Create and vote on your favorite furniture designs on

Imagine you are moving into your first apartment. At that moment, it is finally possible to furnish the apartment to your own preference. However, when you start orienting for furniture, you discover that there are no options to be found that resemble the image of how the new apartment should look preferably. Moreover, the furniture is often expensive as well. That is why decided to create a community in which its customers can vote for the designs they want to produce.

Business model is an online furniture retailer from England without warehouses and inventory. This allows the company to save costs. Instead of warehouses and inventory, they use crowdsourcing. The website allows members to submit designs. Whether the design will get produced, is determined by the number of votes it gets from members of the website. This is also a great opportunity to draw attention for designers who lack reputation (Goldsmith, 2010).

When a design is proved to be popular, makes it available for pre-order. The pieces are then shipped directly to the customer, which cuts costs (Graham, 2010). In the past years, has started opening showrooms that allow customers to view the products available on the website in real life.

Efficiency criteria benefits from joint profitability because designers get paid 5% royalties on successful designs and members benefit from being able to vote for their preferred pieces. Value is therefore co-created by involving customers actively in the process of deciding which pieces should be produced. A situation is created in which customers will not tend to switch to competitors because they have more options with and because they buy the exact pieces they want from, on its turn, benefits from knowing which pieces they will probably sell (Graham, 2010). did, however, get negatively affected after Britain voted to leave the EU in 2016. The feasibility of required allocations is therefore far from optimal at the moment. The Brexit was a huge setback to technology founders who are very dependent of foreign developers and engineers. Hiring these skilled employees will now be even tougher than before, since it was already hard to find expertise within the United Kingdom. Moreover, 35% of the employees that are located in London, are European. There is a huge uncertainty whether these employees will be allowed to stay in London (Olson, 2016). It could be decided any moment that Europeans need certain visas, which would affect the positions of the current employees and would make hiring skilled workers from outside the UK even harder. It could take two years for Britain to leave the EU, which means years of uncertainty where will not know regulations will impact their business (Meyers, 2016). The political institutional environment has created this situation, and people involved with are also socially impacted. Brent Hoberman, co-founder of, has stated that people feel rejection and that the atmosphere at the headquarters is very depressing (Olson, 2016).

The above illustrates that companies can be heavily impacted by its institutional environment, and that companies sometimes have little power to prevent such threats.

DogVacay -The perfect solution for a man’s best friend

Weekend getaways have becoming increasingly popular in recent years. Rightfully so, as it gives people a quick escape from their busy, and maybe even stressful, day-to-day life. Unfortunately, for some this is less easily planned than for others. Take for example dog owners. It is not as easy for them to book that last-minute deal they just saw online, as they have to arrange for a place to stay for their beloved canine. Possibly they could ask one of their family members or a good friend to look after their pet, or they could consider bringing their dog to the kennel. However, this may be an imposition on some people, or if friends are willing, they may not know how to properly look after your dog. Sure, a kennel usually employs professional dog sitters, but then you are stuck with a bill that is larger than the cost of your weekend getaway! Even when money is not an issue, some dog owners have come home to traumatized pets after their stay at a kennel.

This last incident is exactly what prompted Aaron Hirschhorn and Karine Nissim to open up their home to other people’s dogs. After putting up a listing on Yelp called Aaron’s Dog Boarding in 2011, the couple realized that there was indeed a large demand for their services and that good money could be earnt with their business. This is when Aaron and Karine decided to scale things up. They reinvented their business model from pet sitting themselves to operating a platform on which dog sitters and dog owners are brought together, and so DogVacay was born. DogVacay is thus a two-sided marketplace, which has enjoyed great network-effects over the past years. Currently, 40,000 dog sitters across the U.S. are registered on the platform, making DogVacay the leading online platform in its niche industry. 

DogVacay works as follows. Dog lovers can apply to become a sitter on the platform, however Aaron and Kate ensure their capability through a strict screening process. In order to become a DogVacay Host, applicant must pass interviews, video training, and a reference check. In turn, sitters can set their own rates, schedule, and preferred dog breed. In addition, they have access to 24/7 customer support. Dog owners on the other hand, can search for the perfect sitter simply by entering their zip code. They can select their DogVacay Host based on their profile, which includes a short biography, rating, reviews, number of repeat visits, and whether they own a dog themselves. Furthermore, every reservation is covered with premium pet insurance, which thus takes the legal aspect into consideration. DogVacay also encourages both parties to meet up beforehand to guarantee a perfect fit and a happy stay. The platform itself generates revenues by taking a 15% percentage cut from the transaction. With a revenue stream of $70mln in 2016, DogVacay is expecting to hit profitability this year. Currently rated 4.97 out of 5 stars, is there really any better alternative out there for a man’s best friend?


Drinking beer for science: Which brew is the best?

Who doesn’t want to taste a beer that has been chosen as best beer amongst a crowd of over 25,000 people from all across the USA? In 2012, Budweiser introduced Project 12. The American brewer challenged its twelve brewmasters to create a unique beer recipe. Only one could be the winner, resulting in the Budweiser Black Crown.

Project 12 is a typical crowdsourcing project. As the name describes, crowdsourcing is a type of outsourcing, utilizing a crowd of people instead of an external organization (Howe, 2006). Since the introduction of the concept in 2006, the technology industry was one of the early adopters. However, in the last couple of years, this industry has been overtaken by the fast-moving customer goods (FMCG) industry (Roth et al., 2015). The evolution of crowdsourcing usage per sector is depicted in Figure 1 (Roth et al, 2015).


Figure 1: Evolution of crowdsourcing usage

Crowd consultation

Companies can use different ways to exploit the crowd. The main purposes for crowdsourcing are problem solving, gathering ideas, collecting designs, and outsourcing tasks. With problem solving and ideation contests, the crowd comes up with the ideas and solutions. Decisions on the results are often done internally by companies. Budweiser used a variation on this crowdsourcing model. The brewer created the beers itself (the ‘’ideas’’ / ‘’solutions’’), and used the crowd as consultants (‘’decision makers’’). Hence, the company reversed the typical crowdsourcing model. In summer of 2012, the company traveled across the USA to get in contact with thousands of customers at local events, festivals, and other activities to gather opinions. As such, the participants acted as consultants for Budweiser.

Project 12

In 2012, Budweiser asked twelve of its brewmasters, located in the USA, to create a distinctive beer recipe worthy of the Budweiser name. The beer recipe had to be inspired by regional influences of their brewing location. Out of these twelve, six beers were chosen to join the Budweiser brewers on their tour across America. Consumers with many different backgrounds had the opportunity to taste the different beers and rate them on taste, flavor, freshness, and style before picking their favorites. A summer-long sampling program resulted in the biggest focus group in brand history, maybe even beer history, according to AB InBev, parent company of Budweiser (Brady, 2012). See the video below about Project 12.

There can be only one

Eventually, three brews were distributed in limited edition. One of them was the winner, called ‘Black Crown’. Each beer was named after the zipcode of the brewery location it was created. The  winning beer was introduced using TV ads and even a 30-second Super Bowl commercial. However, the question is whether this expensive marketing tools were really necessary, since Project 12 was already a marketing tool itself. Crowdsourcing projects namely have an advantage that the crowd becomes eager for the product to come out. Participants already become brand ambassadors through spreading the word during the project (IdeaConnection, 2014).

Whether these marketing expenses were really necessary or not, Project 12 turned out to be really successful. The success was so enormous that the brewer decided to launch a similar project the following year (IdeaConnection, 2014). Hence, Budweiser benefitted from their crowdsourcing strategy.

Nowadays, Budweiser is still the most important brand of Ab InBev (largest brewer worldwide), and is even the best selling beer in America (Statista, 2016). That’s why Budweiser is called ‘’The King of Beers’’.


