How much value does an additional dollar of cash create for a firm? It is generally recognized that the marginal value of cash (MVC) can either exceed or fall below one dollar. Estimates of MVC can guide corporate cash and payout policy, indicate the quality of governance, and make a firm a target for takeover or activism. Yet the existing methods of estimation lack a rigorous theoretical foundation and often provide implausibly high or low estimates. In this paper, we provide a formulation of MVC and structurally estimate the MVC based on a model that encompasses the important determinants for the choice of cash savings, including financing and agency costs. We find that firms with large cash and capital stocks have lower marginal value of cash, whereas the relationship between leverage and marginal value of cash is hump shaped. Two quasi-natural experiments validate the MVC estimates.

We explore the possibility of designing matching mechanisms that can accommodate nonstandard choice behavior. We pin down the necessary and sufficient conditions on participants' choice behavior for the existence of stable and incentive-compatible mechanisms. Our results imply that well-functioning matching markets can be designed to adequately accommodate a plethora of choice behaviors, including the standard behavior consistent with preference maximization. To illustrate the significance of our results in practice, we show that a simple modification in a commonly used matching mechanism enables it to accommodate nonstandard choice behavior.

This paper considers a random search model where some locations provide sellers with better chances of meeting many buyers than other locations (for example popular shopping streets or the first page of a search engine). When sellers are heterogeneous in terms of the quality of their product and/or the probability that a given buyer likes their product, it is desirable that sellers of high-quality niche products sort into the best locations (positive assortative matching, PAM). We show that this does not always happen in a decentralized market. Finally, we endogenize the location distribution and show that PAM between sellers and locations always arises in equilibrium. However, the equilibrium distribution of locations is too favorable for the sellers of high-quality, niche products.

This paper studies whether and how corporate venture capital (CVC) spurs changes in firm scope. Using two sets of firm scope metrics, a text-based emerging business measure and Compustat segment measures, I document that CVC investments are strongly associated with subsequent firm scope changes of the CVC corporate parent, including seeding emerging businesses, establishing new divisions, terminating obsolete divisions, and changing the primary industry. Further evidence is consistent with an experimentation view of CVC investments, with more promising ventures having a stronger impact on the scope change of parent firms. Finally, to sharpen the causality, I explore the idiosyncratic fund inflow shocks of those connected independent VCs in each CVC program, as well as the US non-stop airline routes.

As algorithm-driven content platforms sweep the world, what is changing in journalism? This article investigates news production of the Chinese official media on Douyin (the Chinese version of TikTok). From the perspectives of news gathering, professional role, and news value, we conducted a manual content analysis (N = 991) of four representative Chinese official media (People’s Daily, China Youth Daily, Southern Metropolis Daily and Sichuan Observer) to reveal the commonalities and heterogeneities of their news production on Douyin. Then, through an automated content analysis of Sichuan Observer (N = 16,045), we illustrate how district media convergence centers have fought for public attention as emerging actors in the news ecosystem. Overall, we map the current practices of Chinese official media on the emerging algorithm-driven content platforms, focusing on how they pursue a new type of news orientation and popularize the Party’s message while disseminating entertainment content. Contributions, such as t

Three experimental studies demonstrate if, when, and how an organization involved in information system (IS) incidents can effectively strategize the use of emoji in its online communication. Theoretical foundations drawn from the stereotype content model, the psychological distance literature, and the situational crisis communication theory have informed the predictions. Among the Chinese, emoji in social media responses reduced psychological distance and alleviated anger, which had positive impacts on evaluations of the company involved in the incident. The impact was particularly evident when the business social media account (vs. the CEO account) employed emoji. Furthermore, emoji in incident responses signaled warmth and competence, while its impact was contingent on incident type. The positive emoji effect on competence was stronger when the company was deemed responsible for the incident indicating Chinese’ public appreciation for emoji as an additional communication effort for emotional disclosure and

The digital era has necessitated a better understanding of effective customer interaction strategies for luxury brands in the e-commerce space. This article proposes a model that explains how online response speed (i.e. the amount of time it takes for a business to respond to a customer’s inquiry) can influence brand attitudes among luxury e-commerce consumers. Results from two empirical studies (N = 615), demonstrate that the speed of online responses can impact brand attitude via two mediators: perceived exclusivity and interaction quality. A slower response speed enhances the perceived exclusivity of the brand, thereby positively influencing brand attitude. However, this slow response speed negatively impacts the perceived interaction quality, subsequently diminishing brand attitudes. These competing pathways illustrate the multifaceted influence of online response speed on brand attitudes. Moreover, the indirect effect of response speed on brand attitude through perceived exclusivity depends on the produc

We examine how social norms measured by religiosity influence institutional investors' willingness to lend stock and constrain short selling in the U.S. markets. We find that firms with blockholders located in higher religiosity areas are associated with lower supply and higher utilization of lendable shares, but are not related to the demand for stock borrowing. Short interest, utilization rates, and lending fees, when combined with high blockholder religiosity, are stronger negative predictors of future stock returns. Our findings suggest that the social norms of institutional investors serve as a source of limits to arbitrage, which hinders market efficiency through stock lending.

Recently, Kurisu and Otsu (2022b, Econometric Theory 38(1), 172-193) derived the uniform convergence rates for the nonparametric deconvolution estimators proposed by Li and Vuong (1998, Journal of Multivariate Analysis 65(2), 139-165). This article shows that faster uniform convergence rates can be established for their estimators under the same assumptions. In addition, a new class of deconvolution estimators based on a variant of Kotlarski's identity is also proposed. It is shown that in some cases, these new estimators can have faster uniform convergence rates than the existing estimators.

Idea screening in collaborative crowdsourcing communities poses significant challenges for firms. These challenges are primarily attributable to issues of prediction accuracy and information overload. The rapid expansion of idea pools generates a vast amount of data, making it difficult to effectively identify valuable ideas for new product development. This study introduces an interpretable framework for machine learning that integrates a novel exploration and exploitation perspective within the value cocreation model to enhance idea screening. The framework incorporates six theoretical dimensions of the exploration and exploitation of value cocreation (EEVC): the exploration and exploitation of digital resources, direct interactions, and ideas and their comments. Our evaluation reveals that the EEVC-based idea-screening system significantly outperforms the traditional 3Cs model in terms of prediction accuracy. SHAP value analysis further reveals that the exploration and exploitation of digital resources are