Impact of Telemedicine through Social Media: A Study of Topics in User Comments on Twitter DOI Creative Commons
Mario Sierra Martín, Fang-Wei Chen, Pilar Alarcón Urbistondo

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Окт. 14, 2024

Abstract Background The use of new technologies has transformed society, affecting communication, information seeking and ways working. Telemedicine, as a remote health practice through ICTs, grown exponentially, especially after the pandemic. Objective This qualitative study aims to explore users' perceptions concerns about telemedicine comments posted on Twitter by users, identifying primary, secondary residual themes. Methods Natural Language Processing (NLP) Machine Learning techniques, specifically Latent Dirichlet Allocation (LDA) model, were used analyse 156,633 extracted from related topics. Results The revealed several issues be addressed. Data was collected using keywords such "teleconsultation" "telemedicine". We can see that most frequent words in include "health", "service", "doctor" "patient". themes identified grouped into four dimensions: general information, benefits sought, specific professional issues. results showed 60.1% focused generic topics, ease service information. queries observed public nature, focusing accessibility, while disease or treatment topics less frequent. Conclusions provide for proper development social networks. is platform mainly queries, with convenience accessibility main mentioned. suggest online interactions are complex offer valuable insights improving communication strategies. Future research could hashtags differences interaction patterns according user profile, providing deeper understanding audiences' behaviour These findings underline importance considering audience preferences improve effectiveness communications.

Язык: Английский

Intelligent-Driven Resilience Enhancement: Nonlinear Impacts and Spatial Spillover Effects of AI Penetration on China’s NEV Industry Chain DOI

Qiong Yang,

Haibin Liu

Technology in Society, Год журнала: 2025, Номер unknown, С. 102827 - 102827

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

2
Artificial Intelligence: Intensifying or Mitigating Unemployment? DOI
Meng Qin, Yongshan Wan,

Junyi Dou

и другие.

Technology in Society, Год журнала: 2024, Номер 79, С. 102755 - 102755

Опубликована: Ноя. 6, 2024

Язык: Английский

Процитировано

9
Robot and crime: Evidence from China DOI

Guanfu Fang,

Liya Miao

World Development, Год журнала: 2025, Номер 188, С. 106921 - 106921

Опубликована: Янв. 15, 2025

Язык: Английский

Процитировано

0
Unlocking innovation empowerment: how can industrial robots accelerate total factor productivity? DOI

Ting Chen,

Zongqiang Ren,

大 妹尾

и другие.

Journal of strategy and management, Год журнала: 2025, Номер unknown

Опубликована: Фев. 8, 2025

Purpose Embodied intelligent robots are the iconic productivity of Industry 4.0 era, and their potential to bring about a surge mainly comes from driving force on innovation rather than efficiency. However, dynamic impact capability enterprises has not been empirically tested. Design/methodology/approach This study integrates panel vector autoregression threshold effects investigate this relationship by multi-level analysis based data Chinese A-share manufacturing listed enterprises. Findings (1) The short-term momentum industrial robot applications (IRA) exploitative (EII) is significant long-term exploratory (ERI) stronger. (2) EII affected IRA main source total factor (TFP) growth, while ERI for TFP growth. (3) exhibits double-threshold effect follows “stepped” incremental pattern. promoting will significantly increase only when surpasses certain thresholds. Originality/value Industrial accelerate growth in long term, coming augmented contribution ERI, providing reference inspiration fully utilize endogenous implement strategies. It also provides forward-looking guidance organisations undertake adaptive changes forthcoming AI economic revolution.

Язык: Английский

Процитировано

0
How Does Artificial Intelligence Shape Supply Chain Resilience? The Moderating Role of the CEOs’ Sports Experience DOI Creative Commons
Yuxuan Xu,

Yu Hua,

Ran Qiu

и другие.

