Exploring big data-driven innovation in the manufacturing sector: evidence from UK firms

Abstract

Although innovation from analytics is surging in the manufacturing sector, the understanding of the data-driven innovation (DDI) process remains a challenge. Drawing on a systematic literature review, thematic analysis and qualitative interview findings, this study presents a seven-step process to understand DDI in the context of the UK manufacturing sector. The findings discuss the significance of critical seven-step in DDI, ranging from conceptualisation to commercialisation of innovative data products. The results reveal that the steps in DDI are sequential, but they are all interlinked. The proposed seven-step DDI process with solid evidence from the UK manufacturing and research implications based on dynamic capability theory, institutional theory and TOE framework establish the building blocks for future studies and industry practice.

Decision optimization in cooperation innovation: the impact of big data analytics capability and cooperative modes

“…(1) Collaborative innovation based on big data significantly improves innovation performance, regardless of the cooperation mode. Previous studies have shown that cooperation innovation is conducive to improving innovation performance (Trigo & Vence, 2012, Hu et al, 2016, and the big data is also beneficial to the firm's innovation (Babu et al, 2021;Fosso Wamba & Akter, 2019;Li et al, 2018). This study confirms that data cooperation is mutually beneficial for supply chain members, and that no matter what kind of collaboration mode can benefit from data-driven innovation.…”

“…Big data has received considerable attention from academics and practitioners in recent years (Gandomi & Haider, 2015). Many researchers point out that big data makes significant influence on the firm's innovation (Babu et al, 2021;Fosso Wamba & Akter, 2019;Li et al, 2018). Data-driven innovation is regarded as an emerging approach to enhance innovation by acquiring, analyzing and acting upon consumer data (Babu et al, 2021).…”

“…Many researchers point out that big data makes significant influence on the firm's innovation (Babu et al, 2021;Fosso Wamba & Akter, 2019;Li et al, 2018). Data-driven innovation is regarded as an emerging approach to enhance innovation by acquiring, analyzing and acting upon consumer data (Babu et al, 2021). In the data-driven supply chain, data as driving forces and raw materials are getting more and more attentions (Liu & Yi, 2018b).…”

“…The main challenge related to the use of Big Data, specifically the skills for handling it, has been identified as being of particular concern, as not only are the skills difficult to find but they are, most importantly, expensive to acquire (Del Vecchio et al, 2018). Considering Big Data as an important approach to help firms to maximize their innovation, efficiency (Babu et al, 2021), it is important to seek external cooperation to improve their big data capabilities as well as contribute to their success in promoting collaborative innovation.…”

“…The main theoretical contribution of this study is that: (1) Previous studies have emphasized that big data analytics capability can help firms improve innovation performance (Babu et al, 2021;Fosso Wamba & Akter, 2019;Li et al, 2018), and analyzed the process of big data analytics capability assisted decision-making (He & Liu, 2017;He et al, 2019;Mikalef et al, 2019, Yasmin et al, 2020. However, existing studies still limit the commercial value of big data analytics capability to the firm's operation process, while ignoring the impact of big data analytics capability on the cooperation process.…”