Stevens Business Faculty Help Shape Industry Future with Groundbreaking Research

The Stevens School of Business faculty continued its remarkable momentum in scholarly publishing, research productivity and academic impact. In 2024-25, SSB faculty members secured publication of 16 research articles across some of the most prestigious academic journals in business and management on the Financial Times 50 (FT50) and UT-Dallas 24 (UTD24) lists, representing not just quantity, but a sustained commitment to advancing knowledge at the highest levels of academic rigor and scholarly excellence.

Publications have appeared in elite outlets including Management Science, Information Systems Research, Journal of Applied Psychology, Operations Research, and MIS Quarterly – journals that represent the pinnacle of academic achievement in their respective fields. Remarkably, Stevens faculty FT50 publications have surged by more than 400 percent since 2012, reflecting both the school's strategic investment in research excellence and the exceptional caliber of its academic community.

The breadth of research topics covered by Stevens faculty demonstrates the school's comprehensive approach to understanding modern business challenges. From artificial intelligence and digital transformation to leadership psychology and financial markets, faculty members are tackling the most pressing issues facing organizations today. Their work blends traditional business disciplines with emerging intersections between technology, human behavior and organizational dynamics. This ensures that Stevens graduates are exposed to innovative thinking across the full spectrum of business knowledge.

The following deeper dive into four of the recent publications exemplify the scope, quality and impact of Stevens School of Business research.

Practitioner Experiences with Digitization in Human Resource Management

Human Resource Management Journal, Published online June 2025.

Thomas M. Begley, Pete Dominick, Gregory Prastacos, Dimitra Iordanoglou, Theano Lianidou, Marc Marchese

This study explores how HR professionals handle major technology changes within their own departments. HR practitioners were interviewed to understand their experiences implementing digital tools and systems. The research shows that technology adoption in HR follows a pattern involving three key elements: the technology itself, the organization, and the people using it. This combination affects three main outcomes, including day-to-day operations, how well HR aligns with company goals, and HR's strategic role in the business. Finding shows that different HR areas — like recruiting, payroll and training — adopt technology at different speeds and use different tools. Some HR functions are more digitally advanced than others, creating a spectrum of technological maturity across departments. Technology implementation in HR isn't a one-time event. It’s an ongoing cycle of introducing new tools, making adjustments and refining processes. Success requires continuous adaptation rather than expecting immediate, perfect results. These findings help HR leaders better plan and manage their technology transformations.

From the Authors

Explain your research findings in terms that would be accessible to someone outside your field?

Dominick: Much of the academic and practitioner literature about digital technologies and transformation focuses on what people and organizations should do. This has especially been the case in relation to the Human Resources function. We were interested in better understanding the actual experience of HR practitioners. We wanted to get answers to questions like what were the biggest challenges they faced in practice? Which HR subfunctions were most/least being transformed? To what extent is digital transformation moving across HR subfunctions? To do this we especially focused on two kinds of technology, AI/algorithms/automation and Big data/analytics.

Prastacos: HR is becoming one of the most critical corporate functions. With the increasing emphasis on talent and the continuous change in skills due to the digital technologies, the importance of HR cannot be overstated. This research examines how digital transformation happens in an HR department. It focuses on how HR practitioners experience the implementation of significant changes to policies and practices within their own function due to digital transformation. By coding transcripts from semi‐structured interviews with practitioners, we confirmed a model of HR digitalization that relates technology, organization and people (TOP) to its operational, strategic alignment and strategic integration consequences. We also found that each of seven major HR subfunctions uses different technologies to digitalize and at different paces of implementation, that we can array HR subfunctions along a continuum of consequences as they digitalize, and that technology implementation advances dynamically as it iterates over time through cycles of development and adjustment.

What originally inspired you to pursue this particular research topic or problem?

Dominick: This research was a direct result of the Managing Curriculum in the Digital Era (MaCuDe) Project sponsored by Stevens, AACSB and PwC. Its goal has been to examine how digital technology is transforming today’s workplace so that business schools can evolve what and how they teach, and ultimately better prepare students to thrive and innovate in the Digital Era. HR was just one of the functions that were a focus for the MaCuDe Project. Gregory actually spearheaded the entire MaCuDe initiative, but we were grateful that he had a particular professional interest in the Management and HR subgroup that conducted this particular research.

