DATA-DRIVEN ANALYSIS OF LAST-MILE DELIVERY EFFICIENCY AND ITS IMPACT ON SERVICE QUALITY AND ORGANIZATIONAL PRODUCTIVITY: EVIDENCE FROM FOOD DELIVERY PLATFORMS IN CHENNAI

The emergence of online food delivery apps like Swiggy, Zomato and Dunzo has revolutionized
the food service industry in India's urban cities. In Chennai - a densely populated urban
agglomeration with a population of over ten million and high tech-savviness amongst
consumers - last-mile delivery is the most critical and high cost aspect of the food delivery
supply chain. This research conducts a quantitative analysis of the efficiency of last-mile
delivery and the resulting effect on service quality and organisational productivity for the food
delivery platforms in Chennai.
A structured questionnaire was distributed to 103 delivery partners of food delivery platforms
such as Swiggy, Zomato, Zepto and Eatsure. The study used five statistical techniques:
Percentage Analysis, Descriptive Statistics, Pearson Correlation, Regression Analysis and OneWay ANOVA. The study finds that workload, technology reliability and service design account
for 67 percent of the variance in delivery performance and job satisfaction (R² = 0.670, R =
0.818). High workload is the strongest predictor of complaints (r = .461**), and reliability of
GPS is the second most positive predictor of delivery performance. The research offers insights
for food delivery platforms, logistics managers, and policymakers.
Keywords: Last-Mile Delivery, Food Delivery Platforms, Service Quality, Organizational
Productivity, Chennai, Route Optimization, Delivery Efficiency, Data-Driven Logistics, Gig
Economy.