Understanding the Interrelationships Between Organizational Performance Measurement System Implementation Variables.
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| Title: | Understanding the Interrelationships Between Organizational Performance Measurement System Implementation Variables. |
|---|---|
| Authors: | Oladimeji, O.1 (AUTHOR) oladimejioo@cofc.edu, Keathley-Herring, H. Heather2 (AUTHOR), Cross, J. A.3 (AUTHOR) |
| Source: | Engineering Management Journal. 2025, Vol. 37 Issue 1, p71-89. 19p. |
| Subjects: | Analytic network process, Organizational performance measurement, Information technology, Perceived benefit, Multiple criteria decision making |
| Abstract: | Performance measurement (PM) systems are increasingly being adopted to manage and improve organizations' effectiveness. However, a review of the research shows that there are a significant number of unsuccessful PM systems with indications of challenges arising during the implementation phase. A study involving subject-area experts was conducted and the analytic network process (ANP), for evaluating the multi-criteria decision model, was used to quantify the effects of the dynamic interrelationships among the model variables as well as the systemic effect of the factors on PM system implementation success (IS). The results show that Leadership Support and the Implementation Approach are the most important factors for successful implementation of PM systems. Meanwhile, factors related to training, participation, and an effective information technology system help users of PM understand the measures and identify their perceived benefits, thereby contributing to performance goals and objectives. This study provides a comprehensive and rigorous analysis by employing an expert study to evaluate and quantify the effects of model variables and their interrelationships on PM system implementation success using the ANP methodology. Managers and researchers can use the prioritization of the factors and insights regarding key interrelationships to develop more specific strategies and better manage resources of the implementation effort. [ABSTRACT FROM AUTHOR] |
| Copyright of Engineering Management Journal is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 183416277 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Understanding the Interrelationships Between Organizational Performance Measurement System Implementation Variables. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Oladimeji%2C+O%2E%22">Oladimeji, O.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> oladimejioo@cofc.edu</i><br /><searchLink fieldCode="AR" term="%22Keathley-Herring%2C+H%2E+Heather%22">Keathley-Herring, H. Heather</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cross%2C+J%2E+A%2E%22">Cross, J. A.</searchLink><relatesTo>3</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Engineering+Management+Journal%22">Engineering Management Journal</searchLink>. 2025, Vol. 37 Issue 1, p71-89. 19p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Analytic+network+process%22">Analytic network process</searchLink><br /><searchLink fieldCode="DE" term="%22Organizational+performance+measurement%22">Organizational performance measurement</searchLink><br /><searchLink fieldCode="DE" term="%22Information+technology%22">Information technology</searchLink><br /><searchLink fieldCode="DE" term="%22Perceived+benefit%22">Perceived benefit</searchLink><br /><searchLink fieldCode="DE" term="%22Multiple+criteria+decision+making%22">Multiple criteria decision making</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Performance measurement (PM) systems are increasingly being adopted to manage and improve organizations' effectiveness. However, a review of the research shows that there are a significant number of unsuccessful PM systems with indications of challenges arising during the implementation phase. A study involving subject-area experts was conducted and the analytic network process (ANP), for evaluating the multi-criteria decision model, was used to quantify the effects of the dynamic interrelationships among the model variables as well as the systemic effect of the factors on PM system implementation success (IS). The results show that Leadership Support and the Implementation Approach are the most important factors for successful implementation of PM systems. Meanwhile, factors related to training, participation, and an effective information technology system help users of PM understand the measures and identify their perceived benefits, thereby contributing to performance goals and objectives. This study provides a comprehensive and rigorous analysis by employing an expert study to evaluate and quantify the effects of model variables and their interrelationships on PM system implementation success using the ANP methodology. Managers and researchers can use the prioritization of the factors and insights regarding key interrelationships to develop more specific strategies and better manage resources of the implementation effort. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Engineering Management Journal is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/10429247.2024.2361219 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 71 Subjects: – SubjectFull: Analytic network process Type: general – SubjectFull: Organizational performance measurement Type: general – SubjectFull: Information technology Type: general – SubjectFull: Perceived benefit Type: general – SubjectFull: Multiple criteria decision making Type: general Titles: – TitleFull: Understanding the Interrelationships Between Organizational Performance Measurement System Implementation Variables. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Oladimeji, O. – PersonEntity: Name: NameFull: Keathley-Herring, H. Heather – PersonEntity: Name: NameFull: Cross, J. A. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 10429247 Numbering: – Type: volume Value: 37 – Type: issue Value: 1 Titles: – TitleFull: Engineering Management Journal Type: main |
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