Tag Archives: Public Transportation

Moovit – The future of urban mobility?


By Denis Ceric, 410688

While public transport itself has not changed that much in recent years, the way in which we find information about public transport has. Here in the Netherlands, I can not imagine taking the public transport without looking at either Google Maps or 9292. However, there might soon be an addition to this small list, going by the name of Moovit.

Moovit is a “leading Mobility as a Service provider and the world’s #1 transit app” (Moovit, 2019a). Moovit combines information from public transport operators with live information gathered from their passionate user community. This user community has been dubbed the “Mooviter Community” and helps mapping and maintaining local transit information in cities that could otherwise not be served by the app (Moovit, s.d.). Moovit themselves dub this community the “Wikipedia of Transit” (Moovit, 2019a). Moovit has over 330 million users across Android, iOS and the web, their app is fully localized to 44 languages and they offer their service in over 2,700 cities across 87 countries (Moovit, 2019a). In addition to this, their community of Mooviters counts over 500,000 members, with another 150 employees working for Moovit itself (Moovit, 2019a).

Why Moovit over alternatives?

This large community is one of the largest reasons why Moovit is likely to surpass alternatives such as Google Maps on a global scale. The CEO presented that Moovit amasses up to 500 million anonymized data points a day from transit riders, which they then combine with data gathered from their Mooviter community (Moovit, 2017a). Additionally, thanks to this data, they offer precise and hyper-local transit data that allows them to provide real-time data for thousands of transit operators worldwide in cities where Google does not, such as Hong Kong, Istanbul, Madrid or even Paris (Moovit, 2017a). Next to this, where Google plots (bus) stops using official transit data, Moovit combines this data with their own technology and community of users to avoid inaccuracies (Moovit, 2017a). The community not only allows Moovit to gather the precise location of the stops where people enter, they also sends active reports about their travel experience, such as bus congestion levels, cleanliness and more (Moovit, 2017b). This combination of data leads to the following analytics:

Figure 1: Moovit Urban Mobility Analytics. Source: (Moovit, 2019b)

This provides for an easy to use app for consumers, but all this data gathered also provides a clear business case for Moovit to convince cities to support their app. With these analytics, Moovit offers cities more reliable data than traditional surveys, faster analysis, granular insights and a rich visualization (Moovit, 2019b).

The future of Moovit

All of the above has played a large in securing a total funding of $131.5 million over four funding series, including a number of notable companies such as Intel Capital and BMW i Ventures (Crunchbase, 2019). Despite such a large amount of funding, they have not gathered much revenue to this date. However, this might soon change, as the founder of the app notes that they will be switching from a focus on growth and coverage to making money through selling data (Solomon, 2018). Building on this, they have already closed deals with multiple cities in Europe and are in talks with cities in Latin America (Solomon, 2018). In addition to this, they are preparing for the future of autonomous vehicles in cities and believe that they will play an instrumental part in making cities ready for these autonomous vehicles (Solomon, 2018).

However, whether this passionate user community will remain as passionate when Moovit starts selling all of their data and becomes the Facebook of public transport has to be seen. Amidst growing privacy concerns across the globe, Moovit will have to tread carefully in order to not suffer from backlash. Moovit, however, themselves appear to be aware of this and are taking user privacy seriously. To use Moovit, you are not required to make an account, they are GDPR compliant, all data is anonymized and all analytics are anonymized as well (Meydad, 2019). As such, what the future holds for Moovit, nobody really knows. But, it does not appear as if they will be slowing down their growth as long as they continue the way they have been.

Link to theory

Looking at the four types of crowdsourcing, I argue that Moovit’s app is mostly a form of information pooling but also has some open collaboration elements (Blohm, Zogaj, Bretschneider & Leimeister, 2018). The tools provided by Moovit make it quite easy for Mooviters to provide the data required to map the public transport in a specific town or city, thereby creating quite simple tasks for the Mooviters (Blohm et al., 2018). While the end result provided by Moovit in the app is quite complex, the individual contributions of the community are not, as most data is simply gathered through the app and not much else has to be done in these cases (similar to Google Maps, a prime example of information pooling). However, as mentioned earlier, the community does provide added value by taking into account individual user contributions, such as pictures of bus stops and reports of their travel experience (Moovit, 2017b).

