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Adekunle, T O (2019) Field measurements of comfort, seasonal performance and cold stress in cross-laminated timber (CLT) school buildings. Smart and Sustainable Built Environment, 9(04), 655–73.

Aggarwal, A, Rani, A and Kumar, M (2019) A robust method to authenticate car license plates using segmentation and ROI based approach. Smart and Sustainable Built Environment, 9(04), 737–47.

Aggarwal, T and Solomon, P (2019) Quantitative analysis of the development of smart cities in India. Smart and Sustainable Built Environment, 9(04), 711–26.

• Type: Journal Article
• Keywords:
• ISBN/ISSN: 2046-6099
• URL: https://doi.org/10.1108/SASBE-06-2019-0076
• Abstract:
  Smart cities are an attempt to recognize the pioneering projects designed to make the cities livable, sustainable, functional and viable. The purpose of this paper is to evaluate funding released by the government city wise and sources available for finance for the development of the smart cities. The impact of fund released by the government for the development of smart cities (Chandigarh, Karnal, Faridabad, Pune, Chennai, Ahmedabad, Kanpur, Delhi, Lucknow and Agra) in India has been studied in detail. Urbanization is a continuous process, which is taking place throughout the globe, especially in developing countries like India. The research is descriptive in nature. The sources of funding for smart cities in India have been taken into consideration, and χ² test of independence has been employed to study the impact of fund released by the government for smart city development in India by using IBM SPSS. The total investment, area-based projects, pan-city initiatives and O&M costs for smart cities ranged between Rs 133,368 and Rs 203,979 lakh crores, Rs 105,621 and Rs 163,138 lakh crores, Rs 26,141 and Rs 38,840 lakh crores, and Rs 1,604 and Rs 1,999 lakh crores, respectively, in the year 2016 (for 60 smart cities) to 2017 (for 99 smart cities), which shows an increasing trend. The investment in retrofitting projects, redevelopment projects, greenfield projects and area-based projects ranged between Rs 94,419 and Rs 131,003 lakh crores, Rs 8,247 and Rs 23,119 lakh crores, Rs 2,955 and Rs 8,986 lakh crores, and Rs 105,621 and Rs 163,138 lakh crores, respectively, in the year 2016 (60 smart cities) to 2017 (99 smart cities), which shows the division of projects funding for smart city development in India. The funding released for smart city development such as other sources, loans from the financial institution, private investment, convergence, state government share funding and Central Government Funding ranged between Rs 14,828 and Rs 15,930 lakh crores, Rs 7,775 and Rs 9,795 lakh crores, Rs 30,858 and Rs 43,622 lakh crores, Rs 25,726 and Rs 43,088 lakh crores, Rs 27,260 and Rs 45,695 lakh crores, and Rs 29,207 and Rs 47,858 lakh crores, respectively, in the year 2016 (60 smart cities) to 2017 (99 smart cities), which reflects the different sources of funding for the development of smart cities in India. The χ² test of independence has been applied, which shows that there is no impact of fund released by the government on cities for smart city development in India as the p-values of Chandigarh (0.213), Karnal (0.199), Faridabad (0.213), Pune (0.199), Chennai (0.213), Ahmadabad (0.199), Kanpur (0.199), Delhi (0.199), Kolkata, Lucknow (0.213) and Agra (0.199) are greater than 0.05. For the Smart Cities Mission to be financially sustainable, the right policy and institutional framework should be implemented for modernization and aggregation of government landholding. Consolidation of all the landholdings under the smart city project should be properly implemented, and the role of private sectors should be encouraged for public‒private partnership projects to make Smart City Mission more successful. The benefits of smart cities development will help provide affordable, cleaner and greener housing infrastructure for all, especially the inclusive group of developers belonging to the lower middle-income strata of India, and the benefits will be replicated when adopted on a smaller scale in the rural part of the country. The research paper is original and χ² test has been used to study the impact of fund released by the government for smart city development in India.

