Discrimination on online platforms: a call for regulation


In the housing and rental market, anti-discrimination laws in the US gradually reduced discrimination through the legal system for the past two decades. However, academic scholars (Edelman, Luca & Svirsky, 2017) argue that the emergence of online platforms facilitate discrimination, as these laws do not reach smaller property owners using online platforms. Airbnb, the world largest online platform for short-term rental and housing, adopts a design choice that enables discrimination on its platform. Hosts decide whether or not to accept a guest after seeing the name and profile picture of the guest.

Methodology and experiment

In order to test whether Airbnb facilitated discrimination through its design choice, the authors (Edelman, Luca & Svirsky, 2017) conducted a field experiment across five different cities, including: Baltimore, Dallas, Los Angeles, St. Louis and Washing DC between 7 July 2015 and 30 July 2015 (see Figure 1). Originally, the experiment aimed to gather data from the top 20 cities in the US, but the experiment was halted due to Airbnb’s systems detected and blocked the automated tools used to gather the data.

Figure 1. Research scope.

The experiment gathered a wide range of information about hosts and their listings (see Figure 2). Information of hosts include but are not limited to profile image, gender, age, number of properties listed and previous guests that visited the host. Information on listings include price, number of rooms, cancellation policy, cleaning fee, rating and whether the room was shared or not to control for interaction between the guest and the host.

Figure 2. Data collection.

After gathering data, the experiment sent 6,400 messages with 20 Airbnb accounts. Hosts who offered multiple listings on the platform were contacted for one of their listings to prevent the host from receiving identical e-mails and to reduce the imposed burden. The accounts used to send messages are identical except for two variables: i) race and ii) gender. Race and gender were indirectly embedded in the profiles through the use of names based on Bertrand and Mullainathan (2004). Additionally, to alleviate confounds that would arise from using profile pictures, accounts did not include a profile picture. Finally, the experiment tracked the response over 30 days after the message was sent.


The authors found that guests with distinctive White American sounding names were accepted ±50 of the time, while guests with African American sounding names were accepted at ±42 of the time. The ±8% gap persists across characteristics of the hosts and listings as control variables. More important, the results infer that the discrimination effect occurs in differences of a simple “Yes” or “No” response and not because of intermediate response and non-response. The authors further found that the discrimination effect disappears when hosts previously accepted African American guests. Control variables including homophily concerning race, age categories, price of the listing and demographics of the vicinity are however of no significant influence on the discrimination effect. Discrimination further cause financial consequences, as host incur costs when rejecting guests causes a unit to remain unrented.

Discussion: strengths and weaknesses

This paper provides clear evidence of the presence of discrimination in online platforms. The relevance of this paper is also strengthened by the way it emphasizes discrimination in the online channels, while in the past the focus was primarily on discrimination in offline channels. The results are consistent with other studies on discrimination in the online rental and housing market. Ge, Knittel, MacKenzie and Zoepf (2016) found a similar pattern of discrimination in peer transportation companies such as Uber and Lyft; African American passengers face longer waiting times and more frequent cancellations compared to their White-American counterparts.

The research also has a few flaws. First, the research is not able to detect the type of discrimination that occurs (e.g. statistical discrimination and taste-based discrimination) and whether discrimination is based on socioeconomic status or race that is associated with the name. Second, the paper suggests that the discrimination effect occurs when users of these platforms gain the choice to accept or to reject guests and passengers, which suggests that the problem lies in the platform’s design choice. The suggestions to alleviate discrimination by limiting design choice such as removing information of guests and passengers such as concealing names and profile photos or to eliminate the screening procedures by introducing instant book options as the only option, may harm the user experience for both (hosts and guests) sides. For hosts it is desirable if they can maintain control on who they allow to stay at their place, while for guests the platform is attractive if they can choose the place and host of their liking. When choosing to reduce discrimination by lowering the user experience for either party, online platforms run the risk of becoming less attractive than their competitors and jeopardizing their own competitiveness. Ultimately, discrimination will continue to occur on competing platforms that do not change their design in benefit of combatting discrimination and the non-discriminating company will lose its competitive edge and fail. Third, the inferences made by the paper are to a certain extent limited to the US. A recent study found that racial discrimination is more prominent in the US than in Europe (Pitner, 2018). The focus on metropolitan areas also questions whether the same effect will occur in rural areas. On the assumption that metropolitan areas are more globally connected and face higher exposure to other races, one can logically assume that metropolitan areas are more tolerant and discriminate less against other races.

Airbnb adjusted its non-discrimination policy in 2018. Hosts are no longer allowed to request a guest’s photo before accepting a booking agreement (Thinkprogress, 2018). Based on the research (Edelman, Luca and Svirsky, 2017), the adjustment will not help as hosts can still view names prior to the selection procedure. A potential solution is to increase the prevalence of reviews in the selection procedure. Cui, Li and Zhang (2016) found that encouraging credible peer-generated reviews mitigates the discrimination effect of guests with African American-sounding names on Airbnb. However, we argued that the action of one platform may not suffice as a solution to stop discrimination and call for more regulation on online platforms from authorities.

Airbnb adjusted its non-discrimination policy in 2018. Hosts are no longer allowed to request a guest’s photo before accepting a booking agreement (Thinkprogress, 2018). Based on the research (Edelman, Luca and Svirsky, 2017), the adjustment will not help as hosts can still view names prior to the selection procedure. A potential solution is to increase the prevalence of reviews in the selection procedure. Cui, Li and Zhang (2016) found that encouraging credible peer-generated reviews mitigates the discrimination effect of guests with African American-sounding names on Airbnb. However, we argued that the action of one platform may not suffice as a solution to stop discrimination and call for more regulation on online platforms from authorities.


Bertrand, M. & Mullainathan, S. (2004). “Are Emily and Greg More Employable Than Lakisha and Jamal? A Field Experiment on Labor Market Discrimination.” American Economic review 94 (4): 991–1013.

Cui, R., Li, J., & Zhang, D. (2016). Discrimination with incomplete information in the sharing economy: Evidence from field experiments on Airbnb.

Edelman, B., Luca, M., & Svirsky, D. (2017). Racial discrimination in the sharing economy: Evidence from a field experiment. American Economic Journal: Applied Economics, 9(2), 1-22.

Ge, Y., Knittel, C. R., MacKenzie, D., & Zoepf, S. (2016). Racial and gender discrimination in transportation network companies (No. w22776). National Bureau of Economic Research.

Pitner, B. H. (2018, May 17). Viewpoint: Why racism in US is worse than in Europe. Retrieved March 5, 2019, from https://www.bbc.com/news/world-us-canada-4415809

Thinkprogress. (2018). Airbnb announces booking policy change to head off outcry over persistent racial discrimination. Retrieved fromhttps://thinkprogress.org/airbnb-changes-photo-policy-combat-racial-discrimination-4f71c375553a/

The influence of the gig economy on entrepreneurial activity

TAt the moment, more than one third of the workforce in the United States works (part-time) as freelancer (Muhammed, 2019). Almost half of the freelancers over the age of 55, use supplemental gig work as a means to finance their retirement. It is expected that by 2020, almost half of the entire population will (part-time) perform gig work.

These facts are caused by the rise of the gig economy. A gig economy is an economy in which temporary, flexible jobs are common. In the gig economy, employees usually work part-time as contractors and freelancers, whilst in a classical economy employees work full-time, rarely switch jobs and often work for the same company their whole career (Kenton, 2018). During the last decade the gig economy has experienced a significant rise, caused by three major developments: First, Millennials have a different attitude towards working than the traditional workforce, as they prefer to have variety in work and a good balance between working and private life. Second, since the financial crisis of 2008, companies increasingly use gig workers to lower labor costs and to improve flexibility. Third, due to technological advances and the digitalization of the world, gig economy platforms were introduced, improving the access to gig work and workers for both firms as the labour force (Muhammed, 2018).

However, whereas the rise of the gig economy has several welfare benefits (Jennings, 2018), there are also possible downsides to it. In the paper “Can you gig it? An empirical examination of the gig economy and entrepreneurial activity.”, authors Gordon Burtch and Seth Carnahan researched a possible downside, whether the introduction of a gig economy platform in a geographical area would lead to a decrease in entrepreneurial activity.

Context & methodology

The authors used the introduction of Uber X into a specific geographical area as measure of an introduction of a gig economy platform. Uber X was chosen for two reasons: First, Uber enters the economy city-wise, meaning that for a specific area, the service might be available in one city, but might not be in another. This makes it possible to directly analyse the results of the entry of Uber X in a certain area. Second, Uber X is used instead of the (premium) Uber Black service because of the lower entry barrier and a larger network of drivers. Additionally, to measure the influence of entry barriers of the gig economy on the observed effect, the results gained by researching Uber X are compared to those of Uber Black.

The research was conducted as a natural experiment. The authors used real life examples of entries of the gig economy and measures of entrepreneurial activity. The researchers measured entrepreneurial activity by combining 2 data from 2 sources:

  • First, the US Census Current Population Survey (CPS). In this survey, self-employment is measured.
  • Second, Kickstarter campaign data was used, where the volume and size of Kickstarter campaigns were measured.


The research found a significant negative correlation between the introduction of the gig economy and the entrepreneurial activity within the same geographical area. This negative correlation can be explained by the fact that gig economy platforms offers a source of income for the unemployed with a very low entry barrier, so there is no direct need for them to engage in entrepreneurial activity in order to ensure an income.

However, the research also found a significant increase in the average quality of entrepreneurial activity. According to the findings, this can be explained by the fact that people with mediocre or bad ideas that would engage in entrepreneurial activity without the entry of a gig economy platform, are now participating in that gig economy. The people that are still convinced of their own entrepreneurial qualities are pursuing their idea and don’t give it up to start driving for Uber X. These people apparently have a higher quality entrepreneurial activity, which increases the average quality of the entrepreneurial activity.

Additionally, a significant positive correlation was found between lower entry barriers of a gig economy platform and its effect on entrepreneurial activity. The research found that the introduction of Uber X (which has a low entry barrier), leads to a bigger decrease in entrepreneurial activity and a higher increase in average quality of entrepreneurial activity, as opposed to the introduction of Uber Black (which has a higher entry barrier: you have to buy a black car).


The paper written by Burtch and Carnahan (2018) included several strengths. First, the paper included several robustness checks regarding the validity of data. By making use of multiple measures for the same phenomena, it is more likely that the correct effect was captured. Second, another strength of this paper would be the novelty of the research, as the paper is the first to examine the supply side of the gig economy. By researching novel subjects, the added-value to literature of this particular research area is higher. Third, as the paper makes use of two different data sources to measure entrepreneurial activity, the reliability of the data used in this paper is higher.


Besides several strengths, the research done by Burtch and Carnahan (2018)  has several weaknesses as well. First, a weakness of this paper would be the low generalizability of the sample. The research is solely performed in the United States, which is a country with low unemployment benefits. According to Cowling and Bygrave (2002) has a significant correlation with entrepreneurial activity. Having only performed research within the United States, the generalizability of the results is lower, which reduces the findings’ value.

Second, the paper’s assumption that Uber drivers would otherwise engage in entrepreneurial activity, might be too big of an assumption. As Uber offers low-skilled jobs, its drivers might not be the people who would otherwise engage in entrepreneurial activity. People might even start driving Uber X to make some money, but use the flexibility in planning to actually start a business next to driving for Uber X. Moreover, the paper assumes that the entry and timing of Uber X is exogenous with respect to entrepreneurial activity. These assumptions both deteriorate the research quality, but proved necessary to perform the research.

Lastly, the paper contains data issues. For the first time, the volume of Kickstarter campaigns was used as a (partial) measure for entrepreneurial activity. Kickstarter campaigns may be run multiple times, which implies that the quality of the data might be lower than expected. Another reason why the data from kickstarter might not be generalizable, is that it was obtained during a period of economic recession, during which unemployment rates are higher than normal, which could mean that the impact might be different than it would be during a ‘normal’ period of time.


The paper proves worthy both in research and in practice. For academics, this paper proves valuable as it is one of the pioneers in researching the supply side of the gig economy. On top of that, the researchers also pioneered in using kickstarter as a measure for entrepreneurial activity, despite its limitations. For policymakers debating about the legality of gig economy platforms as Uber, this paper could provide relevant insights for crafting legislation around gig economy platforms.

In many countries Uber faces legal problems.


The paper provides new information towards research about the gig economy as it offers insights on the supply side, which was rarely researched previously. The insights of this paper are relevant but should be taken cautiously however, as there are multiple notable concerns towards the validity, despite the efforts of the authors to ensure the quality.


Burtch, G., Carnahan, S., & Greenwood, B. N. (2018). Can you gig it? An empirical examination of the gig economy and entrepreneurial activity. Management Science, 64(12), 5497-5520.

Cowling, M., & Bygrave, W. D. (2002). Entrepreneurship and unemployment: relationships between unemployment and entrepreneurship in 37 nations participating in the Global Entrepreneurship Monitor (GEM) 2002. In Babson College, Babson Kauffman Entrepreneurship Research Conference (BKERC) (Vol. 2006).

Gooch, K. (2018). More Americans turn to crowdfunding for medical bills: 6 things to know. Many Americans struggle to afford their medical bills and are increasingly turning to crowdfunding for support, reports Yahoo Finance. Retrieved from https://www.beckershospitalreview.com/finance/more-americans-turn-to-crowdfunding-for-medical-bills-6-things-to-know.html

Jennings, M. (2018). 7 Reasons Why the gig economy is a Net Positive. Retrieved from https://www.entrepreneur.com/article/310685

Kenton, W. (2018). gig economy. Retrieved from https://www.investopedia.com/terms/g/gig-economy.asp

Muhammed, A. (2018). 4 Reasons Why The gig economy Will Only Keep Growing In Numbers. Retrieved from https://www.forbes.com/sites/abdullahimuhammed/2018/06/28/4-reasons-why-the-gig-economy-will-only-keep-growing-in-numbers/#6344d33e11eb

The Rise of the Sharing Economy: Estimating the Impact of Airbnb on the Hotel Industry

Paper discussed:
Zervas, G., Proserpio, D., & Byers, J. W. (2017). The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry. Journal of marketing research, 54(5), 687-705

1. Introduction

Peer-to-peer markets, also known as the sharing economy, has enabled people to collaboratively make use of underutilized inventory through fee-based sharing. The rapid growth of peer-to-peer platforms has arguably been enabled by two key factors: technology innovations and supply-side flexibility. This study analyzes Airbnb’s entry into the state of Texas and quantifies the impact on the Texas hotel industry between 2008 and 2014. The paper contributes to the growing literature on multi-sided platform competition, as Airbnb is an example of a two-sided platform. Besides, the work contributes to the existing literature by focusing on the impact of external shocks on the tourism and the hospitality industry. The researchers expect that some stays on the Airbnb platform will substitute certain hotel accommodations. This can significantly affect the hotel revenue. Though, the authors note that the impact differs per geographic region, hotel market segment and season.

2. Method

In order to quantify the extent to which Airbnb’s entry has negatively affected the hotel room revenue, the researchers gathered data from various sources. The Airbnb platform was the main source of data for this study. Additionally, the monthly room revenue from 3,000 hotels in Texas together with several other datasets were included in this study to account for the information on control variables and in order to conduct robustness checks.

After collecting the necessary data, a difference in differences (DD) empirical strategy is conducted to identify the causal impact of Airbnb on hotel revenue. This strategy identifies the Airbnb treatment effect by comparing differences in revenue for hotels affected by Airbnb before and after Airbnb’s entry with a baseline of differences in revenue for hotels that were not affected by Airbnb in the same period. To perform the analysis, they regress against two measures of Airbnb supply, namely a cumulative measure of all Airbnb listings and an instantaneous measure that defines supply as those Airbnb listings active within a short period. In all their specifications, they included a set of control variables that vary over time. For example, control variables such as population, wages, unemployment, total hotel room supply, airport passengers counts and TripAdvisor ratings were taken into account for each hotel as a proxy for quality. Also, they included city-specific trends and city-month dummies to account for seasonal differences in demand across the different markets. Finally, they have conducted several robustness check in order to support the causal interpretation of the estimates.

3. Findings

The authors found that, in Texas, each additional 10% increase in the size of the Airbnb market resulted in a .39% decrease in hotel room revenue. These effects are primarily driven by Austin, where Airbnb inventory has grown extremely rapidly over the last years, resulting in an estimated revenue impact of 8%-10% for the most vulnerable hotels in Austin. Accordingly, the researchers found that the impact of Airbnb is bigger on cheaper hotels in comparison with expensive hotels. The impact of Airbnb also falls disproportionately on hotels lacking conference facilities. Another finding is related to type of hotel; chain hotels tend to be less affected by Airbnb than independent hotels. This can be explained by the fact that chain hotels have a larger marketing budget and can thus benefit from their stronger brand identity. To conclude, the research showed that Airbnb is flexible in terms of their ability to flexibly scale instantaneous supply in response to seasonal demand, whereas hotels lack the flexibility. This has significantly limited hotels’ pricing power during periods of peak demand.

