Department of Information Systems & Operations Management

Research Seminar Series

The Research Seminar Series in ISOM is organized to disseminate the latest research in Information Systems and Operations Management.


  1. 02.05.2016
    Felipe Caro
    • Associate Professor of Decisions, Operations, and Technology Management, UCLA Anderson School of Management
    • Bio

    • “Managing Online Content to Build a Follower Base”
    • 10:30am—12noon at STZ 102


    Content providers typically manage a dual objective of generating interest for current followers and at the same time reaching out to new audiences that may become repeat visitors. The pace at which content is created must thus take into account how much it contributes to maintain the follower base. We formulate a simple model to study follower base build-up dynamics under the assumption that the attractiveness of past content decays over time. Using stochastic dynamic programming we develop heuristics for content release and an upper bound to assess performance. We then apply our model to the case of blogs: we analyze four blogs and their daily traffic for over 3 years. Our findings show that adjusting posting frequency to the optimum can raise total traffic levels by generating a larger follower base.

  2. 02.19.2016
    Laurens Debo
    • Associate Professor of Decisions, Operations, and Technology Management, UCLA Anderson School of Management
    • Bio
    • Paper

    • “Observational Learning in Environments with Multiple Choice Options: The Wisdom of Majorities and Minorities”
    • 10:30am to 12:00pm at STZ 102


    We study the formation of market shares in environments where customers choose from among multiple options for which they observe the aggregate choices of previous customers (the sales of each option). With imperfect information regarding the true quality of the different options, the choices of better informed customers turn sales into informative signals, allowing less informed customers to learn about the options' quality. Besides such informational externalities, we consider possible direct negative externalities that characterize many economic environments—customers often derive lower utility from options chosen by more other customers, ceteris paribus. Our equilibrium analyses demonstrate a moderating, and counterintuitive, effect of negative externalities on observational learning. For example, when negative externalities are negligible, the “majority” option with the highest sales might seem like the obvious choice as it is a cheap signal of quality, but we find that rational uninformed customers instead choose a “minority” option with lower sales. We test our theory in a controlled laboratory environment with human subjects, and find strong evidence for observational learning predicted by our equilibrium analyses, with one notable exception: With negligible negative externalities, uninformed subjects ignore minority options and choose majority options instead. We explain this behavior via random choice theory.

  3. 03.11.2016
    Dr. Anuj Kumar
    • Associate Professor of Decisions, Operations, and Technology Management, UCLA Anderson School of Management
    • Bio

    • “Remedying Education with Personalized Learning: Evidence from Randomized Field Experiment in India”
    • 10:30am to 12:00pm at STZ 102


    Can Information Technology (IT) enabled personalization remedy the educational production in resource strapped schooling systems? We conduct a randomized field experiment on a group of residential schools in Hyderabad India to examine this question. In a school setting, students first learn concepts through class room instructions and then reinforce their learning by doing homework questions. In our experiment, students were first taught different topics in mathematics through classroom instructions, and then a randomly selected one half of them were assigned computer generated adaptive homework (CGAHW) and the other half were offered paper based traditional homework (PBTHW). In a PBTHW, a pre-decided fixed number of easy and hard questions were offered from different covered topics. In contrast, first half of the total questions in easy category were offered in a CGAHW, and based on a student’s performance on these questions, later questions were adaptively generated such that, (1) more questions were offered on the topics in which student incorrectly answered questions and (2) hard questions on a topic were offered when the student correctly answered easy questions on that topic. Thus, while all PBTHW students received the same number of easy and hard questions on different topics, CGAHW students received different numbers and difficulty levels of questions on different topics based on their individual learning needs. Total 50 homework in each category were offered to students between October 2014 and April 2015, and their learning were assessed in two standardized exams offered in this period.

    We found that CGAHW students on average obtained lower homework scores than PBTHW students but they obtained 4.28 percent higher scores in exams than PBTHW students. Lower homework scores could be attributed to students receiving more questions in their weak areas in CGAHW. However, by doing more questions in their weak areas and less in their strong areas, students achieved higher and personalized learning in CGAHW, and hence obtained higher exam scores. We provide empirical evidence that personalized learning through CGAHW caused improvement in students’ exam scores by showing students, who were offered higher levels of personalization in CGAHW, obtained higher exam scores.

