Purpose Based on the existing literature in the field of green supply chain management (GSCM), the purpose of this paper is to find essential to conceptualize and develop an efficient appraisement platform for the purpose of benchmarking green alternative in supply chain network. Design/methodology/approach The authors explored multiple approaches, i.e. Višekriterijumsko kompromisno rangiranje (VIKOR), simple additive weighting (SAW) and grey relational analysis (GRA) by amalgamating fuzzy sets theory to select the most appropriate alternative for GSCM. The work is supported by triangular fuzzy number sets to choose the green alternative industry among available industries, while dealing with the uncertainty and vagueness in GSCM. A case study is exposed to identify strong and weak indices and to exhibit the feasibility of the proposed work. Findings It is requisite by the managers of many firms to identify the strong and weak indices relating their firms. Thus, the authors presented an approach for measuring and appraising the performance of the selected green alternative by determining the strong and weak indices. The presented work illustrates the performance measurement model that identifies comprehensive GSCM practices of the firms. The presented work incorporates green supply chain activities to support environmental sustainability throughout the supply chain. Research limitations/implications GSCM is necessary to the firms, as it considers impact onto the environment due to their supply chain activities. The authors build decision support system to facilitate the managers of various firms for modeling green practices in their decision making. The authors attempt to devise a conceptual framework linked with knowledge-based theory. Originality/value The authors conceptualized VIKOR, SAW and GRA methodology to rank and benchmark the green performance of distinguish alternative industries among available industries. Additionally, the performance measurement model for the selected significant green alternative is presented for determining the strong and weak indices.

Purpose The use of smart electronic gadgets is proportionately increased during last decades as these gadgets are crafting coziness and relief to the society by making their work easier, effective, etc. These gadgets are the need of today’s working environment for effective planning and work execution. Today, people pertaining to almost every corner of the world are addicted to smart mobile phones, and nowadays, these mobile handsets have become very essential and it is not possible to survive without using them. On the other hand, these smart mobile handsets become inefficient and obsolete over time due to which there is a need to replace the old phones by the new ones, thus creating e-waste. The purpose of this paper is to recognize the significant enablers which are responsible for replacing the existing working mobile phones with the new ones by the end consumers. Design/methodology/approach The Grey-DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach is proposed by the authors to compute the decision results. The present work is supported by the structural modeling equations for supporting sustainability throughout and recognizes the most significant enablers responsible for creating e-waste by replacing the working mobile phones with the new ones. Findings The implication for reducing e-waste using a qualitative approach is presented by easy computation steps for collaborating green issues in the present work. The authors explained numerous enablers, which are responsible for handsets replacement by the consumers. The work can aid the companies as well as the government legislations to identify the significant enablers, drivers, factors, attributes, etc., in moving toward green environmental issue; the generation of e-waste by the obsolete existing working handsets due to non-identification of deficient enablers can be insignificant to the society. Research limitations/implications The implication of developed Grey-DEMATEL techniques is presented by its integration with the application field of e-waste generation by mobile handsets. The authors attempt to devise a conceptual framework linked with knowledge-based theory. The work is illustrated by the case research to understand its applicability and validity in the present scenario. Originality/value The authors attempt to propose a decision model, which will aid in identifying the most significant factorial condition responsible for replacing the existing mobile phones with the new ones by the end consumers. The proposed appraisement module can be used as an investigative tool to build and fabricate a planned environmental progress map for overall business considering environmental domain by the companies.

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In this study, a new process namely, ultrasonic-assisted jet electrodeposition, has been conceived. The ultrasonic-assisted jet electrodeposition process integrates the use of ultrasonic vibrations and high-speed selective jet electrodeposition process to fabricate micro shapes with comparatively high accuracy and with no edge effect. The present study focuses on the development of ultrasonic-assisted jet electrodeposition setup. The impacts of voltage, pulse on time of ultrasonic vibration, concentration of CuSO 4 Á5H 2 O and interelectrode gap for the fabrication of square-shaped micro part have been studied. Deposition rate and dimensional accuracy of fabricated micro features were considered as responses. The experimental results showed that the ultrasonic-assisted jet electrodeposition process has the capability to fabricate micro parts, which yield better dimensional accuracy and no edge effect but waviness of the order of 10-50 mm, as compared to uneven depositional width and edge effect (gap of 200-250 mm) obtained by jet electrodeposition process.

