Matthew Tingchi Liu, Yongdan Liu, Ziying Mo, Zhidong Zhao and Zhenghao Zhu
The purpose of this paper is to focus on how corporate social responsibility (CSR) (i.e. responsibility to customers, employees and society) influences customer behavioural…
Abstract
Purpose
The purpose of this paper is to focus on how corporate social responsibility (CSR) (i.e. responsibility to customers, employees and society) influences customer behavioural loyalty in the hotel industry. The mediating effects of brand image and customer trust on the relationship between CSR and customer behavioural loyalty are also considered.
Design/methodology/approach
In total, 298 valid responses to questionnaire surveys were collected from a convenience sample in China in 2017. A structural equation model was used to test the hypotheses.
Findings
Hotel customer behavioural loyalty can be enhanced by CSR performance. Performance in each of the three CSR domains positively impacted customer behavioural loyalty to different degrees. The impact of CSR on the customer had the strongest influence on Chinese customers’ behavioural loyalty among the three CSR domains of customer, employee and society. Brand image and customer trust were found to be mediators of the relationship between CSR performance and customer behavioural loyalty.
Originality/value
The current research contributes to the literature by demonstrating that CSR activities are not all equally effective. Results reveal that the society dimension of CSR had the strongest impact on Chinese customers’ brand image of hotels among the three CSR dimensions investigated. In terms of Chinese hotel customers’ trust, the CSR–customer dimension plays the most effective role. The findings also support the notion that Chinese consumers are beginning to use CSR information to evaluate hotels.
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Hongjoo Woo, Wi-Suk Kwon, Amrut Sadachar, Zhenghao Tong and Jimin Yang
When retail businesses, especially small businesses with greater vulnerability, could not meet consumers in person during the recent pandemic crisis, how did they adapt to the…
Abstract
Purpose
When retail businesses, especially small businesses with greater vulnerability, could not meet consumers in person during the recent pandemic crisis, how did they adapt to the situation? This study examined how small business practitioners (SBPs’) perceptions, trust and adoption intention levels for social media, as well as the relationships among these variables, changed before and during the crisis based on the integration of the contingency theory and the diffusion of innovation theory (DIT).
Design/methodology/approach
Online surveys were conducted with USA SBPs before (n = 175) and during (n = 225) the recent pandemic. The hypotheses were tested using structural equation modeling (SEM), multivariate analysis of variance (MANOVA) and multiple-group SEM analysis.
Findings
The results confirmed significant sequential positive relationships between SBPs’ perceived external pressure and perceived benefits of adopting social media, which in turn led to their trust in and then adoption intentions for social media. Further, the comparisons between the pre- and in-pandemic samples revealed that SBPs’ perceptions and adoption intentions all became significantly higher during (vs before) the pandemic, but the structural relationships among these variables weakened during the pandemic.
Originality/value
This study uses a novel approach to integrate the contingency theory with the DIT to propose small businesses' perceptions, trust and adoption intentions for social media during the innovation decision process under rapid contingency changes. Our findings also offer practical implications including recommendations for small businesses’ innovation management as well as training programs.
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Zhenghao Liu, Yuxing Qian, Wenlong Lv, Yanbin Fang and Shenglan Liu
Stock prices are subject to the influence of news and social media, and a discernible co-movement pattern exists among multiple stocks. Using a knowledge graph to represent news…
Abstract
Purpose
Stock prices are subject to the influence of news and social media, and a discernible co-movement pattern exists among multiple stocks. Using a knowledge graph to represent news semantics and establish connections between stocks is deemed essential and viable.
Design/methodology/approach
This study presents a knowledge-driven framework for predicting stock prices. The framework integrates relevant stocks with the semantic and emotional characteristics of textual data. The authors construct a stock knowledge graph (SKG) to extract pertinent stock information and use a knowledge graph representation model to capture both the relevant stock features and the semantic features of news articles. Additionally, the authors consider the emotional characteristics of news and investor comments, drawing insights from behavioral finance theory. The authors examined the effectiveness of these features using the combined deep learning model CNN+LSTM+Attention.