Looking at the recommendations of Blohm et al. (2018) for governance mechanisms for information pooling crowdsourcing platforms, Moovit follows most of them. They provide clear contribution requirements, they have a demographic-based allocation of tasks (as users map the area around them), they make use of reputation systems and framing (e.g. by recognizing extraordinary Mooviters as “Ambassadors” and providing them with goodies and opportunities to meet other ambassadors at exclusive events), and by providing tutorials (Moovit, 2018). Next to this, recommendations by Dellaert (2019) can also be found in Moovit, as the consumers of the map are often also co-producers. The increase in customers’ joint payoff at a network level is most relevant (Dellaert, 2019). The establishment of the community itself, rather than having each user of the app contribute, is an example of this. By encouraging users to join this network and become active in the network, greater utility for the total network is achieved (Dellaert, 2019).

Efficiency criteria

Lastly, I will briefly evaluate this crowdsourcing approach using the efficiency criteria. I believe the joint profitability is currently efficient, but there could be a greater recognition of their Mooviters and for the future, monetary rewards might be in place. Currently, I believe it is efficient as Moovit is not really generating any revenue so it would not make much sense to use their funding to pay their community, but once the selling of data gathered from this community is implemented throughout the platform, it would make sense to share some of this with these Mooviters, whose data is being sold.

In terms of feasibility of required reallocations, I believe it would be relatively difficult to establish the necessary institutional arrangements and institutional environment for most competitors. This is mainly due to the fact that location-based data is gathered continuously, which could lead to large privacy concerns and trust issues among users. Additionally, the largest strength of Moovit’s crowdsourcing approach now is the large network of Mooviters they have built, and the network effects that come with such a large network (in addition to the map they have built using this network). As such, this would only really be feasible for a large company with an established network and the ability to adhere to the instutional arrangements and environment, such as, for example, Google.

References

Blohm, I., Zogaj, S., Bretschneider, U. , Leimeister, J.M. (2018): How to Manage Crowdsourcing Platforms Effectively? in: California Management Review, Vol 60, Issue 2, p. 122-149, doi: 10.1177/0008125617738255

Crunchbase (2019). Moovit. Retrieved February 23, 2019 from https://www.crunchbase.com/organization/moovitapp#section-company-tech-stack-by-siftery

Dellaert, B. G. (2019). The consumer production journey: marketing to consumers as co-producers in the sharing economy. Journal of the Academy of Marketing Science, 1-17.

Meydad, Y. (2019). Supply and demand: how data collection and analysis became the key to unlocking MaaS. Retrieved February 24, 2019 from https://www.intelligenttransport.com/transport-articles/74591/transport-data-maas-solutions/

Moovit (2017a). Moovit “Eclipses” Better-Known Services Like Google Maps. Retrieved February 23, 2019 from https://moovitapp.com/blog/moovit-versus-google/

Moovit (2017b). Moovit Press Factsheet November 2018. Retrieved February 23, 2019 from https://docs.wixstatic.com/ugd/c729fe_82d633f838e44572a129d75ce2e31eaa.pdf

Moovit (2018). Commuter Kate: How To Make A Difference In Your Community. Retrieved February 24, 2019 from https://moovitapp.com/blog/community-crowdsourcing/

Moovit (2019a). About. Retrieved February 23, 2019 from https://www.company.moovit.com/about

Moovit (2019b). Origin-Destination Visualizer. Retrieved February 24, 2019 from https://www.solutions.moovit.com/origin-destination-visualizer

Moovit (s.d.). Join the Mooviter Community. Retrieved February 23, 2019 from https://editor.moovitapp.com/web/community

Solomon, S. (2018). Israeli founder of Moovit app sees himself as the ‘Marco Polo of transit’. Retrieved February 24, 2019 from https://www.timesofisrael.com/israeli-founder-of-moovit-app-sees-himself-as-the-marco-polo-of-transit/

GoMetro – Real Time Passenger Data for Public Transportation Systems


Cape Town, South Africa.

