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1 – 10 of 25Vishal Singh and Arvind K. Rajput
The present paper aims to analyse the synergistic effect of pocket orientation and piezo-viscous-polar (PVP) lubrication on the performance of multi-recessed hybrid journal…
Abstract
Purpose
The present paper aims to analyse the synergistic effect of pocket orientation and piezo-viscous-polar (PVP) lubrication on the performance of multi-recessed hybrid journal bearing (MHJB) system.
Design/methodology/approach
To simulate the behaviour of PVP lubricant in clearance space of the MHJB system, the modified form of Reynolds equation is numerically solved by using finite element method. Galerkin’s method is used to obtain the weak form of the governing equation. The system equation is solved by Gauss–Seidal iterative method to compute the unknown values of nodal oil film pressure. Subsequently, performance characteristics of bearing system are computed.
Findings
The simulated results reveal that the location of pressurised lubricant inlets significantly affects the oil film pressure distribution and may cause a significant effect on the characteristics of bearing system. Further, the use of PVP lubricant may significantly enhances the performance of the bearing system, namely.
Originality/value
The present work examines the influence of pocket orientation with respect to loading direction on the characteristics of PVP fluid lubricated MHJB system and provides vital information regarding the design of journal bearing system.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2023-0241/
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Gaurav Gupta, Jitendra Mahakud and Vishal Kumar Singh
This study examines the impact of economic policy uncertainty (EPU) on the investment-cash flow sensitivity (ICFS) of Indian manufacturing firms.
Abstract
Purpose
This study examines the impact of economic policy uncertainty (EPU) on the investment-cash flow sensitivity (ICFS) of Indian manufacturing firms.
Design/methodology/approach
This study uses the fixed-effect method to investigate the effect of EPU on ICFS from 2004 to 2019.
Findings
This study finds that EPU increases ICFS, which is more (less) during the crisis (before and post-crisis) period. The authors also find that the effect of EPU on ICFS is more for smaller, younger and standalone (SA) firms than the larger, matured and business group affiliated (BGA) firms. This study also reveals that EPU reduces corporate investment (CI). Further, the authors find that cash flow is more significant for the investment of financially constrained firms and the negative effect of EPU is more for these firms.
Research limitations/implications
This study considers the Indian manufacturing sector. Therefore, this study can be extended by analyzing the relationship between EPU and ICFS for the service sector.
Practical implications
First, this study can be useful for corporates, academicians and government bodies to understand the effect of EPU on ICFS and CI. Second, this study will help corporates to focus on internal funds to finance corporates' investment during the crisis period because EPU increases the cost of external finance which may increase ICFS and reduce CI. Third, lending agencies, investors and stakeholders should also focus on the firm's nature, ownership, size and age because these factors play a crucial role to reduce or increase the negative effect of EPU on ICFS. Fourth, the Government should make appropriate policy measures in terms of concessional interest rates to increase the easy availability of external finance for SA, small size, and young firms to reduce the negative effect of EPU on CI because these firms are considered as more financially constrained firms.
Originality/value
This study adds new inputs to the current literature of EPU in several ways. First, this study is one of the main studies focused on the relationship between EPU and ICFS (CI). Especially in emerging countries like India, examining this relationship extends previous research. Second, this study also examines the impact of EPU on ICFS for BGA, SA, small, large, matured and young firms as well as crisis and non-crisis periods. Third, this study uses the sample of the Indian manufacturing sector which has emerged the qualities to become a global manufacturing hub and attracting global investors. Therefore, examining the effect of EPU on ICFS for these firms will be more interesting.
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Ayesha Khatun, Vishal Singh and Akashdeep Joshi
Studies have so far focused on learning in organizations, factors affecting learning, learning effectiveness and so on but the concept of learning in a hybrid work arrangement is…
Abstract
Purpose
Studies have so far focused on learning in organizations, factors affecting learning, learning effectiveness and so on but the concept of learning in a hybrid work arrangement is yet unexplored. The purpose of this study is to measure the perception of faculty members in higher education institutions towards learning in a hybrid work arrangement and also to measure the differences of perception towards hybrid work arrangement based on employees’ gender and organization type.
