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Terry, Your memory is faulty. On several occasions, I have asked you to demonstrate your quantitative, mathematical methods. You claim to posses mathematical, predictive tools. Demonstrating them requires you to use mathematics. On December 2, I requested a demonstration of these mathematical tools two times. You’ll find both requests in the PhD-Design archives. Klaus Krippendorff is right: “You are playing rhetorical games to hide your inability to substantiate your claims.” Your paper (Love and Cooper 2008) demonstrates this to be so. Your paper does not use mathematical modelling to make predictions. It uses a qualitative diagram to describe the past. This is not an example of precise, workable quantitative modelling methods for design that accounts for complex dynamic systems with multiple loops of action and behaviour. Neither does it show designers how to use your methods to intervene or how to reliably predict the outcomes of design interventions. This paper doesn’t even meet the internal claims of the paper itself. You claim to apply and extend Beer’s Viable Systems Model, Ashby’s Laws of Requisite Variety, Checkland’s Soft Systems, Critical Systems Analysis, System Dynamics, and Causal Loop Diagrams. There is no evidence that you apply and extend Beer, Ashby, Checkland, or the other methods. You use a causal loop diagram, but you do not show how you apply or extend causal loop diagrams. The model represents two dozen different groups of actors, institutions, processes, and facts. While the model claims to link these different kinds of entities in causal relationships, the paper does not provide enough data to show that the model represents the relationships accurately. What little data you provide is incomplete or problematic. At several points, you cherry-pick data to support the conclusions you wish to reach. A clear example occurs in your chart on RPI bias. This chart does not compare factors of a comparable nature. It is meaningless to compare the cost of PhD supervision against the cost of presenting international conference papers. Explaining why is easy. Conference costs are the same for a professor as for a lecturer More significant, many universities support accepted international conference papers, and in some nations, grant funding specifically supports dissemination — including conferences. Presenters do not draw down their research funds for supported papers. Whether they must use their own funds or not, professors do not have greater access to paper selection. Conference committees generally accept papers through double-blind review without respect to academic rank. If costs are a crucial disincentive, however, you neglect the most important fact. It costs nothing to publish a journal article rather than to present a conference paper. Every incentive scheme known to me gives greater weight and credit to peer-reviewed journal articles than to conference papers. This paper does raise some interesting points. Nevertheless, it is poorly developed. There is not enough evidence to substantiate the claims this paper makes. You don’t show how you built the model. Inaccuracies throughout the paper cause readers to wonder about the accuracy of the model. With so little substantive evidence, there is no way to know. Where you do attempt to substantiate your claims with references to evidence, careless and imprecise citations make it meaningless to check. For example, you claim that Deming (1986) supports your view on an issue that doesn’t seem to appear in his book. If Deming does discuss the topic you attribute to him, there is no way to read more than 500 pages of dense text to find the single paragraph or sentence that allegedly supports your views. It is your responsibility to show exactly where Deming writes on this issue. You make careless claims throughout the paper without providing evidence. List members can review it for themselves to judge the value of your claims. The paper is available here: http://www.love.com.au/docs/2008/motivational-information-systems.pdf Lianne Simonse’s (2014) article on the closely related topic of modelling business models offers a useful comparison. Simonse does not claim to be comprehensive or mathematically precise. Instead, she shows workable models, acknowledging their deficiencies and describing their virtues. She shows the modelling process in enough detail for readers to learn something about how these models work and how to apply them in their own work. She provides careful and precise references to the supporting literature, with useful information on where to look for more information. Since some of these sources predate your article, you could have done the same. Simonse’s article is notable for style and structure as much as for content. Simonse does not make outlandish and grandiose claims. She provides substantive evidence for the claims that she makes. She demonstrates the utility and value of the models she describes. And she draws all these issues together in a coherent, well reasoned, self-consistent discussion. Your second ANZSYS paper (Love 2002) seems no better than the first. As it shows no quantitative, predictive modelling, I won’t discuss it further. If you really did have workable, mathematically precise quantitative modelling methods for design that account for complex dynamic systems with multiple loops of action and behaviour, you would publish them. You are eager to publish. You fill the list with posts. You publish a blog. You maintain a web site with dozens of conference papers like the one you gave us. You even have your own publishing house. What you don’t do is to publish your research in any forum you do not control. You have never published the workable, mathematically precise quantitative modelling methods you claim to use. You have not demonstrated these methods in enough detail for anyone else to use them, not in your own blog, not on your own web site, not in your own books. You criticise the rest of us because we lack precise, predictable quantitative methods for design. We do not have such methods, but your critique is specious: you have no such methods either. There is no way that designers can reliably predict the outcomes of design interventions. This is why designers use multiple methods for research and practice, and this is why we iterate, test, trial, and iterate again. Repeated cycles of prototyping and iteration allow us to test artefacts, processes, services, and systems — or their components — to see if our interventions actually meet the needs for which we design them. That’s how we learn from the actual context of the design situations we meet in the empirical world. Making design work for people in the real world is the ultimate test. The list would benefit if you spent less time deflecting otherwise productive conversations with rhetoric, especially on a topic where you present no evidence. If you can demonstrate precise quantitative methods for predicting the outcomes of human intervention in dynamic systems, do it. Show the mathematics. Publish your results. We’d all like to read them. There will be equal interest in engineering, neuroscience, cognitive science, applied mathematics, systems science, cliometrics, cybernetics, complexity theory, systems dynamics, and another dozen fields where people struggle to make modest advances and incremental gains. If you could do everything that you claim to do, you would be a major contributor to our field. But major contributors publish their work. You do not. If you can do what you claim to do and teach what you claim you can teach, you should be able to publish it. Everything else is a rhetorical game about imagined virtues and imaginary methods. Ken Ken Friedman, PhD, DSc (hc), FDRS | Editor-in-Chief | 设计 She Ji. The Journal of Design, Economics, and Innovation | Published by Elsevier in Cooperation with Tongji University Press | Launching in 2015 Chair Professor of Design Innovation Studies | College of Design and Innovation | Tongji University | Shanghai, China ||| University Distinguished Professor | Centre for Design Innovation | Swinburne University of Technology | Melbourne, Australia Email [log in to unmask] | Academia http://swinburne.academia.edu/KenFriedman | D&I http://tjdi.tongji.edu.cn — References Deming, W. Edwards. 1986. Out of the Crisis. Quality, Productivity and Competitive Position. Cambridge, England: Cambridge University Press. Love, Terence. 2002. “Complexity in Design Management: Layered System Dynamics Graphs.” ANZSYS’02. ‘Management Approaches to Complex Systems.’ Mooloolaba, Queensland: ANZSYS. Love, Terence, & Cooper, Trudi. 2008. Motivational Information Systems: Case study of a University Research Productivity Index and 6th Extension to Ashby’s Law. ANZSYS'08: 14th International Conference. Perth, Western Australia: ANZSYS. Simonse, Lianne. 2014. “Modelling Business Models.” Design Issues, Vol. XXX, No. 4, Autumn, pp. 67-82. -- ----------------------------------------------------------------- PhD-Design mailing list <[log in to unmask]> Discussion of PhD studies and related research in Design Subscribe or Unsubscribe at https://www.jiscmail.ac.uk/phd-design -----------------------------------------------------------------