    To further understand the differential effect of CGAHW on students of different abilities, we categorized students in low, medium, and high categories of mathematical ability based on their mathematics scores in standardized exams at the beginning of experiment. We found that personalized learning through CGAHW mainly helped the students in low and medium ability categories but not in high ability category. Overall, we developed and deployed an adaptive software in a field set up to show how IT enabled personalized learning could improve educational production with existing school resources. Our findings have significant policy implications for resources strapped educational systems in developing countries. ​

  4. 03.25.2016
    Dorothee Honhon
    • Associate Professor, Operations Management, Naveen Jindal School of Management
    • Bio:

      Dr. Dorothee Honhon is an Associate Professor of of Operations Management at the Jindal School of Management of the University of Texas at Dallas. She earned a PhD in Operations Management from New York University. Before joining the UT at Dallas, she was with the faculty of the McCombs School of Business of the University of Texas at Austin and the Eindhoven University of Technology, the Netherlands. Dorothee’s research interests include inventory management, assortment planning, retail operations, behavioral operations management and transportation theory. She has published papers in Management Science, Operations Research, Manufacturing & Service Operations Management, and Production and Operations Management, among other journals. Dorothee is an associate editor of Management Science, the Senior VP of meetings for the Women in OR/MS organization and the VP of communications for the POMS College of Supply Chain Management.

      In 2010, she received the Regents’ Outstanding Teacher Award from the Board of Regents of the University of Texas system and in 2011 she received the Trammell/CBA Foundation Teaching Award for Assistant Professors. Her paper “Assortment planning with vertically differentiated products” received the Wickham Skinner Best Paper Published in Production and Operations Management During 2012 Award.

    • “Learning About Customer Preferences from Clickstream Data”
    • 10:30am to 12:00pm at STZ 200


    We study the problem of an e-tailer who learns about consumer preferences from observing sales or clickstream data on his website in a Bayesian fashion. In each period, the e-tailer decides which products to display on the search page and which products to make available for purchase. We use a ranking-based model to represent consumer choice for two types of products: basic products for which consumers have well-defined preferences and fashion products for which consumers develop their preferences via browsing. We prove that, when the e-tailer learns from clickstream data, it may be optimal to include so-called phantom products, i.e. products which are shown on the search page but in fact unavailable for purchase. We also numerically estimate the value of learning from clickstream data versus learning from sales data only and find that the benefits of gathering clickstream data are significant, especially for fashion products.

Past Speakers

  1. 10.03.2014
    Jeffrey Hu
    • Associate Professor of Management, Director of China Program, Chief Scientist of Business Analytics Center, and Associate Director of Center for Data Analytics at Georgia Institute of Technology’s Scheller College of Business
    • Bio

    • “A Dynamic Structural Model for Heterogeneous Mobile Data Consumption and Targeted Promotion”
    • 10:30am—12noon at STZ 200
  2. 10.10.2014
    Anuj Kumar
    • Assistant Professor, Warrington College of Business Administration, University of Florida
    • Email (akumar1 at
    • Bio

    • “Impact of Facilitating Store Usage on Customers’ Online Purchase Behavior”
    • 10:30am—12noon at STZ 200
  3. 01.30.2015
    Rahul Telang
    • Professor, Information Systems and Management H. John Heinz III College, Tepper School of Business Carnegie Mellon University
    • Email (rtelang at

    • “What is a cookie worth?”
    • 10:30am—12noon at STZ 102
  4. 03.20.2015
    Dr. Gediminas Adomavicius
    • Professor in Carson School of Management, University of Minnesota
    • Email (gedas at

    • “De-Biasing User Preference Ratings in Recommender Systems”
    • 10:30am—12noon at Bryan 101A
  5. 04.17.2015
    Dr. Karthik Kannan
    • Associate Professor in Krannert School of management in University of Purdue
    • Email (kkarthik at

    • “Cardinality Bundling with Spence-Mirrlees Reservation Prices”
    • 10:30am—12noon at STZ 200
  1. 09.27.2013
    Ganesh Janakiraman
    • Professor of Operations Management
    • Naveen Jindal School of Management, The University of Texas at Dallas
    • Bio