4. Strengths & Weaknesses

The main limitation of this study is related to the representativeness of this study since the AirBnb effect on the hotel industry is only studied in Texas. The generalizability of the findings should be taken into account considering the volatility of the housing market and the sensitivity of the hotel industry towards economic differences and other dynamics influencing supply and demand for accommodation. Though, the research uses a diverse set of data sources and controls for various exogenous variables (e.g. population, wages, unemployment and total hotel room supply). The authors point a similar limitation In addition, the study investigates multiple cities in a large state and the data is collected in a time period of 6 years (2008-2014). On the one hand, the long time period adds to the level of reliability and consistency of the research. On the other hand, the timing of the data period (2008-2014) yields a point of discussion since it investigated the vacation rental platform before the explosion of peer-2-peer networks happened.

Another limitation of this paper is related to the analyzed properties, the authors only consider AirBnb as the main peer-to-peer platform, whereas other vacation rental platforms such as HomeAway and VRBO do gain traction as well and might influence the negative on the hotel industry as studied. Also, the authors of the research add that only short run implications are considered by including only two metrics;  price and occupancy rate. A longer time scale is not included, this reasons that the authors did not include the longer time scale is arguable. Further research can take the findings of this research as a starting point to study possible ways to respond to peer-to-peer platforms such as AirBnb. For example, alterations of investment schedules can be analyzed or effect of government regulations can be taken into account.

Overall the paper considers the short-term effect of the peer-to-peer platform AirBnb on the revenue stream of the hotel industry in Texas. Strengths of this paper are mainly related to the comprehensive investigation of the AirBnb platform, economy and housing market in Texas including controlling for exogenous factors such as airport passengers counts and TripAdvisor ratings. Not to mention the wide time span of six years (2008-2014). All strengths of this research considered, generalizability is a main concern of the findings. Though, the research takes a first step in quantifying the effect on society by analyzing AirBnb which contributes to the recent development of peer-to-peer networks in the raising sharing economy. By quantifying the effect through including several reliable data sources (e.g. platform itself and the monthly room revenue from 3,000 hotels in Texas), control variables and other exogenous factors, the study does provide practical relevance in terms of showing the exact effect in percentages and how the researched variables account for differences in the effect. The study is therefore relevant for society and other countries as well as governmental bodies, consumers and the hotel industry itself.


Zervas, G., Proserpio, D., & Byers, J. W. (2017). The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry. Journal of marketing research, 54(5), 687-705


Chinese Speech Recognition Company focused on Natural Language Processing


Unisound Information Technology Co. Ltd. also called Unisound or Yunzhisheng in Chinese is a speech recognition and artificial intelligence company based in Beijing. Current applications of its algorithms include smart medical plans, smart home solutions and intelligent car solutions (Unisound, 2019).

The company was founded in 2012 by Huang Wei, its current CEO, and made recent news by being described worth over $1 billion dollar, which makes it one of China’s unicorns (Yelin et al. 2018). The company states that its vision is to “make the future enjoyable” and it sees the technology industry moving from “device-centric” to “user-centric” and “data-centric”.

Business Model

Next to its endeavors in the industrial production, medical, mobility and teaching sector; one of Unisound’s core products is “UniHome”. UniHome offers its users IoT for apartments and houses including voice-controlled devices, intelligent execution decisions and sound source localization.

To build these services and the required products, Unisound focuses most of its resources on recruiting the best talent, strategically selecting production & marketing locations and collaborating with various top-notch partners. Partners include Lenovo, Intel Qualcomm and Huawei. Next to leveraging its own resources, Unisound extensively leverages the knowledge of external developer by allowing them to create programs for its IoT platforms and devices. Unisound provides open source developer tools and guidance on its website (Unisound, 2019).

What differentiates Unisound from its competitors is its proprietary and patented voice recognition chip. It allows programs to accurately and quickly understand semantics, connect is with a user profile and synthesis text to speech.

While the company’s core product is a solution for the business-to-consumer segment, most of Unisound’s customers, if counted in groups, are business-to-business customers. Its education solutions are sold to schools, its medical solutions are sold to hospitals and its car solutions to car manufacturers and original equipment manufacturers (Unisound, 2019). While it is not explicitly stated on their website, it can be assumed that it tries to maintain strong customer relationships with large business customers and keep start-ups and scale-ups that soon might opt for expanding their solution by voice control, at arm’s length.

The company’s revenue was estimated to be 13 million Euro, i.e. 100 million yuan, in 2018 (Yelin, 2018). Costs are expected to have exceeded the 13 million Euro revenue as the company invested a lot in R&D. However, over time costs are expected to settle at around 80% of revenue (Damodoran, 2018).

Customer Involvement

While, to the best of my knowledge, Unisound is not planning to involve customers for feeding its voice recognition systems for instance, the company’s open source developer tools can be seen as crowd-sourcing customer knowledge (Olson, 2013). Moreover, data collected, showing when and how users engage with the voice recognition and AI systems can be used. While many aspects, such as the specifics of what is said to whom and when may not be used for analytics, other parts of customer data can be used to further improve the products and services.

Literature on crowd sourcing

Blohm et al. (2018), finds 4 archetypes of crowd sourcing of which Unisound can be awarded to the “open collaboration” type. It invites contributors to team up to jointly solve complex problems that require input of many contributors. By providing extensive documentation, multiple software downloads such as SDK and helping developers to manage their applications, Unisound assures quality and regulates the use of the open source platform as suggested by Blohm et al. (2018). However, neither does the company provide incentives to developers nor does it provide support through coaching, tutorials or on-boarding. Blohm et al. also recommends to market the solutions as crowd-sourced, which Unisound does.

Moreover, Nishikawa et al. (2017) find that companies which market their product as crowd-sourced will have increased market performance. Their experiment finds that the performance can go up by 20%. Unisound does emphasize their use of crowd-sourcing solutions on one of its landing pages that visitors will find even if they do not browse to the “developers” section.

Lastly, Schlaeger et al.(2018), emphasize the importance of customization. Unisound does to my knowledge not close the feedback loop from customers to developers extensively enough to help developers customize solutions. The data analytics board is kept rather simple by tracking engagement but direct communication about customer wished for changes is not facilitated by rating systems and other functions yet (Unisound, 2019)

Efficiency of the Business Model

Overall it can be concluded that Unisound has a well-functioning and thought through business model that can be assumed to create the desired results. The revenue and cost structure as well as the key activities and partners match with the value proposition and expectations of an R&D driven company. The focus on its in-house hardware improvement and out-sourced product development seems efficient and is expected to succeed. However, incentives for developers should be created to increased developer input. Moreover, Unisound could think about tracking customers attempts to engage with the systems that failed to improve it.


Blohm, I., Zogaj, S., Bretschneider, U., & Leimeister, J. M. (2018). How to manage crowdsourcing platforms effectively?. California Management Review60(2), 122-149.

Damodoran. 2018. Retrieved on 12.03.2019 at http://pages.stern.nyu.edu/~adamodar/

Nishikawa, H., Schreier, M., Fuchs, C., & Ogawa, S. (2017). The value of marketing crowdsourced new products as such: Evidence from two randomized field experiments. Journal of Marketing Research54(4), 525-539.

Schlager, T., Hildebrand, C., Häubl, G., Franke, N., & Herrmann, A. (2018). Social product-customization systems: Peer input, conformity, and consumers’ evaluation of customized products. Journal of Management Information Systems35(1), 319-349.

Olson. 2013. Retreived on 11.03.2019 at https://www.researchgate.net/publication/257704728_Crowdsourcing_and_open_source_software_participation

Unisound, 2019 Retrieved at 05.03.2019 on https://www.unisound.com/usc.html

Yelin. M, Zhanqu Z. and Quijan H. (2018) Retrieved at 05.03.2019 on

Co-creation through Onderling

Your winter tires get stolen from your garage. That is a bummer! Luckily, you have a household insurance policy. You file a claim at your insurance company but guess what? Your cars belongings are not covered by this insurance (Gaastra and Lasthuizen 2013). That does not sound very logical right? Well that is what the majority of the people on Onderling, an initiative of Dutch insurance company FBTO, also agreed upon. And that is why FBTO ended up paying out the money still (Emerce 2016). 

In order to innovate successfully, companies are increasingly seeking for new product or service ideas outside their boundaries (Nishikawa, Schreier, Fuchs, Ogawa 2017). Online communities are of increasing importance to businesses as they give companies new ways to interact with their consumers and can be used as input to innovate the offerings of a company (Ren et al. 2012).With the establishment of Onderling, FBTO tries to innovate beyond the existing way of doing business, making an attempt to address the problem arising between consumers and their insurance company.  Jeppesen Lakhani (2010) argue problem-solving effectiveness is vital to superior organizational performance. The goal of FBTO is to bring consumers and the company closer together. On the online platform everyone can join in the conversation and vote for real, actual claims and statements about insurances (Emerce 2016). 

This is how it works: you report a loss. When this loss is not insured according to the conditions, people insured at the company and employees of the firm have the opportunity to present their claim to the community on onderling.nl– experts already made the decision at this point. The community has the option to vote whether a claim should be paid and add their reasoning. For instance, someone could say the conditions do not classify this case clearly or it should be an exception to the rule. If 60% of the community decides the claim should get paid out, that is what will happen. Additionally, FBTO reassesses if the conditions as they designed it should be adjusted. This way, people help FBTO improve their products, communication and services (Emerce 2016; Gaastra and Lasthuizen 2013; Kruiper 2013) In summary, following the value co-creation framework of Saarjärvi, Kannan and Kuusela (2013), value is created by reassessing rejected claims and improving offerings from the gained insight provided by consumers. This value is created through B2C, in the form of re-evaluation and through C2B in the form of opinions and ideas. The mechanism used for co-creation is co-development, where FBTO can improves its offerings and gets to know what is important to their customers (Saarjärvi, Kannan and Kuusela 2013).Essentially, by providing feedback to improve offerings, they become part of the production process (Tsekouras 2019). 

The platform created by FBTO can be seen as a form of social computing, which is concerned with the intersection of social behavior and computational systems. The platform is a modern example of a technology giving rise to new ways of co-creation and interaction between companies and consumers (Oestreicher-Singer and Zalmanson 2013). FBTO created the platform to regain the trust of consumers and enhance transparency in the insurance industry, shifting from a service centric business to a customer centric business (Tsekouras 2019).The online community can provide users with useful informationm, support or  it can be a venue for discussion (Ren et al. 2014).The latter is the main strength of the website. The more people give their opinion, the more it becomes visible what people find important when it comes to insurance. With these insights FBTO can adjust their offerings to the needs of the customer. Even though the concept sounded promising, in the beginning the question was whether the concept would be successful. Would the insured be people loyal to each other and vote to pay out the money for every case? The opposite was true. Customers appeared to be critical and often agree with the choices of FBTO (Kruiper 2013).

According to Dellaert (2017),  FBTO’s system design could be efficient since it attempts to maximize joint payoffs for both the company as well as the customers. So, do customers see the added value of the new concept? Research shows they do. As you can see in the graph alongside, every aspect is assessed more positively after the implementation of Onderling (Gaastra and Lasthuizen 2013). Furthermore, the last few years FBTO has been declared most customer-friendly insurance company of the year multiple times. Overall, it seems customers see the added value of the concept. However, as with any business idea, FBTO experiences some challenges. The analysis also pointed out respondents were not very familiar with the platform. Only 23% of the people insured at FBTO ever visited the website of which 16% felt like voicing their opinion (Gaastra and Lasthuizen 2013). Furthermore, the biggest challenge is to involve the customers.Community engagement plays a primary part in creating sustainable competitive advantage,yielding higher profits and gaining loyalty from consumers (King, Racherla and Bush 2014).It is important to find users that have an high attachment to the community (Ren et al. 2014) Ren et al. 2014 highlight that a key downfall for companies is to attract the critical mass and engage them. This is no different for Onderling. When you want to let customer think along and incorporate their ideas, this demands organizational commitment. It is one thing to les customers think along, but the feedback from the community has to be processed and something has to be done with it. This means customers have to be top priority (Ren et al. 2014). On the one hand, the objectives of the organization have to be met, on the other hand it is extremely important task to represent the interests of the community members (King, Racherla and Bush 2014). Although it is proven that customer input did actually contribute to the improvement for products and services, it is not always easy to show employees of the firm the added value of customer interaction and to motivate them to actively support the community(Gaastraand Lasthuizen 2013).

So, what is next? To stay relevant, FBTO keeps experimenting with new ways of doing business that go beyond their existing boundaries. In 2016, FBTO started a trial where customers could decide for themselves what they wanted to insure, without policy conditions (Emerce 2016). In case of damage, the crowd would decide if you get your money or not, in a similar way as Onderling. The first trial did not gave the desired results but FBTO will try to keep innovating and serve their customers in the best way possible. Just like Henry Ford, the founder of the Ford Motor Company, once said about co-creation “Coming together is a beginning, staying together is progress, and working together is success” (Sanders and Stappers 2016).


Dellaert, B. G. (2017). The consumer production journey: marketing to consumers as co-producers in the sharing economy. Journal of the Academy of Marketing Science, 1-17.

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Tsekouras, D. (2019) Lecture 1: value co-creation.

Just say ‘go’ to your kids, with ‘Gokid’ ridesharing..

Imagine yourself rushing home after a busy workday, hoping you do not hit traffic, so you can pick up your kids from school just in time to shuttle them back and forth to sports, friends or other activities, and finally drop them off at home. For parents it often feels like a full-time job besides there existing job. Although, our transportation industry has changed substantially in the past few years with the emergence of major peer-to-peer car services such as Uber or Lyft, there is still no easy way to organize kid’s carpools today.

Ridesharing with GoKid

The perfect solution: GoKid. This New York based start-up founded in 2010, meets this growing need for better children’s transportation through building a mobile application that enables parents to share carpooling responsibilities with a network of friends, families and neighbours they know and trust. An app that not only saves time and money for parents, but also reduces traffic congestion. GoKid is known for its free ride set-up whereas other ridesharing services for kids, like Zum or HopSkipDrive, charges per ride and use paid drivers. More importantly, however, the most fascinating thing about GoKid is the way they actively involve parents and caregivers to build a carpool community based on trust (GoKid, 2018).

How does it work for parents and schools?

GoKid is a mobile application and software as a service (SaaS) solution that serves both parents and schools. Differently from ridesharing services, like HopSkipDrive, GoKid works with an invitation-based voluntary system in which parents or caregivers are the drivers instead of paid drivers. Families can sign-up for GoKid within four basic steps: setting up a family account including parents, children and residential details; crating a carpool with location and time specifications; inviting other families or caregivers to join the carpool and lastly, sign up to drive carpools that suit your schedule best (Waite, 2018). In this way, families do not only save time, but they also save a minimum of 60% in transportation costs (Clark, 2018). However, a big barrier for parents to set up school carpools is that they often do not know who in their child’s class lives nearby or has the same agenda (GoKid, 2018). GoKid overcomes this barrier by providing a secure portal ‘GoKid Connect’, in which data is shared by schools or (sport) teams, to enable parents to reach out to other families who live in the neighbourhood and have kids in the same class (Dhakappa, 2018). Hence, GoKid offers a business-to-business solution that solves the biggest issue with school transportation (GoKid, 2018).

Business Model

GoKid uses a multi-sided market model. On the direct to customer side, there is a freemium model which gives parents free access to features such as, setting up carpools and have an optimized route for carpooling which avoids traffic. The premium version, GoKid Pro, includes additional features such as the ability to sync the carpools with the parents’ calendars and in-app messaging with other families in the carpool group for a monthly or annual subscription. On the business to business side, schools and organizations use the GoKid Connect for an annual subscription fee.

GoKid employs a consumer co-production network, as it shifts the power of value creation to stakeholders in two different ways, so that consumers and schools or teams create most of the value. On one side, parents of caregivers directly produce value for other families by initiating to share rides with families of whom the kids need to go to the same destination (Dellaert, 2018), by acting as service providers. However, families that consume the carpool service by letting other parents or caregivers drive their kids, need to act like service providers as well when it is their turn to ride. In this way, the platform enables parents to reclaim valuable time and save transportation costs. On the other side, schools or teams provide value to consumers (i.e. families) and themselves by sharing their databases with GoKid which helps families to connect with each other and set up carpool groups. Also, they create value for themselves as the shared-ride solution helps them to retain families that otherwise might have chosen to enrol in another school and it reduces the number of absent children (GoKid, 2018).

