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The purpose of this paper is to present a method to obtain the inertia parameter of a captured unknown space target.

An inertia parameter identification method is proposed in the post-capture scenario in this paper. This method is to resolve parameter identification with two steps: coarse estimation and precise estimation. In the coarse estimation step, all the robot arms are fixed and inertia tensor of the combined system is first calculated by the angular momentum conservation equation of the system. Then, inertia parameters of the unknown target are estimated using the least square method. Second, in the precise estimation step, the robot arms are controlled to move and then inertia parameters are once again estimated by optimization method. In the process of optimization, the coarse estimation results are used as an initial value.

Numerical simulation results prove that the method presented in this paper is effective for identifying the inertia parameter of a captured unknown target.

The presented method can also be applied to identify the inertia parameter of space robot.

In the classic momentum-based identification method, the linear momentum and angular momentum of system, both considered to be conserved, are used to identify the parameter of system. If the elliptical orbit in space is considered, the conservation of linear momentum is wrong. In this paper, an identification based on the conservation of angular momentum and dynamics is presented. Compared with the classic momentum-based method, this method can get a more accurate identification result.

This paper studies the nonlinear dynamics of membrane structure considering wrinkling effect. The coupling between wrinkles and vibration is investigated elaborately, and new insight on the dynamics of wrinkled membrane is unveiled.

Based on the stability theory of plates and shells, the wrinkling model of the membrane structure is established. Considering the effects of wrinkling and nonlinearity, the dynamic response is calculated with NewMark method.

Wrinkling will impact the dynamics of the membrane structure significantly for asymmetrical tension loading cases, dynamic response of the wrinkled membrane structure can be classified into three categories: when the vibration is small, the dynamics of the wrinkled membrane structure will behave linearly, and the wrinkles will only affect the dynamic properties as initial conditions; when the vibration is relatively large, the wrinkles will interact with the vibration during the dynamic process, and the dynamics of the structure shows very complex features; when the vibration is large enough, the dynamics will be dominated by the geometric nonlinearity of large-amplitude vibration.

In the previous works on dynamics of wrinkled membrane structure, only the vibration modes have been studied, which means all those investigations are confined with linear vibration; little research has been conducted on the nonlinear dynamics of wrinkled membrane structure. In view of this, this paper presents an investigation of dynamic properties of membrane structure considering the wrinkling and geometric nonlinear effects. This research work presents some novel discoveries on the nonlinear dynamics of wrinkled membrane.

Connected and autonomous mobility may be an imminent game-changing reality, still in its embryonic form, that is set to disrupt a century-long ‘driver-centric’ status quo and recalibrate transport in unprecedented and possibly entirely unexpected ways. Autonomous vehicles (AVs) may have among others, a major impact on sustainability which in an era where concerns about the urgency and magnitude of climate change threats are voiced more and louder than ever before, needs to be a positive one for helping societies to enjoy liveable futures. This might not be an easy task to accomplish, however. This chapter, using a thematically organised narrative review approach, tries to give a well-rounded answer on whether driverless technology can yield sustainability benefits (or not) by looking at all three spheres of sustainability referring to environmental, economic and social implications. Agendas like motor traffic, air pollution, energy consumption, employment dynamics, inclusion, cybersecurity and privacy are all explored, and a conclusion is derived highlighting the need to package automation with connectivity, alternative fuelling and multimodality and building it around public transport (and to a lesser extent sharing service) provision. The road to make driverless transport genuinely sustainable is ‘bumpy’ and ‘uphill’ and requires the development of an appetite not for technology excellence per se, but rather for travel behaviour change. Achieving this needs serious strategic and coordinated multi-stakeholder efforts in terms of pro-active policy reform, user (and transport provider) education and training initiatives, infrastructure investment, business plan development, and living lab experimentation.

The purpose of this paper is to provide a critical synthesis of research conducted within the hospitality and tourism industries in response to the impact of the COVID-19 pandemic, identify key perspectives and themes relating to the recovery and resilience of the two sectors and put forward recommendations that help address organizational and consumer behavior changes produced by the pandemic.

This study adopted a critical reflection approach to identify, select and synthesize relevant research based on which recommendations are drawn.

This study offers a contemporary framework discussing three distinct themes that emerged from existing research regarding the impact of COVID-19 on the hospitality and tourism industries: management, marketing and consumer behavior.

This study offers operational, practical and actionable recommendations for organizations about how to adapt and recover from the impact of the COVID-19 pandemic by guiding the industry in sustaining long-term resilience.

