Just fresh out of CHI 2015 this week, a very interesting article on transferring HCI research into commercial product. “From User-Centered to Adoption-Centered Design: A Case Study of an HCI Research Innovation Becoming a Product” by Chilana, P., Ko, A.J. & Wobbrock, J.O.,  presents a “case study of how an HCI research innovation goes through the process of transitioning from a university project to a revenue-generating startup financed by venture capital.”


Commercialization; productization; dissemination; research impact; technology transfer; adoption-centered design.

ACM Classification Keywords

H.5.2. Information interfaces and presentation (e.g., HCI): User Interfaces—evaluation / methodology.

Structure and content

The paper begins with introducing the “the motivations for adopting different HCI methods at different stages during the evolution of the research, product, and startup business and the tradeoffs made between user-centered design” and what they have coined as “adoption-centered design”. It contextualises the case study within the borders of technology transfer in SE, innovation in the marketplace, and generalisability of HCI research evaluation.

After that, the authors provide two blocks of different knowledge, first one focused on HCI research to come up with a prototype, and the second one, focused on market innovation by transitioning from the research outcome to a commercial product.

After the describing the motivation for innovation and product, authors describe the HCI methods applied in the development and evaluation of a research prototype. First, a formative evaluation to inform interaction design, in which they have explored the design space of the concept and used a lo-fi paper based user study. Then, system feasibility technical evaluation using a mTurk-based crowdsourced user inquiry with simulated data. Finally, an ecological validity evaluation through a longitudinal field study, by getting potential adopters and deploying the prototype in the wild.

This process lead to a validated design and HCI research outcome, however, authors claim that had mainly demonstrated end user value. Not enough evidence of success for financing, or other business reasons like paying customers.

The second block depicts an incursion of the research outcome through the commercial scope of innovation. Business models, marketing, productisation, stakeholders, value proposition, market entry barriers and B2B adoption.

The questions the authors highlight along the paper:

  • Should we expect that good HCI science outcomes be transferable to users or costumers and would this be in the scope of HCI?
  • Should “potential for adoption” be adopted as criteria for research systems evaluation?
  • Is the traditional focus on generalisability only from end users restraining HCI tech transfer?
  • How to augment research systems evaluation with stakeholders perspectives?
  • Does it make sense to focus research on adoption given the lag of adoption of innovations?
  • Should “success” for this criteria focus on knowledge about its adoption barriers?
  • Could these perspectives increase the chances of product adoption and are they valid/adequate for delivering high quality and innovative research?

In the discussion authors reflect, on the one hand, on how “user-centered research innovation can be the invaluable foundation of a B2B software company”, drawing on how HCI evaluations inform business milestones. On the other hand, on how “user-centered focus typical of HCI research also occluded B2B adoption issues by not revealing important insights about the real-world customer support ecosystem and stakeholder dependencies.” making them depart into “adoption-centered design, uncovering knowledge specific to our business and product to fuel customer acquisition and inform product priorities.”

Also, authors provide arguments on the need to investigate Adoption-Centered in, its concerns for incorporating in HCI research, and suggest possible methods to achieve it. The also expose the benefits of such ordeal, suggesting that “more explicit adoption-centered approach to research might increase the chances that an investor, entrepreneur, or prospective employee would see business opportunities in HCI research. Combined with other systemic changes, such as more ex- tensive and rapid publicity of research innovations for the public and greater awareness of university intellectual property policy, an adoption-centered focus in HCI research might lead to a discipline of HCI technology transfer”.

Authors conclude by exposing the limitations of their study to ”one technology, one business, one university project and one perspective.” and by calling for further informing efforts that help ”transform HCI technology research from a source of ideas to a source of commercially disseminated solutions that create widespread value”.

Reference selection:

.Previous from authors:

[3] Chilana, P.K., Ko, A.J., Wobbrock, J.O. & Grossman, T. 2013. A multi-site field study of crowdsourced contextual help: usage and perspectives of end users and software teams. ACM CHI, 217–226.

[4] Chilana, P., Ko, A.J. & Wobbrock, J.O. 2012. Lemon- Aid: selection-based crowdsourced contextual help for web applications. ACM CHI, 1549–1558.

.Innovation and tech transfer:

[9] Henderson, A. 2005. The innovation pipeline: design collaborations between research and development. interac- tions, 12, 1, 24–29.

[11] Isaacs, E.A., Tang, J.C., Foley, J., Johnson, J., Ku- chinsky, A., Scholtz, J. & Bennett, J. 1996. Technology transfer: so much research, so few good products. ACM CHI Companion, 155–156.