Moreover, GoKid’s value creation goes even further through building communities as the business model highly depends on trust. First, Gokid tries to create member attachment by featuring in-app messaging which allows parents to easily contact each other and establish trusted relationships. Interpersonal communication stimulates bond-based attachment and eventually attachment to GoKid’s online community (Ren et al., 2012). Furthermore, bond-based attachment is stimulated as carpooling allows parents and children to have one-on-one interactions with each other resulting in a valuable opportunity for socialization and development of friendships (GoKid, 2018). Member attachment is very important for GoKid’s online community, as the platform strongly depends on network affects. Hence, carpool creators (e.g. parents or caregivers) need to be highly active participants in the carpool themselves to produce value and receive value in return, as GoKid’s premise is inherently viral. The more families participate within a carpool group and initiate to drive their kids and other’s kids to a certain destination (i.e. producers), the more valuable the network is for other families to join the platform, because more rides can be shared reducing the total number of rides each family have to make for their kids (i.e. consumers).

Efficiency of the model

There is growing demand from working parent for safe and efficient shared model child transportation, with little time for complex ride schedules. GoKid’s current system is not only beneficial for parents or caregivers and school in multiple way, but for the whole society as well. On the one hand, families benefit as they save time, due using GoKid for the coordination of carpooling schedules and carpooling, and money due reduced transportation costs. Moreover, the app solves an information gap for families by sharing data collected from schools and teams. On the other hand, schools benefit as GoKid reduces the number of absent children with 30% and makes it harder for parents to switch their children to another school due to the community they have built. The society benefits because there are less vehicles on the road decreasing traffic congestion, and consequently gas pollution which positively effects air- and water quality (Clark, 2016). Finally, GoKid itself benefits from their premium subscriptions, the collection of data (e.g. driver routes, traffic congestion) and their positive contribution to the environment which strengths their image (Waite, 2018).

GoKid has clear internal rules and regulations to ensure the safety of kids, such as behavioural guidelines and rules regarding licenses and car seats (GoKid Terms, 2018). Unlike HopSkipDrive, users of the service are fully responsible for all liabilities relating thereto. Because carpool groups consist of multiple families that know and trust each other, there are no legal measures that drivers most go through assuming that everyone wants their kids to be safe. However, to guarantee this safety for the children, GoKid requires that the parent driving each carpool also has their own kids in the car. Besides that, drivers must abide the traffic laws that apply the country in which they drive (Lemcke, 2016).  

What brings the future?

GoKid is planning to expand its product offerings by integrating their technology into vehicles through partnerships with Bosch and InMotion (Dhakappa, 2018). In addition, the company aims to work with more partners to allow users to sync their schedules from other apps in order to create a seamless carpool set up from existing events or corporates. Koslowski, vice president of the research firm Gartner, Inc., believes that approximately 20% of the vehicles in urban areas will be shared-use vehicles by 2025 (GoKid Team, 2018). This leaves high potential for GoKid to grow their user base and revenue streams in other countries, as GoKid is thinking big and thinking global (GoKid, 2018).


Clark, A. 2018. Efficient school transportation with GoKid to manage traffic congestion. [Online] Available at: https://www.gokid.mobi/efficient-school-transportation-with-gokid-to-manage-traffic-congestion/

Dellaert, B.G.C. 2018. The consumer production journey: marketing to consumers as co-producers in the sharing economy. Journal of the Academy of Marketing Science, forthcoming, 1-17.

Dickey, M. R., 2019. Zūm, a ridesharing service f[or kids, raises $40 million. [Online] Available at: https://techcrunch.com/2019/02/28/zum-a-ridesharing-service-for-kids-raises-40-million/

Dhakappa, B. 2018. GoKid – Making Kids Carpooling Easier. [Online] Avaiable at: https://techweek.com/gokid-newyork-kid-carpool/

GoKid Team., 2018. Is Car sharing the future? [Online] Available at: https://www.gokid.mobi/is-car-sharing-the-future/

GoKid Team., 2018. How GoKid compares to child driving services. [Online] Available at: https://www.gokid.mobi/how-gokid-compares-to-child-driving-services/  

GoKid Team., 2018. Best child transportation tips for busy parents in Chicago. [Online] Available at: https://www.gokid.mobi/best-child-transportation-tips-for-busy-parents-in-chicago/

GoKid., 2018. GoKid Carpool Safety. [Online] Available at: https://www.gokid.mobi/gokid-carpool-safety/

Lemcke, S., 2016. GoKid Carpooling101 – Carpoolingetiquette. [Online] Available at: https://www.gokid.mobi/gokid-carpooling101-carpooletiquette/

Ren, Y., Harper, F.M., Drenner, S., Terveen, L., Kiesler, S., Riedl, J. and Kraut, R.E., 2012. Building member attachment in online communities: Applying theories of group identity and interpersonal bonds. MIS Quarterly, pp.841-864.

Waite, M. 2018. How this app is providing community mobility solutions and personal parenting options. [Online] Available at: https://www.greenbiz.com/article/how-app-providing-community-mobility-solutions-and-personal-parenting-options

Depop, yet another online marketplace?

What is Depop, and how does it work?

The story of Depop begins in 2011 at H-FARM, the Italian startup accelerator headquartered in the Venetian lagoon. Fast forwarding to the early days of 2019, Depop has 15 million users worldwide and H-FARM signed the exit from the startup’s capital with a return of six times the initial investment (Terzano, 2019). Overall, one would not be mistaken to label Depop as one of the most successful startups ever launched on Italian soil. Headquartered in London, Depop is a mobile-based marketplace that allows its users to buy and sell new or second-hand clothes, accessories and designer items. Its community is primarily composed of creative, young people and is the app of choice of many established influencers. It can rely on a stable growth of 250.000 new users per month, a team of 100 people divided among offices in London, Milan, New York and Los Angeles (EconomyUp, 2018).

The user, rather than being a “simple” buyer, is offered a space become a full-fledged entrepreneur by opening a virtual shop. undefined

As the picture shows, the interface closely resembles the one of Instagram. In a similar manner, users can stay updated regarding new listings by following other vendors, they can interact with a new item on sale by liking it, they can gather further information by posting a comment and they can directly message the vendor to negotiate the sale price and agree on the shipping method (by mail or in person). Coming to the revenue stream, Depop manages to stay up running by charging sellers 10% of the item sale price, once the transaction has occurred. This means that, as long as a vendor has not sold the item, no costs are incurred to keep the listing online.

Since the large majority of users are first-timers when it comes to selling a product online, Depop provides each new user with an extensive “bible” containing best-in-class examples to add successful listings, such as how photos of the item on sale should be taken and which information needs to be included in the product description. This, and many more suggestions have a double function: not only do they increase the likelihood that “novel entrepreneurs” have a successful experience with the app, but also that the overall quality of listings on the platform is high. A key feature along these lines is the possibility of leaving reviews on user profiles, which stimulates community members to strive for a quality feed and quickly flags instances of inappropriate behaviour. Another way through which Depop is trying to increase the “fashion savviness” of its users is through collaborations with establishes vintage sellers or experts of the industry that open their own shop on the platform. Such collaborations are another way of sparking curiosity and inspiration for best practices, as well as creating an element of excitement and buzz towards the latest trends in the world of vintage clothing. Overall, such collaborations aim at making the community feel more alive and offers users an opportunity for personal growth within this industry (Witte, 2018).

Problems and suggestions for improvement

In order to grasp what Depop users are mostly unsatisfied with and to provide possible suggestions for improvement, I decided to conduct an in-depth overview of app reviews on the consumer review website Trustpilot. Below are summarised the main issues that users have been reporting.

The Explore section features non personalised listings

One of the features of Depop is the Explore section, which is curated by the app’s Editor Team and is used to promote the best listings on the platform according to the “in-house style guidelines” (Depop, n.d.). However, users might be viewing categories of items that they are just not interest in buying, therefore causing Depop to lose on potential sales revenue. To solve this issue, Depop should tailor the Explore section to each user. For instance, they could populate this section with products that belong to categories similar to the ones viewed by the user during previous searches, therefore matching her/his tastes.

Scammers are a very real issue

Like any online marketplace, Depop users are not immune to scams. Over time, there have been various reports of sellers being paid but not sending the item, sending an item which is different from the one listed, or sending a counterfeit item. Overall, Depop does not seem to be providing enough measures against such unfortunate events and seller reviews alone are not a strong enough deterrent. To improve the current situation, Depop could take inspiration from eBay. For profiles that have too little reviews or do not provide parcel tracking with their deliveries, the famous online marketplace holds the payment for 21 days (eBay, n.d.). If, after such time frame, the buyer has received the parcel and has not reporting any wrongdoings, the payment is unlocked.

Vendors cannot track the performance of their listings

The last issue that users are facing is connected to the amount of information they have available to measure whether they are performing well and if there is room for improvement. In this regard, the only measures available at hand are the amount of likes and comments a listing receives and the customer reviews received by the community. To provide a better service to the community and attract new users, Depop could provide analytics insights that describe a profile performance in a more detailed manner. For instance, by knowing which item is being viewed the most, a user could shift her/his focus onto a specific product category. As it stands now, the user base is left in the dark and is missing out on key measures that would help them improve their virtual shop and the overall quality of the listings that populate the platform.

Overall, a close cooperation with its users can bring tangible improvements to the platform. The three points listed above provide three of the most mentioned pain points and require immediate action in order to provide a personalised, safe and insightful experience to the users.   


Depop. (n.d.). How do I get featured on the Explore page?. [online] Available at: https://depophelp.zendesk.com/hc/en-gb/articles/360001792207-How-do-I-get-featured-on-the-Explore-page- [Accessed 10 Mar. 2019].

eBay. (n.d.). Funds Availability. [online] Available at: https://pages.ebay.com/seller-center/service-and-payments/funds-availability.html [Accessed 10 Mar. 2019].

Economyup. (2018). 20 milioni a Depop, la lezione per il retail: permettere al cliente di aprire il proprio store online | Economyup. [online] Available at: https://www.economyup.it/retail/ratail-10-milioni-depop-la-startup-vende-abiti-online/ [Accessed 10 Mar. 2019].

Terzano, C. (2019). Exit H-Farm da Depop, cedute quote per 2,5 milioni di euro – Startupitalia. [online] Startupitalia. Available at: https://startupitalia.eu/103334-20190118-exit-h-farm-depop-cedute-quote-25-milioni-euro [Accessed 10 Mar. 2019].

Trustpilot. (2019). Depop is rated “Poor” with 4.5 / 10 on Trustpilot. [online] Available at: https://www.trustpilot.com/review/depop.com?languages=en [Accessed 10 Mar. 2019].

Witte, R. (2018). How Depop is Leveraging Collaborations to Grow Their Community. [online] Forbes.com. Available at: https://www.forbes.com/sites/raewitte/2018/06/26/how-depop-is-leveraging-collaborations-to-grow-their-community/#cad41705a004 [Accessed 10 Mar. 2019].

battle of the food waste: ‘Too good to go’

An exploration of the different stakeholders and business model of famous food waste reduction app ‘Too Good To Go’

Ever walked into your local student dominated Albert Heijn and seen multiple fruits, vegetables and even full-made meals having a reduction sticker on them? Ever wondered what happened to these products if they don’t get sold by the end of the day? Well, I can burst your bubble, over 2.5 million tons of such products are thrown away annually in the Netherlands only (Toogoodtogo.nl/aboutus, 2019). As can be seen in the picture below (figure 1), households are the biggest spillers, followed by manufacturers, hospitality and retailers. This is very unfortunate because these products are foods that are on, or past, their expiration date, but are absolutely still fit for consumption. It would therefore be a pity for them to end up in the bin.

Figure 1: Distribution of spillage across the value chain (mst.dk/toogoodtogo, p.5)

Too good to go: the business model and market

In regards to the large food spillage annually, that adds up to one third of all food being produced going to waste, the app Too Good To Go was brought into life (toogoodtogo.nl/aboutus, 2019). Established in 2015 in Denmark, Chris Wilson and Jamie Crummie created the app in order to  reduce food spillage and CO2 production in Denmark. By having a 20% subscription rate of Danish citizens, Too Good to Go felt secure enough to spread their innovative idea to non-European countries and other European countries like the Netherlands (Toogoodtogo.nl, 2019). This proved to be increasingly successful as the app is based on a very simple, though effectively smart business model.

Since its launch in the Netherlands in January 2018, over 200.000 meals were saved through Too Good To Go (Boskma, 2019; Figure 2). When comparing the Dutch market to the Danish one, several differences can be found. Due to the large amount of plastic packed vegetables for example, in all shapes, mixes and sizes, in the Netherlands, products are barely preservable (Keyzer, 2019). In the Danish market, they are presented in crates. Therefore, ease of use stands central to the Dutch consumer market. Moreover, in the Danish market many initiatives already existed that battled food waste, many of them being subsidized by the government. In the Netherlands, on the contrary, little initiatives are up and running, besides Kromkommer and Instock, who never made the so called ‘frontpage’ due to little consumer interest (Keyzer, 2019).

So, back to the app, how does it function and what principles is it based on (Figure 3)? Too good to go makes sure that local horeca and retail owners are connected to local citizens, who are up for purchasing past-date food (Posthumus, 2019). Local shops can every day indicate whether they have left-over food and place it on the Too Good To Go platform. Consumers in return, can purchase these products in a ‘Magic Box’. On beforehand, they do not know what will be in the actual box (Boskma, 2019). By following this business model, consumers are helped by getting high quality food for a reduced price, whereas local shops receive more revenue (Loritz, 2019).

Figure 2: Screenshot of the Dutch Too Good To Go Instagram account disclosing that 200.000 meals were saved

Figure 3: Outlook of the app design

Value creation and the three perspectives

When elaborating on the business model we see that the value proposition for the consumer, or end user, is based on the previously spoken about reduced price. Here, the final selling price, which is between €3 and €5,  is based on one third of the original price. Another value proposition, which will mainly speak to environmentally conscious consumers, is that by purchasing a Magic Box a certain amount of CO2 is reduced (Boska, 2019). Therefore, environmental conscious, and even non-environmental conscious consumers are targeted and persuaded into buying high quality food against a reduced price. Overall, we see that the largest consumer base is presented by millenials, who are overall more aware and involved with the environment (Smith & Brower, 2012). As Too Good to Go connects with their consumers via the app and social media to stay in contact and provide a communication stream, they do well as again, millenials are the most frequent users of social media (Statista.com, 2019; Figure 4).

However, not only the value propositions for the end consumer are very clear, also the suppliers (the restaurants, local bakeries and so on) profit from their Too Good To Go presence. Products that would be disregarded to the bin, now are given a new life. Therefore, money that is invested in stock purchase or the production process is now being turned in revenue by reselling via Too Good To Go. Moreover, reducing food spillage is often on the bottom of the priority list (Keyzer, 2019). However, in many cases the wish to reduce waste is there but setting up a seperate incentive to resell stock is very money and time intensive. Too Good To Go gives a helping hand here. The app and its functions are very much adaptable in the business operations and easy in use (Keyzer, 2019). Besides gaining more revenue, compared to not using Too Good To Go, Too Good To Go can be a platform for end users to find and meet suppliers. Therefore, Too Good To Go functions as a marketing platform for suppliers that by being part of the app, can attract new consumers (Wang, Kim & Malthouse, 2016).

Lastly, we may view the platform perspective of Too Good To Go. The value creation process of Too Good To Go as a platform is mainly based on the making profits and reducing food waste. By its large customer base, the latter is no concern anymore. There is however room for growth and To Good To Go suspects to be self-sustainable in a few years. The first value proposition however, is not being met yet. Too Good To Go is still in its developmental phase in the Netherlands gaining more users by the day (Posthumus, 2019). At this very moment the cost structure is based on a percentage of the revenue each supplier makes, and differ across companies (Keyzer, 2019). By gaining more customers, and at the same time enlisting more suppliers to the app, Too Good To Go will become profitable on the longer term.

Figure 4: Distribution of Instagram users categorized by age groups (Statista.com, 2019)

Efficiency of the model

As can be stated, the model proves to be very efficient so far. The success of Too Good To Go lies mainly in the price reduction of the food that is being offered. The prices range from €3 to €5 respectively, leaving customers to buy quicker. From day one, Too Good To Go had little to no marketing budget but mainly grew by their online presence and positive WOM (Keyzer, 2019). Moreover, the app offers easy use, indicates distance from your current location to the supplier, and leaves you saving favourite restaurants to keep up to date to the latest offers. Also, the app offers not only restaurant food, you are also able to purchase your groceries from the supermarket or local bakery (Posthumus, 2019). Overall this seems very favourable. However, the efficiency of Too Good To Go’s model suffered some damage in the past. Before, no payment with IDeal was offered. Only payment with PayPal or creditcard was possible. As a relatively low percentage of Dutch consumers do have PayPal accounts or creditcards, some potential customers were not able to purchase from the platform. Too Good To Go fortunately made payment via iDeal possible in December 2018 (Keyzer, 2019). Another flaw in the efficiency of the model is the coverage / spread as well as the restaurant offerings on the platform. At this moment, Too Good To Go is very much present in cities, but lack presence in more rural areas. Also, it is very hard to keep up with the demand of the customers (Keyzer, 2019). Too Good To Go is rapidly growing and needs to close new deals with suppliers every day to stay up with the demand. This will prove to be tough, but by the success that Too Good To Go had so far, I expect that it will become as successful as in the Danish market.


