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Developing nursing leadership has become a key policy priority to achieve universal health coverage. This study aims to explore the current status, developing trends and research frontiers in the field of nursing leadership.

In total, 1,137 articles and reviews on nursing leadership from 1985 to 2022 were retrieved from the Web of Science Core Collection database. Trends of publications, journals, countries/regions, institutions, documents and keywords were visualized and analyzed using Microsoft Excel and CiteSpace software.

Nursing leadership research showed an overall increase in number despite slight fluctuations in annual publications. The USA was the leading country in nursing leadership research, and the University of Alberta was the most productive institution. The Journal of Nursing Management was the most widely published journal that focused on nursing leadership, followed by the Journal of Nursing Administration. Keyword analysis showed that the main research hotspots of nursing leadership are improvement, practice and impact of nursing leadership.

This article summarizes the current state and frontiers of nursing leadership for researchers, managers and policy makers, as well as follow-up, development and implementation of nursing leadership. More research is needed that focuses on the improvement, practice and impact of nursing leadership, which are cyclical, complementary and mutually reinforcing. Longitudinal and intervention studies of nursing leadership, especially on patient prognosis, are also particularly needed.

Automatic optical inspection (AOI) systems have been widely used in many fields to evaluate the qualities of products at the end of the production line. The purpose of this paper is to propose a local-to-global ensemble learning method for the AOI system based on to inspect integrated circuit (IC) solder joints defects.

In the proposed method, the locally statistically modeling stage and the globally ensemble learning stage are involved to tackle the inspection problem. At the former stage, the improved visual background extraction–based algorithm is used for locally statistically modeling to grasp tiny appearance differences between the IC solder joints to achieve potential defect images for the subsequent stage. At the latter stage, mean unqualified probability is introduced based on a novel ensemble learning, in which an adaptive weighted strategy is proposed for revealing different contributions of the base classifier to the inspection performance.

Experimental results demonstrate that the proposed method achieves better inspection performance with an acceptable inspection time compared with some state-of-the-art methods.

The approach is a promising method for IC solder joint inspection, which can simultaneously grasp the local characteristics of IC solder joints and reveal inherently global relationships between IC solder joints.

Lightweight apps such as WeChat mini programs (WMPs) are an emerging mobile channel (m-channel) touchpoint that have gained remarkable popularity among consumers. Despite the focus of migration research on traditional m-channel touchpoints (e.g. native apps and mobile websites), but few researchers have examined why consumers switch from native to lightweight apps. Drawing on the push-pull-mooring framework, this study aims to identify the key factors influencing consumers' switching related to lightweight apps.

The data were collected using a questionnaire survey of 416 WMP consumers and the proposed model was analyzed through structural equation modeling.

The results show that the push effect, specifically, high privacy concern, nudges consumers away from native apps, whereas the pull effects, including relative ease of use, convenience of access and exit and socially-oriented interaction, entice consumers to lightweight apps. Further, consumer switching intention is influenced by habit and perceived technology control, both of which reflect the mooring effects. Switching intention also stands as an important precedent of actual behavior.

This study is among the first theoretical explorations of consumer switching across m-channel touchpoints in the context of mobile commerce. For information system practice, these findings provide new insights for both incumbent providers and newcomers on how to retain existing shoppers as well as attract potential shoppers effectively.

Drawing on attribution theory, the current paper aims to examine the effects of review content structures on online review helpfulness, focusing on three pertinent variables: review sidedness, information factuality, and emotional intensity at the beginning of a review. Moreover, the moderating roles of reviewer reputation and review sentiment are investigated.

The review sentiment of 144,982 online hotel reviews was computed at the sentence level by considering the presence of adverbs and negative terms. Then, the authors quantified the impact of variables that were pertinent to review content structures on online review helpfulness in terms of review sidedness, information factuality and emotional intensity at the beginning of a review. Zero-inflated negative binomial regression was employed to test the model.

The results reveal that review sidedness negatively affects online review helpfulness, and reviewer reputation moderates this effect. Information factuality positively affects online review helpfulness, and positive sentiment moderates this impact. A review that begins with a highly emotional statement is more likely to be perceived as less helpful.

Using attribution theory as a theoretical lens, this study contributes to the online customer review literature by investigating the impact of review content structures on online review helpfulness and by demonstrating the important moderating effects of reviewer reputation and review sentiment. The findings can help practitioners develop effective review appraisal mechanisms and guide consumers in producing helpful reviews.

The authors examined how the identification mechanism of the innovation performance of knowledge employees is affected by empowering leadership by influencing the organizational identification and the moderating effect of leaders on the role expectation of knowledge employees as an essential innovation subject.

The authors employed a mixed-method research approach. The authors collected data from 378 knowledge employees and managers in 20 companies in China's Yangtze River Delta cities. The authors analyzed data using multiple regression analysis forecasting methods.

The authors found that there was an inverted U-shaped relationship between empowering leadership and the innovation performance of knowledge employees; organizational identity played a partial mediating role between empowering leadership and the innovation performance of knowledge employees; role expectation of leaders on the innovation behavior of employees regulated the relationship between the organizational identity and innovation performance of knowledge employees.

This study extends the literature on empowering leadership and innovation performance. This study empirically examines the mediating effect of organizational identity between empowering leadership and innovation performance. In addition, this study empirically examines how empowered leaders' expected innovation level moderates the association between organizational identity and innovation performance.

