Biodiversity Entrepreneurship
We study an emerging class of start-up organizations focused on biodiversity conservation and the challenges they face in financing these ventures. Using a novel machine learning method, we identify 630 biodiversity-linked start-ups in PitchBook and compare their financing dynamics to other ventures. Biodiversity start-ups raise less capital but attract a broader coalition of investors, including not only venture capitalists (“value investors”) but also mission-aligned impact funds and public institutions (“values investors”).
The Influential Solo Consumer: When Engaging in Activities Alone (vs. Accompanied) Increases the Impact of Recommendations
Information about the social context of consumption is often seen on review websites or social media when consumers sharing word-of-mouth about an experience indicate whether they engaged in the activity solo or with companions. Across a secondary dataset scraped from Tripadvisor.com, five main experiments, and one supplemental experiment, the current research finds that individuals who engage in consumption activities alone can be a more influential source of recommendations than people who engage in these same activities with others.
EPA Scrutiny and Voluntary Environmental Disclosures
Market participants have called on the SEC to address the lack of disclosures about firms’ environmental impacts, investments, and exposures. However, the frictions that obstruct the flow of environmental information are not well understood. I shed light on these frictions by examining whether scrutiny by the Environmental Protection Agency (EPA) restricts the firm’s voluntary environmental disclosures in earnings conference calls.
Identifying Competitors in Geographical Markets Using the CSIS Method
Businesses with physical footprints – hotels, retailers, and restaurants – must identify the competitors that matter most. Traditional approaches using brand tier or proximity often fail in dynamic or asymmetric markets. We introduce the Conditional Sure Independence Screening (CSIS) method to marketing to identify true competitors based on their pricing influence on a focal firm’s demand. CSIS is computationally efficient, robust to spatial mis-specifications, and effective for identifying, asymmetric, even non-local, and segment-specific competition.
CFO Narcissism and the Power of Persuasion Over Analysts: A Mixed-Methods Approach
We study the role of CFO narcissism in the intent and ability to positively influence sell-side analysts’ perceptions of the firm. Consistent with narcissists casting favorable impressions on others, we find CFO narcissism is associated with overly optimistic analyst valuations. We then study public persuasion attempts by analyzing conference call transcripts and private persuasion attempts through a laboratory study.
Do Credit Rating Agencies Learn from the Options Market?
Do credit rating agencies (CRAs) learn from the options market? We examine this question by exploring the relation between options trading activity and credit rating accuracy. We find that as options trading volume increases, credit ratings become more responsive to expected credit risk and exhibit greater ability to predict future defaults. We also find that CRAs rely more on the options market as a source of ratings-related information when firm default risk is higher, options trading is more informative, manager-provided information is of lower quality, and firm uncertainty is higher.
The Theory-Based View and Strategic Pivots: The Effects of Theorization and Experimentation on the Type and Nature of Pivots
We examine how formalization in cognitive processes (theorization) and evidence evaluation (experimentation) influence the type (frequency and radicalness) and nature (impetus, clarity, and coherence) of entrepreneurial pivots. We use a mixed-method research design to analyze rich data from over 1,600 interviews with 261 entrepreneurs within a randomized control trial in London.
How to Talk When a Machine Is Listening: Corporate Disclosure in the Age of AI
Growing AI readership (proxied for by machine downloads and ownership by AI-equipped investors) motivates firms to prepare filings friendlier to machine processing and to mitigate linguistic tones that are unfavorably perceived by algorithms. Loughran and McDonald (2011) and BERT available since 2018 serve as event studies supporting attribution of the decrease in the measured negative sentiment to increased machine readership. This relationship is stronger among firms with higher benefits to (e.g., external financing needs) or lower cost (e.g., litigation risk) of sentiment management.
Holding Horizon: A New Measure of Active Investment Management
This article introduces a new holding horizon measure of active management and examines its relation to future risk-adjusted fund performance (alpha). Our measure reveals a wide cross-sectional dispersion in mutual fund investment horizons, and shows that long-horizon funds exhibit positive future long-term alphas by holding stocks with superior long-term fundamentals. Further, stocks largely held by long-horizon funds outperform stocks largely held by short-horizon funds by more than 3% annually, adjusted for risk, over the following 5-year period.
Applied AI for finance and accounting: Alternative data and opportunities
Big data and artificial intelligence (AI) have transformed the finance industry by altering the way data and information are generated, processed, and incorporated into decision-making processes. Data and information have emerged as a new class of assets, facilitating efficient contracting and risk-sharing among corporate stakeholders. Researchers have also increasingly embraced machine learning and AI analytics tools, which enable them to exploit empirical evidence to an extent that far surpasses traditional methodologies.