@article{yu_mankad_shunko_2023, title={Evidence of the Unintended Labor Scheduling Implications of the Minimum Wage}, volume={6}, ISSN={["1526-5498"]}, url={https://doi.org/10.1287/msom.2023.1212}, DOI={10.1287/msom.2023.1212}, abstractNote={ Problem definition: The effect of the minimum wage is an important yet controversial topic that has received attention for decades. Our study is the first to take an operational lens and empirically study the impact of the minimum wage on firms’ scheduling practices. Methodology/results: Using a highly granular data set from a chain of fashion retail stores, we estimate that a $1 increase in the minimum wage, although having a negligible impact on the total labor hours used by the stores, leads to a 27.7% increase in the number of workers scheduled per week, but a 19.4% reduction in weekly hours per worker. For an average store in California, these changes translate into four extra workers and five fewer hours per worker per week. Such scheduling adjustment not only reduces the total wage compensation per worker but also reduces workers’ eligibility for benefits. We also show that the minimum wage increase reduces the consistency of weekly and daily schedules for workers. For example, the absolute (relative) deviation in weekly hours worked by each worker increases by up to 32.9% (6.6%) and by up to 9.7% (2.1%) in daily hours, as the minimum wage increases by $1. Managerial implications: Our study empirically identifies and highlights a new operational mechanism through which increasing the minimum wage may negatively impact worker welfare. Our further analysis suggests that the combination of the reduced hours, lower eligibility for benefits, and less consistent schedules (that resulted from the minimum wage increase) may substantially hurt worker welfare, even when the overall employment at the stores stay unchanged. By better understanding the intrinsic tradeoff of firms’ scheduling decisions, policy makers can better design minimum wage policies that will truly benefit workers. }, journal={M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT}, author={Yu, Qiuping and Mankad, Shawn and Shunko, Masha}, year={2023}, month={Jun} }
 @article{brunetti_harris_mankad_2023, title={Networks, interconnectedness, and interbank information asymmetry}, volume={67}, ISSN={["1878-0962"]}, url={https://doi.org/10.1016/j.jfs.2023.101163}, DOI={10.1016/j.jfs.2023.101163}, abstractNote={We explore interconnectedness in the interbank overnight lending market and propose the liquidity network and the urgent borrower network which capture the urgency to trade. The liquidity network connects the initiating party in a trade to the passive party, while the urgent borrower network connects passive sellers (lenders) to urgent buyers (borrowers). Along with the buyer/seller trading network, we show these networks complement each other, revealing valuable information that improves short-term forecasts of soft and hard information and country-specific yield spreads. Connectivity increases in these networks during raises volatility and boosts volume, revealing the dual nature of interconnectedness—too much interconnectedness may increase systemic risk, but too little may impede market functioning.}, journal={JOURNAL OF FINANCIAL STABILITY}, author={Brunetti, Celso and Harris, Jeffrey H. and Mankad, Shawn}, year={2023}, month={Aug} }
 @article{schneider_hu_mankad_bale_2023, title={Protecting the anonymity of online users through Bayesian data synthesis}, volume={216}, ISSN={["1873-6793"]}, url={https://doi.org/10.1016/j.eswa.2022.119409}, DOI={10.1016/j.eswa.2022.119409}, abstractNote={Privacy concerns emerge when online users of popular user-generated content (UGC) platforms are identified through a combination of their structured data (e.g., location and name) and textual content (e.g., word choices and writing style). To overcome this problem, we introduce a Bayesian sequential synthesis methodology for organizations to share structured data adjoined to textual content. Our proposed approach enables platforms to use a single shrinkage parameter to control the privacy level of their released UGC data. Our results show that our synthesis strategy decreases the probability of identification of a user to an acceptable threshold while maintaining much of the textual content present in the structured data. Additionally, we find that the value of sharing our protected data exceeds that of sharing the unprotected structured data and textual content separately. These findings encourage UGC platforms that wish to be known for consumer privacy to protect anonymity of their online users with synthetic data.}, journal={EXPERT SYSTEMS WITH APPLICATIONS}, author={Schneider, Matthew J. and Hu, Jingchen and Mankad, Shawn and Bale, Cameron D.}, year={2023}, month={Apr} }
