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Induction heating as an energy source is a novel, recent method in extrusion-based metal additive manufacturing. The purpose of this paper is to develop an optimized coil for extrusion-based metal wire additive manufacturing. The optimized coil is so designed that uniform temperature distribution can be achieved in the extruder, achieving uniform material deposition in a semi-solid state, which is required for additive manufacturing.

Coil shape optimization is achieved by using arrangement of coil turns as a control variable in the form optimization process, and the objective function is to minimize the gradient in the distribution of the magnetic field to achieve uniform heating in the extruder for maintaining consistent solid and liquid fraction during material deposition. A combination of numerical solutions and geometrical optimization has been used for this study.

Experimental and simulation results reveal that the optimized induction coil produced a more uniform axial temperature distribution in the extruder, which is suitable for maintaining a uniform solid-to-liquid fraction ratio during material deposition.

The author has investigated the use of optimized-shaped induction coils in extrusion-based additive manufacturing. The optimized coil can achieve a more uniform temperature distribution in the extruder in comparison to the standard helical coil used in the existing process, which means optimized coil achieves a more uniform solid-to-liquid ratio during printing in comparison to existing standard coil shapes used for heating extruders and fulfils the requirement of additive manufacturing.

The purpose of this paper is to review how knowledge transfer, including knowledge integration, absorptive capacity and reverse knowledge transfer (RKT) in cross-border acquisitions, is examined in existing research work. The authors also propose directions to advance research in cross-border acquisitions.

A systematic literature review is conducted, and related propositions are advanced based on scientometric and bibliometric analysis of 146 papers published over 10 years about tacit knowledge transfer, innovation activities, industrial policy effect on merger decisions, top management experience and value creation in cross-border acquisition. First, the authors searched major themes with the help of Scopus, and later, the authors analysed all received literature with the help of VOS Viewer.

This review facilitates us to identify six clusters and main author keywords. These six clusters are the underlying six research streams, including RKT, cultural distances, value creation, absorptive capacity, innovation and reference to India and China.

Despite knowledge transfer constituting important antecedents and critical factors for the success of cross-border acquisitions, knowledge management in the acquired company through proper knowledge transfer and knowledge integration is not given enough attention. Current literature still fails to provide a holistic picture of how firms strategically manage knowledge post-acquisition. To the best of the authors’ knowledge, this study is the first to analyse the dynamics of knowledge transfer in cross-border acquisitions. The study is a novel attempt to relate current research themes to emerging areas of cross-border acquisitions.

This chapter examines the role of sustainable finance in propelling India's economic growth, drawing insights from a comprehensive review of 50 research papers. Employing a Boolean search strategy, the analysis delves into the influence of environmental, social and governance (ESG) factors on various entities within the Indian financial ecosystem. This chapter explores how sustainable finance practices, embraced by businesses, financial institutions and policymakers, can contribute to long-term economic prosperity while mitigating environmental and social risks. Key findings illuminate opportunities and challenges associated with integrating sustainability principles into financial decision-making. This chapter explores how India’s progress in establishing itself as a significant participant in sustainable finance can be attributed to a variety of key initiatives and policy interventions. The government's dedication to promoting environmental sustainability and facilitating the shift towards a green economy is clearly demonstrated through the implementation of diverse regulations and frameworks by regulatory entities. This chapter provides valuable guidance for stakeholders seeking to leverage sustainable finance for a more resilient and inclusive Indian economy.

This study aims to investigate the tensile strength and compressive behaviour of two thermoplastic polyurethane (TPU) filaments produced via material extrusion (ME): TPU 95A and Reciflex (recycled).

Tensile strength and compressive behaviour are assessed. The influence of extrusion temperature and infill pattern on these properties is examined, supported by thermal characterization, surface morphology analyses and a comprehensive comparison with existing literature. An analytical method is presented for estimating the solid ratio of ME parts, using an ellipse model to describe the material bead geometry.

