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Mechanical recycling is an indispensable tool for plastic waste (PW) recycling and has the highest share in the PW recycling sector in India. The transition to the circular economy of plastics (CEoP) needs a systemic perspective on the mechanical recycling processes. Nevertheless, the assessment of multiple parameters influencing the mechanical recycling of PW is a complex decision-making problem for the development of triple-bottom-line mechanical recycling. A systemic perspective of various mechanical recycling scenarios was performed by employing a multi-criteria decision-making approach to examine the complexity of interlinked factors in the present investigation. Analytical hierarchy process (AHP) integrated with grey relational analysis (GRA) was used to evaluate the criteria that directly influence quality-oriented mechanical recycling. Data were collected by conducting semi-structured interviews using a framed questionnaire in stakeholder engagement with mechanical recyclers of PW. The first level hierarchy included economy, technical, resource consumption and environmental criteria. These criteria were further categorized into various significant indices such as quality of recyclate, recyclability, water and energy consumption during recycling. The results of the integrated grey relational analysis indicated that the technical parameters including quality of recyclate, resource efficiency, PW processing rate and recyclability have a significant influence on mechanical recycling. Based on AHP-GRA, scenario MR6, i.e. manufacturing of PET strap from recycled PET flakes, was ranked the optimal mechanical process amongst the various scenarios. MR6 was followed by Straps and Films at the second and third rank. The lowest ranking was observed for polymer blend recycling. These processes with higher ranks produced good quality recyclate with better efficiency and recyclability. Moreover, these processes consumed optimal resources during manufacturing. These processes also exhibited less maintenance cost, high production rate, low chemical consumption and waste generation as well as implemented pollution control practices. [ABSTRACT FROM AUTHOR]

Purpose: Supplier selection (SS) is one of the prime competencies in a sourcing decision. Taking into account the key role played by suppliers in facilitating the implementation of green supply chain management (GSCM), it is somewhat surprising that very little research attention has been imparted to the development of a strategic sourcing model for GSCM. This research aims to develop a strategic sourcing framework in which supplier organizations are prioritized and ranked based on their GSCM performance. Accordingly, the benchmark organization is identified and its strategy is explored for GSCM performance improvement. Design/methodology/approach: The research develops an innovative GSCM performance evaluation framework using six parameters, namely, investment in corporate social responsibility, investment in research and development, utilization of renewable energy, total energy consumption, total carbon-di-oxide emissions and total waste generation. An integrated multicriteria decision-making (MCDM) approach is proposed in which the entropy method calculates criteria weights. The Complex Proportional Assessment (COPRAS) and the Grey relational analysis (GRA) methods are used to rank supplier organizations based on their performance scores. A real-world case of green supplier selection (GSS) is considered in which five leading India-based automobile manufacturing organizations (Supplier 1, Supplier 2, Supplier 3, Supplier 4 and Supplier 5) are selected. Surveys with industry experts at the strategic, tactical, and operational levels are carried out to collect relevant data. Findings: The results reveal that total carbon dioxide emission is the most influential parameter, as it gains the highest weight. On the contrary, investment in research and development, and total waste generation have no significant impact on GSCM performance. Results show that Supplier 5 secures the top rank. Hence, it is the benchmark organization. Research limitations/implications: The proposed methodology offers an easy and comprehensive approach to sourcing decisions in the field of GSCM. The entropy weight-based COPRAS and GRA methods offer an error-free channel of decision-making and can be proficiently used to outrank various industrial sectors based on their GSCM performances. This research is specific to the automobile manufacturing supply chain. Therefore, research outcomes may vary across supply chains with distinct characteristics. Practical implications: The basic propositions of this research are based on a real-world case. Hence, the research findings are practically feasible. The less significant parameters identified in this study would enable managers to impart more attention to vulnerable areas for improvement. This research may help policymakers identify the influential parameters for effective GSCM implementation. As this research considers all aspects of sustainability, the strategies of the benchmark supplier have a direct impact on organizations' overall sustainability. The study would enable practitioners to make various strategies for GSCM performance improvement and to develop a cleaner production system. Originality/value: The originality of this research lies in the consideration of both economic, social, environmental and operational aspects of sustainability for assessing the GSCM performance of supplier organizations. Quantitative criteria are considered so that vagueness can be removed from the decision. The use of an integrated grey-based approach for developing a strategic sourcing model is another unique feature of this study. [ABSTRACT FROM AUTHOR]

