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Article
Publication date: 10 October 2016

Fanxing Meng, Xiaomei Wang, Huajiao Chen, Jin Zhang, Wei Yang, Jin Wang and Quanquan Zheng

The purpose of this paper is to explore the influence of organizational culture (OC) on talent management (TM) by a case study of a real estate company.

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Abstract

Purpose

The purpose of this paper is to explore the influence of organizational culture (OC) on talent management (TM) by a case study of a real estate company.

Design/methodology/approach

The method of case study is adopted in the present study.

Findings

The authors present four propositions. The first is OC has an effect on TM. The second is a new conceptual model of TM. The third is a 4-P pattern to identify and develop the talent. The fourth is to adopt both the spiritual and material satisfactions that retain the talent.

Research limitations/implications

The primary limitation of this study is embedded in the case study method, which is not sufficient to represent the totality. The other limitation is that the issue of cohesion and team efficacy of talents is not considered. This study argues the relationship between OC and TM and expands the existing TM and OC theory. The effect of professional idealism is emphasized on in the process of TM. Talent can be retained firmly within the organization through the methods of rebuilding and strengthening OC.

Originality/value

A conceptual model of TM, 4-P pattern of evaluation and the operational mean to retain the talent is introduced.

Details

Journal of Chinese Human Resource Management, vol. 7 no. 2
Type: Research Article
ISSN: 2040-8005

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Article
Publication date: 8 April 2016

Guimei Wang and Xiaomei Li

With the widespread use and development of automobile, much attention has been paid to its security issues. So to ensure the driving safety, the automobile must be equipped with…

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Abstract

Purpose

With the widespread use and development of automobile, much attention has been paid to its security issues. So to ensure the driving safety, the automobile must be equipped with good braking performance. In the process of braking, the friction from friction pair causes continuous wear and tear of the surface of brake lining and increases the gap between break pairs, until the lining is not being used (Belhocinea et al., 2014); thus, it is very important to detect the lining wear rate.

Design/methodology/approach

This paper designed the automobile brake friction test wear rate detection system based on Labview.

Findings

Through the detect data, we find that the automobile brake lining wear rate detection system has higher detect accuracy, in the process of detection, the brake lining without the defects such as cracks and bulges, which shall effect the normal use, the lining has no remarkable scratch to disk friction surface, can completed meet the requirements of users.

Originality/value

The automobile brake friction test wear rate detecting system adopts the components of USB-9211 DAQ, optoNCDT1700 non-contract high accuracy displacement sensor, in addition the Labview software to complete the functions such as lining wear rate real time detection, data multichannel real time acquisition, display, and storage record, etc., and uses LabSQL to import the detecting data to Microsoft Access database, which can satisfy the demands of various customers. Moreover, the wear rate real time detection can reflect the lining’s wear regulation of different manufacturers and different material and provide a reliable basis for selecting the appropriate lining material and predicting the lining’s lifetime.

Details

World Journal of Engineering, vol. 13 no. 2
Type: Research Article
ISSN: 1708-5284

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Article
Publication date: 1 November 2007

Larry D. Makus, H. Holly Wang and Xiaomei Chen

A utility maximization model is used to assess alternative risk management portfolios of Pacific Northwest non‐irrigated grain producers using three rotational practices. Risk…

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Abstract

A utility maximization model is used to assess alternative risk management portfolios of Pacific Northwest non‐irrigated grain producers using three rotational practices. Risk management tools include hedging with wheat futures, yield insurance, two revenue insurance products (with and without price replacement), and government programs under the 2002 Food Security and Rural Investment (FSRI) Act. Government programs account for the primary risk management value of all the analyzed portfolios. The revenue insurance product with price replacement is preferred when available, and yield insurance is preferred over revenue insurance without price replacement. Hedging is not extensively utilized unless government programs are eliminated.

