Designation: Associate Professor
Department: Management Studies and Industrial Engineering
Email: krishnendu[at]iitism[dot]ac[dot]in
Contact Number:
Personal Page: Under Construction
About Me: Dr. Krishnendu Shaw is an Associate Professor in the Department of Management Studies and Industrial Engineering at the Indian Institute of Technology (Indian School of Mines), Dhanbad. He obtained his Ph.D. from the Indian Institute of Technology Delhi (IIT Delhi). Prior to his current position, Dr. Shaw served as an Assistant Professor at IIT (ISM) Dhanbad, where he joined in 2014. Dr. Shaw’s academic and research interests lie at the interface of management science and industrial engineering, with a focus on operations management, sustainable development, supply chain optimization, and decision analytics. His work emphasizes the application of quantitative and optimization-based methodologies to address real-world industrial and socio-economic challenges. He has published extensively in reputed national and international journals and conference proceedings, with his research achieving significant citation impact, reflected in an h-index of approximately 17. Dr. Shaw has also supervised research scholars and postgraduate students in diverse areas of management and systems engineering. In addition to his academic contributions, Dr. Shaw has been actively involved in sponsored research and consultancy projects, including initiatives supported by government and institutional funding. Dr. Shaw continues to contribute to the academic community through teaching, research, and institutional service, fostering interdisciplinary engagement and advancing the frontiers of management and industrial systems research.
Research Interest: Supply Chain Management; Lot-sizing; Mathematical Modelling (Mixed integer programming; Fuzzy Optimization; Goal Programming; Benders Decomposition; Lagrangian Relaxation; Possibilistic Programming; e-constraint Method, Robust Optimization etc); Sustainable Development (ESG quantification; Social Sustainability Quantification); Exploring AI adoption using SEM modelling; Portfolio Optimization & Topics of behavioral finance and crypto currency adoption; Service Operations Management.
Current Teaching
Operations Management
Supply Chain Management
Software Lab
Courses Taught Previously
Service Operations Management
Research Methodology & Statistics
Operations Research
Project Management
Industrial Engineering & Management
Materials Management
PhD in Supply Chain Management - IIT Delhi (NIRF - 4th Rank 2025)
PhD Topic: Low Carbon Global Supply Chain: a Study of Indian Textile Sector
M.Tech - IIT Delhi
B.Tech - Govt. College of Engineering & Textile Technology, Serampore
Currently - Associate Professor
MBA admission coordinator
Administrative Position Served
- Warden of Emerald Hostel
- DAC Secretary
- DPGC Convener
- Library Committee
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2021 2009-2014 |
Highly cited article in Technology in Society, Elsevier Awarded institute scholarship during PhD. |
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2013 |
The “Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain” paper was in the list of most Top 25 Hottest Articles in Expert Systems with Applications Journal, from January – March 2013. |
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2012 |
Got Best paper award in 16th Annual conference of Society of Operations Management, held at Indian Institute of Technology Delhi, on December 21-23, 2012. |
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2006-2008 |
Awarded MHRD scholarship during M. Tech. |
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2006 |
Ranked among Top 5 in Textile Technology during B. Tech under WBUT University, West Bengal. Ranked 25th in GATE Examination. |
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2005 |
Awarded Platinum Jubilee Celebration Trust Scholarship for achieving 1st position in the institution (G.C.E.T.T.S) in the 3rd Year in B. Tech. |
2025
Roy, R., Shaw, K., Mishra, S., & Shankar, R. (2025). Lagrangian relaxation-based heuristics for solving uncertain supply chain network design problem addressing supplier’s ESG factor. Journal of Modelling in Management.
→ ABDC = C, Scopus indexed.
Mishra, S., Shaw, K., & Shukla, N. (2025). Integrating environmental, social and risk factors in lot-sizing and supply chain network design. Journal of the Operational Research Society, 1–34.
→ ABDC = A, SCI / SSCI, Q1.
Mishra, S., & Shaw, K. (2025). Integration of capacitated lot sizing decision and supply chain network design model addressing sustainable and risk factors. Journal of Modelling in Management.
→ ABDC = C, Scopus indexed.
2023
Roy, P. K., & Shaw, K. (2023). A credit scoring model for SMEs using AHP and TOPSIS. International Journal of Finance & Economics, 28(1), 372–391.
→ ABDC = B, SSCI, Q2.
Roy, P. K., Shaw, K., & Ishizaka, A. (2023). Developing an integrated fuzzy credit rating system for SMEs using fuzzy-BWM and fuzzy-TOPSIS-Sort-C. Annals of Operations Research, 325(2), 1197–1229.
→ ABDC = A, SCI, Q1.
Roy, P., & Shaw, K. (2023). A fuzzy MCDM decision-making model for m-banking evaluations: Comparing several m-banking applications. Journal of Ambient Intelligence and Humanized Computing, 14(9), 11873–11895.
→ SCI (Springer), Q1.
Roy, P. K., & Shaw, K. (2023). An integrated fuzzy credit rating model using fuzzy-BWM and new fuzzy-TOPSIS-Sort-C. Complex & Intelligent Systems, 9(4), 3581–3600.
→ SCI, Q1.
Shaw, K., Lahri, V., Shankar, R., & Ishizaka, A. (2023). Joint multi-item multi-supplier sustainable lot-sizing model applying combined BWM, TOPSIS, possibilistic programming, and ε-constraint method. IEEE Transactions on Engineering Management, 71, 4530–4547.
