• Ph.D. 2010

    Ph.D. in Business and Management

    Robert H. Smith School of Business, University of Maryland, College Park (2005-2010)

  • M.A.2004

    Master of Arts in Economics

    University of Maryland, College Park (2002-2004)

  • M.A.2002

    Master of Arts in Economics

    School of Economics, Peking University (2000-2002)

  • B.A.2000

    Bachelor of Arts in Economics

    School of Economics, Peking University (1996-2000)

Honors, Awards and Grants

  • 2024
    Georgia Tech,CIOS Honor Roll
  • 2022
    Melvyn P. and Eleanor N. Galin Creativity Award, Scheller College of Business, Georgia Institute of Technology
  • 2020
    INFORMS Conference on Information Systems and Technology (CIST), Nomination for Best Student Paper
    For paper on search engine precision, available on SSRN .
  • 2020
    International Conference on Information Systems, Best Paper in Track
    For paper on search engine precision, available on SSRN .
  • 2019
    Keynote Speaker, the 7th CrowdInvesting Symposium (Berlin, Germany)
  • 2019
    Management Science Meritorious Service Award
  • 2017
    Sandy Slaughter Early Career Award (Awarded by INFORMS Information Systems Society)
  • 2016
    Emerald Citations of Excellence for 2016
    For Lin, Viswanathan and Prabhala (2013), "Judging borrowers by the company they keep: Friendship networks and information asymmetry in online peer-to-peer lending."
  • 2016
    Management Science Meritorious Service Award
  • 2016
    Eller College Small Research Grant
    With Wei Chen (project on equity crowdfunding). Eller College of Management, University of Arizona.
  • 2016
    Kalt Prize for doctoral student placement
    Eller College of Management, University of Arizona.
  • 2015
    Management Science Best Paper Award in Information Systems
  • 2015
    Management Science Distinguished Service Award
  • 2015
    University of California Santa Cruz, Center for Analytical Finance, Small Research Grant
    To study the role of diversity in online crowdfunding.
  • 2015
    Kauffman Foundation Research Grant
    Funding from Kauffman Foundation to study women entrepreneurs in equity crowdfunding, using data from US and UK.
  • 2015
    Eller College Small Research Grant
    Funding to study equity crowdfunding.
  • 2015
    Wharton Customer Analytics Initiative Research Proposal Competitions
    BazaarVoice and Equilar
  • 2015
    Nomination for INFORMS CIST Best Conference Paper Award
    For paper coauthored with Zaiyan Wei (institutional investors in online debt crowdfunding).
  • 2014
    Management Science Distinguished Service Award
  • 2014
    Nomination for INFORMS CIST Best Conference Paper Award
    For paper coauthored with Qiang Gao (informational value of texts in online crowdfunding).
  • 2013
    McGuire Center for Entrepreneurship, Interdisciplinary Research Grant
    Funding to study signaling in online labor markets; joint with Yong Liu (Eller Marketing)
  • 2012
    NET Institute Summer Research Grant
    Funding to study online labor markets.
  • 2012
    Nomination for INFORMS CIST Best Conference Paper Award
    For paper coauthored with Siva Viswanathan and Yong Liu (effect of reputation under contracts in online labor markets).
  • 2011
    McGuire Center for Entrepreneurship, Small Research Grant
    Funding to study online labor markets.
  • 2010
    NET Institute, Summer Research Grant
    Funding to study online labor markets.
  • 2010
    Paine Award for Academic Excellence
    Robert H. Smith School of Business, University of Maryland, College Park
  • 2009
    Nomination for ICIS Best Conference Paper Award
    For paper coauthored with Siva Viswanathan and N.R. Prabhala (social networks in online peer-to-peer lending).
  • 2009
    Best Doctoral Student Paper Award, INFORMS CIST
    For paper coauthored with Siva Viswanathan and N.R. Prabhala (social networks in online peer-to-peer lending).
  • 2009
    Kauffman Foundation Dissertation Fellowship Grant
    Funding from Kauffman Foundation for dissertation support (online crowdfunding, and online labor markets).
  • 2009
    Economic Club of Washington Doctoral Fellowship Grant
    Funding for dissertation support (online crowdfunding, and online labor markets).
  • 2009
    Research Grant for Social Value Creation, R.H.Smith School of Business
    Funding for research on microfinance and online crowdfunding for third world countries.

