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The purpose of this paper is to propose a seamless autonomous navigation method based on the motion constraint of the mobile robot, which is able to meet the practical need of maintaining the navigation accuracy during global positioning system (GPS) outages.

The seamless method uses the motion constraint of the mobile robot to establish the filter model of the system, in which the virtual observation about the speed is used to overcome the shortage of the navigation accuracy during GPS outages. The corresponding motion constraint model of the mobile robot is established. The proposed seamless navigation scheme includes two parts: the micro inertial navigation system (MINS)/GPS-integrated filter model and the motion constraint filter model. When the satellite signals are good, the system works on the MINS/GPS-integrated mode. If some obstacles block the GPS signals, the motion constraint measurement equation will be effective so as to improve the navigation accuracy of the mobile robot.

Three different vehicle tests of the mobile robot show that the seamless navigation method can overcome the shortage of the navigation accuracy during GPS outages, so as to improve the navigation performance in practical applications.

A seamless navigation system based on the motion constraint of the mobile robot is proposed to overcome the shortage of the navigation accuracy during GPS outages, thus improving the adaptability of the robot navigation.

The development and evolution of stakeholder collaborative innovation in megaprojects is impacted by various influencing factors. The effect of influencing factors on collaborative innovation performance (CIP) in megaprojects is not a simplistic linear relationship but an iterative and non-linear relationship that requires a dynamic perspective to analyze. Therefore, this paper adopts the system dynamic (SD) approach to investigate the dynamic and interactive relationships between the CIP and the influencing factors.

The study first develops a research framework with the system boundary of “CIP system – organizational collaboration subsystem – knowledge collaboration subsystem – strategic collaboration subsystem”. Then, the causal relationship model, the stock-flow model, and the mathematical equations were determined based on the literature review and the expert interviews. Finally, five performance improvement scenarios were designed according to the practice context of CIP in megaprojects, and simulations were performed using the Vensim PLE software to investigate the CIP from a dynamic perspective.

The findings reveal that the effect of different influencing factors on CIP grows non-linearly, with the cumulative effect becoming more pronounced as time advances. The incentive mechanism has the most significant effect, and the combined effect of multiple influencing factors has a highly significant facilitating effect on improving CIP. Strategic collaboration, organizational collaboration and knowledge collaboration are mutually conditional and reinforcing with each other, which ultimately promotes the improvement of CIP.

This study uncovers the inherent pattern and the interactive dynamic mechanism of factors for improving CIP in the context of megaprojects. It enriches the theoretical research in the area of collaborative innovation in megaprojects and provides practical management strategies for improving CIP.

Predicting a user’s click-through rate on an advertisement or item often uses deep learning methods to mine hidden information in data features, which can provide users with more accurate personalized recommendations. However, existing works usually ignore the problem that the drift of user interests may lead to the generation of new features when they compute feature interactions. Based on this, this paper aims to design a model to address this issue.

First, the authors use graph neural networks to model users’ interest relationships, using the existing user features as the node features of the graph neural networks. Second, through the squeeze-and-excitation network mechanism, the user features and item features are subjected to squeeze operation and excitation operation, respectively, and the importance of the features is adaptively adjusted by learning the channel weights of the features. Finally, the feature space is divided into multiple subspaces to allocate features to different models, which can improve the performance of the model.

The authors conduct experiments on two real-world data sets, and the results show that the model can effectively improve the prediction accuracy of advertisement or item click events.

In the study, the authors propose graph network and feature squeeze-and-excitation model for click-through rate prediction, which is used to dynamically learn the importance of features. The results indicate the effectiveness of the model.

Managing knowledge is relevant for the innovativeness of an organization. The innovation of the organization currently aligns with the environment and applies green innovation concepts. Knowledge management (KM) is a key to fostering green innovation and to saving the environment from unnecessary pollution. In line with this, this study aims to evaluate the relationship between KM and green innovation in the literature from 2000 to 2023 synthesize and suggest future directions.

This study used the preferred reporting items for systematic review and meta-analysis technique to identify eligible articles. The papers were identified from the Web of Science core collection and ScienceDirect databases. The results were presented using tables, graphs and the co-occurrence of citations was analyzed using VOSviewer software.

