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Data governance and the secondary use of data: The board influence
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2023 | Information and Organization | Citations: 0
Authors: Black, Stuart; Davern, Michael; Maynard, Sean B.; Nasser, Humza

Abstract: The business analytics and strategic management literatures suggest that organiz ... Expand

Abstract: The business analytics and strategic management literatures suggest that organizations should seek to exploit data as a key mechanism for competitive advantage. However, the rules of engagement are evolving, the regulatory landscape is becoming increasingly complex, and ex amples of poor outcomes are increasingly common. The board – in its role of setting and moni toring risk appetite – needs to be able to govern the risk/reward trade-off of the data asset. Contemporary data governance approaches are inadequate: they are overly rigid and risk ori ented, limited in scope to an organization’s self-interest rather than considering the broad set of stakeholders, and do not provide a platform for the board to manage this critical risk. This paper uses a unique set of informants – 41 board directors – to demonstrate that differences in board perspectives influence how organizations explore the secondary use of data. Furthermore, this paper identifies a set of relevant individual, organizational and environmental factors and pre sents empirically based configurations of these factors that lead organizations to consider (or neglect) the secondary use of data as a critical enabler of competitive advantage. Collapse

Semantic filters: fuzzy set theory contingency theory

Topics: data governance competitive advantage IT governance fuzzy logic strategic management

Methods: qualitative interview qualitative coding theory development mixed method personal interview

Theories: contingency theory fuzzy set theory transaction cost economics dynamic capabilities theory theory of everything
Examining the interplay between big data analytics and contextual factors in driving process innovation capabilities
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2020 | European Journal of Information Systems | Citations: 41
Authors: Mikalef, Patrick; Krogstie, John

Abstract: The potential of big data analytics in enabling improvements in business process ... Expand

Abstract: The potential of big data analytics in enabling improvements in business processes has urged researchers and practitioners to understand if, and under what combination of conditions, such novel technologies can support the enactment and management of business processes. While there is much discussion around how big data analytics can impact a firm's incremental and radical process innovation capabilities, we still know very little about what big data analytics resources firms must invest in to drive such outcomes. To explore this topic, we ground this study on a theory-driven conceptualisation of big data analytics based on the resource-based view (RBV) of the firm. Based on this conceptualisation, we examine the fit between the big data analytics resources that underpin the notion, and their interplay with organisational contextual factors in driving a firm's incremental and radical process innovation capabilities. Survey data from 202 chief information officers and IT managers working in Norwegian firms are analysed by means of fuzzy set qualitative comparative analysis (fsQCA). Results show that under different combinations of contextual factors the significance of big data analytics resources varies, with specific configurations leading to high levels of incremental and radical process innovation capabilities. Collapse

Semantic filters: fuzzy set theory contingency theory

Topics: innovation management business process innovation big data fuzzy logic organization learning

Methods: survey computational algorithm survey design fuzzy set qualitative comparative analysis descriptive statistic

Theories: fuzzy set theory contingency theory resource based view of the firm

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Data governance and the secondary use of data: The board influence

Examining the interplay between big data analytics and contextual factors in driving process innovation capabilities