Reproduction of consumer spaces and historic district touristification in Old Beijing City

Abstract

With increasing globalization and consumerism, heritage tourism has contributed to local economic development, while over-tourism may have impeded experienced locality by residents and facilitated cultural alienation. To compensate for the dearth of cross-case comparisons and spatial quantifications using big data of existing research, this study constructed an enriched framework of space production theory integrating historic-sociological analysis and spatial analysis to connect the process and outcomes of consumer space reproduction in historic districts in Old Beijing City. Following a historical analysis of social interrelationships in the consumer space reproduction process, binary consumer spaces, namely tourist- and resident-oriented, were distinguished based on points of interest. Case studies were adopted to reveal the heterogeneity of consumer space reproduction in touristification with the aim of addressing the current lack of case individuality in spatial and social analysis. The results reveal that (1) since the 1990s, multiple social forces with varying and interdependently influential perspectives on historic districts have combined to reshape consumer spaces in historic districts. (2) Capital and authority have dominated the touristification process, but residents’ spatial power has been declining. (3) Although the old city is in danger of over-consumerism and cultural alienation, individual differences in spatial reproduction suggest multiple possibilities in terms of development models and reveal policy implications for sustainable heritage tourism.

摘要

在全球化和消费主义的背景下, 遗产旅游在推动当地经济发展的同时, 过度旅游则可能阻碍居民对地方性的体验并加剧文化的异化。为了弥补现有研究中在多案例比较和大数据空间分析方面的不足, 本研究构建了一个内涵丰富的空间生产理论框架, 将历史社会分析和空间分析相结合, 以联系北京老城历史街区的消费空间再生产的过程和结果。在对消费空间再生产过程中的社会关系进行历史分析后, 本研究根据兴趣点区分了二元消费空间, 即游客友好型和居民友好型, 并采用案例分析来揭示旅游化过程中消费空间再生产的异质性, 以解决目前空间和社会分析中案例欠缺个性的问题。研究结果显示：(1) 自20世纪90年代以来, 多种社会力量从不同的角度对历史街区产生了彼此相互作用的影响, 共同重塑了历史街区的消费空间；(2) 资本和政府在旅游化过程中占主导地位, 而居民的空间权力一直在下降；(3) 尽管老城面临着过度消费化和文化异化的风险, 但空间再生产的个体差异使得多种发展模式成为可能, 这为遗产旅游的可持续发展提供了政策建议。

Keywords:

• Space production
• historic districts
• consumer space
• heritage tourism
• tourist-resident relation
• regeneration sustainability
• Old Beijing City

关键词:

• 空间生产
• 历史街区
• 消费空间
• 遗产旅游
• 游客与居民的关系
• 可持续更新
• 北京老城 

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 The sample was based on three batches of historic and cultural protection districts announced by the Beijing Government, which had 25, 5, and 3 areas, respectively. The first batch was consolidated into 15 larger pieces (Beijing Municipal Commission of Planning, 2002). The districts of the North-South Long and Xihuamen Streets were removed from the sample as they were the current site of the central government, which was not open to the public. The forbidden city was also removed because of the absence of residents. Therefore, 21 historic districts were selected for this study. Besides, most districts were mentioned as Area X (X = 1, …, 21) except for highly significant areas (i.e., Nanluogu Lane, Dashilar, Fucheng Gate Inner Street, Jingshan Eight Area, Shichahai Area, and Beiluogu Lane).

2 Amap (https://lbs.amap.com) is a Chinese counterpart of Google Maps.

3 Weibo (https://m.weibo.cn/) is a Chinese counterpart of Twitter.

4 Kernel density estimation uses a sample of known points to measure the region density, which smooths the result distribution with kernel functions and assigns points within the sample different weights. When the binary businesses are compared, the scale variables (e.g., search radius) are the same to ensure statistical objectivity. This is the case for other quantification.

5 The univariate LISA measures the spatial autocorrelation of individual variables and identifies spatial clusters, wherein a High-Low cluster suggests high values of one variable surrounded by low values of the same variable, and so on. Conversely, the bivariate LISA measures the spatial autocorrelation between variables to categorize the clusters, wherein a High-Low cluster suggests that high values of one variable are surrounded by low values of a second variable, and so on.

6 Integration reflects how close each segment is to all others under various types of distances, where a high value indicates high accessibility, frequent social encounters, and flourishing retail activity. Choice describes the importance of space by measuring movement through space, where a high value suggests a greater potential for pedestrians and vehicular movement. Besides, integration and choice are both relative values and cannot be compared to different axes.

Additional information

Funding

The research was supported by the National Natural Science Foundation of China (Grant No. 51778005).

Notes on contributors

Keer Zhang

Keer Zhang is an undergraduate majoring in urban planning at Peking University, China and a prospective software engineer at Shopee, Singapore. His research interests include computational geosciences, smart cities, and machine learning.

Handuo Deng

Handuo Deng is an undergraduate majoring in urban planning and economics at Peking University, China. Her research interests include urban spatial structure, urban governance, local development economics, and equitable development aided by socio-spatial policies.

Fang Wang

Fang Wang, Ph.D., is a professor in the College of Architecture and Landscape Architecture, Peaking University, China. Her research interests include cultural landscapes and geo-architecture.

Ye Yuan

Ye Yuan, Ph.D., is a National First Grade Registered Architect at China Construction Engineering Design Group Corporation Limited. His research interests include urban renewal and urban design.