All posts by nienkeliebe


A healthy body and mind is probably the most common answer, when asked what we wish for in our future. Getting seriously ill is of course something we hope to never become, however when faced with this situation getting diagnosed and treated appropriately seems rather logical. But, what if you’ve seen countless medical experts and no one seems to be able to help you? Introducing; CrowdMed.


The creators of CrowdMed understand that, due to an endless amount of different diseases and disorders, it is highly unlikely for any doctor to know every possible condition associated with a specific set of symptoms. To overcome this problem, they use patented crowdsourcing technologies and an online platform that aggregates collective intelligence and facilitates collaboration among medical experts all over the world. The combination of the crowd and advanced analytics helps solve these cases within just days! By using the wisdom of (and collaboration between medical) practitioners and providing personal reports, CrowdMed differs from other platforms such as PatientsLikeMe, HealthTap and iTriage.


So how does it work?

When signing up as a case solver you are officially named a “Medical Detective”. Medical Detectives do not need to be licensed physicians to participate, however CrowdMed does believe in evidence and science-based diagnoses and thus strongly prefers objective medical evidence. In order to actually be eligible for any monetary rewards you need a certain degree of “DetectiveRating”, which is based on a performance and credential-based reputation system. However, you can participate in diagnosing a patient without any form of relevant education. Even I, Nienke with one year of biology experience in high school could help you with your mysterious symptoms.

Patients are asked to fill in an extensive questionnaire when starting a new case. In addition, they need to upload all medical information, all of which can be done anonymously. The patient then decides how long the case will be online and how they want to reward the Medical Detectives, who helped solve the case. This is a based on a combination of points (which increases DetectiveRatings) and monetary compensations.

CrowdMed uses a prediction market algorithm to assign probabilities to each diagnostic suggestion based upon Medical Detectives’ previous performance and behavior. These suggestions are bundled in a report and provided to the patient after the case is closed. The report includes the top diagnostic and solution suggestions, solution details and patient conversations. The patient is advised to these with the doctor.


Joint Profitability?

When uploading a case patients need to pay a monthly subscription of $149 – $749 depending on the specific DetectiveRating degree of the Detectives they would like to work on their case. These amounts seem gigantic. However in the United States, where not everybody is insured, this could be only a fraction of the costs they otherwise would have paid when consulting with doctors on their own. After the case is closed, the biggest chunk is divided amongst participating Detectives and 10% stays with CrowdMed as a commission fee.  Because of the unique nature of CrowdMed (bringing numerous ‘medical’ practitioners together), it is unfeasible for patients to replicate the service without this mediating platform.

Some drawbacks, however…

Firstly, Medical Detectives do not need any medical background to participate and thus the reliability and quality of diagnoses may be questionable. Moreover, by using a prediction market model, diagnoses are based on non-transparent algorithms and thus it is difficult to assess why certain suggestions rank higher than others.

Secondly, when not satisfied with the outcome, patients do not get their money back. In my eyes this is unethical when working with desperate people, as CrowdMed’s only certainty is the fact that they will cash big sums of money regardless of the outcome. Thus, there is no incentive to ensure for high quality services.

Lastly, diagnoses made by the Medical Detectives do not guarantee for correctness nor do they guarantee for any therapy. This all depends on the willingness of the patient’s practitioner. So spending hundreds of dollars on uncertified/self-proclaimed physicians may get you nowhere in the end. However, possible complaints about quality or applicability of the reports are discouraged by an extensive list of legal compliances, member conducts, warranty disclaimers, limitations of liability and a medical service disclaimer. I suddenly feel symptoms of suspiciousness…



CrowdMed (2017, March 9). Frequently Asked Questions. Retrieved from



A Design For Life:

In recent years multiple crowdsourcing platforms regarding logo designs have emerged. An infinite list from 48HoursLogo, Logomyway, DesignCrowd to 99designs, all guaranteeing professional logo designs for business use. But, what about designs on your body? Yes you heard me right: a crowdsourcing platform for tattoo ideas.


I have to be honest here. I do not have tattoos at the moment, nor am I planning on getting one in the future. Having something put on your body today and still being happy with it fifty years later seems impossible to me. Either way, I can imagine when planning on getting a tattoo, having a unique design is of great importance.  However, when going to a tattoo shop most likely you are limited to the imagination and skills of one tattoo designer and therefore the actual result may not always be how you envisioned it in the first place…


The owners of understand this problem and thus created a platform on which you are able to connect with a community of tattoo designers, drawing designs based on your wishes and budget. With over twenty thousand designers and twenty-two designs per contest on average, guarantees for satisfaction or you get your money back. is unique in its sort. Several websites on tattoo inspiration exist (,, however none of these platforms offer competition possibilities.

So How Does it Work?

The process is simple and straight forward. When creating a contest for your next tattoo design, you are asked to write a short summary on your wishes and pick your price, which you pay the platform upfront. Then just wait; during the next ten to sixteen days designers are working on their designs and submissions will pop up. Throughout the competition you are then able to rate submissions, give feedback and answer questions if needed. After choosing the winning design, you are provided with the design on stencil, which you can take with you to your local tattoo shop. The quality of the final product once on your body, therefore depends on the performing artist of course.


