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Journal articles on the topic 'Industrial capacity'

Author: Grafiati
Published: 4 June 2021
Last updated: 29 July 2024

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1

Vodianov, A. "Industrial Capacity." Problems of Economic Transition 43, no. 2 (June 1, 2000): 62–73. http://dx.doi.org/10.2753/pet1061-1991430262.

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2

Krasnostanova, Natalia, and Anastasiia Chebanu. "COMPLEX EVALUATION OF INNOVATIVE CAPACITY OF THE INDUSTRIAL ENTERPRISE." Scientific Notes of Ostroh Academy National University, "Economics" Series 1, no. 16(44) (March 26, 2020): 54–61. http://dx.doi.org/10.25264/2311-5149-2020-16(44)-54-61.

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3

Nazarova, Tatiana. "FINANCIAL CAPACITY OF INDUSTRIAL ENTERPRISE." Baltic Journal of Economic Studies 2, no. 3 (2016): 141–45. http://dx.doi.org/10.30525/2256-0742/2016-2-3-141-145.

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4

Vieira, Leonardo Augusto dos Santos, Sergio Fernando Mayerle, Carolina Luisa dos Santos Vieira, and Mônica Maria Mendes Luna. "Industrial capacity planning in oligopolistic markets." Optimization and Engineering 17, no. 4 (March 31, 2016): 761–80. http://dx.doi.org/10.1007/s11081-016-9318-1.

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5

Maloney, William F., and Gaurav Nayyar. "Industrial Policy, Information, and Government Capacity." World Bank Research Observer 33, no. 2 (March 14, 2018): 189–217. http://dx.doi.org/10.1093/wbro/lkx006.

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6

Yi Wu, Cunzhi Tian, and Xiani Yang. "Industrial Policy, Financing Capacity and Equity Value." Journal of Convergence Information Technology 8, no. 7 (April 15, 2013): 467–75. http://dx.doi.org/10.4156/jcit.vol8.issue7.60.

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7

Prokhorov, Victor V. "ASSESSMENT OF DEBT CAPACITY OF INDUSTRIAL ENTERPRISES." Statistics and Economics, no. 2 (January 1, 2015): 110–12. http://dx.doi.org/10.21686/2500-3925-2015-2-110-112.

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8

Fontes, Margarida, Nuno Bento, and Allan Dahl Andersen. "Unleashing the industrial transformative capacity of innovations." Environmental Innovation and Societal Transitions 40 (September 2021): 207–21. http://dx.doi.org/10.1016/j.eist.2021.07.004.

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9

Embi, MRr Lilik Ekowanti, Muhamad Ali, Ahmad Bakri Putra, Suraji a, and Arif Nugroho. "Capacity Building: Fisherman’s Society Institution Empowerment Against the Industrial 4.0 Age in Indonesia." International Journal of Psychosocial Rehabilitation 23, no. 4 (December 20, 2019): 903–11. http://dx.doi.org/10.37200/ijpr/v23i4/pr190419.

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10

Alp, Osman, and Tarkan Tan. "Tactical capacity management under capacity flexibility." IIE Transactions 40, no. 3 (January 8, 2008): 221–37. http://dx.doi.org/10.1080/07408170701488052.

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11

Molina Morales, Francesc Xavier, Valentina De Marchi, and Luis Martínez-Cháfer. "Absorptive capacity and radical innovation in industrial districts." Technology Analysis & Strategic Management 33, no. 9 (January 7, 2021): 1088–100. http://dx.doi.org/10.1080/09537325.2020.1869207.

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12

Moroshkina, Marina. "Institutional arrangements: SEZ and industrial and investment capacity." Drukerovskij Vestnik, no. 4 (September 2020): 193–207. http://dx.doi.org/10.17213/2312-6469-2020-4-193-207.

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13

Sudanti, Sudgarto P. Hadi, Sutikno, and Purwanto. "The Carrying Capacity of Genuk Industrial Zone, Semarang." International Journal of Sustainable Future for Human Security 1, no. 1 (November 30, 2013): 30–34. http://dx.doi.org/10.24910/jsustain/1.1/3034.

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14

Yahlinskyi, Viktor, Serhii Hutyrуa, Yuriy Khomiak, and Viktor Belikov. "GENERALIZED CRITERIA FOR LOADING CAPACITY OF INDUSTRIAL ROBOTS." Bulletin of the National Technical University «KhPI» Series: Engineering and CAD, no. 2 (December 30, 2021): 135–42. http://dx.doi.org/10.20998/2079-0775.2021.2.15.

