Compressed Stabilized Earth Blocks for Sustainable Building Construction: A PRISMA-Guided Systematic Review and TCCM Analysis Swati Sinha, Jayaraman Sethuraman Sudarsan, Abhijat Arun Abhyankar Buildings, 2026 Global interest in sustainable building materials is increasing due to growing concerns regarding the environmental impacts of conventional construction materials, particularly fired clay bricks. Compressed Stabilized Earth Blocks (CSEBs) have emerged as a viable, cost-effective, and environmentally sustainable alternative for building construction. The incorporation of waste-derived additives in CSEBs not only addresses waste management challenges but also enhances the functional performance of earthen materials. This study presents a comprehensive synthesis of existing research on the influence of fibers, binders, stabilizers, and production processes on the performance characteristics of CSEBs. A systematic literature review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 guidelines, resulting in the identification and analysis of 256 relevant studies. The selected literature was synthesized using the Theories, Contexts, Characteristics, and Methodologies (TCCM) framework to map research trends and methodological approaches. The review indicates that fiber reinforcement primarily improves flexural strength and thermal performance, while binders significantly enhance compressive strength and erosion resistance. The findings also demonstrate that selected waste materials can partially replace natural soil, provided minimum material and performance standards are satisfied. The study highlights the need for standardized manufacturing guidelines and testing protocols to improve the reliability, scalability, and wider adoption of CSEBs in sustainable building applications.
Integrating ESG principles in India's construction sector: A comprehensive assessment A. A. Abhyankar, J.S. Sudarsan, V. Balon Journal of Environmental Biology, 2026 Aim: The given research explores the integration of Environmental, Social, and Governance (ESG) principles within India's construction sector, highlighting their influence on sustainability, project performance, and governance structures. The necessity for ESG adoption has been highlighted in recent years by the global shift toward sustainable business practices, especially in high-impact sectors like construction. Methodology: Through an analysis of corporate governance frameworks, social responsibility initiatives, and environmentally friendly construction techniques, this study assesses the degree to which Indian construction companies have adopted ESG. Results: To give a thorough grasp of the importance of ESG factors in the industry, the analysis ranks them using the Relative Importance Index (RII) technique. To visually compare ESG aspects across different categories, the study also makes use of a variety of visualizations. Interpretation: This study points out the weaknesses in current frameworks and suggest ways to improve ESG integration in order to meet the Sustainable Development Goals (SDGs). This study advances sustainable construction practices in India by providing information to investors, legislators, and industry stakeholders. The results of the study relate the importance of ESG component by means of RII. It was interpreted how different factors among ESG are valued in the construction industry. Key words: Construction Sector, ESG, Framework, Policy, Principles, Sustainability
Life Cycle Analysis of Steel, Glass Fiber Rebar Polymer and Basalt Fiber Reinforcement Polymer Virendra Balon, A. A. Abhyankar, J. S. Sudarsan Journal of Mines Metals and Fuels, 2025 This study aims to identify an alternative material to steel with a lower environmental footprint while maintaining comparable performance, durability, and cost-effectiveness. We have used Life Cycle Assessment (LCA) as a tool for the present study. We have compared steel with Glass Fiber Polymer Rebar (GFRP) and Basalt Fiber Rebar Polymer (BFRP). There are four major steps involved in cradle-to-grave analysis: Goal definition, inventory analysis, impact assessment, and improvement analysis. Life Cycle Cost Assessment (LCCA) per unit analysis for each material considers raw materials, production costs, and market price comparison. Major Findings: BFRP or Basalt rebar or Basalt offers competitive performance at a lower environmental cost. Basalt rebar shows promise as a sustainable alternative to steel and GFRP. BFRP is better in performance in terms of less corrosion than steel and GFRP. Steel, despite its poor environmental performance (i.e. in terms of air emission i.e. NOx and SOx, and waste water quality) remains widely used due to cost-effectiveness. Based on the environmental performance the research concluded: Basalt > GFRP > Steel. The economic viability of steel still remains, but basalt offers better eco-efficiency. LCA proves that basalt rebar is a strong alternative for sustainability.
