Industry Cluster Research Articles

Investment Priorities for Technological Breakthroughs Based on Scale Effect

The article presents an analytical approach to calculating the value of technological scale effect in regional industry clusters using econometric models. This approach allows for the identification of production zones in Russia with the highest technological potential. The authors propose a method for calculating investments based on the traditional investment multiplier. This method enables rapid technological advancements in specific regional and sectoral clusters within the country. The methodology has been tested on two groups related to the agricultural sector: the main group and the control group, each consisting of seven territorial entities of the Russian Federation. The article also discusses the implementation of a selective investment policy to foster economic growth and enhance the performance of existing advanced industries.

Relationship lending and the role of loan officers in China: Empirical analysis based on the data on companies in industrial clusters

Relationship lending refers to lending behavior in which a financial institution makes loan decisions based on the accumulated soft information on the borrower. Empirical studies have revealed the positive effect of relationship lending. However, questions concerning who generates and accumulates soft information and in what ways in China have never been analyzed empirically. This paper empirically aims to explain whether loan officers generate soft information in relationship lending using data collected through surveys conducted among SMEs in the apparel industry clusters in Zhejiang and Jiangsu provinces. Based on the results of this study, relationship banking in China, which deals with the role of loan officers, seems even more important than is generally recognized.

Cross-industry innovation for sustainable repositioning through cluster collaboration

ABSTRACT Recent literature on sustainable transitions seeks to bridge macro – and micro-level dynamics; this study examines how agents at different levels interact, and what implications these lower-level dynamics have on sustainable repositioning. A new normal characterized by frequent industry crises, coupled with green policy initiatives, creates push and pull opportunities for sustainable repositioning; thus, incumbent firms must continuously adjust to changing conditions. Cross-industry innovation (CII) has emerged as a favorable option for sustaining competitiveness. To illustrate this development, this study provides insights into how firms from the oil and gas industry attempt CII in the aquaculture industry based on cluster-to-cluster collaboration and facilitation. Our findings indicate a form of tandem development for both industry clusters and incumbent firms, with the cluster responding to bottom-up changes in its firms. Moreover, cluster collaboration lowers initial CII obstacles in terms of knowledge and entry points and offers a gateway for incumbent firms looking to enter different industries. This facilitates an outbound and coupled CII that emerges to maintain a knowledge continuum for incumbent actors within sustainable repositioning. On a larger scale, these cluster initiatives can act as agents for stepwise sustainability transitions and further evolve into a cross-industry cluster.

Start Switch for Innovation in “Construction Sequencing”: Research Funding

Clusters of knowledge-intensive industries and manufacturing industries form industrial agglomeration in Step I and activate innovation in Step II. Industry clusters are formed by building segments. “Construction sequencing” in the construction industry refers to the process of determining the sequence of segments to optimize a project’s resources, budget, and scheduled timeline. The process usually begins by dividing a project into segments. Urban segments consist of public spaces, airports, factories, health, housing, etc. A “segment” is a component of a cluster; the organization of a cluster consists of constructing segments. These segments can be divided into four main categories: human resources, physical infrastructure, institutions, and the living environment. Each segment has a specific function in the process of building a cluster. This study focused on innovation in Step II and extended the Fujita–Thisse model of spatial economics to hypothesize that research expenditure per researcher leads to value being added. The Granger causality was tested for the knowledge and manufacturing industries in nine major countries including China and the U.S. The results showed that the hypothesis was significant in identifying the starting segment of innovation in Step II. Accordingly, it can be concluded that research funding is the start switch that triggers innovation. The policy implication is that activating innovation in cluster policies begins with the establishment of a research fund for researchers in its assigned clusters.

Green technology diffusion mechanism in China's aviation industry cluster based on complex network game model

The aviation industry cluster's diverse strategic choices of firms significantly influence the green technology diffusion. To examine how external factors and intra-cluster associative structures influence green technology diffusion, this paper constructs an evolutionary game model of green technology networks based on small-world networks, integrating governmental regulation and public oversight perspectives. Through simulations within the real-world aviation context, we analyze the dynamic characteristics of green technology diffusion. Furthermore, we investigate the driving effects of governmental and public initiatives in facilitating green transformation of aviation manufacturing firms. The empirical results reveal several critical insights: (1) A government-mandated minimum threshold for environmental subsidies is crucial to propel the green technology diffusion. In scenarios where environmental regulation penalties are inadequately low, speculative behaviors among firms occur, hindering the diffusion process. (2) Amplifying public engagement significantly bolsters the rate of green technology diffusion and augments the average returns for firms. The public's tolerance threshold for environmental pollution exhibits a high sensitivity to the success of green technology diffusion. (3) We discern variances in green technology diffusion across different network types. While green technology successfully permeates scale-free networks with diverse densities, its diffusion is notably impeded in small-world networks with lower densities. The associative structures and hierarchical distribution of firms within clusters drive varying outcomes in green technology diffusion.