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The analysis of the correspondence of the set of functional indicators of industrial robots to the criteria of criteria similarity conditions is carried out. Using the methods of the theory of dimensions, criteria for the similarity of the functional properties of carrying capacity, speed-action and dynamism of industrial robots in terms of rotational and translational degrees of mobility have been determined. The necessary set of criteria has been created and a concept has been proposed for determining the generalized criterion complexes of the load capacity for modules, aggregates and the entire structure of the robot as a whole using the method of defragmentation and averaging the corresponding criteria by degrees of mobility. The proposed performance criterion makes it possible to compare the performance of a group of robots in terms of three kinematic indicators: speed, acceleration and the range of permissible displacements. For robots of light load capacity, the technical evolution of the considered criterion complexes is presented. It is noticed that with an increase in the reach of the robot, the criterion of load-carrying capacity for all robots decreases. The developed criteria make it possible to assess the speed action and loading capacity of a robot of any design and can be used to determine the technical level of robots and identify reserves for increasing it. Key words: degrees of mobility; manipulation system; homogeneous functions; dynamic parameters
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15

Gregg, Matthew, John Ghilarducci, and Nate Runyan. "Industrial Capacity Optimization: How to Get Back $10M." Proceedings of the Water Environment Federation 2016, no. 12 (January 1, 2016): 2140–45. http://dx.doi.org/10.2175/193864716819706374.

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16

Caputo, A. C., and P. M. Pelagagge. "Polyfunctional plants for industrial waste disposal: Capacity analysis." Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering 213, no. 1 (February 1999): 11–16. http://dx.doi.org/10.1243/0954408991529951.

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17

Sharif, Nawz. "Project evaluation framework for industrial technology capacity enhancement." Technology Analysis & Strategic Management 6, no. 1 (January 1994): 83–106. http://dx.doi.org/10.1080/09537329408524153.

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18

DRIVER, C. "Spare Capacity and the Scope for Industrial Expansion." Fiscal Studies 7, no. 3 (August 1986): 67–75. http://dx.doi.org/10.1111/j.1475-5890.1986.tb00427.x.

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19

Gilbert, Charles, and Richard D. Raddock. "Industrial Production and Capacity Utilization: 1998 Annual Revision." Federal Reserve Bulletin 85, no. 1 (1999): 0. http://dx.doi.org/10.17016/bulletin.1999.85-1-2.

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20

Hu, Wei Tong, Yu Xuan Zhang, Yan Sun, Wang Sheng Liu, and Li Zhong Zhang. "Research on Small-Capacity Capacitor Type Sensor Detection Method." Advanced Materials Research 981 (July 2014): 594–97. http://dx.doi.org/10.4028/www.scientific.net/amr.981.594.

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In the field of industrial measurement, capacitive sensors are widely used. In many types of capacitive sensors, the output capacitance value range of many sensors is very small, generally between 10pF to 1000pF, but accuracy is usually required to be more than one thousandth. The conventional method of detecting capacitance value is generally the capacitor charge and discharge. By charging and discharging time statistics and calculations, capacitance values are deduced finally. The inherent disadvantages of this method are: (1) Temperature drift of the measurement circuit is large. (2) The spatial magnetic field under special circumstances impact on measurement circuit. (3) Long-term stability of the device will deteriorate. In this paper, a "capacitance measurement method with reference and comparison" is summed up through a lot of measurement experiments of humidity capacitance, that method can eliminate three kinds of defects in the capacitor charging and discharging process.
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21

Batyaeva, A. "Capacity and Labor Resource Endowment of Industrial Enterprises: Consequences of Deviation from the “Perfect Balance”." Russian Economic Barometer (QuE), no. 3 (2020): 3–20. http://dx.doi.org/10.20542/0202-179x-2020-3-3-20.

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The article deals with one of the aspects of adapting industrial enterprises to demand: the correspondence of available production capacities and labor force to the annual demand. The base for comparison was a group of manufacturers whose capacity and labor were in full correspondence with demand. This “ideal” group was compared with others which had an excessive or insufficient volume of resource in various combinations. In total, nine groups of enterprises were examined. As a result of the analysis, the following conclusions were made. For almost 30 years of observations, the share of enterprises whose capacity and labor met the demand has doubled and now exceeds 60%. This group had the biggest share of financially sound enterprises. Over time, lack or excess of resources became more expensive for enterprises, and the surplus of labor appeared to be particularly harmful.
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22

Mardiana, Mardiana, Dahlan Tampubolon, and Irina Safitri Zen. "Environmental carrying capacity assessment of industrial growth center region." E3S Web of Conferences 373 (2023): 04018. http://dx.doi.org/10.1051/e3sconf/202337304018.

