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Full-Text Articles in Business Analytics
Distilling Managerial Insights And Lessons From Ai Projects At Singapore's Changi Airport (Part 2), Steve Lee, Steven M. Miller
Distilling Managerial Insights And Lessons From Ai Projects At Singapore's Changi Airport (Part 2), Steve Lee, Steven M. Miller
Asian Management Insights
Since 2017, Changi Airport group (CAG) has initiated a host of pilot projects that use connective and intelligent technologies to enable its move towards digital transformation and SMART Airport Vision. This has resulted in a first wave of deployment of AI and Machine Learning-enabled applications across various functions that can better sense, analyse, predict, and interact with people.
Ai Gets Real At Singapore's Changi Airport (Part 1), Steve Lee, Steven M. Miller
Ai Gets Real At Singapore's Changi Airport (Part 1), Steve Lee, Steven M. Miller
Asian Management Insights
Ranked as the best airport for seven consecutive years, Singapore’s Changi Airport is lauded the world over for the efficient, safe, pleasurable and seamless service it offers the millions of passengers that pass through its facilities annually. Much of Changi Airport’s success can be attributed to the organisation’s customer-oriented business focus and deeply embedded culture of service excellence, combined with a host of advanced technologies operating invisibly in the background. The framework for this technology enablement is Changi Airport Group’s (CAG’s) SMART Airport Vision—an enterprise-wide approach to connective technologies that leverages sensors, data fusion, data analytics, and artificial intelligence (AI), …
Towards An Effective Design Of The Business Intelligence & Analytics Function Within An Organisation, Eric Sandosham
Towards An Effective Design Of The Business Intelligence & Analytics Function Within An Organisation, Eric Sandosham
Dissertations and Theses Collection
This dissertation is about the organisational considerations in setting up a successful business intelligence and analytics (BI&A) function. It addresses a gap in academic literature by presenting a theoretical framework on organisational attributes that impacts the BI&A function’s ability to improve the completeness and relevance of their data-driven solutions.
BI&A is a subset of information processing, and as such, subject to the phenomenon of uncertainty and equivocality. Most BI&A functions do not explicitly address this phenomenon in their organisation design, leading to suboptimal BI&A outcomes as widely publicised in both academic and practice literature.
This dissertation contributes to theory by …