The influence of online ordering systems on Cape Town Restaurants

<p dir="ltr">During the COVID-19 outbreak in 2020, there was a noticeable shift towards digital transformation and increased reliance on ICT-based business solutions. This phenomenon was observed in all economic sectors on a global scale when the lockdown measures were imposed by governments worldwide to halt the spread of COVID-19. Considering this, the reliance of many South African restaurants on third-party delivery platforms like Mr. D, Bolt Food and Uber Eats increased and became imperative to ensure the sustainability of their economic activity, especially considering the closure of numerous restaurants that lacked the necessary digital capacity. Owing to the digital capacity of these food delivery platforms, they facilitated seamless communication between restaurants and customers by providing online ordering systems (OOSs) and food delivery services (FDSs) for restaurant businesses. The collaboration of restaurants with third-party digital platforms had a profound impact on the restaurant industry during the pandemic. Although online ordering systems (OOSs) are becoming more common among restaurants to enhance operational efficiency, the long-term impacts of outsourcing online ordering systems to third-party service providers on the financial, operational and strategic performance of small and independent restaurants remain underexplored. Hence, the main objective of the study was to investigate the influence of online ordering systems and to determine the extent to which restaurants owners/managers are dependent on third-party delivery platforms for (OOS) and (FDS) in a COVID-19 free society. In addition, the study sought to ensure the continued implementation of these systems in restaurants through the exploration of risk management issues associated with the use of third-party online ordering systems. To achieve this task, quantitative research approach was adopted. A total of 133 questionnaires were distributed to restaurant owners/managers operating within the Cape Peninsula and 124 were returned. Four of the returned questionnaires were excluded due to incomplete information, which resulted in an overall response rate of 90%. Non- probability sampling techniques were employed to draw a sample of restaurants that were conveniently reachable. As the response was calculated at the above rate, data from 120 restaurants in Cape Town were analysed, specifically targeting restaurants in the suburbs rather than townships owing to security concerns and the limited presence of restaurants in township areas. </p>