The Future of Work: A Human-centric Approach to AI, Robotics, and Cloud Computing

This study investigates the impact of artificial intelligence (AI), robotics, and cloud computing on the future of work, focusing on adoption trends, productivity gains, and ethical challenges. Using a mixed-method approach, data were sourced from the OECD AI Policy Observatory, Pew Research Center, and European Union Open Data Portal. Quantitative analysis included K-Means clustering of industries based on technology adoption, with high adopters like North America and Europe leading in cloud computing (65.87%), and Africa showing stronger AI adoption (63.02%). The analysis also highlighted a 14.5% productivity increase in manufacturing, but a 19.3% risk of job displacement. Sentiment analysis revealed that 75% of public sentiment on algorithmic bias was negative, correlating strongly (0.74) with reported violations. The study affirms the need for improved AI governance and stronger GDPR compliance to address ethical challenges, while prioritizing human-centric strategies that ensure inclusive and sustainable outcomes for the workforce.

Digital Economy and Urban Carbon Emissions: A Quasi-Natural Experiment of the National Big Data Comprehensive Pilot Zone in China

In this study, we assess the impact of digital economy development on urban carbon emissions using a difference-in-differences (DID) approach based on the quasi-natural experiment of the national big data comprehensive pilot zone (NBDCPZ) policy and panel data from 168 prefecture-level cities in China from 2006 to 2019. We find that the establishment of NBDCPZ has a significant carbon emission reduction effect. This finding is robust to various sensitivity tests. Further mechanism validation illustrates that the construction of NBDCPZ promotes the regional digital development level and reduces urban carbon emissions through three channels: improving energy efficiency to optimize energy consumption, increasing green total factor productivity, and promoting the clustering of high-tech industries. The heterogeneity analysis concludes that the carbon emission reduction effect of NBDCPZ policy varies with different regional locations and different city characteristics. Moreover, using spatial models, we find that the positive impact is characterized by spatial spillover effect. The findings provide detailed empirical evidence to formulate urban development strategies for enabling carbon reduction of the digital economy. JEL Classification: O30, Q53, Q55, Q58, R10

Industry clusters and firm performance: Evidence from the leather product industry in Addis Ababa

Industrial clustering is the co-location of firms in a geographic area, which can lead to numerous economic benefits such as joint resources and knowledge pooling, R&D collaboration, technology sharing, and joint marketing. This study aims to examine the influence of industrial clustering on the performance of firms in the leather and leather products industry in Addis Ababa. Moreover, this study aims to investigates whether innovation capacity and collaboration networks indirectly contribute to the relationship between clustering factors and firms' performance. In this study, both primary and secondary data were collected for analysis. Partial Least Squares Structural Equation Modeling was employed to explore the impact of clustering on performance in terms of innovation, job creation, attracting investment, export intensity, and productivity growth. This study found that a one-unit increase in cluster factors is associated with a 0.43-unit increase in firm performance. The mediation analysis revealed that collaboration networks mediate the relationship between cluster factors and firm performance by 0.21 and innovation capacity mediates the relationship between cluster factors and firm performance by 0.15 units. The findings indicate that industrial clusters strongly influence firm performance within the leather industry in Addis Ababa. Therefore, the results suggest that innovation capacity and collaboration networks are mechanisms through which industrial clusters affect firm performance. Future researchers should explore the cluster effect in other industrial sectors and regions to validate the research findings.

Standardization Efforts for Ayam Goreng Kalasan Industry Cluster Through a Partnership Between the University and Local Government to Maintain its Local Wisdom

A community service partnership is carried out between a universityand a local government to standardize processes and products produced by theAyam Goreng Kalasan industry cluster. Efforts are made through a series offocused discussion activities, knowledge sharing, and material provision, as wellas training and mentoring on aspects of standardization, product diversification,and promotion toward marketing with a broader scope. The first three stageswere carried out with the involvement of local government. The results ofthe community service implementation were measured using a comparison ofknowledge of business actors before and after the implementation of the activities.A total of 31 business actors, as members of the Ayam Goreng Kalasan MajuMakmur industry cluster, have participated in this activity. Increased knowledgeis observed in all aspects: standardization, diversification, management, andmarketing. The collaboration between the university and the local government,therefore, can increase the participation of business actors, accelerate the requiredstandardization and certification process, and further increase the possibility ofsustainability of cluster business development.