Howe, J. (2006). The rise of crowdsourcing. Wired magazine14(6), 1-4.

Roth, Y., Pétavy, F., & Céré, J. (2015). The state of crowdsourcing in 2015. eYeka Analyst Report.

Brady, S. (2012), AB InBev Woos Beer-Drinkers With Crowdsourced, Locally Developed Bud Flavors, brandchannel [Accessed 17-02-2017 from:].

IdeaConnection (2014), Crowdsourcing a New Beer Bevarage with Budweiser [Accessed 17-02-2017 from:]

IdeaScale (2017), Crowdsourcing Ideation [Accessed 17-02-2017 from:].

Statista (2016), Sales of the leading domestic beer brands of the United States in 2016 [Accessed 17-02-2017 from:].


Advertising can be a profitable business and in the United States alone, advertising is a $200 billion industry. As consumers, we are all exposed to advertising on a daily base, either on the TV, via e-mail, social networks, or through other related online content. Yet advertising remains poorly understood by economists. This is mainly because offline data has been insufficient for business and academics to measure the true impact of advertising on consumer purchasing behavior (Lewis et al., 2014). In 2013, for the first time in the history of advertising in the United States, digital advertising surpassed TV broadcast advertising, which for a long period of time has been considered the best mass-marketing medium (IAB, 2014).

Because now a day people are more and more online and get more often exposed to online digital advertising, a lot of valuable data is generated which allows businesses and academics to reduce the information gap that is present in the advertising world.
In this study, Ghose & Todri-Adamopuolos (2016) go beyond the existing literature and with the use of individual-level data, research the effectiveness of online display advertising and the effects display advertising has on different consumer behaviors online. Studying the latter is a novelty compared to historical research of display advertising. In this case to understand consumers’ response to advertising, not just a probable exposure to it, often simple proxies were used like click-through-rates. Ghose & Todri-Adamopuolos (2016) surpass these relative simple methods and proxies and use an experimental framework that allows to compare the online behavior of two groups of users: those who view the display advertisements and those who do not view the display advertisements. What the data shows is that if consumers are just exposed to display advertisement this already significantly increases the interest of consumers to search for the displayed brand or product. Subsequently, the increased interest results in either active online searching for the product/brand or an increased likelihood to click on a related future display advertisement. Secondly, the longer a consumer looks at the advertisement the higher the probability a consumer goes directly to the website of the specific brand or product (36% bigger chance than average) instead of using search engines like google. Lastly, after seeing a display advertisement consumers are 7,1% more likely to buy the advertised product.

Practical implications for business

Ghose & Todri-Adamopuolos (2016) propose a model that demonstrates how advertisers can divide resources across the different types of display advertising. This model allows advertisers to use big data analytics in order to move advertising budget from less effective and cost efficient channels/media towards more effective advertising and increase the overall effectiveness and return on investment of the digital marketing strategy.  Furthermore, as the results signal that search advertising exposure only happens in a consumer’s funnel path after the consumer launches a search session that shows his or her interest for a brand/product, it is important for advertisers who would like to control the presence and the frequency of search advertising exposures that they examine what triggers consumers to initiate a search session before examining anything else. Lastly, it is important that potential consumers are targeted by businesses sooner in their shopping journey, as this could increase the effectiveness of the advertisements up to four times.


Ghose, A., & Todri, V. (2015). Towards a Digital Attribution Model: Measuring the Impact of Display Advertising on Online Consumer Behavior. (pp. 889-910) MIS Quarterly

Interactive Advertising Bureau (IAB). 2014. “IAB Internet Advertising Revenue Report: 2013 Full Year Results,” PricewaterhouseCoopers LLP.

Lewis, R., Rao, J. M., & Reiley, D. H. (2014). Measuring the effects of advertising: The digital frontier. In Economic Analysis of the Digital Economy (pp. 191-218). University of Chicago Press.

Research Framework, Strategies, And Applications Of Intelligent Agent Technologies (IATs) In Marketing

What is an agent?

Anything that perceives its environment through sensors and in return acts upon it(Russell and Norvig 1995).

What is an intelligent agent? An agent that displays machine learning abilities.

Does perhaps Amazon Alexa, Apple’s Siri, Google Assistant, Microsoft’s Cortana ring a bell?

In “Research framework, strategies, and applications of intelligent agent technologies (IATs) in marketing applied” the authors attempt to define how are these intelligent agent technologies used in the context of marketing and how can marketers understand and exploiting them. First step towards that direction was to try and establish a marketing centric definition. Hence, Intelligent Agent Technologies are according to authors:

Systems that operate in a complex dynamic environment and continuously perform marketing functions such as:

  • dynamically and continuously gathering any data that could influence marketing decisions
  • analyzing and learning from data to provide solutions/suggestions
  • implementing customer-focused strategies that create value (for customers and firms)

The second step was to classify all marketing applications of IATs in a way that would demonstrate relationships and differences among them. A useful and understandable tool for researchers and managers, the proposed marketing taxonomy is depicted below:



To answer all these research questions the authors reviewed the existing literature and then conducted 100 in depth interviews with managers form 50 randomly selected companies. Two independent researchers analyzed the interview data, that were then used to shape the taxonomy and the below framework.They also made some propositions that would help researchers and mainly managers to utilize IATs and ultimately drive company performance.


Overall, implementing the right IAT can assist the progress of numerous marketing functions permitting companies to achieve a sustainable competitive advantage. Both firms and customers can benefit from them. Companies are in a position to understand and put customers’ interest first (through collaborative filtering, personalization, recommendation systems) and in return gain customer loyalty and trust.On the other hand IATs offer consumers value, by providing them with convenience, better information, customized selection and less information overload (e.g price-comparison engines or agents that configure and customize their computer systems on the basis of their preferences).

Strengths and Weaknesses:

%ce%b4%ce%b9%ce%b1%cf%86%ce%ac%ce%bd%ce%b5%ce%b9%ce%b11Since there was no concrete research or a fully developed theory surrounding IATs in marketing and subsequently no certain phenomena or existing theoretical frameworks to test, the authors rightfully opted for the grounded theory approach.So in contrast to the traditional research method they tried to construct a theory by discerning which ideas and concepts are repeatedly used in the interview data. These patterns were then grouped into categories that formulated their theory and shaped both the taxonomy and the framework.


Although the authors reasonably based their analysis on grounded theory, whether they applied it correctly is another question. The fact that they reviewed the existing literature in order to formulate the interview questions somehow conflict with the grounded theory methodology. The goal of this approach is to discern natural patterns. However, the used questionnaires possibly inhibited this since they kind of predisposed the managers’ answers since the queries were literature related.

%ce%b4%ce%b9%ce%b1%cf%86%ce%ac%ce%bd%ce%b5%ce%b9%ce%b13Given further progress in recommender systems (or other means of reducing costs for the customer), a situation might arise in which a “ready-made” solution provided by the system delivers higher preference fit than a customer-designed product—which, on the other hand, delivers the advantage of enabling “I designed it myself” feelings.” (Franke, N., Schreier, M. and Kaiser, U, 2010). This poses a very serious question for companies. When it is preferable to let an agent customize, decide or recommend a product/website? How quickly and how frequently should the agents respond and adjust to user needs? Ultimately what is more beneficial for both parties, implementing agents or give consumers the freedom to tailor products and and websites to their needs. Perhaps, technological advancements and the machine learning capabilities of IATs could soon enable companies them to successfully distinct these two categories of consumers and accordingly present them the proper interface.



Franke, N., Schreier, M. and Kaiser, U. (2010). The “I Designed It Myself” Effect in Mass Customization. Management Science, 56(1), pp.125-140.

