Measuring Deficiencies in Nonprofit Management Lawrence C. Hunt, Organisational Scientist, Faculty of Business, Education, Law and Arts, University of.

Slides:



Advertisements
Similar presentations
European Commission, DG EAC – Unit A3
Advertisements

Variations of the Turing Machine
STATISTICS HYPOTHESES TEST (I)
Variance Estimation in Complex Surveys Third International Conference on Establishment Surveys Montreal, Quebec June 18-21, 2007 Presented by: Kirk Wolter,
David Burdett May 11, 2004 Package Binding for WS CDL.
1. 2 Begin with the end in mind! 3 Understand Audience Needs Stakeholder Analysis WIIFM Typical Presentations Expert Peer Junior.
Multiple-choice question
Converting Data to Information. Know your data Know your audience Tell a story.
Biostatistics Unit 5 Samples Needs to be completed. 12/24/13.
Break Time Remaining 10:00.
You will need Your text Your calculator
1 Heating and Cooling of Structure Observations by Thermo Imaging Camera during the Cardington Fire Test, January 16, 2003 Pašek J., Svoboda J., Wald.
Statistics and Data Analysis Professor William Greene Stern School of Business IOMS Department Department of Economics.
Adding Up In Chunks.
Artificial Intelligence
Chapter 8: Introduction to Hypothesis Testing. 2 Hypothesis Testing An inferential procedure that uses sample data to evaluate the credibility of a hypothesis.
Developing an Objective Measure for Flushing on Chipseals Dave Whitehead – Senior Asset Manager NZTA National Office.
© The McGraw-Hill Companies, Inc., Chapter 10 Testing the Difference between Means and Variances.
$100,000 Pyramid A Fun Vocabulary Game! CAN YOU GUESS ALL SIX WORDS IN 1 MINUTE? Player 1: Sees the word and defines/describes it without saying the word.
9. Two Functions of Two Random Variables
4/4/2015Slide 1 SOLVING THE PROBLEM A one-sample t-test of a population mean requires that the variable be quantitative. A one-sample test of a population.
Kazakh National University in the education system of Kazakhstan
Student conference Tuesday 7 and Wednesday 8 October 2014.
FIGURE 3-1 Basic parts of a computer. Dale R. Patrick Electricity and Electronics: A Survey, 5e Copyright ©2002 by Pearson Education, Inc. Upper Saddle.
Data, Now What? Skills for Analyzing and Interpreting Data
Hypothesis testing Week 10 Lecture 2.
© 2001 Prentice-Hall, Inc.Chap 9-1 BA 201 Lecture 15 Test for Population Mean Known.
Chapter 9 Hypothesis Testing 9.4 Testing a Hypothesis about a Population Proportion.
Business Statistics: A Decision-Making Approach, 7e © 2008 Prentice-Hall, Inc. Chap 9-1 Business Statistics: A Decision-Making Approach 7 th Edition Chapter.
Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap 8-1 Business Statistics: A Decision-Making Approach 6 th Edition Chapter.
Copyright © 2010 Pearson Education, Inc. Publishing as Prentice Hall Statistics for Business and Economics 7 th Edition Chapter 9 Hypothesis Testing: Single.
Chapter 8 Introduction to Hypothesis Testing
Science and Engineering Practices
Copyright c 2001 The McGraw-Hill Companies, Inc.1 Chapter 7 Sampling, Significance Levels, and Hypothesis Testing Three scientific traditions critical.
Solid Science…Better Results Science Unlocking the Science of Talent Management Predictive Performance Analytics.
Assessing Critical Thinking Skills Dr. Barry Stein - Professor of Psychology, Director of Planning, Coordinator of TTU Critical Thinking Initiative Dr.
Chapter 10 Hypothesis Testing
Confidence Intervals and Hypothesis Testing - II
Claims about a Population Mean when σ is Known Objective: test a claim.
Business Statistics: A Decision-Making Approach, 6e © 2005 Prentice-Hall, Inc. Chap th Lesson Introduction to Hypothesis Testing.
Impact assessment framework
Stages of Commitment to Change: Leading Institutional Engagement Lorilee R. Sandmann, University of Georgia Jeri Childers, Virginia Tech National Outreach.
Week 8 Fundamentals of Hypothesis Testing: One-Sample Tests
Chapter 10 Hypothesis Testing
1 Introduction to Hypothesis Testing. 2 What is a Hypothesis? A hypothesis is a claim A hypothesis is a claim (assumption) about a population parameter:
Lecture 7 Introduction to Hypothesis Testing. Lecture Goals After completing this lecture, you should be able to: Formulate null and alternative hypotheses.
Section 9.2 Testing the Mean  9.2 / 1. Testing the Mean  When  is Known Let x be the appropriate random variable. Obtain a simple random sample (of.
Testing of Hypothesis Fundamentals of Hypothesis.
Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 8-1 Chapter 8 Fundamentals of Hypothesis Testing: One-Sample Tests Statistics.
Chap 8-1 A Course In Business Statistics, 4th © 2006 Prentice-Hall, Inc. A Course In Business Statistics 4 th Edition Chapter 8 Introduction to Hypothesis.
ISECON 2006 The Work System Model as a Tool for Understanding the Problem in an Introductory IS Project Doncho Petkov Eastern Connecticut State University.
HYPOTHESIS TESTING Null Hypothesis and Research Hypothesis ?
© 2006 by The McGraw-Hill Companies, Inc. All rights reserved. 1 Chapter 7 Sampling, Significance Levels, and Hypothesis Testing Three scientific traditions.
Hypothesis Testing Errors. Hypothesis Testing Suppose we believe the average systolic blood pressure of healthy adults is normally distributed with mean.
HYPOTHESIS TESTING Null Hypothesis and Research Hypothesis ?
Psych 230 Psychological Measurement and Statistics Pedro Wolf October 21, 2009.
Advancing Innovation in Measuring Patient Advocacy Outcomes.
1 Lecture 5: Section B Class Web page URL: Data used in some examples can be found in:
New FOCUS or OBSERVATION Critical Thinking Cyclic Model: QUESTION or HYPOTHESIS CONTENT ANYALYSIS and DELIBERATION scrutinize data using most rigorous.
Copyright © 2013 Pearson Education, Inc. Publishing as Prentice Hall Statistics for Business and Economics 8 th Edition Chapter 9 Hypothesis Testing: Single.
Research Proposal Writing Resource Person : Furqan-ul-haq Siddiqui Lecture on; Wednesday, May 13, 2015 Quetta Campus.
© PeopleAdvantage 2013 All Rights Reserved We will Show You How to Easily Conduct Effective Performance Appraisals LCSA Conference 2013.
Evidence Synthesis/Systematic Reviews of Eyewitness Accuracy
Chapter 7 Hypothesis Testing with One Sample.
Dr.MUSTAQUE AHMED MBBS,MD(COMMUNITY MEDICINE), FELLOWSHIP IN HIV/AIDS
Chapter 9 Hypothesis Testing
Introduction to Hypothesis Testing
Third International Seville Conference on Future-Oriented Technology Analysis (FTA): Impacts and implications for policy and decision-making 16th- 17th.
Presentation transcript:

