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1 – 2 of 2Dan Liu, Tiange Liu and Yuting Zheng
By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the…
Abstract
Purpose
By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the sustainable practices implemented in these developed regions, and derive valuable insights that can foster the promotion of green transformation.
Design/methodology/approach
First, the urban green development system (GDS) was decomposed into the economic benefit subsystem (EBS), social benefit subsystem (SBS), and pollution control subsystem (PCS). Then, a mixed network SBM model was proposed to evaluate the GDE during 20152020, with Moran’s I and Bootstrap truncated regression model subsequently applied to measure the spatial characteristics and driving factors of efficiency.
Findings
Subsystem efficiency presents a distribution trend of PCS > EBS > SBS. There is a particular spatial aggregation effect in EBS efficiency, whereas SBS and PCS efficiencies have no significant spatial autocorrelation. Furthermore, urbanization level contributes significantly to the efficiency of all subsystems; industrial structure, energy consumption, and technological innovation play a crucial role in EBS and SBS; external openness is a pivotal factor in SBS; and environmental regulation has a significant effect on PCS.
Originality/value
This study further decomposes the black box of GDS into subsystems including the economy, society, and environment. Additionally, by employing a mixed network SBM model and Bootstrap truncated regression model to investigate efficiency and its driving factors from the subsystem perspective, it endeavors to derive more detailed research conclusions and policy implications.
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Ying Chang, Chubing Zhang, Tiange Li and Yina Li
This study aims to examine the effects of the perceived warmth and competence of humanoid robots on customer tolerance of service failure through the affective response and the…
Abstract
Purpose
This study aims to examine the effects of the perceived warmth and competence of humanoid robots on customer tolerance of service failure through the affective response and the boundary condition of relationship norms.
Design/methodology/approach
Two experimental studies were conducted to investigate the effects of perceived warmth and competence of humanoid robots’ physical appearances on tolerance of service failure and the mediating role of anger. The boundary influence of relationship norms is also explored.
Findings
The results reveal that the perception of warmth (vs. competence) robot leads to less (more) anger, which significantly results in tolerance of service failure. However, customer tolerance is insignificant under exchange norms, as the undelivered service violates the expectations of both warm and competent robots.
Practical implications
This study provides practical guidance for hospitality managers to implement humanoid robots in a way that minimizes the negative outcomes of service failure. Managers should also think about the appropriate match of different types of humanoid robots and relationship norms in which robots will be deployed.
Originality/value
This study contributes to the tolerance literature by taking a social cognition perspective to investigate the effect of humanoid robots’ physical appearances on customers’ reactions to service failure. The findings also reveal that its affective mechanism lies in the effect of expectancy violations of service failure on tolerance. Furthermore, this study extends the literature on relationship norms to the influence of company factors on effective humanoid robot implementation.
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