    • “Analysis of Tailored Base-Surge Policies in Dual Sourcing Inventory Systems”
    • Bryan 101 A, 10:30-12:00 Noon
    • Abstract:

      We study a model of a firm managing its inventory of a single product by sourcing supplies from two supply sources, a regular supplier who offers a lower unit cost and a longer lead time than a second, emergency, supplier. A practically implementable policy for such a firm is a Tailored Base-Surge (TBS) Policy (Allon and Van Mieghem, 2010) to manage its inventory: Under this policy, the firm procures a constant quantity from the regular supplier in every period and dynamically makes procurement decisions for the emergency supplier. Allon and Van Mieghem describe this practice as using the regular supplier to meet a base level of demand and the emergency supplier to manage demand surges, and they conjecture that this practice is most effective when the lead time difference between the two suppliers is large. We confirm these statements in two ways. First, we show the following analytical result: When demand is composed of a base demand random component plus a surge demand random component, which occurs with a certain small probability, the best TBS Policy is close to optimal (over all policies) in a well defined sense. Second, we also numerically investigate the cost-effectiveness of the best TBS policy on a test bed of problem instances. The emphasis of this investigation is the study of the effect of the lead time difference between the two suppliers. Our study reveals that the cost difference between the best TBS policy and the optimal policy decreases dramatically as the lead time of the regular supplier increases. On our test bed, this cost difference decreases from an average (over the test bed) of 21 % when the lead time from the regular supplier is two periods (the emergency supplier offers instant delivery) to 3.5 % when that lead time is seven periods.

  2. 10.18.2013
    Martin K. Starr
    • Distinguished Professor of Production and Operations Management Emeritus, Crummer Graduate School of Business, Rollins College, Winter Park, Florida
    • Emeritus Senior Professor of Operations Research (OR), Management Science, and Operations Management, Graduate School of Business at Columbia University, New York City
    • Bio

    • “The Roles of POM and IT in Crisis (Disaster) Management”
    • Bryan 101 A, 10:30-12:00 Noon
    • Abstract:

      The field of crisis management works hand in glove with the body of knowledge and experience known as HO (humanitarian operations). It is also known as humanitarian logistics since supply chains are the means for bringing aid and assistance to those afflicted. Crisis management, CM, is an umbrella term under which HO is vested. These are different aspects of the same system known as HO&CM (the acronym used by the POMS College). The domain of research and application for HO&CM is relatively new and wide open. It requires an unusual combination of engineering and healthcare abilities. It also requires IT skills to allow data mining and analytics. POM provides real supply chain savvy. This incredible blend of multi-disciplinary interests has opened up a wonderful arena for PhD research. Its complex of inter-dependencies lends itself to analysis by system dynamics (viz., the bull whip effect). Publication experiences are discussed including the Special Issue of POM for HO&CM. A POM-IT partnership is better equipped than any other functional alliance to manage disrupted systems. The POM-IT cross-discipline partnership must keep the team informed about what is going on under chaotic circumstances. It is essential to be able to set up adequate processes for coping with trouble; to be able to anticipate future events (forecasting domino-type causality) on strong data-mining platforms that generate “big-data.” Failure at the “last mile” is discussed. The basic matrix of disaster management is presented. Cells are at the intersections of Timing (rows) and Crisis-Type (columns). The three Timing rows are defined as Before, During, and After. The three Crisis-Type columns are defined as Terror, Error, and Nature. HO applies to all nine cells but attention is paid mainly to the six cells encompassed by the two rows During and After. Different CM scenarios apply to all three cells in the Before row where early warning (EW) is a necessity to allow prevention and mitigation to apply. Operational Readiness initiatives for A2 are also discussed. The general state of research and publication concludes the discussion.

