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Studying The Executive Perception Of Investment In Intelligent Systems And The Effect On Firm Performance, Noel Romesh Wijesinha
Studying The Executive Perception Of Investment In Intelligent Systems And The Effect On Firm Performance, Noel Romesh Wijesinha
FIU Electronic Theses and Dissertations
This research was conducted to examine the relationship between investment in intelligent systems resources and capabilities (based on artificial intelligence and machine learning algorithms) and the effect on company performance. Despite existing research on the benefits of adopting intelligent systems, companies have been slow to adopt as there is lack of research on intelligent systems use cases that will increase firm performance. This research study used resource-based view (RBV) and dynamic capabilities (DCF) theory to investigate firms’ investment in intelligent systems resources that build intelligent systems capabilities and the association to organization performance dimensions, revenue and profits. To answer this …
Artificial Intelligence And It Professionals, Sunil Mithas, Thomas Kude, Jonathan W. Whitaker
Artificial Intelligence And It Professionals, Sunil Mithas, Thomas Kude, Jonathan W. Whitaker
Management Faculty Publications
How will continuing developments in artificial intelligence (AI) and machine learning influence IT professionals? This article approaches this question by identifying the factors that influence the demand for software developers and IT professionals, describing how these factors relate to AI, and articulating the likely impact on IT professionals.
Vungle Inc. Improves Monetization Using Big-Data Analytics, Bert De Reyck, Ioannis Fragkos, Yael Gruksha-Cockayne, Casey Lichtendahl, Hammond Guerin, Andre Kritzer
Vungle Inc. Improves Monetization Using Big-Data Analytics, Bert De Reyck, Ioannis Fragkos, Yael Gruksha-Cockayne, Casey Lichtendahl, Hammond Guerin, Andre Kritzer
Research Collection Lee Kong Chian School Of Business
The advent of big data has created opportunities for firms to customize their products and services to unprecedented levels of granularity. Using big data to personalize an offering in real time, however, remains a major challenge. In the mobile advertising industry, once a customer enters the network, an ad-serving decision must be made in a matter of milliseconds. In this work, we describe the design and implementation of an ad-serving algorithm that incorporates machine-learning methods to make personalized ad-serving decisions within milliseconds. We developed this algorithm for Vungle Inc., one of the largest global mobile ad networks. Our approach also …