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Article
Publication date: 27 July 2023

Binchao Deng, Xindong Lv, Yaling Du, Xiaoyu Li and Yilin Yin

Inefficiency dilemmas in project governance are caused by various risks arising from the characteristic of construction supply chain projects, such as poor project performance…

Abstract

Purpose

Inefficiency dilemmas in project governance are caused by various risks arising from the characteristic of construction supply chain projects, such as poor project performance, conflicts between stakeholders and cost overrun. This research aims to establish a fuzzy synthetic evaluation (FSE) model to analyze construction supply chain risk factors. Corresponding risk mitigation strategies are provided to facilitate the improvement performance of ongoing construction supply chain projects.

Design/methodology/approach

A literature review is utilized to reveal the deficiencies of construction supply chain risk management. Thus, a total of five hundred (500) questionnaires are distributed to construction professionals, and four hundred and thirty-five (435) questionnaires are recovered to obtain the evaluation data of construction professionals on critical risk factors. Additionally, the FSE is used to analyze and rank the significance of critical risk factors. Finally, this research discusses nine critical risk factors with high weight in the model, and explains the reason for the significance of critical risk factors in the construction supply chain.

Findings

The questionnaire results show that the thirty-one (31) identified critical risk factors are verified by related practitioners (government departments, universities and research institutions, owners, construction units, financial institutions, design units, consulting firms). Thirty-one (31) identified critical risk factors are divided into common risks, risks from contractors and risks from owners. The most significant factors in the three categories, respectively, are “political risks,” “owner's unprofessional” approach and “cash flow.” Managing these risks can facilitate the development of the construction supply chain.

Originality/value

This paper expands the research perspective of construction supply chain risk management and complements the risks in the construction supply chain. For practitioners, the research result provides some corresponding measures to deal with these risks. For researchers, the research result provides the direction of construction supply chain risk treatment.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 5 June 2017

Xiaoyu Li, Osamu Yoshie and Daoping Huang

The purpose of this paper is to detect the existence of unknown wireless devices which could result negative means to the privacy. The perceptual layer of internet of things…

Abstract

Purpose

The purpose of this paper is to detect the existence of unknown wireless devices which could result negative means to the privacy. The perceptual layer of internet of things (IoTs) suffers the most significant privacy disclosing because of limited hardware resources, huge quantity and wide varieties of sensing equipment. Determining whether there are unknown wireless devices in the communicating environment is an effective method to implement the privacy protection for the perceptual layer of IoTs.

Design/methodology/approach

The authors use horizontal hierarchy slicing (HHS) algorithm to extract the morphology feature of signals. Meanwhile, partitioning around medoids algorithm is used to cluster the HHS curves and agglomerative hierarchical clustering algorithm is utilized to distinguish final results. Link quality indicator (LQI) data are chosen as the network parameters in this research.

Findings

Nowadays data encryption and anonymization are the most common methods to protect private information for the perceptual layer of IoTs. However, these efforts are ineffective to avoid privacy disclosure if the communication environment exists unknown wireless nodes which could be malicious devices. How to detect these unknown wireless devices in the communication environment is a valuable topic in the further research.

Originality/value

The authors derive an innovative and passive unknown wireless devices detection method based on the mathematical morphology and machine learning algorithms to detect the existence of unknown wireless devices which could result negative means to the privacy. The simulation results show their effectiveness in privacy protection.

Details

International Journal of Pervasive Computing and Communications, vol. 13 no. 2
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 4 April 2016

Xiaoyu Yu, Bang Nguyen and Yi Chen

The purpose of this paper is to examine the role of capability and alliance arising from the internet of things (IoT), specifically in the relationships between strategic…

4330

Abstract

Purpose

The purpose of this paper is to examine the role of capability and alliance arising from the internet of things (IoT), specifically in the relationships between strategic orientations (entrepreneurial and market foci) with product and process innovations. In addition, it investigates the direct relationship between IoT capability and alliance. Improving these relationships assist in ensuring that new knowledge from the IoT can be translated into tangible business innovations that contribute to economic development.

Design/methodology/approach

Data from 207 new high-technology IoT ventures in China were obtained after three-wave mailing (i.e. two reminders). Following a rigorous process to purify and validate the measurement scale items, the study used structural equation modeling to test the conceptual model.