Details

Agricultural Finance Review, vol. 67 no. 2
Type: Research Article
ISSN: 0002-1466

Keywords

Available. Open Access. Open Access
Article
Publication date: 6 October 2023

Xiaomei Jiang, Shuo Wang, Wenjian Liu and Yun Yang

Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these…

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Abstract

Purpose

Traditional Chinese medicine (TCM) prescriptions have always relied on the experience of TCM doctors, and machine learning(ML) provides a technical means for learning these experiences and intelligently assists in prescribing. However, in TCM prescription, there are the main (Jun) herb and the auxiliary (Chen, Zuo and Shi) herb collocations. In a prescription, the types of auxiliary herbs are often more than the main herb and the auxiliary herbs often appear in other prescriptions. This leads to different frequencies of different herbs in prescriptions, namely, imbalanced labels (herbs). As a result, the existing ML algorithms are biased, and it is difficult to predict the main herb with less frequency in the actual prediction and poor performance. In order to solve the impact of this problem, this paper proposes a framework for multi-label traditional Chinese medicine (ML-TCM) based on multi-label resampling.

Design/methodology/approach

In this work, a multi-label learning framework is proposed that adopts and compares the multi-label random resampling (MLROS), multi-label synthesized resampling (MLSMOTE) and multi-label synthesized resampling based on local label imbalance (MLSOL), three multi-label oversampling techniques to rebalance the TCM data.

Findings

The experimental results show that after resampling, the less frequent but important herbs can be predicted more accurately. The MLSOL method is shown to be the best with over 10% improvements on average because it balances the data by considering both features and labels when resampling.

Originality/value

The authors first systematically analyzed the label imbalance problem of different sampling methods in the field of TCM and provide a solution. And through the experimental results analysis, the authors proved the feasibility of this method, which can improve the performance by 10%−30% compared with the state-of-the-art methods.

Details

Journal of Electronic Business & Digital Economics, vol. 2 no. 2
Type: Research Article
ISSN: 2754-4214

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Article
Publication date: 6 May 2021

Chengbo Wang, Xiaomei Li, Hong Su and Ying Tian

This paper aims to report findings of up-to-date insights to fill the knowledge gap of lack of theoretical and practical understandings of how knowledge is used in medium-sized…

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Abstract

Purpose

This paper aims to report findings of up-to-date insights to fill the knowledge gap of lack of theoretical and practical understandings of how knowledge is used in medium-sized enterprises (MEs) for ensuring their performance excellence, healthy survival and growth, particularly using the contextual background of quality improvement as the standing point to concretise the research content and research participants’ mind-set for data collection.

Design/methodology/approach

The empirical data were attained by conducting first a multiple-case study and thereafter a structured interview. Insights were obtained through analysing the collected data and triangulating the findings with the contention from the extant literature where available.

Findings

A set of approaches for effective quality improvement knowledge (QIK) utilisation in MEs have been identified and attested, as well as prioritised for a clear guidance on their application by practical businesses.

Originality/value

As a pioneering study on the particularly focussed issue, namely, a current knowledge gap – QIK utilisation in MEs, theoretically the research contributes to the enrichment of the current KM and QI literature with a primary focus on knowledge utilisation in MEs. Practically its findings provide insightful guidance to practice on the approaches of QIK utilisation.

Details

Journal of Knowledge Management, vol. 25 no. 10
Type: Research Article
ISSN: 1367-3270

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Article
Publication date: 20 April 2020

Changchang Che, Huawei Wang, Xiaomei Ni and Qiang Fu

The purpose of this study is to analyze the intelligent fault diagnosis method of rolling bearing.

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Abstract

Purpose

The purpose of this study is to analyze the intelligent fault diagnosis method of rolling bearing.

Design/methodology/approach

The vibration signal data of rolling bearing has long time series and strong noise interference, which brings great difficulties for the accurate diagnosis of bearing faults. To solve those problems, an intelligent fault diagnosis model based on stacked denoising autoencoder (SDAE) and convolutional neural network (CNN) is proposed in this paper. The SDAE is used to process the time series data with multiple dimensions and noise interference. Then the dimension-reduced samples can be put into CNN model, and the fault classification results can be obtained by convolution and pooling operations of hidden layers in CNN.

Findings

The effectiveness of the proposed method is validated through experimental verification and comparative experimental analysis. The results demonstrate that the proposed model can achieve an average classification accuracy of 96.5% under three noise levels, which is 3-13% higher than the traditional models and single deep-learning models.

