Kai Xiong, Chunling Wei and Peng Zhou
This paper aims to improve the performance of the autonomous optical navigation using relativistic perturbation of starlight, which is a promising technique for future space…
Abstract
Purpose
This paper aims to improve the performance of the autonomous optical navigation using relativistic perturbation of starlight, which is a promising technique for future space missions. Through measuring the change in inter-star angle due to the stellar aberration and the gravitational deflection of light with space-based optical instruments, the position and velocity vectors of the spacecraft can be estimated iteratively.
Design/methodology/approach
To enhance the navigation performance, an integrated optical navigation (ION) method based on the fusion of both the inter-star angle and the inter-satellite line-of-sight measurements is presented. A Q-learning extended Kalman filter (QLEKF) is designed to optimize the state estimate.
Findings
Simulations illustrate that the integrated optical navigation outperforms the existing method using only inter-star angle measurement. Moreover, the QLEKF is superior to the traditional extended Kalman filter in navigation accuracy.
Originality/value
A novel ION method is presented, and an effective QLEKF algorithm is designed for information fusion.
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Keywords
This paper aims to present a multiple-model adaptive estimator (MMAE) to calibrate the star sensor low frequency error (LFE). The star sensor LFE, which is caused primarily by the…
Abstract
Purpose
This paper aims to present a multiple-model adaptive estimator (MMAE) to calibrate the star sensor low frequency error (LFE). The star sensor LFE, which is caused primarily by the periodic thermal distortion, has a great impact on spacecraft attitude determination accuracy.
Design/methodology/approach
The unfavorable effect of the LFE can be partly eliminated by using the calibration algorithm based on the augmented Kalman filter (AKF). However, the AKF may be worse than the traditional Kalman filter (KF) in the absence of the LFE. To cope with this problem, the MMAE is applied first time for combining the AKF and the KF in the spacecraft attitude determination system, such that satisfactory performance can be achieved in different operating scenarios.
Findings
The convergence of the presented MMAE is demonstrated through a formal derivation. A novel method is proposed to tune the MMAE design parameter, such that the convergence rate of the estimator is increased. It is shown via numerical studies that the presented algorithm outperforms the AKF and the KF.
Practical implications
The calibration algorithm is applicable for spacecraft attitude determination.
Originality/value
An effective star sensor LFE calibration algorithm based on the MMAE is developed. In addition, a novel method is proposed to increase convergence rate of the estimator.
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Song Hua, Huiyin Huang, Fangfang Yin and Chunling Wei
This paper aims to propose a constant-gain Kalman Filter algorithm based on the projection method and constant dimension projection, which ensures that the dimension of the…
Abstract
Purpose
This paper aims to propose a constant-gain Kalman Filter algorithm based on the projection method and constant dimension projection, which ensures that the dimension of the observation matrix obtained is maintained when there is a satellite with multiple sensors.
Design/methodology/approach
First, a time-invariant observation matrix is determined with the projection method, which does not require the Jacobi matrix to be calculated. Second, the constant-gain matrix replaces the EKF (extended Kalman filter) gain matrix, which requires online computation, considerably improving the stability and real-time properties of the algorithm.
Findings
The simulation results indicate that compared to the EKF algorithm, the constant-gain Kalman filter algorithm has a considerably lower computational burden and improved real-time properties and stability without a significant loss of accuracy. The algorithm based on the constant dimension projection has better real-time properties, simpler computations and greater fault tolerance than the conventional EKF algorithm when handling an attitude determination system with three or more star trackers.
Originality/value
In satellite attitude determination systems, the constant-gain Kalman Filter algorithm based on the projection method reduces the large computational burden and improve the real-time properties of the EKF algorithm.
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Kai Xiong, Chunling Wei and Liangdong Liu
The purpose of this paper is to present a variable structure multiple model adaptive estimator (VSMMAE) for liaison navigation system. Liaison navigation is an autonomous…
Abstract
Purpose
The purpose of this paper is to present a variable structure multiple model adaptive estimator (VSMMAE) for liaison navigation system. Liaison navigation is an autonomous navigation method where inter-satellite range measurements are used to estimate the orbits of all participating spacecrafts simultaneously.
Design/methodology/approach
To overcome the problem caused by an inaccurate initial state, a navigation algorithm is designed based on the multiple model adaptive estimation technique. The multiple models are constructed by different initial error covariance matrices. To reduce the computational cost, the likely-model set (LMS) algorithm is adopted to eliminate the unlikely models.
Findings
It is specified that the performance of the liaison navigation based on the extended Kalman filter (EKF) is sensitive to the initial error. Simulation results show that the VSMMAE outperforms the EKF in the presence of a large initial error.
