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Measuring employee attrition intention in an auto-component manufacturing organisation
Orientation: The auto-component manufacturing sector, a critical contributor to industrial growth, faces persistent challenges related to employee attrition, affecting operational efficiency and workforce stability. This study examines the influence of job satisfaction, work-life balance, and job stress on attrition intention among employees in Indian auto-component manufacturing organisations. Research purpose: To identify the key factors contributing to employee turnover and evaluate their relative impact on attrition intention. Motivation for the study: Amid rising concerns over attrition in the manufacturing industry, this research aims to explore how work-life balance and job stress influence employees intentions to leave their organisations. Research approach/design and method: Data were collected from 192 employees across 10 auto-component manufacturing companies in Pune, Maharashtra, India, using a structured questionnaire. The responses were analysed through structural equation modelling (SEM) using SPSS and AMOS. Main findings: The study reveals that work-life balance and job stress significantly impact attrition intention. Employees with poor work-life balance and high job stress are more likely to consider leaving. However, job satisfaction does not have a direct effect on attrition intention. Practical/managerial implications: Organisations should prioritise improving work-life balance and managing job stress by implementing flexible work policies, wellness programmes, and realistic workload distribution. Contribution/value-add: This study underscores the importance of addressing work-life balance and job stress in retention strategies, offering actionable insights for HR managers to mitigate attrition in the auto-component manufacturing sector. 2025. The Authors. -
Integrating Renewable Energy in Airports: A Roadmap Towards Carbon-Neutral Aviation Hubs
This chapter explains how one of the means of achieving carbon-neutral airports is by the airports integrating renewable energy. It examines how solar, wind, geothermal and hydropower technology can be used to curb carbon emission, reduce energy costs, and make the aviation industry environmentally sustainable. It lists the best practice, the impediments to the implementation, and the policy recommendations to the successful implementation based on the world case studies such as San Diego, Amsterdam Schiphol, and Denver airports. The discussion notes financial, technological and regulatory challenges, and predicts future trends of smart grids, energy storage, and electric ground equipment that can turn airports to sustainable energy centers that will support low-carbon aviation. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Segmentation and Recognition of E. coli Bacteria Cell in Digital Microscopic Images Based on Enhanced Particle Filtering Framework
Image processing and pattern recognitions play an important role in biomedical image analysis. Using these techniques, one can aid biomedical experts to identify the microbial particles in electron microscopy images. So far, many algorithms and methods are proposed in the state-of-the-art literature. But still, the exact identification of region of interest in biomedical image is a research topic. In this paper, E. coli bacteria particle segmentation and classification is proposed. For the current research work, the hybrid algorithm is developed based on sequential importance sampling (SIS) framework, particle filtering, and Chan–Vese level set method. The proposed research work produces 95.50% of average classification accuracy. 2019, Springer Nature Singapore Pte Ltd. -
3D face recognition based on symbolic FDA using SVM classifier with similarity and dissimilarity distance measure
Human face images are the basis not only for person recognition, but for also identifying other attributes like gender, age, ethnicity, and emotional states of a person. Therefore, face is an important biometric identifier in the law enforcement and human-computer interaction (HCI) systems. The 3D human face recognition is emerging as a significant biometric technology. Research interest into 3D face recognition has increased during recent years due to availability of improved 3D acquisition devices and processing algorithms. A 3D face image is represented by 3D meshes or range images which contain depth information. In this paper, the objective is to propose a new 3D face recognition method based on radon transform and symbolic factorial discriminant analysis using KNN and SVM classifier with similarity and dissimilarity measures, which are applied on 3D facial range images. The experimentation is done using three publicly available databases, namely, Bhosphorus, Texas and CASIA 3D face database. The experimental results demonstrate the effectiveness of the proposed method. 2017 World Scientific Publishing Company. -
3D face recognition based on symobolic FDA using SVM classifier with similarity and dissimilarity distance measure /
International Journal of Pattern Recognition and Artificial Intelligence, 31, Issue 4, ISSN: 1793-6381. -