Impact of solid waste landfill proximity on residential property offer values: a case study of Pune Abhijat Arun Abhyankar, Anand Prakash, Harish Kumar Singla International Journal of Housing Markets and Analysis, 2025 Purpose This study aims to examine whether or not residential properties closer to landfill sites have lower offer values by the developers. That is, by analyzing real estate data and landfill site locations, the study seeks to provide insights into whether properties situated closer to landfill sites tend to have a lower offer values than those located farther away. Design/methodology/approach The study is exploratory in nature, and a case study approach is applied. A landfill site named “Uruli Devachi” is selected in the region of Pune district, and data is collected from 102 developers selling residential projects within a radius of 15 km (about 9.32 mi). The gathered data is analyzed by using basic descriptive statistics, one-way ANOVA and ordinary least squares (OLS) regression. The OLS regression helps to determine whether there is a relationship between the distance of a residential property from a landfill site and its offer value. Findings The findings suggest that landfill sites have a detrimental impact on residential property offer values, with the negative impact increasing with proximity to a landfill site. The negative effect seems to vanish after over 10 km (about 6.21 mi). The developers provide extra facilities including a clubhouse, a children’s play area, a gym and a swimming pool in an effort to mitigate the negative effects of the landfill site on residential properties. Practical implications The findings of this study could have implications for property developers, real estate professionals and policymakers in understanding how landfill proximity might impact property offer values. Originality/value This study presents many novelties for the Indian housing market: the landfill sites do have a negative effect on the offer value of residential property; the closer the residential property to a landfill site, the higher the negative effect. Further, the developers try and mitigate the negative effect of landfill sites on residential properties by providing additional amenities such as a clubhouse, children’s play park, gym and swimming pool.
Comparing predictive performance of general regression neural network (GRNN) and hedonic regression model for factors affecting housing prices in “Pune-India” Abhijat Arun Abhyankar, Harish Kumar Singla International Journal of Housing Markets and Analysis, 2022 PurposeThe purpose of this study is to compare the predictive performance of the hedonic multivariate regression model with the probabilistic neural network (PNN)-based general regression neural network (GRNN) model of housing prices in “Pune-India.”Design/methodology/approachData on 211 properties across “Pune city-India” is collected. The price per square feet is considered as a dependent variable whereas distances from important landmarks such as railway station, fort, university, airport, hospital, temple, parks, solid waste site and stadium are considered as independent variables along with a dummy for amenities. The data is analyzed using a hedonic type multivariate regression model and GRNN. The GRNN divides the entire data set into two sets, namely, training set and testing set and establishes a functional relationship between the dependent and target variables based on the probability density function of the training data (Alomair and Garrouch, 2016).FindingsWhile comparing the performance of the hedonic multivariate regression model and PNN-based GRNN, the study finds that the output variable (i.e. price) has been accurately predicted by the GRNN model. All the 42 observations of the testing set are correctly classified giving an accuracy rate of 100%. According to Cortez (2015), a value close to 100% indicates that the model can correctly classify the test data set. Further, the root mean square error (RMSE) value for the final testing for the GRNN model is 0.089 compared to 0.146 for the hedonic multivariate regression model. A lesser value of RMSE indicates that the model contains smaller errors and is a better fit. Therefore, it is concluded that GRNN is a better model to predict the housing price functions. The distance from the solid waste site has the highest degree of variable senstivity impact on the housing prices (22.59%) followed by distance from university (17.78%) and fort (17.73%).Research limitations/implicationsThe study being a “case” is restricted to a particular geographic location hence, the findings of the study cannot be generalized. Further, as the objective of the study is restricted to just to compare the predictive performance of two models, it is felt appropriate to restrict the scope of work by focusing only on “location specific hedonic factors,” as determinants of housing prices.Practical implicationsThe study opens up a new dimension for scholars working in the field of housing prices/valuation. Authors do not rule out the use of traditional statistical techniques such as ordinary least square regression but strongly recommend that it is high time scholars use advanced statistical methods to develop the domain. The application of GRNN, artificial intelligence or other techniques such as auto regressive integrated moving average and vector auto regression modeling helps analyze the data in a much more sophisticated manner and help come up with more robust and conclusive evidence.Originality/valueTo the best of the author’s knowledge, it is the first case study that compares the predictive performance of the hedonic multivariate regression model with the PNN-based GRNN model for housing prices in India.
