Lincoln University - California

The paper aims at examining the effect of sustainable finance programs on financial markets and economic stability, particularly in emerging and developing markets. Sustainable finance or environmental, social, and governance (ESG) standards, green bonds, and social impact investments are all recent terms that have become popular as a policy tool in enhancing the economic resilience of the long-term. The study examines both quantitative and qualitative information of financial markets and qualitative information of policy frameworks and institutional practices using a mixed-methods approach. The results indicate that incorporation of ESG factors in financial tools improves market stability, draws responsible investments and economic growth through promotion of sustainable business conducts. Green bonds and environmentally-responsible investment portfolio are determined as the most important instruments that connect the environmental goals with financial performance, minimizing the systemic risks of the unstable markets. The paper also notes some of these challenges such as lack of ESG disclosure, data access, and regulatory arbitrage, especially in developing markets. The findings highlight the significance of balancing financial policies with sustainability objectives in order to attain the long-term economic and environmental stability. The study is useful to inform policymakers, investors, and financial institutions interested in stimulating sustainable economic development in that research provides information on the effectiveness of the sustainable finance mechanism in enhancing the financial markets, promoting inclusive and sustainable growth.

This symposium highlights the transformative interplay between control and trust dynamics in the age of AI and Big Data by integrating insights across macro, meso, and micro levels of analysis. Juxtaposing these insights in the discussion facilitated by Sim Sitkin, the symposium reveals a comprehensive understanding of how technological advancements redefine control and trust dynamics inherent in managerial practices, organizational structures, and broader societal governance. On a more macro level, Paul Adler examines how societal governance structures influence the trajectory of AI development, that is how governments and societal collectives engage with and control AI development to maximize benefits and mitigate risks, providing insights into the intersection of societal control, trust, and technological evolution. At the organizational level, Markus Kreutzer and Jorge Walter focus on algorithmic supervision and human-AI teams (HATs), exploring how these configurations influence control-trust dynamics within modern organizations and, thus, provide a detailed understanding of how AI-enabled controls shape trust among those being controlled and those implementing the controls. On the more meso/micro-level Mareike Möhlmann and colleagues adopt a grounded theory approach on how YouTube as a platform organization controls conflicts (e.g., freedom of speech, content diversity, and safety) while fostering trust and performance through human-machine collaboration. Finally, Kirsimarja Blomqvist’s work on fast expert teams addresses the orchestration of trust and control in high-stakes problem-solving, bridging the need for controls with interpersonal and system-based trust cues. By synthesizing these scholarly emphases, the symposium advances a unified perspective on control-trust dynamics in the age of AI and Big Data, uncovering their interconnectedness and implications across societal, organizational, and digital ecosystems. AI, Control, Trust, and Political-Economic Power Author: Paul S. Adler; University of Southern California Control-Trust Dynamics in the Context of Agentic Algorithms Author: Markus Kreutzer; EBS University of Business and Law Author: Jorge Walter; The George Washington University Algorithmic Stakeholder Governance on YouTube: A Lead Role Perspective Author: Mareike Möhlmann; Bentley University Author: Robert Wayne Gregory; University of Miami Author: Ola Henfridsson; University of Miami Building trust and control for orchestrating temporary online knowledge collaboration Author: Kirsimarja Blomqvist; LUT University, LUT Business School

Abstract Thesis defense, business, conference, public, and university lectures and presentations are very different by their structure, timing, and the audience. However, all of them have a lot in common as of their conceptual framework, preparation technique, and presentation strategy and tactics.

Abstract The most straightforward way of forming a sample is to select it randomly from the population. Such a sample is referred to as a simple random sample or a random sample, and the approach of forming such a sample is called simple random sampling or random sampling. Thus, each simple random sample of the same size has an equal probability of being selected from the same population.

Due to the promising effects of mesenchymal stem cells (MSCs) in the treatment of various diseases, this commentary aimed to focus on the auxiliary role of MSCs to reduce inflammatory processes of acute respiratory infections caused by the 2019 novel coronavirus (COVID-19). Since early in 2020, COVID-19, a consequence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly affected millions of people world-wide. The SARS-CoV-2 infection in children appears to be an unusual event. Despite the high number of affected adult and elderly, children and adolescents remained low in amounts, and marginally touched. Based on the promising role of cell therapy and regenerative medicine approaches in the treatment of several life-threatening diseases, it seems that applying MSCs cell-based approaches can also be a hopeful strategy for improving subjects with severe acute respiratory infections caused by COVID-19.

This article investigates the impact of linguistic style in the Management Discussion and Analysis of Financial Condition and Results of Operations (hereafter MD&A) section of a company’s annual report on stock market response. It provides a new technique for combining qualitative with quantitative information by applying the partial least squares–structural equation modeling. In this article, we model the influence of verbal tone from the MD&A section on stock market reaction. The quantity predicted is the cumulative abnormal return as a proxy of market return, while the capital assets pricing model and volatility are a proxy of market risk. Furthermore, Future of Return on Assets is a proxy of expected future financial performance. Results show that the model for predicting future performance is considered moderate, while it is considered poor for predicting market reaction. As for the path coefficients, we find no evidence that the linguistic style in an MD&A has a significant effect on market reaction in general. The results reveal an insignificant difference between the effects of the long MD&A and the short MD&A on market reaction. However, based on the disclosure year of an MD&A, there is a significant difference between 2010 and 2012 in terms of impact on expected future performance by net optimism. Nevertheless, descriptive statistics designate that the verbal tone in an MD&A was not adequately consistent with financial performance. Therefore, it can be concluded that management writers create an MD&A as part of an annual routine just to satisfy the shareholders. Due to some limitations, these findings must be interpreted with caution.