From the review, the authors were assured that there is a strong relationship between KM practices and green innovation in different organizations. Some papers were supported by different theories. From the total of 48 papers, 16 have not mentioned the theories applied in their studies. The geographical distribution of the papers is asymmetrical. Asian and European scholars published more papers. The papers distribution across publishers also varies. For instance, Elsevier and Emerald Group Publishing Ltd. published 29 papers and the remaining papers were published in BMC, Springer, Frontiers Media Sa, IEEE-Inst Electrical Electronics Engineers Inc., MDPI, Routledge Journals and Taylor & Francis Ltd. Major themes were identified and future research directions were forwarded.

The limitation of this review is the authors generated the papers from two databases (WoS and ScienceDirect). This paper does not consider other databases (Scopus, dimensions, etc.) papers. This can be considered as a limitation of this review.

The review is original by integrating PARISMA and bibliometric analysis method (VOS Viewer). The paper tried to explore the role of KM on green innovation.

Despite the acknowledgment of the significant role leaders play in knowledge management, there has been limited focus on the dynamic relationship between one particular leader’s behavior and knowledge sharing of employees. This study aims to investigate the impact of leader generosity on employee knowledge sharing.

Drawing upon the generalized reciprocity theory, we develop a process model that examines the impact of leader generosity on knowledge sharing, and empirically tests the resulting mechanism. Based on event-contingent ESM that collected 1147 episodic data points, the data are analyzed by Mplus 8.30 and R software.

The findings indicate that employee gratitude and prosocial motivation respectively play a mediating role in the relationship between leader generosity and knowledge sharing. Additionally, leader generosity has an indirect impact on knowledge sharing via employee gratitude and prosocial motivation. Furthermore, relational self positively moderates the relationship between leader generosity and employee gratitude, while also moderates the chain mediation effect between leader generosity and knowledge sharing.

By exploring the important influence of leaders in implementing knowledge management practices, the authors demonstrate that a specific leader behavior (i.e. leader generosity) shapes the positive emotion and reciprocal motivation of employees and its subsequent impact on knowledge sharing. This paper complements the focus on knowledge sharing in the daily behavior literature of leaders, suggesting that leader generosity matters for employee knowledge sharing.

The purpose of this paper is to reveal the economic impact of policy reversals related to market liberalization reforms in China.

To perform the analysis, the authors hand-collect 59 financial market liberalization policy reversals from 1999 to 2017. These reversals are related to the liberalization of the stock market, bond market, derivatives market, forex market, lending market, and real estate market etc. The authors employ a stylized equilibrium interest rate model from Li et al. (2013) to deduce the impact of policy reversals on economic growth and the associated volatility after the announcement of each policy reversal.

First, the authors discover that about half of reversals are related to some tradeoff between the economic growth and the volatility associated with growth. Second, the authors also find that about a quarter of the reversals are detrimental to both the growth and the stability. These reversals, if known to policymakers, should be entirely avoided or corrected. Third, using a simple diagnostic test, the authors can identify detrimental reversals at the intra-day frequency by computing the change of the term spread and the volatility before and after the reversals.

The findings are useful for identifying effective policymaking in developing countries where mature democratic and rigorous policymaking processes are often lacking and formulating economic policies is challenging. The findings suggest that policy reversals serve China well by improving the quality of the policy made without posing destructive consequences to the existing economic infrastructure. This empirical evidence is important for a better understanding of the benefits of policy reversals on economic growth.

The empirical procedure provides a timely and objective evaluation of policy shifts, allowing for the general public to discern the rationale behind the policy decisions. Consequently, stakeholders’ trust and confidence in policymakers is enhanced so that the probability of the successful implementation of structural reforms may increase in these developing countries.

First, the results reveal some successful examples of Chinese policymaking in the path of liberalizing financial market. The authors find that the Chinese liberalization policy flip-flops have resulted in a more balanced growth on some occasions with reduced growth rate and volatility. Second, the proposed methodology provides an objective evaluation of policy shifts, allowing for the public to infer the general direction of the impact generated by policy shifts. Subsequently, stakeholders’ trust and confidence in policymakers can be enhanced and/or restored if the process of finding a successful path of structural reforms is unambiguous. Finally, the interest rate model also provides a timely method to evaluate the impact of policy shifts at an intra-day frequency, whereas most macroeconomic indicators are available at longer frequencies such as monthly or quarterly. The timeliness in understanding the economic consequences of policy reversals can be critical to prevent the destructive consequences of bad ones.

