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With the yearly increase of mileage and passenger volume in China's high-speed railway, the problems of traditional paper railway tickets have become increasingly prominent, including complexity of business handling process, low efficiency of ticket inspection and high cost of usage and management. This paper aims to make extensive references to successful experiences of electronic ticket applications both domestically and internationally. The research on key technologies and system implementation of railway electronic ticket with Chinese characteristics has been carried out.

Research in key technologies is conducted including synchronization technique in distributed heterogeneous database system, the grid-oriented passenger service record (PSR) data storage model, efficient access to massive PSR data under high concurrency condition, the linkage between face recognition service platforms and various terminals in large scenarios, and two-factor authentication of the e-ticket identification code based on the key and the user identity information. Focusing on the key technologies and architecture the of existing ticketing system, multiple service resources are expanded and developed such as electronic ticket clusters, PSR clusters, face recognition clusters and electronic ticket identification code clusters.

The proportion of paper ticket printed has dropped to 20%, saving more than 2 billion tickets annually since the launch of the application of E-ticketing nationwide. The average time for passengers to pass through the automatic ticket gates has decreased from 3 seconds to 1.3 seconds, significantly improving the efficiency of passenger transport organization. Meanwhile, problems of paper ticket counterfeiting, reselling and loss have been generally eliminated.

E-ticketing has laid a technical foundation for the further development of railway passenger transport services in the direction of digitalization and intelligence.

The purpose of this study is to analyze the performance of indigenous innovation in developing countries in the era of trade liberalization. It analyzes indigenous innovation from research and development (R&D) investments to innovation output and its effect on economic growth.

The sample for this study includes 20 middle-income countries across five continents for the period between 1994 and 2018. The study employs the Crepon Duguet and Mairessec CDM model in a panel data setting to do a multistage analysis of the innovation process. A vector error correction model VECM is employed to test for Granger causality between the variables investigated.

The results show that imports and foreign direct investments (FDI) have generally have short-run and long-run causal effects on domestic R&D investments. In regions where imports and FDI do not have individual causal effects on innovation output, a joint increase in each of them and R&D have both short-run and long-run causal effects. Indigenous innovation is a significant contributor to economic growth when a country can produce and export novel products.

The sample is only limited to developing economies, and due to the unavailability of data, only 20 countries were captured.

Imported products and FDI are critical to the innovation drive when such activities are targeted at enhancing indigenous innovation from R&D to the production of new products. Hence, policy formulation should encourage the absorption of foreign technologies that serve as inputs to indigenous innovation.

This paper focuses specifically on indigenous innovation and analyses the influence of foreign technologies in this effort. It tests the moderating roles of imports and FDI in the relationship between R&D and innovation output, concluding that both variables enhance the effect of R&D on innovation output.

This paper aims to obtain the evolution law of dynamic performance of CR400BF electric multiple unit (EMU).

Using the dynamic simulation based on field test, stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers were tested. Stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to research the evolution law with running mileage of dynamic index of CR400BF EMU.

The results showed that stiffness and damping coefficient subjected to normal distribution, the mean and variance were computed and the evolution law of stiffness and damping coefficient with running mileage was obtained.

Firstly, based on the field test we found that stiffness of rotary arm nodes and damping coefficient of anti-hunting dampers subjected to normal distribution, and the evolution law of stiffness and damping coefficient with running mileage was proposed. Secondly stiffness, damping coefficient, friction coefficient, track gauge were taken as random variables, the stochastic dynamics simulation method was constructed and applied to the research to the evolution law with running mileage of dynamic index of CR400BF EMU.

Large displacement misalignment under the action of active faults can cause complex three-dimensional deformation in subway tunnels, resulting in severe damage, distortion and misalignment. There is no developed system of fortification and related codes to follow. There are scientific problems and technical challenges in this field that have never been encountered in past research and practices.

This paper adopted a self-designed large-scale active fault dislocation simulation loading system to conduct a similar model test of the tunnel under active fault dislocation based on the open-cut tunnel project of the Urumqi Rail Transit Line 2, which passes through the Jiujiawan normal fault. The test simulated the subway tunnel passing through the normal fault, which is inclined at 60°. This research compared and analyzed the differences in mechanical behavior between two types of lining section: the open-cut double-line box tunnel and the modified double-line box arch tunnel. The structural response and failure characteristics of the open-cut segmented lining of the tunnel under the stick-slip part of the normal fault were studied.