Measuring Deficiencies in Nonprofit Management Lawrence C. Hunt, Organisational Scientist, Faculty of Business, Education, Law and Arts, University of Southern Queensland, Australia Mehryar Nooriafshar, Senior Lecturer, Faculty of Business, Education, Law and Arts, University of Southern Queensland, Australia Chandrasekhar Krishnamurti, Professor, Faculty of Business, Education, Law and Arts, University of Southern Queensland, Australia The Annual International Conference on Cognitive - Social, and Behavioural Sciences icCSBs 2015 January

Introduction The Problem: The boards of nonprofit organisations need a simple, practical technique that will measure their performance. Traditional, analytical approaches to solve this complex, multi- dimensional problem have failed to find a solution that has broad acceptance. The Approach: Focus on individual competencies, select management deficiency as the dimension of management performance to measure and adopt a heuristic methodology. The Objective: Identify factors associated with nonprofit management performance and build a heuristic model to measure individual management deficiency in nonprofit boards. icCSBs 2015 January

Methodology Build a model framework to identify factors associated with management performance. Develop techniques to quantify the factors. Adopt the heuristic methodology known as simulated annealing to: Build an initial form of the heuristic model to obtain an initial solution. Refine the model to obtain new solutions. Plot the solution path mapped out by each new solution. Continue until an optimal state is reached. Validate the solution produced by the model by establishing that there is an alignment of the model results with an assessment of individual management deficiency obtained by an individual performance ratings method. icCSBs 2015 January

Results The heuristic model produced a detailed assessment of management deficiency across the factors for each board member. The results produced by the model for a large sample enabled the relationships between each factor and management performance to be analysed. Factors Board Members’ Deficiency RatiosAverage Age Resistance to Change Commitment Skills Experience Knowledge Individual Deficiency icCSBs 2015 January

Results Validating the Model’s Results Random Sample: 50 NPO board members Average management deficiency ratios: Heuristic model: 0.337Performance rating method: T-test for significance of the difference between two means: Null hypothesis: There is no significant difference between the two means Critical region: t Computed value of t: t = Conclusion: Do not reject the null hypothesis This statistical analysis established that the results are aligned which effectively validated the results produced by the model icCSBs 2015 January

Results Primary Factor Average Deficiency* Average Board Deficiency Age Resistance To ChangeCommitmentSkillsExperienceKnowledge 27%39%58%52%37%42%50% Summary of Results: Primary Factor Average Deficiency * Average management deficiency results for a random sample of 57 NPO board members icCSBs 2015 January

Implications for Policy/Practice Future research into NPO board performance should focus on individual board members’ competencies and personal attributes. The methodology adopted in this study: Provides a foundation for the application of heuristic modelling to further research in this and related fields. Could be applied to solve the long standing problem of measuring nonprofit organisation performance. The development of an online application of the model will provide NPO boards with a performance measurement technique that is easy to use and produces immediate, practical results. icCSBs 2015 January

Conclusions The heuristic model below does produce an acceptable, approximate measurement of individual management deficiency, D, for an NPO board member: where a = skills factorb = experience factor c = knowledge factord = commitment factor e = resistance to change factor f = age factor icCSBs 2015 January

Conclusions The analysis of the detailed results produced by the model for a random sample of 57 NPO board members led to the following conclusions: The main competencies an NPO board member should possess are management skills, management experience, relevant knowledge and commitment. There is a positive relationship between age and management performance. icCSBs 2015 January

Conclusions For volunteer-only NPOs, sound management practices and long term planning are not related to management performance. In general, the experience gained from years of serving on the board, combined with the accumulated knowledge of the organisation’s norms and management processes, forms the means by which the organisation is managed. icCSBs 2015 January

Identify and Measure Management Deficiency in Nonprofit Organisations Lawrence C. Hunt, Organisational Scientist, University of Southern Queensland. Mehryar Nooriafshar, Senior Lecturer, University of Southern Queensland. Chandrasekhar Krishnamurti, Professor, University of Southern Queensland. The Annual International Conference on Cognitive - Social, and Behavioural Sciences icCSBs 2015 January