Platforms as service ecosystems: a new economic organization around data
May 14, 2020
- The paper specifically analyzes the case of Tripadvisor, but it also mentions other social networking platforms such as Facebook and Instagram: what is meant by the concept of “ecosystems” associated with these platforms?
Digital ecosystems are highly interesting collaborative forms because they offer the actors who participate advantages that cannot be acquired by taking part in existing collaborative configurations, such as supply chains or networks. Ecosystems are different because they are multi-actor associations characterized by synergies and complementarities that would not emerge in other types of configurations. Whereas in networks, bilateral ties represent the minimum unit, in ecosystems the minimum unit is represented by multilateral ties of actors where the complementarities of activities, resources and outputs emerge, constituting their added value.
The concept of complementarity is therefore central to digital ecosystems and refers precisely to the benefits that each actor can extract from linking with the activities, resources and outputs of the other actors. To go back to your questions, we used to think of TripAdvisor or Facebook merely as places of exchange. For example, we use Facebook to acquire information, to see the news feed of friends, in exchange we leave our digital traces and data. We recently learned that Facebook takes our data and sells them to advertisers and marketers in exchange for money. This way of thinking about platforms limited to exchange, however, is both highly reductive and deceptive, because it prevents us from observing the mechanisms of production of digital goods and of data-based services. How does the production of digital goods work? This is the reason why the concept of ecosystem can be important: it can, in fact, help us understanding what are the relevant multilateral links and complementarities which enable Facebook to produce digital goods and extract value from user-generated data. Facebook, Instagram and Tripadvisor have not become giants of the digital economy because they facilitate exchanges but because they are able to produce data-based services. It happens because these platforms are part of complex ecosystems where value is created from the production and exchange of data, therefore they must be studied and regulated looking at the entire ecosystems in which they belong. The ecosystems perspective allows us to ask questions about the type of goods that are produced, as well as on the production methods and concept of value upon which these ecosystems operate. To ask the right questions, however, we need to understand how the production of digital goods takes place, how ecosystems are formed, how they emerge, otherwise there is the risk of looking at the platforms, to regulate them or to study them, without taking into consideration the value chain and complementarities that structures them into ecosystems.
- The paper shows how the use and the purpose of these platforms has changed over the years: can it be said that today they have become real economic organizations?
This question made me consider how hard is sometimes to conceive that some of these platforms have already been active for twenty years. Twenty years in the internet age is the equivalent of centuries in normal time! Smartphones, for example, did not exist twenty years ago, nor did all the uses related to their technology and to mobile connectivity in general. There were no location data, no selfies, no likes, in short, there were none of the features and related data that have now become commonplace. Returning to the platforms and their change in use, one way to think about it is therefore to put it in relation to technological developments, as in the case with the functions acquired thanks to smartphones. Yet, this alone is not enough, to understand how platforms have changed in recent years and how their organizational and economic environment has expanded, it is also necessary to consider how they have been able to transform the use of technology into resources, and in particular how they have been able to transform all user activities into data and to use these data as resources. If the changes in use depend on the technologies adopted, the expansion of the economic and organizational sphere of these platforms, i.e. the fact that they can become productive ecosystems, essentially depends on their ability to acquire technologies and organizational tools that allow them to produce data and to innovate. Digital platforms have always been real economic organizations, they were born as for-profit companies, what has changed in the last twenty years is the economy. The economy today, unlike twenty years ago, primarily means data economy. This is one of the central contributions of the paper, which is illustrated very well by the evolutionary paradigm of Tripadvisor, but which also concerns many other digital platforms. The engine of innovation, especially today and particularly for some sectors of the economy, are the technologies of data production, acquisition and data analytics and the organizational and strategic changes to which they must be accompanied in order to generate value. Technology alone won’t take you anywhere, it needs organizational changes to innovate responsibly and sustainably. There is still much to be done to structure this new economic paradigm and help companies to act with a long-term strategic vision.
- What data did you analyze in the case study of Tripadvisor, starting from the identification of the three main stages of the platform evolution (initially a simple travel search engine, then a social media platform and finally an ecosystem of end-to-end services)?
