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Agricultural science and technology (AST) often need the form of industry-university-research cooperation in successfully completing breakthrough agricultural technology innovations. Therefore, AST industry-university-research cooperation is not only the need of the AST development strategy in China but also the only way for the development of agricultural colleges and universities, agricultural scientific research institutions and agricultural enterprises. Among them, in the process of cooperative breakthrough agricultural technology innovation, the correct selection of partners is the basis for ensuring its effective operation.

Aiming at the time-series characteristics and information ambiguity of decision information in the dynamic selection process of AST industry-university-research partners, this research introduces the dynamic intuitionistic fuzzy multi-criteria decision-making method of time degree and orthogonal projection. On this basis, field theory is used to construct the cooperative innovation capability field model of the partners, and the threshold for the partners to enter or exit the system is designed to dynamically select and eliminate the partners.

Results show that this method fully considers the situation of cooperative innovation resources within the AST industry-university-research system and the resource complementarity of candidate partners.

Combined with examples from agricultural scientific research institutions, the applicability and superiority of the model are verified.

The role of intermediate urban centers (IUCs) (like towns/small cities/rural counties) between large cities and villages in leading urbanization has been increasingly highlighted. This article conceptually and empirically examines what types of industrial agglomeration (specialized or diversified agglomeration) of rural county in China would provide a more inclusive and efficient local labor market for rural workers to be inclusively urbanized.

We employ a three-stage labor supply model to theoretically generalize the decisions of rural workers to migrate to large city, to undertake nonfarm jobs in rural counties and the length of nonfarm jobs. Then, combining three national-level datasets of China (National Economic Census (NEC), China Household Income Project (CHIP) and the China county statistical yearbook), we explore how the type of industrial agglomeration in a rural county affects the labor supply decision of rural workers.

We show that rural workers in rural counties with higher level of industrial specialization are more likely to: (1) work locally than migrating to large cities; (2) find nonfarm jobs by themselves instead of relying on social networks (3) find a more stable and formal nonfarm job. These effects are significant when rural counties specialize in industries that they have local comparative advantages compared to large cities. This work provides insights into achieving inclusive urbanization by developing industry specialization in rural counties in China, which may also be useful for other developing countries.

First, the conceptual framework of this paper extends the basic model of rural-urban migration longstanding in the literature, to a multi-choice and three-stage labor supply model. Second, we empirically quantify the industrial structure of rural counties using unique dataset, which has been emphasized in the development economics literature but neglected due to data limitations. Third, this paper expands our understanding of the role of rural counties in inclusive urbanization and contributes to the future development of the county-led urbanization policies.

Defining and validating a map of related technologies is critical for managers, investors and inventors. Because of the increase in the applications of and demand for semiconductor lasers, analyzing the technological position of developers has become increasingly critical. Therefore, the purpose of this study is to adopt the technological position analysis to identify mainstream technologies and developments relevant to semiconductor lasers.

Correspondence analysis and k-means cluster analysis, which are data mining techniques, are used to reveal strategic groups of major competitors in the semiconductor laser market according to their Patent Cooperation Treaty (PCT) patent applications.

The results of this study reveal that PCT patent applications are generally obtained for masers, optical elements, semiconductor devices and methods for measuring and that technology developers have varying technological positions.

Through position analysis, this study identifies the technological focuses of different manufacturers to obtain information that can guide the allocation of research and development resources.