [18] . | Big data, contextual factors, and firm performance | Grounded Theory | Diverse blends of contextual factors affect the significance of big data analytics |
Mikalef et al. [9] . | Big data, dynamic capabilities, and firm performance | Structural Equation Model | Big data affect dynamic competencies while incremental innovation capability is enhanced through a sequence |
Ghasemaghaei & Calic, [12] . | Big data characteristic on firm innovation | Grounded Theory | Data velocity, variety, and veracity enhance data-driven insight generation than data volume |
Lozada et al. [20] . | Big data and innovation | Structural Equation Model | Big data analytics promotes responsive processes of product and service co-creation |
Prester & Jurić, [6] . | Big data and product innovation | Ordinary Least Square | Some sources of big data are significant while others are not |