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Article
Publication date: 9 March 2020

Vishal Gupta

Integrating the behavioral theory of leadership, the componential theory of creativity and the self-determination theory (SDT), the study tests the relationships between…

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Abstract

Purpose

Integrating the behavioral theory of leadership, the componential theory of creativity and the self-determination theory (SDT), the study tests the relationships between leadership, work motivation (intrinsic motivation, integrated extrinsic motivation, extrinsic motivation) and employee-level innovation (innovative work behavior and innovation outcomes) in a work setting.

Design/methodology/approach

Data were collected using a survey questionnaire from 493 scientists working in India's largest civilian research and development (R&D) organization. The structural equation modeling (SEM) method was used to test the hypothesized relationships between the study variables.

Findings

The study found evidence for positive relationships between leadership, employee autonomous motivation (intrinsic and integrated extrinsic motivation) and employee-level innovation. The study shows that extrinsic motivation is positively related to innovation only when the value of rewards is integrated to one's sense of self (integrated extrinsic motivation). Extrinsic motivation, otherwise, is not related to innovation.

Research limitations

The study was cross-sectional, so inferences about causality are limited.

Practical implications

First, while extrinsic motivation is considered bad for innovation, the study provides evidence that integrated extrinsic motivation complements intrinsic motivation and encourages employee-level innovation. Second, the study shows that leaders can aid the process of development of autonomous motivation by displaying positive behaviors. Third, the study validates the mediating role of autonomous motivation for the leadership–innovation relationship.

Originality/value

The study provides an insight into the underlying process through which leaders can impact innovation at the workplace. To the best of the author's knowledge, such a study is the first of its kind undertaken in an organizational context.

Details

Personnel Review, vol. 49 no. 7
Type: Research Article
ISSN: 0048-3486

Keywords

Article
Publication date: 20 October 2022

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.

Details

Personnel Review, vol. 53 no. 1
Type: Research Article
ISSN: 0048-3486

Keywords

Article
Publication date: 19 April 2022

Raj Agarwal, Vishal Gupta and Jaskaran Singh

The complications caused by metallic orthopaedic bone screws like stress-shielding effect, screw loosening, screw migration, higher density difference, painful reoperation and…

Abstract

Purpose

The complications caused by metallic orthopaedic bone screws like stress-shielding effect, screw loosening, screw migration, higher density difference, painful reoperation and revision surgery for screw extraction can be overcome with the bioabsorbable bone screws. This study aims to use additive manufacturing (AM) technology to fabricate orthopaedic biodegradable cortical screws to reduce the bone-screw-related-complications.

Design/methodology/approach

The fused filament fabrication technology (FFFT)-based AM technique is used to fabricate orthopaedic cortical screws. The influence of various process parameters like infill pattern, infill percentage, layer height, wall thickness and different biological solutions were observed on the compressive strength and degradation behaviour of cortical screws.

Findings

The porous lattice structures in cortical screws using the rapid prototyping technique were found to be better as porous screws can enhance bone growth and accelerate the osseointegration process with sufficient mechanical strength. The compressive strength and degradation rate of the screw is highly dependent on process parameters used during the fabrication of the screw. The compressive strength of screw is inversely proportional to the degradation rate of the cortical screw.

Research limitations/implications

The present study is focused on cortical screws. Further different orthopaedic screws can be modified with the use of different rapid prototyping techniques.

Originality/value

The use of rapid prototyping techniques for patient-specific bone screw designs is scantly reported. This study uses FFFT-based AM technique to fabricate various infill patterns and porosity of cortical screws to enhance the design of orthopaedic cortical screws.

Details

Rapid Prototyping Journal, vol. 28 no. 9
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 1 January 2024

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.

Details

Rapid Prototyping Journal, vol. 30 no. 3
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 13 September 2023

Abhinav Shard, Mohinder Pal Garg and Vishal Gupta

The purpose of this study is to explore the machining characteristics of electrical discharge machining (EDM) when a tool is fabricated using powder metallurgy. Because pure Cu…

Abstract

Purpose

The purpose of this study is to explore the machining characteristics of electrical discharge machining (EDM) when a tool is fabricated using powder metallurgy. Because pure Cu tools obtained using conventional machining pose problems of high tool wear rate, tool oxidation causes loss of characteristics in tool shape.

Design/methodology/approach

The research investigation carried out experiments planned through Taguchi’s robust design of experiments and used analysis of variance (ANOVA) to carry out statistical analysis.

