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The purpose of this paper is to develop a conceptual framework of fly ash (FA) handling by using the total interpretive structural modeling (TISM) technique in the Indian context.

The conceptual framework of the FA handling technique has been developed by using the TISM technique, where the FA handling factors have been identified from literature and verified by experts.

The conceptual framework of FA handling technique developed by using TISM contributes to the development of FA handling hierarchy. The framework identifies that there are 12 important factors which play a vital role in FA handling. The conceptual model indicates that particle size distribution derives FA handling technology.

This study identified important factors for FA handling and it has implication for both organizations and policy makers. This study delivers the factors which play an important role in handling FA in a thermal power plant. This study highlights important linkages essential for the expansion of FA handling technologies and policies.

This study is unique in itself as it studies the FA handling factors through the qualitative modeling technique and has made its contribution in FA handling by providing the conceptual framework for managing FA in the thermal power plant.

This paper investigates how the channel leadership strategies develop a post-coronavirus disease (COVID-19) resilient agri-supply chain, which reduces supplier and retailer's price loss and enhances the logistics service quality level considering logistics outsourcing of agri-product especially for the rapidly changing market condition.

Based on the classical leadership theory, two channel leadership strategies, i.e. LPL and SL, are considered. The proposed framework first derives the equilibrium price and service quality level decision among the supplier, the logistics provider and the retailer. Then it compares both leadership strategies in terms of the equilibrium prices and service quality theoretically. This article also presents a case study of Arabian dates pricing and supply chain to test the theoretically derived propositions.

Selection of suitable leadership strategy is a critical factor for profit maximization of the supply chain drivers and proper optimization of equilibrium price and service quality. Here, the product's quality and the market's socio-economic condition play an important role in selecting a suitable leadership strategy. A random transformation of the physical market to an e-commerce portal creates a wide variation of the market's socio-economic parameters, affecting the equilibrium pricing and the logistics provider's service quality.

This study proposes a post-COVID-19 resilient agri-supply chain framework considering price and quality-dependent stochastic market demand, incorporating a wide range of socio-economic factors in the model to counteract the effect of rapid behavior change of agri-market due to COVID-19 norms. This research examines the effect of different channel leadership strategies to facilitate suitable decisions on prices and service quality and retrieve the profit of the supplier, retailer and logistics provider. The future models can incorporate competitiveness in logistics outsourcing, fourth-party logistics (4PL) and contract farming in the agri-supply chain. Each of the extensions can open avenues in different directions.

As the post-COVID-19 market and the customer behavior is randomly changing, and the traditional market is rapidly converting into supermarkets and e-commerce portals, this paper examines the model with a wide variety of e-commerce portals with multi-variation of product. It is conclusive that the product's quality and the market's socio-economic behavior significantly impact the equilibrium decision. The drivers of the supply chain must take them into account before choosing a particular channel leadership strategy.

This study considers a multi-product and multi-market (e-commerce) model by integrating a wide variety of products and the market's socio-economic parameters. The model is tested in a price and quality-dependent stochastic market condition, contributing to the literature by reconciling two different channel leadership strategies into the global logistics of fresh agri-product.

The research in competitive facility location (CFL) is quite dynamic, both from a problem formulation and an algorithmic point of view. Research direction has changed immensely over the years to address various competitive challenges. This study aims to explore CFL literature to highlight these research trends, important issues and future research opportunities.

This study utilises the Scopus database to search for related CFL models and adopts a five-step systematic approach for the review process. The five steps involve (1) Article Identification and keyword selection, (2) Selection criteria, (3) Literature review, (4) Literature analysis and (5) Research studies.

The paper presents a comprehensive review of CFL modelling efforts from 1981 to 2021 to provide a depth study of the research evolution in this area. The published articles are classified based on multiple characteristics, including the type of problem, type of competition, game-theoretical approaches, customer behaviour, decision space, type of demand, number of facilities, capacity and budget limitations. The review also highlights the popular problem areas and dedicated research in the respective domain. In addition, a second classification is also provided based on solution methods adopted to solve various CFL models and real-world case studies.

The paper covers 40 years of CFL literature from the perspective of the problem area, CFL characteristics and the solution approach. Additionally, it introduces characteristics such as capacity limit and budget constraint for the first time for classification purposes.

In construction management, risks and claims are treated separately, but several studies tacitly acknowledge a strong link between the two. In this context, this research intends to investigate whether risks and claims have a causal relationship? Based on this causal relationship, a claim-based risk assessment model (C-RAM) is developed to quantify occurrences and cost implications of risks using project data.

First, the causal relationship between risks and claims is established through a conceptual framework for content analysis of the literature on risk management (RM) and claim management (CM). Then, a C-RAM is developed based on the content analysis of 234 claims from 24 settled arbitration awards.