Identification of vulnerable areas in municipal corporation of Greater Mumbai due to extreme events based on socio economic indicators Indian Journal of Marine Sciences, 2013
Estimation of flooded areas due to supercyclone using Radarsat-1 SAR data and discriminant approach - An Indian case study 33rd Asian Conference on Remote Sensing 2012 Acrs 2012, 2012
Identifying patterns of tropical cyclones making landfall on Indian coast using gis 33rd Asian Conference on Remote Sensing 2012 Acrs 2012, 2012
Spectral responses of water subclasses in C band HH polarized data 29th Asian Conference on Remote Sensing 2008 Acrs 2008, 2008
Monitoring changes in rice due to tropical Cyclone using Radarsat-1 SAR data 29th Asian Conference on Remote Sensing 2008 Acrs 2008, 2008
Chlorophyll concentration studies in the Thane creek, Mumbai, India, through remote sensing: Comparison of ground truth and OCM (IRS-P4) data Progress in Water Resources, 2003
RECENT SCHOLAR PUBLICATIONS
Compressed Stabilized Earth Blocks for Sustainable Building Construction: A PRISMA-Guided Systematic Review and TCCM Analysis S Sinha, JS Sudarsan, AA Abhyankar Buildings 16 (8), 1633 , 2026 2026
Integrating ESG principles in India's construction sector: A comprehensive assessment AA Abhyankar, JS Sudarsan, V Balon Journal of Environmental Biology , 2026 2026
Resilient and sustainable construction industry: leveraging crisis and lean management JS Sudarsan, J Rajprasad, V V. Gedam, A A. Abhyankar, N S. Sriram, ... International Journal of Construction Management 26 (2), 219-233 , 2026 2026 Citations: 2
Life Cycle Analysis of Steel, Glass Fiber Rebar Polymer and Basalt Fiber Reinforcement Polymer. V Balon, AA Abhyankar, JS Sudarsan Journal of Mines, Metals & Fuels 73 (5) , 2025 2025
Impact of solid waste landfill proximity on residential property offer values: a case study of Pune AA Abhyankar, A Prakash, HK Singla International Journal of Housing Markets and Analysis 18 (2), 334-353 , 2025 2025 Citations: 13
Damage Assessment Due to Wildfire Using Remote Sensing and GIS: An Indian Case Study of Similipal, Odisha C Singh, A Naithani, Y Solanki, A Jaiswal, V Patil, A Abhyankar International Conference on Construction, Real Estate, Infrastructure … , 2024 2024
Understanding the Awareness of Consumers About EPR with Respect to E-Waste JS Sudarsan, AA Abhyankar, S Sinha, A Poddar, C Baruah, C Nema, ... International Conference on Construction, Real Estate, Infrastructure … , 2023 2023 Citations: 1
Analysis of construction and demolition (C&D) waste management framework in India: strategies for improvement JS Sudarsan, PK Samanta, AA Abhyankar, S Sinha International Conference on Recent Developments in Sustainable … , 2023 2023 Citations: 1
Identification of Incinerator Sites for Disposal of Bio-Medical Waste Using Remote Sensing and Geographic Information Systems: An Indian Case Study A Bandyopadhyay, KK Shetty, A Chahande, AA Abhyankar Journal of Real Estate, Construction & Management 38 (1), 32-42 , 2023 2023
Assessing the Air Quality of Pune Using Unsupervised Classification Technique Y Parekh, M Keswani, S Dama, N Bhudhrani, AA Abhyankar Journal of Real Estate, Construction & Management 37 (S1), 130-137 , 2022 2022
