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Wire-arc-based additive manufacturing (WAAM) is a promising technology for the efficient and economical fabrication of medium-large components. However, the anisotropic behavior of the multilayered WAAM-fabricated components remains a challenging problem.

The purpose of this paper is to conduct a comprehensive study of the grain morphology, crystallographic orientation and texture in three regions of the WAAM printed component. Furthermore, the interdependence of the grain morphology in different regions of the fabricated component with their mechanical and tribological properties was established.

The electron back-scattered diffraction analysis of the top and bottom regions revealed fine recrystallized grains, whereas the middle regions acquired columnar grains with an average size of approximately 8.980 µm. The analysis revealed a higher misorientation angle and an intense crystallographic texture in the upper and lower regions. The investigations found a higher microhardness value of 168.93 ± 1.71 HV with superior wear resistance in the bottom region. The quantitative evaluation of the residual stress detected higher compressive stress in the upper regions. Evidence for comparable ultimate tensile strength and greater elongation (%) compared to its wrought counterpart has been observed.

The study found a good correlation between the grain morphology in different regions of the WAAM-fabricated component and their mechanical and wear properties. The Hall–Petch relationship also established good agreement between the grain morphology and tensile test results. Improved ductility compared to its wrought counterpart was observed. The anisotropy exists with improved mechanical properties along the longitudinal direction. Moreover, cylindrical components have superior tribological properties compared with cuboidal components.

The prime objective of this paper is to design a green supply chain management (GSCM) framework to evaluate the performance of environmental-conscious suppliers using multi-criteria decision-making (MCDM) approach.

The literature survey reveals critical factors for implementing GSCM, adopted methodologies and the result obtained by several researchers. Data have been collected by conducting surveys and interviews with strategic-level personnel of five esteemed organizations in automobile manufacturing sectors. A GSCM framework is developed in which a mathematical tool entropy–the technique for order of preference by similarity to ideal solution (TOPSIS) has been used to analyze the six parameters of automobile manufacturing unit. Initially, entropy is used to find the weights of each of the parameters that influence the decision matrix of the TOPSIS method. Secondly, the proposed GSCM framework ranks the supplier. Finally, sensitivity analysis of the model satisfies the GSCM framework and benchmarked the supplier.

The result shows that “Total CO₂ emission” has an influential role for GSCM sustainability, and hence, firms should put more effort to reduce emissions to improve overall performance. Again, the parameters like investment in R&D and total waste generation may be ignored in the selection process. The result reveals the benchmarked supplier and its strategies for effective sourcing, which would have an indirect effect on organizations' overall sustainability.

This research entirely focuses on sustainability within supply chain considering economic, social and environmental paradigms. The mathematical modeling of the proposed work considers many influential parameters and provides an easy and comprehensive decision-making technique.

The methods may be adopted by the industries for sustainable supply chain management. This study benchmarks the supplier organizations and explores the adopted policies by benchmarked organizations. Other organizations should follow the policies followed by benchmarked organization for enhancing environmental, social and economic performance. Organizations striving for sustainable development can adopt this framework for evaluation of supplier performance and benchmark with better accuracy.

The design of the GSCM framework explores both the qualitative and quantitative data based on environmental, social and economic parameters simultaneously in the evaluation of environmentally conscious suppliers. The research also investigates the constraints of the system to implement the GSCM in automobile manufacturing unit. Additionally, the sensitivity analysis justifies the benchmarked supplier and the adopted strategies to be followed by other manufacturing unit.

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.

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.

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.

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.

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.

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.

The purpose of this paper is to present an overview of trends of Indian information technology and business processing management (IT-BPM) sector and to analyse the determinants of IT-BPM sector during the period 1991-2014.

The study is based on annual data collected from National Association of Software and Service Companies and Department of Electronic and Information Technology for the period 1991 to 2014. The methodology adopted for studying the objectives are simple averages, percentages, ratios, growth rates, graphs prepared on the basis of data from the IT-BPM sector and regression analysis. Trends and patterns in key variables, such as total revenue, domestic revenue, export revenue, employment and exports of the IT-BPM sector have been examined. Factors influencing IT-BPM export growth have been analysed using ordinary least square multiple regression model, with growth rates of gross domestic product (GDP), labour productivity, exchange rate and previous year’s export, as the explanatory variables.

The export revenue from IT-BPM sector increased continuously over the years, at an average growth rate of 36.60 per cent during the period 1991 to 2014. Similarly, domestic revenue of IT-BPM sector also increased, but at a lower growth rate. This is because domestic market in India is captured by multinational giants against Indian firms, which do not possess full comparative advantage in the case of IT-BPM sector. Indian firms are producing low skill activities required for production, mainly concentrated only in the export sector. Direct employment, excluding hardware from IT-BPM sector, has grown at an average rate of 18.08 per cent over the study period. The determinants of IT-BPM exports indicated previous year’s export demand to be significantly contributing the highest to export growth rate. This was followed by GDP growth rate, implying that overall growth of the economy leads to significant increase in export growth. Increased labour productivity followed next in significantly encouraging export growth.

Generalization of the results may not be possible, as Indian conditions and policies vary.

The paper has implications for the expansion of domestic market, diversification of trade and products, innovations for increasing competitiveness and sustainability in the global market in the wake of stiff competitions from new competitors.

This paper focuses on originality in analysis of determinants of export growth.