Purpose: The Indian hospitality and tourism industries, major economic growth drivers and employment generators, have been greatly affected by the outbreak of the COVID-19 pandemic. In FY 2020, the Indian tourism sector created 39 million jobs and contributed nearly US$194.3bn, or 6.8%, to India's gross domestic product. The purpose of this study is to focus on ranking 22 listed hotels and 9 listed travel agencies in India based on their performance across 14 selected financial parameters in both the pre-COVID-19 year ending in March 2019 and the post-COVID-19 year ending in March 2021 to understand how the pandemic affected their businesses. Design/methodology/approach: This research proposes to analyze the impact of the COVID-19 pandemic on the financial performance of 22 listed Indian hotels and 9 listed travel agencies evaluated over 14 financial parameters using a pipeline of two recently developed multicriteria decision-making techniques, method based on the removal effects of criteria (MEREC) and grey-based combined compromised solution (CoCoSo). First, the criteria weights are objectively determined using MEREC, and then the financial performances of the selected companies in both the hospitality and tourism industries are separately assessed using CoCoSo to get their overall performance score, based on which the companies are ranked in order of preference. Findings: It was observed that Westlife Development, Lemon Tree Hotels, Indian Tourism Development Corporation, Royal Orchid and Country Club performed significantly poorer than their peers in the aftermath of the pandemic, whereas EIH, Advani Hotels and Resorts and TGB Banquets performed relatively better. Travel agencies Easy Trip and International Travel House performed particularly poorly because of the pandemic, but VMV Holidays performed relatively better in FY 2021. Practical implications: The findings of the analysis will aid portfolio construction, corporate investment decisions, competition research, government policymaking and industrial analysis. Originality/value: The proposed model is novel because it fills the research gap in the application of the integrated MEREC–CoCoSo method to study the impact of COVID-19 on the hospitality and tourism sectors in India. [ABSTRACT FROM AUTHOR]

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Solar energy that contains bright heat and light from the sun is often controlled using modern technology such as photovoltaic, solar heating, artificial photosynthesis, solar architecture and solar thermal electricity. This study concerned with an experimental analysis of solar parabolic trough collector. The sunlight is reflected from the parabolic trough surface and focused on the evacuated absorber tube. The trough is usually aligned to the N-S axis and can be rotated normally according to the sun position from east to west. We have studied the potential of a solar thermal system for hot-water generation. The parabolic trough concentrator was made of galvanized sheet metal on which solar reflective films were pasted. The heat transfer fluid, viz. water runs through the absorber tube and absorbs concentrated heat energy. It has been designed with principal focus 0.1 m from the vertex so that the receiver heat loss is minimized. Data were collected on water inlet temperature, outlet temperature of the heat transfer fluid, solar radiation and water flow rate (days) during March to May 2019 at Coimbatore, Tamil Nadu, India. Also, the processing parameters were optimized because they are the key factors affecting the performance of the solar collector. Grey relational analysis was used to solve the optimization. Through confirmatory experiments, the input variables such as time, angle of tracking and solar radiation, as well as output variables such as inlet temperature, outlet temperature and efficiency were obtained, and the optimal conditions were verified. A suitable choice of input parameters such as tracking angle of 120° provides a high efficiency rate at 2 pm for March, April and May. [ABSTRACT FROM AUTHOR]

This study aims to assess the value of architectural heritage (AH) for its management. Previously, evaluation of AH has been done based on the opinions of experts. In this study, weights of criteria and overall aggregation have been used based on the collected data, thus minimizing the bias in the opinions of experts and reducing the time of evaluation. To derive relative importance of the multi-dimensional values, criteria importance through inter-criteria correlation has been used, and for aggregation of the grey relationship values, the grey relational analysis method has been applied. In a hierarchy process, these two methods have been repetitively applied to obtain the index value of AH. For a case study, the Odisha temple architecture in India has been considered. The results have been compared with the existing state of protection, and the areas where there is a possibility of improvement of architectural heritage value for its management are discussed. [ABSTRACT FROM AUTHOR]

