How Do Digital Capabilities Impact the Sustained Growth of Entrepreneurial Income: Evidence from Chinese Farmer Entrepreneurs DOI Open Access

Shanhu Zhang,

Jinxiu Yang, Yun Shen

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(17), P. 7522 - 7522

Published: Aug. 30, 2024

The application of digital technology in China’s rural areas has triggered a brand-new allocation agricultural factors, posing challenges to the sustainable growth entrepreneurial income. Using empowerment theory and process theory, this paper explores mediating role alertness resource bricolage relationship between capabilities questionnaire survey data from 490 farmer entrepreneurs China, empirically tests effect on income through multiple regression model. findings show that: (1) have significant positive increase income; (2) applicational innovation can affect intermediary paths bricolage; (3) more impact sustained for young farmers those with professional work experience large cities who embark farming entrepreneurship. This reveals when embedded process. It also provides theoretical reference empirical support government formulate reasonable policies offers new solutions promote development capabilities.

Language: Английский

Extreme weather and the green transition of energy firms: The moderating effect of digital technology and digital inclusive finance DOI

Niu Niu,

Junhua Ma,

Deyuan Zheng

et al.

Research in International Business and Finance, Journal Year: 2025, Volume and Issue: unknown, P. 102858 - 102858

Published: March 1, 2025

Language: Английский

Citations

1
The Adoption of Blockchain and Financing Constraints: Evidence from China DOI
Dengjia Li, Chaoqun Ma, Hao Li

et al.

International Review of Economics & Finance, Journal Year: 2024, Volume and Issue: 96, P. 103672 - 103672

Published: Oct. 9, 2024

Language: Английский

Citations

4
Predictive Analytics Solution for Digital Capabilities Identification Towards Business Performance Improvement DOI Creative Commons
Iman Raeesi Vanani, Mohammad Taghi Taghavifard, Mohammad Amin Yalpanian

et al.

SN Computer Science, Journal Year: 2025, Volume and Issue: 6(1)

Published: Jan. 20, 2025

Language: Английский

Citations

0
Predicting 30-Day Hospital Readmission in Medicare Patients: Insights from an LSTM Deep Learning Model DOI Creative Commons
Xintao Li,

Sibei Liu

Published: Sept. 9, 2024

Abstract Background Readmissions among Medicare beneficiaries are a major problem for the US healthcare system from perspective of both operations and patient caregiving outcomes. Our study analyzes hospital readmissions using LSTM networks with feature engineering to assess contributions. Design The 21002 senior admission data MIMIC-III clinical database at Beth Israel Deaconess Medical Center.is utilized in We selected variables admission-level data, inpatient medical history demography. baseline model is logistic-regression based on LACE index, designed capture temporal dynamic patient-level data. leveraged Area Under Curve metric, precision recall evaluate model’s performance. Results outperformed logistic regression baseline, accurately leveraging features predict readmission. were Charlson Comorbidity Index, length stay, admissions over past 6 months or number medications before discharge, while demographic less impactful Limitations use single-center limits generalizability findings. Additionally, exclusion specific chronic conditions external factors limit ability complexities diseases. Conclusions This work suggests that offers more promising approach improve readmission prediction. It captures interactions databases, enhancing current prediction models providers. Implications Adoption predictive into practice may be effective identifying patients provide early targeted interventions Highlights Improved Prediction: outperforms index predicting readmissions. Feature Contribution: ranks base impact, deprioritizing importance variables, highlighting patients’ diseases leading hospitalizations guiding prevent Effective Use Data: incorporates time-series enhance accuracy all-cause predictions, especially high-risk patients. Actionable Insights: result demonstrates utilization deep learning decision-making reduce seniors.

Language: Английский

Citations

2
Has Digital Transformation Enhanced the Resilience of Manufacturing Enterprises? DOI
Yuqing Zhan, Wanhong Li

International Review of Economics & Finance, Journal Year: 2024, Volume and Issue: unknown, P. 103688 - 103688

Published: Oct. 1, 2024

Language: Английский

Citations

2
How Do Digital Capabilities Impact the Sustained Growth of Entrepreneurial Income: Evidence from Chinese Farmer Entrepreneurs DOI Open Access

Shanhu Zhang,

Jinxiu Yang, Yun Shen

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(17), P. 7522 - 7522

Published: Aug. 30, 2024

The application of digital technology in China’s rural areas has triggered a brand-new allocation agricultural factors, posing challenges to the sustainable growth entrepreneurial income. Using empowerment theory and process theory, this paper explores mediating role alertness resource bricolage relationship between capabilities questionnaire survey data from 490 farmer entrepreneurs China, empirically tests effect on income through multiple regression model. findings show that: (1) have significant positive increase income; (2) applicational innovation can affect intermediary paths bricolage; (3) more impact sustained for young farmers those with professional work experience large cities who embark farming entrepreneurship. This reveals when embedded process. It also provides theoretical reference empirical support government formulate reasonable policies offers new solutions promote development capabilities.

Language: Английский

Citations

1