The current study examines the impact of big data analytics capabilities (BDAC) on supply chain performances of the manufacturing firms. Based on the underpinning of resource-based view (RBV) theory, the current study will highlight the significance of BDAC on green dynamic capabilities (GDC), supply chain agility (SCA) and green competitive advantage (GCA). Furthermore, the study examines the moderating effect of supply chain innovativeness (SCI) on the relationship between GCA and firm performance (FP).

Online survey method was employed for the data collection from the 331 managers employed in Pakistan Stock Exchange (PSX)-listed manufacturing firms. The hypothesized model was tested using partial least squares structural equation modeling (PLS-SEM) technique.

The study results indicate that BDAC has a positive influence on both GDC and SCA, leading to enhanced GCA. Furthermore, the results demonstrate that GCA significantly and positively impacts FP, and the relationship between them is positively moderated by SCI.

This study developed a novel theoretical perspective based on RBV theory and provided empirical evidence that manufacturing firms' performances are significantly influenced by BDAC, GDC and SCA. The study results provide valuable practical implications top management regarding the effectiveness of BDAC and SCA in the supply chain. The findings further highlight the significance of SCI strengthening relationship between GCA and FP.

This research aims to explore generation (Gen) Z's personal branding on social media when job seeking.

Gen Z students, in their final year of university, were interviewed about personal branding, as well as recruiters and career advisors to gain insights into the recruitment process and expectations of online personal brands. Before interviewing, Gen Z students' LinkedIn profiles were examined, and then fed into the interview process.

Using impression management theory, the findings show that Gen Z perceive online personal brands as a crucial tool to gain more advantage in job markets. A gap was found between desired and perceived selves in Gen Z's online personal brands. Strategies such as effective self-reflection, authentic communication, self-promotion processes, awareness of risks and constantly controlling digital footprints were suggested to build stronger and more coherent personal brands. Gen Z are in favour of a more dynamic, interactive, work-in-process of authentic personal brands.

This research demonstrates the importance of authentically building online personal branding strategies and tactics to bridge the divide between Gen Z's desired and perceived images in personal branding on social media when job seeking.

Research into older adults' use of social media remains limited. Driven by increasing digitalisation in China, the authors focus on Chinese older adults (aged 60–75)’ use of WeChat.

This study used a qualitative interpretive approach and interviewed Chinese older adults to uncover their social practices of WeChat use in everyday life.

By using social practice theory (SPT), the paper unfolds Chinese older adults' social practices of WeChat use in everyday life and reveals how they adopt and resist the drastic changes in Chinese society.

The study contributes to new understandings of SPT from technology use by emphasising the dynamic characteristics of its three elements. The authors synthesise both adoptions and resistance in SPT and highlight the importance of understanding three elements interdependently within specific contexts, which are conditioned by structure and agency.

The purpose of this paper is to study the modelling mechanisms of several grey incidence analysis models with great influence, including Deng’s grey incidence model, absolute degree of grey incidence model, slope degree of incidence model, similitude degree of incidence model and closeness degree of incidence model; then analyse the problems to be solved in grey incidence analysis models; and clarify the applicable ranges of commonly used grey incidence models.

The paper comes to conclusions by means of comparable analysis. The authors compare several commonly used grey incidence analysis models, including Deng’s grey incidence model, absolute degree of grey incidence model, slope degree of incidence model, similitude degree of incidence model and closeness degree of incidence model and give several examples to clarify the reasons why quantitative analysis results of different models are not exactly the same.

As the intension of each kind of incidence model is clear and the extension is relatively obscure, grey incidence orders calculated by different incidence models are often different. When making actual decisions, incompatible results may appear. According to different characteristics of extraction, grey incidence analysis models can be divided into three types: incidence model based on closeness perspective, incidence model based on similarity perspective and incidence model based on comprehensive perspective.

The conclusions obtained in this paper can help people avoid some defects in the process of actual selection and choose the better incidence analysis model.

The conclusions can be used as a reference and basis for the selection of grey incidence analysis models, it can help to overcome the defects and shortcomings of models caused by themselves and screen out more excellent analytical models.

The purpose of this paper is to investigate the effect of NaCl solution with different concentrations on impact-sliding fretting corrosion behavior of Inconel 690TT steam generator heat transfer tubes.

The optical 3D profiler was used to measure the wear profile and calculated the wear volume. Corrosion behavior was studied using open circuit potential monitoring and potentiodynamic polarization testing. The morphologies and elemental distributions of wear scars were analyzed using scanning electron microscopy and energy-dispersive spectroscopy. The synergism of wear and corrosion was analyzed according to the ASTM G119 standard.

The corrosion tendency reflected by OCP and the corrosion current calculated by Tafel both increased with the increase of NaCl concentration. The total volume loss of the material increased with concentration, and it was known from the synergism that the volume loss caused by corrosion-enhanced wear accounted for the largest proportion, while the wear-enhanced corrosion also made a greater contribution to volume loss than tangential fretting corrosion. Through the analysis of the material morphologies and synergism of wear and corrosion, the damage mechanism was elucidated.

The research findings can provide reference for impact-sliding fretting corrosion behavior of Inconel 690TT heat transfer tubes in NaCl solution with different concentrations.