Findings

Findings demonstrate that an IoT capability only enhances product innovation, however, with the addition and support from IoT alliance, both product and process innovation can be achieved in new high-tech IoT ventures. This nuanced insight suggests that new high-tech IoT ventures should focus on building their IoT capability, and at the same time, develop IoT alliances with value chain partners in order to fully take advantage of IoT and gain a better position to formulate more novel offerings.

Originality/value

The study is first to contribute with a much needed framework of IoT and entrepreneurship by examining the role of IoT capability further in the relationships between: entrepreneurial orientation and market orientation with product and process innovations arising from IoT; and the role of IoT alliance (interfirm relations, partnerships, etc.) on the relationship above.

Details

Internet Research, vol. 26 no. 2
Type: Research Article
ISSN: 1066-2243

Keywords

Article
Publication date: 1 October 2005

Jingjun Liu, Yuzhen Lin and Xiaoyu Li

To study flow‐induced corrosion mechanisms for carbon steel in high velocity flowing seawater and explain corrosive phenomena.

Abstract

Purpose

To study flow‐induced corrosion mechanisms for carbon steel in high velocity flowing seawater and explain corrosive phenomena.

Design/methodology/approach

An overall mathematical model for flow‐induced corrosion of carbon steel in high velocity flow seawater was established in rotating disk apparatus using both numerical simulation and test methods. By studying the impact of turbulent flow using the kinetic energy of turbulent approach and the effects of the computational near‐wall hydrodynamic parameters on corrosion rates, corrosion behaviour and mechanism are discussed here. It is applicable to deeply understand the synergistic effect mechanism of flow‐induced corrosion.

Findings

It is scientific and reasonable to investigate carbon steel corrosion through correlation of the near‐wall hydrodynamic parameters, which can accurately describe the influence of fluid flow on corrosion. The computational corrosion rates obtained by this model are in agreement with measured corrosion data. It is shown that serious flow‐induced corrosion is caused by the synergistic effect between corrosion electrochemical factor and hydrodynamic factor. While corrosion electrochemical factor plays a dominant role in flow‐induced corrosion.

Originality/value

The corrosion kinetics and mechanism of metals in high velocity flowing medium is discussed in this paper. These results will help someone who is interested in flow‐induced corrosion to understand in depth the type of issue.

Details

Anti-Corrosion Methods and Materials, vol. 52 no. 5
Type: Research Article
ISSN: 0003-5599

Keywords

Article
Publication date: 21 March 2008

Liu Jingjun, Lin Yuzhen and Li Xiaoyu

This paper aims to study flow‐induced corrosion mechanisms for carbon steel in high‐velocity flowing seawater and to explain corrosive phenomena.

Abstract

Purpose

This paper aims to study flow‐induced corrosion mechanisms for carbon steel in high‐velocity flowing seawater and to explain corrosive phenomena.

Design/methodology/approach

An overall mathematical model for flow‐induced corrosion of carbon steel in high‐velocity flow seawater was established in a rotating disk apparatus using both numerical simulation and test methods. By studying the impact of turbulent flow using the kinetic energy of a turbulent approach and the effects of the computational near‐wall hydrodynamic parameters on corrosion rates, corrosion behavior and mechanism are discussed here. It is applicable in order to understand in depth the synergistic effect mechanism of flow‐induced corrosion.

Findings

It was found that it is scientific and reasonable to investigate carbon steel corrosion through correlation of the near‐wall hydrodynamic parameters, which can accurately describe the influence of fluid flow on corrosion. The computational corrosion rates obtained by this model are in good agreement with measured corrosion data. It is shown that serious flow‐induced corrosion is caused by the synergistic effect between the corrosion electrochemical factor and the hydrodynamic factor, while the corrosion electrochemical factor plays a dominant role in flow‐induced corrosion.

Originality/value

The corrosion kinetics and mechanism of metals in a high‐velocity flowing medium is discussed here. These results will help those interested in flow‐induced corrosion to understand in depth the type of issue.

Details

Anti-Corrosion Methods and Materials, vol. 55 no. 2
Type: Research Article
ISSN: 0003-5599

Keywords

Article
Publication date: 3 March 2021

Wilson Kia Onn Wong

This paper analyses the escalating Sino-Western race to develop a safe, efficacious and durable vaccine (i.e. “Goldilocks COVID-19 vaccine”). It argues that such efforts would be…

Abstract

Purpose

This paper analyses the escalating Sino-Western race to develop a safe, efficacious and durable vaccine (i.e. “Goldilocks COVID-19 vaccine”). It argues that such efforts would be considerably more effective if there is greater international cooperation instead of the corrosive rivalry driven by misplaced nationalism.