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Peer-Reviewed Journal Publications

Higher Precision is Not Always Better: Search Algorithm and Consumer Engagement

Wei Zhou, Mingfeng Lin, Mo Xiaoand Lu Fang.
E-Commerce and Online Community Management Science, forthcoming.


On decentralized e-commerce platforms, search algorithms play a critical role in matching buyers and sellers. A typical search algorithm routinely refines and improves its catalog of data to increase search precision, but the effects of more precise search are little known. We evaluate such effects via a 2019 quasi-experiment on a world-leading e-commerce platform, in which the search algorithm refined some product categories into finer subgroups to allocate consumer queries to more relevant product listings. Our data cover millions of consumers’ search and purchase behaviors over six months across multiple search sessions and product categories, enabling us to investigate tradeoffs over time and across categories. We find that a more precise search algorithm improves consumers’ click-through and purchase rates drastically and instantaneously, but it comes at the cost of a significant decrease in consumer engagement and unplanned purchases over a longer time horizon. On average, consumers who used to spend more time searching now conduct 5.5% fewer searches, spend 4.1% less time on the platform, and decrease their spending on related categories by 2.2% in the week after the search precision increases. Our examination of the mechanisms behind these consequences calls for more careful search algorithm designs that account for not only instant conversion based on search precision, but also consumer engagement and sellers’ strategic responses in the longer horizon.

Experts vs. Non-Experts in Online Crowdfunding Markets

Mingfeng Lin, Richard Siasand Zaiyan Wei.
Crowdfunding MIS Quarterly (2023), Volume 47, Issue 1, Pages 97-126


The growth of crowdfunding markets that include both expert and non-expert investors will soon accelerate due to recent changes in Securities Exchange Commission (SEC) regulations. Work suggests that non-experts (1) may benefit from experts’ participation via mimicking their trades, but (2) will also face a cost as experts crowding non-experts out of the best opportunities ensures that non-experts will suffer lower returns than experts. Traditional economic theory holds that the crowding effect means the relative importance of non-experts in the market will decline over time until they become unimportant. Exploiting a unique period in one crowdfunding market ( that allows us to directly estimate the net cost of competing with better informed experts, we find that the net negative effects of expert participation on non-experts are small. We use simulations to both better understand (1) the market characteristics and crowdfunding platform choices that influence experts’ and non-experts’ returns, their return gap, and the extent to which non-experts are better or worse off relative to a market without expert participation, and (2) the factors that may contribute to the small expert/non-expert Prosper return gap.

Words Matter: The Role of Texts in Online Credit Markets

Qiang Gao, Mingfeng Lin, and Richard Sias.
Crowdfunding Journal of Financial and Quantitative Analysis (2023), Volume 58, Issue 1, Pages 1-28.


Using online debt crowdfunding data, we show that borrower’s writing style is associated with both borrower and lender behavior. Borrowers whose writing is more readable, more positive, and has fewer deception cues are less likely to default. Moreover, lenders appear to recognize this, as more readable, more positive tone, and fewer deception cues are all associated with a higher likelihood of funding and lower interest rate, even when controlling for hard credit and other borrower characteristics. Investors, however, fail to fully account for the information contained in borrowers’ writing especially with respect to deception cues, i.e., although borrowers with greater deception cues face higher rates, the rate is not high enough to offset the additional default risk.

