Research

The central purpose of the Centre for Business Analytics is to contribute broadly and deeply to knowledge and practice in analytics. To aid this purpose the Centre for Business Analytics has partnered with AT Kearney to create the analytics Impact Index. Seed funding ranging from $5K-$20K is also provided to research projects across the University of Melbourne.

Topics of research include developing new text-mining techniques, new security analytics methods, understanding the shareholder value of investments in analytics, developing new customer lifetime value models and optimising supply chains.

Analytics Impact Index

The Analytic Impact Index is a globally recognised guide for organisational leaders to compare and improve their analytics capabilities.

As invest in analytics continues to grow, many wonder how their level of maturity compares to their peers, and what they can do to extract maximum value from that investment.

Melbourne Business School and A.T. Kearney have collaborated to produce the Analytics Impact Index in 2018 and 2019 – based on input from more than 350 companies across 46 countries and 27 industries – to pinpoint the bottom-line impact and structural elements required to set an organisation up for success.

To access a copy of the 2019 Analytics Impact Index white paper, please click here. Or, to find out directly how your organisation is tracking, the Analytics Impact Index survey can be taken here.

2019 Analytics Impact Index presentation

Popularity signals in trial-offer markets with social influence and position bias

Maldonado, F., Van Hentenryck, P., Berbeglia, G., & Berbeglia, F. (2018). Popularity signals in trial-offer markets with social influence and position bias. European Journal of Operational Research, 266, 775-793.

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Taming the Unpredictability of Cultural Markets with Social Influence

Abeliuk, A., Berbeglia, G., Van Hentenryck, P., Hogg, T., & Lerman, K. (2017). Taming the Unpredictability of Cultural Markets with Social Influence. WWW '17 Proceedings of the 26th International Conference on World Wide Web, 745-754.

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A Business Analytics Capability Framework

Cosic, R., Shanks, G., & Maynard, S. B. (2015). A business analytics capability framework. Australasian Journal of Information Systems, 19.

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Designing Multi-Attribute Procurement Mechanisms for Assortment Planning

Li, Z., Shao, L., & Sun, D. (2015). Designing Multi‐Attribute Procurement Mechanisms for Assortment Planning. Decision Sciences, 46(3), 597-622.

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Domain Adaption of Named Entity Recognition to Support Credit Risk Assessment

Alvarado, J. C. S., Verspoor, K., & Baldwin, T. Domain Adaption of Named Entity Recognition to Support Credit Risk Assessment. In Australasian Language Technology Association Workshop 2015 (p. 84).

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The Benefits of Social Influence in Optimized Cultural Markets

Abeliuk, A., Berbeglia, G., Cebrian, M., & Van Hentenryck, P. (2015). The benefits of social influence in optimized cultural markets. PloS one, 10(4), e0121934.

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From Academic Research to Marketing Practice: Exploring the Marketing Science Value Chain

Roberts, J. H., Kayande, U., & Stremersch, S. (2014). From academic research to marketing practice: Exploring the marketing science value chain. International Journal of Research in Marketing, 31(2), 127-140.

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