Riding Attention Spikes: How Analysts Respond to Advertising 

Authors: Professor Minjae KOO et al. (co-authors: Annika Wang, Yin Wang, Liandong Zhang) 

Journal: Contemporary Accounting Research 

This study empirically examines how security analysts strategically respond when product advertising increases investor attention. By combining weekly advertising data with analyst report data, the analysis reveals that analysts tend to issue more optimistic earnings forecasts following periods of intensive advertising. This tendency is particularly pronounced among analysts at brokerage firms whose revenue structures rely on commissions, suggesting that such behavior reflects the strategic use of investor attention rather than mere cognitive bias. 

The study also finds that optimistic forecasts increase trading activity among retail investors, thereby amplifying market reactions. These findings demonstrate that analysts are not passive recipients of information distortion but active participants in shaping market sentiment, offering new insights into the interactions among advertising, information flows, and financial decision-making. As an integrative study bridging accounting and finance, it provides important implications for market transparency and regulatory policy. 

The Closing-the-Gap Effect: Joint Evaluation Leads Donors to Help Charities Farther from Their Goal 

Authors: Professor Baek Jung KIM et al. (co-authors: Rishad Habib, David J. Hardisty, Katherine White) 

Journal: Journal of Marketing Research 

This study identifies the “Closing-the-Gap Effect,” a phenomenon in which donors contribute more to charities that are farther from meeting their fundraising goals when these organizations are evaluated jointly. Drawing on six preregistered experiments, seven follow-up experiments, and more than 10,000 real crowdfunding observations, the researchers empirically validate this effect. The findings show that when donors assess charities side by side, they perceive greater need salience and therefore tend to allocate more donations to organizations with lower goal-achievement rates. However, this effect disappears when charities are evaluated individually. 

The effect also weakens when differences between organizations are small or when for-profit entities are included in the choice set. By illuminating the psychological mechanisms linking social comparison to donation behavior, this study advances theoretical understanding in nonprofit marketing and social psychology. It further offers practical implications for designing platform-based fundraising campaigns and strategies that effectively encourage charitable giving. 

Service Operations for Justice-on-Time: A Data-Driven Queueing Approach 

Authors: Professor Jeunghyun Kim et al. (co-authors: Nitin Bakshi, Ramandeep Randhawa) 

Journal: Manufacturing & Service Operations Management (Vol. 27, Issue 1) 

This study offers an innovative attempt to analyze structural delays in judicial systems from an Operations Management perspective. Focusing on the Supreme Court of India, the authors conduct simulations based on real court data and model the judicial process, in which cases are routed through pre-admission and post-admission stages. The analysis identifies judges’ limited processing capacity and rigid scheduling practices as key drivers of delays. The results further show that implementing greater work-hour flexibility and schedule-adjustment policies can reduce average delays by up to 65%. 

As the first empirical study to reframe the social value of “Justice-on-Time” as a data-driven operations efficiency problem, this research is recognized as an exemplary convergence study that bridges public service and operations management. 

Evaluating Quality Reward and Other Interventions to Mitigate US Drug Shortages 

Authors: Professor In Joon Noh et al. (co-authors: Sergey Naumov, Hui Zhao) 

Journal: Journal of Operations Management (Vol. 71, Issue 3) 

This study quantitatively evaluates policy interventions aimed at addressing drug shortages in the U.S. generic pharmaceutical market. The researchers develop a system dynamics model to compare the long-term effects of traditional policies—such as shortening approval processes and expanding production—with those of the recently highlighted “Quality Reward” incentive system. The simulation results indicate that while traditional policies offer only short-term relief, quality-based incentives provide a sustainable solution that structurally mitigates drug shortages. However, the study also finds that such incentives may induce market monopolization by certain firms, underscoring the need for complementary quality information disclosure mechanisms. 

By empirically demonstrating that quality-focused supply chain management can maintain a balance between public health stability and industrial competitiveness, this study offers robust scientific evidence for pharmaceutical policy design and is highly regarded for its contribution. 

Are All Generic Drugs Created Equal? An Empirical Analysis of Generic Drug Manufacturing Location and Serious Drug Adverse Events 

Authors: Professor In Joon Noh et al. (Gray John, Ball George, Wright Zachary, Hyunwoo Park) 

Journal: Production & Operations Management 

This study quantitatively evaluates policy interventions aimed at addressing drug shortages in the U.S. generic pharmaceutical market. The researchers develop a system dynamics model to compare the long-term effects of traditional policies—such as shortening approval processes and expanding production—with those of the recently highlighted “Quality Reward” incentive system. The simulation results indicate that while traditional policies offer only short-term relief, quality-based incentives provide a sustainable solution that structurally mitigates drug shortages. However, the study also finds that such incentives may induce market monopolization by certain firms, underscoring the need for complementary quality information disclosure mechanisms. 