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Sustainable economic development, especially the industrial sector, is an important agenda in improving the welfare of the population. The problem that arises is that land use for industry is dominant compared to considerations of the carrying capacity. This study aims to analyze the carrying capacity of the environment, especially land and water in the industrial growth center region (WPPI) South Riau. This study will quantify the potential of WPPI and its impact on the environment using the ECC approach. Data analysis was carried out using quantitative and descriptive analysis methods. Quantitative method is used to analyze the carrying capacity of the environment and descriptive method is used to analyze the recommendations resulting from the calculation of the carrying capacity of the environment. The land for the development of industrial areas is mainly peat domes and marine. The status of the carrying capacity of the land experienced a deficit, namely the regencies of Indragiri Hilir, Indragiri Hulu and Kuantan Singingi. The need for raw water/clean water in industrial growth centers reaches 3,758 liters/second. The land carrying capacity in the study area is dominantly low and the water carrying capacity is very low.
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23

Lagodiienko, V. V., and N. V. Lagodiienko. "MODELING THE ASSESSMENT OF INNOVATION CAPACITY OF INDUSTRIAL ENTERPRISES." Financial and credit activity: problems of theory and practice 1, no. 28 (March 29, 2019): 280–89. http://dx.doi.org/10.18371/fcaptp.v1i28.162979.

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24

Shang Hua, and Li Jiabo. "The Evaluation of Industrial Group's Synergetic Capacity Based on." Journal of Convergence Information Technology 6, no. 8 (August 31, 2011): 58–66. http://dx.doi.org/10.4156/jcit.vol6.issue8.7.

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25

Kim, Moon Sun, Dae-Seong Jeoune, Kyung H. Nam, Gyu-Ro Kim, and Chan-Myeong Han. "Implication of Industrial Security Capacity Based on Level Evaluation." Journal of the Korean society for quality management 41, no. 4 (December 31, 2013): 649–57. http://dx.doi.org/10.7469/jksqm.2013.41.4.649.

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26

Chen, Chung-Jen, Bou-Wen Lin, Jun-You Lin, and Yung-Chang Hsiao. "Technological diversity, knowledge flow and capacity, and industrial innovation." Technology Analysis & Strategic Management 30, no. 12 (May 7, 2018): 1365–77. http://dx.doi.org/10.1080/09537325.2018.1472759.

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27

Savu, Tom, and Bogdan Alexandru Jugravu. "Remanent battery capacity estimation for autonomous ground industrial vehicles." MATEC Web of Conferences 290 (2019): 02009. http://dx.doi.org/10.1051/matecconf/201929002009.

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When travelling in an industrial system for completing their assigned tasks, autonomous ground vehicles must estimate the remanent capacity of their batteries and decide if they are able to assume the next task and afterward travel to the charging or replacement station. The amount of energy needed for moving on a certain distance depends on a set of parameters belonging to the vehicle, to the runway and to the vehicle’s trajectory. The paper proposes a model for estimating the remaining capacity of the batteries after a certain distance would be covered by a vehicle. Parameters values were obtained by simulation, capacity loss was computed using the proposed model and then a neural network was taught to perform the estimation. The neural network was further used to simulate the situation when a vehicle is estimating the needed capacity before accepting a task to be performed. The results proved that the model and the network, even developed using low data volume and processing time, are able to provide accurate enough estimations and are able to allow future developments.
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28

Kang, Peng, and Linyu Xu. "Water Environmental Carrying Capacity Assessment of an Industrial Park." Procedia Environmental Sciences 13 (2012): 879–90. http://dx.doi.org/10.1016/j.proenv.2012.01.082.

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29

Arnold, Walter. "Bureaucratic Politics, State Capacity, and Taiwan's Automobile Industrial Policy." Modern China 15, no. 2 (April 1989): 178–214. http://dx.doi.org/10.1177/009770048901500203.

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30

Corrado, Carol. "Industrial Production and Capacity Utilization: The 2000 Annual Revision." Federal Reserve Bulletin 87, no. 3 (2001): 0. http://dx.doi.org/10.17016/bulletin.2001.87-3-2.

