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This paper investigates how the gap between the host country's actual and optimal financial conditions affects foreign direct investment (FDI) inflows through evidence from China.

The authors first employ principal component analysis (PCA) to measure FDI target countries' actual financial conditions and use 30 OECD countries as a reference group to assess the optimal financial condition. The authors then estimate a two-way fixed effect model with panel data of China's outward FDI in 64 countries for the period 2003–2017 to get the regression results. The authors' results overcome endogeneity and are robust.

Results show that (1) the gaps between host countries' actual and optimal financial conditions positively affect FDI inflows from China; (2) there is a heterogeneous effect between low-income and high-income countries. The gaps for high-income countries significantly increase FDI inflows from China, while the gaps are not significant for low-income countries.

The authors examine how the gap affects FDI inflows from China. An increase of 1% in the target country's gap promotes a 6.3% increase in FDI inflows. However, the authors do not explore what mechanisms are key to these results. The authors will explore these questions in the future.

This paper complements the influence factors of FDI and enriches theories of FDI. The gap between actual and optimal financial conditions plays an essential role in FDI flows across countries for policymakers.

The high-pressure accumulator has been widely used in the hydraulic system. Failure pressure prediction is crucial for the safe design and integrity assessment of the accumulators. The purpose of this study is to accurately predict the burst pressure and location for the accumulator shells due to internal pressure.

This study concentrates the non-linear finite element simulation procedure, which allows determination of the burst pressure and crack location using extensive plastic straining criterion. Meanwhile, the full-scale hydraulic burst test and the analytical solution are conducted for comparative analysis.

A good agreement between predicted and measured the burst pressure that was obtained, and the predicted failure point coincided very well with the fracture location of the actual shell very well. Meanwhile, the burst pressure of the shells increases with wall thickness, independent of the length. It can be said that the non-linear finite element method can be employed to predict the failure behavior of a cylindrical shell with sufficient accuracy.

This paper can provide a designer with additional insight into how the pressurized hollow cylinder might fail, and the failure pressure has been predicted accurately with a minimum error below 1%, comparing the numerical results with experimental data.

As digital spaces for team collaboration, virtual worlds bring considerable verisimilitude to technology-mediated social interaction and change the process of traditional team learning. The purpose of this study is to understand how to promote collaborative learning in virtual worlds by leveraging the power of we-intention to participate in virtual worlds. The authors further use the valence–instrumentality–self-efficacy–trust model (VIST) model as a means of understanding the formation of we-intention to participate in virtual worlds, during which behavioral desire serves a bridging role.

The authors tested the research model using the data gathered from 298 users of a prominent form of virtual world, i.e. massively multiplayer online role-playing games. The authors used the structural equation modeling approach and the partial least squares technique for data analysis.

Results show that the four factors of the VIST model (i.e. valence on team goals, instrumentality of contribution, self-efficacy in team tasks and trust in team members) all positively influence we-intention to participate in virtual worlds through behavioral desire for team actions. We-intention to participate in virtual worlds further exerts a stronger positive effect on collaborative learning in virtual worlds, compared with I-intention to participate in virtual worlds.

This work advances the information systems literature by introducing a relevant and important concept, i.e. we-intention, to explain collaborative learning in virtual worlds. This study especially compared the effect of we-intention and I-intention on collaborative learning in virtual worlds. The results of this work also provide practitioners with insights into the role of we-intention in promoting collective actions in virtual worlds.

Members' knowledge contribution behavior has positive significance for maintaining the activity of the knowledge community, as well as for improving knowledge interaction efficiency and member viscosity. With the development of the mobile Internet, knowledge communities based on social platforms have become more convenient and popular. This study aims to explore what and how factors influence members' knowledge contribution behavior in social knowledge communities from the perspective of social distance.

Based on the theory of reciprocity and on the theory of self-efficacy, hypotheses and research models are proposed. In the empirical study, WeChat learning group is selected as the research case. The empirical investigation (N = 244) collects research data through questionnaires.

I-intention and we-intention both have positive influence on members' knowledge contribution behavior. Knowledge self-efficacy positively moderates the influence of we-intention and affects knowledge contribution behavior. In addition, I-intention is positively affected by expected knowledge benefit, expected emotional benefit and expected image benefit, while costs have no effect. We-intention is positively influenced by affective commitment, continuance commitment and normative commitment in relationship strength, as well as affiliation to the contributing climate.