Boskma, I. (2019). Too Good To Go gaat samenwerken met Albert Heijn en Jumbo. Retrieved from https://www.dutchcowboys.nl/nieuws/too-good-to-go-gaat-samenwerken-met-albert-heijn-en-jumbo

Keyzer, T. (2019). Deze app tegen voedselverspilling trok binnen 1 jaar 300 duizend gebruikers. Retrieved from https://www.businessinsider.nl/too-good-to-go-joost-rietveld/

Loritz, M. (2019). Copenhagen-based app Too Good To Go raises a further €6 million to eliminate food waste | EU-Startups. Retrieved from https://www.eu-startups.com/2019/02/copenhagen-based-app-too-good-to-go-raises-a-further-e6-million-to-eliminate-food-waste/

mst.dk (2019). Retrieved from https://mst.dk/media/91627/stian-olesen-too_good_to_go.pdf

Posthuma, W. (2019). Too Good To Go: ‘200.000 maaltijden gered van de vuilnisbak’. Retrieved from https://www.missethoreca.nl/restaurant/nieuws/2019/01/too-good-to-go-200-000-maaltijden-gered-van-de-vuilnisbak-101315444?vakmedianet-approve-cookies=1&_ga=2.235803906.261607741.1552232949-1156442447.1552232949

Smith, K., & Brower, T. (2012). Longitudinal study of green marketing strategies that influence Millennials. Journal Of Strategic Marketing, 20(6), 535-551. doi: 10.1080/0965254x.2012.711345

Statista.com (2019). Global Instagram user age & gender distribution 2019 | Statistic. Retrieved from https://www.statista.com/statistics/248769/age-distribution-of-worldwide-instagram-users/

Too Good To Go (2019). Retrieved from https://toogoodtogo.nl/nl

Wang, B., Kim, S., & Malthouse, E. (2016). Branded apps and mobile platforms as new tools for advertising, 2, 1-39.

The rise and fall of carpooling.com

Today’s sharing economy is characterized by the co-production of consumers, which offers a lot of new opportunities to companies that can exploit new ways of generating revenue (Dellaert, 2018). One of the promising trends that can be seen in our sharing economy is the increasing popularity of ridesharing practices (Statista, n.d.; McKinsey, 2017). More and more drivers decide to fill up their empty car seats and offer these spots on online ridesharing platforms to a growing number of riders. One of the early companies that successfully established its business model around ridesharing practices is Carpooling.com. Moreover, this company was in 2012 world’s largest ridesharing provider. However, only three years later Carpooling.com seized to exist and was acquired and folded into its competitor BlaBlaCar.

So… what went wrong? How could such a large and powerful platform go down so quickly?


Carpooling.com was created in 2001 by three innovative MBA students in Munich (Kite-Powell, 2012). These students captured the opportunity of an unmet need that existed in the automobile market. Moreover, gas prices were rising, congestion was worsening, and the majority of car owners was mostly driving in their car alone. To address these factors, Carpooling.com was launched with the idea to offer a platform through which drivers and riders are connected. Drivers could post their empty seats online and riders could book these seats. Consequently, drivers were driving less times by themselves, resources were shared, and an impressive impact was made on the CO2 emission (Jalali et al., 2017). For example, in 2011 the platform service saved drivers 27 million gallons of gas and prevented a CO2 emission of  205,000 tons (Kite-Powell, 2012).

In 2007, the platform was the largest carpooling platform of Germany. At this moment in time, the main revenue stream of the company came from advertising and key partnerships with associations or companies that were involved into the car industry (e.g. ADAC, the German automobile club). In 2009, the company received a capital injection and expanded its scope to other European countries. The company continued to grow due to the economic crisis, the improvement of mobile technology, and the emerging trend of the sharing economy. All of these factors increased the popularity of ridesharing and consequently led Carpooling.com to become the world’s largest provider of car-sharing services in 2012. In the following years, the company started some partnerships with the focus on sustainability and received another capital injection for its expansion towards the United States.

This sounds like a story similar to companies such as Facebook or Amazon that usually end with the facts on how great the company is doing at the moment (Haucap & Heimeshoff, 2013). However, in 2015, Carpooling.com got sold to its competitor BlaBlaCar, only three years after establishing its position as global leader. The question at hand is what mistakes the company made in order for it to go down so quickly; the answer can be found in some destructive adjustments in its business model.

Business model

Carpooling.com offered a platform at which drivers and riders were connected. Riders could choose which driver they wanted to join and could select from a variety of features, such as car size, comfort, and price. After each ride, drivers and riders could rate each other, building up a profiles of two-way reviews. According to Shen et al. (2015), a high rating results in increased attention and a better reputation; consequently, drivers and riders with a higher rating were more likely to be accepted for a certain ride. Furthermore, the users could use an in-app service that offered rides by public transport as a final step to get to their destination.

Revenue was generated through two different streams (Boyd, 2012). First of all, the company earned money by personalizing its software for bigger companies that wanted to use the service for their employees. The second income stream came from advertising, which was by far the largest revenue generator. Moreover, due to the large two-sided network effects that Carpooling.com was enjoying, the company’s user base kept growing and its website, on which ads were shown, was frequently visited by high numbers of users (Parker et al., 2005).

In 2013, Carpooling.com introduced a new revenue model in which a third income stream was added (Täuscher & Kietzmann, 2017). Moreover, the company became ‘greedy’ and started to charge its users a small fee per ride; this changed everything. Previously, payments were done in person after the ride. However, to be able to collect money from its users, the company now insisted that all users register themselves and pay the price of the ride up front and online. This led to a decrease in the perceived ease of use of the platform, because users had to put more effort in to book or sell their rides (Venkatesh & Bala, 2008). Consequently, a lot of clamor emerged on the platform and users heavily complained about the fact that a previously free service suddenly had been given a price label.

According to King et al. (2014), the importance of electronic word-of-mouth cannot be underestimated. Moreover, as a consequence of the dispersion of negative online posts about the company and the decreased user satisfaction, an initially gradient downstream of users started to appear who switched over to alternative carpooling sites. This downstream became increased rapidly, due to a loss of two-sided network effects (Parker et al., 2005). The less drivers that were active on the platform, the less riders could use carpooling services and vice versa. Consequently, Carpooling.com lost a large share of its users which weakened the company and made it vulnerable to the takeover from its main competitor BlaBlaCar.

Lessons learned

The case of Carpooling.com is a school example of having the wrong priorities and underestimating the power electronic word-of-mouth in our sharing economy. Consumer co-production offers many opportunities to companies and the ones that manage to exploit this successfully, receive high customer satisfaction and loyalty, and can enjoy terrific profits (Edvardsson et al., 2000). However, companies these days should prioritize their business focus on their customer, because customers have a great, potentially devastating, influence on the life expectancy of a firm.


Boyd, C. (2012). Carpooling the German way. PRI’s the World. Available from https://www.pri.org/stories/2012-02-08/carpooling-german-way

Dellaert, B.G.C. (2018). The consumer production journey: Marketing to consumers as co-producers in the sharing economy. Journal of the Academy of Marketing Science, pp. 1-17. Available from https://doi.org/10.1007/s11747-018-0607-4

Edvardsson, B., Johnson, M.D., Gustafsson, A. & Strandvik, T. (2000). The effects of satisfaction and loyalty on profits and growth: Products versus services. Total Quality Management, Vol. 11, Issue: 7, pp. 917-927. Available from https://www.tandfonline.com/doi/abs/10.1080/09544120050135461?casa_token=KmKFB3GtqnIAAAAA:BaQrIvERmOA1eY_EbNy5RkWw1f2UdUHgs684MmWGzQigOp_GrTIB5M4TT_cdmm-O5LDMhjkOEAX6

Haucap, J. & Heimeshoff, U. (2014). Google, Facebook, Amazon, eBay: Is the Internet driving competition or market monopolization? International Economics and Economic Policy, Vol. 11, Issue: 1-2, pp. 49-61. Available from https://link.springer.com/article/10.1007/s10368-013-0247-6

Jalali, R., Koohi-Fayegh, S., El-Khatib, K., Hoornweg, D. & Li, H. (2017). Investigating the potential of ridesharing to reduce vehicle emissions. Urban Planning, Vol. 2, Issue: 2, pp. 26-40. Available from https://www.cogitatiopress.com/urbanplanning/article/view/937/937

Käuscher, K. & Kietzmann, J. (2017). Learning from failures in the sharing economy. Management Information Systems Quarterly Executive, Vol. 16, Issue: 4, pp. 253-263. Available from https://www.researchgate.net/profile/Karl_Taeuscher/publication/321747580_Learning_from_Failures_in_the_Sharing_Economy/links/5a2f8f04aca2726d0bd6eafc/Learning-from-Failures-in-the-Sharing-Economy.pdf

King, R.A., Racherla, P. & Bush, V.D. (2014). What we know and don’t know about online word-of-mouth: A review and synthesis of the literature. Journal of Interactive Marketing, Vol. 28, pp. 167-183. Available from https://www.sciencedirect.com/science/article/pii/S1094996814000139

Kite-Powell, J. (2012). Germany’s Carpooling.com proves rideshare works. Forbes. Available from https://www.forbes.com/sites/jenniferhicks/2012/06/08/germanys-carpooling-com-proves-rideshare-works/#50a130d358d2

McKinsey (2017). Cracks in the ridesharing market – and how to fill them. McKinsey Quarterly. Available from https://www.mckinsey.com/industries/automotive-and-assembly/our-insights/cracks-in-the-ridesharing-market-and-how-to-fill-them

Parker, G.G. & Van Alstyne, M.W. (2005). Two-sided network effects: A theory of information product design. Management Science, Vol. 51, Issue: 10, pp. 1449-1592. Available from https://pubsonline.informs.org/doi/abs/10.1287/mnsc.1050.0400

Shen, W., Hu, Y.J. & Ulmer, J.R. (2015). Competing for attention: An emperical study of online reviewers’ strategic behavior. MIS Quarterly, Vol. 39, Issue: 3, pp. 683-696. Available from https://www.researchgate.net/publication/267250558_Competing_for_Attention_An_Empirical_Study_of_Online_Reviewers’_Strategic_Behavior

Statista (n.d.). Ridesharing services in the U.S. – Statistics & Facts. Webstite Statista. Retrieved at 11-03-2019 from https://www.statista.com/topics/4610/ridesharing-services-in-the-us/

Venkatesh, V. & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, Vol. 39, Issue: 2, pp. 273-315. Available from https://onlinelibrary.wiley.com/doi/full/10.1111/j.1540-5915.2008.00192.x


Todays competition in many industries is like the Red Queen’s race: “It takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!”. This chapter of Lewis Carroll’s book Through the Looking-Glass (1871),describes the situation in which Alice is chased by the Red Queen and even though she is constantly running, she is only remaining the same spot. This symbolises the fierce race of competition in the current economy, as companies must pull out all the stops, just to stay relevant in the market.

When the book was written, in 1871, the solution to get rid of the Red Queen was to run twice as fast, but in todays economy you should run twice as smart to win the race. In an economy where disruption is not an exception anymore, you are always one innovation away from getting wiped out (Armit & Zott, 2012)

While you are reading this article on consumervaluecreation.com, you are actually the witness of the outcome of the disruptive transformation of journalism. How did journalism transform from a mass production of  newspapers and magazines to an extensive supply of co-created platforms like this? Diamandis and Kotler (2016), from the Singularity University have developed a chain reaction of Six Ds, which lead to exponential growth and disruption. There are six key steps in exponential growth of an organization: digitization, deception, disruption, demonetization, dematerialization and democratization.

Figure 1: A visual representation of the 6 Ds


A few decades ago, journalism existed of the mass production of physical newspapers and magazines. It provided the reader with a limited amount of identical information, which was in a fixed ordering sold to the mass market. With the rise of the internet, journalism is no longer based on pressing longitudinal articles in a magazine, but by sharing the information represented in ones and zeros, journalism has changes into a technology and entered the exponential growth.


When something is digitized, the initial period of growth is deceptive. As it is an exponential growth, it takes very long before you grow from 0,01 to 2, but 2 quickly becomes 16, which becomes 16.000 impressively fast. Internet already existed in 1990, the first commercial newspaper was online in 1996 (Van de Heijden, 2019), and the first weblog (also called blog) in The Netherlands went life in 1997, but the online journalism is only booming since 2013 (Bakker, 2018).

Figure 2: Deception and Disruption


A market is disrupted when the new technology for the niche market becomes regular for the mainstream customers and therefore outperforms the established alternatives (Christensen, 1997). Disruption takes place when something is underperforming in first dimension, but overperforming in the secondary dimension.

The first dimension is based on the elements that are highly valued by the mainstream customer. For journalism these elements were especially the guaranteed quality of the news and the articles, trust based on expertise and having a physical newspaper or magazine of paper. In the traditional way of journalism, these aspects were captured and online journalism is underperforming on these aspects as everyone can post something on the web, there is no guarantee of objectivity or quality.

Before the existence of online journalism, it took at least twelve hours before a happening could be shared via the newspapers or flyers. Nowadays, events are spread before you know it, and it is a matter of seconds before the whole world has access to the news. Also, in the case of physical magazines and newspapers, the customer cannot personalize what articles are in there and therefore the customers pays for content they are not interested in. Via the internet the customer is not paying for the articles they are not reading. This are the two main secondary dimension aspects in which the online journalism is overperforming compared to the traditional journalism.

As the preferences of the mainstream market are changing and the boundaries are moving, online journalism is becoming more and more present in the market. This is resulting in less and les official journalist (Oremus, 2018) and more journalistic online platforms.

Figure 3: The amount of digital newspapers in the Netherlands on national (black) and regional (pink) level per year (Bakker, 2018).

As the platforms introduces a self-controlling mechanism, there is an increasing quality guarantee and as the social norms are changing, the trust-issues are decreasing. The online journalism disrupted the market.


Money is increasingly detached from the reckoning as online journalism becomes cheaper or even free. Nowadays, customers use the web and with a few clicks they will find a dozen of articles of their interest without paying anything. On the other hand, publishing an article used to be very expensive as it had to be checked by several people, printed on paper and then distributed to the market, but online people can upload their article or blog for a small amount of money or even for free.


The magazine- and newspaper-publishers that pressed their items and distributed their product via the mailman are now focussing on their online versions and offering subscriptions on their online version only. In this way the expensive mass production is replaced by an app on the smartphone, all fitting in pocket of every customer.


The more and more people have access to it and the broadcast of news and articles is no longer only for large organizations, but for everyone. Through online platforms, everyone with access to the web can become a journalist. This could also be seen as the outsourcing of the task of writing articles, by creating microtasks the crowd becomes the source of journalism (Tsekouras, 2019). This also includes the counterpart; as journalism is cheap and often even for free, reading news and articles is no longer for the wealthy, but for the mass market with access to internet. Business functions are no longer product-centric, but changed toward a customer-centric approach (Vargo and Lusch, 2004).

In conclusion we could state Red Queen’s Race of journalism is won by the digital platforms. By running in a smart way, though the six Ds of Diamandis and Kotler (2016), platforms like consumervaluecreation.com will be leading in the market of journalism and therefore escape from the Red Queen.


Armit, R. & Zott, Chr. (2012) Creating Value Through Business Model Innovation. MIT Sloan Management Review, Vol. 53 (3), 41-49.

Bakker, P. (2018, April 18). Digitale oplage kranten blijft fors stijgen. Retrieved from Stimuleringsfons voor de Journalistiek: https://www.svdj.nl/de-stand-van-de-nieuwsmedia/digitale-oplage-kranten-stijgen/

Carroll, L. (1871). Through the Looking-Glass.

Christensen, C.M. (1997). The Innovator’s Dilemma: When New Technologies Cause Great Firms to   Fail. Boston: Harvard Business School Press.

Diamandis, P.H. & Kotler, S. (2016). Bold: How to Go Big, Create Wealth and Impact the World. New York: Simon & Schuster.

Oremus, F. (2018, October 4). Verhouding communicatieprofessionals-journalisten. Wat zeggen de cijfers? Retrieved from Villamedia: https://www.villamedia.nl/artikel/verhouding-communicatieprofessionals-journalisten.-wat-zeggen-de-cijfers

Tsekouras, D. (2019, Februari 14). Customer Centric Digital Commerce Lecture 3.

Van der Heijden, Chr. (2019, February 24). 25 jaar digitale transitie van de journalistiek 1: Opmaat. Retrieved from Journalismlab: https://www.journalismlab.nl/25-jaar-digitale-transitie-van-de-journalistiek/

Vargo, S.L. and Lusch, R.F. (2004), Evolving to a new dominant logic for marketing, Journal of Marketing, Vol. 68, (1), 1‐17.

