These sources explore stock return response modeling as a method to understand how financial markets evaluate changes in a company's marketing strategy and its perceived long-term value. The authors, Mizik and Jacobson, explain how this modeling assesses whether information in marketing metrics reflects what investors believe will impact future cash flows and stock prices. They specifically examine the trade-off between a firm's emphasis on value creation (like R&D) versus value appropriation (like advertising) and its effect on stock market returns. The research indicates that while both are important, a greater emphasis on value appropriation can be favorably received by the market, though this is influenced by factors like a firm's financial performance, past strategies, and the technological landscape in which it operates.

We discuss how to replicate Mitchell's "The Impact of External Parties on Brand-Name Capital" employs an event study to investigate the financial consequences of the 1982 Tylenol poisonings on Johnson & Johnson. 

We provide a comprehensive review of event study methodology, a statistical tool widely used in finance and other disciplines to assess the impact of specific events on asset prices. The paper traces the historical development of event studies, highlighting key early works and the evolution of methodological approaches. It examines various aspects of event study design, including parametric and nonparametric test statistics, the challenges posed by event-induced variance, and optimal methods for aggregating results across multiple events. Furthermore, the review analyzes the power and specification of different statistical tests, considering the impact of non-normally distributed data and the importance of selecting appropriate market models. The author also discusses the implications of focusing on a specific sample versus generalizing to a broader population. Ultimately, the paper aims to provide a thorough understanding of the nuances and ongoing debates within event study methodology, offering insights for researchers applying these techniques.

We review the Handbook of Corporate Finance, Volume 1, specifically Chapter 1 titled "Econometrics of Event Studies," which provides a detailed examination of the methodological approaches used in event studies within finance. The chapter, authored by S.P. Kothari and Jerold B. Warner, explores the design, execution, and interpretation of event studies, which analyze the impact of specific corporate events on stock prices. It covers essential aspects such as event study literature, methodologies for characterizing event study methods, various test statistics, and considerations for long-horizon event studies. Furthermore, it addresses potential issues like risk adjustment, errors in expected returns, and approaches to abnormal performance measurement, offering a comprehensive guide to conducting rigorous empirical research in this area of corporate finance.

This review paper offers a comprehensive overview of event study methodology within marketing literature, explaining how stock price movements around corporate announcements are analyzed to understand their financial impact. The authors summarize the current understanding of designing and interpreting event studies, providing guidelines for researchers and readers. The paper discusses various aspects of the methodology, including event definition, handling confounding factors, selecting appropriate asset pricing models, and addressing issues of statistical significance and sample selection bias. Furthermore, it provides practical guidance on implementing event studies using the Eventus platform and contrasts this approach with stock return response modeling. Ultimately, the paper aims to enhance the rigor and interpretation of event studies in marketing research, highlighting areas for future exploration.

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This paper is primarily a research paper exploring a novel method for demand estimation by incorporating unstructured data like product images and text (titles, descriptions, reviews). The authors propose using deep learning models to extract relevant features from this data and integrate them into a random coefficients logit model, allowing for the inference of consumer substitution patterns. The paper validates this approach using a choice experiment where they demonstrate its superior ability to predict second choices compared to traditional attribute-based models and a simple logit model. Furthermore, the methodology is applied to a wide range of product categories on Amazon.com, consistently showing that text and image data offer valuable information for identifying product substitutes.

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Conner's 1991 article provides a historical comparison of resource-based theory with five established schools of thought within industrial organization (IO) economics. The paper aims to determine if resource-based theory offers a genuinely new perspective on the firm. It analyzes the similarities and differences between resource-based theory and the neoclassical, Bain-type IO, Schumpeterian, Chicago, and Coase/Williamson transaction cost economics approaches. The analysis explores how each theory views the firm as a source of competitive advantage and the implications for firm strategy. Ultimately, the work seeks to clarify the distinctiveness and potential contributions of the resource-based view to the broader understanding of the firm within economic theory.

"Beyond Conjoint Analysis: Advances in Preference Measurement" reviews the evolution of preference measurement beyond traditional conjoint analysis. The authors propose a framework centered on the problem, task design, and model specification, highlighting recent research and future directions for each component. The paper discusses the expanding applications of preference measurement to various stakeholders and problems, novel data collection methods focusing on engagement and incentives, and advancements in modeling that incorporate complexities like social interactions and behavioral effects. Furthermore, it examines new estimation techniques and the crucial integration of preference measurement with actionable outcomes and stakeholder objectives. The authors advocate for a more comprehensive and context-aware approach to understanding and utilizing consumer preferences.