  3. 11.06.2013
    Ruoxuan Wang
    • PhD Candidate, ISOM Department, University of Florida
    • Bio

    • “Outsourcing for Power Disruptions”
    • Bryan 101A, 10:00-11:30am
    • Abstract:

      In the event of a large scale power disruption, many manufacturers are now outsourcing to a third party supplier. We model different types of contracts between a manufacturer and a supplier in the event of a disruption utilizing options contracts and game theory methodologies. While the literature on outsourcing is well developed, we find that the notion of outsourcing only in the case of a supply chain disruption has not been thoroughly explored. We develop theoretical results which show the specific mechanisms of different types of contracts which can effectively coordinate the supply chain. In particular, we create a policy for which the buyer asks for a specified level of capacity in the event of a disruption and the supplier has flexibility in determining the optimal capacity (i.e. voluntary compliance) but must pay a penalty for a potential shortage. Finally, numerical results show that the benefits of these types of contracts include (a) increased profit for the buyer, (b) increased flexibility for the supplier, and (c) increased risk mitigation for the buyer in the event of power disruption.

  4. 11.12.2013
    Mili Mehrotra
    • Assistant Professor, Supply Chain and Operations
    • Carlson School of Management, University of Minnesota

    • “Proposer Selection With Episode-Based Payment For Service Bundles”
    • Bryan 101A, 2:00pm-3:30pm
    • Abstract
  5. 12.04.2013
    Nazli Turken
    • PhD Candidate, ISOM Department, The University of Florida
    • Bio:

      Nazli holds a B.S. degree in Industrial Engineering from Penn State University and a M.E. degree in Industrial and Systems Engineering from University of Florida. Prior to entering the doctoral program, she worked as an industrial engineering and quality department intern at The Coca-Cola Bottlers of Turkey and Siemens Wiring Technologies and as a part of the Kaizen Team at Oyak-Renault Automotive Systems. Her current research interests include environmentally and socially responsible operations, innovation in healthcare and humanitarian operations.

  6. 01.31.2014
    Ananth V Iyer
    • Susan Bulkeley Butler Chair in Operations Management Faculty Director, Krannert School of Management, Purdue University, West Lafayette, IN 47907
    • Bio

  7. 03.21.2014
    Georgia Perakis
    • William F. Pounds Professor of Management, Professor of Operations Research and Operations Management, Co-Director of Leaders for Global Operations Program, MIT Sloan School of Management
    • Bio:

      Georgia Perakis is the William F. Pounds Professor at the Sloan School of Management at MIT since 1998. She received an M.S. degree and a PhD in Applied Mathematics from Brown University and a BA from the University of Athens in Greece. Perakis is currently visiting Columbia University as she is on sabbatical.

      Georgia Perakis' research interests include applications of operations research in many areas such as pricing, energy applications, supply chain management and transportation among others. She has widely published in journals such as Operations Research, Management Science, POM, Mathematics of Operations Research and Mathematical Programming among others. She has received the CAREER award from the National Science Foundation and subsequently, the PECASE award from the office of the President on Science and Technology awarded to the 50 top scientists and engineers in the nation. She has also received an honorable mention in the TSL Best Paper Award, the second prize in 2011 and the first prize in 2012 in the Best Paper competition of the Informs Service Science Section for two of her papers, the Graduate Student Council Teaching Award for excellence in teaching and the Samuel M. Seegal prize. Perakis was the recipient of the Sloan Career Development Chair and subsequently of the J. Spencer Standish Career Development Chair. In 2009, Perakis received the William F. Pounds chair that she currently holds. Perakis has passion supervising her students and builds lifelong relationships with them. So far she has graduated fifteen PhD and twenty two Masters students. She has been awarded recently the Samuel M. Seegal prize at MIT for “inspiring students to pursue and achieve excellence”.

      Perakis is currently serving as the co-director from the MIT Sloan School side for the Leaders for Global Operations (former LFM) program. She is also currently the group head of the Operations Management Group at MIT Sloan. She serves as an Associate Editor for the journals Management Science, Operations Research and Naval Logistics Research and a senior editor for POM. Perakis has served as a member of the INFORMS Council. She served as the chair of the Pricing and Revenue Management Section of INFORMS and in 2009-2010 as the VP for Meetings of the MSOM Society of INFORMS. She has co-organized the MSOM 2009 conference and served in the organizing committee of the 2010 MSOM conference. She has also been the co-chair and co-organizer of the Annual Conference of the INFORMS Section on Pricing and Revenue Management for several years and the chair of the cluster on the same topics for the annual INFORMS and ISMP conferences for several years.

