Industrial Layout Research Articles

Research on Vocational Regional to Development by Vocational Education

Zhejiang province of China has a large economic aggregate, optimized industrial structure, balanced regional development pattern, transformation and upgrading of industrial layout, along with excellent business environment and urban-rural integrated development. For decades, through the training of technical talents which directly meets the needs of regional economic development; deepens the cooperation between schools and enterprises, provides skilled personnel support for economic and social development, and promotes regional cooperation and foreign cooperation. Taking Zhejiang Province as an example, this paper discusses how vocational education promotes the regional economy, and analyzes the existing problems and future prospects.

Refined Identification of Urban Functional Zones Integrating Multisource Data Features: A Case Study of Lanzhou, China

Identifying urban functional zones is one of the important foundational activities for urban renewal and the development of high-quality urban areas. Efficient and accurate identification methods for urban functional zones are significant for smart city planning and industrial layout optimization. However, existing studies have not adequately considered the impact of the interactions between human activities and geographical space provision on the delineation of urban functional zones. Therefore, from the perspective of integrating the spatiotemporal characteristics of human activities with the distribution of urban functional facilities, by incorporating mobile signaling, POI (point of interest), and building outline data, we propose a multifactorial weighted kernel density model that integrates ‘human activity–land feature area–public awareness’ to delineate urban functional zones quantitatively. The results show that the urban functional zones in the central city area of Lanzhou are primarily characterized by dominant single functional zones nested within mixed functional zones, forming a spatial pattern of ‘single–mixed’ synergistic development. Mixed function zones are widely distributed in the center of Lanzhou City. However, the area accounted for a relatively small proportion, the overall degree of functional mixing is not high, and the inter-district differences are obvious. The confusion matrix showed 85% accuracy and a Kappa coefficient of 0.83.

Spatial distribution characteristics and influencing factors of youth soccer specialty schools in China

Youth soccer specialty schools are the primary project to strengthen the foundation of soccer talents, improve the level of soccer development, and achieve the dream of Chinese soccer. Taking 32,775 soccer specialty schools in China as the research sample, ArcGIS spatial analysis technology is used to explore the spatial distribution characteristics of soccer specialty schools and their influencing factors. The analysis shows that the overall distribution of the country forms five quantity concentration area and eight high-density core areas, with a high degree of spatial concentration and significant differences between the East and West. The factors influencing soccer specialty schools include nine factors in four dimensions: historical development, geographical environment, socio-economic, and educational resources. It was found that geographic environment and socio-economy provide the foundation and background for developing educational resources. However, the direct role of educational resources is more significant in a specific educational program, such as soccer specialty schools, followed by socio-economy and geographic environment. This study comprehensively analyzes and interprets soccer specialty schools’ spatial distribution characteristics and influencing factors. These results enrich the research on the spatial layout of sports, providing necessary theoretical support and practical references for the layout and high-quality development of related industries in China and other countries or regions.

Research on Empowering High Quality Development of Xinjiang Cotton Textile Industry with New Quality Productivity

In recent years, the uncertainty risk of the international cotton textile market has increased. The cotton planting and textile industry in Xinjiang, China still has shortcomings in cotton variety selection, mechanized planting and harvesting, agricultural environmental protection, and product processing and sales. It is urgent to enhance the resilience of the cotton textile industry supply chain to resist market risks. The characteristic of new quality productivity is innovation, and the key lies in quality. New quality productivity can empower the high-quality development of Xinjiang s cotton planting and textile industry from three aspects: new materials, new technologies, and new business models. New quality productivity, through technological innovation, can strengthen the cultivation of high-quality cotton varieties in Xinjiang, enhance the digitalization level of the cotton textile industry, optimize the structure and layout of the textile industry, and thus achieve high-quality development of the cotton textile industry in Xinjiang.