Prastacos: This research was part of a major project, MaCuDE, whose objective was to revise the management curriculum for the digital era. One phase of the project involved meeting with managers and leaders in various sectors and roles in order to better understand how the digital technologies are changing their role, their function and their business. The project was organized in nine task forces, each task force looking into a specific management function – finance, accounting, marketing, operations, and so one. This specific task force looked into HR and met with more than 60 HR managers across a multitude of industries and countries.

Why is this research important right now? What gap in knowledge or understanding does it address?

Dominick: It can be overwhelming to keep up with the pace, challenges and opportunities digital technologies are bringing. This work sheds light on what that experience is like for HR practitioners. It helps bridge the gap between what is recommended as best practice and what is occurring in day to day.

Prastacos: Every organization and every unit within an organization, including its HR division, is at some phase of its digital transformation. This paper looks at the experiences of HR managers and practitioners and can be of help in preparing them for success.

What are the practical applications of your findings? How might this research be used in the real world?

Dominick: It offers HR practitioners a roadmap for moving from one stage of digitalization to the next and gives them a framework to gauge where their digitalization efforts are at. It also can help them to discern the strategic implications of their transformation efforts. Finally, it helps to humanize the digital transformation process. For example, virtually everyone we interviewed for this study endorsed digital transformations, but they also acknowledged the uncertainty that it can bring and the ways in which people had to adapt to new roles as a result.

Prastacos: With the growing importance of HR, it is important that the digital transformation effort in which every organization is embarks on, succeeds. Hopefully, this paper helps HR practitioners understand major elements of digitalization. It identifies stages of digitalization their subfunctions occupy, anticipates activities characterizing next steps in the process, and considers resources available and types of technologies needed to move to the next stage

Where do you see this research leading next? What questions has it opened for future investigation?

Dominick: The model we developed can be used to look at if, or how, there are differences in HR digitalization experiences across industries or even in relation to other factors like size or geographic location. It can also be used to look at the digitalization processes in other functions like marketing or finance. We also think it is worth using this framework to look at other kinds of changes and innovations, whether they are digital or not.

Prastacos: It would be important to explore how the digitalization process and experiences described here relate to other functions of the firm, and/or to other industries or cultures.

Nonparametric Estimation of Sponsored Search Auctions and Impact of Ad Quality on Search Revenue

Management Science, Published online April 2025

Pallavi Pal & Dongwoo Kim

This study examines how online advertising auctions work, specifically how companies bid for ad placement on search engines like Yahoo! or Google. When users search for something, multiple advertisers compete to show their ads, and search engines rank these ads based on both how much advertisers bid and the quality of their ads. The researchers developed a mathematical model to understand how advertisers decide what to bid when they don't know what their competitors are bidding. Using real data from Yahoo!, they analyzed bidding patterns across different product categories and estimated how much advertisers actually value different ad placements. The authors then tested what would happen if search engines changed their quality scoring systems. Their results show that the best scoring strategy depends on how competitive the market is for each product category.

From the Author

What was the core question you set out to answer?

Pal: We looked at how platforms like Google or Yahoo! decide which ads appear when you search for something. These ads aren’t just picked randomly. They go through a behind-the-scenes auction where advertisers bid for your attention. Our core question was how can these platforms rank ads in a way that makes them the most money? What we found was surprising. Showing the “best” ad isn’t always the most profitable choice. If the platform makes the ranking too accurate, say, always putting the most relevant ad on top, then other advertisers stop trying. That means less bidding, less competition, and lower prices. Ironically, the platform can earn more by making the rankings less perfect, essentially blurring the match just enough to keep everyone bidding.

Why is this research important right now? What gap in knowledge or understanding does it address?

Pal: Online ads drive the internet economy — Google alone earns over $200 billion a year from them. Yet, we still don’t fully understand how ad auctions work behind the scenes. Our work shines a light on the hidden trade-off platforms face between showing the best ads and maximizing their own revenue. It helps explain why you might see less personalized ads, or lower quality ad, and why that might be deliberate. This research shows that platforms are not just passive matchmakers. They are strategic actors who shape the entire playing field to serve their own goals. Understanding that helps demystify a lot about how the digital world works—and why you see the ads you do.

What are the practical applications of your findings?

Pal: For tech companies, this research helps optimize how they rank and price ads, potentially boosting revenue without raising prices. For advertisers, it shows why bidding high isn’t always enough. Your ad’s “clickability score” (and how it’s treated) really matters. For regulators and the public, it raises important questions about fairness and transparency in how ads are shown.