The results indicated that the double-line box arch tunnel improved the shear and longitudinal bending performance. Longitudinal cracks were mainly distributed in the baseplate, wall foot and arch foot, and the crack position was basically consistent with the longitudinal distribution of surrounding rock pressure. This indicated that the longitudinal cracks were due to the large local load of the cross-section of the structure, leading to an excessive local bending moment of the structure, which resulted in large eccentric failure of the lining and formation of longitudinal cracks. Compared with the ordinary box section tunnel, the improved double-line box arch tunnel significantly reduced the destroyed and damage areas of the hanging wall and footwall. The damage area and crack length were reduced by 39 and 59.3%, respectively. This indicates that the improved double-line box arch tunnel had good anti-sliding performance.

This paper adopted a self-designed large-scale active fault dislocation simulation loading system to conduct a similar model test of the tunnel under active fault dislocation. This system increased the similarity ratio of the test model, improved the dislocation loading rate and optimized the simulation scheme of the segmented flexible lining and other key factors affecting the test. It is of great scientific significance and engineering value to investigate the structure of subway tunnels under active fault misalignment, to study its force characteristics and damage modes, and to provide a technical reserve for the design and construction of subway tunnels through active faults.

Drawing on the transformational leadership (TL) and knowledge-based view (KBV) theory, the present study investigates the impact of TL on radical innovation (RI) through the mediation of knowledge management capabilities (KMCs) and moderation of competitive intensity (CI) of textile and apparel industries with an Asian context.

Data were collected from the relevant stakeholders of the industry-university collaboration teams with a structured survey questionnaire. Working with 304 textile and apparel industry respondents, structural equation modeling based partial least square (PLS-SEM) is used to test the conceptual framework. PLS-SEM technique was applied to test the hypothesis using Smart-PLS 3.8 packages program.

The results proposed TL has a positive impact on KMC and RI. Furthermore, the study reveals KMC positively mediated the relationship between TL and RI. This mediation is conditional on the moderating role of CI for the KMC (knowledge acquisition capability + knowledge-sharing capability) path to RI. Conversely, moderation of CI is insignificant and does not influence on fostering RI.

Leaders and managers have realized creative and innovative culture is built within the organizations by leader-follower collaboration through actual knowledge acquisition and knowledge sharing. Moreover, industry policymakers and practitioners establish the knowledge management department to enhance the innovation culture among the firms' stakeholders to encourage RI to sustain the global business market.

The study has introduced KMC as a mediator and CI as a moderator in the proposed model between TL-RI and KMC-RI. Further, it explores the linkages between TL, KMC, CI and RI.

In order to better optimize the internal management system of book publishing and to cope with the changes in the external market environment, the purpose of this paper is to carry out cross-border publishing with the help of a transmedia storytelling model to realize the transformation and upgrading of the industry. Focusing on the relationship between the book publishing transmedia storytelling model and business performance, the moderating effect of the innovation environment on different variables is assessed.

This paper proposes several feasible hypotheses based on existing research. The research data came from 365 managers of Chinese book publishing organizations, and the scale was validated by Cronbach’s a, composite reliability (CR) and average variance extracted (AVE). Reliability and validity were verified, and correlation and regression analyses were used to test the impact of the book publishing transmedia storytelling model on business performance and to analyze the moderating role of the innovation environment.

The results show that the book publishing transmedia storytelling model (content production, technology integration, organizational innovation, marketing integration) helps to improve business performance (market performance, financial performance), and the innovation environment has a positive moderating effect on the relationship between the book publishing transmedia storytelling model and business performance, which provides a guarantee for the transformation and upgrading of book publishing. The market information reflected in the innovation environment has a certain role in promoting the innovation and business performance of the book publishing transmedia storytelling model.

The empirical evidence provides a theoretical link between the book publishing transmedia storytelling model and business performance, but there are still some shortcomings, and more factors, such as equity structure, government subsidies and research and development investment, should be included in future research. In addition, the scope of the research should be broadened on this basis to make the results of the data analysis more objective.

This paper introduces the transmedia storytelling model and deeply analyzes the relationship between the book publishing transmedia storytelling model and business performance, which is of great practical significance for optimizing the application and service quality of book publishing, prolonging the industrial chain, enhancing the interaction and participation of users and perfecting the business management system of the book publishing industry.

