A DEA–based efficiency evaluation method for metro-led urban underground public space

Abstract

Despite the thriving development of metro-led urban underground public space (UUPS) and its significant benefits and costs, there remains a critical research gap in understanding and evaluating its efficiency. This paper intends to improve the post-evaluation system of metro-led UUPS by proposing an efficiency evaluation framework based on data envelopment analysis. The public and the private sectors are taken as different coexisting decision-makers, and a pair of linear programming is built accordingly (with different assignments of discretionary and non-discretionary inputs) for each decision-making unit. The directional vector is calculated based on CRITIC weights to model the searching process of referential cases in terms of urban renewal. The empirical study of twenty metro-led UUPSs in central Shanghai reveals that (1) the proposed evaluation framework is feasible and discriminative, (2) the efficient form of metro-led UUPS in Shanghai is mainly limited to a compact pattern with a low proportion of pure public space, (3) the essential solution to promote efficiencies is closer cooperation between different parties, and (4) efficiency evaluation is crucial to avoiding the ‘‘the-more-the-better” type of development. The findings of this study are expected to shed light on the future planning and operation of metro-led UUPS.

Keywords

Data envelopment analysis / Directional distance function / Efficiency / Metro-led / Underground public space

References

[1] Andor, M., & Hesse, F. (2011). A Monte Carlo simulation comparing DEA, SFA and two simple approaches to combine efficiency estimates (Working Paper 51). CAWM Discussion Paper. https://www.econstor.eu/handle/10419/51383.

[2] Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science (Pre-1986), 30(9), 1078-1902. ABI/INFORM Collection.

[3] Banker, R. D., & Morey, R. C. (1986). Efficiency analysis for exogenously fixed inputs and outputs. Operations Research, 34(4), 513-521.

[4] Bélanger, P. (2007). Underground landscape: The urbanism and infrastructure of Toronto’s downtown pedestrian network. Tunnelling and Underground Space Technology, 22(3), 272-292.

[5] Ben Yahia, F., Essid, H., & Rebai, S. (2018). Do dropout and environmental factors matter? A directional distance function assessment of Tunisian education efficiency. International Journal of Educational Development, 60, 120-127.

[6] Bobylev, N. (2010). Underground space in the Alexanderplatz area, Berlin: Research into the quantification of urban underground space use. Tunnelling and Underground Space Technology, 25(5), 495-507.

[7] Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.

[8] Chiaradia, A., Cooper, C. H. V., & Wedderburn, M. (2014, July 2). Network Geography and Accessibility. In Proceedings of 12th Transport Practitioners’ Meeting. 12th Transport Practitioners’ Meeting, London.

[9] Chinese Academy of Engineering, Chinese Society for Rock Mechanics & Engineering, & Urban Planning Society of China . (2021). China Urban Underground Space Development Blue Book (Public Edition). Retrieved from https://www.planning.org.cn/news/view?id=12092&cid=0 (in Chinese).

[10] Cooper, C. H. V. (2015). Spatial localization of closeness and betweenness measures: A self-contradictory but useful form of network analysis. International Journal of Geographical Information Science, 29(8), 1293-1309.

[11] Cooper, C. H. V. (2024). Spatial Design Network Analysis (sDNA) version 4.1 Manual. http://sdna.cardiff.ac.uk/sdna/software/documentation.

[12] Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software (2nd ed.). Springer.

[13] Cui, J. (2021). Building three-dimensional pedestrian networks in cities. Underground Space, 6(2), 217-224.

[14] Cui, J.-Q., Allan, A., Taylor, M. A. P., & Lin, D. (2013). Underground pedestrian systems development in cities: Influencing factors and implications. Tunnelling and Underground Space Technology, 35, 152-160.

[15] Dong, Y.-H., Peng, F.-L., & Guo, T.-F. (2021). Quantitative assessment method on urban vitality of metro-led underground space based on multi-source data: A case study of Shanghai Inner Ring area. Tunnelling and Underground Space Technology, 116, 104108.

[16] Dyckhoff, H., & Souren, R. (2020). Performance Evaluation: Foundations and Challenges. Springer International Publishing.

[17] Färe, R., & Grosskopf, S. (2000). Theory and application of directional distance functions. Journal of Productivity Analysis, 13(2), 93-103.

[18] Guo, J., Nakamura, F., Li, Q., & Zhou, Y. (2018). Efficiency assessment of transit-oriented development by data envelopment analysis: Case study on the Den-en Toshi Line in Japan. Journal of Advanced Transportation, 2018(1), 6701484.

[19] Hong, X., Li, S., Chen, T., Ji, X., & Song, X. (2024). Spatial performance evaluation and optimization of integrated aboveground and underground spaces in urban commercial complexes. Journal of Asian Architecture and Building Engineering, 24(2), 623-649.

[20] Ibraeva, A., Correia, G. H. de A., Silva, C., & Antunes, A. P. (2020). Transit-oriented development: A review of research achievements and challenges. Transportation Research Part A: Policy and Practice, 132, 110-130.

[21] Jia, X., Wang, J., & Yan, B. (2024). Evaluation of existing underground public space supply based on the Node-Place-Experience model. Tunnelling and Underground Space Technology, 144, 105517.

[22] Kohl, S., Schoenfelder, J., Fuegener, A., & Brunner, J. O. (2019). The use of data envelopment analysis (DEA) in healthcare with a focus on hospitals. Health Care Management Science, 22(2), 245-286.

