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The impact of data visualisation on the use of shopper insight in the marketing decisionmaking of small food producers

Stefan Penczynski, Konrad Maliszewski and Andrew Fearne
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Stefan Penczynski: School of Economics and CBESS, University of East Anglia, Norwich.
Konrad Maliszewski: Norwich Business School and CBESS, University of East Anglia, Norwich.
Andrew Fearne: Norwich Business School, University of East Anglia, Norwich.

No 20-05, Working Paper series, University of East Anglia, Centre for Behavioural and Experimental Social Science (CBESS) from School of Economics, University of East Anglia, Norwich, UK.

Abstract: Recent advances in machine learning and the availability of big data have made the study of Business Intelligence Systems (BIS) increasingly relevant. BI, which includes processes and methods for improving decision making with the use of fact-based support systems, is reported to be widely used across sectors and different businesses functions. However, most of the research effort centres around the question of how BIS can deliver value to an organisation (Trieu, 2017). Since one of the key determinants of organisational impacts is the actual use of the system, many studies investigate the factors that facilitate more effective use of the information provided. The data presentation format is a promising areas of research (Kelton, Pennington and Tuttle, 2010; Luo, 2019). However, studies conducted thus far tend to rely on laboratory experiments with students and ignore objective usage data, thus reducing the validity and the reliability of the findings (see e.g. Luo, 2019). What is more, the empirical research studies predominantly examine BIS use amongst large businesses neglecting the specific context of SMEs (Arnott, Lizama and Song, 2017; PopoviÄ , Puklavec and Oliveira, 2019). In this research we conduct an online experiment to study the impact of experience on the previously identified relationships between information presentation format, task characteristics and individual differences.

Keywords: Data visualisation; Business Intelligence Systems (BIS); Improving decision making; Small and Medium Enterprises (SME) (search for similar items in EconPapers)
Date: 2020-11
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