This study provides a critical and current synthesis of selected literature and theory that discuss key implications of the COVID-19 pandemic for the recovery and resilience-building of the hospitality and tourism sectors.

State-owned enterprises (SOEs) play an immense role throughout the world. Historically lacking in innovativeness, SOEs are now compelled to be more innovative. This study aims to explore the innovative tendencies of SOEs and non-SOEs as they strive to be preferred suppliers to their key accounts. This study also examines the effects of top management involvement (TMI) and customer knowledge utilization on suppliers’ tendencies to provide innovative solutions to key customers. In addition, this study examines the moderating effects of state ownership on these relationships.

Following institutional theory and dynamic capabilities logic to guide expectations, this study collected survey responses from 185 managers at SOEs and non-SOEs in Beijing, Shanghai, Guangzhou and Shenzhen in China. Using partial least squares structural equation modeling, this study examined main and moderating effects of variables on innovation.

Results indicate that state ownership does not have a significant effect on innovation, suggesting Chinese SOEs may no longer be innovation-disadvantaged vis-à-vis non-SOEs. In addition, both TMI and customer knowledge utilization have positive effects on innovation. The hypothesized magnifying effect of state ownership on TMI’s main effect is not present. Data support our expectation that state ownership amplifies the positive effect of customer knowledge utilization on innovation.

Our research provides evidence that China’s SOEs are closing the competitive gap in innovation and mechanisms for this occurrence. The relatively small sample from limited geographies necessitates research in more regions of China. Also, research should investigate not just the ownership type of suppliers, but also of buyers.

This study offers unique insights into factors affecting the innovative tendencies of Chinese SOEs and non-SOEs. Until now, little research has addressed what practices SOEs use to provide more innovative solutions to customers.

The purpose of this paper is to present an on-orbit frequency identification method for spacecraft directly using attitude maneuver data. Natural frequency of flexible solar arrays plays an important role in attitude control design of spacecraft with solar arrays, and its precision will directly affect the accuracy of attitude maneuver. However, when the flexibility of the solar arrays is large, because of air damping, gravity effect etc., the frequency obtained by ground test shows great error compared with the on-orbit real value. One solution to this problem is to conduct on-orbit identification during which proper identification methods are used to obtain the parameters of interest based on the real on-orbit data of spacecraft.

The observer/Kalman filter identification and eigensystem realization algorithm are used as identification methods, and the attitude maneuver controller is designed using the rigid-body dynamics method.

Two conclusions are drawn in this paper according to results of numerical simulations. The first one is that the attitude controller based on the rigid-body dynamics method is effective in attitude maneuver of the spacecraft. The second one is that the on-orbit parameter identification can be directly achieved by using attitude maneuver data of spacecraft without adding additional missions.

Based on the methods proposed in this paper, it is convenient to obtain the natural frequencies of the spacecraft using the data of the attitude maneuver, which may greatly reduce the cost of on-orbit identification test.

The way of obtaining natural frequencies based on attitude maneuver data of spacecraft provides high originality and value for practical application.

This study aims to explore the relationship between managerial ownership and environmental innovation, particularly focusing on the impact of minority shareholder protection within the context of China’s A-share listed companies.

The study employs a fixed effect model over a decade-long sample, analysing secondary data from nonfinancial Chinese A-share firms. The two-stage least squares (2SLS) method is adopted to address endogeneity concerns.

The results demonstrate a significant positive influence of managerial ownership on environmental innovation, suggesting that top managers who have a say in the boardroom are inclined towards sustainable development. The presence of minority shareholders' protection positively moderates this relationship, underlining their roles in fostering environmentally friendly development. The subsample analysis showed that these relationships vary between state-owned enterprises (SOEs) and non-SOEs. It also differs between heavily and lightly polluting industries, which indicates that it is not enough to just have internal self-management, and more external pressure is necessary in heavily polluting industries.

Our study underscores the importance for managers to recognize the potential of aligning their ownership interests with environmental objectives. Companies can enhance their commitment to sustainability by fostering an internal environment that supports minority shareholder rights.

This study specifically focuses on the role of top managers and minority shareholders, providing new empirical evidence on how their influence can drive sustainable development initiatives. It is also among the few studies that differentiate between firm characteristics and pollution intensity, which provides valuable insights into how the impact of managerial ownership and minority shareholder protection varies across different contexts.

One challenge for tourism recommendation systems (TRSs) is the long-tail phenomenon of ratings or popularity among tourist products. This paper aims to improve the diversity and efficiency of TRSs utilizing the power-law distribution of long-tail data.

