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Book ; Online: Sustainable Assessment in Supply Chain and Infrastructure Management

Kabir, Golam / Paul, Sanjoy Kumar / Ali, Syed Mithun

2022

Keywords	Technology: general issues ; History of engineering & technology ; green supply chain ; performance measurement ; Bayesian belief network ; sustainability ; trenchless technologies ; pipelines ; construction ; social cost ; fuzzy QFD ; flexibility ; IT flexibility ; importance‒performance analysis ; partial least squared structured equation modelling ; performance gap ; sustainable growth ; higher educational institutions ; academic buildings ; environmental performance ; performance benchmarking ; fuzzy clustering analysis ; metabolic flows ; green supply chain management ; carbon tax and cap ; can-order policy ; mixed-integer programming ; fuzzy constraints ; social sustainability ; small- and medium-sized enterprises (SMEs) ; stakeholder support ; social sustainability awareness ; transport networks ; logistics ; simulation games ; serious games ; innovation ecosystem ; Port of Rotterdam ; complex systems ; truck platooning ; barge transport ; multi-sided platforms ; Bayesian ; geoadditive ; quantile ; P-splines ; boosting optimization ; resilience ; housing infrastructure ; flood hazard and sensitivity analysis ; shipping cost ; risk assessment and management ; conditional value-at-risk ; investment projects ; financial analysis ; economic analysis ; energy efficiency ; public buildings ; literature review ; multi-criteria decision-making ; MCDM methods ; sustainable supply chain management ; SSCM ; efficiency assessment ; operations strategy matrix ; data envelopment analysis ; healthcare systems ; COVID-19 ; n/a
Language	0\|e
Size	1 electronic resource (274 pages)
Publisher	MDPI - Multidisciplinary Digital Publishing Institute
Publishing place	Basel
Document type	Book ; Online
Note	English ; Open Access
HBZ-ID	HT021619661
ISBN	9783036545202 ; 3036545204
Database	ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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Article ; Online: Sustainable Assessment in Supply Chain and Infrastructure Management

Golam Kabir / Sanjoy Kumar Paul / Syed Mithun Ali

Sustainability, Vol 14, Iss 6787, p

2022 Volume 6787

Abstract: Assessing sustainability in supply chain and infrastructure management is important for any organization in the competitive business environment or public domain [.] ...

Abstract	Assessing sustainability in supply chain and infrastructure management is important for any organization in the competitive business environment or public domain [.]
Keywords	n/a ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
Language	English
Publishing date	2022-06-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Benchmarking sustainable E-commerce enterprises based on evolving customer expectations amidst COVID-19 pandemic.

Pratap, Saurabh / Jauhar, Sunil Kumar / Daultani, Yash / Paul, Sanjoy Kumar

Business strategy and the environment

2022

Abstract: The 2019 coronavirus disease (COVID-19) pandemic has seriously impacted the performance of all types of businesses. It has given a tremendous structural boost to e-commerce enterprises by forcing customers to online shopping over visiting physical stores. ...

Abstract	The 2019 coronavirus disease (COVID-19) pandemic has seriously impacted the performance of all types of businesses. It has given a tremendous structural boost to e-commerce enterprises by forcing customers to online shopping over visiting physical stores. Moreover, customer expectations of the digital and operational capabilities of e-commerce firms are also increasing globally. Thus, it has become crucial for an e-commerce enterprise to reassess and realign its business practices to meet evolving customer needs and remain sustainable. This paper presents a comprehensive performance evaluation framework for e-commerce enterprises based on evolving customer expectations due to the COVID-19 pandemic. The framework comprises seven primary criteria, which are further divided into 25 sub-criteria, including two sustainability factors, namely, environmental sustainability and carbon emissions. The evaluation approach is then practically demonstrated by analyzing the case of three Indian e-commerce firms. The results are obtained using a multi-criteria decision-making (MCDM) method, namely, Fuzzy VIKOR, to capture the fuzziness of the inherent decision-making problem. Further, numerical analysis is conducted to evaluate and rank various e-commerce enterprises based on customer expectations and satisfaction benchmarks. The findings explain the most important criteria and sub-criteria for e-commerce businesses to ensure customer expectations along with their economic and environmental sustainability.
Language	English
Publishing date	2022-06-24
Publishing country	United States
Document type	Journal Article
ZDB-ID	2025936-0
ISSN	1099-0836 ; 0964-4733
ISSN (online)	1099-0836
ISSN	0964-4733
DOI	10.1002/bse.3172
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Strategies for Managing the Impacts of Disruptions During COVID-19: an Example of Toilet Paper.

