The sharing economy: The challenge of regulating information

The sharing economy: The challenge of regulating information

Phuah Eng Chye (2 December 2017)

Sharing platforms have already built a ubiquitous presence across the globe despite owning minimal assets and having a small number of full-time employees. In doing so, the sharing platforms have demonstrated the tremendous value that can be unlocked from a business model built on information. This also suggests that the regulation of the sharing economy should revolve around the regulation of information.

As Philippe Crist, Tom Voege and Diego Canales point out, new technologies resulting in the capture of a massive amount of sensor-generated data “largely via the proliferation of mobile phones, on-board navigation devices and vehicle-to-vehicle communication”. They note public authorities also often lack the ability to monitor and control the use of this data.

In this regard, government agencies are usually organised along traditional lines of segmentation by activities, assets and localities. Their focus is on regulating activities and tangible assets within geographical localities. But rising levels of information are changing the way activities are organised. As the boundaries around regulatees, assets, activities and localities are erased by convergence and intangibility, regulators either find themselves are running into each other more frequently or gaps open up as new business activities take place in new and unregulated territories.

It is thus a major challenge for government agencies to regulate industries disrupted by information. The government agencies face the challenge of coordinating the regulation of the multiple roles of people, assets and firms in a transient and volatile environment. This causes the regulatory landscape to further fragment; with businesses being subject to constantly changing administrative requirements and duplicative and conflicting guidelines.

The changing landscape reflects the need for government agencies to put information at the core of their regulatory work. The problem is that government agencies are neither incentivised nor set up to manage information in the same way as would a tech company. There are several obstacles.

Tech companies are set up for rapid experimentation. Governments, in line with their accountabilities, are subject to governance and process controls which impedes the speed of decision making and makes mistakes costly and difficult to unwind. The operating costs, incentive structure and culture of tech companies are aimed at achieving technological excellence and market dominance. Governments have large physical components and cost structures that can’t be suddenly disposed. They also need to maintain a public administration structure and culture compatible with achieving public interest goals rather than private preferences.

But perhaps the most overlooked hurdle is confidentiality requirements. The use of information on private citizens is rightly subject to strict controls to guard privacy. But the quality of information increases exponentially with multiple users. Hence, limiting access to information limits potential benefits and sharply increases collection and maintenance costs.

Nevertheless, it is critical is to shift the regulatory process towards a high-information approach to the greatest extent possible. In terms of administration, the traditional approach of physical inspections and monitoring is time-consuming, costly and ineffective. An information-based regulatory model provides opportunities to lower administration and monitoring costs.

In the taxi industry, technological assistance on routes and safety reduces the minimum knowledge and training needed by a driver. Rating systems and profile information on drivers and cars (accident, traffic offences and customer feedback) provides a cost-effective means of improving public safety, confidence and satisfaction. Transparency helps to reduce the risks of scams, accidents and lower administration and enforcement costs. In addition, analysis of user patterns can assist in optimising route coverage and efficiency in transport systems.

To address the information challenge, regulators have several choices. One approach is to compel regulated entities to provide data. Philippe Crist, Tom Voege and Diego Canales suggest this approach should be adopted “when mutual benefits exist – for example, establishing data sharing schemes in return for transport service licensing – or when data sharing is required to deliver on public policy objectives.”

But it is not a simple process to request for data from commercial operators who warily try to keep the process as arms-length as possible. Philippe Crist, Tom Voege and Diego Canales says Uber’s 2016 Transparency Report stated that “governments may request information about trips, trip requests, pickup and dropoff areas, fares, vehicles, and drivers in their jurisdictions for a set time period. Uber notes that in many instances government agencies request overly broad (in Uber’s view) data in relation to the regulatory task at hand. In those instances, Uber reports that they have sought to negotiate with authorities to narrow the scope of the data requested.”

It is also difficult to develop a uniform and consistent regulatory framework for information as the regulation of transport is highly fragmented with a mix of local and federal agencies with different purviews.

There appears to be prospects for collaborative partnerships. Philippe Crist, Tom Voege and Diego Canales highlights several such initiatives. One example is Xerox’s partnership with the city of Los Angeles and the city of Denver to develop a multi-modal routing and booking app that aggregates several modes such as biking, transit, taxi and driving, and additional shared mobility services provided locally such as bikesharing, carsharing and ride-hailing.

Another example is Waze’s public-private partnerships with several cities around the world through their “Connected Citizens Program”. The partnership is based on a mutual data sharing agreement where live data on traffic conditions and major events are exchanged to identify congestion and bottlenecks.[1]

Philippe Crist, Tom Voege and Diego Canales cautioned the ever-increasing accumulation of data by the private sector could lead to a future where “most traffic operations and control responsibilities are effectively outsourced to those that hold the data. In a not too distant future, navigation services providers who are already layering traffic information, digital mapping and navigation algorithms over the road infrastructure, might take control over traffic flows…This shift from public to private control is already happening, e.g. in traffic control centres managed by commercial operators.”

But regulation of sharing platforms and information is in its infancy. The agencies are on a learning curve to define their relationships, their operations and the information they require from the sharing platforms. Over time, it is inevitable the agencies would flex their muscles to impose regulatory obligations on information reporting.

In regulating information, there are many critical issues such as which and what information should be made transparent and to whom. Each of these decisions have major implications relating to reputations, norms, fairness, privacy, efficiency and competitiveness. For example, are fares fully transparent to customers? Do drivers receive sufficient information on fares and routes prior to accepting a ride? Should driver profiles be widely accessible? Should ridesharing companies share more information with regulators such as on traffic patterns, ridership and fare information? The regulation of information would also need to consider the strategic aspects of opacity preferences.

References

Philippe Crist, Tom Voege, Diego Canales (2016) “Data driven transport policy”. International Transport Forum’s Corporate Partnership Board (CPB). https://www.itf-oecd.org/sites/default/files/docs/data-driven-transport-policy.pdf

Phuah Eng Chye (2015) Policy paradigms for the anorexic and financialised economy: Managing the transition to an information societyhttp://www.amazon.com/dp/B01AWRAKJG

Phuah Eng Chye (4 November 2017) “The sharing economy: The challenge of regulating ridesharing.” Economicsofinformationsociety.com. http://economicsofinformationsociety.com/the-sharing-economy-the-challenge-of-regulating-ridesharing/

Phuah Eng Chye (18 November 2017) “The sharing economy: Scale and regulatory arrangements.” Economicsofinformationsociety.com. http://economicsofinformationsociety.com/the-sharing-economy-scale-and-regulatory-arrangements/

 

[1] Philippe Crist, Tom Voege and Diego Canales

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