Using Sina Weibo check-in data for example, this paper demonstrates that the long-tail phenomenon exists in user travel behaviors and fits the long-tail travel data with power-law distribution. To solve data sparsity in the long-tail part and increase recommendation diversity of TRSs, the paper proposes a collaborative filtering (CF) recommendation algorithm combining with power-law distribution. Furthermore, by combining power-law distribution with locality sensitive hashing (LSH), the paper optimizes user similarity calculation to improve the calculation efficiency of TRSs.

The comparison experiments show that the proposed algorithm greatly improves the recommendation diversity and calculation efficiency while maintaining high precision and recall of recommendation, providing basis for further dynamic recommendation.

TRSs provide a better solution to the problem of information overload in the tourism field. However, based on the historical travel data over the whole population, most current TRSs tend to recommend hot and similar spots to users, lacking in diversity and failing to provide personalized recommendations. Meanwhile, the large high-dimensional sparse data in online social networks (OSNs) brings huge computational cost when calculating user similarity with traditional CF algorithms. In this paper, by integrating the power-law distribution of travel data and tourism recommendation technology, the authors’ work solves the problem existing in traditional TRSs that recommendation results are overly narrow and lack in serendipity, and provides users with a wider range of choices and hence improves user experience in TRSs. Meanwhile, utilizing locality sensitive hash functions, the authors’ work hashes users from high-dimensional vectors to one-dimensional integers and maps similar users into the same buckets, which realizes fast nearest neighbors search in high-dimensional space and solves the extreme sparsity problem of high dimensional travel data. Furthermore, applying the hashing results to user similarity calculation, the paper greatly reduces computational complexity and improves calculation efficiency of TRSs, which reduces the system load and enables TRSs to provide effective and timely recommendations for users.

Attitude determination and control subsystem (ADCS) is a vital part of earth observation satellites (EO-Satellites) that governs the satellite’s rotational motion and pointing. In designing such a complicated sub-system, many parameters including mission, system and performance requirements (PRs), as well as system design parameters (DPs), should be considered. Design cycles which prolong the time-duration and consequently increase the cost of the design process are due to the dependence of these parameters to each other. This paper aims to describe a rapid-sizing method based on the design for performance strategy, which could minimize the design cycles imposed by conventional methods.

The proposed technique is an adaptation from that used in the aircraft industries for aircraft design and provides a ball-park figure with little engineering man-hours. The authors have shown how such a design technique could be generalized to cover the EO-satellites platform ADCS. The authors divided the system requirements into five categories, including maneuverability, agility, accuracy, stability and durability. These requirements have been formulated as functions of spatial resolution that is the highest level of EO-missions PRs. To size, the ADCS main components, parametric characteristics of the matching diagram were determined by means of the design drivers.

Integrating the design boundaries based on the PRs in critical phases of the mission allowed selecting the best point in the design space as the baseline design with only two iterations. The ADCS of an operational agile EO-satellite is sized using the proposed method. The results show that the proposed method can significantly reduce the complexity and time duration of the performance sizing process of ADCS in EO-satellites with an acceptable level of accuracy.

Rapid performance sizing of EO-satellites ADCS using matching diagram technique and consequently, a drastic reduction in design time via minimization of design cycles makes this study novel and represents a valuable contribution in this field.

The purpose of this study is to examine the impact of environmental disclosures (END) on the corporate financial performance (CFP) of listed companies in Ghana before and during the Banking crisis (BKC) and the COVID-19 pandemic (COV).

This study used data from 16 companies listed on the Ghana Stock Exchange between 2012 and 2021. The END Index was used, which uses percentile ranking and is guided by Global Reporting Initiative guidelines. A diverse set of empirical tests were used to examine whether ENDs affect CFP during crises.

The study offered support for the stakeholder and signaling theories generally applied to the study of END. The results confirmed that ENDs have a significant positive effect on CFP measures, return on equity and earnings per share, before and during the crises. The BKC and COV had no impact on the CFP.

As Ghana is still recovering from the 2017 to 2020 BKC and COV, the findings of this study highlight the need for managers to embrace END reporting and engagement strategies to improve CFP and firm reputation.

To the best of the authors’ knowledge, this study is the first to examine the effect of END on CFP in the context of before and considering the Ghanaian BKC and COV. In addition, it is one of the few studies that investigates how ENDs affect the CFP of Ghanaian-listed firms.