The Commercialisation of the Internet
The Internet connects global connectivity. With the rapid development of the sharing economy and network platform, Multi-stakeholder governance gradually comes to people’s attention. It brings together multiple stakeholders to participate in dialogue, make decisions implement responses to commonly perceived problems, and solve problems. If multiple types of participants are involved in the platform with input, then consensus decisions after negotiations will be more legitimate and inclusive.
The range of stakeholders is a collection of actors from different socio-economic fields, and their range can include media personalities, multinational corporations, national enterprises, and other institutions. Take TikTok as an example, users (Internet celebrities and distributors), advertisers, platform operators, and network operators will rise rapidly with the full penetration of the Internet into social and economic life in the modern media-dominated society. Some platforms occupy a dominant position in their respective markets, for example, Uber almost occupies the travel market, Amazon occupies the market position of online shopping and online sales, Internet platforms have accumulated a large amount of wealth, and digitialization creates a super platform, and stakeholder participation equalizes the network platform economy. This article mainly analysis how the emergence of multi-stakeholders regulates the network platform economy and separately analysis the advantages and disadvantages of multi-stakeholders.
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First, the emergence of multistakeholder regulates platform data, social trend and the algorithm – “digital platform operations are part of larger processes referred to as digitalization and datafication.” (Mansell, & Steinmueller, 2020). Data built the Internet. In the process of platform operation, many Internet platforms will allow consumers to provide free services, the cost is to provide data, and the data is monitored in real-time. Users use data as currency to pay, and many platform enterprises collect a large amount of data to track users. Internet platform Due to network effects and the use of data optimization platform services, taking UberEats as an example, users are exchanged for enjoying UberEats service when registering. UberEats provides users with three steps in “How to use the UberEats app”. Users can scroll through specific restaurants. “From search results to the list of restaurants and explicit recommendations on the app’s home screen, we tailor the selection and ranking of restaurants to our understanding of what our eaters crave.”( Yuyan Wang& Yuanchi Ning& Isaac Liu, Xian Xing Zhang, 2018). When you are ready to check out, you will see the address, the estimated delivery time, and the price of the order, and finally the tracking – the delivery of the order to the door, providing their browsing data to the platform developer, the user has agreed to the privacy agreement when signing up for the platform account to continue to use the platform, the platform developer uses the advantages and privileges of these developers to promote the business. It has increased the services of online delivery and online shopping, as well as the promotion and advertising within the platform. Advertisers use the platform to promote products and software. For example, they cooperate with Uber to provide all goods delivery services on the homepage of Uber Eats, so that users can enjoy the convenience brought by the network inside the platform and increase the traffic advantage within the platform. More and more people choose Uber Eats as the platform, and the trend advantage can also affect the formation of users’ opinions. Just as “The search engine manipulation effect (SEME)” proposed by Robert Epstein, search engine manipulates users’ information to effectively influence users’ tendency. As a member of the stakeholder, Uber operators also have advertisers, who use SEME to strengthen the traffic advantage of the platform. For example, when searching for a food delivery platform in the Apple app store, Uber Eats is recommended first, and in product promotion, they will generally recommend corresponding products according to the search results of users.
In addition, multi-stakeholders also bring advantages that cannot be ignored. They can adapt to the fast-paced changes of the digital economy more quickly and meet people’s personalized and diversified consumption needs. In a delivery system like Uber Eats, I define multi-stakeholders as three main stakeholders, users, restaurants, and deliverers. Users need to solve problems related to food and delivery. Restaurants need more exposure and money, while deliverers have more flexible delivery times and satisfactory monetary returns. “By creating a two-sided market, digital platforms connect consumers who seek resources with resource owners who can offer resources,” (Guo& Zeng. 2019). None of these three stakeholders can operate Uber Eats, which means that all stakeholders get the benefits they need in terms of platform economy. Allowing a wider range of voices and professional innovation, bringing in companies with proven technologies, encouraging the sharing of information and knowledge, and enabling all parties to share data, research results, and practical experience, Mansell and Steinmueller also put forward the view that “the exogenous arrival of a new technology is a potential” engine of growth.” (Mansell, & Steinmueller, 2020). The digital economy is becoming an important area of cooperation between different countries, the development of the digital economy has broken geographical restrictions, and through the Internet and mobile communication technology, different countries and different enterprises and individuals have more convenient and efficient cooperation, multi-stakeholder approach makes it easier to reach consensus on Internet governance and digital policies.
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However, there are still challenges in the emergence of multi-stakeholders, Markets are assumed to be competitive. “Multisided platforms need to satisfy both the consumers of recommendations and the providers of items that are being recommended.”(Abdollahpouri& Adomavicius& Burke& Jannach& Kamishima& Pizzato,2020). Aligning stakeholders’ interests is time-consuming and complex, Abdollahpouri and Burke proposed that “Stakeholders do not have necessarily be the consumer of recommendations nor do they have to be the provider of the items being recommended. “The provider of the items being recommended.” Uber Eat will also affect the recommenders, the recommencers, and the deliverers, and will change their preferences. If a restaurant is frequently recommended to the home page, it will affect the choice of new users.”Allowing information to have economic value by assuming it is unevenly distributed opens the door to considerable as well as difficulties in observations.”(Mansell, & Steinmueller, 2020), it may reflect bias towards the suppliers. It’s a probabilistic event. The recommender will pay more attention to the profit, they not only have to consider the reputation of the business, but also need to consider the benefits that the business can bring to the platform, and the workload assigned to the delivery personnel should also be considered in this system. The fairness of the platform system is also an issue that needs to be considered to balance the rights allocated by various stakeholders. However, the reality is that large companies often bear more responsibilities and risks than small groups, and the influence of large companies is greater than that of civil groups, but the needs and preferences of small enterprises should also be fairly taken into account. Moreover, since stakeholders have a cooperative relationship when they supervise the network platform, the decisions they make for the process do not have a strong execution mechanism, which makes it a challenge to comply with the agreed rules.
References
Mansell, Robin, and W. E Steinmueller. “Economic Analysis of Platforms.” In Advanced Introduction to Platform Economics. United Kingdom: Edward Elgar Publishing Limited,2020. https://ebookcentral-proquest-com.ezproxy.library.sydney.edu.au/lib/usyd/detail.action?docID=6317825#
Abdollahpouri, Himan& Burke, Robin (2019). Multi-stakeholder Recommendation and its Connection to Multi-sided Fairness. https://www.researchgate.net/publication/334772875_Multi-stakeholder_Recommendation_and_its_Connection_to_Multi-sided_Fairness
Guo, Y., Li, X., & Zeng, X. (2019). Platform competition in the sharing economy: Understanding how ride-hailing services influence new car purchases. Journal of Management Information Systems, 36(4), 1043–1070. https://doi.org/10.1080/07421222.2019.1661087
Abdollahpouri, H., Adomavicius, G., Burke, R., Guy, I., Jannach, D., Kamishima, T., Krasnodebski, J., & Pizzato, L. (2020). Multistakeholder recommendation: Survey and research directions. User Modeling and User-Adapted Interaction, 30(1), 127–158.
https://doi.org/10.1007/s11257-019-09256-1
Yuyan Wang& Yuanchi Ning& Isaac Liu& Xian Xing Zhang.(2018, September,10). Food Discovery with Uber Eats: Recommending for the Marketplace. Uber Blog.
https://www.uber.com/en-AU/blog/uber-eats-recommending-marketplace/