Artificial intelligence (AI) governance in organizational decision-making: balancing autonomy, accountability and transparency
Purpose This study aims to investigate the ethical and practical implications of delegating decision-making to AI systems, focusing on the necessity for a robust governance framework. Specifically, it examines how autonomy, transparency and accountability within AI governance influence organizational decision-making. Design/methodology/approach Employing a quantitative survey methodology, this study gathered data from 452 business owners and managers in Indian IT companies. The questionnaire was disseminated using online platforms and departmental communication channels. Structural equation modelling (SEM) was utilized for data analysis, allowing for the examination of relationships among autonomy, transparency, accountability and decision-making. Findings The findings indicate that autonomy, transparency and accountability significantly impact organizational decision-making processes. Specifically, autonomy and accountability were found to directly influence decision-making, while transparency also played a crucial role. Additionally, social innovation was identified as a significant moderating factor, enhancing the relationship between AI governance and decision-making outcomes. Originality/value This research contributes to the existing literature on AI governance by elucidating the critical role of ethical frameworks in organizational decision-making. By incorporating social innovation as a moderating variable, the study offers novel insights into how AI governance can be optimized to enhance decision-making processes. The application of SEM provides a rigorous analytical approach, facilitating a deeper understanding of the interplay between governance dimensions and decision-making outcomes. The findings have practical implications for organizations seeking to implement effective AI governance strategies in their operations. 2025 Emerald Publishing Limited -
GNSS Signal Obstruction Removal Tool for Evaluating and Improving Position Accuracy in Satellite Networks
The positioning accuracy of Global Navigation Satellite System (GNSS) is largely affected by the site's surroundings. However, the methods to simulate GNSS signal obstruction and the nature of signal obstruction have not yet been explored fully. In this research, we investigated a way to remove the signals received from a specific region by specifying azimuth and elevation from GNSS observation files and evaluating how the removal of signals affects GNSS positioning accuracy. In addition, we also investigated the signal blockage for buildings of certain dimensions and a mountain. Python was used as a programming language to develop a program for the signal removal. RTKPOST was used for the GNSS data processing, and RTKPLOT was used for the visualisation of processed data and analysis of positioning accuracy. We successfully developed a Python shell script to remove the signals in GNSS data file from specific region by specifying azimuth and elevation. It was also found that removing signals from azimuth 0 to 100 degree and elevation 0 to 30 degree increased the positioning accuracy within a low multipath dataset. However, when the maximum elevation angle was increased to 45 degrees, positioning accuracy degraded, indicating that the signal from certain elevations have a positive or negative impact on positioning accuracy. Further research avenues are explored as an extension of work done here. 2023 IEEE. -
A short review on environmental impacts and application of iron ore tailings in development of sustainable eco-friendly bricks
Increased mining activity of iron ore has led to the generation of voluminous wastes of various nature, especially during the different stages of its extraction and production. The improper disposal of such waste causes negative impact on the environment. One such waste which is generated during the beneficiation process of iron ore is waste iron ore tailings, which is also termed as IOT. Further, dumping of IOT on open ground creates huge dumping sites. This dumping sites have been a concern to the environment and human population in its close vicinity. Therefore, a need to effectively use IOT has become one of the subjects of interest for many researchers. This article provides a short review of environmental problems caused due to improper disposal of IOT, and also reviews on the reuse methods of IOT in the construction sector, which helps to alleviate the environmental pollution associated with improper disposal of IOT. Furthermore, reuse of IOT in construction sector reduces the exploitation of the virgin materials for production of construction material, and thus reducing depletion of natural resources. Based on the existing literatures and findings it was observed that the use of IOT to develop stable building blocks using unconventional methods showed great potential and improved performance, when compared with conventional materials such as clay fired bricks. 2021 -
Phytochemicals of Nardostachys jatamansi as potential inhibitors of HCV E2 receptor: An in silico study
