How Big Data Helped Russia Become A Leader In Car Sharing

摘要： Big data is playing a more important role in Russia than ever before. A 2017 report by Science Direct illustrated this point. One of the ways big data is being applied is in one of the fastest growing new industries ? car sharing. It still might be a bit difficult for the average driver to imagine, but auto industry experts are nearly in agreement: Car sharing is the future.

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Big data is playing a more important role in Russia than ever before. A 2017 report by Science Direct illustrated this point. One of the ways big data is being applied is in one of the fastest growing new industries ? car sharing. It still might be a bit difficult for the average driver to imagine, but auto industry experts are nearly in agreement: Car sharing is the future. New analytics tools have made it more achievable than ever. Considering the explosive growth of both ride sharing and car sharing within the last decade ? the entire global market is estimated to be worth more than $218 billion ? as well as the leaps and bounds of technological advances associated with the market, it?s unlikely that the automobile sharing economy will suddenly collapse.

Big Data Makes Car sharing a Big Business in Russia

In fact, it isn?t just the United States that is experiencing upheaval within transportation. Countries across the world are coming to rely on ride- and car sharing as ways to get around metropolitan areas. A prime example is Russia, where car sharing use has tripled in just one year ? and where automakers are concerned for their own future. They have used big data to drive this market in massive ways. How Car sharing Evolved in Moscow Russia in general relies heavily on automobiles for transportation; at roughly 6.5 million square miles, the country is the largest in the world, and contains more than 45 million vehicles ? the majority privately owned but many managed in corporate fleets. However, because Moscow is a large, old, densely populated city, there isn?t much space for every resident to own a car. In fact, the city boasts some of the highest parking fees and fines in the world, further disincentivizing private vehicle ownership. This wouldn?t have been possible without big data. As Telefonica writes, big data and the IoT are the parents of the car sharing industry. Russia is using its big data infrastructure to make this possible. About a decade ago, Moscow began experimenting with large-scale car sharing programs. It didn?t take much to convince Muscovites to transition to the service; the exorbitant costs of owning a car ? when it spends 90 percent of its life parked, requiring even more cash in the city ? continues to convince hundreds of Russians to sell their cars and use car sharing every day. By 2015, Moscow city authorities saw so much success with car sharing that they announced plans to expand fleets to over 10,000 cars, to meet growing demand. Today, a handful of car sharing outfits are competing for the attention of hundreds of thousands of Russian car sharing customers. By far, the largest is Yandex.Drive, which more than tripled the number of available car share vehicles in the city and lowered prices to as little as 5 rubles (8 cents) per minute. Thanks to Yandex.Drive, Moscow now boasts the largest shared fleet in Europe, and the second-largest in the world. How Carmakers Are Responding The success of Moscow?s car sharing programs is driving automakers mad. As private vehicle ownership dwindles, carmakers risk becoming mere suppliers to shared mobility services, which will mean they will lose their direct relationships with customers. In other cities around the world, manufacturers are experimenting with car sharing programs of their own: GM offers Maven, a peer-to-peer service, and invests heavily in Lyft; Volkswagen manages a German rideshare called MOIA; Daimler?s Car2Go, BMW?s DriveNow and others are holding steady in various locations. However, none have penetrated Russia?s capital, which means the home grown car sharing enterprises have been left to thrive ? and automakers have been driven out. They realize that big data is a tool they can use to maintain their own edge. A report from Deloitte says big data is essential for the industry. It will be even more important as they compete against ridesharing services. What Average Americans Should Take Away Not only will it become increasingly difficult for other ride- and car shares to find a foothold in Moscow, but automakers are continuing to lose ground to these more affordable and more convenient sharing services. Because Moscow isn?t unlike major American cities ? especially in its prior reliance on private vehicles and its population density ? this is a good model for how car sharing will develop stateside. Already, there is substantial competition in the ride- and car sharing space. While many of the largest American cities have established car share services, most notably Zipcar, offered by Avis, smaller cities have seen smaller car share startups rise. Facilitated by technology like Ridecell?s car sharing platform, it is easier than ever for entrepreneurs to develop a promising venture, especially for niche markets like more rural communities or customers with specific vehicle needs. There are many regions of the U.S. where private car ownership continues to make sense, but residents of well-developed, urban areas should see Moscow as a shining example of what transportation could look like. For dollars per ride ? as opposed to thousands of dollars per month ? drivers could enjoy the privacy and convenience of cars and cut down on issues like traffic congestion, parking lot deserts and toxic emissions. For everyone but carmakers, it?s a win ? and carmakers have won at everyone else?s expense for too long, anyway.

Big Data Drives the Ridesharing Industry in Russia and Beyond

Car sharing is big business, thanks to advances in big data and machine learning. It will play an even more vital role in emerging markets, as well as established, former communist countries like Russia.

轉貼自： SmartData Collective

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