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With the advance of the Silk Road Initiative proposed by China, it has been a focus of China government to develop strategic emerging industries. The development of strategic emerging industries needs the support of competitive intelligence on many aspects such as strategical planning, policy making, industrial structure adjustment, and technology innovation. However, so far there are few studies toward the competitive intelligence systems for strategic emerging industries. In this article, we focus on a number of issues related to the competitive intelligence for strategic emerging industries in China. First, we conduct a strengths, weaknesses, opportunities, and threats analysis on the situations of strategic emerging industries in China, based on which the necessity of building a competitive intelligence (CI) service system for strategic emerging industries is discussed. Next, the authors present a framework of a CI service system for strategic emerging industries in China. The principles, components, working process, and product forms are deeply described. The CI service system proposed in this article consists of a cooperation network platform, three layered organizations, and three systems, which integrates organizations, information, people, network, and service platforms into an ecosystem to offer competitive intelligence supports for government, industry, and enterprises. Finally, the authors discuss a case study of the proposed CI service system for the new energy automobile industry.

In as much as it is contested, the Belt and Road Initiative (BRI) is also unexplored, underdiscussed, and, as a result, misunderstood. Frequently viewed through the lens of international relations and global economy, the diverse dimensions of collaboration, including business and research-industry clusters, that BRI enhances, tend to be excluded from the analysis. In a similar manner, the role of the Arab Peninsula in the grand strategy underpinning BRI and its implementation is rarely discussed. BRI is a forward-oriented initiative, an attempt to reap benefits of developments and circumstances that are only nascent. This bears two potent implications. First, as China attempts to influence the context in which it operates, it is subject to change itself; the Chinese business sector evolution attests to that. Second, some of China’s not so obvious partners of today, including those in the Arab Peninsula, are about to turn into key interlocutors of tomorrow. BRI taps into opportunities thus created. This chapter elaborates on these issues and, against this backdrop, outlines how the remaining chapters included in this volume add to this discussion.

Decision-making is always an issue that managers have to deal with. Keenly observing to different preferences of the targets provides useful information for decision-makers who do not require too much information to make decisions. The main purpose is to avoid decision-makers in a dilemma because of too much or opaque information. Based on problem-oriented, this research aims to help decision-makers to develop a macro-vision strategy that fits the needs of different clusters of customers in terms of their favorite restaurants. This research also focuses on providing the rules to rank data sets for decision-makers to make choices for their favorite restaurant.

When the decision-makers need to rethink a new strategic planning, they have to think about whether they want to retain or rebuild their relationship with the old consumers or continue to care for new customers. Furthermore, many of the lecturers show that the relative concept will be more effective than the absolute one. Therefore, based on rough set theory, this research proposes an algorithm of related concepts and sends questionnaires to verify the efficiency of the algorithm.

By feeding the relative order of calculating the ranking rules, we find that it will be more efficient to deal with the faced problems.

The algorithm proposed in this research is applied to the ranking data of food. This research proves that the algorithm is practical and has the potential to reveal important patterns in the data set.

The online platform is one of the essential components of the platform economy that is constructed by a large scale of the personal data resource. However, accurate empirical test of the competition structure of the data-driven online platform is still less. This research is trying to reveal market allocation structure of the personal data resource of China's car-hailing platforms competition by the empirical data analysis.

This research is applying the social network analysis by R packages, which include k-core decomposition and multilevel community detection from the data connectedness via the decompilation and the examination of the application programming interface of terminal applications.

This research has found that the car-hailing platforms, which establish more constant personal data connectedness and connectivity with social media platforms, are taking the competitive market advantage within the sample network. Data access discrimination is a complementary method of market power in China's car-hailing industry.

This research offers a new perspective on the analysis of the multi-sided market from the personal data resource allocation mechanism of the car-hailing platform. However, the measurement of the data connectedness requires more empirical industry data.

This research reveals the competition structure that relies on personal data resource allocation mechanism. It offers empirical evidence for governance, which is considered as the critical issue of big data research, by reviewing the nature of the data network.

It also reveals the data convergence process of the social system and the technological system.

This research offers a new research method for the real-time regulation of the car-hailing platform.