Analysing construction and demolition waste practices: an Indian case study JS Sudarsan, AA Abhyankar, A Parashar, SV Krishna Recent Developments in Sustainable Infrastructure (ICRDSI-2020)—Structure … , 2022 2022 Citations: 7
Comparing predictive performance of general regression neural network (GRNN) and hedonic regression model for factors affecting housing prices in “Pune-India” AA Abhyankar, HK Singla International Journal of Housing Markets and Analysis 15 (2), 451-477 , 2022 2022 Citations: 20
Mapping and change detection of mangroves around Mumbai using remote sensing and geographic information systems (Gis) A Abhyankar, T Sahoo, B Seth, P Mohapatra, S Palai, P Bhargava, ... Journal of Civil Engineering 12 (1) , 2021 2021 Citations: 2
CREATION OF TELANGANA: A CASE FOR A BETTER GOVERNED SMALLER STATE RB Shah, P Kumar, MM Varadpande, S Singh, A Abhyankar Journal of Emerging Technologies and Business Management 10 (1), 36 , 2021 2021 Citations: 1
Real Estate Housing Prices And Microeconomic Theory: Case Study Of Four Indian Metro Cities S Sinha, A Kulkarni, L Pothen, A Shirodkar, U Lonare, AA Abhyankar BVIMSR’s Journal of Management Research 12 (2), 48-58 , 2020 2020 Citations: 1
PRICING DRINKING WATER-IS IT ETHICAL?-TEACHING NOTE. A Gautam, K Bang, A Kalia, M Kotian, R Gupta, D Desai, AA Abhyankar Global Management Review 14 (2) , 2020 2020 Citations: 1
Pricing Drinking Water-is it ethical?-case stuDy A Gautam, K Bang, A Kalia, M Kotian, R Gupta, D Desai, AA Abhyankar Global Management Review 14 (2), 75-82 , 2020 2020
Identification of flooded areas due to severe storm using envisat asar data and neural networks A Abhyankar, A Patwardhan, M Paliwal, A Inamdar Journal of Civil Engineering, Science and Technology 10 (2), 113-120 , 2019 2019 Citations: 14
PLASTIC BAN IN MAHARASHTRA STATE FROM MARCH 2018: IS IT A WIN-WIN POLICY? 1 N Singh, C Agrawal, A Vora, AA Angadi, AA Abhyankar Global Management Review 12 (2), 35-42 , 2018 2018
PLASTIC BAN IN MAHARASHTRA STATE FROM MARCH 2018: IS IT A WIN-WIN POLICY? N Singh, C Agrawal, A Vora, AA Angadi, AA Abhyankar Global Management Review 12 (2), 43-54 , 2018 2018 Citations: 1
MOST CITED SCHOLAR PUBLICATIONS
Comparing predictive performance of general regression neural network (GRNN) and hedonic regression model for factors affecting housing prices in “Pune-India” AA Abhyankar, HK Singla International Journal of Housing Markets and Analysis 15 (2), 451-477 , 2022 2022 Citations: 20
Identification of flooded areas due to severe storm using envisat asar data and neural networks A Abhyankar, A Patwardhan, M Paliwal, A Inamdar Journal of Civil Engineering, Science and Technology 10 (2), 113-120 , 2019 2019 Citations: 14
Impact of solid waste landfill proximity on residential property offer values: a case study of Pune AA Abhyankar, A Prakash, HK Singla International Journal of Housing Markets and Analysis 18 (2), 334-353 , 2025 2025 Citations: 13
Identification of vulnerable areas in municipal corporation of Greater Mumbai due to extreme events based on socio economic indicators AA Abhyankar, M Paliwal, A Patwardhan, AB Inamdar Indian Journal of Geo-Marine Sciences 42 (7), 907-914 , 2013 2013 Citations: 8
Analysing construction and demolition waste practices: an Indian case study JS Sudarsan, AA Abhyankar, A Parashar, SV Krishna Recent Developments in Sustainable Infrastructure (ICRDSI-2020)—Structure … , 2022 2022 Citations: 7