This paper aims to discuss I-intention, we-intention, and their roles in members' knowledge contribution behavior. It is a beneficial development for existing research to combine the characteristics of new style communities with systematical analysis of knowledge contribution behavior. Findings may provide enlightenment to the social knowledge community on diversity development and differentiated marketing strategies.

The CEEQUAL certification system promotes sustainable development (SD) principles in infrastructure construction, with 12 categories of criteria and indicators. ENVISION assigns 60 points to five categories, while Green Guide is divided into seven classifications. SD certification requires 11 requirements, including an ecological assessment procedure, life-cycle costing assessment, quality control plan, noise mitigation plan, waste management plan, pollution prevention plan, low impact development, pavement management system, site maintenance plan, and educational outreach. SD certification technique provides 8 critical criteria, 153 standards, 17 stringent prerequisites, and 8 categories of points. Culp (2011) developed a grading system to incorporate SD principles into infrastructure projects; Shen et al. (2011) explored significant assessment parameters for the SD of infrastructure projects using the fuzzy set method; Lui and Cui (2012) studied SD frameworks for building projects, Montgomery et al. (2014) and Lim (2009) identified 77 major SD indicators based on a comprehensive review of the relevant literature, and the Transport Division of New South Wales established a Transportation Project Sustainability Framework to ensure the long-term viability of their transportation network and the continuous improvement of their environmental and sustainability performance. Assah Amiril (2014) revealed a global network of 27 SD criteria produced by professionals, for-profit and non-profit organizations, divided into five groups: ecological, financial, sociological, engineering, asset use, and project management. The most important details in this study are that 57 indicators were categorized into eight types, weighted according to their respective impacts, and the influence of each component on SD was evaluated using a 100-dimensional scale. This study investigated the eight criteria and the impact of three additional criteria (public participation, climate change response, and stakeholder management). This chapter examined the criteria and indicators of SD criteria and indicators for road infrastructure development in developing countries. The most important findings are that the CEEQUAL, Ugwu, Haupt, and Lim models are the most comprehensive theoretical models of SD requirements for infrastructure design, and that all frameworks and models promote the sharing, promotion, and acknowledgement of SD concepts.

This study aims to investigate the relationship between mentors’ paradox mindset and career mentoring directly and indirectly through self-efficacy and work engagement, drawing insights from attachment theory.

A serial mediation model was tested using survey data from 297 employees working in a bank company in China.

Paradox mindset had a significant indirect effect on career mentoring through self-efficacy and work engagement, self-efficacy had a significant indirect effect on career mentoring through work engagement, and paradox mindset had a significant indirect effect on career mentoring through self-efficacy and work engagement.

The results offer practical insights for human resource managers by investigating how mentors’ mindsets affect their psychological states and behaviors. By training and developing mentors’ paradox mindset, mentors can better deal with tensions with a high level of self-efficacy and work engagement in the increasingly changing and demanding work environment and foster functional mentoring relationships.

Findings of this study provide fresh insights into the relationship between individual differences and mentoring relationships by uncovering the critical role of paradox mindset in enhancing self-efficacy and work engagement. Moreover, the interaction of mentors’ paradox mindset and self-efficacy advances previous studies on attachment theory by investigating the underlying mechanisms of mentoring relationships involving affectionate or emotional factors.

Online health communities (OHCs) have been recognized as emerging platforms on the Internet used for health purposes. Despite its emergence, developing a successful OHC is still a challenge. Prior studies identified that value co-creation behavior (VCB) of members is an essential factor for sustaining OHCs; however, little is known about how members’ behavior drives to co-create value? Therefore, this study aims to discover the inclusive mechanism for members’ VCB in OHCs.

The authors develop the study model and hypothesis based on the service-dominant logic of value co-creation theory and social support (SS) literature. The survey data of 608 active OHCs users in China were analyzed using partial least squares structural equation modeling (PLS-SEM).

The results revealed that SS positively affects members’ VCBs. Ethical aspects; Trust and ethical interaction (EI) partially mediate their relationships. In addition, community members’ current health status (CHS) negatively moderates the relationships between SS and VCB. From the findings, it becomes evident that only SS is not enough; developing an ethical environment in OHCs, i.e. trust and ethically rich interactions among members, significantly helps OHCs to promote co-creation. Also, the negative moderation of CHS findings provides novel insights when cramming health conditions.