→ ABDC = A, SCI, Q1.
2022
Roy, P. K., & Shaw, K. (2022). An integrated fuzzy model for evaluation and selection of mobile banking (m-banking) applications using new fuzzy-BWM and fuzzy-TOPSIS. Complex & Intelligent Systems, 8(3), 2017–2038.
→ SCI, Q1.
Roy, P. K., & Shaw, K. (2022). Developing a multi-criteria sustainable credit score system using fuzzy BWM and fuzzy TOPSIS. Environment, Development and Sustainability, 24(4), 5368–5399.
→ SCI, Q1.
Lahri, V., & Shaw, K. (2022). Multi-objective sustainable distribution network design under uncertain environment. In Flexibility, Innovation, and Sustainable Business (pp. 231–243). Springer→ Book chapter (Scopus indexed).
2021
Rajak, M., & Shaw, K. (2021). An extension of technology acceptance model for mHealth user adoption. Technology in Society, 67, Article 101800.
→ ABDC = A, SSCI, Q1.
Lahri, V., Shaw, K., & Ishizaka, A. (2021). Sustainable supply chain network design problem: Using the integrated BWM, TOPSIS, possibilistic programming, and ε-constrained methods. Expert Systems with Applications, 168, Article 114373.
→ SCI, Q1.
Irfan, M., Yadav, S., & Shaw, K. (2021). The adoption of solar photovoltaic technology among Indian households: Examining the influence of entrepreneurship. Technological Forecasting and Social Change, 169, 120815.
→ ABDC = A, SSCI, Q1.
Roy, P. K., & Shaw, K. (2021). A multicriteria credit scoring model for SMEs using hybrid BWM and TOPSIS. Financial Innovation, 7(1), 77.
→ SSCI, Q1.
2020
Das, R., Shaw, K., & Irfan, M. (2020). Supply chain network design considering carbon footprint, water footprint, supplier’s social risk, solid waste, and service level under the uncertain condition. Clean Technologies and Environmental Policy, 22(2), 337–370.
→ SCI, Q2.
2019
Rajak, M., & Shaw, K. (2019). Evaluation and selection of mobile health (mHealth) applications using AHP and fuzzy TOPSIS. Technology in Society, 59, 101186.
→ ABDC = A, SSCI, Q1.
Shaw, K. (2019). Implementing sustainability in global supply chain. Problemy Ekorozwoju, 14(2).
→ Scopus indexed, not in ABDC.
2017
Irfan, M., & Shaw, K. (2017). Modeling the effects of energy consumption and urbanization on environmental pollution in South Asian countries: A nonparametric panel approach. Quality & Quantity, 51(1), 65–78.
→ SCI, Q2.
Das, R., & Shaw, K. (2017). Uncertain supply chain network design considering carbon footprint and social factors using two-stage approach. Clean Technologies and Environmental Policy, 19(10), 2491–2519.
→ SCI, Q2.
Shaw, K. (2017). Fuzzy multi-objective, multi-item, multi-supplier lot-sizing considering carbon footprint. International Journal of Mathematics in Operational Research, 11(2), 171–203.
→ Scopus indexed.
2016
Shaw, K., Irfan, M., Shankar, R., & Yadav, S. S. (2016). Low carbon chance constrained supply chain network design problem: a Benders decomposition-based approach. Computers & Industrial Engineering, 98, 483–497.
→ ABDC = A, SCI, Q1.
Shaw, K., Shankar, R., & Yadav, S. S. (2016). Carbon constrained dual sourcing supplier selection problem: a Benders decomposition approach. International Journal of Logistics Systems and Management, 23(3), 363–393.
→ Scopus indexed.
2013
Shaw, K., Shankar, R., Yadav, S. S., & Thakur, L. S. (2013). Modeling a low-carbon garment supply chain. Production Planning & Control, 24(8–9), 851–865.
→ ABDC = A, SCI, Q1.
Shaw, K., Shankar, R., Yadav, S. S., & Thakur, L. S. (2013). Global supplier selection considering sustainability and carbon footprint issue: AHP multi-objective fuzzy linear programming approach. International Journal of Operational Research, 17(2), 215–247.
→ Scopus indexed.
2012
Shaw, K., Shankar, R., Yadav, S. S., & Thakur, L. S. (2012). Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low-carbon supply chain. Expert Systems with Applications, 39(9), 8182–8192.
→ SCI, Q1.
R&D Project
1. Understanding the Drivers and Barriers of Adopting Solar Pumps under PM KUSUM Yojana among Marginalised and Tribal Farmers in Jharkhand - Finding Agency ICSSR
1. Dr. Manindra Rajak - Assistant Professor - XISS Ranchi - https://www.xiss.ac.in/faculty/dr-manindra-rajak
2. Dr. Vijay Lahri - Assistant Professor - Universiti Teknologi PETRONAS - Singapore
3. Dr. Pranit Roy - Assistant Professor - IIM Raipur ; https://iimraipur.ac.in/profile/?uid=33&re=1
PhD Ongoing Sole Supervision
4. Shivam Mishra - Supply Chain Modelling using Lagrangian Relaxation
5. Sandeep Singh - Portfolio Optimization
Part-Time PhD Students (Sole Supervision)
6. Ghanadip Das - Tata Consultancy Services
7. Babun Mondal - Mind Tree Ltd.
8. Bireshwar Bannerjee - Jpmorgan Services Ltd
9. Bikash Ghosh - Tata Steel
10. Souvik Bisai - IIT Kgp