Design/methodology/approach
The data was collected from a sample of 390 faculty members composing of Assistant Professors, Associate Professors and Professors, purposely chosen from two of the premier higher education institutions (one private and one public) located in Punjab, India. A self-structured questionnaire was administered to the faculty members who are working on a regular basis and have minimum of two years of work experience with the chosen university. For analysing the collected data exploratory factor analysis and other descriptive statistics have been applied.
Findings
The findings of the survey show that in terms of gender differences, it is the female employees who are more satisfied with different aspects of hybrid/remote work arrangement as compared to male employees. In regard to organizational differences in the perception towards learning in a hybrid work arrangement it is found that public university employees have a more positive attitude so far as individual factors are concerned, but in terms of organizational factors, it is the private university that is scoring better than the public university.
Research limitations/implications
The study is limited to only two higher education institutions, and its findings to be applicable in all higher education institutions, further studies may be required on a larger canvas. Future studies may be undertaken using advanced statistical tools like structural equation modelling to explore various variables associated with learning in a hybrid work arrangement.
Originality/value
Applicability of hybrid work arrangement is very high in higher education institutions and to the best of the authors’ knowledge, this is the first study which adds to the literature on perception of employees towards organizational learning in a hybrid work arrangement.
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Puja Singh, Vishal Suresh Pradhan and Yogesh B. Patil
The main purpose of this paper is to investigate drivers and barriers of climate change mitigation strategies (CCMS), their linkages and impact in Indian Iron and Steel Industry…
Abstract
Purpose
The main purpose of this paper is to investigate drivers and barriers of climate change mitigation strategies (CCMS), their linkages and impact in Indian Iron and Steel Industry (IISI) in light of ninth sustainable development goal (building resilient infrastructure, promote sustainable industrialization and foster innovation).
Design/methodology/approach
To identify relevant drivers and barriers, a thorough literature review and opinions of industry experts were obtained. Utilizing Total Interpretive Structural Modeling (TISM), the selected drivers and barriers were modeled separately along with Cross Impact Matrix-multiplication Applied to Classification (MICMAC).
Findings
Pragmatic and cost-effective technology, less supply chain complexity, robust policy and legal framework were found to have the highest driving power over all the other drivers. Findings suggest political pressure as the most critical barrier in this study. The results from TISM and MICMAC analysis have been used to elucidate a framework for the understanding of policymakers and achieve top management commitment.
Practical implications
This paper will help researchers, academicians, industry analysts and policymakers in developing a systems approach in prioritizing CCMS in energy-intensive (coal dependent) iron and steel plants. The model outcomes of this work will aid operational research to understand the working principles in other industries as well.
Originality/value
To the best of authors' knowledge, there is paucity of reported literature for the drivers and barriers of CCMS in iron and steel industry. This paper can be considered a unique, first attempt to use data from developing nations like India to develop a model and explain relationships of the existing drivers and barriers of CCMS.
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Shekhar Srivastava, Rajiv Kumar Garg, Anish Sachdeva, Vishal S. Sharma, Sehijpal Singh and Munish Kumar Gupta
Gas metal arc-based directed energy deposition (GMA-DED) process experiences residual stress (RS) developed due to heat accumulation during successive layer deposition as a…
Abstract
Purpose
Gas metal arc-based directed energy deposition (GMA-DED) process experiences residual stress (RS) developed due to heat accumulation during successive layer deposition as a significant challenge. To address that, monitoring of transient temperature distribution concerning time is a critical input. Finite element analysis (FEA) is considered a decisive engineering tool in quantifying temperature and RS in all manufacturing processes. However, computational time and prediction accuracy has always been a matter of concern for FEA-based prediction of responses in the GMA-DED process. Therefore, this study aims to investigate the effect of finite element mesh variations on the developed RS in the GMA-DED process.
