Search results

1 – 4 of 4
Per page
102050
Citations:
Loading...
Available. Open Access. Open Access
Article
Publication date: 3 December 2021

Li Xuemei, Benshuo Yang, Yun Cao, Liyan Zhang, Han Liu, Pengcheng Wang and Xiaomei Qu

China's marine economy occupies an important position within the national economy, and its contribution thereto is constantly improving. The overall operation of the marine…

1083

Abstract

Purpose

China's marine economy occupies an important position within the national economy, and its contribution thereto is constantly improving. The overall operation of the marine economy shows positive developmental trends with potential for further growth. The purpose of this research is to analyse the prosperity of China's marine economy, reveal trends therein and forecast the likely turning point in its operation.

Design/methodology/approach

Based on the periodicity and fluctuation of China's marine economy development, China's marine economic prosperity indicator system is established from five perspectives. On this basis, China's marine economic operation prosperity index can be synthesised and calculated, then a dynamic factor model is constructed. Using the filtering method to calculate China's marine economic operational Stock–Watson index, Markov switching has been used to determine the trend to transition. Furthermore, China's current marine economic prosperity is evaluated through analysis of influencing factors and correlation analysis.

Findings

The analysis shows that, from 2017 to 2019, the operation of the marine economy is relatively stable, and the prosperity index supports this finding; meanwhile it also exposes problems in China's marine economy, such as an unbalanced industrial structure, low marine economic benefits and insufficient capacity for sustainable development.

Originality/value

Through the analysis of the prosperity of China's marine economy, the authors reveal the trends in China's marine economy and forecast its likely future turning point.

Details

Marine Economics and Management, vol. 4 no. 2
Type: Research Article
ISSN: 2516-158X

Keywords

Access Restricted. View access options
Article
Publication date: 21 July 2022

Wei Xiong, Meijiao Huang, Xi Yu Leung, Yuanhui Zhang and Xiaomei Cai

The aim of this study was to investigate the themes related to the achievement of Sustainable Development Goal (SDG) 12 in relation to tourism, and specifically to explore how the…

1047

Abstract

Purpose

The aim of this study was to investigate the themes related to the achievement of Sustainable Development Goal (SDG) 12 in relation to tourism, and specifically to explore how the emotional psyche affects tourists’ environmentally responsible behaviors.

Design/methodology/approach

Based on the value-belief-norm theory, a research framework was developed to examine the serial mediation effects of environmental emotions in predicting tourists’ environmentally responsible behaviors. A total of 741 responses was collected from an online survey. Data were analyzed by the partial least squares structural equation modeling.

Findings

Environmental concern does not directly predict tourists’ environmentally responsible behaviors. Instead, environmental awe and environmental worry serially mediate the relationship between environmental concern and tourists’ environmentally responsible behaviors.

Originality/value

This study extends the value-belief-norm theory by integrating environmental emotions and empirically tests the effect of multiple psyches on responsible consumption, contributing to the achievement of SDG 12 in UN Agenda 2030.

研究目的

本研究的目的是探究与旅游相关的可持续发展目标12的实现, 特别是探讨环境情感如何影响旅游者的环境责任行为。

研究方法

基于价值信念-规范理论, 构建了环境情感预测旅游者环境责任行为的链式中介模型。研究共收集741份有效样本, 并采用偏最小二乘结构方程模型进行分析。

研究发现

环境关心并不能直接预测旅游者的环境责任行为。但是, 环境敬畏和环境忧虑在环境关心与环境责任行为之间起链式中介作用。

原创性

本研究将环境情感扩展到价值信念规范理论中, 并实证检验了环境敬畏和环境忧虑两种环境情感对旅游者的负责任消费行为的影响, 呼应了联合国2030年议程中的可持续发展目标12。

Propósito

el objetivo de este estudio fue investigar los temas relacionados con el logro del Objetivo de Desarrollo Sostenible 12 en relación con el turismo, y específicamente explorar cómo la psique emocional afecta los comportamientos ambientalmente responsables de los turistas.

