Search results

1 – 10 of 22
To view the access options for this content please click here
Article
Publication date: 18 January 2021

Haiyan Kong, Yue Yuan, Yehuda Baruch, Naipeng Bu, Xinyu Jiang and Kangping Wang

The prevalence of artificial intelligence (AI) has considerably affected management and society. This paper aims to explore its potential impact on hospitality industry…

Downloads
1590

Abstract

Purpose

The prevalence of artificial intelligence (AI) has considerably affected management and society. This paper aims to explore its potential impact on hospitality industry employees, bringing enlightenment to both employees and managers.

Design/methodology/approach

Data were collected from a survey of 432 employees who worked in full-service hotels in China. Structural equation modeling (SEM) was used to analyze the data.

Findings

Results presented a positive relationship between AI awareness and job burnout. No significant direct relationship was found between AI awareness and career competencies. Organizational commitment mediated the relationship between AI awareness and career competencies, as well as the relationship between AI awareness and job burnout.

Research limitations/implications

This study contributes to human resource management in the hospitality industry to theoretical and practical aspects. Theoretically, it enriched both career theory and fit theory. Practically, this study reminds managers to pay attention to the adverse effect of AI on human capital. It also enlightens the manager to think of the positive effects that AI may bring. Managers should provide proper support to overcome AI’s threat to human resources.

Practical implications

Practically, this study reminds managers to pay attention to the adverse effect of AI on human capital. It also enlightens the manager to think of the positive effects that AI may bring. Managers should provide proper support to overcome AI’s threat to human resources.

Originality/value

The study aims to analyze the impact of AI from a career perspective. It provided theoretical support and evidence for hotel managers for the effects of AI awareness on hotel employees. The study conveys a potential topic of concern that the hospitality industry may face in the future.

Details

International Journal of Contemporary Hospitality Management, vol. 33 no. 2
Type: Research Article
ISSN: 0959-6119

Keywords

To view the access options for this content please click here
Article
Publication date: 11 September 2020

Xiaojun Fan, Xinyu Jiang, Nianqi Deng, Xuebing Dong and Yangxi Lin

Using WeChat moments as an example, this article explores the impact of user role conflict on privacy concerns, social media fatigue and the three dimensions of…

Abstract

Purpose

Using WeChat moments as an example, this article explores the impact of user role conflict on privacy concerns, social media fatigue and the three dimensions of discontinuous usage intention: control activities, short breaks and suspend usage intentions. Moreover, the moderating function of self-esteem in this process is examined.

Design/methodology/approach

The conceptual model includes role conflict, privacy concerns, social media fatigue, discontinuous usage intention and self-esteem. Three hundred and thirty-one questionnaires were collected using an online survey, and the data were analyzed with structural equation and hierarchical regression modeling.

Findings

The results show that (1) role conflict positively affects privacy concerns and social media fatigue; (2) privacy concerns also positively affect social media fatigue; (3) privacy concerns positively affect control activities intentions, although their impact on short breaks and suspend usage intentions is not significant, whereas social media fatigue significantly influences control activities, short breaks and suspend usage intentions; and (4) self-esteem negatively moderates the influence of role conflict on privacy concerns.

Research limitations/implications

A key limitation of this research is that it is designed for WeChat. Therefore, the question of whether other social media platforms face role conflict or discontinuous usage problems should be explored in the future.

Originality/value

The article is interesting in that it focuses on the discontinuous usage of social media and identifies factors that contribute to the discontinuous usage of social media. The findings make some theoretical contributions to, and have practical implications for, research into social media usage.

Details

Information Technology & People, vol. 34 no. 3
Type: Research Article
ISSN: 0959-3845

Keywords

To view the access options for this content please click here
Article
Publication date: 14 May 2018

Haiyan Kong, Xinyu Jiang, Wilco Chan and Xiaoge Zhou

This study aims to conduct an overview of previous studies on job satisfaction, particularly its determinants and outcomes, and the research objectives, main themes and…

Downloads
3860

Abstract

Purpose

This study aims to conduct an overview of previous studies on job satisfaction, particularly its determinants and outcomes, and the research objectives, main themes and years of publication of previous studies. This study also seeks to analyze research trends on job satisfaction in the field of hospitality and tourism.

Design/methodology/approach

The top hospitality and tourism journals were reviewed, and relevant papers were searched using the keyword “job satisfaction.” Content analysis was performed to identify the research objectives, main themes, influencing factors, outcomes and journals.

Findings

A total of 143 refereed journal papers were collected, of which 128 papers explored the influencing factors of job satisfaction, and 53 papers aimed to investigate outcomes. The predictors of job satisfaction were further classified into four groups, namely, organizational, individual, social and family and psychological factors.

