From Transactional to Relational: How the Sharing Economy Promote Social Trust


One of the most remarkable traits of human beings is their capacity for empathy, care and sharing. These qualities are essential for building strong social bonds, fostering cooperation and promoting well-being. Human beings are not selfish or violent by nature, but rather have an innate tendency to understand and help others (Decety & Cowell, 2014).
The sharing economy has enabled people to connect with each other and share resources in new and innovative ways. It created new opportunities for people to monetize their assets, it has also led to the emergence of new business models, such as peer-to-peer lending and crowdfunding, which allow individuals to invest in and support each other’s projects and ideas (Botsman R, 2010). However, the sharing economy has also raised important ethical and social questions. For example, how do we ensure that the benefits of the sharing economy are shared fairly and that everyone has access to the resources and opportunities they need? How do we address issues of inequality and discrimination in the sharing economy, and how do we ensure that everyone has the opportunity to participate and benefit from it?
In this blog post I will explore some of the trust issue evidence and implications of modern economy human sharing. I will also suggest some ways to cultivate these qualities in ourselves and others, and how they can help us overcome the challenges we face in the modern world.

Sharing is based on trust, and trust drives sharing

The sharing economy is a complex and multifaceted phenomenon that involves the sharing of a wide range of assets and resources. According to the specific form of shared assets, it can be divided into two categories: tangible asset sharing and intangible asset sharing. Tangible assets sharing are physical items that have value and can be used for business or personal purposes. These assets can be the platform owner provided or peer to peer sharing. Examples of tangible assets include space (land or buildings), equipment, vehicles, inventory, etc. The benefits of the sharing tangible asset mainly include: cost savings, increase efficiency and flexibility (Botsman & Rogers, 2010), reducing the environmental impact of overconsumption (Belk, 2014), and most important fostering social connections and trust among communities (Hamari et al., 2016). But trust is a double-edged sword. Trust can enhance relationships between people, promote cooperation and communication, and improve efficiency and happiness, encouraging innovation and entrepreneurship; but trust can also lead to being deceived, used, hurt, or even losing everything.

TED speech by Paul Castagno: The Power of Believing in Others

Tangible assets sharing

Co-working, a form of shared workspace where individuals or small businesses rent desks, offices or meeting rooms in a common facility, usually on a flexible basis. This can reduce overhead costs, increase networking opportunities and foster collaboration among like-minded professionals (Spinuzzi, 2012). However, since Co-working spaces often involve sharing resources, information and contacts with strangers or competitors, which can create a sense of insecurity or vulnerability. How can co-workers in same company or different build trust and foster collaboration in such a dynamic and diverse environment? How to establish clear and respectful boundaries in public spaces such as rented meeting rooms, or public air-conditioning, or public parking spaces? Besides setting clear rules and expectations, communicating openly and honestly, and giving and seeking feedback, is there anything else we can do?
Moreover, Car-sharing services such as DiDI, Uber (peer to peer) and Hertz(platform owned)have become increasingly popular in recent years, offering convenience, affordability and flexibility to millions of users. However, these services also face some challenges, especially regarding the trust issue between drivers and passengers. How can car-sharing platforms ensure that both parties are safe, reliable and respectful during the ride? How can they prevent or resolve potential conflicts, disputes or accidents that may arise? How can they build and maintain a positive reputation and customer loyalty in a competitive market? These are some of the questions that car-sharing providers need to address in order to overcome the trust issue and enhance their service quality and user satisfaction.

One possible solution is to apply personal identity verification, with service/feedback, rating and insurance systems. This mechanism would request all users to verify their identity, credentials or qualifications, such as photo ID, social media profiles, licenses or certificates. These can increase the credibility and legitimacy of users and reduce the risk of fraud or deception. Later, the mechanism allows users to rate and review each other based on their past experiences, such as ratings, reviews, testimonials or endorsements. These can provide useful information and feedback for potential users and incentivize good behavior and performance among existing users (Dellarocas C. 2003). And don’t forget the Insurance systems. It can reduce the uncertainty and liability of users and encourage them to participate in the sharing economy (Mohlmann, 2016).

The other possible solution is to use smart contracts. Smart contracts are self-executing agreements that are written in code and stored on a blockchain.

(Conceptual picture of “Smart Contracts” by ChengYi Gu Generate by DALL-E 3 is marked with CC0 1.0 Universal ).

This solution can enhance trust in tangible assets sharing by reducing transaction costs, increasing transparency, ensuring accountability and security (Wikipedia 2021, October 11). By using smart contracts, both parties can avoid intermediaries or third parties that may charge fees, cause delays, or introduce errors or fraud. Both parties can also verify the status and outcome of the transaction on the blockchain without relying on external sources of information or verification. Both parties can also be assured that the agreement will be executed as intended without any manipulation or interference. Smart contracts can also enforce penalties or incentives for compliance or non-compliance with the agreement. For example, a smart contract can deduct a fee from the user if they return the asset late or damage it, or reward the owner if they provide a high-quality service or receive positive feedback. (Jani, S. 2020)