How does your work advance or change the way people in your field think about this area of study?

Pal: We challenge the common wisdom that better targeting always helps. Our paper shows that ad platforms may earn more by dialing targeting down — a counterintuitive but revenue-maximizing move. We also provide a new way to estimate ad values without assuming too much about how people behave, making the analysis more robust and data driven.

What was the most surprising or unexpected finding that emerged from your research?

Pal: The biggest surprise? That less personalization can lead to more profit. We found that platforms like Google or Yahoo! can actually make more money by dialing down how precisely they match ads to users. This tactic, called “score squashing,” levels the playing field so more advertisers stay in the game. That drives up competition and, with it, the price per click. It turns out, blurring the match can boost the margin.

What questions has it opened up for future investigation?

Pal: Next, we want to dig into how quality score is calculated. My next project looks at the ad quality black box and analysis how different factor contribute towards deciding the ad quality. Also, as AI-driven targeting gets more precise, we need to ask: will platforms still want to use that precision or hold back for profit?

Modulation in Open Source Software: How Communities Manage Novelty and Complexity

MIS Quarterly, Forthcoming

Aron Lindeberg, Nicholas Berente, James Howison, Kalle Lyytinen

This study examines how volunteer communities develop open-source software (free software that anyone can use and modify) without traditional management structures. The researchers studied two web development frameworks to understand how these communities decide what new features to add and how complex to make their software. The authors discovered that open-source communities use specific communication practices to shape their software based on shared beliefs and design principles. They borrowed the concept of "modulation" from music production — where sounds are mixed and filtered to create new effects — to explain how community discussions influence software development decisions. These findings help explain how volunteer-driven software projects make decisions about innovation and complexity without traditional corporate leadership, revealing alternative approaches to collaborative technology development.

From the Author

Does the Current Expected Credit Loss Approach Decrease the Procyclicality of Banks’ Lending?

The Accounting Review, January 2025

Jing Chen, Yiwei Dou, Stephen G. Ryan, Youli Zou

After the 2008 financial crisis, regulators worried that banks weren't setting aside enough money for potential loan losses until economic downturns hit, which then forced them to cut lending dramatically during recessions. To fix this, new accounting rules (called CECL) required large banks to predict and prepare for loan losses earlier, starting in January 2020. The researchers studied whether these new rules actually helped during the COVID-19 recession. They found the opposite. Banks using the new accounting method set aside even more money for potential losses and reduced their lending more than other banks during the pandemic recession. This lending reduction was strongest among banks with weaker regulatory capital buffer and lower preempted impairment losses. The study also found that communities where these banks were major lenders experienced higher unemployment rates during the recession and slower economic recovery afterward.

From the Author

What was the main question your research sought to answer?

Chen: In January 2020, FASB issued a new accounting rule requiring large public banks to accrue loan losses using the current expected credit loss (CECL). Under CECL, a bank set aside reserves for future loan losses, i.e., recognize a loan loss allowance (LLA), equal to the current expected credit losses on outstanding loans over their entire remaining lives. Before this rule, banks applied the incurred loss model (ILM) and record an LLA only for the portion of current expected credit losses on outstanding loans that are incurred, probable, and capable of reasonable estimation. Hence, CECL front-loads loan loss recognition relative to the ILM. The timing was significant because the COVID-19 pandemic hit shortly after, leading to an economic recession in early 2020. Our research examines how this change in accounting rules affected bank lending during the downturn.

What were some of your more important findings?

Chen: We find that banks that adopted CECL prior to the COVID-19 pandemic recognized larger LLA and reduced loan growth during the accompanying recession more than other banks. The lending contraction is stronger for adopting banks with low regulatory capital and low loan impairment – that is banks with weaker financial buffers – and is primarily driven by commercial loans. Banks’ CECL adoptions before the recession are associated with substantial economic harm during the recession in the areas they serve. We find that counties in which CECL-adopting banks have higher market share experience larger increases in unemployment rates during the recession and slower subsequent recoveries. The results suggest that while the rule was designed to make banks more resilient, it may have unintentionally worsened the recession’s impact by causing a sharper pullback in lending. This, in turn, contributed to higher unemployment and slower recoveries in communities where these banks played a major role.

Why is this research important right now, and what are the practical applications of your findings?