 @article{ma_mankad_2022, title={CP-Squared: A method for change point detection in core–periphery networks}, volume={196}, url={https://doi.org/10.1016/j.eswa.2022.116660}, DOI={10.1016/j.eswa.2022.116660}, abstractNote={Time series of networks are increasingly prevalent in modern data and pose unique challenges to pattern extraction and change detection. In this paper we develop and present a novel methodology to detect regime changes within a sequence of networks that have overlapping and evolving community structure. The core of the methodology is a non-negative matrix factorization that maximizes a Poisson likelihood subject to a penalty that accounts for sparsity in the network. By fitting the factorization model over a rolling window with a fast numerical optimization algorithm, change detection is accomplished by statistical monitoring of the matrix factors’ evolution. A novel statistic is used to characterize the overall network evolution as well as the contribution of each node to the change. We demonstrate that the proposed methodology compares favorably with alternative techniques for on-the-go network change detection using synthetic and real data. A detailed case study on the 2007–2009 financial crisis and the European sovereign debt crisis shows the promise of the methodology for regulators as it identifies particular banks that contributed to each crisis in addition to identifying changing market conditions.}, journal={Expert Systems with Applications}, publisher={Elsevier BV}, author={Ma, Desheng and Mankad, Shawn}, year={2022}, month={Jun}, pages={116660} }
 @article{brunetti_harris_mankad_2022, title={Sidedness in the interbank market}, volume={59}, url={https://doi.org/10.1016/j.finmar.2021.100663}, DOI={10.1016/j.finmar.2021.100663}, abstractNote={We study the motivations of traders in the interbank market around the 2007–2009 subprime crisis. We extend the market sidedness of Sarkar and Schwartz (2009) to a panel setting to study the dispersion of beliefs for banks domiciled in different European countries. We find that country-level sidedness reveals information from the interbank market: sidedness leads sovereign credit default swap (CDS) spreads and reacts to central bank interventions introduced during the crisis. Our results map the linkages between the interbank market and sovereigns, as well as provide insight on the channels that give rise to the sovereign-bank nexus. • We study the motivations of traders in the interbank market around the 2007-09 subprime crisis using Sidedness of Sarkar and Schwartz (2009). • We estimate Sidedness within a panel setting using a regression-based formulation. • We show Sidedness from a European interbank market Granger causes (sometimes with feedback) sovereign CDS spreads. • Sidedness reacts to central bank interventions introduced during the crisis.}, journal={Journal of Financial Markets}, publisher={Elsevier BV}, author={Brunetti, Celso and Harris, Jeffrey H. and Mankad, Shawn}, year={2022}, month={Jun}, pages={100663} }
 @article{brunetti_harris_mankad_2022, title={The urgency to borrow in the interbank market}, volume={221}, ISSN={["1873-7374"]}, url={https://doi.org/10.1016/j.econlet.2022.110900}, DOI={10.1016/j.econlet.2022.110900}, abstractNote={We study the motivations of interbank market traders around the 2007–09 subprime crisis with a new statistic, Trading Urgency, that reveals the underlying urgency to borrow overnight funds. We find that Trading Urgency leads sovereign CDS spreads and reacts to non-standard central bank interventions introduced during the crisis. Our results shed light on the channels that give rise to the sovereign-bank nexus by mapping the linkages between the interbank market and sovereigns.}, journal={ECONOMICS LETTERS}, author={Brunetti, Celso and Harris, Jeffrey H. and Mankad, Shawn}, year={2022}, month={Dec} }
