Customers response to online food delivery services during COVID-19 outbreak using binary logistic regression

Area of Science:

• Consumer Behavior
• Health Economics
• Food Service Management

Background:

• The COVID-19 pandemic significantly impacted consumer behavior and the food service industry.
• Online Food Delivery (OFD) services experienced shifts in demand and usage patterns during the outbreak.
• Understanding customer segmentation is crucial for businesses adapting to crises.

Purpose of the Study:

• To empirically identify distinct characteristics of customers who used and did not use Online Food Delivery (OFD) services in India during the COVID-19 pandemic.
• To analyze demographic, attitudinal, and behavioral factors differentiating OFD users from non-users.
• To inform crisis management strategies for OFD platforms.

Main Methods:

• Data collected from 462 customers of Online Food Delivery services in India.
• Binary logistic regression analysis employed to compare customer characteristics.
• Key variables examined include age, pre-lockdown patronage, beliefs (affective/instrumental), product involvement, and perceived threat.

Main Results:

• High perceived threat, lower product involvement, fewer perceived benefits, and less frequent online food ordering were associated with a lower likelihood of using OFDs.
• Significant differences were found between customers who did and did not order food via OFDs.
• Customer characteristics significantly influence OFD adoption during health crises.

Conclusions:

• Findings provide actionable insights for developing targeted crisis management and marketing strategies for OFD services.
• Understanding customer psychology and behavior during crises is essential for business resilience.
• The study highlights the need for OFD platforms to address perceived risks and enhance perceived benefits to encourage usage during challenging times.