Systems, Год журнала: 2025, Номер 13(3), С. 190 - 190

Опубликована: Март 9, 2025

In the volatility, uncertainty, complexity, and ambiguity (VUCA) environment, application of artificial intelligence (AI) technologies is a key engine for shaping supply chain resilience (SCR). This study employs entropy method to develop an evaluation index system SCR, incorporating two dimensions: resistance recovery capacity. Using sample Chinese-listed enterprises from 2009 2022, this reveals that AI significantly enhances CEOs’ sports experience can positively moderate association between SCR. Mechanism examination shows promotes SCR through operational efficiency optimization, information, knowledge spillover in chain. Heterogeneity analysis positive impact more significant firms with high-skilled labor force, high heterogeneity executive team’s human capital, high-tech industries, regions strong digital infrastructure. Moreover, has diffusion effect on upstream downstream chain, improving adoption levels. Our research not only augments existing literature economic ramifications strategic value derived extramural but also offers both theoretical frameworks empirical insights recruitment fortifying

Язык: Английский

Процитировано

0
Impact of Industrial Robots on Labor Income Share: Empirical Evidence from Chinese A-Listed Companies DOI Open Access

Junhong Du,

Chuanyue Zhao,

Yingying Hu

и другие.

Sustainability, Год журнала: 2024, Номер 16(16), С. 6928 - 6928

Опубликована: Авг. 13, 2024

Based on data from the International Federation of Robotics (IFR) and Chinese A-Share Listed Companies 2011–2019, this paper evaluates how penetration industrial robots in China affects labor income share both theoretical empirical perspectives. We first develop a framework considering task model, consider different tasks matching types labor, construct model including based perform analysis finding that can improve income. Then, we explore mechanism price distortion as an intermediate variable reduce share, are able to effectively negative impact distortions share. After correcting for potential endogeneity problems, results confirm positive, significant, lasting robot confirming is underlying mechanisms through which At same time, firms’ shares varies significantly across regions, external financial dependence, skill premiums. Our findings help government provide decision-making basis better serve people new century, ensuring achievements economic development.

Язык: Английский

Процитировано

2
Can the Inclusiveness of Foreign Capital Improve Corporate Environmental, Social, and Governance (ESG) Performance? Evidence from China DOI Open Access
Bing He,

Cancan Ma

Sustainability, Год журнала: 2024, Номер 16(22), С. 9626 - 9626

Опубликована: Ноя. 5, 2024

Foreign direct investment (FDI) has become an important factor influencing corporate operational strategies, yet the impact of its inclusiveness on environmental, social, and governance (ESG) performance remains unclear. In this study, correlation city-level FDI with corporate-level ESG was investigated based data from 1258 Chinese A-share listed companies between 2011 2021. The effects underlying mechanisms were investigated. findings indicate that increase in significantly improves performance. Additionally, moderating role competitive advantage urban entrepreneurial vitality analyzed, Managerial green attention innovation capability play intermediary roles overall impact, total being positively moderated by investor attention. Furthermore, influence exhibits significant heterogeneity resulting variations digital policies, environmental ownership structures.

Язык: Английский

Процитировано

1
Impact of Telemedicine through Social Media: A Study of Topics in User Comments on Twitter DOI Creative Commons
Mario Sierra Martín, Fang-Wei Chen, Pilar Alarcón Urbistondo

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Окт. 14, 2024

Abstract Background The use of new technologies has transformed society, affecting communication, information seeking and ways working. Telemedicine, as a remote health practice through ICTs, grown exponentially, especially after the pandemic. Objective This qualitative study aims to explore users' perceptions concerns about telemedicine comments posted on Twitter by users, identifying primary, secondary residual themes. Methods Natural Language Processing (NLP) Machine Learning techniques, specifically Latent Dirichlet Allocation (LDA) model, were used analyse 156,633 extracted from related topics. Results The revealed several issues be addressed. Data was collected using keywords such "teleconsultation" "telemedicine". We can see that most frequent words in include "health", "service", "doctor" "patient". themes identified grouped into four dimensions: general information, benefits sought, specific professional issues. results showed 60.1% focused generic topics, ease service information. queries observed public nature, focusing accessibility, while disease or treatment topics less frequent. Conclusions provide for proper development social networks. is platform mainly queries, with convenience accessibility main mentioned. suggest online interactions are complex offer valuable insights improving communication strategies. Future research could hashtags differences interaction patterns according user profile, providing deeper understanding audiences' behaviour These findings underline importance considering audience preferences improve effectiveness communications.

Язык: Английский

Процитировано

0