Three million commuters use the metro rail on a daily basis in South Africa. The underdeveloped public transportation system has frequent delays, however there are no notifications of cancellations or changes in the schedule due to the fact that there are no sources of real time travel information. The South African startup, GoMetro, provides commuters with mobile services through the mobile web, apps, socials networks and sms-services and thereby they connect transit operators with commuters who are at the center of the platform. Commuters in their turn log on to the platform and share their real time location, stops, delays and any cancelations. In return GoMetro can provide and exchange real-time arrival and departure information, current locations of vehicles, early notifications of operational breakdowns and travel disruptions of the public transportation system. Hereby, GoMetro, transit operators and commuters co-create value through the sharing of real time data information creating a platform using a customer-centric approach.

Although GoMetro started in South African cities with underdeveloped transportation systems, the scope of the business model reaches much further. Personal mobile devices are being used and have changed information distribution paradigms, however they have not yet been used in the public transportation domain (Nunes, Galvao and Cunha, 2014). When consumers interact with service providers, in this case GoMetro, a win-win situations is created. This business model incorporates three different roles for the commuters in the co-creation of value; they need to use the information, provide real time information and validate given information (Nunes, Galvao and Cunha, 2014). This business model can be used in many different countries and cities, as the use of mobile devices has risen substantially over the recent years and will continue to do so (Emarketer.com, 2018).

The three parties involved in the platform of GoMetro are the commuters, the transit companies and GoMetro itself, each creating value with each other as to create joint profitability. The commuters create value through sharing the real time travel data and use the travel data of others, thereby creating value for the platform as a whole. The transit companies can provide incentives such as discounts on travel fares for the commuters, as to incentivize them to share their travel data. GoMetro contributes by the creation of the platform and bringing all users together so they can co-create value, in return they make money through advertisements on the platform. The creation and development is done in cooperation with Intel, who provide technical support and insights. All these elements are linked to the customer-centricity of the platform and the interaction between the parties creates joint profitability for all players involved.

The institutional environment GoMetro faces in South African cities has been positive ever since GoMetro started with the idea. With millions of people commuting each day in South Africa and many cannot afford a car themselves, efficient public transportation could be a lifesaver. GoMetro helps to improve the efficiency and commuters adopt the platform in large numbers, as already near to a million people are registered users. Looking at the support the company is getting from both governmental institutions as well as private companies the platform seems to be beneficial for all. Increasing the use of public transportation in the big South African cities helps to reduce the use of private cars, air pollution and frees up space in the cities, as less cars enter the urban areas. All these elements contribute to a more efficient infrastructure of large cities. Having no legal boundaries or complications, makes the institutional environment even more advantageous for the platform of GoMetro.

One drawback is the issue of privacy concerns. Sharing real time personal travel information reveals where you are at a given moment in time and this captures valuable information which can also be used for undesirable purposes. Consumers have to consider whether sharing their real time travel data is worth the costs of sharing private information with the platform. As long as the benefits outweigh the costs, the platform has a sustainable business model and a bright future (Karwatzki et al., 2017).

The extent to which the business model of co-creating value by customers sharing their real time travel information with a platform can reach is yet to be determined. The need for a more efficient public transportation system and the willingness of commuters to share their real time travel data are the least requirements for the business model to succeed. ‘As cities grow, they are in need of a flexible mobility platform to service their mobility needs’ (Justin Coutzee, Founder of GoMetro, 2016). Big cities in Africa, Asia and the Middle East are likely to adopt such business models as they want to improve the way people move within their urban areas.

 

 

 

 

References:

Nunes, A., Galvao, T. and Cunha, J. (2014). Urban Public Transport Service Co-creation: Leveraging Passenger’s Knowledge to Enhance Travel Experience. Procedia Social and Behavioral Sciences, 111, pp.577-585.

Emarketer.com. (2018). Mobile Phone, Smartphone Usage Varries Globally – eMarketer. [online] Available at: https://www.emarketer.com/Article/Mobile-Phone-Smartphone-Usage-Varies-Globally/1014738 [Accessed 13 Feb. 2018].

Karwatzki, S., Dytynko, O., Trenz, M. and Veit, D. (2017). Beyond the Personalization–Privacy Paradox: Privacy Valuation, Transparency Features, and Service Personalization. Journal of Management Information Systems, 34(2), pp.369-400.