A Multi-Criteria Decision Analysis for Locating Optimal Food Zones, Rest Points and Local Markets in Rajkot: Enhancing Urban Livability and Efficiency for the Gig Economic Sector

Rajkot, a bustling industrial city in Gujarat, is home to a diverse population engaged in various occupations. The city's economic landscape thrives, and among its dynamic sectors is the unstructured segment, housing street vendors and delivery agents who play vital roles in the daily hustle. With a strong focus on nurturing Rajkot Smart City's local economic ecosystem, this study aims to leverage the city's unused land to create spaces for thriving local businesses. Three interventions have been proposed: Rest Points, Food Courts, and Local Markets. The Gig Economic Sector, known for its temporary and part-time jobs occupied by freelancers and independent organizations, forms a key area of concern. Delivery agents from food delivery giants like Zomato and Swiggy and e-commerce platforms like Amazon, Myntra, and Flipkart traverse the city tirelessly without proper facilities to rest and recharge. Understanding their challenges was crucial, and a survey involving over 40 delivery agents provided essential insights, including daily travel distances, prime locations for maximum orders, and the availability of amenities like drinking water and sanitation facilities. Another focal point of this study involves identifying suitable sites for Food Courts and Local Markets. These spaces serve as golden opportunities for local entrepreneurs to launch or expand new ventures. The study capitalizes on the untapped potential of existing vacant lands owned by the Rajkot Municipal Corporation (RMC) instead of resorting to new acquisitions. A site suitability analysis was conducted using the Multi-Criteria Decision-Making process to ensure strategic and sophisticated land use planning. The Analytical Hierarchy Process (AHP), a robust Multi-Criteria Decision Analysis (MCDA) approach, played a pivotal role in this process. Accessibility, public amenities, and demographic profiling were weighed to pinpoint the most suitable locations. Additionally, land utilization patterns and transportation accessibility were considered to enhance precision in location identification. Locations of over 350 food joints across Rajkot were geocoded based on Google ratings to identify areas with booming eateries and epicentres for gig economic workers. Locations of other amenities, such as public toilets and parking facilities, along with population, among others, were obtained and mapped. Market values for land parcels were mapped from trusted online sources and interpolated to paint a picture of Market Values for the entire city. Land having higher market values was given a higher preference. The interventions were proposed in three phases based on the economic feasibility of the selected sites. Rest Points, Food Courts, and Local Markets are envisioned to enhance urban liveability, foster sustainable development, and empower the thriving gig economy workforce. This study has the potential for further enhancement through the implementation of simulations, predictive modelling, and replication in similar cities across the country under comparable economic conditions.