    • “The Impact of Linear Optimization on Promotion Planning”
    • 10:30am—12noon, STZ 200
    • Abstract:

      In many important settings, promotions are key for driving sales and profits. Examples include promotions in supermarkets among others. The Promotion Optimization Problem (POP) is a challenging problem as the retailer needs to decide which products to promote, what is the depth of price discounts and finally, when to schedule the promotions.

      In this talk we introduce and discuss an optimization formulation that captures several important business requirements as constraints. We propose two general classes of demand functions depending on whether past prices have a multiplicative or an additive effect on current demand. These functions capture the promotion fatigue effect emerging from the stock-piling behavior of consumers and can be easily estimated from data. The objective is nonlinear (neither convex nor concave) and the feasible region has linear constraints with integer variables. Since the exact formulation is “hard”, we propose a linear approximation that allows us to solve the problem efficiently as a linear program by showing the integrality of the integer programming formulation. We develop analytical results on the accuracy of the approximation relative to the optimal (but intractable) POP solution by showing guarantees relative to the optimal profits.

      Together with our industry collaborators from Oracle Retail, our framework allows us to develop a tool which can help supermarket managers to better understand promotions by testing various strategies and business constraints. We show that the formulation we propose solves fast in practice using actual data from a grocery retailer and that the accuracy is high. We calibrate our models using actual data and determine that they can improve profits by 3% just by optimizing the promotion schedule and up to 5% by slightly modifying some business requirements.

  8. 04.18.2014
    Michael Pinedo
    • Julius Schlesinger Professor of Operations Management, Department of Information, Operations and Management Sciences, Leonard N. Stern School of Business, New York University
    • Bio

    • “Appointment Scheduling in Health Care with No-Shows and Overbooking”
    • 10:30am—12noon, Bryan 101A
    • Abstract
  1. 10.05.2012
    Anuj Kumar
    Assistant Professor of Information Systems Management
    Warrington College of Business Administration, University of Florida
    email (akumar1 at | bio

    “An Information Stock Model of Customer Behavior in Multichannel Customer Support Services”
    Stuzin 102, 11:00 to 12:00 Noon


    We propose a novel information stock-based framework to understand customer behavior in a multichannel customer support services scenario. We assume that a customer’s observed usage behavior is a stochastic function of her latent “information stock,” which is determined dynamically by the queries that arise as she uses the product and the assistance she obtains on contacting the firm’s support channels. We estimate our model on individual-customer-level data obtained from a US-based health insurance firm. Among many interesting results, we quantify the efficacy of different support channels in terms of resolving customers’ queries, and find that, in our setting, the telephone channel offers significantly greater value than the web channel. Our model can also be used to aid in call center management and staffing decisions as it provides accurate predictions for future query volumes, and can identify customers who are expected to have high telephone call volumes in the near future.

  2. 10.26.2012
    Prof Shantanu Bhattacharya
    Associate Professor of Operations Management

    “The Role of Milestone-Based Contracts for Coordinating R&D Partnerships”
    Bryan 101A, 10:30-12:00 Noon


    We analyze optimal contractual arrangements in a bilateral R&D partnership between a risk-averse provider that conducts early-stage research, followed by a regulatory verification stage, and a risk-neutral client that performs late-stage development activities, including production, distribution, and marketing. The problem is formulated as a sequential investment game with the client as the principal, where the investments are observable but not verifiable. The model captures the inherent incentive alignment problems of double-sided moral hazard, risk aversion and holdup. We compare the efficacy of milestone-based options contracts and buyout options contracts from the client's perspective, and identify conditions under which they attain the first-best outcome for the client. We find that milestone options contracts always attain the first-best outcome for the client when the provider has some bargaining power in renegotiation, and identify their applicability to different R&D partnerships.

