Optimal Strategies for a Knowledge Workers Acquisition Problem with Expanding and Volatile Demand: Train Internally or Recruit Externally?

The aim of this paper is to consider the process of supplying trained workers with knowledge and skills for upcoming business opportunities, and of training apprentices prepared to meet future demands in an IT service firm. As the demand for new workers has fluctuations, a firm should employ a buffer workforce such as apprentices or interns. However, as a result of rapid development of a business, the buffer‟s capacity may be exceeded, thus requiring the company to recruit skilled workers from outside the firm. It is thus important for a firm to map out a strategy for manpower planning so as to fulfill the demands of new business and minimize operation costs related to training apprentices and recruiting experienced workers. This paper first analyzes the demand and supply of workers for IT service in a knowledge-intensive field. It then presents optimal human resource planning via the familiar method of stochastic process - queueing analysis

A Sensitivity Analysis on the Impact of Uncertanties of the Supply and Demand of a Workforce on a Recruiting Strategy in an IT Service Company

This paper investigates a managerial problem related to human resource planning for an IT service company which mainly carries out time-base projects. As the demand for new workers is subject to wide fluctuations, the firm should hire workers in advance and train them. However, the firm should urgently recruit skilled workers from outside the firm due to the shortages in the workforce. Hence, it is important for the firm to design an optimal human resource planning program so as to fulfill the needs of new IT service projects and minimize operation costs, though this involves a trade-off between holding excess workers to prepare for upcoming demand and recruiting experienced workers. This paper presents a quantitative model that describes the stochastic behavior of the supply and demands of the workforce. Numerical results pertaining to the optimal solution are given via a simulation

Analysis of Repairable Geo/G/1 Queues with Negative Customers

We consider discrete-time Geo/G/1 queues with negative customers and a repairable server. The server is subject to failure due to a negative customer arrival. As soon as a negative customer arrives at a system, the server fails and one positive (ordinary) customer is forced to leave. At a failure instant, the server is turned off and the repair process immediately begins. We construct the mathematical model and present the probability generating functions of the system size distribution and the FCFS sojourn time distribution. Finally, some numerical examples are given to show the influence of negative customer arrival on the performance measures of the system

Discrete-time queues with discretionary priorities

In this paper, we consider a discrete-time two-class discretionary priority queueing model with generally distributed service times and per slot i.i.d. structured inputs in which preemptions are allowed only when the elapsed service time of a lower-class customer being served does not exceed a certain threshold. As the preemption mode of the discretionary priority discipline, we consider the Preemptive Resume, Preemptive Repeat Different, and Preemptive Repeat Identical modes. We derive the Probability Generating Functions (PGFs) and first moments of queue lengths of each class in this model for all the three preemption modes in a unified manner. The obtained results include all the previous works on discrete-time priority queueing models with general service times and structured inputs as their special cases. A numerical example shows that, using the discretionary priority discipline, we can more subtly adjust the system performances than is possible using either the pure non-preemptive or the preemptive priority disciplines.Queueing Discretionary priority General service times