Intangible assets sharing

Intangible assets, on the other hand, refers to the sharing of services, skills, and expertise. This can include things like freelance work, where individuals offer their skills and expertise to clients on a project-by-project basis (Will Kenton, June 13, 2023). It can also include sharing of knowledge and information, such as through online courses or peer-to-peer learning (Coursera, Khan Academy, Wikipedia, ZhiHu, etc.). However, intangible asset sharing can also be more difficult to quantify and monetize. So it is both easy to obtain, and lacks proper regulation as well either by the government (as in P.R.China and Russia) or the platform operations themselves (as Western Corporate style). Hence, the intellectual property theft, data reliability and privacy are always the challenges associated. For instance, Wikipedia, the most popular free online encyclopedia that allows anyone with an internet connection to access and contribute to its vast repository of knowledge, have been deliberately falsified many times. The most recent major impact was discovered in 2022, also known as “Zhemao hoaxes” (Wikipedia 2023, August 14th). From June 2019 to 2022, Wikipedia editor “Zhemao” created more than 200 entries on Wikipedia about events related to ancient Russian history, made 4,800 edits, and wrote millions of words. These most of the false entries compiled by Zhemao cited reference materials, but some of the reference materials themselves were fabricated and false. These entries have even been translated into the English, Arabic, and Russian versions of Wikipedia. Zhemao also used self-made maps, self-made statistical charts, and the use of photo appropriation to make the details of the entries more perfect and make the overall look more real.

A map “made” by Zhemao, now deleted from Wikipedia. by Wikipedia is licensed under CC BY-NC-ND 4.0 

As we know Wikipedia is famous for its professionalism that every excellent entry must have a citation. However, for a user who is familiar with citation conventions and Wikipedia’s editorial rules, it couldn’t be easier to direct and perform a farce although wikipedia regulated by inspector which also requires its users to cite verifiable authoritative information as much as possible when editing to ensure the neutrality and reliability of the article content. Zhemao, for instance, has made himself an authority in Wikipedia by fabricating one entry after another. Inspections are mostly targeted at newly created entries and only check whether the entries are plagiarized and whether they have appropriate sources. Thus, she has also been granted immunity from IP bans and inspections. This incident makes people have to seriously think about how to protect knowledge authoritativeness, accuracy and credibility in the sharing process? Knowledge sharing supposed to be a win-win situation for both parties, but how to make a clear understanding of each other’s interests and a commitment to protecting them.
This is not just a problem with Wikipedia itself. In fact, is the academic citation principle followed by Wikipedia really a binding principle? I can’t quite see it. In fact, even in academic papers, as long as you carefully check the footnotes or citation one by one, you may also find many problems. Such as the wrong publish version, the wrong page number, and these are the minor problems (although these problems are enough to trouble subsequent researchers). The possibility of quoting out of context It’s not a big deal; what’s more, it is not rare that indirect quotations that distort the author’s original meaning, or even completely contradict it.
Therefore, information that is highly open, editable, free and shared does not necessarily mean that the information is correct. Because it is equally likely to be unchallenged and unquestioned. Therefore, nowadays, a malicious netizen can easily manipulate and poison the entire Internet’s perception of a specific issue by posting an article, and people who know the true situation may not have the opportunity to correct it. Therefore, you must improve your information literacy and your ability to consult information sources, including logical thinking, analytical skills, and foreign language (multilingual) abilities. You must break out of the information cocoon, have extensive contact with others, and ensure that you can escape from your small circle.


Unlike general online transactions where consumer trust is the main concern, trust in the sharing economy includes multiple trust relationships between platforms, suppliers, demanders, and products (Mohlmann, 2016).

When demanders use sharing services, they first have trust in the sharing platform, and then they have trust in the service providers in the platform and the products or services they provide. The factors forming the two types of trust are different. Users' trust in the platform is a kind of institutional trust, established through various structural guarantee factors provided by the platform. (Pavlou and Gefen, 2004. Sundararajan, 2016) believes that measures for users to build trust in the sharing economy include government or third-party certification, brand guarantees, systems and contracts, communication dialogues, personal characteristics, social capital, user feedback evaluations, previous interactions between the two parties, etc. Mohlmann (2016) took Airbnb as an example to study and confirmed that insurance protection, reviews and platform network scale are important factors that affect demanders’ trust in sharing platforms. User trust in sharing platforms is affected by the quality and design of the platform. The better a sharing platform does in terms of information and privacy protection, functionality and ease of use, the easier it is to win the trust of users. Yang et al. (2016) took the accommodation sharing company Airbnb as an example and believed that in the sharing economy, demanders’ trust in the platform is mainly cognitive trust. The establishment of trust in the platform mainly relies on perceptions of security and privacy, system quality, and the relative advantages of the platform. In addition, users’ trust in the platform may also be a kind of experiential trust. Mittendorf (2017) took Uber as an example, and research confirmed that passengers’ familiarity with the sharing platform significantly affects users’ trust in the platform.

The reputation mechanism based on comments is an important method of building trust among users in the sharing economy (Keymolen, 2013). In the sharing economy, there is a two-way comment mechanism where both parties can comment. Through the reputation mechanism based on reviews, the information asymmetry between transaction parties can be reduced, helping consumers make better choices, thereby avoiding the formation of a “lemon market” (Thierer et al., 2016).

(Conceptual picture of “Multi trust relationship and reputation system” by ChengYi Gu Generate by DALL-E 3 is marked with CC0 1.0 Universal )

On the supply and demand side on the Airbnb platform, if there is detailed personal information on Facebook and connections with common interests, the success rate of renting a house will increase many times. That is to say, if supply and demand parties are allowed to communicate, the degree and level of trust can be significantly enhanced. In order to increase understanding and trust of landlords, online short-term rental platforms such as Airbnb provide video communication functions between landlords and tenants. Visual information such as photos provides consumers with clues to identify donors’ facial features and increases their sense of social presence. (Cyr et al., 2009) proposed that consumer choice behavior is affected by host characteristics and product characteristics, where host characteristics include reputation based on online ratings and credibility based on visuals (photos or video chat).


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