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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.

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.

The traditional drug development process is costly, time consuming and risky. Using computational methods to discover drug repositioning opportunities is a promising and efficient strategy in the era of big data. The explosive growth of large-scale genomic, phenotypic data and all kinds of “omics” data brings opportunities for developing new computational drug repositioning methods based on big data. The paper aims to discuss this issue.

Here, a new computational strategy is proposed for inferring drug–disease associations from rich biomedical resources toward drug repositioning. First, the network embedding (NE) algorithm is adopted to learn the latent feature representation of drugs from multiple biomedical resources. Furthermore, on the basis of the latent vectors of drugs from the NE module, a binary support vector machine classifier is trained to divide unknown drug–disease pairs into positive and negative instances. Finally, this model is validated on a well-established drug–disease association data set with tenfold cross-validation.

This model obtains the performance of an area under the receiver operating characteristic curve of 90.3 percent, which is comparable to those of similar systems. The authors also analyze the performance of the model and validate its effect on predicting the new indications of old drugs.

This study shows that the authors’ method is predictive, identifying novel drug–disease interactions for drug discovery. The new feature learning methods also positively contribute to the heterogeneous data integration.

The purpose of this paper is to analyze the operational decisions of a manufacturer who produces multiple products and the government's selection of cap-and-trade and carbon tax regulations.

This paper explores the production decisions of a multi-product manufacturer under cap-and-trade and carbon tax regulations in a cap-dependent carbon trading price setting and compares carbon emission, the manufacturer's profits and social welfare under the two regulations. Game theory and extreme value theory are used to analyze our models.

First, the authors find that the optimal profit of the manufacturer (the optimal cap) increases and then decreases with the cap (the unit carbon emission of product). Second, if the environmental damage coefficient is moderate, the optimal cap of unit environmental damage coefficient is independent of the product carbon emission or other related product parameters. Ultimately, cap-and-trade regulation always generates more carbon emission than carbon tax regulation. And cap-and-trade regulation (carbon tax regulation) can generate more social welfare if the environmental damage coefficient is low (high), and the social welfare under the two regulations is equal to each other, or otherwise.

This paper contributes the prior literature by considering the inverse relationship of the allocated cap and the carbon trading price and discusses the social welfare under cap-and-trade and carbon tax regulations. Some important and new results are found, which can guide the government's implementation of the two regulations.

The purpose of this research is to investigate how generalisable the public service motivation (PSM) observed in Western society is to China and to examine the effects of public service motivation on job satisfaction.

Exploratory factor analysis and confirmatory factor analysis techniques are applied to survey data of 191 public servants in China to investigate the generalisability of Western PSM. Using hierarchical regression analysis, the paper examines the effects of the dimensions of PSM on job satisfaction.

The results show that the public service motivation observed in the West exists in China, but the generalisability of the construct is limited. Three of the four dimensions of public service motivation (attraction to public policy making, commitment to the public interest, and self‐sacrifice) exist in China, but the fourth dimension (compassion) is unconfirmed.

The paper is the first to examine the generalisability and instrumentality of PSM as observed in Western society to China. The results indicate that the public service motivation observed in the West also exists in China, but that the generalisability is limited. Public service motivation emerges from the results as a positively significant predictor of job satisfaction in the public sector of China. It enhances the applicability and meaningfulness of the concept of public service motivation across political and cultural environments.

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.

Based on the study of overall situation of the tagging function in the provincial public libraries and library of major colleges and universities, this paper aims to examine the difference of tagging behaviour of its users in library and social community sites. The authors also want to understand the causes of a variety of annotation behavior in social community sites and libraries.

The authors collected all system log data of tags, comments and ratings users added in Wuhan University library, and then found the tags, comments and rating of corresponding books in Douban. Then, the authors did questionnaire survey to the Wuhan University students.

The authors found that the annotation service in the library is not perfect as that in social community site. Enthusiasm of users annotating books in the library is far less high than that on the social community sites. Lack of understanding of the annotation service is the main reason why users are not concerned or do not use the tagging service. But users have the needs of the organization of personal information in the library using tags.

