Using analytic hierarchy process (AHP) to improve human performance: An application of multiple criteria decision making problem

被引:0
|
作者
Esra Albayrak
Yasemin Claire Erensal
机构
[1] Galatasaray University,Industrial Engineering Faculty
[2] Dogus University,Industrial Engineering Faculty
来源
关键词
Decision making; performance management; analytic hierarchy process; human performance;
D O I
暂无
中图分类号
学科分类号
摘要
In the global economy, the modern commercial and industrial organization needs to develop better methods of assessing the performance of the human resource than simply using performance measures such as efficiency or effectiveness. As organizations seek more aggressive ways to cut costs and to increase global competitiveness, the importance of establishing and sustaining high levels of employee performance increases. The main purpose of this paper is to solve the human performance improvement problem by employing Analytic Hierarchy Process (AHP) method. Decision makers (DMs) often deal with problems that involve multiple criteria. At given moments in time, companies will display characteristics that make certain factors; key factors in their competences. In this paper, we present a model, which illustrates the relations and importance between human performance improvement and the style of management. In using the AHP to model this problem, we developed a hierarchic structure to represent the problem of human performance management and made pairwise comparisons. In this paper, the AHP is suggested as a tool for implementing a multiple criteria performance improvement scheme. The AHP was used for the purpose of structuring and clarifying the relations and importance between human performance improvement and the style of management. The study found that in terms of company culture, participation, human capability, and attitudes the best management style in improving human performance is management by values.
引用
收藏
页码:491 / 503
页数:12
相关论文
共 50 条
  • [1] Using analytic hierarchy process (AHP) to improve human performance: An application of multiple criteria decision making problem
    Albayrak, E
    Erensal, YC
    [J]. JOURNAL OF INTELLIGENT MANUFACTURING, 2004, 15 (04) : 491 - 503
  • [2] Cognitive Multiple Criteria Decision Making and the Legacy of the Analytic Hierarchy Process
    Maria Moreno-Jimenez, Jose
    Vargas, Luis G.
    [J]. ESTUDIOS DE ECONOMIA APLICADA, 2018, 36 (01): : 67 - 80
  • [3] AN APPROACH TO USING THE ANALYTIC HIERARCHY PROCESS FOR SOLVING MULTIPLE CRITERIA DECISION-MAKING PROBLEMS
    BRYSON, N
    MOBOLURIN, A
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1994, 76 (03) : 440 - 454
  • [4] Application of AHP on multiple criteria decision making
    Xiong, Rui
    Jiang, Xiaoya
    [J]. Nanjing Hangkong Hangtian Daxue Xuebao/Journal of Nanjing University of Aeronautics & Astronautics, 1994, 26 (02):
  • [5] The Analytic Hierarchy Process for the Decision Tree with Multiple Criteria
    Brozova, Helena
    [J]. PROCEEDINGS OF THE 21ST INTERNATIONAL CONFERENCE MATHEMATICAL METHODS IN ECONOMICS 2003, 2003, : 26 - 33
  • [6] Multi-Criteria Decision Making Model for Application Maintenance Offshoring Using Analytic Hierarchy Process
    Rahman, Hanif Ur
    Raza, Mushtaq
    Afsar, Palwasha
    Alharbi, Abdullah
    Ahmad, Sultan
    Alyami, Hashym
    [J]. APPLIED SCIENCES-BASEL, 2021, 11 (18):
  • [7] An attempt at decision making in tissue engineering: reactor evaluation using the analytic hierarchy process (AHP)
    Omasa, T
    Kishimoto, M
    Kawase, M
    Yagi, K
    [J]. BIOCHEMICAL ENGINEERING JOURNAL, 2004, 20 (2-3) : 173 - 179
  • [8] Ethical Decision Making Using the Analytic Hierarchy Process
    Ido Millet
    [J]. Journal of Business Ethics, 1998, 17 : 1197 - 1204
  • [9] Ethical decision making using the analytic hierarchy process
    Millet, I
    [J]. JOURNAL OF BUSINESS ETHICS, 1998, 17 (11) : 1197 - 1204
  • [10] An Analytic Hierarchy Process (AHP) Group Decision Making Methodology for Imprecise Preferences
    Lee, Kathleen
    Jalao, Eugene Rex
    [J]. FUZZY SYSTEMS AND DATA MINING III (FSDM 2017), 2017, 299 : 203 - 220