Theme of the Special Issue
The prominent role of data in information-driven organisations is sometimes summarised in the statement that 'data is the new oil' (e.g. The Economist, 2017). The analogy suggests that data is the fuel and lubricant of organisations 'big data is everywhere' (George et al., 2014, p.321). However, if oil is a finite resource, data is potentially reusable, enduring and infinitely available (Iqbal et al., 2018).
Data availability has increased exponentially in the last decade, paving the way for a new business environment (Fosso Wamba et al., 2015; Hou et al., 2018), innovative business models (Wang et al., 2018) and new challenges (Blazquez and Domenech, 2018). As this growth accelerates, a better understanding is needed of the opportunities that the new phenomenon offers - and of the innovation, ethical, social, privacy and security challenges it poses. "Big data" appears to give rise to organisational changes and new tensions for individuals, organisations and society that need to be addressed. Such tensions include the digital skills shortages, threats from cyber-attacks, requirements to embrace GDPR legislation and the use of Artificial Intelligence for forecasting and decision-making. Recent news items, such as Facebook's fines for breaking data protection laws, highlight the importance and topicality of these issues. This Special Issue will focus on how organisations from the private, public and third sectors are experiencing and responding to such tensions and challenges in the business environment, and the implications of these challenges for individuals, organisations and society.
We invite the submission of original manuscripts that advance empirical (quantitative, qualitative and mixed methods), theoretical and conceptual understanding of the changing use of data and its impact. Manuscripts must have strong implications for theory and practice. The Special Issue is designed to widen interdisciplinary perspectives in relation to the topic of data.
Some indicative themes of relevance to this issue include (but are not limited to) the following:
- New ways of doing business and new business models emerging from the transformation of data;
- The role of new business models in transforming data ownership, including privacy-friendly business models;
- Big data, analytics and its application as a driver of innovation and strategy development;
- Antecedents and causes of tensions and risk surrounding data use for private, public and third sectors organisations;
- Impact of the digital skills gap in organisations;
- Navigating the relationships between stakeholders who own, store, manage and use data;
- Privacy issues emerging from the collection and storage of personal data by organisations;
- Data governance and the implications of GDPR for organisations;
- The implications of black box algorithms and algorithmic accountability;
- Understanding organisational responses to regulatory pressures in data security management;
- Implications for organisations of data security breaches Managerial issues emerging around cyber security management;
- Analysis of the interaction of Artificial Intelligence with social, behavioural and environmental aspects in organisations;
- The use of Artificial Intelligence and Big Data Analytics in organisations for forecasting and decision-making;
- The effects of big data and Artificial Intelligence on the risk evaluation of large public corporations and small private enterprises;
- The developing trends and applications of combining block chains, big data, and Artificial Intelligence in diverse aspects of organisations;
- Bridging digital transformation and digital sustainability for increased value.
Suggested submission deadline: 30th May 2019 (earlier submissions, starting from 1st December 2018, are welcome)
Notifying the submitting authors regarding status of their paper: September 2019
Suggested publication release: late 2020
For more information please visit: https://www.journals.elsevier.com/technological-forecasting-and-social-change/call-for-papers/tension-in-the-data-environment.