Does Telehealth Reduce Rural-Urban Care Access Disparities? Evidence from Covid-19 Telehealth Expansion

Using hospital claims data, we study the effect of telehealth expansion on the disparities between care access in rural and urban areas during Covid-19. We use urban areas as the control group and compare the changes in patients' access to care before and after the telehealth expansion. We find that the rural-urban disparities in overall access to care (i.e., the total number of visits) remain unchanged after the policy. We further distinguish in-person from telehealth visits and find enlarged disparities in patients' visiting modalities. In particular, urban patients substitute in-person visits with telehealth visits, yet rural patients have a much lower adoption rate of telehealth services and continue with in-person visits. Finally, we perform visit-level analyses and identify patients' social determinants and physicians' characteristics associated with telehealth adoptions

Link Formation on Twitter: The Role of Achieved Status and Value Homophily

Homophily has been a widely recognized dominant factor in offline social network connection, which refers to one’s propensity to seek interactions with others of similar status or values. Existing studies regarding homophily factors have been limited mostly to offline sociodemographic characteristics, such as race, gender, religion, education and occupation, which may not necessarily manifest homophily in online social network. Some researchers dabble in online social network, but they extract homophily characteristics from static user profile or link data, which has not incorporated the dynamic process of social network. To better understand the key factors in the establishment of online relationship, we explore a large data set on Twitter, which contains all initiated links by 1453 organizational Twitter users over three months. An initiated link refers to organization following a user who is currently not a follower of the organization. We crawl data on a daily basis and monitor whether the initiated one-way link ends up with a two-way relationship. Based on the established homophily theory, we define two online homophily factors: achieved status homophily (estimated by the gap of the followers count), value homophily (measured by the overlap ratio of common followee, Pearson correlation, and Cosine similarity between two users’ tweets, respectively). We find that both homophily factors play a key role in the formation of online reciprocal relationship, and the effect of status homophily is larger for superior followee (one who has more followers than the corresponding organization) than for inferior followee (one who has less followers than the corresponding organization). Our finding not only extends the offline “individual- individual” homophily theory to the new online “organization- individual” relationship, but also provides Twitter users insight into extending their social network by strategically targeting followee

Does Telemedicine Affect Physician Decisions? Evidence from Antibiotic Prescriptions

Telemedicine has long been of interest to the U.S. general public. Yet, despite the advent of high-speed internet and mobile device technology, telemedicine did not reach its full potential until the COVID-19 pandemic spurred its unparalleled adoption. This sudden shift in the setting of healthcare delivery raises questions regarding possible changes in clinical decision-making. Using a unique set of patient-provider encounter data from the U.S. in 2020 and 2021, we examine the effect of telemedicine on antibiotic prescription errors for urinary tract infections. After accounting for potential endogeneity issues using provider fixed effects and an instrumental variable approach, we find a significantly lower likelihood of prescription errors with telemedicine relative to in-person encounters. We also find heterogeneous effects by a provider's patient volume and the patient-provider relationship

The Value of Humanization in Customer Service

As algorithm-based agents become increasingly capable of handling customer service queries, customers are often uncertain whether they are served by humans or algorithms, and managers are left to question the value of human agents once the technology matures. The current paper studies this question by quantifying the impact of customers\u27 enhanced perception of being served by human agents on customer service interactions. Our identification strategy hinges on the abrupt implementation by Southwest Airlines of a signature policy, which requires the inclusion of an agent\u27s first name in responses on Twitter, thereby making the agent more humanized in the eyes of customers. Multiple empirical analyses consistently show that customers are more willing to engage, and upon engagement, more likely to reach a resolution, with more humanized agents. Furthermore, we find that customers do not behave more aggressively to more humanized agents, hence humanization incurs no additional cost to agents

She? The Role of Perceived Agent Gender in Social Media Customer Service

This paper investigated the role of perceived agent gender in customer behavior using a unique dataset from Southwest Airlines\u27 Twitter account. We inferred agent gender based on the first names provided by agents when responding to customers. We measured customer behavior using three outcomes: whether a customer decided to continue the service conversation upon receiving an agent’s initial response as well as the valence and arousal levels in their second tweet if the customer chose to continue the interaction. Our identification strategy relied on the Backdoor Criterion and hinged on the assumption that customer service requests are assigned to the next available agent, independent of agent gender. The findings revealed that customers were more likely to continue interactions with female agents than male agents and they were more negative in valence but less intense in arousal with the former group than with the latter

DCP-Net: A Distributed Collaborative Perception Network for Remote Sensing Semantic Segmentation

Onboard intelligent processing is widely applied in emergency tasks in the field of remote sensing. However, it is predominantly confined to an individual platform with a limited observation range as well as susceptibility to interference, resulting in limited accuracy. Considering the current state of multi-platform collaborative observation, this article innovatively presents a distributed collaborative perception network called DCP-Net. Firstly, the proposed DCP-Net helps members to enhance perception performance by integrating features from other platforms. Secondly, a self-mutual information match module is proposed to identify collaboration opportunities and select suitable partners, prioritizing critical collaborative features and reducing redundant transmission cost. Thirdly, a related feature fusion module is designed to address the misalignment between local and collaborative features, improving the quality of fused features for the downstream task. We conduct extensive experiments and visualization analyses using three semantic segmentation datasets, including Potsdam, iSAID and DFC23. The results demonstrate that DCP-Net outperforms the existing methods comprehensively, improving mIoU by 2.61%~16.89% at the highest collaboration efficiency, which promotes the performance to a state-of-the-art level

The Impact of Heterogeneous Shared Leadership in Scientific Teams

Leadership is evolving dynamically from an individual endeavor to shared efforts. This paper aims to advance our understanding of shared leadership in scientific teams. We define three kinds of leaders, junior (10-15), mid (15-20), and senior (20+) based on career age. By considering the combinations of any two leaders, we distinguish shared leadership as heterogeneous when leaders are in different age cohorts and homogeneous when leaders are in the same age cohort. Drawing on 1,845,351 CS, 254,039 Sociology, and 193,338 Business teams with two leaders in the OpenAlex dataset, we identify that heterogeneous shared leadership brings higher citation impact for teams than homogeneous shared leadership. Specifically, when junior leaders are paired with senior leaders, it significantly increases team citation ranking by 1-2%, in comparison with two leaders of similar age. We explore the patterns between homogeneous leaders and heterogeneous leaders from team scale, expertise composition, and knowledge recency perspectives. Compared with homogeneous leaders, heterogeneous leaders are more adaptive in large teams, have more diverse expertise, and trace both the newest and oldest references