Educational Crowdfunding and Student Performance: An Empirical Study

Qiang Gao, Mingfeng Lin, and DJ Wu.
CrowdfundingInformation Systems Research (2020), Volume 32, Issue 1, Pages 53-71


Despite the growing popularity of online education crowdfunding, controversy remains as to whether teachers’ efforts to use this channel are justified and whether donations thus received can actually make a difference. We present the first empirical evidence of the use and impact of education crowdfunding donations after campaign success. Using data on California public school teachers and their students as well as the teachers’ fundraising activities on, we find that students’ academic performance improves after their teacher successfully raises funding on the platform. This finding survives a large number of robustness tests. More importantly, through a series of tests, we show that this positive impact is partly due to the nonfinancial benefits of receiving online crowdfunding donations. Our study contributes not only to the literature on crowdfunding and charitable giving but also ongoing debates on the financing of public education.

Do Electronic Health Records Affect Quality of Care? Evidence from the HITECH Act

Yukai Lin, Mingfeng Lin, and Hsinchun Chen
OtherInformation Systems Research (2019), Volume 30, issue 1, pp 306-318


The 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act is landmark legislation that places electronic health record (EHR) technologies at the center of health system reform in the United States. However, despite their promises, studies in the EHR evaluation literature have found mixed evidence of EHRs’ quality benefits. In contrast to existing research that has focused on EHR investments or adoption, we propose that its actual use should be the focus in evaluating the advantages of EHRs. We leveraged the meaningful use (MU) provisions of the HITECH Act to quantify different degrees of EHR use in a large and heterogeneous set of hospitals. The results provided evidence of EHRs’ positive effects on quality of care and reconciled earlier mixed findings by showing that their benefits vary according to different levels of use and hospital characteristics. Specifically, we found that while adopting EHR had no significant quality impact, attaining MU of EHR yielded a significant 0.19–0.43 percentage point increase in process quality of care, which further translates into significant societal benefits. The effect sizes were larger in disadvantaged (i.e., small and rural) hospitals, suggesting the potential of EHRs in mitigating the disparities in the quality of healthcare. This study contributes to this ongoing discussion and the literature on EHR evaluations and use of information systems. Implications for research, policy, and practice are discussed.

When More is Less: Field Evidence on Unintended Consequences of Multitasking

Paulo Goes, Noyan Ilk, Mingfeng Lin, and Leon Zhao
E-Commerce and Online CommunityManagement Science (2018), Volume 64, Issue 7, Pages 3033-3054


Online customer service chats provide new opportunities for firms to interact with their customers, and are increasingly popular in recent years for firms of all sizes. One reason for their popularity is the ability for customer service agents to multitask, i.e., interact with multiple customers at a time, thereby increasing the system “throughput” and agent productivity. Yet, little is known of how multitasking impacts customer satisfaction, the ultimate goal of customer engagements. We address this question using a proprietary dataset from an S&P 500 service firm that documents agent multitasking activities (unobservable to customers) in the form of server logs, customer service chat transcripts and post-service customer surveys. We find that agent multitasking leads to longer in-service delays for customers, and also lower problem resolution rates. Both lead to lower customer satisfaction. Meanwhile, such impact on satisfaction also varies by different customers. Our study is among the first to document the link between multitasking and customer satisfaction, and has implications for the design of agent time allocation in contact centers, and more broadly for how firms can best manage customer relations in new service channels enabled by IT.

Effectiveness of Reputation in Contracting for Customized Production: Evidence from Online Labor Markets

Mingfeng Lin, Yong Liu, and Siva Viswanathan
Online Labor MarketsManagement Science (2018), Volume 64, Issue 1, Pages 345-359


This study examines the effects of reputation in the nascent but rapidly growing online labor markets. In these markets contract winners (vendors) provide clients with customized products such as computer software, business plans and artistic designs. The products are used primarily for business purposes and require time for production after project-specific contracts are awarded. These characteristics render it unclear whether online reputation will have similar effects as in online retailing, where finished and standardized products are sold for consumption. We analyze field transaction data from a major online labor market. The analyses using matched contract samples and vendor panels consistently show that, despite the governing power provided by contracts as well as the litigation and arbitration options, vendors’ online reputation can still be influential on clients. Vendors who have no reputation ratings are less likely to be chosen, and those with higher ratings are more likely to win subsequent bids. Importantly, however, such influences depend on the contract form that is used for a particular transaction—they are significant in output-based contracts but non-significant in input-based contacts. Besides extending the research on online reputation to the markets of customized production, this study shows contract form as an important boundary condition for the effectiveness of reputational information. It also provides direct managerial implications for electronic commerce in general and online labor markets in particular.