Kumar, V., Dixit, A., Javalgi, R. and Dass, M. (2015). Research framework, strategies, and applications of intelligent agent technologies (IATs) in marketing. Journal of the Academy of Marketing Science, 44(1), pp.24-45.

Russell, S. and Norvig, P. (1995). Artificial Intelligence: A Modern Approach. 1st ed. Prentice Hall, p.31.

Citizen science: Crowdsourcing Scientific Knowledge

Citizen Science






Nowadays you can pretty much crowdsource anything from statistical analysis (Kaggle) to Graphic Design (99Designs), whatever you want help with you can find it online. But science is probably not the first thing on peoples’ mind when they think of this phenomenon. Science has an image of being a restricted activity, that requires specific knowledge and skills. Scientists are smart people locked away in laboratories or universities. citizen-scienceWe believe science is our most reliable system of gaining new knowledge and should be reserved for special people who are trained for it. However, nothing is further from the truth according to citizen science (also called crowd science and/or amateur science). Citizen science projects can be very diverse and can serve both specific research questions and open-ended data collection (Lukyanenko, et al., 2016).


Citizen science has been met with some criticism, including issues with data quality and ethics.

Data Quality

Is citizen science reliable? crossed-fingersThis is, of course, a valid question and the corresponding answer could fill a blog post on its own. To give a short answer: yes, in most cases (Galloway et al., 2006). When scientists use citizen science in their research, they can take different actions to ensure data quality. For example, they could provide training/close supervision to the participants, of course keeping in mind the time/costs incurred with this.
Furthermore, scientists can cross-check for consistency with existing literature or with their own previous observations and last but not least the task that is asked to the public could be simplified to the point ‘little can go wrong’ (Riesch, et al., 2014). Actions that are appropriate to take of course depend on the characteristics of each research and ultimately need to be decided and justified by the researchers themselves.


An obvious problem in citizen science is the accreditation of research results. In some projects, the involvement of participants is high and requires a lot of time and/or effort making their contribution to the research quite substantial. Ownership of data should be clearly defined beforehand and considerations regarding accreditation should be handled in a fair manner and communicated explicitly before participation.


Citizen science of course also has significant benefits including increasing accessibility of science, changes in science literacy, providing a different perspective and the possibility to analyze larger datasets.


As mentioned before the term science and research can sound intimidating, especially for ‘outsiders’. Citizen science can help people ‘ease into’ the world of science in a manageable manner. It helps make research more inclusive (Lukyanenko, et al., 2016). This inclusiveness, in turn, can increase interest for science in general, change people’s views and can persuade more people to study and/or work in any field of science.

 Science Literacy

There is some debate about this but studies have shown that participating in citizen science can increase science literacy and familiarity with the scientific method (Cronje, Rohlinger, Crall & Newman, 2011).


Since most participants in citizen science lack academic scientific education, they can offer a new perspective on issues/research which can be useful to explore new options, help studies advance after problems have occurred and/or offer future research ideas (Lukyanenko, et al., 2016). By including a larger group of people, the group most likely also becomes more diverse and thus also more diverse in terms of knowledge (Raddick et al., 2013).

Larger datasets

By outsourcing some of the data analysis larger data sets can be included in studies. Of course computers also have the power to analyze large data sets, however, some tasks require capabilities that humans are more efficient in such as image and sound analysis (Fleming, 2001).

Examples of current applications of

citizen science

Bird research

Citizen science projects have made a serious contribution to scientific knowledge (Ceccaroni, 2016). For example, it has helped examine the distribution of bird populations (Cooper et al. 2007, Bonter and Harvey 2008, Bonter et al. 2009), the influence of environmental change on birds’ breeding behavior (Hames et al., 2002a) and the effect of acid rain on bird population (Hames et al. 2002b).

Scistarter is a website stimulating people to learn about, participate in and contribute to science. Their goal is to create a place in which there is an open communication between citizens and scientists. It is an online database of current citizen science projects and acts as a link between interested citizens and researchers in need of these citizens (“About Us”, 2017).


galaxy-zooGalaxy Zoo

This is possibly the most famous example of an online citizen science project. It is a crowdsourced astronomy project in which people can help classify galaxies. It launched on the 11th of July 2007 and collected more than 50 million during its first year. To date is has gone through 13 different ‘rounds’ each focusing on a different task/image set (“Story”, 2017). The data collected has been used in many studies and contributes greatly to a better understanding of the phenomenon (Raddick et al., 2013).


About Us. (2017). SciStarter. Retrieved 15 February 2017, from

Bonter DN, Harvey MG. 2008. Winter survey data reveal rangewide dedine in Evening Grosbeak populations.The Condor 110: 376–381. BioOne

Bonter DN, Zuckerberg B, Dickinson JL. 2009. Invasive birds in a novel landscape: Habitat associations and effects on established species. Ecography.doi:10.1111/j.1600-0587.2009.06017.x

Ceccaroni, L. (2016). Analyzing the role of citizen science in modern research (1st ed.). IGI Global.

Cooper CB, Dickinson J, Phillips TB, Bonney R. 2007. Citizen science as a tool for conservation in residential ecosystems. Ecology and Society 12: 11.

Cronje, R., Rohlinger, S., Crall, A., & Newman, G. (2011). Does Participation in Citizen Science Improve Scientific Literacy?. Applied Environmental Education & Communication, 10(3), 135-145. doi:10.1080/1533015x.2011.603611

Estelles Arolas, E., Gonzalez Ladron de Guerra, F., 2012. Towards an integrated crowdsourcing definition, Journal of Information Science 38 (2), 189-200.

Fleming, L., 2001. Recombinant uncertainty in technological search. Management Science 47 (1), 117–132

Galloway, A. W. E., Tudor, M. T. and Haegen, W. M. V. (2006), The Reliability of Citizen Science: A Case Study of Oregon White Oak Stand Surveys. Wildlife Society Bulletin, 34: 1425–1429. doi:10.2193/0091-7648(2006)34[1425:TROCSA]2.0.CO;2

Hames RS, Rosenberg K, Lowe JD, Barker S, Dhondt AA. 2002a. Effects of forest fragmentation on tanager and thrush species in eastern and western North America. Pages 81–91 in George L, Dobkins DS, eds. The Effects of Habitat Fragmentation on Birds in Western Landscapes: Contrasts with Paradigms from the Eastern United States, vol. 25. Cooper Ornithological Society.

Hames RS, Rosenberg K, Lowe JD, Barker S, Dhondt AA. 2002b. Adverse effects of acid rain on the distribution of the wood thrush Hylocichla mustelina in North America. Proceedings of the National Academy of Sciences 99: 11235–11240. CrossRefPubMed

Lukyanenko, R., Parsons, J. and Wiersma, Y. F. (2016), Emerging problems of data quality in citizen science. Conservation Biology, 30: 447–449. doi:10.1111/cobi.12706

Riesch, H. and Potter, C., (2014) Citizen science as seen by scientists: Methodological, epistemological and ethical dimensions, Public Understanding of Science 23 (1) : 107-120Jordan

Jordan Raddick; G. Bracey; P. L. Gay; C. J. Lintott; C. Cardamone; P. Murray; K. Schawinski; A.S. Szalay; J. Vandenberg (2013). “Galaxy Zoo: Motivations of Citizen Scientists”.

Jordan Raddick; G. Bracey; P. L. Gay; C. J. Lintott; C. Cardamone; P. Murray; K. Schawinski; A.S. Szalay; J. Vandenberg (2013). “Galaxy Zoo: Motivations of Citizen Scientists”.

Serrano, F. (2013). Green Paper on Citizen Science. Citizen Science for Europe: Towards a better society of empowered citizens and enhanced research.

