Areas of Expertise (5)
Social Media Analytics
Optimal Contract Design
Huaxia Rui is professor and Xerox Chair of Computer and Information Systems at the Simon Business School. He is also one of the inaugural Distinguished Researcher and Scholar of the Center of Excellence in Data Science at The University of Rochester. He is interested in social media analytics, big data, economics of information systems, optimal contract design, and health economics. His research has been published in leading academic journals such as (alphabetically), Information Systems Research, Journal of Financial Economics, Journal of Mathematical Economics, Management Science, MIS Quarterly, and Production and Operation Management.
The University of Texas at Austin: PhD, Business Administration 2012
Tsinghua University: ME, Control Theory and Engineering 2009
Selected Media Appearances (1)
Branding Yourself on Twitter Works. (It Did in 2012, Anyway)
A new study finds that the redesign of Twitter gave a measurable boost to the personal branding and career prospects of S&P 500 C-suite execs: CEOs, chief marketing officers, chief technology officers, and chief product or innovation officers.
Selected Articles (4)
Optimal Auction Design for WiFi Capacity ProcurementInformation Systems Research
Huaxia Rui, Liangfei Qiu, and Andrew Whinston
The unprecedented growth of cellular traffic driven by the use of smartphones for web surfing, video streaming, and cloud-based services poses bandwidth challenges for cellular service providers. To manage the increasing data traffic, cellular service providers are experimenting with the use of third-party Wi-Fi hot spots to augment their cellular capacity. We develop an analytical framework to study the optimal procurement auction for Wi-Fi capacity. Such an auction design is complicated by the fact that Wi-Fi networks have much more limited spatial coverage compared with the cellular network. Neither a global auction that includes all Wi-Fi hot spots nor multiple local auctions that include only hot spots in each local Wi-Fi region is optimal. We find that the optimal mechanism is an integration of one global auction that includes hot spots from an endogeneously determined set of Wi-Fi regions and many separate local auctions that are only held in the rest of the Wi-Fi regions. To implement the optimal mechanism, we also provide an efficient algorithm whose computation complexity is of the order of the number of Wi-Fi regions. Our work contributes to the literature by designing the optimal mechanism for a unique type of IT procurement auction problem that is a tight integration of economics and computational technology.
Social Media Strategies in Product Harm CrisesInformation Systems Research
Huaxia Rui, Shu He, and Andrew B. Whinston
When a focal firm undergoes a product-harm crisis, nonfocal firms offering similar products or services can suffer from a negative spillover effect, but can also benefit from customers switching from the troubled focal firm, which we call the competitive effect. In response, a nonfocal firm can adapt its marketing strategy in consideration of these two opposing effects. Because social media is a flexible medium through which firms can quickly adjust marketing strategies in response to such unexpected events, we study how nonfocal firms adjust their post-crisis social media efforts to induce purchases and to improve customer relationships—two strategies known in the literature as offensive and defensive marketing, respectively. In particular, we use the daily social media activities of 56 major airlines on Twitter around the time of the Germanwings Flight 9525 crash to study how nonfocal airlines ran offensive and defensive marketing on social media before and after the crisis. We find that, on average, nonfocal airlines increased their defensive marketing efforts but decreased their offensive marketing efforts after the crash, which we attribute to the negative spillover effect. However, the strategic adjustment of decreasing offensive marketing is attenuated by the competition between nonfocal airlines and the focal one, which we attribute to the moderating role of the competitive effect. These results are shown to be robust in various tests and reveal how the interplay of the two effects of a product-harm crisis on nonfocal firms shapes their postcrisis social media strategies.
Can We Trust Online Physician Ratings? Evidence from Cardiac Surgeons in FloridaManagement Science
Huaxia Rui and Susan F. Lu
Despite heated debate about the pros and cons of online physician ratings, little systematic work has examined the correlation between physicians’ online ratings and their actual medical quality. Using the ratings of cardiac surgeons at RateMDs and the patient outcomes of coronary artery bypass graft surgeries in the 2013 Florida Hospital Inpatient Discharge Data, we investigate whether online ratings are informative about physicians’ medical quality. To account for potentially nonrandom matchings of patients of different severity levels to surgeons of different rating categories, we focus on patients who arrived through the emergency department and explicitly consider how observed and unobserved patient health conditions jointly affect the matching arrangements and surgical outcomes. Both reduced form and two-stage estimation results show that, compared with surgeons rated four stars or higher, or those without rating information, lower rated surgeons are associated with significantly higher in-hospital mortality rates. Our findings suggest that online physician ratings could be a valuable information source for patients to learn about physician quality, at least for cardiac surgeons, a specialty for which treatment outcomes are relatively observable to patients and their family members.
Does Technology Substitute for Nurses? Staffing Decisions in Nursing HomesManagement Science
Huaxia Rui, Susan F. Lu, and Abraham Seidmann
Over the past 10 years, many healthcare organizations have made significant investments in automating their clinical operations, mostly through the introduction of advanced information systems. Yet the impact of these investments on staffing is still not well understood. In this paper, we study the effect of information technology (IT)-enabled automation on staffing decisions in healthcare facilities. Using unique nursing home IT data from 2006 to 2012, we find that the licensed nurse staffing level decreases by 5.8% in high-end nursing homes but increases by 7.6% in low-end homes after the adoption of automation technology. Our research explains this by analyzing the interplay of two competing effects of automation: the substitution of technology for labor and the leveraging of complementarity between technology and labor. We also find that increased automation improves the ratings on clinical quality by 6.9% and decreases admissions of less profitable residents by 14.7% on average. These observations are consistent with the predictions of an analytical staffing model that incorporates technology adoption and vertical differentiation. Overall, these findings suggest that the impact of automation technology on staffing decisions depends crucially on a facility’s vertical position in the local marketplace.