Market Mechanisms in Online Peer-to-Peer Lending

Zaiyan Wei and Mingfeng Lin
CrowdfundingManagement Science (2017), Volume 63, Issue 12, Pages 4236-4257


Online Peer-to-Peer lending (P2P lending) has emerged as an appealing new channel of financing in recent years. A fundamental but largely unanswered question in this nascent industry is the choice of market mechanisms, i.e., how the supply and demand of funds are matched, and the terms (price) at which transactions will occur. Two of the most popular mechanisms are auctions (where the "crowd" determines the price of the transaction through an auction process) and posted prices (where the platform determines the price). While P2P lending platforms typically use one or the other, there is little systematic research on the implications of such choices for market participants, transaction outcomes, and social welfare. We address this question both theoretically and empirically. We first develop a game-theoretic model that yields empirically testable hypotheses, taking into account the incentive of the platform. We then test these hypotheses by exploiting a regime change from auctions to posted prices on one of the largest P2P lending platforms. Consistent with our hypotheses, we find that under platform-mandated posted prices, loans are funded with higher probability, but the pre-set interest rates are higher than borrowers' starting interest rates and contract interest rates in auctions. More important, all else equal, loans funded under posted prices are more likely to default, thereby undermining lenders' returns on investment and their surplus. Although platform-mandated posted prices may be faster in originating loans, auctions that rely on the "crowd" to discover prices are not necessarily inferior in terms of overall social welfare.

Do Incentive Hierarchies Induce User Effort? Evidence from an Online Knowledge Exchange

Paulo Goes, Chenhui Guo, and Mingfeng Lin
E-Commerce and Online CommunityInformation Systems Research (2016), Volume 27, Issue 3, Pages 497-516


UGC (User-generated content) websites routinely deploy incentive hierarchies, where users achieve increasingly higher status in the community after achieving increasingly more difficult goals, to motivate users to contribute. Yet the existing empirical literature remains largely unclear whether such hierarchies are indeed effective in inducing user contributions. We gathered data from a large online crowd-based knowledge exchange to answer this question, and drew on the goal setting theory to study users’ contributions before and after they reach consecutive levels of a vertical incentive hierarchy. We found evidence that even though these “glory”-based incentives may motivate users to contribute more before the goals are reached, user contribution levels dropped significantly after that. In other words, the cumulative effect appears only temporary. Our results hence highlight some unintended and heretofore undocumented effects of incentive hierarchies, and have important implications for business models that rely on user contributions, such as knowledge exchange and crowdsourcing, as well as the broader phenomenon of “gamification” in other contexts.

Home Bias in Online Investments: An Empirical Study of An Online Crowdfunding Market

Mingfeng Lin, Siva Viswanathan
CrowdfundingManagement Science (2016), Volume 62, Issue 5, Pages 1393-1414


An extensive literature in economics and finance has documented “home bias,” the tendency that transactions are more likely to occur between parties in the same geographical area, rather than outside. Using data from a large online crowdfunding marketplace and employing a quasi-experimental design, we find evidence that home bias still exists in this virtual marketplace for financial products. Furthermore, through a series of empirical tests, we show that rationality-based explanations cannot fully explain such behavior, and that behavioral reasons at least partially drive this remarkable phenomenon. As crowdfunding becomes an alternative and increasingly appealing channel for financing, a better understanding of home bias in this new context provides important managerial, practical, and policy implications.

