We first considered the relationship between OFD Performance indicators and traffic conditions because captured by Google Maps API. Kolmogorov-Smirnov tests showed that none of all these OFD indicators show a normal symmetrical distribution.
They are considering that the significant multinational variance of the Number of Comments and the minimum fee ordering, we implemented a log-transformation to their raw values for analytic purposes. Fig. 1(A) shows the statistical distributions of the logarithm of the variety of comments. Food providers with all the maximum quantity of opinions were people with heavy traffic in the morning and at noon grocery stores in aspen colorado (R-R-G), whereas those with totally free transport in the morning and the afternoon (G-R-G) received the minimum number of comments. The typical anticipated delivery intervals ranged from 38 min for food providers situated in regions with heavy traffic at the morning and at times (R-R-O) to 60 minutes for meals suppliers located in areas with highly congested traffic (i.e., R-R-R daily traffic). Fig. 1(C) reveals the typical minimum cost purchasing in Colombian currency ranged from COP 9440 (approximately 3 US$) into COP 19,400 (6.5 US$) for restaurants located in congested points of town (e.g., people having an RRO or an ORR daily traffic). Eventually, Fig. 1D demonstrates that the typical delivery price from Colombian money ranged from COP 2024 (approximately 75 US$ cents) to COP 4900 (roughly 2.6 US$).
We proceeded by analyzing food providers’ DTF. We discovered that Injuries ranged between 40 and 53 min. However, the majority of online food providers revealed a satisfactory DTF since they tended to dispatch the orders 23 min ahead of their announced travel times throughout Saturdays hurry hours. We got these numbers since the average of the travel times between the bodily location of internet food providers and also the physiological location of clients throughout rush hour. Statistical distributions of DTFs revealed significant differences based on this Google average traffic for mornings (F = 8.96; ; = 0.002), respectively noons (F = 4.88; ; = 0.002), and evenings (F = 7.71; s = 0.002), though how big these differences also proved to be minimal.
It could be argued that since OFD platforms could show them Expected delivery times according to real traffic conditions provided by Google Services, those expectations already feature congestion impacts. To test if this is true, we anticipated the Spearman nonparametric correlation matrix Between the announced delivery time (DTT), Google estimations of traveling times Time gratification (DTF) (Fig. 3).