 @article{brunetti_harris_mankad_2021, title={Liquidity Networks, Interconnectedness, and Interbank Information Asymmetry}, url={https://doi.org/10.17016/FEDS.2021.017}, DOI={10.17016/FEDS.2021.017}, abstractNote={Network analysis has demonstrated that interconnectedness among market participants results in spillovers, amplifies or absorbs shocks, and creates other nonlinear effects that ultimately affect market health. In this paper, we propose a new directed network construct, the liquidity network, to capture the urgency to trade by connecting the initiating party in a trade to the passive party. Alongside the conventional trading network connecting sellers to buyers, we show both network types complement each other: Liquidity networks reveal valuable information, particularly when information asymmetry in the market is high, and provide a more comprehensive characterization of interconnectivity in the overnight-lending market.}, journal={Finance and Economics Discussion Series}, author={Brunetti, Celso and Harris, Jeffrey H. and Mankad, Shawn}, year={2021}, month={Mar} }
 @article{mejia_mankad_gopal_2021, title={Service Quality Using Text Mining: Measurement and Consequences}, url={https://doi.org/10.1287/msom.2020.0883}, DOI={10.1287/msom.2020.0883}, abstractNote={ Problem description: Measuring quality in the service industry remains a challenge. Existing methodologies are often costly and unscalable. Furthermore, understanding how elements of service quality contribute to the performance of service providers continues to be a concern in the service industry. In this paper, we address these challenges in the restaurant sector, a vital component of the service industry. Academic/practical relevance: Our work provides a scalable methodology for measuring the quality of service providers using the vast amount of text in social media. The quality metrics proposed are associated with economic outcomes for restaurants and can help predict future restaurant performance. Methodology: We use text present in online reviews on Yelp.com to identify and extract service dimensions using nonnegative matrix factorization for a large set of restaurants located in a major city in the United States. We subsequently validate these service dimensions as proxies for service quality using external data sources and a series of laboratory experiments. Finally, we use econometrics to test the relationship between these dimensions and restaurant survival as additional validation. Results: We find that our proposed service quality dimensions are scalable, match industry standards, and are correctly identified by subjects in a controlled setting. Furthermore, we show that specific service dimensions are significantly correlated with the survival of merchants, even after controlling for competition and other factors. Managerial implications: This work has implications for the strategic use of text analytics in the context of service operations, where an increasingly large text corpus is available. We discuss the benefits of this work for service providers and platforms, such as Yelp and OpenTable. }, journal={Manufacturing & Service Operations Management}, author={Mejia, Jorge and Mankad, Shawn and Gopal, Anandasivam}, year={2021}, month={Nov} }
 @article{mejia_mankad_gopal_2019, title={A for Effort? Using the Crowd to Identify Moral Hazard in New York City Restaurant Hygiene Inspections}, volume={30}, url={https://doi.org/10.1287/isre.2019.0866}, DOI={10.1287/isre.2019.0866}, abstractNote={ From an upset stomach to a life-threatening foodborne illness, getting sick is all too common after eating in restaurants. Although health inspection programs for restaurants are designed to protect consumers, such inspections typically occur sporadically, allowing restaurant hygiene to remain unknown for diners. At the same time, online reviews for restaurants provide a valuable source of information about the current status and quality of a restaurant. In this paper, we use the text contained in these reviews of restaurants to effectively identify cases of hygiene violations in restaurants, even after the restaurants have been inspected. Using data about restaurant hygiene in New York City from 2010 through 2016 and the associated set of online reviews for the same set of restaurants from Yelp, we use supervised machine learning techniques to develop a hygiene dictionary specifically crafted to identify hygiene-related problems. With this dictionary, we report systematic instances of moral hazard, wherein restaurants with positive hygiene inspection scores are seen to regress in their hygiene maintenance within 90 days of receiving the inspection scores. Based on these results, we provide strategies for how cities and policymakers may design effective restaurant inspection programs. }, number={4}, journal={Information Systems Research}, publisher={Institute for Operations Research and the Management Sciences (INFORMS)}, author={Mejia, Jorge and Mankad, Shawn and Gopal, Anandasivam}, year={2019}, month={Dec}, pages={1363–1386} }
