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Measuring productivity in education ...
~
Moore, Kenneth.
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Measuring productivity in education and not-for-profits = with tools and examples in R /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Measuring productivity in education and not-for-profits/ by Kenneth Moore.
其他題名:
with tools and examples in R /
作者:
Moore, Kenneth.
出版者:
Cham :Springer International Publishing : : 2021.,
面頁冊數:
x, 148 p. :ill., digital ;24 cm.
內容註:
Chapter 1: Introduction -- Chapter 2: Inputs and Outputs -- Chapter 3: The Productivity Ratio -- Chapter 4: Productivity Change -- Chapter 5: Productivity Change with Threshold Analysis -- Chapter 6: Frontier Analysis with DEA -- Chapter 7: Values Analysis with DEA -- Chapter 8: Threshold Analysis for Absolute Productivity -- Chapter 9: Hypothesis Testing.
Contained By:
Springer Nature eBook
標題:
Nonprofit organizations - Capital productivity -
電子資源:
https://doi.org/10.1007/978-3-030-72965-3
ISBN:
9783030729653
Measuring productivity in education and not-for-profits = with tools and examples in R /
Moore, Kenneth.
Measuring productivity in education and not-for-profits
with tools and examples in R /[electronic resource] :by Kenneth Moore. - Cham :Springer International Publishing :2021. - x, 148 p. :ill., digital ;24 cm. - Management for professionals,2192-8096. - Management for professionals..
Chapter 1: Introduction -- Chapter 2: Inputs and Outputs -- Chapter 3: The Productivity Ratio -- Chapter 4: Productivity Change -- Chapter 5: Productivity Change with Threshold Analysis -- Chapter 6: Frontier Analysis with DEA -- Chapter 7: Values Analysis with DEA -- Chapter 8: Threshold Analysis for Absolute Productivity -- Chapter 9: Hypothesis Testing.
This book takes the reader through real-world examples for how to characterize and measure the productivity and performance of NFPs and education institutions-that is, organisations that produce value for society, which cannot be measured accurately in financial KPIs. It focuses on how best to frame non-profit performance and productivity, and provides a suite of tools for measurement and benchmarking. It further challenges the reader to consider alternative and appropriate uses of quantitative measures, which are fit-for-purpose in individual contexts. It is true that the risk of misusing quantitative measures is ever-present. But does that risk outweigh the benefits of forming a more precise and shared understanding of what could generate better outcomes? There will always be concerns about policy and performance management. Goodheart's Law states that once a measure becomes a target, it is no longer a good measure. This book helps to strike a meaningful balance between what can be measured, what cannot, and how best to use quantitative information in sectors that are often averse to being held up to the light and put on a scale by outsiders.
ISBN: 9783030729653
Standard No.: 10.1007/978-3-030-72965-3doiSubjects--Topical Terms:
3504921
Nonprofit organizations
--Capital productivity
LC Class. No.: HD2769.15
Dewey Class. No.: 657.98
Measuring productivity in education and not-for-profits = with tools and examples in R /
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This book takes the reader through real-world examples for how to characterize and measure the productivity and performance of NFPs and education institutions-that is, organisations that produce value for society, which cannot be measured accurately in financial KPIs. It focuses on how best to frame non-profit performance and productivity, and provides a suite of tools for measurement and benchmarking. It further challenges the reader to consider alternative and appropriate uses of quantitative measures, which are fit-for-purpose in individual contexts. It is true that the risk of misusing quantitative measures is ever-present. But does that risk outweigh the benefits of forming a more precise and shared understanding of what could generate better outcomes? There will always be concerns about policy and performance management. Goodheart's Law states that once a measure becomes a target, it is no longer a good measure. This book helps to strike a meaningful balance between what can be measured, what cannot, and how best to use quantitative information in sectors that are often averse to being held up to the light and put on a scale by outsiders.
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