Reciflex is generally stiffer than TPU 95A in both tensile and compressive tests. Specimens loaded orthogonally in compression tests exhibited stiffer behaviour than those loaded parallelly, and higher tensile properties were typically observed when material beads were deposited parallel to the load direction. Unlike TPU 95A, Reciflex is sensitive to extrusion temperature variations.

By comparing recycled and virgin TPU filaments, this research addresses waste management concerns and advocates for environmentally sustainable production practices in the broadly used filament/based ME technique.

This study provides an extensive comparison of computed values with existing literature, offering insights into how different materials may behave under similar processing conditions. Given ongoing challenges in controlling melt flow during extrusion, these results may offer insights for optimizing the production of ME parts made with thermoplastic elastomers.

This study aims to focus on optimization of process parameters for porosity and strength of polyamide porous bone scaffolds fabricated via selective laser sintering (SLS) process.

Taguchi’s design of experiment approach with L18 orthogonal array (OA) has been used to optimize the process parameters. Five process and four response parameters have been considered for this study. Initially, minimum size of the pores that can be depowdered was identified. Then, porous CAD models of test specimen to measure porosity and strength were designed in Solidworks® software and fabricated using EOSINT P395 m/c. Signal-to-noise ratio and analysis of variance were used to identify the optimal levels of parameters and statistical significance of the parameters.

Among five parameters, powder refresh rate, build chamber temperature and layer thickness were found to have significant influence on all the response parameters, whereas build orientation and build position were found insignificant for all the responses. The Taguchi’s confirmation test validated the results of the study with maximum deviation of 5.8% for compressive strength. Comparison of predicted and experimental values revealed a satisfactory predictability of all the developed linear regression models.

This study reveals optimal set of parameters for SLS of the polyamide porous bone scaffolds. The optimal set of parameters may be used by other researchers to get enhanced combination of strength and porosity while fabricating porous scaffolds.

The main objective of this paper is to integrate quality with triple bottom line dimensions as well as economic, social and environmental concerns within a disassembly line balancing problem.

This study presents a new disassembly line balancing model to maintain the triple bottom line. This proposed model applies a hybrid MCDM considering social, environmental, quantitative and qualitative business and quality dimensions. In this research, fuzzy AHP prioritizes the dimensions and fuzzy TOPSIS ranks the disassembly operations.

The findings show that the disassembly line’s cycle time decreased from 36 s to 32 s, with the main and sub-criteria considered. Therefore, this study reveals that integrating sustainability dimensions with quality may not result in sacrificing cycle time.

Globalization, the increase in demand, the complexity of supply chains and the environmental, economic and social dimensions should be examined together for these operations to be sustainable. Not only these dimensions but also the perception of quality, an essential aspect of production, must be reflected in the disassembly line balancing. There is a need for sustainability issues in disassembly line balancing, which is becoming increasingly important due to environmental concerns, resource conservation, corporate social responsibility and potential cost savings. However, a significant gap in the literature points to the need to cover all three dimensions of the triple bottom line and other production-related dimensions in the disassembly line balancing problem.

This paper aims to examine the influence of sustainability reporting on bank performance. Furthermore, this study investigates the impact of the country’s economic development, financial system and crisis in moderating sustainability reporting and bank performance relationship.

The sample consists of 400 listed banks from 19 countries over the 2009–2022 period. Panel fixed-effect regression is applied, and System Generalized Method of Moments is used as robustness to address endogeneity concerns. The results are robust and survive several sensitivity tests.

The results, aligning with legitimacy and agency theories, suggest a negative relationship between sustainability reporting and bank performance. Based on further classifications, results suggest the negative (positive) impact of country’s financial system (economic development) in moderating the sustainability reporting and bank performance nexus. Finally, this study documents the positive influence of sustainability reporting on bank performance during the crisis period. Overall, the findings fail to support the reduced information asymmetry accruing from higher sustainability disclosures in developing and bank-based economies.

This study has important implications for regulators, policymakers and other stakeholders, especially in light of recent banking scandals that have deteriorated stakeholders' faith in financial institutions' reporting quality.