Findings

It has been found that copper and chromium electrodes give less metal removal rate as compared to the pure Cu tool. Analytical outcomes of ANOVA demonstrated that MRR is notably affected by the variable’s polarity, peak current, pulse on time and electrode type in the machining of EN9 steel with EDM, whereas the variables pulse on time, gap voltage and electrode type have a significant influence on EWR. Furthermore, the process also showed that the use of powder metallurgy tool effectively reduces the value of SR of the machined surface as well as the tool wear rate. The investigation exhibited the possibility of the use of powder metallurgy electrodes to upgrade the machining efficiency of EDM process.

Research limitations/implications

There is no major limitation or implication of this study. However, the composition of the powders used in powder metallurgy for the fabrication of tools needs to be precisely controlled with careful control of process variables during subsequent fabrication of electrodes.

Originality/value

To the best of the authors’ knowledge, this is the first study that investigates the effectiveness of copper and chromium electrodes/tools fabricated by means of powder metallurgy in EDM of EN9 steel. The effectiveness of the tool is assessed in terms of productivity, as well as accuracy measures of MRR and surface roughness of the components in EDM machining.

Details

World Journal of Engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1708-5284

Keywords

Article
Publication date: 16 August 2021

Vishwanath Bijalwan, Vijay Bhaskar Semwal and Vishal Gupta

This paper aims to deal with the human activity recognition using human gait pattern. The paper has considered the experiment results of seven different activities: normal walk…

Abstract

Purpose

This paper aims to deal with the human activity recognition using human gait pattern. The paper has considered the experiment results of seven different activities: normal walk, jogging, walking on toe, walking on heel, upstairs, downstairs and sit-ups.

Design/methodology/approach

In this current research, the data is collected for different activities using tri-axial inertial measurement unit (IMU) sensor enabled with three-axis accelerometer to capture the spatial data, three-axis gyroscopes to capture the orientation around axis and 3° magnetometer. It was wirelessly connected to the receiver. The IMU sensor is placed at the centre of mass position of each subject. The data is collected for 30 subjects including 11 females and 19 males of different age groups between 10 and 45 years. The captured data is pre-processed using different filters and cubic spline techniques. After processing, the data are labelled into seven activities. For data acquisition, a Python-based GUI has been designed to analyse and display the processed data. The data is further classified using four different deep learning model: deep neural network, bidirectional-long short-term memory (BLSTM), convolution neural network (CNN) and CNN-LSTM. The model classification accuracy of different classifiers is reported to be 58%, 84%, 86% and 90%.

Findings

The activities recognition using gait was obtained in an open environment. All data is collected using an IMU sensor enabled with gyroscope, accelerometer and magnetometer in both offline and real-time activity recognition using gait. Both sensors showed their usefulness in empirical capability to capture a precised data during all seven activities. The inverse kinematics algorithm is solved to calculate the joint angle from spatial data for all six joints hip, knee, ankle of left and right leg.

Practical implications

This work helps to recognize the walking activity using gait pattern analysis. Further, it helps to understand the different joint angle patterns during different activities. A system is designed for real-time analysis of human walking activity using gait. A standalone real-time system has been designed and realized for analysis of these seven different activities.

Originality/value

The data is collected through IMU sensors for seven activities with equal timestamp without noise and data loss using wirelessly. The setup is useful for the data collection in an open environment outside the laboratory environment for activity recognition. The paper also presents the analysis of all seven different activity trajectories patterns.

Details

Industrial Robot: the international journal of robotics research and application, vol. 49 no. 1
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 27 January 2022

Safal Batra, Vishal K. Gupta, Sunil Sharma and Rahul Yadav

The purpose of this study is to investigate potential lenders of legitimacy for business-to-business (B2B) startups as reflected in the willingness of potential customers to do…

Abstract

Purpose

The purpose of this study is to investigate potential lenders of legitimacy for business-to-business (B2B) startups as reflected in the willingness of potential customers to do business with startup firms. This study theorizes the role of familiarity with B2B startups, their founding teams and their product offerings in influencing perceptions about legitimacy among potential customers.

Design/methodology/approach

Data are collected from key decision-makers involved in B2B procurements in large Indian companies and analyzed using conjoint analysis.

Findings

Results suggest that familiarity with product/service offerings from B2B startups is the most salient factor in forming favorable assessments for the venture, followed by the awareness of the startups and their founding teams, in that order.

