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Article
Publication date: 14 December 2023

Huijuan Zhou, Rui Wang, Dongyang Weng, Ruoyu Wang and Yaoqin Qiao

The interruption event will seriously affect the normal operation of urban rail transit lines,causing a large number of passengers to be stranded in the station and even making…

416

Abstract

Purpose

The interruption event will seriously affect the normal operation of urban rail transit lines,causing a large number of passengers to be stranded in the station and even making the train stranded in the interval between stations. This study aims to reduce the impact of interrupt events and improve service levels.

Design/methodology/approach

To address this issue, this paper considers the constraints of train operation safety, capacity and dynamic passenger flow demand. It proposes a method for adjusting small loops during interruption events and constructs a train operation adjustment model with the objective of minimizing the total passenger waiting time. This model enables the rapid development of train operation plans in interruption scenarios, coordinating train scheduling and line resources to minimize passenger travel time and mitigate the impact of interruptions. Regarding the proposed train operation adjustment model, an improved genetic algorithm (GA) is designed to solve it.

Findings

The model and algorithm are applied to a case study of interruption events on Beijing Subway Line 5. The results indicate that after solving the constructed model, the train departure intervals can be maintained between 1.5 min and 3 min. This ensures both the safety of train operations on the line and a good match with passengers’ travel demands, effectively reducing the total passenger waiting time and improving the service level of the urban rail transit system during interruptions. Compared to the GA algorithm, the algorithm proposed in this paper demonstrates faster convergence speed and better computational results.

Originality/value

This study explicitly outlines the adjustment method of using short-turn operation during operational interruptions, with train departure times and station stop times as decision variables. It takes into full consideration safety constraints on train operations, train capacity constraints and dynamic passenger demand. It has constructed a train schedule optimization model with the goal of minimizing the total waiting time for all passengers in the system.

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Article
Publication date: 23 August 2019

Honggang Wang, Shanshan Wang, Jia Yao, Ruoyu Pan, Qiongdan Huang, Hanlu Zhang and Jingfeng Yang

The purpose of this paper is to study how to improve the performance of RFID robot system by anti-collision algorithms. For radio frequency identification (RFID) robots operating…

148

Abstract

Purpose

The purpose of this paper is to study how to improve the performance of RFID robot system by anti-collision algorithms. For radio frequency identification (RFID) robots operating in mobile scenes, effective anti-collision algorithm not only reduces missed reading but also enhances the speed of RFID robots movement.

Design/methodology/approach

An effective anti-collision algorithm is proposed to accelerate tag identification in RFID robots systems in this paper. The tag collisions in the current time slot are detected by a new method, and then further resolve each small tag collision to improve system throughput, rather than the total tags number estimation. After the reader detected the collision, three different collision resolution methods were described and studied, and the situation of missing tag caused by reader moving is also discussed.

Findings

The proposed algorithm achieves theoretical system throughput of about 0.48, 0.50 and 0.61 and simulates to show that the proposed algorithm performance is significantly improved compared with the existing ALOHA-based algorithm.

Originality/value

The proposed RFID anti-collision algorithm is beneficial to improve the moving speed and identification reliability of the RFID robots in complex environments.

Details

Assembly Automation, vol. 40 no. 1
Type: Research Article
ISSN: 0144-5154

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Article
Publication date: 19 March 2021

Honggang Wang, Ruixue Yu, Ruoyu Pan, Mengyuan Liu, Qiongdan Huang and Jingfeng Yang

In manufacturing environments, mobile radio frequency identification (RFID) robots need to quickly identify and collect various types of passive tag and active tag sensor data…

220

Abstract

Purpose

In manufacturing environments, mobile radio frequency identification (RFID) robots need to quickly identify and collect various types of passive tag and active tag sensor data. The purpose of this paper is to design a robot system compatible with ultra high frequency (UHF) band passive and active RFID applications and to propose a new anti-collision protocol to improve identification efficiency for active tag data collection.