Originality/value

The combined SDAE–CNN model proposed in this paper can denoise and reduce dimensions of raw vibration signal data, and extract the in-depth features in image samples of rolling bearing. Consequently, the proposed model has more accurate fault diagnosis results for the rolling bearing vibration signal data with long time series and noise interference.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-11-2019-0496/

Details

Industrial Lubrication and Tribology, vol. 72 no. 7
Type: Research Article
ISSN: 0036-8792

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Article
Publication date: 22 June 2021

Yonggui Wang, Xiaomei Cai, Changliang Xu and Jun (Justin) Li

This study aims to explore the antecedents of perceived value and the moderating effect of trust and the relationship between these antecedents and perceived value in the context…

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Abstract

Purpose

This study aims to explore the antecedents of perceived value and the moderating effect of trust and the relationship between these antecedents and perceived value in the context of the service sector.

Design/methodology/approach

The multivariate statistical analysis technique of structural equation modeling was used to test the proposed theoretical model.

Findings

The results indicate that self-efficacy, motivation, social influence, facilitating conditions and emotions have a significant and direct relationship with customers’ perceived value and that trust can enhance the effect of these antecedents on perceived value. These findings have several significant implications for service robot implementation within the service sector.

Originality/value

With the advancement in artificial intelligence and sensor technology, various industries have launched the practice of deploying intelligent robots to build competitive advantages. The use of intelligent robots to assist with the customer service process and improve consumers’ experience within the service sector is becoming more commonplace.

摘要

研究目的

本论文旨在研究服务业中决定感知价值以及哪些中介变量调节感知价值决定因子和感知价值之间的关系。

研究设计/方法/途径

本论文采用多变量SEM法分析提出的理论模型。

研究结果

研究结果表明, 自我效能、动机、社会影响、辅助条件、以及情感对消费者感知价值有直接且显著的影响, 此外, 信任对于其影响因子对感知价值的关系有增强作用。本论文研究结果对服务型机器人在服务业中的应用有着很大的启示。

研究原创性/价值

随着人工智能和感应科技的发展, 很多产业都开始应用智能机器人来增强竞争力。使用智能机器人来辅助消费者服务过程以及提高服务体验感受越来越成为普遍。

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Article
Publication date: 21 July 2022

Wei Xiong, Meijiao Huang, Xi Yu Leung, Yuanhui Zhang and Xiaomei Cai

The aim of this study was to investigate the themes related to the achievement of Sustainable Development Goal (SDG) 12 in relation to tourism, and specifically to explore how the…

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Abstract

Purpose

The aim of this study was to investigate the themes related to the achievement of Sustainable Development Goal (SDG) 12 in relation to tourism, and specifically to explore how the emotional psyche affects tourists’ environmentally responsible behaviors.

Design/methodology/approach

Based on the value-belief-norm theory, a research framework was developed to examine the serial mediation effects of environmental emotions in predicting tourists’ environmentally responsible behaviors. A total of 741 responses was collected from an online survey. Data were analyzed by the partial least squares structural equation modeling.

Findings

Environmental concern does not directly predict tourists’ environmentally responsible behaviors. Instead, environmental awe and environmental worry serially mediate the relationship between environmental concern and tourists’ environmentally responsible behaviors.

Originality/value

This study extends the value-belief-norm theory by integrating environmental emotions and empirically tests the effect of multiple psyches on responsible consumption, contributing to the achievement of SDG 12 in UN Agenda 2030.

研究目的

本研究的目的是探究与旅游相关的可持续发展目标12的实现, 特别是探讨环境情感如何影响旅游者的环境责任行为。

研究方法

基于价值信念-规范理论, 构建了环境情感预测旅游者环境责任行为的链式中介模型。研究共收集741份有效样本, 并采用偏最小二乘结构方程模型进行分析。

研究发现

环境关心并不能直接预测旅游者的环境责任行为。但是, 环境敬畏和环境忧虑在环境关心与环境责任行为之间起链式中介作用。

原创性

本研究将环境情感扩展到价值信念规范理论中, 并实证检验了环境敬畏和环境忧虑两种环境情感对旅游者的负责任消费行为的影响, 呼应了联合国2030年议程中的可持续发展目标12。

Propósito

el objetivo de este estudio fue investigar los temas relacionados con el logro del Objetivo de Desarrollo Sostenible 12 en relación con el turismo, y específicamente explorar cómo la psique emocional afecta los comportamientos ambientalmente responsables de los turistas.

Diseño/metodología/enfoque

Basado en la teoría del valor-creencia-norma, se desarrolló un marco de investigación para examinar los efectos de mediación en serie de las emociones ambientales en la predicción de los comportamientos ambientalmente responsables de los turistas. Se recopiló un total de 741 respuestas de una encuesta en línea. Los datos se analizaron mediante el modelo de ecuaciones estructurales de mínimos cuadrados parciales.

