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Examining social distance in the sharing economy

ZHENG XIAOBI | 2019-01-18 | Hits:
(Chinese Social Sciences Today)

Yunmanman (literally full loading), China’s leading road freight dispatching platform, has redefined the land-based logistics scene, having connected businesses requiring cargo delivery with 78 percent of the nation’s heavy truck drivers in more than 350 cities. Photo: FILE


In recent years, the emerging sharing economy, represented by ride-hailing, knowledge sharing and shared bikes, has achieved rapid development. According to the 2018 annual report on the development of China’s sharing economy released by the State Information Center, the transaction volume of China’s sharing economy market reached 4.921 trillion yuan in 2017, up 47.2 percent year-on-year.

In addition to improving the utilization efficiency of idle resources, the sharing economy expands the traditional acquaintance relationship to a broader group of strangers. The interaction distance and mutual trust levels of members of society are changing significantly, resulting in different sharing economy business models and incentive methods.


Shorten social distance
The development of the sharing economy is not the result of the deliberate designs of government and internet platforms, but the derivative of dynamic changes in social distance.
The main idea behind the concept of social distance is that any given social relationship—let it be between individuals, between groups, or in the intercourse between the two—involves elements of “nearness” and “distance.”

Only when the social distance exceeds a breaking point will the society form a sharing economy, which in turn promotes the transition of traditional acquaintance acceptance to commercial trust and improves the frequency of interactions and the level of trust among members of society.

With the development of internet technology, content providers can utilize the internet to achieve “ultra-connective” sharing communities with a broad audience, so as to complete transactions at a faster speed and more frequently, thus shortening the social distance and eventually promoting the coverage of the sharing economy.

For example, many short-term rental platforms in China are embedded with third-party payment services such as Alipay and Finalpass. Content providers, consumers and multiple services providers are able to build a value-creating network to realize a multi-directional cross-border connection.

At the same time, the development of the sharing economy expands a person’s circle of acquaintances into a “society of strangers.” For example, in the case of online car hailing services, the original behavior of private car owners is mainly personal, and private cars are mainly used within the interpersonal network familiar to the car owner.

However, with the emergence of online car-hailing platforms, private car owners can efficiently and conveniently provide idle private car services to strangers, thus expanding the interaction scope of members of society.

Therefore, in the sharing economy community, the trust and interaction among people are changing. Frequent contact is conducive to improving the level of mutual trust, and thus reducing the social distance between the content providers and users, which comes back to benefit the development of the sharing economy.


Four business models
With reference to British sociologist Anthony Giddens’ theory of social trust and the mutual enhancement mechanism of social distance and the sharing economy mentioned above, the emerging sharing economy could be seen as represented by four business models, namely personal, organizational, coordinative and professional sharing models.

For the personal sharing model, the most typical case is C2C (Consumer to Consumer) sharing, which accounts for more than 80 percent of all the sharing business in this category.

With the aid of internet platforms, owners of idle resources can match information with users and make direct contact. Due to a large number of content providers that are specialized providers of certain idle resources, the internet platform does not need to organize production.
More importantly, as sharing is oriented to a large number of content providers and users who can easily interact with each other, the personal sharing economy has the signature of positive network externalities. C2C sharing modes such as Didi Chuxing, Airbnb, Zhihu and Renren Express are typical representatives.

For the organizational sharing model, B2C (Business to Consumer), such as shared bikes, is the most representative. Shared bicycles are not idle resources, and their ownership belongs to the platform enterprises. The platform transfers the right to use its assets to consumers, so it is a “one-to-many” time-sharing lease, in which the internet platform plays a role in the leasing of its own assets and in information matching.

In this sense, the bike-sharing operating firms do not establish a direct interaction with users, so users tend to direct an impersonal trust on the whole sharing system, and the social distance between content providers and users is relatively long.

At the same time, platform enterprises not only provide matching services, but also invest resources to organize production, so the degree of specialization is low.

In this light, the sustainable development of the organizational sharing model depends on whether the social distance can be shortened and the degree of specialization can be improved.
In addition, due to the existence of a single producer in the upstream link and a large number of users in the downstream, the externality of the sharing model is at a medium level.

For the coordinative sharing model represented by C2B (Consumer to Business), content providers with idle capacity and time can match the demand of enterprise users through internet platforms and complete transactions.

For example, G7 is a Chinese internet of things and big data company specializing in intelligence-powered fleet management. On the G7 platform, truck owners with idle capacity and time and enterprises in need post their information, and they do not have to carry out direct interaction. The platform will realize the information matching, scheduling and coordination, so the social distance between content providers and users is long.

However, truck owners mainly provide professional services to enterprises, so the specialization of the coordinated sharing model is high. At the same time, due to a large number of enterprises and truck owners aggregating and distributing on the internet platform, the network externality is positive.

For the professional sharing model, both supply and demand ends are enterprises, so it is a typical B2B sharing model. Capacity sharing platforms such as Floow2, Yunmanman and Haichuang provide information matching and professional services for the owners with idle capacity and users, so it has a very professional specialization.

From the perspective of social distance, since enterprises and users need to conduct in-depth interaction and communication directly, the level of mutual trust between them is often high and the social distance is short.

In this sense, this sharing business model has broad prospects for development. However, due to the professionalism of production capacity, the number of content providers and enterprise users are both small, so the network externality is mainly limited to a certain group.


Policy advice
To promote the sustainable development of the sharing economy, efforts can be made to shorten social distance in the areas of implementing differentiated policies, building sharing communities and establishing data sharing mechanisms.

First, it is important to introduce and implement differentiated policies. For the personal sharing model, the key is to manage the security risks. For example, different municipalities across China are taking action and asking for additional security for customers in the wake of the scandal engulfing Didi Chuxing. Didi has now suspended its Hitch ride-hailing service nationwide after a murder allegedly committed by one of its drivers.

For the organizational sharing model that takes up public resources, the government should not only construct the ecosystem and shorten the social distance, but also standardize the development of different business models through policies and technical means to achieve a dynamic balance between the profitability of platform enterprises and public resources.

For the coordinative sharing model, due to its long social distance and positive externalities, the government should encourage the introduction of intelligent technology devices to promote the effective allocation of idle resources.

For the professional sharing model with low externalities, the key is to build an alliance conducive to capacity and information sharing.

Second, in sharing communities, frequent value-added interactions among users promote the level of trust, thus reducing social distance. Sharing communities are not exclusive to cross-border integration. The mixture of social needs, knowledge sharing and payment services on internet platforms means that cross-border integration itself can constitute the value growth mechanism of sharing communities.

To this end, we can effectively make full use of the online communities such as Makerspace for “connecting everything,” to achieve multi-directional connection and shorten the physical and psychological distance of interaction.

Lastly, a three-dimensional credit data sharing platform can be established among the central and local governments, cities, and enterprises to facilitate the connection of credit platforms at all levels and establish a mechanism for information cooperation and sharing.

Big data, cloud computing, third party certification, and credit rating should be facilitated to gain credit data. The market analysis, utilization and dissemination of this data can enhance data security and bridge the digital divide.

Finally, the government and platforms should actively promote the safe operation mechanism of the sharing economy. It is critical to strengthen the safe operation responsibility of platform enterprises and improve their awareness and default costs through credit data, disciplinary supervision and other means.


Zheng Xiaobi is an associate professor from the College of Economics and Management at Zhejiang Normal University.

​(edited by YANG XUE)