Gamification: The Holy Grail of Customer Engagement?

Do you like learning languages? If so, you are probably familiar with Duolingo, a compelling example of the power of gamification. Duolingo, one of the world’s most popular language-learning platforms, sets itself apart by pouring gamification into every lesson. At Duolingo each lesson forms a bite-size skill that makes you feel like you are playing a mini-game. You score points when you give the right answer, while you lose hearts when you make a mistake. You are challenged to race against the clock, while you are stimulated to maintain your streak count. Like in many games, you can earn rewards, such as “lingots”, Duolingo’s own virtual currency, with which you are able to unlock even more content on the platform. The result: An engaged community of 300 million users who learn on average in 34 hours the equivalent of one full semester of college (Vesselinov & Grego, 2012).

An example of how Duolingo applies game elements in their lessons.
Source: https://yukaichou.com/gamification-examples/top-10-education-gamification-examples/attachment/duolingo-gamification/

The gamification hype       

Gamification is defined as a design approach that is concerned with applying typical game elements, such as competitions, points and rewards, to non-game contexts (Murray, Exton, Buckley, Exton, & DeWille, 2018). Duolingo along with other exemplars, such as Nike+ Fuel, My Starbucks Rewards and SAP Community Network, boosted the global gamification hype that took off in 2010 (Yu-Kai Chou, 2018). But, like most other innovations, gamification followed the curve of Gartner’s Hype Cycle (Simões, 2015). In 2013, during the peak period of inflated expectations, companies were massively trying to adopt game elements, such as points, badges and leaderboards, into their services (Scicluna, 2017). However, in their endeavor to avoid falling behind, many companies rushed their solutions without carefully considering a logical underlying game design to create an engaging experience (Scicluna, 2017). As a consequence of this “bandwagon effect”, 2014 marked a period of disappointment, in which many gamified solutions failed (Broer, 2014). Ever since 2014 gamification has not been on Gartner’s Hype Cycle (Downer, 2018).

Is this a sign that we should forget about gamification or are we already at a plateau of productivity?

Gartner’s Gamification Hype Cycle
Source: https://medium.com/casumo/gamification-is-a-fad-shall-we-call-it-motivational-design-5c8c836f4fc8

The Science Behind Gamification

To understand the value of gamification we first have to understand the science behind it. In consumer behavior theory, products and brand attitudes are generally conceptualized along two dimensions: hedonic and utilitarian (Voss, Spangenberg, & Grohmann, 2003). The term hedonic stems from the Greek word hēdonē (ἡδονή), which translates to “pleasure” (Vocabulary.com, 2019). In ancient Greek mythology Hedone was also the goddess and the personification of sensual pleasure and enjoyment (George, 2018). Accordingly, in consumer behavior theory hedonic goods are defined as goods that are consumed for pleasure and enjoyment (Voss et al., 2003). Hedonic goods are bought for the sake of the goods themselves (Koivisto & Hamari, 2019). On the other hand, utilitarian goods are used for their instrumental-value (Liu, Santhanam, & Webster, 2017). They are used to reach a particular goal that is external to the good itself (Koivisto & Hamari, 2019). Consequently, utilitarian goods derive their usefulness from their practicality and productivity. From a motivational viewpoint the use of a hedonic good is characterized as an intrinsically motivated action, while the use of a utilitarian good is considered as an extrinsically motivated action (Koivisto & Hamari, 2019).

Just like goods, information systems can be classified as hedonic and utilitarian (van der Heijden, 2017). While information systems have historically been considered one-dimensionally as either hedonic or utilitarian, recent literature has recognized that information systems are often a mix of the two (Voss et al., 2003). Nowadays, information systems are increasingly designed from scratch to serve both hedonic and utilitarian needs to increase customer engagement (Koivisto & Hamari, 2019). The idea of such mixed systems is to cater a diverse set of motivational needs into one single motivational information system (Koivisto & Hamari, 2019). The goal of a motivational information system is “to achieve productivity through fun” (Hamari & Keronen, 2017) . However, as the undermining effect of external rewards shows, combining different motivational needs in an effective way can be a very challenging task (Burtch, Hong, Bapna, & Griskevicius, 2016).

This is where gamification comes into play. The theory of self-determination states that intrinsic motivation mainly derives from three motivational needs: competence, autonomy and relatedness (Liu, Santhanam, & Webster, 2017). Throughout the literature, games are widely recognized as a means to satisfy these three motivational needs (Koivisto & Hamari, 2019). Through gamification motivational information systems are able to satisfy these needs as well. Duolingo, for example, offers competence by creating a challenging environment that provides users with a feeling of mastery. Duolingo also offers a sense of autonomy through their divers set of lessons that provide users with a feeling of choice. Furthermore, Duolingo offers relatedness through the social components that allow users to both compete and cooperate with each other.

Not a silver bullet

The fact that so many gamification projects fail teaches us that gamification by itself is not a silver bullet for customer engagement (Post, 2014). As Gartner’s research vice present, Brian Burke (2014), put it:

“Poor game design is one of the key failings of many gamified applications today. The focus is on the obvious game mechanics, such as points, badges and leader boards, rather than the more subtle and more important game design elements, such as balancing competition and collaboration, or defining a meaningful game economy. As a result, in many cases, organizations are simply counting points, slapping meaningless badges on activities and creating gamified applications that are simply not engaging for the target audience.”

Besides the common pitfall of “pointification”, the merits of gamification also need to be legal and ethical (Werbach & Hunter, 2012). A grocery store owner in Iowa learned this lesson the hard way. He thought it was a good idea to motivate his workers by organizing a “fire-contest” (Fastenberg, 2011). While he promised a cash price to every worker that rightly guessed who would be fired next, he ended up paying for their voluntarily resignation (Miller, 2011).

Negligent gamification could also lead to manipulation and exploitation (Werbach & Hunter, 2012). Laundry workers of the Disneyland hotel in California, for example, renamed their leaderboard system “the electronic whip” (Allen, 2011). After the system was implemented, the progress of the workers was continually tracked and prominently shown on huge flat screen TVs in laundry rooms (Allen, 2011). The system had a large impact on the competitiveness of the working environment (Werbach & Hunter, 2012). Employee relationships started to intensify, lower-ranked employees began to worry about their jobs, and some workers even stopped using their bathroom breaks to increase their rankings (Werbach & Hunter, 2012).

Disneyland’s Electronic Wip Persiflage
Source: https://boingboing.net/2018/11/03/neotaylorism.html


So, should gamification be used as a means to increase customer engagement? As with many business issues, the answer is: “it depends”. We have learned that gamification is not a silver bullet and that implementing it may lead to unforeseen consequences. Yet, if prudently designed, gamification is able to significantly increase customer engagement.

Companies willing to adopt gamification should first learn how to think like game designers. Before embracing game elements, companies should have a thorough understanding of the rules of motivation. To obtain these capabilities companies could consider hiring talented game designers and consider applying one of the many gamification design frameworks out there.

We can conclude that gamification might not be the holy grail of customer engagement, but it is definitely not going away soon either. While the hype maybe over, we probably just started to tap the plateau of productivity.

I hope that this article has given you a different perspective on motivation. Do you know great success stories of gamification? Please let them know in the comment section below!


Allen, F. E. (2011). Disneyland Uses “Electronic Whip” on Employees. Retrieved March 11, 2019, from https://www.forbes.com/sites/frederickallen/2011/10/21/disneyland-uses-electronic-whip-on-employees/#4fcf99e51b32

Broer, J. (2014). Gamification and the Trough of Disillusionment. Mensch & Computer 2014 – Workshopband, 389–396. https://doi.org/10.1524/9783110344509.389

Burke, B. (2014). Gamify: How Gamification Motivates People to Do Extraordinary Things. Retrieved from https://www-oreilly-com.eur.idm.oclc.org/library/view/gamify-how-gamification/9781937134860/chapter010.html

Burtch, G., Hong, Y., Bapna, R., & Griskevicius, V. (2016). Stimulating Online Reviews by Combining Financial Incentives and Social Norms. Ssrn, (March 2019). https://doi.org/10.2139/ssrn.2848398

Downer, K. (2018). Gamification – From Player to Professional -. Retrieved March 11, 2019, from https://ps-ee.com/gamification-from-player-to-professional/

Fastenberg, D. (2011). Workers Quit After Boss Starts “Guess Who Gets Fired Next” Contest – AOL Finance. Retrieved March 11, 2019, from https://www.aol.com/2011/10/07/workers-quit-after-boss-starts-guess-who-gets-fired-next-conte/?guccounter=1&guce_referrer_us=aHR0cHM6Ly93d3cuZ29vZ2xlLmNvbS8&guce_referrer_cs=YIYuo2RgpawxIO-SDlI7FA

George, J. J. (2018). Greek Mythology: Eros & Psyche | Owlcation. Retrieved March 11, 2019, from https://owlcation.com/humanities/Greek-Mythology-Eros-Psyche

Hamari, J., & Keronen, L. (2017). Why do people play games? A meta-analysis. International Journal of Information Management, 37(3), 125–141. https://doi.org/10.1016/j.ijinfomgt.2017.01.006

Koivisto, J., & Hamari, J. (2019). The rise of motivational information systems: A review of gamification research. International Journal of Information Management, 45(October 2018), 191–210. https://doi.org/10.1016/j.ijinfomgt.2018.10.013

Liu, D., Santhanam, R., & Webster, J. (2017). Toward Meaningful E Ngagement : a F Ramework for D Esign and R Esearch of G Amified. MIS Quarterly, 41(4), 1011–1034. https://doi.org/10.25300/MISQ/2017/41.4.01

Miller, D. (2011). Company that offered employees $10 to guess next worker to be fired | Daily Mail Online. Retrieved March 11, 2019, from https://www.dailymail.co.uk/news/article-2045027/Company-offered-employees-10-guess-worker-fired.html

Murray, L., Exton, C., Buckley, J., Exton, G., & DeWille, T. (2018). A Gamification–Motivation Design Framework for Educational Software Developers. Journal of Educational Technology Systems, 47(1), 101–127. https://doi.org/10.1177/0047239518783153

Post, R. (2014). Game on: could gamification help business change behaviour? | Guardian Sustainable Business | The Guardian. Retrieved March 11, 2019, from https://www.theguardian.com/sustainable-business/game-on-gamification-business-change-behavior

Scicluna, C. (2017). Gamification is a fad. Shall we call it Motivational Design? Retrieved March 11, 2019, from https://medium.com/casumo/gamification-is-a-fad-shall-we-call-it-motivational-design-5c8c836f4fc8

Simões, J. (2015). Using Gamification to Improve Participation in a Social Learning Environment. 4th International Conference on Personal Learning Environments, (November 2015), 169–186. https://doi.org/10.13140/RG.2.1.4253.0328

van der Heijden. (2017). User Acceptance of Hedonic Information Systems. MIS Quarterly, 28(4), 695. https://doi.org/10.2307/25148660

Vesselinov, R., & Grego, J. (2012). Duolingo Effectiveness Study. City University of New York, (December 2012), 1–25.

Vocabulary.com. (2019). hedonism – Dictionary Definition : Vocabulary.com. Retrieved March 11, 2019, from https://www.vocabulary.com/dictionary/hedonism

Voss, K. E., Spangenberg, E. R., & Grohmann, B. (2003). Measuring the Hedonic and Utilitarian Dimensions of Consumer Attitude. Journal of Marketing Research, 40(3), 310–320. https://doi.org/10.1509/jmkr.40.3.310.19238

Werbach, K., & Hunter, D. (2012). For the Win: How Game Thinking Can Revolutionize Your Business. Game Thinking. Even Ninja Monkeys Like to Play: Gamification, Game Thinking and Motivational Design. Retrieved from https://www.amazon.com/Win-Game-Thinking-Revolutionize-Business/dp/1613630239

Yu-Kai Chou. (2018). Top 10 Marketing Gamification Cases You Won’t Forget. Retrieved March 11, 2019, from https://yukaichou.com/gamification-examples/top-10-marketing-gamification-cases-remember/#.WvHlx1SpnyU

Teqoia: the platform for experts, not stars

Work has changed dramatically through digitalization. New forms of organizing work are gaining more and more attention. The emergence of peer-to-peer platforms, collectively known as the “platform economy,” has enabled people to collaboratively connect with each other and thereby link the demand for labour with its supply. Consumers have so far enthusiastically adopted the services offered by firms such as Uber, Lyft, and TaskRabbit (Zervas et al. 2017). These business operate as gig-economy platforms, formally defined as digital, on-demand platforms that enable a flexible work arrangement (Burtch et al. 2018).

The challenges of gig platforms

Although there are a lot of advantages for these gig platforms, there are also a number of challenges that lie ahead. One of the biggest challenges is to keep the work offered on the platform relevant. For the three abovementioned platforms, this is not really the case, because the work that has to be done is not that complex. However, for platforms as UpWork, where experts can offer their work, this is becoming increasingly challenging. When these online crowd experts want to have a viable long-term career option, they must be able to grow and continually refresh their skills (Suzuki et al. 2016). 

The downside of stars

Traditional workplaces make use of on the job training and internships to enable employees to develop their skills while providing financial support. Crowd workers, however, are disincentivized from learning new skills, because the time they spent on learning they are not working, which reduces income. Even if a worker does spend time learning new skills, platforms do not make it easy for the investment to pay off, as it is difficult to get hired for new skills. This is caused by the fact that most platforms are based on review systems, as ratings and reviews (Gupta et al. 2015). Users of platforms increasingly rely on online opinions and experiences shared by fellow users when deciding what products to purchase, or who to hire for a job (Shen et al. 2015). Because gig economy platforms have no ratings for the workers in their new skill areas, the possibility to get hired decreases. As a result, the skills of many workers remain static, and workers today often view these platforms as places to seek temporary jobs for their already existing skills, rather than as marketplaces for long-term career development (Suzuki et al. 2016). With online work is capable of expanding many full-time jobs, new business opportunities arise that integrate crowd work and career development. 


Since last year this gap in the market has been filled by the platform Teqoia IT Solutions, which has the aim to match supply and demand of labor. Teqoia makes technical knowledge and capacity of highly trained and specialized IT staff accessible to (inter)national clients. It has a clear focus on local for local, learning & development, and entrepreneurship. In the right balance this approach results in an optimal result for all parties involved and there is a win-win situation in which the platforms, workers and suppliers reinforce each other (Teqoia 2019).

The platform doesn’t work with review systems but gives a guarantee that each individual on the platform does meet a certain standard. To realize that promise, they have the Teqoia academy, where different trainings are given to ensure that they keep up with the current changes in technology. Teqoia also offers the possibility to follow the teqoia masterclass to improve their services. This is a traineeship that, through various training courses and modules, ensures that the worker has the required skills within seven months. 

Business case

Like most gig economy platforms, the financial model of Teqoia is based on a commission fee for mediating between supply and demand. In terms of strategy, Teqoia is pretty unique. It has positioned itself between traditional employment agencies and purely digital gig platforms; the reasonably fixed group of workers, the training and the quality guarantee of a traditional business, but with self employed workers, as on many different gig platforms. Which ensures a more lean business, which is a main advantage over the traditional businesses (Aloisi 2015).

Downsides of Teqoia

So, the main strengths of Teqoia are their lean business model and their quality guarantee. However, the organization of a platform in this way also has its drawbacks. One of the downsides of this approach is that Teqoia can’t make use of network effects, as most platforms do, because all the workers must be tested and trained to meet the quality requirements. Other platforms have grown exponentially, partly because of the two-sided network effects. This implies that when the number of users one side of the platform increases, the other side will be attracted more as well. In the end, a greater number of users increases the value to each and thus the total value of the platform (Eisenmann et al. 2011).Another, more straightforward downside has to do with the cost of testing and training workers. Most gig platforms charge a commission fee of around the 15% (Aloisi 2015), which should therefore be higher at Teqoia to cover the costs of training and testing. 

Future of gig work

The use of review systems to measure quality of workers does not improve the expertise of gig workers on the long term. Therefore, other business models, as Teqoia, arise. However, Teqoia faces some challenges, the idea of not looking at reviews and star-ratings anymore but providing a quality label for workers seems plausible. So I think that the future of experts gig platforms no longer focusses on stars, but on expertise.

For those who are interested in the platform (unfortunately in Dutch only):


Aloisi, A. (2015). Commoditized workers: Case study research on labor law issues arising from a set of on-demand/gig economy platforms. Comp. Lab. L. & Pol’y J., 37, 653.

Burtch, G., Carnahan, S., & Greenwood, B. N. (2018). Can you gig it? An empirical examination of the gig economy and entrepreneurial activity. Management Science, 64(12), 5497-5520.

Eisenmann, T., Parker, G., & Van Alstyne, M. (2011). Platform envelopment. Strategic Management Journal, 32(12), 1270-1285.

