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This paper aims to develop a new 3-level implicit numerical method of order 2 in time and 4 in space based on half-step cubic polynomial approximations for the solution of 1D quasi-linear hyperbolic partial differential equations. The method is derived directly from the consistency condition of spline function which is fourth-order accurate. The method is directly applied to hyperbolic equations, irrespective of coordinate system, and fourth-order nonlinear hyperbolic equation, which is main advantage of the work.

In this method, three grid points for the unknown function w(x,t) and two half-step points for the known variable x in spatial direction are used. The methodology followed in this paper is construction of a cubic spline polynomial and using its continuity properties to obtain fourth-order consistency condition. The proposed method, when applied to a linear equation is shown to be unconditionally stable. The technique is extended to solve system of quasi-linear hyperbolic equations. To assess the validity and accuracy, the method is applied to solve several benchmark problems, and numerical results are provided to demonstrate the usefulness of the method.

The paper provides a fourth-order numerical scheme obtained directly from fourth-order consistency condition. In earlier methods, consistency conditions were only second-order accurate. This brings an edge over other past methods. In addition, the method is directly applicable to physical problems involving singular coefficients. Therefore, no modification in the method is required at singular points. This saves CPU time, as well as computational costs.

There are no limitations. Obtaining a fourth-order method directly from consistency condition is a new work. In addition, being an implicit method, this method is unconditionally stable for a linear test equation.

Physical problems with singular and nonsingular coefficients are directly solved by this method.

The paper develops a new fourth-order implicit method which is original and has substantial value because many benchmark problems of physical significance are solved in this method.

The purpose of this paper is to assist a manufacturing firm in designing the closed-loop supply chain network under risks that are affecting its supply quality and logistics operations. The modeling approach adopted aims at the embedding supply chain risks in a closed-loop supply chain (CLSC) network design process and suggests optimal supply chain configuration and risk mitigation strategies.

The method proposes a closed-loop supply chain network and identifies the network parameter and variables required for closing the loop. Mixed-integer-linear-programming-based mathematical modeling approach is used to formulate the research problem. The solutions and test results are obtained from CPLEX solver.

The outcomes of the proposed model were demonstrated through a case study conducted in an Indian hospital furniture manufacturing firm. The modern supply chain is mapped to make it closed loop, and potential risks in its supply chain are identified. The supply chain network of the firm is redesigned through embedding risk in the modeling process. It was found that companies can be in great profit if they follow closed-loop practices and simultaneously keep a check on risks as well. The cost of making the supply chain risk averse was found to be insignificant.

Although the study was conducted in a practical case situation, the obtained results are not indiscriminate to the other circumstances. However, the approach followed and proposed methodology can be applied to many industries once a firm decides to redesign its supply chain for closing its loop or model under risks.

By using the identified CLSC parameters and applying the proposed network design methodology, a firm can design/redesign their supply chain network to counter the risk and accordingly come up with planned mitigation strategies to achieve a certain degree of robustness.

Agriculture is a vital sector for every country, especially for a country like India, where the majority of the population is dependent on agriculture as their earning source. Technological improvements in agriculture will increase output with proper forecasting of input resources. In this study, the author tries to investigate the attitude of end users (farmers) about the use of Industry 4.0 (I4.0) technologies.

The unified theory of acceptance and use of technology (UTAUT) model is used to assess the behavioral aspects. The significance of socioeconomic and technological factors is highlighted, providing the study with a thorough understanding of farmers' decision-making processes. A research questionnaire was developed for data collection, and descriptive and inferential statistics were used to analyse the results using AMOS and SPSS software.

A total of 371 survey responses were collected. The results demonstrate that the hypothesis regarding UTAUT model components is validated, while several mediating hypotheses are not supported, indicating that they are not significant in farmers' decision-making.

In this study, socioeconomic and technological factors are considered to be mediating and moderating elements between the constructs of the UTAUT model. Increasing the accuracy and reliability of our study by integrating mediating and moderating variables. This study assists industry specialists in understanding the elements that farmers consider while switching toward new technologies.

This study is centered on the identification of the most appropriate Technology Adoption (TA) model for investigating the adoption of Industry 4.0 technologies within pharmaceutical and related enterprises. The aim is to facilitate a smooth transition to advanced technologies while concurrently achieving environmental sustainability.

Selection of a suitable TA theory is carried out using a hybrid multi-criteria decision-making (MCDM) approach incorporating PIvot Pairwise RElative Criteria Importance Assessment (PIPRECIA) and Fuzzy Measurement of alternatives and ranking according to Compromise solution (F-MARCOS) methods. A group of three experts is formulated for the ranking of criteria and alternatives based on those criteria.

The results indicate that out of all six TA models considered unified theory of acceptance and use of technology (UTAUT) model gets the highest utility function value, followed by the technical adoption model (TAM). Further, sensitivity analysis is conducted to confirm the validity of the MCDM model employed.

Challenging times like COVID-19 pointed out the importance of technology in the pharmaceutical and healthcare sectors. TA studies in this area can help in the identification of critical factors that can assist pharmaceutical firms in their efforts to embrace emerging technologies, enhance their outputs and increase their efficiency.

The novelty of this research lies in the fact that the utilization of a TA theory prior to its implementation has not been witnessed in existing scholarly literature. The utilization of a TA theory, specifically within the pharmaceutical industry, can assist enterprises in directing their attention toward pertinent factors when contemplating the implementation of emerging technologies and achieving sustainable development.

The operational activities of manufacturing organizations are continuously degrading the environment. Circular economy adoption can help industries optimize their resources along with minimal waste generation. The purpose of this study is to identify and analyze the barriers that hinder the adoption of circular economy (CE) in the manufacturing sector.

The barriers are extracted from a critical review of the literature and listed into three categories as social, economic and environmental. The barriers in each category are then analyzed using the fuzzy-based analytic hierarchy process method. The approach is capable to consider the fuzziness in the preference of barriers and determine their priority.

The pairwise comparison and weight of all the main and sub-criteria are computed, which helps in deciding the ranking of barriers. The results show that social criteria are having the highest importance followed by economic and environmental criteria. Among all the sub-criteria, low demand and acceptance of remanufactured products is at the highest level followed by lack of government support and legislation barrier.

The outcome of this study would be helpful for the decision makers and business managers in the manufacturing sector to focus on the barriers in each category and accordingly formulate strategies for CE adoption.