Optimization of industrial layout in airport economic zone through government-enterprise interaction

To avoid the issue of industrial layout plans in Airport Economic Zones (AEZs) being hard to implement due to mismatched the land supply and demand, it is necessary to clarify industrial layout factors that the government (land supplier) and locating enterprises (land demanders) focus on. This study constructs a AEZ's industrial layout optimization model from the government's perspective and enterprises’ locating utility. Based on the Gale-Shapley algorithm, aiming at eliminating blocking pairs, we establish government-enterprise interacting rules and coordinating mechanisms, corresponding to two types of government-enterprise interactions, namely public consultation and investment promotion joint meeting. According to government transparency and enterprise participation, the optimization model and Agent-Based Model are adopted in the combination to simulate the government-enterprise interactions in the decision-making of industrial layout in AEZ, under two interaction rules of “enterprises provide feedback in one go - the government makes revisions in one go” and “enterprises provide feedback one by one - the government makes revisions one by one”, respectively. By analyzing the changing curves of their objective functions, the equilibrium point where both parties can reach an agreement is identified, and the industrial layout scheme in AEZ is determined that will be mutually accepted. It is found that positive interaction with high government transparency and high enterprise participation will help improve the rationality of the industrial layout in AEZ, maximizing the efficiency of spatial allocation of elements and resources.

Dynamic evolution and influencing factors of internal and external synergy in China's energy industry: From the perspective of industrial chain

The distortion of factors between the upstream and downstream of the energy industry, as well as the lack of collaborative models between it and the energy equipment manufacturing industry, impede the smooth achievement of the "dual-carbon" goal, and industrial synergy can better solve this problem. From the perspective of the industrial chain, this study measures for the first time the level of internal and external synergies in the energy industry based on industrial data from 30 provinces in China from 2013-2022, and analyzes in depth the dynamic evolution of internal and external synergies in the energy industry and the factors influencing them. Using ArcMap 10.2 and the variance decomposition model, it is found that the upstream and downstream sectors of the energy industry have non-equilibrium in time and space, and their factor mismatch in resource-based regions is still more serious. Therefore, a state of synergy needs to be created between upstream and downstream sectors, between the energy industry and the energy equipment manufacturing industry. Using each of the status quo maps as well as the Kernel model, it was concluded that external synergies decrease and then increase, with a gradual decrease in the gap between regions. However, internal synergies show an upward and then downward trend. Meanwhile, the results of the GTWR model show that the effects of various influences on internal and external synergies are not only positively or negatively different, but also spatially more unbalanced. It should accelerate the promotion of policy guidance, actively cultivate the external environment, rationalize the layout of regional industries, and promote the synergistic development of the energy industry internally and externally.

How artificial intelligence affects international industrial transfer ——Evidence from industrial robot application

The development of high technology represented by artificial intelligence is an essential driver of international industrial transfer. Using country-industry-level industrial robot data and value-added trade data from 2002-2018, this paper empirically examines the impact and mechanism of artificial intelligence on the international industrial transfer undertaken by a country (region). The study shows that the application of artificial intelligence can significantly enhance the international industrial transfer undertaken by a country (region). Further analysis shows that artificial intelligence positively affects international industry transfer through two channels: Improving the quality of labor force and promoting the level technological innovation. Further heterogeneity analysis shows that, first, from the economic development degree perspective, artificial intelligence's role in promoting developing economies is more substantial than that in developed economies. Second, the financial crisis has weakened the impact of artificial intelligence on international industrial transfer from the perspective of time division，especially in developing economies. Third, from the perspective of industry heterogeneity, artificial intelligence has significantly promoted the transfer of medium-low and medium-high technology industries. The research in this paper extends the analysis of the effect of artificial intelligence. It provides realistic insights for optimizing the strategic layout of the robotics industry, achieving industrial structure upgrading, optimizing resource allocation efficiency, and grasping the opportunities of global industrial chain restructuring.

Characteristics, drivers and ecological risk assessment of microplastics in the surface water of urban rivers in Guangdong-Hong Kong-Macao Greater Bay Area cities - A case study of Dongguan city

In the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), microplastic pollution in urban rivers is a prominent problem due to the developed economy and high industrial intensity. Using the Xiaohai River, Hanxi River and Dongguan Canal in Dongguan City, an important node city in the GBA, as an example, microplastic characteristics, drivers and ecological risks in the surface water of three rivers were investigated. Results showed that the average abundance of rivers in the wet period (1646.22 ± 154.73 items/m3) was 4.7 times higher than that in the dry period (351.09 ± 34.2 items/m3). Microplastics were mainly in the form of fragments and fibers, with a size range of 30–500 μm, and appeared transparent with white color. The microplastic polymer types PE, PP, PET and PA accounted for more than 70%. There are large differences in the characteristics of microplastic pollution during different hydrological periods. Redundancy analysis showed that the distribution of plastics, chemical materials, packaging and printing industries along the rivers dominated the differences in microplastic abundance. The electronic information industry contributed most to the composition of microplastic polymer types. The polymer hazard index, pollution load index, and potential ecological risk index for rivers indicate a medium-high risk classification or higher. Therefore, the industrial layout along the urban rivers should be rationalized, the disposal of microplastics in wastewater should be increased, and the use of green plastic products should be promoted. This study provides support for the management of microplastic pollution in urban surface water in the GBA.

