Path to Success: Human Resource Management Decision-Making

2012 ◽  
Author(s):  
Steven D. Formaneck
Keyword(s):  
Decision Making ◽  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Management Decision ◽  
Management Decision Making

scholarly journals An Objective-Based Entropy Approach for Interpretable Decision Tree Models in Support of Human Resource Management: The Case of Absenteeism at Work

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 821 ◽  
Author(s):  
Gonen Singer ◽  
Izack Cohen
Keyword(s):  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Information Gain ◽  
Negative Impact ◽  
Management Decision ◽  
Human Resource Managers ◽  
Resource Managers ◽  
Management Decision Making ◽  
Cart Model

The negative impact of absenteeism on organizations’ productivity and profitability is well established. To decrease absenteeism, it is imperative to understand its underlying causes and to identify susceptible employee subgroups. Most research studies apply hypotheses testing and regression models to identify features that are correlated with absenteeism—typically, these models are limited to finding simple correlations. We illustrate the use of interpretable classification algorithms for uncovering subgroups of employees with common characteristics and a similar level of absenteeism. This process may assist human resource managers in understanding the underlying reasons for absenteeism, which, in turn, could stimulate measures to decrease it. Our proposed methodology makes use of an objective-based information gain measure in conjunction with an ordinal CART model. Our results indicate that the ordinal CART model outperforms conventional classifiers and, more importantly, identifies patterns in the data that have not been revealed by other models. We demonstrate the importance of interpretability for human resource management through three examples. The main contributions of this research are (1) the development of an information-based ordinal classifier for a published absenteeism dataset and (2) the illustration of an interpretable approach that could be of considerable value in supporting human resource management decision-making.

The Human Resource Factor in Small Business Decision Making

1985 ◽  
Vol 10 (2) ◽  
pp. 53-62 ◽  
Author(s):  
Joseph R. Rocha ◽  
M. Riaz Khan
Keyword(s):  
Decision Making ◽  
Resource Management ◽  
Small Business ◽  
Human Resource Management ◽  
Human Resource ◽  
Small Firms ◽  
Counseling Program ◽  
Business Decision ◽  
Functional Areas ◽  
Resource Factor

Activities of a group of small firms were studied over a six-year period to determine the manner In which their performance reflected the results of a counseling program. The effects of counseling In a number of functional areas were explored. Findings of the Investigation suggest that while adequate attention to marketing, financial, and technological matters Is essential, firms that Ignore the requirements of sound human resource management may fall to remain competitive.

Application of Statistics in Human Resource Management

2017 ◽  
pp. 15-37
Author(s):  
Roma Puri ◽  
Pooja Sengupta
Keyword(s):  
Decision Making ◽  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Statistical Techniques ◽  
Evidence Based ◽  
Statistical Tools ◽  
Overall Functioning

The chapter gives an outline of the shift in HRM from being intuitive to quantitative in its decision making and overall functioning. The role of HRM is transforming with application of statistical techniques that make HR more evidence based and accountable. The chapter will discuss some successful applications of statistical techniques, basic and, in HRM by renowned organizations worldwide as well as elucidate upon some of the most applied statistical techniques. After reading this chapter learner will appreciate the need for applying Statistics in HRM, have an understanding of the avenues for application of statistical tools and get an outline of the various statistical techniques that are appropriate for different HR functions.

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