Design/methodology/approach

This study deploys a case-study approach, supported by literature on existing coronavirus disease 2019 (COVID-19) vaccine development efforts.

Findings

Despite the seeming success of recent COVID-19 vaccines, their actual efficacy is far from certain. Moreover, access to these vaccines would not be equitable internationally. This problem is exacerbated by the fact that their unique properties make storage and distribution prohibitively expensive, and international mechanisms to provide distribution to economically depressed regions are non-existent. Given the significant difficulties, it would be incumbent upon the great powers (i.e. China and America) to work together not only in vaccine development but also in the establishment of a distribution platform to ensure equitable access worldwide.

Originality/value

This study is one of the few social science research papers on COVID-19 vaccine development and its implications for society at large.

Details

Asian Education and Development Studies, vol. 10 no. 4
Type: Research Article
ISSN: 2046-3162

Keywords

Article
Publication date: 10 November 2023

Yonghong Zhang, Shouwei Li, Jingwei Li and Xiaoyu Tang

This paper aims to develop a novel grey Bernoulli model with memory characteristics, which is designed to dynamically choose the optimal memory kernel function and the length of…

Abstract

Purpose

This paper aims to develop a novel grey Bernoulli model with memory characteristics, which is designed to dynamically choose the optimal memory kernel function and the length of memory dependence period, ultimately enhancing the model's predictive accuracy.

Design/methodology/approach

This paper enhances the traditional grey Bernoulli model by introducing memory-dependent derivatives, resulting in a novel memory-dependent derivative grey model. Additionally, fractional-order accumulation is employed for preprocessing the original data. The length of the memory dependence period for memory-dependent derivatives is determined through grey correlation analysis. Furthermore, the whale optimization algorithm is utilized to optimize the cumulative order, power index and memory kernel function index of the model, enabling adaptability to diverse scenarios.

Findings

The selection of appropriate memory kernel functions and memory dependency lengths will improve model prediction performance. The model can adaptively select the memory kernel function and memory dependence length, and the performance of the model is better than other comparison models.

Research limitations/implications

The model presented in this article has some limitations. The grey model is itself suitable for small sample data, and memory-dependent derivatives mainly consider the memory effect on a fixed length. Therefore, this model is mainly applicable to data prediction with short-term memory effect and has certain limitations on time series of long-term memory.

Practical implications

In practical systems, memory effects typically exhibit a decaying pattern, which is effectively characterized by the memory kernel function. The model in this study skillfully determines the appropriate kernel functions and memory dependency lengths to capture these memory effects, enhancing its alignment with real-world scenarios.

Originality/value

Based on the memory-dependent derivative method, a memory-dependent derivative grey Bernoulli model that more accurately reflects the actual memory effect is constructed and applied to power generation forecasting in China, South Korea and India.

Details

Grey Systems: Theory and Application, vol. 14 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 11 February 2021

Sai Liang, Xiaoxia Zhang, Chunxiao Li, Hui Li and Xiaoyu Yu

Due to their very different contexts, the responses made by property hosts to online reviews can differ from those posted by hotel managers. Thus, the purpose of this study is to…

Abstract

Purpose

Due to their very different contexts, the responses made by property hosts to online reviews can differ from those posted by hotel managers. Thus, the purpose of this study is to investigate the determinants of the responding behavior of hosts on peer-to-peer property rental platforms.

Design/methodology/approach

This study applied a comprehensive framework based on the theory of planned behavior. Empirical models are constructed based on 89,967 guest reviews with their associated responses to reveal the responding pattern of property hosts.

Findings

Unlike hotel managers, property hosts are more likely to reply to positive than to negative reviews; moreover, when they do choose to respond to negative reviews, they are likely to do so negatively, in a “tit-for-tat” way. This study also finds that one reason for the difference of responding patterns between property hosts and hotel managers is the hosts’ lack of experience of consumer relationship management and service recovery.

Research limitations/implications

This study provides a good start point for future theoretical development regarding effective responding strategy on peer-to-peer property rental platforms, as well as some useful implications for practitioners.

Originality/value

This study is an early attempt to analyze the impact of the particularity of emerging platforms on the responding behavior of service providers based on a comprehensive conceptual framework and empirical model thus provides a good starting point for the further investigation of effective response strategies on these emerging platforms.