 @article{brunetti_harris_mankad_michailidis_2019, title={Interconnectedness in the interbank market}, volume={133}, number={2}, journal={Journal of Financial Economics}, publisher={Elsevier}, author={Brunetti, Celso and Harris, Jeffrey H and Mankad, Shawn and Michailidis, George}, year={2019}, pages={520–538} }
 @article{mankad_michailidis_kirilenko_2019, title={On the formation of Dodd-Frank Act derivatives regulations}, url={https://doi.org/10.1371/journal.pone.0213730}, DOI={10.1371/journal.pone.0213730}, abstractNote={Following the 2007-2009 financial crisis, governments around the world passed laws that marked the beginning of new period of enhanced regulation of the financial industry. These laws called for a myriad of new regulations, which in the U.S. are created through the so-called notice-and-comment process. Through examining the text documents generated through this process, we study the formation of regulations to gain insight into how new regulatory regimes are implemented following major laws like the landmark Dodd-Frank Wall Street Reform and Consumer Protection Act. Due to the variety of constituent preferences and political pressures, we find evidence that the government implements rules strategically to extend the regulatory boundary by first pursuing procedural rules that establish how economic activities will be regulated, followed by specifying who is subject to the procedural requirements. Our findings together with the unique nature of the Dodd-Frank Act translate to a number of stylized facts that should guide development of formal models of the rule-making process.}, journal={PLOS ONE}, author={Mankad, Shawn and Michailidis, George and Kirilenko, Andrei}, editor={Kiss, Hubert JanosEditor}, year={2019}, month={Mar} }
 @article{brunetti_harris_mankad_2018, title={Bank Holdings and Systemic Risk}, url={https://doi.org/10.17016/feds.2018.063}, DOI={10.17016/FEDS.2018.063}, abstractNote={The recent financial crisis has focused attention on identifying and measuring systemic risk. In this paper, we propose a novel approach to estimate the portfolio composition of banks as function of daily interbank trades and stock returns. While banks’ assets are reported to regulators and/or the public at relatively low frequencies (e.g. quarterly or annually), our approach estimates bank asset holdings at higher frequencies which allows us to derive precise estimates of (i) portfolio concentration within each bank—a measure of diversification—and (ii) common holdings across banks—a measure of market susceptibility to propagating shocks. We find evidence that systemic risk measures derived from our approach lead, in a forecasting sense, several commonly used systemic risk indicators.}, journal={Finance and Economics Discussion Series}, author={Brunetti, Celso and Harris, Jeffrey H. and Mankad, Shawn}, year={2018}, month={Aug} }
 @article{mankad_hu_gopal_others_2018, title={Single stage prediction with embedded topic modeling of online reviews for mobile app management}, volume={12}, number={4}, journal={The Annals of Applied Statistics}, publisher={Institute of Mathematical Statistics}, author={Mankad, Shawn and Hu, Shengli and Gopal, Anandasivam and others}, year={2018}, pages={2279–2311} }
 @article{baker_haydar_mankad_2017, title={A feedback and evaluation system that provokes minimal retaliation by trainees}, volume={126}, number={2}, journal={Anesthesiology: The Journal of the American Society of Anesthesiologists}, publisher={The American Society of Anesthesiologists}, author={Baker, Keith and Haydar, Bishr and Mankad, Shawn}, year={2017}, pages={327–337} }
 @article{xia_mankad_michailidis_2016, title={Measuring influence of users in Twitter ecosystems using a counting process modeling framework}, volume={58}, number={3}, journal={Technometrics}, publisher={Taylor & Francis}, author={Xia, Donggeng and Mankad, Shawn and Michailidis, George}, year={2016}, pages={360–370} }
