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This paper aims to examine the optimal promotion strategy of an e-retailer, who may advertise, or launch rebates initiative to encourage consumers' disseminating electronic word-of-mouth (eWOM) messages, with an aim to boost product sales.

This paper analyzes the decisions of the e-retailer in a two-period model, using utility function approach and backward induction method, and obtains the optimal solutions in four promotion strategies.

The study finds that rebate scheme greatly impacts the timing of advertising, and neither lower nor higher consumers' eWOM effort invariably benefits the retailer, rather, a medium level is the best choice for the retailer. When eWOM impact power is at a relatively high level, it can supplement advertising effect to attract more consumers' purchase. Otherwise, eWOM may counteract the role of advertising.

Different from the extant literature focusing on advertising or eWOM without rebates, the paper studies the issue of advertising and eWOM with rebates in two- period model which seldom addresses before the authors examine the optimal timing of advertising and eWOM with/without rebates in four promotion strategies i.e. the A-NE model the NE-A model the A-ER model and the ER-A model.

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.

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.

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.

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.

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.

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.

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.

The presented algorithm is applicable to spacecraft autonomous navigation.

A novel navigation algorithm based on the VSMMAE is developed. It is an effective method for the liaison navigation system.

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.

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.

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.

A novel ION method is presented, and an effective QLEKF algorithm is designed for information fusion.

This paper aims to design a composite, aiming to improve the static puncture resistance through polyurethane impregnated treatment with five concentration gradients.

The relationship between polyurethane concentration, the number of polyester nonwovens, component fiber type (filament or staple) and the static puncture resistance is explored respectively and elaborately.

This study provides a new perspective to design flexible composites with better static puncture resistance, feasible preparation process as well as low cost.

The results show that the static puncture resistance of nonwovens impregnated by polyurethane is improved obviously. Meanwhile the puncture strength-T of nonwovens increases first and then decreases with the increase of the number of layers, and the maximum puncture strength-T is found at 20 layers. Moreover, the composite with filaments illustrates better mechanical resistance.

The purpose of this paper is to demonstrate that there are three major blood donor segments in China, namely benefit‐oriented donors, altruistic donors and health salience donors, with the use of factor‐cluster segmentation approach. It also investigates the blood donation attitudes, group characteristics, and preference for information acquisition of the identified donor segments.

A factor‐cluster segmentation approach was used in this study. A questionnaire survey on Chinese respondents who had just completed a blood donation process was conducted in China and 7‐point Likert‐type questions were used to measure the respondents’ attitude toward blood donation, their motivation to donate blood, lifestyles, demographics and information acquisition. K‐means non‐hierarchical clustering method was used to segment groups of blood donors. ANOVAs were conducted to assess the differences regarding the blood donation factors across the cluster segments.

Results demonstrate that there are three blood donor segments as predicted. Benefit‐oriented donors are found to be the largest cluster (42.6 per cent), followed by altruistic donors (29.6 per cent) and health salience donors (27.8 per cent). The three clusters of donors show some extent of differences in attitudes toward blood donation, lifestyles and preference for information acquisition.

Through a better understanding of the donor segments, a more effective marketing communication strategy can be formulated. This can promote more blood donation by the first‐time and repeat blood donors and may save many more lives in a society.

The major advertising appeal for blood donation is altruistic in nature, particularly in Western countries. However, in other emerging countries such as China, some other appeals may be even more effective. Benefit appeal or health fitness appeal may be a better option in marketing communication strategy.

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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

Based on the theoretical background of stakeholder capitalism, the purpose of this paper is to contribute to the scientific debate on the topic of public–private partnerships (PPPs), considering in particular how this governance structure relates to the pursuit of sustainable development. Specifically, this objective will be pursued with a focus on stakeholder relations and governance aspects, to highlight enablers and barriers in change for sustainability.

The systematic literature review is applied starting with the use of keywords in Web of Science, which leads to the extrapolation of 629 articles on the topic of “PPP and sustainability”. Subsequently, through various skimming steps, 75 papers are sampled. A mixed (quantitative-qualitative) approach is then followed: a co-word semantic network to identify the pattern of discourse and a more in-depth and explanatory analysis of the papers. These quantitative and qualitative tools synergistically work together to evidence the main aspects related to the aim of the paper.

With reference to the governance structure and stakeholders of PPPs, the analyses highlight the shift towards a triadic type of relational governance that considers stakeholders (especially the community) in addition to public–private partners. This can improve the partnership's performance (particularly in sustainable development) and social legitimacy. With reference to the role of PPPs in the implementation of sustainable development, they have positive potential in terms of implementing sustainability and raising stakeholder awareness of it. Nevertheless, PPPs may entail risks to the implementation of sustainability. The findings lead to some concluding remarks on future research opportunities.

The research leads to some managerial implications, such as the need to follow a competitive collaboration approach among stakeholders, to develop relational governance skills and related managerial tools and to incorporate sustainability aspects starting from the design of PPPs.

The originality aspect of this research is the consideration of a PPP by relating it to the pursuit of sustainability. Such an inter-organizational structure could be suitable to deal with the complexity inherent in the implementation of sustainability and is peculiar in terms of governance and stakeholder relations, considering that it is characterised by the presence of several partners of different nature (public and private).