Research limitations/implications

This study conducted a literature review on job satisfaction by using content analysis. A relatively comprehensive review of job satisfaction is provided. However, this preliminary study still has considerable room for improvement given the extensive studies on job satisfaction. Future studies may perform meta-analysis and attempt to find new values of job satisfaction.

Practical implications

Findings may shed light on practical management. From the individual perspective, education, interest and skills were found to be related to job satisfaction. Thus, managers should provide their employees with opportunities to train and update their skills. From the organizational perspective, organizational support and culture contributed positively to job satisfaction. This perspective highlighted the importance of effective management activities and policies. From the social and family perspective, family–work supportive policies must be implemented to enhance job satisfaction. From the psychological perspective, psychological issues were found to be closely related to job satisfaction. Thus, the employees’ stress should be reduced to ensure that they perform their jobs well.

Social implications

This study analyzed the determinants and outcomes of job satisfaction and highlighted the importance of enhancing job satisfaction from different perspectives. The interest of employees should be enhanced, their family–work conflict should be reduced and their psychological issues should be addressed to stimulate their enthusiasm. As job satisfaction contributes positively to organizational commitment and intention to stay, managers should conduct a series of organizational supportive activities to enhance job satisfaction, which will retain qualified employees.

Originality/value

This study conducted extensive research on job satisfaction and drew a systematic picture of job satisfaction on the basis of its determinants and outcomes, research objectives, main themes and journals. All findings were comprehensive and combined to contribute to the literature and serve as a foundation for further study.

Details

International Journal of Contemporary Hospitality Management, vol. 30 no. 5
Type: Research Article
ISSN: 0959-6119

Keywords

To view the access options for this content please click here
Article
Publication date: 5 November 2019

Zhenbin Jiang, Juan Guo and Xinyu Zhang

A common pipeline of apparel design and simulation is adjusting 2D apparel patterns, putting them onto a virtual human model and performing 3D physically based simulation…

Abstract

Purpose

A common pipeline of apparel design and simulation is adjusting 2D apparel patterns, putting them onto a virtual human model and performing 3D physically based simulation. However, manually adjusting 2D apparel patterns and performing simulations require repetitive adjustments and trials in order to achieve satisfactory results. To support future made-to-fit apparel design and manufacturing, efficient tools for fast custom design purposes are desired. The purpose of this paper is to propose a method to automatically adjust 2D apparel patterns and rapidly generate acustom apparel style for a given human model.

Design/methodology/approach

The authors first pre-define a set of constraints using feature points, feature lines and ease allowance for existing apparels and human models. The authors formulate the apparel fitting to a human model, as a process of optimization using these predefined constraints. Then, the authors iteratively solve the problem by minimizing the total fitting metric.

Findings

The authors observed that through reusing existing apparel styles, the process of designing apparels can be greatly simplified. The authors used a new fitting function to measure the geometric fitting of corresponding feature points/lines between apparels and a human model. Then, the optimized 2D patterns are automatically obtained by minimizing the matching function. The authors’ experiments show that the authors’ approach can increase the reusability of existing apparel styles and improve apparel design efficiency.

Research limitations/implications

There are some limitations. First, in order to achieve interactive performance, the authors’ current 3D simulation does not detect collision within or between adjacent apparel surfaces. Second, the authors’ did not consider multiple layer apparels. It is non-trivial to define ease allowance between multiple layers.

Originality/value

The authors use a set of constraints such as ease allowance, feature points, feature lines, etc. for existing apparels and human models. The authors define a few new fitting functions using these pre-specified constraints. During physics-driven simulation, the authors iteratively minimize these fitting functions.

Details

International Journal of Clothing Science and Technology, vol. 32 no. 2
Type: Research Article
ISSN: 0955-6222

Keywords

To view the access options for this content please click here
Article
Publication date: 18 April 2017

Qi Zhou, Ping Jiang, Xinyu Shao, Hui Zhou and Jiexiang Hu

Uncertainty is inevitable in real-world engineering optimization. With an outer-inner optimization structure, most previous robust optimization (RO) approaches under…

Abstract

Purpose

Uncertainty is inevitable in real-world engineering optimization. With an outer-inner optimization structure, most previous robust optimization (RO) approaches under interval uncertainty can become computationally intractable because the inner level must perform robust evaluation for each design alternative delivered from the outer level. This paper aims to propose an on-line Kriging metamodel-assisted variable adjustment robust optimization (OLK-VARO) to ease the computational burden of previous VARO approach.

Design/methodology/approach

In OLK-VARO, Kriging metamodels are constructed for replacing robust evaluations of the design alternative delivered from the outer level, reducing the nested optimization structure of previous VARO approach into a single loop optimization structure. An on-line updating mechanism is introduced in OLK-VARO to exploit the obtained data from previous iterations.