Agyekum, K, Adinyira, E and Ampratwum, G (2020) Factors driving the adoption of green certification of buildings in Ghana. Smart and Sustainable Built Environment, 9(04), 595–613.

Dell'Anna, F, Bottero, M, Becchio, C, Corgnati, S P and Mondini, G (2020) Designing a decision support system to evaluate the environmental and extra-economic performances of a nearly zero-energy building. Smart and Sustainable Built Environment, 9(04), 413–42.

Dewan, S and Singh, L (2020) Use of blockchain in designing smart city. Smart and Sustainable Built Environment, 9(04), 695–709.

du Toit, J and Wagner, C (2020) The effect of housing type on householders' self-reported participation in recycling. Smart and Sustainable Built Environment, 9(04), 395–412.

Ekemode, B G (2019) Impact of urban regeneration on commercial property values in Osogbo, Osun State, Nigeria. Smart and Sustainable Built Environment, 9(04), 557–71.

Eslamirad, N, Malekpour Kolbadinejad, S, Mahdavinejad, M and Mehranrad, M (2020) Thermal comfort prediction by applying supervised machine learning in green sidewalks of Tehran. Smart and Sustainable Built Environment, 9(04), 361–74.

Hussein, D (2020) A user preference modelling method for the assessment of visual complexity in building façade. Smart and Sustainable Built Environment, 9(04), 483–501.

Khan, N A, Ullah Khan, S, Ahmed, S, Farooqi, I H, Hussain, A, Vambol, S and Vambol, V (2019) Smart ways of hospital wastewater management, regulatory standards and conventional treatment techniques. Smart and Sustainable Built Environment, 9(04), 727–36.

Konstantinou, T, de Jonge, T, Oorschot, L, El Messlaki, S, van Oel, C and Asselbergs, T (2019) The relation of energy efficiency upgrades and cost of living, investigated in two cases of multi-residential buildings in the Netherlands. Smart and Sustainable Built Environment, 9(04), 615–33.

Kumar, A, Jain, S and Yadav, D (2020) A novel simulation-annealing enabled ranking and scaling statistical simulation constrained optimization algorithm for Internet-of-things (IoTs). Smart and Sustainable Built Environment, 9(04), 675–93.

Lau, J L and Hashim, A H (2019) Mediation analysis of the relationship between environmental concern and intention to adopt green concepts. Smart and Sustainable Built Environment, 9(04), 539–56.

Moshtaghian, F, Golabchi, M and Noorzai, E (2020) A framework to dynamic identification of project risks. Smart and Sustainable Built Environment, 9(04), 375–93.

Ndlangamandla, M G and Combrinck, C (2019) Environmental sustainability of construction practices in informal settlements. Smart and Sustainable Built Environment, 9(04), 523–38.

Opawole, A, Babatunde, S O, Kajimo-Shakantu, K and Ateji, O A (2020) Analysis of barriers to the application of life cycle costing in building projects in developing countries. Smart and Sustainable Built Environment, 9(04), 503–21.

Saadi, A and Belhadef, H (2020) Deep neural networks for Arabic information extraction. Smart and Sustainable Built Environment, 9(04), 467–82.

Sahebzadeh, S, Dalvand, Z, Sadeghfar, M and Heidari, A (2018) Vernacular architecture of Iran’s hot regions; elements and strategies for a comfortable living environment. Smart and Sustainable Built Environment, 9(04), 573–93.

Susilo, A, Fitriah, F, Sunaryo, Ayu Rachmawati, E T and Suryo, E A (2020) Analysis of landslide area of Tulung subdistrict, Ponorogo, Indonesia in 2017 using resistivity method. Smart and Sustainable Built Environment, 9(04), 341–60.

Tunji-Olayeni, P, Kajimo-Shakantu, K and Osunrayi, E (2020) Practitioners' experiences with the drivers and practices for implementing sustainable construction in Nigeria: a qualitative assessment. Smart and Sustainable Built Environment, 9(04), 443–65.

van Stijn, A and Gruis, V (2020) Towards a circular built environment. Smart and Sustainable Built Environment, 9(04), 635–53.