Spatial Distribution and Functional Configuration of Industry 4.0 Enterprises: A Case Study of Germany

Abstract

The intersection of industrialization and urbanization has long been a driving force behind the development of urban industrial spaces. As technology and innovation continue to evolve, cities have adapted to accommodate various industries, shaping new spatial configurations alongside population growth and improved infrastructure.

Today, the fourth industrial revolution, propelled by disruptive technologies such as artificial intelligence, big data, additive manufacturing, and quantum computing, is reshaping our world. In this era of Industry 4.0, urban spaces must respond to the ongoing technological revolution.

This research delves into the spatial distribution characteristics of Industry 4.0 cities in Germany, exploring their relationships with Industry 4.0 enterprises and surrounding functional facilities. The aim is to establish a model for industrial spatial function configuration, providing insights for the development of urban industrial spaces.

The study primarily addresses two questions:

1. What spatial distribution characteristics do Germany's Industry 4.0 enterprises exhibit?

2. What patterns emerge in the industrial spatial function configuration of German Industry 4.0 enterprises?

To answer these questions, the research examines Germany's Industry 4.0 enterprise distribution from various dimensions, evaluating distribution status, density, and key locations across different cities.

The city of Stuttgart is selected as a focal point, investigating its Industry 4.0 enterprises alongside ten categories of urban industrial space functional elements. A quantitative analysis, utilizing multi-factor urban Point of Interest (POI) data, reveals correlations and characteristics among these factors, leading to the identification of functional configuration patterns for Industry 4.0 enterprises.

The distribution of Industry 4.0 enterprises in urban spaces exhibits distinct characteristics: they tend to cluster in major cities, particularly in city centers, while their presence is relatively limited in other areas, with a focus on industrial parks. These enterprises have close functional relationships within urban environments, particularly with higher education institutions, research organizations, logistics and warehousing areas, and industrial parks. They emphasize the "research and development (R&D) + production" paradigm, relying on research outcomes and striving for large-scale applications.

Regarding the allocation of functional facilities, the study identifies two key patterns: distance gradient and correlation. The distance gradient pattern reveals that the number of Points of Interest (POIs) around these enterprises varies with distance, showing five trends. Residential functions increase with distance, while others decrease. The correlation pattern indicates that Industry 4.0 enterprises have the weakest correlation with residential functions but the strongest correlation with cultural, sports, dining, and commercial and retail functions.

The findings of this study offer valuable references for the rational, scientific, and efficient planning and policymaking of industrial space construction in new cities and urban regenerations worldwide. By enhancing urban industrial spaces, we aim to facilitate future industrial planning, enhance the quality and efficiency of urban industrial areas, attract exceptional enterprises and talent, and promote the sustainable development of cities.