"Popularity Effect" in User-Generated Content: Evidence from Online Product Reviews

E-Commerce and Online Community Information Systems Research (2014), Volume 25, Issue 2, Pages 222-238.


Online product reviews are increasingly important for consumer decisions, yet we still know little about how reviews are generated in the first place. In an effort to gather more reviews, many websites encourage user interactions such as allowing one user to subscribe to another. Do these interactions actually facilitate the generation of product reviews? More importantly, what kind of reviews do such interactions induce? We study these questions using data from one of the largest product review websites where users can subscribe to one another. By applying both panel data and a flexible matching method, we find that as users become more popular, they produce more reviews and more objective reviews; however, their numeric ratings also systematically change and become more negative and more varied. Such trade-off has not been previously documented and has important implications for both product review and other user-generated content websites.

Judging Borrowers by the Company They Keep: Friendship Networks and Information Asymmetry in Online Peer-to-Peer Lending

CrowdfundingManagement Science (2013), Volume 59, Issue 1, Pages 17-35


We study the online market for peer-to-peer (P2P) lending, in which individuals bid on unsecured microloans sought by other individual borrowers. Using a large sample of consummated and failed listings from the largest online P2P lending marketplace,, we find that the online friendships of borrowers act as signals of credit quality. Friendships increase the probability of successful funding, lower interest rates on funded loans, and are associated with lower ex post default rates. The economic effects of friendships show a striking gradation based on the roles and identities of the friends. We discuss the implications of our findings for the disintermediation of financial markets and the design of decentralized electronic markets.

Too Big to Fail: Large Samples and the p-Value Problem

Mingfeng Lin, Hank Lucas, Galit Shmueli
Other Information Systems Research (2013), Volume 24, Issue 4, Pages 906-917.


The Internet has provided IS researchers with the opportunity to conduct studies with extremely large samples, frequently well over 10,000 observations. There are many advantages to large samples, but researchers using statistical inference must be aware of the p-value problem associated with them. In very large samples, p-values go quickly to zero, and solely relying on p-values can lead the researcher to claim support for results of no practical significance. In a survey of large sample IS research, we found that a significant number of papers rely on a low p-value and the sign of a regression coefficient alone to support their hypotheses. This research commentary recommends a series of actions the researcher can take to mitigate the p-value problem in large samples and illustrates them with an example of over 300,000 camera sales on eBay. We believe that addressing the p-value problem will increase the credibility of large sample IS research as well as provide more insights for readers.

Working Papers

Revealed Wisdom of the Crowd: Bids Predict Loan Quality

Under review. Coauthored with Jiayu Yao and DJ Wu

Traditional studies on the wisdom of the crowd focus on member characteristics that are either static (e.g., demographics) or slow to change (e.g., expertise). However, members of a crowd are different not only in terms of who they are but also what they do when faced with different opportunities. Using data from online debt crowdfunding, we propose and find significant informational value in the heterogeneity of observable actions of crowd members. We quantify investor behavior in two ways: bid size and bid timing. We find that loans funded with fewer but larger bids are less likely to default than those funded with a larger number of smaller bids. For loans with similar bid-amount distributions, those receiving larger bids earlier in the bidding process are less likely to default. These features also help improve the predictive performance of loan default models. Importantly, these features are easily accessible and less subject to privacy concerns. Our findings point to a novel direction of extracting wisdom of the crowd, new methods of evaluating loan quality in secondary markets, and have implications for the design of online crowdsourcing platforms in general.