Paul, Sanjoy Kumar / Chowdhury, Priyabrata

Global journal of flexible systems management

2020 Volume 21, Issue 3, Page(s) 283–293

Abstract: Due to the recent pandemic of coronavirus, known as the COVID-19 outbreak, the supply chains have been impacted most significantly. Manufacturers of certain items have experienced a substantial increase in demand, and on the other hand, raw materials ... ...

Abstract	Due to the recent pandemic of coronavirus, known as the COVID-19 outbreak, the supply chains have been impacted most significantly. Manufacturers of certain items have experienced a substantial increase in demand, and on the other hand, raw materials supply, to produce those items, has reduced because of supply failure. To overcome these challenges, this paper proposes some strategies to improve service level during an extraordinary pandemic outbreak, such as COVID-19, for the most wanted products such as toilet paper. This study considers meeting the increased demand of the customers for an essential product of daily life like toilet paper during a pandemic is beyond the traditional economic objective, i.e., increase profit, of the manufacturers. Instead, this should be more about the social responsibility of all the manufactures to ensure that they can serve more customers. Motivated by this and taking toilet paper as an example of the product, we first analyzed the current scenario of the manufacturing and the demand for the product and then proposed some strategies to deal with this unprecedented risk and analyzed the results. We have compared the results, using hypothetical data, between the current scenario and proposed strategies. The result shows that sharing information and resources from all manufacturers to produce under a single brand, emergency sourcing, producing basic quality items, and packing in the smallest sizes have a significant positive impact on the service level. This paper first investigates the strategies for a high-demand and essential item during a pandemic situation and proposes strategies to deal with this unique, extraordinary disruption.
Language	English
Publishing date	2020-07-12
Publishing country	India
Document type	Journal Article
ZDB-ID	2135478-9
ISSN	0974-0198 ; 0972-2696
ISSN (online)	0974-0198
ISSN	0972-2696
DOI	10.1007/s40171-020-00248-4
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Modeling the artificial intelligence-based imperatives of industry 5.0 towards resilient supply chains: A post-COVID-19 pandemic perspective.

Ahmed, Tazim / Karmaker, Chitra Lekha / Nasir, Sumaiya Benta / Moktadir, Md Abdul / Paul, Sanjoy Kumar

Computers & industrial engineering

2023 Volume 177, Page(s) 109055

Abstract: The recent COVID-19 pandemic has significantly affected emerging economies' global supply chains (SCs) by disrupting their manufacturing activities. To ensure business survivability during the current and post-COVID-19 era, it is crucial to adopt ... ...

Abstract	The recent COVID-19 pandemic has significantly affected emerging economies' global supply chains (SCs) by disrupting their manufacturing activities. To ensure business survivability during the current and post-COVID-19 era, it is crucial to adopt artificial intelligence (AI) technologies to renovate traditional manufacturing activities. The fifth industrial revolution, Industry 5.0 (I5.0), and artificial intelligence (AI) offer the overwhelming potential to build an inclusive digital future by ensuring supply chain (SC) resiliency and sustainability. Accordingly, this research aims to identify, assess, and prioritize the AI-based imperatives of I5.0 to improve SC resiliency. An integrated and intelligent approach consisting of Pareto analysis, the Bayesian approach, and the Best-Worst Method (BWM) was developed to fulfill the objectives. Based on the literature review and expert opinions, nine AI-based imperatives were identified and analyzed using Bayesian-BWM to evaluate their potential applicability. The findings reveal that real-time tracking of SC activities using the Internet of Things (IoT) is the most crucial AI-based imperative to improving a manufacturing SC's survivability. The research insights can assist industry leaders, practitioners, and relevant stakeholders in dealing with the impacts of large-scale SC disruptions in the post-COVID-19 era.
Language	English
Publishing date	2023-01-31
Publishing country	England
Document type	Journal Article
ISSN	1879-0550
ISSN (online)	1879-0550
DOI	10.1016/j.cie.2023.109055
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: A framework for the estimation of treatment costs of cardiovascular conditions in the presence of disease transition.

Goswami, Mohit / Daultani, Yash / Paul, Sanjoy Kumar / Pratap, Saurabh

Annals of operations research

2022 , Page(s) 1–40

Abstract: The current research aims to aid policymakers and healthcare service providers in estimating expected long-term costs of medical treatment, particularly for chronic conditions characterized by disease transition. The study comprised two phases ( ... ...