The application and research of the book publishing transmedia storytelling model are imperfect. Therefore, this paper not only helps to promote the innovation of book publishing organizational structure and improve the management system of business performance, but also may help to improve the innovation environment of book publishing enterprises and promote the diversification of industrial structure.

This study aims to review the literature on sharing economy logistics and crowd logistics to answer the three following questions: How is the literature on sharing economy logistics structured? What are the main trends in sharing economy logistics and crowd logistics? What are the future research options?

Bibliometric analysis is used to evaluate 85 articles published over the past 12 years; it identifies the top academic journals, authors and research topics contributing to the field.

The sharing economy logistics and crowd logistics literature is structured around several disciplines and highlights that some are more scientifically advanced than others in their subject definitions, designs, modelling and innovative solutions. The main trends are organized around three clusters: Cluster 1 refers to the optimal allocation of costs, prices, distribution and supplier relationships; Cluster 2 corresponds to business related crowdsourcing and international industry practices; and Cluster 3 includes the impact of transport on last-mile delivery, crowd shipping and the environment.

The study is based on data from peer-reviewed scientific journals and conferences. A broader overview could include other data sources such as books, book chapters, working papers, etc.

Future research directions are discussed in the context of the evolution from crowd logistics to crowd intelligence, and the complexities of crowd logistics such as understanding how the social crowd can be integrated into the logistics process. Our results are part of the crowd science and engineering concept and provide some answers about crowd cyber-system questions regarding crowd intelligence in logistic sector.

Constant or decreasing returns and increasing returns to scale are two kinds of mechanism in economic growth. The goal of supply-side structural reform is to promote the establishment of the mechanism with increasing returns to scale. The paper aims to discuss this issue.

This paper argues that the overall economic structure of the developing economy has been divided into the sector of constant or decreasing returns to scale and the sector of increasing returns to scale due to the dual economic structure. Among them, the supply-side structural reform is mainly to reduce the sector of decreasing returns to scale and increase the sector of increasing returns to scale. Based on the hypothesis of such two-sector economic structure in the supply side of developing economies and on the industrial data, this paper empirically tests the returns to scale of China’s supply structure. The result suggests that so far the sector of constant or decreasing returns to scale dominates the supply structure of China’s economic growth, which results in the state of decreasing returns to scale in China’s overall economy.

Therefore, to realize the long-term sustained growth and transformation of the development pattern of China’s economy, the authors must carry out the supply-side structural reform, vigorously develop the modern industrial sectors characterized by modern knowledge and technology, and promote the development of an innovation-driven economy.

Besides, the authors must accelerate the transformation from traditional industrial sectors to modern industrial sectors, actively promote China’s industrial structure toward rationalization and high gradation, as well as build a modern industrial system so as to facilitate the formation of the mechanism of increasing returns to scale and accelerate the transformation of the driving force of China’s economic growth.

This paper aims to create a new searchable 3D city model to help managers improve their decision-making.

This paper identifies data management basics and the key elements used in the new model design; it further analyzes five-city models, presents its findings and proposes analytical trends for the new model. It discusses the concepts underlying existing models, explains the benefit brought by the proposed model and demonstrates its robustness.

City systems can be interconnected, thanks to data digitization and the integration of new technologies into different management processes. Although there are several 3D city models available, none of those identified in this research can be queried for several sectors.

This model design can only be successfully realized in the presence of a public mandate. Potential limitations include information security risks and political non-acceptance.

The present work proposes a searchable and high performance model having the distinctive capacity to bring together city systems and perform real-time data analysis in order to extract important information needed to guide the city, and in the context of a global vision.

Digital resources such as smart applications reviews and online feedback information are important sources to seek customers’ feedback and input. This paper aims to help government entities gain insights on the needs and expectations of their customers. Towards this end, we propose an aspect-based sentiment analysis hybrid approach that integrates domain lexicons and rules to analyse the entities smart apps reviews. The proposed model aims to extract the important aspects from the reviews and classify the corresponding sentiments. This approach adopts language processing techniques, rules, and lexicons to address several sentiment analysis challenges, and produce summarized results. According to the reported results, the aspect extraction accuracy improves significantly when the implicit aspects are considered. Also, the integrated classification model outperforms the lexicon-based baseline and the other rules combinations by 5% in terms of Accuracy on average. Also, when using the same dataset, the proposed approach outperforms machine learning approaches that uses support vector machine (SVM). However, using these lexicons and rules as input features to the SVM model has achieved higher accuracy than other SVM models.