Gupta, N., Martin, D., Hanrahan, B. V., & O’Neill, J. (2014). Turk-life in India. In Proceedings of the 18th International Conference on Supporting Group Work (pp. 1-11). 

Shen, W., Hu, Y. J., & Ulmer, J. R. (2015). Competing for Attention: An Empirical Study of Online Reviewers’ Strategic Behavior. Mis Quarterly, 39(3), 683-696.

Suzuki, R., Salehi, N., Lam, M. S., Marroquin, J. C., & Bernstein, M. S. (2016). Atelier: Repurposing expert crowdsourcing tasks as micro-internships. In Proceedings of the 2016 CHI conference on human factors in computing systems (pp. 2645-2656). 

Teqoia (2019). Jouw toekomst. Via: https://teqoia.com/jouw-toekomst/het-begint-bij-jou/

Zervas, G., Proserpio, D., & Byers, J. W. (2017). The rise of the sharing economy: Estimating the impact of Airbnb on the hotel industry. Journal of marketing research, 54(5), 687-705.

How feelings of pride and respect affect ongoing member activity on crowdsourcing platforms.

After a long day you are called in by your boss to meet her at her office. You are exhausted, because you have been working hard lately for a high status company. Your boss compliments you and is impressed with your work. At the end of that day, you leave the office with extra motivation to keep putting in the effort. This anecdote serves as an illustration of how traditional companies can motivate their employees to keep them happy and productive. Recently, the advancements in technology have made it possible for traditional firms to organize their work over the internet and source particular tasks to an online crowd of independent contractors referred to as crowdsourcing (Afuah and Tucci, 2012). Workers on so-called crowdsourcing platforms, like Amazon Mechanical Turk and Deliveroo, work on a voluntary basis as they are not formal employees of the company. Therefore, it is interesting to look at what drives this new generation of crowd workers in contrast to traditional employees to actively participate on these platforms as this is currently not well understood.

Nowadays, organizations use crowdsourcing for different purposes such as problem solving, idea generation, information pooling, or outsourcing tasks (Tsekouras, 2019). Companies use the crowd as they might be able to solve certain problems faster and cheaper than in house employees (Blohm et al, 2018). Hence, from a firms’ perspective it becomes evident to use the crowd as it allows for lower transaction costs, repetitive tasks that require human intelligence and keeping control over sensitive data by splitting up the tasks (Tsekouras, 2019). Although you might think you have never participated in a crowdsourcing task, most of you have even unintentionally. To illustrate, Google uses your search history to look for interesting keywords for ads (Kitter et al., 2008). 

From a crowd workers’ perspective, it is harder to trace the drivers. Why would you participate on a crowdsourcing platform? There are of course factors such as under- and unemployment which may drive people towards crowdsourcing platforms for obvious reasons such as money (Burtch et al, 2018). Nonetheless, there are also less straightforward motives such as glory, love, or a product reward as drivers for contribution (Tsekouras, 2019). To frame it from a customer-centric perspective, customers get the opportunity to speak their minds about product solutions and in that way reduce the costs of firms to obtain detailed consumer information (Tsekouras, 2019). In other words, you might benefit from the information pooling of companies. You might have an interesting feature for Apple that you want them to introduce in their new Iphone.

For the survival of a platform it is important to drive members for continuous cooperative behavior, referring back to the earlier mentioned voluntary nature. In a way, members of crowdsourcing platforms can be seen as a community in which attachment is crucial for success (Ren et al., 2012; Boons et al., 2015). Consequently, a study by Boons et al. (2015) was conducted to look into feelings of pride and respect as drivers of ongoing member activity on crowdsourcing platforms. The non-traditional work setting of crowd workers asks for a research method which is able to explain member activity on a voluntary basis. Therefore, the engagement model was used as it is capable of measuring cooperative behaviors in groups in a voluntary setting (Boons et al. 2015). The engagement model measures identification with the firm to increase activity as a result from perceived feelings of pride and respect. 

Think of the anecdote in the introduction, the compliment you got from your boss. You were positively evaluated by someone which made you feel respected (Boons et al., 2015). Furthermore, the organization is one with high regard which gives you a feeling of pride. Due to these two factors you are more likely to identify with your group of colleagues and the company. This identification gave you the extra motivation to keep putting in the effort.  However, according to Boons et al. (2015) it may be difficult to compare a crowdsourcing platform to a traditional firm as they are virtual organizations lacking the physical proximity and interaction. In contrast, they argue that it is still possible to use the engagement model as members are able to develop a sense of pride and respect based on an autonomous evaluation against personally held norms and standards (Boons et al., 2015). This is in harmony with initial thoughts of Ren et al. (2012) as they do not expect the identification process to be dependent on bonding with other members. Therefore, the engagement model is expected to fit the needs of this research.  

The authors collected data from a platform that matches organizations, that seek for idea generation, to its community of solvers. A survey was conducted amongst its members (n=153) who had participated on tasks and received feedback. The survey looked into the three earlier discussed items pride, perceived respect and organizational identification (Boons et al., 2015). These items suggest a positive cue which in turn could lead to active participation. The authors found that only pride was an important predictor of member participation (figure 1). However, the authors did not find support for perceived respect and organizational identification as predictors of ongoing member activity. Although, perceived respect and pride both were positively related to organizational identification (Figure 2). These findings implicate that the authors were able to use the engagement model in a non-traditional setting to find drivers on crowdsourcing platforms (Boons et al., 2015). Furthermore, they contribute to literature by suggesting that in a crowdsourcing setting the perceived organizational identification is inferior to pride for member activity. 

So, how can you increase pride to enhance members’ performance? As a platform leader you can benefit from this research by increasing members’ pride by communicating positive media attention about your platform. Your community will associate positive news items with the status of the organization as a whole thereby increasing members pride and activity. 

To conclude, crowdsourcing platforms differ a lot from traditional organizations in terms of interaction with workers. Therefore, finding out what drives them is important and was not well understood. However, Boons et al. (2015) build on the engagement model to find out what drives members’ activity influenced by feelings of pride and respect. They contribute to existing literature by successfully using the engagement model in another setting than traditional companies. Furthermore, they found support for pride as a driver for ongoing member activity.


Afuah, A., & Tucci, C. L. (2012). Crowdsourcing as a solution to distant search. Academy of Management Review37(3), 355-375.

Boons, M., Stam, D., & Barkema, H. G. (2015). Feelings of pride and respect as drivers of ongoing member activity on crowdsourcing platforms. Journal of Management studies, 52(6), 717-741.

Burtch, G., Ghose, A., & Wattal, S. (2013). An empirical examination of the antecedents and consequences of contribution patterns in crowd-funded markets. Information Systems Research, 24(3), 499-519.

Kittur, A., Chi, E. H., & Suh, B. (2008, April). Crowdsourcing user studies with Mechanical Turk. In Proceedings of the SIGCHI conference on human factors in computing systems(pp. 453-456). ACM.

Ren, Y., Harper, F. M., Drenner, S., Terveen, L., Kiesler, S., Riedl, J., & Kraut, R. E. (2012). Building member attachment in online communities: Applying theories of group identity and interpersonal bonds. Mis Quarterly, 841-864.

Tsekouras, D.K. 2019. Lecture 3: Crowdsourcing

Interpreting Social Identity in Online Brand Communities: Considering Posters and Lurkers


The increasing use of online communication and advertising practices has led to a rising interest in understanding the drivers and influencing factors of consumers in terms of their interactions with brands. The research paper of Mousavi et al. (2017) has set its focus on online brand communities (OBCs). These are defined as “specialized, geographically non-bound communities, based on a structured set of social relations among admirers of a brand” (Muniz & O’Guinn, 2001). OCBs were found to be marketing instruments that increase customer loyalty and commitment towards a brand (Hartmann et al., 2015). Until now, most research in this field had its focus on the behavior of active members (“posters”) in OBCs. However, so-called “lurkers” represent the vast majority of online communities (>90%). This is why recent research has become interested in finding out more about the motivations behind passively consuming information on online communities. The paper investigates this question and extends it with the examination of the effects of OBCs on brand commitment, positive word-of-mouth, and resistance to negative information.

What differentiates posters from lurkers?

The researchers base their reasoning on the theory of social identity formation: Social identity is a person’s sense of who they are based on their group membership(s).[i] According to the theory, there are two different routes of social identity formation (Postmes, Haslam, & Swaab, 2005):

The inductive route which has its basis in interactive participation in groups (bottom-up process). In the context of online communities, former research has shown that inductive social identity formation can result in higher identification than deductive social identity formation. According to this theory, posters will form a stronger social identity than lurkers because of more experience of involvement in the group tasks which leads to a greater emotional attachment.

The deductive route is a top-down process of self-categorization which is based on a response to the perceptions of shared characteristics within the group. This one does not require active participation, hence social identity is acquired by lurkers without active participation. According to this theory, lurkers are not nonproductive and nonparticipant. Their passive information consumption is a positive activity and a means of acquiring knowledge that guides future behavior.

This study investigates the mediating role of social identity in OBCs on brand commitment. In their hypotheses, the researchers expected the components of social identity (which are illustrated in figure 1) to have a stronger effect if people fall into the “poster” category.


For the data collection, an online survey was carried out. No specific online community was targeted; people had to indicate whether they were members of OBCs after having given them some examples for OBCs. Therefore, the sample consisted of participants from a wide variety of different online communities, which the researchers saw as an advantage in terms of generalizability. 752 usable questionnaires were collected, consisting of 55% lurkers and 45% posters. Using multi-sample analyses, the researchers tested the hypotheses for the moderating effects of members’ participation type for posters and lurkers.

Main findings

The results suggest that, in general, being part of an OBC cultivates customers brand commitment. This leads to greater positive WOM and higher resistance to negative information consumers may hear about the brand. Although lurkers do not visibly participate in the community, they are as likely as posters to feel the sense of belonging to the community. They do see themselves as members, and so identify with the brand community and experience a social identity. The different components of social identity in OBCs for both posters and lurkers stimulate brand commitment, positive WOM, and resistance to negative information for both groups.

Fig.1: Comparison between posters and lurkers. Source: Mousavi et al. (2017)


The research gives useful insights into the consumer behavior in the context of online brand communities. Given the fact that the majority of their visitors are lurkers, it is interesting that most prior research had its focus on only the active members. Mousavi et al. (2017) filled a gap with their study by finding out that lurkers also feel part of the community. The researchers suggest to further investigate the influences of marketing techniques on visitors who prefer to passively consume the contents of online communities. The fact that such a huge majority of people are classified as lurkers, yet prior research had mainly focused on the active members, gives ground to further explore the behavior and motivations of the passive members.


Hartmann, B. J., Wiertz, C., & Arnould, E. J. (2015). Exploring consumptive moments of value-creating practice in online community. Psychology & Marketing, 32, 319–340.

Mousavi, S. , Roper, S. and Keeling, K. A. (2017), Interpreting Social Identity in Online Brand Communities: Considering Posters and Lurkers. Psychol. Mark., 34: 376-393. doi:10.1002/mar.20995

Muniz, A., & O’Guinn, T. (2001). Brand community. Journal of Consumer Research, 27(4), 412-432.

Postmes, T., Haslam, S. A., & Swaab, R. I. (2005). Social influence in small groups: An interactive model of social identity formation. European Review of Social Psychology, 16, 1-42.

[i] https://www.simplypsychology.org/social-identity-theory.html

Everyone can become an Instagram influencer

If you are active on Instagram, you probably are familiar with so called ‘influencers’. Influencers are people that are extremely active on Instagram and have built a certain credibility in a specific industry. Influencers post a lot of authentic content on Instagram and have often generated large numbers of engaged followers who trust them (Pixlee, 2019). Influencers have the power to affect the opinions and purchase decisions of their followers and more and more businesses are starting to work with them. The influencers post content featuring certain brands in exchange for money or gifts.

In the last couple of years, the influencer marketing industry has grown immensely. In the image below you can see that the industry value this year will be double compared to the value of two years ago (Influencer MarketingHub, 2019).

Influencer Marketinghub, 2019

Why is this marketing channel so popular? On Instagram, people have endless choices on what they would like to see. This is creating a problem for businesses as it is getting harder to reach their desirable audience. Influencer marketing offers a solution because businesses can target large audiences by letting influencers promote their product to their followers (Mathew, 2018). Nowadays consumers are becoming more sceptical about ads created by brands so another advantage of Instagram marketing is the fact that followers trust the influencers (Mathew, 2018).

Influencer marketing might be the perfect solution for large, international businesses who have a large amount of funds but it might be too expensive for small, local businesses. Popular influencers also have an audience consisting from people all over the world which means that the reach is too broad.  There is some research that even suggests that a cooperation with influencers that have a large number of followers can be negative for a business as it decreases the perceived uniqueness of the business (De Veirman, Cauberghe & Hudders, 2017)

As a result, a growing amount of businesses is starting to work with micro-influencers, which are influencers with less than 3000 followers. It is less expensive to collaborate with them, they have higher follower engagement and businesses can specifically target the niche that they operate in (Influencer MarketingHub, 2019).

So, Influencer marketing is on the rise, but there is also countermovement that argues that people reached a peak of trust in online influencers. Influencers are moving closer towards traditional media brands. The distinction between sponsorships and authentic recommendations is becoming vague and people do not know who to trust (Quoc, 2017). This is where Cirkle comes in and offers a solution.

What is Cirkle?

Think about your own Instagram behaviour, you’ve probably posted a picture of yourself and your friends in your favourite restaurant or in your new clothes just for fun. But what if you could get a reward for doing it?

Cirkle is a Dutch marketing- and loyalty platform where customers or visitors can promote and recommend their favourite businesses in exchange for discount on their next purchase. Cirkle’s vision is that everybody counts; it doesn’t matter whether you have 10 or 10.000 followers. Everyone on Instagram has a unique reach which can be valuable to businesses. Their idea is that businesses can outsource their social media marketing via the Cirkle platform to their own customers (Cirkle, 2019a).

How does it work for users?  

Instagram users can download the Cirkle app and view which businesses participate on the platform. Whenever users create authentic content featuring one of the participating businesses, they can post this content on their Instagram via the Cirkle app and recommend it to their own ‘inner circle’. The Cirkle app will make sure that the user will enclose the right tags and hashtags so the content is on point. As a reward for promoting the business, the user receives a discount. The discount depends on the reach and engagement on the user’s Instagram profile. The user can spend this discount the next time he or she visits the store (Cirkle, 2019b). So basically, users can get rewards for fun pictures they would normally post just by using the Cirkle app.

How does it work for businesses?

Businesses can register themselves on the platform for free and whenever someone posts content via the Cirkle app, the businesses pay a fixed fee of two euros. Cirkle helps businesses to increase their brand awareness and to create more instore traffic. Their own customers or visitors recommend the business on their Instagram which means that businesses reach new potential customers. Next to this, Cirkle also encourages customers or visitors to return to the business as they have discount that they can spend there. Cirkle also enables businesses to accurately track their Instagram presence by offering them data insights via their own dashboard. This way, companies can keep track of their social media presence. In order to make the platform accessible to all businesses, businesses can set a maximum amount of discount that a Cirkle user can earn. This way, it will be affordable for all businesses (Cirkle, 2019c).

I think that the platform is an innovative way to respond to the influencer marketing trend. Users can get rewarded for posting pictures they would post anyway which sounds extremely good. Businesses can outsource their marketing to their own customers, reach a larger audience and gets more loyal customers. Next to this, people on Instagram will get recommendations from their friends who they probably trust more than an influencer who was paid to promote the product.

Currently, Cirkle is still testing their platform so it is not yet available to the public. From 15 March 2019, it will be available to the public and around 500 businesses spread across Amsterdam and Rotterdam already joined the platform. So, if you’ve always dreamed of becoming an Instagram influencer, this is your chance!


Cirkle (2019a) Over ons. Accessed via https://www.cirkle.social/about-cirkle/

Cirkle (2019b) User. Accessed via https://www.cirkle.social/user/

Cirkle (2019c) Business. Accessed via https://www.cirkle.social/business/

De Veirman, M., Cauberghe, V., & Hudders, L. (2017). Marketing through Instagram influencers: the impact of number of followers and product divergence on brand attitude. International Journal of Advertising36(5), 798-828.

Influencer MarketingHub (2019). Influencer Marketing Benchmark Report: 2019. Accessed via https://influencermarketinghub.com/IM_Benchmark_Report_2019.pdf

Mathew, J (2018, 30 July). Understanding Influencer Marketing And Why It Is So Effective. Accessed via https://www.forbes.com/sites/theyec/2018/07/30/understanding-influencer-marketing-and-why-it-is-so-effective/#d35a9b871a94

Pixlee (2019). What is a social media influencer? Accessed via https://www.pixlee.com/definitions/definition-social-media-influencer

Quoc, M. (2017, 15 Dec) Millenials Are Losing Trust in Online Influencers. Here’s What Marketers Can Do. Accessed via https://medium.com/dealspotr/influencer-marketing-tips-millennials-trust-da946f0bce18


Where traditional spy agencies like the CIA, MI6 and Interpol fail to identify and answer global criminal cases, a new independent investigative journalism platform has been created that utilizes crowd-sourcing in order to solve these cases. Sounds almost superhero-like, doesn’t it? Well, Bellingcat might just be the ‘crime-solver’ the world was actually looking for.