The purpose of this paper is to investigate the impact of various decision-making approaches and government subsidies on supply chain performance, aiming to enhance the profits of disposal firms and retailers as well as to improve social welfare.

In this paper, a two-echelon biomass supply chain composed of a disposal firm and a retailer is developed. Firstly, considering the effects of government subsidies, we analyze biofuels prices, corporate social responsibility levels, social welfare and supply chain profitability under centralized and decentralized decision-making scenarios, respectively. Furthermore, we assess how subsidies influence pricing, market participation, profitability and social welfare. Secondly, we propose a revenue sharing–cost sharing contract to enhance the profits of the disposal firm and retailer. Thirdly, we extend the supply chain to a disposal firm and two retailers and explore the impact of competition intensity on corporate decision-making behavior. Finally, numerical analysis is conducted by taking one biomass energy firm as an example to support the results.

Our research finds that (1) Equilibrium strategies under the centralized decision-making scenario are greater than those under the decentralized decision-making scenario. Centralized decision-making can increase market demand and consumer surplus. (2) Government subsidies can promote corporate social responsibility levels, despite causing a slight increase in retail price for biofuels. When market competition intensifies, companies usually reduce their investment in CSR, and this trend is particularly pronounced in the absence of subsidies. (3) In both the decentralized and the centralized decision-making scenarios, increasing conversion rates and the CSR coefficient can significantly increase the overall profitability and social welfare.

A three-echelon biomass supply chain involving collection station, disposal firm and retailer can be studied in the future.

By examining the effects of subsidies on CSR engagement and market outcomes, our study contributes valuable insights into policy design for promoting sustainable practices in biomass industries.

We review the state of the literature concerning work–family conflict in the military, focusing on service members’ parenting roles and overall family and child well-being. This includes recognition that for many women service members, parenting considerations often arise long before a child is born, thereby further complicating work–family conflict considerations in regard to gender-specific conflict factors such as pregnancy, childbirth, postpartum, and breastfeeding. Subsequently, we consider more gender-invariant conflict factors, such as the nature of the work itself as causing conflict for the service member as parent (e.g., nontraditional hours, long separations, and child care challenges) as well as for the child (e.g., irregular contact with parent, fear for parent’s safety, and frequent relocations), and the ramifications of such conflict on service member and child well-being. Finally, we review formalized support resources that are in place to mitigate negative effects of such conflict, and make recommendations to facilitate progress in research and practice moving forward.

This study empirically investigates the impacts of technological innovation and operational efficiency on environmental performance and the moderating effects of environmental orientation.

We develop a conceptual framework based on the Porter Hypothesis. We collect a sample of 850 listed firms in China between 2010 and 2019. The fixed effect model was used to analyse the data.

The empirical findings reveal that technological innovation indirectly enhances environmental performance through operational efficiency and partially mediates this impact. We also find that environmental orientation strengthens the positive impacts of technological innovation and operational efficiency on environmental performance.

This study contributes to the literature by revealing that technological innovation is positively associated with operational efficiency and environmental performance, which suggests that technological innovation can simultaneously enhance business and environmental performance. Hence, this study provides empirical support for the Porter Hypothesis. The results also extend the Porter Hypothesis by revealing how technological innovation affects environmental performance and under what conditions technological innovation has a greater impact on environmental performance.

This paper aims to investigate the impacts of green bond issuance on the environment while taking into account the moderating role of issuing countries’ institutional quality.

The analysis is based on a longitudinal data set covering 171 countries and territories during 2007–2018. The authors rigorously account for endogeneity issues using two-stage least squares estimation and a set of instrumental variables for green bond issuance volume.

The overall results confirm the positive environmental impacts of green bonds in reducing carbon dioxide and greenhouse gas emissions, enhancing renewable energy consumption rate and accelerating the progress towards sustainable development goals (SDGs). However, these effects are contingent upon the levels of institutional development of the issuing countries in a way that green bond issuance only benefits the environment when the institutional quality has reached a minimum level.

The results provide important policy implications for countries in their efforts to prevent environmental degradation and achieve SDGs.

This paper contributes to the existing literature by providing a macro-level evaluation of the environmental impact of green bonds, hence, enabling policy implications to be drawn for countries to achieve their SDGs. The analysis is more comprehensive using a wide range of indicators for environmental performance. To the best of the authors’ knowledge, this paper is also one of the first attempts to examine the moderating effect of institutions on the environmental impact of green bonds.