Story. (2017). Retrieved 15 February 2017, from



Share a ride TOOGETHER

In times of sustainability, the increasing importance of mobility, and the environmental issues the use of vehicles is still the most important way to go to work. A big irritation to motorists are the traffic jams caused by the increasing use of the car. Moreover, the limited parking areas frustrates the motorist. Regardless of the distance to their final destination, the motorist’s first choice is still using their car. The use of the car and especially the traffic jams causes a lot of environmental issues. When we hate the traffic jams, are frustrated by the limited parking areas and we know using the car is harmful to the environment, why do we simply keep using such manners to go to work?

Toogether finds this gap in the market and offers a solution. Toogether is a platform that makes it very easy to get together and share a ride. How does it work? Instead of driving to work on your own, despite the remaining seats in the car, Toogether offers a possibility to travel together. This has consequences regarding the reducing of traffic jams, reduced limited parking areas and finally reduced emission of co2. Toogether provides an overview of where all of the colleagues are living (especially colleagues living nearby) and offers the possibility to make an appointment to drive together with the particular colleague. As user of the platform you have to create your own profile and Toogether provides matches based on the desired destination, the location, and the associated travel time. An additional benefit of this platform is cost sharing, since the users split the gasoline costs.

Toogether is an innovative startup which uses the concept of co-value creation. According to Prahalad & Ramaswamy (2004) co creation is a management initiative that brings different parties together in order to produce a mutually valued outcome. Furthermore, Lusch and Vargo (2006) defines co creation of value as a desired goal as it can assist firms in highlighting the customer’s or consumer’s point of view and in improving the front-end process of identifying customers’ needs and wants. Both definitions are in line with the concept of Toogether, which provides a mutually valued outcome to multiple parties and accomplish their needs. On the one hand motorists denounces the traffic jams and limiting parking areas’ which accomplish the motorist needs, and on the other hand solving the mobility problem ensures reducing environmental issues which create sustainable value to all of us (government, population and organizations).

When the users of the platform increases, there is more and more data available of each user. We can think about data regarding to travel routes and peaking hours. When all of these data could be analyzed the company could offer more specific recommendations and finally increases the customer satisfaction. More specifically, users create value for themselves and for the Toogether when they are commonly uses the platform. Like aforementioned, Toogether needs their users to accomplish such goals. This is in accordance with the theory towards co value creation which emphasized that no single firm can create anything of value without the engagement of individuals (Prahalad, C.K. & Ramaswamy, V. (2004).


Lusch, R. P., & Vargo, S. L. (2006). The service dominant logic of marketing: Dialog, debate and directions. Armonk, NY: M.I. Sharpe.

Prahalad, C. K., & Ramaswamy, V. (2004). The future of competition: Creating unique value with customers. Boston, MA: Harvard Business School Press

Grrrowd: The outsourcing of justice

When people think about crowdsourcing, they will often associate this with companies asking their customers to help them with innovative business ideas. However, it is a lot more than that. Crowdsourcing is used by companies to solve problems; generate ideas; design (logo’s, etc.) and for the outsourcing of tasks. This seems logical; companies utilizing the ‘wisdom of the crowd’ in order to come up with novel business ideas. The pros and cons of crowdsourcing are known by the companies that use this phenomenon. The pros of outsourcing obvious; you will generate a lot of ideas, in a short period of time and at a low cost. On the other hand, the cons might be less obvious. Although, the generating of ideas will go fast and with high volume it is often the case that only a small fraction can even be considered. Many of the ideas are simply not realizable by the firm, due to costs; brand image or other factors.

In 2014 there arose another application of the ‘crowdsourcing’-principle. Greenpeace came up with the idea to crowd source activism. This new application of crowdsourcing has not been seen before. It can be considered as a kind of ‘kickstarter’ for justice. In other words, Greenpeace offers potential users; considering the well-being of our planet, initiatives to participate in their activism. They have created a platform on which people can contribute to specific activism projects. They call this ‘the outsourcing of justice’. Examples of project in which people can invest are; A case to block the Ibutho coal company’s application for mining rights in the oldest proclaimed nature reserve in Africa; A case from a coffee farmer in Uganda who has been thrown off his land; A case to stop manufacturers of Genetically Modified Corn from invading the country where corn was born. (

The first case that was described above was an initiative to participate in blocking the activities of a coal company in a nature reserve in Africa. The coal company and their way of earning money would be a direct threat to the inhabitants of this nature reserve. This nature reserve was home to the greatest rhino population in the world and was the last 1% true wilderness in South-Africa. ( People could visit the platform and just as with Kickstarter, donate money for the specific cause.

Greenpeace has been the first company, within this domain, which has made use of crowd sourcing in order to achieve a greater goal. It was not only possible to donate money for specific causes, but also to ask attention for these causes by re-posting the cause on social media. As they specify it themselves: “Grrrowd is founded in the belief that the special interests that drive environmental destruction and human injustice can be defeated by the power of the crowd”. ( I think it is great initiative to make use crowd sourcing in this context. Not only will they obtain money for their activism, but people might also be encouraged to ask attention for specific causes which they find important. This is different from the conventional way in which companies like Greenpeace obtain money. Normally, they will ask you to subscribe and donate a fixed amount of money monthly. In this new initiative, people can still donate money. However, the money is directly associated with a specific goal that these donators consider as important. This will add a personal touch to activism, also creating synergies by the use of social media. After all, you are not just asking money for the good cause; but also helping Greenpeace get attention for specific causes.

B2B value creation using Salesforce AppExchange

Value co-creation is best known for its use in business-to-consumer situations. The main success stories of Uber and Airbnb are lauded worldwide for making millions in revenue, without actually owning the physical assets needed for the service they provide. However, value co-creation also exists within the business-to-business market. An example is the Salesforce AppExchange platform.

About the company

Salesforce is a global technology company specialising in CRM and customer centric business processes. Since starting in 1999, the company has helped more than 150.000 clients grow and serve their customers better.

 Business model

Salesforce’s business model revolves around selling licenses to use the different Salesforce products. In simple terms, their value proposition is that they help business deliver more value towards their customers by helping them understand and service their customers in a better way. This is done via one of more of their seven cloud based solutions. These solutions include:

  • Sales cloud – CRM & Sales automatization
  • Service cloud – Online service centres, and customer support
  • Marketing cloud – Customer Journey management
  • Community cloud – Client communities & teams
  • Analytics cloud – Business Intelligence
  • App cloud – App creation
  • IOT cloud – IOT data integration

Because all of their products are run from the cloud, there are no high service or maintenance costs for clients and clients can run their operations from anywhere. Besides the company itself, Salesforce has many partners around the world that specialize in and use their technology to implement customer based business solutions.

Customer value co-creation within Salesforce

Even though the current Salesforce platform was already a success, the company felt that it could serve its clients more if it opened up the platform to more input from other corporations. During the growth of the company, many small subgroups of clients formed. All the subgroups had unique needs and circumstances. As it would be impossible to add all these needs into the current Salesforce feature list, they decided to establish a two-sided network in which business partners could co-create extra functionality to the core product (Muzellec, Ronteau & Lambkin, 2015).