Practical implications
The presented algorithm is applicable to spacecraft autonomous navigation.
Originality/value
A novel navigation algorithm based on the VSMMAE is developed. It is an effective method for the liaison navigation system.
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Haizhong Wang, Yujie Wei and Chunling Yu
There is a growing interest in brand formation and brand valuation among global firms today, but global marketers typically ignore one of the key factors of brand building �…
Abstract
Purpose
There is a growing interest in brand formation and brand valuation among global firms today, but global marketers typically ignore one of the key factors of brand building – corporation ability association (CAA). This paper aims to explore the structural relationship between CAA and consumer‐based brand equity variables and its product‐market outcomes.
Design/methodology/approach
Utilizing Aaker and Keller's theoretical framework of brand equity, this paper develops a brand equity model combining customer‐based brand equity with product‐market outcome approaches. A set of scales are developed and tested on a national sample of Chinese consumers.
Findings
The data provide support for ten of the 12 hypotheses. The results indicate that CAA is an important factor in building and preserving brand equity. CAA and brand awareness have impact on quality perception, which has positive impact on brand resonance, brand extensibility, and price flexibility. Brand resonance has positive influence on brand extensibility and the intention to repurchase.
Practical implications
For global marketers operating in China, brand equity is a cultural market‐based asset and global companies must focus on building corporation ability association in China in order to enjoy the substantial competitive and economic advantages provided by brand equity. Theoretically, the proposed brand equity model is an extension of the model proposed by Keller.
Originality/value
For the first time, CAA is integrated into fhe brand equity model. This may provide a theoretical base for further research in the endorsement role of company ability in brand equity building.
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Dara G. Schniederjans, Stephen A. Atlas and Christopher M. Starkey
As organizations increasingly engage with consumers over mobile devices, there is a growing need to understand how consumers react to impression management over platforms with…
Abstract
Purpose
As organizations increasingly engage with consumers over mobile devices, there is a growing need to understand how consumers react to impression management over platforms with limited textual content. The purpose of this paper is to empirically assess how different impression management tactics can be used in mobile media to enhance consumer perception-attitude-intentions toward a corporate brand.
Design/methodology/approach
We surveyed 670 consumers and estimate structural equation models and repeated-measures ANOVAs to determine how short passages employing alternate impression management tactics influence consumers’ perceptions, attitudes and purchase intentions.
Findings
Results reveal that each impressions management tactic (i.e. ingratiation, intimidation, organizational promotion, supplication and exemplification) influences consumer perceptions, attitudes and intentions. The authors compare differences in how the impressions management tactics influence each stage of the perception-attitude-intentions model and find evidence that initial differences in perceptions favoring ingratiation and exemplification appeals become magnified for purchase intentions.
Research limitations/implications
Recent calls for research focus on an understanding of how consumers process information on reduced-content platforms of small-screened mobile devices. These results provide empirical evidence of the use of impression management and the difference between five impression management tactics on enhancing consumer perception-attitude-intentions model.
Practical implications
The results of this study will provide marketers with insights to optimize communications and corporate brands with consumers over mobile media.
Originality/value
This paper adds to the nascent yet vital literature on mobile marketing by focusing on how impression management tactics influence perceptions, attitudes and intentions through the short message characteristic of mobile platforms. The authors develop a framework for how corporate brand management can strategically use impressions management tactics in this novel domain.
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The purpose of this paper is to explore the reasons for the high‐frequency switches of lead underwriters by Chinese listed companies in their seasoned equity offerings. It…
Abstract
Purpose
The purpose of this paper is to explore the reasons for the high‐frequency switches of lead underwriters by Chinese listed companies in their seasoned equity offerings. It contributes to the literature by filling the gap and providing evidence that institutional and non‐market factors could affect listed companies' decisions to switch their lead underwriters in the Chinese capital market.
Design/methodology/approach
This paper employs a numerical measure of listed companies' loyalty to evaluate their frequency of switching lead underwriters, and employs a Logit model and an OLS model to identify the key determinants of switching lead underwriters by Chinese listed companies.
Findings
It is observed that the frequency of switching lead underwriters is very high among Chinese listed companies for their seasoned offerings. It is also found that underwriters' deficient reputation and the lack of industrial experience, together with the depreciation of relationship‐specific assets, could have important impacts on lead underwriters being frequently switched in China. Besides, the frequent switches of lead underwriters could also be attributable to the non‐market supervision and regulatory influences by Chinese authorities over the security underwriting market.
Originality/value
This paper could help further the understanding of the factors that could explain the listed companies' frequent switches of their lead underwriters for their seasoned offerings in China. In addition, this paper has policy implications on how to improve the listed companies' loyalty for regulators in China. These implications could help improve the regulatory environment and promote the overall performance of the Chinese security underwriting market.