Design/methodology/approach
The variation in the element shape functions, i.e. linear- and quadratic-interpolation elements, has been used to model a single-track 10-layered thin-walled component in Ansys parametric design language. Two cases have been proposed in this study: Case 1 has been meshed with the linear-interpolation elements and Case 2 has been meshed with the combination of linear- and quadratic-interpolation elements. Furthermore, the modelled responses are authenticated with the experimental results measured through the data acquisition system for temperature and RS.
Findings
A good agreement of temperature and RS profile has been observed between predicted and experimental values. Considering similar parameters, Case 1 produced an average error of 4.13%, whereas Case 2 produced an average error of 23.45% in temperature prediction. Besides, comparing the longitudinal stress in the transverse direction for Cases 1 and 2 produced an error of 8.282% and 12.796%, respectively.
Originality/value
To avoid the costly and time-taking experimental approach, the experts have suggested the utilization of numerical methods in the design optimization of engineering problems. The FEA approach, however, is a subtle tool, still, it faces high computational cost and low accuracy based on the choice of selected element technology. This research can serve as a basis for the choice of element technology which can predict better responses in the thermo-mechanical modelling of the GMA-DED process.
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Vishal Ashok Wankhede, Rohit Agrawal, Anil Kumar, Sunil Luthra, Dragan Pamucar and Željko Stević
Sustainable development goals (SDGs) are gaining significant importance in the current environment. Many businesses are keen to adopt SDGs to get a competitive edge. There are…
Abstract
Purpose
Sustainable development goals (SDGs) are gaining significant importance in the current environment. Many businesses are keen to adopt SDGs to get a competitive edge. There are certain challenges in realigning the present working scenario for sustainable development, which is a primary concern for society. Various firms are adopting sustainable engineering (SE) practices to tackle such issues. Artificial intelligence (AI) is an emerging technology that can help the ineffective adoption of sustainable practices in an uncertain environment. In this regard, there is a need to review the current research practices in the field of SE in AI. The purpose of the present study is to comprehensive review the research trend in the field of SE in AI.
Design/methodology/approach
This work presents a review of AI applications in SE for decision-making in an uncertain environment. SCOPUS database was considered for shortlisting the articles. Specific keywords on AI, SE and decision-making were given, and a total of 127 articles were shortlisted after implying inclusion and exclusion criteria.
Findings
Bibliometric study and network analyses were performed to analyse the current research trends and to see the research collaboration between researchers and countries. Emerging research themes were identified by using structural topic modelling (STM) and were discussed further.
Research limitations/implications
Research propositions corresponding to each research theme were presented for future research directions. Finally, the implications of the study were discussed.
Originality/value
This work presents a systematic review of articles in the field of AI applications in SE with the help of bibliometric study, network analyses and STM.
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Shrutika Sharma, Vishal Gupta, Deepa Mudgal and Vishal Srivastava
Three-dimensional (3D) printing is highly dependent on printing process parameters for achieving high mechanical strength. It is a time-consuming and expensive operation to…
Abstract
Purpose
Three-dimensional (3D) printing is highly dependent on printing process parameters for achieving high mechanical strength. It is a time-consuming and expensive operation to experiment with different printing settings. The current study aims to propose a regression-based machine learning model to predict the mechanical behavior of ulna bone plates.
Design/methodology/approach
The bone plates were formed using fused deposition modeling (FDM) technique, with printing attributes being varied. The machine learning models such as linear regression, AdaBoost regression, gradient boosting regression (GBR), random forest, decision trees and k-nearest neighbors were trained for predicting tensile strength and flexural strength. Model performance was assessed using root mean square error (RMSE), coefficient of determination (R2) and mean absolute error (MAE).