Research on the Competitiveness Evaluation of Rural B&B Cluster Based on GEMS Model——Taking Pengzhou Longmen Mountain Jianjiang River Valley Eco-tourism Area as an Example

In the context of rural revitalization, the rural B&B industry demonstrates notable dynamism and exhibits a tendency towards clustering. Using the GEMS model, the competitiveness of the local rural B&B industry cluster is evaluated at four levels: foundation, enterprise, market and environment. The findings indicate that the rural B&B industry cluster in the Pengzhou Longmen Shan Jinjiang Valley Eco-tourism Area exhibits certain competitive advantages. However, there is potential for enhancement at the market and enterprise levels. Consequently, recommendations for promoting the sustainable development of the cluster are proposed.

Industry clusters and macroeconomic (in)stability

Abstract While the competitive behavior of firms with regard to entry and exit activities serves as a driving force behind the business cycle, little attention has been paid to the issue of industry clusters when discussing belief-driven cyclical fluctuations. Faced with this deficiency, this study analyzes the possibility of the emergence of equilibrium indeterminacy from the perspective of industrial organization. By analyzing the effects of endogenous overhead costs in the market, this paper finds that belief-driven business cycle fluctuations are related to industry clusters. More specifically, a stronger spillover effect or a less pronounced congestion effect tends to increase the likelihood of local indeterminacy.

Prediction of Market Share of Different Vehicle Powertrains on Interprovincial Highways amid the Development of Urban Agglomerations

In the coordinated development of urban agglomerations in China, inter-city connections within urban agglomerations have been gradually strengthened, with more interprovincial highways built. Given the complex geological conditions, interprovincial highways often require tunnels. The construction of tunnel ventilation facilities needs to take into account the types of vehicle, traffic flows, and the market share of different vehicle powertrains using the highways. This paper aims to develop a method to predict the future market share of the powertrains of different types of vehicle on the interprovincial highway. The paper builds a policy cluster by analyzing the regional policies for new energy vehicles and then builds a parameter cluster by summarizing industry reports, expert opinion, and policy clusters to predict the market share of different vehicle types categorized by powertrains. Finally, based on the historical vehicle stock data, and using vehicle sales and scrappage rate models, the paper builds a future stock cluster to estimate the annual stock share of different vehicle powertrains up to 2045. The paper applies the method to the interprovincial highway S7 in the Yangtze River Delta urban agglomeration. It obtains the future trend of the market share of the powertrains of different vehicle types on S7 in the target year, validating the model. The results show that the share of new energy vehicles on the S7 highway will increase gradually until 2025. Electric vehicles will dominate the growth, with light trucks forming the highest proportion, followed by cars, and finally buses and heavy trucks.

Based on Gated Recurrent network analysis of advanced manufacturing cluster and unified large market to promote regional economic development

This study evaluates the catalytic effects of advanced manufacturing industry clusters and unified large markets on regional economic development from a computer science perspective, revealing their underlying mechanisms. It employs a Gated Recurrent Network (GRN) model optimized with Gradient Boosting Decision Tree (GBDT) technology to conduct empirical analysis through comprehensive data collection and analysis. The primary objectives are to assess these catalytic effects, highlight the importance of innovation and environmental indicators, determine the contribution levels of various factors, and test the computational fit and predictive accuracy of the model. Key findings indicate that the GBDT-GRN model demonstrates a significant improvement in data computation accuracy, ranging from 20% to 52%, and an increase in response time by 23% to 52%. The model achieves a computational fit of 92% to 99% when analyzing regional economic development. The proposed GBDT-GRN model is highly accurate and reliable in evaluating catalytic effects, providing strong support for policy-making and business decision-making. Innovation and environmental indicators play a crucial role, with varying contributions from different factors. This study offers an effective solution for sequence data prediction problems, supports policy-making and business decisions, and points to promising directions for future research.

