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Although combinatorial auctions are important mechanisms for many specialized applications, their adoption in general-purpose marketplaces is still fairly limited, partly due to the inherent difficulty in evaluating the efficacy of bids without the availability of comprehensive bidder support....
Persistent link: https://www.econbiz.de/10012907179
We develop efficient computational strategies for inventory liquidation problem, which is characterized by a retailer disposing of a fixed amount of inventory over a period of time. Liquidating end-of-cycle products optimally represents a challenging problem due to its inherent stochasticity....
Persistent link: https://www.econbiz.de/10012910964
The application of predictive data mining techniques in Information Systems research has grown in recent years, likely due to their effectiveness and scalability in extracting information from large amounts of data. A number of scholars have sought to combine data mining with traditional...
Persistent link: https://www.econbiz.de/10012957533
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed by the inclusion of those...
Persistent link: https://www.econbiz.de/10012850047
We study the impact and interplay of social design features on the engagement behaviors toward user-generated content on Facebook business pages. By examining the introduction of the “Reactions” feature on Facebook, we aim to understand how the introduction of a new engagement feature...
Persistent link: https://www.econbiz.de/10012827255
Many important decisions are increasingly being made with the help of information systems that use artificial intelligence and machine learning models. These computational models are designed to discover useful patterns from large amounts of data, which augment human capabilities to make...
Persistent link: https://www.econbiz.de/10012863727
We develop a general agent-based modeling and computational simulation approach to study the impact of various factors on the temporal dynamics of recommender systems' performance. The proposed agent-based simulation approach allows for comprehensive analysis of longitudinal recommender systems...
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