Findings
Traditional experimentation with various settings is both time-consuming and expensive, emphasizing the need for alternative approaches. Among the models tested, GBR model demonstrated the best performance in predicting both tensile and flexural strength and achieved the lowest RMSE, highest R2 and lowest MAE, which are 1.4778 ± 0.4336 MPa, 0.9213 ± 0.0589 and 1.2555 ± 0.3799 MPa, respectively, and 3.0337 ± 0.3725 MPa, 0.9269 ± 0.0293 and 2.3815 ± 0.2915 MPa, respectively. The findings open up opportunities for doctors and surgeons to use GBR as a reliable tool for fabricating patient-specific bone plates, without the need for extensive trial experiments.
Research limitations/implications
The current study is limited to the usage of a few models. Other machine learning-based models can be used for prediction-based study.
Originality/value
This study uses machine learning to predict the mechanical properties of FDM-based distal ulna bone plate, replacing traditional design of experiments methods with machine learning to streamline the production of orthopedic implants. It helps medical professionals, such as physicians and surgeons, make informed decisions when fabricating customized bone plates for their patients while reducing the need for time-consuming experimentation, thereby addressing a common limitation of 3D printing medical implants.
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Vishal Gupta, Shweta Mittal, P. Vigneswara Ilavarasan and Pawan Budhwar
Building on the arguments of expectancy theory and social exchange theory, the present study provides insights into the process by which pay-for-performance (PFP) impacts employee…
Abstract
Purpose
Building on the arguments of expectancy theory and social exchange theory, the present study provides insights into the process by which pay-for-performance (PFP) impacts employee job performance.
Design/methodology/approach
Based on a sample size of 226 employees working in a technology company in India, the study examines the relationships between PFP, procedural justice, organizational citizenship behavior (OCB) and employee job performance. Data on perceptions of PFP and procedural justice were collected from the employees, data on OCB were collected from the supervisors and the data on employee job performance were collected from organizational appraisal records.
Findings
The study found support for the positive relationship between PFP and job performance and for the sequential mediation of the relationship between PFP and job performance via procedural justice and OCB. Further, procedural justice was found to mediate the relationship between PFP and OCB.
Research limitations/implications
The study was cross-sectional, so inferences about causality are limited.
Practical implications
The study tests the relationship between PFP and employee job performance in the Indian work context. The study shows that the existence of PFP is positively related to procedural justice which, in turn, is positively related to OCB. The study found support for the sequential mediation of PFP-job performance relationship via procedural justice and OCB.
Originality/value
The study provides an insight into the underlying process through which PFP is related to employee job performance. To the best of our knowledge, such a study is the first of its kind undertaken in an organizational context.
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Rohit Markan, Navneet Seth, Vishal Vinayak and Gagandeep S. Salhan
Introduction: The effectiveness of management faculty members depends on several factors, including self-efficacy. Albert Bandura coined the term ‘self-efficacy’, defined as ‘the…
Abstract
Introduction: The effectiveness of management faculty members depends on several factors, including self-efficacy. Albert Bandura coined the term ‘self-efficacy’, defined as ‘the capacity to do things as per one’s ability’ – the self-belief that one ‘can-do’ something.
Purpose: The study aims to discuss the effects of high and low degrees of self-efficacy. Faculty members with high-order competencies achieve higher positions, whereas those with low self-efficacy will generally have less self-belief in achieving success, translating into not progressing either at all or as quickly. There exists a need to study the levels of self-efficacy among faculty members to determine issues that create skill gaps and lead to both high and low efficacy. For better general performance, all faculty members should have high degrees of self-efficacy as it leads to high enthusiasm, increased commitment, and a capacity to dilute and address a range of challenges.
Methodology: This chapter falls under the category of a review paper. As different papers/studies have been reviewed and compared in this study, it does not need to conform to any particular methodology.
Findings: Various findings and practical implications shall be discussed in this chapter regarding self-efficacy among management faculty members. To improve youth’s future abilities by 2030, teachers ought to have higher levels of self-efficacy. Self-efficacy is imperative in accomplishing objectives, achieving results, and accomplishing educational difficulties in instructing understudies (Tumkaya, 2020).
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