Leveraging Large-scale AI Models for Transforming China's Marine Industry: A TOE Framework Analysis

As an important driving force leading a new round of scientific and technological revolution and industrial change, artificial intelligence is becoming a hot spot. Promoting the deep integration of "artificial intelligence + ocean" will help build a world-class Marine artificial intelligence industry cluster with global competitiveness. How to effectively apply artificial intelligence to the Marine industry to solve the problems of resource redundancy and information island caused by industrial agglomeration is urgent for innovation and breakthrough. In this paper, TOE and modified T-TOE framework are used to analyze the above problems, and the following conclusions are drawn: 1) From the perspective of technical factors, intelligent information technology plays an important role in promoting the construction of large-scale models at the level of hardware and software; From the perspective of organizational factors, enterprise digital transformation and open sharing platform play an important role in supporting organization construction. From the perspective of environmental factors, policy support and market orientation play an important role in encouraging the construction of large models. 2) From the perspective of T-T, the breakthrough and application of technology need to balance the contradiction between development and conflict; From the perspective of T-O, intelligent supply-demand matching and transition resistance have both positive and negative effects; From the perspective of T-E, there is a problem of actively promoting multidimensional interactive innovation and achieving a balance. Relevant studies provide new ideas for the comprehensive development scenario of Marine industry and inject new impetus into the development of Marine industry.

Pollution Characterization and Source Apportionment of Volatile Organic Compounds and Their Odor-causing Species in Industrial Parks

To improve the phenomenon of the volatile organic compounds （VOCs） odor pollution nuisance in industrial parks and to promote the synergistic control of atmospheric VOCs and their odor-causing substances, based on the field observation of atmospheric VOCs in residential living areas and five different types of industrial clusters in industrial parks, we analyzed the pollution characteristics of atmospheric VOCs and their odor-causing volatile organic compounds （O-VOCs） in the residential living areas and each industrial cluster, evaluated the characteristics of the odor activity of the O-VOCs in the industrial parks, and identified the key odor-causing species and their main sources. The results showed that the mean values of atmospheric φ （TVOCs） and φ（O-VOCs） in the residential living area of the industrial park were 102.57×10-9 and 72.33×10-9, respectively. φ（TVOCs） and φ（O-VOCs） were significantly higher in the industrial clusters of basic chemical industry and pharmaceutics than in the other industrial clusters, and the sum （OAVsum） and maximum （OAVmax） of the odor activity values of these two clusters were relatively high, with a potential risk of odor nuisance. Overall, the O-VOCs species with higher odor intensity were similar in residential living areas and the five industrial clusters, and effective control of O-VOCs species such as acrolein, p-diethylbenzene, p-xylene, and 1,3-diethylbenzene is essential to mitigate or eliminate organic odor pollution. The results of the source apportionment of O-VOCs in the residential area showed that the sources of O-VOCs in the residential area were mainly influenced by natural gas chemical and pharmaceutics, and the coefficients of divergence （CDO-VOCs） between the O-VOC chemical profiles from residential areas and those from natural gas chemical and pharmaceutics were 0.31 and 0.38, respectively. Principal component analysis （PCA） also confirmed this result, with residential O-VOCs mainly originating from natural gas chemicals and pharmaceutics, followed by iron and steel manufacturing and automobile manufacturing, with the lowest contribution from the basic chemicals.

The Development of Industrial Agglomeration in Industrial Designation Areas and its Impact on Land Use Change (Case Study: Pringsurat Subdistrict and Kranggan Subdistrict, Temanggung Regency)

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>Industrial agglomeration refers to the clustering of industries in a specific region, where they are in close proximity and have interconnections. This phenomenon not only stimulates the growth of industrial activities, but also influences the development of other economic sectors. As industrialization expands, it gradually extends into rural areas that usually have abundant undeveloped land primarily used for agriculture. Consequently, this trend prompts a transition from agricultural to industrial land use. Pringsurat subdistrict and Kranggan subdistrict are located in Temanggung Regency, Central Java Province. Both of these subdistricts are designated as Industrial Designation Areas (KPI) according to the Temanggung Regency Spatial Plan 2011-2031. The plan has implications for the rapid development of large and medium industries. The purpose of this study is to examine the growth of industrial agglomeration in Pringsurat subdistrict and Kranggan subdistrict and their impact on agricultural land conversion. This research was conducted from 2023 to 2024 and utilizing data from 2021 and 2022. The approach of this research is descriptive quantitative and utilizes spatial analysis with Geographic Information Systems (GIS) and descriptive analysis techniques. Based on the results of the analysis, there is an agglomeration of large and medium industries in Pringsurat subdistrict and Kranggan subdistrict. The growth of agglomeration encourages the establishment of new industries and industry linkages. Furthermore, agglomeration growth has led to changes in land use, an increase in the variety of land uses, and an increase in land prices. Results of the analysis also show that there are regulatory changes in the development of industrial agglomeration that will affect to local government decision in the future. </span></p></div></div></div>

