Exploring the dynamica virtus of Machine Learning (ML) in Human Resource Management - A Critical Analysis of IT industry

2017 ◽  
Vol 5 (12) ◽  
pp. 173-180
Author(s):  
Malathi Sriram ◽  
◽  
◽  
L. Gandhi
Keyword(s):  
Machine Learning ◽  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Critical Analysis ◽  
It Industry

Linking Work Engagement to Job Performance Through Flexible Human Resource Management

2017 ◽  
Vol 20 (1) ◽  
pp. 72-87 ◽  
Author(s):  
Chandra Sekhar ◽  
Manoj Patwardhan ◽  
Vishal Vyas
Keyword(s):  
Resource Management ◽  
Job Performance ◽  
Human Resource Management ◽  
Employee Engagement ◽  
Human Resource ◽  
Work Engagement ◽  
It Professionals ◽  
It Industry ◽  
Relationship Of ◽  
The Impact

The Problem The Indian information technology (IT) industry has shown a phenomenal growth over the last two decades. These changes such as increased global competition and the shift in the blend and level of the workforce have led to an increasing level of uncertainty in the industry. To overcome this unprecedented change, IT firms need to adopt flexible human resource management (FHRM) that has a direct and/or indirect impact on job performance. Therefore, the purpose of this article is to explore the impact of work engagement on job performance through FHRM among IT professionals in India. The Solution The results indicate that the use of FHRM by the employees is an important mediator between the positive relationship of work engagement and job performance. Both work engagement and FHRM contributed to job performance. The sample firm and responses for the study were limited to IT industry domain only. The results suggest that FHRM should be promoted at the employee and firm levels to boost job performance. The Stakeholders Reflecting on the employee engagement and job performance via FHRM would boost the organizational flexibility in the IT industry. FHRM makes the employee more organization fit and more engaged for their respective job. This study may be helpful in unveiling the importance of flexibility in job performance. To the best of the authors’ knowledge, this is the first study that links work engagement, FHRM, and job performance in the Indian IT industry context. The study helps in the development of theory in FHRM and employee engagement.

Human resource management model based on three-layer BP neural network and machine learning

2020 ◽  
pp. 1-12
Author(s):  
Guohua Wei ◽  
Yi Jin
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Bp Neural Network ◽  
Management System ◽  
Learning Technology ◽  
Human Resource Management System ◽  
Resource Management System

At present, data is in a state of explosive growth. The rapid growth of data collected by enterprises has exceeded the processing capacity of traditional human resource management systems, resulting in their inability to perform data management and data analysis. In order to improve the practicality of the human resource management system, this paper applies machine learning technology to the human resource management system, selects dimensions according to the prediction method, and builds a combined model consisting of an optimized GM (1,1) model and a BP neural network model. The model is implemented by a three-layer BP neural network. In order to verify the performance of the research model, this article conducts research using an entity as an example. The research results show that the method proposed in this paper has certain practical effects and can improve the reference for subsequent related research.

scholarly journals Human Resource Management: A Critical Analysis

1970 ◽  
Author(s):  
Joanna Cullinane
Keyword(s):  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Critical Analysis ◽  
Industrial Relations ◽  
The Other ◽  
Management Theory ◽  
Western World ◽  
Employment Relationships ◽  
The Subject

Since the 1970-BOs, employment relationships in the western world have been influenced by the emergence of human resource management (HRM) which has, to some degree, challenged the existing order- industrial relations (IR). The debate resulting from the emergence of HRM has kept the academic presses churning. At one Level, there is a 'co-existence' debate which explores the likelihood that HRM will supplant IR. At another Level, debate focuses on the 'distinctiveness' of HRM from IR and/or personnel management theory. However, the debates between the HRM and IR fields have only been intra-discourse; HRM literature has been almost silent on the subject of IR, while IR has had little to say about HRM. This, despite the fact that it could be argued that IR and HRM are simply different views of the same set of phenomena. Neither the HRM nor IR fields seem able to incorporate the strengths of the other. By mapping the underlying paradigms of these two fields, this paper explores the question: 'What makes the fields of HRM and IR unable to articulate?'

Employees' Perspective on Human Resource Procurement Practices as a Retention Tool in Indian IT Sector

2008 ◽  
Vol 12 (4) ◽  
pp. 57-69 ◽  
Author(s):  
B. K. Punia ◽  
Priyanka Sharma
Keyword(s):  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Employee Retention ◽  
Management Practices ◽  
Dominant Role ◽  
It Industry ◽  
Human Resource Management Practices ◽  
Changing Economy ◽  
It Personnel

Employee Retention is the biggest challenge that Human Resource Management is facing today. The uncertainty of a changing economy, increasing competition and diversity in the workplace have compelled the organisations to hold on to their top performers at whatever cost they have to pay. It is a very difficult task for the recruiters to hire professionals with right skills set all over again. Thus the focus has shifted from ‘numbers' to ‘quality’ and from ‘recruitment’ to ‘retention.’ Many organisational human resource management practices play dominant role in building employee commitment and loyalty. Out of the plentiful practices, the procurement practice facilitates the entry of an employee in an organisation. Hence keeping in view the significance of this function, the researchers have ventured to investigate the influence of procurement practices on employees ‘retention intentions in the Indian IT industry. This paper studies the influence of organisational procurement practices on employee retention intentions on the basis of personal and positional variables of employees. It also examines the variations in the corporate perception on the procurement practices as a retention tool for IT Personnel.

A review of machine learning applications in human resource management

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Swati Garg ◽  
Shuchi Sinha ◽  
Arpan Kumar Kar ◽  
Mauricio Mani
Keyword(s):  
Machine Learning ◽  
Resource Management ◽  
Human Resource Management ◽  
Performance Management ◽  
Human Resource ◽  
Systematic Approach ◽  
Early Stage ◽  
Theoretical Frameworks ◽  
Content Type ◽  
And Performance

PurposeThis paper reviews 105 Scopus-indexed articles to identify the degree, scope and purposes of machine learning (ML) adoption in the core functions of human resource management (HRM).Design/methodology/approachA semi-systematic approach has been used in this review. It allows for a more detailed analysis of the literature which emerges from multiple disciplines and uses different methods and theoretical frameworks. Since ML research comes from multiple disciplines and consists of several methods, a semi-systematic approach to literature review was considered appropriate.FindingsThe review suggests that HRM has embraced ML, albeit it is at a nascent stage and is receiving attention largely from technology-oriented researchers. ML applications are strongest in the areas of recruitment and performance management and the use of decision trees and text-mining algorithms for classification dominate all functions of HRM. For complex processes, ML applications are still at an early stage; requiring HR experts and ML specialists to work together.Originality/valueGiven the current focus of organizations on digitalization, this review contributes significantly to the understanding of the current state of ML integration in HRM. Along with increasing efficiency and effectiveness of HRM functions, ML applications improve employees' experience and facilitate performance in the organizations.

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