This study extends the scant literature on sustainability reporting in banking from a cost-benefit vantage point. Furthermore, to the best of the author’s knowledge, no previous research has examined the moderating role of the country’s financial structure and crisis in sustainability reporting and bank performance relationship.

Influenced by the constantly changing manufacturing environment, no single dispatching rule (SDR) can consistently obtain better scheduling results than other rules for the dynamic job-shop scheduling problem (DJSP). Although the dynamic SDR selection classifier (DSSC) mined by traditional data-mining-based scheduling method has shown some improvement in comparison to an SDR, the enhancement is not significant since the rule selected by DSSC is still an SDR.

This paper presents a novel data-mining-based scheduling method for the DJSP with machine failure aiming at minimizing the makespan. Firstly, a scheduling priority relation model (SPRM) is constructed to determine the appropriate priority relation between two operations based on the production system state and the difference between their priority values calculated using multiple SDRs. Subsequently, a training sample acquisition mechanism based on the optimal scheduling schemes is proposed to acquire training samples for the SPRM. Furthermore, feature selection and machine learning are conducted using the genetic algorithm and extreme learning machine to mine the SPRM.

Results from numerical experiments demonstrate that the SPRM, mined by the proposed method, not only achieves better scheduling results in most manufacturing environments but also maintains a higher level of stability in diverse manufacturing environments than an SDR and the DSSC.

This paper constructs a SPRM and mines it based on data mining technologies to obtain better results than an SDR and the DSSC in various manufacturing environments.

This paper aims to examine various indicators related to corruption and determine their impact on financial globalization in emerging countries. It will consider other factors that may impact financial globalization and focus on how corruption within political, executive and public sector institutions can affect this process.

This paper uses a generalized method of moments (GMM) for a data sample of emerging countries covering 2000–2020. Corruption measurements are derived from the varieties of democracy data sets and Transparency International. It also includes data on foreign direct investment, portfolio flows, foreign exchange and international debt as separate indicators of financial globalization. These measures provide more detailed information on the types of financial transactions occurring across countries.

The results reveal that foreign investors may be less likely to enter certain sectors of the economy due to concerns about unethical practices and difficulties navigating the regulatory landscape in countries with high levels of corruption. This can lead to underdevelopment in sectors that are attractive to foreign investment and a reliance on a narrow range of sectors.

This paper offers valuable insights by integrating corruption and financial globalization indicators, using the GMM for robust analysis. It highlights how corruption influences foreign investment decisions, potentially leading to sectoral underdevelopment and overreliance in emerging countries.

The purpose of this study is to investigate resource-constrained multi-project scheduling problems (RCMPSP) involving uncertainty in the form of time-dependent renewable resource reliability. A key focus is to minimize the makespan (completion time) of projects when resources can become unavailable or fail over time at non-constant rates. Accounting for realistic resource reliability seeks to provide scheduling solutions that better reflect potential delays in practical multi-project environments.

A new discrete-time binary integer programming formulation of RCMPSP is expanded to include time-dependent resource reliability and simultaneously evaluate the time-dependent failure rate and constant repair rate of a resource. A new hybrid immune genetic algorithm with local search (HIGALS) is developed to solve this NP-hard problem. HIGALS incorporates a new coding mechanism, initialization method and local search operator.

A case study tests the proposed HIGALS approach. The validity of the mathematical model is confirmed by solving small-sized problems with GAMS software. The proposed HIGALS algorithm is validated by solving small-sized problems and comparing its solutions with GAMS. The superiority of HIGALS is demonstrated by comparing its solutions with six basic algorithms on medium- and large-sized problems. Results show that HIGALS outperforms existing algorithms, achieving an average reduction in makespan of over 11.79%, while maintaining the advantages of genetic, immune and local search algorithms and avoiding their disadvantages.

Considering time-dependent resource reliability can help project managers plan for disruptions and delays in resource-critical projects. HIGALS provides decision support for robust multi-project scheduling.

This study contributes to the field by investigating RCMPSP with time-dependent renewable resource reliability, which reflects real-world uncertainty more accurately. HIGALS presents a novel approach to balance intensification and diversification for this challenging problem.