We used several sources; we first conducted a pilot case which was mainly based on data obtained from interviews; we interviewed hoteliers and other companies that work with Tripadvisor using a classic qualitative approach. This allowed us to formulate our research questions and to understand what activities were behind the Tripadvisor interface. We began to map the presence of a series of actors, such as Internet Booking Engines (IBEs) or Online Travel Agencies (OTAs), whose activity is often unknown. Still, these are key players for TripAdvisor given that, for example, IBEs process hotel reservations and room price data in real time and transmit them to TripAdvisor. The pilot case led us to understand that we were facing a giant, complex and fascinating ecosystem. We then undertook the principal case study. The data we used were mainly archive data, from the Tripadvisor media archive. We collected 3,388 press releases, of which 1,677, in English, served as the body of our data. We used different methodological tools: first we carried out a thematic analysis, then we mapped the content of the whole database by themes, after that we reconstructed a timeline of TripAdvisor activities. The integration of all the analytical steps let to the emergence of the three evolutionary phases of Tripadvisor (travel search engine, social media and ecosystem of end-to-end services). Successively, we validated our analysis’s results with a co-term network analysis, a computational technique of analysis, or text mining technique, that allows to measure the frequency of a set of words in a text and to aggregate the words that tend to be frequently used together in networks. Such an innovative methodological approach is part of the so called digital methods and consists in the quantitative reading of the text, which is very useful particularly when integrated with other methods. Relying solely on a quantitative analysis of the text, would not give the possibility to understand its content, therefore a qualitative reading is also necessary. Co-term network analysis is a very powerful tool to validate the results of thematic analysis and to visualize the connections between themes. In our case, the co-term network analysis confirmed our results and helped us to strengthen our research methodology.
- The research has made visible the set of reciprocal relationships existing between different types of data, services, actors, technological operations: how can this evidence influence the choices of social media and thus society itself in the future?
This is a fundamental and also very complex question. It is clear that at this moment we are at a strategic crossroads: today there is the awareness that innovation will start from data. So often we hear catchphrases such as “Data is the new oil”, but we have not yet found a vision or model capable to direct social and economic development in this sense. What kind of society do we want? We talk a lot about data, but in reality we know very little still about data, and above all, we know almost nothing about how they are produced within organizations and ecosystems. There is still little discussion about the organizational practices that have been put in place to produce data. I am not talking, of course, about the technical aspects of data production, but about how organizations are changing due to the innovative modalities of value creation which emerge around data production.
For instance, what kind of business models are best suited for these new organizational processes? This point connects to your question on social media as right now we are witnessing a great change in this area. On the one hand there are giants like Facebook who use a business model that is almost completely linked to marketing and advertising. Such a model, as it has been demonstrated in recent years, is not sustainable, has very high social and economic costs. In the case of Facebook, its monopoly had led, among other things to the failure to develop alternative models a social cost that still await to be taken into consideration. Facebook will try to move onto other types of operations and business models, it tried with cryptocurrencies, but it seems to have failed. For giants like Facebook it will be difficult to move from the marketing of personal data. Other platforms such as Linkedin or Tripadvisor have been trying to break away from this business model, seeking to open up to the innovation and diversification of their services thanks to the use of different typologies of data. These platforms have become producers of data-based services with which they have gained competitive advantage. Tripadvisor, if we think about it, does not sell holidays and is not a tour operator. Its leadership in the hospitality sector, comes from the platform’s ability to produce, for instance, popularity indexes, personalized booking suggestions in real time, data and content analytics tools for hotels, and contents of different types. All of these are data-based services, services created by aggregating different types of data. Our study shows that the production of data-driven services depends on the formation of virtuous multi-actor bonds that lead to the emergence of ecosystems. Here is another interesting result of our research: digital ecosystems are data-based, they emerge out of complementarities linked to the production and exchange of different types of data.
As for the second part of the question, that is, the effects on society, it needs to be considered that we are at the beginning of a paradigm shift. As we have seen, some social media are moving in this direction, others are trying, not everyone will succeed. It is very difficult to make predictions, but we can certainly say that with the diffusion of new technologies, with the proliferation of smart objects and the related production of new types of data, as for example, in the case of Internet of Things, the role of data and their complementarities will undergo a very powerful acceleration.
The results of our study are clear: there are new and interesting processes in place which demonstrate that the future of competition will be played strategically on the connection between value and data, a very important combination that has profound economic and social implications. The connection between value and data has an extraordinary strength which requires a much wider reflection that includes but goes beyond possible economic implications. The debate on the value-data combination should be opened at different levels, at the level of individual organizations, at the level of ecosystems, but also at the public or societal level. With our study, we have tried to help clarify some of the dynamics related to the production of data-based services by documenting the mechanisms of value creation within digital ecosystems. Yet, the game is on. Companies that want to innovate from data must be aware that technology alone is not enough. Long-term vision, strategic planning, training of human resources, sustainability and social responsibility are necessary conditions to build a data-driven economy.