Diseño/metodología/enfoque

Basado en la teoría del valor-creencia-norma, se desarrolló un marco de investigación para examinar los efectos de mediación en serie de las emociones ambientales en la predicción de los comportamientos ambientalmente responsables de los turistas. Se recopiló un total de 741 respuestas de una encuesta en línea. Los datos se analizaron mediante el modelo de ecuaciones estructurales de mínimos cuadrados parciales.

Hallazgos

la preocupación ambiental no predice directamente los comportamientos ambientalmente responsables de los turistas. En cambio, el temor ambiental y la preocupación ambiental median en serie la relación entre la preocupación ambiental y los comportamientos ambientalmente responsables de los turistas.

Originalidad

este estudio amplía la teoría del valor-creencia-norma al integrar las emociones ambientales y prueba empíricamente el efecto de múltiples psiques en el consumo responsable, contribuyendo al logro del ODS 12 en la Agenda 2030 de la ONU.

Access Restricted. View access options
Article
Publication date: 7 June 2019

Xiaomei Wei, Yaliang Zhang, Yu Huang and Yaping Fang

The traditional drug development process is costly, time consuming and risky. Using computational methods to discover drug repositioning opportunities is a promising and efficient…

720

Abstract

Purpose

The traditional drug development process is costly, time consuming and risky. Using computational methods to discover drug repositioning opportunities is a promising and efficient strategy in the era of big data. The explosive growth of large-scale genomic, phenotypic data and all kinds of “omics” data brings opportunities for developing new computational drug repositioning methods based on big data. The paper aims to discuss this issue.

Design/methodology/approach

Here, a new computational strategy is proposed for inferring drug–disease associations from rich biomedical resources toward drug repositioning. First, the network embedding (NE) algorithm is adopted to learn the latent feature representation of drugs from multiple biomedical resources. Furthermore, on the basis of the latent vectors of drugs from the NE module, a binary support vector machine classifier is trained to divide unknown drug–disease pairs into positive and negative instances. Finally, this model is validated on a well-established drug–disease association data set with tenfold cross-validation.

Findings

This model obtains the performance of an area under the receiver operating characteristic curve of 90.3 percent, which is comparable to those of similar systems. The authors also analyze the performance of the model and validate its effect on predicting the new indications of old drugs.

Originality/value

This study shows that the authors’ method is predictive, identifying novel drug–disease interactions for drug discovery. The new feature learning methods also positively contribute to the heterogeneous data integration.

Details

Data Technologies and Applications, vol. 53 no. 2
Type: Research Article
ISSN: 2514-9288

Keywords

Access Restricted. View access options
Article
Publication date: 1 January 2025

Xin Zhang, Peng Yu and Liang Ma

The potential of generative AI (GenAI) to stimulate employee creativity has received extensive attention from industry and academia. However, there is still limited research on…

294

Abstract

Purpose

The potential of generative AI (GenAI) to stimulate employee creativity has received extensive attention from industry and academia. However, there is still limited research on strategically using GenAI to leverage its positive effects on employee creativity. This study aims to clarify the effects of different GenAI use purposes on employee creativity.

Design/methodology/approach

Based on self-determination theory, this study explores the effects of work-related and nonwork-related GenAI use on incremental and radical creativity through the mediator role of exploratory and exploitative learning and the boundary role of perceived ease of use. This study constructs a theoretical model and uses structural equation modeling to test the model by analyzing survey data from 330 employees.

Findings

(1) Work-related and nonwork-related GenAI use positively impacts incremental and radical creativity through exploratory and exploitative learning; (2) work-related GenAI use contributes more to exploitative learning than to exploratory learning, while nonwork-related GenAI use contributes more to exploratory learning than to exploitative learning; (3) exploitative learning has a stronger positive impact on incremental creativity, and exploratory learning has a stronger positive impact on radical creativity; (4) perceived ease of use weakens the positive effects of nonwork-related GenAI use on exploratory and exploitative learning.

Originality/value

First, this study enriches employee creativity research by revealing the relationship between different GenAI use purposes and incremental and radical creativity. Second, this study enriches employee creativity research by revealing the mediating role of exploratory and exploitative learning between GenAI use and incremental and radical creativity. Finally, this study enriches GenAI use research by revealing the moderating role of perceived ease of use between GenAI use and employee learning.

Details

European Journal of Innovation Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1460-1060

Keywords

1 – 4 of 4
Per page
102050