Via API’s and toolkits, business partners could build their own Salesforce extensions and sell them on the AppExchange platform. This way, Salesforce’s client needs could be better served and business partners had the chance to utilize the large network of Salesforce’s clients. Following the value co-creation framework of Saarjärvi, Kannan & Kuusela (2013), the exact specifics of have co-creation is achieved can be established

  “Value” “Co” “Creation”
Customer (business partner) Customer benefit: Income through application fees or expansion of own customer base Use of firm resources: Salesforce App Innovator Resources (account manager, marketing resources, partner community, etc.) Integration mechanism: Through API’s & Toolkit’s and the platform
Firm Firm benefit: Extra platform functionality to better service client needs Use of client resources: Client time and development expertise Integration mechanism: Through new application listings on the AppExchange platform

Further reading:

Hannu Saarijärvi P.K. Kannan Hannu Kuusela, (2013),”Value co-creation: theoretical approaches and practical implications”, European Business Review, Vol. 25 Iss 1 pp. 6 – 19 Permanent link to this document:

Muzellec, L., Ronteau, S. and Lambkin, M. (2015). Two-sided Internet platforms: A business model lifecycle perspective. Industrial Marketing Management, 45, pp.139-150.

A Critical Review: The Importance of Trust for Personalized Online Advertising

Online advertising efforts now account for more than a third of total ad spending in the US (Media Buying, 2016). As such competition to gain banner space and consumers attention has intensified. Therefor in order to gain higher effectiveness retailers have begun using an instrument called retargeting in order to create more relevant ads. Retargeting is a type of algorithm that can design ad banners featuring images of products that match consumers’ recent browsing behavior. This extreme form of personalized advertising has received a mixed response from consumers. On the one hand these ads more relevant and therefore more useful for consumers. However, on the other hand individuals at times find these advertisements inappropriately close to their personal preferences, raising concerns regarding privacy. As such retargeting is fueling the debate in between privacy and personalization.

This paper examines the impact of retargeting on click through rates and adds to the aforementioned debate by examining how retailers trust may moderate this relationship. The researchers partnered up with two ad agencies in order to gain enough ad impressions for their banners. They state that ad personalization with retargeting can be described along two dimensions, a banners depth and breadth. A banners depth of personalization refers to how closely the banner reflects that person’s interest. For example, a featured ad of a product that was recently in a persons virtual shopping cart reflects a person’s interest closer than an ad that features a product that a consumer merely inspected. A banners breadth refers to how complete the banner reflects that person’s interest (all the products in the shopping cart vs. only a few).

Their findings indicate that for banners of more trusted retailers, click-through rates are particularly high when a banner has high depth and narrow breadth as these adds appear more relevant and useful. However, for less trusted retailers a higher depth of personalization decreases consumers’ click-through rates as there is an increased reactance to privacy concerns. In general, though regardless of trust, retargeting is still more effective than normal advertising (Figure 1).

Figure 1:


These findings appear to be intuitive but it has important implications for retailers. Retailers should carefully asses their corporate standing and adjust their retargeting strategies dependent on the trust consumers bestow on them.

This article however does not comment on one critical aspect, which is consent. A consumer report found that 52% of people feel violated when personal information is used for advertising without their consent (SAS, 2015). In some cases, personalized advertising has even lead to lawsuits, a case based example is Target an American retailer that sent coupons of baby items to a young teenager. These ads were seen by her farther who found out her daughter was pregnant before she even knew. (Hill, 2016)

This raises an important question should retargeting be allowed from an ethical perspective? and to what extent should companies be held liable for algorithmic accountability?

Academic Article: Bleier, Alexander, and Maik Eisenbeiss. “The importance of trust for personalized online advertising.” Journal of Retailing 91.3 (2015): 390-409.


Hill, K. (2016, February 2). How Target Figured Out A Teen Girl Was Pregnant Before Her Father Did. Retrieved from Forbes:

Media Buying. (2016, September 13). US Digital Ad Spending to Surpass TV this Year. Retrieved from eMarketer:

SAS. (2015). Finding the Right Balance Between Personalization and Privacy. SAS. SAS Institute Inc.




Social Trading: A new way to invest

Have you ever wanted to get into trading but don’t know where to get started? Trading and investing in stocks, currencies, indices and commodities offer a high potential payoff, however can be hard to get in to. Often people don’t know how and where to get started, and end up making poor choices due to the steep learning curve. In the past, people have looked to their brokers or third parties for advice and guidance in trading, however with the rise of social and crowd platforms, a new style of trading has emerged.

What is Etoro and how does social trading work?

Etoro is a social trading platform where people can trade using ‘the wisdom of the crowds’ principle. The platform offers free trading advice, tutorials, a trading simulator, and an integrated social trading platform. On the social trading platform experienced investors can make market predictions, share information, and show their current and past trades through their public profile.  The aggregate of the current trade actions is made visible for each stock, currency pair, and commodity, so users know what the crowd is doing. Users can also select individual investors based on their past trading success, subscribe to their profile (via which they can receive advice or information), and even select to automatically copy their trades. This adds a new element to investing as users can track all trades made by their favorite investors, and automatically execute those exact same trades.


Investors can moreover benefit from being a ‘popular investor’, through which they can earn payments and other benefits relating to their popularity within the platform. Etoro charges users with a transaction fee for each trade as well as a general fee when withdrawing funds (relating to the size of the amount withdrawn).

Efficiency Criteria

In essence, the platform is split into two distinct sides that interact to create value together. Experienced investors join the platform with the intention of sharing their knowledge and trades in order to build up a reputation, and benefit from the rewards and payments that come with being a ‘popular’ investor. Meanwhile, new investors join the platform with the intention of benefiting from the crowd’s collective knowledge and copying experienced investors. Through this, new investors can start building a portfolio while learning from the advice and behaviors of experienced traders. As such, the value derived on both sides of the platform is maximized by the combined knowledge and interaction of the crowd.

Etoro itself also greatly benefits from this network effect. The more experienced traders join the platform, the more useful content will be available to new users, thereby making the platform more attractive to join. Additionally, the more trades are executed by users, the higher the profit generated by the company. Etoro further encourages sign ups using a referral program in which users can gain rewards for each new person that signs up through their referral link. This serves to further enhance the network effect by bringing more users to both sides of the platform.

The business model itself is not specifically adapted to the political, social or legal regulations of each individual country in which it operates, but rather is static across all regions. As such, a country’s legal environment poses the greatest threat to the survival of the company. Due to the strict regulations that come with operating in the financial sector, Etoro’s business model has not yet been approved in all countries. Currently, the USA, Iran and Cuba are among a few countries that have not yet allowed Etoro to operate under its current business model. This is understandable since social trading and the concept of copying trades can bring about many negative consequences. For example, a user could instantly lose all their equity by forgetting they are ‘copying’ an investor who might have executed a (failed) high-leverage trade.

Etoro. (2017). Retrieved from


How Scarcity and Personalization Affect Seed Stage Referrals

Admit it: you all have spent hours at those rotating displays when looking for a key ring/mug/magnet with your name on it. Personalization is not new, but the digital age is changing the way how this phenomenon is practiced. Koch & Benlian (2015) studied the implementation of scarcity and personalization in viral videos.  Previous research on viral marketing focused on firm level outcomes (e.g. sales) and individual level outcomes (decision making). Also factors that stimulate virality, such as content characteristics, have been studied in the past. The goal of this paper was to find out how ‘traditional promotional tactics’ as scarcity and personalization (in video advertisements) influence consumers’ referral decisions.

Hmm interesting. But how did they measure it?

The authors based their study on an online service called ‘StyleCrowd’, which gives its users style recommendations based on body characteristics. Users of this service can directly shop these recommendations at significant discounts. They used a 2 x 3 design, which implied that there were two conditions for personalization (presence/absence) and three conditions for scarcity (non/low/high). The participants (n=119) were randomly assigned to one of the six groups. The participants watched a video about StyleCrowd and after that, a message was shown.


Sounds cool, what did they found out?

  • It was found that scarcity has indeed a significant positive effect on the likelihood that a consumer engages in referrals.
  • The same effect was found for personalization, especially when there was a pre-existing relationship between customer and company.
  • They also looked at the interaction between personalization and scarcity, there outcome was that personalization is particularly effective when scarcity cues are absent.

