Mingfeng Lin is an Associate Professor of Information Technology Management (ITM) and the ITM PhD Program Coordinator at the Scheller College of Business, Georgia Institute of Technology. He studies financial technologies (FinTech), Internet-enabled communities and markets, as well as business models as drivers of innovation and entrepreneurship. Specifically he has done or is conducting research on:
Prior to joining Georgia Tech in summer 2018, he was an Associate Professor in the MIS Department, Eller College of Management, University of Arizona. His CV is available here, and his ORCID page is at:
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Ph.D. in Business and Management
Robert H. Smith School of Business, University of Maryland, College Park (2005-2010)
Master of Arts in Economics
University of Maryland, College Park (2002-2004)
Master of Arts in Economics
School of Economics, Peking University (2000-2002)
Bachelor of Arts in Economics
School of Economics, Peking University (1996-2000)
I am interested in empirical studies of online markets and communities, especially two types of markets: online crowdfunding and online labor markets. I am particularly interested in validating, or proposing, various mechanisms that can help mitigate the issue of information asymmetry (or trust) between different stakeholders of the market. I am also interested in empirical studies of interactions among consumers, or between consumers and businesses.
Please see below for a list of my published papers, and papers that are currently under review at journals (regardless of which round) or have been publicly presented, but not yet published. Research-in-progress is not listed. My SSRN page is http://ssrn.com/author=703780.
Click on the titles to view abstracts. Links to journal websites and SSRN (if available) are provided for each article as well. Please contact me directly if you need any of the following published papers for research purposes.
Peer-Reviewed Journal Publications
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.
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.
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.
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.
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.
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.
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.
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, Prosper.com, 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.
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.
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 DonorsChoose.org, 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.
Currently under revision.
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 Prosper.com’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.
The dynamics between coexisting experts and non-experts has important implications for online market and platform design. We study their relationship in the context of crowdfunding. While crowdfunding originated as a non-expert market, experts have become active participants. We investigate the costs and benefits associated with experts competing with non-experts during a unique period in one crowdfunding market when every investor was given the same unambiguous signal of relative valuation. Contrary to previous evidence, we find that experts are substantially better than non-experts at using common information to evaluate project success. Moreover, because experts overinvest in the best projects, experts outperform non-experts who invest more heavily in worse projects. Thus, expert participation in crowdfunding markets has both positive and negative implications for these platforms. On the positive side, experts increase the efficiency of these markets, which can drive both borrowers and lenders to the market. On the negative side, the higher returns garnered by experts are at the expense of non-expert investors. Surprisingly, however, the latter effects are quite small. Our findings provide an important contribution to understanding the relationship between experts and non-experts in online markets.
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.
Third-party skill certification is widely used in many markets, online and offline, to address the ubiquitous information asymmetry between workers and employers. In online labor markets, however, the usefulness of third-party certification is not yet fully established in that some leading platforms tout its effectiveness whereas others abandon it altogether. It is unclear whether such certifications exert a meaningful influence on the recruitment decisions of employers (i.e., buyers) and whether they reveal the quality of employees (i.e., workers). In addition, there is no ex-ante theoretical consensus about whether certification attempts should be offered free of charge. Using a comprehensive dataset from one of the largest online labor markets, we first study whether certifications are desirable for employers when they make recruitment decisions. We then examine whether certifications actually do reflect worker quality (therefore serving as a valid economic signal) by examining their ex-post performance after being hired. We further examine how zero-cost certification tests affect the above relationships by exploiting data surrounding a policy change on the platform. Our findings show that employers do prefer workers with certifications over those without, and justifiably so: Workers with certifications do outperform those without certifications. Certifications are especially helpful for new workers in obtaining jobs, especially workers who have not yet accumulated ratings. Contrary to some theoretical arguments, offering certification tests free of charge actually reduces the signaling value of certifications: It negatively affects employers’ preference for certified workers.
Preliminary draft of the paper is available upon request.
Working paper available soon.
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.
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.
Peer-Reviewed Conference Proceedings
Data preparation and visualization for MBA students at the Scheller College.
Introduces Scheller ITM PhD students to empirical economic studies in information systems and related disciplines.
Introduces data visualization principles and best practice to undergraduate business students at Scheller College.
Teaches principles of project management using a combination of lectures, tutorials, and simulations.
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.
Teaches principles of project management using a combination of lectures, tutorials, and simulations. Starting from 2015, this class is delivered fully online.
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.
Teaches principles of project management using a combination of lectures, tutorials, simulations and team assignments. Delivered fully online.
Teaches principles of project management using a combination of lectures, tutorials, simulations and team assignments. Delivered fully online.
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:
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(This list may not be up to date. Please see my CV for a full list.)
(Please see CV for a full list.)
Please right click here (PDF format) to download, or see a preview below.
This is a slightly abbreviated version of my CV and does not list detailed status of my papers under review. Please contact me directly if you need a full copy. Thank you.