Studies in stochastic models for human resource management problems

Abstract

Human resource management is an essential function of all enterprises. The complexity of the function depends on several factors such as the size of the organisation the industry sector the economic social political and regulatory framework The elements of human resource management at a very broad level encompass human resource acquisition development engagement and retirement Human resource planning is an integral part of each one of these elements The uncertainty in the environment that impacts the scale of operations and the behaviour of human resources under various conditions provide an opportunity to propose stochastic models to address industry problems. Such stochastic models facilitate in building decision support and decision management systems in the functional areas of human resource management. The focus of this thesis is on stochastic models in human resource management In this work the functional perspectives of human resource management have been integrated with applications of renewal theory newlineprinciples of optimisation and logistic regression to propose approaches and solutions to real world problems Grade sizes in hierarchical human resource systems assume importance as they facilitate effective control over operations efficient newlinefinancial planning and enhanced employee engagement. In a k grade human resource system an approach to determine grade sizes when there is a pattern between intermediate grade sizes is discussed In two grade human resource systems an approach to determine grade size characteristics when the system allows for training of personnel at a higher grade by a movement to the previous grade and recruitment of a certain proportion of voluntary attritions vi into the system is discussed The transient behaviour of the systems and the steady state characteristics for both these systems are derived newline newline