That sounds almost too good to be true

Well, it’s indeed a nice study, viral marketing is a relatively new research area. They did a good job by including personalization in this study, especially as this phenomenon is getting more important (Tam & Ho, 2006). They also used a new platform which means less biased participants as they see it for the first time. But it’s not clear from their study how scarce a product should be in order to increase clicks. In other words: scarcity can’t be measured as a nominal variable (no/low/high). It would be better if they included more than three conditions. Another option is to randomize the number of available spots (e.g. between 15 and 100) to see if an increasing scarcity correlates with higher clicks. For future research I suggest that it would be interesting to look at other product groups, as online fashion is more appealing for women.

Good for them, but what are the practical implications?

For companies, it can be useful to include scarcity cues in their videos/advertisements. When there is a pre-existing relationship between marketer and consumer, personalization should be included in videos. It is not recommended to use both scarcity and personalization at the same time, as it reduces referrals. An example of a company which ‘nails’ scarcity is KLM: when you want to book a flight, a message is shown when there are ‘only a few spots left’. Nike is a company which successfully implemented personalized videos. They sent 100.000 personalized videos to Nike+ users which included their progress over the past year. The videos were fun to watch and they eventually went viral.


Koch, O., F., Benlian, A. (2015) ‘Promotional Tactics for Online Viral marketing Campaigns: How Scarcity and Personalization Affect Seed Stage Referrals’, Journal of Interactive Marketing, 32: pp. 37-52.

Tam, K., Y., Ho, S., Y. (2006) ‘Understanding the Impact of Web Personalization on User Information Processing and Decision Outcomes’, MIS Quarterly, 30, 4: pp. 865-890.

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.

A better way to co-create – build relationships while building innovation

Consumers can be an incredibly rich source of ideas for product and brand development, and collaborating with them can increase not just R&D productivity (Huston & Sakkab, 2006), but brand competitiveness as well (Bendapudi & Leone, 2003). And while co-creation for innovation is by its very nature one of the closest forms of collaboration between firms and consumers, very little has been said about how engaging in co-creation affects the consumer-brand relationship.

Through a combination of surveys and in-depth interviews conducted to address the above-mentioned paucity of research, Hsieh and Chang (2016) discover a complex relationship between a number of factors in co-creation – such as the perceived benefits of co-creation and the brand-self connection (i.e. the extent to which a consumer feels the brand reflects their core values) – which affect brand co-creation engagement. Engagement, in turn, increases purchase intention and brand citizenship behaviour – which both signify a stronger relationship with the brand.

In simpler terms, when co-creation is done right – when it appeals to the brand-self connection, and when it makes users feel competent, autonomous, and related to the brand – it increases the engagement users feel with both the co-creation platform and the brand. This increase in engagement has positive implications not only for purchase intention, but also for the intention to help others co-creators and offer feedback on their ideas. Therefore, engaging in co-creation projects does not only provide a firm with ideas for innovation – it can actually deepen consumer engagement, which can be leveraged into stronger brand equity as well.

Figure 1. A simplified model of how co-creation projects build engagement and brand benefits


Three principles for designing platforms that maximise co-creation engagement

  • Set clear objectives and guidelines, but encourage users to come up with diverse solutions within them. When the goals of co-creation are clear, consumers submit higher quality ideas and feel more competent at handling the task – and higher perceived competency leads to higher engagement. Co-creation tasks that allow users to think outside of the box and apply different skills are more engaging and enjoyable, and thus also lead to more positive brand affect.
  • Foster collaboration, not competition. When users encounter strong competition in a co-creation contest, it reduces their perceived self-competence and their level of engagement. On the other hand, a strong co-creation communities and a feeling of relatedness can provide consumers with a sense of belonging and a stronger sense of brand co-creation engagement – which can in turn increase purchase intention and brand citizenship behaviour. Therefore, brands should focus on maintaining a positive and trusting environment on their co-creation platforms, and giving users the opportunity to communicate with both the firm and each other.
  • Promote strong brand values. When consumers feel that a brand is congruent with their core values, they are not only more engaged with the brand and more likely to advocate it to their acquaintances – they are also more likely to take an active role in co-creation projects. Ensuring that a brand’s offline communication materials convey the brand’s core values will help breed an active online community.



Bendapudi, N., & Leone, R.P. (2003). Psychological implications of customer participation in co-production. Journal of Marketing, 67 (1), 14-28.

Huston, L., & Sakkab, N. (2006). Connect and develop. Harvard Business Review, 84 (3), 58-66.

Hsieh, S.H., & Chang, A. (2016). The psychological mechanism of brand co-creation engagement. Journal of Interactive Marketing, 33, 13-26.

The Milkman is cool again: Everything for an ultimate customer experience

After the disappearance of the labor-intense and specialized grocery-jobs, the Milkman is on its return in the Netherlands. Waking up the grocery giants such as Jumbo and Albert Heijn: a super-efficient online supermarket focusing on home deliveries emerged, Picnic. Making life for busy people much more convenient, this online retail distributor delivers your products at your home for free! And it becomes even better, since they manage to guarantee the lowest prices, leaving the establishment at their wit’s end with their unattainable business model.

How does it work?

Although online groceries are not completely new, this company makes it into their core business. After you have ordered your products and selected your most favorable delivery timeslot, Picnic does what they are doing best: delivering your groceries as quick as possible for the lowest price. Furthermore there is no need for waiting, since Picnic’s “Runners” are trackable via the real-time app on your mobile device. Even better, with an estimated arrival time up to 10 minutes accurate.

This makes it into a highly relevant opportunity for hardworking people with tight schedules, but also for the infirm and elderly (Keh & Shieh, 2001). Furthermore, Picnic is created together with the customer. Having the opportunity to reengineer the app or influence the available assortment, Picnic centralizes their customers to guarantee an optimal service level.

What is their unique formula?

However sceptics question the business model, Picnic has no doubts. Due to the savings as a result of skipping the physical supermarkets, these related costs are evaded. This leaves room for higher profit margins per product and a substantial budget for its distribution network. But how do they make their deliveries so efficient? The foundation lies in an extremely efficient supply chain. After shipping the products from their centralized warehouse-center to crossdocking locations at strategically positioned hubs, Picnic’s self-developed route planning system cracks the last mile to the customers.

Leaving from the environmental friendly hubs without energy-wasting cooling systems, electrical mini-trucks filled with grocery-boxes deliver the products at customers’ homes. By eliminating product oversupply and gas pollution via alternative fuels, Picnic wants to be as green as possible since that is what the modern customer wants.

Future ambitions

Although Picnic still focuses on a small part of the Netherlands, their potential goes far across the border of the country. Not only in places with a high population density but also in distant rural areas. Though, so far it is more complementary for households, especially throughout the week on top of their weekend-groceries. Nevertheless, Picnic is shaking up the traditional market and addresses some relevant issues in modern life. Which is, putting it mildly, remarkable in a country where most people live less than a kilometer away from a supermarket. So, do people really need dozens of locations with all those choices of different products, wasting all this food?

Thinking in a progressive manner with a customer becoming more aware about the environment and the positive influences of this business model (Ramus & Nielsen, 2005), Picnic has a huge potential. And although the online retail for groceries is not yet on fire, there will be a breakpoint. So will Picnic be the David that beats the Goliaths in their industry with its business model?

References:                                                                                                                                                            Keh, H. T., & Shieh, E. (2001). Online grocery retailing: success factors and potential pitfalls. Business Horizons, 73-83.     Ramus, K., & Nielsen, N. A. (2005). Online grocery retailing: what do consumers think? Internet Research, 15(3), 335 – 352.


