Taiye Luo, Juanjuan Qu and Shuo Cheng
Innovation resilience, which refers to firms’ ability to consistently innovate and recover from disruptions, has recently gained increasing attention. Digital transformation plays…
Abstract
Purpose
Innovation resilience, which refers to firms’ ability to consistently innovate and recover from disruptions, has recently gained increasing attention. Digital transformation plays a crucial role in the innovation of manufacturing firms. This paper aims to investigate the impact mechanisms of manufacturing firms’ innovation resilience in the context of digital transformation.
Design/methodology/approach
Using panel data from Chinese A-share listed manufacturing firms spanning from 2017 to 2022 as an example, this research examines the impact of digital transformation on innovation resilience. It also tests the moderating effect of innovation network embeddedness and the mediation effect of absorptive capacity.
Findings
It is found that digital transformation can enhance the innovation resilience of manufacturing firms. Furthermore, the structural embeddedness and relational embeddedness of manufacturing firms within innovation networks moderate the relationship between digital transformation and innovation resilience. The absorptive capacity of manufacturing firms acts as a mediator in the relationship between digital transformation and innovation resilience.
Originality/value
This paper is one of the first studies that investigates the impact mechanisms of digital transformation on the innovation resilience of manufacturing firms based on network embeddedness theory and dynamic capability theory.
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Taiye Luo, Juanjuan Qu and Shuo Cheng
Enhancing total factor productivity through digital transformation is a crucial pathway for the high-quality development of manufacturing enterprises. This research aims to…
Abstract
Purpose
Enhancing total factor productivity through digital transformation is a crucial pathway for the high-quality development of manufacturing enterprises. This research aims to investigate the impact mechanisms of manufacturing enterprises’ total factor productivity in the context of digital transformation.
Design/methodology/approach
Using the data from 536 Chinese listed manufacturing enterprises from 2018 to 2021, this research divides digital transformation into two dimensions (i.e. digital transformation breadth and digital transformation depth) and examines their impacts on total factor productivity as well as the mediation effects of innovation capability and reconfiguration capacity.
Findings
It is found that digital transformation breadth, digital transformation depth and their interaction can positively affect manufacturing enterprises’ total factor productivity. The innovation capability and reconfiguration capacity of manufacturing enterprises act as mediators between digital transformation breadth and total factor productivity, as well as between digital transformation depth and total factor productivity.
Originality/value
This study is one of the first attempts to investigate the impact mechanisms of manufacturing enterprises’ total factor productivity from the perspective of digital transformation breadth and depth.
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Li Zhou, Ying Lu, Hu Yu, Lin Lu, Dianting Wu and Juanjuan Zhao
While the economic benefits of the exhibition industry for the hotel sector have been addressed, the impact of exhibitions on individual hotels is unknown, especially when…
Abstract
Purpose
While the economic benefits of the exhibition industry for the hotel sector have been addressed, the impact of exhibitions on individual hotels is unknown, especially when individual hotels’ star classification and locations are considered. This study aims to provide a better understanding of how room rates of different hotels change during different stages of the Canton Fair in China from a spatial-temporal perspective.
Design/methodology/approach
Room rates of 681 star-hotels within the city of Guangzhou before, during and after the Fair were extracted from websites. Through spatial interpolation and autocorrelation analysis and geographical detector (GeoDetector) technique, spatial and temporal patterns of hotel room rates and the interdependence between the convention center and the hotels with different star classification and locations were examined.
Findings
An inverse-U shape of room rate change was identified before, during and after the Fair, and the five-star hotels had the sharpest increase. Moreover, the distribution of hotel room rates followed the law of distance decay. The variation of hotel rates became larger when the distance to the convention center was larger. Spatial high-high clusters varied among hotels with different star classification.
Originality/value
This study contributed to the hotel literature by providing empirical evidence regarding how hotels with different star classification and locations were affected by events. This study also advanced the event literature by introducing GeoDetector. The findings of this study offered insights into the hotel location selection, pricing strategies and hotel collaboration with events.
研究目的
虽然展览业对酒店业的经济效益已经得到解决, 但展览对单个酒店的影响尚不清楚, 尤其是在考虑单个酒店的星级和位置时。本研究旨在从时空角度更好地了解中国广交会不同阶段不同酒店的房价变化情况。
研究方法
网站提取了广交会前、中、后广州市内681家星级酒店的房价。通过空间插值和自相关分析以及地理探测器(GeoDetector)技术, 研究了酒店房价的时空格局以及会议中心与不同星级和位置的酒店之间的相互依赖关系。
研究发现
会前、会中、会后房价变化呈倒U型, 其中五星级酒店涨幅最大。此外, 酒店房价的分布遵循距离衰减规律。到会展中心的距离越远, 酒店价格的变化就越大。不同星级酒店的空间高-高集群存在差异。
研究原创性
该研究通过提供关于不同星级和位置的酒店如何受到事件影响的经验证据, 为酒店文献做出了贡献。这项研究还通过引入 GeoDetector 推进了事件文献。研究结果为酒店选址、定价策略和酒店与活动的合作提供了见解。
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Li Si, Yueting Li, Xiaozhe Zhuang, Wenming Xing, Xiaoqin Hua, Xin Li and Juanjuan Xin
The purpose of this paper is to conduct performance evaluation of eight main scientific data sharing platforms in China and find existing problems, thus providing reference for…
Abstract
Purpose
The purpose of this paper is to conduct performance evaluation of eight main scientific data sharing platforms in China and find existing problems, thus providing reference for maximizing the value of scientific data and enhancing scientific research efficiency.
Design/methodology/approach
First, the authors built an evaluation indicator system for the performance of scientific data sharing platforms. Next, the analytic hierarchy process was employed to set indicator weights. Then, the authors use experts grading method to give scored for each indicator and calculated the scoring results of the scientific data sharing platform performance evaluation. Finally, an analysis of the results was conducted.
Findings
The performance evaluation of eight platforms is arranged by descending order by the value of F: the Data Sharing Infrastructure of Earth System Science (76.962), the Basic Science Data Sharing Center (76.595), the National Scientific Data Sharing Platform for Population and Health (71.577), the China Earthquake Data Center (66.296), the China Meteorological Data Sharing Service System (65.159), the National Agricultural Scientific Data Sharing Center (55.068), the Chinese Forestry Science Data Center (56.894) and the National Scientific Data Sharing & Service Network on Material Environmental Corrosion (Aging) (52.528). And some existing shortcomings such as the relevant policies and regulation, standards of data description and organization, data availability and the services should be improved.
Originality/value
This paper is mainly discussing about the performance evaluation system covering operation management, data resource, platform function, service efficiency and influence of eight scientific data sharing centers and made comparative analysis. It reflected the reality development of scientific data sharing in China.