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1. Introduction
Big data (BD) is generated from multiple sources, from scientific, industry, smart sensors and social media. BD offers characteristics known as five Vs. This includes properties such a (1) volume (large quantity of data), (2) velocity (the speed at which the data is generated and processed), (3) variety (different types of data in the form of a structured database or spreadsheet data, unstructured (text, voice, video and web objects and semi-structured (files and documents), (4) veracity (the quality of data) and (5) value (the richness of information and the knowledge acquired through processing and analysis of large datasets). Big data analytics (BDA) tools offer organisations a cost-effective multiplatform environment for data analysis, data visualisations and user-friendly dashboards.
In this context, BDA have become an increasingly important component for firms to enhance business value and firm performance (Ren et al., 2017; Demchenko et al., 2014). Using real-time, multivendor, cross-domain data, BDA provides actionable insights about customer experience and behaviour that can automate actions and drive decisions across marketing, customer relationship performance, operations and planning. BDA offers firms opportunities to predict, prioritise and manage customers' demands in a real-time fashion, resulting in superior service, experience, customers' satisfaction, royalty, engagement, brand awareness and sales (Farrokhi et al., 2020; Erevelles et al., 2016). It also offers opportunities for new product development (Jagtap and Duong, 2019; Tan and Zhan, 2017; Zhan et al., 2016) and new product success (NPS) and performance (Hajli et al., 2020; Johnson et al., 2017; Jain, 2016; Xu et al., 2016; Chen et al., 2005).
In business-to-business (B2B) contexts, the organisational use of BDA illustrates the process of deploying a combination of skills, technologies, applications and processes in the examination of BD to uncover useful information such as hidden patterns and unknown relationships. This process could result in achieving success in new product development (Kiron, 2017). It could also help make better decisions across business processes among intra-functions or inter-organisations (Chen et al., 2015; Wiersema, 2013). One possible means of achieving this is through leveraging BDA capabilities.
Acquiring and deploying required BDA capabilities, technological developments, and their use, such as BDA in B2B contexts, could be pivotal to the timely development of business solutions...