  3. 12.07.2012
    Zhi Li
    Ph.D. Job Candidate, ISOM Department
    Warrington College of Business Administration, University of Florida

    “Cloud Computing Spot Pricing Dynamics: Latency and Limits to Arbitrage”
    Bryan 101 A, 10:30-12:00 Noon


    In this paper, we examine cloud computing pricing dynamics across east and west Amazon EC2 markets and test for the influence of latency as a pricing wedge in the observed pricing dynamics. Without limits to arbitrage, theory predicts that there should not be any persistent pricing differentials for the same good across markets. We hypothesize that latency differentials create pricing wedges across cloud computing markets. In our analysis, we use various econometric modeling approaches and intra-day Amazon EC2 spot instance pricing data as well as intra-day latency data over the April 9, 2010 to May 22, 2011 sample period. We find that there is considerable time variation in spot instance prices and that prices in the west are often persistently greater than prices in the east over our sample period. Results from using a bivariate VAR model of east and west spot instance prices suggest that there are significant dynamic pricing relations both within and across the east and west markets. The within market autoregressive pricing effect is larger than the across market effect, but there are also significantly pronounced across market pricing effects. We also find that a large portion of the relative price discovery (over 70%) occurs in the east market relative to the west market. To explain the observed time varying pricing differentials across the east and west markets, we use both regression procedures and an Error Correction model (ECM). We find that both east and west latency differentials have a significantly positive effect on the pricing differentials. These results suggest that larger (smaller) latency effects result in larger (smaller) pricing differentials; in effect, latency creates a dynamic pricing wedge that widens or narrows conditional on the latency differentials. From the ECM results, we also find that the speed of adjustment from long run pricing convergence errors causes the short run price differential to narrow, but the adjustment is only partial. From a broader perspective, this paper provides some further evidence and insights into market-based pricing dynamics and market efficiency issues in a burgeoning new market with unique characteristics, including latency effects.

  4. 12.11.2012
    Mei Lin
    Assistant Professor of Information Systems and Management
    Singapore Management University
    bio | cv

    “Dynamic Two-Sided Pricing Under Sequential Innovation”
    Stuzin 102, 10:30-12:00 Noon


    Technology innovation engenders products of higher qualities and reduces production costs. This paper focuses on a two-sided platform tied with quality-improving hardware devices that are introduced sequentially. We analyze a monopolist's dynamic pricing strategies facing decreasing future production cost and strategic buyers. Findings in both the traditional (buyer-side only) and two-sided business models show that future cost reductions raise the optimal price of the present product, which shifts the buyer-side demand forward and mitigates inter-temporal cannibalization. Furthermore, future cost reductions may also lead to a higher optimal price for the future product, given a substantial quality improvement. Thus, the monopolist may leverage future cost reductions to position its product line to the high-end market. By comparing the traditional and two-sided business models, we find that the impact of future cost reductions is more pronounced for a two-sided platform.

  5. 02.22.2013
    Sandra Slaughter
    Alton M. Costley Chair and Professor of Information Technology Management
    Scheller College of Business, Georgia Institute of Technology

    “Are Software Contracts Effective? The Impacts of Contract Type and Repeated Contracting on Software Development Outsourcing Outcomes”
    Stuzin 101, 10:30-12:00 Noon


    Departing from prior research that focuses on the ex ante conditions predicting contract type, we investigate the consequences of contract type on a wide array of performance outcomes associated with software development outsourcing. Drawing on agency theory and institutional economics, we hypothesize that contract type (fixed price-FP, Hybrid, time and materials-T&M) with its varying inherent incentive properties will engender differential software development performance outcomes in terms of technical design verification quality, cost and schedule performance, and client validation quality. We further posit that repeated contracting should improve software development performance outcomes as repeated contractual experiences serve to mitigate issues of adverse selection and moral hazard. We tested our hypotheses using feasible generalized least squares and spline regression to analyze longitudinal archival data on software development contracts and performance outcomes drawn from a large software vendor for a major client. Results show that, consistent with our contract type hypotheses, FP contracts produce the best - and Hybrid contracts produce the worst - technical outcomes of design verification quality, cost performance and schedule performance. Further both T&M and Hybrid contracts yield higher client validation quality than FP contracts. Contrary to our repeated contracting hypotheses, we found that repeated contracting does not always improve performance outcomes. Instead, repeated contracting serves more to ‘reinforce’ the incentives associated with a particular contract type. These results have important implications for research on software development contracts and for managerial practice.