Hepatitis C virus (HCV) is the causative agent of acute and chronic hepatitis and can lead to liver cirrhosis. High variability in the HCV genome renders vaccine formulation strenuous. Modern pharmaceuticals rely heavily on plant-based compounds for drug production. This study focuses on in-silico screening of phytochemicals derived from an herbal plant, Nardostachys jatamansi, for the treatment of HCV by inhibiting its E2 receptor, which binds to the hepatocytes, enabling viral entry into the liver. Computer-aided drug design utilizes various tools such as molecular docking tools, including AutoDock Vina, Avogadro, PyMol, Discovery Studio Visualizer, LigPlot+, and online tools like SwissADME (Absorption, Delivery, Metabolism and Excretion) for analysis of pharmacokinetics and pharmacodynamics of phytochemicals. Toxicity studies were carried out using pkCSM. 25 bioactive phytochemicals of N. jatamansi were analysed. The analysis was validated by comparing the data of the phytochemicals with an established antiviral drug, ribavirin. This is a novel approach to docking studies, exploring the possibility of medicinal plants as anti-hepatic drugs. Of the 25 compounds, nardosatachysin and ?-gurjunene are the standout performers and are considered potent inhibitors of HCV E2 receptor. The two compounds are recommended for further in vivo and in vitro trials to assess their efficacy in treating HCV infection. 2024 Lalrintluanga Hnamte, et al. -
Purpose-driven leadership and organizational success: a case of higher educational institutions
Purpose: This paper aims to examine the relationships between organizational purpose, leadership practices and sustainable outcomes for universities in emerging economies. We propose that a strong sense of purpose is a fundamental and defining feature in the leadership practices of these institutions, which ultimately contributes to their success. Design/methodology/approach: The authors present a research model that defines the relationships between a sense of purpose, leadership practices, student success outcomes, alumni involvement outcomes and societal reputation outcomes. Over 200 higher education administrators in India participated in the study. Findings: The institutions' sense of purpose directly relates to their leadership engagement practices and their student success outcomes. Student success outcomes are a crucial linkage between leadership engagement practices and alumni involvement outcomes to achieve their societal reputation. Practical implications: As competitiveness intensifies, educational institutions under resource constraints must differentiate their organizational practices. This paper demonstrates how their core purpose and leadership actions result in achieving effective outcomes and overall sustainable societal reputation. Originality/value: There is a significant difference between having an organizational purpose and enacting that purpose through their leadership practices. These results highlight the cascading effect from the institution's fundamental sense of purpose to their leadership practices and the positive outcomes of student success, alumni involvement and societal reputation. 2021, Emerald Publishing Limited. -
The merging odyssey of trade, investment and partnership: a linkage model of India and Korea interactions
With the rising presence of India as a global power and Korea as an advanced economy, the collaborative alliance between two nations is of growing research interest. India and Korea are vastly different in terms of demographics, cultural traditions and historical experiences. However, they are unusually compatible for their shared vision and amazingly comparable in their unique positions in the dynamic world that involves strong coordinating linkage mechanisms and constructive influences. This paper aims to examine how India and Korea come to forge strategic alliance both in business relationships and national interests. We briefly review the history of interactions between India and Korea and define a unique model of linkage roles. After discussing network theory of interactions in liberal international order, propositions explain step by step how India and Korea merge to create better future for countless people through trade, investment, and partnerships. Growth stages of global firms for domestic advantage and global competitiveness are presented as well. Managerial implications and future research issues are discussed. Copyright 2022 Inderscience Enterprises Ltd. -
Managing change, growth and transformation: Case studies of organizations in an emerging economy
Purpose: In view of dynamic and widespread economic transformation in emerging economies, managing organizational change and growth in this context deserves more research attention. The purpose of this paper is to examine how three organizations in different industries manage change, growth and transformation in their organizational ecosystem. Design/methodology/approach: The authors conducted in-depth interviews with the leadership of three organizations in different economic sectors in India, a country representing an emerging economy. The authors also reviewed historical data from these organizations. Three case studies illustrating the evolution of these organizations were developed from the data collected. Findings: Lessons and implications from the three case studies suggest the following key