This paper investigated the library users’ behavior in the using library OPAC course and compared the difference of annotation behavior between library and social community site.

Purpose: The public health burden caused by tobacco is heavy among first-generation Chinese immigrant men whose home country has significantly higher smoking rates than the United States. The current study is part of a larger effort to pilot an mHealth tobacco cessation intervention using MMS (graphic) mobile phone technologies to target East Asian immigrant populations. Grounded in the Extended Parallel Process Model (EPPM), our specific aims were to determine what message themes, level of graphic intensity, and types of efficacy information are most appropriate and useful for mHealth interventions targeting this population.

Methodology/Approach: A qualitative study utilizing a series of focus groups (k = 5) was conducted with male adult smokers who were born in China and currently reside in the United States. The primary aim of the focus groups was to solicit reactions to a series of preliminary messages developed by the research team. A secondary aim was to gauge receptivity to the use of MMS as a vehicle for smoking cessation intervention. Participants (n = 32) were recruited from local Chinese communities in a large Mid-Atlantic metropolitan area.

Findings: Opinions about different message strategies were mixed. However, participants tended to rate messages more positively when they focused on the impact of smoking on family and loved ones, particularly children. Messages with fear-arousing images were also perceived to be effective at low frequency of exposure, but there were concerns that they may backfire at high exposure. Awareness of and interest in Quitline were low, and concrete quitting tips were perceived as more effective. Participants reported a preference for receiving messages a few times a week, and an MMS message platform was generally preferred to WeChat (a Chinese social media platform).

Implications: Our results suggest that graphic MMS messaging holds promise as an effective intervention method for this population and that EPPM is an appropriate framework to develop, test, and analyze mHealth intervention messages. While messages that focused primarily on impact on children, health, and specific quitting tips were generally found to be more effective, a mix of different types of messages that address a wide range of issues may be most appropriate for this population.

Originality/Value: This study is the first to explore the utility of graphic text messaging as an intervention method to promote smoking cessation among male Chinese immigrants. Findings from the study provide important insights for future intervention work targeting this underserved population.

Relationship management evolves with dynamic and complex environments of megaprojects. However, studies on the longitudinal measurement of relationship management performance for each stakeholder in dynamic and complex project environments are lacking. The purpose of this research is to propose an NK-network evolution model to evaluate stakeholder performance on relationship management in the development of megaprojects.

The model input includes the stakeholder-associated issues and stakeholders' relational strategies, the co-effects of which determine the internal effects of relationship management in megaprojects. The model processing simulates the stakeholder performance of relationship management under the dynamic and complex nature of megaprojects. The NK model shows the dynamic stakeholder interactions on relationship management, whereas the network model presents the complex stakeholder structures of the relationships between stakeholders and relevant issues. The model output is the evolution graph to reveal the weak stakeholder performance on relationship management in the timeline of the project duration.

The research finding reveals that all stakeholders experience the plunge of stakeholder performance of relationship management at the decision-making moment of the planning stage. Construction, environmental and pressure groups may experience the hardship of relationship management at the start of the construction stage. The government is likely to suffer difficulties in relationship management in the late construction stage. Local industry groups would face challenges in relationship management in the middle of the construction stage and handover stage.

The research provides a useful approach to measuring weak moments of relationship management for each stakeholder in various project phases, considering the dynamic and complex environments of megaprojects. The proposed model extends the current knowledge body on how to make project stakeholder analysis by modelling dynamic and complex environments of megaprojects, with bridging the knowledge domains of evolution modeling techniques and network methods.

According to the relevance of product quality and machine degradation state, a hybrid maintenance policy is designed. The paper aims to discuss this issue.

Product quality control and machine maintenance are considered simultaneously in this policy. Based on this policy, the economic model of x-bar control chart is proposed using statistical process control and renewal reward theory.

This model is solved by genetic algorithm and the experimental results validated its feasibility.

In this model, the four corresponding relationship, which is between product quality monitoring result and machine degradation state, is analyzed.