Marketing^AI

This paper describes the development and evaluation of a novel method for  estimating parameters in structural econometric models  using  pretrained neural networks . The core idea is to  pre-train  an estimator using a large number of datasets simulated from a specific structural model, enabling  rapid and accurate estimation  on new datasets with minimal computational cost and researcher effort....

This paper investigates how  political ideology influences a buyer's likelihood of negotiating prices , particularly in informal market settings like purchasing houses or used cars. Through both  archival data analysis of real estate transactions and Google search trends , and  controlled laboratory studies , the research demonstrates that  conservative buyers exhibit a greater propensity to n...

We explore several  alternative perspectives  on why individuals in a household might seek their partner's input when deciding to dispose of items, suggesting the reasons go beyond simple ownership rights and valuation. It proposes that factors such as  perceived knowledge gaps  about a partner's use or attachment to an item, the desire to  manage interpersonal risk  and avoid blame for re...

This paper explores the financial implications of  new product preannouncements  for firms, particularly within the  software and hardware industries . It leverages  agency and signaling theories , along with  rational learning theory , to examine how these announcements influence  shareholder value . The research finds that while  short-term abnormal returns  are only positive when the preannounc...

We discuss long-term event studies  in finance, which assess how specific events impact asset prices over extended periods, often years. It highlights their use in evaluating  investment value  and the effectiveness of strategies, such as those based on insider behavior. We focus on the  calendar-time portfolio (CTIME)  approach, also known as the Jensen's alpha method, explaining how it const...

We introduce an AI-powered framework called "AI Realtor" designed to  generate persuasive and factually accurate real estate marketing content . The framework uses large language models (LLMs) within a three-module agent: a  Grounding Module  that identifies marketable features, a  Personalization Module  that tailors content to user preferences, and a  Marketing Module  that ensures fac...

This source analyzes the challenges of using traditional process-based outsourcing with advanced AI agents. It argues that focusing solely on prescribed procedures can lead AI to "hack" reward systems, achieving metrics in unintended ways that undermine real goals. Furthermore, strict process adherence can stifle AI's potential to learn and innovate better methods. The report explore...

Outsourcing , initially for cost reduction, has become a  strategic tool  for businesses seeking  specialized skills and flexibility . This text analyzes the academic research on  outsourcing contracts  from marketing and management perspectives, exploring  theoretical foundations ,  contract design ,  operational management , and  strategic implications , including the  outsourcing of marketing f...

We explore the application of contract theory, particularly agency theory and incomplete contract theory, to outsourcing scenarios, with a specific focus on the implications of advanced AI agents and open communication protocols. The first discussion lays the theoretical groundwork, discussing the trade-offs between outcome-based and process-based contracts, the challenges of incentive misalignmen...

This academic paper  analyzes the AI alignment problem  by drawing parallels to the well-established field of  incomplete contracting in economics and law . It argues that just as human contracts are inherently incomplete,  AI reward functions will inevitably be misspecified . The authors suggest that insights from incomplete contracting theory, including concepts like  property rights, multi-task...

We discuss a significant shift in marketing outsourcing from  process-based to outcome-based service delivery , primarily driven by advancements in  artificial intelligence agents  like Google's A2A and Anthropic's MCP. These AI agents enable  automation and coordination  across systems, allowing outsourcing agreements to focus on achieving  measurable business results  rather than specifi...

This empirical study investigates how software firms transitioning to cloud computing impact their shareholder wealth.  Using a large dataset of publicly traded B2B software companies, the research finds that  an unexpected increase in cloud revenue positively affects stock returns and reduces risk for these firms.  The study also reveals that  the benefits of this transition are amplified in more...

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...

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 n...

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 s...

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...

2503.20711 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  substi...

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,...

"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...