When "Signals" Boomerang: Employers' Reactions to a Novel Signaling Mechanism

Under review. Coauthored with Yong Liu and Qiang Gao. Under review.
Online Labor Markets


Signaling mechanisms are prevalent in two-sided markets because they typically help reduce information asymmetry and improve efficiency. While a growing number of studies focus on the actions of signal-senders, there has been little empirical research on how signal-receivers may react to the signals, despite the importance of this question. A well-intentioned signal could backfire, or "boomerang," if the receiver does not react the way that its sender or designer intends. The introduction of a novel project-specific, voluntary guarantee-deposit ("guarantee" for short) in an online labor market provides an excellent opportunity to answer this question. Leveraging detailed transaction data, we study how employers (signal-receivers) react to the presence guarantees in the bids placed by workers (signal-senders). We find strong evidence that, despite the platform's advocacy for the benefits of providing a guarantee, employers are less likely to award contracts to workers who use this signaling mechanism than those who do not. This is particularly prominent when uncertainty about the project or worker is high. Only workers who already possess high customer ratings improve their chances of winning contracts by offering such a guarantee. These results indicate that employers do not just ignore this novel signal, but use it to "counter-screen" workers. In other words, this well-intentioned "signal" boomerangs (or backfires) for most workers who need them the most. Remarkably, such employers' reactions seem economically justified: Workers who offer guarantees are less likely to perform well on the job compared to those who do not. The level of sophistication the employers demonstrate regarding the signaling mechanism in online labor markets is striking. Our findings provide fresh nuances to the signaling literature in two-sided markets and have implications for platform designs.

The Effect of Secondary Market Existence on Primary Market Liquidity: Theory and Evidence from a Natural Experiment in Peer-to-Peer Lending

Under review. Coauthored with Craig Holden, Kai Lu, Jun Yang, and Zaiyan Wei.


We develop a theoretical model of a primary market either with or without a secondary market for any type of risky security. We find that the existence of a secondary market increases primary market liquidity in the form of lower effective spreads and higher issuance quantities. The same underlying intuition suggests shorter funding time as well. We then use the unexpected closure of’s secondary market to study how the secondary market existence affects primary market liquidity, as well as the spillover effect on the primary market liquidity of a prime competitor. Uniquely, our comprehensive intraday issuance data for the primary market allows us to precisely measure the liquidity of the primary market. We find that the closure of Prosper’s secondary market reduces primary market liquidity in all three standard dimensions: time, cost, and quantity. Specifically, Prosper’s primary market liquidity is reduced because it takes longer to fund loans both by individuals and by institutions, requires a higher origination fee to fund loans by individuals, and the percentage of loans funded by both individuals and institutions also decreases. Further, we find that the closure of Prosper’s secondary market leads to a positive primary market liquidity spillover for Lending Club by reducing its time to fund by individuals.

All That Glitters Is Not Gold: The Impact of Certification Costs In Online Labor Markets

Under review. Coauthored with Jiaru Bai, Qiang Gao and Paulo Goes.
Online Labor Markets


Third-party skill certification is widely used to address the ubiquitous information asymmetry between workers and employers. When more workers attempt certification exams, the market should become more transparent, and the reduced information asymmetry should enable more transactions to occur. A natural way to encourage workers to take certification exams is to make the certification tests free. However, neither theoretical nor empirical studies have examined how the decision to offer free tests influences this emerging marketplace. This research fills this gap. First, we develop a stylized model to hypothesize the possible effects of zero-cost certification tests on the recruitment decisions of employers and their transaction amounts (i.e., contract prices) with workers at both job and platform levels. Second, we empirically test these hypotheses by exploiting a natural experiment that occurred when one of the largest online labor markets unexpectedly removed its certification test fees. Contrary to the platform's expectations, the offering of free certification tests reduced the signaling value of the certifications: Employers' preference for certified workers decreased (both in terms of hiring likelihood and price paid). More importantly, such preference change appeared economically justified, as workers certified under the new policy are less likely to deliver high-quality work. Furthermore, the fall in signaling value is particularly high for inexperienced workers who are still in the process of accruing reviews and are thus more dependent on certifications to secure work. The findings remained consistent over the longer term during our study period. Our results provide strong support for the study’s theoretical propositions and have important implications for platforms and practitioners in online labor markets.

Spatial Distribution of Online Alternative Finance: Field Evidence from the UK Crowdfunding Industry

Coauthored with Bryan Zhang. Manuscript in preparation.

Working paper available soon.

