Data analytics in operations management: A review
Research in operations management has traditionally focused on models for understanding,
mostly at a strategic level, how firms should operate. Spurred by the growing availability of …
mostly at a strategic level, how firms should operate. Spurred by the growing availability of …
Smart “predict, then optimize”
Many real-world analytics problems involve two significant challenges: prediction and
optimization. Because of the typically complex nature of each challenge, the standard …
optimization. Because of the typically complex nature of each challenge, the standard …
Frontiers in service science: Data-driven revenue management: The interplay of data, model, and decisions
Revenue management (RM) is the application of analytical methodologies and tools that
predict consumer behavior and optimize product availability and prices to maximize a firm's …
predict consumer behavior and optimize product availability and prices to maximize a firm's …
Banking crises without panics
We examine historical banking crises through the lens of bank equity declines, which cover
a broad sample of episodes of banking distress with and without banking panics. To do this …
a broad sample of episodes of banking distress with and without banking panics. To do this …
Smart predict-and-optimize for hard combinatorial optimization problems
Combinatorial optimization assumes that all parameters of the optimization problem, eg the
weights in the objective function, are fixed. Often, these weights are mere estimates and …
weights in the objective function, are fixed. Often, these weights are mere estimates and …
Behavioral operations: Past, present, and future
Behavioral operations is now an established and fundamental research field dedicated to
understanding how the behavior of managers, workers, and customers influences …
understanding how the behavior of managers, workers, and customers influences …
Interior point solving for lp-based prediction+ optimisation
Solving optimization problem is the key to decision making in many real-life analytics
applications. However, the coefficients of the optimization problems are often uncertain and …
applications. However, the coefficients of the optimization problems are often uncertain and …
Competition-based dynamic pricing in online retailing: A methodology validated with field experiments
A retailer following a competition-based dynamic-pricing strategy tracks competitors' price
changes and then must answer the following questions:(i) Should we respond?(ii) If so, to …
changes and then must answer the following questions:(i) Should we respond?(ii) If so, to …
Joint dynamic pricing and order fulfillment for e-commerce retailers
We consider an e-commerce retailer (e-tailer) who sells a catalog of products to customers
from different regions during a finite selling season and fulfills orders through multiple …
from different regions during a finite selling season and fulfills orders through multiple …
The value of personalized pricing
Increased availability of high-quality customer information has fueled interest in
personalized pricing strategies, that is, strategies that predict an individual customer's …
personalized pricing strategies, that is, strategies that predict an individual customer's …