Details

International Journal of Contemporary Hospitality Management, vol. 33 no. 3
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 24 November 2022

Nao Li, Xiaoyu Yang, IpKin Anthony Wong, Rob Law, Jing Yang Xu and Binru Zhang

This paper aims to classify the sentiment of online tourism-hospitality reviews at an aspect level. A new aspect-oriented sentiment classification method is proposed based on a…

358

Abstract

Purpose

This paper aims to classify the sentiment of online tourism-hospitality reviews at an aspect level. A new aspect-oriented sentiment classification method is proposed based on a neural network model.

Design/methodology/approach

This study constructs an aspect-oriented sentiment classification model using an integrated four-layer neural network: the bidirectional encoder representation from transformers (BERT) word vector model, long short-term memory, interactive attention-over-attention (IAOA) mechanism and a linear output layer. The model was trained, tested and validated on an open training data set and 92,905 reviews extrapolated from restaurants in Tokyo.

Findings

The model achieves significantly better performance compared with other neural networks. The findings provide empirical evidence to validate the suitability of this new approach in the tourism-hospitality domain.

Research limitations/implications

More sentiments should be identified to measure more fine-grained tourism-hospitality experience, and new aspects are recommended that can be automatically added into the aspect set to provide dynamic support for new dining experiences.

Originality/value

This study provides an update to the literature with respect to how a neural network could improve the performance of aspect-oriented sentiment classification for tourism-hospitality online reviews.

研究目的

本文旨在从方面级对在线旅游-酒店评论的情感进行分类。提出了一种基于神经网络模型的面向方面的情感分类新方法。

研究设计/方法/途径

本研究使用集成的四层神经网络构建面向方面的情感分类模型:BERT 词向量模型、LSTM、IAOA 机制和线性输出层。该模型在一个开放的训练数据集和从东京餐厅推断的 92,905 条评论上进行了训练、测试和验证。

研究发现

与其他神经网络相比, 该模型实现了显着更好的性能。研究结果提供了经验证据, 以验证这种新方法在旅游酒店领域的适用性。

研究原创性

该研究提供了有关神经网络如何提高旅游酒店在线评论的面向方面的情感分类性能的新文献。

研究研究局限

应该识别更多的情感从而来更加细化衡量旅游酒店体验, 并推荐新的方面/维度可以被自动添加到方面集中, 为新的用餐体验提供动态支持。

Details

Journal of Hospitality and Tourism Technology, vol. 14 no. 1
Type: Research Article
ISSN: 1757-9880

Keywords

Article
Publication date: 16 October 2020

Xiaoyu Yang, Zhigeng Fang, Xiaochuan Li, Yingjie Yang and David Mba

Online health monitoring of large complex equipment has become a trend in the field of equipment diagnostics and prognostics due to the rapid development of sensing and computing…

Abstract

Purpose

Online health monitoring of large complex equipment has become a trend in the field of equipment diagnostics and prognostics due to the rapid development of sensing and computing technologies. The purpose of this paper is to construct a more accurate and stable grey model based on similar information fusion to predict the real-time remaining useful life (RUL) of aircraft engines.

Design/methodology/approach

First, a referential database is created by applying multiple linear regressions on historical samples. Then similarity matching is conducted between the monitored engine and historical samples. After that, an information fusion grey model is applied to predict the future degradation trajectory of the monitored engine considering the latest trend of monitored sensory data and long-term trends of several similar referential samples, and the real-time RUL is obtained correspondingly.

Findings

The results of comparative analysis reveal that the proposed model, which is called similarity-based information fusion grey model (SIFGM), could provide better RUL prediction from the early degradation stage. Furthermore, SIFGM is still able to predict system failures relatively accurately when only partial information of the referential samples is available, making the method a viable choice when the historical whole life cycle data are scarce.

Research limitations/implications

The prediction of SIFGM method is based on a single monotonically changing health indicator (HI) synthesized from monitoring sensory signals, which is assumed to be highly relevant to the degradation processes of the engine.

Practical implications

The SIFGM can be used to predict the degradation trajectories and RULs of those online condition monitoring systems with similar irreversible degradation behaviors before failure occurs, such as aircraft engines and centrifugal pumps.

Originality/value

This paper introduces the similarity information into traditional GM(1,1) model to make it more suitable for long-term RUL prediction and also provide a solution of similarity-based RUL prediction with limited historical whole life cycle data.

Details

Grey Systems: Theory and Application, vol. 11 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

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