The Impact of Population Aging from the Perspective of New Productive Forces: Empirical Evidence from 30 Provinces in China

The new quality productive forces are the important means to promote the high quality of Chinese economic development, which is driven by the innovation of science and technology, the layout of new industries and the development of regional links. In the context of China's aging, it is significant to research the influence of the aging population on the NQHP. Based on the data of 30 Chinese provinces between 2010 and 2022, this paper discusses the influence of population aging on NQF in China. The paper found that population aging hurts new quality productivity. The effect of population aging on NQF has the feature of regional heterogeneity, and the biggest negative influence on NQF is the eastern area, and the second is the northeastern area. In the middle and west area, the aging of the population has no negative influence on the new quality productive forces, and it has an obvious positive influence. By means of the intermediary mechanism, we find that the aging population can inhibit the growth of NQF by decreasing the proportion of TPL.

Study on Influencing Factors of Grain Supply Chain Resilience Based on DEMATEL-ISM Method

The essential requirement for the resilience and safety of the food industry supply chain is to achieve independent, controllable, safe, efficient, and sustainable development. Currently, and for a significant period in the future, the food industry supply chain faces several risks, primarily due to increased uncertainties. These risks manifest as the need for optimization in the layout of the food industry, prominent structural shortages, and a lack of full autonomy and control in key links of the industry chain. Such risks can potentially evolve into critical factors that restrict the resilience and security of the food industry supply chain. To effectively address these risks, this paper identifies 12 influencing factors based on four key capabilities of the food supply chain: forecasting ability, response-ability, adaptation ability, and recovery ability. An evaluation index system for the resilience of the food supply chain is constructed, integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) methodologies. Analysis of the interactions between these factors reveals that three factors, including supply chain visibility, are fundamental, seven factors, including the level of agricultural mechanization, are intermediate, and dynamic logistics and flexibility are direct factors. Based on these conclusions, this paper proposes several targeted recommendations to enhance the development of the food supply chain. These recommendations aim to improve the supply chain's resilience and ability to withstand potential risks.

The Impact of Digital Inclusive Finance on the Sustainable Growth of Income of Herdsmen in China’s Pastoral Areas

The sustainable growth of income for farming households in pastoral areas represents a crucial challenge not only for China but also for other developing nations in the process of transition to ecologically friendly models. The scarcity of assets available for collateral, along with vulnerable production conditions and developmental shortcomings, pose significant barriers to the consistent expansion of herdsmen’s income. This paper analyzes the impact of digital financial inclusion on the income of herdsmen in ethnic minority regions using panel data models from nine major pastoral provinces in China from 2011 to 2022. Through a fixed-effects model approach, the analysis delves into the influence of digital financial inclusion and subjects it to multi-dimensional and robustness tests to ensure the reliability of the findings. Furthermore, the research explores the underlying mechanisms through which digital financial inclusion contributes to income enhancement for herdsmen in these areas, employing mediation effect techniques to provide deeper insights into the relationship between digital financial services and economic upliftment in remote ethnic communities. The research findings indicate that digital financial inclusion has a positive impact on the income of herdsmen in ethnic minority regions. The breadth of coverage, depth of usage, and level of digitalization of digital financial inclusion all play a significant role in enhancing the income levels of herdsmen. In terms of the degree of influence, the impact of digital finance on the income of ethnic minorities follows this order: depth of usage > degree of digitalization > breadth of coverage. Notably, through financial backing that catalyzes a shift in herdsmen’s production methodologies and propels industrial upgrading, there is a profound potential to increase herdsmen’s output efficiency. This, in turn, alleviates the ecological strain on China’s environmentally delicate zones. Moreover, financial backing can condense the breeding periods for herdsmen, thereby ameliorating the ecological degradation associated with excessive grazing in pastoral regions. A mediating-effect analysis reveals that digital financial inclusion can boost economic development in ethnic minority regions by increasing wage income, raising per capita GDP levels, and promoting industrial structure upgrading. This, in turn, leads to an improvement in the income of herdsmen in these regions. This is particularly pertinent in China, where the eco-fragility of pastoral regions coincides with the modest income of herdsmen, underscoring the critical importance of herdsmen’s finance. To foster sustainable progress in these regions, financial backing is imperative to elevate herdsmen’s income and to induce a transformative shift in production approaches and industrial layout, paving the way for the sustainable development of these pastoral regions.