Exploring the complex mechanism of co-creation in OHC, the authors illustrate the potential of service-dominant logic to create new theoretical insight for healthcare and provide the framework of co-creation with ethics for the first time. This will extend the application of ethics in healthcare services and offer a robust platform from which the understanding of drivers of members’ VCB can be advanced in the OHC context.

The majority of existing studies about named entity recognition (NER) concentrate on the prediction enhancement of deep neural network (DNN)-based models themselves, but the issues about the scarcity of training corpus and the difficulty of annotation quality control are not fully solved, especially for Chinese ancient corpora. Therefore, designing a new integrated solution for Chinese historical NER, including automatic entity extraction and man-machine cooperative annotation, is quite valuable for improving the effectiveness of Chinese historical NER and fostering the development of low-resource information extraction.

The research provides a systematic approach for Chinese historical NER with a three-stage framework. In addition to the stage of basic preprocessing, the authors create, retrain and yield a high-performance NER model only using limited labeled resources during the stage of augmented deep active learning (ADAL), which entails three steps—DNN-based NER modeling, hybrid pool-based sampling (HPS) based on the active learning (AL), and NER-oriented data augmentation (DA). ADAL is thought to have the capacity to maintain the performance of DNN as high as possible under the few-shot constraint. Then, to realize machine-aided quality control in crowdsourcing settings, the authors design a stage of globally-optimized automatic label consolidation (GALC). The core of GALC is a newly-designed label consolidation model called simulated annealing-based automatic label aggregation (“SA-ALC”), which incorporates the factors of worker reliability and global label estimation. The model can assure the annotation quality of those data from a crowdsourcing annotation system.

Extensive experiments on two types of Chinese classical historical datasets show that the authors’ solution can effectively reduce the corpus dependency of a DNN-based NER model and alleviate the problem of label quality. Moreover, the results also show the superior performance of the authors’ pipeline approaches (i.e. HPS + DA and SA-ALC) compared to equivalent baselines in each stage.

The study sheds new light on the automatic extraction of Chinese historical entities in an all-technological-process integration. The solution is helpful to effectively reducing the annotation cost and controlling the labeling quality for the NER task. It can be further applied to similar tasks of information extraction and other low-resource fields in theoretical and practical ways.

Ever since its emergence, the metaverse has presented opportunities and disruptions to every stakeholder, including individual users and organizations. This article aims to offer valuable perspectives on six identified critical areas that the metaverse could significantly impact: marketing ethics, marketing communication, relationship marketing, retail marketing, supply chain management and transportation management.

Through a multi-perspective approach, this paper gathers valuable perspectives from various invited contributors to each of the six identified key areas that the metaverse could significantly impact.

For each key area identified, the invited contributors first share their valuable perspectives by discussing the roles of the metaverse. Subsequently, the invited contributors discuss their views on vital opportunities, challenges and research agenda concerning the metaverse.

With the widespread metaverse, it is expected that each key area identified is likely to undergo significant levels of disruption. Against this backdrop, this paper contributes to the academic literature and industry by gathering different perspectives from invited contributors on the relevance of the metaverse in marketing and logistics domains.

This study aims to examine newcomers experiencing maladjustment due to cognitive diversity, specifically, how maladjustment affects their turnover intentions; the mediating role of reported workplace bullying; and the buffering effect of perceived inclusive practices in the hospitality sector.

The authors collected time-lagged data from 403 respondents and analyzed the data through hierarchical regression analyses using statistical package for the social sciences (SPSS) 25.0.

Role ambiguity, low self-efficacy and social exclusion could each lead to newcomers’ reported workplace bullying (NRB). Perceived inclusive practices buffered the impacts of role ambiguity and social exclusion. NRB negatively mediated the relationships between role ambiguity and NRB; and social exclusion and NRB.

Hospitality practitioners should specify work procedures to minimize role ambiguities and record service processes to correct mistakes, reward veterans who help newcomers improve self-efficacy, invite newcomers to develop inclusive practices and review employee comments on third-party platforms to understand factors responsible for turnover intention.

This study contextualized cognitive diversity into newcomers’ maladjustment-bullying-turnover model in China’s hospitality industry. It highlighted the buffering effect of perceived inclusive practices in the relationships between maladjustment and reported bullying and turnover intentions among newcomers and confirmed the important role of self-efficacy in addressing adverse work events.