Risks and claims are found to be two stages in the same chain of uncertain events that affect projects, subsequently revealing a causal relationship between risks and claims. Due to this causal relationship, claim documents become a potential source of risk information from past projects. Proposed C-RAM quantifies occurrences of risks with three parameters: number of projects in which a risk occurs, number of ways in which a risk occurs, and number of claims a risk causes if it occurs. Also, cost implications of risks are quantified as percentage of contract sums for interpretation as tangible values.

Though C-RAM is applicable to all types of claims, the results in this paper are based on impacts of risks in past projects that caused claims and reached to arbitration stage.

The causal relationship between risks and claims will encourage integration of knowledge on RM and CM which is currently treated separately. Practitioners can now visualize claims as cost implications of risks that occurred in projects. Further, C-RAM makes risk assessment (RA) more objective by quantifying the cost implications of risks as percentage of contract sums which can be readily used for contingency estimation.

The relationship between risks and claims, and the potential of claim documents as a source of project risk information, can initiate a new paradigm in RM research based on project data.

The purpose of this paper is to outline and prioritizes risk sources in medical device development (MDD) process using an integrated “structural equation modeling” (SEM) and fuzzy “technique for order performance by similarity to ideal solution (TOPSIS)” framework.

Risk sources which deter MDD process are explored through literature review. Initial structural model is proposed, factor loadings are determined by exploratory factor analysis and model fit is established by confirmatory factor analysis. Further, the sources are ranked using FTOPSIS, and sensitivity analysis is carried to check robustness of results.

The sources of risks have catastrophic effect on MDD process. The initial SEM model developed based on survey of experts is found reliable and valid which breaks up the risk sources into three categories – internal sources of risks, user-related sources of risks and third-party-related sources of risks. The risk sources are ranked and prioritized based on perspective of experts from the categories using FTOPSIS; unmet user needs/requirements is found as the most important source of risk. Results of sensitivity analysis confirm that the factors are relatively less sensitive to criteria weights confirming reliability of initial solution.

The proposed methodology combines qualitative and quantative approaches, making it little complex and lengthy, but results in dual confirmation.

The outcomes of this research will be of prime use for MDD industries to mitigate risk sources. It will help to increase the success rate of MDD.

Integrated SEM-FTOPSIS provides a unique and effective structural modeling-based decision support tool. The framework can be effectively utilized in other domains, and failure events of medical devices can be potentially controlled by applying risk mitigation measures.

The literature on Maritime Transportation (MT) is experiencing a transition phase where the focus of the research is repositioning. It registered steep growth in recent years with its beginning articles on the concepts of cost minimization to the current focus on achieving sustainable operational effectiveness using Information and Communication Technologies (ICTs). Thus, this becomes a right time to investigate the trajectory of research on MT.

The proposed study aims to explore the potential of data analytics techniques such as data mining and network analytics to reflect the trajectory of research in the maritime supply chain over time. This study identifies the eight main dimensions of the research published under maritime paradigm through network analytics. The in-depth review of these dimensions rendered us to segregate them further into sub-dimensions for the ease of understanding and interpretability. Further, the text mining is employed to extract thematic evolution of the research.

The evolved themes are completely exclusive from the conventional MT research with artificial intelligence, digital storage, waste management and biofuels emerging as contemporary themes. It is found that although there are a sufficient amount of literature on sustainable port practices but their policy implications are still underexplored. The inter-dimension research is needed to achieve the motive of economic efficiency and environmental sustainability simultaneously.

The study has contributed on the methodology side of conducting literature reviews. The dimensions, sub-dimensions and themes are obtained using data analytics tools and techniques. This omits the possibility of personal bias and thus making the results verifiable.

The purpose of this paper is to identify the Industry 4.0 barriers to achieve circular economy (CE). The study focuses on exploring the link between Industry 4.0 and CE. This leads to the implementation of integrated Industry 4.0-CE and attainment of sustainable production and consumption through analyzing the technological benefits of Industry 4.0.

Industry 4.0 barriers are identified from literature review and discussions with industry experts. Here, the interpretive structural modeling (ISM) technique is applied to develop the contextual relationship among the barriers and to identify the prominent barriers hindering the CE implementation.

The ISM hierarchical model and Matriced’ impacts croised-multiplication applique’ and classment analysis illustrate that the digitalization process and the semantic interoperability possess high driving power and low dependence. These barriers require keen attention to play a significant role in improving resource efficiency and sustainability, and absence of these barriers may not drive other barriers for CE. Apart from these barriers, cyber-physical systems standards and specifications, sensor technology and design challenges are also the most influential Industry 4.0 barriers for achieving CE.

The findings provide an opportunity for industry practitioners to explore the most driving Industry 4.0 barriers. The study confirms that integrated Industry 4.0-CE will maintain sustainable operations management by optimizing the production and consumption patterns. It will also provide an opportunity of customization where customers and products interact and can monitor the performance of the operations through the Internet of Things sensors.

