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The numerous spoil grounds brought about by mega transportation infrastructure projects which can be influenced by the ecological environment. To achieve better management of spoil grounds, this paper aims to assess their comprehensive risk levels and categorize them into different categories based on ecological environmental risks.

Based on analysis of the environmental characteristics of spoil grounds, this paper first comprehensively identified the ecological environmental risk factors and developed a risk assessment index system to quantitatively describe the comprehensive risk levels. Second, this paper proposed a comprehensive model to determine the risk assessment and categorization of spoil ground group in mega projects integrating improved projection pursuit clustering (PPC) method and K-means clustering algorithm. Finally, a case study of a spoil ground group (includes 50 spoil grounds) in a mega infrastructure project in western China is presented to demonstrate and validate the proposed method.

The results show that our proposed comprehensive model can efficiently assess and categorize the spoil grounds in the group based on their comprehensive ecological environmental risk. In addition, during the process of risk assessment and categorization of spoil grounds, it is necessary to distinguish between sensitive factors and nonsensitive factors. The differences between different categories of spoil grounds can be recognized based on nonsensitive factors, and high-risk spoil grounds which need to be focused more on can be identified according to sensitive factors.

This paper develops a comprehensive model of risk assessment and categorization of a group of spoil grounds based on their ecological environmental risks, which can provide a reference for the management of spoil grounds in mega projects.

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.

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 purpose of this study is to explore the continuity and stability of the impact of accounting information quality on cash holdings, and the moderating effect of this relationship on state ownerships and local appointments.

Based on China's companies from 2011 to 2019, the authors divided cross-section and panel samples, adopted a linear and classification model and performed grouping regression.

The authors find that: first, the quality of corporate accounting information can significantly improve the level of cash holding, giving play to the strategic value effect of cash holding. But that boost is based on economies being able to solve agency problems. Second, the reduction of earnings management and the improvement of accounting information quality of NSOEs improve the level of cash holdings, while SOEs are on the contrary. Third, local appointments can play to the emotional strengths of their hometowns and play a synergistic role in this relationship, but the supervision effect of remote appointments is not obvious.

Through endogeneity and other tests, the conclusion is robust. Based on the agency and information asymmetry theory, the authors considered China's institutional and cultural factors, optimized accounting information's measurement and expanded the research boundary of the accounting field. The authors believe that applicable scenarios should be fully considered in the concluding relationship between accounting information quality and cash holdings. Enterprises should give full play to the advantages of cash holdings in strategic decision-making and financial efficiency, improve the quality of accounting information and also consider state ownerships and the differences in directors' emotions to reduce internal agency costs.

An alliance portfolio can help latecomer firms to acquire the necessary knowledge and resources to catch up with market leaders. However, how latecomer firms construct an alliance portfolio in terms of the nature of windows of opportunity has not been fully analyzed. This paper aims to explore how latecomer firms can build appropriate coalitions according to the nature of the window of opportunity to achieve technological catch-up in different catch-up phases.

Based on a longitudinal case study from 1984 to 2018 of Sunny Group, now a leading manufacturer of integrated optical components and products, this paper explores the process of technological catch-up of latecomer firms building different types of alliance portfolio in different windows of opportunity.

This paper finds that there is a sequence when latecomers build an alliance portfolio in the process of catch-up. When the uncertainty of opportunity increases, the governance mechanism of the alliance portfolio will change from contractual to equity-based. Also, latecomer firms build market-dominated and technology-dominated alliance portfolios to overcome their market and technology disadvantages, respectively.

These conclusions not only enrich the theory of latecomer catch-up from the perspective of windows of opportunity but also expand research on alliance portfolio processes from a temporal perspective.

The purpose of this study is to establish a method for accurately extracting torch and seam features. This will improve the quality of narrow gap welding. An adaptive deflection correction system based on passive light vision sensors was designed using the Halcon software from MVtec Germany as a platform.

This paper proposes an adaptive correction system for welding guns and seams divided into image calibration and feature extraction. In the image calibration method, the field of view distortion because of the position of the camera is resolved using image calibration techniques. In the feature extraction method, clear features of the weld gun and weld seam are accurately extracted after processing using algorithms such as impact filtering, subpixel (XLD), Gaussian Laplacian and sense region for the weld gun and weld seam. The gun and weld seam centers are accurately fitted using least squares. After calculating the deviation values, the error values are monitored, and error correction is achieved by programmable logic controller (PLC) control. Finally, experimental verification and analysis of the tracking errors are carried out.

The results show that the system achieves great results in dealing with camera aberrations. Weld gun features can be effectively and accurately identified. The difference between a scratch and a weld is effectively distinguished. The system accurately detects the center features of the torch and weld and controls the correction error to within 0.3mm.

An adaptive correction system based on a passive light vision sensor is designed which corrects the field-of-view distortion caused by the camera’s position deviation. Differences in features between scratches and welds are distinguished, and image features are effectively extracted. The final system weld error is controlled to 0.3 mm.