A Co-production system of cement and methanol: Unveiling its advancements and potential

Both the cement and methanol sectors face increasing pressure to reduce their carbon emissions to combat climate change. Coupling the production process can provide economic and environmental benefits when implementing breakthrough technologies in these industries. The advantages and application potential of the co-production system need to be assessed quantitatively in long-term decarbonization pathways. This study proposes a co-production system of cement and methanol that capitalizes on strong complementarity through bidirectional material flow. Multi-regional planning models are established to evaluate the spatiotemporal deployment of low-carbon technologies, including coupling technologies. The results demonstrate that the co-production system can achieve a 6.6% higher emissions reduction and a 21.2 % lower production cost of clinker by 2060 compared to implementing breakthrough technologies separately. The co-production routes may be widely distributed across China by 2060, accounting for 24.1 % of clinker output and 54.7 % of methanol output. Introducing coupling technologies can influence the industrial layout and trade patterns of China's cement and methanol sectors, carrying policy implications for the deployment of low-carbon technologies.

A study on the macro-micro two-stage site selection of electric-hydrogen hybrid refueling stations based on GIS and Fuzzy-TODIM

With the increasing global demand for clean energy and sustainable development, hydrogen energy has gained significant attention as an environmentally friendly energy carrier. Hydrogen refueling stations, serving as crucial intermediaries in hydrogen production, storage, transport, and refueling, play a pivotal role in the hydrogen energy industry's layout. A novel model for hydrogen refueling stations based on DC microgrids utilizing renewable energy sources for hydrogen production and refueling has become a focal point of interest. However, there is currently limited research on the site selection of electric-hydrogen hybrid refueling stations. Addressing current needs and research gaps, this study proposes a macro-micro two-stage site selection model based on DC microgrids. In the macro-level site selection stage, factors such as regional photovoltaic and wind resources, hydrogen energy policies, and the layout of the hydrogen energy industry are comprehensively considered, with Guangdong Province, China selected as the study area. ArcGIS is utilized to create thematic layers and establish constraints. The DEMATEL method is employed to determine the weights of macro-level site selection criteria. The results indicate that the most suitable areas are located in coastal regions. This study's site selection model offers a scientific and systematic approach to evaluating electric-hydrogen hybrid refueling stations in DC microgrids, providing a scientific basis for decision-making for governments and investors.

Study on Optimization of Land Use Structure in Fujian Province Based on Low-Carbon Perspective

Carbon peaking and carbon neutrality strategies are pivotal in addressing climate change. Optimizing land use structure is a fundamental approach to achieving low-carbon development within a given territory. This study focuses on Fujian Province as the research subject, predicting carbon emissions for the next decade by analyzing the correlation between land use types and carbon emissions using the gray model. This analysis is based on land use panel data spanning from 2007 to 2021. The study applies the FLUS-Markov model to simulate Fujian’s land use in 2030. A multi-objective optimization model is developed from a low-carbon perspective, integrating carbon emissions, economic, and ecological factors. The study explores land use under three scenarios: natural development scenario (NS), low carbon scenario (LCS), and comprehensive scenario (CS). Findings highlight the relationship between land use-related carbon emissions, urbanization, and relevant policies in Fujian. The FLUS-Markov simulations suggest that under the NS scenario, carbon emissions in 2030 will reach 77.829 million tons, an increase of 11.013 million tons from 2020. In contrast, the LCS demonstrates that optimizing land use structures can effectively balance carbon reduction, economic growth, and ecological preservation. Under the CS, 2030 emissions could be reduced by 7.2854 million tons while maintaining economic and ecological benefits. Despite variations in construction land expansion across these scenarios, all follow a “one belt, one core” development pattern. The study concludes with policy recommendations, including industrial layout optimization and clean energy promotion. These findings support the alignment of land use optimization with Fujian’s future development needs, offering guidance for land-use planning and policies focused on low-carbon objectives.

