Presenter Information

Olgerta Tona, Lund UniversityFollow

Description

The generation of new mobile devices and the need to make decisions ‘on the move’ led to a new technology coined as mobile business intelligence (m-BI). M-BI is different from traditional BI in terms of user profiles, level of analytics and functionalities. Although there is a growing interest from both practitioners and academics, very little is known about m-BI in general and even less on its usage. A case study research is conducted to explore how m-BI usage patterns emerge and develop. M-BI is used to investigate after a trigger, monitor real-time data, control and support liminality. Users engage with usage patterns based on the their mode (lean back or lean forward) and attention scope (narrow or wide). However, usage patterns developed are not static because m-BI users engage continuously with different usage patterns when shifting among different modes and attention scopes.

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Mobile Business Intelligence Usage Patterns

The generation of new mobile devices and the need to make decisions ‘on the move’ led to a new technology coined as mobile business intelligence (m-BI). M-BI is different from traditional BI in terms of user profiles, level of analytics and functionalities. Although there is a growing interest from both practitioners and academics, very little is known about m-BI in general and even less on its usage. A case study research is conducted to explore how m-BI usage patterns emerge and develop. M-BI is used to investigate after a trigger, monitor real-time data, control and support liminality. Users engage with usage patterns based on the their mode (lean back or lean forward) and attention scope (narrow or wide). However, usage patterns developed are not static because m-BI users engage continuously with different usage patterns when shifting among different modes and attention scopes.