Carrie Queenan

The “Killer Application” of Revenue Management: Harrah's Cherokee Casino & Hotel

Harrahs Cherokee Casino & Hotel is an unusual example of the use of revenue-management (RM) techniques. Typical RM installations yield revenue improvements of between 3 and 7 percent. The Harrah chain has seen 15-percent improvements, with Harrahs Cherokee Casino & Hotel as the largest beneficiary---although it does not serve alcohol or have traditional table games. In addition, the RM techniques that the Cherokee uses, such as its pricing decisions and customer-segmentation rules, are different from those used in RM applications in other industries.

Complements or Substitutes? Culture–Technology Interactions in Healthcare

The U.S. government recommends that hospitals adopt Computerized Provider Order Entry (CPOE) systems to improve the quality problems that plague U.S. hospitals. However, CPOE studies show mixed results. We hypothesize that CPOE effectiveness depends on the prevalence of patient safety culture within a hospital. Using organizational information processing theory, we describe how patient safety culture and CPOE enable healthcare organizations to better process information. Specifically, we posit that CPOE complements some aspects of patient safety culture and substitutes for others. Using ridge regression, we empirically test this proposition using data from 268 hospitals and multiple data sources. Results show that while CPOE complements the patient safety dimensions of handoffs and transitions, feedback and communication about error, and organizational learning, CPOE substitutes for the dimension of management support for safety, in the context of our dependent variable. As organizations work to implement new systems, this research can help decision-makers understand how culture impacts such initiatives and account for culture when anticipating effects. [web URL: http://onlinelibrary.wiley.com/doi/10.1111/deci.12199/full]

Case Article---Starting with Good Inputs: Unconstraining Demand Data in Revenue Management

Sales of goods and services are often limited by supply. This limitation restricts the knowledge of the true parameter values for the underlying demand distributions, values needed to calculate optimal protection levels in a revenue management system. We provide a teaching module and a case study to introduce students to the dangers of using “constrained demand.” The teaching module illustrates the negative financial impact of failing to unconstrain demand data. The case study provides realistic constrained demand data that students can use to practice unconstraining methods, such as the commonly used averaging method. We have used these materials successfully in MBA and executive education classes on revenue management. Case Teaching Note: Interested Instructors please see the Instructor Materials page for access to the restricted materials. To maintain the integrity and usefulness of cases published in ITE, unapproved distribution of the case teaching notes and other restricted materials to any other party is prohibited.

Prediction of Patient Activation during Technology Enabled Continuity of Care Intervention

Patients’ skills, knowledge, and motivation to actively engage in their healthcare are assessed with the Patient Activation Measure (PAM) – a metric associated with positive healthcare outcomes. The literature on predicting PAM, when patient counseling is coupled with a telemonitoring intervention, is scant. This proof-of-concept study employs a two-phase framework to (i) posit a causal relationship between a telemonitoring intervention and enhanced patient activation; and (ii) link healthcare providers’ operating decisions and patients’ willingness to change with prediction of PAM. We test the framework using data from a randomized, controlled field experiment and find a causal relationship between telemonitoring and increased PAM. Based on this causal result the PAM levels are predicted as a function of the strength of the information signals using a machine learning methodology. We show that these predictions are subject to under-over-estimation biases, consistent with the behavioral concept of system neglect in signal detection theory.

Teaching Note---Starting with Good Inputs: Unconstraining Demand Data in Revenue Management

Case Teaching Note: Interested Instructors please see the Instructor Materials page for access to the restricted materials. To maintain the integrity and usefulness of cases published in ITE, unapproved distribution of the case teaching notes and other restricted materials to any other party is prohibited.