Incentive mechanism in social networks key to governance
Many cities in China have launched social platforms to record users’ low-carbon activities including green transport, garbage-sorting, and philanthropy. The platforms award points with multiple applications. Photo: CFP
In the “internet plus” era, social communication networking trends have profoundly changed interactions between individual members, between organizations, and between individuals and organizations. Driven by each of their specific goals, social networks’ interaction efficiency is affected by network structure, interaction frequency, network node energy levels, and intensity of rewards and punishments. A typical incentive mechanism design makes specific rules which promote efficient interactions in specific social networks.
As of today, traditional organizations’ boundaries have increasingly blurred, and it is common for social network interactions to move beyond boundaries. Accordingly, incentive mechanisms for social networks are also different from traditional incentive mechanisms which are confined by organizational boundaries, and discussion of participation, growth, and innovation may help to construct social network incentive mechanisms in the new era.
Participatory incentive
In order to engage more individuals in a particular network, expand the scale of interaction, and enhance the frequency of interaction, it is better to engage network relationships built on individual interactions than to use traditional means to encourage individuals. Take for example the promotion of a green and low-carbon life in various cities in China. If an individual carries out a low-carbon life, they will be rewarded with points that can be used to buy movie tickets, shop, or use public transportation. More importantly, one can see how well their friends are doing and earn extra points by inviting friends to join the campaign, so that people are more willing to participate in green and low-carbon actions out of peer encouragement.
Tiktok, a platform launched by Beijing-based Bytedance, has attracted more than 800 million users in just a few years using similar incentive methods, such as likes, followers, and comments.
Similarly, the Smart Travel reward program in Singapore has successfully encouraged more than 380,000 participants by using “likes” from friends in their social networks to adopt alternative modes of travel during peak hours, which effectively reduces the traffic load by 10% during rush hours and optimizes public transport.
In congressional elections in the United States, voters need to be incentivized to vote, and hearing that a friend is voting is four times more effective than simply telling citizens that they should be voting. Airbnb’s promotion strategy also centers on social network relationships. If a customer invites friends to register, both parties receive a considerable reward. When the incentive compensation is greater than the participation cost, according to the principle of incentive compatibility, individuals are more willing to comply. This incentive compensation can come from an individual’s personal gain of pleasure and satisfaction resulting from respect, appreciation, identity, and reputation in network relationships.
Network relationships motivate by encouraging individual externalities in social networks. When an individual’s network relationship is stimulated, one is more likely to participate, which improves the interaction efficiency of the whole social network. Interestingly, this kind of encouragement in network relationships does not necessarily always translate to economic incentives, such as money and material rewards. These incentives could work as an effective set of rules for friends who are already organically interacting with each other, such as giving small red flowers to each other, gaining likes, collecting points, and having the opportunity to reach different promotional levels, and so on.
Growth incentive
Individual behaviors in social networks are embedded in their specific networks, meaning that when one interacts with others within social networks, their behaviors are influenced by the actions of others. This network interaction can benefit individual growth in two ways.
First, the collective intelligence generated by network interactions promotes individual knowledge accumulation and information learning. In his book Smart Society, Alex Pentland, an expert on big data from MIT, cited a large number of cases which proved that in the social media era, the flow of ideas among individuals produces collective intelligence, which is further developed in an information exchange at each node of the social network. The wisdom of crowds also promotes the growth of each individual in a social network.
Second, network nodes with strong energy levels provide high-quality experiences and information for individual growth. A working paper from the London School of Economics provides strong statistical evidence that social networks have a significant impact on individual progress, and that working with colleagues who are stronger than you is associated with higher job productivity. The synchronicity between nodes of strong network relationships will create positive pressure for growth. Mutual influence and imitation can prompt individuals to change their habits, and produce synchronized behaviors within a team.
The more an individual directly establishes a relationship with other individuals in a network, the more resources one obtains, the higher the frequency of information exchange, and the faster one will grow. The stronger an individual’s ability to control or intervene in interactions with other individuals, the more opportunities one has to be noticed and understood, the more one receives opportunities to share and communicate, and the greater the opportunity for growth. Similarly, with closer interactions between individuals and others, transmission of knowledge between contributors and recipients becomes faster and wider, and as knowledge and information are shared more frequently, individuals grow faster.
