A Markov Model for Human Resources Supply Forecast Dividing the HR System into Subgroups

Belhaj, Rachid; Tkiouat, Mohamed

doi:10.4236/jssm.2013.63023

Cited by 16 publications

(16 citation statements)

References 11 publications

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“…In this type of method, fluctuations in labor levels are projected using historical transition rates 85 . These fluctuations are projected by analyzing historical trends in staff retention or movement, and keep it in to the future with the same trends of the past 86 .…”

Section: Markov Models Definitionmentioning

confidence: 99%

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Health Manpower Forecasting: A systematic Review for Models and Approaches

Rafiei

Abdollahzade

Hashemi

2019

Bangladesh J Med Sci

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Background: An appropriate planning requires forecasting the demand and supply of health manpower in an accurate manner. Objectives: The paper objective was to review health manpower forecasting approaches and methods and propose the improvement features for effectiveness of health manpower planning. Data sources: A systematic review was conducted for studies published in English from 1970-2014 using Pub Med, Science Direct, Pro Quest, and Google Scholar databases. Study eligibility criteria: Review articles, qualitative studies, questionnaire driven surveys, retrospective and prospective studies describing or applying various types of forecasting approaches and methods in health manpower forecasting were included in the review. Data collection and study appraisal: Two reviewers (SR and MA) independently appraised the studies to identify relevant ones to be included in the review. Results: A total of 128 studies were included in the review. As a result, two main categories of approaches (conceptual and analytical) for health manpower forecasting were identified with their strengths and weaknesses. Conclusions: Future forecasting methods should benefit from advantages of current approaches and overcome some of their main limitations. Applying a method which incorporates a wide range of factors affecting supply and demand, facilitates the collection of good quality data, monitors changing trends over time, considers the uncertainty of health systems and has a dynamic approach is proposed as an improvement roadmap for future forecasting. Bangladesh Journal of Medical Science Vol.18(3) 2019 p.458-472

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Section: Markov Models Definitionmentioning

confidence: 99%

“…They are able to give a variety of parameter values, also use confidence intervals and test statistical significance for different estimates 45 . Ability to simulate the consequence of different policy changes is another characteristic can be mentioned for 39,45,[86][87][88][89] .…”

Section: Strong Sidesmentioning

confidence: 99%

Health Manpower Forecasting: A systematic Review for Models and Approaches

Rafiei

Abdollahzade

Hashemi

2019

Bangladesh J Med Sci

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“…Belhaj and Tkiouat (2013) introduced a supplyand-demand forecasting model of the number of employees in a hierarchical time-dependent human resource system. Belhaj and Tkiouat (2013) introduced a supplyand-demand forecasting model of the number of employees in a hierarchical time-dependent human resource system.…”

Section: Time Series Modelsmentioning

confidence: 99%

“…In their model, the workforce system was managed through recruitment processes and hiring sources; promotion rates at the lowest two ranks were mandated, but not at the higher ranks, and retention rates varied across pay grades. Belhaj and Tkiouat (2013) introduced a supplyand-demand forecasting model of the number of employees in a hierarchical time-dependent human resource system. They assumed that each employee has limited promotion possibilities.…”

Section: Time Series Modelsmentioning

confidence: 99%

Workforce forecasting models: A systematic review

Safarishahrbijari

2018

Journal of Forecasting

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Workforce analytics involves using models that integrate internal and external data to predict future workforce and help organizations in any industry examine factors that have a prognostic effect. This paper assesses workforce modeling and prediction methods by examining their rationale, strengths, and constraints. It aims to identify enhancements for further development of workforce forecasting models and compares the capacity and reliability of different forecasting methods. Past and present modeling trends are described and critiqued based on their relevance to current requirements. Several approaches are reviewed, such as time series modeling and system dynamics simulation. Sensitivity analysis in models is assessed. The models are decomposed into three modes: supply‐based, demand‐based, and need‐based, which in some cases provide substantially different estimates of future workforce need. The chronological progression of models' development is analyzed. The articles are also classified based on the countries and the sectors that have paid great attention to workforce prediction research. Consideration of the use of workforce models and the inputs into such models is not within the scope of this paper.

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“…5) gives the proposed steps for a SHRM formulation beginning with the strategic planning; it relies on quantitative and qualitative data to define a HR strategy. Quantitative Information comes from the Gap Analysis using Markov Modeling (for Example), (Belhaj and Tkiouat, 2013) In forecasting the supply of human resources, organizations must consider both internal and external supply of qualified candidates. The domestic supply of candidates is influenced by the training, the manpower development, mobility policies, promotion and retirement.…”

Section: The Approachmentioning

confidence: 99%

A new Framework of Strategic Human Resource Management (SHRM) Based on Quantitative and Qualitative Data

Belhaj¹,

Tkiouat²

2017

American Journal of Applied Sciences

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Strategic Human Resource Management (SHRM) is a new concept followed especially in private sector; it is an approach to managing human resource that supports long-term business goals, it tries to enhance the management of HR to a strategic level through human capital. The purpose of this paper is to shed light on the main concepts used in the strategic human resource management, including the management and planning of human resource and focusing on the strategy formulation steps to arrive to a general framework of the SHRM. The present study was performed after analysing the SHRM formulation steps and proposing the process of implementation in the public and private sectors, the proposed framework suggests the use of scientific tools such as Markov modelling for the HR supply forecasting and the fuzzy method to refine the choice of a suitable strategy among others. The main finding of the paper is the proposition of a framework of SHRM that relies on quantitative and qualitative data, which enable us to rely on well analysed information to build a strategy. The reason behind this is to emphasize and encourage the use of scientific models in order to approach the reality and to refine the future projections.

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A Markov Model for Human Resources Supply Forecast Dividing the HR System into Subgroups

Cited by 16 publications

References 11 publications

Health Manpower Forecasting: A systematic Review for Models and Approaches

Health Manpower Forecasting: A systematic Review for Models and Approaches

Workforce forecasting models: A systematic review

A new Framework of Strategic Human Resource Management (SHRM) Based on Quantitative and Qualitative Data

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