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The overall goal of this chapter is twofold. First, the authors aim to identify indigenous phenomena that influence employee turnover and retention in the Chinese context. Second, the authors link these phenomena to the contextualization of job embeddedness theory. To achieve the goal, the authors begin by introducing three macro-level forces (i.e., political, economic, and cultural forces) in China that help scholars analyze contextual issues in turnover studies. The authors then provide findings in the literature research on employee retention studies published in Chinese academic journals. Next, the authors discuss six indigenous phenomena (i.e., hukou, community in China, migrant workers, state-owned companies, family benefit prioritization, and guanxi) under the three macro-level forces and offer exploratory propositions illustrating how these phenomena contribute to understanding employee retention in China. Finally, the authors offer suggestions on how contextualized turnover studies shall be conducted in China.

The current study examines the relation of guanxi human resource management (HRM) practices with subjective evaluations of creative performance by direct supervisors, as well as conceptualizes the employee ambidextrous behavior as a mediator, and social comparison orientation and leader–member exchange (LMX) as moderators for understanding the relation.

Survey data were collected from 211 employee–supervisor dyads in China. Hierarchical regression analyses, Preacher and Hayes’ (2008) indirect effects PROCESS macro, and Preacher et al.'s (2007) moderated mediation analysis approach were conducted to test the hypothesized relationships.

Guanxi HRM practices were negatively associated with employee creative performance, mediated by the employee ambidextrous behavior. The authors also found that social comparison orientation showed a strong moderating effect, such that it amplified the indirect relationship between guanxi HRM practices and employee creative performance via ambidextrous behavior. In contrast, LMX showed a weak moderating effect, such that it attenuated this indirect relationship.

This study provides evidence that the extent to which employee ambidextrous behavior mediates the relationship between guanxi HRM practices and creative performance depends on LMX and social comparison orientation. It represents a promising new direction for the guanxi HRM practices and creative performance literatures.

To introduce the Securities Law of the People's Republic of China (the “Securities Law 2019”) revised on 28 December 2019, and provide a detailed analysis on its key implications to the securities regulatory regime and market activities, especially securities issuance and trading activities in China.

This article starts from a historical overview of the Securities Law and its several revisions and amendments, highlights the notable core revisions in the Securities Law 2019, analyzes the key legal and regulatory impacts to the securities-related activities and market players, and finally, provides an outlook to the future developments of securities regulatory regime in conformity with the Securities Law 2019.

This article concludes that the revisions made to the Securities Law 2019 cover a broad range of issues including the issuance and trading of securities, acquisition of a listed company, information disclosure, securities registration and settlement, etc. Such revisions to the Securities Law will lead to far-reaching and profound implications on the securities regulatory system and industry practice in China.

The Securities Law 2019 attracts broad attention from securities market players as well as relevant professionals of the industry, including securities lawyers. As this is a novel and hot topic within the industry, it is important for securities lawyers to keep on track.

High-level guidance from experienced lawyers in the Capital Markets and Financial Regulation practices.

The e-freight program launched by the International Air Transport Association (IATA) has gradually become a standard specification for international air freight operations. This study examined critical factors affecting air freight forwarders’ decision to adopt the IATA e-freight using a technology-organization-environment model with air freight forwarders in Taiwan as the base. Our findings show that ‘information technology (IT) competence’, ‘trading partner pressure’, ‘government policy’ and ‘competitive pressure’ all have significant positive effects on air freight forwarders’ decision to adopt the e-freight and the top three factors among these are ‘government funding’, ‘government’s active promotion’ and ‘government’s requirement of electronic air waybill (e-AWB)’. Finally, this study proposes strategies that can encourage air freight forwarders to decide on e-freight adoption for the information of relevant oK regyawniozradtison International Air Transport Association (IATA); IATA e-freight; Technology organization environment model; Air freight forwarder

This paper aims to introduce a systematic computing and analytical procedure that is applied to the co-author network to identify the temporal evolution and growth of research collaborations in the area of e-governance. The empirical analysis of the temporal co-author network can trace the emerging authors and knowledge bursts over time.