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Chunjiang Yang, Nan Guo, Yuting Wang and Chunling Li
Mentoring was considered as an efficient way to facilitate staff attachment with hotels. Such a strong attachment has been demonstrated to reduce employees’ intention to quit…
Abstract
Purpose
Mentoring was considered as an efficient way to facilitate staff attachment with hotels. Such a strong attachment has been demonstrated to reduce employees’ intention to quit. This study aims to investigate the mediating roles of organizational and occupational embeddedness in the relationships between mentoring functions and turnover intention.
Design/methodology/approach
The responses were collected from a sample of 354 employees in four hotels group across three Chinese provinces. A structural equation model (SEM) was applied to test the model and mediating roles of organizational and occupational embeddedness.
Findings
The results of SEM suggest that both organizational and occupational embeddedness mediated the relationships between mentoring functions (career and psychosocial support) and turnover intention. Specifically, employees who are able to receive successful mentoring can easily embed in their organization and occupation. Thus, these employees are reluctant to leave.
Research limitations/implications
Although this study reveals the important role of mediation, it has several limitations. First, the data drawn from Hebei, Beijing and Zhejiang provinces may lack geography representativeness. Second, this paper neglects potential moderating role of certain personal or context factors. Third, the time lag between the three data collections are not the same.
Practical implications
Managers should retain proper employees by introducing mentoring programs. Furthermore, to increase organizational and occupational embeddedness, managers should also consider the person-organization/occupation attachments of this industry.
Originality/value
This study tests organizational and occupational embeddedness simultaneously as mediators between mentoring and turnover intention through data obtained from the Chinese hotels.
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Marzena Frankowska and Katarzyna Cheba
The purpose of this paper is to fill the research and cognitive gap by comparative analyzing of the cluster supply chain (CSC) and supply chains not belonging to the clusters to…
Abstract
Purpose
The purpose of this paper is to fill the research and cognitive gap by comparative analyzing of the cluster supply chain (CSC) and supply chains not belonging to the clusters to examine the relational embeddedness as the differentiator of supply chains operating in the clusters.
Design/methodology/approach
The conceptual model was tested with data collected from 475 industrial companies cooperating with their partners within supply chains, including 135 CSC. To identify the livraisons between different indicators, the correspondence analysis was applied.
Findings
The division of enterprises participating in this study into groups allows for the determination of relatively clear boundaries between enterprises belonging to the cluster and those that do not declare such affiliation. The obtained results confirmed that the relational embeddedness is the differentiator of the CSC collaboration.
Research limitations/implications
The main limitations are referred to as the static character of the data.
Practical implications
The paper contains implications for cluster facilitators, as well as for cluster policy decision makers, to better design support for cluster organizations.
Originality/value
This research is a contribution to the literature on inter-organizational structures, such as clusters and supply chains, and in particular, contributes to the creation of the scientific ground of SCS theory. The research allowed to better understand the nature of collaboration taking into consideration the fact of the relational embeddedness of the companies operating within supply chains located in clusters. It proves the existence of a new type of inter-organizational form that is CSC.
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Hui-Wen Vivian Tang and Tzu-chin Rojoice Chou
The purpose of this paper is to evaluate the forecasting performance of grey prediction models on educational attainment vis-à-vis that of exponential smoothing combined with…
Abstract
Purpose
The purpose of this paper is to evaluate the forecasting performance of grey prediction models on educational attainment vis-à-vis that of exponential smoothing combined with multiple linear regression employed by the National Center for Education Statistics (NCES).
Design/methodology/approach
An out-of-sample forecasting experiment was carried out to compare the forecasting performances on educational attainments among GM(1,1), GM(1,1) rolling, FGM(1,1) derived from the grey system theory and exponential smoothing prediction combined with multivariate regression. The predictive power of each model was measured based on MAD, MAPE, RMSE and simple F-test of equal variance.
Findings
The forecasting efficiency evaluated by MAD, MAPE, RMSE and simple F-test of equal variance revealed that the GM(1,1) rolling model displays promise for use in forecasting educational attainment.
Research limitations/implications
Since the possible inadequacy of MAD, MAPE, RMSE and F-type test of equal variance was documented in the literature, further large-scale forecasting comparison studies may be done to test the prediction powers of grey prediction and its competing out-of-sample forecasts by other alternative measures of accuracy.
Practical implications
The findings of this study would be useful for NCES and professional forecasters who are expected to provide government authorities and education policy makers with accurate information for planning future policy directions and optimizing decision-making.
Originality/value
As a continuing effort to evaluate the forecasting efficiency of grey prediction models, the present study provided accumulated evidence for the predictive power of grey prediction on short-term forecasts of educational statistics.