[13] Kolko, J. 2014. Running an entrepreneurial pilot to identify value. interactions, 21, 4, 22–23.

[15] Larsson, M., Wall, A., Norström, C. & Crnkovic, I. 2006. Technology transfer: why some succeed and some don’t. Software Tech Transfer in Soft. Engr., 23–28.

[19] Pfleeger, S.L. 1999. Understanding and improving technology transfer in software engineering. J. of Systems and Software, 47, 2, 111–124.

[21] Rogers, E.M. 2010. Diffusion of innovations. Simon and Schuster.

[26] Winkler, D., Mordinyi, R. & Biffl, S. 2013. Research Prototypes versus Products: Lessons Learned from Software Development Processes in Research Projects. Systems, Soft- ware and Services Process Improvement. Springer, 48–59.


[16] Lee, A.S. & Baskerville, R.L. 2003. Generalizing generalizability in information systems research. Information systems research, 14, 3, 221–243.


One of the aspects I’m working on my dissertation covers the categories or roles in which music consumers can be classified. The goal here is to come up with a scientific sustained categorization/profiling of music users.

I’ve been looking for articles which are able to help me in this task and found some for which I’ll reviewing their main points here.

“Live and prerecorded popular music consumption” – Montoro and Cuadrado analyzed the profile of the popular music consumer, considering both live and prerecorded popular music, having profiled the average and frequent music consumer. Furthermore, they have tested hypotheses regarding the impact of the internet and file sharing on popular music consumption and the potential substitution and social motives for attendance of live show. Links between both markets were taken into consideration, and direct causal links were observed.

Gender, age and the impact of active practice and cultural participation were variables which have shown similarities between both profiles. The distinctive determinants of consumption were time constraints for live attendance for frequent consumers, and available income for both profiles.

The demand for popular music of some frequent consumers is more of a demand for information, while for the rest, other aspects like the social motivation, seem to have a more important role in it. This shows differences between profiles regarding to the potential substitution effect between live and prerecorded music.

Frequent consumers show a common disposition to music, either live or prerecorded, being catered for by both markets. This supports the “substitutability relationship between live and prerecorded music for frequent consumers”. On the contrary, average consumers are moved either to one market or the other, in an heterogeneous fashion; “once we account for direct links between both markets and for all the covariates, the average consumer is either a consumer of live or prerecorded music.”

A causal link between both markets was observed, with prerecorded music consumption increasing the probability of live concerts attendance, with stronger incidence on frequent users. Live concerts attendance showed no significant affectance on prerecorded music consumption.

The exposition to file-sharing networks showed an increase of live attendance for average users, rather than for frequent users. A negative impact was observed on the prerecorded music market by the use of the internet and file-sharing, although weaker for the frequent consumer. For the latter case, the origin of the prerecorded music was considered, either by legal acquisition, copy or internet download was considered.

Several conclusions can be taken regarding the evolution of the music business. Despite that, in the past, the prerecorded sector has subsidized the live sector, things have evolved in the opposite way. Nowadays, live shows support prerecord music sales, which is consistent with the rise of prices in live shows, with artists giving away recorded music in concerts and through the internet. This also explains and supports and the positioning and market strategies that labels are adopting with the all-inclusive contracts that cover not only prerecorded music sales, but also management, concert, merchandise and endorsement revenues.

Interestingly, the authors claim that, the fact that different agents in the music business sustain different activities, such as labels and concert promoters, leads to the under provisioning of these activities like promotion; otherwise, the internalization of all the generated effects in one entity would lead to optimal outcomes.

Within the efforts of my research activity, I’ve been introduced to this crowdsourcing platform  for sound-designers called AudioDraft. This platform implements the crowdsourcing model in a very lean and straightforward way. For the ones who aren’t familiar with this, this platform brings brands and sound-designers together, through contests to which the crowd applies with sound-design works, from which a final winner is selected and remunerated.

Following some related links, I came to find out that it’s mentor, Tommi Koskinen, takes part in a very interesting band from Helsinki, self assigned as post-indie electronic, with visible nordic influences, that reminded me The Knife, among others.


Apart from this, the owner of the beautiful vocals, Hanna Toivonen is also a music tech entrepreneur, CEO of a company called Mukava Music. This company released a mobile app called clerkd, but it seems that, after peeking at the social media around it, they are aiming for something bigger. It is not very explicit though. I wonder what it is…

So, my first post on the blog regards trademark registration.. Somehow, I would say that would be the least expected of the main axes to start the blog with.

Trademark registration is completed here, at the INPI website, where you can search for already existent trademarks and register your own.

Getting to know the financial costs of each type of registration isn’t that obvious! Still on the lookout, though.