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The aim of this article is to describe Huawei's internationalization process in Venezuela and show how socio-political and economic conditions helped to expedite the company's development in this Latin American nation between 2006 and 2019. Through this internationalization process, Huawei participated in a large technological transition in Venezuelan telecommunications.

This research uses an integrative approach, developing a quasi-case study from a review of the academic literature, contemporary news stories and institutional and practitioner documents.

The review indicates that Huawei was engaged in business with the Venezuelan phone company before its renationalization. Secondly, Huawei's internationalization was a beneficiary of the increased relations between the Venezuelan and Chinese governments, mainly through “oil for loans/goods” agreements. Lastly, this internationalization process includes wholly owned subsidiaries, direct export, greenfield and government joint ventures.

This research provides an understanding to other firms and strategists about the benefits of strong bilateral economic relationships between home and host countries.

This paper is among the first academic articles that describe the internationalization process of Huawei in Venezuela. Considering the host country's changing political and economic conditions during the last 20 years, such research may provide a perspective for considering other Chinese business expansions in Venezuela and Latin America.

Previous research has studied interactive value formation (IVF) using resource- or practice-based approaches but has neglected the role of emotions. This article aims to show how emotions are correlated in problematic social media interactions and explore their role in IVF.

By combining a text mining algorithm, nonparametric Spearman's rho and thematic qualitative analysis in an explanatory sequential mixed-method design, the authors (1) categorize customers' comments as positive, neutral or negative; (2) pinpoint peaks of negative comments; (3) classify problematic interactions as detrimental, contradictory or conflictual; (4) identify customers' main positive (joy, trust and surprise) and negative emotions (anger, dissatisfaction, disgust, fear and sadness) and (5) correlate these emotions.

Despite several problematic social interactions, the same pattern of emotions appears but with different intensities. Additionally, value co-creation, value no-creation and value co-destruction co-occur in a context of problematic social interactions (peak of negative comments).

This study provides new insights into the effect of customers' emotions during IVF by studying the links between positive and negative emotions and their effects on different sorts of problematic social interactions.

The quick growth of web-based and mobile e-learning applications such as massive open online courses have created a large volume of online learning resources. Confronting such a large amount of learning data, it is important to develop effective clustering approaches for user group modeling and intelligent tutoring. The paper aims to discuss these issues.

In this paper, a minimum spanning tree based approach is proposed for clustering of online learning resources. The novel clustering approach has two main stages, namely, elimination stage and construction stage. During the elimination stage, the Euclidean distance is adopted as a metrics formula to measure density of learning resources. Resources with quite low densities are identified as outliers and therefore removed. During the construction stage, a minimum spanning tree is built by initializing the centroids according to the degree of freedom of the resources. Online learning resources are subsequently partitioned into clusters by exploiting the structure of minimum spanning tree.

Conventional clustering algorithms have a number of shortcomings such that they cannot handle online learning resources effectively. On the one hand, extant partitional clustering methods use a randomly assigned centroid for each cluster, which usually cause the problem of ineffective clustering results. On the other hand, classical density-based clustering methods are very computationally expensive and time-consuming. Experimental results indicate that the algorithm proposed outperforms the traditional clustering algorithms for online learning resources.

The effectiveness of the proposed algorithms has been validated by using several data sets. Moreover, the proposed clustering algorithm has great potential in e-learning applications. It has been demonstrated how the novel technique can be integrated in various e-learning systems. For example, the clustering technique can classify learners into groups so that homogeneous grouping can improve the effectiveness of learning. Moreover, clustering of online learning resources is valuable to decision making in terms of tutorial strategies and instructional design for intelligent tutoring. Lastly, a number of directions for future research have been identified in the study.

This research aims to improve the performance of rail fastener defect inspection method for multi railways, to effectively ensure the safety of railway operation.

Firstly, a fastener region location method based on online learning strategy was proposed, which can locate fastener regions according to the prior knowledge of track image and template matching method. Online learning strategy is used to update the template library dynamically, so that the method not only can locate fastener regions in the track images of multi railways, but also can automatically collect and annotate fastener samples. Secondly, a fastener defect recognition method based on deep convolutional neural network was proposed. The structure of recognition network was designed according to the smaller size and the relatively single content of the fastener region. The data augmentation method based on the sample random sorting strategy is adopted to reduce the impact of the imbalance of sample size on recognition performance.

Test verification of the proposed method is conducted based on the rail fastener datasets of multi railways. Specifically, fastener location module has achieved an average detection rate of 99.36%, and fastener defect recognition module has achieved an average precision of 96.82%.

The proposed method can accurately locate fastener regions and identify fastener defect in the track images of different railways, which has high reliability and strong adaptability to multi railways.

The purpose of this paper is to systematically review the evolution, characteristics, motivations, entry patterns, organizational structure and effectiveness of the internationalization of Chinese research institutions in the past 40 years of reform and opening-up.

This paper describes the evolution and practice of Chinese research institutions “going out” by constructing a theoretical framework diagram and uses official statistics and existing research to explain the authors’ points.

The research results show that the internationalization of research institutions has undergone four phases: sprout period, starting period, adjustment period and accelerating period. It shows a rapid growth of investment scale, diversification of investment entities, rich and varied forms, and transition to major countries along the “One Belt and One Road.” Expanding the international market, tracking and acquiring technological frontiers, nurturing domestic R&D talents, and evading the risks of political, economic, cultural and scientific differences between home and host countries are the main motivations for Chinese research institutions to “go global.” Multinational corporations have entered the host country with modes such as M&A, greenfield investment and joint R&D alliances in their own strengths and also presented a variety of organizational structures such as integrated R&D networks.

This paper systematically summarizes the internationalized experience model of research institutions with Chinese characteristics since the reform and opening-up. From the perspective of internationalization model transformation, policy integration and cooperation among emerging economies, it presents the opportunities and challenges faced by the research institutions in the process of internationalization and provides a theoretical basis for improving the internationalization ability of research institutions.