Research

In this paper, we study the Non-fungible Token (NFT) art marketplace to gain insights into how trading networks, platform connections, and social media interactions impact prices. We focus on the interdependence among artists, collectors, and sellers, each with varying levels of influence and visibility. Our findings reveal differential effects on the price distribution: for lower-valued NFTs, seller trading networks primarily dictate prices, whereas for higher-valued NFTs, the influence of platform connections, specifically popularity, emerges as a critical pricing factor. Buyers often perceive extensive trading networks as validation for higher bids, while involvement in the platform community and social media interactions appear to have no bearing on prices. Our research underscores that in decentralized markets, the power to set prices rests to a large extent with trading networks and platform connections, while their relative influence varies based on the NFT's value.

We explore how technology use helped to cope with the stresses of social distancing during the pandemic contributing insights about the impact of work adaptation enabled by technology on economic vulnerability and resilience. Using a three-wave survey conducted across 10 states in the United States, we found evidence that a high level of technology use was linked to a greater chance of maintaining employment during the pandemic. We evaluate job retention as a function of an index based on the prevalence of information technology (IT) usage in the workplace and psychological and somatic well-being, controlling for technology use outside of the workplace, and socioeconomic and demographic characteristics.

We study the evolution of subcontracting networks of airline carriers in the U.S. and the effect of COVID-19 on competition and cooperative behaviors in the airline industry. We show how shelter-in-place restrictions during the pandemic affected the market and altered the subcontracting networks of airlines. Using Bayesian estimation, we find the probability of link formation based on the rivals' network, past relationships, and types of service. Additionally, we examine the impact of shelter-in-place restrictions on the market exit decisions of regional airlines.

We investigate the route network decisions made by airline carriers in the United States and the impact of pandemic-related restrictions on these networks. Our modeling approach enables us to examine airlines' decisions regarding the complete route network, instead of focusing on route choices at the market level. We estimate the likelihood of selecting a route network based on the past network, network of competitors, and characteristics of the routes.