Ola, Uber fares surge in Chandigarh, but firms in denial mode
Commuters say fare has gone up 20-30% within a month.punjab Updated: Dec 08, 2017 00:00 IST
Commuters availing themselves of the app-based cab services Ola and Uber are experiencing an unusual surge in fares.
Even as both firms denied any hike in rates, several people HT talked to complained of high fares upsetting their travelling budget over the past month.
Sonia Thakur, an IT employee who works in the Mohali industrial area, said a month ago, it cost her Rs 130-Rs 150 to commute to work from her home in Sector 27, but now the fare has shot up to Rs 170-Rs 180.
“Once or twice a week, I end up paying Rs 270 per ride,” she said. “Instead of Rs 6,000, my monthly travel expense has reached Rs 9,000.”
Parmeet Kaur, who works at Chandigarh’s IT Park, too is ending up shelling ₹30 extra for each ride.
“Till last month, I used to pay Rs 140 for commuting from my house in Sector 48. Now, I am paying Rs 170. At times, the fare is Rs 250,” she said.
Ravneet Kamboj, a homoeopathy doctor in Sector 26, also questioned the promotional codes shared by these firms. “Many a times when I enter the promo code, I receive a message that it is invalid.”
Her colleague, Sonia Kawatra, complained of cab drivers cancelling the ride but the firm charging her Rs 40 extra during the next ride.
Meanwhile, an Uber driver, not wishing to be named, said the hike was due to lesser number of cabs available after the company reduced incentives to the drivers.
‘No change in operations’
Denying any unusual change in fares, an Ola spokesperson told HT: “We are operating the way we were operating earlier.”
An Uber spokesperson, meanwhile, talked of dynamic pricing while claiming the prices were within the norms mandated by the government.
“At this time, we are not seeing any unusual patterns on fares or trips emerge across Chandigarh,” said the spokesperson.
“Upfront fares are calculated using an algorithm that takes into consideration the expected time and distance of the trip, local traffic patterns, demand and supply at a given location. We’re able to use past data to estimate the likely cost of the trip and can present that price to a rider before they request for a ride.”