Abstract	The current research aims to aid policymakers and healthcare service providers in estimating expected long-term costs of medical treatment, particularly for chronic conditions characterized by disease transition. The study comprised two phases (qualitative and quantitative), in which we developed linear optimization-based mathematical frameworks to ascertain the expected long-term treatment cost per patient considering the integration of various related dimensions such as the progression of the medical condition, the accuracy of medical treatment, treatment decisions at respective severity levels of the medical condition, and randomized/deterministic policies. At the qualitative research stage, we conducted the data collection and validation of various cogent hypotheses acting as inputs to the prescriptive modeling stage. We relied on data collected from 115 different cardio-vascular clinicians to understand the nuances of disease transition and related medical dimensions. The framework developed was implemented in the context of a multi-specialty hospital chain headquartered in the capital city of a state in Eastern India, the results of which have led to some interesting insights. For instance, at the prescriptive modeling stage, though one of our contributions related to the development of a novel medical decision-making framework, we illustrated that the randomized versus deterministic policy seemed more cost-competitive. We also identified that the expected treatment cost was most sensitive to variations in steady-state probability at the "major" as opposed to the "severe" stage of a medical condition, even though the steady-state probability of the "severe" state was less than that of the "major" state.
Language	English
Publishing date	2022-08-23
Publishing country	United States
Document type	Journal Article
ISSN	0254-5330
ISSN	0254-5330
DOI	10.1007/s10479-022-04914-x
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Modeling the blockchain readiness challenges for product recovery system.

Dwivedi, Ashish / Agrawal, Dindayal / Paul, Sanjoy Kumar / Pratap, Saurabh

Annals of operations research

2022 , Page(s) 1–45

Abstract: Product Recovery System (PRS) transfers products from their typical final place to their source to arrest some value on the product. There are obstructions, such as costs, associated with the modification of accounts and assessment of products and ... ...

Abstract	Product Recovery System (PRS) transfers products from their typical final place to their source to arrest some value on the product. There are obstructions, such as costs, associated with the modification of accounts and assessment of products and refunds associated with the implementation of PRS. Blockchain Technology (BCT) emerged as an innovative approach to constructing trust in a trust less environment and assures the availability, traceability, and security in data management. It also presents a valuable solution to PRS. This study aims to analyze the Blockchain Readiness Challenges (BRCs) to PRS in the context of manufacturing industries. The study observes 20 readiness challenges linked with the implementation of BCT in PRS. The BRCs are identified from the literature survey and confirmed after consequent examinations with industry experts and researchers. The study employed a Multi-Criteria Decision-Making (MCDM) i.e., the Decision-Making Trial And Evaluation Laboratory (Fuzzy DEMATEL) approach to find the cause-and-effect interactions to prioritize BRCs. The Maximum Mean De-Entropy (MMDE) algorithm was adopted to establish the threshold value based on the information entropy of the interactions among the BRCs for PRS. The fuzzy set theory was adopted to tackle the uncertainty and vagueness of personnel biases and data deficiency problems. The findings from this study reveal that inadequate financing for PRS exercises, lack of governance and standards, and security challenges to BCT implementation are the most influential readiness challenges for the adoption of blockchain in PRS. The study is useful to manufacturing organizations for identifying the potential BRCs to implement PRS among all existing readiness challenges so that they can take suitable measures before proceeding to adopt blockchain in PRS. The managers are suggested to eliminate the readiness challenges and widen the blockchain technology adoption in PRS.
Language	English
Publishing date	2022-01-20
Publishing country	United States
Document type	Journal Article
ISSN	0254-5330
ISSN	0254-5330
DOI	10.1007/s10479-021-04468-4
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Strategies for Managing the Impacts of Disruptions During COVID-19

Paul, Sanjoy Kumar / Chowdhury, Priyabrata

Global Journal of Flexible Systems Management

an Example of Toilet Paper

2020 Volume 21, Issue 3, Page(s) 283–293

Keywords	Strategy and Management ; Business and International Management ; covid19
Language	English
Publisher	Springer Science and Business Media LLC
Publishing country	us
Document type	Article ; Online
ZDB-ID	2135478-9
ISSN	0974-0198 ; 0972-2696
ISSN (online)	0974-0198
ISSN	0972-2696
DOI	10.1007/s40171-020-00248-4
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: A mathematical model for managing the multi-dimensional impacts of the COVID-19 pandemic in supply chain of a high-demand item.