Surveys in China show that information exchange concerning entrepreneurial plans and opportunities in social network interactions have a significant impact on the growth of China’s sci-tech entrepreneurs. To conclude, individual growth has an incentive mechanism hidden in social networks.
Innovation incentive
The strength of interpersonal ties can be defined as combinations of time spent in interaction, emotional intensity, intimacy, and reciprocal services. Building on this, American scholar Mark Granovetter has categorized interpersonal ties as strong, weak, or absent.
First of all, strong tie relationships are defined as frequent interactions and close mutual contact where trust can facilitate efficient and smooth knowledge sharing and communication, reduce the information flow cost, increase the dissemination of ideas and information, and promote creativity and innovation among members. Moreover, strong ties are conducive to spreading complex knowledge. Only strong ties can realize effective non-explicit knowledge sharing such as experience and comprehension. It is easy to unite goals and visions among people with strong ties, so they can take concerted actions, reduce conflicts, and achieve effective cooperation, which are important foundations for innovation.
Second, relationships with weak ties are characterized by infrequent interactions and ties between casual acquaintances. While strong ties provide bonds, weak ties serve as bridges: they provide more efficient access to new information. Weak ties are the people we know casually, so there is great variety in the information exchanged and diversity of knowledge shared. Weak ties thus play an important role in information dissemination across heterogeneous networks and networks of different levels, taking on an unexpected role in promoting knowledge, ideas and technological innovation. Innovation activities need to be carried out based on diverse information, views, and ideas. Only when different objects are connected can new concepts be produced. Without diversity, innovation is nearly impossible to achieve.
Next, when weak ties are connected to more than two strong ties, information, knowledge, and resources can be fully precipitated and absorbed into the strong ties, and then innovation occurs through weak-tie cross-network communication. Weak ties can break the echo chamber effect of strong ties and avoid blind spots in thought processes. According to research, it is more likely for an entrepreneur to have a new business idea through a weaker than a stronger relationship because strong relationships are typically formed between like-minded individuals, and tend to reinforce the insights and ideas which people already have.
At the same time, a “structural hole” is a gap between two individuals who exhibit complementary skill sets or knowledge. In contrast to a weak tie, which deals with the strength of the relationship between two connections, a structural hole is a “chasm” or absence of a tie between two connections. Research has linked entrepreneurial success to structural holes in entrepreneurs’ social networks. When we exploit structural holes in our network, we can broker opportunities and combine knowledge in new and exciting ways.
In the context of “internet plus,” information technology’s development provides more opportunities for interaction between individuals, this establishes weak ties, and the social learning which ensues is easier than before, increasing the probability of impact, a collision of ideas, and breakthroughs. A good example of this is Tencent Music’s innovation of “digital reality integration.” They apply artificial intelligence and other cutting-edge technologies to music production and circulation, and actively seek creative works and inspiration elements from the vast number of independent musicians and free creators on the internet.
To say the least, strong and weak ties in social networks are essential to the foundation for innovation and breakthrough. A balanced number of strong and weak ties in society can effectively stimulate innovative activities.
In summary, interactions between social networks contain incentive mechanisms for participation, growth, and innovation. Participatory incentives can expand the scale of social networks, growth incentives can promote the progress and maturity of participants, and innovation incentives based on strong and weak ties can inspire innovation. Optimized design of all three incentives can achieve unexpected effects and goals, so that all network participants are greatly rewarded.
Against the backdrop of “internet plus,” many interaction obstacles created by geographical distance and space no longer exist, information dissemination costs are greatly reduced, and the speed of information exchange increases exponentially. Mobile devices enable rapid and convenient information reception and feedback, and improve interaction efficiency at the technical level. The incentive mechanisms for participation, growth, and innovation in social networks show unprecedented vitality and importance.
Zhou Bihua is an associate professor at the School of Political Science and Public Administration at Huaqiao University.
Edited by YANG XUE
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