Big Data- A Big Deal for Sharing Economy?
Sharing or collaborative economy is a socio-economic ecosystem where participants share their underutilized physical properties. As the sphere of sharing economy expand, it now includes sharing of any goods, service or human resources. With the emergence of sharing economy, dynamics of the entire business landscape has undergone a tremendous change. The interplay between consumer, producer has witnessed sea change while the idea of ownership is transforming. By disrupting all sectors of existing businesses, this sharing economy is likely to yield revenue of $335 billion by 2025[1]. Across geographies, this new business model is finding growing acceptance. Big Data is trillions of quintillions of bytes generated from different digital medium like social networks, video or image upload, emails, SMS, traffic signals, online financial transactions. This gamut of data is being utilized by companies to derive insights. According to IDC big data market revenue is estimated to clock a figure of $ 54 billion by 2017. Wal-Mart and Amazon is utilizing Big Data to extract consumer insights. It ultimately helps in improvement of operational efficiency and customer service. Big Data which is a summation of 3Vs (Velocity, Volume, Variety) ensures better decision making process at lower cost. The concept of sharing economy is all about allocation of resources. Introduction of technology has become a great differentiator to figure out the demand and supply scenario of collaborative economy ecosystem. Participants can freely share data regarding their requirement. Now, big data algorithms perform the crucial task of capacity calculations to make the best possible recommendation. Big data analytics has lowered the entry barrier. Big data analytics has minimized the trust deficit as it can integrate all available information regarding a person and provide the verified identity. So, strangers can feel secured to share information regarding their needs or possessions. BMW launched a car sharing service named DriveNow. Drivers share information regarding journey time, destination. Then the nearest available car is picked up. Similarly, other leading car sharing companies like Zipcar function. They extensively use data analytics to identify demand hotspots and satisfy that demand in real time. 20 terabytes of new data is created everyday on Airbnb site. Besides, Airbnb has tons of archived data. Airbnb employs various big data analytics tools to generate much more personalized search results based on users’ preferences, rental history, social connections, and reviews.  Predictive modelling is utilized to prioritize the resources based on season and market specific demand forecasts. Airbnb launched Price Tips, a price suggestion feature which mines tons of data to assist hosts in setting rental price[2]. This rise of collaborative consumption or peer-to-peer economy has many proponents who believe that this sharing of resources is the way forward. However, there are many challenges that need to be overcome before it truly becomes a global trend. The success of the sharing or collaborative economy hinges on the penetration of smartphones and fast internet connection. The reach of these companies is limited to the tech savvy population and thus, a large number of people remain outside their ecosystem. Hence, a huge chunk of the market is not available to them. Another issue plaguing the sharing economy is the trust factor. The success of companies in the sharing economy depends on the people on their platform. But getting the right people on board and verifying their identity is not so easy. There have been incidents where guests have ransacked the house of their hosts and drivers have misbehaved with passengers. Thus, adequate background checks and processes need to be in place so to gain the trust of customers on these platforms. Companies such as Rover, DogVacay, Lyft and RelayRides in the US have multitier review and on boarding process which include background checks, references, verification of social media accounts, online training and exams etc.[3]. A recent study found that, around 16% of reviews on Yelp are not genuine[4]. Since, feedback and reviews from fellow peers is a major influence before choosing the service provider, it can have an adverse effect for participants of the shared economy. Users with bias or mala fide intent against certain companies or individuals can post negative reviews harming their reputation, and in the process affecting their business. Also, people on the platform may post positive reviews just to maintain their own reputation so that they are not portrayed as too demanding. Thus, companies need to invest in technology which analyse such trends and filter fake reviews from the genuine ones. The future of the sharing economy might move to one of the two extremes wherein your every digital move may be recorded and becomes part of your online reputation or you get control of your data and decide how and which companies are allowed to use it.  Once the participants in the sharing economy start sharing data with one another, as is predicted by many people, it can lead to the rise of a reputation based economy[5]. Track record and previous performance would be available online and any transgression from the acceptable behaviour would be flagged which could lead to expulsion from the system depending on the severity. Platforms like Quora, Airbnb, TaskRabbit, Etsy would be used to paint a picture about every individual who participates in the sharing economy and every transaction would contribute to that picture. Another possible scenario which might stunt the growth of the sharing economy is the rise of companies such as TheGoodData, which give you control over your browsing data, along with judicial interventions such as the “right to be forgotten”. If individuals get control over their own data, it will severely affect the bottom line of companies in the sharing economy because then they will have to pay users if they want to use their data for forecasting, analysing or any other purpose. [1] http://download.pwc.com/ie/pubs/2015-pwc-cis-sharing-economy.pdf [2] http://www.forbes.com/sites/ellenhuet/2015/06/05/how-airbnb-uses-big-data-and-machine-learning-to-guide-hosts-to-the-perfect-price/ [3] Paula Andruss. ”How to Launch a Business in the Sharing Economy”, http://www.entrepreneur.com/article/240687 (July 19, 2015) [4] Michael Luca and Georgios Zervas, Fake It Till You Make It, http://people.hbs.edu/mluca/FakeItTillYouMakeIt.pdf(July 18, 2015) [5] Jason Tanz, “The Sharing Economy Needs to Start Sharing Its Data Too”, http://www.wired.com/2014/05/sharing-economy-fico/ (July 19, 2015) Kanishk Khandelwal Pursuing PGDM in Marketing from IMT Ghaziabad. An avid reader, I like to keep myself updated with latest happenings around the world. I follow the internet commerce and start-up sector with keen interest as to how new ventures are disrupting the old business models through the use of technology. Arijit Samaddar Currently pursuing PGDM in Marketing from IMT Ghaziabad. I, an avid reader, always strive for exploring new opportunities. My area of interest lies in figuring out the interplay among technology, marketing and new business development.
Sharing or collaborative economy is a socio-economic ecosystem where participants share their underutilized physical properties. As the sphere of sharing economy expand, it now includes sharing of any goods, service or human resources. With the emergence of sharing economy, dynamics of the entire business landscape has undergone a tremendous change. The interplay between consumer, producer […]
Sharing or collaborative economy is a socio-economic ecosystem where participants share their underutilized physical properties. As the sphere of sharing
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["big data", "Go", "programming_languages:R", "AI", "ML", "Git", "Ray", "analytics", "Rust", "R"]
["AI", "ML", "analytics", "Ray", "R", "Go", "Rust", "Git", "big data", "programming_languages:R"]
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