Paul, Sanjoy Kumar / Chowdhury, Priyabrata / Chakrabortty, Ripon Kumar / Ivanov, Dmitry / Sallam, Karam

Annals of operations research

2022 , Page(s) 1–46

Abstract: The COVID-19 pandemic has wreaked havoc across supply chain (SC) operations worldwide. Specifically, decisions on the recovery planning are subject to multi-dimensional uncertainty stemming from singular and correlated disruptions in demand, supply, and ... ...

Abstract	The COVID-19 pandemic has wreaked havoc across supply chain (SC) operations worldwide. Specifically, decisions on the recovery planning are subject to multi-dimensional uncertainty stemming from singular and correlated disruptions in demand, supply, and production capacities. This is a new and understudied research area. In this study, we examine, SC recovery for high-demand items (e.g., hand sanitizer and face masks). We first developed a stochastic mathematical model to optimise recovery for a three-stage SC exposed to the multi-dimensional impacts of COVID-19 pandemic. This allows to generalize a novel problem setting with simultaneous demand, supply, and capacity uncertainty in a multi-stage SC recovery context. We then developed a chance-constrained programming approach and present in this article a new and enhanced multi-operator differential evolution variant-based solution approach to solve our model. With the optimisation, we sought to understand the impact of different recovery strategies on SC profitability as well as identify optimal recovery plans. Through extensive numerical experiments, we demonstrated capability towards efficiently solving both small- and large-scale SC recovery problems. We tested, evaluated, and analyzed different recovery strategies, scenarios, and problem scales to validate our approach. Ultimately, the study provides a useful tool to optimise reactive adaptation strategies related to how and when SC recovery operations should be deployed during a pandemic. This study contributes to literature through development of a unique problem setting with multi-dimensional uncertainty impacts for SC recovery, as well as an efficient solution approach for solution of both small- and large-scale SC recovery problems. Relevant decision-makers can use the findings of this research to select the most efficient SC recovery plan under pandemic conditions and to determine the timing of its deployment.
Language	English
Publishing date	2022-04-11
Publishing country	United States
Document type	Journal Article
ISSN	0254-5330
ISSN	0254-5330
DOI	10.1007/s10479-022-04650-2
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Stochastic optimization approach for green routing and planning in perishable food production

Pratap, Saurabh / Jauhar, Sunil Kumar / Paul, Sanjoy Kumar / Zhou, Fuli

Elsevier Ltd Journal of cleaner production. 2022 Jan. 20, v. 333

2022

Abstract: Perishable food products present a production-inventory routing dilemma critical to logistics planning for several industries. Due to the speedy deterioration of perishable food products, proper production, inventory, and shipping planning are essential. ...

Abstract	Perishable food products present a production-inventory routing dilemma critical to logistics planning for several industries. Due to the speedy deterioration of perishable food products, proper production, inventory, and shipping planning are essential. Meanwhile, the growing impact of greenhouse emissions due to fuel usage indicates that mitigation for these impacts must be factored into the routing problem. As a result, the perishable food product industry's logistics planning must include production-inventory-routing coordination with carbon footprint considerations. This paper aimed to create an integrated production-inventory-routing problem for perishable food products that took into account capacity, time windows, and carbon emissions reduction. The inventory routing problems are NP-hard in nature. Therefore, the proposed problems were solved using two nature-inspired algorithms: flower pollination algorithm (FPA) and cuckoo search algorithm (CSA). The effect of model parameters on the response value was investigated using sensitivity analysis, and the computational experiment discussed the comparative results obtained from both algorithms for different case scenarios. The outcomes of the two algorithms were evaluated for ten instances, and the CSA consistently outperformed the FPA. By incorporating uncertain demands via a random variable with a specified probability distribution, the proposed framework generates compelling opportunities. Individual logistics units may use the proposed framework to mitigate the stochastic nature of problems in uncertain circumstances.
Keywords	algorithms ; carbon ; carbon footprint ; food production ; greenhouses ; industry ; inventories ; perishable foods ; probability distribution
Language	English
Dates of publication	2022-0120
Publishing place	Elsevier Ltd
Document type	Article
ISSN	0959-6526
DOI	10.1016/j.jclepro.2021.130063
Database	NAL-Catalogue (AGRICOLA)

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