On understanding company perceptions of risk – a text mining application

Jim Freeman; Zhuopeng Jiang; Alex Karagrigoriou; Teresa Oliveira; Christos H Skiadas

On understanding company perceptions of risk – a text mining application

Jim Freeman, Zhuopeng Jiang, Alex Karagrigoriou (Editor), Teresa Oliveira (Editor), Christos H Skiadas (Editor)

MSM Decision Sciences

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Two methodologies – thematic analysis and laddering theory – were used to analyse qualitative data on risk management. The data – in the form of interview transcripts – were obtained from an in-depth survey of how risk is perceived by UK business. Using the NVivo software, four main themes were identified: concepts of risk, risk management, roles in risk management and data encryption. From these, inferential codes on attributes, consequences and values were used in conjunction with means–end theory to help explain the motivations behind the competing core values of the participating organisations.

Original language	English
Title of host publication	Statistical, Stochastic and Data Analysis Methods and Applications
Place of Publication	Athens
Publisher	International Society for Art, Science and Technology
Publication status	Published - 2016

Keywords

Hierarchy value map, Implication matrix, Laddering theory, Risk management

Cite this

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title = "On understanding company perceptions of risk – a text mining application",

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M3 - Chapter

BT - Statistical, Stochastic and Data Analysis Methods and Applications

PB - International Society for Art, Science and Technology

CY - Athens

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On understanding company perceptions of risk – a text mining application

Abstract

Keywords

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