Design/methodology/approach

A new UHF RFID robot system based on a cloud platform is designed and verified. For the active RFID system, a grouping reservation–based anti-collision algorithm is proposed in which an inventory round is divided into reservation period and polling period. The reservation period is divided into multiple sub-slots. Grouped tags complete sub-slot by randomly transmitting a short reservation frame. Then, in the polling period, the reader accesses each tag by polling. When tags’ reply collision occurs, the reader tries to re-query collided tags once, and the pre-reply tags avoid collisions through random back-off and channel activity detection.

Findings

The proposed algorithm achieves a maximum theoretical system throughput of about 0.94, and very few tag data frame transmissions overhead. The capture effect and channel activity detection in physical layer can effectively improve system throughput and reduce tag data transmission.

Originality/value

In this paper, the authors design and verify the UHF band passive and active hybrid RFID robot architecture based on cloud collaboration. And, the proposed anti-collision algorithm would improve active tag data collection speed and reduce tag transmission overhead in complex manufacturing environments.

Details

Assembly Automation, vol. 41 no. 3
Type: Research Article
ISSN: 0144-5154

Keywords

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Article
Publication date: 29 November 2017

Qing Zheng, Wei Guo, Weijin An, Lei Wang and Ruoyu Liang

Many users build personal projects in co-innovation community to accomplish their innovations. However, very few projects from such communities are successful and understanding of…

428

Abstract

Purpose

Many users build personal projects in co-innovation community to accomplish their innovations. However, very few projects from such communities are successful and understanding of this phenomenon is limited. The purpose of this paper is to identify the factors facilitating user projects success in online co-innovation communities.

Design/methodology/approach

Based on the theories of persuasion and diffusion of innovation (DOI), a conceptual model is proposed to explain how project success likelihood is affected by the creator, project and user participation characteristics. Then, the model and hypotheses are tested through binary logistic regression on a secondary data set of 572 projects collected from a typical user co-innovation community, Local Motors.

Findings

The results show that creator characteristics (prior success rate), project characteristics (project popularity, length and duration) and user participation characteristics (participation users and degree) have significant and positive impacts on project success likelihood. The number of prior projects, which can hardly represent the creator’s credibility in open and unrestricted situations, has no significant influence on the project success likelihood.

Practical implications

This study offers project creators the keys to increase their projects successful possibility. Besides, this study recommends a new way to attract users and helps to identify creative and effective users for community practitioners.

Originality/value

This study expands the research scope in online co-innovation community by focusing on user personal projects. In addition, it combines persuasion theory and DOI theory to add the holistic understanding of user project success likelihood.

Details

Kybernetes, vol. 47 no. 4
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 8 December 2020

Yeunjae Lee, Weiting Tao, Jo-Yun Queenie Li and Ruoyu Sun

This study aims to examine the effects of diversity-oriented leadership and strategic internal communication on employees’ knowledge-sharing behavior during a crisis situation…

6666

Abstract

Purpose

This study aims to examine the effects of diversity-oriented leadership and strategic internal communication on employees’ knowledge-sharing behavior during a crisis situation, coronavirus (COVID-19) outbreak in particular. Integrating knowledge sharing research with internal crisis communication literature as well as self-determination theory, the mediating roles of employees’ intrinsic needs satisfaction are also identified.

Design/methodology/approach

An online survey was conducted with 490 full-time employees in the USA across industry sectors during the COVID-19 outbreak.

Findings

Results suggest that diversity-oriented leadership contributes to transparent internal communication during a crisis and increases employees’ satisfaction of autonomy, competence and relatedness needs. Transparent internal communication also increases employees’ intrinsic needs satisfaction, which in turn fosters their job engagement and knowledge-sharing behavior during the crisis.

Originality/value

This study is one of the earliest studies to demonstrate the effectiveness of diversity-oriented leadership and strategic internal crisis communication in enhancing employees’ knowledge-sharing behavior, especially in the context of COVID-19.