By empirically demonstrating that quality-focused supply chain management can maintain a balance between public health stability and industrial competitiveness, this study offers robust scientific evidence for pharmaceutical policy design and is highly regarded for its contribution. 

Protecting Workers from Rude Customers to Enhance Organizational Identification in Emotional Labor Environments 

Authors: Professor Kwangtae Park (co-authors: Hyojeong Kim, Nagesh N Murthy, Anurag Agarwal) 

Journal: Production and Operations Management 

This study empirically examines how Emotional Dissonance—experienced by workers in call center environments where emotional labor is routine—affects their Organizational Identification (OID). Emotional dissonance arises when employees’ actual feelings do not align with the emotional expressions required by the organization, and over time, it weakens organizational commitment and job satisfaction. Using data from a large sample of call center employees, the study elucidates the mechanism through which emotional dissonance diminishes organizational identification and tests moderating factors that may alleviate this effect. 

The analysis shows that, first, the more employees perceive customer-interaction protection policies as genuine and effective, the more the negative impact is reduced; and second, strong supervisor Servant Leadership helps sustain OID levels. Notably, although long-tenured employees experience greater cumulative emotional labor, their sense of organizational attachment can be restored when institutional protection and leadership support are provided together. By demonstrating that psychological protection for emotional laborers and organizational policy design operate complementarily, this study expands scholarly understanding of human-centered leadership in the field of service management. 

Consumer Evaluation of Digital Product Innovations: Disentangling Effects of Novelty, Familiarity, and Complementarity 

Authors: Professor Gunwoong Lee et al. (co-authors: Nilla Zhang, Wai Fong Boh)

Journal: MIS Quarterly 

This study empirically examines how consumers’ familiarity and novelty perceptions influence their evaluations when digital product manufacturers pursue innovation. Using data on hardware feature innovations in complex digital devices such as smartphones and laptops, the researchers test the interaction effects of innovation timing and software support on consumer satisfaction. The results indicate that familiar functions receive more favorable evaluations when introduced early in the product cycle, whereas novel functions gain greater acceptance when introduced with some delay. In contrast, simultaneously releasing new features alongside complex software leads to consumer confusion and negative evaluations. 

By clarifying the complementarities and timing strategies between hardware and software innovation, the study offers meaningful practical implications for technology marketing and innovation management. It is also academically recognized for explaining the market acceptance of technological innovation through the lens of the consumer learning curve. 

Leveraging Large Language Models for Hate Speech Detection: Multi-Agent, Information-Theoretic Prompt Learning for Enhancing Contextual Understanding 

Authors: Professor Kyuhan Lee et al. (co-author: Sudha Ram) 

Journal: Journal of Management Information Systems 

This study proposes a novel approach to enhancing the accuracy and contextual understanding of hate speech detection by designing Large Language Models (LLMs) within a Multi-Agent framework. Whereas single-model detection methods struggle to capture complex linguistic elements such as context, satire, and metaphor, this study develops a system in which multiple AI agents cross-verify and collaborate on their judgments. The authors also introduce an information-theoretic entropy criterion to quantify the efficiency of prompt selection, resulting in significant improvements in detection accuracy compared with existing models. 

This approach improves the feasibility of real-time content monitoring on large-scale online platforms and demonstrates that technological interventions can help curb the spread of hate speech, a major source of social conflict. The study is recognized for advancing ethical and public values in the information systems field by illustrating how AI technologies can support societal responsibility. In doing so, it contributes to reducing social tensions and fostering healthier communication environments. 

Fear of Appreciation and Current Account Adjustment 

Authors: Professor Ju Hyun Pyun et al. (co-corresponding authors: Paul R. Bergin a, Kyunghun Kim b) 

Journal: Journal of International Economics 

This paper finds that one-sided nominal exchange-rate interventions—specifically, a “fear of appreciation”—delay the adjustment of current account surpluses, offering new evidence for Friedman’s claim that current account adjustment proceeds more rapidly under flexible exchange rates. The study shows that countries with more flexible exchange-rate regimes adjust current account deficits more quickly than those with fixed regimes, but this pattern does not hold in the case of surpluses. 

This asymmetry is associated with policies aimed at resisting currency appreciation in some countries. To account for this, the authors develop a multi-country monetary model that incorporates a policy rule representing a “fear of appreciation,” modeled as an occasionally binding constraint. The model illustrates how government capital controls that sustain an exchange-rate regime influence international financial adjustment mechanisms and explains the substantial asymmetries in adjustment speeds depending on the exchange-rate regime and whether a country is in surplus or deficit. 

The study empirically extends Friedman’s argument and presents a new theoretical framework that accounts for asymmetries in modern capital control and reserve accumulation policies.