Microstructural and elemental analyses of slags excavated from the Gushishan iron‐smelting site, Sichuan Province, China

AbstractThe Shu Commandery was an important iron production center in southwest China during the Han Dynasty (202 BC‐AD 220). In 2007, archaeologists excavated a Han Dynasty smelting furnace (L1) at the Gushishan site and collected large amounts of smelting remains including slags, furnace bricks, and ores. Scientific analysis of the excavated slags was carried out to ascertain that the Gushishan site was a pig iron smelting site. No flux was used at the Gushishan site, and the site is dated no later than the Eastern Han period. No remains related to iron casting of the Han Dynasty was found at or near the iron smelting sites in southwest China, which indicates a separation between iron smelting and iron casting as characteristics of the industrial layout in this region.

English Translation of New Vocabulary for Text Analysis of New Energy Industry and International Evaluation of Power Quality

With the advancement of global energy transformation, the rapid rise of the new energy industry has become a strategic highland that countries are eager to seize. The inherent instability and unpredictability of renewable energy production pose significant obstacles to the seamless operation of the power system. To address these challenges, this article employs text analysis, data-driven methods, and artificial intelligence technology in neologisms to conduct an in-depth international evaluation and comparative research on the power quality of the new energy industry. Using text mining techniques to conduct an in-depth analysis of new energy policy texts in various countries, revealing their policy characteristics and trends. At the same time, the combination of data-driven and artificial intelligence technology enables more accurate prediction and decision analysis. Based on the findings of this study, the United States has achieved a significant 35% enhancement in the quality of new energy electricity over the past decade, attributed to its consistent monitoring and improvement initiatives. Meanwhile, Germany, owing to its robust monitoring system, has witnessed a 25% improvement in electricity quality in the last five years. However, in developing nations like India and Brazil, approximately 60% of new energy projects encounter challenges related to grid connectivity and scheduling, resulting in a deterioration of electricity quality. In contrast, only 20% of developed countries have issues with grid access and scheduling. This phenomenon reflects that developing countries still need to increase investment and improve the layout of new energy industries and the construction of power grid infrastructure. Developing countries should actively learn from the successful experiences of developed countries in the new energy industry and power grid construction, formulate appropriate policy measures based on their national conditions, improve the quality of new energy electricity, and promote energy transformation and sustainable development.

Impact of urban-rural development and its industrial elements on regional economic growth: An analysis based on provincial panel data in China

Urban-rural development is an important driving force for regional economic growth. The existing researches have studied this issue from various perspectives, but they ignore the impact of big data on the economy. In the post pandemic era, big data, as an emerging production factor, has a significant indicative effect in promoting urban-rural economic recovery and fostering new business forms. Therefore, fully considering the factor of big data can help reveal its impact mechanism on urban-rural economic growth in the post-epidemic period. Based on the data of 30 provinces and cities in China, this paper introduced big data on the basis of traditional models and constructed a multi-dimensional factor indicator system. At the same time, the panel regression model was established by using unit root test, Hausman test and precision test. Through benchmark regression and heterogeneity analysis, the impact of urban-rural development factors on economic growth was discussed. The results showed that the panel model passed all tests, and its regression error was stable below 5 %. Transportation, technology, and the three major industries can all promote positive economic growth, with a significance of 1 %. The three industries' contribution to economic growth ranks the third, second and first industries in order. In addition, the good ecological environment contributes to the benign economic growth during the study period. A 1 % increase in forest cover would drive economic growth by 0.215 %. But the impact of public's attention on the overall economy was an indirect effect manifested through its physical industries.The regional heterogeneity indicated that each element had different effects on economic development in eastern, central and western regions. Based on its results, this paper proposed suggestions for each region. In addition, this study found that the Internet attention reflected by big data did not directly drive economic growth, but affected economic growth through indirect channels such as information flow and resource allocation of real industries. This study provided data support for the existing theoretical review, and provided policy reference for the rational planning and industrial layout of China's regional economy.