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Article
Publication date: 3 May 2022

Yuming Zhai, Kaibo Yang, Lu Chen, Han Lin, Mingchuan Yu and Ruoyu Jin

Digital technologies, such as big data and artificial intelligence, significantly impact entrepreneurial activities worldwide. However, research on entrepreneurial activities…

1861

Abstract

Purpose

Digital technologies, such as big data and artificial intelligence, significantly impact entrepreneurial activities worldwide. However, research on entrepreneurial activities enabled by digital technologies is fragmented, divergent and delayed. This study aims to provide a structured review of digital entrepreneurship (DE) to identify status, hotspots, knowledge structure, dynamic trends and future developments in this field.

Design/methodology/approach

The bibliometric analysis was applied to offer a technological review on DE. In total 704 publications and their 34,083 references from Web of Science were retrieved as the sample set. Basic characteristics of publications, including the most influential documents, authors, journals and countries, were obtained. Then, co-citation and co-occurrence analyses were conducted to sketch the contours of the structure and evolution of DE.

Findings

DE has attracted increasing attention in the past three decades, especially after 2013. There are dozens of countries, hundreds of journals and more than 1,000 authors that have contributed to this field. Based on keyword co-occurrence clustering and co-citation clustering, the authors proposed a 3E (empower, evolution and ecosystem) framework of DE to facilitate an interdisciplinary dialogue for evidence-based policymaking and practice. In the future, researchers need to pay more attention to theoretical research and study DE from a holistic and dynamic perspective with consideration to the negative impact of digital technology on entrepreneurial activities.

Originality/value

This study draws an outline of the global advance on DE research. It presents an opportunity to comprehensively understand the contemporary achievements, the march of knowledge and the logical venation underlying academic developments as well as foundations for policymaking.

Details

Journal of Business & Industrial Marketing, vol. 38 no. 3
Type: Research Article
ISSN: 0885-8624

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Article
Publication date: 8 December 2020

Yeunjae Lee, Su Yeon Cho, Ruoyu Sun and Cong Li

This study examines the effects of employees' personal social media posts on external publics' online engagement and offline word-of-mouth (WOM) intentions about a company…

1719

Abstract

Purpose

This study examines the effects of employees' personal social media posts on external publics' online engagement and offline word-of-mouth (WOM) intentions about a company. Specifically, it investigates how employee post characteristics including valence and content and employer reputation jointly influence publics' online and offline behaviors.

Design/methodology/approach

A 2 (post valence: positive vs. negative) × 2 (post content: organization-related vs. job-related) × 2 (employer reputation: good vs. bad) between-subjects experiment was conducted. Participants were asked to view a stimulus social media post created by a fictitious company employee, reflecting one of the eight experimental conditions on a random basis. After viewing, they were requested to report their online engagement intentions (i.e., “like,” “share” and “comment”) with the post and offline WOM intentions about the company.

Findings

The experimental results showed that participants expressed more “like” intentions when they viewed a positive post than a negative post. Further, they were more likely to “comment” on a job-related post as opposed to an organization-related post. In addition, a significant interaction effect between post valence and employer reputation on publics' online engagement was found, which in turn influenced their offline WOM intentions about the company.

Originality/value

This study is among the first empirical attempts to examine the effectiveness of employees' personal social media posts on external publics' online and offline behaviors. The experimental findings highlight the importance of managing employee relations from a corporate reputation perspective.

Details

Internet Research, vol. 31 no. 3
Type: Research Article
ISSN: 1066-2243

Keywords

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Article
Publication date: 5 January 2021

Xudong Tang, Yan Gu, Ruoyu Weng and Kungcheng Ho

Confucianism underpins Chinese traditional culture and the values of the Chinese people. The purpose of this study is to examine the relationship between adherence to Confucianism…

1352

Abstract

Purpose

Confucianism underpins Chinese traditional culture and the values of the Chinese people. The purpose of this study is to examine the relationship between adherence to Confucianism and corporate irregularities.

Design/methodology/approach

The authors use the historical numbers of Jinshi (Imperial Scholars) in the Ming and Qing dynasties within 200 km of a company's location to proxy for the influence of Confucianism on the company, presenting strong evidence that Confucianism significantly reduces corporate irregularities.

Findings

The authors' findings are robust even when criticized with alternative definitions of Confucianism, sensitivity analysis and instrumental variable regression. The authors also discover that this effect is weaker in state-owned and foreign enterprises and weakened by the influence of Western culture.