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31

Corrado, Carol, Charles Gilbert, and Norman J. Morin. "Industrial Production and Capacity Utilization: The 2001 Annual Revision." Federal Reserve Bulletin 88, no. 3 (2002): 0. http://dx.doi.org/10.17016/bulletin.2002.88-3.

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32

Bayard, Kimberly, and Norman J. Morin. "Industrial Production and Capacity Utilization: The 2003 Annual Revision." Federal Reserve Bulletin 90, no. 1 (2004): 0. http://dx.doi.org/10.17016/bulletin.2004.90-1-3.

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33

Gilbert, Charles, and Kimberly Bayard. "Industrial Production and Capacity Utilization: The 2004 Annual Revision." Federal Reserve Bulletin 91, no. 1 (2005): 0. http://dx.doi.org/10.17016/bulletin.2005.91-1-2.

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34

Bayard, Kimberly, and Charles Gilbert. "Industrial Production and Capacity Utilization: The 2005 Annual Revision." Federal Reserve Bulletin 92, no. 3 (2006): 0. http://dx.doi.org/10.17016/bulletin.2006.92-3-2.

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35

Gilbert, Charles, and Maria Ward Otoo. "Industrial Production and Capacity Utilization: The 2006 Annual Revision." Federal Reserve Bulletin 93, no. 5 (2007): 0. http://dx.doi.org/10.17016/bulletin.2007.93-5-2.

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36

Gilbert, Charles, and Kimberly Bayard. "Industrial Production and Capacity Utilization: The 2008 Annual Revision." Federal Reserve Bulletin 94, no. 8 (2008): 0. http://dx.doi.org/10.17016/bulletin.2008.94-8.

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37

Hall, Anne E. "Industrial Production and Capacity Utilization: The 2009 Annual Revision." Federal Reserve Bulletin 95, no. 8 (2009): 0. http://dx.doi.org/10.17016/bulletin.2009.95-8.

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38

Li, Guang Hua, and Qun Feng Yang. "Non-Pressure Heater Utilization on Low-Capacity Industrial Boiler." Advanced Materials Research 960-961 (June 2014): 394–98. http://dx.doi.org/10.4028/www.scientific.net/amr.960-961.394.

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A new non-pressure waste heat recycling system was designed and arranged on KHSS0.5-0.7-AⅡ industrial coal-fired boiler to decrease the exhausted gas temperature about 35°C, improve the boiler efficiency about 3.2%. Results showed that this system can avoid low-temperature sulfur corrosion and operate in normal and intermittent water supply condition safely and economically.
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39

Akinnuli, B. O., and T. C. Akintayo. "An Empirical Model for Industrial Generator’s Capacity Requirement Determination." Engineering Management Research 4, no. 2 (October 19, 2015): 70. http://dx.doi.org/10.5539/emr.v4n2p70.

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<p>In our community today, the existence of Power Holding Company of Nigeria can only help for a short period when it is available. In some areas, it is not available at all. Therefore, there is always need for generator as back up or continuous use in our industries. Determination of capacity of generator to procure is always a problem. Some company by error purchased generators that cannot carry the load of their industries. This always led to load shed either on machines or the entire facilities they have. This is due to the fact that the capacity of the generator required was not predetermined and also the expansion of the companies in the nearest future was not considered. This had contributed to the low productivity of many companies because of their inability to meet their monthly as well as yearly production targets. Hence the development of a model for the appropriate generator capacity selection for industrial installation which is empirically oriented. Developing an empirical model for this selection involves adequate understanding of electrical load distributions, variations and utilities connected to the electrical load of the generator. Parameters for industrial generator capacity were identified, mathematical model for each parameter were determined and integrated to form a unique model for decision making. The identified parameters are: capacity utilization, diversity factors, deration factor and usage type. The scenarios for computation were three based on the type of load required. This load were identified to be existing load, new and future loads. The developed models were applied using Honeywell foods (FMCG) company as case study under the first scenario. The load analysis for both the non-factory and factory load gave Summation of 531.47kW with power factor of 0.8 gave a converted value of 664.34kVA. The total variation factor gotten is 0.765 with 0.85 capacity utilization factor and diversity factor was 0.9. Application of total variation factor gave the converted load of 664.kVA and new load value of 508 kVA. Using power factor of 0.8 resulted into 406kW the generator considerations were derating factor of 0.75 and usage type factor (which is continuous) is 1 or 100%. The final determined generator capacity for this case study using derating factor of 0.75 made the required capacity to be 677kVA, and 542kW.</p>
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40

Gorbachev, Andrey, and Tatiana Fedorova. "Assessing the innovative capacity of the scientific-industrial complex." SHS Web of Conferences 55 (2018): 01016. http://dx.doi.org/10.1051/shsconf/20185501016.

