There is a natural order to most events in life: Everything from learning to read to DNA sequences in molecular biology follows some predetermined, structured methodology that has been refined to yield improved results. Likewise, it would seem that firms could benefit by adopting and implementing technologies in some logical way so as to increase their overall performance. In this study of 555 hospitals, we investigate the order in which medical technologies are transformed into information technologies through a process of converting them from stand‐alone technologies to interoperable, integrated information systems and whether certain configurations of sequences of integration yield additional value. We find that sequence does matter and that hospitals that integrated foundational technologies first—which in this case are known to be more complex—tend to perform better. Theoretical and practical implications of this finding and others are discussed.

Doctors’ orders entered with Computerized Physician Order Entry (CPOE) systems are designed to enhance patient care by standardizing routines that are intended to improve quality of healthcare. As with other health information technology (IT) performance studies, literature shows conflicting results regarding the CPOE–performance relationship. By adopting a more nuanced perspective and employing not just adoption but extent of use of CPOE, we first examine whether or not CPOE use improves patient satisfaction. Next, given that CPOEs are implemented in the backdrop of other hospital IT infrastructure, we examine how IT infrastructure impacts the relationship between CPOE use and satisfaction, testing both a complementary and substitution perspective. Finally, we examine the differential impact of CPOE use between academic and non‐academic hospitals. Using data from 806 hospitals nationwide, we find a positive relationship between extent of CPOE use and patient satisfaction. Contrary to extant research, our results suggest this relationship is stronger in non‐academic hospitals. We also find evidence that a hospital's IT infrastructure substitutes for CPOE use in its effect on patient satisfaction.

Asuccessful revenue management system requires accurate demand forecasts for each customer segment. The forecasts are used to set booking limits for lower value customers to ensure an adequate supply for higher value customers. The very use of booking limits, however, constrains the historical demand data needed for an accurate forecast. Ignoring this interaction leads to substantial penalties in a firm's potential revenues. We review existing unconstraining methods and propose a new method that includes some attractive properties not found in the existing methods. We evaluate several of the common unconstraining methods against our proposed method by testing them on intentionally constrained simulated data. Results indicate our proposed method outperforms other methods in two of three data sets. We also test the revenue impact of our proposed method, expectation maximization (EM), and “no unconstraining” on actual booking data from a hotel/casino. We show that performance varies with the initial starting protection limits and a lack of unconstraining leads to significant revenue losses.

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.

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Patients’ skills, knowledge, and motivation to actively engage in their health care are assessed with the patient activation measure (PAM). The literature on the role of PAM, when patient counseling is coupled with a technology enabled continuity of care intervention, is scant. We model the patient–health care provider feedback loop and learning through error corrections to explore the relations between continuity of care, PAM and patient readmissions. We test this model using data from a randomized, controlled field experiment. Our data show a direct effect of technology‐enabled continuity of care, together with its interaction with PAM, reduces readmissions over the base case without technology enabled continuity of care. Using exploratory analysis, we further show how a machine learning algorithm can be used to predict PAM, that can potentially furnish health care providers with useful information during the process of supporting their patients.

Harrah's 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 Harrah's 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.

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