| Description |
1 online resource (155 pages) |
| Series |
Management for Professionals |
|
Management for professionals.
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| Contents |
Intro -- Preface -- Contents -- 1: Introduction -- 1.1 The Value of This Book -- 1.2 Who Is This Book For? -- 1.3 Background and Motivation -- 1.4 Assumptions -- 1.5 Why R? -- 1.6 Terminology and Contextual Considerations -- 1.7 Structure of the Book -- 1.7.1 Chapter Structure -- 1.7.2 Chapter Progression -- 1.8 Getting the Most Out of this Book -- 1.9 Tutorial: A Brief Intro to Some Tidyverse Functions -- 1.9.1 Setup -- 1.9.2 Intro to the "Pipe" -- 1.9.3 Using Filter, Select, Mutate, Group, and Summarise -- 1.9.4 Long and Wide Format -- 1.9.5 Using ggplot2 for Visualization |
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1.9.6 Using Purrr and Map for Iteration -- 1.10 Reflections on the Tidyverse in Practice -- 2: Inputs and Outputs -- 2.1 Objective -- 2.2 What Are Inputs and Outputs? -- 2.3 A Detailed Look at Inputs and Outputs -- 2.3.1 The Input-Output Paradigm -- 2.3.2 Identifying Inputs and Outputs -- 2.4 Tutorial: Organizing Input-Output Data -- 2.4.1 Setup -- 2.4.2 Introduction -- 2.4.3 Clean the Data -- 2.4.4 Input-Output Structure -- 2.4.5 Add in More Data -- 2.4.6 Fashion a Data Set for Specific Analysis -- 2.5 Reflections on Inputs and Outputs in Practice -- 3: The Productivity Ratio |
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3.1 Objective -- 3.2 What Is the Productivity Ratio? -- 3.3 A Detailed Look at the Productivity Ratio -- 3.3.1 Total-Factor, Multi-Factor, and Single-Factor Productivity -- 3.3.2 Selecting Appropriate Indicators for Education -- 3.3.3 Value-Add -- 3.4 Tutorial: Competing Production Functions -- 3.4.1 Setup -- 3.4.2 Introduction -- 3.4.3 Create and Join the New Test Scores Data -- 3.4.4 Operational Efficiency Productivity -- 3.4.5 Reputational Productivity -- 3.4.6 Value-Add Productivity -- 3.4.7 Compile All the Results -- 3.5 Reflections on the Productivity Ratio in Practice |
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4: Productivity Change -- 4.1 Objective -- 4.2 What Is Productivity Change? -- 4.3 A Detailed Look at Measuring Productivity Change -- 4.3.1 Estimation Technique -- 4.3.2 Defining TI -- 4.3.3 NRC Model (Adjusted Load) -- 4.3.4 Adjusting for the Real Value of Money -- 4.4 Tutorial: Measuring University Productivity Change -- 4.4.1 Setup -- 4.4.2 Introduction -- 4.4.3 Get the Raw Data -- 4.4.4 Adjust for RVM and Adjusted Load -- 4.4.5 Calculate Change Indexes -- 4.4.6 Calculate Cumulative Change -- 4.4.7 Further Functionalize Our Code -- 4.4.8 Calculate Data for TI Weights |
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4.4.9 Calculate TIs -- 4.5 Reflections on Productivity Change in Practice -- 5: Productivity Change with Threshold Analysis -- 5.1 Objective -- 5.2 What Is Threshold Analysis? -- 5.3 A Detailed Look at Threshold Analysis for Universities -- 5.3.1 Multiple Outputs -- 5.3.2 Characterizing Production Technology -- 5.3.3 Adjusted Publications -- 5.4 Tutorial: Teaching-Research Nexus or Divide? -- 5.4.1 Setup -- 5.4.2 Introduction -- 5.4.3 Create New Data Set -- 5.4.4 Examine Institutional Change Profiles -- 5.4.5 Calculate Productivity -- 5.4.6 Threshold Analysis |
| Summary |
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 |
| Notes |
5.4.7 Rankings Analysis |
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Includes index |
| Subject |
Nonprofit organizations -- Capital productivity -- Data processing
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|
R (Computer program language)
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|
R (Computer program language)
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| Form |
Electronic book
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| ISBN |
9783030729653 |
|
3030729656 |
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