Findings

One nonlinear numerical example and two engineering cases have been used to demonstrate the applicability and efficiency of the proposed OLK-VARO approach. Results illustrate that OLK-VARO is able to obtain comparable robust optimums as to that obtained by previous VARO, while at the same time significantly reducing computational cost.

Practical implications

The proposed approach exhibits great capability for practical engineering design optimization problems under interval uncertainty.

Originality/value

The main contribution of this paper lies in the following: an OLK-VARO approach under interval uncertainty is proposed, which can significantly ease the computational burden of previous VARO approach.

Details

Engineering Computations, vol. 34 no. 2
Type: Research Article
ISSN: 0264-4401

Keywords

To view the access options for this content please click here
Article
Publication date: 16 April 2018

Qi Zhou, Xinyu Shao, Ping Jiang, Tingli Xie, Jiexiang Hu, Leshi Shu, Longchao Cao and Zhongmei Gao

Engineering system design and optimization problems are usually multi-objective and constrained and have uncertainties in the inputs. These uncertainties might…

Abstract

Purpose

Engineering system design and optimization problems are usually multi-objective and constrained and have uncertainties in the inputs. These uncertainties might significantly degrade the overall performance of engineering systems and change the feasibility of the obtained solutions. This paper aims to propose a multi-objective robust optimization approach based on Kriging metamodel (K-MORO) to obtain the robust Pareto set under the interval uncertainty.

Design/methodology/approach

In K-MORO, the nested optimization structure is reduced into a single loop optimization structure to ease the computational burden. Considering the interpolation uncertainty from the Kriging metamodel may affect the robustness of the Pareto optima, an objective switching and sequential updating strategy is introduced in K-MORO to determine (1) whether the robust analysis or the Kriging metamodel should be used to evaluate the robustness of design alternatives, and (2) which design alternatives are selected to improve the prediction accuracy of the Kriging metamodel during the robust optimization process.

Findings

Five numerical and engineering cases are used to demonstrate the applicability of the proposed approach. The results illustrate that K-MORO is able to obtain robust Pareto frontier, while significantly reducing computational cost.

Practical implications

The proposed approach exhibits great capability for practical engineering design optimization problems that are multi-objective and constrained and have uncertainties.

Originality/value

A K-MORO approach is proposed, which can obtain the robust Pareto set under the interval uncertainty and ease the computational burden of the robust optimization process.

Details

Engineering Computations, vol. 35 no. 2
Type: Research Article
ISSN: 0264-4401

Keywords

To view the access options for this content please click here
Article
Publication date: 6 November 2017

Leshi Shu, Ping Jiang, Li Wan, Qi Zhou, Xinyu Shao and Yahui Zhang

Metamodels are widely used to replace simulation models in engineering design optimization to reduce the computational cost. The purpose of this paper is to develop a…

Abstract

Purpose

Metamodels are widely used to replace simulation models in engineering design optimization to reduce the computational cost. The purpose of this paper is to develop a novel sequential sampling strategy (weighted accumulative error sampling, WAES) to obtain accurate metamodels and apply it to improve the quality of global optimization.

Design/methodology/approach

A sequential single objective formulation is constructed to adaptively select new sample points. In this formulation, the optimization objective is to select a sample point with the maximum weighted accumulative predicted error obtained by analyzing data from previous iterations, and a space-filling criterion is introduced and treated as a constraint to avoid generating clustered sample points. Based on the proposed sequential sampling strategy, a two-step global optimization approach is developed.

Findings

The proposed WAES approach and the global optimization approach are tested in several cases. A comparison has been made between the proposed approach and other existing approaches. Results illustrate that WAES approach performs the best in improving metamodel accuracy and the two-step global optimization approach has a great ability to avoid local optimum.

Originality/value

The proposed WAES approach overcomes the shortcomings of some existing approaches. Besides, the two-step global optimization approach can be used for improving the optimization results.

Details

Engineering Computations, vol. 34 no. 8
Type: Research Article
ISSN: 0264-4401

Keywords

To view the access options for this content please click here
Article
Publication date: 25 March 2019

Ji Cheng, Ping Jiang, Qi Zhou, Jiexiang Hu, Tao Yu, Leshi Shu and Xinyu Shao

Engineering design optimization involving computational simulations is usually a time-consuming, even computationally prohibitive process. To relieve the computational…

Abstract

Purpose

Engineering design optimization involving computational simulations is usually a time-consuming, even computationally prohibitive process. To relieve the computational burden, the adaptive metamodel-based design optimization (AMBDO) approaches have been widely used. This paper aims to develop an AMBDO approach, a lower confidence bounding approach based on the coefficient of variation (CV-LCB) approach, to balance the exploration and exploitation objectively for obtaining a global optimum under limited computational budget.