Findings
Experimental results demonstrate that the knowledge-driven combined feature model exhibits significantly improved predictive accuracy compared to single-feature models.
Originality/value
The study highlights the value of the SKG in uncovering potential correlations among stocks. Moreover, the knowledge-driven multi-feature fusion stock forecasting model enhances the prediction of stock trends for well-known enterprises, providing valuable guidance for investor decision-making.
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Yan Liang, Yingying Wei, Panjie Li, Liangliang Li and Zhenghao Zhao
For coastal bridges, the ability to recover traffic functions after the earthquake has crucial implications for post-disaster reconstruction, which makes resilience become a…
Abstract
Purpose
For coastal bridges, the ability to recover traffic functions after the earthquake has crucial implications for post-disaster reconstruction, which makes resilience become a significant index to evaluate the seismic behavior. However, the deterioration of the material is particularly prominent in coastal bridge, which causes the degradation of the seismic behavior. As far, the research studies on resilience of coastal bridges considering multiple degradation factors and different disaster prevention capability are scarce. For further evaluating the seismic behavior of coastal bridge in the long-term context, the seismic resilience is conducted in this paper with considering multiple durability damage.
Design/methodology/approach
The fuzzy theory and time-varying fragility analysis are combined in this paper to obtain the life-cycle resilience of coastal bridges.
Findings
The results show that durability damage has a remarkable impact on the resilience. After 100 years of service, the seismic resilience of bridge with poor disaster-prevention capability has greatest reduction, about 18%. In addition, the improvement of the disaster prevention capability can stabilize the resilience of the bridge at a higher level.
Originality/value
In this paper, the time-varying fragility analysis of case bridge are evaluated with considering chloride ion erosion and concrete carbonization, firstly. Then, combining fuzzy theory and fragility analysis, the triangular fuzzy values of resilience parameters under different service period are obtained. Finally, the life-cycle resilience of bridge in different disaster prevention capability is analyzed.
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Valentina Goglio and Sonia Bertolini
The study aims to investigate whether participation to massive open online courses (MOOCs) may lead to labor market returns and through which mechanisms such relative advantage…
Abstract
Purpose
The study aims to investigate whether participation to massive open online courses (MOOCs) may lead to labor market returns and through which mechanisms such relative advantage may take place. Indeed, despite high figures of registered users, empirical studies on occupational returns are limited and MOOCs may represent a viable, cost-efficient example of lifelong learning practice to respond to the demand of a better skilled workforce for the fourth industrial revolution.
Design/methodology/approach
The study is based on qualitative empirical material constituted by a set of 21 qualitative semi-structured interviews conducted in 2019 among learners who registered in MOOCs provided by European higher education institutions.
Findings
Interviews return a situation in which MOOCs are beneficial for work: learners appreciate the new knowledge and skills they can access, with time flexibility and low entry cost. However, MOOCs positive contribution is not at everyone’s reach: self-selection issues tend to further advantage individuals with high levels of education and individual resources. Moreover, MOOCs can increase the risk of a shift of responsibility for training to the employees and qualify as a lower tier type of qualification, reinforcing social closure mechanisms based on educational credentials.
Originality/value
The study contributes to the empirical analysis of MOOCs economic returns empirically, by providing original qualitative material. Second, it contributes theoretically by bridging literature on economic and occupational returns to education on one side and literature on digital technologies in education on the other, providing new insights on the potentials and limits of MOOCs as a new form of lifelong learning.
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China is currently developing and promoting an industrial cluster policy at the government level. By enacting the ‘Opinion on promoting industrial cluster development’, China is…
Abstract
China is currently developing and promoting an industrial cluster policy at the government level. By enacting the ‘Opinion on promoting industrial cluster development’, China is supporting the development of industrial clusters. Building an industrial cluster is done by using a single factor but requires many additional factors like regional characteristics, competitiveness factors are also diversified. To evaluate the competitiveness of the Chinese automobile industry cluster, a competitiveness element index should be developed and a competitiveness evaluation method is needed to evaluate the importance of each element. To accomplish this objective, this research applied the analytic hierarchy process (AHP) and focused on the importance of the competitiveness elements.