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One of the most effective structures on release of innovative products is the scientific-industrial complex today. To make innovative products for the establishment of capability of scientific-industrial complex and to perform competitive activity, such characteristic of the enterprise as its innovative potential having three following components is estimated: the volume of the resources of the enterprise used for performance of works, an opportunity to perform profitable works and to perform investing activities by means of implementation of orders with remote financial result. Efficiency of activity of scientific-industrial complex depends on capability of the enterprise competently to distribute the potential between different job groups, providing financial result, both today and in the future.
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41

Kenderdine, Tristan, and Han Ling. "International Capacity Cooperation-Financing China's Export of Industrial Overcapacity." Global Policy 9, no. 1 (October 20, 2017): 41–52. http://dx.doi.org/10.1111/1758-5899.12509.

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42

Gallien, Jérémie, and Lawrence M. Wein. "A Smart Market for Industrial Procurement with Capacity Constraints." Management Science 51, no. 1 (January 2005): 76–91. http://dx.doi.org/10.1287/mnsc.1040.0230.

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43

Peterson, J. R., and D. B. Smathers. "Vanadium: An overview of industrial capacity and other factors." Journal of Nuclear Materials 141-143 (November 1986): 1113–16. http://dx.doi.org/10.1016/0022-3115(86)90151-0.

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44

Reeves, Gary R., Kenneth D. Lawrence, Sheila M. Lawrence, and Juan J. Gonzalez. "A multiple criteria approach to aggregate industrial capacity expansion." Computers & Operations Research 15, no. 4 (January 1988): 333–39. http://dx.doi.org/10.1016/0305-0548(88)90017-2.

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45

Celestine Ugwuoke, Ikechukwu. "DEVELOPMENT OF A 50-LITRE BATCH CAPACITY INDUSTRIAL MIXER." International Journal of Engineering Applied Sciences and Technology 5, no. 1 (May 1, 2023): 370–82. http://dx.doi.org/10.33564/ijeast.2023.v08i01.053.

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This work focused on the development of a 50- litre batch capacity industrial mixer using locally sourced material. The essence is to produce an industrial liquid mixer that is relatively cheap and easily affordable. The design is simplified in such a way that limits operational hazards. The development of the machine involved the use of simple fabrication techniques and methods for each component part so as to eliminate unnecessary complexity, for ease of maintenance. The electric motor capacity is 0.5hp. Calculation results gave the volume of vessel as 70. 372 liters, the total tension on the belt as 1033.063N, the force acting on the impeller as 197.867N, the power required to drive the 2 impellers as 22.694Watts (0.0304hp), the belt length as 254.435mm, the minimum length of the shaft as 760mm, the equivalent bending moment acting on the shaft as 142.603Nm, the equivalent twisting moment acting on the shaft as 71.371Nm, the shaft diameter as 20.5mm. Performance testing shows that the machine performed well as expected. The highly homogeneous product obtained during testing proves the viability of the machine and is indicative of the overall efficiency of the machine.
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46

Hou, Linke, Zhikuo Liu, Qi Zhang, and Xiaolu Zhao. "Local State Capacity and Uneven Taxation across Industrial Firms." China & World Economy 32, no. 3 (May 2024): 191–214. http://dx.doi.org/10.1111/cwe.12536.

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AbstractIn this research we investigate the association between local state capacity (LSC) and effective tax burdens (ETBs) on industrial firms within counties between 1998 and 2013. The LSC measures a state's capacity for policy implementation and specifically its ability to acquire low‐cost agricultural land for nonagricultural (industrial or commercial) purposes. Based on China's government‐led development experience since the 1990s, we draw on two unique household survey datasets to capture LSC at county level. We find robust evidence that greater LSC was associated with much lower ETBs on large industrial firms. This taxation pattern implies local government's primary reliance on larger manufacturing firms, while the ETBs for small‐and‐medium enterprises are not as prominently addressed. This research highlights that LSC can affect both the amount of revenue a local government can generate and the methods it uses to collect these revenues.
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47

Spirin, Alexander. "The formation of output capacity of industrial housing construction enterprises." E3S Web of Conferences 535 (2024): 01014. http://dx.doi.org/10.1051/e3sconf/202453501014.

