arXiv subjects

Pawel Robert Smolinski

Publications and source records attributed to Pawel Robert Smolinski.

4 recordsLinked to original sources

arXiv2026

The Buffett Effect

We study whether stock disclosures by recognizable investors generate abnormal market reactions beyond the reactions produced by comparable but non-recognizable managers. We define the Buffett effect as the incremental abnormal return to a disclosed new position that is attributable to the public recognition of the disclosing investor. We construct a recognition index from Wikipedia pageviews and ProQuest news mentions. Using data from 2000 to 2025 we compare market reaction to disclosures of 24 recognizable discretionary funds with disclosures of 24 matched control funds. New-position disclosures by recognizable managers generate a positive disclosure premium over the filing date and the following trading days, and the premium increases with investor recognition. We construct calendar-time portfolios that mechanically copy each group's disclosed purchases and find that copying the most recognized investors earns a significant alpha that persists for months and does not reverse. The evidence is most consistent with an entangled attention-information channel: investor recognition directs scarce investor attention toward selected disclosures, and the information revealed in those disclosures is then capitalized into prices.

q-fin.ST↗

arXiv2025

Exploring the Impact of Generative Artificial Intelligence on Software Development in the IT Sector: Preliminary Findings on Productivity, Efficiency and Job Security

This study investigates the impact of Generative AI on software development within the IT sector through a mixed-method approach, utilizing a survey developed based on expert interviews. The preliminary results of an ongoing survey offer early insights into how Generative AI reshapes personal productivity, organizational efficiency, adoption, business strategy and job insecurity. The findings reveal that 97% of IT workers use Generative AI tools, mainly ChatGPT. Participants report significant personal productivity gain and perceive organizational efficiency improvements that correlate positively with Generative AI adoption by their organizations (r = .470, p < .05). However, increased organizational adoption of AI strongly correlates with heightened employee job security concerns (r = .549, p < .001). Key adoption challenges include inaccurate outputs (64.2%), regulatory compliance issues (58.2%) and ethical concerns (52.2%). This research offers early empirical insights into Generative AI's economic and organizational implications.

econ.GN↗

arXiv2024

Scaling Technology Acceptance Analysis with Large Language Model (LLM) Annotation Systems

Technology acceptance models effectively predict how users will adopt new technology products. Traditional surveys, often expensive and cumbersome, are commonly used for this assessment. As an alternative to surveys, we explore the use of large language models for annotating online user-generated content, like digital reviews and comments. Our research involved designing an LLM annotation system that transform reviews into structured data based on the Unified Theory of Acceptance and Use of Technology model. We conducted two studies to validate the consistency and accuracy of the annotations. Results showed moderate-to-strong consistency of LLM annotation systems, improving further by lowering the model temperature. LLM annotations achieved close agreement with human expert annotations and outperformed the agreement between experts for UTAUT variables. These results suggest that LLMs can be an effective tool for analyzing user sentiment, offering a practical alternative to traditional survey methods and enabling deeper insights into technology design and adoption.

cs.CL↗

arXiv2023

Nuclear Energy Acceptance in Poland: From Societal Attitudes to Effective Policy Strategies -- Network Modeling Approach

Poland is currently undergoing substantial transformation in its energy sector, and gaining public support is pivotal for the success of its energy policies. We conducted a study with 338 Polish participants to investigate societal attitudes towards various energy sources, including nuclear energy and renewables. Applying a novel network approach, we identified a multitude of factors influencing energy acceptance. Political ideology is the central factor in shaping public acceptance, however we also found that environmental attitudes, risk perception, safety concerns, and economic variables play substantial roles. Considering the long-term commitment associated with nuclear energy and its role in Poland's energy transformation, our findings provide a foundation for improving energy policy in Poland. Our research underscores the importance of policies that resonate with the diverse values, beliefs, and preferences of the population. While the risk-risk trade-off and technology-focused strategies are effective to a degree, we advocate for a more comprehensive approach. The framing strategy, which tailors messages to distinct societal values, shows particular promise.

econ.GN↗