Guanghao Wang, Chenghao Liu, Erwann Sbai, Mingyue Selena Sheng, Jinhong Hu and Miaomiao Tao
The purpose of this study is to examine Bitcoin's price behavior across market conditions, focusing on the influence of Bitcoin's historical prices, news sentiment and market…
Abstract
Purpose
The purpose of this study is to examine Bitcoin's price behavior across market conditions, focusing on the influence of Bitcoin's historical prices, news sentiment and market indicators like oil prices, gold and the S&P index. The authors also assess the stability of Bitcoin-inclusive hedging portfolios under different market conditions, for example, bearish, bullish and moderate market states.
Design/methodology/approach
This study uses the Quantile Autoregressive Distributed Lag model to explore the effects of different factors on Bitcoin's prices across various market situations. This method allows for a detailed analysis of historical trends, investor expectations and external market influences on Bitcoin's price movements and systematic stability.
Findings
Key findings reveal historical prices and investor expectations significantly influence Bitcoin in all market scenarios, with news sentiment exhibiting substantial volatility. This study indicates that oil prices have minimal impacts on Bitcoin, whereas gold is a stabilizing asset in bear markets, with the S&P index influencing short-term fluctuations. At the same time, Bitcoin's volatility varies with market conditions, proving more efficient as a hedging tool in bear and stable markets than in bull ones.
Originality/value
This study highlights the intrinsic correlation between Bitcoin's prices, news sentiment and financial market indicators, enhancing understanding of Bitcoin's market dynamics. The authors demonstrate Bitcoin's weak direct correlation with commodities like oil, the stabilizing role of gold in crypto portfolios and the stock market's indirect effect on Bitcoin prices. By examining these factors' impacts across various market conditions, the findings offer strategies for investors to improve hedging and portfolio management in cryptocurrency markets.
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Jinhong Gong, Xinhua Guan and Tzung-Cheng Huan
This study aims to explore the key attributes of robot chef restaurants and their influencing factors from the perspective of customers and analyzes how these key attributes…
Abstract
Purpose
This study aims to explore the key attributes of robot chef restaurants and their influencing factors from the perspective of customers and analyzes how these key attributes affect customer perceived value.
Design/methodology/approach
A mixed-methods research design was used in this study. Using 473 online reviews and ratings (Study 1), the research summarized customers’ evaluations on three types of attributes (environment, service and food) and identified the key attributes along with their influencing factors. Subsequently, through field questionnaires (Study 2) involving 269 actual customers, structural equation modeling was used to analyze how the identified key attributes and their influencing factors impact customer perceived value.
Findings
This study reveals that customers in robot chef restaurants prioritize food attributes, particularly valuing food authenticity alongside food quality. In contrast to traditional restaurants, customers’ evaluations of food attributes in robot chef restaurants are significantly influenced by the competence of robot chefs. Notably, customers’ negative attitudes toward robots diminish the positive effects on both food quality and food authenticity.
Practical implications
To enhance customer perceived value, robot chef restaurants should concentrate on food attributes. They can achieve this by fostering a high-quality, authentic food experience through the elevation of robot chefs’ competence and by providing customer education.
Originality/value
This study expands research on the customer experience in robotic restaurants by proposing an integrated model determining factors that affect the perceived customer value.
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Xinhua Guan, Jinhong Gong, Mingjie Li and Tzung-Cheng Huan
The purpose of this study is to explore the impact of the robot restaurant servicescape and robot service competence (RSC) on customers’ behavioral intentions and to analyze the…
Abstract
Purpose
The purpose of this study is to explore the impact of the robot restaurant servicescape and robot service competence (RSC) on customers’ behavioral intentions and to analyze the mediating role of hedonic value (HV) and utilitarian value (UV) in these relationships and the moderating role of individual characteristics.
Design/methodology/approach
This research involves seven constructs to be measured, namely, servicescape, RSC, negative attitude toward robots (NAR), openness to change (OC), HV, UV and behavioral intention. This research selects Foodom robot restaurants, located in Shunde and Guangzhou of China, as the research site, and the research objects are customers having dinner in the restaurant. A total of 485 valid data was collected. Structural equation modeling was used to analyze the data, verify the proposed research model, and test the research hypotheses.
