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The purpose of this study is to use the grounded theory to summarize the types of celebrity persona and to construct a theoretical model for celebrity persona on consumer purchase intention. Based on the study results, it provides better suggestions for merchants and live streamers and is an expansion of previous research on live-streaming e-commerce.

The grounded theory is recognized as the most scientific qualitative research method and is the ideal explorative method for generating theory. First, the participants were interviewed, and interview data were collected. Then the interview data were organized and analyzed. Finally, this paper summarizes the types of celebrity persona and constructes a theoretical model framework of celebrity persona on consumers' purchase intention.

The results show that the celebrity live streamer persona can be divided into two types: personalized persona and professional persona. Through emotional attachment, the celebrity's persona affects the consumer's purchase intentions. As well as, product type plays a moderating role between celebrity persona and consumer purchase intentions.

The contribution of this research is to start from the celebrity persona, link the celebrity persona with the consumer purchase intentions and expand the research scope of the celebrity persona. It opens the “black box” of the heterogeneity of celebrity live streamers' characteristics on consumer purchase intentions.

The objective of this paper is to develop a model for planning and establishment of knowledge management (KM) strategy in one of the Iranian Sub‐stream Aerospace Industries Organization to improve company's performance.

This research tries to use multi‐method approach by integrating balanced score card, which is a renowned strategic management approach, and Nonaka and colleagues' knowledge creation process (socialization, externalization, combination, and internalization model), which is a well‐known knowledge creation and conversion model, being adopted as the foundations of strategic knowledge management model (SKMM).

The analytical approach identifies eight issues as critical success factors of the knowledge strategy map in this case study. The overall results from the case study are positive as well, thus reflecting the appropriateness of the suggested SKMM model.

SKMM can be used to help forward the plan, establishment and evaluation of KM strategies and initiatives. This helps to ensure that the essential issues are covered during design and implementation phases of KM strategies.

This paper further provides an integrated perspective of KM metrics in high‐tech industries including the aerospace industry. It gives valuable information and guidelines that hopefully will help leaders to consider important issues during performance measurement of KM strategies in organizations.

This paper aims to reveal the factors patients consider when choosing a doctor for consultation on an online medical consultation (OMC) platform and how these factors influence doctors' consultation volumes.

In Study 1, influencing factors reflected as service features were identified by applying a feature extraction method to physician reviews, and the importance of each feature was determined based on word frequencies and the PageRank algorithm. Sentiment analysis was used to analyze patient satisfaction with each service feature. In Study 2, regression models were used to analyze the relationships between the service features obtained from Study 1 and the doctor's consultation volume.

The study identified 14 service features of patients' concerns and found that patients mostly care about features such as trust, phraseology, overall service experience, word of mouth and personality traits, all of which describe a doctor's soft skills. These service features affect patients' trust in doctors, which, in turn, affects doctors' consultation volumes.

This research is important as it informs doctors about the features they should improve, to increase their consultation volume on OMC platforms. Furthermore, it not only enriches current trust-related research in the field of OMC, which has a certain reference significance for subsequent research on establishing trust in online doctor–patient relationships, but it also provides a reference for research concerning the antecedents of trust in general.

On-orbit service technology is one of the key technologies of space manipulation activities such as spacecraft life extension, fault spacecraft capture, on-orbit debris removal and so on. It is known that the failure satellites, space debris and enemy spacecrafts in space are almost all non-cooperative targets. Relatively accurate pose estimation is critical to spatial operations, but also a recognized technical difficulty because of the undefined prior information of non-cooperative targets. With the rapid development of laser radar, the application of laser scanning equipment is increasing in the measurement of non-cooperative targets. It is necessary to research a new pose estimation method for non-cooperative targets based on 3D point cloud. The paper aims to discuss these issues.

In this paper, a method based on the inherent characteristics of a spacecraft is proposed for estimating the pose (position and attitude) of the spatial non-cooperative target. First, we need to preprocess the obtained point cloud to reduce noise and improve the quality of data. Second, according to the features of the satellite, a recognition system used for non-cooperative measurement is designed. The components which are common in the configuration of satellite are chosen as the recognized object. Finally, based on the identified object, the ICP algorithm is used to calculate the pose between two frames of point cloud in different times to finish pose estimation.

