Sustainable development early warning and financing risk management of resource-based industrial clusters using optimization algorithms

PurposeThe purpose is to analyze and discuss the sustainable development (SD) and financing risk assessment (FRA) of resource-based industrial clusters under the Internet of Things (IoT) economy and promote the application of Machine Learning methods and intelligent optimization algorithms in FRA.Design/methodology/approachThis study used the Support Vector Machine (SVM) algorithm that is analyzed together with the Genetic Algorithm (GA) and Ant Colony Optimization (ACO) algorithm. First, Yulin City in Shaanxi Province is selected for case analysis. Then, resource-based industrial clusters are studied, and an SD early-warning model is implemented. Then, the financing Risk Assessment Index System is established from the perspective of construction-operation-transfer. Finally, the risk assessment results of Support Vector Regression (SVR) and ACO-based SVR (ACO-SVR) are analyzed.FindingsThe results show that the overall sustainability of resource-based industrial clusters and IoT industrial clusters is good in the Yulin City of Shaanxi Province, and the early warning model of GA-based SVR (GA-SVR) has been achieved good results. Yulin City shows an excellent SD momentum in the resource-based industrial cluster, but there are still some risks. Therefore, it is necessary to promote the industrial structure of SD and improve the stability of the resource-based industrial cluster for Yulin City.Originality/valueThe results can provide a direction for the research on the early warning and evaluation of the SD-oriented resource-based industrial clusters and the IoT industrial clusters, promoting the application of SVM technology in the engineering field.

The identification, logic and enlightenments of intra-urban place communities in China

Spatial agglomeration phenomena on the earth permeate in various fields of the natural and human world, yet their researches in human society are relatively few with the focus mainly on the economic concept of “industrial clusters”. Precise quantitative descriptions, in-depth logical analyses and proper application approaches for urban planning are lacked in various intra-urban spatial agglomeration phenomena. By using over 10 million POIs in the mainland China, 18 grid network models with two varieties of spatial relationships (co-location/adjacent) are constructed in this article. 23 typical place communities are extracted based on complex network analysis, and four types of agglomeration driving forces are summarized. A comprehensive demonstration displaying the application process of co-location/adjacent place matrices in auxiliary decision of the implanted place types is carried out with the example of the revitalization project of Taoxichuan Area in the city of Jingdezhen.

Developing high-quality human resources in quang ngai province (Viet Nam) currently

Currently, developing the high-quality human resources to meet the socio-economic development requirements of Vietnam in general and Quang Ngai province in particular is a very urgent need, is a very urgent need. This is a both fundamental and long-term issue in order to realize the strong and happy national aspirations. Located in the central key economic region with Dung Quat economic zone whose core is Dung Quat oil refinery, Quang Ngai is developing day by day. Presently, Dung Quat economic zone together with industrial clusters of the province have been creating a huge value of industrial output, especially heavy industry - an important spearhead industry in the process of industrialization, modernization, creating momentum to promote the development of industry and service in the whole region, and play an important role in creating the driving force for the development of the central region. Due to the specific requirements of industries with modern technology, Quang Ngai is required to have highly qualified and skilled human resources. Being well aware of this, Quang Ngai province has paid great attention to the development of high-quality human resources and initially achieved certain achievements over the past time.

SELECTED INNOVATION TOOLS IN DESIGNING PROCESS MANAGEMENT

This contribution deals with the specification of the current immunity of strategy and status and level of procedural management in special organizational structures referred to as industrial clusters. It represents selected specifics of the design and application of innovative tools, system integration, and agile project management of clusters. It describes and explains the context between the strategy, the organizational structure, and the need for project procedural management at the current position and competitiveness of clusters on the market in demanding energy and environmental conditions. In the end, it shall submit its own author's design scheme for a new organizational project aimed at a cluster structure and draft management process and coordination of clustered projects for their clients.

Prediction of Evolution and Development Trend in Sports Industry Cluster Based on Particle Swarm Optimization

Sports industry cluster refers to the economic phenomenon that sports related enterprises gather in a large number in a specific area. For the sports enterprises in the cluster, they can obtain huge competitive advantages through enterprise agglomeration, thus obtaining better development and rich economic benefits. The optimization of particle swarm optimization is interlinked with the agglomeration of industrial clusters. Therefore, in view of the limitation of the standard particle swarm optimization (PSO) algorithm, an improved particle swarm optimization algorithm-diaphragm particle swarm optimization (D-PSO) was proposed and used to simulate the formation of sports industry clusters. D-PSO introduces the cell membrane processing mechanism of the biological system into the PSO algorithm, which improves the ability of the PSO algorithm to get rid of local extremum points. The competitiveness value of the sports industry cluster is the value of the objective function solved by the D-PSO algorithm. The geographical coordinates of the industrial cluster were the locations in the particle search space of the D-PSO algorithm. The D-PSO algorithm is used to simulate the aggregation process of enterprises in the cluster. Compared with the standard PSO, the D-PSO algorithm has better convergence performance and optimal rate. The results of case analysis show that the proposed method can effectively predict the development trend of sports industrial clusters.