"Banking" on the Internet: Does Internet Banking Really Improve Bank Performance?

Coauthored with Hank Lucas and Joseph Bailey.


Internet banking represents an important innovation in the banking industry, yet empirical analyses of how it affects bank performance remain rare. Using a comprehensive dataset of U.S. banks between 2003 and 2008, we combine propensity-score matching and difference-in-differences methods to study how the adoption of Internet banking affects bank performance. Contrary to common wisdom and several previous studies, we find only modest evidence that Internet banking adoption improves bank performance. In fact, the adoption of Internet banking actually results in worse performance for many banks. Additional analyses suggest that younger banks and banks that are earlier adopters are more likely to enjoy the benefits of Internet banking.

Book Chapters

An Overview of Technologically Enabled Finance

David Brown and Mingfeng Lin
Crowdfunding Handbook of Alternative Finance, edited by Raghavendra Rau, Robert Wardrop, and Luigi Zingales.

Technologically-enabled finance, or FinTech, is the application of new technologies to financial activities. Broadly speaking, FinTech developments fall into two general areas of finance: matching capital supply with demand and personal finance. In each area, we discuss a range of topics, from microlending, peer-to-peer lending and credit monitoring, to crowdfunding, cryptocurrencies and robo-advisors. In some cases, such as credit decisioning, new technologies can make finance more efficient, but also raise potential concerns related to the use and security of information. In other cases, such as crowdfunding or cryptocurrencies, new technologies have the potential to fundamentally change how finance operates. We highlight businesses that are pushing the boundaries of finance and we discuss open questions of interest to practitioners, regulators and academics.

Out of the Shadow? Promises and Chellenges of Peer-to-Peer Lending

Mingfeng Lin
Crowdfunding Research Handbook on Shadow Banking: Legal and Regulatory Aspects (forthcoming), edited by Iris H. Chiu and Iain MacNeil.
(Draft available upon request.)

Peer-Reviewed Conference Proceedings

Can Social Networks Mitigate Information Asymmetry in Online Markets

Mingfeng Lin, Siva Viswanathan and N. Prabhala
Crowdfunding Proceedings of the 30th International Conference on Information Systems (2009)

Peer-to-peer Lending: An Empirical Investigation

Mingfeng Lin
Crowdfunding Proceedings of the 2009 America's Conference on Information Systems (2009)

Bidder Migration

Mingfeng Lin, Wolfgang Jank
Other Proceedings of the 2008 America's Conference on Information Systems (2008)

Current Courses

  • Present 2019

    Business Data Preparation and Visualization

    Data preparation and visualization for MBA students (full time and evening MBAs) at the Scheller College.

  • Present 2019

    Phd Seminar: Empirical Studies in Information Systems

    Introduces Scheller ITM PhD students to empirical economic studies in information systems and related disciplines.

  • Present 2018

    Business Data Preparation and Visualization

    Introduces data visualization principles and best practice to undergraduate business students at Scheller College.

  • 2018 2018

    Project Management

    Teaches principles of project management using a combination of lectures, tutorials, and simulations.

Previously Taught

  • 2018 2016

    Economics of Information Systems (PhD Seminar), University of Arizona

    Introduces PhD students to economics of information systems (applying theories and research methods in economics to subjects of interest in information systems). To start in the fall of 2016.

  • 2018 2011

    Project Management (Undergraduate), University of Arizona

    Teaches principles of project management using a combination of lectures, tutorials, and simulations. Starting from 2015, this class is delivered fully online.

  • 2018 2011

    Business Foundations for IT (MS in MIS)

    Focuses on critical thinking and communication skills for MS in MIS students. Uses a combination of lectures, team-based case competitions (debates), data visualization and analyses, and guest lectures. The lectures cover basic principles in strategy, marketing, and other non-IT aspects of business.

  • 2018 2014

    Project Management (Online MBA)

    Teaches principles of project management using a combination of lectures, tutorials, simulations and team assignments. Delivered fully online.

