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Autonomous orbit determination using geomagnetic measurements is an important backup technique for safe spacecraft navigation with a mere magnetometer. The geomagnetic model is used for the state estimation of orbit elements, but this model is highly nonlinear. Therefore, many efforts have been paid to developing nonlinear filters based on extended Kalman filter (EKF) and unscented Kalman filter (UKF). This paper aims to analyze whether to use UKF or EKF in solving the geomagnetic orbit determination problem and try to give a general conclusion.

This paper revisits the problem and from both the theoretical and engineering results, the authors show that the EKF and UKF show identical estimation performances in the presence of nonlinearity in the geomagnetic model.

While EKF consumes less computational time, the UKF is computationally inefficient but owns better accuracy for most nonlinear models. It is also noted that some other navigation techniques are also very similar with the geomagnetic orbit determination.

The intrinsic reason of such equivalence is because of the orthogonality of the spherical harmonics which has not been discovered in previous studies. Thus, the applicability of the presented findings are not limited only to the major problem in this paper but can be extended to all those schemes with spherical harmonic models.

The results of this paper provide a fact that there is no need to choose UKF as a preferred candidate in orbit determination. As UKF achieves almost the same accuracy as that of EKF, its loss in computational efficiency will be a significant obstacle in real-time implementation.

Recent spacecraft attitude control systems tend to use wireless communication for cost-saving and distributed mission purposes while encountering limited communication resources and data exposure issues. This paper aims to study the attitude control problem with low communication frequency under the sampled-data.

The authors propose constructive control system structures based on quantization and event-triggered methods for intra-spacecraft and multi-spacecraft systems, and they also provide potential solutions to shield the control system's data security. The proposed control architectures can effectively save communication resources for both intra-spacecraft and multi-spacecraft systems.

The proposed control architectures no longer require sensors with trigger-ing mechanism and can achieve distributed control schemes. This paper also provides proposals of employing the public key encryption to secure the data in control-loop, which is transmitted by the event-triggered control mechanism.

Spacecraft attempts to use wireless communication, yet the attitude control system does not follow up promptly to accommodate these variations. Compared with existing approaches, the proposed control structures can save communication resources of control-loop in multi-sections effectively, and systematically, by rationally configuring the location of quantization and event-triggered mechanisms.

This paper presents several new control schemes and a necessary condition for the employment of encryption algorithms for control systems based on event-based communication.

This paper gathers tourism digital footprint from online travel platforms, choosing social network analysis method to learn the structure of destination networks and to probe into the features of tourist flow network structure and flow characteristics in Guilin of China.

The digital footprint of tourists can be applied to study the behaviors and laws of digital footprint. This research contributes to improving the understanding of demand-driven network relationships among tourist attractions in a destination.

(1) Yulong River, Yangshuo West Street, Longji Terraced Fields, Silver Rock and Four Lakes are the divergent and agglomerative centers of tourist flow, which are the top tourist attractions for transiting tourists. (2) The core-periphery structure of the network is clearly stratified. More specifically, the core nodes in the network are prominent and the core area of the network has weak interaction with the peripheral area. (3) There are eight cohesive subgroups in the network structure, which contains certain differences in the radiation effects.

This research aims at exploring the spatial network structure characteristics of tourism flows in Guilin by analyzing the online footprints of tourists. It takes a good try to analyze the application of network footprint with the research of tourism flow characteristics, and also provides a theoretical reference for the design of tourist routes and the cooperative marketing among various attractions.

The purpose of this paper is to develop and empirically test a conceptual framework to analyze how inter-organizational knowledge sharing facilitates enterprise resource planning (ERP) implementation.

Data were collected from a 2014 survey on 283 Chinese companies. Structural equation modeling was used to test the structural model of the framework.

The results of the study indicated that organizational preparedness (in terms of internal culture, organizational structure, availability of resources, and technological capabilities), positive benefits and costs perception, and external influences (in terms of environmental uncertainty, competitive pressure, and partner readiness) would facilitate inter-organizational knowledge sharing, which in turn, would enhance ERP implementation effectiveness.

Convenience samples from an author’s MBA classes were used in the survey, and a single respondent from each organization answering all questions for such complicated issues also posed the risk of measurement bias and inaccuracy.

The study provided evidences to practitioners about how organizations should collaborate with supply chain partners at a full scale in knowledge generation, maintenance, dissemination, and application in order to enhance their effectiveness on ERP implementation.

ERP projects are predominately observed in existing research as internal initiatives that companies take independently within their own organizational boundaries. This study represents one of the early large-scale empirical efforts to investigate ERP implementation from an inter-firm supply chain collaboration perspective. Additional contribution includes some interesting empirical evidences on the current state of ERP utilization in the Chinese market.

The rise of the mobile Internet has accumulated much text information in various online financial forums. Such information often contains the emotional attitudes of investors toward financial technology (fintech) platforms, so extracting the sentimental tendency information has great practical value for the development of fintech platforms. Based on the investor sentiment theory, the paper aims to analyze the relevant social media data and test the influence path of online news evaluation on the stock price fluctuation of fintech platforms.

Taking Oriental Fortune as the research object, this paper selects multiple variables such as stock bar popularity, snowball popularity, news popularity and news sentiment scores collected by UQER and combines the sentiment scores of single daily news into a daily sentiment score. Based on the period from November 1, 2019 to March 31, 2020, during the emergence of the coronavirus disease 2019 (COVID-19) pandemic as the background, the authors conduct the Granger causality test based on the vector autoregressive (VAR) model and analyze the relevant evaluation of Oriental Fortune through the empirical model.

