A Data Snapshot Approach for Making Real-Time Predictions in Basketball.

This article proposes a novel approach, called data snapshots, to generate real-time probabilities of winning for National Basketball Association (NBA) teams while games are being played. The approach takes a snapshot from a live game, identifies historical games that have the same snapshot, and uses the outcomes of these games to calculate the winning probabilities of the teams in this game as the game is underway. Using data obtained from 20 seasons worth of NBA games, we build three models and compare their accuracies to a baseline accuracy.

How honest are the signals? A protocol for validating wearable sensors.

There is growing interest among organizational researchers in tapping into alternative sources of data beyond self-reports to provide a new avenue for measuring behavioral constructs. Use of alternative data sources such as wearable sensors is necessary for developing theory and enhancing organizational practice. Although wearable sensors are now commercially available, the veracity of the data they capture is largely unknown and mostly based on manufacturers' claims.

Seeking health information on the web: positive hypothesis testing.

Purpose: The goal of this study is to investigate positive hypothesis testing among consumers of health information when they search the Web. After demonstrating the extent of positive hypothesis testing using Experiment 1, we conduct Experiment 2 to test the effectiveness of two debiasing techniques.

Methods: A total of 60 undergraduate students searched a tightly controlled online database developed by the authors to test the validity of a hypothesis.

The role of organizational factors in the adoption of healthcare information technology in Florida hospitals.

This study examines whether specific organizational characteristics, such as hospital size, geographic location (urban versus rural), system membership (stand-alone versus system-affiliated), and tax status (for-profit versus non-profit), influence adoption of healthcare information technologies (HIT) in hospitals. We hypothesize the above organizational characteristics to be related to hospitals' adoption of clinical, administrative, and strategic HIT, as well as all HIT in general. Using survey data collected from 98 Florida hospitals, we demonstrate that hospital size, system membership, and tax status, but not geographic location, are systematically related to HIT adoption, and that such factors explain about 28-41% of the adoption variance.