The business model

Bellingcat identifies itself as “the home of online investigation”, as it uses open source initiatives and social media in order to investigate criminal activities and conflicts around the world. By bringing together professionals and volunteers, Bellingcat provides a platform where these injustices can be tackled collectively. (Bellingcat, n.a.) The collective approach to problem-solving can be traced back within the name. “Belling the cat” stems from a tale about a group of mice deciding that the best way to protect themselves from a cat is to place a bell around the cat’s neck, but are then unable to find a volunteer to attach the bell. “Therefore, we are the mice”, according to founder and CEO Elliot Higgins. (Doward, 2018)

The concept started out as a hobby by British journalist Eliot Higgins, once a college drop-out from his study Media Technology at Southampton University. Initially, he started writing blogs on conflicts, such as in Libya, under the pseudonym of Brown Moses. He realized that social media content on these conflicts were being largely ignored within investigations. Therefore, he began collecting this content and combining them to make compelling cases. (Doward, 2018) Eventually in 2014, the Bellingcat platform was launched with crowdfunding help from their Kickstarter campaign. As of now, they consist of 11 full-time employees, with their head office located in Leicester. To keep the business running, paid workshops and seminars on online investigative techniques are given to create revenue and motivate individuals to contribute. Increased interest from NGO’s such as the Google Digital News Initiative and charities such as the Dutch Postcodeloterij have also provided Bellingcat with grants in order for them to expand their operations. (Matthews, 2018)

Methods, techniques and contributions

Known as OSINT (open-source intelligence), Bellingcat’s method of journalism collects data from publicly available sources to piece together, debunk or verify a story. The investigative technique involves strolling the internet and then cross-referencing social media posts, tweets, news photographs, databases, Google Street View and maps into a detailed mosaic of apparently undisputable data. (Matthews, 2018) This is done by professionals who work full-time at Bellingcat, leading these investigations and are supported by a larger group of “amateur investigators” who, from the comfort of their own homes, voluntarily perform these methods. They meet and talk in Facebook groups, subreddits and threads of direct messages on Twitter, discussing new tools and techniques and working with any changes to social networks that might help or hinder their work. “A lot of people who are involved with Bellingcat are from those communities, and have a kind of nerdy desire or obsession with problem-solving when it relates to big stories”, says Press Association social media journalist, Alastair Reid. (Chakelian, 2018)

Figure 1: OSINT Landscape by Bellingcat

Due to the large pool of volunteering contributors, the ‘Wisdom of the Crowds’ phenomenon arises, where input from a larger group results in more trustworthy answers. Bellingcat’s information has been judged watertight enough to be used by the official commission investigating the downing of MH-17 and has been cited in the United Nations as proof of Syrian war crimes (Matthews, 2018). Bellingcat contributors found photos on the internet of fourteen Russian officers posing with the alleged BUK-rocket which shot Malaysian Airline flight MH17 from Amsterdam to Kuala Lumpur out of the air near Donetsk, Ukraine (Doward, 2018). Next to that, contributors were able to pinpoint the blame for chemical weapon attacks by the Syrian regime. The latest investigation that caught the global news headlines and is still ongoing is about the poisoning of Sergei Skripal and his daughter Yulia in Salisbury, England. Together with Russian website The Insider, Bellingcat contributors were able to identify one of the wanted men by downloading passport data of millions of Russian citizens. The suspect was found to be Anatoliy Chepiga, who is an officer from the GRU, the Russian military intelligence, being active behind the alias Ruslan Boshirov. (Doward, 2018)

Allegations, refutations and potential

Although much praise is being given to Bellingcat, also allegations and critic has been given from mainly the Russian government. Allegations vary from being accused as a CIA information warfare department to spreading fake news and illegally retrieving their information (Matthews, 2018). As mentioned, most of these allegations come from the Russian government. This is not that surprising, as many of the investigations led by Bellingcat see Russia playing a large role within the injustices (e.g. MH17, Skripal).

“When Russia started attacking our work I’d already spent two years building up a reputation. All they’ve managed to do since is to prove that whenever they end up attacking our work it’s because we end up being right about something. The more noise they make, the more truthful something appears, basically”, according to Bellingcat director Elliot Higgins (Doward, 2018). Moreover, in many of the investigations, Bellingcat is ahead of Western intelligence agencies when it comes to finding evidence due to Bellingcat’s willingness to buy information on the black market or retrieve it from pirate sites, making them better than governments at gathering information from open sources. (Matthews, 2018) Therefore, they are proving to be a highly efficient independent agency, simply leveraging the power of active member participation of a large and diverse group of contributors.

It is safe to say that Bellingcat’s potential is huge. They are still a relatively young platform, growing every day. As more volunteers join, more information will be found which will also prove to be more trustworthy. This will result in more support from NGO’s, charities and eventually official government systems. Recently, the Dutch Postcodeloterij funded them half a million euros in order to set up a new office in The Hague, the city home to the International Court of Justice (Walker, 2019). Will it just be a matter of time for Bellingcat, an open crowd-sourced investigative platform, to become the global leader in solving worldwide crime and an official authority within the constitutional state? Time will tell, but it is certain that exciting times are ahead.


Bellingcat, (n.a.).About”. Bellingcat.com.Retrieved from <https://www.bellingcat.com/about/&gt;.

Doward J., (2018).“How a college dropout became a champion of investigative journalism”. The Guardian. Retrieved from <https://www.theguardian.com/media/2018/sep/30/bellingcat-eliot-higgins-exposed-novichok-russian-spy-anatoliy-chepiga&gt;.

Matthews, O., (2018). “How Bellingcat outfoxes the world’s spy agencies”. The Spectator. Retrieved from <https://www.spectator.co.uk/2018/10/how-bellingcat-outfoxes-the-worlds-spy-agencies/&gt;.

Chakelian A., (2018). “What is Bellingcat? Behind the tactics revealing the Skripal suspect and Cameroon killers”. NewStatesman. Retrieved from <https://www.newstatesman.com/politics/media/2018/09/what-bellingcat-behind-tactics-revealing-skripal-suspect-and-cameroon-killers&gt;.

Walker J., (2019). “Bellingcat to establish new office in The Hague after €500,000 funding win through Dutch postcode lottery”. PressGazette. Retrieved from <https://www.pressgazette.co.uk/bellingcat-to-establish-new-office-in-the-hague-after-e500000-funding-win-through-dutch-postcode-lottery/&gt;.

From e-commerce to Re-commerce: rediscovering fashion on Vestiaire Collective’s digital platform


We are all familiar with online peer-to-peer marketplaces, such as eBay, serving as online platforms to buy and sell preowned items. The secondary market has grown exponentially in the past decade (Gorra, 2019), and the fashion industry is no exception to this trend. With the growing fashion consciousness of consumers and spending awareness habits since the recession, it is no surprise that the fashion industry followed this path of “re-commerce”. In recent years, many online preowned fashion marketplaces started to pop up, focusing on the resale of preowned fashion and luxury products. One of them is Vestiaire Collective – “a leading global marketplace and community for preowned luxury and designer fashion” (Pallardo, 2017).

Introduction to Vestiaire Collective

Launched in 2009, Vestiaire Collective (VC) had the mission to extend the lifespan of beautiful luxury fashion pieces by bringing them back into circulation (“Vestiaire Collective”, n.d.). With over 7 million members located in over 50 countries, VC has established itself as one of the global leaders in fashion and luxury resale. The difference between VC and other preowned luxury and fashion marketplaces is that it focusses on the peer-to-peer interaction (buyers buy from sellers). Other competitors, such as The RealReal, have consignment models (sellers receive a listing price up front from a company that then puts the item for sale) and therefore focus on the business-to-consumer interaction. VC therefore has no inventory, yet leverages that of its customers’.

How does the platform work?

Access to the platform is only granted by becoming a member. Sellers can submit their item on the platform, which VC then evaluates. The item can be accepted, negotiated a different listing price, or declined. If accepted, VC lists the item on their platform (Figure 1). Once an item is sold, the seller ships the item with a prepaid shipping label (paid for by VC) to one of VC’s offices where thorough authentication and quality control of the item is conducted. VC’s experts then make sure the item is not counterfeited and in the expected state. Finally, if the item passes quality control, it is shipped to the buyer and the seller gets paid. 

Vestiaire Collective’s Business Model

The platform mainly earns revenue from collecting commission fees for every item sold on their platform. Roughly 1000 to 2000 pieces undergo quality control every day and an average basket is worth €400 (Pallardo, 2017). VC takes between 18% and 34% commission, depending on the listing price (“Vestiaire Collective FAQ”, n.d.). This fee includes the free shipment of the sold product to one of VC’s offices and quality control services. 

Why Vestiaire Collective?

One might wonder why sellers choose to list their items on VC instead of on other platforms where commission rates are significantly lower (for example, eBay charges a maximum of 10% (“eBay Customer Service”, n.d.)). Essentially, sellers must make a trade-off between lower commission rates and the benefits of VC’s platform. Many sellers, including myself, are choosing for the latter. 

Figure 1: Article for inspiration written by VC (right), and example of listing (left).
Source: Screenshot in app.


VC is specialised in luxury fashion. Although rivals such as eBay are large in the secondary market, they are not specialised in luxury goods. VC is also proactive with its members, creating a lot of content around their platform, educating them about fast-moving products and brands, and providing them with information on the latest trends (Figure 1). Once in a while special sales are organised to connect with members on a different level by featuring items for sale of famous influencers.

Convenience and scope

Listing an item is easy. VC step-by-step guides sellers in this process, and along the way, educates them on how more information and better images can increase sale likelihood and seller trustworthiness. Furthermore, shipping costs to VC’s office for quality control is prepaid, regardless of where in the world the buyer lives. Sellers simply print out the prepaid shipping label. No need for exchange of personal information. VC reliefs sellers from language barriers and the burden of having to factor in shipping costs, and simultaneously broadens sales reach. 

Figure 2: “Resale Calculator” feature in app (right), and Notification page (left)
Source: Screenshot in app.

Semi-anonymous peer-to-peer interaction

As a member of the community, you are not anonymous; names, countries and number of sold items are disclosed. However, as a bidder and buyer you are (Figure 2 and 3). Members cannot directly or privately contact each other, but can publicly comment on and “like” the item to ask questions and to give the community an indication of popularity of the item (Figure 2). Although direct contact among members is not possible, the main interaction on the platform is between peers. The platform basically functions as facilitator and regulator, by allowing peer-to-peer trade and ensuring ethical behaviour.

Figure 3: Negotiation area. After three rounds the (anonymous) bidder/buyer can no longer make an offer.
Source: Screenshot in app.

Trust in the platform: no market for lemons

VC’s community is built on trust, maintained by the rules and regulations of the platform. Members’ inability to send each other private messages does not restrict them from obtaining the right information about products and sellers. The quality control service protects buyers from counterfeit, and makes sure accurate information is provided by sellers on product condition (Figure 4). Additionally, members will not be cheated on. VC is a semi-centralized platform in terms of pricing. Sellers’ listing price must be accepted by VC to avoid extremely high prices (Figure 2). Also, buyers cannot offer sellers a price lower than 30% below the listing price, so sellers can anticipate their earnings up front. With its semi-centralised pricing system and trustworthiness, VC avoids a market for lemons, and assures fair prices for fair trade.

Figure 4: Vestiaire Collectives quality control department (Bertrand, 2016).
Source: http://www.lesechos.fr

Opportunities and Challenges for Vestiaire Collective


VC’s trustworthiness has come at a cost, and still costs them a lot of money. Authenticating sold products is at the core of their business and trustworthiness. However, it is also one of their most expensive processes. The prepaid shipping label VC provides their sellers with, is extremely expensive, especially when items are deemed inaccurate and thus do not pass quality control. One of VC’s internal challenges is therefore to find more efficient ways of authenticating items. One interesting opportunity that requires adaptation from the entire fashion industry, is the use of Blockchain technology. Authentication could then be validated by the chain, instead of by expensive experts, and simultaneously mitigates shipping costs. Items that are especially susceptible to counterfeit often carry unique reference numbers that are registered at the manufacturer. Although a long shot, it might be interesting for VC to explore the possibilities of Blockchain for their business.


“The more products sold in the boutique, the more products sold on the secondary market” (Sherman, 2017). VC’s focus is on expanding to other countries and increasing user base to obtain more supply to fuel the marketplace. With a total funding of $130 million, VC therefore continues to expand their marketplace to China (Milnes, 2017), as the Chinese are the biggest spenders on luxury and making up 32% of its total spending in the global market (Pymnts, 2018). However, like every platform or online community, its success depends on member engagement, which in VC’s case is members’ willingness to put their items for sale. VC’s external challenge is to make sellers from boutique buyers, and to make sure that sellers remain boutique buyers as well. Without “buying sellers,” the platform has nothing to sell. Re-commerce is therefore not a threat, but rather a complement to traditional or e-commerce. 


  1. https://www.kantox.com/en/the-difficulty-lies-in-structuring-the-business/
  2. https://www.businessoffashion.com/articles/bof-exclusive/vestiaire-collective-62-million-raise-recommerce-war-rages
  3. https://digiday.com/marketing/vestiaire-collective-paving-way-online-secondhand-luxury-china/
  4. https://digital.hbs.edu/innovation-disruption/new-normal-luxury-secondary-market/
  5. https://faq.vestiairecollective.com/hc/en-gb/articles/200429161-Calculate-our-commission
  6. https://www.ebay.com/help/selling/fees-credits-invoices/selling-fees?id=4364
  7. https://www.pymnts.com/news/retail/2018/ecommerce-china-luxury-goods-retail-tiffany/
  8. https://www.vestiairecollective.com/about/

Rethinking Ridesharing … For Kids?

Nowadays, through just a few taps on your smartphone, you can get a ride to your desired destination from your current location. This is because innovation and technological advancements, paired with the widespread ownership of smartphones, have given rise to peer-to-peer centralized taxicab platforms. These app-based platforms match demand (people who need a ride) with suppliers (people with cars), and set prices to facilitate transactions. (Proserpio & Tellis, 2017). Today, the global ridesharing industry has been valued at over $61 billion, with projections that it will grow to $218 billion by 2025 (Curley, 2019).

With major players like Uber and Lyft dominating the market, who have a combined market share of 98% in the US for example, it’s difficult to see the space or need for new entrants (Molla, 2018). But there is one group of riders who are underserved in this market – kids. Namely, kids soliciting ridesharing services, or parents requesting it in order to shuttle their kids to activities. This seems like a convenient way for busy parents to get their kids from A to B, but there is a major problem – it’s simply not allowed. Account holders on Uber and Lyft must be 18 or older and cannot request a ride on the behalf of minors, unless they are accompanied by an adult (Heilweil, 2019). Uber and Lyft simply don’t have the certificates or insurance necessary to allow unaccompanied minors, and don’t want the liability that comes with it (Gibbins, 2018).  So how are kids supposed to get where they need to go when their parents are busy?


This is where HopSkipDrive enters the picture. HopSkipDrive is a California based ridesharing taxi cab service, founded by three moms, catered specifically to minors. It was founded in 2014 by three working moms struggling to get their kids where they needed to go. (HopSkipDrive, 2019) With initial funding of $14.1 million, their objective is to make a difference in the lives of kids and parents by providing a safe and dependable way of getting kids where they need to go.