Design/methodology/approach

In the proposed CV-LCB approach, the coefficient of variation (CV) of predicted values is introduced to indicate the degree of dispersion of objective function values, while the CV of predicting errors is introduced to represent the accuracy of the established metamodel. Then, a weighted formula, which takes the degree of dispersion and the prediction accuracy into consideration, is defined based on the already-acquired CV information to adaptively update the metamodel during the optimization process.

Findings

Ten numerical examples with different degrees of complexity and an AIAA aerodynamic design optimization problem are used to demonstrate the effectiveness of the proposed CV-LCB approach. The comparisons between the proposed approach and four existing approaches regarding the computational efficiency and robustness are made. Results illustrate the merits of the proposed CV-LCB approach in computational efficiency and robustness.

Practical implications

The proposed approach exhibits high efficiency and robustness in engineering design optimization involving computational simulations.

Originality/value

CV-LCB approach can balance the exploration and exploitation objectively.

Details

Engineering Computations, vol. 36 no. 3
Type: Research Article
ISSN: 0264-4401

Keywords

To view the access options for this content please click here
Article
Publication date: 14 July 2020

Xiaojun Wang, Zhenxian Luo and Xinyu Geng

This paper is to present an experiment to verify that the motion errors of robust topology optimization results of compliant mechanisms are insensitive to load dispersion.

Downloads
210

Abstract

Purpose

This paper is to present an experiment to verify that the motion errors of robust topology optimization results of compliant mechanisms are insensitive to load dispersion.

Design/methodology/approach

First, the test pieces of deterministic optimization and robust optimization results are manufactured by the combination of three-dimensional (3D) printing and casting techniques. To measure the displacement of the test piece of compliant mechanism, a displacement measurement method based on the image recognition technique is proposed in this paper.

Findings

According to the experimental data analysis, the robust topology optimization results of compliant mechanisms are less sensitive to uncertainties, comparing with the deterministic optimization results.

Originality/value

An experiment is presented to verify the effectiveness of robust topology optimization for compliant mechanisms. The test pieces of deterministic optimization and robust optimization results are manufactured by the combination of 3D printing and casting techniques. By comparing the experimental data, it is found that the motion errors of robust topology optimization results of compliant mechanisms are insensitive to load dispersion.

Details

Rapid Prototyping Journal, vol. 26 no. 9
Type: Research Article
ISSN: 1355-2546

Keywords

To view the access options for this content please click here
Article
Publication date: 23 November 2018

Qiang Wei, Sheng Li, Xinyu Gou and Baofeng Huo

The rapid development of e-commerce has caused not only explosive growth of the express delivery industry, but also ever-greater operational pressures. Models from the…

Abstract

Purpose

The rapid development of e-commerce has caused not only explosive growth of the express delivery industry, but also ever-greater operational pressures. Models from the sharing economy may provide new ideas for operational improvement. The purpose of this paper is to consider an optimization method that reduces costs and increases efficiency. The proposed method enables a shared distribution system based on revenue-sharing and cooperative investment contracts.

Design/methodology/approach

The authors design a two-echelon supply chain (SC) of the shared distribution system with one shared distribution company and N express companies. In this SC, the express companies provide only inter-city transportation, and they outsource internal-city transportation to a shared distribution company. This distribution system differs from that of the traditional express delivery industry. The traditional system of delivery requires large numbers of empty trips (with no load to deliver), because the operating mode of urban distribution has been the franchise. To offer greater efficiency and performance, the authors introduce the sharing economy mode of express delivery. The authors examine the potential of a joint optimal decision-making strategy that involves revenue-sharing and cooperative investment contracts based on an order flow proportion (OFP) and a revenue-sharing factor (RSF). In this shared distribution system, the most important innovation is that all of the express companies jointly invest in and establish a shared distribution company based on OFP or RSF principles.

Findings

The profitability of an SC with revenue-sharing contracts based on an OFP system is much higher than that of a decentralized SC, and it is very close to the profitability of a centralized SC. In SCs with revenue-sharing contracts that are based on RSFs, there are many possible combinations of RSFs that can increase the overall profitability. The analyses indicate that the OFP system offers the best solution in designing revenue-sharing contracts based on RSFs.

Practical implications

This study indicates that revenue-sharing contracts based on both OFP and RSF principles can increase overall SC returns by 0.21 to 0.44 percent. In sum total, this improvement could mean a 0.84 to 1.76bn Yuan increase in revenues for the 400+ bn-Yuan express delivery industry.

Originality/value

The authors find that a combination of equity investment and SC coordination contracts makes the cooperation between SC members much more stable. Through this kind of shared distribution system, the scale of economy can further reduce the costs and increase the efficiency of the express delivery industry.

Details

Industrial Management & Data Systems, vol. 119 no. 3
Type: Research Article
ISSN: 0263-5577

Keywords

1 – 10 of 22