Practical implications

The research makes several contributions to understanding the legitimacy of B2B startups from the customers’ perspective. The study provides a nuanced view of the factors impinging on legitimacy. The conceptualization of legitimacy as a reflection of willingness to buy (in other words, willingness to do business with) provides a useful lens with which to study the interactions between B2B startups and potential customers.

Originality/value

The strong empirical support the study finds for the predicted relationships in an international context, specifically India, enhances theory development, providing a solid foundation for future knowledge generation around the demand side legitimacy concept.

Details

Journal of Business & Industrial Marketing, vol. 37 no. 12
Type: Research Article
ISSN: 0885-8624

Keywords

Article
Publication date: 2 November 2023

Khaled Hamed Alyoubi, Fahd Saleh Alotaibi, Akhil Kumar, Vishal Gupta and Akashdeep Sharma

The purpose of this paper is to describe a new approach to sentence representation learning leading to text classification using Bidirectional Encoder Representations from…

Abstract

Purpose

The purpose of this paper is to describe a new approach to sentence representation learning leading to text classification using Bidirectional Encoder Representations from Transformers (BERT) embeddings. This work proposes a novel BERT-convolutional neural network (CNN)-based model for sentence representation learning and text classification. The proposed model can be used by industries that work in the area of classification of similarity scores between the texts and sentiments and opinion analysis.

Design/methodology/approach

The approach developed is based on the use of the BERT model to provide distinct features from its transformer encoder layers to the CNNs to achieve multi-layer feature fusion. To achieve multi-layer feature fusion, the distinct feature vectors of the last three layers of the BERT are passed to three separate CNN layers to generate a rich feature representation that can be used for extracting the keywords in the sentences. For sentence representation learning and text classification, the proposed model is trained and tested on the Stanford Sentiment Treebank-2 (SST-2) data set for sentiment analysis and the Quora Question Pair (QQP) data set for sentence classification. To obtain benchmark results, a selective training approach has been applied with the proposed model.

Findings

On the SST-2 data set, the proposed model achieved an accuracy of 92.90%, whereas, on the QQP data set, it achieved an accuracy of 91.51%. For other evaluation metrics such as precision, recall and F1 Score, the results obtained are overwhelming. The results with the proposed model are 1.17%–1.2% better as compared to the original BERT model on the SST-2 and QQP data sets.

Originality/value

The novelty of the proposed model lies in the multi-layer feature fusion between the last three layers of the BERT model with CNN layers and the selective training approach based on gated pruning to achieve benchmark results.

Details

Robotic Intelligence and Automation, vol. 43 no. 6
Type: Research Article
ISSN: 2754-6969

Keywords

Content available
Article
Publication date: 19 October 2021

Vishal Gupta, Naresh Khatri and Karthik Dhandapani

246

Abstract

Details

South Asian Journal of Business Studies, vol. 10 no. 3
Type: Research Article
ISSN: 2398-628X

Article
Publication date: 10 January 2023

Shrutika Sharma, Vishal Gupta and Deepa Mudgal

The implications of metallic biomaterials involve stress shielding, bone osteoporosis, release of toxic ions, poor wear and corrosion resistance and patient discomfort due to the…

Abstract

Purpose

The implications of metallic biomaterials involve stress shielding, bone osteoporosis, release of toxic ions, poor wear and corrosion resistance and patient discomfort due to the need of second operation. This study aims to use additive manufacturing (AM) process for fabrication of biodegradable orthopedic small locking bone plates to overcome complications related to metallic biomaterials.

Design/methodology/approach

Fused deposition modeling technique has been used for fabrication of bone plates. The effect of varying printing parameters such as infill density, layer height, wall thickness and print speed has been studied on tensile and flexural properties of bone plates using response surface methodology-based design of experiments.

Findings

The maximum tensile and flexural strengths are mainly dependent on printing parameters used during the fabrication of bone plates. Tensile and flexural strengths increase with increase in infill density and wall thickness and decrease with increase in layer height and wall thickness.

Research limitations/implications

The present work is focused on bone plates. In addition, different AM techniques can be used for fabrication of other biomedical implants.

Originality/value

Studies on application of AM techniques on distal ulna small locking bone plates have been hardly reported. This work involves optimization of printing parameters for development of distal ulna-based bone plate with high mechanical strength. Characterization of microscopic fractures has also been performed for understanding the fracture behavior of bone plates.

Details

Rapid Prototyping Journal, vol. 29 no. 5
Type: Research Article
ISSN: 1355-2546

Keywords

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