Consider it sold

Opendoor is a San Francisco based start-up that steps into the real estate business, trying to make this process as easy as possible for the sellers and buyers. They are basically an intermediary in the market that brings together buyers and sellers. They buy real estate for cash, fix it and sell it for a small premium.

Business Model and Value creation

Opendoor uses an algorithm to determine what price to offer to the people that want to sell their homes via Opedoor. This algorithm includes thousands of variables, including for example square footage, numbers of bedrooms etcetera. Furthermore, Opendoor uses questionnaires to determine the preferences of the buyers and sellers, incorporating this in their model. In this way, the customers are actually co-creating the houses that Opendoor fixes. In the future, Opendoor also wants to offer customer mortgages and home decorations. Overall, the value that Opendoor adds is providing a service that takes away the burden of the customer to buy or sell houses and using the preferences of the customers in this process.

Opendoor buys family homes built after 1960 in the price range of $125000-$500000. Opendoor makes the homeowner an offer and once he accepts, inspects the house and closes the deal in cash.  The company makes money by taking a service fee of 6%, similar to the standard real estate commission, plus an additional fee that varies with the riskiness of the transaction what brings the total charge to an average of 8%. It then makes fixes recommended by inspectors and tries to sell the homes for a small premium. Buyers can look at the property and they receive a 30-day guarantee that Opendoor will buy it back if they’re not satisfied. (Forbes Welcome, 2017) (Opendoor, 2017)

Efficiency criteria and risks

When we look at the efficiency of the value system of Opendoor, we can look at two criteria, the joint profitability and the feasibility of required reallocations. (Carson et al., 1999) Opendoor definitely offers joint profitability, because consumers can easily sell or buy their homes via the platform, and Opendoor can profit by making money from the fixed houses. The second criteria is more difficult because Opendoor solely depends on investors and loans and when they don’t make profits they cannot reallocate their assets to satisfy their investors. Next to that, trust issues are also important to take into account. Opendoor cannot see the homes before they make an offer an have to rely on trust. Finally, competitors will not be that happy with Opendoor and therefore legal aspects will be important to consider while expanding.

The business model depends on whether the algorithm is right or wrong. If it is right then Opendoor will earn money, however, if the price is lower, Opendoor will make a loss. Next to that Opendoor pays in cash and loans this money. It is dependent on investors and if they encounter a low in the market they have a problem. They did not face a crisis like the one in 2008. All in all, let’s keep a close watch at this company and see whether they will conquer the real estate market.


Carson, S. J., Devinney, T. M., Dowling, G. R., & John, G. (1999). Understanding institutional designs within marketing value systems. Journal of Marketing, 115-130.

Forbes Welcome. (2017). [online] Available at: [Accessed 14 Feb. 2017].

Opendoor. (2017). [online] Available at: [Accessed 17 Feb. 2017].

Saarijärvi, H., Kannan, P. K., & Kuusela, H. (2013). Value co-creation: theoretical approaches and practical implications. European Business Review, 25(1), 6-19.


Mapping the Impact of Social Media for Innovation

Facebook, YouTube, Instagram, Wikis, Twitter – Social media (SM) are everywhere. Those websites and applications allow the creation and exchange of user-generated content in a community setting (Kaplan & Haenlein, 2010). The users are not only private people, but also companies are exploring SM as a tool for commercial success. Next to outbound marketing, SM are also applied to enhance business interactions as part of the innovation and product development process (Kenly & Poston, 2011). However, so far new product development (NPD) through social media channels can only be observed anecdotally. Specialized consultancies also jump on the train and offer their services to get a piece of the pie (Accenture Interactive, 2017). But how nourishing is this pie?

The impact of SM on innovation performance was investigated in a study by Roberts, Piller and Lüttgens (2016). The analysis of 186 companies contributed to a better understanding of the dynamics between SM activities and NPD performance. The idea to use SM for innovation and NPD purposes is not novel. However, their study reveals some surprising results:

  • Gathering information from SM channels can lead to higher performance, but only when embedded in complementary, formalized processes. A defined structure and sequence for the flow of activities provides control, helps to reduce uncertainty and mitigates risk.
  • The relationship between SM usage and innovation performance is not entirely positive. An extremely broad application of SM results in a negative performance effect for all kind of innovation projects.
  • The relationship between seeking market-related and technology-related information in the open innovation context is complementary. Leveraging this dependency has a significant positive effect on NPD performance.
  • SM is better suited for gathering need information than for accessing solution information. Depending on the information needed, the explicit SM channels (forums, social networks, blogs, wikis etc.) differ.

These findings imply the positivity of SM for a firm’s innovation performance. But I personally doubt its large-scale effectiveness. After having screened the literature for mentioned best-practice examples, there are enormous differences between companies in how they leverage and exploit benefits of SM usage for innovative efforts. The involvement of customers into new product creations for consumer goods rather resembles the characteristics of a marketing or market research tools. Haribo asked its fan base to vote on new flavors for a special edition during the 2014 soccer world cup. Home-appliances manufacturer Liebherr invited its customers to participate in a fridge-design competition. In contrast to that, I found technology-oriented companies, like NASA, or IBM in collaboration with Topcoder, to give their followers far more influential power by posting demanding challenges. This is surprising, because the study stated SM to be more suitable for gathering needs than (technical) solutions. So, is there a difference between industries concerning the successful integration of SM in NPD? Are technology companies simply more knowledgeable in utilizing SM? Or are their users simply identifying more with the product and thus engaging in NPD processes? The multitude of questions call for a further investigation of the results in relation to different industries and specific firm capabilities in dealing with SM. Hence, up to now how nourishing and likely this cake for businesses and consultancies is, might still be questionable and has to be answered for individual initiatives specifically.



Accenture Interactive (2017). Social Media: Optimization to Harness Innovation. Retrieved February 15, 2017, from

Kaplan, A. M., & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of Social Media. Business horizons53(1), 59-68.

Kenly, A., & Poston, B. (2011). Social Media and Product Innovation: Early Adopters Reaping Benefits amidst Challenge and Uncertainty. In A Kalypso White Paper. Kalypso.

Roberts, D. L., Piller, F. T., & Lüttgens, D. (2016). Mapping the Impact of Social Media for Innovation: The Role of Social Media in Explaining Innovation Performance in the PDMA Comparative Performance Assessment Study. Journal of Product Innovation Management33(S1), 117-135.

The Future of Beauty: Makeup Tailored For You.

When it comes to finding the right shade of make up for your skin, I’m confident that I’m not alone in my frustration. Most, if not all, cosmetic brands offer a range of makeup in different shades, catering to both light and dark skins, with different moisture levels. However, this standard range of shades don’t cover all skin tones, which leaves the consumer constantly wondering if they’re leaving home with their face too light or too dark.

Lancôme, one of the pioneers among the cosmetic industry leaders that have shifted their focus to be more customer-centric, are now engaging in personalized products by co-creating with their consumers.

What is it?

The company recently introduced their new product – Le Tient Particulier. It’s a foundation in the shade custom-made for your skin. The consumers face is scanned with a small handheld gadget and the data is then presented to them on a screen with information about their skin. The consumer has the option to select the moisture level of the formula and it’s coverage intensity. The data is sent to a machine that dispenses the formula’s ingredients and blends it together. Within a few minutes, the personalized product is ready. The consumer can test it on their skin and tweak it to their liking. The final product is then saved to the consumers’ custom Complexion ID, which is printed on the bottle with their name, for easy refills. (Lancôme 2017a)

In this experience, the consumers needs are centred and the consumers become part of the value creation process . Lancôme is also able to build stronger relationships with their consumers. Their business model is to offer high quality products that are relevant for all consumers, in addition to meeting their goal of “continually taking science and creativity to new levels” (Lancôme 2017b).