Environmental knowledge for disaster risk management AK Gupta, SS Nair Abstract Volume of International Conference, 10-11 , 2011 2011 Citations: 7
Constructing a tropical cyclone hazard index for coastal India AA Abhyankar, A Singh, U Sharma, A Patwardhan, AB Inamdar International Symposium on Natural Hazards, Hyderabad, February, 24-28 , 2004 2004 Citations: 5
Extreme Weather Events in India-A Preliminary Analysis of Impacts A Singh, A Patwardhan, A Abhyankar, NL Sarda IIT Bombay, India , 2011 2011 Citations: 3
Identification of Completely Submerged Areas Due to Tropical Cyclone using Satellite Data: An Indian Case Study A Abhyankar, A Patwardhan, A Inamdar 2006 IEEE International Symposium on Geoscience and Remote Sensing, 3305-3308 , 2006 2006 Citations: 3
Chlorophyll concentration studies in the Thane creek, Mumbai, India, through remote sensing: Comparison of ground truth and OCM (IRS-P4) data S Baji, AB Inamdar, AA Abhyankar, AS Rajawat, M Gupta WIT Transactions on Ecology and the Environment 65 , 2003 2003 Citations: 3
Resilient and sustainable construction industry: leveraging crisis and lean management JS Sudarsan, J Rajprasad, V V. Gedam, A A. Abhyankar, N S. Sriram, ... International Journal of Construction Management 26 (2), 219-233 , 2026 2026 Citations: 2
Mapping and change detection of mangroves around Mumbai using remote sensing and geographic information systems (Gis) A Abhyankar, T Sahoo, B Seth, P Mohapatra, S Palai, P Bhargava, ... Journal of Civil Engineering 12 (1) , 2021 2021 Citations: 2
Understanding the Awareness of Consumers About EPR with Respect to E-Waste JS Sudarsan, AA Abhyankar, S Sinha, A Poddar, C Baruah, C Nema, ... International Conference on Construction, Real Estate, Infrastructure … , 2023 2023 Citations: 1
Analysis of construction and demolition (C&D) waste management framework in India: strategies for improvement JS Sudarsan, PK Samanta, AA Abhyankar, S Sinha International Conference on Recent Developments in Sustainable … , 2023 2023 Citations: 1
CREATION OF TELANGANA: A CASE FOR A BETTER GOVERNED SMALLER STATE RB Shah, P Kumar, MM Varadpande, S Singh, A Abhyankar Journal of Emerging Technologies and Business Management 10 (1), 36 , 2021 2021 Citations: 1
Real Estate Housing Prices And Microeconomic Theory: Case Study Of Four Indian Metro Cities S Sinha, A Kulkarni, L Pothen, A Shirodkar, U Lonare, AA Abhyankar BVIMSR’s Journal of Management Research 12 (2), 48-58 , 2020 2020 Citations: 1
PRICING DRINKING WATER-IS IT ETHICAL?-TEACHING NOTE. A Gautam, K Bang, A Kalia, M Kotian, R Gupta, D Desai, AA Abhyankar Global Management Review 14 (2) , 2020 2020 Citations: 1
PLASTIC BAN IN MAHARASHTRA STATE FROM MARCH 2018: IS IT A WIN-WIN POLICY? N Singh, C Agrawal, A Vora, AA Angadi, AA Abhyankar Global Management Review 12 (2), 43-54 , 2018 2018 Citations: 1
SOCIO-ECONOMIC ANALYSIS OF CONSTRUCTION WORKERS IN AND AROUND BANER BALEWADI AREA A Shewale, S Kalantri, A Rai, AA Abhyankar BVIMSR’s Journal of Management Research 10 (1), 42-50 , 2018 2018 Citations: 1
Qualitative approaches to rapidly identify completely submerged rice due to tropical cyclone using satellite data AA Abhyankar, A Patwardhan, A Inamdar 2007 IEEE International Geoscience and Remote Sensing Symposium, 1283-1286 , 2007 2007 Citations: 1