Besides the contest holder no one is able to see the designs of other competitors throughout the contest. Only after the contest has ended, submissions are made public for everyone to see. This blind setting may be applied to prevent free-riding amongst designers or highly similar submissions. However, Bockstedt et al. (2016) researched contestant’s behavior in unblind innovations contests and concluded that an unblind setting does not prevent contestant’s from submitting early in the contest due to free-riding scares, but instead provides the advantage of emerging information. These early birds are also more likely to be successful. Making submissions on open for everyone to see may have a positive impact on the overall quality.

Who’s to profit?

 Joint profitability is gained as all three participating parties profit from and on  Firstly, the winning designers are paid through an eighty-five percent share of contest prices, which vary from $20 up to $800 ( But, also the satisfaction of creating and being able to show of skills can be seen as profits for the designers. The remaining fifteen percent of the price money  stays with the platform owner. Although not directly monetary profiting from, indirect profits may also be assigned to the contest holder. By not having to search for the perfect tattoo design on different websites or tattoo shops, search costs are minimalized. In addition, one could imagine that due to the fact that the contest holder can give feedback and therefore optimize the final product, the possible costs of regret or even removing a disappointing tattoo are much lower.

Lastly, institutional arrangements are mentioned. As intellectual property is put up for sale on, the website provides an extensive user agreement list. This, in order to protect designers and prevent any claims on issues regarding copy rights, trademarks and publicity rights. This, to prevent designers from not wanting to post any content, as they may not trust their work being handled with care and is being protected.

So what about you? Would use this platform or stick to your local tattoo shop when contemplating on a new design?



Sources; (2017) Available at: Accessed on 04/03/2017

Bockstedt, J., Druehl, C., & Mishra, A. (2016). Heterogeneous submission behavior and its implications for success in innovation contests with public submissions. Production and Operations Management.



Why Recommendation Agents Should Let Us Participate

“I see you are looking at our infinite range of stuffed animals, may I help you find what you need?” They are the salespeople of the online retailers; recommendation agents (RA’s). By capturing our perceived preferences based on browsing patterns or interests, RA’s aim to understand our needs. Not an unnecessary luxury of any sort, as the complexity and amount of information we are confronted with often exceeds our limited information-processing capacities and thus the benefits of RA’s can turn into costs. (Dabholkar, 2006; West et al., 1999). If there would be a Maslow pyramid for online shopping needs, it would be the bottom layer; a basic need, indeed.

However, one recommendation agent does not fit all. Different websites use different types of RA’s and the extent to which we can interact with these systems is heavily influenced by the interface design and its dialogue initiation process. Ranging from extensive questionnaires to not even a “hello, I’m here”, the possibility to participate in a two-way dialogue depends on the online salesperson you have encountered. But does the quality and quantity of customers’ input really matter?

In their lab based experiment, using existing RA’s in a controlled setting, Dabholkar and Sheng (2011) show that greater consumer participation in using RA’s leads to more satisfaction, greater trust and higher purchase intentions with respect to the recommended products and the system itself. Existing research already elaborates on the effects of participation in decision making on satisfaction, trust and purchase intentions in the offline and online context (Driscoll, 1978; Chang et al., 2009; Yoon 2002). In addition, much research has been conducted in the RA field, but upon this point failed to combine these two topics.

A great strength in Dabholkar and Shengs’ research, is the fact that there is a significant importance in understanding these relationships in the RA field as they are of huge strategic importance to online marketers. Therefore this topic is highly relevant. Moreover, by adding the dimension of financial risk, the authors are able to also identify that higher product prices moderate the need of participation in the RA context. This gives marketers insight for which products their recommendation agents should have high/low levels of possible interaction and therefore are able to personalize their RA’s per product and possibly increase purchases.

But, there are also a few limitations that need to be taken into account. One could argue that the used sample is non-representative for the online shopping population, as it completely consisted of college students with an average age of 21.91. Although the authors highlight the fact that the largest share of the Internet population is aged 18-32, it is not unthinkable that a student’s perception of financial risk differs from a middle aged person with substantially more spending power. Besides, students perceptions of trust in the online shopping context may be not completely representative, as they grew up with the Internet.

Summarizing, Dabholkar and Sheng give great insights in the effects of consumer participation in RA’s on satisfaction, trust and even purchase intentions. However, generalizability at this point is questionable, so further research across different age groups needs to be conducted to validate these results. But for now; Does your customer base primarily consist of students? Then it is time to revaluate your online salespeople. Get them to communicate with us, we would love to talk!


Chang, C. C., Chen, H. Y., & Huang, I. C. (2009). The interplay between customer participation and difficulty of design examples in the online designing process and its effect on customer satisfaction: Mediational analyses. Cyber Psychology & Behaviour, 12(2), 147-154.
Dabholkar, P. A. (2006). Factors influencing consumer choice of a ‘rating web site’: An experimental investigation of an online interactive decision aid. Journal of Marketing Theory & Practice, 14(4), 259-273.
Dabholkar, P. A., & Sheng, X. (2011). Consumer participation in using online recommendation agents: effects on satisfaction, trust and purchase intentions. The Service Industries Journal, 32(9), 1433-1449.
Driscoll, J. W. (1978). Trust and participation in organizational decision making as predictors of satisfaction. Academy of Management Journal, 21(1), 44-56.
West, P. M., Ariely, D., Bellman, S., Bradlow, E., Huber, J., Johnson, E., . . . Schkade, D. (1999). Agents to the Rescue? Marketing Letters, 10(3), 285-300.
Yoon, S. J. (2002). The antecedents and consequences of trust in online-purchase decisions. Journal of Interactive Marketing, 16(2), 47-63.