Digital Transformation, Robotics, Artificial Intelligence, and Innovation

Abstract

Contemporary business organizations continue to embrace Digital Transformation (DT) on the back of the accelerated progress in technology, algorithms, internet, interconnectedness, and big data storage (Foerster-Metz, Marquardt, Golowko, Kompalla, & Hell, 2018; Hanelta, Bohnsack, Marzc and Maranteb, 2021). The pervasive adoption of digital technologies has generated extensive transformation in organizations, which is expected to impact organizations’ internal operations and processes (Kretschmer & Khashabi, 2020; Magistretti, Pham, & Dell’Era, 2021). Especially, organizations perceive that digitalization will assist them to radically improve their efficiency and effectiveness in the way they organize resources, staffing, culture, decision making (Devonport, 2018), and internal education tailored training (Foerster-Metz et al., 2018) for competitive advantage. Given that DT is multidimensional (Appio, Frattini, Petruzzelli and Neirotti, 2021; Zangiacomi, Pessot, Fornasiero, Bertetti, & Sacco, 2020), researchers define it variously (see Verhoef, Broekhuizen, Bart, Bhattacharya, Dong, Fabian, & Haenlein, 2021; Vial, 2019). Indeed, Warner and Wager (2019) suggest that DT suffers from a lack of common agreement on exactly what it is and what it entails (Wessel, Baiyere, Ologeanu-Taddei, Cha, & Blegind-Jensen, 2021). However, it is agreed that DT can be described as an emerging integration of new digital technologies into the fabric of an organisation suggesting a need to transform the traditional business models (Reier Forradellas, & Garay Gallastegui, 2021). Especially, Tang (2021) argues that DT is driven by trends in technology such as social media, mobility, internet of things (IoT), cyber security, big data and analytics, cloud computing, robotics, automation, artificial intelligence (AI, including Machine Learning). These technological trends provide businesses with the capability to fully digitize, transform, and grow their organizations spanning both growth and operational improvement, and are associated with organizational strategic renewal (Kretschmar & Khashabi, 2020). Against this backdrop, the collections of papers in this current issue (27.5) examine the intersection between DT, the Robotics, AI, and Innovation. The first paper is from an emerging economy and tackles the issue of DT head on. In this paper, “Digital transformation: a conceptual framing for attaining sustainable development goals 4 and 9 in Nigeria”, the authors Ufua, Emielu, Olujobi, Lakhani, Borishade, Ibidunni and Osabuohien explore the potentials of digital transformation for achieving the United Nations Sustainable Development Goals (SDGs), with emphasis on SDG 4 and SDG 9 in Nigeria. The study adopts a conceptual approach and focuses on the contextual factors such as stakeholder input to the process of implementing digitalisation and SDGs 4 and 9. These goals primarily target development of education at all levels, industrial collaboration, and improvements. Literature review indicates that digital transformation potentially enhances the attainment of SDGs 4 and 9, but this is mediated by the level of stakeholder commitment and e-governance performance. The authors recommend the adoption of a multidisciplinary approach to development-oriented digital transformation interventions for SDGs 4 and 9 in Nigeria, through a process of effective stakeholder engagement and transparent