The study applied social network theory to trace the author collaboration patterns in the domain of e-governance. Analysis of the co-author network using micro and macro parameters was done to trace the temporal evolution of the author collaborations.

E-governance is a multi-disciplinary research domain split over streams of management, politics, information technology and electronics. Hence, research collaborations play a significant role in its advancement. The knowledge sharing between individual authors, institutions and groups through research collaborations, resulting in extensive sharing of data, equipment and research methods, has boosted research activities and development in e-governance. In this paper, the authors systematically analyse the current scenario of research collaborations in the area of e-governance using co-author network to estimate its impact on the advancement of the field. The authors also analysed the temporal evolution of the co-author networks, which show remarkable growth of research collaborations in the domain of e-governance from the year 2000.

The co-author network analysis is only a proxy measure for the analysis of research collaborations. The names of the authors and the university affiliations used in the article are as retrieved from the research repository of Scopus. The degree, citations and other parameters related with authors have scope only within the environment of the co-author network used in the analysis. The criteria used in the study is limited to the degree of research collaborations and the number of co-authored publications in the giant component of the co-author network.

Institutions, authors and governments can trace and select suitable topics and choose research groups of co-authors over the world for future research collaborations in e-governance. The knowledge about the emerging and most discussed topics gives an overview of the global research trends of e-governance.

The study identified the evolution of creative collaborations in e-governance in the global perspective. The methodology introduced here is helpful to detect the proficient and productive author collaborations and the spectrum of related e-governance research topics associated with them. As the author collaborations can be mapped to the institutional and country-level collaborations, the information is helpful for researchers, institutions and governments to establish the best collaborations in e-governance research based on the author proficiency, collaboration patterns and research topics as per the requirements.

The paper introduces a novel research methodology using temporal analysis of co-author network to identify the evolution of research patterns and the associated research topics.

There is significant amount of literature tackling different issues related to the port industry. The present chapter focuses on a single business unit of seaports aiming at the documentation of works related to container terminals.

An effort to review, collect and present the majority of the works present in the last 30 years, between 1980 and 2010, has been made in order to picture the problems dealt and methods used by the authors in the specific research field. To facilitate the reader, studies have been grouped under five categories of addressed problems (productivity and competitiveness, yard and equipment utilization, equipment scheduling, berth planning, loading/unloading) and four modelling methodologies (mathematics and operations research, management and economics, simulation, stochastic modelling).

The analysis shows that most works focus on productivity and competitiveness issues followed by yard and equipment utilisation and equipment scheduling. In reference to the methodologies used managerial and economic approaches lead, followed by mathematics and operations research.

In reference to future research, two fields have been identified where there is scope of significant contribution by the academic community: container terminal security and container terminal supply chain integration.

The present chapter provides the framework for researchers in the field of port container terminals to picture the so far works in this research area and enables the identification of gaps at both research question and methodology level for further research.

The current study aims to empirically analyze the influence of different information sources, together with the persuasiveness of recommender systems (RSs) on the consumer’s purchase intention (PI). It also expands the research on RSs from the point of view of consumer behavior and psychology, considering perceived usefulness and relevance. In addition, it analyzes how different types of personalized recommendations, along with non-personalized ones, influence PI.

The proposed model has been validated using partial least squares structural equation modeling (PLS-SEM), based on the data collected from 597 online shoppers.

This study proves that both information search and RSs influence PI, being complementary rather than mutually exclusive. Recommender systems’ findings indicate that the PI is primarily influenced by the perceived relevance of RSs, the information provided by manufacturers and reviews. Moreover, only the influence of the perceived usefulness of personalized recommendations strongly affects PI. Conversely, non-personalized recommendations do not affect PI.