Research on the Dynamic Evaluation of the Competitiveness of Listed Seed Enterprises in China

Seed enterprises are crucial for ensuring national food security, the driving force behind the seed industry’s advancement, and the core entity in constructing a modern seed industry system. At the micro and macro levels, agricultural seed enterprises face challenges and pressures in earning excess profits, enhancing their competitive edge, and resisting the incursion of multinational seed enterprises. This article selects panel data from 49 listed seed enterprises in China from 2015 to 2022 and uses methods such as global principal component analysis (GPCA) and Q-type cluster analysis to measure and evaluate the competitiveness of Chinese seed enterprises. Research has found that: (1) From 2015 to 2022, the overall competitiveness of listed Chinese agricultural seed enterprises has shown an upward trend. The competitiveness of agricultural seed enterprises can be further decomposed into operational capabilities, growth capabilities, production efficiency, technological innovation capabilities, etc. (2) The top ten agricultural seed enterprises in China have obvious advantages in operational and technological innovation capabilities, but their growth capabilities and production efficiency are insufficient. (3) Regarding the vertical comparison of the seed industry, the ranking of the competitiveness of Chinese listed agricultural seed enterprises from strong to weak is wheat seed enterprises > other seed enterprises > melon and vegetable seed enterprises > corn seed enterprises > rice seed enterprises. (4) Compared with international seed industry giants, there are various reasons why China’s top agricultural seed enterprises have weaker competitiveness, specifically reflected in research and development investment, scale and market share, industrial layout, and other aspects. The findings of this research offer empirical evidence to bolster the competitiveness of seed enterprises and advance the seed industry, while also aiding in fortifying the nation’s strategic oversight of the seed sector, bearing profound implications for safeguarding food security.

Higher risk of spring frost under future climate change across China's apple planting regions

Spring frost is one of major agro-meteorological disasters impacting apple production. Previous studies focused on the impacts of spring frost during the flowering period on apples, however, the frost events occurring at both pre- and post-flowering phases have significant impacts on apples. Our study employed four phenology models (parallel model, M1 model, sequential model, and growing degree hour model), along with their ensemble model driven by five global climate models (GCMs) to predict the key spring phenphases of apple across China’s apple planting regions under two emission scenarios (SSP245 and SSP585) during the 2050 s (2040–2069) and 2080 s (2070–2099). A new spring frost assessment index (FI) combining frequency and intensity of spring frost was developed to evaluate the impacts of climate change on spring frost risk of apple. The results showed a large spatial variation in projected spring phenophases across China’s apple planting regions. Projected budbreak (BBCH 09), initial flowering (BBCH 60), and final flowering (BBCH 69) would advance 5.6–15.9 days, 5.7–14.8 days, and 5.6–14.5 days, respectively, in regions I, II, and V of northern China apple planting regions. However, in regions III and IV of southern China apple planting regions, projected budbreak, initial flowering, and final flowering would delay –9.2–21.5 days, –7.5–20.6 days, and –6.8–20.8 days in the future climate scenarios, compared with the baseline (1980–2009). Projected last spring frost date considering the entire spring phenphases would advance 3.7–11.8 d in the future climate scenarios, compared with the baseline. Projected spring frost risk would increase in all the three growth stages including budbreak to initial flowering, flowering period, and final flowering to the last spring frost date across all the China's apple plating regions in future climate scenarios except southward China's apple plating region under the SSP585 in the 2080 s. Our study provides an important reference for early warning, prevention and mitigation of spring frost disasters, and the layout of the apple industry.

Current state and development trend of China's customized home furnishing industry

ABSTRACT Customization has become a new development trend in the furniture industry. Home customization can meet people's personalized needs and promote the innovative development of the furniture industry. This study combines the literature review and industry trend report to explore the development status of China's customized home furnishing industry. It analyzes the market scale, industrial layout, product penetration rate, industrial chain structure, and intelligent manufacturing equipment of this industry. The development characteristics of China's panel furniture machinery industry are as follows: lack of innovation in technology and equipment, market fragmentation and hierarchical, intelligent manufacturing equipment needs upgrading iteratively. As for the transformation and upgrading of China's customized home furnishing industry, the specific situation is summarized from the upstream, midstream and downstream of the industrial chain, mainly including raw and auxiliary material suppliers focus on terminal product research and development, integration of digital design and manufacturing technology, industry segmentation increases, and diversification of marketing channels. In the future, the customized home furnishing industry will build digital workshop, improve the standard system, emphasize the training of intelligent manufacturing professionals, and realize green and sustainable development. This study provides a reference for the world to understand the development of China's customized home furniture industry.