The authors' results show that different online evaluations impact the rise and fall of stock prices differently, while news popularity has the most significant impact. Besides, news sentiment scores on share price fluctuation have a relatively substantial influence. These findings indicate that the authoritative news evaluation can strongly guide investors to make relevant investment behavior operations in the information dissemination process, significantly affecting stock prices.

The research findings of this paper have good inspiration and reference values for investors and financial regulators.

The paper aims to study the relationship between corporate social responsibility, green supply chain management, and operational performance and the moderating effects of relational capital on these relationships.

The authors conduct an empirical study with a structural equation modeling approach to investigate the relationship between corporate social responsibility—constructed by the quality and environmental responsibility, green supply chain management—including green supplier and customer management and operational performance—manifested by quality, cost, flexibility, and delivery performance using data from 308 manufacturers in China. Besides, the authors explore the moderating effect of supplier and customer relational capital on these relationships.

The findings indicate that a company's quality and environmental responsibility significantly impacts its green supply chain management practices, which further improve its operational performance in quality, cost, flexibility, and delivery. In addition, supplier and customer relational capital strengthens the influence of environmental responsibility on green supply chain management. While supplier relational capital reinforces the impact of green supplier management on flexibility and delivery performance, customer relational capital only strengthens the influence of green customer management on flexibility performance.

The study enriches the extant literature by developing a holistic framework integrating corporate social responsibility, green supply chain management, relational capital, and operational performance and unraveling their intricate relationships. The authors’ findings help practitioners prioritize proactive steps in environmental conservation more than achieving operational performance.

The purpose of this paper is to examine the effect of environmental characteristics, business partnership relationship, knowledge complementarity, organizational characteristics on knowledge management practices and innovation performance.

The research used primary data, i.e. data obtained directly from the distribution of questionnaires to respondents, namely, the company’s managers/leaders/directors in the companies that became the research sample. Data were collected by sending questionnaires either by mail or email to the respondents. To examine the effect of environmental characteristics, business partnership relationship, knowledge complementarity and organizational characteristics on knowledge management practices and innovation performance.

Environmental characteristics, business partnership relationship, knowledge complementarity and organizational characteristics partially have a significant effect on knowledge management practices. Environmental characteristics and business partnership relationship partially have a significant effect on innovation performance, while knowledge complementarity and organizational characteristics have no significant effect. For other constructs, knowledge management practices are able to be a moderator variable, which can relate these constructs with innovation performance.

The research using the diffusion of innovation paradigm, the combination of market-based and knowledge-based paradigms is expected to fill the previous research gap and become the first uniqueness and originality, as well as characteristic of this research. The second originality is this research examines the role of the knowledge management practice variable as the moderator variable. Then, the third originality is this research investigates the relationship between business partner relationship and innovation performance. These three originalities are still rarely studied in previous studies, so this research will further complement, expand the study, especially in the knowledge management, innovation performance area.

This research measured and compared the brand identity of Kentucky Fried Chicken (KFC) in China and the United States. Brand identity was defined as the customer impressions of four different KFC identity elements – properties, products, presentations, and publications. A survey of young consumers in the two countries (n = 795), showed that the Chinese respondents were more apt to eat within KFC restaurants, and spend more time doing so, than the Americans. The Chinese also had much more positive impressions of KFC than their US counterparts. Brand identity impressions were correlated with overall customer satisfaction and with future patronage intentions for both groups, but much more so for the Americans. These findings support a model where differences in cultural frames of reference lead consumers to actively localize the brand identity of this nominally globalized product.

Drawing on the organizational learning and relational governance literature, this study aims to advance a theoretical model to explain the export performance of emerging market export ventures.

This study selects quantitative methodology because the main objective of this study is to explore the role of export ventures’ performance (past) on guanxi networking, co-creation marketing strategies and present performance.

The empirical evidence suggests that guanxi networking and co-creation strategy can mediate the relationship between export venture performance in the preceding year and export venture performance in the following year. In addition, this study also provides some guidance for emerging market export ventures on how to build a strong guanxi networking and create opportunities for collaboration when the effect of export performance in the preceding year on current performance is absent.

The authors propose the inclusion of strategic guanxi networking-related factors (e.g. top executives’ ties with business-to-business customers, such as distributors in the host market) in the prior performance-current performance paradigm. The outcomes of this study also contribute to extant organizational learning theory research by integrating preceding performance research with the co-creation theory. The study offers new insights into organizational learning and relational governance from the emerging market perspective.

Currently, there is a dearth of research studies regarding macro analysis of the workforce productivity of the US construction industry. The purpose of this paper is to calculate the workforce productivity changes of the US construction industry from 2006 to 2016, with the number of laborers as input and value of construction industry as output.

The present study introduced the data envelopment analysis (DEA) based Malmquist productivity index model to measure the workforce productivity of the US construction industry from 2006 to 2016.

The results indicated that the workforce productivity of the US construction industry experienced a continuous decline, except for the increases from 2011 to 2013 and from 2014 to 2015. It was also shown that there were gaps in the workforce productivity development level among all states and nine regions in the US construction industry. Besides, the relationship between workforce productivity and four aspects, including real estate price, workforce, climate distribution and economic factors, was analyzed.

The calculation of the productivity of the US construction industry is based on the premise that the external environment is fixed and unchanged from 2006 to 2016, but the multi-level DEA model for further calculation is required for obtaining more effective conclusions.

This paper measures the workforce productivity of the US construction industry over the past 11 years, which added latest analysis and knowledge into the construction industry, providing decision-makers with advice and data support to formulate policies to improve workforce productivity.

This study provided both government decision-makers and industrial practitioners with important macro background environment information, which will facilitate the improvement of workforce productivity in the construction industry in different regions of the US.