How It Works

On the app, parents can request a ride or preschedule one up to 8 hours in advance. For reoccurring activities like after school sports, parents can save rides and ‘repeat’ them. If kids from many families are all going to the same destination, the app has a carpool feature which will coordinate the pickup of kids from several locations for a discounted price. (HopSkipDrive, 2019)

In addition to servicing families, HopSkipDrive also offer ridesharing services to schools. By working with school districts, they are able to unlock opportunities for substantial business growth (Roof, 2018). Schools can book drivers for field trips or students who require special care, with just a few taps. Furthermore, if a school bus isn’t completely full, it can be a much cheaper option for schools to hire HopSkipDrive services instead. (HopSkipDrive, 2019)

HopSkipDrive Mobile App

To ensure the safety of kids using the service, HopSkipDrive puts it at the center of everything they do. Drivers are referred to as “CareDrivers”, who double as caregivers. To be a CareDriver, you need to be over 23 years old, have at least five years of childcaring experience,  a clean driving record, as well as a car that is no more than 10 years old (HopSkipDrive, 2019). Furthermore, drivers are required to pass a multi-agency background check, which includes fingerprinting, before they are officially registered on the app. HopSkipDrive also allows parents to provide detailed pick-up and drop-off instructions, and CareDrivers will confirm a predetermined ‘codeword’ and date of birth with each kid they pick up. Furthermore, all rides are monitored in real time by the HopSkipDrive team. (HopSkipDrive, 2019)

Efficiency of the Business Model

There is considerable demand from working parents to get their kids to activities efficiently and safely and with little time for preplanning. HopSkipDrive allows parents to organize rides for their kids whenever the need arises. On the other side, drivers are able to use their own cars, and spare time, to earn extra money. HopSkipDrive drivers can earn up to $30/hour, which is about three time more than Uber or Lyft drivers (Gibbins, 2018). Many parents are willing to pay the premium price for a safe service, and it is often cheaper than getting babysitter. There is however less flexibility regarding working hours for drivers on the HopSkipDrive app than on Uber of Lyft. This is because kids are in school all day and for the most part require rides in the early mornings, with requests only picking up again in the afternoon. Furthermore, a large number of rides on the app are prescheduled. (Gibbins, 2018)

There are clear internal rules and regulations in place to ensure the safety of kids, like strict behavioural guidelines as to how drivers are supposed to interact with the kids they are driving (HopSkipDrive, 2019). Unlike Uber of Lyft, HopSkipDrive has certificates and insurance necessary to work with minors, and a $1 million liability coverage (HopSkipDrive, 2019). There are legal measures that drivers must go through, namely drivers in California must register with TrustLine, which is a state database for nannys and babysitters. On the one hand, this restricts the number of potential drivers considerably because many do not fit the requirements, or do not have the time to go through the registration process. On the other hand, it may in fact open up the ridesharing industry to potential drivers who otherwise wouldn’t have considered it. HopSkipDrive drivers are almost all female, and either mothers, babysitter, teachers or so called ‘empty nesters’, who feel safer driving for HopSkipDrive than Uber or Lyft, and enjoy caring for kids (Heilweil, 2019).

This business model of ridesharing for kids has not been met without difficulties. Several similar platforms, like Shuddle and Shepherd, have shut down, despite receiving  considerable funding initially. These platforms sited issues stemming from the driver vetting and registration process taking too long, and failing to secure more funding after running into financial difficulties (Heilweil, 2019). In 2017, Uber piloted its own program for teenagers ages 13 to 17, but eventually shut it down after little success. This stemmed mainly from the fact that regular Uber drivers were used, who received no extra training or guidelines as to how teens should be transported  (Heilweil, 2019).

The Future Ahead

Building a ridesharing business is already a difficult and expensive thing to do, and adding kids into the mix doesn’t make it any easier. Despite the challenges noted above, the market for kid’s ridesharing is continuing to grow, with HopSkipDrive securing another $7.4 million of funding just last year (Roof, 2018). However, HopSkipDrive is not without competition and Zūm, another ridesharing platform for kids just raised their total funding to $70 million, and is already present in three States (Dickey, 2019).

Due to the somewhat uniform schedules of children, it’s a questionable whether drivers on kids ridesharing platforms will continue to get enough work on the average day. Because of this, it could be essential for these platforms to expand their businesses further than just parents requesting rides. The future of ridesharing for kids could be to sell rides directly to schools, largely replacing traditional school busses, something these platforms have already started exploring (Pinsker, 2018).


Chuang, T., 2018. First “Uber for kids” ride service launches in Denver by three moms, including one who grew up here. [Online]  Available at: https://www.denverpost.com/2018/04/05/hopskipdrive-uber-for-kids/

Curley, R., 2019. Global ride sharing industry valued at more than $61 Billion. [Online] Available at: https://www.businesstraveller.com/business-travel/2019/01/04/value-of-global-ride-sharing-industry-estimated-at-more-than-61-billion/

Dickey, M. R., 2019. Zūm, a ridesharing service for kids, raises $40 million. [Online] Available at: https://techcrunch.com/2019/02/28/zum-a-ridesharing-service-for-kids-raises-40-million/

Gibbins, P., 2018. Comparing the Top 4 Rideshare Apps for Kids. [Online] Available at: https://therideshareguy.com/top-rideshare-apps-for-kids/

Goldstein, M., 2018. Uber And Lyft: The Cost And Benefits Of Disruption. [Online]  Available at: https://www.forbes.com/sites/michaelgoldstein/2018/05/09/uber-and-lyft-the-cost-and-benefits-of-disruption/#568fcc4adfcb

Heilweil, R., 2019. THE TRICKY BUSINESS OF MAKING RIDE-HAIL WORK FOR KIDS. [Online] Available at: https://www.wired.com/story/ride-hail-sharing-kids-hopskipdrive-zum-kango/

HopSkipDrive, 2019. About. [Online] Available at: https://www.hopskipdrive.com/about

Molla, R., 2018. Lyft has eaten into Uber’s U.S. market share, new data suggests. [Online]  Available at: https://www.recode.net/2018/12/12/18134882/lyft-uber-ride-car-market-share

Pinsker, J., 2018. What Is the Future of Getting Kids to Soccer Practice?. [Online] Available at: https://www.theatlantic.com/family/archive/2018/10/uber-lyft-kids-hopskipdrive-zum/573424/

Proserpio, D. & Tellis, G. J., 2017. Baring the Sharing Economy: Concepts, Classification, Findings, and Future Directions. [Online]
Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3084329

Roof, K., 2018. HopSkipDrive raises another $7.4 million for its Uber for kids business. [Online] Available at: https://techcrunch.com/2017/11/21/hopskipdrive-raises-another-7-4-million-for-its-uber-for-kids-business/

Value co-creation in health care – New patient centric approaches

Though customer value co-creation is not a new concept, tracing back to the 1970s when it was first discussed in the business literature (Janamian et al., 2016), it might be surprising (and even shocking) to hear that it found its way into health care only recently. With more options and more information available online, patients took on an increasingly active role in their health and wellness (Elg et al., 2012). This changed the traditional view of many health care systems where consumers were seen as having a passive, receiving role (Nambisan & Nambisan, 2009). 

Consequently, today an increased focus is put on partnerships between the different participants within health systems, such as researchers, health care professionals, health care organizations and the consumer community. Especially online health communities have experienced growing popularity in recent years, both among patients and health care organizations. The advantage of these communities is that they often show strong identity-based as well as bond-based attachment between members resulting in very active groups that health care organizations try to tap into.

What are the benefits? 

For patients

  • improved health outcomes
  • increased trust in the health care system
  • reduced healthcare costs

For health care organizations

  • new innovative ideas
  • reduced cost and time to market
  • more positive perception

For the health system

  • increased efficiencies in health services
  • identification of improvement opportunities
  • reduced costs for the health system
  • increased patient satisfaction

How does it work in practice?

Nambisan and Nambisan (2009) developed a framework of consumer value co-creation in health care, differentiating between four different models. These models are resembled in the following matrix and are differentiated via two dimensions, the Nature of Leadership which can either be the consumer or the health care organization versus  the Nature of Knowledge activity, where they differentiate between knowledge creation and knowledge sharing.

Figure 1: Models of consumer value co-creation in health care (Nambisan & Nambisan, 2009)

Based on the framework we can classify existing practices based on their related consumer value co-creation model. A Partnership Model is characterized according to Nambisan and Nambisan (2009) by an online health community that participates in activities that are led by health care organizations to create new knowledge. An example are for instance online communities where organizations reach out to patients for clinical trials, for instance to understand the side effects of drugs. A global online health community that is especially active in this area is HealthUnlocked. The platform also enables peer support and allows users to see and contribute in over 700 health communities about specific health conditions. These communities are often run in partnership with established healthcare organizations (HealthUnlocked, 2019).

Figure 2: HealthUnlocked a social network hosting more than 700 health communities

In contrast to the previous model, Open-Source Models are characterized by consumer community led activities, sometimes also referred to as consumer centers of research (Nambisan & Nambisan, 2009). This kind of model might be especially valuable for people with rare disease that can then form communities with peers and experts and focus on the research of specific diseases. As the „crowd“ in these communities does not consist of experts, the value in insights might be limited though. Nevertheless, the social network project Panoply could be considered a successful model that started off as a relatively small open-source project which eventually resulted in a successful app that promotes well-being to combat depression (Rucker, 2017). 

Support Group Models are consumer community led forums for sharing consumers’ knowledge about a disease or treatment (Nambisan & Nambisan, 2009). Phoenix Helix is such a platform, that provides help and advice for people that suffer from auto-immune diseases (Phoenix Helix, 2019). Health care organizations could provide additional value in these communities for instance by offering complementary services or access to databases.

Finally, Diffusion Models are characterized by knowledge sharing activities initiated and led by health care organizations. These models have the potential advantage that they facilitate the diffusion of knowledge about an organizations existing or new product. Multinational pharmaceutical company GlaxoSmithKline used this model when it launched a new weight loss drug and invited 400 overweight men and women to share their experience in an online community (Nambisan & Nambisan, 2009). It should be noted however that diffusion could be both positive as well as negative.


While the approaches discussed above can offer real value for patients, health care organizations and health system, there are some risks. In most of the above cases patient data is self reported and not always directly linked to medical records or clinical information which may result in invalid and biased data (Bhomwmick & Hribar, 2016). Moreover, some individuals in the community might be motivated by extrinsic rewards like glory or money and thus knowingly give wrong information to stick out. Furthermore, data published on online communities might be confidential and could expose very sensitive information (Bhowmick & Hribar, 2016). 


It is evident that online health communities can serve as valuable resources for patients as well as health care providers for value based co-creation in health care. Online health communities can positively effect efficiency, feasibility and speed of health research while engaging many customers (Bhomwick & Hribar, 2016). While focusing mainly on consumer value co-creation between the consumer and a single health care organization in this blogpost, it should be noted that health care organizations are increasingly putting efforts on working together on common ecosystem to drive digitalization and utility for the consumers, such as the platform established by Siemens Healthineers in 2017 (Siemens Healthineers, 2017). 


Bhowmick, A. & Hribar, C. (2016). Online Health Communities: A New Frontier in Health Research. Medium. Retrieved from https://medium.com/@abhowmick1/online-health-communities-a-new-frontier-in-health-research-71fb73edbea2.

Elg, M., Engström, J., Witell, L. & Poksinska, B. (2012). Co-creation and learning in health-care service development. Journal of Service Management, 23(3), pp.328-343.

HealthUnlocked. (2019). HealthUnlocked About Us. Retrieved from https://healthunlocked.com/about.

Janamian, T., Crossland, L. & Wells, L. (2016). On the road to value co-creation in health care: the role of consumers in defining the destination, planning the journey and sharing the drive. MJA, 204(7).

Nambisan, P. & Nambisan, S. (2009). Models of consumer value concretion in health care. Health Care Management Review, 34(4), pp.344-354.

Phoenix Helix (2019). Phoenix Helix. Retrieved from https://www.phoenixhelix.com&nbsp;

Rucker, M. (2017). 5 Great Online Communities for Patients With Medical Conditions. Verywell Health. Retrieved from https://www.verywellhealth.com/great-online-communities-for-medical-patients-1739169.&nbsp;

Siemens Healthineers (2017). Siemens Healthineers establishes global Digital Ecosystem to drive digitalization of healthcare. Retrieved from https://www.siemens.com/press/en/pressrelease/?press=/en/pressrelease/2017/healthineers/pr2017020180hcen.htm&content%5B%5D=HC.

How does my review affect the price of your accommodation?

The following is a review of the paper “Reviews and price on online platforms: Evidence from sentiment analysis of Airbnb reviews in Boston” by Lawani et al., (2019).

With the rise of platforms such as Airbnb, that now provides access to more than five million rooms in approximately 191 countries, the power dynamic in the traditional hospitality industry has shifted (Airbnb, n.d.). What are the reasons behind the relatively recent success of these peer-to-peer platforms, with a focus on hospitality in particular? Technological advances is one explanation for the sharing economy (P2P markets) as it made the process of connecting people with each other faster and more efficient, and significantly reduced overall costs. Subsequently, it facilitated the development of reputational systems, which is considered a major influence in overcoming moral hazard and adverse selection (Horton & Zeckhauser, 2016).

The process of making a decision on what accommodation you would like to stay at, is dependent on a multitude of factors and personal preferences. The amount of bedrooms, proximity to the city center, amenities, and price to name only a few things that can be taken under consideration. But ultimately, when the guests that came before you have merely negative experiences with the accommodation, it is unlikely that you will follow their footsteps. Lawani at al. (2019) studied the relationship between content of reviews and accommodation price in Boston. While previous research mainly focused on one-dimensional ratings such as number of reviews and star rating, this paper uses reviews as a proxy for quality.


The research is focused on two main components, namely first the difference between the effect of the unidimensional ratings on price and the effect of several separate quality measures (which they constructed themselves) on the price, and secondly how quality opinions from sentiment analysis of the reviews affect price. A previous study on the effect of online reviews on sales by Hu et al. (2008) states that product reviews are one of the main indicators of quality perceived by consumers. Since research by Zervas et al. (2017) has indicated that Airbnb rentals have a negative effect on hotel revenue, they are seen as substitutes. Overall, the importance of word-of-mouth on consumer decisions has been highlighted extensively throughout multiple researches. The paper looks at the characteristics of the platform Airbnb, where hosts can determine the price of their accommodation and which services are included, while the consumers have their quality preferences and their willingness-to-pay. Guests are positively impacted by competition on the supply side, as hosts might have to lower prices or increase their quality to competitors’ standards.

Methods and main findings

Retrieved from Inside Airbnb, the researchers used a dataset of 2051 individual hosts in Boston, gathered in September 2016. This accommodation data was connected to Boston’s economic data originating from the American Community Survey, which included neighborhood variables, income measures, and education level. To overcome the unidimensionality of ratings, Lawani et al. (2019) also focus on sentiment of reviews. Furthermore, they dissect quality as a construct and develop seven other variables that each represent an aspect of quality. A sentiment analysis of reviews resulted in a score for quality for the accommodations. The remaining six quality variables are accuracy, cleanliness, check-in, communication, location, and value of the accommodation.

Among the main results from the theoretical models they find that prices for short-term accommodations are strategic complements, meaning hosts’ adopt their prices according to their competitors. Secondly, from the empirical analysis they find that the sentiment score is a better quality proxy than the rating score, since the opinions in reviews can represent more indicators of quality than a singular score. Ratings are easier to understand, while reviews provide better insights (Tsekouras, 2019). However, the six quality component variables mentioned before are better predictors of price that the sentiment score. The number of bedrooms and bathrooms as well as overall capacity are associated with higher prices. Furthermore, they found that cleanliness of the accommodation followed by accuracy of the description are the quality measures that influence price the most, which has implications for hosts that are looking to improve their competitiveness.


The researchers opt for a vertical product differentiation model to depict competition. One of the strengths of the paper is the comprehensibility of the profit-maximization framework. They denote that competition between Airbnb hosts in a city usually takes place within a certain mile radius, instead of over the whole city. In addition, the sentiment analysis is conducted on the reviews that were posted on Airbnb in 2016 only. Having a topical dataset is important for the analysis of reviews since consumers usually only read the most recent reviews. More generally, this research is one of the first to look at the relation between consumer review content and its effect on the price on a sharing economy platform.

One weakness of the study that is highlighted as well is that the conceptual model is completely tailored around traditional profit maximization. It is also possible that hosts deliberately lower their accommodation price to have more options to choose from. Additionally, the researchers show little regard for the implications and relevance for Airbnb hosts, especially on how they can directly derive value from reviews. Besides, it is to be expected that sentiment score from review content is a better indicator of quality than a unidimensional rating. A rating represents the overall impression of the accommodation, but can also reflect discontent with only one aspect of the experience, while reviews allow for a more complete image. The academic relevance of that result is therefore lower compared to the other findings.


Airbnb. (n.d.) About us [online]. Available at: https://press.airbnb.com/about-us/ [Accessed 9 March, 2019].

Edelman, B., Luca, M. & Svirsky, D. (2017). Racial Discrimination in the Sharing Economy: Evidence from a Field Experiment. American Economic Journal: Applied Economics. Nr. 9(2), pp. 1-22.

Horton, J.J. & Zeckhauser, R.J. (2016).  Owning, Using and Renting: Some Simple Economics of the “Sharing Economy”. National Bureau of Economic Research, Inc. [online]. Available at: https://www-nber-org.eur.idm.oclc.org/papers/w22029.pdf [Accessed 9 March, 2019].

Hu, N., Liu, L., Zhang, J.J. (2008). Do online reviews affect product sales? The role of reviewer characteristics and temporal effects. Information Technology Management. Nr. 9, pp. 201–214.

Tsekouras, D. (2019). CCDC.

Zervas, G., Proserpio, D., Byers, J.W. (2017). The rise of the sharing economy: estimating the impact of Airbnb on the hotel industry. Journal of Marketing Research. Nr. 54, pp. 687–705.

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