Findings
The study finds that servicescape and RSC improve customer behavioral intention. Additionally, HV and UV mediate the influence of servicescape and RSC on customer behavioral intention. Moreover, OC negatively moderates the influence of servicescape on UV and that a NAR negatively moderates the influence of RSC on HV.
Originality/value
Through carefully design of servicescape and the improvement in service capabilities of robots, the original service delivery dominated by frontline service personnel can be transformed into service delivery dominated by service robots, which is conductive to providing a pleasant and unforgettable experience for customers.
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Yubing Dong, Chen Qian, Jian Lu and Yaqin Fu
Epoxy (EP) and polye-caprolactone (PCL) are typical dual-shape memory polymer (DSMP). To get excellent triple-shape memory effect (TSME) polymer composites which are made from EP…
Abstract
Purpose
Epoxy (EP) and polye-caprolactone (PCL) are typical dual-shape memory polymer (DSMP). To get excellent triple-shape memory effect (TSME) polymer composites which are made from EP and PCL. Miscible PCL/EP blend composites have been investigated and compared to the TSMEs with electrospun PCL microfiber membranes/EP composites. Clay montmorillonite (MMT)-modified electrospun PCL microfiber membranes were prepared to improve the shape memory fixities of electrospun PCL microfiber membranes/EP composites.
Design/methodology/approach
The morphologies of electrospun PCL microfiber membranes and the cross section of PCL/EP composites were studied using a field emission scanning electron microscope (FE-SEM), and the existence of MMT was confirmed by a transmission electron microscope. Thermal mechanical properties were observed by a differential scanning calorimeter (DSC) and a dynamic thermomechanical analysis machine, and the TSMEs were also determined through dynamic mechanical analysis.
Findings
Results indicate that the TSMEs of electrospun PCL microfiber membranes/EP composites were excellent, whereas the TSMEs of PCL/EP blend composites were poor. The TSMEs of PCL electrospun microfiber membranes/EP composites significantly improved with the addition of the PCL electrospun microfiber modified with moderate MMT.
Research limitations/implications
Adding a moderate content of MMT into the electrospun PCL fibers, could improve the TSME of the PCL fiber membranes/EP composites. This study was to create a simple and effective method that can be applied to improve the performance of other SMP.
Originality/value
A novel triple-shape memory composite were made from dual-shape memory EP and electrospun PCL fiber membranes.
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Linlin Xie, Ting Xu, Tianhao Ju and Bo Xia
The alienation of megaproject environmental responsibility (MER) behavior is destructive, but its mechanism has not been clearly depicted. Based on fraud triangle theory and the…
Abstract
Purpose
The alienation of megaproject environmental responsibility (MER) behavior is destructive, but its mechanism has not been clearly depicted. Based on fraud triangle theory and the fuzzy set qualitative comparative analysis (fsQCA) method, this study explored the combined effect of antecedent factors on alienation of MER behavior.
Design/methodology/approach
Based on the fraud triangle theory and literature review, eight influencing factors associated with the alienation of MER behavior were first identified. Subsequently, the fuzzy-set qualitative comparative analysis was used in this study to reveal configurations influencing alienation of MER behavior.
Findings
The study found nine configurations of MER behavioral alienation antecedent factors, integrated into three types of driving modes, i.e. “economic pressure + learning effect,” “institutional defect + moral rejection,” and “information asymmetry + economic pressure + expectation pressure.”
Originality/value
By analyzing the configuration effects of various induced conditions, this study puts forward a comprehensive analysis framework to solve the alienation of MER behavior in the megaprojects and a practical strategy to control alienation of MER behavior.
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This study aims to address how the social structure of the hospitality management field has evolved from 1960 to 2016.
Abstract
Purpose
This study aims to address how the social structure of the hospitality management field has evolved from 1960 to 2016.