The new method enhances the matching speed and improves the accuracy of pose estimation compared with traditional methods by reducing the number of matching points. The recognition of components on non-cooperative spacecraft directly contributes to the space docking, on-orbit capture and relative navigation.

Limited to the measurement distance of the laser radar, this paper considers the pose estimation for non-cooperative spacecraft in the close range.

The pose estimation method for non-cooperative spacecraft in this paper is mainly applied to close proximity space operations such as final rendezvous phase of spacecraft or ultra-close approaching phase of target capture. The system can recognize components needed to be capture and provide the relative pose of non-cooperative spacecraft. The method in this paper is more robust compared with the traditional single component recognition method and overall matching method when scanning of laser radar is not complete or the components are blocked.

This paper introduces a new pose estimation method for non-cooperative spacecraft based on point cloud. The experimental results show that the proposed method can effectively identify the features of non-cooperative targets and track their position and attitude. The method is robust to the noise and greatly improves the speed of pose estimation while guarantee the accuracy.

The purpose of this study is to introduce a novel method for the measurement of electromagnetic material parameters.

The main idea behind the approach is the fact that for slabs with elongated shapes, the intensity of the backscattered field and the electromagnetic resonance frequency corresponding to the length of the sample are dependent on the conductivity of the sample’s material.

It is shown that for a known scattered field and resonance frequency, it is possible to formulate an inverse problem as to the calculation of the conductivity of the sample’s material at the considered frequencies. To investigate the applicability of the method, demonstrative experiments are performed during which the micro-Doppler effect is used to increase the measurement accuracy. The idea is extended to the case of anisotropic samples, with slight modifications proposed to the experimental setup in the case of significant anisotropy in the investigated material.

The measurement method may prove useful for the investigation of the high-frequency conductive properties of certain materials of interest.

To the best of the authors’ knowledge, this is the first time the use of the micro-Doppler effect is proposed for the purpose of the measurement of material parameters.

In the background of the post-financial crisis era and the transition of China’s economic development, the frequent occurrence of workplace deviant behavior in the economic field, such as stealing and bribery, caused a huge impact on the enterprise. In recent years, the deviant behavior of employees has been increased noticeably. The purpose of this study is to explore the influence of paternalistic leadership on employee deviant behavior in workplace. To have a deep understanding of the relationship between paternalistic leadership and employee deviant behavior, the author’s design rule-oriented ethical climate and self-interest-oriented ethical climate as two mediators in this research model.

Based on social learning theory and stressor-emotion model, this study conducts an investigation of influence mechanism between paternalistic leadership and workplace deviant behavior. Time-lagged data was collected from 226 employees from six cities in China. To test the hypothesis that the authors developed in this paper, the authors use empirical models from the existing literature about paternalistic leadership on employee deviant behavior. They establish multiple linear regressions to test the hypotheses.

This study reveals the direct effect of authoritarian leadership on employee deviant behavior and the moderated roles of benevolent leadership and moral leadership, also analysis the mediated mechanism of self-interest-oriented ethical climate and rule-oriented ethical climate. The results show that the higher the degree of authority leaders show in the organization, the easier to stimulate workplace deviance of employee, self-interest-oriented ethical climate and rule-oriented ethical climate play mediated role between authoritarian leadership and workplace deviant behavior. The interaction of benevolent leadership and moral leadership with authoritarian leadership can weaken the self-interest-oriented ethical climate but has nothing to do with rule-oriented ethical climate.

This study has three main contributions to the previous literature. First, this study explores the relationship between authoritarian leadership and employee workplace deviance, which could enrich the research on these negative behaviors in the Chinese context. Second, this study unpacks the “black box” in which authoritarian leadership influences employee workplace deviant behavior. Third, this study further examines the impacts of different combinations of the three factors of paternalistic leadership.