Over two decades, telecommunication market has been continuing a huge growth in urban, semi-urban and rural regions of India. Investigating and choosing the desirable cellular mobile telephone service providers (TSPs) based on operative constraint can facilitate to obtain the ideal of TSPs selection. Here, the evaluation commonly encompasses different TSP options under various operational factors; thus, the assessment of TSPs can be considered as a rigorous multi-criteria decision-making (MCDM) issue. This paper initiates a structure for the exploration of the TSPs in the Madhya Pradesh region, India. To do this, a framework associated with grey relational analysis (GRA) on intuitionistic fuzzy sets (IFSs) is planned to obtain the performance of various telecom participants. The developed approach is based on the conception of the best and worst solutions. To find the attribute weights, a divergence measure is developed and employed by relative comparisons. Additionally, to show the proficiency and practicality, a selection problem of TSPs options of Madhya Pradesh circle, India is presented within the IFSs context. By employing the developed model, an expert can enlarge tactics to enhance the performance by standard operational factors. Comparison and sensitivity analysis are considered to validate the developed approach in the prioritization of the TSPs options. [ABSTRACT FROM AUTHOR]

This paper proposes a structured, integrated decision model for evaluating suppliers by combining the fuzzy analytical hierarchy process (FAHP) and grey relational analysis (GRA). The qualitative and partially-known information is incorporated in this decision model using the fuzzy set theory. In this proposed methodology, the weights of the evaluation criteria are calculated by using FAHP, then the ranking of the suppliers is determined by using GRA. Finally to show the robustness of the model, a sensitivity analysis is also performed. In this study, the supplier selection problem of an electroplating industry in the southern part of India was investigated, demonstrating the effectiveness of this developed integrated model. This model can help in solving the complex decision in supplier selection practice. The results generated from the model are properly validated and finally a systematic solution with decision support is provided for decision makers. This model can be integrated with other decision support systems of similar kinds of industries. [ABSTRACT FROM PUBLISHER]

Criminal network investigation is an ignited research area nowadays. There are several types of criminal network. Terrorist network is one of them. Exploring terrorist network is a demand of several investigating agencies. Different properties of network can be better considered to probe network properly using multi criteria decision-making methods. Grey Relational Analysis (GRA) method is a structural technique for organizing and analyzing complex decisions based on typical mathematics. This process can be employed for analyzing available datasets and designing useful conclusions. If network is explored and visualized, it can be destabilized efficiently. Identified members can be studied and thus their future actions can be prevented. These generalized designs can be used by government agencies for destabilization of terrorist group. This system is especially useful for countries like India that face a constant threat from various group of terrorists. This generalization can further be used to destabilize various criminal networks and their activities can be prevented. Thus, life and property of individuals can be saved. [ABSTRACT FROM AUTHOR]

• Optimal renewable energy source in India is selected using a robust decision making approach. • Ten criteria and four renewable energy sources are considered. • Weights of the criteria are determined using Entropy and CRITIC methods. • Renewable energy sources are ranked using PIV, MABAC, MARCOS, WASPAS, MOORA, EDAS, GRA and TOPSIS methods. • Robustness and stability of the ranking results are evaluated through sensitivity analysis. The evaluation of alternate energy sources to select an appropriate one has always been an important matter of consideration for investors and project engineers, especially for developing countries like India. This necessitates the need for a robust approach where the scope of the decision making process increases and the results can be analysed through different perspectives in scrutiny. This study presents a novel robust approach to assist in the decision making process in the field of sustainable energy and uses India as a case study to define the scope for India's renewable energy development. It implements Entropy and CRiteria Importance Through Intercriteria Correlation criteria weighting methods and eight distinct multi criteria decision making methods to rank the renewable energy sources so as to select the optimal one. The ranking results establish solar to be the best alternative for energy production in India. Wind and biomass stand at second and third places interchangeably in the aggregate rankings obtained in the case of Entropy and CRiteria Importance Through Intercriteria Correlation weights, whereas hydro is ranked last. Furthermore, sensitivity analysis is carried out to check the influence of the criteria weights on the decision, and to measure the stability and robustness of the methods used in this approach. [ABSTRACT FROM AUTHOR]

Land use pattern of a location is a key factor to determine the quality of water in that area. A case study was performed to understand the influence of land use on the quality of surface water. Water quality indices of surface water from different locations within study area were compared with the land use pattern of that location. Multi-criteria decision-making methods, like weighted sum method, weighted product method and grey relational analysis, were used to determine the priority values (PV) of the different water quality parameters on the basis of important criteria like hazard potential, cost of mitigation, utilization potential and popularity among the researchers. Water quality indices of the samples were calculated from those PV by weighted average method. The indices were then compared with respective land use pattern to assess the relation between land use pattern and water quality. The results suggest that dense settlement, moderate to low vegetation and dense cultivation is good for surface water, whereas low settlement, dense vegetation and moderate cultivation is bad for surface water. These findings may be useful for managers and policy makers to manage land use for maintaining the optimum quality of surface water. [ABSTRACT FROM AUTHOR]

