The NCLAT Wednesday set aside an order of fair trade regulator CCI imposing a Rs 87 crore fine on Hyundai Motor India for allegedly adopting unfair business ways with respect to discounts for passenger cars.
A three-member bench of the National Company Law Appellate Tribunal (NCLAT) headed by Chairman Justice S J Mukhopadhaya said the CCI order against Hyundai Motor was "not based on any specific evidence".
"... has been passed merely on the basis of opinion of DG (probe arm of CCI). The DG as well as CCI also failed to decide relevant geographic market as required... The finding is against the law laid down by the Supreme Court...," the NCLAT said.
It has also asked the Competition Commission of India (CCI) to refund the penalty amount, if any, deposited by the country's second largest car maker.
"In view of such infirmity, we have no other option but to set aside the impugned order dated June 14, 2017. It is accordingly set aside. Hyundai Motor will be entitled to refund of the amount, if any, deposited pursuant to the interim order dated July 18, 2017," it said.
CCI had in June last year imposed a fine of Rs 87 crore on Hyundai Motor for allegedly forcing dealers to procure spare parts, accessories and all other requirements, either directly from Hyundai Motor or through vendors approved by it.
In a 44-page order, the regulator said the company's anti-competitive conduct includes putting in place arrangements that resulted in resale price maintenance by way of monitoring of maximum permissible discount level.
This was done through discount control and penalty mechanisms for non-compliance of the discount scheme, it added.
"Such conduct pertains to and emanates out of sale of motor vehicles. Hence, for the purposes of determining the relevant turnover for this infringement, revenue from sale of motor vehicles alone has to be taken into account," CCI had noted.
This was challenged by Hyundai Motor India before NCLAT, which is an appellate authority over CCI.
(This article has not been edited by Zeebiz editorial team and is auto-generated from an agency feed.)