Determinants affecting the current state and perspectives of development of textile and clothing industry clusters within the European Union

The textile and clothing industry is one of the oldest industries ever, as the need for clothing is as old as human existence itself. Of course, the challenges and problems it faces are connected with this, currently primarily the environmental burden, the need for digitization, low wages for workers as well as the protection of brands and the development of the grey economy. With its positions, the European Union declares its interest in solving these issues. Many traditional companies are undergoing changes and there is a natural need for innovation, thus the textile and clothing industry is interfering with the creative industry. The barriers to innovation in this area are frequently small and medium-sized enterprises, which cannot solve many things and be competitive compared to large enterprises, but their flexibility and quick response to the changing needs of customers and the market give them advantages compared to the big ones. The possibilities of how smaller businesses can succeed and compete even in the long term are through clusters, which will provide them with the necessary scope, strength, and research, but at the same time keep them independent. In our contribution, we tried to find out the perspective of the development of textile and clothing industry clusters in Europe given the existing market situation and consumer expectations.

Research Hotspots and Development Trends on JIT Production Mode

JIT production mode plays an important role in production operation management in China. At present, the JIT production method in China has begun to take shape, but there are still some research directions that are not clear, and there are few achievements in using visualization methods to study new energy industry clusters. This article analyzes the relevant research literature on JIT production mode from 2003 to 2023, sorts out the research hotspots and evolution trends, and shows that: (1) domestic research on JIT mode has been ongoing since 2003, and with the continuous deepening of the market economy, JIT production mode is still a key consideration for enterprise production and operation; (2) The trend of refining the focus of research on JIT production mode; (3) The research on JIT production mode is still in the preliminary development stage, and the indicator system needs to be improved.

Do employee-friendly practices affect inventory leanness?

ABSTRACT We examine the impact of employee-friendly practices (i.e. employment quality, training and development, and employee turnover) on inventory leanness. We use the Empirical Leanness Indicator (ELI) as a proxy for inventory leanness. We employ OLS estimates to estimate our regressions while controlling for country, industry, and year-fixed effects and clustering standard errors at the firm level. We use alternative approaches to address endogeneity issues, such as the instrumental variable and the Heckman two-stage approaches. Our results suggest that employee-friendly practices improve inventory leanness. Our findings suggest that firms should invest in employee-friendly practices. This policy implication is of paramount importance for firms with more employees working in roles involving inventory (as opposed to automation or non-labour methods) and in environments with high dynamism and complexity. We also suggest that reputation mediates the relationship between employee-friendly practices and inventory leanness.

Analysis Of Strategies for Strengthening the Online Game Industry Using an Industrial Cluster Approach

Based on data, as one of the creative economy sectors, the game industry has much potential to boost the Indonesian economy. The total market value of the games industry in Indonesia is US$ 1.92 billion or 25 trillion rupiah. However, Foreign developers from Europe and the US dominate the games industry market in Indonesia, making Indonesia only able to contribute 0.49% of total revenue. This research aims to map Indonesia's game industry players, analyse its ecosystem's environmental determinants, and formulate effective industry development strategies. This qualitative research uses interview methods with key informants, observation, and literature study, with purposive sampling as a sampling technique. The results show that the core industry value chain of the game industry cluster consists of Game Developers and Game Publishers and is supported by Supply industries (hardware providers, HR, digital content, and financial services) and supporting industries (marketing, logistics, law, and networks). There are related institutions/institutions such as the Ministry of Tourism and Creative Economy, the Coordinating Ministry for Maritime and Investment Affairs, the Ministry of Communications and Informatics, the Ministry of Education and Culture, and the Indonesian Game Association. This industry is also related to animation, music, e-sports and tourism. This value chain ends with buyers. This research recommends concrete steps for relevant agencies to enhance the gaming industry ecosystem through human resource development, increasing access to financing, promotion and providing technological infrastructure. Collaboration across industries is expected to increase the global competitiveness and contribute significantly to the national creative economy.