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Identifying the frontiers of a specific research field is one of the most basic tasks in bibliometrics and research published in leading conferences is crucial to the data mining research community, whereas few research studies have focused on it. The purpose of this study is to detect the intellectual structure of data mining based on conference papers.

This study takes the authoritative conference papers of the ranking 9 in the data mining field provided by Google Scholar Metrics as a sample. According to paper amount, this paper first detects the annual situation of the published documents and the distribution of the published conferences. Furthermore, from the research perspective of keywords, CiteSpace was used to dig into the conference papers to identify the frontiers of data mining, which focus on keywords term frequency, keywords betweenness centrality, keywords clustering and burst keywords.

Research showed that the research heat of data mining had experienced a linear upward trend during 2007 and 2016. The frontier identification based on the conference papers showed that there were five research hotspots in data mining, including clustering, classification, recommendation, social network analysis and community detection. The research contents embodied in the conference papers were also very rich.

This study detected the research frontier from leading data mining conference papers. Based on the keyword co-occurrence network, from four dimensions of keyword term frequency, betweeness centrality, clustering analysis and burst analysis, this paper identified and analyzed the research frontiers of data mining discipline from 2007 to 2016.

Extensive atomistic simulations of the mechanical deformation of defective nanowires (NWs) were performed using the embedded-atom molecular dynamics modeling approach. The investigation focuses on the coupled effects of various vacancy cluster (VC) defects, operation temperature, and wire cross-sectional area on the mechanical properties and plastic deformations of defective NWs. The stress-strain behaviors show that the elastic modulus is independent of the vacancy cluster defects. Quasi-linear decreasing Young's moduli were observed with increasing operation temperature. For a given operation temperature, NW Young's modulus increased with increasing NW size.

The purpose of this paper is to provide insights for flower retailers, horticultural practitioners and marketing managers into the prioritisation of cut flower attributes by German residents.

Applying a best–worst scaling approach, this analysis identified the relative ranking of importance amongst product attributes relevant to German consumers when buying fresh cut flowers. A latent class analysis determined four flower consumer segments for further study. The study builds on a sample of 978 consumers and is consistent with the most recent German census in terms of age, gender, income and federal state.

The best-worst analysis showed that intrinsic flower attributes, in particular appearance, freshness and scent were found to be more important to German consumers than the extrinsic attributes studied, namely, price, country of origin and a certification indicating fair trade. The latent class analysis determined four consumer segments that desire either budget, luxury or ethical flowers or more information about flowers. For all identified consumer segments, appearance was the attribute of greatest importance. The segments that desired luxury or ethical flowers, as well as the segment that desires more information were interested in appearance, but also had relatively large shares of preferences dedicated to flower freshness guarantees. The preference for freshness guarantees in addition to appearance may be interpreted jointly as a desire for not only beautiful and aesthetically pleasing flowers, but for sustained beauty.

Internationally, the study fills a research gap by exploring consumer’s relative preference for cut flower attributes. In contrast to existing studies on consumer preferences for flowers in Germany, the present study builds on a sample that was targeted in terms of age, gender, net household income and federal state to the most recent German census.

As the global emphasis on environmental consciousness intensifies, many corporations claim to be environmentally responsible. However, some merely partake in “greenwashing” – a facade of eco-responsibility. Such deceptive behavior is especially prevalent in Chinese heavy-pollution industries. To counter these deceptive practices, this study aims to use machine learning (ML) techniques to develop predictive models against corporate greenwashing, thus facilitating the sustainable development of corporations.

This study develops effective predictive models for greenwashing by integrating multifaceted data sets, which include corporate external, organizational and managerial characteristics, and using a range of ML algorithms, namely, linear regression, random forest, K-nearest neighbors, support vector machines and artificial neural network.

The proposed predictive models register an improvement of over 20% in prediction accuracy compared to the benchmark value, furnishing stakeholders with a robust tool to challenge corporate greenwashing behaviors. Further analysis of feature importance, industry-specific predictions and real-world validation enhances the model’s interpretability and its practical applications across different domains.

This research introduces an innovative ML-based model designed to predict greenwashing activities within Chinese heavy-pollution sectors. It holds potential for application in other emerging economies, serving as a practical tool for both academics and practitioners.

The findings offer insights for crafting informed, data-driven policies to curb greenwashing and promote corporate responsibility, transparency and sustainable development.

While prior research mainly concentrated on the factors influencing greenwashing behavior, this study takes a proactive approach. It aims to forecast the extent of corporate greenwashing by using a range of multi-dimensional variables, thus providing enhanced value to stakeholders. To the best of the authors’ knowledge, this is the first study introducing ML-based models designed to predict a company’s level of greenwashing.

Investments.