 @article{understanding online hotel reviews through automated text analysis_2016, volume={8}, url={http://dx.doi.org/10.1287/serv.2016.0126}, DOI={10.1287/serv.2016.0126}, abstractNote={ Customer reviews submitted at Internet travel portals are an important yet underexplored new resource for obtaining feedback on customer experience for the hospitality industry. These data are often voluminous and unstructured, presenting analytical challenges for traditional tools that were designed for well-structured, quantitative data. We adapt methods from natural language processing and machine learning to illustrate how the hotel industry can leverage this new data source by performing automated evaluation of the quality of writing, sentiment estimation, and topic extraction. By analyzing 5,830 reviews from 57 hotels in Moscow, Russia, we find that (i) negative reviews tend to focus on a small number of topics, whereas positive reviews tend to touch on a greater number of topics; (ii) negative sentiment inherent in a review has a larger downward impact than corresponding positive sentiment; and (iii) negative reviews contain a larger variation in sentiment on average than positive reviews. These insights can be instrumental in helping hotels achieve their strategic, financial, and operational objectives. }, number={2}, journal={Service Science}, publisher={Institute for Operations Research and the Management Sciences (INFORMS)}, year={2016}, month={Jun}, pages={124–138} }
 @article{mankad_michailidis_2015, title={Analysis of multiview legislative networks with structured matrix factorization: Does Twitter influence translate to the real world?}, journal={The Annals of Applied Statistics}, publisher={JSTOR}, author={Mankad, Shawn and Michailidis, George}, year={2015}, pages={1950–1972} }
 @article{brunetti_harris_mankad_michailidis_2015, title={Interconnectedness in the Interbank Market}, url={https://doi.org/10.17016/feds.2015.090}, DOI={10.17016/FEDS.2015.090}, abstractNote={We study the behavior of the interbank market before, during and after the 2008 financial crisis. Leveraging recent advances in network analysis, we study two network structures, a correlation network based on publicly traded bank returns, and a physical network based on interbank lending transactions. While the two networks behave similarly pre-crisis, during the crisis the correlation network shows an increase in interconnectedness while the physical network highlights a marked decrease in interconnectedness. Moreover, these networks respond differently to monetary and macroeconomic shocks. Physical networks forecast liquidity problems while correlation networks forecast financial crises.}, journal={Finance and Economics Discussion Series}, author={Brunetti, Celso and Harris, Jeffrey H. and Mankad, Shawn and Michailidis, George}, year={2015}, month={Oct} }
 @article{tang_banerjee_michailidis_mankad_2015, title={Two-Stage Plans for Estimating the Inverse of a Monotone Function}, volume={57}, number={3}, journal={Technometrics}, publisher={Taylor & Francis}, author={Tang, Runlong and Banerjee, Moulinath and Michailidis, George and Mankad, Shawn}, year={2015}, pages={395–407} }
 @article{mankad_michailidis_2014, title={Biclustering three-dimensional data arrays with plaid models}, volume={23}, number={4}, journal={Journal of Computational and Graphical Statistics}, publisher={Taylor & Francis}, author={Mankad, Shawn and Michailidis, George}, year={2014}, pages={943–965} }
 @article{mankad_michailidis_kirilenko_2013, title={Discovering the ecosystem of an electronic financial market with a dynamic machine-learning method}, volume={2}, number={2}, journal={Algorithmic Finance}, publisher={IOS Press}, author={Mankad, Shawn and Michailidis, George and Kirilenko, Andrei}, year={2013}, pages={151–165} }
 @article{mankad_michailidis_2013, title={Structural and functional discovery in dynamic networks with non-negative matrix factorization}, volume={88}, url={http://dx.doi.org/10.1103/physreve.88.042812}, DOI={10.1103/physreve.88.042812}, abstractNote={Time series of graphs are increasingly prevalent in modern data and pose unique challenges to visual exploration and pattern extraction. This paper describes the development and application of matrix factorizations for exploration and time-varying community detection in time-evolving graph sequences. The matrix factorization model allows the user to home in on and display interesting, underlying structure and its evolution over time. The methods are scalable to weighted networks with a large number of time points or nodes and can accommodate sudden changes to graph topology. Our techniques are demonstrated with several dynamic graph series from both synthetic and real-world data, including citation and trade networks. These examples illustrate how users can steer the techniques and combine them with existing methods to discover and display meaningful patterns in sizable graphs over many time points.}, number={4}, journal={Physical Review E}, publisher={American Physical Society (APS)}, author={Mankad, Shawn and Michailidis, George}, year={2013}, month={Oct} }