Efficiency Criteria

The joint profitability criteria is met as the product maximizes the joint payoffs for both the consumers and the company. The consumers benefit from obtaining the product designed for their skin, which perfectly meets their needs, thus eliminating the need for them to continue experimenting with different products or settling for one that is less satisfactory. Furthermore, consumers will be able to enjoy the feeling of accomplishment that arise by modifying the product to their preferences (Franke, Schreier & Kaiser 2010).

Even though the company is faced with the investment cost of the machines per store location, the company benefits from the high switching costs consumers experience after purchasing this product. They will likely continue to purchase the product as they’ve found the ideal formula for their skin. In addition, the company further secures consumer loyalty by offering consumers the option to tweak the formula if the consumers become unhappy with it.

The feasibility of the required allocations is also met. While the polity and judiciary dimensions of the institutional environment are not directly related in this case, the social norms dimension is met. Lancôme is a reputable luxury skincare and cosmetics brand, which increases trust in its brand.


Franke, N, Schreier, M & Kaiser, U 2010, ‘The “I Designed It Myself” Effect in Mass Customization’, Management Science, vol. 56, no. 1, pp. 125 – 140, viewed 12 February 2017, <;.

Lancôme 2017a, Le Tient Particulier, Lancôme, viewed 16 February 2017, <;.

Lancôme 2017b, Discover Lancôme, Lancôme, viewed 16 Februrary 2017, <;.



The Impact of Timing and Product Portfolio of Recommendation Systems on Customer Satisfaction

It’s safe to say we have all bought something online. The web has become an important platform over the years for people to obtain information and shop. Why? It’s easy, you can shop whenever, wherever you want and all the information you need is in the product description. Because of rise of e-commerce, personalised recommendation was created to recommend products that meet consumers’ preferences, reduce cognitive efforts, improve user experience, and help purchasing decisions while prompting sales. We’ve all seen companies such as,, and, and even online supermarkets use these recommendation tools. By looking at their consumers browsing history, purchase history and comment history these companies can determine consumer behavioural preferences and recommend consumers the products that they may interest.

The paper written by Yan, Q. et al., looks at the decision-making process of consumers and analyses the mechanisms involved in consumers’ acceptance of these recommendations.  What makes the paper unique is its distinctive assessment of the personalised recommendation system by analysing it from two angles; the recommendation timing and product portfolio. Past papers looked at accuracy and efficiency of recommendation algorithms and their ways to reduce perceived risks, however according to Yan al, a good recommendation system does not only focus on accuracy but also on customer satisfaction which isn’t determined by accuracy. What does determine customer satisfaction is time.

How can time increase customer satisfaction? By recommending products at the right time with the right diversity. According to the preference inconsistency theory, there is a discrepancy of consideration sets in the first and second stage of the decision-making process. In the first stage, when users are browsing, for example for a new pair of jeans, consumers want a lot of choices while in the second stage, before users click submit for purchase, the focus is to minimise the difficulty in decision making and making the right decisions. Too much product choices will cause users cognitive overload, and lower consumer satisfaction. Hence, consumer preferences for recommended products vary in time and the recommended product portfolio and recommendation timing should be consistent with the consumers’ preferences, or it can cause a burden on consumers and decrease consumers’ satisfaction of the system!

What also affects consumer satisfaction is the difference in the type of products recommended in each stage. When consumers browse e-commerce sites, they tend to focus on their own needs and objectives and conduct search on the initial target product and products in the same category. Because consumers tend to focus more on similar products, similar products recommended by the system will be recommended. However, in the second stage, consumers have developed certain awareness and made choices regarding their target product, hence their focus easily moves to products complementary to the target product and consider purchasing other products that are not the target product!

Also, there is a difference in the acceptance of personalised recommendation between practical and hedonic products. Think about the difference of buying dental floss or buying a new television.  The motives for practical products include meeting basic needs and convenience while the motives for hedonic products is based by perceived fun and entertainment. Hence, consumers are likely to have different cognitive and emotional reactions when purchasing these different products. The research shows that consumers who have hedonic products in their consideration set are more susceptible to the systems product recommendations, compared to practical products!

The strength of the research is its further in-depth analysis of the various factors influencing recommendations on consumers. The study takes a different approach compared to past research papers and can be a theoretical basis for e-commerce companies in understanding consumers focus and behaviours at the different stages of the shopping journey. The meticulous understanding can be used to improve customer satisfaction by reducing the cognitive journey and ultimately increase sales! Recommendation systems based on accurate timing and product portfolio are a win-win situation for both the consumer and the retailer!


Tsekouras, D. (2017). Session 2: Personalization & Product Recommendations.

What every marketer should know about hedonic shoppers. (2017). [online] The Rooster Blog. Available at: [Accessed 10 Feb. 2017].

Yan, Q., Zhang, L., Li, Y., Wu, S., Sun, T., Wang, L. and Chen, H. (2016). Effects of product portfolios and recommendation timing in the efficiency of personalized recommendation. Journal of Consumer Behaviour, 15(6), pp.516-526.

UNITED WARDROBE An Infinite Closet in Your Pocket

Imagine you bought a pair of sneakers. After wearing them a few times you realize they don’t fit properly. Even though they are as good as new, you are not able to return them. You could try to resell them online on Facebook or Marktplaats, but you have some uncertainties about safety and security. This is where United Wardrobe comes in: a hip, social and safe fashion platform.

United Wardrobe is an online platform for buying and selling second hand fashion. The key aspects of the platform are safety, sustainability and service. But United Wardrobe is more than just a marketplace platform, it is a community where you can chat with other fashion lovers, follow users and favorite each other’s products. These social functions empower users to become co-creators of value.

How does it work?
A user can create a profile and upload products for sale. The moment a buyer has paid for a product, the seller receives their contact details. As soon as the package has been received, United Wardrobe transfers the money within 14 days to the seller (United Wardrobe, 2017). This relates to what Carson et al. (1999) define as institutional arrangements, the formal and informal rules of exchange created by specific parties to a specific exchange, in this case the exchange of fashion.

The institutional arrangements of United Wardrobe meet three criteria set by Carson et al. (1999). Firstly, they are efficient in a sense that they enable joint profitability and create incentives for users to contribute. Next to this, they are feasible given the characteristics of the exchange of products. Finally, they are achievable in a sense that United Wardrobe has succeeded in growing the platform and community. These institutional arrangements allow United Wardrobe to tackle safety and security issues such as scamming, which no other marketplace platform has succeeded to do.

Users are an important part of United Wardrobe’s business model and enable more creation of value than the company could create on its own. In fact, without its users, the company would not even exist. This is the essence of value co-creation, where new ways are identified to support either the customer’s or the firm’s value-creating process (Saarijärvi et al., 2013). An interesting feature on the website is a page where you can see what the most popular search terms are. This reflects a customer value co-creation mechanism where the firm has refined user data and returned it to the users (Saarijärvi et al., 2013). United Wardrobe has won several prizes with its concept including Dutch Online Retail Experience Award 2015 and the public award of Accenture’s Innovation Awards in 2014.

From my own experience with the platform I can assure you that it is a fun and easy way to sell some clothes. Everyone has clothing at the back of their closet they never wear. A pair of trousers that you might hate another might love, so get up and make that extra money. From an environmental perspective I think this business model is a great step towards a better planet by recycling fashion.

Carson, S. J., Devinney, T. M., Dowling, G. R., & John, G. (1999). Understanding institutional designs within marketing value systems. Journal of Marketing, 115-130.

Saarijärvi, H., Kannan, P. K., & Kuusela, H. (2013). Value co-creation: theoretical approaches and practical implications. European Business Review, 25(1), 6-19.

United Wardrobe (2017) Available at: Accessed on 15/02/2017