  6. 03.29.2013
    Ritu Agarwal
    Professor and Robert H. Smith Dean’s Chair of Information Systems
    University of Maryland

    “Vocal Minority and Silent Majority: How do Online Ratings Reflect Population Perceptions of Quality?”
    Stuzin 101, 10:30-12:00 Noon


    Recently, the Internet has fostered a rapid rise in consumer-generated ratings. However, limited research has examined how these ratings reflect the opinions of the population at large, notably in the domain of professional services, where quality is often opaque to consumers. Building on the word-of-mouth research literature, we examine the relationship between online ratings and the offline population’s perception of physician quality. A distinctive feature that differentiates this study from prior work is a unique dataset that includes direct measures of both the offline population’s perception of physician quality, and consumer generated online reviews. These data allow us to examine how closely the online ratings reflect patients’ opinion about physician quality at large. We find, in sharp contrast to the widely voiced concerns by medical practitioners, that physicians who are rated lower in quality by the patient population are less likely to be rated online. Additionally, although ratings provided online are correlated with patient population opinions, the online ratings tend to be exaggerated at the ends of the quality spectrum. This study is one of the first to provide empirical evidence of the relationship between online ratings and the underlying consumer perceived quality. It also extends prior research on online word-of-mouth to the domain of professional services.

  7. 04.11.2013
    Paul A. Pavlou
    Professor of Management Information Systems, Marketing, and Strategic Management
    Stauffer Senior Research Fellow
    Fox School of Business at Temple University

    “Are Global Labor Markets Truly “Flat”? Global Frictions, Labor Arbitrage, and Reputation Signals in Online Markets”
    Bryan 101 A, 10:30- 12:00 Noon


    Visionaries conjecture that the world is becoming a level (“flat”) playing field due to the Internet that connects professional workers with employers anywhere around the world. To examine this “flat world” conjecture for global online labor markets for software development services, we analytically model and empirically examine the key factors that affect the dual aspects - pricing of professional service providers and their selection by clients (employers): (1) global frictions, (2) labor arbitrage and (3) reputation signals. We first model and derive the equilibrium pricing strategy of service providers via backward induction of a two-stage game (which includes the client’s selection of a service provider given the provider’s bid price), and we propose a set of hypotheses about the key factors that affect both the providers’ pricing and also their selection by clients. We empirically test our hypotheses with an integrated dataset formed by a random sample (473,970 price bids for 27,450 service projects) from the transaction data from an global online labor marketplace for software development services matched with multiple archival sources (e.g., purchasing power parity (PPP) across countries, language, time-zone, and cultural differences). The results from our econometric analyses show that when submitting their price bids, service providers take into account global frictions (particularly language differences), try to exploit labor arbitrage opportunities with labor low PPP countries, and take advantage of their own reputation signals. In turn, clients avoid global frictions (language, time zone, and cultural differences) and favor providers with strong reputation signals from high PPP countries. Interestingly, online labor markets are not truly level (“flat”) playing fields due to the proposed global frictions that are detrimental to both the service providers’ and clients’ surplus. We discuss theoretical and managerial implications for designing “flatter” global online labor markets.

  8. 05.10.2013
    Yong Tan
    Neal and Jan Dempsey Professor of Information Systems
    Michael G. Foster School of Business, University of Washington

    “Feel Blue so Go Online: An Empirical Study of Online Supports among Patients”
    Stuzin 101, 10:30-12:00 Noon


    This paper investigates whether an online healthcare community benefits patients’ mental health. We propose an inhomogeneous Partially Observed Markov Decision Process (POMDP) model to examine the latent health outcomes of online health community members. The transition between different health states is modeled as a probability function that incorporates different forms of social support that patients receive via online communication, and other factors that impact patients’ online behaviors. We find that patients gain benefits from learning from others, and their participation in the online community helps them to improve their health condition and better engage in their disease self-management processes. Our results also reveal the effectiveness of various forms of social support on the dynamic evolution of patients’ health conditions. We find measurable evidence that informational support is the most-sought support in the online healthcare community. However, emotional support plays the most significant role in helping patients move to a healthier state. The helpfulness of social supports is found to vary with patients’ health conditions. Finally, we demonstrate that our proposed POMDP model can provide accurate predictions for patients’ health states, and it can be used to recover missing or unavailable information on patients’ health conditions.


College Info

Warrington College of Business
BRY 100
PO Box 117150
Gainesville, FL 32611-7150
Phone: 352.392.2397
Fax: 352.392.2086

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