Jan Ljungberg, Professor Informatics Göteborg University Anita Mirjamsdotter ,

1. Mechanism design for total quality management: Using the bootstrap algorithm for changing the control gamePetterØgland Jan Ljungberg, Professor Informatics Göteborg University Anita Mirjamsdotter, Professor Informatics, Linneus University

2. Contributions • The objective is to contribute to successful TQM implementation in complex environments (both technical and social complexity). • The thesis addresses Total Quality Management (TQM) as a methodology for improving software development processes. It points at difficulties to implement TQM and suggests building on a design theory, the Bootstrap Algorithm (BA), to overcome theses difficulties. The research then sets out to explore the stability and robustness of the BA approach including its impact for successful TQM implementation and proposes a set of hypothesis, which is then operationalized into research questions. The lenses used for investigating the appropriateness of the BA algorithm for successful TQM implementation are game theories and systems theory. • Large empirical material with interesting examples • Rich insights • Original and creative use of theories on a practical problem • Application of mathematical models on organizational/IS problems

3. Aim & questions • Research hypothesis (p. 24) • The bootstrap algorithm is an optimal mechanism design for implementing TQM? • RH1: BA can be implemented in a state of statistical control • RH2: The response to the BA treatment is performance improvement measurable by TQM assessments • RH3: BA is optimal for implementing TQM in complex environments • Overall aim: • Improve practical use of BA as a TQM implementation method in environments of technical complexity and social distrust

4. Research questions • RQ1.1: How can one use the “what gets measured gets done” principle for explaining success and failure of quality management initiatives? • RQ 1.2: How can one explain the success and failure of quality management initiatives on a systemic level? • RQ 2.1: How can one use EGT (evolutionary game theory) to understand TQM information infrastructure dynamics? • RQ 2.2: How can one use CST to understand TQM information infrastructure dynamics? • RQ 3.1: How should one design the details of BA to optimise the interaction between TQM designer and management? • RQ 3.2: How should one design the details of BA to optimise the interaction between TQM designer and management?

5. What is quality?

6. Positioning • TQM fails in 80 % of the cases • Why TQM? • QMS, TQM, SPI • TQM vs Six Sigma, BPR, ISO and other standardization efforts) • Change and change management in general • (Emergent/planned, radical/incremental)

7. Where do you stand? • Do you take a Management perspective? • A workforce perspective? • A TQM designer perspective? • Who’s mission is TQM?

8. Agency? • Who decides to start a QMP • Who is the TQM designer acting on behalf of? • TQM designer in between workforce and management? • TQM consultant have to convince management s(p. 39)

9. Theory • How did you chose theory? • What is the role of theory? • Are there theories you chose not to use?

10. Ontology • “The progress of science does not consist of getting closer to the truth about reality but in improving our models of reality” (p. 30) • A mathematical view on the world

11. Game theory • Mechanism design vs. rules • Optimal mechanism design • TQM as infrastructure • TQM as game • Infrastructure as game • Bootstrap algorithm

12. Other theories and concepts • Infrastructure • Actor Network Theory • Critical theory, emancipation • Systems theory • Culture • Organizational hypocrisy

13. Method • Canonical action research (retrospective) • Why? • What’s in a RCA? (p. 70, 71 and 72) • Longitudinal case study? • How did theory inform the design? When?

14. Aim & questions • Research hypothesis (p. 24) • The bootstrap algorithm is an optimal mechanism design for implementing TQM? • RH1: BA can be implemented in a state of statistical control • RH2: The response to the BA treatment is performance improvement measurable by TQM assessments • RH3: BA is optimal for implementing TQM in complex environments • Overall aim: • Improve practical use of BA as a TQM implementation method in environments of technical complexity and social distrust

15. Research questions • RQ1.1: How can one use the “what gets measured gets done” principle for explaining success and failure of quality management initiatives? • RQ 1.2: How can one explain the success and failure of quality management initiatives on a systemic level? • RQ 2.1: How can one use EGT (evolutionary game theory) to understand TQM information infrastructure dynamics? • RQ 2.2: How can one use CST to understand TQM information infrastructure dynamics? • RQ 3.1: How should one design the details of BA to optimise the interaction between TQM designer and management? • RQ 3.2: How should one design the details of BA to optimise the interaction between TQM designer and management?

16. General questions • What’s the main learning experience? • What would you do differently? • How do you view QM in relation to open source, open innovation and open data? • What will you do now?