The natural fibers of banana and coir from southern part of India was taken as the reinforcement material. Taguchi-based grey relational analysis was used for optimizing the factors influencing tensile, flexural and impact strength of banana/coir composites. Banana wt%, coir wt%, alkali treatment %, pressure and temperature during compression moulding process were the five major factors used for optimizing the mechanical strengths of epoxy-based composites. Grey relational analysis observed 20% banana/15% coir/3% alkali treatment/16 MPa pressure and 100°C temperature combination having the maximum mechanical properties in 16 trial combinations. The signal-to-noise ratio table of grey relational analysis showed combination with 20% banana /15% coir/5% alkali treatment/16 MPa pressure and 100°C temperature having optimized mechanical properties. Banana has the highest rank in improving the mechanical strength of natural composites, followed by coir, alkali treatment %, pressure and temperature. The graph between actual and artificial neural network computed results observed high correlation, proving that network topology of 5-3-1 with five factors, three hidden nodes and one response is the best method for analyzing the parameters in mechanical strength. Hybrid fiber composites with NaOH treatment showed hackles in interface with improved interfacial bonding during SEM analysis. [ABSTRACT FROM AUTHOR]

Intellectual capital is most vital enabler of enterprises. Managing intellectual capital effectively can greatly enhance the competitive advantages of any enterprises. This study focused on how the enterprises utilize intellectual capital, in order to strengthen the competitiveness of enterprises. This research established a novel assessment model to measure the performance of intellectual capital management. The research target is the Indian Public Sector Enterprises (PSE). The research collected data from the Annual Report of PSEs listed in Bombay Stock Exchange for the period 2001-02 to 2010-11. A total of 50 companies randomly selected amongst Indian Public Sector Enterprises and were chosen as empirical samples. The results demonstrated that, this novel assessment method really identify the relative advantages and benchmarking for Indian Public Sector Enterprises. The best company is chosen both in operational performance and productivity improvement. This model is a performance assessment model to judge Intellectual Capital along with Financial Capital. [ABSTRACT FROM AUTHOR]

This study explored multiplex, country-level connections between a wide range of cardiac risk factors and associated mortality within the South Asian Association for Regional Cooperation (SAARC) countries. The grey relational analysis (GRA) methodology is used to evaluate data from 2001 to 2018 to compute scores and rank countries based on cardiac mortality. Subsequently, we used the conservative (Min-Max) technique to determine which South Asian country contributes the most to cardiac mortality. The Hurwicz criterion is further applied for optimization by highlighting the risk factors with the highest impact on cardiac mortality. Empirical findings revealed that India and Nepal are the leading drivers of cardiovascular disease (CVD) mortality among all SAARC nations based on the results of the GRA methodology. Moreover, the outcomes based on the Hurwicz criterion and the conservative criterion indicated that CVD mortality is considerably impacted by household air pollution from the combustion of solid fuel, with India as a potential contributor in the SAARC region. The outcomes of this research may enable international organizations and public health policymakers to make better decisions and investments within the SAARC region to minimize the burden of CVD while also strengthening environmentally sustainable healthcare practices., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Rehman and Rehman.)

The goal of this study was to optimize the coagulation-flocculation process in wastewater generated from the paper and pulp industry using a grey relational analysis (GRA)-based Taguchi method. Process parameters included types and doses of natural coagulants and coagulant aid, and pH. To track the efficiency of the treatment process, the following responses were chosen for optimization: chemical oxygen demand (COD), total dissolved solids (TDS) and turbidity ofwastewater, alone or in combination or all together. Analysis of variance showed that the type and dose of the coagulant aid were the most significant parameters, followed by pH and the dose of the coagulant; the type of coagulant used was found to be insignificant in the coagulation-flocculation process. Optimization of process parameters to achieve lower turbidity and greater removal of COD and TDS was verified in a separate confirmatory experiment, which showed improvements in COD and TDS removal and a decrease in turbidity of 8.2, 6.35 and 26.17%, respectively, with the application of the Taguchi method and GRA. [ABSTRACT FROM AUTHOR]