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The productivity of industrial housing construction enterprise (IHCE) is determined by its output capacity, reflecting the volume of construction products realized by it for a period. The output capacity of IHCE is based on its potential - the totality of all the resources available to the enterprise, which can be used by it in economic activity. Under the influence of various factors, the potential of IHCE is transformed into its input capacity. Input capacity reflects the maximum volume of construction products that IHCE can produce over a period. Being limited by the resource base, the input capacity of the enterprise is transformed into the resource capacity. Due to low workload, unfavorable probabilistic events and reasons related to economic management, there are losses of resource capacity, and the remaining part of it represents the output capacity. To increase the output capacity of the enterprise it is advisable to resort to the process method - based on the stages of the product life cycle of industrial housing construction enterprises to make a system of interrelated processes and consider the output capacity of each of them.
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48

She, Yan Shuang, Meng Gang Li, and Jing Hua Sha. "A Comparison Study of Industrial Structure Transformation Capacity of Resource-Based Cities in China West." Advanced Materials Research 616-618 (December 2012): 1331–34. http://dx.doi.org/10.4028/www.scientific.net/amr.616-618.1331.

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The sustainable development of resource-based cities is a hot issue in China. This paper will focus on the industrial structure of sustainable development. There is close relationship between regional economic development and industrial structure transformation Capacity. Comparison research of cities’ regional industrial structure capacity will help to understand variation status and potential of regional industrial structures. With principal components analysis, this paper based on the regional industrial structure comparison theory, analyzed industrial structure transformation Capacity of 20 resource-based cities in China west. It will provide references for promoting optimization and upgrading of regional industrial structure, making regional industrial development strategy, improving environmental conditions, and enhancing local economic development.
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49

Quintero, Juan, Mariana Cardona, and Juliana Osorio. "Degradation of industrial dyes with white rot fungi." Revista Facultad de Ingeniería Universidad de Antioquia, no. 48 (July 23, 2013): 27–37. http://dx.doi.org/10.17533/udea.redin.16006.

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White rot fungi have shown a great potential for degrading recalcitrant chemicals compounds as PAHs, explosives, pesticides, dyes, etc. This capacity is due mainly to an extracellular enzymatic complex that they use naturally in lignin degradation of wood. This work evaluated seven strains in function of its decoloration capacity of Orange II dye and industrail dyes Cibacrón® red, Erionyl® red, Terasil® blue y Erionyl® turquoise in semisolid and liquid mediums. Phanerochaete chrysosporium and Phanerochaete sordida showed high decoloration capacity, with a 98% for Orange II and between 82-86% for industrial dyes in liquid medium. In semisolid medium all dyes were totally eliminated. The growh fungi in each degrading tretatment of Orange II showed a diauxic performance, in the first step of fungi growth , they showed partial adsorption of orange II in biomass, posterior liberation in stationary step and finally total degradation in medium.
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50

Han, Zhipeng, Liguo Wang, Feifei Zhao, and Zijun Mao. "Does Low-Carbon City Policy Improve Industrial Capacity Utilization? Evidence from a Quasi-Natural Experiment in China." Sustainability 14, no. 17 (September 1, 2022): 10941. http://dx.doi.org/10.3390/su141710941.

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A low-carbon city policy (LCC) is a comprehensive environmental regulation to promote urban green development and resolve the overcapacity contradiction. This study uses China’s low-carbon city pilot policy as a “quasi-natural experiment” based on a panel of 266 Chinese cities, covering three batches of low-carbon pilot cities from 2003 to 2019. We measure industrial capacity utilization at the city level and then construct a time-varying DID (TV-DID) model to investigate the effect of a low-carbon city policy on industrial capacity utilization in Chinese cities, exploring the mechanism, heterogeneity, and spatial effects. It is found that (1) LCC improves industrial capacity utilization by approximately 3.2%, and the above finding still holds after a series of robustness tests, such as the parallel trend test, PSM-DID, DDD, and placebo test. (2) LCC improves industrial capacity utilization through three channels: alleviating resource misallocation, promoting industrial structure upgrading, and stimulating technological innovation. (3) The improvement of LCC on industrial capacity utilization has heterogeneity and positive spatial spillover effect. (4) The heterogeneity analysis shows that the improvement of LCC on industrial capacity utilization is stronger in cities in the high quartile of industrial capacity utilization, cities in old industrial bases, cities along the “Belt and Road” route, and cities in a free-trade zone. The theoretical analysis and empirical results of this study provide empirical support for the promotion of low-carbon city policy globally and provide ideas for solving the overcapacity contradiction in the context of global decarbonization.
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