Drawing on theories of social information processing and social identity, the authors explore how abusive supervision climate affects team creativity in a Chinese cultural context. The authors propose that this relation will be mediated by collective efficacy and group identification and moderated by task interdependence

The study conducted a confirmatory factor analysis and hierarchical regression to analyze the paired data from 67 research and development (R&D) teams involving 378 employees and employers in a Chinese cultural context.

Results demonstrate that abusive supervision climate was negatively related to team creativity, fully mediated by collective efficacy and group identification in a Chinese cultural context. In addition, task interdependence strengthened the positive relation between collective efficacy and team creativity, as well the positive relation between group identification and team creativity.

Although research has explored how abusive supervision climate influences individual creativity, few studies have investigated the relation between abusive supervision climate and team creativity in a Chinese cultural context. This study is one of the first to explore how abusive supervision climate affects team creativity in a Chinese cultural context and examine the moderating role of task interdependence in the relation between abusive supervision climate and team creativity.

Celebrity endorsement advertising receives increased attention in the relevant literature. Approaching from the abnormal stock market return perspective, the purpose of this paper is to investigate the potential risks and expected profit associated with celebrity endorsement. The factors that are included in this investigation are the attributes relating to celebrities and the endorsed firms.

Data were collected from over 300 firms that use celebrity endorsements and are listed in two of the biggest stock exchanges in China. The study uses the event study method to analyze the proposed relationships.

Some of the findings in the current study are consistent with or contrast to those in previous research. Specifically, this study finds that the celebrities’ demographics such as age and gender have little influence on financial return of the endorsed firm. However, investors respond rather negatively toward using actor celebrities to endorse a product or a brand, especially for high-tech products. The match-up endorsement has a positive effect on the firm’s abnormal return.

The current study has implications for the relevant literature and practitioners. Very few studies have used stock market return to measure celebrity endorsement effectiveness. This study provides insights into the influence of various factors associating with celebrities and the endorsed firm, extending the celebrity endorsement research into a broader domain. In particular, this study has practical implications for firms that have used or intend to use actor celebrity endorsement.

This study is the first to use event study method to comprehensively analyze influence of attributes relating to both the celebrities and the endorsed firms in China on stock market return.

With the rapid development of social media, many organizations have begun to attach importance to social media platforms. This research studies the management and the use of social media in academic music libraries, taking the Center for Chinese Music Studies of the Chinese University of Hong Kong (CCMS) as a case study.

We conducted a sentiment analysis of posts on Facebook’s public page to analyze the reaction to the posts with some exploratory analysis, including the communication trend and relevant factors that affect user interaction.

Our results show that the Facebook channel for the library has a good publicity effect and active interaction, but the number of posts and interactions has a downward trend. Therefore, the library needs to pay more attention to the management of the Facebook channel and take adequate measures to improve the quality of posts to increase interaction.

Few studies have analyzed existing data directly collected from social media by programming based on sentiment analysis and natural language processing technology to explore potential methods to promote music libraries, especially in East Asia, and about traditional music.

The purpose of this paper is to construct a novel delay grey incidence analysis model to analyze drivers and obstacles of university R&D performance.

With respect to the fact that university R&D activities typically experience two stages of knowledge creation and technology transfer, and different drivers and obstacles come into play to affect the conversion of R&D investment to outcomes at each stage, based on the thought of grey incidence analysis and the specific characteristics of science and technology (sci-tech) development, a novel delay grey incidence analysis model is proposed in this paper, and then according to the yearbook statistical data, Chinese university R&D activities are investigated and the drivers and obstacles of university R&D performance are analyzed.

The results show that the R&D full-time staff and R&D funds of basic research are the key drivers of influencing factors, and the sci-tech innovation talents in universities’ R&D institutions and experiment development funds are the restraining factors to improve R&D performance in the stage of knowledge creation; the expenses of R&D achievement application and technology service and the full-time staff of achievement application and technology service are the key drivers and obstacles of influencing the aggregate amount of patent sale respectively.

This research helps policy makers to reflect on their university R&D policies and understand how to enhance the technology transfer rate in China.

The paper succeeds in identifying key drivers and obstacles of affecting university R&D performance in China by examining the input and output incidence at both the knowledge creation and technology transfer stages.