Hallazgos

la preocupación ambiental no predice directamente los comportamientos ambientalmente responsables de los turistas. En cambio, el temor ambiental y la preocupación ambiental median en serie la relación entre la preocupación ambiental y los comportamientos ambientalmente responsables de los turistas.

Originalidad

este estudio amplía la teoría del valor-creencia-norma al integrar las emociones ambientales y prueba empíricamente el efecto de múltiples psiques en el consumo responsable, contribuyendo al logro del ODS 12 en la Agenda 2030 de la ONU.

Available. Open Access. Open Access
Article
Publication date: 3 December 2021

Li Xuemei, Benshuo Yang, Yun Cao, Liyan Zhang, Han Liu, Pengcheng Wang and Xiaomei Qu

China's marine economy occupies an important position within the national economy, and its contribution thereto is constantly improving. The overall operation of the marine…

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Abstract

Purpose

China's marine economy occupies an important position within the national economy, and its contribution thereto is constantly improving. The overall operation of the marine economy shows positive developmental trends with potential for further growth. The purpose of this research is to analyse the prosperity of China's marine economy, reveal trends therein and forecast the likely turning point in its operation.

Design/methodology/approach

Based on the periodicity and fluctuation of China's marine economy development, China's marine economic prosperity indicator system is established from five perspectives. On this basis, China's marine economic operation prosperity index can be synthesised and calculated, then a dynamic factor model is constructed. Using the filtering method to calculate China's marine economic operational Stock–Watson index, Markov switching has been used to determine the trend to transition. Furthermore, China's current marine economic prosperity is evaluated through analysis of influencing factors and correlation analysis.

Findings

The analysis shows that, from 2017 to 2019, the operation of the marine economy is relatively stable, and the prosperity index supports this finding; meanwhile it also exposes problems in China's marine economy, such as an unbalanced industrial structure, low marine economic benefits and insufficient capacity for sustainable development.

Originality/value

Through the analysis of the prosperity of China's marine economy, the authors reveal the trends in China's marine economy and forecast its likely future turning point.

Details

Marine Economics and Management, vol. 4 no. 2
Type: Research Article
ISSN: 2516-158X

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Article
Publication date: 27 March 2024

Xiaomei Liu, Bin Ma, Meina Gao and Lin Chen

A time-varying grey Fourier model (TVGFM(1,1,N)) is proposed for the simulation of variable amplitude seasonal fluctuation time series, as the performance of traditional grey…

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Abstract

Purpose

A time-varying grey Fourier model (TVGFM(1,1,N)) is proposed for the simulation of variable amplitude seasonal fluctuation time series, as the performance of traditional grey models can't catch the time-varying trend well.

Design/methodology/approach

The proposed model couples Fourier series and linear time-varying terms as the grey action, to describe the characteristics of variable amplitude and seasonality. The truncated Fourier order N is preselected from the alternative order set by Nyquist-Shannon sampling theorem and the principle of simplicity, then the optimal Fourier order is determined by hold-out method to improve the robustness of the proposed model. Initial value correction and the multiple transformation are also studied to improve the precision.

Findings

The new model has a broader applicability range as a result of the new grey action, attaining higher fitting and forecasting accuracy. The numerical experiment of a generated monthly time series indicates the proposed model can accurately fit the variable amplitude seasonal sequence, in which the mean absolute percentage error (MAPE) is only 0.01%, and the complex simulations based on Monte-Carlo method testify the validity of the proposed model. The results of monthly electricity consumption in China's primary industry, demonstrate the proposed model catches the time-varying trend and has good performances, where MAPEF and MAPET are below 5%. Moreover, the proposed TVGFM(1,1,N) model is superior to the benchmark models, grey polynomial model (GMP(1,1,N)), grey Fourier model (GFM(1,1,N)), seasonal grey model (SGM(1,1)), seasonal ARIMA model seasonal autoregressive integrated moving average model (SARIMA) and support vector regression (SVR).

Originality/value

The parameter estimates and forecasting of the new proposed TVGFM are studied, and the good fitting and forecasting accuracy of time-varying amplitude seasonal fluctuation series are testified by numerical simulations and a case study.

Details

Grey Systems: Theory and Application, vol. 14 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

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