  • 2018 2015

    Project Management (MIS Online)

    Teaches principles of project management using a combination of lectures, tutorials, simulations and team assignments. Delivered fully online.

  • 2008 2007

    Introduction to Management Information Systems

    Taught this as a PhD student in the R.H.Smith School of Business, University of Maryland, College Park. For undergraduate students (Fall 2007).

The best way to reach me is via email, but you can also reach me using other methods listed here. Please leave a voice message if you call. The mailing address for my office is:

  •                         Scheller College of Business
  •                         800 West Peachtree Street, N.W.
  •                         Georgia Institute of Technology
  •                         Atlanta, GA 30308

Google Map for Scheller College:

  •    office: +1(404)894-4921
  •    /in/mingfeng
  • September 2017

    Eli Broad College of Business, Michigan State University

  • July 2017

    China Summer Workshop on Information Management (CSWIM)

  • January 2017

    Scheller College of Business, Georgia Institute of Technology

  • December 2016
  • December 2016

    Tsinghua University, PBC School of Finance

  • Apr. 2016

    Carnegie Mellon University, Tepper School of Business

  • Feb. 2016

    Kauffman Emerging Scholars Conference (scheduled)

  • Nov. 2015

    Weiland Speaker Series, Department of Marketing, University of Arizona

  • Oct. 2015

    Simon School of Business, University of Rochester

  • Oct. 2015

    MIS Speaker Series, MIS Department, University of Arizona

  • Sep. 2015

    Third Annual Acadmic Symposium on Crowdfunding, University of California, Berkeley

  • May 2015

    Industry Studies Conference, Kansas City, MO

  • Apr. 2015

    Workshop on “Financial Access, New Platforms for Finance,” Center for Analytical Finance at the University of California, Santa Cruz

  • Feb. 2015

    Rady School of Business, University of California, San Diego

  • Jan. 2014

    Scheller College of Business, Georgia Institute of Technology

  • Oct. 2013

    Smeal College of Business, Pennsylvania State University

  • Oct. 2013

    Academic Symposium on Crowdfunding, University of California, Berkeley

  • Oct. 2013

    Conference on Information Systems and Technology (CIST)

  • Feb. 2013

    Department of Economics, University of Arizona

  • Dec. 2012

    Workshop on Information Systems and Economics (WISE)

  • Oct. 2012

    Conference on Information Systems and Technology (CIST); INFORMS Annual Meeting

  •       PhD Coordinator, Information Technology Management (ITM) Area, Scheller College of Business, Georgia Institute of Technology
  •       Conference Co-chair, INFORMS Conference on Information Systems and Technology (CIST) 2020 (Program)
  •       Conference Co-chair, MIS Teaching Workshop (2020)
  •       Track Co-chair, International Conference on Information Systems (2018), Economics and Information Systems
  •       Associate Editor, Information Systems Research
  •       Associate Editor, Information Systems ResearchSpecial Issue on Digital Infrastructure and Platforms
  •       Advisory board member,
  •       Co-Chair and Program Committee Member, , International Summit on Smart Finance (May 2016)
  •       Mentor, Kauffman Entrepreneurship Mentoring Workshop (January 2016, 2017)
  •       Associate Editor, International Conference on Information Systems (ICIS) (2013, 2014, 2016)
  •       Associate Editor, European Conference on Information Systems (ICIS) (2016)
  •       Cluster Co-Chair, INFORMS Annual Meeting, eBusiness Cluster (2015)
  •       Track Co-Chair, International Conference on Electronic Commerce (2014)
  •       Track Co-Chair, Pacific Asia Conference on Information Systems (Economics of IS Track) (2012)
  •       Program Committee member, INFORMS Conference on Information Systems and Technology (CIST) (2010-present)
  •       Program Committee member, China Summer Workshop on Information Management (CSWIM) (2014, 2015, 2016)
  •       Conference Co-Chair, Statistical Challenges in Electronic Commerce Research (SCECR) (2011)