Developers should focus on increasing the perceived usefulness and relevance of RSs. Thus, they could adopt the hybridization of RSs with the aggregation of both personal shopping behavior and social network contacts. It should integrate information signals from multiple sources to include sentiment extracted from reviews or links to the manufacturer’s page. Furthermore, the recommendation of discounted products must be only for products preferred by customers, because only these influence the PI.

This research provides a structural model that examines together, for the first time, the influence on the PI of the main RSs and sources of information.

This paper examines the impact of residents’ human capital investment inequality on the urban–rural income gap, using China’s provincial panel data from 1997 to 2013. The results show that, at the national level as well as at the regional level, residents’ overall human capital investment inequality has a positive significant impact on the urban–rural income gap. In addition, the impact of overall human capital investment inequality increased monotonically from the eastern region inward to the western region. In terms of the relative impact of each component of human capital investment inequality on the urban–rural income gap, migration investment inequality appears to have the greatest impact at the national level, whereas health investment inequality has the greatest impact on the urban–rural income gap in the eastern region, and education investment inequality exhibits the greatest impact in the central and western regions. We also investigate the impact of human capital investment inequality on the urban–rural income gap over different periods. The results show that residents’ overall human capital investment inequality had a positive impact on the urban–rural income gap in the period 1997–2008, but the impact rapidly shrunk in 2009–2013. Furthermore, the impact of residents’ health investment inequality on the urban–rural income gap shows a downward trend, and the impact of residents’ education investment inequality trended slightly upward from 1997 to 2008, and then rapidly shrunk in 2009–2013. Finally, the impact of residents’ migration investment inequality was only significant in 1997–2002.

Shelf space is often retailer's critical resource. Growing number of products has posed a challenge to the retailers for efficient allocation of available shelf space to them. The paper aims to consider a retail shelf space allocation problem with linear profit function and aims to develop efficient heuristics to solve this problem.

The paper develops three heuristics to solve a shelf space allocation problem. It compares three heuristics with existing heuristic using empirical study.

In an empirical study of 320 randomly generated instances of problems with size (products, shelves) varying from (25, 5) to (200, 50), it was found that all three new heuristics are competitive with existing heuristic. The best amongst three heuristics found solution with average objective value of 99.59 percent of upper bound in a reasonable central processing unit time.

The linearity assumption of the profit function is based on earlier findings that marginal returns to space first increase and then decrease in an S‐shaped curve. Hence, linearity assumption for profit function is justified by the fact that retails would want to operate on linear (or approximately linear) and more strongly increasing part of the curve.

The proposed heuristics are applied to a case of existing retail store which gave more profit than the current allocation scheme.

The paper proposes new initial constructor and neighbourhood move strategy to develop efficient heuristic. Heuristics proposed in this paper are competitive with existing heuristics.

Breathing resistance is the main factor that influences the wearing comfort of respirators. This paper aims to demonstrate the feasibility of using the gene expression programming (GEP) for the purpose of predicting subjective perceptions of breathing resistances of wearing respirators via surface electromyography (sEMG) and respiratory signals (RSP) sensors.

The authors developed a physiological signal monitoring system with a specific garment. The inputs included seven physical measures extracted from (RSP) and (sEMG) signals. The output was the subjective index of breathing resistances of wearing respirators derived from the category partitioning-100 scale with proven levels of reliability and validity. The prediction model was developed and validated using data collected from 30 subjects and 24 test combinations (12 respirator conditions × 2 motion conditions). The subjects evaluated 24 conditions of breathing resistances in repeated measures fashion.

The results show that the GEP model can provide good prediction performance (R² = 0.71, RMSE = 0.11). This study demonstrates that subjective perceptions of breathing resistance of wearing respirators on the human body can be predicted using the GEP via sEMG and RSP in real-time, at little cost, non-invasively and automatically.

This is the first paper suggesting that subjective perceptions of subjective breathing resistances can be predicted from sEMG and RSP sensors using a GEP model, which will remain helpful to the scientific community to start further human-centered research work and product development using wearable biosensors and evolutionary algorithms.