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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.

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.

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.

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.

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.

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

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.

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.

We challenge the discontinuity (also called incompatibility) hypothesis of generalized and particularistic trust, suggesting that the two types of trust are incompatible. This view is problematic because if so, it remains unclear, for instance, how communities scoring high in particularistic trust can ever develop further when transferring trust to spheres outside the community is not an option. In this research, we explore the potential permeability of different types of trust in an emerging market context using the case of China.

Using a purposeful sampling technique, we gathered data among Chinese professionals (n = 290) in the Jingjinji Metropolitan Region in Tianjin. We analyzed the data by performing structural equation modeling.

As we identify interdependencies between generalized and particularistic types of trust, our results speak in favor of the continuity hypothesis. We find that the more people trust other people from an outside group (out-group trust), the less they trust quasi-familiar others (in-group trust). Further, in-group trust increases once the environment urges people to engage in informal network (guanxi)-based transactions.

Advancing the common view of China being a typical low-trust society, in which distrust in strangers (outsiders) prevails, we find a recent trend of an increase in general trust, which might lead to increases of out-group and in-group trust alike. Contrary to the wide spread idea that guanxi is declining in the present day, we find guanxi to be persistent.

We consider a joint optimization problem of product platform design and scheduling on unrelated additive/subtractive hybrid machines, and seek to find efficient solution approaches to solve such problem.

We propose a mathematical formulation for the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines, and develop a simulated annealing-based hyper-heuristic algorithm with adjustable operator sequence length to solve the problem.

The simulated annealing-based hyper-heuristic algorithm with adjustable operator sequence length (SAHH-osla) that we proposed can be quite efficient in solving the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines.

To the best of our knowledge, we are one of the first to consider both cost-related and time-related criteria for the problem of simultaneous product platform design and scheduling on unrelated additive/subtractive hybrid machines.

This paper aims to effectively achieve endmembers and relative abundances simultaneously in hyperspectral image unmixing yield. Hyperspectral unmixing, which is an important step before image classification and recognition, is a challenging issue because of the limited resolution of image sensors and the complex diversity of nature. Unmixing can be performed using different methods, such as blind source separation and semi-supervised spectral unmixing. However, these methods have disadvantages such as inaccurate results or the need for the spectral library to be known a priori.

This paper proposes a novel method for hyperspectral unmixing called fuzzy c-means unmixing, which achieves endmembers and relative abundance through repeated iteration analysis at the same time.

Experimental results demonstrate that the proposed method can effectively implement hyperspectral unmixing with high accuracy.

The proposed method present an effective framework for the challenging field of hyperspectral image unmixing.

Drawing upon Hofstede's cultural dimensions theory, a comprehensive model exploring the relationships among four distinct culture values and their influence on employees' turnover intention through the mediating roles of organizational commitment and organizational citizenship behavior was developed and tested.

This study covers 585 migrant workers from nine countries who work in the food and beverage industry in Guangzhou, China. Structural equation modeling (SEM) was used to analyze the data collected from these migrant workers.

The results reveal that (1) among the four culture values, only uncertainty avoidance, collectivism orientation and masculinity orientation significantly affect organizational commitment and organizational citizenship behavior, (2) organizational commitment is significantly positively related to organizational citizenship behavior and (3) both organizational commitment and organizational citizenship behavior have a negative direct effect on turnover intention, while organizational citizenship behavior has a stronger impact on migrants' turnover intention than organizational commitment.

The issue of cultural diversity, particularly among relevant migrant workers in the hospitality industry in developing countries, such as China, needs more attention than ever.

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.

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

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.

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.

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。

本论文采用多变量SEM法分析提出的理论模型。

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。

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。

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.

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.

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.

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.

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。

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。

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。

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。

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.