elements of effective organizational change mechanisms in an emerging economy: visionary entrepreneurial leadership; program quality excellence; scale growth and scope expansion; network capabilities; and sustainable stakeholders engagement. At the same time, this study also shows how these organizations manage change, growth and transformation in the context of a society with strong traditions and cultural norms. Research limitations/implications: Results and conclusions may be limited by the fact that the study is based on three case studies. Additional studies from a variety of industries with large numbers of participants will be helpful in more fully understanding the ways in which change, growth and transformation can best be developed and deployed in different organizational settings. Practical implications: The proposed model of organizational change in an emerging economy may assist organizational leadership in designing and sustaining their change efforts. Social implications: This study highlights the role of visionary entrepreneurial leadership and the impact of organizational growth mechanisms on organizational value delivery capabilities and organizational reputation. Originality/value: Lessons and implications of five growth steps of outstanding organizations in an emerging economy context provide valuable insight for organizational change, growth and transformation in other emerging contexts. 2019, Emerald Publishing Limited. -
Responding to pandemic challenges: leadership lessons from multinational enterprises (MNEs) in India
Purpose: The business sector plays a major role in achieving comprehensive economic development goals in emerging economies. Consequently, the effects of business responses to the COVID-19 pandemic are receiving increasing research attention from an organizational management development perspective. This article aims to examine the role of leadership in charting the course in an extraordinary crisis context. Design/methodology/approach: Using institutional leadership theory, leadership contingency theory and dynamic leadership capability theory, the authors present a research framework that defines macrochallenges and organizational level responses and outcomes. The article adopts a case study approach, which includes the identification of four target companies and conducting in-depth interviews with senior management professionals within those companies at different time periods. Findings: Based on the interviews, the steps that Indian companies adopted to respond to the COVID-19 challenge are identified. Expanding the insight from the case study, the findings suggest that although feeling overwhelmed at first, organizational leaders combine prudent (i.e. timely and speedy actions for survival first) and bold (i.e. future envisioning for expansion and growth) actions enabling these firms to weather two waves of the COVID-19 pandemic in India. Originality/value: These multiple case studies are unique in exploring MNEs from different industries. This study also highlights the dynamic relationships between leadership practices, risk management strategies and performance outcomes based on a sound theoretical model and rigorous study methods. 2022, Emerald Publishing Limited. -
An Integrated Model for Team Dynamics for Enhanced Collaboration and Performance
The CTF model introduces a new approach to team organization, inspired by the atomic structure of carbon. This interdisciplinary model combines organizational psychology, team dynamics research, and chemistry principles. The paper evaluates current team models, such as Belbins team roles, Hackmans model of team effectiveness, and the GRPI model, emphasizing their strengths and weaknesses. CTF expands on these frameworks while addressing their limitations. It consists of a productivity core (similar to protons and neutrons) and critique networks (similar to electrons), connected by Team Cohesion Factors. Unlike previous models that focus on specific aspects, CTF provides a comprehensive structure that integrates leadership, execution, and feedback mechanisms. It balances a hierarchical structure with collaborative input, including internal and external feedback systems. Inspired by the adaptability of carbon, the model is suitable for dynamic environments. Although it shows promise in addressing the limitations of previous models, CTF needs empirical validation. This paper lays out the theoretical basis of CTF, compares it with existing frameworks, explores its potential benefits and limitations, and outlines future research directions. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
K-shell fluorescence yields of barium and lanthanum
K-shell fluorescence yields for barium and lanthanum have been measured adopting simple 2? geometrical configuration and employing a weak 57Co radioactive source. A scintillation spectrometer with an NaI(Tl) detector of dimensions 44.5mm diameter0mm thickness was employed for the detection and measurement of radiation. The results obtained are in good agreement with the best-fitted values of Hubbell et al. (1994) and also with the other experimental values, indicating that our simple method can be extended to determine fluorescence parameters of high Z materials. 2011 Elsevier Ltd.