This research investigated the character is tics regarding cases of clusters and also analyzed the competitiveness of the Changchun automobile cluster located in northeastern China. The purpose of this research is to help Korean enterprises who enter China in the hopes that Korea will emerge as a top automobile production country.
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Hongman Liu, Shibin Wen and Zhuang Wang
Agricultural carbon productivity considers the dual goals of “agricultural economic growth” and “carbon emission reduction”. Improving agricultural carbon productivity is a…
Abstract
Purpose
Agricultural carbon productivity considers the dual goals of “agricultural economic growth” and “carbon emission reduction”. Improving agricultural carbon productivity is a requirement for promoting green and low-carbon development of agriculture. Agricultural production agglomeration is widespread worldwide, but the relationship between agricultural production agglomeration and agricultural carbon productivity is inconclusive. This paper aims to study the impact of agricultural production agglomeration on agricultural carbon productivity, which is conducive to a better understanding of the relationships among agglomeration, agricultural economic development and carbon emission, better planning of agricultural layout to build a modern agricultural industrial system and achieve the goal of carbon peaking and carbon neutrality.
Design/methodology/approach
Based on China's provincial data from 1991 to 2019, this paper uses non-radial directional distance function (NDDF) and Metafrontier Malmquist–Luenberger (MML) productivity index to measure total factor agricultural carbon productivity. Subsequently, using a panel two-way fixed effect model to study the effect and mechanism of agricultural production agglomeration on agricultural carbon productivity, and the two-stage least squares method (IV-2SLS) is used to solve endogeneity. Finally, this paper formulates a moderating effect model from the perspective of the efficiency of agricultural material capital inputs.
Findings
The empirical results identify that Chinese provincial agricultural carbon productivity has an overall growth trend and agricultural technological progress is the major source of growth. There is an inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity. The input efficiency of agricultural film, machine and water resources have moderating effects on the inverted U-shaped relationship. Agricultural production agglomeration also promotes agricultural carbon productivity by inhibiting agricultural carbon emissions in addition to affecting agricultural input factors and its internal mechanisms are agricultural green technology progress and rural human capital improvement.
Originality/value
This paper innovatively adopts the NDDF–MML method to measure the total factor agricultural carbon productivity more scientifically and accurately and solves the problems of ignoring group heterogeneity and the shortcomings of traditional productivity measurement in previous studies. This paper also explains the inverted U-shaped relationship between agricultural production agglomeration and agricultural carbon productivity theoretically and empirically. Furthermore, from the perspective of agricultural material capital input efficiency, this paper discusses the moderating effect of input efficiency of fertilizers, pesticides, agricultural film, agricultural machines and water resources on agricultural production agglomeration affecting agricultural carbon productivity and answers the mechanism of carbon emission reduction of agricultural production agglomeration.
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Jiahao Zhang and Yu Wei
This study conducts a comparative analysis of the diversification effects of China's national carbon market (CEA) and the EU ETS Phase IV (EUA) within major commodity markets.
Abstract
Purpose
This study conducts a comparative analysis of the diversification effects of China's national carbon market (CEA) and the EU ETS Phase IV (EUA) within major commodity markets.
Design/methodology/approach
The study employs the TVP-VAR extension of the spillover index framework to scrutinize the information spillovers among the energy, agriculture, metal, and carbon markets. Subsequently, the study explores practical applications of these findings, emphasizing how investors can harness insights from information spillovers to refine their investment strategies.
Findings
First, the CEA provide ample opportunities for portfolio diversification between the energy, agriculture, and metal markets, a desirable feature that the EUA does not possess. Second, a portfolio comprising exclusively energy and carbon assets often exhibits the highest Sharpe ratio. Nevertheless, the inclusion of agricultural and metal commodities in a carbon-oriented portfolio may potentially compromise its performance. Finally, our results underscore the pronounced advantage of minimum spillover portfolios; particularly those that designed minimize net pairwise volatility spillover, in the context of China's national carbon market.
Originality/value
This study addresses the previously unexplored intersection of information spillovers and portfolio diversification in major commodity markets, with an emphasis on the role of CEA.