Design/methodology/approach
The informal social structure of the hospitality management literature was analyzed by collecting authorship data from seven hospitality management journals. Co-authorship analyses via network analysis were conducted.
Findings
According to the findings, throughout the history of hospitality management, international collaboration levels are relatively low. Based on social network analysis, the research community is only loosely connected, and the network of the community does not fit with the small-world network theory. Additional findings indicate that researchers in the hospitality management literature are ranked via degree centrality, closeness centrality and betweenness centrality. Cliques, which contain at least five researchers, and core researchers are identified.
Practical implications
This study helps both scholars and practitioners improve the informal structure of the field. Scholars must generate strong ties to strengthen cross-fertilization in the field; hence, they collaborate with authors who have strong positions in the field. Specifically, this provides a useful performance analysis. To the extent that institutions and individuals are rewarded for publications, this study demonstrates the performance and connectivity of several key researchers in the field. This finding could be interesting to (post)graduate students. Hospitality managers looking for advisors and consultants could benefit from the findings. Additionally, these are beneficial for journal editors, junior researchers and agencies/institutions.
Originality/value
As one of the first study in the field, this research examines the informal social structure of hospitality management literature in seven journals.
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Nasiru Salihu, Poom Kumam, Sulaiman Mohammed Ibrahim and Huzaifa Aliyu Babando
Previous RMIL versions of the conjugate gradient method proposed in literature exhibit sufficient descent with Wolfe line search conditions, yet their global convergence depends…
Abstract
Purpose
Previous RMIL versions of the conjugate gradient method proposed in literature exhibit sufficient descent with Wolfe line search conditions, yet their global convergence depends on certain restrictions. To alleviate these assumptions, a hybrid conjugate gradient method is proposed based on the conjugacy condition.
Design/methodology/approach
The conjugate gradient (CG) method strategically alternates between RMIL and KMD CG methods by using a convex combination of the two schemes, mitigating their respective weaknesses. The theoretical analysis of the hybrid method, conducted without line search consideration, demonstrates its sufficient descent property. This theoretical understanding of sufficient descent enables the removal of restrictions previously imposed on versions of the RMIL CG method for global convergence result.
Findings
Numerical experiments conducted using a hybrid strategy that combines the RMIL and KMD CG methods demonstrate superior performance compared to each method used individually and even outperform some recent versions of the RMIL method. Furthermore, when applied to solve an image reconstruction model, the method exhibits reliable results.
Originality/value
The strategy used to demonstrate the sufficient descent property and convergence result of RMIL CG without line search consideration through hybrid techniques has not been previously explored in literature. Additionally, the two CG schemes involved in the combination exhibit similar sufficient descent structures based on the assumption regarding the norm of the search direction.
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He Huang, Jing Huang and Yanfeng Zhong
This study clarifies the operational performance of fashion companies during the coronavirus pandemic. Meanwhile, improvement strategies have been provided in the post-pandemic…
Abstract
Purpose
This study clarifies the operational performance of fashion companies during the coronavirus pandemic. Meanwhile, improvement strategies have been provided in the post-pandemic era.
Design/methodology/approach
The static and dynamic perspectives were combined to comprehensively analyze the operational performance of fashion companies before, during and after the COVID-19 outbreak. A comparative analysis among five representative countries was conducted to achieve global conclusions. Additionally, data envelopment analysis (DEA) theory and various DEA models were employed for the analysis.
Findings
The fashion industry has not achieved overall effectiveness. American companies have the best operational performance, followed by European and Chinese companies. In contrast, the impact of the pandemic on American companies was severe, whereas Chinese and European companies showed operational resilience. In addition, the pandemic had a devastating influence on the global fashion industry. This resulted in a decline in total factor productivity, and the main reason was technological regress. Furthermore, labor redundancy is a critical issue for the fashion industry in the post-pandemic era, even if it shows a decrease because of the pandemic.
Originality/value
The existing theory on the fashion industry during the pandemic was improved by expanding the time and geographical dimensions and integrating the advantages of various DEA models. Scientific improvement strategies were presented in the post-pandemic era with application value.