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This chapter contributes to the growing global VAR (GVAR) literature by showing how global and national shocks can be identified within a GVAR framework. The usefulness of the proposed approach is illustrated in an application to the analysis of the interactions between public debt and real output growth in a multicountry setting, and the results are compared to those obtained from standard single country VAR analysis. We find that on average (across countries) global shocks explain about one-third of the long-horizon forecast error variance of output growth, and about one-fifth of the long-run variance of the rate of change of debt-to-GDP. Evidence on the degree of cross-sectional dependence in these variables and their innovations are exploited to identify the global shocks, and priors are used to identify the national shocks within a Bayesian framework. It is found that posterior median debt elasticity with respect to output is much larger when the rise in output is due to a fiscal policy shock, as compared to when the rise in output is due to a positive technology shock. The cross-country average of the median debt elasticity is 1.45 when the rise in output is due to a fiscal expansion as compared to 0.76 when the rise in output follows from a favorable output shock.

Around the world, protecting environment and purchasing green products by the manufacturing firms progressively becomes a popular and important issue. Manufacturers are realizing the importance of producing green products under green practices. This study aims to propose an appraisement platform to evaluate the overall performance index of a firm under green practices. Furthermore, the study also helps in identifying ill-performing areas, which necessarily require future attention to augment green supply chain (GSC) of a firm. A case research is conducted to assess the real-life application by the proposed approach.

The authors used fuzzy performance index to measure the overall performance index of a firm. Beside this, they proposed a degree of similarity approach amalgamated with fuzzy performance importance index to classify the ills and strong indices in GSC extent.

The intermittent assessment of green practices and their metrics in the organizational supply chain management (SCM) is indeed necessary. The present study provides an appraisement module to assess overall GSC fuzzy performance index and also helps in identifying the ill-performing areas which require future augmentation toward successful green implementation.

The exposed research work dealt with chains of subjective indices (measure and their interrelated metrics), which are induced into hierarchical appraisement module. To tackle the uncertainty of indices, the subjective indices are transposed into interval-valued fuzzy number set (IVFNS), as IVFNs are preferred to undertake the uncertainty of GSC indices. The proposed approach is demonstrated with a case research to justify its validity and originality.

This paper aims to research the lubrication performance of large-size rectangular oil pad in hydrostatic thrust bearing for heavy computer numerical control (CNC) vertical lathe.

The research establishes the mathematical models of velocity, flux and pressure fields, etc., for lubrication performance distribution, and analyzes its load-bearing behavior.

When hydrostatic thrust bearing’s rotating speed is within ω₁-ω₂, the oil flow generated by plate’s relative motion is greater than that generated by pressure difference and centrifugal force, and in the opposite direction, making it not easy to emit friction heat, so the rotating speed range ω₁-ω₂ should be avoided for bearing.

The research provides powerful theoretical basis for the structure design, operating reliability and practical application of large size rectangular oil pad hydrostatic thrust bearing, and realizing the prediction of its lubrication performance.

A number of digital libraries have been set up in the course of various research and development activities in different parts of the world during the last few years. How do these digital libraries fair in terms of information retrieval features? This paper looks into this question by reviewing the information retrieval features of 20 digital libraries chosen from around the globe. The first part of the paper briefly describes the features of the chosen digital libraries in terms of their nature and content. The second part looks into the information retrieval features of each digital library. Unique features of some digital libraries have been indicated. Major areas of research that would improve the information retrieval features of the future digital libraries have been indicated.

In the paper, the authors study the simultaneous influence of incentive compatibility and individual rationality (IR) on a multi-echelon supply chain (SC) under uncertainty. The authors study the impact of contract sequence on coordination strategies of a serial three-echelon SC consisting of a supplier, a manufacturer and a retailer in an uncertain environment.

The authors develop a game-theoretic framework of a serial decentralized three-echelon SC. Under a decentralized setting, the supplier and the manufacturer can choose from two contract types namely, wholesale price (WP) and linear two-part tariff (LTT) and it leads to four different cases of contract sequence.

The study show that SC coordination is possible when both the supplier and the manufacturer choose LTT contract. This study not only identifies the influence of contract sequence on profit distribution among SC agents, but also establishes cut-off policies for all SC agents for each contract sequence. This study also examine the influence of chosen contract sequence on optimal profit distribution among SC agents.

Three-echelon SC coordination under uncertain environment depends upon the contract sequence chosen by SC agents.

This study results will be helpful to managers of various SCs to take operational decisions under uncertain situations.

The main contribution of this study is that it explores the possibility of coordination by supply contracts for three-echelon SC in a fuzzy environment.

This paper aims to develop a new multi-fiber element for predicting the structural behavior of planar-reinforced concrete (RC) members.

In this work, an exact multi-directional stiffness matrix is analytically derived based on the post-cracking bond-slip interaction between concrete and steel bars. The approach is also extended for large displacement analysis using Green–Lagrange finite strain tensor. In the proposed formulation, the weak form of governed differential equations is approximated by a trial-function expansion based on a finite strain-description and an additional degree of freedom for steel bars.

The findings provide a realistic description of cracking in the concrete structure. Numerical studies are conducted to examine the accuracy of the suggested approach and its capability to predict fairly complex responses of RC models. The findings prove that the proposed element can evaluate local and global responses of RC members, and it can be used as a reliable tool to reflect bond-slip effects in large displacement level. This leads to a robust and precise model for non-linear analysis of RC structures.

The methodology is capable of simulating coupled inelastic shear-flexural behavior of RC members through local stress field theory and Timoshenko beam model.

Robot appraisement under various dimensions and directions is a crucial issue in real-time manufacturing scenario. Logistic robots are programable-independent movable devices capable of transporting stuffs in a logistic cycle. The purpose of this paper is to opt for the most economical robot under chains of criteria, which is always considered as a sizzling issue in an industrial domain.

The authors proposed a cluster approach, i.e. ratio analysis, reference point analysis and full mutification form, embedded type-2 fuzzy sets with weighted geometric aggregation operator (WGAO) to tackle the elected problem of industrial robot. The motive to use WGAO coupled with type-2 fuzzy sets is to effectively undertake the uncertainty associated with comprehensive information of professionals against defined dimensions. Furthermore, the cluster approach is used to carry out the comparative analysis for evaluating robust scores against candidate robot’s manufacturing firms, considering 59 crucial beneficial and non-beneficial dimensions. A case research study is carried out to demonstrate the validity of the proposed approach.

The most challenging task in real-time manufacturing scenario is robot selection for a particular industrial application. This problem has become more complex in recent years because of advanced features and facilities that are continuously being incorporated into the robots by different manufacturers. In the past decade, robots have been selected in accordance with cost criteria excluding other beneficial criteria, which results in declined product quality, customer’s expectation, ill productivity, higher deliver time, etc. The proposed research incorporates the aforesaid issues and provides the various important attributes needed to be considered for the optimum evaluation and selection of industrial robots.

The need for changes in the technological dimensions (speed, productivity, navigation, upgraded product demands, etc.) of robot was encountered as a hardship work for managers to take wise decision dealing with a wide range of availability of robot types and models with distinct features in the manufacturing firms. The presented work aids the managers in taking their decisions effectively while dealing with the aforesaid circumstances.

The proposed work suggests chains of dimensions (59 crucial beneficial and non-beneficial dimensions) that can be used by managers to measure the economic worth of robot to carry out logistic activities in updated manufacturing environment. The proposed work evolves as an effective cluster approach-embedded type-2 fuzzy sets with WGAO to assess manufacturing firms under availability of low information.