Originality/value

This paper brings a new traditional-cultural perspective to the understanding of corporate irregularities and contributes to the literature on culture and finance. This paper also helps the authors understand the “China Puzzle” that is China's rapid economic development under an imperfect legal system.

Details

International Journal of Emerging Markets, vol. 17 no. 6
Type: Research Article
ISSN: 1746-8809

Keywords

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Article
Publication date: 11 April 2023

Shiyun Tian, Su Yeon Cho, Xiaofeng Jia, Ruoyu Sun and Wanhsiu Sunny Tsai

This study aims to focus on the dynamics in influencer-consumer relationships to understand how Generation Z consumers’ identification and social comparison with influencers shape…

3406

Abstract

Purpose

This study aims to focus on the dynamics in influencer-consumer relationships to understand how Generation Z consumers’ identification and social comparison with influencers shape their response to influencers’ branded posts. Specifically, this study investigates how perceived similarity and wishful identification lead to distinct social comparison mechanisms that affect Generation Z consumers’ self-improvement motives, which, in turn, drive their message engagement, brand attitudes and purchase intentions.

Design/methodology/approach

An online survey was conducted with 295 college students who are digital natives and whose purchase decisions are heavily influenced by social media influencers.

Findings

The study findings confirmed that perceived similarity positively influenced assimilative comparison emotions of optimism, admiration and aspiration while negatively influenced contrastive comparison emotions of envy, depression and resentment. Wishful identification positively affected both assimilative and contrastive comparison emotions. Both types of social comparison emotions further affected consumers’ motivations to follow the influencer for self-improvement, thereby enhancing their brand attitude, purchase intention and engagement behaviors.

Originality/value

This study is one of the earliest attempts to investigate the relationship dynamics between influencers and consumers from the lens of social comparison. The study examines the antecedents of perceived similarity and wishful identification, the mediators of upward comparison emotions and self-improvement motives and the brand evaluation outcomes of message engagement, brand attitude and purchase intention.

Details

Journal of Product & Brand Management, vol. 32 no. 7
Type: Research Article
ISSN: 1061-0421

Keywords

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Article
Publication date: 3 November 2020

Linhua Sang, Mingchuan Yu, Han Lin, Zixin Zhang and Ruoyu Jin

Embracing big data has been at the forefront of research for project management. Although there is a consensus that the adoption of big data has significantly positive impact on…

1370

Abstract

Purpose

Embracing big data has been at the forefront of research for project management. Although there is a consensus that the adoption of big data has significantly positive impact on project performance, far less is known about how this innovative information technology becomes an effective driver of construction project quality improvement. This study aims to better understand the mechanism and conditions under which big data can effectively improve project quality performance.

Design/methodology/approach

Adopting Chinese construction enterprises as samples, the theoretical framework proposed in this paper is verified by the empirical results of the two-level hierarchical linear model. The moderated mediation analysis is also conducted to test the hypotheses. Finally, the empirical findings are validated by a comparative case study.

Findings

The results show that big data facilitates the development of technology capability, which further produces remarkable quality performance. That is, a project team's technology capability acts as a mediator in the relationship between organizational adaptability of big data and predictive analytics and project quality performance. It is also observed that two types of project team interdependence (goal and task interdependence) positively moderate the mediation effect.

Research limitations/implications

The questionnaire study from China only represents the relationship within a short time interval in the current context. Future studies should apply longitudinal designs to properly test the causality and use multiple data sources to ensure the validity and robustness of the conclusions.

Practical implications

The value of big data in terms of quality improvement could not be determined in a vacuum; it also depends on the internal capability development and elaborate design of project governance.

Originality/value

This study provides an extension of the existing big data studies and fuels the ongoing debate on its actual outcomes in project management. It not only clarifies the direct effect of big data on project quality improvement but also identifies the mechanism and conditions under which the adoption of big data can play an effective role.

Details

Engineering, Construction and Architectural Management, vol. 28 no. 3
Type: Research Article
ISSN: 0969-9988

Keywords

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