Chen: In the wake of the 2007–2009 financial crisis, policymakers expressed the concern that the ILM model that banks use for their loan loss recognition exacerbates the procyclicality of banks’ lending because the use of the ILM delays the recognition of a sizeable portion of current expected loan losses to periods of economic stress, such as recessions, when the losses first meet the conditions for recognizing loan loss allowance. Addressing this concern, the FASB issued a rule which requires large public banks to use the CECL approach to accrue for loan losses as of the beginning of the 2020 fiscal year.

Our paper informs the ongoing and pitched debate regarding whether CECL mitigates banks’ lending contraction during recessions. In the wake of the financial crisis, the Financial Stability Forum (2009) posited that “[e]arlier recognition of loan losses could have dampened cyclical moves in the current crisis.” In contrast, the American Bankers Association expressed the concern that “banks and other financial companies are finding—through the testing of their estimation models—that CECL would actually increase procyclicality and perhaps significantly. By increasing procyclicality into the banking system, CECL will cause economic downturns to be more severe and to last longer.” Our results provide support for this concern.

2024-2025 Financial Times 50 and UT-Dallas 24 Publications (Published & Accepted)

Lindberg, A., Berente, N., Howison, J., Lyytinen, K. Modulation in Open-Source Software: How Communities Manage Novelty and Complexity, MIS Quarterly, forthcoming.

Begley, T., Dominick, P., Iordanoglou, D, Lianidou, T., Marchese, M., Prastacos, G. (2025). Practitioner Experiences with Digitization in Human Resource Management. Human Resource Management Journal, Published online June 2025.

Herve, J., Oh, H., (2025). Quiet Quitting in Times of Uncertainty: Definition and Relationship with Perceived Control. Human Resource Management, Published online June 2025.

Zheng, W., Kim, J. & Kark, R. (2025). Every Rose Has Its Thorns - How Exemplars Manage the Tensions in Inclusive Leadership. J Bus Ethics, Published online April 2025.

Kim, D., Pal, P. (2025). Nonparametric Estimation of Sponsored Search Auctions and Impact of Ad Quality on Search Revenue. Management Science, Published online April 2025.

Aaltonen, A., Wattal, S. (2025). Not Good Enough, But Try Again! The Impact of Improved Rejection Communications on Contributor Retention and Performance in Open Knowledge Collaboration, Management Science, accepted.

Ursu, R.M., Simonov, A., and An, E. (2025) Online Advertising as Passive Search, Management Science, 71(2), 1050-1073.

Chen, J., Dou, Y., Ryan, S., Zou, Y. (2025) Does the Current Expected Credit Loss Approach Decrease the Procyclicality of Banks’ Lending?, The Accounting Review.

Xu, H., Hannah, S. T., Wang, Z., Moss, S. E., Sumanth, J. J., & Song, M. (2025). Jekyll and Hyde leadership: Examining the direct and vicarious experiences of abusive and ethical leadership through a justice variability lens. Journal of Applied Psychology, 110(6), 831–845.

Mindel, V., Aaltonen, A., Rai, A., Mathiassen, L., and Jabr, W. (2025) Timely Quality Problem Resolution in Peer-Production Systems: The Impact of Bots, Policy Citations, and Contributor Experience. Information Systems Research, 36(2), 647-1267.

Bonini, S., Enache, L., Ferrari, M., Ross, D.G., John,K. (2024), Why Your Board Should Include a Long-Tenured Director, Harvard Business Review, (web) December 2024.

Xu, H., Hannah, S. T., Sumanth, J., & Moss, S. (2024) Leaders can’t make up for bad behavior by being nice later. Harvard Business Review (web), November 2024.

H. Zhong, F. Mahdavi Pajouh, S. Butenko, and O. Prokopyev. On interdicting dense clusters in a network, INFORMS Journal on Computing, Published online October 2024,

Feinstein, Z., Hey, N., & Rudloff, B. (2024). Approximating the set of Nash equilibria for convex games, Operations Research. Published online October 2024.

Ozgen, S., Mooney, A., & Zhou, Y. (2024). CEO Power: A Review, Critique, and Future Research Directions. Journal of Management, 51(1), 132-171.

Gopal, Qiao, X., Strub, M.S., Yang, Z. (2024) Gaining a Seat at the Table: Enhancing the Attractiveness of Online Lending for Institutional Investors. Information Systems Research, 36(1), 1-646.