The study provides integration of Industry 4.0 challenges to implement CE. However, the integration of the two burgeoning fields is still very scarce and lacks in adopting the technological benefits of the integrated Industry 4.0-CE.

Emission reduction methodologies alone are not sufficient to mitigate the climatic catastrophes caused due to ongoing carbon emissions. Rather, a bidirectional approach is required to decarbonize the excess carbon in the atmosphere through carbon sequestration along with carbon reduction. Since the manufacturing sector contributes heavily to the ongoing carbon emissions, the purpose of this paper is to propose a framework for carbon emission reduction and carbon sequestration in the context of the manufacturing industry.

In this paper, life cycle assessment (LCA) is employed to track the carbon emission at each stage of the product development life cycle. The pre-requisite for this is the accurate evaluation of the carbon emissions. Therefore, IoT technologies have been employed for collecting real-time data with high credibility to perceive environmental impact caused during the entire life cycle of the product. The total carbon emission calculation is based on the bill of material (BOM)-based LCA of the product to realize the multi-structure (from parts and components to product) as well as multi-stage (from cradle to gate) carbon emission evaluation. Carbon sequestration due to plantation is evaluated using root-shoot ratio and total biomass.

A five interwoven layered structure is proposed in the paper to facilitate the real-time data collection and carbon emission evaluation using BOM-based LCA of products. Further, a carbon neutral coefficient (CNC) is proposed to indicate the state of a firm’s carbon sink and carbon emissions. CNC=1 indicates that the firm is carbon neutral. CNC >1 implies that the firm’s carbon sequestration is more than carbon emissions. CNC <1 indicates that the firm’s carbon emission is more than the carbon sink.

The paper provides a novel framework which integrates the real-time data collection and evaluation of carbon emissions with the carbon sequestration.

The purpose of this paper is to prioritize Indian energy sector projects, namely, coal, gas, hydro and solar using fuzzy PROMETHHE (F-PROMETHEE) and Visual PROMETHEE applications and multicriteria decision-making (MCDM) analyses.

The MCDM outranking approach of PROMETHEE under fuzzy environment is used. Four projects of energy sector are selected as alternatives and are compared based on various criteria. These criteria selected on the perspectives of life cycle costing (LCC) analysis and related management approaches for prioritizing projects for effective decision-making (DM). The F-PROMETHEE is described and results are also compared with outranking application in Visual PROMETHEE software based on same set of criteria. For better understanding, the graphical representations of the multicriteria problem are also shown using graphical analysis for interactive aid.

On applying F-PROMETHEE on four energy projects, coal and solar projects outrank high and results shows that coal-based project is preferable and should be considered.

Here F-PROMETHEE and Visual PROMETHEE are used as MCDM techniques. However, few other MCDM techniques such as ELECTRE and EATWOS can be also explored to outrank Indian energy sector projects.

Indian energy sector involves high degree of complexity for effective DM on the front of prioritized investment-related capacity addition through energy projects. Outranking methods like F-PROMETHEE is able to address the criteria to criteria impact on DM support precisely.

The finding can provide information to the government or public sector regarding various possible investment options on energy projects in India.

This paper can be supplement and act as the support for DM in conflicting situations specifically for prioritizing investments on various energy projects, which further can synergize conflicting ideas of various stakeholders of the Indian energy sector.

To assess the state of supply chain management (SCM) research in India and to understand the research trends and methodologies used. The present study also aims to create a taxonomy of the subject areas researched in India.

The present study employed the systematic literature review methodology. Literature from 395 peer journal papers in 67 leading journals over a 20-year period (2000–2020 Quarter-1) was comprehensively reviewed and assessed.

SCM research in India started around the year 2000. The quantum of research was low (single digit) until 2010. There has been steady growth over the last decade, and over 50% of the total papers up until now has been published in the last four years. The present study created a three-tiered taxonomy of the subject areas and classified the papers as per it. The first tier (level-1) has seven categories (SCM strategy, network design, SCM processes and integration, IT systems, skills, performance measurement and others). A perusal of the newly created taxonomy revealed that, except for a few areas under level-1 categories (such as SCM processes and SCM strategy), the other level-1 categories have not seen much research. Similarly, there is little or no research in a large number of level-2 categories (such as outsourcing strategy, channel strategy, demand management, demand fulfillment, customer relationship management, integrated supply chain planning, new product development, returns, supply chain orientation, performance monitoring, performance improvement, SCM adoption process, SCM implementation issues and quantified benefits of SCM). Methodologically, the rigor of SCM research in India needs improvement.

A comprehensive taxonomy of SCM subject areas researched in India at three cascading levels was created for the first time in the present study. The taxonomy will help provide researchers with a clear understanding of the structure of the subject areas and help in identifying areas where research has been carried out and the subject areas where gaps exist for future research to proceed. The present study also provides an overview of the methodological rigor of SCM research in India and points out some of the limitations that researchers should avoid in future studies.