Decision-Making Performance in Big Data Era: The Role of Actual Business Intelligence Systems Use and Affecting External Constraints
2018
- 433Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Usage433
- Abstract Views248
- Downloads185
Article Description
Business Intelligence (BI) has received wide recognition in the business world as a tool to ad-dress ‘big’ data-related problems, to help managers understand their businesses and to assist them in making effective decisions. To date, however, there have been few studies which have clearly articulated a theoretically grounded model that explains how the use of BI systems provides benefits to organisations, or explains what factors influence the actual use of BI systems. To fully achieve greater decision-making performance and effective use of BI, we contend that BI systems integration with a systems user’s work routine (dependence on the systems) is essential. Following this argument, we examine the effects of system dependent use along with effective use (infusion) on individual’s decision-making performance with BI. Additionally, we pro-pose that a fact-based decision-making culture, and data quality of source systems are constraints factors that impact on BI system dependence and infusion. We adopt a quantitative method approach. Specifically, we will conduct a two-wave cross-sectional survey targeting 400 North American BI users who describe themselves as both using a BI system and making decision using data from the system. We expect to make an important theoretical contribution to BI literature by providing a model that explains the dimensions of actual BI system use, and makes a practical contribution by providing insights into how organisational external constraints facilitate BI dependence and infusion in the pursuit of BI-enabled performance gain.
Bibliographic Details
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