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Purpose Agile practices are important for executing business dealings proficiently in today’s scenario, as they thrust on implicating strategies for meeting quick market requirements. These practices are noteworthy from the point of competitiveness and for fulfilling customer’s demands speedily and promptly. The purpose of this paper is to appraise agile supplier selection dilemma based on analytical hierarchy process (AHP), which accompanied grey information. The authors drafted a group of momentous agile supplier selection measures, which can be utilized by the group of industrial and manufacturing industries to measure the status of agile parameters in their partner firms. G-TOPSIS approach to handling the case of agile supplier selection problem is presented by the authors in this work. Design/methodology/approach The conception of AHP, grey theory and TOPSIS techniques is fused in this study, under the application arena of agile supply chain management (ASCM). The AHP principals are implicated in the first phase to define the priority importance weights of agile measures and, additionally, grey theory and TOPSIS principals are fused in the second phase to fabricate a significant agile supplier selection model. Findings A merged approach accompanying multiple measures is developed for aiding decision making and for modeling qualitative characteristics of agile arena under grey domain. The present work can be utilized to access the agile performance characteristics of the organization and can define the status of their partner suppliers. The technical guidelines of AHP and G-TOPSIS approach are explained in this study to be implicated in distinguish decision fields. An educational podium for dispensing the theoretical knowledge on supply chain management, ASCM and agility is presented in this study. Originality/value A second-level hierarchical structure is built by the authors to facilitate the managers in taking effective decision pertaining to agile measure in their organizations. The lists of qualitative characteristics are catalogued from the literature review in this study. The built model can undertake risk associated in defining the nature of agile criterions as grey concept can undertake risk associated with the system. Thus, the authors implicated G-TOPSIS approach to handling the case of agile supplier selection problem in this study. The presented hierarchical structure will capably assist the industrial and manufacturing firms to react toward random and unpredictable market requirements, along with attaining organizations goals and profits.

Purpose In the presented research, the authors have conducted the literature review and organised real interviews of fruit retailers (FRs) to construct the advanced hierarchical structural (AHS) chain of macro-micro parameters for measuring the performances of defined fruit supply bazaars (FSBs). Apart from this, the purpose of this paper is to develop the grey set-based scorecard model for solving the proposed AHS chain of macro-micro parameters. Design/methodology/approach The performance of FSBs is linked with the supply of fruits towards clients under a feasible rate, which circuitously depends upon the evaluation of the economic locality of FSBs. The authors developed an advanced hierarchical structure of macro-micro parameters via a literature survey and considered these parameters based on the sampling score of FRs corresponding to select feasible FSBs/alternatives. Furthermore, the authors developed a grey set-based scorecard model for undertaking the incomplete information of FRs against the hierarchical structure. Findings It is found that the work is well suited for FRs as they can measure the performances of defined FSBs in accordance with their own opinions under the proposed AHS of macro-micro parameters. Apart from this, the work is useful for benchmarking the vegetable supply bazaars (VSBs) on the replacement of AHS. The proposed hierarchical structure with a grey-based scorecard model is flexible in its nature and can undertake more than 1,000 macro-micro parameters and FRs to access potential decision. Originality/value The conducted research work has a precise value for evaluating the economic FSB locality. The overall performance scores of considered FSB localities are computed as (∂1)=1.991, (∂2)=2.567 and (∂3)=2.855, where (∂3) is found to be more significant than available FSBs. This work can be used for opting the economic locality of VSB too.