[23] Li, Z.-H., Lu, Y., Zhuang, Y., & Yang, L.-C. (2024). Influencing factors of spatial vitality in underground space around railway stations: A case study in Shanghai. Tunnelling and Underground Space Technology, 147, 105730.

[24] Li, Z.-K., Han, Z.-X., Xin, J., Luo, X., Su, S.-L., & Weng, M. (2019). Transit oriented development among metro station areas in Shanghai, China: Variations, typology, optimization and implications for land use planning. Land Use Policy, 82, 269-282.

[25] Liu, D., Wu, L., & Yang, Y. (2020). A hybrid weight assignment model for urban underground space resources evaluation integrated with the weight of time dimension. Applied Science-Basel, 10(15), 5152.

[26] Lopes, M. N., & Camanho, A. S. (2013). Public green space use and consequences on urban vitality: an assessment of European cities. Social Indicators Research, 113(3), 751-767.

[27] Ma, C.-X., Peng, F.-L., Qiao, Y.-K., & Li, H. (2022). Evaluation of spatial performance of metro-led urban underground public space: A case study in Shanghai. Tunnelling and Underground Space Technology, 124, 104484.

[28] Ma, C.-X., Peng, F.-L., Qiao, Y.-K., & Li, H. (2023). Influential factors of spatial performance in metro-led urban underground public space: A case study in Shanghai. Underground Space, 8, 229-251.

[29] Mohler, B. J., Thompson, W. B., Creem-Regehr, S. H., Pick, H. L., & Warren, W. H. (2007). Visual flow influences gait transition speed and preferred walking speed. Experimental Brain Research, 181(2), 221-228.

[30] Nepomuceno, T. C. C., Santiago, K. T. M., Daraio, C., & Costa, A. P. C. S. (2022). Exogenous crimes and the assessment of public safety efficiency and effectiveness. Annals of Operations Research, 316(2), 1349-1382.

[31] Niewerth, S., Vogt, P., & Thewes, M. (2022). Tender evaluation through efficiency analysis for public construction contracts. Frontiers of Engineering Management, 9(1), 148-158.

[32] Pan, X.-W., Dong, J.-J., Ren, R., Chen, Y.-C., Sun, B., & Chen, Z.-L. (2023). Monetary evaluation of the external benefits of urban underground logistics system: A case study of Beijing. Tunnelling and Underground Space Technology, 136, 105094.

[33] Peng, F.-L., Dong, Y.-H., Wang, W.-X., & Ma, C.-X. (2023). The next frontier: Data-driven urban underground space planning orienting multiple development concepts. Smart Construction and Sustainable Cities, 1(1), 3.

[34] Peng, F.-L., Qiao, Y.-K., Zhao, J.-W., Liu, K., & Li, J.-C. (2020). Planning and implementation of underground space in Chinese central business district (CBD): A case of Shanghai Hongqiao CBD. Tunnelling and Underground Space Technology, 95, 103176.

[35] Qiao, Y.-K., Peng, F.-L., Dong, Y.-H., & Lu, C.-F. (2024). Planning an adaptive reuse development of underutilized urban underground infrastructures: A case study of Qingdao, China. Underground Space, 14, 18-33.

[36] Qiao, Y.-K., Peng, F.-L., Luan, Y.-P., & Wu, X.-L. (2022). Rethinking underground land value and pricing: A sustainability perspective. Tunnelling and Underground Space Technology, 127, 104573.

[37] Quélin, B. V., Kivleniece, I., & Lazzarini, S. (2017). Public-private collaboration, hybridity and social value: towards new theoretical perspectives. Journal of Management Studies, 54(6), 763-792.

[38] Rahman, M. H., Ashik, F. R., & Mouli, M. J. (2022). Investigating spatial accessibility to urban facility outcome of transit-oriented development in Dhaka. Transportation Research Interdisciplinary Perspectives, 14, 100607.

[39] Shahrabi, B. A. (2024). Strategies for designing public open spaces in baghdad city. Mesopotamian Journal of Civil Engineering, 2024, 15-22.

[40] Wang, Y.-C. (2009). The connectivity evaluation of Shanghai urban landscape eco-network. Geographical Research, 28(2), 284-292.

[41] Yuan, H., He, Y., Zhou, J., Li, Y., Cui, X., & Shen, Z. (2020). Research on compactness ratio model of urban underground space and compact development mechanism of rail transit station affected area. Sustainable Cities and Society, 55, 102043.

[42] Zacharias, J., & Xu, M . (2007). The underground system as economic generator for Montreal’s Central City. Urban Planning International, 6, 28-34.

[43] Zhang, Z.-Y., Ma, C.-X., Qiao, Y.-K., & Peng, F.-L. (2024). Evaluating efficiency of metro-led urban underground public space: A case study in Shanghai. IOP Conference Series: Earth and Environmental Science, 1333(1), 012003.

[44] Zhang, Z.-Y., Peng, F.-L., Ma, C.-X., Zhang, H., & Fu, S.-J. (2021). External benefit assessment of urban utility tunnels based on sustainable development. Sustainability, 13(2), 900.

[45] Zhou, B., Gui, Y., Xie, X., Li, W., & Li, Q. (2022). A measurable evaluation method of visual comfort in underground space by intelligent sorting and classification algorithms. Underground Space, 7(3), 453-464.

[46] Zhuang, Y., & Zhang, L. (2016). Exploring synergistic effect in metro station areas: A case study of Shanghai, China. International Journal of High-Rise Buildings, 5(2), 105-115.