The case is suitable for students with diverse backgrounds – from different countries with different cultures, and from different programs (undergraduate or graduate). The case will be used for an all-English course “The research of Chinese stock markets” and has been used for the course “Portfolio theory and management” (junior student level) at Nankai University.

The case introduces Chinese stock markets' uniqueness that there exists a huge number of previously nontradable shares. The release of the shares radically changes the markets' balance and causes the absolute dominance of stock supply over stock demand. Based on the analysis for ICBC, the case demonstrates that the dominance can explain the drop of ICBC's stock price by supply-demand law but fundamental analysis cannot.

The case will help students to understand the uniqueness of Chinese stock markets and the applicability of supply-demand law in the markets and then be able to make investment decisions.

The case can help to educate not only students but also Chinese and foreign investors about the uniqueness of Chinese stock markets and arm the students and investors with the supply-demand methodology to analyse the markets and the reasoning of when and how to invest.

Teaching notes are available for educators only. Please contact your library to gain login details or e-mail support@emeraldinsight.com to request teaching notes.

Reports a study of 1,304 Chinese brand names of ten types of products in China. These brand names are content analyzed following a linguistic approach which the authors developed from their earlier studies. The ten types of brand names are presented in three broad categories representing the three different developing stages of the consumer product industry in China: brands of traditional products (illustrated by matches and spirits), brands of traditional products with current development (illustrated by bicycles, shoes, and toothpastes), and brands of new and modern products (illustrated by cosmetics, soft drinks, washing machines, refrigerators and TV sets). The conclusion drawn from the analysis is that one of the variables in determining how linguistic principles are being applied to Chinese brand naming is the respective stages of development of such products in the context of the Chinese market economy.

This is the third of a series of studies on Chinese brand naming using content analysis from a linguistic perspective. The first study generalized the principles guiding Chinese brands in terms of syllable pattern, tone pattern, compounding structure and semantic preference. The second looked at specific branding rules, focusing on two entirely different products: cosmetic products and bicycles. The present study, following the same linguistic framework of analysis, analyzes three groups of closely related products: spirits, beers, soft drinks, to see how these brands are creatively and distinctively constructed. Finds that the brand naming patterns of the three drinks are basically in agreement with the general Chinese branding principles, and the differences among them directly reflect the development, the consumer markets and characteristics of each product.

This paper aims to reveal the curvilinear relationships between perceived development human resource practices (DHRPs) and both affective commitment and work stress, and the moderating effects of age on the curvilinear relationships.

Hypotheses were developed from an employee-oriented contingent view based on the person-job fit theory and lifespan development theories. Methods suggested by Haans et al. (2016) and Dawson (2014) to test curvilinear relationships and related moderations, and a two-wave survey data from 742 Chinese employees were used.

The results showed that perceived DHRPs related to affective commitment in an inverted U shape and work stress in a U shape. However, age moderated the nature of the relationships such that both the curvilinear relationships only existed under low age while under high age perceived DHRPs related to affective commitment positively and work stress negatively.

This study advances the prevailing linear (positive or negative) thinking on the DHRPs–outcomes relationships by showing that perceived DHRPs relate to both affective commitment and work stress nonlinearly. Moreover, different from existing findings that age moderates the strength of the linear DHRPs–outcomes relationships, the results indicate that age moderates the nature of the relationships between perceived DHRPs and affective commitment and work stress. This implies a refined age-differential approach to use DHRPs to sustain a committed and healthy workforce in the context of workforce aging.

In recent years, many new and interesting business models for Internet-based selling have emerged with the advent of electronic commerce, one of which is the Internet-based group-buying. Since group-buying can be quickly built and removed, and the consumers can pay a lower price for the product through it, the group-buying can be a new online promotion form. In this chapter we build up a two-period pricing model for a supply chain when a supply chain member utilizes group-buying program to promote its products. In detail, we consider a supply chain consisting of a supplier and a retailer, where the supplier or retailer may launch a group-buying program to promote the products via a group-buying web site in the promotion period (i.e., the first period), as well as the supplier may sell its products through the retailer traditionally in both periods. Utilizing game theory, we derive the equilibrium decisions of the two supply chain members in three different scenarios, that is, (i) there is no group-buying program, (ii) the supplier launches a group-buying program, and (iii) the retailer launches a group-buying program. Analysis of the equilibrium decisions illustrates the following results: (i) both, the supplier and the retailer, will set low prices in the promotion period and high prices in the regular period; (ii) this trend will be enhanced when a group-buying program occurs, especially when such program is launched by the supplier; (iii) while the retailer can always benefit from a group-buying program, the supplier’s profit may be reduced under certain conditions; and (iv) in spite of the fact that the supplier’s profit may be damaged by the group-buying program, when the two supply chain members decide to launch a group-buying program, the unique equilibrium is that the supplier will launch such a program.