Influencing factors and paths of upgrading consumer goods industry in Shanghai: a FsQCA approach

PurposeThis study examines the factors that influence the improvement of the consumer goods sector in three dimensions (technology, internal factors and external environment) for exploring the upgrading paths of Shanghai's consumer goods industry.Design/methodology/approachThis paper targeted eight sub-industries of consumer goods as case studies, including food processing, and investigated from qualitative and quantitative perspectives using the technology-organization-environment (TOE) framework.FindingsThe study confirms the diversity of paths to promote the upgrading of the consumer goods industry in Shanghai, and three paths are summarized in this paper. The “human–environment” linkage upgrade path is to bring sufficient economic contribution to help industrial upgrading by expanding market share, and this path is suitable for large enterprises in the industry to adopt; the “internal factor aggregation” upgrading path is to strengthen the aggregation effect of resources, form industrial clusters and link high human aggregation with industrial aggregation to exert leverage to transform and upgrade the consumer goods industry, and this path is suitable for SMEs in the industry to adopt; the “technology–environment” linkage upgrade path is to use technological factors for product innovation to occupy a favorable market position, to obtain high economic returns and realize industrial upgrading under the joint action of technology and external environment, and this path is suitable for high-tech enterprises to adopt.Originality/valueShanghai still has a large area for growth toward foreign metropolises, under the backdrop of the strong development of new manufacturing. Also, to diversify their investment portfolio, the consumer goods industry should focus on population, job density and industrial growth while looking into industrial aggregation.

Chinese entrepreneurs and workers at the crossroad: the role of social networks in ethnic industrial clusters in Italy

PurposeThis paper aims to analyse the evolution of Chinese industrial ethnic clusters in Italy, by focusing on the role of social networks and the processes behind the phenomenon of Chinese worker exploitation and entrepreneur “self-exploitation”.Design/methodology/approachThe case study is a sub-cluster of micro and small enterprises owned by Chinese entrepreneurs within the leather industrial district of Florence, Italy. This research adopts the following mixed methods: a small-scale survey to capture the characteristics of the sub-cluster and a social network analysis to describe cluster evolution, complemented by life-course interviews conducted with key informants and entrepreneurs.FindingsMigrant social capital and social networks play a central role in the evolution of the case study sub-cluster. Social networks play a supportive role in migration, job creation, entrepreneurship formation and the creation of business opportunities. Simultaneously, they enhance the phenomenon of worker exploitation and entrepreneur self-exploitation. Furthermore, the more the business community grows, the more the economic performance of ethnic enterprises depends on agglomeration forces produced by the cluster.Practical implicationsThe findings suggest a series of potential policies to upgrade the ethnic enterprises' capacities, to increase their formality and inclusion in the Italian social and economic systems and sub-cluster.Originality/valueTo the authors’ knowledge, this paper is the first attempt to examine the evolution of social networks in relation to the phenomenon of Chinese worker exploitation and entrepreneur self-exploitation in an ethnic industrial sub-cluster.

The Impact of Innovative Industrial Cluster Policy on Regional Innovation: Evidence from a Quasi-Natural Experiment in China

As important carriers of local innovation activities, innovative industrial clusters are attracting increasing attention. Therefore, several countries have started promotion policies for innovative industrial clusters. However, there are few empirical studies on relevant policies. This paper investigates the impact of China’s “innovative industrial cluster pilot” (IICP) policy on regional innovation. Taking the implementation of IICP policy as a quasi-natural experiment and using the panel data of 266 prefecture-level cities in China in 2008-2019, this paper provides strong evidence that IICP policy promotes regional innovation. The conclusion still holds after a battery of robustness checks. The heterogeneity test shows that the promoting effect of IICP policy on innovation is more significant in central and western region than in eastern region. Moreover, the lower the city administrative level and the lower the dependence on natural resource, the more prominent the innovation effect of IICP policy. Further, the mechanism test shows that the IICP policy can promote regional innovation indirectly by strengthening government support for innovation and attracting the agglomeration of science and technological talents, but the mediation effect of industrial structure has not been verified.